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# The Evolving Paradigm in the Management of Intracranial Atherosclerotic Disease
**Authors:** Ali K. Ozturk; Ketan R. Bulsara
**Journal:** International Journal of Vascular Medicine
(2012)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2012/289852
---
## Abstract
Intracranial atherosclerotic disease (ICAD) is a major cause of ischemic stroke worldwide and represents a significant health problem. The pathogenesis and natural history of ICAD are poorly understood, and rigorous treatment paradigms do not exist as they do for extracranial atherosclerosis. Currently, the best treatment for ICAD remains aspirin therapy, but many patients who are placed on aspirin continue to experience recurrent strokes. As microsurgical and endovascular techniques continue to evolve, the role of extracranial to intracranial bypass operations and stenting are increasingly being reconsidered. We performed a PubMed review of the English literature with a particular focus on treatment options for ICAD and present evidence-based data for the role of surgery and stenting in ICAD against medical therapy alone.
---
## Body
## 1. Introduction
Intracranial atherosclerotic disease (ICAD) is the process by which atherosclerotic plaques affect large intracranial arteries. Intracranial stenosis represents the most advanced stage of ICAD and is a precursor to ischemic stroke. ICAD is the leading cause of stroke among patients of Asian ancestry [1], and Hispanics and Africans also appear to be more prone to [2] intracranial as opposed to extracranial atherosclerosis. Whites, on the other hand, are less affected, but ICAD is still thought to account for almost 10% of ischemic strokes in this subpopulation [3]. Thus, worldwide, ICAD may be the leading the cause of ischemic stroke.Atherosclerotic lesions, as elsewhere in the body, develop silently and insidiously over years prior to becoming suddenly symptomatic in the form of a stroke. Symptomatic ICAD is burdened with an unacceptably high recurrence rate, such that among patients with symptomatic ICAD and >70% stenosis, approximately 23% will have a recurrent stroke over the ensuing 12 months [4], and nearly half of these recurrent strokes tend to be disabling. The prevalence and natural history of asymptomatic ICAD are much less understood, particularly in people of European descent.Due to this lack of insight, rigorous treatment paradigms do not exist for ICAD as they do for extracranial atherosclerotic disease. The treatment strategies for ICAD include optimal medical management, surgical, and endovascular options. In this paper, we aim to define the optimal treatment strategies for this devastating disease.
## 2. Methods
MEDLINE and PubMed searches of the English literature were performed with the following keywords: intracranial atherosclerosis, extracranial-intracranial bypass, intracranial stenting, Wingspan, drug-eluding stent, stroke, and medical therapy. The relevant literature was reviewed and was supplemented as necessary from the bibliography of selected articles, with a particular focus on articles which discussed therapeutic interventions for ICAD.
## 3. Results
### 3.1. Optimal Medical Management
The results of the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) study not only demonstrated the role for medical therapy in ICAD, but also provided important information regarding the natural history. Patients presenting within 90 days of a transient ischemic attack (TIA) or nonsevere stroke attributable to angiographically proven high-grade (50–99%) stenosis of a major intracranial artery were given either aspirin or warfarin and were followed for the primary endpoints of ischemic stroke, hemorrhagic stroke, and vascular death. Based on this data, warfarin did no better than aspirin in stroke prevention but was associated with significantly higher rates of adverse events, such that 8.3% of patients randomized to warfarin had one episode of major hemorrhage compared to 3.2% of patients randomized to aspirin therapy [4].Based on the WASID data, aspirin is the antithrombotic drug of choice in ICAD. More recent evidence suggests that dual antiplatelet therapy may be more effective than aspirin alone in preventing microembolic signals detected with transcranial Doppler ultrasound with similar adverse events in both arms [5]. Further evidence is needed to determine if dual antiplatelet therapy is indeed superior to aspirin alone in preventing clinical strokes in patients with symptomatic ICAD.Although the WASID trial was not designed to study the importance of risk factor control, several important conclusions are reached from its substudies. Thus, while lowering blood pressure during followup appears to reduce recurrence risk [6], the effects of lipid management seem more controversial [7]. Further studies will be needed to clarify the role of risk factor management in these patients.
### 3.2. EC-IC Bypass
Flow augmentation in the setting of anterior circulation ischemia can be achieved surgically via external carotid to internal carotid (EC-IC) bypass procedures. Typically, the superficial temporal artery (STA) is anastomosed to the middle cerebral artery (MCA) provided sufficient flow is obtained via the STA (Figure1). If the STA demonstrates insufficient flow, the cervical carotid can be used via an interposition graft, such as the saphenous vein.Figure 1
Schematic of STA-MCA bypass.The EC-IC study published in 1985 [8] quickly led to a sharp decline in the use of this intervention for anterior circulation ICAD, since it failed to demonstrate any reduction in strokes compared to best medical management. Briefly, 1377 patients were randomized to surgery plus medical management versus medical management alone. Despite bypass patency rates of 96% and a relatively low complication rate of 3%, long-term followup at 55 months revealed no benefit with regards to stroke prevention [8].Upon closer examination, several shortcomings become apparent in this study. First and foremost, patients who had ICAD who were not amenable to carotid endarterectomy and who demonstrated symptoms were included in the study, with disregard toward hemodynamic compromise. Thus, patients who may have had disease due to embolic phenomenon and small vessel disease who would not have benefited from EC-IC were indiscriminately included in the study. Patients with stage 2 hemodynamic insufficiency (i.e., those with a higher oxygen extraction fraction (OEF)), have been shown to have a 26% versus 5% risk of stroke at 2 years compared to those with normal OEF as detected by PET measurement [9, 10]. Second, many patients who underwent surgery did so outside of the trial, potentially implicating that those who needed the surgery more urgently were omitted, thus diluting the beneficial effects of the procedure.In lieu of these criticisms, the Carotid Occlusion Surgery Study (COSS) [11] and the Japanese EC-IC Bypass Trial (JET) were underway in the United Stated and Japan, respectively, to assess the potential for a newfound usefulness of this operation if the patients are selected based on a more sophisticated analysis of hemodynamic compromise. At the time of writing this paper, the results of these trials have not been published; however, COSS was terminated prematurely due to lack of benefit in patients undergoing EC-IC bypass.The excimer laser-assisted nonocclusive anastomosis (ELANA) is a novel bypass technique which critically omits the use of temporary occlusion using a suction laser catheter which produces an arteriotomy only after the anastomosis is created [12]. While the main use of this technique has been in surgery for complex intracranial aneurysms, recent work is starting to allude to a potential role for it in ICAD. In a recent publication, van Doormaal et al. used ELANA in performing high-flow EC-IC bypasses in 24 patients with TIA or minor strokes in the setting of carotid artery occlusion. All patients had a successful bypass procedure. Two patients suffered a fatal intracerebral hemorrhage within 30 days of the procedure. During an average followup of 4 years, 18 of the surviving 22 patients had patent bypasses and were free of recurrent symptoms. In the remaining 4, the bypass had occluded causing ischemic symptoms [13]. Larger, more specific studies are needed to investigate the potential use of this novel technique in the treatment of ICAD.
### 3.3. Endovascular Therapy
Endovascular devices and expertise using them continue to improve at a rapid pace, and they represent a promising new approach to treating symptomatic ICAD. Initially, endovascular therapy was limited to percutaneous transluminal angioplasty (PTA), but this fell out of favor due to periprocedural morbidity and mortality along with significant and highly problematic rates of restenosis. The chief cause of morbidity using PTA alone comes from vessel dissection, ranging from 14–50% reported in the literature [14, 15]. In addition, over one quarter (27%) of treated vessels will demonstrate restenosis at 5 months following treatment [14, 16]. Ultimately, angioplasty proved to be only a temporary fix.The advent of stents, which have the capacity to not only increase tissue perfusion but also remodel the diseased vasculature, is an area of increasing promise. Procedural success rates, periprocedural morbidity and mortality, and restenosis rates are the chief parameters that are used to compare different stent types in the use of ICAD and are the subject of much research and controversy.Drug-eluting stents (DESs) were shown to greatly decrease the restenosis rates in coronary artery disease [17], and there have been attempts to duplicate this success in the treatment of ICAD. Initial work using DES in intracranial disease by Abou-Chebl et al. [18] treating a small number of patients demonstrated a similarly promising decrease in short-term restenosis rates compared to bare metal stents. However, due to the known risk of delayed stent thrombosis, combined with the lack of long-term data, DES in the treatment of ICAD has largely fallen out of practice.The balloon expandable Pharos stent has showed initial promise in two small studies in the treatment of ICAD. In a retrospective study, Freitas et al. treated 32 patients with >50% stenosis using the Pharos stent with a 96% success rate. The 30-day clinical followup revealed 2 patients who had suffered ipsilateral stroke and 3 patients who had died, though 2 of the deaths were likely due to medication noncompliance. Ten-month clinical followup, however, revealed no additional strokes or deaths, and only four clinically silent restenosis [19]. A second study from Germany enrolled 21 patients with >70% stenosis, 7 of which were treated in the setting of acute stroke. They achieved a 90% clinical success rate. Of the electively treated patients (14), 3 went on to suffer a stroke or die during an average clinical followup of 7 months. Interestingly, of the 7 patients treated acutely, 2 died within the first 30 days, and another 2 went on to develop ipsilateral strokes over the following 10 months [20], reiterating the risk of intracranial stenting in the setting of acute stroke.The flexible Wingspan stent was approved for use in intracranial vessels with >50% stenosis in 2005. The flexibility afforded by this stent increases its usefulness in the tortuous intracranial vasculature (Figure2), and technical success rates using the Wingspan stent have been reported to be as high as 97-98% [21]. Guo et al. reported a 98% technical success rate specifically for MCA stenosis [22], a vessel traditionally challenging to treat endovascularly. A prospective Wingspan study, however, demonstrated an approximately 30% rate of in-stent stenosis [23], higher than what had previously been reported in the neurosurgical literature. While most of these were clinically silent, 5% led to significant morbidity and mortality [23]. In a recent review, Ding and Liu [24] found the Wingspan stent to have an overall higher technical success rate in the literature and possibly a lower complication rate, although the authors admit that shorter clinical followup for the Wingspan studies made the comparison uneven.Figure 2
Stent and balloon catheter commonly used in ICAD.Due to the initially promising and conflicting results of the Wingspan stent, the SAMMPRIS trial was designed to compare the Wingspan stent and medical therapy to aggressive medical therapy alone in symptomatic ICAD patients randomizing patients in 50 centers across the US. At the time of writing this paper, the results of that trial have not been published; however, this trial was terminated prematurely because patients in the angioplasty/stent group fared worse than those in the medical therapy group. What has been released about this trial thus far implies that optimizing medical management remains the first treatment of choice for symptomatic intracranial atherosclerotic disease. The SAMMPRIS trial did not address those patients who had failed optimal medical therapy. Endovascular treatment in these patients may still play an important role in optimizing clinical outcome.
## 3.1. Optimal Medical Management
The results of the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) study not only demonstrated the role for medical therapy in ICAD, but also provided important information regarding the natural history. Patients presenting within 90 days of a transient ischemic attack (TIA) or nonsevere stroke attributable to angiographically proven high-grade (50–99%) stenosis of a major intracranial artery were given either aspirin or warfarin and were followed for the primary endpoints of ischemic stroke, hemorrhagic stroke, and vascular death. Based on this data, warfarin did no better than aspirin in stroke prevention but was associated with significantly higher rates of adverse events, such that 8.3% of patients randomized to warfarin had one episode of major hemorrhage compared to 3.2% of patients randomized to aspirin therapy [4].Based on the WASID data, aspirin is the antithrombotic drug of choice in ICAD. More recent evidence suggests that dual antiplatelet therapy may be more effective than aspirin alone in preventing microembolic signals detected with transcranial Doppler ultrasound with similar adverse events in both arms [5]. Further evidence is needed to determine if dual antiplatelet therapy is indeed superior to aspirin alone in preventing clinical strokes in patients with symptomatic ICAD.Although the WASID trial was not designed to study the importance of risk factor control, several important conclusions are reached from its substudies. Thus, while lowering blood pressure during followup appears to reduce recurrence risk [6], the effects of lipid management seem more controversial [7]. Further studies will be needed to clarify the role of risk factor management in these patients.
## 3.2. EC-IC Bypass
Flow augmentation in the setting of anterior circulation ischemia can be achieved surgically via external carotid to internal carotid (EC-IC) bypass procedures. Typically, the superficial temporal artery (STA) is anastomosed to the middle cerebral artery (MCA) provided sufficient flow is obtained via the STA (Figure1). If the STA demonstrates insufficient flow, the cervical carotid can be used via an interposition graft, such as the saphenous vein.Figure 1
Schematic of STA-MCA bypass.The EC-IC study published in 1985 [8] quickly led to a sharp decline in the use of this intervention for anterior circulation ICAD, since it failed to demonstrate any reduction in strokes compared to best medical management. Briefly, 1377 patients were randomized to surgery plus medical management versus medical management alone. Despite bypass patency rates of 96% and a relatively low complication rate of 3%, long-term followup at 55 months revealed no benefit with regards to stroke prevention [8].Upon closer examination, several shortcomings become apparent in this study. First and foremost, patients who had ICAD who were not amenable to carotid endarterectomy and who demonstrated symptoms were included in the study, with disregard toward hemodynamic compromise. Thus, patients who may have had disease due to embolic phenomenon and small vessel disease who would not have benefited from EC-IC were indiscriminately included in the study. Patients with stage 2 hemodynamic insufficiency (i.e., those with a higher oxygen extraction fraction (OEF)), have been shown to have a 26% versus 5% risk of stroke at 2 years compared to those with normal OEF as detected by PET measurement [9, 10]. Second, many patients who underwent surgery did so outside of the trial, potentially implicating that those who needed the surgery more urgently were omitted, thus diluting the beneficial effects of the procedure.In lieu of these criticisms, the Carotid Occlusion Surgery Study (COSS) [11] and the Japanese EC-IC Bypass Trial (JET) were underway in the United Stated and Japan, respectively, to assess the potential for a newfound usefulness of this operation if the patients are selected based on a more sophisticated analysis of hemodynamic compromise. At the time of writing this paper, the results of these trials have not been published; however, COSS was terminated prematurely due to lack of benefit in patients undergoing EC-IC bypass.The excimer laser-assisted nonocclusive anastomosis (ELANA) is a novel bypass technique which critically omits the use of temporary occlusion using a suction laser catheter which produces an arteriotomy only after the anastomosis is created [12]. While the main use of this technique has been in surgery for complex intracranial aneurysms, recent work is starting to allude to a potential role for it in ICAD. In a recent publication, van Doormaal et al. used ELANA in performing high-flow EC-IC bypasses in 24 patients with TIA or minor strokes in the setting of carotid artery occlusion. All patients had a successful bypass procedure. Two patients suffered a fatal intracerebral hemorrhage within 30 days of the procedure. During an average followup of 4 years, 18 of the surviving 22 patients had patent bypasses and were free of recurrent symptoms. In the remaining 4, the bypass had occluded causing ischemic symptoms [13]. Larger, more specific studies are needed to investigate the potential use of this novel technique in the treatment of ICAD.
## 3.3. Endovascular Therapy
Endovascular devices and expertise using them continue to improve at a rapid pace, and they represent a promising new approach to treating symptomatic ICAD. Initially, endovascular therapy was limited to percutaneous transluminal angioplasty (PTA), but this fell out of favor due to periprocedural morbidity and mortality along with significant and highly problematic rates of restenosis. The chief cause of morbidity using PTA alone comes from vessel dissection, ranging from 14–50% reported in the literature [14, 15]. In addition, over one quarter (27%) of treated vessels will demonstrate restenosis at 5 months following treatment [14, 16]. Ultimately, angioplasty proved to be only a temporary fix.The advent of stents, which have the capacity to not only increase tissue perfusion but also remodel the diseased vasculature, is an area of increasing promise. Procedural success rates, periprocedural morbidity and mortality, and restenosis rates are the chief parameters that are used to compare different stent types in the use of ICAD and are the subject of much research and controversy.Drug-eluting stents (DESs) were shown to greatly decrease the restenosis rates in coronary artery disease [17], and there have been attempts to duplicate this success in the treatment of ICAD. Initial work using DES in intracranial disease by Abou-Chebl et al. [18] treating a small number of patients demonstrated a similarly promising decrease in short-term restenosis rates compared to bare metal stents. However, due to the known risk of delayed stent thrombosis, combined with the lack of long-term data, DES in the treatment of ICAD has largely fallen out of practice.The balloon expandable Pharos stent has showed initial promise in two small studies in the treatment of ICAD. In a retrospective study, Freitas et al. treated 32 patients with >50% stenosis using the Pharos stent with a 96% success rate. The 30-day clinical followup revealed 2 patients who had suffered ipsilateral stroke and 3 patients who had died, though 2 of the deaths were likely due to medication noncompliance. Ten-month clinical followup, however, revealed no additional strokes or deaths, and only four clinically silent restenosis [19]. A second study from Germany enrolled 21 patients with >70% stenosis, 7 of which were treated in the setting of acute stroke. They achieved a 90% clinical success rate. Of the electively treated patients (14), 3 went on to suffer a stroke or die during an average clinical followup of 7 months. Interestingly, of the 7 patients treated acutely, 2 died within the first 30 days, and another 2 went on to develop ipsilateral strokes over the following 10 months [20], reiterating the risk of intracranial stenting in the setting of acute stroke.The flexible Wingspan stent was approved for use in intracranial vessels with >50% stenosis in 2005. The flexibility afforded by this stent increases its usefulness in the tortuous intracranial vasculature (Figure2), and technical success rates using the Wingspan stent have been reported to be as high as 97-98% [21]. Guo et al. reported a 98% technical success rate specifically for MCA stenosis [22], a vessel traditionally challenging to treat endovascularly. A prospective Wingspan study, however, demonstrated an approximately 30% rate of in-stent stenosis [23], higher than what had previously been reported in the neurosurgical literature. While most of these were clinically silent, 5% led to significant morbidity and mortality [23]. In a recent review, Ding and Liu [24] found the Wingspan stent to have an overall higher technical success rate in the literature and possibly a lower complication rate, although the authors admit that shorter clinical followup for the Wingspan studies made the comparison uneven.Figure 2
Stent and balloon catheter commonly used in ICAD.Due to the initially promising and conflicting results of the Wingspan stent, the SAMMPRIS trial was designed to compare the Wingspan stent and medical therapy to aggressive medical therapy alone in symptomatic ICAD patients randomizing patients in 50 centers across the US. At the time of writing this paper, the results of that trial have not been published; however, this trial was terminated prematurely because patients in the angioplasty/stent group fared worse than those in the medical therapy group. What has been released about this trial thus far implies that optimizing medical management remains the first treatment of choice for symptomatic intracranial atherosclerotic disease. The SAMMPRIS trial did not address those patients who had failed optimal medical therapy. Endovascular treatment in these patients may still play an important role in optimizing clinical outcome.
## 4. Discussion
ICAD remains a common cause of stroke worldwide, and our understanding regarding the optimal treatment of it remains dismal. The risk of ICAD-associated stroke increases with high-grade (>70%) stenoses and in those patients who demonstrate an increased OEF [25]. The conclusion that these patients need to be treated is likely a sound one, but the optimal therapy for this group desperately needs clarification.Aspirin, as the antithrombotic drug of choice, reduces the rate of recurrent ipsilateral stroke but does not eliminate it, and approximately 1 in 7 such patients will go on to experience recurrent ischemic events [4]. Patients with high-grade stenosis who also have an elevated OEF who experience recurrent strokes despite aspirin therapy are in need of revascularization procedures. The premature termination of the COSS study implies that microsurgical EC-IC bypass may not be the revascularization treatment of choice for these patients.Surgery, in the form of EC-IC bypass procedures is yet to be proven to lower recurrent strokes compared to medical management only. Previous trials may have been flawed by indiscriminate inclusion of subjects without the use of hemodynamic testing to determine who would more likely benefit from the procedure. The COSS and JET trials were initiated to investigate if indeed patients with an elevated OEF were more likely to benefit from surgery. While the final results of the JET trial are pending, the premature termination of the COSS trial implies the limited role of EC-IC bypass in this patient population.Previous stents were largely designed for coronary disease, and the tortuous anatomy of the intracranial vasculature limited their utility. The advent of the Wingspan stent with its flexibility is quite promising, but the initial results of the SAMMPRIS trial comparing the use of the Wingspan stent with medical management imply that medical management remains the treatment of choice for patients with symptomatic ICAD. The role of angioplasty alone or angioplasty/stenting in the patient population that has failed optimal medical management remains to be determined. As of now, these patients have no other reliable alternative other than endovascular therapy.
## 5. Conclusion
Symptomatic ICAD is a significant health burden, and often times, leads to recurrent, disabling strokes. The natural history of ICAD is poorly understood, as are optimal treatment strategies. The results of long-term outcome studies assessing the utility of both microsurgical and endovascular treatment options continue to support the fact that optimizing medical management remains the initial treatment of choice. As refinements in both microsurgical and endovascular techniques/technologies continue, patients suffering from this devastating disease may have other alternatives.
---
*Source: 289852-2011-12-19.xml* | 289852-2011-12-19_289852-2011-12-19.md | 26,218 | The Evolving Paradigm in the Management of Intracranial Atherosclerotic Disease | Ali K. Ozturk; Ketan R. Bulsara | International Journal of Vascular Medicine
(2012) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2012/289852 | 289852-2011-12-19.xml | ---
## Abstract
Intracranial atherosclerotic disease (ICAD) is a major cause of ischemic stroke worldwide and represents a significant health problem. The pathogenesis and natural history of ICAD are poorly understood, and rigorous treatment paradigms do not exist as they do for extracranial atherosclerosis. Currently, the best treatment for ICAD remains aspirin therapy, but many patients who are placed on aspirin continue to experience recurrent strokes. As microsurgical and endovascular techniques continue to evolve, the role of extracranial to intracranial bypass operations and stenting are increasingly being reconsidered. We performed a PubMed review of the English literature with a particular focus on treatment options for ICAD and present evidence-based data for the role of surgery and stenting in ICAD against medical therapy alone.
---
## Body
## 1. Introduction
Intracranial atherosclerotic disease (ICAD) is the process by which atherosclerotic plaques affect large intracranial arteries. Intracranial stenosis represents the most advanced stage of ICAD and is a precursor to ischemic stroke. ICAD is the leading cause of stroke among patients of Asian ancestry [1], and Hispanics and Africans also appear to be more prone to [2] intracranial as opposed to extracranial atherosclerosis. Whites, on the other hand, are less affected, but ICAD is still thought to account for almost 10% of ischemic strokes in this subpopulation [3]. Thus, worldwide, ICAD may be the leading the cause of ischemic stroke.Atherosclerotic lesions, as elsewhere in the body, develop silently and insidiously over years prior to becoming suddenly symptomatic in the form of a stroke. Symptomatic ICAD is burdened with an unacceptably high recurrence rate, such that among patients with symptomatic ICAD and >70% stenosis, approximately 23% will have a recurrent stroke over the ensuing 12 months [4], and nearly half of these recurrent strokes tend to be disabling. The prevalence and natural history of asymptomatic ICAD are much less understood, particularly in people of European descent.Due to this lack of insight, rigorous treatment paradigms do not exist for ICAD as they do for extracranial atherosclerotic disease. The treatment strategies for ICAD include optimal medical management, surgical, and endovascular options. In this paper, we aim to define the optimal treatment strategies for this devastating disease.
## 2. Methods
MEDLINE and PubMed searches of the English literature were performed with the following keywords: intracranial atherosclerosis, extracranial-intracranial bypass, intracranial stenting, Wingspan, drug-eluding stent, stroke, and medical therapy. The relevant literature was reviewed and was supplemented as necessary from the bibliography of selected articles, with a particular focus on articles which discussed therapeutic interventions for ICAD.
## 3. Results
### 3.1. Optimal Medical Management
The results of the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) study not only demonstrated the role for medical therapy in ICAD, but also provided important information regarding the natural history. Patients presenting within 90 days of a transient ischemic attack (TIA) or nonsevere stroke attributable to angiographically proven high-grade (50–99%) stenosis of a major intracranial artery were given either aspirin or warfarin and were followed for the primary endpoints of ischemic stroke, hemorrhagic stroke, and vascular death. Based on this data, warfarin did no better than aspirin in stroke prevention but was associated with significantly higher rates of adverse events, such that 8.3% of patients randomized to warfarin had one episode of major hemorrhage compared to 3.2% of patients randomized to aspirin therapy [4].Based on the WASID data, aspirin is the antithrombotic drug of choice in ICAD. More recent evidence suggests that dual antiplatelet therapy may be more effective than aspirin alone in preventing microembolic signals detected with transcranial Doppler ultrasound with similar adverse events in both arms [5]. Further evidence is needed to determine if dual antiplatelet therapy is indeed superior to aspirin alone in preventing clinical strokes in patients with symptomatic ICAD.Although the WASID trial was not designed to study the importance of risk factor control, several important conclusions are reached from its substudies. Thus, while lowering blood pressure during followup appears to reduce recurrence risk [6], the effects of lipid management seem more controversial [7]. Further studies will be needed to clarify the role of risk factor management in these patients.
### 3.2. EC-IC Bypass
Flow augmentation in the setting of anterior circulation ischemia can be achieved surgically via external carotid to internal carotid (EC-IC) bypass procedures. Typically, the superficial temporal artery (STA) is anastomosed to the middle cerebral artery (MCA) provided sufficient flow is obtained via the STA (Figure1). If the STA demonstrates insufficient flow, the cervical carotid can be used via an interposition graft, such as the saphenous vein.Figure 1
Schematic of STA-MCA bypass.The EC-IC study published in 1985 [8] quickly led to a sharp decline in the use of this intervention for anterior circulation ICAD, since it failed to demonstrate any reduction in strokes compared to best medical management. Briefly, 1377 patients were randomized to surgery plus medical management versus medical management alone. Despite bypass patency rates of 96% and a relatively low complication rate of 3%, long-term followup at 55 months revealed no benefit with regards to stroke prevention [8].Upon closer examination, several shortcomings become apparent in this study. First and foremost, patients who had ICAD who were not amenable to carotid endarterectomy and who demonstrated symptoms were included in the study, with disregard toward hemodynamic compromise. Thus, patients who may have had disease due to embolic phenomenon and small vessel disease who would not have benefited from EC-IC were indiscriminately included in the study. Patients with stage 2 hemodynamic insufficiency (i.e., those with a higher oxygen extraction fraction (OEF)), have been shown to have a 26% versus 5% risk of stroke at 2 years compared to those with normal OEF as detected by PET measurement [9, 10]. Second, many patients who underwent surgery did so outside of the trial, potentially implicating that those who needed the surgery more urgently were omitted, thus diluting the beneficial effects of the procedure.In lieu of these criticisms, the Carotid Occlusion Surgery Study (COSS) [11] and the Japanese EC-IC Bypass Trial (JET) were underway in the United Stated and Japan, respectively, to assess the potential for a newfound usefulness of this operation if the patients are selected based on a more sophisticated analysis of hemodynamic compromise. At the time of writing this paper, the results of these trials have not been published; however, COSS was terminated prematurely due to lack of benefit in patients undergoing EC-IC bypass.The excimer laser-assisted nonocclusive anastomosis (ELANA) is a novel bypass technique which critically omits the use of temporary occlusion using a suction laser catheter which produces an arteriotomy only after the anastomosis is created [12]. While the main use of this technique has been in surgery for complex intracranial aneurysms, recent work is starting to allude to a potential role for it in ICAD. In a recent publication, van Doormaal et al. used ELANA in performing high-flow EC-IC bypasses in 24 patients with TIA or minor strokes in the setting of carotid artery occlusion. All patients had a successful bypass procedure. Two patients suffered a fatal intracerebral hemorrhage within 30 days of the procedure. During an average followup of 4 years, 18 of the surviving 22 patients had patent bypasses and were free of recurrent symptoms. In the remaining 4, the bypass had occluded causing ischemic symptoms [13]. Larger, more specific studies are needed to investigate the potential use of this novel technique in the treatment of ICAD.
### 3.3. Endovascular Therapy
Endovascular devices and expertise using them continue to improve at a rapid pace, and they represent a promising new approach to treating symptomatic ICAD. Initially, endovascular therapy was limited to percutaneous transluminal angioplasty (PTA), but this fell out of favor due to periprocedural morbidity and mortality along with significant and highly problematic rates of restenosis. The chief cause of morbidity using PTA alone comes from vessel dissection, ranging from 14–50% reported in the literature [14, 15]. In addition, over one quarter (27%) of treated vessels will demonstrate restenosis at 5 months following treatment [14, 16]. Ultimately, angioplasty proved to be only a temporary fix.The advent of stents, which have the capacity to not only increase tissue perfusion but also remodel the diseased vasculature, is an area of increasing promise. Procedural success rates, periprocedural morbidity and mortality, and restenosis rates are the chief parameters that are used to compare different stent types in the use of ICAD and are the subject of much research and controversy.Drug-eluting stents (DESs) were shown to greatly decrease the restenosis rates in coronary artery disease [17], and there have been attempts to duplicate this success in the treatment of ICAD. Initial work using DES in intracranial disease by Abou-Chebl et al. [18] treating a small number of patients demonstrated a similarly promising decrease in short-term restenosis rates compared to bare metal stents. However, due to the known risk of delayed stent thrombosis, combined with the lack of long-term data, DES in the treatment of ICAD has largely fallen out of practice.The balloon expandable Pharos stent has showed initial promise in two small studies in the treatment of ICAD. In a retrospective study, Freitas et al. treated 32 patients with >50% stenosis using the Pharos stent with a 96% success rate. The 30-day clinical followup revealed 2 patients who had suffered ipsilateral stroke and 3 patients who had died, though 2 of the deaths were likely due to medication noncompliance. Ten-month clinical followup, however, revealed no additional strokes or deaths, and only four clinically silent restenosis [19]. A second study from Germany enrolled 21 patients with >70% stenosis, 7 of which were treated in the setting of acute stroke. They achieved a 90% clinical success rate. Of the electively treated patients (14), 3 went on to suffer a stroke or die during an average clinical followup of 7 months. Interestingly, of the 7 patients treated acutely, 2 died within the first 30 days, and another 2 went on to develop ipsilateral strokes over the following 10 months [20], reiterating the risk of intracranial stenting in the setting of acute stroke.The flexible Wingspan stent was approved for use in intracranial vessels with >50% stenosis in 2005. The flexibility afforded by this stent increases its usefulness in the tortuous intracranial vasculature (Figure2), and technical success rates using the Wingspan stent have been reported to be as high as 97-98% [21]. Guo et al. reported a 98% technical success rate specifically for MCA stenosis [22], a vessel traditionally challenging to treat endovascularly. A prospective Wingspan study, however, demonstrated an approximately 30% rate of in-stent stenosis [23], higher than what had previously been reported in the neurosurgical literature. While most of these were clinically silent, 5% led to significant morbidity and mortality [23]. In a recent review, Ding and Liu [24] found the Wingspan stent to have an overall higher technical success rate in the literature and possibly a lower complication rate, although the authors admit that shorter clinical followup for the Wingspan studies made the comparison uneven.Figure 2
Stent and balloon catheter commonly used in ICAD.Due to the initially promising and conflicting results of the Wingspan stent, the SAMMPRIS trial was designed to compare the Wingspan stent and medical therapy to aggressive medical therapy alone in symptomatic ICAD patients randomizing patients in 50 centers across the US. At the time of writing this paper, the results of that trial have not been published; however, this trial was terminated prematurely because patients in the angioplasty/stent group fared worse than those in the medical therapy group. What has been released about this trial thus far implies that optimizing medical management remains the first treatment of choice for symptomatic intracranial atherosclerotic disease. The SAMMPRIS trial did not address those patients who had failed optimal medical therapy. Endovascular treatment in these patients may still play an important role in optimizing clinical outcome.
## 3.1. Optimal Medical Management
The results of the Warfarin-Aspirin Symptomatic Intracranial Disease (WASID) study not only demonstrated the role for medical therapy in ICAD, but also provided important information regarding the natural history. Patients presenting within 90 days of a transient ischemic attack (TIA) or nonsevere stroke attributable to angiographically proven high-grade (50–99%) stenosis of a major intracranial artery were given either aspirin or warfarin and were followed for the primary endpoints of ischemic stroke, hemorrhagic stroke, and vascular death. Based on this data, warfarin did no better than aspirin in stroke prevention but was associated with significantly higher rates of adverse events, such that 8.3% of patients randomized to warfarin had one episode of major hemorrhage compared to 3.2% of patients randomized to aspirin therapy [4].Based on the WASID data, aspirin is the antithrombotic drug of choice in ICAD. More recent evidence suggests that dual antiplatelet therapy may be more effective than aspirin alone in preventing microembolic signals detected with transcranial Doppler ultrasound with similar adverse events in both arms [5]. Further evidence is needed to determine if dual antiplatelet therapy is indeed superior to aspirin alone in preventing clinical strokes in patients with symptomatic ICAD.Although the WASID trial was not designed to study the importance of risk factor control, several important conclusions are reached from its substudies. Thus, while lowering blood pressure during followup appears to reduce recurrence risk [6], the effects of lipid management seem more controversial [7]. Further studies will be needed to clarify the role of risk factor management in these patients.
## 3.2. EC-IC Bypass
Flow augmentation in the setting of anterior circulation ischemia can be achieved surgically via external carotid to internal carotid (EC-IC) bypass procedures. Typically, the superficial temporal artery (STA) is anastomosed to the middle cerebral artery (MCA) provided sufficient flow is obtained via the STA (Figure1). If the STA demonstrates insufficient flow, the cervical carotid can be used via an interposition graft, such as the saphenous vein.Figure 1
Schematic of STA-MCA bypass.The EC-IC study published in 1985 [8] quickly led to a sharp decline in the use of this intervention for anterior circulation ICAD, since it failed to demonstrate any reduction in strokes compared to best medical management. Briefly, 1377 patients were randomized to surgery plus medical management versus medical management alone. Despite bypass patency rates of 96% and a relatively low complication rate of 3%, long-term followup at 55 months revealed no benefit with regards to stroke prevention [8].Upon closer examination, several shortcomings become apparent in this study. First and foremost, patients who had ICAD who were not amenable to carotid endarterectomy and who demonstrated symptoms were included in the study, with disregard toward hemodynamic compromise. Thus, patients who may have had disease due to embolic phenomenon and small vessel disease who would not have benefited from EC-IC were indiscriminately included in the study. Patients with stage 2 hemodynamic insufficiency (i.e., those with a higher oxygen extraction fraction (OEF)), have been shown to have a 26% versus 5% risk of stroke at 2 years compared to those with normal OEF as detected by PET measurement [9, 10]. Second, many patients who underwent surgery did so outside of the trial, potentially implicating that those who needed the surgery more urgently were omitted, thus diluting the beneficial effects of the procedure.In lieu of these criticisms, the Carotid Occlusion Surgery Study (COSS) [11] and the Japanese EC-IC Bypass Trial (JET) were underway in the United Stated and Japan, respectively, to assess the potential for a newfound usefulness of this operation if the patients are selected based on a more sophisticated analysis of hemodynamic compromise. At the time of writing this paper, the results of these trials have not been published; however, COSS was terminated prematurely due to lack of benefit in patients undergoing EC-IC bypass.The excimer laser-assisted nonocclusive anastomosis (ELANA) is a novel bypass technique which critically omits the use of temporary occlusion using a suction laser catheter which produces an arteriotomy only after the anastomosis is created [12]. While the main use of this technique has been in surgery for complex intracranial aneurysms, recent work is starting to allude to a potential role for it in ICAD. In a recent publication, van Doormaal et al. used ELANA in performing high-flow EC-IC bypasses in 24 patients with TIA or minor strokes in the setting of carotid artery occlusion. All patients had a successful bypass procedure. Two patients suffered a fatal intracerebral hemorrhage within 30 days of the procedure. During an average followup of 4 years, 18 of the surviving 22 patients had patent bypasses and were free of recurrent symptoms. In the remaining 4, the bypass had occluded causing ischemic symptoms [13]. Larger, more specific studies are needed to investigate the potential use of this novel technique in the treatment of ICAD.
## 3.3. Endovascular Therapy
Endovascular devices and expertise using them continue to improve at a rapid pace, and they represent a promising new approach to treating symptomatic ICAD. Initially, endovascular therapy was limited to percutaneous transluminal angioplasty (PTA), but this fell out of favor due to periprocedural morbidity and mortality along with significant and highly problematic rates of restenosis. The chief cause of morbidity using PTA alone comes from vessel dissection, ranging from 14–50% reported in the literature [14, 15]. In addition, over one quarter (27%) of treated vessels will demonstrate restenosis at 5 months following treatment [14, 16]. Ultimately, angioplasty proved to be only a temporary fix.The advent of stents, which have the capacity to not only increase tissue perfusion but also remodel the diseased vasculature, is an area of increasing promise. Procedural success rates, periprocedural morbidity and mortality, and restenosis rates are the chief parameters that are used to compare different stent types in the use of ICAD and are the subject of much research and controversy.Drug-eluting stents (DESs) were shown to greatly decrease the restenosis rates in coronary artery disease [17], and there have been attempts to duplicate this success in the treatment of ICAD. Initial work using DES in intracranial disease by Abou-Chebl et al. [18] treating a small number of patients demonstrated a similarly promising decrease in short-term restenosis rates compared to bare metal stents. However, due to the known risk of delayed stent thrombosis, combined with the lack of long-term data, DES in the treatment of ICAD has largely fallen out of practice.The balloon expandable Pharos stent has showed initial promise in two small studies in the treatment of ICAD. In a retrospective study, Freitas et al. treated 32 patients with >50% stenosis using the Pharos stent with a 96% success rate. The 30-day clinical followup revealed 2 patients who had suffered ipsilateral stroke and 3 patients who had died, though 2 of the deaths were likely due to medication noncompliance. Ten-month clinical followup, however, revealed no additional strokes or deaths, and only four clinically silent restenosis [19]. A second study from Germany enrolled 21 patients with >70% stenosis, 7 of which were treated in the setting of acute stroke. They achieved a 90% clinical success rate. Of the electively treated patients (14), 3 went on to suffer a stroke or die during an average clinical followup of 7 months. Interestingly, of the 7 patients treated acutely, 2 died within the first 30 days, and another 2 went on to develop ipsilateral strokes over the following 10 months [20], reiterating the risk of intracranial stenting in the setting of acute stroke.The flexible Wingspan stent was approved for use in intracranial vessels with >50% stenosis in 2005. The flexibility afforded by this stent increases its usefulness in the tortuous intracranial vasculature (Figure2), and technical success rates using the Wingspan stent have been reported to be as high as 97-98% [21]. Guo et al. reported a 98% technical success rate specifically for MCA stenosis [22], a vessel traditionally challenging to treat endovascularly. A prospective Wingspan study, however, demonstrated an approximately 30% rate of in-stent stenosis [23], higher than what had previously been reported in the neurosurgical literature. While most of these were clinically silent, 5% led to significant morbidity and mortality [23]. In a recent review, Ding and Liu [24] found the Wingspan stent to have an overall higher technical success rate in the literature and possibly a lower complication rate, although the authors admit that shorter clinical followup for the Wingspan studies made the comparison uneven.Figure 2
Stent and balloon catheter commonly used in ICAD.Due to the initially promising and conflicting results of the Wingspan stent, the SAMMPRIS trial was designed to compare the Wingspan stent and medical therapy to aggressive medical therapy alone in symptomatic ICAD patients randomizing patients in 50 centers across the US. At the time of writing this paper, the results of that trial have not been published; however, this trial was terminated prematurely because patients in the angioplasty/stent group fared worse than those in the medical therapy group. What has been released about this trial thus far implies that optimizing medical management remains the first treatment of choice for symptomatic intracranial atherosclerotic disease. The SAMMPRIS trial did not address those patients who had failed optimal medical therapy. Endovascular treatment in these patients may still play an important role in optimizing clinical outcome.
## 4. Discussion
ICAD remains a common cause of stroke worldwide, and our understanding regarding the optimal treatment of it remains dismal. The risk of ICAD-associated stroke increases with high-grade (>70%) stenoses and in those patients who demonstrate an increased OEF [25]. The conclusion that these patients need to be treated is likely a sound one, but the optimal therapy for this group desperately needs clarification.Aspirin, as the antithrombotic drug of choice, reduces the rate of recurrent ipsilateral stroke but does not eliminate it, and approximately 1 in 7 such patients will go on to experience recurrent ischemic events [4]. Patients with high-grade stenosis who also have an elevated OEF who experience recurrent strokes despite aspirin therapy are in need of revascularization procedures. The premature termination of the COSS study implies that microsurgical EC-IC bypass may not be the revascularization treatment of choice for these patients.Surgery, in the form of EC-IC bypass procedures is yet to be proven to lower recurrent strokes compared to medical management only. Previous trials may have been flawed by indiscriminate inclusion of subjects without the use of hemodynamic testing to determine who would more likely benefit from the procedure. The COSS and JET trials were initiated to investigate if indeed patients with an elevated OEF were more likely to benefit from surgery. While the final results of the JET trial are pending, the premature termination of the COSS trial implies the limited role of EC-IC bypass in this patient population.Previous stents were largely designed for coronary disease, and the tortuous anatomy of the intracranial vasculature limited their utility. The advent of the Wingspan stent with its flexibility is quite promising, but the initial results of the SAMMPRIS trial comparing the use of the Wingspan stent with medical management imply that medical management remains the treatment of choice for patients with symptomatic ICAD. The role of angioplasty alone or angioplasty/stenting in the patient population that has failed optimal medical management remains to be determined. As of now, these patients have no other reliable alternative other than endovascular therapy.
## 5. Conclusion
Symptomatic ICAD is a significant health burden, and often times, leads to recurrent, disabling strokes. The natural history of ICAD is poorly understood, as are optimal treatment strategies. The results of long-term outcome studies assessing the utility of both microsurgical and endovascular treatment options continue to support the fact that optimizing medical management remains the initial treatment of choice. As refinements in both microsurgical and endovascular techniques/technologies continue, patients suffering from this devastating disease may have other alternatives.
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*Source: 289852-2011-12-19.xml* | 2012 |
# The Monoid Consisting of Kuratowski Operations
**Authors:** Szymon Plewik; Marta Walczyńska
**Journal:** Journal of Mathematics
(2013)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2013/289854
---
## Abstract
The paper fills gaps in knowledge about Kuratowski
operations which are already in the literature. The Cayley table
for these operations has been drawn up. Techniques, using only
paper and pencil, to point out all semigroups and its isomorphism
types are applied. Some results apply only to topology, and one cannot bring them out, using only properties of the complement and
a closure-like operation. The arguments are by systematic study
of possibilities.
---
## Body
## 1. Introduction
LetX be a topological space. Denote by A- closure of the set A⊆X. Let Ac be the complement of A; that is, X∖A=Ac. The aim of this paper is to examine monoids generated under compositions from the closure and the complement. A widely known fact due to Kuratowski [1] states that at most 14 distinct operations can be formed from such compositions. Mark them as follows. Kuratowski operations:σ0(A)=A (the identity),σ1(A)=Ac (the complement),σ2(A)=A- (the closure),σ3(A)=Ac-,σ4(A)=A-c,σ5(A)=Ac-c(the interior),σ6(A)=A-c-,σ7(A)=Ac-c-,σ8(A)=A-c-c,σ9(A)=Ac-c-c,σ10(A)=A-c-c-,σ11(A)=Ac-c-c-,σ12(A)=A-c-c-c,σ13(A)=Ac-c-c-c.The following rules was found in the original paper by Kuratowski [1, pages 183-184]. In the Engelking book [2], they are commented by a hint on page 81. Cancellation rules:
(1)A-c-=A-c-c-c-,Ac-c-=Ac-c-c-c-.Kuratowski operations have been studied by several authors, for example, [3] or [4]. A list of some other authors one can find in the paper [5] by Gardner and Jackson. For the first time these operations were systematically studied in the dissertation by Kuratowski, whose results were published in [1]. Tasks relating to these operations are usually resolved at lectures or exercises with general topology. They are normally left to students for independent resolution. For example, determine how many different ways they convert a given set.This note is organized as follows. Kuratowski operations and their marking are described in the introduction. Their properties of a much broader context than for topologies are presented in Section2. The Cayley table, for the monoid 𝕄 of all Kuratowski operations, has been drawn up in Section 3. We hope that this table has not yet been published in the literature. Having this table, one can create a computer program that calculates all the semigroups contained in 𝕄. However, in Sections 4–8, we present a framework (i.e., techniques using only paper and pencil) to point out all 118 semigroups and 56 isomorphism types of them. The list of 43 semigroups which are not monoids is presented in Section 9. In this section, also isomorphism types are discussed in order of the number of elements in semigroups. Finally, we present cancellation rules (relations) motivated by some topological spaces.
## 2. Cancellation Rules
A mapf:P(X)→P(X) is called: (i)
increasing, if A⊆B implies f(A)⊆f(B);(ii)
decreasing, if A⊆B implies f(B)⊆f(A);(iii)
an involution, if the composition f∘f is the identity;(iv)
an idempotent, if f∘f=f. Assume that A↦σ0(A) is the identity, A↦σ1(A) is a decreasing involution, and A↦σ2(A) is an increasing idempotent map. Other operations σi let be compositions of σ1 and σ2 as it was with the kuratowski operations. We get the following cancellation rules.Lemma 1.
IfB⊆σ2(B), then
(2)σ2∘σ12=σ6,σ2∘σ13=σ7.Proof.
For clarity of this proof, use designationsσ1(A)=Ac and σ2(A)=A-. Thus, we shall prove
(3)A-c-c-c-=A-c-,Ac-c-c-c-=Ac-c-.
We start with A-c-c⊆A-c-c-, substituting B=A-c-c in B⊆B-. This corresponds to A-c-c-c⊆A-c-cc=A-c-, since σ1 is a decreasing involution. Hence A-c-c-c-⊆A-c-, since σ2 an increasing idempotent.
Sinceσ1 is decreasing, σ2 is increasing, and B⊆B-, we have
(4)B-c⊆Bc⊆Bc-.
Thus A-c-c⊆A-cc-=A-, if we put A-c=B. Again using that σ2 is increasing and σ1 is decreasing, we obtain A-c-c-⊆A- and then A-c⊆A-c-c-c. Finally, we get A-c-⊆A-c-c-c-.
WithAc in the place of A in the rule A-c-=A-c-c-c- we get the second rule.In academic textbooks of general topology, for example, [2, Problem 1.7.1.], one can find a hint suggested to prove the above cancellation rules. Students go like this: steps A⊆A- and Ac⊆Ac- lead to Ac-c⊆A; the special case A-c-c-c⊆A-c- (of Ac-c⊆A) leads to A-c-c-c-⊆A-c-; steps A-c-c⊆A- and A-c-c-⊆A- lead to A-c-⊆A-c-c-c-; at the end, use the last step of the proof of Lemma 1. Note that, the above proofs do not use the axioms of topology as follows: (i)
∅=∅-;(ii)
(A∪B)-=A-∪B-. In the literature there are articles in which Kuratowski operations are replaced by some other mappings. For example, Koenen [6] considered linear spaces and put σ2(A) to be the convex hull of A. In fact, Shum [7] considered σ2 as the closure due to the algebraic operations. Add to this, that these operations can be applied to so-called Fréchet (V) spaces, which were considered in the book [8, pages 3–37].
## 3. The Monoid𝕄
Let𝕄 be the monoid consisting of all Kuratowski operations; that is, there are assumed cancellation rules: σ6=σ2∘σ12 and σ7=σ2∘σ13. Fill in the Cayley table for 𝕄, where the row and column marked by the identity are omitted. Similarly as in [9], the factor that labels the row comes first, and that the factor that labels the column is second. For example, σi∘σk is in the row marked by σi and the column marked by σk(5)σ1σ2σ3σ4σ5σ6σ7σ8σ9σ10σ11σ12σ13σ1σ0σ4σ5σ2σ3σ8σ9σ6σ7σ12σ13σ10σ11σ2σ3σ2σ3σ6σ7σ6σ7σ10σ11σ10σ11σ6σ7σ3σ2σ6σ7σ2σ3σ10σ11σ6σ7σ6σ7σ10σ11σ4σ5σ4σ5σ8σ9σ8σ9σ12σ13σ12σ13σ8σ9σ5σ4σ8σ9σ4σ5σ12σ13σ8σ9σ8σ9σ12σ13σ6σ7σ6σ7σ10σ11σ10σ11σ6σ7σ6σ7σ10σ11σ7σ6σ10σ11σ6σ7σ6σ7σ10σ11σ10σ11σ6σ7σ8σ9σ8σ9σ12σ13σ12σ13σ8σ9σ8σ9σ12σ13σ9σ8σ12σ13σ8σ9σ8σ9σ12σ13σ12σ13σ8σ9σ10σ11σ10σ11σ6σ7σ6σ7σ10σ11σ10σ11σ6σ7σ11σ10σ6σ7σ10σ11σ10σ11σ6σ7σ6σ7σ10σ11σ12σ13σ12σ13σ8σ9σ8σ9σ12σ13σ12σ13σ8σ9σ13σ12σ8σ9σ12σ13σ12σ13σ8σ9σ8σ9σ12σ13It turns out that the above table allows us to describe all semigroups contained in𝕄, using pencil-and-paper techniques, only. The argument will be by a systematic study of possibilities. Preparing the list of all semigroups consisting of Kuratowski operations we used following principles: (i)
minimal collection of generators is written using〈A,B,…,Z〉, where letters denote generators;(ii)
when a semigroup has a few minimal collections of generators, then its name is the first collection in the dictionary order;(iii)
all minimal collections of generators are written with the exception of some containingσ0;(iv)
we leave to the readers verification that our list is complete, sometimes we add hints.
## 4. Semigroups withσ1
Observe that each semigroup which containsσ0 is a monoid. Since σ1∘σ1=σ0, a semigroup which contains σ1 is a monoid, too.Theorem 2.
There are three monoids containingσ1: (1)
〈σ1〉={σ0,σ1};(2)
𝕄=〈σ1,σi〉={σ0,σ1,…,σ13}, where i∈{2,3,4,5};(3)
let𝕄1=〈σ1,σ6〉. If j∈{6,7,…,13}, then
(6)𝕄1=〈σ1,σj〉={σ0,σ1}∪{σ6,σ7,…,σ13}.Proof.
The equality〈σ1〉={σ0,σ1} is obvious.
Sinceσ2=σ3∘σ1=σ1∘σ4=σ1∘σ5∘σ1, we have 〈σ1,σ2〉=〈σ1,σ3〉=〈σ1,σ4〉=〈σ1,σ5〉=𝕄.
Ifj∈{6,7,…,13}, then any composition σj∘σi or σk∘σj belongs to 𝕄1, and so 〈σ1,σj〉⊆𝕄1. We have σ7=σ6∘σ1, σ8=σ1∘σ6, σ9=σ1∘σ7, σ10=σ6∘σ6, σ11=σ6∘σ7, σ12=σ8∘σ6, and σ13=σ8∘σ7, and so 𝕄1=〈σ1,σ6〉={σ0,σ1}∪{σ6,σ7,…,σ13}.
Sinceσ6=σ7∘σ1=σ1∘σ8=σ1∘σ9∘σ1=σ10∘σ1∘σ10=σ11∘σ11∘σ1=σ1∘σ12∘σ12 and σ6=σ1∘σ13∘σ1∘σ13∘σ1, we have 〈σ1,σj〉=𝕄1 for j∈{6,7,…,13}.Consider the permutation(7)(σ0σ1σ2σ3σ4σ5σ6σ7σ8σ9σ10σ11σ12σ13σ0σ1σ5σ4σ3σ2σ9σ8σ7σ6σ13σ12σ11σ10).
It determines an automorphism 𝔸:𝕄→𝕄.Theorem 3.
The identity and𝔸 are the only automorphisms of 𝕄.Proof.
Delete rows and columns marked byσ1 in the Cayley table for 𝕄. Then, check that the operation σ3 is in the row or the column marked by σ3 only. Also, the operation σ4 is in the row or the column marked by σ4 only. Therefore the semigroup
(8)〈σ3,σ4〉={σ2,σ3,…,σ13}
has a unique minimal set of generators {σ3,σ4}. The reader is left to check this with the Cayley table for 𝕄.
Suppose𝔾 is an automorphism of 𝕄. By Theorem 2, 𝔾 transforms the set {σ2,σ3,σ4,σ5} onto itself. However σ2 and σ5 are idempotents, but σ3 and σ4 are not idempotents. So, there are two possibilities: 𝔾(σ3)=σ3 and 𝔾(σ4)=σ4, which implies that 𝔾 is the identity; 𝔾(σ3)=σ4 and 𝔾(σ4)=σ3, which implies 𝔾=𝔸. The reader is left to check this with the Cayley table for 𝕄. We offer hints: σ2=σ3∘σ4, σ5=σ4∘σ3, σ6=σ3∘σ2, σ7=σ3∘σ3, σ8=σ4∘σ4, σ9=σ4∘σ5, σ10=σ6∘σ6, σ11=σ6∘σ7, σ12=σ8∘σ6, and σ13=σ8∘σ7, to verify the details of this proof.
## 5. The Monoid of All Idempotents
The set{σ0,σ2,σ5,σ7,σ8,σ10,σ13} consists of all squares in 𝕄. These squares are idempotents and lie on the main diagonal in the Cayley table for 𝕄. They constitute a monoid and
(9){σ0,σ2,σ5,σ7,σ8,σ10,σ13}=〈σ0,σ2,σ5〉.
The permutation
(10)(σ0σ2σ5σ7σ8σ10σ13σ0σ2σ5σ8σ7σ10σ13)
determines the bijection 𝕀:〈σ0,σ2,σ5〉→〈σ0,σ2,σ5〉, such that
(11)𝕀(α∘β)=𝕀(β)∘𝕀(α),
for any α,β∈〈σ0,σ2,σ5〉. To verify this, apply equalities σ2∘σ5=σ7, σ5∘σ2=σ8, σ2∘σ5∘σ2=σ10, and σ5∘σ2∘σ5=σ13. Any bijection 𝕀:G→H, having property 𝕀(α∘β)=𝕀(β)∘𝕀(α), transposes Cayley tables for semigroups G and H. Several semigroups contained in 𝕄 have this property. We leave the reader to verify this.We shall classify all semigroups contained in the semigroup〈σ2,σ5〉. Every such semigroup can be extended to a monoid by attaching σ0 to it. This gives a complete classification of all semigroups in 〈σ0,σ2,σ5〉.The semigroup〈σ2,σ5〉 contains six groups with exactly one element.Semigroups〈σ2,σ10〉={σ2,σ10} and 〈σ5,σ13〉={σ5,σ13} are monoids. Both consist of exactly two elements and are not groups, so they are isomorphic.Semigroups〈σ7,σ10〉 and 〈σ8,σ13〉 are isomorphic, in particular 𝔸[〈σ7,σ10〉]=〈σ8,σ13〉. Also, semigroups 〈σ7,σ13〉 and 〈σ8,σ10〉 are isomorphic by 𝔸. Every of these four semigroups has exactly two elements. None of them is a monoid. They form two types of nonisomorphic semigroups, because the bijections {(σ7,σ10),(σ10,σ8)} and {(σ7,σ8),(σ10,σ10)} are not isomorphisms.Semigroups〈σ2,σ7〉={σ2,σ7,σ10} and 〈σ5,σ8〉={σ5,σ8,σ13} are isomorphic. Also, semigroups 〈σ2,σ8〉={σ2,σ8,σ10} and 〈σ5,σ7〉={σ5,σ7,σ13} are isomorphic. In fact, 𝔸[〈σ2,σ7〉]=〈σ5,σ8〉 and 𝔸[〈σ2,σ8〉]=〈σ5,σ7〉. None of these semigroups is a monoid. They form two types of nonisomorphic semigroups. Indeed, any isomorphism between 〈σ2,σ7〉 and 〈σ2,σ8〉 must be the identity on the monoid 〈σ2,σ10〉. Therefore would have to be the restriction of 𝕀. But 𝕀 restricted to 〈σ7,σ10〉 is not an isomorphism.Semigroups〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13} and 〈σ5,σ10〉=〈σ5,σ7,σ8〉={σ5,σ7,σ8,σ10,σ13} are not monoids. They are isomorphic by 𝔸.The semigroup〈σ2,σ5〉 contains exactly one semigroup with four elements 〈σ7,σ8〉=〈σ10,σ13〉={σ7,σ8,σ10,σ13} which is not a monoid.Note that〈σ2,σ5〉 contains twenty different semigroups with nine non-isomorphism types. These are six isomorphic groups with exactly one element 〈σ2〉≅〈σ5〉≅〈σ7〉≅〈σ8〉≅〈σ10〉≅〈σ13〉, two isomorphic monoids with exactly two elements 〈σ2,σ10〉≅〈σ5,σ13〉, two pairs of isomorphic semigroups with exactly two elements 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ7,σ13〉≅〈σ8,σ10〉, two pairs of isomorphic semigroups with exactly three elements 〈σ2,σ7〉≅〈σ5,σ8〉 and 〈σ2,σ8〉≅〈σ5,σ7〉, a semigroup with exactly four elements 〈σ7,σ8〉, and two isomorphic semigroups with exactly five elements 〈σ2,σ13〉≅〈σ5,σ10〉 and also 〈σ2,σ5〉. Thus, 〈σ2,σ5〉 contains twenty different semigroups with nine isomorphism types. But 〈σ0,σ2,σ5〉 contains forty-one different semigroups with seventeen isomorphism types. Indeed, adding σ0 to semigroups contained in 〈σ2,σ5〉, which are not monoids, we get twenty monoids with eight non-isomorphism types. Adding σ0 to a group contained in 〈σ2,σ5〉 we get a monoid isomorphic to 〈σ2,σ10〉.
## 6. The Semigroup Consisting of{σ6,σ7,…,σ13}
Using the Cayley table for𝕄, check that
(12)𝔸[{σ6,σ7,…,σ13}]={σ6,σ7,…,σ13}.
Similarly, check that the semigroup 〈σ6,σ9〉={σ6,σ7,…,σ13} can be represented as 〈σ6,σ13〉, 〈σ7,σ12〉, 〈σ8,σ11〉, 〈σ9,σ10〉, or 〈σ11,σ12〉. Also 〈σ6,σ9〉=〈σ6,σ7,σ8〉=〈σ7,σ8,σ9〉=〈σ10,σ11,σ13〉=〈σ10,σ12,σ13〉. These representations exhaust all minimal collections of the Kuratowski operations which generate 〈σ6,σ9〉. Other semigroups included in 〈σ6,σ9〉 have one or two minimal collection of generators. One generator has groups 〈σ6〉={σ6,σ10}, 〈σ9〉={σ9,σ13}, 〈σ11〉={σ7,σ11}, and 〈σ12〉={σ8,σ12}. Each of them has exactly two elements, so they are isomorphic. Semigroups 〈σ7,σ10〉, 〈σ7,σ13〉, 〈σ8,σ10〉, 〈σ8,σ13〉, and 〈σ7,σ8〉 are discussed in the previous section. Contained in 〈σ6,σ9〉 and not previously discussed semigroups are 〈σ6,σ7〉, 〈σ6,σ8〉,〈σ7,σ9〉, and 〈σ8,σ9〉. We leave the reader to verify that the following are all possible pairs of Kuratowski operations which constitute a minimal collection of generators for semigroups contained in 〈σ6,σ9〉, but different from the whole. One has (i)
〈σ6,σ7〉=〈σ6,σ11〉=〈σ10,σ11〉={σ6,σ7,σ10,σ11};(ii)
〈σ6,σ8〉=〈σ6,σ12〉=〈σ10,σ12〉={σ6,σ8,σ10,σ12};(iii)
〈σ7,σ9〉=〈σ9,σ11〉=〈σ11,σ13〉={σ7,σ9,σ11,σ13};(iv)
〈σ8,σ9〉=〈σ9,σ12〉=〈σ12,σ13〉={σ8,σ9,σ12,σ13}.Proposition 4.
Semigroups〈σ6,σ7〉 and 〈σ8,σ9〉 are isomorphic, and also semigroups 〈σ6,σ8〉 and 〈σ7,σ9〉 are isomorphic, but semigroups 〈σ6,σ7〉, 〈σ6,σ8〉 are not isomorphic.Proof.
Isomorphisms are defined by𝔸. Suppose J:〈σ6,σ7〉→〈σ6,σ8〉 is an isomorphism. Thus J[〈σ7,σ10〉]=〈σ8,σ10〉. Given J(σ7)=σ8, we get σ10=J(σ10)=J(σ7∘σ10)≠σ8∘σ10=σ8. But J(σ7)=σ10 implies σ10=J(σ7)=J(σ10∘σ7)≠σ8∘σ10=σ8. Both possibilities lead to a contradiction.So,〈σ6,σ9〉 contains eighteen different semigroups with eight non-isomorphism types. Indeed, these are four isomorphic groups with exactly one element 〈σ7〉≅〈σ8〉≅〈σ10〉≅〈σ13〉, four isomorphic groups with exactly two elements 〈σ6〉≅〈σ9〉≅〈σ11〉≅〈σ12〉, two pairs of isomorphic semigroups with exactly two elements 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ7,σ13〉≅〈σ8,σ10〉, and five semigroups with exactly four elements 〈σ6,σ7〉≅〈σ8,σ9〉, 〈σ6,σ8〉≅〈σ7,σ9〉, 〈σ7,σ8〉, and also 〈σ6,σ9〉.
## 7. Remaining Semigroups in〈σ3,σ4〉
We have yet to discuss semigroups included in〈σ3,σ4〉, not included in 〈σ2,σ5〉 and containing at least one of Kuratowski operation σ2, σ3, σ4, or σ5. It will be discussed up to the isomorphism 𝔸. Obviously, 〈σ2〉={σ2} and 〈σ5〉={σ5} are groups.
### 7.1. Extensions of〈σ2〉 and 〈σ5〉 with Elements of 〈σ6,σ9〉
Monoids〈σ2,σ6〉={σ2,σ6,σ10} and 〈σ2,σ10〉={σ2,σ10} have different numbers of elements. Also, 〈σ2,σ6〉 is isomorphic to 〈σ0,σ6〉. Nonisomorphic semigroups 〈σ2,σ7〉 and 〈σ2,σ8〉 are discussed above. The following three semigroups: (i)
〈σ2,σ11〉=〈σ2,σ6,σ7〉={σ2,σ6,σ7,σ10,σ11},(ii)
〈σ2,σ12〉=〈σ2,σ6,σ8〉={σ2,σ6,σ8,σ10,σ12},(iii)
〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13} are not monoids. They are not isomorphic. Indeed, any isomorphism between these semigroups would lead an isomorphism between 〈σ6,σ7〉, 〈σ6,σ8〉, or 〈σ7,σ8〉. This is impossible, by Proposition 4 and because 〈σ7,σ8〉 consists of idempotents, but σ6 is not an idempotent. The nine-element semigroup on the set {σ2,σ6,σ7,…,σ13} is represented as 〈σ2,σ9〉. So, we have added four new semigroups, which are not isomorphic with the semigroups previously discussed. These are 〈σ2,σ11〉, 〈σ2,σ12〉, 〈σ2,σ13〉, and 〈σ2,σ9〉.Using𝔸, we have described eight semigroups—each one isomorphic to a semigroup previously discussed—which contains σ5 and elements (at least one) of 〈σ6,σ9〉. Collections of generators: 〈σ2,σ6,σ13〉, 〈σ2,σ7,σ12〉, 〈σ2,σ8,σ11〉, 〈σ2,σ11,σ12〉, 〈σ2,σ11,σ13〉, and 〈σ2,σ12,σ13〉 are minimal in 〈σ2,σ9〉. Also, collections of generators: 〈σ5,σ7,σ12〉, 〈σ5,σ8,σ11〉, 〈σ5,σ9,σ10〉, 〈σ5,σ10,σ11〉, 〈σ5,σ10,σ12〉, and 〈σ5,σ11,σ12〉 are minimal in 〈σ5,σ6〉.
### 7.2. Extensions of〈σ3〉 and 〈σ4〉 by Elements from the Semigroup 〈σ6,σ9〉
Semigroups〈σ3〉={σ3,σ7,σ11} and 〈σ4〉={σ4,σ8,σ12} are isomorphic by 𝔸. They are not monoids. The semigroup 〈σ3〉 can be extended using elements of 〈σ6,σ9〉, in three following ways:(i)
〈σ3,σ6〉=〈σ3,σ10〉={σ3,σ6,σ7,σ10,σ11};(ii)
〈σ3,σ8〉=〈σ3,σ12〉={σ3,σ6,σ7,…,σ13};(iii)
〈σ3,σ9〉=〈σ3,σ13〉={σ3,σ7,σ9,σ11,σ13}.Semigroups 〈σ3,σ6〉 and 〈σ3,σ9〉 are not isomorphic. Indeed, suppose J:〈σ3,σ6〉→〈σ3,σ9〉 is an isomorphism. Thus, J is the identity on 〈σ3〉, J(σ6)=σ9, and J(σ10)=σ13. This gives a contradiction, since σ3∘σ6=σ10 and σ3∘σ9=σ7.Neither〈σ3,σ6〉 nor 〈σ3,σ9〉 has a minimal collection of generators with three elements, so they give new isomorphism types. Also, 〈σ2,σ9〉 is not isomorphic to 〈σ3,σ8〉, since 〈σ2,σ9〉 has a unique pair of generators and 〈σ3,σ8〉=〈σ3,σ12〉.Using𝔸, we get—isomorphic to previously discussed ones—semigroups 〈σ4,σ9〉=〈σ4,σ13〉={σ4,σ8,σ9σ12,σ13}, 〈σ4,σ6〉=〈σ4,σ10〉={σ4,σ6,σ8σ10,σ12}, and 〈σ4,σ7〉=〈σ4,σ11〉={σ4,σ6,σ7,…,σ13}. There exist minimal collections of generators, such as follows:
(13)〈σ3,σ8〉=〈σ3,σ6,σ9〉=〈σ3,σ6,σ13〉=〈σ3,σ9,σ10〉=〈σ3,σ10,σ13〉,〈σ4,σ7〉=〈σ4,σ6,σ9〉=〈σ4,σ9,σ10〉=〈σ4,σ6,σ13〉=〈σ4,σ10,σ13〉.
### 7.3. More Generators from the Set{σ2,σ3,σ4,σ5}
Now we check that〈σ2,σ3〉={σ2,σ3,σ6,σ7,σ10σ11} and 〈σ4,σ5〉={σ4,σ5,σ8,σ9,σ12σ13}=𝔸[〈σ2,σ3〉] and also 〈σ2,σ4〉={σ2,σ4,σ6,σ8,σ10σ12} and 〈σ3,σ5〉={σ3,σ5,σ7,σ9,σ11σ13}=𝔸[〈σ2,σ4〉] are two pairs of isomorphic semigroups which give two new isomorphism types. Each of these semigroups has six element, so in 𝕄 there are five six-element semigroups of three isomorphism types, since 〈σ2,σ5〉 has 6 elements which are idempotents.In〈σ3,σ4〉 there are seven semigroups which have three generators and have not two generators. These are (1)
〈σ2,σ3,σ8〉=〈σ2,σ3,σ9〉=〈σ2,σ3,σ12〉=〈σ2,σ3,σ13〉;(2)
〈σ4,σ5,σ6〉=〈σ4,σ5,σ7〉=〈σ4,σ5,σ10〉=〈σ4,σ5,σ11〉;(3)
〈σ2,σ4,σ7〉=〈σ2,σ4,σ9〉=〈σ2,σ4,σ11〉=〈σ2,σ4,σ13〉;(4)
〈σ3,σ5,σ6〉=〈σ3,σ5,σ8〉=〈σ3,σ5,σ10〉=〈σ3,σ5,σ12〉;(5)
〈σ2,σ5,σ6〉=〈σ2,σ5,σ9〉=〈σ2,σ5,σ11〉=〈σ2,σ5,σ12〉;(6)
〈σ2,σ3,σ5〉;(7)
〈σ2,σ4,σ5〉.
## 7.1. Extensions of〈σ2〉 and 〈σ5〉 with Elements of 〈σ6,σ9〉
Monoids〈σ2,σ6〉={σ2,σ6,σ10} and 〈σ2,σ10〉={σ2,σ10} have different numbers of elements. Also, 〈σ2,σ6〉 is isomorphic to 〈σ0,σ6〉. Nonisomorphic semigroups 〈σ2,σ7〉 and 〈σ2,σ8〉 are discussed above. The following three semigroups: (i)
〈σ2,σ11〉=〈σ2,σ6,σ7〉={σ2,σ6,σ7,σ10,σ11},(ii)
〈σ2,σ12〉=〈σ2,σ6,σ8〉={σ2,σ6,σ8,σ10,σ12},(iii)
〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13} are not monoids. They are not isomorphic. Indeed, any isomorphism between these semigroups would lead an isomorphism between 〈σ6,σ7〉, 〈σ6,σ8〉, or 〈σ7,σ8〉. This is impossible, by Proposition 4 and because 〈σ7,σ8〉 consists of idempotents, but σ6 is not an idempotent. The nine-element semigroup on the set {σ2,σ6,σ7,…,σ13} is represented as 〈σ2,σ9〉. So, we have added four new semigroups, which are not isomorphic with the semigroups previously discussed. These are 〈σ2,σ11〉, 〈σ2,σ12〉, 〈σ2,σ13〉, and 〈σ2,σ9〉.Using𝔸, we have described eight semigroups—each one isomorphic to a semigroup previously discussed—which contains σ5 and elements (at least one) of 〈σ6,σ9〉. Collections of generators: 〈σ2,σ6,σ13〉, 〈σ2,σ7,σ12〉, 〈σ2,σ8,σ11〉, 〈σ2,σ11,σ12〉, 〈σ2,σ11,σ13〉, and 〈σ2,σ12,σ13〉 are minimal in 〈σ2,σ9〉. Also, collections of generators: 〈σ5,σ7,σ12〉, 〈σ5,σ8,σ11〉, 〈σ5,σ9,σ10〉, 〈σ5,σ10,σ11〉, 〈σ5,σ10,σ12〉, and 〈σ5,σ11,σ12〉 are minimal in 〈σ5,σ6〉.
## 7.2. Extensions of〈σ3〉 and 〈σ4〉 by Elements from the Semigroup 〈σ6,σ9〉
Semigroups〈σ3〉={σ3,σ7,σ11} and 〈σ4〉={σ4,σ8,σ12} are isomorphic by 𝔸. They are not monoids. The semigroup 〈σ3〉 can be extended using elements of 〈σ6,σ9〉, in three following ways:(i)
〈σ3,σ6〉=〈σ3,σ10〉={σ3,σ6,σ7,σ10,σ11};(ii)
〈σ3,σ8〉=〈σ3,σ12〉={σ3,σ6,σ7,…,σ13};(iii)
〈σ3,σ9〉=〈σ3,σ13〉={σ3,σ7,σ9,σ11,σ13}.Semigroups 〈σ3,σ6〉 and 〈σ3,σ9〉 are not isomorphic. Indeed, suppose J:〈σ3,σ6〉→〈σ3,σ9〉 is an isomorphism. Thus, J is the identity on 〈σ3〉, J(σ6)=σ9, and J(σ10)=σ13. This gives a contradiction, since σ3∘σ6=σ10 and σ3∘σ9=σ7.Neither〈σ3,σ6〉 nor 〈σ3,σ9〉 has a minimal collection of generators with three elements, so they give new isomorphism types. Also, 〈σ2,σ9〉 is not isomorphic to 〈σ3,σ8〉, since 〈σ2,σ9〉 has a unique pair of generators and 〈σ3,σ8〉=〈σ3,σ12〉.Using𝔸, we get—isomorphic to previously discussed ones—semigroups 〈σ4,σ9〉=〈σ4,σ13〉={σ4,σ8,σ9σ12,σ13}, 〈σ4,σ6〉=〈σ4,σ10〉={σ4,σ6,σ8σ10,σ12}, and 〈σ4,σ7〉=〈σ4,σ11〉={σ4,σ6,σ7,…,σ13}. There exist minimal collections of generators, such as follows:
(13)〈σ3,σ8〉=〈σ3,σ6,σ9〉=〈σ3,σ6,σ13〉=〈σ3,σ9,σ10〉=〈σ3,σ10,σ13〉,〈σ4,σ7〉=〈σ4,σ6,σ9〉=〈σ4,σ9,σ10〉=〈σ4,σ6,σ13〉=〈σ4,σ10,σ13〉.
## 7.3. More Generators from the Set{σ2,σ3,σ4,σ5}
Now we check that〈σ2,σ3〉={σ2,σ3,σ6,σ7,σ10σ11} and 〈σ4,σ5〉={σ4,σ5,σ8,σ9,σ12σ13}=𝔸[〈σ2,σ3〉] and also 〈σ2,σ4〉={σ2,σ4,σ6,σ8,σ10σ12} and 〈σ3,σ5〉={σ3,σ5,σ7,σ9,σ11σ13}=𝔸[〈σ2,σ4〉] are two pairs of isomorphic semigroups which give two new isomorphism types. Each of these semigroups has six element, so in 𝕄 there are five six-element semigroups of three isomorphism types, since 〈σ2,σ5〉 has 6 elements which are idempotents.In〈σ3,σ4〉 there are seven semigroups which have three generators and have not two generators. These are (1)
〈σ2,σ3,σ8〉=〈σ2,σ3,σ9〉=〈σ2,σ3,σ12〉=〈σ2,σ3,σ13〉;(2)
〈σ4,σ5,σ6〉=〈σ4,σ5,σ7〉=〈σ4,σ5,σ10〉=〈σ4,σ5,σ11〉;(3)
〈σ2,σ4,σ7〉=〈σ2,σ4,σ9〉=〈σ2,σ4,σ11〉=〈σ2,σ4,σ13〉;(4)
〈σ3,σ5,σ6〉=〈σ3,σ5,σ8〉=〈σ3,σ5,σ10〉=〈σ3,σ5,σ12〉;(5)
〈σ2,σ5,σ6〉=〈σ2,σ5,σ9〉=〈σ2,σ5,σ11〉=〈σ2,σ5,σ12〉;(6)
〈σ2,σ3,σ5〉;(7)
〈σ2,σ4,σ5〉.
## 8. Semigroups which Are Contained in〈σ3,σ4〉
Groups〈σ2〉≅〈σ5〉≅〈σ7〉≅〈σ8〉≅〈σ10〉≅〈σ13〉 have one element and are isomorphic.Groups〈σ6〉≅〈σ9〉≅〈σ11〉≅〈σ12〉, monoids 〈σ2,σ10〉≅〈σ5,σ13〉, and also semigroups 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ7,σ13〉≅〈σ8,σ10〉 have two elements and Cayley tables as follows:
(14)ABABABABABAABBBAABAABBABABAAABBBMonoids〈σ2,σ6〉≅〈σ5,σ9〉, and also semigroups 〈σ2,σ7〉≅〈σ5,σ8〉, 〈σ2,σ8〉≅〈σ5,σ7〉, and 〈σ3〉≅〈σ4〉 have three elements and Cayley tables as follows:
(15)ABCAABCBBCBCCBCABCAABCBCBCCCBCABCAACCBBBBCCCCABCABCBBCBCCBCBSemigroups〈σ6,σ7〉≅〈σ8,σ9〉, 〈σ6,σ8〉≅〈σ7,σ9〉, and 〈σ7,σ8〉 have four elements and Cayley tables as follows:
(16)ABCDACDABBABCDCABCDDCDABABCDACAACBDBBDCACCADBDDBABCDAACCABDBBDCACCADDBBDSemigroups〈σ2,σ11〉≅〈σ5,σ12〉, 〈σ2,σ12〉≅〈σ5,σ11〉, 〈σ2,σ13〉≅〈σ5,σ10〉, 〈σ3,σ6〉≅〈σ4,σ9〉, and 〈σ3,σ9〉≅〈σ4,σ6〉 have five elements. Semigroups 〈σ2,σ3〉≅〈σ4,σ5〉, 〈σ2,σ4〉≅〈σ3,σ5〉, and 〈σ2,σ5〉 have six elements. Construction of Cayley tables for these semigroups, as well as other semigroups, we leave it to the readers. One can prepare such tables removing from the Cayley table for 𝕄 some columns and rows. Then change Kuratowski operations onto letters of the alphabet. For example, 〈σ0,σ2,σ5〉 has the following Cayley table:
(17)0ABCDEF00ABCDEFAAACCEECBBDBFDDFCCECCEECDDDFFDDFEEECCEECFFDFFDDF
Preparing the Cayley table for 〈σ0,σ2,σ5〉 we put σ0=0,σ2=A,σ5=B,σ7=C,σ8=D,σ10=E, and σ13=F. This table immediately shows that semigroups 〈σ2,σ5〉 and 〈σ0,σ2,σ5〉 have exactly two automorphisms. These are identities and restrictions of 𝔸.Semigroup〈σ6,σ9〉 has eight elements. Semigroups 〈σ2,σ9〉≅〈σ5,σ6〉 and 〈σ3,σ8〉≅〈σ4,σ7〉 have nine elements. Semigroups 〈σ2,σ3,σ8〉≅〈σ4,σ5,σ7〉, 〈σ2,σ4,σ7〉≅〈σ3,σ5,σ8〉, and 〈σ2,σ5,σ6〉 have ten elements. Semigroups 〈σ2,σ3,σ5〉≅〈σ2,σ4,σ5〉 have eleven elements. In the end, the semigroup 〈σ3,σ4〉 has twelve elements.Thus, the semigroup〈σ3,σ4〉 includes fifty-seven semigroups, among which there are ten groups, fourteen monoids, and also forty-three semigroups which are not monoids. These semigroups consist of twenty-eight types of nonisomorphic semigroups, two non-isomorphism types of groups, two non-isomorphism types of monoids which are not groups, and twenty four non-isomorphism types of semigroups which are not monoids.
## 9. Viewing Semigroups Contained in𝕄
### 9.1. Descriptive Data on Semigroups which Are Contained in𝕄
There are one hundred eighteen, that is,118=2·57+4, semigroups which are contained in 𝕄. These are fifty-seven semigroups contained in 〈σ3,σ4〉, fifty-seven monoids formed by adding σ0 to a semigroup contained in 〈σ3,σ4〉, groups 〈σ0〉, 〈σ1〉, and monoids 〈σ1,σ6〉=𝕄1 and 〈σ1,σ2〉=𝕄.There are fifty-six types of nonisomorphic semigroups in𝕄. These are twenty-eight non-isomorphism types of semigroups contained in 〈σ3,σ4〉, twenty-six types of nonisomorphic monoids formed by adding σ0 to a semigroup contained in 〈σ3,σ4〉, and also 𝕄1 and 𝕄. Indeed, adding σ0 to a semigroup which is not a monoid we obtain a monoid. In this way, we get twenty-four types of nonisomorphic monoids. Adding σ0 to a monoid contained in 〈σ3,σ4〉 we get two new non-isomorphism types of monoids. But, adding σ0 to a group contained in 〈σ3,σ4〉 we get no new type of monoid, since we get a monoid isomorphic to 〈σ2,σ10〉 or 〈σ2,σ6〉. The other two types are 𝕄1 and 𝕄.
### 9.2. Semigroups which Are Not Monoids
Below we have reproduced, using the smallest number of generators and the dictionary order, a list of all 43 semigroups, which are included in the𝕄 as follows:(1)
〈σ2,σ3〉={σ2,σ3,σ6,σ7,σ10,σ11}.(2)
〈σ2,σ3,σ5〉={σ2,σ3,σ5,σ6,…,σ13}.(3)
〈σ2,σ3,σ8〉=〈σ2,σ3,σ9〉=〈σ2,σ3,σ12〉=〈σ2,σ3,σ13〉={σ2,σ3,σ6,σ7,…,σ13}.(4)
〈σ2,σ4〉={σ2,σ4,σ6,σ8,σ10,σ12}.(5)
〈σ2,σ4,σ5〉={σ2,σ4,σ5,…,σ13}.(6)
〈σ2,σ4,σ7〉=〈σ2,σ4,σ9〉=〈σ2,σ4,σ11〉=〈σ2,σ4,σ13〉={σ2,σ4,σ6,σ7…,σ13}.(7)
〈σ2,σ5〉={σ2,σ5,σ7,σ8,σ10,σ13}.(8)
〈σ2,σ5,σ6〉=〈σ2,σ5,σ9〉=〈σ2,σ5,σ11〉=〈σ2,σ5,σ12〉={σ2,σ5,σ6,…,σ13}.(9)
〈σ2,σ7〉={σ2,σ7,σ10}.(10)
〈σ2,σ8〉={σ2,σ8,σ10}.(11)
〈σ2,σ9〉=〈σ2,σ6,σ13〉=〈σ2,σ7,σ12〉=〈σ2,σ8,σ11〉=〈σ2,σ11,σ12〉=〈σ2,σ11,σ13〉 = 〈σ2,σ12,σ13〉={σ2,σ6,σ7,…,σ13}.(12)
〈σ2,σ11〉=〈σ2,σ6,σ7〉={σ2,σ6,σ7,σ10,σ11}.(13)
〈σ2,σ12〉=〈σ2,σ6,σ8〉={σ2,σ6,σ8,σ10,σ12}.(14)
〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13}.(15)
〈σ3〉={σ3,σ7,σ11}.(16)
〈σ3,σ4〉={σ2,σ3,…,σ13}.(17)
〈σ3,σ5〉={σ3,σ5,σ7,σ9,σ11,σ13}.(18)
〈σ3,σ5,σ6〉=〈σ3,σ5,σ8〉=〈σ3,σ5,σ10〉=〈σ3,σ5,σ12〉={σ3,σ5,σ6,…,σ13}.(19)
〈σ3,σ6〉=〈σ3,σ10〉={σ3,σ6,σ7,σ10,σ11}.(20)
〈σ3,σ8〉=〈σ3,σ12〉={σ3,σ6,σ7,…,σ13}.(21)
〈σ3,σ9〉=〈σ3,σ13〉={σ3,σ7,σ9,σ11,σ13}.(22)
〈σ4〉={σ4,σ8,σ12}.(23)
〈σ4,σ5〉={σ4,σ5,σ8,σ9,σ12,σ13}.(24)
〈σ4,σ5,σ6〉=〈σ4,σ5,σ7〉=〈σ4,σ5,σ10〉=〈σ4,σ5,σ11〉={σ4,σ5,…,σ13}.(25)
〈σ4,σ6〉=〈σ4,σ10〉={σ4,σ6,σ8,σ10,σ12}.(26)
〈σ4,σ7〉=〈σ4,σ11〉={σ4,σ6,σ7,…,σ13}.(27)
〈σ4,σ9〉=〈σ4,σ13〉={σ4,σ8,σ9,σ12,σ13}.(28)
〈σ5,σ6〉=〈σ5,σ7,σ12〉=〈σ5,σ8,σ11〉=〈σ5,σ9,σ10〉=〈σ5,σ10,σ11〉=〈σ5,σ10,σ12〉 = 〈σ5,σ11,σ12〉={σ5,σ6,…,σ13}.(29)
〈σ5,σ7〉={σ5,σ7,σ13}.(30)
〈σ5,σ8〉={σ5,σ8,σ13}.(31)
〈σ5,σ10〉=〈σ5,σ7,σ8〉={σ5,σ7,σ8,σ10,σ13}.(32)
〈σ5,σ11〉=〈σ5,σ7,σ9〉={σ5,σ7,σ9,σ11,σ13}.(33)
〈σ5,σ12〉=〈σ5,σ8,σ9〉={σ5,σ8,σ9,σ12,σ13}.(34)
〈σ6,σ7〉=〈σ6,σ11〉=〈σ10,σ11〉={σ6,σ7,σ10,σ11}.(35)
〈σ6,σ8〉=〈σ6,σ12〉=〈σ10,σ12〉={σ6,σ8,σ10,σ12}.(36)
〈σ6,σ9〉=〈σ6,σ13〉=〈σ7,σ12〉=〈σ8,σ11〉=〈σ9,σ10〉=〈σ11,σ12〉 = 〈σ6,σ7,σ8〉=〈σ7,σ8,σ9〉 = 〈σ10,σ11,σ13〉=〈σ10,σ12,σ13〉={σ6,σ7,…,σ13}.(37)
〈σ7,σ8〉={σ7,σ8,σ10,σ13}.(38)
〈σ7,σ9〉={σ7,σ9,σ11,σ13}.(39)
〈σ7,σ10〉={σ7,σ10}.(40)
〈σ7,σ13〉={σ7,σ13}.(41)
〈σ8,σ9〉={σ8,σ9,σ12,σ13}.(42)
〈σ8,σ10〉={σ8,σ10}.(43)
〈σ8,σ13〉={σ8,σ13}.
### 9.3. Isomorphism Types of Semigroups Contained in𝕄
Systematize the list of all isomorphism types of semigroups contained in the monoid𝕄. Isomorphisms, which are restrictions of the isomorphism 𝔸, will be regarded as self-evident, and therefore they will not be commented on.(i)
The monoid𝕄 contains 12 groups with 2 isomorphism types. These are 7 one-element groups and 5 two-element groups.(ii)
The monoid𝕄 contains 8 two-element monoids with 2 isomorphism types. These are σ0 added to 6 one-element groups and 〈σ2,σ10〉≅〈σ5,σ13〉. Also, it contains 4 two-element semigroups, not monoids, with 2 isomorphism types. These are 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ8,σ10〉≅〈σ7,σ13〉.(iii)
The monoid𝕄 contains 12 three-element monoids with 5 isomorphism types. These are σ0 added to 4 two-element groups and also 〈σ0,σ2,σ10〉≅〈σ0,σ5,σ13〉, 〈σ0,σ7,σ10〉≅〈σ0,σ8,σ13〉, 〈σ0,σ8,σ10〉≅〈σ0,σ7,σ13〉, and 〈σ2,σ6〉≅〈σ5,σ9〉.(iv)
The monoid𝕄 contains 6 three-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ2,σ7〉≅〈σ5,σ8〉, 〈σ2,σ8〉≅〈σ5,σ7〉, and 〈σ3〉≅〈σ4〉.(v)
The monoid𝕄 contains 8 four-element monoids, each contains σ0, with 4 isomorphism types. These are semigroups from two preceding items that can be substantially extended by σ0.(vi)
The monoid𝕄 contains 5 four-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ6,σ7〉≅〈σ8,σ9〉, 〈σ6,σ8〉≅〈σ7,σ9〉 and 〈σ7,σ8〉. These semigroups extended by σ0 yield 5 monoids, all which consist of five elements, with 3 isomorphism types.(vii)
The monoid𝕄 contains 10 five-element semigroups—not monoids, with 5 isomorphism types. These are 〈σ2,σ11〉≅〈σ5,σ12〉, 〈σ2,σ12〉≅〈σ5,σ11〉, 〈σ2,σ13〉≅〈σ5,σ10〉, 〈σ3,σ6〉≅〈σ4,σ9〉, and 〈σ3,σ9〉≅〈σ4,σ6〉. These semigroups extended by σ0 yield 10 monoids, all of which consist of six elements, with 5 isomorphism types. We get 10 new isomorphism types, since the semigroups are distinguished by semigroups 〈σ3〉 and 〈σ4〉, and by nonisomorphic semigroups 〈σ6,σ7〉, 〈σ6,σ8〉, and 〈σ7,σ8〉.(viii)
The monoid𝕄 contains 5 six-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ2,σ3〉≅〈σ4,σ5〉, 〈σ2,σ4〉≅〈σ3,σ5〉, and 〈σ2,σ5〉. These semigroups extended by σ0 yield 5 monoids, all of which consist of seven elements, with 3 isomorphism types. We get 6 new isomorphism types, since the semigroups are distinguished by non isomorphic semigroups 〈σ6,σ7〉, 〈σ6,σ8〉, and 〈σ7,σ8〉.(ix)
The monoid𝕄 contains no seven-element semigroup, not a monoid, no eight-element monoid and the only semigroup 〈σ6,σ9〉 with exactly eight elements and the only monoid 〈σ0,σ6,σ9〉 with exactly nine elements.(x)
The monoid𝕄 contains 4 nine-element semigroups, not monoids, with 2 isomorphism types. These are 〈σ2,σ9〉≅〈σ5,σ6〉 and 〈σ3,σ8〉≅〈σ4,σ7〉. The semigroup 〈σ2,σ9〉 does not contain a semigroup isomorphic to 〈σ3〉, hence it is not isomorphic to 〈σ3,σ8〉. These semigroups extended by σ0 yield 4 monoids, all of which consist of ten elements, with 2 isomorphism types.(xi)
The monoid𝕄 contains 6 ten-element semigroups, not monoids, with 4 isomorphism types. These are 〈σ1,σ6〉, 〈σ2,σ3,σ8〉≅〈σ4,σ5,σ6〉, 〈σ2,σ4,σ7〉≅〈σ3,σ5,σ6〉, and 〈σ2,σ5,σ6〉. These semigroups (except 〈σ1,σ6〉) extended by σ0 yield 5 monoids, all of which consist of ten elements, with 3 isomorphism types. We get 6 new isomorphism types, since the semigroups are distinguished by not isomorphic semigroups 〈σ2,σ3〉, 〈σ2,σ4〉, and 〈σ2,σ5〉.(xii)
The monoid𝕄 contains 2 isomorphic semigroups, not monoids, which consist of 11 elements, that is, 〈σ2,σ3,σ5〉≅〈σ2,σ4,σ5〉. These semigroups extended by σ0 yield 2 isomorphic monoids, which consist of 12 elements. The monoid 𝕄 contains no larger semigroup with the exception of itself.
## 9.1. Descriptive Data on Semigroups which Are Contained in𝕄
There are one hundred eighteen, that is,118=2·57+4, semigroups which are contained in 𝕄. These are fifty-seven semigroups contained in 〈σ3,σ4〉, fifty-seven monoids formed by adding σ0 to a semigroup contained in 〈σ3,σ4〉, groups 〈σ0〉, 〈σ1〉, and monoids 〈σ1,σ6〉=𝕄1 and 〈σ1,σ2〉=𝕄.There are fifty-six types of nonisomorphic semigroups in𝕄. These are twenty-eight non-isomorphism types of semigroups contained in 〈σ3,σ4〉, twenty-six types of nonisomorphic monoids formed by adding σ0 to a semigroup contained in 〈σ3,σ4〉, and also 𝕄1 and 𝕄. Indeed, adding σ0 to a semigroup which is not a monoid we obtain a monoid. In this way, we get twenty-four types of nonisomorphic monoids. Adding σ0 to a monoid contained in 〈σ3,σ4〉 we get two new non-isomorphism types of monoids. But, adding σ0 to a group contained in 〈σ3,σ4〉 we get no new type of monoid, since we get a monoid isomorphic to 〈σ2,σ10〉 or 〈σ2,σ6〉. The other two types are 𝕄1 and 𝕄.
## 9.2. Semigroups which Are Not Monoids
Below we have reproduced, using the smallest number of generators and the dictionary order, a list of all 43 semigroups, which are included in the𝕄 as follows:(1)
〈σ2,σ3〉={σ2,σ3,σ6,σ7,σ10,σ11}.(2)
〈σ2,σ3,σ5〉={σ2,σ3,σ5,σ6,…,σ13}.(3)
〈σ2,σ3,σ8〉=〈σ2,σ3,σ9〉=〈σ2,σ3,σ12〉=〈σ2,σ3,σ13〉={σ2,σ3,σ6,σ7,…,σ13}.(4)
〈σ2,σ4〉={σ2,σ4,σ6,σ8,σ10,σ12}.(5)
〈σ2,σ4,σ5〉={σ2,σ4,σ5,…,σ13}.(6)
〈σ2,σ4,σ7〉=〈σ2,σ4,σ9〉=〈σ2,σ4,σ11〉=〈σ2,σ4,σ13〉={σ2,σ4,σ6,σ7…,σ13}.(7)
〈σ2,σ5〉={σ2,σ5,σ7,σ8,σ10,σ13}.(8)
〈σ2,σ5,σ6〉=〈σ2,σ5,σ9〉=〈σ2,σ5,σ11〉=〈σ2,σ5,σ12〉={σ2,σ5,σ6,…,σ13}.(9)
〈σ2,σ7〉={σ2,σ7,σ10}.(10)
〈σ2,σ8〉={σ2,σ8,σ10}.(11)
〈σ2,σ9〉=〈σ2,σ6,σ13〉=〈σ2,σ7,σ12〉=〈σ2,σ8,σ11〉=〈σ2,σ11,σ12〉=〈σ2,σ11,σ13〉 = 〈σ2,σ12,σ13〉={σ2,σ6,σ7,…,σ13}.(12)
〈σ2,σ11〉=〈σ2,σ6,σ7〉={σ2,σ6,σ7,σ10,σ11}.(13)
〈σ2,σ12〉=〈σ2,σ6,σ8〉={σ2,σ6,σ8,σ10,σ12}.(14)
〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13}.(15)
〈σ3〉={σ3,σ7,σ11}.(16)
〈σ3,σ4〉={σ2,σ3,…,σ13}.(17)
〈σ3,σ5〉={σ3,σ5,σ7,σ9,σ11,σ13}.(18)
〈σ3,σ5,σ6〉=〈σ3,σ5,σ8〉=〈σ3,σ5,σ10〉=〈σ3,σ5,σ12〉={σ3,σ5,σ6,…,σ13}.(19)
〈σ3,σ6〉=〈σ3,σ10〉={σ3,σ6,σ7,σ10,σ11}.(20)
〈σ3,σ8〉=〈σ3,σ12〉={σ3,σ6,σ7,…,σ13}.(21)
〈σ3,σ9〉=〈σ3,σ13〉={σ3,σ7,σ9,σ11,σ13}.(22)
〈σ4〉={σ4,σ8,σ12}.(23)
〈σ4,σ5〉={σ4,σ5,σ8,σ9,σ12,σ13}.(24)
〈σ4,σ5,σ6〉=〈σ4,σ5,σ7〉=〈σ4,σ5,σ10〉=〈σ4,σ5,σ11〉={σ4,σ5,…,σ13}.(25)
〈σ4,σ6〉=〈σ4,σ10〉={σ4,σ6,σ8,σ10,σ12}.(26)
〈σ4,σ7〉=〈σ4,σ11〉={σ4,σ6,σ7,…,σ13}.(27)
〈σ4,σ9〉=〈σ4,σ13〉={σ4,σ8,σ9,σ12,σ13}.(28)
〈σ5,σ6〉=〈σ5,σ7,σ12〉=〈σ5,σ8,σ11〉=〈σ5,σ9,σ10〉=〈σ5,σ10,σ11〉=〈σ5,σ10,σ12〉 = 〈σ5,σ11,σ12〉={σ5,σ6,…,σ13}.(29)
〈σ5,σ7〉={σ5,σ7,σ13}.(30)
〈σ5,σ8〉={σ5,σ8,σ13}.(31)
〈σ5,σ10〉=〈σ5,σ7,σ8〉={σ5,σ7,σ8,σ10,σ13}.(32)
〈σ5,σ11〉=〈σ5,σ7,σ9〉={σ5,σ7,σ9,σ11,σ13}.(33)
〈σ5,σ12〉=〈σ5,σ8,σ9〉={σ5,σ8,σ9,σ12,σ13}.(34)
〈σ6,σ7〉=〈σ6,σ11〉=〈σ10,σ11〉={σ6,σ7,σ10,σ11}.(35)
〈σ6,σ8〉=〈σ6,σ12〉=〈σ10,σ12〉={σ6,σ8,σ10,σ12}.(36)
〈σ6,σ9〉=〈σ6,σ13〉=〈σ7,σ12〉=〈σ8,σ11〉=〈σ9,σ10〉=〈σ11,σ12〉 = 〈σ6,σ7,σ8〉=〈σ7,σ8,σ9〉 = 〈σ10,σ11,σ13〉=〈σ10,σ12,σ13〉={σ6,σ7,…,σ13}.(37)
〈σ7,σ8〉={σ7,σ8,σ10,σ13}.(38)
〈σ7,σ9〉={σ7,σ9,σ11,σ13}.(39)
〈σ7,σ10〉={σ7,σ10}.(40)
〈σ7,σ13〉={σ7,σ13}.(41)
〈σ8,σ9〉={σ8,σ9,σ12,σ13}.(42)
〈σ8,σ10〉={σ8,σ10}.(43)
〈σ8,σ13〉={σ8,σ13}.
## 9.3. Isomorphism Types of Semigroups Contained in𝕄
Systematize the list of all isomorphism types of semigroups contained in the monoid𝕄. Isomorphisms, which are restrictions of the isomorphism 𝔸, will be regarded as self-evident, and therefore they will not be commented on.(i)
The monoid𝕄 contains 12 groups with 2 isomorphism types. These are 7 one-element groups and 5 two-element groups.(ii)
The monoid𝕄 contains 8 two-element monoids with 2 isomorphism types. These are σ0 added to 6 one-element groups and 〈σ2,σ10〉≅〈σ5,σ13〉. Also, it contains 4 two-element semigroups, not monoids, with 2 isomorphism types. These are 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ8,σ10〉≅〈σ7,σ13〉.(iii)
The monoid𝕄 contains 12 three-element monoids with 5 isomorphism types. These are σ0 added to 4 two-element groups and also 〈σ0,σ2,σ10〉≅〈σ0,σ5,σ13〉, 〈σ0,σ7,σ10〉≅〈σ0,σ8,σ13〉, 〈σ0,σ8,σ10〉≅〈σ0,σ7,σ13〉, and 〈σ2,σ6〉≅〈σ5,σ9〉.(iv)
The monoid𝕄 contains 6 three-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ2,σ7〉≅〈σ5,σ8〉, 〈σ2,σ8〉≅〈σ5,σ7〉, and 〈σ3〉≅〈σ4〉.(v)
The monoid𝕄 contains 8 four-element monoids, each contains σ0, with 4 isomorphism types. These are semigroups from two preceding items that can be substantially extended by σ0.(vi)
The monoid𝕄 contains 5 four-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ6,σ7〉≅〈σ8,σ9〉, 〈σ6,σ8〉≅〈σ7,σ9〉 and 〈σ7,σ8〉. These semigroups extended by σ0 yield 5 monoids, all which consist of five elements, with 3 isomorphism types.(vii)
The monoid𝕄 contains 10 five-element semigroups—not monoids, with 5 isomorphism types. These are 〈σ2,σ11〉≅〈σ5,σ12〉, 〈σ2,σ12〉≅〈σ5,σ11〉, 〈σ2,σ13〉≅〈σ5,σ10〉, 〈σ3,σ6〉≅〈σ4,σ9〉, and 〈σ3,σ9〉≅〈σ4,σ6〉. These semigroups extended by σ0 yield 10 monoids, all of which consist of six elements, with 5 isomorphism types. We get 10 new isomorphism types, since the semigroups are distinguished by semigroups 〈σ3〉 and 〈σ4〉, and by nonisomorphic semigroups 〈σ6,σ7〉, 〈σ6,σ8〉, and 〈σ7,σ8〉.(viii)
The monoid𝕄 contains 5 six-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ2,σ3〉≅〈σ4,σ5〉, 〈σ2,σ4〉≅〈σ3,σ5〉, and 〈σ2,σ5〉. These semigroups extended by σ0 yield 5 monoids, all of which consist of seven elements, with 3 isomorphism types. We get 6 new isomorphism types, since the semigroups are distinguished by non isomorphic semigroups 〈σ6,σ7〉, 〈σ6,σ8〉, and 〈σ7,σ8〉.(ix)
The monoid𝕄 contains no seven-element semigroup, not a monoid, no eight-element monoid and the only semigroup 〈σ6,σ9〉 with exactly eight elements and the only monoid 〈σ0,σ6,σ9〉 with exactly nine elements.(x)
The monoid𝕄 contains 4 nine-element semigroups, not monoids, with 2 isomorphism types. These are 〈σ2,σ9〉≅〈σ5,σ6〉 and 〈σ3,σ8〉≅〈σ4,σ7〉. The semigroup 〈σ2,σ9〉 does not contain a semigroup isomorphic to 〈σ3〉, hence it is not isomorphic to 〈σ3,σ8〉. These semigroups extended by σ0 yield 4 monoids, all of which consist of ten elements, with 2 isomorphism types.(xi)
The monoid𝕄 contains 6 ten-element semigroups, not monoids, with 4 isomorphism types. These are 〈σ1,σ6〉, 〈σ2,σ3,σ8〉≅〈σ4,σ5,σ6〉, 〈σ2,σ4,σ7〉≅〈σ3,σ5,σ6〉, and 〈σ2,σ5,σ6〉. These semigroups (except 〈σ1,σ6〉) extended by σ0 yield 5 monoids, all of which consist of ten elements, with 3 isomorphism types. We get 6 new isomorphism types, since the semigroups are distinguished by not isomorphic semigroups 〈σ2,σ3〉, 〈σ2,σ4〉, and 〈σ2,σ5〉.(xii)
The monoid𝕄 contains 2 isomorphic semigroups, not monoids, which consist of 11 elements, that is, 〈σ2,σ3,σ5〉≅〈σ2,σ4,σ5〉. These semigroups extended by σ0 yield 2 isomorphic monoids, which consist of 12 elements. The monoid 𝕄 contains no larger semigroup with the exception of itself.
## 10. Cancellation Rules Motivated by Some Topological Properties
### 10.1. Some Consequences of the Axiom∅=∅-
So far, we used only the following relations (above named cancellation rules):σ2∘σ2=σ2, σ1∘σ1=σ0, σ2∘σ12=σ6, and σ2∘σ13=σ7. When one assumes X≠∅=∅-, then
(18)X=σ0(X)=σ2(X)=σ5(X)=σ7(X)=σ8(X)=σ10(X)=σ13(X),∅=σ1(X)=σ3(X)=σ4(X)=σ6(X)=σ9(X)=σ11(X)=σ12(X).
Using the substitution A↦Ac, one obtains equivalent relations between operations from the set {σ1,σ3,σ4,σ6,σ9,σ11,σ12}, and conversely. Therefore, cancellation rules are topologically reasonable only between the operations from the monoid as follows:
(19)〈σ0,σ2,σ5〉={σ0,σ2,σ5,σ7,σ8,σ10,σ13}.
Chapman, see [3], considered properties of subsets with respect to such relations. Below, we are going to identify relations that are determined by some topological spaces; compare [10, 11].
### 10.2. The Relationσ0=σ2
If a topological spaceX is discrete, then there exist two Kuratowski operation, only. These are σ0 and σ1. So, the monoid of Kuratowski operations reduced to the group 〈σ1〉.The relationσ0=σ2 is equivalent to any relation σ0=σi, where i∈{5,7,8,10,13}. Any such relation implies that every subset of X has to be closed and open; that is, X has to be discrete. However, one can check these using (only) the facts that σ1 is an involution and σ2 is an idempotent and the cancellation rules, that is, the Cayley table for 𝕄. So, σ0=σ2 follows
(20)σ0=σ2=σ5=σ7=σ8=σ10=σ13.
### 10.3. The Relationσ2=σ5
Topologically,σ2=σ5 means that X must be discrete. This is so because Ac-c⊆A⊆A- for any A⊆X.
### 10.4. The Relationσ2=σ7
Topologically, the relationσ2=σ7 implies σ0=σ2. But it requires the use of topology axioms ∅=∅- and C-∪B-=(C∪B)- for each C and B.Lemma 5.
For any topological spaceσ2=σ7 implies σ2=σ8.Proof.
Ifσ2=σ7, then A≠∅⇒Ac-c≠∅, for any A⊆X. Indeed, if Ac-c=∅, then σ7(A)=∅-=∅. Since A≠∅, then σ2(A)≠∅. Hence σ2(A)≠σ7(A), a contradiction.
The axiomC-∪B-=(C∪B)- implies that always
(21)(A-∩A-c-)c-c=∅.
Thus, the additional assumption σ2=σ7 follows that always A-∩A-c-=∅. Therefore, always A-c-=A-c, but this means that any closed set has to be open; in other words, σ2=σ8.Proposition 6.
For any topological spaceσ2=σ7 implies σ0=σ2.Proof.
But the relationσ2=σ7 is equivalent with σ5=σ8. By Lemma 5, we get σ2=σ5. Finally σ0=σ2.The relationσ2=σ7 has interpretation without the axiom ∅=∅-. Indeed, suppose X={a,b}. Put
(22)σ2(∅)={a}=σ2({a}),X=σ2(X)=σ2({b}).
Then, check that σ2=σ7 and
(23)σ8(∅)=σ5({a})=σ4({b})=σ1(X)=∅;
in other words, σ2=σ7 and σ2≠σ8. However, σ2=σ7 is equivalent to σ5=σ8.This relation impliesσ2=σ7=σ10, σ5=σ8=σ13, σ3=σ6=σ11, and σ4=σ9=σ12. For this interpretation, the monoid 𝕄/(σ2=σ7), consisting of Kuratowski operation over a such X, has six elements, only. In 𝕄/(σ2=σ7), there are relations covered by the following proposition, only.Proposition 7.
For any monoid with the Cayley table as for𝕄, the relation σ2=σ7 implies (i)
σ2=σ7=σ10=σ7∘σ2;(ii)
σ5=σ1∘σ2∘σ1=σ1∘σ7∘σ1=σ8=σ5∘σ2=σ5∘σ7=σ13;(iii)
σ3=σ2∘σ1=σ7∘σ1=σ6=σ10∘σ1=σ11;(iv)
σ4=σ1∘σ2=σ1∘σ7=σ9=σ1∘σ10=σ12.Thus, the Cayley table does not contain the complete information resulting from the axioms of topology.
### 10.5. The Relationσ2=σ8
Topologically, the relationσ2=σ8 means that any closed set is open, too. Thus, if X={a,b,c} is a topological space with the open sets X, ∅, {a,b}, and {c}, then 𝕄/(σ2=σ8) is the monoid of all Kuratowski operations over X. Relations σ2=σ8 and σ5=σ7 are equivalent. They imply relations: σ2=σ8=σ10, σ5=σ7=σ13, σ3=σ9=σ11, and σ4=σ6=σ12. The permutation
(24)(σ0σ1σ2σ3σ4σ5σ0σ1σ5σ4σ3σ2)
determines the isomorphism between monoids 𝕄/(σ2=σ7) and 𝕄/(σ2=σ8).
### 10.6. The Relationsσ2=σ10 and σ2=σ13
Topologically, the relationσ2=σ8 means that any nonempty closed set has nonempty interior. For each A, the closed set A-∩A-c- has empty interior, so the relation σ2=σ10 implies that A-c is closed. Hence, any open set has to be closed, so it implies σ2=σ8. The relation σ2=σ13 follows that each closed set has to be open, so it implies σ2=σ8, too.
### 10.7. The Relationσ7=σ8
Using the Cayley table for𝕄, one can check that the relations σ7=σ8 and σ10=σ13 are equivalent. Each of them gives σ7=σ8=σ10=σ13 and σ6=σ9=σ11=σ12. If X={a,b} is a topological space with the open sets X, ∅, and {a}, then 𝕄/(σ7=σ8) is the monoid of all Kuratowski operations over X and consists of 8 elements.
### 10.8. The Relationσ7=σ10
Using the Cayley table for𝕄, one can check that the relations σ7=σ10, σ8=σ13, σ6=σ11, and σ9=σ12 are equivalent. If X is a sequence converging to the point g and g∈X, then 𝕄/(σ7=σ10) is the monoid of all Kuratowski operations over X and consists of 10 elements.
### 10.9. The Relationσ7=σ13
Using the Cayley table for𝕄, one can check that the relations σ7=σ13 and σ8=σ10 are equivalent. Also σ6=σ12 and σ9=σ11. These relations give the monoid with the following Cayley table, where the row and column marked by the identity are omitted:
(25)σ1σ2σ3σ4σ5σ6σ7σ8σ9σ1σ0σ4σ5σ2σ3σ8σ9σ6σ7σ2σ3σ2σ3σ6σ7σ6σ7σ8σ9σ3σ2σ6σ7σ2σ3σ8σ9σ6σ7σ4σ5σ4σ5σ8σ9σ8σ9σ6σ7σ5σ4σ8σ9σ4σ5σ6σ7σ8σ9σ6σ7σ6σ7σ8σ9σ8σ9σ6σ7σ7σ6σ8σ9σ6σ7σ6σ7σ8σ9σ8σ9σ8σ9σ6σ7σ6σ7σ8σ9σ9σ8σ6σ7σ8σ9σ8σ9σ6σ7If a spaceX is extremally disconnected, then the closures of open sets are open; compare [2, page 452]. It follows that σ6=σ12. The space X={a,b} with the open sets X, ∅, and {a} is extremally disconnected. But it contains a one-element open and dense set {a}, and it follows that σ7=σ8. Similar is for the space βN; see [2, pages 228 and 453] to find the definition and properties of βN. There are Hausdorff extremally disconnected spaces which are dense in itself. For example, the Stone space of the complete Boolean algebra of all regular closed subsets of the unit interval, compare [12]. For such spaces σ7≠σ8 and σ7=σ13. To see this, suppose a Hausdorff X is extremally disconnected and dense in itself. Let X=U∪V∪W, where sets U,V, and W are closed and open. Consider a set A=Ac-c∪B∪C, such that (i)
Cc-c=∅ and C-=W;(ii)
∅≠B⊆V and B-c-c=∅;(iii)
U=Ac-c-≠Ac-c. Then check that (i)
σ0(A)=A and σ1(A)=X∖(Ac-c∪B∪C);(ii)
σ2(A)=U∪B-∪W and σ3(A)=X∖Ac-c;(iii)
σ4(A)=V∖B- and σ5(A)=Ac-c;(iv)
σ6(A)=σ12(A)=V and σ7(A)=σ13(A)=U;(v)
σ8(A)=σ10(A)=U∪W and σ9(A)=σ11(A)=V∪W. Hence we have that σ7≠σ8. Note that, if W=∅, then σ7(A)=σ8(A). This is the case of subsets of βN.
## 10.1. Some Consequences of the Axiom∅=∅-
So far, we used only the following relations (above named cancellation rules):σ2∘σ2=σ2, σ1∘σ1=σ0, σ2∘σ12=σ6, and σ2∘σ13=σ7. When one assumes X≠∅=∅-, then
(18)X=σ0(X)=σ2(X)=σ5(X)=σ7(X)=σ8(X)=σ10(X)=σ13(X),∅=σ1(X)=σ3(X)=σ4(X)=σ6(X)=σ9(X)=σ11(X)=σ12(X).
Using the substitution A↦Ac, one obtains equivalent relations between operations from the set {σ1,σ3,σ4,σ6,σ9,σ11,σ12}, and conversely. Therefore, cancellation rules are topologically reasonable only between the operations from the monoid as follows:
(19)〈σ0,σ2,σ5〉={σ0,σ2,σ5,σ7,σ8,σ10,σ13}.
Chapman, see [3], considered properties of subsets with respect to such relations. Below, we are going to identify relations that are determined by some topological spaces; compare [10, 11].
## 10.2. The Relationσ0=σ2
If a topological spaceX is discrete, then there exist two Kuratowski operation, only. These are σ0 and σ1. So, the monoid of Kuratowski operations reduced to the group 〈σ1〉.The relationσ0=σ2 is equivalent to any relation σ0=σi, where i∈{5,7,8,10,13}. Any such relation implies that every subset of X has to be closed and open; that is, X has to be discrete. However, one can check these using (only) the facts that σ1 is an involution and σ2 is an idempotent and the cancellation rules, that is, the Cayley table for 𝕄. So, σ0=σ2 follows
(20)σ0=σ2=σ5=σ7=σ8=σ10=σ13.
## 10.3. The Relationσ2=σ5
Topologically,σ2=σ5 means that X must be discrete. This is so because Ac-c⊆A⊆A- for any A⊆X.
## 10.4. The Relationσ2=σ7
Topologically, the relationσ2=σ7 implies σ0=σ2. But it requires the use of topology axioms ∅=∅- and C-∪B-=(C∪B)- for each C and B.Lemma 5.
For any topological spaceσ2=σ7 implies σ2=σ8.Proof.
Ifσ2=σ7, then A≠∅⇒Ac-c≠∅, for any A⊆X. Indeed, if Ac-c=∅, then σ7(A)=∅-=∅. Since A≠∅, then σ2(A)≠∅. Hence σ2(A)≠σ7(A), a contradiction.
The axiomC-∪B-=(C∪B)- implies that always
(21)(A-∩A-c-)c-c=∅.
Thus, the additional assumption σ2=σ7 follows that always A-∩A-c-=∅. Therefore, always A-c-=A-c, but this means that any closed set has to be open; in other words, σ2=σ8.Proposition 6.
For any topological spaceσ2=σ7 implies σ0=σ2.Proof.
But the relationσ2=σ7 is equivalent with σ5=σ8. By Lemma 5, we get σ2=σ5. Finally σ0=σ2.The relationσ2=σ7 has interpretation without the axiom ∅=∅-. Indeed, suppose X={a,b}. Put
(22)σ2(∅)={a}=σ2({a}),X=σ2(X)=σ2({b}).
Then, check that σ2=σ7 and
(23)σ8(∅)=σ5({a})=σ4({b})=σ1(X)=∅;
in other words, σ2=σ7 and σ2≠σ8. However, σ2=σ7 is equivalent to σ5=σ8.This relation impliesσ2=σ7=σ10, σ5=σ8=σ13, σ3=σ6=σ11, and σ4=σ9=σ12. For this interpretation, the monoid 𝕄/(σ2=σ7), consisting of Kuratowski operation over a such X, has six elements, only. In 𝕄/(σ2=σ7), there are relations covered by the following proposition, only.Proposition 7.
For any monoid with the Cayley table as for𝕄, the relation σ2=σ7 implies (i)
σ2=σ7=σ10=σ7∘σ2;(ii)
σ5=σ1∘σ2∘σ1=σ1∘σ7∘σ1=σ8=σ5∘σ2=σ5∘σ7=σ13;(iii)
σ3=σ2∘σ1=σ7∘σ1=σ6=σ10∘σ1=σ11;(iv)
σ4=σ1∘σ2=σ1∘σ7=σ9=σ1∘σ10=σ12.Thus, the Cayley table does not contain the complete information resulting from the axioms of topology.
## 10.5. The Relationσ2=σ8
Topologically, the relationσ2=σ8 means that any closed set is open, too. Thus, if X={a,b,c} is a topological space with the open sets X, ∅, {a,b}, and {c}, then 𝕄/(σ2=σ8) is the monoid of all Kuratowski operations over X. Relations σ2=σ8 and σ5=σ7 are equivalent. They imply relations: σ2=σ8=σ10, σ5=σ7=σ13, σ3=σ9=σ11, and σ4=σ6=σ12. The permutation
(24)(σ0σ1σ2σ3σ4σ5σ0σ1σ5σ4σ3σ2)
determines the isomorphism between monoids 𝕄/(σ2=σ7) and 𝕄/(σ2=σ8).
## 10.6. The Relationsσ2=σ10 and σ2=σ13
Topologically, the relationσ2=σ8 means that any nonempty closed set has nonempty interior. For each A, the closed set A-∩A-c- has empty interior, so the relation σ2=σ10 implies that A-c is closed. Hence, any open set has to be closed, so it implies σ2=σ8. The relation σ2=σ13 follows that each closed set has to be open, so it implies σ2=σ8, too.
## 10.7. The Relationσ7=σ8
Using the Cayley table for𝕄, one can check that the relations σ7=σ8 and σ10=σ13 are equivalent. Each of them gives σ7=σ8=σ10=σ13 and σ6=σ9=σ11=σ12. If X={a,b} is a topological space with the open sets X, ∅, and {a}, then 𝕄/(σ7=σ8) is the monoid of all Kuratowski operations over X and consists of 8 elements.
## 10.8. The Relationσ7=σ10
Using the Cayley table for𝕄, one can check that the relations σ7=σ10, σ8=σ13, σ6=σ11, and σ9=σ12 are equivalent. If X is a sequence converging to the point g and g∈X, then 𝕄/(σ7=σ10) is the monoid of all Kuratowski operations over X and consists of 10 elements.
## 10.9. The Relationσ7=σ13
Using the Cayley table for𝕄, one can check that the relations σ7=σ13 and σ8=σ10 are equivalent. Also σ6=σ12 and σ9=σ11. These relations give the monoid with the following Cayley table, where the row and column marked by the identity are omitted:
(25)σ1σ2σ3σ4σ5σ6σ7σ8σ9σ1σ0σ4σ5σ2σ3σ8σ9σ6σ7σ2σ3σ2σ3σ6σ7σ6σ7σ8σ9σ3σ2σ6σ7σ2σ3σ8σ9σ6σ7σ4σ5σ4σ5σ8σ9σ8σ9σ6σ7σ5σ4σ8σ9σ4σ5σ6σ7σ8σ9σ6σ7σ6σ7σ8σ9σ8σ9σ6σ7σ7σ6σ8σ9σ6σ7σ6σ7σ8σ9σ8σ9σ8σ9σ6σ7σ6σ7σ8σ9σ9σ8σ6σ7σ8σ9σ8σ9σ6σ7If a spaceX is extremally disconnected, then the closures of open sets are open; compare [2, page 452]. It follows that σ6=σ12. The space X={a,b} with the open sets X, ∅, and {a} is extremally disconnected. But it contains a one-element open and dense set {a}, and it follows that σ7=σ8. Similar is for the space βN; see [2, pages 228 and 453] to find the definition and properties of βN. There are Hausdorff extremally disconnected spaces which are dense in itself. For example, the Stone space of the complete Boolean algebra of all regular closed subsets of the unit interval, compare [12]. For such spaces σ7≠σ8 and σ7=σ13. To see this, suppose a Hausdorff X is extremally disconnected and dense in itself. Let X=U∪V∪W, where sets U,V, and W are closed and open. Consider a set A=Ac-c∪B∪C, such that (i)
Cc-c=∅ and C-=W;(ii)
∅≠B⊆V and B-c-c=∅;(iii)
U=Ac-c-≠Ac-c. Then check that (i)
σ0(A)=A and σ1(A)=X∖(Ac-c∪B∪C);(ii)
σ2(A)=U∪B-∪W and σ3(A)=X∖Ac-c;(iii)
σ4(A)=V∖B- and σ5(A)=Ac-c;(iv)
σ6(A)=σ12(A)=V and σ7(A)=σ13(A)=U;(v)
σ8(A)=σ10(A)=U∪W and σ9(A)=σ11(A)=V∪W. Hence we have that σ7≠σ8. Note that, if W=∅, then σ7(A)=σ8(A). This is the case of subsets of βN.
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*Source: 289854-2013-03-06.xml* | 289854-2013-03-06_289854-2013-03-06.md | 57,606 | The Monoid Consisting of Kuratowski Operations | Szymon Plewik; Marta Walczyńska | Journal of Mathematics
(2013) | Mathematical Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2013/289854 | 289854-2013-03-06.xml | ---
## Abstract
The paper fills gaps in knowledge about Kuratowski
operations which are already in the literature. The Cayley table
for these operations has been drawn up. Techniques, using only
paper and pencil, to point out all semigroups and its isomorphism
types are applied. Some results apply only to topology, and one cannot bring them out, using only properties of the complement and
a closure-like operation. The arguments are by systematic study
of possibilities.
---
## Body
## 1. Introduction
LetX be a topological space. Denote by A- closure of the set A⊆X. Let Ac be the complement of A; that is, X∖A=Ac. The aim of this paper is to examine monoids generated under compositions from the closure and the complement. A widely known fact due to Kuratowski [1] states that at most 14 distinct operations can be formed from such compositions. Mark them as follows. Kuratowski operations:σ0(A)=A (the identity),σ1(A)=Ac (the complement),σ2(A)=A- (the closure),σ3(A)=Ac-,σ4(A)=A-c,σ5(A)=Ac-c(the interior),σ6(A)=A-c-,σ7(A)=Ac-c-,σ8(A)=A-c-c,σ9(A)=Ac-c-c,σ10(A)=A-c-c-,σ11(A)=Ac-c-c-,σ12(A)=A-c-c-c,σ13(A)=Ac-c-c-c.The following rules was found in the original paper by Kuratowski [1, pages 183-184]. In the Engelking book [2], they are commented by a hint on page 81. Cancellation rules:
(1)A-c-=A-c-c-c-,Ac-c-=Ac-c-c-c-.Kuratowski operations have been studied by several authors, for example, [3] or [4]. A list of some other authors one can find in the paper [5] by Gardner and Jackson. For the first time these operations were systematically studied in the dissertation by Kuratowski, whose results were published in [1]. Tasks relating to these operations are usually resolved at lectures or exercises with general topology. They are normally left to students for independent resolution. For example, determine how many different ways they convert a given set.This note is organized as follows. Kuratowski operations and their marking are described in the introduction. Their properties of a much broader context than for topologies are presented in Section2. The Cayley table, for the monoid 𝕄 of all Kuratowski operations, has been drawn up in Section 3. We hope that this table has not yet been published in the literature. Having this table, one can create a computer program that calculates all the semigroups contained in 𝕄. However, in Sections 4–8, we present a framework (i.e., techniques using only paper and pencil) to point out all 118 semigroups and 56 isomorphism types of them. The list of 43 semigroups which are not monoids is presented in Section 9. In this section, also isomorphism types are discussed in order of the number of elements in semigroups. Finally, we present cancellation rules (relations) motivated by some topological spaces.
## 2. Cancellation Rules
A mapf:P(X)→P(X) is called: (i)
increasing, if A⊆B implies f(A)⊆f(B);(ii)
decreasing, if A⊆B implies f(B)⊆f(A);(iii)
an involution, if the composition f∘f is the identity;(iv)
an idempotent, if f∘f=f. Assume that A↦σ0(A) is the identity, A↦σ1(A) is a decreasing involution, and A↦σ2(A) is an increasing idempotent map. Other operations σi let be compositions of σ1 and σ2 as it was with the kuratowski operations. We get the following cancellation rules.Lemma 1.
IfB⊆σ2(B), then
(2)σ2∘σ12=σ6,σ2∘σ13=σ7.Proof.
For clarity of this proof, use designationsσ1(A)=Ac and σ2(A)=A-. Thus, we shall prove
(3)A-c-c-c-=A-c-,Ac-c-c-c-=Ac-c-.
We start with A-c-c⊆A-c-c-, substituting B=A-c-c in B⊆B-. This corresponds to A-c-c-c⊆A-c-cc=A-c-, since σ1 is a decreasing involution. Hence A-c-c-c-⊆A-c-, since σ2 an increasing idempotent.
Sinceσ1 is decreasing, σ2 is increasing, and B⊆B-, we have
(4)B-c⊆Bc⊆Bc-.
Thus A-c-c⊆A-cc-=A-, if we put A-c=B. Again using that σ2 is increasing and σ1 is decreasing, we obtain A-c-c-⊆A- and then A-c⊆A-c-c-c. Finally, we get A-c-⊆A-c-c-c-.
WithAc in the place of A in the rule A-c-=A-c-c-c- we get the second rule.In academic textbooks of general topology, for example, [2, Problem 1.7.1.], one can find a hint suggested to prove the above cancellation rules. Students go like this: steps A⊆A- and Ac⊆Ac- lead to Ac-c⊆A; the special case A-c-c-c⊆A-c- (of Ac-c⊆A) leads to A-c-c-c-⊆A-c-; steps A-c-c⊆A- and A-c-c-⊆A- lead to A-c-⊆A-c-c-c-; at the end, use the last step of the proof of Lemma 1. Note that, the above proofs do not use the axioms of topology as follows: (i)
∅=∅-;(ii)
(A∪B)-=A-∪B-. In the literature there are articles in which Kuratowski operations are replaced by some other mappings. For example, Koenen [6] considered linear spaces and put σ2(A) to be the convex hull of A. In fact, Shum [7] considered σ2 as the closure due to the algebraic operations. Add to this, that these operations can be applied to so-called Fréchet (V) spaces, which were considered in the book [8, pages 3–37].
## 3. The Monoid𝕄
Let𝕄 be the monoid consisting of all Kuratowski operations; that is, there are assumed cancellation rules: σ6=σ2∘σ12 and σ7=σ2∘σ13. Fill in the Cayley table for 𝕄, where the row and column marked by the identity are omitted. Similarly as in [9], the factor that labels the row comes first, and that the factor that labels the column is second. For example, σi∘σk is in the row marked by σi and the column marked by σk(5)σ1σ2σ3σ4σ5σ6σ7σ8σ9σ10σ11σ12σ13σ1σ0σ4σ5σ2σ3σ8σ9σ6σ7σ12σ13σ10σ11σ2σ3σ2σ3σ6σ7σ6σ7σ10σ11σ10σ11σ6σ7σ3σ2σ6σ7σ2σ3σ10σ11σ6σ7σ6σ7σ10σ11σ4σ5σ4σ5σ8σ9σ8σ9σ12σ13σ12σ13σ8σ9σ5σ4σ8σ9σ4σ5σ12σ13σ8σ9σ8σ9σ12σ13σ6σ7σ6σ7σ10σ11σ10σ11σ6σ7σ6σ7σ10σ11σ7σ6σ10σ11σ6σ7σ6σ7σ10σ11σ10σ11σ6σ7σ8σ9σ8σ9σ12σ13σ12σ13σ8σ9σ8σ9σ12σ13σ9σ8σ12σ13σ8σ9σ8σ9σ12σ13σ12σ13σ8σ9σ10σ11σ10σ11σ6σ7σ6σ7σ10σ11σ10σ11σ6σ7σ11σ10σ6σ7σ10σ11σ10σ11σ6σ7σ6σ7σ10σ11σ12σ13σ12σ13σ8σ9σ8σ9σ12σ13σ12σ13σ8σ9σ13σ12σ8σ9σ12σ13σ12σ13σ8σ9σ8σ9σ12σ13It turns out that the above table allows us to describe all semigroups contained in𝕄, using pencil-and-paper techniques, only. The argument will be by a systematic study of possibilities. Preparing the list of all semigroups consisting of Kuratowski operations we used following principles: (i)
minimal collection of generators is written using〈A,B,…,Z〉, where letters denote generators;(ii)
when a semigroup has a few minimal collections of generators, then its name is the first collection in the dictionary order;(iii)
all minimal collections of generators are written with the exception of some containingσ0;(iv)
we leave to the readers verification that our list is complete, sometimes we add hints.
## 4. Semigroups withσ1
Observe that each semigroup which containsσ0 is a monoid. Since σ1∘σ1=σ0, a semigroup which contains σ1 is a monoid, too.Theorem 2.
There are three monoids containingσ1: (1)
〈σ1〉={σ0,σ1};(2)
𝕄=〈σ1,σi〉={σ0,σ1,…,σ13}, where i∈{2,3,4,5};(3)
let𝕄1=〈σ1,σ6〉. If j∈{6,7,…,13}, then
(6)𝕄1=〈σ1,σj〉={σ0,σ1}∪{σ6,σ7,…,σ13}.Proof.
The equality〈σ1〉={σ0,σ1} is obvious.
Sinceσ2=σ3∘σ1=σ1∘σ4=σ1∘σ5∘σ1, we have 〈σ1,σ2〉=〈σ1,σ3〉=〈σ1,σ4〉=〈σ1,σ5〉=𝕄.
Ifj∈{6,7,…,13}, then any composition σj∘σi or σk∘σj belongs to 𝕄1, and so 〈σ1,σj〉⊆𝕄1. We have σ7=σ6∘σ1, σ8=σ1∘σ6, σ9=σ1∘σ7, σ10=σ6∘σ6, σ11=σ6∘σ7, σ12=σ8∘σ6, and σ13=σ8∘σ7, and so 𝕄1=〈σ1,σ6〉={σ0,σ1}∪{σ6,σ7,…,σ13}.
Sinceσ6=σ7∘σ1=σ1∘σ8=σ1∘σ9∘σ1=σ10∘σ1∘σ10=σ11∘σ11∘σ1=σ1∘σ12∘σ12 and σ6=σ1∘σ13∘σ1∘σ13∘σ1, we have 〈σ1,σj〉=𝕄1 for j∈{6,7,…,13}.Consider the permutation(7)(σ0σ1σ2σ3σ4σ5σ6σ7σ8σ9σ10σ11σ12σ13σ0σ1σ5σ4σ3σ2σ9σ8σ7σ6σ13σ12σ11σ10).
It determines an automorphism 𝔸:𝕄→𝕄.Theorem 3.
The identity and𝔸 are the only automorphisms of 𝕄.Proof.
Delete rows and columns marked byσ1 in the Cayley table for 𝕄. Then, check that the operation σ3 is in the row or the column marked by σ3 only. Also, the operation σ4 is in the row or the column marked by σ4 only. Therefore the semigroup
(8)〈σ3,σ4〉={σ2,σ3,…,σ13}
has a unique minimal set of generators {σ3,σ4}. The reader is left to check this with the Cayley table for 𝕄.
Suppose𝔾 is an automorphism of 𝕄. By Theorem 2, 𝔾 transforms the set {σ2,σ3,σ4,σ5} onto itself. However σ2 and σ5 are idempotents, but σ3 and σ4 are not idempotents. So, there are two possibilities: 𝔾(σ3)=σ3 and 𝔾(σ4)=σ4, which implies that 𝔾 is the identity; 𝔾(σ3)=σ4 and 𝔾(σ4)=σ3, which implies 𝔾=𝔸. The reader is left to check this with the Cayley table for 𝕄. We offer hints: σ2=σ3∘σ4, σ5=σ4∘σ3, σ6=σ3∘σ2, σ7=σ3∘σ3, σ8=σ4∘σ4, σ9=σ4∘σ5, σ10=σ6∘σ6, σ11=σ6∘σ7, σ12=σ8∘σ6, and σ13=σ8∘σ7, to verify the details of this proof.
## 5. The Monoid of All Idempotents
The set{σ0,σ2,σ5,σ7,σ8,σ10,σ13} consists of all squares in 𝕄. These squares are idempotents and lie on the main diagonal in the Cayley table for 𝕄. They constitute a monoid and
(9){σ0,σ2,σ5,σ7,σ8,σ10,σ13}=〈σ0,σ2,σ5〉.
The permutation
(10)(σ0σ2σ5σ7σ8σ10σ13σ0σ2σ5σ8σ7σ10σ13)
determines the bijection 𝕀:〈σ0,σ2,σ5〉→〈σ0,σ2,σ5〉, such that
(11)𝕀(α∘β)=𝕀(β)∘𝕀(α),
for any α,β∈〈σ0,σ2,σ5〉. To verify this, apply equalities σ2∘σ5=σ7, σ5∘σ2=σ8, σ2∘σ5∘σ2=σ10, and σ5∘σ2∘σ5=σ13. Any bijection 𝕀:G→H, having property 𝕀(α∘β)=𝕀(β)∘𝕀(α), transposes Cayley tables for semigroups G and H. Several semigroups contained in 𝕄 have this property. We leave the reader to verify this.We shall classify all semigroups contained in the semigroup〈σ2,σ5〉. Every such semigroup can be extended to a monoid by attaching σ0 to it. This gives a complete classification of all semigroups in 〈σ0,σ2,σ5〉.The semigroup〈σ2,σ5〉 contains six groups with exactly one element.Semigroups〈σ2,σ10〉={σ2,σ10} and 〈σ5,σ13〉={σ5,σ13} are monoids. Both consist of exactly two elements and are not groups, so they are isomorphic.Semigroups〈σ7,σ10〉 and 〈σ8,σ13〉 are isomorphic, in particular 𝔸[〈σ7,σ10〉]=〈σ8,σ13〉. Also, semigroups 〈σ7,σ13〉 and 〈σ8,σ10〉 are isomorphic by 𝔸. Every of these four semigroups has exactly two elements. None of them is a monoid. They form two types of nonisomorphic semigroups, because the bijections {(σ7,σ10),(σ10,σ8)} and {(σ7,σ8),(σ10,σ10)} are not isomorphisms.Semigroups〈σ2,σ7〉={σ2,σ7,σ10} and 〈σ5,σ8〉={σ5,σ8,σ13} are isomorphic. Also, semigroups 〈σ2,σ8〉={σ2,σ8,σ10} and 〈σ5,σ7〉={σ5,σ7,σ13} are isomorphic. In fact, 𝔸[〈σ2,σ7〉]=〈σ5,σ8〉 and 𝔸[〈σ2,σ8〉]=〈σ5,σ7〉. None of these semigroups is a monoid. They form two types of nonisomorphic semigroups. Indeed, any isomorphism between 〈σ2,σ7〉 and 〈σ2,σ8〉 must be the identity on the monoid 〈σ2,σ10〉. Therefore would have to be the restriction of 𝕀. But 𝕀 restricted to 〈σ7,σ10〉 is not an isomorphism.Semigroups〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13} and 〈σ5,σ10〉=〈σ5,σ7,σ8〉={σ5,σ7,σ8,σ10,σ13} are not monoids. They are isomorphic by 𝔸.The semigroup〈σ2,σ5〉 contains exactly one semigroup with four elements 〈σ7,σ8〉=〈σ10,σ13〉={σ7,σ8,σ10,σ13} which is not a monoid.Note that〈σ2,σ5〉 contains twenty different semigroups with nine non-isomorphism types. These are six isomorphic groups with exactly one element 〈σ2〉≅〈σ5〉≅〈σ7〉≅〈σ8〉≅〈σ10〉≅〈σ13〉, two isomorphic monoids with exactly two elements 〈σ2,σ10〉≅〈σ5,σ13〉, two pairs of isomorphic semigroups with exactly two elements 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ7,σ13〉≅〈σ8,σ10〉, two pairs of isomorphic semigroups with exactly three elements 〈σ2,σ7〉≅〈σ5,σ8〉 and 〈σ2,σ8〉≅〈σ5,σ7〉, a semigroup with exactly four elements 〈σ7,σ8〉, and two isomorphic semigroups with exactly five elements 〈σ2,σ13〉≅〈σ5,σ10〉 and also 〈σ2,σ5〉. Thus, 〈σ2,σ5〉 contains twenty different semigroups with nine isomorphism types. But 〈σ0,σ2,σ5〉 contains forty-one different semigroups with seventeen isomorphism types. Indeed, adding σ0 to semigroups contained in 〈σ2,σ5〉, which are not monoids, we get twenty monoids with eight non-isomorphism types. Adding σ0 to a group contained in 〈σ2,σ5〉 we get a monoid isomorphic to 〈σ2,σ10〉.
## 6. The Semigroup Consisting of{σ6,σ7,…,σ13}
Using the Cayley table for𝕄, check that
(12)𝔸[{σ6,σ7,…,σ13}]={σ6,σ7,…,σ13}.
Similarly, check that the semigroup 〈σ6,σ9〉={σ6,σ7,…,σ13} can be represented as 〈σ6,σ13〉, 〈σ7,σ12〉, 〈σ8,σ11〉, 〈σ9,σ10〉, or 〈σ11,σ12〉. Also 〈σ6,σ9〉=〈σ6,σ7,σ8〉=〈σ7,σ8,σ9〉=〈σ10,σ11,σ13〉=〈σ10,σ12,σ13〉. These representations exhaust all minimal collections of the Kuratowski operations which generate 〈σ6,σ9〉. Other semigroups included in 〈σ6,σ9〉 have one or two minimal collection of generators. One generator has groups 〈σ6〉={σ6,σ10}, 〈σ9〉={σ9,σ13}, 〈σ11〉={σ7,σ11}, and 〈σ12〉={σ8,σ12}. Each of them has exactly two elements, so they are isomorphic. Semigroups 〈σ7,σ10〉, 〈σ7,σ13〉, 〈σ8,σ10〉, 〈σ8,σ13〉, and 〈σ7,σ8〉 are discussed in the previous section. Contained in 〈σ6,σ9〉 and not previously discussed semigroups are 〈σ6,σ7〉, 〈σ6,σ8〉,〈σ7,σ9〉, and 〈σ8,σ9〉. We leave the reader to verify that the following are all possible pairs of Kuratowski operations which constitute a minimal collection of generators for semigroups contained in 〈σ6,σ9〉, but different from the whole. One has (i)
〈σ6,σ7〉=〈σ6,σ11〉=〈σ10,σ11〉={σ6,σ7,σ10,σ11};(ii)
〈σ6,σ8〉=〈σ6,σ12〉=〈σ10,σ12〉={σ6,σ8,σ10,σ12};(iii)
〈σ7,σ9〉=〈σ9,σ11〉=〈σ11,σ13〉={σ7,σ9,σ11,σ13};(iv)
〈σ8,σ9〉=〈σ9,σ12〉=〈σ12,σ13〉={σ8,σ9,σ12,σ13}.Proposition 4.
Semigroups〈σ6,σ7〉 and 〈σ8,σ9〉 are isomorphic, and also semigroups 〈σ6,σ8〉 and 〈σ7,σ9〉 are isomorphic, but semigroups 〈σ6,σ7〉, 〈σ6,σ8〉 are not isomorphic.Proof.
Isomorphisms are defined by𝔸. Suppose J:〈σ6,σ7〉→〈σ6,σ8〉 is an isomorphism. Thus J[〈σ7,σ10〉]=〈σ8,σ10〉. Given J(σ7)=σ8, we get σ10=J(σ10)=J(σ7∘σ10)≠σ8∘σ10=σ8. But J(σ7)=σ10 implies σ10=J(σ7)=J(σ10∘σ7)≠σ8∘σ10=σ8. Both possibilities lead to a contradiction.So,〈σ6,σ9〉 contains eighteen different semigroups with eight non-isomorphism types. Indeed, these are four isomorphic groups with exactly one element 〈σ7〉≅〈σ8〉≅〈σ10〉≅〈σ13〉, four isomorphic groups with exactly two elements 〈σ6〉≅〈σ9〉≅〈σ11〉≅〈σ12〉, two pairs of isomorphic semigroups with exactly two elements 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ7,σ13〉≅〈σ8,σ10〉, and five semigroups with exactly four elements 〈σ6,σ7〉≅〈σ8,σ9〉, 〈σ6,σ8〉≅〈σ7,σ9〉, 〈σ7,σ8〉, and also 〈σ6,σ9〉.
## 7. Remaining Semigroups in〈σ3,σ4〉
We have yet to discuss semigroups included in〈σ3,σ4〉, not included in 〈σ2,σ5〉 and containing at least one of Kuratowski operation σ2, σ3, σ4, or σ5. It will be discussed up to the isomorphism 𝔸. Obviously, 〈σ2〉={σ2} and 〈σ5〉={σ5} are groups.
### 7.1. Extensions of〈σ2〉 and 〈σ5〉 with Elements of 〈σ6,σ9〉
Monoids〈σ2,σ6〉={σ2,σ6,σ10} and 〈σ2,σ10〉={σ2,σ10} have different numbers of elements. Also, 〈σ2,σ6〉 is isomorphic to 〈σ0,σ6〉. Nonisomorphic semigroups 〈σ2,σ7〉 and 〈σ2,σ8〉 are discussed above. The following three semigroups: (i)
〈σ2,σ11〉=〈σ2,σ6,σ7〉={σ2,σ6,σ7,σ10,σ11},(ii)
〈σ2,σ12〉=〈σ2,σ6,σ8〉={σ2,σ6,σ8,σ10,σ12},(iii)
〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13} are not monoids. They are not isomorphic. Indeed, any isomorphism between these semigroups would lead an isomorphism between 〈σ6,σ7〉, 〈σ6,σ8〉, or 〈σ7,σ8〉. This is impossible, by Proposition 4 and because 〈σ7,σ8〉 consists of idempotents, but σ6 is not an idempotent. The nine-element semigroup on the set {σ2,σ6,σ7,…,σ13} is represented as 〈σ2,σ9〉. So, we have added four new semigroups, which are not isomorphic with the semigroups previously discussed. These are 〈σ2,σ11〉, 〈σ2,σ12〉, 〈σ2,σ13〉, and 〈σ2,σ9〉.Using𝔸, we have described eight semigroups—each one isomorphic to a semigroup previously discussed—which contains σ5 and elements (at least one) of 〈σ6,σ9〉. Collections of generators: 〈σ2,σ6,σ13〉, 〈σ2,σ7,σ12〉, 〈σ2,σ8,σ11〉, 〈σ2,σ11,σ12〉, 〈σ2,σ11,σ13〉, and 〈σ2,σ12,σ13〉 are minimal in 〈σ2,σ9〉. Also, collections of generators: 〈σ5,σ7,σ12〉, 〈σ5,σ8,σ11〉, 〈σ5,σ9,σ10〉, 〈σ5,σ10,σ11〉, 〈σ5,σ10,σ12〉, and 〈σ5,σ11,σ12〉 are minimal in 〈σ5,σ6〉.
### 7.2. Extensions of〈σ3〉 and 〈σ4〉 by Elements from the Semigroup 〈σ6,σ9〉
Semigroups〈σ3〉={σ3,σ7,σ11} and 〈σ4〉={σ4,σ8,σ12} are isomorphic by 𝔸. They are not monoids. The semigroup 〈σ3〉 can be extended using elements of 〈σ6,σ9〉, in three following ways:(i)
〈σ3,σ6〉=〈σ3,σ10〉={σ3,σ6,σ7,σ10,σ11};(ii)
〈σ3,σ8〉=〈σ3,σ12〉={σ3,σ6,σ7,…,σ13};(iii)
〈σ3,σ9〉=〈σ3,σ13〉={σ3,σ7,σ9,σ11,σ13}.Semigroups 〈σ3,σ6〉 and 〈σ3,σ9〉 are not isomorphic. Indeed, suppose J:〈σ3,σ6〉→〈σ3,σ9〉 is an isomorphism. Thus, J is the identity on 〈σ3〉, J(σ6)=σ9, and J(σ10)=σ13. This gives a contradiction, since σ3∘σ6=σ10 and σ3∘σ9=σ7.Neither〈σ3,σ6〉 nor 〈σ3,σ9〉 has a minimal collection of generators with three elements, so they give new isomorphism types. Also, 〈σ2,σ9〉 is not isomorphic to 〈σ3,σ8〉, since 〈σ2,σ9〉 has a unique pair of generators and 〈σ3,σ8〉=〈σ3,σ12〉.Using𝔸, we get—isomorphic to previously discussed ones—semigroups 〈σ4,σ9〉=〈σ4,σ13〉={σ4,σ8,σ9σ12,σ13}, 〈σ4,σ6〉=〈σ4,σ10〉={σ4,σ6,σ8σ10,σ12}, and 〈σ4,σ7〉=〈σ4,σ11〉={σ4,σ6,σ7,…,σ13}. There exist minimal collections of generators, such as follows:
(13)〈σ3,σ8〉=〈σ3,σ6,σ9〉=〈σ3,σ6,σ13〉=〈σ3,σ9,σ10〉=〈σ3,σ10,σ13〉,〈σ4,σ7〉=〈σ4,σ6,σ9〉=〈σ4,σ9,σ10〉=〈σ4,σ6,σ13〉=〈σ4,σ10,σ13〉.
### 7.3. More Generators from the Set{σ2,σ3,σ4,σ5}
Now we check that〈σ2,σ3〉={σ2,σ3,σ6,σ7,σ10σ11} and 〈σ4,σ5〉={σ4,σ5,σ8,σ9,σ12σ13}=𝔸[〈σ2,σ3〉] and also 〈σ2,σ4〉={σ2,σ4,σ6,σ8,σ10σ12} and 〈σ3,σ5〉={σ3,σ5,σ7,σ9,σ11σ13}=𝔸[〈σ2,σ4〉] are two pairs of isomorphic semigroups which give two new isomorphism types. Each of these semigroups has six element, so in 𝕄 there are five six-element semigroups of three isomorphism types, since 〈σ2,σ5〉 has 6 elements which are idempotents.In〈σ3,σ4〉 there are seven semigroups which have three generators and have not two generators. These are (1)
〈σ2,σ3,σ8〉=〈σ2,σ3,σ9〉=〈σ2,σ3,σ12〉=〈σ2,σ3,σ13〉;(2)
〈σ4,σ5,σ6〉=〈σ4,σ5,σ7〉=〈σ4,σ5,σ10〉=〈σ4,σ5,σ11〉;(3)
〈σ2,σ4,σ7〉=〈σ2,σ4,σ9〉=〈σ2,σ4,σ11〉=〈σ2,σ4,σ13〉;(4)
〈σ3,σ5,σ6〉=〈σ3,σ5,σ8〉=〈σ3,σ5,σ10〉=〈σ3,σ5,σ12〉;(5)
〈σ2,σ5,σ6〉=〈σ2,σ5,σ9〉=〈σ2,σ5,σ11〉=〈σ2,σ5,σ12〉;(6)
〈σ2,σ3,σ5〉;(7)
〈σ2,σ4,σ5〉.
## 7.1. Extensions of〈σ2〉 and 〈σ5〉 with Elements of 〈σ6,σ9〉
Monoids〈σ2,σ6〉={σ2,σ6,σ10} and 〈σ2,σ10〉={σ2,σ10} have different numbers of elements. Also, 〈σ2,σ6〉 is isomorphic to 〈σ0,σ6〉. Nonisomorphic semigroups 〈σ2,σ7〉 and 〈σ2,σ8〉 are discussed above. The following three semigroups: (i)
〈σ2,σ11〉=〈σ2,σ6,σ7〉={σ2,σ6,σ7,σ10,σ11},(ii)
〈σ2,σ12〉=〈σ2,σ6,σ8〉={σ2,σ6,σ8,σ10,σ12},(iii)
〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13} are not monoids. They are not isomorphic. Indeed, any isomorphism between these semigroups would lead an isomorphism between 〈σ6,σ7〉, 〈σ6,σ8〉, or 〈σ7,σ8〉. This is impossible, by Proposition 4 and because 〈σ7,σ8〉 consists of idempotents, but σ6 is not an idempotent. The nine-element semigroup on the set {σ2,σ6,σ7,…,σ13} is represented as 〈σ2,σ9〉. So, we have added four new semigroups, which are not isomorphic with the semigroups previously discussed. These are 〈σ2,σ11〉, 〈σ2,σ12〉, 〈σ2,σ13〉, and 〈σ2,σ9〉.Using𝔸, we have described eight semigroups—each one isomorphic to a semigroup previously discussed—which contains σ5 and elements (at least one) of 〈σ6,σ9〉. Collections of generators: 〈σ2,σ6,σ13〉, 〈σ2,σ7,σ12〉, 〈σ2,σ8,σ11〉, 〈σ2,σ11,σ12〉, 〈σ2,σ11,σ13〉, and 〈σ2,σ12,σ13〉 are minimal in 〈σ2,σ9〉. Also, collections of generators: 〈σ5,σ7,σ12〉, 〈σ5,σ8,σ11〉, 〈σ5,σ9,σ10〉, 〈σ5,σ10,σ11〉, 〈σ5,σ10,σ12〉, and 〈σ5,σ11,σ12〉 are minimal in 〈σ5,σ6〉.
## 7.2. Extensions of〈σ3〉 and 〈σ4〉 by Elements from the Semigroup 〈σ6,σ9〉
Semigroups〈σ3〉={σ3,σ7,σ11} and 〈σ4〉={σ4,σ8,σ12} are isomorphic by 𝔸. They are not monoids. The semigroup 〈σ3〉 can be extended using elements of 〈σ6,σ9〉, in three following ways:(i)
〈σ3,σ6〉=〈σ3,σ10〉={σ3,σ6,σ7,σ10,σ11};(ii)
〈σ3,σ8〉=〈σ3,σ12〉={σ3,σ6,σ7,…,σ13};(iii)
〈σ3,σ9〉=〈σ3,σ13〉={σ3,σ7,σ9,σ11,σ13}.Semigroups 〈σ3,σ6〉 and 〈σ3,σ9〉 are not isomorphic. Indeed, suppose J:〈σ3,σ6〉→〈σ3,σ9〉 is an isomorphism. Thus, J is the identity on 〈σ3〉, J(σ6)=σ9, and J(σ10)=σ13. This gives a contradiction, since σ3∘σ6=σ10 and σ3∘σ9=σ7.Neither〈σ3,σ6〉 nor 〈σ3,σ9〉 has a minimal collection of generators with three elements, so they give new isomorphism types. Also, 〈σ2,σ9〉 is not isomorphic to 〈σ3,σ8〉, since 〈σ2,σ9〉 has a unique pair of generators and 〈σ3,σ8〉=〈σ3,σ12〉.Using𝔸, we get—isomorphic to previously discussed ones—semigroups 〈σ4,σ9〉=〈σ4,σ13〉={σ4,σ8,σ9σ12,σ13}, 〈σ4,σ6〉=〈σ4,σ10〉={σ4,σ6,σ8σ10,σ12}, and 〈σ4,σ7〉=〈σ4,σ11〉={σ4,σ6,σ7,…,σ13}. There exist minimal collections of generators, such as follows:
(13)〈σ3,σ8〉=〈σ3,σ6,σ9〉=〈σ3,σ6,σ13〉=〈σ3,σ9,σ10〉=〈σ3,σ10,σ13〉,〈σ4,σ7〉=〈σ4,σ6,σ9〉=〈σ4,σ9,σ10〉=〈σ4,σ6,σ13〉=〈σ4,σ10,σ13〉.
## 7.3. More Generators from the Set{σ2,σ3,σ4,σ5}
Now we check that〈σ2,σ3〉={σ2,σ3,σ6,σ7,σ10σ11} and 〈σ4,σ5〉={σ4,σ5,σ8,σ9,σ12σ13}=𝔸[〈σ2,σ3〉] and also 〈σ2,σ4〉={σ2,σ4,σ6,σ8,σ10σ12} and 〈σ3,σ5〉={σ3,σ5,σ7,σ9,σ11σ13}=𝔸[〈σ2,σ4〉] are two pairs of isomorphic semigroups which give two new isomorphism types. Each of these semigroups has six element, so in 𝕄 there are five six-element semigroups of three isomorphism types, since 〈σ2,σ5〉 has 6 elements which are idempotents.In〈σ3,σ4〉 there are seven semigroups which have three generators and have not two generators. These are (1)
〈σ2,σ3,σ8〉=〈σ2,σ3,σ9〉=〈σ2,σ3,σ12〉=〈σ2,σ3,σ13〉;(2)
〈σ4,σ5,σ6〉=〈σ4,σ5,σ7〉=〈σ4,σ5,σ10〉=〈σ4,σ5,σ11〉;(3)
〈σ2,σ4,σ7〉=〈σ2,σ4,σ9〉=〈σ2,σ4,σ11〉=〈σ2,σ4,σ13〉;(4)
〈σ3,σ5,σ6〉=〈σ3,σ5,σ8〉=〈σ3,σ5,σ10〉=〈σ3,σ5,σ12〉;(5)
〈σ2,σ5,σ6〉=〈σ2,σ5,σ9〉=〈σ2,σ5,σ11〉=〈σ2,σ5,σ12〉;(6)
〈σ2,σ3,σ5〉;(7)
〈σ2,σ4,σ5〉.
## 8. Semigroups which Are Contained in〈σ3,σ4〉
Groups〈σ2〉≅〈σ5〉≅〈σ7〉≅〈σ8〉≅〈σ10〉≅〈σ13〉 have one element and are isomorphic.Groups〈σ6〉≅〈σ9〉≅〈σ11〉≅〈σ12〉, monoids 〈σ2,σ10〉≅〈σ5,σ13〉, and also semigroups 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ7,σ13〉≅〈σ8,σ10〉 have two elements and Cayley tables as follows:
(14)ABABABABABAABBBAABAABBABABAAABBBMonoids〈σ2,σ6〉≅〈σ5,σ9〉, and also semigroups 〈σ2,σ7〉≅〈σ5,σ8〉, 〈σ2,σ8〉≅〈σ5,σ7〉, and 〈σ3〉≅〈σ4〉 have three elements and Cayley tables as follows:
(15)ABCAABCBBCBCCBCABCAABCBCBCCCBCABCAACCBBBBCCCCABCABCBBCBCCBCBSemigroups〈σ6,σ7〉≅〈σ8,σ9〉, 〈σ6,σ8〉≅〈σ7,σ9〉, and 〈σ7,σ8〉 have four elements and Cayley tables as follows:
(16)ABCDACDABBABCDCABCDDCDABABCDACAACBDBBDCACCADBDDBABCDAACCABDBBDCACCADDBBDSemigroups〈σ2,σ11〉≅〈σ5,σ12〉, 〈σ2,σ12〉≅〈σ5,σ11〉, 〈σ2,σ13〉≅〈σ5,σ10〉, 〈σ3,σ6〉≅〈σ4,σ9〉, and 〈σ3,σ9〉≅〈σ4,σ6〉 have five elements. Semigroups 〈σ2,σ3〉≅〈σ4,σ5〉, 〈σ2,σ4〉≅〈σ3,σ5〉, and 〈σ2,σ5〉 have six elements. Construction of Cayley tables for these semigroups, as well as other semigroups, we leave it to the readers. One can prepare such tables removing from the Cayley table for 𝕄 some columns and rows. Then change Kuratowski operations onto letters of the alphabet. For example, 〈σ0,σ2,σ5〉 has the following Cayley table:
(17)0ABCDEF00ABCDEFAAACCEECBBDBFDDFCCECCEECDDDFFDDFEEECCEECFFDFFDDF
Preparing the Cayley table for 〈σ0,σ2,σ5〉 we put σ0=0,σ2=A,σ5=B,σ7=C,σ8=D,σ10=E, and σ13=F. This table immediately shows that semigroups 〈σ2,σ5〉 and 〈σ0,σ2,σ5〉 have exactly two automorphisms. These are identities and restrictions of 𝔸.Semigroup〈σ6,σ9〉 has eight elements. Semigroups 〈σ2,σ9〉≅〈σ5,σ6〉 and 〈σ3,σ8〉≅〈σ4,σ7〉 have nine elements. Semigroups 〈σ2,σ3,σ8〉≅〈σ4,σ5,σ7〉, 〈σ2,σ4,σ7〉≅〈σ3,σ5,σ8〉, and 〈σ2,σ5,σ6〉 have ten elements. Semigroups 〈σ2,σ3,σ5〉≅〈σ2,σ4,σ5〉 have eleven elements. In the end, the semigroup 〈σ3,σ4〉 has twelve elements.Thus, the semigroup〈σ3,σ4〉 includes fifty-seven semigroups, among which there are ten groups, fourteen monoids, and also forty-three semigroups which are not monoids. These semigroups consist of twenty-eight types of nonisomorphic semigroups, two non-isomorphism types of groups, two non-isomorphism types of monoids which are not groups, and twenty four non-isomorphism types of semigroups which are not monoids.
## 9. Viewing Semigroups Contained in𝕄
### 9.1. Descriptive Data on Semigroups which Are Contained in𝕄
There are one hundred eighteen, that is,118=2·57+4, semigroups which are contained in 𝕄. These are fifty-seven semigroups contained in 〈σ3,σ4〉, fifty-seven monoids formed by adding σ0 to a semigroup contained in 〈σ3,σ4〉, groups 〈σ0〉, 〈σ1〉, and monoids 〈σ1,σ6〉=𝕄1 and 〈σ1,σ2〉=𝕄.There are fifty-six types of nonisomorphic semigroups in𝕄. These are twenty-eight non-isomorphism types of semigroups contained in 〈σ3,σ4〉, twenty-six types of nonisomorphic monoids formed by adding σ0 to a semigroup contained in 〈σ3,σ4〉, and also 𝕄1 and 𝕄. Indeed, adding σ0 to a semigroup which is not a monoid we obtain a monoid. In this way, we get twenty-four types of nonisomorphic monoids. Adding σ0 to a monoid contained in 〈σ3,σ4〉 we get two new non-isomorphism types of monoids. But, adding σ0 to a group contained in 〈σ3,σ4〉 we get no new type of monoid, since we get a monoid isomorphic to 〈σ2,σ10〉 or 〈σ2,σ6〉. The other two types are 𝕄1 and 𝕄.
### 9.2. Semigroups which Are Not Monoids
Below we have reproduced, using the smallest number of generators and the dictionary order, a list of all 43 semigroups, which are included in the𝕄 as follows:(1)
〈σ2,σ3〉={σ2,σ3,σ6,σ7,σ10,σ11}.(2)
〈σ2,σ3,σ5〉={σ2,σ3,σ5,σ6,…,σ13}.(3)
〈σ2,σ3,σ8〉=〈σ2,σ3,σ9〉=〈σ2,σ3,σ12〉=〈σ2,σ3,σ13〉={σ2,σ3,σ6,σ7,…,σ13}.(4)
〈σ2,σ4〉={σ2,σ4,σ6,σ8,σ10,σ12}.(5)
〈σ2,σ4,σ5〉={σ2,σ4,σ5,…,σ13}.(6)
〈σ2,σ4,σ7〉=〈σ2,σ4,σ9〉=〈σ2,σ4,σ11〉=〈σ2,σ4,σ13〉={σ2,σ4,σ6,σ7…,σ13}.(7)
〈σ2,σ5〉={σ2,σ5,σ7,σ8,σ10,σ13}.(8)
〈σ2,σ5,σ6〉=〈σ2,σ5,σ9〉=〈σ2,σ5,σ11〉=〈σ2,σ5,σ12〉={σ2,σ5,σ6,…,σ13}.(9)
〈σ2,σ7〉={σ2,σ7,σ10}.(10)
〈σ2,σ8〉={σ2,σ8,σ10}.(11)
〈σ2,σ9〉=〈σ2,σ6,σ13〉=〈σ2,σ7,σ12〉=〈σ2,σ8,σ11〉=〈σ2,σ11,σ12〉=〈σ2,σ11,σ13〉 = 〈σ2,σ12,σ13〉={σ2,σ6,σ7,…,σ13}.(12)
〈σ2,σ11〉=〈σ2,σ6,σ7〉={σ2,σ6,σ7,σ10,σ11}.(13)
〈σ2,σ12〉=〈σ2,σ6,σ8〉={σ2,σ6,σ8,σ10,σ12}.(14)
〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13}.(15)
〈σ3〉={σ3,σ7,σ11}.(16)
〈σ3,σ4〉={σ2,σ3,…,σ13}.(17)
〈σ3,σ5〉={σ3,σ5,σ7,σ9,σ11,σ13}.(18)
〈σ3,σ5,σ6〉=〈σ3,σ5,σ8〉=〈σ3,σ5,σ10〉=〈σ3,σ5,σ12〉={σ3,σ5,σ6,…,σ13}.(19)
〈σ3,σ6〉=〈σ3,σ10〉={σ3,σ6,σ7,σ10,σ11}.(20)
〈σ3,σ8〉=〈σ3,σ12〉={σ3,σ6,σ7,…,σ13}.(21)
〈σ3,σ9〉=〈σ3,σ13〉={σ3,σ7,σ9,σ11,σ13}.(22)
〈σ4〉={σ4,σ8,σ12}.(23)
〈σ4,σ5〉={σ4,σ5,σ8,σ9,σ12,σ13}.(24)
〈σ4,σ5,σ6〉=〈σ4,σ5,σ7〉=〈σ4,σ5,σ10〉=〈σ4,σ5,σ11〉={σ4,σ5,…,σ13}.(25)
〈σ4,σ6〉=〈σ4,σ10〉={σ4,σ6,σ8,σ10,σ12}.(26)
〈σ4,σ7〉=〈σ4,σ11〉={σ4,σ6,σ7,…,σ13}.(27)
〈σ4,σ9〉=〈σ4,σ13〉={σ4,σ8,σ9,σ12,σ13}.(28)
〈σ5,σ6〉=〈σ5,σ7,σ12〉=〈σ5,σ8,σ11〉=〈σ5,σ9,σ10〉=〈σ5,σ10,σ11〉=〈σ5,σ10,σ12〉 = 〈σ5,σ11,σ12〉={σ5,σ6,…,σ13}.(29)
〈σ5,σ7〉={σ5,σ7,σ13}.(30)
〈σ5,σ8〉={σ5,σ8,σ13}.(31)
〈σ5,σ10〉=〈σ5,σ7,σ8〉={σ5,σ7,σ8,σ10,σ13}.(32)
〈σ5,σ11〉=〈σ5,σ7,σ9〉={σ5,σ7,σ9,σ11,σ13}.(33)
〈σ5,σ12〉=〈σ5,σ8,σ9〉={σ5,σ8,σ9,σ12,σ13}.(34)
〈σ6,σ7〉=〈σ6,σ11〉=〈σ10,σ11〉={σ6,σ7,σ10,σ11}.(35)
〈σ6,σ8〉=〈σ6,σ12〉=〈σ10,σ12〉={σ6,σ8,σ10,σ12}.(36)
〈σ6,σ9〉=〈σ6,σ13〉=〈σ7,σ12〉=〈σ8,σ11〉=〈σ9,σ10〉=〈σ11,σ12〉 = 〈σ6,σ7,σ8〉=〈σ7,σ8,σ9〉 = 〈σ10,σ11,σ13〉=〈σ10,σ12,σ13〉={σ6,σ7,…,σ13}.(37)
〈σ7,σ8〉={σ7,σ8,σ10,σ13}.(38)
〈σ7,σ9〉={σ7,σ9,σ11,σ13}.(39)
〈σ7,σ10〉={σ7,σ10}.(40)
〈σ7,σ13〉={σ7,σ13}.(41)
〈σ8,σ9〉={σ8,σ9,σ12,σ13}.(42)
〈σ8,σ10〉={σ8,σ10}.(43)
〈σ8,σ13〉={σ8,σ13}.
### 9.3. Isomorphism Types of Semigroups Contained in𝕄
Systematize the list of all isomorphism types of semigroups contained in the monoid𝕄. Isomorphisms, which are restrictions of the isomorphism 𝔸, will be regarded as self-evident, and therefore they will not be commented on.(i)
The monoid𝕄 contains 12 groups with 2 isomorphism types. These are 7 one-element groups and 5 two-element groups.(ii)
The monoid𝕄 contains 8 two-element monoids with 2 isomorphism types. These are σ0 added to 6 one-element groups and 〈σ2,σ10〉≅〈σ5,σ13〉. Also, it contains 4 two-element semigroups, not monoids, with 2 isomorphism types. These are 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ8,σ10〉≅〈σ7,σ13〉.(iii)
The monoid𝕄 contains 12 three-element monoids with 5 isomorphism types. These are σ0 added to 4 two-element groups and also 〈σ0,σ2,σ10〉≅〈σ0,σ5,σ13〉, 〈σ0,σ7,σ10〉≅〈σ0,σ8,σ13〉, 〈σ0,σ8,σ10〉≅〈σ0,σ7,σ13〉, and 〈σ2,σ6〉≅〈σ5,σ9〉.(iv)
The monoid𝕄 contains 6 three-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ2,σ7〉≅〈σ5,σ8〉, 〈σ2,σ8〉≅〈σ5,σ7〉, and 〈σ3〉≅〈σ4〉.(v)
The monoid𝕄 contains 8 four-element monoids, each contains σ0, with 4 isomorphism types. These are semigroups from two preceding items that can be substantially extended by σ0.(vi)
The monoid𝕄 contains 5 four-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ6,σ7〉≅〈σ8,σ9〉, 〈σ6,σ8〉≅〈σ7,σ9〉 and 〈σ7,σ8〉. These semigroups extended by σ0 yield 5 monoids, all which consist of five elements, with 3 isomorphism types.(vii)
The monoid𝕄 contains 10 five-element semigroups—not monoids, with 5 isomorphism types. These are 〈σ2,σ11〉≅〈σ5,σ12〉, 〈σ2,σ12〉≅〈σ5,σ11〉, 〈σ2,σ13〉≅〈σ5,σ10〉, 〈σ3,σ6〉≅〈σ4,σ9〉, and 〈σ3,σ9〉≅〈σ4,σ6〉. These semigroups extended by σ0 yield 10 monoids, all of which consist of six elements, with 5 isomorphism types. We get 10 new isomorphism types, since the semigroups are distinguished by semigroups 〈σ3〉 and 〈σ4〉, and by nonisomorphic semigroups 〈σ6,σ7〉, 〈σ6,σ8〉, and 〈σ7,σ8〉.(viii)
The monoid𝕄 contains 5 six-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ2,σ3〉≅〈σ4,σ5〉, 〈σ2,σ4〉≅〈σ3,σ5〉, and 〈σ2,σ5〉. These semigroups extended by σ0 yield 5 monoids, all of which consist of seven elements, with 3 isomorphism types. We get 6 new isomorphism types, since the semigroups are distinguished by non isomorphic semigroups 〈σ6,σ7〉, 〈σ6,σ8〉, and 〈σ7,σ8〉.(ix)
The monoid𝕄 contains no seven-element semigroup, not a monoid, no eight-element monoid and the only semigroup 〈σ6,σ9〉 with exactly eight elements and the only monoid 〈σ0,σ6,σ9〉 with exactly nine elements.(x)
The monoid𝕄 contains 4 nine-element semigroups, not monoids, with 2 isomorphism types. These are 〈σ2,σ9〉≅〈σ5,σ6〉 and 〈σ3,σ8〉≅〈σ4,σ7〉. The semigroup 〈σ2,σ9〉 does not contain a semigroup isomorphic to 〈σ3〉, hence it is not isomorphic to 〈σ3,σ8〉. These semigroups extended by σ0 yield 4 monoids, all of which consist of ten elements, with 2 isomorphism types.(xi)
The monoid𝕄 contains 6 ten-element semigroups, not monoids, with 4 isomorphism types. These are 〈σ1,σ6〉, 〈σ2,σ3,σ8〉≅〈σ4,σ5,σ6〉, 〈σ2,σ4,σ7〉≅〈σ3,σ5,σ6〉, and 〈σ2,σ5,σ6〉. These semigroups (except 〈σ1,σ6〉) extended by σ0 yield 5 monoids, all of which consist of ten elements, with 3 isomorphism types. We get 6 new isomorphism types, since the semigroups are distinguished by not isomorphic semigroups 〈σ2,σ3〉, 〈σ2,σ4〉, and 〈σ2,σ5〉.(xii)
The monoid𝕄 contains 2 isomorphic semigroups, not monoids, which consist of 11 elements, that is, 〈σ2,σ3,σ5〉≅〈σ2,σ4,σ5〉. These semigroups extended by σ0 yield 2 isomorphic monoids, which consist of 12 elements. The monoid 𝕄 contains no larger semigroup with the exception of itself.
## 9.1. Descriptive Data on Semigroups which Are Contained in𝕄
There are one hundred eighteen, that is,118=2·57+4, semigroups which are contained in 𝕄. These are fifty-seven semigroups contained in 〈σ3,σ4〉, fifty-seven monoids formed by adding σ0 to a semigroup contained in 〈σ3,σ4〉, groups 〈σ0〉, 〈σ1〉, and monoids 〈σ1,σ6〉=𝕄1 and 〈σ1,σ2〉=𝕄.There are fifty-six types of nonisomorphic semigroups in𝕄. These are twenty-eight non-isomorphism types of semigroups contained in 〈σ3,σ4〉, twenty-six types of nonisomorphic monoids formed by adding σ0 to a semigroup contained in 〈σ3,σ4〉, and also 𝕄1 and 𝕄. Indeed, adding σ0 to a semigroup which is not a monoid we obtain a monoid. In this way, we get twenty-four types of nonisomorphic monoids. Adding σ0 to a monoid contained in 〈σ3,σ4〉 we get two new non-isomorphism types of monoids. But, adding σ0 to a group contained in 〈σ3,σ4〉 we get no new type of monoid, since we get a monoid isomorphic to 〈σ2,σ10〉 or 〈σ2,σ6〉. The other two types are 𝕄1 and 𝕄.
## 9.2. Semigroups which Are Not Monoids
Below we have reproduced, using the smallest number of generators and the dictionary order, a list of all 43 semigroups, which are included in the𝕄 as follows:(1)
〈σ2,σ3〉={σ2,σ3,σ6,σ7,σ10,σ11}.(2)
〈σ2,σ3,σ5〉={σ2,σ3,σ5,σ6,…,σ13}.(3)
〈σ2,σ3,σ8〉=〈σ2,σ3,σ9〉=〈σ2,σ3,σ12〉=〈σ2,σ3,σ13〉={σ2,σ3,σ6,σ7,…,σ13}.(4)
〈σ2,σ4〉={σ2,σ4,σ6,σ8,σ10,σ12}.(5)
〈σ2,σ4,σ5〉={σ2,σ4,σ5,…,σ13}.(6)
〈σ2,σ4,σ7〉=〈σ2,σ4,σ9〉=〈σ2,σ4,σ11〉=〈σ2,σ4,σ13〉={σ2,σ4,σ6,σ7…,σ13}.(7)
〈σ2,σ5〉={σ2,σ5,σ7,σ8,σ10,σ13}.(8)
〈σ2,σ5,σ6〉=〈σ2,σ5,σ9〉=〈σ2,σ5,σ11〉=〈σ2,σ5,σ12〉={σ2,σ5,σ6,…,σ13}.(9)
〈σ2,σ7〉={σ2,σ7,σ10}.(10)
〈σ2,σ8〉={σ2,σ8,σ10}.(11)
〈σ2,σ9〉=〈σ2,σ6,σ13〉=〈σ2,σ7,σ12〉=〈σ2,σ8,σ11〉=〈σ2,σ11,σ12〉=〈σ2,σ11,σ13〉 = 〈σ2,σ12,σ13〉={σ2,σ6,σ7,…,σ13}.(12)
〈σ2,σ11〉=〈σ2,σ6,σ7〉={σ2,σ6,σ7,σ10,σ11}.(13)
〈σ2,σ12〉=〈σ2,σ6,σ8〉={σ2,σ6,σ8,σ10,σ12}.(14)
〈σ2,σ13〉=〈σ2,σ7,σ8〉={σ2,σ7,σ8,σ10,σ13}.(15)
〈σ3〉={σ3,σ7,σ11}.(16)
〈σ3,σ4〉={σ2,σ3,…,σ13}.(17)
〈σ3,σ5〉={σ3,σ5,σ7,σ9,σ11,σ13}.(18)
〈σ3,σ5,σ6〉=〈σ3,σ5,σ8〉=〈σ3,σ5,σ10〉=〈σ3,σ5,σ12〉={σ3,σ5,σ6,…,σ13}.(19)
〈σ3,σ6〉=〈σ3,σ10〉={σ3,σ6,σ7,σ10,σ11}.(20)
〈σ3,σ8〉=〈σ3,σ12〉={σ3,σ6,σ7,…,σ13}.(21)
〈σ3,σ9〉=〈σ3,σ13〉={σ3,σ7,σ9,σ11,σ13}.(22)
〈σ4〉={σ4,σ8,σ12}.(23)
〈σ4,σ5〉={σ4,σ5,σ8,σ9,σ12,σ13}.(24)
〈σ4,σ5,σ6〉=〈σ4,σ5,σ7〉=〈σ4,σ5,σ10〉=〈σ4,σ5,σ11〉={σ4,σ5,…,σ13}.(25)
〈σ4,σ6〉=〈σ4,σ10〉={σ4,σ6,σ8,σ10,σ12}.(26)
〈σ4,σ7〉=〈σ4,σ11〉={σ4,σ6,σ7,…,σ13}.(27)
〈σ4,σ9〉=〈σ4,σ13〉={σ4,σ8,σ9,σ12,σ13}.(28)
〈σ5,σ6〉=〈σ5,σ7,σ12〉=〈σ5,σ8,σ11〉=〈σ5,σ9,σ10〉=〈σ5,σ10,σ11〉=〈σ5,σ10,σ12〉 = 〈σ5,σ11,σ12〉={σ5,σ6,…,σ13}.(29)
〈σ5,σ7〉={σ5,σ7,σ13}.(30)
〈σ5,σ8〉={σ5,σ8,σ13}.(31)
〈σ5,σ10〉=〈σ5,σ7,σ8〉={σ5,σ7,σ8,σ10,σ13}.(32)
〈σ5,σ11〉=〈σ5,σ7,σ9〉={σ5,σ7,σ9,σ11,σ13}.(33)
〈σ5,σ12〉=〈σ5,σ8,σ9〉={σ5,σ8,σ9,σ12,σ13}.(34)
〈σ6,σ7〉=〈σ6,σ11〉=〈σ10,σ11〉={σ6,σ7,σ10,σ11}.(35)
〈σ6,σ8〉=〈σ6,σ12〉=〈σ10,σ12〉={σ6,σ8,σ10,σ12}.(36)
〈σ6,σ9〉=〈σ6,σ13〉=〈σ7,σ12〉=〈σ8,σ11〉=〈σ9,σ10〉=〈σ11,σ12〉 = 〈σ6,σ7,σ8〉=〈σ7,σ8,σ9〉 = 〈σ10,σ11,σ13〉=〈σ10,σ12,σ13〉={σ6,σ7,…,σ13}.(37)
〈σ7,σ8〉={σ7,σ8,σ10,σ13}.(38)
〈σ7,σ9〉={σ7,σ9,σ11,σ13}.(39)
〈σ7,σ10〉={σ7,σ10}.(40)
〈σ7,σ13〉={σ7,σ13}.(41)
〈σ8,σ9〉={σ8,σ9,σ12,σ13}.(42)
〈σ8,σ10〉={σ8,σ10}.(43)
〈σ8,σ13〉={σ8,σ13}.
## 9.3. Isomorphism Types of Semigroups Contained in𝕄
Systematize the list of all isomorphism types of semigroups contained in the monoid𝕄. Isomorphisms, which are restrictions of the isomorphism 𝔸, will be regarded as self-evident, and therefore they will not be commented on.(i)
The monoid𝕄 contains 12 groups with 2 isomorphism types. These are 7 one-element groups and 5 two-element groups.(ii)
The monoid𝕄 contains 8 two-element monoids with 2 isomorphism types. These are σ0 added to 6 one-element groups and 〈σ2,σ10〉≅〈σ5,σ13〉. Also, it contains 4 two-element semigroups, not monoids, with 2 isomorphism types. These are 〈σ7,σ10〉≅〈σ8,σ13〉 and 〈σ8,σ10〉≅〈σ7,σ13〉.(iii)
The monoid𝕄 contains 12 three-element monoids with 5 isomorphism types. These are σ0 added to 4 two-element groups and also 〈σ0,σ2,σ10〉≅〈σ0,σ5,σ13〉, 〈σ0,σ7,σ10〉≅〈σ0,σ8,σ13〉, 〈σ0,σ8,σ10〉≅〈σ0,σ7,σ13〉, and 〈σ2,σ6〉≅〈σ5,σ9〉.(iv)
The monoid𝕄 contains 6 three-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ2,σ7〉≅〈σ5,σ8〉, 〈σ2,σ8〉≅〈σ5,σ7〉, and 〈σ3〉≅〈σ4〉.(v)
The monoid𝕄 contains 8 four-element monoids, each contains σ0, with 4 isomorphism types. These are semigroups from two preceding items that can be substantially extended by σ0.(vi)
The monoid𝕄 contains 5 four-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ6,σ7〉≅〈σ8,σ9〉, 〈σ6,σ8〉≅〈σ7,σ9〉 and 〈σ7,σ8〉. These semigroups extended by σ0 yield 5 monoids, all which consist of five elements, with 3 isomorphism types.(vii)
The monoid𝕄 contains 10 five-element semigroups—not monoids, with 5 isomorphism types. These are 〈σ2,σ11〉≅〈σ5,σ12〉, 〈σ2,σ12〉≅〈σ5,σ11〉, 〈σ2,σ13〉≅〈σ5,σ10〉, 〈σ3,σ6〉≅〈σ4,σ9〉, and 〈σ3,σ9〉≅〈σ4,σ6〉. These semigroups extended by σ0 yield 10 monoids, all of which consist of six elements, with 5 isomorphism types. We get 10 new isomorphism types, since the semigroups are distinguished by semigroups 〈σ3〉 and 〈σ4〉, and by nonisomorphic semigroups 〈σ6,σ7〉, 〈σ6,σ8〉, and 〈σ7,σ8〉.(viii)
The monoid𝕄 contains 5 six-element semigroups, not monoids, with 3 isomorphism types. These are 〈σ2,σ3〉≅〈σ4,σ5〉, 〈σ2,σ4〉≅〈σ3,σ5〉, and 〈σ2,σ5〉. These semigroups extended by σ0 yield 5 monoids, all of which consist of seven elements, with 3 isomorphism types. We get 6 new isomorphism types, since the semigroups are distinguished by non isomorphic semigroups 〈σ6,σ7〉, 〈σ6,σ8〉, and 〈σ7,σ8〉.(ix)
The monoid𝕄 contains no seven-element semigroup, not a monoid, no eight-element monoid and the only semigroup 〈σ6,σ9〉 with exactly eight elements and the only monoid 〈σ0,σ6,σ9〉 with exactly nine elements.(x)
The monoid𝕄 contains 4 nine-element semigroups, not monoids, with 2 isomorphism types. These are 〈σ2,σ9〉≅〈σ5,σ6〉 and 〈σ3,σ8〉≅〈σ4,σ7〉. The semigroup 〈σ2,σ9〉 does not contain a semigroup isomorphic to 〈σ3〉, hence it is not isomorphic to 〈σ3,σ8〉. These semigroups extended by σ0 yield 4 monoids, all of which consist of ten elements, with 2 isomorphism types.(xi)
The monoid𝕄 contains 6 ten-element semigroups, not monoids, with 4 isomorphism types. These are 〈σ1,σ6〉, 〈σ2,σ3,σ8〉≅〈σ4,σ5,σ6〉, 〈σ2,σ4,σ7〉≅〈σ3,σ5,σ6〉, and 〈σ2,σ5,σ6〉. These semigroups (except 〈σ1,σ6〉) extended by σ0 yield 5 monoids, all of which consist of ten elements, with 3 isomorphism types. We get 6 new isomorphism types, since the semigroups are distinguished by not isomorphic semigroups 〈σ2,σ3〉, 〈σ2,σ4〉, and 〈σ2,σ5〉.(xii)
The monoid𝕄 contains 2 isomorphic semigroups, not monoids, which consist of 11 elements, that is, 〈σ2,σ3,σ5〉≅〈σ2,σ4,σ5〉. These semigroups extended by σ0 yield 2 isomorphic monoids, which consist of 12 elements. The monoid 𝕄 contains no larger semigroup with the exception of itself.
## 10. Cancellation Rules Motivated by Some Topological Properties
### 10.1. Some Consequences of the Axiom∅=∅-
So far, we used only the following relations (above named cancellation rules):σ2∘σ2=σ2, σ1∘σ1=σ0, σ2∘σ12=σ6, and σ2∘σ13=σ7. When one assumes X≠∅=∅-, then
(18)X=σ0(X)=σ2(X)=σ5(X)=σ7(X)=σ8(X)=σ10(X)=σ13(X),∅=σ1(X)=σ3(X)=σ4(X)=σ6(X)=σ9(X)=σ11(X)=σ12(X).
Using the substitution A↦Ac, one obtains equivalent relations between operations from the set {σ1,σ3,σ4,σ6,σ9,σ11,σ12}, and conversely. Therefore, cancellation rules are topologically reasonable only between the operations from the monoid as follows:
(19)〈σ0,σ2,σ5〉={σ0,σ2,σ5,σ7,σ8,σ10,σ13}.
Chapman, see [3], considered properties of subsets with respect to such relations. Below, we are going to identify relations that are determined by some topological spaces; compare [10, 11].
### 10.2. The Relationσ0=σ2
If a topological spaceX is discrete, then there exist two Kuratowski operation, only. These are σ0 and σ1. So, the monoid of Kuratowski operations reduced to the group 〈σ1〉.The relationσ0=σ2 is equivalent to any relation σ0=σi, where i∈{5,7,8,10,13}. Any such relation implies that every subset of X has to be closed and open; that is, X has to be discrete. However, one can check these using (only) the facts that σ1 is an involution and σ2 is an idempotent and the cancellation rules, that is, the Cayley table for 𝕄. So, σ0=σ2 follows
(20)σ0=σ2=σ5=σ7=σ8=σ10=σ13.
### 10.3. The Relationσ2=σ5
Topologically,σ2=σ5 means that X must be discrete. This is so because Ac-c⊆A⊆A- for any A⊆X.
### 10.4. The Relationσ2=σ7
Topologically, the relationσ2=σ7 implies σ0=σ2. But it requires the use of topology axioms ∅=∅- and C-∪B-=(C∪B)- for each C and B.Lemma 5.
For any topological spaceσ2=σ7 implies σ2=σ8.Proof.
Ifσ2=σ7, then A≠∅⇒Ac-c≠∅, for any A⊆X. Indeed, if Ac-c=∅, then σ7(A)=∅-=∅. Since A≠∅, then σ2(A)≠∅. Hence σ2(A)≠σ7(A), a contradiction.
The axiomC-∪B-=(C∪B)- implies that always
(21)(A-∩A-c-)c-c=∅.
Thus, the additional assumption σ2=σ7 follows that always A-∩A-c-=∅. Therefore, always A-c-=A-c, but this means that any closed set has to be open; in other words, σ2=σ8.Proposition 6.
For any topological spaceσ2=σ7 implies σ0=σ2.Proof.
But the relationσ2=σ7 is equivalent with σ5=σ8. By Lemma 5, we get σ2=σ5. Finally σ0=σ2.The relationσ2=σ7 has interpretation without the axiom ∅=∅-. Indeed, suppose X={a,b}. Put
(22)σ2(∅)={a}=σ2({a}),X=σ2(X)=σ2({b}).
Then, check that σ2=σ7 and
(23)σ8(∅)=σ5({a})=σ4({b})=σ1(X)=∅;
in other words, σ2=σ7 and σ2≠σ8. However, σ2=σ7 is equivalent to σ5=σ8.This relation impliesσ2=σ7=σ10, σ5=σ8=σ13, σ3=σ6=σ11, and σ4=σ9=σ12. For this interpretation, the monoid 𝕄/(σ2=σ7), consisting of Kuratowski operation over a such X, has six elements, only. In 𝕄/(σ2=σ7), there are relations covered by the following proposition, only.Proposition 7.
For any monoid with the Cayley table as for𝕄, the relation σ2=σ7 implies (i)
σ2=σ7=σ10=σ7∘σ2;(ii)
σ5=σ1∘σ2∘σ1=σ1∘σ7∘σ1=σ8=σ5∘σ2=σ5∘σ7=σ13;(iii)
σ3=σ2∘σ1=σ7∘σ1=σ6=σ10∘σ1=σ11;(iv)
σ4=σ1∘σ2=σ1∘σ7=σ9=σ1∘σ10=σ12.Thus, the Cayley table does not contain the complete information resulting from the axioms of topology.
### 10.5. The Relationσ2=σ8
Topologically, the relationσ2=σ8 means that any closed set is open, too. Thus, if X={a,b,c} is a topological space with the open sets X, ∅, {a,b}, and {c}, then 𝕄/(σ2=σ8) is the monoid of all Kuratowski operations over X. Relations σ2=σ8 and σ5=σ7 are equivalent. They imply relations: σ2=σ8=σ10, σ5=σ7=σ13, σ3=σ9=σ11, and σ4=σ6=σ12. The permutation
(24)(σ0σ1σ2σ3σ4σ5σ0σ1σ5σ4σ3σ2)
determines the isomorphism between monoids 𝕄/(σ2=σ7) and 𝕄/(σ2=σ8).
### 10.6. The Relationsσ2=σ10 and σ2=σ13
Topologically, the relationσ2=σ8 means that any nonempty closed set has nonempty interior. For each A, the closed set A-∩A-c- has empty interior, so the relation σ2=σ10 implies that A-c is closed. Hence, any open set has to be closed, so it implies σ2=σ8. The relation σ2=σ13 follows that each closed set has to be open, so it implies σ2=σ8, too.
### 10.7. The Relationσ7=σ8
Using the Cayley table for𝕄, one can check that the relations σ7=σ8 and σ10=σ13 are equivalent. Each of them gives σ7=σ8=σ10=σ13 and σ6=σ9=σ11=σ12. If X={a,b} is a topological space with the open sets X, ∅, and {a}, then 𝕄/(σ7=σ8) is the monoid of all Kuratowski operations over X and consists of 8 elements.
### 10.8. The Relationσ7=σ10
Using the Cayley table for𝕄, one can check that the relations σ7=σ10, σ8=σ13, σ6=σ11, and σ9=σ12 are equivalent. If X is a sequence converging to the point g and g∈X, then 𝕄/(σ7=σ10) is the monoid of all Kuratowski operations over X and consists of 10 elements.
### 10.9. The Relationσ7=σ13
Using the Cayley table for𝕄, one can check that the relations σ7=σ13 and σ8=σ10 are equivalent. Also σ6=σ12 and σ9=σ11. These relations give the monoid with the following Cayley table, where the row and column marked by the identity are omitted:
(25)σ1σ2σ3σ4σ5σ6σ7σ8σ9σ1σ0σ4σ5σ2σ3σ8σ9σ6σ7σ2σ3σ2σ3σ6σ7σ6σ7σ8σ9σ3σ2σ6σ7σ2σ3σ8σ9σ6σ7σ4σ5σ4σ5σ8σ9σ8σ9σ6σ7σ5σ4σ8σ9σ4σ5σ6σ7σ8σ9σ6σ7σ6σ7σ8σ9σ8σ9σ6σ7σ7σ6σ8σ9σ6σ7σ6σ7σ8σ9σ8σ9σ8σ9σ6σ7σ6σ7σ8σ9σ9σ8σ6σ7σ8σ9σ8σ9σ6σ7If a spaceX is extremally disconnected, then the closures of open sets are open; compare [2, page 452]. It follows that σ6=σ12. The space X={a,b} with the open sets X, ∅, and {a} is extremally disconnected. But it contains a one-element open and dense set {a}, and it follows that σ7=σ8. Similar is for the space βN; see [2, pages 228 and 453] to find the definition and properties of βN. There are Hausdorff extremally disconnected spaces which are dense in itself. For example, the Stone space of the complete Boolean algebra of all regular closed subsets of the unit interval, compare [12]. For such spaces σ7≠σ8 and σ7=σ13. To see this, suppose a Hausdorff X is extremally disconnected and dense in itself. Let X=U∪V∪W, where sets U,V, and W are closed and open. Consider a set A=Ac-c∪B∪C, such that (i)
Cc-c=∅ and C-=W;(ii)
∅≠B⊆V and B-c-c=∅;(iii)
U=Ac-c-≠Ac-c. Then check that (i)
σ0(A)=A and σ1(A)=X∖(Ac-c∪B∪C);(ii)
σ2(A)=U∪B-∪W and σ3(A)=X∖Ac-c;(iii)
σ4(A)=V∖B- and σ5(A)=Ac-c;(iv)
σ6(A)=σ12(A)=V and σ7(A)=σ13(A)=U;(v)
σ8(A)=σ10(A)=U∪W and σ9(A)=σ11(A)=V∪W. Hence we have that σ7≠σ8. Note that, if W=∅, then σ7(A)=σ8(A). This is the case of subsets of βN.
## 10.1. Some Consequences of the Axiom∅=∅-
So far, we used only the following relations (above named cancellation rules):σ2∘σ2=σ2, σ1∘σ1=σ0, σ2∘σ12=σ6, and σ2∘σ13=σ7. When one assumes X≠∅=∅-, then
(18)X=σ0(X)=σ2(X)=σ5(X)=σ7(X)=σ8(X)=σ10(X)=σ13(X),∅=σ1(X)=σ3(X)=σ4(X)=σ6(X)=σ9(X)=σ11(X)=σ12(X).
Using the substitution A↦Ac, one obtains equivalent relations between operations from the set {σ1,σ3,σ4,σ6,σ9,σ11,σ12}, and conversely. Therefore, cancellation rules are topologically reasonable only between the operations from the monoid as follows:
(19)〈σ0,σ2,σ5〉={σ0,σ2,σ5,σ7,σ8,σ10,σ13}.
Chapman, see [3], considered properties of subsets with respect to such relations. Below, we are going to identify relations that are determined by some topological spaces; compare [10, 11].
## 10.2. The Relationσ0=σ2
If a topological spaceX is discrete, then there exist two Kuratowski operation, only. These are σ0 and σ1. So, the monoid of Kuratowski operations reduced to the group 〈σ1〉.The relationσ0=σ2 is equivalent to any relation σ0=σi, where i∈{5,7,8,10,13}. Any such relation implies that every subset of X has to be closed and open; that is, X has to be discrete. However, one can check these using (only) the facts that σ1 is an involution and σ2 is an idempotent and the cancellation rules, that is, the Cayley table for 𝕄. So, σ0=σ2 follows
(20)σ0=σ2=σ5=σ7=σ8=σ10=σ13.
## 10.3. The Relationσ2=σ5
Topologically,σ2=σ5 means that X must be discrete. This is so because Ac-c⊆A⊆A- for any A⊆X.
## 10.4. The Relationσ2=σ7
Topologically, the relationσ2=σ7 implies σ0=σ2. But it requires the use of topology axioms ∅=∅- and C-∪B-=(C∪B)- for each C and B.Lemma 5.
For any topological spaceσ2=σ7 implies σ2=σ8.Proof.
Ifσ2=σ7, then A≠∅⇒Ac-c≠∅, for any A⊆X. Indeed, if Ac-c=∅, then σ7(A)=∅-=∅. Since A≠∅, then σ2(A)≠∅. Hence σ2(A)≠σ7(A), a contradiction.
The axiomC-∪B-=(C∪B)- implies that always
(21)(A-∩A-c-)c-c=∅.
Thus, the additional assumption σ2=σ7 follows that always A-∩A-c-=∅. Therefore, always A-c-=A-c, but this means that any closed set has to be open; in other words, σ2=σ8.Proposition 6.
For any topological spaceσ2=σ7 implies σ0=σ2.Proof.
But the relationσ2=σ7 is equivalent with σ5=σ8. By Lemma 5, we get σ2=σ5. Finally σ0=σ2.The relationσ2=σ7 has interpretation without the axiom ∅=∅-. Indeed, suppose X={a,b}. Put
(22)σ2(∅)={a}=σ2({a}),X=σ2(X)=σ2({b}).
Then, check that σ2=σ7 and
(23)σ8(∅)=σ5({a})=σ4({b})=σ1(X)=∅;
in other words, σ2=σ7 and σ2≠σ8. However, σ2=σ7 is equivalent to σ5=σ8.This relation impliesσ2=σ7=σ10, σ5=σ8=σ13, σ3=σ6=σ11, and σ4=σ9=σ12. For this interpretation, the monoid 𝕄/(σ2=σ7), consisting of Kuratowski operation over a such X, has six elements, only. In 𝕄/(σ2=σ7), there are relations covered by the following proposition, only.Proposition 7.
For any monoid with the Cayley table as for𝕄, the relation σ2=σ7 implies (i)
σ2=σ7=σ10=σ7∘σ2;(ii)
σ5=σ1∘σ2∘σ1=σ1∘σ7∘σ1=σ8=σ5∘σ2=σ5∘σ7=σ13;(iii)
σ3=σ2∘σ1=σ7∘σ1=σ6=σ10∘σ1=σ11;(iv)
σ4=σ1∘σ2=σ1∘σ7=σ9=σ1∘σ10=σ12.Thus, the Cayley table does not contain the complete information resulting from the axioms of topology.
## 10.5. The Relationσ2=σ8
Topologically, the relationσ2=σ8 means that any closed set is open, too. Thus, if X={a,b,c} is a topological space with the open sets X, ∅, {a,b}, and {c}, then 𝕄/(σ2=σ8) is the monoid of all Kuratowski operations over X. Relations σ2=σ8 and σ5=σ7 are equivalent. They imply relations: σ2=σ8=σ10, σ5=σ7=σ13, σ3=σ9=σ11, and σ4=σ6=σ12. The permutation
(24)(σ0σ1σ2σ3σ4σ5σ0σ1σ5σ4σ3σ2)
determines the isomorphism between monoids 𝕄/(σ2=σ7) and 𝕄/(σ2=σ8).
## 10.6. The Relationsσ2=σ10 and σ2=σ13
Topologically, the relationσ2=σ8 means that any nonempty closed set has nonempty interior. For each A, the closed set A-∩A-c- has empty interior, so the relation σ2=σ10 implies that A-c is closed. Hence, any open set has to be closed, so it implies σ2=σ8. The relation σ2=σ13 follows that each closed set has to be open, so it implies σ2=σ8, too.
## 10.7. The Relationσ7=σ8
Using the Cayley table for𝕄, one can check that the relations σ7=σ8 and σ10=σ13 are equivalent. Each of them gives σ7=σ8=σ10=σ13 and σ6=σ9=σ11=σ12. If X={a,b} is a topological space with the open sets X, ∅, and {a}, then 𝕄/(σ7=σ8) is the monoid of all Kuratowski operations over X and consists of 8 elements.
## 10.8. The Relationσ7=σ10
Using the Cayley table for𝕄, one can check that the relations σ7=σ10, σ8=σ13, σ6=σ11, and σ9=σ12 are equivalent. If X is a sequence converging to the point g and g∈X, then 𝕄/(σ7=σ10) is the monoid of all Kuratowski operations over X and consists of 10 elements.
## 10.9. The Relationσ7=σ13
Using the Cayley table for𝕄, one can check that the relations σ7=σ13 and σ8=σ10 are equivalent. Also σ6=σ12 and σ9=σ11. These relations give the monoid with the following Cayley table, where the row and column marked by the identity are omitted:
(25)σ1σ2σ3σ4σ5σ6σ7σ8σ9σ1σ0σ4σ5σ2σ3σ8σ9σ6σ7σ2σ3σ2σ3σ6σ7σ6σ7σ8σ9σ3σ2σ6σ7σ2σ3σ8σ9σ6σ7σ4σ5σ4σ5σ8σ9σ8σ9σ6σ7σ5σ4σ8σ9σ4σ5σ6σ7σ8σ9σ6σ7σ6σ7σ8σ9σ8σ9σ6σ7σ7σ6σ8σ9σ6σ7σ6σ7σ8σ9σ8σ9σ8σ9σ6σ7σ6σ7σ8σ9σ9σ8σ6σ7σ8σ9σ8σ9σ6σ7If a spaceX is extremally disconnected, then the closures of open sets are open; compare [2, page 452]. It follows that σ6=σ12. The space X={a,b} with the open sets X, ∅, and {a} is extremally disconnected. But it contains a one-element open and dense set {a}, and it follows that σ7=σ8. Similar is for the space βN; see [2, pages 228 and 453] to find the definition and properties of βN. There are Hausdorff extremally disconnected spaces which are dense in itself. For example, the Stone space of the complete Boolean algebra of all regular closed subsets of the unit interval, compare [12]. For such spaces σ7≠σ8 and σ7=σ13. To see this, suppose a Hausdorff X is extremally disconnected and dense in itself. Let X=U∪V∪W, where sets U,V, and W are closed and open. Consider a set A=Ac-c∪B∪C, such that (i)
Cc-c=∅ and C-=W;(ii)
∅≠B⊆V and B-c-c=∅;(iii)
U=Ac-c-≠Ac-c. Then check that (i)
σ0(A)=A and σ1(A)=X∖(Ac-c∪B∪C);(ii)
σ2(A)=U∪B-∪W and σ3(A)=X∖Ac-c;(iii)
σ4(A)=V∖B- and σ5(A)=Ac-c;(iv)
σ6(A)=σ12(A)=V and σ7(A)=σ13(A)=U;(v)
σ8(A)=σ10(A)=U∪W and σ9(A)=σ11(A)=V∪W. Hence we have that σ7≠σ8. Note that, if W=∅, then σ7(A)=σ8(A). This is the case of subsets of βN.
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*Source: 289854-2013-03-06.xml* | 2013 |
# Maximum Swing Flexion or Gait Symmetry: A Comparative Evaluation of Control Targets on Metabolic Energy Expenditure of Amputee Using Intelligent Prosthetic Knee
**Authors:** Wujing Cao; Weiliang Zhao; Hongliu Yu; Wenming Chen; Qiaoling Meng
**Journal:** BioMed Research International
(2018)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2018/2898546
---
## Abstract
Background. The metabolic energy expenditure (MEE) was the most important assessment standard of intelligent prosthetic knee (IPK). Maximum swing flexion (MSF) angle and gait symmetry (GS) were two control targets representing different developing directions for IPK. However, the few comparisons based on MEE assessment between the MSF and GS limited the development of the IPK design.Objectives. The aim of the present work was to find out the MEE difference of amputees using IPK with control targets of MSF and GS and determine which target was more suitable for the control of IPK based on the MEE assessment.Methods. The crossover trial was designed. Six unilateral transfemoral amputees participated in the study. The amputees were assessed when wearing the IPK with different control targets, namely, the maximum swing flexion angle and gait symmetry. The oxygen consumption analysis during walking at different speeds on a treadmill was carried out.Results. All subjects showed increased oxygen consumption as walking speed increased. However, no statistically significant differences were found in oxygen consumption for different control targets. The ANOVA test showed that the overall effects of the control targets of the prosthetic knee on oxygen consumption were not significant across all walking speeds.Conclusions. The control targets of MSF and GS showed no significant differences on MEE in above-knee amputees using IPK. From perspective of amputee’s metabolic costs, either maximum swing flexion or gait symmetry could be suitable control target for the IPK.
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## Body
## 1. Introduction
The loss of lower limb is usually caused by disease, trauma, and congenital disorder [1]. The way to restore walking ability is to install lower limb prosthesis [2]. A lower limb prosthesis generally consists of a socket, a knee joint, a pylon, and a prosthetic foot [3]. Because the knee needs to be stabilized and controlled by the amputee, the amputee’s ability to walk safely and efficiently with the prosthesis is largely determined by the knee joint [4].Prosthetic knee joints are currently described as mechanical or intelligent prosthetic (microprocessor-controlled) knees [5]. In general, mechanical control knees only provide swing or stance phase control with manual locking, constant friction, weight-activated friction, geometrically locking, pneumatics, or hydraulics [6]. They usually have no automated mechanism for adjustment when the walking speed or road condition changes. In contrast, intelligent prosthetic knees are equipped with sensors that continuously detect the position and the angular velocity of the prosthesis, as well as the forces that act on the ankle adapter [7]. This allows instantaneous adaptation of the flexion and extension resistance, which facilitates ambulation with varying walking speeds and cadence on different terrains, under various environmental conditions. The prosthetist can easily manipulate the control parameters of the intelligent prosthetic knee by means of software.The energy cost, gait dynamics, and general mobility reflect the ability to perform gait tasks of the prosthetic knee [8]. Previous efforts have been made to develop prosthetic knee mechanisms that could increase stability in stance phase, flexibility, and gait symmetry during swing phase and, consequently, reduce the metabolic energy expenditure during gait. Indeed, one of the most important considerations in the design and prescription of lower limb prosthesis is the metabolic energy expenditure [9].For amputee wearing an intelligent prosthetic knee, a physiological gait pattern may be realized with different control targets that could be generally divided into two groups, i.e., maximum swing flexion angle and gait symmetry. However, different control targets may lead to either reduced or increased energy costs in amputees. For control target as the maximum swing flexion angle, if the target angle is too large, the prosthetic knee joint will not be fully extended before the next heel strike. To prevent tripping under this condition, amputees are forced to either walk slower or work harder to push the knee forward during swing extension. Consequently, this may increase energy consumption and even cause uncomfortable gait patterns. On the other hand, gait symmetry may also be set as the control target, because a large difference in gait between the prosthesis and the amputee’s contralateral limb may be visible and discordant. Asymmetry, or lack of symmetry, appears to be a relevant aspect for differentiating a normal and pathological gait. From control perspective, this can often be realized through the control of prosthetic knee to track the intact leg. And theoretically, gait symmetry may help reduce the metabolic costs in amputees.A few previous studies exist that have compared the energy expenditure during ambulation of amputees wearing intelligent prosthetic knee and mechanically passive prosthetic knee. Datta et al. made the comparative evaluation of oxygen consumption in amputees using Intelligent Prosthesis and conventionally damped knee swing-phase control. Mean oxygen cost for all subjects at 0.69 m/s was 0.33 ml/kg.m with the conventional limb and 0.30 ml/kg.m with the Intelligent Prosthesis (p = 0.01). At 1.25 m/s the mean oxygen cost for the conventional limb was 0.24 ml/kg.m and for the Intelligent Prosthesis was 0.22 ml/kg.m. The results showed that oxygen cost of conventional limb and Intelligent Prosthesis decreased with the speed increased [10]. Jepson et al. assessed energy requirements using the Physiological Cost Index (PCI) to make a comparative evaluation of the Adaptive knee and Catech knee. The PCI results did not demonstrate improvement with the use of the Adaptive knee [11]. Johansson et al. compared the metabolic rate of two variable-damping knees, the hydraulic-based Otto Bock C-leg and the magnetorheological-based Ossur Rheo, with the mechanically passive, hydraulic-based Mauch SNS. When using the Rheo, metabolic rate decreased by 5% compared with the Mauch and by 3% compared with the C-leg. Metabolic cost during steady-state walking at a self-selected, comfortable speed was significantly different across the three tested knees. The results indicated that variable-damping knee prostheses offered metabolic energy expenditure advantages over mechanically passive designs for unilateral transfemoral amputees walking at self-selected ambulatory speeds [12]. Seymour et al. investigated energy expenditure between the C-leg and various nonmicroprocessor control (NMC) prosthetic knees. Statistically significant differences were found in oxygen consumption between prostheses at both typical and fast paces with the C-leg showing decreased values [13]. Kaufman et al. researched energy expenditure and activity of transfemoral amputees using mechanical and microprocessor-controlled prosthetic knees. Subjects demonstrated significantly increased physical activity–related energy expenditure levels in the participant’s free-living environment after wearing the microprocessor-controlled prosthetic knee joint. There was no significant difference in the energy efficiency of walking [14]. However, all of these studies have primarily focused on the comparison between intelligent prosthetic knee joints and conventional mechanical prosthetic devices. The influence of control targets on metabolic energy expenditure of amputee using intelligent prosthetic knee is rarely known.Therefore, the purpose of this study was to quantitatively compare the oxygen consumption in amputees wearing intelligent prosthetic knees when the control targets of intelligent knee are set to be maximum swing flexion and gait symmetry. The knowledge gained would help answer the following research question: whether different control targets in intelligent prosthetic knee may lead to different metabolic energy expenditures in amputees at different walking speeds?
## 2. Materials and Methods
### 2.1. Developed Intelligent Prosthetic Knee
The intelligent prosthetic knee, shown in Figure1(a), was designed based on the characteristics of hydraulic damping forces. The provided hydraulic system (Figure 1(b)) had two separate needle valves (2a, 2b) to generate joint resistance for the flexion and the extension movement. The valves opening were controlled by linear motors. As the valve opening changed, the flow resistance could be continuously varied from low to high values. When the piston 1 moved down during flexion, the oil flowed through flexion needle valve 2b and check valve 3b (flow marked in green). The steel spring was pressed during flexion by the displacement of the piston rod. For extension, the piston moved up and the oil passed extension needle valve 2a and check valve 3a (flow marked in red). The energy stored by compression of steel spring 4 was released. This could provide assistance for extension. Most of the sensors were integrated directly into the knee joint. In addition, loading sensors and ankle pressure sensor were built into the tube adapter that connected the knee joint with the prosthetic foot. Two prototypes of intelligent prosthetic knee had been made. They were mechanically identical except for the control targets. The control target of prototype one was maximum swing flexion and the other was the gait symmetry.Figure 1
(a) Microprocessor-controlled knee prosthesis. (b) Functional principle of the hydraulic damper.
### 2.2. Control Target with Maximum Swing Flexion
The auto-adaptation for swing flexion was designed to limit the maximum flexion angle for swing. The prosthetic knee joint and wearer were a nonlinear system [15]. Fuzzy logic control was easy to get good control in the nonlinear system with simple fuzzy inference [16]. Human walking was an unstable, strong coupling, and nonlinear system, which was suitable for fuzzy rules to control. The idea of control algorithm was to compare the differential of contact time for the stance phase in the sequential gait cycle with error threshold to control the valve position. The control block diagram of swing flexion was shown in Figure 2.Figure 2
Control block diagram of swing flexion.When the time error absolute value was less than the set value, it indicated that gait velocity had no change, and the valve position also kept the same with previous step:If|Tn-Tn-1| < Et then Kn = Kn-1;When the time error was greater than the set value, it indicated that gait velocity decreased compared to forward step, and the valve position would decrease:IfTn-Tn-1 > Et then Kn = Kn-1 – A Ek;When the error is smaller than the negative set value, it indicated that gait velocity increased compared to forward step, and the valve position would increase:IfTn-Tn-1 < -Et then Kn = Kn-1 + A Ek;K n is valve position calculated in the nth gait cycle; Kn-1is valve position calculated in the (n-1)th gait cycle; Tn-Tn-1 is differential of contact time for the stance phase in the sequential gait cycle; A is gain coefficient; Et is time error threshold; Ek is the minimum adjustment value of valve position; a: 5 degrees.The gain coefficient A was adjusted through the fuzzy logic control. When the input error was larger, the bigger gain coefficient was used to increase the rate of convergence. When the input error was smaller, the lesser gain coefficient was used to ensure the stability of the control.
### 2.3. Control Target with Gait Symmetry
Cerebella model articulation controller (CMAC) neural networks were very suitable for real-time nonlinear system and had the advantage of fast learning characteristics [17]. The required storage capacity of CMAC control would has a geometric growth with the increase of input dimension. Thus, it affected the quantification of the input space series and limited the final study accuracy. To seek a better method of intelligent control of prosthetic knee, a hybrid inverse dynamic method based on PD and Fuzzy-CMAC (cerebellar model of fuzzy neural network) was proposed. The core concept of this method was making the prosthesis track the intact knee angle to realize gait symmetry [18]. The control framework was shown in Figure 3. It had two main characteristics: the feedforward control was realized through Fuzzy-CMAC and the feedback control was realized using traditional controller to ensure the stability of the system and inhibit the disturbance. The output signals Up were obtained by cerebellar network feedback control through the PD controller and the input signals X(θ,θ˙,θ¨) were set for online training. PD/Fuzzy-CMAC had used the instructor δ learning algorithm. At the end of each control cycle, the corresponding Fuzzy-CMAC output μn(k) was calculated. Then the total control input μ(k) was compared with μn(k), and it could adjust the weight of the amendment into the learning process. The purpose of the learning was to make the difference smallest between the control input and the output of Fuzzy-CMAC. Adjust the target for the FCMAC by(1)Ek=12μnk-μk2·1cΔωk=-η∂Ek∂ω=ημk-μnkcαi=ημpkcαiωk=ωk-1+Δωk+αωk-ωk-1Figure 3
Control framework based on PD-FCMAC.whereE(k) was the error of controlling, ω(k) was weight value, η was network learning rate and η∈(0,1),α was inertial, and α∈(0,1).At the beginning of the system run-time, letω=0, and then μn=0, μ=μn. At this point the system was controlled by the conventional controller. Through the learning of the Fuzzy-CMAC, the output of PD controller gradually became zero, and the output μn(k) of CMAC control gradually converged to the total output μ(k).
### 2.4. Data Collection
Six transfemoral amputees gave informed consents to participate in this study. All subjects were surgically amputated due to trauma. The testing protocol was approved by the University of Shanghai for Science and Technology human subjects committee.All subjects were recruited by the certified prosthetists in Shanghai. The inclusion criteria were (i) at least one year after amputation; (ii) functional level from K3 (i.e., the patient has the ability or potential for ambulation with variable cadence) or higher; (iii) never previously fitted with an intelligent prosthetic knee [19]. The six participants were 22-45 years old, 168-180 cm in height, and weighed 62-70 kg. The patient characteristics were summarized in Table 1.Table 1
Subject demographics.
Subject Age(years) Height(cm) Weight(kg) Gender K-Level 1 22 175 70 Male K4 2 42 173 70 Male K3 3 35 180 75 Male K4 4 37 168 62 Male K3 5 45 176 72 Male K3 6 40 173 63 Male K3All subjects were not permitted to drink alcohol or caffeine for 24 hours prior to testing. The subjects’ diets were recorded on the day of and prior to the testing session. The similar diets were carried out for the following test.The Group 1 experiments were performed with the subjects wearing the knee prosthesis that had control target of maximum swing flexion (described as MSF). Each individual was given approximately 5 hrs to adapt to the wearing of the knee prosthesis. Before the test began, the subjects were requested to practice walking on a treadmill that had a1.8×1.2m2 surface area. When a normal gait pattern was observed by the prosthetist, the subject was allowed to have a rest for about 20~30 mins. The subject was then requested to walk consecutively on the treadmill at the specific walking speeds for a total of 19 minutes. The first 2 minutes were for the warm-up, followed by five sessions at different walking speeds (3min walking at 0.5m/s, 3 min at 0.7m/s, 3 min at 0.9m/s, 3 min at 1.1m/s, and 3 min at1.3m/s). The last 2 minutes were for the subject to slow down. To obtain oxygen consumption data, subjects wore a mouthpiece and nose plug to collect gases during tests. Through this period, breath-by-breath analysis of the subject’s expired air was carried out by means of Ultima™ CardiO2® (MGC Diagnostics Corporation, USA) gas exchange analysis system. Oxygen consumption was normalized to body weight (milliliter O2/kilogram/minute) for each testing trial.The Group 2 experiments were conducted four weeks later. The same experimental procedure was repeated except that the prosthetic knee had control target of gait symmetry (described as GS). When the control target was the GS, the prosthetic knee tracked the joint angle from the contralateral knee during walking. To achieve this target, a knee angle sensor was placed on contralateral leg of the subject to serve as an input signal to the prosthetic knee. In all cases, the same socket was used in both trials and only the prosthetic knees were changed for the MSF and GS trials. The fitting and alignment of the prosthetic knee to all six subjects were carried out by the same prosthetist.
## 2.1. Developed Intelligent Prosthetic Knee
The intelligent prosthetic knee, shown in Figure1(a), was designed based on the characteristics of hydraulic damping forces. The provided hydraulic system (Figure 1(b)) had two separate needle valves (2a, 2b) to generate joint resistance for the flexion and the extension movement. The valves opening were controlled by linear motors. As the valve opening changed, the flow resistance could be continuously varied from low to high values. When the piston 1 moved down during flexion, the oil flowed through flexion needle valve 2b and check valve 3b (flow marked in green). The steel spring was pressed during flexion by the displacement of the piston rod. For extension, the piston moved up and the oil passed extension needle valve 2a and check valve 3a (flow marked in red). The energy stored by compression of steel spring 4 was released. This could provide assistance for extension. Most of the sensors were integrated directly into the knee joint. In addition, loading sensors and ankle pressure sensor were built into the tube adapter that connected the knee joint with the prosthetic foot. Two prototypes of intelligent prosthetic knee had been made. They were mechanically identical except for the control targets. The control target of prototype one was maximum swing flexion and the other was the gait symmetry.Figure 1
(a) Microprocessor-controlled knee prosthesis. (b) Functional principle of the hydraulic damper.
## 2.2. Control Target with Maximum Swing Flexion
The auto-adaptation for swing flexion was designed to limit the maximum flexion angle for swing. The prosthetic knee joint and wearer were a nonlinear system [15]. Fuzzy logic control was easy to get good control in the nonlinear system with simple fuzzy inference [16]. Human walking was an unstable, strong coupling, and nonlinear system, which was suitable for fuzzy rules to control. The idea of control algorithm was to compare the differential of contact time for the stance phase in the sequential gait cycle with error threshold to control the valve position. The control block diagram of swing flexion was shown in Figure 2.Figure 2
Control block diagram of swing flexion.When the time error absolute value was less than the set value, it indicated that gait velocity had no change, and the valve position also kept the same with previous step:If|Tn-Tn-1| < Et then Kn = Kn-1;When the time error was greater than the set value, it indicated that gait velocity decreased compared to forward step, and the valve position would decrease:IfTn-Tn-1 > Et then Kn = Kn-1 – A Ek;When the error is smaller than the negative set value, it indicated that gait velocity increased compared to forward step, and the valve position would increase:IfTn-Tn-1 < -Et then Kn = Kn-1 + A Ek;K n is valve position calculated in the nth gait cycle; Kn-1is valve position calculated in the (n-1)th gait cycle; Tn-Tn-1 is differential of contact time for the stance phase in the sequential gait cycle; A is gain coefficient; Et is time error threshold; Ek is the minimum adjustment value of valve position; a: 5 degrees.The gain coefficient A was adjusted through the fuzzy logic control. When the input error was larger, the bigger gain coefficient was used to increase the rate of convergence. When the input error was smaller, the lesser gain coefficient was used to ensure the stability of the control.
## 2.3. Control Target with Gait Symmetry
Cerebella model articulation controller (CMAC) neural networks were very suitable for real-time nonlinear system and had the advantage of fast learning characteristics [17]. The required storage capacity of CMAC control would has a geometric growth with the increase of input dimension. Thus, it affected the quantification of the input space series and limited the final study accuracy. To seek a better method of intelligent control of prosthetic knee, a hybrid inverse dynamic method based on PD and Fuzzy-CMAC (cerebellar model of fuzzy neural network) was proposed. The core concept of this method was making the prosthesis track the intact knee angle to realize gait symmetry [18]. The control framework was shown in Figure 3. It had two main characteristics: the feedforward control was realized through Fuzzy-CMAC and the feedback control was realized using traditional controller to ensure the stability of the system and inhibit the disturbance. The output signals Up were obtained by cerebellar network feedback control through the PD controller and the input signals X(θ,θ˙,θ¨) were set for online training. PD/Fuzzy-CMAC had used the instructor δ learning algorithm. At the end of each control cycle, the corresponding Fuzzy-CMAC output μn(k) was calculated. Then the total control input μ(k) was compared with μn(k), and it could adjust the weight of the amendment into the learning process. The purpose of the learning was to make the difference smallest between the control input and the output of Fuzzy-CMAC. Adjust the target for the FCMAC by(1)Ek=12μnk-μk2·1cΔωk=-η∂Ek∂ω=ημk-μnkcαi=ημpkcαiωk=ωk-1+Δωk+αωk-ωk-1Figure 3
Control framework based on PD-FCMAC.whereE(k) was the error of controlling, ω(k) was weight value, η was network learning rate and η∈(0,1),α was inertial, and α∈(0,1).At the beginning of the system run-time, letω=0, and then μn=0, μ=μn. At this point the system was controlled by the conventional controller. Through the learning of the Fuzzy-CMAC, the output of PD controller gradually became zero, and the output μn(k) of CMAC control gradually converged to the total output μ(k).
## 2.4. Data Collection
Six transfemoral amputees gave informed consents to participate in this study. All subjects were surgically amputated due to trauma. The testing protocol was approved by the University of Shanghai for Science and Technology human subjects committee.All subjects were recruited by the certified prosthetists in Shanghai. The inclusion criteria were (i) at least one year after amputation; (ii) functional level from K3 (i.e., the patient has the ability or potential for ambulation with variable cadence) or higher; (iii) never previously fitted with an intelligent prosthetic knee [19]. The six participants were 22-45 years old, 168-180 cm in height, and weighed 62-70 kg. The patient characteristics were summarized in Table 1.Table 1
Subject demographics.
Subject Age(years) Height(cm) Weight(kg) Gender K-Level 1 22 175 70 Male K4 2 42 173 70 Male K3 3 35 180 75 Male K4 4 37 168 62 Male K3 5 45 176 72 Male K3 6 40 173 63 Male K3All subjects were not permitted to drink alcohol or caffeine for 24 hours prior to testing. The subjects’ diets were recorded on the day of and prior to the testing session. The similar diets were carried out for the following test.The Group 1 experiments were performed with the subjects wearing the knee prosthesis that had control target of maximum swing flexion (described as MSF). Each individual was given approximately 5 hrs to adapt to the wearing of the knee prosthesis. Before the test began, the subjects were requested to practice walking on a treadmill that had a1.8×1.2m2 surface area. When a normal gait pattern was observed by the prosthetist, the subject was allowed to have a rest for about 20~30 mins. The subject was then requested to walk consecutively on the treadmill at the specific walking speeds for a total of 19 minutes. The first 2 minutes were for the warm-up, followed by five sessions at different walking speeds (3min walking at 0.5m/s, 3 min at 0.7m/s, 3 min at 0.9m/s, 3 min at 1.1m/s, and 3 min at1.3m/s). The last 2 minutes were for the subject to slow down. To obtain oxygen consumption data, subjects wore a mouthpiece and nose plug to collect gases during tests. Through this period, breath-by-breath analysis of the subject’s expired air was carried out by means of Ultima™ CardiO2® (MGC Diagnostics Corporation, USA) gas exchange analysis system. Oxygen consumption was normalized to body weight (milliliter O2/kilogram/minute) for each testing trial.The Group 2 experiments were conducted four weeks later. The same experimental procedure was repeated except that the prosthetic knee had control target of gait symmetry (described as GS). When the control target was the GS, the prosthetic knee tracked the joint angle from the contralateral knee during walking. To achieve this target, a knee angle sensor was placed on contralateral leg of the subject to serve as an input signal to the prosthetic knee. In all cases, the same socket was used in both trials and only the prosthetic knees were changed for the MSF and GS trials. The fitting and alignment of the prosthetic knee to all six subjects were carried out by the same prosthetist.
## 3. Results and Discussion
### 3.1. Results
The oxygen consumption for individual subject wearing prosthetic knees of different control targets was plotted against increasing walking speeds, respectively (see Figures4~9).Figure 4
Oxygen consumption under different speeds for subject 1.Figure 5
Oxygen consumption under different speeds for subject 2.Figure 6
Oxygen consumption under different speeds for subject 3.Figure 7
Oxygen consumption under different speeds for subject 4.Figure 8
Oxygen consumption under different speeds for subject 5.Figure 9
Oxygen consumption under different speeds for subject 6.The six subjects did not show statistically significant differences in oxygen consumption when the control target was MSF compared with the GS. There were general trends that the oxygen consumption increased with the increased walking speeds, regardless of the control targets. The ANOVA tests showed that the overall effects of the control targets on oxygen consumption were not significant across all walking speeds (Table2). However, individual testing results showed that oxygen consumption for subjects 1, 4, and 6 were generally lower when the control target was GS under given testing speed. In contrast, oxygen consumption for subjects 3 and 5 was lower when the control target was MSF under given testing speed. Subject 2 showed mixed effects on walking efficiency across different speeds.Table 2
Mean comparisons of oxygen consumption.
Speed(m/s) Oxygen consumption(ml/kg/min) P-value MSF GS 0.5 14 ± 0.77 13.8 ± 0.78 0.664 0.7 14.43 ± 0.87 14.37 ± 0.98 0.904 0.9 14.93 ± 0.85 14.98 ± 0.89 0.922 1.1 15.9 ± 0.79 15.87 ± 0.73 0.941 1.3 16.5 ± 0.74 16.35 ± 0.7 0.726
### 3.2. Discussion
Our results clearly demonstrated that the net oxygen consumption increased as the walking speed increased when the amputees used the intelligent prosthetic knee, no matter the control target was MSF or GS. It was different with the previous report by Datta et al. [10]. Although the focus of their study was comparative evaluation of oxygen consumption in amputees using Intelligent Prostheses and conventionally damped knee, their results showed that the mean oxygen consumption decreased with the increased walking speed.Previous study suggested that the oxygen consumption (ml/kg/min) for able-bodied individuals during level-ground walking could be predicted using the formula VO2 = 0.1 ∗ speed (m/min) + 3.5 [13]. Using the above formula, oxygen consumption prediction for the subjects should increase with the increased walking speed. The trend of our results was in line with the formula. However, the oxygen consumption for our subjects was generally higher than those predicted by the formula. The reason might be that the formula was based on data obtained from healthy people walking on the level ground, while the current tests were for amputees wearing prosthetic knee walking on the treadmill.Our study also demonstrated that the control targets of maximum swing flexion or gait symmetry showed no significant difference in oxygen consumption over a range of walking speeds. This might explain why many researches had chosen the maximum swing flexion or gait symmetry to be the performance contrast indicators of prosthetic knees. Prinsena et al. compared the Rheo Knee II (a microprocessor-controlled prosthetic knee) with NMPKs across varying walking speeds. No differences on maximum swing flexion were found between prosthetic knee conditions. In addition, maximum swing flexion knee angle increased significantly with walking speed for both prosthetic knee conditions [19]. Julius et al. showed that the slope of the linear regression line of the maximum swing flexion under increased walking speed was 3.5°/m/s with C-Leg, 28.1°/m/s with Plié2.0, 18.3°/m/s with Orion, and 17.0°/m/s with Rel-K. On the contralateral side, the natural knee flexion angle was similar with all tested knee joints, resulting in a mean slope of 6.2°/m/s [20]. Kaufman et al. compared the gait symmetry of active transfemoral amputees while using a passive mechanical knee joint or a microprocessor-controlled knee joint. The results showed that the use of the microprocessor-controlled knee joint resulted in improved gait symmetry. These improvements might lead to a reduction in the degenerative musculoskeletal changes often experienced by amputees [21]. The choice of performance contrast indicators of maximum swing flexion or gait symmetry seemed to be supported by the results of this work.The oxygen consumption was similar to previous research with other prosthetic knees. In the research of Seymour et al., mean oxygen consumption with C-leg was12.6±1(ml/kg/min) in typical pace (49±15m/min) and 16.0±2(ml/kg/min) in fast pace (70±20m/min) [13]. Although the results in this work were a little higher, the differences were acceptable.This study had several limitations. A number of confounding factors might have contributed to the limited differences we found. The sample size was small. It affected statistical power and thereby the ability to detect significant differences. The tests were all level-walking. More realistic conditions including uneven terrain, sitting down, and standing up rather than steady level walking may be more revealing.
## 3.1. Results
The oxygen consumption for individual subject wearing prosthetic knees of different control targets was plotted against increasing walking speeds, respectively (see Figures4~9).Figure 4
Oxygen consumption under different speeds for subject 1.Figure 5
Oxygen consumption under different speeds for subject 2.Figure 6
Oxygen consumption under different speeds for subject 3.Figure 7
Oxygen consumption under different speeds for subject 4.Figure 8
Oxygen consumption under different speeds for subject 5.Figure 9
Oxygen consumption under different speeds for subject 6.The six subjects did not show statistically significant differences in oxygen consumption when the control target was MSF compared with the GS. There were general trends that the oxygen consumption increased with the increased walking speeds, regardless of the control targets. The ANOVA tests showed that the overall effects of the control targets on oxygen consumption were not significant across all walking speeds (Table2). However, individual testing results showed that oxygen consumption for subjects 1, 4, and 6 were generally lower when the control target was GS under given testing speed. In contrast, oxygen consumption for subjects 3 and 5 was lower when the control target was MSF under given testing speed. Subject 2 showed mixed effects on walking efficiency across different speeds.Table 2
Mean comparisons of oxygen consumption.
Speed(m/s) Oxygen consumption(ml/kg/min) P-value MSF GS 0.5 14 ± 0.77 13.8 ± 0.78 0.664 0.7 14.43 ± 0.87 14.37 ± 0.98 0.904 0.9 14.93 ± 0.85 14.98 ± 0.89 0.922 1.1 15.9 ± 0.79 15.87 ± 0.73 0.941 1.3 16.5 ± 0.74 16.35 ± 0.7 0.726
## 3.2. Discussion
Our results clearly demonstrated that the net oxygen consumption increased as the walking speed increased when the amputees used the intelligent prosthetic knee, no matter the control target was MSF or GS. It was different with the previous report by Datta et al. [10]. Although the focus of their study was comparative evaluation of oxygen consumption in amputees using Intelligent Prostheses and conventionally damped knee, their results showed that the mean oxygen consumption decreased with the increased walking speed.Previous study suggested that the oxygen consumption (ml/kg/min) for able-bodied individuals during level-ground walking could be predicted using the formula VO2 = 0.1 ∗ speed (m/min) + 3.5 [13]. Using the above formula, oxygen consumption prediction for the subjects should increase with the increased walking speed. The trend of our results was in line with the formula. However, the oxygen consumption for our subjects was generally higher than those predicted by the formula. The reason might be that the formula was based on data obtained from healthy people walking on the level ground, while the current tests were for amputees wearing prosthetic knee walking on the treadmill.Our study also demonstrated that the control targets of maximum swing flexion or gait symmetry showed no significant difference in oxygen consumption over a range of walking speeds. This might explain why many researches had chosen the maximum swing flexion or gait symmetry to be the performance contrast indicators of prosthetic knees. Prinsena et al. compared the Rheo Knee II (a microprocessor-controlled prosthetic knee) with NMPKs across varying walking speeds. No differences on maximum swing flexion were found between prosthetic knee conditions. In addition, maximum swing flexion knee angle increased significantly with walking speed for both prosthetic knee conditions [19]. Julius et al. showed that the slope of the linear regression line of the maximum swing flexion under increased walking speed was 3.5°/m/s with C-Leg, 28.1°/m/s with Plié2.0, 18.3°/m/s with Orion, and 17.0°/m/s with Rel-K. On the contralateral side, the natural knee flexion angle was similar with all tested knee joints, resulting in a mean slope of 6.2°/m/s [20]. Kaufman et al. compared the gait symmetry of active transfemoral amputees while using a passive mechanical knee joint or a microprocessor-controlled knee joint. The results showed that the use of the microprocessor-controlled knee joint resulted in improved gait symmetry. These improvements might lead to a reduction in the degenerative musculoskeletal changes often experienced by amputees [21]. The choice of performance contrast indicators of maximum swing flexion or gait symmetry seemed to be supported by the results of this work.The oxygen consumption was similar to previous research with other prosthetic knees. In the research of Seymour et al., mean oxygen consumption with C-leg was12.6±1(ml/kg/min) in typical pace (49±15m/min) and 16.0±2(ml/kg/min) in fast pace (70±20m/min) [13]. Although the results in this work were a little higher, the differences were acceptable.This study had several limitations. A number of confounding factors might have contributed to the limited differences we found. The sample size was small. It affected statistical power and thereby the ability to detect significant differences. The tests were all level-walking. More realistic conditions including uneven terrain, sitting down, and standing up rather than steady level walking may be more revealing.
## 4. Conclusions
The aim of the present work was to find out the metabolic energy expenditure difference of amputees using IPK with control targets of MSF and GS and determine which target was more suitable for the control of IPK based on the metabolic energy expenditure assessment. We concluded that the control targets of maximum swing flexion and gait symmetry had no significant difference on metabolic energy expenditure of amputee using intelligent prosthetic knee. From perspective of amputee’s metabolic costs, either maximum swing flexion or gait symmetry could be suitable control targets for IPK. No matter the control target of IPK was maximum swing flexion or gait symmetry, the oxygen consumption increased with the increased walking speed. The trend of the results was in line with able-bodied individuals walking over level ground.
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*Source: 2898546-2018-11-21.xml* | 2898546-2018-11-21_2898546-2018-11-21.md | 37,526 | Maximum Swing Flexion or Gait Symmetry: A Comparative Evaluation of Control Targets on Metabolic Energy Expenditure of Amputee Using Intelligent Prosthetic Knee | Wujing Cao; Weiliang Zhao; Hongliu Yu; Wenming Chen; Qiaoling Meng | BioMed Research International
(2018) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2018/2898546 | 2898546-2018-11-21.xml | ---
## Abstract
Background. The metabolic energy expenditure (MEE) was the most important assessment standard of intelligent prosthetic knee (IPK). Maximum swing flexion (MSF) angle and gait symmetry (GS) were two control targets representing different developing directions for IPK. However, the few comparisons based on MEE assessment between the MSF and GS limited the development of the IPK design.Objectives. The aim of the present work was to find out the MEE difference of amputees using IPK with control targets of MSF and GS and determine which target was more suitable for the control of IPK based on the MEE assessment.Methods. The crossover trial was designed. Six unilateral transfemoral amputees participated in the study. The amputees were assessed when wearing the IPK with different control targets, namely, the maximum swing flexion angle and gait symmetry. The oxygen consumption analysis during walking at different speeds on a treadmill was carried out.Results. All subjects showed increased oxygen consumption as walking speed increased. However, no statistically significant differences were found in oxygen consumption for different control targets. The ANOVA test showed that the overall effects of the control targets of the prosthetic knee on oxygen consumption were not significant across all walking speeds.Conclusions. The control targets of MSF and GS showed no significant differences on MEE in above-knee amputees using IPK. From perspective of amputee’s metabolic costs, either maximum swing flexion or gait symmetry could be suitable control target for the IPK.
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## Body
## 1. Introduction
The loss of lower limb is usually caused by disease, trauma, and congenital disorder [1]. The way to restore walking ability is to install lower limb prosthesis [2]. A lower limb prosthesis generally consists of a socket, a knee joint, a pylon, and a prosthetic foot [3]. Because the knee needs to be stabilized and controlled by the amputee, the amputee’s ability to walk safely and efficiently with the prosthesis is largely determined by the knee joint [4].Prosthetic knee joints are currently described as mechanical or intelligent prosthetic (microprocessor-controlled) knees [5]. In general, mechanical control knees only provide swing or stance phase control with manual locking, constant friction, weight-activated friction, geometrically locking, pneumatics, or hydraulics [6]. They usually have no automated mechanism for adjustment when the walking speed or road condition changes. In contrast, intelligent prosthetic knees are equipped with sensors that continuously detect the position and the angular velocity of the prosthesis, as well as the forces that act on the ankle adapter [7]. This allows instantaneous adaptation of the flexion and extension resistance, which facilitates ambulation with varying walking speeds and cadence on different terrains, under various environmental conditions. The prosthetist can easily manipulate the control parameters of the intelligent prosthetic knee by means of software.The energy cost, gait dynamics, and general mobility reflect the ability to perform gait tasks of the prosthetic knee [8]. Previous efforts have been made to develop prosthetic knee mechanisms that could increase stability in stance phase, flexibility, and gait symmetry during swing phase and, consequently, reduce the metabolic energy expenditure during gait. Indeed, one of the most important considerations in the design and prescription of lower limb prosthesis is the metabolic energy expenditure [9].For amputee wearing an intelligent prosthetic knee, a physiological gait pattern may be realized with different control targets that could be generally divided into two groups, i.e., maximum swing flexion angle and gait symmetry. However, different control targets may lead to either reduced or increased energy costs in amputees. For control target as the maximum swing flexion angle, if the target angle is too large, the prosthetic knee joint will not be fully extended before the next heel strike. To prevent tripping under this condition, amputees are forced to either walk slower or work harder to push the knee forward during swing extension. Consequently, this may increase energy consumption and even cause uncomfortable gait patterns. On the other hand, gait symmetry may also be set as the control target, because a large difference in gait between the prosthesis and the amputee’s contralateral limb may be visible and discordant. Asymmetry, or lack of symmetry, appears to be a relevant aspect for differentiating a normal and pathological gait. From control perspective, this can often be realized through the control of prosthetic knee to track the intact leg. And theoretically, gait symmetry may help reduce the metabolic costs in amputees.A few previous studies exist that have compared the energy expenditure during ambulation of amputees wearing intelligent prosthetic knee and mechanically passive prosthetic knee. Datta et al. made the comparative evaluation of oxygen consumption in amputees using Intelligent Prosthesis and conventionally damped knee swing-phase control. Mean oxygen cost for all subjects at 0.69 m/s was 0.33 ml/kg.m with the conventional limb and 0.30 ml/kg.m with the Intelligent Prosthesis (p = 0.01). At 1.25 m/s the mean oxygen cost for the conventional limb was 0.24 ml/kg.m and for the Intelligent Prosthesis was 0.22 ml/kg.m. The results showed that oxygen cost of conventional limb and Intelligent Prosthesis decreased with the speed increased [10]. Jepson et al. assessed energy requirements using the Physiological Cost Index (PCI) to make a comparative evaluation of the Adaptive knee and Catech knee. The PCI results did not demonstrate improvement with the use of the Adaptive knee [11]. Johansson et al. compared the metabolic rate of two variable-damping knees, the hydraulic-based Otto Bock C-leg and the magnetorheological-based Ossur Rheo, with the mechanically passive, hydraulic-based Mauch SNS. When using the Rheo, metabolic rate decreased by 5% compared with the Mauch and by 3% compared with the C-leg. Metabolic cost during steady-state walking at a self-selected, comfortable speed was significantly different across the three tested knees. The results indicated that variable-damping knee prostheses offered metabolic energy expenditure advantages over mechanically passive designs for unilateral transfemoral amputees walking at self-selected ambulatory speeds [12]. Seymour et al. investigated energy expenditure between the C-leg and various nonmicroprocessor control (NMC) prosthetic knees. Statistically significant differences were found in oxygen consumption between prostheses at both typical and fast paces with the C-leg showing decreased values [13]. Kaufman et al. researched energy expenditure and activity of transfemoral amputees using mechanical and microprocessor-controlled prosthetic knees. Subjects demonstrated significantly increased physical activity–related energy expenditure levels in the participant’s free-living environment after wearing the microprocessor-controlled prosthetic knee joint. There was no significant difference in the energy efficiency of walking [14]. However, all of these studies have primarily focused on the comparison between intelligent prosthetic knee joints and conventional mechanical prosthetic devices. The influence of control targets on metabolic energy expenditure of amputee using intelligent prosthetic knee is rarely known.Therefore, the purpose of this study was to quantitatively compare the oxygen consumption in amputees wearing intelligent prosthetic knees when the control targets of intelligent knee are set to be maximum swing flexion and gait symmetry. The knowledge gained would help answer the following research question: whether different control targets in intelligent prosthetic knee may lead to different metabolic energy expenditures in amputees at different walking speeds?
## 2. Materials and Methods
### 2.1. Developed Intelligent Prosthetic Knee
The intelligent prosthetic knee, shown in Figure1(a), was designed based on the characteristics of hydraulic damping forces. The provided hydraulic system (Figure 1(b)) had two separate needle valves (2a, 2b) to generate joint resistance for the flexion and the extension movement. The valves opening were controlled by linear motors. As the valve opening changed, the flow resistance could be continuously varied from low to high values. When the piston 1 moved down during flexion, the oil flowed through flexion needle valve 2b and check valve 3b (flow marked in green). The steel spring was pressed during flexion by the displacement of the piston rod. For extension, the piston moved up and the oil passed extension needle valve 2a and check valve 3a (flow marked in red). The energy stored by compression of steel spring 4 was released. This could provide assistance for extension. Most of the sensors were integrated directly into the knee joint. In addition, loading sensors and ankle pressure sensor were built into the tube adapter that connected the knee joint with the prosthetic foot. Two prototypes of intelligent prosthetic knee had been made. They were mechanically identical except for the control targets. The control target of prototype one was maximum swing flexion and the other was the gait symmetry.Figure 1
(a) Microprocessor-controlled knee prosthesis. (b) Functional principle of the hydraulic damper.
### 2.2. Control Target with Maximum Swing Flexion
The auto-adaptation for swing flexion was designed to limit the maximum flexion angle for swing. The prosthetic knee joint and wearer were a nonlinear system [15]. Fuzzy logic control was easy to get good control in the nonlinear system with simple fuzzy inference [16]. Human walking was an unstable, strong coupling, and nonlinear system, which was suitable for fuzzy rules to control. The idea of control algorithm was to compare the differential of contact time for the stance phase in the sequential gait cycle with error threshold to control the valve position. The control block diagram of swing flexion was shown in Figure 2.Figure 2
Control block diagram of swing flexion.When the time error absolute value was less than the set value, it indicated that gait velocity had no change, and the valve position also kept the same with previous step:If|Tn-Tn-1| < Et then Kn = Kn-1;When the time error was greater than the set value, it indicated that gait velocity decreased compared to forward step, and the valve position would decrease:IfTn-Tn-1 > Et then Kn = Kn-1 – A Ek;When the error is smaller than the negative set value, it indicated that gait velocity increased compared to forward step, and the valve position would increase:IfTn-Tn-1 < -Et then Kn = Kn-1 + A Ek;K n is valve position calculated in the nth gait cycle; Kn-1is valve position calculated in the (n-1)th gait cycle; Tn-Tn-1 is differential of contact time for the stance phase in the sequential gait cycle; A is gain coefficient; Et is time error threshold; Ek is the minimum adjustment value of valve position; a: 5 degrees.The gain coefficient A was adjusted through the fuzzy logic control. When the input error was larger, the bigger gain coefficient was used to increase the rate of convergence. When the input error was smaller, the lesser gain coefficient was used to ensure the stability of the control.
### 2.3. Control Target with Gait Symmetry
Cerebella model articulation controller (CMAC) neural networks were very suitable for real-time nonlinear system and had the advantage of fast learning characteristics [17]. The required storage capacity of CMAC control would has a geometric growth with the increase of input dimension. Thus, it affected the quantification of the input space series and limited the final study accuracy. To seek a better method of intelligent control of prosthetic knee, a hybrid inverse dynamic method based on PD and Fuzzy-CMAC (cerebellar model of fuzzy neural network) was proposed. The core concept of this method was making the prosthesis track the intact knee angle to realize gait symmetry [18]. The control framework was shown in Figure 3. It had two main characteristics: the feedforward control was realized through Fuzzy-CMAC and the feedback control was realized using traditional controller to ensure the stability of the system and inhibit the disturbance. The output signals Up were obtained by cerebellar network feedback control through the PD controller and the input signals X(θ,θ˙,θ¨) were set for online training. PD/Fuzzy-CMAC had used the instructor δ learning algorithm. At the end of each control cycle, the corresponding Fuzzy-CMAC output μn(k) was calculated. Then the total control input μ(k) was compared with μn(k), and it could adjust the weight of the amendment into the learning process. The purpose of the learning was to make the difference smallest between the control input and the output of Fuzzy-CMAC. Adjust the target for the FCMAC by(1)Ek=12μnk-μk2·1cΔωk=-η∂Ek∂ω=ημk-μnkcαi=ημpkcαiωk=ωk-1+Δωk+αωk-ωk-1Figure 3
Control framework based on PD-FCMAC.whereE(k) was the error of controlling, ω(k) was weight value, η was network learning rate and η∈(0,1),α was inertial, and α∈(0,1).At the beginning of the system run-time, letω=0, and then μn=0, μ=μn. At this point the system was controlled by the conventional controller. Through the learning of the Fuzzy-CMAC, the output of PD controller gradually became zero, and the output μn(k) of CMAC control gradually converged to the total output μ(k).
### 2.4. Data Collection
Six transfemoral amputees gave informed consents to participate in this study. All subjects were surgically amputated due to trauma. The testing protocol was approved by the University of Shanghai for Science and Technology human subjects committee.All subjects were recruited by the certified prosthetists in Shanghai. The inclusion criteria were (i) at least one year after amputation; (ii) functional level from K3 (i.e., the patient has the ability or potential for ambulation with variable cadence) or higher; (iii) never previously fitted with an intelligent prosthetic knee [19]. The six participants were 22-45 years old, 168-180 cm in height, and weighed 62-70 kg. The patient characteristics were summarized in Table 1.Table 1
Subject demographics.
Subject Age(years) Height(cm) Weight(kg) Gender K-Level 1 22 175 70 Male K4 2 42 173 70 Male K3 3 35 180 75 Male K4 4 37 168 62 Male K3 5 45 176 72 Male K3 6 40 173 63 Male K3All subjects were not permitted to drink alcohol or caffeine for 24 hours prior to testing. The subjects’ diets were recorded on the day of and prior to the testing session. The similar diets were carried out for the following test.The Group 1 experiments were performed with the subjects wearing the knee prosthesis that had control target of maximum swing flexion (described as MSF). Each individual was given approximately 5 hrs to adapt to the wearing of the knee prosthesis. Before the test began, the subjects were requested to practice walking on a treadmill that had a1.8×1.2m2 surface area. When a normal gait pattern was observed by the prosthetist, the subject was allowed to have a rest for about 20~30 mins. The subject was then requested to walk consecutively on the treadmill at the specific walking speeds for a total of 19 minutes. The first 2 minutes were for the warm-up, followed by five sessions at different walking speeds (3min walking at 0.5m/s, 3 min at 0.7m/s, 3 min at 0.9m/s, 3 min at 1.1m/s, and 3 min at1.3m/s). The last 2 minutes were for the subject to slow down. To obtain oxygen consumption data, subjects wore a mouthpiece and nose plug to collect gases during tests. Through this period, breath-by-breath analysis of the subject’s expired air was carried out by means of Ultima™ CardiO2® (MGC Diagnostics Corporation, USA) gas exchange analysis system. Oxygen consumption was normalized to body weight (milliliter O2/kilogram/minute) for each testing trial.The Group 2 experiments were conducted four weeks later. The same experimental procedure was repeated except that the prosthetic knee had control target of gait symmetry (described as GS). When the control target was the GS, the prosthetic knee tracked the joint angle from the contralateral knee during walking. To achieve this target, a knee angle sensor was placed on contralateral leg of the subject to serve as an input signal to the prosthetic knee. In all cases, the same socket was used in both trials and only the prosthetic knees were changed for the MSF and GS trials. The fitting and alignment of the prosthetic knee to all six subjects were carried out by the same prosthetist.
## 2.1. Developed Intelligent Prosthetic Knee
The intelligent prosthetic knee, shown in Figure1(a), was designed based on the characteristics of hydraulic damping forces. The provided hydraulic system (Figure 1(b)) had two separate needle valves (2a, 2b) to generate joint resistance for the flexion and the extension movement. The valves opening were controlled by linear motors. As the valve opening changed, the flow resistance could be continuously varied from low to high values. When the piston 1 moved down during flexion, the oil flowed through flexion needle valve 2b and check valve 3b (flow marked in green). The steel spring was pressed during flexion by the displacement of the piston rod. For extension, the piston moved up and the oil passed extension needle valve 2a and check valve 3a (flow marked in red). The energy stored by compression of steel spring 4 was released. This could provide assistance for extension. Most of the sensors were integrated directly into the knee joint. In addition, loading sensors and ankle pressure sensor were built into the tube adapter that connected the knee joint with the prosthetic foot. Two prototypes of intelligent prosthetic knee had been made. They were mechanically identical except for the control targets. The control target of prototype one was maximum swing flexion and the other was the gait symmetry.Figure 1
(a) Microprocessor-controlled knee prosthesis. (b) Functional principle of the hydraulic damper.
## 2.2. Control Target with Maximum Swing Flexion
The auto-adaptation for swing flexion was designed to limit the maximum flexion angle for swing. The prosthetic knee joint and wearer were a nonlinear system [15]. Fuzzy logic control was easy to get good control in the nonlinear system with simple fuzzy inference [16]. Human walking was an unstable, strong coupling, and nonlinear system, which was suitable for fuzzy rules to control. The idea of control algorithm was to compare the differential of contact time for the stance phase in the sequential gait cycle with error threshold to control the valve position. The control block diagram of swing flexion was shown in Figure 2.Figure 2
Control block diagram of swing flexion.When the time error absolute value was less than the set value, it indicated that gait velocity had no change, and the valve position also kept the same with previous step:If|Tn-Tn-1| < Et then Kn = Kn-1;When the time error was greater than the set value, it indicated that gait velocity decreased compared to forward step, and the valve position would decrease:IfTn-Tn-1 > Et then Kn = Kn-1 – A Ek;When the error is smaller than the negative set value, it indicated that gait velocity increased compared to forward step, and the valve position would increase:IfTn-Tn-1 < -Et then Kn = Kn-1 + A Ek;K n is valve position calculated in the nth gait cycle; Kn-1is valve position calculated in the (n-1)th gait cycle; Tn-Tn-1 is differential of contact time for the stance phase in the sequential gait cycle; A is gain coefficient; Et is time error threshold; Ek is the minimum adjustment value of valve position; a: 5 degrees.The gain coefficient A was adjusted through the fuzzy logic control. When the input error was larger, the bigger gain coefficient was used to increase the rate of convergence. When the input error was smaller, the lesser gain coefficient was used to ensure the stability of the control.
## 2.3. Control Target with Gait Symmetry
Cerebella model articulation controller (CMAC) neural networks were very suitable for real-time nonlinear system and had the advantage of fast learning characteristics [17]. The required storage capacity of CMAC control would has a geometric growth with the increase of input dimension. Thus, it affected the quantification of the input space series and limited the final study accuracy. To seek a better method of intelligent control of prosthetic knee, a hybrid inverse dynamic method based on PD and Fuzzy-CMAC (cerebellar model of fuzzy neural network) was proposed. The core concept of this method was making the prosthesis track the intact knee angle to realize gait symmetry [18]. The control framework was shown in Figure 3. It had two main characteristics: the feedforward control was realized through Fuzzy-CMAC and the feedback control was realized using traditional controller to ensure the stability of the system and inhibit the disturbance. The output signals Up were obtained by cerebellar network feedback control through the PD controller and the input signals X(θ,θ˙,θ¨) were set for online training. PD/Fuzzy-CMAC had used the instructor δ learning algorithm. At the end of each control cycle, the corresponding Fuzzy-CMAC output μn(k) was calculated. Then the total control input μ(k) was compared with μn(k), and it could adjust the weight of the amendment into the learning process. The purpose of the learning was to make the difference smallest between the control input and the output of Fuzzy-CMAC. Adjust the target for the FCMAC by(1)Ek=12μnk-μk2·1cΔωk=-η∂Ek∂ω=ημk-μnkcαi=ημpkcαiωk=ωk-1+Δωk+αωk-ωk-1Figure 3
Control framework based on PD-FCMAC.whereE(k) was the error of controlling, ω(k) was weight value, η was network learning rate and η∈(0,1),α was inertial, and α∈(0,1).At the beginning of the system run-time, letω=0, and then μn=0, μ=μn. At this point the system was controlled by the conventional controller. Through the learning of the Fuzzy-CMAC, the output of PD controller gradually became zero, and the output μn(k) of CMAC control gradually converged to the total output μ(k).
## 2.4. Data Collection
Six transfemoral amputees gave informed consents to participate in this study. All subjects were surgically amputated due to trauma. The testing protocol was approved by the University of Shanghai for Science and Technology human subjects committee.All subjects were recruited by the certified prosthetists in Shanghai. The inclusion criteria were (i) at least one year after amputation; (ii) functional level from K3 (i.e., the patient has the ability or potential for ambulation with variable cadence) or higher; (iii) never previously fitted with an intelligent prosthetic knee [19]. The six participants were 22-45 years old, 168-180 cm in height, and weighed 62-70 kg. The patient characteristics were summarized in Table 1.Table 1
Subject demographics.
Subject Age(years) Height(cm) Weight(kg) Gender K-Level 1 22 175 70 Male K4 2 42 173 70 Male K3 3 35 180 75 Male K4 4 37 168 62 Male K3 5 45 176 72 Male K3 6 40 173 63 Male K3All subjects were not permitted to drink alcohol or caffeine for 24 hours prior to testing. The subjects’ diets were recorded on the day of and prior to the testing session. The similar diets were carried out for the following test.The Group 1 experiments were performed with the subjects wearing the knee prosthesis that had control target of maximum swing flexion (described as MSF). Each individual was given approximately 5 hrs to adapt to the wearing of the knee prosthesis. Before the test began, the subjects were requested to practice walking on a treadmill that had a1.8×1.2m2 surface area. When a normal gait pattern was observed by the prosthetist, the subject was allowed to have a rest for about 20~30 mins. The subject was then requested to walk consecutively on the treadmill at the specific walking speeds for a total of 19 minutes. The first 2 minutes were for the warm-up, followed by five sessions at different walking speeds (3min walking at 0.5m/s, 3 min at 0.7m/s, 3 min at 0.9m/s, 3 min at 1.1m/s, and 3 min at1.3m/s). The last 2 minutes were for the subject to slow down. To obtain oxygen consumption data, subjects wore a mouthpiece and nose plug to collect gases during tests. Through this period, breath-by-breath analysis of the subject’s expired air was carried out by means of Ultima™ CardiO2® (MGC Diagnostics Corporation, USA) gas exchange analysis system. Oxygen consumption was normalized to body weight (milliliter O2/kilogram/minute) for each testing trial.The Group 2 experiments were conducted four weeks later. The same experimental procedure was repeated except that the prosthetic knee had control target of gait symmetry (described as GS). When the control target was the GS, the prosthetic knee tracked the joint angle from the contralateral knee during walking. To achieve this target, a knee angle sensor was placed on contralateral leg of the subject to serve as an input signal to the prosthetic knee. In all cases, the same socket was used in both trials and only the prosthetic knees were changed for the MSF and GS trials. The fitting and alignment of the prosthetic knee to all six subjects were carried out by the same prosthetist.
## 3. Results and Discussion
### 3.1. Results
The oxygen consumption for individual subject wearing prosthetic knees of different control targets was plotted against increasing walking speeds, respectively (see Figures4~9).Figure 4
Oxygen consumption under different speeds for subject 1.Figure 5
Oxygen consumption under different speeds for subject 2.Figure 6
Oxygen consumption under different speeds for subject 3.Figure 7
Oxygen consumption under different speeds for subject 4.Figure 8
Oxygen consumption under different speeds for subject 5.Figure 9
Oxygen consumption under different speeds for subject 6.The six subjects did not show statistically significant differences in oxygen consumption when the control target was MSF compared with the GS. There were general trends that the oxygen consumption increased with the increased walking speeds, regardless of the control targets. The ANOVA tests showed that the overall effects of the control targets on oxygen consumption were not significant across all walking speeds (Table2). However, individual testing results showed that oxygen consumption for subjects 1, 4, and 6 were generally lower when the control target was GS under given testing speed. In contrast, oxygen consumption for subjects 3 and 5 was lower when the control target was MSF under given testing speed. Subject 2 showed mixed effects on walking efficiency across different speeds.Table 2
Mean comparisons of oxygen consumption.
Speed(m/s) Oxygen consumption(ml/kg/min) P-value MSF GS 0.5 14 ± 0.77 13.8 ± 0.78 0.664 0.7 14.43 ± 0.87 14.37 ± 0.98 0.904 0.9 14.93 ± 0.85 14.98 ± 0.89 0.922 1.1 15.9 ± 0.79 15.87 ± 0.73 0.941 1.3 16.5 ± 0.74 16.35 ± 0.7 0.726
### 3.2. Discussion
Our results clearly demonstrated that the net oxygen consumption increased as the walking speed increased when the amputees used the intelligent prosthetic knee, no matter the control target was MSF or GS. It was different with the previous report by Datta et al. [10]. Although the focus of their study was comparative evaluation of oxygen consumption in amputees using Intelligent Prostheses and conventionally damped knee, their results showed that the mean oxygen consumption decreased with the increased walking speed.Previous study suggested that the oxygen consumption (ml/kg/min) for able-bodied individuals during level-ground walking could be predicted using the formula VO2 = 0.1 ∗ speed (m/min) + 3.5 [13]. Using the above formula, oxygen consumption prediction for the subjects should increase with the increased walking speed. The trend of our results was in line with the formula. However, the oxygen consumption for our subjects was generally higher than those predicted by the formula. The reason might be that the formula was based on data obtained from healthy people walking on the level ground, while the current tests were for amputees wearing prosthetic knee walking on the treadmill.Our study also demonstrated that the control targets of maximum swing flexion or gait symmetry showed no significant difference in oxygen consumption over a range of walking speeds. This might explain why many researches had chosen the maximum swing flexion or gait symmetry to be the performance contrast indicators of prosthetic knees. Prinsena et al. compared the Rheo Knee II (a microprocessor-controlled prosthetic knee) with NMPKs across varying walking speeds. No differences on maximum swing flexion were found between prosthetic knee conditions. In addition, maximum swing flexion knee angle increased significantly with walking speed for both prosthetic knee conditions [19]. Julius et al. showed that the slope of the linear regression line of the maximum swing flexion under increased walking speed was 3.5°/m/s with C-Leg, 28.1°/m/s with Plié2.0, 18.3°/m/s with Orion, and 17.0°/m/s with Rel-K. On the contralateral side, the natural knee flexion angle was similar with all tested knee joints, resulting in a mean slope of 6.2°/m/s [20]. Kaufman et al. compared the gait symmetry of active transfemoral amputees while using a passive mechanical knee joint or a microprocessor-controlled knee joint. The results showed that the use of the microprocessor-controlled knee joint resulted in improved gait symmetry. These improvements might lead to a reduction in the degenerative musculoskeletal changes often experienced by amputees [21]. The choice of performance contrast indicators of maximum swing flexion or gait symmetry seemed to be supported by the results of this work.The oxygen consumption was similar to previous research with other prosthetic knees. In the research of Seymour et al., mean oxygen consumption with C-leg was12.6±1(ml/kg/min) in typical pace (49±15m/min) and 16.0±2(ml/kg/min) in fast pace (70±20m/min) [13]. Although the results in this work were a little higher, the differences were acceptable.This study had several limitations. A number of confounding factors might have contributed to the limited differences we found. The sample size was small. It affected statistical power and thereby the ability to detect significant differences. The tests were all level-walking. More realistic conditions including uneven terrain, sitting down, and standing up rather than steady level walking may be more revealing.
## 3.1. Results
The oxygen consumption for individual subject wearing prosthetic knees of different control targets was plotted against increasing walking speeds, respectively (see Figures4~9).Figure 4
Oxygen consumption under different speeds for subject 1.Figure 5
Oxygen consumption under different speeds for subject 2.Figure 6
Oxygen consumption under different speeds for subject 3.Figure 7
Oxygen consumption under different speeds for subject 4.Figure 8
Oxygen consumption under different speeds for subject 5.Figure 9
Oxygen consumption under different speeds for subject 6.The six subjects did not show statistically significant differences in oxygen consumption when the control target was MSF compared with the GS. There were general trends that the oxygen consumption increased with the increased walking speeds, regardless of the control targets. The ANOVA tests showed that the overall effects of the control targets on oxygen consumption were not significant across all walking speeds (Table2). However, individual testing results showed that oxygen consumption for subjects 1, 4, and 6 were generally lower when the control target was GS under given testing speed. In contrast, oxygen consumption for subjects 3 and 5 was lower when the control target was MSF under given testing speed. Subject 2 showed mixed effects on walking efficiency across different speeds.Table 2
Mean comparisons of oxygen consumption.
Speed(m/s) Oxygen consumption(ml/kg/min) P-value MSF GS 0.5 14 ± 0.77 13.8 ± 0.78 0.664 0.7 14.43 ± 0.87 14.37 ± 0.98 0.904 0.9 14.93 ± 0.85 14.98 ± 0.89 0.922 1.1 15.9 ± 0.79 15.87 ± 0.73 0.941 1.3 16.5 ± 0.74 16.35 ± 0.7 0.726
## 3.2. Discussion
Our results clearly demonstrated that the net oxygen consumption increased as the walking speed increased when the amputees used the intelligent prosthetic knee, no matter the control target was MSF or GS. It was different with the previous report by Datta et al. [10]. Although the focus of their study was comparative evaluation of oxygen consumption in amputees using Intelligent Prostheses and conventionally damped knee, their results showed that the mean oxygen consumption decreased with the increased walking speed.Previous study suggested that the oxygen consumption (ml/kg/min) for able-bodied individuals during level-ground walking could be predicted using the formula VO2 = 0.1 ∗ speed (m/min) + 3.5 [13]. Using the above formula, oxygen consumption prediction for the subjects should increase with the increased walking speed. The trend of our results was in line with the formula. However, the oxygen consumption for our subjects was generally higher than those predicted by the formula. The reason might be that the formula was based on data obtained from healthy people walking on the level ground, while the current tests were for amputees wearing prosthetic knee walking on the treadmill.Our study also demonstrated that the control targets of maximum swing flexion or gait symmetry showed no significant difference in oxygen consumption over a range of walking speeds. This might explain why many researches had chosen the maximum swing flexion or gait symmetry to be the performance contrast indicators of prosthetic knees. Prinsena et al. compared the Rheo Knee II (a microprocessor-controlled prosthetic knee) with NMPKs across varying walking speeds. No differences on maximum swing flexion were found between prosthetic knee conditions. In addition, maximum swing flexion knee angle increased significantly with walking speed for both prosthetic knee conditions [19]. Julius et al. showed that the slope of the linear regression line of the maximum swing flexion under increased walking speed was 3.5°/m/s with C-Leg, 28.1°/m/s with Plié2.0, 18.3°/m/s with Orion, and 17.0°/m/s with Rel-K. On the contralateral side, the natural knee flexion angle was similar with all tested knee joints, resulting in a mean slope of 6.2°/m/s [20]. Kaufman et al. compared the gait symmetry of active transfemoral amputees while using a passive mechanical knee joint or a microprocessor-controlled knee joint. The results showed that the use of the microprocessor-controlled knee joint resulted in improved gait symmetry. These improvements might lead to a reduction in the degenerative musculoskeletal changes often experienced by amputees [21]. The choice of performance contrast indicators of maximum swing flexion or gait symmetry seemed to be supported by the results of this work.The oxygen consumption was similar to previous research with other prosthetic knees. In the research of Seymour et al., mean oxygen consumption with C-leg was12.6±1(ml/kg/min) in typical pace (49±15m/min) and 16.0±2(ml/kg/min) in fast pace (70±20m/min) [13]. Although the results in this work were a little higher, the differences were acceptable.This study had several limitations. A number of confounding factors might have contributed to the limited differences we found. The sample size was small. It affected statistical power and thereby the ability to detect significant differences. The tests were all level-walking. More realistic conditions including uneven terrain, sitting down, and standing up rather than steady level walking may be more revealing.
## 4. Conclusions
The aim of the present work was to find out the metabolic energy expenditure difference of amputees using IPK with control targets of MSF and GS and determine which target was more suitable for the control of IPK based on the metabolic energy expenditure assessment. We concluded that the control targets of maximum swing flexion and gait symmetry had no significant difference on metabolic energy expenditure of amputee using intelligent prosthetic knee. From perspective of amputee’s metabolic costs, either maximum swing flexion or gait symmetry could be suitable control targets for IPK. No matter the control target of IPK was maximum swing flexion or gait symmetry, the oxygen consumption increased with the increased walking speed. The trend of the results was in line with able-bodied individuals walking over level ground.
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*Source: 2898546-2018-11-21.xml* | 2018 |
# The Efficacy of Anti-Tumor Necrosis Factor Therapy in Cryopyrin-Associated Periodic Syndromes: A Report of Two Cases
**Authors:** Fatemeh Tahghighi; Mahdieh Vahedi; Nima Parvaneh; Mohammad Shahrooei; Vahid Ziaee
**Journal:** Case Reports in Genetics
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2898553
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## Abstract
Background. Cryopyrin-associated periodic syndromes (CAPSs) are a group of autoinflammatory disorders caused by a mutation in the NLRP3 gene. NLRP3 mutations increase inflammasome activation; therefore, IL-1 targeted therapies are frequently used in the aforementioned disorders. Case Presentation. We report two cases of CAPS in which the diagnosis was confirmed by genetic tests and an evaluation of the therapeutic response to anti-tumor necrosis factor (anti-TNF) agents. Conclusion. IL-1 inhibitors are highly effective in treating CAPS patients. Most patients with severe symptoms such as neurologic involvement improve with IL-1 blockade. Anti-TNF agents might be effective in reducing mild manifestation; however, they are not effective in improving more severe complications.
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## Body
## 1. Introduction
Cryopyrin-associated periodic syndromes (CAPS) are a group of autoinflammatory disorders caused by a gain-of-function mutation in the NLRP3 (CIAS1) gene located on the long arm of chromosome 1. CAPS are a spectrum of disorders with a range of severity. The moderate form of the CAPS is Muckle–Wells syndrome, often inherited as an autosomal dominant trait. The main clinical manifestations include recurrent episodes of fever, urticaria-like rash, and ocular and articular involvement. The severe form of the CAPS is the chronic infantile neurological cutaneous and articular (CINCA) disease that is presented with urticaria-like rash, mental delay, arthritis, and sensorineural hearing loss [1–5].Formation of NLRP3 inflammasome leads to caspase 1-mediated release of the proinflammatory cytokines such as IL-1B and IL-18. Since NLRP3 mutations can result in increased inflammasome activation and IL-1 production, IL-1 targeted therapies are used frequently in the patients. Interleukin 1 receptor antagonists such as anakinra can improve CAPS symptoms and prevent major complications such as hearing loss and amyloidosis [6–9]. Some patients with CAPS show partial response to IL-1 blockade. Other biologics such as anti-tumor necrosis factor (anti-TNF) agents are less effective than IL-1 inhibitors. In a few patients, anti-TNF agents have been able to result in partial response and improvement. TNF-α may play a role in regulating and activating the NLRP3 inflammasome [1, 2, 10].We will describe two cases of CAPS and evaluate the responses to anti-TNF agents and IL-1 inhibitors. The current study aims to describe the relative effectiveness of anti-TNF agents in improving CAPS symptoms, highlighting the role of TNF-α in the pathogenesis of the disorders.
## 2. Case 1
A 1-year-old boy was brought to our clinic with joint pain and swelling in his left ankle and knees that had lasted for more than 14 days. Since birth, he had had a recurrent urticarial rash that was not triggered by cold or other physical stimuli (Figure1). Often presented with high-grade fever, the rash lasted 24 hours and resolved without scarring. Additionally, he was treated with antihistamines for a long time due to a history of chronic urticaria. He was born premature and admitted for 60 days in the neonatal intensive care unit (NICU). His parents were not blood relatives. His older brother has a history of chronic atopic dermatitis. On examination, neurodevelopmental evaluation result was normal, but his weight and height were below the 3rd percentile for his age. He had significant synovial hypertrophy in both knees. No hepatosplenomegaly or lymphadenopathy was present. Other physical examinations indicated normal results. However, laboratory findings showed leukocytosis, anemia, and thrombocytosis. Moreover, there was an increase in acute phase reactants. The patient’s laboratory tests are listed in Table 1. Both chest X-ray and abdominal ultrasonography were normal. The left ankle and right knee sonography showed mild to moderate effusion and synovial hypertrophy.Figure 1
Urticaria-like rash on face and extremities. (c) At 10 months old, (b) at 3 years old (the first case), and (a) at 2 years old (the second case).
(a)(b)(c)Table 1
Laboratory tests of cryopyrin-associated periodic syndromes cases.
LAB (unit)Case 1Case 2WBC (µl)1610016000Hemoglobin (g/dl)7.59.5HCT (%)25.435.5Platelets (µl)567000703000GRA (%)5245LYM (%)4035MON (%)3.914.1EOS (%)44.9BASO (%)0.11ESR (mm/hr)60112CRP (mg/l)75180AST (U/l)1729ALT (U/l)1130LDH (U/l)347450Uric acid (mg/dl)3.34Ferritin (ng/ml)29167BUN3540Creatinine0.40.5ANANNCANCANNP-ANCANNACE34—RFNNACPAN—IgG (g/l)16671740IgM (g/l)122160IgA (g/l)181178IgE (g/l)10211210IL6 (IU/l)2850LAB: laboratory; WBC: white blood cell count; HCT: hematocrit test; GRA: granulocytes; LYM: lymphocytes; MON: monocytes; EOS: eosinophils; BASO: basophils; ESR: erythrocyte sedimentation rate; CRP: C-reactive protein; AST: aspartate aminotransferase; ALT: alanine aminotransferase; LDH: lactate dehydrogenase; BUN: blood urea nitrogen; ANA: antinuclear antibody; C-ANCA: antineutrophil cytoplasmic autoantibody; P-ANCA: perinuclear antineutrophil cytoplasmic antibodies; ACE: angiotensin-converting enzyme; RF: rheumatoid factor; ACPC: anti-citrullinated peptide antibody; Ig: immunoglobulin; IL: interleukin; N: negative.Echocardiography expressed normal ventricular function and no pericardial effusion. He had normal bone marrow aspiration and biopsy. Due to prolonged fever, arthritis, and an increase in acute phase reactants, the diagnosis of systemic juvenile idiopathic arthritis was established for him. Therefore, he was treated with prednisolone, methotrexate, and naproxen. At the age of three, he was readmitted to the hospital because of his inability to walk due to arthritis, persistent fever, and urticarial rash. An X-ray of the knees indicated metaphyseal irregularity, widening of growth palate, and soft tissue swelling (Figure2). In three-phase bone scintigraphy, there were inflammatory processes in several joints, including the right elbow and both knees (Figure 3). At that time, the diagnosis of autoinflammatory disorders, especially CAPS, was made for him. A genetic test was performed, and the whole exome sequencing (WES) identified a new variant in exon 5 of NLRP3 (NM-001079821: c. G1060T, p. A354S) (9). The patient was heterozygous for this mutation, while his parents were homozygous wild type. It was a de novo mutation. The patient was treated with etanercept at a dose of 0.8 mg/kg per week subcutaneously because anakinra was not available at the time. After six months of anti-TNF therapy, joint involvement relatively improved. Not only could he walk but also his fever was under control. However, he had a mild effusion in his left knee during treatment with etanercept. Furthermore, the urticarial-like rash had decreased but did not resolve completely. At the age of 4, he developed both eyelids’ swelling and erythema, which decreased his visual acuity (Figure 4). Ophthalmologic examination showed retinal vasculitis and severe optic disc edema. When anakinra was available, treatment was initiated. Anakinra was initiated at a dose of 1 mg/kg subcutaneously daily. After one month, a considerable response was observed, while full recovery occurred after four months. We reported this case in detail in our previous report [11].Figure 2
Knees X-ray shows metaphyseal irregularity, widening of growth palate, and soft tissue swelling (the first case).
(a)(b)Figure 3
Three-phase bone scintigraphy shows inflammatory processes in several joints, including both left and right knees. (a) Immediate phase and (b) delayed phase (for the first case).Figure 4
Swelling and erythema of both eyelids (the first case).
## 3. Case 2
A 2-year-old girl was referred to our clinic for periodic fever and rash. Fever often worsened at night; besides, she had abdominal pain during some febrile episodes. She had had a recurrent purpuric urticarial rash since three months (Figure1). The rash was usually accompanied by the onset of fever. The immunological evaluation result was normal, and she had been treated with antihistamines due to a history of chronic urticarial rash. She did not have a history of seizures, joint involvement, or conjunctivitis. She was the third child of the family. Her parents were blood relatives, and her siblings were healthy. She was hospitalized at the age of 1, with a diagnosis of sepsis and at the age of 3, for an evaluation of fever with unknown origin. Physical examinations revealed a high-grade fever, urticarial rash, and subcutaneous nodule in the subcostal and inguinal region. No hepatosplenomegaly or lymphadenopathy was present. There were no conjunctivitis, arthritis, or mental and physical disability. Neurologic examination results were normal. However, laboratory findings reported leukocytosis, anemia, and thrombocytosis. Erythrocyte sedimentation (ESR) and C-reactive protein (CRP) levels were elevated. The patient’s laboratory tests are listed in Table 1. Chest X-ray and echocardiography were normal. Three-phase bone scintigraphy did not report clear evidence of inflammatory or active bone lesion. Skin biopsy showed dermis vessels with plump endothelial cells, intramural and perivascular neutrophils, and few eosinophils with no evidence of granuloma or necrosis. Also, she had normal bone marrow aspiration and biopsy. She had been treated with prednisolone and ibuprofen due to a diagnosis of systemic juvenile idiopathic arthritis; however, fevers and skin rashes had not been taken under control. The autoinflammatory disease was suggested as a diagnosis. Whole exome sequencing reported a variant in exon 3 NLRP3 gene (NM_001127462: c. G1057C, p. V353L). She was heterozygous for this variant. It was a de novo mutation. She was treated with etanercept at a dose of 0.8 mg/kg per week subcutaneously. Thereafter, fever was relatively controlled, but the rash did not respond to anti-TNF therapy. Relapse occurred after four months of treatment with etanercept. Anakinra was initiated at a dose of 1 mg/kg subcutaneously daily, and a dramatic response was observed after two months.The signs and symptoms of the two patients are compared in Table2.Table 2
Signs and symptoms of cryopyrin-associated periodic syndromes cases.
Sign and symptomsCase 1Case 2Urticarial rash++Conjunctivitis−−Dysmorphic features−−Joint involvement+−Hearing loss−−Visual loss+−Aseptic meningitis−−Optic disc edema+−Intellectual disability−−
## 4. Discussion
It is important to know that autoinflammatory syndromes are rare; however, they should be considered in any patient with recurrent or persistent inflammation. Most patients with these disorders experience delays in diagnosis. Our first patient had a fever, urticarial rash, and arthritis. He had been treated with systemic juvenile idiopathic arthritis (SJIA) diagnosis, but he was diagnosed with CAPS after further evaluation. The second patient had a recurrent fever and urticarial rash, but there was no joint involvement. She was initially treated with a diagnosis of SJIA, but her final diagnosis was Muckle–Wells syndrome after more evaluation and genetic tests.The symptoms of cryopyrin-associated periodic fever syndromes are variable presented with a broad range of clinical manifestations [2]. Inheritance of CAPS is usually autosomal dominant. Additionally, the disease has a spectrum of symptoms in different generations. The severity of symptoms increases as the age goes up. For example, the disease may be seen as amyloidosis and renal failure in the first generations. However, in younger children, urticaria, and fever may be observed. CNS manifestations are one of the common clinical presentations of CINCA. In Muckle–Wells syndrome, joint involvement is mild to moderate, while severe joint involvement and deformity are more common in CINCA syndrome. Our first case had severe joint disease correlated with CINCA syndrome, but CNS manifestations and mental disability were not observed. Our first case also had optic disc edema that is usually presented in CINCA syndrome [11–15].In young children with Muckle–Wells, hearing loss and amyloidosis does not usually occur, and the only manifestation of the disease may be recurrent urticarial rash and fever. The second case had typical symptoms of Muckle–Wells, including urticaria-like rash and fever. Nevertheless, she did not have joint involvement. The primary treatment for CAPS is the IL-1 inhibitors, which can completely relieve the disease’s symptoms [10, 16, 17].Both of our patients were initially treated with anti-TNF agents because IL-1 inhibitors were unavailable. In the first case, joint involvement and fever were resolved with anti-TNF agents; yet, the urticarial rash did not respond to this therapy, and optic disc edema occurred during the anti-TNF therapy. The second case was initially treated with an anti-TNF agent (etanercept) too. Nevertheless, the response was transient, and relapse occurred after four months. Some of the CAPS manifestations, such as fever, were resolved with anti-TNF agents, but some of them did not resolve fully, and relapse might occur. After IL-1 inhibitors therapy, all of the symptoms resolved dramatically and entirely.TNF-α might play a regulatory role upstream of the NLRP3 inflammasome. Caspase 11-mediated inflammasome activation participates in driving the production of TNF-α. However, the cellular source of the TNF-α and the mechanism of generation are unclear. In patients with CAPS, proinflammatory cytokines such as IL-1B play an essential role in the development of symptoms. At least half of the patients with CAPS have a range of neurological manifestations at some course of illness. A few studies have shown that IL-1 inhibitors are effective for treating neurological symptoms and preventing severe CNS complications. The most common neurologic manifestations in CAPS are headache, aseptic meningitis, seizures, papilledema, and hearing loss. Serious neurological complications include optic atrophy and mental disability. Skin rash, fever, and arthritis are milder CAPS symptoms [17–20].
## 5. Limitations
In case reports, causal inference is not plausible. Response to the treatment could be a mere coincidence. Accordingly, the effects of anti-TNF agents on clinical presentations from the current case report of CAPS cannot be generalized.
## 6. Conclusion
Based on our experiences in this study, although TNF-α inhibitors effectively reduced mild manifestations such as fever and rash, they were not effective for improving more serious complications like papilledema and arthritis. Since CAPS is a rare disease, there are few reports of this disorder. Future studies are needed to evaluate the effect of such medical treatments on improving the various symptoms of CAPS.
---
*Source: 2898553-2022-03-03.xml* | 2898553-2022-03-03_2898553-2022-03-03.md | 15,226 | The Efficacy of Anti-Tumor Necrosis Factor Therapy in Cryopyrin-Associated Periodic Syndromes: A Report of Two Cases | Fatemeh Tahghighi; Mahdieh Vahedi; Nima Parvaneh; Mohammad Shahrooei; Vahid Ziaee | Case Reports in Genetics
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2898553 | 2898553-2022-03-03.xml | ---
## Abstract
Background. Cryopyrin-associated periodic syndromes (CAPSs) are a group of autoinflammatory disorders caused by a mutation in the NLRP3 gene. NLRP3 mutations increase inflammasome activation; therefore, IL-1 targeted therapies are frequently used in the aforementioned disorders. Case Presentation. We report two cases of CAPS in which the diagnosis was confirmed by genetic tests and an evaluation of the therapeutic response to anti-tumor necrosis factor (anti-TNF) agents. Conclusion. IL-1 inhibitors are highly effective in treating CAPS patients. Most patients with severe symptoms such as neurologic involvement improve with IL-1 blockade. Anti-TNF agents might be effective in reducing mild manifestation; however, they are not effective in improving more severe complications.
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## Body
## 1. Introduction
Cryopyrin-associated periodic syndromes (CAPS) are a group of autoinflammatory disorders caused by a gain-of-function mutation in the NLRP3 (CIAS1) gene located on the long arm of chromosome 1. CAPS are a spectrum of disorders with a range of severity. The moderate form of the CAPS is Muckle–Wells syndrome, often inherited as an autosomal dominant trait. The main clinical manifestations include recurrent episodes of fever, urticaria-like rash, and ocular and articular involvement. The severe form of the CAPS is the chronic infantile neurological cutaneous and articular (CINCA) disease that is presented with urticaria-like rash, mental delay, arthritis, and sensorineural hearing loss [1–5].Formation of NLRP3 inflammasome leads to caspase 1-mediated release of the proinflammatory cytokines such as IL-1B and IL-18. Since NLRP3 mutations can result in increased inflammasome activation and IL-1 production, IL-1 targeted therapies are used frequently in the patients. Interleukin 1 receptor antagonists such as anakinra can improve CAPS symptoms and prevent major complications such as hearing loss and amyloidosis [6–9]. Some patients with CAPS show partial response to IL-1 blockade. Other biologics such as anti-tumor necrosis factor (anti-TNF) agents are less effective than IL-1 inhibitors. In a few patients, anti-TNF agents have been able to result in partial response and improvement. TNF-α may play a role in regulating and activating the NLRP3 inflammasome [1, 2, 10].We will describe two cases of CAPS and evaluate the responses to anti-TNF agents and IL-1 inhibitors. The current study aims to describe the relative effectiveness of anti-TNF agents in improving CAPS symptoms, highlighting the role of TNF-α in the pathogenesis of the disorders.
## 2. Case 1
A 1-year-old boy was brought to our clinic with joint pain and swelling in his left ankle and knees that had lasted for more than 14 days. Since birth, he had had a recurrent urticarial rash that was not triggered by cold or other physical stimuli (Figure1). Often presented with high-grade fever, the rash lasted 24 hours and resolved without scarring. Additionally, he was treated with antihistamines for a long time due to a history of chronic urticaria. He was born premature and admitted for 60 days in the neonatal intensive care unit (NICU). His parents were not blood relatives. His older brother has a history of chronic atopic dermatitis. On examination, neurodevelopmental evaluation result was normal, but his weight and height were below the 3rd percentile for his age. He had significant synovial hypertrophy in both knees. No hepatosplenomegaly or lymphadenopathy was present. Other physical examinations indicated normal results. However, laboratory findings showed leukocytosis, anemia, and thrombocytosis. Moreover, there was an increase in acute phase reactants. The patient’s laboratory tests are listed in Table 1. Both chest X-ray and abdominal ultrasonography were normal. The left ankle and right knee sonography showed mild to moderate effusion and synovial hypertrophy.Figure 1
Urticaria-like rash on face and extremities. (c) At 10 months old, (b) at 3 years old (the first case), and (a) at 2 years old (the second case).
(a)(b)(c)Table 1
Laboratory tests of cryopyrin-associated periodic syndromes cases.
LAB (unit)Case 1Case 2WBC (µl)1610016000Hemoglobin (g/dl)7.59.5HCT (%)25.435.5Platelets (µl)567000703000GRA (%)5245LYM (%)4035MON (%)3.914.1EOS (%)44.9BASO (%)0.11ESR (mm/hr)60112CRP (mg/l)75180AST (U/l)1729ALT (U/l)1130LDH (U/l)347450Uric acid (mg/dl)3.34Ferritin (ng/ml)29167BUN3540Creatinine0.40.5ANANNCANCANNP-ANCANNACE34—RFNNACPAN—IgG (g/l)16671740IgM (g/l)122160IgA (g/l)181178IgE (g/l)10211210IL6 (IU/l)2850LAB: laboratory; WBC: white blood cell count; HCT: hematocrit test; GRA: granulocytes; LYM: lymphocytes; MON: monocytes; EOS: eosinophils; BASO: basophils; ESR: erythrocyte sedimentation rate; CRP: C-reactive protein; AST: aspartate aminotransferase; ALT: alanine aminotransferase; LDH: lactate dehydrogenase; BUN: blood urea nitrogen; ANA: antinuclear antibody; C-ANCA: antineutrophil cytoplasmic autoantibody; P-ANCA: perinuclear antineutrophil cytoplasmic antibodies; ACE: angiotensin-converting enzyme; RF: rheumatoid factor; ACPC: anti-citrullinated peptide antibody; Ig: immunoglobulin; IL: interleukin; N: negative.Echocardiography expressed normal ventricular function and no pericardial effusion. He had normal bone marrow aspiration and biopsy. Due to prolonged fever, arthritis, and an increase in acute phase reactants, the diagnosis of systemic juvenile idiopathic arthritis was established for him. Therefore, he was treated with prednisolone, methotrexate, and naproxen. At the age of three, he was readmitted to the hospital because of his inability to walk due to arthritis, persistent fever, and urticarial rash. An X-ray of the knees indicated metaphyseal irregularity, widening of growth palate, and soft tissue swelling (Figure2). In three-phase bone scintigraphy, there were inflammatory processes in several joints, including the right elbow and both knees (Figure 3). At that time, the diagnosis of autoinflammatory disorders, especially CAPS, was made for him. A genetic test was performed, and the whole exome sequencing (WES) identified a new variant in exon 5 of NLRP3 (NM-001079821: c. G1060T, p. A354S) (9). The patient was heterozygous for this mutation, while his parents were homozygous wild type. It was a de novo mutation. The patient was treated with etanercept at a dose of 0.8 mg/kg per week subcutaneously because anakinra was not available at the time. After six months of anti-TNF therapy, joint involvement relatively improved. Not only could he walk but also his fever was under control. However, he had a mild effusion in his left knee during treatment with etanercept. Furthermore, the urticarial-like rash had decreased but did not resolve completely. At the age of 4, he developed both eyelids’ swelling and erythema, which decreased his visual acuity (Figure 4). Ophthalmologic examination showed retinal vasculitis and severe optic disc edema. When anakinra was available, treatment was initiated. Anakinra was initiated at a dose of 1 mg/kg subcutaneously daily. After one month, a considerable response was observed, while full recovery occurred after four months. We reported this case in detail in our previous report [11].Figure 2
Knees X-ray shows metaphyseal irregularity, widening of growth palate, and soft tissue swelling (the first case).
(a)(b)Figure 3
Three-phase bone scintigraphy shows inflammatory processes in several joints, including both left and right knees. (a) Immediate phase and (b) delayed phase (for the first case).Figure 4
Swelling and erythema of both eyelids (the first case).
## 3. Case 2
A 2-year-old girl was referred to our clinic for periodic fever and rash. Fever often worsened at night; besides, she had abdominal pain during some febrile episodes. She had had a recurrent purpuric urticarial rash since three months (Figure1). The rash was usually accompanied by the onset of fever. The immunological evaluation result was normal, and she had been treated with antihistamines due to a history of chronic urticarial rash. She did not have a history of seizures, joint involvement, or conjunctivitis. She was the third child of the family. Her parents were blood relatives, and her siblings were healthy. She was hospitalized at the age of 1, with a diagnosis of sepsis and at the age of 3, for an evaluation of fever with unknown origin. Physical examinations revealed a high-grade fever, urticarial rash, and subcutaneous nodule in the subcostal and inguinal region. No hepatosplenomegaly or lymphadenopathy was present. There were no conjunctivitis, arthritis, or mental and physical disability. Neurologic examination results were normal. However, laboratory findings reported leukocytosis, anemia, and thrombocytosis. Erythrocyte sedimentation (ESR) and C-reactive protein (CRP) levels were elevated. The patient’s laboratory tests are listed in Table 1. Chest X-ray and echocardiography were normal. Three-phase bone scintigraphy did not report clear evidence of inflammatory or active bone lesion. Skin biopsy showed dermis vessels with plump endothelial cells, intramural and perivascular neutrophils, and few eosinophils with no evidence of granuloma or necrosis. Also, she had normal bone marrow aspiration and biopsy. She had been treated with prednisolone and ibuprofen due to a diagnosis of systemic juvenile idiopathic arthritis; however, fevers and skin rashes had not been taken under control. The autoinflammatory disease was suggested as a diagnosis. Whole exome sequencing reported a variant in exon 3 NLRP3 gene (NM_001127462: c. G1057C, p. V353L). She was heterozygous for this variant. It was a de novo mutation. She was treated with etanercept at a dose of 0.8 mg/kg per week subcutaneously. Thereafter, fever was relatively controlled, but the rash did not respond to anti-TNF therapy. Relapse occurred after four months of treatment with etanercept. Anakinra was initiated at a dose of 1 mg/kg subcutaneously daily, and a dramatic response was observed after two months.The signs and symptoms of the two patients are compared in Table2.Table 2
Signs and symptoms of cryopyrin-associated periodic syndromes cases.
Sign and symptomsCase 1Case 2Urticarial rash++Conjunctivitis−−Dysmorphic features−−Joint involvement+−Hearing loss−−Visual loss+−Aseptic meningitis−−Optic disc edema+−Intellectual disability−−
## 4. Discussion
It is important to know that autoinflammatory syndromes are rare; however, they should be considered in any patient with recurrent or persistent inflammation. Most patients with these disorders experience delays in diagnosis. Our first patient had a fever, urticarial rash, and arthritis. He had been treated with systemic juvenile idiopathic arthritis (SJIA) diagnosis, but he was diagnosed with CAPS after further evaluation. The second patient had a recurrent fever and urticarial rash, but there was no joint involvement. She was initially treated with a diagnosis of SJIA, but her final diagnosis was Muckle–Wells syndrome after more evaluation and genetic tests.The symptoms of cryopyrin-associated periodic fever syndromes are variable presented with a broad range of clinical manifestations [2]. Inheritance of CAPS is usually autosomal dominant. Additionally, the disease has a spectrum of symptoms in different generations. The severity of symptoms increases as the age goes up. For example, the disease may be seen as amyloidosis and renal failure in the first generations. However, in younger children, urticaria, and fever may be observed. CNS manifestations are one of the common clinical presentations of CINCA. In Muckle–Wells syndrome, joint involvement is mild to moderate, while severe joint involvement and deformity are more common in CINCA syndrome. Our first case had severe joint disease correlated with CINCA syndrome, but CNS manifestations and mental disability were not observed. Our first case also had optic disc edema that is usually presented in CINCA syndrome [11–15].In young children with Muckle–Wells, hearing loss and amyloidosis does not usually occur, and the only manifestation of the disease may be recurrent urticarial rash and fever. The second case had typical symptoms of Muckle–Wells, including urticaria-like rash and fever. Nevertheless, she did not have joint involvement. The primary treatment for CAPS is the IL-1 inhibitors, which can completely relieve the disease’s symptoms [10, 16, 17].Both of our patients were initially treated with anti-TNF agents because IL-1 inhibitors were unavailable. In the first case, joint involvement and fever were resolved with anti-TNF agents; yet, the urticarial rash did not respond to this therapy, and optic disc edema occurred during the anti-TNF therapy. The second case was initially treated with an anti-TNF agent (etanercept) too. Nevertheless, the response was transient, and relapse occurred after four months. Some of the CAPS manifestations, such as fever, were resolved with anti-TNF agents, but some of them did not resolve fully, and relapse might occur. After IL-1 inhibitors therapy, all of the symptoms resolved dramatically and entirely.TNF-α might play a regulatory role upstream of the NLRP3 inflammasome. Caspase 11-mediated inflammasome activation participates in driving the production of TNF-α. However, the cellular source of the TNF-α and the mechanism of generation are unclear. In patients with CAPS, proinflammatory cytokines such as IL-1B play an essential role in the development of symptoms. At least half of the patients with CAPS have a range of neurological manifestations at some course of illness. A few studies have shown that IL-1 inhibitors are effective for treating neurological symptoms and preventing severe CNS complications. The most common neurologic manifestations in CAPS are headache, aseptic meningitis, seizures, papilledema, and hearing loss. Serious neurological complications include optic atrophy and mental disability. Skin rash, fever, and arthritis are milder CAPS symptoms [17–20].
## 5. Limitations
In case reports, causal inference is not plausible. Response to the treatment could be a mere coincidence. Accordingly, the effects of anti-TNF agents on clinical presentations from the current case report of CAPS cannot be generalized.
## 6. Conclusion
Based on our experiences in this study, although TNF-α inhibitors effectively reduced mild manifestations such as fever and rash, they were not effective for improving more serious complications like papilledema and arthritis. Since CAPS is a rare disease, there are few reports of this disorder. Future studies are needed to evaluate the effect of such medical treatments on improving the various symptoms of CAPS.
---
*Source: 2898553-2022-03-03.xml* | 2022 |
# Metabolic and Molecular Events Occurring during Chromoplast Biogenesis
**Authors:** Wanping Bian; Cristina Barsan; Isabel Egea; Eduardo Purgatto; Christian Chervin; Mohamed Zouine; Alain Latché; Mondher Bouzayen; Jean-Claude Pech
**Journal:** Journal of Botany
(2011)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2011/289859
---
## Abstract
Chromoplasts are nonphotosynthetic plastids that accumulate carotenoids. They derive from other plastid forms, mostly chloroplasts. The biochemical events responsible for the interconversion of one plastid form into another are poorly documented. However, thanks to transcriptomics and proteomics approaches, novel information is now available. Data of proteomic and biochemical analysis revealed the importance of lipid metabolism and carotenoids biosynthetic activities. The loss of photosynthetic activity was associated with the absence of the chlorophyll biosynthesis branch and the presence of proteins involved in chlorophyll degradation. Surprisingly, the entire set of Calvin cycle and of the oxidative pentose phosphate pathway persisted after the transition from chloroplast to chromoplast. The role of plastoglobules in the formation and organisation of carotenoid-containing structures and that of theOr gene in the control of chromoplastogenesis are reviewed. Finally, using transcriptomic data, an overview is given the expression pattern of a number of genes encoding plastid-located proteins during tomato fruit ripening.
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## Body
## 1. Introduction
Chromoplasts are nonphotosynthetic plastids that accumulate carotenoids and give a bright colour to plant organs such as fruit, flowers, roots, and tubers. They derive from chloroplasts such as in ripening fruit [1], but they may also arise from proplastids such as in carrot roots [2] or from amyloplasts such as in saffron flowers [3] or tobacco floral nectaries [4]. Chromoplasts are variable in terms of morphology of the carotenoid-accumulating structures and the type of carotenoids [5, 6]. For instance, in tomato, lycopene is the major carotenoid, and it accumulates in membrane-shaped structures [7] while in red pepper beta-carotene is prominent and accumulates mostly in large globules [8]. Reviews specifically dedicated to the biogenesis of chromoplasts have been published [9–11]. Some information can also be found in papers dedicated to plastid differentiation in general [12, 13]. Thanks to transcriptomics and proteomics approaches, novel information is now available on the biochemical and molecular aspects of chromoplasts differentiation [14–16]. The present paper will review these novel data and provide a recent view of the metabolic and molecular events occurring during the biogenesis of chromoplasts and conferring specificities to the organelle. Focus will be made on the chloroplast to chromoplast transition.
## 2. Chromoplast Differentiation Is Associated with Important Structural, Metabolic, and Molecular Reorientations
Important structural changes occur during the chloroplast to chromoplast transition, thylakoid disintegration being the most significant (Figure1). Early microscopic observations have shown that plastoglobuli increase in size and number during the chloroplast-chromoplast transition [7] and that the internal membrane system is profoundly affected at the level of the grana and intergrana thylakoids [17]. Stromules (stroma-filled tubules) that are dynamic extensions of the plastid envelope allowing communication between plastids and other cell compartments like the nucleus [18] are also affected during chromoplastogenesis. A large number of long stromules can be found in mature chromoplasts contrasting with the few small stromules of the chloroplasts in green fruit [19]. It can therefore be assumed that the exchange of metabolites between the network of plastids and between the plastids and the cytosol is increased in the chromoplast as compared to the chloroplast. However, the most visible structural change is the disruption of the thylakoid grana, the disappearance of chlorophyll, and the biogenesis of carotenoid-containing bodies. Associated with the structural changes, the toc/tic transmembrane transport machinery is disintegrated [16, 20]. The noncanonical signal peptide transport [21] and intracellular vesicular transport [22, 23] may represent the most active form of trans-membrane transport into the chromoplast as compared to the chloroplast. Proteins involved in vesicular transport were detected in the tomato chromoplastic proteome [16].Figure 1
Schematic representation of the main structural changes occurring during the chloroplast to chromoplast transition.One of the most visible metabolic changes occurring during the chloroplast to chromoplast transition is the loss of chlorophyll and the accumulation of carotenoids [24]. A spectral confocal microscopy analysis of carotenoids and chlorophylls has been carried out during the chloroplast to chromoplast transition in tomato fruit, including a time-lapse recording on intact live tissue [25]. Details of the early steps of tomato chromoplast biogenesis from chloroplasts are provided at the cellular level that show the formation of intermediate plastids containing both carotenoids and chlorophylls. This study also demonstrated that the chloroplast to chromoplast transition was synchronous for all plastids of a single cell and that all chromoplasts derived from preexisting chloroplasts.The photosynthetic machinery is strongly disrupted and a reduction in the levels of proteins and mRNAs associated with photosynthesis was observed [26]. Also the decrease in photosynthetic capacity during the later stages of tomato fruit development was confirmed by transcriptomic data [27]. However, part of the machinery persist in the chromoplast. It has been suggested that it participates in the production of C4 acids, in particular malate a key substrate for respiration during fruit ripening [28]. In the tomato chromoplast proteome, all proteins of the chlorophyll biosynthesis branch are lacking [16]. In the early stages of tomato fruit ripening, the fruits are green and the plastids contain low levels of carotenoids that are essentially the same as in green leaves, that is, mainly β-carotene, lutein, and violaxanthin. At the “breaker” stage of ripening, lycopene begins to accumulate and its concentration increases 500-fold in ripe fruits, reaching ca.70 mg/g fresh weight [24]. During the ripening of tomato fruit, an upregulation of the transcription ofPsyand Pds, which encode phytoene synthase and phytoene desaturase, respectively, was reported [29]. One of the main components of the carotenoid-protein complex, a chromoplast-specific 35-kD protein (chrC), has been purified and characterized in Cucumis sativus corollas. It showed increasing steady-state level in parallel with flower development and carotenoid accumulation, with a maximum in mature flowers [30]. In tomato, concomitantly with increased biosynthesis of lycopene, the processes for splitting into β and γ carotene were absent [16]. The mRNAs of CrtL-band CrtL-e were strongly downregulated during fruit ripening [29]. They encode lycopene β-cyclase and ε-cyclase, enzymes involved in the cyclization of lycopene leading to the formation of β and δ carotene, respectively. In these conditions, the low rate of cyclization and splitting contributes to the accumulation of lycopene in ripe tomato fruit.In terms of reactive oxygen species, antioxidant enzymes are upregulated during chromoplast development, and lipids, rather than proteins, seem to be a target for oxidation. In the chromoplasts, an upregulation in the activity of superoxide dismutase and of components of the ascorbate-glutathione cycle was observed [31].The plastid-to-nucleus signaling also undergoes important changes. In the chromoplast, the main proteins involved in the synthesis of Mg-protoporphyrin IX, a molecule supposed to play an important role in retrograde signaling [32] is absent, but other mechanisms such as hexokinase 1 or calcium signaling were present [16]. The plastid-nucleus communication is still an open subject with many still unanswered questions.
## 3. A Number of Metabolic Pathways Are Conserved during Chromoplast Differentiation
The comparison of data arising from proteomics of the chloroplast [33] and of the chromoplast [16] as well as biochemical analysis of enzyme activities suggest that several pathways are conserved during the transition from chloroplast to chromoplast. Such is the case for (i) the Calvin cycle which generates sugars from CO2, (ii) the oxidative pentose phosphate pathway (OxPPP) which utilizes the 6 carbons of glucose to generate 5 carbon sugars and reducing equivalents, and (iii) many aspects of lipid metabolism (Figure 2). Activities of enzymes of the Calvin cycle have been measured in plastids isolated from sweet pepper. They may even be higher in chromoplasts than in chloroplasts [34] In ripening tomato fruits, several enzymes of the Calvin cycle (hexokinase, fructokinase, phosphoglucoisomerase, pyrophosphate-dependent phosphofructokinase, triose phosphate isomerase, glyceraldehyde 3-phosphate dehydrogenase, phosphoglycerate kinase, and glucose 6-phosphate dehydrogenase) are active [35]. The activity of glucose 6-phosphate dehydrogenase (G6PDH), a key component of the OxPPP, was higher in fully ripe tomato fruit chromoplasts than in leaves or green fruits [36]. Also, a functional oxidative OxPPP has been encountered in isolated buttercup chromoplasts [37]. Proteomic analysis have demonstrated that an almost complete set of proteins involved in the OxPPP are present in isolated tomato fruit chromoplasts (Figure 2). The persistence of the Calvin cycle and the OxPPP cannot be related to photosynthesis since the photosynthetic system is disrupted. In nonphotosynthetic plastids, the Calvin cycle could provide reductants and also precursors of nucleotides and aromatic aminoacids to allow the OxPPP cycle to function optimally [16].Presence of proteins of the Calvin cycle in the tomato chromoplastic proteome. Proteins are indicated by white squares inside black frames and represented by their generic name and unigene SGN code. Numbers represent the position of the protein in the cycle. Data are derived from [16].
(a)(b)Starch transiently accumulates in young tomato fruit and undergoes almost complete degradation by maturity. In fact, starch accumulation results from an unbalance between synthesis and degradation. Enzymes capable of degrading starch have been detected in the plastids of tomato fruit. In addition, tomato fruit can synthesize starch during the period of net starch breakdown, illustrating that these two mechanisms can coexist [38]. As indicated in Figure 3, proteins for starch synthesis have been encountered in the tomato chromoplast (ADP-glucose pyrophosphorylase, starch synthase, and starch branching enzyme). In addition, the system for providing neutral sugars to the starch biosynthesis pathway is complete including the glucose-6P-translocator which imports sugars from the cytosol. The presence of active import of glucose-6P, but not glucose-1P, had been demonstrated in buttercup chromoplasts [37]. Although some starch granules may be present in ripe tomatoes, the amount of starch is strongly reduced [39]. The most probable explanation is that starch undergoes rapid turnover with intense degradation. This assumption is supported by the presence in the tomato chromoplast of most of the proteins involved in starch degradation (Figure 3). Particularly interesting is the presence of one glucan-water dikinase (GWD), one phospho-glucan-dikinase (PWD), and one phospho-glucan-phosphatase (PGP) that facilitate the action of β-amylases [40]. Mutants of these proteins, named starch excess (SEX1 corresponding to GWD and SEX4 to PGP), accumulate large amounts of starch [40]. In agreement with the above-mentioned hypothesis, high activity of β-amylase has been found during apple and pear fruit ripening at a time where starch has disappeared [41]. The presence of a glucose translocator for the export of sugars generated by starch degradation represents another support to the functionality of the starch metabolism pathways in chromoplasts. In olive fruit, a high expression of a glucose transporter gene was observed at full maturity when the chromoplasts were devoid of starch [42]. Nevertheless, the enzymatic activity of all of the proteins remains to be demonstrated inasmuch as posttranslational regulation of enzymes of starch metabolism has been reported [43] including protein phosphorylation [44]. Interestingly, orthologs of the 14-3-3 proteins of the μ family of Arabidopsis involved in the regulation of starch accumulation [45] are present in the tomato chromoplastic proteome (Figure 3). The 14-3-3 proteins participate in the phosphorylation-mediated regulatory functions in plants.Presence of proteins of the starch synthesis and degradation pathways, of posttranslational regulation of starch synthesis, and of sugar translocators in the tomato chromoplastic proteome. Proteins are indicated by white squares inside black frames and represented by their generic name and unigene SGN code. Numbers represent the position of the protein in the cycle. Data are derived from [16].
(a)(b)In chloroplasts, thylakoid membranes, as well as envelope membranes, are rich in galactolipids and sulfolipids [46]. Lipid metabolism is also highly active in the chromoplasts. Despite thylakoid disassembly, new membranes are synthesized such as those participating in the formation of carotenoid storage structures. These newly synthesized membranes are not derived from the thylakoids but rather from vesicles generated from the inner membrane of the plastid [47]. Key proteins for the synthesis of phospholipids, glycolipids, and sterols were identified [16] along with some proteins involved in the lipoxygenase (LOX) pathway. They have been described in the chloroplast, and they lead to the formation oxylipins, which are important compounds for plant defense responses [48]. In the tomato chromoplast, all proteins potentially involved in the LOX pathway leading to the generation of aroma volatiles were found [16].The shikimate pathway, which is present in microorganisms and plants and never in animals, is a branch point between the metabolism of carbohydrates and aromatic compounds. It leads to the biosynthetic of the aromatic amino acids tyrosine, tryptophan, and phenylalanine [49]. The presence of an active shikimate pathway has been demonstrated in chromoplasts isolated from wild buttercup petals by measuring the activity of the shikimate oxidoreductase [50], and a number of proteins involved in the shikimate pathway have been encountered in the tomato chromoplast proteome [16]. The aromatic amino acids derived from the shikimate pathway are the precursors of a number of important secondary metabolites. Tyrosine is the precursor of tocopherols and tocotrienols. Tryptophane is involved in the synthesis of indole alkaloids which are essential for the generation of some glucosinolates, terpenoids, and tryptamine derivatives [50]. Phenylalanine is the precursor of several classes of flavonoids, including anthocyanins. It is also a precursor for the biosynthesis of volatile compounds which are important for fruit flavor and flower scent, eugenol, 2-phenylacetaldehyde and, 2-phenylethanol [51, 52]. In tomato fruit, for instance, 2-phenylacetaldehyde and 2-phenylethanol are generated from phenylalanine by an aromatic amino acid decarboxylase and a phenylacetaldehyde reductase, respectively [53, 54]. Nevertheless, there is no indication that the synthesis of the secondary metabolites derived from the shikimate pathway takes place in the chromoplast.During fruit ripening, an increased synthesis ofα-tocopherol was observed [55]. The biosynthesis of α-tocopherol was localized in the envelope membranes of the Capsicum annum [56], and the almost complete set of proteins of the pathway were present in the tomato chromoplast [16]. The accumulation of α-tocopherol, by protecting membrane lipids against oxidation, may contribute to delaying senescence [57].
## 4. Plastoglobuli, Plastoglobules, and the Chloroplast-to-Chromoplast Transition
Plastoglobules are lipoprotein particles present in chloroplasts (Figure1) and other plastids. They have been recently recognized as participating in some metabolic pathways [58]. For instance, plastoglobules accumulate tocopherols and harbor a tocopherol cyclase, an enzyme catalyzing the conversion of 2,3-dimethyl-5-phytyl-1,4-hydroquinol to γ-tocopherol [59]. Plastoglobuli also accumulate carotenoids as crystals or as long tubules named fibrils [60, 61]. Part of the enzymes involved in the carotenoid biosynthesis pathway (ζ-carotene desaturase, lycopene β cyclase, and two β-carotene β hydroxylases) were found in the plastoglobuli [62].Plastoglobules arise from a blistering of the stroma-side leaflet of the thylakoid membrane [63], and they are physically attached to it [45]. During the chloroplast-to-chromoplast transition, a change in the size and number of plastoglobuli was observed (Figure 1). They are larger and more numerous than in the chloroplast [7]. Plastoglobules are the predominant proteins of plastoglobules. Several types of plastoglobules have been described: fibrillin, plastid lipid-associated proteins (PAP) and carotenoid-associated protein (CHRC). All plastoglobules participate in the accumulation of carotenoids in the plastoglobule structure. Carotenoids accumulate as fibrils to form supramolecular lipoprotein structures. A model for fibril assembly has been proposed in which the core is occupied by carotenoids that interact with polar galacto- and phospho-lipids. Fibrillin molecules are located at the periphery in contact with the plastid stroma [64]. In tomato, the overexpression of a pepper fibrillin caused an increase in carotenoid and carotenoid-derived flavour volatiles [47] along with a delayed loss of thylakoids during the chloroplast-to-chromoplast transition. In fibrillin overexpressing tomato, the plastids displayed a typical chromoplastic zone contiguous with a preserved chloroplastic zone. PAP is another major protein of plastoglobules that also participates in the sequestration of carotenoids [64, 65]. As for CHRC, its downregulation resulted in a 30% reduction of carotenoids in tomato flowers [66]. Plastoglobuli are, therefore, complex assemblies that play a key role in carotenoid metabolism and greatly influence the evolution of the internal structure of the plastid during the chloroplast to chromoplast transition.
## 5. A key Player in Chromoplast Differentiation: TheOr Gene
TheOr gene was discovered in cauliflower where the dominant mutation Or conferred an orange pigmentation with the accumulation of β-carotene mostly in the inflorescence [67]. The Or gene was isolated by positional cloning [68]. It is localized in the nuclear genome and is highly conserved among divergent plant species [69]. The Or protein corresponds to plastid-targeted a DnaJ-like co-chaperone with a cysteine-rich domain lacking the J-domain [68]. DnaJ proteins are known for interacting with Hsp70 chaperones to perform protein folding, assembly, disassembly, and translocation. The Or mutation is not a loss of function mutation as indicated by the absence of phenotype upon RNAi silencing. It is probably a dominant-negative mutation affecting the interaction with Hsp70 chaperones [70]. The OR mutants displayed an arrest in plastid division so that a limited number of chromoplasts (one or two) were present in the affected cells [71]. Potato tubers over-expressing the Or gene accumulate carotenoids [69]. In the OR mutant, the expression of carotenoid biosynthetic genes was unaffected and chromoplasts differentiated normally with membranous inclusions of carotenoids similar to those of carrot roots. It is concluded that the Or gene is not involved in carotenoid biosynthesis but rather creates a metabolic sink for carotenoid accumulation through inducing the formation of chromoplasts [72].
## 6. Transcriptional and Translational Activity in the Plastid Undergo Subtle Changes during Chromoplast Biogenesis
Most proteins present in the plastid are encoded by nuclear genes. The plastid genome encodes around 84 proteins [60]. Restriction enzyme analysis between chloroplasts of leaves and chromoplasts of tomato fruit indicates the absence of rearrangements, losses, or gains in the chromoplastic DNA [61]. During chromoplast differentiation, the global transcriptional activity is stable, except for a limited number of genes such as accD, encoding a subunit of the acetyl-CoA carboxylase involved in fatty acid biosynthesis, trnA (tRNA-ALA), and rpoC2 (RNA polymerase subunit) [15]. Polysome formation within the plastids declined during ripening suggesting that, while the overall RNA levels remain largely constant, plastid translation is gradually downregulated during chloroplast-to-chromoplast differentiation. This trend was particularly pronounced for the photosynthesis gene group. A single exception was observed; the translation of accD stayed high and even increased at the onset of ripening [15].Specific studies of few plastid-localized genes have been carried out. Genes involved in photosynthesis were, as expected, downregulated during chromoplast formation [25]. However, an upregulation of the large subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase and the 32 kD photosystem II quinone binding protein genes has been observed in the chromoplasts of squash fruits (Cucurbitae pepo) [62]. A possible explanation would be that these genes could be regulated independently from the plastid differentiation processes. Genes involved in carotenoid biosynthesis such as the lycopeneβ-cyclase (CYCB) were upregulated during chromoplast formation in many plants including the wild species of tomato Solanum habrochaites [63].
## 7. Changes in Gene Expression during Chromoplast Differentiation in Ripening Tomato
The availability of proteomic data of tomato chromoplasts [16] and expression data of a wide range of tomato genes (The Tomato Expression Database: http://ted.bti.cornell.edu) [73] allowed classifying genes encoding chromoplastic proteins according to their expression pattern (Table 1). Among the 87 unigenes whose encoded proteins are located in the chromoplast, the biggest functional class corresponds to genes involved in photosynthesis. Most of them (18 out of 24) are either permanently (Table 1(c)) or transiently (Table 1(e)) downregulated at the breaker stage. This is in agreement with the dramatic decrease in the photosynthetic activity of the chromoplast. Three of them show constant expression (Table 1(a): U313693 ATP synthase delta chain; U312985 glycine cleavage system H protein; U312532 oxygen-evolving enhancer protein) and three upregulation (Table 1(b): U312690 plastocyanin; U312593 chlorophyll A-B binding protein 4; U314994 phosphoglycolate phosphatase). In the case of Calvin cycle, 5 out of 12 genes (U312344 fructose-bisphosphate aldolase; U312608 fructose-bisphosphate aldolase; U312609 fructose-bisphosphate aldolase; U314254 ribulose bisphosphate carboxylase small chain 1A; U314701 ribulose bisphosphate carboxylase small chain 3B) had a constant decrease during chromoplast differentiation (Table 1(c)). In tomato fruit, the activity of the ribulose-1,5-bisphosphate carboxylase/oxygenase had a constant decrease during fruit ripening [74], which is in line with the transcriptomic and proteomic data. The genes encoding fructose-bisphosphate aldolase isoforms presented different expression profiles being either up- (U314788) or down- (U312344) regulated during tomato fruit ripening. An increase in overall transcript levels for the fructose-1,6-bisphosphate aldolase has been described during ripening [75]. The importance of transcripts and enzyme activity of the various isoforms are unknown. The remaining genes involved in the Calvin cycle showed either increased (Table 1(b); U312802 glyceraldehyde-3-phosphate dehydrogenase B; U312538 RuBisCO subunit binding-protein) or unchanged expression (Table 1(a); U316424 fructose-1,6-bisphosphatase; U312544 ribulose bisphosphate carboxylase/-oxygenase activase). Three genes coding for the OxPPP were found: two of them exhibited a transient increase in expression at the breaker stage (Table 1(d): U315528 ribose 5-phosphate isomerase-related; U332994 6-phosphogluconate dehydrogenase family protein) and one a transient decrease (Table 1(e): U315064 transaldolase). The 3 genes involved in tetrapyrrole biosynthesis are not part of the chlorophyll synthesis branch and all of them had an increased expression (Table 1(b): U315993 coproporphyrinogen III oxidase; U315267 uroporphyrinogen decarboxylase; U315567 hydroxymethylbilane synthase), suggesting that the synthesis of tetrapyrroles continues during the transition from chloroplast to chromoplast. As expected, most of the genes (5 out of 6) coding for enzymes involved in carotenoid synthesis showed continuous (Table 1(b): U314429 phytoene synthase; U315069 isopentenyl-diphosphate delta-isomerase II; U316915 geranylgeranyl pyrophosphate synthase; U318137 phytoene dehydrogenase) or transient (Table 1(d): U313450 geranylgeranyl reductase) upregulation. The precursors for carotenoid production are synthesized through the methylerythritol phosphate (MEP) pathway. The gene encoding hydroxymethylbutenyl 4-diphosphate synthase (HDS) (U314139) downstream in the pathway has stable expression (Table 1(a)). This is consistent with previous studies that showed that there were no significant changes in HDS gene expression during tomato fruit ripening [76].Table 1
Expression profile analysis of 87 genes whose products are targeted to tomato chromoplasts (*).
Photosystem: U313693 ATP synthase delta chain; U312985 glycine cleavage system H protein; U312532 oxygen-evolving enhancer protein. Calvin cycle: U316424 fructose-1, 6-bisphosphatase; U312544 ribulose bisphosphate carboxylase/-oxygenase activase.Secondary metabolism: U314139 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase.Photosystem: U312690 plastocyanin; U312593 chlorophyll A-B binding protein 4; U314994 phosphoglycolate phosphatase.Calvin cycle: U314788 fructose-bisphosphate aldolase; U312802 glyceraldehyde-3-phosphate dehydrogenase B; U312538 RuBisCO subunit binding-protein.Redox: U314092 L-ascorbate peroxidase; U319145 thioredoxin family protein; U320487 monodehydroascorbate reductase.Amino acid metabolism: U321505 anthranilate synthase; U317466 3-phosphoshikimate 1-Carboxyvinyltransferase; U317564 tryptophan synthase.Lipid metabolism: U315474 3-oxoacyl-(acyl-carrier-protein) synthase I; U315475 3-oxoacyl-(acyl-carrier-protein) synthase I; U313753 pyruvate dehydrogenase E1 component. Major CHO metabolism: U315116 starch excess protein (SEX1); U333011 isoamylase, putative; U312423 1, 4-alpha-glucan branching enzyme; U312427 1, 4-alpha-glucan branching enzyme.Secondary metabolism: U314429 phytoene synthase; U315069 isopentenyl-diphosphate delta-isomerase II; U316915 geranylgeranyl pyrophosphate synthase; U318137 phytoene dehydrogenase.Tetrapyrrole synthesis: U315993 coproporphyrinogen III oxidase; U315267 uroporphyrinogen decarboxylase; U315567 hydroxymethylbilane synthase.Mitochondrial electron transport: U316255 NADH-ubiquinone oxidoreductase.Fermentation, ADH: U314358 alcohol dehydrogenase (ADH).Miscellaneous, cytochrome P450: U313813 NADPH-cytochrome p450 reductase.S-assimilation. APS: U313496 sulfate adenylyltransferase 1.Development unspecified: U316277 senescence-associated protein (SEN1).Cell organisation: U313480 plastid lipid-associated protein PAP, putative. Hormone metabolism: U315633 lipoxygenase. N-metabolism ammonia metabolism: U323261 glutamate synthase (GLU1).Stress abiotic heat: U315717 HS protein 70.Not assigned, No ontology: U317890 hydrolase, alpha/beta fold family protein.Photosystem: U312531 oxygen-evolving enhancer protein; U313447 photosystem I reaction center subunit IV; U313204 chlorophyll A-B binding protein 2; U313245 ATP synthase gamma chain 1; U312436 chlorophyll A-B binding protein; U313211 chlorophyll A-B binding protein 2; U313212 chlorophyll A-B binding protein 2; U313213 chlorophyll A-B binding protein 2; U312572 photosystem II oxygen-evolving complex 23 (OEC23); U314260 photosystem I reaction center subunit III family protein.Calvin cycle: U312344 fructose-bisphosphate aldolase; U312608 fructose-bisphosphate aldolase; U312609 fructose-bisphosphate aldolase; U314254 ribulose bisphosphate carboxylase small chain 1A; U314701 ribulose bisphosphate carboxylase small chain 3B.Lipid metabolism: U319207 phosphatidylglycerol phosphate synthase (PGS1).Redox: U313537 dehydroascorbate reductase.Major CHO metabolism: U316416 glucan phosphorylase, putative. N-metabolism: U314517 glutamine synthetase (GS2).Amino acid metabolism: U317344 bifunctional aspartate kinase/homoserine dehydrogenase; U320667 cystathionine beta-lyase.Redox: U314061 peroxiredoxin Q; U314093 L-ascorbate peroxidase, thylakoid-bound (tAPX); U314923 2-cys peroxiredoxin.OPP, Nonreductive PP: U315528 ribose 5-phosphate isomerase related; U332994 6-phosphogluconate dehydrogenase family protein; U316131 6-phosphogluconate dehydrogenase NAD-binding domain-containing protein.Secondary metabolism: U317741 acetyl coenzyme A carboxylase carboxyl transferase alpha subunit family; U313450 geranylgeranyl reductase.Amino acid metabolism: U317245 tryptophan synthase related.N-metabolism ammonia metabolism: U317524 ferredoxin-nitrite reductase.Lipid metabolism: U315697 enoyl-(acyl-carrier protein) reductase (NADH) U321151 lipoxygenase. Transport metabolite: U312460 triose phosphate/phosphate translocator, putative. Signalling calcium: U315961 calnexin 1 (CNX1).Photosystem: U312843 chlorophyll A-B binding protein; U312858 cytochrome B6-F complex iron-sulfur subunit; U313214 chlorophyll A-B binding protein 2; U312791 phosphoribulokinase (PRK); U317040 photosystem II reaction center PsbP family protein; U312449 chlorophyll A-B binding protein CP26; U312661 chlorophyll A-B binding protein CP29 (LHCB4); U313789 ATP synthase family.Calvin cycle: U312461 glyceraldehyde 3-phosphate dehydrogenase A; U312871 oxygen-evolving enhancer protein 3.Redox: U315728 glutathione peroxidase.OPP nonreductive PP transaldolase: U315064 transaldolase. Signaling calcium: U318939 calcium-binding EF hand family protein.Major CHO metabolism: U313315 beta amylase.(*) Genes represented in this table are filtered from TED database [64] crossing with the proteins described by Barsan et al. [16]. The expression profiles were clustered with the Bioinformatics tools of the Matlab (MathWorks) software package and further reduced to five representative expression profiles according to their general tendencies represented in the first column. The expression values used in this analysis were taken from experiment E011 from TED database. Relative expression refers to the ratio between the expression values of each ripening point and MG. All data were normalized by the mean and log2 transformed. (a) Genes that remain stable during the ripening, (b) genes that have an increase or (c) a decrease until breaker stage and then reaches a plateau, (d) genes that have a positive or (e) negative transient expression around the breaker stage. (MG, mature green; B-1, 1 d before breaker; B, breaker stage; B + 1, 1 d after breaker; B + 5, 5 d after breaker; B + 10, 10 d after breaker.)In the case of lipid metabolism, three genes showed increased expression (Table1(b): U315474 3-oxoacyl-(acyl-carrier-protein) synthase I; U315475 3-oxoacyl-(acyl-carrier-protein) synthase I; U313753 pyruvate dehydrogenase E1 component), and two genes had transient increase (Table 1(d): U315697 enoyl-(acyl-carrier protein) reductase (NADH); U321151 lipoxygenase). Phosphatidylglycerol phosphate synthase showed decreased expression (Table 1(c)). This enzyme is involved in the biosynthesis of phosphatidylglycerol and is considered as playing an important role in the ordered assembly and structural maintenance of the photosynthetic apparatus in thylakoid membranes and in the functioning of the photosystem II [77]. The downregulation of this gene during chromoplast differentiation is consistent with thylakoid disintegration and photosynthesis disappearance.Four genes of the starch metabolism present upregulation (Table1(b)). Two of them are part of the starch biosynthesis (U312423 1,4-alpha-glucan branching enzyme; U312427 1, 4-alpha-glucan branching enzyme), and one of them is involved starch degradation U315116 starch excess protein (SEX1). The fourth one, an isoamylase (U333011) can participate either in starch degradation or in starch synthesis, depending on the isoform [78]. The expression of the gene that codes a starch degrading glucan phosphorylase (U316416) decreases, and the expression of another starch degrading gene, beta-amylase (U313315), has a negative transient expression (Table 1(b)). In addition, proteomic studies have shown the presence of two starch excess proteins (SEX1 and 4) that probably contribute to the absence of starch accumulation [16]. Starch is degraded during the chloroplast to chromoplast transition to provide carbon and energy necessary to sustain the metabolic activity during fruit ripening. Several enzymes are responsible for the processes, each one possessing several isoforms with different regulatory mechanisms [78].Interestingly genes involved in aroma production such asADH (U314358) or LOXC (U315633) had a constant increase in gene expression (Table 1(b)). This could be related to the increase in aroma production via the LOX pathway.The microarray data discussed in this section cover a wide range of the tomato transcriptome. However, several isoforms of several genes are not represented in the database, which could explain some contradictory patterns of expression encountered in our analysis. Nevertheless, although not providing a full picture of the molecular events occuring during the chloroplast to chromoplast transition, these data confirm the regulation at the transcriptional level of the most salient events.
## 8. Conclusions and Perspectives
With the advent of high throughput technologies, great progress has been made in the recent years in the elucidation of the structure and function of plastids. The most important data obtained in the area have been generated for the chloroplast of Arabidopsis. Much less information is available for the chromoplast. However, recent studies with bell pepper [14] and tomato fruit [16] have allowed assigning to chromoplasts a number of proteins around 1000, which is in the same order of magnitude as Arabidopsis chloroplasts [33]. This number is, however, much lower than the number of proteins predicted to be located in the plastid which has been estimated at up to 2700 [79] or even 3800 [80]. The increased sensitivity of the mass spectrometry technologies associated with efficient methods of purification of plastids, particularly chromoplasts, will allow in the future identifying more proteins. So far, changes in the proteome have not been described during the differentiation of chromoplast. Such studies imply the development of efficient protocols for isolating plastids at different stages of differentiation during chromoplastogenesis. The combination of proteomics and transcriptomics may also give novel information on the process in a near future. The discovery of the Or gene has been a great step forward to the understanding of the molecular determinism of chromoplast differentiation. There is a need to better understand the regulatory mechanism controlling the expression of the Or gene. Many genes encoding for plastidial proteins are regulated by the plant hormone ethylene and, therefore, participate in the transcriptional regulation of the fruit ripening process in general [81, 82]. Other hormones such as ABA and auxin may also be involved. Interactions between hormones and other signals (light, for instance) during chromoplast differentiation represent another field of investigation to be explored. Because most of the proteins present in the chromoplast are encoded by nuclear genes, it will be important in future to better understand the changes occurring in the processes of transport of proteins to the chromoplast. It is suspected that vesicular transport is gaining importance, but more experimental evidence is required. Finally the dialog between the nucleus and the chromoplast and the signals involved needs to be explored. So far most of the studies in this area have been carried out with chloroplasts [83].In conclusion, important steps forward have been made into a better understanding of chromoplast differentiation. Metabolic reorientations and specific biochemical and molecular events have been clearly identified. It is predictable that more information will arise from the indepth description of the molecular events occurring during the chloroplast to chromoplast transition using genomic tools.
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*Source: 289859-2011-09-15.xml* | 289859-2011-09-15_289859-2011-09-15.md | 37,428 | Metabolic and Molecular Events Occurring during Chromoplast Biogenesis | Wanping Bian; Cristina Barsan; Isabel Egea; Eduardo Purgatto; Christian Chervin; Mohamed Zouine; Alain Latché; Mondher Bouzayen; Jean-Claude Pech | Journal of Botany
(2011) | Biological Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2011/289859 | 289859-2011-09-15.xml | ---
## Abstract
Chromoplasts are nonphotosynthetic plastids that accumulate carotenoids. They derive from other plastid forms, mostly chloroplasts. The biochemical events responsible for the interconversion of one plastid form into another are poorly documented. However, thanks to transcriptomics and proteomics approaches, novel information is now available. Data of proteomic and biochemical analysis revealed the importance of lipid metabolism and carotenoids biosynthetic activities. The loss of photosynthetic activity was associated with the absence of the chlorophyll biosynthesis branch and the presence of proteins involved in chlorophyll degradation. Surprisingly, the entire set of Calvin cycle and of the oxidative pentose phosphate pathway persisted after the transition from chloroplast to chromoplast. The role of plastoglobules in the formation and organisation of carotenoid-containing structures and that of theOr gene in the control of chromoplastogenesis are reviewed. Finally, using transcriptomic data, an overview is given the expression pattern of a number of genes encoding plastid-located proteins during tomato fruit ripening.
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## Body
## 1. Introduction
Chromoplasts are nonphotosynthetic plastids that accumulate carotenoids and give a bright colour to plant organs such as fruit, flowers, roots, and tubers. They derive from chloroplasts such as in ripening fruit [1], but they may also arise from proplastids such as in carrot roots [2] or from amyloplasts such as in saffron flowers [3] or tobacco floral nectaries [4]. Chromoplasts are variable in terms of morphology of the carotenoid-accumulating structures and the type of carotenoids [5, 6]. For instance, in tomato, lycopene is the major carotenoid, and it accumulates in membrane-shaped structures [7] while in red pepper beta-carotene is prominent and accumulates mostly in large globules [8]. Reviews specifically dedicated to the biogenesis of chromoplasts have been published [9–11]. Some information can also be found in papers dedicated to plastid differentiation in general [12, 13]. Thanks to transcriptomics and proteomics approaches, novel information is now available on the biochemical and molecular aspects of chromoplasts differentiation [14–16]. The present paper will review these novel data and provide a recent view of the metabolic and molecular events occurring during the biogenesis of chromoplasts and conferring specificities to the organelle. Focus will be made on the chloroplast to chromoplast transition.
## 2. Chromoplast Differentiation Is Associated with Important Structural, Metabolic, and Molecular Reorientations
Important structural changes occur during the chloroplast to chromoplast transition, thylakoid disintegration being the most significant (Figure1). Early microscopic observations have shown that plastoglobuli increase in size and number during the chloroplast-chromoplast transition [7] and that the internal membrane system is profoundly affected at the level of the grana and intergrana thylakoids [17]. Stromules (stroma-filled tubules) that are dynamic extensions of the plastid envelope allowing communication between plastids and other cell compartments like the nucleus [18] are also affected during chromoplastogenesis. A large number of long stromules can be found in mature chromoplasts contrasting with the few small stromules of the chloroplasts in green fruit [19]. It can therefore be assumed that the exchange of metabolites between the network of plastids and between the plastids and the cytosol is increased in the chromoplast as compared to the chloroplast. However, the most visible structural change is the disruption of the thylakoid grana, the disappearance of chlorophyll, and the biogenesis of carotenoid-containing bodies. Associated with the structural changes, the toc/tic transmembrane transport machinery is disintegrated [16, 20]. The noncanonical signal peptide transport [21] and intracellular vesicular transport [22, 23] may represent the most active form of trans-membrane transport into the chromoplast as compared to the chloroplast. Proteins involved in vesicular transport were detected in the tomato chromoplastic proteome [16].Figure 1
Schematic representation of the main structural changes occurring during the chloroplast to chromoplast transition.One of the most visible metabolic changes occurring during the chloroplast to chromoplast transition is the loss of chlorophyll and the accumulation of carotenoids [24]. A spectral confocal microscopy analysis of carotenoids and chlorophylls has been carried out during the chloroplast to chromoplast transition in tomato fruit, including a time-lapse recording on intact live tissue [25]. Details of the early steps of tomato chromoplast biogenesis from chloroplasts are provided at the cellular level that show the formation of intermediate plastids containing both carotenoids and chlorophylls. This study also demonstrated that the chloroplast to chromoplast transition was synchronous for all plastids of a single cell and that all chromoplasts derived from preexisting chloroplasts.The photosynthetic machinery is strongly disrupted and a reduction in the levels of proteins and mRNAs associated with photosynthesis was observed [26]. Also the decrease in photosynthetic capacity during the later stages of tomato fruit development was confirmed by transcriptomic data [27]. However, part of the machinery persist in the chromoplast. It has been suggested that it participates in the production of C4 acids, in particular malate a key substrate for respiration during fruit ripening [28]. In the tomato chromoplast proteome, all proteins of the chlorophyll biosynthesis branch are lacking [16]. In the early stages of tomato fruit ripening, the fruits are green and the plastids contain low levels of carotenoids that are essentially the same as in green leaves, that is, mainly β-carotene, lutein, and violaxanthin. At the “breaker” stage of ripening, lycopene begins to accumulate and its concentration increases 500-fold in ripe fruits, reaching ca.70 mg/g fresh weight [24]. During the ripening of tomato fruit, an upregulation of the transcription ofPsyand Pds, which encode phytoene synthase and phytoene desaturase, respectively, was reported [29]. One of the main components of the carotenoid-protein complex, a chromoplast-specific 35-kD protein (chrC), has been purified and characterized in Cucumis sativus corollas. It showed increasing steady-state level in parallel with flower development and carotenoid accumulation, with a maximum in mature flowers [30]. In tomato, concomitantly with increased biosynthesis of lycopene, the processes for splitting into β and γ carotene were absent [16]. The mRNAs of CrtL-band CrtL-e were strongly downregulated during fruit ripening [29]. They encode lycopene β-cyclase and ε-cyclase, enzymes involved in the cyclization of lycopene leading to the formation of β and δ carotene, respectively. In these conditions, the low rate of cyclization and splitting contributes to the accumulation of lycopene in ripe tomato fruit.In terms of reactive oxygen species, antioxidant enzymes are upregulated during chromoplast development, and lipids, rather than proteins, seem to be a target for oxidation. In the chromoplasts, an upregulation in the activity of superoxide dismutase and of components of the ascorbate-glutathione cycle was observed [31].The plastid-to-nucleus signaling also undergoes important changes. In the chromoplast, the main proteins involved in the synthesis of Mg-protoporphyrin IX, a molecule supposed to play an important role in retrograde signaling [32] is absent, but other mechanisms such as hexokinase 1 or calcium signaling were present [16]. The plastid-nucleus communication is still an open subject with many still unanswered questions.
## 3. A Number of Metabolic Pathways Are Conserved during Chromoplast Differentiation
The comparison of data arising from proteomics of the chloroplast [33] and of the chromoplast [16] as well as biochemical analysis of enzyme activities suggest that several pathways are conserved during the transition from chloroplast to chromoplast. Such is the case for (i) the Calvin cycle which generates sugars from CO2, (ii) the oxidative pentose phosphate pathway (OxPPP) which utilizes the 6 carbons of glucose to generate 5 carbon sugars and reducing equivalents, and (iii) many aspects of lipid metabolism (Figure 2). Activities of enzymes of the Calvin cycle have been measured in plastids isolated from sweet pepper. They may even be higher in chromoplasts than in chloroplasts [34] In ripening tomato fruits, several enzymes of the Calvin cycle (hexokinase, fructokinase, phosphoglucoisomerase, pyrophosphate-dependent phosphofructokinase, triose phosphate isomerase, glyceraldehyde 3-phosphate dehydrogenase, phosphoglycerate kinase, and glucose 6-phosphate dehydrogenase) are active [35]. The activity of glucose 6-phosphate dehydrogenase (G6PDH), a key component of the OxPPP, was higher in fully ripe tomato fruit chromoplasts than in leaves or green fruits [36]. Also, a functional oxidative OxPPP has been encountered in isolated buttercup chromoplasts [37]. Proteomic analysis have demonstrated that an almost complete set of proteins involved in the OxPPP are present in isolated tomato fruit chromoplasts (Figure 2). The persistence of the Calvin cycle and the OxPPP cannot be related to photosynthesis since the photosynthetic system is disrupted. In nonphotosynthetic plastids, the Calvin cycle could provide reductants and also precursors of nucleotides and aromatic aminoacids to allow the OxPPP cycle to function optimally [16].Presence of proteins of the Calvin cycle in the tomato chromoplastic proteome. Proteins are indicated by white squares inside black frames and represented by their generic name and unigene SGN code. Numbers represent the position of the protein in the cycle. Data are derived from [16].
(a)(b)Starch transiently accumulates in young tomato fruit and undergoes almost complete degradation by maturity. In fact, starch accumulation results from an unbalance between synthesis and degradation. Enzymes capable of degrading starch have been detected in the plastids of tomato fruit. In addition, tomato fruit can synthesize starch during the period of net starch breakdown, illustrating that these two mechanisms can coexist [38]. As indicated in Figure 3, proteins for starch synthesis have been encountered in the tomato chromoplast (ADP-glucose pyrophosphorylase, starch synthase, and starch branching enzyme). In addition, the system for providing neutral sugars to the starch biosynthesis pathway is complete including the glucose-6P-translocator which imports sugars from the cytosol. The presence of active import of glucose-6P, but not glucose-1P, had been demonstrated in buttercup chromoplasts [37]. Although some starch granules may be present in ripe tomatoes, the amount of starch is strongly reduced [39]. The most probable explanation is that starch undergoes rapid turnover with intense degradation. This assumption is supported by the presence in the tomato chromoplast of most of the proteins involved in starch degradation (Figure 3). Particularly interesting is the presence of one glucan-water dikinase (GWD), one phospho-glucan-dikinase (PWD), and one phospho-glucan-phosphatase (PGP) that facilitate the action of β-amylases [40]. Mutants of these proteins, named starch excess (SEX1 corresponding to GWD and SEX4 to PGP), accumulate large amounts of starch [40]. In agreement with the above-mentioned hypothesis, high activity of β-amylase has been found during apple and pear fruit ripening at a time where starch has disappeared [41]. The presence of a glucose translocator for the export of sugars generated by starch degradation represents another support to the functionality of the starch metabolism pathways in chromoplasts. In olive fruit, a high expression of a glucose transporter gene was observed at full maturity when the chromoplasts were devoid of starch [42]. Nevertheless, the enzymatic activity of all of the proteins remains to be demonstrated inasmuch as posttranslational regulation of enzymes of starch metabolism has been reported [43] including protein phosphorylation [44]. Interestingly, orthologs of the 14-3-3 proteins of the μ family of Arabidopsis involved in the regulation of starch accumulation [45] are present in the tomato chromoplastic proteome (Figure 3). The 14-3-3 proteins participate in the phosphorylation-mediated regulatory functions in plants.Presence of proteins of the starch synthesis and degradation pathways, of posttranslational regulation of starch synthesis, and of sugar translocators in the tomato chromoplastic proteome. Proteins are indicated by white squares inside black frames and represented by their generic name and unigene SGN code. Numbers represent the position of the protein in the cycle. Data are derived from [16].
(a)(b)In chloroplasts, thylakoid membranes, as well as envelope membranes, are rich in galactolipids and sulfolipids [46]. Lipid metabolism is also highly active in the chromoplasts. Despite thylakoid disassembly, new membranes are synthesized such as those participating in the formation of carotenoid storage structures. These newly synthesized membranes are not derived from the thylakoids but rather from vesicles generated from the inner membrane of the plastid [47]. Key proteins for the synthesis of phospholipids, glycolipids, and sterols were identified [16] along with some proteins involved in the lipoxygenase (LOX) pathway. They have been described in the chloroplast, and they lead to the formation oxylipins, which are important compounds for plant defense responses [48]. In the tomato chromoplast, all proteins potentially involved in the LOX pathway leading to the generation of aroma volatiles were found [16].The shikimate pathway, which is present in microorganisms and plants and never in animals, is a branch point between the metabolism of carbohydrates and aromatic compounds. It leads to the biosynthetic of the aromatic amino acids tyrosine, tryptophan, and phenylalanine [49]. The presence of an active shikimate pathway has been demonstrated in chromoplasts isolated from wild buttercup petals by measuring the activity of the shikimate oxidoreductase [50], and a number of proteins involved in the shikimate pathway have been encountered in the tomato chromoplast proteome [16]. The aromatic amino acids derived from the shikimate pathway are the precursors of a number of important secondary metabolites. Tyrosine is the precursor of tocopherols and tocotrienols. Tryptophane is involved in the synthesis of indole alkaloids which are essential for the generation of some glucosinolates, terpenoids, and tryptamine derivatives [50]. Phenylalanine is the precursor of several classes of flavonoids, including anthocyanins. It is also a precursor for the biosynthesis of volatile compounds which are important for fruit flavor and flower scent, eugenol, 2-phenylacetaldehyde and, 2-phenylethanol [51, 52]. In tomato fruit, for instance, 2-phenylacetaldehyde and 2-phenylethanol are generated from phenylalanine by an aromatic amino acid decarboxylase and a phenylacetaldehyde reductase, respectively [53, 54]. Nevertheless, there is no indication that the synthesis of the secondary metabolites derived from the shikimate pathway takes place in the chromoplast.During fruit ripening, an increased synthesis ofα-tocopherol was observed [55]. The biosynthesis of α-tocopherol was localized in the envelope membranes of the Capsicum annum [56], and the almost complete set of proteins of the pathway were present in the tomato chromoplast [16]. The accumulation of α-tocopherol, by protecting membrane lipids against oxidation, may contribute to delaying senescence [57].
## 4. Plastoglobuli, Plastoglobules, and the Chloroplast-to-Chromoplast Transition
Plastoglobules are lipoprotein particles present in chloroplasts (Figure1) and other plastids. They have been recently recognized as participating in some metabolic pathways [58]. For instance, plastoglobules accumulate tocopherols and harbor a tocopherol cyclase, an enzyme catalyzing the conversion of 2,3-dimethyl-5-phytyl-1,4-hydroquinol to γ-tocopherol [59]. Plastoglobuli also accumulate carotenoids as crystals or as long tubules named fibrils [60, 61]. Part of the enzymes involved in the carotenoid biosynthesis pathway (ζ-carotene desaturase, lycopene β cyclase, and two β-carotene β hydroxylases) were found in the plastoglobuli [62].Plastoglobules arise from a blistering of the stroma-side leaflet of the thylakoid membrane [63], and they are physically attached to it [45]. During the chloroplast-to-chromoplast transition, a change in the size and number of plastoglobuli was observed (Figure 1). They are larger and more numerous than in the chloroplast [7]. Plastoglobules are the predominant proteins of plastoglobules. Several types of plastoglobules have been described: fibrillin, plastid lipid-associated proteins (PAP) and carotenoid-associated protein (CHRC). All plastoglobules participate in the accumulation of carotenoids in the plastoglobule structure. Carotenoids accumulate as fibrils to form supramolecular lipoprotein structures. A model for fibril assembly has been proposed in which the core is occupied by carotenoids that interact with polar galacto- and phospho-lipids. Fibrillin molecules are located at the periphery in contact with the plastid stroma [64]. In tomato, the overexpression of a pepper fibrillin caused an increase in carotenoid and carotenoid-derived flavour volatiles [47] along with a delayed loss of thylakoids during the chloroplast-to-chromoplast transition. In fibrillin overexpressing tomato, the plastids displayed a typical chromoplastic zone contiguous with a preserved chloroplastic zone. PAP is another major protein of plastoglobules that also participates in the sequestration of carotenoids [64, 65]. As for CHRC, its downregulation resulted in a 30% reduction of carotenoids in tomato flowers [66]. Plastoglobuli are, therefore, complex assemblies that play a key role in carotenoid metabolism and greatly influence the evolution of the internal structure of the plastid during the chloroplast to chromoplast transition.
## 5. A key Player in Chromoplast Differentiation: TheOr Gene
TheOr gene was discovered in cauliflower where the dominant mutation Or conferred an orange pigmentation with the accumulation of β-carotene mostly in the inflorescence [67]. The Or gene was isolated by positional cloning [68]. It is localized in the nuclear genome and is highly conserved among divergent plant species [69]. The Or protein corresponds to plastid-targeted a DnaJ-like co-chaperone with a cysteine-rich domain lacking the J-domain [68]. DnaJ proteins are known for interacting with Hsp70 chaperones to perform protein folding, assembly, disassembly, and translocation. The Or mutation is not a loss of function mutation as indicated by the absence of phenotype upon RNAi silencing. It is probably a dominant-negative mutation affecting the interaction with Hsp70 chaperones [70]. The OR mutants displayed an arrest in plastid division so that a limited number of chromoplasts (one or two) were present in the affected cells [71]. Potato tubers over-expressing the Or gene accumulate carotenoids [69]. In the OR mutant, the expression of carotenoid biosynthetic genes was unaffected and chromoplasts differentiated normally with membranous inclusions of carotenoids similar to those of carrot roots. It is concluded that the Or gene is not involved in carotenoid biosynthesis but rather creates a metabolic sink for carotenoid accumulation through inducing the formation of chromoplasts [72].
## 6. Transcriptional and Translational Activity in the Plastid Undergo Subtle Changes during Chromoplast Biogenesis
Most proteins present in the plastid are encoded by nuclear genes. The plastid genome encodes around 84 proteins [60]. Restriction enzyme analysis between chloroplasts of leaves and chromoplasts of tomato fruit indicates the absence of rearrangements, losses, or gains in the chromoplastic DNA [61]. During chromoplast differentiation, the global transcriptional activity is stable, except for a limited number of genes such as accD, encoding a subunit of the acetyl-CoA carboxylase involved in fatty acid biosynthesis, trnA (tRNA-ALA), and rpoC2 (RNA polymerase subunit) [15]. Polysome formation within the plastids declined during ripening suggesting that, while the overall RNA levels remain largely constant, plastid translation is gradually downregulated during chloroplast-to-chromoplast differentiation. This trend was particularly pronounced for the photosynthesis gene group. A single exception was observed; the translation of accD stayed high and even increased at the onset of ripening [15].Specific studies of few plastid-localized genes have been carried out. Genes involved in photosynthesis were, as expected, downregulated during chromoplast formation [25]. However, an upregulation of the large subunit of ribulose-1,5-bisphosphate carboxylase/oxygenase and the 32 kD photosystem II quinone binding protein genes has been observed in the chromoplasts of squash fruits (Cucurbitae pepo) [62]. A possible explanation would be that these genes could be regulated independently from the plastid differentiation processes. Genes involved in carotenoid biosynthesis such as the lycopeneβ-cyclase (CYCB) were upregulated during chromoplast formation in many plants including the wild species of tomato Solanum habrochaites [63].
## 7. Changes in Gene Expression during Chromoplast Differentiation in Ripening Tomato
The availability of proteomic data of tomato chromoplasts [16] and expression data of a wide range of tomato genes (The Tomato Expression Database: http://ted.bti.cornell.edu) [73] allowed classifying genes encoding chromoplastic proteins according to their expression pattern (Table 1). Among the 87 unigenes whose encoded proteins are located in the chromoplast, the biggest functional class corresponds to genes involved in photosynthesis. Most of them (18 out of 24) are either permanently (Table 1(c)) or transiently (Table 1(e)) downregulated at the breaker stage. This is in agreement with the dramatic decrease in the photosynthetic activity of the chromoplast. Three of them show constant expression (Table 1(a): U313693 ATP synthase delta chain; U312985 glycine cleavage system H protein; U312532 oxygen-evolving enhancer protein) and three upregulation (Table 1(b): U312690 plastocyanin; U312593 chlorophyll A-B binding protein 4; U314994 phosphoglycolate phosphatase). In the case of Calvin cycle, 5 out of 12 genes (U312344 fructose-bisphosphate aldolase; U312608 fructose-bisphosphate aldolase; U312609 fructose-bisphosphate aldolase; U314254 ribulose bisphosphate carboxylase small chain 1A; U314701 ribulose bisphosphate carboxylase small chain 3B) had a constant decrease during chromoplast differentiation (Table 1(c)). In tomato fruit, the activity of the ribulose-1,5-bisphosphate carboxylase/oxygenase had a constant decrease during fruit ripening [74], which is in line with the transcriptomic and proteomic data. The genes encoding fructose-bisphosphate aldolase isoforms presented different expression profiles being either up- (U314788) or down- (U312344) regulated during tomato fruit ripening. An increase in overall transcript levels for the fructose-1,6-bisphosphate aldolase has been described during ripening [75]. The importance of transcripts and enzyme activity of the various isoforms are unknown. The remaining genes involved in the Calvin cycle showed either increased (Table 1(b); U312802 glyceraldehyde-3-phosphate dehydrogenase B; U312538 RuBisCO subunit binding-protein) or unchanged expression (Table 1(a); U316424 fructose-1,6-bisphosphatase; U312544 ribulose bisphosphate carboxylase/-oxygenase activase). Three genes coding for the OxPPP were found: two of them exhibited a transient increase in expression at the breaker stage (Table 1(d): U315528 ribose 5-phosphate isomerase-related; U332994 6-phosphogluconate dehydrogenase family protein) and one a transient decrease (Table 1(e): U315064 transaldolase). The 3 genes involved in tetrapyrrole biosynthesis are not part of the chlorophyll synthesis branch and all of them had an increased expression (Table 1(b): U315993 coproporphyrinogen III oxidase; U315267 uroporphyrinogen decarboxylase; U315567 hydroxymethylbilane synthase), suggesting that the synthesis of tetrapyrroles continues during the transition from chloroplast to chromoplast. As expected, most of the genes (5 out of 6) coding for enzymes involved in carotenoid synthesis showed continuous (Table 1(b): U314429 phytoene synthase; U315069 isopentenyl-diphosphate delta-isomerase II; U316915 geranylgeranyl pyrophosphate synthase; U318137 phytoene dehydrogenase) or transient (Table 1(d): U313450 geranylgeranyl reductase) upregulation. The precursors for carotenoid production are synthesized through the methylerythritol phosphate (MEP) pathway. The gene encoding hydroxymethylbutenyl 4-diphosphate synthase (HDS) (U314139) downstream in the pathway has stable expression (Table 1(a)). This is consistent with previous studies that showed that there were no significant changes in HDS gene expression during tomato fruit ripening [76].Table 1
Expression profile analysis of 87 genes whose products are targeted to tomato chromoplasts (*).
Photosystem: U313693 ATP synthase delta chain; U312985 glycine cleavage system H protein; U312532 oxygen-evolving enhancer protein. Calvin cycle: U316424 fructose-1, 6-bisphosphatase; U312544 ribulose bisphosphate carboxylase/-oxygenase activase.Secondary metabolism: U314139 1-hydroxy-2-methyl-2-(E)-butenyl 4-diphosphate synthase.Photosystem: U312690 plastocyanin; U312593 chlorophyll A-B binding protein 4; U314994 phosphoglycolate phosphatase.Calvin cycle: U314788 fructose-bisphosphate aldolase; U312802 glyceraldehyde-3-phosphate dehydrogenase B; U312538 RuBisCO subunit binding-protein.Redox: U314092 L-ascorbate peroxidase; U319145 thioredoxin family protein; U320487 monodehydroascorbate reductase.Amino acid metabolism: U321505 anthranilate synthase; U317466 3-phosphoshikimate 1-Carboxyvinyltransferase; U317564 tryptophan synthase.Lipid metabolism: U315474 3-oxoacyl-(acyl-carrier-protein) synthase I; U315475 3-oxoacyl-(acyl-carrier-protein) synthase I; U313753 pyruvate dehydrogenase E1 component. Major CHO metabolism: U315116 starch excess protein (SEX1); U333011 isoamylase, putative; U312423 1, 4-alpha-glucan branching enzyme; U312427 1, 4-alpha-glucan branching enzyme.Secondary metabolism: U314429 phytoene synthase; U315069 isopentenyl-diphosphate delta-isomerase II; U316915 geranylgeranyl pyrophosphate synthase; U318137 phytoene dehydrogenase.Tetrapyrrole synthesis: U315993 coproporphyrinogen III oxidase; U315267 uroporphyrinogen decarboxylase; U315567 hydroxymethylbilane synthase.Mitochondrial electron transport: U316255 NADH-ubiquinone oxidoreductase.Fermentation, ADH: U314358 alcohol dehydrogenase (ADH).Miscellaneous, cytochrome P450: U313813 NADPH-cytochrome p450 reductase.S-assimilation. APS: U313496 sulfate adenylyltransferase 1.Development unspecified: U316277 senescence-associated protein (SEN1).Cell organisation: U313480 plastid lipid-associated protein PAP, putative. Hormone metabolism: U315633 lipoxygenase. N-metabolism ammonia metabolism: U323261 glutamate synthase (GLU1).Stress abiotic heat: U315717 HS protein 70.Not assigned, No ontology: U317890 hydrolase, alpha/beta fold family protein.Photosystem: U312531 oxygen-evolving enhancer protein; U313447 photosystem I reaction center subunit IV; U313204 chlorophyll A-B binding protein 2; U313245 ATP synthase gamma chain 1; U312436 chlorophyll A-B binding protein; U313211 chlorophyll A-B binding protein 2; U313212 chlorophyll A-B binding protein 2; U313213 chlorophyll A-B binding protein 2; U312572 photosystem II oxygen-evolving complex 23 (OEC23); U314260 photosystem I reaction center subunit III family protein.Calvin cycle: U312344 fructose-bisphosphate aldolase; U312608 fructose-bisphosphate aldolase; U312609 fructose-bisphosphate aldolase; U314254 ribulose bisphosphate carboxylase small chain 1A; U314701 ribulose bisphosphate carboxylase small chain 3B.Lipid metabolism: U319207 phosphatidylglycerol phosphate synthase (PGS1).Redox: U313537 dehydroascorbate reductase.Major CHO metabolism: U316416 glucan phosphorylase, putative. N-metabolism: U314517 glutamine synthetase (GS2).Amino acid metabolism: U317344 bifunctional aspartate kinase/homoserine dehydrogenase; U320667 cystathionine beta-lyase.Redox: U314061 peroxiredoxin Q; U314093 L-ascorbate peroxidase, thylakoid-bound (tAPX); U314923 2-cys peroxiredoxin.OPP, Nonreductive PP: U315528 ribose 5-phosphate isomerase related; U332994 6-phosphogluconate dehydrogenase family protein; U316131 6-phosphogluconate dehydrogenase NAD-binding domain-containing protein.Secondary metabolism: U317741 acetyl coenzyme A carboxylase carboxyl transferase alpha subunit family; U313450 geranylgeranyl reductase.Amino acid metabolism: U317245 tryptophan synthase related.N-metabolism ammonia metabolism: U317524 ferredoxin-nitrite reductase.Lipid metabolism: U315697 enoyl-(acyl-carrier protein) reductase (NADH) U321151 lipoxygenase. Transport metabolite: U312460 triose phosphate/phosphate translocator, putative. Signalling calcium: U315961 calnexin 1 (CNX1).Photosystem: U312843 chlorophyll A-B binding protein; U312858 cytochrome B6-F complex iron-sulfur subunit; U313214 chlorophyll A-B binding protein 2; U312791 phosphoribulokinase (PRK); U317040 photosystem II reaction center PsbP family protein; U312449 chlorophyll A-B binding protein CP26; U312661 chlorophyll A-B binding protein CP29 (LHCB4); U313789 ATP synthase family.Calvin cycle: U312461 glyceraldehyde 3-phosphate dehydrogenase A; U312871 oxygen-evolving enhancer protein 3.Redox: U315728 glutathione peroxidase.OPP nonreductive PP transaldolase: U315064 transaldolase. Signaling calcium: U318939 calcium-binding EF hand family protein.Major CHO metabolism: U313315 beta amylase.(*) Genes represented in this table are filtered from TED database [64] crossing with the proteins described by Barsan et al. [16]. The expression profiles were clustered with the Bioinformatics tools of the Matlab (MathWorks) software package and further reduced to five representative expression profiles according to their general tendencies represented in the first column. The expression values used in this analysis were taken from experiment E011 from TED database. Relative expression refers to the ratio between the expression values of each ripening point and MG. All data were normalized by the mean and log2 transformed. (a) Genes that remain stable during the ripening, (b) genes that have an increase or (c) a decrease until breaker stage and then reaches a plateau, (d) genes that have a positive or (e) negative transient expression around the breaker stage. (MG, mature green; B-1, 1 d before breaker; B, breaker stage; B + 1, 1 d after breaker; B + 5, 5 d after breaker; B + 10, 10 d after breaker.)In the case of lipid metabolism, three genes showed increased expression (Table1(b): U315474 3-oxoacyl-(acyl-carrier-protein) synthase I; U315475 3-oxoacyl-(acyl-carrier-protein) synthase I; U313753 pyruvate dehydrogenase E1 component), and two genes had transient increase (Table 1(d): U315697 enoyl-(acyl-carrier protein) reductase (NADH); U321151 lipoxygenase). Phosphatidylglycerol phosphate synthase showed decreased expression (Table 1(c)). This enzyme is involved in the biosynthesis of phosphatidylglycerol and is considered as playing an important role in the ordered assembly and structural maintenance of the photosynthetic apparatus in thylakoid membranes and in the functioning of the photosystem II [77]. The downregulation of this gene during chromoplast differentiation is consistent with thylakoid disintegration and photosynthesis disappearance.Four genes of the starch metabolism present upregulation (Table1(b)). Two of them are part of the starch biosynthesis (U312423 1,4-alpha-glucan branching enzyme; U312427 1, 4-alpha-glucan branching enzyme), and one of them is involved starch degradation U315116 starch excess protein (SEX1). The fourth one, an isoamylase (U333011) can participate either in starch degradation or in starch synthesis, depending on the isoform [78]. The expression of the gene that codes a starch degrading glucan phosphorylase (U316416) decreases, and the expression of another starch degrading gene, beta-amylase (U313315), has a negative transient expression (Table 1(b)). In addition, proteomic studies have shown the presence of two starch excess proteins (SEX1 and 4) that probably contribute to the absence of starch accumulation [16]. Starch is degraded during the chloroplast to chromoplast transition to provide carbon and energy necessary to sustain the metabolic activity during fruit ripening. Several enzymes are responsible for the processes, each one possessing several isoforms with different regulatory mechanisms [78].Interestingly genes involved in aroma production such asADH (U314358) or LOXC (U315633) had a constant increase in gene expression (Table 1(b)). This could be related to the increase in aroma production via the LOX pathway.The microarray data discussed in this section cover a wide range of the tomato transcriptome. However, several isoforms of several genes are not represented in the database, which could explain some contradictory patterns of expression encountered in our analysis. Nevertheless, although not providing a full picture of the molecular events occuring during the chloroplast to chromoplast transition, these data confirm the regulation at the transcriptional level of the most salient events.
## 8. Conclusions and Perspectives
With the advent of high throughput technologies, great progress has been made in the recent years in the elucidation of the structure and function of plastids. The most important data obtained in the area have been generated for the chloroplast of Arabidopsis. Much less information is available for the chromoplast. However, recent studies with bell pepper [14] and tomato fruit [16] have allowed assigning to chromoplasts a number of proteins around 1000, which is in the same order of magnitude as Arabidopsis chloroplasts [33]. This number is, however, much lower than the number of proteins predicted to be located in the plastid which has been estimated at up to 2700 [79] or even 3800 [80]. The increased sensitivity of the mass spectrometry technologies associated with efficient methods of purification of plastids, particularly chromoplasts, will allow in the future identifying more proteins. So far, changes in the proteome have not been described during the differentiation of chromoplast. Such studies imply the development of efficient protocols for isolating plastids at different stages of differentiation during chromoplastogenesis. The combination of proteomics and transcriptomics may also give novel information on the process in a near future. The discovery of the Or gene has been a great step forward to the understanding of the molecular determinism of chromoplast differentiation. There is a need to better understand the regulatory mechanism controlling the expression of the Or gene. Many genes encoding for plastidial proteins are regulated by the plant hormone ethylene and, therefore, participate in the transcriptional regulation of the fruit ripening process in general [81, 82]. Other hormones such as ABA and auxin may also be involved. Interactions between hormones and other signals (light, for instance) during chromoplast differentiation represent another field of investigation to be explored. Because most of the proteins present in the chromoplast are encoded by nuclear genes, it will be important in future to better understand the changes occurring in the processes of transport of proteins to the chromoplast. It is suspected that vesicular transport is gaining importance, but more experimental evidence is required. Finally the dialog between the nucleus and the chromoplast and the signals involved needs to be explored. So far most of the studies in this area have been carried out with chloroplasts [83].In conclusion, important steps forward have been made into a better understanding of chromoplast differentiation. Metabolic reorientations and specific biochemical and molecular events have been clearly identified. It is predictable that more information will arise from the indepth description of the molecular events occurring during the chloroplast to chromoplast transition using genomic tools.
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*Source: 289859-2011-09-15.xml* | 2011 |
# PPARγ Signaling Mediates the Evolution, Development, Homeostasis, and Repair of the Lung
**Authors:** Virender K. Rehan; John S. Torday
**Journal:** PPAR Research
(2012)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2012/289867
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## Abstract
Epithelial-mesenchymal interactions mediated by soluble growth factors determine the evolution of vertebrate lung physiology, including development, homeostasis, and repair. The final common pathway for all of these positively adaptive properties of the lung is the expression of epithelial parathyroid-hormone-related protein, and its binding to its receptor on the mesenchyme, inducing PPARγ expression by lipofibroblasts. Lipofibroblasts then produce leptin, which binds to alveolar type II cells, stimulating their production of surfactant, which is necessary for both evolutionary and physiologic adaptation to atmospheric oxygen from fish to man. A wide variety of molecular insults disrupt such highly evolved physiologic cell-cell interactions, ranging from overdistention to oxidants, infection, and nicotine, all of which predictably cause loss of mesenchymal peroxisome-proliferator-activated receptor gamma (PPARγ) expression and the transdifferentiation of lipofibroblasts to myofibroblasts, the signature cell type for lung fibrosis. By exploiting such deep cell-molecular functional homologies as targets for leveraging lung homeostasis, we have discovered that we can effectively prevent and/or reverse the deleterious effects of these pathogenic agents, demonstrating the utility of evolutionary biology for the prevention and treatment of chronic lung disease. By understanding mechanisms of health and disease as an evolutionary continuum rather than as dissociated processes, we can evolve predictive medicine.
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## Body
## 1. Background
Normal lung development is the result of a functionally interconnected series of cell-molecular steps. This sequence of biologic events has been positively selected for evolutionarily over biologic time and space [1], resulting in optimal gas exchange mediated by alveolar homeostasis [2]. Elsewhere we have suggested that chronic lung disease (CLD) causes simplification of the lung in a manner consistent with the reversal of the evolutionary process [3, 4]. Therefore, by identifying those mechanisms that have evolved under selection pressure for optimal gas exchange [5], we have theorized that we can effectively reverse the deleterious effects of CLD by promoting the evolutionarily adaptive mechanism [6], rather than by just treating the symptoms [7]. By determining the cell-molecular sequence of spatiotemporal signals that have evolved the lung over phylogeny and ontogeny, we can identify physiologically rational targets for effectively preventing and reversing the deleterious effects of endogenous and exogenous factors known to irreversibly damage normal lung development and function.The ground-breaking tissue culture experiments conducted by Grobstein in 1967 demonstrating that lung development was dependent on endodermal-mesenchymal interactions [8] led to decades of research to determine the underlying cell-molecular mechanisms. The seemingly simple epithelial-mesenchymal interactions during well-defined (embryonic, pseudoglandular, canalicular, saccular, and alveolar), but overlapping stages of lung development result in more than 40 different cell types [9]. Much of what we currently know about the mechanisms involved in lung development is derived from such studies of cultured lung cells signaling through growth factor-mediated pathways for proliferation and differentiation [10–12]. The discovery that epithelial-mesenchymal signaling induced the lipofibroblast via peroxisome proliferator-activated receptor gamma (PPARγ) [13] gave rise to the hypothesis that normal lung development could be reconstituted [14] and recapitulated [15, 16]. The following recounts the essential role of PPARγ in lipofibroblast differentiation and its exploitation for the effective treatment of the preterm lung.
## 2. Epithelial-Mesenchymal Interactions Generate Alveolar Lung Development
The paracrine growth factor model used to study the maturation of the pulmonary surfactant system and the etiology of CLD is shown in the accompanying schematic (see Figure1, steps 1–11). Briefly, we have observed coordinating effects of stretch on alveolar type II (ATII) cell expression of parathyroid-hormone-related protein (PTHrP) and PGE2 (Prostaglandin E2) (step 1), the lipofibroblast PTHrP receptor (step 2), PPARγ upregulation (step 4) via Protein Kinase A activation (step3), its downstream effect on lipofibroblast ADRP (Adipocyte-Differentiation-Related Protein) expression (step 5) and triglyceride (TG) uptake by both the lipofibroblast and the ATII cell (steps 6a and 6b), and on the interaction between lipofibroblast-produced leptin (step7) and the ATII cell leptin receptor (step8), stimulating de novo surfactant phospholipid synthesis by ATII cells (step9). The schematic depicts lipofibroblast-to-myofibroblast transdifferentiation (step10) due to decreased PTHrP following exposure to hyperoxia, volutrauma, or infection. All of these effects are shown to be prevented by PPARγ agonists (step11).Figure 1
Schematic for paracrine determinants of alveolar homeostasis and disease.These studies were originally fostered by Barry Smith’s seminal observation [10] that glucocorticoids accelerate ATII cell surfactant synthesis by stimulating fibroblast synthesis of an oligopeptide that he termed Fibroblast-Pneumonocyte Factor (FPF). It was known at that time that lung, prostate, and mammary mesodermal development were under endocrine control. Importantly, it was shown that early signals emanated from the epithelium to differentiate the immature mesenchyme in the neighboring epithelium of the developing mammary gland [17]. Moreover, Brody’s laboratory had shown that the developing lung fibroblast acquired an adipocyte-like phenotype [18–20], termed the lipid-laden fibroblast, leaving open the question as to whether these cells might be a source of lipid substrate for surfactant synthesis by the ATII cell. The Torday laboratory later discovered the physiologic significance of these lipid-laden fibroblasts by coculturing them with type II cells, which resulted in the rapid trafficking of the lipid from the fibroblast to the type II cell, and its highly enriched incorporation into specific surfactant phospholipids. These data indicated the existence of a specific mechanism for the recruitment of lipid substrate from the vasculature to the type II cell for de novo surfactant synthesis. This trafficking was even more robust when the cocultured cells were treated with glucocorticoids, which are known to stimulate cell-cell interactions in the alveolus in association with increased surfactant synthesis, further reinforcing the notion of a putative mechanism for neutral lipid trafficking for surfactant synthesis since it appeared to be a regulated process [21].Interestingly, the fibroblasts took up the neutral lipid, but did not release it unless they were in the presence of type II cells; conversely, the type II cells were unable to take up neutral lipid. These observations led to the discovery that type II cell secretion of prostaglandin E2 (Figure 1, step 1), a stretch- and glucocorticoid-regulated mechanism, caused the active release of neutral lipid from the fibroblasts [22]. This effect was further stimulated by glucocorticoid treatment of the lung fibroblasts [22], but the nature of the lipid uptake mechanism by the type II cells remained unknown. Yet we were well aware that the synthesis of pulmonary surfactant was a so-called “on demand” system [23–25], in which increased alveolar distension resulted in increased surfactant production, suggesting the existence of a stretch-sensitive signal emanating from the type II cell. With this in mind, we began studying the role of PTHrP in lung development because (a) it was expressed in the embryonic endoderm [26], (b) its receptor was present on the adepithelial mesoderm [27], (c) it had been shown to be stretch regulated in the urinary bladder [28] and uterus [29], and distension of the lung was known to be of physiologic importance in normal lung development [30], (d) knockout of PTHrP caused stage-specific inhibition of fetal lung alveolarization in the transition from the pseudoglandular to the canalicular stage [31].Early functional studies of PTHrP had shown that it was a paracrine factor that stimulated surfactant phospholipid synthesis [32], and that it was stretch regulated [11] (Figure 1, step 1). We subsequently discovered that PTHrP stimulated neutral lipid uptake by developing lung fibroblasts (Figure 1, steps 1 and 2), which we chose to call lipofibroblasts [33], by upregulating ADRP (Figure 1, step 2), a molecule previously shown to be necessary for lipid uptake and storage [34] (Figure 1, step 5). We subsequently found that ADRP was the factor necessary for the uptake of neutral lipid by the lipofibroblast (Figure 1, step 6a) and transit of neutral lipid from the lipofibroblast to the ATII cell for surfactant phospholipid synthesis (Figure 1, step6b) [35, 36]. The missing component for the PTHrP regulation of lung surfactant was the putative lipofibroblast paracrine factor that empirically stimulated ATII cell surfactant synthesis (32). Reasoning that lipofibroblasts were homologs of adipocytes, we hypothesized that lipofibroblasts, like fat cells, expressed leptin, which would bind to the type II cell and stimulate surfactant synthesis—we found that lipofibroblasts did indeed express leptin during rat lung development, plateauing immediately prior to the onset of surfactant synthesis by the type II cell, and that leptin stimulates ATII cell surfactant synthesis [37] (Figure 1, step 7). Importantly, from a mechanistic standpoint, we discovered that type II cells express the leptin receptor [38] (Figure 1, step 8), thus providing a ligand-receptor signaling pathway between the lipofibroblast and type II cell. Moreover, PTHrP was discovered to stimulate leptin expression by fetal lung fibroblasts [37] (Figure 1, steps 1, 2 and 7), thus providing an integrated, growth factor-mediated homeostatic paracrine loop for the synthesis of pulmonary surfactant, as predicted by the PTHrP-based model of lung development.Since the major inducers of bronchopulmonary dysplasia (BPD)—barotrauma [39], oxotrauma [40] and infection [41] —all cause ATII cell injury and damage, we investigated the effects of PTHrP deprivation on the lipofibroblast phenotype, only to discover that in the absence of PTHrP, the lipofibroblast transdifferentiates to a myofibroblast, the cell-type that characterizes lung fibrosis. Furthermore, myofibroblasts cannot support type II cell growth or differentiation, whereas lipofibroblasts can [13], demonstrating the functional significance of these two fibroblast phenotypes for lung development; importantly, when myofibroblasts are treated with a PPARγ agonist, they revert back to the lipofibroblast phenotype, including their ability to promote type II cell growth and differentiation. As a result of these seminal observations, we have found that all of the above-mentioned BPD inducers cause downregulation of alveolar li-pofibroblast PPARγ expression [38, 42, 43], inhibiting normal lung development. Moreover, in all of these conditions, PPARγ agonists have been found to prevent delayed lung development, and in the case of nicotine inhibition of lung development, to even reverse this process [42–51].
## 3. The Evolution of Peroxisome Biology
Peroxisomes were first observed by Rhodin in 1954 [52] and were characterized as a novel cellular organelle by de Duve and Baudhin, whose laboratory first isolated peroxisomes from rat liver and determined their biochemical properties [53]. Since the core mechanisms involved in peroxisome biology are shared by a wide variety of organisms, it suggests a common evolutionary origin. Speculations about the evolution of peroxisomes began shortly after their discovery. Early photomicrographs suggested interactions between the peroxisome and endoplasmic reticulum (ER), leading some to speculate that peroxisomes were derived from the endomembrane system [54]. Subsequently, an alternative view that peroxisomes are independent organelles originating by endosymbiosis was proposed after it was observed that the peroxisomes formed from the division of existing peroxisomes, and that they import proteins [55], both features resembling those of bacterially derived organelles such as mitochondria and chloroplasts. But the most elaborate hypothesis regarding the evolutionary origins of the peroxisome was that of de Duve [56], who proposed a metabolic scenario for the establishment of an endosymbiosis mechanism that entailed the role of peroxisome enzymes in the detoxification of highly reactive oxygen species. In this scenario, the protoperoxisome was acquired at a time when the level of atmospheric oxygen was increasing and represented a toxic compound for the majority of living organisms. This concept is consistent with the evolution of the lung lipofibroblast [15] as an example of how vertebrates have entrained otherwise toxic substances in the environment as physiologic mechanisms [57]. Csete et al. [58] have observed that skeletal muscle satellite cells in culture will spontaneously become adipocytes in 21% oxygen, but not in 6% oxygen, suggesting that the episodic increases and falls in atmospheric oxygen over the last 500 million years may have caused the evolution of fat cells in the lung (lipofibroblasts) and periphery (adipocytes) [3]. Such a mechanism is a selection advantage since the lipofibroblast protects the alveolus against oxidant injury [59], and its production of leptin [37, 38] may have fostered modern-day stretch-regulation of alveolar surfactant [60–63], facilitating the increase in lung surface area [1, 4, 15] and mediating ventilation-perfusion matching [64]. The concomitant production of oxygen free radicals, lipid peroxides and other oxidative products likely generated eicosanoids (22) as a balancing selection for endogenous PPAR ligands. Bolstered by the popularity of the serial endosymbiotic theory [65], this view has been the most widely accepted among biologists.More recently, the endosymbiosis theory for the origin of the peroxisome has been challenged. Experimental evidence shows a close relationship between the ER and peroxisome formation-certain peroxisomal membrane proteins must first be targeted to the ER before they reach the peroxisome [66], and peroxisome-less mutant yeast can form new peroxisomes from the ER upon introduction of the wild-type peroxisome gene [67]. And independent evidence for an evolutionary link between peroxisomes and the ER was provided by phylogenetic studies showing that homologous relationships between components of the peroxisomal import machinery and those of the ER-decay (ERAD) pathway [68, 69]. These data have led the research community to conclude that the peroxisome originates in the ER [70, 71], but have not excluded the possibility of an endosymbiont [71].In the early 1990s,based on sequence homology with previously identified members of nuclear hormone receptor superfamily, three PPAR isotypes (PPARα, β/δ, and γ) were identified, initially in Xenopus laevis and the mouse, and later in human, rat, fish, hamster, and chicken [72, 73]. These isotypes were initially shown to be activated by peroxisome proliferators, a group of substances able to induce peroxisome proliferation. Subsequently, various endogenous and exogenous PPAR ligands were identified, including fatty acids, eicosanoids, synthetic hypolipidemic, and antidiabetic agents [74]. Though PPARs are involved in several aspects of rodent development, they are most importantly involved in various aspects of lipid metabolism and energy homeostasis, with PPARγ’s role in adipogenesis and lipid storage and PPARα’s role in fatty acid catabolism in the liver being the best characterized [74, 75].
## 4. PPARγ Mediates the Evolutionary History of the Adipocyte: Homologies Run Deep
Over the course of vertebrate evolution, during the Phanerozoic Period (the last 500 million years) the amount of oxygen in the atmosphere has increased to its current level of 21%. However, it did not increase linearly; instead, it increased and decreased several times, reaching concentrations as high as 35% and falling to as low as 15% over this time-period [76]. As pointed out above, the increased oxygen tension may have caused the differentiation of muscle satellite cells into lipofibroblasts, or lung adipocytes, in the lung, as the first directly affected anatomic site where the increased atmospheric oxygen would have generated selection pressure for evolutionary change. Consistent with this hypothesized adaptive response to the rising oxygen tension in the atmosphere, we have previously shown that the lipids stored in alveolar lipofibroblasts protect the lung against oxidant injury [59]. Like adipocytes, lipofibroblast differentiation requires upregulation of PPARγ [13, 42, 44], which stimulates differentiation of myofibroblasts to lipofibroblasts [45]. In turn, the leptin secreted by the lipofibroblasts binds to its receptor on the alveolar epithelial cells lining the alveoli, stimulating surfactant synthesis [37, 38], and reducing alveolar surface tension. This results in a more deformable and efficient gas-exchange surface. Such positive selection pressure could have led to the stretch-regulated coregulation of surfactant and microvascular perfusion [77] by PTHrP, recognized physiologically as the mechanism of ventilation-perfusion matching. The evolution of these molecular mechanisms could ultimately have given rise to the definitive mammalian lung alveolus, with maximal gas exchange resulting from coordinate stretch-regulated surfactant production and alveolar capillary perfusion, thinner alveolar walls due to PTHrP’s apoptotic or “programmed cell death” effect on fibroblasts [78], and a blood-gas barrier buttressed by type IV collagen [79]. We speculate that this last feature may have contributed generally to the molecular bauplan for the peripheral microvasculature of evolving vertebrates, given its effect on angiogenesis [80]. One physiologic consequence of the increased oxygenation may have been the concomitant induction of fat cells in the peripheral circulation, which led to endothermy or warm bloodedness- Mezentseva et al. [81] have shown that thermogenic fat cells differentiate from embryonic limb bud mesenchymal cells in association with the expression of PPARγ. The resulting increase in body temperature synergized increased lung oxygenation because lung surfactant is 300% more active at 37°C than at ambient atmospheric temperature (i.e., the body temperature for cold-blooded organisms). For example, map turtles (Graptemys geographica) show different surfactant compositions depending on the ambient temperature [82]. Therefore, the advent of thermogenesis would have facilitated the physical increase in lung surfactant surface-tension-lowering activity. Moreover, it has been shown that treatment of cold blooded lizards with leptin, a product of adipocytes, increases their body temperature [83]. These synergistic selection pressures for adipogenesis would have been further functionally enhanced by the coordinate physiologic effects of epinephrine on the heart [84], lung [85], and fat depots [86], underpinned structurally by the increased production of leptin by fat cells, which is known to promote the formation of blood vessels [80] and bone [87], accommodating the infrastructural changes necessitated by the evolution of complex physiologic traits.
## 5. Everything Put Together Falls Apart in Bronchopulmonary Dysplasia
Since BPD can be induced by all of the varied factors cited above, disrupting epithelial-mesenchymal interactions, we designed experiments to determine the spatiotemporal effects of these disruptors on PTHrP-PPARγ signaling. The effective distension of the newborn lung has a profound physiologic effect on pulmonary homeostasis [60, 61], and stretching of the ATII cell increases the expression and production of PTHrP [11]. In contrast, overdistension of the type II cell [88] results in downregulation of PTHrP expression, and hence PPARγ, simulating the consequences of volutrauma [43]. Since hyperoxia also augments the transdifferentiation of lipofibroblasts to myofibroblasts in vitro [44], we determined the occurrence of hyperoxia-induced alveolar lipo-to-myofibroblast transdifferentiation in vivo. Either 24 hour or 7d in vivo exposure to hyperoxia significantly decreased the expression of lipogenic markers, and significantly increased the myogenic markers in association with arrested alveolarization; the lungs demonstrated relatively larger air spaces, thinned interstitia, decreased secondary septal crest formation, and a significant reduction in radial alveolar counts. Moreover, since lung inflammation is a key factor predisposing preterm infants to BPD, we determined the effects of lipopolysaccharide (LPS) on key alveolar epithelial-mesenchymal paracrine interactions [46]. There were acute (24 hour), significant increases in the expression of PTHrP, PPARγ, ADRP, and surfactant protein-B (SP-B), without any significant effects on the expression of α-smooth muscle actin (αSMA). This was followed (72 h) by significant decreases in the expression of PTHrP, PPARγ, ADRP, and SP-B, accompanied by a significant increase in the expression of αSMA, the key molecular and functional marker for BPD. And since nicotine affects lung growth and development [47], we determined the effect of in utero nicotine exposure on epithelial-mesenchymal interactions as well. Nicotine indirectly inhibited ATII cell proliferation and metabolism via its paracrine effects on the adepithelial lipofibroblasts [48], causing lipo-to-myofibroblast transdifferentiation [49, 89]. In all of the above-cited studies, a PPARγ agonist blocked the disruptive effects, even reversing them in the case of nicotine.
## 6. PPARγ Agonists Turn on a “Master Switch” for Normal Lung Development That Universally Prevents BPD
It is clear from the work outlined above that lipofibroblast PPARγ signaling plays a central role in epithelial-mesenchymal interactions by maintaining alveolar homeostasis in volutrauma, oxotrauma, infection, and nicotine-mediated lung injury. The lipofibroblast expresses PPARγ in response to PTHrP signaling from the ATII cell, resulting in both the direct protection of the mesoderm against oxidant injury [59], and protection against atelectasis by augmenting surfactant protein [37] and phospholipid [38] synthesis. Molecular injury to either the ATII cell or the lipofibroblast downregulates this molecular signaling pathway, causing myofibroblast transdifferentiation. And as indicated above, myofibroblasts cannot promote ATII cell proliferation and differentiation [13], leading to the failed alveolarization characteristic of BPD [50]. In contrast, lipofibroblasts support ATII cell proliferation and differentiation under the influence of factors implicated in the pathogenesis of BPD. This scenario is validated by a plethora of in vitro [13, 44–46, 51, 89, 90] and in vivo [42, 43, 48, 89] studies. Importantly, these studies show that PPARγ agonists such as Prostaglandin J2 and rosiglitazone can prevent or reverse myofibroblast transdifferentiation, potentially preventing the inhibition of alveolarization in the developing lung, the hallmark of CLD of the newborn [13, 42, 45, 47–49, 51, 89, 90].
## 7. Conclusion
Using a basic cell biologic approach to elucidate the pathophysiology of BPD based on evolved cell-physiologic principles, we have determined the paracrine cell/molecular mechanism by which stretch coordinates epithelial-mesenchymal signaling, upregulating key genes for the induction of the prohomeostatic lipofibroblast phenotype—including PPARγ, ADRP, and leptin—and the retrograde stimulation of ATII cell surfactant phospholipid and protein synthesis by the lipofibroblast product leptin. Each of these paracrine interactions requires cell-specific receptors on adjacent cells derived from the endoderm or mesoderm, respectively, that is, PTHrP receptors on the mesoderm and leptin receptors on the endoderm, to specifically mediate the signaling pathways within each cell type. More importantly, we have exploited the cell-specific molecular nature of this mechanism in order to effectively and comprehensively prevent and treat lung injuries that affect this signaling pathway. By identifying deep homologous mechanisms that have determined both the phylogeny and ontogeny of the lung, by using exogenous PPARγ agonists we have been able to prevent and even reverse the effects of a wide variety of injurious agents affecting the epithelial-mesenchymal interactions that have evolved to determine the gas-exchange surface of the lung [1–5].
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*Source: 289867-2012-06-26.xml* | 289867-2012-06-26_289867-2012-06-26.md | 25,355 | PPARγ Signaling Mediates the Evolution, Development, Homeostasis, and Repair of the Lung | Virender K. Rehan; John S. Torday | PPAR Research
(2012) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2012/289867 | 289867-2012-06-26.xml | ---
## Abstract
Epithelial-mesenchymal interactions mediated by soluble growth factors determine the evolution of vertebrate lung physiology, including development, homeostasis, and repair. The final common pathway for all of these positively adaptive properties of the lung is the expression of epithelial parathyroid-hormone-related protein, and its binding to its receptor on the mesenchyme, inducing PPARγ expression by lipofibroblasts. Lipofibroblasts then produce leptin, which binds to alveolar type II cells, stimulating their production of surfactant, which is necessary for both evolutionary and physiologic adaptation to atmospheric oxygen from fish to man. A wide variety of molecular insults disrupt such highly evolved physiologic cell-cell interactions, ranging from overdistention to oxidants, infection, and nicotine, all of which predictably cause loss of mesenchymal peroxisome-proliferator-activated receptor gamma (PPARγ) expression and the transdifferentiation of lipofibroblasts to myofibroblasts, the signature cell type for lung fibrosis. By exploiting such deep cell-molecular functional homologies as targets for leveraging lung homeostasis, we have discovered that we can effectively prevent and/or reverse the deleterious effects of these pathogenic agents, demonstrating the utility of evolutionary biology for the prevention and treatment of chronic lung disease. By understanding mechanisms of health and disease as an evolutionary continuum rather than as dissociated processes, we can evolve predictive medicine.
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## Body
## 1. Background
Normal lung development is the result of a functionally interconnected series of cell-molecular steps. This sequence of biologic events has been positively selected for evolutionarily over biologic time and space [1], resulting in optimal gas exchange mediated by alveolar homeostasis [2]. Elsewhere we have suggested that chronic lung disease (CLD) causes simplification of the lung in a manner consistent with the reversal of the evolutionary process [3, 4]. Therefore, by identifying those mechanisms that have evolved under selection pressure for optimal gas exchange [5], we have theorized that we can effectively reverse the deleterious effects of CLD by promoting the evolutionarily adaptive mechanism [6], rather than by just treating the symptoms [7]. By determining the cell-molecular sequence of spatiotemporal signals that have evolved the lung over phylogeny and ontogeny, we can identify physiologically rational targets for effectively preventing and reversing the deleterious effects of endogenous and exogenous factors known to irreversibly damage normal lung development and function.The ground-breaking tissue culture experiments conducted by Grobstein in 1967 demonstrating that lung development was dependent on endodermal-mesenchymal interactions [8] led to decades of research to determine the underlying cell-molecular mechanisms. The seemingly simple epithelial-mesenchymal interactions during well-defined (embryonic, pseudoglandular, canalicular, saccular, and alveolar), but overlapping stages of lung development result in more than 40 different cell types [9]. Much of what we currently know about the mechanisms involved in lung development is derived from such studies of cultured lung cells signaling through growth factor-mediated pathways for proliferation and differentiation [10–12]. The discovery that epithelial-mesenchymal signaling induced the lipofibroblast via peroxisome proliferator-activated receptor gamma (PPARγ) [13] gave rise to the hypothesis that normal lung development could be reconstituted [14] and recapitulated [15, 16]. The following recounts the essential role of PPARγ in lipofibroblast differentiation and its exploitation for the effective treatment of the preterm lung.
## 2. Epithelial-Mesenchymal Interactions Generate Alveolar Lung Development
The paracrine growth factor model used to study the maturation of the pulmonary surfactant system and the etiology of CLD is shown in the accompanying schematic (see Figure1, steps 1–11). Briefly, we have observed coordinating effects of stretch on alveolar type II (ATII) cell expression of parathyroid-hormone-related protein (PTHrP) and PGE2 (Prostaglandin E2) (step 1), the lipofibroblast PTHrP receptor (step 2), PPARγ upregulation (step 4) via Protein Kinase A activation (step3), its downstream effect on lipofibroblast ADRP (Adipocyte-Differentiation-Related Protein) expression (step 5) and triglyceride (TG) uptake by both the lipofibroblast and the ATII cell (steps 6a and 6b), and on the interaction between lipofibroblast-produced leptin (step7) and the ATII cell leptin receptor (step8), stimulating de novo surfactant phospholipid synthesis by ATII cells (step9). The schematic depicts lipofibroblast-to-myofibroblast transdifferentiation (step10) due to decreased PTHrP following exposure to hyperoxia, volutrauma, or infection. All of these effects are shown to be prevented by PPARγ agonists (step11).Figure 1
Schematic for paracrine determinants of alveolar homeostasis and disease.These studies were originally fostered by Barry Smith’s seminal observation [10] that glucocorticoids accelerate ATII cell surfactant synthesis by stimulating fibroblast synthesis of an oligopeptide that he termed Fibroblast-Pneumonocyte Factor (FPF). It was known at that time that lung, prostate, and mammary mesodermal development were under endocrine control. Importantly, it was shown that early signals emanated from the epithelium to differentiate the immature mesenchyme in the neighboring epithelium of the developing mammary gland [17]. Moreover, Brody’s laboratory had shown that the developing lung fibroblast acquired an adipocyte-like phenotype [18–20], termed the lipid-laden fibroblast, leaving open the question as to whether these cells might be a source of lipid substrate for surfactant synthesis by the ATII cell. The Torday laboratory later discovered the physiologic significance of these lipid-laden fibroblasts by coculturing them with type II cells, which resulted in the rapid trafficking of the lipid from the fibroblast to the type II cell, and its highly enriched incorporation into specific surfactant phospholipids. These data indicated the existence of a specific mechanism for the recruitment of lipid substrate from the vasculature to the type II cell for de novo surfactant synthesis. This trafficking was even more robust when the cocultured cells were treated with glucocorticoids, which are known to stimulate cell-cell interactions in the alveolus in association with increased surfactant synthesis, further reinforcing the notion of a putative mechanism for neutral lipid trafficking for surfactant synthesis since it appeared to be a regulated process [21].Interestingly, the fibroblasts took up the neutral lipid, but did not release it unless they were in the presence of type II cells; conversely, the type II cells were unable to take up neutral lipid. These observations led to the discovery that type II cell secretion of prostaglandin E2 (Figure 1, step 1), a stretch- and glucocorticoid-regulated mechanism, caused the active release of neutral lipid from the fibroblasts [22]. This effect was further stimulated by glucocorticoid treatment of the lung fibroblasts [22], but the nature of the lipid uptake mechanism by the type II cells remained unknown. Yet we were well aware that the synthesis of pulmonary surfactant was a so-called “on demand” system [23–25], in which increased alveolar distension resulted in increased surfactant production, suggesting the existence of a stretch-sensitive signal emanating from the type II cell. With this in mind, we began studying the role of PTHrP in lung development because (a) it was expressed in the embryonic endoderm [26], (b) its receptor was present on the adepithelial mesoderm [27], (c) it had been shown to be stretch regulated in the urinary bladder [28] and uterus [29], and distension of the lung was known to be of physiologic importance in normal lung development [30], (d) knockout of PTHrP caused stage-specific inhibition of fetal lung alveolarization in the transition from the pseudoglandular to the canalicular stage [31].Early functional studies of PTHrP had shown that it was a paracrine factor that stimulated surfactant phospholipid synthesis [32], and that it was stretch regulated [11] (Figure 1, step 1). We subsequently discovered that PTHrP stimulated neutral lipid uptake by developing lung fibroblasts (Figure 1, steps 1 and 2), which we chose to call lipofibroblasts [33], by upregulating ADRP (Figure 1, step 2), a molecule previously shown to be necessary for lipid uptake and storage [34] (Figure 1, step 5). We subsequently found that ADRP was the factor necessary for the uptake of neutral lipid by the lipofibroblast (Figure 1, step 6a) and transit of neutral lipid from the lipofibroblast to the ATII cell for surfactant phospholipid synthesis (Figure 1, step6b) [35, 36]. The missing component for the PTHrP regulation of lung surfactant was the putative lipofibroblast paracrine factor that empirically stimulated ATII cell surfactant synthesis (32). Reasoning that lipofibroblasts were homologs of adipocytes, we hypothesized that lipofibroblasts, like fat cells, expressed leptin, which would bind to the type II cell and stimulate surfactant synthesis—we found that lipofibroblasts did indeed express leptin during rat lung development, plateauing immediately prior to the onset of surfactant synthesis by the type II cell, and that leptin stimulates ATII cell surfactant synthesis [37] (Figure 1, step 7). Importantly, from a mechanistic standpoint, we discovered that type II cells express the leptin receptor [38] (Figure 1, step 8), thus providing a ligand-receptor signaling pathway between the lipofibroblast and type II cell. Moreover, PTHrP was discovered to stimulate leptin expression by fetal lung fibroblasts [37] (Figure 1, steps 1, 2 and 7), thus providing an integrated, growth factor-mediated homeostatic paracrine loop for the synthesis of pulmonary surfactant, as predicted by the PTHrP-based model of lung development.Since the major inducers of bronchopulmonary dysplasia (BPD)—barotrauma [39], oxotrauma [40] and infection [41] —all cause ATII cell injury and damage, we investigated the effects of PTHrP deprivation on the lipofibroblast phenotype, only to discover that in the absence of PTHrP, the lipofibroblast transdifferentiates to a myofibroblast, the cell-type that characterizes lung fibrosis. Furthermore, myofibroblasts cannot support type II cell growth or differentiation, whereas lipofibroblasts can [13], demonstrating the functional significance of these two fibroblast phenotypes for lung development; importantly, when myofibroblasts are treated with a PPARγ agonist, they revert back to the lipofibroblast phenotype, including their ability to promote type II cell growth and differentiation. As a result of these seminal observations, we have found that all of the above-mentioned BPD inducers cause downregulation of alveolar li-pofibroblast PPARγ expression [38, 42, 43], inhibiting normal lung development. Moreover, in all of these conditions, PPARγ agonists have been found to prevent delayed lung development, and in the case of nicotine inhibition of lung development, to even reverse this process [42–51].
## 3. The Evolution of Peroxisome Biology
Peroxisomes were first observed by Rhodin in 1954 [52] and were characterized as a novel cellular organelle by de Duve and Baudhin, whose laboratory first isolated peroxisomes from rat liver and determined their biochemical properties [53]. Since the core mechanisms involved in peroxisome biology are shared by a wide variety of organisms, it suggests a common evolutionary origin. Speculations about the evolution of peroxisomes began shortly after their discovery. Early photomicrographs suggested interactions between the peroxisome and endoplasmic reticulum (ER), leading some to speculate that peroxisomes were derived from the endomembrane system [54]. Subsequently, an alternative view that peroxisomes are independent organelles originating by endosymbiosis was proposed after it was observed that the peroxisomes formed from the division of existing peroxisomes, and that they import proteins [55], both features resembling those of bacterially derived organelles such as mitochondria and chloroplasts. But the most elaborate hypothesis regarding the evolutionary origins of the peroxisome was that of de Duve [56], who proposed a metabolic scenario for the establishment of an endosymbiosis mechanism that entailed the role of peroxisome enzymes in the detoxification of highly reactive oxygen species. In this scenario, the protoperoxisome was acquired at a time when the level of atmospheric oxygen was increasing and represented a toxic compound for the majority of living organisms. This concept is consistent with the evolution of the lung lipofibroblast [15] as an example of how vertebrates have entrained otherwise toxic substances in the environment as physiologic mechanisms [57]. Csete et al. [58] have observed that skeletal muscle satellite cells in culture will spontaneously become adipocytes in 21% oxygen, but not in 6% oxygen, suggesting that the episodic increases and falls in atmospheric oxygen over the last 500 million years may have caused the evolution of fat cells in the lung (lipofibroblasts) and periphery (adipocytes) [3]. Such a mechanism is a selection advantage since the lipofibroblast protects the alveolus against oxidant injury [59], and its production of leptin [37, 38] may have fostered modern-day stretch-regulation of alveolar surfactant [60–63], facilitating the increase in lung surface area [1, 4, 15] and mediating ventilation-perfusion matching [64]. The concomitant production of oxygen free radicals, lipid peroxides and other oxidative products likely generated eicosanoids (22) as a balancing selection for endogenous PPAR ligands. Bolstered by the popularity of the serial endosymbiotic theory [65], this view has been the most widely accepted among biologists.More recently, the endosymbiosis theory for the origin of the peroxisome has been challenged. Experimental evidence shows a close relationship between the ER and peroxisome formation-certain peroxisomal membrane proteins must first be targeted to the ER before they reach the peroxisome [66], and peroxisome-less mutant yeast can form new peroxisomes from the ER upon introduction of the wild-type peroxisome gene [67]. And independent evidence for an evolutionary link between peroxisomes and the ER was provided by phylogenetic studies showing that homologous relationships between components of the peroxisomal import machinery and those of the ER-decay (ERAD) pathway [68, 69]. These data have led the research community to conclude that the peroxisome originates in the ER [70, 71], but have not excluded the possibility of an endosymbiont [71].In the early 1990s,based on sequence homology with previously identified members of nuclear hormone receptor superfamily, three PPAR isotypes (PPARα, β/δ, and γ) were identified, initially in Xenopus laevis and the mouse, and later in human, rat, fish, hamster, and chicken [72, 73]. These isotypes were initially shown to be activated by peroxisome proliferators, a group of substances able to induce peroxisome proliferation. Subsequently, various endogenous and exogenous PPAR ligands were identified, including fatty acids, eicosanoids, synthetic hypolipidemic, and antidiabetic agents [74]. Though PPARs are involved in several aspects of rodent development, they are most importantly involved in various aspects of lipid metabolism and energy homeostasis, with PPARγ’s role in adipogenesis and lipid storage and PPARα’s role in fatty acid catabolism in the liver being the best characterized [74, 75].
## 4. PPARγ Mediates the Evolutionary History of the Adipocyte: Homologies Run Deep
Over the course of vertebrate evolution, during the Phanerozoic Period (the last 500 million years) the amount of oxygen in the atmosphere has increased to its current level of 21%. However, it did not increase linearly; instead, it increased and decreased several times, reaching concentrations as high as 35% and falling to as low as 15% over this time-period [76]. As pointed out above, the increased oxygen tension may have caused the differentiation of muscle satellite cells into lipofibroblasts, or lung adipocytes, in the lung, as the first directly affected anatomic site where the increased atmospheric oxygen would have generated selection pressure for evolutionary change. Consistent with this hypothesized adaptive response to the rising oxygen tension in the atmosphere, we have previously shown that the lipids stored in alveolar lipofibroblasts protect the lung against oxidant injury [59]. Like adipocytes, lipofibroblast differentiation requires upregulation of PPARγ [13, 42, 44], which stimulates differentiation of myofibroblasts to lipofibroblasts [45]. In turn, the leptin secreted by the lipofibroblasts binds to its receptor on the alveolar epithelial cells lining the alveoli, stimulating surfactant synthesis [37, 38], and reducing alveolar surface tension. This results in a more deformable and efficient gas-exchange surface. Such positive selection pressure could have led to the stretch-regulated coregulation of surfactant and microvascular perfusion [77] by PTHrP, recognized physiologically as the mechanism of ventilation-perfusion matching. The evolution of these molecular mechanisms could ultimately have given rise to the definitive mammalian lung alveolus, with maximal gas exchange resulting from coordinate stretch-regulated surfactant production and alveolar capillary perfusion, thinner alveolar walls due to PTHrP’s apoptotic or “programmed cell death” effect on fibroblasts [78], and a blood-gas barrier buttressed by type IV collagen [79]. We speculate that this last feature may have contributed generally to the molecular bauplan for the peripheral microvasculature of evolving vertebrates, given its effect on angiogenesis [80]. One physiologic consequence of the increased oxygenation may have been the concomitant induction of fat cells in the peripheral circulation, which led to endothermy or warm bloodedness- Mezentseva et al. [81] have shown that thermogenic fat cells differentiate from embryonic limb bud mesenchymal cells in association with the expression of PPARγ. The resulting increase in body temperature synergized increased lung oxygenation because lung surfactant is 300% more active at 37°C than at ambient atmospheric temperature (i.e., the body temperature for cold-blooded organisms). For example, map turtles (Graptemys geographica) show different surfactant compositions depending on the ambient temperature [82]. Therefore, the advent of thermogenesis would have facilitated the physical increase in lung surfactant surface-tension-lowering activity. Moreover, it has been shown that treatment of cold blooded lizards with leptin, a product of adipocytes, increases their body temperature [83]. These synergistic selection pressures for adipogenesis would have been further functionally enhanced by the coordinate physiologic effects of epinephrine on the heart [84], lung [85], and fat depots [86], underpinned structurally by the increased production of leptin by fat cells, which is known to promote the formation of blood vessels [80] and bone [87], accommodating the infrastructural changes necessitated by the evolution of complex physiologic traits.
## 5. Everything Put Together Falls Apart in Bronchopulmonary Dysplasia
Since BPD can be induced by all of the varied factors cited above, disrupting epithelial-mesenchymal interactions, we designed experiments to determine the spatiotemporal effects of these disruptors on PTHrP-PPARγ signaling. The effective distension of the newborn lung has a profound physiologic effect on pulmonary homeostasis [60, 61], and stretching of the ATII cell increases the expression and production of PTHrP [11]. In contrast, overdistension of the type II cell [88] results in downregulation of PTHrP expression, and hence PPARγ, simulating the consequences of volutrauma [43]. Since hyperoxia also augments the transdifferentiation of lipofibroblasts to myofibroblasts in vitro [44], we determined the occurrence of hyperoxia-induced alveolar lipo-to-myofibroblast transdifferentiation in vivo. Either 24 hour or 7d in vivo exposure to hyperoxia significantly decreased the expression of lipogenic markers, and significantly increased the myogenic markers in association with arrested alveolarization; the lungs demonstrated relatively larger air spaces, thinned interstitia, decreased secondary septal crest formation, and a significant reduction in radial alveolar counts. Moreover, since lung inflammation is a key factor predisposing preterm infants to BPD, we determined the effects of lipopolysaccharide (LPS) on key alveolar epithelial-mesenchymal paracrine interactions [46]. There were acute (24 hour), significant increases in the expression of PTHrP, PPARγ, ADRP, and surfactant protein-B (SP-B), without any significant effects on the expression of α-smooth muscle actin (αSMA). This was followed (72 h) by significant decreases in the expression of PTHrP, PPARγ, ADRP, and SP-B, accompanied by a significant increase in the expression of αSMA, the key molecular and functional marker for BPD. And since nicotine affects lung growth and development [47], we determined the effect of in utero nicotine exposure on epithelial-mesenchymal interactions as well. Nicotine indirectly inhibited ATII cell proliferation and metabolism via its paracrine effects on the adepithelial lipofibroblasts [48], causing lipo-to-myofibroblast transdifferentiation [49, 89]. In all of the above-cited studies, a PPARγ agonist blocked the disruptive effects, even reversing them in the case of nicotine.
## 6. PPARγ Agonists Turn on a “Master Switch” for Normal Lung Development That Universally Prevents BPD
It is clear from the work outlined above that lipofibroblast PPARγ signaling plays a central role in epithelial-mesenchymal interactions by maintaining alveolar homeostasis in volutrauma, oxotrauma, infection, and nicotine-mediated lung injury. The lipofibroblast expresses PPARγ in response to PTHrP signaling from the ATII cell, resulting in both the direct protection of the mesoderm against oxidant injury [59], and protection against atelectasis by augmenting surfactant protein [37] and phospholipid [38] synthesis. Molecular injury to either the ATII cell or the lipofibroblast downregulates this molecular signaling pathway, causing myofibroblast transdifferentiation. And as indicated above, myofibroblasts cannot promote ATII cell proliferation and differentiation [13], leading to the failed alveolarization characteristic of BPD [50]. In contrast, lipofibroblasts support ATII cell proliferation and differentiation under the influence of factors implicated in the pathogenesis of BPD. This scenario is validated by a plethora of in vitro [13, 44–46, 51, 89, 90] and in vivo [42, 43, 48, 89] studies. Importantly, these studies show that PPARγ agonists such as Prostaglandin J2 and rosiglitazone can prevent or reverse myofibroblast transdifferentiation, potentially preventing the inhibition of alveolarization in the developing lung, the hallmark of CLD of the newborn [13, 42, 45, 47–49, 51, 89, 90].
## 7. Conclusion
Using a basic cell biologic approach to elucidate the pathophysiology of BPD based on evolved cell-physiologic principles, we have determined the paracrine cell/molecular mechanism by which stretch coordinates epithelial-mesenchymal signaling, upregulating key genes for the induction of the prohomeostatic lipofibroblast phenotype—including PPARγ, ADRP, and leptin—and the retrograde stimulation of ATII cell surfactant phospholipid and protein synthesis by the lipofibroblast product leptin. Each of these paracrine interactions requires cell-specific receptors on adjacent cells derived from the endoderm or mesoderm, respectively, that is, PTHrP receptors on the mesoderm and leptin receptors on the endoderm, to specifically mediate the signaling pathways within each cell type. More importantly, we have exploited the cell-specific molecular nature of this mechanism in order to effectively and comprehensively prevent and treat lung injuries that affect this signaling pathway. By identifying deep homologous mechanisms that have determined both the phylogeny and ontogeny of the lung, by using exogenous PPARγ agonists we have been able to prevent and even reverse the effects of a wide variety of injurious agents affecting the epithelial-mesenchymal interactions that have evolved to determine the gas-exchange surface of the lung [1–5].
---
*Source: 289867-2012-06-26.xml* | 2012 |
# Surgical Resection of Anastomotic Stenosis after Rectal Cancer Surgery Using a Circular Stapler and Colostomy with Double Orifice
**Authors:** Toru Imagami; Satoru Takayama; Yohei Maeda; Taku Hattori; Ryohei Matsui; Masaki Sakamoto; Hisanori Kani
**Journal:** Case Reports in Surgery
(2019)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2019/2898691
---
## Abstract
The double stapling technique has greatly facilitated intestinal reconstruction, particularly for anastomosis after anterior resection. However, anastomotic stenosis may occur, which sometimes requires surgical treatment. Redo surgery with reresection and reanastomosis presents a high risk of complications. Treatment methods need to be selected depending on the degree and location of stenosis. In an effort to propose a new resolution, reporting new cases and sharing valid experiences are necessary. An 82-year-old man diagnosed with rectal cancer had undergone laparoscopic anterior resection. Endoscopic balloon dilation performed for anastomotic stenosis had failed. Therefore, colostomy with double orifice was constructed on the oral side at 10 cm from the stenosis. Approaching from the anal and stoma side, the anastomotic stenosis was resected using a circular stapler. The colostomy was closed 1 month after surgery. Stenosis resection using a circular stapler requires the following steps: (1) passing the center shaft through the stenosis, (2) inserting the anvil head into the oral side of the stenosis, and (3) attaching the anvil head to the center shaft. This method can resect the stenosis using a circular stapler without being affected by postoperative adhesion in the pelvis. Compared to endoscopic balloon dilation, resection of the stricture by the circular stapler is thought to be reliable. This technique is particularly effective for localized stenosis, including anastomotic stenosis. It is considered that this method is minimally invasive and is low risk for complications. This method can contribute to the useful surgical option for refractory anastomotic stenosis after anterior resection.
---
## Body
## 1. Introduction
The double stapling technique (DST) has greatly facilitated intestinal reconstruction, particularly for anastomosis after low anterior resection [1]. A postoperative anastomotic stricture may occur after anterior rectal resection and/or in case of low rectal anastomosis [2]. In recent years, endoscopic dilation has been widely used to relieve anastomotic stenosis. However, when this procedure is unsuccessful, surgical treatment is required. In previous reports, the morbidity rate after the redo surgery for colorectal anastomosis when endoscopic dilation had failed was considerably high, with 46% cases classified as having Clavien-Dindo grades II–IV complications [3, 4]. Therefore, alternative surgical techniques need to be established. There are many reports of immediate and late complications associated with stapled anastomosis; however, very little information is available regarding the technical difficulties encountered during surgery, despite the popularity of use of mechanical staplers in colorectal surgery [5].In this report, we present a case for which, after endoscopic balloon dilation was unsuccessful for anastomotic stenosis after anterior resection, we surgically resected the anastomotic stricture using a circular stapler following a temporary sigmoid colostomy with double orifice.
## 2. Case Presentation
An 82-year-old man was referred to our hospital for the evaluation of bloody stools. He had a medical history of hypertension. A colonoscopy revealed a semicircumferential rectal adenocarcinoma at 20 cm from the anal verge, and computed tomography revealed no evidence of lymph node metastasis or distant metastasis. He underwent a laparoscopic anterior resection. His pathological diagnosis was stage T3N0M0. For anastomosis, DST was performed using a 60 mm linear stapler and a 31 mm circular stapler. He required a blood transfusion for postoperative melena and was discharged 20 days postoperatively.The patient experienced frequent diarrhea 1 month after surgery, and a sensation of fullness in the abdomen appeared 2 months after surgery. He was hospitalized with a large intestinal obstruction 4 months after surgery. The colonoscopy revealed severe stenosis at 15 cm from the anal verge (Figure1(a)). A staple was confirmed there, and he was diagnosed with anastomotic stenosis. Endoscopic balloon dilation was performed several times (Figure 1(b)), allowing the passage of loose stool. Mucosal injury occurred during the last dilation (Figure 1(c)), making further balloon dilation difficult. He was discharged with drug treatment.Figure 1
(a) Colonoscopy showed severe anastomotic stenosis 4 months after surgery. (b) When the balloon was expanded by injecting a contrast agent, localized stenosis was shown (yellow arrow). (c) Mucosal injury occurred during the fourth endoscopic balloon dilation therapy. The passage of colonoscope has become possible.
(a)
(b)
(c)Nine months after surgery, the patient was hospitalized again with a large intestinal obstruction. The colonoscopy revealed the complete obstruction of the anastomotic site (Figure2). Based on previous history, the diagnosis of anastomotic stenosis resistant to endoscopic treatment was made. We decided to perform surgical decompression of the colon.Figure 2
Colonoscopy showed restenosis of the anastomotic site 5 months after balloon dilation. It seemed that endoscopic colonic decompression could not be done.Under general anesthesia, the abdominal cavity was laparoscopically investigated. However, the anastomotic site was difficult to visualize owing to postoperative severe adhesion in the pelvis. We performed colostomy with double orifices on the anal side as close as possible in the sigmoid colon. The colonoscopy confirmed that colostomy was 10 cm to the oral side from the anastomotic stenosis. We decided to perform a reresection of anastomotic stenosis using a circular stapler.
## 3. Surgical Procedure
Under general anesthesia, the patient was placed in lithotomy position. The colonoscopy was transanally inserted until the stenosis (Figure3(a)). A biopsy forceps was passed through the stenosis and was guided to the stoma. Using no. 0 silk thread, the biopsy forceps was passed through the stenosis and was guided to the anus (Figure 3(b)). We decided to use a 31 mm EEA circular stapler® (Medtronic Inc.) for the reresection of anastomotic stenosis. After tying the silk thread to the suture hole at the tip of the anvil, the anvil was inserted from the stoma toward the stenosis. Next, using the silk thread as a guide tool, the anvil central rod was passed as a bougie to the anastomotic stenosis. Subsequently, the anvil was inserted from the anus, and similarly, the anvil central rod was passed in the direction of the stoma as a bougie (Figure 3(c)). The instrument body was inserted transanally, and the central shaft was passed through the hole created with mechanical bougie by the anvil central rod (Figure 3(d)). Looking inside the stoma, the central shaft was visually confirmed to pass through the anastomotic stenosis. The anvil was inserted from the stoma, and the anvil central rod was manually attached to the central shaft (Figure 3(e)). The EEA circular stapler® is closed, activated, and fired. After resection, the colonoscopy confirmed that the procedure was successful (Figure 3(f)).Figure 3
(a) A pin hole was made with a biopsy forceps at anastomotic stenosis. The biopsy forceps was passed through the stenosis. (b) Silk thread was passed as a guide tool from the stoma to the anus. (c) By pulling the silk thread tied to the suture hole of the anvil, the anvil central rod was passed through the stenosis as a bougie. (d) The instrument body was inserted transanally, and the central shaft was passed through the hole of stenosis made with the mechanical bougie. (e) Looking inside the stoma, the anvil center rod was manually attached to the central shaft under direct viewing. (f) After EEA firing, the colonoscopy showed that stenosis was resected successfully.
(a)
(b)
(c)
(d)
(e)
(f)
## 4. Postoperative Course
The patient’s postoperative course was unremarkable. The colonoscopy revealed no stenosis in anastomosis 4 days after surgery, and the patient was discharged 5 days after surgery. The colonoscopy showed no restenosis 1 month after surgery (Figure4), and the patient could undergo stoma closure. The patient remains cancer-free with no evidence of recurrence at 36 months after rectal cancer surgery.Figure 4
Colonoscopy showed no restenosis 1 month after resection of anastomotic stenosis.
## 5. Discussion
Presently, DST allows lower anastomosis in some patients, and it can be easily and safely performed [6]. However, after colorectal surgery, a certain number of patients experience anastomotic complications, including anastomotic stenosis. Anastomotic colonic or rectal strictures, which are the result of the proliferation of the fibroblasts and cross-linking of collagen fibers, represent a challenging complication after colonic or rectal resection [7, 8]. Although healing of intestinal anastomosis has been extensively studied, the pathophysiology and contributing factors are still only partially understood; briefly, tissue ischemia, leakage, suturing technique (i.e., the use of a circular stapler), and radiotherapy have been shown to be implicated [8]. Circular stapled anastomosis is an inverted anastomosis, clamping muscular and serosal tissues between both mucosal tissues, thereby resulting in anastomotic stenosis from associated scar formation [9]. Currently, no methods capable of completely preventing anastomotic stenosis have been established.Endoscopic balloon dilation has been reported to be a widely used technique and a safe approach to effectively relieve an anastomotic stenosis following colorectal resection [10]. However, endoscopic balloon dilation can fail to improve anastomotic stenosis after multiple sessions of dilation, and the stricture recurrence rate is high, reaching up to 18%–20% [11]. In recent years, favorable results of endoscopic electrocautery incision have been reported [8, 11]. A variety of endoscopic techniques have been described; however, data from controlled prospective trials representing the optimal approach are lacking [12]. Treatment methods need to be selected depending on the degree and location of stenosis, justifying an increase of treatment options. Taken together, reporting new cases and their resolution is essential for sharing valid experiences and suggesting alternative options [4].In the case reported here, we first performed endoscopic balloon dilation for anastomotic stenosis. However, because of mucosal injury during the fourth balloon dilation, further balloon dilation presented a risk of perforation deemed too high. We had no experience of an alternative endoscopic procedure, such as endoscopic electrocautery incision. Instead, we had previous experience of laparoscopic surgery to simultaneously repair the perforation and stenosis using a circular stapler in cases where iatrogenic perforation had been caused by endoscopic balloon dilation [12]. Therefore, we decided resecting the anastomotic stenosis with a circular stapler. By completing the procedure in the intestinal tract, this technique is not affected by postoperative adhesion in the pelvis. This is expected to lead to minimally invasive surgery. From the experience of this case, anastomotic resection with a circular stapler is thought to be more reliable treatment than repeating endoscopic balloon dilation. Our technique requires a colostomy with double orifices near the oral side of the stenosis. If the anastomotic stenosis after anterior resection occurs, it is recommended that a loop stoma of the sigmoid colon is constructed as close to the stenosis as possible.The following steps must be performed for stenosis removal using a circular stapler: (1) passing the central shaft through the stenosis, (2) inserting the anvil head into the oral side of the stenosis, and (3) attaching the anvil central rod to the central shaft. The surgical procedure for the above steps was safely performed. First, the silk thread was passed as a guide tool; next, we mechanically dilated the stenosis using the anvil central rod along the silk thread. This technique mimics the Seldinger method and makes it possible to safely pass through the central shaft. The anvil was inserted on the oral side of the stenosis by performing colostomy with double orifices close to the stenosis. Looking inside the anal side of the colectomy, we could observe the anastomotic stenosis and the central shaft passing through. The anvil central rod can be manually attached to the central shaft in the intestinal tract, which is considered a safe and reliable method.This technique requires consideration of the distance between the anal verge of the stenosis and the cause of the stenosis. Since the instrument body of the circular stapler must reach the stenosis transanally, a stenosis within 25 cm from the anus is considered to be an indication for this technique. Another consideration is that there is a limit to the thickness of the tissue that can be sandwiched with the circular stapler. Therefore, inflammatory diffuse stenosis cannot be resected. Anastomotic stenosis is the best indication for this technique, as stenosis is usually localized. For localized stenosis, resection may be possible; it may be resectable even after radiotherapy or fistulization. In this case, as shown in Figure1(c), the range of stenosis was limited. The patient’s condition was a good indication for this technique.Although several techniques for resecting the anastomotic stenosis using a circular stapler have been reported, our procedure is different and unique. Araki et al. reported a technique that entails to mechanically dilate the stenosis using a metal bougie, passing the stenosis with the anvil attached to the central shaft and then resecting the stenosis using a circular stapler [13]. In our case, the anal side was distant, and the degree of stenosis was severe; therefore, neither the metal bougie nor the anvil could transanally pass through the anastomotic stenosis. Rees et al. and Christos et al. reported a surgical experience resecting the stenosis with a circular stapler that entailed inserting the anvil from the colotomy or colostomy and carrying the anvil to the stenosis using an endoscope snare [13, 14]. Our method is modified to allow manual attachment in the intestinal tract with direct viewing. This is the first report where, to the best our knowledge, the postoperative anastomotic stenosis was resected using a circular stapler after systematically performing colostomy.However, a disadvantage of this surgery is the simultaneous requirement of a temporary colostomy. Sufficient intestinal length at the left-side colon is necessary for the colostomy and its closure after rectal cancer surgery. In addition, general anesthesia being necessary several times is considered a disadvantage.Our method can potentially be improved in the future. Because we used this technique for the first time, we decided to close the colostomy after confirming that restenosis did not occur. Considering the course of this case, it may be possible to simultaneously perform the colostomy closure and the stricture excision during a single intervention. If preoperative bowel preparation is possible, one-time surgery can be performed, as reported previously [15]. Briefly, the intestine is incised within 10 cm on the oral side from the stenosis, an anvil is inserted, the stenosis is excised by a circular stapler, and the incisional intestinal tract is sutured. If the oral side of the colon is incised within 10 cm from the stenosis, the lesion can be directly visualized, which represents a new finding. A colorectal tube may be a useful option for bowel preparation. If preoperative bowel preparation is not possible, the sigmoid colonic incision presents a high risk of intraperitoneal contamination, requiring a temporary stoma.Although its adaptation is limited, this technique is a useful surgical procedure for anastomotic stenosis. The long-term result of this procedure is unknown, and a careful follow-up observation is considered necessary.
## 6. Conclusion
We surgically resected the anastomotic stenosis using a circular stapler following a temporary sigmoid colostomy with double orifice. This method can resect the stenosis using a circular stapler without being affected by postoperative adhesion in the pelvis. Compared to repeated endoscopic balloon dilation, resection of the stenosis by a circular stapler was a reliable treatment. Although multiple surgeries are necessary, both are minimally invasive and are low risk for complications. Based on these findings, this method is a very useful option for an anastomotic stricture after anterior resection. We believe that this report can contribute to the surgical option for refractory anastomotic stenosis after anterior resection.
---
*Source: 2898691-2019-05-12.xml* | 2898691-2019-05-12_2898691-2019-05-12.md | 17,298 | Surgical Resection of Anastomotic Stenosis after Rectal Cancer Surgery Using a Circular Stapler and Colostomy with Double Orifice | Toru Imagami; Satoru Takayama; Yohei Maeda; Taku Hattori; Ryohei Matsui; Masaki Sakamoto; Hisanori Kani | Case Reports in Surgery
(2019) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2019/2898691 | 2898691-2019-05-12.xml | ---
## Abstract
The double stapling technique has greatly facilitated intestinal reconstruction, particularly for anastomosis after anterior resection. However, anastomotic stenosis may occur, which sometimes requires surgical treatment. Redo surgery with reresection and reanastomosis presents a high risk of complications. Treatment methods need to be selected depending on the degree and location of stenosis. In an effort to propose a new resolution, reporting new cases and sharing valid experiences are necessary. An 82-year-old man diagnosed with rectal cancer had undergone laparoscopic anterior resection. Endoscopic balloon dilation performed for anastomotic stenosis had failed. Therefore, colostomy with double orifice was constructed on the oral side at 10 cm from the stenosis. Approaching from the anal and stoma side, the anastomotic stenosis was resected using a circular stapler. The colostomy was closed 1 month after surgery. Stenosis resection using a circular stapler requires the following steps: (1) passing the center shaft through the stenosis, (2) inserting the anvil head into the oral side of the stenosis, and (3) attaching the anvil head to the center shaft. This method can resect the stenosis using a circular stapler without being affected by postoperative adhesion in the pelvis. Compared to endoscopic balloon dilation, resection of the stricture by the circular stapler is thought to be reliable. This technique is particularly effective for localized stenosis, including anastomotic stenosis. It is considered that this method is minimally invasive and is low risk for complications. This method can contribute to the useful surgical option for refractory anastomotic stenosis after anterior resection.
---
## Body
## 1. Introduction
The double stapling technique (DST) has greatly facilitated intestinal reconstruction, particularly for anastomosis after low anterior resection [1]. A postoperative anastomotic stricture may occur after anterior rectal resection and/or in case of low rectal anastomosis [2]. In recent years, endoscopic dilation has been widely used to relieve anastomotic stenosis. However, when this procedure is unsuccessful, surgical treatment is required. In previous reports, the morbidity rate after the redo surgery for colorectal anastomosis when endoscopic dilation had failed was considerably high, with 46% cases classified as having Clavien-Dindo grades II–IV complications [3, 4]. Therefore, alternative surgical techniques need to be established. There are many reports of immediate and late complications associated with stapled anastomosis; however, very little information is available regarding the technical difficulties encountered during surgery, despite the popularity of use of mechanical staplers in colorectal surgery [5].In this report, we present a case for which, after endoscopic balloon dilation was unsuccessful for anastomotic stenosis after anterior resection, we surgically resected the anastomotic stricture using a circular stapler following a temporary sigmoid colostomy with double orifice.
## 2. Case Presentation
An 82-year-old man was referred to our hospital for the evaluation of bloody stools. He had a medical history of hypertension. A colonoscopy revealed a semicircumferential rectal adenocarcinoma at 20 cm from the anal verge, and computed tomography revealed no evidence of lymph node metastasis or distant metastasis. He underwent a laparoscopic anterior resection. His pathological diagnosis was stage T3N0M0. For anastomosis, DST was performed using a 60 mm linear stapler and a 31 mm circular stapler. He required a blood transfusion for postoperative melena and was discharged 20 days postoperatively.The patient experienced frequent diarrhea 1 month after surgery, and a sensation of fullness in the abdomen appeared 2 months after surgery. He was hospitalized with a large intestinal obstruction 4 months after surgery. The colonoscopy revealed severe stenosis at 15 cm from the anal verge (Figure1(a)). A staple was confirmed there, and he was diagnosed with anastomotic stenosis. Endoscopic balloon dilation was performed several times (Figure 1(b)), allowing the passage of loose stool. Mucosal injury occurred during the last dilation (Figure 1(c)), making further balloon dilation difficult. He was discharged with drug treatment.Figure 1
(a) Colonoscopy showed severe anastomotic stenosis 4 months after surgery. (b) When the balloon was expanded by injecting a contrast agent, localized stenosis was shown (yellow arrow). (c) Mucosal injury occurred during the fourth endoscopic balloon dilation therapy. The passage of colonoscope has become possible.
(a)
(b)
(c)Nine months after surgery, the patient was hospitalized again with a large intestinal obstruction. The colonoscopy revealed the complete obstruction of the anastomotic site (Figure2). Based on previous history, the diagnosis of anastomotic stenosis resistant to endoscopic treatment was made. We decided to perform surgical decompression of the colon.Figure 2
Colonoscopy showed restenosis of the anastomotic site 5 months after balloon dilation. It seemed that endoscopic colonic decompression could not be done.Under general anesthesia, the abdominal cavity was laparoscopically investigated. However, the anastomotic site was difficult to visualize owing to postoperative severe adhesion in the pelvis. We performed colostomy with double orifices on the anal side as close as possible in the sigmoid colon. The colonoscopy confirmed that colostomy was 10 cm to the oral side from the anastomotic stenosis. We decided to perform a reresection of anastomotic stenosis using a circular stapler.
## 3. Surgical Procedure
Under general anesthesia, the patient was placed in lithotomy position. The colonoscopy was transanally inserted until the stenosis (Figure3(a)). A biopsy forceps was passed through the stenosis and was guided to the stoma. Using no. 0 silk thread, the biopsy forceps was passed through the stenosis and was guided to the anus (Figure 3(b)). We decided to use a 31 mm EEA circular stapler® (Medtronic Inc.) for the reresection of anastomotic stenosis. After tying the silk thread to the suture hole at the tip of the anvil, the anvil was inserted from the stoma toward the stenosis. Next, using the silk thread as a guide tool, the anvil central rod was passed as a bougie to the anastomotic stenosis. Subsequently, the anvil was inserted from the anus, and similarly, the anvil central rod was passed in the direction of the stoma as a bougie (Figure 3(c)). The instrument body was inserted transanally, and the central shaft was passed through the hole created with mechanical bougie by the anvil central rod (Figure 3(d)). Looking inside the stoma, the central shaft was visually confirmed to pass through the anastomotic stenosis. The anvil was inserted from the stoma, and the anvil central rod was manually attached to the central shaft (Figure 3(e)). The EEA circular stapler® is closed, activated, and fired. After resection, the colonoscopy confirmed that the procedure was successful (Figure 3(f)).Figure 3
(a) A pin hole was made with a biopsy forceps at anastomotic stenosis. The biopsy forceps was passed through the stenosis. (b) Silk thread was passed as a guide tool from the stoma to the anus. (c) By pulling the silk thread tied to the suture hole of the anvil, the anvil central rod was passed through the stenosis as a bougie. (d) The instrument body was inserted transanally, and the central shaft was passed through the hole of stenosis made with the mechanical bougie. (e) Looking inside the stoma, the anvil center rod was manually attached to the central shaft under direct viewing. (f) After EEA firing, the colonoscopy showed that stenosis was resected successfully.
(a)
(b)
(c)
(d)
(e)
(f)
## 4. Postoperative Course
The patient’s postoperative course was unremarkable. The colonoscopy revealed no stenosis in anastomosis 4 days after surgery, and the patient was discharged 5 days after surgery. The colonoscopy showed no restenosis 1 month after surgery (Figure4), and the patient could undergo stoma closure. The patient remains cancer-free with no evidence of recurrence at 36 months after rectal cancer surgery.Figure 4
Colonoscopy showed no restenosis 1 month after resection of anastomotic stenosis.
## 5. Discussion
Presently, DST allows lower anastomosis in some patients, and it can be easily and safely performed [6]. However, after colorectal surgery, a certain number of patients experience anastomotic complications, including anastomotic stenosis. Anastomotic colonic or rectal strictures, which are the result of the proliferation of the fibroblasts and cross-linking of collagen fibers, represent a challenging complication after colonic or rectal resection [7, 8]. Although healing of intestinal anastomosis has been extensively studied, the pathophysiology and contributing factors are still only partially understood; briefly, tissue ischemia, leakage, suturing technique (i.e., the use of a circular stapler), and radiotherapy have been shown to be implicated [8]. Circular stapled anastomosis is an inverted anastomosis, clamping muscular and serosal tissues between both mucosal tissues, thereby resulting in anastomotic stenosis from associated scar formation [9]. Currently, no methods capable of completely preventing anastomotic stenosis have been established.Endoscopic balloon dilation has been reported to be a widely used technique and a safe approach to effectively relieve an anastomotic stenosis following colorectal resection [10]. However, endoscopic balloon dilation can fail to improve anastomotic stenosis after multiple sessions of dilation, and the stricture recurrence rate is high, reaching up to 18%–20% [11]. In recent years, favorable results of endoscopic electrocautery incision have been reported [8, 11]. A variety of endoscopic techniques have been described; however, data from controlled prospective trials representing the optimal approach are lacking [12]. Treatment methods need to be selected depending on the degree and location of stenosis, justifying an increase of treatment options. Taken together, reporting new cases and their resolution is essential for sharing valid experiences and suggesting alternative options [4].In the case reported here, we first performed endoscopic balloon dilation for anastomotic stenosis. However, because of mucosal injury during the fourth balloon dilation, further balloon dilation presented a risk of perforation deemed too high. We had no experience of an alternative endoscopic procedure, such as endoscopic electrocautery incision. Instead, we had previous experience of laparoscopic surgery to simultaneously repair the perforation and stenosis using a circular stapler in cases where iatrogenic perforation had been caused by endoscopic balloon dilation [12]. Therefore, we decided resecting the anastomotic stenosis with a circular stapler. By completing the procedure in the intestinal tract, this technique is not affected by postoperative adhesion in the pelvis. This is expected to lead to minimally invasive surgery. From the experience of this case, anastomotic resection with a circular stapler is thought to be more reliable treatment than repeating endoscopic balloon dilation. Our technique requires a colostomy with double orifices near the oral side of the stenosis. If the anastomotic stenosis after anterior resection occurs, it is recommended that a loop stoma of the sigmoid colon is constructed as close to the stenosis as possible.The following steps must be performed for stenosis removal using a circular stapler: (1) passing the central shaft through the stenosis, (2) inserting the anvil head into the oral side of the stenosis, and (3) attaching the anvil central rod to the central shaft. The surgical procedure for the above steps was safely performed. First, the silk thread was passed as a guide tool; next, we mechanically dilated the stenosis using the anvil central rod along the silk thread. This technique mimics the Seldinger method and makes it possible to safely pass through the central shaft. The anvil was inserted on the oral side of the stenosis by performing colostomy with double orifices close to the stenosis. Looking inside the anal side of the colectomy, we could observe the anastomotic stenosis and the central shaft passing through. The anvil central rod can be manually attached to the central shaft in the intestinal tract, which is considered a safe and reliable method.This technique requires consideration of the distance between the anal verge of the stenosis and the cause of the stenosis. Since the instrument body of the circular stapler must reach the stenosis transanally, a stenosis within 25 cm from the anus is considered to be an indication for this technique. Another consideration is that there is a limit to the thickness of the tissue that can be sandwiched with the circular stapler. Therefore, inflammatory diffuse stenosis cannot be resected. Anastomotic stenosis is the best indication for this technique, as stenosis is usually localized. For localized stenosis, resection may be possible; it may be resectable even after radiotherapy or fistulization. In this case, as shown in Figure1(c), the range of stenosis was limited. The patient’s condition was a good indication for this technique.Although several techniques for resecting the anastomotic stenosis using a circular stapler have been reported, our procedure is different and unique. Araki et al. reported a technique that entails to mechanically dilate the stenosis using a metal bougie, passing the stenosis with the anvil attached to the central shaft and then resecting the stenosis using a circular stapler [13]. In our case, the anal side was distant, and the degree of stenosis was severe; therefore, neither the metal bougie nor the anvil could transanally pass through the anastomotic stenosis. Rees et al. and Christos et al. reported a surgical experience resecting the stenosis with a circular stapler that entailed inserting the anvil from the colotomy or colostomy and carrying the anvil to the stenosis using an endoscope snare [13, 14]. Our method is modified to allow manual attachment in the intestinal tract with direct viewing. This is the first report where, to the best our knowledge, the postoperative anastomotic stenosis was resected using a circular stapler after systematically performing colostomy.However, a disadvantage of this surgery is the simultaneous requirement of a temporary colostomy. Sufficient intestinal length at the left-side colon is necessary for the colostomy and its closure after rectal cancer surgery. In addition, general anesthesia being necessary several times is considered a disadvantage.Our method can potentially be improved in the future. Because we used this technique for the first time, we decided to close the colostomy after confirming that restenosis did not occur. Considering the course of this case, it may be possible to simultaneously perform the colostomy closure and the stricture excision during a single intervention. If preoperative bowel preparation is possible, one-time surgery can be performed, as reported previously [15]. Briefly, the intestine is incised within 10 cm on the oral side from the stenosis, an anvil is inserted, the stenosis is excised by a circular stapler, and the incisional intestinal tract is sutured. If the oral side of the colon is incised within 10 cm from the stenosis, the lesion can be directly visualized, which represents a new finding. A colorectal tube may be a useful option for bowel preparation. If preoperative bowel preparation is not possible, the sigmoid colonic incision presents a high risk of intraperitoneal contamination, requiring a temporary stoma.Although its adaptation is limited, this technique is a useful surgical procedure for anastomotic stenosis. The long-term result of this procedure is unknown, and a careful follow-up observation is considered necessary.
## 6. Conclusion
We surgically resected the anastomotic stenosis using a circular stapler following a temporary sigmoid colostomy with double orifice. This method can resect the stenosis using a circular stapler without being affected by postoperative adhesion in the pelvis. Compared to repeated endoscopic balloon dilation, resection of the stenosis by a circular stapler was a reliable treatment. Although multiple surgeries are necessary, both are minimally invasive and are low risk for complications. Based on these findings, this method is a very useful option for an anastomotic stricture after anterior resection. We believe that this report can contribute to the surgical option for refractory anastomotic stenosis after anterior resection.
---
*Source: 2898691-2019-05-12.xml* | 2019 |
# Response to: Comment on “Choroidal Thickness in Patients with Mild Cognitive Impairment and Alzheimer’s Type Dementia”
**Authors:** Mehmet Bulut; Aylin Yaman; Muhammet Kazim Erol; Fatma Kurtuluş; Devrim Toslak; Berna Doğan; Deniz Turgut Çoban; Ebru Kaya
**Journal:** Journal of Ophthalmology
(2016)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2016/2898704
---
## Body
---
*Source: 2898704-2016-11-29.xml* | 2898704-2016-11-29_2898704-2016-11-29.md | 504 | Response to: Comment on “Choroidal Thickness in Patients with Mild Cognitive Impairment and Alzheimer’s Type Dementia” | Mehmet Bulut; Aylin Yaman; Muhammet Kazim Erol; Fatma Kurtuluş; Devrim Toslak; Berna Doğan; Deniz Turgut Çoban; Ebru Kaya | Journal of Ophthalmology
(2016) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2016/2898704 | 2898704-2016-11-29.xml | ---
## Body
---
*Source: 2898704-2016-11-29.xml* | 2016 |
# MSN@IL-4 Sustainingly Mediates Macrophagocyte M2 Polarization and Relieves Osteoblast Damage via NF-κB Pathway-Associated Apoptosis
**Authors:** Cheng Shi; Fei Yuan; Zhilong Li; Zhenhua Zheng; Changliang Yuan; Ziyang Huang; Jianping Liu; Xuping Lin; Taoyi Cai; Guofeng Huang; Zhenqi Ding
**Journal:** BioMed Research International
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2898729
---
## Abstract
Background. The microenvironment of bone defects displayed that M2 polarization of macrophagocyte could promote the osteoblast growth and benefit the wound healing. Bone scaffold transplantation is considered to be one of the most promising methods for repairing bone defects. The present research was aimed at constructing a kind of novel bone scaffold nanomaterial of MSN@IL-4 for treating bone defects responding to the wound microenvironment of bone defects and elucidating the mechanics of MSN@IL-4 treating bone defect via controlling release of IL-4, inducing M2 polarization and active factor release of macrophagocyte, and eventually relieving osteoblast injury. Methods. MSN@IL-4 was firstly fabricated and its release of IL-4 was assessed in vitro. Following, the effects of MSN@IL-4 nanocomplex on the release of active factors of macrophage were examined using Elisa assay and promoting M2 polarization of the macrophage by immunofluorescence staining. And then, the effects of active factors from macrophage supernatant induced by MSN@IL-4 on osteoblast growth were examined by CCK-8, flow cytometry, and western blot assay. Results. The release curve of IL-4 in vitro displayed that there was more than 80% release ratio for 30th day with a sustained manner in pH 5.5. Elisa assay data showed that MSN@IL-4 nanocomplex could constantly promote the release of proproliferative cytokine IL-10, SDF-1α, and BMP-2 in macrophagocyte compared to only IL-4 treatment, and immunofluorescent image showed that MSN@IL-4 could promote M2 polarization of macrophagocytes via inducing CD206 expression and suppressing CD86 expression. Osteoblast injury data showed that the supernatant from macrophagocyte treated by MSN@IL-4 could promote the osteoblast proliferation by MTT assay. Flow cytometry data showed that the supernatant from macrophagocyte treated by MSN@IL-4 could suppress the osteoblast apoptosis from 22.1% to 14.6%, and apoptosis-related protein expression data showed that the supernatant from macrophagocyte treated by MSN@IL-4 could suppress the expression of Bax, cleaved caspase 3, and cleaved caspase 8. Furthermore, the immunofluorescent image showed that the supernatant from macrophagocyte treated by MSN@IL-4 could inhibit nucleus location of p65, and western blot data showed that the supernatant from macrophagocyte treated by MSN@IL-4 could suppress the phosphorylation of IKK and induce the expression of IκB. Conclusion. MSN@IL-4 could control the sustaining release of IL-4, and it exerts the protective effect on osteoblast injury via inducing M2 polarization and proproliferative cytokine of macrophagocyte and following inhibiting the apoptosis and NF-κB pathway-associated inflammation of osteoblast.
---
## Body
## 1. Introduction
Bone defect is a kind of bone deficiency caused by trauma or surgery, which often causes bone nonunion, delayed healing or nonunion, and even local dysfunction [1, 2]. Tissue engineering bone transplantation, mainly composed of bone scaffold materials, seed cells, and cytokines, is considered to be one of the most promising methods for repairing bone defects [3–6]. Although great progress has been made in the research of bone scaffold materials in the past 30 years, its clinical application has not made a breakthrough. The key reason is that the vascularization and osteogenic replacement of tissue-engineered bone scaffolds are slow after transplantation. Some researchers have improved the acceleration of bone regeneration by subcutaneous prevascularization of stents and achieved good results, but this is not feasible in clinical practice [6]. Our previous researches have constructed a series of deproteinized scaffolds which have played a role in the treatment of bone defects to some extent. However, there are still problems such as slow bone growth and poor sustainability. If the microenvironment on the surface of this bone scaffold can be adjusted to make it composite with other bioactive materials to reasonably promote osteogenesis, it will be more ideal and easier to be used in clinic. Therefore, we propose that modifying surface properties of bone scaffolds with bioactive materials may be a potential strategy to improve the healing efficiency of bone defects.Bone immune response is a common inflammatory process response to bone defect, which runs through the whole process of bone healing and osteoblast growth [7–9]. Macrophages are an important immune regulatory cell of bone immune inflammatory response playing an essential role in phagocytosis of necrotic tissue, detection of bacterial products, and antigen presentation. Macrophages widely exist in periosteum and bone, affecting the maintenance of normal bone morphology and the process of fracture repair. It also exists and acts on multiple stages of fracture repair, producing prosynthetic growth factors at the fracture site and promoting more stable callus formation [10–13]. Macrophages possess many subtypes, and different subtypes can carry out different functions via the polarization transformation according to the changes of the cell environment. In acute inflammatory reaction, macrophages were stimulated by interleukin-2 (IL-2) or liposomes to polarize into M1 type (cd11c+ and ccr7+), which enhanced Th1 helper cells and promoted inflammatory reaction; when stimulated by IL-4, macrophages can polarize into M2 type (cd163+ and cd206+), enhance Th2 helper cell function, reduce inflammation, and promote tissue repair [14, 15].It has been reported that macrophages cultured on the modified bone scaffold can induce M2 polarization, produce many active bone factors, induce osteoblast proliferation, and eventually promote fracture healing [16]. Although macrophages indirectly participate in the process of bone regeneration, it promotes bone formation by inducing BMP-2 secretion. Many inflammatory cytokines such as IL-4 cannot also directly affect bone metabolism but promote osteoblast growth by inducing macrophage polarization. IL-4-modified tissue engineering bone scaffolds can effectively promote the polarization of macrophages in bone defects and the growth of osteoblasts to achieve the therapeutic effect of bone defects. However, IL-4-modified tissue engineering bone scaffold material still has the problem of one-time release of IL-4, which is difficult to continue to treat bone defects. Therefore, it is necessary to develop tissue engineering bone scaffolds that can control the slow and sustained release of IL-4.Recently, drug-loaded nanoparticles with controlled release and regulation functions have been widely concerned in the research and development of targeted drugs for various diseases because of their good size and biocompatibility, which can effectively load drug molecules, change their biological distribution and drug metabolism, and control drug release. Among them, the mesoporous silicon nanocarrier (MSN) is a hollow spherical structure with thorns and holes on the surface, which has the characteristics of high specific surface area, good biocompatibility, easy modification, and so on. It is an ideal carrier material for disease treatment drugs. After modification, MSN nanoparticles that respond to low pH, redox reaction, photo enzyme, and other stimuli to control the release of drugs have been reported for many times. MSN nanomaterials can effectively adhere to the surface of deproteinized cancellous bone scaffolds because of their good spines on the surface. Meanwhile, a large number of hydroxyl groups exist on the surface of MSN nanomaterials and can be coupled with IL-4 to form MSN@IL-4 nanocomposites. In a slightly acidic environment, the nanocomposites can slowly release IL-4, so as to achieve the function of sustainable release of IL-4. Therefore, bone scaffold@MSN@IL-4 nanomaterials will be a potentially effective treatment for bone defects.The present research was aimed at constructing a nanomaterial of bone scaffold@MSN@IL-4 and elucidating its mechanism of promoting fracture healing via the sustaining release of IL-4 to induce M2 polarization of the macrophage to produce many active bone factors causing osteoblast growth. Firstly, the MSN@IL-4 nanocomplex was fabricated and its release of IL-4 was assessed in vitro. Following, the effects of MSN@IL-4 nanocomplex on the release of active factors of macrophage were examined using Elisa assay and promoting M2 polarization of the macrophage by immunofluorescence staining. And then, the effects of active factors from macrophage supernatant induced by MSN@IL-4 on osteoblast growth were examined by CCK-8, flow cytometry, and western blot assay. Bone defect is a kind of bone deficiency caused by trauma or surgery, which often causes bone nonunion, delayed healing or nonunion, and even local dysfunction. Tissue engineering bone transplantation, mainly composed of bone scaffold materials, seed cells, and cytokines, is considered to be one of the most promising methods for repairing bone defects. Although great progress has been made in the research of bone scaffold materials in the past 30 years, its clinical application has not made a breakthrough. The key reason is that the vascularization and osteogenic replacement of tissue-engineered bone scaffolds are slow after transplantation. Some researchers have improved the acceleration of bone regeneration by subcutaneous prevascularization of stents and achieved good results, but this is not feasible in clinical practice. Our previous researches have constructed a series of deproteinized scaffolds which have played a role in the treatment of bone defects to some extent. However, there are still problems such as slow bone growth and poor sustainability. If the microenvironment on the surface of this bone scaffold can be adjusted to make it composite with other bioactive materials to reasonably promote osteogenesis, it will be more ideal and easier to be used in clinic. Therefore, we propose that modifying surface properties of bone scaffolds with bioactive materials may be a potential strategy to improve the healing efficiency of bone defects.
## 2. Methods and Materials
### 2.1. Synthesis of MSN
5 g cetyltrimethylammonium bromide (CTAB, Sigma, USA) was weighted and added into 100 mL of ultrapure water and stirred vigorously for 30 minutes at 90°C until CTAB was completely dissolved. 10 g triethanolamine (TTA, sigma, USA) was weighted and added into 30 mL of ultrapure water to obtain 0.3 mg/mL TTA solution. After that, 5 mL of TTA solution and an additional mixture solution of 30 mL cyclohexane (Sinopharm, China) and 8 mL ethyl orthosilicate (TEOS, Sinopharm, China) were added into the dissolved CTAB solution. The mixed solution reacted under the condition of the continuous stirring at 300 rpm and 90°C for 24 hours. After the reaction, the product of MSN was centrifuged at 1200 rpm for 20 minutes and washed with ethanol and sodium chloride solution for removing the excess raw materials of CTAB. Finally, the prepared MSN was incubated with IL-4 solution, and the product was characterized by scanning electron microscope (SEM).
### 2.2. Elisa Assay for Detecting the Controlled Release of IL-4 from MSN@lL-4
The 100 mg MSN@IL-4 were, respectively, added into the indicated pH (pH 5.5, pH 7.2, and pH 8.8) of phosphate buffer. The buffer was stirred twice per day for 30 days, and the solution was collected at 10 time points of 3rd, 6th, 9th, 12th, 15th, 18th, 21st, 24th, 27th, and 30th day. After that, the collected buffer and the standard substrate were added into the coated wells from Elisa assay kit (R&D, USA) according to the instructions, and the coated plate was shocked and detected for OD value using microplate reader (Thermo, USA). The standard curve of IL-4 was drawn. The contents of IL-4 in buffer were calculated according to the standard curve, and the cumulative release curve of IL-4 was drawn.
### 2.3. Elisa Assay for Detecting the Secretion of Cytokines from Macrophagocyte
The macrophage Raw 264.7 cells (ATCC, USA) were seeded into 12-well plate and cultured for 12 hours. And then, the seeded cells were treated with MSN@IL-4 or MSN for the specific time, and the cell supernatant was collected. After that, the collected supernatant and the standard substrate were added into the coated wells from Elisa assay kit (R&D, USA) according to the instructions, and the coated plate was shocked and detected for OD value using microplate reader (Thermo, USA). The standard curve of IL-10, SDF-1α, and BMP-2 was drawn, and their contents in cellular supernatant were calculated.
### 2.4. Immunofluorescent Assay for Detecting the Type of Macrophagocytes
The macrophage Raw 264.7 cells (ATCC, USA) were seeded to the slices in a 24-well plate and cultured for 12 hours. And then, the seeded cells were treated with MSN@IL-4 or MSN for the specific time. After treating, the slices were fixed with 4% formaldehyde (Sinopharm, China) at room temperature for 30 minutes, perforated with 1% triton X-100 solution (Solarbio, China) for 1 hour, blocked with 5% BSA (Aladdin, China) for 1 hour, incubated with primary antibody of CD206 (Abcam, USA) and CD86 (Abcam, USA) for 2 hours, following incubated with the rabbit secondary antibody (Lulong, China) at room temperature, and stained with DAPI (Solarbio, China) and sealed. At last, the slices were imaged by confocal microscope (Carl Zeiss AG, Germany).
### 2.5. MTT Assay for Detecting the Proliferation of Osteoblast
The osteoblast cells were prepared from shin bone of mice and cultured in DMEM medium containing 10% fetal calf serum (FBS, Gibco, USA) for 3 days. And then, the cells were seeded into 96-well plate, cultured in incubator (ThermoFisher, USA) with 5% CO2 for 12 hours, and treated with H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4. After treating, the cells in wells were added with 20 μL MTT solution (Bio-Tek, China) with the final concentration of 0.5 mg/mL and incubated at 37°C for 2 hours. The precipitate of formazan in the incubated wells of 96-well plates was diluted with 100 μL DMSO (Sigma, USA) per well, and the absorbance at 490 nm was tested by microplate reader (ThermoFisher, USA). The proliferation ratio was calculated as
(1)Proliferationrate=ODsample−ODblankODcontrol−ODblank×100%.
### 2.6. Flow Cytometry of Dual Staining of FITC-Annexin V/PI for Detecting the Cellular Apoptosis in Osteoblast
The prepared osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were digested into single cells with 0.25% trypsin (Biosharp, China) and, following stopping the digestion with DMEM medium with FBS, washed and resuspended with PBS. The resuspended cells were stained via adding 5 μL Annexin V-FITC and PI to incubate at 25°C for 15 minutes according to the instruction from manufacturer (RD, Germany). Finally, the stained osteoblast was diluted with PBS to 1.0 mL and tested using the flow cytometry (BD, USA).
### 2.7. Western Blotting for Detecting the Apoptosis-Related Protein Expression in Osteoblast
The osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were collected and lysed with RIPA buffer, and the total protein was harvested and denatured. The denatured proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore, USA). The PVDF membrane loading with the protein was blocked with 5% skim milk and incubated with the primary antibodies against Bcl-2 (CST, USA), Bax (CST, USA), caspase 3 (CST, USA), caspase 8 (Abcam, UK), and β-actin (CST, USA) at 4°C overnight, following the corresponding secondary antibody (CST, USA). Finally, the band from PVDF membrane was detected by enhanced chemiluminescence solution (ECL, Sigma, USA) and photographic film (Keda, USA).
### 2.8. Immunofluorescent Assay for Detecting the NF-κB Pathway-Related p65 Nuclear Location in Osteoblast
The prepared osteoblast cells were seeded to the slices in a 24-well plate and cultured for 12 hours. And then, the seeded cells were treated with H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 for the specific time. After treating, the slices were fixed with 4% formaldehyde (Sinopharm, China) at room temperature for 30 minutes, perforated with 1% triton X-100 solution (Solarbio, China) for 1 hour, blocked with 5% BSA (Aladdin, China) for 1 hour, incubated with primary antibody of CD206 (Abcam, USA) and CD86 (Abcam, USA) for 2 hours, following incubated with the rabbit secondary antibody (CST, USA) at room temperature, and stained with DAPI (Solarbio, China) and sealed. Finally, the slices were imaged by confocal microscope (Carl Zeiss AG, Germany).
### 2.9. Western Blotting for Detecting the NF-κB Pathway-Related Protein Expression in Osteoblast
The osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were collected and lysed with RIPA buffer, and the total protein was harvested and denatured. The denatured proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore, USA). The PVDF membrane loading with the protein was blocked with 5% skim milk and incubated with the primary antibodies against p-IKK (CST, USA), IKK (CST, USA), IκB (CST, USA), and β-actin (CST, USA) at 4°C overnight, following the corresponding secondary antibody (CST, USA). Finally, the band from PVDF membrane was detected by enhanced chemiluminescence solution (ECL, Sigma, USA) and photographic film (Keda, USA).
### 2.10. Statistical Analysis
By using the software of SPSS and GraphPad, all of the experimental data were presented as themean±standarddeviation(S.D.). The statistical differences among the groups were compared using one-way ANOVA by SPSS of version 19.0 (SPSS, USA). p<0.05 was considered to be statistically significant. The asterisk (∗) represented the comparison with the normal group, and the pound sign (#) was for the comparison with model group.
## 2.1. Synthesis of MSN
5 g cetyltrimethylammonium bromide (CTAB, Sigma, USA) was weighted and added into 100 mL of ultrapure water and stirred vigorously for 30 minutes at 90°C until CTAB was completely dissolved. 10 g triethanolamine (TTA, sigma, USA) was weighted and added into 30 mL of ultrapure water to obtain 0.3 mg/mL TTA solution. After that, 5 mL of TTA solution and an additional mixture solution of 30 mL cyclohexane (Sinopharm, China) and 8 mL ethyl orthosilicate (TEOS, Sinopharm, China) were added into the dissolved CTAB solution. The mixed solution reacted under the condition of the continuous stirring at 300 rpm and 90°C for 24 hours. After the reaction, the product of MSN was centrifuged at 1200 rpm for 20 minutes and washed with ethanol and sodium chloride solution for removing the excess raw materials of CTAB. Finally, the prepared MSN was incubated with IL-4 solution, and the product was characterized by scanning electron microscope (SEM).
## 2.2. Elisa Assay for Detecting the Controlled Release of IL-4 from MSN@lL-4
The 100 mg MSN@IL-4 were, respectively, added into the indicated pH (pH 5.5, pH 7.2, and pH 8.8) of phosphate buffer. The buffer was stirred twice per day for 30 days, and the solution was collected at 10 time points of 3rd, 6th, 9th, 12th, 15th, 18th, 21st, 24th, 27th, and 30th day. After that, the collected buffer and the standard substrate were added into the coated wells from Elisa assay kit (R&D, USA) according to the instructions, and the coated plate was shocked and detected for OD value using microplate reader (Thermo, USA). The standard curve of IL-4 was drawn. The contents of IL-4 in buffer were calculated according to the standard curve, and the cumulative release curve of IL-4 was drawn.
## 2.3. Elisa Assay for Detecting the Secretion of Cytokines from Macrophagocyte
The macrophage Raw 264.7 cells (ATCC, USA) were seeded into 12-well plate and cultured for 12 hours. And then, the seeded cells were treated with MSN@IL-4 or MSN for the specific time, and the cell supernatant was collected. After that, the collected supernatant and the standard substrate were added into the coated wells from Elisa assay kit (R&D, USA) according to the instructions, and the coated plate was shocked and detected for OD value using microplate reader (Thermo, USA). The standard curve of IL-10, SDF-1α, and BMP-2 was drawn, and their contents in cellular supernatant were calculated.
## 2.4. Immunofluorescent Assay for Detecting the Type of Macrophagocytes
The macrophage Raw 264.7 cells (ATCC, USA) were seeded to the slices in a 24-well plate and cultured for 12 hours. And then, the seeded cells were treated with MSN@IL-4 or MSN for the specific time. After treating, the slices were fixed with 4% formaldehyde (Sinopharm, China) at room temperature for 30 minutes, perforated with 1% triton X-100 solution (Solarbio, China) for 1 hour, blocked with 5% BSA (Aladdin, China) for 1 hour, incubated with primary antibody of CD206 (Abcam, USA) and CD86 (Abcam, USA) for 2 hours, following incubated with the rabbit secondary antibody (Lulong, China) at room temperature, and stained with DAPI (Solarbio, China) and sealed. At last, the slices were imaged by confocal microscope (Carl Zeiss AG, Germany).
## 2.5. MTT Assay for Detecting the Proliferation of Osteoblast
The osteoblast cells were prepared from shin bone of mice and cultured in DMEM medium containing 10% fetal calf serum (FBS, Gibco, USA) for 3 days. And then, the cells were seeded into 96-well plate, cultured in incubator (ThermoFisher, USA) with 5% CO2 for 12 hours, and treated with H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4. After treating, the cells in wells were added with 20 μL MTT solution (Bio-Tek, China) with the final concentration of 0.5 mg/mL and incubated at 37°C for 2 hours. The precipitate of formazan in the incubated wells of 96-well plates was diluted with 100 μL DMSO (Sigma, USA) per well, and the absorbance at 490 nm was tested by microplate reader (ThermoFisher, USA). The proliferation ratio was calculated as
(1)Proliferationrate=ODsample−ODblankODcontrol−ODblank×100%.
## 2.6. Flow Cytometry of Dual Staining of FITC-Annexin V/PI for Detecting the Cellular Apoptosis in Osteoblast
The prepared osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were digested into single cells with 0.25% trypsin (Biosharp, China) and, following stopping the digestion with DMEM medium with FBS, washed and resuspended with PBS. The resuspended cells were stained via adding 5 μL Annexin V-FITC and PI to incubate at 25°C for 15 minutes according to the instruction from manufacturer (RD, Germany). Finally, the stained osteoblast was diluted with PBS to 1.0 mL and tested using the flow cytometry (BD, USA).
## 2.7. Western Blotting for Detecting the Apoptosis-Related Protein Expression in Osteoblast
The osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were collected and lysed with RIPA buffer, and the total protein was harvested and denatured. The denatured proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore, USA). The PVDF membrane loading with the protein was blocked with 5% skim milk and incubated with the primary antibodies against Bcl-2 (CST, USA), Bax (CST, USA), caspase 3 (CST, USA), caspase 8 (Abcam, UK), and β-actin (CST, USA) at 4°C overnight, following the corresponding secondary antibody (CST, USA). Finally, the band from PVDF membrane was detected by enhanced chemiluminescence solution (ECL, Sigma, USA) and photographic film (Keda, USA).
## 2.8. Immunofluorescent Assay for Detecting the NF-κB Pathway-Related p65 Nuclear Location in Osteoblast
The prepared osteoblast cells were seeded to the slices in a 24-well plate and cultured for 12 hours. And then, the seeded cells were treated with H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 for the specific time. After treating, the slices were fixed with 4% formaldehyde (Sinopharm, China) at room temperature for 30 minutes, perforated with 1% triton X-100 solution (Solarbio, China) for 1 hour, blocked with 5% BSA (Aladdin, China) for 1 hour, incubated with primary antibody of CD206 (Abcam, USA) and CD86 (Abcam, USA) for 2 hours, following incubated with the rabbit secondary antibody (CST, USA) at room temperature, and stained with DAPI (Solarbio, China) and sealed. Finally, the slices were imaged by confocal microscope (Carl Zeiss AG, Germany).
## 2.9. Western Blotting for Detecting the NF-κB Pathway-Related Protein Expression in Osteoblast
The osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were collected and lysed with RIPA buffer, and the total protein was harvested and denatured. The denatured proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore, USA). The PVDF membrane loading with the protein was blocked with 5% skim milk and incubated with the primary antibodies against p-IKK (CST, USA), IKK (CST, USA), IκB (CST, USA), and β-actin (CST, USA) at 4°C overnight, following the corresponding secondary antibody (CST, USA). Finally, the band from PVDF membrane was detected by enhanced chemiluminescence solution (ECL, Sigma, USA) and photographic film (Keda, USA).
## 2.10. Statistical Analysis
By using the software of SPSS and GraphPad, all of the experimental data were presented as themean±standarddeviation(S.D.). The statistical differences among the groups were compared using one-way ANOVA by SPSS of version 19.0 (SPSS, USA). p<0.05 was considered to be statistically significant. The asterisk (∗) represented the comparison with the normal group, and the pound sign (#) was for the comparison with model group.
## 3. Results
### 3.1. Characteristics of MSN@IL-4 Scaffold and IL-4 Release Rate In Vitro
In order to obtain the controlled-release IL-4 system, MSN@IL-4 nanomaterial was fabricated via two-phase process, and in vitro IL-4 release response to pH was evaluated via Elisa assay. SEM photograph of MSN@IL-4 nanoparticle in Figure1(a) showed that several black spherical particles adhere to the surface of the grey balls, demonstrating that IL-4 was conjugated to MSN. The release curve of IL-4 in vitro (Figure 1(b)) showed that there are 12% release rate for 3th day and more than 80% for 30th day with a sustained manner in pH 5.5, and the release is adequate during 30 days; however, the release rate is only 51% in pH 7.2 and lower than 20% in pH 8.8 for 30th day; even from 15th day, the release is extremely slow or standstill. These release data demonstrate that MSN@IL-4 nanosystem possesses the sustained and adequate IL-4 release potential response to the acid environment.Figure 1
The scaffold of MSN@IL-4 and IL-4 release from MSN@IL-4 in vitro. (a) SEM image of MSN@IL-4 and (b) cumulative release of IL-4 response to pH.
(a)(b)
### 3.2. MSN@IL-4 Promote the Sustaining Secretion of Cytokines of IL-10, SDF-1α, and BMP-2 in Macrophagocyte
In order to confirm the effect of fabricated MSN@IL-4 nanomaterial on controlling pro-proliferative cytokine release, the secretion difference of IL-10, SDF-1α and BMP-2 in acrophagocyte subjecting to MSN@IL-4 nanocomplex or only IL-4 were detected by Elisa assay. The content curve in Figure 2(a) showed that the cells subjected to MSN@IL-4 nanocomplex treatment with the indicated time displayed a constantly linear increase of IL-10 secretion from 12 hours to 72 hours; however, the content of IL-10 in macrophagocyte subjected to only IL-4 displayed a rising for 24 hours compared to 12 hours and a constant decreasing from 24 hours to 72 hours. The change trends of SDF-1α secretion (Figure 2(b)) and BMP-2 secretion (Figure 2(c)) were similar in macrophagocyte subjected to MSN@IL-4 nanocomplex and only IL-4, which were that MSN@IL-4 promotes the constant and time-dependent increase of cytokines and only IL-4 was unsustainable. These results demonstrated that MSN@IL-4 nanocomplex could constantly promote proproliferative cytokine release in macrophagocyte compared to only IL-4 treatment.Figure 2
The effect of MSN@IL-4 nanomaterials for promoting the sustaining secretion of cytokines of IL-10, SDF-1α, and BMP-2 in macrophagocyte. Elisa assay for detecting the contents of IL-10 (a), SDF-1α (b), and BMP-2 (c) in the cellular supernatant.
(a)(b)(c)
### 3.3. MSN@IL-4 Promotes M2 Polarization in Macrophagocyte
To evaluate the promotive effect of MSN@IL-4 on M2 polarization, the M1/M2 indicator of CD86 and CD206 was detected via immunofluorescent experiments. The fluorescent images in Figure3 showed that macrophagocyte in MSN@IL-4 group displayed a decrease of CD86 expression compared to that in control group (0.01<∗p<0.05); oppositely, CD206 expression displayed an increasing trend in cells subjected to MSN@IL-4 nanomaterial compared to that in the control group (0.001<∗∗p<0.01). Meanwhile, the cells in only MSN group displayed similar expressions of CD86 and CD206 with that in the control group. These results demonstrated that MSN@IL-4 nanocomplex could promote the M2 polarization of macrophagocyte, but only MSN has no the similar effect.Figure 3
The promotive effect of MSN@IL-4 nanomaterials on M2 polarization in macrophagocyte. The representative fluorescent images of the stained CD86 and CD206 were displayed and relative expression were analyzed using GraphPad software.∗p<0.05 and ∗∗p<0.01 vs. control group.
### 3.4. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Protects the Damaged Osteoblast
To confirm the protective effect of M2-polarizationed macrophagocyte on osteoblast, the secretion supernatant from macrophagocyte subjected to MSN@IL-4 was employed to treat the damaged osteoblast, the proliferation was examined via CCK-8 assay and apoptosis was evaluated by flow cytometer. CCK-8 data in Figure4(a) showed that osteoblast subjected to H2O2 displayed a decrease of proliferation rate from 100% to 54.7% relative to cells in normal group (0.001<∗∗p<0.01), and the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse enhancement of proliferation rate from 54.7% to 84.2% compared to that in the model group (0.01<#p<0.05). The scatter diagram of flow cytometer in Figure 4(b) showed that osteoblast subjected to H2O2 displayed an increase of apoptosis rate from 7.5% to 27.3% relative to cells in the normal group (0.001<∗∗p<0.01), and the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse decrease of apoptosis rate from 27.3% to 14.5% compared to that in the model group (0.01<#p<0.05). These results demonstrated that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could protect the osteoblast from H2O2-induced injury.Figure 4
The protective effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial against H2O2-induced osteoblast injury. (a) CCK-8 assay for detecting the cellular proliferation of the normal osteoblast (normal group), H2O2-treated osteoblast (model group), and the treated osteoblast with H2O2 and supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial (MSN@IL-4 group). (b) Flow cytometry analysis with dual staining of PI and FITC-annexin V for testing the cellular apoptosis rate. (c) The statistical analysis for the apoptosis rate using GraphPad software. ∗∗p<0.01 and ∗∗∗p<0.001 vs. normal group; #p<0.05 vs. model group.
(a)(b)(c)
### 3.5. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the Apoptosis-Related Protein Expression in Osteoblast
To further confirm the protective effect of M2-polarizationed macrophagocyte on the apoptosis during osteoblast injury, the apoptosis-associated proteins of bcl-2, bax, caspase 3, and caspase 9 were probed using western blotting. The band images in Figure5 showed that osteoblast subjected to H2O2 displayed the expression increase of bax (∗∗p<0.01), cleaved caspase 3 (∗∗p<0.01), and cleaved caspase 8 (∗∗p<0.01) relative to cells in the normal group. Expectantly, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse regulation of protein expression that bax (##p<0.01), cleaved caspase 3 (#p<0.05), and cleaved caspase 8 (#p<0.05) were inhibited relative to cells in the model group. These results were consist with the apoptosis data from flow cytometry, demonstrating that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could protect the osteoblast from H2O2-induced apoptosis.Figure 5
The regulatory effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on apoptosis-associated proteins of bcl-2, bax, cleaved caspase 3, and cleaved caspase 8.∗∗p<0.01 vs. normal group; #p<0.05 and ##p<0.01 vs. model group.
### 3.6. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the NF-κB Pathway-Related p65 Nuclear Location in Osteoblast
To evaluate the inhibitory effect of M2-polarizationed macrophagocyte on osteoblast inflammation, p65 nucleus location, a classical NF-κB pathway indicator, was probed via immunofluorescent experiments. The fluorescent images in Figure 6 showed the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a inhibitory effect of p65 nucleus location compared that in the model group and have the significant statistical difference of 0.01<∗∗p<0.01; however, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN displayed a weak inhibitory of p65 nucleus location with no statistical difference compared that in the model group. The result demonstrated that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could suppress the osteoblast inflammation via NF-κB p65 nuclear location.Figure 6
The inhibitive effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on the NF-κB pathway. The nucleus location of p65 in H2O2-treated osteoblast (model group) and the treated osteoblast with supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial (MSN@IL-4 group) or only MSN (MSN group). The statistical analysis of p65 nucleus location using GraphPad software. ∗∗p<0.01 vs. model group.
### 3.7. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the NF-κB Pathway-Related Protein Expression in Osteoblast
To further confirm the suppressive effect of M2-polarizationed macrophagocyte on inflammation during osteoblast injury, the NF-κB pathway-associated proteins of p-IKK, IKK, and IκB were probed using western blotting. The band images in Figure 7 showed that osteoblast subjected to H2O2 displayed a evident decrease of IκB expression (∗∗p<0.01) and the phosphorylation increase of IKK (∗∗p<0.01) relative to cells in the normal group. Expectantly, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse regulation of protein expression that IκB expression in osteoblast cells of MSN@IL-4 group was induced (##p<0.01) and the protein phosphorylation of IKK was inhibited (#p<0.05) relative to cells in the model group. These results were consistent with the p65 nuclear location from immunofluorescent, demonstrating that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could suppress NF-κB pathway-associated inflammation in osteoblast.Figure 7
The regulatory effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on NF-κB pathway-associated proteins of p-IKK, IKK, and IκB. ∗p<0.01 vs. normal group; #p<0.05 and ##p<0.01 vs. model group.
## 3.1. Characteristics of MSN@IL-4 Scaffold and IL-4 Release Rate In Vitro
In order to obtain the controlled-release IL-4 system, MSN@IL-4 nanomaterial was fabricated via two-phase process, and in vitro IL-4 release response to pH was evaluated via Elisa assay. SEM photograph of MSN@IL-4 nanoparticle in Figure1(a) showed that several black spherical particles adhere to the surface of the grey balls, demonstrating that IL-4 was conjugated to MSN. The release curve of IL-4 in vitro (Figure 1(b)) showed that there are 12% release rate for 3th day and more than 80% for 30th day with a sustained manner in pH 5.5, and the release is adequate during 30 days; however, the release rate is only 51% in pH 7.2 and lower than 20% in pH 8.8 for 30th day; even from 15th day, the release is extremely slow or standstill. These release data demonstrate that MSN@IL-4 nanosystem possesses the sustained and adequate IL-4 release potential response to the acid environment.Figure 1
The scaffold of MSN@IL-4 and IL-4 release from MSN@IL-4 in vitro. (a) SEM image of MSN@IL-4 and (b) cumulative release of IL-4 response to pH.
(a)(b)
## 3.2. MSN@IL-4 Promote the Sustaining Secretion of Cytokines of IL-10, SDF-1α, and BMP-2 in Macrophagocyte
In order to confirm the effect of fabricated MSN@IL-4 nanomaterial on controlling pro-proliferative cytokine release, the secretion difference of IL-10, SDF-1α and BMP-2 in acrophagocyte subjecting to MSN@IL-4 nanocomplex or only IL-4 were detected by Elisa assay. The content curve in Figure 2(a) showed that the cells subjected to MSN@IL-4 nanocomplex treatment with the indicated time displayed a constantly linear increase of IL-10 secretion from 12 hours to 72 hours; however, the content of IL-10 in macrophagocyte subjected to only IL-4 displayed a rising for 24 hours compared to 12 hours and a constant decreasing from 24 hours to 72 hours. The change trends of SDF-1α secretion (Figure 2(b)) and BMP-2 secretion (Figure 2(c)) were similar in macrophagocyte subjected to MSN@IL-4 nanocomplex and only IL-4, which were that MSN@IL-4 promotes the constant and time-dependent increase of cytokines and only IL-4 was unsustainable. These results demonstrated that MSN@IL-4 nanocomplex could constantly promote proproliferative cytokine release in macrophagocyte compared to only IL-4 treatment.Figure 2
The effect of MSN@IL-4 nanomaterials for promoting the sustaining secretion of cytokines of IL-10, SDF-1α, and BMP-2 in macrophagocyte. Elisa assay for detecting the contents of IL-10 (a), SDF-1α (b), and BMP-2 (c) in the cellular supernatant.
(a)(b)(c)
## 3.3. MSN@IL-4 Promotes M2 Polarization in Macrophagocyte
To evaluate the promotive effect of MSN@IL-4 on M2 polarization, the M1/M2 indicator of CD86 and CD206 was detected via immunofluorescent experiments. The fluorescent images in Figure3 showed that macrophagocyte in MSN@IL-4 group displayed a decrease of CD86 expression compared to that in control group (0.01<∗p<0.05); oppositely, CD206 expression displayed an increasing trend in cells subjected to MSN@IL-4 nanomaterial compared to that in the control group (0.001<∗∗p<0.01). Meanwhile, the cells in only MSN group displayed similar expressions of CD86 and CD206 with that in the control group. These results demonstrated that MSN@IL-4 nanocomplex could promote the M2 polarization of macrophagocyte, but only MSN has no the similar effect.Figure 3
The promotive effect of MSN@IL-4 nanomaterials on M2 polarization in macrophagocyte. The representative fluorescent images of the stained CD86 and CD206 were displayed and relative expression were analyzed using GraphPad software.∗p<0.05 and ∗∗p<0.01 vs. control group.
## 3.4. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Protects the Damaged Osteoblast
To confirm the protective effect of M2-polarizationed macrophagocyte on osteoblast, the secretion supernatant from macrophagocyte subjected to MSN@IL-4 was employed to treat the damaged osteoblast, the proliferation was examined via CCK-8 assay and apoptosis was evaluated by flow cytometer. CCK-8 data in Figure4(a) showed that osteoblast subjected to H2O2 displayed a decrease of proliferation rate from 100% to 54.7% relative to cells in normal group (0.001<∗∗p<0.01), and the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse enhancement of proliferation rate from 54.7% to 84.2% compared to that in the model group (0.01<#p<0.05). The scatter diagram of flow cytometer in Figure 4(b) showed that osteoblast subjected to H2O2 displayed an increase of apoptosis rate from 7.5% to 27.3% relative to cells in the normal group (0.001<∗∗p<0.01), and the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse decrease of apoptosis rate from 27.3% to 14.5% compared to that in the model group (0.01<#p<0.05). These results demonstrated that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could protect the osteoblast from H2O2-induced injury.Figure 4
The protective effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial against H2O2-induced osteoblast injury. (a) CCK-8 assay for detecting the cellular proliferation of the normal osteoblast (normal group), H2O2-treated osteoblast (model group), and the treated osteoblast with H2O2 and supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial (MSN@IL-4 group). (b) Flow cytometry analysis with dual staining of PI and FITC-annexin V for testing the cellular apoptosis rate. (c) The statistical analysis for the apoptosis rate using GraphPad software. ∗∗p<0.01 and ∗∗∗p<0.001 vs. normal group; #p<0.05 vs. model group.
(a)(b)(c)
## 3.5. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the Apoptosis-Related Protein Expression in Osteoblast
To further confirm the protective effect of M2-polarizationed macrophagocyte on the apoptosis during osteoblast injury, the apoptosis-associated proteins of bcl-2, bax, caspase 3, and caspase 9 were probed using western blotting. The band images in Figure5 showed that osteoblast subjected to H2O2 displayed the expression increase of bax (∗∗p<0.01), cleaved caspase 3 (∗∗p<0.01), and cleaved caspase 8 (∗∗p<0.01) relative to cells in the normal group. Expectantly, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse regulation of protein expression that bax (##p<0.01), cleaved caspase 3 (#p<0.05), and cleaved caspase 8 (#p<0.05) were inhibited relative to cells in the model group. These results were consist with the apoptosis data from flow cytometry, demonstrating that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could protect the osteoblast from H2O2-induced apoptosis.Figure 5
The regulatory effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on apoptosis-associated proteins of bcl-2, bax, cleaved caspase 3, and cleaved caspase 8.∗∗p<0.01 vs. normal group; #p<0.05 and ##p<0.01 vs. model group.
## 3.6. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the NF-κB Pathway-Related p65 Nuclear Location in Osteoblast
To evaluate the inhibitory effect of M2-polarizationed macrophagocyte on osteoblast inflammation, p65 nucleus location, a classical NF-κB pathway indicator, was probed via immunofluorescent experiments. The fluorescent images in Figure 6 showed the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a inhibitory effect of p65 nucleus location compared that in the model group and have the significant statistical difference of 0.01<∗∗p<0.01; however, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN displayed a weak inhibitory of p65 nucleus location with no statistical difference compared that in the model group. The result demonstrated that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could suppress the osteoblast inflammation via NF-κB p65 nuclear location.Figure 6
The inhibitive effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on the NF-κB pathway. The nucleus location of p65 in H2O2-treated osteoblast (model group) and the treated osteoblast with supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial (MSN@IL-4 group) or only MSN (MSN group). The statistical analysis of p65 nucleus location using GraphPad software. ∗∗p<0.01 vs. model group.
## 3.7. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the NF-κB Pathway-Related Protein Expression in Osteoblast
To further confirm the suppressive effect of M2-polarizationed macrophagocyte on inflammation during osteoblast injury, the NF-κB pathway-associated proteins of p-IKK, IKK, and IκB were probed using western blotting. The band images in Figure 7 showed that osteoblast subjected to H2O2 displayed a evident decrease of IκB expression (∗∗p<0.01) and the phosphorylation increase of IKK (∗∗p<0.01) relative to cells in the normal group. Expectantly, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse regulation of protein expression that IκB expression in osteoblast cells of MSN@IL-4 group was induced (##p<0.01) and the protein phosphorylation of IKK was inhibited (#p<0.05) relative to cells in the model group. These results were consistent with the p65 nuclear location from immunofluorescent, demonstrating that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could suppress NF-κB pathway-associated inflammation in osteoblast.Figure 7
The regulatory effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on NF-κB pathway-associated proteins of p-IKK, IKK, and IκB. ∗p<0.01 vs. normal group; #p<0.05 and ##p<0.01 vs. model group.
## 4. Discussion
It is commonly recognized that a large number of inflammatory cells infiltrated at the injury site of bone defect, and inflammatory cells under different conditions will have different subtypes exerting diametrically opposite regulatory effects on osteoblasts of wound [17–19]. M2-polarized macrophages can play an importantly role in wound healing by promoting the secretion of proosteocyte growth factors [20, 21]. Therefore, the supplement of inducer of macrophage-M2-polarizaition such as IL-4 into the wound of bone defect would effectively promote wound healing. At present, the main treatment method for bone defects is bone transplantation. We have also reported the therapeutic effect of deproteinized bone scaffolds in the treatment of bone defects. However, the modified bone scaffolds added with macrophage M2 polarization inducers such as IL-4 have rarely been reported in the treatment of bone defects. Meanwhile, how to control the release of IL-4 in the modified bone scaffold to achieve sustained induction of macrophage polarization is also a technical problem. In this project, we constructed a nanomaterial of MSN@IL-4 loaded on a deproteinized bone scaffold, which can continuously and slowly release IL-4 in response to a slightly acidic environment. We found that MSN@IL-4 could promote the sustaining secretion of cytokines of IL-10, SDF-1α, and BMP-2 compared to only IL-4 and induced M2 polarization in macrophagocyte. The supernatant from macrophagocyte treated with MSN@IL-4 was added into the damaged osteoblast by H2O2, the proliferation ratio of the damaged osteoblast increased, the apoptosis ratio decreased, and NF-κB-associated inflammation was inhibited. These results demonstrated that MSN@IL-4 could protect osteoblast against cell injury induced H2O2 via macrophagocyte M2 polarization and sustainingly promoted the release of active osteoblast factor.Apoptosis is considered as a physiologically and pathologically programmed cell death process to clear off the redundant and malfunctional cells for keeping the cellular homeostasis [22]. Mitochondrial exerts the roles of the controlling center for cellular activities, which masters the oxidative phosphorylation and respiratory chain regulating almost all of the cellular physiopathology including apoptosis. During the apoptosis progression, apoptosis stimuli initiate the mitochondrial depolarization, induces/inhibits the expression of apoptosis-associated proteins of bax, bad, and bcl-2 from mitochondrial, triggers the cysteinyl aspartate specific proteinase (caspase) of caspase 3, caspase 8, and caspase 9, and consequently activates the cleavage of poly ADP-ribose polymerase (PARP), cell death, and tissue damage [23]. In the present research, H2O2 initiate the osteoblast apoptosis via regulating bax and bcl-2 expression and evoking caspase activities. Oppositely, the supernatant from macrophagocyte treated by MSN@IL-4 relieved the apoptosis induced by H2O2. These data demonstrated that MSN@IL-4 could relieve osteoblast injury via inducing macrophagocyte release the active cellular factors.The nuclear factorκB pathway (NF-κB pathway) has long been considered as a prototypical proinflammatory signaling pathway and controlled the expression of proinflammatory genes including cytokines, chemokines, and adhesion molecules [24]. NF-κB pathway was initiatively trigged with the phosphorylation of IKK response to inflammation factor, following the phosphorylation and degradation of IκB and then release the p65 protein from the complex of p65/p115/IκB, and induced its translocation from cytoplasm to nucleus for activating the gene expression of inflammatory factor such as TNFα, IL-1β, and IL-6, consequently causing the development of chronic diseases including cancer, diabetes, and osteoarthritis. In the present research, we found that the osteoblast damaged by H2O2 displayed an obvious phosphorylation of IKK, degradation of IκB, and phosphorylation of p65; meanwhile, the cells treated with the supernatant from macrophagocyte treated by MSN@IL-4 had a reverse trend change of the above NF-κB pathway indicators, demonstrating that MSN@IL-4 could protect against H2O2-inducing osteoblast injury via the induction of macrophagocyte release of the active cellular factors inhibiting the NF-κB inflammation pathway in osteoblast (Figure 8).Figure 8
Scheme summarizing MSN@IL-4 relieving osteoblast damage via macrophagocyte M2 polarization.
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*Source: 2898729-2022-10-03.xml* | 2898729-2022-10-03_2898729-2022-10-03.md | 51,361 | MSN@IL-4 Sustainingly Mediates Macrophagocyte M2 Polarization and Relieves Osteoblast Damage via NF-κB Pathway-Associated Apoptosis | Cheng Shi; Fei Yuan; Zhilong Li; Zhenhua Zheng; Changliang Yuan; Ziyang Huang; Jianping Liu; Xuping Lin; Taoyi Cai; Guofeng Huang; Zhenqi Ding | BioMed Research International
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2898729 | 2898729-2022-10-03.xml | ---
## Abstract
Background. The microenvironment of bone defects displayed that M2 polarization of macrophagocyte could promote the osteoblast growth and benefit the wound healing. Bone scaffold transplantation is considered to be one of the most promising methods for repairing bone defects. The present research was aimed at constructing a kind of novel bone scaffold nanomaterial of MSN@IL-4 for treating bone defects responding to the wound microenvironment of bone defects and elucidating the mechanics of MSN@IL-4 treating bone defect via controlling release of IL-4, inducing M2 polarization and active factor release of macrophagocyte, and eventually relieving osteoblast injury. Methods. MSN@IL-4 was firstly fabricated and its release of IL-4 was assessed in vitro. Following, the effects of MSN@IL-4 nanocomplex on the release of active factors of macrophage were examined using Elisa assay and promoting M2 polarization of the macrophage by immunofluorescence staining. And then, the effects of active factors from macrophage supernatant induced by MSN@IL-4 on osteoblast growth were examined by CCK-8, flow cytometry, and western blot assay. Results. The release curve of IL-4 in vitro displayed that there was more than 80% release ratio for 30th day with a sustained manner in pH 5.5. Elisa assay data showed that MSN@IL-4 nanocomplex could constantly promote the release of proproliferative cytokine IL-10, SDF-1α, and BMP-2 in macrophagocyte compared to only IL-4 treatment, and immunofluorescent image showed that MSN@IL-4 could promote M2 polarization of macrophagocytes via inducing CD206 expression and suppressing CD86 expression. Osteoblast injury data showed that the supernatant from macrophagocyte treated by MSN@IL-4 could promote the osteoblast proliferation by MTT assay. Flow cytometry data showed that the supernatant from macrophagocyte treated by MSN@IL-4 could suppress the osteoblast apoptosis from 22.1% to 14.6%, and apoptosis-related protein expression data showed that the supernatant from macrophagocyte treated by MSN@IL-4 could suppress the expression of Bax, cleaved caspase 3, and cleaved caspase 8. Furthermore, the immunofluorescent image showed that the supernatant from macrophagocyte treated by MSN@IL-4 could inhibit nucleus location of p65, and western blot data showed that the supernatant from macrophagocyte treated by MSN@IL-4 could suppress the phosphorylation of IKK and induce the expression of IκB. Conclusion. MSN@IL-4 could control the sustaining release of IL-4, and it exerts the protective effect on osteoblast injury via inducing M2 polarization and proproliferative cytokine of macrophagocyte and following inhibiting the apoptosis and NF-κB pathway-associated inflammation of osteoblast.
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## Body
## 1. Introduction
Bone defect is a kind of bone deficiency caused by trauma or surgery, which often causes bone nonunion, delayed healing or nonunion, and even local dysfunction [1, 2]. Tissue engineering bone transplantation, mainly composed of bone scaffold materials, seed cells, and cytokines, is considered to be one of the most promising methods for repairing bone defects [3–6]. Although great progress has been made in the research of bone scaffold materials in the past 30 years, its clinical application has not made a breakthrough. The key reason is that the vascularization and osteogenic replacement of tissue-engineered bone scaffolds are slow after transplantation. Some researchers have improved the acceleration of bone regeneration by subcutaneous prevascularization of stents and achieved good results, but this is not feasible in clinical practice [6]. Our previous researches have constructed a series of deproteinized scaffolds which have played a role in the treatment of bone defects to some extent. However, there are still problems such as slow bone growth and poor sustainability. If the microenvironment on the surface of this bone scaffold can be adjusted to make it composite with other bioactive materials to reasonably promote osteogenesis, it will be more ideal and easier to be used in clinic. Therefore, we propose that modifying surface properties of bone scaffolds with bioactive materials may be a potential strategy to improve the healing efficiency of bone defects.Bone immune response is a common inflammatory process response to bone defect, which runs through the whole process of bone healing and osteoblast growth [7–9]. Macrophages are an important immune regulatory cell of bone immune inflammatory response playing an essential role in phagocytosis of necrotic tissue, detection of bacterial products, and antigen presentation. Macrophages widely exist in periosteum and bone, affecting the maintenance of normal bone morphology and the process of fracture repair. It also exists and acts on multiple stages of fracture repair, producing prosynthetic growth factors at the fracture site and promoting more stable callus formation [10–13]. Macrophages possess many subtypes, and different subtypes can carry out different functions via the polarization transformation according to the changes of the cell environment. In acute inflammatory reaction, macrophages were stimulated by interleukin-2 (IL-2) or liposomes to polarize into M1 type (cd11c+ and ccr7+), which enhanced Th1 helper cells and promoted inflammatory reaction; when stimulated by IL-4, macrophages can polarize into M2 type (cd163+ and cd206+), enhance Th2 helper cell function, reduce inflammation, and promote tissue repair [14, 15].It has been reported that macrophages cultured on the modified bone scaffold can induce M2 polarization, produce many active bone factors, induce osteoblast proliferation, and eventually promote fracture healing [16]. Although macrophages indirectly participate in the process of bone regeneration, it promotes bone formation by inducing BMP-2 secretion. Many inflammatory cytokines such as IL-4 cannot also directly affect bone metabolism but promote osteoblast growth by inducing macrophage polarization. IL-4-modified tissue engineering bone scaffolds can effectively promote the polarization of macrophages in bone defects and the growth of osteoblasts to achieve the therapeutic effect of bone defects. However, IL-4-modified tissue engineering bone scaffold material still has the problem of one-time release of IL-4, which is difficult to continue to treat bone defects. Therefore, it is necessary to develop tissue engineering bone scaffolds that can control the slow and sustained release of IL-4.Recently, drug-loaded nanoparticles with controlled release and regulation functions have been widely concerned in the research and development of targeted drugs for various diseases because of their good size and biocompatibility, which can effectively load drug molecules, change their biological distribution and drug metabolism, and control drug release. Among them, the mesoporous silicon nanocarrier (MSN) is a hollow spherical structure with thorns and holes on the surface, which has the characteristics of high specific surface area, good biocompatibility, easy modification, and so on. It is an ideal carrier material for disease treatment drugs. After modification, MSN nanoparticles that respond to low pH, redox reaction, photo enzyme, and other stimuli to control the release of drugs have been reported for many times. MSN nanomaterials can effectively adhere to the surface of deproteinized cancellous bone scaffolds because of their good spines on the surface. Meanwhile, a large number of hydroxyl groups exist on the surface of MSN nanomaterials and can be coupled with IL-4 to form MSN@IL-4 nanocomposites. In a slightly acidic environment, the nanocomposites can slowly release IL-4, so as to achieve the function of sustainable release of IL-4. Therefore, bone scaffold@MSN@IL-4 nanomaterials will be a potentially effective treatment for bone defects.The present research was aimed at constructing a nanomaterial of bone scaffold@MSN@IL-4 and elucidating its mechanism of promoting fracture healing via the sustaining release of IL-4 to induce M2 polarization of the macrophage to produce many active bone factors causing osteoblast growth. Firstly, the MSN@IL-4 nanocomplex was fabricated and its release of IL-4 was assessed in vitro. Following, the effects of MSN@IL-4 nanocomplex on the release of active factors of macrophage were examined using Elisa assay and promoting M2 polarization of the macrophage by immunofluorescence staining. And then, the effects of active factors from macrophage supernatant induced by MSN@IL-4 on osteoblast growth were examined by CCK-8, flow cytometry, and western blot assay. Bone defect is a kind of bone deficiency caused by trauma or surgery, which often causes bone nonunion, delayed healing or nonunion, and even local dysfunction. Tissue engineering bone transplantation, mainly composed of bone scaffold materials, seed cells, and cytokines, is considered to be one of the most promising methods for repairing bone defects. Although great progress has been made in the research of bone scaffold materials in the past 30 years, its clinical application has not made a breakthrough. The key reason is that the vascularization and osteogenic replacement of tissue-engineered bone scaffolds are slow after transplantation. Some researchers have improved the acceleration of bone regeneration by subcutaneous prevascularization of stents and achieved good results, but this is not feasible in clinical practice. Our previous researches have constructed a series of deproteinized scaffolds which have played a role in the treatment of bone defects to some extent. However, there are still problems such as slow bone growth and poor sustainability. If the microenvironment on the surface of this bone scaffold can be adjusted to make it composite with other bioactive materials to reasonably promote osteogenesis, it will be more ideal and easier to be used in clinic. Therefore, we propose that modifying surface properties of bone scaffolds with bioactive materials may be a potential strategy to improve the healing efficiency of bone defects.
## 2. Methods and Materials
### 2.1. Synthesis of MSN
5 g cetyltrimethylammonium bromide (CTAB, Sigma, USA) was weighted and added into 100 mL of ultrapure water and stirred vigorously for 30 minutes at 90°C until CTAB was completely dissolved. 10 g triethanolamine (TTA, sigma, USA) was weighted and added into 30 mL of ultrapure water to obtain 0.3 mg/mL TTA solution. After that, 5 mL of TTA solution and an additional mixture solution of 30 mL cyclohexane (Sinopharm, China) and 8 mL ethyl orthosilicate (TEOS, Sinopharm, China) were added into the dissolved CTAB solution. The mixed solution reacted under the condition of the continuous stirring at 300 rpm and 90°C for 24 hours. After the reaction, the product of MSN was centrifuged at 1200 rpm for 20 minutes and washed with ethanol and sodium chloride solution for removing the excess raw materials of CTAB. Finally, the prepared MSN was incubated with IL-4 solution, and the product was characterized by scanning electron microscope (SEM).
### 2.2. Elisa Assay for Detecting the Controlled Release of IL-4 from MSN@lL-4
The 100 mg MSN@IL-4 were, respectively, added into the indicated pH (pH 5.5, pH 7.2, and pH 8.8) of phosphate buffer. The buffer was stirred twice per day for 30 days, and the solution was collected at 10 time points of 3rd, 6th, 9th, 12th, 15th, 18th, 21st, 24th, 27th, and 30th day. After that, the collected buffer and the standard substrate were added into the coated wells from Elisa assay kit (R&D, USA) according to the instructions, and the coated plate was shocked and detected for OD value using microplate reader (Thermo, USA). The standard curve of IL-4 was drawn. The contents of IL-4 in buffer were calculated according to the standard curve, and the cumulative release curve of IL-4 was drawn.
### 2.3. Elisa Assay for Detecting the Secretion of Cytokines from Macrophagocyte
The macrophage Raw 264.7 cells (ATCC, USA) were seeded into 12-well plate and cultured for 12 hours. And then, the seeded cells were treated with MSN@IL-4 or MSN for the specific time, and the cell supernatant was collected. After that, the collected supernatant and the standard substrate were added into the coated wells from Elisa assay kit (R&D, USA) according to the instructions, and the coated plate was shocked and detected for OD value using microplate reader (Thermo, USA). The standard curve of IL-10, SDF-1α, and BMP-2 was drawn, and their contents in cellular supernatant were calculated.
### 2.4. Immunofluorescent Assay for Detecting the Type of Macrophagocytes
The macrophage Raw 264.7 cells (ATCC, USA) were seeded to the slices in a 24-well plate and cultured for 12 hours. And then, the seeded cells were treated with MSN@IL-4 or MSN for the specific time. After treating, the slices were fixed with 4% formaldehyde (Sinopharm, China) at room temperature for 30 minutes, perforated with 1% triton X-100 solution (Solarbio, China) for 1 hour, blocked with 5% BSA (Aladdin, China) for 1 hour, incubated with primary antibody of CD206 (Abcam, USA) and CD86 (Abcam, USA) for 2 hours, following incubated with the rabbit secondary antibody (Lulong, China) at room temperature, and stained with DAPI (Solarbio, China) and sealed. At last, the slices were imaged by confocal microscope (Carl Zeiss AG, Germany).
### 2.5. MTT Assay for Detecting the Proliferation of Osteoblast
The osteoblast cells were prepared from shin bone of mice and cultured in DMEM medium containing 10% fetal calf serum (FBS, Gibco, USA) for 3 days. And then, the cells were seeded into 96-well plate, cultured in incubator (ThermoFisher, USA) with 5% CO2 for 12 hours, and treated with H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4. After treating, the cells in wells were added with 20 μL MTT solution (Bio-Tek, China) with the final concentration of 0.5 mg/mL and incubated at 37°C for 2 hours. The precipitate of formazan in the incubated wells of 96-well plates was diluted with 100 μL DMSO (Sigma, USA) per well, and the absorbance at 490 nm was tested by microplate reader (ThermoFisher, USA). The proliferation ratio was calculated as
(1)Proliferationrate=ODsample−ODblankODcontrol−ODblank×100%.
### 2.6. Flow Cytometry of Dual Staining of FITC-Annexin V/PI for Detecting the Cellular Apoptosis in Osteoblast
The prepared osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were digested into single cells with 0.25% trypsin (Biosharp, China) and, following stopping the digestion with DMEM medium with FBS, washed and resuspended with PBS. The resuspended cells were stained via adding 5 μL Annexin V-FITC and PI to incubate at 25°C for 15 minutes according to the instruction from manufacturer (RD, Germany). Finally, the stained osteoblast was diluted with PBS to 1.0 mL and tested using the flow cytometry (BD, USA).
### 2.7. Western Blotting for Detecting the Apoptosis-Related Protein Expression in Osteoblast
The osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were collected and lysed with RIPA buffer, and the total protein was harvested and denatured. The denatured proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore, USA). The PVDF membrane loading with the protein was blocked with 5% skim milk and incubated with the primary antibodies against Bcl-2 (CST, USA), Bax (CST, USA), caspase 3 (CST, USA), caspase 8 (Abcam, UK), and β-actin (CST, USA) at 4°C overnight, following the corresponding secondary antibody (CST, USA). Finally, the band from PVDF membrane was detected by enhanced chemiluminescence solution (ECL, Sigma, USA) and photographic film (Keda, USA).
### 2.8. Immunofluorescent Assay for Detecting the NF-κB Pathway-Related p65 Nuclear Location in Osteoblast
The prepared osteoblast cells were seeded to the slices in a 24-well plate and cultured for 12 hours. And then, the seeded cells were treated with H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 for the specific time. After treating, the slices were fixed with 4% formaldehyde (Sinopharm, China) at room temperature for 30 minutes, perforated with 1% triton X-100 solution (Solarbio, China) for 1 hour, blocked with 5% BSA (Aladdin, China) for 1 hour, incubated with primary antibody of CD206 (Abcam, USA) and CD86 (Abcam, USA) for 2 hours, following incubated with the rabbit secondary antibody (CST, USA) at room temperature, and stained with DAPI (Solarbio, China) and sealed. Finally, the slices were imaged by confocal microscope (Carl Zeiss AG, Germany).
### 2.9. Western Blotting for Detecting the NF-κB Pathway-Related Protein Expression in Osteoblast
The osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were collected and lysed with RIPA buffer, and the total protein was harvested and denatured. The denatured proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore, USA). The PVDF membrane loading with the protein was blocked with 5% skim milk and incubated with the primary antibodies against p-IKK (CST, USA), IKK (CST, USA), IκB (CST, USA), and β-actin (CST, USA) at 4°C overnight, following the corresponding secondary antibody (CST, USA). Finally, the band from PVDF membrane was detected by enhanced chemiluminescence solution (ECL, Sigma, USA) and photographic film (Keda, USA).
### 2.10. Statistical Analysis
By using the software of SPSS and GraphPad, all of the experimental data were presented as themean±standarddeviation(S.D.). The statistical differences among the groups were compared using one-way ANOVA by SPSS of version 19.0 (SPSS, USA). p<0.05 was considered to be statistically significant. The asterisk (∗) represented the comparison with the normal group, and the pound sign (#) was for the comparison with model group.
## 2.1. Synthesis of MSN
5 g cetyltrimethylammonium bromide (CTAB, Sigma, USA) was weighted and added into 100 mL of ultrapure water and stirred vigorously for 30 minutes at 90°C until CTAB was completely dissolved. 10 g triethanolamine (TTA, sigma, USA) was weighted and added into 30 mL of ultrapure water to obtain 0.3 mg/mL TTA solution. After that, 5 mL of TTA solution and an additional mixture solution of 30 mL cyclohexane (Sinopharm, China) and 8 mL ethyl orthosilicate (TEOS, Sinopharm, China) were added into the dissolved CTAB solution. The mixed solution reacted under the condition of the continuous stirring at 300 rpm and 90°C for 24 hours. After the reaction, the product of MSN was centrifuged at 1200 rpm for 20 minutes and washed with ethanol and sodium chloride solution for removing the excess raw materials of CTAB. Finally, the prepared MSN was incubated with IL-4 solution, and the product was characterized by scanning electron microscope (SEM).
## 2.2. Elisa Assay for Detecting the Controlled Release of IL-4 from MSN@lL-4
The 100 mg MSN@IL-4 were, respectively, added into the indicated pH (pH 5.5, pH 7.2, and pH 8.8) of phosphate buffer. The buffer was stirred twice per day for 30 days, and the solution was collected at 10 time points of 3rd, 6th, 9th, 12th, 15th, 18th, 21st, 24th, 27th, and 30th day. After that, the collected buffer and the standard substrate were added into the coated wells from Elisa assay kit (R&D, USA) according to the instructions, and the coated plate was shocked and detected for OD value using microplate reader (Thermo, USA). The standard curve of IL-4 was drawn. The contents of IL-4 in buffer were calculated according to the standard curve, and the cumulative release curve of IL-4 was drawn.
## 2.3. Elisa Assay for Detecting the Secretion of Cytokines from Macrophagocyte
The macrophage Raw 264.7 cells (ATCC, USA) were seeded into 12-well plate and cultured for 12 hours. And then, the seeded cells were treated with MSN@IL-4 or MSN for the specific time, and the cell supernatant was collected. After that, the collected supernatant and the standard substrate were added into the coated wells from Elisa assay kit (R&D, USA) according to the instructions, and the coated plate was shocked and detected for OD value using microplate reader (Thermo, USA). The standard curve of IL-10, SDF-1α, and BMP-2 was drawn, and their contents in cellular supernatant were calculated.
## 2.4. Immunofluorescent Assay for Detecting the Type of Macrophagocytes
The macrophage Raw 264.7 cells (ATCC, USA) were seeded to the slices in a 24-well plate and cultured for 12 hours. And then, the seeded cells were treated with MSN@IL-4 or MSN for the specific time. After treating, the slices were fixed with 4% formaldehyde (Sinopharm, China) at room temperature for 30 minutes, perforated with 1% triton X-100 solution (Solarbio, China) for 1 hour, blocked with 5% BSA (Aladdin, China) for 1 hour, incubated with primary antibody of CD206 (Abcam, USA) and CD86 (Abcam, USA) for 2 hours, following incubated with the rabbit secondary antibody (Lulong, China) at room temperature, and stained with DAPI (Solarbio, China) and sealed. At last, the slices were imaged by confocal microscope (Carl Zeiss AG, Germany).
## 2.5. MTT Assay for Detecting the Proliferation of Osteoblast
The osteoblast cells were prepared from shin bone of mice and cultured in DMEM medium containing 10% fetal calf serum (FBS, Gibco, USA) for 3 days. And then, the cells were seeded into 96-well plate, cultured in incubator (ThermoFisher, USA) with 5% CO2 for 12 hours, and treated with H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4. After treating, the cells in wells were added with 20 μL MTT solution (Bio-Tek, China) with the final concentration of 0.5 mg/mL and incubated at 37°C for 2 hours. The precipitate of formazan in the incubated wells of 96-well plates was diluted with 100 μL DMSO (Sigma, USA) per well, and the absorbance at 490 nm was tested by microplate reader (ThermoFisher, USA). The proliferation ratio was calculated as
(1)Proliferationrate=ODsample−ODblankODcontrol−ODblank×100%.
## 2.6. Flow Cytometry of Dual Staining of FITC-Annexin V/PI for Detecting the Cellular Apoptosis in Osteoblast
The prepared osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were digested into single cells with 0.25% trypsin (Biosharp, China) and, following stopping the digestion with DMEM medium with FBS, washed and resuspended with PBS. The resuspended cells were stained via adding 5 μL Annexin V-FITC and PI to incubate at 25°C for 15 minutes according to the instruction from manufacturer (RD, Germany). Finally, the stained osteoblast was diluted with PBS to 1.0 mL and tested using the flow cytometry (BD, USA).
## 2.7. Western Blotting for Detecting the Apoptosis-Related Protein Expression in Osteoblast
The osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were collected and lysed with RIPA buffer, and the total protein was harvested and denatured. The denatured proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore, USA). The PVDF membrane loading with the protein was blocked with 5% skim milk and incubated with the primary antibodies against Bcl-2 (CST, USA), Bax (CST, USA), caspase 3 (CST, USA), caspase 8 (Abcam, UK), and β-actin (CST, USA) at 4°C overnight, following the corresponding secondary antibody (CST, USA). Finally, the band from PVDF membrane was detected by enhanced chemiluminescence solution (ECL, Sigma, USA) and photographic film (Keda, USA).
## 2.8. Immunofluorescent Assay for Detecting the NF-κB Pathway-Related p65 Nuclear Location in Osteoblast
The prepared osteoblast cells were seeded to the slices in a 24-well plate and cultured for 12 hours. And then, the seeded cells were treated with H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 for the specific time. After treating, the slices were fixed with 4% formaldehyde (Sinopharm, China) at room temperature for 30 minutes, perforated with 1% triton X-100 solution (Solarbio, China) for 1 hour, blocked with 5% BSA (Aladdin, China) for 1 hour, incubated with primary antibody of CD206 (Abcam, USA) and CD86 (Abcam, USA) for 2 hours, following incubated with the rabbit secondary antibody (CST, USA) at room temperature, and stained with DAPI (Solarbio, China) and sealed. Finally, the slices were imaged by confocal microscope (Carl Zeiss AG, Germany).
## 2.9. Western Blotting for Detecting the NF-κB Pathway-Related Protein Expression in Osteoblast
The osteoblast cells treated by H2O2 and the secretion supernatant from macrophagocyte subjected to MSN@IL-4 were collected and lysed with RIPA buffer, and the total protein was harvested and denatured. The denatured proteins were separated by SDS-PAGE and transferred to PVDF membrane (Millipore, USA). The PVDF membrane loading with the protein was blocked with 5% skim milk and incubated with the primary antibodies against p-IKK (CST, USA), IKK (CST, USA), IκB (CST, USA), and β-actin (CST, USA) at 4°C overnight, following the corresponding secondary antibody (CST, USA). Finally, the band from PVDF membrane was detected by enhanced chemiluminescence solution (ECL, Sigma, USA) and photographic film (Keda, USA).
## 2.10. Statistical Analysis
By using the software of SPSS and GraphPad, all of the experimental data were presented as themean±standarddeviation(S.D.). The statistical differences among the groups were compared using one-way ANOVA by SPSS of version 19.0 (SPSS, USA). p<0.05 was considered to be statistically significant. The asterisk (∗) represented the comparison with the normal group, and the pound sign (#) was for the comparison with model group.
## 3. Results
### 3.1. Characteristics of MSN@IL-4 Scaffold and IL-4 Release Rate In Vitro
In order to obtain the controlled-release IL-4 system, MSN@IL-4 nanomaterial was fabricated via two-phase process, and in vitro IL-4 release response to pH was evaluated via Elisa assay. SEM photograph of MSN@IL-4 nanoparticle in Figure1(a) showed that several black spherical particles adhere to the surface of the grey balls, demonstrating that IL-4 was conjugated to MSN. The release curve of IL-4 in vitro (Figure 1(b)) showed that there are 12% release rate for 3th day and more than 80% for 30th day with a sustained manner in pH 5.5, and the release is adequate during 30 days; however, the release rate is only 51% in pH 7.2 and lower than 20% in pH 8.8 for 30th day; even from 15th day, the release is extremely slow or standstill. These release data demonstrate that MSN@IL-4 nanosystem possesses the sustained and adequate IL-4 release potential response to the acid environment.Figure 1
The scaffold of MSN@IL-4 and IL-4 release from MSN@IL-4 in vitro. (a) SEM image of MSN@IL-4 and (b) cumulative release of IL-4 response to pH.
(a)(b)
### 3.2. MSN@IL-4 Promote the Sustaining Secretion of Cytokines of IL-10, SDF-1α, and BMP-2 in Macrophagocyte
In order to confirm the effect of fabricated MSN@IL-4 nanomaterial on controlling pro-proliferative cytokine release, the secretion difference of IL-10, SDF-1α and BMP-2 in acrophagocyte subjecting to MSN@IL-4 nanocomplex or only IL-4 were detected by Elisa assay. The content curve in Figure 2(a) showed that the cells subjected to MSN@IL-4 nanocomplex treatment with the indicated time displayed a constantly linear increase of IL-10 secretion from 12 hours to 72 hours; however, the content of IL-10 in macrophagocyte subjected to only IL-4 displayed a rising for 24 hours compared to 12 hours and a constant decreasing from 24 hours to 72 hours. The change trends of SDF-1α secretion (Figure 2(b)) and BMP-2 secretion (Figure 2(c)) were similar in macrophagocyte subjected to MSN@IL-4 nanocomplex and only IL-4, which were that MSN@IL-4 promotes the constant and time-dependent increase of cytokines and only IL-4 was unsustainable. These results demonstrated that MSN@IL-4 nanocomplex could constantly promote proproliferative cytokine release in macrophagocyte compared to only IL-4 treatment.Figure 2
The effect of MSN@IL-4 nanomaterials for promoting the sustaining secretion of cytokines of IL-10, SDF-1α, and BMP-2 in macrophagocyte. Elisa assay for detecting the contents of IL-10 (a), SDF-1α (b), and BMP-2 (c) in the cellular supernatant.
(a)(b)(c)
### 3.3. MSN@IL-4 Promotes M2 Polarization in Macrophagocyte
To evaluate the promotive effect of MSN@IL-4 on M2 polarization, the M1/M2 indicator of CD86 and CD206 was detected via immunofluorescent experiments. The fluorescent images in Figure3 showed that macrophagocyte in MSN@IL-4 group displayed a decrease of CD86 expression compared to that in control group (0.01<∗p<0.05); oppositely, CD206 expression displayed an increasing trend in cells subjected to MSN@IL-4 nanomaterial compared to that in the control group (0.001<∗∗p<0.01). Meanwhile, the cells in only MSN group displayed similar expressions of CD86 and CD206 with that in the control group. These results demonstrated that MSN@IL-4 nanocomplex could promote the M2 polarization of macrophagocyte, but only MSN has no the similar effect.Figure 3
The promotive effect of MSN@IL-4 nanomaterials on M2 polarization in macrophagocyte. The representative fluorescent images of the stained CD86 and CD206 were displayed and relative expression were analyzed using GraphPad software.∗p<0.05 and ∗∗p<0.01 vs. control group.
### 3.4. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Protects the Damaged Osteoblast
To confirm the protective effect of M2-polarizationed macrophagocyte on osteoblast, the secretion supernatant from macrophagocyte subjected to MSN@IL-4 was employed to treat the damaged osteoblast, the proliferation was examined via CCK-8 assay and apoptosis was evaluated by flow cytometer. CCK-8 data in Figure4(a) showed that osteoblast subjected to H2O2 displayed a decrease of proliferation rate from 100% to 54.7% relative to cells in normal group (0.001<∗∗p<0.01), and the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse enhancement of proliferation rate from 54.7% to 84.2% compared to that in the model group (0.01<#p<0.05). The scatter diagram of flow cytometer in Figure 4(b) showed that osteoblast subjected to H2O2 displayed an increase of apoptosis rate from 7.5% to 27.3% relative to cells in the normal group (0.001<∗∗p<0.01), and the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse decrease of apoptosis rate from 27.3% to 14.5% compared to that in the model group (0.01<#p<0.05). These results demonstrated that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could protect the osteoblast from H2O2-induced injury.Figure 4
The protective effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial against H2O2-induced osteoblast injury. (a) CCK-8 assay for detecting the cellular proliferation of the normal osteoblast (normal group), H2O2-treated osteoblast (model group), and the treated osteoblast with H2O2 and supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial (MSN@IL-4 group). (b) Flow cytometry analysis with dual staining of PI and FITC-annexin V for testing the cellular apoptosis rate. (c) The statistical analysis for the apoptosis rate using GraphPad software. ∗∗p<0.01 and ∗∗∗p<0.001 vs. normal group; #p<0.05 vs. model group.
(a)(b)(c)
### 3.5. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the Apoptosis-Related Protein Expression in Osteoblast
To further confirm the protective effect of M2-polarizationed macrophagocyte on the apoptosis during osteoblast injury, the apoptosis-associated proteins of bcl-2, bax, caspase 3, and caspase 9 were probed using western blotting. The band images in Figure5 showed that osteoblast subjected to H2O2 displayed the expression increase of bax (∗∗p<0.01), cleaved caspase 3 (∗∗p<0.01), and cleaved caspase 8 (∗∗p<0.01) relative to cells in the normal group. Expectantly, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse regulation of protein expression that bax (##p<0.01), cleaved caspase 3 (#p<0.05), and cleaved caspase 8 (#p<0.05) were inhibited relative to cells in the model group. These results were consist with the apoptosis data from flow cytometry, demonstrating that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could protect the osteoblast from H2O2-induced apoptosis.Figure 5
The regulatory effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on apoptosis-associated proteins of bcl-2, bax, cleaved caspase 3, and cleaved caspase 8.∗∗p<0.01 vs. normal group; #p<0.05 and ##p<0.01 vs. model group.
### 3.6. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the NF-κB Pathway-Related p65 Nuclear Location in Osteoblast
To evaluate the inhibitory effect of M2-polarizationed macrophagocyte on osteoblast inflammation, p65 nucleus location, a classical NF-κB pathway indicator, was probed via immunofluorescent experiments. The fluorescent images in Figure 6 showed the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a inhibitory effect of p65 nucleus location compared that in the model group and have the significant statistical difference of 0.01<∗∗p<0.01; however, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN displayed a weak inhibitory of p65 nucleus location with no statistical difference compared that in the model group. The result demonstrated that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could suppress the osteoblast inflammation via NF-κB p65 nuclear location.Figure 6
The inhibitive effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on the NF-κB pathway. The nucleus location of p65 in H2O2-treated osteoblast (model group) and the treated osteoblast with supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial (MSN@IL-4 group) or only MSN (MSN group). The statistical analysis of p65 nucleus location using GraphPad software. ∗∗p<0.01 vs. model group.
### 3.7. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the NF-κB Pathway-Related Protein Expression in Osteoblast
To further confirm the suppressive effect of M2-polarizationed macrophagocyte on inflammation during osteoblast injury, the NF-κB pathway-associated proteins of p-IKK, IKK, and IκB were probed using western blotting. The band images in Figure 7 showed that osteoblast subjected to H2O2 displayed a evident decrease of IκB expression (∗∗p<0.01) and the phosphorylation increase of IKK (∗∗p<0.01) relative to cells in the normal group. Expectantly, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse regulation of protein expression that IκB expression in osteoblast cells of MSN@IL-4 group was induced (##p<0.01) and the protein phosphorylation of IKK was inhibited (#p<0.05) relative to cells in the model group. These results were consistent with the p65 nuclear location from immunofluorescent, demonstrating that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could suppress NF-κB pathway-associated inflammation in osteoblast.Figure 7
The regulatory effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on NF-κB pathway-associated proteins of p-IKK, IKK, and IκB. ∗p<0.01 vs. normal group; #p<0.05 and ##p<0.01 vs. model group.
## 3.1. Characteristics of MSN@IL-4 Scaffold and IL-4 Release Rate In Vitro
In order to obtain the controlled-release IL-4 system, MSN@IL-4 nanomaterial was fabricated via two-phase process, and in vitro IL-4 release response to pH was evaluated via Elisa assay. SEM photograph of MSN@IL-4 nanoparticle in Figure1(a) showed that several black spherical particles adhere to the surface of the grey balls, demonstrating that IL-4 was conjugated to MSN. The release curve of IL-4 in vitro (Figure 1(b)) showed that there are 12% release rate for 3th day and more than 80% for 30th day with a sustained manner in pH 5.5, and the release is adequate during 30 days; however, the release rate is only 51% in pH 7.2 and lower than 20% in pH 8.8 for 30th day; even from 15th day, the release is extremely slow or standstill. These release data demonstrate that MSN@IL-4 nanosystem possesses the sustained and adequate IL-4 release potential response to the acid environment.Figure 1
The scaffold of MSN@IL-4 and IL-4 release from MSN@IL-4 in vitro. (a) SEM image of MSN@IL-4 and (b) cumulative release of IL-4 response to pH.
(a)(b)
## 3.2. MSN@IL-4 Promote the Sustaining Secretion of Cytokines of IL-10, SDF-1α, and BMP-2 in Macrophagocyte
In order to confirm the effect of fabricated MSN@IL-4 nanomaterial on controlling pro-proliferative cytokine release, the secretion difference of IL-10, SDF-1α and BMP-2 in acrophagocyte subjecting to MSN@IL-4 nanocomplex or only IL-4 were detected by Elisa assay. The content curve in Figure 2(a) showed that the cells subjected to MSN@IL-4 nanocomplex treatment with the indicated time displayed a constantly linear increase of IL-10 secretion from 12 hours to 72 hours; however, the content of IL-10 in macrophagocyte subjected to only IL-4 displayed a rising for 24 hours compared to 12 hours and a constant decreasing from 24 hours to 72 hours. The change trends of SDF-1α secretion (Figure 2(b)) and BMP-2 secretion (Figure 2(c)) were similar in macrophagocyte subjected to MSN@IL-4 nanocomplex and only IL-4, which were that MSN@IL-4 promotes the constant and time-dependent increase of cytokines and only IL-4 was unsustainable. These results demonstrated that MSN@IL-4 nanocomplex could constantly promote proproliferative cytokine release in macrophagocyte compared to only IL-4 treatment.Figure 2
The effect of MSN@IL-4 nanomaterials for promoting the sustaining secretion of cytokines of IL-10, SDF-1α, and BMP-2 in macrophagocyte. Elisa assay for detecting the contents of IL-10 (a), SDF-1α (b), and BMP-2 (c) in the cellular supernatant.
(a)(b)(c)
## 3.3. MSN@IL-4 Promotes M2 Polarization in Macrophagocyte
To evaluate the promotive effect of MSN@IL-4 on M2 polarization, the M1/M2 indicator of CD86 and CD206 was detected via immunofluorescent experiments. The fluorescent images in Figure3 showed that macrophagocyte in MSN@IL-4 group displayed a decrease of CD86 expression compared to that in control group (0.01<∗p<0.05); oppositely, CD206 expression displayed an increasing trend in cells subjected to MSN@IL-4 nanomaterial compared to that in the control group (0.001<∗∗p<0.01). Meanwhile, the cells in only MSN group displayed similar expressions of CD86 and CD206 with that in the control group. These results demonstrated that MSN@IL-4 nanocomplex could promote the M2 polarization of macrophagocyte, but only MSN has no the similar effect.Figure 3
The promotive effect of MSN@IL-4 nanomaterials on M2 polarization in macrophagocyte. The representative fluorescent images of the stained CD86 and CD206 were displayed and relative expression were analyzed using GraphPad software.∗p<0.05 and ∗∗p<0.01 vs. control group.
## 3.4. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Protects the Damaged Osteoblast
To confirm the protective effect of M2-polarizationed macrophagocyte on osteoblast, the secretion supernatant from macrophagocyte subjected to MSN@IL-4 was employed to treat the damaged osteoblast, the proliferation was examined via CCK-8 assay and apoptosis was evaluated by flow cytometer. CCK-8 data in Figure4(a) showed that osteoblast subjected to H2O2 displayed a decrease of proliferation rate from 100% to 54.7% relative to cells in normal group (0.001<∗∗p<0.01), and the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse enhancement of proliferation rate from 54.7% to 84.2% compared to that in the model group (0.01<#p<0.05). The scatter diagram of flow cytometer in Figure 4(b) showed that osteoblast subjected to H2O2 displayed an increase of apoptosis rate from 7.5% to 27.3% relative to cells in the normal group (0.001<∗∗p<0.01), and the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse decrease of apoptosis rate from 27.3% to 14.5% compared to that in the model group (0.01<#p<0.05). These results demonstrated that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could protect the osteoblast from H2O2-induced injury.Figure 4
The protective effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial against H2O2-induced osteoblast injury. (a) CCK-8 assay for detecting the cellular proliferation of the normal osteoblast (normal group), H2O2-treated osteoblast (model group), and the treated osteoblast with H2O2 and supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial (MSN@IL-4 group). (b) Flow cytometry analysis with dual staining of PI and FITC-annexin V for testing the cellular apoptosis rate. (c) The statistical analysis for the apoptosis rate using GraphPad software. ∗∗p<0.01 and ∗∗∗p<0.001 vs. normal group; #p<0.05 vs. model group.
(a)(b)(c)
## 3.5. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the Apoptosis-Related Protein Expression in Osteoblast
To further confirm the protective effect of M2-polarizationed macrophagocyte on the apoptosis during osteoblast injury, the apoptosis-associated proteins of bcl-2, bax, caspase 3, and caspase 9 were probed using western blotting. The band images in Figure5 showed that osteoblast subjected to H2O2 displayed the expression increase of bax (∗∗p<0.01), cleaved caspase 3 (∗∗p<0.01), and cleaved caspase 8 (∗∗p<0.01) relative to cells in the normal group. Expectantly, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse regulation of protein expression that bax (##p<0.01), cleaved caspase 3 (#p<0.05), and cleaved caspase 8 (#p<0.05) were inhibited relative to cells in the model group. These results were consist with the apoptosis data from flow cytometry, demonstrating that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could protect the osteoblast from H2O2-induced apoptosis.Figure 5
The regulatory effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on apoptosis-associated proteins of bcl-2, bax, cleaved caspase 3, and cleaved caspase 8.∗∗p<0.01 vs. normal group; #p<0.05 and ##p<0.01 vs. model group.
## 3.6. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the NF-κB Pathway-Related p65 Nuclear Location in Osteoblast
To evaluate the inhibitory effect of M2-polarizationed macrophagocyte on osteoblast inflammation, p65 nucleus location, a classical NF-κB pathway indicator, was probed via immunofluorescent experiments. The fluorescent images in Figure 6 showed the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a inhibitory effect of p65 nucleus location compared that in the model group and have the significant statistical difference of 0.01<∗∗p<0.01; however, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN displayed a weak inhibitory of p65 nucleus location with no statistical difference compared that in the model group. The result demonstrated that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could suppress the osteoblast inflammation via NF-κB p65 nuclear location.Figure 6
The inhibitive effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on the NF-κB pathway. The nucleus location of p65 in H2O2-treated osteoblast (model group) and the treated osteoblast with supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial (MSN@IL-4 group) or only MSN (MSN group). The statistical analysis of p65 nucleus location using GraphPad software. ∗∗p<0.01 vs. model group.
## 3.7. The Secretion Supernatant from Macrophagocyte Subjected to MSN@IL-4 Suppresses the NF-κB Pathway-Related Protein Expression in Osteoblast
To further confirm the suppressive effect of M2-polarizationed macrophagocyte on inflammation during osteoblast injury, the NF-κB pathway-associated proteins of p-IKK, IKK, and IκB were probed using western blotting. The band images in Figure 7 showed that osteoblast subjected to H2O2 displayed a evident decrease of IκB expression (∗∗p<0.01) and the phosphorylation increase of IKK (∗∗p<0.01) relative to cells in the normal group. Expectantly, the osteoblast treated with H2O2 and the supernatant from macrophagocyte subjected to MSN@IL-4 displayed a reverse regulation of protein expression that IκB expression in osteoblast cells of MSN@IL-4 group was induced (##p<0.01) and the protein phosphorylation of IKK was inhibited (#p<0.05) relative to cells in the model group. These results were consistent with the p65 nuclear location from immunofluorescent, demonstrating that the supernatant from the M2-polarizationed macrophagocyte induced by MSN@IL-4 could suppress NF-κB pathway-associated inflammation in osteoblast.Figure 7
The regulatory effect of the secretion supernatant from macrophagocyte subjected to MSN@IL-4 nanomaterial on NF-κB pathway-associated proteins of p-IKK, IKK, and IκB. ∗p<0.01 vs. normal group; #p<0.05 and ##p<0.01 vs. model group.
## 4. Discussion
It is commonly recognized that a large number of inflammatory cells infiltrated at the injury site of bone defect, and inflammatory cells under different conditions will have different subtypes exerting diametrically opposite regulatory effects on osteoblasts of wound [17–19]. M2-polarized macrophages can play an importantly role in wound healing by promoting the secretion of proosteocyte growth factors [20, 21]. Therefore, the supplement of inducer of macrophage-M2-polarizaition such as IL-4 into the wound of bone defect would effectively promote wound healing. At present, the main treatment method for bone defects is bone transplantation. We have also reported the therapeutic effect of deproteinized bone scaffolds in the treatment of bone defects. However, the modified bone scaffolds added with macrophage M2 polarization inducers such as IL-4 have rarely been reported in the treatment of bone defects. Meanwhile, how to control the release of IL-4 in the modified bone scaffold to achieve sustained induction of macrophage polarization is also a technical problem. In this project, we constructed a nanomaterial of MSN@IL-4 loaded on a deproteinized bone scaffold, which can continuously and slowly release IL-4 in response to a slightly acidic environment. We found that MSN@IL-4 could promote the sustaining secretion of cytokines of IL-10, SDF-1α, and BMP-2 compared to only IL-4 and induced M2 polarization in macrophagocyte. The supernatant from macrophagocyte treated with MSN@IL-4 was added into the damaged osteoblast by H2O2, the proliferation ratio of the damaged osteoblast increased, the apoptosis ratio decreased, and NF-κB-associated inflammation was inhibited. These results demonstrated that MSN@IL-4 could protect osteoblast against cell injury induced H2O2 via macrophagocyte M2 polarization and sustainingly promoted the release of active osteoblast factor.Apoptosis is considered as a physiologically and pathologically programmed cell death process to clear off the redundant and malfunctional cells for keeping the cellular homeostasis [22]. Mitochondrial exerts the roles of the controlling center for cellular activities, which masters the oxidative phosphorylation and respiratory chain regulating almost all of the cellular physiopathology including apoptosis. During the apoptosis progression, apoptosis stimuli initiate the mitochondrial depolarization, induces/inhibits the expression of apoptosis-associated proteins of bax, bad, and bcl-2 from mitochondrial, triggers the cysteinyl aspartate specific proteinase (caspase) of caspase 3, caspase 8, and caspase 9, and consequently activates the cleavage of poly ADP-ribose polymerase (PARP), cell death, and tissue damage [23]. In the present research, H2O2 initiate the osteoblast apoptosis via regulating bax and bcl-2 expression and evoking caspase activities. Oppositely, the supernatant from macrophagocyte treated by MSN@IL-4 relieved the apoptosis induced by H2O2. These data demonstrated that MSN@IL-4 could relieve osteoblast injury via inducing macrophagocyte release the active cellular factors.The nuclear factorκB pathway (NF-κB pathway) has long been considered as a prototypical proinflammatory signaling pathway and controlled the expression of proinflammatory genes including cytokines, chemokines, and adhesion molecules [24]. NF-κB pathway was initiatively trigged with the phosphorylation of IKK response to inflammation factor, following the phosphorylation and degradation of IκB and then release the p65 protein from the complex of p65/p115/IκB, and induced its translocation from cytoplasm to nucleus for activating the gene expression of inflammatory factor such as TNFα, IL-1β, and IL-6, consequently causing the development of chronic diseases including cancer, diabetes, and osteoarthritis. In the present research, we found that the osteoblast damaged by H2O2 displayed an obvious phosphorylation of IKK, degradation of IκB, and phosphorylation of p65; meanwhile, the cells treated with the supernatant from macrophagocyte treated by MSN@IL-4 had a reverse trend change of the above NF-κB pathway indicators, demonstrating that MSN@IL-4 could protect against H2O2-inducing osteoblast injury via the induction of macrophagocyte release of the active cellular factors inhibiting the NF-κB inflammation pathway in osteoblast (Figure 8).Figure 8
Scheme summarizing MSN@IL-4 relieving osteoblast damage via macrophagocyte M2 polarization.
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*Source: 2898729-2022-10-03.xml* | 2022 |
# Hyper-IgE Syndrome with STAT3 Mutation: A Case Report in Mainland China
**Authors:** Lixin Xie; Xiaoxiang Hu; Yang Li; Weihua Zhang; Liang'an Chen
**Journal:** Clinical and Developmental Immunology
(2010)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2010/289873
---
## Abstract
Hyper-immunoglobulin E syndromes (HIES) including compound primary immunodeficiency and nonimmunological abnormalities are characterized by extremely high serum IgE levels, eosinophilia, eczema, susceptibility to infections, distinctive facial appearance, retention of deciduous teeth, cyst-forming pneumonias, and skeletal abnormalities. Itis reported that some cases of familial HIES are relative to autosomal dominant or recessive inheritance, but most cases are sporadic, and result from mutations in the human signal transducer and activator of transcription 3 (STAT3) gene. In this paper, we firstly report a young man diagnosed of Hyper-IgE syndrome with STAT3 mutation in Mainland China, and investigate the autosomal dominant trait of his family members.
---
## Body
## 1. Introduction
The hyper-IgE syndromes (HIES) are rare primary immune deficiencies characterized by elevated serum IgE, dermatitis, and recurrent skin and lung infections. There are two forms of HIES: a dominant form caused by mutations in STAT3, and a recessive form, for which a genetic cause is unclear. These two different syndromes have distinct presentations, courses, and outcomes and share very little in terms of pathogenesis other than the IgE elevation. In this paper, we firstly report a young man diagnosed of Hyper-IgE syndrome with STAT3 mutation in Mainland China, and investigate the autosomal dominant trait of his family members.Our patient, a 20-year-old man in mainland China, was suffering from eczema, lung cyst, skeletal and dental abnormalities, and so forth, which are the characteristics of type 1 HIES. He has extremely high serum IgE level is 200 times than that of normal person. Then, we sequenced the STAT3 gene by complementary DNA (cDNA) and genomic DNA, and we found a mutation locus, in which his parents and sister are normal.
## 2. Patient and Diagnosis
A 20-year-old man was found to presented with over ten-years history of cough with yellow-colored sputum and one year history of bloody sputum. He also reported universal boils on the face and limbs and recurrent pneumonias. In 1998, he received right upper lung cyst surgical therapy. His medical history was significant for eczema since newborn period and recurrent pustular and eczematoid rashes on the face and scalp in the childhood. Several primary teeth arrachement surgeries were performed in 13 years old on account of failure of the primary teeth to exfoliate.On physical examination, the vital signs were normal, clubbed fingers and toes; the characteristic facial appearance was noted with broad nose, deep-set eyes with a prominent forehead (Figure1(a)), and a rough facial skin with exaggerated pore size. Flat chest, scattered rash scars were showed on the chest skin. Bilateral fine crackles were audible in the lower lung, decreased breath sounds at the right base, and scattered expiratory wheeze bilaterally. Abdominal examination revealed moderate left middle abdominal tenderness.Symptoms. (a) The patient with broad nose, deep-set-eyes, a prominent forehead, and a rough facial skin with exaggerated pore size. (b) Multiple cysts in the left upper abdomen.
(a)(b)The leukocyte count was 11,350 cells/L (62% neutrophils, 19% lymphocytes, and 9% eosinophils). The hemoglobin concentration was 104 g/L, the red blood cell count3.82×1012/L, and the platelets count was 354×109/L. The erythrocyte sedimentation rate (ESR) was 87 mm/h. The C-reactive protein (CRP) was 7.15 mg/dL. The findings of further laboratory workup included the following: serum IgA, 135.0 mg/dL (reference range, 70 to 400 mg/dL); serum IgG, 2,560.0 mg/dL (reference range, 700 to 1600 mg/dL); and serum IgE, 37,700.0 IU/mL (reference range, 0 to 100 IU/mL). IgM concentrations (subclasses included) were within the normal range. CD4/CD8 count was normal. The findings of an enzymelinked immunosorbent assay for HIV antibody and an antineutrophil antibody screen were negative.A chest CT scan showed extensive consolidation and cystic changes in the right lung and patchy infiltration and cystic changes in the left lower lung. An abdominal CT scan revealed a big lower density mass measured10.6cm×9.5cm with multiple cysts in the left upper abdomen (Figure 1(b)). Bronchoscope examination found multimucous sputum in the tracheal and right and left bronchus. Percutaneous abdominal mass puncture and drainage guided by ultrasonography were performed, and laboratory examination of drainage liquid reported purulent fluid with a great amount of leukocytes. Cultivation of bacteria both in abdominal abscess and bronchial alveolar lavage fluid (BALF) revealed staphylococcus aureus (Methicillin sensitive staphylococcus aureus, MSSA).Based on these findings, we made the diagnosis of Hyper-IgE syndrome (HIES). According to these characteristics, we confirmed it the type 1 HIES. (This study was approved by the patient and informed consent was obtained from the families).
## 3. Material and Method
### 3.1. Mutational Analysis
EDTA blood was obtained and genomic DNA was isolated by using standard methods. All 24 exons and exon/intron boundaries were separately amplified by PCR. (The primers were designed according to GenBank NG_007370, the mutation in Exon 15 was amplified with 15F-5′-GATGGAGTTTTGCTGTGCTG-3′ and 15R-5′-AGATG GGATGCCAAGGATTT-3′).
### 3.2. Total RNA Extraction and cDNA Preparation
Total RNA was prepared from leucocyte of whole blood samples of the patient and his families using the QIAZOL Lysis Reagent (RNeasy Lipid Tissue) isolation method according to the manufacturer’s protocols (Qiagen, Valencia, CA, USA). Total RNA was isolated from by an RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufacturers’ instructions. About 1μg RNA was reverse transcribed into single-strand cDNA using oligo(dT) 18-mer primers and M-MLV Reverse Transcriptase (Invitrogen, Karlsruhe, Germany).
### 3.3. Quantitative Real-Time RT-PCR
Real-time RT-PCR was performed on a fluorescence thermal cycler (ABI Prism 7900 HT Sequence Detection System, Applied Biosystems). A standard two-step procedure was applied. RNAs were reverse transcribed into single strand cDNAs using oligo dT primers and M-MLV reverse transcriptase (Invitrogen, Karlsruhe, Germany). Real-time RT-PCR was performed in 15-μL reaction mixtures consisting of cDNA, 0.5 μM specific primer sets for each target gene, and SYBR Green PCR Master Mix (Applied Biosystems, UK). Conditions were: 50°C for 2 minutes, 95°C for 10 minutes, followed by 40 repetitive cycles of 95°C for 15 seconds, and 60°C for 1 minute. Details of melting curve analysis and relative standard curve generation were described in Supplemental Materials and Methods. β-actin was used as internal controls to normalize for initial RNA input and this gene was found to display remarkably stable expression levels across experimental treatments. (The primers of stat3 gene for RT-PCR were F: 5′-CAGTCCGTGGAACCATACACA-3′, R: 5′-GACCAGTGGAGA CACCAGGATA-3′; the primers of β-actin for RT-PCR were F: 5′-AAGATCATTGCTCCTCCTGAGC-3′, R: 5′-TCCTGCTTGCTGATCCACATC-3′).
### 3.4. Analysis of Allelic Expression of STAT3 Gene
Pyrosequencing technology on the PyroMark ID instrument was used to analyze allelic expression of stat3 gene at the mutational locus. Amplifying the dsDNA by PCR with one biotinylated primer (R-pyro:5′-CACGACGTTGTAAAACGACGGA GTGGGTCTCT-3′) and one unlabelled primer (F-pyro: 5′-CCGAGCCAATTGTGAT GC-3′); immobilizing the DNA samples, typically 2 pmol PCR product, 109 bp in length (CCGAGCCAATTGTGATGCTTCCCTGATTGTGACTGAGGAGCTG C[A/C]CCTGATCACCTTTGAGACCGAGGTGTATCACCAAGGCCTCAAGATTGACCTAGAGACCCACTCC), to Streptavidin Sepharose beads; separating the DNA strands; dispensing the ssDNA samples into the wells of the PSQ 96 Plate Low; annealing the samples to a sequencing primer (Seq-pyro: 5′-TGACTGAGGAGCTG C-3′) were carried out.
## 3.1. Mutational Analysis
EDTA blood was obtained and genomic DNA was isolated by using standard methods. All 24 exons and exon/intron boundaries were separately amplified by PCR. (The primers were designed according to GenBank NG_007370, the mutation in Exon 15 was amplified with 15F-5′-GATGGAGTTTTGCTGTGCTG-3′ and 15R-5′-AGATG GGATGCCAAGGATTT-3′).
## 3.2. Total RNA Extraction and cDNA Preparation
Total RNA was prepared from leucocyte of whole blood samples of the patient and his families using the QIAZOL Lysis Reagent (RNeasy Lipid Tissue) isolation method according to the manufacturer’s protocols (Qiagen, Valencia, CA, USA). Total RNA was isolated from by an RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufacturers’ instructions. About 1μg RNA was reverse transcribed into single-strand cDNA using oligo(dT) 18-mer primers and M-MLV Reverse Transcriptase (Invitrogen, Karlsruhe, Germany).
## 3.3. Quantitative Real-Time RT-PCR
Real-time RT-PCR was performed on a fluorescence thermal cycler (ABI Prism 7900 HT Sequence Detection System, Applied Biosystems). A standard two-step procedure was applied. RNAs were reverse transcribed into single strand cDNAs using oligo dT primers and M-MLV reverse transcriptase (Invitrogen, Karlsruhe, Germany). Real-time RT-PCR was performed in 15-μL reaction mixtures consisting of cDNA, 0.5 μM specific primer sets for each target gene, and SYBR Green PCR Master Mix (Applied Biosystems, UK). Conditions were: 50°C for 2 minutes, 95°C for 10 minutes, followed by 40 repetitive cycles of 95°C for 15 seconds, and 60°C for 1 minute. Details of melting curve analysis and relative standard curve generation were described in Supplemental Materials and Methods. β-actin was used as internal controls to normalize for initial RNA input and this gene was found to display remarkably stable expression levels across experimental treatments. (The primers of stat3 gene for RT-PCR were F: 5′-CAGTCCGTGGAACCATACACA-3′, R: 5′-GACCAGTGGAGA CACCAGGATA-3′; the primers of β-actin for RT-PCR were F: 5′-AAGATCATTGCTCCTCCTGAGC-3′, R: 5′-TCCTGCTTGCTGATCCACATC-3′).
## 3.4. Analysis of Allelic Expression of STAT3 Gene
Pyrosequencing technology on the PyroMark ID instrument was used to analyze allelic expression of stat3 gene at the mutational locus. Amplifying the dsDNA by PCR with one biotinylated primer (R-pyro:5′-CACGACGTTGTAAAACGACGGA GTGGGTCTCT-3′) and one unlabelled primer (F-pyro: 5′-CCGAGCCAATTGTGAT GC-3′); immobilizing the DNA samples, typically 2 pmol PCR product, 109 bp in length (CCGAGCCAATTGTGATGCTTCCCTGATTGTGACTGAGGAGCTG C[A/C]CCTGATCACCTTTGAGACCGAGGTGTATCACCAAGGCCTCAAGATTGACCTAGAGACCCACTCC), to Streptavidin Sepharose beads; separating the DNA strands; dispensing the ssDNA samples into the wells of the PSQ 96 Plate Low; annealing the samples to a sequencing primer (Seq-pyro: 5′-TGACTGAGGAGCTG C-3′) were carried out.
## 4. Results
### 4.1. The Identified Mutation in the STAT3 Gene
Several previous studies have showed mutations in the STAT3 gene on chromosome 17q21 as major causes of AD and sporadic HIES [1, 2]. We thus sequenced the regulatory region, the coding exons, and the intron-exon junctions of the STAT3 gene in the patient and his families. A heterozygous mutation H437P (1310A→C) occurred only in the patient who had extremely high IgE level. This mutation seemed to be de novo since none of the parents and the sibling of the patients carried this mutation, (Figure 2) with Mildly to moderately elevated IgE levels for his mother (162 IU/mL) and his younger sister (887 IU/mL).Sequencing results of STAT3 cDNA. (a) Heterozygous mutation in STAT3 genomic sequence of the patient. (b) Schematic of STAT3 amino acid structure and the identified mutation, H437P (1310A→C) in the DNA binding domain. (c) Pedigree of this family affected by the Hyper-IgE syndrome, the mutation was de novo, not inheritance.
(a)(b)(c)
### 4.2. The Gene Express Analysis of STAT3 by Real-Time PCR
The mRNA expression of STAT3 gene in the leucocyte from whole blood samples of the patient and his families control was examined by RT-PCR, using a pair of specific primers amplifying a 111-bp amplicon of this gene. The house-keeping geneβ-actin was used as an internal control for normalization. A relatively reduction level of expression of STAT3 gene can be observed in the patient (Figure 3).Figure 3
Relative STAT3 mRNA expression levels in the family. The expression of the patient is twice times lower than his families control.
### 4.3. The Allele Expression Quantified by cDNA Pyro-Sequence
To study this mutated allele expression more directly, we quantified the relative expression of alleles in leucocyte from whole blood samples of the patient and his families control using the1310A→C SNPs located in the Exon 15 of STAT3 gene. cDNA sequences from patient samples revealed expression of both alleles (38.9% C and 61.1% A through the exactly calculation) indicating the mutated transcription of STAT3 gene present in the patient. The association between the expression levels implies that the 1310A→C SNPs is the causative mutation for this dominant case (Figure 4).Pyrosequencing results (a) 38.9% C and 61.1% A at the mutational point of the patient. (b)–(d) 100.0% A and 0.0% C at the corresponding point of his parents and sister.
(a)(b)(c)(d)
## 4.1. The Identified Mutation in the STAT3 Gene
Several previous studies have showed mutations in the STAT3 gene on chromosome 17q21 as major causes of AD and sporadic HIES [1, 2]. We thus sequenced the regulatory region, the coding exons, and the intron-exon junctions of the STAT3 gene in the patient and his families. A heterozygous mutation H437P (1310A→C) occurred only in the patient who had extremely high IgE level. This mutation seemed to be de novo since none of the parents and the sibling of the patients carried this mutation, (Figure 2) with Mildly to moderately elevated IgE levels for his mother (162 IU/mL) and his younger sister (887 IU/mL).Sequencing results of STAT3 cDNA. (a) Heterozygous mutation in STAT3 genomic sequence of the patient. (b) Schematic of STAT3 amino acid structure and the identified mutation, H437P (1310A→C) in the DNA binding domain. (c) Pedigree of this family affected by the Hyper-IgE syndrome, the mutation was de novo, not inheritance.
(a)(b)(c)
## 4.2. The Gene Express Analysis of STAT3 by Real-Time PCR
The mRNA expression of STAT3 gene in the leucocyte from whole blood samples of the patient and his families control was examined by RT-PCR, using a pair of specific primers amplifying a 111-bp amplicon of this gene. The house-keeping geneβ-actin was used as an internal control for normalization. A relatively reduction level of expression of STAT3 gene can be observed in the patient (Figure 3).Figure 3
Relative STAT3 mRNA expression levels in the family. The expression of the patient is twice times lower than his families control.
## 4.3. The Allele Expression Quantified by cDNA Pyro-Sequence
To study this mutated allele expression more directly, we quantified the relative expression of alleles in leucocyte from whole blood samples of the patient and his families control using the1310A→C SNPs located in the Exon 15 of STAT3 gene. cDNA sequences from patient samples revealed expression of both alleles (38.9% C and 61.1% A through the exactly calculation) indicating the mutated transcription of STAT3 gene present in the patient. The association between the expression levels implies that the 1310A→C SNPs is the causative mutation for this dominant case (Figure 4).Pyrosequencing results (a) 38.9% C and 61.1% A at the mutational point of the patient. (b)–(d) 100.0% A and 0.0% C at the corresponding point of his parents and sister.
(a)(b)(c)(d)
## 5. Discussion
In 1966, the syndrome was first described as “Job’s syndrome” by Davis et al. in two girls suffering from recurrent “cold” staphylococcal abscesses, pneumonia, and neonatal-onset eczematoil rash, referring to the Biblical Job, who was “smote with sore boils” [3]. Then the disease was reported as hyper-IgE syndrome by Buckley et al. in 1972 because they found that these symptoms were associated with exceptionally high serum concentrations of IgE [4].HIES is a rare immunodeficiency syndrome of which the exact pathogenesis is still unknown. There is no specific clinical and laboratory test for confirming. Several symptoms such as elevated IgE levels and eosinophilia might also be found in other immunodeficiency syndromes [5]. Therefore, we must synthetically analyze the medical history, appearance and skin characteristics, visceral abnormalities, and necessary laboratory study findings including cytokines and immunoglobulins levels. Our patient’s pathogenesis was not working out until all the abovementioned aspects were examined. And all the symptoms indicated that he is a patient with hyper-IgE syndrome.The diagnosis of HIES is difficult to be confirmed in that both immunologic and somatic features need to be identified prior to genetic testing. There are two forms of HIES [6]. They have different pathogenesis, processes, and outcomes, and the only common ground is the IgE elevation, with values reaching >2000 IU (normal <200 IU) [7]. The type 1 HIES, a dominant form caused by hypomorphic mutations in STAT3, is a disease of multiorgan dysfunction. Besides eczema and recurrent staphylococcal infections in skin and lung, these patients suffer from abnormalities in vessels, connective tissue, and skeleton [8]. STAT3 (signal transducer and activator of transcription 3) is located on human chromosome 17q21, which was reported to contain a disease locus for familial autosomal dominant (AD)-HIES [7]. It is a transcription factor, which binds to the STAT3-responsive elements in the promoters of various genes and plays a critical role in responses to many cytokines, in which, IL-17 produced by TH17 cell is protective in the host defence against extracellular bacteria [9], and IL-22 stimulates cells in the skin and respiratory systems to produce β-defensins through STAT3 activation [10]. Therefore, the HIES aetiology might be directly and indirectly linked to STAT3. In other words, a human deficiency in STAT3 is a major cause of sporadic and familial HIES. The type 2 HIES is autosomal recessive (AR) syndrome [11]. The patients with type 2 HIES did not show any skeletal and dental abnormalities, and had no pulmonary cyst, but most of them suffered from viral infections such as chronic refractory molluscum contagiosum and herpes simplex virus infections, which were not identified in type 1 HIES. The genetic origin for a subpopulation of type 2 HIES is a null mutation of tyrosine kinase 2 (Tyk2) [12].For the past few years, the research in the etiology of HIES has got some achievements, especially with the development of molecular biology. But it is not completely clear to us. Until now, it is generally believed that STAT3 mutations act in a dominant negative manner to cause of autosomal dominant HIES [13]. And Tyk2 deficiency acts in a recessive manner to cause one of the cases of AR-HIES, although other genomic loci may also be involved [14]. Most STAT3 mutations are restricted to the DNA-binding or SH2 domains [15], and might concern the protein level, phosphorylation, and nuclear localization. In our research, we found a heterozygous mutation in the DNA-binding region of STAT3 gene, it could be one of the essential causes of the disease. Furthermore, may be his lower STAT3 protein expression level is a result of the mutation. However, its concrete effect still remains to be studied, for instance, when the mutation happens, how the STAT3 protein structure changes, and how the underlying mechanisms and passages make mistakes. They all need us to explore deeply.
## 6. Conclusion
These new and evolving genetic and immunologic understandings probably eventually lead to more effective disease-specific treatment for patients, including stem cell transplantations and gene-targeted therapies.
---
*Source: 289873-2010-05-17.xml* | 289873-2010-05-17_289873-2010-05-17.md | 20,535 | Hyper-IgE Syndrome with STAT3 Mutation: A Case Report in Mainland China | Lixin Xie; Xiaoxiang Hu; Yang Li; Weihua Zhang; Liang'an Chen | Clinical and Developmental Immunology
(2010) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2010/289873 | 289873-2010-05-17.xml | ---
## Abstract
Hyper-immunoglobulin E syndromes (HIES) including compound primary immunodeficiency and nonimmunological abnormalities are characterized by extremely high serum IgE levels, eosinophilia, eczema, susceptibility to infections, distinctive facial appearance, retention of deciduous teeth, cyst-forming pneumonias, and skeletal abnormalities. Itis reported that some cases of familial HIES are relative to autosomal dominant or recessive inheritance, but most cases are sporadic, and result from mutations in the human signal transducer and activator of transcription 3 (STAT3) gene. In this paper, we firstly report a young man diagnosed of Hyper-IgE syndrome with STAT3 mutation in Mainland China, and investigate the autosomal dominant trait of his family members.
---
## Body
## 1. Introduction
The hyper-IgE syndromes (HIES) are rare primary immune deficiencies characterized by elevated serum IgE, dermatitis, and recurrent skin and lung infections. There are two forms of HIES: a dominant form caused by mutations in STAT3, and a recessive form, for which a genetic cause is unclear. These two different syndromes have distinct presentations, courses, and outcomes and share very little in terms of pathogenesis other than the IgE elevation. In this paper, we firstly report a young man diagnosed of Hyper-IgE syndrome with STAT3 mutation in Mainland China, and investigate the autosomal dominant trait of his family members.Our patient, a 20-year-old man in mainland China, was suffering from eczema, lung cyst, skeletal and dental abnormalities, and so forth, which are the characteristics of type 1 HIES. He has extremely high serum IgE level is 200 times than that of normal person. Then, we sequenced the STAT3 gene by complementary DNA (cDNA) and genomic DNA, and we found a mutation locus, in which his parents and sister are normal.
## 2. Patient and Diagnosis
A 20-year-old man was found to presented with over ten-years history of cough with yellow-colored sputum and one year history of bloody sputum. He also reported universal boils on the face and limbs and recurrent pneumonias. In 1998, he received right upper lung cyst surgical therapy. His medical history was significant for eczema since newborn period and recurrent pustular and eczematoid rashes on the face and scalp in the childhood. Several primary teeth arrachement surgeries were performed in 13 years old on account of failure of the primary teeth to exfoliate.On physical examination, the vital signs were normal, clubbed fingers and toes; the characteristic facial appearance was noted with broad nose, deep-set eyes with a prominent forehead (Figure1(a)), and a rough facial skin with exaggerated pore size. Flat chest, scattered rash scars were showed on the chest skin. Bilateral fine crackles were audible in the lower lung, decreased breath sounds at the right base, and scattered expiratory wheeze bilaterally. Abdominal examination revealed moderate left middle abdominal tenderness.Symptoms. (a) The patient with broad nose, deep-set-eyes, a prominent forehead, and a rough facial skin with exaggerated pore size. (b) Multiple cysts in the left upper abdomen.
(a)(b)The leukocyte count was 11,350 cells/L (62% neutrophils, 19% lymphocytes, and 9% eosinophils). The hemoglobin concentration was 104 g/L, the red blood cell count3.82×1012/L, and the platelets count was 354×109/L. The erythrocyte sedimentation rate (ESR) was 87 mm/h. The C-reactive protein (CRP) was 7.15 mg/dL. The findings of further laboratory workup included the following: serum IgA, 135.0 mg/dL (reference range, 70 to 400 mg/dL); serum IgG, 2,560.0 mg/dL (reference range, 700 to 1600 mg/dL); and serum IgE, 37,700.0 IU/mL (reference range, 0 to 100 IU/mL). IgM concentrations (subclasses included) were within the normal range. CD4/CD8 count was normal. The findings of an enzymelinked immunosorbent assay for HIV antibody and an antineutrophil antibody screen were negative.A chest CT scan showed extensive consolidation and cystic changes in the right lung and patchy infiltration and cystic changes in the left lower lung. An abdominal CT scan revealed a big lower density mass measured10.6cm×9.5cm with multiple cysts in the left upper abdomen (Figure 1(b)). Bronchoscope examination found multimucous sputum in the tracheal and right and left bronchus. Percutaneous abdominal mass puncture and drainage guided by ultrasonography were performed, and laboratory examination of drainage liquid reported purulent fluid with a great amount of leukocytes. Cultivation of bacteria both in abdominal abscess and bronchial alveolar lavage fluid (BALF) revealed staphylococcus aureus (Methicillin sensitive staphylococcus aureus, MSSA).Based on these findings, we made the diagnosis of Hyper-IgE syndrome (HIES). According to these characteristics, we confirmed it the type 1 HIES. (This study was approved by the patient and informed consent was obtained from the families).
## 3. Material and Method
### 3.1. Mutational Analysis
EDTA blood was obtained and genomic DNA was isolated by using standard methods. All 24 exons and exon/intron boundaries were separately amplified by PCR. (The primers were designed according to GenBank NG_007370, the mutation in Exon 15 was amplified with 15F-5′-GATGGAGTTTTGCTGTGCTG-3′ and 15R-5′-AGATG GGATGCCAAGGATTT-3′).
### 3.2. Total RNA Extraction and cDNA Preparation
Total RNA was prepared from leucocyte of whole blood samples of the patient and his families using the QIAZOL Lysis Reagent (RNeasy Lipid Tissue) isolation method according to the manufacturer’s protocols (Qiagen, Valencia, CA, USA). Total RNA was isolated from by an RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufacturers’ instructions. About 1μg RNA was reverse transcribed into single-strand cDNA using oligo(dT) 18-mer primers and M-MLV Reverse Transcriptase (Invitrogen, Karlsruhe, Germany).
### 3.3. Quantitative Real-Time RT-PCR
Real-time RT-PCR was performed on a fluorescence thermal cycler (ABI Prism 7900 HT Sequence Detection System, Applied Biosystems). A standard two-step procedure was applied. RNAs were reverse transcribed into single strand cDNAs using oligo dT primers and M-MLV reverse transcriptase (Invitrogen, Karlsruhe, Germany). Real-time RT-PCR was performed in 15-μL reaction mixtures consisting of cDNA, 0.5 μM specific primer sets for each target gene, and SYBR Green PCR Master Mix (Applied Biosystems, UK). Conditions were: 50°C for 2 minutes, 95°C for 10 minutes, followed by 40 repetitive cycles of 95°C for 15 seconds, and 60°C for 1 minute. Details of melting curve analysis and relative standard curve generation were described in Supplemental Materials and Methods. β-actin was used as internal controls to normalize for initial RNA input and this gene was found to display remarkably stable expression levels across experimental treatments. (The primers of stat3 gene for RT-PCR were F: 5′-CAGTCCGTGGAACCATACACA-3′, R: 5′-GACCAGTGGAGA CACCAGGATA-3′; the primers of β-actin for RT-PCR were F: 5′-AAGATCATTGCTCCTCCTGAGC-3′, R: 5′-TCCTGCTTGCTGATCCACATC-3′).
### 3.4. Analysis of Allelic Expression of STAT3 Gene
Pyrosequencing technology on the PyroMark ID instrument was used to analyze allelic expression of stat3 gene at the mutational locus. Amplifying the dsDNA by PCR with one biotinylated primer (R-pyro:5′-CACGACGTTGTAAAACGACGGA GTGGGTCTCT-3′) and one unlabelled primer (F-pyro: 5′-CCGAGCCAATTGTGAT GC-3′); immobilizing the DNA samples, typically 2 pmol PCR product, 109 bp in length (CCGAGCCAATTGTGATGCTTCCCTGATTGTGACTGAGGAGCTG C[A/C]CCTGATCACCTTTGAGACCGAGGTGTATCACCAAGGCCTCAAGATTGACCTAGAGACCCACTCC), to Streptavidin Sepharose beads; separating the DNA strands; dispensing the ssDNA samples into the wells of the PSQ 96 Plate Low; annealing the samples to a sequencing primer (Seq-pyro: 5′-TGACTGAGGAGCTG C-3′) were carried out.
## 3.1. Mutational Analysis
EDTA blood was obtained and genomic DNA was isolated by using standard methods. All 24 exons and exon/intron boundaries were separately amplified by PCR. (The primers were designed according to GenBank NG_007370, the mutation in Exon 15 was amplified with 15F-5′-GATGGAGTTTTGCTGTGCTG-3′ and 15R-5′-AGATG GGATGCCAAGGATTT-3′).
## 3.2. Total RNA Extraction and cDNA Preparation
Total RNA was prepared from leucocyte of whole blood samples of the patient and his families using the QIAZOL Lysis Reagent (RNeasy Lipid Tissue) isolation method according to the manufacturer’s protocols (Qiagen, Valencia, CA, USA). Total RNA was isolated from by an RNeasy mini kit (Qiagen, Valencia, CA, USA) according to the manufacturers’ instructions. About 1μg RNA was reverse transcribed into single-strand cDNA using oligo(dT) 18-mer primers and M-MLV Reverse Transcriptase (Invitrogen, Karlsruhe, Germany).
## 3.3. Quantitative Real-Time RT-PCR
Real-time RT-PCR was performed on a fluorescence thermal cycler (ABI Prism 7900 HT Sequence Detection System, Applied Biosystems). A standard two-step procedure was applied. RNAs were reverse transcribed into single strand cDNAs using oligo dT primers and M-MLV reverse transcriptase (Invitrogen, Karlsruhe, Germany). Real-time RT-PCR was performed in 15-μL reaction mixtures consisting of cDNA, 0.5 μM specific primer sets for each target gene, and SYBR Green PCR Master Mix (Applied Biosystems, UK). Conditions were: 50°C for 2 minutes, 95°C for 10 minutes, followed by 40 repetitive cycles of 95°C for 15 seconds, and 60°C for 1 minute. Details of melting curve analysis and relative standard curve generation were described in Supplemental Materials and Methods. β-actin was used as internal controls to normalize for initial RNA input and this gene was found to display remarkably stable expression levels across experimental treatments. (The primers of stat3 gene for RT-PCR were F: 5′-CAGTCCGTGGAACCATACACA-3′, R: 5′-GACCAGTGGAGA CACCAGGATA-3′; the primers of β-actin for RT-PCR were F: 5′-AAGATCATTGCTCCTCCTGAGC-3′, R: 5′-TCCTGCTTGCTGATCCACATC-3′).
## 3.4. Analysis of Allelic Expression of STAT3 Gene
Pyrosequencing technology on the PyroMark ID instrument was used to analyze allelic expression of stat3 gene at the mutational locus. Amplifying the dsDNA by PCR with one biotinylated primer (R-pyro:5′-CACGACGTTGTAAAACGACGGA GTGGGTCTCT-3′) and one unlabelled primer (F-pyro: 5′-CCGAGCCAATTGTGAT GC-3′); immobilizing the DNA samples, typically 2 pmol PCR product, 109 bp in length (CCGAGCCAATTGTGATGCTTCCCTGATTGTGACTGAGGAGCTG C[A/C]CCTGATCACCTTTGAGACCGAGGTGTATCACCAAGGCCTCAAGATTGACCTAGAGACCCACTCC), to Streptavidin Sepharose beads; separating the DNA strands; dispensing the ssDNA samples into the wells of the PSQ 96 Plate Low; annealing the samples to a sequencing primer (Seq-pyro: 5′-TGACTGAGGAGCTG C-3′) were carried out.
## 4. Results
### 4.1. The Identified Mutation in the STAT3 Gene
Several previous studies have showed mutations in the STAT3 gene on chromosome 17q21 as major causes of AD and sporadic HIES [1, 2]. We thus sequenced the regulatory region, the coding exons, and the intron-exon junctions of the STAT3 gene in the patient and his families. A heterozygous mutation H437P (1310A→C) occurred only in the patient who had extremely high IgE level. This mutation seemed to be de novo since none of the parents and the sibling of the patients carried this mutation, (Figure 2) with Mildly to moderately elevated IgE levels for his mother (162 IU/mL) and his younger sister (887 IU/mL).Sequencing results of STAT3 cDNA. (a) Heterozygous mutation in STAT3 genomic sequence of the patient. (b) Schematic of STAT3 amino acid structure and the identified mutation, H437P (1310A→C) in the DNA binding domain. (c) Pedigree of this family affected by the Hyper-IgE syndrome, the mutation was de novo, not inheritance.
(a)(b)(c)
### 4.2. The Gene Express Analysis of STAT3 by Real-Time PCR
The mRNA expression of STAT3 gene in the leucocyte from whole blood samples of the patient and his families control was examined by RT-PCR, using a pair of specific primers amplifying a 111-bp amplicon of this gene. The house-keeping geneβ-actin was used as an internal control for normalization. A relatively reduction level of expression of STAT3 gene can be observed in the patient (Figure 3).Figure 3
Relative STAT3 mRNA expression levels in the family. The expression of the patient is twice times lower than his families control.
### 4.3. The Allele Expression Quantified by cDNA Pyro-Sequence
To study this mutated allele expression more directly, we quantified the relative expression of alleles in leucocyte from whole blood samples of the patient and his families control using the1310A→C SNPs located in the Exon 15 of STAT3 gene. cDNA sequences from patient samples revealed expression of both alleles (38.9% C and 61.1% A through the exactly calculation) indicating the mutated transcription of STAT3 gene present in the patient. The association between the expression levels implies that the 1310A→C SNPs is the causative mutation for this dominant case (Figure 4).Pyrosequencing results (a) 38.9% C and 61.1% A at the mutational point of the patient. (b)–(d) 100.0% A and 0.0% C at the corresponding point of his parents and sister.
(a)(b)(c)(d)
## 4.1. The Identified Mutation in the STAT3 Gene
Several previous studies have showed mutations in the STAT3 gene on chromosome 17q21 as major causes of AD and sporadic HIES [1, 2]. We thus sequenced the regulatory region, the coding exons, and the intron-exon junctions of the STAT3 gene in the patient and his families. A heterozygous mutation H437P (1310A→C) occurred only in the patient who had extremely high IgE level. This mutation seemed to be de novo since none of the parents and the sibling of the patients carried this mutation, (Figure 2) with Mildly to moderately elevated IgE levels for his mother (162 IU/mL) and his younger sister (887 IU/mL).Sequencing results of STAT3 cDNA. (a) Heterozygous mutation in STAT3 genomic sequence of the patient. (b) Schematic of STAT3 amino acid structure and the identified mutation, H437P (1310A→C) in the DNA binding domain. (c) Pedigree of this family affected by the Hyper-IgE syndrome, the mutation was de novo, not inheritance.
(a)(b)(c)
## 4.2. The Gene Express Analysis of STAT3 by Real-Time PCR
The mRNA expression of STAT3 gene in the leucocyte from whole blood samples of the patient and his families control was examined by RT-PCR, using a pair of specific primers amplifying a 111-bp amplicon of this gene. The house-keeping geneβ-actin was used as an internal control for normalization. A relatively reduction level of expression of STAT3 gene can be observed in the patient (Figure 3).Figure 3
Relative STAT3 mRNA expression levels in the family. The expression of the patient is twice times lower than his families control.
## 4.3. The Allele Expression Quantified by cDNA Pyro-Sequence
To study this mutated allele expression more directly, we quantified the relative expression of alleles in leucocyte from whole blood samples of the patient and his families control using the1310A→C SNPs located in the Exon 15 of STAT3 gene. cDNA sequences from patient samples revealed expression of both alleles (38.9% C and 61.1% A through the exactly calculation) indicating the mutated transcription of STAT3 gene present in the patient. The association between the expression levels implies that the 1310A→C SNPs is the causative mutation for this dominant case (Figure 4).Pyrosequencing results (a) 38.9% C and 61.1% A at the mutational point of the patient. (b)–(d) 100.0% A and 0.0% C at the corresponding point of his parents and sister.
(a)(b)(c)(d)
## 5. Discussion
In 1966, the syndrome was first described as “Job’s syndrome” by Davis et al. in two girls suffering from recurrent “cold” staphylococcal abscesses, pneumonia, and neonatal-onset eczematoil rash, referring to the Biblical Job, who was “smote with sore boils” [3]. Then the disease was reported as hyper-IgE syndrome by Buckley et al. in 1972 because they found that these symptoms were associated with exceptionally high serum concentrations of IgE [4].HIES is a rare immunodeficiency syndrome of which the exact pathogenesis is still unknown. There is no specific clinical and laboratory test for confirming. Several symptoms such as elevated IgE levels and eosinophilia might also be found in other immunodeficiency syndromes [5]. Therefore, we must synthetically analyze the medical history, appearance and skin characteristics, visceral abnormalities, and necessary laboratory study findings including cytokines and immunoglobulins levels. Our patient’s pathogenesis was not working out until all the abovementioned aspects were examined. And all the symptoms indicated that he is a patient with hyper-IgE syndrome.The diagnosis of HIES is difficult to be confirmed in that both immunologic and somatic features need to be identified prior to genetic testing. There are two forms of HIES [6]. They have different pathogenesis, processes, and outcomes, and the only common ground is the IgE elevation, with values reaching >2000 IU (normal <200 IU) [7]. The type 1 HIES, a dominant form caused by hypomorphic mutations in STAT3, is a disease of multiorgan dysfunction. Besides eczema and recurrent staphylococcal infections in skin and lung, these patients suffer from abnormalities in vessels, connective tissue, and skeleton [8]. STAT3 (signal transducer and activator of transcription 3) is located on human chromosome 17q21, which was reported to contain a disease locus for familial autosomal dominant (AD)-HIES [7]. It is a transcription factor, which binds to the STAT3-responsive elements in the promoters of various genes and plays a critical role in responses to many cytokines, in which, IL-17 produced by TH17 cell is protective in the host defence against extracellular bacteria [9], and IL-22 stimulates cells in the skin and respiratory systems to produce β-defensins through STAT3 activation [10]. Therefore, the HIES aetiology might be directly and indirectly linked to STAT3. In other words, a human deficiency in STAT3 is a major cause of sporadic and familial HIES. The type 2 HIES is autosomal recessive (AR) syndrome [11]. The patients with type 2 HIES did not show any skeletal and dental abnormalities, and had no pulmonary cyst, but most of them suffered from viral infections such as chronic refractory molluscum contagiosum and herpes simplex virus infections, which were not identified in type 1 HIES. The genetic origin for a subpopulation of type 2 HIES is a null mutation of tyrosine kinase 2 (Tyk2) [12].For the past few years, the research in the etiology of HIES has got some achievements, especially with the development of molecular biology. But it is not completely clear to us. Until now, it is generally believed that STAT3 mutations act in a dominant negative manner to cause of autosomal dominant HIES [13]. And Tyk2 deficiency acts in a recessive manner to cause one of the cases of AR-HIES, although other genomic loci may also be involved [14]. Most STAT3 mutations are restricted to the DNA-binding or SH2 domains [15], and might concern the protein level, phosphorylation, and nuclear localization. In our research, we found a heterozygous mutation in the DNA-binding region of STAT3 gene, it could be one of the essential causes of the disease. Furthermore, may be his lower STAT3 protein expression level is a result of the mutation. However, its concrete effect still remains to be studied, for instance, when the mutation happens, how the STAT3 protein structure changes, and how the underlying mechanisms and passages make mistakes. They all need us to explore deeply.
## 6. Conclusion
These new and evolving genetic and immunologic understandings probably eventually lead to more effective disease-specific treatment for patients, including stem cell transplantations and gene-targeted therapies.
---
*Source: 289873-2010-05-17.xml* | 2010 |
# Fumigant Compounds from the Essential Oil of ChineseBlumea balsamifera Leaves against the Maize Weevil (Sitophilus zeamais)
**Authors:** Sha Sha Chu; Shu Shan Du; Zhi Long Liu
**Journal:** Journal of Chemistry
(2013)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2013/289874
---
## Abstract
Essential oil of Chinese medicinal herb,Blumea balsamifera leaves, was found to possess fumigant toxicity against the maize weevils, Sitophilus zeamais. The main components of the essential oil of B. balsamifera were 1,8-cineole (20.98%), borneol (11.99%), β-caryophyllene (10.38%), camphor (8.06%), 4-terpineol (6.49%), α-terpineol (5.91%), and caryophyllene oxide (5.35%). Bioactivity-guided chromatographic separation of the essential oil on repeated silica gel columns led to isolate five constituent compounds, namely, 1,8-cineole, borneol, camphor, α-terpineol, and 4-terpineol. 1,8-Cineole, 4-terpineol, and α-terpineol showed pronounced fumigant toxicity against S. zeamais adults (LC50 = 2.96 mg/L, 4.79 mg/L, and 7.45 mg/L air, resp.) and were more toxic than camphor (LC50 = 21.64 mg/L air) and borneol (LC50 = 21.67 mg/L air). The crude essential oil also possessed strong fumigant toxicity against S. zeamais adults (LC50 = 10.71 mg/L air).
---
## Body
## 1. Introduction
Fumigants play a very important role in insect pest elimination in stored products not only because of their ability to kill a broad spectrum of pests but also because of their easy penetration into the commodity while leaving minimal residues [1]. Currently, phosphine and methyl bromide (MeBr) are the two common fumigants used for stored-product protection all over the world. Due to insect resistance to phosphine and MeBr as an ozone-depleting compound, there is a global interest in looking for new fumigants [1, 2] and plant essential oils and their components have been shown to possess potential to be developed as new fumigants. Plant essential oils and their components may have the advantage over conventional fumigants in terms of low mammalian toxicity, rapid degradation, and local availability [3, 4]. Essential oils derived from more than 75 plant species have been studied for fumigant toxicity against stored product insects [5].Botanical pesticides have the advantage of providing novel modes of action against insects that can reduce the risk of cross-resistance as well as offering new leads for design of target-specific molecules [1]. During the screening program for new agrochemicals from Chinese medicinal herbs, the essential oil of Blumea balsamiferaDC. (Family: Asteraceae) leaves was found to possess strong fumigant toxicity to the maize weevil, Sitophilus zeamais (Motsch). The maize weevil (S. zeamais) is one of the most widespread and destructive primary insect pests of stored cereals [6]. Infestations not only cause significant losses due to the consumption of grains; they also result in elevated temperature and moisture conditions that lead to an accelerated growth of molds, including toxigenic species. B. balsamifera is a perennial evergreen shrub native of Southeast Asia but is distributed throughout tropical Asia. It is a small tree that can grow up to 4 m in height and imparts a strong camphorous odor around it. Use of B. balsamifera leaves has been recommended as traditional Chinese medicine in the treatment of various diseases [7]. It has anti-inflammatory, anticatarrhal and expectorant properties which render it useful in the treatment of both upper and lower respiratory tracts like sinusitis, influenza, and asthmatic bronchitis. Several studies on the chemical constituents of B. balsamifera have been reported, and a number of flavonoids, sesquiterpenoids, and triterpenoids, have been isolated from this plant [8–17]. Chemical composition of the essential oil of B. balsamifera leaves has been studied [18–22]. However, the essential oil of B. balsamifera leaves was not evaluated to have insecticidal activity against grain storage insects and the bioactive (fumigant) constituent compounds of the essential oil have not been isolated and identified from this Chinese medicinal herb. In this paper, we report the isolation and identification of five active compounds contained in the essential oil of B. balsamifera leaves against the maize weevil by bioassay-guided fractionation.
## 2. Experimental
1H nuclear magnetic resonance (NMR) spectra were recorded on Bruker ACF300 (300 MHz (1H)) and AMX500 (500 MHz (1H)) instruments using deuterochloroform (CDCl3) as the solvent with tetramethylsilane (TMS) as the internal standard. Electron impact ionone mass spectra (EIMS) were determined on a Micromass VG7035 mass spectrometer at 70 eV (probe). The crude essential oil (20 mL) was chromatographed on a silica gel (Merck 9385, 1,000 g) column (85 mm i.d., 850 mm length) by gradient elution with a mixture of solvents (n-hexane, n-hexane-ethyl acetate, and acetone). Fractions of 500 mL were collected and concentrated at 40°C, and similar fractions according to TLC profiles were combined to yield 28 fractions. Each fraction was tested with fumigant toxicity bioassay (see the following) to identify the bioactive fractions (fractions 5, 9, 11, 14, and 16). Fractions that possessed fumigant toxicity, with similar TLC profiles, were pooled and further purified by preparative silica gel column chromatography (PTLC) until obtaining three pure compounds for determining structure (Figure 1). The spectral data of 1,8-cineole (1) (2.7 g) matched with the previous reports [23, 24]. The data of camphor (2) (1.6 g) and borneol (3) (1.2 g) matched with the previous reports [23, 25, 26]. The spectral data were identical to the published data of 4-terpineol (4) (1.1 g) and α-terpineol (5) (0.9 g) (Table 3) [23, 27, 28].Figure 1
Constituent compounds isolated fromB. balsamifera essential oil.
### 2.1. Chinese Medicinal Herb and Hydrodistillation
Fresh leaves ofB. balsamifera were collected from the suburb of Nanning City (22.8°N, 108.3°E, Guangxi Zhuang Autonomous Region, China) at August 2008. The plant was identified by Dr. QR Liu (College of Life Sciences, Beijing Normal University, China), and a voucher specimen (CMH-Dafengai-Guangxi-2008-08) was deposited in the Department of Entomology, China Agricultural University. To obtain volatile essential oil, the air-dried samples were first ground to a powder then soaked in water at a ratio of 1 : 4 (w/v) for 1 h, prior to hydrodistillation using a round bottom container over a period of 6 h. The volatile essential oil was collected in a specific receiver, measured, dried over anhydrous sulfate, weighed, and stored in airtight containers.
### 2.2. Analysis of the Essential Oil
Components of the essential oil ofB. balsamifera leaves were separated and identified by gas chromatography-mass spectrometry (GC-MS) Agilent 6890N gas chromatography hooked to Agilent 5973N mass selective detector. They equipped with a flame ionization detector and capillary column with HP-5MS (30m×0.25mm×0.25μm). The GC settings were as follows: the initial oven temperature was held at 60°C for 1 min and ramped at 10°C min−1 to 180°C for 1 min, and then ramped at 20°C min−1 to 280°C for 15 min. The injector temperature was maintained at 270°C. The samples (1 μL) were injected neat, with a split ratio of 1 : 10. The carrier gas was helium at flow rate of 1.0 mL min−1. Spectra were scanned from 20 to 550 m/z at 2 scans s−1. Most constituents were identified by gas chromatography by comparison of their retention indices with those of the literature [18–22] or with those of authentic compounds available in our laboratories. The retention indices were determined in relation to a homologous series of n-alkanes (C8–C24) under the same operating conditions. Further identification was made by comparison of their mass spectra on both columns with those stored in NIST 05 and Wiley 275 libraries or with mass spectra from literature [29]. Component relative percentages were calculated based on GC peak areas without using correction factors.
### 2.3. Fumigant Toxicity [6]
The maize weevils were obtained from laboratory cultures maintained for the last 15 years in the dark in incubators at 29–30°C and 65–75% r.h. They were reared on whole wheat at 12–13% moisture content. The unsexed adults used in the experiments were 2–4 weeks posteclosion. A Whatman filter paper (CAT number 1001020, diameter 2.0 cm) was placed on the underside of the screw cap of a glass vial (diameter 2.5 cm, height 5.5 cm, volume 24 mL). Ten microliters of an appropriate concentration of compounds/oil (1.0%–40.0%, 5 concentrations) were added to the filter paper. The solvent was allowed to evaporate for 30 seconds before the cap was placed tightly on the glass vial (with 10 insects).n-Hexane was used as controls. The vials were upright and the Fluon (ICI America Inc) coating restricted the insects to the lower portion of the vial to prevent them from the treated filter paper. Six replicates were used in all treatments and controls, and they were incubated at 29–30°C and 65–75% RH for 24 hrs. The insects were then transferred to clean vials with some culture media and kept in an incubator for determination of end-point mortality, which was reached after one week. The insects were considered dead if appendages did not move when probed with a camel brush. The observed mortality data were corrected for control mortality using Abbott’s formula. Results from all replicates were subjected to probit analysis using the PriProbit Program V1.6.3 to determine LC50 and LC90 values [30].
## 2.1. Chinese Medicinal Herb and Hydrodistillation
Fresh leaves ofB. balsamifera were collected from the suburb of Nanning City (22.8°N, 108.3°E, Guangxi Zhuang Autonomous Region, China) at August 2008. The plant was identified by Dr. QR Liu (College of Life Sciences, Beijing Normal University, China), and a voucher specimen (CMH-Dafengai-Guangxi-2008-08) was deposited in the Department of Entomology, China Agricultural University. To obtain volatile essential oil, the air-dried samples were first ground to a powder then soaked in water at a ratio of 1 : 4 (w/v) for 1 h, prior to hydrodistillation using a round bottom container over a period of 6 h. The volatile essential oil was collected in a specific receiver, measured, dried over anhydrous sulfate, weighed, and stored in airtight containers.
## 2.2. Analysis of the Essential Oil
Components of the essential oil ofB. balsamifera leaves were separated and identified by gas chromatography-mass spectrometry (GC-MS) Agilent 6890N gas chromatography hooked to Agilent 5973N mass selective detector. They equipped with a flame ionization detector and capillary column with HP-5MS (30m×0.25mm×0.25μm). The GC settings were as follows: the initial oven temperature was held at 60°C for 1 min and ramped at 10°C min−1 to 180°C for 1 min, and then ramped at 20°C min−1 to 280°C for 15 min. The injector temperature was maintained at 270°C. The samples (1 μL) were injected neat, with a split ratio of 1 : 10. The carrier gas was helium at flow rate of 1.0 mL min−1. Spectra were scanned from 20 to 550 m/z at 2 scans s−1. Most constituents were identified by gas chromatography by comparison of their retention indices with those of the literature [18–22] or with those of authentic compounds available in our laboratories. The retention indices were determined in relation to a homologous series of n-alkanes (C8–C24) under the same operating conditions. Further identification was made by comparison of their mass spectra on both columns with those stored in NIST 05 and Wiley 275 libraries or with mass spectra from literature [29]. Component relative percentages were calculated based on GC peak areas without using correction factors.
## 2.3. Fumigant Toxicity [6]
The maize weevils were obtained from laboratory cultures maintained for the last 15 years in the dark in incubators at 29–30°C and 65–75% r.h. They were reared on whole wheat at 12–13% moisture content. The unsexed adults used in the experiments were 2–4 weeks posteclosion. A Whatman filter paper (CAT number 1001020, diameter 2.0 cm) was placed on the underside of the screw cap of a glass vial (diameter 2.5 cm, height 5.5 cm, volume 24 mL). Ten microliters of an appropriate concentration of compounds/oil (1.0%–40.0%, 5 concentrations) were added to the filter paper. The solvent was allowed to evaporate for 30 seconds before the cap was placed tightly on the glass vial (with 10 insects).n-Hexane was used as controls. The vials were upright and the Fluon (ICI America Inc) coating restricted the insects to the lower portion of the vial to prevent them from the treated filter paper. Six replicates were used in all treatments and controls, and they were incubated at 29–30°C and 65–75% RH for 24 hrs. The insects were then transferred to clean vials with some culture media and kept in an incubator for determination of end-point mortality, which was reached after one week. The insects were considered dead if appendages did not move when probed with a camel brush. The observed mortality data were corrected for control mortality using Abbott’s formula. Results from all replicates were subjected to probit analysis using the PriProbit Program V1.6.3 to determine LC50 and LC90 values [30].
## 3. Results and Discussion
### 3.1. Chemical Constituents of the Essential Oil
Hydrodistillation of dried leaves ofB. balsamifera yielded 0.88% essential oil (v/w), and the density of the essential oil was determined as 0.87%. The results of GC-MS of B. balsamifera essential oil are presented in Table 1. A total of 27 components were identified in the essential oil of B. balsamifera, accounting for 99.23% of the total oil (Table 1). The main components are 1,8-cineole (20.98%), borneol (11.99%), β-caryophyllene (10.38%), camphor (8.06%), 4-terpineol (6.49%), α-terpineol (5.91%), and caryophyllene oxide (5.35%). Monoterpenoids represented 12 of the 27 compounds, corresponding to 70.47% of the whole oil while 13 of the 27 constituents were sesquiterpenoids (27.42% of the crude essential oil). The chemical composition of B. balsamifera essential oil was different from that reported in other studies. For example, borneol (33.2%), caryophyllene (8.2%), ledol (7.1%), tetracyclo[6,3,2,0,(2.5).0(1,8) tridecan-9-ol, 4,4-dimethyl (5.2%), phytol (4.6%), caryophyllene oxide (4.1%), guaiol (3.4%), thujopsene-13 (4.4%), dimethoxydurene (3.6%), and γ-eudesmol (3.2%) were the dominant components in the essential oil of B. balsamifera leaves collected from Bangladesh (Chittagong, 22.20°N, 91.50°E) [20]. However, borneol (57.7%), caryophyllene (7.6%), and camphor (5.0%) were the three main components of the essential oil of B. balsamifera from Guizhou, China (Luodian Country, 25.43°N, 106.75°E) [21], while bornel (52.4%) and camphor (17.7%) were the two components of the essential oil from Yunnan, China (Puer City, 22.48°N, 100.58°E) [22]. There were great geographic variations in chemical composition of essential oils of B. balsamifera harvested in three provinces of Vietnam [18]. The major components of the essential oils were borneol (57.8%), caryophyllene (8.3%), δ-cadinol (8.0%), and caryophyllene oxide (3.1%) (Ha Giang, 22.80°N, 104.98°E); borneol (50.6%), camphor (18.7%), caryophyllene (10.1%), δ-cadinol (3.1%), patchoulene (3.0%), and veridiflorol (2.0%) (Hanoi, 21.02°N, 105.51°E); camphor (70.1%), caryophyllene (10.5%), borneol (5.7%), and carvacrol (5.7%) (Dak Lak, 22.80°N, 104.98°E). The above findings suggest that further studies on plant cultivation and essential oil standardization are necessary because chemical composition of the essential oil varies greatly with the plant population.Table 1
Chemical constituents of essential oil fromBlumea balsamifera leaves.
RI*
Compound
Formula
RA** (%)
998
Yomogi alcohol
C10H18O
2.58
1032
1,8-Cineole
C10H18O
20.98
1083
Artemisia alcohol
C10H18O
1.87
1114
β-Thujone
C10H16O
3.21
1126
ρ-Menth-2-en-1-ol
C10H18O
1.84
1138
2,2,4-Trimethyl-3-cyclohexene-1-carboxaldehyde
C10H16O
3.34
1143
Camphor
C10H16O
8.06
1168
Borneol
C10H18O
11.99
1179
4-Terpineol
C10H18O
6.49
1188
α-Terpineol
C10H18O
5.91
1205
Verbenone
C10H14O
1.84
1222
cis-Carveol
C10H16O
2.36
1356
Eugenol
C10H12O2
1.02
1374
Copaene
C15H24
0.28
1387
β-Cubebene
C15H24
0.43
1420
Caryophyllene
C15H24
10.38
1434
β-Gurjunene
C15H24
0.45
1452
cis-β-Farnesene
C15H24
0.37
1455
α-Caryophyllene
C15H24
1.50
1473
γ-Muurolene
C15H24
0.35
1480
Germacrene D
C15H24
1.10
1483
(+)-β-Selinene
C15H24
0.95
1523
δ-Cadinene
C15H24
0.53
1578
Spathulenol
C15H24O
2.64
1583
Caryophyllene oxide
C15H24O
5.35
1556
Guaia-3,9-diene
C15H24
3.09
2119
Phytol
C20H40O
0.32
Total
99.23
Monoterpenoids
70.47
Sesquiterpenoids
27.42
Others
1.34
*RI: retention index as determined on a HP-5MS column using the homologous series of n-hydrocarbons.
*
*RA: relative area (peak area relative to total peak area).
### 3.2. Fumigant Toxicity of Isolated Constituent Compounds against the Maize Weevils
1,8-Cineole (1) (LC50 = 2.96 mg/L air), 4-terpineol (4) (LC50 = 4.79 mg/L air), and α-terpineol (5) (LC50 = 7.45 mg/L air) showed stronger fumigant toxicity than the crude essential oil (LC50 = 10.71 mg/L air) against S. zeamais (Table 2). It indicates that fumigant toxicity of the essential oil may be attributed to the three constituent compounds. In the previous studies, 1,8-cineole was found to exhibit fumigant toxicity against red flour beetles, Tribolium castaneum adult with LC50 = 41 μL/L air [31], 15.3 μL/L air [32], and 1.52 mg/L air [33]. It also possesses fumigant toxicity against several other stored product insects and cockroaches as well as mosquitoes, for example, the rice weevil (S. oryzae) (LC50 = 22.8 μL/L air [32]), the lesser grain borer (Rhyzopertha dominica) (LC50 = 9.5 μL/L air [32]). However, compared with the current used fumigant (MeBr, LC50 = 0.67 mg/L air), the three compounds and the crude essential oil exhibited only 4–16 times less toxic to the maize weevils. The three constituent compounds and the crude essential oil were more toxic to S. zeamais than another two isolated compounds, camphor (2) (LC50 = 21.67 mg/L air) and borneol (3) (LC50 = 29.64 mg/L air) (Figure 2). Compared with the other essential oils in the previous studies that were tested using a similar bioassay, B. balsamifera essential oil exhibited stronger fumigant toxicity against S. zeamais adults, for example, essential oils of Schizonepeta multifida [34],Murraya exotica [35], and several essential oils from Genus Artemisia [36–38]. Moreover, the two other active constituent compounds, 4-terpineol and α-terpineol, have been found to possess strong fumigant toxicity against several grain storage insects, such as S. granarius, S. oryzae, T. castaneum, T. confusum, and R. dominica [31, 32, 39–43]. The two other active constituents, camphor and borneol, were also demonstrated fumigant toxicity against grain storage insects [31, 41, 44, 45].Table 2
Fumigant toxicity ofBlumea balsamifera essential oil and its constituent compounds against Sitophilus zeamais adults.
Treatments
Conc.
Mortality
LC50 (mg/L air)
LC
9
0 (mg/L air)
Slope ± SE
Chi square (χ2)
(%)
(%±SE)
(95% FL)
(95% FL)
20.00
98.0 ± 1.22
14.29
72.0 ± 3.43
Borneol
10.20
48.0 ± 3.41
29.64 (27.39–31.98)
40.11 (37.67–43.24)
2.37 ± 0.32
15.34
7.29
34.0 ± 2.34
5.21
8.0 ± 1.22
20.00
88.0 ± 3.43
13.33
65.0 ± 2.45
Camphor
8.89
47.0 ± 1.43
21.67 (19.74–23.25)
43.54 (39.76–47.32)
2.18 ± 0.25
8.39
5.92
36.0 ± 1.32
3.95
10.0 ± 2.32
3.00
95.0 ± 1.34
1.50
78.0 ± 3.43
1,8-Cineole
0.75
56.0 ± 2.45
2.96 (2.76–3.21)
5.46 (4.78–5.93)
1.72 ± 0.15
9.48
0.38
35.0 ± 1.56
0.19
12.5 ± 0.78
10.00
95.0 ± 2.34
5.00
84.0 ± 1.68
α-Terpineol
2.50
62.0 ± 1.87
7.45 (6.51–8.32)
12.18 (10.79–13.23)
2.13 ± 0.21
11.79
1.25
38.0 ± 1.54
0.66
13.0 ± 0.89
8.00
94.0 ± 3.43
4.00
72.0 ± 2.43
4-Terpineol
2.00
48.0 ± 1.45
4.79 (4.31–5.22)
8.37 (7.67–9.27)
2.07 ± 0.19
3.14
1.00
32.0 ± 1.67
0.50
7.0 ± 0.56
MeBr*
—
—
0.67
—
—
—
15.0
98.0 ± 2.54
7.50
86.0 ± 1.95
Crude oil
3.75
65.0 ± 1.65
10.71 (9.76–11.75)
18.82 (17.13–20.67)
1.77 ± 0.13
5.28
1.88
42.0 ± 1.44
0.94
16.0 ± 0.99
*MeBr: Methyl bromide; values from Liu and Ho [6].Table 3
1H and 13C values (δ (ppm)) of the isolated compounds.
Number
1,8-Cineole
Camphor
Borneol
4-Terpineol
α-Terpineol
1H
13C
1H
13C
1H
13C
1H
13C
1H
13C
1
—
72.7
—
220.0
3.15
76.1
—
133.9
—
133.9
2
1.52
37.3
2.14; 1.89
40.4
1.67; 1.42
35.8
5.37
123.3
5.37
123.3
3
1.40
24.2
1.99
34.4
1.42
45.2
2.19; 1.94
40.8
2.04; 1.79
24.1
4
1.74
39.6
1.60; 1.35
28.4
1.52; 1.27
23.6
—
71.7
1.71
46.5
5
1.52; 1.27
24.2
1.84; 1.59
31.5
1.49; 1.24
30.0
1.88; 1.63
30.3
1.74; 1.49
19.1
6
1.65; 1.40
37.3
—
61.6
—
52.7
2.01; 1.91
24.7
2.01; 1.91
31.2
7
1.31
25.4
1.26
15.6
1.16
13.3
1.71
23.1
17.1
23.1
8
—
76.8
—
39.8
—
50.4
1.90
37.6
—
73.3
9
1.26
25.4
1.11
21.8
1.11
19.8
1.01
14.9
1.26
27.7
10
1.26
25.4
1.11
21.8
1.11
19.8
1.01
14.9
1.26
27.7Dose response curves ofSitophilus zeamais treated with the essential oil and its constituent compounds.
(a)
(b)
(c)
(d)
(e)
(f)Considering the currently used fumigants are synthetic insecticides, fumigant activity of the crude essential oil ofB. balsamifera leaves and the three isolated active compounds are quite promising and they show potential to be developed as possible natural fumigants for control of stored product insects with low toxicity to humans. Although dried leaves of B. balsamifera were used as a common Chinese medicinal herb [7], there are no toxicity data for this herb and the three isolated compounds and available on human consumption. For the practical use of the three compounds and crude essential oil as novel botanical insecticides, further studies are necessary on the safety of these materials to human, on phytotoxicity to crop seeds, and on the development of formulations to improve efficacy and stability, and to cut cost as well. The isolated three active compounds exhibited fumigant toxicity against several grain storage insects [31, 32, 39–43]. However, little has been done on mechanisms of action of these three monoterpenes. In addition, further testing is necessary to evaluate the spectrum of fumigant activity against other stored-product insects (as well as other life stages of these stored-product insects, especially eggs).
## 3.1. Chemical Constituents of the Essential Oil
Hydrodistillation of dried leaves ofB. balsamifera yielded 0.88% essential oil (v/w), and the density of the essential oil was determined as 0.87%. The results of GC-MS of B. balsamifera essential oil are presented in Table 1. A total of 27 components were identified in the essential oil of B. balsamifera, accounting for 99.23% of the total oil (Table 1). The main components are 1,8-cineole (20.98%), borneol (11.99%), β-caryophyllene (10.38%), camphor (8.06%), 4-terpineol (6.49%), α-terpineol (5.91%), and caryophyllene oxide (5.35%). Monoterpenoids represented 12 of the 27 compounds, corresponding to 70.47% of the whole oil while 13 of the 27 constituents were sesquiterpenoids (27.42% of the crude essential oil). The chemical composition of B. balsamifera essential oil was different from that reported in other studies. For example, borneol (33.2%), caryophyllene (8.2%), ledol (7.1%), tetracyclo[6,3,2,0,(2.5).0(1,8) tridecan-9-ol, 4,4-dimethyl (5.2%), phytol (4.6%), caryophyllene oxide (4.1%), guaiol (3.4%), thujopsene-13 (4.4%), dimethoxydurene (3.6%), and γ-eudesmol (3.2%) were the dominant components in the essential oil of B. balsamifera leaves collected from Bangladesh (Chittagong, 22.20°N, 91.50°E) [20]. However, borneol (57.7%), caryophyllene (7.6%), and camphor (5.0%) were the three main components of the essential oil of B. balsamifera from Guizhou, China (Luodian Country, 25.43°N, 106.75°E) [21], while bornel (52.4%) and camphor (17.7%) were the two components of the essential oil from Yunnan, China (Puer City, 22.48°N, 100.58°E) [22]. There were great geographic variations in chemical composition of essential oils of B. balsamifera harvested in three provinces of Vietnam [18]. The major components of the essential oils were borneol (57.8%), caryophyllene (8.3%), δ-cadinol (8.0%), and caryophyllene oxide (3.1%) (Ha Giang, 22.80°N, 104.98°E); borneol (50.6%), camphor (18.7%), caryophyllene (10.1%), δ-cadinol (3.1%), patchoulene (3.0%), and veridiflorol (2.0%) (Hanoi, 21.02°N, 105.51°E); camphor (70.1%), caryophyllene (10.5%), borneol (5.7%), and carvacrol (5.7%) (Dak Lak, 22.80°N, 104.98°E). The above findings suggest that further studies on plant cultivation and essential oil standardization are necessary because chemical composition of the essential oil varies greatly with the plant population.Table 1
Chemical constituents of essential oil fromBlumea balsamifera leaves.
RI*
Compound
Formula
RA** (%)
998
Yomogi alcohol
C10H18O
2.58
1032
1,8-Cineole
C10H18O
20.98
1083
Artemisia alcohol
C10H18O
1.87
1114
β-Thujone
C10H16O
3.21
1126
ρ-Menth-2-en-1-ol
C10H18O
1.84
1138
2,2,4-Trimethyl-3-cyclohexene-1-carboxaldehyde
C10H16O
3.34
1143
Camphor
C10H16O
8.06
1168
Borneol
C10H18O
11.99
1179
4-Terpineol
C10H18O
6.49
1188
α-Terpineol
C10H18O
5.91
1205
Verbenone
C10H14O
1.84
1222
cis-Carveol
C10H16O
2.36
1356
Eugenol
C10H12O2
1.02
1374
Copaene
C15H24
0.28
1387
β-Cubebene
C15H24
0.43
1420
Caryophyllene
C15H24
10.38
1434
β-Gurjunene
C15H24
0.45
1452
cis-β-Farnesene
C15H24
0.37
1455
α-Caryophyllene
C15H24
1.50
1473
γ-Muurolene
C15H24
0.35
1480
Germacrene D
C15H24
1.10
1483
(+)-β-Selinene
C15H24
0.95
1523
δ-Cadinene
C15H24
0.53
1578
Spathulenol
C15H24O
2.64
1583
Caryophyllene oxide
C15H24O
5.35
1556
Guaia-3,9-diene
C15H24
3.09
2119
Phytol
C20H40O
0.32
Total
99.23
Monoterpenoids
70.47
Sesquiterpenoids
27.42
Others
1.34
*RI: retention index as determined on a HP-5MS column using the homologous series of n-hydrocarbons.
*
*RA: relative area (peak area relative to total peak area).
## 3.2. Fumigant Toxicity of Isolated Constituent Compounds against the Maize Weevils
1,8-Cineole (1) (LC50 = 2.96 mg/L air), 4-terpineol (4) (LC50 = 4.79 mg/L air), and α-terpineol (5) (LC50 = 7.45 mg/L air) showed stronger fumigant toxicity than the crude essential oil (LC50 = 10.71 mg/L air) against S. zeamais (Table 2). It indicates that fumigant toxicity of the essential oil may be attributed to the three constituent compounds. In the previous studies, 1,8-cineole was found to exhibit fumigant toxicity against red flour beetles, Tribolium castaneum adult with LC50 = 41 μL/L air [31], 15.3 μL/L air [32], and 1.52 mg/L air [33]. It also possesses fumigant toxicity against several other stored product insects and cockroaches as well as mosquitoes, for example, the rice weevil (S. oryzae) (LC50 = 22.8 μL/L air [32]), the lesser grain borer (Rhyzopertha dominica) (LC50 = 9.5 μL/L air [32]). However, compared with the current used fumigant (MeBr, LC50 = 0.67 mg/L air), the three compounds and the crude essential oil exhibited only 4–16 times less toxic to the maize weevils. The three constituent compounds and the crude essential oil were more toxic to S. zeamais than another two isolated compounds, camphor (2) (LC50 = 21.67 mg/L air) and borneol (3) (LC50 = 29.64 mg/L air) (Figure 2). Compared with the other essential oils in the previous studies that were tested using a similar bioassay, B. balsamifera essential oil exhibited stronger fumigant toxicity against S. zeamais adults, for example, essential oils of Schizonepeta multifida [34],Murraya exotica [35], and several essential oils from Genus Artemisia [36–38]. Moreover, the two other active constituent compounds, 4-terpineol and α-terpineol, have been found to possess strong fumigant toxicity against several grain storage insects, such as S. granarius, S. oryzae, T. castaneum, T. confusum, and R. dominica [31, 32, 39–43]. The two other active constituents, camphor and borneol, were also demonstrated fumigant toxicity against grain storage insects [31, 41, 44, 45].Table 2
Fumigant toxicity ofBlumea balsamifera essential oil and its constituent compounds against Sitophilus zeamais adults.
Treatments
Conc.
Mortality
LC50 (mg/L air)
LC
9
0 (mg/L air)
Slope ± SE
Chi square (χ2)
(%)
(%±SE)
(95% FL)
(95% FL)
20.00
98.0 ± 1.22
14.29
72.0 ± 3.43
Borneol
10.20
48.0 ± 3.41
29.64 (27.39–31.98)
40.11 (37.67–43.24)
2.37 ± 0.32
15.34
7.29
34.0 ± 2.34
5.21
8.0 ± 1.22
20.00
88.0 ± 3.43
13.33
65.0 ± 2.45
Camphor
8.89
47.0 ± 1.43
21.67 (19.74–23.25)
43.54 (39.76–47.32)
2.18 ± 0.25
8.39
5.92
36.0 ± 1.32
3.95
10.0 ± 2.32
3.00
95.0 ± 1.34
1.50
78.0 ± 3.43
1,8-Cineole
0.75
56.0 ± 2.45
2.96 (2.76–3.21)
5.46 (4.78–5.93)
1.72 ± 0.15
9.48
0.38
35.0 ± 1.56
0.19
12.5 ± 0.78
10.00
95.0 ± 2.34
5.00
84.0 ± 1.68
α-Terpineol
2.50
62.0 ± 1.87
7.45 (6.51–8.32)
12.18 (10.79–13.23)
2.13 ± 0.21
11.79
1.25
38.0 ± 1.54
0.66
13.0 ± 0.89
8.00
94.0 ± 3.43
4.00
72.0 ± 2.43
4-Terpineol
2.00
48.0 ± 1.45
4.79 (4.31–5.22)
8.37 (7.67–9.27)
2.07 ± 0.19
3.14
1.00
32.0 ± 1.67
0.50
7.0 ± 0.56
MeBr*
—
—
0.67
—
—
—
15.0
98.0 ± 2.54
7.50
86.0 ± 1.95
Crude oil
3.75
65.0 ± 1.65
10.71 (9.76–11.75)
18.82 (17.13–20.67)
1.77 ± 0.13
5.28
1.88
42.0 ± 1.44
0.94
16.0 ± 0.99
*MeBr: Methyl bromide; values from Liu and Ho [6].Table 3
1H and 13C values (δ (ppm)) of the isolated compounds.
Number
1,8-Cineole
Camphor
Borneol
4-Terpineol
α-Terpineol
1H
13C
1H
13C
1H
13C
1H
13C
1H
13C
1
—
72.7
—
220.0
3.15
76.1
—
133.9
—
133.9
2
1.52
37.3
2.14; 1.89
40.4
1.67; 1.42
35.8
5.37
123.3
5.37
123.3
3
1.40
24.2
1.99
34.4
1.42
45.2
2.19; 1.94
40.8
2.04; 1.79
24.1
4
1.74
39.6
1.60; 1.35
28.4
1.52; 1.27
23.6
—
71.7
1.71
46.5
5
1.52; 1.27
24.2
1.84; 1.59
31.5
1.49; 1.24
30.0
1.88; 1.63
30.3
1.74; 1.49
19.1
6
1.65; 1.40
37.3
—
61.6
—
52.7
2.01; 1.91
24.7
2.01; 1.91
31.2
7
1.31
25.4
1.26
15.6
1.16
13.3
1.71
23.1
17.1
23.1
8
—
76.8
—
39.8
—
50.4
1.90
37.6
—
73.3
9
1.26
25.4
1.11
21.8
1.11
19.8
1.01
14.9
1.26
27.7
10
1.26
25.4
1.11
21.8
1.11
19.8
1.01
14.9
1.26
27.7Dose response curves ofSitophilus zeamais treated with the essential oil and its constituent compounds.
(a)
(b)
(c)
(d)
(e)
(f)Considering the currently used fumigants are synthetic insecticides, fumigant activity of the crude essential oil ofB. balsamifera leaves and the three isolated active compounds are quite promising and they show potential to be developed as possible natural fumigants for control of stored product insects with low toxicity to humans. Although dried leaves of B. balsamifera were used as a common Chinese medicinal herb [7], there are no toxicity data for this herb and the three isolated compounds and available on human consumption. For the practical use of the three compounds and crude essential oil as novel botanical insecticides, further studies are necessary on the safety of these materials to human, on phytotoxicity to crop seeds, and on the development of formulations to improve efficacy and stability, and to cut cost as well. The isolated three active compounds exhibited fumigant toxicity against several grain storage insects [31, 32, 39–43]. However, little has been done on mechanisms of action of these three monoterpenes. In addition, further testing is necessary to evaluate the spectrum of fumigant activity against other stored-product insects (as well as other life stages of these stored-product insects, especially eggs).
---
*Source: 289874-2012-08-09.xml* | 289874-2012-08-09_289874-2012-08-09.md | 31,962 | Fumigant Compounds from the Essential Oil of ChineseBlumea balsamifera Leaves against the Maize Weevil (Sitophilus zeamais) | Sha Sha Chu; Shu Shan Du; Zhi Long Liu | Journal of Chemistry
(2013) | Chemistry and Chemical Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2013/289874 | 289874-2012-08-09.xml | ---
## Abstract
Essential oil of Chinese medicinal herb,Blumea balsamifera leaves, was found to possess fumigant toxicity against the maize weevils, Sitophilus zeamais. The main components of the essential oil of B. balsamifera were 1,8-cineole (20.98%), borneol (11.99%), β-caryophyllene (10.38%), camphor (8.06%), 4-terpineol (6.49%), α-terpineol (5.91%), and caryophyllene oxide (5.35%). Bioactivity-guided chromatographic separation of the essential oil on repeated silica gel columns led to isolate five constituent compounds, namely, 1,8-cineole, borneol, camphor, α-terpineol, and 4-terpineol. 1,8-Cineole, 4-terpineol, and α-terpineol showed pronounced fumigant toxicity against S. zeamais adults (LC50 = 2.96 mg/L, 4.79 mg/L, and 7.45 mg/L air, resp.) and were more toxic than camphor (LC50 = 21.64 mg/L air) and borneol (LC50 = 21.67 mg/L air). The crude essential oil also possessed strong fumigant toxicity against S. zeamais adults (LC50 = 10.71 mg/L air).
---
## Body
## 1. Introduction
Fumigants play a very important role in insect pest elimination in stored products not only because of their ability to kill a broad spectrum of pests but also because of their easy penetration into the commodity while leaving minimal residues [1]. Currently, phosphine and methyl bromide (MeBr) are the two common fumigants used for stored-product protection all over the world. Due to insect resistance to phosphine and MeBr as an ozone-depleting compound, there is a global interest in looking for new fumigants [1, 2] and plant essential oils and their components have been shown to possess potential to be developed as new fumigants. Plant essential oils and their components may have the advantage over conventional fumigants in terms of low mammalian toxicity, rapid degradation, and local availability [3, 4]. Essential oils derived from more than 75 plant species have been studied for fumigant toxicity against stored product insects [5].Botanical pesticides have the advantage of providing novel modes of action against insects that can reduce the risk of cross-resistance as well as offering new leads for design of target-specific molecules [1]. During the screening program for new agrochemicals from Chinese medicinal herbs, the essential oil of Blumea balsamiferaDC. (Family: Asteraceae) leaves was found to possess strong fumigant toxicity to the maize weevil, Sitophilus zeamais (Motsch). The maize weevil (S. zeamais) is one of the most widespread and destructive primary insect pests of stored cereals [6]. Infestations not only cause significant losses due to the consumption of grains; they also result in elevated temperature and moisture conditions that lead to an accelerated growth of molds, including toxigenic species. B. balsamifera is a perennial evergreen shrub native of Southeast Asia but is distributed throughout tropical Asia. It is a small tree that can grow up to 4 m in height and imparts a strong camphorous odor around it. Use of B. balsamifera leaves has been recommended as traditional Chinese medicine in the treatment of various diseases [7]. It has anti-inflammatory, anticatarrhal and expectorant properties which render it useful in the treatment of both upper and lower respiratory tracts like sinusitis, influenza, and asthmatic bronchitis. Several studies on the chemical constituents of B. balsamifera have been reported, and a number of flavonoids, sesquiterpenoids, and triterpenoids, have been isolated from this plant [8–17]. Chemical composition of the essential oil of B. balsamifera leaves has been studied [18–22]. However, the essential oil of B. balsamifera leaves was not evaluated to have insecticidal activity against grain storage insects and the bioactive (fumigant) constituent compounds of the essential oil have not been isolated and identified from this Chinese medicinal herb. In this paper, we report the isolation and identification of five active compounds contained in the essential oil of B. balsamifera leaves against the maize weevil by bioassay-guided fractionation.
## 2. Experimental
1H nuclear magnetic resonance (NMR) spectra were recorded on Bruker ACF300 (300 MHz (1H)) and AMX500 (500 MHz (1H)) instruments using deuterochloroform (CDCl3) as the solvent with tetramethylsilane (TMS) as the internal standard. Electron impact ionone mass spectra (EIMS) were determined on a Micromass VG7035 mass spectrometer at 70 eV (probe). The crude essential oil (20 mL) was chromatographed on a silica gel (Merck 9385, 1,000 g) column (85 mm i.d., 850 mm length) by gradient elution with a mixture of solvents (n-hexane, n-hexane-ethyl acetate, and acetone). Fractions of 500 mL were collected and concentrated at 40°C, and similar fractions according to TLC profiles were combined to yield 28 fractions. Each fraction was tested with fumigant toxicity bioassay (see the following) to identify the bioactive fractions (fractions 5, 9, 11, 14, and 16). Fractions that possessed fumigant toxicity, with similar TLC profiles, were pooled and further purified by preparative silica gel column chromatography (PTLC) until obtaining three pure compounds for determining structure (Figure 1). The spectral data of 1,8-cineole (1) (2.7 g) matched with the previous reports [23, 24]. The data of camphor (2) (1.6 g) and borneol (3) (1.2 g) matched with the previous reports [23, 25, 26]. The spectral data were identical to the published data of 4-terpineol (4) (1.1 g) and α-terpineol (5) (0.9 g) (Table 3) [23, 27, 28].Figure 1
Constituent compounds isolated fromB. balsamifera essential oil.
### 2.1. Chinese Medicinal Herb and Hydrodistillation
Fresh leaves ofB. balsamifera were collected from the suburb of Nanning City (22.8°N, 108.3°E, Guangxi Zhuang Autonomous Region, China) at August 2008. The plant was identified by Dr. QR Liu (College of Life Sciences, Beijing Normal University, China), and a voucher specimen (CMH-Dafengai-Guangxi-2008-08) was deposited in the Department of Entomology, China Agricultural University. To obtain volatile essential oil, the air-dried samples were first ground to a powder then soaked in water at a ratio of 1 : 4 (w/v) for 1 h, prior to hydrodistillation using a round bottom container over a period of 6 h. The volatile essential oil was collected in a specific receiver, measured, dried over anhydrous sulfate, weighed, and stored in airtight containers.
### 2.2. Analysis of the Essential Oil
Components of the essential oil ofB. balsamifera leaves were separated and identified by gas chromatography-mass spectrometry (GC-MS) Agilent 6890N gas chromatography hooked to Agilent 5973N mass selective detector. They equipped with a flame ionization detector and capillary column with HP-5MS (30m×0.25mm×0.25μm). The GC settings were as follows: the initial oven temperature was held at 60°C for 1 min and ramped at 10°C min−1 to 180°C for 1 min, and then ramped at 20°C min−1 to 280°C for 15 min. The injector temperature was maintained at 270°C. The samples (1 μL) were injected neat, with a split ratio of 1 : 10. The carrier gas was helium at flow rate of 1.0 mL min−1. Spectra were scanned from 20 to 550 m/z at 2 scans s−1. Most constituents were identified by gas chromatography by comparison of their retention indices with those of the literature [18–22] or with those of authentic compounds available in our laboratories. The retention indices were determined in relation to a homologous series of n-alkanes (C8–C24) under the same operating conditions. Further identification was made by comparison of their mass spectra on both columns with those stored in NIST 05 and Wiley 275 libraries or with mass spectra from literature [29]. Component relative percentages were calculated based on GC peak areas without using correction factors.
### 2.3. Fumigant Toxicity [6]
The maize weevils were obtained from laboratory cultures maintained for the last 15 years in the dark in incubators at 29–30°C and 65–75% r.h. They were reared on whole wheat at 12–13% moisture content. The unsexed adults used in the experiments were 2–4 weeks posteclosion. A Whatman filter paper (CAT number 1001020, diameter 2.0 cm) was placed on the underside of the screw cap of a glass vial (diameter 2.5 cm, height 5.5 cm, volume 24 mL). Ten microliters of an appropriate concentration of compounds/oil (1.0%–40.0%, 5 concentrations) were added to the filter paper. The solvent was allowed to evaporate for 30 seconds before the cap was placed tightly on the glass vial (with 10 insects).n-Hexane was used as controls. The vials were upright and the Fluon (ICI America Inc) coating restricted the insects to the lower portion of the vial to prevent them from the treated filter paper. Six replicates were used in all treatments and controls, and they were incubated at 29–30°C and 65–75% RH for 24 hrs. The insects were then transferred to clean vials with some culture media and kept in an incubator for determination of end-point mortality, which was reached after one week. The insects were considered dead if appendages did not move when probed with a camel brush. The observed mortality data were corrected for control mortality using Abbott’s formula. Results from all replicates were subjected to probit analysis using the PriProbit Program V1.6.3 to determine LC50 and LC90 values [30].
## 2.1. Chinese Medicinal Herb and Hydrodistillation
Fresh leaves ofB. balsamifera were collected from the suburb of Nanning City (22.8°N, 108.3°E, Guangxi Zhuang Autonomous Region, China) at August 2008. The plant was identified by Dr. QR Liu (College of Life Sciences, Beijing Normal University, China), and a voucher specimen (CMH-Dafengai-Guangxi-2008-08) was deposited in the Department of Entomology, China Agricultural University. To obtain volatile essential oil, the air-dried samples were first ground to a powder then soaked in water at a ratio of 1 : 4 (w/v) for 1 h, prior to hydrodistillation using a round bottom container over a period of 6 h. The volatile essential oil was collected in a specific receiver, measured, dried over anhydrous sulfate, weighed, and stored in airtight containers.
## 2.2. Analysis of the Essential Oil
Components of the essential oil ofB. balsamifera leaves were separated and identified by gas chromatography-mass spectrometry (GC-MS) Agilent 6890N gas chromatography hooked to Agilent 5973N mass selective detector. They equipped with a flame ionization detector and capillary column with HP-5MS (30m×0.25mm×0.25μm). The GC settings were as follows: the initial oven temperature was held at 60°C for 1 min and ramped at 10°C min−1 to 180°C for 1 min, and then ramped at 20°C min−1 to 280°C for 15 min. The injector temperature was maintained at 270°C. The samples (1 μL) were injected neat, with a split ratio of 1 : 10. The carrier gas was helium at flow rate of 1.0 mL min−1. Spectra were scanned from 20 to 550 m/z at 2 scans s−1. Most constituents were identified by gas chromatography by comparison of their retention indices with those of the literature [18–22] or with those of authentic compounds available in our laboratories. The retention indices were determined in relation to a homologous series of n-alkanes (C8–C24) under the same operating conditions. Further identification was made by comparison of their mass spectra on both columns with those stored in NIST 05 and Wiley 275 libraries or with mass spectra from literature [29]. Component relative percentages were calculated based on GC peak areas without using correction factors.
## 2.3. Fumigant Toxicity [6]
The maize weevils were obtained from laboratory cultures maintained for the last 15 years in the dark in incubators at 29–30°C and 65–75% r.h. They were reared on whole wheat at 12–13% moisture content. The unsexed adults used in the experiments were 2–4 weeks posteclosion. A Whatman filter paper (CAT number 1001020, diameter 2.0 cm) was placed on the underside of the screw cap of a glass vial (diameter 2.5 cm, height 5.5 cm, volume 24 mL). Ten microliters of an appropriate concentration of compounds/oil (1.0%–40.0%, 5 concentrations) were added to the filter paper. The solvent was allowed to evaporate for 30 seconds before the cap was placed tightly on the glass vial (with 10 insects).n-Hexane was used as controls. The vials were upright and the Fluon (ICI America Inc) coating restricted the insects to the lower portion of the vial to prevent them from the treated filter paper. Six replicates were used in all treatments and controls, and they were incubated at 29–30°C and 65–75% RH for 24 hrs. The insects were then transferred to clean vials with some culture media and kept in an incubator for determination of end-point mortality, which was reached after one week. The insects were considered dead if appendages did not move when probed with a camel brush. The observed mortality data were corrected for control mortality using Abbott’s formula. Results from all replicates were subjected to probit analysis using the PriProbit Program V1.6.3 to determine LC50 and LC90 values [30].
## 3. Results and Discussion
### 3.1. Chemical Constituents of the Essential Oil
Hydrodistillation of dried leaves ofB. balsamifera yielded 0.88% essential oil (v/w), and the density of the essential oil was determined as 0.87%. The results of GC-MS of B. balsamifera essential oil are presented in Table 1. A total of 27 components were identified in the essential oil of B. balsamifera, accounting for 99.23% of the total oil (Table 1). The main components are 1,8-cineole (20.98%), borneol (11.99%), β-caryophyllene (10.38%), camphor (8.06%), 4-terpineol (6.49%), α-terpineol (5.91%), and caryophyllene oxide (5.35%). Monoterpenoids represented 12 of the 27 compounds, corresponding to 70.47% of the whole oil while 13 of the 27 constituents were sesquiterpenoids (27.42% of the crude essential oil). The chemical composition of B. balsamifera essential oil was different from that reported in other studies. For example, borneol (33.2%), caryophyllene (8.2%), ledol (7.1%), tetracyclo[6,3,2,0,(2.5).0(1,8) tridecan-9-ol, 4,4-dimethyl (5.2%), phytol (4.6%), caryophyllene oxide (4.1%), guaiol (3.4%), thujopsene-13 (4.4%), dimethoxydurene (3.6%), and γ-eudesmol (3.2%) were the dominant components in the essential oil of B. balsamifera leaves collected from Bangladesh (Chittagong, 22.20°N, 91.50°E) [20]. However, borneol (57.7%), caryophyllene (7.6%), and camphor (5.0%) were the three main components of the essential oil of B. balsamifera from Guizhou, China (Luodian Country, 25.43°N, 106.75°E) [21], while bornel (52.4%) and camphor (17.7%) were the two components of the essential oil from Yunnan, China (Puer City, 22.48°N, 100.58°E) [22]. There were great geographic variations in chemical composition of essential oils of B. balsamifera harvested in three provinces of Vietnam [18]. The major components of the essential oils were borneol (57.8%), caryophyllene (8.3%), δ-cadinol (8.0%), and caryophyllene oxide (3.1%) (Ha Giang, 22.80°N, 104.98°E); borneol (50.6%), camphor (18.7%), caryophyllene (10.1%), δ-cadinol (3.1%), patchoulene (3.0%), and veridiflorol (2.0%) (Hanoi, 21.02°N, 105.51°E); camphor (70.1%), caryophyllene (10.5%), borneol (5.7%), and carvacrol (5.7%) (Dak Lak, 22.80°N, 104.98°E). The above findings suggest that further studies on plant cultivation and essential oil standardization are necessary because chemical composition of the essential oil varies greatly with the plant population.Table 1
Chemical constituents of essential oil fromBlumea balsamifera leaves.
RI*
Compound
Formula
RA** (%)
998
Yomogi alcohol
C10H18O
2.58
1032
1,8-Cineole
C10H18O
20.98
1083
Artemisia alcohol
C10H18O
1.87
1114
β-Thujone
C10H16O
3.21
1126
ρ-Menth-2-en-1-ol
C10H18O
1.84
1138
2,2,4-Trimethyl-3-cyclohexene-1-carboxaldehyde
C10H16O
3.34
1143
Camphor
C10H16O
8.06
1168
Borneol
C10H18O
11.99
1179
4-Terpineol
C10H18O
6.49
1188
α-Terpineol
C10H18O
5.91
1205
Verbenone
C10H14O
1.84
1222
cis-Carveol
C10H16O
2.36
1356
Eugenol
C10H12O2
1.02
1374
Copaene
C15H24
0.28
1387
β-Cubebene
C15H24
0.43
1420
Caryophyllene
C15H24
10.38
1434
β-Gurjunene
C15H24
0.45
1452
cis-β-Farnesene
C15H24
0.37
1455
α-Caryophyllene
C15H24
1.50
1473
γ-Muurolene
C15H24
0.35
1480
Germacrene D
C15H24
1.10
1483
(+)-β-Selinene
C15H24
0.95
1523
δ-Cadinene
C15H24
0.53
1578
Spathulenol
C15H24O
2.64
1583
Caryophyllene oxide
C15H24O
5.35
1556
Guaia-3,9-diene
C15H24
3.09
2119
Phytol
C20H40O
0.32
Total
99.23
Monoterpenoids
70.47
Sesquiterpenoids
27.42
Others
1.34
*RI: retention index as determined on a HP-5MS column using the homologous series of n-hydrocarbons.
*
*RA: relative area (peak area relative to total peak area).
### 3.2. Fumigant Toxicity of Isolated Constituent Compounds against the Maize Weevils
1,8-Cineole (1) (LC50 = 2.96 mg/L air), 4-terpineol (4) (LC50 = 4.79 mg/L air), and α-terpineol (5) (LC50 = 7.45 mg/L air) showed stronger fumigant toxicity than the crude essential oil (LC50 = 10.71 mg/L air) against S. zeamais (Table 2). It indicates that fumigant toxicity of the essential oil may be attributed to the three constituent compounds. In the previous studies, 1,8-cineole was found to exhibit fumigant toxicity against red flour beetles, Tribolium castaneum adult with LC50 = 41 μL/L air [31], 15.3 μL/L air [32], and 1.52 mg/L air [33]. It also possesses fumigant toxicity against several other stored product insects and cockroaches as well as mosquitoes, for example, the rice weevil (S. oryzae) (LC50 = 22.8 μL/L air [32]), the lesser grain borer (Rhyzopertha dominica) (LC50 = 9.5 μL/L air [32]). However, compared with the current used fumigant (MeBr, LC50 = 0.67 mg/L air), the three compounds and the crude essential oil exhibited only 4–16 times less toxic to the maize weevils. The three constituent compounds and the crude essential oil were more toxic to S. zeamais than another two isolated compounds, camphor (2) (LC50 = 21.67 mg/L air) and borneol (3) (LC50 = 29.64 mg/L air) (Figure 2). Compared with the other essential oils in the previous studies that were tested using a similar bioassay, B. balsamifera essential oil exhibited stronger fumigant toxicity against S. zeamais adults, for example, essential oils of Schizonepeta multifida [34],Murraya exotica [35], and several essential oils from Genus Artemisia [36–38]. Moreover, the two other active constituent compounds, 4-terpineol and α-terpineol, have been found to possess strong fumigant toxicity against several grain storage insects, such as S. granarius, S. oryzae, T. castaneum, T. confusum, and R. dominica [31, 32, 39–43]. The two other active constituents, camphor and borneol, were also demonstrated fumigant toxicity against grain storage insects [31, 41, 44, 45].Table 2
Fumigant toxicity ofBlumea balsamifera essential oil and its constituent compounds against Sitophilus zeamais adults.
Treatments
Conc.
Mortality
LC50 (mg/L air)
LC
9
0 (mg/L air)
Slope ± SE
Chi square (χ2)
(%)
(%±SE)
(95% FL)
(95% FL)
20.00
98.0 ± 1.22
14.29
72.0 ± 3.43
Borneol
10.20
48.0 ± 3.41
29.64 (27.39–31.98)
40.11 (37.67–43.24)
2.37 ± 0.32
15.34
7.29
34.0 ± 2.34
5.21
8.0 ± 1.22
20.00
88.0 ± 3.43
13.33
65.0 ± 2.45
Camphor
8.89
47.0 ± 1.43
21.67 (19.74–23.25)
43.54 (39.76–47.32)
2.18 ± 0.25
8.39
5.92
36.0 ± 1.32
3.95
10.0 ± 2.32
3.00
95.0 ± 1.34
1.50
78.0 ± 3.43
1,8-Cineole
0.75
56.0 ± 2.45
2.96 (2.76–3.21)
5.46 (4.78–5.93)
1.72 ± 0.15
9.48
0.38
35.0 ± 1.56
0.19
12.5 ± 0.78
10.00
95.0 ± 2.34
5.00
84.0 ± 1.68
α-Terpineol
2.50
62.0 ± 1.87
7.45 (6.51–8.32)
12.18 (10.79–13.23)
2.13 ± 0.21
11.79
1.25
38.0 ± 1.54
0.66
13.0 ± 0.89
8.00
94.0 ± 3.43
4.00
72.0 ± 2.43
4-Terpineol
2.00
48.0 ± 1.45
4.79 (4.31–5.22)
8.37 (7.67–9.27)
2.07 ± 0.19
3.14
1.00
32.0 ± 1.67
0.50
7.0 ± 0.56
MeBr*
—
—
0.67
—
—
—
15.0
98.0 ± 2.54
7.50
86.0 ± 1.95
Crude oil
3.75
65.0 ± 1.65
10.71 (9.76–11.75)
18.82 (17.13–20.67)
1.77 ± 0.13
5.28
1.88
42.0 ± 1.44
0.94
16.0 ± 0.99
*MeBr: Methyl bromide; values from Liu and Ho [6].Table 3
1H and 13C values (δ (ppm)) of the isolated compounds.
Number
1,8-Cineole
Camphor
Borneol
4-Terpineol
α-Terpineol
1H
13C
1H
13C
1H
13C
1H
13C
1H
13C
1
—
72.7
—
220.0
3.15
76.1
—
133.9
—
133.9
2
1.52
37.3
2.14; 1.89
40.4
1.67; 1.42
35.8
5.37
123.3
5.37
123.3
3
1.40
24.2
1.99
34.4
1.42
45.2
2.19; 1.94
40.8
2.04; 1.79
24.1
4
1.74
39.6
1.60; 1.35
28.4
1.52; 1.27
23.6
—
71.7
1.71
46.5
5
1.52; 1.27
24.2
1.84; 1.59
31.5
1.49; 1.24
30.0
1.88; 1.63
30.3
1.74; 1.49
19.1
6
1.65; 1.40
37.3
—
61.6
—
52.7
2.01; 1.91
24.7
2.01; 1.91
31.2
7
1.31
25.4
1.26
15.6
1.16
13.3
1.71
23.1
17.1
23.1
8
—
76.8
—
39.8
—
50.4
1.90
37.6
—
73.3
9
1.26
25.4
1.11
21.8
1.11
19.8
1.01
14.9
1.26
27.7
10
1.26
25.4
1.11
21.8
1.11
19.8
1.01
14.9
1.26
27.7Dose response curves ofSitophilus zeamais treated with the essential oil and its constituent compounds.
(a)
(b)
(c)
(d)
(e)
(f)Considering the currently used fumigants are synthetic insecticides, fumigant activity of the crude essential oil ofB. balsamifera leaves and the three isolated active compounds are quite promising and they show potential to be developed as possible natural fumigants for control of stored product insects with low toxicity to humans. Although dried leaves of B. balsamifera were used as a common Chinese medicinal herb [7], there are no toxicity data for this herb and the three isolated compounds and available on human consumption. For the practical use of the three compounds and crude essential oil as novel botanical insecticides, further studies are necessary on the safety of these materials to human, on phytotoxicity to crop seeds, and on the development of formulations to improve efficacy and stability, and to cut cost as well. The isolated three active compounds exhibited fumigant toxicity against several grain storage insects [31, 32, 39–43]. However, little has been done on mechanisms of action of these three monoterpenes. In addition, further testing is necessary to evaluate the spectrum of fumigant activity against other stored-product insects (as well as other life stages of these stored-product insects, especially eggs).
## 3.1. Chemical Constituents of the Essential Oil
Hydrodistillation of dried leaves ofB. balsamifera yielded 0.88% essential oil (v/w), and the density of the essential oil was determined as 0.87%. The results of GC-MS of B. balsamifera essential oil are presented in Table 1. A total of 27 components were identified in the essential oil of B. balsamifera, accounting for 99.23% of the total oil (Table 1). The main components are 1,8-cineole (20.98%), borneol (11.99%), β-caryophyllene (10.38%), camphor (8.06%), 4-terpineol (6.49%), α-terpineol (5.91%), and caryophyllene oxide (5.35%). Monoterpenoids represented 12 of the 27 compounds, corresponding to 70.47% of the whole oil while 13 of the 27 constituents were sesquiterpenoids (27.42% of the crude essential oil). The chemical composition of B. balsamifera essential oil was different from that reported in other studies. For example, borneol (33.2%), caryophyllene (8.2%), ledol (7.1%), tetracyclo[6,3,2,0,(2.5).0(1,8) tridecan-9-ol, 4,4-dimethyl (5.2%), phytol (4.6%), caryophyllene oxide (4.1%), guaiol (3.4%), thujopsene-13 (4.4%), dimethoxydurene (3.6%), and γ-eudesmol (3.2%) were the dominant components in the essential oil of B. balsamifera leaves collected from Bangladesh (Chittagong, 22.20°N, 91.50°E) [20]. However, borneol (57.7%), caryophyllene (7.6%), and camphor (5.0%) were the three main components of the essential oil of B. balsamifera from Guizhou, China (Luodian Country, 25.43°N, 106.75°E) [21], while bornel (52.4%) and camphor (17.7%) were the two components of the essential oil from Yunnan, China (Puer City, 22.48°N, 100.58°E) [22]. There were great geographic variations in chemical composition of essential oils of B. balsamifera harvested in three provinces of Vietnam [18]. The major components of the essential oils were borneol (57.8%), caryophyllene (8.3%), δ-cadinol (8.0%), and caryophyllene oxide (3.1%) (Ha Giang, 22.80°N, 104.98°E); borneol (50.6%), camphor (18.7%), caryophyllene (10.1%), δ-cadinol (3.1%), patchoulene (3.0%), and veridiflorol (2.0%) (Hanoi, 21.02°N, 105.51°E); camphor (70.1%), caryophyllene (10.5%), borneol (5.7%), and carvacrol (5.7%) (Dak Lak, 22.80°N, 104.98°E). The above findings suggest that further studies on plant cultivation and essential oil standardization are necessary because chemical composition of the essential oil varies greatly with the plant population.Table 1
Chemical constituents of essential oil fromBlumea balsamifera leaves.
RI*
Compound
Formula
RA** (%)
998
Yomogi alcohol
C10H18O
2.58
1032
1,8-Cineole
C10H18O
20.98
1083
Artemisia alcohol
C10H18O
1.87
1114
β-Thujone
C10H16O
3.21
1126
ρ-Menth-2-en-1-ol
C10H18O
1.84
1138
2,2,4-Trimethyl-3-cyclohexene-1-carboxaldehyde
C10H16O
3.34
1143
Camphor
C10H16O
8.06
1168
Borneol
C10H18O
11.99
1179
4-Terpineol
C10H18O
6.49
1188
α-Terpineol
C10H18O
5.91
1205
Verbenone
C10H14O
1.84
1222
cis-Carveol
C10H16O
2.36
1356
Eugenol
C10H12O2
1.02
1374
Copaene
C15H24
0.28
1387
β-Cubebene
C15H24
0.43
1420
Caryophyllene
C15H24
10.38
1434
β-Gurjunene
C15H24
0.45
1452
cis-β-Farnesene
C15H24
0.37
1455
α-Caryophyllene
C15H24
1.50
1473
γ-Muurolene
C15H24
0.35
1480
Germacrene D
C15H24
1.10
1483
(+)-β-Selinene
C15H24
0.95
1523
δ-Cadinene
C15H24
0.53
1578
Spathulenol
C15H24O
2.64
1583
Caryophyllene oxide
C15H24O
5.35
1556
Guaia-3,9-diene
C15H24
3.09
2119
Phytol
C20H40O
0.32
Total
99.23
Monoterpenoids
70.47
Sesquiterpenoids
27.42
Others
1.34
*RI: retention index as determined on a HP-5MS column using the homologous series of n-hydrocarbons.
*
*RA: relative area (peak area relative to total peak area).
## 3.2. Fumigant Toxicity of Isolated Constituent Compounds against the Maize Weevils
1,8-Cineole (1) (LC50 = 2.96 mg/L air), 4-terpineol (4) (LC50 = 4.79 mg/L air), and α-terpineol (5) (LC50 = 7.45 mg/L air) showed stronger fumigant toxicity than the crude essential oil (LC50 = 10.71 mg/L air) against S. zeamais (Table 2). It indicates that fumigant toxicity of the essential oil may be attributed to the three constituent compounds. In the previous studies, 1,8-cineole was found to exhibit fumigant toxicity against red flour beetles, Tribolium castaneum adult with LC50 = 41 μL/L air [31], 15.3 μL/L air [32], and 1.52 mg/L air [33]. It also possesses fumigant toxicity against several other stored product insects and cockroaches as well as mosquitoes, for example, the rice weevil (S. oryzae) (LC50 = 22.8 μL/L air [32]), the lesser grain borer (Rhyzopertha dominica) (LC50 = 9.5 μL/L air [32]). However, compared with the current used fumigant (MeBr, LC50 = 0.67 mg/L air), the three compounds and the crude essential oil exhibited only 4–16 times less toxic to the maize weevils. The three constituent compounds and the crude essential oil were more toxic to S. zeamais than another two isolated compounds, camphor (2) (LC50 = 21.67 mg/L air) and borneol (3) (LC50 = 29.64 mg/L air) (Figure 2). Compared with the other essential oils in the previous studies that were tested using a similar bioassay, B. balsamifera essential oil exhibited stronger fumigant toxicity against S. zeamais adults, for example, essential oils of Schizonepeta multifida [34],Murraya exotica [35], and several essential oils from Genus Artemisia [36–38]. Moreover, the two other active constituent compounds, 4-terpineol and α-terpineol, have been found to possess strong fumigant toxicity against several grain storage insects, such as S. granarius, S. oryzae, T. castaneum, T. confusum, and R. dominica [31, 32, 39–43]. The two other active constituents, camphor and borneol, were also demonstrated fumigant toxicity against grain storage insects [31, 41, 44, 45].Table 2
Fumigant toxicity ofBlumea balsamifera essential oil and its constituent compounds against Sitophilus zeamais adults.
Treatments
Conc.
Mortality
LC50 (mg/L air)
LC
9
0 (mg/L air)
Slope ± SE
Chi square (χ2)
(%)
(%±SE)
(95% FL)
(95% FL)
20.00
98.0 ± 1.22
14.29
72.0 ± 3.43
Borneol
10.20
48.0 ± 3.41
29.64 (27.39–31.98)
40.11 (37.67–43.24)
2.37 ± 0.32
15.34
7.29
34.0 ± 2.34
5.21
8.0 ± 1.22
20.00
88.0 ± 3.43
13.33
65.0 ± 2.45
Camphor
8.89
47.0 ± 1.43
21.67 (19.74–23.25)
43.54 (39.76–47.32)
2.18 ± 0.25
8.39
5.92
36.0 ± 1.32
3.95
10.0 ± 2.32
3.00
95.0 ± 1.34
1.50
78.0 ± 3.43
1,8-Cineole
0.75
56.0 ± 2.45
2.96 (2.76–3.21)
5.46 (4.78–5.93)
1.72 ± 0.15
9.48
0.38
35.0 ± 1.56
0.19
12.5 ± 0.78
10.00
95.0 ± 2.34
5.00
84.0 ± 1.68
α-Terpineol
2.50
62.0 ± 1.87
7.45 (6.51–8.32)
12.18 (10.79–13.23)
2.13 ± 0.21
11.79
1.25
38.0 ± 1.54
0.66
13.0 ± 0.89
8.00
94.0 ± 3.43
4.00
72.0 ± 2.43
4-Terpineol
2.00
48.0 ± 1.45
4.79 (4.31–5.22)
8.37 (7.67–9.27)
2.07 ± 0.19
3.14
1.00
32.0 ± 1.67
0.50
7.0 ± 0.56
MeBr*
—
—
0.67
—
—
—
15.0
98.0 ± 2.54
7.50
86.0 ± 1.95
Crude oil
3.75
65.0 ± 1.65
10.71 (9.76–11.75)
18.82 (17.13–20.67)
1.77 ± 0.13
5.28
1.88
42.0 ± 1.44
0.94
16.0 ± 0.99
*MeBr: Methyl bromide; values from Liu and Ho [6].Table 3
1H and 13C values (δ (ppm)) of the isolated compounds.
Number
1,8-Cineole
Camphor
Borneol
4-Terpineol
α-Terpineol
1H
13C
1H
13C
1H
13C
1H
13C
1H
13C
1
—
72.7
—
220.0
3.15
76.1
—
133.9
—
133.9
2
1.52
37.3
2.14; 1.89
40.4
1.67; 1.42
35.8
5.37
123.3
5.37
123.3
3
1.40
24.2
1.99
34.4
1.42
45.2
2.19; 1.94
40.8
2.04; 1.79
24.1
4
1.74
39.6
1.60; 1.35
28.4
1.52; 1.27
23.6
—
71.7
1.71
46.5
5
1.52; 1.27
24.2
1.84; 1.59
31.5
1.49; 1.24
30.0
1.88; 1.63
30.3
1.74; 1.49
19.1
6
1.65; 1.40
37.3
—
61.6
—
52.7
2.01; 1.91
24.7
2.01; 1.91
31.2
7
1.31
25.4
1.26
15.6
1.16
13.3
1.71
23.1
17.1
23.1
8
—
76.8
—
39.8
—
50.4
1.90
37.6
—
73.3
9
1.26
25.4
1.11
21.8
1.11
19.8
1.01
14.9
1.26
27.7
10
1.26
25.4
1.11
21.8
1.11
19.8
1.01
14.9
1.26
27.7Dose response curves ofSitophilus zeamais treated with the essential oil and its constituent compounds.
(a)
(b)
(c)
(d)
(e)
(f)Considering the currently used fumigants are synthetic insecticides, fumigant activity of the crude essential oil ofB. balsamifera leaves and the three isolated active compounds are quite promising and they show potential to be developed as possible natural fumigants for control of stored product insects with low toxicity to humans. Although dried leaves of B. balsamifera were used as a common Chinese medicinal herb [7], there are no toxicity data for this herb and the three isolated compounds and available on human consumption. For the practical use of the three compounds and crude essential oil as novel botanical insecticides, further studies are necessary on the safety of these materials to human, on phytotoxicity to crop seeds, and on the development of formulations to improve efficacy and stability, and to cut cost as well. The isolated three active compounds exhibited fumigant toxicity against several grain storage insects [31, 32, 39–43]. However, little has been done on mechanisms of action of these three monoterpenes. In addition, further testing is necessary to evaluate the spectrum of fumigant activity against other stored-product insects (as well as other life stages of these stored-product insects, especially eggs).
---
*Source: 289874-2012-08-09.xml* | 2013 |
# Management of Fetal Growth Arrest in One of Dichorionic Twins: Three Cases and a Literature Review
**Authors:** Shoji Kaku; Fuminori Kimura; Takashi Murakami
**Journal:** Obstetrics and Gynecology International
(2015)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2015/289875
---
## Abstract
Progressive fetal growth restriction (FGR) is often an indication for delivery. In dichorionic diamniotic (DD) twin pregnancy with growth restriction only affecting one fetus (selective fetal growth restriction: sFGR), the normal twin is also delivered prematurely. There is still not enough evidence about the optimal timing of delivery for DD twins with sFGR in relation to discordance and gestational age. We report three sets of DD twins with sFGR (almost complete growth arrest affecting one fetus for ≥2 weeks) before 30 weeks of gestation. The interval from growth arrest to delivery was 21–24 days and the discordance was 33.7–49.8%. A large-scale study showed no difference of overall mortality or the long-term outcome between immediate and delayed delivery for FGR, while many studies have identified a risk of developmental delay following delivery of the normal growth fetus before 32 weeks. Therefore, delivery of DD twins with sFGR should be delayed if the condition of the sFGR fetus permits in order to increase the gestational age of the normal growth fetus.
---
## Body
## 1. Introduction
When fetal growth restriction (FGR) is progressive, with no increase of the estimated fetal body weight (EFW) and deterioration of Doppler flow parameters measured at the umbilical artery and ductus venosus, delivery is required. However, there is little consensus about the optimal timing of delivery [1]. Early delivery carries the risks associated with prematurity, but delay may increase hypoxic damage [2]. In monochorionic twins, one fetus may show growth restriction while the growth of the other fetus is normal. This is called selective fetal growth restriction (sFGR) and its frequency is 10–15%. However, there have been no reports about the management of dichorionic diamniotic (DD) twin pregnancy with sFGR. Over the past few decades, the incidence of twin pregnancies has increased by nearly 70% because of the widespread use of assisted reproductive technology [3], which means that DD twin pregnancies have also been increasing. Inde et al. reported that 32.9% of patients who had DD twins received in vitro fertilization [4]. Accordingly, we reviewed our cases and the literature to investigate the management and timing of delivery in DD twins with sFGR and almost complete growth restriction.
## 2. Case Reports
We searched the clinical records of our hospital from January 2009 to December 2013 for DD twins with sFGR diagnosed before 30 weeks of gestation. Twins were eligible when the EFW of one twin was below the 10th percentile and there was almost complete growth restriction for more than two weeks, while the EFW of the other twin was within the normal range based on a weight nomogram. We excluded cases where the FGR fetus had an abnormal karyotype. Three twin pregnancies were identified that met these criteria. For these fetuses, we examined the period between the diagnosis of growth restriction and delivery in relation to the prognosis of both twins. In all pregnancies, gestational age was confirmed and chorionicity and amnionicity were evaluated prior to 12 weeks. Gestational age was assigned by measurement of crown-rump length. The EFW of the twin with sIUGR was determined by ultrasound once or twice a week with a Voluson E8 (GE Healthcare, Milwaukee, WI).For management of sFGR in DD twins, the mother was hospitalized. CTG monitoring was performed every day and the EFW was assessed by ultrasound, with both EFW and Doppler examination being done twice a week. If late deceleration or reduced short-term variation was seen or there was an abnormal UA pulsatility index (more than 2 SD above the normal reference mean) or absence of end-diastolic flow in the UA, we considered delivery if the gestational age was more than 32 weeks. If the gestational age was less than 32 weeks, we increased CTG monitoring to two or three times a day and performed daily ultrasound examination. If late deceleration, absence of short-term variation, or reverse end-diastolic flow (RED) was detected, we considered delivery.Details of the three cases of sFGR are displayed in Table1. The gestational age was 27–29 weeks at the detection of almost complete growth restriction persisting for ≥2 weeks, while birth weight discordance was 33.7–49.8% (Table 1). Investigation of the cause of the growth restriction revealed a difference of placental area between the FGR twin and normal twin in case 1 (Figure 1(a)), but there was no significant difference in cases 2 and 3 (Figures 1(b) and 1(c)). In case 2, the FGR fetus showed heterotaxia, but the karyotype was normal. In case 3, the cause of growth restriction was not identified despite prenatal and postnatal investigation. The method of delivery was cesarean section in all three cases. Although we aimed for delivery after 32 weeks of gestation, this was only achieved in case 1. In case 2, RED in the umbilical artery was found at 30 weeks of gestation, and cesarean section was performed three days after the appearance RED. In case 3, labor started at 29 weeks in spite of tocolysis. Accordingly, cesarean section was performed at 29–32 weeks of gestation, and the interval from detection of growth arrest to cesarean section was 21–24 days (median: 22.7 days) (Table 1). The birth weight of the FGR twin was 778–884 g and that of the normal twin was 1174–1760 g (Table 1). After follow-up of the sFGR infants for one to four years since birth, no major abnormalities have been found other than heterotaxia in case 2. Among the normal growth infants, cerebral hemorrhage was detected in the normal weight twin of case 2 at 4 days after birth and this child requires ongoing treatment.Table 1
Case number
Age
G
P
Gestational age at detectionof growth restriction
Gestational age at delivery
Reason for delivery
Period of growthrestriction (days)
Birth weight (g)
Sex
Major sequelae
1
38
0
0
29 w 2 d
32 w 4 d
Planning delivery
24
8841760
FM
——
2
30
0
0
27 w 0 d
30 w 1 d
RED of UA
23
8381636
MM
—Cerebral hemorrhage
3
29
0
0
27 w 0 d
29 w 6 d
Onset of labor
21
7781174
FM
——
G: gravidity, P: parity, RED: reverse of end-diastolic flow, UA: umbilical artery, F: female, and M: male.Figure 1
Placentas of 3 cases. (a) Placenta of case 1. (b) Placenta of case 2. (c) Placenta of case 3. (a) There is an obvious difference of placental area between the FGR fetus and the normal fetus. (b, c) There is no marked difference of placental area between the FGR fetus and the normal fetus.
(a)
(b)
(c)
## 3. Discussion
When sFGR occurs in DD twins, our objective is to achieve the best outcome for both fetuses. The timing of delivery is generally the major issue in severe FGR and policies about delivery vary widely [5, 6]. A large-scale prospective study showed that the developmental quotient was significantly lower at a corrected age of 2 years after premature delivery of normal growth fetuses between 22 and 32 weeks of gestation [7]. There is no consensus about the management of sFGR in DD twins, including the timing of delivery. Accordingly, we reviewed published reports on the management of sFGR and investigated the timing of delivery in relation to the severity of discordance to determine whether discordance influenced the normal twin because an adverse event occurred in one of our normal growth twins. We also investigated the timing of delivery in relation to the umbilical artery Doppler flow parameters in the sFGR fetus because RED was found in one of our cases.With regard to the timing of delivery in relation to the severity of discordance, we found that discordance exceeded 30% in all 3 of our DD twins. In most studies, the cut-off value is 15%–25%, and it is reported that the risk of morbidity and mortality increases if discordance exceeds that value [8–10]. Unfortunately, there have been no reports focusing on the relation between discordance and prognosis of DD twins, but some studies have investigated the influence of gender. In same sex twins, Demissie et al. reported that greater discordance is associated with an increased risk of intrauterine death for both smaller and larger twin, while intrauterine death and the prognosis of the larger twin are unrelated to discordance when the twins are of different sexes [11]. The same sex twins in these reports included both DD twins and monochorionic twins, while the twins of different sexes would only be DD twins. However, the authors did not distinguish between DD twins of the same and DD twins of different sexes, and the chorionicity and amnionicity are also unclear because the studies were based on twin birth data from the United States [11, 12]. However, we considered that the data for different sex twins corresponded to findings for DD twins.A few prospective multicenter studies have addressed the timing of delivery based on Doppler flow parameters in the umbilical artery of the FGR fetus. The Growth Restriction Intervention Trial (GRIT) investigated the timing of delivery for FGR [13]. Pregnant women between 24 and 36 weeks of gestation with FGR were randomly assigned to immediate delivery (n
=
296) or delayed (n
=
291) delivery if the obstetrician was uncertain about when the FGR fetus should be delivered based on UA Doppler parameters. As a result, there was no difference of overall mortality between the two groups. In addition, 2-year and 6-year follow-up studies showed that there were no significant differences between the two groups with regard to death or disability rates [14, 15]. Although the GRIT study cannot provide us with standard criteria for determining the timing of delivery, the lack of a difference in overall mortality and long-term outcomes of the FGR fetus between immediate and delayed delivery suggests that it may be important for parents or obstetricians to consider prolonging the time in utero for the normal twin of DD twins with sFGR, even for a short period.When we reassessed our 3 cases based on the literature review, we considered that the timing of delivery should not be decided from the discordance (even though it exceeded 30% in all of our cases), because there is no evidence of a relation between the cut-off value for discordance and the risk of morbidity or mortality in dichorionic twins. Although we aimed for delivery after a gestational age of 32 weeks, delivery was earlier than 32 weeks in 2 cases because of RED and spontaneous onset of labor, respectively, with cerebral hemorrhage occurring in one normal growth twin after premature delivery. In conclusion, there is still not enough evidence about the optimal timing of delivery for DD twins with sFGR in relation to discordance and gestational age, but data from the GRIT study suggest that delivery should be delayed if the condition of the sFGR fetus permits in order to increase the gestational age of the normal growth fetus.
---
*Source: 289875-2015-12-29.xml* | 289875-2015-12-29_289875-2015-12-29.md | 11,331 | Management of Fetal Growth Arrest in One of Dichorionic Twins: Three Cases and a Literature Review | Shoji Kaku; Fuminori Kimura; Takashi Murakami | Obstetrics and Gynecology International
(2015) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2015/289875 | 289875-2015-12-29.xml | ---
## Abstract
Progressive fetal growth restriction (FGR) is often an indication for delivery. In dichorionic diamniotic (DD) twin pregnancy with growth restriction only affecting one fetus (selective fetal growth restriction: sFGR), the normal twin is also delivered prematurely. There is still not enough evidence about the optimal timing of delivery for DD twins with sFGR in relation to discordance and gestational age. We report three sets of DD twins with sFGR (almost complete growth arrest affecting one fetus for ≥2 weeks) before 30 weeks of gestation. The interval from growth arrest to delivery was 21–24 days and the discordance was 33.7–49.8%. A large-scale study showed no difference of overall mortality or the long-term outcome between immediate and delayed delivery for FGR, while many studies have identified a risk of developmental delay following delivery of the normal growth fetus before 32 weeks. Therefore, delivery of DD twins with sFGR should be delayed if the condition of the sFGR fetus permits in order to increase the gestational age of the normal growth fetus.
---
## Body
## 1. Introduction
When fetal growth restriction (FGR) is progressive, with no increase of the estimated fetal body weight (EFW) and deterioration of Doppler flow parameters measured at the umbilical artery and ductus venosus, delivery is required. However, there is little consensus about the optimal timing of delivery [1]. Early delivery carries the risks associated with prematurity, but delay may increase hypoxic damage [2]. In monochorionic twins, one fetus may show growth restriction while the growth of the other fetus is normal. This is called selective fetal growth restriction (sFGR) and its frequency is 10–15%. However, there have been no reports about the management of dichorionic diamniotic (DD) twin pregnancy with sFGR. Over the past few decades, the incidence of twin pregnancies has increased by nearly 70% because of the widespread use of assisted reproductive technology [3], which means that DD twin pregnancies have also been increasing. Inde et al. reported that 32.9% of patients who had DD twins received in vitro fertilization [4]. Accordingly, we reviewed our cases and the literature to investigate the management and timing of delivery in DD twins with sFGR and almost complete growth restriction.
## 2. Case Reports
We searched the clinical records of our hospital from January 2009 to December 2013 for DD twins with sFGR diagnosed before 30 weeks of gestation. Twins were eligible when the EFW of one twin was below the 10th percentile and there was almost complete growth restriction for more than two weeks, while the EFW of the other twin was within the normal range based on a weight nomogram. We excluded cases where the FGR fetus had an abnormal karyotype. Three twin pregnancies were identified that met these criteria. For these fetuses, we examined the period between the diagnosis of growth restriction and delivery in relation to the prognosis of both twins. In all pregnancies, gestational age was confirmed and chorionicity and amnionicity were evaluated prior to 12 weeks. Gestational age was assigned by measurement of crown-rump length. The EFW of the twin with sIUGR was determined by ultrasound once or twice a week with a Voluson E8 (GE Healthcare, Milwaukee, WI).For management of sFGR in DD twins, the mother was hospitalized. CTG monitoring was performed every day and the EFW was assessed by ultrasound, with both EFW and Doppler examination being done twice a week. If late deceleration or reduced short-term variation was seen or there was an abnormal UA pulsatility index (more than 2 SD above the normal reference mean) or absence of end-diastolic flow in the UA, we considered delivery if the gestational age was more than 32 weeks. If the gestational age was less than 32 weeks, we increased CTG monitoring to two or three times a day and performed daily ultrasound examination. If late deceleration, absence of short-term variation, or reverse end-diastolic flow (RED) was detected, we considered delivery.Details of the three cases of sFGR are displayed in Table1. The gestational age was 27–29 weeks at the detection of almost complete growth restriction persisting for ≥2 weeks, while birth weight discordance was 33.7–49.8% (Table 1). Investigation of the cause of the growth restriction revealed a difference of placental area between the FGR twin and normal twin in case 1 (Figure 1(a)), but there was no significant difference in cases 2 and 3 (Figures 1(b) and 1(c)). In case 2, the FGR fetus showed heterotaxia, but the karyotype was normal. In case 3, the cause of growth restriction was not identified despite prenatal and postnatal investigation. The method of delivery was cesarean section in all three cases. Although we aimed for delivery after 32 weeks of gestation, this was only achieved in case 1. In case 2, RED in the umbilical artery was found at 30 weeks of gestation, and cesarean section was performed three days after the appearance RED. In case 3, labor started at 29 weeks in spite of tocolysis. Accordingly, cesarean section was performed at 29–32 weeks of gestation, and the interval from detection of growth arrest to cesarean section was 21–24 days (median: 22.7 days) (Table 1). The birth weight of the FGR twin was 778–884 g and that of the normal twin was 1174–1760 g (Table 1). After follow-up of the sFGR infants for one to four years since birth, no major abnormalities have been found other than heterotaxia in case 2. Among the normal growth infants, cerebral hemorrhage was detected in the normal weight twin of case 2 at 4 days after birth and this child requires ongoing treatment.Table 1
Case number
Age
G
P
Gestational age at detectionof growth restriction
Gestational age at delivery
Reason for delivery
Period of growthrestriction (days)
Birth weight (g)
Sex
Major sequelae
1
38
0
0
29 w 2 d
32 w 4 d
Planning delivery
24
8841760
FM
——
2
30
0
0
27 w 0 d
30 w 1 d
RED of UA
23
8381636
MM
—Cerebral hemorrhage
3
29
0
0
27 w 0 d
29 w 6 d
Onset of labor
21
7781174
FM
——
G: gravidity, P: parity, RED: reverse of end-diastolic flow, UA: umbilical artery, F: female, and M: male.Figure 1
Placentas of 3 cases. (a) Placenta of case 1. (b) Placenta of case 2. (c) Placenta of case 3. (a) There is an obvious difference of placental area between the FGR fetus and the normal fetus. (b, c) There is no marked difference of placental area between the FGR fetus and the normal fetus.
(a)
(b)
(c)
## 3. Discussion
When sFGR occurs in DD twins, our objective is to achieve the best outcome for both fetuses. The timing of delivery is generally the major issue in severe FGR and policies about delivery vary widely [5, 6]. A large-scale prospective study showed that the developmental quotient was significantly lower at a corrected age of 2 years after premature delivery of normal growth fetuses between 22 and 32 weeks of gestation [7]. There is no consensus about the management of sFGR in DD twins, including the timing of delivery. Accordingly, we reviewed published reports on the management of sFGR and investigated the timing of delivery in relation to the severity of discordance to determine whether discordance influenced the normal twin because an adverse event occurred in one of our normal growth twins. We also investigated the timing of delivery in relation to the umbilical artery Doppler flow parameters in the sFGR fetus because RED was found in one of our cases.With regard to the timing of delivery in relation to the severity of discordance, we found that discordance exceeded 30% in all 3 of our DD twins. In most studies, the cut-off value is 15%–25%, and it is reported that the risk of morbidity and mortality increases if discordance exceeds that value [8–10]. Unfortunately, there have been no reports focusing on the relation between discordance and prognosis of DD twins, but some studies have investigated the influence of gender. In same sex twins, Demissie et al. reported that greater discordance is associated with an increased risk of intrauterine death for both smaller and larger twin, while intrauterine death and the prognosis of the larger twin are unrelated to discordance when the twins are of different sexes [11]. The same sex twins in these reports included both DD twins and monochorionic twins, while the twins of different sexes would only be DD twins. However, the authors did not distinguish between DD twins of the same and DD twins of different sexes, and the chorionicity and amnionicity are also unclear because the studies were based on twin birth data from the United States [11, 12]. However, we considered that the data for different sex twins corresponded to findings for DD twins.A few prospective multicenter studies have addressed the timing of delivery based on Doppler flow parameters in the umbilical artery of the FGR fetus. The Growth Restriction Intervention Trial (GRIT) investigated the timing of delivery for FGR [13]. Pregnant women between 24 and 36 weeks of gestation with FGR were randomly assigned to immediate delivery (n
=
296) or delayed (n
=
291) delivery if the obstetrician was uncertain about when the FGR fetus should be delivered based on UA Doppler parameters. As a result, there was no difference of overall mortality between the two groups. In addition, 2-year and 6-year follow-up studies showed that there were no significant differences between the two groups with regard to death or disability rates [14, 15]. Although the GRIT study cannot provide us with standard criteria for determining the timing of delivery, the lack of a difference in overall mortality and long-term outcomes of the FGR fetus between immediate and delayed delivery suggests that it may be important for parents or obstetricians to consider prolonging the time in utero for the normal twin of DD twins with sFGR, even for a short period.When we reassessed our 3 cases based on the literature review, we considered that the timing of delivery should not be decided from the discordance (even though it exceeded 30% in all of our cases), because there is no evidence of a relation between the cut-off value for discordance and the risk of morbidity or mortality in dichorionic twins. Although we aimed for delivery after a gestational age of 32 weeks, delivery was earlier than 32 weeks in 2 cases because of RED and spontaneous onset of labor, respectively, with cerebral hemorrhage occurring in one normal growth twin after premature delivery. In conclusion, there is still not enough evidence about the optimal timing of delivery for DD twins with sFGR in relation to discordance and gestational age, but data from the GRIT study suggest that delivery should be delayed if the condition of the sFGR fetus permits in order to increase the gestational age of the normal growth fetus.
---
*Source: 289875-2015-12-29.xml* | 2015 |
# Nitroglycerine Induced Acute Myocardial Infarction in a Patient with Myocardial Bridging
**Authors:** Dragana Rujic; Mette Lundgren Nielsen; Karsten Tange Veien; Manan Pareek
**Journal:** Case Reports in Cardiology
(2014)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2014/289879
---
## Abstract
Muscle overlying an intramyocardial segment of a coronary artery is termed a myocardial bridge. The intramyocardial segment, the tunneled artery, is compressed during systole. The condition is generally benign but may occasionally cause myocardial ischemia, infarction, arrhythmia, or sudden cardiac death. We present a case regarding a 52-year-old man with exercise-induced angina who was diagnosed with a myocardial bridge overlying the left anterior descending artery. He was initially treated with beta-blockers and later received coronary bypass graft surgery.
---
## Body
## 1. Introduction
The major coronary arteries are normally distributed epicardially, that is, on the surface of the myocardium. Occasionally, these vessels have a segmental intramyocardial course. During systole, this segment is compressed either partially or completely. Muscle overlying the intramyocardial segment is called a myocardial bridge, and the artery coursing within the myocardium is termed a tunneled artery [1–3].
## 2. Case Presentation
A 52-year-old man with a long-standing history of smoking and a positive family history of coronary artery disease (CAD) had undergone multiple admissions and investigations in several different hospitals during the last 13 years due to exercise-induced chest pain, shortness of breath, and palpitations.The electrocardiogram (ECG) showed sinus rhythm with complete right bundle branch block. The concentration of the myocardial tissue-specific biomarker, troponin T, was within the reference range during each hospitalization. A 7-day Holter-monitor recording and an exercise stress test also showed normal results.A transthoracic echocardiogram showed a slightly increased tricuspid regurgitation jet peak gradient (38 mmHg), and a subsequent computed tomography (CT) of the heart revealed dilatation of the right-sided chambers with a sinus venosus-type atrial septal defect (ASD) with partial anomalous pulmonary venous return (abnormal return of the right upper pulmonary vein into sinus venosus) and poor contrast enhancement of the left anterior descending artery (LAD), but no coronary artery calcification. The anomalous anatomical findings were confirmed by transesophageal echocardiography.To further examine the coronary anatomy, the patient underwent invasive coronary angiography, revealing a myocardial bridge confined to the LAD with mild systolic compression (Figure1), which worsened during intravenous administration of nitroglycerin (Figure 2). During the angiography, he developed mild chest pain, which continued thereafter in the ward. Despite the angiographic findings, he was given sublingual nitroglycerin, which caused worsening of the symptoms, development of anterior ST-segment elevation in the ECG, and an increased level of high-sensitivity TnT at 686 ng/L (99th percentile 14 ng/L), thus fulfilling the criteria for ST-segment elevation acute myocardial infarction.Figure 1
Coronary angiogram showing slight systolic compression of LAD.Figure 2
Systolic compression of LAD augmented during nitroglycerin infusion.Since the coronary anatomy was known, a reangiography was not deemed necessary. The patient was initially treated with metoprolol and aspirin and later underwent surgical closure of the ASD, redirection of the right upper pulmonary vein into the left atrium, and coronary artery bypass surgery (CABG) with the left internal mammary artery (LIMA) to LAD.
## 3. Discussion
Myocardial bridging represents the most common congenital coronary anomaly and most often involves the LAD [1–3]. The prevalence depends greatly on the method of evaluation and is less than 5% in patients undergoing coronary angiography, during which the condition is distinguished from fixed stenoses by showing narrowing of the involved coronary vessels only during systole [1]. In contrast, CT and autopsy studies have reported frequencies of up to 80% [1–3].The finding of myocardial bridging is usually of little or no clinical significance. The severity, however, varies, and myocardial bridging may lead to myocardial ischemia, myocardial infarction, arrhythmia, or sudden cardiac death [1–3]. Because of the hemodynamic alterations, atherosclerotic changes are often located proximal to the bridge, whereas the tunneled segment itself typically is not atherosclerotic [4–7]. The anatomical changes cannot fully explain the symptoms; however, myocardial bridging augments the risk of significant ischemia during increased sympathetic drive and tachycardia due to a greater systolic-diastolic time ratio and increased contractility [1, 8]. Studies also suggest that a severe systolic compression can, by itself, affect the diastolic blood flow and that the intramyocardial segment may be the source of endothelial dysfunction leading to an increased risk of arterial spasm and thrombosis [1, 5–7].The diagnosis of myocardial bridging should be considered in younger patients without significant risk factors for CAD, who have exercise-induced angina and possibly perfusion defects detected by appropriate imaging modalities [2]. The systolic compression can be accentuated by careful injection of nitroglycerin during coronary angiography [9, 10].Medication is considered first-line therapy. Beta-blockers and possibly nondihydropyridine calcium channel blockers are the preferred antianginal agents due to their negative inotropic and chronotropic effects [1–3, 11]. Nitrates may relieve symptoms but are considered contraindicated by most investigators since they reduce the intrinsic coronary wall tension and increase the reflex sympathetic stimulation of contractility [2]. In view of the frequently found atherosclerotic changes proximal to the bridge, antiplatelet drugs and statins may be considered as preventive measures. Invasive treatment strategies should be reserved for high-risk patients and patients with evidence of clinically relevant ischemia and persistent symptoms despite medical therapy [1, 3]. Surgical myotomy (resection of the muscle bridge) or coronary artery bypass surgery (CABG) are preferred over percutaneous coronary intervention (PCI) with stenting because data indicate a high risk of in-stent restenosis [1–3, 12, 13].The present case illustrates the fact that myocardial bridges are not always benign and may be associated with other congenital heart defects. Clearly shown is also the fact that nitroglycerin, besides diagnostic use, is contraindicated in these patients.
---
*Source: 289879-2014-03-04.xml* | 289879-2014-03-04_289879-2014-03-04.md | 6,921 | Nitroglycerine Induced Acute Myocardial Infarction in a Patient with Myocardial Bridging | Dragana Rujic; Mette Lundgren Nielsen; Karsten Tange Veien; Manan Pareek | Case Reports in Cardiology
(2014) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2014/289879 | 289879-2014-03-04.xml | ---
## Abstract
Muscle overlying an intramyocardial segment of a coronary artery is termed a myocardial bridge. The intramyocardial segment, the tunneled artery, is compressed during systole. The condition is generally benign but may occasionally cause myocardial ischemia, infarction, arrhythmia, or sudden cardiac death. We present a case regarding a 52-year-old man with exercise-induced angina who was diagnosed with a myocardial bridge overlying the left anterior descending artery. He was initially treated with beta-blockers and later received coronary bypass graft surgery.
---
## Body
## 1. Introduction
The major coronary arteries are normally distributed epicardially, that is, on the surface of the myocardium. Occasionally, these vessels have a segmental intramyocardial course. During systole, this segment is compressed either partially or completely. Muscle overlying the intramyocardial segment is called a myocardial bridge, and the artery coursing within the myocardium is termed a tunneled artery [1–3].
## 2. Case Presentation
A 52-year-old man with a long-standing history of smoking and a positive family history of coronary artery disease (CAD) had undergone multiple admissions and investigations in several different hospitals during the last 13 years due to exercise-induced chest pain, shortness of breath, and palpitations.The electrocardiogram (ECG) showed sinus rhythm with complete right bundle branch block. The concentration of the myocardial tissue-specific biomarker, troponin T, was within the reference range during each hospitalization. A 7-day Holter-monitor recording and an exercise stress test also showed normal results.A transthoracic echocardiogram showed a slightly increased tricuspid regurgitation jet peak gradient (38 mmHg), and a subsequent computed tomography (CT) of the heart revealed dilatation of the right-sided chambers with a sinus venosus-type atrial septal defect (ASD) with partial anomalous pulmonary venous return (abnormal return of the right upper pulmonary vein into sinus venosus) and poor contrast enhancement of the left anterior descending artery (LAD), but no coronary artery calcification. The anomalous anatomical findings were confirmed by transesophageal echocardiography.To further examine the coronary anatomy, the patient underwent invasive coronary angiography, revealing a myocardial bridge confined to the LAD with mild systolic compression (Figure1), which worsened during intravenous administration of nitroglycerin (Figure 2). During the angiography, he developed mild chest pain, which continued thereafter in the ward. Despite the angiographic findings, he was given sublingual nitroglycerin, which caused worsening of the symptoms, development of anterior ST-segment elevation in the ECG, and an increased level of high-sensitivity TnT at 686 ng/L (99th percentile 14 ng/L), thus fulfilling the criteria for ST-segment elevation acute myocardial infarction.Figure 1
Coronary angiogram showing slight systolic compression of LAD.Figure 2
Systolic compression of LAD augmented during nitroglycerin infusion.Since the coronary anatomy was known, a reangiography was not deemed necessary. The patient was initially treated with metoprolol and aspirin and later underwent surgical closure of the ASD, redirection of the right upper pulmonary vein into the left atrium, and coronary artery bypass surgery (CABG) with the left internal mammary artery (LIMA) to LAD.
## 3. Discussion
Myocardial bridging represents the most common congenital coronary anomaly and most often involves the LAD [1–3]. The prevalence depends greatly on the method of evaluation and is less than 5% in patients undergoing coronary angiography, during which the condition is distinguished from fixed stenoses by showing narrowing of the involved coronary vessels only during systole [1]. In contrast, CT and autopsy studies have reported frequencies of up to 80% [1–3].The finding of myocardial bridging is usually of little or no clinical significance. The severity, however, varies, and myocardial bridging may lead to myocardial ischemia, myocardial infarction, arrhythmia, or sudden cardiac death [1–3]. Because of the hemodynamic alterations, atherosclerotic changes are often located proximal to the bridge, whereas the tunneled segment itself typically is not atherosclerotic [4–7]. The anatomical changes cannot fully explain the symptoms; however, myocardial bridging augments the risk of significant ischemia during increased sympathetic drive and tachycardia due to a greater systolic-diastolic time ratio and increased contractility [1, 8]. Studies also suggest that a severe systolic compression can, by itself, affect the diastolic blood flow and that the intramyocardial segment may be the source of endothelial dysfunction leading to an increased risk of arterial spasm and thrombosis [1, 5–7].The diagnosis of myocardial bridging should be considered in younger patients without significant risk factors for CAD, who have exercise-induced angina and possibly perfusion defects detected by appropriate imaging modalities [2]. The systolic compression can be accentuated by careful injection of nitroglycerin during coronary angiography [9, 10].Medication is considered first-line therapy. Beta-blockers and possibly nondihydropyridine calcium channel blockers are the preferred antianginal agents due to their negative inotropic and chronotropic effects [1–3, 11]. Nitrates may relieve symptoms but are considered contraindicated by most investigators since they reduce the intrinsic coronary wall tension and increase the reflex sympathetic stimulation of contractility [2]. In view of the frequently found atherosclerotic changes proximal to the bridge, antiplatelet drugs and statins may be considered as preventive measures. Invasive treatment strategies should be reserved for high-risk patients and patients with evidence of clinically relevant ischemia and persistent symptoms despite medical therapy [1, 3]. Surgical myotomy (resection of the muscle bridge) or coronary artery bypass surgery (CABG) are preferred over percutaneous coronary intervention (PCI) with stenting because data indicate a high risk of in-stent restenosis [1–3, 12, 13].The present case illustrates the fact that myocardial bridges are not always benign and may be associated with other congenital heart defects. Clearly shown is also the fact that nitroglycerin, besides diagnostic use, is contraindicated in these patients.
---
*Source: 289879-2014-03-04.xml* | 2014 |
# Unusual Mortality Events of Harbor Porpoise Strandings in North Carolina, 1997–2009
**Authors:** Aleta A. Hohn; David S. Rotstein; Barbie L. Byrd
**Journal:** Journal of Marine Biology
(2013)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2013/289892
---
## Abstract
A marked increase in the frequency of harbor porpoises (Phocoena phocoena) stranded in North Carolina in 2005 was declared as an Unusual Mortality Event (UME). Strandings occurred in January through May when harbor porpoises are seasonally present. Increased stranding rates were measured relative to a threshold to determine that the UME was occurring. The threshold analysis also revealed elevated strandings during 1999, an undeclared UME year. Recovered carcasses during 1999 and 2005 accounted for 39% of 261 strandings during 1997–2009. During 2005, of 43 strandings, primary or secondary causes of mortality included fishery interactions, emaciation, and interspecific aggression. Apart from small but significant differences in timing and condition of strandings, composition of strandings during UME and non-UME years was similar, with most being young-of-the-year and occurring during March and April, north of Cape Hatteras. Porpoises had high levels of parasitic infestation typical for this species. However, no indication of infectious disease and no cause of the 2005 event were found from gross and histologic findings. Response to UMEs is challenging, particularly along the expanses of North Carolina beaches, requiring additional effort to obtain carcasses in sufficiently fresh condition to determine the cause of these events.
---
## Body
## 1. Introduction
Of the six species in the odontocete family Phocoenidae, only one is found in the Atlantic Ocean, the harbor porpoise (Phocoena phocoena). Members of this family, including the harbor porpoise, generally occur at high latitude, while harbor porpoises are found only in the northern hemisphere [1]. Although it is primarily a cold-water temperate and boreal species, documented takes in gillnet fisheries in the western mid-Atlantic region in winter [2] support the mid-Atlantic coast of the United States of America (USA) being part of the normal winter range for the species. Further, harbor porpoises are one of the most commonly stranded species along the extensive beaches of North Carolina (NC) [3]. Historical data indicate that along the US Atlantic coast only Massachusetts has more documented strandings than NC [4].Worldwide, harbor porpoise strandings have been associated with infectious and noninfectious diseases. Infectious diseases include morbillivirus (e.g., [5, 6]), herpesvirus [5], brucellosis [7, 8], bartonellosis [9, 10], and verminous pneumonia [6, 11, 12]. Papillomavirus has been reported to result in self-limiting cutaneous lesions rather than mortalities [13–15]. Noninfectious diseases found in harbor porpoises include colloid goiter [16] and dystocia [17]. Domoic acid toxicosis was identified in harbor porpoises from California [18]. From detailed postmortem examinations of 41 stranded harbor porpoises from the United Kingdom (UK), parasitic and bacterial pneumonia were common causes of death and nonfatal parasitic infestation was common [17]. Jepson et al. [19] found a correlation between body burdens of polychlorinated biphenyls (PCBs) and health status of harbor porpoises in the United Kingdom; animals with infectious diseases had higher body burdens of PCBs.Harbor porpoise mortalities also occur as a result of nondisease factors. Fishery interactions have been widely documented (e.g., [17, 20–24], including along the Atlantic coast of the USA. For example, fishery interactions in gillnets have been observed by at-sea observers from the Gulf of Maine to the mid-Atlantic [2] as well as determined from the presence of entanglement lesions on stranded harbor porpoises along the coasts of Maryland, Virginia, and NC since at least the mid-1990s [25]. During 1997–2008 in NC, Byrd et al. [3] documented that about 21% of stranded porpoises for which it was possible to document whether a human interaction occurred (n=52) showed entanglement lesions consistent with fishing gear. Another 13% were mutilated in a manner consistent with mutilation seen on carcasses with entanglement lesions [26, 27]; although the former were too decomposed to determine if entanglement lesions were present, the type of mutilation infers that they also died due to fishery interactions. Apart from human interactions, harbor porpoises are also susceptible to interactions with dolphins. Blunt-force trauma likely due to aggressive interactions with bottlenose dolphins (Tursiops truncatus) was identified as the most common identified cause of death in a multiyear sample of harbor porpoise strandings from California [18]. The findings were supported by direct observations of aggressive behaviors of bottlenose dolphins toward harbor porpoises in California [28]. Harassment by Pacific white-sided dolphins (Lagenorhynchus obliquidens) of a neonatal harbor porpoise also was observed in Puget Sound, Washington, and this porpoise ultimately died [29]. Furthermore, in a study of 106 stranded harbor porpoises in the UK, the majority had internal and external traumatic injuries attributed to aggressive interactions between the porpoises and bottlenose dolphins [30]. The authors suggested that dolphin-induced porpoise mortality might result in a significant overall source of mortality for harbor porpoises in that area.While winter strandings in NC are common, the number of strandings per year is highly variable. In March 2005, so many harbor porpoises were stranding that, at times, responders needed to continuously drive beaches any given day, intermittently loading carcasses into the truck instead of responding to strandings individually. By late March, the number of reported strandings was sufficiently high that it triggered a request to the Working Group on Marine Mammal Unusual Mortality Events (WGMMUME) on 30 March 2005, that the strandings be designated as an Unusual Mortality Event (UME) (MMPA 16 U.S.C. 1361 et seq.) [31, 32] (http://www.nmfs.noaa.gov/pr/health/mmume/criteria.htm). The purpose of this study was to (1) evaluate the strandings in 2005 relative to other years in order to characterize the UME and (2) describe gross and histologic findings from carcasses that stranded during the 2005 event.
## 2. Materials and Methods
### 2.1. Stranding Response and Data Collection
Members of the stranding network collected basic, or Level A, data (e.g., species, geographic coordinates, straight length, and sex; [33]) whenever possible for each harbor porpoise recovered in NC (Figure 1). Level A data also include a condition code characterizing the stage of decomposition: (1) live animal, (2) carcass—fresh dead, (3) carcass—moderate decomposition, (4) carcass—advanced decomposition, (5) carcass—mummified or skeletal remains, or (6) dead but unknown because carcass was not recovered. Additionally, strandings were examined for signs of human interaction (HI) [27], particularly for indications of fishery interactions (HI-FI) [34]. Each carcass was assigned to a HI category: positive for fishery interactions (HI-FI), positive for human interactions not attributable to fisheries (HI-Other), negative for human interactions (HI-No), or could not be determined if a human interaction occurred (HI-CBD) [34]. Carcasses were also examined for signs of interspecific aggression, such as rake marks [30]. For this study, stranding data were extracted for the period 1997–2009; relatively consistent coast-wide coverage by the stranding network began in 1997 [3], providing reliable data in comparison to other years, and the last complete year for harbor porpoise data in the NC database was 2009.Figure 1
Coastal North Carolina. The barrier islands east of the island Bogue Banks north to the Virginia border are called the Outer Banks. The star corresponds to the end of Highway 12, after which access to the area to the north is by beach only.
### 2.2. Determination of the 1999 and 2005 Events as UMEs
The applicable UME criterion for the declaration of this event was “a marked increase in the magnitude…[of] strandings when compared to prior records” (http://www.nmfs.noaa.gov/pr/health/mmume/criteria.htm). Thus, stranding rates of harbor porpoises during 2005 were compared to historical average strandings starting from 1997. Data from 1999 were excluded from the historical average because of an extraordinarily high number of strandings of harbor porpoises that year. These strandings likely represented an undeclared UME, in part because the complete “historical” record at that time encompassed only the prior two years.Marked increases in the magnitude of strandings were defined as stranding frequencies that exceeded the historical overall mean plus two standard deviations (SDs) [31], in this case by week. The weekly mean plus two SDs is hereafter referred to as the weekly UME threshold. Weeks consisted of 7-day increments by Julian date starting on 1 January. The number of strandings per week in 2005 was compared to the historical UME threshold for that week calculated from data from 1997–2004 (excluding 1999, as noted above). This indicator is referred to as UME threshold A. To determine whether the 2005 event would have been a UME if a longer time series of stranding data were available, an a posteriori threshold analysis was conducted that also included stranding data from 2006–2009 (the longer time series is hereafter referred to as UME threshold B). To determine if a UME declaration for 1999 would have been warranted, similar comparisons were made between data from 1999 and UME thresholds A and B. The focus for the weekly monitoring was on detecting elevated stranding rates in short periods of time during the event. To evaluate whether strandings were elevated when retrospectively summed by year, annual strandings during 2005 and 1999 were compared to the annual mean plus 2 SDs using years in a manner comparable to weekly thresholds A and B.
### 2.3. Characteristics of Harbor Porpoises Stranded in North Carolina
Contingency table analysis was used to test for effects of month, condition, sex ratio, age-class, and HI category on the relative frequency of strandings that occurred during the declared (2005) and undeclared (1999) UME and non-UME years. For temporal effects, calendar month was used instead of week due to the excessive number of zeros and small values in the weekly time series. Analyses of condition excluded Code 6 carcasses because their condition and disposition were unknown. When both sex and length were recorded, strandings were assigned to age-class categories: (1) young-of-year (YOY) ≤118 cm [35], (2) juvenile = 119–134 cm for males [35] and 119–142 cm for females [36], and (3) mature >135 cm for males and >142 cm for females. Because of sexual dimorphism in mature porpoises, carcasses not identified to sex were excluded if lengths were 119–142 cm; that is, all animals <119 cm were considered YOYs, and all animals of either sex >142 cm were considered mature. Independence in parameters between UME and non-UME years was tested using Fisher’s exact tests due to small sample sizes in some cells and the skewed distribution of observations, for example, few strandings occurred in the first or last months of the timeframe when strandings typically occur. When significant P values (P≤0.05) indicated lack of fit, standardized residuals (>|1.96|) from Chi-Square tests were used to identify in which cells significant differences occurred. All tests were conducted using SAS versus 9.3 (SAS Institute, 100 SAS Campus Drive, Cary, NC 27513-2414).
### 2.4. Pathology Investigation of 2005 Strandings
During the 2005 UME, intact carcasses were necropsied immediately or, if time did not allow for immediate necropsy, frozen for future necropsy. When possible, histological samples were collected from euthanized animals and Code 2 carcasses that had not been frozen; samples collected from major organs (heart, lung, liver, kidney, spleen, liver, lymph nodes, and brain) and lesions were preserved in 10% formalin. Preserved subsamples were embedded in tissue cassettes, sectioned at 5 to 7μ, and stained with hematoxylin and eosin. Special stains, Periodic acid-Schiff (PAS) and Gomori-Grocott methenamine silver (GMS) for fungi and algae, were used as needed. All slides were examined by a single pathologist, DSR. Limited necropsies were conducted on carcasses in poor condition. Only external examination for gross observations, such as emaciation, mutilation, or scavenger damage, was possible for other carcasses. Contingency table analysis with Fisher’s exact test was used to test for differences in relative frequency of emaciated animals between the declared (2005) and undeclared (1999) UME and the non-UME years.
## 2.1. Stranding Response and Data Collection
Members of the stranding network collected basic, or Level A, data (e.g., species, geographic coordinates, straight length, and sex; [33]) whenever possible for each harbor porpoise recovered in NC (Figure 1). Level A data also include a condition code characterizing the stage of decomposition: (1) live animal, (2) carcass—fresh dead, (3) carcass—moderate decomposition, (4) carcass—advanced decomposition, (5) carcass—mummified or skeletal remains, or (6) dead but unknown because carcass was not recovered. Additionally, strandings were examined for signs of human interaction (HI) [27], particularly for indications of fishery interactions (HI-FI) [34]. Each carcass was assigned to a HI category: positive for fishery interactions (HI-FI), positive for human interactions not attributable to fisheries (HI-Other), negative for human interactions (HI-No), or could not be determined if a human interaction occurred (HI-CBD) [34]. Carcasses were also examined for signs of interspecific aggression, such as rake marks [30]. For this study, stranding data were extracted for the period 1997–2009; relatively consistent coast-wide coverage by the stranding network began in 1997 [3], providing reliable data in comparison to other years, and the last complete year for harbor porpoise data in the NC database was 2009.Figure 1
Coastal North Carolina. The barrier islands east of the island Bogue Banks north to the Virginia border are called the Outer Banks. The star corresponds to the end of Highway 12, after which access to the area to the north is by beach only.
## 2.2. Determination of the 1999 and 2005 Events as UMEs
The applicable UME criterion for the declaration of this event was “a marked increase in the magnitude…[of] strandings when compared to prior records” (http://www.nmfs.noaa.gov/pr/health/mmume/criteria.htm). Thus, stranding rates of harbor porpoises during 2005 were compared to historical average strandings starting from 1997. Data from 1999 were excluded from the historical average because of an extraordinarily high number of strandings of harbor porpoises that year. These strandings likely represented an undeclared UME, in part because the complete “historical” record at that time encompassed only the prior two years.Marked increases in the magnitude of strandings were defined as stranding frequencies that exceeded the historical overall mean plus two standard deviations (SDs) [31], in this case by week. The weekly mean plus two SDs is hereafter referred to as the weekly UME threshold. Weeks consisted of 7-day increments by Julian date starting on 1 January. The number of strandings per week in 2005 was compared to the historical UME threshold for that week calculated from data from 1997–2004 (excluding 1999, as noted above). This indicator is referred to as UME threshold A. To determine whether the 2005 event would have been a UME if a longer time series of stranding data were available, an a posteriori threshold analysis was conducted that also included stranding data from 2006–2009 (the longer time series is hereafter referred to as UME threshold B). To determine if a UME declaration for 1999 would have been warranted, similar comparisons were made between data from 1999 and UME thresholds A and B. The focus for the weekly monitoring was on detecting elevated stranding rates in short periods of time during the event. To evaluate whether strandings were elevated when retrospectively summed by year, annual strandings during 2005 and 1999 were compared to the annual mean plus 2 SDs using years in a manner comparable to weekly thresholds A and B.
## 2.3. Characteristics of Harbor Porpoises Stranded in North Carolina
Contingency table analysis was used to test for effects of month, condition, sex ratio, age-class, and HI category on the relative frequency of strandings that occurred during the declared (2005) and undeclared (1999) UME and non-UME years. For temporal effects, calendar month was used instead of week due to the excessive number of zeros and small values in the weekly time series. Analyses of condition excluded Code 6 carcasses because their condition and disposition were unknown. When both sex and length were recorded, strandings were assigned to age-class categories: (1) young-of-year (YOY) ≤118 cm [35], (2) juvenile = 119–134 cm for males [35] and 119–142 cm for females [36], and (3) mature >135 cm for males and >142 cm for females. Because of sexual dimorphism in mature porpoises, carcasses not identified to sex were excluded if lengths were 119–142 cm; that is, all animals <119 cm were considered YOYs, and all animals of either sex >142 cm were considered mature. Independence in parameters between UME and non-UME years was tested using Fisher’s exact tests due to small sample sizes in some cells and the skewed distribution of observations, for example, few strandings occurred in the first or last months of the timeframe when strandings typically occur. When significant P values (P≤0.05) indicated lack of fit, standardized residuals (>|1.96|) from Chi-Square tests were used to identify in which cells significant differences occurred. All tests were conducted using SAS versus 9.3 (SAS Institute, 100 SAS Campus Drive, Cary, NC 27513-2414).
## 2.4. Pathology Investigation of 2005 Strandings
During the 2005 UME, intact carcasses were necropsied immediately or, if time did not allow for immediate necropsy, frozen for future necropsy. When possible, histological samples were collected from euthanized animals and Code 2 carcasses that had not been frozen; samples collected from major organs (heart, lung, liver, kidney, spleen, liver, lymph nodes, and brain) and lesions were preserved in 10% formalin. Preserved subsamples were embedded in tissue cassettes, sectioned at 5 to 7μ, and stained with hematoxylin and eosin. Special stains, Periodic acid-Schiff (PAS) and Gomori-Grocott methenamine silver (GMS) for fungi and algae, were used as needed. All slides were examined by a single pathologist, DSR. Limited necropsies were conducted on carcasses in poor condition. Only external examination for gross observations, such as emaciation, mutilation, or scavenger damage, was possible for other carcasses. Contingency table analysis with Fisher’s exact test was used to test for differences in relative frequency of emaciated animals between the declared (2005) and undeclared (1999) UME and the non-UME years.
## 3. Results
### 3.1. Determination of the 1999 and 2005 Events as UMEs
From 1997 to 2009, 262 harbor porpoise strandings were reported, ranging annually from 4 (1998) to 59 (1999), with an overall annual mean of 20.1 (SD = 17.15) and a mean of 14.5 (SD = 10.7) when 2005 and 1999 were excluded. Thirty-nine percent of the strandings occurred during 1999 and 2005. On a weekly basis, elevated strandings occurred during both 2005 (declared UME) and 1999 (undeclared UME). The weekly stranding frequency in 2005 exceeded the corresponding weekly threshold A from week 9 (26 February–4 March) through week 12 (19–25 March) (Figure2). These data were used to make the initial declaration of a UME. In the a posteriori analysis, the same weeks exceeded threshold B with the addition of week seven (Figure 2). The weekly stranding frequency in 1999 exceeded the corresponding weekly thresholds A and B in weeks 12–16 (Figure 2). Thresholds were also exceeded in weeks 4 and 6 reflecting only one stranding when the mean number of strandings was close to zero (Figure 2). Week 13 in 1999 had more porpoise strandings than the annual total in all but three years: 1999, 2003, and 2005. Retrospectively, the annual stranding frequency exceeded the annual thresholds A and B during both 2005 and 1999, while 2003 exceeded threshold B (Figure 2).(a) Weekly harbor porpoise strandings in 1999 (darker blue bars) and 2005 (lighter blue bars) compared to weekly threshold A (mean + 2 standard deviations: 1997-1998, 2000–2004) (black horizontal solid line) and threshold B (mean + 2 standard deviations: 1997-1998, 2000–2004, 2006–2009) (red horizontal dashed line). (b) Annual harbor porpoise strandings during 1997–2009 (blue bars) compared to annual threshold A (black horizontal solid line) and threshold B (red horizontal dashed line).
(a)
(b)
### 3.2. Characteristics of Harbor Porpoises Stranded in North Carolina
Overall, harbor porpoises stranded between January and May, but primarily in February through April (Figure3). Relative to non-UME years, in 2005, more strandings occurred in March and fewer occurred in April (P=0.03), while in 1999, in addition to the notable peak in March (Figure 3), fewer strandings occurred in February (P=0.001) (Figure 3). These opposite patterns of earlier versus later strandings were emphasized when comparing 2005 to 1999 (P=0.0007).Harbor porpoise strandings by month (a), condition code (b), and human interaction (HI) category (c) as a percentage of the total for 1999 (n=59), 2005 (n=43), and non-UME years (n=160). Condition codes are (1) live animal, (2) carcass-fresh dead, (3) carcass-moderately decomposed, (4) carcass-advanced decomposition, (5) carcass-mummified or skeletal remains, and (6) disposition unknown. HI categories are HI-FI (evidence of Fishery Interaction), HI-Other (other evidence of HI), HI-No (no evidence of HI), and HI-CBD (HI could not be determined).
(a)
(b)
(c)During non-UME years, harbor porpoises were recovered from the NC border with Virginia to Topsail Beach (~410 km of coastline) (Figure4); 84% of strandings occurred north of Cape Hatteras (~160 km of coastline). The spatial patterns were similar in 2005 (77% north of Cape Hatteras) and 1999 (88% north of Cape Hatteras), although in 2005 most of the strandings occurred in the northern half of the coast between the Virginia Line and Cape Hatteras, and in 1999 most strandings were in the southern half. Strandings inshore were rare, occurring only twice and both in 2005.Figure 4
Annual harbor porpoise strandings in North Carolina, 1997–2009. In addition, in 2009 one stranding was recovered in Topsail Beach (see Figure1).Biological characteristics during non-UME and UME years were similar. Sex could be determined for 78% of stranded harbor porpoises between 1997 and 2009, with almost equal numbers of females and males (105 females, 99 males). The sex ratio did not differ between non-UME years and 2005 or 1999 (P=0.26 and P=1.00, resp.), or between 2005 and 1999 (P=1.00). For both sexes, stranded porpoises ranged from 84 to 169 cm in total length (n=99, actual length, not estimated) during non-UME years, from 99 to 154 cm in 2005 (n=31), and from 107 to 143 cm in 1999 (n=39). The relative age structure (YOY, juvenile, and adult) did not differ between non-UME years and 2005 (females, P=0.26; males, P=0.41) or 1999 (females P=0.48; males P=0.18) or between 2005 and 1999 (females, P=0.74, males, P=0.41). The most prevalent age class in all years and for both sexes was YOY (72%) (Figure 5); none of the few mature animals stranded during the study period was recovered in 1999 (Figure 5), and only one was documented in 2005. Only two harbor porpoises were pregnant, one in March 2001 with a 54 cm fetus and the other in January 2006 with a 40 cm fetus. Neither pregnant female was lactating. An additional 26 animals were measured (size range 89–136 cm), but sex could not be determined. Although it was not possible to categorize the single animal >136 cm as adult (if it was male) or juvenile (if it was female), 20 of the strandings CBD for sex were YOYs (≤118 cm).Age class categories by sex (female = 87; male = 82) of harbor porpoise strandings in North Carolina during 1997–2009: Young-of-Year (YOY) (≤118 cm); juvenile (females = 119–142 cm; males = 119–134 cm); mature (females ≥ 143 cm; males ≥ 135 cm). Strandings of unknown sex or for which lengths were estimated were excluded.
(a)
(b)Condition code was recorded for all 43 specimens in 2005. The majority of strandings were condition code 3 (51%) (Figure3). There was no evidence of differences in condition between non-UME years (mean condition code = 2.73, SD = 0.96) and 2005 (mean = 2.72, SD = 0.91) (P=0.35), but carcasses in 1999 were relatively more decomposed (mean condition code = 3.05, SD = 0.66) than those during non-UME years (P=0.02) or 2005 (P=0.07) (Figure 3). Live strandings (Code 1) were rare (n=14), occurring during only 7 of the 14 years in the time series and with not more than two in any non-UME year; 10 died (naturally or euthanized), 2 were released immediately, and 2 were released after rehabilitation. Whereas no live strandings were found in 1999, five occurred during 2005. Two of the live strandings in 2005 were recovered in estuarine waters, representing the only porpoise strandings recovered inshore during 1997–2009. The first inshore stranding occurred on 18 March when a harbor porpoise found swimming in a drainage canal was removed, roto tagged, and transported to ocean waters where it was released. The second occurred on 8 May in northern Currituck Sound and was euthanized. Subsequently, both animals tested positive for Bartonella infection [10]. The three other live strandings in 2005 were in poor condition and euthanized, one after sustaining serious injuries from being pecked by gulls (Larus sp.).Human interactions could not be determined (HI-CBD) for most carcasses during non-UME years (75%), 2005 (81%), or 1999 (81%) (Figure3). The relative frequency of carcasses assigned to the four HI categories (HI-FI, HI-Other, HI-No, and HI-CBD) was similar between non-UME years and 2005 (P=0.33) and 1999 (P=0.46) as well as between 2005 and 1999 (P=1.00). The relative frequency was also similar for carcasses when a human interaction could be determined, that is, when HI-CBD was excluded (non-UME years v. 2005, P=0.17; v. 1999, P=0.44; 2005 v. 1999, P=1.00). Although sample size was small, almost twice the rate of carcasses were HI during UME years (50% in 2005, 45% in 1999) than those during non-UME years (26%). In all years, entanglement lesions were the most common form of HI evidence (n=11), and one of those carcasses also had a slit along the abdomen and the dorsal fin was cut off (Table 1). All strandings categorized as HI-Other had similar mutilations, but decomposition, scavenger damage, or both prevented the determination of whether entanglement lesions were present or absent (Table 1). One of the HI-FI animals had a penetrating wound near the blowhole that might have been from a fishing gaff.Table 1
Information for harbor porpoise strandings during 1997–2009 categorized as positive for human interactions (HI), either HI-FI (fishery interaction) or HI-Other (other evidence of HI). CBD: could not be determined.
HI-category
Field number
Mo
Year
Condition code
Sex
Length (cm)
Mutilation
Body slit
Missing appendages
Scavenger damage
Entanglement lesion location
HI-FI
BRM001
3
1999
3
Female
132
No
No
No
Yes
Flukes
HI-FI
PTM041
3
1999
3
Female
—
CBD
No
No
Yes
Head, left flipper
HI-FI
HOF013
4
1999
3
Male
121
Yes
Yes
Yes
Yes
Peduncle
HI-FI
KMS099
2
2001
2
Male
117
No
No
No
Yes
Left fluke
HI-FI
KMS238
2
2003
2
Female
128
CBD
No
No
Yes
Right flipper, right fluke
HI-FI
CALO0408
4
2004
3
Female
112
N/R
No
No
N/R
Peduncle
HI-FI
KMS335
4
2004
2
Female
111
No
No
No
Yes
Right fluke
HI-FI
KMS336
4
2004
2
Female
115
No
No
No
Yes
Right fluke
HI-FI
KMS388
2
2005
3
CBD
108
No
No
No
Yes
Left flipper
HI-FI
KMS404
3
2005
2
Male
116
No
No
No
Yes
Head, both flippers
HI-FI
KMS417
4
2005
2
Female
—
No
No
No
No
Flipper
HI-Other
HOF011
3
1999
3
Female
—
Yes
Yes
Yes
Yes
N/A
HI-Other
JGM001
4
1999
3
Female
120
Yes
No
Yes
Yes
N/A
HI-Other
KMS121
4
2001
4
CBD
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT001
4
2003
3
Female
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT002
4
2003
3
Female
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT004
4
2003
3
Male
105
Yes
No
Yes
Yes
N/A
HI-Other
KTM009
4
2003
3
CBD
—
Yes
No
Yes
Yes
N/A
HI-Other
JND002
3
2005
4
Male
—
Yes
No
Yes
Yes
N/A
### 3.3. Pathology Findings from 2005 Strandings
Of the 42 carcasses recovered (one animal was released alive), few were of sufficient quality to assess gross pathology and fewer still were suitable for histologic assessment. Over half (n=27) of all carcasses sustained moderate to heavy scavenger damage (e.g., from gulls and foxes), often leaving no internal organs to examine or sample. Emaciation could be determined for only 17 carcasses and, of these, 9 were emaciated. There was no difference in the relative number of emaciated animals between non-UME years (60% emaciated) and 2005 (50% emaciated) (P=0.58) or 1999 (76% emaciated) (P=0.12) and a marginal difference between 1999 and 2005 (P=0.07). During 2005, an assessment of whether there were stomach contents was possible only for 21 strandings (13 empty: 10 HI-CBD, 2 HI-FI, and 1 HI-No; 8 with contents: 7 HI-CBD and 1 HI-No). Five porpoises had evidence of interspecific aggression; however, the presence/absence of evidence could not be determined for 31 porpoises. Limited necropsies were conducted for 14 carcasses, and only external exams were conducted for 23. Of the limited necropsies, five animals (all HI-CBD) had varying amounts of tracheal froth suggesting an agonal response consistent with live stranding or gear entanglement [37].Six (14%) animals received complete necropsies and histopathologic assessment. Three of these six animals were emaciated. Gross lesions were observed in four systems: sensory, respiratory, integumentary, and hepatobiliary (Table2). Overall, the integumentary and respiratory systems accounted for the greatest percentage of gross lesions, including scavenger lesions (3/6, 50%), entanglement lesions (2/6, 33%), a penetrating wound near the blowhole (1/6, 16%), fresh rake marks (1/6, 16%), adherent material to the fluke (1/6, 16%), verminous pneumonia (1/6, 16%), and pulmonary edema (1/6, 16%). In the hepatobiliary and sensory system, there were focal biliary hyperplasia (1/6, 16%) and pooled blood in the ears (1/6, 16%). All but one animal had stomach compartments devoid of contents.Table 2
Specific gross necropsy findings by system for the six harbor porpoises with submitted tissues for histopathologic evaluation. Each porpoise is listed by its field identification number. Cells for human interaction (HI) evidence are listed as follows: HI-FI (evidence of fishery interaction), HI-No (no evidence of HI), and HI-CBD (could not be determined).
System affected
JND003
KMS387
KMS389
KMS404
KMS417
MLC001
Body-general
—
—
Emaciation
—
Emaciation
Emaciation
Cardiovascular
—
—
—
—
—
—
Digestive
—
—
—
—
—
—
Endocrine
—
—
—
—
—
—
Hemato/lymphoreticular
—
—
—
—
—
—
Hepatobiliary
—
—
—
—
Focal biliary hyperplasia
—
Integumentary
Scavenger damage
Yes
Yes
Yes
Yes
HI evidence
HI-CBD
HI-CBD
HI-CBD
HI-FI
HI-FI
HI-No
Interspecific aggression evidence
CBD
CBD
No
CBD
Yes
No
Other
—
—
Adherent material on fluke
—
Penetrating wound near blowhole
—
Musculoskeletal
—
—
—
—
—
—
Nervous
—
—
—
—
—
—
Reproductive
—
—
—
—
—
—
Respiratory
Pulmonary edema
—
Verminous pneumonia
—
—
—
Sensory
—
—
—
—
Ears-pooled blood
Stomach contents
Full
Empty
Empty
Empty
Empty
Empty
Urinary
—
—
—
—
—
—Histologic lesions involved the respiratory (3/6, 50%), integumentary (2/6, 33%), hepatobiliary (3/6, 50%), hematopoietic/lymphoreticular (3/6, 50%), digestive (3/6, 50%), sensory (2/6, 33%), and nervous systems (1/6, 16%) (Table3). The lesions ranged from incidental (no effect on the animal) to significant (some effect on the animal). There was no commonality of lesions. Endoparasitism was a common finding in the liver (hepatobiliary) (3/6, 50%) and lung (respiratory system) (3/6, 50%). Parasites, including nematodes in the lung (Figure 6) and trematode ova in the liver (Figure 7), were not always evident in the lesions; however, the presence of eosinophils and granulomatous inflammation were supportive of their presence. In addition to inflammation in the liver, there were biliary hyperplasia (increased number of bile ducts) and fibrosis of the portal tracts. The changes in the lung and liver denoted chronic inflammation. A single emaciated porpoise had lesions suggestive of septicemia including splenic necrosis and lymphoid depletion; however, bacteria were not observed. Other findings for this animal included superficial algal dermatitis (Figure 8) and pancreatic atrophy.Table 3
Specific histologic findings by system for the six harbor porpoises for which tissues were submitted for histopathologic evaluation. Each porpoise is listed by its field identification number.
System affected
JND003
KMS387
KMS389
KMS404
KMS417
MLC001
Body-general
—
—
—
—
—
—
Cardiovascular
—
—
—
—
—
—
Digestive
—
Mucosal hyperplasia
(1) Pancreas-zymogen granule depletion,(2) Colitis
—
—
Eosinophilic enteritis
Endocrine
—
—
—
—
—
—
Hemato/lymphoreticular
—
Reactive lymph node
(1) Spleen-necrosis,(2) Lymph node depletion
—
—
(1) Hyperplasia,(2) Eosinophilia
Hepatobiliary
(1) Bile duct hyperplasia,(2) Pericholangitis
—
—
Biliary hyperplasia
Hepatic trematodiasis
—
Integumentary
—
—
Algal dermatitis
—
Steatitis
—
Musculoskeletal
—
—
—
—
—
—
Nervous
—
—
—
—
Myelin sheath swelling
—
Reproductive
—
—
—
—
—
—
Respiratory
—
Eosinophilic broncho-pneumonia
Verminous pneumonia
—
—
Eosinophilic interstitial pneumonia
Sensory
—
—
—
—
(1) Corneal edema,(2) Retinal atrophy
—
Urinary
—
—
—
—
—
—Figure 6
Microscopic section of lung from KMS389. Nematode larvae are present within regions of parenchymal destruction and fibrosis.Figure 7
Section of the liver from KMS417. Trematode ova are present within the portal tract surrounded by mixed inflammatory cells.Figure 8
Algae adhered to the superficial epithelium of KMS 389. Algae are arranged in dense sheets.Other lesions observed were incidental. The animal with a penetrating wound had inflammation of the adipose of the site of puncture (steatitis); however, there was no evidence of systemic infection related to this wound. Perimortem hypoxic changes including myelin sheath swelling in the brain were observed in one porpoise and mild retinal atrophy and corneal edema in another, with the latter likely resulting from superficial trauma perhaps at the time of stranding. Two porpoises had mild eosinophilic inflammation in the small and large intestine that may have been associated with parasitic infection. Lymph nodes in two animals were reactive with one lymph node containing eosinophils in increased numbers. While a cause of this was not evident, it does indicate antigenic stimulation.
## 3.1. Determination of the 1999 and 2005 Events as UMEs
From 1997 to 2009, 262 harbor porpoise strandings were reported, ranging annually from 4 (1998) to 59 (1999), with an overall annual mean of 20.1 (SD = 17.15) and a mean of 14.5 (SD = 10.7) when 2005 and 1999 were excluded. Thirty-nine percent of the strandings occurred during 1999 and 2005. On a weekly basis, elevated strandings occurred during both 2005 (declared UME) and 1999 (undeclared UME). The weekly stranding frequency in 2005 exceeded the corresponding weekly threshold A from week 9 (26 February–4 March) through week 12 (19–25 March) (Figure2). These data were used to make the initial declaration of a UME. In the a posteriori analysis, the same weeks exceeded threshold B with the addition of week seven (Figure 2). The weekly stranding frequency in 1999 exceeded the corresponding weekly thresholds A and B in weeks 12–16 (Figure 2). Thresholds were also exceeded in weeks 4 and 6 reflecting only one stranding when the mean number of strandings was close to zero (Figure 2). Week 13 in 1999 had more porpoise strandings than the annual total in all but three years: 1999, 2003, and 2005. Retrospectively, the annual stranding frequency exceeded the annual thresholds A and B during both 2005 and 1999, while 2003 exceeded threshold B (Figure 2).(a) Weekly harbor porpoise strandings in 1999 (darker blue bars) and 2005 (lighter blue bars) compared to weekly threshold A (mean + 2 standard deviations: 1997-1998, 2000–2004) (black horizontal solid line) and threshold B (mean + 2 standard deviations: 1997-1998, 2000–2004, 2006–2009) (red horizontal dashed line). (b) Annual harbor porpoise strandings during 1997–2009 (blue bars) compared to annual threshold A (black horizontal solid line) and threshold B (red horizontal dashed line).
(a)
(b)
## 3.2. Characteristics of Harbor Porpoises Stranded in North Carolina
Overall, harbor porpoises stranded between January and May, but primarily in February through April (Figure3). Relative to non-UME years, in 2005, more strandings occurred in March and fewer occurred in April (P=0.03), while in 1999, in addition to the notable peak in March (Figure 3), fewer strandings occurred in February (P=0.001) (Figure 3). These opposite patterns of earlier versus later strandings were emphasized when comparing 2005 to 1999 (P=0.0007).Harbor porpoise strandings by month (a), condition code (b), and human interaction (HI) category (c) as a percentage of the total for 1999 (n=59), 2005 (n=43), and non-UME years (n=160). Condition codes are (1) live animal, (2) carcass-fresh dead, (3) carcass-moderately decomposed, (4) carcass-advanced decomposition, (5) carcass-mummified or skeletal remains, and (6) disposition unknown. HI categories are HI-FI (evidence of Fishery Interaction), HI-Other (other evidence of HI), HI-No (no evidence of HI), and HI-CBD (HI could not be determined).
(a)
(b)
(c)During non-UME years, harbor porpoises were recovered from the NC border with Virginia to Topsail Beach (~410 km of coastline) (Figure4); 84% of strandings occurred north of Cape Hatteras (~160 km of coastline). The spatial patterns were similar in 2005 (77% north of Cape Hatteras) and 1999 (88% north of Cape Hatteras), although in 2005 most of the strandings occurred in the northern half of the coast between the Virginia Line and Cape Hatteras, and in 1999 most strandings were in the southern half. Strandings inshore were rare, occurring only twice and both in 2005.Figure 4
Annual harbor porpoise strandings in North Carolina, 1997–2009. In addition, in 2009 one stranding was recovered in Topsail Beach (see Figure1).Biological characteristics during non-UME and UME years were similar. Sex could be determined for 78% of stranded harbor porpoises between 1997 and 2009, with almost equal numbers of females and males (105 females, 99 males). The sex ratio did not differ between non-UME years and 2005 or 1999 (P=0.26 and P=1.00, resp.), or between 2005 and 1999 (P=1.00). For both sexes, stranded porpoises ranged from 84 to 169 cm in total length (n=99, actual length, not estimated) during non-UME years, from 99 to 154 cm in 2005 (n=31), and from 107 to 143 cm in 1999 (n=39). The relative age structure (YOY, juvenile, and adult) did not differ between non-UME years and 2005 (females, P=0.26; males, P=0.41) or 1999 (females P=0.48; males P=0.18) or between 2005 and 1999 (females, P=0.74, males, P=0.41). The most prevalent age class in all years and for both sexes was YOY (72%) (Figure 5); none of the few mature animals stranded during the study period was recovered in 1999 (Figure 5), and only one was documented in 2005. Only two harbor porpoises were pregnant, one in March 2001 with a 54 cm fetus and the other in January 2006 with a 40 cm fetus. Neither pregnant female was lactating. An additional 26 animals were measured (size range 89–136 cm), but sex could not be determined. Although it was not possible to categorize the single animal >136 cm as adult (if it was male) or juvenile (if it was female), 20 of the strandings CBD for sex were YOYs (≤118 cm).Age class categories by sex (female = 87; male = 82) of harbor porpoise strandings in North Carolina during 1997–2009: Young-of-Year (YOY) (≤118 cm); juvenile (females = 119–142 cm; males = 119–134 cm); mature (females ≥ 143 cm; males ≥ 135 cm). Strandings of unknown sex or for which lengths were estimated were excluded.
(a)
(b)Condition code was recorded for all 43 specimens in 2005. The majority of strandings were condition code 3 (51%) (Figure3). There was no evidence of differences in condition between non-UME years (mean condition code = 2.73, SD = 0.96) and 2005 (mean = 2.72, SD = 0.91) (P=0.35), but carcasses in 1999 were relatively more decomposed (mean condition code = 3.05, SD = 0.66) than those during non-UME years (P=0.02) or 2005 (P=0.07) (Figure 3). Live strandings (Code 1) were rare (n=14), occurring during only 7 of the 14 years in the time series and with not more than two in any non-UME year; 10 died (naturally or euthanized), 2 were released immediately, and 2 were released after rehabilitation. Whereas no live strandings were found in 1999, five occurred during 2005. Two of the live strandings in 2005 were recovered in estuarine waters, representing the only porpoise strandings recovered inshore during 1997–2009. The first inshore stranding occurred on 18 March when a harbor porpoise found swimming in a drainage canal was removed, roto tagged, and transported to ocean waters where it was released. The second occurred on 8 May in northern Currituck Sound and was euthanized. Subsequently, both animals tested positive for Bartonella infection [10]. The three other live strandings in 2005 were in poor condition and euthanized, one after sustaining serious injuries from being pecked by gulls (Larus sp.).Human interactions could not be determined (HI-CBD) for most carcasses during non-UME years (75%), 2005 (81%), or 1999 (81%) (Figure3). The relative frequency of carcasses assigned to the four HI categories (HI-FI, HI-Other, HI-No, and HI-CBD) was similar between non-UME years and 2005 (P=0.33) and 1999 (P=0.46) as well as between 2005 and 1999 (P=1.00). The relative frequency was also similar for carcasses when a human interaction could be determined, that is, when HI-CBD was excluded (non-UME years v. 2005, P=0.17; v. 1999, P=0.44; 2005 v. 1999, P=1.00). Although sample size was small, almost twice the rate of carcasses were HI during UME years (50% in 2005, 45% in 1999) than those during non-UME years (26%). In all years, entanglement lesions were the most common form of HI evidence (n=11), and one of those carcasses also had a slit along the abdomen and the dorsal fin was cut off (Table 1). All strandings categorized as HI-Other had similar mutilations, but decomposition, scavenger damage, or both prevented the determination of whether entanglement lesions were present or absent (Table 1). One of the HI-FI animals had a penetrating wound near the blowhole that might have been from a fishing gaff.Table 1
Information for harbor porpoise strandings during 1997–2009 categorized as positive for human interactions (HI), either HI-FI (fishery interaction) or HI-Other (other evidence of HI). CBD: could not be determined.
HI-category
Field number
Mo
Year
Condition code
Sex
Length (cm)
Mutilation
Body slit
Missing appendages
Scavenger damage
Entanglement lesion location
HI-FI
BRM001
3
1999
3
Female
132
No
No
No
Yes
Flukes
HI-FI
PTM041
3
1999
3
Female
—
CBD
No
No
Yes
Head, left flipper
HI-FI
HOF013
4
1999
3
Male
121
Yes
Yes
Yes
Yes
Peduncle
HI-FI
KMS099
2
2001
2
Male
117
No
No
No
Yes
Left fluke
HI-FI
KMS238
2
2003
2
Female
128
CBD
No
No
Yes
Right flipper, right fluke
HI-FI
CALO0408
4
2004
3
Female
112
N/R
No
No
N/R
Peduncle
HI-FI
KMS335
4
2004
2
Female
111
No
No
No
Yes
Right fluke
HI-FI
KMS336
4
2004
2
Female
115
No
No
No
Yes
Right fluke
HI-FI
KMS388
2
2005
3
CBD
108
No
No
No
Yes
Left flipper
HI-FI
KMS404
3
2005
2
Male
116
No
No
No
Yes
Head, both flippers
HI-FI
KMS417
4
2005
2
Female
—
No
No
No
No
Flipper
HI-Other
HOF011
3
1999
3
Female
—
Yes
Yes
Yes
Yes
N/A
HI-Other
JGM001
4
1999
3
Female
120
Yes
No
Yes
Yes
N/A
HI-Other
KMS121
4
2001
4
CBD
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT001
4
2003
3
Female
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT002
4
2003
3
Female
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT004
4
2003
3
Male
105
Yes
No
Yes
Yes
N/A
HI-Other
KTM009
4
2003
3
CBD
—
Yes
No
Yes
Yes
N/A
HI-Other
JND002
3
2005
4
Male
—
Yes
No
Yes
Yes
N/A
## 3.3. Pathology Findings from 2005 Strandings
Of the 42 carcasses recovered (one animal was released alive), few were of sufficient quality to assess gross pathology and fewer still were suitable for histologic assessment. Over half (n=27) of all carcasses sustained moderate to heavy scavenger damage (e.g., from gulls and foxes), often leaving no internal organs to examine or sample. Emaciation could be determined for only 17 carcasses and, of these, 9 were emaciated. There was no difference in the relative number of emaciated animals between non-UME years (60% emaciated) and 2005 (50% emaciated) (P=0.58) or 1999 (76% emaciated) (P=0.12) and a marginal difference between 1999 and 2005 (P=0.07). During 2005, an assessment of whether there were stomach contents was possible only for 21 strandings (13 empty: 10 HI-CBD, 2 HI-FI, and 1 HI-No; 8 with contents: 7 HI-CBD and 1 HI-No). Five porpoises had evidence of interspecific aggression; however, the presence/absence of evidence could not be determined for 31 porpoises. Limited necropsies were conducted for 14 carcasses, and only external exams were conducted for 23. Of the limited necropsies, five animals (all HI-CBD) had varying amounts of tracheal froth suggesting an agonal response consistent with live stranding or gear entanglement [37].Six (14%) animals received complete necropsies and histopathologic assessment. Three of these six animals were emaciated. Gross lesions were observed in four systems: sensory, respiratory, integumentary, and hepatobiliary (Table2). Overall, the integumentary and respiratory systems accounted for the greatest percentage of gross lesions, including scavenger lesions (3/6, 50%), entanglement lesions (2/6, 33%), a penetrating wound near the blowhole (1/6, 16%), fresh rake marks (1/6, 16%), adherent material to the fluke (1/6, 16%), verminous pneumonia (1/6, 16%), and pulmonary edema (1/6, 16%). In the hepatobiliary and sensory system, there were focal biliary hyperplasia (1/6, 16%) and pooled blood in the ears (1/6, 16%). All but one animal had stomach compartments devoid of contents.Table 2
Specific gross necropsy findings by system for the six harbor porpoises with submitted tissues for histopathologic evaluation. Each porpoise is listed by its field identification number. Cells for human interaction (HI) evidence are listed as follows: HI-FI (evidence of fishery interaction), HI-No (no evidence of HI), and HI-CBD (could not be determined).
System affected
JND003
KMS387
KMS389
KMS404
KMS417
MLC001
Body-general
—
—
Emaciation
—
Emaciation
Emaciation
Cardiovascular
—
—
—
—
—
—
Digestive
—
—
—
—
—
—
Endocrine
—
—
—
—
—
—
Hemato/lymphoreticular
—
—
—
—
—
—
Hepatobiliary
—
—
—
—
Focal biliary hyperplasia
—
Integumentary
Scavenger damage
Yes
Yes
Yes
Yes
HI evidence
HI-CBD
HI-CBD
HI-CBD
HI-FI
HI-FI
HI-No
Interspecific aggression evidence
CBD
CBD
No
CBD
Yes
No
Other
—
—
Adherent material on fluke
—
Penetrating wound near blowhole
—
Musculoskeletal
—
—
—
—
—
—
Nervous
—
—
—
—
—
—
Reproductive
—
—
—
—
—
—
Respiratory
Pulmonary edema
—
Verminous pneumonia
—
—
—
Sensory
—
—
—
—
Ears-pooled blood
Stomach contents
Full
Empty
Empty
Empty
Empty
Empty
Urinary
—
—
—
—
—
—Histologic lesions involved the respiratory (3/6, 50%), integumentary (2/6, 33%), hepatobiliary (3/6, 50%), hematopoietic/lymphoreticular (3/6, 50%), digestive (3/6, 50%), sensory (2/6, 33%), and nervous systems (1/6, 16%) (Table3). The lesions ranged from incidental (no effect on the animal) to significant (some effect on the animal). There was no commonality of lesions. Endoparasitism was a common finding in the liver (hepatobiliary) (3/6, 50%) and lung (respiratory system) (3/6, 50%). Parasites, including nematodes in the lung (Figure 6) and trematode ova in the liver (Figure 7), were not always evident in the lesions; however, the presence of eosinophils and granulomatous inflammation were supportive of their presence. In addition to inflammation in the liver, there were biliary hyperplasia (increased number of bile ducts) and fibrosis of the portal tracts. The changes in the lung and liver denoted chronic inflammation. A single emaciated porpoise had lesions suggestive of septicemia including splenic necrosis and lymphoid depletion; however, bacteria were not observed. Other findings for this animal included superficial algal dermatitis (Figure 8) and pancreatic atrophy.Table 3
Specific histologic findings by system for the six harbor porpoises for which tissues were submitted for histopathologic evaluation. Each porpoise is listed by its field identification number.
System affected
JND003
KMS387
KMS389
KMS404
KMS417
MLC001
Body-general
—
—
—
—
—
—
Cardiovascular
—
—
—
—
—
—
Digestive
—
Mucosal hyperplasia
(1) Pancreas-zymogen granule depletion,(2) Colitis
—
—
Eosinophilic enteritis
Endocrine
—
—
—
—
—
—
Hemato/lymphoreticular
—
Reactive lymph node
(1) Spleen-necrosis,(2) Lymph node depletion
—
—
(1) Hyperplasia,(2) Eosinophilia
Hepatobiliary
(1) Bile duct hyperplasia,(2) Pericholangitis
—
—
Biliary hyperplasia
Hepatic trematodiasis
—
Integumentary
—
—
Algal dermatitis
—
Steatitis
—
Musculoskeletal
—
—
—
—
—
—
Nervous
—
—
—
—
Myelin sheath swelling
—
Reproductive
—
—
—
—
—
—
Respiratory
—
Eosinophilic broncho-pneumonia
Verminous pneumonia
—
—
Eosinophilic interstitial pneumonia
Sensory
—
—
—
—
(1) Corneal edema,(2) Retinal atrophy
—
Urinary
—
—
—
—
—
—Figure 6
Microscopic section of lung from KMS389. Nematode larvae are present within regions of parenchymal destruction and fibrosis.Figure 7
Section of the liver from KMS417. Trematode ova are present within the portal tract surrounded by mixed inflammatory cells.Figure 8
Algae adhered to the superficial epithelium of KMS 389. Algae are arranged in dense sheets.Other lesions observed were incidental. The animal with a penetrating wound had inflammation of the adipose of the site of puncture (steatitis); however, there was no evidence of systemic infection related to this wound. Perimortem hypoxic changes including myelin sheath swelling in the brain were observed in one porpoise and mild retinal atrophy and corneal edema in another, with the latter likely resulting from superficial trauma perhaps at the time of stranding. Two porpoises had mild eosinophilic inflammation in the small and large intestine that may have been associated with parasitic infection. Lymph nodes in two animals were reactive with one lymph node containing eosinophils in increased numbers. While a cause of this was not evident, it does indicate antigenic stimulation.
## 4. Discussion
Both 2005 (the declared UME) and 1999 (an undeclared UME) sustained stranding levels that exceeded the UME threshold indicators for a marked increase in strandings for harbor porpoises in NC. Using the threshold criteria, and because stranding frequency in 1999 was higher than in that 2005, there is justification for considering 1999 as a UME year for harbor porpoises. The characteristics of porpoise strandings in NC remained similar throughout the years except for shifts in timing of strandings between UME and non-UME years, albeit all were within the normal timeframe. In addition, during UME years twice as many carcasses had signs of HI when it was possible to determine whether an interaction occurred (HI-FI, HI-Other, and HI-No only), while there was an increase in HI-CBD strandings. While this finding was not statistically significant, the proportions of HI-FI during UME years were similar to the 63% of carcasses with entanglement lesions documented in the mid-Atlantic from 1994 to 1996 [25]. Although the preponderance of HI-CBD may negatively bias the number of strandings known to be HI, no correction factor could be applied to each year to adjust for the CBD designations. Nonetheless, bycaught porpoises generally are in good or moderate nutritional condition or not emaciated [22, 25, 38], while in 2005 half of the carcasses were emaciated.No cause of the 2005 event in NC was found from gross and histologic findings, possibly due to the low number of specimens examined for pathology. Nonetheless, necropsy and histopathology findings did not differ significantly from other published reports from harbor porpoises, including parasite infestation (e.g., [11, 12, 22, 39]). While these parasites may have some effect upon these animals, it is unlikely they caused the strandings. One porpoise had lesions suggestive of possible septicemia based on lymph node depletion and splenic necrosis. However, there was no evidence of inflammation in other organs or bacteria in the lesions. Some types of organ lesions were considered mild or incidental without a net effect upon the animal. In contrast, other findings, such as zymogen granule depletion in the pancreas, are indicators of the overall body condition (e.g., emaciation). Of the three emaciated specimens, zymogen granule depletion was observed in a single porpoise. Some animals may have had disease processes that were not determined due to poor carcass condition and histologically nondiagnostic samples. Nonetheless, in the animals examined, no overwhelming systemic disease or infection was found. Therefore, if the six examined animals represent a true cross-section of the stranded population, the cause of strandings is unlikely to be infectious in nature. Although gross findings from the 2005 strandings provide the first indication of interspecific aggression in NC, the rate was low suggesting it was not a primary cause of the UME.Diagnostic testing forBartonella infection was previously reported for the live harbor porpoises found in the estuary in 2005 [9, 10]. In addition to these porpoises, Bartonella infection was found in other stranded cetaceans [10] and loggerhead sea turtles (Caretta caretta) from NC [40]. Maggi et al. [9] suggested that “bartonellosis may become an important emerging marine mammal infectious disease.” However, the extent of Bartonella infection among marine mammal populations and its results are not known because (1) stranded specimens are not routinely tested, (2) subtle effects of Bartonella prevent analysis of suspected cases, and (3) Bartonella can be difficult to detect [10]. In addition, marine mammals may be asymptomatic carriers similar to domestic and free-ranging terrestrial felids [41, 42]. It is unlikely, however, that Bartonella infection was responsible for the UME in 2005 based on the lack of histologic findings, such as uveitis and myocarditis, observed in other species.The majority of harbor porpoise strandings in NC, during UME and non-UME years, are young-of-year (YOY). Harbor porpoises are synchronized, seasonal breeders [43, 44]. In the western North Atlantic, most females calve annually with peak parturition in May [36]. Lactation duration is mostly speculative, but it appears to be eight to 12 months [43]. Given the month of stranding and body length (predicted length at 1 yr = 118 cm, [35]), most of these YOYs are approximately the size at weaning, and they would be 9–11 months of age. Porpoise strandings in Maryland, Virginia, and NC during 1994–1996 were also predominantly YOY [25]. YOY may be more common in the stranding record because they have a higher mortality rate [43]. For example, as newly weaned animals they are likely to be novice foragers, and even though juveniles have some of the thickest blubber [35], weight loss can be dramatic for porpoises not feeding [45]. For an animal with such important thermoregulatory needs and given that most were newly weaned, emaciation would be extremely deleterious due to physiologic stress associated with inadequate protection from cold water and lack of nutrients, including electrolytes and calories. Of the animals in 2005 that could be categorized as emaciated or robust, almost half were emaciated. Whether the emaciation was the primary cause of death, possibly resulting from recently weaned individuals being unable to forage on their own, or a secondary effect of undetected pathologies is unknown.Spatial segregation may also contribute to the prevalence of YOY strandings. Cox et al. [25] found that the mean length of HI-FI stranded porpoises along the mid-Atlantic coast of the USA was significantly smaller than that of porpoises documented as bycatch by fishery observers. Because most of the bycaught animals were entangled far from shore, they concluded that spatial segregation occurs between mature and immature animals resulting in a decreased likelihood of mature animals stranding. In addition, immature porpoises from the North Sea to the western Baltic Sea have been shown to have larger ranges than mature animals [46]. Thus, if YOYs are closer to shore, they likely would be more represented in the stranding record.Elevated strandings of harbor porpoises have been reported elsewhere. Notably, in a study of 55 stranded porpoises from 1990 to 2000, the number of strandings increased multifold along the Belgium and northern France coasts during 1999 [47]. The primary findings included emaciation (60%), bronchopneumonia (49%), and parasitosis (51%), while 70% had empty stomachs. Only 15% were attributed to bycatch. The authors suggested that the increase in strandings may have been due to an increase in the number of porpoises in the southern North Sea, possibly due to a shift in distribution during the latter years of the study and particularly in 1999, because the number of strandings in the nearby English Channel had also increased during this time. Along the nearby coasts of the Netherlands, porpoise strandings increased from the late 1990s through 2007, also presumably due to migration of primarily juvenile porpoises into the southern North Sea, with some possible contribution from inconsistent stranding-response effort over time [48]. A particularly notable increase in 2006 was not addressed. Large fluctuations within a small part of the range of harbor porpoises have been reported off the coast of Scotland [49], so local increases in abundance combined with similar stranding rates could result in a multifold increase in frequency of strandings. An increase in Danish strandings during a 9-day period in 2005 was declared a UME [24]. The incidence of potentially bycatch-related injuries during this event was higher than that in non-UME years 2003–2008, and the presence of naval activity correlated in models with higher rates of strandings. In 2007, a mass mortality of harbor porpoises and harbor seals (Phoca vitulina) was reported during a 2-month period along the Swedish coast [50]. The cause appeared to be an unknown pathogenic virus. Elevated strandings of harbor porpoises caused primarily by aggressive interactions with bottlenose dolphins occurred along the central coast of California from 2007–2009 [18]. Thus, the cause of unusually high stranding frequencies can be caused by various unrelated factors and the cause of harbor porpoise unusual stranding events in the western Atlantic and Belgium/northern France in 1999 [47] or the Danish coast in 2005 [24] seems unrelated. The events have in common high rates of emaciation and empty stomachs as well as parasitosis, a common finding in stranded harbor porpoises (e.g., [11, 22]), but not an infectious disease. In addition, harbor porpoises in the eastern and western Atlantic comprise separate stocks and little, if any, mixing occurs [51].The use of a quantitative approach, such as developing a threshold, to define a marked increase in the magnitude of strandings relative to historic levels provides a relatively objective and straightforward means of evaluating whether an event is occurring or occurred and how elevated stranding numbers are compared among years. When strandings occur year-round, such as for harbor porpoises in California, seasonal adjustments can remove variability that may obscure true unusual seasonal increases in strandings [18]. Detection of anomalies in stranding patterns may be enhanced by including the influence of carcass drift [52]. These methods have in common use of a quantitative, objective means to compare potentially elevated numbers to average stranding patterns. Reevaluating UMEs in light of additional time-series data can confirm UMEs or, possibly, help determine if a gradual increase or decrease in number of strandings is resulting in a shifting threshold.A UME indicator is needed in real time to ascertain that an event is occurring. In the USA, formal declaration of a UME provides opportunity to request/obtain support for enhanced response and beneficial oversight to ensure standardized sampling and testing [32]. For harbor porpoises in NC, weekly assessment is an appropriate metric because the stranding season is relatively contracted, and strandings are sufficiently infrequent in many years that a finer-scale time frame could not be supported. For other situations, more or less frequent comparisons may be appropriate, including biweekly [53], monthly [54], seasonally [18, 34, 52], or annually [55]. Retrospective examination of annual stranding numbers may provide a different perspective, such as the current finding that harbor porpoise strandings in 2003 exceed the annual stranding threshold and, thus, potentially could have been a UME. Such retrospective information will not help with current stranding response, including implementing specific protocols adopted for an UME, but may assist with detecting future UMEs by influencing which years are included for calculating the threshold. This approach also assists with interpreting historical stranding data. For example, from 1975 to 1989, harbor porpoises were reported stranding in NC in low numbers except for the spring of 1977 when 60 porpoise strandings were documented [4]. It is possible that the reported numbers across those years underestimated the true number of strandings because a comprehensive stranding network was not yet developed, but in 1977 the reported level would have exceeded the thresholds developed in recent years when stranding reports were more systematic and reliable.In NC, the harbor porpoise is a challenging species for robust stranding response because, per our long-term observations, more than most dolphins or whales these small carcasses can be difficult to detect on beaches, wash out at high tides fairly easily, are consumed quickly by gulls and other predators, and decompose rapidly, even during winter. Almost certainly, the number of porpoises detected is negatively biased. A more robust response for this species would have required stationing teams of responders along the 160 km of coast where the majority of porpoise strand. However, when UMEs occur over short periods, there frequently is insufficient time to implement this type of increased response. As a result, it is often possible to determine that an unusually high number of porpoises are stranded without obtaining sufficient information from those strandings to determine the cause of the event.
### 4.1. Conclusions
Harbor porpoises strand annually along NC beaches in highly variable numbers. Periodically, increases in the frequency of standings result in Unusual Mortality Events. The cause of the most recent UME, in 2005, could not be determined. Relative to non-UME years and to an undeclared UME during 1999, there were no significant differences in age class, sex ratio, or spatial distribution of strandings and only a suggestion of an increase in fishery interactions. There was a significant temporal effect, with a peak in strandings during one month rather than more distributed over 3 months; however, they occurred within the normal timeframe of porpoise strandings. No overall cause of the 2005 event in NC was found from gross and histologic findings and, except for parasite infestation typical for harbor porpoises, there was no commonality in findings and no pervasive evidence of infectious disease. Potential unexplored explanatory factors include an increase in mortality rate due to an unidentified cause, such as reduced prey availability, an increase in strandings due to changes in abundance or distribution off the NC coast, or a shift in environmental conditions such as wind [56–58]. Response to harbor porpoise UMEs is especially challenging, particularly along the vast expanses of NC beaches, requiring additional effort to obtain carcasses in sufficient condition to determine the cause of these events.
## 4.1. Conclusions
Harbor porpoises strand annually along NC beaches in highly variable numbers. Periodically, increases in the frequency of standings result in Unusual Mortality Events. The cause of the most recent UME, in 2005, could not be determined. Relative to non-UME years and to an undeclared UME during 1999, there were no significant differences in age class, sex ratio, or spatial distribution of strandings and only a suggestion of an increase in fishery interactions. There was a significant temporal effect, with a peak in strandings during one month rather than more distributed over 3 months; however, they occurred within the normal timeframe of porpoise strandings. No overall cause of the 2005 event in NC was found from gross and histologic findings and, except for parasite infestation typical for harbor porpoises, there was no commonality in findings and no pervasive evidence of infectious disease. Potential unexplored explanatory factors include an increase in mortality rate due to an unidentified cause, such as reduced prey availability, an increase in strandings due to changes in abundance or distribution off the NC coast, or a shift in environmental conditions such as wind [56–58]. Response to harbor porpoise UMEs is especially challenging, particularly along the vast expanses of NC beaches, requiring additional effort to obtain carcasses in sufficient condition to determine the cause of these events.
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*Source: 289892-2013-09-30.xml* | 289892-2013-09-30_289892-2013-09-30.md | 67,862 | Unusual Mortality Events of Harbor Porpoise Strandings in North Carolina, 1997–2009 | Aleta A. Hohn; David S. Rotstein; Barbie L. Byrd | Journal of Marine Biology
(2013) | Biological Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2013/289892 | 289892-2013-09-30.xml | ---
## Abstract
A marked increase in the frequency of harbor porpoises (Phocoena phocoena) stranded in North Carolina in 2005 was declared as an Unusual Mortality Event (UME). Strandings occurred in January through May when harbor porpoises are seasonally present. Increased stranding rates were measured relative to a threshold to determine that the UME was occurring. The threshold analysis also revealed elevated strandings during 1999, an undeclared UME year. Recovered carcasses during 1999 and 2005 accounted for 39% of 261 strandings during 1997–2009. During 2005, of 43 strandings, primary or secondary causes of mortality included fishery interactions, emaciation, and interspecific aggression. Apart from small but significant differences in timing and condition of strandings, composition of strandings during UME and non-UME years was similar, with most being young-of-the-year and occurring during March and April, north of Cape Hatteras. Porpoises had high levels of parasitic infestation typical for this species. However, no indication of infectious disease and no cause of the 2005 event were found from gross and histologic findings. Response to UMEs is challenging, particularly along the expanses of North Carolina beaches, requiring additional effort to obtain carcasses in sufficiently fresh condition to determine the cause of these events.
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## Body
## 1. Introduction
Of the six species in the odontocete family Phocoenidae, only one is found in the Atlantic Ocean, the harbor porpoise (Phocoena phocoena). Members of this family, including the harbor porpoise, generally occur at high latitude, while harbor porpoises are found only in the northern hemisphere [1]. Although it is primarily a cold-water temperate and boreal species, documented takes in gillnet fisheries in the western mid-Atlantic region in winter [2] support the mid-Atlantic coast of the United States of America (USA) being part of the normal winter range for the species. Further, harbor porpoises are one of the most commonly stranded species along the extensive beaches of North Carolina (NC) [3]. Historical data indicate that along the US Atlantic coast only Massachusetts has more documented strandings than NC [4].Worldwide, harbor porpoise strandings have been associated with infectious and noninfectious diseases. Infectious diseases include morbillivirus (e.g., [5, 6]), herpesvirus [5], brucellosis [7, 8], bartonellosis [9, 10], and verminous pneumonia [6, 11, 12]. Papillomavirus has been reported to result in self-limiting cutaneous lesions rather than mortalities [13–15]. Noninfectious diseases found in harbor porpoises include colloid goiter [16] and dystocia [17]. Domoic acid toxicosis was identified in harbor porpoises from California [18]. From detailed postmortem examinations of 41 stranded harbor porpoises from the United Kingdom (UK), parasitic and bacterial pneumonia were common causes of death and nonfatal parasitic infestation was common [17]. Jepson et al. [19] found a correlation between body burdens of polychlorinated biphenyls (PCBs) and health status of harbor porpoises in the United Kingdom; animals with infectious diseases had higher body burdens of PCBs.Harbor porpoise mortalities also occur as a result of nondisease factors. Fishery interactions have been widely documented (e.g., [17, 20–24], including along the Atlantic coast of the USA. For example, fishery interactions in gillnets have been observed by at-sea observers from the Gulf of Maine to the mid-Atlantic [2] as well as determined from the presence of entanglement lesions on stranded harbor porpoises along the coasts of Maryland, Virginia, and NC since at least the mid-1990s [25]. During 1997–2008 in NC, Byrd et al. [3] documented that about 21% of stranded porpoises for which it was possible to document whether a human interaction occurred (n=52) showed entanglement lesions consistent with fishing gear. Another 13% were mutilated in a manner consistent with mutilation seen on carcasses with entanglement lesions [26, 27]; although the former were too decomposed to determine if entanglement lesions were present, the type of mutilation infers that they also died due to fishery interactions. Apart from human interactions, harbor porpoises are also susceptible to interactions with dolphins. Blunt-force trauma likely due to aggressive interactions with bottlenose dolphins (Tursiops truncatus) was identified as the most common identified cause of death in a multiyear sample of harbor porpoise strandings from California [18]. The findings were supported by direct observations of aggressive behaviors of bottlenose dolphins toward harbor porpoises in California [28]. Harassment by Pacific white-sided dolphins (Lagenorhynchus obliquidens) of a neonatal harbor porpoise also was observed in Puget Sound, Washington, and this porpoise ultimately died [29]. Furthermore, in a study of 106 stranded harbor porpoises in the UK, the majority had internal and external traumatic injuries attributed to aggressive interactions between the porpoises and bottlenose dolphins [30]. The authors suggested that dolphin-induced porpoise mortality might result in a significant overall source of mortality for harbor porpoises in that area.While winter strandings in NC are common, the number of strandings per year is highly variable. In March 2005, so many harbor porpoises were stranding that, at times, responders needed to continuously drive beaches any given day, intermittently loading carcasses into the truck instead of responding to strandings individually. By late March, the number of reported strandings was sufficiently high that it triggered a request to the Working Group on Marine Mammal Unusual Mortality Events (WGMMUME) on 30 March 2005, that the strandings be designated as an Unusual Mortality Event (UME) (MMPA 16 U.S.C. 1361 et seq.) [31, 32] (http://www.nmfs.noaa.gov/pr/health/mmume/criteria.htm). The purpose of this study was to (1) evaluate the strandings in 2005 relative to other years in order to characterize the UME and (2) describe gross and histologic findings from carcasses that stranded during the 2005 event.
## 2. Materials and Methods
### 2.1. Stranding Response and Data Collection
Members of the stranding network collected basic, or Level A, data (e.g., species, geographic coordinates, straight length, and sex; [33]) whenever possible for each harbor porpoise recovered in NC (Figure 1). Level A data also include a condition code characterizing the stage of decomposition: (1) live animal, (2) carcass—fresh dead, (3) carcass—moderate decomposition, (4) carcass—advanced decomposition, (5) carcass—mummified or skeletal remains, or (6) dead but unknown because carcass was not recovered. Additionally, strandings were examined for signs of human interaction (HI) [27], particularly for indications of fishery interactions (HI-FI) [34]. Each carcass was assigned to a HI category: positive for fishery interactions (HI-FI), positive for human interactions not attributable to fisheries (HI-Other), negative for human interactions (HI-No), or could not be determined if a human interaction occurred (HI-CBD) [34]. Carcasses were also examined for signs of interspecific aggression, such as rake marks [30]. For this study, stranding data were extracted for the period 1997–2009; relatively consistent coast-wide coverage by the stranding network began in 1997 [3], providing reliable data in comparison to other years, and the last complete year for harbor porpoise data in the NC database was 2009.Figure 1
Coastal North Carolina. The barrier islands east of the island Bogue Banks north to the Virginia border are called the Outer Banks. The star corresponds to the end of Highway 12, after which access to the area to the north is by beach only.
### 2.2. Determination of the 1999 and 2005 Events as UMEs
The applicable UME criterion for the declaration of this event was “a marked increase in the magnitude…[of] strandings when compared to prior records” (http://www.nmfs.noaa.gov/pr/health/mmume/criteria.htm). Thus, stranding rates of harbor porpoises during 2005 were compared to historical average strandings starting from 1997. Data from 1999 were excluded from the historical average because of an extraordinarily high number of strandings of harbor porpoises that year. These strandings likely represented an undeclared UME, in part because the complete “historical” record at that time encompassed only the prior two years.Marked increases in the magnitude of strandings were defined as stranding frequencies that exceeded the historical overall mean plus two standard deviations (SDs) [31], in this case by week. The weekly mean plus two SDs is hereafter referred to as the weekly UME threshold. Weeks consisted of 7-day increments by Julian date starting on 1 January. The number of strandings per week in 2005 was compared to the historical UME threshold for that week calculated from data from 1997–2004 (excluding 1999, as noted above). This indicator is referred to as UME threshold A. To determine whether the 2005 event would have been a UME if a longer time series of stranding data were available, an a posteriori threshold analysis was conducted that also included stranding data from 2006–2009 (the longer time series is hereafter referred to as UME threshold B). To determine if a UME declaration for 1999 would have been warranted, similar comparisons were made between data from 1999 and UME thresholds A and B. The focus for the weekly monitoring was on detecting elevated stranding rates in short periods of time during the event. To evaluate whether strandings were elevated when retrospectively summed by year, annual strandings during 2005 and 1999 were compared to the annual mean plus 2 SDs using years in a manner comparable to weekly thresholds A and B.
### 2.3. Characteristics of Harbor Porpoises Stranded in North Carolina
Contingency table analysis was used to test for effects of month, condition, sex ratio, age-class, and HI category on the relative frequency of strandings that occurred during the declared (2005) and undeclared (1999) UME and non-UME years. For temporal effects, calendar month was used instead of week due to the excessive number of zeros and small values in the weekly time series. Analyses of condition excluded Code 6 carcasses because their condition and disposition were unknown. When both sex and length were recorded, strandings were assigned to age-class categories: (1) young-of-year (YOY) ≤118 cm [35], (2) juvenile = 119–134 cm for males [35] and 119–142 cm for females [36], and (3) mature >135 cm for males and >142 cm for females. Because of sexual dimorphism in mature porpoises, carcasses not identified to sex were excluded if lengths were 119–142 cm; that is, all animals <119 cm were considered YOYs, and all animals of either sex >142 cm were considered mature. Independence in parameters between UME and non-UME years was tested using Fisher’s exact tests due to small sample sizes in some cells and the skewed distribution of observations, for example, few strandings occurred in the first or last months of the timeframe when strandings typically occur. When significant P values (P≤0.05) indicated lack of fit, standardized residuals (>|1.96|) from Chi-Square tests were used to identify in which cells significant differences occurred. All tests were conducted using SAS versus 9.3 (SAS Institute, 100 SAS Campus Drive, Cary, NC 27513-2414).
### 2.4. Pathology Investigation of 2005 Strandings
During the 2005 UME, intact carcasses were necropsied immediately or, if time did not allow for immediate necropsy, frozen for future necropsy. When possible, histological samples were collected from euthanized animals and Code 2 carcasses that had not been frozen; samples collected from major organs (heart, lung, liver, kidney, spleen, liver, lymph nodes, and brain) and lesions were preserved in 10% formalin. Preserved subsamples were embedded in tissue cassettes, sectioned at 5 to 7μ, and stained with hematoxylin and eosin. Special stains, Periodic acid-Schiff (PAS) and Gomori-Grocott methenamine silver (GMS) for fungi and algae, were used as needed. All slides were examined by a single pathologist, DSR. Limited necropsies were conducted on carcasses in poor condition. Only external examination for gross observations, such as emaciation, mutilation, or scavenger damage, was possible for other carcasses. Contingency table analysis with Fisher’s exact test was used to test for differences in relative frequency of emaciated animals between the declared (2005) and undeclared (1999) UME and the non-UME years.
## 2.1. Stranding Response and Data Collection
Members of the stranding network collected basic, or Level A, data (e.g., species, geographic coordinates, straight length, and sex; [33]) whenever possible for each harbor porpoise recovered in NC (Figure 1). Level A data also include a condition code characterizing the stage of decomposition: (1) live animal, (2) carcass—fresh dead, (3) carcass—moderate decomposition, (4) carcass—advanced decomposition, (5) carcass—mummified or skeletal remains, or (6) dead but unknown because carcass was not recovered. Additionally, strandings were examined for signs of human interaction (HI) [27], particularly for indications of fishery interactions (HI-FI) [34]. Each carcass was assigned to a HI category: positive for fishery interactions (HI-FI), positive for human interactions not attributable to fisheries (HI-Other), negative for human interactions (HI-No), or could not be determined if a human interaction occurred (HI-CBD) [34]. Carcasses were also examined for signs of interspecific aggression, such as rake marks [30]. For this study, stranding data were extracted for the period 1997–2009; relatively consistent coast-wide coverage by the stranding network began in 1997 [3], providing reliable data in comparison to other years, and the last complete year for harbor porpoise data in the NC database was 2009.Figure 1
Coastal North Carolina. The barrier islands east of the island Bogue Banks north to the Virginia border are called the Outer Banks. The star corresponds to the end of Highway 12, after which access to the area to the north is by beach only.
## 2.2. Determination of the 1999 and 2005 Events as UMEs
The applicable UME criterion for the declaration of this event was “a marked increase in the magnitude…[of] strandings when compared to prior records” (http://www.nmfs.noaa.gov/pr/health/mmume/criteria.htm). Thus, stranding rates of harbor porpoises during 2005 were compared to historical average strandings starting from 1997. Data from 1999 were excluded from the historical average because of an extraordinarily high number of strandings of harbor porpoises that year. These strandings likely represented an undeclared UME, in part because the complete “historical” record at that time encompassed only the prior two years.Marked increases in the magnitude of strandings were defined as stranding frequencies that exceeded the historical overall mean plus two standard deviations (SDs) [31], in this case by week. The weekly mean plus two SDs is hereafter referred to as the weekly UME threshold. Weeks consisted of 7-day increments by Julian date starting on 1 January. The number of strandings per week in 2005 was compared to the historical UME threshold for that week calculated from data from 1997–2004 (excluding 1999, as noted above). This indicator is referred to as UME threshold A. To determine whether the 2005 event would have been a UME if a longer time series of stranding data were available, an a posteriori threshold analysis was conducted that also included stranding data from 2006–2009 (the longer time series is hereafter referred to as UME threshold B). To determine if a UME declaration for 1999 would have been warranted, similar comparisons were made between data from 1999 and UME thresholds A and B. The focus for the weekly monitoring was on detecting elevated stranding rates in short periods of time during the event. To evaluate whether strandings were elevated when retrospectively summed by year, annual strandings during 2005 and 1999 were compared to the annual mean plus 2 SDs using years in a manner comparable to weekly thresholds A and B.
## 2.3. Characteristics of Harbor Porpoises Stranded in North Carolina
Contingency table analysis was used to test for effects of month, condition, sex ratio, age-class, and HI category on the relative frequency of strandings that occurred during the declared (2005) and undeclared (1999) UME and non-UME years. For temporal effects, calendar month was used instead of week due to the excessive number of zeros and small values in the weekly time series. Analyses of condition excluded Code 6 carcasses because their condition and disposition were unknown. When both sex and length were recorded, strandings were assigned to age-class categories: (1) young-of-year (YOY) ≤118 cm [35], (2) juvenile = 119–134 cm for males [35] and 119–142 cm for females [36], and (3) mature >135 cm for males and >142 cm for females. Because of sexual dimorphism in mature porpoises, carcasses not identified to sex were excluded if lengths were 119–142 cm; that is, all animals <119 cm were considered YOYs, and all animals of either sex >142 cm were considered mature. Independence in parameters between UME and non-UME years was tested using Fisher’s exact tests due to small sample sizes in some cells and the skewed distribution of observations, for example, few strandings occurred in the first or last months of the timeframe when strandings typically occur. When significant P values (P≤0.05) indicated lack of fit, standardized residuals (>|1.96|) from Chi-Square tests were used to identify in which cells significant differences occurred. All tests were conducted using SAS versus 9.3 (SAS Institute, 100 SAS Campus Drive, Cary, NC 27513-2414).
## 2.4. Pathology Investigation of 2005 Strandings
During the 2005 UME, intact carcasses were necropsied immediately or, if time did not allow for immediate necropsy, frozen for future necropsy. When possible, histological samples were collected from euthanized animals and Code 2 carcasses that had not been frozen; samples collected from major organs (heart, lung, liver, kidney, spleen, liver, lymph nodes, and brain) and lesions were preserved in 10% formalin. Preserved subsamples were embedded in tissue cassettes, sectioned at 5 to 7μ, and stained with hematoxylin and eosin. Special stains, Periodic acid-Schiff (PAS) and Gomori-Grocott methenamine silver (GMS) for fungi and algae, were used as needed. All slides were examined by a single pathologist, DSR. Limited necropsies were conducted on carcasses in poor condition. Only external examination for gross observations, such as emaciation, mutilation, or scavenger damage, was possible for other carcasses. Contingency table analysis with Fisher’s exact test was used to test for differences in relative frequency of emaciated animals between the declared (2005) and undeclared (1999) UME and the non-UME years.
## 3. Results
### 3.1. Determination of the 1999 and 2005 Events as UMEs
From 1997 to 2009, 262 harbor porpoise strandings were reported, ranging annually from 4 (1998) to 59 (1999), with an overall annual mean of 20.1 (SD = 17.15) and a mean of 14.5 (SD = 10.7) when 2005 and 1999 were excluded. Thirty-nine percent of the strandings occurred during 1999 and 2005. On a weekly basis, elevated strandings occurred during both 2005 (declared UME) and 1999 (undeclared UME). The weekly stranding frequency in 2005 exceeded the corresponding weekly threshold A from week 9 (26 February–4 March) through week 12 (19–25 March) (Figure2). These data were used to make the initial declaration of a UME. In the a posteriori analysis, the same weeks exceeded threshold B with the addition of week seven (Figure 2). The weekly stranding frequency in 1999 exceeded the corresponding weekly thresholds A and B in weeks 12–16 (Figure 2). Thresholds were also exceeded in weeks 4 and 6 reflecting only one stranding when the mean number of strandings was close to zero (Figure 2). Week 13 in 1999 had more porpoise strandings than the annual total in all but three years: 1999, 2003, and 2005. Retrospectively, the annual stranding frequency exceeded the annual thresholds A and B during both 2005 and 1999, while 2003 exceeded threshold B (Figure 2).(a) Weekly harbor porpoise strandings in 1999 (darker blue bars) and 2005 (lighter blue bars) compared to weekly threshold A (mean + 2 standard deviations: 1997-1998, 2000–2004) (black horizontal solid line) and threshold B (mean + 2 standard deviations: 1997-1998, 2000–2004, 2006–2009) (red horizontal dashed line). (b) Annual harbor porpoise strandings during 1997–2009 (blue bars) compared to annual threshold A (black horizontal solid line) and threshold B (red horizontal dashed line).
(a)
(b)
### 3.2. Characteristics of Harbor Porpoises Stranded in North Carolina
Overall, harbor porpoises stranded between January and May, but primarily in February through April (Figure3). Relative to non-UME years, in 2005, more strandings occurred in March and fewer occurred in April (P=0.03), while in 1999, in addition to the notable peak in March (Figure 3), fewer strandings occurred in February (P=0.001) (Figure 3). These opposite patterns of earlier versus later strandings were emphasized when comparing 2005 to 1999 (P=0.0007).Harbor porpoise strandings by month (a), condition code (b), and human interaction (HI) category (c) as a percentage of the total for 1999 (n=59), 2005 (n=43), and non-UME years (n=160). Condition codes are (1) live animal, (2) carcass-fresh dead, (3) carcass-moderately decomposed, (4) carcass-advanced decomposition, (5) carcass-mummified or skeletal remains, and (6) disposition unknown. HI categories are HI-FI (evidence of Fishery Interaction), HI-Other (other evidence of HI), HI-No (no evidence of HI), and HI-CBD (HI could not be determined).
(a)
(b)
(c)During non-UME years, harbor porpoises were recovered from the NC border with Virginia to Topsail Beach (~410 km of coastline) (Figure4); 84% of strandings occurred north of Cape Hatteras (~160 km of coastline). The spatial patterns were similar in 2005 (77% north of Cape Hatteras) and 1999 (88% north of Cape Hatteras), although in 2005 most of the strandings occurred in the northern half of the coast between the Virginia Line and Cape Hatteras, and in 1999 most strandings were in the southern half. Strandings inshore were rare, occurring only twice and both in 2005.Figure 4
Annual harbor porpoise strandings in North Carolina, 1997–2009. In addition, in 2009 one stranding was recovered in Topsail Beach (see Figure1).Biological characteristics during non-UME and UME years were similar. Sex could be determined for 78% of stranded harbor porpoises between 1997 and 2009, with almost equal numbers of females and males (105 females, 99 males). The sex ratio did not differ between non-UME years and 2005 or 1999 (P=0.26 and P=1.00, resp.), or between 2005 and 1999 (P=1.00). For both sexes, stranded porpoises ranged from 84 to 169 cm in total length (n=99, actual length, not estimated) during non-UME years, from 99 to 154 cm in 2005 (n=31), and from 107 to 143 cm in 1999 (n=39). The relative age structure (YOY, juvenile, and adult) did not differ between non-UME years and 2005 (females, P=0.26; males, P=0.41) or 1999 (females P=0.48; males P=0.18) or between 2005 and 1999 (females, P=0.74, males, P=0.41). The most prevalent age class in all years and for both sexes was YOY (72%) (Figure 5); none of the few mature animals stranded during the study period was recovered in 1999 (Figure 5), and only one was documented in 2005. Only two harbor porpoises were pregnant, one in March 2001 with a 54 cm fetus and the other in January 2006 with a 40 cm fetus. Neither pregnant female was lactating. An additional 26 animals were measured (size range 89–136 cm), but sex could not be determined. Although it was not possible to categorize the single animal >136 cm as adult (if it was male) or juvenile (if it was female), 20 of the strandings CBD for sex were YOYs (≤118 cm).Age class categories by sex (female = 87; male = 82) of harbor porpoise strandings in North Carolina during 1997–2009: Young-of-Year (YOY) (≤118 cm); juvenile (females = 119–142 cm; males = 119–134 cm); mature (females ≥ 143 cm; males ≥ 135 cm). Strandings of unknown sex or for which lengths were estimated were excluded.
(a)
(b)Condition code was recorded for all 43 specimens in 2005. The majority of strandings were condition code 3 (51%) (Figure3). There was no evidence of differences in condition between non-UME years (mean condition code = 2.73, SD = 0.96) and 2005 (mean = 2.72, SD = 0.91) (P=0.35), but carcasses in 1999 were relatively more decomposed (mean condition code = 3.05, SD = 0.66) than those during non-UME years (P=0.02) or 2005 (P=0.07) (Figure 3). Live strandings (Code 1) were rare (n=14), occurring during only 7 of the 14 years in the time series and with not more than two in any non-UME year; 10 died (naturally or euthanized), 2 were released immediately, and 2 were released after rehabilitation. Whereas no live strandings were found in 1999, five occurred during 2005. Two of the live strandings in 2005 were recovered in estuarine waters, representing the only porpoise strandings recovered inshore during 1997–2009. The first inshore stranding occurred on 18 March when a harbor porpoise found swimming in a drainage canal was removed, roto tagged, and transported to ocean waters where it was released. The second occurred on 8 May in northern Currituck Sound and was euthanized. Subsequently, both animals tested positive for Bartonella infection [10]. The three other live strandings in 2005 were in poor condition and euthanized, one after sustaining serious injuries from being pecked by gulls (Larus sp.).Human interactions could not be determined (HI-CBD) for most carcasses during non-UME years (75%), 2005 (81%), or 1999 (81%) (Figure3). The relative frequency of carcasses assigned to the four HI categories (HI-FI, HI-Other, HI-No, and HI-CBD) was similar between non-UME years and 2005 (P=0.33) and 1999 (P=0.46) as well as between 2005 and 1999 (P=1.00). The relative frequency was also similar for carcasses when a human interaction could be determined, that is, when HI-CBD was excluded (non-UME years v. 2005, P=0.17; v. 1999, P=0.44; 2005 v. 1999, P=1.00). Although sample size was small, almost twice the rate of carcasses were HI during UME years (50% in 2005, 45% in 1999) than those during non-UME years (26%). In all years, entanglement lesions were the most common form of HI evidence (n=11), and one of those carcasses also had a slit along the abdomen and the dorsal fin was cut off (Table 1). All strandings categorized as HI-Other had similar mutilations, but decomposition, scavenger damage, or both prevented the determination of whether entanglement lesions were present or absent (Table 1). One of the HI-FI animals had a penetrating wound near the blowhole that might have been from a fishing gaff.Table 1
Information for harbor porpoise strandings during 1997–2009 categorized as positive for human interactions (HI), either HI-FI (fishery interaction) or HI-Other (other evidence of HI). CBD: could not be determined.
HI-category
Field number
Mo
Year
Condition code
Sex
Length (cm)
Mutilation
Body slit
Missing appendages
Scavenger damage
Entanglement lesion location
HI-FI
BRM001
3
1999
3
Female
132
No
No
No
Yes
Flukes
HI-FI
PTM041
3
1999
3
Female
—
CBD
No
No
Yes
Head, left flipper
HI-FI
HOF013
4
1999
3
Male
121
Yes
Yes
Yes
Yes
Peduncle
HI-FI
KMS099
2
2001
2
Male
117
No
No
No
Yes
Left fluke
HI-FI
KMS238
2
2003
2
Female
128
CBD
No
No
Yes
Right flipper, right fluke
HI-FI
CALO0408
4
2004
3
Female
112
N/R
No
No
N/R
Peduncle
HI-FI
KMS335
4
2004
2
Female
111
No
No
No
Yes
Right fluke
HI-FI
KMS336
4
2004
2
Female
115
No
No
No
Yes
Right fluke
HI-FI
KMS388
2
2005
3
CBD
108
No
No
No
Yes
Left flipper
HI-FI
KMS404
3
2005
2
Male
116
No
No
No
Yes
Head, both flippers
HI-FI
KMS417
4
2005
2
Female
—
No
No
No
No
Flipper
HI-Other
HOF011
3
1999
3
Female
—
Yes
Yes
Yes
Yes
N/A
HI-Other
JGM001
4
1999
3
Female
120
Yes
No
Yes
Yes
N/A
HI-Other
KMS121
4
2001
4
CBD
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT001
4
2003
3
Female
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT002
4
2003
3
Female
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT004
4
2003
3
Male
105
Yes
No
Yes
Yes
N/A
HI-Other
KTM009
4
2003
3
CBD
—
Yes
No
Yes
Yes
N/A
HI-Other
JND002
3
2005
4
Male
—
Yes
No
Yes
Yes
N/A
### 3.3. Pathology Findings from 2005 Strandings
Of the 42 carcasses recovered (one animal was released alive), few were of sufficient quality to assess gross pathology and fewer still were suitable for histologic assessment. Over half (n=27) of all carcasses sustained moderate to heavy scavenger damage (e.g., from gulls and foxes), often leaving no internal organs to examine or sample. Emaciation could be determined for only 17 carcasses and, of these, 9 were emaciated. There was no difference in the relative number of emaciated animals between non-UME years (60% emaciated) and 2005 (50% emaciated) (P=0.58) or 1999 (76% emaciated) (P=0.12) and a marginal difference between 1999 and 2005 (P=0.07). During 2005, an assessment of whether there were stomach contents was possible only for 21 strandings (13 empty: 10 HI-CBD, 2 HI-FI, and 1 HI-No; 8 with contents: 7 HI-CBD and 1 HI-No). Five porpoises had evidence of interspecific aggression; however, the presence/absence of evidence could not be determined for 31 porpoises. Limited necropsies were conducted for 14 carcasses, and only external exams were conducted for 23. Of the limited necropsies, five animals (all HI-CBD) had varying amounts of tracheal froth suggesting an agonal response consistent with live stranding or gear entanglement [37].Six (14%) animals received complete necropsies and histopathologic assessment. Three of these six animals were emaciated. Gross lesions were observed in four systems: sensory, respiratory, integumentary, and hepatobiliary (Table2). Overall, the integumentary and respiratory systems accounted for the greatest percentage of gross lesions, including scavenger lesions (3/6, 50%), entanglement lesions (2/6, 33%), a penetrating wound near the blowhole (1/6, 16%), fresh rake marks (1/6, 16%), adherent material to the fluke (1/6, 16%), verminous pneumonia (1/6, 16%), and pulmonary edema (1/6, 16%). In the hepatobiliary and sensory system, there were focal biliary hyperplasia (1/6, 16%) and pooled blood in the ears (1/6, 16%). All but one animal had stomach compartments devoid of contents.Table 2
Specific gross necropsy findings by system for the six harbor porpoises with submitted tissues for histopathologic evaluation. Each porpoise is listed by its field identification number. Cells for human interaction (HI) evidence are listed as follows: HI-FI (evidence of fishery interaction), HI-No (no evidence of HI), and HI-CBD (could not be determined).
System affected
JND003
KMS387
KMS389
KMS404
KMS417
MLC001
Body-general
—
—
Emaciation
—
Emaciation
Emaciation
Cardiovascular
—
—
—
—
—
—
Digestive
—
—
—
—
—
—
Endocrine
—
—
—
—
—
—
Hemato/lymphoreticular
—
—
—
—
—
—
Hepatobiliary
—
—
—
—
Focal biliary hyperplasia
—
Integumentary
Scavenger damage
Yes
Yes
Yes
Yes
HI evidence
HI-CBD
HI-CBD
HI-CBD
HI-FI
HI-FI
HI-No
Interspecific aggression evidence
CBD
CBD
No
CBD
Yes
No
Other
—
—
Adherent material on fluke
—
Penetrating wound near blowhole
—
Musculoskeletal
—
—
—
—
—
—
Nervous
—
—
—
—
—
—
Reproductive
—
—
—
—
—
—
Respiratory
Pulmonary edema
—
Verminous pneumonia
—
—
—
Sensory
—
—
—
—
Ears-pooled blood
Stomach contents
Full
Empty
Empty
Empty
Empty
Empty
Urinary
—
—
—
—
—
—Histologic lesions involved the respiratory (3/6, 50%), integumentary (2/6, 33%), hepatobiliary (3/6, 50%), hematopoietic/lymphoreticular (3/6, 50%), digestive (3/6, 50%), sensory (2/6, 33%), and nervous systems (1/6, 16%) (Table3). The lesions ranged from incidental (no effect on the animal) to significant (some effect on the animal). There was no commonality of lesions. Endoparasitism was a common finding in the liver (hepatobiliary) (3/6, 50%) and lung (respiratory system) (3/6, 50%). Parasites, including nematodes in the lung (Figure 6) and trematode ova in the liver (Figure 7), were not always evident in the lesions; however, the presence of eosinophils and granulomatous inflammation were supportive of their presence. In addition to inflammation in the liver, there were biliary hyperplasia (increased number of bile ducts) and fibrosis of the portal tracts. The changes in the lung and liver denoted chronic inflammation. A single emaciated porpoise had lesions suggestive of septicemia including splenic necrosis and lymphoid depletion; however, bacteria were not observed. Other findings for this animal included superficial algal dermatitis (Figure 8) and pancreatic atrophy.Table 3
Specific histologic findings by system for the six harbor porpoises for which tissues were submitted for histopathologic evaluation. Each porpoise is listed by its field identification number.
System affected
JND003
KMS387
KMS389
KMS404
KMS417
MLC001
Body-general
—
—
—
—
—
—
Cardiovascular
—
—
—
—
—
—
Digestive
—
Mucosal hyperplasia
(1) Pancreas-zymogen granule depletion,(2) Colitis
—
—
Eosinophilic enteritis
Endocrine
—
—
—
—
—
—
Hemato/lymphoreticular
—
Reactive lymph node
(1) Spleen-necrosis,(2) Lymph node depletion
—
—
(1) Hyperplasia,(2) Eosinophilia
Hepatobiliary
(1) Bile duct hyperplasia,(2) Pericholangitis
—
—
Biliary hyperplasia
Hepatic trematodiasis
—
Integumentary
—
—
Algal dermatitis
—
Steatitis
—
Musculoskeletal
—
—
—
—
—
—
Nervous
—
—
—
—
Myelin sheath swelling
—
Reproductive
—
—
—
—
—
—
Respiratory
—
Eosinophilic broncho-pneumonia
Verminous pneumonia
—
—
Eosinophilic interstitial pneumonia
Sensory
—
—
—
—
(1) Corneal edema,(2) Retinal atrophy
—
Urinary
—
—
—
—
—
—Figure 6
Microscopic section of lung from KMS389. Nematode larvae are present within regions of parenchymal destruction and fibrosis.Figure 7
Section of the liver from KMS417. Trematode ova are present within the portal tract surrounded by mixed inflammatory cells.Figure 8
Algae adhered to the superficial epithelium of KMS 389. Algae are arranged in dense sheets.Other lesions observed were incidental. The animal with a penetrating wound had inflammation of the adipose of the site of puncture (steatitis); however, there was no evidence of systemic infection related to this wound. Perimortem hypoxic changes including myelin sheath swelling in the brain were observed in one porpoise and mild retinal atrophy and corneal edema in another, with the latter likely resulting from superficial trauma perhaps at the time of stranding. Two porpoises had mild eosinophilic inflammation in the small and large intestine that may have been associated with parasitic infection. Lymph nodes in two animals were reactive with one lymph node containing eosinophils in increased numbers. While a cause of this was not evident, it does indicate antigenic stimulation.
## 3.1. Determination of the 1999 and 2005 Events as UMEs
From 1997 to 2009, 262 harbor porpoise strandings were reported, ranging annually from 4 (1998) to 59 (1999), with an overall annual mean of 20.1 (SD = 17.15) and a mean of 14.5 (SD = 10.7) when 2005 and 1999 were excluded. Thirty-nine percent of the strandings occurred during 1999 and 2005. On a weekly basis, elevated strandings occurred during both 2005 (declared UME) and 1999 (undeclared UME). The weekly stranding frequency in 2005 exceeded the corresponding weekly threshold A from week 9 (26 February–4 March) through week 12 (19–25 March) (Figure2). These data were used to make the initial declaration of a UME. In the a posteriori analysis, the same weeks exceeded threshold B with the addition of week seven (Figure 2). The weekly stranding frequency in 1999 exceeded the corresponding weekly thresholds A and B in weeks 12–16 (Figure 2). Thresholds were also exceeded in weeks 4 and 6 reflecting only one stranding when the mean number of strandings was close to zero (Figure 2). Week 13 in 1999 had more porpoise strandings than the annual total in all but three years: 1999, 2003, and 2005. Retrospectively, the annual stranding frequency exceeded the annual thresholds A and B during both 2005 and 1999, while 2003 exceeded threshold B (Figure 2).(a) Weekly harbor porpoise strandings in 1999 (darker blue bars) and 2005 (lighter blue bars) compared to weekly threshold A (mean + 2 standard deviations: 1997-1998, 2000–2004) (black horizontal solid line) and threshold B (mean + 2 standard deviations: 1997-1998, 2000–2004, 2006–2009) (red horizontal dashed line). (b) Annual harbor porpoise strandings during 1997–2009 (blue bars) compared to annual threshold A (black horizontal solid line) and threshold B (red horizontal dashed line).
(a)
(b)
## 3.2. Characteristics of Harbor Porpoises Stranded in North Carolina
Overall, harbor porpoises stranded between January and May, but primarily in February through April (Figure3). Relative to non-UME years, in 2005, more strandings occurred in March and fewer occurred in April (P=0.03), while in 1999, in addition to the notable peak in March (Figure 3), fewer strandings occurred in February (P=0.001) (Figure 3). These opposite patterns of earlier versus later strandings were emphasized when comparing 2005 to 1999 (P=0.0007).Harbor porpoise strandings by month (a), condition code (b), and human interaction (HI) category (c) as a percentage of the total for 1999 (n=59), 2005 (n=43), and non-UME years (n=160). Condition codes are (1) live animal, (2) carcass-fresh dead, (3) carcass-moderately decomposed, (4) carcass-advanced decomposition, (5) carcass-mummified or skeletal remains, and (6) disposition unknown. HI categories are HI-FI (evidence of Fishery Interaction), HI-Other (other evidence of HI), HI-No (no evidence of HI), and HI-CBD (HI could not be determined).
(a)
(b)
(c)During non-UME years, harbor porpoises were recovered from the NC border with Virginia to Topsail Beach (~410 km of coastline) (Figure4); 84% of strandings occurred north of Cape Hatteras (~160 km of coastline). The spatial patterns were similar in 2005 (77% north of Cape Hatteras) and 1999 (88% north of Cape Hatteras), although in 2005 most of the strandings occurred in the northern half of the coast between the Virginia Line and Cape Hatteras, and in 1999 most strandings were in the southern half. Strandings inshore were rare, occurring only twice and both in 2005.Figure 4
Annual harbor porpoise strandings in North Carolina, 1997–2009. In addition, in 2009 one stranding was recovered in Topsail Beach (see Figure1).Biological characteristics during non-UME and UME years were similar. Sex could be determined for 78% of stranded harbor porpoises between 1997 and 2009, with almost equal numbers of females and males (105 females, 99 males). The sex ratio did not differ between non-UME years and 2005 or 1999 (P=0.26 and P=1.00, resp.), or between 2005 and 1999 (P=1.00). For both sexes, stranded porpoises ranged from 84 to 169 cm in total length (n=99, actual length, not estimated) during non-UME years, from 99 to 154 cm in 2005 (n=31), and from 107 to 143 cm in 1999 (n=39). The relative age structure (YOY, juvenile, and adult) did not differ between non-UME years and 2005 (females, P=0.26; males, P=0.41) or 1999 (females P=0.48; males P=0.18) or between 2005 and 1999 (females, P=0.74, males, P=0.41). The most prevalent age class in all years and for both sexes was YOY (72%) (Figure 5); none of the few mature animals stranded during the study period was recovered in 1999 (Figure 5), and only one was documented in 2005. Only two harbor porpoises were pregnant, one in March 2001 with a 54 cm fetus and the other in January 2006 with a 40 cm fetus. Neither pregnant female was lactating. An additional 26 animals were measured (size range 89–136 cm), but sex could not be determined. Although it was not possible to categorize the single animal >136 cm as adult (if it was male) or juvenile (if it was female), 20 of the strandings CBD for sex were YOYs (≤118 cm).Age class categories by sex (female = 87; male = 82) of harbor porpoise strandings in North Carolina during 1997–2009: Young-of-Year (YOY) (≤118 cm); juvenile (females = 119–142 cm; males = 119–134 cm); mature (females ≥ 143 cm; males ≥ 135 cm). Strandings of unknown sex or for which lengths were estimated were excluded.
(a)
(b)Condition code was recorded for all 43 specimens in 2005. The majority of strandings were condition code 3 (51%) (Figure3). There was no evidence of differences in condition between non-UME years (mean condition code = 2.73, SD = 0.96) and 2005 (mean = 2.72, SD = 0.91) (P=0.35), but carcasses in 1999 were relatively more decomposed (mean condition code = 3.05, SD = 0.66) than those during non-UME years (P=0.02) or 2005 (P=0.07) (Figure 3). Live strandings (Code 1) were rare (n=14), occurring during only 7 of the 14 years in the time series and with not more than two in any non-UME year; 10 died (naturally or euthanized), 2 were released immediately, and 2 were released after rehabilitation. Whereas no live strandings were found in 1999, five occurred during 2005. Two of the live strandings in 2005 were recovered in estuarine waters, representing the only porpoise strandings recovered inshore during 1997–2009. The first inshore stranding occurred on 18 March when a harbor porpoise found swimming in a drainage canal was removed, roto tagged, and transported to ocean waters where it was released. The second occurred on 8 May in northern Currituck Sound and was euthanized. Subsequently, both animals tested positive for Bartonella infection [10]. The three other live strandings in 2005 were in poor condition and euthanized, one after sustaining serious injuries from being pecked by gulls (Larus sp.).Human interactions could not be determined (HI-CBD) for most carcasses during non-UME years (75%), 2005 (81%), or 1999 (81%) (Figure3). The relative frequency of carcasses assigned to the four HI categories (HI-FI, HI-Other, HI-No, and HI-CBD) was similar between non-UME years and 2005 (P=0.33) and 1999 (P=0.46) as well as between 2005 and 1999 (P=1.00). The relative frequency was also similar for carcasses when a human interaction could be determined, that is, when HI-CBD was excluded (non-UME years v. 2005, P=0.17; v. 1999, P=0.44; 2005 v. 1999, P=1.00). Although sample size was small, almost twice the rate of carcasses were HI during UME years (50% in 2005, 45% in 1999) than those during non-UME years (26%). In all years, entanglement lesions were the most common form of HI evidence (n=11), and one of those carcasses also had a slit along the abdomen and the dorsal fin was cut off (Table 1). All strandings categorized as HI-Other had similar mutilations, but decomposition, scavenger damage, or both prevented the determination of whether entanglement lesions were present or absent (Table 1). One of the HI-FI animals had a penetrating wound near the blowhole that might have been from a fishing gaff.Table 1
Information for harbor porpoise strandings during 1997–2009 categorized as positive for human interactions (HI), either HI-FI (fishery interaction) or HI-Other (other evidence of HI). CBD: could not be determined.
HI-category
Field number
Mo
Year
Condition code
Sex
Length (cm)
Mutilation
Body slit
Missing appendages
Scavenger damage
Entanglement lesion location
HI-FI
BRM001
3
1999
3
Female
132
No
No
No
Yes
Flukes
HI-FI
PTM041
3
1999
3
Female
—
CBD
No
No
Yes
Head, left flipper
HI-FI
HOF013
4
1999
3
Male
121
Yes
Yes
Yes
Yes
Peduncle
HI-FI
KMS099
2
2001
2
Male
117
No
No
No
Yes
Left fluke
HI-FI
KMS238
2
2003
2
Female
128
CBD
No
No
Yes
Right flipper, right fluke
HI-FI
CALO0408
4
2004
3
Female
112
N/R
No
No
N/R
Peduncle
HI-FI
KMS335
4
2004
2
Female
111
No
No
No
Yes
Right fluke
HI-FI
KMS336
4
2004
2
Female
115
No
No
No
Yes
Right fluke
HI-FI
KMS388
2
2005
3
CBD
108
No
No
No
Yes
Left flipper
HI-FI
KMS404
3
2005
2
Male
116
No
No
No
Yes
Head, both flippers
HI-FI
KMS417
4
2005
2
Female
—
No
No
No
No
Flipper
HI-Other
HOF011
3
1999
3
Female
—
Yes
Yes
Yes
Yes
N/A
HI-Other
JGM001
4
1999
3
Female
120
Yes
No
Yes
Yes
N/A
HI-Other
KMS121
4
2001
4
CBD
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT001
4
2003
3
Female
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT002
4
2003
3
Female
—
Yes
No
Yes
Yes
N/A
HI-Other
CMT004
4
2003
3
Male
105
Yes
No
Yes
Yes
N/A
HI-Other
KTM009
4
2003
3
CBD
—
Yes
No
Yes
Yes
N/A
HI-Other
JND002
3
2005
4
Male
—
Yes
No
Yes
Yes
N/A
## 3.3. Pathology Findings from 2005 Strandings
Of the 42 carcasses recovered (one animal was released alive), few were of sufficient quality to assess gross pathology and fewer still were suitable for histologic assessment. Over half (n=27) of all carcasses sustained moderate to heavy scavenger damage (e.g., from gulls and foxes), often leaving no internal organs to examine or sample. Emaciation could be determined for only 17 carcasses and, of these, 9 were emaciated. There was no difference in the relative number of emaciated animals between non-UME years (60% emaciated) and 2005 (50% emaciated) (P=0.58) or 1999 (76% emaciated) (P=0.12) and a marginal difference between 1999 and 2005 (P=0.07). During 2005, an assessment of whether there were stomach contents was possible only for 21 strandings (13 empty: 10 HI-CBD, 2 HI-FI, and 1 HI-No; 8 with contents: 7 HI-CBD and 1 HI-No). Five porpoises had evidence of interspecific aggression; however, the presence/absence of evidence could not be determined for 31 porpoises. Limited necropsies were conducted for 14 carcasses, and only external exams were conducted for 23. Of the limited necropsies, five animals (all HI-CBD) had varying amounts of tracheal froth suggesting an agonal response consistent with live stranding or gear entanglement [37].Six (14%) animals received complete necropsies and histopathologic assessment. Three of these six animals were emaciated. Gross lesions were observed in four systems: sensory, respiratory, integumentary, and hepatobiliary (Table2). Overall, the integumentary and respiratory systems accounted for the greatest percentage of gross lesions, including scavenger lesions (3/6, 50%), entanglement lesions (2/6, 33%), a penetrating wound near the blowhole (1/6, 16%), fresh rake marks (1/6, 16%), adherent material to the fluke (1/6, 16%), verminous pneumonia (1/6, 16%), and pulmonary edema (1/6, 16%). In the hepatobiliary and sensory system, there were focal biliary hyperplasia (1/6, 16%) and pooled blood in the ears (1/6, 16%). All but one animal had stomach compartments devoid of contents.Table 2
Specific gross necropsy findings by system for the six harbor porpoises with submitted tissues for histopathologic evaluation. Each porpoise is listed by its field identification number. Cells for human interaction (HI) evidence are listed as follows: HI-FI (evidence of fishery interaction), HI-No (no evidence of HI), and HI-CBD (could not be determined).
System affected
JND003
KMS387
KMS389
KMS404
KMS417
MLC001
Body-general
—
—
Emaciation
—
Emaciation
Emaciation
Cardiovascular
—
—
—
—
—
—
Digestive
—
—
—
—
—
—
Endocrine
—
—
—
—
—
—
Hemato/lymphoreticular
—
—
—
—
—
—
Hepatobiliary
—
—
—
—
Focal biliary hyperplasia
—
Integumentary
Scavenger damage
Yes
Yes
Yes
Yes
HI evidence
HI-CBD
HI-CBD
HI-CBD
HI-FI
HI-FI
HI-No
Interspecific aggression evidence
CBD
CBD
No
CBD
Yes
No
Other
—
—
Adherent material on fluke
—
Penetrating wound near blowhole
—
Musculoskeletal
—
—
—
—
—
—
Nervous
—
—
—
—
—
—
Reproductive
—
—
—
—
—
—
Respiratory
Pulmonary edema
—
Verminous pneumonia
—
—
—
Sensory
—
—
—
—
Ears-pooled blood
Stomach contents
Full
Empty
Empty
Empty
Empty
Empty
Urinary
—
—
—
—
—
—Histologic lesions involved the respiratory (3/6, 50%), integumentary (2/6, 33%), hepatobiliary (3/6, 50%), hematopoietic/lymphoreticular (3/6, 50%), digestive (3/6, 50%), sensory (2/6, 33%), and nervous systems (1/6, 16%) (Table3). The lesions ranged from incidental (no effect on the animal) to significant (some effect on the animal). There was no commonality of lesions. Endoparasitism was a common finding in the liver (hepatobiliary) (3/6, 50%) and lung (respiratory system) (3/6, 50%). Parasites, including nematodes in the lung (Figure 6) and trematode ova in the liver (Figure 7), were not always evident in the lesions; however, the presence of eosinophils and granulomatous inflammation were supportive of their presence. In addition to inflammation in the liver, there were biliary hyperplasia (increased number of bile ducts) and fibrosis of the portal tracts. The changes in the lung and liver denoted chronic inflammation. A single emaciated porpoise had lesions suggestive of septicemia including splenic necrosis and lymphoid depletion; however, bacteria were not observed. Other findings for this animal included superficial algal dermatitis (Figure 8) and pancreatic atrophy.Table 3
Specific histologic findings by system for the six harbor porpoises for which tissues were submitted for histopathologic evaluation. Each porpoise is listed by its field identification number.
System affected
JND003
KMS387
KMS389
KMS404
KMS417
MLC001
Body-general
—
—
—
—
—
—
Cardiovascular
—
—
—
—
—
—
Digestive
—
Mucosal hyperplasia
(1) Pancreas-zymogen granule depletion,(2) Colitis
—
—
Eosinophilic enteritis
Endocrine
—
—
—
—
—
—
Hemato/lymphoreticular
—
Reactive lymph node
(1) Spleen-necrosis,(2) Lymph node depletion
—
—
(1) Hyperplasia,(2) Eosinophilia
Hepatobiliary
(1) Bile duct hyperplasia,(2) Pericholangitis
—
—
Biliary hyperplasia
Hepatic trematodiasis
—
Integumentary
—
—
Algal dermatitis
—
Steatitis
—
Musculoskeletal
—
—
—
—
—
—
Nervous
—
—
—
—
Myelin sheath swelling
—
Reproductive
—
—
—
—
—
—
Respiratory
—
Eosinophilic broncho-pneumonia
Verminous pneumonia
—
—
Eosinophilic interstitial pneumonia
Sensory
—
—
—
—
(1) Corneal edema,(2) Retinal atrophy
—
Urinary
—
—
—
—
—
—Figure 6
Microscopic section of lung from KMS389. Nematode larvae are present within regions of parenchymal destruction and fibrosis.Figure 7
Section of the liver from KMS417. Trematode ova are present within the portal tract surrounded by mixed inflammatory cells.Figure 8
Algae adhered to the superficial epithelium of KMS 389. Algae are arranged in dense sheets.Other lesions observed were incidental. The animal with a penetrating wound had inflammation of the adipose of the site of puncture (steatitis); however, there was no evidence of systemic infection related to this wound. Perimortem hypoxic changes including myelin sheath swelling in the brain were observed in one porpoise and mild retinal atrophy and corneal edema in another, with the latter likely resulting from superficial trauma perhaps at the time of stranding. Two porpoises had mild eosinophilic inflammation in the small and large intestine that may have been associated with parasitic infection. Lymph nodes in two animals were reactive with one lymph node containing eosinophils in increased numbers. While a cause of this was not evident, it does indicate antigenic stimulation.
## 4. Discussion
Both 2005 (the declared UME) and 1999 (an undeclared UME) sustained stranding levels that exceeded the UME threshold indicators for a marked increase in strandings for harbor porpoises in NC. Using the threshold criteria, and because stranding frequency in 1999 was higher than in that 2005, there is justification for considering 1999 as a UME year for harbor porpoises. The characteristics of porpoise strandings in NC remained similar throughout the years except for shifts in timing of strandings between UME and non-UME years, albeit all were within the normal timeframe. In addition, during UME years twice as many carcasses had signs of HI when it was possible to determine whether an interaction occurred (HI-FI, HI-Other, and HI-No only), while there was an increase in HI-CBD strandings. While this finding was not statistically significant, the proportions of HI-FI during UME years were similar to the 63% of carcasses with entanglement lesions documented in the mid-Atlantic from 1994 to 1996 [25]. Although the preponderance of HI-CBD may negatively bias the number of strandings known to be HI, no correction factor could be applied to each year to adjust for the CBD designations. Nonetheless, bycaught porpoises generally are in good or moderate nutritional condition or not emaciated [22, 25, 38], while in 2005 half of the carcasses were emaciated.No cause of the 2005 event in NC was found from gross and histologic findings, possibly due to the low number of specimens examined for pathology. Nonetheless, necropsy and histopathology findings did not differ significantly from other published reports from harbor porpoises, including parasite infestation (e.g., [11, 12, 22, 39]). While these parasites may have some effect upon these animals, it is unlikely they caused the strandings. One porpoise had lesions suggestive of possible septicemia based on lymph node depletion and splenic necrosis. However, there was no evidence of inflammation in other organs or bacteria in the lesions. Some types of organ lesions were considered mild or incidental without a net effect upon the animal. In contrast, other findings, such as zymogen granule depletion in the pancreas, are indicators of the overall body condition (e.g., emaciation). Of the three emaciated specimens, zymogen granule depletion was observed in a single porpoise. Some animals may have had disease processes that were not determined due to poor carcass condition and histologically nondiagnostic samples. Nonetheless, in the animals examined, no overwhelming systemic disease or infection was found. Therefore, if the six examined animals represent a true cross-section of the stranded population, the cause of strandings is unlikely to be infectious in nature. Although gross findings from the 2005 strandings provide the first indication of interspecific aggression in NC, the rate was low suggesting it was not a primary cause of the UME.Diagnostic testing forBartonella infection was previously reported for the live harbor porpoises found in the estuary in 2005 [9, 10]. In addition to these porpoises, Bartonella infection was found in other stranded cetaceans [10] and loggerhead sea turtles (Caretta caretta) from NC [40]. Maggi et al. [9] suggested that “bartonellosis may become an important emerging marine mammal infectious disease.” However, the extent of Bartonella infection among marine mammal populations and its results are not known because (1) stranded specimens are not routinely tested, (2) subtle effects of Bartonella prevent analysis of suspected cases, and (3) Bartonella can be difficult to detect [10]. In addition, marine mammals may be asymptomatic carriers similar to domestic and free-ranging terrestrial felids [41, 42]. It is unlikely, however, that Bartonella infection was responsible for the UME in 2005 based on the lack of histologic findings, such as uveitis and myocarditis, observed in other species.The majority of harbor porpoise strandings in NC, during UME and non-UME years, are young-of-year (YOY). Harbor porpoises are synchronized, seasonal breeders [43, 44]. In the western North Atlantic, most females calve annually with peak parturition in May [36]. Lactation duration is mostly speculative, but it appears to be eight to 12 months [43]. Given the month of stranding and body length (predicted length at 1 yr = 118 cm, [35]), most of these YOYs are approximately the size at weaning, and they would be 9–11 months of age. Porpoise strandings in Maryland, Virginia, and NC during 1994–1996 were also predominantly YOY [25]. YOY may be more common in the stranding record because they have a higher mortality rate [43]. For example, as newly weaned animals they are likely to be novice foragers, and even though juveniles have some of the thickest blubber [35], weight loss can be dramatic for porpoises not feeding [45]. For an animal with such important thermoregulatory needs and given that most were newly weaned, emaciation would be extremely deleterious due to physiologic stress associated with inadequate protection from cold water and lack of nutrients, including electrolytes and calories. Of the animals in 2005 that could be categorized as emaciated or robust, almost half were emaciated. Whether the emaciation was the primary cause of death, possibly resulting from recently weaned individuals being unable to forage on their own, or a secondary effect of undetected pathologies is unknown.Spatial segregation may also contribute to the prevalence of YOY strandings. Cox et al. [25] found that the mean length of HI-FI stranded porpoises along the mid-Atlantic coast of the USA was significantly smaller than that of porpoises documented as bycatch by fishery observers. Because most of the bycaught animals were entangled far from shore, they concluded that spatial segregation occurs between mature and immature animals resulting in a decreased likelihood of mature animals stranding. In addition, immature porpoises from the North Sea to the western Baltic Sea have been shown to have larger ranges than mature animals [46]. Thus, if YOYs are closer to shore, they likely would be more represented in the stranding record.Elevated strandings of harbor porpoises have been reported elsewhere. Notably, in a study of 55 stranded porpoises from 1990 to 2000, the number of strandings increased multifold along the Belgium and northern France coasts during 1999 [47]. The primary findings included emaciation (60%), bronchopneumonia (49%), and parasitosis (51%), while 70% had empty stomachs. Only 15% were attributed to bycatch. The authors suggested that the increase in strandings may have been due to an increase in the number of porpoises in the southern North Sea, possibly due to a shift in distribution during the latter years of the study and particularly in 1999, because the number of strandings in the nearby English Channel had also increased during this time. Along the nearby coasts of the Netherlands, porpoise strandings increased from the late 1990s through 2007, also presumably due to migration of primarily juvenile porpoises into the southern North Sea, with some possible contribution from inconsistent stranding-response effort over time [48]. A particularly notable increase in 2006 was not addressed. Large fluctuations within a small part of the range of harbor porpoises have been reported off the coast of Scotland [49], so local increases in abundance combined with similar stranding rates could result in a multifold increase in frequency of strandings. An increase in Danish strandings during a 9-day period in 2005 was declared a UME [24]. The incidence of potentially bycatch-related injuries during this event was higher than that in non-UME years 2003–2008, and the presence of naval activity correlated in models with higher rates of strandings. In 2007, a mass mortality of harbor porpoises and harbor seals (Phoca vitulina) was reported during a 2-month period along the Swedish coast [50]. The cause appeared to be an unknown pathogenic virus. Elevated strandings of harbor porpoises caused primarily by aggressive interactions with bottlenose dolphins occurred along the central coast of California from 2007–2009 [18]. Thus, the cause of unusually high stranding frequencies can be caused by various unrelated factors and the cause of harbor porpoise unusual stranding events in the western Atlantic and Belgium/northern France in 1999 [47] or the Danish coast in 2005 [24] seems unrelated. The events have in common high rates of emaciation and empty stomachs as well as parasitosis, a common finding in stranded harbor porpoises (e.g., [11, 22]), but not an infectious disease. In addition, harbor porpoises in the eastern and western Atlantic comprise separate stocks and little, if any, mixing occurs [51].The use of a quantitative approach, such as developing a threshold, to define a marked increase in the magnitude of strandings relative to historic levels provides a relatively objective and straightforward means of evaluating whether an event is occurring or occurred and how elevated stranding numbers are compared among years. When strandings occur year-round, such as for harbor porpoises in California, seasonal adjustments can remove variability that may obscure true unusual seasonal increases in strandings [18]. Detection of anomalies in stranding patterns may be enhanced by including the influence of carcass drift [52]. These methods have in common use of a quantitative, objective means to compare potentially elevated numbers to average stranding patterns. Reevaluating UMEs in light of additional time-series data can confirm UMEs or, possibly, help determine if a gradual increase or decrease in number of strandings is resulting in a shifting threshold.A UME indicator is needed in real time to ascertain that an event is occurring. In the USA, formal declaration of a UME provides opportunity to request/obtain support for enhanced response and beneficial oversight to ensure standardized sampling and testing [32]. For harbor porpoises in NC, weekly assessment is an appropriate metric because the stranding season is relatively contracted, and strandings are sufficiently infrequent in many years that a finer-scale time frame could not be supported. For other situations, more or less frequent comparisons may be appropriate, including biweekly [53], monthly [54], seasonally [18, 34, 52], or annually [55]. Retrospective examination of annual stranding numbers may provide a different perspective, such as the current finding that harbor porpoise strandings in 2003 exceed the annual stranding threshold and, thus, potentially could have been a UME. Such retrospective information will not help with current stranding response, including implementing specific protocols adopted for an UME, but may assist with detecting future UMEs by influencing which years are included for calculating the threshold. This approach also assists with interpreting historical stranding data. For example, from 1975 to 1989, harbor porpoises were reported stranding in NC in low numbers except for the spring of 1977 when 60 porpoise strandings were documented [4]. It is possible that the reported numbers across those years underestimated the true number of strandings because a comprehensive stranding network was not yet developed, but in 1977 the reported level would have exceeded the thresholds developed in recent years when stranding reports were more systematic and reliable.In NC, the harbor porpoise is a challenging species for robust stranding response because, per our long-term observations, more than most dolphins or whales these small carcasses can be difficult to detect on beaches, wash out at high tides fairly easily, are consumed quickly by gulls and other predators, and decompose rapidly, even during winter. Almost certainly, the number of porpoises detected is negatively biased. A more robust response for this species would have required stationing teams of responders along the 160 km of coast where the majority of porpoise strand. However, when UMEs occur over short periods, there frequently is insufficient time to implement this type of increased response. As a result, it is often possible to determine that an unusually high number of porpoises are stranded without obtaining sufficient information from those strandings to determine the cause of the event.
### 4.1. Conclusions
Harbor porpoises strand annually along NC beaches in highly variable numbers. Periodically, increases in the frequency of standings result in Unusual Mortality Events. The cause of the most recent UME, in 2005, could not be determined. Relative to non-UME years and to an undeclared UME during 1999, there were no significant differences in age class, sex ratio, or spatial distribution of strandings and only a suggestion of an increase in fishery interactions. There was a significant temporal effect, with a peak in strandings during one month rather than more distributed over 3 months; however, they occurred within the normal timeframe of porpoise strandings. No overall cause of the 2005 event in NC was found from gross and histologic findings and, except for parasite infestation typical for harbor porpoises, there was no commonality in findings and no pervasive evidence of infectious disease. Potential unexplored explanatory factors include an increase in mortality rate due to an unidentified cause, such as reduced prey availability, an increase in strandings due to changes in abundance or distribution off the NC coast, or a shift in environmental conditions such as wind [56–58]. Response to harbor porpoise UMEs is especially challenging, particularly along the vast expanses of NC beaches, requiring additional effort to obtain carcasses in sufficient condition to determine the cause of these events.
## 4.1. Conclusions
Harbor porpoises strand annually along NC beaches in highly variable numbers. Periodically, increases in the frequency of standings result in Unusual Mortality Events. The cause of the most recent UME, in 2005, could not be determined. Relative to non-UME years and to an undeclared UME during 1999, there were no significant differences in age class, sex ratio, or spatial distribution of strandings and only a suggestion of an increase in fishery interactions. There was a significant temporal effect, with a peak in strandings during one month rather than more distributed over 3 months; however, they occurred within the normal timeframe of porpoise strandings. No overall cause of the 2005 event in NC was found from gross and histologic findings and, except for parasite infestation typical for harbor porpoises, there was no commonality in findings and no pervasive evidence of infectious disease. Potential unexplored explanatory factors include an increase in mortality rate due to an unidentified cause, such as reduced prey availability, an increase in strandings due to changes in abundance or distribution off the NC coast, or a shift in environmental conditions such as wind [56–58]. Response to harbor porpoise UMEs is especially challenging, particularly along the vast expanses of NC beaches, requiring additional effort to obtain carcasses in sufficient condition to determine the cause of these events.
---
*Source: 289892-2013-09-30.xml* | 2013 |
# Effect of Composting on Dissolved Organic Matter in Animal Manure and Its Binding with Cu
**Authors:** Fengsong Zhang; Yanxia Li; Xiong Xiong; Ming Yang; Wei Li
**Journal:** The Scientific World Journal
(2012)
**Publisher:** The Scientific World Journal
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1100/2012/289896
---
## Abstract
The agricultural application of raw animal manure introduces large amounts of dissolved organic matter (DOM) into soil and would increase transport of heavy metals such as Cu which are widely present in animal manure. The purpose of this research was to evaluate the evolution of DOM from pig and cattle manures during composting through excitation-emission matrix (EEM) fluorescence spectroscopy and the binding ability of DOM toward copper (Cu) ions with the aid of fluorescence quenching titration. The excitation-emission matrix spectra indicated that tyrosine-like, tryptophan-like, and soluble microbial byproduct-like fluorescence decreased significantly, while humic-like and fulvic-like fluorescence increased and became the main peaks in composted manure DOM. Fluorescence quenching titration showed that the complexing capacities of pig and cattle manure DOM decreased after composting. Correlation analysis confirmed that complexing capacity of DOM positively and significantly correlates with tyrosine-like and soluble microbial byproduct-like materials which mostly degraded after composting. These results would suggest that the ability of manure DOM to complex with Cu is inhibited as a result of reduced protein-like materials after composting.
---
## Body
## 1. Introduction
Animal manure was usually applied to arable soils in order to improve soil fertility and increase the organic matter content. However, in recent years, high concentration of heavy metal such as Cu in animal manure has been frequently reported in China due to abuse of mineral additives [1, 2]. Because part of the organic substances in animal manure are water soluble, a direct impact of the application of animal manure to agricultural land is the release of dissolved organic matter (DOM) into soil solution [3]. DOM could complex with heavy metals and then improve their transport to surface water [4, 5].In natural water, humic acids and fulvic acids are major components and represent up to 70% of DOM, which contributed the most organic ligands to Cu complexing [6]. However, a recent study indicates that nonhumic substances such as amino acids are likely engaged in the Cu complexation [7]; as one type of protein-like materials, amino acids are important components in DOM of organic wastes [8–10]. In addition, de Zarruk et al. [9] verified that the fraction in vinasse with the highest proteinaceous fluorescence has the greatest ability to bind with Cu. According to previous research, raw pig manure and cattle manure DOM also have a large number of proteinaceous materials [8, 10]. Whether the proteinaceous materials in manure DOM play a key role in complexing with Cu was not clear.Composting is a useful method for organic wastes stabilization [11–13]. A decline in DOM has been reported by Inbar et al. [14] and Huang et al. [12] for cattle manure and pig manure composting, respectively. The common characteristic is that DOM composition may undergo significant transformation after the composting process [10, 15]. For example, domestic organic wastes (coffee residues and garden trimmings) had a reduction of carbohydrates and increase of aromatic, phenolic, carboxylic, and carbonylic C in DOM after composting [16]. Accordingly, a decrease in the tyrosine-like and tryptophan-like materials and an increase in the humic, and fulvic-like materials were observed by excitation-emission matrix (EEM) fluorescence spectroscopy during composting of winery residues and municipal solid wastes [10, 13]. However, little is reported about the transformation of animal manure DOM during composting process at present. Furthermore, variation of binding ability of manure DOM with heavy metals after composing was also unknown.As a selective, sensitive, and nondestructive analytical technique, EEM fluorescence spectroscopy has been always used to characterize the DOM composition using contour plots, number of fluorescence peaks, position of wavelength-independent fluorescence maxima (Exmax/Emmax), and fluorescence intensity at Exmax/Emmax [8, 17–19]. However, it is limited to quantifying the properties based on one, two, or three data points from the fluorescence spectra. Chen et al. [20] developed the fluorescence regional integration (FRI) technique for quantitative analysis, which has been successfully used to study the evolution of organic waste DOM during the composting process [10, 13]. In addition, fluorescence spectroscopy has been revealed as a very promising technique for the study of metal ion binding to DOM [7, 21, 22]. Metal ions, especially paramagnetic metals, that is, Cu and Hg, are able to quench the intrinsic fluorescence of DOM [23, 24]. Therefore, together with the fluorescence quenching titration, the metal ion complexing capacities of DOM and stability constants of metal-DOM complexes can be examined.The objectives of this study were (1) to explore the composition evolution of animal manure (pig manure and cattle manure) DOM during composting by EEM fluorescence spectroscopy; (2) to investigate the effect of composting process on manure DOM complexation with Cu.
## 2. Materials and Methods
### 2.1. Composting Procedure and Sample Preparation
The composting experiment was conducted in the same way with our previous study [22]. Manures and bulking agents were collected at local farms. Sawdust and corn stalks were chopped into 2-3 cm pieces and air dried before composting. The treatments of the composting piles on a dry volume basis were as follows. Treatment A: 50% pig manure + 50% sawdust; treatment B: 50% pig manure + 50% corn stalks; treatment C: 50% cattle manure + 50% sawdust; treatment D: 50% cattle manure + 50% corn stalks.The composting experiments were performed in cylindrical vessels (diameter: 500 mm; height: 600 mm). The uniform forced ventilation was equipped at a rate of 0.1 m3/min for 10 minutes at 60-minute intervals through perforated plates fixed at the bottom of the vessels to provide oxygen. The moisture content of each pile was kept at 50–60% (weight/weight) during composting. In the first 30 days of composting, the piles were turned periodically to keep the temperature under 60°C. Afterwards, the forced ventilation was stopped, and the piles were stirred daily for further humification.The composting process was stopped when the compost temperature equaled the ambient temperature with no measurable changes for approximately 20 days. The pig manure and cattle manure were composted for 71 days and 46 days, respectively. Samples were collected from treatment A and treatment B on days 1, 8, 11, 17, 32, and 71 (A1, B1, A8, B8, A11, B11, A17, B17, A32, B32, A71, and B71), whereas sampling was done on days 1, 6, 10, 13, 29, and 46 (C1, D1, C6, D6, C10, D10, C13, D13, C29, D29, C46, and D46) for treatment C and treatment D, respectively. The subsamples were taken at different positions within the vessel and then thoroughly mixed as a composite sample. Prior to extracting the DOM, the samples were air dried.
### 2.2. Extraction of DOM and Fluorescence Analysis
Two grams of subsamples were extracted with 40 mL of deionized water and shaken for 24 hours. The solution was then centrifuged at 10,000 rpm for 10 minutes. The supernatant was then filtered using Whatman GF/F glass microfiber filter papers that had previously been heated at 450°C to remove any possible organic matter. The extracts were immediately analyzed for dissolved organic carbon using the TOC analyzer (Liqui TOC, Elementar, Germany).The fluorescence of the filtered DOM samples was determined with a model F-4500 fluorescence spectrophotometer (Hitachi, Japan) with a 150-W Xe arc lamp. Prior to fluorescence analysis, all sub-samples for fluorescence analysis were diluted to the uniform concentration of 10 mg C/L to reduce inner filter effects [9]. To generate an EEM, excitation wavelengths were scanned from 200 to 400 nm in 2 nm steps, and the emitted fluorescence was detected between 300 and 550 nm in 5 nm steps. The band-pass width was 5 nm for excitation and 10 nm for emission, and the scan speed was 2400 nm/min [24].Fluorescence regional integration method was applied for spectral comparison to thoroughly explore the transformation of DOM composition during manure composting [20]. To avoid the scattering effects of fluorescence data, the treatment method of the first-order Rayleigh, Raman and second-order Rayleigh scatters was applied, which was proposed by Bahram et al. [25]. The EEM plots were generated from the fluorescence spectral data using Sigmaplot 10.0 software (Systat Software, Inc.).
### 2.3. Fluorescence Quenching Titration and Complexation Modeling
Fluorescence quenching titration was carried out to characterize the complexation of manure DOM with Cu according to the research of Plaza et al. [21]. Experiments were carried out by adding 0.01 M Cu(NO3)2 solutions to a series of glass bottles that contained 50 mL of DOM solution. The pH value was then adjusted to 7.0. All samples were shaken in the dark for 24 hours under a nitrogen atmosphere at constant temperature (25±0.1°C) to ensure complexation equilibrium.The selection of the wavelengths for the fluorescence titration was based on the highest fluorescence intensity observed from the EEM of the samples [21]. The complexation model of Ryan and Weber was used to determine the binding parameters between DOM and Cu ions [26]. The model assumes a simple 1 : 1 equilibrium between a metal ion and an organic ligand
(1)I=I0+(ICuL-I0)(12KCuCL)×((1+KCuCL+KCuCCu)2-4KCu2CCuCL1+KCuCL+KCuCCu-(1+KCuCL+KCuCCu)2-4KCu2CCuCL),
where I and I0 are the fluorescence intensity (arbitrary units) at the Cu concentration of CCu and at the start of the titration, respectively, ICuL is the limiting value below which the fluorescence cannot decrease with the addition of Cu2+, CL is the total ligand concentration, CCu is the total Cu ion concentration, and KCu is the conditional stability constant.The complexation capacity (CCCu), that is, the amount of active binding sites per unit mass of DOM, was calculated as
(2)CCCu=CL(DOM)total,
where (DOM)total is the total concentration of DOM. KCu and CL were solved by a nonlinear regression analysis with the software 1st Opt 1.5 (7D-soft High Technology Inc., China). The optimum set of fitting parameters for each DOM sample was obtained by iteratively varying the adjustable parameter values until the sum of the squares of the differences between the observed and fitted values of I was minimized. Full, unconstrained optimization was achieved using the quasi-Newton algorithm.
### 2.4. Statistical Analysis
Correlations were analyzed between percentages of fluorescence response (Pi,n) to elucidate the transformation of DOM during the composting. Meanwhile, correlation analysis was also used to determine the correlations between Pi,n and parameters of DOM binding with Cu (i.e., CCCu and logKCu). Statistical analyses were performed with the software SPSS 11.5 (SPSS Inc., Chicago, IL, USA) for Windows.
## 2.1. Composting Procedure and Sample Preparation
The composting experiment was conducted in the same way with our previous study [22]. Manures and bulking agents were collected at local farms. Sawdust and corn stalks were chopped into 2-3 cm pieces and air dried before composting. The treatments of the composting piles on a dry volume basis were as follows. Treatment A: 50% pig manure + 50% sawdust; treatment B: 50% pig manure + 50% corn stalks; treatment C: 50% cattle manure + 50% sawdust; treatment D: 50% cattle manure + 50% corn stalks.The composting experiments were performed in cylindrical vessels (diameter: 500 mm; height: 600 mm). The uniform forced ventilation was equipped at a rate of 0.1 m3/min for 10 minutes at 60-minute intervals through perforated plates fixed at the bottom of the vessels to provide oxygen. The moisture content of each pile was kept at 50–60% (weight/weight) during composting. In the first 30 days of composting, the piles were turned periodically to keep the temperature under 60°C. Afterwards, the forced ventilation was stopped, and the piles were stirred daily for further humification.The composting process was stopped when the compost temperature equaled the ambient temperature with no measurable changes for approximately 20 days. The pig manure and cattle manure were composted for 71 days and 46 days, respectively. Samples were collected from treatment A and treatment B on days 1, 8, 11, 17, 32, and 71 (A1, B1, A8, B8, A11, B11, A17, B17, A32, B32, A71, and B71), whereas sampling was done on days 1, 6, 10, 13, 29, and 46 (C1, D1, C6, D6, C10, D10, C13, D13, C29, D29, C46, and D46) for treatment C and treatment D, respectively. The subsamples were taken at different positions within the vessel and then thoroughly mixed as a composite sample. Prior to extracting the DOM, the samples were air dried.
## 2.2. Extraction of DOM and Fluorescence Analysis
Two grams of subsamples were extracted with 40 mL of deionized water and shaken for 24 hours. The solution was then centrifuged at 10,000 rpm for 10 minutes. The supernatant was then filtered using Whatman GF/F glass microfiber filter papers that had previously been heated at 450°C to remove any possible organic matter. The extracts were immediately analyzed for dissolved organic carbon using the TOC analyzer (Liqui TOC, Elementar, Germany).The fluorescence of the filtered DOM samples was determined with a model F-4500 fluorescence spectrophotometer (Hitachi, Japan) with a 150-W Xe arc lamp. Prior to fluorescence analysis, all sub-samples for fluorescence analysis were diluted to the uniform concentration of 10 mg C/L to reduce inner filter effects [9]. To generate an EEM, excitation wavelengths were scanned from 200 to 400 nm in 2 nm steps, and the emitted fluorescence was detected between 300 and 550 nm in 5 nm steps. The band-pass width was 5 nm for excitation and 10 nm for emission, and the scan speed was 2400 nm/min [24].Fluorescence regional integration method was applied for spectral comparison to thoroughly explore the transformation of DOM composition during manure composting [20]. To avoid the scattering effects of fluorescence data, the treatment method of the first-order Rayleigh, Raman and second-order Rayleigh scatters was applied, which was proposed by Bahram et al. [25]. The EEM plots were generated from the fluorescence spectral data using Sigmaplot 10.0 software (Systat Software, Inc.).
## 2.3. Fluorescence Quenching Titration and Complexation Modeling
Fluorescence quenching titration was carried out to characterize the complexation of manure DOM with Cu according to the research of Plaza et al. [21]. Experiments were carried out by adding 0.01 M Cu(NO3)2 solutions to a series of glass bottles that contained 50 mL of DOM solution. The pH value was then adjusted to 7.0. All samples were shaken in the dark for 24 hours under a nitrogen atmosphere at constant temperature (25±0.1°C) to ensure complexation equilibrium.The selection of the wavelengths for the fluorescence titration was based on the highest fluorescence intensity observed from the EEM of the samples [21]. The complexation model of Ryan and Weber was used to determine the binding parameters between DOM and Cu ions [26]. The model assumes a simple 1 : 1 equilibrium between a metal ion and an organic ligand
(1)I=I0+(ICuL-I0)(12KCuCL)×((1+KCuCL+KCuCCu)2-4KCu2CCuCL1+KCuCL+KCuCCu-(1+KCuCL+KCuCCu)2-4KCu2CCuCL),
where I and I0 are the fluorescence intensity (arbitrary units) at the Cu concentration of CCu and at the start of the titration, respectively, ICuL is the limiting value below which the fluorescence cannot decrease with the addition of Cu2+, CL is the total ligand concentration, CCu is the total Cu ion concentration, and KCu is the conditional stability constant.The complexation capacity (CCCu), that is, the amount of active binding sites per unit mass of DOM, was calculated as
(2)CCCu=CL(DOM)total,
where (DOM)total is the total concentration of DOM. KCu and CL were solved by a nonlinear regression analysis with the software 1st Opt 1.5 (7D-soft High Technology Inc., China). The optimum set of fitting parameters for each DOM sample was obtained by iteratively varying the adjustable parameter values until the sum of the squares of the differences between the observed and fitted values of I was minimized. Full, unconstrained optimization was achieved using the quasi-Newton algorithm.
## 2.4. Statistical Analysis
Correlations were analyzed between percentages of fluorescence response (Pi,n) to elucidate the transformation of DOM during the composting. Meanwhile, correlation analysis was also used to determine the correlations between Pi,n and parameters of DOM binding with Cu (i.e., CCCu and logKCu). Statistical analyses were performed with the software SPSS 11.5 (SPSS Inc., Chicago, IL, USA) for Windows.
## 3. Results and Discussion
### 3.1. Change of DOM Concentrations during Composting
The total concentration of DOM in pig and cattle manure was reduced after composting (Figure1), which was similar to results obtained by Inbar et al. [14] and Huang et al. [12]. Cattle manure DOM concentrations continuously declined during the composting process, with a sharp reduction occurring in the initial stage of composting. During co-composting with corn stalk and sawdust, DOM in cattle manure was reduced by 27.4% and 31.4%, respectively. However, during cocomposting with exhausted grape marc, cattle manure DOM only reduced by 18.3% [27].Changes of dissolved organic matter (DOM) concentrations during manure composting.
(a)
(b)During composting of pig manure, DOM increased after a sharp initial decrease. At the end of the composting process, DOM concentration in pig manure with addition of sawdust and corn stalk decreased to 58.6% and 69.5%, respectively, of the raw materials after composting. In comparison to the cattle manure, there is more DOM degraded during pig manure composting than cattle manure, using the same composting method. This observation may reflect that pig manure contains far more DOM than cattle manure, but that the DOM in pig manure is also more easily degradable. In contrast, it was reported that about 95.8% of DOM in municipal solid waste had been degraded at the end of composting [13]. Our results and the cited study show that the rate of decrease in DOM concentration depends not only on the composting technique utilized, but also on the composition of the source material.
### 3.2. DOM Fluorescence Characteristics
As the EEM spectra evolution of DOM from treatment B and treatment D were similar to that from treatment A and treatment C, the DOM spectra of treatment A and treatment C are displayed as the representative in Figure2. According to the research of Chen et al. [20], the fluorescence of regions I, II, and IV in manure DOM are related to tyrosine-like, tryptophan-like, and soluble microbial byproduct-like materials while the fluorescence of regions III and V are related to fulvic-like and humic-like materials. Soluble microbial byproduct-like materials also contained another kind of tyrosine-like and tryptophan-like compounds, which were different from materials associated with region I and region II [28]. In the raw pig manure DOM (A1), the most intense fluorescence peak of Ex/Em = 280 nm/342 nm centered at region IV. Protein-like fluorescence peaks such as tyrosine-like and tryptophan-like peaks were associated with growth of living organisms in marine water [17]. However, these peaks were also detected in organic wastes, such as animal slurry and landfill leachates [8, 29]. In addition, we observed a peak of Ex/Em = 245 nm/399 nm centered at region III in raw pig manure DOM (A1), which may be attributed to aromatic and aliphatic groups in the DOM and widely labeled as fulvic-like substances [19]. However, there was no obvious humic-like fluorescence peak in pig manure DOM. Similar to raw pig manure, cattle manure DOM (C1) had intense tryptophan-like and tyrosine-like fluorescence peaks. However, cattle manure also had two intense fulvic acid-like and humic acid-like peaks centered at Ex/Em = 245 nm/400 nm and 305 nm/412 nm.Figure 2
Excitation-emission matrix (EEM) spectra of DOM from treatment A (pig manure + sawdust) on days 1, 17, 32, and 71 (A1, A17, A32, and A71) and treatment C (cattle manure + sawdust) on day 1, 13, 29, and 46 (C1, C13, C29, and C46).The percentage fluorescence response (Pi,n) of the five regions in the different composting samples is displayed in Figure 3. In the raw pig manure DOM (A1), the quantities of P1,n, P2,n, and P4,n in raw pig manure were approximately 16.6%, 19.9%, and 40.0% of total DOM, respectively, while the fulvic-like, and humic-like materials only contribute 10.9%, and 12.5%, respectively. In contrast, Pi,n of tyrosine-like, tryptophan-like and soluble microbial byproduct-like materials in cattle manure DOM were 17.1%, 23.2%, and 26.3%, while the fulvic acid-like and humic acid-like substances were 18.1% and 15.3%. Thus, there are more humic substances in cattle manure DOM than in pig manure DOM in the manures obtained for this study.Figure 3
Evolution of the percentage fluorescence response (Pi,n) during composting.DOM from treatment A (pig manure + sawdust) and treatment B (pig manure + corn stalk) was on days 1, 17, 32, and 71 (A1, B1, A17, B17, A32, B32, A71, and B71), treatment C (cattle manure + sawdust) and treatment D (cattle manure + corn stalk) on days 1, 13, 29, and 46 (C1, D1, C13, D13, C29, D29, C46, and D46).During the composting process, a sharp decrease of tyrosine-like, tryptophan-like, and soluble microbial byproduct-like fluorescence occurred in the initial stage of composting for pig manure and cattle manure, while fulvic-like and humic-like fluorescence displayed reverse trends. At the end of composting, there were only fulvic-like and humic-like fluorescence peaks left both in cattle manure and pig manure DOM. The totalP5,n values of pig manure or cattle manure cocomposting with sawdust increased by 16.3% and 4.2%, respectively, compared with the raw materials, while the values of P3,n increased by 6.4% and 7.6%, respectively. Similar results were obtained for DOM evolution of exhausted grape marc cocomposted with cattle manure and poultry manure in the study of Marhuenda-Egea et al. [10]. Shao et al. [13] also reported that P5,n increased from 18.8% to 54.8%, and humic acid-like compounds became the main component in municipal solid wastes DOM at the end of the composting process.
### 3.3. Implications of the DOM Change on Cu-DOM Complexation
The high determinative coefficients (DCs) in Table1 indicated that the experimental data fit well with the Ryan-Weber model [26]. The complexing capacity (CCCu) is an indicator presenting the amount of active binding sites for complexation with metal ions in a unit mass of DOM. The CCCu of raw pig manure ranged from 50.6 to 55.0 mmol/g, which was far higher than that of raw cattle manure. After the composting process, the manure DOM featured much lower CCCu values in the range of 0.41 to 1.99 mmol/g. The increases in P3,n and P5,n confirmed that humification of manure DOM occurred during composting. Previous study has shown that carboxylic- and phenolic-type groups are two kinds of binding sites in humic acids and fulvic acids [30]. Plaza et al. [31] investigated that total acidic functional group contents including phenolic OH group and carboxyl group increased in cattle manure after composing. Caricasole et al. [16] also reported the increasing of phenolic, carboxylic, and carbonylic C occurred in DOM from domestic organic wastes after composting. However, there were negative linear relationships between CCCu and P5,n (R2=0.58, P<0.01) or P3,n (R2=0.62, P<0.01) shown in Figure 4. In contrast, significantly positive linear correlations were found between CCCu and P4,n (R2=0.59, P<0.01) or P1,n (R2=0.54, P<0.01). The results may suggest that raw manure DOM has higher CCCu than that of composted manure DOM that can be attributed to its more tyrosine-like organic compounds and soluble microbial byproduct-like materials. The remarkable diversity of Cu complex capacity may be attributed to the difference of protein-like materials in manure DOM. In surface water, fulvic acid and humic acid in DOM were accepted as main components which complexed with Cu [6]. However, Yamashita and Jaffé [7] reported that nonhumic substances such as amino acids are likely engaged in the Cu complexation in surface water. de Zarruk et al. [9] have also verified that the fraction with high proteinaceous fluorescence in vinasse formed the most DOM-Cu complexes. Thus, the binding of Cu to DOM was inhibited properly due to the degradation of protein-like materials during composting, particularly in DOM from composted pig manure.Table 1
Fitting parameters of Ryan-Weber model.
DOM samplesa
Ex/Em (nm)b
I
Cu
L (AU)b
CCCu (mmol/g)b
log
K
Cu
b
DCb
A1
276/306
260.98
50.60
5.24
0.992**
A71
315/412
79.04
1.99
5.14
0.998**
B1
276/306
296.51
55.00
5.17
0.987**
B71
315/412
91.00
0.41
5.02
0.996**
C1
305/412
39.90
6.52
4.90
0.997**
C46
310/408
46.48
0.53
5.08
0.998**
D1
310/414
81.69
7.78
4.93
0.996**
D46
310/420
53.71
1.62
5.00
0.998**
aDOM from treatment A (pig manure + sawdust) on days 1 and 71 (A1, A71), treatment B (pig manure + corn stalk) on days 1 and 71 (B1, B71), treatment C (cattle manure + sawdust) on days 1 and 46 (C1, C46), and treatment D (cattle manure + corn stalk) on days 1 and 46 (D1, D46).
bEx/Em: selected wavelengths for the fluorescence titration; ICuL: fluorescence intensity of Cu ion-saturated complex (arbitrary units: AU); CCCu: complexing capacity (mmol/g); log KCu: the conditional stability constant; DC: determinative coefficiency.
**Statistical significance valueP<0.001.Relationships between percentages of fluorescence response of the five regions (Pi,n) and complexing capacity (CCCu) and the conditional stability constant (logKCu) *Statistical significance value P<0.05.
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)The conditional stability constants (logKCu) of Cu complexes with manure DOM were between 4.90 and 5.24 (Table 1), and the values are similar to those studies on surface water DOM [7]. The DOM of composted cattle manure with sawdust and corn stalk featured higher logKCu than that of raw cattle manure. On the contrary, pig manure DOM showed the decreasing trend after composting. The significantly positive linear correlation between logKCu and P4,n can be observed in Figure 4 (R2=0.51, P<0.01). This may indicate, in part, that some functional groups in soluble microbial byproduct-like materials play an important role in determining the conditional stability constant logKCu. Soluble microbial byproduct-like materials contain a large number of proteins and amino acids [20]. It has been reported that protein-like fraction of natural water DOM has the highest logKCu [23]. If it was also true for manure DOM, the decrease in the complex stability of pig manure DOM may be attributed to the degradation of large amounts of aromatic amino acid materials.
## 3.1. Change of DOM Concentrations during Composting
The total concentration of DOM in pig and cattle manure was reduced after composting (Figure1), which was similar to results obtained by Inbar et al. [14] and Huang et al. [12]. Cattle manure DOM concentrations continuously declined during the composting process, with a sharp reduction occurring in the initial stage of composting. During co-composting with corn stalk and sawdust, DOM in cattle manure was reduced by 27.4% and 31.4%, respectively. However, during cocomposting with exhausted grape marc, cattle manure DOM only reduced by 18.3% [27].Changes of dissolved organic matter (DOM) concentrations during manure composting.
(a)
(b)During composting of pig manure, DOM increased after a sharp initial decrease. At the end of the composting process, DOM concentration in pig manure with addition of sawdust and corn stalk decreased to 58.6% and 69.5%, respectively, of the raw materials after composting. In comparison to the cattle manure, there is more DOM degraded during pig manure composting than cattle manure, using the same composting method. This observation may reflect that pig manure contains far more DOM than cattle manure, but that the DOM in pig manure is also more easily degradable. In contrast, it was reported that about 95.8% of DOM in municipal solid waste had been degraded at the end of composting [13]. Our results and the cited study show that the rate of decrease in DOM concentration depends not only on the composting technique utilized, but also on the composition of the source material.
## 3.2. DOM Fluorescence Characteristics
As the EEM spectra evolution of DOM from treatment B and treatment D were similar to that from treatment A and treatment C, the DOM spectra of treatment A and treatment C are displayed as the representative in Figure2. According to the research of Chen et al. [20], the fluorescence of regions I, II, and IV in manure DOM are related to tyrosine-like, tryptophan-like, and soluble microbial byproduct-like materials while the fluorescence of regions III and V are related to fulvic-like and humic-like materials. Soluble microbial byproduct-like materials also contained another kind of tyrosine-like and tryptophan-like compounds, which were different from materials associated with region I and region II [28]. In the raw pig manure DOM (A1), the most intense fluorescence peak of Ex/Em = 280 nm/342 nm centered at region IV. Protein-like fluorescence peaks such as tyrosine-like and tryptophan-like peaks were associated with growth of living organisms in marine water [17]. However, these peaks were also detected in organic wastes, such as animal slurry and landfill leachates [8, 29]. In addition, we observed a peak of Ex/Em = 245 nm/399 nm centered at region III in raw pig manure DOM (A1), which may be attributed to aromatic and aliphatic groups in the DOM and widely labeled as fulvic-like substances [19]. However, there was no obvious humic-like fluorescence peak in pig manure DOM. Similar to raw pig manure, cattle manure DOM (C1) had intense tryptophan-like and tyrosine-like fluorescence peaks. However, cattle manure also had two intense fulvic acid-like and humic acid-like peaks centered at Ex/Em = 245 nm/400 nm and 305 nm/412 nm.Figure 2
Excitation-emission matrix (EEM) spectra of DOM from treatment A (pig manure + sawdust) on days 1, 17, 32, and 71 (A1, A17, A32, and A71) and treatment C (cattle manure + sawdust) on day 1, 13, 29, and 46 (C1, C13, C29, and C46).The percentage fluorescence response (Pi,n) of the five regions in the different composting samples is displayed in Figure 3. In the raw pig manure DOM (A1), the quantities of P1,n, P2,n, and P4,n in raw pig manure were approximately 16.6%, 19.9%, and 40.0% of total DOM, respectively, while the fulvic-like, and humic-like materials only contribute 10.9%, and 12.5%, respectively. In contrast, Pi,n of tyrosine-like, tryptophan-like and soluble microbial byproduct-like materials in cattle manure DOM were 17.1%, 23.2%, and 26.3%, while the fulvic acid-like and humic acid-like substances were 18.1% and 15.3%. Thus, there are more humic substances in cattle manure DOM than in pig manure DOM in the manures obtained for this study.Figure 3
Evolution of the percentage fluorescence response (Pi,n) during composting.DOM from treatment A (pig manure + sawdust) and treatment B (pig manure + corn stalk) was on days 1, 17, 32, and 71 (A1, B1, A17, B17, A32, B32, A71, and B71), treatment C (cattle manure + sawdust) and treatment D (cattle manure + corn stalk) on days 1, 13, 29, and 46 (C1, D1, C13, D13, C29, D29, C46, and D46).During the composting process, a sharp decrease of tyrosine-like, tryptophan-like, and soluble microbial byproduct-like fluorescence occurred in the initial stage of composting for pig manure and cattle manure, while fulvic-like and humic-like fluorescence displayed reverse trends. At the end of composting, there were only fulvic-like and humic-like fluorescence peaks left both in cattle manure and pig manure DOM. The totalP5,n values of pig manure or cattle manure cocomposting with sawdust increased by 16.3% and 4.2%, respectively, compared with the raw materials, while the values of P3,n increased by 6.4% and 7.6%, respectively. Similar results were obtained for DOM evolution of exhausted grape marc cocomposted with cattle manure and poultry manure in the study of Marhuenda-Egea et al. [10]. Shao et al. [13] also reported that P5,n increased from 18.8% to 54.8%, and humic acid-like compounds became the main component in municipal solid wastes DOM at the end of the composting process.
## 3.3. Implications of the DOM Change on Cu-DOM Complexation
The high determinative coefficients (DCs) in Table1 indicated that the experimental data fit well with the Ryan-Weber model [26]. The complexing capacity (CCCu) is an indicator presenting the amount of active binding sites for complexation with metal ions in a unit mass of DOM. The CCCu of raw pig manure ranged from 50.6 to 55.0 mmol/g, which was far higher than that of raw cattle manure. After the composting process, the manure DOM featured much lower CCCu values in the range of 0.41 to 1.99 mmol/g. The increases in P3,n and P5,n confirmed that humification of manure DOM occurred during composting. Previous study has shown that carboxylic- and phenolic-type groups are two kinds of binding sites in humic acids and fulvic acids [30]. Plaza et al. [31] investigated that total acidic functional group contents including phenolic OH group and carboxyl group increased in cattle manure after composing. Caricasole et al. [16] also reported the increasing of phenolic, carboxylic, and carbonylic C occurred in DOM from domestic organic wastes after composting. However, there were negative linear relationships between CCCu and P5,n (R2=0.58, P<0.01) or P3,n (R2=0.62, P<0.01) shown in Figure 4. In contrast, significantly positive linear correlations were found between CCCu and P4,n (R2=0.59, P<0.01) or P1,n (R2=0.54, P<0.01). The results may suggest that raw manure DOM has higher CCCu than that of composted manure DOM that can be attributed to its more tyrosine-like organic compounds and soluble microbial byproduct-like materials. The remarkable diversity of Cu complex capacity may be attributed to the difference of protein-like materials in manure DOM. In surface water, fulvic acid and humic acid in DOM were accepted as main components which complexed with Cu [6]. However, Yamashita and Jaffé [7] reported that nonhumic substances such as amino acids are likely engaged in the Cu complexation in surface water. de Zarruk et al. [9] have also verified that the fraction with high proteinaceous fluorescence in vinasse formed the most DOM-Cu complexes. Thus, the binding of Cu to DOM was inhibited properly due to the degradation of protein-like materials during composting, particularly in DOM from composted pig manure.Table 1
Fitting parameters of Ryan-Weber model.
DOM samplesa
Ex/Em (nm)b
I
Cu
L (AU)b
CCCu (mmol/g)b
log
K
Cu
b
DCb
A1
276/306
260.98
50.60
5.24
0.992**
A71
315/412
79.04
1.99
5.14
0.998**
B1
276/306
296.51
55.00
5.17
0.987**
B71
315/412
91.00
0.41
5.02
0.996**
C1
305/412
39.90
6.52
4.90
0.997**
C46
310/408
46.48
0.53
5.08
0.998**
D1
310/414
81.69
7.78
4.93
0.996**
D46
310/420
53.71
1.62
5.00
0.998**
aDOM from treatment A (pig manure + sawdust) on days 1 and 71 (A1, A71), treatment B (pig manure + corn stalk) on days 1 and 71 (B1, B71), treatment C (cattle manure + sawdust) on days 1 and 46 (C1, C46), and treatment D (cattle manure + corn stalk) on days 1 and 46 (D1, D46).
bEx/Em: selected wavelengths for the fluorescence titration; ICuL: fluorescence intensity of Cu ion-saturated complex (arbitrary units: AU); CCCu: complexing capacity (mmol/g); log KCu: the conditional stability constant; DC: determinative coefficiency.
**Statistical significance valueP<0.001.Relationships between percentages of fluorescence response of the five regions (Pi,n) and complexing capacity (CCCu) and the conditional stability constant (logKCu) *Statistical significance value P<0.05.
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)The conditional stability constants (logKCu) of Cu complexes with manure DOM were between 4.90 and 5.24 (Table 1), and the values are similar to those studies on surface water DOM [7]. The DOM of composted cattle manure with sawdust and corn stalk featured higher logKCu than that of raw cattle manure. On the contrary, pig manure DOM showed the decreasing trend after composting. The significantly positive linear correlation between logKCu and P4,n can be observed in Figure 4 (R2=0.51, P<0.01). This may indicate, in part, that some functional groups in soluble microbial byproduct-like materials play an important role in determining the conditional stability constant logKCu. Soluble microbial byproduct-like materials contain a large number of proteins and amino acids [20]. It has been reported that protein-like fraction of natural water DOM has the highest logKCu [23]. If it was also true for manure DOM, the decrease in the complex stability of pig manure DOM may be attributed to the degradation of large amounts of aromatic amino acid materials.
## 4. Conclusion
The composting process reduced the amounts of DOM in pig and cattle manure. A majority of the protein-like materials were decomposed, and new humic-like and fulvic-like components were repolymerized. Humic-like materials in composted DOM were mainly transformed from tryptophan-like organic compounds, whereas fulvic-like components were largely transformed from soluble microbial byproduct-like substances.The complexing capacities of pig and cattle manure DOM decreased after composting, which can be attributed to the degradation of protein-like components. Furthermore, the degradation of protein-like components in pig manure reduced the stability constants oflogKCu. Our study suggests that the composting process might be a way to decrease the bioavailability, mobilization, and transport of manure DOM-Cu complexes, and lower the potential pollution risk to soil and ground water.
---
*Source: 289896-2012-10-17.xml* | 289896-2012-10-17_289896-2012-10-17.md | 38,870 | Effect of Composting on Dissolved Organic Matter in Animal Manure and Its Binding with Cu | Fengsong Zhang; Yanxia Li; Xiong Xiong; Ming Yang; Wei Li | The Scientific World Journal
(2012) | Medical & Health Sciences | The Scientific World Journal | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1100/2012/289896 | 289896-2012-10-17.xml | ---
## Abstract
The agricultural application of raw animal manure introduces large amounts of dissolved organic matter (DOM) into soil and would increase transport of heavy metals such as Cu which are widely present in animal manure. The purpose of this research was to evaluate the evolution of DOM from pig and cattle manures during composting through excitation-emission matrix (EEM) fluorescence spectroscopy and the binding ability of DOM toward copper (Cu) ions with the aid of fluorescence quenching titration. The excitation-emission matrix spectra indicated that tyrosine-like, tryptophan-like, and soluble microbial byproduct-like fluorescence decreased significantly, while humic-like and fulvic-like fluorescence increased and became the main peaks in composted manure DOM. Fluorescence quenching titration showed that the complexing capacities of pig and cattle manure DOM decreased after composting. Correlation analysis confirmed that complexing capacity of DOM positively and significantly correlates with tyrosine-like and soluble microbial byproduct-like materials which mostly degraded after composting. These results would suggest that the ability of manure DOM to complex with Cu is inhibited as a result of reduced protein-like materials after composting.
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## Body
## 1. Introduction
Animal manure was usually applied to arable soils in order to improve soil fertility and increase the organic matter content. However, in recent years, high concentration of heavy metal such as Cu in animal manure has been frequently reported in China due to abuse of mineral additives [1, 2]. Because part of the organic substances in animal manure are water soluble, a direct impact of the application of animal manure to agricultural land is the release of dissolved organic matter (DOM) into soil solution [3]. DOM could complex with heavy metals and then improve their transport to surface water [4, 5].In natural water, humic acids and fulvic acids are major components and represent up to 70% of DOM, which contributed the most organic ligands to Cu complexing [6]. However, a recent study indicates that nonhumic substances such as amino acids are likely engaged in the Cu complexation [7]; as one type of protein-like materials, amino acids are important components in DOM of organic wastes [8–10]. In addition, de Zarruk et al. [9] verified that the fraction in vinasse with the highest proteinaceous fluorescence has the greatest ability to bind with Cu. According to previous research, raw pig manure and cattle manure DOM also have a large number of proteinaceous materials [8, 10]. Whether the proteinaceous materials in manure DOM play a key role in complexing with Cu was not clear.Composting is a useful method for organic wastes stabilization [11–13]. A decline in DOM has been reported by Inbar et al. [14] and Huang et al. [12] for cattle manure and pig manure composting, respectively. The common characteristic is that DOM composition may undergo significant transformation after the composting process [10, 15]. For example, domestic organic wastes (coffee residues and garden trimmings) had a reduction of carbohydrates and increase of aromatic, phenolic, carboxylic, and carbonylic C in DOM after composting [16]. Accordingly, a decrease in the tyrosine-like and tryptophan-like materials and an increase in the humic, and fulvic-like materials were observed by excitation-emission matrix (EEM) fluorescence spectroscopy during composting of winery residues and municipal solid wastes [10, 13]. However, little is reported about the transformation of animal manure DOM during composting process at present. Furthermore, variation of binding ability of manure DOM with heavy metals after composing was also unknown.As a selective, sensitive, and nondestructive analytical technique, EEM fluorescence spectroscopy has been always used to characterize the DOM composition using contour plots, number of fluorescence peaks, position of wavelength-independent fluorescence maxima (Exmax/Emmax), and fluorescence intensity at Exmax/Emmax [8, 17–19]. However, it is limited to quantifying the properties based on one, two, or three data points from the fluorescence spectra. Chen et al. [20] developed the fluorescence regional integration (FRI) technique for quantitative analysis, which has been successfully used to study the evolution of organic waste DOM during the composting process [10, 13]. In addition, fluorescence spectroscopy has been revealed as a very promising technique for the study of metal ion binding to DOM [7, 21, 22]. Metal ions, especially paramagnetic metals, that is, Cu and Hg, are able to quench the intrinsic fluorescence of DOM [23, 24]. Therefore, together with the fluorescence quenching titration, the metal ion complexing capacities of DOM and stability constants of metal-DOM complexes can be examined.The objectives of this study were (1) to explore the composition evolution of animal manure (pig manure and cattle manure) DOM during composting by EEM fluorescence spectroscopy; (2) to investigate the effect of composting process on manure DOM complexation with Cu.
## 2. Materials and Methods
### 2.1. Composting Procedure and Sample Preparation
The composting experiment was conducted in the same way with our previous study [22]. Manures and bulking agents were collected at local farms. Sawdust and corn stalks were chopped into 2-3 cm pieces and air dried before composting. The treatments of the composting piles on a dry volume basis were as follows. Treatment A: 50% pig manure + 50% sawdust; treatment B: 50% pig manure + 50% corn stalks; treatment C: 50% cattle manure + 50% sawdust; treatment D: 50% cattle manure + 50% corn stalks.The composting experiments were performed in cylindrical vessels (diameter: 500 mm; height: 600 mm). The uniform forced ventilation was equipped at a rate of 0.1 m3/min for 10 minutes at 60-minute intervals through perforated plates fixed at the bottom of the vessels to provide oxygen. The moisture content of each pile was kept at 50–60% (weight/weight) during composting. In the first 30 days of composting, the piles were turned periodically to keep the temperature under 60°C. Afterwards, the forced ventilation was stopped, and the piles were stirred daily for further humification.The composting process was stopped when the compost temperature equaled the ambient temperature with no measurable changes for approximately 20 days. The pig manure and cattle manure were composted for 71 days and 46 days, respectively. Samples were collected from treatment A and treatment B on days 1, 8, 11, 17, 32, and 71 (A1, B1, A8, B8, A11, B11, A17, B17, A32, B32, A71, and B71), whereas sampling was done on days 1, 6, 10, 13, 29, and 46 (C1, D1, C6, D6, C10, D10, C13, D13, C29, D29, C46, and D46) for treatment C and treatment D, respectively. The subsamples were taken at different positions within the vessel and then thoroughly mixed as a composite sample. Prior to extracting the DOM, the samples were air dried.
### 2.2. Extraction of DOM and Fluorescence Analysis
Two grams of subsamples were extracted with 40 mL of deionized water and shaken for 24 hours. The solution was then centrifuged at 10,000 rpm for 10 minutes. The supernatant was then filtered using Whatman GF/F glass microfiber filter papers that had previously been heated at 450°C to remove any possible organic matter. The extracts were immediately analyzed for dissolved organic carbon using the TOC analyzer (Liqui TOC, Elementar, Germany).The fluorescence of the filtered DOM samples was determined with a model F-4500 fluorescence spectrophotometer (Hitachi, Japan) with a 150-W Xe arc lamp. Prior to fluorescence analysis, all sub-samples for fluorescence analysis were diluted to the uniform concentration of 10 mg C/L to reduce inner filter effects [9]. To generate an EEM, excitation wavelengths were scanned from 200 to 400 nm in 2 nm steps, and the emitted fluorescence was detected between 300 and 550 nm in 5 nm steps. The band-pass width was 5 nm for excitation and 10 nm for emission, and the scan speed was 2400 nm/min [24].Fluorescence regional integration method was applied for spectral comparison to thoroughly explore the transformation of DOM composition during manure composting [20]. To avoid the scattering effects of fluorescence data, the treatment method of the first-order Rayleigh, Raman and second-order Rayleigh scatters was applied, which was proposed by Bahram et al. [25]. The EEM plots were generated from the fluorescence spectral data using Sigmaplot 10.0 software (Systat Software, Inc.).
### 2.3. Fluorescence Quenching Titration and Complexation Modeling
Fluorescence quenching titration was carried out to characterize the complexation of manure DOM with Cu according to the research of Plaza et al. [21]. Experiments were carried out by adding 0.01 M Cu(NO3)2 solutions to a series of glass bottles that contained 50 mL of DOM solution. The pH value was then adjusted to 7.0. All samples were shaken in the dark for 24 hours under a nitrogen atmosphere at constant temperature (25±0.1°C) to ensure complexation equilibrium.The selection of the wavelengths for the fluorescence titration was based on the highest fluorescence intensity observed from the EEM of the samples [21]. The complexation model of Ryan and Weber was used to determine the binding parameters between DOM and Cu ions [26]. The model assumes a simple 1 : 1 equilibrium between a metal ion and an organic ligand
(1)I=I0+(ICuL-I0)(12KCuCL)×((1+KCuCL+KCuCCu)2-4KCu2CCuCL1+KCuCL+KCuCCu-(1+KCuCL+KCuCCu)2-4KCu2CCuCL),
where I and I0 are the fluorescence intensity (arbitrary units) at the Cu concentration of CCu and at the start of the titration, respectively, ICuL is the limiting value below which the fluorescence cannot decrease with the addition of Cu2+, CL is the total ligand concentration, CCu is the total Cu ion concentration, and KCu is the conditional stability constant.The complexation capacity (CCCu), that is, the amount of active binding sites per unit mass of DOM, was calculated as
(2)CCCu=CL(DOM)total,
where (DOM)total is the total concentration of DOM. KCu and CL were solved by a nonlinear regression analysis with the software 1st Opt 1.5 (7D-soft High Technology Inc., China). The optimum set of fitting parameters for each DOM sample was obtained by iteratively varying the adjustable parameter values until the sum of the squares of the differences between the observed and fitted values of I was minimized. Full, unconstrained optimization was achieved using the quasi-Newton algorithm.
### 2.4. Statistical Analysis
Correlations were analyzed between percentages of fluorescence response (Pi,n) to elucidate the transformation of DOM during the composting. Meanwhile, correlation analysis was also used to determine the correlations between Pi,n and parameters of DOM binding with Cu (i.e., CCCu and logKCu). Statistical analyses were performed with the software SPSS 11.5 (SPSS Inc., Chicago, IL, USA) for Windows.
## 2.1. Composting Procedure and Sample Preparation
The composting experiment was conducted in the same way with our previous study [22]. Manures and bulking agents were collected at local farms. Sawdust and corn stalks were chopped into 2-3 cm pieces and air dried before composting. The treatments of the composting piles on a dry volume basis were as follows. Treatment A: 50% pig manure + 50% sawdust; treatment B: 50% pig manure + 50% corn stalks; treatment C: 50% cattle manure + 50% sawdust; treatment D: 50% cattle manure + 50% corn stalks.The composting experiments were performed in cylindrical vessels (diameter: 500 mm; height: 600 mm). The uniform forced ventilation was equipped at a rate of 0.1 m3/min for 10 minutes at 60-minute intervals through perforated plates fixed at the bottom of the vessels to provide oxygen. The moisture content of each pile was kept at 50–60% (weight/weight) during composting. In the first 30 days of composting, the piles were turned periodically to keep the temperature under 60°C. Afterwards, the forced ventilation was stopped, and the piles were stirred daily for further humification.The composting process was stopped when the compost temperature equaled the ambient temperature with no measurable changes for approximately 20 days. The pig manure and cattle manure were composted for 71 days and 46 days, respectively. Samples were collected from treatment A and treatment B on days 1, 8, 11, 17, 32, and 71 (A1, B1, A8, B8, A11, B11, A17, B17, A32, B32, A71, and B71), whereas sampling was done on days 1, 6, 10, 13, 29, and 46 (C1, D1, C6, D6, C10, D10, C13, D13, C29, D29, C46, and D46) for treatment C and treatment D, respectively. The subsamples were taken at different positions within the vessel and then thoroughly mixed as a composite sample. Prior to extracting the DOM, the samples were air dried.
## 2.2. Extraction of DOM and Fluorescence Analysis
Two grams of subsamples were extracted with 40 mL of deionized water and shaken for 24 hours. The solution was then centrifuged at 10,000 rpm for 10 minutes. The supernatant was then filtered using Whatman GF/F glass microfiber filter papers that had previously been heated at 450°C to remove any possible organic matter. The extracts were immediately analyzed for dissolved organic carbon using the TOC analyzer (Liqui TOC, Elementar, Germany).The fluorescence of the filtered DOM samples was determined with a model F-4500 fluorescence spectrophotometer (Hitachi, Japan) with a 150-W Xe arc lamp. Prior to fluorescence analysis, all sub-samples for fluorescence analysis were diluted to the uniform concentration of 10 mg C/L to reduce inner filter effects [9]. To generate an EEM, excitation wavelengths were scanned from 200 to 400 nm in 2 nm steps, and the emitted fluorescence was detected between 300 and 550 nm in 5 nm steps. The band-pass width was 5 nm for excitation and 10 nm for emission, and the scan speed was 2400 nm/min [24].Fluorescence regional integration method was applied for spectral comparison to thoroughly explore the transformation of DOM composition during manure composting [20]. To avoid the scattering effects of fluorescence data, the treatment method of the first-order Rayleigh, Raman and second-order Rayleigh scatters was applied, which was proposed by Bahram et al. [25]. The EEM plots were generated from the fluorescence spectral data using Sigmaplot 10.0 software (Systat Software, Inc.).
## 2.3. Fluorescence Quenching Titration and Complexation Modeling
Fluorescence quenching titration was carried out to characterize the complexation of manure DOM with Cu according to the research of Plaza et al. [21]. Experiments were carried out by adding 0.01 M Cu(NO3)2 solutions to a series of glass bottles that contained 50 mL of DOM solution. The pH value was then adjusted to 7.0. All samples were shaken in the dark for 24 hours under a nitrogen atmosphere at constant temperature (25±0.1°C) to ensure complexation equilibrium.The selection of the wavelengths for the fluorescence titration was based on the highest fluorescence intensity observed from the EEM of the samples [21]. The complexation model of Ryan and Weber was used to determine the binding parameters between DOM and Cu ions [26]. The model assumes a simple 1 : 1 equilibrium between a metal ion and an organic ligand
(1)I=I0+(ICuL-I0)(12KCuCL)×((1+KCuCL+KCuCCu)2-4KCu2CCuCL1+KCuCL+KCuCCu-(1+KCuCL+KCuCCu)2-4KCu2CCuCL),
where I and I0 are the fluorescence intensity (arbitrary units) at the Cu concentration of CCu and at the start of the titration, respectively, ICuL is the limiting value below which the fluorescence cannot decrease with the addition of Cu2+, CL is the total ligand concentration, CCu is the total Cu ion concentration, and KCu is the conditional stability constant.The complexation capacity (CCCu), that is, the amount of active binding sites per unit mass of DOM, was calculated as
(2)CCCu=CL(DOM)total,
where (DOM)total is the total concentration of DOM. KCu and CL were solved by a nonlinear regression analysis with the software 1st Opt 1.5 (7D-soft High Technology Inc., China). The optimum set of fitting parameters for each DOM sample was obtained by iteratively varying the adjustable parameter values until the sum of the squares of the differences between the observed and fitted values of I was minimized. Full, unconstrained optimization was achieved using the quasi-Newton algorithm.
## 2.4. Statistical Analysis
Correlations were analyzed between percentages of fluorescence response (Pi,n) to elucidate the transformation of DOM during the composting. Meanwhile, correlation analysis was also used to determine the correlations between Pi,n and parameters of DOM binding with Cu (i.e., CCCu and logKCu). Statistical analyses were performed with the software SPSS 11.5 (SPSS Inc., Chicago, IL, USA) for Windows.
## 3. Results and Discussion
### 3.1. Change of DOM Concentrations during Composting
The total concentration of DOM in pig and cattle manure was reduced after composting (Figure1), which was similar to results obtained by Inbar et al. [14] and Huang et al. [12]. Cattle manure DOM concentrations continuously declined during the composting process, with a sharp reduction occurring in the initial stage of composting. During co-composting with corn stalk and sawdust, DOM in cattle manure was reduced by 27.4% and 31.4%, respectively. However, during cocomposting with exhausted grape marc, cattle manure DOM only reduced by 18.3% [27].Changes of dissolved organic matter (DOM) concentrations during manure composting.
(a)
(b)During composting of pig manure, DOM increased after a sharp initial decrease. At the end of the composting process, DOM concentration in pig manure with addition of sawdust and corn stalk decreased to 58.6% and 69.5%, respectively, of the raw materials after composting. In comparison to the cattle manure, there is more DOM degraded during pig manure composting than cattle manure, using the same composting method. This observation may reflect that pig manure contains far more DOM than cattle manure, but that the DOM in pig manure is also more easily degradable. In contrast, it was reported that about 95.8% of DOM in municipal solid waste had been degraded at the end of composting [13]. Our results and the cited study show that the rate of decrease in DOM concentration depends not only on the composting technique utilized, but also on the composition of the source material.
### 3.2. DOM Fluorescence Characteristics
As the EEM spectra evolution of DOM from treatment B and treatment D were similar to that from treatment A and treatment C, the DOM spectra of treatment A and treatment C are displayed as the representative in Figure2. According to the research of Chen et al. [20], the fluorescence of regions I, II, and IV in manure DOM are related to tyrosine-like, tryptophan-like, and soluble microbial byproduct-like materials while the fluorescence of regions III and V are related to fulvic-like and humic-like materials. Soluble microbial byproduct-like materials also contained another kind of tyrosine-like and tryptophan-like compounds, which were different from materials associated with region I and region II [28]. In the raw pig manure DOM (A1), the most intense fluorescence peak of Ex/Em = 280 nm/342 nm centered at region IV. Protein-like fluorescence peaks such as tyrosine-like and tryptophan-like peaks were associated with growth of living organisms in marine water [17]. However, these peaks were also detected in organic wastes, such as animal slurry and landfill leachates [8, 29]. In addition, we observed a peak of Ex/Em = 245 nm/399 nm centered at region III in raw pig manure DOM (A1), which may be attributed to aromatic and aliphatic groups in the DOM and widely labeled as fulvic-like substances [19]. However, there was no obvious humic-like fluorescence peak in pig manure DOM. Similar to raw pig manure, cattle manure DOM (C1) had intense tryptophan-like and tyrosine-like fluorescence peaks. However, cattle manure also had two intense fulvic acid-like and humic acid-like peaks centered at Ex/Em = 245 nm/400 nm and 305 nm/412 nm.Figure 2
Excitation-emission matrix (EEM) spectra of DOM from treatment A (pig manure + sawdust) on days 1, 17, 32, and 71 (A1, A17, A32, and A71) and treatment C (cattle manure + sawdust) on day 1, 13, 29, and 46 (C1, C13, C29, and C46).The percentage fluorescence response (Pi,n) of the five regions in the different composting samples is displayed in Figure 3. In the raw pig manure DOM (A1), the quantities of P1,n, P2,n, and P4,n in raw pig manure were approximately 16.6%, 19.9%, and 40.0% of total DOM, respectively, while the fulvic-like, and humic-like materials only contribute 10.9%, and 12.5%, respectively. In contrast, Pi,n of tyrosine-like, tryptophan-like and soluble microbial byproduct-like materials in cattle manure DOM were 17.1%, 23.2%, and 26.3%, while the fulvic acid-like and humic acid-like substances were 18.1% and 15.3%. Thus, there are more humic substances in cattle manure DOM than in pig manure DOM in the manures obtained for this study.Figure 3
Evolution of the percentage fluorescence response (Pi,n) during composting.DOM from treatment A (pig manure + sawdust) and treatment B (pig manure + corn stalk) was on days 1, 17, 32, and 71 (A1, B1, A17, B17, A32, B32, A71, and B71), treatment C (cattle manure + sawdust) and treatment D (cattle manure + corn stalk) on days 1, 13, 29, and 46 (C1, D1, C13, D13, C29, D29, C46, and D46).During the composting process, a sharp decrease of tyrosine-like, tryptophan-like, and soluble microbial byproduct-like fluorescence occurred in the initial stage of composting for pig manure and cattle manure, while fulvic-like and humic-like fluorescence displayed reverse trends. At the end of composting, there were only fulvic-like and humic-like fluorescence peaks left both in cattle manure and pig manure DOM. The totalP5,n values of pig manure or cattle manure cocomposting with sawdust increased by 16.3% and 4.2%, respectively, compared with the raw materials, while the values of P3,n increased by 6.4% and 7.6%, respectively. Similar results were obtained for DOM evolution of exhausted grape marc cocomposted with cattle manure and poultry manure in the study of Marhuenda-Egea et al. [10]. Shao et al. [13] also reported that P5,n increased from 18.8% to 54.8%, and humic acid-like compounds became the main component in municipal solid wastes DOM at the end of the composting process.
### 3.3. Implications of the DOM Change on Cu-DOM Complexation
The high determinative coefficients (DCs) in Table1 indicated that the experimental data fit well with the Ryan-Weber model [26]. The complexing capacity (CCCu) is an indicator presenting the amount of active binding sites for complexation with metal ions in a unit mass of DOM. The CCCu of raw pig manure ranged from 50.6 to 55.0 mmol/g, which was far higher than that of raw cattle manure. After the composting process, the manure DOM featured much lower CCCu values in the range of 0.41 to 1.99 mmol/g. The increases in P3,n and P5,n confirmed that humification of manure DOM occurred during composting. Previous study has shown that carboxylic- and phenolic-type groups are two kinds of binding sites in humic acids and fulvic acids [30]. Plaza et al. [31] investigated that total acidic functional group contents including phenolic OH group and carboxyl group increased in cattle manure after composing. Caricasole et al. [16] also reported the increasing of phenolic, carboxylic, and carbonylic C occurred in DOM from domestic organic wastes after composting. However, there were negative linear relationships between CCCu and P5,n (R2=0.58, P<0.01) or P3,n (R2=0.62, P<0.01) shown in Figure 4. In contrast, significantly positive linear correlations were found between CCCu and P4,n (R2=0.59, P<0.01) or P1,n (R2=0.54, P<0.01). The results may suggest that raw manure DOM has higher CCCu than that of composted manure DOM that can be attributed to its more tyrosine-like organic compounds and soluble microbial byproduct-like materials. The remarkable diversity of Cu complex capacity may be attributed to the difference of protein-like materials in manure DOM. In surface water, fulvic acid and humic acid in DOM were accepted as main components which complexed with Cu [6]. However, Yamashita and Jaffé [7] reported that nonhumic substances such as amino acids are likely engaged in the Cu complexation in surface water. de Zarruk et al. [9] have also verified that the fraction with high proteinaceous fluorescence in vinasse formed the most DOM-Cu complexes. Thus, the binding of Cu to DOM was inhibited properly due to the degradation of protein-like materials during composting, particularly in DOM from composted pig manure.Table 1
Fitting parameters of Ryan-Weber model.
DOM samplesa
Ex/Em (nm)b
I
Cu
L (AU)b
CCCu (mmol/g)b
log
K
Cu
b
DCb
A1
276/306
260.98
50.60
5.24
0.992**
A71
315/412
79.04
1.99
5.14
0.998**
B1
276/306
296.51
55.00
5.17
0.987**
B71
315/412
91.00
0.41
5.02
0.996**
C1
305/412
39.90
6.52
4.90
0.997**
C46
310/408
46.48
0.53
5.08
0.998**
D1
310/414
81.69
7.78
4.93
0.996**
D46
310/420
53.71
1.62
5.00
0.998**
aDOM from treatment A (pig manure + sawdust) on days 1 and 71 (A1, A71), treatment B (pig manure + corn stalk) on days 1 and 71 (B1, B71), treatment C (cattle manure + sawdust) on days 1 and 46 (C1, C46), and treatment D (cattle manure + corn stalk) on days 1 and 46 (D1, D46).
bEx/Em: selected wavelengths for the fluorescence titration; ICuL: fluorescence intensity of Cu ion-saturated complex (arbitrary units: AU); CCCu: complexing capacity (mmol/g); log KCu: the conditional stability constant; DC: determinative coefficiency.
**Statistical significance valueP<0.001.Relationships between percentages of fluorescence response of the five regions (Pi,n) and complexing capacity (CCCu) and the conditional stability constant (logKCu) *Statistical significance value P<0.05.
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)The conditional stability constants (logKCu) of Cu complexes with manure DOM were between 4.90 and 5.24 (Table 1), and the values are similar to those studies on surface water DOM [7]. The DOM of composted cattle manure with sawdust and corn stalk featured higher logKCu than that of raw cattle manure. On the contrary, pig manure DOM showed the decreasing trend after composting. The significantly positive linear correlation between logKCu and P4,n can be observed in Figure 4 (R2=0.51, P<0.01). This may indicate, in part, that some functional groups in soluble microbial byproduct-like materials play an important role in determining the conditional stability constant logKCu. Soluble microbial byproduct-like materials contain a large number of proteins and amino acids [20]. It has been reported that protein-like fraction of natural water DOM has the highest logKCu [23]. If it was also true for manure DOM, the decrease in the complex stability of pig manure DOM may be attributed to the degradation of large amounts of aromatic amino acid materials.
## 3.1. Change of DOM Concentrations during Composting
The total concentration of DOM in pig and cattle manure was reduced after composting (Figure1), which was similar to results obtained by Inbar et al. [14] and Huang et al. [12]. Cattle manure DOM concentrations continuously declined during the composting process, with a sharp reduction occurring in the initial stage of composting. During co-composting with corn stalk and sawdust, DOM in cattle manure was reduced by 27.4% and 31.4%, respectively. However, during cocomposting with exhausted grape marc, cattle manure DOM only reduced by 18.3% [27].Changes of dissolved organic matter (DOM) concentrations during manure composting.
(a)
(b)During composting of pig manure, DOM increased after a sharp initial decrease. At the end of the composting process, DOM concentration in pig manure with addition of sawdust and corn stalk decreased to 58.6% and 69.5%, respectively, of the raw materials after composting. In comparison to the cattle manure, there is more DOM degraded during pig manure composting than cattle manure, using the same composting method. This observation may reflect that pig manure contains far more DOM than cattle manure, but that the DOM in pig manure is also more easily degradable. In contrast, it was reported that about 95.8% of DOM in municipal solid waste had been degraded at the end of composting [13]. Our results and the cited study show that the rate of decrease in DOM concentration depends not only on the composting technique utilized, but also on the composition of the source material.
## 3.2. DOM Fluorescence Characteristics
As the EEM spectra evolution of DOM from treatment B and treatment D were similar to that from treatment A and treatment C, the DOM spectra of treatment A and treatment C are displayed as the representative in Figure2. According to the research of Chen et al. [20], the fluorescence of regions I, II, and IV in manure DOM are related to tyrosine-like, tryptophan-like, and soluble microbial byproduct-like materials while the fluorescence of regions III and V are related to fulvic-like and humic-like materials. Soluble microbial byproduct-like materials also contained another kind of tyrosine-like and tryptophan-like compounds, which were different from materials associated with region I and region II [28]. In the raw pig manure DOM (A1), the most intense fluorescence peak of Ex/Em = 280 nm/342 nm centered at region IV. Protein-like fluorescence peaks such as tyrosine-like and tryptophan-like peaks were associated with growth of living organisms in marine water [17]. However, these peaks were also detected in organic wastes, such as animal slurry and landfill leachates [8, 29]. In addition, we observed a peak of Ex/Em = 245 nm/399 nm centered at region III in raw pig manure DOM (A1), which may be attributed to aromatic and aliphatic groups in the DOM and widely labeled as fulvic-like substances [19]. However, there was no obvious humic-like fluorescence peak in pig manure DOM. Similar to raw pig manure, cattle manure DOM (C1) had intense tryptophan-like and tyrosine-like fluorescence peaks. However, cattle manure also had two intense fulvic acid-like and humic acid-like peaks centered at Ex/Em = 245 nm/400 nm and 305 nm/412 nm.Figure 2
Excitation-emission matrix (EEM) spectra of DOM from treatment A (pig manure + sawdust) on days 1, 17, 32, and 71 (A1, A17, A32, and A71) and treatment C (cattle manure + sawdust) on day 1, 13, 29, and 46 (C1, C13, C29, and C46).The percentage fluorescence response (Pi,n) of the five regions in the different composting samples is displayed in Figure 3. In the raw pig manure DOM (A1), the quantities of P1,n, P2,n, and P4,n in raw pig manure were approximately 16.6%, 19.9%, and 40.0% of total DOM, respectively, while the fulvic-like, and humic-like materials only contribute 10.9%, and 12.5%, respectively. In contrast, Pi,n of tyrosine-like, tryptophan-like and soluble microbial byproduct-like materials in cattle manure DOM were 17.1%, 23.2%, and 26.3%, while the fulvic acid-like and humic acid-like substances were 18.1% and 15.3%. Thus, there are more humic substances in cattle manure DOM than in pig manure DOM in the manures obtained for this study.Figure 3
Evolution of the percentage fluorescence response (Pi,n) during composting.DOM from treatment A (pig manure + sawdust) and treatment B (pig manure + corn stalk) was on days 1, 17, 32, and 71 (A1, B1, A17, B17, A32, B32, A71, and B71), treatment C (cattle manure + sawdust) and treatment D (cattle manure + corn stalk) on days 1, 13, 29, and 46 (C1, D1, C13, D13, C29, D29, C46, and D46).During the composting process, a sharp decrease of tyrosine-like, tryptophan-like, and soluble microbial byproduct-like fluorescence occurred in the initial stage of composting for pig manure and cattle manure, while fulvic-like and humic-like fluorescence displayed reverse trends. At the end of composting, there were only fulvic-like and humic-like fluorescence peaks left both in cattle manure and pig manure DOM. The totalP5,n values of pig manure or cattle manure cocomposting with sawdust increased by 16.3% and 4.2%, respectively, compared with the raw materials, while the values of P3,n increased by 6.4% and 7.6%, respectively. Similar results were obtained for DOM evolution of exhausted grape marc cocomposted with cattle manure and poultry manure in the study of Marhuenda-Egea et al. [10]. Shao et al. [13] also reported that P5,n increased from 18.8% to 54.8%, and humic acid-like compounds became the main component in municipal solid wastes DOM at the end of the composting process.
## 3.3. Implications of the DOM Change on Cu-DOM Complexation
The high determinative coefficients (DCs) in Table1 indicated that the experimental data fit well with the Ryan-Weber model [26]. The complexing capacity (CCCu) is an indicator presenting the amount of active binding sites for complexation with metal ions in a unit mass of DOM. The CCCu of raw pig manure ranged from 50.6 to 55.0 mmol/g, which was far higher than that of raw cattle manure. After the composting process, the manure DOM featured much lower CCCu values in the range of 0.41 to 1.99 mmol/g. The increases in P3,n and P5,n confirmed that humification of manure DOM occurred during composting. Previous study has shown that carboxylic- and phenolic-type groups are two kinds of binding sites in humic acids and fulvic acids [30]. Plaza et al. [31] investigated that total acidic functional group contents including phenolic OH group and carboxyl group increased in cattle manure after composing. Caricasole et al. [16] also reported the increasing of phenolic, carboxylic, and carbonylic C occurred in DOM from domestic organic wastes after composting. However, there were negative linear relationships between CCCu and P5,n (R2=0.58, P<0.01) or P3,n (R2=0.62, P<0.01) shown in Figure 4. In contrast, significantly positive linear correlations were found between CCCu and P4,n (R2=0.59, P<0.01) or P1,n (R2=0.54, P<0.01). The results may suggest that raw manure DOM has higher CCCu than that of composted manure DOM that can be attributed to its more tyrosine-like organic compounds and soluble microbial byproduct-like materials. The remarkable diversity of Cu complex capacity may be attributed to the difference of protein-like materials in manure DOM. In surface water, fulvic acid and humic acid in DOM were accepted as main components which complexed with Cu [6]. However, Yamashita and Jaffé [7] reported that nonhumic substances such as amino acids are likely engaged in the Cu complexation in surface water. de Zarruk et al. [9] have also verified that the fraction with high proteinaceous fluorescence in vinasse formed the most DOM-Cu complexes. Thus, the binding of Cu to DOM was inhibited properly due to the degradation of protein-like materials during composting, particularly in DOM from composted pig manure.Table 1
Fitting parameters of Ryan-Weber model.
DOM samplesa
Ex/Em (nm)b
I
Cu
L (AU)b
CCCu (mmol/g)b
log
K
Cu
b
DCb
A1
276/306
260.98
50.60
5.24
0.992**
A71
315/412
79.04
1.99
5.14
0.998**
B1
276/306
296.51
55.00
5.17
0.987**
B71
315/412
91.00
0.41
5.02
0.996**
C1
305/412
39.90
6.52
4.90
0.997**
C46
310/408
46.48
0.53
5.08
0.998**
D1
310/414
81.69
7.78
4.93
0.996**
D46
310/420
53.71
1.62
5.00
0.998**
aDOM from treatment A (pig manure + sawdust) on days 1 and 71 (A1, A71), treatment B (pig manure + corn stalk) on days 1 and 71 (B1, B71), treatment C (cattle manure + sawdust) on days 1 and 46 (C1, C46), and treatment D (cattle manure + corn stalk) on days 1 and 46 (D1, D46).
bEx/Em: selected wavelengths for the fluorescence titration; ICuL: fluorescence intensity of Cu ion-saturated complex (arbitrary units: AU); CCCu: complexing capacity (mmol/g); log KCu: the conditional stability constant; DC: determinative coefficiency.
**Statistical significance valueP<0.001.Relationships between percentages of fluorescence response of the five regions (Pi,n) and complexing capacity (CCCu) and the conditional stability constant (logKCu) *Statistical significance value P<0.05.
(a)
(b)
(c)
(d)
(e)
(f)
(g)
(h)
(i)
(j)The conditional stability constants (logKCu) of Cu complexes with manure DOM were between 4.90 and 5.24 (Table 1), and the values are similar to those studies on surface water DOM [7]. The DOM of composted cattle manure with sawdust and corn stalk featured higher logKCu than that of raw cattle manure. On the contrary, pig manure DOM showed the decreasing trend after composting. The significantly positive linear correlation between logKCu and P4,n can be observed in Figure 4 (R2=0.51, P<0.01). This may indicate, in part, that some functional groups in soluble microbial byproduct-like materials play an important role in determining the conditional stability constant logKCu. Soluble microbial byproduct-like materials contain a large number of proteins and amino acids [20]. It has been reported that protein-like fraction of natural water DOM has the highest logKCu [23]. If it was also true for manure DOM, the decrease in the complex stability of pig manure DOM may be attributed to the degradation of large amounts of aromatic amino acid materials.
## 4. Conclusion
The composting process reduced the amounts of DOM in pig and cattle manure. A majority of the protein-like materials were decomposed, and new humic-like and fulvic-like components were repolymerized. Humic-like materials in composted DOM were mainly transformed from tryptophan-like organic compounds, whereas fulvic-like components were largely transformed from soluble microbial byproduct-like substances.The complexing capacities of pig and cattle manure DOM decreased after composting, which can be attributed to the degradation of protein-like components. Furthermore, the degradation of protein-like components in pig manure reduced the stability constants oflogKCu. Our study suggests that the composting process might be a way to decrease the bioavailability, mobilization, and transport of manure DOM-Cu complexes, and lower the potential pollution risk to soil and ground water.
---
*Source: 289896-2012-10-17.xml* | 2012 |
# Prospective Evaluation of Unprocessed Core Needle Biopsy DNA and RNA Yield from Lung, Liver, and Kidney Tumors: Implications for Cancer Genomics
**Authors:** Mikhail T. Silk; Nina Mikkilineni; Tarik C. Silk; Emily C. Zabor; Irina Ostrovnaya; Ari A. Hakimi; James J. Hsieh; Etay Ziv; Natasha Rekhtman; Stephen B. Solomon; Jeremy C. Durack
**Journal:** Analytical Cellular Pathology
(2018)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2018/2898962
---
## Abstract
Context. Targeted needle biopsies are increasingly performed for the genetic characterization of cancer. While the nucleic acid content of core needle biopsies after standard pathology processing (i.e., formalin fixation and paraffin embedding (FFPE)) has been previously reported, little is known about the potential yield for molecular analysis at the time of biopsy sample acquisition. Objectives. Our objective was to improve the understanding of DNA and RNA yields from commonly used core needle biopsy techniques prior to sample processing. Methods. We performed 552 ex vivo 18 and 20G core biopsies in the lungs, liver, and kidneys. DNA and RNA were extracted from fresh-frozen core samples and quantified for statistical comparisons based on needle gauge, biopsy site, and tissue type. Results. Median tumor DNA yields from all 18G and 20G samples were 5880 ng and 2710 ng, respectively. Median tumor RNA yields from all 18G and 20G samples were 1100 ng and 230 ng, respectively. A wide range of DNA and RNA quantities (1060–13,390 ng and 370–6280 ng, respectively) were acquired. Median DNA and RNA yields from 18G needles were significantly greater than those from 20G needles across all organs (p<0.001). Conclusions. Core needle biopsy techniques for cancer diagnostics yield a broad range of DNA and RNA for molecular pathology, though quantities are greater than what has been reported for FFPE processed material. Since non-formalin-fixed DNA is advantageous for molecular studies, workflows that optimize core needle biopsy yield for molecular characterization should be explored.
---
## Body
## 1. Introduction
Image-guided solid tumor needle biopsies are frequently the starting point for modern cancer care. The ability to genomically characterize tumors has amplified the importance of tissue biopsies for cancer treatment selection, determining eligibility for clinical trials and understanding disease progression. In recent years, the brisk pace of discoveries revealing the genetic basis for malignant transformation has empowered oncologists, enabling therapies targeting specific molecular aberrations [1–3]. Needle biopsies can provide material for targeted genetic mutation analysis or to assess response to treatment, obviating the need for surgical biopsy.A high-quality, high-value biopsy is now defined by sufficient cancer cellularity for diagnosis and genomic analysis [4]. Diagnostic rates for contemporary targeted biopsies are high, but procedural practice guidelines have been slow to consider additional sampling requirements associated with molecular characterization [5]. Real-time CT, ultrasound, or MR image-guidance technologies have enabled more accurate percutaneous sampling of smaller targets [6]. However, the quantity of genetic material that can be obtained from small tumors is not easily defined due to many factors influencing biopsy yield, including normal tissue versus solid tumor cellularity and variable density of tumor nuclei per volume of tissue. Furthermore, single-site biopsies may not sufficiently portray intratumoral genetic heterogeneity [7].Deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) quantities required for a combination of routine clinical care, clinical trials, and research protocols often vary by individual institution and clinical team. Quantities sufficient for analysis will also vary in relation to the increasing number and range of molecular tests and technical advances in tissue analytics. Furthermore, several analyses of preanalytic factors related to tumor sequencing have raised concerns about low DNA and RNA yields from percutaneous tumor biopsies [8, 9].Importantly, standard core biopsy processing in pathology laboratories includes formalin fixation and paraffin embedding (FFPE). All downstream diagnostic and molecular assays are generally performed on thin sections prepared by microtomy from FFPE tissue blocks. In most studies to date, DNA and RNA content in core biopsies has been analyzed from FFPE material, whereas quantities of nucleic acid in unprocessed core biopsies are not well established. The goal of this study was to assess DNA and RNA quantities obtained using widely used core biopsy techniques from different cancer types in order to facilitate planning and decision-making with regard to molecular oncology testing. Knowledge of needle biopsy sampling capabilities can be essential for patient management in the setting of either known or suspected cancer. For both patient and healthcare provider, the anticipated value of quantitative data to plan needle biopsies is a better understanding of the potential risk versus clinical benefit [10–12].
## 2. Materials and Methods
We performed an Institutional Review Board-approved prospective study of surgically resected specimens at a comprehensive cancer center with a waiver of informed consent. Biopsies were performed in a tissue procurement service facility under direct visualization within 2 hours of surgical excision using 18-gauge (18G) and 20-gauge (20G) core biopsy needles (Temno Evolution, CareFusion, Waukegan, IL). Each surgical specimen was first dissected to allow direct visualization of the tumor and surrounding normal tissues. Biopsies were acquired from a variety of locations in normal parenchyma and tumor, avoiding areas of visible necrosis, and each 2 cm long core needle sampling tray was visually inspected. Core specimens that did not fill at least 85% of the sampling tray were discarded. Biopsies were performed in triplicate using 18G and 20G needles for both DNA and RNA processing. Biopsy sample sizes were estimated based on the number of samples required to achieve statistical significance from a preliminary kidney biopsy cohort. Each specimen was immediately placed in a 1.7 ml Eppendorf tube and snap frozen in liquid nitrogen. Samples were then stored in a −80°C freezer until molecular extractions were performed.
### 2.1. DNA Extraction
DNA was extracted using a standard protocol (DNeasy, Qiagen, Venlo, Netherlands) with 4μl RNase A added immediately after incubation. 50 μl of 10 nM Tris-Cl and 0.5 mM EDTA buffer (AE, pH 9.0) were used for the elution step.
### 2.2. RNA Extraction
RNA was extracted in an RNase-free environment according to the standard product protocol (RNeasy, Qiagen). All RNA samples were kept on dry ice during extraction. Tissues were lysed using 1.4 mm ceramic spheres (lysing matrix D, MP Biomedicals, Solon, OH) in a tissue homogenizer (Fast Prep 24, MP Biomedicals) and 650μl of lysis buffer (RLT Buffer, Qiagen) with the addition of on-column DNase digestion before RNA purification. 30 μl of RNase-free water was used to elute all samples.
### 2.3. Quantitative Measurements
DNA and RNA quantity (total DNA and RNA) was calculated from concentration multiplied by volume. Concentration was measured using a spectrophotometer (Nanodrop 2000, Thermo Scientific). If the measured ratio of absorbance at 260 : 280 was less than 1.6 for DNA or 1.8 for RNA, the samples were run for an additional time on the chromatography columns in the extraction protocol until the purity threshold was reached.
### 2.4. Statistical Analysis
The three repeated observations for each tumor sample were averaged into a single observation for analysis after examining the variation of repeated observations using descriptive statistics and graphical displays. Box plots of averaged data were generated for each tumor separately for RNA and DNA and by needle gauge (18G versus 20G) and tissue type (normal vs. tumor). For comparisons between tissue type and needle gauge, the Wilcoxon signed-rank test for paired data was used. For comparisons across organ sites (lung versus liver versus kidney), the Kruskal-Wallis rank sum test was applied. Ap value < 0.05 was considered statistically significant. Analyses were conducted using R software version 3.1.0 (R Core Development Team, Vienna, Austria).
### 2.5. Results
A total of 552 ex vivo biopsies from 46 surgically resected lung (n=15), liver (n=15), and kidney (n=16) specimens were performed. Table 1 indicates the number of biopsies obtained from each organ and the final pathologic diagnosis for each tumor type. The quantitative yield by organ, needle gauge, and tissue type (normal vs. tumor) is provided for DNA and RNA in Tables 2 and 3, respectively.Table 1
Pathologic tissue diagnoses by organ.
Kidney (n=16)
Clear cell carcinoma
13
Papillary carcinoma
1
Unclassified renal cell carcinoma
1
Chromophobe carcinoma
1
Liver (n=15)
Colorectal adenocarcinoma
12
Hepatocellular carcinoma
1
Cholangiocarcinoma
1
Lung adenocarcinoma
1
Lung (n=15)
Squamous cell carcinoma
6
Lung adenocarcinoma
5
Carcinoid
1
Metastatic poorly differentiated carcinoma
1
Mucinous carcinoma
1
Lymphoma
1
Total number of specimens biopsied
46
Total biopsy samples (normal + tumor tissues)
552Table 2
Median DNA (range) from 18- versus 20-gauge needle samples from normal and tumor tissues obtained from the kidney, lung, and liver.
18G biopsy (ng DNA)
20G biopsy (ng DNA)
p value (18G vs. 20G)
Any organ
Normal
4350 (1730, 13040)
1970 (700, 5620)
<0.001
Tumor
5880 (1060, 13390)
2710 (370, 6280)
<0.001
Kidney
Normal
4150 (1930, 11890)
1360 (700, 3870)
<0.001
Tumor
3170 (1180, 13390)
1450 (370, 4600)
<0.001
p value (normal vs. tumor)
1.00
0.890
Lung
Normal
3240 (1740, 13040)
1720 (760, 3520)
<0.001
Tumor
6910 (3070, 12570)
3350 (1110, 6280)
<0.001
p value (normal vs. tumor)
<0.001
<0.001
Liver
Normal
6050 (3790, 9740)
2480 (1890, 5620)
<0.001
Tumor
6190 (1060, 11530)
2630 (480, 5160)
<0.001
p value (normal vs. tumor)
0.804
0.847Table 3
Median RNA (range) from 18- versus 20-gauge needle samples from normal and tumor tissues obtained from the kidney, lung, and liver.
18G biopsy (ng RNA)
20G biopsy (ng RNA)
p value (18G vs. 20G)
Any organ
Normal
510 (30, 23540)
240 (30, 7090)
<0.001
Tumor
1100 (110, 17210)
230 (60, 5210)
<0.001a
Kidney
Normal
480 (230, 1210)
270 (110, 460)
<0.001
Tumor
510 (220, 3420)
290 (70, 2480)
<0.001
p value (normal vs. tumor)
0.855
0.217
Lung
Normal
150 (30, 4940)
120 (30, 400)
0.008
Tumor
2870 (170, 12700)
290 (70, 2480)
<0.001
p value (normal vs. tumor)
<0.001
<0.001
Liver
Normal
4740 (60, 23540)
700 (60, 7090)
<0.001
Tumor
1190 (110, 17210)
150 (60, 5210)
<0.001
p value (normal vs. tumor)
0.012
0.002
aExact test could not be performed due to ties, normal approximation used.
### 2.6. DNA Yield
For all pooled organ sites, the median DNA yield from the larger 18G biopsy needles was significantly greater (p<0.001) than that from 20G needles in both tumor and normal tissue samples. Median DNA quantities were greater for lung tumor samples compared to normal lung tissue (18G biopsies, p<0.001; 20G biopsies, p<0.001). There was no statistical difference in median DNA obtained from normal versus tumor tissues in the liver or kidney. For all cancer types sampled, the median DNA quantity acquired from single-needle pass 18G and 20G core biopsies was 5880 ng (range 1060–13390 ng) and 2710 ng (range 370–6280 ng), respectively. Box plots in Figure 1 depict median DNA content as well as interquartile ranges for each tissue type and biopsy needle gauge.Figure 1
DNA content by tissue type and needle gauge in (a) lung tumors, (b) liver tumors, and (c) kidney tumors (N18 = normal tissue/18 gauge, T18 = tumor tissue/18 gauge, N20 = normal tissue/20 gauge, and T20 = tumor tissues/20 gauge). The dark bar represents median DNA quantity, the surrounding box encompasses the 25–75% interquartile range (IQR), and the brackets reflect 1.5∗IQR. Diamonds represent statistical outliers.
(a)
(b)
(c)
### 2.7. RNA Yield
The median RNA yield from 18G needles was also significantly greater (p<0.001) than that from 20G biopsies when tumor and normal samples were pooled for all organs. Median RNA quantities were greater for lung tumor tissue compared to nonmalignant tissues for 18G and 20G from the lungs (18G biopsies (p=0.001) and 20G biopsies (p<0.001), respectively) and liver (p=0.012 and p=0.002, respectively), but not from the kidney. The median RNA quantity from 18G and 20G cancer biopsies was 1100 ng (range 110–17210 ng) and 230 ng (range 60–5210 ng), respectively. Box plots in Figure 2 depict median RNA quantities and interquartile range by needle gauge and tissue type.Figure 2
Logarithmic scale of RNA content by tissue type and needle gauge in (a) lung tumors, (b) liver tumors, and (c) kidney tumors (N18 = normal tissue/18 gauge, T18 = tumor tissue/18 gauge, N20 = normal tissue/20 gauge, T20 = tumor tissues/20 gauge). The dark bar is the median, the box encompasses the 25–75 interquartile range (IQR), the dotted brackets are 1.5∗IQR, and dots are outliers.
(a)
(b)
(c)
## 2.1. DNA Extraction
DNA was extracted using a standard protocol (DNeasy, Qiagen, Venlo, Netherlands) with 4μl RNase A added immediately after incubation. 50 μl of 10 nM Tris-Cl and 0.5 mM EDTA buffer (AE, pH 9.0) were used for the elution step.
## 2.2. RNA Extraction
RNA was extracted in an RNase-free environment according to the standard product protocol (RNeasy, Qiagen). All RNA samples were kept on dry ice during extraction. Tissues were lysed using 1.4 mm ceramic spheres (lysing matrix D, MP Biomedicals, Solon, OH) in a tissue homogenizer (Fast Prep 24, MP Biomedicals) and 650μl of lysis buffer (RLT Buffer, Qiagen) with the addition of on-column DNase digestion before RNA purification. 30 μl of RNase-free water was used to elute all samples.
## 2.3. Quantitative Measurements
DNA and RNA quantity (total DNA and RNA) was calculated from concentration multiplied by volume. Concentration was measured using a spectrophotometer (Nanodrop 2000, Thermo Scientific). If the measured ratio of absorbance at 260 : 280 was less than 1.6 for DNA or 1.8 for RNA, the samples were run for an additional time on the chromatography columns in the extraction protocol until the purity threshold was reached.
## 2.4. Statistical Analysis
The three repeated observations for each tumor sample were averaged into a single observation for analysis after examining the variation of repeated observations using descriptive statistics and graphical displays. Box plots of averaged data were generated for each tumor separately for RNA and DNA and by needle gauge (18G versus 20G) and tissue type (normal vs. tumor). For comparisons between tissue type and needle gauge, the Wilcoxon signed-rank test for paired data was used. For comparisons across organ sites (lung versus liver versus kidney), the Kruskal-Wallis rank sum test was applied. Ap value < 0.05 was considered statistically significant. Analyses were conducted using R software version 3.1.0 (R Core Development Team, Vienna, Austria).
## 2.5. Results
A total of 552 ex vivo biopsies from 46 surgically resected lung (n=15), liver (n=15), and kidney (n=16) specimens were performed. Table 1 indicates the number of biopsies obtained from each organ and the final pathologic diagnosis for each tumor type. The quantitative yield by organ, needle gauge, and tissue type (normal vs. tumor) is provided for DNA and RNA in Tables 2 and 3, respectively.Table 1
Pathologic tissue diagnoses by organ.
Kidney (n=16)
Clear cell carcinoma
13
Papillary carcinoma
1
Unclassified renal cell carcinoma
1
Chromophobe carcinoma
1
Liver (n=15)
Colorectal adenocarcinoma
12
Hepatocellular carcinoma
1
Cholangiocarcinoma
1
Lung adenocarcinoma
1
Lung (n=15)
Squamous cell carcinoma
6
Lung adenocarcinoma
5
Carcinoid
1
Metastatic poorly differentiated carcinoma
1
Mucinous carcinoma
1
Lymphoma
1
Total number of specimens biopsied
46
Total biopsy samples (normal + tumor tissues)
552Table 2
Median DNA (range) from 18- versus 20-gauge needle samples from normal and tumor tissues obtained from the kidney, lung, and liver.
18G biopsy (ng DNA)
20G biopsy (ng DNA)
p value (18G vs. 20G)
Any organ
Normal
4350 (1730, 13040)
1970 (700, 5620)
<0.001
Tumor
5880 (1060, 13390)
2710 (370, 6280)
<0.001
Kidney
Normal
4150 (1930, 11890)
1360 (700, 3870)
<0.001
Tumor
3170 (1180, 13390)
1450 (370, 4600)
<0.001
p value (normal vs. tumor)
1.00
0.890
Lung
Normal
3240 (1740, 13040)
1720 (760, 3520)
<0.001
Tumor
6910 (3070, 12570)
3350 (1110, 6280)
<0.001
p value (normal vs. tumor)
<0.001
<0.001
Liver
Normal
6050 (3790, 9740)
2480 (1890, 5620)
<0.001
Tumor
6190 (1060, 11530)
2630 (480, 5160)
<0.001
p value (normal vs. tumor)
0.804
0.847Table 3
Median RNA (range) from 18- versus 20-gauge needle samples from normal and tumor tissues obtained from the kidney, lung, and liver.
18G biopsy (ng RNA)
20G biopsy (ng RNA)
p value (18G vs. 20G)
Any organ
Normal
510 (30, 23540)
240 (30, 7090)
<0.001
Tumor
1100 (110, 17210)
230 (60, 5210)
<0.001a
Kidney
Normal
480 (230, 1210)
270 (110, 460)
<0.001
Tumor
510 (220, 3420)
290 (70, 2480)
<0.001
p value (normal vs. tumor)
0.855
0.217
Lung
Normal
150 (30, 4940)
120 (30, 400)
0.008
Tumor
2870 (170, 12700)
290 (70, 2480)
<0.001
p value (normal vs. tumor)
<0.001
<0.001
Liver
Normal
4740 (60, 23540)
700 (60, 7090)
<0.001
Tumor
1190 (110, 17210)
150 (60, 5210)
<0.001
p value (normal vs. tumor)
0.012
0.002
aExact test could not be performed due to ties, normal approximation used.
## 2.6. DNA Yield
For all pooled organ sites, the median DNA yield from the larger 18G biopsy needles was significantly greater (p<0.001) than that from 20G needles in both tumor and normal tissue samples. Median DNA quantities were greater for lung tumor samples compared to normal lung tissue (18G biopsies, p<0.001; 20G biopsies, p<0.001). There was no statistical difference in median DNA obtained from normal versus tumor tissues in the liver or kidney. For all cancer types sampled, the median DNA quantity acquired from single-needle pass 18G and 20G core biopsies was 5880 ng (range 1060–13390 ng) and 2710 ng (range 370–6280 ng), respectively. Box plots in Figure 1 depict median DNA content as well as interquartile ranges for each tissue type and biopsy needle gauge.Figure 1
DNA content by tissue type and needle gauge in (a) lung tumors, (b) liver tumors, and (c) kidney tumors (N18 = normal tissue/18 gauge, T18 = tumor tissue/18 gauge, N20 = normal tissue/20 gauge, and T20 = tumor tissues/20 gauge). The dark bar represents median DNA quantity, the surrounding box encompasses the 25–75% interquartile range (IQR), and the brackets reflect 1.5∗IQR. Diamonds represent statistical outliers.
(a)
(b)
(c)
## 2.7. RNA Yield
The median RNA yield from 18G needles was also significantly greater (p<0.001) than that from 20G biopsies when tumor and normal samples were pooled for all organs. Median RNA quantities were greater for lung tumor tissue compared to nonmalignant tissues for 18G and 20G from the lungs (18G biopsies (p=0.001) and 20G biopsies (p<0.001), respectively) and liver (p=0.012 and p=0.002, respectively), but not from the kidney. The median RNA quantity from 18G and 20G cancer biopsies was 1100 ng (range 110–17210 ng) and 230 ng (range 60–5210 ng), respectively. Box plots in Figure 2 depict median RNA quantities and interquartile range by needle gauge and tissue type.Figure 2
Logarithmic scale of RNA content by tissue type and needle gauge in (a) lung tumors, (b) liver tumors, and (c) kidney tumors (N18 = normal tissue/18 gauge, T18 = tumor tissue/18 gauge, N20 = normal tissue/20 gauge, T20 = tumor tissues/20 gauge). The dark bar is the median, the box encompasses the 25–75 interquartile range (IQR), the dotted brackets are 1.5∗IQR, and dots are outliers.
(a)
(b)
(c)
## 3. Discussion
In the recent years, cancer genetic technologies such as next-generation sequencing (NGS) have evolved, offering insights beyond traditional histopathologic or radiographic diagnoses [13]. Increased emphasis on molecular characterization has highlighted the role of targeted tissue biopsies in oncology, now routinely obtained for personalized treatment planning and for correlative studies in clinical trials. Gene sequencing for mutation profiling can be particularly challenging for solid tumors as formalin fixatives can disrupt DNA integrity [14]. As nucleic acid yield is not enumerated at the time of biopsy, even when on-site cytopathology review is performed, it can be difficult to determine whether sufficient genetic material has been obtained [15].While tumor heterogeneity, cellularity, and size as well as other preanalytic parameters and factors can impact downstream analytic success, important information can be gained from studies examining DNA and RNA yield using standardized ex vivo conditions [16, 17]. Notably, one previous study focused on lung tumor core biopsies reported no statistical difference between in vivo and ex vivo nuclei acid yields within cohorts of the same tumor type [17]. These same authors also attempted to predict tissue yields from core biopsies using needles of different gauges used in clinical practice with multivariate regression. A moderately strong correlation between calculated sampling volume and nucleic acid yield was observed, though analysis was limited to lung tumors and a relatively small number of biopsy samples. In this study, we examined a larger number of primary and metastatic tumor biopsies from the lungs, livers, and kidneys, increasing the potential generalizability of our findings.Only in the lung, and not in the liver or kidney, did we observe a statistically significant difference in DNA quantities obtained from normal parenchyma versus tumor tissues. In this case, increased cell density, particularly relative to normally air-filled lung tissues, and higher nuclear to cytoplasmic ratios may account for higher quantities of genetic material in lung tumor samples versus normal aerated lung [18, 19]. RNA differences were observed in the liver and lung but not observed in the kidney. A previous study also reported no difference in RNA content between primary renal malignancies and normal renal parenchyma [20].Similar to other studies, we found that larger 18G needles acquired twofold more DNA and fivefold more RNA on average compared to 20G needles, suggesting that additional needle passes may be necessary to obtain sufficient genetic material when using smaller-gauge needles. The clinical implications of substantial yield variance should not be minimized however, as linear models have not been validated in clinical practice, and smaller 20G needles can effectively reveal clinically meaningful mutations in lung tumors [17, 21]. Based on our findings, the notion that one additional large volume core needle pass will guarantee nucleic acid sampling adequacy could lead to analytic failure. In real-world practice, percutaneous biopsy indications, approach, and technique must be considered to minimize procedural morbidity and maximize efficacy. In a recent meta-analysis, the risk for complications following a lung biopsy correlated with larger biopsy needles [22]. Prior knowledge of minimum sampling requirements can facilitate estimation of biopsy feasibility, safety, and likelihood of success. In particular, the number and type of analytic studies to be performed can influence biopsy decisions as higher complication rates are associated with increased needle passes and larger-gauge needles [10, 11]. Ideally, specimen quantities would be well balanced with procedure time and the lowest achievable patient risk.The practical implications of this study are most apparent in relation to contemporary genetic testing requirements and sources of preanalytic biopsy sample variation. Minimum DNA for NGS can vary depending upon the clinical laboratory technology platform, as well as the target enrichment strategy and number of genes tested in a panel. For example, for the NGS platform currently used at our institution—hybridization capture MiSeq Illumina-based MSK-IMPACT assay [23]—200–250 ng of DNA is optimally required. DNA quantities as low as 10 ng may be successfully analyzed using the Ion Torrent (Thermo Scientific, Waltham, MA) platform [8], though sequencing errors may occur with limited DNA.Biopsy sample RNA profiling is highly dependent upon quality, as fragmentation or degradation by RNases can hamper mutational analysis. Microarray technologies can be used to analyze 500 ng of RNA, while NGS and amplification techniques can substantially lower thresholds for clinically meaningful sequencing, even to the level of single-cell genetic material [24, 25].Assuming no degradation, fragmentation, or other preanalytic disruption of biopsy samples, based on the median DNA content revealed in this study, a single 2 cm long 18G or 20G biopsy should be sufficient for most contemporary NGS assays. The same holds true for RNA; however, at the lower end of the RNA range, as low as 60 ng for 20G core needle biopsies, a single biopsy sample may be more susceptible to analytic failure. In practice, sample degradation and disruption do occur during acquisition and processing. The routine fixation methods fail to conserve the structure of nucleic acids and proteins in tissues. Even short-term treatment of sections with formalin has been shown to significantly reduce the DNA solubility. Similarly, the extraction of useful RNA from FFPE tissue is often compromised because of incomplete lysis leading to poor extraction efficiency. In a recent study, RNA extracted from FFPE samples was severely degraded compared to fresh-frozen samples [26]. In our results, the DNA and RNA yield prior to sample processing was 4–6-fold greater than what has previously been reported for FFPE cell blocks [27]. Our results reveal unprocessed nucleic acid yield from core biopsies, which can be frozen at the point of acquisition and submitted for DNA sequencing without FFPE. The potential limitation of this approach is that direct molecular characterization without histopathologic confirmation could result in unconstructive processing of nontumor tissues. Therefore, workflows that increase tumor yield from biopsies, such as radiographic image guidance to confirm needle position within tumor tissues, could mitigate this limitation. Ongoing work suggests that transmission optical spectroscopy imaging of fresh core samples can rapidly characterize tissues at the point of acquisition, which could be used to select appropriate samples for flash freezing prior to molecular diagnostic assays [28].Although the biopsy yields reported here can serve as a reference for physicians planning or performing molecular studies, the following limitations must be considered in regard to the generalizability of our data. Many factors may reduce the quantity of RNA and DNA suitable for analysis within a small solid tumor biopsy sample, including prior chemotherapy [29] or tumor-associated desmoplasia [30, 31]. In addition, necrotic tissue has a lower cellular content and can adversely impact biopsy efficacy, even when molecular studies are not planned [32, 33]. While each biopsy was visually screened for a minimum tissue sample length, we did not examine tissues at the microscopic level for cellular composition. We selected tumors that were large enough to fill a 2 cm core needle biopsy sampling tray. As increased tumor size is associated with increased necrosis [34], we cannot be certain that molecular quantities reported here are valid for larger tumors. By the same token, we cannot certify based on these data that tumors smaller than 2 cm will contain less genetic material in linear proportion to biopsy sample length. We also used common spectroscopy-based techniques to quantify the molecular content of biopsy samples; however, these types of measurements can result in overestimations. Decreased accuracy is attributed to poor 260 : 280 nm absorption ratios and cross-contamination of RNA and DNA [35]. We used recommended extraction protocols to remove DNA or RNA contaminants; however, remaining contaminants could have influenced yield. Finally, due to the wide variation in the operator technique impacting sampling volumes, we did not study common alternative needle biopsy methods such as fine-needle aspiration.In summary, we report a wide range of nucleic acid quantities obtained from core needle biopsies in organs commonly afflicted with primary or metastatic cancer. Overall, unprocessed sample nucleic acid quantities are increased relative to FFPE processed tissues; therefore, workflows that bypass fixation and paraffin-based processing may improve yield and utility of core needle sampling for molecular diagnostics.
---
*Source: 2898962-2018-12-10.xml* | 2898962-2018-12-10_2898962-2018-12-10.md | 29,288 | Prospective Evaluation of Unprocessed Core Needle Biopsy DNA and RNA Yield from Lung, Liver, and Kidney Tumors: Implications for Cancer Genomics | Mikhail T. Silk; Nina Mikkilineni; Tarik C. Silk; Emily C. Zabor; Irina Ostrovnaya; Ari A. Hakimi; James J. Hsieh; Etay Ziv; Natasha Rekhtman; Stephen B. Solomon; Jeremy C. Durack | Analytical Cellular Pathology
(2018) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2018/2898962 | 2898962-2018-12-10.xml | ---
## Abstract
Context. Targeted needle biopsies are increasingly performed for the genetic characterization of cancer. While the nucleic acid content of core needle biopsies after standard pathology processing (i.e., formalin fixation and paraffin embedding (FFPE)) has been previously reported, little is known about the potential yield for molecular analysis at the time of biopsy sample acquisition. Objectives. Our objective was to improve the understanding of DNA and RNA yields from commonly used core needle biopsy techniques prior to sample processing. Methods. We performed 552 ex vivo 18 and 20G core biopsies in the lungs, liver, and kidneys. DNA and RNA were extracted from fresh-frozen core samples and quantified for statistical comparisons based on needle gauge, biopsy site, and tissue type. Results. Median tumor DNA yields from all 18G and 20G samples were 5880 ng and 2710 ng, respectively. Median tumor RNA yields from all 18G and 20G samples were 1100 ng and 230 ng, respectively. A wide range of DNA and RNA quantities (1060–13,390 ng and 370–6280 ng, respectively) were acquired. Median DNA and RNA yields from 18G needles were significantly greater than those from 20G needles across all organs (p<0.001). Conclusions. Core needle biopsy techniques for cancer diagnostics yield a broad range of DNA and RNA for molecular pathology, though quantities are greater than what has been reported for FFPE processed material. Since non-formalin-fixed DNA is advantageous for molecular studies, workflows that optimize core needle biopsy yield for molecular characterization should be explored.
---
## Body
## 1. Introduction
Image-guided solid tumor needle biopsies are frequently the starting point for modern cancer care. The ability to genomically characterize tumors has amplified the importance of tissue biopsies for cancer treatment selection, determining eligibility for clinical trials and understanding disease progression. In recent years, the brisk pace of discoveries revealing the genetic basis for malignant transformation has empowered oncologists, enabling therapies targeting specific molecular aberrations [1–3]. Needle biopsies can provide material for targeted genetic mutation analysis or to assess response to treatment, obviating the need for surgical biopsy.A high-quality, high-value biopsy is now defined by sufficient cancer cellularity for diagnosis and genomic analysis [4]. Diagnostic rates for contemporary targeted biopsies are high, but procedural practice guidelines have been slow to consider additional sampling requirements associated with molecular characterization [5]. Real-time CT, ultrasound, or MR image-guidance technologies have enabled more accurate percutaneous sampling of smaller targets [6]. However, the quantity of genetic material that can be obtained from small tumors is not easily defined due to many factors influencing biopsy yield, including normal tissue versus solid tumor cellularity and variable density of tumor nuclei per volume of tissue. Furthermore, single-site biopsies may not sufficiently portray intratumoral genetic heterogeneity [7].Deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) quantities required for a combination of routine clinical care, clinical trials, and research protocols often vary by individual institution and clinical team. Quantities sufficient for analysis will also vary in relation to the increasing number and range of molecular tests and technical advances in tissue analytics. Furthermore, several analyses of preanalytic factors related to tumor sequencing have raised concerns about low DNA and RNA yields from percutaneous tumor biopsies [8, 9].Importantly, standard core biopsy processing in pathology laboratories includes formalin fixation and paraffin embedding (FFPE). All downstream diagnostic and molecular assays are generally performed on thin sections prepared by microtomy from FFPE tissue blocks. In most studies to date, DNA and RNA content in core biopsies has been analyzed from FFPE material, whereas quantities of nucleic acid in unprocessed core biopsies are not well established. The goal of this study was to assess DNA and RNA quantities obtained using widely used core biopsy techniques from different cancer types in order to facilitate planning and decision-making with regard to molecular oncology testing. Knowledge of needle biopsy sampling capabilities can be essential for patient management in the setting of either known or suspected cancer. For both patient and healthcare provider, the anticipated value of quantitative data to plan needle biopsies is a better understanding of the potential risk versus clinical benefit [10–12].
## 2. Materials and Methods
We performed an Institutional Review Board-approved prospective study of surgically resected specimens at a comprehensive cancer center with a waiver of informed consent. Biopsies were performed in a tissue procurement service facility under direct visualization within 2 hours of surgical excision using 18-gauge (18G) and 20-gauge (20G) core biopsy needles (Temno Evolution, CareFusion, Waukegan, IL). Each surgical specimen was first dissected to allow direct visualization of the tumor and surrounding normal tissues. Biopsies were acquired from a variety of locations in normal parenchyma and tumor, avoiding areas of visible necrosis, and each 2 cm long core needle sampling tray was visually inspected. Core specimens that did not fill at least 85% of the sampling tray were discarded. Biopsies were performed in triplicate using 18G and 20G needles for both DNA and RNA processing. Biopsy sample sizes were estimated based on the number of samples required to achieve statistical significance from a preliminary kidney biopsy cohort. Each specimen was immediately placed in a 1.7 ml Eppendorf tube and snap frozen in liquid nitrogen. Samples were then stored in a −80°C freezer until molecular extractions were performed.
### 2.1. DNA Extraction
DNA was extracted using a standard protocol (DNeasy, Qiagen, Venlo, Netherlands) with 4μl RNase A added immediately after incubation. 50 μl of 10 nM Tris-Cl and 0.5 mM EDTA buffer (AE, pH 9.0) were used for the elution step.
### 2.2. RNA Extraction
RNA was extracted in an RNase-free environment according to the standard product protocol (RNeasy, Qiagen). All RNA samples were kept on dry ice during extraction. Tissues were lysed using 1.4 mm ceramic spheres (lysing matrix D, MP Biomedicals, Solon, OH) in a tissue homogenizer (Fast Prep 24, MP Biomedicals) and 650μl of lysis buffer (RLT Buffer, Qiagen) with the addition of on-column DNase digestion before RNA purification. 30 μl of RNase-free water was used to elute all samples.
### 2.3. Quantitative Measurements
DNA and RNA quantity (total DNA and RNA) was calculated from concentration multiplied by volume. Concentration was measured using a spectrophotometer (Nanodrop 2000, Thermo Scientific). If the measured ratio of absorbance at 260 : 280 was less than 1.6 for DNA or 1.8 for RNA, the samples were run for an additional time on the chromatography columns in the extraction protocol until the purity threshold was reached.
### 2.4. Statistical Analysis
The three repeated observations for each tumor sample were averaged into a single observation for analysis after examining the variation of repeated observations using descriptive statistics and graphical displays. Box plots of averaged data were generated for each tumor separately for RNA and DNA and by needle gauge (18G versus 20G) and tissue type (normal vs. tumor). For comparisons between tissue type and needle gauge, the Wilcoxon signed-rank test for paired data was used. For comparisons across organ sites (lung versus liver versus kidney), the Kruskal-Wallis rank sum test was applied. Ap value < 0.05 was considered statistically significant. Analyses were conducted using R software version 3.1.0 (R Core Development Team, Vienna, Austria).
### 2.5. Results
A total of 552 ex vivo biopsies from 46 surgically resected lung (n=15), liver (n=15), and kidney (n=16) specimens were performed. Table 1 indicates the number of biopsies obtained from each organ and the final pathologic diagnosis for each tumor type. The quantitative yield by organ, needle gauge, and tissue type (normal vs. tumor) is provided for DNA and RNA in Tables 2 and 3, respectively.Table 1
Pathologic tissue diagnoses by organ.
Kidney (n=16)
Clear cell carcinoma
13
Papillary carcinoma
1
Unclassified renal cell carcinoma
1
Chromophobe carcinoma
1
Liver (n=15)
Colorectal adenocarcinoma
12
Hepatocellular carcinoma
1
Cholangiocarcinoma
1
Lung adenocarcinoma
1
Lung (n=15)
Squamous cell carcinoma
6
Lung adenocarcinoma
5
Carcinoid
1
Metastatic poorly differentiated carcinoma
1
Mucinous carcinoma
1
Lymphoma
1
Total number of specimens biopsied
46
Total biopsy samples (normal + tumor tissues)
552Table 2
Median DNA (range) from 18- versus 20-gauge needle samples from normal and tumor tissues obtained from the kidney, lung, and liver.
18G biopsy (ng DNA)
20G biopsy (ng DNA)
p value (18G vs. 20G)
Any organ
Normal
4350 (1730, 13040)
1970 (700, 5620)
<0.001
Tumor
5880 (1060, 13390)
2710 (370, 6280)
<0.001
Kidney
Normal
4150 (1930, 11890)
1360 (700, 3870)
<0.001
Tumor
3170 (1180, 13390)
1450 (370, 4600)
<0.001
p value (normal vs. tumor)
1.00
0.890
Lung
Normal
3240 (1740, 13040)
1720 (760, 3520)
<0.001
Tumor
6910 (3070, 12570)
3350 (1110, 6280)
<0.001
p value (normal vs. tumor)
<0.001
<0.001
Liver
Normal
6050 (3790, 9740)
2480 (1890, 5620)
<0.001
Tumor
6190 (1060, 11530)
2630 (480, 5160)
<0.001
p value (normal vs. tumor)
0.804
0.847Table 3
Median RNA (range) from 18- versus 20-gauge needle samples from normal and tumor tissues obtained from the kidney, lung, and liver.
18G biopsy (ng RNA)
20G biopsy (ng RNA)
p value (18G vs. 20G)
Any organ
Normal
510 (30, 23540)
240 (30, 7090)
<0.001
Tumor
1100 (110, 17210)
230 (60, 5210)
<0.001a
Kidney
Normal
480 (230, 1210)
270 (110, 460)
<0.001
Tumor
510 (220, 3420)
290 (70, 2480)
<0.001
p value (normal vs. tumor)
0.855
0.217
Lung
Normal
150 (30, 4940)
120 (30, 400)
0.008
Tumor
2870 (170, 12700)
290 (70, 2480)
<0.001
p value (normal vs. tumor)
<0.001
<0.001
Liver
Normal
4740 (60, 23540)
700 (60, 7090)
<0.001
Tumor
1190 (110, 17210)
150 (60, 5210)
<0.001
p value (normal vs. tumor)
0.012
0.002
aExact test could not be performed due to ties, normal approximation used.
### 2.6. DNA Yield
For all pooled organ sites, the median DNA yield from the larger 18G biopsy needles was significantly greater (p<0.001) than that from 20G needles in both tumor and normal tissue samples. Median DNA quantities were greater for lung tumor samples compared to normal lung tissue (18G biopsies, p<0.001; 20G biopsies, p<0.001). There was no statistical difference in median DNA obtained from normal versus tumor tissues in the liver or kidney. For all cancer types sampled, the median DNA quantity acquired from single-needle pass 18G and 20G core biopsies was 5880 ng (range 1060–13390 ng) and 2710 ng (range 370–6280 ng), respectively. Box plots in Figure 1 depict median DNA content as well as interquartile ranges for each tissue type and biopsy needle gauge.Figure 1
DNA content by tissue type and needle gauge in (a) lung tumors, (b) liver tumors, and (c) kidney tumors (N18 = normal tissue/18 gauge, T18 = tumor tissue/18 gauge, N20 = normal tissue/20 gauge, and T20 = tumor tissues/20 gauge). The dark bar represents median DNA quantity, the surrounding box encompasses the 25–75% interquartile range (IQR), and the brackets reflect 1.5∗IQR. Diamonds represent statistical outliers.
(a)
(b)
(c)
### 2.7. RNA Yield
The median RNA yield from 18G needles was also significantly greater (p<0.001) than that from 20G biopsies when tumor and normal samples were pooled for all organs. Median RNA quantities were greater for lung tumor tissue compared to nonmalignant tissues for 18G and 20G from the lungs (18G biopsies (p=0.001) and 20G biopsies (p<0.001), respectively) and liver (p=0.012 and p=0.002, respectively), but not from the kidney. The median RNA quantity from 18G and 20G cancer biopsies was 1100 ng (range 110–17210 ng) and 230 ng (range 60–5210 ng), respectively. Box plots in Figure 2 depict median RNA quantities and interquartile range by needle gauge and tissue type.Figure 2
Logarithmic scale of RNA content by tissue type and needle gauge in (a) lung tumors, (b) liver tumors, and (c) kidney tumors (N18 = normal tissue/18 gauge, T18 = tumor tissue/18 gauge, N20 = normal tissue/20 gauge, T20 = tumor tissues/20 gauge). The dark bar is the median, the box encompasses the 25–75 interquartile range (IQR), the dotted brackets are 1.5∗IQR, and dots are outliers.
(a)
(b)
(c)
## 2.1. DNA Extraction
DNA was extracted using a standard protocol (DNeasy, Qiagen, Venlo, Netherlands) with 4μl RNase A added immediately after incubation. 50 μl of 10 nM Tris-Cl and 0.5 mM EDTA buffer (AE, pH 9.0) were used for the elution step.
## 2.2. RNA Extraction
RNA was extracted in an RNase-free environment according to the standard product protocol (RNeasy, Qiagen). All RNA samples were kept on dry ice during extraction. Tissues were lysed using 1.4 mm ceramic spheres (lysing matrix D, MP Biomedicals, Solon, OH) in a tissue homogenizer (Fast Prep 24, MP Biomedicals) and 650μl of lysis buffer (RLT Buffer, Qiagen) with the addition of on-column DNase digestion before RNA purification. 30 μl of RNase-free water was used to elute all samples.
## 2.3. Quantitative Measurements
DNA and RNA quantity (total DNA and RNA) was calculated from concentration multiplied by volume. Concentration was measured using a spectrophotometer (Nanodrop 2000, Thermo Scientific). If the measured ratio of absorbance at 260 : 280 was less than 1.6 for DNA or 1.8 for RNA, the samples were run for an additional time on the chromatography columns in the extraction protocol until the purity threshold was reached.
## 2.4. Statistical Analysis
The three repeated observations for each tumor sample were averaged into a single observation for analysis after examining the variation of repeated observations using descriptive statistics and graphical displays. Box plots of averaged data were generated for each tumor separately for RNA and DNA and by needle gauge (18G versus 20G) and tissue type (normal vs. tumor). For comparisons between tissue type and needle gauge, the Wilcoxon signed-rank test for paired data was used. For comparisons across organ sites (lung versus liver versus kidney), the Kruskal-Wallis rank sum test was applied. Ap value < 0.05 was considered statistically significant. Analyses were conducted using R software version 3.1.0 (R Core Development Team, Vienna, Austria).
## 2.5. Results
A total of 552 ex vivo biopsies from 46 surgically resected lung (n=15), liver (n=15), and kidney (n=16) specimens were performed. Table 1 indicates the number of biopsies obtained from each organ and the final pathologic diagnosis for each tumor type. The quantitative yield by organ, needle gauge, and tissue type (normal vs. tumor) is provided for DNA and RNA in Tables 2 and 3, respectively.Table 1
Pathologic tissue diagnoses by organ.
Kidney (n=16)
Clear cell carcinoma
13
Papillary carcinoma
1
Unclassified renal cell carcinoma
1
Chromophobe carcinoma
1
Liver (n=15)
Colorectal adenocarcinoma
12
Hepatocellular carcinoma
1
Cholangiocarcinoma
1
Lung adenocarcinoma
1
Lung (n=15)
Squamous cell carcinoma
6
Lung adenocarcinoma
5
Carcinoid
1
Metastatic poorly differentiated carcinoma
1
Mucinous carcinoma
1
Lymphoma
1
Total number of specimens biopsied
46
Total biopsy samples (normal + tumor tissues)
552Table 2
Median DNA (range) from 18- versus 20-gauge needle samples from normal and tumor tissues obtained from the kidney, lung, and liver.
18G biopsy (ng DNA)
20G biopsy (ng DNA)
p value (18G vs. 20G)
Any organ
Normal
4350 (1730, 13040)
1970 (700, 5620)
<0.001
Tumor
5880 (1060, 13390)
2710 (370, 6280)
<0.001
Kidney
Normal
4150 (1930, 11890)
1360 (700, 3870)
<0.001
Tumor
3170 (1180, 13390)
1450 (370, 4600)
<0.001
p value (normal vs. tumor)
1.00
0.890
Lung
Normal
3240 (1740, 13040)
1720 (760, 3520)
<0.001
Tumor
6910 (3070, 12570)
3350 (1110, 6280)
<0.001
p value (normal vs. tumor)
<0.001
<0.001
Liver
Normal
6050 (3790, 9740)
2480 (1890, 5620)
<0.001
Tumor
6190 (1060, 11530)
2630 (480, 5160)
<0.001
p value (normal vs. tumor)
0.804
0.847Table 3
Median RNA (range) from 18- versus 20-gauge needle samples from normal and tumor tissues obtained from the kidney, lung, and liver.
18G biopsy (ng RNA)
20G biopsy (ng RNA)
p value (18G vs. 20G)
Any organ
Normal
510 (30, 23540)
240 (30, 7090)
<0.001
Tumor
1100 (110, 17210)
230 (60, 5210)
<0.001a
Kidney
Normal
480 (230, 1210)
270 (110, 460)
<0.001
Tumor
510 (220, 3420)
290 (70, 2480)
<0.001
p value (normal vs. tumor)
0.855
0.217
Lung
Normal
150 (30, 4940)
120 (30, 400)
0.008
Tumor
2870 (170, 12700)
290 (70, 2480)
<0.001
p value (normal vs. tumor)
<0.001
<0.001
Liver
Normal
4740 (60, 23540)
700 (60, 7090)
<0.001
Tumor
1190 (110, 17210)
150 (60, 5210)
<0.001
p value (normal vs. tumor)
0.012
0.002
aExact test could not be performed due to ties, normal approximation used.
## 2.6. DNA Yield
For all pooled organ sites, the median DNA yield from the larger 18G biopsy needles was significantly greater (p<0.001) than that from 20G needles in both tumor and normal tissue samples. Median DNA quantities were greater for lung tumor samples compared to normal lung tissue (18G biopsies, p<0.001; 20G biopsies, p<0.001). There was no statistical difference in median DNA obtained from normal versus tumor tissues in the liver or kidney. For all cancer types sampled, the median DNA quantity acquired from single-needle pass 18G and 20G core biopsies was 5880 ng (range 1060–13390 ng) and 2710 ng (range 370–6280 ng), respectively. Box plots in Figure 1 depict median DNA content as well as interquartile ranges for each tissue type and biopsy needle gauge.Figure 1
DNA content by tissue type and needle gauge in (a) lung tumors, (b) liver tumors, and (c) kidney tumors (N18 = normal tissue/18 gauge, T18 = tumor tissue/18 gauge, N20 = normal tissue/20 gauge, and T20 = tumor tissues/20 gauge). The dark bar represents median DNA quantity, the surrounding box encompasses the 25–75% interquartile range (IQR), and the brackets reflect 1.5∗IQR. Diamonds represent statistical outliers.
(a)
(b)
(c)
## 2.7. RNA Yield
The median RNA yield from 18G needles was also significantly greater (p<0.001) than that from 20G biopsies when tumor and normal samples were pooled for all organs. Median RNA quantities were greater for lung tumor tissue compared to nonmalignant tissues for 18G and 20G from the lungs (18G biopsies (p=0.001) and 20G biopsies (p<0.001), respectively) and liver (p=0.012 and p=0.002, respectively), but not from the kidney. The median RNA quantity from 18G and 20G cancer biopsies was 1100 ng (range 110–17210 ng) and 230 ng (range 60–5210 ng), respectively. Box plots in Figure 2 depict median RNA quantities and interquartile range by needle gauge and tissue type.Figure 2
Logarithmic scale of RNA content by tissue type and needle gauge in (a) lung tumors, (b) liver tumors, and (c) kidney tumors (N18 = normal tissue/18 gauge, T18 = tumor tissue/18 gauge, N20 = normal tissue/20 gauge, T20 = tumor tissues/20 gauge). The dark bar is the median, the box encompasses the 25–75 interquartile range (IQR), the dotted brackets are 1.5∗IQR, and dots are outliers.
(a)
(b)
(c)
## 3. Discussion
In the recent years, cancer genetic technologies such as next-generation sequencing (NGS) have evolved, offering insights beyond traditional histopathologic or radiographic diagnoses [13]. Increased emphasis on molecular characterization has highlighted the role of targeted tissue biopsies in oncology, now routinely obtained for personalized treatment planning and for correlative studies in clinical trials. Gene sequencing for mutation profiling can be particularly challenging for solid tumors as formalin fixatives can disrupt DNA integrity [14]. As nucleic acid yield is not enumerated at the time of biopsy, even when on-site cytopathology review is performed, it can be difficult to determine whether sufficient genetic material has been obtained [15].While tumor heterogeneity, cellularity, and size as well as other preanalytic parameters and factors can impact downstream analytic success, important information can be gained from studies examining DNA and RNA yield using standardized ex vivo conditions [16, 17]. Notably, one previous study focused on lung tumor core biopsies reported no statistical difference between in vivo and ex vivo nuclei acid yields within cohorts of the same tumor type [17]. These same authors also attempted to predict tissue yields from core biopsies using needles of different gauges used in clinical practice with multivariate regression. A moderately strong correlation between calculated sampling volume and nucleic acid yield was observed, though analysis was limited to lung tumors and a relatively small number of biopsy samples. In this study, we examined a larger number of primary and metastatic tumor biopsies from the lungs, livers, and kidneys, increasing the potential generalizability of our findings.Only in the lung, and not in the liver or kidney, did we observe a statistically significant difference in DNA quantities obtained from normal parenchyma versus tumor tissues. In this case, increased cell density, particularly relative to normally air-filled lung tissues, and higher nuclear to cytoplasmic ratios may account for higher quantities of genetic material in lung tumor samples versus normal aerated lung [18, 19]. RNA differences were observed in the liver and lung but not observed in the kidney. A previous study also reported no difference in RNA content between primary renal malignancies and normal renal parenchyma [20].Similar to other studies, we found that larger 18G needles acquired twofold more DNA and fivefold more RNA on average compared to 20G needles, suggesting that additional needle passes may be necessary to obtain sufficient genetic material when using smaller-gauge needles. The clinical implications of substantial yield variance should not be minimized however, as linear models have not been validated in clinical practice, and smaller 20G needles can effectively reveal clinically meaningful mutations in lung tumors [17, 21]. Based on our findings, the notion that one additional large volume core needle pass will guarantee nucleic acid sampling adequacy could lead to analytic failure. In real-world practice, percutaneous biopsy indications, approach, and technique must be considered to minimize procedural morbidity and maximize efficacy. In a recent meta-analysis, the risk for complications following a lung biopsy correlated with larger biopsy needles [22]. Prior knowledge of minimum sampling requirements can facilitate estimation of biopsy feasibility, safety, and likelihood of success. In particular, the number and type of analytic studies to be performed can influence biopsy decisions as higher complication rates are associated with increased needle passes and larger-gauge needles [10, 11]. Ideally, specimen quantities would be well balanced with procedure time and the lowest achievable patient risk.The practical implications of this study are most apparent in relation to contemporary genetic testing requirements and sources of preanalytic biopsy sample variation. Minimum DNA for NGS can vary depending upon the clinical laboratory technology platform, as well as the target enrichment strategy and number of genes tested in a panel. For example, for the NGS platform currently used at our institution—hybridization capture MiSeq Illumina-based MSK-IMPACT assay [23]—200–250 ng of DNA is optimally required. DNA quantities as low as 10 ng may be successfully analyzed using the Ion Torrent (Thermo Scientific, Waltham, MA) platform [8], though sequencing errors may occur with limited DNA.Biopsy sample RNA profiling is highly dependent upon quality, as fragmentation or degradation by RNases can hamper mutational analysis. Microarray technologies can be used to analyze 500 ng of RNA, while NGS and amplification techniques can substantially lower thresholds for clinically meaningful sequencing, even to the level of single-cell genetic material [24, 25].Assuming no degradation, fragmentation, or other preanalytic disruption of biopsy samples, based on the median DNA content revealed in this study, a single 2 cm long 18G or 20G biopsy should be sufficient for most contemporary NGS assays. The same holds true for RNA; however, at the lower end of the RNA range, as low as 60 ng for 20G core needle biopsies, a single biopsy sample may be more susceptible to analytic failure. In practice, sample degradation and disruption do occur during acquisition and processing. The routine fixation methods fail to conserve the structure of nucleic acids and proteins in tissues. Even short-term treatment of sections with formalin has been shown to significantly reduce the DNA solubility. Similarly, the extraction of useful RNA from FFPE tissue is often compromised because of incomplete lysis leading to poor extraction efficiency. In a recent study, RNA extracted from FFPE samples was severely degraded compared to fresh-frozen samples [26]. In our results, the DNA and RNA yield prior to sample processing was 4–6-fold greater than what has previously been reported for FFPE cell blocks [27]. Our results reveal unprocessed nucleic acid yield from core biopsies, which can be frozen at the point of acquisition and submitted for DNA sequencing without FFPE. The potential limitation of this approach is that direct molecular characterization without histopathologic confirmation could result in unconstructive processing of nontumor tissues. Therefore, workflows that increase tumor yield from biopsies, such as radiographic image guidance to confirm needle position within tumor tissues, could mitigate this limitation. Ongoing work suggests that transmission optical spectroscopy imaging of fresh core samples can rapidly characterize tissues at the point of acquisition, which could be used to select appropriate samples for flash freezing prior to molecular diagnostic assays [28].Although the biopsy yields reported here can serve as a reference for physicians planning or performing molecular studies, the following limitations must be considered in regard to the generalizability of our data. Many factors may reduce the quantity of RNA and DNA suitable for analysis within a small solid tumor biopsy sample, including prior chemotherapy [29] or tumor-associated desmoplasia [30, 31]. In addition, necrotic tissue has a lower cellular content and can adversely impact biopsy efficacy, even when molecular studies are not planned [32, 33]. While each biopsy was visually screened for a minimum tissue sample length, we did not examine tissues at the microscopic level for cellular composition. We selected tumors that were large enough to fill a 2 cm core needle biopsy sampling tray. As increased tumor size is associated with increased necrosis [34], we cannot be certain that molecular quantities reported here are valid for larger tumors. By the same token, we cannot certify based on these data that tumors smaller than 2 cm will contain less genetic material in linear proportion to biopsy sample length. We also used common spectroscopy-based techniques to quantify the molecular content of biopsy samples; however, these types of measurements can result in overestimations. Decreased accuracy is attributed to poor 260 : 280 nm absorption ratios and cross-contamination of RNA and DNA [35]. We used recommended extraction protocols to remove DNA or RNA contaminants; however, remaining contaminants could have influenced yield. Finally, due to the wide variation in the operator technique impacting sampling volumes, we did not study common alternative needle biopsy methods such as fine-needle aspiration.In summary, we report a wide range of nucleic acid quantities obtained from core needle biopsies in organs commonly afflicted with primary or metastatic cancer. Overall, unprocessed sample nucleic acid quantities are increased relative to FFPE processed tissues; therefore, workflows that bypass fixation and paraffin-based processing may improve yield and utility of core needle sampling for molecular diagnostics.
---
*Source: 2898962-2018-12-10.xml* | 2018 |
# Study on Law of Overlying Strata Breakage and Migration in Downward Mining of Extremely Close Coal Seams by Physical Similarity Simulation
**Authors:** Xiaobin Li; Wenrui He; Zhuhe Xu
**Journal:** Advances in Civil Engineering
(2020)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2020/2898971
---
## Abstract
Extremely close coal seam groups are widely distributed in China, and the main mining method is downward mining. In the downward mining process of extremely close coal seam groups, the violent movement of overlying strata will cause the redistribution of surrounding rock stress. It not only produces stress concentration on the pillar but also causes the roof of the lower coal seam to be broken and difficulty in maintaining the mining roadway. In this study, the physical similitude modeling method and field observations were used to study the breakage and migration law of overlying strata in the downward mining of extremely close coal seams. Results show that in the process of mining upper coal seam, the first weighting step of the main roof is 37.5 m and the periodic weighting step is 12.5 m. The occurrence of strata separation is beneficial to the prediction of roof weighting. When the working face advances to 25 m, the rock stratum approximating a parallelogram of height 5 m does not collapse, and the working face is relatively dangerous. When mining the lower coal seam, the overall pressure of the working face is large, but the periodic weighting of the working face is not obvious. The first collapse step of the immediate roof is 15 m. When mining the upper and lower coal seams, the subsidence of the monitoring point increases significantly at 17.5 and 15 m, respectively. The roof collapse of the lower coal seam occurs 2.5 m ahead of that of the upper coal seam. The hydraulic value of the support, roof fall height, and sloughing depth in the entire working face reach the maximum at the coal pillar, and the extreme points at the coal pillar are relatively concentrated. This research provides some guidance for the safe and efficient mining of extremely close coal seams in the future.
---
## Body
## 1. Introduction
China produces and consumes the most amount of coal in the world [1]. The proportion of coal in primary energy production and consumption is approximately 70%. According to the British Petroleum Statistical Review of World Energy 2018 program, China’s coal output reached 3.523 billion tons in 2017, accounting for 45.6% of the world’s total output [2]. Therefore, coal is important for China’s economic development [3]. Recently, with large-scale mining, coal seams with good geological conditions have been gradually exhausted [4]. Owing to the large proportion of extremely close coal seams in China, the mining of extremely close coal seams is becoming more common for improving the utilization of coal resources [5]. Extremely close coal seams are closely spaced and interact with each other during mining. With the decrease in spacing, the interaction between coal seams will gradually increase [6]. When the distance of coal seams is extremely close, the roof integrity of the lower coal seam will be damaged by the mining of the upper coal seam. The area above the roof is the caving zone formed by the collapsed immediate roof [7]. Moreover, the remaining pillars in the upper coal seam can easily cause stress concentration [8, 9]. Consequently, the roof structure and stress environment in the mining area of the lower coal seam changed, and many new mine pressure phenomena occurred during the mining of extremely close coal seams [10].Many engineering examples show that the violent movement of overlying strata will induce serious air leakages and water and gas accidents [11, 12]. Factors such as mining thickness, burial depth, and dip angle of coal seam are closely related to the law of overlying strata movement [13]. Because the process of strata movement is complex and no theoretical analysis method exists to satisfy engineering practices [14], physical similarity simulation is still the main method to study strata movement. This method overcomes the invisibility of mine pressure and overlying strata movement in field production, reflects the mechanical phenomenon visually, and can simulate the entire process in a short time. Based on physical similarity simulations, Huang et al. [15] studied the characteristics of overlying strata movement and strata behavior law in fully mechanized coal mining and backfilling longwall faces. Yuan et al. [16] proposed a new method for a similar material simulation experiment of steeply inclined upper protective layer mining and successfully applied it to the Nantong mining district. Niu et al. [17] constructed a similar physical model of coal rock to verify that a new method could be applied for the monitoring and early warning of coal and rock dynamic disasters. Zhang et al. [18] discussed the roof movement law of a fully mechanized mining face under a large dip angle through physical similarity simulations. Based on the engineering background of the Wuhushan coal mine, the law of overlying strata breakage and migration in the downward mining of extremely close coal seams was studied using the physical similitude modeling method. The current study can provide important guidance for the safe and efficient mining of extremely close coal seams in the future.Recently, experts and scholars have performed relevant research and exploration on the mining system and safety technology of extremely close coal seams. Based on a mechanical model and FLAC 3D numerical simulations, Wu et al. [19] studied the stress distribution under a coal pillar and optimized the roadway layout. Based on the in situ monitoring of overburden failure, Ning et al. [20] proposed a statistical formula for predicting the maximum height of overburden failure induced by extremely close coal seam mining. Zhang et al. [21] discussed the relationship between pillar size and roadway stability, incorporating a strain softening model for pillars and a double yield model for goaf material. By considering horizontal, vertical, and tangential stresses, Yan et al. [22] and Yuan et al. [23] proposed a new method for calculating the stress distribution of coal pillars. Based on experimental research and the UDEC software, Zhang et al. [24] analyzed the relationship between mining sequence under water body and overburden failure degree. Zhang et al. [25] incorporated geotechnical considerations for concurrent pillar recovery in extremely close coal seams, where mining sequence, panel layout, and pillar size were considered. Based on the observations of surface subsidence and three-dimensional simulations, Yu et al. [26] and Zhu et al. [27] studied the relationship between upper coal pillar and lower working face. Based on the floor failure mechanics model, Zhang et al. [28] proposed a new method to monitor floor failure depth and successfully applied it to the Caocun coal mine in China. Liu et al. [29] deduced a formula for the analysis of floor stress distribution and roadway position in extremely close coal seams. Aiming at the large deformation and destruction of roadway in extremely close coal seams, Li et al. [30] proposed an asymmetric support scheme, which has been successfully applied in other mines. Based on the finite element method, Ghabraie et al. [31] and Khanal et al. [32] developed a new method that can accurately simulate the collapse of overlying strata and surface subsidence during multiseam mining. Based on the law of gas occurrence and outburst characteristics, Wang et al. [33] and Konicek and Schreiber [34] studied the sequence of coal seam mining, key protective seam mining technology, and gas control measures.As described above, scholars primarily focused on the layout of mining roadways in the lower coal seam, gas control, mining sequence, and stress distribution of pillars and floor in the upper coal seam. However, studies regarding the breakage and migration law of overlying strata by physical similarity simulations are rare. Therefore, the law of strata breakage and migration must be studied to realize the safe and efficient mining of extremely close coal seams.
## 2. Engineering Background
### 2.1. Mining and Geological Condition
The Wuhushan coal mine, located in Wuhai city, Inner Mongolia autonomous region, China (Figure1), covers a mining area of 12.6 km2. Coals 9 and 10 are extremely close coal seams, with a 0.45–5.02 m layer of sandy mudstone in the middle. The inclination and strike length of the working face are 130 and 400 m, respectively. A fully mechanized mining method was adopted. The average thickness of coal 9 was 3.2 m. The rock strata above coal 9 were mudstone of average thickness 9.4 m and medium sandstone of average thickness 6.0 m, while the rock stratum below coal 9 was sandy mudstone of average thickness 2.0 m. The average thickness of coal 10 was 2.2 m. Its roof was also the floor of coal 9, and the rock stratum below coal 10 was siltstone of average thickness 5.4 m. Figure 2 shows the generalized stratigraphy column.Figure 1
Location of Wuhushan coal mine in Inner Mongolia autonomous region, China.Figure 2
Generalized stratigraphy column of the test site.
### 2.2. Experiments for Determining Rock Mechanical Properties
To understand the rock mechanical properties better, the coal and rock mass in the field were processed into a certain shape using the ZS-100 fully automatic drilling machine, SCM200 double-end grinder, HJD-150A concrete sawing machine, and SC200 automatic core-taking machine. Figure3 shows the coal and rock samples for use in experiments. Figure 4 shows the processing equipment. Uniaxial compression, splitting, and shear strength tests were performed on the samples to determine the mechanical parameters of coal and rock mass [35], as shown in Table 1.Figure 3
Coal and rock samples used in the experiments.Figure 4
Processing equipment: (a) ZS-100 fully automatic drilling machine; (b) SCM200 double-end grinder; (c) HJD-150A concrete sawing machine; (d) SC200 automatic core-taking machine.
(a)
(b)
(c)
(d)Table 1
Mechanical properties of coal-rock strata.
Number
Lithology
Density (kg/m³)
Shear modulus (GPa)
Bulk modulus (GPa)
Cohesion (MPa)
Friction angle (°)
Tensile strength (MPa)
1
Fine sandstone
2540
5.08
6.25
10.1
27
6.6
2
Siltstone
2640
5.82
6.09
7.9
28
7.1
3
Fine sandstone
2540
5.08
6.25
10.1
27
6.6
4
Sandy mudstone
2200
3.6
6.0
3.0
32
5.9
5
Siltstone
2640
5.82
6.09
7.9
28
7.1
6
Mudstone
2220
1.3
3.0
0.8
32
5.9
7
Medium sandstone
2540
5.91
6.81
10.7
31
6.5
8
Mudstone
2220
1.3
3.0
0.8
32
5.9
9
Coal 9
1400
0.76
1.6
2.65
25
1.8
10
Sandy mudstone
2200
3.6
6.0
3.0
32
5.9
11
Coal 10
1400
0.76
1.6
2.65
25
1.8
12
Siltstone
2640
5.82
6.09
7.9
28
7.1
## 2.1. Mining and Geological Condition
The Wuhushan coal mine, located in Wuhai city, Inner Mongolia autonomous region, China (Figure1), covers a mining area of 12.6 km2. Coals 9 and 10 are extremely close coal seams, with a 0.45–5.02 m layer of sandy mudstone in the middle. The inclination and strike length of the working face are 130 and 400 m, respectively. A fully mechanized mining method was adopted. The average thickness of coal 9 was 3.2 m. The rock strata above coal 9 were mudstone of average thickness 9.4 m and medium sandstone of average thickness 6.0 m, while the rock stratum below coal 9 was sandy mudstone of average thickness 2.0 m. The average thickness of coal 10 was 2.2 m. Its roof was also the floor of coal 9, and the rock stratum below coal 10 was siltstone of average thickness 5.4 m. Figure 2 shows the generalized stratigraphy column.Figure 1
Location of Wuhushan coal mine in Inner Mongolia autonomous region, China.Figure 2
Generalized stratigraphy column of the test site.
## 2.2. Experiments for Determining Rock Mechanical Properties
To understand the rock mechanical properties better, the coal and rock mass in the field were processed into a certain shape using the ZS-100 fully automatic drilling machine, SCM200 double-end grinder, HJD-150A concrete sawing machine, and SC200 automatic core-taking machine. Figure3 shows the coal and rock samples for use in experiments. Figure 4 shows the processing equipment. Uniaxial compression, splitting, and shear strength tests were performed on the samples to determine the mechanical parameters of coal and rock mass [35], as shown in Table 1.Figure 3
Coal and rock samples used in the experiments.Figure 4
Processing equipment: (a) ZS-100 fully automatic drilling machine; (b) SCM200 double-end grinder; (c) HJD-150A concrete sawing machine; (d) SC200 automatic core-taking machine.
(a)
(b)
(c)
(d)Table 1
Mechanical properties of coal-rock strata.
Number
Lithology
Density (kg/m³)
Shear modulus (GPa)
Bulk modulus (GPa)
Cohesion (MPa)
Friction angle (°)
Tensile strength (MPa)
1
Fine sandstone
2540
5.08
6.25
10.1
27
6.6
2
Siltstone
2640
5.82
6.09
7.9
28
7.1
3
Fine sandstone
2540
5.08
6.25
10.1
27
6.6
4
Sandy mudstone
2200
3.6
6.0
3.0
32
5.9
5
Siltstone
2640
5.82
6.09
7.9
28
7.1
6
Mudstone
2220
1.3
3.0
0.8
32
5.9
7
Medium sandstone
2540
5.91
6.81
10.7
31
6.5
8
Mudstone
2220
1.3
3.0
0.8
32
5.9
9
Coal 9
1400
0.76
1.6
2.65
25
1.8
10
Sandy mudstone
2200
3.6
6.0
3.0
32
5.9
11
Coal 10
1400
0.76
1.6
2.65
25
1.8
12
Siltstone
2640
5.82
6.09
7.9
28
7.1
## 3. Similar Material Simulation
### 3.1. Similarity Theory
A similar material simulation was performed based on the similarity theory. Geometric, time, and dynamic similarities must be considered between the model and prototype. Based on [18] and “dimensional analysis,” the dynamic similarity rate is presented as shown in equation (4). Meanwhile, Ren et al. [36] indicated that the dynamic similarity requires the force of the model and prototype at the corresponding point and time to be at a certain proportion to each other, and the main characteristics of force are reflected by compressive strength and bulk density in the experiment. Therefore, the compressive strength can be described as the dynamic similarity rate.The geometric similarity rate of the model is(1)CL=LmLp=150,where CL refers to the length similarity constant and Lm and Lp are the lengths of the similar material simulation model and prototype, respectively.The time similarity rate of the model is(2)CT=TmTp=CL=17,where CT is the time similarity constant and Tm and Tp are the time of the similar material simulation model and prototype, respectively.The density similarity rate of the model is(3)Cρ=ρmρp=11.6,where Cρ is the density similarity constant and ρm and ρp are the densities of the similar material simulation model and prototype, respectively.The dynamic similarity rate of the model is(4)Cσ=FmFp=mmdvm/dtmmddvd/dtd=σmσp=LmLpγmγp=LmLpρmρp=180,where Cσ is the strength similarity constant and σm, σp, γm, and γp are the compressive strengths and bulk densities of the similar material simulation model and prototype, respectively.According to the dynamic similarity rate formula, the compressive strength and bulk density of the strata in the model and prototype can be obtained (Table2).Table 2
Mechanics parameters of the similar rock material.
Prototype
Model
Number
Lithology
Bulk density (g/cm3)
Compressive strength (MPa)
Bulk density (g/cm3)
Compressive strength (MPa)
1
Fine sandstone
2.54
75.3
1.588
0.941
2
Siltstone
2.64
50.5
1.65
0.631
3
Fine sandstone
2.54
75.3
1.588
0.941
4
Sandy mudstone
2.2
30.2
1.375
0.377
5
Siltstone
2.64
44.2
1.65
0.553
6
Mudstone
2.22
32
1.388
0.400
7
Medium sandstone
2.54
85
1.588
1.063
8
Mudstone
2.22
30.1
1.388
0.377
9
Coal 9
1.4
9.5
0.875
0.119
10
Sandy mudstone
2.2
30.2
1.375
0.377
11
Coal 10
1.4
9.5
0.875
0.119
12
Siltstone
2.64
50.5
1.65
0.631
### 3.2. Overall Design of Physical Similarity Model
Based on the actual geological data of the fully mechanized mining face of the Wuhushan coal mine, fine sand, lime, and gypsum were selected as similar materials. The size of the test bench was 1800 mm (length) × 160 mm (width) × 1300 mm (height), and the plane stress model was adopted. The model building process is presented as follows [37]: (1) based on the calculation in Table 3, sand, lime, and gypsum were weighed and combined in a mixer. (2) The mixed material was paved evenly and compacted to maintain the required bulk density. Subsequently, mica powder was sprinkled on the strata to clarify the model bedding. (3) The other strata of the model followed the preceding steps until the required height was reached. (4) The weight of the overlying strata above the model was determined by adding the counterweight. (5) The model was dried naturally for five days.Table 3
Similar simulation strata distribution and material mixture ratio.
Number
Lithology
Thickness (mm)
Proportioning
Material consumption (kg)
Sand
Lime
Gypsum
Water
1
Fine sandstone
136.0
9 : 6 : 4
56.402
3.760
2.507
2.507
2
Siltstone
88.0
8 : 7 : 3
36.045
3.154
1.352
1.622
3
Fine sandstone
30.0
9 : 6 : 4
12.442
0.829
0.553
0.553
4
Sandy mudstone
106.0
10 : 7 : 3
44.404
3.108
1.332
1.954
5
Siltstone
152.0
9 : 8 : 2
63.037
5.603
1.401
2.802
6
Mudstone
84.0
8 : 8 : 2
34.406
3.441
0.860
1.548
7
Medium sandstone
120.0
8 : 6 : 4
49.152
3.686
2.458
2.212
8
Mudstone
188.0
10 : 7 : 3
78.755
5.513
2.363
3.465
9
Coal 9
64.0
10 : 9 : 1
26.810
2.413
0.268
1.180
10
Sandy mudstone
40.0
10 : 7 : 3
16.756
1.173
0.503
0.737
11
Coal 10
44.0
10 : 9 : 1
16.756
1.508
0.168
0.737
12
Siltstone
100.0
7 : 5 : 5
16.128
1.152
1.152
0.737Because the thickness and strength of the floor of coal 10 will not significantly affect the test, they can be simplified during building. The average height was 200 m from the actual working face to the surface. The thickness of the simulated overlying strata was 45.2 m, and the remaining height of 154.8 m was generated by the simulated pressure. The total height of this test was 1148 mm. The total excavation length was 1000 mm, and the length of each excavation was 50 mm. During building, the actual size of the strata should be adhered strictly. The specific amount of similar material is shown in Table3.
### 3.3. Layout of Monitoring Points
To acquire the displacement variation of the overlying strata, displacement monitoring points were evenly arranged. An electronic theodolite with high precision was used to measure strata movement during mining. As shown in Figure5, the monitoring points were evenly arranged above the roof of coal 10. Six detection lines were arranged in the model, namely, 2, 12, 22, 32, 42, and 52 cm from Coal 9. A total of 11 monitoring points were set on each line. A 15 cm × 10 cm grid design was adopted. To acquire data accurately during mining, a data collector was used to record the pressure data automatically; subsequently, the data are transmitted to a computer for analysis, as shown in Figure 6.Figure 5
Similar simulation model and layout of monitoring points.Figure 6
Data acquisition device.
## 3.1. Similarity Theory
A similar material simulation was performed based on the similarity theory. Geometric, time, and dynamic similarities must be considered between the model and prototype. Based on [18] and “dimensional analysis,” the dynamic similarity rate is presented as shown in equation (4). Meanwhile, Ren et al. [36] indicated that the dynamic similarity requires the force of the model and prototype at the corresponding point and time to be at a certain proportion to each other, and the main characteristics of force are reflected by compressive strength and bulk density in the experiment. Therefore, the compressive strength can be described as the dynamic similarity rate.The geometric similarity rate of the model is(1)CL=LmLp=150,where CL refers to the length similarity constant and Lm and Lp are the lengths of the similar material simulation model and prototype, respectively.The time similarity rate of the model is(2)CT=TmTp=CL=17,where CT is the time similarity constant and Tm and Tp are the time of the similar material simulation model and prototype, respectively.The density similarity rate of the model is(3)Cρ=ρmρp=11.6,where Cρ is the density similarity constant and ρm and ρp are the densities of the similar material simulation model and prototype, respectively.The dynamic similarity rate of the model is(4)Cσ=FmFp=mmdvm/dtmmddvd/dtd=σmσp=LmLpγmγp=LmLpρmρp=180,where Cσ is the strength similarity constant and σm, σp, γm, and γp are the compressive strengths and bulk densities of the similar material simulation model and prototype, respectively.According to the dynamic similarity rate formula, the compressive strength and bulk density of the strata in the model and prototype can be obtained (Table2).Table 2
Mechanics parameters of the similar rock material.
Prototype
Model
Number
Lithology
Bulk density (g/cm3)
Compressive strength (MPa)
Bulk density (g/cm3)
Compressive strength (MPa)
1
Fine sandstone
2.54
75.3
1.588
0.941
2
Siltstone
2.64
50.5
1.65
0.631
3
Fine sandstone
2.54
75.3
1.588
0.941
4
Sandy mudstone
2.2
30.2
1.375
0.377
5
Siltstone
2.64
44.2
1.65
0.553
6
Mudstone
2.22
32
1.388
0.400
7
Medium sandstone
2.54
85
1.588
1.063
8
Mudstone
2.22
30.1
1.388
0.377
9
Coal 9
1.4
9.5
0.875
0.119
10
Sandy mudstone
2.2
30.2
1.375
0.377
11
Coal 10
1.4
9.5
0.875
0.119
12
Siltstone
2.64
50.5
1.65
0.631
## 3.2. Overall Design of Physical Similarity Model
Based on the actual geological data of the fully mechanized mining face of the Wuhushan coal mine, fine sand, lime, and gypsum were selected as similar materials. The size of the test bench was 1800 mm (length) × 160 mm (width) × 1300 mm (height), and the plane stress model was adopted. The model building process is presented as follows [37]: (1) based on the calculation in Table 3, sand, lime, and gypsum were weighed and combined in a mixer. (2) The mixed material was paved evenly and compacted to maintain the required bulk density. Subsequently, mica powder was sprinkled on the strata to clarify the model bedding. (3) The other strata of the model followed the preceding steps until the required height was reached. (4) The weight of the overlying strata above the model was determined by adding the counterweight. (5) The model was dried naturally for five days.Table 3
Similar simulation strata distribution and material mixture ratio.
Number
Lithology
Thickness (mm)
Proportioning
Material consumption (kg)
Sand
Lime
Gypsum
Water
1
Fine sandstone
136.0
9 : 6 : 4
56.402
3.760
2.507
2.507
2
Siltstone
88.0
8 : 7 : 3
36.045
3.154
1.352
1.622
3
Fine sandstone
30.0
9 : 6 : 4
12.442
0.829
0.553
0.553
4
Sandy mudstone
106.0
10 : 7 : 3
44.404
3.108
1.332
1.954
5
Siltstone
152.0
9 : 8 : 2
63.037
5.603
1.401
2.802
6
Mudstone
84.0
8 : 8 : 2
34.406
3.441
0.860
1.548
7
Medium sandstone
120.0
8 : 6 : 4
49.152
3.686
2.458
2.212
8
Mudstone
188.0
10 : 7 : 3
78.755
5.513
2.363
3.465
9
Coal 9
64.0
10 : 9 : 1
26.810
2.413
0.268
1.180
10
Sandy mudstone
40.0
10 : 7 : 3
16.756
1.173
0.503
0.737
11
Coal 10
44.0
10 : 9 : 1
16.756
1.508
0.168
0.737
12
Siltstone
100.0
7 : 5 : 5
16.128
1.152
1.152
0.737Because the thickness and strength of the floor of coal 10 will not significantly affect the test, they can be simplified during building. The average height was 200 m from the actual working face to the surface. The thickness of the simulated overlying strata was 45.2 m, and the remaining height of 154.8 m was generated by the simulated pressure. The total height of this test was 1148 mm. The total excavation length was 1000 mm, and the length of each excavation was 50 mm. During building, the actual size of the strata should be adhered strictly. The specific amount of similar material is shown in Table3.
## 3.3. Layout of Monitoring Points
To acquire the displacement variation of the overlying strata, displacement monitoring points were evenly arranged. An electronic theodolite with high precision was used to measure strata movement during mining. As shown in Figure5, the monitoring points were evenly arranged above the roof of coal 10. Six detection lines were arranged in the model, namely, 2, 12, 22, 32, 42, and 52 cm from Coal 9. A total of 11 monitoring points were set on each line. A 15 cm × 10 cm grid design was adopted. To acquire data accurately during mining, a data collector was used to record the pressure data automatically; subsequently, the data are transmitted to a computer for analysis, as shown in Figure 6.Figure 5
Similar simulation model and layout of monitoring points.Figure 6
Data acquisition device.
## 4. Mining Result Analysis of Upper Coal Seam
### 4.1. Mine Pressure Appearance Law
The open-off cut of the working face is 7.5 m. When the working face advances to 17.5 m, the first collapse of the immediate roof occurs. The collapse height is 2.5 m. As shown in Figure7, when the working face advances to 25 m, the mining-induced fracture will not extend to the main roof. The collapsed strata form a two-part masonry beam articulated structure. The collapse height is 5 m, which is approximately 1.5 times the mining height. The upper minimum collapse range is 10 m. Because of its self-stabilization ability, the strata approximating a parallelogram did not collapse. However, when the working face advances to 27.5 m, the first collapse of the main roof occurs. The working face encounters the first weighting of the main roof. As shown in Figure 8, the overlying strata begin to separate when the working face advances to 32.5 m. The first periodic weighting of the main roof occurs when the working face advances to 37.5 m (Figure 9). The second periodic weighting of the main roof occurs when the working face advances to 50 m (Figure 10). The average periodic weighting step is 12.5 m.Figure 7
25 m advancement.Figure 8
32.5 m advancement.Figure 9
37.5 m advancement.Figure 10
50 m advancement.From the discussion above, it is clear that with the advance of the working face, the first collapse of the immediate roof and the first and periodic weighting of the main roof will occur. Finally, the overlying strata will collapse in a large area. When the periodic weighting of the main roof occurs, the collapsed roof will exhibit a specific regularity. The collapse length of the overlying strata is the same, which is approximately equal to the periodic weighting step. From the working face up, the collapsed strata become more orderly and a stable articulated structure can be formed easily. This is because the strength of the first collapsed strata is low, and with the advance of the working face, the collapsed strata are gradually crushed by the strata above.
### 4.2. Analysis of Roof Subsidence
As shown in Figure11, the subsidence of the overlying strata shows a certain regularity. The maximum and uniform subsidence is line 1, which is 2 cm from coal 9. The variation range is between 55 and 64 mm, which is close to coal seam thickness. The maximum subsidence of lines 2, 3, 4, 5, and 6 is 48, 45, 42, 36, and 26 mm, respectively. This shows that the subsidence of the overlying strata decreases with the increase in distance from the coal seam. This is because with the increase in distance from the coal seam, the probability of interaction increases between the collapsed overlying strata. In addition, some stable structures may be formed between the large strata. Consequently, the space between the strata and the dilatancy coefficient increase. Ultimately, the subsidence of the overlying strata is reduced. When the advancement distance of the working face is 17.5 m, the subsidence of the monitoring point increases significantly. This phenomenon is caused by a sudden roof caving in the gob, which is consistent with the physical similarity simulation results.Figure 11
Subsidence of monitoring points.
## 4.1. Mine Pressure Appearance Law
The open-off cut of the working face is 7.5 m. When the working face advances to 17.5 m, the first collapse of the immediate roof occurs. The collapse height is 2.5 m. As shown in Figure7, when the working face advances to 25 m, the mining-induced fracture will not extend to the main roof. The collapsed strata form a two-part masonry beam articulated structure. The collapse height is 5 m, which is approximately 1.5 times the mining height. The upper minimum collapse range is 10 m. Because of its self-stabilization ability, the strata approximating a parallelogram did not collapse. However, when the working face advances to 27.5 m, the first collapse of the main roof occurs. The working face encounters the first weighting of the main roof. As shown in Figure 8, the overlying strata begin to separate when the working face advances to 32.5 m. The first periodic weighting of the main roof occurs when the working face advances to 37.5 m (Figure 9). The second periodic weighting of the main roof occurs when the working face advances to 50 m (Figure 10). The average periodic weighting step is 12.5 m.Figure 7
25 m advancement.Figure 8
32.5 m advancement.Figure 9
37.5 m advancement.Figure 10
50 m advancement.From the discussion above, it is clear that with the advance of the working face, the first collapse of the immediate roof and the first and periodic weighting of the main roof will occur. Finally, the overlying strata will collapse in a large area. When the periodic weighting of the main roof occurs, the collapsed roof will exhibit a specific regularity. The collapse length of the overlying strata is the same, which is approximately equal to the periodic weighting step. From the working face up, the collapsed strata become more orderly and a stable articulated structure can be formed easily. This is because the strength of the first collapsed strata is low, and with the advance of the working face, the collapsed strata are gradually crushed by the strata above.
## 4.2. Analysis of Roof Subsidence
As shown in Figure11, the subsidence of the overlying strata shows a certain regularity. The maximum and uniform subsidence is line 1, which is 2 cm from coal 9. The variation range is between 55 and 64 mm, which is close to coal seam thickness. The maximum subsidence of lines 2, 3, 4, 5, and 6 is 48, 45, 42, 36, and 26 mm, respectively. This shows that the subsidence of the overlying strata decreases with the increase in distance from the coal seam. This is because with the increase in distance from the coal seam, the probability of interaction increases between the collapsed overlying strata. In addition, some stable structures may be formed between the large strata. Consequently, the space between the strata and the dilatancy coefficient increase. Ultimately, the subsidence of the overlying strata is reduced. When the advancement distance of the working face is 17.5 m, the subsidence of the monitoring point increases significantly. This phenomenon is caused by a sudden roof caving in the gob, which is consistent with the physical similarity simulation results.Figure 11
Subsidence of monitoring points.
## 5. Mining Result Analysis of Lower Coal Seam
### 5.1. Mine Pressure Appearance Law
When the lower coal seam was mined, the overlying strata and the roof of the upper coal seam collapsed and recemented. Owing to the mining activity of the upper coal seam, the roof of coal 10 was damaged and generated some microfractures; additionally, the roof strength was low. Therefore, the first collapse of the immediate roof occurred at 15 m during mining. The roof collapse of the lower coal seam was 2.5 m ahead of that of the upper coal seam. In the subsequent mining process, no obvious periodic weighting of the main roof occurred, the roof falls with mining, and no obvious structure was formed, as shown in Figure12.Figure 12
Roof collapse patterns at different distances.
### 5.2. Analysis of Roof Subsidence
As shown in Figures11 and 13, the subsidence of the overlying strata has little effect on the outside of the mining area. However, the subsidence of the overlying strata above the mining area changed significantly. Most of the subsidence was concentrated between 80 and 104 mm. The subsidence of lines 1, 2, and 3 was approximately equal to the thickness of Coal 10. Owing to effect of mining, the original structure of the overlying strata was destroyed and the subsidence of the upward detection lines increased. Ultimately, the collapsed strata’s dilatancy coefficient would be reduced, and the rock mass further compacted. The increase in the sinking point of lines 4, 5, and 6 exceeded the coal seam thickness after mining Coal 10, and the maximum increase could reach to 227.9%. This was caused by the decrease in the coefficient of fragmentation and expansion. Meanwhile, it could be attributed to Coal 10 being directly excavated before the strata movement had stopped completely. As shown in Figure 13, when the advancement distance of the working face is 15 m, the subsidence of the monitoring point increases sharply and the roof collapses in a large area. The subsidence curve is approximately symmetric, with an unstable area on both sides and no obvious periodic weighting area in the middle.Figure 13
Subsidence of monitoring points.
## 5.1. Mine Pressure Appearance Law
When the lower coal seam was mined, the overlying strata and the roof of the upper coal seam collapsed and recemented. Owing to the mining activity of the upper coal seam, the roof of coal 10 was damaged and generated some microfractures; additionally, the roof strength was low. Therefore, the first collapse of the immediate roof occurred at 15 m during mining. The roof collapse of the lower coal seam was 2.5 m ahead of that of the upper coal seam. In the subsequent mining process, no obvious periodic weighting of the main roof occurred, the roof falls with mining, and no obvious structure was formed, as shown in Figure12.Figure 12
Roof collapse patterns at different distances.
## 5.2. Analysis of Roof Subsidence
As shown in Figures11 and 13, the subsidence of the overlying strata has little effect on the outside of the mining area. However, the subsidence of the overlying strata above the mining area changed significantly. Most of the subsidence was concentrated between 80 and 104 mm. The subsidence of lines 1, 2, and 3 was approximately equal to the thickness of Coal 10. Owing to effect of mining, the original structure of the overlying strata was destroyed and the subsidence of the upward detection lines increased. Ultimately, the collapsed strata’s dilatancy coefficient would be reduced, and the rock mass further compacted. The increase in the sinking point of lines 4, 5, and 6 exceeded the coal seam thickness after mining Coal 10, and the maximum increase could reach to 227.9%. This was caused by the decrease in the coefficient of fragmentation and expansion. Meanwhile, it could be attributed to Coal 10 being directly excavated before the strata movement had stopped completely. As shown in Figure 13, when the advancement distance of the working face is 15 m, the subsidence of the monitoring point increases sharply and the roof collapses in a large area. The subsidence curve is approximately symmetric, with an unstable area on both sides and no obvious periodic weighting area in the middle.Figure 13
Subsidence of monitoring points.
## 6. Field Observation
### 6.1. Layout of Stations
To understand the law of mine pressure in extremely close coal seams, the mine pressure in 1001 working face of the Wuhushan coal mine was observed. Eight stations were arranged in the working face. The stations were densely distributed under the coal pillar and evenly distributed in other places, as shown in Figure14. The stations were located at hydraulic support nos. 6, 20, 24, 28, 31, 56, 81, and 106.Figure 14
Layout of stations.
### 6.2. Analysis of Observation Results
The collected hydraulic information of all supports was divided into four regions: the upper, middle, coal pillar, and lower regions. The pressure values of the hydraulic support and the change characteristics of the roof fall and sloughing in each region were considered, as shown in Figure15.Figure 15
Hydraulic information of support and variation characteristics of roof fall and sloughing. (a) Upper region; (b) middle region; (c) coal pillar region; (d) lower region.
(a)
(b)
(c)
(d)From the data, it can be concluded that the first collapse steps of the immediate roof in the upper, middle, coal pillar, and lower regions of the working face are 16, 16, 14.5, and 14.3 m, respectively. Comprehensive analysis shows that the average first collapse step of the immediate roof in 1001 working face is 15 m and no obvious periodic weighting is shown, which is consistent with the physical similarity simulation results. The hydraulic value of the support, roof fall height, and sloughing depth in the entire working face reached the maximum at the coal pillar, and the extreme points at the coal pillar were relatively concentrated. Furthermore, maximum points appeared at the upper and lower regions, but the entire working face was not as large as the coal pillar. The hydraulic value of the working face was generally large, roof fall and sloughing occurred occasionally, and preventive measures must be improved.
## 6.1. Layout of Stations
To understand the law of mine pressure in extremely close coal seams, the mine pressure in 1001 working face of the Wuhushan coal mine was observed. Eight stations were arranged in the working face. The stations were densely distributed under the coal pillar and evenly distributed in other places, as shown in Figure14. The stations were located at hydraulic support nos. 6, 20, 24, 28, 31, 56, 81, and 106.Figure 14
Layout of stations.
## 6.2. Analysis of Observation Results
The collected hydraulic information of all supports was divided into four regions: the upper, middle, coal pillar, and lower regions. The pressure values of the hydraulic support and the change characteristics of the roof fall and sloughing in each region were considered, as shown in Figure15.Figure 15
Hydraulic information of support and variation characteristics of roof fall and sloughing. (a) Upper region; (b) middle region; (c) coal pillar region; (d) lower region.
(a)
(b)
(c)
(d)From the data, it can be concluded that the first collapse steps of the immediate roof in the upper, middle, coal pillar, and lower regions of the working face are 16, 16, 14.5, and 14.3 m, respectively. Comprehensive analysis shows that the average first collapse step of the immediate roof in 1001 working face is 15 m and no obvious periodic weighting is shown, which is consistent with the physical similarity simulation results. The hydraulic value of the support, roof fall height, and sloughing depth in the entire working face reached the maximum at the coal pillar, and the extreme points at the coal pillar were relatively concentrated. Furthermore, maximum points appeared at the upper and lower regions, but the entire working face was not as large as the coal pillar. The hydraulic value of the working face was generally large, roof fall and sloughing occurred occasionally, and preventive measures must be improved.
## 7. Conclusions
In this study, the physical similitude modeling method was used to study the breakage and migration law of overlying strata in the downward mining of extremely close coal seams, which was verified by field observations in the working face. The conclusions are as follows:(1)
In the process of mining upper coal seam, the first weighting step of the main roof was 37.5 m, and the periodic weighting step was 12.5 m. The occurrence of strata separation was beneficial to the prediction of roof weighting.(2)
When the working face advanced to 25 m, the rock stratum approximating a parallelogram of height 5 m did not collapse, and the working face was relatively dangerous.(3)
When mining the lower coal seam, the overall pressure of the working face was large, but the periodic weighting of the working face was not obvious. The first collapse step of the immediate roof was 15 m.(4)
When mining the upper and lower coal seams, the subsidence of the monitoring point increased significantly at 17.5 and 15 m, respectively. The roof collapse of the lower coal seam was 2.5 m ahead of that of the upper coal seam.(5)
The hydraulic value of the support, roof fall height, and sloughing depth in the entire working face reached the maximum at the coal pillar, and the extreme points at the coal pillar were relatively concentrated. The hydraulic value of the working face was generally large, roof fall and sloughing occurred occasionally, and preventive measures must be improved.
---
*Source: 2898971-2020-02-14.xml* | 2898971-2020-02-14_2898971-2020-02-14.md | 41,220 | Study on Law of Overlying Strata Breakage and Migration in Downward Mining of Extremely Close Coal Seams by Physical Similarity Simulation | Xiaobin Li; Wenrui He; Zhuhe Xu | Advances in Civil Engineering
(2020) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2020/2898971 | 2898971-2020-02-14.xml | ---
## Abstract
Extremely close coal seam groups are widely distributed in China, and the main mining method is downward mining. In the downward mining process of extremely close coal seam groups, the violent movement of overlying strata will cause the redistribution of surrounding rock stress. It not only produces stress concentration on the pillar but also causes the roof of the lower coal seam to be broken and difficulty in maintaining the mining roadway. In this study, the physical similitude modeling method and field observations were used to study the breakage and migration law of overlying strata in the downward mining of extremely close coal seams. Results show that in the process of mining upper coal seam, the first weighting step of the main roof is 37.5 m and the periodic weighting step is 12.5 m. The occurrence of strata separation is beneficial to the prediction of roof weighting. When the working face advances to 25 m, the rock stratum approximating a parallelogram of height 5 m does not collapse, and the working face is relatively dangerous. When mining the lower coal seam, the overall pressure of the working face is large, but the periodic weighting of the working face is not obvious. The first collapse step of the immediate roof is 15 m. When mining the upper and lower coal seams, the subsidence of the monitoring point increases significantly at 17.5 and 15 m, respectively. The roof collapse of the lower coal seam occurs 2.5 m ahead of that of the upper coal seam. The hydraulic value of the support, roof fall height, and sloughing depth in the entire working face reach the maximum at the coal pillar, and the extreme points at the coal pillar are relatively concentrated. This research provides some guidance for the safe and efficient mining of extremely close coal seams in the future.
---
## Body
## 1. Introduction
China produces and consumes the most amount of coal in the world [1]. The proportion of coal in primary energy production and consumption is approximately 70%. According to the British Petroleum Statistical Review of World Energy 2018 program, China’s coal output reached 3.523 billion tons in 2017, accounting for 45.6% of the world’s total output [2]. Therefore, coal is important for China’s economic development [3]. Recently, with large-scale mining, coal seams with good geological conditions have been gradually exhausted [4]. Owing to the large proportion of extremely close coal seams in China, the mining of extremely close coal seams is becoming more common for improving the utilization of coal resources [5]. Extremely close coal seams are closely spaced and interact with each other during mining. With the decrease in spacing, the interaction between coal seams will gradually increase [6]. When the distance of coal seams is extremely close, the roof integrity of the lower coal seam will be damaged by the mining of the upper coal seam. The area above the roof is the caving zone formed by the collapsed immediate roof [7]. Moreover, the remaining pillars in the upper coal seam can easily cause stress concentration [8, 9]. Consequently, the roof structure and stress environment in the mining area of the lower coal seam changed, and many new mine pressure phenomena occurred during the mining of extremely close coal seams [10].Many engineering examples show that the violent movement of overlying strata will induce serious air leakages and water and gas accidents [11, 12]. Factors such as mining thickness, burial depth, and dip angle of coal seam are closely related to the law of overlying strata movement [13]. Because the process of strata movement is complex and no theoretical analysis method exists to satisfy engineering practices [14], physical similarity simulation is still the main method to study strata movement. This method overcomes the invisibility of mine pressure and overlying strata movement in field production, reflects the mechanical phenomenon visually, and can simulate the entire process in a short time. Based on physical similarity simulations, Huang et al. [15] studied the characteristics of overlying strata movement and strata behavior law in fully mechanized coal mining and backfilling longwall faces. Yuan et al. [16] proposed a new method for a similar material simulation experiment of steeply inclined upper protective layer mining and successfully applied it to the Nantong mining district. Niu et al. [17] constructed a similar physical model of coal rock to verify that a new method could be applied for the monitoring and early warning of coal and rock dynamic disasters. Zhang et al. [18] discussed the roof movement law of a fully mechanized mining face under a large dip angle through physical similarity simulations. Based on the engineering background of the Wuhushan coal mine, the law of overlying strata breakage and migration in the downward mining of extremely close coal seams was studied using the physical similitude modeling method. The current study can provide important guidance for the safe and efficient mining of extremely close coal seams in the future.Recently, experts and scholars have performed relevant research and exploration on the mining system and safety technology of extremely close coal seams. Based on a mechanical model and FLAC 3D numerical simulations, Wu et al. [19] studied the stress distribution under a coal pillar and optimized the roadway layout. Based on the in situ monitoring of overburden failure, Ning et al. [20] proposed a statistical formula for predicting the maximum height of overburden failure induced by extremely close coal seam mining. Zhang et al. [21] discussed the relationship between pillar size and roadway stability, incorporating a strain softening model for pillars and a double yield model for goaf material. By considering horizontal, vertical, and tangential stresses, Yan et al. [22] and Yuan et al. [23] proposed a new method for calculating the stress distribution of coal pillars. Based on experimental research and the UDEC software, Zhang et al. [24] analyzed the relationship between mining sequence under water body and overburden failure degree. Zhang et al. [25] incorporated geotechnical considerations for concurrent pillar recovery in extremely close coal seams, where mining sequence, panel layout, and pillar size were considered. Based on the observations of surface subsidence and three-dimensional simulations, Yu et al. [26] and Zhu et al. [27] studied the relationship between upper coal pillar and lower working face. Based on the floor failure mechanics model, Zhang et al. [28] proposed a new method to monitor floor failure depth and successfully applied it to the Caocun coal mine in China. Liu et al. [29] deduced a formula for the analysis of floor stress distribution and roadway position in extremely close coal seams. Aiming at the large deformation and destruction of roadway in extremely close coal seams, Li et al. [30] proposed an asymmetric support scheme, which has been successfully applied in other mines. Based on the finite element method, Ghabraie et al. [31] and Khanal et al. [32] developed a new method that can accurately simulate the collapse of overlying strata and surface subsidence during multiseam mining. Based on the law of gas occurrence and outburst characteristics, Wang et al. [33] and Konicek and Schreiber [34] studied the sequence of coal seam mining, key protective seam mining technology, and gas control measures.As described above, scholars primarily focused on the layout of mining roadways in the lower coal seam, gas control, mining sequence, and stress distribution of pillars and floor in the upper coal seam. However, studies regarding the breakage and migration law of overlying strata by physical similarity simulations are rare. Therefore, the law of strata breakage and migration must be studied to realize the safe and efficient mining of extremely close coal seams.
## 2. Engineering Background
### 2.1. Mining and Geological Condition
The Wuhushan coal mine, located in Wuhai city, Inner Mongolia autonomous region, China (Figure1), covers a mining area of 12.6 km2. Coals 9 and 10 are extremely close coal seams, with a 0.45–5.02 m layer of sandy mudstone in the middle. The inclination and strike length of the working face are 130 and 400 m, respectively. A fully mechanized mining method was adopted. The average thickness of coal 9 was 3.2 m. The rock strata above coal 9 were mudstone of average thickness 9.4 m and medium sandstone of average thickness 6.0 m, while the rock stratum below coal 9 was sandy mudstone of average thickness 2.0 m. The average thickness of coal 10 was 2.2 m. Its roof was also the floor of coal 9, and the rock stratum below coal 10 was siltstone of average thickness 5.4 m. Figure 2 shows the generalized stratigraphy column.Figure 1
Location of Wuhushan coal mine in Inner Mongolia autonomous region, China.Figure 2
Generalized stratigraphy column of the test site.
### 2.2. Experiments for Determining Rock Mechanical Properties
To understand the rock mechanical properties better, the coal and rock mass in the field were processed into a certain shape using the ZS-100 fully automatic drilling machine, SCM200 double-end grinder, HJD-150A concrete sawing machine, and SC200 automatic core-taking machine. Figure3 shows the coal and rock samples for use in experiments. Figure 4 shows the processing equipment. Uniaxial compression, splitting, and shear strength tests were performed on the samples to determine the mechanical parameters of coal and rock mass [35], as shown in Table 1.Figure 3
Coal and rock samples used in the experiments.Figure 4
Processing equipment: (a) ZS-100 fully automatic drilling machine; (b) SCM200 double-end grinder; (c) HJD-150A concrete sawing machine; (d) SC200 automatic core-taking machine.
(a)
(b)
(c)
(d)Table 1
Mechanical properties of coal-rock strata.
Number
Lithology
Density (kg/m³)
Shear modulus (GPa)
Bulk modulus (GPa)
Cohesion (MPa)
Friction angle (°)
Tensile strength (MPa)
1
Fine sandstone
2540
5.08
6.25
10.1
27
6.6
2
Siltstone
2640
5.82
6.09
7.9
28
7.1
3
Fine sandstone
2540
5.08
6.25
10.1
27
6.6
4
Sandy mudstone
2200
3.6
6.0
3.0
32
5.9
5
Siltstone
2640
5.82
6.09
7.9
28
7.1
6
Mudstone
2220
1.3
3.0
0.8
32
5.9
7
Medium sandstone
2540
5.91
6.81
10.7
31
6.5
8
Mudstone
2220
1.3
3.0
0.8
32
5.9
9
Coal 9
1400
0.76
1.6
2.65
25
1.8
10
Sandy mudstone
2200
3.6
6.0
3.0
32
5.9
11
Coal 10
1400
0.76
1.6
2.65
25
1.8
12
Siltstone
2640
5.82
6.09
7.9
28
7.1
## 2.1. Mining and Geological Condition
The Wuhushan coal mine, located in Wuhai city, Inner Mongolia autonomous region, China (Figure1), covers a mining area of 12.6 km2. Coals 9 and 10 are extremely close coal seams, with a 0.45–5.02 m layer of sandy mudstone in the middle. The inclination and strike length of the working face are 130 and 400 m, respectively. A fully mechanized mining method was adopted. The average thickness of coal 9 was 3.2 m. The rock strata above coal 9 were mudstone of average thickness 9.4 m and medium sandstone of average thickness 6.0 m, while the rock stratum below coal 9 was sandy mudstone of average thickness 2.0 m. The average thickness of coal 10 was 2.2 m. Its roof was also the floor of coal 9, and the rock stratum below coal 10 was siltstone of average thickness 5.4 m. Figure 2 shows the generalized stratigraphy column.Figure 1
Location of Wuhushan coal mine in Inner Mongolia autonomous region, China.Figure 2
Generalized stratigraphy column of the test site.
## 2.2. Experiments for Determining Rock Mechanical Properties
To understand the rock mechanical properties better, the coal and rock mass in the field were processed into a certain shape using the ZS-100 fully automatic drilling machine, SCM200 double-end grinder, HJD-150A concrete sawing machine, and SC200 automatic core-taking machine. Figure3 shows the coal and rock samples for use in experiments. Figure 4 shows the processing equipment. Uniaxial compression, splitting, and shear strength tests were performed on the samples to determine the mechanical parameters of coal and rock mass [35], as shown in Table 1.Figure 3
Coal and rock samples used in the experiments.Figure 4
Processing equipment: (a) ZS-100 fully automatic drilling machine; (b) SCM200 double-end grinder; (c) HJD-150A concrete sawing machine; (d) SC200 automatic core-taking machine.
(a)
(b)
(c)
(d)Table 1
Mechanical properties of coal-rock strata.
Number
Lithology
Density (kg/m³)
Shear modulus (GPa)
Bulk modulus (GPa)
Cohesion (MPa)
Friction angle (°)
Tensile strength (MPa)
1
Fine sandstone
2540
5.08
6.25
10.1
27
6.6
2
Siltstone
2640
5.82
6.09
7.9
28
7.1
3
Fine sandstone
2540
5.08
6.25
10.1
27
6.6
4
Sandy mudstone
2200
3.6
6.0
3.0
32
5.9
5
Siltstone
2640
5.82
6.09
7.9
28
7.1
6
Mudstone
2220
1.3
3.0
0.8
32
5.9
7
Medium sandstone
2540
5.91
6.81
10.7
31
6.5
8
Mudstone
2220
1.3
3.0
0.8
32
5.9
9
Coal 9
1400
0.76
1.6
2.65
25
1.8
10
Sandy mudstone
2200
3.6
6.0
3.0
32
5.9
11
Coal 10
1400
0.76
1.6
2.65
25
1.8
12
Siltstone
2640
5.82
6.09
7.9
28
7.1
## 3. Similar Material Simulation
### 3.1. Similarity Theory
A similar material simulation was performed based on the similarity theory. Geometric, time, and dynamic similarities must be considered between the model and prototype. Based on [18] and “dimensional analysis,” the dynamic similarity rate is presented as shown in equation (4). Meanwhile, Ren et al. [36] indicated that the dynamic similarity requires the force of the model and prototype at the corresponding point and time to be at a certain proportion to each other, and the main characteristics of force are reflected by compressive strength and bulk density in the experiment. Therefore, the compressive strength can be described as the dynamic similarity rate.The geometric similarity rate of the model is(1)CL=LmLp=150,where CL refers to the length similarity constant and Lm and Lp are the lengths of the similar material simulation model and prototype, respectively.The time similarity rate of the model is(2)CT=TmTp=CL=17,where CT is the time similarity constant and Tm and Tp are the time of the similar material simulation model and prototype, respectively.The density similarity rate of the model is(3)Cρ=ρmρp=11.6,where Cρ is the density similarity constant and ρm and ρp are the densities of the similar material simulation model and prototype, respectively.The dynamic similarity rate of the model is(4)Cσ=FmFp=mmdvm/dtmmddvd/dtd=σmσp=LmLpγmγp=LmLpρmρp=180,where Cσ is the strength similarity constant and σm, σp, γm, and γp are the compressive strengths and bulk densities of the similar material simulation model and prototype, respectively.According to the dynamic similarity rate formula, the compressive strength and bulk density of the strata in the model and prototype can be obtained (Table2).Table 2
Mechanics parameters of the similar rock material.
Prototype
Model
Number
Lithology
Bulk density (g/cm3)
Compressive strength (MPa)
Bulk density (g/cm3)
Compressive strength (MPa)
1
Fine sandstone
2.54
75.3
1.588
0.941
2
Siltstone
2.64
50.5
1.65
0.631
3
Fine sandstone
2.54
75.3
1.588
0.941
4
Sandy mudstone
2.2
30.2
1.375
0.377
5
Siltstone
2.64
44.2
1.65
0.553
6
Mudstone
2.22
32
1.388
0.400
7
Medium sandstone
2.54
85
1.588
1.063
8
Mudstone
2.22
30.1
1.388
0.377
9
Coal 9
1.4
9.5
0.875
0.119
10
Sandy mudstone
2.2
30.2
1.375
0.377
11
Coal 10
1.4
9.5
0.875
0.119
12
Siltstone
2.64
50.5
1.65
0.631
### 3.2. Overall Design of Physical Similarity Model
Based on the actual geological data of the fully mechanized mining face of the Wuhushan coal mine, fine sand, lime, and gypsum were selected as similar materials. The size of the test bench was 1800 mm (length) × 160 mm (width) × 1300 mm (height), and the plane stress model was adopted. The model building process is presented as follows [37]: (1) based on the calculation in Table 3, sand, lime, and gypsum were weighed and combined in a mixer. (2) The mixed material was paved evenly and compacted to maintain the required bulk density. Subsequently, mica powder was sprinkled on the strata to clarify the model bedding. (3) The other strata of the model followed the preceding steps until the required height was reached. (4) The weight of the overlying strata above the model was determined by adding the counterweight. (5) The model was dried naturally for five days.Table 3
Similar simulation strata distribution and material mixture ratio.
Number
Lithology
Thickness (mm)
Proportioning
Material consumption (kg)
Sand
Lime
Gypsum
Water
1
Fine sandstone
136.0
9 : 6 : 4
56.402
3.760
2.507
2.507
2
Siltstone
88.0
8 : 7 : 3
36.045
3.154
1.352
1.622
3
Fine sandstone
30.0
9 : 6 : 4
12.442
0.829
0.553
0.553
4
Sandy mudstone
106.0
10 : 7 : 3
44.404
3.108
1.332
1.954
5
Siltstone
152.0
9 : 8 : 2
63.037
5.603
1.401
2.802
6
Mudstone
84.0
8 : 8 : 2
34.406
3.441
0.860
1.548
7
Medium sandstone
120.0
8 : 6 : 4
49.152
3.686
2.458
2.212
8
Mudstone
188.0
10 : 7 : 3
78.755
5.513
2.363
3.465
9
Coal 9
64.0
10 : 9 : 1
26.810
2.413
0.268
1.180
10
Sandy mudstone
40.0
10 : 7 : 3
16.756
1.173
0.503
0.737
11
Coal 10
44.0
10 : 9 : 1
16.756
1.508
0.168
0.737
12
Siltstone
100.0
7 : 5 : 5
16.128
1.152
1.152
0.737Because the thickness and strength of the floor of coal 10 will not significantly affect the test, they can be simplified during building. The average height was 200 m from the actual working face to the surface. The thickness of the simulated overlying strata was 45.2 m, and the remaining height of 154.8 m was generated by the simulated pressure. The total height of this test was 1148 mm. The total excavation length was 1000 mm, and the length of each excavation was 50 mm. During building, the actual size of the strata should be adhered strictly. The specific amount of similar material is shown in Table3.
### 3.3. Layout of Monitoring Points
To acquire the displacement variation of the overlying strata, displacement monitoring points were evenly arranged. An electronic theodolite with high precision was used to measure strata movement during mining. As shown in Figure5, the monitoring points were evenly arranged above the roof of coal 10. Six detection lines were arranged in the model, namely, 2, 12, 22, 32, 42, and 52 cm from Coal 9. A total of 11 monitoring points were set on each line. A 15 cm × 10 cm grid design was adopted. To acquire data accurately during mining, a data collector was used to record the pressure data automatically; subsequently, the data are transmitted to a computer for analysis, as shown in Figure 6.Figure 5
Similar simulation model and layout of monitoring points.Figure 6
Data acquisition device.
## 3.1. Similarity Theory
A similar material simulation was performed based on the similarity theory. Geometric, time, and dynamic similarities must be considered between the model and prototype. Based on [18] and “dimensional analysis,” the dynamic similarity rate is presented as shown in equation (4). Meanwhile, Ren et al. [36] indicated that the dynamic similarity requires the force of the model and prototype at the corresponding point and time to be at a certain proportion to each other, and the main characteristics of force are reflected by compressive strength and bulk density in the experiment. Therefore, the compressive strength can be described as the dynamic similarity rate.The geometric similarity rate of the model is(1)CL=LmLp=150,where CL refers to the length similarity constant and Lm and Lp are the lengths of the similar material simulation model and prototype, respectively.The time similarity rate of the model is(2)CT=TmTp=CL=17,where CT is the time similarity constant and Tm and Tp are the time of the similar material simulation model and prototype, respectively.The density similarity rate of the model is(3)Cρ=ρmρp=11.6,where Cρ is the density similarity constant and ρm and ρp are the densities of the similar material simulation model and prototype, respectively.The dynamic similarity rate of the model is(4)Cσ=FmFp=mmdvm/dtmmddvd/dtd=σmσp=LmLpγmγp=LmLpρmρp=180,where Cσ is the strength similarity constant and σm, σp, γm, and γp are the compressive strengths and bulk densities of the similar material simulation model and prototype, respectively.According to the dynamic similarity rate formula, the compressive strength and bulk density of the strata in the model and prototype can be obtained (Table2).Table 2
Mechanics parameters of the similar rock material.
Prototype
Model
Number
Lithology
Bulk density (g/cm3)
Compressive strength (MPa)
Bulk density (g/cm3)
Compressive strength (MPa)
1
Fine sandstone
2.54
75.3
1.588
0.941
2
Siltstone
2.64
50.5
1.65
0.631
3
Fine sandstone
2.54
75.3
1.588
0.941
4
Sandy mudstone
2.2
30.2
1.375
0.377
5
Siltstone
2.64
44.2
1.65
0.553
6
Mudstone
2.22
32
1.388
0.400
7
Medium sandstone
2.54
85
1.588
1.063
8
Mudstone
2.22
30.1
1.388
0.377
9
Coal 9
1.4
9.5
0.875
0.119
10
Sandy mudstone
2.2
30.2
1.375
0.377
11
Coal 10
1.4
9.5
0.875
0.119
12
Siltstone
2.64
50.5
1.65
0.631
## 3.2. Overall Design of Physical Similarity Model
Based on the actual geological data of the fully mechanized mining face of the Wuhushan coal mine, fine sand, lime, and gypsum were selected as similar materials. The size of the test bench was 1800 mm (length) × 160 mm (width) × 1300 mm (height), and the plane stress model was adopted. The model building process is presented as follows [37]: (1) based on the calculation in Table 3, sand, lime, and gypsum were weighed and combined in a mixer. (2) The mixed material was paved evenly and compacted to maintain the required bulk density. Subsequently, mica powder was sprinkled on the strata to clarify the model bedding. (3) The other strata of the model followed the preceding steps until the required height was reached. (4) The weight of the overlying strata above the model was determined by adding the counterweight. (5) The model was dried naturally for five days.Table 3
Similar simulation strata distribution and material mixture ratio.
Number
Lithology
Thickness (mm)
Proportioning
Material consumption (kg)
Sand
Lime
Gypsum
Water
1
Fine sandstone
136.0
9 : 6 : 4
56.402
3.760
2.507
2.507
2
Siltstone
88.0
8 : 7 : 3
36.045
3.154
1.352
1.622
3
Fine sandstone
30.0
9 : 6 : 4
12.442
0.829
0.553
0.553
4
Sandy mudstone
106.0
10 : 7 : 3
44.404
3.108
1.332
1.954
5
Siltstone
152.0
9 : 8 : 2
63.037
5.603
1.401
2.802
6
Mudstone
84.0
8 : 8 : 2
34.406
3.441
0.860
1.548
7
Medium sandstone
120.0
8 : 6 : 4
49.152
3.686
2.458
2.212
8
Mudstone
188.0
10 : 7 : 3
78.755
5.513
2.363
3.465
9
Coal 9
64.0
10 : 9 : 1
26.810
2.413
0.268
1.180
10
Sandy mudstone
40.0
10 : 7 : 3
16.756
1.173
0.503
0.737
11
Coal 10
44.0
10 : 9 : 1
16.756
1.508
0.168
0.737
12
Siltstone
100.0
7 : 5 : 5
16.128
1.152
1.152
0.737Because the thickness and strength of the floor of coal 10 will not significantly affect the test, they can be simplified during building. The average height was 200 m from the actual working face to the surface. The thickness of the simulated overlying strata was 45.2 m, and the remaining height of 154.8 m was generated by the simulated pressure. The total height of this test was 1148 mm. The total excavation length was 1000 mm, and the length of each excavation was 50 mm. During building, the actual size of the strata should be adhered strictly. The specific amount of similar material is shown in Table3.
## 3.3. Layout of Monitoring Points
To acquire the displacement variation of the overlying strata, displacement monitoring points were evenly arranged. An electronic theodolite with high precision was used to measure strata movement during mining. As shown in Figure5, the monitoring points were evenly arranged above the roof of coal 10. Six detection lines were arranged in the model, namely, 2, 12, 22, 32, 42, and 52 cm from Coal 9. A total of 11 monitoring points were set on each line. A 15 cm × 10 cm grid design was adopted. To acquire data accurately during mining, a data collector was used to record the pressure data automatically; subsequently, the data are transmitted to a computer for analysis, as shown in Figure 6.Figure 5
Similar simulation model and layout of monitoring points.Figure 6
Data acquisition device.
## 4. Mining Result Analysis of Upper Coal Seam
### 4.1. Mine Pressure Appearance Law
The open-off cut of the working face is 7.5 m. When the working face advances to 17.5 m, the first collapse of the immediate roof occurs. The collapse height is 2.5 m. As shown in Figure7, when the working face advances to 25 m, the mining-induced fracture will not extend to the main roof. The collapsed strata form a two-part masonry beam articulated structure. The collapse height is 5 m, which is approximately 1.5 times the mining height. The upper minimum collapse range is 10 m. Because of its self-stabilization ability, the strata approximating a parallelogram did not collapse. However, when the working face advances to 27.5 m, the first collapse of the main roof occurs. The working face encounters the first weighting of the main roof. As shown in Figure 8, the overlying strata begin to separate when the working face advances to 32.5 m. The first periodic weighting of the main roof occurs when the working face advances to 37.5 m (Figure 9). The second periodic weighting of the main roof occurs when the working face advances to 50 m (Figure 10). The average periodic weighting step is 12.5 m.Figure 7
25 m advancement.Figure 8
32.5 m advancement.Figure 9
37.5 m advancement.Figure 10
50 m advancement.From the discussion above, it is clear that with the advance of the working face, the first collapse of the immediate roof and the first and periodic weighting of the main roof will occur. Finally, the overlying strata will collapse in a large area. When the periodic weighting of the main roof occurs, the collapsed roof will exhibit a specific regularity. The collapse length of the overlying strata is the same, which is approximately equal to the periodic weighting step. From the working face up, the collapsed strata become more orderly and a stable articulated structure can be formed easily. This is because the strength of the first collapsed strata is low, and with the advance of the working face, the collapsed strata are gradually crushed by the strata above.
### 4.2. Analysis of Roof Subsidence
As shown in Figure11, the subsidence of the overlying strata shows a certain regularity. The maximum and uniform subsidence is line 1, which is 2 cm from coal 9. The variation range is between 55 and 64 mm, which is close to coal seam thickness. The maximum subsidence of lines 2, 3, 4, 5, and 6 is 48, 45, 42, 36, and 26 mm, respectively. This shows that the subsidence of the overlying strata decreases with the increase in distance from the coal seam. This is because with the increase in distance from the coal seam, the probability of interaction increases between the collapsed overlying strata. In addition, some stable structures may be formed between the large strata. Consequently, the space between the strata and the dilatancy coefficient increase. Ultimately, the subsidence of the overlying strata is reduced. When the advancement distance of the working face is 17.5 m, the subsidence of the monitoring point increases significantly. This phenomenon is caused by a sudden roof caving in the gob, which is consistent with the physical similarity simulation results.Figure 11
Subsidence of monitoring points.
## 4.1. Mine Pressure Appearance Law
The open-off cut of the working face is 7.5 m. When the working face advances to 17.5 m, the first collapse of the immediate roof occurs. The collapse height is 2.5 m. As shown in Figure7, when the working face advances to 25 m, the mining-induced fracture will not extend to the main roof. The collapsed strata form a two-part masonry beam articulated structure. The collapse height is 5 m, which is approximately 1.5 times the mining height. The upper minimum collapse range is 10 m. Because of its self-stabilization ability, the strata approximating a parallelogram did not collapse. However, when the working face advances to 27.5 m, the first collapse of the main roof occurs. The working face encounters the first weighting of the main roof. As shown in Figure 8, the overlying strata begin to separate when the working face advances to 32.5 m. The first periodic weighting of the main roof occurs when the working face advances to 37.5 m (Figure 9). The second periodic weighting of the main roof occurs when the working face advances to 50 m (Figure 10). The average periodic weighting step is 12.5 m.Figure 7
25 m advancement.Figure 8
32.5 m advancement.Figure 9
37.5 m advancement.Figure 10
50 m advancement.From the discussion above, it is clear that with the advance of the working face, the first collapse of the immediate roof and the first and periodic weighting of the main roof will occur. Finally, the overlying strata will collapse in a large area. When the periodic weighting of the main roof occurs, the collapsed roof will exhibit a specific regularity. The collapse length of the overlying strata is the same, which is approximately equal to the periodic weighting step. From the working face up, the collapsed strata become more orderly and a stable articulated structure can be formed easily. This is because the strength of the first collapsed strata is low, and with the advance of the working face, the collapsed strata are gradually crushed by the strata above.
## 4.2. Analysis of Roof Subsidence
As shown in Figure11, the subsidence of the overlying strata shows a certain regularity. The maximum and uniform subsidence is line 1, which is 2 cm from coal 9. The variation range is between 55 and 64 mm, which is close to coal seam thickness. The maximum subsidence of lines 2, 3, 4, 5, and 6 is 48, 45, 42, 36, and 26 mm, respectively. This shows that the subsidence of the overlying strata decreases with the increase in distance from the coal seam. This is because with the increase in distance from the coal seam, the probability of interaction increases between the collapsed overlying strata. In addition, some stable structures may be formed between the large strata. Consequently, the space between the strata and the dilatancy coefficient increase. Ultimately, the subsidence of the overlying strata is reduced. When the advancement distance of the working face is 17.5 m, the subsidence of the monitoring point increases significantly. This phenomenon is caused by a sudden roof caving in the gob, which is consistent with the physical similarity simulation results.Figure 11
Subsidence of monitoring points.
## 5. Mining Result Analysis of Lower Coal Seam
### 5.1. Mine Pressure Appearance Law
When the lower coal seam was mined, the overlying strata and the roof of the upper coal seam collapsed and recemented. Owing to the mining activity of the upper coal seam, the roof of coal 10 was damaged and generated some microfractures; additionally, the roof strength was low. Therefore, the first collapse of the immediate roof occurred at 15 m during mining. The roof collapse of the lower coal seam was 2.5 m ahead of that of the upper coal seam. In the subsequent mining process, no obvious periodic weighting of the main roof occurred, the roof falls with mining, and no obvious structure was formed, as shown in Figure12.Figure 12
Roof collapse patterns at different distances.
### 5.2. Analysis of Roof Subsidence
As shown in Figures11 and 13, the subsidence of the overlying strata has little effect on the outside of the mining area. However, the subsidence of the overlying strata above the mining area changed significantly. Most of the subsidence was concentrated between 80 and 104 mm. The subsidence of lines 1, 2, and 3 was approximately equal to the thickness of Coal 10. Owing to effect of mining, the original structure of the overlying strata was destroyed and the subsidence of the upward detection lines increased. Ultimately, the collapsed strata’s dilatancy coefficient would be reduced, and the rock mass further compacted. The increase in the sinking point of lines 4, 5, and 6 exceeded the coal seam thickness after mining Coal 10, and the maximum increase could reach to 227.9%. This was caused by the decrease in the coefficient of fragmentation and expansion. Meanwhile, it could be attributed to Coal 10 being directly excavated before the strata movement had stopped completely. As shown in Figure 13, when the advancement distance of the working face is 15 m, the subsidence of the monitoring point increases sharply and the roof collapses in a large area. The subsidence curve is approximately symmetric, with an unstable area on both sides and no obvious periodic weighting area in the middle.Figure 13
Subsidence of monitoring points.
## 5.1. Mine Pressure Appearance Law
When the lower coal seam was mined, the overlying strata and the roof of the upper coal seam collapsed and recemented. Owing to the mining activity of the upper coal seam, the roof of coal 10 was damaged and generated some microfractures; additionally, the roof strength was low. Therefore, the first collapse of the immediate roof occurred at 15 m during mining. The roof collapse of the lower coal seam was 2.5 m ahead of that of the upper coal seam. In the subsequent mining process, no obvious periodic weighting of the main roof occurred, the roof falls with mining, and no obvious structure was formed, as shown in Figure12.Figure 12
Roof collapse patterns at different distances.
## 5.2. Analysis of Roof Subsidence
As shown in Figures11 and 13, the subsidence of the overlying strata has little effect on the outside of the mining area. However, the subsidence of the overlying strata above the mining area changed significantly. Most of the subsidence was concentrated between 80 and 104 mm. The subsidence of lines 1, 2, and 3 was approximately equal to the thickness of Coal 10. Owing to effect of mining, the original structure of the overlying strata was destroyed and the subsidence of the upward detection lines increased. Ultimately, the collapsed strata’s dilatancy coefficient would be reduced, and the rock mass further compacted. The increase in the sinking point of lines 4, 5, and 6 exceeded the coal seam thickness after mining Coal 10, and the maximum increase could reach to 227.9%. This was caused by the decrease in the coefficient of fragmentation and expansion. Meanwhile, it could be attributed to Coal 10 being directly excavated before the strata movement had stopped completely. As shown in Figure 13, when the advancement distance of the working face is 15 m, the subsidence of the monitoring point increases sharply and the roof collapses in a large area. The subsidence curve is approximately symmetric, with an unstable area on both sides and no obvious periodic weighting area in the middle.Figure 13
Subsidence of monitoring points.
## 6. Field Observation
### 6.1. Layout of Stations
To understand the law of mine pressure in extremely close coal seams, the mine pressure in 1001 working face of the Wuhushan coal mine was observed. Eight stations were arranged in the working face. The stations were densely distributed under the coal pillar and evenly distributed in other places, as shown in Figure14. The stations were located at hydraulic support nos. 6, 20, 24, 28, 31, 56, 81, and 106.Figure 14
Layout of stations.
### 6.2. Analysis of Observation Results
The collected hydraulic information of all supports was divided into four regions: the upper, middle, coal pillar, and lower regions. The pressure values of the hydraulic support and the change characteristics of the roof fall and sloughing in each region were considered, as shown in Figure15.Figure 15
Hydraulic information of support and variation characteristics of roof fall and sloughing. (a) Upper region; (b) middle region; (c) coal pillar region; (d) lower region.
(a)
(b)
(c)
(d)From the data, it can be concluded that the first collapse steps of the immediate roof in the upper, middle, coal pillar, and lower regions of the working face are 16, 16, 14.5, and 14.3 m, respectively. Comprehensive analysis shows that the average first collapse step of the immediate roof in 1001 working face is 15 m and no obvious periodic weighting is shown, which is consistent with the physical similarity simulation results. The hydraulic value of the support, roof fall height, and sloughing depth in the entire working face reached the maximum at the coal pillar, and the extreme points at the coal pillar were relatively concentrated. Furthermore, maximum points appeared at the upper and lower regions, but the entire working face was not as large as the coal pillar. The hydraulic value of the working face was generally large, roof fall and sloughing occurred occasionally, and preventive measures must be improved.
## 6.1. Layout of Stations
To understand the law of mine pressure in extremely close coal seams, the mine pressure in 1001 working face of the Wuhushan coal mine was observed. Eight stations were arranged in the working face. The stations were densely distributed under the coal pillar and evenly distributed in other places, as shown in Figure14. The stations were located at hydraulic support nos. 6, 20, 24, 28, 31, 56, 81, and 106.Figure 14
Layout of stations.
## 6.2. Analysis of Observation Results
The collected hydraulic information of all supports was divided into four regions: the upper, middle, coal pillar, and lower regions. The pressure values of the hydraulic support and the change characteristics of the roof fall and sloughing in each region were considered, as shown in Figure15.Figure 15
Hydraulic information of support and variation characteristics of roof fall and sloughing. (a) Upper region; (b) middle region; (c) coal pillar region; (d) lower region.
(a)
(b)
(c)
(d)From the data, it can be concluded that the first collapse steps of the immediate roof in the upper, middle, coal pillar, and lower regions of the working face are 16, 16, 14.5, and 14.3 m, respectively. Comprehensive analysis shows that the average first collapse step of the immediate roof in 1001 working face is 15 m and no obvious periodic weighting is shown, which is consistent with the physical similarity simulation results. The hydraulic value of the support, roof fall height, and sloughing depth in the entire working face reached the maximum at the coal pillar, and the extreme points at the coal pillar were relatively concentrated. Furthermore, maximum points appeared at the upper and lower regions, but the entire working face was not as large as the coal pillar. The hydraulic value of the working face was generally large, roof fall and sloughing occurred occasionally, and preventive measures must be improved.
## 7. Conclusions
In this study, the physical similitude modeling method was used to study the breakage and migration law of overlying strata in the downward mining of extremely close coal seams, which was verified by field observations in the working face. The conclusions are as follows:(1)
In the process of mining upper coal seam, the first weighting step of the main roof was 37.5 m, and the periodic weighting step was 12.5 m. The occurrence of strata separation was beneficial to the prediction of roof weighting.(2)
When the working face advanced to 25 m, the rock stratum approximating a parallelogram of height 5 m did not collapse, and the working face was relatively dangerous.(3)
When mining the lower coal seam, the overall pressure of the working face was large, but the periodic weighting of the working face was not obvious. The first collapse step of the immediate roof was 15 m.(4)
When mining the upper and lower coal seams, the subsidence of the monitoring point increased significantly at 17.5 and 15 m, respectively. The roof collapse of the lower coal seam was 2.5 m ahead of that of the upper coal seam.(5)
The hydraulic value of the support, roof fall height, and sloughing depth in the entire working face reached the maximum at the coal pillar, and the extreme points at the coal pillar were relatively concentrated. The hydraulic value of the working face was generally large, roof fall and sloughing occurred occasionally, and preventive measures must be improved.
---
*Source: 2898971-2020-02-14.xml* | 2020 |
# Quercetin Reduces Oxidative Stress and Apoptosis by Inhibiting HMGB1 and Its Translocation, Thereby Alleviating Liver Injury in ACLF Rats
**Authors:** Peng Fang; Bo Dou; Jiajun Liang; Weixin Hou; Chongyang Ma; Qiuyun Zhang
**Journal:** Evidence-Based Complementary and Alternative Medicine
(2021)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2021/2898995
---
## Abstract
Background. Acute on chronic liver failure (ACLF) is a syndrome of acute liver failure that occurs on the basis of chronic liver disease, which is characterized by a rapid deterioration in a short period and high mortality. High mobility group box 1 (HMGB1) may be involved in the pathological process of ACLF; its specific role remains to be further elucidated. Our previous studies have shown that quercetin (Que) exerts anti-oxidant and anti-apoptotic effects by inhibiting HMGB1 in vitro. The present study aimed to investigate the effect of Que on liver injury in ACLF rats. Methods. The contents of ALT, AST, TBiL, and PT time of rats in each group were observed. HE staining was used to detect liver pathology. The levels of oxidative stress indicators such as MDA, GSH, and 4-HNE in the rat liver were detected. TUNEL assay was used to detect apoptosis in rat hepatocytes. Immunofluorescence and western blot analysis were performed to explore the protective effect of Que on ACLF rats and the underlying mechanism. Results. The results showed that Que could reduce the increase of serum biochemical indices, improve liver pathology, and reduce liver damage in ACLF rats. Further results confirmed that Que reduced the occurrence of oxidative stress and apoptosis of hepatocytes, and these reactions may aggravate the progress of ACLF. Meanwhile, the results of immunofluorescence and western blotting also confirmed that the expression of HMGB1 and extranuclear translocation in ACLF rat hepatocytes were significantly increased, which was alleviated by the treatment of Que. In addition, when cotreated with glycyrrhizin (Gly), an inhibitor of HMGB1, the inhibition of Que on HMGB1 and its translocation, apoptosis and oxidative stress, and the related proteins of HMGB1-mediated cellular pathway have been significantly enhanced. Conclusion. Thus, Que alleviates liver injury in ACLF rats, and its mechanism may be related to oxidative stress and apoptosis caused by HMGB1 and its translocation.
---
## Body
## 1. Introduction
Acute on chronic liver failure (ACLF) refers to a syndrome of liver failure caused by various factors on the basis of chronic liver disease, which is manifested by acute jaundice deepening and coagulopathy [1]. It can be complicated by various symptoms such as hepatic encephalopathy, ascites, infection, and extrahepatic organ failure [2]. ACLF is accompanied by rapid deterioration and high mortality in the short term. In Western countries, ACLF is mainly caused by alcoholic liver injury, improper drug use, and infection. In Asia, the main cause is hepatitis virus, and about 80% of patients are caused by acute exacerbation of HBV infection, followed by damage from drugs and hepatotoxic substances [3]. A study on hospitalized patients with liver cirrhosis in the United States showed that the incidence of ACLF among hospitalized patients with cirrhosis was 26.39%, and the 90-day mortality rate was 40.02% [4, 5]. Another 10-year cohort study conducted in China showed that the 60-day mortality rate of ACLF patients who did not undergo liver transplantation was 37.4% [6]. Even though the East and West have different understanding and definitions of ACLF, the mortality rate of ACLF is extremely high in both parties [7].Although the pathogenesis of ACLF is poorly understood, however, the release of damage-associated molecular patterns (DAMPs) caused by immune system imbalance and inflammatory response has been confirmed to aggravate the pathological process of ACLF [8]. High mobility group box 1 (HMGB1), an evolutionarily conserved nuclear DNA binding protein, is widely present in eukaryotic cells and has important biological activities both inside and outside the cell [9, 10]. Once released outside the cell membrane, it can also act as DAMP. Many convincing evidence indicate that the pathological process of ACLF is affected by HMGB1 [11, 12].Quercetin (3,3′,4′,5,7-pentahydroxyflavone, Que), a typical flavonol-type flavonoid, is also considered as a potential inhibitor of HMGB1 [13]. Several research suggest that Que has a wide range of biological effects such as anti-oxidant, anti-inflammatory, and anti-apoptosis [14, 15]. Supplementing the diet with Que has beneficial effects on many liver diseases [16]. Que improves liver cell damage by inhibiting inflammation, oxidative stress, and cell apoptosis, thereby reducing liver damage caused by various hepatoxins in vivo [17–19]. As an effective phytochemical component for the treatment of various liver diseases, it has been studied in hepatitis, acute liver failure, and fibrosis [13, 20, 21]. Our previous studies have shown that Que exerts anti-oxidant and anti-apoptotic effects via inhibiting HMGB1, thereby protecting the liver cell from damage caused by D-GaLN in vitro [22]. In the present ACLF rat model, the application of D-GaLN is the main stimulating factor for acute liver injury. However, whether Que can reduce liver injury in ACLF rats has not yet been adequately studied. In the present study, we investigated the protective effect of Que on liver injury in ACLF rats, following the research method of the hepatoprotective effect of flavonoids [23]. In addition, an exact inhibitor of HMGB1 was combined to further verify the hypothesis that HMGB1 plays an important role in the disease process of ACLF and the beneficial therapeutic effect of its inhibition.
## 2. Materials and Methods
### 2.1. Chemicals and Regents
Que was obtained from Sigma-Aldrich (St. Louis, USA; cat: Q4951); its purity is ≥95%. Human serum albumin (HSA; cat: A9731), D-galactosamine (D-GaLN; cat:G1639), and lipopolysaccharides (LPS; cat:L3012) were also obtained from Sigma-Aldrich (St. Louis, USA). Anti-Bcl-2 (cat: ab19645), anti-Bax (cat:ab32503), anti-HMGB1 (cat:ab79823), anti-iNOS (cat:ab49999), anti-COX-2 (cat:ab15191), and anti-4HNE (cat:ab48506) were obtained from Abcam (Shanghai, China). Anti-TLR-4 (cat: SC-293072) was obtained from Santa Cruz Biotechnology (Santa Cruz, USA). Anti-caspase-9 (cat: #9508), anti-caspase-3 (cat: #9662), anti-NF-κB p65 (cat:#8242) were obtained from Cell Signaling Technology (Boston, USA).
### 2.2. Experimental Animals
Ninety male Wistar rats weighing 200 to 240 g were purchased from Vital River Laboratory Animal Technology Co. Ltd. (Beijing, China). The animals were housed in a specific pathogen-free environment under constant temperature (25 ± 3°C) and humidity (60 ± 10%), with a 12 h light/dark cycle. All animals were acclimated to the environment for 5 days before the experiments. All of the procedures were performed according to the Institutional Guidelines for the Care and Use of Laboratory Animals and were authorized by the Animal Ethics Committee of Capital Medical University (NO.AEEI-2019-067).
### 2.3. Animal Treatment
The ACLF rat model was established as we described previously [24]. Briefly, acute liver failure was induced on the basis of chronic immune liver fibrosis. As shown in (Figure 1), except for the normal control group (n = 10), the remaining 80 rats were injected with HSA to induce immune liver injury. After 6 weeks, 50 survived rats with liver fibrosis confirmed by Masson’s trichrome staining [25] were selected, and then the rats were injected intraperitoneally with 400 mg/kg D-GaLN and 100 μg/kg LPS to establish the ACLF model. Then the rats were randomly divided into 5 groups: (1) ACLF group, rats were intragastric administration of an equal volume of normal saline solution and intraperitoneal injection of an equal amount of vehicle; (2) low-dose Que treatment group (Que-25), rats were intragastric administration of 25 mg/kg Que for 7 consecutive days and intraperitoneal injection of an equal amount of vehicle; (3) middle dose of Que treatment group (Que-50), treatment was the same as the Que-25 group, while the dose of Que was 50 mg/kg; (4) high dose of Que treatment group (Que-100), treatment was the same as the Que-25 group, while the dose of Que was 100 mg/kg; and (5) HMGB1 inhibitor intervention group (Que-100 + Gly), rats were intragastric administration of 100 mg/kg Que and intraperitoneal injection of 50 mg/kg glycyrrhizin (Gly) for 7 consecutive days. Gly is a direct inhibitor of HMGB1, which can bind to HMGB1 directly, interacting with two shallow concave surfaces formed by the two arms of both HMG boxes [26, 27]. At the end of the experiment, there were 10 survivors in the normal control group, 5 in the ACLF group, 6 in Que-25 group, 6 in the Que-50 group, 7 in the Que-100 group, and 7 in the Que-100 + Gly group. Before tissue collection, rats were deeply anesthetized by intraperitoneal injection of 1% pentobarbital sodium (40 mg/kg). After the anesthesia was stable, blood was collected from the abdominal aorta, and the serum collected by centrifugation was stored at −80°C. The liver tissue was quickly collected and weighed, frozen in liquid nitrogen, and stored at −80°C. Then the rats were euthanized by cervical dislocation.Figure 1
Establishment of ACLF rat model and experimental intervention. The rats were injected with HSA to induce immune hepatic fibrosis. At first stage, rats were sensitized by subcutaneous injection of HSA solution (0.5 ml, HSA 4 mg) for a total of 4 injections (days 0, 14, 24, and 34). Subsequently, tail vein injection was performed twice a week for 6 weeks (0.5 ml, gradually increased the HSA dose, 2.5 mg⟶3 mg⟶3.5 mg⟶4 mg⟶4.5 mg, and then maintained at 4.5 mg), and the normal group was injected with the same amount of normal saline. And then, intraperitoneal injection of 400 mg/kg D-GaLN and 100μg/kg LPS caused acute liver injury to establish the ACLF model. Finally, the rats were randomly divided into 5 intervention groups: receiving Que and/or glycyrrhizin, or vehicle treatment for 7 consecutive days. The normal control group underwent the same procedures without therapeutic intervention.
### 2.4. Determination of Serum Biochemical Indices
Blood samples were collected in tubes and centrifuged for 15 min at 3,000 rpm (Sigma-Aldrich, USA) to collect serum. The levels of alanine aminotransferase, aspartate aminotransferase (AST), and total bilirubin (TBiL) in serum were detected with an automatic analyzer (Hitachi, Inc., Japan) using commercial kits following the manufacturer’s instructions.
### 2.5. Determination of Prothrombin Times
Blood samples were collected in anti-coagulant tubes containing sodium citrate solution and centrifuged for 15 min at 3,000 rpm (Sigma-Aldrich, USA) to collect plasma. Prothrombin times (PTs) were measured using a kit (Nanjing, China) according to the manufacturer’s instructions.
### 2.6. Liver Histological Observation
Left lobes of liver tissues were isolated and fixed immediately with 10% neutral buffered formalin. The paraffin-embedded liver tissue samples were cut into 5μm thick sections for hematoxylin and eosin (H&E) staining, and then the sections were observed with a pathological section panoramic scanner (Leica Aperio AT2).
### 2.7. Assessment of Oxidative Stress
The content of hepatic malondialdehyde (MDA) was determined by thiobarbituric acid (TBA) reagent test using a commercial kit (Beyotime, China; cat: S0131). The liver homogenate was mixed with TBA buffer, incubated at 95°C for 1 hour, and then incubated on ice to stop the reaction. The mixture was centrifuged (4,000 rpm; 10 min), and the absorbance was measured by a microplate reader at a wavelength of 532 nm. The results were presented as nmol/mg protein.The level of anti-oxidant enzyme-reduced glutathione (GSH) content was determined by the 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) reactant test using a commercial kit (Beyotime, China; cat: S0053). Briefly, after mixing liver homogenate with DTNB stock solution and reacted, the absorbance was measured at a wavelength of 412 nm by a microplate reader. The GSH content in the sample was calculated according to the standard curve and presented as nmol/mg protein.
### 2.8. Immunofluorescence Analysis
Briefly, after dewaxing and antigen retrieval, the paraffin section was blocked by incubating with bovine serum albumin (BSA). Then the sections were individually incubated with anti-4-hydroxynonenal (4-HNE), anti-TLR-4, and anti-HMGB1 at 4°C overnight. After washing with PBS, the sections were incubated with FITC or TIRTC-labeled secondary antibody for 2 h at 37°C in the dark. Then the sections were washed 3 times with PBS for 5 min each time. Then, the tables were sealed with antifluorescence attenuation sealing solution (containing DAPI). Fluorescence images were collected by using a confocal microscope (Leica TCS SP8), and the results were analyzed using Image J software version 1.80.
### 2.9. Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling (TUNEL) Assays
The apoptotic response of hepatocytes was detected with paraffin-embedded sections using a TUNEL assay and Fluorescein In Situ Cell Death Assay Kit (KeyGEN BioTECH, China; cat: KGA7072) according to the manufacturer’s instructions. The positive cells were counted in 10 random fields at 400X magnification, and 3 sections of each sample were analyzed.
### 2.10. Western Blot Analysis
Liver proteins were homogenized and then collected by using RIPA lysis buffer. Cytoplasmic and nuclear proteins were isolated using nuclear and cytoplasmic protein extraction kits (Beyotime, China; cat: P0028), according to the manufacturer’s instructions. The BCA protein assay reagent kit was used to determine the concentration of total liver protein and the extracted nuclear protein and cytoplasmic protein. An equal amount of protein (30μg) was separated by 8–12% SDS-PAGE and transferred into PVDF membranes. Next, membranes were incubated with Tris-buffered saline, containing 5% non-fat dry milk for blocking purposes at room temperature for 1 hour. Then, membranes were incubated overnight at 4°C with primary antibodies directed against HMGB1, TLR-4, caspase-3, caspase-9, Bax, Bcl-2, NF- kB p65, iNOS, and COX-2. After washing with TBST, the membrane was incubated with a secondary antibody for 1 h at room temperature. Finally, the reaction was detected with an enhanced chemiluminescent reagent (NCM Biotech, China; cat: P10100). An ImageQuantLAS4000 chemiluminescence imaging system was used to visualize the target proteins (GE Co., USA), and densitometry was performed using the Image J software version 1.80.
### 2.11. Statistical Analysis
All data in the present study were analyzed using Prism 8.0 and expressed as the mean ± standard deviation (SD). Differences between groups were determined by ANOVA with Tukey’s post hoc test.p<0.05 was regarded as statistically significant.
## 2.1. Chemicals and Regents
Que was obtained from Sigma-Aldrich (St. Louis, USA; cat: Q4951); its purity is ≥95%. Human serum albumin (HSA; cat: A9731), D-galactosamine (D-GaLN; cat:G1639), and lipopolysaccharides (LPS; cat:L3012) were also obtained from Sigma-Aldrich (St. Louis, USA). Anti-Bcl-2 (cat: ab19645), anti-Bax (cat:ab32503), anti-HMGB1 (cat:ab79823), anti-iNOS (cat:ab49999), anti-COX-2 (cat:ab15191), and anti-4HNE (cat:ab48506) were obtained from Abcam (Shanghai, China). Anti-TLR-4 (cat: SC-293072) was obtained from Santa Cruz Biotechnology (Santa Cruz, USA). Anti-caspase-9 (cat: #9508), anti-caspase-3 (cat: #9662), anti-NF-κB p65 (cat:#8242) were obtained from Cell Signaling Technology (Boston, USA).
## 2.2. Experimental Animals
Ninety male Wistar rats weighing 200 to 240 g were purchased from Vital River Laboratory Animal Technology Co. Ltd. (Beijing, China). The animals were housed in a specific pathogen-free environment under constant temperature (25 ± 3°C) and humidity (60 ± 10%), with a 12 h light/dark cycle. All animals were acclimated to the environment for 5 days before the experiments. All of the procedures were performed according to the Institutional Guidelines for the Care and Use of Laboratory Animals and were authorized by the Animal Ethics Committee of Capital Medical University (NO.AEEI-2019-067).
## 2.3. Animal Treatment
The ACLF rat model was established as we described previously [24]. Briefly, acute liver failure was induced on the basis of chronic immune liver fibrosis. As shown in (Figure 1), except for the normal control group (n = 10), the remaining 80 rats were injected with HSA to induce immune liver injury. After 6 weeks, 50 survived rats with liver fibrosis confirmed by Masson’s trichrome staining [25] were selected, and then the rats were injected intraperitoneally with 400 mg/kg D-GaLN and 100 μg/kg LPS to establish the ACLF model. Then the rats were randomly divided into 5 groups: (1) ACLF group, rats were intragastric administration of an equal volume of normal saline solution and intraperitoneal injection of an equal amount of vehicle; (2) low-dose Que treatment group (Que-25), rats were intragastric administration of 25 mg/kg Que for 7 consecutive days and intraperitoneal injection of an equal amount of vehicle; (3) middle dose of Que treatment group (Que-50), treatment was the same as the Que-25 group, while the dose of Que was 50 mg/kg; (4) high dose of Que treatment group (Que-100), treatment was the same as the Que-25 group, while the dose of Que was 100 mg/kg; and (5) HMGB1 inhibitor intervention group (Que-100 + Gly), rats were intragastric administration of 100 mg/kg Que and intraperitoneal injection of 50 mg/kg glycyrrhizin (Gly) for 7 consecutive days. Gly is a direct inhibitor of HMGB1, which can bind to HMGB1 directly, interacting with two shallow concave surfaces formed by the two arms of both HMG boxes [26, 27]. At the end of the experiment, there were 10 survivors in the normal control group, 5 in the ACLF group, 6 in Que-25 group, 6 in the Que-50 group, 7 in the Que-100 group, and 7 in the Que-100 + Gly group. Before tissue collection, rats were deeply anesthetized by intraperitoneal injection of 1% pentobarbital sodium (40 mg/kg). After the anesthesia was stable, blood was collected from the abdominal aorta, and the serum collected by centrifugation was stored at −80°C. The liver tissue was quickly collected and weighed, frozen in liquid nitrogen, and stored at −80°C. Then the rats were euthanized by cervical dislocation.Figure 1
Establishment of ACLF rat model and experimental intervention. The rats were injected with HSA to induce immune hepatic fibrosis. At first stage, rats were sensitized by subcutaneous injection of HSA solution (0.5 ml, HSA 4 mg) for a total of 4 injections (days 0, 14, 24, and 34). Subsequently, tail vein injection was performed twice a week for 6 weeks (0.5 ml, gradually increased the HSA dose, 2.5 mg⟶3 mg⟶3.5 mg⟶4 mg⟶4.5 mg, and then maintained at 4.5 mg), and the normal group was injected with the same amount of normal saline. And then, intraperitoneal injection of 400 mg/kg D-GaLN and 100μg/kg LPS caused acute liver injury to establish the ACLF model. Finally, the rats were randomly divided into 5 intervention groups: receiving Que and/or glycyrrhizin, or vehicle treatment for 7 consecutive days. The normal control group underwent the same procedures without therapeutic intervention.
## 2.4. Determination of Serum Biochemical Indices
Blood samples were collected in tubes and centrifuged for 15 min at 3,000 rpm (Sigma-Aldrich, USA) to collect serum. The levels of alanine aminotransferase, aspartate aminotransferase (AST), and total bilirubin (TBiL) in serum were detected with an automatic analyzer (Hitachi, Inc., Japan) using commercial kits following the manufacturer’s instructions.
## 2.5. Determination of Prothrombin Times
Blood samples were collected in anti-coagulant tubes containing sodium citrate solution and centrifuged for 15 min at 3,000 rpm (Sigma-Aldrich, USA) to collect plasma. Prothrombin times (PTs) were measured using a kit (Nanjing, China) according to the manufacturer’s instructions.
## 2.6. Liver Histological Observation
Left lobes of liver tissues were isolated and fixed immediately with 10% neutral buffered formalin. The paraffin-embedded liver tissue samples were cut into 5μm thick sections for hematoxylin and eosin (H&E) staining, and then the sections were observed with a pathological section panoramic scanner (Leica Aperio AT2).
## 2.7. Assessment of Oxidative Stress
The content of hepatic malondialdehyde (MDA) was determined by thiobarbituric acid (TBA) reagent test using a commercial kit (Beyotime, China; cat: S0131). The liver homogenate was mixed with TBA buffer, incubated at 95°C for 1 hour, and then incubated on ice to stop the reaction. The mixture was centrifuged (4,000 rpm; 10 min), and the absorbance was measured by a microplate reader at a wavelength of 532 nm. The results were presented as nmol/mg protein.The level of anti-oxidant enzyme-reduced glutathione (GSH) content was determined by the 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) reactant test using a commercial kit (Beyotime, China; cat: S0053). Briefly, after mixing liver homogenate with DTNB stock solution and reacted, the absorbance was measured at a wavelength of 412 nm by a microplate reader. The GSH content in the sample was calculated according to the standard curve and presented as nmol/mg protein.
## 2.8. Immunofluorescence Analysis
Briefly, after dewaxing and antigen retrieval, the paraffin section was blocked by incubating with bovine serum albumin (BSA). Then the sections were individually incubated with anti-4-hydroxynonenal (4-HNE), anti-TLR-4, and anti-HMGB1 at 4°C overnight. After washing with PBS, the sections were incubated with FITC or TIRTC-labeled secondary antibody for 2 h at 37°C in the dark. Then the sections were washed 3 times with PBS for 5 min each time. Then, the tables were sealed with antifluorescence attenuation sealing solution (containing DAPI). Fluorescence images were collected by using a confocal microscope (Leica TCS SP8), and the results were analyzed using Image J software version 1.80.
## 2.9. Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling (TUNEL) Assays
The apoptotic response of hepatocytes was detected with paraffin-embedded sections using a TUNEL assay and Fluorescein In Situ Cell Death Assay Kit (KeyGEN BioTECH, China; cat: KGA7072) according to the manufacturer’s instructions. The positive cells were counted in 10 random fields at 400X magnification, and 3 sections of each sample were analyzed.
## 2.10. Western Blot Analysis
Liver proteins were homogenized and then collected by using RIPA lysis buffer. Cytoplasmic and nuclear proteins were isolated using nuclear and cytoplasmic protein extraction kits (Beyotime, China; cat: P0028), according to the manufacturer’s instructions. The BCA protein assay reagent kit was used to determine the concentration of total liver protein and the extracted nuclear protein and cytoplasmic protein. An equal amount of protein (30μg) was separated by 8–12% SDS-PAGE and transferred into PVDF membranes. Next, membranes were incubated with Tris-buffered saline, containing 5% non-fat dry milk for blocking purposes at room temperature for 1 hour. Then, membranes were incubated overnight at 4°C with primary antibodies directed against HMGB1, TLR-4, caspase-3, caspase-9, Bax, Bcl-2, NF- kB p65, iNOS, and COX-2. After washing with TBST, the membrane was incubated with a secondary antibody for 1 h at room temperature. Finally, the reaction was detected with an enhanced chemiluminescent reagent (NCM Biotech, China; cat: P10100). An ImageQuantLAS4000 chemiluminescence imaging system was used to visualize the target proteins (GE Co., USA), and densitometry was performed using the Image J software version 1.80.
## 2.11. Statistical Analysis
All data in the present study were analyzed using Prism 8.0 and expressed as the mean ± standard deviation (SD). Differences between groups were determined by ANOVA with Tukey’s post hoc test.p<0.05 was regarded as statistically significant.
## 3. Results
### 3.1. Que Alleviates Hepatic Injury in ACLF Rats
As shown in Figures2(a)–2(d), serum ALT, AST, and TBiL were significantly increased, whereas PT was significantly prolonged in the ACLF model group, and these increases were attenuated dose dependently by Que. Furthermore, H&E staining was performed to verify the extent of liver injury. In the normal control group, clear lobular structures could be observed, and hepatocytes were arranged in an orderly manner. In the ACLF group, disordered cell arrangement, inflammatory cell infiltration, hepatic sinus expansion and bleeding, and numerous necrotic liver cells were observed. However, the treatment with Que at the dose of 25 mg/kg, 50 mg/kg, and 100 mg/kg ameliorated liver pathological damage, and the dose of 100 mg/kg Que was more obvious (Figure 2(e)). On the basis of the results of liver function and pathological analysis, 100 mg/kg Que was chosen as the optimal dose for further studies. What’s more, when compared with Que-100, the ALT, AST, TBiL, and PT were further decreased after addition with Gly, an inhibitor of HMGB1, and the amelioration of pathologies showed the same performance.Figure 2
Effects of different doses of Que on liver function and pathology in acute on chronic liver failure (ACLF) rats: (a) the serum levels of alanine aminotransferase, (b) aspartate aminotransferase (AST), (c) total bilirubin (TBiL), (d) prothrombin times (PTs), and (e) hematoxylin and eosin (H&E) staining. Magnification 200X and 800X; scale bar: 200μm and 50 μm; data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01, representative of 5–10 rats/group).
(a)(b)(c)(d)(e)
### 3.2. Que Reduces Oxidative Stress Damage in ACLF Rats
To assess the oxidative stress damage, the levels of MDA and GSH in the liver of rats were detected. The MDA level (Figure3(a)) was significantly increased, and the GSH level (Figure 3(b)) was decreased in the ACLF group. However, the intervention of Que reduced the increase in MDA and increased the level of GSH. The level of 4-HNE accumulation, the main product of lipid peroxidation [28], was measurement by IF. Massive 4-HNE accumulation was in hepatocytes of the ACLF group, which decreased after Que intervention. What’s more, the above-mentioned effects of Que were significantly enhanced by Gly (Figures 3(c) and 3(d)).Figure 3
Effects of Que on oxidative stress damage in ACLF rats. The content of hepatic malondialdehyde (MDA); (b) glutathione (GSH); (c, d) immunofluorescence analysis of 4-hydroxynonenal (4-HNE). Magnification 400X; scale bar: 50μm; data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01, representative of 5–10 rats/group).
(a)(b)(c)(d)
### 3.3. Que Inhibits Hepatocyte Apoptosis in ACLF Rats
Next, the extent of apoptosis in liver tissues was evaluated by TUNEL staining, which labels 3′-OH ends of DNA by ribonuclease that are activated during apoptosis. Our results showed that the number of TUNEL-positive cells in the ACLF group dramatically increase, while Que blocked the changes significantly (Figures4(a) and 4(c)). Furthermore, we performed western blot to detect changes in apoptosis-related proteins. As results (Figures 4(b) and 4(d)–4(g)) shown, the upregulation of Bax, the ratio of cleaved caspase-9 and cleaved caspase-3, and the downregulation of anti-apoptotic protein Bcl-2 were observed in the ACLF group, which were reversed by Que treatment. Moreover, after addition with Gly, this anti-apoptotic effect was enhanced.Figure 4
Effects of Que on apoptosis in ACLF rats. (a, c) Representative stainings and positive cells of TUNEL assays. The positive cells were counted in 10 random fields at 400X magnification, and 3 sections of each sample were analyzed, representative of 5–10 rats/group, scale bar: 50μm. (b, d, e, f) Representative western blot analyses of apoptosis-related proteins (Bax, Bcl-2, Pro-caspase-9, caspase-9, Pro-caspase-3, and caspase-3). Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)(g)
### 3.4. Que Decreases the Expression and Translocation of HMGB1 in Hepatocytes of ACLF Rats
On the basis of our previous research, Que could inhibit HMGB1-mediated hepatocyte damage in vitro [22]. Therefore, in order to determine whether the improvement effect of ACLF by Que is related to HMGB1, we performed IF and western blot to detect the expression of HMGB1. IF showed the increased expression and distribution in the cytoplasm of HMGB1 in the ACLF group (Figure 5(a)). Western blot also confirmed that the total amount of HMGB1 and the ratio of HMGB1 in the cytoplasm to the total were increased (Figures 5(b)–5(f)). The treatment of Que reduced the increase and translocation of HMGB1. While cotreated with Gly, the inhibition was significantly enhanced.Figure 5
Effects of Que on the expression and translocation of HMGB1 in ACLF rats. (a) Immunofluorescence staining of HMGB1 expression and translocation. Arrows indicate the HMGB1 in cytoplasm. Magnification 400 (X); scale bar: 100μm. (b) Representative immunoblots for the HMGB1 in the nucleus; HMGB1 in the cytoplasm. (c, d) HMGB1 in the cytoplasm and nucleus under different treatments under different treatment by western blot assay. (e, f) Calculated results of the ratio of HMGB1 in the cytoplasm and the total expression of HMGB1. According to the different positions of HMGB1 expressed in the cytoplasm and nucleus, GAPDH and histone H3 were selected as housekeeping proteins. Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)
### 3.5. Que Inhibits HMGB1-Mediated Signaling Pathway
Next, to investigate the molecular mechanism of Que on HMGB1-mediated oxidative stress and apoptosis in ACLF, we analyzed changes in proteins expression of related pathways. The expression of TLR-4, an HMGB1 receptor, was significantly increased (Figures6(b) and 6(c)), and IF showed the extensive expression of TLR-4 in the cytoplasm of damaged hepatocytes. The treatment of Que reduced this kind of expression (Figure 6(a)). Moreover, the expressions of related pathway proteins NF-kB-p65, iNOS, and Cox-2 were also increased in the ACLF group, and the treatment of Que reduced this increase of expression. What’s more, the cotreatment of Gly, the inhibition effect on the expression of TLR-4, and related pathway proteins were significantly enhanced over that of Que alone (Figures 6(b) and 6(d)–6(f)).Figure 6
Effects of Que on the HMGB1 signaling pathway. (a) Immunofluorescence staining of TLR-4 receptor expression under different treatment conditions. Magnification 400X; scale bar: 75μm. (b–f) The TLR-4, NF-κB P65, iNOS, and COX-2 proteins expression levels were evaluated by western blot assay. Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)
## 3.1. Que Alleviates Hepatic Injury in ACLF Rats
As shown in Figures2(a)–2(d), serum ALT, AST, and TBiL were significantly increased, whereas PT was significantly prolonged in the ACLF model group, and these increases were attenuated dose dependently by Que. Furthermore, H&E staining was performed to verify the extent of liver injury. In the normal control group, clear lobular structures could be observed, and hepatocytes were arranged in an orderly manner. In the ACLF group, disordered cell arrangement, inflammatory cell infiltration, hepatic sinus expansion and bleeding, and numerous necrotic liver cells were observed. However, the treatment with Que at the dose of 25 mg/kg, 50 mg/kg, and 100 mg/kg ameliorated liver pathological damage, and the dose of 100 mg/kg Que was more obvious (Figure 2(e)). On the basis of the results of liver function and pathological analysis, 100 mg/kg Que was chosen as the optimal dose for further studies. What’s more, when compared with Que-100, the ALT, AST, TBiL, and PT were further decreased after addition with Gly, an inhibitor of HMGB1, and the amelioration of pathologies showed the same performance.Figure 2
Effects of different doses of Que on liver function and pathology in acute on chronic liver failure (ACLF) rats: (a) the serum levels of alanine aminotransferase, (b) aspartate aminotransferase (AST), (c) total bilirubin (TBiL), (d) prothrombin times (PTs), and (e) hematoxylin and eosin (H&E) staining. Magnification 200X and 800X; scale bar: 200μm and 50 μm; data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01, representative of 5–10 rats/group).
(a)(b)(c)(d)(e)
## 3.2. Que Reduces Oxidative Stress Damage in ACLF Rats
To assess the oxidative stress damage, the levels of MDA and GSH in the liver of rats were detected. The MDA level (Figure3(a)) was significantly increased, and the GSH level (Figure 3(b)) was decreased in the ACLF group. However, the intervention of Que reduced the increase in MDA and increased the level of GSH. The level of 4-HNE accumulation, the main product of lipid peroxidation [28], was measurement by IF. Massive 4-HNE accumulation was in hepatocytes of the ACLF group, which decreased after Que intervention. What’s more, the above-mentioned effects of Que were significantly enhanced by Gly (Figures 3(c) and 3(d)).Figure 3
Effects of Que on oxidative stress damage in ACLF rats. The content of hepatic malondialdehyde (MDA); (b) glutathione (GSH); (c, d) immunofluorescence analysis of 4-hydroxynonenal (4-HNE). Magnification 400X; scale bar: 50μm; data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01, representative of 5–10 rats/group).
(a)(b)(c)(d)
## 3.3. Que Inhibits Hepatocyte Apoptosis in ACLF Rats
Next, the extent of apoptosis in liver tissues was evaluated by TUNEL staining, which labels 3′-OH ends of DNA by ribonuclease that are activated during apoptosis. Our results showed that the number of TUNEL-positive cells in the ACLF group dramatically increase, while Que blocked the changes significantly (Figures4(a) and 4(c)). Furthermore, we performed western blot to detect changes in apoptosis-related proteins. As results (Figures 4(b) and 4(d)–4(g)) shown, the upregulation of Bax, the ratio of cleaved caspase-9 and cleaved caspase-3, and the downregulation of anti-apoptotic protein Bcl-2 were observed in the ACLF group, which were reversed by Que treatment. Moreover, after addition with Gly, this anti-apoptotic effect was enhanced.Figure 4
Effects of Que on apoptosis in ACLF rats. (a, c) Representative stainings and positive cells of TUNEL assays. The positive cells were counted in 10 random fields at 400X magnification, and 3 sections of each sample were analyzed, representative of 5–10 rats/group, scale bar: 50μm. (b, d, e, f) Representative western blot analyses of apoptosis-related proteins (Bax, Bcl-2, Pro-caspase-9, caspase-9, Pro-caspase-3, and caspase-3). Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)(g)
## 3.4. Que Decreases the Expression and Translocation of HMGB1 in Hepatocytes of ACLF Rats
On the basis of our previous research, Que could inhibit HMGB1-mediated hepatocyte damage in vitro [22]. Therefore, in order to determine whether the improvement effect of ACLF by Que is related to HMGB1, we performed IF and western blot to detect the expression of HMGB1. IF showed the increased expression and distribution in the cytoplasm of HMGB1 in the ACLF group (Figure 5(a)). Western blot also confirmed that the total amount of HMGB1 and the ratio of HMGB1 in the cytoplasm to the total were increased (Figures 5(b)–5(f)). The treatment of Que reduced the increase and translocation of HMGB1. While cotreated with Gly, the inhibition was significantly enhanced.Figure 5
Effects of Que on the expression and translocation of HMGB1 in ACLF rats. (a) Immunofluorescence staining of HMGB1 expression and translocation. Arrows indicate the HMGB1 in cytoplasm. Magnification 400 (X); scale bar: 100μm. (b) Representative immunoblots for the HMGB1 in the nucleus; HMGB1 in the cytoplasm. (c, d) HMGB1 in the cytoplasm and nucleus under different treatments under different treatment by western blot assay. (e, f) Calculated results of the ratio of HMGB1 in the cytoplasm and the total expression of HMGB1. According to the different positions of HMGB1 expressed in the cytoplasm and nucleus, GAPDH and histone H3 were selected as housekeeping proteins. Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)
## 3.5. Que Inhibits HMGB1-Mediated Signaling Pathway
Next, to investigate the molecular mechanism of Que on HMGB1-mediated oxidative stress and apoptosis in ACLF, we analyzed changes in proteins expression of related pathways. The expression of TLR-4, an HMGB1 receptor, was significantly increased (Figures6(b) and 6(c)), and IF showed the extensive expression of TLR-4 in the cytoplasm of damaged hepatocytes. The treatment of Que reduced this kind of expression (Figure 6(a)). Moreover, the expressions of related pathway proteins NF-kB-p65, iNOS, and Cox-2 were also increased in the ACLF group, and the treatment of Que reduced this increase of expression. What’s more, the cotreatment of Gly, the inhibition effect on the expression of TLR-4, and related pathway proteins were significantly enhanced over that of Que alone (Figures 6(b) and 6(d)–6(f)).Figure 6
Effects of Que on the HMGB1 signaling pathway. (a) Immunofluorescence staining of TLR-4 receptor expression under different treatment conditions. Magnification 400X; scale bar: 75μm. (b–f) The TLR-4, NF-κB P65, iNOS, and COX-2 proteins expression levels were evaluated by western blot assay. Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)
## 4. Discussion
At present, the pathophysiology of ACLF remains poorly understood, and pharmacological approaches to reduce mortality from ACLF are still lacking. However, increasing evidence indicate that HMGB1 may be involved in the pathological progress of liver failure [11, 29]. A study on the detection of hepatocyte death biomarkers in patients with hepatitis B virus-related ACLF (HBV-ACLF) finds that the serum HMGB1 level of HBV-ACLF patients is significantly higher than that of healthy controls and chronic hepatitis B (CHB) patients [30]. Moreover, the increased expression of HMGB1 is significantly correlated with the occurrence of ACLF [31]. A meta-analysis also indicates that HMGB1 may be a useful therapeutic target for severe hepatitis B and ACLF [32]. Meanwhile, the translocation of HMGB1 to extranuclear does not exist in hepatocytes of healthy people and CHB patients. But, in ACLF patients, even in their non-necrotic hepatocytes, a lot of extranuclear translocations occurred. The nucleus-to-cytoplasm translocation of HMGB1 is a key process prior to its extracellular secretion [33].The extracellular HMGB1, which acts as a DAMP factor, plays an important role in various liver injuries. Especially in severe liver injury, the level of HMGB1 is significantly increased [34]. However, previous studies have focused more on the proinflammatory effects of HMGB1. The increasing credible evidence confirms that HMGB1 is also essential to mediate the occurrence of oxidative stress [35]. In vitro, recombinant HMGB1 caused oxidative stress with TLR-4-dependent activation of NADPH oxidase [36]. What’s more, HMGB1 activates the TLR-4 signal transduction pathway and induces the translocation of NF-κB-p65 subunits to the nucleus, thereby increasing its transcriptional activity [37]. Thus, the activation of COX-2 and iNOS is induced, leading to the accumulation of 4-HNE, causing lipid peroxidation and oxidative stress [38, 39].For liver failure, excessive apoptosis is also one of the main ways of cell death, which is also confirmed in our current experiment. And, the release of HMGB1 is also present in apoptotic cells. HMGB1 can be released in late apoptotic cells by binding to DNA [40]. Macrophages are also activated by apoptotic cells to release HMGB1 [41]. After being released, caspase-3 dependent apoptosis can be activated by HMGB1 through the TLR-4 pathway [42]. Moreover, it has been confirmed that blocking HMGB1 can inhibit caspase-3 activation, thereby reducing cell apoptosis [43]. Oxidative stress regulates the mitochondrial membrane potential, leading to the initiation of apoptosis in the mitochondrial pathway [44]. Mitochondria plays an important role in apoptosis by relocating intermembrane mitochondrial proteins, such as Bcl-2 and Bax [45]. Here, in the present study, we found that HMGB1 may play a regulatory role in hepatocyte apoptosis and oxidative stress in ACLF rats. Therefore, we hypothesize that HMGB1-mediated apoptosis is caused by the mitochondrial release of apoptotic proteins caused by oxidative stress. To our best knowledge, this mechanism by which HMGB1 is involved in ACLF pathological progression is confirmed for the first time.Que, as an effective phytochemical ingredient for the treatment of various liver diseases, has been proved to have hepatocellular protection in vivo and in vitro [46]. Que inhibits the production of oxidative markers and the activation of NF-κB and MAPK signaling pathways; thus, the expression of apoptosis-related proteins has been induced in acute liver failure (ALF) mice induced by LPS/D-GalN [21]. Que also inhibits the translocation and release of HMGB1 in macrophages induced by LPS and protects mice from immune liver injury induced by Con-A by inhibiting the HMGB1-TLR2/TLR4-NF-κB pathway [20]. Our previous research shows that Que inhibits HMGB1-mediated oxidative stress and apoptosis, thereby protecting L02 cells from D-GaLN mediated damage in vitro [22]. In the present study, we confirmed that Que could reduce the pathological damage, the occurrence of oxidative stress, and apoptosis in ACLF rats for the first time. The treatment of Que also reduced the translocation and overexpression of HMGB1, and its signaling pathway proteins mediated by it. The cotreatment with Gly, a direct HMGB1 inhibitor, further inhibited HMGB1 and its translocation, as well as the oxidative stress and apoptosis mediated by it, when compared with Que alone. Therefore, part of the mechanism of Que attenuating ACLF may be related to inhibiting HMGB1 and its translocation, thereby the oxidative stress and apoptosis mediated by it (Figure 7). However, there are some limitations in current research, such as the effect of Que on ACLF rats after HMGB1 overexpression or activation was not observed, and also the lack of a group with Gly alone. These should be considered in our future research.Figure 7
The mechanism of Que attenuating liver injury in ACLF rats by inhibiting HMGB1 and its translocation.
## 5. Conclusion
In conclusion, our present study confirmed that HMGB1 and its translocation were involved in ACLF, and the specific mechanism may be related to the oxidative stress and apoptosis mediated by it. Thus, this provides further evidence for ACLF treatment with intervention HMGB1 as the target. And also Que may provide a new pharmacological intervention option for ACLF.
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*Source: 2898995-2021-10-25.xml* | 2898995-2021-10-25_2898995-2021-10-25.md | 44,195 | Quercetin Reduces Oxidative Stress and Apoptosis by Inhibiting HMGB1 and Its Translocation, Thereby Alleviating Liver Injury in ACLF Rats | Peng Fang; Bo Dou; Jiajun Liang; Weixin Hou; Chongyang Ma; Qiuyun Zhang | Evidence-Based Complementary and Alternative Medicine
(2021) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2021/2898995 | 2898995-2021-10-25.xml | ---
## Abstract
Background. Acute on chronic liver failure (ACLF) is a syndrome of acute liver failure that occurs on the basis of chronic liver disease, which is characterized by a rapid deterioration in a short period and high mortality. High mobility group box 1 (HMGB1) may be involved in the pathological process of ACLF; its specific role remains to be further elucidated. Our previous studies have shown that quercetin (Que) exerts anti-oxidant and anti-apoptotic effects by inhibiting HMGB1 in vitro. The present study aimed to investigate the effect of Que on liver injury in ACLF rats. Methods. The contents of ALT, AST, TBiL, and PT time of rats in each group were observed. HE staining was used to detect liver pathology. The levels of oxidative stress indicators such as MDA, GSH, and 4-HNE in the rat liver were detected. TUNEL assay was used to detect apoptosis in rat hepatocytes. Immunofluorescence and western blot analysis were performed to explore the protective effect of Que on ACLF rats and the underlying mechanism. Results. The results showed that Que could reduce the increase of serum biochemical indices, improve liver pathology, and reduce liver damage in ACLF rats. Further results confirmed that Que reduced the occurrence of oxidative stress and apoptosis of hepatocytes, and these reactions may aggravate the progress of ACLF. Meanwhile, the results of immunofluorescence and western blotting also confirmed that the expression of HMGB1 and extranuclear translocation in ACLF rat hepatocytes were significantly increased, which was alleviated by the treatment of Que. In addition, when cotreated with glycyrrhizin (Gly), an inhibitor of HMGB1, the inhibition of Que on HMGB1 and its translocation, apoptosis and oxidative stress, and the related proteins of HMGB1-mediated cellular pathway have been significantly enhanced. Conclusion. Thus, Que alleviates liver injury in ACLF rats, and its mechanism may be related to oxidative stress and apoptosis caused by HMGB1 and its translocation.
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## Body
## 1. Introduction
Acute on chronic liver failure (ACLF) refers to a syndrome of liver failure caused by various factors on the basis of chronic liver disease, which is manifested by acute jaundice deepening and coagulopathy [1]. It can be complicated by various symptoms such as hepatic encephalopathy, ascites, infection, and extrahepatic organ failure [2]. ACLF is accompanied by rapid deterioration and high mortality in the short term. In Western countries, ACLF is mainly caused by alcoholic liver injury, improper drug use, and infection. In Asia, the main cause is hepatitis virus, and about 80% of patients are caused by acute exacerbation of HBV infection, followed by damage from drugs and hepatotoxic substances [3]. A study on hospitalized patients with liver cirrhosis in the United States showed that the incidence of ACLF among hospitalized patients with cirrhosis was 26.39%, and the 90-day mortality rate was 40.02% [4, 5]. Another 10-year cohort study conducted in China showed that the 60-day mortality rate of ACLF patients who did not undergo liver transplantation was 37.4% [6]. Even though the East and West have different understanding and definitions of ACLF, the mortality rate of ACLF is extremely high in both parties [7].Although the pathogenesis of ACLF is poorly understood, however, the release of damage-associated molecular patterns (DAMPs) caused by immune system imbalance and inflammatory response has been confirmed to aggravate the pathological process of ACLF [8]. High mobility group box 1 (HMGB1), an evolutionarily conserved nuclear DNA binding protein, is widely present in eukaryotic cells and has important biological activities both inside and outside the cell [9, 10]. Once released outside the cell membrane, it can also act as DAMP. Many convincing evidence indicate that the pathological process of ACLF is affected by HMGB1 [11, 12].Quercetin (3,3′,4′,5,7-pentahydroxyflavone, Que), a typical flavonol-type flavonoid, is also considered as a potential inhibitor of HMGB1 [13]. Several research suggest that Que has a wide range of biological effects such as anti-oxidant, anti-inflammatory, and anti-apoptosis [14, 15]. Supplementing the diet with Que has beneficial effects on many liver diseases [16]. Que improves liver cell damage by inhibiting inflammation, oxidative stress, and cell apoptosis, thereby reducing liver damage caused by various hepatoxins in vivo [17–19]. As an effective phytochemical component for the treatment of various liver diseases, it has been studied in hepatitis, acute liver failure, and fibrosis [13, 20, 21]. Our previous studies have shown that Que exerts anti-oxidant and anti-apoptotic effects via inhibiting HMGB1, thereby protecting the liver cell from damage caused by D-GaLN in vitro [22]. In the present ACLF rat model, the application of D-GaLN is the main stimulating factor for acute liver injury. However, whether Que can reduce liver injury in ACLF rats has not yet been adequately studied. In the present study, we investigated the protective effect of Que on liver injury in ACLF rats, following the research method of the hepatoprotective effect of flavonoids [23]. In addition, an exact inhibitor of HMGB1 was combined to further verify the hypothesis that HMGB1 plays an important role in the disease process of ACLF and the beneficial therapeutic effect of its inhibition.
## 2. Materials and Methods
### 2.1. Chemicals and Regents
Que was obtained from Sigma-Aldrich (St. Louis, USA; cat: Q4951); its purity is ≥95%. Human serum albumin (HSA; cat: A9731), D-galactosamine (D-GaLN; cat:G1639), and lipopolysaccharides (LPS; cat:L3012) were also obtained from Sigma-Aldrich (St. Louis, USA). Anti-Bcl-2 (cat: ab19645), anti-Bax (cat:ab32503), anti-HMGB1 (cat:ab79823), anti-iNOS (cat:ab49999), anti-COX-2 (cat:ab15191), and anti-4HNE (cat:ab48506) were obtained from Abcam (Shanghai, China). Anti-TLR-4 (cat: SC-293072) was obtained from Santa Cruz Biotechnology (Santa Cruz, USA). Anti-caspase-9 (cat: #9508), anti-caspase-3 (cat: #9662), anti-NF-κB p65 (cat:#8242) were obtained from Cell Signaling Technology (Boston, USA).
### 2.2. Experimental Animals
Ninety male Wistar rats weighing 200 to 240 g were purchased from Vital River Laboratory Animal Technology Co. Ltd. (Beijing, China). The animals were housed in a specific pathogen-free environment under constant temperature (25 ± 3°C) and humidity (60 ± 10%), with a 12 h light/dark cycle. All animals were acclimated to the environment for 5 days before the experiments. All of the procedures were performed according to the Institutional Guidelines for the Care and Use of Laboratory Animals and were authorized by the Animal Ethics Committee of Capital Medical University (NO.AEEI-2019-067).
### 2.3. Animal Treatment
The ACLF rat model was established as we described previously [24]. Briefly, acute liver failure was induced on the basis of chronic immune liver fibrosis. As shown in (Figure 1), except for the normal control group (n = 10), the remaining 80 rats were injected with HSA to induce immune liver injury. After 6 weeks, 50 survived rats with liver fibrosis confirmed by Masson’s trichrome staining [25] were selected, and then the rats were injected intraperitoneally with 400 mg/kg D-GaLN and 100 μg/kg LPS to establish the ACLF model. Then the rats were randomly divided into 5 groups: (1) ACLF group, rats were intragastric administration of an equal volume of normal saline solution and intraperitoneal injection of an equal amount of vehicle; (2) low-dose Que treatment group (Que-25), rats were intragastric administration of 25 mg/kg Que for 7 consecutive days and intraperitoneal injection of an equal amount of vehicle; (3) middle dose of Que treatment group (Que-50), treatment was the same as the Que-25 group, while the dose of Que was 50 mg/kg; (4) high dose of Que treatment group (Que-100), treatment was the same as the Que-25 group, while the dose of Que was 100 mg/kg; and (5) HMGB1 inhibitor intervention group (Que-100 + Gly), rats were intragastric administration of 100 mg/kg Que and intraperitoneal injection of 50 mg/kg glycyrrhizin (Gly) for 7 consecutive days. Gly is a direct inhibitor of HMGB1, which can bind to HMGB1 directly, interacting with two shallow concave surfaces formed by the two arms of both HMG boxes [26, 27]. At the end of the experiment, there were 10 survivors in the normal control group, 5 in the ACLF group, 6 in Que-25 group, 6 in the Que-50 group, 7 in the Que-100 group, and 7 in the Que-100 + Gly group. Before tissue collection, rats were deeply anesthetized by intraperitoneal injection of 1% pentobarbital sodium (40 mg/kg). After the anesthesia was stable, blood was collected from the abdominal aorta, and the serum collected by centrifugation was stored at −80°C. The liver tissue was quickly collected and weighed, frozen in liquid nitrogen, and stored at −80°C. Then the rats were euthanized by cervical dislocation.Figure 1
Establishment of ACLF rat model and experimental intervention. The rats were injected with HSA to induce immune hepatic fibrosis. At first stage, rats were sensitized by subcutaneous injection of HSA solution (0.5 ml, HSA 4 mg) for a total of 4 injections (days 0, 14, 24, and 34). Subsequently, tail vein injection was performed twice a week for 6 weeks (0.5 ml, gradually increased the HSA dose, 2.5 mg⟶3 mg⟶3.5 mg⟶4 mg⟶4.5 mg, and then maintained at 4.5 mg), and the normal group was injected with the same amount of normal saline. And then, intraperitoneal injection of 400 mg/kg D-GaLN and 100μg/kg LPS caused acute liver injury to establish the ACLF model. Finally, the rats were randomly divided into 5 intervention groups: receiving Que and/or glycyrrhizin, or vehicle treatment for 7 consecutive days. The normal control group underwent the same procedures without therapeutic intervention.
### 2.4. Determination of Serum Biochemical Indices
Blood samples were collected in tubes and centrifuged for 15 min at 3,000 rpm (Sigma-Aldrich, USA) to collect serum. The levels of alanine aminotransferase, aspartate aminotransferase (AST), and total bilirubin (TBiL) in serum were detected with an automatic analyzer (Hitachi, Inc., Japan) using commercial kits following the manufacturer’s instructions.
### 2.5. Determination of Prothrombin Times
Blood samples were collected in anti-coagulant tubes containing sodium citrate solution and centrifuged for 15 min at 3,000 rpm (Sigma-Aldrich, USA) to collect plasma. Prothrombin times (PTs) were measured using a kit (Nanjing, China) according to the manufacturer’s instructions.
### 2.6. Liver Histological Observation
Left lobes of liver tissues were isolated and fixed immediately with 10% neutral buffered formalin. The paraffin-embedded liver tissue samples were cut into 5μm thick sections for hematoxylin and eosin (H&E) staining, and then the sections were observed with a pathological section panoramic scanner (Leica Aperio AT2).
### 2.7. Assessment of Oxidative Stress
The content of hepatic malondialdehyde (MDA) was determined by thiobarbituric acid (TBA) reagent test using a commercial kit (Beyotime, China; cat: S0131). The liver homogenate was mixed with TBA buffer, incubated at 95°C for 1 hour, and then incubated on ice to stop the reaction. The mixture was centrifuged (4,000 rpm; 10 min), and the absorbance was measured by a microplate reader at a wavelength of 532 nm. The results were presented as nmol/mg protein.The level of anti-oxidant enzyme-reduced glutathione (GSH) content was determined by the 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) reactant test using a commercial kit (Beyotime, China; cat: S0053). Briefly, after mixing liver homogenate with DTNB stock solution and reacted, the absorbance was measured at a wavelength of 412 nm by a microplate reader. The GSH content in the sample was calculated according to the standard curve and presented as nmol/mg protein.
### 2.8. Immunofluorescence Analysis
Briefly, after dewaxing and antigen retrieval, the paraffin section was blocked by incubating with bovine serum albumin (BSA). Then the sections were individually incubated with anti-4-hydroxynonenal (4-HNE), anti-TLR-4, and anti-HMGB1 at 4°C overnight. After washing with PBS, the sections were incubated with FITC or TIRTC-labeled secondary antibody for 2 h at 37°C in the dark. Then the sections were washed 3 times with PBS for 5 min each time. Then, the tables were sealed with antifluorescence attenuation sealing solution (containing DAPI). Fluorescence images were collected by using a confocal microscope (Leica TCS SP8), and the results were analyzed using Image J software version 1.80.
### 2.9. Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling (TUNEL) Assays
The apoptotic response of hepatocytes was detected with paraffin-embedded sections using a TUNEL assay and Fluorescein In Situ Cell Death Assay Kit (KeyGEN BioTECH, China; cat: KGA7072) according to the manufacturer’s instructions. The positive cells were counted in 10 random fields at 400X magnification, and 3 sections of each sample were analyzed.
### 2.10. Western Blot Analysis
Liver proteins were homogenized and then collected by using RIPA lysis buffer. Cytoplasmic and nuclear proteins were isolated using nuclear and cytoplasmic protein extraction kits (Beyotime, China; cat: P0028), according to the manufacturer’s instructions. The BCA protein assay reagent kit was used to determine the concentration of total liver protein and the extracted nuclear protein and cytoplasmic protein. An equal amount of protein (30μg) was separated by 8–12% SDS-PAGE and transferred into PVDF membranes. Next, membranes were incubated with Tris-buffered saline, containing 5% non-fat dry milk for blocking purposes at room temperature for 1 hour. Then, membranes were incubated overnight at 4°C with primary antibodies directed against HMGB1, TLR-4, caspase-3, caspase-9, Bax, Bcl-2, NF- kB p65, iNOS, and COX-2. After washing with TBST, the membrane was incubated with a secondary antibody for 1 h at room temperature. Finally, the reaction was detected with an enhanced chemiluminescent reagent (NCM Biotech, China; cat: P10100). An ImageQuantLAS4000 chemiluminescence imaging system was used to visualize the target proteins (GE Co., USA), and densitometry was performed using the Image J software version 1.80.
### 2.11. Statistical Analysis
All data in the present study were analyzed using Prism 8.0 and expressed as the mean ± standard deviation (SD). Differences between groups were determined by ANOVA with Tukey’s post hoc test.p<0.05 was regarded as statistically significant.
## 2.1. Chemicals and Regents
Que was obtained from Sigma-Aldrich (St. Louis, USA; cat: Q4951); its purity is ≥95%. Human serum albumin (HSA; cat: A9731), D-galactosamine (D-GaLN; cat:G1639), and lipopolysaccharides (LPS; cat:L3012) were also obtained from Sigma-Aldrich (St. Louis, USA). Anti-Bcl-2 (cat: ab19645), anti-Bax (cat:ab32503), anti-HMGB1 (cat:ab79823), anti-iNOS (cat:ab49999), anti-COX-2 (cat:ab15191), and anti-4HNE (cat:ab48506) were obtained from Abcam (Shanghai, China). Anti-TLR-4 (cat: SC-293072) was obtained from Santa Cruz Biotechnology (Santa Cruz, USA). Anti-caspase-9 (cat: #9508), anti-caspase-3 (cat: #9662), anti-NF-κB p65 (cat:#8242) were obtained from Cell Signaling Technology (Boston, USA).
## 2.2. Experimental Animals
Ninety male Wistar rats weighing 200 to 240 g were purchased from Vital River Laboratory Animal Technology Co. Ltd. (Beijing, China). The animals were housed in a specific pathogen-free environment under constant temperature (25 ± 3°C) and humidity (60 ± 10%), with a 12 h light/dark cycle. All animals were acclimated to the environment for 5 days before the experiments. All of the procedures were performed according to the Institutional Guidelines for the Care and Use of Laboratory Animals and were authorized by the Animal Ethics Committee of Capital Medical University (NO.AEEI-2019-067).
## 2.3. Animal Treatment
The ACLF rat model was established as we described previously [24]. Briefly, acute liver failure was induced on the basis of chronic immune liver fibrosis. As shown in (Figure 1), except for the normal control group (n = 10), the remaining 80 rats were injected with HSA to induce immune liver injury. After 6 weeks, 50 survived rats with liver fibrosis confirmed by Masson’s trichrome staining [25] were selected, and then the rats were injected intraperitoneally with 400 mg/kg D-GaLN and 100 μg/kg LPS to establish the ACLF model. Then the rats were randomly divided into 5 groups: (1) ACLF group, rats were intragastric administration of an equal volume of normal saline solution and intraperitoneal injection of an equal amount of vehicle; (2) low-dose Que treatment group (Que-25), rats were intragastric administration of 25 mg/kg Que for 7 consecutive days and intraperitoneal injection of an equal amount of vehicle; (3) middle dose of Que treatment group (Que-50), treatment was the same as the Que-25 group, while the dose of Que was 50 mg/kg; (4) high dose of Que treatment group (Que-100), treatment was the same as the Que-25 group, while the dose of Que was 100 mg/kg; and (5) HMGB1 inhibitor intervention group (Que-100 + Gly), rats were intragastric administration of 100 mg/kg Que and intraperitoneal injection of 50 mg/kg glycyrrhizin (Gly) for 7 consecutive days. Gly is a direct inhibitor of HMGB1, which can bind to HMGB1 directly, interacting with two shallow concave surfaces formed by the two arms of both HMG boxes [26, 27]. At the end of the experiment, there were 10 survivors in the normal control group, 5 in the ACLF group, 6 in Que-25 group, 6 in the Que-50 group, 7 in the Que-100 group, and 7 in the Que-100 + Gly group. Before tissue collection, rats were deeply anesthetized by intraperitoneal injection of 1% pentobarbital sodium (40 mg/kg). After the anesthesia was stable, blood was collected from the abdominal aorta, and the serum collected by centrifugation was stored at −80°C. The liver tissue was quickly collected and weighed, frozen in liquid nitrogen, and stored at −80°C. Then the rats were euthanized by cervical dislocation.Figure 1
Establishment of ACLF rat model and experimental intervention. The rats were injected with HSA to induce immune hepatic fibrosis. At first stage, rats were sensitized by subcutaneous injection of HSA solution (0.5 ml, HSA 4 mg) for a total of 4 injections (days 0, 14, 24, and 34). Subsequently, tail vein injection was performed twice a week for 6 weeks (0.5 ml, gradually increased the HSA dose, 2.5 mg⟶3 mg⟶3.5 mg⟶4 mg⟶4.5 mg, and then maintained at 4.5 mg), and the normal group was injected with the same amount of normal saline. And then, intraperitoneal injection of 400 mg/kg D-GaLN and 100μg/kg LPS caused acute liver injury to establish the ACLF model. Finally, the rats were randomly divided into 5 intervention groups: receiving Que and/or glycyrrhizin, or vehicle treatment for 7 consecutive days. The normal control group underwent the same procedures without therapeutic intervention.
## 2.4. Determination of Serum Biochemical Indices
Blood samples were collected in tubes and centrifuged for 15 min at 3,000 rpm (Sigma-Aldrich, USA) to collect serum. The levels of alanine aminotransferase, aspartate aminotransferase (AST), and total bilirubin (TBiL) in serum were detected with an automatic analyzer (Hitachi, Inc., Japan) using commercial kits following the manufacturer’s instructions.
## 2.5. Determination of Prothrombin Times
Blood samples were collected in anti-coagulant tubes containing sodium citrate solution and centrifuged for 15 min at 3,000 rpm (Sigma-Aldrich, USA) to collect plasma. Prothrombin times (PTs) were measured using a kit (Nanjing, China) according to the manufacturer’s instructions.
## 2.6. Liver Histological Observation
Left lobes of liver tissues were isolated and fixed immediately with 10% neutral buffered formalin. The paraffin-embedded liver tissue samples were cut into 5μm thick sections for hematoxylin and eosin (H&E) staining, and then the sections were observed with a pathological section panoramic scanner (Leica Aperio AT2).
## 2.7. Assessment of Oxidative Stress
The content of hepatic malondialdehyde (MDA) was determined by thiobarbituric acid (TBA) reagent test using a commercial kit (Beyotime, China; cat: S0131). The liver homogenate was mixed with TBA buffer, incubated at 95°C for 1 hour, and then incubated on ice to stop the reaction. The mixture was centrifuged (4,000 rpm; 10 min), and the absorbance was measured by a microplate reader at a wavelength of 532 nm. The results were presented as nmol/mg protein.The level of anti-oxidant enzyme-reduced glutathione (GSH) content was determined by the 5,5'-dithiobis-(2-nitrobenzoic acid) (DTNB) reactant test using a commercial kit (Beyotime, China; cat: S0053). Briefly, after mixing liver homogenate with DTNB stock solution and reacted, the absorbance was measured at a wavelength of 412 nm by a microplate reader. The GSH content in the sample was calculated according to the standard curve and presented as nmol/mg protein.
## 2.8. Immunofluorescence Analysis
Briefly, after dewaxing and antigen retrieval, the paraffin section was blocked by incubating with bovine serum albumin (BSA). Then the sections were individually incubated with anti-4-hydroxynonenal (4-HNE), anti-TLR-4, and anti-HMGB1 at 4°C overnight. After washing with PBS, the sections were incubated with FITC or TIRTC-labeled secondary antibody for 2 h at 37°C in the dark. Then the sections were washed 3 times with PBS for 5 min each time. Then, the tables were sealed with antifluorescence attenuation sealing solution (containing DAPI). Fluorescence images were collected by using a confocal microscope (Leica TCS SP8), and the results were analyzed using Image J software version 1.80.
## 2.9. Terminal Deoxynucleotidyl Transferase dUTP Nick End Labeling (TUNEL) Assays
The apoptotic response of hepatocytes was detected with paraffin-embedded sections using a TUNEL assay and Fluorescein In Situ Cell Death Assay Kit (KeyGEN BioTECH, China; cat: KGA7072) according to the manufacturer’s instructions. The positive cells were counted in 10 random fields at 400X magnification, and 3 sections of each sample were analyzed.
## 2.10. Western Blot Analysis
Liver proteins were homogenized and then collected by using RIPA lysis buffer. Cytoplasmic and nuclear proteins were isolated using nuclear and cytoplasmic protein extraction kits (Beyotime, China; cat: P0028), according to the manufacturer’s instructions. The BCA protein assay reagent kit was used to determine the concentration of total liver protein and the extracted nuclear protein and cytoplasmic protein. An equal amount of protein (30μg) was separated by 8–12% SDS-PAGE and transferred into PVDF membranes. Next, membranes were incubated with Tris-buffered saline, containing 5% non-fat dry milk for blocking purposes at room temperature for 1 hour. Then, membranes were incubated overnight at 4°C with primary antibodies directed against HMGB1, TLR-4, caspase-3, caspase-9, Bax, Bcl-2, NF- kB p65, iNOS, and COX-2. After washing with TBST, the membrane was incubated with a secondary antibody for 1 h at room temperature. Finally, the reaction was detected with an enhanced chemiluminescent reagent (NCM Biotech, China; cat: P10100). An ImageQuantLAS4000 chemiluminescence imaging system was used to visualize the target proteins (GE Co., USA), and densitometry was performed using the Image J software version 1.80.
## 2.11. Statistical Analysis
All data in the present study were analyzed using Prism 8.0 and expressed as the mean ± standard deviation (SD). Differences between groups were determined by ANOVA with Tukey’s post hoc test.p<0.05 was regarded as statistically significant.
## 3. Results
### 3.1. Que Alleviates Hepatic Injury in ACLF Rats
As shown in Figures2(a)–2(d), serum ALT, AST, and TBiL were significantly increased, whereas PT was significantly prolonged in the ACLF model group, and these increases were attenuated dose dependently by Que. Furthermore, H&E staining was performed to verify the extent of liver injury. In the normal control group, clear lobular structures could be observed, and hepatocytes were arranged in an orderly manner. In the ACLF group, disordered cell arrangement, inflammatory cell infiltration, hepatic sinus expansion and bleeding, and numerous necrotic liver cells were observed. However, the treatment with Que at the dose of 25 mg/kg, 50 mg/kg, and 100 mg/kg ameliorated liver pathological damage, and the dose of 100 mg/kg Que was more obvious (Figure 2(e)). On the basis of the results of liver function and pathological analysis, 100 mg/kg Que was chosen as the optimal dose for further studies. What’s more, when compared with Que-100, the ALT, AST, TBiL, and PT were further decreased after addition with Gly, an inhibitor of HMGB1, and the amelioration of pathologies showed the same performance.Figure 2
Effects of different doses of Que on liver function and pathology in acute on chronic liver failure (ACLF) rats: (a) the serum levels of alanine aminotransferase, (b) aspartate aminotransferase (AST), (c) total bilirubin (TBiL), (d) prothrombin times (PTs), and (e) hematoxylin and eosin (H&E) staining. Magnification 200X and 800X; scale bar: 200μm and 50 μm; data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01, representative of 5–10 rats/group).
(a)(b)(c)(d)(e)
### 3.2. Que Reduces Oxidative Stress Damage in ACLF Rats
To assess the oxidative stress damage, the levels of MDA and GSH in the liver of rats were detected. The MDA level (Figure3(a)) was significantly increased, and the GSH level (Figure 3(b)) was decreased in the ACLF group. However, the intervention of Que reduced the increase in MDA and increased the level of GSH. The level of 4-HNE accumulation, the main product of lipid peroxidation [28], was measurement by IF. Massive 4-HNE accumulation was in hepatocytes of the ACLF group, which decreased after Que intervention. What’s more, the above-mentioned effects of Que were significantly enhanced by Gly (Figures 3(c) and 3(d)).Figure 3
Effects of Que on oxidative stress damage in ACLF rats. The content of hepatic malondialdehyde (MDA); (b) glutathione (GSH); (c, d) immunofluorescence analysis of 4-hydroxynonenal (4-HNE). Magnification 400X; scale bar: 50μm; data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01, representative of 5–10 rats/group).
(a)(b)(c)(d)
### 3.3. Que Inhibits Hepatocyte Apoptosis in ACLF Rats
Next, the extent of apoptosis in liver tissues was evaluated by TUNEL staining, which labels 3′-OH ends of DNA by ribonuclease that are activated during apoptosis. Our results showed that the number of TUNEL-positive cells in the ACLF group dramatically increase, while Que blocked the changes significantly (Figures4(a) and 4(c)). Furthermore, we performed western blot to detect changes in apoptosis-related proteins. As results (Figures 4(b) and 4(d)–4(g)) shown, the upregulation of Bax, the ratio of cleaved caspase-9 and cleaved caspase-3, and the downregulation of anti-apoptotic protein Bcl-2 were observed in the ACLF group, which were reversed by Que treatment. Moreover, after addition with Gly, this anti-apoptotic effect was enhanced.Figure 4
Effects of Que on apoptosis in ACLF rats. (a, c) Representative stainings and positive cells of TUNEL assays. The positive cells were counted in 10 random fields at 400X magnification, and 3 sections of each sample were analyzed, representative of 5–10 rats/group, scale bar: 50μm. (b, d, e, f) Representative western blot analyses of apoptosis-related proteins (Bax, Bcl-2, Pro-caspase-9, caspase-9, Pro-caspase-3, and caspase-3). Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)(g)
### 3.4. Que Decreases the Expression and Translocation of HMGB1 in Hepatocytes of ACLF Rats
On the basis of our previous research, Que could inhibit HMGB1-mediated hepatocyte damage in vitro [22]. Therefore, in order to determine whether the improvement effect of ACLF by Que is related to HMGB1, we performed IF and western blot to detect the expression of HMGB1. IF showed the increased expression and distribution in the cytoplasm of HMGB1 in the ACLF group (Figure 5(a)). Western blot also confirmed that the total amount of HMGB1 and the ratio of HMGB1 in the cytoplasm to the total were increased (Figures 5(b)–5(f)). The treatment of Que reduced the increase and translocation of HMGB1. While cotreated with Gly, the inhibition was significantly enhanced.Figure 5
Effects of Que on the expression and translocation of HMGB1 in ACLF rats. (a) Immunofluorescence staining of HMGB1 expression and translocation. Arrows indicate the HMGB1 in cytoplasm. Magnification 400 (X); scale bar: 100μm. (b) Representative immunoblots for the HMGB1 in the nucleus; HMGB1 in the cytoplasm. (c, d) HMGB1 in the cytoplasm and nucleus under different treatments under different treatment by western blot assay. (e, f) Calculated results of the ratio of HMGB1 in the cytoplasm and the total expression of HMGB1. According to the different positions of HMGB1 expressed in the cytoplasm and nucleus, GAPDH and histone H3 were selected as housekeeping proteins. Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)
### 3.5. Que Inhibits HMGB1-Mediated Signaling Pathway
Next, to investigate the molecular mechanism of Que on HMGB1-mediated oxidative stress and apoptosis in ACLF, we analyzed changes in proteins expression of related pathways. The expression of TLR-4, an HMGB1 receptor, was significantly increased (Figures6(b) and 6(c)), and IF showed the extensive expression of TLR-4 in the cytoplasm of damaged hepatocytes. The treatment of Que reduced this kind of expression (Figure 6(a)). Moreover, the expressions of related pathway proteins NF-kB-p65, iNOS, and Cox-2 were also increased in the ACLF group, and the treatment of Que reduced this increase of expression. What’s more, the cotreatment of Gly, the inhibition effect on the expression of TLR-4, and related pathway proteins were significantly enhanced over that of Que alone (Figures 6(b) and 6(d)–6(f)).Figure 6
Effects of Que on the HMGB1 signaling pathway. (a) Immunofluorescence staining of TLR-4 receptor expression under different treatment conditions. Magnification 400X; scale bar: 75μm. (b–f) The TLR-4, NF-κB P65, iNOS, and COX-2 proteins expression levels were evaluated by western blot assay. Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)
## 3.1. Que Alleviates Hepatic Injury in ACLF Rats
As shown in Figures2(a)–2(d), serum ALT, AST, and TBiL were significantly increased, whereas PT was significantly prolonged in the ACLF model group, and these increases were attenuated dose dependently by Que. Furthermore, H&E staining was performed to verify the extent of liver injury. In the normal control group, clear lobular structures could be observed, and hepatocytes were arranged in an orderly manner. In the ACLF group, disordered cell arrangement, inflammatory cell infiltration, hepatic sinus expansion and bleeding, and numerous necrotic liver cells were observed. However, the treatment with Que at the dose of 25 mg/kg, 50 mg/kg, and 100 mg/kg ameliorated liver pathological damage, and the dose of 100 mg/kg Que was more obvious (Figure 2(e)). On the basis of the results of liver function and pathological analysis, 100 mg/kg Que was chosen as the optimal dose for further studies. What’s more, when compared with Que-100, the ALT, AST, TBiL, and PT were further decreased after addition with Gly, an inhibitor of HMGB1, and the amelioration of pathologies showed the same performance.Figure 2
Effects of different doses of Que on liver function and pathology in acute on chronic liver failure (ACLF) rats: (a) the serum levels of alanine aminotransferase, (b) aspartate aminotransferase (AST), (c) total bilirubin (TBiL), (d) prothrombin times (PTs), and (e) hematoxylin and eosin (H&E) staining. Magnification 200X and 800X; scale bar: 200μm and 50 μm; data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01, representative of 5–10 rats/group).
(a)(b)(c)(d)(e)
## 3.2. Que Reduces Oxidative Stress Damage in ACLF Rats
To assess the oxidative stress damage, the levels of MDA and GSH in the liver of rats were detected. The MDA level (Figure3(a)) was significantly increased, and the GSH level (Figure 3(b)) was decreased in the ACLF group. However, the intervention of Que reduced the increase in MDA and increased the level of GSH. The level of 4-HNE accumulation, the main product of lipid peroxidation [28], was measurement by IF. Massive 4-HNE accumulation was in hepatocytes of the ACLF group, which decreased after Que intervention. What’s more, the above-mentioned effects of Que were significantly enhanced by Gly (Figures 3(c) and 3(d)).Figure 3
Effects of Que on oxidative stress damage in ACLF rats. The content of hepatic malondialdehyde (MDA); (b) glutathione (GSH); (c, d) immunofluorescence analysis of 4-hydroxynonenal (4-HNE). Magnification 400X; scale bar: 50μm; data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01, representative of 5–10 rats/group).
(a)(b)(c)(d)
## 3.3. Que Inhibits Hepatocyte Apoptosis in ACLF Rats
Next, the extent of apoptosis in liver tissues was evaluated by TUNEL staining, which labels 3′-OH ends of DNA by ribonuclease that are activated during apoptosis. Our results showed that the number of TUNEL-positive cells in the ACLF group dramatically increase, while Que blocked the changes significantly (Figures4(a) and 4(c)). Furthermore, we performed western blot to detect changes in apoptosis-related proteins. As results (Figures 4(b) and 4(d)–4(g)) shown, the upregulation of Bax, the ratio of cleaved caspase-9 and cleaved caspase-3, and the downregulation of anti-apoptotic protein Bcl-2 were observed in the ACLF group, which were reversed by Que treatment. Moreover, after addition with Gly, this anti-apoptotic effect was enhanced.Figure 4
Effects of Que on apoptosis in ACLF rats. (a, c) Representative stainings and positive cells of TUNEL assays. The positive cells were counted in 10 random fields at 400X magnification, and 3 sections of each sample were analyzed, representative of 5–10 rats/group, scale bar: 50μm. (b, d, e, f) Representative western blot analyses of apoptosis-related proteins (Bax, Bcl-2, Pro-caspase-9, caspase-9, Pro-caspase-3, and caspase-3). Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)(g)
## 3.4. Que Decreases the Expression and Translocation of HMGB1 in Hepatocytes of ACLF Rats
On the basis of our previous research, Que could inhibit HMGB1-mediated hepatocyte damage in vitro [22]. Therefore, in order to determine whether the improvement effect of ACLF by Que is related to HMGB1, we performed IF and western blot to detect the expression of HMGB1. IF showed the increased expression and distribution in the cytoplasm of HMGB1 in the ACLF group (Figure 5(a)). Western blot also confirmed that the total amount of HMGB1 and the ratio of HMGB1 in the cytoplasm to the total were increased (Figures 5(b)–5(f)). The treatment of Que reduced the increase and translocation of HMGB1. While cotreated with Gly, the inhibition was significantly enhanced.Figure 5
Effects of Que on the expression and translocation of HMGB1 in ACLF rats. (a) Immunofluorescence staining of HMGB1 expression and translocation. Arrows indicate the HMGB1 in cytoplasm. Magnification 400 (X); scale bar: 100μm. (b) Representative immunoblots for the HMGB1 in the nucleus; HMGB1 in the cytoplasm. (c, d) HMGB1 in the cytoplasm and nucleus under different treatments under different treatment by western blot assay. (e, f) Calculated results of the ratio of HMGB1 in the cytoplasm and the total expression of HMGB1. According to the different positions of HMGB1 expressed in the cytoplasm and nucleus, GAPDH and histone H3 were selected as housekeeping proteins. Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)
## 3.5. Que Inhibits HMGB1-Mediated Signaling Pathway
Next, to investigate the molecular mechanism of Que on HMGB1-mediated oxidative stress and apoptosis in ACLF, we analyzed changes in proteins expression of related pathways. The expression of TLR-4, an HMGB1 receptor, was significantly increased (Figures6(b) and 6(c)), and IF showed the extensive expression of TLR-4 in the cytoplasm of damaged hepatocytes. The treatment of Que reduced this kind of expression (Figure 6(a)). Moreover, the expressions of related pathway proteins NF-kB-p65, iNOS, and Cox-2 were also increased in the ACLF group, and the treatment of Que reduced this increase of expression. What’s more, the cotreatment of Gly, the inhibition effect on the expression of TLR-4, and related pathway proteins were significantly enhanced over that of Que alone (Figures 6(b) and 6(d)–6(f)).Figure 6
Effects of Que on the HMGB1 signaling pathway. (a) Immunofluorescence staining of TLR-4 receptor expression under different treatment conditions. Magnification 400X; scale bar: 75μm. (b–f) The TLR-4, NF-κB P65, iNOS, and COX-2 proteins expression levels were evaluated by western blot assay. Data are presented as the mean ± SD (∗p<0.05, ∗∗p<0.01). The blots shown are representative of 3 independent experiments.
(a)(b)(c)(d)(e)(f)
## 4. Discussion
At present, the pathophysiology of ACLF remains poorly understood, and pharmacological approaches to reduce mortality from ACLF are still lacking. However, increasing evidence indicate that HMGB1 may be involved in the pathological progress of liver failure [11, 29]. A study on the detection of hepatocyte death biomarkers in patients with hepatitis B virus-related ACLF (HBV-ACLF) finds that the serum HMGB1 level of HBV-ACLF patients is significantly higher than that of healthy controls and chronic hepatitis B (CHB) patients [30]. Moreover, the increased expression of HMGB1 is significantly correlated with the occurrence of ACLF [31]. A meta-analysis also indicates that HMGB1 may be a useful therapeutic target for severe hepatitis B and ACLF [32]. Meanwhile, the translocation of HMGB1 to extranuclear does not exist in hepatocytes of healthy people and CHB patients. But, in ACLF patients, even in their non-necrotic hepatocytes, a lot of extranuclear translocations occurred. The nucleus-to-cytoplasm translocation of HMGB1 is a key process prior to its extracellular secretion [33].The extracellular HMGB1, which acts as a DAMP factor, plays an important role in various liver injuries. Especially in severe liver injury, the level of HMGB1 is significantly increased [34]. However, previous studies have focused more on the proinflammatory effects of HMGB1. The increasing credible evidence confirms that HMGB1 is also essential to mediate the occurrence of oxidative stress [35]. In vitro, recombinant HMGB1 caused oxidative stress with TLR-4-dependent activation of NADPH oxidase [36]. What’s more, HMGB1 activates the TLR-4 signal transduction pathway and induces the translocation of NF-κB-p65 subunits to the nucleus, thereby increasing its transcriptional activity [37]. Thus, the activation of COX-2 and iNOS is induced, leading to the accumulation of 4-HNE, causing lipid peroxidation and oxidative stress [38, 39].For liver failure, excessive apoptosis is also one of the main ways of cell death, which is also confirmed in our current experiment. And, the release of HMGB1 is also present in apoptotic cells. HMGB1 can be released in late apoptotic cells by binding to DNA [40]. Macrophages are also activated by apoptotic cells to release HMGB1 [41]. After being released, caspase-3 dependent apoptosis can be activated by HMGB1 through the TLR-4 pathway [42]. Moreover, it has been confirmed that blocking HMGB1 can inhibit caspase-3 activation, thereby reducing cell apoptosis [43]. Oxidative stress regulates the mitochondrial membrane potential, leading to the initiation of apoptosis in the mitochondrial pathway [44]. Mitochondria plays an important role in apoptosis by relocating intermembrane mitochondrial proteins, such as Bcl-2 and Bax [45]. Here, in the present study, we found that HMGB1 may play a regulatory role in hepatocyte apoptosis and oxidative stress in ACLF rats. Therefore, we hypothesize that HMGB1-mediated apoptosis is caused by the mitochondrial release of apoptotic proteins caused by oxidative stress. To our best knowledge, this mechanism by which HMGB1 is involved in ACLF pathological progression is confirmed for the first time.Que, as an effective phytochemical ingredient for the treatment of various liver diseases, has been proved to have hepatocellular protection in vivo and in vitro [46]. Que inhibits the production of oxidative markers and the activation of NF-κB and MAPK signaling pathways; thus, the expression of apoptosis-related proteins has been induced in acute liver failure (ALF) mice induced by LPS/D-GalN [21]. Que also inhibits the translocation and release of HMGB1 in macrophages induced by LPS and protects mice from immune liver injury induced by Con-A by inhibiting the HMGB1-TLR2/TLR4-NF-κB pathway [20]. Our previous research shows that Que inhibits HMGB1-mediated oxidative stress and apoptosis, thereby protecting L02 cells from D-GaLN mediated damage in vitro [22]. In the present study, we confirmed that Que could reduce the pathological damage, the occurrence of oxidative stress, and apoptosis in ACLF rats for the first time. The treatment of Que also reduced the translocation and overexpression of HMGB1, and its signaling pathway proteins mediated by it. The cotreatment with Gly, a direct HMGB1 inhibitor, further inhibited HMGB1 and its translocation, as well as the oxidative stress and apoptosis mediated by it, when compared with Que alone. Therefore, part of the mechanism of Que attenuating ACLF may be related to inhibiting HMGB1 and its translocation, thereby the oxidative stress and apoptosis mediated by it (Figure 7). However, there are some limitations in current research, such as the effect of Que on ACLF rats after HMGB1 overexpression or activation was not observed, and also the lack of a group with Gly alone. These should be considered in our future research.Figure 7
The mechanism of Que attenuating liver injury in ACLF rats by inhibiting HMGB1 and its translocation.
## 5. Conclusion
In conclusion, our present study confirmed that HMGB1 and its translocation were involved in ACLF, and the specific mechanism may be related to the oxidative stress and apoptosis mediated by it. Thus, this provides further evidence for ACLF treatment with intervention HMGB1 as the target. And also Que may provide a new pharmacological intervention option for ACLF.
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*Source: 2898995-2021-10-25.xml* | 2021 |
# Highly Porous 3D Printed Tantalum Scaffolds Have Better Biomechanical and Microstructural Properties than Titanium Scaffolds
**Authors:** Huaquan Fan; Shu Deng; Wentao Tang; Aikeremujiang Muheremu; Xianzhe Wu; Peng He; Caihua Tan; Guohua Wang; Jianzhong Tang; Kaixuan Guo; Liu Yang; Fuyou Wang
**Journal:** BioMed Research International
(2021)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2021/2899043
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## Abstract
Objective. To test the biomechanical properties of 3D printed tantalum and titanium porous scaffolds. Methods. Four types of tantalum and titanium scaffolds with four alternative pore diameters, #1 (1000-700 μm), #2 (700-1000 μm), #3 (500-800 μm), and #4 (800-500 μm), were molded by selective laser melting technique, and the scaffolds were tested by scanning electronic microscope, uniaxial-compression tests, and Young’s modulus tests; they were compared with same size pig femoral bone scaffolds. Results. Under uniaxial-compression tests, equivalent stress of tantalum scaffold was 411±1.43 MPa, which was significantly larger than the titanium scaffolds (P<0.05). Young’s modulus of tantalum scaffold was 2.61±0.02 GPa, which was only half of that of titanium scaffold. The stress-strain curves of tantalum scaffolds were more similar to pig bone scaffolds than titanium scaffolds. Conclusion. 3D printed tantalum scaffolds with varying pore diameters are more similar to actual bone scaffolds compared with titanium scaffolds in biomechanical properties.
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## Body
## 1. Background
Due to excellent corrosion resistance, toughness, and bioactivity, tantalum has been used for a variety of medical implant since 1940 [1–5]. While titanium is still considered the gold standard for porous biomaterials with skeletal biocompatibility [6–8], tantalum has been increasingly used as bone-substitute material with great potential. Highly porous tantalum scaffold was proven to have good bone conduction and induction capabilities and was shown to integrate well with bone in both basic research and human trials, indicating great prospect in its clinical application [9–11]. However, due to challenges in the processing of tantalum, its application is still limited in musculoskeletal system.For tantalum scaffolds to have fine osteogenic properties and be easily integrated with the host bone to prevent stress shielding and implant loosening, it is essential to improve the porosity of tantalum scaffold structure to obtain bone like mechanical properties. Previous studies have reported that pore diameter and porosity of tantalum scaffold have significant influence on its biocompatibility and adequate pore diameter, and high porosity is beneficial to the ingrowth of bone, soft tissues, and blood vessels [12–15].Traditional additive manufacturing techniques such as metal fiber sintering, powder metallurgy, and plasma spraying have been widely used in the production of porous metals. However, metal fiber sintering cannot precisely control the pore parameters [16–18], and traditional powder metallurgy and plasma spraying cannot guarantee the structural uniformity of porous implants [19, 20]. In the meanwhile, newly developed 3D printing technologies made independently controlling pore parameters possible [21]. The first additive manufacturing (AM) processed tantalum structure used laser engineered net shaping technique to create porous tantalum structures with different porosity and tested their in vitro biocompatibility with osteoblast cell lines and MMT assays. The results showed better cell survival, adherence, and extracellular matrix formation with tantalum scaffolds than titanium scaffolds. Considering the high cost of all tantalum implants, Balla et al. used laser engineering net shaping method to deposit tantalum coating on titanium and tested its biocompatibility by osteoblast cell line, which showed significantly better cell adherence and extracellular matrix formation on tantalum coating than titanium scaffolds, further proving the superior cell-material interaction of tantalum.Although 3D printing appears to be perfect for fine molding of tantalum scaffolds, the methods for designing and assessing the properties of 3D printed tantalum scaffolds are rudimentary. To provide reference for future clinical application of 3D printed tantalum scaffolds, here we modified the existing tantalum scaffold to apply to specific biological sites and tested their structural properties [22].
## 2. Materials and Methods
In the current study, the 3D Max software was used to conduct 3D modeling of the femoral head and acetabulum cup; 4 types of scaffolds with different pore diameter and porosity (Figure1(a)) were used to replace bone growth part on the implant. Selective laser melting (SLM) was used to mold four types of tantalum and titanium scaffolds with alternative pore diameters: 1000-700 μm (indicating that the inner diameter of the scaffold is 1000 μm, and the outer diameter is 700 μm, Figure 2), 700-1000 μm, 500-800 μm, and 800-500 μm, in contrast to single pore diameter design by previous authors due to molding limitations [23, 24]. The shape of each scaffold was a cylinder with the diameter of 6 mm and the height of 6.8 mm. The corresponding scanning electron microscope (SEM) images are shown in Figures 1(b) and 1(c), respectively.Figure 1
(a) 4 kinds of 3D modeling scaffold and corresponding biological site. (b) SEM images of 4 kinds of tantalum scaffold before compression. (c) SEM images of 4 kinds of titanium scaffold before compression.
(a)(b)(c)Figure 2
The general image and the cross section of the tantalum and titanium scaffolds.ZB-YSJ5000 compressive strength tester was used to carry out uniaxial-compression tests on above scaffolds. Compression resistance and fracture of tantalum scaffolds were compared with of titanium scaffolds. In the uniaxial-compression tests, the contact area between scaffold and pressure monitor was named as contact region, and the internal material of scaffold was named as noncontact region. Figures1(b) and 1(c) show that the scaffolds had no obvious initial cracks either on the surface contact region or in the internal noncontact region.In order to compare the compression deformation resistance of the above tantalum and titanium scaffolds with that of animal bone, similar biomechanical tests were carried out on five pig proximal femoral bone grafts with the same size as the tantalum and titanium scaffolds. The average test results were used to form the final stress-strain curve.
## 3. Results
The equivalent stress of four types of scaffolds was all significantly larger in tantalum scaffolds than titanium scaffolds (P<0.01, Table 1). The range of Young’s modulus of tantalum was 2.61±0.02 GPa-3.03±0.04 GPa, and the range of Young’s modulus of titanium was 4.66±0.04 GPa-4.93±0.04 GPa, which was significantly different between the two groups (P<0.01). The engineering stress-strain curve of titanium scaffold #2 (700-1000 μm) is presented in Figure 3. Under the compression speed of 0.05 mm/s, the whole deformation and fracture process was different between tantalum and titanium scaffolds. When the internal compressive resistance reached its highest limit (17.9%, 87.6 MPa), the connecting beams among the pores begin to fracture, starting internal collapse. The number of fractured connecting beams increased as compression continued, reducing the stress to minimum at 26.4%, 51.5.4 MPa. The internal material was compacted when the internal space reduced to 0 at 35.4% strain, and the stress restarted to increase until the compression test stopped.Table 1
Equivalent stress of four types of scaffolds.
DiameterTantalumTitaniumP1000-700μm403±1.51 MPa201±4.61<0.01700-1000μm411±1.43 MPa212±1.73<0.01500-800μm389±1.84 MPa214±3.81<0.01800-500μm404±1.69 MPa191±2.14<0.01Figure 3
Engineering stress-strain curve of scaffold titanium #2 (700-1000μm) under the compressive speed of 0.05 mm/s.Samples were extracted from the eight types of scaffolds at the time of complete internal fracture (Figure4(a)). There was significant difference between the tantalum and titanium stress/strain curves. Initial point of fracture started at 15% engineering strain in titanium scaffolds, while it was 25% with tantalum scaffolds, indicating higher resistance to deformation of tantalum than titanium, and that tantalum scaffolds can undergo a greater degree of uniform deformation before connecting beam starts fracture. Scanning electron microscope observation showed no obvious microcracks in the contact and noncontact region of all tantalum scaffolds, with width range of microcrack of 14-50 μm (Figure 4(b)). On the other hand, there were obvious microcracks in the contact and noncontact region of all titanium scaffolds, with microcrack width range of 70-210 μm (Figure 4(c)). This difference was consistent with the difference of the two series of stress/strain curves of tantalum and titanium scaffolds (Figure 4(a)).Figure 4
(a) Partial stress-strain curves of all tested scaffolds, which show the process of internal fracture starting to completion. (b) SEM images of 4 kinds of tantalum scaffolds after compression. (c) SEM images of 4 kinds of titanium scaffolds after compression.
(a)(b)(c)The compression deformation resistance of the above tantalum and titanium scaffolds was compared with that of pig femoral bone; results showed that pig bone scaffolds began compression deformation about 50% before the internal bone beams began to fail, which was much later than that of tantalum and titanium (Figure5(a)). And the SEM images in Figure 5(b) showed that the width of cracks in pig femoral bone scaffold was significantly smaller than 10 μm. When compared with titanium scaffolds, the deformation behavior and stress-strain parameters of tantalum scaffolds are closer to that of pig bone scaffolds (0.61±0.07 GPa-0.83±0.09 GPa).Figure 5
(a) Engineering stress-strain curves of the tantalum and titanium scaffolds before connecting beams start to fracture and the deformation curve of pig bone before failure. (b) SEM images of pig bone sample after compression.
(a)(b)
## 4. Discussion
Artificial biocompatible implants are needed in various orthopedic surgeries such as joint replacement surgeries, orthopedic reconstruction of the bone defects due to tumor, infection, and trauma as well as congenital deformities. Ideal implants in those occasions are those with fine biocompatibility, osteogenic induction capability, and bone like biomechanical properties.Titanium alloys are the most commonly used materials for orthopedic implants. Laser engineering technique was used to fabricate low-modulus, tailored porous titanium alloy structure. The titanium alloy with 23-32% porosity is similar to that of cortical bone, and a 16-week study on rats showed fine integration between the implant and bone tissue. It is reported that, by laser engineered net shaping technique, it is possible to construct complex 3-dimentional titanium structures and found that titanium structure with 35-42 vol.% porosity is similar to that of human cortical bone. In a previous study, titanium implants with porosity of 17-58% and pore size of 800μm were fabricated using laser engineered net shaping method. They showed excellent mechanical strength, strong cell adhesion, and more extracellular matrix when experimented with human osteoblast cells.However, due to bioinert surface, titanium alloys display poor biological response in vivo. This might be overcome with various surface modification techniques such as coatings with more biocompatible materials. Previous studies used rat and rabbit models to prove the possibility of improving titanium biocompatibility by 3D printed tantalum coatings and found that microporosity design and nanoscale surface modification significantly increased the cytocompatibility and osseointegration of the implant.Although titanium implants are widely used in various orthopedic, spinal, and dental procedures, there are reports that tantalum scaffolds are superior to titanium in terms of bone induction and osseointegration. By directly comparing additively manufactured porous titanium and tantalum implants for their osseointegration properties using rat distal femur model for five and 12 weeks, previous studies found that there are no significant differences between titanium and tantalum implant in terms of osteointegration 5 weeks after surgery. However, porous tantalum scaffolds showed higher osteoid formation at 12 weeks after surgery, indicating better osseo-inductive properties of tantalum than titanium. Lu et al. [25] used bone marrow mesenchymal stem cells from ovariectomized rats to study cellular activity on tantalum and titanium plates and found that tantalum can better promote cell adhesion, proliferation, and osteogenic differentiation than titanium plates. When used to bridge the femoral bone defect of ovariectomized rats, the amount of new bone formation on the surface of tantalum plate was significantly larger than that of titanium plate. Further studies showed that the genetic expression and protein secretion of osteocalcin, type I collagen, and the formation of calcium nodules were significantly higher on the surface of tantalum than that of titanium when cocultured with bone marrow mesenchymal stem cells. Based on the gene expression of integrin α5, β1, and extracellular signal regulated kinase (Erkl/2) on the surface of tantalum plates, it was speculated that tantalum may have higher osteogenic induction properties through integrin α5β1/Erkl/2 signaling pathway [26]. Shi et al. [27] also found that the osteogenic differentiation on the surface of tantalum plates was better than titanium, but they believed that tantalum-mediated osteogenic differentiation was achieved through Wnt/β-catenin and TGF-β/smad signaling pathways. In our previous studies, we have also found that 3D printed tantalum implants can provide excellent structural support for patients with large iliac tumors and long femoral bone defect due to postoperative infection [28, 29]. However, there are few studies comparing the biomechanical properties of 3D printed tantalum and titanium scaffolds with different diameters.In order to further evaluate the biomechanical properties of tantalum and titanium scaffolds to reconstruct bone defect, here we tested 3D printed tantalum and titanium scaffolds with different pore diameters. Results of our study showed that the equivalent stress of four types of scaffolds was all significantly larger in tantalum scaffolds than titanium scaffolds, while the range of Young’s modulus of tantalum was significantly lower than titanium scaffolds. In a separate series of studies, we found that the pore diameter of 1000-700μm is more suitable for tantalum scaffolds to induce osseointegration, while 700-1000 μm is more suitable for titanium (unpublished data). The engineering stress-strain curves showed that tantalum scaffolds can undergo a greater degree of uniform deformation before connecting beams start to fracture, which was later proved by scanning electron microscope tests. Further analysis on same size pig femoral bone scaffolds showed that the deformation behavior and stress-strain parameters of tantalum scaffolds are closer to that of pig bone scaffolds than titanium scaffolds. In in vitro studies, microcracks were formed because the compression strength exceeded the bearing strength of the scaffolds. The porous implants themselves are strong enough to be used as implants, and their strength is further increased with osseous integration 4-6 weeks after surgery.Other metals such as magnesium and zinc have great potential as bone substitutes. However, their application is limited due to unfavorable biomechanical properties. Yang et al. used laser additive manufacturing technique to use graphene oxide reinforcement in zinc scaffold, which simultaneously enhanced the strength and ductility of zinc scaffold. They contributed the enhanced strength to the grain refinement and orientation, efficient load shift, and the Orowan strengthening by the homogeneously distributed graphene oxide reinforcement [30]. Yang et al. also used sol-gel method to synthesize mesoporous bioglass and used laser additive manufacturing to infuse the mesoporous bioglass into Mg-based composite, which showed significantly increased osseointegration and enhanced corrosion resistance [31]. In our study, we directly compared the 3D printed tantalum and titanium scaffolds and found that tantalum had better biomechanical characteristics than the titanium scaffolds. Further mechanical tests can be carried out to compare the mechanical characteristics of tantalum as compared with other metals such as Mg and Zn except for titanium in the future studies.It is clear from the current study that tantalum scaffolds are superior to titanium scaffolds in stress-strain curves and more similar to animal bones. Further osseous integration experiments are still needed to further validate the potential of tantalum scaffolds as replacement for titanium scaffolds.
## 5. Conclusion
3D printed tantalum scaffolds are superior to titanium scaffolds in resistance to compression and deformation and have biomechanical properties closer to bone scaffolds.
---
*Source: 2899043-2021-09-28.xml* | 2899043-2021-09-28_2899043-2021-09-28.md | 17,534 | Highly Porous 3D Printed Tantalum Scaffolds Have Better Biomechanical and Microstructural Properties than Titanium Scaffolds | Huaquan Fan; Shu Deng; Wentao Tang; Aikeremujiang Muheremu; Xianzhe Wu; Peng He; Caihua Tan; Guohua Wang; Jianzhong Tang; Kaixuan Guo; Liu Yang; Fuyou Wang | BioMed Research International
(2021) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2021/2899043 | 2899043-2021-09-28.xml | ---
## Abstract
Objective. To test the biomechanical properties of 3D printed tantalum and titanium porous scaffolds. Methods. Four types of tantalum and titanium scaffolds with four alternative pore diameters, #1 (1000-700 μm), #2 (700-1000 μm), #3 (500-800 μm), and #4 (800-500 μm), were molded by selective laser melting technique, and the scaffolds were tested by scanning electronic microscope, uniaxial-compression tests, and Young’s modulus tests; they were compared with same size pig femoral bone scaffolds. Results. Under uniaxial-compression tests, equivalent stress of tantalum scaffold was 411±1.43 MPa, which was significantly larger than the titanium scaffolds (P<0.05). Young’s modulus of tantalum scaffold was 2.61±0.02 GPa, which was only half of that of titanium scaffold. The stress-strain curves of tantalum scaffolds were more similar to pig bone scaffolds than titanium scaffolds. Conclusion. 3D printed tantalum scaffolds with varying pore diameters are more similar to actual bone scaffolds compared with titanium scaffolds in biomechanical properties.
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## Body
## 1. Background
Due to excellent corrosion resistance, toughness, and bioactivity, tantalum has been used for a variety of medical implant since 1940 [1–5]. While titanium is still considered the gold standard for porous biomaterials with skeletal biocompatibility [6–8], tantalum has been increasingly used as bone-substitute material with great potential. Highly porous tantalum scaffold was proven to have good bone conduction and induction capabilities and was shown to integrate well with bone in both basic research and human trials, indicating great prospect in its clinical application [9–11]. However, due to challenges in the processing of tantalum, its application is still limited in musculoskeletal system.For tantalum scaffolds to have fine osteogenic properties and be easily integrated with the host bone to prevent stress shielding and implant loosening, it is essential to improve the porosity of tantalum scaffold structure to obtain bone like mechanical properties. Previous studies have reported that pore diameter and porosity of tantalum scaffold have significant influence on its biocompatibility and adequate pore diameter, and high porosity is beneficial to the ingrowth of bone, soft tissues, and blood vessels [12–15].Traditional additive manufacturing techniques such as metal fiber sintering, powder metallurgy, and plasma spraying have been widely used in the production of porous metals. However, metal fiber sintering cannot precisely control the pore parameters [16–18], and traditional powder metallurgy and plasma spraying cannot guarantee the structural uniformity of porous implants [19, 20]. In the meanwhile, newly developed 3D printing technologies made independently controlling pore parameters possible [21]. The first additive manufacturing (AM) processed tantalum structure used laser engineered net shaping technique to create porous tantalum structures with different porosity and tested their in vitro biocompatibility with osteoblast cell lines and MMT assays. The results showed better cell survival, adherence, and extracellular matrix formation with tantalum scaffolds than titanium scaffolds. Considering the high cost of all tantalum implants, Balla et al. used laser engineering net shaping method to deposit tantalum coating on titanium and tested its biocompatibility by osteoblast cell line, which showed significantly better cell adherence and extracellular matrix formation on tantalum coating than titanium scaffolds, further proving the superior cell-material interaction of tantalum.Although 3D printing appears to be perfect for fine molding of tantalum scaffolds, the methods for designing and assessing the properties of 3D printed tantalum scaffolds are rudimentary. To provide reference for future clinical application of 3D printed tantalum scaffolds, here we modified the existing tantalum scaffold to apply to specific biological sites and tested their structural properties [22].
## 2. Materials and Methods
In the current study, the 3D Max software was used to conduct 3D modeling of the femoral head and acetabulum cup; 4 types of scaffolds with different pore diameter and porosity (Figure1(a)) were used to replace bone growth part on the implant. Selective laser melting (SLM) was used to mold four types of tantalum and titanium scaffolds with alternative pore diameters: 1000-700 μm (indicating that the inner diameter of the scaffold is 1000 μm, and the outer diameter is 700 μm, Figure 2), 700-1000 μm, 500-800 μm, and 800-500 μm, in contrast to single pore diameter design by previous authors due to molding limitations [23, 24]. The shape of each scaffold was a cylinder with the diameter of 6 mm and the height of 6.8 mm. The corresponding scanning electron microscope (SEM) images are shown in Figures 1(b) and 1(c), respectively.Figure 1
(a) 4 kinds of 3D modeling scaffold and corresponding biological site. (b) SEM images of 4 kinds of tantalum scaffold before compression. (c) SEM images of 4 kinds of titanium scaffold before compression.
(a)(b)(c)Figure 2
The general image and the cross section of the tantalum and titanium scaffolds.ZB-YSJ5000 compressive strength tester was used to carry out uniaxial-compression tests on above scaffolds. Compression resistance and fracture of tantalum scaffolds were compared with of titanium scaffolds. In the uniaxial-compression tests, the contact area between scaffold and pressure monitor was named as contact region, and the internal material of scaffold was named as noncontact region. Figures1(b) and 1(c) show that the scaffolds had no obvious initial cracks either on the surface contact region or in the internal noncontact region.In order to compare the compression deformation resistance of the above tantalum and titanium scaffolds with that of animal bone, similar biomechanical tests were carried out on five pig proximal femoral bone grafts with the same size as the tantalum and titanium scaffolds. The average test results were used to form the final stress-strain curve.
## 3. Results
The equivalent stress of four types of scaffolds was all significantly larger in tantalum scaffolds than titanium scaffolds (P<0.01, Table 1). The range of Young’s modulus of tantalum was 2.61±0.02 GPa-3.03±0.04 GPa, and the range of Young’s modulus of titanium was 4.66±0.04 GPa-4.93±0.04 GPa, which was significantly different between the two groups (P<0.01). The engineering stress-strain curve of titanium scaffold #2 (700-1000 μm) is presented in Figure 3. Under the compression speed of 0.05 mm/s, the whole deformation and fracture process was different between tantalum and titanium scaffolds. When the internal compressive resistance reached its highest limit (17.9%, 87.6 MPa), the connecting beams among the pores begin to fracture, starting internal collapse. The number of fractured connecting beams increased as compression continued, reducing the stress to minimum at 26.4%, 51.5.4 MPa. The internal material was compacted when the internal space reduced to 0 at 35.4% strain, and the stress restarted to increase until the compression test stopped.Table 1
Equivalent stress of four types of scaffolds.
DiameterTantalumTitaniumP1000-700μm403±1.51 MPa201±4.61<0.01700-1000μm411±1.43 MPa212±1.73<0.01500-800μm389±1.84 MPa214±3.81<0.01800-500μm404±1.69 MPa191±2.14<0.01Figure 3
Engineering stress-strain curve of scaffold titanium #2 (700-1000μm) under the compressive speed of 0.05 mm/s.Samples were extracted from the eight types of scaffolds at the time of complete internal fracture (Figure4(a)). There was significant difference between the tantalum and titanium stress/strain curves. Initial point of fracture started at 15% engineering strain in titanium scaffolds, while it was 25% with tantalum scaffolds, indicating higher resistance to deformation of tantalum than titanium, and that tantalum scaffolds can undergo a greater degree of uniform deformation before connecting beam starts fracture. Scanning electron microscope observation showed no obvious microcracks in the contact and noncontact region of all tantalum scaffolds, with width range of microcrack of 14-50 μm (Figure 4(b)). On the other hand, there were obvious microcracks in the contact and noncontact region of all titanium scaffolds, with microcrack width range of 70-210 μm (Figure 4(c)). This difference was consistent with the difference of the two series of stress/strain curves of tantalum and titanium scaffolds (Figure 4(a)).Figure 4
(a) Partial stress-strain curves of all tested scaffolds, which show the process of internal fracture starting to completion. (b) SEM images of 4 kinds of tantalum scaffolds after compression. (c) SEM images of 4 kinds of titanium scaffolds after compression.
(a)(b)(c)The compression deformation resistance of the above tantalum and titanium scaffolds was compared with that of pig femoral bone; results showed that pig bone scaffolds began compression deformation about 50% before the internal bone beams began to fail, which was much later than that of tantalum and titanium (Figure5(a)). And the SEM images in Figure 5(b) showed that the width of cracks in pig femoral bone scaffold was significantly smaller than 10 μm. When compared with titanium scaffolds, the deformation behavior and stress-strain parameters of tantalum scaffolds are closer to that of pig bone scaffolds (0.61±0.07 GPa-0.83±0.09 GPa).Figure 5
(a) Engineering stress-strain curves of the tantalum and titanium scaffolds before connecting beams start to fracture and the deformation curve of pig bone before failure. (b) SEM images of pig bone sample after compression.
(a)(b)
## 4. Discussion
Artificial biocompatible implants are needed in various orthopedic surgeries such as joint replacement surgeries, orthopedic reconstruction of the bone defects due to tumor, infection, and trauma as well as congenital deformities. Ideal implants in those occasions are those with fine biocompatibility, osteogenic induction capability, and bone like biomechanical properties.Titanium alloys are the most commonly used materials for orthopedic implants. Laser engineering technique was used to fabricate low-modulus, tailored porous titanium alloy structure. The titanium alloy with 23-32% porosity is similar to that of cortical bone, and a 16-week study on rats showed fine integration between the implant and bone tissue. It is reported that, by laser engineered net shaping technique, it is possible to construct complex 3-dimentional titanium structures and found that titanium structure with 35-42 vol.% porosity is similar to that of human cortical bone. In a previous study, titanium implants with porosity of 17-58% and pore size of 800μm were fabricated using laser engineered net shaping method. They showed excellent mechanical strength, strong cell adhesion, and more extracellular matrix when experimented with human osteoblast cells.However, due to bioinert surface, titanium alloys display poor biological response in vivo. This might be overcome with various surface modification techniques such as coatings with more biocompatible materials. Previous studies used rat and rabbit models to prove the possibility of improving titanium biocompatibility by 3D printed tantalum coatings and found that microporosity design and nanoscale surface modification significantly increased the cytocompatibility and osseointegration of the implant.Although titanium implants are widely used in various orthopedic, spinal, and dental procedures, there are reports that tantalum scaffolds are superior to titanium in terms of bone induction and osseointegration. By directly comparing additively manufactured porous titanium and tantalum implants for their osseointegration properties using rat distal femur model for five and 12 weeks, previous studies found that there are no significant differences between titanium and tantalum implant in terms of osteointegration 5 weeks after surgery. However, porous tantalum scaffolds showed higher osteoid formation at 12 weeks after surgery, indicating better osseo-inductive properties of tantalum than titanium. Lu et al. [25] used bone marrow mesenchymal stem cells from ovariectomized rats to study cellular activity on tantalum and titanium plates and found that tantalum can better promote cell adhesion, proliferation, and osteogenic differentiation than titanium plates. When used to bridge the femoral bone defect of ovariectomized rats, the amount of new bone formation on the surface of tantalum plate was significantly larger than that of titanium plate. Further studies showed that the genetic expression and protein secretion of osteocalcin, type I collagen, and the formation of calcium nodules were significantly higher on the surface of tantalum than that of titanium when cocultured with bone marrow mesenchymal stem cells. Based on the gene expression of integrin α5, β1, and extracellular signal regulated kinase (Erkl/2) on the surface of tantalum plates, it was speculated that tantalum may have higher osteogenic induction properties through integrin α5β1/Erkl/2 signaling pathway [26]. Shi et al. [27] also found that the osteogenic differentiation on the surface of tantalum plates was better than titanium, but they believed that tantalum-mediated osteogenic differentiation was achieved through Wnt/β-catenin and TGF-β/smad signaling pathways. In our previous studies, we have also found that 3D printed tantalum implants can provide excellent structural support for patients with large iliac tumors and long femoral bone defect due to postoperative infection [28, 29]. However, there are few studies comparing the biomechanical properties of 3D printed tantalum and titanium scaffolds with different diameters.In order to further evaluate the biomechanical properties of tantalum and titanium scaffolds to reconstruct bone defect, here we tested 3D printed tantalum and titanium scaffolds with different pore diameters. Results of our study showed that the equivalent stress of four types of scaffolds was all significantly larger in tantalum scaffolds than titanium scaffolds, while the range of Young’s modulus of tantalum was significantly lower than titanium scaffolds. In a separate series of studies, we found that the pore diameter of 1000-700μm is more suitable for tantalum scaffolds to induce osseointegration, while 700-1000 μm is more suitable for titanium (unpublished data). The engineering stress-strain curves showed that tantalum scaffolds can undergo a greater degree of uniform deformation before connecting beams start to fracture, which was later proved by scanning electron microscope tests. Further analysis on same size pig femoral bone scaffolds showed that the deformation behavior and stress-strain parameters of tantalum scaffolds are closer to that of pig bone scaffolds than titanium scaffolds. In in vitro studies, microcracks were formed because the compression strength exceeded the bearing strength of the scaffolds. The porous implants themselves are strong enough to be used as implants, and their strength is further increased with osseous integration 4-6 weeks after surgery.Other metals such as magnesium and zinc have great potential as bone substitutes. However, their application is limited due to unfavorable biomechanical properties. Yang et al. used laser additive manufacturing technique to use graphene oxide reinforcement in zinc scaffold, which simultaneously enhanced the strength and ductility of zinc scaffold. They contributed the enhanced strength to the grain refinement and orientation, efficient load shift, and the Orowan strengthening by the homogeneously distributed graphene oxide reinforcement [30]. Yang et al. also used sol-gel method to synthesize mesoporous bioglass and used laser additive manufacturing to infuse the mesoporous bioglass into Mg-based composite, which showed significantly increased osseointegration and enhanced corrosion resistance [31]. In our study, we directly compared the 3D printed tantalum and titanium scaffolds and found that tantalum had better biomechanical characteristics than the titanium scaffolds. Further mechanical tests can be carried out to compare the mechanical characteristics of tantalum as compared with other metals such as Mg and Zn except for titanium in the future studies.It is clear from the current study that tantalum scaffolds are superior to titanium scaffolds in stress-strain curves and more similar to animal bones. Further osseous integration experiments are still needed to further validate the potential of tantalum scaffolds as replacement for titanium scaffolds.
## 5. Conclusion
3D printed tantalum scaffolds are superior to titanium scaffolds in resistance to compression and deformation and have biomechanical properties closer to bone scaffolds.
---
*Source: 2899043-2021-09-28.xml* | 2021 |
# Evaluating and Exploring the Effectiveness of Journalism and Communication Discipline Construction in the Context of Smart Era
**Authors:** Yang Li
**Journal:** Mathematical Problems in Engineering
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2899128
---
## Abstract
In today’s intelligent era, the talent training mode of traditional journalism and communication discipline cannot keep up with the pace of the times. Under the background of intelligent era, the cultivation of compound talents in journalism and communication discipline is not only in line with the direction of education reform in journalism and communication discipline, but also in line with the objective requirements of economic and social development. Based on this, this paper puts forward three suggestions: improve the discipline layout of “smart age + journalism and communication discipline” and strengthen professional construction; enrich the textbook resources in the era of wisdom and promote smart teaching.
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## Body
## 1. Introduction
Guided by the goal of educational modernization and building China into an educational power by 2035, the discipline of communication in China has updated the concept of liberal arts education in national universities and outlined a new picture of the construction of Johnson & Johnson discipline with Chinese characteristics, practicality, and interdisciplinary nature [1]. Johnson & Johnson discipline is a strategic measure to cultivate new liberal arts talents in China. “The core significance is to base on the new era, respond to the new needs of society, and promote the integration, modernization, sinicization, and internationalization of liberal arts [2].Intelligent education is an intelligent concept and educational method developed and perfected with the development of intelligent technology. This is an effective way to establish Johnson & Johnson discipline [3–5]. The discipline of Johnson & Johnson can make use of intelligent education to break the shackles of Johnson & Johnson education in teaching methods, educational resources, educational objectives, and other aspects so as to strengthen the discipline function and social function of the specialty [6].As the saying goes, “if you don’t keep justice, you won’t know the way to the future; if you don’t innovate, there will be no way out.” We must follow and inherit the humanistic tradition and the basic laws of liberal arts, such as following the basic laws of liberal arts education and personnel training, and inheriting China’s excellent traditional culture. Innovation lies in that it must improve itself in the contemporary era. Its main characteristics are the docking with the new information technology in the 21st century, the cross integration with similar majors and other disciplines, and the integration with the social life and students’ psychology in the new era. We must take this discipline authorization as the most basic starting point.
## 2. Related Work
Technology is the basic element of news communication, which determines the basic form and function of news communication. As a science that studies the phenomena and laws of news communication activities in human society, the development of J & C has always been branded with the first marks of technology, and its theory and discipline system have often undergone profound changes due to the evolution of media technology, such as the development of printing technology and radio and television technology, which not only supported the theoretical development of the Western school of media criticism and the school of media experience, but also directly contributed to the development of the school of media technology (the development of print and broadcast technologies not only supported the theoretical development of the Western media critical school and the media empirical school, but also directly contributed to the formation of the media technology school (media environment school). With the emergence of new technologies, J&C are inevitably ushering in a kind of disruptive revolution in the face of the richness and complexity of new communication activities and phenomena, and to a certain extent, its disciplinary system and attributes will be redefined due to technology [7–9].As China enters a new era, people have higher and higher requirements for news. The greatest expectation of the public for news is to enrich people’s spiritual world and tell a good Chinese story. News practice reflects the characteristics of the times of “writing news on the Earth and in the hearts of the people.” This authorization is also reflected in the new practice part of the course teaching, which should be strengthened by seizing the opportunity of in-depth media integration [10]. The design and teaching of Johnson & Johnson courses should not only focus on the classroom but also break the physical space-time constraints in the classroom, constantly broaden the vision of teaching and learning, integrate (academic circles), industry and society, practical courses, professional practice, base construction and media technology, media ecology, media production and even daily life, and not only develop and update the courses on the basis of joint discussion and consultation. We should also jointly undertake the design and teaching of practical courses. They shall not only formulate and update the training plan on the basis of joint discussion and consultation but also jointly undertake the design and teaching of practical courses [11]. In particular, China Johnson & Johnson urgently needs to promote the training of all media talents by strengthening all media practical teaching activities, and improve students’ basic professional abilities, such as all media reporting ability. Through diversified practical training and media experience, they have the ability of comprehensive media expression and cross media cooperation.Finally, practice empowerment is also reflected in the international perspective of strengthening curriculum practice. Under the historical background of building a community with a shared future for mankind, the education and teaching of this discipline should be combined with the global vision and China’s position [12], clearly explain China’s position and philosophy, and cultivate outstanding news reserve talents who can speak Chinese logic and are good at spreading Chinese views.
## 3. Methods
Based on the above compilation of policies, issues, and trends of J&C discipline talent training, the development trend of J&C discipline environment in the age of intelligence is analyzed, and the factors influencing the competence of J&C discipline are compiled and analyzed (see Figure1).Figure 1
Factors influencing competence in J&C disciplines.In the era of intelligence, which is deeply rooted in the hearts of the people, the educational concept, model, and governance will be reshaped. The discipline construction of Johnson & Johnson under the background of the wisdom era is a reform project for the reconstruction of the discipline education of Johnson & Johnson. “Smart age + Johnson & Johnson discipline” is based on a new educational concept (moderate education, not optimal education), with the goal of people’s all-round development (not just employment oriented), rethinking, and designing new talent training mode, new curriculum system, new teaching mode, and new teaching platform to cultivate innovative Johnson & Johnson discipline talents. Therefore, Johnson & Johnson discipline is comprehensively and fundamentally reconstructing a new set of Johnson & Johnson discipline education concepts, systems, mechanisms, methods, evaluation, etc., and a new reform of Johnson & Johnson discipline education governance has taken place [13–16].The curriculum training objectives should be combined with students’ learning needs to jointly serve the creation of an efficient foreign language learning ecology. As shown in Figure2, the curriculum of Johnson & Johnson discipline is based on the needs of language use and defines the dual goals of “promoting learning” and “educating people” of Johnson & Johnson discipline, as well as the knowledge, ability, and political goals of foreign language courses.Figure 2
Analysis of curriculum needs and teaching objectives of J&C disciplines.On the basis of fully investigating the international evaluation paradigm and combining with the actual situation of the University, the international evaluation work innovates the evaluation concepts and methods, pays more attention to the organic unity of discipline construction objective evaluation, process evaluation, and result evaluation, pays more attention to the connection and integration of problem orientation and result sharing, and pays more attention to the design of the closed-loop system and long-term mechanism of “evaluation optimization and re evaluation.” The work plan of the discipline international evaluation model is formed by designing a closed-loop system and a long-term mechanism. One of the main links is shown in Figure2.Local governments and education departments will take the lead in formulating supporting policies and measures to guide schools, vocational training institutions, enterprises, and other institutions to jointly build an intelligent education ecosystem of industrial Johnson and Johnson disciplines in the smart era, realize the integration of industry and education and the linkage between government and enterprises, and build a diversified and collaborative intelligent education ecosystem. As shown in Table1, “teacher” has the highest word frequency of 88, followed by “talent training” and “scientific research,” with word frequencies of 81 and 71, respectively. “Planning initiative,” “discipline reputation and cultural construction,” and “international cooperation” have more than 20 keywords [17].Table 1
High-frequency key words in the expert evaluation report.
KeywordsWord frequencyKeywordsWord frequencyFaculty88Interdisciplinary research8Talent cultivation81Young faculty8Scientific research71Developing a plan7Planning initiatives45Building initiatives7Academic reputation and culture building31International exchange opportunities7International cooperation26International impact7Cultivation system19Social service7Research quality11Adjunct faculty6Academic backbone10International cooperation in scientific research6Research direction8Culture building5Student quality9International evaluation5Comprehensive ability7International cooperation in teaching5In order to cultivate the compound ability required by the “intelligent era + Johnson & Johnson era,” it is necessary to cultivate students’ compound ability through school enterprise cooperation and engineering combination so that students’ knowledge application ability, engineering practice ability, management practice ability, professional development ability, and innovation and entrepreneurship ability can be exercised in the real work practice and business environment [12, 18–20]; Johnson has certain compound knowledge. Professional development ability and innovation and entrepreneurship ability are exercised in the actual work practice and business environment. The integration of talent training and innovation research bases are strengthened, the multidisciplinary collaborative education mechanism is improved in the field of the intelligent age, and multilevel talents are cultivated in the field of the intelligent age in various forms.
## 4. Experiments
In the discipline evaluation, there are 278 first-level disciplines in 17 higher education institutions, accounting for 4% of all the disciplines evaluated. According to the evaluation results, there are 159 disciplines above category C. There are 4 A subjects, accounting for 0.56% of 710 A subjects, 53 B subjects, accounting for 2.42% of 2,187 B subjects, and 102 C subjects, accounting for 4.60% of 2,215 C subjects, as shown in Figures3 and 4.Figure 3
Percentage of disciplines above category C in the fourth round of national discipline evaluation.Figure 4
The fourth round of national discipline evaluation of higher education institutions above category C.As the saying goes, “classroom is the main channel and position of education and teaching,” the realization of subject empowerment takes classroom teaching as the basic path. Classroom teaching is the basic organizational form of human education and teaching since modern times. With the popularization of higher education in China, classroom teaching will still be the leading form of education and teaching in our country in the future [12].Creating a classroom of “love, righteousness, warmth, and love” needs systematic support. Educators should naturally take classroom empowerment as a breakthrough to leverage the chain effect of discipline construction and further promote professional optimization, including course objective design, course system setting, syllabus approval, textbook review and selection, teaching plan and courseware production, practice base selection and collaborative education, degree setting and certificate issuance, teaching and management personnel evaluation, and even international exchange and transnational training [14]. It runs through the course arrangement, classroom teaching, teaching seminars, experimental training, assignments and papers, examination and assessment, salary incentive and management system and mechanism, and is finally unified in the discipline construction. Finally, it is unified in the complete discipline construction system. The speciality construction layout is closely related to the cities where the 15 specialties above class C are located, as shown in Figure 5.Figure 5
Number and percentage of disciplines with category C.The degree of concentration of experts’ opinions is measured by the mean, standard deviation, and selection rate of each indicator’s importance score. The whole process of classroom teaching and all its effects and internal and external links will be reflected. This process is also the process of promoting discipline construction by taking discipline empowerment as the logical starting point, and the empowerment of the construction of J&C disciplines in the new era in China can take classroom teaching as the main grasp and breakthrough point, as shown in Figure6.Figure 6
Comparison results of evaluation schemes.As shown in Table2, the overall importance is 0.301, 0.362, 0.275, and 0.253, respectively, and the Kendall coordination coefficient of the operability of the three-level indicators is 0.378. Kendall coordination coefficient and overall importance are 0.360, 0.298, 0.456, and 0.335, respectively. Kendall coordination coefficient for operability of Kendall coordination coefficient of level III indicators is 0.380. The significance test is statistically significant (<0.05), as shown in Table 3.Table 2
Distribution of indicators judged by the degree of concentration of indicators.
Concentration judgment indexRound 1Round 2Minimum valueMaximum valuex¯±sMinimum valueMaximum valuex¯±sMean3.8355.0004.658 ± 0.3154.1855.0004.758 ± 0.162Standard deviation01.2880.598 ± 0.1990.00001.1350.526 ± 0.229Entry selection rate (%)55.568100.00090.289 ± 12.32570.59810.00095.012 ± 6.315Table 3
Kendall’sW harmony coefficients and significance tests for 2 rounds of expert opinions.
ProjectsImportance of level 2, level 2 and level 3 indicatorsReasonableness assignment of the scoring method of the three levels of indicatorsNo. of entriesKendall’sWPNo. of entriesKendall’sWPRound 1620.255<0.001450.388<0.001Round 2650.365<0.001460.386<0.001The cut-off values for the mean, perfect score, and coefficient of variation of each item in the two rounds of consultation were calculated according to the “cut-off value method,” as shown in Table4.Table 4
Threshold values for screening indicators.
ProjectsMeanStandard deviationBoundary value121212K68.5576.1517.5510.1850.8765.89M4.654.780.330.174.324.55CV0.110.130.080.040.230.19Note. K refers to the perfect score rate (%) of each index, M refers to the mean of each index, both of which are high-performing indicators; CV refers to the coefficient of variation, which is a low-performing indicator.
## 5. Conclusion
Talent cultivation of J&C disciplines based on the intelligent era is not only a trend of educational reform of J&C disciplines but also an inevitable requirement of economic and social development. Through this mode of talent cultivation, students can improve comprehensive quality while learning theoretical knowledge systematically and closely integrate with corresponding industries, which can also better support the cultivation of cross-border talents in universities. In general, in the process of transformation, institutions should update new educational concepts, find new professional positioning, grasp new teaching requirements, find new teaching methods, and cultivate new media talents to ensure that J&C education can respond to the strategic deployment of the new liberal arts construction and help build a strong education country in 2035.
---
*Source: 2899128-2022-07-21.xml* | 2899128-2022-07-21_2899128-2022-07-21.md | 17,419 | Evaluating and Exploring the Effectiveness of Journalism and Communication Discipline Construction in the Context of Smart Era | Yang Li | Mathematical Problems in Engineering
(2022) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2899128 | 2899128-2022-07-21.xml | ---
## Abstract
In today’s intelligent era, the talent training mode of traditional journalism and communication discipline cannot keep up with the pace of the times. Under the background of intelligent era, the cultivation of compound talents in journalism and communication discipline is not only in line with the direction of education reform in journalism and communication discipline, but also in line with the objective requirements of economic and social development. Based on this, this paper puts forward three suggestions: improve the discipline layout of “smart age + journalism and communication discipline” and strengthen professional construction; enrich the textbook resources in the era of wisdom and promote smart teaching.
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## Body
## 1. Introduction
Guided by the goal of educational modernization and building China into an educational power by 2035, the discipline of communication in China has updated the concept of liberal arts education in national universities and outlined a new picture of the construction of Johnson & Johnson discipline with Chinese characteristics, practicality, and interdisciplinary nature [1]. Johnson & Johnson discipline is a strategic measure to cultivate new liberal arts talents in China. “The core significance is to base on the new era, respond to the new needs of society, and promote the integration, modernization, sinicization, and internationalization of liberal arts [2].Intelligent education is an intelligent concept and educational method developed and perfected with the development of intelligent technology. This is an effective way to establish Johnson & Johnson discipline [3–5]. The discipline of Johnson & Johnson can make use of intelligent education to break the shackles of Johnson & Johnson education in teaching methods, educational resources, educational objectives, and other aspects so as to strengthen the discipline function and social function of the specialty [6].As the saying goes, “if you don’t keep justice, you won’t know the way to the future; if you don’t innovate, there will be no way out.” We must follow and inherit the humanistic tradition and the basic laws of liberal arts, such as following the basic laws of liberal arts education and personnel training, and inheriting China’s excellent traditional culture. Innovation lies in that it must improve itself in the contemporary era. Its main characteristics are the docking with the new information technology in the 21st century, the cross integration with similar majors and other disciplines, and the integration with the social life and students’ psychology in the new era. We must take this discipline authorization as the most basic starting point.
## 2. Related Work
Technology is the basic element of news communication, which determines the basic form and function of news communication. As a science that studies the phenomena and laws of news communication activities in human society, the development of J & C has always been branded with the first marks of technology, and its theory and discipline system have often undergone profound changes due to the evolution of media technology, such as the development of printing technology and radio and television technology, which not only supported the theoretical development of the Western school of media criticism and the school of media experience, but also directly contributed to the development of the school of media technology (the development of print and broadcast technologies not only supported the theoretical development of the Western media critical school and the media empirical school, but also directly contributed to the formation of the media technology school (media environment school). With the emergence of new technologies, J&C are inevitably ushering in a kind of disruptive revolution in the face of the richness and complexity of new communication activities and phenomena, and to a certain extent, its disciplinary system and attributes will be redefined due to technology [7–9].As China enters a new era, people have higher and higher requirements for news. The greatest expectation of the public for news is to enrich people’s spiritual world and tell a good Chinese story. News practice reflects the characteristics of the times of “writing news on the Earth and in the hearts of the people.” This authorization is also reflected in the new practice part of the course teaching, which should be strengthened by seizing the opportunity of in-depth media integration [10]. The design and teaching of Johnson & Johnson courses should not only focus on the classroom but also break the physical space-time constraints in the classroom, constantly broaden the vision of teaching and learning, integrate (academic circles), industry and society, practical courses, professional practice, base construction and media technology, media ecology, media production and even daily life, and not only develop and update the courses on the basis of joint discussion and consultation. We should also jointly undertake the design and teaching of practical courses. They shall not only formulate and update the training plan on the basis of joint discussion and consultation but also jointly undertake the design and teaching of practical courses [11]. In particular, China Johnson & Johnson urgently needs to promote the training of all media talents by strengthening all media practical teaching activities, and improve students’ basic professional abilities, such as all media reporting ability. Through diversified practical training and media experience, they have the ability of comprehensive media expression and cross media cooperation.Finally, practice empowerment is also reflected in the international perspective of strengthening curriculum practice. Under the historical background of building a community with a shared future for mankind, the education and teaching of this discipline should be combined with the global vision and China’s position [12], clearly explain China’s position and philosophy, and cultivate outstanding news reserve talents who can speak Chinese logic and are good at spreading Chinese views.
## 3. Methods
Based on the above compilation of policies, issues, and trends of J&C discipline talent training, the development trend of J&C discipline environment in the age of intelligence is analyzed, and the factors influencing the competence of J&C discipline are compiled and analyzed (see Figure1).Figure 1
Factors influencing competence in J&C disciplines.In the era of intelligence, which is deeply rooted in the hearts of the people, the educational concept, model, and governance will be reshaped. The discipline construction of Johnson & Johnson under the background of the wisdom era is a reform project for the reconstruction of the discipline education of Johnson & Johnson. “Smart age + Johnson & Johnson discipline” is based on a new educational concept (moderate education, not optimal education), with the goal of people’s all-round development (not just employment oriented), rethinking, and designing new talent training mode, new curriculum system, new teaching mode, and new teaching platform to cultivate innovative Johnson & Johnson discipline talents. Therefore, Johnson & Johnson discipline is comprehensively and fundamentally reconstructing a new set of Johnson & Johnson discipline education concepts, systems, mechanisms, methods, evaluation, etc., and a new reform of Johnson & Johnson discipline education governance has taken place [13–16].The curriculum training objectives should be combined with students’ learning needs to jointly serve the creation of an efficient foreign language learning ecology. As shown in Figure2, the curriculum of Johnson & Johnson discipline is based on the needs of language use and defines the dual goals of “promoting learning” and “educating people” of Johnson & Johnson discipline, as well as the knowledge, ability, and political goals of foreign language courses.Figure 2
Analysis of curriculum needs and teaching objectives of J&C disciplines.On the basis of fully investigating the international evaluation paradigm and combining with the actual situation of the University, the international evaluation work innovates the evaluation concepts and methods, pays more attention to the organic unity of discipline construction objective evaluation, process evaluation, and result evaluation, pays more attention to the connection and integration of problem orientation and result sharing, and pays more attention to the design of the closed-loop system and long-term mechanism of “evaluation optimization and re evaluation.” The work plan of the discipline international evaluation model is formed by designing a closed-loop system and a long-term mechanism. One of the main links is shown in Figure2.Local governments and education departments will take the lead in formulating supporting policies and measures to guide schools, vocational training institutions, enterprises, and other institutions to jointly build an intelligent education ecosystem of industrial Johnson and Johnson disciplines in the smart era, realize the integration of industry and education and the linkage between government and enterprises, and build a diversified and collaborative intelligent education ecosystem. As shown in Table1, “teacher” has the highest word frequency of 88, followed by “talent training” and “scientific research,” with word frequencies of 81 and 71, respectively. “Planning initiative,” “discipline reputation and cultural construction,” and “international cooperation” have more than 20 keywords [17].Table 1
High-frequency key words in the expert evaluation report.
KeywordsWord frequencyKeywordsWord frequencyFaculty88Interdisciplinary research8Talent cultivation81Young faculty8Scientific research71Developing a plan7Planning initiatives45Building initiatives7Academic reputation and culture building31International exchange opportunities7International cooperation26International impact7Cultivation system19Social service7Research quality11Adjunct faculty6Academic backbone10International cooperation in scientific research6Research direction8Culture building5Student quality9International evaluation5Comprehensive ability7International cooperation in teaching5In order to cultivate the compound ability required by the “intelligent era + Johnson & Johnson era,” it is necessary to cultivate students’ compound ability through school enterprise cooperation and engineering combination so that students’ knowledge application ability, engineering practice ability, management practice ability, professional development ability, and innovation and entrepreneurship ability can be exercised in the real work practice and business environment [12, 18–20]; Johnson has certain compound knowledge. Professional development ability and innovation and entrepreneurship ability are exercised in the actual work practice and business environment. The integration of talent training and innovation research bases are strengthened, the multidisciplinary collaborative education mechanism is improved in the field of the intelligent age, and multilevel talents are cultivated in the field of the intelligent age in various forms.
## 4. Experiments
In the discipline evaluation, there are 278 first-level disciplines in 17 higher education institutions, accounting for 4% of all the disciplines evaluated. According to the evaluation results, there are 159 disciplines above category C. There are 4 A subjects, accounting for 0.56% of 710 A subjects, 53 B subjects, accounting for 2.42% of 2,187 B subjects, and 102 C subjects, accounting for 4.60% of 2,215 C subjects, as shown in Figures3 and 4.Figure 3
Percentage of disciplines above category C in the fourth round of national discipline evaluation.Figure 4
The fourth round of national discipline evaluation of higher education institutions above category C.As the saying goes, “classroom is the main channel and position of education and teaching,” the realization of subject empowerment takes classroom teaching as the basic path. Classroom teaching is the basic organizational form of human education and teaching since modern times. With the popularization of higher education in China, classroom teaching will still be the leading form of education and teaching in our country in the future [12].Creating a classroom of “love, righteousness, warmth, and love” needs systematic support. Educators should naturally take classroom empowerment as a breakthrough to leverage the chain effect of discipline construction and further promote professional optimization, including course objective design, course system setting, syllabus approval, textbook review and selection, teaching plan and courseware production, practice base selection and collaborative education, degree setting and certificate issuance, teaching and management personnel evaluation, and even international exchange and transnational training [14]. It runs through the course arrangement, classroom teaching, teaching seminars, experimental training, assignments and papers, examination and assessment, salary incentive and management system and mechanism, and is finally unified in the discipline construction. Finally, it is unified in the complete discipline construction system. The speciality construction layout is closely related to the cities where the 15 specialties above class C are located, as shown in Figure 5.Figure 5
Number and percentage of disciplines with category C.The degree of concentration of experts’ opinions is measured by the mean, standard deviation, and selection rate of each indicator’s importance score. The whole process of classroom teaching and all its effects and internal and external links will be reflected. This process is also the process of promoting discipline construction by taking discipline empowerment as the logical starting point, and the empowerment of the construction of J&C disciplines in the new era in China can take classroom teaching as the main grasp and breakthrough point, as shown in Figure6.Figure 6
Comparison results of evaluation schemes.As shown in Table2, the overall importance is 0.301, 0.362, 0.275, and 0.253, respectively, and the Kendall coordination coefficient of the operability of the three-level indicators is 0.378. Kendall coordination coefficient and overall importance are 0.360, 0.298, 0.456, and 0.335, respectively. Kendall coordination coefficient for operability of Kendall coordination coefficient of level III indicators is 0.380. The significance test is statistically significant (<0.05), as shown in Table 3.Table 2
Distribution of indicators judged by the degree of concentration of indicators.
Concentration judgment indexRound 1Round 2Minimum valueMaximum valuex¯±sMinimum valueMaximum valuex¯±sMean3.8355.0004.658 ± 0.3154.1855.0004.758 ± 0.162Standard deviation01.2880.598 ± 0.1990.00001.1350.526 ± 0.229Entry selection rate (%)55.568100.00090.289 ± 12.32570.59810.00095.012 ± 6.315Table 3
Kendall’sW harmony coefficients and significance tests for 2 rounds of expert opinions.
ProjectsImportance of level 2, level 2 and level 3 indicatorsReasonableness assignment of the scoring method of the three levels of indicatorsNo. of entriesKendall’sWPNo. of entriesKendall’sWPRound 1620.255<0.001450.388<0.001Round 2650.365<0.001460.386<0.001The cut-off values for the mean, perfect score, and coefficient of variation of each item in the two rounds of consultation were calculated according to the “cut-off value method,” as shown in Table4.Table 4
Threshold values for screening indicators.
ProjectsMeanStandard deviationBoundary value121212K68.5576.1517.5510.1850.8765.89M4.654.780.330.174.324.55CV0.110.130.080.040.230.19Note. K refers to the perfect score rate (%) of each index, M refers to the mean of each index, both of which are high-performing indicators; CV refers to the coefficient of variation, which is a low-performing indicator.
## 5. Conclusion
Talent cultivation of J&C disciplines based on the intelligent era is not only a trend of educational reform of J&C disciplines but also an inevitable requirement of economic and social development. Through this mode of talent cultivation, students can improve comprehensive quality while learning theoretical knowledge systematically and closely integrate with corresponding industries, which can also better support the cultivation of cross-border talents in universities. In general, in the process of transformation, institutions should update new educational concepts, find new professional positioning, grasp new teaching requirements, find new teaching methods, and cultivate new media talents to ensure that J&C education can respond to the strategic deployment of the new liberal arts construction and help build a strong education country in 2035.
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*Source: 2899128-2022-07-21.xml* | 2022 |
# TIRAP, TRAM, and Toll-Like Receptors: The Untold Story
**Authors:** Valérie Lannoy; Anthony Côté-Biron; Claude Asselin; Nathalie Rivard
**Journal:** Mediators of Inflammation
(2023)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2023/2899271
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## Abstract
Toll-like receptors (TLRs) are the most studied receptors among the pattern recognition receptors (PRRs). They act as microbial sensors, playing major roles in the regulation of the innate immune system. TLRs mediate their cellular functions through the activation of MyD88-dependent or MyD88-independent signaling pathways. Myd88, or myeloid differentiation primary response 88, is a cytosolic adaptor protein essential for the induction of proinflammatory cytokines by all TLRs except TLR3. While the crucial role of Myd88 is well described, the contribution of other adaptors in mediating TLR signaling and function has been underestimated. In this review, we highlight important results demonstrating that TIRAP and TRAM adaptors are also required for full signaling activity and responses induced by most TLRs.
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## Body
## 1. Introduction
The history of Toll-like receptors (TLRs) over the last 30 years begins with the discovery of theToll gene responsible for Drosophila dorsoventral patterning during development. This was followed by the discovery, in 1996, that Drosophila Toll is involved in antifungal responses [1]. Since then, TLRs have been identified in invertebrates and vertebrates, including mammals, and their role in innate immunity has been extensively studied. The first mammalian homolog of Drosophila Toll was identified in 1997 as hToll, now termed TLR4 [2]. Today, the TLR family includes ten members in human (TLR1-TLR10) and twelve in mouse (TLR1-TLR9 and TLR11-TLR13) [3].TLRs belong to the innate immunity receptor superfamily pattern recognition receptors (PRRs) [4]. TLRs consist of a cytoplasmic Toll-interleukin-1 receptor (TIR) domain conserved between TLR and the interleukin-1 receptor (IL-1R) families, as well as extracellular leucine-rich repeats (LRRs) [5]. Ubiquitously expressed [6], TLRs detect specific microbe-, pathogen-, and damage-associated molecular patterns, respectively, named MAMPs, PAMPs, and DAMPs, through LRR motif binding [7]. TLR-dependent recognition of microbial components triggers innate immune activation by regulating proinflammatory gene expression, among others. Individual TLRs differentially distributed within the cell interact with specific microbial-derived ligands. For example, TLR1, TLR2, TLR4, TLR5 and TLR6 are expressed on the cell surface and recognize conserved motifs on extracellular microorganisms like bacteria, fungi or protozoa [8]. In contrast, TLR3, TLR7, TLR8, and TLR9 are mostly expressed in the endo-lysosomal compartments [9–11]. During viral infection, receptor-mediated virus entry is usually directed to the cytoplasm, but occasionally, the virus enters the endosomal compartment. This may result in viral particle degradation, causing endosomal TLR ligand exposure to double- and single-stranded ribonucleic acids (dsRNAs and ssRNAs), which are TLR3 and TLR7/8 ligands, respectively [12].Microbial motif recognition promotes TLR dimerization. TLR2 forms a heterophilic dimer with TLR1 or TLR6, while TLRs may form homodimers in other cases [13]. TLR dimerization activates signaling pathways that originate from the conserved intracellular TIR domain. Downstream of TIR, the TIR domain-containing adaptor myeloid differentiation primary response 88 (MyD88), is essential for the induction of proinflammatory cytokines, such as tumor necrosis factor-α (TNF-α) and interleukin-12 (IL-12) by all TLRs, except TLR3 [14]. Notably, TLR signaling operates through MyD88-dependent or MyD88-independent pathways. While a major role for Myd88 in mediating TLR signaling and function has been well described [15], the contribution of other signaling adaptors has been underestimated (Figure 1).Figure 1
TLR4 and MyD88 hegemony in TLR research. The number of publications regarding each TLR and TLR-related adaptor referenced in PubMed® was calculated on 27th October 2022. 28,034 publications regarding TLR4 were found; 13,431 on TLR2; 6,237 on TLR9; 5,516 on TLR3; 4,426 on TLR7; 2,011 on TLR5; 1,435 on TLR8; 10,148 on MyD88; 2,037 on TRIF; 601 on TIRAP; and 118 on TRAM.In this review, we highlight important results suggesting that TIRAP and TRAM adaptors are also required for full signaling activity and responses induced by most TLRs.
## 2. TLR Adaptors: An Overview
### 2.1. MyD88
MyD88, the universal adaptor protein for all TLRs except TLR3, triggers the activation of the proinflammatory nuclear factor-κB (NF-κB) pathway. Inflammatory cytokines are not induced in MyD88-deficient mice in response to stimulation by all TLRs but TLR3 [16]. MyD88 contains a N-terminal death domain (DD) and a C-terminal TIR domain [17], which associates with the TLR intracellular TIR domain after ligand stimulation. MyD88 recruits IL-1 receptor-associated kinase 4 (IRAK4) through DD-DD interactions and facilitates IRAK4-mediated phosphorylation of IRAK1 [18] for TNF receptor-associated factor 6 (TRAF6) engagement. Both IRAK1 and TRAF6 are polyubiquitinated in response to TLR agonists, then activating mitogen-activated protein kinases (MAPK) and NF-κB signaling pathways [19].
### 2.2. TIR Domain-Containing Adaptor Protein (TIRAP)
The search for Myd88 structurally related proteins identified TIRAP [23]. Similar to MyD88-deficient macrophages, Tirap-deficient macrophages are impaired for cytokine production, following TLR2 and TLR4 stimulation [24]. The activation of MyD88-dependent pathways requires the TIRAP adaptor to bridge MyD88 to TLR4 [25]. While TIRAP bears a C-terminal TIR domain for TLR interaction (Figure 2), TIRAP lacks a motif to associate with downstream signaling effectors, as opposed to MyD88 which possesses a DD domain [26]. Importantly, TIRAP carries a N-terminal phosphatidylinositol-4,5 bisphosphate (PIP2) binding motif enabling its recruitment to the plasma membrane [27]. Indeed, TLR4 initially recruits TIRAP at the plasma membrane, then MyD88, triggering NF-κB and MAPK pathways. Subsequently, TLR4 endocytosis and depletion of PIP2 from the plasma membrane release TLR4 from the TIRAP-MyD88 complex [28, 29]. This allows TLR4 to associate with TRIF-related adaptor molecule (TRAM) and then TIR-domain-containing adaptor-inducing interferon-β (TRIF) (Figure 3) for endosomal signaling.Figure 2
Structural view of human TIRAP and TRAM adaptor proteins. TIRAP contains a N-terminal PIP2-binding motif and a PEST domain, allowing polyubiquitination for rapid proteasomal degradation through suppressor of cytokine signaling 1 (SOCS1) binding [20]. TIRAP contains a C-terminal TIR domain. Its TRAF-6 binding motif permits direct association with TRAF6 for activation [21]. TRAM contains a N-terminal bipartite sorting signal that comprises its myristylation glycine site and controls its trafficking between the plasma membrane and the endosomes [22]. Similar to TIRAP, TRAM contains a C-terminal TIR domain.Figure 3
Schematic representation of the adaptors that bind the TIR domain of TLRs. TIRAP is preferentially localized at the cytoplasmic membrane through a PIP2-binding domain and recruits MyD88. Myristoylated TRAM localizes at the endosomes and triggers IFN I production via TRIF. Abbreviations: MAPKs: mitogen-activated protein kinases; MyD88: myeloid differentiation primary response 88; NF-κB: nuclear factor-κB; PIP2: phosphatidylinositol bisphosphate; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein; TLR: Toll-like receptor; TRAM: TRIF-related adaptor molecule; TRIF: TIR domain-containing adaptor-inducing interferon-β.
### 2.3. TRAM and TRIF: The Endosome Specific Adaptor Molecules
Metadatabase searches led to the discovery of TRAM (Figure2) [30]. Similar to the TIRAP and MyD88 pair, TRAM is required for TRIF adaptor engagement [22]. In contrast to TIRAP, TRAM is myristoylated at its N-terminus [31] (Figure 3), allowing anchoring to the endosomal membrane. Mutations abolishing TRAM myristoylation restrain TRAM cytoplasmic localization, thereby inhibiting TRIF-generated signal transduction by TLR4 [31]. In addition, cell treatment with dynasore, a dynamin 2 guanosine triphosphate (GTPase) pharmacological inhibitor, demonstrated that TLR4 internalization mediates TRAM/TRIF signaling [22, 32].Notably, TRIF is involved in antiviral protection by promoting the secretion of antiviral-specialized cytokines, namely, type I Interferons (IFN I : IFN-α and IFN-β) [33]. TRIF is recruited downstream of endosomal TLRs recognizing nucleic acids. This specific endosomal location, along with nucleic acid specific binding, protects from host DNA or mRNA detection-mediated autoimmunity. Indeed, lipofected host DNA stimulates TLR9 [34]. Viral carbohydrate and lipid structures are very similar to those observed in host cells and therefore do not represent suitable PAMPs. Instead, the immune system has evolved to express PRRs—TLRs included—that recognize viral nucleic acids [35]. For instance, TLR3 recognizes double-stranded RNA (dsRNA), and TLR9 binds unmethylated cytosine-phosphate-guanine (CpG) dinucleotides [36, 37]. Of note, Trif-deficient mice show impaired IFN-β expression in response to TLR3 and TLR4 ligands [38]. Thus, even if TLR4 detects bacterial MAMPs at the cell membrane, TLR4 induces antiviral pathways when localized within endosomes [28]. In 2014, more than ten years after this discovery, a similar function has been detailed regarding TLR2 [39].
## 2.1. MyD88
MyD88, the universal adaptor protein for all TLRs except TLR3, triggers the activation of the proinflammatory nuclear factor-κB (NF-κB) pathway. Inflammatory cytokines are not induced in MyD88-deficient mice in response to stimulation by all TLRs but TLR3 [16]. MyD88 contains a N-terminal death domain (DD) and a C-terminal TIR domain [17], which associates with the TLR intracellular TIR domain after ligand stimulation. MyD88 recruits IL-1 receptor-associated kinase 4 (IRAK4) through DD-DD interactions and facilitates IRAK4-mediated phosphorylation of IRAK1 [18] for TNF receptor-associated factor 6 (TRAF6) engagement. Both IRAK1 and TRAF6 are polyubiquitinated in response to TLR agonists, then activating mitogen-activated protein kinases (MAPK) and NF-κB signaling pathways [19].
## 2.2. TIR Domain-Containing Adaptor Protein (TIRAP)
The search for Myd88 structurally related proteins identified TIRAP [23]. Similar to MyD88-deficient macrophages, Tirap-deficient macrophages are impaired for cytokine production, following TLR2 and TLR4 stimulation [24]. The activation of MyD88-dependent pathways requires the TIRAP adaptor to bridge MyD88 to TLR4 [25]. While TIRAP bears a C-terminal TIR domain for TLR interaction (Figure 2), TIRAP lacks a motif to associate with downstream signaling effectors, as opposed to MyD88 which possesses a DD domain [26]. Importantly, TIRAP carries a N-terminal phosphatidylinositol-4,5 bisphosphate (PIP2) binding motif enabling its recruitment to the plasma membrane [27]. Indeed, TLR4 initially recruits TIRAP at the plasma membrane, then MyD88, triggering NF-κB and MAPK pathways. Subsequently, TLR4 endocytosis and depletion of PIP2 from the plasma membrane release TLR4 from the TIRAP-MyD88 complex [28, 29]. This allows TLR4 to associate with TRIF-related adaptor molecule (TRAM) and then TIR-domain-containing adaptor-inducing interferon-β (TRIF) (Figure 3) for endosomal signaling.Figure 2
Structural view of human TIRAP and TRAM adaptor proteins. TIRAP contains a N-terminal PIP2-binding motif and a PEST domain, allowing polyubiquitination for rapid proteasomal degradation through suppressor of cytokine signaling 1 (SOCS1) binding [20]. TIRAP contains a C-terminal TIR domain. Its TRAF-6 binding motif permits direct association with TRAF6 for activation [21]. TRAM contains a N-terminal bipartite sorting signal that comprises its myristylation glycine site and controls its trafficking between the plasma membrane and the endosomes [22]. Similar to TIRAP, TRAM contains a C-terminal TIR domain.Figure 3
Schematic representation of the adaptors that bind the TIR domain of TLRs. TIRAP is preferentially localized at the cytoplasmic membrane through a PIP2-binding domain and recruits MyD88. Myristoylated TRAM localizes at the endosomes and triggers IFN I production via TRIF. Abbreviations: MAPKs: mitogen-activated protein kinases; MyD88: myeloid differentiation primary response 88; NF-κB: nuclear factor-κB; PIP2: phosphatidylinositol bisphosphate; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein; TLR: Toll-like receptor; TRAM: TRIF-related adaptor molecule; TRIF: TIR domain-containing adaptor-inducing interferon-β.
## 2.3. TRAM and TRIF: The Endosome Specific Adaptor Molecules
Metadatabase searches led to the discovery of TRAM (Figure2) [30]. Similar to the TIRAP and MyD88 pair, TRAM is required for TRIF adaptor engagement [22]. In contrast to TIRAP, TRAM is myristoylated at its N-terminus [31] (Figure 3), allowing anchoring to the endosomal membrane. Mutations abolishing TRAM myristoylation restrain TRAM cytoplasmic localization, thereby inhibiting TRIF-generated signal transduction by TLR4 [31]. In addition, cell treatment with dynasore, a dynamin 2 guanosine triphosphate (GTPase) pharmacological inhibitor, demonstrated that TLR4 internalization mediates TRAM/TRIF signaling [22, 32].Notably, TRIF is involved in antiviral protection by promoting the secretion of antiviral-specialized cytokines, namely, type I Interferons (IFN I : IFN-α and IFN-β) [33]. TRIF is recruited downstream of endosomal TLRs recognizing nucleic acids. This specific endosomal location, along with nucleic acid specific binding, protects from host DNA or mRNA detection-mediated autoimmunity. Indeed, lipofected host DNA stimulates TLR9 [34]. Viral carbohydrate and lipid structures are very similar to those observed in host cells and therefore do not represent suitable PAMPs. Instead, the immune system has evolved to express PRRs—TLRs included—that recognize viral nucleic acids [35]. For instance, TLR3 recognizes double-stranded RNA (dsRNA), and TLR9 binds unmethylated cytosine-phosphate-guanine (CpG) dinucleotides [36, 37]. Of note, Trif-deficient mice show impaired IFN-β expression in response to TLR3 and TLR4 ligands [38]. Thus, even if TLR4 detects bacterial MAMPs at the cell membrane, TLR4 induces antiviral pathways when localized within endosomes [28]. In 2014, more than ten years after this discovery, a similar function has been detailed regarding TLR2 [39].
## 3. TLR2 and TLR4: The “Only” TIRAP-Dependent TLRs
Signaling through TLR4, the most investigated TLR, has been well dissected in comparison to other TLRs (Figure1). MyD88, the first identified TLR adaptor downstream of TLR4 [14], is considered to be the adaptor “of choice” for other TLRs, except TLR3. However, this MyD88-only assumption has been challenged by various studies, suggesting that TIRAP- and TRAM-dependent signaling may be used in a larger set of TLRs. In 2002, two works have revealed that TIRAP is specific to TLR2 and TLR4 [24, 40]. Recent reviews still mention these two papers [41–43]. In this section, we explore and contextualize those two hyperreferenced studies.In 2001, flagellin was identified as a ligand for TLR5 (Figure4). A year later, it was revealed that Tirap-deficient mice are still responsive to flagellin, implying that TLR5 signaling is TIRAP-independent [24]. However, TLR5 is not the only flagellin sensor. Indeed, NOD-like receptor caspase activation and recruitment domain-containing protein 4 (NLRC4 inflammasome) is very sensitive to flagellin [44] in the cytosol of myeloid cells [45]. Unfortunately, no cellular assessment was done to discriminate this in 2002, five years before the discovery that another sensor may play a compensatory role [24]. Since then, the idea that TLR5 signaling is TIRAP-independent became the norm.Figure 4
The history of Toll-like receptors and their signaling: summarized timeline of discoveries. Abbreviations: CpG-DNA: cytosine-phosphate-guanine-deoxyribo-nucleic acid; LPS: lipopolysaccharide; MyD88: myeloid differentiation primary response 88; PRRs: pattern recognition receptors; ssRNA: single-stranded ribonucleic acid; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein; TLR4/5/7/8/9: Toll-like receptor 4/5/7/8/9; TRAM: TRIF-related adaptor molecule.In 2002, it was demonstrated that NF-κB and MAPK induction downstream of TLR9 was TIRAP-independent [24]. It was shown that Tirap-deficient macrophages activate NF-κB with delayed kinetics in response to TLR2 and TLR4 agonists, but not CpG [24]. Nevertheless, according to the NF-κB assay, TLR2- and TLR4-mediated activations are fast (20 and 10 minutes, respectively), while NF-κB activation does not start before 60-minute downstream of TLR9. No intermediary time was tested to exactly evaluate if the kinetics in response to CpG is delayed or not. MAPK assays were then performed [24]. MAPKs are not activated before one hour of CpG stimulation, but the phosphorylation status of JNK and p38 is reduced downstream of TLR9 in Tirap-deficient macrophages compared with wild-type macrophages. Unfortunately, these results were not taken into consideration by the authors. Subsequently, TLR9 gained its “directly binds MyD88” notoriety [46]. Additional studies would have been needed to further our understanding of the TLR9-induced signaling through other adaptors (Figure 1).All these discoveries emerged during a very frenetic period (Figure4) where information appeared as things progressed, without the supporting data to have a better view of TLR signaling. TLR4- and MyD88-related studies were particularly favored (Figure 1).
## 4. TLR5, TLR7, TLR8, and TLR9 Are Not “Only MyD88-Dependent” TLRs
### 4.1. TLR5
TLR5 is plasma membrane-localized and recognizes flagellin from invasive motile bacteria [47]. It has been well-described that TLR5 is only Myd88-dependent for its downstream signaling [48]. Yet, Choi et al. have demonstrated that TLR5 does require TIRAP to induce NF-κB-dependent responses. Indeed, reduced Tirap gene expression in cultured colonocytes impaired the response to flagellin. Further immunoprecipitation experiments confirmed direct interaction between TLR5 and TIRAP, following flagellin exposure [49]. Of note, colonocytes represent a more relevant experimental model for TLR5 signaling studies, since they barely express NLRC4 [50]. Intriguingly, flagellin has been recently found to mediate IFN-β production in macrophages, after TLR5 internalization from the plasma membrane to endosomes [51]. In addition, TLR5 signaling was shown to be TRIF-dependent in human colonic cells [52]. TRIF directly interacts with TLR5 upon flagellin stimulation in NCM460 colonic cells [52]. In this study, TRAM also directly interacts with TLR5 in nonstimulated conditions, as opposed to TRIF. Unfortunately, this result was not taken into consideration by the authors, and more studies are required to elucidate such observation. Altogether, adaptors other than MyD88, including TIRAP and TRIF, may contribute to the induction of TLR5 downstream signaling.
### 4.2. TLR7 and TLR8
TLR7 and TLR8 are endosomal TLRs recognizing ssRNA, the reason why both are often represented together in the endosomal compartment. Additionally, TLR7 and TLR8 share common synthetic agonists, such as R-8748 (resiquimod) [53] or gardiquimod [54]. Even though they are localized in endosomes, TLR7 and TLR8 activate NF-κB and IFN I-generating pathways [55]. In 2015, by using a peptide (decoy peptide 2R9) that blocks TIRAP recruitment, Piao et al. have shown that TLR7- and TLR8-dependent NF-κB activations are TIRAP-dependent in macrophages [56]. More recently, experiments on Carp Toll-like receptor 8 (Tlr8) have disclosed that TLR8 can directly interact with the TIRAP adaptor and that such interaction is necessary for MyD88-dependent responses [57]. Regrettably, few researches have been done on TLR8 (Figure 1), and therefore, functional studies on mammalian TIRAP and TLR8 interactions are still lacking.Interestingly, TRIF engagement and IFN secretion by TLR7 require another adaptor protein, TRAM [58]. Indeed, while Tram-deficient macrophages exhibit a complete NF-κB response to the TLR7 ligand imiquimod, IFN I secretion is abolished. Whether TRAM may also play a role in TLR8 transduction has never been investigated. A potential TRAM compensatory role may explain why, in 2002, there was no impaired proliferation of Tirap-deficient splenocytes to R-848 [24]. But TRAM was discovered a year later (Figure 4), and such possibility could even not be suggested. Furthermore, downstream of TLRs, MyD88 activation, is required for cell division [59], which could explain why MyD88-deficient splenocytes show impaired proliferation to R-848 [24]. Taken together, these recent data suggest that, in addition to the known role of Myd88, TIRAP and TRAM can be involved in TLR7 and TLR8 signaling. However, one question remains: how endosomal TLR7 and TLR8 could activate both MyD88-dependent and -independent pathways? The beginning of an answer is provided by studies on TLR9 detailed as follows.
### 4.3. TLR9
TLR9 is an endosomal TLR that detects unmethylated CpG dinucleotides from viral and bacterial DNA [60] and is located in endosomes. TLR9 activation triggers NF-κB and IFN I signaling pathways [61]. TIRAP expression enhances the MyD88-dependent response mediated by TLR9 [62]. Moreover, immortalized bone marrow-derived macrophages (iBMDMs) isolated from Tirap KO (knockout) mice do not respond to ODN1668, a TLR9 agonist [56]. iBMDMs represent a useful experimental model to explore signaling, as they retain the signaling properties of primary macrophages [62]. TLR9-provoked secretion of TNF-α and IL-6 is TIRAP-dependent in iBMDMs [56]. In this study, these data were confirmed by using a decoy peptide that directly targets TIRAP. More recently, the same group has demonstrated that ODN-induced cytokine secretion and lethality are abrogated by intraperitoneally pretreating mice with the 9R34 decoy peptide, a more specific TLR9 inhibitor [63]. Finally, Tirap-deficient macrophages infected with herpes virus simplex (HSV), a natural TLR9 activator, are unable to trigger NF-κB signaling [62].The use of two structurally diverse synthetic TLR9 ligands uncovers surprising outcomes. Plasmacytoid dendritic cells do express TLR7 and TLR9 within endosomal compartments [64], which allow these cells to produce high amounts of IFN type I, in contrast to conventional dendritic cells [65]. CpG-A treatment led to increased IFN I production in mouse plasmacytoid dendritic cells, while proinflammatory cytokine release, related to NF-κB activation, was induced only in response to CpG-B [66]. The authors explained their data through distinct localization of both ligands, since CpG-A and CpG-B do not always traffic in the same way within cells. For instance, in plasmacytoid dendritic cells, CpG-A is retained in early endosomes, whereas CpG-B translocates to late endosomes and lysosomes [67].Dendritic cells are professional antigen-presenting cells, also acting as mediators between the innate and the adaptative immune systems [68]. Primary dendritic cells, namely, bone marrow-derived dendritic cells (BMDCs), represent an interesting working model, as primary BMDC cultures can be matured in a number of cell types, including dendritic cells and macrophages [69]. In BMDCs, CpG-A and CpG-B ligands are both transported to late endosomes and lysosomes, leading to NF-κB responses. In addition, conventional dendritic cells produce IFN I when stimulated with dioleoyl-3-trimethyl-ammonium propane- (DOTAP-) lipofected CpG-A, which is retained in endosomes [67]. PI(3,5)P2, abundant in late endosomes and lysosomes [70], facilitates the anchoring of TIRAP in response to CpG [71]. In plasmacytoid dendritic cells, TLR9 stimulation initiates IFN I expression in a TRIF-dependent manner [72], which was recently confirmed in macrophages [73]. But studies on the role of TRAM in endosome-mediated TLR9 responses are still missing. Taken together, these data support a model in which TLR9 functionally traffics within the cell to trigger distinct pathways, by recruiting different signaling adaptors other than Myd88, with differences related to the cell type. Most of the research on TLR9 has been done in plasmacytoid dendritic cells, specialized in antiviral responses [65]. It would be relevant to see if similar results can be observed in other cell types.
## 4.1. TLR5
TLR5 is plasma membrane-localized and recognizes flagellin from invasive motile bacteria [47]. It has been well-described that TLR5 is only Myd88-dependent for its downstream signaling [48]. Yet, Choi et al. have demonstrated that TLR5 does require TIRAP to induce NF-κB-dependent responses. Indeed, reduced Tirap gene expression in cultured colonocytes impaired the response to flagellin. Further immunoprecipitation experiments confirmed direct interaction between TLR5 and TIRAP, following flagellin exposure [49]. Of note, colonocytes represent a more relevant experimental model for TLR5 signaling studies, since they barely express NLRC4 [50]. Intriguingly, flagellin has been recently found to mediate IFN-β production in macrophages, after TLR5 internalization from the plasma membrane to endosomes [51]. In addition, TLR5 signaling was shown to be TRIF-dependent in human colonic cells [52]. TRIF directly interacts with TLR5 upon flagellin stimulation in NCM460 colonic cells [52]. In this study, TRAM also directly interacts with TLR5 in nonstimulated conditions, as opposed to TRIF. Unfortunately, this result was not taken into consideration by the authors, and more studies are required to elucidate such observation. Altogether, adaptors other than MyD88, including TIRAP and TRIF, may contribute to the induction of TLR5 downstream signaling.
## 4.2. TLR7 and TLR8
TLR7 and TLR8 are endosomal TLRs recognizing ssRNA, the reason why both are often represented together in the endosomal compartment. Additionally, TLR7 and TLR8 share common synthetic agonists, such as R-8748 (resiquimod) [53] or gardiquimod [54]. Even though they are localized in endosomes, TLR7 and TLR8 activate NF-κB and IFN I-generating pathways [55]. In 2015, by using a peptide (decoy peptide 2R9) that blocks TIRAP recruitment, Piao et al. have shown that TLR7- and TLR8-dependent NF-κB activations are TIRAP-dependent in macrophages [56]. More recently, experiments on Carp Toll-like receptor 8 (Tlr8) have disclosed that TLR8 can directly interact with the TIRAP adaptor and that such interaction is necessary for MyD88-dependent responses [57]. Regrettably, few researches have been done on TLR8 (Figure 1), and therefore, functional studies on mammalian TIRAP and TLR8 interactions are still lacking.Interestingly, TRIF engagement and IFN secretion by TLR7 require another adaptor protein, TRAM [58]. Indeed, while Tram-deficient macrophages exhibit a complete NF-κB response to the TLR7 ligand imiquimod, IFN I secretion is abolished. Whether TRAM may also play a role in TLR8 transduction has never been investigated. A potential TRAM compensatory role may explain why, in 2002, there was no impaired proliferation of Tirap-deficient splenocytes to R-848 [24]. But TRAM was discovered a year later (Figure 4), and such possibility could even not be suggested. Furthermore, downstream of TLRs, MyD88 activation, is required for cell division [59], which could explain why MyD88-deficient splenocytes show impaired proliferation to R-848 [24]. Taken together, these recent data suggest that, in addition to the known role of Myd88, TIRAP and TRAM can be involved in TLR7 and TLR8 signaling. However, one question remains: how endosomal TLR7 and TLR8 could activate both MyD88-dependent and -independent pathways? The beginning of an answer is provided by studies on TLR9 detailed as follows.
## 4.3. TLR9
TLR9 is an endosomal TLR that detects unmethylated CpG dinucleotides from viral and bacterial DNA [60] and is located in endosomes. TLR9 activation triggers NF-κB and IFN I signaling pathways [61]. TIRAP expression enhances the MyD88-dependent response mediated by TLR9 [62]. Moreover, immortalized bone marrow-derived macrophages (iBMDMs) isolated from Tirap KO (knockout) mice do not respond to ODN1668, a TLR9 agonist [56]. iBMDMs represent a useful experimental model to explore signaling, as they retain the signaling properties of primary macrophages [62]. TLR9-provoked secretion of TNF-α and IL-6 is TIRAP-dependent in iBMDMs [56]. In this study, these data were confirmed by using a decoy peptide that directly targets TIRAP. More recently, the same group has demonstrated that ODN-induced cytokine secretion and lethality are abrogated by intraperitoneally pretreating mice with the 9R34 decoy peptide, a more specific TLR9 inhibitor [63]. Finally, Tirap-deficient macrophages infected with herpes virus simplex (HSV), a natural TLR9 activator, are unable to trigger NF-κB signaling [62].The use of two structurally diverse synthetic TLR9 ligands uncovers surprising outcomes. Plasmacytoid dendritic cells do express TLR7 and TLR9 within endosomal compartments [64], which allow these cells to produce high amounts of IFN type I, in contrast to conventional dendritic cells [65]. CpG-A treatment led to increased IFN I production in mouse plasmacytoid dendritic cells, while proinflammatory cytokine release, related to NF-κB activation, was induced only in response to CpG-B [66]. The authors explained their data through distinct localization of both ligands, since CpG-A and CpG-B do not always traffic in the same way within cells. For instance, in plasmacytoid dendritic cells, CpG-A is retained in early endosomes, whereas CpG-B translocates to late endosomes and lysosomes [67].Dendritic cells are professional antigen-presenting cells, also acting as mediators between the innate and the adaptative immune systems [68]. Primary dendritic cells, namely, bone marrow-derived dendritic cells (BMDCs), represent an interesting working model, as primary BMDC cultures can be matured in a number of cell types, including dendritic cells and macrophages [69]. In BMDCs, CpG-A and CpG-B ligands are both transported to late endosomes and lysosomes, leading to NF-κB responses. In addition, conventional dendritic cells produce IFN I when stimulated with dioleoyl-3-trimethyl-ammonium propane- (DOTAP-) lipofected CpG-A, which is retained in endosomes [67]. PI(3,5)P2, abundant in late endosomes and lysosomes [70], facilitates the anchoring of TIRAP in response to CpG [71]. In plasmacytoid dendritic cells, TLR9 stimulation initiates IFN I expression in a TRIF-dependent manner [72], which was recently confirmed in macrophages [73]. But studies on the role of TRAM in endosome-mediated TLR9 responses are still missing. Taken together, these data support a model in which TLR9 functionally traffics within the cell to trigger distinct pathways, by recruiting different signaling adaptors other than Myd88, with differences related to the cell type. Most of the research on TLR9 has been done in plasmacytoid dendritic cells, specialized in antiviral responses [65]. It would be relevant to see if similar results can be observed in other cell types.
## 5. Why the Endosomal Trio TLR7/8/9 Is Believed to Be MyD88-Dependent
As opposed to IRF3, theIFN-beta-specialized transcription factor, IRF7, is less specific and promotes both IFN-alpha and IFN-beta transcriptions [74]. Like IRF3, IRF7 is phosphorylated by members of the IκB kinase family (IKKs), including IKKα, IKKβ, IKKε, and TRAF-associated NF-κB activator-binding kinase 1 (TBK1) [75]. IKKα and IKKβ are also involved in the canonical NF-κB pathway. Despite redundancy, IKKε and TBK1 are the two more specialized kinases in IRF3 phosphorylation-promoted activation [76]. Some papers have provided explanations for this preference. Indeed, IRF3 regulation requires phosphatidylinositol-5-phosphate (PI5P) [71]. PI5P, which is enriched in membranes of early endosomes during viral infection, binds to both IRF3 and TBK1 to facilitate complex formation [71]. TRAM, involved in TBK1 and IRF3 activations, binds phosphatidylinositol-3-phosphate (PIP3) and PI5P [22] and is localized to early endosomes as well. Findings on phosphoinositide-mediated effector recruitment in TLR signaling are summarized in Table 1. IRF7 interacts with MyD88 and TRAF6 [77], required for IKK engagement and IKKα- and IKKβ-induced IRF7 phosphorylation [75]. IRF7 is thus activated downstream of TLR7, TLR8, and TLR9, all recognized to “directly bind MyD88.”Table 1
Cellular compartments for TLR signaling effector recruitment.
TLR effectorRelated pathwayTLRPI lipidsCellular compartmentsCell typesReferencesTIRAPNF-κBTLR2, TLR4PI(4,5)P2Plasma membraneHuman monocytes, macrophages[28, 78]TLR4, TLR9PI(3,5)P2LysosomeBMDMs[62, 67]IFN I (via IRF7)TLR4PI3P, PI5PEarly endosomeMEFs, macrophages[17, 27]TRAMIFN I (via TRIF)Macrophages[22]TBK1TLR3, TLR4PI5PMEFs, GMDCs[71]IRF3Abbreviations: BMDMs: bone marrow-derived macrophages; GMDCs: genetically modified dendritic cells; IFN I: type I interferons; IRF3: interferon regulatory factor 3; IRF7: interferon regulatory factor 7; MEFs: mouse embryonic fibroblasts; NF-κB: nuclear factor-κB; PI: phosphatidylinositol; PI3P: phosphatidylinositol-3-phosphate; PI5P: phosphatidylinositol-5-phosphate; PI(3,5)P2: phosphatidylinositol-3,5-biphosphate; PI(4,5)P2: phosphatidylinositol-4,5-biphosphate; TBK1: TRAF-associated NF-κB activator-binding kinase 1; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein; TLR: Toll-like receptor; TRAM: TRIF-related adaptor molecule; TRIF: TIR domain-containing adaptor-inducing interferon-β.Very recently, it has been demonstrated that TIRAP is also necessary for IRF7 phosphorylation in macrophages and human plasmacytoid dendritic cells, by bridging MyD88 to TLR7 [79]. Whether TLR8 and TLR9 adopt a similar requirement for TIRAP to activate IRF7 remains to be determined. Of note, in plasmacytoid dendritic cells, the TLR9 agonist CpG-A, initiating IFN I release, colocalizes with IRF7 in early endosomes [66]. TIRAP binds to PI(4,5)P2 at the cytoplasmic membrane and to PI3P on early endosomes [17, 27, 78]. Thus, while IRF7 activation is MyD88-dependent, some recent data suggest that TIRAP may be needed for such activation.
## 6. An Emerging Model for TLR/TIRAP/MyD88 Signaling
According to an emerging TLR signaling model (Figure5), all TLRs except TLR3 are TIRAP-dependent for MyD88-mediated pathways [80]. However, one question remains: what is the biological relevance of the TIRAP bridging adaptor, knowing that all TLRs can directly bind MyD88 through TIR-TIR interactions? Answers are provided by crystallographic structural studies and by the myddosome discovery [81, 82]. The myddosome is a multiproteic and functional signaling complex, including six MyD88, four IRAK4, and four IRAK1 subunits [41, 80], triggering NF-κB activation. 3D structures reveal that each TLR4 homodimer recruits two TIRAP homodimers, each recruiting in turn four MyD88 molecules [80]. So, eight MyD88 molecules are clustered following TLR4 homodimerization, which is enough to engage a myddosome. By amplifying MyD88 engagement, TIRAP allows transduction of favorable signal downstream of TLRs. This TLR4-dependent pattern may be valid for all TLRs except TLR3, according to the authors [80] and discussed in a recent review [83].Figure 5
Emerging model for TLR signaling. Recent data suggest a new model according to which all TLRs, but TLR3, are TIRAP-dependent for MyD88-mediated pathways and TRAM-dependent for the TRIF cascade. TLR3 directly recruits the TRIF adaptor to the endosomal compartment. TRAF3: TNF receptor-associated factor 3.
## 7. Clinical Relevance
### 7.1.TIRAP Gene Polymorphisms and Pathogenesis
TLR receptors evolved before the adaptive immune system to form an indispensable first line of innate defense [84]. TLRs play key roles in homeostatic as well as in pathogenic responses in many disease settings. TLR signaling represents an important target for putative treatments. As we mentioned before, TIRAP and TRAM are essential TLR bridging adaptors, while largely neglected in the scientific literature, as opposed to Myd88 (Figure 1). Remarkably, small nucleotide polymorphisms (SNPs) of TLRs and their adaptors are associated with infections and other diseases, such as atherosclerosis, asthma, or colorectal cancer [85]. Notably, TIRAP is the most polymorphic of all adaptors, harboring at least eight nonsynonymous mutations in its coding sequence [86]. Some reported TIRAP gene SNPs are presented in Table 2. Excluding the roles of TIRAP and other adaptors in TLR responses reduces our capacity to fully comprehend the TLR-dependent regulatory mechanisms implicated in acute and chronic disorders.Table 2
Reported SNPs in theTIRAP gene.
SNPAssociated diseasesReferencesS55NMeningeal tuberculosis[87]D96NLymphoma[88]E132KAtopic dermatitis[89]S180LMalaria, sepsis, and Chagas cardiomyopathy[89–91]C539TTuberculosis susceptibility[92]Abbreviations: C: cysteine; D: aspartate; E: glutamate; K: lysine; L: leucine; N: asparagine; S: serine; SNP: single-nucleotide polymorphism; T: threonine; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein.Interestingly, theTIRAP gene S180L SNP is associated with protection against infections and autoimmune diseases, such as invasive pneumococcal disease, malaria, and systemic lupus erythematosus [88, 93]. The chronic Chagas cardiomyopathy is a tropical parasitic disease caused by the intracellular protozoan Trypanosoma cruzi [94], detected by TLR4 and TLR2/6 [95]. Up to 45% of patients with chronic infections develop cardiomyopathy, between 10 and 30 years after the initial sickness [94]. It has been reported that heterozygosity for the TIRAP S180L variant is associated with lower risk of developing chronic Chagas cardiomyopathy [91]. Mechanistically, the authors propose that the S180L variant leads to decreased signal transduction downstream of TLR2 and TLR4. Accordingly, Tirap-deficient MEFs, transfected with a plasmid encoding Tirap L180, failed to induce the NF-κB pathway [93]. In contrast, homozygosity for the S180L variant confers increased susceptibility to invasive pneumococcal disease, while the heterozygosity state provides a protective phenotype [93]. The authors speculate that S180L homozygosity results in decreased NF-κB signaling, thus aggravating susceptibility to infections.The TIRAP D96N variant is considered a loss-of-function SNP [88]. Crystal structure of TIRAP reveals that amino acids D96 and S180 are within the TIR domain interacting with the MyD88 adaptor protein [96]. A worldwide polymorphism distribution investigation proposes that the TIRAP variant S180L has been evolutionary selected to provide protection against septic shock [97]. This study supplies a world map of S180L distribution, which intriguingly correlates negatively with global sepsis incidence [98]. Knowing that all TLRs are involved in septic shock [99], these data imply that the role of TIRAP in TLR signaling related to human diseases should be better considered. Recent data by Rajpoot et al. provide new structural studies and insights on TIRAP [100]. Using an in silico approach, they have determined that the phospho-motif P-Y86 on TIRAP interacts with p38 MAPK for activation, which is worth to be validated in an in vitro model [101]. Activated p38 is a well-described proinflammatory mediator involved in acute and chronic inflammations [102]. Rajpoot et al. have also identified new TIRAP inhibitors by combining several docking tools, and their future validation may lead to novel treatments against inflammatory disorders [103]. These promising docking designs may well promote further research on the TIRAP adaptor.
### 7.2.TRAM Gene Polymorphisms and Tuberculosis
Unfortunately, few studies have reportedTRAM (also named TICAM2 for TIR domain-containing adaptor molecule 2) gene polymorphisms, since TRAM is the less investigated TLR-related adaptor (Figure 1). In 2015, one polymorphism localized in the flanking 5′ untranslated region (UTR) of TRAM was associated with tuberculosis caused by the bacteria Mycobacterium tuberculosis [104, 105]. Different components of Mycobacterium tuberculosis interact with TLRs (e.g., TLR2, TLR4, TLR8 and TLR9) in macrophages, natural killer (NK) cells, dendritic cells and T cells and and induce an appropriate immune response to overcome infection [106]. While the significance of TRAM polymorphism and how it relates to its expression are unknown, these observations point to a link between TRAM and tuberculosis infection. Interestingly, levels of TRAM expression in peripheral blood mononuclear cells (PBMCs) predict with 80% accuracy whether subjects are high or low responders to a poxvirus vector tuberculosis vaccine candidate, expressing antigen 85A [107].In BMDMs, the heat shock protein 70 (Hsp70) is derived fromMycobacterium tuberculosis signals through TLR2 and TLR4 and the TIRAP, MyD88, TRAM, and TRIF adaptor molecules [108]. More studies are needed to understand the role of TRAM adaptor in tuberculosis infection and more largely in human chronic diseases.
### 7.3. Coronavirus Disease 2019 (COVID-19)
We are facing new sanitary challenges with COVID-19, the most recent coronavirus-mediated acute respiratory illness caused by the SARS-coronavirus-2 (SARS-CoV-2). Since this viral infection causes severe symptoms through the induction of a cytokine storm, many groups have studied TLR signaling to identify therapeutic targets. Prior SARS-CoV-1 research has exposed the importance of TLR adaptors in viral responses. For example, overexpression of the SARS-CoV-1 membrane protein (M) in HEK293T cells leads to increased TIRAP and TRAM protein levels in comparison to control cells. This correlates with upregulated IFN-b- and NF-κB-related gene expressions [109]. Tram-/- mice are more susceptible to mouse-adapted SARS-CoV-1 infection, without extra mortality [110]. Genetic studies in mice have revealed Tram as a susceptibility gene for SARS-CoV-1 infection [111], underlining the importance of IFN I release during SARS-CoV-1 infection recovery. In line with this observation, decreased aging-associated number of plasmacytoid dendritic cells is associated with COVID-19 severity [112]. In addition, neutralizing autoantibodies against IFN I have been detected in patients with life-threatening COVID-19 [113]. Finally, increased TIRAP phosphorylation is detected in COVID-19-infected individuals [114]. These data suggest that both TIRAP and TRAM adaptors play a role in the control of SARS-CoV-2 infections.The above results highlight the importance to study TLR signaling and to include TLR adaptor regulatory functions to understand COVID-19 disease. The SARS-CoV genomes activate TLR7 [115]. Rare putative loss-of-function variants of the X-chromosome-located TLR7 gene are associated with altered type I IFN expression in young men with severe COVID-19 [116]. TLR8, being more specific, recognizes both SARS-CoV-2 ssRNA and derived ribonuclease T2 degradation products [117]. Thus, these recent findings call for more research on TLR7 and TLR8 (Figure 1), as targets of SARS-CoV-2 viral motifs. Clinical trials aimed to stimulate endosomal TLRs to promote IFN I production at the early steps of infection or to inhibit TLRs to reduce the NF-κB-promoted cytokine storm are ongoing. Imiquimod, a TLR7 ligand, has been proposed as an option to manage the initial stages of COVID-19 [118, 119]. Conversely, clinical studies exploring TLR blockade during COVID-19 late steps are ongoing. MERCK KGaA has initiated a randomized double-blind phase II clinical trial with M5049, a selective TLR7/8 pharmacological inhibitor initially designed to treat autoimmunity [120], for the treatment of severe symptoms of COVID-19 [121].
## 7.1.TIRAP Gene Polymorphisms and Pathogenesis
TLR receptors evolved before the adaptive immune system to form an indispensable first line of innate defense [84]. TLRs play key roles in homeostatic as well as in pathogenic responses in many disease settings. TLR signaling represents an important target for putative treatments. As we mentioned before, TIRAP and TRAM are essential TLR bridging adaptors, while largely neglected in the scientific literature, as opposed to Myd88 (Figure 1). Remarkably, small nucleotide polymorphisms (SNPs) of TLRs and their adaptors are associated with infections and other diseases, such as atherosclerosis, asthma, or colorectal cancer [85]. Notably, TIRAP is the most polymorphic of all adaptors, harboring at least eight nonsynonymous mutations in its coding sequence [86]. Some reported TIRAP gene SNPs are presented in Table 2. Excluding the roles of TIRAP and other adaptors in TLR responses reduces our capacity to fully comprehend the TLR-dependent regulatory mechanisms implicated in acute and chronic disorders.Table 2
Reported SNPs in theTIRAP gene.
SNPAssociated diseasesReferencesS55NMeningeal tuberculosis[87]D96NLymphoma[88]E132KAtopic dermatitis[89]S180LMalaria, sepsis, and Chagas cardiomyopathy[89–91]C539TTuberculosis susceptibility[92]Abbreviations: C: cysteine; D: aspartate; E: glutamate; K: lysine; L: leucine; N: asparagine; S: serine; SNP: single-nucleotide polymorphism; T: threonine; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein.Interestingly, theTIRAP gene S180L SNP is associated with protection against infections and autoimmune diseases, such as invasive pneumococcal disease, malaria, and systemic lupus erythematosus [88, 93]. The chronic Chagas cardiomyopathy is a tropical parasitic disease caused by the intracellular protozoan Trypanosoma cruzi [94], detected by TLR4 and TLR2/6 [95]. Up to 45% of patients with chronic infections develop cardiomyopathy, between 10 and 30 years after the initial sickness [94]. It has been reported that heterozygosity for the TIRAP S180L variant is associated with lower risk of developing chronic Chagas cardiomyopathy [91]. Mechanistically, the authors propose that the S180L variant leads to decreased signal transduction downstream of TLR2 and TLR4. Accordingly, Tirap-deficient MEFs, transfected with a plasmid encoding Tirap L180, failed to induce the NF-κB pathway [93]. In contrast, homozygosity for the S180L variant confers increased susceptibility to invasive pneumococcal disease, while the heterozygosity state provides a protective phenotype [93]. The authors speculate that S180L homozygosity results in decreased NF-κB signaling, thus aggravating susceptibility to infections.The TIRAP D96N variant is considered a loss-of-function SNP [88]. Crystal structure of TIRAP reveals that amino acids D96 and S180 are within the TIR domain interacting with the MyD88 adaptor protein [96]. A worldwide polymorphism distribution investigation proposes that the TIRAP variant S180L has been evolutionary selected to provide protection against septic shock [97]. This study supplies a world map of S180L distribution, which intriguingly correlates negatively with global sepsis incidence [98]. Knowing that all TLRs are involved in septic shock [99], these data imply that the role of TIRAP in TLR signaling related to human diseases should be better considered. Recent data by Rajpoot et al. provide new structural studies and insights on TIRAP [100]. Using an in silico approach, they have determined that the phospho-motif P-Y86 on TIRAP interacts with p38 MAPK for activation, which is worth to be validated in an in vitro model [101]. Activated p38 is a well-described proinflammatory mediator involved in acute and chronic inflammations [102]. Rajpoot et al. have also identified new TIRAP inhibitors by combining several docking tools, and their future validation may lead to novel treatments against inflammatory disorders [103]. These promising docking designs may well promote further research on the TIRAP adaptor.
## 7.2.TRAM Gene Polymorphisms and Tuberculosis
Unfortunately, few studies have reportedTRAM (also named TICAM2 for TIR domain-containing adaptor molecule 2) gene polymorphisms, since TRAM is the less investigated TLR-related adaptor (Figure 1). In 2015, one polymorphism localized in the flanking 5′ untranslated region (UTR) of TRAM was associated with tuberculosis caused by the bacteria Mycobacterium tuberculosis [104, 105]. Different components of Mycobacterium tuberculosis interact with TLRs (e.g., TLR2, TLR4, TLR8 and TLR9) in macrophages, natural killer (NK) cells, dendritic cells and T cells and and induce an appropriate immune response to overcome infection [106]. While the significance of TRAM polymorphism and how it relates to its expression are unknown, these observations point to a link between TRAM and tuberculosis infection. Interestingly, levels of TRAM expression in peripheral blood mononuclear cells (PBMCs) predict with 80% accuracy whether subjects are high or low responders to a poxvirus vector tuberculosis vaccine candidate, expressing antigen 85A [107].In BMDMs, the heat shock protein 70 (Hsp70) is derived fromMycobacterium tuberculosis signals through TLR2 and TLR4 and the TIRAP, MyD88, TRAM, and TRIF adaptor molecules [108]. More studies are needed to understand the role of TRAM adaptor in tuberculosis infection and more largely in human chronic diseases.
## 7.3. Coronavirus Disease 2019 (COVID-19)
We are facing new sanitary challenges with COVID-19, the most recent coronavirus-mediated acute respiratory illness caused by the SARS-coronavirus-2 (SARS-CoV-2). Since this viral infection causes severe symptoms through the induction of a cytokine storm, many groups have studied TLR signaling to identify therapeutic targets. Prior SARS-CoV-1 research has exposed the importance of TLR adaptors in viral responses. For example, overexpression of the SARS-CoV-1 membrane protein (M) in HEK293T cells leads to increased TIRAP and TRAM protein levels in comparison to control cells. This correlates with upregulated IFN-b- and NF-κB-related gene expressions [109]. Tram-/- mice are more susceptible to mouse-adapted SARS-CoV-1 infection, without extra mortality [110]. Genetic studies in mice have revealed Tram as a susceptibility gene for SARS-CoV-1 infection [111], underlining the importance of IFN I release during SARS-CoV-1 infection recovery. In line with this observation, decreased aging-associated number of plasmacytoid dendritic cells is associated with COVID-19 severity [112]. In addition, neutralizing autoantibodies against IFN I have been detected in patients with life-threatening COVID-19 [113]. Finally, increased TIRAP phosphorylation is detected in COVID-19-infected individuals [114]. These data suggest that both TIRAP and TRAM adaptors play a role in the control of SARS-CoV-2 infections.The above results highlight the importance to study TLR signaling and to include TLR adaptor regulatory functions to understand COVID-19 disease. The SARS-CoV genomes activate TLR7 [115]. Rare putative loss-of-function variants of the X-chromosome-located TLR7 gene are associated with altered type I IFN expression in young men with severe COVID-19 [116]. TLR8, being more specific, recognizes both SARS-CoV-2 ssRNA and derived ribonuclease T2 degradation products [117]. Thus, these recent findings call for more research on TLR7 and TLR8 (Figure 1), as targets of SARS-CoV-2 viral motifs. Clinical trials aimed to stimulate endosomal TLRs to promote IFN I production at the early steps of infection or to inhibit TLRs to reduce the NF-κB-promoted cytokine storm are ongoing. Imiquimod, a TLR7 ligand, has been proposed as an option to manage the initial stages of COVID-19 [118, 119]. Conversely, clinical studies exploring TLR blockade during COVID-19 late steps are ongoing. MERCK KGaA has initiated a randomized double-blind phase II clinical trial with M5049, a selective TLR7/8 pharmacological inhibitor initially designed to treat autoimmunity [120], for the treatment of severe symptoms of COVID-19 [121].
## 8. Conclusion
In this review, we have underscored the importance of TIRAP and TRAM bridging molecules in MyD88 and TRIF recruitments. In the last few years, most research was performed on TLR4 because of the importance of its ligand LPS [122] in mediating sepsis, a worldwide public health issue [123]. Sepsis is indeed the leading cause of death in intensive care units in the United States [124]. Gram-bacterial sepsis mortality is 20 to 50% among total sepsis deaths [125]. In 2010, Chaby reported that a paper on LPS was published every two hours [123]. Therefore, TLR4 has been extensively explored in comparison to other TLRs, and studies about TLR4 signaling have been fundamental in discovering the TIRAP-MyD88 and TRAM-TRIF signaling patterns. Unexpectedly, these patterns were also revealed downstream of TLR2 [39]. Pursuing such efforts to analyze other TLRs is needed to discover treatments against novel infections, such as COVID-19. Thus, while TLR signaling is believed to be “well-described,” further studies are warranted for a complete understanding of TLR signaling pathways, including the role of TIRAP and TRAM adaptors.
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*Source: 2899271-2023-03-07.xml* | 2899271-2023-03-07_2899271-2023-03-07.md | 53,741 | TIRAP, TRAM, and Toll-Like Receptors: The Untold Story | Valérie Lannoy; Anthony Côté-Biron; Claude Asselin; Nathalie Rivard | Mediators of Inflammation
(2023) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2023/2899271 | 2899271-2023-03-07.xml | ---
## Abstract
Toll-like receptors (TLRs) are the most studied receptors among the pattern recognition receptors (PRRs). They act as microbial sensors, playing major roles in the regulation of the innate immune system. TLRs mediate their cellular functions through the activation of MyD88-dependent or MyD88-independent signaling pathways. Myd88, or myeloid differentiation primary response 88, is a cytosolic adaptor protein essential for the induction of proinflammatory cytokines by all TLRs except TLR3. While the crucial role of Myd88 is well described, the contribution of other adaptors in mediating TLR signaling and function has been underestimated. In this review, we highlight important results demonstrating that TIRAP and TRAM adaptors are also required for full signaling activity and responses induced by most TLRs.
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## Body
## 1. Introduction
The history of Toll-like receptors (TLRs) over the last 30 years begins with the discovery of theToll gene responsible for Drosophila dorsoventral patterning during development. This was followed by the discovery, in 1996, that Drosophila Toll is involved in antifungal responses [1]. Since then, TLRs have been identified in invertebrates and vertebrates, including mammals, and their role in innate immunity has been extensively studied. The first mammalian homolog of Drosophila Toll was identified in 1997 as hToll, now termed TLR4 [2]. Today, the TLR family includes ten members in human (TLR1-TLR10) and twelve in mouse (TLR1-TLR9 and TLR11-TLR13) [3].TLRs belong to the innate immunity receptor superfamily pattern recognition receptors (PRRs) [4]. TLRs consist of a cytoplasmic Toll-interleukin-1 receptor (TIR) domain conserved between TLR and the interleukin-1 receptor (IL-1R) families, as well as extracellular leucine-rich repeats (LRRs) [5]. Ubiquitously expressed [6], TLRs detect specific microbe-, pathogen-, and damage-associated molecular patterns, respectively, named MAMPs, PAMPs, and DAMPs, through LRR motif binding [7]. TLR-dependent recognition of microbial components triggers innate immune activation by regulating proinflammatory gene expression, among others. Individual TLRs differentially distributed within the cell interact with specific microbial-derived ligands. For example, TLR1, TLR2, TLR4, TLR5 and TLR6 are expressed on the cell surface and recognize conserved motifs on extracellular microorganisms like bacteria, fungi or protozoa [8]. In contrast, TLR3, TLR7, TLR8, and TLR9 are mostly expressed in the endo-lysosomal compartments [9–11]. During viral infection, receptor-mediated virus entry is usually directed to the cytoplasm, but occasionally, the virus enters the endosomal compartment. This may result in viral particle degradation, causing endosomal TLR ligand exposure to double- and single-stranded ribonucleic acids (dsRNAs and ssRNAs), which are TLR3 and TLR7/8 ligands, respectively [12].Microbial motif recognition promotes TLR dimerization. TLR2 forms a heterophilic dimer with TLR1 or TLR6, while TLRs may form homodimers in other cases [13]. TLR dimerization activates signaling pathways that originate from the conserved intracellular TIR domain. Downstream of TIR, the TIR domain-containing adaptor myeloid differentiation primary response 88 (MyD88), is essential for the induction of proinflammatory cytokines, such as tumor necrosis factor-α (TNF-α) and interleukin-12 (IL-12) by all TLRs, except TLR3 [14]. Notably, TLR signaling operates through MyD88-dependent or MyD88-independent pathways. While a major role for Myd88 in mediating TLR signaling and function has been well described [15], the contribution of other signaling adaptors has been underestimated (Figure 1).Figure 1
TLR4 and MyD88 hegemony in TLR research. The number of publications regarding each TLR and TLR-related adaptor referenced in PubMed® was calculated on 27th October 2022. 28,034 publications regarding TLR4 were found; 13,431 on TLR2; 6,237 on TLR9; 5,516 on TLR3; 4,426 on TLR7; 2,011 on TLR5; 1,435 on TLR8; 10,148 on MyD88; 2,037 on TRIF; 601 on TIRAP; and 118 on TRAM.In this review, we highlight important results suggesting that TIRAP and TRAM adaptors are also required for full signaling activity and responses induced by most TLRs.
## 2. TLR Adaptors: An Overview
### 2.1. MyD88
MyD88, the universal adaptor protein for all TLRs except TLR3, triggers the activation of the proinflammatory nuclear factor-κB (NF-κB) pathway. Inflammatory cytokines are not induced in MyD88-deficient mice in response to stimulation by all TLRs but TLR3 [16]. MyD88 contains a N-terminal death domain (DD) and a C-terminal TIR domain [17], which associates with the TLR intracellular TIR domain after ligand stimulation. MyD88 recruits IL-1 receptor-associated kinase 4 (IRAK4) through DD-DD interactions and facilitates IRAK4-mediated phosphorylation of IRAK1 [18] for TNF receptor-associated factor 6 (TRAF6) engagement. Both IRAK1 and TRAF6 are polyubiquitinated in response to TLR agonists, then activating mitogen-activated protein kinases (MAPK) and NF-κB signaling pathways [19].
### 2.2. TIR Domain-Containing Adaptor Protein (TIRAP)
The search for Myd88 structurally related proteins identified TIRAP [23]. Similar to MyD88-deficient macrophages, Tirap-deficient macrophages are impaired for cytokine production, following TLR2 and TLR4 stimulation [24]. The activation of MyD88-dependent pathways requires the TIRAP adaptor to bridge MyD88 to TLR4 [25]. While TIRAP bears a C-terminal TIR domain for TLR interaction (Figure 2), TIRAP lacks a motif to associate with downstream signaling effectors, as opposed to MyD88 which possesses a DD domain [26]. Importantly, TIRAP carries a N-terminal phosphatidylinositol-4,5 bisphosphate (PIP2) binding motif enabling its recruitment to the plasma membrane [27]. Indeed, TLR4 initially recruits TIRAP at the plasma membrane, then MyD88, triggering NF-κB and MAPK pathways. Subsequently, TLR4 endocytosis and depletion of PIP2 from the plasma membrane release TLR4 from the TIRAP-MyD88 complex [28, 29]. This allows TLR4 to associate with TRIF-related adaptor molecule (TRAM) and then TIR-domain-containing adaptor-inducing interferon-β (TRIF) (Figure 3) for endosomal signaling.Figure 2
Structural view of human TIRAP and TRAM adaptor proteins. TIRAP contains a N-terminal PIP2-binding motif and a PEST domain, allowing polyubiquitination for rapid proteasomal degradation through suppressor of cytokine signaling 1 (SOCS1) binding [20]. TIRAP contains a C-terminal TIR domain. Its TRAF-6 binding motif permits direct association with TRAF6 for activation [21]. TRAM contains a N-terminal bipartite sorting signal that comprises its myristylation glycine site and controls its trafficking between the plasma membrane and the endosomes [22]. Similar to TIRAP, TRAM contains a C-terminal TIR domain.Figure 3
Schematic representation of the adaptors that bind the TIR domain of TLRs. TIRAP is preferentially localized at the cytoplasmic membrane through a PIP2-binding domain and recruits MyD88. Myristoylated TRAM localizes at the endosomes and triggers IFN I production via TRIF. Abbreviations: MAPKs: mitogen-activated protein kinases; MyD88: myeloid differentiation primary response 88; NF-κB: nuclear factor-κB; PIP2: phosphatidylinositol bisphosphate; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein; TLR: Toll-like receptor; TRAM: TRIF-related adaptor molecule; TRIF: TIR domain-containing adaptor-inducing interferon-β.
### 2.3. TRAM and TRIF: The Endosome Specific Adaptor Molecules
Metadatabase searches led to the discovery of TRAM (Figure2) [30]. Similar to the TIRAP and MyD88 pair, TRAM is required for TRIF adaptor engagement [22]. In contrast to TIRAP, TRAM is myristoylated at its N-terminus [31] (Figure 3), allowing anchoring to the endosomal membrane. Mutations abolishing TRAM myristoylation restrain TRAM cytoplasmic localization, thereby inhibiting TRIF-generated signal transduction by TLR4 [31]. In addition, cell treatment with dynasore, a dynamin 2 guanosine triphosphate (GTPase) pharmacological inhibitor, demonstrated that TLR4 internalization mediates TRAM/TRIF signaling [22, 32].Notably, TRIF is involved in antiviral protection by promoting the secretion of antiviral-specialized cytokines, namely, type I Interferons (IFN I : IFN-α and IFN-β) [33]. TRIF is recruited downstream of endosomal TLRs recognizing nucleic acids. This specific endosomal location, along with nucleic acid specific binding, protects from host DNA or mRNA detection-mediated autoimmunity. Indeed, lipofected host DNA stimulates TLR9 [34]. Viral carbohydrate and lipid structures are very similar to those observed in host cells and therefore do not represent suitable PAMPs. Instead, the immune system has evolved to express PRRs—TLRs included—that recognize viral nucleic acids [35]. For instance, TLR3 recognizes double-stranded RNA (dsRNA), and TLR9 binds unmethylated cytosine-phosphate-guanine (CpG) dinucleotides [36, 37]. Of note, Trif-deficient mice show impaired IFN-β expression in response to TLR3 and TLR4 ligands [38]. Thus, even if TLR4 detects bacterial MAMPs at the cell membrane, TLR4 induces antiviral pathways when localized within endosomes [28]. In 2014, more than ten years after this discovery, a similar function has been detailed regarding TLR2 [39].
## 2.1. MyD88
MyD88, the universal adaptor protein for all TLRs except TLR3, triggers the activation of the proinflammatory nuclear factor-κB (NF-κB) pathway. Inflammatory cytokines are not induced in MyD88-deficient mice in response to stimulation by all TLRs but TLR3 [16]. MyD88 contains a N-terminal death domain (DD) and a C-terminal TIR domain [17], which associates with the TLR intracellular TIR domain after ligand stimulation. MyD88 recruits IL-1 receptor-associated kinase 4 (IRAK4) through DD-DD interactions and facilitates IRAK4-mediated phosphorylation of IRAK1 [18] for TNF receptor-associated factor 6 (TRAF6) engagement. Both IRAK1 and TRAF6 are polyubiquitinated in response to TLR agonists, then activating mitogen-activated protein kinases (MAPK) and NF-κB signaling pathways [19].
## 2.2. TIR Domain-Containing Adaptor Protein (TIRAP)
The search for Myd88 structurally related proteins identified TIRAP [23]. Similar to MyD88-deficient macrophages, Tirap-deficient macrophages are impaired for cytokine production, following TLR2 and TLR4 stimulation [24]. The activation of MyD88-dependent pathways requires the TIRAP adaptor to bridge MyD88 to TLR4 [25]. While TIRAP bears a C-terminal TIR domain for TLR interaction (Figure 2), TIRAP lacks a motif to associate with downstream signaling effectors, as opposed to MyD88 which possesses a DD domain [26]. Importantly, TIRAP carries a N-terminal phosphatidylinositol-4,5 bisphosphate (PIP2) binding motif enabling its recruitment to the plasma membrane [27]. Indeed, TLR4 initially recruits TIRAP at the plasma membrane, then MyD88, triggering NF-κB and MAPK pathways. Subsequently, TLR4 endocytosis and depletion of PIP2 from the plasma membrane release TLR4 from the TIRAP-MyD88 complex [28, 29]. This allows TLR4 to associate with TRIF-related adaptor molecule (TRAM) and then TIR-domain-containing adaptor-inducing interferon-β (TRIF) (Figure 3) for endosomal signaling.Figure 2
Structural view of human TIRAP and TRAM adaptor proteins. TIRAP contains a N-terminal PIP2-binding motif and a PEST domain, allowing polyubiquitination for rapid proteasomal degradation through suppressor of cytokine signaling 1 (SOCS1) binding [20]. TIRAP contains a C-terminal TIR domain. Its TRAF-6 binding motif permits direct association with TRAF6 for activation [21]. TRAM contains a N-terminal bipartite sorting signal that comprises its myristylation glycine site and controls its trafficking between the plasma membrane and the endosomes [22]. Similar to TIRAP, TRAM contains a C-terminal TIR domain.Figure 3
Schematic representation of the adaptors that bind the TIR domain of TLRs. TIRAP is preferentially localized at the cytoplasmic membrane through a PIP2-binding domain and recruits MyD88. Myristoylated TRAM localizes at the endosomes and triggers IFN I production via TRIF. Abbreviations: MAPKs: mitogen-activated protein kinases; MyD88: myeloid differentiation primary response 88; NF-κB: nuclear factor-κB; PIP2: phosphatidylinositol bisphosphate; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein; TLR: Toll-like receptor; TRAM: TRIF-related adaptor molecule; TRIF: TIR domain-containing adaptor-inducing interferon-β.
## 2.3. TRAM and TRIF: The Endosome Specific Adaptor Molecules
Metadatabase searches led to the discovery of TRAM (Figure2) [30]. Similar to the TIRAP and MyD88 pair, TRAM is required for TRIF adaptor engagement [22]. In contrast to TIRAP, TRAM is myristoylated at its N-terminus [31] (Figure 3), allowing anchoring to the endosomal membrane. Mutations abolishing TRAM myristoylation restrain TRAM cytoplasmic localization, thereby inhibiting TRIF-generated signal transduction by TLR4 [31]. In addition, cell treatment with dynasore, a dynamin 2 guanosine triphosphate (GTPase) pharmacological inhibitor, demonstrated that TLR4 internalization mediates TRAM/TRIF signaling [22, 32].Notably, TRIF is involved in antiviral protection by promoting the secretion of antiviral-specialized cytokines, namely, type I Interferons (IFN I : IFN-α and IFN-β) [33]. TRIF is recruited downstream of endosomal TLRs recognizing nucleic acids. This specific endosomal location, along with nucleic acid specific binding, protects from host DNA or mRNA detection-mediated autoimmunity. Indeed, lipofected host DNA stimulates TLR9 [34]. Viral carbohydrate and lipid structures are very similar to those observed in host cells and therefore do not represent suitable PAMPs. Instead, the immune system has evolved to express PRRs—TLRs included—that recognize viral nucleic acids [35]. For instance, TLR3 recognizes double-stranded RNA (dsRNA), and TLR9 binds unmethylated cytosine-phosphate-guanine (CpG) dinucleotides [36, 37]. Of note, Trif-deficient mice show impaired IFN-β expression in response to TLR3 and TLR4 ligands [38]. Thus, even if TLR4 detects bacterial MAMPs at the cell membrane, TLR4 induces antiviral pathways when localized within endosomes [28]. In 2014, more than ten years after this discovery, a similar function has been detailed regarding TLR2 [39].
## 3. TLR2 and TLR4: The “Only” TIRAP-Dependent TLRs
Signaling through TLR4, the most investigated TLR, has been well dissected in comparison to other TLRs (Figure1). MyD88, the first identified TLR adaptor downstream of TLR4 [14], is considered to be the adaptor “of choice” for other TLRs, except TLR3. However, this MyD88-only assumption has been challenged by various studies, suggesting that TIRAP- and TRAM-dependent signaling may be used in a larger set of TLRs. In 2002, two works have revealed that TIRAP is specific to TLR2 and TLR4 [24, 40]. Recent reviews still mention these two papers [41–43]. In this section, we explore and contextualize those two hyperreferenced studies.In 2001, flagellin was identified as a ligand for TLR5 (Figure4). A year later, it was revealed that Tirap-deficient mice are still responsive to flagellin, implying that TLR5 signaling is TIRAP-independent [24]. However, TLR5 is not the only flagellin sensor. Indeed, NOD-like receptor caspase activation and recruitment domain-containing protein 4 (NLRC4 inflammasome) is very sensitive to flagellin [44] in the cytosol of myeloid cells [45]. Unfortunately, no cellular assessment was done to discriminate this in 2002, five years before the discovery that another sensor may play a compensatory role [24]. Since then, the idea that TLR5 signaling is TIRAP-independent became the norm.Figure 4
The history of Toll-like receptors and their signaling: summarized timeline of discoveries. Abbreviations: CpG-DNA: cytosine-phosphate-guanine-deoxyribo-nucleic acid; LPS: lipopolysaccharide; MyD88: myeloid differentiation primary response 88; PRRs: pattern recognition receptors; ssRNA: single-stranded ribonucleic acid; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein; TLR4/5/7/8/9: Toll-like receptor 4/5/7/8/9; TRAM: TRIF-related adaptor molecule.In 2002, it was demonstrated that NF-κB and MAPK induction downstream of TLR9 was TIRAP-independent [24]. It was shown that Tirap-deficient macrophages activate NF-κB with delayed kinetics in response to TLR2 and TLR4 agonists, but not CpG [24]. Nevertheless, according to the NF-κB assay, TLR2- and TLR4-mediated activations are fast (20 and 10 minutes, respectively), while NF-κB activation does not start before 60-minute downstream of TLR9. No intermediary time was tested to exactly evaluate if the kinetics in response to CpG is delayed or not. MAPK assays were then performed [24]. MAPKs are not activated before one hour of CpG stimulation, but the phosphorylation status of JNK and p38 is reduced downstream of TLR9 in Tirap-deficient macrophages compared with wild-type macrophages. Unfortunately, these results were not taken into consideration by the authors. Subsequently, TLR9 gained its “directly binds MyD88” notoriety [46]. Additional studies would have been needed to further our understanding of the TLR9-induced signaling through other adaptors (Figure 1).All these discoveries emerged during a very frenetic period (Figure4) where information appeared as things progressed, without the supporting data to have a better view of TLR signaling. TLR4- and MyD88-related studies were particularly favored (Figure 1).
## 4. TLR5, TLR7, TLR8, and TLR9 Are Not “Only MyD88-Dependent” TLRs
### 4.1. TLR5
TLR5 is plasma membrane-localized and recognizes flagellin from invasive motile bacteria [47]. It has been well-described that TLR5 is only Myd88-dependent for its downstream signaling [48]. Yet, Choi et al. have demonstrated that TLR5 does require TIRAP to induce NF-κB-dependent responses. Indeed, reduced Tirap gene expression in cultured colonocytes impaired the response to flagellin. Further immunoprecipitation experiments confirmed direct interaction between TLR5 and TIRAP, following flagellin exposure [49]. Of note, colonocytes represent a more relevant experimental model for TLR5 signaling studies, since they barely express NLRC4 [50]. Intriguingly, flagellin has been recently found to mediate IFN-β production in macrophages, after TLR5 internalization from the plasma membrane to endosomes [51]. In addition, TLR5 signaling was shown to be TRIF-dependent in human colonic cells [52]. TRIF directly interacts with TLR5 upon flagellin stimulation in NCM460 colonic cells [52]. In this study, TRAM also directly interacts with TLR5 in nonstimulated conditions, as opposed to TRIF. Unfortunately, this result was not taken into consideration by the authors, and more studies are required to elucidate such observation. Altogether, adaptors other than MyD88, including TIRAP and TRIF, may contribute to the induction of TLR5 downstream signaling.
### 4.2. TLR7 and TLR8
TLR7 and TLR8 are endosomal TLRs recognizing ssRNA, the reason why both are often represented together in the endosomal compartment. Additionally, TLR7 and TLR8 share common synthetic agonists, such as R-8748 (resiquimod) [53] or gardiquimod [54]. Even though they are localized in endosomes, TLR7 and TLR8 activate NF-κB and IFN I-generating pathways [55]. In 2015, by using a peptide (decoy peptide 2R9) that blocks TIRAP recruitment, Piao et al. have shown that TLR7- and TLR8-dependent NF-κB activations are TIRAP-dependent in macrophages [56]. More recently, experiments on Carp Toll-like receptor 8 (Tlr8) have disclosed that TLR8 can directly interact with the TIRAP adaptor and that such interaction is necessary for MyD88-dependent responses [57]. Regrettably, few researches have been done on TLR8 (Figure 1), and therefore, functional studies on mammalian TIRAP and TLR8 interactions are still lacking.Interestingly, TRIF engagement and IFN secretion by TLR7 require another adaptor protein, TRAM [58]. Indeed, while Tram-deficient macrophages exhibit a complete NF-κB response to the TLR7 ligand imiquimod, IFN I secretion is abolished. Whether TRAM may also play a role in TLR8 transduction has never been investigated. A potential TRAM compensatory role may explain why, in 2002, there was no impaired proliferation of Tirap-deficient splenocytes to R-848 [24]. But TRAM was discovered a year later (Figure 4), and such possibility could even not be suggested. Furthermore, downstream of TLRs, MyD88 activation, is required for cell division [59], which could explain why MyD88-deficient splenocytes show impaired proliferation to R-848 [24]. Taken together, these recent data suggest that, in addition to the known role of Myd88, TIRAP and TRAM can be involved in TLR7 and TLR8 signaling. However, one question remains: how endosomal TLR7 and TLR8 could activate both MyD88-dependent and -independent pathways? The beginning of an answer is provided by studies on TLR9 detailed as follows.
### 4.3. TLR9
TLR9 is an endosomal TLR that detects unmethylated CpG dinucleotides from viral and bacterial DNA [60] and is located in endosomes. TLR9 activation triggers NF-κB and IFN I signaling pathways [61]. TIRAP expression enhances the MyD88-dependent response mediated by TLR9 [62]. Moreover, immortalized bone marrow-derived macrophages (iBMDMs) isolated from Tirap KO (knockout) mice do not respond to ODN1668, a TLR9 agonist [56]. iBMDMs represent a useful experimental model to explore signaling, as they retain the signaling properties of primary macrophages [62]. TLR9-provoked secretion of TNF-α and IL-6 is TIRAP-dependent in iBMDMs [56]. In this study, these data were confirmed by using a decoy peptide that directly targets TIRAP. More recently, the same group has demonstrated that ODN-induced cytokine secretion and lethality are abrogated by intraperitoneally pretreating mice with the 9R34 decoy peptide, a more specific TLR9 inhibitor [63]. Finally, Tirap-deficient macrophages infected with herpes virus simplex (HSV), a natural TLR9 activator, are unable to trigger NF-κB signaling [62].The use of two structurally diverse synthetic TLR9 ligands uncovers surprising outcomes. Plasmacytoid dendritic cells do express TLR7 and TLR9 within endosomal compartments [64], which allow these cells to produce high amounts of IFN type I, in contrast to conventional dendritic cells [65]. CpG-A treatment led to increased IFN I production in mouse plasmacytoid dendritic cells, while proinflammatory cytokine release, related to NF-κB activation, was induced only in response to CpG-B [66]. The authors explained their data through distinct localization of both ligands, since CpG-A and CpG-B do not always traffic in the same way within cells. For instance, in plasmacytoid dendritic cells, CpG-A is retained in early endosomes, whereas CpG-B translocates to late endosomes and lysosomes [67].Dendritic cells are professional antigen-presenting cells, also acting as mediators between the innate and the adaptative immune systems [68]. Primary dendritic cells, namely, bone marrow-derived dendritic cells (BMDCs), represent an interesting working model, as primary BMDC cultures can be matured in a number of cell types, including dendritic cells and macrophages [69]. In BMDCs, CpG-A and CpG-B ligands are both transported to late endosomes and lysosomes, leading to NF-κB responses. In addition, conventional dendritic cells produce IFN I when stimulated with dioleoyl-3-trimethyl-ammonium propane- (DOTAP-) lipofected CpG-A, which is retained in endosomes [67]. PI(3,5)P2, abundant in late endosomes and lysosomes [70], facilitates the anchoring of TIRAP in response to CpG [71]. In plasmacytoid dendritic cells, TLR9 stimulation initiates IFN I expression in a TRIF-dependent manner [72], which was recently confirmed in macrophages [73]. But studies on the role of TRAM in endosome-mediated TLR9 responses are still missing. Taken together, these data support a model in which TLR9 functionally traffics within the cell to trigger distinct pathways, by recruiting different signaling adaptors other than Myd88, with differences related to the cell type. Most of the research on TLR9 has been done in plasmacytoid dendritic cells, specialized in antiviral responses [65]. It would be relevant to see if similar results can be observed in other cell types.
## 4.1. TLR5
TLR5 is plasma membrane-localized and recognizes flagellin from invasive motile bacteria [47]. It has been well-described that TLR5 is only Myd88-dependent for its downstream signaling [48]. Yet, Choi et al. have demonstrated that TLR5 does require TIRAP to induce NF-κB-dependent responses. Indeed, reduced Tirap gene expression in cultured colonocytes impaired the response to flagellin. Further immunoprecipitation experiments confirmed direct interaction between TLR5 and TIRAP, following flagellin exposure [49]. Of note, colonocytes represent a more relevant experimental model for TLR5 signaling studies, since they barely express NLRC4 [50]. Intriguingly, flagellin has been recently found to mediate IFN-β production in macrophages, after TLR5 internalization from the plasma membrane to endosomes [51]. In addition, TLR5 signaling was shown to be TRIF-dependent in human colonic cells [52]. TRIF directly interacts with TLR5 upon flagellin stimulation in NCM460 colonic cells [52]. In this study, TRAM also directly interacts with TLR5 in nonstimulated conditions, as opposed to TRIF. Unfortunately, this result was not taken into consideration by the authors, and more studies are required to elucidate such observation. Altogether, adaptors other than MyD88, including TIRAP and TRIF, may contribute to the induction of TLR5 downstream signaling.
## 4.2. TLR7 and TLR8
TLR7 and TLR8 are endosomal TLRs recognizing ssRNA, the reason why both are often represented together in the endosomal compartment. Additionally, TLR7 and TLR8 share common synthetic agonists, such as R-8748 (resiquimod) [53] or gardiquimod [54]. Even though they are localized in endosomes, TLR7 and TLR8 activate NF-κB and IFN I-generating pathways [55]. In 2015, by using a peptide (decoy peptide 2R9) that blocks TIRAP recruitment, Piao et al. have shown that TLR7- and TLR8-dependent NF-κB activations are TIRAP-dependent in macrophages [56]. More recently, experiments on Carp Toll-like receptor 8 (Tlr8) have disclosed that TLR8 can directly interact with the TIRAP adaptor and that such interaction is necessary for MyD88-dependent responses [57]. Regrettably, few researches have been done on TLR8 (Figure 1), and therefore, functional studies on mammalian TIRAP and TLR8 interactions are still lacking.Interestingly, TRIF engagement and IFN secretion by TLR7 require another adaptor protein, TRAM [58]. Indeed, while Tram-deficient macrophages exhibit a complete NF-κB response to the TLR7 ligand imiquimod, IFN I secretion is abolished. Whether TRAM may also play a role in TLR8 transduction has never been investigated. A potential TRAM compensatory role may explain why, in 2002, there was no impaired proliferation of Tirap-deficient splenocytes to R-848 [24]. But TRAM was discovered a year later (Figure 4), and such possibility could even not be suggested. Furthermore, downstream of TLRs, MyD88 activation, is required for cell division [59], which could explain why MyD88-deficient splenocytes show impaired proliferation to R-848 [24]. Taken together, these recent data suggest that, in addition to the known role of Myd88, TIRAP and TRAM can be involved in TLR7 and TLR8 signaling. However, one question remains: how endosomal TLR7 and TLR8 could activate both MyD88-dependent and -independent pathways? The beginning of an answer is provided by studies on TLR9 detailed as follows.
## 4.3. TLR9
TLR9 is an endosomal TLR that detects unmethylated CpG dinucleotides from viral and bacterial DNA [60] and is located in endosomes. TLR9 activation triggers NF-κB and IFN I signaling pathways [61]. TIRAP expression enhances the MyD88-dependent response mediated by TLR9 [62]. Moreover, immortalized bone marrow-derived macrophages (iBMDMs) isolated from Tirap KO (knockout) mice do not respond to ODN1668, a TLR9 agonist [56]. iBMDMs represent a useful experimental model to explore signaling, as they retain the signaling properties of primary macrophages [62]. TLR9-provoked secretion of TNF-α and IL-6 is TIRAP-dependent in iBMDMs [56]. In this study, these data were confirmed by using a decoy peptide that directly targets TIRAP. More recently, the same group has demonstrated that ODN-induced cytokine secretion and lethality are abrogated by intraperitoneally pretreating mice with the 9R34 decoy peptide, a more specific TLR9 inhibitor [63]. Finally, Tirap-deficient macrophages infected with herpes virus simplex (HSV), a natural TLR9 activator, are unable to trigger NF-κB signaling [62].The use of two structurally diverse synthetic TLR9 ligands uncovers surprising outcomes. Plasmacytoid dendritic cells do express TLR7 and TLR9 within endosomal compartments [64], which allow these cells to produce high amounts of IFN type I, in contrast to conventional dendritic cells [65]. CpG-A treatment led to increased IFN I production in mouse plasmacytoid dendritic cells, while proinflammatory cytokine release, related to NF-κB activation, was induced only in response to CpG-B [66]. The authors explained their data through distinct localization of both ligands, since CpG-A and CpG-B do not always traffic in the same way within cells. For instance, in plasmacytoid dendritic cells, CpG-A is retained in early endosomes, whereas CpG-B translocates to late endosomes and lysosomes [67].Dendritic cells are professional antigen-presenting cells, also acting as mediators between the innate and the adaptative immune systems [68]. Primary dendritic cells, namely, bone marrow-derived dendritic cells (BMDCs), represent an interesting working model, as primary BMDC cultures can be matured in a number of cell types, including dendritic cells and macrophages [69]. In BMDCs, CpG-A and CpG-B ligands are both transported to late endosomes and lysosomes, leading to NF-κB responses. In addition, conventional dendritic cells produce IFN I when stimulated with dioleoyl-3-trimethyl-ammonium propane- (DOTAP-) lipofected CpG-A, which is retained in endosomes [67]. PI(3,5)P2, abundant in late endosomes and lysosomes [70], facilitates the anchoring of TIRAP in response to CpG [71]. In plasmacytoid dendritic cells, TLR9 stimulation initiates IFN I expression in a TRIF-dependent manner [72], which was recently confirmed in macrophages [73]. But studies on the role of TRAM in endosome-mediated TLR9 responses are still missing. Taken together, these data support a model in which TLR9 functionally traffics within the cell to trigger distinct pathways, by recruiting different signaling adaptors other than Myd88, with differences related to the cell type. Most of the research on TLR9 has been done in plasmacytoid dendritic cells, specialized in antiviral responses [65]. It would be relevant to see if similar results can be observed in other cell types.
## 5. Why the Endosomal Trio TLR7/8/9 Is Believed to Be MyD88-Dependent
As opposed to IRF3, theIFN-beta-specialized transcription factor, IRF7, is less specific and promotes both IFN-alpha and IFN-beta transcriptions [74]. Like IRF3, IRF7 is phosphorylated by members of the IκB kinase family (IKKs), including IKKα, IKKβ, IKKε, and TRAF-associated NF-κB activator-binding kinase 1 (TBK1) [75]. IKKα and IKKβ are also involved in the canonical NF-κB pathway. Despite redundancy, IKKε and TBK1 are the two more specialized kinases in IRF3 phosphorylation-promoted activation [76]. Some papers have provided explanations for this preference. Indeed, IRF3 regulation requires phosphatidylinositol-5-phosphate (PI5P) [71]. PI5P, which is enriched in membranes of early endosomes during viral infection, binds to both IRF3 and TBK1 to facilitate complex formation [71]. TRAM, involved in TBK1 and IRF3 activations, binds phosphatidylinositol-3-phosphate (PIP3) and PI5P [22] and is localized to early endosomes as well. Findings on phosphoinositide-mediated effector recruitment in TLR signaling are summarized in Table 1. IRF7 interacts with MyD88 and TRAF6 [77], required for IKK engagement and IKKα- and IKKβ-induced IRF7 phosphorylation [75]. IRF7 is thus activated downstream of TLR7, TLR8, and TLR9, all recognized to “directly bind MyD88.”Table 1
Cellular compartments for TLR signaling effector recruitment.
TLR effectorRelated pathwayTLRPI lipidsCellular compartmentsCell typesReferencesTIRAPNF-κBTLR2, TLR4PI(4,5)P2Plasma membraneHuman monocytes, macrophages[28, 78]TLR4, TLR9PI(3,5)P2LysosomeBMDMs[62, 67]IFN I (via IRF7)TLR4PI3P, PI5PEarly endosomeMEFs, macrophages[17, 27]TRAMIFN I (via TRIF)Macrophages[22]TBK1TLR3, TLR4PI5PMEFs, GMDCs[71]IRF3Abbreviations: BMDMs: bone marrow-derived macrophages; GMDCs: genetically modified dendritic cells; IFN I: type I interferons; IRF3: interferon regulatory factor 3; IRF7: interferon regulatory factor 7; MEFs: mouse embryonic fibroblasts; NF-κB: nuclear factor-κB; PI: phosphatidylinositol; PI3P: phosphatidylinositol-3-phosphate; PI5P: phosphatidylinositol-5-phosphate; PI(3,5)P2: phosphatidylinositol-3,5-biphosphate; PI(4,5)P2: phosphatidylinositol-4,5-biphosphate; TBK1: TRAF-associated NF-κB activator-binding kinase 1; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein; TLR: Toll-like receptor; TRAM: TRIF-related adaptor molecule; TRIF: TIR domain-containing adaptor-inducing interferon-β.Very recently, it has been demonstrated that TIRAP is also necessary for IRF7 phosphorylation in macrophages and human plasmacytoid dendritic cells, by bridging MyD88 to TLR7 [79]. Whether TLR8 and TLR9 adopt a similar requirement for TIRAP to activate IRF7 remains to be determined. Of note, in plasmacytoid dendritic cells, the TLR9 agonist CpG-A, initiating IFN I release, colocalizes with IRF7 in early endosomes [66]. TIRAP binds to PI(4,5)P2 at the cytoplasmic membrane and to PI3P on early endosomes [17, 27, 78]. Thus, while IRF7 activation is MyD88-dependent, some recent data suggest that TIRAP may be needed for such activation.
## 6. An Emerging Model for TLR/TIRAP/MyD88 Signaling
According to an emerging TLR signaling model (Figure5), all TLRs except TLR3 are TIRAP-dependent for MyD88-mediated pathways [80]. However, one question remains: what is the biological relevance of the TIRAP bridging adaptor, knowing that all TLRs can directly bind MyD88 through TIR-TIR interactions? Answers are provided by crystallographic structural studies and by the myddosome discovery [81, 82]. The myddosome is a multiproteic and functional signaling complex, including six MyD88, four IRAK4, and four IRAK1 subunits [41, 80], triggering NF-κB activation. 3D structures reveal that each TLR4 homodimer recruits two TIRAP homodimers, each recruiting in turn four MyD88 molecules [80]. So, eight MyD88 molecules are clustered following TLR4 homodimerization, which is enough to engage a myddosome. By amplifying MyD88 engagement, TIRAP allows transduction of favorable signal downstream of TLRs. This TLR4-dependent pattern may be valid for all TLRs except TLR3, according to the authors [80] and discussed in a recent review [83].Figure 5
Emerging model for TLR signaling. Recent data suggest a new model according to which all TLRs, but TLR3, are TIRAP-dependent for MyD88-mediated pathways and TRAM-dependent for the TRIF cascade. TLR3 directly recruits the TRIF adaptor to the endosomal compartment. TRAF3: TNF receptor-associated factor 3.
## 7. Clinical Relevance
### 7.1.TIRAP Gene Polymorphisms and Pathogenesis
TLR receptors evolved before the adaptive immune system to form an indispensable first line of innate defense [84]. TLRs play key roles in homeostatic as well as in pathogenic responses in many disease settings. TLR signaling represents an important target for putative treatments. As we mentioned before, TIRAP and TRAM are essential TLR bridging adaptors, while largely neglected in the scientific literature, as opposed to Myd88 (Figure 1). Remarkably, small nucleotide polymorphisms (SNPs) of TLRs and their adaptors are associated with infections and other diseases, such as atherosclerosis, asthma, or colorectal cancer [85]. Notably, TIRAP is the most polymorphic of all adaptors, harboring at least eight nonsynonymous mutations in its coding sequence [86]. Some reported TIRAP gene SNPs are presented in Table 2. Excluding the roles of TIRAP and other adaptors in TLR responses reduces our capacity to fully comprehend the TLR-dependent regulatory mechanisms implicated in acute and chronic disorders.Table 2
Reported SNPs in theTIRAP gene.
SNPAssociated diseasesReferencesS55NMeningeal tuberculosis[87]D96NLymphoma[88]E132KAtopic dermatitis[89]S180LMalaria, sepsis, and Chagas cardiomyopathy[89–91]C539TTuberculosis susceptibility[92]Abbreviations: C: cysteine; D: aspartate; E: glutamate; K: lysine; L: leucine; N: asparagine; S: serine; SNP: single-nucleotide polymorphism; T: threonine; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein.Interestingly, theTIRAP gene S180L SNP is associated with protection against infections and autoimmune diseases, such as invasive pneumococcal disease, malaria, and systemic lupus erythematosus [88, 93]. The chronic Chagas cardiomyopathy is a tropical parasitic disease caused by the intracellular protozoan Trypanosoma cruzi [94], detected by TLR4 and TLR2/6 [95]. Up to 45% of patients with chronic infections develop cardiomyopathy, between 10 and 30 years after the initial sickness [94]. It has been reported that heterozygosity for the TIRAP S180L variant is associated with lower risk of developing chronic Chagas cardiomyopathy [91]. Mechanistically, the authors propose that the S180L variant leads to decreased signal transduction downstream of TLR2 and TLR4. Accordingly, Tirap-deficient MEFs, transfected with a plasmid encoding Tirap L180, failed to induce the NF-κB pathway [93]. In contrast, homozygosity for the S180L variant confers increased susceptibility to invasive pneumococcal disease, while the heterozygosity state provides a protective phenotype [93]. The authors speculate that S180L homozygosity results in decreased NF-κB signaling, thus aggravating susceptibility to infections.The TIRAP D96N variant is considered a loss-of-function SNP [88]. Crystal structure of TIRAP reveals that amino acids D96 and S180 are within the TIR domain interacting with the MyD88 adaptor protein [96]. A worldwide polymorphism distribution investigation proposes that the TIRAP variant S180L has been evolutionary selected to provide protection against septic shock [97]. This study supplies a world map of S180L distribution, which intriguingly correlates negatively with global sepsis incidence [98]. Knowing that all TLRs are involved in septic shock [99], these data imply that the role of TIRAP in TLR signaling related to human diseases should be better considered. Recent data by Rajpoot et al. provide new structural studies and insights on TIRAP [100]. Using an in silico approach, they have determined that the phospho-motif P-Y86 on TIRAP interacts with p38 MAPK for activation, which is worth to be validated in an in vitro model [101]. Activated p38 is a well-described proinflammatory mediator involved in acute and chronic inflammations [102]. Rajpoot et al. have also identified new TIRAP inhibitors by combining several docking tools, and their future validation may lead to novel treatments against inflammatory disorders [103]. These promising docking designs may well promote further research on the TIRAP adaptor.
### 7.2.TRAM Gene Polymorphisms and Tuberculosis
Unfortunately, few studies have reportedTRAM (also named TICAM2 for TIR domain-containing adaptor molecule 2) gene polymorphisms, since TRAM is the less investigated TLR-related adaptor (Figure 1). In 2015, one polymorphism localized in the flanking 5′ untranslated region (UTR) of TRAM was associated with tuberculosis caused by the bacteria Mycobacterium tuberculosis [104, 105]. Different components of Mycobacterium tuberculosis interact with TLRs (e.g., TLR2, TLR4, TLR8 and TLR9) in macrophages, natural killer (NK) cells, dendritic cells and T cells and and induce an appropriate immune response to overcome infection [106]. While the significance of TRAM polymorphism and how it relates to its expression are unknown, these observations point to a link between TRAM and tuberculosis infection. Interestingly, levels of TRAM expression in peripheral blood mononuclear cells (PBMCs) predict with 80% accuracy whether subjects are high or low responders to a poxvirus vector tuberculosis vaccine candidate, expressing antigen 85A [107].In BMDMs, the heat shock protein 70 (Hsp70) is derived fromMycobacterium tuberculosis signals through TLR2 and TLR4 and the TIRAP, MyD88, TRAM, and TRIF adaptor molecules [108]. More studies are needed to understand the role of TRAM adaptor in tuberculosis infection and more largely in human chronic diseases.
### 7.3. Coronavirus Disease 2019 (COVID-19)
We are facing new sanitary challenges with COVID-19, the most recent coronavirus-mediated acute respiratory illness caused by the SARS-coronavirus-2 (SARS-CoV-2). Since this viral infection causes severe symptoms through the induction of a cytokine storm, many groups have studied TLR signaling to identify therapeutic targets. Prior SARS-CoV-1 research has exposed the importance of TLR adaptors in viral responses. For example, overexpression of the SARS-CoV-1 membrane protein (M) in HEK293T cells leads to increased TIRAP and TRAM protein levels in comparison to control cells. This correlates with upregulated IFN-b- and NF-κB-related gene expressions [109]. Tram-/- mice are more susceptible to mouse-adapted SARS-CoV-1 infection, without extra mortality [110]. Genetic studies in mice have revealed Tram as a susceptibility gene for SARS-CoV-1 infection [111], underlining the importance of IFN I release during SARS-CoV-1 infection recovery. In line with this observation, decreased aging-associated number of plasmacytoid dendritic cells is associated with COVID-19 severity [112]. In addition, neutralizing autoantibodies against IFN I have been detected in patients with life-threatening COVID-19 [113]. Finally, increased TIRAP phosphorylation is detected in COVID-19-infected individuals [114]. These data suggest that both TIRAP and TRAM adaptors play a role in the control of SARS-CoV-2 infections.The above results highlight the importance to study TLR signaling and to include TLR adaptor regulatory functions to understand COVID-19 disease. The SARS-CoV genomes activate TLR7 [115]. Rare putative loss-of-function variants of the X-chromosome-located TLR7 gene are associated with altered type I IFN expression in young men with severe COVID-19 [116]. TLR8, being more specific, recognizes both SARS-CoV-2 ssRNA and derived ribonuclease T2 degradation products [117]. Thus, these recent findings call for more research on TLR7 and TLR8 (Figure 1), as targets of SARS-CoV-2 viral motifs. Clinical trials aimed to stimulate endosomal TLRs to promote IFN I production at the early steps of infection or to inhibit TLRs to reduce the NF-κB-promoted cytokine storm are ongoing. Imiquimod, a TLR7 ligand, has been proposed as an option to manage the initial stages of COVID-19 [118, 119]. Conversely, clinical studies exploring TLR blockade during COVID-19 late steps are ongoing. MERCK KGaA has initiated a randomized double-blind phase II clinical trial with M5049, a selective TLR7/8 pharmacological inhibitor initially designed to treat autoimmunity [120], for the treatment of severe symptoms of COVID-19 [121].
## 7.1.TIRAP Gene Polymorphisms and Pathogenesis
TLR receptors evolved before the adaptive immune system to form an indispensable first line of innate defense [84]. TLRs play key roles in homeostatic as well as in pathogenic responses in many disease settings. TLR signaling represents an important target for putative treatments. As we mentioned before, TIRAP and TRAM are essential TLR bridging adaptors, while largely neglected in the scientific literature, as opposed to Myd88 (Figure 1). Remarkably, small nucleotide polymorphisms (SNPs) of TLRs and their adaptors are associated with infections and other diseases, such as atherosclerosis, asthma, or colorectal cancer [85]. Notably, TIRAP is the most polymorphic of all adaptors, harboring at least eight nonsynonymous mutations in its coding sequence [86]. Some reported TIRAP gene SNPs are presented in Table 2. Excluding the roles of TIRAP and other adaptors in TLR responses reduces our capacity to fully comprehend the TLR-dependent regulatory mechanisms implicated in acute and chronic disorders.Table 2
Reported SNPs in theTIRAP gene.
SNPAssociated diseasesReferencesS55NMeningeal tuberculosis[87]D96NLymphoma[88]E132KAtopic dermatitis[89]S180LMalaria, sepsis, and Chagas cardiomyopathy[89–91]C539TTuberculosis susceptibility[92]Abbreviations: C: cysteine; D: aspartate; E: glutamate; K: lysine; L: leucine; N: asparagine; S: serine; SNP: single-nucleotide polymorphism; T: threonine; TIRAP: Toll/interleukin-1 receptor domain-containing adaptor protein.Interestingly, theTIRAP gene S180L SNP is associated with protection against infections and autoimmune diseases, such as invasive pneumococcal disease, malaria, and systemic lupus erythematosus [88, 93]. The chronic Chagas cardiomyopathy is a tropical parasitic disease caused by the intracellular protozoan Trypanosoma cruzi [94], detected by TLR4 and TLR2/6 [95]. Up to 45% of patients with chronic infections develop cardiomyopathy, between 10 and 30 years after the initial sickness [94]. It has been reported that heterozygosity for the TIRAP S180L variant is associated with lower risk of developing chronic Chagas cardiomyopathy [91]. Mechanistically, the authors propose that the S180L variant leads to decreased signal transduction downstream of TLR2 and TLR4. Accordingly, Tirap-deficient MEFs, transfected with a plasmid encoding Tirap L180, failed to induce the NF-κB pathway [93]. In contrast, homozygosity for the S180L variant confers increased susceptibility to invasive pneumococcal disease, while the heterozygosity state provides a protective phenotype [93]. The authors speculate that S180L homozygosity results in decreased NF-κB signaling, thus aggravating susceptibility to infections.The TIRAP D96N variant is considered a loss-of-function SNP [88]. Crystal structure of TIRAP reveals that amino acids D96 and S180 are within the TIR domain interacting with the MyD88 adaptor protein [96]. A worldwide polymorphism distribution investigation proposes that the TIRAP variant S180L has been evolutionary selected to provide protection against septic shock [97]. This study supplies a world map of S180L distribution, which intriguingly correlates negatively with global sepsis incidence [98]. Knowing that all TLRs are involved in septic shock [99], these data imply that the role of TIRAP in TLR signaling related to human diseases should be better considered. Recent data by Rajpoot et al. provide new structural studies and insights on TIRAP [100]. Using an in silico approach, they have determined that the phospho-motif P-Y86 on TIRAP interacts with p38 MAPK for activation, which is worth to be validated in an in vitro model [101]. Activated p38 is a well-described proinflammatory mediator involved in acute and chronic inflammations [102]. Rajpoot et al. have also identified new TIRAP inhibitors by combining several docking tools, and their future validation may lead to novel treatments against inflammatory disorders [103]. These promising docking designs may well promote further research on the TIRAP adaptor.
## 7.2.TRAM Gene Polymorphisms and Tuberculosis
Unfortunately, few studies have reportedTRAM (also named TICAM2 for TIR domain-containing adaptor molecule 2) gene polymorphisms, since TRAM is the less investigated TLR-related adaptor (Figure 1). In 2015, one polymorphism localized in the flanking 5′ untranslated region (UTR) of TRAM was associated with tuberculosis caused by the bacteria Mycobacterium tuberculosis [104, 105]. Different components of Mycobacterium tuberculosis interact with TLRs (e.g., TLR2, TLR4, TLR8 and TLR9) in macrophages, natural killer (NK) cells, dendritic cells and T cells and and induce an appropriate immune response to overcome infection [106]. While the significance of TRAM polymorphism and how it relates to its expression are unknown, these observations point to a link between TRAM and tuberculosis infection. Interestingly, levels of TRAM expression in peripheral blood mononuclear cells (PBMCs) predict with 80% accuracy whether subjects are high or low responders to a poxvirus vector tuberculosis vaccine candidate, expressing antigen 85A [107].In BMDMs, the heat shock protein 70 (Hsp70) is derived fromMycobacterium tuberculosis signals through TLR2 and TLR4 and the TIRAP, MyD88, TRAM, and TRIF adaptor molecules [108]. More studies are needed to understand the role of TRAM adaptor in tuberculosis infection and more largely in human chronic diseases.
## 7.3. Coronavirus Disease 2019 (COVID-19)
We are facing new sanitary challenges with COVID-19, the most recent coronavirus-mediated acute respiratory illness caused by the SARS-coronavirus-2 (SARS-CoV-2). Since this viral infection causes severe symptoms through the induction of a cytokine storm, many groups have studied TLR signaling to identify therapeutic targets. Prior SARS-CoV-1 research has exposed the importance of TLR adaptors in viral responses. For example, overexpression of the SARS-CoV-1 membrane protein (M) in HEK293T cells leads to increased TIRAP and TRAM protein levels in comparison to control cells. This correlates with upregulated IFN-b- and NF-κB-related gene expressions [109]. Tram-/- mice are more susceptible to mouse-adapted SARS-CoV-1 infection, without extra mortality [110]. Genetic studies in mice have revealed Tram as a susceptibility gene for SARS-CoV-1 infection [111], underlining the importance of IFN I release during SARS-CoV-1 infection recovery. In line with this observation, decreased aging-associated number of plasmacytoid dendritic cells is associated with COVID-19 severity [112]. In addition, neutralizing autoantibodies against IFN I have been detected in patients with life-threatening COVID-19 [113]. Finally, increased TIRAP phosphorylation is detected in COVID-19-infected individuals [114]. These data suggest that both TIRAP and TRAM adaptors play a role in the control of SARS-CoV-2 infections.The above results highlight the importance to study TLR signaling and to include TLR adaptor regulatory functions to understand COVID-19 disease. The SARS-CoV genomes activate TLR7 [115]. Rare putative loss-of-function variants of the X-chromosome-located TLR7 gene are associated with altered type I IFN expression in young men with severe COVID-19 [116]. TLR8, being more specific, recognizes both SARS-CoV-2 ssRNA and derived ribonuclease T2 degradation products [117]. Thus, these recent findings call for more research on TLR7 and TLR8 (Figure 1), as targets of SARS-CoV-2 viral motifs. Clinical trials aimed to stimulate endosomal TLRs to promote IFN I production at the early steps of infection or to inhibit TLRs to reduce the NF-κB-promoted cytokine storm are ongoing. Imiquimod, a TLR7 ligand, has been proposed as an option to manage the initial stages of COVID-19 [118, 119]. Conversely, clinical studies exploring TLR blockade during COVID-19 late steps are ongoing. MERCK KGaA has initiated a randomized double-blind phase II clinical trial with M5049, a selective TLR7/8 pharmacological inhibitor initially designed to treat autoimmunity [120], for the treatment of severe symptoms of COVID-19 [121].
## 8. Conclusion
In this review, we have underscored the importance of TIRAP and TRAM bridging molecules in MyD88 and TRIF recruitments. In the last few years, most research was performed on TLR4 because of the importance of its ligand LPS [122] in mediating sepsis, a worldwide public health issue [123]. Sepsis is indeed the leading cause of death in intensive care units in the United States [124]. Gram-bacterial sepsis mortality is 20 to 50% among total sepsis deaths [125]. In 2010, Chaby reported that a paper on LPS was published every two hours [123]. Therefore, TLR4 has been extensively explored in comparison to other TLRs, and studies about TLR4 signaling have been fundamental in discovering the TIRAP-MyD88 and TRAM-TRIF signaling patterns. Unexpectedly, these patterns were also revealed downstream of TLR2 [39]. Pursuing such efforts to analyze other TLRs is needed to discover treatments against novel infections, such as COVID-19. Thus, while TLR signaling is believed to be “well-described,” further studies are warranted for a complete understanding of TLR signaling pathways, including the role of TIRAP and TRAM adaptors.
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*Source: 2899271-2023-03-07.xml* | 2023 |
# Asymptotic Portfolio Strategy Based on the CEV Model with General Utility Function
**Authors:** Yu Jia; Liyun Su; Yong He; Qi Huang
**Journal:** Mathematical Problems in Engineering
(2021)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2021/2899277
---
## Abstract
The optimal investment problem is a hot field of financial risk control. The analytical solution of investment strategy can be obtained with the power function utility and exponential function utility when the stock price obeys the constant elasticity of variance (CEV) model. However, different investors have different risk preferences; it means that different investors have different utility functions. In this paper, we propose an asymptotic analysis method to obtain the asymptotic solution of investment strategy with the general utility function. The value function is expanded in the form of series, the expressions of the zero-order term and first-order term of the series expansion are derived, respectively, and the error between the asymptotic approximation and the optimal value function is calculated. Finally, the numerical examples provide comparative analysis between the analytical solution and the asymptotic solution to verify the effectiveness of the proposed method.
---
## Body
## 1. Introduction
Investment portfolio is a collection of stocks, bonds, financial derivatives, etc., held by investors or financial institutions, with the purpose of diversifying risks. Usually investment portfolio is composed of two financial assets in the market: one is risk-free assets (bank deposits, etc.) and the other is risky assets (stocks, etc.). Given timet and initial assets including various known parameters, investors want to find optimal portfolio strategy to maximize the expected wealth utility at time T. Merton proposed the optimal portfolio problem in the case of continuous time in 1969, constructed the Hamilton–Jacobi–Bellman equation (HJB equation) satisfied by the objective value function by using the principle of dynamic programming, and then obtained the optimal investment strategy under the Black–Scholes (BS) model according to the homogeneity of the utility function. However, the volatility coefficient of BS stock price model is constant, which is inconsistent with most empirical data. Cox and Ross [1] proposed a constant elasticity of variance (CEV) model to describe the stock price. The volatility is a power function of the stock price, which is no longer a constant. The CEV model is usually used to calculate the theoretical price, sensitivity, and implied volatility of options (Cox [2], Davydov [3], Detemple [4], Lo [5], Widdicks [6], and Yuen [7], and well explains the empirical deviations shown by the BS model, such as volatility smile. In the works of Beckers [8] and Emanuel and Macbeth [9], there are some theoretical arguments and empirical evidence to support the change of volatility with stock price and the negative elasticity coefficient. Gao [10] solved the optimal investment problem under the CEV model by using stochastic optimal control, Legendre transformation, and partial differential equation theories, and the analytical solutions are obtained under the power utility and exponential utility.Different investors have different risk preferences, which means that they have different utility functions. Therefore, it is necessary to consider the investment problem with general utility functions. Ma [11] provides a method to solve the general utility function; the original problem is transformed into a dual problem through dual transformation; then, the upper and lower bounds of the value function are calculated by the Monte Carlo method. By continuously narrowing the range of the upper and lower bounds, the results meeting a certain accuracy are achieved, but this method needs good programming ability and long computing time. In this paper, we expand the value function in the form of Taylor series and calculate the approximate value function which contains zero-order and first-order terms; the higher-order terms (third-order and above) are neglected as the errors.This paper considers that there are two kinds of financial assets in the financial market: one is risk-free asset (bank deposit) and the other is risk asset (stock). Based on the principle of dynamic programming, the HJB equation of the value function under the general utility function is established, and the first three terms of the Taylor series are obtained. Finally, we compare the error between the analytical solution and the asymptotic solution under the power function utility and the exponential function utility in the numerical part.
## 2. Models and Theorems
Bt represents the price of risk-free assets (bank accounts) at time t, and the equation is given by(1)dBt=rBtdt,where r is a risk-free interest rate and St represents the price of risky assets at time t, which is described by the CEV model (Lo et al. [5] and Yuen et al. [7]):(2)dStSt=μdt+kStβdWt,where μ is the expected instantaneous rate of return of the stock and satisfies the condition μ>r, kStβ is the instantaneous volatility of stock price, and β is an elastic parameter that satisfies β<0. Wt:t≥0 is a standard Brownian motion in the complete probability space ω,F,P and P is the probability. F=Ft is the right continuous filter in this space, which represents the information structure generated by Brownian motion.LetXt represent the wealth process, t∈0,T, πt represent the amount of wealth invested in risk assets, and Xt−πt represent the amount of wealth invested in risk-free assets. So, we have(3)dXt=πtdStSt+Xt−πtdBtBt,X0=x,where x is the initial wealth value. Substituting (1) and (2) into (3), the wealth process obeys the following equation:(4)dXt=πtμ−r+rXtdt+πtkStβdWt,X0=x.LetA represent the admissible strategy set, and we define the value function Jt,x,s as follows:(5)Jt,x,s:=esssupπ∈AEUTXTπ|Xtπ=x,st=s,under the boundary condition JT,x,s=UTx.Using the dynamic programming principle, the value functionJ satisfies the following Hamilton–Jacobi–Bellman (HJB) equation:(6)Jt+rxJx+μsJs+12k2s2β+2Jss+maxπμ−rπ+12π2k2s2βJxx+πk2s2β+1Jxs=0.The optimal strategyπt∗ is obtained according to the first-order maximization condition of (6):(7)πt∗=−μ−rJx+k2s2β+1Jxsk2s2βJxx.Substituting formula (7) into the partial differential equation, we obtain(8)Jt+rxJx+μsJs+12k2s2β+2Jss−μ−rJx+k2s2β+1Jxs22k2s2βJxx=0.We consider that the asymptotic solution is related to timet and is expanded with the form of Taylor series. Theoretically, the higher the order of Taylor series, the smaller the error between the asymptotic solution and the real value function. However, it needs lots of calculations to obtain the higher-order terms. Therefore, in this paper, the second order and above are looked as errors. It is worth noting that, in [12], the difference between the subsolutions J¯t,x,y and the optimal solution J¯t,x,y is in the second-order term, that is, the error term. A probabilistic argument using martingale inequalities will show that the value function lies between the constructed sub- and super-solutions.Theorem 1.
LetJ^t,x,s be the value function of formula (5) and UTx be the terminal utility function, and we define(9)J^t,x,s=UTx+T−trxUT′x−1/2k2s2βμ−r2UT′x2UT′′x,satisfy Jt,x,s−J^t,x,s≤c2T−t2,for allx,s∈0,∞×∞,0.
Proof. We expand the value function in the terms ofT−t as follows:(10)Jt,x,s:=J0x,s+T−tJ1x,s+T−t2J2x,s.
In order to make our first-order approximation consistent with the value function at the terminal timeT, we assume the terminal condition of the value function as the value of J0. Namely, note that Jt,x,s satisfies the boundary condition JT,x,s=UTx, so we have(11)J0x,s:=UTx,for allx,s∈0,∞×∞,0.
SubstitutingJ0x,s into (8), we obtain(12)−U1−2T−tU2+rxUx0+T−tUx1+T−t2Ux2+μsUs0+T−tUs1+T−t2Us2+k2s2β+22Uss0+T−tUss1+T−t2Uss2×12k2s2β1Uxx0+T−tUxx1+T−t2Uxx2×μ−rUx0+T−tUx0+T−t2Ux2+k2s2β+1Uxs0+T−tUxs1+T−t2Uxs22=0.
For convenience, we useU instead of UTx, that is, U′=UxandU″=Uxx. Collect the different terms of T−t in (12), and let the constant term equal to zero, so we can obtain the solution of J1x,s as follows:(13)J1x,s=rxU′−μ−r22k2s2βU′2U″,for allx,s∈0,∞×∞,0.
Next, we let coefficient of the termT−t equal to 0, and it follows that(14)J2x,s=12Jxx0−J1Jxx1+rxUx0Jxx1+Jx1Uxx0+μJs1Uxx0+12k2s2β+2Jss1Uxx0−12k2s2β2μ−r2Ux0Jx1+2μ−rk2s2β+1Ux0Jxs1,where(15)Jx1=rU′+rxU″−μ−r22k2s2β2U′U″2−U′2U‴U″2,Jxx1=2rU″+rxU‴−μ−r2k2s2βU′′−2U′U″U‴+U′2U″″2U″2+U′2U″2U″3,Js1=μ−r2βk2s2β+1U′2U″,Jss1=−μ−r2β2β+1k2s2β+2U′2U″,Jxs1=μ−r2βk2s2β+12U′U″2−U′2U‴U″2.
Let(16)c2≔7max1≤i≤7supx>0S∈∞,0ai+1.
Next, the classical subsolutions and optimal solutionsJ¯t,x,y and J¯t,x,y of the HJB equation will be constructed, respectively. We will prove that the value function lies between the subsolution and the optimal solution, namely, J¯t,x,y≤Jt,x,y≤J¯t,x,y.
DefineJ¯2:=c2 and J¯2:=−J¯2, and let(17)J¯:=J0+T−tJ1+T−t2J¯2,J¯:=J0+T−tJ1+T−t2J¯2,
We will prove that(18)J¯t,x,s≤Jt,x,s≤J¯t,x,s,for allt,x,s∈0,T×0,∞×∞,0.
We consider the trading strategyπ¯ affected by J¯t,x,s:(19)π¯t,x,s=−μ−rJ¯x+k2s2β+1J¯xsk2s2βJ¯xx.
Apply Ito’s formula:(20)J¯T,XTπ¯,ST−J¯t,Xtπ¯,St=∫tTJ¯t+rxJ¯x+μsJ¯s+12k2s2β+2J¯ss+μ−rπ¯+12π¯2k2s2βJ¯xx+π¯k2s2β+1J¯xsdu+∫tTπ¯ksβJ¯x+ksβ+1J¯sdWu︸local martingales.
The formula is a local martingale. Define a sequence of ending timeτnn=1∞, where τn∈t,T,τn≤τn+1,∀n,∃τn⟶T a.s. as n⟶∞. Replacing T with T∧τn, the formula of local martingale becomes(21)J¯T∧τn,XT∧τnπ¯,ST∧τn−J¯t,Xtπ¯,St=∫tT∧τnJ¯t+rxJ¯x+μsJ¯s+12k2s2β+2J¯ss+μ−rπ¯+12π¯2k2s2βJ¯xx+π¯k2s2β+1J¯xsdu+∫tT∧τnπ¯ksβJ¯x+ksβ+1J¯sdWu︸local martingales.
Since the integrand function of the first term on the right side of equation (21) is substituted into the left side of the HJB equation of the subsolution J¯, this term is nonnegative. Taking the conditional expectations on both sides of equation (21), we have(22)J¯t,x,y≤EJ¯T∧τn,XT∧τnπ¯,ST∧τnXtπ¯=x,St=s,where J¯T∧τn,XT∧τnπ¯,ST∧τn⟶J¯T,Xtπ¯,St=JTXTπ¯ a.s. n⟶∞, so(23)J¯T∧τn,XT∧τnπ¯,ST∧τn=JTXT∧τnπ¯+T∧τn−trXT∧τnπ¯JT′XT∧τnπ¯−1/2k2s2βμ−r2JT′XT∧τnπ¯2JT′′XT∧τnπ¯+c2T∧τn−t2≤JTXT∧τnπ¯+TrXT∧τnπ¯JT′XT∧τnπ¯−1/2k2s2βμ−r2JT′XT∧τnπ¯2JT′′XT∧τnπ¯+c2T2≤c3GXT∧τnπ¯.
GXT∧τnπ¯n=1∞ is an integrable random variable(see Appendix). Applying the dominance and convergence theorem, we can get the following equation:(24)EJ¯T∧τn,XT∧τnπ¯,ST∧τnXtπ¯=x,St=s→EJTXTπ¯Xtπ¯=x,St=s.a.s.
Whenn⟶∞, it follows that(25)J¯t,x,y≤EJTXTπ¯Xtπ¯=x,St=s,
According to the admissibility ofπ¯t,Xtπ¯,St, J¯t,x,s≤Jt,x,s holds.
Next, we will prove thatJt,x,s≤J¯t,x,s, where J¯ is the solution of the HJB equation. With the same method, we have(26)EJ¯T∧τn,XT∧τnπ˜,ST∧τnXtπ˜=x,St=y≤J¯t,x,y,for eachn.
From equation (23), we can prove that J¯T∧τn,XT∧τnπ˜,ST∧τn≤c3GXT∧τnπ˜, so(27)EJTXTπ¯|Xtπ¯=x,St=s≤J¯t,x,y.
We can also prove thatJt,x,s≤J¯t,x,s. So, J¯t,x,s≤Jt,x,s≤J¯t,x,s. According to the definition of J¯ and J¯, it follows that(28)J^t,x,s=JTx+T−trxJT′x−1/2k2s2βμ−r2JT′x2JT′′x.
Thus,Jt,x,s−J^t,x,s≤c2T−t2.
## 3. The Asymptotic Solution
In this paper, because there is an error between the asymptotic solution and the exact solution of the value function, the error is affected by the timet. In order to reduce the error, we divide t,T into n segments; the length of each segment is very small, and we calculate the approximation solution in each segment. Since the term of T−t2 is an error term, it is directly ignored when substituting into the value function to calculate the investment strategy. The asymptotic value function expression is given by(29)J^t,x,s=J0T,x,s+T−tJ1T,x,s.We divide0,T into two parts, named as the first part and the second part in turn; δ is the break point, δ=T/2. Note that the value function reaches the maximum value at t=T, so in the approximation process, it decreases with time from T to 0. The expression of the second part is given by(30)J^t,x,s=J0T,x,s+T−tJ1T,x,s,δ≤t≤T.BecauseJ^T,x,s=J0T,x,s=UTx, so we have(31)J^t,x,s=UTx+T−tJ1T,x,s,δ≤t≤T.Note thatt=δ is the starting time of the second part and the ending time of the first part. The value of J^t,x,s at t=δ is given by(32)J^δ,x,s=J0T,x,s+T−δJ1T,x,s.The first part of the value function is given by(33)J^t,x,s=J0δ,x,s+δ−tJ1δ,x,s,0≤t≤δ.Whent=δ, we have(34)J^δ,x,s=J0δ,x,s=Uδx.Substituting (32) into (33), we have(35)J^t,x,s=J^δ,x,s+δ−tJ1δ,x,s=J0T,x,s+T−δJ1T,x,s+δ−tJ1δ,x,s,t∈0,δ,where(36)J1δ,x,s=rxJ^xδ,x,s+μsJ^sδ,x,s+12k2s2β+2J^ssδ,x,s−12k2s2βμ−r2J^xδ,x,s2+k4s4β+2J^xsδ,x,s2J^xxδ,x,s+2μ−rk2s2β+1J^xδ,x,sJ^xsδ,x,sJ^xxδ,x,s.
## 4. Numerical Analysis
In this section, we compare the asymptotic solution with the analytic solution given by Gao [10] under power utility function and exponential utility function. The parameters are set as follows:(37)r=0.03,μ=0.12,k=16.16,β=−1,s=67,T=2,p=−4,q=0.05.First,0,T is divided into some small subintervals to satisfy 0=t0<t1<⋯<tn−1<tn=T,n=1,2,…, so the value function J^tn−1,x,s is(38)J^tn−1,x,s=J^tn,x,s+tn−tn−1J^1tn,x,s,where x,s∈0,∞×∞,0,J^T,x,s=UTx:(39)J^1tn,x,s=rxJ^x+μsJ^s+12k2s2β+2J^ss−12k2s2βμ−r2J^x2J^xx+k4s4β+2J^xs2+2μ−rk2s2β+1J^xJ^xsJ^xx,The optimal investment strategy is(40)π^tn∗=−μ−rJ^x+k2s2β+1J^xsk2s2βJ^xx,x,s∈0,∞×∞,0.When the interval oft,T is divided into n segments, the value function at the end time T is known and recursive from the end to the beginning. J^t,x,s and π^t∗ are vectors. In the process of recursion, the end of former segment is the initial position of the behind segment. The whole process can deduce the value function of arbitrary time t and the optimal strategy. According to the numerical analysis, we find the error between the asymptotic solution and analytical solution is small with both power utility function and exponential utility function.
### 4.1. Power Utility
Gao [10] gained the analytical solution of the value function with the power utility function. The basic form of the power utility function is Ux=xp/p. The value function is given by(41)Ht,x,s=Aek−2Its−2β1−pxpp,where(42)At=eλ1β2β+1+rp/1−pT−tλ2−λ1λ2−λ1e2β2λ1−λ2T−t2β+1/2β,It=λ1−λ1e2β2λ1−λ2T−t1−λ1/λ2e2β2λ1−λ2T−t,λ1,2=μ−rp±1−pμ2−r2p2β1−p.The optimal investment strategy is(43)πt=μ−rx1−pksβ21−2β1−pItμ−r.Figure1 indicates the comparison between the analytical solution and the different term of approximate solution. We find that the zero-order approximation is bigger than first-order approximation (approximation with correction).Figure 1
The impact of wealth on utility:t = 1.5 and T = 2.We also find that the first-order utility asymptotic solution (approximation with correction) is very close to the analytical solution from Figures2 and 3. The approximation error is very small when t⟶T.Figure 2
The impact of wealth on utility:t = 1.5 and T = 2.Figure 3
The impact of wealth on utility:t = 1.9 and T = 2.In Figure4 and 5, it indicates the optimal investment strategy at different time periods t with first-order (approximation with correction) and zero-order asymptotic solution, respectively. We find that the error between the asymptotic solution and the analytical solution becomes smaller when the value of time t is close to T. In order to reduce the error, a piecewise approximation is used. The result of value function is given in Figures 6 and 7 under the condition of n=4.Figure 4
The impact of wealth on portfolio:t = 1.5 and T = 2.Figure 5
The impact of wealth on portfolio:t = 1.9 and T = 2.Figure 6
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 7
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figures8 and 9 give the investment strategies with 4 sections. The difference is not obvious due to the large range.Figure 8
The impact of wealth on portfolio:t = 0, T = 2, and n = 4.Figure 9
The impact of wealth on portfolio:t = 0, T = 2, and n = 4.
### 4.2. Exponential Utility
The form of the exponential utility function isUx=−1/qe−qx; let H^t,x,s represent the value function as follows:(44)H^t,x,s=−1qe−qerT−tx+A^+k−2Its−2β,where A^=2β+1μ−r2/4rqT−t−1−e2rβt−T/2rβ and It=μ−r2/4rβq1−e2rβt−T.The optimal investment strategy is given by(45)π^t=μ−rert−Tqk2s2β1+μ−r2r1−e2rβt−T.According to equation (44), we obtain the analytical solution and compare it with the zero-order asymptotic solution and the first-order asymptotic solution (approximation with correction), which is similar to the power utility function.In Figure10, the wealth x∈60,140, the zero-order approximation is UTx, and the first-order approximation is J^x. We find that zero-order and the first-order approximation (approximation with correction) are very close to the analytical solution.Figure 10
The impact of wealth on utility:t = 1.5 and T = 2.From Figures11 and 12, we find the error becomes smaller. When time t is closer to the terminal time T, it means that the asymptotic solution is better in a short time.Figure 11
The impact of wealth on utility:t = 1.5 and T = 2.Figure 12
The impact of wealth on utility:t = 1.9 and T = 2.Figures13 and 14 are relative errors describing investment strategies, which gradually increase with the increasing of wealth. The reason for this difference is that the analytical solution is independent of the wealth value, while the asymptotic solution is related to the wealth value. It should be noted that when the time t approaches the terminal time T, the relative error will become smaller.Figure 13
The impact of wealth on portfolio:t = 1.5 and T = 2.Figure 14
The impact of wealth on portfolio:t = 1.9 and T = 2.From Figures15 and 16, the asymptotic result is close to the analytical solution, which shows that our method is effective.Figure 15
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 16
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure17 is the result of piecewise asymptotic analysis describing the relative error of investment strategy. When wealth increases, the relative error also increases. The reason for this difference is that the analytical solution is independent of the wealth value, while the asymptotic solution is related to the wealth value.Figure 17
The impact of wealth on portfolio:t = 1.5 and T = 2.In theory,n can increase infinitely. In fact, we are limited by computing power. Therefore, we give the asymptotic solution of the exponential utility function in the case of n=2 and n=4 and compare it with the analytical solution.From Figure18, the asymptotic solution of the value function can be well fitted as n=2 and n=4. Figure 19 is a part of Figure 18, where wealth x belongs to 60,140. The asymptotic solution of the value function is closer to the analytical solution and converges when n increases.Figure 18
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 19
The impact of wealth on utility:t = 0, T = 2, and n = 4.
## 4.1. Power Utility
Gao [10] gained the analytical solution of the value function with the power utility function. The basic form of the power utility function is Ux=xp/p. The value function is given by(41)Ht,x,s=Aek−2Its−2β1−pxpp,where(42)At=eλ1β2β+1+rp/1−pT−tλ2−λ1λ2−λ1e2β2λ1−λ2T−t2β+1/2β,It=λ1−λ1e2β2λ1−λ2T−t1−λ1/λ2e2β2λ1−λ2T−t,λ1,2=μ−rp±1−pμ2−r2p2β1−p.The optimal investment strategy is(43)πt=μ−rx1−pksβ21−2β1−pItμ−r.Figure1 indicates the comparison between the analytical solution and the different term of approximate solution. We find that the zero-order approximation is bigger than first-order approximation (approximation with correction).Figure 1
The impact of wealth on utility:t = 1.5 and T = 2.We also find that the first-order utility asymptotic solution (approximation with correction) is very close to the analytical solution from Figures2 and 3. The approximation error is very small when t⟶T.Figure 2
The impact of wealth on utility:t = 1.5 and T = 2.Figure 3
The impact of wealth on utility:t = 1.9 and T = 2.In Figure4 and 5, it indicates the optimal investment strategy at different time periods t with first-order (approximation with correction) and zero-order asymptotic solution, respectively. We find that the error between the asymptotic solution and the analytical solution becomes smaller when the value of time t is close to T. In order to reduce the error, a piecewise approximation is used. The result of value function is given in Figures 6 and 7 under the condition of n=4.Figure 4
The impact of wealth on portfolio:t = 1.5 and T = 2.Figure 5
The impact of wealth on portfolio:t = 1.9 and T = 2.Figure 6
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 7
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figures8 and 9 give the investment strategies with 4 sections. The difference is not obvious due to the large range.Figure 8
The impact of wealth on portfolio:t = 0, T = 2, and n = 4.Figure 9
The impact of wealth on portfolio:t = 0, T = 2, and n = 4.
## 4.2. Exponential Utility
The form of the exponential utility function isUx=−1/qe−qx; let H^t,x,s represent the value function as follows:(44)H^t,x,s=−1qe−qerT−tx+A^+k−2Its−2β,where A^=2β+1μ−r2/4rqT−t−1−e2rβt−T/2rβ and It=μ−r2/4rβq1−e2rβt−T.The optimal investment strategy is given by(45)π^t=μ−rert−Tqk2s2β1+μ−r2r1−e2rβt−T.According to equation (44), we obtain the analytical solution and compare it with the zero-order asymptotic solution and the first-order asymptotic solution (approximation with correction), which is similar to the power utility function.In Figure10, the wealth x∈60,140, the zero-order approximation is UTx, and the first-order approximation is J^x. We find that zero-order and the first-order approximation (approximation with correction) are very close to the analytical solution.Figure 10
The impact of wealth on utility:t = 1.5 and T = 2.From Figures11 and 12, we find the error becomes smaller. When time t is closer to the terminal time T, it means that the asymptotic solution is better in a short time.Figure 11
The impact of wealth on utility:t = 1.5 and T = 2.Figure 12
The impact of wealth on utility:t = 1.9 and T = 2.Figures13 and 14 are relative errors describing investment strategies, which gradually increase with the increasing of wealth. The reason for this difference is that the analytical solution is independent of the wealth value, while the asymptotic solution is related to the wealth value. It should be noted that when the time t approaches the terminal time T, the relative error will become smaller.Figure 13
The impact of wealth on portfolio:t = 1.5 and T = 2.Figure 14
The impact of wealth on portfolio:t = 1.9 and T = 2.From Figures15 and 16, the asymptotic result is close to the analytical solution, which shows that our method is effective.Figure 15
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 16
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure17 is the result of piecewise asymptotic analysis describing the relative error of investment strategy. When wealth increases, the relative error also increases. The reason for this difference is that the analytical solution is independent of the wealth value, while the asymptotic solution is related to the wealth value.Figure 17
The impact of wealth on portfolio:t = 1.5 and T = 2.In theory,n can increase infinitely. In fact, we are limited by computing power. Therefore, we give the asymptotic solution of the exponential utility function in the case of n=2 and n=4 and compare it with the analytical solution.From Figure18, the asymptotic solution of the value function can be well fitted as n=2 and n=4. Figure 19 is a part of Figure 18, where wealth x belongs to 60,140. The asymptotic solution of the value function is closer to the analytical solution and converges when n increases.Figure 18
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 19
The impact of wealth on utility:t = 0, T = 2, and n = 4.
## 5. Conclusion
This paper studies the approximation solution of HJB equation when stock price obeys the CEV model. At present, many studies have solved the exact solution of the CEV model with some special utilities, and each utility has a different exact solution, but the asymptotic solution effectively avoids this point and can be applied to general utility. From the results obtained, the asymptotic solution is significantly close to the exact solution, and the error is small, and the approximation process needs less calculation.In the future, we can try some other methods. For examples, Gariappi [13] uses the Taylor series approximations to solve the optimal investment strategy. Ma and Zheng [11] propose an efficient dual-control Monte Carlo method to compute tight lower and upper bounds of the value function for general utilities. Our analysis can be extended to solve the investment problems in the presence of transaction costs, stochastic affine interest rates, and other uncertain factors, which will involve more complicated HJB equations to solve. We leave these work for a future study.
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*Source: 2899277-2021-11-01.xml* | 2899277-2021-11-01_2899277-2021-11-01.md | 26,404 | Asymptotic Portfolio Strategy Based on the CEV Model with General Utility Function | Yu Jia; Liyun Su; Yong He; Qi Huang | Mathematical Problems in Engineering
(2021) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2021/2899277 | 2899277-2021-11-01.xml | ---
## Abstract
The optimal investment problem is a hot field of financial risk control. The analytical solution of investment strategy can be obtained with the power function utility and exponential function utility when the stock price obeys the constant elasticity of variance (CEV) model. However, different investors have different risk preferences; it means that different investors have different utility functions. In this paper, we propose an asymptotic analysis method to obtain the asymptotic solution of investment strategy with the general utility function. The value function is expanded in the form of series, the expressions of the zero-order term and first-order term of the series expansion are derived, respectively, and the error between the asymptotic approximation and the optimal value function is calculated. Finally, the numerical examples provide comparative analysis between the analytical solution and the asymptotic solution to verify the effectiveness of the proposed method.
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## Body
## 1. Introduction
Investment portfolio is a collection of stocks, bonds, financial derivatives, etc., held by investors or financial institutions, with the purpose of diversifying risks. Usually investment portfolio is composed of two financial assets in the market: one is risk-free assets (bank deposits, etc.) and the other is risky assets (stocks, etc.). Given timet and initial assets including various known parameters, investors want to find optimal portfolio strategy to maximize the expected wealth utility at time T. Merton proposed the optimal portfolio problem in the case of continuous time in 1969, constructed the Hamilton–Jacobi–Bellman equation (HJB equation) satisfied by the objective value function by using the principle of dynamic programming, and then obtained the optimal investment strategy under the Black–Scholes (BS) model according to the homogeneity of the utility function. However, the volatility coefficient of BS stock price model is constant, which is inconsistent with most empirical data. Cox and Ross [1] proposed a constant elasticity of variance (CEV) model to describe the stock price. The volatility is a power function of the stock price, which is no longer a constant. The CEV model is usually used to calculate the theoretical price, sensitivity, and implied volatility of options (Cox [2], Davydov [3], Detemple [4], Lo [5], Widdicks [6], and Yuen [7], and well explains the empirical deviations shown by the BS model, such as volatility smile. In the works of Beckers [8] and Emanuel and Macbeth [9], there are some theoretical arguments and empirical evidence to support the change of volatility with stock price and the negative elasticity coefficient. Gao [10] solved the optimal investment problem under the CEV model by using stochastic optimal control, Legendre transformation, and partial differential equation theories, and the analytical solutions are obtained under the power utility and exponential utility.Different investors have different risk preferences, which means that they have different utility functions. Therefore, it is necessary to consider the investment problem with general utility functions. Ma [11] provides a method to solve the general utility function; the original problem is transformed into a dual problem through dual transformation; then, the upper and lower bounds of the value function are calculated by the Monte Carlo method. By continuously narrowing the range of the upper and lower bounds, the results meeting a certain accuracy are achieved, but this method needs good programming ability and long computing time. In this paper, we expand the value function in the form of Taylor series and calculate the approximate value function which contains zero-order and first-order terms; the higher-order terms (third-order and above) are neglected as the errors.This paper considers that there are two kinds of financial assets in the financial market: one is risk-free asset (bank deposit) and the other is risk asset (stock). Based on the principle of dynamic programming, the HJB equation of the value function under the general utility function is established, and the first three terms of the Taylor series are obtained. Finally, we compare the error between the analytical solution and the asymptotic solution under the power function utility and the exponential function utility in the numerical part.
## 2. Models and Theorems
Bt represents the price of risk-free assets (bank accounts) at time t, and the equation is given by(1)dBt=rBtdt,where r is a risk-free interest rate and St represents the price of risky assets at time t, which is described by the CEV model (Lo et al. [5] and Yuen et al. [7]):(2)dStSt=μdt+kStβdWt,where μ is the expected instantaneous rate of return of the stock and satisfies the condition μ>r, kStβ is the instantaneous volatility of stock price, and β is an elastic parameter that satisfies β<0. Wt:t≥0 is a standard Brownian motion in the complete probability space ω,F,P and P is the probability. F=Ft is the right continuous filter in this space, which represents the information structure generated by Brownian motion.LetXt represent the wealth process, t∈0,T, πt represent the amount of wealth invested in risk assets, and Xt−πt represent the amount of wealth invested in risk-free assets. So, we have(3)dXt=πtdStSt+Xt−πtdBtBt,X0=x,where x is the initial wealth value. Substituting (1) and (2) into (3), the wealth process obeys the following equation:(4)dXt=πtμ−r+rXtdt+πtkStβdWt,X0=x.LetA represent the admissible strategy set, and we define the value function Jt,x,s as follows:(5)Jt,x,s:=esssupπ∈AEUTXTπ|Xtπ=x,st=s,under the boundary condition JT,x,s=UTx.Using the dynamic programming principle, the value functionJ satisfies the following Hamilton–Jacobi–Bellman (HJB) equation:(6)Jt+rxJx+μsJs+12k2s2β+2Jss+maxπμ−rπ+12π2k2s2βJxx+πk2s2β+1Jxs=0.The optimal strategyπt∗ is obtained according to the first-order maximization condition of (6):(7)πt∗=−μ−rJx+k2s2β+1Jxsk2s2βJxx.Substituting formula (7) into the partial differential equation, we obtain(8)Jt+rxJx+μsJs+12k2s2β+2Jss−μ−rJx+k2s2β+1Jxs22k2s2βJxx=0.We consider that the asymptotic solution is related to timet and is expanded with the form of Taylor series. Theoretically, the higher the order of Taylor series, the smaller the error between the asymptotic solution and the real value function. However, it needs lots of calculations to obtain the higher-order terms. Therefore, in this paper, the second order and above are looked as errors. It is worth noting that, in [12], the difference between the subsolutions J¯t,x,y and the optimal solution J¯t,x,y is in the second-order term, that is, the error term. A probabilistic argument using martingale inequalities will show that the value function lies between the constructed sub- and super-solutions.Theorem 1.
LetJ^t,x,s be the value function of formula (5) and UTx be the terminal utility function, and we define(9)J^t,x,s=UTx+T−trxUT′x−1/2k2s2βμ−r2UT′x2UT′′x,satisfy Jt,x,s−J^t,x,s≤c2T−t2,for allx,s∈0,∞×∞,0.
Proof. We expand the value function in the terms ofT−t as follows:(10)Jt,x,s:=J0x,s+T−tJ1x,s+T−t2J2x,s.
In order to make our first-order approximation consistent with the value function at the terminal timeT, we assume the terminal condition of the value function as the value of J0. Namely, note that Jt,x,s satisfies the boundary condition JT,x,s=UTx, so we have(11)J0x,s:=UTx,for allx,s∈0,∞×∞,0.
SubstitutingJ0x,s into (8), we obtain(12)−U1−2T−tU2+rxUx0+T−tUx1+T−t2Ux2+μsUs0+T−tUs1+T−t2Us2+k2s2β+22Uss0+T−tUss1+T−t2Uss2×12k2s2β1Uxx0+T−tUxx1+T−t2Uxx2×μ−rUx0+T−tUx0+T−t2Ux2+k2s2β+1Uxs0+T−tUxs1+T−t2Uxs22=0.
For convenience, we useU instead of UTx, that is, U′=UxandU″=Uxx. Collect the different terms of T−t in (12), and let the constant term equal to zero, so we can obtain the solution of J1x,s as follows:(13)J1x,s=rxU′−μ−r22k2s2βU′2U″,for allx,s∈0,∞×∞,0.
Next, we let coefficient of the termT−t equal to 0, and it follows that(14)J2x,s=12Jxx0−J1Jxx1+rxUx0Jxx1+Jx1Uxx0+μJs1Uxx0+12k2s2β+2Jss1Uxx0−12k2s2β2μ−r2Ux0Jx1+2μ−rk2s2β+1Ux0Jxs1,where(15)Jx1=rU′+rxU″−μ−r22k2s2β2U′U″2−U′2U‴U″2,Jxx1=2rU″+rxU‴−μ−r2k2s2βU′′−2U′U″U‴+U′2U″″2U″2+U′2U″2U″3,Js1=μ−r2βk2s2β+1U′2U″,Jss1=−μ−r2β2β+1k2s2β+2U′2U″,Jxs1=μ−r2βk2s2β+12U′U″2−U′2U‴U″2.
Let(16)c2≔7max1≤i≤7supx>0S∈∞,0ai+1.
Next, the classical subsolutions and optimal solutionsJ¯t,x,y and J¯t,x,y of the HJB equation will be constructed, respectively. We will prove that the value function lies between the subsolution and the optimal solution, namely, J¯t,x,y≤Jt,x,y≤J¯t,x,y.
DefineJ¯2:=c2 and J¯2:=−J¯2, and let(17)J¯:=J0+T−tJ1+T−t2J¯2,J¯:=J0+T−tJ1+T−t2J¯2,
We will prove that(18)J¯t,x,s≤Jt,x,s≤J¯t,x,s,for allt,x,s∈0,T×0,∞×∞,0.
We consider the trading strategyπ¯ affected by J¯t,x,s:(19)π¯t,x,s=−μ−rJ¯x+k2s2β+1J¯xsk2s2βJ¯xx.
Apply Ito’s formula:(20)J¯T,XTπ¯,ST−J¯t,Xtπ¯,St=∫tTJ¯t+rxJ¯x+μsJ¯s+12k2s2β+2J¯ss+μ−rπ¯+12π¯2k2s2βJ¯xx+π¯k2s2β+1J¯xsdu+∫tTπ¯ksβJ¯x+ksβ+1J¯sdWu︸local martingales.
The formula is a local martingale. Define a sequence of ending timeτnn=1∞, where τn∈t,T,τn≤τn+1,∀n,∃τn⟶T a.s. as n⟶∞. Replacing T with T∧τn, the formula of local martingale becomes(21)J¯T∧τn,XT∧τnπ¯,ST∧τn−J¯t,Xtπ¯,St=∫tT∧τnJ¯t+rxJ¯x+μsJ¯s+12k2s2β+2J¯ss+μ−rπ¯+12π¯2k2s2βJ¯xx+π¯k2s2β+1J¯xsdu+∫tT∧τnπ¯ksβJ¯x+ksβ+1J¯sdWu︸local martingales.
Since the integrand function of the first term on the right side of equation (21) is substituted into the left side of the HJB equation of the subsolution J¯, this term is nonnegative. Taking the conditional expectations on both sides of equation (21), we have(22)J¯t,x,y≤EJ¯T∧τn,XT∧τnπ¯,ST∧τnXtπ¯=x,St=s,where J¯T∧τn,XT∧τnπ¯,ST∧τn⟶J¯T,Xtπ¯,St=JTXTπ¯ a.s. n⟶∞, so(23)J¯T∧τn,XT∧τnπ¯,ST∧τn=JTXT∧τnπ¯+T∧τn−trXT∧τnπ¯JT′XT∧τnπ¯−1/2k2s2βμ−r2JT′XT∧τnπ¯2JT′′XT∧τnπ¯+c2T∧τn−t2≤JTXT∧τnπ¯+TrXT∧τnπ¯JT′XT∧τnπ¯−1/2k2s2βμ−r2JT′XT∧τnπ¯2JT′′XT∧τnπ¯+c2T2≤c3GXT∧τnπ¯.
GXT∧τnπ¯n=1∞ is an integrable random variable(see Appendix). Applying the dominance and convergence theorem, we can get the following equation:(24)EJ¯T∧τn,XT∧τnπ¯,ST∧τnXtπ¯=x,St=s→EJTXTπ¯Xtπ¯=x,St=s.a.s.
Whenn⟶∞, it follows that(25)J¯t,x,y≤EJTXTπ¯Xtπ¯=x,St=s,
According to the admissibility ofπ¯t,Xtπ¯,St, J¯t,x,s≤Jt,x,s holds.
Next, we will prove thatJt,x,s≤J¯t,x,s, where J¯ is the solution of the HJB equation. With the same method, we have(26)EJ¯T∧τn,XT∧τnπ˜,ST∧τnXtπ˜=x,St=y≤J¯t,x,y,for eachn.
From equation (23), we can prove that J¯T∧τn,XT∧τnπ˜,ST∧τn≤c3GXT∧τnπ˜, so(27)EJTXTπ¯|Xtπ¯=x,St=s≤J¯t,x,y.
We can also prove thatJt,x,s≤J¯t,x,s. So, J¯t,x,s≤Jt,x,s≤J¯t,x,s. According to the definition of J¯ and J¯, it follows that(28)J^t,x,s=JTx+T−trxJT′x−1/2k2s2βμ−r2JT′x2JT′′x.
Thus,Jt,x,s−J^t,x,s≤c2T−t2.
## 3. The Asymptotic Solution
In this paper, because there is an error between the asymptotic solution and the exact solution of the value function, the error is affected by the timet. In order to reduce the error, we divide t,T into n segments; the length of each segment is very small, and we calculate the approximation solution in each segment. Since the term of T−t2 is an error term, it is directly ignored when substituting into the value function to calculate the investment strategy. The asymptotic value function expression is given by(29)J^t,x,s=J0T,x,s+T−tJ1T,x,s.We divide0,T into two parts, named as the first part and the second part in turn; δ is the break point, δ=T/2. Note that the value function reaches the maximum value at t=T, so in the approximation process, it decreases with time from T to 0. The expression of the second part is given by(30)J^t,x,s=J0T,x,s+T−tJ1T,x,s,δ≤t≤T.BecauseJ^T,x,s=J0T,x,s=UTx, so we have(31)J^t,x,s=UTx+T−tJ1T,x,s,δ≤t≤T.Note thatt=δ is the starting time of the second part and the ending time of the first part. The value of J^t,x,s at t=δ is given by(32)J^δ,x,s=J0T,x,s+T−δJ1T,x,s.The first part of the value function is given by(33)J^t,x,s=J0δ,x,s+δ−tJ1δ,x,s,0≤t≤δ.Whent=δ, we have(34)J^δ,x,s=J0δ,x,s=Uδx.Substituting (32) into (33), we have(35)J^t,x,s=J^δ,x,s+δ−tJ1δ,x,s=J0T,x,s+T−δJ1T,x,s+δ−tJ1δ,x,s,t∈0,δ,where(36)J1δ,x,s=rxJ^xδ,x,s+μsJ^sδ,x,s+12k2s2β+2J^ssδ,x,s−12k2s2βμ−r2J^xδ,x,s2+k4s4β+2J^xsδ,x,s2J^xxδ,x,s+2μ−rk2s2β+1J^xδ,x,sJ^xsδ,x,sJ^xxδ,x,s.
## 4. Numerical Analysis
In this section, we compare the asymptotic solution with the analytic solution given by Gao [10] under power utility function and exponential utility function. The parameters are set as follows:(37)r=0.03,μ=0.12,k=16.16,β=−1,s=67,T=2,p=−4,q=0.05.First,0,T is divided into some small subintervals to satisfy 0=t0<t1<⋯<tn−1<tn=T,n=1,2,…, so the value function J^tn−1,x,s is(38)J^tn−1,x,s=J^tn,x,s+tn−tn−1J^1tn,x,s,where x,s∈0,∞×∞,0,J^T,x,s=UTx:(39)J^1tn,x,s=rxJ^x+μsJ^s+12k2s2β+2J^ss−12k2s2βμ−r2J^x2J^xx+k4s4β+2J^xs2+2μ−rk2s2β+1J^xJ^xsJ^xx,The optimal investment strategy is(40)π^tn∗=−μ−rJ^x+k2s2β+1J^xsk2s2βJ^xx,x,s∈0,∞×∞,0.When the interval oft,T is divided into n segments, the value function at the end time T is known and recursive from the end to the beginning. J^t,x,s and π^t∗ are vectors. In the process of recursion, the end of former segment is the initial position of the behind segment. The whole process can deduce the value function of arbitrary time t and the optimal strategy. According to the numerical analysis, we find the error between the asymptotic solution and analytical solution is small with both power utility function and exponential utility function.
### 4.1. Power Utility
Gao [10] gained the analytical solution of the value function with the power utility function. The basic form of the power utility function is Ux=xp/p. The value function is given by(41)Ht,x,s=Aek−2Its−2β1−pxpp,where(42)At=eλ1β2β+1+rp/1−pT−tλ2−λ1λ2−λ1e2β2λ1−λ2T−t2β+1/2β,It=λ1−λ1e2β2λ1−λ2T−t1−λ1/λ2e2β2λ1−λ2T−t,λ1,2=μ−rp±1−pμ2−r2p2β1−p.The optimal investment strategy is(43)πt=μ−rx1−pksβ21−2β1−pItμ−r.Figure1 indicates the comparison between the analytical solution and the different term of approximate solution. We find that the zero-order approximation is bigger than first-order approximation (approximation with correction).Figure 1
The impact of wealth on utility:t = 1.5 and T = 2.We also find that the first-order utility asymptotic solution (approximation with correction) is very close to the analytical solution from Figures2 and 3. The approximation error is very small when t⟶T.Figure 2
The impact of wealth on utility:t = 1.5 and T = 2.Figure 3
The impact of wealth on utility:t = 1.9 and T = 2.In Figure4 and 5, it indicates the optimal investment strategy at different time periods t with first-order (approximation with correction) and zero-order asymptotic solution, respectively. We find that the error between the asymptotic solution and the analytical solution becomes smaller when the value of time t is close to T. In order to reduce the error, a piecewise approximation is used. The result of value function is given in Figures 6 and 7 under the condition of n=4.Figure 4
The impact of wealth on portfolio:t = 1.5 and T = 2.Figure 5
The impact of wealth on portfolio:t = 1.9 and T = 2.Figure 6
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 7
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figures8 and 9 give the investment strategies with 4 sections. The difference is not obvious due to the large range.Figure 8
The impact of wealth on portfolio:t = 0, T = 2, and n = 4.Figure 9
The impact of wealth on portfolio:t = 0, T = 2, and n = 4.
### 4.2. Exponential Utility
The form of the exponential utility function isUx=−1/qe−qx; let H^t,x,s represent the value function as follows:(44)H^t,x,s=−1qe−qerT−tx+A^+k−2Its−2β,where A^=2β+1μ−r2/4rqT−t−1−e2rβt−T/2rβ and It=μ−r2/4rβq1−e2rβt−T.The optimal investment strategy is given by(45)π^t=μ−rert−Tqk2s2β1+μ−r2r1−e2rβt−T.According to equation (44), we obtain the analytical solution and compare it with the zero-order asymptotic solution and the first-order asymptotic solution (approximation with correction), which is similar to the power utility function.In Figure10, the wealth x∈60,140, the zero-order approximation is UTx, and the first-order approximation is J^x. We find that zero-order and the first-order approximation (approximation with correction) are very close to the analytical solution.Figure 10
The impact of wealth on utility:t = 1.5 and T = 2.From Figures11 and 12, we find the error becomes smaller. When time t is closer to the terminal time T, it means that the asymptotic solution is better in a short time.Figure 11
The impact of wealth on utility:t = 1.5 and T = 2.Figure 12
The impact of wealth on utility:t = 1.9 and T = 2.Figures13 and 14 are relative errors describing investment strategies, which gradually increase with the increasing of wealth. The reason for this difference is that the analytical solution is independent of the wealth value, while the asymptotic solution is related to the wealth value. It should be noted that when the time t approaches the terminal time T, the relative error will become smaller.Figure 13
The impact of wealth on portfolio:t = 1.5 and T = 2.Figure 14
The impact of wealth on portfolio:t = 1.9 and T = 2.From Figures15 and 16, the asymptotic result is close to the analytical solution, which shows that our method is effective.Figure 15
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 16
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure17 is the result of piecewise asymptotic analysis describing the relative error of investment strategy. When wealth increases, the relative error also increases. The reason for this difference is that the analytical solution is independent of the wealth value, while the asymptotic solution is related to the wealth value.Figure 17
The impact of wealth on portfolio:t = 1.5 and T = 2.In theory,n can increase infinitely. In fact, we are limited by computing power. Therefore, we give the asymptotic solution of the exponential utility function in the case of n=2 and n=4 and compare it with the analytical solution.From Figure18, the asymptotic solution of the value function can be well fitted as n=2 and n=4. Figure 19 is a part of Figure 18, where wealth x belongs to 60,140. The asymptotic solution of the value function is closer to the analytical solution and converges when n increases.Figure 18
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 19
The impact of wealth on utility:t = 0, T = 2, and n = 4.
## 4.1. Power Utility
Gao [10] gained the analytical solution of the value function with the power utility function. The basic form of the power utility function is Ux=xp/p. The value function is given by(41)Ht,x,s=Aek−2Its−2β1−pxpp,where(42)At=eλ1β2β+1+rp/1−pT−tλ2−λ1λ2−λ1e2β2λ1−λ2T−t2β+1/2β,It=λ1−λ1e2β2λ1−λ2T−t1−λ1/λ2e2β2λ1−λ2T−t,λ1,2=μ−rp±1−pμ2−r2p2β1−p.The optimal investment strategy is(43)πt=μ−rx1−pksβ21−2β1−pItμ−r.Figure1 indicates the comparison between the analytical solution and the different term of approximate solution. We find that the zero-order approximation is bigger than first-order approximation (approximation with correction).Figure 1
The impact of wealth on utility:t = 1.5 and T = 2.We also find that the first-order utility asymptotic solution (approximation with correction) is very close to the analytical solution from Figures2 and 3. The approximation error is very small when t⟶T.Figure 2
The impact of wealth on utility:t = 1.5 and T = 2.Figure 3
The impact of wealth on utility:t = 1.9 and T = 2.In Figure4 and 5, it indicates the optimal investment strategy at different time periods t with first-order (approximation with correction) and zero-order asymptotic solution, respectively. We find that the error between the asymptotic solution and the analytical solution becomes smaller when the value of time t is close to T. In order to reduce the error, a piecewise approximation is used. The result of value function is given in Figures 6 and 7 under the condition of n=4.Figure 4
The impact of wealth on portfolio:t = 1.5 and T = 2.Figure 5
The impact of wealth on portfolio:t = 1.9 and T = 2.Figure 6
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 7
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figures8 and 9 give the investment strategies with 4 sections. The difference is not obvious due to the large range.Figure 8
The impact of wealth on portfolio:t = 0, T = 2, and n = 4.Figure 9
The impact of wealth on portfolio:t = 0, T = 2, and n = 4.
## 4.2. Exponential Utility
The form of the exponential utility function isUx=−1/qe−qx; let H^t,x,s represent the value function as follows:(44)H^t,x,s=−1qe−qerT−tx+A^+k−2Its−2β,where A^=2β+1μ−r2/4rqT−t−1−e2rβt−T/2rβ and It=μ−r2/4rβq1−e2rβt−T.The optimal investment strategy is given by(45)π^t=μ−rert−Tqk2s2β1+μ−r2r1−e2rβt−T.According to equation (44), we obtain the analytical solution and compare it with the zero-order asymptotic solution and the first-order asymptotic solution (approximation with correction), which is similar to the power utility function.In Figure10, the wealth x∈60,140, the zero-order approximation is UTx, and the first-order approximation is J^x. We find that zero-order and the first-order approximation (approximation with correction) are very close to the analytical solution.Figure 10
The impact of wealth on utility:t = 1.5 and T = 2.From Figures11 and 12, we find the error becomes smaller. When time t is closer to the terminal time T, it means that the asymptotic solution is better in a short time.Figure 11
The impact of wealth on utility:t = 1.5 and T = 2.Figure 12
The impact of wealth on utility:t = 1.9 and T = 2.Figures13 and 14 are relative errors describing investment strategies, which gradually increase with the increasing of wealth. The reason for this difference is that the analytical solution is independent of the wealth value, while the asymptotic solution is related to the wealth value. It should be noted that when the time t approaches the terminal time T, the relative error will become smaller.Figure 13
The impact of wealth on portfolio:t = 1.5 and T = 2.Figure 14
The impact of wealth on portfolio:t = 1.9 and T = 2.From Figures15 and 16, the asymptotic result is close to the analytical solution, which shows that our method is effective.Figure 15
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 16
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure17 is the result of piecewise asymptotic analysis describing the relative error of investment strategy. When wealth increases, the relative error also increases. The reason for this difference is that the analytical solution is independent of the wealth value, while the asymptotic solution is related to the wealth value.Figure 17
The impact of wealth on portfolio:t = 1.5 and T = 2.In theory,n can increase infinitely. In fact, we are limited by computing power. Therefore, we give the asymptotic solution of the exponential utility function in the case of n=2 and n=4 and compare it with the analytical solution.From Figure18, the asymptotic solution of the value function can be well fitted as n=2 and n=4. Figure 19 is a part of Figure 18, where wealth x belongs to 60,140. The asymptotic solution of the value function is closer to the analytical solution and converges when n increases.Figure 18
The impact of wealth on utility:t = 0, T = 2, and n = 4.Figure 19
The impact of wealth on utility:t = 0, T = 2, and n = 4.
## 5. Conclusion
This paper studies the approximation solution of HJB equation when stock price obeys the CEV model. At present, many studies have solved the exact solution of the CEV model with some special utilities, and each utility has a different exact solution, but the asymptotic solution effectively avoids this point and can be applied to general utility. From the results obtained, the asymptotic solution is significantly close to the exact solution, and the error is small, and the approximation process needs less calculation.In the future, we can try some other methods. For examples, Gariappi [13] uses the Taylor series approximations to solve the optimal investment strategy. Ma and Zheng [11] propose an efficient dual-control Monte Carlo method to compute tight lower and upper bounds of the value function for general utilities. Our analysis can be extended to solve the investment problems in the presence of transaction costs, stochastic affine interest rates, and other uncertain factors, which will involve more complicated HJB equations to solve. We leave these work for a future study.
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*Source: 2899277-2021-11-01.xml* | 2021 |
# Haematological Features of White Rats(Rattus norvegicus) Infected with S. pyogenes and Administered with Probiotics (Yogurt)
**Authors:** Novina Rahmawati; Maimun Syukri; Darmawi Darmawi; Indra Zachreini; Utari Zulfiani; Muhammad Yusuf; Rinaldi Idroes
**Journal:** The Scientific World Journal
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2899462
---
## Abstract
This study aimed to study the inhibition activity of lactic acid bacteria probiotics deriving from Acehnese fermented Etawa goat’s milk (yogurt) againstStreptococcus pyogenes bacterial infection in rats (Rattus norvegicus). Haematological analysis of the rats’ blood was performed on the following parameters: platelets, leukocytes, lymphocytes, neutrophils, and monocytes, where the data were further processed using ANOVA and Duncan’s test with a confidence level of 95% (0.05). The results revealed that administering yogurt containing probiotics could reduce infections in the throats of rats caused by S. pyogenes. Based on the haematology examination, the probiotic yogurt could maintain the number of platelets, leukocytes, lymphocytes, neutrophils, and monocytes. Statistical significance was obtained when the infected rats were administered with a ±1.00 mL/day dose for seven days of treatment (p<0.05).
---
## Body
## 1. Introduction
The use of antibiotics to treat infectious diseases in humans could cause adverse reactions and induce the emergence of antibiotic-resistant pathogens [1]. One of the diseases commonly treated using antibiotics is a sore throat caused by irritation or inflammation in pharyngitis or tonsillitis [2]. It is due to the fact that the disease is a common manifestation of Streptococcus pyogenes bacterial infection [2]. To overcome the antibiotic resistance in streptococci, the administration of probiotics (i.e., Lactobacillus probiotics) could be used as an integrative therapy [3]. Lactic acid bacteria are microflora classified as probiotics which could be obtained from fermentation [4]. The isolated lactic acid bacteria have several advantages as a probiotic including their survivability, reproducibility, and secretion of antibacterial substances (which could inhibit enteric gut bacteria) [5]. Lactobacillus and Bifidobacteria are the most common lactic acid bacteria used as probiotic microorganisms [5].Food and beverages containing probiotics have many health benefits, such as helping the digestive system process and absorption of nutrients [6]. Moreover, such probiotic products could inhibit the pathogen in the digestive tract (i.e., Escherichia coli, Streptococcus aureus, Salmonella typhimurium, Vibrio cholerae, and Mycobacterium tuberculosis) [6]. In addition, consuming food or beverages with probiotics could prevent constipation, cancer, excessive blood cholesterol level, lactose intolerance, and increase immune response [6]. Based on a previous report [7], ten local lactic acid bacteria species were extracted from raw beef showing probiotic properties by producing antimicrobial compounds. Another source to obtain lactic acid bacteria is yogurt, in which the yogurt made of Etawa goat’s milk has been reported to contain Gram-positive isolates with a negative catalase test [8]. Further investigation under the microscope in the foregoing report revealed the shape of the bacillus cells suggesting the milk isolate contained Lactobacillus bacteria [8].Nonetheless, the administration of probiotic bacteria via the oral route was reported to affect the body’s metabolic system [9], including the haematological status [10]. Dysregulation of blood parameters could adversely affect blood function. Hence, it is important for researchers to investigate the effect of probiotic administration on haematological blood parameters including the number of platelets, leukocytes, lymphocytes, neutrophils, and monocytes.Herein, the objective of this study is to investigate the ability of local probiotics (in the form of lactic acid bacteria) derived from fermented Etawa goat’s milk (yogurt) procured from Kopelma Village, Banda Aceh, Aceh Province, Indonesia, to treatS. pyogenes infection-induced inflammation in the throat of the rat model. The changes of haematological profiles (platelets, leukocytes, lymphocytes, neutrophils, and monocytes) following the probiotic therapy were also investigated.
## 2. Materials and Methods
### 2.1. Experiment Animals and Feeding
Twenty male rats (Rattus norvegicus) aged 5-6 weeks with a bodyweight range of 115–135 grams were obtained from the Test Animal Laboratory, Faculty of Veterinary Medicine, Universitas Syiah Kuala. The rats were divided into four treatment groups comprising five rats/group (K0 (negative control) and K1-3). Before treatment, all rats were acclimated for three days and fed ad libitum. The treatment process is presented in Table 1.Table 1
Treatment group on experimental rats [11].
No.Rat groupsTreatment1Negative control (K0)Normal rats were only fed and aquadest. A blood test was conducted on the 1st, 7th, and 14th days.2Bacterial infection (K1)Rats were fed and infected withS. pyogenes bacteria in the throat on the first day. A blood test was conducted on the 1st, 7th, and 14th days.3Administering yogurt and bacterial infection (K2)Rats were fed and infected withS. pyogenes bacteria in the throat on the first day. They were also administered with yogurt for 14 days at a dose of ±1.00 mL. A blood test was conducted on the 1st, 7th, and 14th days.4Administering yogurt and bacterial infection (K3)Rats were fed and administered with yogurt at a dose of ±1.00 mL for seven days, then,S. pyogenes bacteria were infected in the throat. A blood test was conducted on the 1st, 7th, and 14th days.
### 2.2.S. pyogenes Bacterial Infection
The rats were prepared to be infected withS. pyogenes bacteria. The culture of S. pyogenes (ATCC 12344) used was collected from the Laboratory of Oral Biology, Faculty of Dentistry, Universitas Indonesia, Jakarta. S. pyogenes infection was carried out using a population of 0.5 McFarland bacteria (1.5 × 108 CFU/mL) administered orally (swab) using a probe.
### 2.3. Yogurt Administration
Yogurt was orally administrated to the K2 group on the second day for the following 13 days, whilst the administration was carried out on the first day for the following 7 days for the K3 group. The administration was carried out by force-feeding 1 mL yogurt via injection to the mouth of the rat into the throat using a gastric probe.
### 2.4. Blood Sampling and Hematological Analysis
Blood samples were drawn from the rat through the lateral vein in the tail [12], and taken on days 1, 7, and 14. Each sample was inserted in a tube which had been priorly added with EDTA and subsequently analysed for S. pyogenes parameters [10]. Haematological observation was performed on the blood components including the number of platelets, leukocytes, lymphocytes, neutrophils, and monocytes.
### 2.5. Data Analysis
The data obtained in this study were analysed statistically using ANOVA (analysis of variance) after the Shapiro–Wilk normality test. The post hoc Duncan test was then performed with a 95% confidence interval (CI), following the suggestion from previous reports [13]. All analyses were carried out using the SPSS software (SPSS Inc., Chicago, IL, USA).
## 2.1. Experiment Animals and Feeding
Twenty male rats (Rattus norvegicus) aged 5-6 weeks with a bodyweight range of 115–135 grams were obtained from the Test Animal Laboratory, Faculty of Veterinary Medicine, Universitas Syiah Kuala. The rats were divided into four treatment groups comprising five rats/group (K0 (negative control) and K1-3). Before treatment, all rats were acclimated for three days and fed ad libitum. The treatment process is presented in Table 1.Table 1
Treatment group on experimental rats [11].
No.Rat groupsTreatment1Negative control (K0)Normal rats were only fed and aquadest. A blood test was conducted on the 1st, 7th, and 14th days.2Bacterial infection (K1)Rats were fed and infected withS. pyogenes bacteria in the throat on the first day. A blood test was conducted on the 1st, 7th, and 14th days.3Administering yogurt and bacterial infection (K2)Rats were fed and infected withS. pyogenes bacteria in the throat on the first day. They were also administered with yogurt for 14 days at a dose of ±1.00 mL. A blood test was conducted on the 1st, 7th, and 14th days.4Administering yogurt and bacterial infection (K3)Rats were fed and administered with yogurt at a dose of ±1.00 mL for seven days, then,S. pyogenes bacteria were infected in the throat. A blood test was conducted on the 1st, 7th, and 14th days.
## 2.2.S. pyogenes Bacterial Infection
The rats were prepared to be infected withS. pyogenes bacteria. The culture of S. pyogenes (ATCC 12344) used was collected from the Laboratory of Oral Biology, Faculty of Dentistry, Universitas Indonesia, Jakarta. S. pyogenes infection was carried out using a population of 0.5 McFarland bacteria (1.5 × 108 CFU/mL) administered orally (swab) using a probe.
## 2.3. Yogurt Administration
Yogurt was orally administrated to the K2 group on the second day for the following 13 days, whilst the administration was carried out on the first day for the following 7 days for the K3 group. The administration was carried out by force-feeding 1 mL yogurt via injection to the mouth of the rat into the throat using a gastric probe.
## 2.4. Blood Sampling and Hematological Analysis
Blood samples were drawn from the rat through the lateral vein in the tail [12], and taken on days 1, 7, and 14. Each sample was inserted in a tube which had been priorly added with EDTA and subsequently analysed for S. pyogenes parameters [10]. Haematological observation was performed on the blood components including the number of platelets, leukocytes, lymphocytes, neutrophils, and monocytes.
## 2.5. Data Analysis
The data obtained in this study were analysed statistically using ANOVA (analysis of variance) after the Shapiro–Wilk normality test. The post hoc Duncan test was then performed with a 95% confidence interval (CI), following the suggestion from previous reports [13]. All analyses were carried out using the SPSS software (SPSS Inc., Chicago, IL, USA).
## 3. Results and Discussion
### 3.1. Platelets
The K0 group, the negative control, was found to possess the highest platelet value (Table2). The pathogenic activity of S. pyogenes reduced the number of platelet cells in the K1 group after infection on the first day. The reduced platelet count was associated with the aggregation of platelets in the infection sites following platelet binding by haemostasis-related receptors [14]. As for the K2 and K3 groups receiving yogurt therapy, the number of platelets was higher in the K2 group as compared with that in the K1 group. It suggests the ability of yogurt containing probiotics in maintaining the number of platelets. Probiotics could attach to epithelial cells and release several free amino acids and synthesize vitamins needed by the growth of the host platelets [15]. It was corroborated by the observation on day 7 and 14, where the K2 and K3 groups had a relatively higher number of platelets. The K2 group (14 days therapy) was found to have a higher platelet count than the K3 (7 days therapy), indicating that longer probiotic therapy may induce clinical benefits. Interestingly, the number of platelets keeps increasing 7 days post probiotic therapy (K3 group) indicating the longer effect of the probiotic in maintaining the platelets (Table 2) [11].Table 2
Results of rat’s blood haematology analysis.
ParameterDayTreatment groupsK0K1K2K3Platelets (cells/μL)1714355500 ± 7778.2b362500 ± 24748.7b324500 ± 31819.8b96000 ± 1414.2a92500 ± 3535.5a91500 ± 2121.3a247500 ± 22627.4c390000 ± 12727.9b330000 ± 4242.6b238000 ± 99649.4c230000 ± 70710.6c324500 ± 7778.2bLeukocyte (cells/μL)171410750 ± 353.5b10800 ± 424.2b10850 ± 353.5b8200 ± 141.4a8250 ± 353.5a8000 ± 1272.8a10700 ± 989.9b10550 ± 494.9b10500 ± 565.6b9500 ± 565.6a,b9550 ± 353.5b9800 ± 565.6a,bLymphocyte (%)171432.50 ± 0.71a30.00 ± 0.00a31.00 ± 0.00a40.00 ± 1.41b45.50 ± 0.71c43.00 ± 1.41b32.00 ± 1.41a29.50 ± 0.71a30.00 ± 1.41a30.50 ± 0.71a34.50 ± 2.12b,a29.00 ± 2.82aNeutrophil (%)171425.50 ± 0.71a24.50 ± 0.71a24.00 ± 1.41a35.50 ± 0.71c39.00 ± 1.41c37.50 ± 2.12c29.50 ± 2.12b25.00 ± 1.41a23.00 ± 1.41a27.50 ± 0.71a33.50 ± 0.71b29.00 ± 1.41bMonocyte (%)17142.70 ± 0.42a2.55 ± 0.64a2.60 ± 0.56a5.55 ± 0.78a6.15 ± 1.20b6.45 ± 0.63b2.80 ± 0.28a2.55 ± 0.78a2.95 ± 1.34a3.30 ± 0.98a4.50 ± 0.71a4.00 ± 0.00aa, bSimilar letter notation indicates no significant difference in Duncan’s test with a value of 5%.
### 3.2. Leukocyte
The number of leukocytes was found to be lower in the infected group (K1) than in groups receiving no treatment (K0) (Table2). This observation is similar to the findings from the previously reported study [11]. In a normal rat, the range of leukocyte count is 2000–10000 cells/μL [16]. Although the number of leukocytes in the K1 group remained within normal limits, the leukocyte count was statistically lower (p<0.05) as compared with other rat groups. The K2 Group had leukocyte counts higher or similar to that of the K0 group, indicating the effectiveness of 14-days probiotic therapy. It could be attributed to the role of probiotics as immunomodulators, hence improving the leukocyte count [17, 18]. Several strains of lactic acid bacteria that are probiotics stimulate the immune system, e.g., repairing macrophages, increasing antibodies, and controlling infection [19–22]. Nonetheless, the administration of the probiotic did not significantly affect the number of leukocytes in the K1 group, suggesting that a treatment duration of 7 days was insufficient (Table 2).
### 3.3. Lymphocyte
The normal value of mouse lymphocytes is 60–75% [16, 23]. The K0 group was a negative control with lymphocyte count (%) on days 1, 7, and 14, namely 32.50 ± 0.71, 30.00 ± 0.00, and 31.00 ± 0.00, respectively (Table 2). The group of infected rats without yogurt (K1) on days 1, 7, and 14 had lymphocyte counts (%) of 40.00 ± 1.41, 45.50 ± 0.71, and 43.00 ± 1.41, respectively. This shows that the K1 group has a significantly higher number of lymphocytes than the K0 group (p<0.05). It suggests the role S. pyogenes infection in elevating the number of lymphocyte cells, as suggested previously [11]. The number of lymphocytes increased to 45.50 ± 0.71% in the first week. It explains that lymphocytes play a role in forming antibodies to protect the body from infection [24]. In the K2 and K3 groups, yogurt administration for seven days until the 14th day decreased the number of lymphocytes. Only in the K3 group the number of lymphocytes slightly increased to 34.50 ± 2.12% on the 7th day, although it was not significantly different from the negative control group (Table 2). These results indicate that the content of probiotics in yogurt increases the immune system, improving lymphocyte profiles, which are in line with previous findings [25, 26].
### 3.4. Neutrophil
The K0 group was a negative control with the number of neutrophils (%) on days 1, 7, and 14 reaching 25.50 ± 0.71, 24.50 ± 0.71, and 24.00 ± 1.41, respectively (Table2). Meanwhile, the K1 group experienced an elevated number of neutrophils following the course of the infection. The number of neutrophils in the K1 group was the highest among all groups (p<0.05). The role of S. pyogenes in elevating the neutrophil count had been witnessed in a previous study [11]. The administration of probiotics in this present study was proven to be capable of restoring the neutrophil counts to the normal range (Table 2). Restoring the number of neutrophils is important since it has a role in preventing bacterial infection in the body [27].
### 3.5. Monocyte
The K0 group was a negative control with monocyte a count (%) on days 1, 7, and 14 reaching 2.70 ± 0.42, 2.55 ± 0.64, and 2.60 ± 0.56, respectively (Table2). S. pyogenes infection in the K1 group caused a significant increase in the monocyte count, observed on day 7 and 14 (6.15 ± 1.20 and 6.45 ± 0.63%). The normal range of the monocyte count itself is 1–6% [16]. The exacerbated monocyte count following the S. pyogenes infection is in agreement with the findings from a previous study [11]. Monocytes have a phagocytic function. Monocytes are specific initial defense cells in rats that get rid of foreign objects that enter the body [28]. Meanwhile, the monocyte counts in K2 and K3 groups in all observations were found to be insignificant as compared with the negative control (K0) with p>0.05 (Table 2).
## 3.1. Platelets
The K0 group, the negative control, was found to possess the highest platelet value (Table2). The pathogenic activity of S. pyogenes reduced the number of platelet cells in the K1 group after infection on the first day. The reduced platelet count was associated with the aggregation of platelets in the infection sites following platelet binding by haemostasis-related receptors [14]. As for the K2 and K3 groups receiving yogurt therapy, the number of platelets was higher in the K2 group as compared with that in the K1 group. It suggests the ability of yogurt containing probiotics in maintaining the number of platelets. Probiotics could attach to epithelial cells and release several free amino acids and synthesize vitamins needed by the growth of the host platelets [15]. It was corroborated by the observation on day 7 and 14, where the K2 and K3 groups had a relatively higher number of platelets. The K2 group (14 days therapy) was found to have a higher platelet count than the K3 (7 days therapy), indicating that longer probiotic therapy may induce clinical benefits. Interestingly, the number of platelets keeps increasing 7 days post probiotic therapy (K3 group) indicating the longer effect of the probiotic in maintaining the platelets (Table 2) [11].Table 2
Results of rat’s blood haematology analysis.
ParameterDayTreatment groupsK0K1K2K3Platelets (cells/μL)1714355500 ± 7778.2b362500 ± 24748.7b324500 ± 31819.8b96000 ± 1414.2a92500 ± 3535.5a91500 ± 2121.3a247500 ± 22627.4c390000 ± 12727.9b330000 ± 4242.6b238000 ± 99649.4c230000 ± 70710.6c324500 ± 7778.2bLeukocyte (cells/μL)171410750 ± 353.5b10800 ± 424.2b10850 ± 353.5b8200 ± 141.4a8250 ± 353.5a8000 ± 1272.8a10700 ± 989.9b10550 ± 494.9b10500 ± 565.6b9500 ± 565.6a,b9550 ± 353.5b9800 ± 565.6a,bLymphocyte (%)171432.50 ± 0.71a30.00 ± 0.00a31.00 ± 0.00a40.00 ± 1.41b45.50 ± 0.71c43.00 ± 1.41b32.00 ± 1.41a29.50 ± 0.71a30.00 ± 1.41a30.50 ± 0.71a34.50 ± 2.12b,a29.00 ± 2.82aNeutrophil (%)171425.50 ± 0.71a24.50 ± 0.71a24.00 ± 1.41a35.50 ± 0.71c39.00 ± 1.41c37.50 ± 2.12c29.50 ± 2.12b25.00 ± 1.41a23.00 ± 1.41a27.50 ± 0.71a33.50 ± 0.71b29.00 ± 1.41bMonocyte (%)17142.70 ± 0.42a2.55 ± 0.64a2.60 ± 0.56a5.55 ± 0.78a6.15 ± 1.20b6.45 ± 0.63b2.80 ± 0.28a2.55 ± 0.78a2.95 ± 1.34a3.30 ± 0.98a4.50 ± 0.71a4.00 ± 0.00aa, bSimilar letter notation indicates no significant difference in Duncan’s test with a value of 5%.
## 3.2. Leukocyte
The number of leukocytes was found to be lower in the infected group (K1) than in groups receiving no treatment (K0) (Table2). This observation is similar to the findings from the previously reported study [11]. In a normal rat, the range of leukocyte count is 2000–10000 cells/μL [16]. Although the number of leukocytes in the K1 group remained within normal limits, the leukocyte count was statistically lower (p<0.05) as compared with other rat groups. The K2 Group had leukocyte counts higher or similar to that of the K0 group, indicating the effectiveness of 14-days probiotic therapy. It could be attributed to the role of probiotics as immunomodulators, hence improving the leukocyte count [17, 18]. Several strains of lactic acid bacteria that are probiotics stimulate the immune system, e.g., repairing macrophages, increasing antibodies, and controlling infection [19–22]. Nonetheless, the administration of the probiotic did not significantly affect the number of leukocytes in the K1 group, suggesting that a treatment duration of 7 days was insufficient (Table 2).
## 3.3. Lymphocyte
The normal value of mouse lymphocytes is 60–75% [16, 23]. The K0 group was a negative control with lymphocyte count (%) on days 1, 7, and 14, namely 32.50 ± 0.71, 30.00 ± 0.00, and 31.00 ± 0.00, respectively (Table 2). The group of infected rats without yogurt (K1) on days 1, 7, and 14 had lymphocyte counts (%) of 40.00 ± 1.41, 45.50 ± 0.71, and 43.00 ± 1.41, respectively. This shows that the K1 group has a significantly higher number of lymphocytes than the K0 group (p<0.05). It suggests the role S. pyogenes infection in elevating the number of lymphocyte cells, as suggested previously [11]. The number of lymphocytes increased to 45.50 ± 0.71% in the first week. It explains that lymphocytes play a role in forming antibodies to protect the body from infection [24]. In the K2 and K3 groups, yogurt administration for seven days until the 14th day decreased the number of lymphocytes. Only in the K3 group the number of lymphocytes slightly increased to 34.50 ± 2.12% on the 7th day, although it was not significantly different from the negative control group (Table 2). These results indicate that the content of probiotics in yogurt increases the immune system, improving lymphocyte profiles, which are in line with previous findings [25, 26].
## 3.4. Neutrophil
The K0 group was a negative control with the number of neutrophils (%) on days 1, 7, and 14 reaching 25.50 ± 0.71, 24.50 ± 0.71, and 24.00 ± 1.41, respectively (Table2). Meanwhile, the K1 group experienced an elevated number of neutrophils following the course of the infection. The number of neutrophils in the K1 group was the highest among all groups (p<0.05). The role of S. pyogenes in elevating the neutrophil count had been witnessed in a previous study [11]. The administration of probiotics in this present study was proven to be capable of restoring the neutrophil counts to the normal range (Table 2). Restoring the number of neutrophils is important since it has a role in preventing bacterial infection in the body [27].
## 3.5. Monocyte
The K0 group was a negative control with monocyte a count (%) on days 1, 7, and 14 reaching 2.70 ± 0.42, 2.55 ± 0.64, and 2.60 ± 0.56, respectively (Table2). S. pyogenes infection in the K1 group caused a significant increase in the monocyte count, observed on day 7 and 14 (6.15 ± 1.20 and 6.45 ± 0.63%). The normal range of the monocyte count itself is 1–6% [16]. The exacerbated monocyte count following the S. pyogenes infection is in agreement with the findings from a previous study [11]. Monocytes have a phagocytic function. Monocytes are specific initial defense cells in rats that get rid of foreign objects that enter the body [28]. Meanwhile, the monocyte counts in K2 and K3 groups in all observations were found to be insignificant as compared with the negative control (K0) with p>0.05 (Table 2).
## 4. Conclusions
The efficacy of probiotic therapy againstS. pyogenes infection in rats has been proven by the recovery of haematological profiles. Probiotic treatment as short as 7 days could result in improving platelet and leukocyte counts 7 days posttreatment. Longer treatment duration was proven to contribute to the efficacy of probiotics in inhibiting the pathogenic activity of S. pyogenes. Clinical studies were warranted on the efficacy of probiotic therapy for S. pyogenes-induced throat inflammation.
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*Source: 2899462-2022-06-30.xml* | 2899462-2022-06-30_2899462-2022-06-30.md | 24,501 | Haematological Features of White Rats(Rattus norvegicus) Infected with S. pyogenes and Administered with Probiotics (Yogurt) | Novina Rahmawati; Maimun Syukri; Darmawi Darmawi; Indra Zachreini; Utari Zulfiani; Muhammad Yusuf; Rinaldi Idroes | The Scientific World Journal
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2899462 | 2899462-2022-06-30.xml | ---
## Abstract
This study aimed to study the inhibition activity of lactic acid bacteria probiotics deriving from Acehnese fermented Etawa goat’s milk (yogurt) againstStreptococcus pyogenes bacterial infection in rats (Rattus norvegicus). Haematological analysis of the rats’ blood was performed on the following parameters: platelets, leukocytes, lymphocytes, neutrophils, and monocytes, where the data were further processed using ANOVA and Duncan’s test with a confidence level of 95% (0.05). The results revealed that administering yogurt containing probiotics could reduce infections in the throats of rats caused by S. pyogenes. Based on the haematology examination, the probiotic yogurt could maintain the number of platelets, leukocytes, lymphocytes, neutrophils, and monocytes. Statistical significance was obtained when the infected rats were administered with a ±1.00 mL/day dose for seven days of treatment (p<0.05).
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## Body
## 1. Introduction
The use of antibiotics to treat infectious diseases in humans could cause adverse reactions and induce the emergence of antibiotic-resistant pathogens [1]. One of the diseases commonly treated using antibiotics is a sore throat caused by irritation or inflammation in pharyngitis or tonsillitis [2]. It is due to the fact that the disease is a common manifestation of Streptococcus pyogenes bacterial infection [2]. To overcome the antibiotic resistance in streptococci, the administration of probiotics (i.e., Lactobacillus probiotics) could be used as an integrative therapy [3]. Lactic acid bacteria are microflora classified as probiotics which could be obtained from fermentation [4]. The isolated lactic acid bacteria have several advantages as a probiotic including their survivability, reproducibility, and secretion of antibacterial substances (which could inhibit enteric gut bacteria) [5]. Lactobacillus and Bifidobacteria are the most common lactic acid bacteria used as probiotic microorganisms [5].Food and beverages containing probiotics have many health benefits, such as helping the digestive system process and absorption of nutrients [6]. Moreover, such probiotic products could inhibit the pathogen in the digestive tract (i.e., Escherichia coli, Streptococcus aureus, Salmonella typhimurium, Vibrio cholerae, and Mycobacterium tuberculosis) [6]. In addition, consuming food or beverages with probiotics could prevent constipation, cancer, excessive blood cholesterol level, lactose intolerance, and increase immune response [6]. Based on a previous report [7], ten local lactic acid bacteria species were extracted from raw beef showing probiotic properties by producing antimicrobial compounds. Another source to obtain lactic acid bacteria is yogurt, in which the yogurt made of Etawa goat’s milk has been reported to contain Gram-positive isolates with a negative catalase test [8]. Further investigation under the microscope in the foregoing report revealed the shape of the bacillus cells suggesting the milk isolate contained Lactobacillus bacteria [8].Nonetheless, the administration of probiotic bacteria via the oral route was reported to affect the body’s metabolic system [9], including the haematological status [10]. Dysregulation of blood parameters could adversely affect blood function. Hence, it is important for researchers to investigate the effect of probiotic administration on haematological blood parameters including the number of platelets, leukocytes, lymphocytes, neutrophils, and monocytes.Herein, the objective of this study is to investigate the ability of local probiotics (in the form of lactic acid bacteria) derived from fermented Etawa goat’s milk (yogurt) procured from Kopelma Village, Banda Aceh, Aceh Province, Indonesia, to treatS. pyogenes infection-induced inflammation in the throat of the rat model. The changes of haematological profiles (platelets, leukocytes, lymphocytes, neutrophils, and monocytes) following the probiotic therapy were also investigated.
## 2. Materials and Methods
### 2.1. Experiment Animals and Feeding
Twenty male rats (Rattus norvegicus) aged 5-6 weeks with a bodyweight range of 115–135 grams were obtained from the Test Animal Laboratory, Faculty of Veterinary Medicine, Universitas Syiah Kuala. The rats were divided into four treatment groups comprising five rats/group (K0 (negative control) and K1-3). Before treatment, all rats were acclimated for three days and fed ad libitum. The treatment process is presented in Table 1.Table 1
Treatment group on experimental rats [11].
No.Rat groupsTreatment1Negative control (K0)Normal rats were only fed and aquadest. A blood test was conducted on the 1st, 7th, and 14th days.2Bacterial infection (K1)Rats were fed and infected withS. pyogenes bacteria in the throat on the first day. A blood test was conducted on the 1st, 7th, and 14th days.3Administering yogurt and bacterial infection (K2)Rats were fed and infected withS. pyogenes bacteria in the throat on the first day. They were also administered with yogurt for 14 days at a dose of ±1.00 mL. A blood test was conducted on the 1st, 7th, and 14th days.4Administering yogurt and bacterial infection (K3)Rats were fed and administered with yogurt at a dose of ±1.00 mL for seven days, then,S. pyogenes bacteria were infected in the throat. A blood test was conducted on the 1st, 7th, and 14th days.
### 2.2.S. pyogenes Bacterial Infection
The rats were prepared to be infected withS. pyogenes bacteria. The culture of S. pyogenes (ATCC 12344) used was collected from the Laboratory of Oral Biology, Faculty of Dentistry, Universitas Indonesia, Jakarta. S. pyogenes infection was carried out using a population of 0.5 McFarland bacteria (1.5 × 108 CFU/mL) administered orally (swab) using a probe.
### 2.3. Yogurt Administration
Yogurt was orally administrated to the K2 group on the second day for the following 13 days, whilst the administration was carried out on the first day for the following 7 days for the K3 group. The administration was carried out by force-feeding 1 mL yogurt via injection to the mouth of the rat into the throat using a gastric probe.
### 2.4. Blood Sampling and Hematological Analysis
Blood samples were drawn from the rat through the lateral vein in the tail [12], and taken on days 1, 7, and 14. Each sample was inserted in a tube which had been priorly added with EDTA and subsequently analysed for S. pyogenes parameters [10]. Haematological observation was performed on the blood components including the number of platelets, leukocytes, lymphocytes, neutrophils, and monocytes.
### 2.5. Data Analysis
The data obtained in this study were analysed statistically using ANOVA (analysis of variance) after the Shapiro–Wilk normality test. The post hoc Duncan test was then performed with a 95% confidence interval (CI), following the suggestion from previous reports [13]. All analyses were carried out using the SPSS software (SPSS Inc., Chicago, IL, USA).
## 2.1. Experiment Animals and Feeding
Twenty male rats (Rattus norvegicus) aged 5-6 weeks with a bodyweight range of 115–135 grams were obtained from the Test Animal Laboratory, Faculty of Veterinary Medicine, Universitas Syiah Kuala. The rats were divided into four treatment groups comprising five rats/group (K0 (negative control) and K1-3). Before treatment, all rats were acclimated for three days and fed ad libitum. The treatment process is presented in Table 1.Table 1
Treatment group on experimental rats [11].
No.Rat groupsTreatment1Negative control (K0)Normal rats were only fed and aquadest. A blood test was conducted on the 1st, 7th, and 14th days.2Bacterial infection (K1)Rats were fed and infected withS. pyogenes bacteria in the throat on the first day. A blood test was conducted on the 1st, 7th, and 14th days.3Administering yogurt and bacterial infection (K2)Rats were fed and infected withS. pyogenes bacteria in the throat on the first day. They were also administered with yogurt for 14 days at a dose of ±1.00 mL. A blood test was conducted on the 1st, 7th, and 14th days.4Administering yogurt and bacterial infection (K3)Rats were fed and administered with yogurt at a dose of ±1.00 mL for seven days, then,S. pyogenes bacteria were infected in the throat. A blood test was conducted on the 1st, 7th, and 14th days.
## 2.2.S. pyogenes Bacterial Infection
The rats were prepared to be infected withS. pyogenes bacteria. The culture of S. pyogenes (ATCC 12344) used was collected from the Laboratory of Oral Biology, Faculty of Dentistry, Universitas Indonesia, Jakarta. S. pyogenes infection was carried out using a population of 0.5 McFarland bacteria (1.5 × 108 CFU/mL) administered orally (swab) using a probe.
## 2.3. Yogurt Administration
Yogurt was orally administrated to the K2 group on the second day for the following 13 days, whilst the administration was carried out on the first day for the following 7 days for the K3 group. The administration was carried out by force-feeding 1 mL yogurt via injection to the mouth of the rat into the throat using a gastric probe.
## 2.4. Blood Sampling and Hematological Analysis
Blood samples were drawn from the rat through the lateral vein in the tail [12], and taken on days 1, 7, and 14. Each sample was inserted in a tube which had been priorly added with EDTA and subsequently analysed for S. pyogenes parameters [10]. Haematological observation was performed on the blood components including the number of platelets, leukocytes, lymphocytes, neutrophils, and monocytes.
## 2.5. Data Analysis
The data obtained in this study were analysed statistically using ANOVA (analysis of variance) after the Shapiro–Wilk normality test. The post hoc Duncan test was then performed with a 95% confidence interval (CI), following the suggestion from previous reports [13]. All analyses were carried out using the SPSS software (SPSS Inc., Chicago, IL, USA).
## 3. Results and Discussion
### 3.1. Platelets
The K0 group, the negative control, was found to possess the highest platelet value (Table2). The pathogenic activity of S. pyogenes reduced the number of platelet cells in the K1 group after infection on the first day. The reduced platelet count was associated with the aggregation of platelets in the infection sites following platelet binding by haemostasis-related receptors [14]. As for the K2 and K3 groups receiving yogurt therapy, the number of platelets was higher in the K2 group as compared with that in the K1 group. It suggests the ability of yogurt containing probiotics in maintaining the number of platelets. Probiotics could attach to epithelial cells and release several free amino acids and synthesize vitamins needed by the growth of the host platelets [15]. It was corroborated by the observation on day 7 and 14, where the K2 and K3 groups had a relatively higher number of platelets. The K2 group (14 days therapy) was found to have a higher platelet count than the K3 (7 days therapy), indicating that longer probiotic therapy may induce clinical benefits. Interestingly, the number of platelets keeps increasing 7 days post probiotic therapy (K3 group) indicating the longer effect of the probiotic in maintaining the platelets (Table 2) [11].Table 2
Results of rat’s blood haematology analysis.
ParameterDayTreatment groupsK0K1K2K3Platelets (cells/μL)1714355500 ± 7778.2b362500 ± 24748.7b324500 ± 31819.8b96000 ± 1414.2a92500 ± 3535.5a91500 ± 2121.3a247500 ± 22627.4c390000 ± 12727.9b330000 ± 4242.6b238000 ± 99649.4c230000 ± 70710.6c324500 ± 7778.2bLeukocyte (cells/μL)171410750 ± 353.5b10800 ± 424.2b10850 ± 353.5b8200 ± 141.4a8250 ± 353.5a8000 ± 1272.8a10700 ± 989.9b10550 ± 494.9b10500 ± 565.6b9500 ± 565.6a,b9550 ± 353.5b9800 ± 565.6a,bLymphocyte (%)171432.50 ± 0.71a30.00 ± 0.00a31.00 ± 0.00a40.00 ± 1.41b45.50 ± 0.71c43.00 ± 1.41b32.00 ± 1.41a29.50 ± 0.71a30.00 ± 1.41a30.50 ± 0.71a34.50 ± 2.12b,a29.00 ± 2.82aNeutrophil (%)171425.50 ± 0.71a24.50 ± 0.71a24.00 ± 1.41a35.50 ± 0.71c39.00 ± 1.41c37.50 ± 2.12c29.50 ± 2.12b25.00 ± 1.41a23.00 ± 1.41a27.50 ± 0.71a33.50 ± 0.71b29.00 ± 1.41bMonocyte (%)17142.70 ± 0.42a2.55 ± 0.64a2.60 ± 0.56a5.55 ± 0.78a6.15 ± 1.20b6.45 ± 0.63b2.80 ± 0.28a2.55 ± 0.78a2.95 ± 1.34a3.30 ± 0.98a4.50 ± 0.71a4.00 ± 0.00aa, bSimilar letter notation indicates no significant difference in Duncan’s test with a value of 5%.
### 3.2. Leukocyte
The number of leukocytes was found to be lower in the infected group (K1) than in groups receiving no treatment (K0) (Table2). This observation is similar to the findings from the previously reported study [11]. In a normal rat, the range of leukocyte count is 2000–10000 cells/μL [16]. Although the number of leukocytes in the K1 group remained within normal limits, the leukocyte count was statistically lower (p<0.05) as compared with other rat groups. The K2 Group had leukocyte counts higher or similar to that of the K0 group, indicating the effectiveness of 14-days probiotic therapy. It could be attributed to the role of probiotics as immunomodulators, hence improving the leukocyte count [17, 18]. Several strains of lactic acid bacteria that are probiotics stimulate the immune system, e.g., repairing macrophages, increasing antibodies, and controlling infection [19–22]. Nonetheless, the administration of the probiotic did not significantly affect the number of leukocytes in the K1 group, suggesting that a treatment duration of 7 days was insufficient (Table 2).
### 3.3. Lymphocyte
The normal value of mouse lymphocytes is 60–75% [16, 23]. The K0 group was a negative control with lymphocyte count (%) on days 1, 7, and 14, namely 32.50 ± 0.71, 30.00 ± 0.00, and 31.00 ± 0.00, respectively (Table 2). The group of infected rats without yogurt (K1) on days 1, 7, and 14 had lymphocyte counts (%) of 40.00 ± 1.41, 45.50 ± 0.71, and 43.00 ± 1.41, respectively. This shows that the K1 group has a significantly higher number of lymphocytes than the K0 group (p<0.05). It suggests the role S. pyogenes infection in elevating the number of lymphocyte cells, as suggested previously [11]. The number of lymphocytes increased to 45.50 ± 0.71% in the first week. It explains that lymphocytes play a role in forming antibodies to protect the body from infection [24]. In the K2 and K3 groups, yogurt administration for seven days until the 14th day decreased the number of lymphocytes. Only in the K3 group the number of lymphocytes slightly increased to 34.50 ± 2.12% on the 7th day, although it was not significantly different from the negative control group (Table 2). These results indicate that the content of probiotics in yogurt increases the immune system, improving lymphocyte profiles, which are in line with previous findings [25, 26].
### 3.4. Neutrophil
The K0 group was a negative control with the number of neutrophils (%) on days 1, 7, and 14 reaching 25.50 ± 0.71, 24.50 ± 0.71, and 24.00 ± 1.41, respectively (Table2). Meanwhile, the K1 group experienced an elevated number of neutrophils following the course of the infection. The number of neutrophils in the K1 group was the highest among all groups (p<0.05). The role of S. pyogenes in elevating the neutrophil count had been witnessed in a previous study [11]. The administration of probiotics in this present study was proven to be capable of restoring the neutrophil counts to the normal range (Table 2). Restoring the number of neutrophils is important since it has a role in preventing bacterial infection in the body [27].
### 3.5. Monocyte
The K0 group was a negative control with monocyte a count (%) on days 1, 7, and 14 reaching 2.70 ± 0.42, 2.55 ± 0.64, and 2.60 ± 0.56, respectively (Table2). S. pyogenes infection in the K1 group caused a significant increase in the monocyte count, observed on day 7 and 14 (6.15 ± 1.20 and 6.45 ± 0.63%). The normal range of the monocyte count itself is 1–6% [16]. The exacerbated monocyte count following the S. pyogenes infection is in agreement with the findings from a previous study [11]. Monocytes have a phagocytic function. Monocytes are specific initial defense cells in rats that get rid of foreign objects that enter the body [28]. Meanwhile, the monocyte counts in K2 and K3 groups in all observations were found to be insignificant as compared with the negative control (K0) with p>0.05 (Table 2).
## 3.1. Platelets
The K0 group, the negative control, was found to possess the highest platelet value (Table2). The pathogenic activity of S. pyogenes reduced the number of platelet cells in the K1 group after infection on the first day. The reduced platelet count was associated with the aggregation of platelets in the infection sites following platelet binding by haemostasis-related receptors [14]. As for the K2 and K3 groups receiving yogurt therapy, the number of platelets was higher in the K2 group as compared with that in the K1 group. It suggests the ability of yogurt containing probiotics in maintaining the number of platelets. Probiotics could attach to epithelial cells and release several free amino acids and synthesize vitamins needed by the growth of the host platelets [15]. It was corroborated by the observation on day 7 and 14, where the K2 and K3 groups had a relatively higher number of platelets. The K2 group (14 days therapy) was found to have a higher platelet count than the K3 (7 days therapy), indicating that longer probiotic therapy may induce clinical benefits. Interestingly, the number of platelets keeps increasing 7 days post probiotic therapy (K3 group) indicating the longer effect of the probiotic in maintaining the platelets (Table 2) [11].Table 2
Results of rat’s blood haematology analysis.
ParameterDayTreatment groupsK0K1K2K3Platelets (cells/μL)1714355500 ± 7778.2b362500 ± 24748.7b324500 ± 31819.8b96000 ± 1414.2a92500 ± 3535.5a91500 ± 2121.3a247500 ± 22627.4c390000 ± 12727.9b330000 ± 4242.6b238000 ± 99649.4c230000 ± 70710.6c324500 ± 7778.2bLeukocyte (cells/μL)171410750 ± 353.5b10800 ± 424.2b10850 ± 353.5b8200 ± 141.4a8250 ± 353.5a8000 ± 1272.8a10700 ± 989.9b10550 ± 494.9b10500 ± 565.6b9500 ± 565.6a,b9550 ± 353.5b9800 ± 565.6a,bLymphocyte (%)171432.50 ± 0.71a30.00 ± 0.00a31.00 ± 0.00a40.00 ± 1.41b45.50 ± 0.71c43.00 ± 1.41b32.00 ± 1.41a29.50 ± 0.71a30.00 ± 1.41a30.50 ± 0.71a34.50 ± 2.12b,a29.00 ± 2.82aNeutrophil (%)171425.50 ± 0.71a24.50 ± 0.71a24.00 ± 1.41a35.50 ± 0.71c39.00 ± 1.41c37.50 ± 2.12c29.50 ± 2.12b25.00 ± 1.41a23.00 ± 1.41a27.50 ± 0.71a33.50 ± 0.71b29.00 ± 1.41bMonocyte (%)17142.70 ± 0.42a2.55 ± 0.64a2.60 ± 0.56a5.55 ± 0.78a6.15 ± 1.20b6.45 ± 0.63b2.80 ± 0.28a2.55 ± 0.78a2.95 ± 1.34a3.30 ± 0.98a4.50 ± 0.71a4.00 ± 0.00aa, bSimilar letter notation indicates no significant difference in Duncan’s test with a value of 5%.
## 3.2. Leukocyte
The number of leukocytes was found to be lower in the infected group (K1) than in groups receiving no treatment (K0) (Table2). This observation is similar to the findings from the previously reported study [11]. In a normal rat, the range of leukocyte count is 2000–10000 cells/μL [16]. Although the number of leukocytes in the K1 group remained within normal limits, the leukocyte count was statistically lower (p<0.05) as compared with other rat groups. The K2 Group had leukocyte counts higher or similar to that of the K0 group, indicating the effectiveness of 14-days probiotic therapy. It could be attributed to the role of probiotics as immunomodulators, hence improving the leukocyte count [17, 18]. Several strains of lactic acid bacteria that are probiotics stimulate the immune system, e.g., repairing macrophages, increasing antibodies, and controlling infection [19–22]. Nonetheless, the administration of the probiotic did not significantly affect the number of leukocytes in the K1 group, suggesting that a treatment duration of 7 days was insufficient (Table 2).
## 3.3. Lymphocyte
The normal value of mouse lymphocytes is 60–75% [16, 23]. The K0 group was a negative control with lymphocyte count (%) on days 1, 7, and 14, namely 32.50 ± 0.71, 30.00 ± 0.00, and 31.00 ± 0.00, respectively (Table 2). The group of infected rats without yogurt (K1) on days 1, 7, and 14 had lymphocyte counts (%) of 40.00 ± 1.41, 45.50 ± 0.71, and 43.00 ± 1.41, respectively. This shows that the K1 group has a significantly higher number of lymphocytes than the K0 group (p<0.05). It suggests the role S. pyogenes infection in elevating the number of lymphocyte cells, as suggested previously [11]. The number of lymphocytes increased to 45.50 ± 0.71% in the first week. It explains that lymphocytes play a role in forming antibodies to protect the body from infection [24]. In the K2 and K3 groups, yogurt administration for seven days until the 14th day decreased the number of lymphocytes. Only in the K3 group the number of lymphocytes slightly increased to 34.50 ± 2.12% on the 7th day, although it was not significantly different from the negative control group (Table 2). These results indicate that the content of probiotics in yogurt increases the immune system, improving lymphocyte profiles, which are in line with previous findings [25, 26].
## 3.4. Neutrophil
The K0 group was a negative control with the number of neutrophils (%) on days 1, 7, and 14 reaching 25.50 ± 0.71, 24.50 ± 0.71, and 24.00 ± 1.41, respectively (Table2). Meanwhile, the K1 group experienced an elevated number of neutrophils following the course of the infection. The number of neutrophils in the K1 group was the highest among all groups (p<0.05). The role of S. pyogenes in elevating the neutrophil count had been witnessed in a previous study [11]. The administration of probiotics in this present study was proven to be capable of restoring the neutrophil counts to the normal range (Table 2). Restoring the number of neutrophils is important since it has a role in preventing bacterial infection in the body [27].
## 3.5. Monocyte
The K0 group was a negative control with monocyte a count (%) on days 1, 7, and 14 reaching 2.70 ± 0.42, 2.55 ± 0.64, and 2.60 ± 0.56, respectively (Table2). S. pyogenes infection in the K1 group caused a significant increase in the monocyte count, observed on day 7 and 14 (6.15 ± 1.20 and 6.45 ± 0.63%). The normal range of the monocyte count itself is 1–6% [16]. The exacerbated monocyte count following the S. pyogenes infection is in agreement with the findings from a previous study [11]. Monocytes have a phagocytic function. Monocytes are specific initial defense cells in rats that get rid of foreign objects that enter the body [28]. Meanwhile, the monocyte counts in K2 and K3 groups in all observations were found to be insignificant as compared with the negative control (K0) with p>0.05 (Table 2).
## 4. Conclusions
The efficacy of probiotic therapy againstS. pyogenes infection in rats has been proven by the recovery of haematological profiles. Probiotic treatment as short as 7 days could result in improving platelet and leukocyte counts 7 days posttreatment. Longer treatment duration was proven to contribute to the efficacy of probiotics in inhibiting the pathogenic activity of S. pyogenes. Clinical studies were warranted on the efficacy of probiotic therapy for S. pyogenes-induced throat inflammation.
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*Source: 2899462-2022-06-30.xml* | 2022 |
# Risk Warning of Independent Intellectual Property Rights of Small- and Medium-Sized Scientific and Technological Enterprises Using Deep Learning
**Authors:** Junzheng Wu
**Journal:** Mobile Information Systems
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2899674
---
## Abstract
Strengthening the construction of intellectual property rights of SM-TE (small and medium-sized scientific and technological enterprises) in China is an important measure to speed up the development of SM-TE, and improve their scientific and technological innovation ability and market competitiveness. In this paper, a patent recommendation algorithm based on deep semantic similarity is proposed to solve the problem of low calculation accuracy of similarity matrix among users in sparse interaction matrix. The algorithm trains the patent corpus, and obtains the Doc2vec DL (Deep Learning) model, and then constructs the semantic similarity matrix among patents through the DL model. On this basis, to further improve the modeling ability of semantic expression and feature extraction, this paper optimizes CNN (Convolutional Neural Network) model, using a variety of pretrained word vector models, multi-layer classifiers, etc., to improve the model accuracy and generate feature vectors of different dimensions. The results show that the accuracy, recall rate and F1 value of the proposed algorithm are better than those of the traditional recommendation algorithm, which are 22.41%, 20.86% and 21.51% respectively. The experiment shows that this paper can guide Chinese enterprises to establish and improve the risk warning system of independent intellectual property rights, thus reducing the losses of enterprises.
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## Body
## 1. Introduction
SM-TE (Small and Medium-sized Scientific and Technological Enterprises) innovation is an important force to promote social progress, stimulate national economic growth and consolidate the national independent innovation strength. At present, international competition is mainly reflected in the competition of independent innovation forces. Compared with developed countries, China’s small and micro-enterprises in science and technology have insufficient innovation ability, and the low level of intellectual property management is also an urgent problem to be solved. Intellectual property ownership has become an important index to measure the core competitiveness and innovation ability of enterprises. Chinese enterprises urgently need to use independent intellectual property rights to break the international monopoly and blockade, go abroad and strive for greater development space. Due to the simple industrial structure of SM-TE, it is easy to pay attention to the technological development of the leading industries. In addition, SM-TE has a close connection with the market and high market sensitivity. SM-TE with innovative ability must become a new force for independent intellectual property innovation in China.Risk early-warning research is a hot topic both domestically and internationally. Domestic scholars have looked into the medium-term early warning mechanisms of start-up companies, commercial bank loan risk early warning mechanisms, marketing risk early warning mechanisms, and financial risk early warning mechanisms of small and medium-sized businesses, as well as knowledge management risk early warning and knowledge capital risk early warning mechanisms [1–3]. According to He et al., there is generally no financial risk in enterprises during periods of rapid economic growth, and there are many factors that affect the financial risk of enterprises [4], the most prominent of which are the economic situation, stock price, and inflation. Deng et al. used the univariate analysis method to compare 79 companies from crisis and normal enterprises [5]. Finally, it is discovered that cash flow divided by total liabilities is the best predictor of an enterprise’s financial crisis. Liang et al. used multivariate analysis to assess enterprise financial risk early warning. This method combines financial ratios with multivariate judgment to provide an early warning system for financial risk [6]. In their study, Niu et al. used both cash flow and non-cash flow indicators and proposed a research idea of financial early warning based on cash flow [7]. There are, however, few studies on early detection of intellectual property risks. This is because the emergence of intellectual property risk in the process of enterprise independent innovation is influenced by a variety of factors, and it is difficult to predict intellectual property risk in the process of independent innovation.Deep learning (DL) is a new concept in machine learning. The term “deep learning” is derived from the term “neural network.” DL, in particular, has a large number of hidden layers that determine its complicated internal mapping relationship. We can learn the effective characteristics of data and have a strong learning ability thanks to this complex internal relationship. Both the DL network and the BP neural network (BP neural network) are machine learning models, but they differ significantly. A shallow neural network is a BPNN, and a multi-layer deep neural network is DL. Many academic and practical examples demonstrate that DL is more important in defining complex functional relationships. As a result, the goal of this paper is to apply DL knowledge to SM-independent TE’s intellectual property risk warning, to put the scientific concept of development in the field of independent intellectual property risk warning into practise, and to use it flexibly to protect the company’s independent intellectual property security, which has both theoretical and practical implications. The following aspects of this paper’s innovation: (1) In this paper, the existing research on intellectual property risk pre-operation is deeply studied, which breaks the current situation that most of the existing research focuses on the identification, risk assessment, and control of intellectual property risk response measures, and tries to build an early warning system of intellectual property risk. The whole system is divided into the risk identification subsystem, risk assessment subsystem, and risk early warning subsystem, which is conducive to risk prevention and control in the whole process of intellectual property development. (2) In the aspect of collaboration among users, aiming at the problem of low calculation accuracy of similarity matrix among users in sparse interaction matrix, a patent recommendation algorithm based on deep semantic similarity is proposed. The algorithm extracts the nearest neighbor of the target user, estimates the patent score of the target user according to the patent score of the neighbor, sorts the patents according to the score, and recommends the patent with the highest score to the target user. (3) To further improve the semantic expression and feature extraction ability of the model, the neural network model for feature extraction and analysis of patent texts is optimized and enhanced. Through relevant experiments, the improved model is evaluated and analyzed on multiple pretrained word vector models and multiple data sets.
## 2. Related Work
### 2.1. Risk Early Warning Research
Neuner research shows that the financial distress of an enterprise may not necessarily lead to bankruptcy or reorganization, but the bankrupt or reorganized enterprise must be the one with financial distress [8]. Liu et al. believe that the serious cash-out problem of an enterprise cannot be solved by conventional means, and if the operation or structure of the enterprise needs large-scale restructuring, the enterprise will be in financial trouble [9]. Liu’s model for financial risk early warning research has many limitations on assumptions compared with multivariate judgment. Logistic model has lower data requirements and is more applicable, so it is a better method [10].Hz et al. introduced artificial neural network into the field of financial risk early warning, and they chose a three-layer neural network for early warning. At the same time, they used multiple judgment methods to make empirical analyses and compare the results [11]. The results show that the accuracy and fault tolerance of artificial neural networks are better. Zhang et al. introduced qualitative indicators such as working environment, internal control, external environment, business environment, and analyzed them in combination with traditional quantitative indicators such as solvency indicators and profitability indicators [12]. However, it is not tested by specific data, but it is a good idea to introduce qualitative indicators. Yudo et al. have established the financial risk judgment index system for oil companies, and based on this, they have established the financial risk early warning model of fuzzy neural network [13]. Li et al. used the data processed by GM(1 : 1) model of function transformation as the input value of BPNN to make an early warning of financial risks [14].
### 2.2. Research Status of DL Network
DL-based models and algorithms have made remarkable achievements in the fields of computer vision and speech processing. At present, the application of DL in natural language processing has gradually matured. In some natural language processing tasks, such as text classification, sentiment analysis, DL method shows greater advantages than traditional text processing methods.Nateghi et al. verified through experiments that DL methods using unsupervised training at all levels can describe complex functions well and avoid over-fitting problems caused by network training [15]. Colombo et al. have made great success in using DL neural networks. The input values of its model do not contain artificial features but image pixels, which has become a great breakthrough in the field of image recognition [16]. Panwar et al. combined the grey prediction model and neural network model to study financial early warning [17]; Dhuri et al. use statistical methods to optimize the artificial neural network model and improve the financial early warning model based on the neural network with higher reliability [18]; Hui et al. used DL method to build a neural network model to predict the financial distress of enterprises, with high accuracy [19].Chen et al. used DL method to extract the features of objects, initialized the network, and then used back propagation algorithm to fine-tune the network parameters [20]. Liu et al. used a self-coding DL neural network in the field of speech recognition [21]. Firstly, DL method was used to extract the features of speech signals. Then it is tested by BPNN and DL network respectively. The results show that the accuracy of DL method is nearly 20% higher than that of the traditional BPNN method, and it has a good effect. Wei et al. have studied the application of DL network in the prediction of stock index futures. In this paper, an automatic encoder and other algorithms are used to establish DL network model, and the comparison is made. Finally, a network prediction system for trading is constructed according to trading choices [22].
## 2.1. Risk Early Warning Research
Neuner research shows that the financial distress of an enterprise may not necessarily lead to bankruptcy or reorganization, but the bankrupt or reorganized enterprise must be the one with financial distress [8]. Liu et al. believe that the serious cash-out problem of an enterprise cannot be solved by conventional means, and if the operation or structure of the enterprise needs large-scale restructuring, the enterprise will be in financial trouble [9]. Liu’s model for financial risk early warning research has many limitations on assumptions compared with multivariate judgment. Logistic model has lower data requirements and is more applicable, so it is a better method [10].Hz et al. introduced artificial neural network into the field of financial risk early warning, and they chose a three-layer neural network for early warning. At the same time, they used multiple judgment methods to make empirical analyses and compare the results [11]. The results show that the accuracy and fault tolerance of artificial neural networks are better. Zhang et al. introduced qualitative indicators such as working environment, internal control, external environment, business environment, and analyzed them in combination with traditional quantitative indicators such as solvency indicators and profitability indicators [12]. However, it is not tested by specific data, but it is a good idea to introduce qualitative indicators. Yudo et al. have established the financial risk judgment index system for oil companies, and based on this, they have established the financial risk early warning model of fuzzy neural network [13]. Li et al. used the data processed by GM(1 : 1) model of function transformation as the input value of BPNN to make an early warning of financial risks [14].
## 2.2. Research Status of DL Network
DL-based models and algorithms have made remarkable achievements in the fields of computer vision and speech processing. At present, the application of DL in natural language processing has gradually matured. In some natural language processing tasks, such as text classification, sentiment analysis, DL method shows greater advantages than traditional text processing methods.Nateghi et al. verified through experiments that DL methods using unsupervised training at all levels can describe complex functions well and avoid over-fitting problems caused by network training [15]. Colombo et al. have made great success in using DL neural networks. The input values of its model do not contain artificial features but image pixels, which has become a great breakthrough in the field of image recognition [16]. Panwar et al. combined the grey prediction model and neural network model to study financial early warning [17]; Dhuri et al. use statistical methods to optimize the artificial neural network model and improve the financial early warning model based on the neural network with higher reliability [18]; Hui et al. used DL method to build a neural network model to predict the financial distress of enterprises, with high accuracy [19].Chen et al. used DL method to extract the features of objects, initialized the network, and then used back propagation algorithm to fine-tune the network parameters [20]. Liu et al. used a self-coding DL neural network in the field of speech recognition [21]. Firstly, DL method was used to extract the features of speech signals. Then it is tested by BPNN and DL network respectively. The results show that the accuracy of DL method is nearly 20% higher than that of the traditional BPNN method, and it has a good effect. Wei et al. have studied the application of DL network in the prediction of stock index futures. In this paper, an automatic encoder and other algorithms are used to establish DL network model, and the comparison is made. Finally, a network prediction system for trading is constructed according to trading choices [22].
## 3. Methodology
### 3.1. Patent Recommendation Algorithm
Many science and technology small and microenterprises have yet to develop a perfect intellectual property incentive system, have yet to sign intellectual property confidentiality agreements with their employees, and have neglected intellectual property protection negotiations when collaborating with external units. According to synergy theory, the enhancement of nonlinear interaction among all system elements (capital, technology, equipment, R&D personnel, etc.) leads to the creation of innovation, and the related energy is greater than the innovation energy. Individual movement is governed by coordinated movement, and the system is well-structured, resulting in innovative achievements with dissipative structure characteristics.Intellectual property is an important wealth and resource [1], which is vital to the development of enterprises and countries. Intellectual property not only represents the core competitiveness of enterprises but also represents the comprehensive national strength of the country. As an important intellectual property right, patent symbolizes the power of various scientific and technological achievements, and it is essential to protect the core technologies of enterprises and countries. Enterprises with high patent content have the initiative to survive and develop [2], while countries with high patent content have competitive advantages in terms of scientific and technological strength and comprehensive national strength [3, 4].In this chapter, a patent recommendation algorithm based on deep semantic similarity is proposed, which employs a DL model and completion strategy to fill the sparse interaction matrix between users and patents, addressing the issue of low similarity matrix calculation accuracy. To improve recommendation efficiency, the problem of users in sparse interaction matrix is not severe. Fill the sparse interaction matrix between users and patents with Doc2vec DL model and completion strategy, analyse the collaboration relationship between users, find potential neighbors with similar interests, use neighbor scores to predict unknown patent scores, and recommend patents in turn.A cross-patent similarity matrix is a matrix that contains all patents in both the horizontal and vertical directions. The intermediate data is the semantic similarity of cross-patents calculated by the Doc2vec DL model, also known as a deep semantic patent similarity. Two patent documents are used as input parameters of the Doc2vec DL model after training, and the vectors of the two patent documents are generated separately. The cosine similarity formula is then used to calculate the semantic similarity of the two patent documents.Combined with the cross-patent similarity matrix, the score of unexamined patents is predicted, and the interactive matrix is completed. The predicted score is shown in formula:(1)Ruw=∑Iv∈vuSimIv,Iw∗Ruv∑Iv∈vuSimIv,Iw,maxSimIv,Iw≥δ,0,Other,.where Ruw represents the predicted score of the Ungraded w patent by the u -th registered user, and Vu represents the set of the scored patents of the Uth registered user; Iv represents the specific patent in the set Iv; Iw represents a specific patent outside the set Vu; SimIv,Iw represents the similarity of the patent Iv,Iw; R represents the score of the u -th registered user on patent Iv; δ Represents the threshold value, which is a custom value between 0 and 1;The specific steps of patent recommendation algorithm based on deep semantic similarity are shown in Figure1:(1)
Enter the original parameters in the recommended method;(2)
Completes the interaction matrix between all registered users and all patents;(3)
Calculate the similarity matrix among all registered users;(4)
According to the similarity matrix of all registered users, the nearest neighbor user list is obtained;(5)
Find a list of patents that may be used for recommendation according to the nearest user list;(6)
Predicting the score of the recommended user on the patent;(7)
Output the recommendation list to the user according to the score.Figure 1
General flow of algorithm.
### 3.2. Neural Network Model of Patent Feature Extraction
The quality of patent features that characterise the content of patent text is the key to patent text analysis. In the field of natural language processing, text classification problems are first classified using expert-defined rules, and then a knowledge-engineered expert classification system is created. Rules and knowledge systems limit the problems that these two methods can solve, and they are time-consuming and inaccurate. The deep learning method based on word vector and CNN (Convolutional Neural Network) has been gradually tested and practised in text classification to overcome the disadvantages of feature extraction in traditional machine learning methods. This paper proposes a deep learning-based feature extraction method for patent text, combining the application of deep learning in the field of natural language processing.Considering the performance advantages of deep learning in natural language processing, especially text classification, this paper proposes a neural network model based on text classification for patent feature extraction and patent analysis. The neural network model used in this paper is based on the supervised learning model, so it is necessary to use marked or trained data sets. The model selection, structure, and parameter optimization are considered. TextCNN is a representation model that uses the CNN model to perform NLP tasks [18]. It combines the ideas of CNN N-grams and the language model, extracts the context features of different dimensions from text vectors through convolution kernels of different sizes, and then uses the maximum pool operation to enhance the features of the extracted text vectors, thus improving the feature extraction ability of texts and enhancing the classification effect of texts.Assuming that a text word vector representsX=x1,x2,⋯,xm,x∈Rd, TextCNN is divided into three stages: convolution layer, pooling layer and full connection layer, as shown in Figure 2.Figure 2
TextCNN structure.The input layer isxi, which represents the word vector of a patent text.(2)x1:m=x1⊕x2⋯⊕xm,⊕ represents the splicing operation, and xi:j represents the splicing of the i to j word vectors in the patent text. x1:m is used as the input of the convolution layer.Because the Attention mechanism can highlight the key features in long sentences, this paper puts forward the “Word2vec + Attention” model, that is, a set of feature weight matrices corresponding to word vectors are obtained by word vector training, and the final text vector representation is obtained by weighting word vectors based on weights.Assuming that the word vector of a patent text representsX=x1,x2,⋯,xm,x∈Rd, the calculation formula of Word2Vec + Attention model is simply described as follows:(3)ut=tanhWaxt+ba,(4)at=exputTU∑texputTU,(5)c=∑tatxt,(6)O=softmaxWoc+bo,(7)y^=argmaxO,ut is the hidden representation calculated by xt, at is the weight vector normalized by the hidden representation, W,b is the network parameter, and c represents the text vector representation weighted by the Attention weight matrix.Deep learning has had remarkable success in the fields of computer vision and speech recognition in recent years, making it widely used in deep learning. When using deep learning to solve natural language processing problems, the first task is to solve the problem of text representation, and then the deep neural network’s ability to extract feature expression can be used instead of relying on complicated artificial feature extraction engineering. Word2vec is a set of neural network models for word embedding generation. A two-layer shallow neural network can be trained to reconstruct the position of words in this model. In practise, Word2vec provides a faster and more stable initial value for the first word embedding layer of a text processing neural network model, especially when the number of data sets is small. The CNN model is optimized in this paper, including network structure optimization and super-parameter optimization. The model structure and key parameters are shown in Figure3.Figure 3
Optimize the structure and parameters of CNN model based on.128 of the input layer in Figure3 indicates the data quantity of one iteration or a batch of training; 400 in the word embedding layer represents the dimension of the pretrained word vector model. In the third convolution layer, the model uses convolution kernels of 3, 4 and 5 lengths at the same time, and the number of each convolution kernel is 200.1 × 200 × mi represents the dimensions of feature mapping after convolution of different convolution kernels, where the size of mi is related to the sentence length and the length of convolution kernel.The word embedding layer is a two-way cyclic neural network structure, which is represented by reverse and forward cycles respectively, as shown in the following formula:(8)clwi=fWlclwi−1+Wslewi−1,(9)crwi=fWrcrwi+1+Wsrewi+1,wi represents the current word, clwi represents the left text of the current word, crwi represents the right text of the current word, ewi represents the word vector of the word wi, Wl,Wr represents the weight parameter, and f is a nonlinear function.According to the context representation of the current wordwi, it can be inferred that the text representation of the current word is:(10)xi=clwi;ewi;crwi.One feature of text processing is that features in the text are closely related to positions, such as the position information of important sentence components, while the latent semantic vectors constructed in the previous layer do not highlight the important information of certain mapping features. Use the maximum pool operation formula as shown in:(11)y3=maxi=1nyi2.The whole layer part also combines the features extracted from the previous layers of texts by a single-layer neural network, and the formula is shown in:(12)y4=W4⋅y3+b4.
### 3.3. Realization of Intellectual Property Risk Early War Model
SM-TE has few funds and talents, and the quality and quantity of intellectual property rights it owns are not high. First, the foundation of SM-TE intellectual property rights is weak. The subjects involved include the government, evaluation agencies, law firms, guarantee agencies, intellectual property trading centers, etc. Only institutions involved in the financing of enterprise intellectual property guarantee can form cooperation and coordinate the distribution of interests and risks among institutions. To ensure the development of intellectual property clothing financing business. At present, there are not many public welfare intellectual property service organizations facing a large number of SM-TE, which are far from meeting the needs of SM-TE in protecting intellectual property rights.The growth and evolution of independent intellectual property rights of SM-TE is a complex system. The growth of independent intellectual property rights depends not only on the innovation mechanism and intellectual property awareness within the company but also on the corresponding growth environment. Therefore, it cannot just be based on our subjective desire, design, and control. For enterprises that carry out independent innovation, early warning of intellectual property risks is an important task. Through the early warning of intellectual property risks, we can find risks and take early action to prevent further losses.There are many links in the risk early-warning process of enterprises’ independent intellectual property rights, and each link requires different elements in the early-warning mechanism. The intellectual property risk early warning index system’s design requirements are in line with the enterprise’s intellectual property management goals, and the indicators have no strong correlation. The index data must be able to accurately reflect the enterprise’s intellectual property risk, as well as the company’s intellectual property management status, problems, and trends. Only when the intellectual property risk warning mechanism operates normally can the intellectual property risk warning process be implemented. The SM-TE intellectual property risk warning process is shown in Figure4.Figure 4
SM-TE intellectual property risk early warning process.The risk identification subsystem identifies the potential risk factors by analyzing the risk sources in the process of intellectual property development. Based on the enterprise information database, the subsystem uses information retrieval software tools to compare and analyse the data and literature in the database, and finally identifies the factors that lead to the property risks of enterprises. In this daily work, once it is determined that the company’s intellectual property information is highly correlated with the existing information in the database, it will send out the risk monitoring and early warning signal in time, enter the early warning subsystem as soon as possible, and judge the risk level.After quantifying the risk indicators, the risk evaluation subsystem measures and evaluates the degree of risk. The routine management work of enterprise intellectual property risk management is the assessment of intellectual property risk. Companies can assess themselves at key nodes based on their intellectual property development. The risk early warning subsystem divides intellectual property risks into no risk, slight risk, medium risk, and serious risk based on the intelligence monitoring information provided by the first two subsystems. The early warning information is fed into the risk response management link when the system sends out an early warning signal. The company decides whether to keep things as they are or take preventative and control measures based on the early warning signal and which preventative and control measures are available.
## 3.1. Patent Recommendation Algorithm
Many science and technology small and microenterprises have yet to develop a perfect intellectual property incentive system, have yet to sign intellectual property confidentiality agreements with their employees, and have neglected intellectual property protection negotiations when collaborating with external units. According to synergy theory, the enhancement of nonlinear interaction among all system elements (capital, technology, equipment, R&D personnel, etc.) leads to the creation of innovation, and the related energy is greater than the innovation energy. Individual movement is governed by coordinated movement, and the system is well-structured, resulting in innovative achievements with dissipative structure characteristics.Intellectual property is an important wealth and resource [1], which is vital to the development of enterprises and countries. Intellectual property not only represents the core competitiveness of enterprises but also represents the comprehensive national strength of the country. As an important intellectual property right, patent symbolizes the power of various scientific and technological achievements, and it is essential to protect the core technologies of enterprises and countries. Enterprises with high patent content have the initiative to survive and develop [2], while countries with high patent content have competitive advantages in terms of scientific and technological strength and comprehensive national strength [3, 4].In this chapter, a patent recommendation algorithm based on deep semantic similarity is proposed, which employs a DL model and completion strategy to fill the sparse interaction matrix between users and patents, addressing the issue of low similarity matrix calculation accuracy. To improve recommendation efficiency, the problem of users in sparse interaction matrix is not severe. Fill the sparse interaction matrix between users and patents with Doc2vec DL model and completion strategy, analyse the collaboration relationship between users, find potential neighbors with similar interests, use neighbor scores to predict unknown patent scores, and recommend patents in turn.A cross-patent similarity matrix is a matrix that contains all patents in both the horizontal and vertical directions. The intermediate data is the semantic similarity of cross-patents calculated by the Doc2vec DL model, also known as a deep semantic patent similarity. Two patent documents are used as input parameters of the Doc2vec DL model after training, and the vectors of the two patent documents are generated separately. The cosine similarity formula is then used to calculate the semantic similarity of the two patent documents.Combined with the cross-patent similarity matrix, the score of unexamined patents is predicted, and the interactive matrix is completed. The predicted score is shown in formula:(1)Ruw=∑Iv∈vuSimIv,Iw∗Ruv∑Iv∈vuSimIv,Iw,maxSimIv,Iw≥δ,0,Other,.where Ruw represents the predicted score of the Ungraded w patent by the u -th registered user, and Vu represents the set of the scored patents of the Uth registered user; Iv represents the specific patent in the set Iv; Iw represents a specific patent outside the set Vu; SimIv,Iw represents the similarity of the patent Iv,Iw; R represents the score of the u -th registered user on patent Iv; δ Represents the threshold value, which is a custom value between 0 and 1;The specific steps of patent recommendation algorithm based on deep semantic similarity are shown in Figure1:(1)
Enter the original parameters in the recommended method;(2)
Completes the interaction matrix between all registered users and all patents;(3)
Calculate the similarity matrix among all registered users;(4)
According to the similarity matrix of all registered users, the nearest neighbor user list is obtained;(5)
Find a list of patents that may be used for recommendation according to the nearest user list;(6)
Predicting the score of the recommended user on the patent;(7)
Output the recommendation list to the user according to the score.Figure 1
General flow of algorithm.
## 3.2. Neural Network Model of Patent Feature Extraction
The quality of patent features that characterise the content of patent text is the key to patent text analysis. In the field of natural language processing, text classification problems are first classified using expert-defined rules, and then a knowledge-engineered expert classification system is created. Rules and knowledge systems limit the problems that these two methods can solve, and they are time-consuming and inaccurate. The deep learning method based on word vector and CNN (Convolutional Neural Network) has been gradually tested and practised in text classification to overcome the disadvantages of feature extraction in traditional machine learning methods. This paper proposes a deep learning-based feature extraction method for patent text, combining the application of deep learning in the field of natural language processing.Considering the performance advantages of deep learning in natural language processing, especially text classification, this paper proposes a neural network model based on text classification for patent feature extraction and patent analysis. The neural network model used in this paper is based on the supervised learning model, so it is necessary to use marked or trained data sets. The model selection, structure, and parameter optimization are considered. TextCNN is a representation model that uses the CNN model to perform NLP tasks [18]. It combines the ideas of CNN N-grams and the language model, extracts the context features of different dimensions from text vectors through convolution kernels of different sizes, and then uses the maximum pool operation to enhance the features of the extracted text vectors, thus improving the feature extraction ability of texts and enhancing the classification effect of texts.Assuming that a text word vector representsX=x1,x2,⋯,xm,x∈Rd, TextCNN is divided into three stages: convolution layer, pooling layer and full connection layer, as shown in Figure 2.Figure 2
TextCNN structure.The input layer isxi, which represents the word vector of a patent text.(2)x1:m=x1⊕x2⋯⊕xm,⊕ represents the splicing operation, and xi:j represents the splicing of the i to j word vectors in the patent text. x1:m is used as the input of the convolution layer.Because the Attention mechanism can highlight the key features in long sentences, this paper puts forward the “Word2vec + Attention” model, that is, a set of feature weight matrices corresponding to word vectors are obtained by word vector training, and the final text vector representation is obtained by weighting word vectors based on weights.Assuming that the word vector of a patent text representsX=x1,x2,⋯,xm,x∈Rd, the calculation formula of Word2Vec + Attention model is simply described as follows:(3)ut=tanhWaxt+ba,(4)at=exputTU∑texputTU,(5)c=∑tatxt,(6)O=softmaxWoc+bo,(7)y^=argmaxO,ut is the hidden representation calculated by xt, at is the weight vector normalized by the hidden representation, W,b is the network parameter, and c represents the text vector representation weighted by the Attention weight matrix.Deep learning has had remarkable success in the fields of computer vision and speech recognition in recent years, making it widely used in deep learning. When using deep learning to solve natural language processing problems, the first task is to solve the problem of text representation, and then the deep neural network’s ability to extract feature expression can be used instead of relying on complicated artificial feature extraction engineering. Word2vec is a set of neural network models for word embedding generation. A two-layer shallow neural network can be trained to reconstruct the position of words in this model. In practise, Word2vec provides a faster and more stable initial value for the first word embedding layer of a text processing neural network model, especially when the number of data sets is small. The CNN model is optimized in this paper, including network structure optimization and super-parameter optimization. The model structure and key parameters are shown in Figure3.Figure 3
Optimize the structure and parameters of CNN model based on.128 of the input layer in Figure3 indicates the data quantity of one iteration or a batch of training; 400 in the word embedding layer represents the dimension of the pretrained word vector model. In the third convolution layer, the model uses convolution kernels of 3, 4 and 5 lengths at the same time, and the number of each convolution kernel is 200.1 × 200 × mi represents the dimensions of feature mapping after convolution of different convolution kernels, where the size of mi is related to the sentence length and the length of convolution kernel.The word embedding layer is a two-way cyclic neural network structure, which is represented by reverse and forward cycles respectively, as shown in the following formula:(8)clwi=fWlclwi−1+Wslewi−1,(9)crwi=fWrcrwi+1+Wsrewi+1,wi represents the current word, clwi represents the left text of the current word, crwi represents the right text of the current word, ewi represents the word vector of the word wi, Wl,Wr represents the weight parameter, and f is a nonlinear function.According to the context representation of the current wordwi, it can be inferred that the text representation of the current word is:(10)xi=clwi;ewi;crwi.One feature of text processing is that features in the text are closely related to positions, such as the position information of important sentence components, while the latent semantic vectors constructed in the previous layer do not highlight the important information of certain mapping features. Use the maximum pool operation formula as shown in:(11)y3=maxi=1nyi2.The whole layer part also combines the features extracted from the previous layers of texts by a single-layer neural network, and the formula is shown in:(12)y4=W4⋅y3+b4.
## 3.3. Realization of Intellectual Property Risk Early War Model
SM-TE has few funds and talents, and the quality and quantity of intellectual property rights it owns are not high. First, the foundation of SM-TE intellectual property rights is weak. The subjects involved include the government, evaluation agencies, law firms, guarantee agencies, intellectual property trading centers, etc. Only institutions involved in the financing of enterprise intellectual property guarantee can form cooperation and coordinate the distribution of interests and risks among institutions. To ensure the development of intellectual property clothing financing business. At present, there are not many public welfare intellectual property service organizations facing a large number of SM-TE, which are far from meeting the needs of SM-TE in protecting intellectual property rights.The growth and evolution of independent intellectual property rights of SM-TE is a complex system. The growth of independent intellectual property rights depends not only on the innovation mechanism and intellectual property awareness within the company but also on the corresponding growth environment. Therefore, it cannot just be based on our subjective desire, design, and control. For enterprises that carry out independent innovation, early warning of intellectual property risks is an important task. Through the early warning of intellectual property risks, we can find risks and take early action to prevent further losses.There are many links in the risk early-warning process of enterprises’ independent intellectual property rights, and each link requires different elements in the early-warning mechanism. The intellectual property risk early warning index system’s design requirements are in line with the enterprise’s intellectual property management goals, and the indicators have no strong correlation. The index data must be able to accurately reflect the enterprise’s intellectual property risk, as well as the company’s intellectual property management status, problems, and trends. Only when the intellectual property risk warning mechanism operates normally can the intellectual property risk warning process be implemented. The SM-TE intellectual property risk warning process is shown in Figure4.Figure 4
SM-TE intellectual property risk early warning process.The risk identification subsystem identifies the potential risk factors by analyzing the risk sources in the process of intellectual property development. Based on the enterprise information database, the subsystem uses information retrieval software tools to compare and analyse the data and literature in the database, and finally identifies the factors that lead to the property risks of enterprises. In this daily work, once it is determined that the company’s intellectual property information is highly correlated with the existing information in the database, it will send out the risk monitoring and early warning signal in time, enter the early warning subsystem as soon as possible, and judge the risk level.After quantifying the risk indicators, the risk evaluation subsystem measures and evaluates the degree of risk. The routine management work of enterprise intellectual property risk management is the assessment of intellectual property risk. Companies can assess themselves at key nodes based on their intellectual property development. The risk early warning subsystem divides intellectual property risks into no risk, slight risk, medium risk, and serious risk based on the intelligence monitoring information provided by the first two subsystems. The early warning information is fed into the risk response management link when the system sends out an early warning signal. The company decides whether to keep things as they are or take preventative and control measures based on the early warning signal and which preventative and control measures are available.
## 4. Experiment and Results
### 4.1. Experimental Setup
The experiment of this algorithm is carried out in a local computer, and the details of the experimental environment are as follows:Processor: Intel(R)Core(TM)i7-7700CPUMemory: 8.00 GBOperating system: microsoftwindows10DL development framework: Deeplearning4j1.0.0-alphaThe experimental data used in this chapter includes two pieces of data. One piece of data comes from the retrieval system of the intellectual property (patent information) public service platform. The patent literature data was downloaded from the patent retrieval system as a patent corpus, and finally, 18,124 experimental patent data documents were obtained.Another part of the data comes from the user registration data collected in this study. As long as the user’s score is collected on the patent, it means that the user likes the patent. The user registration data includes user id, patent id, and score fields, and finally, there are 8096 user registration data of 133 users.
### 4.2. Experimental Result Analysis
We use 50% cross-validation [10] to randomly divide the user registration data of each user into 6 parts, 5 parts from the training set and 1 part from the test set. An average of 6 results is used, such as the final accuracy, recall, and F1 value. Figure 5 shows the influence of paragraph vector dimension on recommendation results.Figure 5
The influence of paragraph vector dimension on recommendation results.It can be seen that with the increase of paragraph vector dimension, the accuracy rate, recall rate, and F1 value first increase and then decrease. When the vector dimension of a word is less than 240, the semantic information of a paragraph is incomplete; It also brings some noise, which leads to errors in feature rendering. Therefore, the final depth semantic model paragraph vector dimension of Doc2vec is 240.The user’s Knum neighborhood represents the choice of the nearest Knum neighborhood of the target user, which affects the recommendation effect. Knum can be 1, 3, 5, 7, 9, 11, and the dimension of the paragraph vector is 240. Different users’ neighborhoodK has different accuracy, recall rate, and F1 value. The results are shown in Figure 6.Figure 6
The influence of neighborhood number on recommendation results.As can be seen from Figure6, with the increasing number of neighborhoods, the precision, recall rate and F1 value show a trend of first increasing and then decreasing. When Knum<7, the neighbor sets with similar hobbies are not fully excavated; When Knum=7, the recommendation effect is the best; When Knum>7 is used, neighbors with similar hobbies are fully mined, but some neighbors with low similarity are also mined, which leads to errors in recommendation. So the final number of neighborhoods is chosen as 7.This algorithm contains an adjustment parameter, thresholdσ, which represents the threshold of similarity between scored patents and unrated patents, and affects the recommendation effect. The paragraph vector dimension is 240, and the neighborhood k is 7, which have different accuracy, recall and F1 values. The results are shown in Figure 7.Figure 7
Influence onσ recommendation results.It can be seen that with the increase ofσ, the precision, recall rate, and F1 value first increase and then decrease. When σ<0.6, the scores of patents with low similarity are also estimated to complete the interaction matrix, and too much is completed, resulting in inaccurate adjacent user sets.Whenσ=0.6, the interaction matrix is completed properly, the recommendation effect is the best. When σ>0.6, it takes a patent with high similarity to estimate the score to complete the interaction matrix, resulting in the sparse matrix may still be very sparse, and the adjacent user set is inaccurate. Therefore, the final σ is selected as 0.6.Through the above experiments, the appropriate paragraph vector dimension 240,Knum=7, σ=0.6 is obtained, and the patent recommendation algorithm based on deep semantic similarity is the best. Therefore, the best algorithm in this paper is compared with the traditional recommendation algorithm, and the experimental results are shown in Table 1.Table 1
Comparison of experimental results.
Algorithm
Accuracy(%)
Recall(%)
F1value (%)
Traditional recommendationalgorithm
12.74
14.21
13.38
Algorithm in this paper
22.41
20.86
21.51As can be seen from the table, the accuracy, recall and F1 value of the proposed algorithm are superior to those of the traditional recommendation algorithm, which are 22.41%, 20.86% and 21.51% respectively. The algorithm proposed in this paper uses Doc2vec DL model and completion strategy to complete the sparse matrix, thus solving the problems of low calculation accuracy and great mining potential of similarity matrix among users in sparse interactive matrix. Therefore, the algorithm in this paper is superior to the traditional algorithm in the experimental evaluation results.This paper introduces two initialization methods of the word embedding layer, random initialization and initialization using the pretrained word vector model. This paper makes a series of initialization of the CNN model using these three methods. Figures8 and 9 show the accuracy loss curves of the CNN model under three initialization methods of word embedding layer, including two training and verification processes.Figure 8
CNN model iteration times and accuracy loss curve.Figure 9
Loss curve of iteration times and accuracy of CNN under three word embedding methods.Experiments show that CNN model shows good advantages in dealing with patent texts. Most of the texts in the patent data set are long texts or Chinese texts, so context information, such as word and sentence order, is particularly important. However, CNN model needs to artificially determine the size (length) of filter convolution kernel to select different range of context information, which has high instability. In order to further verify that the patent feature vector extracted by CNN model has the ability to express the differences of patent text content, this paper adopts the method of comparative experiment to cluster and verify CNN models of two mapping strategies, and counts two types of models in two types of patent samples. The number of results conforming to the formula in the data set represents the proportion of the sample data set, and the results are shown in Table2.Table 2
Experimental results of two text similarity measurement methods.
Model
Cosine similarity
Euclidean distance
CNN
0.988
0.916
BPNN
0.951
0.928The experimental results in Table2 show that the feature vectors extracted by CNN model have a high accuracy in the text-similarity comparison experiment, and the error is within 5%–10% of the given result, which is much higher than other text feature representation methods. The choice of pre-training word vector model must consider the difference between corpus and actual training set. It is still an ideal state for training general word vector model, but it can be considered that it is used to train word vector model for specific applications through transfer learning in the patent field. A great improvement in the accuracy of feature extraction of this patent by using neural network model is to make use of the superior structure of other models to make up for the deficiency of the model itself.
## 4.1. Experimental Setup
The experiment of this algorithm is carried out in a local computer, and the details of the experimental environment are as follows:Processor: Intel(R)Core(TM)i7-7700CPUMemory: 8.00 GBOperating system: microsoftwindows10DL development framework: Deeplearning4j1.0.0-alphaThe experimental data used in this chapter includes two pieces of data. One piece of data comes from the retrieval system of the intellectual property (patent information) public service platform. The patent literature data was downloaded from the patent retrieval system as a patent corpus, and finally, 18,124 experimental patent data documents were obtained.Another part of the data comes from the user registration data collected in this study. As long as the user’s score is collected on the patent, it means that the user likes the patent. The user registration data includes user id, patent id, and score fields, and finally, there are 8096 user registration data of 133 users.
## 4.2. Experimental Result Analysis
We use 50% cross-validation [10] to randomly divide the user registration data of each user into 6 parts, 5 parts from the training set and 1 part from the test set. An average of 6 results is used, such as the final accuracy, recall, and F1 value. Figure 5 shows the influence of paragraph vector dimension on recommendation results.Figure 5
The influence of paragraph vector dimension on recommendation results.It can be seen that with the increase of paragraph vector dimension, the accuracy rate, recall rate, and F1 value first increase and then decrease. When the vector dimension of a word is less than 240, the semantic information of a paragraph is incomplete; It also brings some noise, which leads to errors in feature rendering. Therefore, the final depth semantic model paragraph vector dimension of Doc2vec is 240.The user’s Knum neighborhood represents the choice of the nearest Knum neighborhood of the target user, which affects the recommendation effect. Knum can be 1, 3, 5, 7, 9, 11, and the dimension of the paragraph vector is 240. Different users’ neighborhoodK has different accuracy, recall rate, and F1 value. The results are shown in Figure 6.Figure 6
The influence of neighborhood number on recommendation results.As can be seen from Figure6, with the increasing number of neighborhoods, the precision, recall rate and F1 value show a trend of first increasing and then decreasing. When Knum<7, the neighbor sets with similar hobbies are not fully excavated; When Knum=7, the recommendation effect is the best; When Knum>7 is used, neighbors with similar hobbies are fully mined, but some neighbors with low similarity are also mined, which leads to errors in recommendation. So the final number of neighborhoods is chosen as 7.This algorithm contains an adjustment parameter, thresholdσ, which represents the threshold of similarity between scored patents and unrated patents, and affects the recommendation effect. The paragraph vector dimension is 240, and the neighborhood k is 7, which have different accuracy, recall and F1 values. The results are shown in Figure 7.Figure 7
Influence onσ recommendation results.It can be seen that with the increase ofσ, the precision, recall rate, and F1 value first increase and then decrease. When σ<0.6, the scores of patents with low similarity are also estimated to complete the interaction matrix, and too much is completed, resulting in inaccurate adjacent user sets.Whenσ=0.6, the interaction matrix is completed properly, the recommendation effect is the best. When σ>0.6, it takes a patent with high similarity to estimate the score to complete the interaction matrix, resulting in the sparse matrix may still be very sparse, and the adjacent user set is inaccurate. Therefore, the final σ is selected as 0.6.Through the above experiments, the appropriate paragraph vector dimension 240,Knum=7, σ=0.6 is obtained, and the patent recommendation algorithm based on deep semantic similarity is the best. Therefore, the best algorithm in this paper is compared with the traditional recommendation algorithm, and the experimental results are shown in Table 1.Table 1
Comparison of experimental results.
Algorithm
Accuracy(%)
Recall(%)
F1value (%)
Traditional recommendationalgorithm
12.74
14.21
13.38
Algorithm in this paper
22.41
20.86
21.51As can be seen from the table, the accuracy, recall and F1 value of the proposed algorithm are superior to those of the traditional recommendation algorithm, which are 22.41%, 20.86% and 21.51% respectively. The algorithm proposed in this paper uses Doc2vec DL model and completion strategy to complete the sparse matrix, thus solving the problems of low calculation accuracy and great mining potential of similarity matrix among users in sparse interactive matrix. Therefore, the algorithm in this paper is superior to the traditional algorithm in the experimental evaluation results.This paper introduces two initialization methods of the word embedding layer, random initialization and initialization using the pretrained word vector model. This paper makes a series of initialization of the CNN model using these three methods. Figures8 and 9 show the accuracy loss curves of the CNN model under three initialization methods of word embedding layer, including two training and verification processes.Figure 8
CNN model iteration times and accuracy loss curve.Figure 9
Loss curve of iteration times and accuracy of CNN under three word embedding methods.Experiments show that CNN model shows good advantages in dealing with patent texts. Most of the texts in the patent data set are long texts or Chinese texts, so context information, such as word and sentence order, is particularly important. However, CNN model needs to artificially determine the size (length) of filter convolution kernel to select different range of context information, which has high instability. In order to further verify that the patent feature vector extracted by CNN model has the ability to express the differences of patent text content, this paper adopts the method of comparative experiment to cluster and verify CNN models of two mapping strategies, and counts two types of models in two types of patent samples. The number of results conforming to the formula in the data set represents the proportion of the sample data set, and the results are shown in Table2.Table 2
Experimental results of two text similarity measurement methods.
Model
Cosine similarity
Euclidean distance
CNN
0.988
0.916
BPNN
0.951
0.928The experimental results in Table2 show that the feature vectors extracted by CNN model have a high accuracy in the text-similarity comparison experiment, and the error is within 5%–10% of the given result, which is much higher than other text feature representation methods. The choice of pre-training word vector model must consider the difference between corpus and actual training set. It is still an ideal state for training general word vector model, but it can be considered that it is used to train word vector model for specific applications through transfer learning in the patent field. A great improvement in the accuracy of feature extraction of this patent by using neural network model is to make use of the superior structure of other models to make up for the deficiency of the model itself.
## 5. Conclusions
Innovation plays an important role in the development of Chinese enterprises. According to the process system of risk prevention and control, enterprises can find the source of risks in the process of intellectual property development from the risk identification subsystem, identify potential risk factors, and then enter the risk identification subsystem, and issue an early warning according to the risk monitoring signals. The patent similarity matrix is constructed by using Doc2vec DL model, and the experimental and analytical results show that the patent recommendation algorithm based on deep semantic similarity designed in this chapter is superior to the traditional algorithm. The accuracy, recall, and F1 value of the proposed algorithm are 22.41%, 20.86%, and 21.51%, respectively. In future research, we can establish different types of independent intellectual property risk early warning index systems for different types of companies through field research.
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*Source: 2899674-2022-07-19.xml* | 2899674-2022-07-19_2899674-2022-07-19.md | 59,235 | Risk Warning of Independent Intellectual Property Rights of Small- and Medium-Sized Scientific and Technological Enterprises Using Deep Learning | Junzheng Wu | Mobile Information Systems
(2022) | Computer Science | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2899674 | 2899674-2022-07-19.xml | ---
## Abstract
Strengthening the construction of intellectual property rights of SM-TE (small and medium-sized scientific and technological enterprises) in China is an important measure to speed up the development of SM-TE, and improve their scientific and technological innovation ability and market competitiveness. In this paper, a patent recommendation algorithm based on deep semantic similarity is proposed to solve the problem of low calculation accuracy of similarity matrix among users in sparse interaction matrix. The algorithm trains the patent corpus, and obtains the Doc2vec DL (Deep Learning) model, and then constructs the semantic similarity matrix among patents through the DL model. On this basis, to further improve the modeling ability of semantic expression and feature extraction, this paper optimizes CNN (Convolutional Neural Network) model, using a variety of pretrained word vector models, multi-layer classifiers, etc., to improve the model accuracy and generate feature vectors of different dimensions. The results show that the accuracy, recall rate and F1 value of the proposed algorithm are better than those of the traditional recommendation algorithm, which are 22.41%, 20.86% and 21.51% respectively. The experiment shows that this paper can guide Chinese enterprises to establish and improve the risk warning system of independent intellectual property rights, thus reducing the losses of enterprises.
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## Body
## 1. Introduction
SM-TE (Small and Medium-sized Scientific and Technological Enterprises) innovation is an important force to promote social progress, stimulate national economic growth and consolidate the national independent innovation strength. At present, international competition is mainly reflected in the competition of independent innovation forces. Compared with developed countries, China’s small and micro-enterprises in science and technology have insufficient innovation ability, and the low level of intellectual property management is also an urgent problem to be solved. Intellectual property ownership has become an important index to measure the core competitiveness and innovation ability of enterprises. Chinese enterprises urgently need to use independent intellectual property rights to break the international monopoly and blockade, go abroad and strive for greater development space. Due to the simple industrial structure of SM-TE, it is easy to pay attention to the technological development of the leading industries. In addition, SM-TE has a close connection with the market and high market sensitivity. SM-TE with innovative ability must become a new force for independent intellectual property innovation in China.Risk early-warning research is a hot topic both domestically and internationally. Domestic scholars have looked into the medium-term early warning mechanisms of start-up companies, commercial bank loan risk early warning mechanisms, marketing risk early warning mechanisms, and financial risk early warning mechanisms of small and medium-sized businesses, as well as knowledge management risk early warning and knowledge capital risk early warning mechanisms [1–3]. According to He et al., there is generally no financial risk in enterprises during periods of rapid economic growth, and there are many factors that affect the financial risk of enterprises [4], the most prominent of which are the economic situation, stock price, and inflation. Deng et al. used the univariate analysis method to compare 79 companies from crisis and normal enterprises [5]. Finally, it is discovered that cash flow divided by total liabilities is the best predictor of an enterprise’s financial crisis. Liang et al. used multivariate analysis to assess enterprise financial risk early warning. This method combines financial ratios with multivariate judgment to provide an early warning system for financial risk [6]. In their study, Niu et al. used both cash flow and non-cash flow indicators and proposed a research idea of financial early warning based on cash flow [7]. There are, however, few studies on early detection of intellectual property risks. This is because the emergence of intellectual property risk in the process of enterprise independent innovation is influenced by a variety of factors, and it is difficult to predict intellectual property risk in the process of independent innovation.Deep learning (DL) is a new concept in machine learning. The term “deep learning” is derived from the term “neural network.” DL, in particular, has a large number of hidden layers that determine its complicated internal mapping relationship. We can learn the effective characteristics of data and have a strong learning ability thanks to this complex internal relationship. Both the DL network and the BP neural network (BP neural network) are machine learning models, but they differ significantly. A shallow neural network is a BPNN, and a multi-layer deep neural network is DL. Many academic and practical examples demonstrate that DL is more important in defining complex functional relationships. As a result, the goal of this paper is to apply DL knowledge to SM-independent TE’s intellectual property risk warning, to put the scientific concept of development in the field of independent intellectual property risk warning into practise, and to use it flexibly to protect the company’s independent intellectual property security, which has both theoretical and practical implications. The following aspects of this paper’s innovation: (1) In this paper, the existing research on intellectual property risk pre-operation is deeply studied, which breaks the current situation that most of the existing research focuses on the identification, risk assessment, and control of intellectual property risk response measures, and tries to build an early warning system of intellectual property risk. The whole system is divided into the risk identification subsystem, risk assessment subsystem, and risk early warning subsystem, which is conducive to risk prevention and control in the whole process of intellectual property development. (2) In the aspect of collaboration among users, aiming at the problem of low calculation accuracy of similarity matrix among users in sparse interaction matrix, a patent recommendation algorithm based on deep semantic similarity is proposed. The algorithm extracts the nearest neighbor of the target user, estimates the patent score of the target user according to the patent score of the neighbor, sorts the patents according to the score, and recommends the patent with the highest score to the target user. (3) To further improve the semantic expression and feature extraction ability of the model, the neural network model for feature extraction and analysis of patent texts is optimized and enhanced. Through relevant experiments, the improved model is evaluated and analyzed on multiple pretrained word vector models and multiple data sets.
## 2. Related Work
### 2.1. Risk Early Warning Research
Neuner research shows that the financial distress of an enterprise may not necessarily lead to bankruptcy or reorganization, but the bankrupt or reorganized enterprise must be the one with financial distress [8]. Liu et al. believe that the serious cash-out problem of an enterprise cannot be solved by conventional means, and if the operation or structure of the enterprise needs large-scale restructuring, the enterprise will be in financial trouble [9]. Liu’s model for financial risk early warning research has many limitations on assumptions compared with multivariate judgment. Logistic model has lower data requirements and is more applicable, so it is a better method [10].Hz et al. introduced artificial neural network into the field of financial risk early warning, and they chose a three-layer neural network for early warning. At the same time, they used multiple judgment methods to make empirical analyses and compare the results [11]. The results show that the accuracy and fault tolerance of artificial neural networks are better. Zhang et al. introduced qualitative indicators such as working environment, internal control, external environment, business environment, and analyzed them in combination with traditional quantitative indicators such as solvency indicators and profitability indicators [12]. However, it is not tested by specific data, but it is a good idea to introduce qualitative indicators. Yudo et al. have established the financial risk judgment index system for oil companies, and based on this, they have established the financial risk early warning model of fuzzy neural network [13]. Li et al. used the data processed by GM(1 : 1) model of function transformation as the input value of BPNN to make an early warning of financial risks [14].
### 2.2. Research Status of DL Network
DL-based models and algorithms have made remarkable achievements in the fields of computer vision and speech processing. At present, the application of DL in natural language processing has gradually matured. In some natural language processing tasks, such as text classification, sentiment analysis, DL method shows greater advantages than traditional text processing methods.Nateghi et al. verified through experiments that DL methods using unsupervised training at all levels can describe complex functions well and avoid over-fitting problems caused by network training [15]. Colombo et al. have made great success in using DL neural networks. The input values of its model do not contain artificial features but image pixels, which has become a great breakthrough in the field of image recognition [16]. Panwar et al. combined the grey prediction model and neural network model to study financial early warning [17]; Dhuri et al. use statistical methods to optimize the artificial neural network model and improve the financial early warning model based on the neural network with higher reliability [18]; Hui et al. used DL method to build a neural network model to predict the financial distress of enterprises, with high accuracy [19].Chen et al. used DL method to extract the features of objects, initialized the network, and then used back propagation algorithm to fine-tune the network parameters [20]. Liu et al. used a self-coding DL neural network in the field of speech recognition [21]. Firstly, DL method was used to extract the features of speech signals. Then it is tested by BPNN and DL network respectively. The results show that the accuracy of DL method is nearly 20% higher than that of the traditional BPNN method, and it has a good effect. Wei et al. have studied the application of DL network in the prediction of stock index futures. In this paper, an automatic encoder and other algorithms are used to establish DL network model, and the comparison is made. Finally, a network prediction system for trading is constructed according to trading choices [22].
## 2.1. Risk Early Warning Research
Neuner research shows that the financial distress of an enterprise may not necessarily lead to bankruptcy or reorganization, but the bankrupt or reorganized enterprise must be the one with financial distress [8]. Liu et al. believe that the serious cash-out problem of an enterprise cannot be solved by conventional means, and if the operation or structure of the enterprise needs large-scale restructuring, the enterprise will be in financial trouble [9]. Liu’s model for financial risk early warning research has many limitations on assumptions compared with multivariate judgment. Logistic model has lower data requirements and is more applicable, so it is a better method [10].Hz et al. introduced artificial neural network into the field of financial risk early warning, and they chose a three-layer neural network for early warning. At the same time, they used multiple judgment methods to make empirical analyses and compare the results [11]. The results show that the accuracy and fault tolerance of artificial neural networks are better. Zhang et al. introduced qualitative indicators such as working environment, internal control, external environment, business environment, and analyzed them in combination with traditional quantitative indicators such as solvency indicators and profitability indicators [12]. However, it is not tested by specific data, but it is a good idea to introduce qualitative indicators. Yudo et al. have established the financial risk judgment index system for oil companies, and based on this, they have established the financial risk early warning model of fuzzy neural network [13]. Li et al. used the data processed by GM(1 : 1) model of function transformation as the input value of BPNN to make an early warning of financial risks [14].
## 2.2. Research Status of DL Network
DL-based models and algorithms have made remarkable achievements in the fields of computer vision and speech processing. At present, the application of DL in natural language processing has gradually matured. In some natural language processing tasks, such as text classification, sentiment analysis, DL method shows greater advantages than traditional text processing methods.Nateghi et al. verified through experiments that DL methods using unsupervised training at all levels can describe complex functions well and avoid over-fitting problems caused by network training [15]. Colombo et al. have made great success in using DL neural networks. The input values of its model do not contain artificial features but image pixels, which has become a great breakthrough in the field of image recognition [16]. Panwar et al. combined the grey prediction model and neural network model to study financial early warning [17]; Dhuri et al. use statistical methods to optimize the artificial neural network model and improve the financial early warning model based on the neural network with higher reliability [18]; Hui et al. used DL method to build a neural network model to predict the financial distress of enterprises, with high accuracy [19].Chen et al. used DL method to extract the features of objects, initialized the network, and then used back propagation algorithm to fine-tune the network parameters [20]. Liu et al. used a self-coding DL neural network in the field of speech recognition [21]. Firstly, DL method was used to extract the features of speech signals. Then it is tested by BPNN and DL network respectively. The results show that the accuracy of DL method is nearly 20% higher than that of the traditional BPNN method, and it has a good effect. Wei et al. have studied the application of DL network in the prediction of stock index futures. In this paper, an automatic encoder and other algorithms are used to establish DL network model, and the comparison is made. Finally, a network prediction system for trading is constructed according to trading choices [22].
## 3. Methodology
### 3.1. Patent Recommendation Algorithm
Many science and technology small and microenterprises have yet to develop a perfect intellectual property incentive system, have yet to sign intellectual property confidentiality agreements with their employees, and have neglected intellectual property protection negotiations when collaborating with external units. According to synergy theory, the enhancement of nonlinear interaction among all system elements (capital, technology, equipment, R&D personnel, etc.) leads to the creation of innovation, and the related energy is greater than the innovation energy. Individual movement is governed by coordinated movement, and the system is well-structured, resulting in innovative achievements with dissipative structure characteristics.Intellectual property is an important wealth and resource [1], which is vital to the development of enterprises and countries. Intellectual property not only represents the core competitiveness of enterprises but also represents the comprehensive national strength of the country. As an important intellectual property right, patent symbolizes the power of various scientific and technological achievements, and it is essential to protect the core technologies of enterprises and countries. Enterprises with high patent content have the initiative to survive and develop [2], while countries with high patent content have competitive advantages in terms of scientific and technological strength and comprehensive national strength [3, 4].In this chapter, a patent recommendation algorithm based on deep semantic similarity is proposed, which employs a DL model and completion strategy to fill the sparse interaction matrix between users and patents, addressing the issue of low similarity matrix calculation accuracy. To improve recommendation efficiency, the problem of users in sparse interaction matrix is not severe. Fill the sparse interaction matrix between users and patents with Doc2vec DL model and completion strategy, analyse the collaboration relationship between users, find potential neighbors with similar interests, use neighbor scores to predict unknown patent scores, and recommend patents in turn.A cross-patent similarity matrix is a matrix that contains all patents in both the horizontal and vertical directions. The intermediate data is the semantic similarity of cross-patents calculated by the Doc2vec DL model, also known as a deep semantic patent similarity. Two patent documents are used as input parameters of the Doc2vec DL model after training, and the vectors of the two patent documents are generated separately. The cosine similarity formula is then used to calculate the semantic similarity of the two patent documents.Combined with the cross-patent similarity matrix, the score of unexamined patents is predicted, and the interactive matrix is completed. The predicted score is shown in formula:(1)Ruw=∑Iv∈vuSimIv,Iw∗Ruv∑Iv∈vuSimIv,Iw,maxSimIv,Iw≥δ,0,Other,.where Ruw represents the predicted score of the Ungraded w patent by the u -th registered user, and Vu represents the set of the scored patents of the Uth registered user; Iv represents the specific patent in the set Iv; Iw represents a specific patent outside the set Vu; SimIv,Iw represents the similarity of the patent Iv,Iw; R represents the score of the u -th registered user on patent Iv; δ Represents the threshold value, which is a custom value between 0 and 1;The specific steps of patent recommendation algorithm based on deep semantic similarity are shown in Figure1:(1)
Enter the original parameters in the recommended method;(2)
Completes the interaction matrix between all registered users and all patents;(3)
Calculate the similarity matrix among all registered users;(4)
According to the similarity matrix of all registered users, the nearest neighbor user list is obtained;(5)
Find a list of patents that may be used for recommendation according to the nearest user list;(6)
Predicting the score of the recommended user on the patent;(7)
Output the recommendation list to the user according to the score.Figure 1
General flow of algorithm.
### 3.2. Neural Network Model of Patent Feature Extraction
The quality of patent features that characterise the content of patent text is the key to patent text analysis. In the field of natural language processing, text classification problems are first classified using expert-defined rules, and then a knowledge-engineered expert classification system is created. Rules and knowledge systems limit the problems that these two methods can solve, and they are time-consuming and inaccurate. The deep learning method based on word vector and CNN (Convolutional Neural Network) has been gradually tested and practised in text classification to overcome the disadvantages of feature extraction in traditional machine learning methods. This paper proposes a deep learning-based feature extraction method for patent text, combining the application of deep learning in the field of natural language processing.Considering the performance advantages of deep learning in natural language processing, especially text classification, this paper proposes a neural network model based on text classification for patent feature extraction and patent analysis. The neural network model used in this paper is based on the supervised learning model, so it is necessary to use marked or trained data sets. The model selection, structure, and parameter optimization are considered. TextCNN is a representation model that uses the CNN model to perform NLP tasks [18]. It combines the ideas of CNN N-grams and the language model, extracts the context features of different dimensions from text vectors through convolution kernels of different sizes, and then uses the maximum pool operation to enhance the features of the extracted text vectors, thus improving the feature extraction ability of texts and enhancing the classification effect of texts.Assuming that a text word vector representsX=x1,x2,⋯,xm,x∈Rd, TextCNN is divided into three stages: convolution layer, pooling layer and full connection layer, as shown in Figure 2.Figure 2
TextCNN structure.The input layer isxi, which represents the word vector of a patent text.(2)x1:m=x1⊕x2⋯⊕xm,⊕ represents the splicing operation, and xi:j represents the splicing of the i to j word vectors in the patent text. x1:m is used as the input of the convolution layer.Because the Attention mechanism can highlight the key features in long sentences, this paper puts forward the “Word2vec + Attention” model, that is, a set of feature weight matrices corresponding to word vectors are obtained by word vector training, and the final text vector representation is obtained by weighting word vectors based on weights.Assuming that the word vector of a patent text representsX=x1,x2,⋯,xm,x∈Rd, the calculation formula of Word2Vec + Attention model is simply described as follows:(3)ut=tanhWaxt+ba,(4)at=exputTU∑texputTU,(5)c=∑tatxt,(6)O=softmaxWoc+bo,(7)y^=argmaxO,ut is the hidden representation calculated by xt, at is the weight vector normalized by the hidden representation, W,b is the network parameter, and c represents the text vector representation weighted by the Attention weight matrix.Deep learning has had remarkable success in the fields of computer vision and speech recognition in recent years, making it widely used in deep learning. When using deep learning to solve natural language processing problems, the first task is to solve the problem of text representation, and then the deep neural network’s ability to extract feature expression can be used instead of relying on complicated artificial feature extraction engineering. Word2vec is a set of neural network models for word embedding generation. A two-layer shallow neural network can be trained to reconstruct the position of words in this model. In practise, Word2vec provides a faster and more stable initial value for the first word embedding layer of a text processing neural network model, especially when the number of data sets is small. The CNN model is optimized in this paper, including network structure optimization and super-parameter optimization. The model structure and key parameters are shown in Figure3.Figure 3
Optimize the structure and parameters of CNN model based on.128 of the input layer in Figure3 indicates the data quantity of one iteration or a batch of training; 400 in the word embedding layer represents the dimension of the pretrained word vector model. In the third convolution layer, the model uses convolution kernels of 3, 4 and 5 lengths at the same time, and the number of each convolution kernel is 200.1 × 200 × mi represents the dimensions of feature mapping after convolution of different convolution kernels, where the size of mi is related to the sentence length and the length of convolution kernel.The word embedding layer is a two-way cyclic neural network structure, which is represented by reverse and forward cycles respectively, as shown in the following formula:(8)clwi=fWlclwi−1+Wslewi−1,(9)crwi=fWrcrwi+1+Wsrewi+1,wi represents the current word, clwi represents the left text of the current word, crwi represents the right text of the current word, ewi represents the word vector of the word wi, Wl,Wr represents the weight parameter, and f is a nonlinear function.According to the context representation of the current wordwi, it can be inferred that the text representation of the current word is:(10)xi=clwi;ewi;crwi.One feature of text processing is that features in the text are closely related to positions, such as the position information of important sentence components, while the latent semantic vectors constructed in the previous layer do not highlight the important information of certain mapping features. Use the maximum pool operation formula as shown in:(11)y3=maxi=1nyi2.The whole layer part also combines the features extracted from the previous layers of texts by a single-layer neural network, and the formula is shown in:(12)y4=W4⋅y3+b4.
### 3.3. Realization of Intellectual Property Risk Early War Model
SM-TE has few funds and talents, and the quality and quantity of intellectual property rights it owns are not high. First, the foundation of SM-TE intellectual property rights is weak. The subjects involved include the government, evaluation agencies, law firms, guarantee agencies, intellectual property trading centers, etc. Only institutions involved in the financing of enterprise intellectual property guarantee can form cooperation and coordinate the distribution of interests and risks among institutions. To ensure the development of intellectual property clothing financing business. At present, there are not many public welfare intellectual property service organizations facing a large number of SM-TE, which are far from meeting the needs of SM-TE in protecting intellectual property rights.The growth and evolution of independent intellectual property rights of SM-TE is a complex system. The growth of independent intellectual property rights depends not only on the innovation mechanism and intellectual property awareness within the company but also on the corresponding growth environment. Therefore, it cannot just be based on our subjective desire, design, and control. For enterprises that carry out independent innovation, early warning of intellectual property risks is an important task. Through the early warning of intellectual property risks, we can find risks and take early action to prevent further losses.There are many links in the risk early-warning process of enterprises’ independent intellectual property rights, and each link requires different elements in the early-warning mechanism. The intellectual property risk early warning index system’s design requirements are in line with the enterprise’s intellectual property management goals, and the indicators have no strong correlation. The index data must be able to accurately reflect the enterprise’s intellectual property risk, as well as the company’s intellectual property management status, problems, and trends. Only when the intellectual property risk warning mechanism operates normally can the intellectual property risk warning process be implemented. The SM-TE intellectual property risk warning process is shown in Figure4.Figure 4
SM-TE intellectual property risk early warning process.The risk identification subsystem identifies the potential risk factors by analyzing the risk sources in the process of intellectual property development. Based on the enterprise information database, the subsystem uses information retrieval software tools to compare and analyse the data and literature in the database, and finally identifies the factors that lead to the property risks of enterprises. In this daily work, once it is determined that the company’s intellectual property information is highly correlated with the existing information in the database, it will send out the risk monitoring and early warning signal in time, enter the early warning subsystem as soon as possible, and judge the risk level.After quantifying the risk indicators, the risk evaluation subsystem measures and evaluates the degree of risk. The routine management work of enterprise intellectual property risk management is the assessment of intellectual property risk. Companies can assess themselves at key nodes based on their intellectual property development. The risk early warning subsystem divides intellectual property risks into no risk, slight risk, medium risk, and serious risk based on the intelligence monitoring information provided by the first two subsystems. The early warning information is fed into the risk response management link when the system sends out an early warning signal. The company decides whether to keep things as they are or take preventative and control measures based on the early warning signal and which preventative and control measures are available.
## 3.1. Patent Recommendation Algorithm
Many science and technology small and microenterprises have yet to develop a perfect intellectual property incentive system, have yet to sign intellectual property confidentiality agreements with their employees, and have neglected intellectual property protection negotiations when collaborating with external units. According to synergy theory, the enhancement of nonlinear interaction among all system elements (capital, technology, equipment, R&D personnel, etc.) leads to the creation of innovation, and the related energy is greater than the innovation energy. Individual movement is governed by coordinated movement, and the system is well-structured, resulting in innovative achievements with dissipative structure characteristics.Intellectual property is an important wealth and resource [1], which is vital to the development of enterprises and countries. Intellectual property not only represents the core competitiveness of enterprises but also represents the comprehensive national strength of the country. As an important intellectual property right, patent symbolizes the power of various scientific and technological achievements, and it is essential to protect the core technologies of enterprises and countries. Enterprises with high patent content have the initiative to survive and develop [2], while countries with high patent content have competitive advantages in terms of scientific and technological strength and comprehensive national strength [3, 4].In this chapter, a patent recommendation algorithm based on deep semantic similarity is proposed, which employs a DL model and completion strategy to fill the sparse interaction matrix between users and patents, addressing the issue of low similarity matrix calculation accuracy. To improve recommendation efficiency, the problem of users in sparse interaction matrix is not severe. Fill the sparse interaction matrix between users and patents with Doc2vec DL model and completion strategy, analyse the collaboration relationship between users, find potential neighbors with similar interests, use neighbor scores to predict unknown patent scores, and recommend patents in turn.A cross-patent similarity matrix is a matrix that contains all patents in both the horizontal and vertical directions. The intermediate data is the semantic similarity of cross-patents calculated by the Doc2vec DL model, also known as a deep semantic patent similarity. Two patent documents are used as input parameters of the Doc2vec DL model after training, and the vectors of the two patent documents are generated separately. The cosine similarity formula is then used to calculate the semantic similarity of the two patent documents.Combined with the cross-patent similarity matrix, the score of unexamined patents is predicted, and the interactive matrix is completed. The predicted score is shown in formula:(1)Ruw=∑Iv∈vuSimIv,Iw∗Ruv∑Iv∈vuSimIv,Iw,maxSimIv,Iw≥δ,0,Other,.where Ruw represents the predicted score of the Ungraded w patent by the u -th registered user, and Vu represents the set of the scored patents of the Uth registered user; Iv represents the specific patent in the set Iv; Iw represents a specific patent outside the set Vu; SimIv,Iw represents the similarity of the patent Iv,Iw; R represents the score of the u -th registered user on patent Iv; δ Represents the threshold value, which is a custom value between 0 and 1;The specific steps of patent recommendation algorithm based on deep semantic similarity are shown in Figure1:(1)
Enter the original parameters in the recommended method;(2)
Completes the interaction matrix between all registered users and all patents;(3)
Calculate the similarity matrix among all registered users;(4)
According to the similarity matrix of all registered users, the nearest neighbor user list is obtained;(5)
Find a list of patents that may be used for recommendation according to the nearest user list;(6)
Predicting the score of the recommended user on the patent;(7)
Output the recommendation list to the user according to the score.Figure 1
General flow of algorithm.
## 3.2. Neural Network Model of Patent Feature Extraction
The quality of patent features that characterise the content of patent text is the key to patent text analysis. In the field of natural language processing, text classification problems are first classified using expert-defined rules, and then a knowledge-engineered expert classification system is created. Rules and knowledge systems limit the problems that these two methods can solve, and they are time-consuming and inaccurate. The deep learning method based on word vector and CNN (Convolutional Neural Network) has been gradually tested and practised in text classification to overcome the disadvantages of feature extraction in traditional machine learning methods. This paper proposes a deep learning-based feature extraction method for patent text, combining the application of deep learning in the field of natural language processing.Considering the performance advantages of deep learning in natural language processing, especially text classification, this paper proposes a neural network model based on text classification for patent feature extraction and patent analysis. The neural network model used in this paper is based on the supervised learning model, so it is necessary to use marked or trained data sets. The model selection, structure, and parameter optimization are considered. TextCNN is a representation model that uses the CNN model to perform NLP tasks [18]. It combines the ideas of CNN N-grams and the language model, extracts the context features of different dimensions from text vectors through convolution kernels of different sizes, and then uses the maximum pool operation to enhance the features of the extracted text vectors, thus improving the feature extraction ability of texts and enhancing the classification effect of texts.Assuming that a text word vector representsX=x1,x2,⋯,xm,x∈Rd, TextCNN is divided into three stages: convolution layer, pooling layer and full connection layer, as shown in Figure 2.Figure 2
TextCNN structure.The input layer isxi, which represents the word vector of a patent text.(2)x1:m=x1⊕x2⋯⊕xm,⊕ represents the splicing operation, and xi:j represents the splicing of the i to j word vectors in the patent text. x1:m is used as the input of the convolution layer.Because the Attention mechanism can highlight the key features in long sentences, this paper puts forward the “Word2vec + Attention” model, that is, a set of feature weight matrices corresponding to word vectors are obtained by word vector training, and the final text vector representation is obtained by weighting word vectors based on weights.Assuming that the word vector of a patent text representsX=x1,x2,⋯,xm,x∈Rd, the calculation formula of Word2Vec + Attention model is simply described as follows:(3)ut=tanhWaxt+ba,(4)at=exputTU∑texputTU,(5)c=∑tatxt,(6)O=softmaxWoc+bo,(7)y^=argmaxO,ut is the hidden representation calculated by xt, at is the weight vector normalized by the hidden representation, W,b is the network parameter, and c represents the text vector representation weighted by the Attention weight matrix.Deep learning has had remarkable success in the fields of computer vision and speech recognition in recent years, making it widely used in deep learning. When using deep learning to solve natural language processing problems, the first task is to solve the problem of text representation, and then the deep neural network’s ability to extract feature expression can be used instead of relying on complicated artificial feature extraction engineering. Word2vec is a set of neural network models for word embedding generation. A two-layer shallow neural network can be trained to reconstruct the position of words in this model. In practise, Word2vec provides a faster and more stable initial value for the first word embedding layer of a text processing neural network model, especially when the number of data sets is small. The CNN model is optimized in this paper, including network structure optimization and super-parameter optimization. The model structure and key parameters are shown in Figure3.Figure 3
Optimize the structure and parameters of CNN model based on.128 of the input layer in Figure3 indicates the data quantity of one iteration or a batch of training; 400 in the word embedding layer represents the dimension of the pretrained word vector model. In the third convolution layer, the model uses convolution kernels of 3, 4 and 5 lengths at the same time, and the number of each convolution kernel is 200.1 × 200 × mi represents the dimensions of feature mapping after convolution of different convolution kernels, where the size of mi is related to the sentence length and the length of convolution kernel.The word embedding layer is a two-way cyclic neural network structure, which is represented by reverse and forward cycles respectively, as shown in the following formula:(8)clwi=fWlclwi−1+Wslewi−1,(9)crwi=fWrcrwi+1+Wsrewi+1,wi represents the current word, clwi represents the left text of the current word, crwi represents the right text of the current word, ewi represents the word vector of the word wi, Wl,Wr represents the weight parameter, and f is a nonlinear function.According to the context representation of the current wordwi, it can be inferred that the text representation of the current word is:(10)xi=clwi;ewi;crwi.One feature of text processing is that features in the text are closely related to positions, such as the position information of important sentence components, while the latent semantic vectors constructed in the previous layer do not highlight the important information of certain mapping features. Use the maximum pool operation formula as shown in:(11)y3=maxi=1nyi2.The whole layer part also combines the features extracted from the previous layers of texts by a single-layer neural network, and the formula is shown in:(12)y4=W4⋅y3+b4.
## 3.3. Realization of Intellectual Property Risk Early War Model
SM-TE has few funds and talents, and the quality and quantity of intellectual property rights it owns are not high. First, the foundation of SM-TE intellectual property rights is weak. The subjects involved include the government, evaluation agencies, law firms, guarantee agencies, intellectual property trading centers, etc. Only institutions involved in the financing of enterprise intellectual property guarantee can form cooperation and coordinate the distribution of interests and risks among institutions. To ensure the development of intellectual property clothing financing business. At present, there are not many public welfare intellectual property service organizations facing a large number of SM-TE, which are far from meeting the needs of SM-TE in protecting intellectual property rights.The growth and evolution of independent intellectual property rights of SM-TE is a complex system. The growth of independent intellectual property rights depends not only on the innovation mechanism and intellectual property awareness within the company but also on the corresponding growth environment. Therefore, it cannot just be based on our subjective desire, design, and control. For enterprises that carry out independent innovation, early warning of intellectual property risks is an important task. Through the early warning of intellectual property risks, we can find risks and take early action to prevent further losses.There are many links in the risk early-warning process of enterprises’ independent intellectual property rights, and each link requires different elements in the early-warning mechanism. The intellectual property risk early warning index system’s design requirements are in line with the enterprise’s intellectual property management goals, and the indicators have no strong correlation. The index data must be able to accurately reflect the enterprise’s intellectual property risk, as well as the company’s intellectual property management status, problems, and trends. Only when the intellectual property risk warning mechanism operates normally can the intellectual property risk warning process be implemented. The SM-TE intellectual property risk warning process is shown in Figure4.Figure 4
SM-TE intellectual property risk early warning process.The risk identification subsystem identifies the potential risk factors by analyzing the risk sources in the process of intellectual property development. Based on the enterprise information database, the subsystem uses information retrieval software tools to compare and analyse the data and literature in the database, and finally identifies the factors that lead to the property risks of enterprises. In this daily work, once it is determined that the company’s intellectual property information is highly correlated with the existing information in the database, it will send out the risk monitoring and early warning signal in time, enter the early warning subsystem as soon as possible, and judge the risk level.After quantifying the risk indicators, the risk evaluation subsystem measures and evaluates the degree of risk. The routine management work of enterprise intellectual property risk management is the assessment of intellectual property risk. Companies can assess themselves at key nodes based on their intellectual property development. The risk early warning subsystem divides intellectual property risks into no risk, slight risk, medium risk, and serious risk based on the intelligence monitoring information provided by the first two subsystems. The early warning information is fed into the risk response management link when the system sends out an early warning signal. The company decides whether to keep things as they are or take preventative and control measures based on the early warning signal and which preventative and control measures are available.
## 4. Experiment and Results
### 4.1. Experimental Setup
The experiment of this algorithm is carried out in a local computer, and the details of the experimental environment are as follows:Processor: Intel(R)Core(TM)i7-7700CPUMemory: 8.00 GBOperating system: microsoftwindows10DL development framework: Deeplearning4j1.0.0-alphaThe experimental data used in this chapter includes two pieces of data. One piece of data comes from the retrieval system of the intellectual property (patent information) public service platform. The patent literature data was downloaded from the patent retrieval system as a patent corpus, and finally, 18,124 experimental patent data documents were obtained.Another part of the data comes from the user registration data collected in this study. As long as the user’s score is collected on the patent, it means that the user likes the patent. The user registration data includes user id, patent id, and score fields, and finally, there are 8096 user registration data of 133 users.
### 4.2. Experimental Result Analysis
We use 50% cross-validation [10] to randomly divide the user registration data of each user into 6 parts, 5 parts from the training set and 1 part from the test set. An average of 6 results is used, such as the final accuracy, recall, and F1 value. Figure 5 shows the influence of paragraph vector dimension on recommendation results.Figure 5
The influence of paragraph vector dimension on recommendation results.It can be seen that with the increase of paragraph vector dimension, the accuracy rate, recall rate, and F1 value first increase and then decrease. When the vector dimension of a word is less than 240, the semantic information of a paragraph is incomplete; It also brings some noise, which leads to errors in feature rendering. Therefore, the final depth semantic model paragraph vector dimension of Doc2vec is 240.The user’s Knum neighborhood represents the choice of the nearest Knum neighborhood of the target user, which affects the recommendation effect. Knum can be 1, 3, 5, 7, 9, 11, and the dimension of the paragraph vector is 240. Different users’ neighborhoodK has different accuracy, recall rate, and F1 value. The results are shown in Figure 6.Figure 6
The influence of neighborhood number on recommendation results.As can be seen from Figure6, with the increasing number of neighborhoods, the precision, recall rate and F1 value show a trend of first increasing and then decreasing. When Knum<7, the neighbor sets with similar hobbies are not fully excavated; When Knum=7, the recommendation effect is the best; When Knum>7 is used, neighbors with similar hobbies are fully mined, but some neighbors with low similarity are also mined, which leads to errors in recommendation. So the final number of neighborhoods is chosen as 7.This algorithm contains an adjustment parameter, thresholdσ, which represents the threshold of similarity between scored patents and unrated patents, and affects the recommendation effect. The paragraph vector dimension is 240, and the neighborhood k is 7, which have different accuracy, recall and F1 values. The results are shown in Figure 7.Figure 7
Influence onσ recommendation results.It can be seen that with the increase ofσ, the precision, recall rate, and F1 value first increase and then decrease. When σ<0.6, the scores of patents with low similarity are also estimated to complete the interaction matrix, and too much is completed, resulting in inaccurate adjacent user sets.Whenσ=0.6, the interaction matrix is completed properly, the recommendation effect is the best. When σ>0.6, it takes a patent with high similarity to estimate the score to complete the interaction matrix, resulting in the sparse matrix may still be very sparse, and the adjacent user set is inaccurate. Therefore, the final σ is selected as 0.6.Through the above experiments, the appropriate paragraph vector dimension 240,Knum=7, σ=0.6 is obtained, and the patent recommendation algorithm based on deep semantic similarity is the best. Therefore, the best algorithm in this paper is compared with the traditional recommendation algorithm, and the experimental results are shown in Table 1.Table 1
Comparison of experimental results.
Algorithm
Accuracy(%)
Recall(%)
F1value (%)
Traditional recommendationalgorithm
12.74
14.21
13.38
Algorithm in this paper
22.41
20.86
21.51As can be seen from the table, the accuracy, recall and F1 value of the proposed algorithm are superior to those of the traditional recommendation algorithm, which are 22.41%, 20.86% and 21.51% respectively. The algorithm proposed in this paper uses Doc2vec DL model and completion strategy to complete the sparse matrix, thus solving the problems of low calculation accuracy and great mining potential of similarity matrix among users in sparse interactive matrix. Therefore, the algorithm in this paper is superior to the traditional algorithm in the experimental evaluation results.This paper introduces two initialization methods of the word embedding layer, random initialization and initialization using the pretrained word vector model. This paper makes a series of initialization of the CNN model using these three methods. Figures8 and 9 show the accuracy loss curves of the CNN model under three initialization methods of word embedding layer, including two training and verification processes.Figure 8
CNN model iteration times and accuracy loss curve.Figure 9
Loss curve of iteration times and accuracy of CNN under three word embedding methods.Experiments show that CNN model shows good advantages in dealing with patent texts. Most of the texts in the patent data set are long texts or Chinese texts, so context information, such as word and sentence order, is particularly important. However, CNN model needs to artificially determine the size (length) of filter convolution kernel to select different range of context information, which has high instability. In order to further verify that the patent feature vector extracted by CNN model has the ability to express the differences of patent text content, this paper adopts the method of comparative experiment to cluster and verify CNN models of two mapping strategies, and counts two types of models in two types of patent samples. The number of results conforming to the formula in the data set represents the proportion of the sample data set, and the results are shown in Table2.Table 2
Experimental results of two text similarity measurement methods.
Model
Cosine similarity
Euclidean distance
CNN
0.988
0.916
BPNN
0.951
0.928The experimental results in Table2 show that the feature vectors extracted by CNN model have a high accuracy in the text-similarity comparison experiment, and the error is within 5%–10% of the given result, which is much higher than other text feature representation methods. The choice of pre-training word vector model must consider the difference between corpus and actual training set. It is still an ideal state for training general word vector model, but it can be considered that it is used to train word vector model for specific applications through transfer learning in the patent field. A great improvement in the accuracy of feature extraction of this patent by using neural network model is to make use of the superior structure of other models to make up for the deficiency of the model itself.
## 4.1. Experimental Setup
The experiment of this algorithm is carried out in a local computer, and the details of the experimental environment are as follows:Processor: Intel(R)Core(TM)i7-7700CPUMemory: 8.00 GBOperating system: microsoftwindows10DL development framework: Deeplearning4j1.0.0-alphaThe experimental data used in this chapter includes two pieces of data. One piece of data comes from the retrieval system of the intellectual property (patent information) public service platform. The patent literature data was downloaded from the patent retrieval system as a patent corpus, and finally, 18,124 experimental patent data documents were obtained.Another part of the data comes from the user registration data collected in this study. As long as the user’s score is collected on the patent, it means that the user likes the patent. The user registration data includes user id, patent id, and score fields, and finally, there are 8096 user registration data of 133 users.
## 4.2. Experimental Result Analysis
We use 50% cross-validation [10] to randomly divide the user registration data of each user into 6 parts, 5 parts from the training set and 1 part from the test set. An average of 6 results is used, such as the final accuracy, recall, and F1 value. Figure 5 shows the influence of paragraph vector dimension on recommendation results.Figure 5
The influence of paragraph vector dimension on recommendation results.It can be seen that with the increase of paragraph vector dimension, the accuracy rate, recall rate, and F1 value first increase and then decrease. When the vector dimension of a word is less than 240, the semantic information of a paragraph is incomplete; It also brings some noise, which leads to errors in feature rendering. Therefore, the final depth semantic model paragraph vector dimension of Doc2vec is 240.The user’s Knum neighborhood represents the choice of the nearest Knum neighborhood of the target user, which affects the recommendation effect. Knum can be 1, 3, 5, 7, 9, 11, and the dimension of the paragraph vector is 240. Different users’ neighborhoodK has different accuracy, recall rate, and F1 value. The results are shown in Figure 6.Figure 6
The influence of neighborhood number on recommendation results.As can be seen from Figure6, with the increasing number of neighborhoods, the precision, recall rate and F1 value show a trend of first increasing and then decreasing. When Knum<7, the neighbor sets with similar hobbies are not fully excavated; When Knum=7, the recommendation effect is the best; When Knum>7 is used, neighbors with similar hobbies are fully mined, but some neighbors with low similarity are also mined, which leads to errors in recommendation. So the final number of neighborhoods is chosen as 7.This algorithm contains an adjustment parameter, thresholdσ, which represents the threshold of similarity between scored patents and unrated patents, and affects the recommendation effect. The paragraph vector dimension is 240, and the neighborhood k is 7, which have different accuracy, recall and F1 values. The results are shown in Figure 7.Figure 7
Influence onσ recommendation results.It can be seen that with the increase ofσ, the precision, recall rate, and F1 value first increase and then decrease. When σ<0.6, the scores of patents with low similarity are also estimated to complete the interaction matrix, and too much is completed, resulting in inaccurate adjacent user sets.Whenσ=0.6, the interaction matrix is completed properly, the recommendation effect is the best. When σ>0.6, it takes a patent with high similarity to estimate the score to complete the interaction matrix, resulting in the sparse matrix may still be very sparse, and the adjacent user set is inaccurate. Therefore, the final σ is selected as 0.6.Through the above experiments, the appropriate paragraph vector dimension 240,Knum=7, σ=0.6 is obtained, and the patent recommendation algorithm based on deep semantic similarity is the best. Therefore, the best algorithm in this paper is compared with the traditional recommendation algorithm, and the experimental results are shown in Table 1.Table 1
Comparison of experimental results.
Algorithm
Accuracy(%)
Recall(%)
F1value (%)
Traditional recommendationalgorithm
12.74
14.21
13.38
Algorithm in this paper
22.41
20.86
21.51As can be seen from the table, the accuracy, recall and F1 value of the proposed algorithm are superior to those of the traditional recommendation algorithm, which are 22.41%, 20.86% and 21.51% respectively. The algorithm proposed in this paper uses Doc2vec DL model and completion strategy to complete the sparse matrix, thus solving the problems of low calculation accuracy and great mining potential of similarity matrix among users in sparse interactive matrix. Therefore, the algorithm in this paper is superior to the traditional algorithm in the experimental evaluation results.This paper introduces two initialization methods of the word embedding layer, random initialization and initialization using the pretrained word vector model. This paper makes a series of initialization of the CNN model using these three methods. Figures8 and 9 show the accuracy loss curves of the CNN model under three initialization methods of word embedding layer, including two training and verification processes.Figure 8
CNN model iteration times and accuracy loss curve.Figure 9
Loss curve of iteration times and accuracy of CNN under three word embedding methods.Experiments show that CNN model shows good advantages in dealing with patent texts. Most of the texts in the patent data set are long texts or Chinese texts, so context information, such as word and sentence order, is particularly important. However, CNN model needs to artificially determine the size (length) of filter convolution kernel to select different range of context information, which has high instability. In order to further verify that the patent feature vector extracted by CNN model has the ability to express the differences of patent text content, this paper adopts the method of comparative experiment to cluster and verify CNN models of two mapping strategies, and counts two types of models in two types of patent samples. The number of results conforming to the formula in the data set represents the proportion of the sample data set, and the results are shown in Table2.Table 2
Experimental results of two text similarity measurement methods.
Model
Cosine similarity
Euclidean distance
CNN
0.988
0.916
BPNN
0.951
0.928The experimental results in Table2 show that the feature vectors extracted by CNN model have a high accuracy in the text-similarity comparison experiment, and the error is within 5%–10% of the given result, which is much higher than other text feature representation methods. The choice of pre-training word vector model must consider the difference between corpus and actual training set. It is still an ideal state for training general word vector model, but it can be considered that it is used to train word vector model for specific applications through transfer learning in the patent field. A great improvement in the accuracy of feature extraction of this patent by using neural network model is to make use of the superior structure of other models to make up for the deficiency of the model itself.
## 5. Conclusions
Innovation plays an important role in the development of Chinese enterprises. According to the process system of risk prevention and control, enterprises can find the source of risks in the process of intellectual property development from the risk identification subsystem, identify potential risk factors, and then enter the risk identification subsystem, and issue an early warning according to the risk monitoring signals. The patent similarity matrix is constructed by using Doc2vec DL model, and the experimental and analytical results show that the patent recommendation algorithm based on deep semantic similarity designed in this chapter is superior to the traditional algorithm. The accuracy, recall, and F1 value of the proposed algorithm are 22.41%, 20.86%, and 21.51%, respectively. In future research, we can establish different types of independent intellectual property risk early warning index systems for different types of companies through field research.
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*Source: 2899674-2022-07-19.xml* | 2022 |
# A Study on English Translation Skills and Modes of Multimodal Network from the Perspective of Teaching Situation
**Authors:** Xinxin Guan; Qin Xing; Yuwei Zhang
**Journal:** Advances in Multimedia
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2899947
---
## Abstract
With the in-depth research and continuous exploration of English translation skill patterns by multimodal networks, the scope of English translation skill analysis has been extended to other aspects besides words, and the traditional single-mode English translation skill analysis has gradually changed into a systematic English translation skill analysis that integrates language, images, music, and other symbols. From the perspective of situational teaching, this paper studies the skills and modes of English translation by multimodal network. The research shows that 30 books are randomly selected from preschool children’s books, primary school books, and junior high school books, among which the highest proportion of multimodal books is 82%, 57%, and 54%, respectively, and the proportion of multimodal network books among 120 literature books is 79%. Translators have a full understanding of the translated content in situational teaching, but in the actual process of translation, they will inevitably face the situation of language integration and word order adjustment. If translators have a certain understanding of the corresponding English translation skills, they can lay a good foundation for English translation skills and ensure the accuracy of translation.
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## Body
## 1. Introduction
Multimodal networking refers to the media and channels for people to communicate, including not only language, but also technology, images, music, and other forms. Traditional translation models and translation concepts emphasize the translation of multimodal networked languages themselves. Therefore, there are certain limitations in the process of actual discourse analysis, ignoring the complementary and supporting roles of other forms of expression in publicity translation [1]. With the in-depth research and continuous exploration of multimodal networking on the mode of English translation skills, scholars have gradually expanded the scope of English translation skills to other aspects other than words. The traditional single-mode analysis form of English translation skills has gradually changed into a systematic discourse analysis that integrates language, images, music, and other symbols. It is undeniable that the multimodal network-based English translation skill model plays an important role in texts. Research on understanding discourse meaning can be traced back to ancient times, but the word “discourse semantics” did not appear until the 1980s. The study of discourse semantics can be divided into four schools. First, the continental European school usually follows its psychological mechanism of analyzing discourse semantics. Although people have studied multimodal networked English translation skills from different perspectives, few have realized bottom-up semantic formalization to represent the development of discourse or in-depth discourse meaning [2]. Since the meaning expressed by a single text mode is incomplete, it needs to be supplemented or strengthened by other modes. In addition to the translation of the text introduction, some information that cannot be expressed in the text should also be displayed in a multimodal network form. In the process of multimodal networked English translation skills, text, sound, image, color, video, facial expression, body movement, and other multimodal forms are the resources of text meaning generation, which can be used to restore and reproduce the multimodal network information in English translation skills in the translated text. Therefore, the macrolevel of discourse structure and detailed semantic analysis need in-depth study at the microlevel, and it is necessary to build a formal representation of discourse semantics.From the perspective of situational teaching, this paper studies multimodal network-based English translation skills and modes. The purpose of this paper is to provide teaching inspiration for teachers and school administrators through the multimodal application of College English comprehensive classroom teaching in competitions and discourse in real contexts [3]. My main interest is to find out the dominant mode of each teaching stage under situational teaching. It is hoped that this is useful and can draw teaching meaning from the research to help optimize the design of multimode classroom teaching. The translator tries to put forward some feasible translation strategies. The translation methods of Qin opera are based on her translation practice and multimodal theoretical perspective, hoping to provide other translators and researchers with a role in the future translation study of Chinese traditional culture. It explains some important concepts in the following fields: audio-visual translation and expounds multimodal theory combined with vivid examples in the process of translation. Therefore, the report is innovative and shows the interdisciplinary nature of translation. Analysis of the multimode application of the English integrated classroom under situational teaching, specifically the choice of modality and symbol resources, as well as the advantages and disadvantages of modality selection. At each teaching stage, the possible reasons for choosing a modality will be studied and reviewed, and teaching implications will be provided for the following choices: the ways of teachers and school administrators. The translation process is mainly based on the translators themselves choosing some translation tools to help translators, such as Baidu translation, Google translation, and the ICAT application [4]. Baidu translation and Google translation are the two best free language translation websites that can be used in the translation process. The translation under situational teaching needs to check the translated version repeatedly, which is the responsibility of the translator. First, in the process of self-proofreading, fidelity should be realized, which means that the translation should be faithful to the information and meaning of the source text, and the target text must be complete and accurate. Second, the target text should be clear and coherent. It means that any grammatical errors, improper use of words, logical errors, and punctuation errors are allowed in the target text, which is important because it directly affects the quality of the target text [5].Although language is an important means and tool for human communication, it is not the only means. Especially for the publicity translation of folk culture, it is difficult to accurately convey the rich folk culture of China by single-modal discourse analysis. According to the semantic feature formula obtained from component analysis after determining the internal relationship between semantic concepts in situational teaching, this study will express semantic concepts through nodes, and the semantic relationships between concepts will be displayed through links [6]. If necessary, nodes and links can be added or combined. Then, when all concepts and their semantic relationships are expressed as utterances, all these will be put into a semantic network. In the translation, different cultural factors should be considered from the following perspectives: multimodal theory. The multimodal network-based teaching method has widened students’ learning range and access to knowledge and promoted dynamic information exchange between people, which is a good signal for cultivating students’ English translation skills to learn independently [7, 8]. In the process of multimodal networking, English translation skills not only involve converting the original text into the target text and converting the original image, sound, or video into the target text but also converting the original text into multimodal forms and carrying out multimodal reorganization in the target text according to the cognitive context of the target language. Some cultural images, including words, music, and frames, should be accurately identified. When these words are translated into English, they must be very compatible with the cultural elements in the visual and auditory modes. Translators have a full understanding of what is translated in situational teaching, but in the actual process of translation, they will inevitably face language integration, word order adjustment, and other situations. If translators have a certain understanding of the corresponding folk culture, they can lay a good foundation for the translation of foreign publicity and ensure the accuracy of translation.The innovation points proposed in this paper are as follows:(1)
This paper analyzes the relationship between multimodal networking and the main body of the English translation skills repository. In the teaching link of “field practice,” teachers can use modern teaching tools such as Shivo whiteboards to simulate the real language environment, design classroom activities for teacher-student and student interaction, and improve the effectiveness of the practice link. The demand for English translation resources and professional materials is increasing due to multimodal networking.(2)
The process of situational classroom teaching is studied. Situational teaching and multimodal networked English translation skills adopt group-based on-the-spot teaching. According to the training characteristics and teaching requirements of vocational and technical personnel, the complex design teaching process is decomposed into many specific and single skills that are easy to understand, and training goals are proposed for each skill to improve students’ professional skills.The overall structure of this paper consists of five parts.Chapter one describes the background and significance of multimodal network English translation skills. The second chapter mainly introduces the related research on multimodal networked English translation skills and the research content of multimodal networked English translation skills proposed in this paper. Chapter three describes the English translation strategies of multimodal networks and the application of multimodal network translation skills from the perspective of situational teaching. In chapter four, the experiment was studied, and the contents and results of the experiment were summarized. The fifth chapter is a summary of the full text.
## 2. Related Work
Different modes have their own characteristics and advantages. The comprehensive use of various modes can give play to the complementarity and synergy of different modes and can effectively promote the realization of English translation skills and mode objectives. It can be said that multimodality is a typical feature of modern education and an inevitable requirement to improve the efficiency of English translation skills and models.Hou showed that multimodal networked language analysis theory is applied to multidimensional interactive English teaching. Through the design of multimodal teaching materials and the selection of teaching modes, students’ audio-visual nerves and learning motivation are activated; their enthusiasm for participating in teaching is mobilized; their English translation skills, language practice ability, innovation consciousness, and independent learning ability are cultivated, and the effectiveness of teaching and learning is achieved [9]. Qin et al. proposed that multimodal networking is a way for human beings to communicate with the outside world. In addition to communicating through language, human beings can also choose to interact through their sensory organs. When human beings communicate and interact, choosing a single sense to communicate is called single-modal interaction, and choosing two or more senses to express together is called multimodal interaction [10]. Niu et al. proposed that English teaching should be guided by social needs, focus on cultivating students’ language practice ability, and embody the teaching principle of “application-oriented, multidimensional interaction and multimodal coordination” in teaching. Due to the diversity of information exchange methods and the multimodal network of meaning expression methods, it is imperative to change from a single English translation skill to a multimodal teaching mode [11]. Zhang et al. proposed that modern teaching equipment provides convenient conditions for teaching. Teachers have multiple modes to choose from and can present teaching content in multiple modes at the same time. For each different teaching stage, the corresponding mode or mode combination should be selected. Due to the simultaneous appearance of multimodality and networking in English translation skills, teachers need to integrate teaching, distinguish primary and secondary modes, and make teaching integrated [12]. Wang et al. proposed that multimodal networking is the sum of all dynamic and static resources, including text. Dynamic resources include audio, video, body language, and other resources, while static resources include images, charts, and other resources. From this perspective, multimodality is to achieve the purpose of transferring the meaning of English translation skills through two or more coding symbols [13]. Combining the cognitive evaluation theory in cognitive psychology, Jiang tried to construct a multidisciplinary and interdisciplinary theoretical framework based on the multimodality of attitude meaning, further improving the theoretical basis of emotional meaning classification in the construction of English translation skills so as to enhance the application value of multimodality networking in discipline construction [14]. Dicerto et al. believed that multimodal networking means that people react to the outside world through sensory stimuli, and interaction using a single sensory stimulus is monomodal interaction. From this perspective, multimodal web-based learning means that students interact with the knowledge they have learned through multisensory stimulation so as to better understand the knowledge of English translation skills, consolidate knowledge, and achieve knowledge output [15]. Parida et al. believed that the purpose of applying multimodal network-based teaching is to integrate resources in the teaching of English translation skills with the help of other perceptual symbol codes. Based on the network platform, the meaning exchange is realized by combining various kinds of reference symbol code systems, such as pictures, videos, and characters, so as to have a more vivid and accurate interpretation of the designed teaching content code [16]. Camciottoli and Fortanet-Gómez confirmed that in the classroom, the common use of multiple resource symbols will have an impact on teachers’ teaching attitudes and methods and will also have a certain impact on students’ participation. At the same time, he also pointed out that multimodal network resources in English translation skills must be used properly, otherwise it will backfire [17]. Wang et al. pointed out that in order to improve teaching efficiency in the teaching of legal English translation skills, different modes such as pictures, recordings, videos, film clips, real objects, and court props should be comprehensively used to organize teaching; various communication modes should be fully used; various modern educational technology means should be flexibly used; and the synergy and reinforcement between different modes should be fully brought into play, so as to organize teaching in a multimodal network as real as possible, so as to improve the teaching effect and promote students’ internalization of what they have learned [18].From the perspective of situational teaching, this paper studies multimodal network-based English translation skills and models. Relying on the law, it uses English to teach legal knowledge and cultivate students’ skills in listening, speaking, reading, writing, and translating legal English. The main teaching content of legal English is the Anglo-American legal system, including the Anglo-American legal culture, legal system and various main departments. In the past few decades, research on situational teaching translation has gained momentum, and audio-visual translation has become a new field. Reading some parallel texts in situational teaching helps to ensure language quality. On the one hand, they may help to confirm the uncertainty in the translation process. On the other hand, on the other hand, they provide guidance on text style and appropriate terminology, establishing such a volunteer background, the feats of the flying tigers, and the significance of their contributions. Multimodal networking mainly consists of the equivalent theory evaluation model rooted in generative grammar, the mathematical evaluation model based on fuzzy mathematics and quantitative analysis, the best approximation model, the functional linguistics model, the pragmatic marker equivalent evaluation model, the relevance theory evaluation model, the “appropriateness” standard evaluation model, the intertwined translation evaluation model, the optimality analysis model, and the analytic hierarchy process situational teaching. In the context of situational teaching, multimodal translation strategies should be reasonably applied. Multimodal online translation is of great help to improve publicity translation. However, in the actual process of multimodal online translation of situational teaching, pictures, sounds, animation, and other auxiliary translations should be reasonably applied to help foreign friends strengthen their understanding and avoid the excessive use of other auxiliary forms. Text translation, pictures, music, and other forms should be reasonably matched.
## 3. Research Method
### 3.1. English Translation Strategies Based on Multimodal Network
We should pay attention to the following content in the process of English translation skills and modes of multimodal network. To strengthen the consideration of cultural differences, the role of publicity translation itself is to realize the export of Chinese culture. Therefore, in the actual translation process, efforts should be made to cross the cultural gap and discover the differences and characteristics between Chinese and foreign cultures instead of mechanical translation word for word. While ensuring the accuracy of meaning transmission, English translation skills and modes should be fully reflected. The cultivation of multimodal network literacy requires very specific requirements. On the basis of the original four skills of listening, speaking, reading, and writing, the skill of “watching” is added, pointing out that “watching usually refers to the skills of understanding meaning by using figures, tables, animations, symbols, and videos in multimodal discourse” [19]. Wang et al., a Chinese translation scholar, put forward that “translatology is a special field of communication”. Language is the traditional carrier of folk culture, but with the development of multimedia technology, unnatural language symbols such as pictures, sounds, images, animations, etc., have also become an integral part of cultural meaning and image construction, and the spread of the new media environment has promoted the integration of text, sounds, videos, and images [20]. Due to the different cultural backgrounds between China and foreign countries, there are also great differences in thinking patterns and habits. Therefore, in the actual process of publicity translation, many words in foreign languages are used to express specific meanings or, because of different thinking patterns, simple literal translation can easily lead to comprehension errors. Therefore, translators need to be familiar with Chinese and foreign language customs to ensure the accuracy of translation results. In the teaching process of “on-the-spot practice,” teachers can use modern teaching tools such as Schiavo whiteboards to simulate the real language environment, design classroom activities for interaction between teachers and students, and improve the effectiveness of the practice process. Multimodal networking is more urgent for English translation resources and professional materials. Teachers, students, enterprises, and the English translation resource base are the four main bodies of teaching activities, and their interaction is shown in Figure 1.Figure 1
Relationship between multimodal networking and the main body of English translation skills resource base.Through multimodal integration and discourse analysis, such problems can be effectively improved. With the help of language, words, images, sounds, videos, and other forms, it is helpful to further promote the content of English translation skills and help the public strengthen their understanding of English translation skills. The forward multimodal network transmission of information refers to the process of gradual transmission through transformation after input data.(1)L=fnetlXW.The error of English translation skills is usually calculated in the form of mean square error, which can be expressed as(2)E=12∑i=1nti−oi.The first step of the gradient descent method is to change the value according to the weight. According to the rules(3)ΔWijL=αδiL,where α is the learning rate, δiL can be obtained by taking the derivative of mean square deviation, and its calculation formula is(4)δiL=fnetlnetl.List the weight change.(5)ΔWijX=αδjX.The calculation formula is(6)δjX=∑p=1nWjpL.Teachers should make use of classroom presuppositions to give students clear guidance so that they can understand the structure and stylistic features of different texts, improve their perception of nonverbal modes, and cultivate their reading and discrimination abilities of nonverbal modes with the help of nonverbal modes in texts. Therefore, in order to ensure the accuracy of the English translation skills and the enrichment of the content, in the actual process of multimodal networked English translation skills, we should focus on the accuracy and enrichment of translation, actively use multimodal networked symbols to achieve the expression of meaning, and reasonably use images, music, gestures, animation, and other language symbols for translation [21]. In the actual process of English translation skills, language is still the main way to convey information, while nonverbal forms refer to body movements, facial expressions, pictures, background music, animation, and other types of information dissemination methods or tools.The teaching contents and learning methods of English translation strategies are embedded in the teaching process, teaching form, and teaching environment, and the online learning method under the background of “Internet + resource bank” of environmental art specialty is used to drive the organic combination and multimodal development of offline classroom teaching and enterprise practice teaching. In the context of multimodality, combined with the cognitive evaluation theory in cognitive psychology, this paper attempts to construct a theoretical framework of English translation skills based on multimodal networking of attitude meaning, further improving the theoretical basis of English translation skills on the classification of emotional meaning and enhancing the application value of multimodal networking in the construction of English translation skills [22]. Through the multimodal translation strategy, through the support of language, picture color, audio, and video, it can further enrich the meaning of the text, help the audience to build psychological schema, ensure the effectiveness of translation, and improve the smoothness of reading translated materials.
### 3.2. Application of English Translation Skills Based on Multimodal Network from the Perspective of Situational Teaching
In situational teaching, consciously use multimodal networks to guide students’ English translation skills. Pay attention to and attract attention, which will have a positive effect on cultivating their thinking and study habits. In situational teaching, multimodal network discourse integration is applied, and in the process of English translation skills, corresponding pictures, music, and video materials are scientifically integrated so as to fully convey the true content of the discourse. For readers, the translation is like gobbledygook, which fails to achieve the purpose of publicity and even keeps people away. Only by transforming some of the contents into the accepted multimodal network form can more people understand them, thus achieving the goal of multimodal network English translation skills in situational teaching. The key aspects of the possibility of multimodal network communication include the choice potential of ideology as the main form and style of culture. The translation should be carried out on the premise of considering the cultural level, which is in line with the cultural significance of the overall linguistic model and the nonlinguistic model construction. In order to ensure the effectiveness of English translation skills and the accuracy of information transmission, efforts should be made to cross this foreign cultural difference and strengthen the integration of multimodal network English translation skills in situational teaching so as to ensure the scientificity, rationality, and accuracy of the translation. After correctly interpreting the text, students screen the required modes, make the best combinations, create multimodal networked works, and demonstrate their English translation skills through PPT, lectures, and other forms. The situational classroom teaching process from the perspective of multimodal networking is shown in Figure2.Figure 2
Flow chart of situational classroom teaching.Translation researchers and practitioners with a high level of competence should devote themselves to the research and practice of publicity translation. Relevant government departments, nongovernmental organizations, cultural scholars, translation researchers, and practitioners should actively cooperate. Situational teaching and multimodal networked English translation skills adopt group-based on-the-spot teaching. According to the training characteristics and teaching requirements of vocational and technical personnel, the complex design teaching process is decomposed into many specific and single skills that are easy to understand, and training goals are proposed for each skill to improve students’ professional skills. Through the use of color, the importance of this paragraph of text is emphasized, which is different from other words. Therefore, nonverbal symbols here have the conceptual function of expressing importance. Together with the text and surrounding text, they form a complete text, thus having the interpersonal function of letting readers participate better. It strengthens the conceptual meaning, helps English readers who may not know much about Chinese culture to better understand the content of this chapter, realizes the conceptual function and interpersonal function, and forms a text for understanding the whole chapter together with the text. Then, from the perspective of situational teaching, teachers can guide students to pay attention to the main clues of story development. The frequency of words appearing in the document. The higher the frequency, the more important the word is to the document than other words. The simplest expression is(7)TF1=Ni,j,where Ni,j is the value of the unit when the matrix is simply counted, that is, the number of times that the word with serial number i appears in the translation with serial number i.There are some improved formulas for word frequency, such as(8)TF2=Ni,jN∗,j,TF3=logNi,j,N∗,j is the total number of words in the translation with serial number j. This practice not only considers the frequency of words but also the influence of column elements in the matrix.If a word only appears in a few translations in the translation set, it is considered that the word is more important to these few translations and should correspond to the weight of the corresponding column in the reinforcement matrix. The calculation formula is(9)IDF=logDDi,where D is the number of translations. Di is the number of documents containing words with serial number i.After roughly browsing the text, the students found that the story unfolded in chronological order, so they continued to read deeply according to the time clues and told the story through illustrations according to their own understanding. Students can not only extract beautiful words and sentences but also write their feelings after reading. They can also record videos to introduce their feelings after reading and reflecting. For novels, you can also make mind maps to straighten out the relationships between characters, which will help to creatively improve their reading and writing abilities. When translating multimodal works, we should give full consideration to the graphic relationships in the original work. Besides the translation of the core language level, we should also give full consideration to the influence of other modal factors such as images, colors, sounds, and even technology on the overall discourse. Among them, discourse meaning mainly refers to the scope and tone of language and the meaning of words formed under the language form, including conceptual meaning, interpersonal meaning, and the meaning of writing. The formal level mainly refers to the form and relationship of discourse. The form refers to language, image perception, sound perception, and feelings. The relationship includes complementary and noncomplementary elements. Reasonable application of multimodal translation strategies and full use of language and human sensory systems can achieve effective complementarity between different modes and achieve the purpose of translation. Therefore, in the process of teaching English translation skills in situational teaching, it is necessary to strengthen the research and discussion on multimodal networking, and at the same time, correctly understand the language habits and thinking modes of English translation skills, rationally apply diversified translation strategies and methods, and adopt multimodal methods to ensure the translation quality and dissemination effect of multimodal networking English translation skills.
## 3.1. English Translation Strategies Based on Multimodal Network
We should pay attention to the following content in the process of English translation skills and modes of multimodal network. To strengthen the consideration of cultural differences, the role of publicity translation itself is to realize the export of Chinese culture. Therefore, in the actual translation process, efforts should be made to cross the cultural gap and discover the differences and characteristics between Chinese and foreign cultures instead of mechanical translation word for word. While ensuring the accuracy of meaning transmission, English translation skills and modes should be fully reflected. The cultivation of multimodal network literacy requires very specific requirements. On the basis of the original four skills of listening, speaking, reading, and writing, the skill of “watching” is added, pointing out that “watching usually refers to the skills of understanding meaning by using figures, tables, animations, symbols, and videos in multimodal discourse” [19]. Wang et al., a Chinese translation scholar, put forward that “translatology is a special field of communication”. Language is the traditional carrier of folk culture, but with the development of multimedia technology, unnatural language symbols such as pictures, sounds, images, animations, etc., have also become an integral part of cultural meaning and image construction, and the spread of the new media environment has promoted the integration of text, sounds, videos, and images [20]. Due to the different cultural backgrounds between China and foreign countries, there are also great differences in thinking patterns and habits. Therefore, in the actual process of publicity translation, many words in foreign languages are used to express specific meanings or, because of different thinking patterns, simple literal translation can easily lead to comprehension errors. Therefore, translators need to be familiar with Chinese and foreign language customs to ensure the accuracy of translation results. In the teaching process of “on-the-spot practice,” teachers can use modern teaching tools such as Schiavo whiteboards to simulate the real language environment, design classroom activities for interaction between teachers and students, and improve the effectiveness of the practice process. Multimodal networking is more urgent for English translation resources and professional materials. Teachers, students, enterprises, and the English translation resource base are the four main bodies of teaching activities, and their interaction is shown in Figure 1.Figure 1
Relationship between multimodal networking and the main body of English translation skills resource base.Through multimodal integration and discourse analysis, such problems can be effectively improved. With the help of language, words, images, sounds, videos, and other forms, it is helpful to further promote the content of English translation skills and help the public strengthen their understanding of English translation skills. The forward multimodal network transmission of information refers to the process of gradual transmission through transformation after input data.(1)L=fnetlXW.The error of English translation skills is usually calculated in the form of mean square error, which can be expressed as(2)E=12∑i=1nti−oi.The first step of the gradient descent method is to change the value according to the weight. According to the rules(3)ΔWijL=αδiL,where α is the learning rate, δiL can be obtained by taking the derivative of mean square deviation, and its calculation formula is(4)δiL=fnetlnetl.List the weight change.(5)ΔWijX=αδjX.The calculation formula is(6)δjX=∑p=1nWjpL.Teachers should make use of classroom presuppositions to give students clear guidance so that they can understand the structure and stylistic features of different texts, improve their perception of nonverbal modes, and cultivate their reading and discrimination abilities of nonverbal modes with the help of nonverbal modes in texts. Therefore, in order to ensure the accuracy of the English translation skills and the enrichment of the content, in the actual process of multimodal networked English translation skills, we should focus on the accuracy and enrichment of translation, actively use multimodal networked symbols to achieve the expression of meaning, and reasonably use images, music, gestures, animation, and other language symbols for translation [21]. In the actual process of English translation skills, language is still the main way to convey information, while nonverbal forms refer to body movements, facial expressions, pictures, background music, animation, and other types of information dissemination methods or tools.The teaching contents and learning methods of English translation strategies are embedded in the teaching process, teaching form, and teaching environment, and the online learning method under the background of “Internet + resource bank” of environmental art specialty is used to drive the organic combination and multimodal development of offline classroom teaching and enterprise practice teaching. In the context of multimodality, combined with the cognitive evaluation theory in cognitive psychology, this paper attempts to construct a theoretical framework of English translation skills based on multimodal networking of attitude meaning, further improving the theoretical basis of English translation skills on the classification of emotional meaning and enhancing the application value of multimodal networking in the construction of English translation skills [22]. Through the multimodal translation strategy, through the support of language, picture color, audio, and video, it can further enrich the meaning of the text, help the audience to build psychological schema, ensure the effectiveness of translation, and improve the smoothness of reading translated materials.
## 3.2. Application of English Translation Skills Based on Multimodal Network from the Perspective of Situational Teaching
In situational teaching, consciously use multimodal networks to guide students’ English translation skills. Pay attention to and attract attention, which will have a positive effect on cultivating their thinking and study habits. In situational teaching, multimodal network discourse integration is applied, and in the process of English translation skills, corresponding pictures, music, and video materials are scientifically integrated so as to fully convey the true content of the discourse. For readers, the translation is like gobbledygook, which fails to achieve the purpose of publicity and even keeps people away. Only by transforming some of the contents into the accepted multimodal network form can more people understand them, thus achieving the goal of multimodal network English translation skills in situational teaching. The key aspects of the possibility of multimodal network communication include the choice potential of ideology as the main form and style of culture. The translation should be carried out on the premise of considering the cultural level, which is in line with the cultural significance of the overall linguistic model and the nonlinguistic model construction. In order to ensure the effectiveness of English translation skills and the accuracy of information transmission, efforts should be made to cross this foreign cultural difference and strengthen the integration of multimodal network English translation skills in situational teaching so as to ensure the scientificity, rationality, and accuracy of the translation. After correctly interpreting the text, students screen the required modes, make the best combinations, create multimodal networked works, and demonstrate their English translation skills through PPT, lectures, and other forms. The situational classroom teaching process from the perspective of multimodal networking is shown in Figure2.Figure 2
Flow chart of situational classroom teaching.Translation researchers and practitioners with a high level of competence should devote themselves to the research and practice of publicity translation. Relevant government departments, nongovernmental organizations, cultural scholars, translation researchers, and practitioners should actively cooperate. Situational teaching and multimodal networked English translation skills adopt group-based on-the-spot teaching. According to the training characteristics and teaching requirements of vocational and technical personnel, the complex design teaching process is decomposed into many specific and single skills that are easy to understand, and training goals are proposed for each skill to improve students’ professional skills. Through the use of color, the importance of this paragraph of text is emphasized, which is different from other words. Therefore, nonverbal symbols here have the conceptual function of expressing importance. Together with the text and surrounding text, they form a complete text, thus having the interpersonal function of letting readers participate better. It strengthens the conceptual meaning, helps English readers who may not know much about Chinese culture to better understand the content of this chapter, realizes the conceptual function and interpersonal function, and forms a text for understanding the whole chapter together with the text. Then, from the perspective of situational teaching, teachers can guide students to pay attention to the main clues of story development. The frequency of words appearing in the document. The higher the frequency, the more important the word is to the document than other words. The simplest expression is(7)TF1=Ni,j,where Ni,j is the value of the unit when the matrix is simply counted, that is, the number of times that the word with serial number i appears in the translation with serial number i.There are some improved formulas for word frequency, such as(8)TF2=Ni,jN∗,j,TF3=logNi,j,N∗,j is the total number of words in the translation with serial number j. This practice not only considers the frequency of words but also the influence of column elements in the matrix.If a word only appears in a few translations in the translation set, it is considered that the word is more important to these few translations and should correspond to the weight of the corresponding column in the reinforcement matrix. The calculation formula is(9)IDF=logDDi,where D is the number of translations. Di is the number of documents containing words with serial number i.After roughly browsing the text, the students found that the story unfolded in chronological order, so they continued to read deeply according to the time clues and told the story through illustrations according to their own understanding. Students can not only extract beautiful words and sentences but also write their feelings after reading. They can also record videos to introduce their feelings after reading and reflecting. For novels, you can also make mind maps to straighten out the relationships between characters, which will help to creatively improve their reading and writing abilities. When translating multimodal works, we should give full consideration to the graphic relationships in the original work. Besides the translation of the core language level, we should also give full consideration to the influence of other modal factors such as images, colors, sounds, and even technology on the overall discourse. Among them, discourse meaning mainly refers to the scope and tone of language and the meaning of words formed under the language form, including conceptual meaning, interpersonal meaning, and the meaning of writing. The formal level mainly refers to the form and relationship of discourse. The form refers to language, image perception, sound perception, and feelings. The relationship includes complementary and noncomplementary elements. Reasonable application of multimodal translation strategies and full use of language and human sensory systems can achieve effective complementarity between different modes and achieve the purpose of translation. Therefore, in the process of teaching English translation skills in situational teaching, it is necessary to strengthen the research and discussion on multimodal networking, and at the same time, correctly understand the language habits and thinking modes of English translation skills, rationally apply diversified translation strategies and methods, and adopt multimodal methods to ensure the translation quality and dissemination effect of multimodal networking English translation skills.
## 4. Results Analysis and Discussion
In this experiment, a large Xinhua bookstore randomly selected 30 books from each of the four categories of literature, philosophy and religion, economy, natural science, and comprehensive books in the basic classification of books. Among the 120 books in total, the distribution of multimodal online reading is shown in Table1.Table 1
Distribution of multimodal networked reading materials.
LiteraturePhilosophy and religionEconomicsNatural scienceTotalNon multimodal networked reading10812636Multimodal networked reading2022182484Total30303030120Proportion of multimodal networked reading materials67%73%60%80%70%In some special books, such as art books and literary works, multimodal network discourse occupies an absolute proportion. Among the 30 selected art books, all are multimodal discourses based on pictures and supplemented by words. The multimodal distribution of 120 randomly selected books is shown in Figure3.Figure 3
Proportion diagram of multimodal networked reading materials.It can be found from the data in Figure3 that 30 books were randomly selected from preschool children’s books, primary school books, and junior high school books, of which the highest proportion of multimodal books was 82%, 57%, and 54%, respectively. Among the 120 literary books, the proportion of multimodal network books was 79%.It can be seen from Figure4 that multimodal online reading accounts for a certain proportion of existing books and a large proportion of literature, philosophy, religion, and natural science. At the same time, there is also a large proportion of multimodal online reading in the translated works, so TQA, which only stays at the language level, is far from serving the current translation practice.Figure 4
Proportion diagram of modal reading materials in the English-Chinese translation.This paper focuses on how to reproduce the three metafunctions of the nonverbal mode in translation and realize the meaning of reproduction under the condition of complementary images and texts. The distribution of nonverbal symbols is shown in Table2.Table 2
Distribution table of nonverbal symbols in original text and translated text.
ChartFrameColorTotalText pagesNonverbal symbol scaleOriginal text1938611161170.98Translation152950921820.51The proportion of nonverbal symbols in the original text is 0.98. That is, there is basically one nonverbal symbol on every page. The proportion of nonverbal symbols in the translated text is 0.51. That is, basically, one nonverbal symbol appears every two pages. Considering the different length characteristics of the Chinese and English languages and the translator’s deletion of chapters in the original text, the proportion of nonverbal symbols in the original text and the translated text is basically the same, and the translated text is slightly less.Chinese and English can be translated into each other, but the corresponding translation results of Chinese words corresponding to English words may be too long. Therefore, in this experiment, 200 groups of secret information with a sentence length of about 20 Chinese characters, about 30 Chinese characters, and about 40 Chinese characters were selected, and the secret information was hidden, and the change of embedding rate was counted, and the collected results were sorted and analyzed and compared. Figures5–7 show the experimental results respectively.Figure 5
Schematic diagram of secret information embedding rate results with a length of 20 words.Figure 6
Schematic diagram of secret information embedding rate results with a length of 30 words.Figure 7
Schematic diagram of secret information embedding rate results with a length of 40 words.The embedding rate data in the above figure are summarized, and the median embedding rate is added for comparative analysis. As shown in Table3.Table 3
Comparison of embedding rates of sentences with different word lengths.
Statement lengthMinimum embedding rate (%)Maximum embedding rate (%)Average embedding rate (%)Median embedding rate (%)20 words15.244.922.821.530 words14.439.123.223.340 words17.632.222.821.9Average value15.738.722.922.2According to Figures5–7, with the increase in the length of Chinese secret information, the embedding rate waveform is gradually stable, which means it is closer to the average embedding rate curve. It can be concluded that the longer the length of Chinese secret information is, the more stable the embedding rate is. From the two columns of the lowest embedding rate and the highest embedding rate in Table 3, we know that with the increase in the length of Chinese secret information, the lowest embedding rate is gradually increasing, while the highest embedding rate is gradually decreasing, which tends to the average value. The weight of words that often appear in some documents makes rare words in a translation play a greater role in distinguishing them. In this way, if an excellent translation uses a high-level vocabulary with little frequency, the translations that also use this high-level vocabulary will have a higher similarity, and it is more likely to appear in the similar translation set of this excellent translation, further strengthening the connection between the translations of the same grade.
## 5. Conclusion
To sum up, the actual process of multimodal online integration of English translation mainly includes the integration of the original text and the translation. To ensure the effectiveness of multimodal translation, we should focus on the scientific integration of culture, content, and expression so as to ensure the effectiveness of multimodal online translation strategies. From the perspective of situational teaching, this paper studies the skills and modes of multimodal networked English translation. The research shows that 30 books are randomly selected from preschool children’s books, primary school books, and junior high school books, of which the highest proportion of multimodal books is 82%, 57%, and 54%, respectively. Among the 120 literary books, the proportion of multimodal networked books is 79%. The main purpose of analyzing multimodal networked English translation skills under situational teaching is to ensure that the original meaning of the translation results is fully, completely, truly, and accurately expressed, and that readers can intuitively understand their own meaning so that the translation results are easy to understand. When evaluating the translation quality of multimodal networked works, we should also carefully consider the translation of nonverbal symbols and the extent to which the functions of various states are reproduced in the translation. At the same time, when the original author and the publisher publish the original work, they should also pay attention to improving the quality of nonverbal symbols so that readers can read multimodally. In the context of situational teaching, multimodal networked English translation skills are growing at an unprecedented rate. Many experts and scholars at home and abroad have affirmed the importance of multimodal networked English translation skills. Therefore, we must fully consider the particularities of multimodal networking when measuring translation quality.
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*Source: 2899947-2022-10-11.xml* | 2899947-2022-10-11_2899947-2022-10-11.md | 50,803 | A Study on English Translation Skills and Modes of Multimodal Network from the Perspective of Teaching Situation | Xinxin Guan; Qin Xing; Yuwei Zhang | Advances in Multimedia
(2022) | Computer Science | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2899947 | 2899947-2022-10-11.xml | ---
## Abstract
With the in-depth research and continuous exploration of English translation skill patterns by multimodal networks, the scope of English translation skill analysis has been extended to other aspects besides words, and the traditional single-mode English translation skill analysis has gradually changed into a systematic English translation skill analysis that integrates language, images, music, and other symbols. From the perspective of situational teaching, this paper studies the skills and modes of English translation by multimodal network. The research shows that 30 books are randomly selected from preschool children’s books, primary school books, and junior high school books, among which the highest proportion of multimodal books is 82%, 57%, and 54%, respectively, and the proportion of multimodal network books among 120 literature books is 79%. Translators have a full understanding of the translated content in situational teaching, but in the actual process of translation, they will inevitably face the situation of language integration and word order adjustment. If translators have a certain understanding of the corresponding English translation skills, they can lay a good foundation for English translation skills and ensure the accuracy of translation.
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## Body
## 1. Introduction
Multimodal networking refers to the media and channels for people to communicate, including not only language, but also technology, images, music, and other forms. Traditional translation models and translation concepts emphasize the translation of multimodal networked languages themselves. Therefore, there are certain limitations in the process of actual discourse analysis, ignoring the complementary and supporting roles of other forms of expression in publicity translation [1]. With the in-depth research and continuous exploration of multimodal networking on the mode of English translation skills, scholars have gradually expanded the scope of English translation skills to other aspects other than words. The traditional single-mode analysis form of English translation skills has gradually changed into a systematic discourse analysis that integrates language, images, music, and other symbols. It is undeniable that the multimodal network-based English translation skill model plays an important role in texts. Research on understanding discourse meaning can be traced back to ancient times, but the word “discourse semantics” did not appear until the 1980s. The study of discourse semantics can be divided into four schools. First, the continental European school usually follows its psychological mechanism of analyzing discourse semantics. Although people have studied multimodal networked English translation skills from different perspectives, few have realized bottom-up semantic formalization to represent the development of discourse or in-depth discourse meaning [2]. Since the meaning expressed by a single text mode is incomplete, it needs to be supplemented or strengthened by other modes. In addition to the translation of the text introduction, some information that cannot be expressed in the text should also be displayed in a multimodal network form. In the process of multimodal networked English translation skills, text, sound, image, color, video, facial expression, body movement, and other multimodal forms are the resources of text meaning generation, which can be used to restore and reproduce the multimodal network information in English translation skills in the translated text. Therefore, the macrolevel of discourse structure and detailed semantic analysis need in-depth study at the microlevel, and it is necessary to build a formal representation of discourse semantics.From the perspective of situational teaching, this paper studies multimodal network-based English translation skills and modes. The purpose of this paper is to provide teaching inspiration for teachers and school administrators through the multimodal application of College English comprehensive classroom teaching in competitions and discourse in real contexts [3]. My main interest is to find out the dominant mode of each teaching stage under situational teaching. It is hoped that this is useful and can draw teaching meaning from the research to help optimize the design of multimode classroom teaching. The translator tries to put forward some feasible translation strategies. The translation methods of Qin opera are based on her translation practice and multimodal theoretical perspective, hoping to provide other translators and researchers with a role in the future translation study of Chinese traditional culture. It explains some important concepts in the following fields: audio-visual translation and expounds multimodal theory combined with vivid examples in the process of translation. Therefore, the report is innovative and shows the interdisciplinary nature of translation. Analysis of the multimode application of the English integrated classroom under situational teaching, specifically the choice of modality and symbol resources, as well as the advantages and disadvantages of modality selection. At each teaching stage, the possible reasons for choosing a modality will be studied and reviewed, and teaching implications will be provided for the following choices: the ways of teachers and school administrators. The translation process is mainly based on the translators themselves choosing some translation tools to help translators, such as Baidu translation, Google translation, and the ICAT application [4]. Baidu translation and Google translation are the two best free language translation websites that can be used in the translation process. The translation under situational teaching needs to check the translated version repeatedly, which is the responsibility of the translator. First, in the process of self-proofreading, fidelity should be realized, which means that the translation should be faithful to the information and meaning of the source text, and the target text must be complete and accurate. Second, the target text should be clear and coherent. It means that any grammatical errors, improper use of words, logical errors, and punctuation errors are allowed in the target text, which is important because it directly affects the quality of the target text [5].Although language is an important means and tool for human communication, it is not the only means. Especially for the publicity translation of folk culture, it is difficult to accurately convey the rich folk culture of China by single-modal discourse analysis. According to the semantic feature formula obtained from component analysis after determining the internal relationship between semantic concepts in situational teaching, this study will express semantic concepts through nodes, and the semantic relationships between concepts will be displayed through links [6]. If necessary, nodes and links can be added or combined. Then, when all concepts and their semantic relationships are expressed as utterances, all these will be put into a semantic network. In the translation, different cultural factors should be considered from the following perspectives: multimodal theory. The multimodal network-based teaching method has widened students’ learning range and access to knowledge and promoted dynamic information exchange between people, which is a good signal for cultivating students’ English translation skills to learn independently [7, 8]. In the process of multimodal networking, English translation skills not only involve converting the original text into the target text and converting the original image, sound, or video into the target text but also converting the original text into multimodal forms and carrying out multimodal reorganization in the target text according to the cognitive context of the target language. Some cultural images, including words, music, and frames, should be accurately identified. When these words are translated into English, they must be very compatible with the cultural elements in the visual and auditory modes. Translators have a full understanding of what is translated in situational teaching, but in the actual process of translation, they will inevitably face language integration, word order adjustment, and other situations. If translators have a certain understanding of the corresponding folk culture, they can lay a good foundation for the translation of foreign publicity and ensure the accuracy of translation.The innovation points proposed in this paper are as follows:(1)
This paper analyzes the relationship between multimodal networking and the main body of the English translation skills repository. In the teaching link of “field practice,” teachers can use modern teaching tools such as Shivo whiteboards to simulate the real language environment, design classroom activities for teacher-student and student interaction, and improve the effectiveness of the practice link. The demand for English translation resources and professional materials is increasing due to multimodal networking.(2)
The process of situational classroom teaching is studied. Situational teaching and multimodal networked English translation skills adopt group-based on-the-spot teaching. According to the training characteristics and teaching requirements of vocational and technical personnel, the complex design teaching process is decomposed into many specific and single skills that are easy to understand, and training goals are proposed for each skill to improve students’ professional skills.The overall structure of this paper consists of five parts.Chapter one describes the background and significance of multimodal network English translation skills. The second chapter mainly introduces the related research on multimodal networked English translation skills and the research content of multimodal networked English translation skills proposed in this paper. Chapter three describes the English translation strategies of multimodal networks and the application of multimodal network translation skills from the perspective of situational teaching. In chapter four, the experiment was studied, and the contents and results of the experiment were summarized. The fifth chapter is a summary of the full text.
## 2. Related Work
Different modes have their own characteristics and advantages. The comprehensive use of various modes can give play to the complementarity and synergy of different modes and can effectively promote the realization of English translation skills and mode objectives. It can be said that multimodality is a typical feature of modern education and an inevitable requirement to improve the efficiency of English translation skills and models.Hou showed that multimodal networked language analysis theory is applied to multidimensional interactive English teaching. Through the design of multimodal teaching materials and the selection of teaching modes, students’ audio-visual nerves and learning motivation are activated; their enthusiasm for participating in teaching is mobilized; their English translation skills, language practice ability, innovation consciousness, and independent learning ability are cultivated, and the effectiveness of teaching and learning is achieved [9]. Qin et al. proposed that multimodal networking is a way for human beings to communicate with the outside world. In addition to communicating through language, human beings can also choose to interact through their sensory organs. When human beings communicate and interact, choosing a single sense to communicate is called single-modal interaction, and choosing two or more senses to express together is called multimodal interaction [10]. Niu et al. proposed that English teaching should be guided by social needs, focus on cultivating students’ language practice ability, and embody the teaching principle of “application-oriented, multidimensional interaction and multimodal coordination” in teaching. Due to the diversity of information exchange methods and the multimodal network of meaning expression methods, it is imperative to change from a single English translation skill to a multimodal teaching mode [11]. Zhang et al. proposed that modern teaching equipment provides convenient conditions for teaching. Teachers have multiple modes to choose from and can present teaching content in multiple modes at the same time. For each different teaching stage, the corresponding mode or mode combination should be selected. Due to the simultaneous appearance of multimodality and networking in English translation skills, teachers need to integrate teaching, distinguish primary and secondary modes, and make teaching integrated [12]. Wang et al. proposed that multimodal networking is the sum of all dynamic and static resources, including text. Dynamic resources include audio, video, body language, and other resources, while static resources include images, charts, and other resources. From this perspective, multimodality is to achieve the purpose of transferring the meaning of English translation skills through two or more coding symbols [13]. Combining the cognitive evaluation theory in cognitive psychology, Jiang tried to construct a multidisciplinary and interdisciplinary theoretical framework based on the multimodality of attitude meaning, further improving the theoretical basis of emotional meaning classification in the construction of English translation skills so as to enhance the application value of multimodality networking in discipline construction [14]. Dicerto et al. believed that multimodal networking means that people react to the outside world through sensory stimuli, and interaction using a single sensory stimulus is monomodal interaction. From this perspective, multimodal web-based learning means that students interact with the knowledge they have learned through multisensory stimulation so as to better understand the knowledge of English translation skills, consolidate knowledge, and achieve knowledge output [15]. Parida et al. believed that the purpose of applying multimodal network-based teaching is to integrate resources in the teaching of English translation skills with the help of other perceptual symbol codes. Based on the network platform, the meaning exchange is realized by combining various kinds of reference symbol code systems, such as pictures, videos, and characters, so as to have a more vivid and accurate interpretation of the designed teaching content code [16]. Camciottoli and Fortanet-Gómez confirmed that in the classroom, the common use of multiple resource symbols will have an impact on teachers’ teaching attitudes and methods and will also have a certain impact on students’ participation. At the same time, he also pointed out that multimodal network resources in English translation skills must be used properly, otherwise it will backfire [17]. Wang et al. pointed out that in order to improve teaching efficiency in the teaching of legal English translation skills, different modes such as pictures, recordings, videos, film clips, real objects, and court props should be comprehensively used to organize teaching; various communication modes should be fully used; various modern educational technology means should be flexibly used; and the synergy and reinforcement between different modes should be fully brought into play, so as to organize teaching in a multimodal network as real as possible, so as to improve the teaching effect and promote students’ internalization of what they have learned [18].From the perspective of situational teaching, this paper studies multimodal network-based English translation skills and models. Relying on the law, it uses English to teach legal knowledge and cultivate students’ skills in listening, speaking, reading, writing, and translating legal English. The main teaching content of legal English is the Anglo-American legal system, including the Anglo-American legal culture, legal system and various main departments. In the past few decades, research on situational teaching translation has gained momentum, and audio-visual translation has become a new field. Reading some parallel texts in situational teaching helps to ensure language quality. On the one hand, they may help to confirm the uncertainty in the translation process. On the other hand, on the other hand, they provide guidance on text style and appropriate terminology, establishing such a volunteer background, the feats of the flying tigers, and the significance of their contributions. Multimodal networking mainly consists of the equivalent theory evaluation model rooted in generative grammar, the mathematical evaluation model based on fuzzy mathematics and quantitative analysis, the best approximation model, the functional linguistics model, the pragmatic marker equivalent evaluation model, the relevance theory evaluation model, the “appropriateness” standard evaluation model, the intertwined translation evaluation model, the optimality analysis model, and the analytic hierarchy process situational teaching. In the context of situational teaching, multimodal translation strategies should be reasonably applied. Multimodal online translation is of great help to improve publicity translation. However, in the actual process of multimodal online translation of situational teaching, pictures, sounds, animation, and other auxiliary translations should be reasonably applied to help foreign friends strengthen their understanding and avoid the excessive use of other auxiliary forms. Text translation, pictures, music, and other forms should be reasonably matched.
## 3. Research Method
### 3.1. English Translation Strategies Based on Multimodal Network
We should pay attention to the following content in the process of English translation skills and modes of multimodal network. To strengthen the consideration of cultural differences, the role of publicity translation itself is to realize the export of Chinese culture. Therefore, in the actual translation process, efforts should be made to cross the cultural gap and discover the differences and characteristics between Chinese and foreign cultures instead of mechanical translation word for word. While ensuring the accuracy of meaning transmission, English translation skills and modes should be fully reflected. The cultivation of multimodal network literacy requires very specific requirements. On the basis of the original four skills of listening, speaking, reading, and writing, the skill of “watching” is added, pointing out that “watching usually refers to the skills of understanding meaning by using figures, tables, animations, symbols, and videos in multimodal discourse” [19]. Wang et al., a Chinese translation scholar, put forward that “translatology is a special field of communication”. Language is the traditional carrier of folk culture, but with the development of multimedia technology, unnatural language symbols such as pictures, sounds, images, animations, etc., have also become an integral part of cultural meaning and image construction, and the spread of the new media environment has promoted the integration of text, sounds, videos, and images [20]. Due to the different cultural backgrounds between China and foreign countries, there are also great differences in thinking patterns and habits. Therefore, in the actual process of publicity translation, many words in foreign languages are used to express specific meanings or, because of different thinking patterns, simple literal translation can easily lead to comprehension errors. Therefore, translators need to be familiar with Chinese and foreign language customs to ensure the accuracy of translation results. In the teaching process of “on-the-spot practice,” teachers can use modern teaching tools such as Schiavo whiteboards to simulate the real language environment, design classroom activities for interaction between teachers and students, and improve the effectiveness of the practice process. Multimodal networking is more urgent for English translation resources and professional materials. Teachers, students, enterprises, and the English translation resource base are the four main bodies of teaching activities, and their interaction is shown in Figure 1.Figure 1
Relationship between multimodal networking and the main body of English translation skills resource base.Through multimodal integration and discourse analysis, such problems can be effectively improved. With the help of language, words, images, sounds, videos, and other forms, it is helpful to further promote the content of English translation skills and help the public strengthen their understanding of English translation skills. The forward multimodal network transmission of information refers to the process of gradual transmission through transformation after input data.(1)L=fnetlXW.The error of English translation skills is usually calculated in the form of mean square error, which can be expressed as(2)E=12∑i=1nti−oi.The first step of the gradient descent method is to change the value according to the weight. According to the rules(3)ΔWijL=αδiL,where α is the learning rate, δiL can be obtained by taking the derivative of mean square deviation, and its calculation formula is(4)δiL=fnetlnetl.List the weight change.(5)ΔWijX=αδjX.The calculation formula is(6)δjX=∑p=1nWjpL.Teachers should make use of classroom presuppositions to give students clear guidance so that they can understand the structure and stylistic features of different texts, improve their perception of nonverbal modes, and cultivate their reading and discrimination abilities of nonverbal modes with the help of nonverbal modes in texts. Therefore, in order to ensure the accuracy of the English translation skills and the enrichment of the content, in the actual process of multimodal networked English translation skills, we should focus on the accuracy and enrichment of translation, actively use multimodal networked symbols to achieve the expression of meaning, and reasonably use images, music, gestures, animation, and other language symbols for translation [21]. In the actual process of English translation skills, language is still the main way to convey information, while nonverbal forms refer to body movements, facial expressions, pictures, background music, animation, and other types of information dissemination methods or tools.The teaching contents and learning methods of English translation strategies are embedded in the teaching process, teaching form, and teaching environment, and the online learning method under the background of “Internet + resource bank” of environmental art specialty is used to drive the organic combination and multimodal development of offline classroom teaching and enterprise practice teaching. In the context of multimodality, combined with the cognitive evaluation theory in cognitive psychology, this paper attempts to construct a theoretical framework of English translation skills based on multimodal networking of attitude meaning, further improving the theoretical basis of English translation skills on the classification of emotional meaning and enhancing the application value of multimodal networking in the construction of English translation skills [22]. Through the multimodal translation strategy, through the support of language, picture color, audio, and video, it can further enrich the meaning of the text, help the audience to build psychological schema, ensure the effectiveness of translation, and improve the smoothness of reading translated materials.
### 3.2. Application of English Translation Skills Based on Multimodal Network from the Perspective of Situational Teaching
In situational teaching, consciously use multimodal networks to guide students’ English translation skills. Pay attention to and attract attention, which will have a positive effect on cultivating their thinking and study habits. In situational teaching, multimodal network discourse integration is applied, and in the process of English translation skills, corresponding pictures, music, and video materials are scientifically integrated so as to fully convey the true content of the discourse. For readers, the translation is like gobbledygook, which fails to achieve the purpose of publicity and even keeps people away. Only by transforming some of the contents into the accepted multimodal network form can more people understand them, thus achieving the goal of multimodal network English translation skills in situational teaching. The key aspects of the possibility of multimodal network communication include the choice potential of ideology as the main form and style of culture. The translation should be carried out on the premise of considering the cultural level, which is in line with the cultural significance of the overall linguistic model and the nonlinguistic model construction. In order to ensure the effectiveness of English translation skills and the accuracy of information transmission, efforts should be made to cross this foreign cultural difference and strengthen the integration of multimodal network English translation skills in situational teaching so as to ensure the scientificity, rationality, and accuracy of the translation. After correctly interpreting the text, students screen the required modes, make the best combinations, create multimodal networked works, and demonstrate their English translation skills through PPT, lectures, and other forms. The situational classroom teaching process from the perspective of multimodal networking is shown in Figure2.Figure 2
Flow chart of situational classroom teaching.Translation researchers and practitioners with a high level of competence should devote themselves to the research and practice of publicity translation. Relevant government departments, nongovernmental organizations, cultural scholars, translation researchers, and practitioners should actively cooperate. Situational teaching and multimodal networked English translation skills adopt group-based on-the-spot teaching. According to the training characteristics and teaching requirements of vocational and technical personnel, the complex design teaching process is decomposed into many specific and single skills that are easy to understand, and training goals are proposed for each skill to improve students’ professional skills. Through the use of color, the importance of this paragraph of text is emphasized, which is different from other words. Therefore, nonverbal symbols here have the conceptual function of expressing importance. Together with the text and surrounding text, they form a complete text, thus having the interpersonal function of letting readers participate better. It strengthens the conceptual meaning, helps English readers who may not know much about Chinese culture to better understand the content of this chapter, realizes the conceptual function and interpersonal function, and forms a text for understanding the whole chapter together with the text. Then, from the perspective of situational teaching, teachers can guide students to pay attention to the main clues of story development. The frequency of words appearing in the document. The higher the frequency, the more important the word is to the document than other words. The simplest expression is(7)TF1=Ni,j,where Ni,j is the value of the unit when the matrix is simply counted, that is, the number of times that the word with serial number i appears in the translation with serial number i.There are some improved formulas for word frequency, such as(8)TF2=Ni,jN∗,j,TF3=logNi,j,N∗,j is the total number of words in the translation with serial number j. This practice not only considers the frequency of words but also the influence of column elements in the matrix.If a word only appears in a few translations in the translation set, it is considered that the word is more important to these few translations and should correspond to the weight of the corresponding column in the reinforcement matrix. The calculation formula is(9)IDF=logDDi,where D is the number of translations. Di is the number of documents containing words with serial number i.After roughly browsing the text, the students found that the story unfolded in chronological order, so they continued to read deeply according to the time clues and told the story through illustrations according to their own understanding. Students can not only extract beautiful words and sentences but also write their feelings after reading. They can also record videos to introduce their feelings after reading and reflecting. For novels, you can also make mind maps to straighten out the relationships between characters, which will help to creatively improve their reading and writing abilities. When translating multimodal works, we should give full consideration to the graphic relationships in the original work. Besides the translation of the core language level, we should also give full consideration to the influence of other modal factors such as images, colors, sounds, and even technology on the overall discourse. Among them, discourse meaning mainly refers to the scope and tone of language and the meaning of words formed under the language form, including conceptual meaning, interpersonal meaning, and the meaning of writing. The formal level mainly refers to the form and relationship of discourse. The form refers to language, image perception, sound perception, and feelings. The relationship includes complementary and noncomplementary elements. Reasonable application of multimodal translation strategies and full use of language and human sensory systems can achieve effective complementarity between different modes and achieve the purpose of translation. Therefore, in the process of teaching English translation skills in situational teaching, it is necessary to strengthen the research and discussion on multimodal networking, and at the same time, correctly understand the language habits and thinking modes of English translation skills, rationally apply diversified translation strategies and methods, and adopt multimodal methods to ensure the translation quality and dissemination effect of multimodal networking English translation skills.
## 3.1. English Translation Strategies Based on Multimodal Network
We should pay attention to the following content in the process of English translation skills and modes of multimodal network. To strengthen the consideration of cultural differences, the role of publicity translation itself is to realize the export of Chinese culture. Therefore, in the actual translation process, efforts should be made to cross the cultural gap and discover the differences and characteristics between Chinese and foreign cultures instead of mechanical translation word for word. While ensuring the accuracy of meaning transmission, English translation skills and modes should be fully reflected. The cultivation of multimodal network literacy requires very specific requirements. On the basis of the original four skills of listening, speaking, reading, and writing, the skill of “watching” is added, pointing out that “watching usually refers to the skills of understanding meaning by using figures, tables, animations, symbols, and videos in multimodal discourse” [19]. Wang et al., a Chinese translation scholar, put forward that “translatology is a special field of communication”. Language is the traditional carrier of folk culture, but with the development of multimedia technology, unnatural language symbols such as pictures, sounds, images, animations, etc., have also become an integral part of cultural meaning and image construction, and the spread of the new media environment has promoted the integration of text, sounds, videos, and images [20]. Due to the different cultural backgrounds between China and foreign countries, there are also great differences in thinking patterns and habits. Therefore, in the actual process of publicity translation, many words in foreign languages are used to express specific meanings or, because of different thinking patterns, simple literal translation can easily lead to comprehension errors. Therefore, translators need to be familiar with Chinese and foreign language customs to ensure the accuracy of translation results. In the teaching process of “on-the-spot practice,” teachers can use modern teaching tools such as Schiavo whiteboards to simulate the real language environment, design classroom activities for interaction between teachers and students, and improve the effectiveness of the practice process. Multimodal networking is more urgent for English translation resources and professional materials. Teachers, students, enterprises, and the English translation resource base are the four main bodies of teaching activities, and their interaction is shown in Figure 1.Figure 1
Relationship between multimodal networking and the main body of English translation skills resource base.Through multimodal integration and discourse analysis, such problems can be effectively improved. With the help of language, words, images, sounds, videos, and other forms, it is helpful to further promote the content of English translation skills and help the public strengthen their understanding of English translation skills. The forward multimodal network transmission of information refers to the process of gradual transmission through transformation after input data.(1)L=fnetlXW.The error of English translation skills is usually calculated in the form of mean square error, which can be expressed as(2)E=12∑i=1nti−oi.The first step of the gradient descent method is to change the value according to the weight. According to the rules(3)ΔWijL=αδiL,where α is the learning rate, δiL can be obtained by taking the derivative of mean square deviation, and its calculation formula is(4)δiL=fnetlnetl.List the weight change.(5)ΔWijX=αδjX.The calculation formula is(6)δjX=∑p=1nWjpL.Teachers should make use of classroom presuppositions to give students clear guidance so that they can understand the structure and stylistic features of different texts, improve their perception of nonverbal modes, and cultivate their reading and discrimination abilities of nonverbal modes with the help of nonverbal modes in texts. Therefore, in order to ensure the accuracy of the English translation skills and the enrichment of the content, in the actual process of multimodal networked English translation skills, we should focus on the accuracy and enrichment of translation, actively use multimodal networked symbols to achieve the expression of meaning, and reasonably use images, music, gestures, animation, and other language symbols for translation [21]. In the actual process of English translation skills, language is still the main way to convey information, while nonverbal forms refer to body movements, facial expressions, pictures, background music, animation, and other types of information dissemination methods or tools.The teaching contents and learning methods of English translation strategies are embedded in the teaching process, teaching form, and teaching environment, and the online learning method under the background of “Internet + resource bank” of environmental art specialty is used to drive the organic combination and multimodal development of offline classroom teaching and enterprise practice teaching. In the context of multimodality, combined with the cognitive evaluation theory in cognitive psychology, this paper attempts to construct a theoretical framework of English translation skills based on multimodal networking of attitude meaning, further improving the theoretical basis of English translation skills on the classification of emotional meaning and enhancing the application value of multimodal networking in the construction of English translation skills [22]. Through the multimodal translation strategy, through the support of language, picture color, audio, and video, it can further enrich the meaning of the text, help the audience to build psychological schema, ensure the effectiveness of translation, and improve the smoothness of reading translated materials.
## 3.2. Application of English Translation Skills Based on Multimodal Network from the Perspective of Situational Teaching
In situational teaching, consciously use multimodal networks to guide students’ English translation skills. Pay attention to and attract attention, which will have a positive effect on cultivating their thinking and study habits. In situational teaching, multimodal network discourse integration is applied, and in the process of English translation skills, corresponding pictures, music, and video materials are scientifically integrated so as to fully convey the true content of the discourse. For readers, the translation is like gobbledygook, which fails to achieve the purpose of publicity and even keeps people away. Only by transforming some of the contents into the accepted multimodal network form can more people understand them, thus achieving the goal of multimodal network English translation skills in situational teaching. The key aspects of the possibility of multimodal network communication include the choice potential of ideology as the main form and style of culture. The translation should be carried out on the premise of considering the cultural level, which is in line with the cultural significance of the overall linguistic model and the nonlinguistic model construction. In order to ensure the effectiveness of English translation skills and the accuracy of information transmission, efforts should be made to cross this foreign cultural difference and strengthen the integration of multimodal network English translation skills in situational teaching so as to ensure the scientificity, rationality, and accuracy of the translation. After correctly interpreting the text, students screen the required modes, make the best combinations, create multimodal networked works, and demonstrate their English translation skills through PPT, lectures, and other forms. The situational classroom teaching process from the perspective of multimodal networking is shown in Figure2.Figure 2
Flow chart of situational classroom teaching.Translation researchers and practitioners with a high level of competence should devote themselves to the research and practice of publicity translation. Relevant government departments, nongovernmental organizations, cultural scholars, translation researchers, and practitioners should actively cooperate. Situational teaching and multimodal networked English translation skills adopt group-based on-the-spot teaching. According to the training characteristics and teaching requirements of vocational and technical personnel, the complex design teaching process is decomposed into many specific and single skills that are easy to understand, and training goals are proposed for each skill to improve students’ professional skills. Through the use of color, the importance of this paragraph of text is emphasized, which is different from other words. Therefore, nonverbal symbols here have the conceptual function of expressing importance. Together with the text and surrounding text, they form a complete text, thus having the interpersonal function of letting readers participate better. It strengthens the conceptual meaning, helps English readers who may not know much about Chinese culture to better understand the content of this chapter, realizes the conceptual function and interpersonal function, and forms a text for understanding the whole chapter together with the text. Then, from the perspective of situational teaching, teachers can guide students to pay attention to the main clues of story development. The frequency of words appearing in the document. The higher the frequency, the more important the word is to the document than other words. The simplest expression is(7)TF1=Ni,j,where Ni,j is the value of the unit when the matrix is simply counted, that is, the number of times that the word with serial number i appears in the translation with serial number i.There are some improved formulas for word frequency, such as(8)TF2=Ni,jN∗,j,TF3=logNi,j,N∗,j is the total number of words in the translation with serial number j. This practice not only considers the frequency of words but also the influence of column elements in the matrix.If a word only appears in a few translations in the translation set, it is considered that the word is more important to these few translations and should correspond to the weight of the corresponding column in the reinforcement matrix. The calculation formula is(9)IDF=logDDi,where D is the number of translations. Di is the number of documents containing words with serial number i.After roughly browsing the text, the students found that the story unfolded in chronological order, so they continued to read deeply according to the time clues and told the story through illustrations according to their own understanding. Students can not only extract beautiful words and sentences but also write their feelings after reading. They can also record videos to introduce their feelings after reading and reflecting. For novels, you can also make mind maps to straighten out the relationships between characters, which will help to creatively improve their reading and writing abilities. When translating multimodal works, we should give full consideration to the graphic relationships in the original work. Besides the translation of the core language level, we should also give full consideration to the influence of other modal factors such as images, colors, sounds, and even technology on the overall discourse. Among them, discourse meaning mainly refers to the scope and tone of language and the meaning of words formed under the language form, including conceptual meaning, interpersonal meaning, and the meaning of writing. The formal level mainly refers to the form and relationship of discourse. The form refers to language, image perception, sound perception, and feelings. The relationship includes complementary and noncomplementary elements. Reasonable application of multimodal translation strategies and full use of language and human sensory systems can achieve effective complementarity between different modes and achieve the purpose of translation. Therefore, in the process of teaching English translation skills in situational teaching, it is necessary to strengthen the research and discussion on multimodal networking, and at the same time, correctly understand the language habits and thinking modes of English translation skills, rationally apply diversified translation strategies and methods, and adopt multimodal methods to ensure the translation quality and dissemination effect of multimodal networking English translation skills.
## 4. Results Analysis and Discussion
In this experiment, a large Xinhua bookstore randomly selected 30 books from each of the four categories of literature, philosophy and religion, economy, natural science, and comprehensive books in the basic classification of books. Among the 120 books in total, the distribution of multimodal online reading is shown in Table1.Table 1
Distribution of multimodal networked reading materials.
LiteraturePhilosophy and religionEconomicsNatural scienceTotalNon multimodal networked reading10812636Multimodal networked reading2022182484Total30303030120Proportion of multimodal networked reading materials67%73%60%80%70%In some special books, such as art books and literary works, multimodal network discourse occupies an absolute proportion. Among the 30 selected art books, all are multimodal discourses based on pictures and supplemented by words. The multimodal distribution of 120 randomly selected books is shown in Figure3.Figure 3
Proportion diagram of multimodal networked reading materials.It can be found from the data in Figure3 that 30 books were randomly selected from preschool children’s books, primary school books, and junior high school books, of which the highest proportion of multimodal books was 82%, 57%, and 54%, respectively. Among the 120 literary books, the proportion of multimodal network books was 79%.It can be seen from Figure4 that multimodal online reading accounts for a certain proportion of existing books and a large proportion of literature, philosophy, religion, and natural science. At the same time, there is also a large proportion of multimodal online reading in the translated works, so TQA, which only stays at the language level, is far from serving the current translation practice.Figure 4
Proportion diagram of modal reading materials in the English-Chinese translation.This paper focuses on how to reproduce the three metafunctions of the nonverbal mode in translation and realize the meaning of reproduction under the condition of complementary images and texts. The distribution of nonverbal symbols is shown in Table2.Table 2
Distribution table of nonverbal symbols in original text and translated text.
ChartFrameColorTotalText pagesNonverbal symbol scaleOriginal text1938611161170.98Translation152950921820.51The proportion of nonverbal symbols in the original text is 0.98. That is, there is basically one nonverbal symbol on every page. The proportion of nonverbal symbols in the translated text is 0.51. That is, basically, one nonverbal symbol appears every two pages. Considering the different length characteristics of the Chinese and English languages and the translator’s deletion of chapters in the original text, the proportion of nonverbal symbols in the original text and the translated text is basically the same, and the translated text is slightly less.Chinese and English can be translated into each other, but the corresponding translation results of Chinese words corresponding to English words may be too long. Therefore, in this experiment, 200 groups of secret information with a sentence length of about 20 Chinese characters, about 30 Chinese characters, and about 40 Chinese characters were selected, and the secret information was hidden, and the change of embedding rate was counted, and the collected results were sorted and analyzed and compared. Figures5–7 show the experimental results respectively.Figure 5
Schematic diagram of secret information embedding rate results with a length of 20 words.Figure 6
Schematic diagram of secret information embedding rate results with a length of 30 words.Figure 7
Schematic diagram of secret information embedding rate results with a length of 40 words.The embedding rate data in the above figure are summarized, and the median embedding rate is added for comparative analysis. As shown in Table3.Table 3
Comparison of embedding rates of sentences with different word lengths.
Statement lengthMinimum embedding rate (%)Maximum embedding rate (%)Average embedding rate (%)Median embedding rate (%)20 words15.244.922.821.530 words14.439.123.223.340 words17.632.222.821.9Average value15.738.722.922.2According to Figures5–7, with the increase in the length of Chinese secret information, the embedding rate waveform is gradually stable, which means it is closer to the average embedding rate curve. It can be concluded that the longer the length of Chinese secret information is, the more stable the embedding rate is. From the two columns of the lowest embedding rate and the highest embedding rate in Table 3, we know that with the increase in the length of Chinese secret information, the lowest embedding rate is gradually increasing, while the highest embedding rate is gradually decreasing, which tends to the average value. The weight of words that often appear in some documents makes rare words in a translation play a greater role in distinguishing them. In this way, if an excellent translation uses a high-level vocabulary with little frequency, the translations that also use this high-level vocabulary will have a higher similarity, and it is more likely to appear in the similar translation set of this excellent translation, further strengthening the connection between the translations of the same grade.
## 5. Conclusion
To sum up, the actual process of multimodal online integration of English translation mainly includes the integration of the original text and the translation. To ensure the effectiveness of multimodal translation, we should focus on the scientific integration of culture, content, and expression so as to ensure the effectiveness of multimodal online translation strategies. From the perspective of situational teaching, this paper studies the skills and modes of multimodal networked English translation. The research shows that 30 books are randomly selected from preschool children’s books, primary school books, and junior high school books, of which the highest proportion of multimodal books is 82%, 57%, and 54%, respectively. Among the 120 literary books, the proportion of multimodal networked books is 79%. The main purpose of analyzing multimodal networked English translation skills under situational teaching is to ensure that the original meaning of the translation results is fully, completely, truly, and accurately expressed, and that readers can intuitively understand their own meaning so that the translation results are easy to understand. When evaluating the translation quality of multimodal networked works, we should also carefully consider the translation of nonverbal symbols and the extent to which the functions of various states are reproduced in the translation. At the same time, when the original author and the publisher publish the original work, they should also pay attention to improving the quality of nonverbal symbols so that readers can read multimodally. In the context of situational teaching, multimodal networked English translation skills are growing at an unprecedented rate. Many experts and scholars at home and abroad have affirmed the importance of multimodal networked English translation skills. Therefore, we must fully consider the particularities of multimodal networking when measuring translation quality.
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*Source: 2899947-2022-10-11.xml* | 2022 |
# Antimicrobial and Immunomodulatory Activity of Herb Extracts Used in Burn Wound Healing: “San Huang Powder”
**Authors:** Jia-Ru Wu; Yu-Chu Lu; Sung-Jen Hung; Jung-Hsing Lin; Kai-Chih Chang; Jhong-Kuei Chen; Wan-Ting Tsai; Tsung-Jung Ho; Hao-Ping Chen
**Journal:** Evidence-Based Complementary and Alternative Medicine
(2021)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2021/2900060
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## Abstract
“San Huang Powder,” a nonsterile milled herb powder, is frequently used to treat burn wounds in traditional Chinese herbal medicine. However, treating a wound with a nonsterile dressing or reagent is not compatible with the current guidelines in modern medicine. Therefore, we investigated the bactericidal and anti-inflammatory activities of four herb extracts used in “San Huang Powder”in vitro. Meanwhile, an in vivo porcine model with superficial second-degree burns was used for the experiments since the size and skin composition of pigs are the closest to that of the human body. The minimal bactericidal concentration (MBC) of the herb extracts was determined. The in vitro assay indicated that Rhubarb and Phellodendron bark extracts decreased the levels of inflammatory cytokines, IL-8, and GM-CSF on LPS-induced HMEC-1 cells. In accordance with this result, the histopathological evaluation results showed that the efficacy of “San Huang Powder” containing both herb materials was much better than the group without Rhubarb. Our results not only provide a basis to understand why “San Huang Powder” has been used to clinically treat wounds without sterilization directly since ancient times but also show the advantages of using multiple herb materials simultaneously on wound sites to prevent infection during treatment. Rhubarb is the recommended ingredient involved in the preparation of “San Huang Powder” to ensure the healing efficacy of burn wounds.
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## Body
## 1. Introduction
“San Huang Powder” is a widely used traditional Chinese herbal medicine. The name of this preparation was first mentioned in an ancient medical book, Beiji Qianjin Yao Fang, published in 652 B.C. It is well known for the treatment of first- and second-degree burn wounds [1–3]. Literally, “San Huang” means that this medicine is made from three different yellow-colored herbs. However, the recipes of “San Huang Powder” vary in different ancient medical books. Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome are the four most frequently used materials to prepare “San Huang Powder.” Moreover, Rhubarb's efficacy in treating burn wounds was recently reported [4, 5]. However, there is no systematic study comparing the efficacy of different “San Huang Powder” recipes for the treatment of burn wounds to date.The milled herbal powder without sterilization is used to treat wounds directly in folk medicine. However, modern medicine physicians constantly criticize this treatment due to concerns relating to infection control. In this study, anin vitro bactericidal activity assay was performed to provide more clarity on this issue. The in vitro immunomodulatory activity of herbal materials was also investigated. Since pig skin structure and function have the closest resemblance to that of humans [6, 7], we used an in vivo porcine burn model in healing burn wounds to examine the efficacy of two different “San Huang Powder” recipes. The results obtained in this study provide the scientific basis for its clinical use and insight for preparation of next generation “San Huang Powder” extract.
## 2. Materials and Methods
The Institutional Animal Care and Use Committee, National Laboratory Animal Center, Taiwan, ROC, approved all experimental animal procedures (Permission number: NLAC (TN)-107-M-009R1).
### 2.1. Materials
Berberine hydrochloride was purchased from TCI Co., Ltd. (Tokyo, Japan). Chrysin was obtained from Acros Organics (Geel, Belgium). Chrysophanol was purchased from Sigma-Aldrich (St. Louis, MI, USA). Vascular endothelial growth factor (VEGF) was bought from B & D Systems (Minneapolis, MN, USA). Rhubarb (dried stem and root fromRheum palmatum LINN) was a product of Da Rong Co., Ltd. (Tao Yuan City, Taiwan) (batch number: DK1070932). Scutellaria root (dried root from Scutellaria baicalensis Georgi) was the product of He Kang Chinese Medicine Co., Ltd. (New Taipei City, Taiwan) (batch number: 0704). Phellodendron bark (dried bark from Phellodendron amurense Ruprecht) was the product of Jin Rong Co., Ltd. (New Taipei City, Taiwan) (batch number: AG80303). Coptidis rhizome (dried rhizome of Coptis chinensis Franch) was the product of Fu Ji Co., Ltd. (Kaohsiung City, Taiwan) (batch number: FG0013). Further identification analysis of these plant-based materials was done by HPLC, as described below. The raw herb materials were ground into fine powder using a coffee grinder (Model: ECG3003S, Electrolux, New Taipei City, Taiwan). The milled powder was further sieved using ultrafine 100 mesh stainless steel filter and stored in a dry cabinet. The recipes of two different types of “San Huang Powder” are listed in Table 1.Table 1
The recipes of two different types of “San Huang Powder” used in this study.
GroupIngredientControl (CA)Scutellaria root : Phellodendron bark : Coptidis rhizome = 1 : 1 : 1Test article (TA)Rhubarb : Scutellaria root : Phellodendron bark : Coptidis rhizome = 1 : 1 : 1 : 1
### 2.2. Determination of Reference Standard Content in Rhubarb, Scutellaria Root, Phellodendron Bark, and Coptidis Rhizome by HPLC
All experiments were performed using a Hitachi L-7000 HPLC system (Hitachi, Ltd., Tokyo, Japan), equipped with a L-7100 quaternary gradient pump and a L-7450 photo diode array detector. Hitachi HSM software was used for machine control and data collection and processing. The analytical column used was theμBondapak™ C18 Column, 125 Å, 10 μm, 3.9 × 300 mm (Waters Corporation, Milford, Massachusetts, USA).A 1 g sample of each dried herb material was ground into fine powder, using a coffee grinder (Model: ECG3003S, Electrolux, New Taipei City, Taiwan). The herbs were then extracted twice with the following solvents: Rhubarb: 10 mL methanol, Scutellaria root: 10 mL of ethanol, Phellodendron bark: 10 mL of methanol, and Coptidis rhizome: 10 mL of 70% ethanol. One gram of grounded solids were weighed and dissolved in 10 ml of solvent. After ultrasonicating for 30 minutes at 25°C, extracts were transferred to a new glass vial using disposable glass Pasteur pipettes. Another 10 ml of solvent was then added and ultrasonicated for another 30 minutes at 25°C. Undissolved particles were removed by centrifugation at 2500 ×g for 10 minutes at 25°C and filtered through a 0.22μm syringe filter. The final volume of the extract was adjusted to 20 ml. To calculate the extraction yield (mass of extract/mass of dry matter), 1 ml extracts were dried under vacuum at 25°C overnight in a Savant SpeedVac Vacuum Concentrator (Thermo Fisher Scientific Inc., Waltham, Massachusetts, USA). Folin-Ciocalteu method was used to determine the total phenolic content in the extracts [8]. Total phenolic content of the extract samples was expressed as gallic acid equivalent (GAE) milligrams per gram of the extract.The methanol extract of Rhubarb was separated using a gradient elution of solvent A (10% CH3CN, containing 0.1% H3PO4) and solvent B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min [9]. The UV detection wavelength was 254 nm. The ethanol extract of Scutellaria root was separated using a gradient elution of solvent A (10% CH3CN, containing 0.1% H3PO4) and solvent B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min. The UV detection wavelength was 280 nm. The methanol extracts of Phellodendron bark were separated using a gradient elution of solvents A (10% CH3CN, containing 0.1% H3PO4) and B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min. The UV detection wavelength was 260 nm. The ethanol extract of Coptidis rhizome was separated using a gradient elution of solvents A (0.1% KH2PO4 buffer) and B (100% CH3CN) at a flow rate of 1 ml/min [10]. The UV detection wavelength was 260 nm. The HPLC elution programs for the four herbs are presented in Table 2.Table 2
HPLC elution programs for Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome.
RhubarbScutellaria rootPhellodendron barkCoptidis rhizomeTime (min)Eluent (B%)Time (min)Eluent (B%)Time (min)Eluent (B%)Time (min)Eluent (B%)0–10350–2150–5200–5010–2535–1002–615–305–2520–305–160–8025–301006–2030–4025–3530–10016–2180–10020–2240–5035–4010021–30100
### 2.3. Determination of the Minimal Bactericidal Concentration (MBC) of the Herbal Materials
The minimal bactericidal concentration (MBC) of the herbal materials used in this study to kill the following,Acinetobacter baumannii Bouvet and Grimont (ATCC® 19606™), Acinetobacter baumannii Bouvet and Grimont (ATCC® 17978™), Elizabethkingia meningoseptica BCRC 10677, Escherichia coli DH5α, Pseudomonas aeruginosa PAO1, Propionibacterium acnes PS023, Staphylococcus epidermidis TCU-1 BCRC 81267, and Staphylococcus aureus subsp. aureus TCU-2 BCRC 81268, was determined. P. acnes PS023 is an erythromycin- and clindamycin-resistant clinical isolate. One gram of each herb material was extracted with 4 mL methanol at room temperature, overnight. The herbal methanol extracts (500 µL each) were dried using a Savant SpeedVac Vacuum Concentrator and dissolved in 25 µL DMSO. The DMSO stock of each herb extract was further diluted (10x) with the Rein-forced Clostridial Medium for P. acnes PS023 and Mueller Hinton broth for the other bacteria. The adjusted herb extract was serially diluted into multiple wells on a 96-well plate to obtain a gradient. After overnight growth at 37°C, the wells which were clear were evaluated for colony-forming units per mL (CFU/mL) on agar plates. Only P. acnes PS023 grow in anaerobic chamber using a mixture of 10% CO2, 10% H2, and 80% N2.
### 2.4. Animal Experiments
Three female Lee-Sung pigs were purchased from the Department of Animal Science and Technology, National Taiwan University, Taiwan. The pigs were 4.5 months old (average weight: 18.0 kg) and had similar body shapes. Each animal was maintained as described previously [7]. The Institutional Animal Care and Use Committee, National Laboratory Animal Center, Taiwan, ROC, approved all experimental animal procedures (Permission number: NLAC(TN)-107-M-009R1). General anesthesia was maintained by isoflurane via inhalation. Intramuscular Zoletil (5 mg/kg) and Xylazine (2.2 mg/kg) and subcutaneous Atropine (0.05 mg/kg) were used for sedation. Subcutaneous injection of Buprenorphine (0.05 mg/kg) for pain relief and oral administration of Enrofloxacin (5 mg/kg) were performed for infection control during the operation. Meanwhile, isoflurane inhalation and Lidocaine (2%) spray anesthesia were administered (Figure 1). A second-degree burn wound was made with the help of a burn device (Model YLS-5Q, Yi Yan Tech. Co., Ltd., Shandong, China), consisting of a 4 cm diameter heating probe. The setting of the burn device for contact pressure, temperature, and time was 500 g, at 90°C for 20 sec, respectively. The procedure was performed under aseptic conditions to create uniform dermal scalding wounds on the three adult minimum disease female Lee-Sung pigs. The burn wounds were created on six different locations on the dorsal side of each animal. Sterile gauze was used to keep the wounds clean. Two different “San Huang Powder” compositions, test article (TA) and control (CA), were directly applied to the wound surface, and dressings were replaced daily (Table 3). In traditional Chinese medicine, the physician directly sprays “San Huang Powder” over the wound site. About one gram of “San Huang Powder” was used over the wound area (12 cm2). Oral cephalexin (20 mg/kg) and meloxicam (0.4 mg/kg) were administered twice daily during the first seven days. No apparent abnormalities were seen during the experimental process until the sacrifice. Euthanasia of all animals was performed one day after completion of the study by using pentobarbital (120 mg/kg). Once euthanasia was performed, the collection of tissues was initiated immediately.Figure 1
Burn wounds were covered with sterile gauze dressing after treatment with CA, and TA.Table 3
Treatment groups and duration.
GroupTreatmentStudy period (biopsy samples taken)7 days14 days21 daysCA1 g/day333TA1 g/day333The wound sites were photographed on days 7, 14, and 21 after the burn injury. The dermal wound tissue was sampled using a 6 mm biopsy punch (Lot no.: 17L13, Integra LifeSciences, Plainsboro, NJ, USA) and preserved in 10% neutral-buffered formalin on days 7, 14, and 21 after the burn injury. After fixation, the tissues were trimmed, embedded, and divided into 5 mm thick sections and placed on glass slides (Immuno Coated slide, MUTO, Japan). These paraffin-embedded sections were treated with hematoxylin and eosin (H & E), Masson-trichrome (MT) stains, and immunohistochemistry (IHC) stain, as reported previously [7].
### 2.5. Inflammatory Cytokine Immunoassay
HMEC-1 cells were cultured, as described previously [11]. For the cell viability test, 1.0 × 105 cells were seeded into a 24-well plate per well then treated with Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome [12, 13]. The working concentrations of each herb material were 0.04, 0.12, 0.36, and 1.08 mg/mL. After incubation with HMEC-1 cells for 24 hours, each herb material’s IC50 (half maximal inhibitory concentration) values were determined by counting of HMEC-1 number. Relative survival rates were shown as mean ± SD, taking the value of the control group as 100%. Through one-tailed test analysis, ∗ denotes statistical significance (p<0.05) compared with control and represents two reproducible results.Cells were treated with 0.1% DMSO, 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, or 0.4 mg/mL Coptidis rhizome for 1 h and then untreated (DMSO and LPS groups) or treated with 0.2 g/mL LPS for an additional 24 h. The amount of human inflammatory cytokines in the cell suspension was determined using a human inflammatory cytokine multiplex ELISA kit (Arigo Biolaboratories, Hsinchu, Taiwan). All steps were performed as per the protocol provided by the manufacturer.
### 2.6. Reverse Transcription and Quantitative PCR
For HMEC-1, cells were pretreated with 0.5 mg/ml CA or 0.5 mg/ml TA for 2 hours and then treated with 0.2 g/ml LPS for another 24 hours. For the heat shock treatment of HaCaT, cells were incubated in a serum-free medium with 0.5 mg/ml CA or 0.5 mg/ml TA at 42°C for 15 min and then maintained at 37°C for another 48 hours. RNA was isolated from HMEC-1 and HaCaT cells using a purification kit (Protech Technology Enterprise, Taipei, Taiwan). Reverse transcription was performed using an RT kit (Protech Technology Enterprise, Taipei, Taiwan). Analysis of target gene expression by quantitative PCR was normalized withβ-Actin. Primer sequences are listed in Table 4.Table 4
Primer sequences for RT-qPCR of target genes in this study.
Target genePrimer sequenceADRPF: GGCTAGACAGGATTGAGGAGAGR: TCACTGCCCCTTTGGTCTTGIL-8F: CTCTCTTGGCAGCCTTCCTGAR: CCCTCTGCACCCAGTTTTCCTTNF-κBF: CCTGGATGACTCTTGGGAAAR: TCAGCCAGCTGTTTCATGTCSTAT3F: CATATGCGGCCAGCAAAGAAR: ATACCTGCTCTGAAGAAACT
### 2.7. Cell Number Analysis
For HMEC-1 and RAW264.7, cells were pretreated with 0.5 mg/ml CA or 0.5 mg/ml TA for 2 hours and then treated with 0.2μg/ml LPS for another 24 hours. At the end of treatment, cells would be detached from culture plates using 0.25% trypsin EDTA solution (Thermo Fisher Scientific, Hualien, Taiwan) and then cell numbers could be counted.
## 2.1. Materials
Berberine hydrochloride was purchased from TCI Co., Ltd. (Tokyo, Japan). Chrysin was obtained from Acros Organics (Geel, Belgium). Chrysophanol was purchased from Sigma-Aldrich (St. Louis, MI, USA). Vascular endothelial growth factor (VEGF) was bought from B & D Systems (Minneapolis, MN, USA). Rhubarb (dried stem and root fromRheum palmatum LINN) was a product of Da Rong Co., Ltd. (Tao Yuan City, Taiwan) (batch number: DK1070932). Scutellaria root (dried root from Scutellaria baicalensis Georgi) was the product of He Kang Chinese Medicine Co., Ltd. (New Taipei City, Taiwan) (batch number: 0704). Phellodendron bark (dried bark from Phellodendron amurense Ruprecht) was the product of Jin Rong Co., Ltd. (New Taipei City, Taiwan) (batch number: AG80303). Coptidis rhizome (dried rhizome of Coptis chinensis Franch) was the product of Fu Ji Co., Ltd. (Kaohsiung City, Taiwan) (batch number: FG0013). Further identification analysis of these plant-based materials was done by HPLC, as described below. The raw herb materials were ground into fine powder using a coffee grinder (Model: ECG3003S, Electrolux, New Taipei City, Taiwan). The milled powder was further sieved using ultrafine 100 mesh stainless steel filter and stored in a dry cabinet. The recipes of two different types of “San Huang Powder” are listed in Table 1.Table 1
The recipes of two different types of “San Huang Powder” used in this study.
GroupIngredientControl (CA)Scutellaria root : Phellodendron bark : Coptidis rhizome = 1 : 1 : 1Test article (TA)Rhubarb : Scutellaria root : Phellodendron bark : Coptidis rhizome = 1 : 1 : 1 : 1
## 2.2. Determination of Reference Standard Content in Rhubarb, Scutellaria Root, Phellodendron Bark, and Coptidis Rhizome by HPLC
All experiments were performed using a Hitachi L-7000 HPLC system (Hitachi, Ltd., Tokyo, Japan), equipped with a L-7100 quaternary gradient pump and a L-7450 photo diode array detector. Hitachi HSM software was used for machine control and data collection and processing. The analytical column used was theμBondapak™ C18 Column, 125 Å, 10 μm, 3.9 × 300 mm (Waters Corporation, Milford, Massachusetts, USA).A 1 g sample of each dried herb material was ground into fine powder, using a coffee grinder (Model: ECG3003S, Electrolux, New Taipei City, Taiwan). The herbs were then extracted twice with the following solvents: Rhubarb: 10 mL methanol, Scutellaria root: 10 mL of ethanol, Phellodendron bark: 10 mL of methanol, and Coptidis rhizome: 10 mL of 70% ethanol. One gram of grounded solids were weighed and dissolved in 10 ml of solvent. After ultrasonicating for 30 minutes at 25°C, extracts were transferred to a new glass vial using disposable glass Pasteur pipettes. Another 10 ml of solvent was then added and ultrasonicated for another 30 minutes at 25°C. Undissolved particles were removed by centrifugation at 2500 ×g for 10 minutes at 25°C and filtered through a 0.22μm syringe filter. The final volume of the extract was adjusted to 20 ml. To calculate the extraction yield (mass of extract/mass of dry matter), 1 ml extracts were dried under vacuum at 25°C overnight in a Savant SpeedVac Vacuum Concentrator (Thermo Fisher Scientific Inc., Waltham, Massachusetts, USA). Folin-Ciocalteu method was used to determine the total phenolic content in the extracts [8]. Total phenolic content of the extract samples was expressed as gallic acid equivalent (GAE) milligrams per gram of the extract.The methanol extract of Rhubarb was separated using a gradient elution of solvent A (10% CH3CN, containing 0.1% H3PO4) and solvent B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min [9]. The UV detection wavelength was 254 nm. The ethanol extract of Scutellaria root was separated using a gradient elution of solvent A (10% CH3CN, containing 0.1% H3PO4) and solvent B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min. The UV detection wavelength was 280 nm. The methanol extracts of Phellodendron bark were separated using a gradient elution of solvents A (10% CH3CN, containing 0.1% H3PO4) and B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min. The UV detection wavelength was 260 nm. The ethanol extract of Coptidis rhizome was separated using a gradient elution of solvents A (0.1% KH2PO4 buffer) and B (100% CH3CN) at a flow rate of 1 ml/min [10]. The UV detection wavelength was 260 nm. The HPLC elution programs for the four herbs are presented in Table 2.Table 2
HPLC elution programs for Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome.
RhubarbScutellaria rootPhellodendron barkCoptidis rhizomeTime (min)Eluent (B%)Time (min)Eluent (B%)Time (min)Eluent (B%)Time (min)Eluent (B%)0–10350–2150–5200–5010–2535–1002–615–305–2520–305–160–8025–301006–2030–4025–3530–10016–2180–10020–2240–5035–4010021–30100
## 2.3. Determination of the Minimal Bactericidal Concentration (MBC) of the Herbal Materials
The minimal bactericidal concentration (MBC) of the herbal materials used in this study to kill the following,Acinetobacter baumannii Bouvet and Grimont (ATCC® 19606™), Acinetobacter baumannii Bouvet and Grimont (ATCC® 17978™), Elizabethkingia meningoseptica BCRC 10677, Escherichia coli DH5α, Pseudomonas aeruginosa PAO1, Propionibacterium acnes PS023, Staphylococcus epidermidis TCU-1 BCRC 81267, and Staphylococcus aureus subsp. aureus TCU-2 BCRC 81268, was determined. P. acnes PS023 is an erythromycin- and clindamycin-resistant clinical isolate. One gram of each herb material was extracted with 4 mL methanol at room temperature, overnight. The herbal methanol extracts (500 µL each) were dried using a Savant SpeedVac Vacuum Concentrator and dissolved in 25 µL DMSO. The DMSO stock of each herb extract was further diluted (10x) with the Rein-forced Clostridial Medium for P. acnes PS023 and Mueller Hinton broth for the other bacteria. The adjusted herb extract was serially diluted into multiple wells on a 96-well plate to obtain a gradient. After overnight growth at 37°C, the wells which were clear were evaluated for colony-forming units per mL (CFU/mL) on agar plates. Only P. acnes PS023 grow in anaerobic chamber using a mixture of 10% CO2, 10% H2, and 80% N2.
## 2.4. Animal Experiments
Three female Lee-Sung pigs were purchased from the Department of Animal Science and Technology, National Taiwan University, Taiwan. The pigs were 4.5 months old (average weight: 18.0 kg) and had similar body shapes. Each animal was maintained as described previously [7]. The Institutional Animal Care and Use Committee, National Laboratory Animal Center, Taiwan, ROC, approved all experimental animal procedures (Permission number: NLAC(TN)-107-M-009R1). General anesthesia was maintained by isoflurane via inhalation. Intramuscular Zoletil (5 mg/kg) and Xylazine (2.2 mg/kg) and subcutaneous Atropine (0.05 mg/kg) were used for sedation. Subcutaneous injection of Buprenorphine (0.05 mg/kg) for pain relief and oral administration of Enrofloxacin (5 mg/kg) were performed for infection control during the operation. Meanwhile, isoflurane inhalation and Lidocaine (2%) spray anesthesia were administered (Figure 1). A second-degree burn wound was made with the help of a burn device (Model YLS-5Q, Yi Yan Tech. Co., Ltd., Shandong, China), consisting of a 4 cm diameter heating probe. The setting of the burn device for contact pressure, temperature, and time was 500 g, at 90°C for 20 sec, respectively. The procedure was performed under aseptic conditions to create uniform dermal scalding wounds on the three adult minimum disease female Lee-Sung pigs. The burn wounds were created on six different locations on the dorsal side of each animal. Sterile gauze was used to keep the wounds clean. Two different “San Huang Powder” compositions, test article (TA) and control (CA), were directly applied to the wound surface, and dressings were replaced daily (Table 3). In traditional Chinese medicine, the physician directly sprays “San Huang Powder” over the wound site. About one gram of “San Huang Powder” was used over the wound area (12 cm2). Oral cephalexin (20 mg/kg) and meloxicam (0.4 mg/kg) were administered twice daily during the first seven days. No apparent abnormalities were seen during the experimental process until the sacrifice. Euthanasia of all animals was performed one day after completion of the study by using pentobarbital (120 mg/kg). Once euthanasia was performed, the collection of tissues was initiated immediately.Figure 1
Burn wounds were covered with sterile gauze dressing after treatment with CA, and TA.Table 3
Treatment groups and duration.
GroupTreatmentStudy period (biopsy samples taken)7 days14 days21 daysCA1 g/day333TA1 g/day333The wound sites were photographed on days 7, 14, and 21 after the burn injury. The dermal wound tissue was sampled using a 6 mm biopsy punch (Lot no.: 17L13, Integra LifeSciences, Plainsboro, NJ, USA) and preserved in 10% neutral-buffered formalin on days 7, 14, and 21 after the burn injury. After fixation, the tissues were trimmed, embedded, and divided into 5 mm thick sections and placed on glass slides (Immuno Coated slide, MUTO, Japan). These paraffin-embedded sections were treated with hematoxylin and eosin (H & E), Masson-trichrome (MT) stains, and immunohistochemistry (IHC) stain, as reported previously [7].
## 2.5. Inflammatory Cytokine Immunoassay
HMEC-1 cells were cultured, as described previously [11]. For the cell viability test, 1.0 × 105 cells were seeded into a 24-well plate per well then treated with Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome [12, 13]. The working concentrations of each herb material were 0.04, 0.12, 0.36, and 1.08 mg/mL. After incubation with HMEC-1 cells for 24 hours, each herb material’s IC50 (half maximal inhibitory concentration) values were determined by counting of HMEC-1 number. Relative survival rates were shown as mean ± SD, taking the value of the control group as 100%. Through one-tailed test analysis, ∗ denotes statistical significance (p<0.05) compared with control and represents two reproducible results.Cells were treated with 0.1% DMSO, 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, or 0.4 mg/mL Coptidis rhizome for 1 h and then untreated (DMSO and LPS groups) or treated with 0.2 g/mL LPS for an additional 24 h. The amount of human inflammatory cytokines in the cell suspension was determined using a human inflammatory cytokine multiplex ELISA kit (Arigo Biolaboratories, Hsinchu, Taiwan). All steps were performed as per the protocol provided by the manufacturer.
## 2.6. Reverse Transcription and Quantitative PCR
For HMEC-1, cells were pretreated with 0.5 mg/ml CA or 0.5 mg/ml TA for 2 hours and then treated with 0.2 g/ml LPS for another 24 hours. For the heat shock treatment of HaCaT, cells were incubated in a serum-free medium with 0.5 mg/ml CA or 0.5 mg/ml TA at 42°C for 15 min and then maintained at 37°C for another 48 hours. RNA was isolated from HMEC-1 and HaCaT cells using a purification kit (Protech Technology Enterprise, Taipei, Taiwan). Reverse transcription was performed using an RT kit (Protech Technology Enterprise, Taipei, Taiwan). Analysis of target gene expression by quantitative PCR was normalized withβ-Actin. Primer sequences are listed in Table 4.Table 4
Primer sequences for RT-qPCR of target genes in this study.
Target genePrimer sequenceADRPF: GGCTAGACAGGATTGAGGAGAGR: TCACTGCCCCTTTGGTCTTGIL-8F: CTCTCTTGGCAGCCTTCCTGAR: CCCTCTGCACCCAGTTTTCCTTNF-κBF: CCTGGATGACTCTTGGGAAAR: TCAGCCAGCTGTTTCATGTCSTAT3F: CATATGCGGCCAGCAAAGAAR: ATACCTGCTCTGAAGAAACT
## 2.7. Cell Number Analysis
For HMEC-1 and RAW264.7, cells were pretreated with 0.5 mg/ml CA or 0.5 mg/ml TA for 2 hours and then treated with 0.2μg/ml LPS for another 24 hours. At the end of treatment, cells would be detached from culture plates using 0.25% trypsin EDTA solution (Thermo Fisher Scientific, Hualien, Taiwan) and then cell numbers could be counted.
## 3. Results and Discussion
### 3.1. Content of Reference Standards Present in Rhubarb, Scutellaria Root, Phellodendron Bark, and Coptidis Rhizome
One of the main problems associated with herbal medicine is the high batch-to-batch variability regarding the concentrations of its active components. The content of pure chemical reference standards in herbal products is therefore used as an indicator for quality control and standardization. To characterize the herbal materials, HPLC was used to determine the content of Chrysophanol in Rhubarb, Chrysin in Scutellaria root, and Berberine hydrochloride in Phellodendron bark and Coptidis rhizome. Accordingly, extraction yield of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was 33.1%, 12.9%, 12.0%, and 10.0%, respectively. Total phenolic content (mg/g GAE) of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was 29.4, 3.3, 10.0, and 76.4, respectively. The content of reference standards in Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was measured by HPLC (Figure2). All calibration curves of reference compounds were linear over the concentration range studied (Table 5). A linear interpolation method was used to calculate the percentage by the mass of each reference standard in the analyzed herbal extracts.Figure 2
HPLC separation of reference compounds present in the extracts of herbal components. HPLC traces of (a) Chrysophanol in Rhubarb, (b) Chrysin in Scutellaria root, (c) Berberine chloride in Phellodendron bark, and (d) Berberine chloride in Coptidis rhizome.
(a)(b)(c)(d)Table 5
HPLC calibration curves of reference compounds, including regression equations, coefficients of determination (R2), and calibration ranges.
Reference compoundRegression equationR2Calibration rangeMass percentage (%)Chrysophanol in Rhubarby = 37412x + 8906.30.9990.15–5μg0.47Chrysin in Scutellaria rooty = 1951500x − 963650.9980.1–10μg0.37Berberine chloride in Phellodendron barky = 48857x + 6720750.9991.25–40μg1.06Berberine chloride in Coptidis rhizomey = 42135x + 1519200.9960.5–10μg2.14
### 3.2. Antibacterial Activity Assay
The MBC of herb materials used in this study against a variety of bacteria is shown in Table6. A. baumannii Bouvet and Grimont (ATCC® 19606™), A. baumannii Bouvet and Grimont (ATCC® 17978™), E. meningoseptica BCRC 10677, E. coli DH5α, and Pseudomonas aeruginosa PAO1 are Gram-negative bacteria. In contrast, P. acnes PS023, S. epidermidis TCU-1 BCRC 81267, and S. aureus subsp. aureus TCU-2 BCRC 81268 are Gram-positive bacteria. The bactericidal effect of these four herbal extracts on Gram-positive bacteria is better compared to Gram-negative bacteria. The lowest MBC (∗) for each bacterial strain was distributed evenly among the four different herbs (Table 6). These results suggest that the combination of multiple herb materials could achieve the best bactericidal results.Table 6
The minimal bactericidal concentration (MBC) of the herbal materials used in this study.
Bacterial strainsRhubarb (mg/ml)Scutellaria root (mg/ml)Phellodendron bark (mg/ml)Coptidis rhizome (mg/ml)A. baumannii Bouvet and Grimont ATCC 1960615.6∗31.312531.3A. baumannii Bouvet and Grimont ATCC 1797815.6∗62.5>250125E. meningoseptica BCRC 10677<7.8∗15.612531.3E. coli DH5α12531.3∗>5031.3∗P. acnes PS02315.631.37.8∗15.6P. aeruginosa PAO115.67.815.615.6S. epidermidis TCU-1 BCRC 81267<7.8∗15.6<7.8∗<7.8∗S. aureus subsp. aureus TCU-2 BCRC 8126831.331.315.6<7.8∗∗The lowest concentration to completely kill the specific strain.During the clinical treatment, for example, one gram of “San Huang Powder” (at least 250 mg of each herb material powder) was used to spray over the wound area (12 cm2). If the thickness of the fluid that covers the wound area is 2 mm, the working concentration of each herbal powder on the site of the wound is approximately 104 mg/ml. Thus, considering the synergic effects from different herb materials, the active components in “San Huang Powder” must be sufficient to kill or inhibit bacterial growth on the wounds during treatment. Considering this calculation, it is clear why “San Huang Powder” has been directly applied onto the wound site without sterilization since ancient times. Although the antibacterial activities of Rhubarb, Scutellaria root, and Coptidis rhizome have been reported sporadically [14–17], we were the first to systematically compare them in this study. Moreover, it is common to detect multidrug-resistant A. baumannii in hospitalized patients [18], and the PS023 used in this study is an erythromycin- and clindamycin-resistant strain. Since the herbal extracts were effective against PS023 and two A. baumannii strains, the results also suggest that the herbal extract complex is promising in treating multidrug-resistant bacteria in the future.
### 3.3. Histopathological Evaluation of the Wound Healing Process
No animal was found dead or moribund during the study period. A partial-thickness burn was successfully produced on every animal with superficial second-degree severity, as confirmed by the formation of vesicles, epidermal discontinuity, superficial dermal necrosis, and inflammation.On day 7, epidermal basal cell migration and proliferation were observed under H&E staining, for all groups. As shown in Figures3(a) and 3(b), the epidermal thickness was similar in both the CA and TA groups. During the early phase of wound healing, polymorphonuclear (PMNL) cell infiltration seemed more prominent in both groups. The scalding procedure not only induces localized tissue edema with transepidermal and superficial dermal necrosis but also causes vesicle and secondary pustule formation between the epidermal and dermal layers of skin. Due to the inflammatory stage of early wound healing, fibroblast proliferation and neo-formation of collagen matrix were not observed among all the groups on day 7, as can be seen in Figures 4(a) and 4(b). Results from the IHC staining of VEGF for angiogenesis revealed that, in the CA group, an increase in the expression of VEGF signals was seen compared to TA group (CA) (Figures 5(a) and 5(b)). This implied that the CA group had a better progression of wound healing at the early stage of acute burn injury.Figure 3
Results from H & E staining on different days after the application of herb, 100×. (a) CA on day 7, migrating epithelium (∗) and vesicle (V) formation with PMNL infiltration on wound surface. (b) TA on day 7, migrating epithelium (∗) and pustule (P) and vesicle (V) formation with PMNL infiltration on wound surface. (c) CA on day 14, bridging epithelium with fibroblasts and PMNL infiltration within wound area. (d) TA on day 14, bridging epithelium with fibroblasts and PMNL infiltration within wound area. (e) CA on day 28, migrating epithelium (∗) and an open wound between the edges. (f) TA on day 28, regenerated epithelium had sealed the wound without PMNL infiltration.Figure 4
Results from Masson-trichrome staining on different days after the application of herb, 100×. (a) CA on day 7, no notable collagen deposition within wound area. (b) TA on day 7, no notable collagen deposition within wound area. (c) CA on day 14, the fibroblast had secreted minimal collagen in granulation tissue (∗). (d) TA on day 14, the fibroblast had secreted minimal collagen in granulation tissue (∗). (e) CA on day 28, unbridged epithelium with moderate collagen in granulation tissue (∗). (f) TA on day 28, bridged epithelium with moderate collagen in granulation tissue (∗).Figure 5
Results from IHC staining of VEGF on different days after the application of herb, 200×. (a) CA on day 7, weak VEGF signals from section. (b) TA on day 7, no positive VEGF result from section. (c) CA on day 14, weak VEGF signals from section. (d) TA on day 14, weak VEGF signals from section. (e) CA on day 21, weak VEGF signals from section. (f) TA on day 21, strong VEGF signals from section.The epidermal proliferation and thickness were prominent in both the CA and the TA groups on day 14 (Figures3(c) and 3(d)). PMNL infiltration in the TA group was significantly less than that observed in the CA group, which means the wound healing step of the CA group is still in an inflammatory state. However, the MT staining showed that the collagen bundles between the dermal layers were more prominent in the TA group than in the CA group. Therefore, the proliferation and regeneration steps had started in the TA group, where the new tissue was rebuilt with collagen and extracellular matrix (Figures 4(c) and 4(d)). Hence, at this point of observation, the healing rate at the proliferation stage of acute burn injury was as follows: TA > CA.On day 21, both groups had complete epidermal regeneration without significant differences under H & E staining (Figures3(e) and 3(f)). MT staining also revealed that the collagen bundles over the epidermal-dermal junction and upper dermis were more thickened and compact in the experimental groups compared to the CA group (Figures 4(e) and 4(f)). Moreover, the PMNL infiltration was absent in TA, whereas PMNL remained in the CA group (Figures 3(e) and 3(f)). The newly formed blood vessels can provide oxygen and nutrients to promote wound repair. Since the VEGF signal in the TA group was higher than that in the CA group, angiogenesis can help the tissue heal faster in the TA group than in the CA group (Figure 5). Therefore, the healing rate of acute burn wounds at this stage was as follows: TA > CA.During the process of wound healing, the pigs felt itchy and would actively rub the wound or even try to remove the dressing. The blisters on the burn wound site were quite fragile. Because the particle size of herb materials is enormous and coarse, the friction from the herb particles led to rough wound surfaces in all experimental groups. Furthermore, the dark-colored herb materials were mixed with the exudate to form black scabs on days 14 and 21. The scab made it challenging to observe the healing process of the wound based on appearance (FigureS1). The wounds were superficial second-degree burns, and granulation tissues were observed on day 14 (Figure S1). Therefore, it is less likely to heal with significant scarring and wound contracture [19].In short, a second-degree superficial burn was created successfully in each pig, as evidenced by epidermal and upper dermal necrosis, vesicle formation, and inflammation. In the experimental groups, an early induction of epidermal basal cell migration and dermal endothelial cell angiogenesis was observed, along with the activation of immune response with PMNL infiltration for foreign pathogens on day 7, during the initial inflammatory stage of wound healing. On day 14 of wound healing (proliferation stage), the TA group had more prominent epidermal regeneration and increased dermal fibroblast proliferation and collagen synthesis. Finally, on day 21 of the wound healing process (proliferation and remodeling stage), a significant increase in fibroblast activities, collagen synthesis, and angiogenesis was observed in the TA group, which helped in an improved healing rate of the acute burn wound. The main difference in the composition between the CA and TA groups was the presence of Rhubarb in the latter groups.
### 3.4. Inflammatory Cytokine Immunoassay
The toxicity of each herb material was first determined by MTT assay [20]. However, the deep color of the herb extract led to significant errors. Therefore, their IC50 (half maximal inhibitory concentration) values for HMEC-1 cells were determined by counting cell numbers directly (Figure 6(a)). The in vitro anti-inflammatory activities of the four herb materials were then measured. Because the solubility and cytotoxicity of each herb material in DMSO are different, the maximum possible dose for each component was used for this assay, i.e., 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, and 0.4 mg/mL Coptidis rhizome.Figure 6
Thein vitro assay of the anti-inflammatory activity of herb materials used in this study. (a) HMEC-1 cells were treated with 0.04, 0.12, 0.36, and 1.08 mg/mL herb, including Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome for 24 h. Cell numbers were calculated and shown as mean ± SD. The IC50 (half maximal inhibitory concentration) values of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome for HMEC-1 cell were 0.88 ± 0.05, 0.71 ± 0.06, 2.65 ± 0.59, and 0.44 ± 0.05 mg/mL, respectively. The 0 group is without herb treatment, only DMSO solvent as control. The cell survival rate of control was taken as 100%. (b) HMEC-1 cells were treated with 0.1% DMSO, 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, or 0.4 mg/mL Coptidis rhizome for 1 h and then untreated (DMSO and LPS groups) or treated with 0.2 g/mL LPS for additional 24 h. Relative folds of OD450 nm values were calculated and shown as mean ± SD, taking the value of DMSO group as 1.0. Through one-tailed test analysis, ∗∗denotes statistical significance (p<0.005) compared with DMSO and represents two reproducible results.
(a)(b)Previous reports have indicated that the concentrations of more than ten different inflammatory cytokines, including interleukin-6 (IL-6), interleukin-8 (IL-8), and granulocyte-macrophage colony-stimulating factor (GM-CSF), were significantly higher in the serum of a burn patient than in controls [21]. As shown in Figure 6(b), the treatment with Rhubarb and Phellodendron bark led to a decrease in the levels of inflammatory cytokines, IL-8, and GM-CSF on LPS-induced HMEC-1 cells.The results obtained from the histopathologic evaluation of the tissues suggested that, on day 21, CA had a slower healing rate. The main difference between CA and TA groups was the presence of Rhubarb. These results were in line with a previous report and suggested that Rhubarb may play a vital role in burn wound healing [4].
### 3.5. Reverse Transcription and Quantitative PCR
To further investigate the gene expression difference in the presence or absence of Rhubarb in San Huang Powder during the wound healing process, RT and qPCR experiments were carried out. LPS was first used to induce inflammatory conditions in human endothelial cells, HMEC-1. NF-κB [22–25] and STAT3 [26–29] are proinflammatory factors to form a transcriptional complex which regulates the inflammatory response related to IL-8 gene expression [30–35]. As shown in Figures 7(a)–7(c), the gene expression of NF-κB, STAT3, and IL-8 was significantly inhibited after the treatment of LPS in both CA and TA groups. The decrease of LPS-induced NF-κB and IL-8 expression in the CA group is slightly higher than that in the TA group; however, the reduction of LPS-induced STAT3 expression in the TA group is more elevated than in the CA group. Therefore, there was no significant difference in the anti-inflammatory response between the CA and TA groups.Figure 7
The effects of the inclusion of Rhubarb on inflammatory and lipogenesis-related genes. HMEC-1 cells were pretreated with 0.5 mg/ml CA or TA for 2 h then with 200 ng/ml LPS (a, b). HaCaT were treated with 0.5 mg/ml CA or TA from heat shock for 15 min to incubate for 48 h (c, d). Cellular RNA was isolated and then mRNA expression of (a) NF-κB, (b) STAT3, (c) IL-8, and (d) ADRP were determined by reverse transcription quantitative PCR. β-actin was used as internal control. p∗<0.05and p∗∗<0.005 present statistical significance compared to CA group.
(a)(b)(c)(d)A previous study has shown that knockdown of the gene encoding adipose differentiation-related protein (ADRP) could impair wound healing in mice [36]. Other studies also indicated that lipid signaling molecules could regulate the wound healing process [37–42]. Moreover, lipids might play a role in the proliferation and migration of fibroblasts [43–48]. The heat-shocked keratinocyte model was used to mimic a burn wound. As shown in Figure 7(d), the treatment of CA and TA could lead to an increase of ADRP expression by 21% and 68%, respectively, in heat-shocked keratinocytes compared with a solvent control (DMSO). ADRP expression is associated with lipid storage as a marker of lipid accumulation in cells. The upregulation of ADRP in both groups might play a role in the wound healing process in this study. The inclusion of Rhubarb in San Huang Powder seems to help wound healing in this respect.The cell numbers of HMEC-1 and mouse macrophages (RAW264.7) were also measured after LPS and herb extract treatment. As shown in Figures8(a) and 8(b), the cell number for the CA group decreased by 26% for HMEC-1 and 33% for RAW264.7, respectively, compared to the group treated with LPS only. On the other hand, the cell number for the TA group was still close to the groups treated with LPS only. In other words, treatment with the Phellodendron bark, Scutellaria root, and Coptidis extract mixture led to the reduction of endothelium cell and macrophage in vitro [37–40]. The inclusion of Rhubarb in San Huang Powder seems to reverse this effect, although the mechanism remains unclear. Previous studies have shown that Rhubarb extract played a protective role against radiation-induced brain injury and neuronal cell apoptosis by inhibiting ROS (Reactive Oxygen Species) formation [41]. The endothelial dysfunction and tissue injury caused by oxidative stress at the inflammatory site have been well documented [42–47]. Therefore, this might account for the efficacy for the TA group being better than that for the CA group on histopathological evaluation.Figure 8
The effects of the inclusion of Rhubarb on cell growth. (a) HMEC-1 and (b) RAW264.7 cells were pretreated with 0.5 mg/ml CA or TA for 2 h and then with 0.2μg/ml LPS for 24 h. Relative cell number were calculated and LPS group refer to 100. Through one-tailed test analysis, ∗ and ∗∗ present statistical significance (p<0.05 and p<0.005, resp.) as denoted.
(a)(b)
## 3.1. Content of Reference Standards Present in Rhubarb, Scutellaria Root, Phellodendron Bark, and Coptidis Rhizome
One of the main problems associated with herbal medicine is the high batch-to-batch variability regarding the concentrations of its active components. The content of pure chemical reference standards in herbal products is therefore used as an indicator for quality control and standardization. To characterize the herbal materials, HPLC was used to determine the content of Chrysophanol in Rhubarb, Chrysin in Scutellaria root, and Berberine hydrochloride in Phellodendron bark and Coptidis rhizome. Accordingly, extraction yield of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was 33.1%, 12.9%, 12.0%, and 10.0%, respectively. Total phenolic content (mg/g GAE) of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was 29.4, 3.3, 10.0, and 76.4, respectively. The content of reference standards in Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was measured by HPLC (Figure2). All calibration curves of reference compounds were linear over the concentration range studied (Table 5). A linear interpolation method was used to calculate the percentage by the mass of each reference standard in the analyzed herbal extracts.Figure 2
HPLC separation of reference compounds present in the extracts of herbal components. HPLC traces of (a) Chrysophanol in Rhubarb, (b) Chrysin in Scutellaria root, (c) Berberine chloride in Phellodendron bark, and (d) Berberine chloride in Coptidis rhizome.
(a)(b)(c)(d)Table 5
HPLC calibration curves of reference compounds, including regression equations, coefficients of determination (R2), and calibration ranges.
Reference compoundRegression equationR2Calibration rangeMass percentage (%)Chrysophanol in Rhubarby = 37412x + 8906.30.9990.15–5μg0.47Chrysin in Scutellaria rooty = 1951500x − 963650.9980.1–10μg0.37Berberine chloride in Phellodendron barky = 48857x + 6720750.9991.25–40μg1.06Berberine chloride in Coptidis rhizomey = 42135x + 1519200.9960.5–10μg2.14
## 3.2. Antibacterial Activity Assay
The MBC of herb materials used in this study against a variety of bacteria is shown in Table6. A. baumannii Bouvet and Grimont (ATCC® 19606™), A. baumannii Bouvet and Grimont (ATCC® 17978™), E. meningoseptica BCRC 10677, E. coli DH5α, and Pseudomonas aeruginosa PAO1 are Gram-negative bacteria. In contrast, P. acnes PS023, S. epidermidis TCU-1 BCRC 81267, and S. aureus subsp. aureus TCU-2 BCRC 81268 are Gram-positive bacteria. The bactericidal effect of these four herbal extracts on Gram-positive bacteria is better compared to Gram-negative bacteria. The lowest MBC (∗) for each bacterial strain was distributed evenly among the four different herbs (Table 6). These results suggest that the combination of multiple herb materials could achieve the best bactericidal results.Table 6
The minimal bactericidal concentration (MBC) of the herbal materials used in this study.
Bacterial strainsRhubarb (mg/ml)Scutellaria root (mg/ml)Phellodendron bark (mg/ml)Coptidis rhizome (mg/ml)A. baumannii Bouvet and Grimont ATCC 1960615.6∗31.312531.3A. baumannii Bouvet and Grimont ATCC 1797815.6∗62.5>250125E. meningoseptica BCRC 10677<7.8∗15.612531.3E. coli DH5α12531.3∗>5031.3∗P. acnes PS02315.631.37.8∗15.6P. aeruginosa PAO115.67.815.615.6S. epidermidis TCU-1 BCRC 81267<7.8∗15.6<7.8∗<7.8∗S. aureus subsp. aureus TCU-2 BCRC 8126831.331.315.6<7.8∗∗The lowest concentration to completely kill the specific strain.During the clinical treatment, for example, one gram of “San Huang Powder” (at least 250 mg of each herb material powder) was used to spray over the wound area (12 cm2). If the thickness of the fluid that covers the wound area is 2 mm, the working concentration of each herbal powder on the site of the wound is approximately 104 mg/ml. Thus, considering the synergic effects from different herb materials, the active components in “San Huang Powder” must be sufficient to kill or inhibit bacterial growth on the wounds during treatment. Considering this calculation, it is clear why “San Huang Powder” has been directly applied onto the wound site without sterilization since ancient times. Although the antibacterial activities of Rhubarb, Scutellaria root, and Coptidis rhizome have been reported sporadically [14–17], we were the first to systematically compare them in this study. Moreover, it is common to detect multidrug-resistant A. baumannii in hospitalized patients [18], and the PS023 used in this study is an erythromycin- and clindamycin-resistant strain. Since the herbal extracts were effective against PS023 and two A. baumannii strains, the results also suggest that the herbal extract complex is promising in treating multidrug-resistant bacteria in the future.
## 3.3. Histopathological Evaluation of the Wound Healing Process
No animal was found dead or moribund during the study period. A partial-thickness burn was successfully produced on every animal with superficial second-degree severity, as confirmed by the formation of vesicles, epidermal discontinuity, superficial dermal necrosis, and inflammation.On day 7, epidermal basal cell migration and proliferation were observed under H&E staining, for all groups. As shown in Figures3(a) and 3(b), the epidermal thickness was similar in both the CA and TA groups. During the early phase of wound healing, polymorphonuclear (PMNL) cell infiltration seemed more prominent in both groups. The scalding procedure not only induces localized tissue edema with transepidermal and superficial dermal necrosis but also causes vesicle and secondary pustule formation between the epidermal and dermal layers of skin. Due to the inflammatory stage of early wound healing, fibroblast proliferation and neo-formation of collagen matrix were not observed among all the groups on day 7, as can be seen in Figures 4(a) and 4(b). Results from the IHC staining of VEGF for angiogenesis revealed that, in the CA group, an increase in the expression of VEGF signals was seen compared to TA group (CA) (Figures 5(a) and 5(b)). This implied that the CA group had a better progression of wound healing at the early stage of acute burn injury.Figure 3
Results from H & E staining on different days after the application of herb, 100×. (a) CA on day 7, migrating epithelium (∗) and vesicle (V) formation with PMNL infiltration on wound surface. (b) TA on day 7, migrating epithelium (∗) and pustule (P) and vesicle (V) formation with PMNL infiltration on wound surface. (c) CA on day 14, bridging epithelium with fibroblasts and PMNL infiltration within wound area. (d) TA on day 14, bridging epithelium with fibroblasts and PMNL infiltration within wound area. (e) CA on day 28, migrating epithelium (∗) and an open wound between the edges. (f) TA on day 28, regenerated epithelium had sealed the wound without PMNL infiltration.Figure 4
Results from Masson-trichrome staining on different days after the application of herb, 100×. (a) CA on day 7, no notable collagen deposition within wound area. (b) TA on day 7, no notable collagen deposition within wound area. (c) CA on day 14, the fibroblast had secreted minimal collagen in granulation tissue (∗). (d) TA on day 14, the fibroblast had secreted minimal collagen in granulation tissue (∗). (e) CA on day 28, unbridged epithelium with moderate collagen in granulation tissue (∗). (f) TA on day 28, bridged epithelium with moderate collagen in granulation tissue (∗).Figure 5
Results from IHC staining of VEGF on different days after the application of herb, 200×. (a) CA on day 7, weak VEGF signals from section. (b) TA on day 7, no positive VEGF result from section. (c) CA on day 14, weak VEGF signals from section. (d) TA on day 14, weak VEGF signals from section. (e) CA on day 21, weak VEGF signals from section. (f) TA on day 21, strong VEGF signals from section.The epidermal proliferation and thickness were prominent in both the CA and the TA groups on day 14 (Figures3(c) and 3(d)). PMNL infiltration in the TA group was significantly less than that observed in the CA group, which means the wound healing step of the CA group is still in an inflammatory state. However, the MT staining showed that the collagen bundles between the dermal layers were more prominent in the TA group than in the CA group. Therefore, the proliferation and regeneration steps had started in the TA group, where the new tissue was rebuilt with collagen and extracellular matrix (Figures 4(c) and 4(d)). Hence, at this point of observation, the healing rate at the proliferation stage of acute burn injury was as follows: TA > CA.On day 21, both groups had complete epidermal regeneration without significant differences under H & E staining (Figures3(e) and 3(f)). MT staining also revealed that the collagen bundles over the epidermal-dermal junction and upper dermis were more thickened and compact in the experimental groups compared to the CA group (Figures 4(e) and 4(f)). Moreover, the PMNL infiltration was absent in TA, whereas PMNL remained in the CA group (Figures 3(e) and 3(f)). The newly formed blood vessels can provide oxygen and nutrients to promote wound repair. Since the VEGF signal in the TA group was higher than that in the CA group, angiogenesis can help the tissue heal faster in the TA group than in the CA group (Figure 5). Therefore, the healing rate of acute burn wounds at this stage was as follows: TA > CA.During the process of wound healing, the pigs felt itchy and would actively rub the wound or even try to remove the dressing. The blisters on the burn wound site were quite fragile. Because the particle size of herb materials is enormous and coarse, the friction from the herb particles led to rough wound surfaces in all experimental groups. Furthermore, the dark-colored herb materials were mixed with the exudate to form black scabs on days 14 and 21. The scab made it challenging to observe the healing process of the wound based on appearance (FigureS1). The wounds were superficial second-degree burns, and granulation tissues were observed on day 14 (Figure S1). Therefore, it is less likely to heal with significant scarring and wound contracture [19].In short, a second-degree superficial burn was created successfully in each pig, as evidenced by epidermal and upper dermal necrosis, vesicle formation, and inflammation. In the experimental groups, an early induction of epidermal basal cell migration and dermal endothelial cell angiogenesis was observed, along with the activation of immune response with PMNL infiltration for foreign pathogens on day 7, during the initial inflammatory stage of wound healing. On day 14 of wound healing (proliferation stage), the TA group had more prominent epidermal regeneration and increased dermal fibroblast proliferation and collagen synthesis. Finally, on day 21 of the wound healing process (proliferation and remodeling stage), a significant increase in fibroblast activities, collagen synthesis, and angiogenesis was observed in the TA group, which helped in an improved healing rate of the acute burn wound. The main difference in the composition between the CA and TA groups was the presence of Rhubarb in the latter groups.
## 3.4. Inflammatory Cytokine Immunoassay
The toxicity of each herb material was first determined by MTT assay [20]. However, the deep color of the herb extract led to significant errors. Therefore, their IC50 (half maximal inhibitory concentration) values for HMEC-1 cells were determined by counting cell numbers directly (Figure 6(a)). The in vitro anti-inflammatory activities of the four herb materials were then measured. Because the solubility and cytotoxicity of each herb material in DMSO are different, the maximum possible dose for each component was used for this assay, i.e., 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, and 0.4 mg/mL Coptidis rhizome.Figure 6
Thein vitro assay of the anti-inflammatory activity of herb materials used in this study. (a) HMEC-1 cells were treated with 0.04, 0.12, 0.36, and 1.08 mg/mL herb, including Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome for 24 h. Cell numbers were calculated and shown as mean ± SD. The IC50 (half maximal inhibitory concentration) values of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome for HMEC-1 cell were 0.88 ± 0.05, 0.71 ± 0.06, 2.65 ± 0.59, and 0.44 ± 0.05 mg/mL, respectively. The 0 group is without herb treatment, only DMSO solvent as control. The cell survival rate of control was taken as 100%. (b) HMEC-1 cells were treated with 0.1% DMSO, 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, or 0.4 mg/mL Coptidis rhizome for 1 h and then untreated (DMSO and LPS groups) or treated with 0.2 g/mL LPS for additional 24 h. Relative folds of OD450 nm values were calculated and shown as mean ± SD, taking the value of DMSO group as 1.0. Through one-tailed test analysis, ∗∗denotes statistical significance (p<0.005) compared with DMSO and represents two reproducible results.
(a)(b)Previous reports have indicated that the concentrations of more than ten different inflammatory cytokines, including interleukin-6 (IL-6), interleukin-8 (IL-8), and granulocyte-macrophage colony-stimulating factor (GM-CSF), were significantly higher in the serum of a burn patient than in controls [21]. As shown in Figure 6(b), the treatment with Rhubarb and Phellodendron bark led to a decrease in the levels of inflammatory cytokines, IL-8, and GM-CSF on LPS-induced HMEC-1 cells.The results obtained from the histopathologic evaluation of the tissues suggested that, on day 21, CA had a slower healing rate. The main difference between CA and TA groups was the presence of Rhubarb. These results were in line with a previous report and suggested that Rhubarb may play a vital role in burn wound healing [4].
## 3.5. Reverse Transcription and Quantitative PCR
To further investigate the gene expression difference in the presence or absence of Rhubarb in San Huang Powder during the wound healing process, RT and qPCR experiments were carried out. LPS was first used to induce inflammatory conditions in human endothelial cells, HMEC-1. NF-κB [22–25] and STAT3 [26–29] are proinflammatory factors to form a transcriptional complex which regulates the inflammatory response related to IL-8 gene expression [30–35]. As shown in Figures 7(a)–7(c), the gene expression of NF-κB, STAT3, and IL-8 was significantly inhibited after the treatment of LPS in both CA and TA groups. The decrease of LPS-induced NF-κB and IL-8 expression in the CA group is slightly higher than that in the TA group; however, the reduction of LPS-induced STAT3 expression in the TA group is more elevated than in the CA group. Therefore, there was no significant difference in the anti-inflammatory response between the CA and TA groups.Figure 7
The effects of the inclusion of Rhubarb on inflammatory and lipogenesis-related genes. HMEC-1 cells were pretreated with 0.5 mg/ml CA or TA for 2 h then with 200 ng/ml LPS (a, b). HaCaT were treated with 0.5 mg/ml CA or TA from heat shock for 15 min to incubate for 48 h (c, d). Cellular RNA was isolated and then mRNA expression of (a) NF-κB, (b) STAT3, (c) IL-8, and (d) ADRP were determined by reverse transcription quantitative PCR. β-actin was used as internal control. p∗<0.05and p∗∗<0.005 present statistical significance compared to CA group.
(a)(b)(c)(d)A previous study has shown that knockdown of the gene encoding adipose differentiation-related protein (ADRP) could impair wound healing in mice [36]. Other studies also indicated that lipid signaling molecules could regulate the wound healing process [37–42]. Moreover, lipids might play a role in the proliferation and migration of fibroblasts [43–48]. The heat-shocked keratinocyte model was used to mimic a burn wound. As shown in Figure 7(d), the treatment of CA and TA could lead to an increase of ADRP expression by 21% and 68%, respectively, in heat-shocked keratinocytes compared with a solvent control (DMSO). ADRP expression is associated with lipid storage as a marker of lipid accumulation in cells. The upregulation of ADRP in both groups might play a role in the wound healing process in this study. The inclusion of Rhubarb in San Huang Powder seems to help wound healing in this respect.The cell numbers of HMEC-1 and mouse macrophages (RAW264.7) were also measured after LPS and herb extract treatment. As shown in Figures8(a) and 8(b), the cell number for the CA group decreased by 26% for HMEC-1 and 33% for RAW264.7, respectively, compared to the group treated with LPS only. On the other hand, the cell number for the TA group was still close to the groups treated with LPS only. In other words, treatment with the Phellodendron bark, Scutellaria root, and Coptidis extract mixture led to the reduction of endothelium cell and macrophage in vitro [37–40]. The inclusion of Rhubarb in San Huang Powder seems to reverse this effect, although the mechanism remains unclear. Previous studies have shown that Rhubarb extract played a protective role against radiation-induced brain injury and neuronal cell apoptosis by inhibiting ROS (Reactive Oxygen Species) formation [41]. The endothelial dysfunction and tissue injury caused by oxidative stress at the inflammatory site have been well documented [42–47]. Therefore, this might account for the efficacy for the TA group being better than that for the CA group on histopathological evaluation.Figure 8
The effects of the inclusion of Rhubarb on cell growth. (a) HMEC-1 and (b) RAW264.7 cells were pretreated with 0.5 mg/ml CA or TA for 2 h and then with 0.2μg/ml LPS for 24 h. Relative cell number were calculated and LPS group refer to 100. Through one-tailed test analysis, ∗ and ∗∗ present statistical significance (p<0.05 and p<0.005, resp.) as denoted.
(a)(b)
## 4. Conclusions
Our results provide a basis to understand why “San Huang Powder” without sterilization can be clinically used to treat wounds directly since ancient times. This study also shows the advantages of using multiple herb materials simultaneously on the wound sites to control infection during treatment. Moreover, the herbal extract complex sheds some light on treating multidrug-resistant bacteria in the future.Both groups possessed similarin vitro anti-inflammatory activity. However, the exclusion of Rhubarb resulted in a decrease of endothelium and macrophage cell numbers under an inflammatory state. Therefore, the inclusion of Rhubarb was recommended for the recipe of “San Huang Powder” for healing efficacy of burn wounds. The results obtained in this study also provide the basis to improve the preparation of this traditional medicine. The next generation of this herbal product is probably in the form of sterile burn wound cream.
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*Source: 2900060-2021-10-12.xml* | 2900060-2021-10-12_2900060-2021-10-12.md | 65,803 | Antimicrobial and Immunomodulatory Activity of Herb Extracts Used in Burn Wound Healing: “San Huang Powder” | Jia-Ru Wu; Yu-Chu Lu; Sung-Jen Hung; Jung-Hsing Lin; Kai-Chih Chang; Jhong-Kuei Chen; Wan-Ting Tsai; Tsung-Jung Ho; Hao-Ping Chen | Evidence-Based Complementary and Alternative Medicine
(2021) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2021/2900060 | 2900060-2021-10-12.xml | ---
## Abstract
“San Huang Powder,” a nonsterile milled herb powder, is frequently used to treat burn wounds in traditional Chinese herbal medicine. However, treating a wound with a nonsterile dressing or reagent is not compatible with the current guidelines in modern medicine. Therefore, we investigated the bactericidal and anti-inflammatory activities of four herb extracts used in “San Huang Powder”in vitro. Meanwhile, an in vivo porcine model with superficial second-degree burns was used for the experiments since the size and skin composition of pigs are the closest to that of the human body. The minimal bactericidal concentration (MBC) of the herb extracts was determined. The in vitro assay indicated that Rhubarb and Phellodendron bark extracts decreased the levels of inflammatory cytokines, IL-8, and GM-CSF on LPS-induced HMEC-1 cells. In accordance with this result, the histopathological evaluation results showed that the efficacy of “San Huang Powder” containing both herb materials was much better than the group without Rhubarb. Our results not only provide a basis to understand why “San Huang Powder” has been used to clinically treat wounds without sterilization directly since ancient times but also show the advantages of using multiple herb materials simultaneously on wound sites to prevent infection during treatment. Rhubarb is the recommended ingredient involved in the preparation of “San Huang Powder” to ensure the healing efficacy of burn wounds.
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## Body
## 1. Introduction
“San Huang Powder” is a widely used traditional Chinese herbal medicine. The name of this preparation was first mentioned in an ancient medical book, Beiji Qianjin Yao Fang, published in 652 B.C. It is well known for the treatment of first- and second-degree burn wounds [1–3]. Literally, “San Huang” means that this medicine is made from three different yellow-colored herbs. However, the recipes of “San Huang Powder” vary in different ancient medical books. Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome are the four most frequently used materials to prepare “San Huang Powder.” Moreover, Rhubarb's efficacy in treating burn wounds was recently reported [4, 5]. However, there is no systematic study comparing the efficacy of different “San Huang Powder” recipes for the treatment of burn wounds to date.The milled herbal powder without sterilization is used to treat wounds directly in folk medicine. However, modern medicine physicians constantly criticize this treatment due to concerns relating to infection control. In this study, anin vitro bactericidal activity assay was performed to provide more clarity on this issue. The in vitro immunomodulatory activity of herbal materials was also investigated. Since pig skin structure and function have the closest resemblance to that of humans [6, 7], we used an in vivo porcine burn model in healing burn wounds to examine the efficacy of two different “San Huang Powder” recipes. The results obtained in this study provide the scientific basis for its clinical use and insight for preparation of next generation “San Huang Powder” extract.
## 2. Materials and Methods
The Institutional Animal Care and Use Committee, National Laboratory Animal Center, Taiwan, ROC, approved all experimental animal procedures (Permission number: NLAC (TN)-107-M-009R1).
### 2.1. Materials
Berberine hydrochloride was purchased from TCI Co., Ltd. (Tokyo, Japan). Chrysin was obtained from Acros Organics (Geel, Belgium). Chrysophanol was purchased from Sigma-Aldrich (St. Louis, MI, USA). Vascular endothelial growth factor (VEGF) was bought from B & D Systems (Minneapolis, MN, USA). Rhubarb (dried stem and root fromRheum palmatum LINN) was a product of Da Rong Co., Ltd. (Tao Yuan City, Taiwan) (batch number: DK1070932). Scutellaria root (dried root from Scutellaria baicalensis Georgi) was the product of He Kang Chinese Medicine Co., Ltd. (New Taipei City, Taiwan) (batch number: 0704). Phellodendron bark (dried bark from Phellodendron amurense Ruprecht) was the product of Jin Rong Co., Ltd. (New Taipei City, Taiwan) (batch number: AG80303). Coptidis rhizome (dried rhizome of Coptis chinensis Franch) was the product of Fu Ji Co., Ltd. (Kaohsiung City, Taiwan) (batch number: FG0013). Further identification analysis of these plant-based materials was done by HPLC, as described below. The raw herb materials were ground into fine powder using a coffee grinder (Model: ECG3003S, Electrolux, New Taipei City, Taiwan). The milled powder was further sieved using ultrafine 100 mesh stainless steel filter and stored in a dry cabinet. The recipes of two different types of “San Huang Powder” are listed in Table 1.Table 1
The recipes of two different types of “San Huang Powder” used in this study.
GroupIngredientControl (CA)Scutellaria root : Phellodendron bark : Coptidis rhizome = 1 : 1 : 1Test article (TA)Rhubarb : Scutellaria root : Phellodendron bark : Coptidis rhizome = 1 : 1 : 1 : 1
### 2.2. Determination of Reference Standard Content in Rhubarb, Scutellaria Root, Phellodendron Bark, and Coptidis Rhizome by HPLC
All experiments were performed using a Hitachi L-7000 HPLC system (Hitachi, Ltd., Tokyo, Japan), equipped with a L-7100 quaternary gradient pump and a L-7450 photo diode array detector. Hitachi HSM software was used for machine control and data collection and processing. The analytical column used was theμBondapak™ C18 Column, 125 Å, 10 μm, 3.9 × 300 mm (Waters Corporation, Milford, Massachusetts, USA).A 1 g sample of each dried herb material was ground into fine powder, using a coffee grinder (Model: ECG3003S, Electrolux, New Taipei City, Taiwan). The herbs were then extracted twice with the following solvents: Rhubarb: 10 mL methanol, Scutellaria root: 10 mL of ethanol, Phellodendron bark: 10 mL of methanol, and Coptidis rhizome: 10 mL of 70% ethanol. One gram of grounded solids were weighed and dissolved in 10 ml of solvent. After ultrasonicating for 30 minutes at 25°C, extracts were transferred to a new glass vial using disposable glass Pasteur pipettes. Another 10 ml of solvent was then added and ultrasonicated for another 30 minutes at 25°C. Undissolved particles were removed by centrifugation at 2500 ×g for 10 minutes at 25°C and filtered through a 0.22μm syringe filter. The final volume of the extract was adjusted to 20 ml. To calculate the extraction yield (mass of extract/mass of dry matter), 1 ml extracts were dried under vacuum at 25°C overnight in a Savant SpeedVac Vacuum Concentrator (Thermo Fisher Scientific Inc., Waltham, Massachusetts, USA). Folin-Ciocalteu method was used to determine the total phenolic content in the extracts [8]. Total phenolic content of the extract samples was expressed as gallic acid equivalent (GAE) milligrams per gram of the extract.The methanol extract of Rhubarb was separated using a gradient elution of solvent A (10% CH3CN, containing 0.1% H3PO4) and solvent B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min [9]. The UV detection wavelength was 254 nm. The ethanol extract of Scutellaria root was separated using a gradient elution of solvent A (10% CH3CN, containing 0.1% H3PO4) and solvent B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min. The UV detection wavelength was 280 nm. The methanol extracts of Phellodendron bark were separated using a gradient elution of solvents A (10% CH3CN, containing 0.1% H3PO4) and B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min. The UV detection wavelength was 260 nm. The ethanol extract of Coptidis rhizome was separated using a gradient elution of solvents A (0.1% KH2PO4 buffer) and B (100% CH3CN) at a flow rate of 1 ml/min [10]. The UV detection wavelength was 260 nm. The HPLC elution programs for the four herbs are presented in Table 2.Table 2
HPLC elution programs for Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome.
RhubarbScutellaria rootPhellodendron barkCoptidis rhizomeTime (min)Eluent (B%)Time (min)Eluent (B%)Time (min)Eluent (B%)Time (min)Eluent (B%)0–10350–2150–5200–5010–2535–1002–615–305–2520–305–160–8025–301006–2030–4025–3530–10016–2180–10020–2240–5035–4010021–30100
### 2.3. Determination of the Minimal Bactericidal Concentration (MBC) of the Herbal Materials
The minimal bactericidal concentration (MBC) of the herbal materials used in this study to kill the following,Acinetobacter baumannii Bouvet and Grimont (ATCC® 19606™), Acinetobacter baumannii Bouvet and Grimont (ATCC® 17978™), Elizabethkingia meningoseptica BCRC 10677, Escherichia coli DH5α, Pseudomonas aeruginosa PAO1, Propionibacterium acnes PS023, Staphylococcus epidermidis TCU-1 BCRC 81267, and Staphylococcus aureus subsp. aureus TCU-2 BCRC 81268, was determined. P. acnes PS023 is an erythromycin- and clindamycin-resistant clinical isolate. One gram of each herb material was extracted with 4 mL methanol at room temperature, overnight. The herbal methanol extracts (500 µL each) were dried using a Savant SpeedVac Vacuum Concentrator and dissolved in 25 µL DMSO. The DMSO stock of each herb extract was further diluted (10x) with the Rein-forced Clostridial Medium for P. acnes PS023 and Mueller Hinton broth for the other bacteria. The adjusted herb extract was serially diluted into multiple wells on a 96-well plate to obtain a gradient. After overnight growth at 37°C, the wells which were clear were evaluated for colony-forming units per mL (CFU/mL) on agar plates. Only P. acnes PS023 grow in anaerobic chamber using a mixture of 10% CO2, 10% H2, and 80% N2.
### 2.4. Animal Experiments
Three female Lee-Sung pigs were purchased from the Department of Animal Science and Technology, National Taiwan University, Taiwan. The pigs were 4.5 months old (average weight: 18.0 kg) and had similar body shapes. Each animal was maintained as described previously [7]. The Institutional Animal Care and Use Committee, National Laboratory Animal Center, Taiwan, ROC, approved all experimental animal procedures (Permission number: NLAC(TN)-107-M-009R1). General anesthesia was maintained by isoflurane via inhalation. Intramuscular Zoletil (5 mg/kg) and Xylazine (2.2 mg/kg) and subcutaneous Atropine (0.05 mg/kg) were used for sedation. Subcutaneous injection of Buprenorphine (0.05 mg/kg) for pain relief and oral administration of Enrofloxacin (5 mg/kg) were performed for infection control during the operation. Meanwhile, isoflurane inhalation and Lidocaine (2%) spray anesthesia were administered (Figure 1). A second-degree burn wound was made with the help of a burn device (Model YLS-5Q, Yi Yan Tech. Co., Ltd., Shandong, China), consisting of a 4 cm diameter heating probe. The setting of the burn device for contact pressure, temperature, and time was 500 g, at 90°C for 20 sec, respectively. The procedure was performed under aseptic conditions to create uniform dermal scalding wounds on the three adult minimum disease female Lee-Sung pigs. The burn wounds were created on six different locations on the dorsal side of each animal. Sterile gauze was used to keep the wounds clean. Two different “San Huang Powder” compositions, test article (TA) and control (CA), were directly applied to the wound surface, and dressings were replaced daily (Table 3). In traditional Chinese medicine, the physician directly sprays “San Huang Powder” over the wound site. About one gram of “San Huang Powder” was used over the wound area (12 cm2). Oral cephalexin (20 mg/kg) and meloxicam (0.4 mg/kg) were administered twice daily during the first seven days. No apparent abnormalities were seen during the experimental process until the sacrifice. Euthanasia of all animals was performed one day after completion of the study by using pentobarbital (120 mg/kg). Once euthanasia was performed, the collection of tissues was initiated immediately.Figure 1
Burn wounds were covered with sterile gauze dressing after treatment with CA, and TA.Table 3
Treatment groups and duration.
GroupTreatmentStudy period (biopsy samples taken)7 days14 days21 daysCA1 g/day333TA1 g/day333The wound sites were photographed on days 7, 14, and 21 after the burn injury. The dermal wound tissue was sampled using a 6 mm biopsy punch (Lot no.: 17L13, Integra LifeSciences, Plainsboro, NJ, USA) and preserved in 10% neutral-buffered formalin on days 7, 14, and 21 after the burn injury. After fixation, the tissues were trimmed, embedded, and divided into 5 mm thick sections and placed on glass slides (Immuno Coated slide, MUTO, Japan). These paraffin-embedded sections were treated with hematoxylin and eosin (H & E), Masson-trichrome (MT) stains, and immunohistochemistry (IHC) stain, as reported previously [7].
### 2.5. Inflammatory Cytokine Immunoassay
HMEC-1 cells were cultured, as described previously [11]. For the cell viability test, 1.0 × 105 cells were seeded into a 24-well plate per well then treated with Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome [12, 13]. The working concentrations of each herb material were 0.04, 0.12, 0.36, and 1.08 mg/mL. After incubation with HMEC-1 cells for 24 hours, each herb material’s IC50 (half maximal inhibitory concentration) values were determined by counting of HMEC-1 number. Relative survival rates were shown as mean ± SD, taking the value of the control group as 100%. Through one-tailed test analysis, ∗ denotes statistical significance (p<0.05) compared with control and represents two reproducible results.Cells were treated with 0.1% DMSO, 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, or 0.4 mg/mL Coptidis rhizome for 1 h and then untreated (DMSO and LPS groups) or treated with 0.2 g/mL LPS for an additional 24 h. The amount of human inflammatory cytokines in the cell suspension was determined using a human inflammatory cytokine multiplex ELISA kit (Arigo Biolaboratories, Hsinchu, Taiwan). All steps were performed as per the protocol provided by the manufacturer.
### 2.6. Reverse Transcription and Quantitative PCR
For HMEC-1, cells were pretreated with 0.5 mg/ml CA or 0.5 mg/ml TA for 2 hours and then treated with 0.2 g/ml LPS for another 24 hours. For the heat shock treatment of HaCaT, cells were incubated in a serum-free medium with 0.5 mg/ml CA or 0.5 mg/ml TA at 42°C for 15 min and then maintained at 37°C for another 48 hours. RNA was isolated from HMEC-1 and HaCaT cells using a purification kit (Protech Technology Enterprise, Taipei, Taiwan). Reverse transcription was performed using an RT kit (Protech Technology Enterprise, Taipei, Taiwan). Analysis of target gene expression by quantitative PCR was normalized withβ-Actin. Primer sequences are listed in Table 4.Table 4
Primer sequences for RT-qPCR of target genes in this study.
Target genePrimer sequenceADRPF: GGCTAGACAGGATTGAGGAGAGR: TCACTGCCCCTTTGGTCTTGIL-8F: CTCTCTTGGCAGCCTTCCTGAR: CCCTCTGCACCCAGTTTTCCTTNF-κBF: CCTGGATGACTCTTGGGAAAR: TCAGCCAGCTGTTTCATGTCSTAT3F: CATATGCGGCCAGCAAAGAAR: ATACCTGCTCTGAAGAAACT
### 2.7. Cell Number Analysis
For HMEC-1 and RAW264.7, cells were pretreated with 0.5 mg/ml CA or 0.5 mg/ml TA for 2 hours and then treated with 0.2μg/ml LPS for another 24 hours. At the end of treatment, cells would be detached from culture plates using 0.25% trypsin EDTA solution (Thermo Fisher Scientific, Hualien, Taiwan) and then cell numbers could be counted.
## 2.1. Materials
Berberine hydrochloride was purchased from TCI Co., Ltd. (Tokyo, Japan). Chrysin was obtained from Acros Organics (Geel, Belgium). Chrysophanol was purchased from Sigma-Aldrich (St. Louis, MI, USA). Vascular endothelial growth factor (VEGF) was bought from B & D Systems (Minneapolis, MN, USA). Rhubarb (dried stem and root fromRheum palmatum LINN) was a product of Da Rong Co., Ltd. (Tao Yuan City, Taiwan) (batch number: DK1070932). Scutellaria root (dried root from Scutellaria baicalensis Georgi) was the product of He Kang Chinese Medicine Co., Ltd. (New Taipei City, Taiwan) (batch number: 0704). Phellodendron bark (dried bark from Phellodendron amurense Ruprecht) was the product of Jin Rong Co., Ltd. (New Taipei City, Taiwan) (batch number: AG80303). Coptidis rhizome (dried rhizome of Coptis chinensis Franch) was the product of Fu Ji Co., Ltd. (Kaohsiung City, Taiwan) (batch number: FG0013). Further identification analysis of these plant-based materials was done by HPLC, as described below. The raw herb materials were ground into fine powder using a coffee grinder (Model: ECG3003S, Electrolux, New Taipei City, Taiwan). The milled powder was further sieved using ultrafine 100 mesh stainless steel filter and stored in a dry cabinet. The recipes of two different types of “San Huang Powder” are listed in Table 1.Table 1
The recipes of two different types of “San Huang Powder” used in this study.
GroupIngredientControl (CA)Scutellaria root : Phellodendron bark : Coptidis rhizome = 1 : 1 : 1Test article (TA)Rhubarb : Scutellaria root : Phellodendron bark : Coptidis rhizome = 1 : 1 : 1 : 1
## 2.2. Determination of Reference Standard Content in Rhubarb, Scutellaria Root, Phellodendron Bark, and Coptidis Rhizome by HPLC
All experiments were performed using a Hitachi L-7000 HPLC system (Hitachi, Ltd., Tokyo, Japan), equipped with a L-7100 quaternary gradient pump and a L-7450 photo diode array detector. Hitachi HSM software was used for machine control and data collection and processing. The analytical column used was theμBondapak™ C18 Column, 125 Å, 10 μm, 3.9 × 300 mm (Waters Corporation, Milford, Massachusetts, USA).A 1 g sample of each dried herb material was ground into fine powder, using a coffee grinder (Model: ECG3003S, Electrolux, New Taipei City, Taiwan). The herbs were then extracted twice with the following solvents: Rhubarb: 10 mL methanol, Scutellaria root: 10 mL of ethanol, Phellodendron bark: 10 mL of methanol, and Coptidis rhizome: 10 mL of 70% ethanol. One gram of grounded solids were weighed and dissolved in 10 ml of solvent. After ultrasonicating for 30 minutes at 25°C, extracts were transferred to a new glass vial using disposable glass Pasteur pipettes. Another 10 ml of solvent was then added and ultrasonicated for another 30 minutes at 25°C. Undissolved particles were removed by centrifugation at 2500 ×g for 10 minutes at 25°C and filtered through a 0.22μm syringe filter. The final volume of the extract was adjusted to 20 ml. To calculate the extraction yield (mass of extract/mass of dry matter), 1 ml extracts were dried under vacuum at 25°C overnight in a Savant SpeedVac Vacuum Concentrator (Thermo Fisher Scientific Inc., Waltham, Massachusetts, USA). Folin-Ciocalteu method was used to determine the total phenolic content in the extracts [8]. Total phenolic content of the extract samples was expressed as gallic acid equivalent (GAE) milligrams per gram of the extract.The methanol extract of Rhubarb was separated using a gradient elution of solvent A (10% CH3CN, containing 0.1% H3PO4) and solvent B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min [9]. The UV detection wavelength was 254 nm. The ethanol extract of Scutellaria root was separated using a gradient elution of solvent A (10% CH3CN, containing 0.1% H3PO4) and solvent B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min. The UV detection wavelength was 280 nm. The methanol extracts of Phellodendron bark were separated using a gradient elution of solvents A (10% CH3CN, containing 0.1% H3PO4) and B (90% CH3CN, containing 0.1% H3PO4) at a flow rate of 1 ml/min. The UV detection wavelength was 260 nm. The ethanol extract of Coptidis rhizome was separated using a gradient elution of solvents A (0.1% KH2PO4 buffer) and B (100% CH3CN) at a flow rate of 1 ml/min [10]. The UV detection wavelength was 260 nm. The HPLC elution programs for the four herbs are presented in Table 2.Table 2
HPLC elution programs for Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome.
RhubarbScutellaria rootPhellodendron barkCoptidis rhizomeTime (min)Eluent (B%)Time (min)Eluent (B%)Time (min)Eluent (B%)Time (min)Eluent (B%)0–10350–2150–5200–5010–2535–1002–615–305–2520–305–160–8025–301006–2030–4025–3530–10016–2180–10020–2240–5035–4010021–30100
## 2.3. Determination of the Minimal Bactericidal Concentration (MBC) of the Herbal Materials
The minimal bactericidal concentration (MBC) of the herbal materials used in this study to kill the following,Acinetobacter baumannii Bouvet and Grimont (ATCC® 19606™), Acinetobacter baumannii Bouvet and Grimont (ATCC® 17978™), Elizabethkingia meningoseptica BCRC 10677, Escherichia coli DH5α, Pseudomonas aeruginosa PAO1, Propionibacterium acnes PS023, Staphylococcus epidermidis TCU-1 BCRC 81267, and Staphylococcus aureus subsp. aureus TCU-2 BCRC 81268, was determined. P. acnes PS023 is an erythromycin- and clindamycin-resistant clinical isolate. One gram of each herb material was extracted with 4 mL methanol at room temperature, overnight. The herbal methanol extracts (500 µL each) were dried using a Savant SpeedVac Vacuum Concentrator and dissolved in 25 µL DMSO. The DMSO stock of each herb extract was further diluted (10x) with the Rein-forced Clostridial Medium for P. acnes PS023 and Mueller Hinton broth for the other bacteria. The adjusted herb extract was serially diluted into multiple wells on a 96-well plate to obtain a gradient. After overnight growth at 37°C, the wells which were clear were evaluated for colony-forming units per mL (CFU/mL) on agar plates. Only P. acnes PS023 grow in anaerobic chamber using a mixture of 10% CO2, 10% H2, and 80% N2.
## 2.4. Animal Experiments
Three female Lee-Sung pigs were purchased from the Department of Animal Science and Technology, National Taiwan University, Taiwan. The pigs were 4.5 months old (average weight: 18.0 kg) and had similar body shapes. Each animal was maintained as described previously [7]. The Institutional Animal Care and Use Committee, National Laboratory Animal Center, Taiwan, ROC, approved all experimental animal procedures (Permission number: NLAC(TN)-107-M-009R1). General anesthesia was maintained by isoflurane via inhalation. Intramuscular Zoletil (5 mg/kg) and Xylazine (2.2 mg/kg) and subcutaneous Atropine (0.05 mg/kg) were used for sedation. Subcutaneous injection of Buprenorphine (0.05 mg/kg) for pain relief and oral administration of Enrofloxacin (5 mg/kg) were performed for infection control during the operation. Meanwhile, isoflurane inhalation and Lidocaine (2%) spray anesthesia were administered (Figure 1). A second-degree burn wound was made with the help of a burn device (Model YLS-5Q, Yi Yan Tech. Co., Ltd., Shandong, China), consisting of a 4 cm diameter heating probe. The setting of the burn device for contact pressure, temperature, and time was 500 g, at 90°C for 20 sec, respectively. The procedure was performed under aseptic conditions to create uniform dermal scalding wounds on the three adult minimum disease female Lee-Sung pigs. The burn wounds were created on six different locations on the dorsal side of each animal. Sterile gauze was used to keep the wounds clean. Two different “San Huang Powder” compositions, test article (TA) and control (CA), were directly applied to the wound surface, and dressings were replaced daily (Table 3). In traditional Chinese medicine, the physician directly sprays “San Huang Powder” over the wound site. About one gram of “San Huang Powder” was used over the wound area (12 cm2). Oral cephalexin (20 mg/kg) and meloxicam (0.4 mg/kg) were administered twice daily during the first seven days. No apparent abnormalities were seen during the experimental process until the sacrifice. Euthanasia of all animals was performed one day after completion of the study by using pentobarbital (120 mg/kg). Once euthanasia was performed, the collection of tissues was initiated immediately.Figure 1
Burn wounds were covered with sterile gauze dressing after treatment with CA, and TA.Table 3
Treatment groups and duration.
GroupTreatmentStudy period (biopsy samples taken)7 days14 days21 daysCA1 g/day333TA1 g/day333The wound sites were photographed on days 7, 14, and 21 after the burn injury. The dermal wound tissue was sampled using a 6 mm biopsy punch (Lot no.: 17L13, Integra LifeSciences, Plainsboro, NJ, USA) and preserved in 10% neutral-buffered formalin on days 7, 14, and 21 after the burn injury. After fixation, the tissues were trimmed, embedded, and divided into 5 mm thick sections and placed on glass slides (Immuno Coated slide, MUTO, Japan). These paraffin-embedded sections were treated with hematoxylin and eosin (H & E), Masson-trichrome (MT) stains, and immunohistochemistry (IHC) stain, as reported previously [7].
## 2.5. Inflammatory Cytokine Immunoassay
HMEC-1 cells were cultured, as described previously [11]. For the cell viability test, 1.0 × 105 cells were seeded into a 24-well plate per well then treated with Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome [12, 13]. The working concentrations of each herb material were 0.04, 0.12, 0.36, and 1.08 mg/mL. After incubation with HMEC-1 cells for 24 hours, each herb material’s IC50 (half maximal inhibitory concentration) values were determined by counting of HMEC-1 number. Relative survival rates were shown as mean ± SD, taking the value of the control group as 100%. Through one-tailed test analysis, ∗ denotes statistical significance (p<0.05) compared with control and represents two reproducible results.Cells were treated with 0.1% DMSO, 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, or 0.4 mg/mL Coptidis rhizome for 1 h and then untreated (DMSO and LPS groups) or treated with 0.2 g/mL LPS for an additional 24 h. The amount of human inflammatory cytokines in the cell suspension was determined using a human inflammatory cytokine multiplex ELISA kit (Arigo Biolaboratories, Hsinchu, Taiwan). All steps were performed as per the protocol provided by the manufacturer.
## 2.6. Reverse Transcription and Quantitative PCR
For HMEC-1, cells were pretreated with 0.5 mg/ml CA or 0.5 mg/ml TA for 2 hours and then treated with 0.2 g/ml LPS for another 24 hours. For the heat shock treatment of HaCaT, cells were incubated in a serum-free medium with 0.5 mg/ml CA or 0.5 mg/ml TA at 42°C for 15 min and then maintained at 37°C for another 48 hours. RNA was isolated from HMEC-1 and HaCaT cells using a purification kit (Protech Technology Enterprise, Taipei, Taiwan). Reverse transcription was performed using an RT kit (Protech Technology Enterprise, Taipei, Taiwan). Analysis of target gene expression by quantitative PCR was normalized withβ-Actin. Primer sequences are listed in Table 4.Table 4
Primer sequences for RT-qPCR of target genes in this study.
Target genePrimer sequenceADRPF: GGCTAGACAGGATTGAGGAGAGR: TCACTGCCCCTTTGGTCTTGIL-8F: CTCTCTTGGCAGCCTTCCTGAR: CCCTCTGCACCCAGTTTTCCTTNF-κBF: CCTGGATGACTCTTGGGAAAR: TCAGCCAGCTGTTTCATGTCSTAT3F: CATATGCGGCCAGCAAAGAAR: ATACCTGCTCTGAAGAAACT
## 2.7. Cell Number Analysis
For HMEC-1 and RAW264.7, cells were pretreated with 0.5 mg/ml CA or 0.5 mg/ml TA for 2 hours and then treated with 0.2μg/ml LPS for another 24 hours. At the end of treatment, cells would be detached from culture plates using 0.25% trypsin EDTA solution (Thermo Fisher Scientific, Hualien, Taiwan) and then cell numbers could be counted.
## 3. Results and Discussion
### 3.1. Content of Reference Standards Present in Rhubarb, Scutellaria Root, Phellodendron Bark, and Coptidis Rhizome
One of the main problems associated with herbal medicine is the high batch-to-batch variability regarding the concentrations of its active components. The content of pure chemical reference standards in herbal products is therefore used as an indicator for quality control and standardization. To characterize the herbal materials, HPLC was used to determine the content of Chrysophanol in Rhubarb, Chrysin in Scutellaria root, and Berberine hydrochloride in Phellodendron bark and Coptidis rhizome. Accordingly, extraction yield of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was 33.1%, 12.9%, 12.0%, and 10.0%, respectively. Total phenolic content (mg/g GAE) of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was 29.4, 3.3, 10.0, and 76.4, respectively. The content of reference standards in Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was measured by HPLC (Figure2). All calibration curves of reference compounds were linear over the concentration range studied (Table 5). A linear interpolation method was used to calculate the percentage by the mass of each reference standard in the analyzed herbal extracts.Figure 2
HPLC separation of reference compounds present in the extracts of herbal components. HPLC traces of (a) Chrysophanol in Rhubarb, (b) Chrysin in Scutellaria root, (c) Berberine chloride in Phellodendron bark, and (d) Berberine chloride in Coptidis rhizome.
(a)(b)(c)(d)Table 5
HPLC calibration curves of reference compounds, including regression equations, coefficients of determination (R2), and calibration ranges.
Reference compoundRegression equationR2Calibration rangeMass percentage (%)Chrysophanol in Rhubarby = 37412x + 8906.30.9990.15–5μg0.47Chrysin in Scutellaria rooty = 1951500x − 963650.9980.1–10μg0.37Berberine chloride in Phellodendron barky = 48857x + 6720750.9991.25–40μg1.06Berberine chloride in Coptidis rhizomey = 42135x + 1519200.9960.5–10μg2.14
### 3.2. Antibacterial Activity Assay
The MBC of herb materials used in this study against a variety of bacteria is shown in Table6. A. baumannii Bouvet and Grimont (ATCC® 19606™), A. baumannii Bouvet and Grimont (ATCC® 17978™), E. meningoseptica BCRC 10677, E. coli DH5α, and Pseudomonas aeruginosa PAO1 are Gram-negative bacteria. In contrast, P. acnes PS023, S. epidermidis TCU-1 BCRC 81267, and S. aureus subsp. aureus TCU-2 BCRC 81268 are Gram-positive bacteria. The bactericidal effect of these four herbal extracts on Gram-positive bacteria is better compared to Gram-negative bacteria. The lowest MBC (∗) for each bacterial strain was distributed evenly among the four different herbs (Table 6). These results suggest that the combination of multiple herb materials could achieve the best bactericidal results.Table 6
The minimal bactericidal concentration (MBC) of the herbal materials used in this study.
Bacterial strainsRhubarb (mg/ml)Scutellaria root (mg/ml)Phellodendron bark (mg/ml)Coptidis rhizome (mg/ml)A. baumannii Bouvet and Grimont ATCC 1960615.6∗31.312531.3A. baumannii Bouvet and Grimont ATCC 1797815.6∗62.5>250125E. meningoseptica BCRC 10677<7.8∗15.612531.3E. coli DH5α12531.3∗>5031.3∗P. acnes PS02315.631.37.8∗15.6P. aeruginosa PAO115.67.815.615.6S. epidermidis TCU-1 BCRC 81267<7.8∗15.6<7.8∗<7.8∗S. aureus subsp. aureus TCU-2 BCRC 8126831.331.315.6<7.8∗∗The lowest concentration to completely kill the specific strain.During the clinical treatment, for example, one gram of “San Huang Powder” (at least 250 mg of each herb material powder) was used to spray over the wound area (12 cm2). If the thickness of the fluid that covers the wound area is 2 mm, the working concentration of each herbal powder on the site of the wound is approximately 104 mg/ml. Thus, considering the synergic effects from different herb materials, the active components in “San Huang Powder” must be sufficient to kill or inhibit bacterial growth on the wounds during treatment. Considering this calculation, it is clear why “San Huang Powder” has been directly applied onto the wound site without sterilization since ancient times. Although the antibacterial activities of Rhubarb, Scutellaria root, and Coptidis rhizome have been reported sporadically [14–17], we were the first to systematically compare them in this study. Moreover, it is common to detect multidrug-resistant A. baumannii in hospitalized patients [18], and the PS023 used in this study is an erythromycin- and clindamycin-resistant strain. Since the herbal extracts were effective against PS023 and two A. baumannii strains, the results also suggest that the herbal extract complex is promising in treating multidrug-resistant bacteria in the future.
### 3.3. Histopathological Evaluation of the Wound Healing Process
No animal was found dead or moribund during the study period. A partial-thickness burn was successfully produced on every animal with superficial second-degree severity, as confirmed by the formation of vesicles, epidermal discontinuity, superficial dermal necrosis, and inflammation.On day 7, epidermal basal cell migration and proliferation were observed under H&E staining, for all groups. As shown in Figures3(a) and 3(b), the epidermal thickness was similar in both the CA and TA groups. During the early phase of wound healing, polymorphonuclear (PMNL) cell infiltration seemed more prominent in both groups. The scalding procedure not only induces localized tissue edema with transepidermal and superficial dermal necrosis but also causes vesicle and secondary pustule formation between the epidermal and dermal layers of skin. Due to the inflammatory stage of early wound healing, fibroblast proliferation and neo-formation of collagen matrix were not observed among all the groups on day 7, as can be seen in Figures 4(a) and 4(b). Results from the IHC staining of VEGF for angiogenesis revealed that, in the CA group, an increase in the expression of VEGF signals was seen compared to TA group (CA) (Figures 5(a) and 5(b)). This implied that the CA group had a better progression of wound healing at the early stage of acute burn injury.Figure 3
Results from H & E staining on different days after the application of herb, 100×. (a) CA on day 7, migrating epithelium (∗) and vesicle (V) formation with PMNL infiltration on wound surface. (b) TA on day 7, migrating epithelium (∗) and pustule (P) and vesicle (V) formation with PMNL infiltration on wound surface. (c) CA on day 14, bridging epithelium with fibroblasts and PMNL infiltration within wound area. (d) TA on day 14, bridging epithelium with fibroblasts and PMNL infiltration within wound area. (e) CA on day 28, migrating epithelium (∗) and an open wound between the edges. (f) TA on day 28, regenerated epithelium had sealed the wound without PMNL infiltration.Figure 4
Results from Masson-trichrome staining on different days after the application of herb, 100×. (a) CA on day 7, no notable collagen deposition within wound area. (b) TA on day 7, no notable collagen deposition within wound area. (c) CA on day 14, the fibroblast had secreted minimal collagen in granulation tissue (∗). (d) TA on day 14, the fibroblast had secreted minimal collagen in granulation tissue (∗). (e) CA on day 28, unbridged epithelium with moderate collagen in granulation tissue (∗). (f) TA on day 28, bridged epithelium with moderate collagen in granulation tissue (∗).Figure 5
Results from IHC staining of VEGF on different days after the application of herb, 200×. (a) CA on day 7, weak VEGF signals from section. (b) TA on day 7, no positive VEGF result from section. (c) CA on day 14, weak VEGF signals from section. (d) TA on day 14, weak VEGF signals from section. (e) CA on day 21, weak VEGF signals from section. (f) TA on day 21, strong VEGF signals from section.The epidermal proliferation and thickness were prominent in both the CA and the TA groups on day 14 (Figures3(c) and 3(d)). PMNL infiltration in the TA group was significantly less than that observed in the CA group, which means the wound healing step of the CA group is still in an inflammatory state. However, the MT staining showed that the collagen bundles between the dermal layers were more prominent in the TA group than in the CA group. Therefore, the proliferation and regeneration steps had started in the TA group, where the new tissue was rebuilt with collagen and extracellular matrix (Figures 4(c) and 4(d)). Hence, at this point of observation, the healing rate at the proliferation stage of acute burn injury was as follows: TA > CA.On day 21, both groups had complete epidermal regeneration without significant differences under H & E staining (Figures3(e) and 3(f)). MT staining also revealed that the collagen bundles over the epidermal-dermal junction and upper dermis were more thickened and compact in the experimental groups compared to the CA group (Figures 4(e) and 4(f)). Moreover, the PMNL infiltration was absent in TA, whereas PMNL remained in the CA group (Figures 3(e) and 3(f)). The newly formed blood vessels can provide oxygen and nutrients to promote wound repair. Since the VEGF signal in the TA group was higher than that in the CA group, angiogenesis can help the tissue heal faster in the TA group than in the CA group (Figure 5). Therefore, the healing rate of acute burn wounds at this stage was as follows: TA > CA.During the process of wound healing, the pigs felt itchy and would actively rub the wound or even try to remove the dressing. The blisters on the burn wound site were quite fragile. Because the particle size of herb materials is enormous and coarse, the friction from the herb particles led to rough wound surfaces in all experimental groups. Furthermore, the dark-colored herb materials were mixed with the exudate to form black scabs on days 14 and 21. The scab made it challenging to observe the healing process of the wound based on appearance (FigureS1). The wounds were superficial second-degree burns, and granulation tissues were observed on day 14 (Figure S1). Therefore, it is less likely to heal with significant scarring and wound contracture [19].In short, a second-degree superficial burn was created successfully in each pig, as evidenced by epidermal and upper dermal necrosis, vesicle formation, and inflammation. In the experimental groups, an early induction of epidermal basal cell migration and dermal endothelial cell angiogenesis was observed, along with the activation of immune response with PMNL infiltration for foreign pathogens on day 7, during the initial inflammatory stage of wound healing. On day 14 of wound healing (proliferation stage), the TA group had more prominent epidermal regeneration and increased dermal fibroblast proliferation and collagen synthesis. Finally, on day 21 of the wound healing process (proliferation and remodeling stage), a significant increase in fibroblast activities, collagen synthesis, and angiogenesis was observed in the TA group, which helped in an improved healing rate of the acute burn wound. The main difference in the composition between the CA and TA groups was the presence of Rhubarb in the latter groups.
### 3.4. Inflammatory Cytokine Immunoassay
The toxicity of each herb material was first determined by MTT assay [20]. However, the deep color of the herb extract led to significant errors. Therefore, their IC50 (half maximal inhibitory concentration) values for HMEC-1 cells were determined by counting cell numbers directly (Figure 6(a)). The in vitro anti-inflammatory activities of the four herb materials were then measured. Because the solubility and cytotoxicity of each herb material in DMSO are different, the maximum possible dose for each component was used for this assay, i.e., 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, and 0.4 mg/mL Coptidis rhizome.Figure 6
Thein vitro assay of the anti-inflammatory activity of herb materials used in this study. (a) HMEC-1 cells were treated with 0.04, 0.12, 0.36, and 1.08 mg/mL herb, including Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome for 24 h. Cell numbers were calculated and shown as mean ± SD. The IC50 (half maximal inhibitory concentration) values of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome for HMEC-1 cell were 0.88 ± 0.05, 0.71 ± 0.06, 2.65 ± 0.59, and 0.44 ± 0.05 mg/mL, respectively. The 0 group is without herb treatment, only DMSO solvent as control. The cell survival rate of control was taken as 100%. (b) HMEC-1 cells were treated with 0.1% DMSO, 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, or 0.4 mg/mL Coptidis rhizome for 1 h and then untreated (DMSO and LPS groups) or treated with 0.2 g/mL LPS for additional 24 h. Relative folds of OD450 nm values were calculated and shown as mean ± SD, taking the value of DMSO group as 1.0. Through one-tailed test analysis, ∗∗denotes statistical significance (p<0.005) compared with DMSO and represents two reproducible results.
(a)(b)Previous reports have indicated that the concentrations of more than ten different inflammatory cytokines, including interleukin-6 (IL-6), interleukin-8 (IL-8), and granulocyte-macrophage colony-stimulating factor (GM-CSF), were significantly higher in the serum of a burn patient than in controls [21]. As shown in Figure 6(b), the treatment with Rhubarb and Phellodendron bark led to a decrease in the levels of inflammatory cytokines, IL-8, and GM-CSF on LPS-induced HMEC-1 cells.The results obtained from the histopathologic evaluation of the tissues suggested that, on day 21, CA had a slower healing rate. The main difference between CA and TA groups was the presence of Rhubarb. These results were in line with a previous report and suggested that Rhubarb may play a vital role in burn wound healing [4].
### 3.5. Reverse Transcription and Quantitative PCR
To further investigate the gene expression difference in the presence or absence of Rhubarb in San Huang Powder during the wound healing process, RT and qPCR experiments were carried out. LPS was first used to induce inflammatory conditions in human endothelial cells, HMEC-1. NF-κB [22–25] and STAT3 [26–29] are proinflammatory factors to form a transcriptional complex which regulates the inflammatory response related to IL-8 gene expression [30–35]. As shown in Figures 7(a)–7(c), the gene expression of NF-κB, STAT3, and IL-8 was significantly inhibited after the treatment of LPS in both CA and TA groups. The decrease of LPS-induced NF-κB and IL-8 expression in the CA group is slightly higher than that in the TA group; however, the reduction of LPS-induced STAT3 expression in the TA group is more elevated than in the CA group. Therefore, there was no significant difference in the anti-inflammatory response between the CA and TA groups.Figure 7
The effects of the inclusion of Rhubarb on inflammatory and lipogenesis-related genes. HMEC-1 cells were pretreated with 0.5 mg/ml CA or TA for 2 h then with 200 ng/ml LPS (a, b). HaCaT were treated with 0.5 mg/ml CA or TA from heat shock for 15 min to incubate for 48 h (c, d). Cellular RNA was isolated and then mRNA expression of (a) NF-κB, (b) STAT3, (c) IL-8, and (d) ADRP were determined by reverse transcription quantitative PCR. β-actin was used as internal control. p∗<0.05and p∗∗<0.005 present statistical significance compared to CA group.
(a)(b)(c)(d)A previous study has shown that knockdown of the gene encoding adipose differentiation-related protein (ADRP) could impair wound healing in mice [36]. Other studies also indicated that lipid signaling molecules could regulate the wound healing process [37–42]. Moreover, lipids might play a role in the proliferation and migration of fibroblasts [43–48]. The heat-shocked keratinocyte model was used to mimic a burn wound. As shown in Figure 7(d), the treatment of CA and TA could lead to an increase of ADRP expression by 21% and 68%, respectively, in heat-shocked keratinocytes compared with a solvent control (DMSO). ADRP expression is associated with lipid storage as a marker of lipid accumulation in cells. The upregulation of ADRP in both groups might play a role in the wound healing process in this study. The inclusion of Rhubarb in San Huang Powder seems to help wound healing in this respect.The cell numbers of HMEC-1 and mouse macrophages (RAW264.7) were also measured after LPS and herb extract treatment. As shown in Figures8(a) and 8(b), the cell number for the CA group decreased by 26% for HMEC-1 and 33% for RAW264.7, respectively, compared to the group treated with LPS only. On the other hand, the cell number for the TA group was still close to the groups treated with LPS only. In other words, treatment with the Phellodendron bark, Scutellaria root, and Coptidis extract mixture led to the reduction of endothelium cell and macrophage in vitro [37–40]. The inclusion of Rhubarb in San Huang Powder seems to reverse this effect, although the mechanism remains unclear. Previous studies have shown that Rhubarb extract played a protective role against radiation-induced brain injury and neuronal cell apoptosis by inhibiting ROS (Reactive Oxygen Species) formation [41]. The endothelial dysfunction and tissue injury caused by oxidative stress at the inflammatory site have been well documented [42–47]. Therefore, this might account for the efficacy for the TA group being better than that for the CA group on histopathological evaluation.Figure 8
The effects of the inclusion of Rhubarb on cell growth. (a) HMEC-1 and (b) RAW264.7 cells were pretreated with 0.5 mg/ml CA or TA for 2 h and then with 0.2μg/ml LPS for 24 h. Relative cell number were calculated and LPS group refer to 100. Through one-tailed test analysis, ∗ and ∗∗ present statistical significance (p<0.05 and p<0.005, resp.) as denoted.
(a)(b)
## 3.1. Content of Reference Standards Present in Rhubarb, Scutellaria Root, Phellodendron Bark, and Coptidis Rhizome
One of the main problems associated with herbal medicine is the high batch-to-batch variability regarding the concentrations of its active components. The content of pure chemical reference standards in herbal products is therefore used as an indicator for quality control and standardization. To characterize the herbal materials, HPLC was used to determine the content of Chrysophanol in Rhubarb, Chrysin in Scutellaria root, and Berberine hydrochloride in Phellodendron bark and Coptidis rhizome. Accordingly, extraction yield of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was 33.1%, 12.9%, 12.0%, and 10.0%, respectively. Total phenolic content (mg/g GAE) of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was 29.4, 3.3, 10.0, and 76.4, respectively. The content of reference standards in Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome was measured by HPLC (Figure2). All calibration curves of reference compounds were linear over the concentration range studied (Table 5). A linear interpolation method was used to calculate the percentage by the mass of each reference standard in the analyzed herbal extracts.Figure 2
HPLC separation of reference compounds present in the extracts of herbal components. HPLC traces of (a) Chrysophanol in Rhubarb, (b) Chrysin in Scutellaria root, (c) Berberine chloride in Phellodendron bark, and (d) Berberine chloride in Coptidis rhizome.
(a)(b)(c)(d)Table 5
HPLC calibration curves of reference compounds, including regression equations, coefficients of determination (R2), and calibration ranges.
Reference compoundRegression equationR2Calibration rangeMass percentage (%)Chrysophanol in Rhubarby = 37412x + 8906.30.9990.15–5μg0.47Chrysin in Scutellaria rooty = 1951500x − 963650.9980.1–10μg0.37Berberine chloride in Phellodendron barky = 48857x + 6720750.9991.25–40μg1.06Berberine chloride in Coptidis rhizomey = 42135x + 1519200.9960.5–10μg2.14
## 3.2. Antibacterial Activity Assay
The MBC of herb materials used in this study against a variety of bacteria is shown in Table6. A. baumannii Bouvet and Grimont (ATCC® 19606™), A. baumannii Bouvet and Grimont (ATCC® 17978™), E. meningoseptica BCRC 10677, E. coli DH5α, and Pseudomonas aeruginosa PAO1 are Gram-negative bacteria. In contrast, P. acnes PS023, S. epidermidis TCU-1 BCRC 81267, and S. aureus subsp. aureus TCU-2 BCRC 81268 are Gram-positive bacteria. The bactericidal effect of these four herbal extracts on Gram-positive bacteria is better compared to Gram-negative bacteria. The lowest MBC (∗) for each bacterial strain was distributed evenly among the four different herbs (Table 6). These results suggest that the combination of multiple herb materials could achieve the best bactericidal results.Table 6
The minimal bactericidal concentration (MBC) of the herbal materials used in this study.
Bacterial strainsRhubarb (mg/ml)Scutellaria root (mg/ml)Phellodendron bark (mg/ml)Coptidis rhizome (mg/ml)A. baumannii Bouvet and Grimont ATCC 1960615.6∗31.312531.3A. baumannii Bouvet and Grimont ATCC 1797815.6∗62.5>250125E. meningoseptica BCRC 10677<7.8∗15.612531.3E. coli DH5α12531.3∗>5031.3∗P. acnes PS02315.631.37.8∗15.6P. aeruginosa PAO115.67.815.615.6S. epidermidis TCU-1 BCRC 81267<7.8∗15.6<7.8∗<7.8∗S. aureus subsp. aureus TCU-2 BCRC 8126831.331.315.6<7.8∗∗The lowest concentration to completely kill the specific strain.During the clinical treatment, for example, one gram of “San Huang Powder” (at least 250 mg of each herb material powder) was used to spray over the wound area (12 cm2). If the thickness of the fluid that covers the wound area is 2 mm, the working concentration of each herbal powder on the site of the wound is approximately 104 mg/ml. Thus, considering the synergic effects from different herb materials, the active components in “San Huang Powder” must be sufficient to kill or inhibit bacterial growth on the wounds during treatment. Considering this calculation, it is clear why “San Huang Powder” has been directly applied onto the wound site without sterilization since ancient times. Although the antibacterial activities of Rhubarb, Scutellaria root, and Coptidis rhizome have been reported sporadically [14–17], we were the first to systematically compare them in this study. Moreover, it is common to detect multidrug-resistant A. baumannii in hospitalized patients [18], and the PS023 used in this study is an erythromycin- and clindamycin-resistant strain. Since the herbal extracts were effective against PS023 and two A. baumannii strains, the results also suggest that the herbal extract complex is promising in treating multidrug-resistant bacteria in the future.
## 3.3. Histopathological Evaluation of the Wound Healing Process
No animal was found dead or moribund during the study period. A partial-thickness burn was successfully produced on every animal with superficial second-degree severity, as confirmed by the formation of vesicles, epidermal discontinuity, superficial dermal necrosis, and inflammation.On day 7, epidermal basal cell migration and proliferation were observed under H&E staining, for all groups. As shown in Figures3(a) and 3(b), the epidermal thickness was similar in both the CA and TA groups. During the early phase of wound healing, polymorphonuclear (PMNL) cell infiltration seemed more prominent in both groups. The scalding procedure not only induces localized tissue edema with transepidermal and superficial dermal necrosis but also causes vesicle and secondary pustule formation between the epidermal and dermal layers of skin. Due to the inflammatory stage of early wound healing, fibroblast proliferation and neo-formation of collagen matrix were not observed among all the groups on day 7, as can be seen in Figures 4(a) and 4(b). Results from the IHC staining of VEGF for angiogenesis revealed that, in the CA group, an increase in the expression of VEGF signals was seen compared to TA group (CA) (Figures 5(a) and 5(b)). This implied that the CA group had a better progression of wound healing at the early stage of acute burn injury.Figure 3
Results from H & E staining on different days after the application of herb, 100×. (a) CA on day 7, migrating epithelium (∗) and vesicle (V) formation with PMNL infiltration on wound surface. (b) TA on day 7, migrating epithelium (∗) and pustule (P) and vesicle (V) formation with PMNL infiltration on wound surface. (c) CA on day 14, bridging epithelium with fibroblasts and PMNL infiltration within wound area. (d) TA on day 14, bridging epithelium with fibroblasts and PMNL infiltration within wound area. (e) CA on day 28, migrating epithelium (∗) and an open wound between the edges. (f) TA on day 28, regenerated epithelium had sealed the wound without PMNL infiltration.Figure 4
Results from Masson-trichrome staining on different days after the application of herb, 100×. (a) CA on day 7, no notable collagen deposition within wound area. (b) TA on day 7, no notable collagen deposition within wound area. (c) CA on day 14, the fibroblast had secreted minimal collagen in granulation tissue (∗). (d) TA on day 14, the fibroblast had secreted minimal collagen in granulation tissue (∗). (e) CA on day 28, unbridged epithelium with moderate collagen in granulation tissue (∗). (f) TA on day 28, bridged epithelium with moderate collagen in granulation tissue (∗).Figure 5
Results from IHC staining of VEGF on different days after the application of herb, 200×. (a) CA on day 7, weak VEGF signals from section. (b) TA on day 7, no positive VEGF result from section. (c) CA on day 14, weak VEGF signals from section. (d) TA on day 14, weak VEGF signals from section. (e) CA on day 21, weak VEGF signals from section. (f) TA on day 21, strong VEGF signals from section.The epidermal proliferation and thickness were prominent in both the CA and the TA groups on day 14 (Figures3(c) and 3(d)). PMNL infiltration in the TA group was significantly less than that observed in the CA group, which means the wound healing step of the CA group is still in an inflammatory state. However, the MT staining showed that the collagen bundles between the dermal layers were more prominent in the TA group than in the CA group. Therefore, the proliferation and regeneration steps had started in the TA group, where the new tissue was rebuilt with collagen and extracellular matrix (Figures 4(c) and 4(d)). Hence, at this point of observation, the healing rate at the proliferation stage of acute burn injury was as follows: TA > CA.On day 21, both groups had complete epidermal regeneration without significant differences under H & E staining (Figures3(e) and 3(f)). MT staining also revealed that the collagen bundles over the epidermal-dermal junction and upper dermis were more thickened and compact in the experimental groups compared to the CA group (Figures 4(e) and 4(f)). Moreover, the PMNL infiltration was absent in TA, whereas PMNL remained in the CA group (Figures 3(e) and 3(f)). The newly formed blood vessels can provide oxygen and nutrients to promote wound repair. Since the VEGF signal in the TA group was higher than that in the CA group, angiogenesis can help the tissue heal faster in the TA group than in the CA group (Figure 5). Therefore, the healing rate of acute burn wounds at this stage was as follows: TA > CA.During the process of wound healing, the pigs felt itchy and would actively rub the wound or even try to remove the dressing. The blisters on the burn wound site were quite fragile. Because the particle size of herb materials is enormous and coarse, the friction from the herb particles led to rough wound surfaces in all experimental groups. Furthermore, the dark-colored herb materials were mixed with the exudate to form black scabs on days 14 and 21. The scab made it challenging to observe the healing process of the wound based on appearance (FigureS1). The wounds were superficial second-degree burns, and granulation tissues were observed on day 14 (Figure S1). Therefore, it is less likely to heal with significant scarring and wound contracture [19].In short, a second-degree superficial burn was created successfully in each pig, as evidenced by epidermal and upper dermal necrosis, vesicle formation, and inflammation. In the experimental groups, an early induction of epidermal basal cell migration and dermal endothelial cell angiogenesis was observed, along with the activation of immune response with PMNL infiltration for foreign pathogens on day 7, during the initial inflammatory stage of wound healing. On day 14 of wound healing (proliferation stage), the TA group had more prominent epidermal regeneration and increased dermal fibroblast proliferation and collagen synthesis. Finally, on day 21 of the wound healing process (proliferation and remodeling stage), a significant increase in fibroblast activities, collagen synthesis, and angiogenesis was observed in the TA group, which helped in an improved healing rate of the acute burn wound. The main difference in the composition between the CA and TA groups was the presence of Rhubarb in the latter groups.
## 3.4. Inflammatory Cytokine Immunoassay
The toxicity of each herb material was first determined by MTT assay [20]. However, the deep color of the herb extract led to significant errors. Therefore, their IC50 (half maximal inhibitory concentration) values for HMEC-1 cells were determined by counting cell numbers directly (Figure 6(a)). The in vitro anti-inflammatory activities of the four herb materials were then measured. Because the solubility and cytotoxicity of each herb material in DMSO are different, the maximum possible dose for each component was used for this assay, i.e., 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, and 0.4 mg/mL Coptidis rhizome.Figure 6
Thein vitro assay of the anti-inflammatory activity of herb materials used in this study. (a) HMEC-1 cells were treated with 0.04, 0.12, 0.36, and 1.08 mg/mL herb, including Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome for 24 h. Cell numbers were calculated and shown as mean ± SD. The IC50 (half maximal inhibitory concentration) values of Rhubarb, Scutellaria root, Phellodendron bark, and Coptidis rhizome for HMEC-1 cell were 0.88 ± 0.05, 0.71 ± 0.06, 2.65 ± 0.59, and 0.44 ± 0.05 mg/mL, respectively. The 0 group is without herb treatment, only DMSO solvent as control. The cell survival rate of control was taken as 100%. (b) HMEC-1 cells were treated with 0.1% DMSO, 0.8 mg/mL Rhubarb, 0.7 mg/mL Scutellaria root, 2.6 mg/mL Phellodendron bark, or 0.4 mg/mL Coptidis rhizome for 1 h and then untreated (DMSO and LPS groups) or treated with 0.2 g/mL LPS for additional 24 h. Relative folds of OD450 nm values were calculated and shown as mean ± SD, taking the value of DMSO group as 1.0. Through one-tailed test analysis, ∗∗denotes statistical significance (p<0.005) compared with DMSO and represents two reproducible results.
(a)(b)Previous reports have indicated that the concentrations of more than ten different inflammatory cytokines, including interleukin-6 (IL-6), interleukin-8 (IL-8), and granulocyte-macrophage colony-stimulating factor (GM-CSF), were significantly higher in the serum of a burn patient than in controls [21]. As shown in Figure 6(b), the treatment with Rhubarb and Phellodendron bark led to a decrease in the levels of inflammatory cytokines, IL-8, and GM-CSF on LPS-induced HMEC-1 cells.The results obtained from the histopathologic evaluation of the tissues suggested that, on day 21, CA had a slower healing rate. The main difference between CA and TA groups was the presence of Rhubarb. These results were in line with a previous report and suggested that Rhubarb may play a vital role in burn wound healing [4].
## 3.5. Reverse Transcription and Quantitative PCR
To further investigate the gene expression difference in the presence or absence of Rhubarb in San Huang Powder during the wound healing process, RT and qPCR experiments were carried out. LPS was first used to induce inflammatory conditions in human endothelial cells, HMEC-1. NF-κB [22–25] and STAT3 [26–29] are proinflammatory factors to form a transcriptional complex which regulates the inflammatory response related to IL-8 gene expression [30–35]. As shown in Figures 7(a)–7(c), the gene expression of NF-κB, STAT3, and IL-8 was significantly inhibited after the treatment of LPS in both CA and TA groups. The decrease of LPS-induced NF-κB and IL-8 expression in the CA group is slightly higher than that in the TA group; however, the reduction of LPS-induced STAT3 expression in the TA group is more elevated than in the CA group. Therefore, there was no significant difference in the anti-inflammatory response between the CA and TA groups.Figure 7
The effects of the inclusion of Rhubarb on inflammatory and lipogenesis-related genes. HMEC-1 cells were pretreated with 0.5 mg/ml CA or TA for 2 h then with 200 ng/ml LPS (a, b). HaCaT were treated with 0.5 mg/ml CA or TA from heat shock for 15 min to incubate for 48 h (c, d). Cellular RNA was isolated and then mRNA expression of (a) NF-κB, (b) STAT3, (c) IL-8, and (d) ADRP were determined by reverse transcription quantitative PCR. β-actin was used as internal control. p∗<0.05and p∗∗<0.005 present statistical significance compared to CA group.
(a)(b)(c)(d)A previous study has shown that knockdown of the gene encoding adipose differentiation-related protein (ADRP) could impair wound healing in mice [36]. Other studies also indicated that lipid signaling molecules could regulate the wound healing process [37–42]. Moreover, lipids might play a role in the proliferation and migration of fibroblasts [43–48]. The heat-shocked keratinocyte model was used to mimic a burn wound. As shown in Figure 7(d), the treatment of CA and TA could lead to an increase of ADRP expression by 21% and 68%, respectively, in heat-shocked keratinocytes compared with a solvent control (DMSO). ADRP expression is associated with lipid storage as a marker of lipid accumulation in cells. The upregulation of ADRP in both groups might play a role in the wound healing process in this study. The inclusion of Rhubarb in San Huang Powder seems to help wound healing in this respect.The cell numbers of HMEC-1 and mouse macrophages (RAW264.7) were also measured after LPS and herb extract treatment. As shown in Figures8(a) and 8(b), the cell number for the CA group decreased by 26% for HMEC-1 and 33% for RAW264.7, respectively, compared to the group treated with LPS only. On the other hand, the cell number for the TA group was still close to the groups treated with LPS only. In other words, treatment with the Phellodendron bark, Scutellaria root, and Coptidis extract mixture led to the reduction of endothelium cell and macrophage in vitro [37–40]. The inclusion of Rhubarb in San Huang Powder seems to reverse this effect, although the mechanism remains unclear. Previous studies have shown that Rhubarb extract played a protective role against radiation-induced brain injury and neuronal cell apoptosis by inhibiting ROS (Reactive Oxygen Species) formation [41]. The endothelial dysfunction and tissue injury caused by oxidative stress at the inflammatory site have been well documented [42–47]. Therefore, this might account for the efficacy for the TA group being better than that for the CA group on histopathological evaluation.Figure 8
The effects of the inclusion of Rhubarb on cell growth. (a) HMEC-1 and (b) RAW264.7 cells were pretreated with 0.5 mg/ml CA or TA for 2 h and then with 0.2μg/ml LPS for 24 h. Relative cell number were calculated and LPS group refer to 100. Through one-tailed test analysis, ∗ and ∗∗ present statistical significance (p<0.05 and p<0.005, resp.) as denoted.
(a)(b)
## 4. Conclusions
Our results provide a basis to understand why “San Huang Powder” without sterilization can be clinically used to treat wounds directly since ancient times. This study also shows the advantages of using multiple herb materials simultaneously on the wound sites to control infection during treatment. Moreover, the herbal extract complex sheds some light on treating multidrug-resistant bacteria in the future.Both groups possessed similarin vitro anti-inflammatory activity. However, the exclusion of Rhubarb resulted in a decrease of endothelium and macrophage cell numbers under an inflammatory state. Therefore, the inclusion of Rhubarb was recommended for the recipe of “San Huang Powder” for healing efficacy of burn wounds. The results obtained in this study also provide the basis to improve the preparation of this traditional medicine. The next generation of this herbal product is probably in the form of sterile burn wound cream.
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*Source: 2900060-2021-10-12.xml* | 2021 |
# Accumulation and Distribution of Natural Gas Reservoir in Volcanic Active Area: A Case Study of the Cretaceous Yingcheng Formation in the Dehui Fault Depression, Songliao Basin, NE China
**Authors:** Fancheng Zeng; Bo Liu; Changmin Zhang; Guoyi Zhang; Jin Gao; Junjie Liu; Mehdi Ostadhassan
**Journal:** Geofluids
(2021)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2021/2900224
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## Abstract
Tight gas sandstone and volcanic gas reservoirs have received global attention in the energy arena for further exploration and exploitation attempts. Considering the Yingcheng Formation of Dehui fault depression in the Songliao Basin as an example, this study focused on the accumulation and distribution of natural gas reservoirs in volcanic area in a fault depression basin. Volcanic activities occurred in the Yingcheng Formation, which is distributed centrally in the northwest of the study area. During the sedimentation of the Yingcheng Formation, fan-delta, lacustrine, and nearshore subaqueous fan facies were deposited. The source rocks of the Yingcheng Formation have high abundance of organic matter mainly in type III at high-overmature stages, indicating favorable conditions for gas production. The porosity of volcanic reservoir is 3.0%-14.8%, the permeability is 0.0004 mD-2.52 mD, and the pore types are mainly secondary dissolved pores and fractures. Besides, the porosity of the tight sandstone reservoir is 0.5%-11.2%, and the permeability is 0.0008 mD-3.17 mD. The pore types are mainly interparticle pores, with a small proportion of intraparticle pores and microfractures. The intrusion of late volcanic magma provided sufficient heat for the thermal maturity progression of organic matter in Yingcheng Formation and promoted the generation of natural gas in large quantities. Volcanic rocks formed at the early and middle stages of volcanic activities occupied the sedimentary space and hindered the development of sedimentary sand bodies to a certain extent. However, volcanic rocks can become the seal to promote the formation of tight sandstone gas traps. Comparing tight sandstone reservoirs with volcanic ones, the latter are less affected by compaction; thus, their petrophysical properties do not vary much with depth, showing more homogeneous characteristics. The pyroclastic rocks influenced by volcanic activity and the secondary pores formed by dissolution in the later stages also provide reservoir space for gas accumulation. Ultimately, the tight sandstone and volcanic rocks in the study area form a complex gas reservoir system, which can become a reference for exploration and exploitation of natural gas in other petroliferous fault depressions that are affected by volcanisms.
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## Body
## 1. Introduction
IEA [1] estimates that global tight gas sandstone resources are roughly 209.6×1012m3. Additionally, exploration and development of tight gas sandstone reservoirs has supported the driving force for increasing global natural gas production in recent years [2]. In China, huge tight sandstone gas reservoirs exist in major oil-bearing basins, including the Tarim, Ordos, and Songliao Basins [3, 4]. As of 2016, gas production from tight sandstone reservoirs has reached 330×108m3, accounting for one-quarter of China’s annual natural gas production [3]. In this regard, volcanic gas reservoirs have also been found sporadically where tight sandstone gas reservoirs are abundant, such as the Lower Cretaceous in the Songliao Basin, the Jurassic in the Hailaer Basin, and the Upper Paleozoic of the Ordos Basin. The tight gas sandstone reservoirs and volcanic gas reservoirs in the volcanically active areas together constitute a complex gas accumulation system which requires further investigation [5–8].In basins located on the eastern China, volcano-sedimentary sequences have been widely developed since the Late Mesozoic [7]. During volcanism, a large number of igneous formations were formed, accompanied by various clastic deposits from igneous materials and volcanic lacustrine deposits during the intercalation period, forming an interactive sedimentary sequence [9]. In addition to the creation of these volcanic reservoirs, volcanic activity also has had an impact on the accumulation of natural gas in tight sandstones regionally [10]. Moreover, the influence of volcanisms on the basin sedimentation manifests itself in the following ways: first, volcanic activity can be used as a regional provenance, providing supply for the basin sedimentation [11, 12]. However, such volcanic activities in the island arc belt not only would change the composition of the supply in the sedimentary system but also play a role in blocking the distribution of the sedimentary system, alter topography, promote the formation or migration of the basin depocenter, develop around it, and thus form a new sedimentary system. Secondly, volcanic activity is also an important event that impacts the basin accommodation. Due to rapid accumulation of volcanic eruptions in some areas, the basin is affected by the thermal subsidence, and somehow, this was accelerated regionally, causing the total water volume to decrease. Conversely, in other areas of the depression, the influence of volcanic activities has been weak; therefore, the change of accommodative space is not significant [13]. This means the overall accommodative space for sediment load varies regionally throughout the basin. In addition, volcanic activities are often accompanied by large-scale hydrothermal events where high temperature as well as high pressure hydrothermal flux upwashes and enters the strata. As a result, this hydrothermal fluid contains rich soluble ions and will have persistent effects of detrital (mineral), which makes its diagenetic intensity to be strong [14]. In addition to the impact of volcanic activities that explained how would influence sedimentation in the basin, syndepositional volcanism controls the development of reservoirs mainly by providing soluble components and promoting the formation of fractures [15]. This has happened via the dissolution of chemically unstable soluble pyroclastic components that were preserved in the adjacent sedimentary sand bodies within the pores during the middle to late burial stages. Furthermore, during the periods of volcanic activity, the influx of a large amount of magma flew into the sedimentary sequence that resulted in the brittle rupture of consolidated sandstone to form microfractures, which increased the reservoir space and permeability of the reservoir [16, 17].In such events, volcanic ash would be beneficial to the enrichment and preservation of organic matter [18, 19] and promotes the conversion of organic matter to hydrocarbons [20–22]. These were some positive impacts of volcanic activities on various components of the petroleum system; however, its destructive effects on hydrocarbon accumulation cannot be neglected either. For example, volcanic activities can disrupt oil and gas accumulation significantly by creating channels or associated faults to damage the integrity of the trap and creating seepages for the accumulated hydrocarbons to escape the reservoir [17]. In addition, the heat source provided by volcanic activity also causes dehydration of minerals containing crystalline water in the adjacent sediments to recrystallize, which would fill the pores and fractures, reducing connectivity and deteriorating reservoir petrophysical properties.Songliao Basin is a large petroliferous basin developed on the basement of the Upper Paleozoic metamorphic rock series. During the rift period, there were intense tectonic movements and frequent volcanic activities. However, the combination of volcanism and sedimentation created good conditions for the formation of oil and gas reservoirs [23, 24]. In recent years, several large tight natural gas reservoirs have been discovered in the Songliao Basin [25], while some are associated with the volcanic rocks of the basin [6, 26, 27]. In the Dehui fault depression that is the subject of this study, both major tight sandstone and volcanic gas reservoirs are found in the Cretaceous strata, with great potential for resources and are good exploration prospects.In this study, tight gas sandstone and volcanic gas reservoir influenced by the volcanic activity of the Yingcheng Formation in the Dehui fault depression of the southern Songliao Basin has been assessed. By systematically sampling the source rocks, volcanic rocks, and tight sandstones in the study area and analyzing and examining them for total organic carbon (TOC) content, vitrinite reflectance (Ro), and reservoir physical property (porosity and permeability), the geochemical characteristics of the source rocks and the petrophysical properties of the reservoir rock including the volcanic and tight sandstone are understood. The goal of this study is to analyze the effects of volcanic activity in the area on the accumulation of natural gas. Furthermore, we comprehensively investigated the complexity of the petroleum system that is formed in the volcano-sedimentary sequence, to provide reference for the exploration and prospect evaluation in this petroliferous basin for future developments.
## 2. Geologic Setting
### 2.1. Location and Stratigraphy
The Dehui fault depression is located in the southeast uplift of the Songliao Basin (Figure1(a); [5]). It is a sedimentary fault depression with synrift and thermal subsidence double-layered structure developed on the basement of Upper Paleozoic metamorphic rock series, covering an area of 4053 km2 (Figure 1(b)). The fault depression generally presents an NNE trending double fault-controlled graben, which is cut by NNE trending faults, forming a structural pattern of horst-graben-steps. It can be further divided into seven secondary structural units, including the Nong’an Graben, Huajia Subdepression, Baojia Subdepression, Nong’an’nan Subdepression, Helong Subdepression, Lanjia Subdepression, and Longwang Subdepression (Figure 1(c)).Figure 1
(a) Geographic location of the Songliao Basin. (b) Location of Dehui Depression in the Southern Songliao Basin. (c) Tectonic units of the Dehui Depression. (d) Generalized Mesozoic-Cenozoic stratigraphy of the Dehui depression, showing the formation thickness, lithology, and stage of tectonic evaluation.
(a)(b)(c)(d)Since the Mesozoic, the fault depression has undergone several tectonic activities of subsidence and uplift, and the Mesozoic and Cenozoic strata with a thickness of more than 5000 m have been deposited [23]. The strata developed from bottom to top in this area are the Carboniferous-Permian basement, the lower Cretaceous Huoshiling Formation (K1hs), Shahezi Formation (K1sh), Yingcheng Formation (K1yc), Denglouku Formation (K1d), Quantou Formation (K1q), the upper Cretaceous Qingshankou Formation (K2qn), Yaojia Formation (K2y), Nenjiang Formation (K2n), and Quaternary (Figure 1(d)), among which the Yingcheng Formation is the target layer of this study.
### 2.2. Volcanic Activities
During the period of the Yingcheng Formation deposition, numerous volcanic activities happened, leading to the creation of faults in Dehui fault depression [28]. By employing the superposition relationship between volcanic rock mass from 3D seismic data and zircon dating, three periods of volcanic activities in this area were recognized, which first increased and then gradually weakened. During the initial stages of volcanic activity, eruptions mainly occurred at the edge of the depression and near the faults which controlled the depression. Large volcanic groups developed, and later, sedimentary strata covered the volcanic rocks [5]. Drilling through these volcanic rocks confirmed mushroom-like structures with obvious volcanic channels dated 118 Ma, which marks the onset of the Yingcheng Formation. The middle stage of the volcanic activity is dominated by eruption of pyroclastic facies and magma flows along the volcanic channels and faults that were formed during the first stage of volcanism forming a large area of pyroclastic shield. This period is dated back to 115 Ma, which represents the middle stage of the creation of the Yingcheng Formation. Finally, in the late period of volcanic activity, volcanic intrusions were formed, and because of its weakened energy, the magma could not reach the surface and only cut through the strata. This took place about 103 Ma, which coincides with the depositional period of the Denglouku Formation (Figure 2; [28]).Figure 2
The seismic profile shows the volcanic activity of the K1yc in the Dehui Depression; location of the profile is shown in Figure 1 (modified from [28]).
### 2.3. Sedimentary Facies
During the deposition of the Yingcheng Formation, the Songliao Basin was tectonically active, and a number of faults were developed. The Yingcheng Formation is divided into two members while the first member is strongly affected by volcanism, and a large set of volcanic formations are developed around the Dehui fault depression [5]. At the margins of the fault depression, a set of fan-delta and lacustrine facies were deposited, and a mixed sequence of volcanic and clastic sedimentary strata was formed. The sedimentary facies in the study area are mainly fan-deltaic, lacustrine, and nearshore subaqueous fan (Figure 3). The fan-delta is widely developed in the eastern and western margins of the depression, while the braided river delta plain is dominant in the south, and the lacustrine facies center is located in the northeast of the depression. During the sedimentation process, the supply of sediment was hindered by the influence of multiple volcanic activities, which limited the range and thickness of sand bodies that were deposited in the northeast.Figure 3
The sedimentary facies map of the K1yc in the Dehui Depression shows the distribution of volcanic and sedimentary rocks.
### 2.4. Petroleum System
Three sets of petroleum source-reservoir-seal systems are identified in the study area [5, 25]. In the K1yc, K1sh, and K1h, thick organic-rich mudstones with a high thermal maturity have been proven to be the effective source for the gas. Meanwhile, fine sandstone, siltstone, conglomerate, and volcanic rocks formed during volcanic activity are widely spread in the K1yc, K1sh, and K1h and act as the reservoir for natural gas accumulation. Thick mudstone developed in the K2d is almost distributed in the entire southern Songliao Basin and could serve as the regional seal, and mudstone layers in each formation mentioned above can serve as the local caprocks [7].
## 2.1. Location and Stratigraphy
The Dehui fault depression is located in the southeast uplift of the Songliao Basin (Figure1(a); [5]). It is a sedimentary fault depression with synrift and thermal subsidence double-layered structure developed on the basement of Upper Paleozoic metamorphic rock series, covering an area of 4053 km2 (Figure 1(b)). The fault depression generally presents an NNE trending double fault-controlled graben, which is cut by NNE trending faults, forming a structural pattern of horst-graben-steps. It can be further divided into seven secondary structural units, including the Nong’an Graben, Huajia Subdepression, Baojia Subdepression, Nong’an’nan Subdepression, Helong Subdepression, Lanjia Subdepression, and Longwang Subdepression (Figure 1(c)).Figure 1
(a) Geographic location of the Songliao Basin. (b) Location of Dehui Depression in the Southern Songliao Basin. (c) Tectonic units of the Dehui Depression. (d) Generalized Mesozoic-Cenozoic stratigraphy of the Dehui depression, showing the formation thickness, lithology, and stage of tectonic evaluation.
(a)(b)(c)(d)Since the Mesozoic, the fault depression has undergone several tectonic activities of subsidence and uplift, and the Mesozoic and Cenozoic strata with a thickness of more than 5000 m have been deposited [23]. The strata developed from bottom to top in this area are the Carboniferous-Permian basement, the lower Cretaceous Huoshiling Formation (K1hs), Shahezi Formation (K1sh), Yingcheng Formation (K1yc), Denglouku Formation (K1d), Quantou Formation (K1q), the upper Cretaceous Qingshankou Formation (K2qn), Yaojia Formation (K2y), Nenjiang Formation (K2n), and Quaternary (Figure 1(d)), among which the Yingcheng Formation is the target layer of this study.
## 2.2. Volcanic Activities
During the period of the Yingcheng Formation deposition, numerous volcanic activities happened, leading to the creation of faults in Dehui fault depression [28]. By employing the superposition relationship between volcanic rock mass from 3D seismic data and zircon dating, three periods of volcanic activities in this area were recognized, which first increased and then gradually weakened. During the initial stages of volcanic activity, eruptions mainly occurred at the edge of the depression and near the faults which controlled the depression. Large volcanic groups developed, and later, sedimentary strata covered the volcanic rocks [5]. Drilling through these volcanic rocks confirmed mushroom-like structures with obvious volcanic channels dated 118 Ma, which marks the onset of the Yingcheng Formation. The middle stage of the volcanic activity is dominated by eruption of pyroclastic facies and magma flows along the volcanic channels and faults that were formed during the first stage of volcanism forming a large area of pyroclastic shield. This period is dated back to 115 Ma, which represents the middle stage of the creation of the Yingcheng Formation. Finally, in the late period of volcanic activity, volcanic intrusions were formed, and because of its weakened energy, the magma could not reach the surface and only cut through the strata. This took place about 103 Ma, which coincides with the depositional period of the Denglouku Formation (Figure 2; [28]).Figure 2
The seismic profile shows the volcanic activity of the K1yc in the Dehui Depression; location of the profile is shown in Figure 1 (modified from [28]).
## 2.3. Sedimentary Facies
During the deposition of the Yingcheng Formation, the Songliao Basin was tectonically active, and a number of faults were developed. The Yingcheng Formation is divided into two members while the first member is strongly affected by volcanism, and a large set of volcanic formations are developed around the Dehui fault depression [5]. At the margins of the fault depression, a set of fan-delta and lacustrine facies were deposited, and a mixed sequence of volcanic and clastic sedimentary strata was formed. The sedimentary facies in the study area are mainly fan-deltaic, lacustrine, and nearshore subaqueous fan (Figure 3). The fan-delta is widely developed in the eastern and western margins of the depression, while the braided river delta plain is dominant in the south, and the lacustrine facies center is located in the northeast of the depression. During the sedimentation process, the supply of sediment was hindered by the influence of multiple volcanic activities, which limited the range and thickness of sand bodies that were deposited in the northeast.Figure 3
The sedimentary facies map of the K1yc in the Dehui Depression shows the distribution of volcanic and sedimentary rocks.
## 2.4. Petroleum System
Three sets of petroleum source-reservoir-seal systems are identified in the study area [5, 25]. In the K1yc, K1sh, and K1h, thick organic-rich mudstones with a high thermal maturity have been proven to be the effective source for the gas. Meanwhile, fine sandstone, siltstone, conglomerate, and volcanic rocks formed during volcanic activity are widely spread in the K1yc, K1sh, and K1h and act as the reservoir for natural gas accumulation. Thick mudstone developed in the K2d is almost distributed in the entire southern Songliao Basin and could serve as the regional seal, and mudstone layers in each formation mentioned above can serve as the local caprocks [7].
## 3. Samples and Methods
A total of 235 core samples from the K1yc were selected in this study (location of sampling well is shown in Figure 1(c)). From these, 97 mudstone samples were selected for Rock-Eval pyrolysis while 16 were chosen for vitrinite reflectance measurements to characterize the source rock. Moreover, 63 samples from the volcanic and 75 from the tight sandstone were tested to characterize petrophysical properties of the reservoir. Thin sections were prepared from all reservoir samples and analyzed by using a petrographic microscope Leica DM2700P to observe pore types.A total of 97 core samples were pulverized to 100-mesh screen in preparation for geochemical analysis and TOC measurement. The TOC was measured using a LECO CS-230 analyzer, and programmed pyrolysis was performed using a Rock-Eval 6 plus analyzer to obtainS1 (free hydrocarbons), S2 (petroleum generated by pyrolysis), and Tmax (the temperature at peak evolution) by default method [29, 30].Vitrinite reflectance (Ro) was measured using a microphotometer, and this analysis was performed at the Geochemistry Laboratory of the Northeast Petroleum University. Analysis was performed with an oil immersion objective under normal white light at a wavelength of 546 mm. A mean value was calculated for each sample on the basis of 12-20 measurements on vitrinite [18].Porosity of core samples (63 volcanic and 75 tight sandstone) was done using core test system AP608 analyzer at Jilin University. The samples were drilled in cylinders with the size of1″×4″, vacuum-dried at 180°C, and then analyzed using a minipermeameter for air permeability measurements by nitrogen (air). The experimental temperature and humidity were 24°C and 35%, respectively [31].
## 4. Results
### 4.1. Geochemistry of Source Rock
Total organic carbon (TOC) in the source rocks of the Yingcheng Formation ranges from 0.22 wt.% to 18.85 wt.%, with an average value of 3.24 wt. %, of which 85.6% is higher than 1.0 wt.%, and 60.8% is higher than 2.0 wt.%, in 97 samples that were tested (Table1). Pyrolysis data was used to determine the type of organic matter following geochemical charts. According to Figures 4 and 5, the pyrolysis data of source rocks plotted in the van Krevelen diagram (HI vs. Tmax and S2 vs. TOC) are pointing to type III, and a small portion of type IV inert organic matter. Therefore, the organic matter type of the source rocks of the Yingcheng Formation is type III, which dominantly generates gas. The samples with abnormal Tmax which is demonstrated in Figure 4 have relatively higher PI index, indicating the presence of bitumen remanence in shale samples.Table 1
Results of Rock-Eval pyrolysis.
Depth (m)TOC (%)S1 (mg/g)S2 (mg/g)Tmax (°C)S1+S2 (mg/g)HI (mg HC/g TOC)PI2856.602.282.531.85486.004.3881.140.582856.653.240.631.57490.002.2048.460.292857.002.671.111.58490.002.6959.180.412857.352.020.361.05489.001.4151.980.262857.703.190.941.86489.002.8058.310.342858.202.430.651.31491.001.9653.910.332858.703.030.731.63489.002.3653.800.312859.491.960.812.47488.003.28126.020.252859.501.690.510.95490.001.4656.210.352860.002.060.541.06488.001.6051.460.342860.703.330.290.68490.000.9720.420.302861.400.220.020.14482.000.1663.640.132861.902.180.521.24488.001.7656.880.302862.202.120.330.96489.001.2945.280.262862.702.120.531.08490.001.6150.940.332863.302.120.391.28488.001.6760.380.232863.802.170.361.14490.001.5052.530.242864.002.130.231.18487.001.4155.400.162864.402.390.381.20490.001.5850.210.242864.901.400.140.68489.000.8248.570.172865.201.590.230.87488.001.1054.720.212865.703.100.611.77490.002.3857.100.262866.201.970.401.08490.001.4854.820.272866.801.950.221.02488.001.2452.310.182867.002.190.311.19488.001.5054.340.212867.202.000.391.00488.001.3950.000.282867.901.400.260.87487.001.1362.140.232868.201.800.430.99488.001.4255.000.302868.701.770.350.98487.001.3355.370.262869.403.180.461.80489.002.2656.600.202869.701.260.140.72488.000.8657.140.162870.201.160.220.66489.000.8856.900.252870.501.300.110.72488.000.8355.380.132885.502.740.681.53490.002.2155.840.313053.951.690.351.87484.002.22110.650.163056.000.780.220.61494.000.8378.210.273056.252.080.251.23495.001.4859.130.173057.550.850.241.09396.001.33128.240.183057.850.580.030.39488.000.4267.240.073059.380.220.010.15488.000.1668.180.063060.450.380.041.07456.001.11281.580.043063.141.130.081.50472.001.58132.740.053063.431.730.162.72462.002.88157.230.063065.500.760.081.46443.001.54192.110.053377.981.400.060.42519.000.4830.000.133395.940.610.040.47487.000.5177.050.083396.900.620.050.41493.000.4666.130.112306.001.512.201.15458.003.3576.160.662307.001.836.951.18505.008.1364.480.852316.000.341.900.34387.002.24100.000.852326.000.342.330.33385.002.6697.060.882820.000.511.060.35485.001.4168.630.752850.000.510.910.31484.001.2260.780.752890.000.431.930.36486.002.2983.720.842910.003.844.502.83487.007.3373.700.612920.003.333.662.23486.005.8966.970.622930.002.722.741.80488.004.5466.180.602940.004.241.192.64489.003.8362.260.312960.006.821.946.47485.008.4194.870.232980.005.941.435.19485.006.6287.370.223005.008.332.768.62485.0011.38103.480.243020.001.641.291.23488.002.5275.000.513035.001.561.681.04490.002.7266.670.623217.541.600.100.49513.000.5930.630.173677.601.280.140.49570.000.6338.280.222665.002.503.352.76465.006.11110.400.552680.0012.904.3117.22472.0021.53133.490.202685.003.532.803.59473.006.39101.700.442690.008.423.569.97473.0013.53118.410.262710.0017.784.2524.81473.0029.06139.540.152725.009.656.8516.05475.0022.90166.320.302880.002.061.011.73483.002.7483.980.372898.002.321.591.84485.003.4379.310.462940.005.516.424.99488.0011.4190.560.562970.001.844.881.50488.006.3881.520.762990.001.935.081.68492.006.7687.050.753010.004.824.184.19489.008.3786.930.503015.0018.857.7916.80489.0024.5989.120.323020.0018.716.7114.31491.0021.0276.480.323060.003.9312.593.42493.0016.0187.020.793078.0013.4614.7513.15492.0027.9097.700.533215.003.8210.342.26504.0012.6059.160.823420.002.000.070.46434.000.5323.000.133830.007.089.538.45483.0017.98119.350.532785.003.1820.923.06356.0023.9896.230.872795.002.8818.552.72351.0021.2794.440.872805.003.2221.383.30357.0024.68102.480.872815.003.2017.153.21360.0020.36100.310.842825.003.3919.153.11358.0022.2691.740.862835.003.5623.333.40364.0026.7395.510.872845.003.3018.993.41364.0022.40103.330.852855.003.1516.833.14363.0019.9799.680.842865.003.1611.402.66344.0014.0684.180.812870.002.786.641.63329.008.2758.630.802878.002.5911.152.35344.0013.5090.730.832885.003.9714.083.09493.0017.1777.830.822890.003.3421.382.87341.0024.2585.930.88TOC: total organic carbon content;S1: free hydrocarbons present in the rock; S2: petroleum generated by pyrolysis; S1+S2: genetic potential; Tmax: the temperature at peak evolution of S2 hydrocarbons (°C); HI: hydrogen index, S2dividedbyTOC×100; PI: production index, S1/S1+S2.Figure 4
Plot of TOC (wt.%) vs. HI (mg HC/g TOC) of the K1yc (according to [35]).Figure 5
The TOC versusS2 plot for the K1yc source rock samples (according to [36]).The distribution of potential hydrocarbon generation capacity (S1+S2) ranges from 0.16 to 29.06 mg/g, with an average of 6.86 mg/g, among which 35.1% are higher than 6 mg/g, and 14.4% are higher than 20 mg/g. An overview of the samples exhibits that they generally represent a poor to good source rock (Figure 6(a)). The HI vs. TOC plot explains that most of the samples are located in the regions of very little to questionable gas (Figure 6(b)). Only parts of the samples are demonstrating to be a good source rock and to have fair gas generation potential with lower S2 at the higher maturations (Figure 6).Figure 6
(a) Plot of total organic carbon (TOC) vs. generative potential (S1+S2) of the K1yc (according to [37]). (b) Plot of TOC vs. HI of the K1yc in the study area (according to [38]).
(a)(b)
### 4.2. Maturation of Organic Matter
The maximum pyrolysis temperature (Tmax) of the source rocks of the Yingcheng Formation was measured between 329°C and 570°C, while most values are more than 470°C, inferring that the source rocks of the Yingcheng Formation are over mature in the gas generation window with the exclusion of the abnormal data under 400°C (Figure 7(a)). The measured vitrinite reflectance (Ro) values of source rocks in the Yingcheng Formation is positively correlated with the burial depth and increases as the formation becomes deeper (Figure 7(b)). Among these 16 samples that were inspected for Ro, except two that are shallower, the Ro was found more than 1.4%, while it appears to be more than 2.0% for samples buried deeper than 3000 m (Table 2). Collectively, the organic matter in the source rocks of the Yingcheng Formation in the study area has entered gas generation window and is highly overmatured.Figure 7
(a)Tmax and (b) Ro versus depth for the K1yc source rocks samples. Thermal maturity zones are divided according to Peters and Cassa [39].Table 2
Results of vitrinite reflectance experiment.
Well nameDepth (m)Ro (%)Num. measu.SDDS1112858.21.39200.16DS1112859.21.76190.04DS1112861.91.40200.14DS1113056.02.13200.15DS1113063.12.15200.11DS1113063.42.17200.14DS1113377.92.49200.16DS17-62518.91.29200.14DS17-62528.01.31200.12DS813085.42.12160.06DS813086.02.08120.06DS813092.02.15200.06DS833280.62.01200.13DS833690.22.38200.16DS833692.32.31170.05DS833692.32.40200.17Ro: vitrinite reflectance; Num. measu.: number of measured points; SD: standard deviation.
### 4.3. Petrophysical Properties
#### 4.3.1. Volcanic Reservoir
As shown in Figure2, volcanic rocks are presenting separate seismic reflections attributes compared to other sedimentary layers, making the interpretation of Yingcheng volcanic rocks based on seismic profiles much easier. Volcanic rocks of the Yingcheng Formation are mainly distributed in the northeast of the study area and are controlled by volcanic activities. Their thickness varies from 0 to 400 m and can reach more than 700 m locally (Figure 8). The porosity of the volcanic reservoir rocks of the Yingcheng Formation in the study area is between 3.0% and 14.8%, with an average value of 7.3%. The porosity distribution is approximately normal, with the main peak around 5%-8%, which also accounts for 74.6% of the entire samples. The permeability of the samples were measured between 0.0004 and 2.52 mD, while the 0.001 to 0.01 mD interval accounts for 43% of the total tested samples.Figure 8
Distribution of volcanic rock reservoir of the K1yc.The pore type of volcanic reservoir rocks is complex and varies but can roughly be divided into three types: (1) primary pores, (2) secondary pores, and (3) fractures based on observations on thin sections. The dominant type is secondary pores, mainly feldspar dissolution pores, which are mostly developed in tuff (Figure9(a)). Moreover, fractures that are formed by the structural stress are more dominant in dacite in the study area (Figures 9(b) and 9(c)) and occasionally observed in tuff (Figure 9(d)).Figure 9
Thin section observed by plane-polarized and light perpendicular-polarized light for volcanic reservoir samples for the K1yc. (a) 2700.0 m, tuff; (b) 2240.0 m, dacite; (c) 2240.9 m, dacite; (d) 2700.0 m, tuff.
(a)(b)(c)(d)
#### 4.3.2. Tight Sandstone Reservoir
Tight sandstone deposition is controlled by changes in the facies, mainly distributed in the delta front and plain subfacies in the northeast and northwestern areas of the fault depression, with a thickness of 0-400 m (Figure10). The thickness of sandstone facies in the middle of the fault depression is less than 100 m. Furthermore, the porosity of tight sandstone in the Yingcheng Formation in the study area was measured between 0.5% and 11.2%, with an average value of 5.1%, and its distribution is also approximately uniform. Comparing their porosity with the volcanic reservoir, the distribution of measured porosity values is relatively dispersed, and 2%-7% of porosity constitutes 69.3% of total collected data. In addition, the permeability of the samples was found to vary between 0.0008 and 3.17 mD, with the peak at 0.001 mD. Considering thin section analysis, the reservoir space in the study area is mainly intergranular pores, with a small amount of intragranular pores and microfractures (Figure 11).Figure 10
Distribution of tight sandstone reservoir of the K1yc.Figure 11
Thin section observed by plane-polarized and light perpendicular-polarized light for tight sandstone reservoir samples for the K1yc. (a) 2522 m, tuffaceous sandstone; (b) 2543 m, tuffaceous sandstone; (c) 2803.5 m, tuffaceous sandstone; (d) 2912.5 m, tuffaceous sandstone ((c) and (d) are referenced from [28]).
(a)(b)(c)(d)
## 4.1. Geochemistry of Source Rock
Total organic carbon (TOC) in the source rocks of the Yingcheng Formation ranges from 0.22 wt.% to 18.85 wt.%, with an average value of 3.24 wt. %, of which 85.6% is higher than 1.0 wt.%, and 60.8% is higher than 2.0 wt.%, in 97 samples that were tested (Table1). Pyrolysis data was used to determine the type of organic matter following geochemical charts. According to Figures 4 and 5, the pyrolysis data of source rocks plotted in the van Krevelen diagram (HI vs. Tmax and S2 vs. TOC) are pointing to type III, and a small portion of type IV inert organic matter. Therefore, the organic matter type of the source rocks of the Yingcheng Formation is type III, which dominantly generates gas. The samples with abnormal Tmax which is demonstrated in Figure 4 have relatively higher PI index, indicating the presence of bitumen remanence in shale samples.Table 1
Results of Rock-Eval pyrolysis.
Depth (m)TOC (%)S1 (mg/g)S2 (mg/g)Tmax (°C)S1+S2 (mg/g)HI (mg HC/g TOC)PI2856.602.282.531.85486.004.3881.140.582856.653.240.631.57490.002.2048.460.292857.002.671.111.58490.002.6959.180.412857.352.020.361.05489.001.4151.980.262857.703.190.941.86489.002.8058.310.342858.202.430.651.31491.001.9653.910.332858.703.030.731.63489.002.3653.800.312859.491.960.812.47488.003.28126.020.252859.501.690.510.95490.001.4656.210.352860.002.060.541.06488.001.6051.460.342860.703.330.290.68490.000.9720.420.302861.400.220.020.14482.000.1663.640.132861.902.180.521.24488.001.7656.880.302862.202.120.330.96489.001.2945.280.262862.702.120.531.08490.001.6150.940.332863.302.120.391.28488.001.6760.380.232863.802.170.361.14490.001.5052.530.242864.002.130.231.18487.001.4155.400.162864.402.390.381.20490.001.5850.210.242864.901.400.140.68489.000.8248.570.172865.201.590.230.87488.001.1054.720.212865.703.100.611.77490.002.3857.100.262866.201.970.401.08490.001.4854.820.272866.801.950.221.02488.001.2452.310.182867.002.190.311.19488.001.5054.340.212867.202.000.391.00488.001.3950.000.282867.901.400.260.87487.001.1362.140.232868.201.800.430.99488.001.4255.000.302868.701.770.350.98487.001.3355.370.262869.403.180.461.80489.002.2656.600.202869.701.260.140.72488.000.8657.140.162870.201.160.220.66489.000.8856.900.252870.501.300.110.72488.000.8355.380.132885.502.740.681.53490.002.2155.840.313053.951.690.351.87484.002.22110.650.163056.000.780.220.61494.000.8378.210.273056.252.080.251.23495.001.4859.130.173057.550.850.241.09396.001.33128.240.183057.850.580.030.39488.000.4267.240.073059.380.220.010.15488.000.1668.180.063060.450.380.041.07456.001.11281.580.043063.141.130.081.50472.001.58132.740.053063.431.730.162.72462.002.88157.230.063065.500.760.081.46443.001.54192.110.053377.981.400.060.42519.000.4830.000.133395.940.610.040.47487.000.5177.050.083396.900.620.050.41493.000.4666.130.112306.001.512.201.15458.003.3576.160.662307.001.836.951.18505.008.1364.480.852316.000.341.900.34387.002.24100.000.852326.000.342.330.33385.002.6697.060.882820.000.511.060.35485.001.4168.630.752850.000.510.910.31484.001.2260.780.752890.000.431.930.36486.002.2983.720.842910.003.844.502.83487.007.3373.700.612920.003.333.662.23486.005.8966.970.622930.002.722.741.80488.004.5466.180.602940.004.241.192.64489.003.8362.260.312960.006.821.946.47485.008.4194.870.232980.005.941.435.19485.006.6287.370.223005.008.332.768.62485.0011.38103.480.243020.001.641.291.23488.002.5275.000.513035.001.561.681.04490.002.7266.670.623217.541.600.100.49513.000.5930.630.173677.601.280.140.49570.000.6338.280.222665.002.503.352.76465.006.11110.400.552680.0012.904.3117.22472.0021.53133.490.202685.003.532.803.59473.006.39101.700.442690.008.423.569.97473.0013.53118.410.262710.0017.784.2524.81473.0029.06139.540.152725.009.656.8516.05475.0022.90166.320.302880.002.061.011.73483.002.7483.980.372898.002.321.591.84485.003.4379.310.462940.005.516.424.99488.0011.4190.560.562970.001.844.881.50488.006.3881.520.762990.001.935.081.68492.006.7687.050.753010.004.824.184.19489.008.3786.930.503015.0018.857.7916.80489.0024.5989.120.323020.0018.716.7114.31491.0021.0276.480.323060.003.9312.593.42493.0016.0187.020.793078.0013.4614.7513.15492.0027.9097.700.533215.003.8210.342.26504.0012.6059.160.823420.002.000.070.46434.000.5323.000.133830.007.089.538.45483.0017.98119.350.532785.003.1820.923.06356.0023.9896.230.872795.002.8818.552.72351.0021.2794.440.872805.003.2221.383.30357.0024.68102.480.872815.003.2017.153.21360.0020.36100.310.842825.003.3919.153.11358.0022.2691.740.862835.003.5623.333.40364.0026.7395.510.872845.003.3018.993.41364.0022.40103.330.852855.003.1516.833.14363.0019.9799.680.842865.003.1611.402.66344.0014.0684.180.812870.002.786.641.63329.008.2758.630.802878.002.5911.152.35344.0013.5090.730.832885.003.9714.083.09493.0017.1777.830.822890.003.3421.382.87341.0024.2585.930.88TOC: total organic carbon content;S1: free hydrocarbons present in the rock; S2: petroleum generated by pyrolysis; S1+S2: genetic potential; Tmax: the temperature at peak evolution of S2 hydrocarbons (°C); HI: hydrogen index, S2dividedbyTOC×100; PI: production index, S1/S1+S2.Figure 4
Plot of TOC (wt.%) vs. HI (mg HC/g TOC) of the K1yc (according to [35]).Figure 5
The TOC versusS2 plot for the K1yc source rock samples (according to [36]).The distribution of potential hydrocarbon generation capacity (S1+S2) ranges from 0.16 to 29.06 mg/g, with an average of 6.86 mg/g, among which 35.1% are higher than 6 mg/g, and 14.4% are higher than 20 mg/g. An overview of the samples exhibits that they generally represent a poor to good source rock (Figure 6(a)). The HI vs. TOC plot explains that most of the samples are located in the regions of very little to questionable gas (Figure 6(b)). Only parts of the samples are demonstrating to be a good source rock and to have fair gas generation potential with lower S2 at the higher maturations (Figure 6).Figure 6
(a) Plot of total organic carbon (TOC) vs. generative potential (S1+S2) of the K1yc (according to [37]). (b) Plot of TOC vs. HI of the K1yc in the study area (according to [38]).
(a)(b)
## 4.2. Maturation of Organic Matter
The maximum pyrolysis temperature (Tmax) of the source rocks of the Yingcheng Formation was measured between 329°C and 570°C, while most values are more than 470°C, inferring that the source rocks of the Yingcheng Formation are over mature in the gas generation window with the exclusion of the abnormal data under 400°C (Figure 7(a)). The measured vitrinite reflectance (Ro) values of source rocks in the Yingcheng Formation is positively correlated with the burial depth and increases as the formation becomes deeper (Figure 7(b)). Among these 16 samples that were inspected for Ro, except two that are shallower, the Ro was found more than 1.4%, while it appears to be more than 2.0% for samples buried deeper than 3000 m (Table 2). Collectively, the organic matter in the source rocks of the Yingcheng Formation in the study area has entered gas generation window and is highly overmatured.Figure 7
(a)Tmax and (b) Ro versus depth for the K1yc source rocks samples. Thermal maturity zones are divided according to Peters and Cassa [39].Table 2
Results of vitrinite reflectance experiment.
Well nameDepth (m)Ro (%)Num. measu.SDDS1112858.21.39200.16DS1112859.21.76190.04DS1112861.91.40200.14DS1113056.02.13200.15DS1113063.12.15200.11DS1113063.42.17200.14DS1113377.92.49200.16DS17-62518.91.29200.14DS17-62528.01.31200.12DS813085.42.12160.06DS813086.02.08120.06DS813092.02.15200.06DS833280.62.01200.13DS833690.22.38200.16DS833692.32.31170.05DS833692.32.40200.17Ro: vitrinite reflectance; Num. measu.: number of measured points; SD: standard deviation.
## 4.3. Petrophysical Properties
### 4.3.1. Volcanic Reservoir
As shown in Figure2, volcanic rocks are presenting separate seismic reflections attributes compared to other sedimentary layers, making the interpretation of Yingcheng volcanic rocks based on seismic profiles much easier. Volcanic rocks of the Yingcheng Formation are mainly distributed in the northeast of the study area and are controlled by volcanic activities. Their thickness varies from 0 to 400 m and can reach more than 700 m locally (Figure 8). The porosity of the volcanic reservoir rocks of the Yingcheng Formation in the study area is between 3.0% and 14.8%, with an average value of 7.3%. The porosity distribution is approximately normal, with the main peak around 5%-8%, which also accounts for 74.6% of the entire samples. The permeability of the samples were measured between 0.0004 and 2.52 mD, while the 0.001 to 0.01 mD interval accounts for 43% of the total tested samples.Figure 8
Distribution of volcanic rock reservoir of the K1yc.The pore type of volcanic reservoir rocks is complex and varies but can roughly be divided into three types: (1) primary pores, (2) secondary pores, and (3) fractures based on observations on thin sections. The dominant type is secondary pores, mainly feldspar dissolution pores, which are mostly developed in tuff (Figure9(a)). Moreover, fractures that are formed by the structural stress are more dominant in dacite in the study area (Figures 9(b) and 9(c)) and occasionally observed in tuff (Figure 9(d)).Figure 9
Thin section observed by plane-polarized and light perpendicular-polarized light for volcanic reservoir samples for the K1yc. (a) 2700.0 m, tuff; (b) 2240.0 m, dacite; (c) 2240.9 m, dacite; (d) 2700.0 m, tuff.
(a)(b)(c)(d)
### 4.3.2. Tight Sandstone Reservoir
Tight sandstone deposition is controlled by changes in the facies, mainly distributed in the delta front and plain subfacies in the northeast and northwestern areas of the fault depression, with a thickness of 0-400 m (Figure10). The thickness of sandstone facies in the middle of the fault depression is less than 100 m. Furthermore, the porosity of tight sandstone in the Yingcheng Formation in the study area was measured between 0.5% and 11.2%, with an average value of 5.1%, and its distribution is also approximately uniform. Comparing their porosity with the volcanic reservoir, the distribution of measured porosity values is relatively dispersed, and 2%-7% of porosity constitutes 69.3% of total collected data. In addition, the permeability of the samples was found to vary between 0.0008 and 3.17 mD, with the peak at 0.001 mD. Considering thin section analysis, the reservoir space in the study area is mainly intergranular pores, with a small amount of intragranular pores and microfractures (Figure 11).Figure 10
Distribution of tight sandstone reservoir of the K1yc.Figure 11
Thin section observed by plane-polarized and light perpendicular-polarized light for tight sandstone reservoir samples for the K1yc. (a) 2522 m, tuffaceous sandstone; (b) 2543 m, tuffaceous sandstone; (c) 2803.5 m, tuffaceous sandstone; (d) 2912.5 m, tuffaceous sandstone ((c) and (d) are referenced from [28]).
(a)(b)(c)(d)
## 4.3.1. Volcanic Reservoir
As shown in Figure2, volcanic rocks are presenting separate seismic reflections attributes compared to other sedimentary layers, making the interpretation of Yingcheng volcanic rocks based on seismic profiles much easier. Volcanic rocks of the Yingcheng Formation are mainly distributed in the northeast of the study area and are controlled by volcanic activities. Their thickness varies from 0 to 400 m and can reach more than 700 m locally (Figure 8). The porosity of the volcanic reservoir rocks of the Yingcheng Formation in the study area is between 3.0% and 14.8%, with an average value of 7.3%. The porosity distribution is approximately normal, with the main peak around 5%-8%, which also accounts for 74.6% of the entire samples. The permeability of the samples were measured between 0.0004 and 2.52 mD, while the 0.001 to 0.01 mD interval accounts for 43% of the total tested samples.Figure 8
Distribution of volcanic rock reservoir of the K1yc.The pore type of volcanic reservoir rocks is complex and varies but can roughly be divided into three types: (1) primary pores, (2) secondary pores, and (3) fractures based on observations on thin sections. The dominant type is secondary pores, mainly feldspar dissolution pores, which are mostly developed in tuff (Figure9(a)). Moreover, fractures that are formed by the structural stress are more dominant in dacite in the study area (Figures 9(b) and 9(c)) and occasionally observed in tuff (Figure 9(d)).Figure 9
Thin section observed by plane-polarized and light perpendicular-polarized light for volcanic reservoir samples for the K1yc. (a) 2700.0 m, tuff; (b) 2240.0 m, dacite; (c) 2240.9 m, dacite; (d) 2700.0 m, tuff.
(a)(b)(c)(d)
## 4.3.2. Tight Sandstone Reservoir
Tight sandstone deposition is controlled by changes in the facies, mainly distributed in the delta front and plain subfacies in the northeast and northwestern areas of the fault depression, with a thickness of 0-400 m (Figure10). The thickness of sandstone facies in the middle of the fault depression is less than 100 m. Furthermore, the porosity of tight sandstone in the Yingcheng Formation in the study area was measured between 0.5% and 11.2%, with an average value of 5.1%, and its distribution is also approximately uniform. Comparing their porosity with the volcanic reservoir, the distribution of measured porosity values is relatively dispersed, and 2%-7% of porosity constitutes 69.3% of total collected data. In addition, the permeability of the samples was found to vary between 0.0008 and 3.17 mD, with the peak at 0.001 mD. Considering thin section analysis, the reservoir space in the study area is mainly intergranular pores, with a small amount of intragranular pores and microfractures (Figure 11).Figure 10
Distribution of tight sandstone reservoir of the K1yc.Figure 11
Thin section observed by plane-polarized and light perpendicular-polarized light for tight sandstone reservoir samples for the K1yc. (a) 2522 m, tuffaceous sandstone; (b) 2543 m, tuffaceous sandstone; (c) 2803.5 m, tuffaceous sandstone; (d) 2912.5 m, tuffaceous sandstone ((c) and (d) are referenced from [28]).
(a)(b)(c)(d)
## 5. Discussion
### 5.1. Volcanic Effects on Hydrocarbon Generation
Volcanic intrusions have increased the temperature and pressure of the Yingcheng Formation and promoted the generation and expulsion of hydrocarbon in the source rocks [32]. Bulk geochemical data sets in this study show that deeply buried source rocks of the Yingcheng Formation in the Songliao Basin are widely developed and have good hydrocarbon generation potential. These source rocks are mostly type III kerogen with high TOC content. Additionally, measured Ro is generally greater than 1.4%, which is overmature, and on the onset of gas generation window. It is speculated that late volcanic intrusions provided sufficient heat source for the transformation of organic matter and caused the generation of natural gas in large quantities. The magmatic thermal field not only improves the geothermal gradient of the basin but also enhances the degree of thermal evolution of the organic matter compensating for the pressure and burial depth. This makes the threshold of gas generation to happen at the shallower depth, enhancing hydrocarbon generation [33]. In the volcanic gas reservoirs, the bitumen is common in micro fractures (Figures 9(b)–9(d)), referring to the abnormal high maturity which is consistent with the high paleo heat flow during the synrift phase [25]. This was caused by the upwelling of mantle plumes and the thinning of the crust, which were accompanied with volcanic activates before the Late Mesozoic-Cenozoic rapid cooling [34].
### 5.2. Pore Genesis of Reservoir
Based on the inspection of thin sections (Figure9), the volcanic reservoir of the Yingcheng Formation is mainly tuff and dacite, and the pores are mainly from mineral dissolution to create pores and microfractures. As shown in Figure 9, dissolution pores in the volcanic reservoirs such as tuff or dacite are mostly isolated and poorly connected. At the same time, the dissolution microfractures have a short extent, small width and irregularity, and limited in scope and number. Observation of thin sections also revealed the presence of asphaltene filling in the cracks.Tight sandstone reservoir of the Yingcheng Formation is generally dominated by intragranular dissolution pores, accounting for 89% of the total pores (Figure11). Among them, feldspar dissolution pores are the most developed ones, accounting for 35%, followed by lithic dissolution pores with 20%, intergranular dissolution pores 19%, and tuffaceous dissolution pores constituting 15% of the entire measured data. Likewise, a small number of intergranular pores, with 8% of the total pores measured, can also be responsible for a certain number of microfractures, around 3%. The intergranular dissolution pores are filled with autogenous albite, felsic particles, coniferous flake chlorite, and a small amount of illite and other clay minerals. The percentage of total surface porosity observed under the microscope is generally about 3%-10%. This kind of reservoir space is dominated by dissolved pores, nanoscale throat and underdeveloped reservoir characteristics, poor pore connectivity, easy-to-form isolated pores, resulting in “isolated pore space,” and dense characteristics of the reservoir with low permeability overall.The porosity of tight sandstone is much less than the volcanic rocks at the same depth (Figure12(a)). The porosity and permeability of sandstones has an obvious decreasing trend in the range of 2000-4500 m, which is caused by the compaction (Figure 12(b)). However, the porosity and permeability of volcanic reservoirs do not change much with depths, and the values are relatively concentrated, proving that compaction has little influence on the quality of the volcanic reservoir. In comparison with tight sandstone reservoir, the porosity of volcanic rock is relatively similar at shallower depth but generally improves with depth. The permeability of volcanic rocks is less than tight sandstones, but again it enhances with depth. That confirms how the effects of compaction on sandstones and volcanic rocks can be different, causing the sandstone to always have relatively better porosity and permeability at shallower depth, though it is important that one does not overlook the improvement of reservoir properties in the volcanic rock, too, as the formation gets deeper.Figure 12
(a) Porosity and (b) permeability versus the depth of volcanic rock reservoir and tight sandstone reservoir samples for the K1yc.
(a)(b)
### 5.3. Gas Accumulation Model in Volcanic Area
During the formation of the Yingcheng Formation in the study area, the basin was under extension [7]; thus, the controlling depression fault expanded eastward, and the sedimentary area gradually expanded, accompanied by volcanic activities for the entire period. The early subsidence center of the Yingcheng Formation is close to the boundary fault, making the deep extension area small. Moreover, volcanic activity mainly happened in the eastern gentle slope of the basin, which controlled sedimentation in the eastern boundary as well. Likewise, volcanic erosions provided additional sediment supply for the basin. In the middle stages of the Yingcheng Formation, the depocenter migrated northward to the east, the deep depression area expanded, and the volcanic rocks in the eastern gentle slope area generally eroded. At the end of the deposition of the Yingcheng Formation, the basin shrunk, and the deeper depression area was distributed along the boundary faults. Besides, the stratigraphic distribution range was large with limited thickness, and as the volcanism was strengthened, it affected the entire basin. This caused the strata to get dispersed between the volcanically active areas and the control-depression fault. Therefore, the reservoirs are scattered in the middle and upper parts of the Yingcheng Formation, which made the relationship between the source and the reservoir rocks stronger.During the earlier phases of volcanic eruption, larger volcanic bodies developed, which controlled the lateral boundaries of the trough of the Yingcheng Formation, to form an updip lateral block due to the tectonic activity that was later followed. The volcanic rocks mainly from tuff in the Yingcheng Formation formed during the middle phases of volcanism have constant thickness (ranging from 80 to 150 m, and more than 200 m locally) and wide lateral distribution, which played the role of the regional caprock [28]. These two volcanic activities promoted the formation of large traps and played a vital role in gas enrichment and preservation. Furthermore, the tuff layer is very dense, is free of fractures, and does not intrude and damage the gas reservoir, sealing the entire tight sandstone reservoir underneath. The early and middle volcanism surrounded the entire Yingcheng Formation and supported the formation of tight sandstone gas traps. The above two volcanic activities formed one block and one cap, which provided favorable trap conditions for tight sandstone gas reservoirs (Figure 13).Figure 13
Cross-section of gas accumulation in the K1yc; location of the profile is shown in Figure 1. In this section, suitable gas productive zones in the volcanic rock reservoir and tight sandstone reservoir are displayed (modified from [28]).On the other hand, volcanic rocks in some areas are replaced with sandstone bodies, to become complementary reservoir space. This combination of tight sandstone and volcanic gas reservoirs formed in the same horizon also produced economic quantities of gas. For example, well DS80 showed21.0×104m3/d flow rate in the 2650-3200 m interval, well DS33, 3.3×104m3/d and 1.6×104m3/d in two separate intervals, and well DS83, 8.0×104m3/d of high-yielding flow in the upper volcanic zone of the reservoir (Figure 13).
## 5.1. Volcanic Effects on Hydrocarbon Generation
Volcanic intrusions have increased the temperature and pressure of the Yingcheng Formation and promoted the generation and expulsion of hydrocarbon in the source rocks [32]. Bulk geochemical data sets in this study show that deeply buried source rocks of the Yingcheng Formation in the Songliao Basin are widely developed and have good hydrocarbon generation potential. These source rocks are mostly type III kerogen with high TOC content. Additionally, measured Ro is generally greater than 1.4%, which is overmature, and on the onset of gas generation window. It is speculated that late volcanic intrusions provided sufficient heat source for the transformation of organic matter and caused the generation of natural gas in large quantities. The magmatic thermal field not only improves the geothermal gradient of the basin but also enhances the degree of thermal evolution of the organic matter compensating for the pressure and burial depth. This makes the threshold of gas generation to happen at the shallower depth, enhancing hydrocarbon generation [33]. In the volcanic gas reservoirs, the bitumen is common in micro fractures (Figures 9(b)–9(d)), referring to the abnormal high maturity which is consistent with the high paleo heat flow during the synrift phase [25]. This was caused by the upwelling of mantle plumes and the thinning of the crust, which were accompanied with volcanic activates before the Late Mesozoic-Cenozoic rapid cooling [34].
## 5.2. Pore Genesis of Reservoir
Based on the inspection of thin sections (Figure9), the volcanic reservoir of the Yingcheng Formation is mainly tuff and dacite, and the pores are mainly from mineral dissolution to create pores and microfractures. As shown in Figure 9, dissolution pores in the volcanic reservoirs such as tuff or dacite are mostly isolated and poorly connected. At the same time, the dissolution microfractures have a short extent, small width and irregularity, and limited in scope and number. Observation of thin sections also revealed the presence of asphaltene filling in the cracks.Tight sandstone reservoir of the Yingcheng Formation is generally dominated by intragranular dissolution pores, accounting for 89% of the total pores (Figure11). Among them, feldspar dissolution pores are the most developed ones, accounting for 35%, followed by lithic dissolution pores with 20%, intergranular dissolution pores 19%, and tuffaceous dissolution pores constituting 15% of the entire measured data. Likewise, a small number of intergranular pores, with 8% of the total pores measured, can also be responsible for a certain number of microfractures, around 3%. The intergranular dissolution pores are filled with autogenous albite, felsic particles, coniferous flake chlorite, and a small amount of illite and other clay minerals. The percentage of total surface porosity observed under the microscope is generally about 3%-10%. This kind of reservoir space is dominated by dissolved pores, nanoscale throat and underdeveloped reservoir characteristics, poor pore connectivity, easy-to-form isolated pores, resulting in “isolated pore space,” and dense characteristics of the reservoir with low permeability overall.The porosity of tight sandstone is much less than the volcanic rocks at the same depth (Figure12(a)). The porosity and permeability of sandstones has an obvious decreasing trend in the range of 2000-4500 m, which is caused by the compaction (Figure 12(b)). However, the porosity and permeability of volcanic reservoirs do not change much with depths, and the values are relatively concentrated, proving that compaction has little influence on the quality of the volcanic reservoir. In comparison with tight sandstone reservoir, the porosity of volcanic rock is relatively similar at shallower depth but generally improves with depth. The permeability of volcanic rocks is less than tight sandstones, but again it enhances with depth. That confirms how the effects of compaction on sandstones and volcanic rocks can be different, causing the sandstone to always have relatively better porosity and permeability at shallower depth, though it is important that one does not overlook the improvement of reservoir properties in the volcanic rock, too, as the formation gets deeper.Figure 12
(a) Porosity and (b) permeability versus the depth of volcanic rock reservoir and tight sandstone reservoir samples for the K1yc.
(a)(b)
## 5.3. Gas Accumulation Model in Volcanic Area
During the formation of the Yingcheng Formation in the study area, the basin was under extension [7]; thus, the controlling depression fault expanded eastward, and the sedimentary area gradually expanded, accompanied by volcanic activities for the entire period. The early subsidence center of the Yingcheng Formation is close to the boundary fault, making the deep extension area small. Moreover, volcanic activity mainly happened in the eastern gentle slope of the basin, which controlled sedimentation in the eastern boundary as well. Likewise, volcanic erosions provided additional sediment supply for the basin. In the middle stages of the Yingcheng Formation, the depocenter migrated northward to the east, the deep depression area expanded, and the volcanic rocks in the eastern gentle slope area generally eroded. At the end of the deposition of the Yingcheng Formation, the basin shrunk, and the deeper depression area was distributed along the boundary faults. Besides, the stratigraphic distribution range was large with limited thickness, and as the volcanism was strengthened, it affected the entire basin. This caused the strata to get dispersed between the volcanically active areas and the control-depression fault. Therefore, the reservoirs are scattered in the middle and upper parts of the Yingcheng Formation, which made the relationship between the source and the reservoir rocks stronger.During the earlier phases of volcanic eruption, larger volcanic bodies developed, which controlled the lateral boundaries of the trough of the Yingcheng Formation, to form an updip lateral block due to the tectonic activity that was later followed. The volcanic rocks mainly from tuff in the Yingcheng Formation formed during the middle phases of volcanism have constant thickness (ranging from 80 to 150 m, and more than 200 m locally) and wide lateral distribution, which played the role of the regional caprock [28]. These two volcanic activities promoted the formation of large traps and played a vital role in gas enrichment and preservation. Furthermore, the tuff layer is very dense, is free of fractures, and does not intrude and damage the gas reservoir, sealing the entire tight sandstone reservoir underneath. The early and middle volcanism surrounded the entire Yingcheng Formation and supported the formation of tight sandstone gas traps. The above two volcanic activities formed one block and one cap, which provided favorable trap conditions for tight sandstone gas reservoirs (Figure 13).Figure 13
Cross-section of gas accumulation in the K1yc; location of the profile is shown in Figure 1. In this section, suitable gas productive zones in the volcanic rock reservoir and tight sandstone reservoir are displayed (modified from [28]).On the other hand, volcanic rocks in some areas are replaced with sandstone bodies, to become complementary reservoir space. This combination of tight sandstone and volcanic gas reservoirs formed in the same horizon also produced economic quantities of gas. For example, well DS80 showed21.0×104m3/d flow rate in the 2650-3200 m interval, well DS33, 3.3×104m3/d and 1.6×104m3/d in two separate intervals, and well DS83, 8.0×104m3/d of high-yielding flow in the upper volcanic zone of the reservoir (Figure 13).
## 6. Conclusion
(1)
The organic carbon content of the source rocks of the Yingcheng Formation in Dehui fault depression varies from 0.22 wt.% to 18.85 wt.%, with an average of 3.05 wt.%. The distribution of potential hydrocarbon generation (S1+S2) was found from 0.16 to 29.06 mg/g, with an average of 6.21 mg/g. Additionally, organic matter is mainly type III and at the high-overmaturity, representing favorable conditions for gas generation(2)
The thickness of volcanic reservoir in the study area is 0-400 m, the porosity is 3.0%-14.8%, the permeability is 0.0004-2.52 mD, and pore types are mainly secondary dissolved pores and fractures. Moreover, the thickness of the tight sandstone reservoir is 0-400 m, the porosity is 0.5%-11.2%, and the permeability is 0.0008-3.17 mD. Pore types are generally intergranular pores, with a small amount of intragranular pores and microfractures(3)
Late volcanic activity of the Yingcheng Formation in the study area provided sufficient heat source for the organic matter transformation and promoted the generation of natural gas in large quantities(4)
The petrophysical properties of the tight sandstone reservoir deteriorated significantly with depth and are affected by compaction notably, while the petrophysical properties of volcanic reservoir do not vary much as the formation get deeper representing more homogeneous characteristics. At the same time, secondary pores formed by late dissolution of pyroclasts formed by volcanic activities also provided storage space for gas accumulation(5)
Volcanic rocks that are formed during the early and middle phases of the Yingcheng Formation development occupied the sedimentary space, which worked against the deposition of sand bodies to some extent. However, volcanic rocks became regional seals as part of the tight sandstone gas trap. Finally, the combination of volcanic rocks and tight sandstones has created a complex petroleum system for the accumulation and preservation of gas in the basin.
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*Source: 2900224-2021-09-30.xml* | 2900224-2021-09-30_2900224-2021-09-30.md | 64,552 | Accumulation and Distribution of Natural Gas Reservoir in Volcanic Active Area: A Case Study of the Cretaceous Yingcheng Formation in the Dehui Fault Depression, Songliao Basin, NE China | Fancheng Zeng; Bo Liu; Changmin Zhang; Guoyi Zhang; Jin Gao; Junjie Liu; Mehdi Ostadhassan | Geofluids
(2021) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2021/2900224 | 2900224-2021-09-30.xml | ---
## Abstract
Tight gas sandstone and volcanic gas reservoirs have received global attention in the energy arena for further exploration and exploitation attempts. Considering the Yingcheng Formation of Dehui fault depression in the Songliao Basin as an example, this study focused on the accumulation and distribution of natural gas reservoirs in volcanic area in a fault depression basin. Volcanic activities occurred in the Yingcheng Formation, which is distributed centrally in the northwest of the study area. During the sedimentation of the Yingcheng Formation, fan-delta, lacustrine, and nearshore subaqueous fan facies were deposited. The source rocks of the Yingcheng Formation have high abundance of organic matter mainly in type III at high-overmature stages, indicating favorable conditions for gas production. The porosity of volcanic reservoir is 3.0%-14.8%, the permeability is 0.0004 mD-2.52 mD, and the pore types are mainly secondary dissolved pores and fractures. Besides, the porosity of the tight sandstone reservoir is 0.5%-11.2%, and the permeability is 0.0008 mD-3.17 mD. The pore types are mainly interparticle pores, with a small proportion of intraparticle pores and microfractures. The intrusion of late volcanic magma provided sufficient heat for the thermal maturity progression of organic matter in Yingcheng Formation and promoted the generation of natural gas in large quantities. Volcanic rocks formed at the early and middle stages of volcanic activities occupied the sedimentary space and hindered the development of sedimentary sand bodies to a certain extent. However, volcanic rocks can become the seal to promote the formation of tight sandstone gas traps. Comparing tight sandstone reservoirs with volcanic ones, the latter are less affected by compaction; thus, their petrophysical properties do not vary much with depth, showing more homogeneous characteristics. The pyroclastic rocks influenced by volcanic activity and the secondary pores formed by dissolution in the later stages also provide reservoir space for gas accumulation. Ultimately, the tight sandstone and volcanic rocks in the study area form a complex gas reservoir system, which can become a reference for exploration and exploitation of natural gas in other petroliferous fault depressions that are affected by volcanisms.
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## Body
## 1. Introduction
IEA [1] estimates that global tight gas sandstone resources are roughly 209.6×1012m3. Additionally, exploration and development of tight gas sandstone reservoirs has supported the driving force for increasing global natural gas production in recent years [2]. In China, huge tight sandstone gas reservoirs exist in major oil-bearing basins, including the Tarim, Ordos, and Songliao Basins [3, 4]. As of 2016, gas production from tight sandstone reservoirs has reached 330×108m3, accounting for one-quarter of China’s annual natural gas production [3]. In this regard, volcanic gas reservoirs have also been found sporadically where tight sandstone gas reservoirs are abundant, such as the Lower Cretaceous in the Songliao Basin, the Jurassic in the Hailaer Basin, and the Upper Paleozoic of the Ordos Basin. The tight gas sandstone reservoirs and volcanic gas reservoirs in the volcanically active areas together constitute a complex gas accumulation system which requires further investigation [5–8].In basins located on the eastern China, volcano-sedimentary sequences have been widely developed since the Late Mesozoic [7]. During volcanism, a large number of igneous formations were formed, accompanied by various clastic deposits from igneous materials and volcanic lacustrine deposits during the intercalation period, forming an interactive sedimentary sequence [9]. In addition to the creation of these volcanic reservoirs, volcanic activity also has had an impact on the accumulation of natural gas in tight sandstones regionally [10]. Moreover, the influence of volcanisms on the basin sedimentation manifests itself in the following ways: first, volcanic activity can be used as a regional provenance, providing supply for the basin sedimentation [11, 12]. However, such volcanic activities in the island arc belt not only would change the composition of the supply in the sedimentary system but also play a role in blocking the distribution of the sedimentary system, alter topography, promote the formation or migration of the basin depocenter, develop around it, and thus form a new sedimentary system. Secondly, volcanic activity is also an important event that impacts the basin accommodation. Due to rapid accumulation of volcanic eruptions in some areas, the basin is affected by the thermal subsidence, and somehow, this was accelerated regionally, causing the total water volume to decrease. Conversely, in other areas of the depression, the influence of volcanic activities has been weak; therefore, the change of accommodative space is not significant [13]. This means the overall accommodative space for sediment load varies regionally throughout the basin. In addition, volcanic activities are often accompanied by large-scale hydrothermal events where high temperature as well as high pressure hydrothermal flux upwashes and enters the strata. As a result, this hydrothermal fluid contains rich soluble ions and will have persistent effects of detrital (mineral), which makes its diagenetic intensity to be strong [14]. In addition to the impact of volcanic activities that explained how would influence sedimentation in the basin, syndepositional volcanism controls the development of reservoirs mainly by providing soluble components and promoting the formation of fractures [15]. This has happened via the dissolution of chemically unstable soluble pyroclastic components that were preserved in the adjacent sedimentary sand bodies within the pores during the middle to late burial stages. Furthermore, during the periods of volcanic activity, the influx of a large amount of magma flew into the sedimentary sequence that resulted in the brittle rupture of consolidated sandstone to form microfractures, which increased the reservoir space and permeability of the reservoir [16, 17].In such events, volcanic ash would be beneficial to the enrichment and preservation of organic matter [18, 19] and promotes the conversion of organic matter to hydrocarbons [20–22]. These were some positive impacts of volcanic activities on various components of the petroleum system; however, its destructive effects on hydrocarbon accumulation cannot be neglected either. For example, volcanic activities can disrupt oil and gas accumulation significantly by creating channels or associated faults to damage the integrity of the trap and creating seepages for the accumulated hydrocarbons to escape the reservoir [17]. In addition, the heat source provided by volcanic activity also causes dehydration of minerals containing crystalline water in the adjacent sediments to recrystallize, which would fill the pores and fractures, reducing connectivity and deteriorating reservoir petrophysical properties.Songliao Basin is a large petroliferous basin developed on the basement of the Upper Paleozoic metamorphic rock series. During the rift period, there were intense tectonic movements and frequent volcanic activities. However, the combination of volcanism and sedimentation created good conditions for the formation of oil and gas reservoirs [23, 24]. In recent years, several large tight natural gas reservoirs have been discovered in the Songliao Basin [25], while some are associated with the volcanic rocks of the basin [6, 26, 27]. In the Dehui fault depression that is the subject of this study, both major tight sandstone and volcanic gas reservoirs are found in the Cretaceous strata, with great potential for resources and are good exploration prospects.In this study, tight gas sandstone and volcanic gas reservoir influenced by the volcanic activity of the Yingcheng Formation in the Dehui fault depression of the southern Songliao Basin has been assessed. By systematically sampling the source rocks, volcanic rocks, and tight sandstones in the study area and analyzing and examining them for total organic carbon (TOC) content, vitrinite reflectance (Ro), and reservoir physical property (porosity and permeability), the geochemical characteristics of the source rocks and the petrophysical properties of the reservoir rock including the volcanic and tight sandstone are understood. The goal of this study is to analyze the effects of volcanic activity in the area on the accumulation of natural gas. Furthermore, we comprehensively investigated the complexity of the petroleum system that is formed in the volcano-sedimentary sequence, to provide reference for the exploration and prospect evaluation in this petroliferous basin for future developments.
## 2. Geologic Setting
### 2.1. Location and Stratigraphy
The Dehui fault depression is located in the southeast uplift of the Songliao Basin (Figure1(a); [5]). It is a sedimentary fault depression with synrift and thermal subsidence double-layered structure developed on the basement of Upper Paleozoic metamorphic rock series, covering an area of 4053 km2 (Figure 1(b)). The fault depression generally presents an NNE trending double fault-controlled graben, which is cut by NNE trending faults, forming a structural pattern of horst-graben-steps. It can be further divided into seven secondary structural units, including the Nong’an Graben, Huajia Subdepression, Baojia Subdepression, Nong’an’nan Subdepression, Helong Subdepression, Lanjia Subdepression, and Longwang Subdepression (Figure 1(c)).Figure 1
(a) Geographic location of the Songliao Basin. (b) Location of Dehui Depression in the Southern Songliao Basin. (c) Tectonic units of the Dehui Depression. (d) Generalized Mesozoic-Cenozoic stratigraphy of the Dehui depression, showing the formation thickness, lithology, and stage of tectonic evaluation.
(a)(b)(c)(d)Since the Mesozoic, the fault depression has undergone several tectonic activities of subsidence and uplift, and the Mesozoic and Cenozoic strata with a thickness of more than 5000 m have been deposited [23]. The strata developed from bottom to top in this area are the Carboniferous-Permian basement, the lower Cretaceous Huoshiling Formation (K1hs), Shahezi Formation (K1sh), Yingcheng Formation (K1yc), Denglouku Formation (K1d), Quantou Formation (K1q), the upper Cretaceous Qingshankou Formation (K2qn), Yaojia Formation (K2y), Nenjiang Formation (K2n), and Quaternary (Figure 1(d)), among which the Yingcheng Formation is the target layer of this study.
### 2.2. Volcanic Activities
During the period of the Yingcheng Formation deposition, numerous volcanic activities happened, leading to the creation of faults in Dehui fault depression [28]. By employing the superposition relationship between volcanic rock mass from 3D seismic data and zircon dating, three periods of volcanic activities in this area were recognized, which first increased and then gradually weakened. During the initial stages of volcanic activity, eruptions mainly occurred at the edge of the depression and near the faults which controlled the depression. Large volcanic groups developed, and later, sedimentary strata covered the volcanic rocks [5]. Drilling through these volcanic rocks confirmed mushroom-like structures with obvious volcanic channels dated 118 Ma, which marks the onset of the Yingcheng Formation. The middle stage of the volcanic activity is dominated by eruption of pyroclastic facies and magma flows along the volcanic channels and faults that were formed during the first stage of volcanism forming a large area of pyroclastic shield. This period is dated back to 115 Ma, which represents the middle stage of the creation of the Yingcheng Formation. Finally, in the late period of volcanic activity, volcanic intrusions were formed, and because of its weakened energy, the magma could not reach the surface and only cut through the strata. This took place about 103 Ma, which coincides with the depositional period of the Denglouku Formation (Figure 2; [28]).Figure 2
The seismic profile shows the volcanic activity of the K1yc in the Dehui Depression; location of the profile is shown in Figure 1 (modified from [28]).
### 2.3. Sedimentary Facies
During the deposition of the Yingcheng Formation, the Songliao Basin was tectonically active, and a number of faults were developed. The Yingcheng Formation is divided into two members while the first member is strongly affected by volcanism, and a large set of volcanic formations are developed around the Dehui fault depression [5]. At the margins of the fault depression, a set of fan-delta and lacustrine facies were deposited, and a mixed sequence of volcanic and clastic sedimentary strata was formed. The sedimentary facies in the study area are mainly fan-deltaic, lacustrine, and nearshore subaqueous fan (Figure 3). The fan-delta is widely developed in the eastern and western margins of the depression, while the braided river delta plain is dominant in the south, and the lacustrine facies center is located in the northeast of the depression. During the sedimentation process, the supply of sediment was hindered by the influence of multiple volcanic activities, which limited the range and thickness of sand bodies that were deposited in the northeast.Figure 3
The sedimentary facies map of the K1yc in the Dehui Depression shows the distribution of volcanic and sedimentary rocks.
### 2.4. Petroleum System
Three sets of petroleum source-reservoir-seal systems are identified in the study area [5, 25]. In the K1yc, K1sh, and K1h, thick organic-rich mudstones with a high thermal maturity have been proven to be the effective source for the gas. Meanwhile, fine sandstone, siltstone, conglomerate, and volcanic rocks formed during volcanic activity are widely spread in the K1yc, K1sh, and K1h and act as the reservoir for natural gas accumulation. Thick mudstone developed in the K2d is almost distributed in the entire southern Songliao Basin and could serve as the regional seal, and mudstone layers in each formation mentioned above can serve as the local caprocks [7].
## 2.1. Location and Stratigraphy
The Dehui fault depression is located in the southeast uplift of the Songliao Basin (Figure1(a); [5]). It is a sedimentary fault depression with synrift and thermal subsidence double-layered structure developed on the basement of Upper Paleozoic metamorphic rock series, covering an area of 4053 km2 (Figure 1(b)). The fault depression generally presents an NNE trending double fault-controlled graben, which is cut by NNE trending faults, forming a structural pattern of horst-graben-steps. It can be further divided into seven secondary structural units, including the Nong’an Graben, Huajia Subdepression, Baojia Subdepression, Nong’an’nan Subdepression, Helong Subdepression, Lanjia Subdepression, and Longwang Subdepression (Figure 1(c)).Figure 1
(a) Geographic location of the Songliao Basin. (b) Location of Dehui Depression in the Southern Songliao Basin. (c) Tectonic units of the Dehui Depression. (d) Generalized Mesozoic-Cenozoic stratigraphy of the Dehui depression, showing the formation thickness, lithology, and stage of tectonic evaluation.
(a)(b)(c)(d)Since the Mesozoic, the fault depression has undergone several tectonic activities of subsidence and uplift, and the Mesozoic and Cenozoic strata with a thickness of more than 5000 m have been deposited [23]. The strata developed from bottom to top in this area are the Carboniferous-Permian basement, the lower Cretaceous Huoshiling Formation (K1hs), Shahezi Formation (K1sh), Yingcheng Formation (K1yc), Denglouku Formation (K1d), Quantou Formation (K1q), the upper Cretaceous Qingshankou Formation (K2qn), Yaojia Formation (K2y), Nenjiang Formation (K2n), and Quaternary (Figure 1(d)), among which the Yingcheng Formation is the target layer of this study.
## 2.2. Volcanic Activities
During the period of the Yingcheng Formation deposition, numerous volcanic activities happened, leading to the creation of faults in Dehui fault depression [28]. By employing the superposition relationship between volcanic rock mass from 3D seismic data and zircon dating, three periods of volcanic activities in this area were recognized, which first increased and then gradually weakened. During the initial stages of volcanic activity, eruptions mainly occurred at the edge of the depression and near the faults which controlled the depression. Large volcanic groups developed, and later, sedimentary strata covered the volcanic rocks [5]. Drilling through these volcanic rocks confirmed mushroom-like structures with obvious volcanic channels dated 118 Ma, which marks the onset of the Yingcheng Formation. The middle stage of the volcanic activity is dominated by eruption of pyroclastic facies and magma flows along the volcanic channels and faults that were formed during the first stage of volcanism forming a large area of pyroclastic shield. This period is dated back to 115 Ma, which represents the middle stage of the creation of the Yingcheng Formation. Finally, in the late period of volcanic activity, volcanic intrusions were formed, and because of its weakened energy, the magma could not reach the surface and only cut through the strata. This took place about 103 Ma, which coincides with the depositional period of the Denglouku Formation (Figure 2; [28]).Figure 2
The seismic profile shows the volcanic activity of the K1yc in the Dehui Depression; location of the profile is shown in Figure 1 (modified from [28]).
## 2.3. Sedimentary Facies
During the deposition of the Yingcheng Formation, the Songliao Basin was tectonically active, and a number of faults were developed. The Yingcheng Formation is divided into two members while the first member is strongly affected by volcanism, and a large set of volcanic formations are developed around the Dehui fault depression [5]. At the margins of the fault depression, a set of fan-delta and lacustrine facies were deposited, and a mixed sequence of volcanic and clastic sedimentary strata was formed. The sedimentary facies in the study area are mainly fan-deltaic, lacustrine, and nearshore subaqueous fan (Figure 3). The fan-delta is widely developed in the eastern and western margins of the depression, while the braided river delta plain is dominant in the south, and the lacustrine facies center is located in the northeast of the depression. During the sedimentation process, the supply of sediment was hindered by the influence of multiple volcanic activities, which limited the range and thickness of sand bodies that were deposited in the northeast.Figure 3
The sedimentary facies map of the K1yc in the Dehui Depression shows the distribution of volcanic and sedimentary rocks.
## 2.4. Petroleum System
Three sets of petroleum source-reservoir-seal systems are identified in the study area [5, 25]. In the K1yc, K1sh, and K1h, thick organic-rich mudstones with a high thermal maturity have been proven to be the effective source for the gas. Meanwhile, fine sandstone, siltstone, conglomerate, and volcanic rocks formed during volcanic activity are widely spread in the K1yc, K1sh, and K1h and act as the reservoir for natural gas accumulation. Thick mudstone developed in the K2d is almost distributed in the entire southern Songliao Basin and could serve as the regional seal, and mudstone layers in each formation mentioned above can serve as the local caprocks [7].
## 3. Samples and Methods
A total of 235 core samples from the K1yc were selected in this study (location of sampling well is shown in Figure 1(c)). From these, 97 mudstone samples were selected for Rock-Eval pyrolysis while 16 were chosen for vitrinite reflectance measurements to characterize the source rock. Moreover, 63 samples from the volcanic and 75 from the tight sandstone were tested to characterize petrophysical properties of the reservoir. Thin sections were prepared from all reservoir samples and analyzed by using a petrographic microscope Leica DM2700P to observe pore types.A total of 97 core samples were pulverized to 100-mesh screen in preparation for geochemical analysis and TOC measurement. The TOC was measured using a LECO CS-230 analyzer, and programmed pyrolysis was performed using a Rock-Eval 6 plus analyzer to obtainS1 (free hydrocarbons), S2 (petroleum generated by pyrolysis), and Tmax (the temperature at peak evolution) by default method [29, 30].Vitrinite reflectance (Ro) was measured using a microphotometer, and this analysis was performed at the Geochemistry Laboratory of the Northeast Petroleum University. Analysis was performed with an oil immersion objective under normal white light at a wavelength of 546 mm. A mean value was calculated for each sample on the basis of 12-20 measurements on vitrinite [18].Porosity of core samples (63 volcanic and 75 tight sandstone) was done using core test system AP608 analyzer at Jilin University. The samples were drilled in cylinders with the size of1″×4″, vacuum-dried at 180°C, and then analyzed using a minipermeameter for air permeability measurements by nitrogen (air). The experimental temperature and humidity were 24°C and 35%, respectively [31].
## 4. Results
### 4.1. Geochemistry of Source Rock
Total organic carbon (TOC) in the source rocks of the Yingcheng Formation ranges from 0.22 wt.% to 18.85 wt.%, with an average value of 3.24 wt. %, of which 85.6% is higher than 1.0 wt.%, and 60.8% is higher than 2.0 wt.%, in 97 samples that were tested (Table1). Pyrolysis data was used to determine the type of organic matter following geochemical charts. According to Figures 4 and 5, the pyrolysis data of source rocks plotted in the van Krevelen diagram (HI vs. Tmax and S2 vs. TOC) are pointing to type III, and a small portion of type IV inert organic matter. Therefore, the organic matter type of the source rocks of the Yingcheng Formation is type III, which dominantly generates gas. The samples with abnormal Tmax which is demonstrated in Figure 4 have relatively higher PI index, indicating the presence of bitumen remanence in shale samples.Table 1
Results of Rock-Eval pyrolysis.
Depth (m)TOC (%)S1 (mg/g)S2 (mg/g)Tmax (°C)S1+S2 (mg/g)HI (mg HC/g TOC)PI2856.602.282.531.85486.004.3881.140.582856.653.240.631.57490.002.2048.460.292857.002.671.111.58490.002.6959.180.412857.352.020.361.05489.001.4151.980.262857.703.190.941.86489.002.8058.310.342858.202.430.651.31491.001.9653.910.332858.703.030.731.63489.002.3653.800.312859.491.960.812.47488.003.28126.020.252859.501.690.510.95490.001.4656.210.352860.002.060.541.06488.001.6051.460.342860.703.330.290.68490.000.9720.420.302861.400.220.020.14482.000.1663.640.132861.902.180.521.24488.001.7656.880.302862.202.120.330.96489.001.2945.280.262862.702.120.531.08490.001.6150.940.332863.302.120.391.28488.001.6760.380.232863.802.170.361.14490.001.5052.530.242864.002.130.231.18487.001.4155.400.162864.402.390.381.20490.001.5850.210.242864.901.400.140.68489.000.8248.570.172865.201.590.230.87488.001.1054.720.212865.703.100.611.77490.002.3857.100.262866.201.970.401.08490.001.4854.820.272866.801.950.221.02488.001.2452.310.182867.002.190.311.19488.001.5054.340.212867.202.000.391.00488.001.3950.000.282867.901.400.260.87487.001.1362.140.232868.201.800.430.99488.001.4255.000.302868.701.770.350.98487.001.3355.370.262869.403.180.461.80489.002.2656.600.202869.701.260.140.72488.000.8657.140.162870.201.160.220.66489.000.8856.900.252870.501.300.110.72488.000.8355.380.132885.502.740.681.53490.002.2155.840.313053.951.690.351.87484.002.22110.650.163056.000.780.220.61494.000.8378.210.273056.252.080.251.23495.001.4859.130.173057.550.850.241.09396.001.33128.240.183057.850.580.030.39488.000.4267.240.073059.380.220.010.15488.000.1668.180.063060.450.380.041.07456.001.11281.580.043063.141.130.081.50472.001.58132.740.053063.431.730.162.72462.002.88157.230.063065.500.760.081.46443.001.54192.110.053377.981.400.060.42519.000.4830.000.133395.940.610.040.47487.000.5177.050.083396.900.620.050.41493.000.4666.130.112306.001.512.201.15458.003.3576.160.662307.001.836.951.18505.008.1364.480.852316.000.341.900.34387.002.24100.000.852326.000.342.330.33385.002.6697.060.882820.000.511.060.35485.001.4168.630.752850.000.510.910.31484.001.2260.780.752890.000.431.930.36486.002.2983.720.842910.003.844.502.83487.007.3373.700.612920.003.333.662.23486.005.8966.970.622930.002.722.741.80488.004.5466.180.602940.004.241.192.64489.003.8362.260.312960.006.821.946.47485.008.4194.870.232980.005.941.435.19485.006.6287.370.223005.008.332.768.62485.0011.38103.480.243020.001.641.291.23488.002.5275.000.513035.001.561.681.04490.002.7266.670.623217.541.600.100.49513.000.5930.630.173677.601.280.140.49570.000.6338.280.222665.002.503.352.76465.006.11110.400.552680.0012.904.3117.22472.0021.53133.490.202685.003.532.803.59473.006.39101.700.442690.008.423.569.97473.0013.53118.410.262710.0017.784.2524.81473.0029.06139.540.152725.009.656.8516.05475.0022.90166.320.302880.002.061.011.73483.002.7483.980.372898.002.321.591.84485.003.4379.310.462940.005.516.424.99488.0011.4190.560.562970.001.844.881.50488.006.3881.520.762990.001.935.081.68492.006.7687.050.753010.004.824.184.19489.008.3786.930.503015.0018.857.7916.80489.0024.5989.120.323020.0018.716.7114.31491.0021.0276.480.323060.003.9312.593.42493.0016.0187.020.793078.0013.4614.7513.15492.0027.9097.700.533215.003.8210.342.26504.0012.6059.160.823420.002.000.070.46434.000.5323.000.133830.007.089.538.45483.0017.98119.350.532785.003.1820.923.06356.0023.9896.230.872795.002.8818.552.72351.0021.2794.440.872805.003.2221.383.30357.0024.68102.480.872815.003.2017.153.21360.0020.36100.310.842825.003.3919.153.11358.0022.2691.740.862835.003.5623.333.40364.0026.7395.510.872845.003.3018.993.41364.0022.40103.330.852855.003.1516.833.14363.0019.9799.680.842865.003.1611.402.66344.0014.0684.180.812870.002.786.641.63329.008.2758.630.802878.002.5911.152.35344.0013.5090.730.832885.003.9714.083.09493.0017.1777.830.822890.003.3421.382.87341.0024.2585.930.88TOC: total organic carbon content;S1: free hydrocarbons present in the rock; S2: petroleum generated by pyrolysis; S1+S2: genetic potential; Tmax: the temperature at peak evolution of S2 hydrocarbons (°C); HI: hydrogen index, S2dividedbyTOC×100; PI: production index, S1/S1+S2.Figure 4
Plot of TOC (wt.%) vs. HI (mg HC/g TOC) of the K1yc (according to [35]).Figure 5
The TOC versusS2 plot for the K1yc source rock samples (according to [36]).The distribution of potential hydrocarbon generation capacity (S1+S2) ranges from 0.16 to 29.06 mg/g, with an average of 6.86 mg/g, among which 35.1% are higher than 6 mg/g, and 14.4% are higher than 20 mg/g. An overview of the samples exhibits that they generally represent a poor to good source rock (Figure 6(a)). The HI vs. TOC plot explains that most of the samples are located in the regions of very little to questionable gas (Figure 6(b)). Only parts of the samples are demonstrating to be a good source rock and to have fair gas generation potential with lower S2 at the higher maturations (Figure 6).Figure 6
(a) Plot of total organic carbon (TOC) vs. generative potential (S1+S2) of the K1yc (according to [37]). (b) Plot of TOC vs. HI of the K1yc in the study area (according to [38]).
(a)(b)
### 4.2. Maturation of Organic Matter
The maximum pyrolysis temperature (Tmax) of the source rocks of the Yingcheng Formation was measured between 329°C and 570°C, while most values are more than 470°C, inferring that the source rocks of the Yingcheng Formation are over mature in the gas generation window with the exclusion of the abnormal data under 400°C (Figure 7(a)). The measured vitrinite reflectance (Ro) values of source rocks in the Yingcheng Formation is positively correlated with the burial depth and increases as the formation becomes deeper (Figure 7(b)). Among these 16 samples that were inspected for Ro, except two that are shallower, the Ro was found more than 1.4%, while it appears to be more than 2.0% for samples buried deeper than 3000 m (Table 2). Collectively, the organic matter in the source rocks of the Yingcheng Formation in the study area has entered gas generation window and is highly overmatured.Figure 7
(a)Tmax and (b) Ro versus depth for the K1yc source rocks samples. Thermal maturity zones are divided according to Peters and Cassa [39].Table 2
Results of vitrinite reflectance experiment.
Well nameDepth (m)Ro (%)Num. measu.SDDS1112858.21.39200.16DS1112859.21.76190.04DS1112861.91.40200.14DS1113056.02.13200.15DS1113063.12.15200.11DS1113063.42.17200.14DS1113377.92.49200.16DS17-62518.91.29200.14DS17-62528.01.31200.12DS813085.42.12160.06DS813086.02.08120.06DS813092.02.15200.06DS833280.62.01200.13DS833690.22.38200.16DS833692.32.31170.05DS833692.32.40200.17Ro: vitrinite reflectance; Num. measu.: number of measured points; SD: standard deviation.
### 4.3. Petrophysical Properties
#### 4.3.1. Volcanic Reservoir
As shown in Figure2, volcanic rocks are presenting separate seismic reflections attributes compared to other sedimentary layers, making the interpretation of Yingcheng volcanic rocks based on seismic profiles much easier. Volcanic rocks of the Yingcheng Formation are mainly distributed in the northeast of the study area and are controlled by volcanic activities. Their thickness varies from 0 to 400 m and can reach more than 700 m locally (Figure 8). The porosity of the volcanic reservoir rocks of the Yingcheng Formation in the study area is between 3.0% and 14.8%, with an average value of 7.3%. The porosity distribution is approximately normal, with the main peak around 5%-8%, which also accounts for 74.6% of the entire samples. The permeability of the samples were measured between 0.0004 and 2.52 mD, while the 0.001 to 0.01 mD interval accounts for 43% of the total tested samples.Figure 8
Distribution of volcanic rock reservoir of the K1yc.The pore type of volcanic reservoir rocks is complex and varies but can roughly be divided into three types: (1) primary pores, (2) secondary pores, and (3) fractures based on observations on thin sections. The dominant type is secondary pores, mainly feldspar dissolution pores, which are mostly developed in tuff (Figure9(a)). Moreover, fractures that are formed by the structural stress are more dominant in dacite in the study area (Figures 9(b) and 9(c)) and occasionally observed in tuff (Figure 9(d)).Figure 9
Thin section observed by plane-polarized and light perpendicular-polarized light for volcanic reservoir samples for the K1yc. (a) 2700.0 m, tuff; (b) 2240.0 m, dacite; (c) 2240.9 m, dacite; (d) 2700.0 m, tuff.
(a)(b)(c)(d)
#### 4.3.2. Tight Sandstone Reservoir
Tight sandstone deposition is controlled by changes in the facies, mainly distributed in the delta front and plain subfacies in the northeast and northwestern areas of the fault depression, with a thickness of 0-400 m (Figure10). The thickness of sandstone facies in the middle of the fault depression is less than 100 m. Furthermore, the porosity of tight sandstone in the Yingcheng Formation in the study area was measured between 0.5% and 11.2%, with an average value of 5.1%, and its distribution is also approximately uniform. Comparing their porosity with the volcanic reservoir, the distribution of measured porosity values is relatively dispersed, and 2%-7% of porosity constitutes 69.3% of total collected data. In addition, the permeability of the samples was found to vary between 0.0008 and 3.17 mD, with the peak at 0.001 mD. Considering thin section analysis, the reservoir space in the study area is mainly intergranular pores, with a small amount of intragranular pores and microfractures (Figure 11).Figure 10
Distribution of tight sandstone reservoir of the K1yc.Figure 11
Thin section observed by plane-polarized and light perpendicular-polarized light for tight sandstone reservoir samples for the K1yc. (a) 2522 m, tuffaceous sandstone; (b) 2543 m, tuffaceous sandstone; (c) 2803.5 m, tuffaceous sandstone; (d) 2912.5 m, tuffaceous sandstone ((c) and (d) are referenced from [28]).
(a)(b)(c)(d)
## 4.1. Geochemistry of Source Rock
Total organic carbon (TOC) in the source rocks of the Yingcheng Formation ranges from 0.22 wt.% to 18.85 wt.%, with an average value of 3.24 wt. %, of which 85.6% is higher than 1.0 wt.%, and 60.8% is higher than 2.0 wt.%, in 97 samples that were tested (Table1). Pyrolysis data was used to determine the type of organic matter following geochemical charts. According to Figures 4 and 5, the pyrolysis data of source rocks plotted in the van Krevelen diagram (HI vs. Tmax and S2 vs. TOC) are pointing to type III, and a small portion of type IV inert organic matter. Therefore, the organic matter type of the source rocks of the Yingcheng Formation is type III, which dominantly generates gas. The samples with abnormal Tmax which is demonstrated in Figure 4 have relatively higher PI index, indicating the presence of bitumen remanence in shale samples.Table 1
Results of Rock-Eval pyrolysis.
Depth (m)TOC (%)S1 (mg/g)S2 (mg/g)Tmax (°C)S1+S2 (mg/g)HI (mg HC/g TOC)PI2856.602.282.531.85486.004.3881.140.582856.653.240.631.57490.002.2048.460.292857.002.671.111.58490.002.6959.180.412857.352.020.361.05489.001.4151.980.262857.703.190.941.86489.002.8058.310.342858.202.430.651.31491.001.9653.910.332858.703.030.731.63489.002.3653.800.312859.491.960.812.47488.003.28126.020.252859.501.690.510.95490.001.4656.210.352860.002.060.541.06488.001.6051.460.342860.703.330.290.68490.000.9720.420.302861.400.220.020.14482.000.1663.640.132861.902.180.521.24488.001.7656.880.302862.202.120.330.96489.001.2945.280.262862.702.120.531.08490.001.6150.940.332863.302.120.391.28488.001.6760.380.232863.802.170.361.14490.001.5052.530.242864.002.130.231.18487.001.4155.400.162864.402.390.381.20490.001.5850.210.242864.901.400.140.68489.000.8248.570.172865.201.590.230.87488.001.1054.720.212865.703.100.611.77490.002.3857.100.262866.201.970.401.08490.001.4854.820.272866.801.950.221.02488.001.2452.310.182867.002.190.311.19488.001.5054.340.212867.202.000.391.00488.001.3950.000.282867.901.400.260.87487.001.1362.140.232868.201.800.430.99488.001.4255.000.302868.701.770.350.98487.001.3355.370.262869.403.180.461.80489.002.2656.600.202869.701.260.140.72488.000.8657.140.162870.201.160.220.66489.000.8856.900.252870.501.300.110.72488.000.8355.380.132885.502.740.681.53490.002.2155.840.313053.951.690.351.87484.002.22110.650.163056.000.780.220.61494.000.8378.210.273056.252.080.251.23495.001.4859.130.173057.550.850.241.09396.001.33128.240.183057.850.580.030.39488.000.4267.240.073059.380.220.010.15488.000.1668.180.063060.450.380.041.07456.001.11281.580.043063.141.130.081.50472.001.58132.740.053063.431.730.162.72462.002.88157.230.063065.500.760.081.46443.001.54192.110.053377.981.400.060.42519.000.4830.000.133395.940.610.040.47487.000.5177.050.083396.900.620.050.41493.000.4666.130.112306.001.512.201.15458.003.3576.160.662307.001.836.951.18505.008.1364.480.852316.000.341.900.34387.002.24100.000.852326.000.342.330.33385.002.6697.060.882820.000.511.060.35485.001.4168.630.752850.000.510.910.31484.001.2260.780.752890.000.431.930.36486.002.2983.720.842910.003.844.502.83487.007.3373.700.612920.003.333.662.23486.005.8966.970.622930.002.722.741.80488.004.5466.180.602940.004.241.192.64489.003.8362.260.312960.006.821.946.47485.008.4194.870.232980.005.941.435.19485.006.6287.370.223005.008.332.768.62485.0011.38103.480.243020.001.641.291.23488.002.5275.000.513035.001.561.681.04490.002.7266.670.623217.541.600.100.49513.000.5930.630.173677.601.280.140.49570.000.6338.280.222665.002.503.352.76465.006.11110.400.552680.0012.904.3117.22472.0021.53133.490.202685.003.532.803.59473.006.39101.700.442690.008.423.569.97473.0013.53118.410.262710.0017.784.2524.81473.0029.06139.540.152725.009.656.8516.05475.0022.90166.320.302880.002.061.011.73483.002.7483.980.372898.002.321.591.84485.003.4379.310.462940.005.516.424.99488.0011.4190.560.562970.001.844.881.50488.006.3881.520.762990.001.935.081.68492.006.7687.050.753010.004.824.184.19489.008.3786.930.503015.0018.857.7916.80489.0024.5989.120.323020.0018.716.7114.31491.0021.0276.480.323060.003.9312.593.42493.0016.0187.020.793078.0013.4614.7513.15492.0027.9097.700.533215.003.8210.342.26504.0012.6059.160.823420.002.000.070.46434.000.5323.000.133830.007.089.538.45483.0017.98119.350.532785.003.1820.923.06356.0023.9896.230.872795.002.8818.552.72351.0021.2794.440.872805.003.2221.383.30357.0024.68102.480.872815.003.2017.153.21360.0020.36100.310.842825.003.3919.153.11358.0022.2691.740.862835.003.5623.333.40364.0026.7395.510.872845.003.3018.993.41364.0022.40103.330.852855.003.1516.833.14363.0019.9799.680.842865.003.1611.402.66344.0014.0684.180.812870.002.786.641.63329.008.2758.630.802878.002.5911.152.35344.0013.5090.730.832885.003.9714.083.09493.0017.1777.830.822890.003.3421.382.87341.0024.2585.930.88TOC: total organic carbon content;S1: free hydrocarbons present in the rock; S2: petroleum generated by pyrolysis; S1+S2: genetic potential; Tmax: the temperature at peak evolution of S2 hydrocarbons (°C); HI: hydrogen index, S2dividedbyTOC×100; PI: production index, S1/S1+S2.Figure 4
Plot of TOC (wt.%) vs. HI (mg HC/g TOC) of the K1yc (according to [35]).Figure 5
The TOC versusS2 plot for the K1yc source rock samples (according to [36]).The distribution of potential hydrocarbon generation capacity (S1+S2) ranges from 0.16 to 29.06 mg/g, with an average of 6.86 mg/g, among which 35.1% are higher than 6 mg/g, and 14.4% are higher than 20 mg/g. An overview of the samples exhibits that they generally represent a poor to good source rock (Figure 6(a)). The HI vs. TOC plot explains that most of the samples are located in the regions of very little to questionable gas (Figure 6(b)). Only parts of the samples are demonstrating to be a good source rock and to have fair gas generation potential with lower S2 at the higher maturations (Figure 6).Figure 6
(a) Plot of total organic carbon (TOC) vs. generative potential (S1+S2) of the K1yc (according to [37]). (b) Plot of TOC vs. HI of the K1yc in the study area (according to [38]).
(a)(b)
## 4.2. Maturation of Organic Matter
The maximum pyrolysis temperature (Tmax) of the source rocks of the Yingcheng Formation was measured between 329°C and 570°C, while most values are more than 470°C, inferring that the source rocks of the Yingcheng Formation are over mature in the gas generation window with the exclusion of the abnormal data under 400°C (Figure 7(a)). The measured vitrinite reflectance (Ro) values of source rocks in the Yingcheng Formation is positively correlated with the burial depth and increases as the formation becomes deeper (Figure 7(b)). Among these 16 samples that were inspected for Ro, except two that are shallower, the Ro was found more than 1.4%, while it appears to be more than 2.0% for samples buried deeper than 3000 m (Table 2). Collectively, the organic matter in the source rocks of the Yingcheng Formation in the study area has entered gas generation window and is highly overmatured.Figure 7
(a)Tmax and (b) Ro versus depth for the K1yc source rocks samples. Thermal maturity zones are divided according to Peters and Cassa [39].Table 2
Results of vitrinite reflectance experiment.
Well nameDepth (m)Ro (%)Num. measu.SDDS1112858.21.39200.16DS1112859.21.76190.04DS1112861.91.40200.14DS1113056.02.13200.15DS1113063.12.15200.11DS1113063.42.17200.14DS1113377.92.49200.16DS17-62518.91.29200.14DS17-62528.01.31200.12DS813085.42.12160.06DS813086.02.08120.06DS813092.02.15200.06DS833280.62.01200.13DS833690.22.38200.16DS833692.32.31170.05DS833692.32.40200.17Ro: vitrinite reflectance; Num. measu.: number of measured points; SD: standard deviation.
## 4.3. Petrophysical Properties
### 4.3.1. Volcanic Reservoir
As shown in Figure2, volcanic rocks are presenting separate seismic reflections attributes compared to other sedimentary layers, making the interpretation of Yingcheng volcanic rocks based on seismic profiles much easier. Volcanic rocks of the Yingcheng Formation are mainly distributed in the northeast of the study area and are controlled by volcanic activities. Their thickness varies from 0 to 400 m and can reach more than 700 m locally (Figure 8). The porosity of the volcanic reservoir rocks of the Yingcheng Formation in the study area is between 3.0% and 14.8%, with an average value of 7.3%. The porosity distribution is approximately normal, with the main peak around 5%-8%, which also accounts for 74.6% of the entire samples. The permeability of the samples were measured between 0.0004 and 2.52 mD, while the 0.001 to 0.01 mD interval accounts for 43% of the total tested samples.Figure 8
Distribution of volcanic rock reservoir of the K1yc.The pore type of volcanic reservoir rocks is complex and varies but can roughly be divided into three types: (1) primary pores, (2) secondary pores, and (3) fractures based on observations on thin sections. The dominant type is secondary pores, mainly feldspar dissolution pores, which are mostly developed in tuff (Figure9(a)). Moreover, fractures that are formed by the structural stress are more dominant in dacite in the study area (Figures 9(b) and 9(c)) and occasionally observed in tuff (Figure 9(d)).Figure 9
Thin section observed by plane-polarized and light perpendicular-polarized light for volcanic reservoir samples for the K1yc. (a) 2700.0 m, tuff; (b) 2240.0 m, dacite; (c) 2240.9 m, dacite; (d) 2700.0 m, tuff.
(a)(b)(c)(d)
### 4.3.2. Tight Sandstone Reservoir
Tight sandstone deposition is controlled by changes in the facies, mainly distributed in the delta front and plain subfacies in the northeast and northwestern areas of the fault depression, with a thickness of 0-400 m (Figure10). The thickness of sandstone facies in the middle of the fault depression is less than 100 m. Furthermore, the porosity of tight sandstone in the Yingcheng Formation in the study area was measured between 0.5% and 11.2%, with an average value of 5.1%, and its distribution is also approximately uniform. Comparing their porosity with the volcanic reservoir, the distribution of measured porosity values is relatively dispersed, and 2%-7% of porosity constitutes 69.3% of total collected data. In addition, the permeability of the samples was found to vary between 0.0008 and 3.17 mD, with the peak at 0.001 mD. Considering thin section analysis, the reservoir space in the study area is mainly intergranular pores, with a small amount of intragranular pores and microfractures (Figure 11).Figure 10
Distribution of tight sandstone reservoir of the K1yc.Figure 11
Thin section observed by plane-polarized and light perpendicular-polarized light for tight sandstone reservoir samples for the K1yc. (a) 2522 m, tuffaceous sandstone; (b) 2543 m, tuffaceous sandstone; (c) 2803.5 m, tuffaceous sandstone; (d) 2912.5 m, tuffaceous sandstone ((c) and (d) are referenced from [28]).
(a)(b)(c)(d)
## 4.3.1. Volcanic Reservoir
As shown in Figure2, volcanic rocks are presenting separate seismic reflections attributes compared to other sedimentary layers, making the interpretation of Yingcheng volcanic rocks based on seismic profiles much easier. Volcanic rocks of the Yingcheng Formation are mainly distributed in the northeast of the study area and are controlled by volcanic activities. Their thickness varies from 0 to 400 m and can reach more than 700 m locally (Figure 8). The porosity of the volcanic reservoir rocks of the Yingcheng Formation in the study area is between 3.0% and 14.8%, with an average value of 7.3%. The porosity distribution is approximately normal, with the main peak around 5%-8%, which also accounts for 74.6% of the entire samples. The permeability of the samples were measured between 0.0004 and 2.52 mD, while the 0.001 to 0.01 mD interval accounts for 43% of the total tested samples.Figure 8
Distribution of volcanic rock reservoir of the K1yc.The pore type of volcanic reservoir rocks is complex and varies but can roughly be divided into three types: (1) primary pores, (2) secondary pores, and (3) fractures based on observations on thin sections. The dominant type is secondary pores, mainly feldspar dissolution pores, which are mostly developed in tuff (Figure9(a)). Moreover, fractures that are formed by the structural stress are more dominant in dacite in the study area (Figures 9(b) and 9(c)) and occasionally observed in tuff (Figure 9(d)).Figure 9
Thin section observed by plane-polarized and light perpendicular-polarized light for volcanic reservoir samples for the K1yc. (a) 2700.0 m, tuff; (b) 2240.0 m, dacite; (c) 2240.9 m, dacite; (d) 2700.0 m, tuff.
(a)(b)(c)(d)
## 4.3.2. Tight Sandstone Reservoir
Tight sandstone deposition is controlled by changes in the facies, mainly distributed in the delta front and plain subfacies in the northeast and northwestern areas of the fault depression, with a thickness of 0-400 m (Figure10). The thickness of sandstone facies in the middle of the fault depression is less than 100 m. Furthermore, the porosity of tight sandstone in the Yingcheng Formation in the study area was measured between 0.5% and 11.2%, with an average value of 5.1%, and its distribution is also approximately uniform. Comparing their porosity with the volcanic reservoir, the distribution of measured porosity values is relatively dispersed, and 2%-7% of porosity constitutes 69.3% of total collected data. In addition, the permeability of the samples was found to vary between 0.0008 and 3.17 mD, with the peak at 0.001 mD. Considering thin section analysis, the reservoir space in the study area is mainly intergranular pores, with a small amount of intragranular pores and microfractures (Figure 11).Figure 10
Distribution of tight sandstone reservoir of the K1yc.Figure 11
Thin section observed by plane-polarized and light perpendicular-polarized light for tight sandstone reservoir samples for the K1yc. (a) 2522 m, tuffaceous sandstone; (b) 2543 m, tuffaceous sandstone; (c) 2803.5 m, tuffaceous sandstone; (d) 2912.5 m, tuffaceous sandstone ((c) and (d) are referenced from [28]).
(a)(b)(c)(d)
## 5. Discussion
### 5.1. Volcanic Effects on Hydrocarbon Generation
Volcanic intrusions have increased the temperature and pressure of the Yingcheng Formation and promoted the generation and expulsion of hydrocarbon in the source rocks [32]. Bulk geochemical data sets in this study show that deeply buried source rocks of the Yingcheng Formation in the Songliao Basin are widely developed and have good hydrocarbon generation potential. These source rocks are mostly type III kerogen with high TOC content. Additionally, measured Ro is generally greater than 1.4%, which is overmature, and on the onset of gas generation window. It is speculated that late volcanic intrusions provided sufficient heat source for the transformation of organic matter and caused the generation of natural gas in large quantities. The magmatic thermal field not only improves the geothermal gradient of the basin but also enhances the degree of thermal evolution of the organic matter compensating for the pressure and burial depth. This makes the threshold of gas generation to happen at the shallower depth, enhancing hydrocarbon generation [33]. In the volcanic gas reservoirs, the bitumen is common in micro fractures (Figures 9(b)–9(d)), referring to the abnormal high maturity which is consistent with the high paleo heat flow during the synrift phase [25]. This was caused by the upwelling of mantle plumes and the thinning of the crust, which were accompanied with volcanic activates before the Late Mesozoic-Cenozoic rapid cooling [34].
### 5.2. Pore Genesis of Reservoir
Based on the inspection of thin sections (Figure9), the volcanic reservoir of the Yingcheng Formation is mainly tuff and dacite, and the pores are mainly from mineral dissolution to create pores and microfractures. As shown in Figure 9, dissolution pores in the volcanic reservoirs such as tuff or dacite are mostly isolated and poorly connected. At the same time, the dissolution microfractures have a short extent, small width and irregularity, and limited in scope and number. Observation of thin sections also revealed the presence of asphaltene filling in the cracks.Tight sandstone reservoir of the Yingcheng Formation is generally dominated by intragranular dissolution pores, accounting for 89% of the total pores (Figure11). Among them, feldspar dissolution pores are the most developed ones, accounting for 35%, followed by lithic dissolution pores with 20%, intergranular dissolution pores 19%, and tuffaceous dissolution pores constituting 15% of the entire measured data. Likewise, a small number of intergranular pores, with 8% of the total pores measured, can also be responsible for a certain number of microfractures, around 3%. The intergranular dissolution pores are filled with autogenous albite, felsic particles, coniferous flake chlorite, and a small amount of illite and other clay minerals. The percentage of total surface porosity observed under the microscope is generally about 3%-10%. This kind of reservoir space is dominated by dissolved pores, nanoscale throat and underdeveloped reservoir characteristics, poor pore connectivity, easy-to-form isolated pores, resulting in “isolated pore space,” and dense characteristics of the reservoir with low permeability overall.The porosity of tight sandstone is much less than the volcanic rocks at the same depth (Figure12(a)). The porosity and permeability of sandstones has an obvious decreasing trend in the range of 2000-4500 m, which is caused by the compaction (Figure 12(b)). However, the porosity and permeability of volcanic reservoirs do not change much with depths, and the values are relatively concentrated, proving that compaction has little influence on the quality of the volcanic reservoir. In comparison with tight sandstone reservoir, the porosity of volcanic rock is relatively similar at shallower depth but generally improves with depth. The permeability of volcanic rocks is less than tight sandstones, but again it enhances with depth. That confirms how the effects of compaction on sandstones and volcanic rocks can be different, causing the sandstone to always have relatively better porosity and permeability at shallower depth, though it is important that one does not overlook the improvement of reservoir properties in the volcanic rock, too, as the formation gets deeper.Figure 12
(a) Porosity and (b) permeability versus the depth of volcanic rock reservoir and tight sandstone reservoir samples for the K1yc.
(a)(b)
### 5.3. Gas Accumulation Model in Volcanic Area
During the formation of the Yingcheng Formation in the study area, the basin was under extension [7]; thus, the controlling depression fault expanded eastward, and the sedimentary area gradually expanded, accompanied by volcanic activities for the entire period. The early subsidence center of the Yingcheng Formation is close to the boundary fault, making the deep extension area small. Moreover, volcanic activity mainly happened in the eastern gentle slope of the basin, which controlled sedimentation in the eastern boundary as well. Likewise, volcanic erosions provided additional sediment supply for the basin. In the middle stages of the Yingcheng Formation, the depocenter migrated northward to the east, the deep depression area expanded, and the volcanic rocks in the eastern gentle slope area generally eroded. At the end of the deposition of the Yingcheng Formation, the basin shrunk, and the deeper depression area was distributed along the boundary faults. Besides, the stratigraphic distribution range was large with limited thickness, and as the volcanism was strengthened, it affected the entire basin. This caused the strata to get dispersed between the volcanically active areas and the control-depression fault. Therefore, the reservoirs are scattered in the middle and upper parts of the Yingcheng Formation, which made the relationship between the source and the reservoir rocks stronger.During the earlier phases of volcanic eruption, larger volcanic bodies developed, which controlled the lateral boundaries of the trough of the Yingcheng Formation, to form an updip lateral block due to the tectonic activity that was later followed. The volcanic rocks mainly from tuff in the Yingcheng Formation formed during the middle phases of volcanism have constant thickness (ranging from 80 to 150 m, and more than 200 m locally) and wide lateral distribution, which played the role of the regional caprock [28]. These two volcanic activities promoted the formation of large traps and played a vital role in gas enrichment and preservation. Furthermore, the tuff layer is very dense, is free of fractures, and does not intrude and damage the gas reservoir, sealing the entire tight sandstone reservoir underneath. The early and middle volcanism surrounded the entire Yingcheng Formation and supported the formation of tight sandstone gas traps. The above two volcanic activities formed one block and one cap, which provided favorable trap conditions for tight sandstone gas reservoirs (Figure 13).Figure 13
Cross-section of gas accumulation in the K1yc; location of the profile is shown in Figure 1. In this section, suitable gas productive zones in the volcanic rock reservoir and tight sandstone reservoir are displayed (modified from [28]).On the other hand, volcanic rocks in some areas are replaced with sandstone bodies, to become complementary reservoir space. This combination of tight sandstone and volcanic gas reservoirs formed in the same horizon also produced economic quantities of gas. For example, well DS80 showed21.0×104m3/d flow rate in the 2650-3200 m interval, well DS33, 3.3×104m3/d and 1.6×104m3/d in two separate intervals, and well DS83, 8.0×104m3/d of high-yielding flow in the upper volcanic zone of the reservoir (Figure 13).
## 5.1. Volcanic Effects on Hydrocarbon Generation
Volcanic intrusions have increased the temperature and pressure of the Yingcheng Formation and promoted the generation and expulsion of hydrocarbon in the source rocks [32]. Bulk geochemical data sets in this study show that deeply buried source rocks of the Yingcheng Formation in the Songliao Basin are widely developed and have good hydrocarbon generation potential. These source rocks are mostly type III kerogen with high TOC content. Additionally, measured Ro is generally greater than 1.4%, which is overmature, and on the onset of gas generation window. It is speculated that late volcanic intrusions provided sufficient heat source for the transformation of organic matter and caused the generation of natural gas in large quantities. The magmatic thermal field not only improves the geothermal gradient of the basin but also enhances the degree of thermal evolution of the organic matter compensating for the pressure and burial depth. This makes the threshold of gas generation to happen at the shallower depth, enhancing hydrocarbon generation [33]. In the volcanic gas reservoirs, the bitumen is common in micro fractures (Figures 9(b)–9(d)), referring to the abnormal high maturity which is consistent with the high paleo heat flow during the synrift phase [25]. This was caused by the upwelling of mantle plumes and the thinning of the crust, which were accompanied with volcanic activates before the Late Mesozoic-Cenozoic rapid cooling [34].
## 5.2. Pore Genesis of Reservoir
Based on the inspection of thin sections (Figure9), the volcanic reservoir of the Yingcheng Formation is mainly tuff and dacite, and the pores are mainly from mineral dissolution to create pores and microfractures. As shown in Figure 9, dissolution pores in the volcanic reservoirs such as tuff or dacite are mostly isolated and poorly connected. At the same time, the dissolution microfractures have a short extent, small width and irregularity, and limited in scope and number. Observation of thin sections also revealed the presence of asphaltene filling in the cracks.Tight sandstone reservoir of the Yingcheng Formation is generally dominated by intragranular dissolution pores, accounting for 89% of the total pores (Figure11). Among them, feldspar dissolution pores are the most developed ones, accounting for 35%, followed by lithic dissolution pores with 20%, intergranular dissolution pores 19%, and tuffaceous dissolution pores constituting 15% of the entire measured data. Likewise, a small number of intergranular pores, with 8% of the total pores measured, can also be responsible for a certain number of microfractures, around 3%. The intergranular dissolution pores are filled with autogenous albite, felsic particles, coniferous flake chlorite, and a small amount of illite and other clay minerals. The percentage of total surface porosity observed under the microscope is generally about 3%-10%. This kind of reservoir space is dominated by dissolved pores, nanoscale throat and underdeveloped reservoir characteristics, poor pore connectivity, easy-to-form isolated pores, resulting in “isolated pore space,” and dense characteristics of the reservoir with low permeability overall.The porosity of tight sandstone is much less than the volcanic rocks at the same depth (Figure12(a)). The porosity and permeability of sandstones has an obvious decreasing trend in the range of 2000-4500 m, which is caused by the compaction (Figure 12(b)). However, the porosity and permeability of volcanic reservoirs do not change much with depths, and the values are relatively concentrated, proving that compaction has little influence on the quality of the volcanic reservoir. In comparison with tight sandstone reservoir, the porosity of volcanic rock is relatively similar at shallower depth but generally improves with depth. The permeability of volcanic rocks is less than tight sandstones, but again it enhances with depth. That confirms how the effects of compaction on sandstones and volcanic rocks can be different, causing the sandstone to always have relatively better porosity and permeability at shallower depth, though it is important that one does not overlook the improvement of reservoir properties in the volcanic rock, too, as the formation gets deeper.Figure 12
(a) Porosity and (b) permeability versus the depth of volcanic rock reservoir and tight sandstone reservoir samples for the K1yc.
(a)(b)
## 5.3. Gas Accumulation Model in Volcanic Area
During the formation of the Yingcheng Formation in the study area, the basin was under extension [7]; thus, the controlling depression fault expanded eastward, and the sedimentary area gradually expanded, accompanied by volcanic activities for the entire period. The early subsidence center of the Yingcheng Formation is close to the boundary fault, making the deep extension area small. Moreover, volcanic activity mainly happened in the eastern gentle slope of the basin, which controlled sedimentation in the eastern boundary as well. Likewise, volcanic erosions provided additional sediment supply for the basin. In the middle stages of the Yingcheng Formation, the depocenter migrated northward to the east, the deep depression area expanded, and the volcanic rocks in the eastern gentle slope area generally eroded. At the end of the deposition of the Yingcheng Formation, the basin shrunk, and the deeper depression area was distributed along the boundary faults. Besides, the stratigraphic distribution range was large with limited thickness, and as the volcanism was strengthened, it affected the entire basin. This caused the strata to get dispersed between the volcanically active areas and the control-depression fault. Therefore, the reservoirs are scattered in the middle and upper parts of the Yingcheng Formation, which made the relationship between the source and the reservoir rocks stronger.During the earlier phases of volcanic eruption, larger volcanic bodies developed, which controlled the lateral boundaries of the trough of the Yingcheng Formation, to form an updip lateral block due to the tectonic activity that was later followed. The volcanic rocks mainly from tuff in the Yingcheng Formation formed during the middle phases of volcanism have constant thickness (ranging from 80 to 150 m, and more than 200 m locally) and wide lateral distribution, which played the role of the regional caprock [28]. These two volcanic activities promoted the formation of large traps and played a vital role in gas enrichment and preservation. Furthermore, the tuff layer is very dense, is free of fractures, and does not intrude and damage the gas reservoir, sealing the entire tight sandstone reservoir underneath. The early and middle volcanism surrounded the entire Yingcheng Formation and supported the formation of tight sandstone gas traps. The above two volcanic activities formed one block and one cap, which provided favorable trap conditions for tight sandstone gas reservoirs (Figure 13).Figure 13
Cross-section of gas accumulation in the K1yc; location of the profile is shown in Figure 1. In this section, suitable gas productive zones in the volcanic rock reservoir and tight sandstone reservoir are displayed (modified from [28]).On the other hand, volcanic rocks in some areas are replaced with sandstone bodies, to become complementary reservoir space. This combination of tight sandstone and volcanic gas reservoirs formed in the same horizon also produced economic quantities of gas. For example, well DS80 showed21.0×104m3/d flow rate in the 2650-3200 m interval, well DS33, 3.3×104m3/d and 1.6×104m3/d in two separate intervals, and well DS83, 8.0×104m3/d of high-yielding flow in the upper volcanic zone of the reservoir (Figure 13).
## 6. Conclusion
(1)
The organic carbon content of the source rocks of the Yingcheng Formation in Dehui fault depression varies from 0.22 wt.% to 18.85 wt.%, with an average of 3.05 wt.%. The distribution of potential hydrocarbon generation (S1+S2) was found from 0.16 to 29.06 mg/g, with an average of 6.21 mg/g. Additionally, organic matter is mainly type III and at the high-overmaturity, representing favorable conditions for gas generation(2)
The thickness of volcanic reservoir in the study area is 0-400 m, the porosity is 3.0%-14.8%, the permeability is 0.0004-2.52 mD, and pore types are mainly secondary dissolved pores and fractures. Moreover, the thickness of the tight sandstone reservoir is 0-400 m, the porosity is 0.5%-11.2%, and the permeability is 0.0008-3.17 mD. Pore types are generally intergranular pores, with a small amount of intragranular pores and microfractures(3)
Late volcanic activity of the Yingcheng Formation in the study area provided sufficient heat source for the organic matter transformation and promoted the generation of natural gas in large quantities(4)
The petrophysical properties of the tight sandstone reservoir deteriorated significantly with depth and are affected by compaction notably, while the petrophysical properties of volcanic reservoir do not vary much as the formation get deeper representing more homogeneous characteristics. At the same time, secondary pores formed by late dissolution of pyroclasts formed by volcanic activities also provided storage space for gas accumulation(5)
Volcanic rocks that are formed during the early and middle phases of the Yingcheng Formation development occupied the sedimentary space, which worked against the deposition of sand bodies to some extent. However, volcanic rocks became regional seals as part of the tight sandstone gas trap. Finally, the combination of volcanic rocks and tight sandstones has created a complex petroleum system for the accumulation and preservation of gas in the basin.
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*Source: 2900224-2021-09-30.xml* | 2021 |
# Supervision Strategy Analysis on Price Discrimination of E-Commerce Company in the Context of Big Data Based on Four-Party Evolutionary Game
**Authors:** Meng Xiao
**Journal:** Computational Intelligence and Neuroscience
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2900286
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## Abstract
This paper focuses on the phenomenon of “big data killing” implied in e-commerce and discusses how to take the government as the lead to coordinately supervise the price discrimination behavior of e-commerce companies towards loyal customers. First, the four-party evolutionary game model of the government regulatory department, e-commerce platform, e-commerce company, and consumer is built. Second, the stability of the strategy choice of each game subject is analyzed. On this basis, the evolutionary stable strategy in the system based on First Law of Lyapunov is explored. Finally, the influences of key elements on system evolution are simulated and analyzed by MATLAB2021. Results demonstrate that (1) the government supervision mechanism can effectively supervise the price discrimination of e-commerce company based on big data to loyal customers; (2) when the government chooses the strict supervision strategy, reducing the information supervision cost of the e-commerce platform and the strict supervision cost of the government enable the government and the e-commerce platform to coordinate supervision and make the e-commerce company incline to choose the nondifferential pricing strategy; (3) when the government chooses the loose supervision strategy, reducing the information supervision cost of the e-commerce platform and increasing the probability of consumer discovering differential pricing and the penalties for differential pricing of e-commerce company enable the e-commerce platform and consumer to coordinate supervision, and make the e-commerce company incline to choose the nondifferential pricing strategy. The results of this study can provide theoretical guidance for the government and companies to make beneficial strategic decisions in the development of e-commerce.
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## Body
## 1. Introduction
With the rise of big data, e-commerce is becoming more and more prosperous. E-commerce can bring convenience to consumers with a variety of options and also collect consumer consumption data and draw user portraits by using big data technology [1]. While the application of algorithms injects new growth drivers into social and economic development, problems caused by the unreasonable application of algorithms such as algorithm discrimination, “big data killing,” and inducing addiction also profoundly affect the normal communication in the market and destroy the market order. Online supply chain stores have different pricing based on user location. On some online booking websites, the price of hotel rooms for Apple customer is higher than that for Windows customer. The well-known e-commerce company, Amazon, was found to use big data to “kill regular” [2]. It priced for different consumers according to their information and purchasing data on the platform. Loyal customers made purchase transactions based on their trust and path dependence on the Amazon platform, but due to the asymmetry of information in the transaction process, some regulars pay higher prices than strangers. This “big data killing” behavior has exposed the hidden dangers of moral hazard in the e-commerce market and makes the industry encounter an unprecedented crisis of trust. “Big data killing” has become an urgent problem to be solved in the fast development of online business [3].The essence of big data killing is price discrimination. Price discrimination refers to formulating different price strategies for different customer groups. However, in traditional business, both “stranger” and “regular” may be discriminated against, while with the participation of algorithm technology, there are more “killing regular” in Internet business. Even in the process of “killing regular,” big data has become a necessary tool. Each platform will collect a lot of user information, and then the company uses technology to offer different prices and discounts for different customers based on the information. Traditionally, companies have not been able to predict the upper limit of the price that buyers want to pay, but based on the technology of big data, the companies can determine the maximum willing price with a high degree of accuracy with sophisticated algorithms [4]. As the collection of consumer data becomes more common, online companies are now more capable of price discrimination than ever [5]. As customer of the Internet commercial company, VIP customer with higher loyalty and stronger consumption power pay much more for the same service than new customers, but gain even lower service quality. Big data killing will cause a variety of harm. Moriarty [6] proposed that customer information is widely used in online retail pricing, and although the benefit of online retailers will increase, price discrimination can cause serious fairness concerns and even violation of regulations and laws. Antimonopoly issues in the digital economy, especially the antimonopoly issues of big data and discrimination algorithms, have been brought to the attention of experts and practitioners. “Killing regular” is algorithmic price discrimination, with which online platforms charge long-term customers higher prices. It is believed that this kind of price discrimination violates the law on antimonopoly and should be held accountable according to the relevant law. The Cyberspace Administration of China (CAC) issued the regulations on The Management of Algorithm Recommendation for Internet Information Services to regulate the “big data killing,” stepping into the era of strict supervision of the industry related to algorithm recommendation. The EU also prohibits discrimination on certain grounds and strictly regulates unfair business practices in B2C relationships [7].Although some studies have carried out related discussion on the problem of big data killing [2, 8], some solutions are proposed [9, 10]. However, existing studies are mostly limited to the pricing between e-commerce companies and consumers [11, 12], the strategic choice between e-commerce platform and consumer, and the supervision strategy choice between e-commerce platform and government [9, 13]. There are few systematic studies on the four-party strategy composed of multiple subjects related to “big data killing.” Therefore, this study establishes an evolutionary game model dominated by government supervision that affects the decision-making of consumer, e-commerce company, and platform, analyzes and simulates that different supervision costs of government and e-commerce platform, consumer discovery levels, and the penalties for differential pricing of e-commerce company affect system equilibrium, evolutionarily stable strategy, and the pricing strategy of e-commerce company, and also establishes the platform-consumer-government collaborative supervision mechanism for e-commerce company pricing behavior. This research contributes to curbing the “big data killing” behavior of e-commerce company, enhance consumers’ confidence in online shopping, and has a positive effect in promoting the development of e-commerce.
## 2. Related Literature
Existing research on price discrimination in e-commerce companies mainly focuses on three aspects: the prevalence of price discrimination by using customer information, the influence factors of price discrimination, and the supervision and management of price discrimination:On the prevalence of price discrimination by e-commerce companies using customer information, although many media outlets provide various evidence of price discrimination, most of them are not based on scientific and systematic methods. Therefore, scholars have researched whether e-commerce companies use big data to discriminate against consumers in price. Botta and Klaus [14] qualitatively proposed that algorithmic price discrimination is different from offline differential pricing and is related to the collection of consumer information, which is a unique feature of the digital economy. With the wide application of big data and the gradual deepening of algorithm technology, the e-commerce company can price discriminate against consumers with great precision [4], and these were confirmed empirically [4, 15]. The pricing ecosystem of the online platform is a dynamic pricing system [15]. Algorithmic price discrimination [16], artificial intelligence techniques, and digital system fingerprints [15] enable the e-commerce company to have the ability of price discrimination. Price discrimination is not only widespread in the field of commodity sales, and there are also discrimination and price difference by using customer information in the field of online car-hailing [8] and the field of advertising recommendation [7, 17]. While consumers benefit from accurate recommendations, sellers may use this information to discriminate on price. Thus, price discrimination is not favored by people [18].Scholars have done a lot of studies on the influence factors of price discrimination in e-commerce companies. Some scholars believe that the premise of “big data killing” is the information asymmetry between e-commerce company and customers [1]. Consumer information data is an influencing factor for the e-commerce company to be able to discriminate in price [19], such as consumer characteristics, location [14], etc., and these data also relate to consumers’ privacy [12]. Nuccio and Marco [20] studied how pricing technology and information transparency are changing merchants’ pricing behavior in online transactions. The price sensitivity and heterogeneity of consumers are factors that affect e-commerce company to set price differentials [11]. Some scholars have analyzed the effects of reference price and search cost on differential pricing and find that consumers’ search cost has become one of the obstacles affecting consumers’ online shopping, which has formed an unequal situation for consumers [21] and has become a tool for e-commerce companies to formulate differential prices [22, 23]. The target of “big data killing” of e-commerce companies is focused on loyal consumers, which has been confirmed by many scholars. For example, Tang et al. [24] found in the research on the group-buying market that with the improvement of consumer retention rate, the best strategy of sellers is changed from quality difference to price discrimination. Chandra and Lederman [25] argued that if consumers have differences in potential willingness to pay and brand loyalty, e-commerce companies may increase price differences among some consumers while reducing price differences among the other consumers. Although differential pricing is an important way for e-commerce companies to obtain profits [26], its focus on loyal consumers is contrary to the principle of fair pricing [24], which will reduce consumer satisfaction and create distrust [27, 28].After the problem of “big data killing” was exposed, it has been attracted widespread attention by scholars, and its supervision and governance have also become an important research topic. Bar-Gill [29] proposed that the normative evaluation of price discrimination depends on the object of discrimination, and the algorithmic price discrimination has the advantages to improve efficiency, but it will harm consumers, which should be governed by rules set by regulators to seriously exploit the potential of personalization. Yu and Li [9] also believed that consumers’ discovery and reporting of being “killed” is the mean to monitor price discrimination of e-commerce company. Xing et al. [3] found that when regulars account for a high proportion of platform customer, giving consumers the right to data portability can curb the phenomenon of “big data killing” to a certain extent. In addition to consumers’ self-discovery of price discrimination by the e-commerce company, many scholars believe that with the help of government supervision [13], increasing penalties and the commission coefficient of government departments [30] can effectively reduce the “killing regular” pricing tendency of e-commerce platforms. However, in the supervision process of existing research, there was little distinction between e-commerce platform and company, and the research is carried out in a mixed way. Most of the discussions focus on the pricing of e-commerce platforms known for its scale. Differential pricing of e-commerce company on the platform is rarely discussed separately, and there is still a lack of research considering multichannel collaborative supervision.Existing studies have adopted a variety of methods for the problem of price discrimination in the e-commerce company. For example, the dynamic pricing method is used in specific pricing. Lindgren et al. [31] studied dynamic pricing by intertemporal price discrimination theory and proposed that retailers should change prices randomly over time. Chevalier and Kashyap [32] proposed the method for aggregating prices when retailers use periodic sales to discriminate price against heterogeneous customers. Tremblay [5] designed more efficient Pareto price discrimination. Game methods are often used in the selection of pricing strategies. Choe et al. [33] analyzed pricing strategy with a two-stage dynamic game model. Zhou et al. [34] adopted two-stage game analysis on joint pricing and bandwidth demand optimization. On the game of price discrimination, the bounded rationality assumption in the evolutionary game makes the research more realistic [30], so many scholars use evolutionary game methods to study this problem [1, 13, 30, 35] and extended to multiple fields of online transactions, such as manufacturing business [36]. However, most studies are limited in the two-party game [22, 37], it is still unclear to analyze the relationship and role of e-commerce company, consumer, e-commerce platform, and the government in the “big data killing” problem system, and their decision-making mechanism needs further research.Therefore, as the price discrimination of e-commerce companies is generated with new technologies, the existing research on this phenomenon is still in the exploratory stage. Most perspectives of the previous research are from both sides of the transaction in traditional business, and there are few differences in the analysis of the e-commerce platform and the companies in the platform. Moreover, the supervision on the differential pricing of the e-commerce company using big data technology to the loyal customers is not very perfect, and some policies and supervision methods are still under discussion. This study systematically analyzes the government, e-commerce platform, e-commerce company, and consumer involved in the supervision of “big data killing,” which makes up for the insufficiency of the existing research and provides useful help for further regulating such behavior.
## 3. Materials and Methods
### 3.1. Problem Description
The e-commerce company will use the platform to collect consumer information during the operation in the network platform. Based on the information provided by the platform, e-commerce company analyzes consumers and raise prices by judging their consumption habits. The pricing strategy of “big data killing” is price discrimination caused by e-commerce company using the feature of opaque information in the online transaction process to different pricing of consumers through big data and complex algorithms. This kind of behavior will bring consumers’ distrust of e-commerce companies and e-commerce platforms, which is not conducive to the development of e-commerce. Therefore, both the government regulatory department and e-commerce platforms should take necessary measures to supervise the price discrimination behavior of e-commerce companies. This study mainly discusses the following three questions: (1) in the context of big data development, how can the government regulatory department take supervision measures to reduce the proportion of price discrimination by e-commerce company? (2) How can e-commerce platform be motivated to supervise information on e-commerce companies? (3) How can consumers be guided to actively safeguard their rights and interests and maintain consumption fairness.This study builds a multi-agent game model for the supervision of price discrimination in e-commerce companies involving the e-commerce platform, the e-commerce company, the consumer, and the government regulatory department. The logical relationship among four-party game subjects is shown in Figure1.Figure 1
Game model logic relationship of multisubject supervision on e-commerce company pricing.
### 3.2. Model Assumption
To build the multisubject supervision model of the e-commerce company pricing in the background of big data, the behavioral strategies of government regulatory department, e-commerce platform, e-commerce company, and consumer are studied, and the following assumptions are made.Assumption 1.
Government regulatory department, e-commerce platform, the e-commerce company, and consumer are selected as the game subjects. Each game subject is bounded rationality and pursues the maximization of their interests in e-commerce transactions. Due to the information asymmetry between game subjects, random behavior strategies, and interactive effects, the optimal strategy cannot be obtained through one game. It is necessary to continuously try and learn in multiple rounds of games to improve the strategy, to formulate the best match of behavioral decision. Therefore, the evolutionary game should be used to analyze the four-party equilibrium strategy. The proportion of e-commerce company implementing nondifferential pricing is represented asx (0 ≤ x ≤ 1), and the proportion of e-commerce company implementing differential pricing is denoted as (1 − x); the proportion of consumer loyalty is represented as y (0 ≤ y ≤ 1) and the proportion of consumer disloyalty is represented as (1 − y); the proportion of e-commerce platform to supervise company information is represented as z (0 ≤ z ≤ 1), and the proportion of e-commerce platform with information nonsupervision is denoted as (1 − z); the proportion of the government regulatory department strictly supervising e-commerce platform and company is denoted as r (0 ≤ r ≤ 1), and the proportion of loosely supervises e-commerce platform and the company is denoted as (1 − r).Assumption 2.
The benefit of nondifferential pricing of the e-commerce company isPn, and the basic benefit of differential pricing is Pd. When the e-commerce company implements differential pricing for loyal consumer, additional benefit ∆P can be obtained due to the increase in selling price, and Pd < Pn < Pd+∆P. The probability of loyal consumers discovering differential pricing of the e-commerce company is α. When consumer purchases goods, the utility obtained by the loyal consumer is Ul, and the utility obtained by the disloyal consumer is Ud, and Ul > Ud. The reputation value of the loyal consumer to the e-commerce company is Te and the reputation value of the loyal consumer to the e-commerce platform is Tp.Assumption 3.
When the government strictly supervises, if price discrimination of the e-commerce company is found, loyal consumers who are subject to differential pricing will be compensated with the compensation amount ofM; When the government loosely supervises, if the loyal consumer is the price-sensitive consumer, he may use Internet information for comparison and analysis, and then find that he has been “killed”. If the cost of reporting is small and the procedure is simple, the consumer will carry out to inform the government regulatory department, and then the e-commerce company must be forced to compensate the consumer. The consumer’s complaint cost is Cc.Assumption 4.
The normal benefit that the government obtains from the operation of the e-commerce platform isS. The cost of strict supervision by government departments is Cg. The social benefit obtained by the government is R if there is no price discrimination by the e-commerce company. If the government adopts the loose supervision policy, consumer complaints will bring social reputation loss as N. After receiving the information, the e-commerce company for price discrimination will be penalized by the government regulatory department, and the fine will be Ie.Assumption 5.
The price discrimination of e-commerce company depends on the information provided by the platform. The benefit of the platform reasonably providing information to the e-commerce company isW, and the cost of the platform information supervision on e-commerce company is Cp. When the e-commerce platform finds the price discrimination of e-commerce company on the consumer, the fine to e-commerce company is F. The e-commerce platform and consumers share this fine in the ratio of β and 1 − β. When the government finds price discrimination by the e-commerce company, it will impose the fine of Ip for the platform’s unfavorable supervision to e-commerce company information.
The parameters are described in Table1.Table 1
Parameter description.
ParameterDescriptionPnThe benefit of nondifferential pricing by e-commerce company to consumerPdThe benefit of differential pricing by e-commerce company to consumer∆PThe additional benefit of differential pricing by e-commerce company to the loyal consumerMCompensation of e-commerce company to the loyal consumer for differential pricingTeThe reputation value of the loyal consumer to e-commerce companyUlThe utility obtained by the loyal consumer from purchasing goodsUdThe utility obtained by the disloyal consumer from purchasing goodsCcThe cost of consumer complaintαProbability of loyal consumer discovering differential pricing under government loose supervision, andα∈0,1CgThe cost of strict supervision by the government regulatory departmentNSocial reputation loss caused by differential pricing under government loose supervisionRThe social benefit of nondifferential pricing under the government strict supervisionIeFine by government regulatory department for differential pricing to e-commerce companyIpFine by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricingSThe normal benefit obtained by the government from the operation of the e-commerce platformWThe benefit of the platform reasonably providing information to the e-commerce companyCpThe cost of the platform’s information supervision on the e-commerce companyFFines imposed by the platform to e-commerce company for differential pricing during information supervisionβThe proportion of the fine imposed by the e-commerce platform for differential pricing of e-commerce company,β∈0,1TpThe reputation value of the loyal consumer to the e-commerce platform
### 3.3. Model Framework
According to the above analysis, the mixed-strategy game matrix of the four-party game subjects of government regulatory department, e-commerce platform, e-commerce company, and consumer is shown in Table2.Table 2
Game model benefit matrix of government regulatory department, e-commerce platform, e-commerce company, and consumer
Strategy choiceE-commerce companyGovernment regulatory departmentStrict supervision,rLoose supervision, 1 −rLoyaltyyDisloyalty 1 −yLoyaltyyDisloyalty 1 −yE-commerce platformInformation supervisionzNondifferential pricingxPn + TePnPn + TePnUlUdUlUdW − Cp + TpW − CpW − Cp + TpW − CpS − Cg+RS − Cg + RSSDifferential pricing 1 −xPd + ∆P + Te − M − Ie − FPd − Ie − FPd + ∆P + Te − αM − αIe − FPd − FUl− ∆P + M + (1 − β)FUdUl − ∆P − Cc + αM + (1 − β)FUdW − Cp + βF + TpW − Cp + FW − Cp + βF + TpW − Cp + FS −Cg + IeS −Cg + IeS + αIe− NS − NInformation nonsupervision 1 −zNondifferential pricingxPn + TePnPn + TePnUlUdUlUdW + TpWW + TpWS −Cg + RS −Cg + RSSDifferential pricing 1 −xPd + ∆P + Te− M − IePd− IePd + ∆P + Te− αM − αIePdUl− ∆P + MUdUl− ∆P − Cc + αMUdW − Ip + TpW − IpW − αIp + TpWS −Cg + Ie + IpS −Cg+Ie + IpS+αIe+αIp− NS − N
### 3.4. Model Analysis
#### 3.4.1. Strategy Stability Analysis of the E-Commerce Company
Assuming that the expected benefit of the e-commerce company when choosing the nondifferential pricing strategy isU11, the expected benefit of the e-commerce company when choosing the differential pricing strategy is U12, and the average expected benefit of the e-commerce company is U1¯, which are defined as follows:(1)U11=yzrPn+Te+1−yzrPn+y1−zrPn+Te+1−y1−zrPn+yz1−rPn+Te+1−yz1−rPn+y1−z1−rPn+Te+1−y1−z1−rPn=Pn+yTe,U12=yzrPd+ΔP+Te−M−Ie−F+1−yzrPd−Ie−F+y1−zrPd+ΔP+Te−M−Ie+1−y1−zrPd−Ie+yz1−rPd+ΔP+Te−αM−αIe−F+1−yz1−rPd−F+y1−z1−rPd+ΔP+Te−αM−αIe+1−y1−z1−rPd=Pd+yΔP+Te−yM+Ier+1−rα−1−yrIe−zF,U1¯=xU11+1−xU12.According to the Malthusian dynamic equation, the replication dynamic equation of the e-commerce company is obtained as follows:(2)Fx=dxdt=xU11−U1¯=x1−xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.The first partial derivative ofF (x) for x is as follows:(3)Fx′x=1−2xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.Based on the stability theorem of differential equations, the e-commerce company implements the strategy of nondifferential pricing in the stable state must meet the conditions:Fx = 0, and Fx′x < 0.Proposition 1.
Whenr > r0, the stable strategy of the e-commerce company is nondifferential pricing; when r < r0, the stable strategy of the e-commerce company is differential pricing; when r = r0, the e-commerce company cannot determine the stable strategy. Where the threshold is as follows:(4)r0=Pd+yΔP−Pn−αyM+Ie−zF1−αyM+1−αyIe.Proof.
AssumeHr=Pn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF, when yM−αM+Ie>0, ∂H/∂r > 0, then H (r) is considered to be an increasing function of r. When r > r0, H (r) > 0, Fx|x=1=0, and Fx′x|x=1<0, so x = 1 has stability; When r < r0, H (r) < 0, Fx|x=0=0, and Fx′x|x=0<0, so x = 0 has stability; when r = r0, H (r) = 0, Fx=0, and Fx′x=0, so x is stable at all levels in the range of 0 to 1, that is, the company’s strategy does not change over time, regardless of the proportion of company choosing to price differentially.
Proposition1 states that the increase of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from differential pricing to nondifferential pricing; Similarly, the decline of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from nondifferential pricing to differential pricing. Therefore, the government’s strict supervision for e-commerce company is essential, and the government should take measures to improve strict supervision for the e-commerce company.
Based on Proposition1, the phase diagram of the strategy evolution of e-commerce company is shown in Figure 2.
Inference 1: with the increase of the value ofPn, M, Ie, F, and α, the e-commerce company is more inclined to implement the nondifferential pricing strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Pd and ∆P, the e-commerce company is more inclined to implement the differential pricing strategy. It shows that the proportion of e-commerce company implementing nondifferential pricing strategy is directly proportional to the benefits of nondifferential pricing, the fines imposed by the government and platform on e-commerce company for differential pricing and the probability of consumers’ discovery, and inversely proportional to the benefits of e-commerce company implementing differential pricing strategy.Figure 2
Phase diagram of strategy evolution of e-commerce company.Proof.
Sincer0=Pd+yΔP−Pn−αyM+Ie−zF/1−αyM+1−αyIe, the volume of Vx1 in Figure 2 represents the proportion of nondifferential pricing by the e-commerce company, and the corresponding volume of Vx0 represents the proportion of differential pricing by the e-commerce company. When the value of Pn, M, Ie, F, and α gradually increases, the value of r0 will gradually decrease, and the volume of Vx1 will increase at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing increases; When the value of Pd and ∆P gradually increases, the value of r0 will gradually increase, and the volume of Vx1 will decrease at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing decreases.
#### 3.4.2. Strategy Stability Analysis of the Consumer
Assuming that the expected benefit of the consumer when choosing loyalty strategy to e-commerce company isU21, the expected benefit of the consumer when choosing disloyalty strategy to e-commerce company is U22, and the average expected benefit of the consumer is U2¯, which are defined as follows:(5)U21=xzrUl+1−xzrUl−ΔP+M+1−βF+x1−zrUl+1−x1−zrUl−ΔP+M+xz1−rUl+1−xz1−rUl−ΔP−Cc+αM+1−βF+x1−z1−rUl+1−x1−z1−rUl−ΔP−Cc+αM=Ul−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF,U22=xzrUd+1−xzrUd+x1−zrUd+1−x1−zrUd+xz1−rUd+1−xz1−rUd+x1−z1−rUd+1−x1−z1−rUd=Ud,U2¯=yU21+1−yU22.According to the Malthusian dynamic equation, the replication dynamic equation of consumer is obtained as follows:(6)Fy=dydt=yU21−U2¯=y1−yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.The first partial derivative ofF (y) for y is as follows:(7)Fy′y=1−2yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.Based on the stability theorem of differential equations, consumer implements the strategy of loyalty in the stable state must meet the conditions:Fy = 0, and Fy′y < 0.Proposition 2.
Whenx > x0, the stable strategy of the consumer is loyalty; when x < x0, the stable strategy of the consumer is disloyalty; when x = x0, the consumer cannot determine the stable strategy. Where the threshold is as follows:(8)x0=Ul−Ud+M−ΔP+1−rαM−Cc+z1−βFM−ΔP+1−rαM−Cc+z1−βF.Proof.
AssumeHx=Ul−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF, when M−ΔP+1−rαM−Cc+z1−βF>0, ∂H/∂x > 0, H (x) is considered to be an increasing function of x. When x > x0, H (x) > 0, Fy|y=1=0, and Fy′y|y=1<0, so y = 1 has stability; When x < x0, H (x) < 0, Fy|y=0=0, and Fy′y|y=0<0, so y = 0 has stability; When x = x0, H (x) = 0, Fy=0, and Fy′y=0, so y is stable at all levels in the range of 0 to 1, that is, the consumer’s strategy does not change over time, regardless of the proportion of consumer choosing to be loyal.
Proposition2 states that the increase of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from disloyalty to loyalty; Similarly, the decline of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from loyalty to disloyalty. Therefore, e-commerce company should reduce the degree of difference in pricing for consumers and try to retain consumers.
Based on Proposition2, the phase diagram of the strategy evolution of consumer is shown in Figure 3.
Inference 2: with the increase of the value ofUl, M, F, α, and β, the consumer is more inclined to be loyalty strategy to the e-commerce company, when other parameters remain unchanged. Similarly, with the increase of the value of Ud, ∆P, and Cc, the consumer is more inclined to be disloyalty strategy to the e-commerce company. It shows that the proportion of consumer being loyalty strategy to e-commerce company is directly proportional to the utility obtained by the loyal consumer from purchasing goods, the fines imposed by the government and e-commerce platform for differential pricing of e-commerce company, and the probability of consumers’ discovery, and inversely proportional to the utility obtained by the disloyal consumer in purchasing goods, the additional benefit obtained by the e-commerce company in implementing differential pricing, the proportion of fines imposed by the platform to the e-commerce company and the cost of consumer complaints.Figure 3
Phase diagram of strategy evolution of consumer.Proof.
Sincex0=1−Ul−Ud/ΔP+1−rCc−1+1−rαM−z1−βF, the volume of Vy1 in Figure 3 represents the proportion of loyalty to e-commerce company by the consumer, and the corresponding volume of Vy0 represents the proportion of disloyalty to e-commerce company by the consumer. When the value of Ul, M, Ie, F, and α gradually increases, the value of x0 will gradually decrease, and the volume of Vy1 will increase at this time, indicating that the proportion of loyalty to e-commerce company by the consumer increases; When the value of Ud, ∆P, β and Cc gradually increase, the value of x0 will gradually increase, and the volume of Vy1 will decrease at this time, indicating that the proportion of loyalty to e-commerce company by consumer decreases.
#### 3.4.3. Strategy Stability Analysis of E-Commerce Platform
Assuming that the expected benefit of the e-commerce platform when choosing the information supervision strategy isU31, the expected benefit of the e-commerce platform when choosing the information nonsupervision strategy is U32, and the average expected benefit of the e-commerce platform is U3¯, which are defined as follows:(9)U31=xyrW−Cp+TP+x1−yrW−Cp+1−xyrW−Cp+TP+βF+1−x1−yrW−Cp+TP+xy1−rW−Cp+βF+x1−y1−rW−Cp+1−xy1−rW−Cp+TP+βF+1−x1−y1−rW−Cp+βF=W−Cp+F+yTp−xF,U32=xyrW+TP+x1−yrW+1−xyrW−Ip+TP+1−x1−yrW−Ip+xy1−rW+TP+x1−y1−rW+1−xy1−rW−αIp+TP+1−x1−y1−rW=W+yTp−1−xrIp−1−xy1−rIp,U3¯=zU31+1−zU32.According to the Malthusian dynamic equation, the replication dynamic equation of e-commerce platform is obtained as follows:(10)Fz=dzdt=zU31−U3¯=z1−zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.The first partial derivative ofF (z) for z is as follows:(11)Fz′z=1−2zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.Based on the stability theorem of differential equations, e-commerce platform implements the strategy of information supervision in the stable state must meet the conditions:Fz = 0, and Fz′z <0.Proposition 3.
Wheny > y0, the e-commerce platform will choose information supervision as the stable strategy; when y < y0, the e-commerce platform will choose information nonsupervision as the stable strategy; when y = y0, the e-commerce platform cannot determine the stable strategy. Where the threshold is as follows:(12)y0=Cp+xβF+1−xrIp−βFTp−1−x1−rIp.Proof.
AssumeHy=F−Cp+yTp−xF−1−xrIp−1−xy1−rIp, when Tp−1−x1−rIp>0, ∂H/∂x >0, H (y) is considered to be an increasing function of y. When y > y0, H (y) > 0, Fz|z=1=0, and Fz′z|z=1<0, so z = 1 has stability; When y < y0, H (y) < 0, Fz|z=0=0, and Fz′z|z=0<0, so z = 0 has stability; When z = z0, H (y) = 0, Fz=0, and Fz′z=0, so z is stable at all levels in the range of 0 to 1, that is, the e-commerce platform’s strategy does not change over time, regardless of the proportion of e-commerce platform choosing information supervision.
Proposition3 states that the increase of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information nonsupervision to information supervision. Similarly, the decline of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information supervision to information nonsupervision. Therefore, if the consumer can be loyal to the e-commerce company in the platform, the platform will also actively supervise its subordinate company.
Based on Proposition3, the phase diagram of the strategy evolution of the e-commerce platform is shown in Figure 4.
Inference 3: with the increase of the value ofF, β, and Tp, the e-commerce platform is more inclined to implement the information supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cp and Ip, the e-commerce platform is more inclined to implement the information nonsupervision strategy. It shows that the proportion of e-commerce platform implementing information supervision strategy is directly proportional to the fines imposed by the platform for differential pricing of e-commerce company, the proportion of fines imposed by the e-commerce platform for differential pricing of e-commerce company, and the reputation value brought by the loyal consumer to the platform, and inversely proportional to the cost of the platform’s information supervision on e-commerce company and the fines by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricing.Figure 4
Phase diagram of strategy evolution of e-commerce platform.Proof.
Sincey0=Cp+1−xrIp−1−xβF/Tp−1−x1−rIp, the volume of Vz1 in Figure 4 represents the proportion of information supervision of e-commerce company by the platform, and the corresponding volume of Vz0 represents the proportion of information nonsupervision by the platform. When the value of F, β, and Tp gradually increase, the value of y0 will gradually decrease, and the volume of Vz1 will increase at this time, indicating that the proportion of e-commerce platform to implement information supervision increases; When the value of Cp and Ip gradually increases, the value of y0 will gradually increase, and the volume of Vz1 will decrease at this time, indicating that the proportion of e-commerce platform to implement information supervision decreases.
#### 3.4.4. Strategy Stability Analysis of Government Regulatory Department
Assuming that the expected benefit of government regulatory department when government implementing the strategy of strictly supervising isU41, the expected benefit of government regulatory department when government implementing the strategy of loosely supervising is U42, and the average expected benefit of the government regulatory department is U4¯, which are defined as follows:(13)U41=xyzS−Cg+R+x1−yzS−Cg+R+1−xyzS−Cg+Ie+1−x1−yzS−Cg+Ie+xy1−zS−Cg+R+x1−y1−zS−Cg+R+1−xy1−zS−Cg+Ie+Ip+1−x1−y1−zS−Cg+Ie+Ip=S−Cg+xR+1−xIe+1−x1−zIp.U42=xyzS+x1−yzS+1−xyzS−N+αIe+1−x1−yzS−N+xy1−zS+x1−y1−zS+1−xy1−zS−N+αIe+αIp+1−x1−y1−zS−N=S−1−xN+1−xyαIe+1−zIp,U4¯=rU41+1−rU42.According to the Malthusian dynamic equation, the replication dynamic equation of the government regulatory department is obtained as follows:(14)Fr=drdt=rU41−U4¯=r1−r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.The first partial derivative ofF (r) for r is as follows:(15)Fr′r=1−2r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.Based on the stability theorem of differential equations, government regulatory department implements the strategy of strictly supervising in the stable state must meet the conditions:Fr = 0, and Fr′r < 0.Proposition 4.
Whenz > z0, the government regulatory department will choose strict supervision as the stable strategy; when z < z0, the stable strategy of the government regulatory department will choose loose supervision as the stable strategy; when z = z0, the government regulatory department cannot determine the stable strategy. Where the threshold is as follows:(16)z0=−Cg+xR+1−x1−αyIp+1−x1−αyIe+N1−x1−αyIp.Proof.
AssumeHz=−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp, when ∂H/∂x < 0, H (z) is considered to be an increasing function of z. When z < z0, H (z) > 0, Fr|r=1=0, and Fr′r|r=1<0, so r = 1 has stability; When z > z0, H (z) < 0, Fr|r=0=0, and Fr′r|r=0<0, so r = 0 has stability; When z = z0, H (z) = 0, Fr=0, and Fr′r=0, so z is stable at all levels in the range of 0 to 1, that is, the government regulatory department’s strategy does not change over time, regardless of the proportion of government regulatory department choosing to strict supervision.
Proposition4 states that the decline of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from loose supervision to strict supervision; Similarly, the increase of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from strictly supervising to loosely supervising. Therefore, the government’s strict supervision on e-commerce company is the necessary measure under the unfavorable conditions of the e-commerce platform’s information supervision on e-commerce company.
Based on Proposition4, the phase diagram of strategy evolution of the government regulatory department is shown in Figure 5.
Inference 4: With the increase of the value ofR, Ie, Ip, and N, the government regulatory department is more inclined to implement the strict supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cg and α, the government is more inclined to implement the loose supervision strategy. It shows that the proportion of government regulatory department implementing strict supervision strategy is directly proportional to the social benefits obtained, the fines punished by the government on e-commerce company and platform, and the social reputation loss caused by differential pricing under the government’s loose supervision, and inversely proportional to the cost for the government to strictly supervise and the proportion of consumer discovering differential pricing.Figure 5
Phase diagram of strategy evolution of government regulatory department.Proof.
Sincez0=1−Cg−xR−1−x1−αyIe+N/1−x1−αyIp, the volume of Vr1 in Figure 5 represents the proportion of strictly supervised by the government, and the corresponding volume of Vr0 represents the proportion of loosely supervised by government. When the value of R, Ie, Ip, and N gradually increases, the value of z0 will gradually increase, and the volume of Vr1 will increase at this time, indicating that the proportion of strict supervision by government regulatory department increases; When the value of Cg and α gradually increase, the value of z0 will gradually decrease, and the volume of Vr1 will decrease at this time, indicating that the proportion of strict supervision by government regulatory department increases decreases.
## 3.1. Problem Description
The e-commerce company will use the platform to collect consumer information during the operation in the network platform. Based on the information provided by the platform, e-commerce company analyzes consumers and raise prices by judging their consumption habits. The pricing strategy of “big data killing” is price discrimination caused by e-commerce company using the feature of opaque information in the online transaction process to different pricing of consumers through big data and complex algorithms. This kind of behavior will bring consumers’ distrust of e-commerce companies and e-commerce platforms, which is not conducive to the development of e-commerce. Therefore, both the government regulatory department and e-commerce platforms should take necessary measures to supervise the price discrimination behavior of e-commerce companies. This study mainly discusses the following three questions: (1) in the context of big data development, how can the government regulatory department take supervision measures to reduce the proportion of price discrimination by e-commerce company? (2) How can e-commerce platform be motivated to supervise information on e-commerce companies? (3) How can consumers be guided to actively safeguard their rights and interests and maintain consumption fairness.This study builds a multi-agent game model for the supervision of price discrimination in e-commerce companies involving the e-commerce platform, the e-commerce company, the consumer, and the government regulatory department. The logical relationship among four-party game subjects is shown in Figure1.Figure 1
Game model logic relationship of multisubject supervision on e-commerce company pricing.
## 3.2. Model Assumption
To build the multisubject supervision model of the e-commerce company pricing in the background of big data, the behavioral strategies of government regulatory department, e-commerce platform, e-commerce company, and consumer are studied, and the following assumptions are made.Assumption 1.
Government regulatory department, e-commerce platform, the e-commerce company, and consumer are selected as the game subjects. Each game subject is bounded rationality and pursues the maximization of their interests in e-commerce transactions. Due to the information asymmetry between game subjects, random behavior strategies, and interactive effects, the optimal strategy cannot be obtained through one game. It is necessary to continuously try and learn in multiple rounds of games to improve the strategy, to formulate the best match of behavioral decision. Therefore, the evolutionary game should be used to analyze the four-party equilibrium strategy. The proportion of e-commerce company implementing nondifferential pricing is represented asx (0 ≤ x ≤ 1), and the proportion of e-commerce company implementing differential pricing is denoted as (1 − x); the proportion of consumer loyalty is represented as y (0 ≤ y ≤ 1) and the proportion of consumer disloyalty is represented as (1 − y); the proportion of e-commerce platform to supervise company information is represented as z (0 ≤ z ≤ 1), and the proportion of e-commerce platform with information nonsupervision is denoted as (1 − z); the proportion of the government regulatory department strictly supervising e-commerce platform and company is denoted as r (0 ≤ r ≤ 1), and the proportion of loosely supervises e-commerce platform and the company is denoted as (1 − r).Assumption 2.
The benefit of nondifferential pricing of the e-commerce company isPn, and the basic benefit of differential pricing is Pd. When the e-commerce company implements differential pricing for loyal consumer, additional benefit ∆P can be obtained due to the increase in selling price, and Pd < Pn < Pd+∆P. The probability of loyal consumers discovering differential pricing of the e-commerce company is α. When consumer purchases goods, the utility obtained by the loyal consumer is Ul, and the utility obtained by the disloyal consumer is Ud, and Ul > Ud. The reputation value of the loyal consumer to the e-commerce company is Te and the reputation value of the loyal consumer to the e-commerce platform is Tp.Assumption 3.
When the government strictly supervises, if price discrimination of the e-commerce company is found, loyal consumers who are subject to differential pricing will be compensated with the compensation amount ofM; When the government loosely supervises, if the loyal consumer is the price-sensitive consumer, he may use Internet information for comparison and analysis, and then find that he has been “killed”. If the cost of reporting is small and the procedure is simple, the consumer will carry out to inform the government regulatory department, and then the e-commerce company must be forced to compensate the consumer. The consumer’s complaint cost is Cc.Assumption 4.
The normal benefit that the government obtains from the operation of the e-commerce platform isS. The cost of strict supervision by government departments is Cg. The social benefit obtained by the government is R if there is no price discrimination by the e-commerce company. If the government adopts the loose supervision policy, consumer complaints will bring social reputation loss as N. After receiving the information, the e-commerce company for price discrimination will be penalized by the government regulatory department, and the fine will be Ie.Assumption 5.
The price discrimination of e-commerce company depends on the information provided by the platform. The benefit of the platform reasonably providing information to the e-commerce company isW, and the cost of the platform information supervision on e-commerce company is Cp. When the e-commerce platform finds the price discrimination of e-commerce company on the consumer, the fine to e-commerce company is F. The e-commerce platform and consumers share this fine in the ratio of β and 1 − β. When the government finds price discrimination by the e-commerce company, it will impose the fine of Ip for the platform’s unfavorable supervision to e-commerce company information.
The parameters are described in Table1.Table 1
Parameter description.
ParameterDescriptionPnThe benefit of nondifferential pricing by e-commerce company to consumerPdThe benefit of differential pricing by e-commerce company to consumer∆PThe additional benefit of differential pricing by e-commerce company to the loyal consumerMCompensation of e-commerce company to the loyal consumer for differential pricingTeThe reputation value of the loyal consumer to e-commerce companyUlThe utility obtained by the loyal consumer from purchasing goodsUdThe utility obtained by the disloyal consumer from purchasing goodsCcThe cost of consumer complaintαProbability of loyal consumer discovering differential pricing under government loose supervision, andα∈0,1CgThe cost of strict supervision by the government regulatory departmentNSocial reputation loss caused by differential pricing under government loose supervisionRThe social benefit of nondifferential pricing under the government strict supervisionIeFine by government regulatory department for differential pricing to e-commerce companyIpFine by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricingSThe normal benefit obtained by the government from the operation of the e-commerce platformWThe benefit of the platform reasonably providing information to the e-commerce companyCpThe cost of the platform’s information supervision on the e-commerce companyFFines imposed by the platform to e-commerce company for differential pricing during information supervisionβThe proportion of the fine imposed by the e-commerce platform for differential pricing of e-commerce company,β∈0,1TpThe reputation value of the loyal consumer to the e-commerce platform
## 3.3. Model Framework
According to the above analysis, the mixed-strategy game matrix of the four-party game subjects of government regulatory department, e-commerce platform, e-commerce company, and consumer is shown in Table2.Table 2
Game model benefit matrix of government regulatory department, e-commerce platform, e-commerce company, and consumer
Strategy choiceE-commerce companyGovernment regulatory departmentStrict supervision,rLoose supervision, 1 −rLoyaltyyDisloyalty 1 −yLoyaltyyDisloyalty 1 −yE-commerce platformInformation supervisionzNondifferential pricingxPn + TePnPn + TePnUlUdUlUdW − Cp + TpW − CpW − Cp + TpW − CpS − Cg+RS − Cg + RSSDifferential pricing 1 −xPd + ∆P + Te − M − Ie − FPd − Ie − FPd + ∆P + Te − αM − αIe − FPd − FUl− ∆P + M + (1 − β)FUdUl − ∆P − Cc + αM + (1 − β)FUdW − Cp + βF + TpW − Cp + FW − Cp + βF + TpW − Cp + FS −Cg + IeS −Cg + IeS + αIe− NS − NInformation nonsupervision 1 −zNondifferential pricingxPn + TePnPn + TePnUlUdUlUdW + TpWW + TpWS −Cg + RS −Cg + RSSDifferential pricing 1 −xPd + ∆P + Te− M − IePd− IePd + ∆P + Te− αM − αIePdUl− ∆P + MUdUl− ∆P − Cc + αMUdW − Ip + TpW − IpW − αIp + TpWS −Cg + Ie + IpS −Cg+Ie + IpS+αIe+αIp− NS − N
## 3.4. Model Analysis
### 3.4.1. Strategy Stability Analysis of the E-Commerce Company
Assuming that the expected benefit of the e-commerce company when choosing the nondifferential pricing strategy isU11, the expected benefit of the e-commerce company when choosing the differential pricing strategy is U12, and the average expected benefit of the e-commerce company is U1¯, which are defined as follows:(1)U11=yzrPn+Te+1−yzrPn+y1−zrPn+Te+1−y1−zrPn+yz1−rPn+Te+1−yz1−rPn+y1−z1−rPn+Te+1−y1−z1−rPn=Pn+yTe,U12=yzrPd+ΔP+Te−M−Ie−F+1−yzrPd−Ie−F+y1−zrPd+ΔP+Te−M−Ie+1−y1−zrPd−Ie+yz1−rPd+ΔP+Te−αM−αIe−F+1−yz1−rPd−F+y1−z1−rPd+ΔP+Te−αM−αIe+1−y1−z1−rPd=Pd+yΔP+Te−yM+Ier+1−rα−1−yrIe−zF,U1¯=xU11+1−xU12.According to the Malthusian dynamic equation, the replication dynamic equation of the e-commerce company is obtained as follows:(2)Fx=dxdt=xU11−U1¯=x1−xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.The first partial derivative ofF (x) for x is as follows:(3)Fx′x=1−2xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.Based on the stability theorem of differential equations, the e-commerce company implements the strategy of nondifferential pricing in the stable state must meet the conditions:Fx = 0, and Fx′x < 0.Proposition 1.
Whenr > r0, the stable strategy of the e-commerce company is nondifferential pricing; when r < r0, the stable strategy of the e-commerce company is differential pricing; when r = r0, the e-commerce company cannot determine the stable strategy. Where the threshold is as follows:(4)r0=Pd+yΔP−Pn−αyM+Ie−zF1−αyM+1−αyIe.Proof.
AssumeHr=Pn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF, when yM−αM+Ie>0, ∂H/∂r > 0, then H (r) is considered to be an increasing function of r. When r > r0, H (r) > 0, Fx|x=1=0, and Fx′x|x=1<0, so x = 1 has stability; When r < r0, H (r) < 0, Fx|x=0=0, and Fx′x|x=0<0, so x = 0 has stability; when r = r0, H (r) = 0, Fx=0, and Fx′x=0, so x is stable at all levels in the range of 0 to 1, that is, the company’s strategy does not change over time, regardless of the proportion of company choosing to price differentially.
Proposition1 states that the increase of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from differential pricing to nondifferential pricing; Similarly, the decline of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from nondifferential pricing to differential pricing. Therefore, the government’s strict supervision for e-commerce company is essential, and the government should take measures to improve strict supervision for the e-commerce company.
Based on Proposition1, the phase diagram of the strategy evolution of e-commerce company is shown in Figure 2.
Inference 1: with the increase of the value ofPn, M, Ie, F, and α, the e-commerce company is more inclined to implement the nondifferential pricing strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Pd and ∆P, the e-commerce company is more inclined to implement the differential pricing strategy. It shows that the proportion of e-commerce company implementing nondifferential pricing strategy is directly proportional to the benefits of nondifferential pricing, the fines imposed by the government and platform on e-commerce company for differential pricing and the probability of consumers’ discovery, and inversely proportional to the benefits of e-commerce company implementing differential pricing strategy.Figure 2
Phase diagram of strategy evolution of e-commerce company.Proof.
Sincer0=Pd+yΔP−Pn−αyM+Ie−zF/1−αyM+1−αyIe, the volume of Vx1 in Figure 2 represents the proportion of nondifferential pricing by the e-commerce company, and the corresponding volume of Vx0 represents the proportion of differential pricing by the e-commerce company. When the value of Pn, M, Ie, F, and α gradually increases, the value of r0 will gradually decrease, and the volume of Vx1 will increase at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing increases; When the value of Pd and ∆P gradually increases, the value of r0 will gradually increase, and the volume of Vx1 will decrease at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing decreases.
### 3.4.2. Strategy Stability Analysis of the Consumer
Assuming that the expected benefit of the consumer when choosing loyalty strategy to e-commerce company isU21, the expected benefit of the consumer when choosing disloyalty strategy to e-commerce company is U22, and the average expected benefit of the consumer is U2¯, which are defined as follows:(5)U21=xzrUl+1−xzrUl−ΔP+M+1−βF+x1−zrUl+1−x1−zrUl−ΔP+M+xz1−rUl+1−xz1−rUl−ΔP−Cc+αM+1−βF+x1−z1−rUl+1−x1−z1−rUl−ΔP−Cc+αM=Ul−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF,U22=xzrUd+1−xzrUd+x1−zrUd+1−x1−zrUd+xz1−rUd+1−xz1−rUd+x1−z1−rUd+1−x1−z1−rUd=Ud,U2¯=yU21+1−yU22.According to the Malthusian dynamic equation, the replication dynamic equation of consumer is obtained as follows:(6)Fy=dydt=yU21−U2¯=y1−yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.The first partial derivative ofF (y) for y is as follows:(7)Fy′y=1−2yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.Based on the stability theorem of differential equations, consumer implements the strategy of loyalty in the stable state must meet the conditions:Fy = 0, and Fy′y < 0.Proposition 2.
Whenx > x0, the stable strategy of the consumer is loyalty; when x < x0, the stable strategy of the consumer is disloyalty; when x = x0, the consumer cannot determine the stable strategy. Where the threshold is as follows:(8)x0=Ul−Ud+M−ΔP+1−rαM−Cc+z1−βFM−ΔP+1−rαM−Cc+z1−βF.Proof.
AssumeHx=Ul−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF, when M−ΔP+1−rαM−Cc+z1−βF>0, ∂H/∂x > 0, H (x) is considered to be an increasing function of x. When x > x0, H (x) > 0, Fy|y=1=0, and Fy′y|y=1<0, so y = 1 has stability; When x < x0, H (x) < 0, Fy|y=0=0, and Fy′y|y=0<0, so y = 0 has stability; When x = x0, H (x) = 0, Fy=0, and Fy′y=0, so y is stable at all levels in the range of 0 to 1, that is, the consumer’s strategy does not change over time, regardless of the proportion of consumer choosing to be loyal.
Proposition2 states that the increase of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from disloyalty to loyalty; Similarly, the decline of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from loyalty to disloyalty. Therefore, e-commerce company should reduce the degree of difference in pricing for consumers and try to retain consumers.
Based on Proposition2, the phase diagram of the strategy evolution of consumer is shown in Figure 3.
Inference 2: with the increase of the value ofUl, M, F, α, and β, the consumer is more inclined to be loyalty strategy to the e-commerce company, when other parameters remain unchanged. Similarly, with the increase of the value of Ud, ∆P, and Cc, the consumer is more inclined to be disloyalty strategy to the e-commerce company. It shows that the proportion of consumer being loyalty strategy to e-commerce company is directly proportional to the utility obtained by the loyal consumer from purchasing goods, the fines imposed by the government and e-commerce platform for differential pricing of e-commerce company, and the probability of consumers’ discovery, and inversely proportional to the utility obtained by the disloyal consumer in purchasing goods, the additional benefit obtained by the e-commerce company in implementing differential pricing, the proportion of fines imposed by the platform to the e-commerce company and the cost of consumer complaints.Figure 3
Phase diagram of strategy evolution of consumer.Proof.
Sincex0=1−Ul−Ud/ΔP+1−rCc−1+1−rαM−z1−βF, the volume of Vy1 in Figure 3 represents the proportion of loyalty to e-commerce company by the consumer, and the corresponding volume of Vy0 represents the proportion of disloyalty to e-commerce company by the consumer. When the value of Ul, M, Ie, F, and α gradually increases, the value of x0 will gradually decrease, and the volume of Vy1 will increase at this time, indicating that the proportion of loyalty to e-commerce company by the consumer increases; When the value of Ud, ∆P, β and Cc gradually increase, the value of x0 will gradually increase, and the volume of Vy1 will decrease at this time, indicating that the proportion of loyalty to e-commerce company by consumer decreases.
### 3.4.3. Strategy Stability Analysis of E-Commerce Platform
Assuming that the expected benefit of the e-commerce platform when choosing the information supervision strategy isU31, the expected benefit of the e-commerce platform when choosing the information nonsupervision strategy is U32, and the average expected benefit of the e-commerce platform is U3¯, which are defined as follows:(9)U31=xyrW−Cp+TP+x1−yrW−Cp+1−xyrW−Cp+TP+βF+1−x1−yrW−Cp+TP+xy1−rW−Cp+βF+x1−y1−rW−Cp+1−xy1−rW−Cp+TP+βF+1−x1−y1−rW−Cp+βF=W−Cp+F+yTp−xF,U32=xyrW+TP+x1−yrW+1−xyrW−Ip+TP+1−x1−yrW−Ip+xy1−rW+TP+x1−y1−rW+1−xy1−rW−αIp+TP+1−x1−y1−rW=W+yTp−1−xrIp−1−xy1−rIp,U3¯=zU31+1−zU32.According to the Malthusian dynamic equation, the replication dynamic equation of e-commerce platform is obtained as follows:(10)Fz=dzdt=zU31−U3¯=z1−zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.The first partial derivative ofF (z) for z is as follows:(11)Fz′z=1−2zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.Based on the stability theorem of differential equations, e-commerce platform implements the strategy of information supervision in the stable state must meet the conditions:Fz = 0, and Fz′z <0.Proposition 3.
Wheny > y0, the e-commerce platform will choose information supervision as the stable strategy; when y < y0, the e-commerce platform will choose information nonsupervision as the stable strategy; when y = y0, the e-commerce platform cannot determine the stable strategy. Where the threshold is as follows:(12)y0=Cp+xβF+1−xrIp−βFTp−1−x1−rIp.Proof.
AssumeHy=F−Cp+yTp−xF−1−xrIp−1−xy1−rIp, when Tp−1−x1−rIp>0, ∂H/∂x >0, H (y) is considered to be an increasing function of y. When y > y0, H (y) > 0, Fz|z=1=0, and Fz′z|z=1<0, so z = 1 has stability; When y < y0, H (y) < 0, Fz|z=0=0, and Fz′z|z=0<0, so z = 0 has stability; When z = z0, H (y) = 0, Fz=0, and Fz′z=0, so z is stable at all levels in the range of 0 to 1, that is, the e-commerce platform’s strategy does not change over time, regardless of the proportion of e-commerce platform choosing information supervision.
Proposition3 states that the increase of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information nonsupervision to information supervision. Similarly, the decline of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information supervision to information nonsupervision. Therefore, if the consumer can be loyal to the e-commerce company in the platform, the platform will also actively supervise its subordinate company.
Based on Proposition3, the phase diagram of the strategy evolution of the e-commerce platform is shown in Figure 4.
Inference 3: with the increase of the value ofF, β, and Tp, the e-commerce platform is more inclined to implement the information supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cp and Ip, the e-commerce platform is more inclined to implement the information nonsupervision strategy. It shows that the proportion of e-commerce platform implementing information supervision strategy is directly proportional to the fines imposed by the platform for differential pricing of e-commerce company, the proportion of fines imposed by the e-commerce platform for differential pricing of e-commerce company, and the reputation value brought by the loyal consumer to the platform, and inversely proportional to the cost of the platform’s information supervision on e-commerce company and the fines by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricing.Figure 4
Phase diagram of strategy evolution of e-commerce platform.Proof.
Sincey0=Cp+1−xrIp−1−xβF/Tp−1−x1−rIp, the volume of Vz1 in Figure 4 represents the proportion of information supervision of e-commerce company by the platform, and the corresponding volume of Vz0 represents the proportion of information nonsupervision by the platform. When the value of F, β, and Tp gradually increase, the value of y0 will gradually decrease, and the volume of Vz1 will increase at this time, indicating that the proportion of e-commerce platform to implement information supervision increases; When the value of Cp and Ip gradually increases, the value of y0 will gradually increase, and the volume of Vz1 will decrease at this time, indicating that the proportion of e-commerce platform to implement information supervision decreases.
### 3.4.4. Strategy Stability Analysis of Government Regulatory Department
Assuming that the expected benefit of government regulatory department when government implementing the strategy of strictly supervising isU41, the expected benefit of government regulatory department when government implementing the strategy of loosely supervising is U42, and the average expected benefit of the government regulatory department is U4¯, which are defined as follows:(13)U41=xyzS−Cg+R+x1−yzS−Cg+R+1−xyzS−Cg+Ie+1−x1−yzS−Cg+Ie+xy1−zS−Cg+R+x1−y1−zS−Cg+R+1−xy1−zS−Cg+Ie+Ip+1−x1−y1−zS−Cg+Ie+Ip=S−Cg+xR+1−xIe+1−x1−zIp.U42=xyzS+x1−yzS+1−xyzS−N+αIe+1−x1−yzS−N+xy1−zS+x1−y1−zS+1−xy1−zS−N+αIe+αIp+1−x1−y1−zS−N=S−1−xN+1−xyαIe+1−zIp,U4¯=rU41+1−rU42.According to the Malthusian dynamic equation, the replication dynamic equation of the government regulatory department is obtained as follows:(14)Fr=drdt=rU41−U4¯=r1−r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.The first partial derivative ofF (r) for r is as follows:(15)Fr′r=1−2r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.Based on the stability theorem of differential equations, government regulatory department implements the strategy of strictly supervising in the stable state must meet the conditions:Fr = 0, and Fr′r < 0.Proposition 4.
Whenz > z0, the government regulatory department will choose strict supervision as the stable strategy; when z < z0, the stable strategy of the government regulatory department will choose loose supervision as the stable strategy; when z = z0, the government regulatory department cannot determine the stable strategy. Where the threshold is as follows:(16)z0=−Cg+xR+1−x1−αyIp+1−x1−αyIe+N1−x1−αyIp.Proof.
AssumeHz=−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp, when ∂H/∂x < 0, H (z) is considered to be an increasing function of z. When z < z0, H (z) > 0, Fr|r=1=0, and Fr′r|r=1<0, so r = 1 has stability; When z > z0, H (z) < 0, Fr|r=0=0, and Fr′r|r=0<0, so r = 0 has stability; When z = z0, H (z) = 0, Fr=0, and Fr′r=0, so z is stable at all levels in the range of 0 to 1, that is, the government regulatory department’s strategy does not change over time, regardless of the proportion of government regulatory department choosing to strict supervision.
Proposition4 states that the decline of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from loose supervision to strict supervision; Similarly, the increase of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from strictly supervising to loosely supervising. Therefore, the government’s strict supervision on e-commerce company is the necessary measure under the unfavorable conditions of the e-commerce platform’s information supervision on e-commerce company.
Based on Proposition4, the phase diagram of strategy evolution of the government regulatory department is shown in Figure 5.
Inference 4: With the increase of the value ofR, Ie, Ip, and N, the government regulatory department is more inclined to implement the strict supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cg and α, the government is more inclined to implement the loose supervision strategy. It shows that the proportion of government regulatory department implementing strict supervision strategy is directly proportional to the social benefits obtained, the fines punished by the government on e-commerce company and platform, and the social reputation loss caused by differential pricing under the government’s loose supervision, and inversely proportional to the cost for the government to strictly supervise and the proportion of consumer discovering differential pricing.Figure 5
Phase diagram of strategy evolution of government regulatory department.Proof.
Sincez0=1−Cg−xR−1−x1−αyIe+N/1−x1−αyIp, the volume of Vr1 in Figure 5 represents the proportion of strictly supervised by the government, and the corresponding volume of Vr0 represents the proportion of loosely supervised by government. When the value of R, Ie, Ip, and N gradually increases, the value of z0 will gradually increase, and the volume of Vr1 will increase at this time, indicating that the proportion of strict supervision by government regulatory department increases; When the value of Cg and α gradually increase, the value of z0 will gradually decrease, and the volume of Vr1 will decrease at this time, indicating that the proportion of strict supervision by government regulatory department increases decreases.
## 3.4.1. Strategy Stability Analysis of the E-Commerce Company
Assuming that the expected benefit of the e-commerce company when choosing the nondifferential pricing strategy isU11, the expected benefit of the e-commerce company when choosing the differential pricing strategy is U12, and the average expected benefit of the e-commerce company is U1¯, which are defined as follows:(1)U11=yzrPn+Te+1−yzrPn+y1−zrPn+Te+1−y1−zrPn+yz1−rPn+Te+1−yz1−rPn+y1−z1−rPn+Te+1−y1−z1−rPn=Pn+yTe,U12=yzrPd+ΔP+Te−M−Ie−F+1−yzrPd−Ie−F+y1−zrPd+ΔP+Te−M−Ie+1−y1−zrPd−Ie+yz1−rPd+ΔP+Te−αM−αIe−F+1−yz1−rPd−F+y1−z1−rPd+ΔP+Te−αM−αIe+1−y1−z1−rPd=Pd+yΔP+Te−yM+Ier+1−rα−1−yrIe−zF,U1¯=xU11+1−xU12.According to the Malthusian dynamic equation, the replication dynamic equation of the e-commerce company is obtained as follows:(2)Fx=dxdt=xU11−U1¯=x1−xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.The first partial derivative ofF (x) for x is as follows:(3)Fx′x=1−2xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.Based on the stability theorem of differential equations, the e-commerce company implements the strategy of nondifferential pricing in the stable state must meet the conditions:Fx = 0, and Fx′x < 0.Proposition 1.
Whenr > r0, the stable strategy of the e-commerce company is nondifferential pricing; when r < r0, the stable strategy of the e-commerce company is differential pricing; when r = r0, the e-commerce company cannot determine the stable strategy. Where the threshold is as follows:(4)r0=Pd+yΔP−Pn−αyM+Ie−zF1−αyM+1−αyIe.Proof.
AssumeHr=Pn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF, when yM−αM+Ie>0, ∂H/∂r > 0, then H (r) is considered to be an increasing function of r. When r > r0, H (r) > 0, Fx|x=1=0, and Fx′x|x=1<0, so x = 1 has stability; When r < r0, H (r) < 0, Fx|x=0=0, and Fx′x|x=0<0, so x = 0 has stability; when r = r0, H (r) = 0, Fx=0, and Fx′x=0, so x is stable at all levels in the range of 0 to 1, that is, the company’s strategy does not change over time, regardless of the proportion of company choosing to price differentially.
Proposition1 states that the increase of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from differential pricing to nondifferential pricing; Similarly, the decline of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from nondifferential pricing to differential pricing. Therefore, the government’s strict supervision for e-commerce company is essential, and the government should take measures to improve strict supervision for the e-commerce company.
Based on Proposition1, the phase diagram of the strategy evolution of e-commerce company is shown in Figure 2.
Inference 1: with the increase of the value ofPn, M, Ie, F, and α, the e-commerce company is more inclined to implement the nondifferential pricing strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Pd and ∆P, the e-commerce company is more inclined to implement the differential pricing strategy. It shows that the proportion of e-commerce company implementing nondifferential pricing strategy is directly proportional to the benefits of nondifferential pricing, the fines imposed by the government and platform on e-commerce company for differential pricing and the probability of consumers’ discovery, and inversely proportional to the benefits of e-commerce company implementing differential pricing strategy.Figure 2
Phase diagram of strategy evolution of e-commerce company.Proof.
Sincer0=Pd+yΔP−Pn−αyM+Ie−zF/1−αyM+1−αyIe, the volume of Vx1 in Figure 2 represents the proportion of nondifferential pricing by the e-commerce company, and the corresponding volume of Vx0 represents the proportion of differential pricing by the e-commerce company. When the value of Pn, M, Ie, F, and α gradually increases, the value of r0 will gradually decrease, and the volume of Vx1 will increase at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing increases; When the value of Pd and ∆P gradually increases, the value of r0 will gradually increase, and the volume of Vx1 will decrease at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing decreases.
## 3.4.2. Strategy Stability Analysis of the Consumer
Assuming that the expected benefit of the consumer when choosing loyalty strategy to e-commerce company isU21, the expected benefit of the consumer when choosing disloyalty strategy to e-commerce company is U22, and the average expected benefit of the consumer is U2¯, which are defined as follows:(5)U21=xzrUl+1−xzrUl−ΔP+M+1−βF+x1−zrUl+1−x1−zrUl−ΔP+M+xz1−rUl+1−xz1−rUl−ΔP−Cc+αM+1−βF+x1−z1−rUl+1−x1−z1−rUl−ΔP−Cc+αM=Ul−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF,U22=xzrUd+1−xzrUd+x1−zrUd+1−x1−zrUd+xz1−rUd+1−xz1−rUd+x1−z1−rUd+1−x1−z1−rUd=Ud,U2¯=yU21+1−yU22.According to the Malthusian dynamic equation, the replication dynamic equation of consumer is obtained as follows:(6)Fy=dydt=yU21−U2¯=y1−yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.The first partial derivative ofF (y) for y is as follows:(7)Fy′y=1−2yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.Based on the stability theorem of differential equations, consumer implements the strategy of loyalty in the stable state must meet the conditions:Fy = 0, and Fy′y < 0.Proposition 2.
Whenx > x0, the stable strategy of the consumer is loyalty; when x < x0, the stable strategy of the consumer is disloyalty; when x = x0, the consumer cannot determine the stable strategy. Where the threshold is as follows:(8)x0=Ul−Ud+M−ΔP+1−rαM−Cc+z1−βFM−ΔP+1−rαM−Cc+z1−βF.Proof.
AssumeHx=Ul−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF, when M−ΔP+1−rαM−Cc+z1−βF>0, ∂H/∂x > 0, H (x) is considered to be an increasing function of x. When x > x0, H (x) > 0, Fy|y=1=0, and Fy′y|y=1<0, so y = 1 has stability; When x < x0, H (x) < 0, Fy|y=0=0, and Fy′y|y=0<0, so y = 0 has stability; When x = x0, H (x) = 0, Fy=0, and Fy′y=0, so y is stable at all levels in the range of 0 to 1, that is, the consumer’s strategy does not change over time, regardless of the proportion of consumer choosing to be loyal.
Proposition2 states that the increase of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from disloyalty to loyalty; Similarly, the decline of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from loyalty to disloyalty. Therefore, e-commerce company should reduce the degree of difference in pricing for consumers and try to retain consumers.
Based on Proposition2, the phase diagram of the strategy evolution of consumer is shown in Figure 3.
Inference 2: with the increase of the value ofUl, M, F, α, and β, the consumer is more inclined to be loyalty strategy to the e-commerce company, when other parameters remain unchanged. Similarly, with the increase of the value of Ud, ∆P, and Cc, the consumer is more inclined to be disloyalty strategy to the e-commerce company. It shows that the proportion of consumer being loyalty strategy to e-commerce company is directly proportional to the utility obtained by the loyal consumer from purchasing goods, the fines imposed by the government and e-commerce platform for differential pricing of e-commerce company, and the probability of consumers’ discovery, and inversely proportional to the utility obtained by the disloyal consumer in purchasing goods, the additional benefit obtained by the e-commerce company in implementing differential pricing, the proportion of fines imposed by the platform to the e-commerce company and the cost of consumer complaints.Figure 3
Phase diagram of strategy evolution of consumer.Proof.
Sincex0=1−Ul−Ud/ΔP+1−rCc−1+1−rαM−z1−βF, the volume of Vy1 in Figure 3 represents the proportion of loyalty to e-commerce company by the consumer, and the corresponding volume of Vy0 represents the proportion of disloyalty to e-commerce company by the consumer. When the value of Ul, M, Ie, F, and α gradually increases, the value of x0 will gradually decrease, and the volume of Vy1 will increase at this time, indicating that the proportion of loyalty to e-commerce company by the consumer increases; When the value of Ud, ∆P, β and Cc gradually increase, the value of x0 will gradually increase, and the volume of Vy1 will decrease at this time, indicating that the proportion of loyalty to e-commerce company by consumer decreases.
## 3.4.3. Strategy Stability Analysis of E-Commerce Platform
Assuming that the expected benefit of the e-commerce platform when choosing the information supervision strategy isU31, the expected benefit of the e-commerce platform when choosing the information nonsupervision strategy is U32, and the average expected benefit of the e-commerce platform is U3¯, which are defined as follows:(9)U31=xyrW−Cp+TP+x1−yrW−Cp+1−xyrW−Cp+TP+βF+1−x1−yrW−Cp+TP+xy1−rW−Cp+βF+x1−y1−rW−Cp+1−xy1−rW−Cp+TP+βF+1−x1−y1−rW−Cp+βF=W−Cp+F+yTp−xF,U32=xyrW+TP+x1−yrW+1−xyrW−Ip+TP+1−x1−yrW−Ip+xy1−rW+TP+x1−y1−rW+1−xy1−rW−αIp+TP+1−x1−y1−rW=W+yTp−1−xrIp−1−xy1−rIp,U3¯=zU31+1−zU32.According to the Malthusian dynamic equation, the replication dynamic equation of e-commerce platform is obtained as follows:(10)Fz=dzdt=zU31−U3¯=z1−zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.The first partial derivative ofF (z) for z is as follows:(11)Fz′z=1−2zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.Based on the stability theorem of differential equations, e-commerce platform implements the strategy of information supervision in the stable state must meet the conditions:Fz = 0, and Fz′z <0.Proposition 3.
Wheny > y0, the e-commerce platform will choose information supervision as the stable strategy; when y < y0, the e-commerce platform will choose information nonsupervision as the stable strategy; when y = y0, the e-commerce platform cannot determine the stable strategy. Where the threshold is as follows:(12)y0=Cp+xβF+1−xrIp−βFTp−1−x1−rIp.Proof.
AssumeHy=F−Cp+yTp−xF−1−xrIp−1−xy1−rIp, when Tp−1−x1−rIp>0, ∂H/∂x >0, H (y) is considered to be an increasing function of y. When y > y0, H (y) > 0, Fz|z=1=0, and Fz′z|z=1<0, so z = 1 has stability; When y < y0, H (y) < 0, Fz|z=0=0, and Fz′z|z=0<0, so z = 0 has stability; When z = z0, H (y) = 0, Fz=0, and Fz′z=0, so z is stable at all levels in the range of 0 to 1, that is, the e-commerce platform’s strategy does not change over time, regardless of the proportion of e-commerce platform choosing information supervision.
Proposition3 states that the increase of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information nonsupervision to information supervision. Similarly, the decline of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information supervision to information nonsupervision. Therefore, if the consumer can be loyal to the e-commerce company in the platform, the platform will also actively supervise its subordinate company.
Based on Proposition3, the phase diagram of the strategy evolution of the e-commerce platform is shown in Figure 4.
Inference 3: with the increase of the value ofF, β, and Tp, the e-commerce platform is more inclined to implement the information supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cp and Ip, the e-commerce platform is more inclined to implement the information nonsupervision strategy. It shows that the proportion of e-commerce platform implementing information supervision strategy is directly proportional to the fines imposed by the platform for differential pricing of e-commerce company, the proportion of fines imposed by the e-commerce platform for differential pricing of e-commerce company, and the reputation value brought by the loyal consumer to the platform, and inversely proportional to the cost of the platform’s information supervision on e-commerce company and the fines by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricing.Figure 4
Phase diagram of strategy evolution of e-commerce platform.Proof.
Sincey0=Cp+1−xrIp−1−xβF/Tp−1−x1−rIp, the volume of Vz1 in Figure 4 represents the proportion of information supervision of e-commerce company by the platform, and the corresponding volume of Vz0 represents the proportion of information nonsupervision by the platform. When the value of F, β, and Tp gradually increase, the value of y0 will gradually decrease, and the volume of Vz1 will increase at this time, indicating that the proportion of e-commerce platform to implement information supervision increases; When the value of Cp and Ip gradually increases, the value of y0 will gradually increase, and the volume of Vz1 will decrease at this time, indicating that the proportion of e-commerce platform to implement information supervision decreases.
## 3.4.4. Strategy Stability Analysis of Government Regulatory Department
Assuming that the expected benefit of government regulatory department when government implementing the strategy of strictly supervising isU41, the expected benefit of government regulatory department when government implementing the strategy of loosely supervising is U42, and the average expected benefit of the government regulatory department is U4¯, which are defined as follows:(13)U41=xyzS−Cg+R+x1−yzS−Cg+R+1−xyzS−Cg+Ie+1−x1−yzS−Cg+Ie+xy1−zS−Cg+R+x1−y1−zS−Cg+R+1−xy1−zS−Cg+Ie+Ip+1−x1−y1−zS−Cg+Ie+Ip=S−Cg+xR+1−xIe+1−x1−zIp.U42=xyzS+x1−yzS+1−xyzS−N+αIe+1−x1−yzS−N+xy1−zS+x1−y1−zS+1−xy1−zS−N+αIe+αIp+1−x1−y1−zS−N=S−1−xN+1−xyαIe+1−zIp,U4¯=rU41+1−rU42.According to the Malthusian dynamic equation, the replication dynamic equation of the government regulatory department is obtained as follows:(14)Fr=drdt=rU41−U4¯=r1−r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.The first partial derivative ofF (r) for r is as follows:(15)Fr′r=1−2r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.Based on the stability theorem of differential equations, government regulatory department implements the strategy of strictly supervising in the stable state must meet the conditions:Fr = 0, and Fr′r < 0.Proposition 4.
Whenz > z0, the government regulatory department will choose strict supervision as the stable strategy; when z < z0, the stable strategy of the government regulatory department will choose loose supervision as the stable strategy; when z = z0, the government regulatory department cannot determine the stable strategy. Where the threshold is as follows:(16)z0=−Cg+xR+1−x1−αyIp+1−x1−αyIe+N1−x1−αyIp.Proof.
AssumeHz=−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp, when ∂H/∂x < 0, H (z) is considered to be an increasing function of z. When z < z0, H (z) > 0, Fr|r=1=0, and Fr′r|r=1<0, so r = 1 has stability; When z > z0, H (z) < 0, Fr|r=0=0, and Fr′r|r=0<0, so r = 0 has stability; When z = z0, H (z) = 0, Fr=0, and Fr′r=0, so z is stable at all levels in the range of 0 to 1, that is, the government regulatory department’s strategy does not change over time, regardless of the proportion of government regulatory department choosing to strict supervision.
Proposition4 states that the decline of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from loose supervision to strict supervision; Similarly, the increase of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from strictly supervising to loosely supervising. Therefore, the government’s strict supervision on e-commerce company is the necessary measure under the unfavorable conditions of the e-commerce platform’s information supervision on e-commerce company.
Based on Proposition4, the phase diagram of strategy evolution of the government regulatory department is shown in Figure 5.
Inference 4: With the increase of the value ofR, Ie, Ip, and N, the government regulatory department is more inclined to implement the strict supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cg and α, the government is more inclined to implement the loose supervision strategy. It shows that the proportion of government regulatory department implementing strict supervision strategy is directly proportional to the social benefits obtained, the fines punished by the government on e-commerce company and platform, and the social reputation loss caused by differential pricing under the government’s loose supervision, and inversely proportional to the cost for the government to strictly supervise and the proportion of consumer discovering differential pricing.Figure 5
Phase diagram of strategy evolution of government regulatory department.Proof.
Sincez0=1−Cg−xR−1−x1−αyIe+N/1−x1−αyIp, the volume of Vr1 in Figure 5 represents the proportion of strictly supervised by the government, and the corresponding volume of Vr0 represents the proportion of loosely supervised by government. When the value of R, Ie, Ip, and N gradually increases, the value of z0 will gradually increase, and the volume of Vr1 will increase at this time, indicating that the proportion of strict supervision by government regulatory department increases; When the value of Cg and α gradually increase, the value of z0 will gradually decrease, and the volume of Vr1 will decrease at this time, indicating that the proportion of strict supervision by government regulatory department increases decreases.
## 4. Results and Discussion
### 4.1. ESS Analysis among Four-Party Game Players
In the dynamic system of government regulatory department, e-commerce platform, e-commerce company and consumer, the stability of the strategic combination of the four-party game subjects can be referred to as the nonlinear function stability discriminant method of First Law of Lyapunov. Ritzberger and Weibull [38] and Selten [39] pointed out that the stable solutions in the multi-group evolutionary game are strict Nash equilibrium, which must be the pure strategy. Therefore, this study analyzes 16 pure strategies in four-party evolutionary game learning from the research method of Sun and Su [40].Due to the replication dynamic equation of each game subject, the Jacobian matrix is obtained as follows:(17)J=Fx′xFy′xFz′xFr′xFx′yFy′yFz′yFr′yFx′zFy′zFz′zFr′zFx′rFy′rFz′rFr′r,where the elements in the matrix are shown in Appendix A.
#### 4.1.1. ESS Analysis among Four-Party Game Players under the Strict Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp<0, government regulatory department implements strict supervision. According to the Jacobian matrix shown in Appendix B, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 3.Condition (a):−Pn+Pd+ΔP−M−Ie<0, Cg−R<0, and −Cp+Tp<0Condition (b):−Pn+Pd+ΔP−M−Ie−F<0, Cg−R<0, and Cp−Tp<0Table 3
Asymptotic stability analysis of equilibrium point of replication dynamic system under the strict supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE1 (0, 0, 0, 1)(+,X, X, X)Instability pointE2 (1, 0, 0, 1)(−, +, −, −)Instability pointE3 (0, 1, 0, 1)(+,X, X, −)Instability pointE4 (0, 0, 1, 1)(+,X, X, −)Instability pointE5 (1, 1, 0, 1)(−, −, −, −)ESS in condition (a)E6 (1, 0, 1, 1)(−, +, +,−)Instability pointE7 (0, 1, 1, 1)(+,X, X,−)Instability pointE8 (1, 1, 1, 1)(−, −, −, −)ESS in condition (b)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.It can be seen from Table3 that there are two possible stable strategies under strict supervision by the government regulatory department, i.e. E5 (1, 1, 0, 1) and E8 (1, 1, 1, 1).When the condition (a) is met, that is,−Pn+Pd+ΔP−M−Ie < 0, Cg−R < 0, and −Cp+Tp < 0. The sum of the benefits of differential pricing to loyal consumers by e-commerce company is less than the sum of the benefits of nondifferential pricing by e-commerce company to the consumer and the fines to the e-commerce company for differential pricing and compensation of e-commerce company to consumer by the government. The strict supervision cost is less than the social benefits when controlling differential pricing for the government. And the reputation value produced by the loyal consumer to the platform is less than the cost of the platform information supervision. Then the strategy of each subject is stable at equilibrium point E5 (1, 1, 0, 1). E-commerce company implements nondifferential pricing, the consumer is loyal to the e-commerce company, e-commerce platform implements information nonsupervision, and the government strictly supervises e-commerce platform and e-commerce company. This situation may exist in the period of chaotic pricing for the e-commerce company. Since the e-commerce platform benefits less from the information supervision of e-commerce company, it has no motivation to supervise e-commerce company. Therefore, the government must come forward to supervise differential pricing, safeguard consumer rights and interests, and help e-commerce company gain consumer loyalty.When the condition (b) is met, that is−Pn+Pd+ΔP−M−Ie−F < 0, Cg−R < 0, and Cp−Tp < 0. With the improvement of consumers’ awareness of differential pricing and the reduction of the cost of platform supervising information, the information supervision cost of the platform is less than the reputation value brought by the loyal consumer to the platform, and the e-commerce platform can also join into the supervision of e-commerce company. When the other conditions remain unchanged, the strategy of each subject is stable at equilibrium point E8 (1, 1, 1, 1). The government and e-commerce platform jointly strengthen the supervision of differential pricing of e-commerce company, so that e-commerce company inclined to to be nondifferential pricing, and consumer is loyal to the e-commerce company.
#### 4.1.2. ESS Analysis among Four-Party Game Players under the Loose Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp>0, government regulatory department implements loosely supervision. According to the Jacobian matrix shown in Appendix C, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 4.Table 4
Asymptotic stability analysis of equilibrium point of replication dynamic system under the loose supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE9 (0, 0, 0, 0)(+,X, X, X)Instability pointE10 (1, 0, 0, 0)(−, +,X, X)Instability pointE11 (0, 1, 0, 0)(+,X, X, X)Instability pointE12 (0, 0, 1, 0)(+,X, X, X)Instability pointE13 (1, 1, 0, 0)(X,−, X, +V)Instability pointE14 (1, 0, 1, 0)(X, +, +, +)Instability pointE15 (0, 1, 1, 0)(+,X, X, X)Instability pointE16 (1, 1, 1, 0)(−, −, −, −)ESS in condition (c)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.Condition (c):−Pn+Pd+ΔP−αM+Ie−F <0, Cp−Tp <0, and −Cg+R <0.As shown in Table4 that there is a possible stabilization strategy under loose supervision by government regulatory authorities, i.e. E16 (1, 1, 1, 0).When the condition (c) is met, that is,−Pn+Pd+ΔP−αM+Ie−F<0, Cp−Tp<0, and −Cg+R <0. The sum of the benefits of e-commerce company’s differential pricing for the loyal consumer is less than the sum of the benefits of e-commerce company’s nondifferential pricing for consumer, the fines punished by government regulatory department under loosely supervising and the compensation for the consumer for differential pricing of e-commerce company, and the fines imposed by e-commerce platform on the e-commerce company. The reputation value brought by the loyal consumer to the platform is greater than the cost of the platform information supervision. And the strict supervision cost is greater than the social benefits when controlling differential pricing for the government. Then the strategy of each subject is stable at equilibrium point E16 (1, 1, 1, 0). This situation may exist in the normative period of discriminatory pricing by the e-commerce company. At this time, as the proportion of the differential pricing of e-commerce company gradually decreases, the social benefits of the government’s strict supervision of differential pricing decrease. When the social benefit is less than the strictly supervising cost of the government regulatory department, the strategy of the government regulatory department will change from strictly supervising to loosely supervising. The main responsibility of supervision will be transferred from the government to the e-commerce platform and consumer. Supervision and fines by e-commerce platform and consumer enable e-commerce company to conduct nondifferential pricing and promote the virtuous circle of the e-commerce industry ecosystem.
### 4.2. Numerical Simulation Analysis
In order to test the reliability of the model and more intuitively demonstrate the influence of key factors in the replication dynamic system on the evolutionary trajectory of stakeholders of the multi-party game, the model is given numerical value combined with the actual situation, and the numerical simulation is carried out by MATLAB2021.For the e-commerce company operating in the e-commerce platform, the benefit of nondifferential pricing to the consumer is set asPn = 10, and the benefit of differential pricing to the consumer is set as Pd = 9, and the additional benefit of differential pricing to the loyal consumer is set as ∆P = 5. If differential pricing is discovered by the government, the compensation of the e-commerce company to the consumer is set as M = 4. The reputation value brought by the loyal consumer to the e-commerce company is set as Te = 5, and the reputation value brought by the loyal consumer to the e-commerce platform is set as Tp = 5. The utility obtained by the loyal consumer when purchasing goods from the e-commerce company is set as Ul = 12, and the utility obtained by the disloyal consumer when purchasing goods from the e-commerce company is set as Ud = 11. The probability of loyal consumer discovering differential pricing under government loose supervision is set as α = 0.2 and the complaint cost of the loyal consumer is set as Cc = 3. The social benefit of nondifferential pricing obtained by the government under strict supervision is set as R = 7, and the cost of strictly supervised by the government is set as Cg = 6. The fine by government regulatory department for differential pricing of e-commerce company Ie = 3. The social reputation loss of the government caused by differential pricing under loose supervision is set as N = 8. The normal benefit obtained by the government from the operation of the platform is set as S = 6. The benefit of the platform reasonably providing information to e-commerce company is set as W = 5, and the cost of the platform’s information supervision on e-commerce company is set as Cp = 7. The fine imposed by the platform to e-commerce company for differential pricing during information supervision is set as F = 3, and the proportion of fine imposed by the e-commerce platform for differential pricing of the e-commerce company is set as β = 0.6.
#### 4.2.1. The Influence of Government Supervision Mechanism
To test whether the government supervision mechanism is effective in the process of differential pricing of e-commerce company, the proportions of government strict supervision are set asr = 0 and r = 1 to represent the two states of loose supervision and strict supervision of government supervision department. The evolution process of different initial strategies of the e-commercial company, consumer, and e-commerce platform is simulated and analyzed in three-dimensional space, and the simulation results with time are shown in Figure 6.Figure 6
Influence of the establishment of government supervision mechanism on strategy evolution of all parties.
(a)(b)(c)As shown in Figure6(a) that when government regulatory department adopts the strict supervision strategy on the differential pricing of e-commerce company, although the e-commerce platform does not take information supervision strategy on account of the high cost for information supervision, the strategies of the e-commerce company and consumer can still incline to be stable in nondifferential pricing and loyalty. This shows that it is very necessary and effective for the government to adopt the strict supervision strategy. With the reduction of Cp, that is, the information supervision cost reduced, the platform will be inclined to adopt the strategy of information supervision, to achieve coordinated supervision to e-commerce company by the government and platform, then the company adopts nondifferential pricing, and consumer is loyal to the e-commerce company. And the stable strategy portfolio is demonstrated in Figure 6(b). As is exhibited in Figure 6(c) that when government regulatory department implements the loosely supervising to e-commerce company for the differential pricing due to the high cost of strict supervision, if Cp is small, that is, the cost of information supervision on the e-commerce platform is small, and α is at a high level, the consumer can actively discover the differential pricing of the e-commerce company and report it, the e-commerce company will also incline to nondifferential pricing. Therefore, although the government selects the loose supervision strategy, the differential pricing behavior of e-commerce company is supervised collaboratively by the platform and consumer. The strategy equilibrium is consistent with the previous analysis of the stability under different government supervision strategies.
#### 4.2.2. The Influence of Information Supervision Cost of E-Commerce Platforms
IfCp = {7, 4, 1}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 7.Figure 7
Influence of information supervision cost of e-commerce platform on strategy evolution of all parties.According to Figure7, with the reduction of the information supervision cost of the e-commerce platform, the supervision strategy of the platform will be transformed from information nonsupervision on e-commerce company to information supervision. Therefore, the platform can join the ranks of the government to regulate the company, and collaboratively supervise the differential pricing of the e-commerce company for loyal consumer. Moreover, the less the information supervision cost of the platform, the faster the stable strategy of information supervision. Therefore, active measures can be adopted to lower the cost for information supervising of e-commerce platform, to stimulate e-commerce platform to supervise the differential pricing behavior of e-commerce company on the platform.
#### 4.2.3. The Influence of the Strict Supervision Cost of Government Regulatory Department
IfCg = {6, 8, 10}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 8.Figure 8
Influence of strict supervision cost of government regulatory department on strategy evolution of all parties.According to Figure8, the strict supervision cost of government affects the decision-making of government regulatory department, as well as affects the evolution of decision-making of the other subjects. With the increase of government supervision cost, the supervision strategy of the government regulatory department to the differential pricing of e-commerce company will be transformed from strict supervision to loose supervision, and gradually become the cyclical alternating strategy between strict supervision and loose supervision with medium proportion. The strategy of the e-commerce platform will be also transformed from information supervision to information nonsupervision of e-commerce company when strictly supervising cost of government Increasing. Free from the supervision of government regulatory department and platform, the pricing strategy of the company for the loyal consumer will be transformed from nondifferential pricing to moderate-proportion differential pricing, and the strategy change periodically. With the increase of the strictly supervising cost of government, the strategy of the consumer will be transformed from loyalty to e-commerce company to disloyalty. Therefore, the strict supervision cost of the government regulatory department is the key factor in restricting the differential pricing of the e-commerce company. Measures should be arranged to actively reduce the strictly supervising cost of the government regulatory department at a certain level, to stimulate platform and the consumer to regulate the behavior of e-commerce company in differential pricing.
#### 4.2.4. The Influence of the Probability of Loyal Consumer Discovering Differential Pricing under Government's Loose Supervision
Ifα = {0.1, 0.3, 0.5}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 9.Figure 9
Influence of the probability of loyal consumer discovering differential pricing under government loose supervision on strategy evolution of all parties.According to Figure9, with the increase of probability of loyal consumer discovering differential pricing under government loose supervision, the probability of exposure of differential pricing behavior of e-commerce company for loyal consumer increases, which will make e-commerce company gradually improve the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The e-commerce platform can also gradually improve the proportion of information supervision due to the increase of fines for nonsupervision of e-commerce company information resulting in differential pricing, and the behavior stabilizes in the information supervision strategy. The government regulatory department can gradually loose supervision and transfer the responsibility of supervision to e-commerce platform and the consumer. Therefore, measures can be taken to encourage the consumer to report the differential pricing behavior of e-commerce company, to maintain the stable and sustainable progress of e-commerce platform and systems.
#### 4.2.5. The Influence of the Penalties for Differential Pricing of E-Commerce Company under Government's Loose Supervision
IfM = {1, 2, 4}, Ie = {1, 2, 4}, and F = {1, 2, 4}, the evolution process and results of the strategy of the four-party game subjects are shown in Figure 10.Figure 10
Influence of the penalties for differential pricing of e-commerce company under government loose supervision on strategy evolution of all parties.According to Figure10, with the increase of the fines given by consumer, e-commerce platform, and government regulatory department for differential pricing of e-commerce company, the e-commerce company will gradually increase the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The consumer will increase the proportion of loyalty to the e-commerce company and the behavior stabilize in the loyalty strategy when the compensation for differential pricing from e-commerce company increases to compensate for the loss of differential pricing. The e-commerce platform will also gradually improve the proportion of information supervision due to the increase of benefits from information supervision fines and the behavior stabilizes in the information supervision strategy. Therefore, the nondifferential pricing behavior of e-commerce company can be promoted by increasing the punishment for differential pricing, to realize the joint dynamic supervision of the e-commerce platform, the consumer, and the government on the pricing of the e-commerce company.
## 4.1. ESS Analysis among Four-Party Game Players
In the dynamic system of government regulatory department, e-commerce platform, e-commerce company and consumer, the stability of the strategic combination of the four-party game subjects can be referred to as the nonlinear function stability discriminant method of First Law of Lyapunov. Ritzberger and Weibull [38] and Selten [39] pointed out that the stable solutions in the multi-group evolutionary game are strict Nash equilibrium, which must be the pure strategy. Therefore, this study analyzes 16 pure strategies in four-party evolutionary game learning from the research method of Sun and Su [40].Due to the replication dynamic equation of each game subject, the Jacobian matrix is obtained as follows:(17)J=Fx′xFy′xFz′xFr′xFx′yFy′yFz′yFr′yFx′zFy′zFz′zFr′zFx′rFy′rFz′rFr′r,where the elements in the matrix are shown in Appendix A.
### 4.1.1. ESS Analysis among Four-Party Game Players under the Strict Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp<0, government regulatory department implements strict supervision. According to the Jacobian matrix shown in Appendix B, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 3.Condition (a):−Pn+Pd+ΔP−M−Ie<0, Cg−R<0, and −Cp+Tp<0Condition (b):−Pn+Pd+ΔP−M−Ie−F<0, Cg−R<0, and Cp−Tp<0Table 3
Asymptotic stability analysis of equilibrium point of replication dynamic system under the strict supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE1 (0, 0, 0, 1)(+,X, X, X)Instability pointE2 (1, 0, 0, 1)(−, +, −, −)Instability pointE3 (0, 1, 0, 1)(+,X, X, −)Instability pointE4 (0, 0, 1, 1)(+,X, X, −)Instability pointE5 (1, 1, 0, 1)(−, −, −, −)ESS in condition (a)E6 (1, 0, 1, 1)(−, +, +,−)Instability pointE7 (0, 1, 1, 1)(+,X, X,−)Instability pointE8 (1, 1, 1, 1)(−, −, −, −)ESS in condition (b)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.It can be seen from Table3 that there are two possible stable strategies under strict supervision by the government regulatory department, i.e. E5 (1, 1, 0, 1) and E8 (1, 1, 1, 1).When the condition (a) is met, that is,−Pn+Pd+ΔP−M−Ie < 0, Cg−R < 0, and −Cp+Tp < 0. The sum of the benefits of differential pricing to loyal consumers by e-commerce company is less than the sum of the benefits of nondifferential pricing by e-commerce company to the consumer and the fines to the e-commerce company for differential pricing and compensation of e-commerce company to consumer by the government. The strict supervision cost is less than the social benefits when controlling differential pricing for the government. And the reputation value produced by the loyal consumer to the platform is less than the cost of the platform information supervision. Then the strategy of each subject is stable at equilibrium point E5 (1, 1, 0, 1). E-commerce company implements nondifferential pricing, the consumer is loyal to the e-commerce company, e-commerce platform implements information nonsupervision, and the government strictly supervises e-commerce platform and e-commerce company. This situation may exist in the period of chaotic pricing for the e-commerce company. Since the e-commerce platform benefits less from the information supervision of e-commerce company, it has no motivation to supervise e-commerce company. Therefore, the government must come forward to supervise differential pricing, safeguard consumer rights and interests, and help e-commerce company gain consumer loyalty.When the condition (b) is met, that is−Pn+Pd+ΔP−M−Ie−F < 0, Cg−R < 0, and Cp−Tp < 0. With the improvement of consumers’ awareness of differential pricing and the reduction of the cost of platform supervising information, the information supervision cost of the platform is less than the reputation value brought by the loyal consumer to the platform, and the e-commerce platform can also join into the supervision of e-commerce company. When the other conditions remain unchanged, the strategy of each subject is stable at equilibrium point E8 (1, 1, 1, 1). The government and e-commerce platform jointly strengthen the supervision of differential pricing of e-commerce company, so that e-commerce company inclined to to be nondifferential pricing, and consumer is loyal to the e-commerce company.
### 4.1.2. ESS Analysis among Four-Party Game Players under the Loose Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp>0, government regulatory department implements loosely supervision. According to the Jacobian matrix shown in Appendix C, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 4.Table 4
Asymptotic stability analysis of equilibrium point of replication dynamic system under the loose supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE9 (0, 0, 0, 0)(+,X, X, X)Instability pointE10 (1, 0, 0, 0)(−, +,X, X)Instability pointE11 (0, 1, 0, 0)(+,X, X, X)Instability pointE12 (0, 0, 1, 0)(+,X, X, X)Instability pointE13 (1, 1, 0, 0)(X,−, X, +V)Instability pointE14 (1, 0, 1, 0)(X, +, +, +)Instability pointE15 (0, 1, 1, 0)(+,X, X, X)Instability pointE16 (1, 1, 1, 0)(−, −, −, −)ESS in condition (c)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.Condition (c):−Pn+Pd+ΔP−αM+Ie−F <0, Cp−Tp <0, and −Cg+R <0.As shown in Table4 that there is a possible stabilization strategy under loose supervision by government regulatory authorities, i.e. E16 (1, 1, 1, 0).When the condition (c) is met, that is,−Pn+Pd+ΔP−αM+Ie−F<0, Cp−Tp<0, and −Cg+R <0. The sum of the benefits of e-commerce company’s differential pricing for the loyal consumer is less than the sum of the benefits of e-commerce company’s nondifferential pricing for consumer, the fines punished by government regulatory department under loosely supervising and the compensation for the consumer for differential pricing of e-commerce company, and the fines imposed by e-commerce platform on the e-commerce company. The reputation value brought by the loyal consumer to the platform is greater than the cost of the platform information supervision. And the strict supervision cost is greater than the social benefits when controlling differential pricing for the government. Then the strategy of each subject is stable at equilibrium point E16 (1, 1, 1, 0). This situation may exist in the normative period of discriminatory pricing by the e-commerce company. At this time, as the proportion of the differential pricing of e-commerce company gradually decreases, the social benefits of the government’s strict supervision of differential pricing decrease. When the social benefit is less than the strictly supervising cost of the government regulatory department, the strategy of the government regulatory department will change from strictly supervising to loosely supervising. The main responsibility of supervision will be transferred from the government to the e-commerce platform and consumer. Supervision and fines by e-commerce platform and consumer enable e-commerce company to conduct nondifferential pricing and promote the virtuous circle of the e-commerce industry ecosystem.
## 4.1.1. ESS Analysis among Four-Party Game Players under the Strict Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp<0, government regulatory department implements strict supervision. According to the Jacobian matrix shown in Appendix B, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 3.Condition (a):−Pn+Pd+ΔP−M−Ie<0, Cg−R<0, and −Cp+Tp<0Condition (b):−Pn+Pd+ΔP−M−Ie−F<0, Cg−R<0, and Cp−Tp<0Table 3
Asymptotic stability analysis of equilibrium point of replication dynamic system under the strict supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE1 (0, 0, 0, 1)(+,X, X, X)Instability pointE2 (1, 0, 0, 1)(−, +, −, −)Instability pointE3 (0, 1, 0, 1)(+,X, X, −)Instability pointE4 (0, 0, 1, 1)(+,X, X, −)Instability pointE5 (1, 1, 0, 1)(−, −, −, −)ESS in condition (a)E6 (1, 0, 1, 1)(−, +, +,−)Instability pointE7 (0, 1, 1, 1)(+,X, X,−)Instability pointE8 (1, 1, 1, 1)(−, −, −, −)ESS in condition (b)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.It can be seen from Table3 that there are two possible stable strategies under strict supervision by the government regulatory department, i.e. E5 (1, 1, 0, 1) and E8 (1, 1, 1, 1).When the condition (a) is met, that is,−Pn+Pd+ΔP−M−Ie < 0, Cg−R < 0, and −Cp+Tp < 0. The sum of the benefits of differential pricing to loyal consumers by e-commerce company is less than the sum of the benefits of nondifferential pricing by e-commerce company to the consumer and the fines to the e-commerce company for differential pricing and compensation of e-commerce company to consumer by the government. The strict supervision cost is less than the social benefits when controlling differential pricing for the government. And the reputation value produced by the loyal consumer to the platform is less than the cost of the platform information supervision. Then the strategy of each subject is stable at equilibrium point E5 (1, 1, 0, 1). E-commerce company implements nondifferential pricing, the consumer is loyal to the e-commerce company, e-commerce platform implements information nonsupervision, and the government strictly supervises e-commerce platform and e-commerce company. This situation may exist in the period of chaotic pricing for the e-commerce company. Since the e-commerce platform benefits less from the information supervision of e-commerce company, it has no motivation to supervise e-commerce company. Therefore, the government must come forward to supervise differential pricing, safeguard consumer rights and interests, and help e-commerce company gain consumer loyalty.When the condition (b) is met, that is−Pn+Pd+ΔP−M−Ie−F < 0, Cg−R < 0, and Cp−Tp < 0. With the improvement of consumers’ awareness of differential pricing and the reduction of the cost of platform supervising information, the information supervision cost of the platform is less than the reputation value brought by the loyal consumer to the platform, and the e-commerce platform can also join into the supervision of e-commerce company. When the other conditions remain unchanged, the strategy of each subject is stable at equilibrium point E8 (1, 1, 1, 1). The government and e-commerce platform jointly strengthen the supervision of differential pricing of e-commerce company, so that e-commerce company inclined to to be nondifferential pricing, and consumer is loyal to the e-commerce company.
## 4.1.2. ESS Analysis among Four-Party Game Players under the Loose Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp>0, government regulatory department implements loosely supervision. According to the Jacobian matrix shown in Appendix C, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 4.Table 4
Asymptotic stability analysis of equilibrium point of replication dynamic system under the loose supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE9 (0, 0, 0, 0)(+,X, X, X)Instability pointE10 (1, 0, 0, 0)(−, +,X, X)Instability pointE11 (0, 1, 0, 0)(+,X, X, X)Instability pointE12 (0, 0, 1, 0)(+,X, X, X)Instability pointE13 (1, 1, 0, 0)(X,−, X, +V)Instability pointE14 (1, 0, 1, 0)(X, +, +, +)Instability pointE15 (0, 1, 1, 0)(+,X, X, X)Instability pointE16 (1, 1, 1, 0)(−, −, −, −)ESS in condition (c)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.Condition (c):−Pn+Pd+ΔP−αM+Ie−F <0, Cp−Tp <0, and −Cg+R <0.As shown in Table4 that there is a possible stabilization strategy under loose supervision by government regulatory authorities, i.e. E16 (1, 1, 1, 0).When the condition (c) is met, that is,−Pn+Pd+ΔP−αM+Ie−F<0, Cp−Tp<0, and −Cg+R <0. The sum of the benefits of e-commerce company’s differential pricing for the loyal consumer is less than the sum of the benefits of e-commerce company’s nondifferential pricing for consumer, the fines punished by government regulatory department under loosely supervising and the compensation for the consumer for differential pricing of e-commerce company, and the fines imposed by e-commerce platform on the e-commerce company. The reputation value brought by the loyal consumer to the platform is greater than the cost of the platform information supervision. And the strict supervision cost is greater than the social benefits when controlling differential pricing for the government. Then the strategy of each subject is stable at equilibrium point E16 (1, 1, 1, 0). This situation may exist in the normative period of discriminatory pricing by the e-commerce company. At this time, as the proportion of the differential pricing of e-commerce company gradually decreases, the social benefits of the government’s strict supervision of differential pricing decrease. When the social benefit is less than the strictly supervising cost of the government regulatory department, the strategy of the government regulatory department will change from strictly supervising to loosely supervising. The main responsibility of supervision will be transferred from the government to the e-commerce platform and consumer. Supervision and fines by e-commerce platform and consumer enable e-commerce company to conduct nondifferential pricing and promote the virtuous circle of the e-commerce industry ecosystem.
## 4.2. Numerical Simulation Analysis
In order to test the reliability of the model and more intuitively demonstrate the influence of key factors in the replication dynamic system on the evolutionary trajectory of stakeholders of the multi-party game, the model is given numerical value combined with the actual situation, and the numerical simulation is carried out by MATLAB2021.For the e-commerce company operating in the e-commerce platform, the benefit of nondifferential pricing to the consumer is set asPn = 10, and the benefit of differential pricing to the consumer is set as Pd = 9, and the additional benefit of differential pricing to the loyal consumer is set as ∆P = 5. If differential pricing is discovered by the government, the compensation of the e-commerce company to the consumer is set as M = 4. The reputation value brought by the loyal consumer to the e-commerce company is set as Te = 5, and the reputation value brought by the loyal consumer to the e-commerce platform is set as Tp = 5. The utility obtained by the loyal consumer when purchasing goods from the e-commerce company is set as Ul = 12, and the utility obtained by the disloyal consumer when purchasing goods from the e-commerce company is set as Ud = 11. The probability of loyal consumer discovering differential pricing under government loose supervision is set as α = 0.2 and the complaint cost of the loyal consumer is set as Cc = 3. The social benefit of nondifferential pricing obtained by the government under strict supervision is set as R = 7, and the cost of strictly supervised by the government is set as Cg = 6. The fine by government regulatory department for differential pricing of e-commerce company Ie = 3. The social reputation loss of the government caused by differential pricing under loose supervision is set as N = 8. The normal benefit obtained by the government from the operation of the platform is set as S = 6. The benefit of the platform reasonably providing information to e-commerce company is set as W = 5, and the cost of the platform’s information supervision on e-commerce company is set as Cp = 7. The fine imposed by the platform to e-commerce company for differential pricing during information supervision is set as F = 3, and the proportion of fine imposed by the e-commerce platform for differential pricing of the e-commerce company is set as β = 0.6.
### 4.2.1. The Influence of Government Supervision Mechanism
To test whether the government supervision mechanism is effective in the process of differential pricing of e-commerce company, the proportions of government strict supervision are set asr = 0 and r = 1 to represent the two states of loose supervision and strict supervision of government supervision department. The evolution process of different initial strategies of the e-commercial company, consumer, and e-commerce platform is simulated and analyzed in three-dimensional space, and the simulation results with time are shown in Figure 6.Figure 6
Influence of the establishment of government supervision mechanism on strategy evolution of all parties.
(a)(b)(c)As shown in Figure6(a) that when government regulatory department adopts the strict supervision strategy on the differential pricing of e-commerce company, although the e-commerce platform does not take information supervision strategy on account of the high cost for information supervision, the strategies of the e-commerce company and consumer can still incline to be stable in nondifferential pricing and loyalty. This shows that it is very necessary and effective for the government to adopt the strict supervision strategy. With the reduction of Cp, that is, the information supervision cost reduced, the platform will be inclined to adopt the strategy of information supervision, to achieve coordinated supervision to e-commerce company by the government and platform, then the company adopts nondifferential pricing, and consumer is loyal to the e-commerce company. And the stable strategy portfolio is demonstrated in Figure 6(b). As is exhibited in Figure 6(c) that when government regulatory department implements the loosely supervising to e-commerce company for the differential pricing due to the high cost of strict supervision, if Cp is small, that is, the cost of information supervision on the e-commerce platform is small, and α is at a high level, the consumer can actively discover the differential pricing of the e-commerce company and report it, the e-commerce company will also incline to nondifferential pricing. Therefore, although the government selects the loose supervision strategy, the differential pricing behavior of e-commerce company is supervised collaboratively by the platform and consumer. The strategy equilibrium is consistent with the previous analysis of the stability under different government supervision strategies.
### 4.2.2. The Influence of Information Supervision Cost of E-Commerce Platforms
IfCp = {7, 4, 1}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 7.Figure 7
Influence of information supervision cost of e-commerce platform on strategy evolution of all parties.According to Figure7, with the reduction of the information supervision cost of the e-commerce platform, the supervision strategy of the platform will be transformed from information nonsupervision on e-commerce company to information supervision. Therefore, the platform can join the ranks of the government to regulate the company, and collaboratively supervise the differential pricing of the e-commerce company for loyal consumer. Moreover, the less the information supervision cost of the platform, the faster the stable strategy of information supervision. Therefore, active measures can be adopted to lower the cost for information supervising of e-commerce platform, to stimulate e-commerce platform to supervise the differential pricing behavior of e-commerce company on the platform.
### 4.2.3. The Influence of the Strict Supervision Cost of Government Regulatory Department
IfCg = {6, 8, 10}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 8.Figure 8
Influence of strict supervision cost of government regulatory department on strategy evolution of all parties.According to Figure8, the strict supervision cost of government affects the decision-making of government regulatory department, as well as affects the evolution of decision-making of the other subjects. With the increase of government supervision cost, the supervision strategy of the government regulatory department to the differential pricing of e-commerce company will be transformed from strict supervision to loose supervision, and gradually become the cyclical alternating strategy between strict supervision and loose supervision with medium proportion. The strategy of the e-commerce platform will be also transformed from information supervision to information nonsupervision of e-commerce company when strictly supervising cost of government Increasing. Free from the supervision of government regulatory department and platform, the pricing strategy of the company for the loyal consumer will be transformed from nondifferential pricing to moderate-proportion differential pricing, and the strategy change periodically. With the increase of the strictly supervising cost of government, the strategy of the consumer will be transformed from loyalty to e-commerce company to disloyalty. Therefore, the strict supervision cost of the government regulatory department is the key factor in restricting the differential pricing of the e-commerce company. Measures should be arranged to actively reduce the strictly supervising cost of the government regulatory department at a certain level, to stimulate platform and the consumer to regulate the behavior of e-commerce company in differential pricing.
### 4.2.4. The Influence of the Probability of Loyal Consumer Discovering Differential Pricing under Government's Loose Supervision
Ifα = {0.1, 0.3, 0.5}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 9.Figure 9
Influence of the probability of loyal consumer discovering differential pricing under government loose supervision on strategy evolution of all parties.According to Figure9, with the increase of probability of loyal consumer discovering differential pricing under government loose supervision, the probability of exposure of differential pricing behavior of e-commerce company for loyal consumer increases, which will make e-commerce company gradually improve the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The e-commerce platform can also gradually improve the proportion of information supervision due to the increase of fines for nonsupervision of e-commerce company information resulting in differential pricing, and the behavior stabilizes in the information supervision strategy. The government regulatory department can gradually loose supervision and transfer the responsibility of supervision to e-commerce platform and the consumer. Therefore, measures can be taken to encourage the consumer to report the differential pricing behavior of e-commerce company, to maintain the stable and sustainable progress of e-commerce platform and systems.
### 4.2.5. The Influence of the Penalties for Differential Pricing of E-Commerce Company under Government's Loose Supervision
IfM = {1, 2, 4}, Ie = {1, 2, 4}, and F = {1, 2, 4}, the evolution process and results of the strategy of the four-party game subjects are shown in Figure 10.Figure 10
Influence of the penalties for differential pricing of e-commerce company under government loose supervision on strategy evolution of all parties.According to Figure10, with the increase of the fines given by consumer, e-commerce platform, and government regulatory department for differential pricing of e-commerce company, the e-commerce company will gradually increase the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The consumer will increase the proportion of loyalty to the e-commerce company and the behavior stabilize in the loyalty strategy when the compensation for differential pricing from e-commerce company increases to compensate for the loss of differential pricing. The e-commerce platform will also gradually improve the proportion of information supervision due to the increase of benefits from information supervision fines and the behavior stabilizes in the information supervision strategy. Therefore, the nondifferential pricing behavior of e-commerce company can be promoted by increasing the punishment for differential pricing, to realize the joint dynamic supervision of the e-commerce platform, the consumer, and the government on the pricing of the e-commerce company.
## 4.2.1. The Influence of Government Supervision Mechanism
To test whether the government supervision mechanism is effective in the process of differential pricing of e-commerce company, the proportions of government strict supervision are set asr = 0 and r = 1 to represent the two states of loose supervision and strict supervision of government supervision department. The evolution process of different initial strategies of the e-commercial company, consumer, and e-commerce platform is simulated and analyzed in three-dimensional space, and the simulation results with time are shown in Figure 6.Figure 6
Influence of the establishment of government supervision mechanism on strategy evolution of all parties.
(a)(b)(c)As shown in Figure6(a) that when government regulatory department adopts the strict supervision strategy on the differential pricing of e-commerce company, although the e-commerce platform does not take information supervision strategy on account of the high cost for information supervision, the strategies of the e-commerce company and consumer can still incline to be stable in nondifferential pricing and loyalty. This shows that it is very necessary and effective for the government to adopt the strict supervision strategy. With the reduction of Cp, that is, the information supervision cost reduced, the platform will be inclined to adopt the strategy of information supervision, to achieve coordinated supervision to e-commerce company by the government and platform, then the company adopts nondifferential pricing, and consumer is loyal to the e-commerce company. And the stable strategy portfolio is demonstrated in Figure 6(b). As is exhibited in Figure 6(c) that when government regulatory department implements the loosely supervising to e-commerce company for the differential pricing due to the high cost of strict supervision, if Cp is small, that is, the cost of information supervision on the e-commerce platform is small, and α is at a high level, the consumer can actively discover the differential pricing of the e-commerce company and report it, the e-commerce company will also incline to nondifferential pricing. Therefore, although the government selects the loose supervision strategy, the differential pricing behavior of e-commerce company is supervised collaboratively by the platform and consumer. The strategy equilibrium is consistent with the previous analysis of the stability under different government supervision strategies.
## 4.2.2. The Influence of Information Supervision Cost of E-Commerce Platforms
IfCp = {7, 4, 1}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 7.Figure 7
Influence of information supervision cost of e-commerce platform on strategy evolution of all parties.According to Figure7, with the reduction of the information supervision cost of the e-commerce platform, the supervision strategy of the platform will be transformed from information nonsupervision on e-commerce company to information supervision. Therefore, the platform can join the ranks of the government to regulate the company, and collaboratively supervise the differential pricing of the e-commerce company for loyal consumer. Moreover, the less the information supervision cost of the platform, the faster the stable strategy of information supervision. Therefore, active measures can be adopted to lower the cost for information supervising of e-commerce platform, to stimulate e-commerce platform to supervise the differential pricing behavior of e-commerce company on the platform.
## 4.2.3. The Influence of the Strict Supervision Cost of Government Regulatory Department
IfCg = {6, 8, 10}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 8.Figure 8
Influence of strict supervision cost of government regulatory department on strategy evolution of all parties.According to Figure8, the strict supervision cost of government affects the decision-making of government regulatory department, as well as affects the evolution of decision-making of the other subjects. With the increase of government supervision cost, the supervision strategy of the government regulatory department to the differential pricing of e-commerce company will be transformed from strict supervision to loose supervision, and gradually become the cyclical alternating strategy between strict supervision and loose supervision with medium proportion. The strategy of the e-commerce platform will be also transformed from information supervision to information nonsupervision of e-commerce company when strictly supervising cost of government Increasing. Free from the supervision of government regulatory department and platform, the pricing strategy of the company for the loyal consumer will be transformed from nondifferential pricing to moderate-proportion differential pricing, and the strategy change periodically. With the increase of the strictly supervising cost of government, the strategy of the consumer will be transformed from loyalty to e-commerce company to disloyalty. Therefore, the strict supervision cost of the government regulatory department is the key factor in restricting the differential pricing of the e-commerce company. Measures should be arranged to actively reduce the strictly supervising cost of the government regulatory department at a certain level, to stimulate platform and the consumer to regulate the behavior of e-commerce company in differential pricing.
## 4.2.4. The Influence of the Probability of Loyal Consumer Discovering Differential Pricing under Government's Loose Supervision
Ifα = {0.1, 0.3, 0.5}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 9.Figure 9
Influence of the probability of loyal consumer discovering differential pricing under government loose supervision on strategy evolution of all parties.According to Figure9, with the increase of probability of loyal consumer discovering differential pricing under government loose supervision, the probability of exposure of differential pricing behavior of e-commerce company for loyal consumer increases, which will make e-commerce company gradually improve the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The e-commerce platform can also gradually improve the proportion of information supervision due to the increase of fines for nonsupervision of e-commerce company information resulting in differential pricing, and the behavior stabilizes in the information supervision strategy. The government regulatory department can gradually loose supervision and transfer the responsibility of supervision to e-commerce platform and the consumer. Therefore, measures can be taken to encourage the consumer to report the differential pricing behavior of e-commerce company, to maintain the stable and sustainable progress of e-commerce platform and systems.
## 4.2.5. The Influence of the Penalties for Differential Pricing of E-Commerce Company under Government's Loose Supervision
IfM = {1, 2, 4}, Ie = {1, 2, 4}, and F = {1, 2, 4}, the evolution process and results of the strategy of the four-party game subjects are shown in Figure 10.Figure 10
Influence of the penalties for differential pricing of e-commerce company under government loose supervision on strategy evolution of all parties.According to Figure10, with the increase of the fines given by consumer, e-commerce platform, and government regulatory department for differential pricing of e-commerce company, the e-commerce company will gradually increase the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The consumer will increase the proportion of loyalty to the e-commerce company and the behavior stabilize in the loyalty strategy when the compensation for differential pricing from e-commerce company increases to compensate for the loss of differential pricing. The e-commerce platform will also gradually improve the proportion of information supervision due to the increase of benefits from information supervision fines and the behavior stabilizes in the information supervision strategy. Therefore, the nondifferential pricing behavior of e-commerce company can be promoted by increasing the punishment for differential pricing, to realize the joint dynamic supervision of the e-commerce platform, the consumer, and the government on the pricing of the e-commerce company.
## 5. Conclusions
Given the phenomenon of “big data killing” that e-commerce companies use customer information in the pricing process, this paper studies how to safeguard consumers’ pricing fairness in the context of the Internet, and builds the four-party evolutionary game model for the supervision on differential pricing of e-commerce company, analyzes the stability of the strategy selection of each subject in the model, and the stability of equilibrium point of the strategic combination in the replication dynamic system, and simulates and analyzes the influence of key elements on the strategy evolution. The main conclusions are as follows:(1)
The government supervision mechanism can play an effective role to limit differential pricing of the e-commerce company. When the proportion of strict government supervision adds, the sum of the benefits of differential pricing for loyal consumers by e-commerce company is less than the penalty cost of e-commerce company, and strict supervision cost of government is less than its social benefits, then e-commerce company inclines more to choose the strategy of nondifferential pricing. Since the reputation value of the e-commerce platform is less than the information supervision cost of platform, the platform inclines more to conduct information nonsupervision. Therefore, the equilibrium strategy of each subject is stable at point E5 (1, 1, 0, 1), which occurs in the early stage of the government’s strict supervision on the e-commerce company. With the reduction of the supervision cost of the platform, it is also willing to join the supervision on differential pricing of e-commerce company for the platform and inclines more to choose information supervision strategy. Therefore, the equilibrium strategy of each subject is stable at point E8 (1, 1, 1, 1), which occurs in the stable stage of the government’s strict supervision of e-commerce company, and the participation of the e-commerce platform relieved the pressure on government supervising on the company. When the strictly supervising cost of government increases, the reputation value of the platform is greater than the supervision cost of the platform, then the government regulatory department inclines more to loose supervision strategy. Therefore, the equilibrium strategy of each subject is stable at point E16 (1, 1, 1, 0), which occurs in the later stage of the government’s strict supervision of e-commerce company. When both e-commerce platform and consumer realize the important role of supervision and conduct strong collaborative supervision, the government can take the way of auxiliary supervision to control the differential pricing of the e-commerce company.(2)
The information supervision cost of the e-commerce platform is the main factor affecting the supervision strategy of the platform. When the supervision cost of the platform is greater than the reputation value of the platform, the platform inclines more to conduct information nonsupervision. However, as the information supervision cost of the platform decreases and is less than the reputation value of the platform, the stable strategy of the e-commerce platform will transform into information supervision and then promote nondifferential pricing for the e-commerce company. Moreover, the less the information supervision cost of the e-commerce platform, the faster the stable strategy of the e-commerce platform can transform into the information supervision strategy.(3)
The strict supervision cost of government is the main factor affecting the strategies of all parties. When the strict supervision cost of government is so small as to be less than the social benefits of government strict supervision on differential pricing of e-commerce company, the equilibrium strategy of all parties is that both government regulatory department and e-commerce platform implement supervision, e-commerce company conduct nondifferential pricing, and consumer is loyal to the e-commerce company. However, when the strict supervision cost of government increases and exceeds the social benefits of government strict supervision on differential pricing of e-commerce company, the government gradually inclines to loose supervision strategy. At this moment, if platform and consumer can supervise the pricing of the e-commerce company to a certain extent, e-commerce company still incline to nondifferential pricing strategy. When the strict supervision cost of government increases to a very high level, not only the government cannot strictly supervise, but also e-commerce platform will not supervise the information used by the e-commerce company. Then e-commerce company will incline to differentiate pricing, and the consumer will be disloyal.(4)
The probability of the consumer discovering differential pricing under the government’s loose supervision policy is an important factor affecting the strategies of all parties. As strict supervision cost of government is at a higher level, and the probability of consumer discovering differential pricing of the e-commerce company is small, neither the government nor the e-commerce platform can incline to the more stable behavioral strategy. Although customer inclines to be loyal to the e-commerce company, the strategies of four subjects cannot maintain the stable equilibrium, and the strategy of e-commerce company become cyclical alternating between differential pricing and nondifferential pricing. When the probability of consumer discovering differential pricing of e-commerce company increases, e-commerce company gradually inclines to nondifferential pricing strategy, e-commerce platform gradually inclines to information supervision strategy, and the government gradually inclines to loose supervision strategy. The equilibrium strategy of four-party behavior achieves. The higher the probability level of consumer discovering differential pricing, the faster the equilibrium strategy of four-party behavior achieves. This conclusion also confirms the conclusion in the research of Yu and Li [9] and Wu et al. [30] that the probability of consumer finding himself killed in price is the important factor affecting the strategy choice of consumer and company.(5)
The penalties for differential pricing of e-commerce company under the government’s loose regulatory are the important factors affecting the strategies of all parties. When consumers, e-commerce platform and government regulatory department impose the fines and compensation on differential pricing of e-commerce companies at a low level, the government and e-commerce platform incline to not supervise, and e-commerce company and consumer cannot maintain a stable equilibrium. When the penalties for differential pricing of e-commerce company is high, e-commerce platform inclines to supervise the information, consumer inclines to be loyal, while e-commerce company inclines to price nondifferentially, the government inclines to loose supervise, and the strategies remains stable. The higher the penalties for differential pricing of e-commerce company, the faster the equilibrium strategy of four-party behavior achieves.In this study, the modeling analysis and simulation of the supervision of “big data killing” of e-commerce company are carried out, which breaks through the limitation of analyzing only two or three parties in the existing “big data killing” problem. It is a beneficial supplement to systematic research on this issue that more participants consider their action strategies under the same system. The four-party evolutionary game model constructed also expands the application scope of the evolutionary game method in the study of pricing supervision of e-commerce company. The research conclusions can provide favorable theoretical support for the “big data killing” problem in practice.Therefore, to better restrain the pricing behavior of e-commerce company, regulate differential pricing, and build a good e-commerce shopping environment, the following measures should be taken by the government regulatory department, e-commerce platform, e-commerce company, and consumer.(1)
From the perspective of the government, the government regulatory department must supervise e-commerce company, especially in the early stage of price discrimination by using customer information. Therefore, the government needs to use economic and policy means to effectively manage the operation of e-commerce platform and company and promote the enthusiasm of e-commerce company to conduct nondifferential pricing. For example, adopting more advanced big data analysis technology to supervise price changes of e-commerce company; establishing more extensive and efficient reporting channels so that consumers can timely price complaints; improving corresponding legal measures to increase the violation cost of the e-commerce company and punishing “big data killing” from the aspects of economy and reputation. While supervising, it is also necessary to pay attention to reducing the strict supervision cost of the government regulatory department.(2)
From the perspective of the e-commerce platform, as the important carrier of e-commerce operation, the e-commerce platform should strengthen information supervising of the e-commerce company. The e-commerce platform is the main body that controls customer information. E-commerce company conducts “big data killing” differential pricing based on the mastery of customer information. Therefore, the e-commerce platform needs to carry out information supervision when providing information for the e-commerce company and formulates policies to punish e-commerce company with differential pricing. It is also necessary to improve the technical management level of the e-commerce platform, and use innovative technology based on big data to monitor e-commerce company and reduce the supervision cost of the e-commerce platform.(3)
From the perspective of consumers, they should actively protect their rights and interests. While online shopping brings convenience to consumers, it may also lead to the possibility of price discrimination with consumer information. In the process of e-commerce shopping, consumers will prefer some e-commerce companies due to path dependence, and then form customer loyalty, but this path dependence should not be the reason for the differential pricing of e-commerce companies. Therefore, consumers should enhance price sensitivity and verify the displayed price of e-commerce companies through various channels, to reduce the infringement of consumer rights and interests by e-commerce companies.(4)
From the perspective of the e-commerce company, although maximizing profits is the important motive of business behavior, the reputation and service in e-commerce shopping are the foundation for the long-term development of the e-commerce company. Under the market conditions where consumers’ transfer costs are getting lower and lower, the e-commerce company can grow gradually mainly based on gaining the loyal customer. Therefore, e-commerce company should not adopt the differential pricing strategy in pursuit of temporary benefits. Although the economic benefits brought by nondifferential pricing of e-commerce company are less in the short term, the reputation benefits and social benefits can create greater economic benefits for the development of the company in the long term, which are the wealth of e-commerce company. The reputation benefits and social benefits brought by nondifferential pricing can be benefit for the more fair and equitable overall development environment for e-commerce.This study systematically analyzes the model on the supervision of “big data killing” in the e-commerce company. However, the mechanism setting of the four-party game in the study has been simplified to a certain extent, and the strategy space needs to be more detailed and in-depth, which should be improved in the future. Moreover, because the simulation data were conducted under simulated conditions according to actual conditions, there may be some deviations in the effectiveness of players’ behavior analysis in the “big data killing” game. In the future, methods such as data mining will be used to collect big data, and empirical analysis of evolutionary game will be carried out, to improve the research on the participants behavior of “big data killing” in e-commerce transactions.
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*Source: 2900286-2022-03-18.xml* | 2900286-2022-03-18_2900286-2022-03-18.md | 156,159 | Supervision Strategy Analysis on Price Discrimination of E-Commerce Company in the Context of Big Data Based on Four-Party Evolutionary Game | Meng Xiao | Computational Intelligence and Neuroscience
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2900286 | 2900286-2022-03-18.xml | ---
## Abstract
This paper focuses on the phenomenon of “big data killing” implied in e-commerce and discusses how to take the government as the lead to coordinately supervise the price discrimination behavior of e-commerce companies towards loyal customers. First, the four-party evolutionary game model of the government regulatory department, e-commerce platform, e-commerce company, and consumer is built. Second, the stability of the strategy choice of each game subject is analyzed. On this basis, the evolutionary stable strategy in the system based on First Law of Lyapunov is explored. Finally, the influences of key elements on system evolution are simulated and analyzed by MATLAB2021. Results demonstrate that (1) the government supervision mechanism can effectively supervise the price discrimination of e-commerce company based on big data to loyal customers; (2) when the government chooses the strict supervision strategy, reducing the information supervision cost of the e-commerce platform and the strict supervision cost of the government enable the government and the e-commerce platform to coordinate supervision and make the e-commerce company incline to choose the nondifferential pricing strategy; (3) when the government chooses the loose supervision strategy, reducing the information supervision cost of the e-commerce platform and increasing the probability of consumer discovering differential pricing and the penalties for differential pricing of e-commerce company enable the e-commerce platform and consumer to coordinate supervision, and make the e-commerce company incline to choose the nondifferential pricing strategy. The results of this study can provide theoretical guidance for the government and companies to make beneficial strategic decisions in the development of e-commerce.
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## Body
## 1. Introduction
With the rise of big data, e-commerce is becoming more and more prosperous. E-commerce can bring convenience to consumers with a variety of options and also collect consumer consumption data and draw user portraits by using big data technology [1]. While the application of algorithms injects new growth drivers into social and economic development, problems caused by the unreasonable application of algorithms such as algorithm discrimination, “big data killing,” and inducing addiction also profoundly affect the normal communication in the market and destroy the market order. Online supply chain stores have different pricing based on user location. On some online booking websites, the price of hotel rooms for Apple customer is higher than that for Windows customer. The well-known e-commerce company, Amazon, was found to use big data to “kill regular” [2]. It priced for different consumers according to their information and purchasing data on the platform. Loyal customers made purchase transactions based on their trust and path dependence on the Amazon platform, but due to the asymmetry of information in the transaction process, some regulars pay higher prices than strangers. This “big data killing” behavior has exposed the hidden dangers of moral hazard in the e-commerce market and makes the industry encounter an unprecedented crisis of trust. “Big data killing” has become an urgent problem to be solved in the fast development of online business [3].The essence of big data killing is price discrimination. Price discrimination refers to formulating different price strategies for different customer groups. However, in traditional business, both “stranger” and “regular” may be discriminated against, while with the participation of algorithm technology, there are more “killing regular” in Internet business. Even in the process of “killing regular,” big data has become a necessary tool. Each platform will collect a lot of user information, and then the company uses technology to offer different prices and discounts for different customers based on the information. Traditionally, companies have not been able to predict the upper limit of the price that buyers want to pay, but based on the technology of big data, the companies can determine the maximum willing price with a high degree of accuracy with sophisticated algorithms [4]. As the collection of consumer data becomes more common, online companies are now more capable of price discrimination than ever [5]. As customer of the Internet commercial company, VIP customer with higher loyalty and stronger consumption power pay much more for the same service than new customers, but gain even lower service quality. Big data killing will cause a variety of harm. Moriarty [6] proposed that customer information is widely used in online retail pricing, and although the benefit of online retailers will increase, price discrimination can cause serious fairness concerns and even violation of regulations and laws. Antimonopoly issues in the digital economy, especially the antimonopoly issues of big data and discrimination algorithms, have been brought to the attention of experts and practitioners. “Killing regular” is algorithmic price discrimination, with which online platforms charge long-term customers higher prices. It is believed that this kind of price discrimination violates the law on antimonopoly and should be held accountable according to the relevant law. The Cyberspace Administration of China (CAC) issued the regulations on The Management of Algorithm Recommendation for Internet Information Services to regulate the “big data killing,” stepping into the era of strict supervision of the industry related to algorithm recommendation. The EU also prohibits discrimination on certain grounds and strictly regulates unfair business practices in B2C relationships [7].Although some studies have carried out related discussion on the problem of big data killing [2, 8], some solutions are proposed [9, 10]. However, existing studies are mostly limited to the pricing between e-commerce companies and consumers [11, 12], the strategic choice between e-commerce platform and consumer, and the supervision strategy choice between e-commerce platform and government [9, 13]. There are few systematic studies on the four-party strategy composed of multiple subjects related to “big data killing.” Therefore, this study establishes an evolutionary game model dominated by government supervision that affects the decision-making of consumer, e-commerce company, and platform, analyzes and simulates that different supervision costs of government and e-commerce platform, consumer discovery levels, and the penalties for differential pricing of e-commerce company affect system equilibrium, evolutionarily stable strategy, and the pricing strategy of e-commerce company, and also establishes the platform-consumer-government collaborative supervision mechanism for e-commerce company pricing behavior. This research contributes to curbing the “big data killing” behavior of e-commerce company, enhance consumers’ confidence in online shopping, and has a positive effect in promoting the development of e-commerce.
## 2. Related Literature
Existing research on price discrimination in e-commerce companies mainly focuses on three aspects: the prevalence of price discrimination by using customer information, the influence factors of price discrimination, and the supervision and management of price discrimination:On the prevalence of price discrimination by e-commerce companies using customer information, although many media outlets provide various evidence of price discrimination, most of them are not based on scientific and systematic methods. Therefore, scholars have researched whether e-commerce companies use big data to discriminate against consumers in price. Botta and Klaus [14] qualitatively proposed that algorithmic price discrimination is different from offline differential pricing and is related to the collection of consumer information, which is a unique feature of the digital economy. With the wide application of big data and the gradual deepening of algorithm technology, the e-commerce company can price discriminate against consumers with great precision [4], and these were confirmed empirically [4, 15]. The pricing ecosystem of the online platform is a dynamic pricing system [15]. Algorithmic price discrimination [16], artificial intelligence techniques, and digital system fingerprints [15] enable the e-commerce company to have the ability of price discrimination. Price discrimination is not only widespread in the field of commodity sales, and there are also discrimination and price difference by using customer information in the field of online car-hailing [8] and the field of advertising recommendation [7, 17]. While consumers benefit from accurate recommendations, sellers may use this information to discriminate on price. Thus, price discrimination is not favored by people [18].Scholars have done a lot of studies on the influence factors of price discrimination in e-commerce companies. Some scholars believe that the premise of “big data killing” is the information asymmetry between e-commerce company and customers [1]. Consumer information data is an influencing factor for the e-commerce company to be able to discriminate in price [19], such as consumer characteristics, location [14], etc., and these data also relate to consumers’ privacy [12]. Nuccio and Marco [20] studied how pricing technology and information transparency are changing merchants’ pricing behavior in online transactions. The price sensitivity and heterogeneity of consumers are factors that affect e-commerce company to set price differentials [11]. Some scholars have analyzed the effects of reference price and search cost on differential pricing and find that consumers’ search cost has become one of the obstacles affecting consumers’ online shopping, which has formed an unequal situation for consumers [21] and has become a tool for e-commerce companies to formulate differential prices [22, 23]. The target of “big data killing” of e-commerce companies is focused on loyal consumers, which has been confirmed by many scholars. For example, Tang et al. [24] found in the research on the group-buying market that with the improvement of consumer retention rate, the best strategy of sellers is changed from quality difference to price discrimination. Chandra and Lederman [25] argued that if consumers have differences in potential willingness to pay and brand loyalty, e-commerce companies may increase price differences among some consumers while reducing price differences among the other consumers. Although differential pricing is an important way for e-commerce companies to obtain profits [26], its focus on loyal consumers is contrary to the principle of fair pricing [24], which will reduce consumer satisfaction and create distrust [27, 28].After the problem of “big data killing” was exposed, it has been attracted widespread attention by scholars, and its supervision and governance have also become an important research topic. Bar-Gill [29] proposed that the normative evaluation of price discrimination depends on the object of discrimination, and the algorithmic price discrimination has the advantages to improve efficiency, but it will harm consumers, which should be governed by rules set by regulators to seriously exploit the potential of personalization. Yu and Li [9] also believed that consumers’ discovery and reporting of being “killed” is the mean to monitor price discrimination of e-commerce company. Xing et al. [3] found that when regulars account for a high proportion of platform customer, giving consumers the right to data portability can curb the phenomenon of “big data killing” to a certain extent. In addition to consumers’ self-discovery of price discrimination by the e-commerce company, many scholars believe that with the help of government supervision [13], increasing penalties and the commission coefficient of government departments [30] can effectively reduce the “killing regular” pricing tendency of e-commerce platforms. However, in the supervision process of existing research, there was little distinction between e-commerce platform and company, and the research is carried out in a mixed way. Most of the discussions focus on the pricing of e-commerce platforms known for its scale. Differential pricing of e-commerce company on the platform is rarely discussed separately, and there is still a lack of research considering multichannel collaborative supervision.Existing studies have adopted a variety of methods for the problem of price discrimination in the e-commerce company. For example, the dynamic pricing method is used in specific pricing. Lindgren et al. [31] studied dynamic pricing by intertemporal price discrimination theory and proposed that retailers should change prices randomly over time. Chevalier and Kashyap [32] proposed the method for aggregating prices when retailers use periodic sales to discriminate price against heterogeneous customers. Tremblay [5] designed more efficient Pareto price discrimination. Game methods are often used in the selection of pricing strategies. Choe et al. [33] analyzed pricing strategy with a two-stage dynamic game model. Zhou et al. [34] adopted two-stage game analysis on joint pricing and bandwidth demand optimization. On the game of price discrimination, the bounded rationality assumption in the evolutionary game makes the research more realistic [30], so many scholars use evolutionary game methods to study this problem [1, 13, 30, 35] and extended to multiple fields of online transactions, such as manufacturing business [36]. However, most studies are limited in the two-party game [22, 37], it is still unclear to analyze the relationship and role of e-commerce company, consumer, e-commerce platform, and the government in the “big data killing” problem system, and their decision-making mechanism needs further research.Therefore, as the price discrimination of e-commerce companies is generated with new technologies, the existing research on this phenomenon is still in the exploratory stage. Most perspectives of the previous research are from both sides of the transaction in traditional business, and there are few differences in the analysis of the e-commerce platform and the companies in the platform. Moreover, the supervision on the differential pricing of the e-commerce company using big data technology to the loyal customers is not very perfect, and some policies and supervision methods are still under discussion. This study systematically analyzes the government, e-commerce platform, e-commerce company, and consumer involved in the supervision of “big data killing,” which makes up for the insufficiency of the existing research and provides useful help for further regulating such behavior.
## 3. Materials and Methods
### 3.1. Problem Description
The e-commerce company will use the platform to collect consumer information during the operation in the network platform. Based on the information provided by the platform, e-commerce company analyzes consumers and raise prices by judging their consumption habits. The pricing strategy of “big data killing” is price discrimination caused by e-commerce company using the feature of opaque information in the online transaction process to different pricing of consumers through big data and complex algorithms. This kind of behavior will bring consumers’ distrust of e-commerce companies and e-commerce platforms, which is not conducive to the development of e-commerce. Therefore, both the government regulatory department and e-commerce platforms should take necessary measures to supervise the price discrimination behavior of e-commerce companies. This study mainly discusses the following three questions: (1) in the context of big data development, how can the government regulatory department take supervision measures to reduce the proportion of price discrimination by e-commerce company? (2) How can e-commerce platform be motivated to supervise information on e-commerce companies? (3) How can consumers be guided to actively safeguard their rights and interests and maintain consumption fairness.This study builds a multi-agent game model for the supervision of price discrimination in e-commerce companies involving the e-commerce platform, the e-commerce company, the consumer, and the government regulatory department. The logical relationship among four-party game subjects is shown in Figure1.Figure 1
Game model logic relationship of multisubject supervision on e-commerce company pricing.
### 3.2. Model Assumption
To build the multisubject supervision model of the e-commerce company pricing in the background of big data, the behavioral strategies of government regulatory department, e-commerce platform, e-commerce company, and consumer are studied, and the following assumptions are made.Assumption 1.
Government regulatory department, e-commerce platform, the e-commerce company, and consumer are selected as the game subjects. Each game subject is bounded rationality and pursues the maximization of their interests in e-commerce transactions. Due to the information asymmetry between game subjects, random behavior strategies, and interactive effects, the optimal strategy cannot be obtained through one game. It is necessary to continuously try and learn in multiple rounds of games to improve the strategy, to formulate the best match of behavioral decision. Therefore, the evolutionary game should be used to analyze the four-party equilibrium strategy. The proportion of e-commerce company implementing nondifferential pricing is represented asx (0 ≤ x ≤ 1), and the proportion of e-commerce company implementing differential pricing is denoted as (1 − x); the proportion of consumer loyalty is represented as y (0 ≤ y ≤ 1) and the proportion of consumer disloyalty is represented as (1 − y); the proportion of e-commerce platform to supervise company information is represented as z (0 ≤ z ≤ 1), and the proportion of e-commerce platform with information nonsupervision is denoted as (1 − z); the proportion of the government regulatory department strictly supervising e-commerce platform and company is denoted as r (0 ≤ r ≤ 1), and the proportion of loosely supervises e-commerce platform and the company is denoted as (1 − r).Assumption 2.
The benefit of nondifferential pricing of the e-commerce company isPn, and the basic benefit of differential pricing is Pd. When the e-commerce company implements differential pricing for loyal consumer, additional benefit ∆P can be obtained due to the increase in selling price, and Pd < Pn < Pd+∆P. The probability of loyal consumers discovering differential pricing of the e-commerce company is α. When consumer purchases goods, the utility obtained by the loyal consumer is Ul, and the utility obtained by the disloyal consumer is Ud, and Ul > Ud. The reputation value of the loyal consumer to the e-commerce company is Te and the reputation value of the loyal consumer to the e-commerce platform is Tp.Assumption 3.
When the government strictly supervises, if price discrimination of the e-commerce company is found, loyal consumers who are subject to differential pricing will be compensated with the compensation amount ofM; When the government loosely supervises, if the loyal consumer is the price-sensitive consumer, he may use Internet information for comparison and analysis, and then find that he has been “killed”. If the cost of reporting is small and the procedure is simple, the consumer will carry out to inform the government regulatory department, and then the e-commerce company must be forced to compensate the consumer. The consumer’s complaint cost is Cc.Assumption 4.
The normal benefit that the government obtains from the operation of the e-commerce platform isS. The cost of strict supervision by government departments is Cg. The social benefit obtained by the government is R if there is no price discrimination by the e-commerce company. If the government adopts the loose supervision policy, consumer complaints will bring social reputation loss as N. After receiving the information, the e-commerce company for price discrimination will be penalized by the government regulatory department, and the fine will be Ie.Assumption 5.
The price discrimination of e-commerce company depends on the information provided by the platform. The benefit of the platform reasonably providing information to the e-commerce company isW, and the cost of the platform information supervision on e-commerce company is Cp. When the e-commerce platform finds the price discrimination of e-commerce company on the consumer, the fine to e-commerce company is F. The e-commerce platform and consumers share this fine in the ratio of β and 1 − β. When the government finds price discrimination by the e-commerce company, it will impose the fine of Ip for the platform’s unfavorable supervision to e-commerce company information.
The parameters are described in Table1.Table 1
Parameter description.
ParameterDescriptionPnThe benefit of nondifferential pricing by e-commerce company to consumerPdThe benefit of differential pricing by e-commerce company to consumer∆PThe additional benefit of differential pricing by e-commerce company to the loyal consumerMCompensation of e-commerce company to the loyal consumer for differential pricingTeThe reputation value of the loyal consumer to e-commerce companyUlThe utility obtained by the loyal consumer from purchasing goodsUdThe utility obtained by the disloyal consumer from purchasing goodsCcThe cost of consumer complaintαProbability of loyal consumer discovering differential pricing under government loose supervision, andα∈0,1CgThe cost of strict supervision by the government regulatory departmentNSocial reputation loss caused by differential pricing under government loose supervisionRThe social benefit of nondifferential pricing under the government strict supervisionIeFine by government regulatory department for differential pricing to e-commerce companyIpFine by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricingSThe normal benefit obtained by the government from the operation of the e-commerce platformWThe benefit of the platform reasonably providing information to the e-commerce companyCpThe cost of the platform’s information supervision on the e-commerce companyFFines imposed by the platform to e-commerce company for differential pricing during information supervisionβThe proportion of the fine imposed by the e-commerce platform for differential pricing of e-commerce company,β∈0,1TpThe reputation value of the loyal consumer to the e-commerce platform
### 3.3. Model Framework
According to the above analysis, the mixed-strategy game matrix of the four-party game subjects of government regulatory department, e-commerce platform, e-commerce company, and consumer is shown in Table2.Table 2
Game model benefit matrix of government regulatory department, e-commerce platform, e-commerce company, and consumer
Strategy choiceE-commerce companyGovernment regulatory departmentStrict supervision,rLoose supervision, 1 −rLoyaltyyDisloyalty 1 −yLoyaltyyDisloyalty 1 −yE-commerce platformInformation supervisionzNondifferential pricingxPn + TePnPn + TePnUlUdUlUdW − Cp + TpW − CpW − Cp + TpW − CpS − Cg+RS − Cg + RSSDifferential pricing 1 −xPd + ∆P + Te − M − Ie − FPd − Ie − FPd + ∆P + Te − αM − αIe − FPd − FUl− ∆P + M + (1 − β)FUdUl − ∆P − Cc + αM + (1 − β)FUdW − Cp + βF + TpW − Cp + FW − Cp + βF + TpW − Cp + FS −Cg + IeS −Cg + IeS + αIe− NS − NInformation nonsupervision 1 −zNondifferential pricingxPn + TePnPn + TePnUlUdUlUdW + TpWW + TpWS −Cg + RS −Cg + RSSDifferential pricing 1 −xPd + ∆P + Te− M − IePd− IePd + ∆P + Te− αM − αIePdUl− ∆P + MUdUl− ∆P − Cc + αMUdW − Ip + TpW − IpW − αIp + TpWS −Cg + Ie + IpS −Cg+Ie + IpS+αIe+αIp− NS − N
### 3.4. Model Analysis
#### 3.4.1. Strategy Stability Analysis of the E-Commerce Company
Assuming that the expected benefit of the e-commerce company when choosing the nondifferential pricing strategy isU11, the expected benefit of the e-commerce company when choosing the differential pricing strategy is U12, and the average expected benefit of the e-commerce company is U1¯, which are defined as follows:(1)U11=yzrPn+Te+1−yzrPn+y1−zrPn+Te+1−y1−zrPn+yz1−rPn+Te+1−yz1−rPn+y1−z1−rPn+Te+1−y1−z1−rPn=Pn+yTe,U12=yzrPd+ΔP+Te−M−Ie−F+1−yzrPd−Ie−F+y1−zrPd+ΔP+Te−M−Ie+1−y1−zrPd−Ie+yz1−rPd+ΔP+Te−αM−αIe−F+1−yz1−rPd−F+y1−z1−rPd+ΔP+Te−αM−αIe+1−y1−z1−rPd=Pd+yΔP+Te−yM+Ier+1−rα−1−yrIe−zF,U1¯=xU11+1−xU12.According to the Malthusian dynamic equation, the replication dynamic equation of the e-commerce company is obtained as follows:(2)Fx=dxdt=xU11−U1¯=x1−xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.The first partial derivative ofF (x) for x is as follows:(3)Fx′x=1−2xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.Based on the stability theorem of differential equations, the e-commerce company implements the strategy of nondifferential pricing in the stable state must meet the conditions:Fx = 0, and Fx′x < 0.Proposition 1.
Whenr > r0, the stable strategy of the e-commerce company is nondifferential pricing; when r < r0, the stable strategy of the e-commerce company is differential pricing; when r = r0, the e-commerce company cannot determine the stable strategy. Where the threshold is as follows:(4)r0=Pd+yΔP−Pn−αyM+Ie−zF1−αyM+1−αyIe.Proof.
AssumeHr=Pn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF, when yM−αM+Ie>0, ∂H/∂r > 0, then H (r) is considered to be an increasing function of r. When r > r0, H (r) > 0, Fx|x=1=0, and Fx′x|x=1<0, so x = 1 has stability; When r < r0, H (r) < 0, Fx|x=0=0, and Fx′x|x=0<0, so x = 0 has stability; when r = r0, H (r) = 0, Fx=0, and Fx′x=0, so x is stable at all levels in the range of 0 to 1, that is, the company’s strategy does not change over time, regardless of the proportion of company choosing to price differentially.
Proposition1 states that the increase of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from differential pricing to nondifferential pricing; Similarly, the decline of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from nondifferential pricing to differential pricing. Therefore, the government’s strict supervision for e-commerce company is essential, and the government should take measures to improve strict supervision for the e-commerce company.
Based on Proposition1, the phase diagram of the strategy evolution of e-commerce company is shown in Figure 2.
Inference 1: with the increase of the value ofPn, M, Ie, F, and α, the e-commerce company is more inclined to implement the nondifferential pricing strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Pd and ∆P, the e-commerce company is more inclined to implement the differential pricing strategy. It shows that the proportion of e-commerce company implementing nondifferential pricing strategy is directly proportional to the benefits of nondifferential pricing, the fines imposed by the government and platform on e-commerce company for differential pricing and the probability of consumers’ discovery, and inversely proportional to the benefits of e-commerce company implementing differential pricing strategy.Figure 2
Phase diagram of strategy evolution of e-commerce company.Proof.
Sincer0=Pd+yΔP−Pn−αyM+Ie−zF/1−αyM+1−αyIe, the volume of Vx1 in Figure 2 represents the proportion of nondifferential pricing by the e-commerce company, and the corresponding volume of Vx0 represents the proportion of differential pricing by the e-commerce company. When the value of Pn, M, Ie, F, and α gradually increases, the value of r0 will gradually decrease, and the volume of Vx1 will increase at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing increases; When the value of Pd and ∆P gradually increases, the value of r0 will gradually increase, and the volume of Vx1 will decrease at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing decreases.
#### 3.4.2. Strategy Stability Analysis of the Consumer
Assuming that the expected benefit of the consumer when choosing loyalty strategy to e-commerce company isU21, the expected benefit of the consumer when choosing disloyalty strategy to e-commerce company is U22, and the average expected benefit of the consumer is U2¯, which are defined as follows:(5)U21=xzrUl+1−xzrUl−ΔP+M+1−βF+x1−zrUl+1−x1−zrUl−ΔP+M+xz1−rUl+1−xz1−rUl−ΔP−Cc+αM+1−βF+x1−z1−rUl+1−x1−z1−rUl−ΔP−Cc+αM=Ul−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF,U22=xzrUd+1−xzrUd+x1−zrUd+1−x1−zrUd+xz1−rUd+1−xz1−rUd+x1−z1−rUd+1−x1−z1−rUd=Ud,U2¯=yU21+1−yU22.According to the Malthusian dynamic equation, the replication dynamic equation of consumer is obtained as follows:(6)Fy=dydt=yU21−U2¯=y1−yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.The first partial derivative ofF (y) for y is as follows:(7)Fy′y=1−2yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.Based on the stability theorem of differential equations, consumer implements the strategy of loyalty in the stable state must meet the conditions:Fy = 0, and Fy′y < 0.Proposition 2.
Whenx > x0, the stable strategy of the consumer is loyalty; when x < x0, the stable strategy of the consumer is disloyalty; when x = x0, the consumer cannot determine the stable strategy. Where the threshold is as follows:(8)x0=Ul−Ud+M−ΔP+1−rαM−Cc+z1−βFM−ΔP+1−rαM−Cc+z1−βF.Proof.
AssumeHx=Ul−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF, when M−ΔP+1−rαM−Cc+z1−βF>0, ∂H/∂x > 0, H (x) is considered to be an increasing function of x. When x > x0, H (x) > 0, Fy|y=1=0, and Fy′y|y=1<0, so y = 1 has stability; When x < x0, H (x) < 0, Fy|y=0=0, and Fy′y|y=0<0, so y = 0 has stability; When x = x0, H (x) = 0, Fy=0, and Fy′y=0, so y is stable at all levels in the range of 0 to 1, that is, the consumer’s strategy does not change over time, regardless of the proportion of consumer choosing to be loyal.
Proposition2 states that the increase of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from disloyalty to loyalty; Similarly, the decline of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from loyalty to disloyalty. Therefore, e-commerce company should reduce the degree of difference in pricing for consumers and try to retain consumers.
Based on Proposition2, the phase diagram of the strategy evolution of consumer is shown in Figure 3.
Inference 2: with the increase of the value ofUl, M, F, α, and β, the consumer is more inclined to be loyalty strategy to the e-commerce company, when other parameters remain unchanged. Similarly, with the increase of the value of Ud, ∆P, and Cc, the consumer is more inclined to be disloyalty strategy to the e-commerce company. It shows that the proportion of consumer being loyalty strategy to e-commerce company is directly proportional to the utility obtained by the loyal consumer from purchasing goods, the fines imposed by the government and e-commerce platform for differential pricing of e-commerce company, and the probability of consumers’ discovery, and inversely proportional to the utility obtained by the disloyal consumer in purchasing goods, the additional benefit obtained by the e-commerce company in implementing differential pricing, the proportion of fines imposed by the platform to the e-commerce company and the cost of consumer complaints.Figure 3
Phase diagram of strategy evolution of consumer.Proof.
Sincex0=1−Ul−Ud/ΔP+1−rCc−1+1−rαM−z1−βF, the volume of Vy1 in Figure 3 represents the proportion of loyalty to e-commerce company by the consumer, and the corresponding volume of Vy0 represents the proportion of disloyalty to e-commerce company by the consumer. When the value of Ul, M, Ie, F, and α gradually increases, the value of x0 will gradually decrease, and the volume of Vy1 will increase at this time, indicating that the proportion of loyalty to e-commerce company by the consumer increases; When the value of Ud, ∆P, β and Cc gradually increase, the value of x0 will gradually increase, and the volume of Vy1 will decrease at this time, indicating that the proportion of loyalty to e-commerce company by consumer decreases.
#### 3.4.3. Strategy Stability Analysis of E-Commerce Platform
Assuming that the expected benefit of the e-commerce platform when choosing the information supervision strategy isU31, the expected benefit of the e-commerce platform when choosing the information nonsupervision strategy is U32, and the average expected benefit of the e-commerce platform is U3¯, which are defined as follows:(9)U31=xyrW−Cp+TP+x1−yrW−Cp+1−xyrW−Cp+TP+βF+1−x1−yrW−Cp+TP+xy1−rW−Cp+βF+x1−y1−rW−Cp+1−xy1−rW−Cp+TP+βF+1−x1−y1−rW−Cp+βF=W−Cp+F+yTp−xF,U32=xyrW+TP+x1−yrW+1−xyrW−Ip+TP+1−x1−yrW−Ip+xy1−rW+TP+x1−y1−rW+1−xy1−rW−αIp+TP+1−x1−y1−rW=W+yTp−1−xrIp−1−xy1−rIp,U3¯=zU31+1−zU32.According to the Malthusian dynamic equation, the replication dynamic equation of e-commerce platform is obtained as follows:(10)Fz=dzdt=zU31−U3¯=z1−zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.The first partial derivative ofF (z) for z is as follows:(11)Fz′z=1−2zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.Based on the stability theorem of differential equations, e-commerce platform implements the strategy of information supervision in the stable state must meet the conditions:Fz = 0, and Fz′z <0.Proposition 3.
Wheny > y0, the e-commerce platform will choose information supervision as the stable strategy; when y < y0, the e-commerce platform will choose information nonsupervision as the stable strategy; when y = y0, the e-commerce platform cannot determine the stable strategy. Where the threshold is as follows:(12)y0=Cp+xβF+1−xrIp−βFTp−1−x1−rIp.Proof.
AssumeHy=F−Cp+yTp−xF−1−xrIp−1−xy1−rIp, when Tp−1−x1−rIp>0, ∂H/∂x >0, H (y) is considered to be an increasing function of y. When y > y0, H (y) > 0, Fz|z=1=0, and Fz′z|z=1<0, so z = 1 has stability; When y < y0, H (y) < 0, Fz|z=0=0, and Fz′z|z=0<0, so z = 0 has stability; When z = z0, H (y) = 0, Fz=0, and Fz′z=0, so z is stable at all levels in the range of 0 to 1, that is, the e-commerce platform’s strategy does not change over time, regardless of the proportion of e-commerce platform choosing information supervision.
Proposition3 states that the increase of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information nonsupervision to information supervision. Similarly, the decline of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information supervision to information nonsupervision. Therefore, if the consumer can be loyal to the e-commerce company in the platform, the platform will also actively supervise its subordinate company.
Based on Proposition3, the phase diagram of the strategy evolution of the e-commerce platform is shown in Figure 4.
Inference 3: with the increase of the value ofF, β, and Tp, the e-commerce platform is more inclined to implement the information supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cp and Ip, the e-commerce platform is more inclined to implement the information nonsupervision strategy. It shows that the proportion of e-commerce platform implementing information supervision strategy is directly proportional to the fines imposed by the platform for differential pricing of e-commerce company, the proportion of fines imposed by the e-commerce platform for differential pricing of e-commerce company, and the reputation value brought by the loyal consumer to the platform, and inversely proportional to the cost of the platform’s information supervision on e-commerce company and the fines by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricing.Figure 4
Phase diagram of strategy evolution of e-commerce platform.Proof.
Sincey0=Cp+1−xrIp−1−xβF/Tp−1−x1−rIp, the volume of Vz1 in Figure 4 represents the proportion of information supervision of e-commerce company by the platform, and the corresponding volume of Vz0 represents the proportion of information nonsupervision by the platform. When the value of F, β, and Tp gradually increase, the value of y0 will gradually decrease, and the volume of Vz1 will increase at this time, indicating that the proportion of e-commerce platform to implement information supervision increases; When the value of Cp and Ip gradually increases, the value of y0 will gradually increase, and the volume of Vz1 will decrease at this time, indicating that the proportion of e-commerce platform to implement information supervision decreases.
#### 3.4.4. Strategy Stability Analysis of Government Regulatory Department
Assuming that the expected benefit of government regulatory department when government implementing the strategy of strictly supervising isU41, the expected benefit of government regulatory department when government implementing the strategy of loosely supervising is U42, and the average expected benefit of the government regulatory department is U4¯, which are defined as follows:(13)U41=xyzS−Cg+R+x1−yzS−Cg+R+1−xyzS−Cg+Ie+1−x1−yzS−Cg+Ie+xy1−zS−Cg+R+x1−y1−zS−Cg+R+1−xy1−zS−Cg+Ie+Ip+1−x1−y1−zS−Cg+Ie+Ip=S−Cg+xR+1−xIe+1−x1−zIp.U42=xyzS+x1−yzS+1−xyzS−N+αIe+1−x1−yzS−N+xy1−zS+x1−y1−zS+1−xy1−zS−N+αIe+αIp+1−x1−y1−zS−N=S−1−xN+1−xyαIe+1−zIp,U4¯=rU41+1−rU42.According to the Malthusian dynamic equation, the replication dynamic equation of the government regulatory department is obtained as follows:(14)Fr=drdt=rU41−U4¯=r1−r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.The first partial derivative ofF (r) for r is as follows:(15)Fr′r=1−2r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.Based on the stability theorem of differential equations, government regulatory department implements the strategy of strictly supervising in the stable state must meet the conditions:Fr = 0, and Fr′r < 0.Proposition 4.
Whenz > z0, the government regulatory department will choose strict supervision as the stable strategy; when z < z0, the stable strategy of the government regulatory department will choose loose supervision as the stable strategy; when z = z0, the government regulatory department cannot determine the stable strategy. Where the threshold is as follows:(16)z0=−Cg+xR+1−x1−αyIp+1−x1−αyIe+N1−x1−αyIp.Proof.
AssumeHz=−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp, when ∂H/∂x < 0, H (z) is considered to be an increasing function of z. When z < z0, H (z) > 0, Fr|r=1=0, and Fr′r|r=1<0, so r = 1 has stability; When z > z0, H (z) < 0, Fr|r=0=0, and Fr′r|r=0<0, so r = 0 has stability; When z = z0, H (z) = 0, Fr=0, and Fr′r=0, so z is stable at all levels in the range of 0 to 1, that is, the government regulatory department’s strategy does not change over time, regardless of the proportion of government regulatory department choosing to strict supervision.
Proposition4 states that the decline of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from loose supervision to strict supervision; Similarly, the increase of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from strictly supervising to loosely supervising. Therefore, the government’s strict supervision on e-commerce company is the necessary measure under the unfavorable conditions of the e-commerce platform’s information supervision on e-commerce company.
Based on Proposition4, the phase diagram of strategy evolution of the government regulatory department is shown in Figure 5.
Inference 4: With the increase of the value ofR, Ie, Ip, and N, the government regulatory department is more inclined to implement the strict supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cg and α, the government is more inclined to implement the loose supervision strategy. It shows that the proportion of government regulatory department implementing strict supervision strategy is directly proportional to the social benefits obtained, the fines punished by the government on e-commerce company and platform, and the social reputation loss caused by differential pricing under the government’s loose supervision, and inversely proportional to the cost for the government to strictly supervise and the proportion of consumer discovering differential pricing.Figure 5
Phase diagram of strategy evolution of government regulatory department.Proof.
Sincez0=1−Cg−xR−1−x1−αyIe+N/1−x1−αyIp, the volume of Vr1 in Figure 5 represents the proportion of strictly supervised by the government, and the corresponding volume of Vr0 represents the proportion of loosely supervised by government. When the value of R, Ie, Ip, and N gradually increases, the value of z0 will gradually increase, and the volume of Vr1 will increase at this time, indicating that the proportion of strict supervision by government regulatory department increases; When the value of Cg and α gradually increase, the value of z0 will gradually decrease, and the volume of Vr1 will decrease at this time, indicating that the proportion of strict supervision by government regulatory department increases decreases.
## 3.1. Problem Description
The e-commerce company will use the platform to collect consumer information during the operation in the network platform. Based on the information provided by the platform, e-commerce company analyzes consumers and raise prices by judging their consumption habits. The pricing strategy of “big data killing” is price discrimination caused by e-commerce company using the feature of opaque information in the online transaction process to different pricing of consumers through big data and complex algorithms. This kind of behavior will bring consumers’ distrust of e-commerce companies and e-commerce platforms, which is not conducive to the development of e-commerce. Therefore, both the government regulatory department and e-commerce platforms should take necessary measures to supervise the price discrimination behavior of e-commerce companies. This study mainly discusses the following three questions: (1) in the context of big data development, how can the government regulatory department take supervision measures to reduce the proportion of price discrimination by e-commerce company? (2) How can e-commerce platform be motivated to supervise information on e-commerce companies? (3) How can consumers be guided to actively safeguard their rights and interests and maintain consumption fairness.This study builds a multi-agent game model for the supervision of price discrimination in e-commerce companies involving the e-commerce platform, the e-commerce company, the consumer, and the government regulatory department. The logical relationship among four-party game subjects is shown in Figure1.Figure 1
Game model logic relationship of multisubject supervision on e-commerce company pricing.
## 3.2. Model Assumption
To build the multisubject supervision model of the e-commerce company pricing in the background of big data, the behavioral strategies of government regulatory department, e-commerce platform, e-commerce company, and consumer are studied, and the following assumptions are made.Assumption 1.
Government regulatory department, e-commerce platform, the e-commerce company, and consumer are selected as the game subjects. Each game subject is bounded rationality and pursues the maximization of their interests in e-commerce transactions. Due to the information asymmetry between game subjects, random behavior strategies, and interactive effects, the optimal strategy cannot be obtained through one game. It is necessary to continuously try and learn in multiple rounds of games to improve the strategy, to formulate the best match of behavioral decision. Therefore, the evolutionary game should be used to analyze the four-party equilibrium strategy. The proportion of e-commerce company implementing nondifferential pricing is represented asx (0 ≤ x ≤ 1), and the proportion of e-commerce company implementing differential pricing is denoted as (1 − x); the proportion of consumer loyalty is represented as y (0 ≤ y ≤ 1) and the proportion of consumer disloyalty is represented as (1 − y); the proportion of e-commerce platform to supervise company information is represented as z (0 ≤ z ≤ 1), and the proportion of e-commerce platform with information nonsupervision is denoted as (1 − z); the proportion of the government regulatory department strictly supervising e-commerce platform and company is denoted as r (0 ≤ r ≤ 1), and the proportion of loosely supervises e-commerce platform and the company is denoted as (1 − r).Assumption 2.
The benefit of nondifferential pricing of the e-commerce company isPn, and the basic benefit of differential pricing is Pd. When the e-commerce company implements differential pricing for loyal consumer, additional benefit ∆P can be obtained due to the increase in selling price, and Pd < Pn < Pd+∆P. The probability of loyal consumers discovering differential pricing of the e-commerce company is α. When consumer purchases goods, the utility obtained by the loyal consumer is Ul, and the utility obtained by the disloyal consumer is Ud, and Ul > Ud. The reputation value of the loyal consumer to the e-commerce company is Te and the reputation value of the loyal consumer to the e-commerce platform is Tp.Assumption 3.
When the government strictly supervises, if price discrimination of the e-commerce company is found, loyal consumers who are subject to differential pricing will be compensated with the compensation amount ofM; When the government loosely supervises, if the loyal consumer is the price-sensitive consumer, he may use Internet information for comparison and analysis, and then find that he has been “killed”. If the cost of reporting is small and the procedure is simple, the consumer will carry out to inform the government regulatory department, and then the e-commerce company must be forced to compensate the consumer. The consumer’s complaint cost is Cc.Assumption 4.
The normal benefit that the government obtains from the operation of the e-commerce platform isS. The cost of strict supervision by government departments is Cg. The social benefit obtained by the government is R if there is no price discrimination by the e-commerce company. If the government adopts the loose supervision policy, consumer complaints will bring social reputation loss as N. After receiving the information, the e-commerce company for price discrimination will be penalized by the government regulatory department, and the fine will be Ie.Assumption 5.
The price discrimination of e-commerce company depends on the information provided by the platform. The benefit of the platform reasonably providing information to the e-commerce company isW, and the cost of the platform information supervision on e-commerce company is Cp. When the e-commerce platform finds the price discrimination of e-commerce company on the consumer, the fine to e-commerce company is F. The e-commerce platform and consumers share this fine in the ratio of β and 1 − β. When the government finds price discrimination by the e-commerce company, it will impose the fine of Ip for the platform’s unfavorable supervision to e-commerce company information.
The parameters are described in Table1.Table 1
Parameter description.
ParameterDescriptionPnThe benefit of nondifferential pricing by e-commerce company to consumerPdThe benefit of differential pricing by e-commerce company to consumer∆PThe additional benefit of differential pricing by e-commerce company to the loyal consumerMCompensation of e-commerce company to the loyal consumer for differential pricingTeThe reputation value of the loyal consumer to e-commerce companyUlThe utility obtained by the loyal consumer from purchasing goodsUdThe utility obtained by the disloyal consumer from purchasing goodsCcThe cost of consumer complaintαProbability of loyal consumer discovering differential pricing under government loose supervision, andα∈0,1CgThe cost of strict supervision by the government regulatory departmentNSocial reputation loss caused by differential pricing under government loose supervisionRThe social benefit of nondifferential pricing under the government strict supervisionIeFine by government regulatory department for differential pricing to e-commerce companyIpFine by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricingSThe normal benefit obtained by the government from the operation of the e-commerce platformWThe benefit of the platform reasonably providing information to the e-commerce companyCpThe cost of the platform’s information supervision on the e-commerce companyFFines imposed by the platform to e-commerce company for differential pricing during information supervisionβThe proportion of the fine imposed by the e-commerce platform for differential pricing of e-commerce company,β∈0,1TpThe reputation value of the loyal consumer to the e-commerce platform
## 3.3. Model Framework
According to the above analysis, the mixed-strategy game matrix of the four-party game subjects of government regulatory department, e-commerce platform, e-commerce company, and consumer is shown in Table2.Table 2
Game model benefit matrix of government regulatory department, e-commerce platform, e-commerce company, and consumer
Strategy choiceE-commerce companyGovernment regulatory departmentStrict supervision,rLoose supervision, 1 −rLoyaltyyDisloyalty 1 −yLoyaltyyDisloyalty 1 −yE-commerce platformInformation supervisionzNondifferential pricingxPn + TePnPn + TePnUlUdUlUdW − Cp + TpW − CpW − Cp + TpW − CpS − Cg+RS − Cg + RSSDifferential pricing 1 −xPd + ∆P + Te − M − Ie − FPd − Ie − FPd + ∆P + Te − αM − αIe − FPd − FUl− ∆P + M + (1 − β)FUdUl − ∆P − Cc + αM + (1 − β)FUdW − Cp + βF + TpW − Cp + FW − Cp + βF + TpW − Cp + FS −Cg + IeS −Cg + IeS + αIe− NS − NInformation nonsupervision 1 −zNondifferential pricingxPn + TePnPn + TePnUlUdUlUdW + TpWW + TpWS −Cg + RS −Cg + RSSDifferential pricing 1 −xPd + ∆P + Te− M − IePd− IePd + ∆P + Te− αM − αIePdUl− ∆P + MUdUl− ∆P − Cc + αMUdW − Ip + TpW − IpW − αIp + TpWS −Cg + Ie + IpS −Cg+Ie + IpS+αIe+αIp− NS − N
## 3.4. Model Analysis
### 3.4.1. Strategy Stability Analysis of the E-Commerce Company
Assuming that the expected benefit of the e-commerce company when choosing the nondifferential pricing strategy isU11, the expected benefit of the e-commerce company when choosing the differential pricing strategy is U12, and the average expected benefit of the e-commerce company is U1¯, which are defined as follows:(1)U11=yzrPn+Te+1−yzrPn+y1−zrPn+Te+1−y1−zrPn+yz1−rPn+Te+1−yz1−rPn+y1−z1−rPn+Te+1−y1−z1−rPn=Pn+yTe,U12=yzrPd+ΔP+Te−M−Ie−F+1−yzrPd−Ie−F+y1−zrPd+ΔP+Te−M−Ie+1−y1−zrPd−Ie+yz1−rPd+ΔP+Te−αM−αIe−F+1−yz1−rPd−F+y1−z1−rPd+ΔP+Te−αM−αIe+1−y1−z1−rPd=Pd+yΔP+Te−yM+Ier+1−rα−1−yrIe−zF,U1¯=xU11+1−xU12.According to the Malthusian dynamic equation, the replication dynamic equation of the e-commerce company is obtained as follows:(2)Fx=dxdt=xU11−U1¯=x1−xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.The first partial derivative ofF (x) for x is as follows:(3)Fx′x=1−2xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.Based on the stability theorem of differential equations, the e-commerce company implements the strategy of nondifferential pricing in the stable state must meet the conditions:Fx = 0, and Fx′x < 0.Proposition 1.
Whenr > r0, the stable strategy of the e-commerce company is nondifferential pricing; when r < r0, the stable strategy of the e-commerce company is differential pricing; when r = r0, the e-commerce company cannot determine the stable strategy. Where the threshold is as follows:(4)r0=Pd+yΔP−Pn−αyM+Ie−zF1−αyM+1−αyIe.Proof.
AssumeHr=Pn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF, when yM−αM+Ie>0, ∂H/∂r > 0, then H (r) is considered to be an increasing function of r. When r > r0, H (r) > 0, Fx|x=1=0, and Fx′x|x=1<0, so x = 1 has stability; When r < r0, H (r) < 0, Fx|x=0=0, and Fx′x|x=0<0, so x = 0 has stability; when r = r0, H (r) = 0, Fx=0, and Fx′x=0, so x is stable at all levels in the range of 0 to 1, that is, the company’s strategy does not change over time, regardless of the proportion of company choosing to price differentially.
Proposition1 states that the increase of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from differential pricing to nondifferential pricing; Similarly, the decline of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from nondifferential pricing to differential pricing. Therefore, the government’s strict supervision for e-commerce company is essential, and the government should take measures to improve strict supervision for the e-commerce company.
Based on Proposition1, the phase diagram of the strategy evolution of e-commerce company is shown in Figure 2.
Inference 1: with the increase of the value ofPn, M, Ie, F, and α, the e-commerce company is more inclined to implement the nondifferential pricing strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Pd and ∆P, the e-commerce company is more inclined to implement the differential pricing strategy. It shows that the proportion of e-commerce company implementing nondifferential pricing strategy is directly proportional to the benefits of nondifferential pricing, the fines imposed by the government and platform on e-commerce company for differential pricing and the probability of consumers’ discovery, and inversely proportional to the benefits of e-commerce company implementing differential pricing strategy.Figure 2
Phase diagram of strategy evolution of e-commerce company.Proof.
Sincer0=Pd+yΔP−Pn−αyM+Ie−zF/1−αyM+1−αyIe, the volume of Vx1 in Figure 2 represents the proportion of nondifferential pricing by the e-commerce company, and the corresponding volume of Vx0 represents the proportion of differential pricing by the e-commerce company. When the value of Pn, M, Ie, F, and α gradually increases, the value of r0 will gradually decrease, and the volume of Vx1 will increase at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing increases; When the value of Pd and ∆P gradually increases, the value of r0 will gradually increase, and the volume of Vx1 will decrease at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing decreases.
### 3.4.2. Strategy Stability Analysis of the Consumer
Assuming that the expected benefit of the consumer when choosing loyalty strategy to e-commerce company isU21, the expected benefit of the consumer when choosing disloyalty strategy to e-commerce company is U22, and the average expected benefit of the consumer is U2¯, which are defined as follows:(5)U21=xzrUl+1−xzrUl−ΔP+M+1−βF+x1−zrUl+1−x1−zrUl−ΔP+M+xz1−rUl+1−xz1−rUl−ΔP−Cc+αM+1−βF+x1−z1−rUl+1−x1−z1−rUl−ΔP−Cc+αM=Ul−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF,U22=xzrUd+1−xzrUd+x1−zrUd+1−x1−zrUd+xz1−rUd+1−xz1−rUd+x1−z1−rUd+1−x1−z1−rUd=Ud,U2¯=yU21+1−yU22.According to the Malthusian dynamic equation, the replication dynamic equation of consumer is obtained as follows:(6)Fy=dydt=yU21−U2¯=y1−yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.The first partial derivative ofF (y) for y is as follows:(7)Fy′y=1−2yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.Based on the stability theorem of differential equations, consumer implements the strategy of loyalty in the stable state must meet the conditions:Fy = 0, and Fy′y < 0.Proposition 2.
Whenx > x0, the stable strategy of the consumer is loyalty; when x < x0, the stable strategy of the consumer is disloyalty; when x = x0, the consumer cannot determine the stable strategy. Where the threshold is as follows:(8)x0=Ul−Ud+M−ΔP+1−rαM−Cc+z1−βFM−ΔP+1−rαM−Cc+z1−βF.Proof.
AssumeHx=Ul−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF, when M−ΔP+1−rαM−Cc+z1−βF>0, ∂H/∂x > 0, H (x) is considered to be an increasing function of x. When x > x0, H (x) > 0, Fy|y=1=0, and Fy′y|y=1<0, so y = 1 has stability; When x < x0, H (x) < 0, Fy|y=0=0, and Fy′y|y=0<0, so y = 0 has stability; When x = x0, H (x) = 0, Fy=0, and Fy′y=0, so y is stable at all levels in the range of 0 to 1, that is, the consumer’s strategy does not change over time, regardless of the proportion of consumer choosing to be loyal.
Proposition2 states that the increase of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from disloyalty to loyalty; Similarly, the decline of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from loyalty to disloyalty. Therefore, e-commerce company should reduce the degree of difference in pricing for consumers and try to retain consumers.
Based on Proposition2, the phase diagram of the strategy evolution of consumer is shown in Figure 3.
Inference 2: with the increase of the value ofUl, M, F, α, and β, the consumer is more inclined to be loyalty strategy to the e-commerce company, when other parameters remain unchanged. Similarly, with the increase of the value of Ud, ∆P, and Cc, the consumer is more inclined to be disloyalty strategy to the e-commerce company. It shows that the proportion of consumer being loyalty strategy to e-commerce company is directly proportional to the utility obtained by the loyal consumer from purchasing goods, the fines imposed by the government and e-commerce platform for differential pricing of e-commerce company, and the probability of consumers’ discovery, and inversely proportional to the utility obtained by the disloyal consumer in purchasing goods, the additional benefit obtained by the e-commerce company in implementing differential pricing, the proportion of fines imposed by the platform to the e-commerce company and the cost of consumer complaints.Figure 3
Phase diagram of strategy evolution of consumer.Proof.
Sincex0=1−Ul−Ud/ΔP+1−rCc−1+1−rαM−z1−βF, the volume of Vy1 in Figure 3 represents the proportion of loyalty to e-commerce company by the consumer, and the corresponding volume of Vy0 represents the proportion of disloyalty to e-commerce company by the consumer. When the value of Ul, M, Ie, F, and α gradually increases, the value of x0 will gradually decrease, and the volume of Vy1 will increase at this time, indicating that the proportion of loyalty to e-commerce company by the consumer increases; When the value of Ud, ∆P, β and Cc gradually increase, the value of x0 will gradually increase, and the volume of Vy1 will decrease at this time, indicating that the proportion of loyalty to e-commerce company by consumer decreases.
### 3.4.3. Strategy Stability Analysis of E-Commerce Platform
Assuming that the expected benefit of the e-commerce platform when choosing the information supervision strategy isU31, the expected benefit of the e-commerce platform when choosing the information nonsupervision strategy is U32, and the average expected benefit of the e-commerce platform is U3¯, which are defined as follows:(9)U31=xyrW−Cp+TP+x1−yrW−Cp+1−xyrW−Cp+TP+βF+1−x1−yrW−Cp+TP+xy1−rW−Cp+βF+x1−y1−rW−Cp+1−xy1−rW−Cp+TP+βF+1−x1−y1−rW−Cp+βF=W−Cp+F+yTp−xF,U32=xyrW+TP+x1−yrW+1−xyrW−Ip+TP+1−x1−yrW−Ip+xy1−rW+TP+x1−y1−rW+1−xy1−rW−αIp+TP+1−x1−y1−rW=W+yTp−1−xrIp−1−xy1−rIp,U3¯=zU31+1−zU32.According to the Malthusian dynamic equation, the replication dynamic equation of e-commerce platform is obtained as follows:(10)Fz=dzdt=zU31−U3¯=z1−zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.The first partial derivative ofF (z) for z is as follows:(11)Fz′z=1−2zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.Based on the stability theorem of differential equations, e-commerce platform implements the strategy of information supervision in the stable state must meet the conditions:Fz = 0, and Fz′z <0.Proposition 3.
Wheny > y0, the e-commerce platform will choose information supervision as the stable strategy; when y < y0, the e-commerce platform will choose information nonsupervision as the stable strategy; when y = y0, the e-commerce platform cannot determine the stable strategy. Where the threshold is as follows:(12)y0=Cp+xβF+1−xrIp−βFTp−1−x1−rIp.Proof.
AssumeHy=F−Cp+yTp−xF−1−xrIp−1−xy1−rIp, when Tp−1−x1−rIp>0, ∂H/∂x >0, H (y) is considered to be an increasing function of y. When y > y0, H (y) > 0, Fz|z=1=0, and Fz′z|z=1<0, so z = 1 has stability; When y < y0, H (y) < 0, Fz|z=0=0, and Fz′z|z=0<0, so z = 0 has stability; When z = z0, H (y) = 0, Fz=0, and Fz′z=0, so z is stable at all levels in the range of 0 to 1, that is, the e-commerce platform’s strategy does not change over time, regardless of the proportion of e-commerce platform choosing information supervision.
Proposition3 states that the increase of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information nonsupervision to information supervision. Similarly, the decline of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information supervision to information nonsupervision. Therefore, if the consumer can be loyal to the e-commerce company in the platform, the platform will also actively supervise its subordinate company.
Based on Proposition3, the phase diagram of the strategy evolution of the e-commerce platform is shown in Figure 4.
Inference 3: with the increase of the value ofF, β, and Tp, the e-commerce platform is more inclined to implement the information supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cp and Ip, the e-commerce platform is more inclined to implement the information nonsupervision strategy. It shows that the proportion of e-commerce platform implementing information supervision strategy is directly proportional to the fines imposed by the platform for differential pricing of e-commerce company, the proportion of fines imposed by the e-commerce platform for differential pricing of e-commerce company, and the reputation value brought by the loyal consumer to the platform, and inversely proportional to the cost of the platform’s information supervision on e-commerce company and the fines by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricing.Figure 4
Phase diagram of strategy evolution of e-commerce platform.Proof.
Sincey0=Cp+1−xrIp−1−xβF/Tp−1−x1−rIp, the volume of Vz1 in Figure 4 represents the proportion of information supervision of e-commerce company by the platform, and the corresponding volume of Vz0 represents the proportion of information nonsupervision by the platform. When the value of F, β, and Tp gradually increase, the value of y0 will gradually decrease, and the volume of Vz1 will increase at this time, indicating that the proportion of e-commerce platform to implement information supervision increases; When the value of Cp and Ip gradually increases, the value of y0 will gradually increase, and the volume of Vz1 will decrease at this time, indicating that the proportion of e-commerce platform to implement information supervision decreases.
### 3.4.4. Strategy Stability Analysis of Government Regulatory Department
Assuming that the expected benefit of government regulatory department when government implementing the strategy of strictly supervising isU41, the expected benefit of government regulatory department when government implementing the strategy of loosely supervising is U42, and the average expected benefit of the government regulatory department is U4¯, which are defined as follows:(13)U41=xyzS−Cg+R+x1−yzS−Cg+R+1−xyzS−Cg+Ie+1−x1−yzS−Cg+Ie+xy1−zS−Cg+R+x1−y1−zS−Cg+R+1−xy1−zS−Cg+Ie+Ip+1−x1−y1−zS−Cg+Ie+Ip=S−Cg+xR+1−xIe+1−x1−zIp.U42=xyzS+x1−yzS+1−xyzS−N+αIe+1−x1−yzS−N+xy1−zS+x1−y1−zS+1−xy1−zS−N+αIe+αIp+1−x1−y1−zS−N=S−1−xN+1−xyαIe+1−zIp,U4¯=rU41+1−rU42.According to the Malthusian dynamic equation, the replication dynamic equation of the government regulatory department is obtained as follows:(14)Fr=drdt=rU41−U4¯=r1−r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.The first partial derivative ofF (r) for r is as follows:(15)Fr′r=1−2r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.Based on the stability theorem of differential equations, government regulatory department implements the strategy of strictly supervising in the stable state must meet the conditions:Fr = 0, and Fr′r < 0.Proposition 4.
Whenz > z0, the government regulatory department will choose strict supervision as the stable strategy; when z < z0, the stable strategy of the government regulatory department will choose loose supervision as the stable strategy; when z = z0, the government regulatory department cannot determine the stable strategy. Where the threshold is as follows:(16)z0=−Cg+xR+1−x1−αyIp+1−x1−αyIe+N1−x1−αyIp.Proof.
AssumeHz=−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp, when ∂H/∂x < 0, H (z) is considered to be an increasing function of z. When z < z0, H (z) > 0, Fr|r=1=0, and Fr′r|r=1<0, so r = 1 has stability; When z > z0, H (z) < 0, Fr|r=0=0, and Fr′r|r=0<0, so r = 0 has stability; When z = z0, H (z) = 0, Fr=0, and Fr′r=0, so z is stable at all levels in the range of 0 to 1, that is, the government regulatory department’s strategy does not change over time, regardless of the proportion of government regulatory department choosing to strict supervision.
Proposition4 states that the decline of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from loose supervision to strict supervision; Similarly, the increase of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from strictly supervising to loosely supervising. Therefore, the government’s strict supervision on e-commerce company is the necessary measure under the unfavorable conditions of the e-commerce platform’s information supervision on e-commerce company.
Based on Proposition4, the phase diagram of strategy evolution of the government regulatory department is shown in Figure 5.
Inference 4: With the increase of the value ofR, Ie, Ip, and N, the government regulatory department is more inclined to implement the strict supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cg and α, the government is more inclined to implement the loose supervision strategy. It shows that the proportion of government regulatory department implementing strict supervision strategy is directly proportional to the social benefits obtained, the fines punished by the government on e-commerce company and platform, and the social reputation loss caused by differential pricing under the government’s loose supervision, and inversely proportional to the cost for the government to strictly supervise and the proportion of consumer discovering differential pricing.Figure 5
Phase diagram of strategy evolution of government regulatory department.Proof.
Sincez0=1−Cg−xR−1−x1−αyIe+N/1−x1−αyIp, the volume of Vr1 in Figure 5 represents the proportion of strictly supervised by the government, and the corresponding volume of Vr0 represents the proportion of loosely supervised by government. When the value of R, Ie, Ip, and N gradually increases, the value of z0 will gradually increase, and the volume of Vr1 will increase at this time, indicating that the proportion of strict supervision by government regulatory department increases; When the value of Cg and α gradually increase, the value of z0 will gradually decrease, and the volume of Vr1 will decrease at this time, indicating that the proportion of strict supervision by government regulatory department increases decreases.
## 3.4.1. Strategy Stability Analysis of the E-Commerce Company
Assuming that the expected benefit of the e-commerce company when choosing the nondifferential pricing strategy isU11, the expected benefit of the e-commerce company when choosing the differential pricing strategy is U12, and the average expected benefit of the e-commerce company is U1¯, which are defined as follows:(1)U11=yzrPn+Te+1−yzrPn+y1−zrPn+Te+1−y1−zrPn+yz1−rPn+Te+1−yz1−rPn+y1−z1−rPn+Te+1−y1−z1−rPn=Pn+yTe,U12=yzrPd+ΔP+Te−M−Ie−F+1−yzrPd−Ie−F+y1−zrPd+ΔP+Te−M−Ie+1−y1−zrPd−Ie+yz1−rPd+ΔP+Te−αM−αIe−F+1−yz1−rPd−F+y1−z1−rPd+ΔP+Te−αM−αIe+1−y1−z1−rPd=Pd+yΔP+Te−yM+Ier+1−rα−1−yrIe−zF,U1¯=xU11+1−xU12.According to the Malthusian dynamic equation, the replication dynamic equation of the e-commerce company is obtained as follows:(2)Fx=dxdt=xU11−U1¯=x1−xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.The first partial derivative ofF (x) for x is as follows:(3)Fx′x=1−2xPn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF.Based on the stability theorem of differential equations, the e-commerce company implements the strategy of nondifferential pricing in the stable state must meet the conditions:Fx = 0, and Fx′x < 0.Proposition 1.
Whenr > r0, the stable strategy of the e-commerce company is nondifferential pricing; when r < r0, the stable strategy of the e-commerce company is differential pricing; when r = r0, the e-commerce company cannot determine the stable strategy. Where the threshold is as follows:(4)r0=Pd+yΔP−Pn−αyM+Ie−zF1−αyM+1−αyIe.Proof.
AssumeHr=Pn−Pd−yΔP+yM+Ier+1−rα+1−yrIe+zF, when yM−αM+Ie>0, ∂H/∂r > 0, then H (r) is considered to be an increasing function of r. When r > r0, H (r) > 0, Fx|x=1=0, and Fx′x|x=1<0, so x = 1 has stability; When r < r0, H (r) < 0, Fx|x=0=0, and Fx′x|x=0<0, so x = 0 has stability; when r = r0, H (r) = 0, Fx=0, and Fx′x=0, so x is stable at all levels in the range of 0 to 1, that is, the company’s strategy does not change over time, regardless of the proportion of company choosing to price differentially.
Proposition1 states that the increase of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from differential pricing to nondifferential pricing; Similarly, the decline of the proportion of the government strict supervision to e-commerce company will change the stable strategy of e-commerce company from nondifferential pricing to differential pricing. Therefore, the government’s strict supervision for e-commerce company is essential, and the government should take measures to improve strict supervision for the e-commerce company.
Based on Proposition1, the phase diagram of the strategy evolution of e-commerce company is shown in Figure 2.
Inference 1: with the increase of the value ofPn, M, Ie, F, and α, the e-commerce company is more inclined to implement the nondifferential pricing strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Pd and ∆P, the e-commerce company is more inclined to implement the differential pricing strategy. It shows that the proportion of e-commerce company implementing nondifferential pricing strategy is directly proportional to the benefits of nondifferential pricing, the fines imposed by the government and platform on e-commerce company for differential pricing and the probability of consumers’ discovery, and inversely proportional to the benefits of e-commerce company implementing differential pricing strategy.Figure 2
Phase diagram of strategy evolution of e-commerce company.Proof.
Sincer0=Pd+yΔP−Pn−αyM+Ie−zF/1−αyM+1−αyIe, the volume of Vx1 in Figure 2 represents the proportion of nondifferential pricing by the e-commerce company, and the corresponding volume of Vx0 represents the proportion of differential pricing by the e-commerce company. When the value of Pn, M, Ie, F, and α gradually increases, the value of r0 will gradually decrease, and the volume of Vx1 will increase at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing increases; When the value of Pd and ∆P gradually increases, the value of r0 will gradually increase, and the volume of Vx1 will decrease at this time, indicating that the proportion of e-commerce company to implement nondifferential pricing decreases.
## 3.4.2. Strategy Stability Analysis of the Consumer
Assuming that the expected benefit of the consumer when choosing loyalty strategy to e-commerce company isU21, the expected benefit of the consumer when choosing disloyalty strategy to e-commerce company is U22, and the average expected benefit of the consumer is U2¯, which are defined as follows:(5)U21=xzrUl+1−xzrUl−ΔP+M+1−βF+x1−zrUl+1−x1−zrUl−ΔP+M+xz1−rUl+1−xz1−rUl−ΔP−Cc+αM+1−βF+x1−z1−rUl+1−x1−z1−rUl−ΔP−Cc+αM=Ul−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF,U22=xzrUd+1−xzrUd+x1−zrUd+1−x1−zrUd+xz1−rUd+1−xz1−rUd+x1−z1−rUd+1−x1−z1−rUd=Ud,U2¯=yU21+1−yU22.According to the Malthusian dynamic equation, the replication dynamic equation of consumer is obtained as follows:(6)Fy=dydt=yU21−U2¯=y1−yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.The first partial derivative ofF (y) for y is as follows:(7)Fy′y=1−2yUl−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF.Based on the stability theorem of differential equations, consumer implements the strategy of loyalty in the stable state must meet the conditions:Fy = 0, and Fy′y < 0.Proposition 2.
Whenx > x0, the stable strategy of the consumer is loyalty; when x < x0, the stable strategy of the consumer is disloyalty; when x = x0, the consumer cannot determine the stable strategy. Where the threshold is as follows:(8)x0=Ul−Ud+M−ΔP+1−rαM−Cc+z1−βFM−ΔP+1−rαM−Cc+z1−βF.Proof.
AssumeHx=Ul−Ud−1−xΔP+1−xM+1−rαM−1−x1−rCc+1−xz1−βF, when M−ΔP+1−rαM−Cc+z1−βF>0, ∂H/∂x > 0, H (x) is considered to be an increasing function of x. When x > x0, H (x) > 0, Fy|y=1=0, and Fy′y|y=1<0, so y = 1 has stability; When x < x0, H (x) < 0, Fy|y=0=0, and Fy′y|y=0<0, so y = 0 has stability; When x = x0, H (x) = 0, Fy=0, and Fy′y=0, so y is stable at all levels in the range of 0 to 1, that is, the consumer’s strategy does not change over time, regardless of the proportion of consumer choosing to be loyal.
Proposition2 states that the increase of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from disloyalty to loyalty; Similarly, the decline of the proportion of nondifferential pricing of e-commerce company will change the stable strategy of consumer from loyalty to disloyalty. Therefore, e-commerce company should reduce the degree of difference in pricing for consumers and try to retain consumers.
Based on Proposition2, the phase diagram of the strategy evolution of consumer is shown in Figure 3.
Inference 2: with the increase of the value ofUl, M, F, α, and β, the consumer is more inclined to be loyalty strategy to the e-commerce company, when other parameters remain unchanged. Similarly, with the increase of the value of Ud, ∆P, and Cc, the consumer is more inclined to be disloyalty strategy to the e-commerce company. It shows that the proportion of consumer being loyalty strategy to e-commerce company is directly proportional to the utility obtained by the loyal consumer from purchasing goods, the fines imposed by the government and e-commerce platform for differential pricing of e-commerce company, and the probability of consumers’ discovery, and inversely proportional to the utility obtained by the disloyal consumer in purchasing goods, the additional benefit obtained by the e-commerce company in implementing differential pricing, the proportion of fines imposed by the platform to the e-commerce company and the cost of consumer complaints.Figure 3
Phase diagram of strategy evolution of consumer.Proof.
Sincex0=1−Ul−Ud/ΔP+1−rCc−1+1−rαM−z1−βF, the volume of Vy1 in Figure 3 represents the proportion of loyalty to e-commerce company by the consumer, and the corresponding volume of Vy0 represents the proportion of disloyalty to e-commerce company by the consumer. When the value of Ul, M, Ie, F, and α gradually increases, the value of x0 will gradually decrease, and the volume of Vy1 will increase at this time, indicating that the proportion of loyalty to e-commerce company by the consumer increases; When the value of Ud, ∆P, β and Cc gradually increase, the value of x0 will gradually increase, and the volume of Vy1 will decrease at this time, indicating that the proportion of loyalty to e-commerce company by consumer decreases.
## 3.4.3. Strategy Stability Analysis of E-Commerce Platform
Assuming that the expected benefit of the e-commerce platform when choosing the information supervision strategy isU31, the expected benefit of the e-commerce platform when choosing the information nonsupervision strategy is U32, and the average expected benefit of the e-commerce platform is U3¯, which are defined as follows:(9)U31=xyrW−Cp+TP+x1−yrW−Cp+1−xyrW−Cp+TP+βF+1−x1−yrW−Cp+TP+xy1−rW−Cp+βF+x1−y1−rW−Cp+1−xy1−rW−Cp+TP+βF+1−x1−y1−rW−Cp+βF=W−Cp+F+yTp−xF,U32=xyrW+TP+x1−yrW+1−xyrW−Ip+TP+1−x1−yrW−Ip+xy1−rW+TP+x1−y1−rW+1−xy1−rW−αIp+TP+1−x1−y1−rW=W+yTp−1−xrIp−1−xy1−rIp,U3¯=zU31+1−zU32.According to the Malthusian dynamic equation, the replication dynamic equation of e-commerce platform is obtained as follows:(10)Fz=dzdt=zU31−U3¯=z1−zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.The first partial derivative ofF (z) for z is as follows:(11)Fz′z=1−2zβF−Cp+yTp−xβF−1−xrIp−1−xy1−rIp.Based on the stability theorem of differential equations, e-commerce platform implements the strategy of information supervision in the stable state must meet the conditions:Fz = 0, and Fz′z <0.Proposition 3.
Wheny > y0, the e-commerce platform will choose information supervision as the stable strategy; when y < y0, the e-commerce platform will choose information nonsupervision as the stable strategy; when y = y0, the e-commerce platform cannot determine the stable strategy. Where the threshold is as follows:(12)y0=Cp+xβF+1−xrIp−βFTp−1−x1−rIp.Proof.
AssumeHy=F−Cp+yTp−xF−1−xrIp−1−xy1−rIp, when Tp−1−x1−rIp>0, ∂H/∂x >0, H (y) is considered to be an increasing function of y. When y > y0, H (y) > 0, Fz|z=1=0, and Fz′z|z=1<0, so z = 1 has stability; When y < y0, H (y) < 0, Fz|z=0=0, and Fz′z|z=0<0, so z = 0 has stability; When z = z0, H (y) = 0, Fz=0, and Fz′z=0, so z is stable at all levels in the range of 0 to 1, that is, the e-commerce platform’s strategy does not change over time, regardless of the proportion of e-commerce platform choosing information supervision.
Proposition3 states that the increase of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information nonsupervision to information supervision. Similarly, the decline of the proportion of consumer loyalty will change the stable strategy of e-commerce platform from information supervision to information nonsupervision. Therefore, if the consumer can be loyal to the e-commerce company in the platform, the platform will also actively supervise its subordinate company.
Based on Proposition3, the phase diagram of the strategy evolution of the e-commerce platform is shown in Figure 4.
Inference 3: with the increase of the value ofF, β, and Tp, the e-commerce platform is more inclined to implement the information supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cp and Ip, the e-commerce platform is more inclined to implement the information nonsupervision strategy. It shows that the proportion of e-commerce platform implementing information supervision strategy is directly proportional to the fines imposed by the platform for differential pricing of e-commerce company, the proportion of fines imposed by the e-commerce platform for differential pricing of e-commerce company, and the reputation value brought by the loyal consumer to the platform, and inversely proportional to the cost of the platform’s information supervision on e-commerce company and the fines by government imposed on the platform for nonsupervision of e-commerce company information resulting in differential pricing.Figure 4
Phase diagram of strategy evolution of e-commerce platform.Proof.
Sincey0=Cp+1−xrIp−1−xβF/Tp−1−x1−rIp, the volume of Vz1 in Figure 4 represents the proportion of information supervision of e-commerce company by the platform, and the corresponding volume of Vz0 represents the proportion of information nonsupervision by the platform. When the value of F, β, and Tp gradually increase, the value of y0 will gradually decrease, and the volume of Vz1 will increase at this time, indicating that the proportion of e-commerce platform to implement information supervision increases; When the value of Cp and Ip gradually increases, the value of y0 will gradually increase, and the volume of Vz1 will decrease at this time, indicating that the proportion of e-commerce platform to implement information supervision decreases.
## 3.4.4. Strategy Stability Analysis of Government Regulatory Department
Assuming that the expected benefit of government regulatory department when government implementing the strategy of strictly supervising isU41, the expected benefit of government regulatory department when government implementing the strategy of loosely supervising is U42, and the average expected benefit of the government regulatory department is U4¯, which are defined as follows:(13)U41=xyzS−Cg+R+x1−yzS−Cg+R+1−xyzS−Cg+Ie+1−x1−yzS−Cg+Ie+xy1−zS−Cg+R+x1−y1−zS−Cg+R+1−xy1−zS−Cg+Ie+Ip+1−x1−y1−zS−Cg+Ie+Ip=S−Cg+xR+1−xIe+1−x1−zIp.U42=xyzS+x1−yzS+1−xyzS−N+αIe+1−x1−yzS−N+xy1−zS+x1−y1−zS+1−xy1−zS−N+αIe+αIp+1−x1−y1−zS−N=S−1−xN+1−xyαIe+1−zIp,U4¯=rU41+1−rU42.According to the Malthusian dynamic equation, the replication dynamic equation of the government regulatory department is obtained as follows:(14)Fr=drdt=rU41−U4¯=r1−r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.The first partial derivative ofF (r) for r is as follows:(15)Fr′r=1−2r−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp.Based on the stability theorem of differential equations, government regulatory department implements the strategy of strictly supervising in the stable state must meet the conditions:Fr = 0, and Fr′r < 0.Proposition 4.
Whenz > z0, the government regulatory department will choose strict supervision as the stable strategy; when z < z0, the stable strategy of the government regulatory department will choose loose supervision as the stable strategy; when z = z0, the government regulatory department cannot determine the stable strategy. Where the threshold is as follows:(16)z0=−Cg+xR+1−x1−αyIp+1−x1−αyIe+N1−x1−αyIp.Proof.
AssumeHz=−Cg+xR+1−xIe+1−x1−zIp+1−xN−1−xyαIe+1−zIp, when ∂H/∂x < 0, H (z) is considered to be an increasing function of z. When z < z0, H (z) > 0, Fr|r=1=0, and Fr′r|r=1<0, so r = 1 has stability; When z > z0, H (z) < 0, Fr|r=0=0, and Fr′r|r=0<0, so r = 0 has stability; When z = z0, H (z) = 0, Fr=0, and Fr′r=0, so z is stable at all levels in the range of 0 to 1, that is, the government regulatory department’s strategy does not change over time, regardless of the proportion of government regulatory department choosing to strict supervision.
Proposition4 states that the decline of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from loose supervision to strict supervision; Similarly, the increase of the proportion of information supervision of e-commerce company by e-commerce platform will change the stable strategy of government regulatory department from strictly supervising to loosely supervising. Therefore, the government’s strict supervision on e-commerce company is the necessary measure under the unfavorable conditions of the e-commerce platform’s information supervision on e-commerce company.
Based on Proposition4, the phase diagram of strategy evolution of the government regulatory department is shown in Figure 5.
Inference 4: With the increase of the value ofR, Ie, Ip, and N, the government regulatory department is more inclined to implement the strict supervision strategy, when other parameters remain unchanged. Similarly, with the increase of the value of Cg and α, the government is more inclined to implement the loose supervision strategy. It shows that the proportion of government regulatory department implementing strict supervision strategy is directly proportional to the social benefits obtained, the fines punished by the government on e-commerce company and platform, and the social reputation loss caused by differential pricing under the government’s loose supervision, and inversely proportional to the cost for the government to strictly supervise and the proportion of consumer discovering differential pricing.Figure 5
Phase diagram of strategy evolution of government regulatory department.Proof.
Sincez0=1−Cg−xR−1−x1−αyIe+N/1−x1−αyIp, the volume of Vr1 in Figure 5 represents the proportion of strictly supervised by the government, and the corresponding volume of Vr0 represents the proportion of loosely supervised by government. When the value of R, Ie, Ip, and N gradually increases, the value of z0 will gradually increase, and the volume of Vr1 will increase at this time, indicating that the proportion of strict supervision by government regulatory department increases; When the value of Cg and α gradually increase, the value of z0 will gradually decrease, and the volume of Vr1 will decrease at this time, indicating that the proportion of strict supervision by government regulatory department increases decreases.
## 4. Results and Discussion
### 4.1. ESS Analysis among Four-Party Game Players
In the dynamic system of government regulatory department, e-commerce platform, e-commerce company and consumer, the stability of the strategic combination of the four-party game subjects can be referred to as the nonlinear function stability discriminant method of First Law of Lyapunov. Ritzberger and Weibull [38] and Selten [39] pointed out that the stable solutions in the multi-group evolutionary game are strict Nash equilibrium, which must be the pure strategy. Therefore, this study analyzes 16 pure strategies in four-party evolutionary game learning from the research method of Sun and Su [40].Due to the replication dynamic equation of each game subject, the Jacobian matrix is obtained as follows:(17)J=Fx′xFy′xFz′xFr′xFx′yFy′yFz′yFr′yFx′zFy′zFz′zFr′zFx′rFy′rFz′rFr′r,where the elements in the matrix are shown in Appendix A.
#### 4.1.1. ESS Analysis among Four-Party Game Players under the Strict Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp<0, government regulatory department implements strict supervision. According to the Jacobian matrix shown in Appendix B, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 3.Condition (a):−Pn+Pd+ΔP−M−Ie<0, Cg−R<0, and −Cp+Tp<0Condition (b):−Pn+Pd+ΔP−M−Ie−F<0, Cg−R<0, and Cp−Tp<0Table 3
Asymptotic stability analysis of equilibrium point of replication dynamic system under the strict supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE1 (0, 0, 0, 1)(+,X, X, X)Instability pointE2 (1, 0, 0, 1)(−, +, −, −)Instability pointE3 (0, 1, 0, 1)(+,X, X, −)Instability pointE4 (0, 0, 1, 1)(+,X, X, −)Instability pointE5 (1, 1, 0, 1)(−, −, −, −)ESS in condition (a)E6 (1, 0, 1, 1)(−, +, +,−)Instability pointE7 (0, 1, 1, 1)(+,X, X,−)Instability pointE8 (1, 1, 1, 1)(−, −, −, −)ESS in condition (b)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.It can be seen from Table3 that there are two possible stable strategies under strict supervision by the government regulatory department, i.e. E5 (1, 1, 0, 1) and E8 (1, 1, 1, 1).When the condition (a) is met, that is,−Pn+Pd+ΔP−M−Ie < 0, Cg−R < 0, and −Cp+Tp < 0. The sum of the benefits of differential pricing to loyal consumers by e-commerce company is less than the sum of the benefits of nondifferential pricing by e-commerce company to the consumer and the fines to the e-commerce company for differential pricing and compensation of e-commerce company to consumer by the government. The strict supervision cost is less than the social benefits when controlling differential pricing for the government. And the reputation value produced by the loyal consumer to the platform is less than the cost of the platform information supervision. Then the strategy of each subject is stable at equilibrium point E5 (1, 1, 0, 1). E-commerce company implements nondifferential pricing, the consumer is loyal to the e-commerce company, e-commerce platform implements information nonsupervision, and the government strictly supervises e-commerce platform and e-commerce company. This situation may exist in the period of chaotic pricing for the e-commerce company. Since the e-commerce platform benefits less from the information supervision of e-commerce company, it has no motivation to supervise e-commerce company. Therefore, the government must come forward to supervise differential pricing, safeguard consumer rights and interests, and help e-commerce company gain consumer loyalty.When the condition (b) is met, that is−Pn+Pd+ΔP−M−Ie−F < 0, Cg−R < 0, and Cp−Tp < 0. With the improvement of consumers’ awareness of differential pricing and the reduction of the cost of platform supervising information, the information supervision cost of the platform is less than the reputation value brought by the loyal consumer to the platform, and the e-commerce platform can also join into the supervision of e-commerce company. When the other conditions remain unchanged, the strategy of each subject is stable at equilibrium point E8 (1, 1, 1, 1). The government and e-commerce platform jointly strengthen the supervision of differential pricing of e-commerce company, so that e-commerce company inclined to to be nondifferential pricing, and consumer is loyal to the e-commerce company.
#### 4.1.2. ESS Analysis among Four-Party Game Players under the Loose Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp>0, government regulatory department implements loosely supervision. According to the Jacobian matrix shown in Appendix C, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 4.Table 4
Asymptotic stability analysis of equilibrium point of replication dynamic system under the loose supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE9 (0, 0, 0, 0)(+,X, X, X)Instability pointE10 (1, 0, 0, 0)(−, +,X, X)Instability pointE11 (0, 1, 0, 0)(+,X, X, X)Instability pointE12 (0, 0, 1, 0)(+,X, X, X)Instability pointE13 (1, 1, 0, 0)(X,−, X, +V)Instability pointE14 (1, 0, 1, 0)(X, +, +, +)Instability pointE15 (0, 1, 1, 0)(+,X, X, X)Instability pointE16 (1, 1, 1, 0)(−, −, −, −)ESS in condition (c)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.Condition (c):−Pn+Pd+ΔP−αM+Ie−F <0, Cp−Tp <0, and −Cg+R <0.As shown in Table4 that there is a possible stabilization strategy under loose supervision by government regulatory authorities, i.e. E16 (1, 1, 1, 0).When the condition (c) is met, that is,−Pn+Pd+ΔP−αM+Ie−F<0, Cp−Tp<0, and −Cg+R <0. The sum of the benefits of e-commerce company’s differential pricing for the loyal consumer is less than the sum of the benefits of e-commerce company’s nondifferential pricing for consumer, the fines punished by government regulatory department under loosely supervising and the compensation for the consumer for differential pricing of e-commerce company, and the fines imposed by e-commerce platform on the e-commerce company. The reputation value brought by the loyal consumer to the platform is greater than the cost of the platform information supervision. And the strict supervision cost is greater than the social benefits when controlling differential pricing for the government. Then the strategy of each subject is stable at equilibrium point E16 (1, 1, 1, 0). This situation may exist in the normative period of discriminatory pricing by the e-commerce company. At this time, as the proportion of the differential pricing of e-commerce company gradually decreases, the social benefits of the government’s strict supervision of differential pricing decrease. When the social benefit is less than the strictly supervising cost of the government regulatory department, the strategy of the government regulatory department will change from strictly supervising to loosely supervising. The main responsibility of supervision will be transferred from the government to the e-commerce platform and consumer. Supervision and fines by e-commerce platform and consumer enable e-commerce company to conduct nondifferential pricing and promote the virtuous circle of the e-commerce industry ecosystem.
### 4.2. Numerical Simulation Analysis
In order to test the reliability of the model and more intuitively demonstrate the influence of key factors in the replication dynamic system on the evolutionary trajectory of stakeholders of the multi-party game, the model is given numerical value combined with the actual situation, and the numerical simulation is carried out by MATLAB2021.For the e-commerce company operating in the e-commerce platform, the benefit of nondifferential pricing to the consumer is set asPn = 10, and the benefit of differential pricing to the consumer is set as Pd = 9, and the additional benefit of differential pricing to the loyal consumer is set as ∆P = 5. If differential pricing is discovered by the government, the compensation of the e-commerce company to the consumer is set as M = 4. The reputation value brought by the loyal consumer to the e-commerce company is set as Te = 5, and the reputation value brought by the loyal consumer to the e-commerce platform is set as Tp = 5. The utility obtained by the loyal consumer when purchasing goods from the e-commerce company is set as Ul = 12, and the utility obtained by the disloyal consumer when purchasing goods from the e-commerce company is set as Ud = 11. The probability of loyal consumer discovering differential pricing under government loose supervision is set as α = 0.2 and the complaint cost of the loyal consumer is set as Cc = 3. The social benefit of nondifferential pricing obtained by the government under strict supervision is set as R = 7, and the cost of strictly supervised by the government is set as Cg = 6. The fine by government regulatory department for differential pricing of e-commerce company Ie = 3. The social reputation loss of the government caused by differential pricing under loose supervision is set as N = 8. The normal benefit obtained by the government from the operation of the platform is set as S = 6. The benefit of the platform reasonably providing information to e-commerce company is set as W = 5, and the cost of the platform’s information supervision on e-commerce company is set as Cp = 7. The fine imposed by the platform to e-commerce company for differential pricing during information supervision is set as F = 3, and the proportion of fine imposed by the e-commerce platform for differential pricing of the e-commerce company is set as β = 0.6.
#### 4.2.1. The Influence of Government Supervision Mechanism
To test whether the government supervision mechanism is effective in the process of differential pricing of e-commerce company, the proportions of government strict supervision are set asr = 0 and r = 1 to represent the two states of loose supervision and strict supervision of government supervision department. The evolution process of different initial strategies of the e-commercial company, consumer, and e-commerce platform is simulated and analyzed in three-dimensional space, and the simulation results with time are shown in Figure 6.Figure 6
Influence of the establishment of government supervision mechanism on strategy evolution of all parties.
(a)(b)(c)As shown in Figure6(a) that when government regulatory department adopts the strict supervision strategy on the differential pricing of e-commerce company, although the e-commerce platform does not take information supervision strategy on account of the high cost for information supervision, the strategies of the e-commerce company and consumer can still incline to be stable in nondifferential pricing and loyalty. This shows that it is very necessary and effective for the government to adopt the strict supervision strategy. With the reduction of Cp, that is, the information supervision cost reduced, the platform will be inclined to adopt the strategy of information supervision, to achieve coordinated supervision to e-commerce company by the government and platform, then the company adopts nondifferential pricing, and consumer is loyal to the e-commerce company. And the stable strategy portfolio is demonstrated in Figure 6(b). As is exhibited in Figure 6(c) that when government regulatory department implements the loosely supervising to e-commerce company for the differential pricing due to the high cost of strict supervision, if Cp is small, that is, the cost of information supervision on the e-commerce platform is small, and α is at a high level, the consumer can actively discover the differential pricing of the e-commerce company and report it, the e-commerce company will also incline to nondifferential pricing. Therefore, although the government selects the loose supervision strategy, the differential pricing behavior of e-commerce company is supervised collaboratively by the platform and consumer. The strategy equilibrium is consistent with the previous analysis of the stability under different government supervision strategies.
#### 4.2.2. The Influence of Information Supervision Cost of E-Commerce Platforms
IfCp = {7, 4, 1}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 7.Figure 7
Influence of information supervision cost of e-commerce platform on strategy evolution of all parties.According to Figure7, with the reduction of the information supervision cost of the e-commerce platform, the supervision strategy of the platform will be transformed from information nonsupervision on e-commerce company to information supervision. Therefore, the platform can join the ranks of the government to regulate the company, and collaboratively supervise the differential pricing of the e-commerce company for loyal consumer. Moreover, the less the information supervision cost of the platform, the faster the stable strategy of information supervision. Therefore, active measures can be adopted to lower the cost for information supervising of e-commerce platform, to stimulate e-commerce platform to supervise the differential pricing behavior of e-commerce company on the platform.
#### 4.2.3. The Influence of the Strict Supervision Cost of Government Regulatory Department
IfCg = {6, 8, 10}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 8.Figure 8
Influence of strict supervision cost of government regulatory department on strategy evolution of all parties.According to Figure8, the strict supervision cost of government affects the decision-making of government regulatory department, as well as affects the evolution of decision-making of the other subjects. With the increase of government supervision cost, the supervision strategy of the government regulatory department to the differential pricing of e-commerce company will be transformed from strict supervision to loose supervision, and gradually become the cyclical alternating strategy between strict supervision and loose supervision with medium proportion. The strategy of the e-commerce platform will be also transformed from information supervision to information nonsupervision of e-commerce company when strictly supervising cost of government Increasing. Free from the supervision of government regulatory department and platform, the pricing strategy of the company for the loyal consumer will be transformed from nondifferential pricing to moderate-proportion differential pricing, and the strategy change periodically. With the increase of the strictly supervising cost of government, the strategy of the consumer will be transformed from loyalty to e-commerce company to disloyalty. Therefore, the strict supervision cost of the government regulatory department is the key factor in restricting the differential pricing of the e-commerce company. Measures should be arranged to actively reduce the strictly supervising cost of the government regulatory department at a certain level, to stimulate platform and the consumer to regulate the behavior of e-commerce company in differential pricing.
#### 4.2.4. The Influence of the Probability of Loyal Consumer Discovering Differential Pricing under Government's Loose Supervision
Ifα = {0.1, 0.3, 0.5}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 9.Figure 9
Influence of the probability of loyal consumer discovering differential pricing under government loose supervision on strategy evolution of all parties.According to Figure9, with the increase of probability of loyal consumer discovering differential pricing under government loose supervision, the probability of exposure of differential pricing behavior of e-commerce company for loyal consumer increases, which will make e-commerce company gradually improve the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The e-commerce platform can also gradually improve the proportion of information supervision due to the increase of fines for nonsupervision of e-commerce company information resulting in differential pricing, and the behavior stabilizes in the information supervision strategy. The government regulatory department can gradually loose supervision and transfer the responsibility of supervision to e-commerce platform and the consumer. Therefore, measures can be taken to encourage the consumer to report the differential pricing behavior of e-commerce company, to maintain the stable and sustainable progress of e-commerce platform and systems.
#### 4.2.5. The Influence of the Penalties for Differential Pricing of E-Commerce Company under Government's Loose Supervision
IfM = {1, 2, 4}, Ie = {1, 2, 4}, and F = {1, 2, 4}, the evolution process and results of the strategy of the four-party game subjects are shown in Figure 10.Figure 10
Influence of the penalties for differential pricing of e-commerce company under government loose supervision on strategy evolution of all parties.According to Figure10, with the increase of the fines given by consumer, e-commerce platform, and government regulatory department for differential pricing of e-commerce company, the e-commerce company will gradually increase the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The consumer will increase the proportion of loyalty to the e-commerce company and the behavior stabilize in the loyalty strategy when the compensation for differential pricing from e-commerce company increases to compensate for the loss of differential pricing. The e-commerce platform will also gradually improve the proportion of information supervision due to the increase of benefits from information supervision fines and the behavior stabilizes in the information supervision strategy. Therefore, the nondifferential pricing behavior of e-commerce company can be promoted by increasing the punishment for differential pricing, to realize the joint dynamic supervision of the e-commerce platform, the consumer, and the government on the pricing of the e-commerce company.
## 4.1. ESS Analysis among Four-Party Game Players
In the dynamic system of government regulatory department, e-commerce platform, e-commerce company and consumer, the stability of the strategic combination of the four-party game subjects can be referred to as the nonlinear function stability discriminant method of First Law of Lyapunov. Ritzberger and Weibull [38] and Selten [39] pointed out that the stable solutions in the multi-group evolutionary game are strict Nash equilibrium, which must be the pure strategy. Therefore, this study analyzes 16 pure strategies in four-party evolutionary game learning from the research method of Sun and Su [40].Due to the replication dynamic equation of each game subject, the Jacobian matrix is obtained as follows:(17)J=Fx′xFy′xFz′xFr′xFx′yFy′yFz′yFr′yFx′zFy′zFz′zFr′zFx′rFy′rFz′rFr′r,where the elements in the matrix are shown in Appendix A.
### 4.1.1. ESS Analysis among Four-Party Game Players under the Strict Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp<0, government regulatory department implements strict supervision. According to the Jacobian matrix shown in Appendix B, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 3.Condition (a):−Pn+Pd+ΔP−M−Ie<0, Cg−R<0, and −Cp+Tp<0Condition (b):−Pn+Pd+ΔP−M−Ie−F<0, Cg−R<0, and Cp−Tp<0Table 3
Asymptotic stability analysis of equilibrium point of replication dynamic system under the strict supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE1 (0, 0, 0, 1)(+,X, X, X)Instability pointE2 (1, 0, 0, 1)(−, +, −, −)Instability pointE3 (0, 1, 0, 1)(+,X, X, −)Instability pointE4 (0, 0, 1, 1)(+,X, X, −)Instability pointE5 (1, 1, 0, 1)(−, −, −, −)ESS in condition (a)E6 (1, 0, 1, 1)(−, +, +,−)Instability pointE7 (0, 1, 1, 1)(+,X, X,−)Instability pointE8 (1, 1, 1, 1)(−, −, −, −)ESS in condition (b)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.It can be seen from Table3 that there are two possible stable strategies under strict supervision by the government regulatory department, i.e. E5 (1, 1, 0, 1) and E8 (1, 1, 1, 1).When the condition (a) is met, that is,−Pn+Pd+ΔP−M−Ie < 0, Cg−R < 0, and −Cp+Tp < 0. The sum of the benefits of differential pricing to loyal consumers by e-commerce company is less than the sum of the benefits of nondifferential pricing by e-commerce company to the consumer and the fines to the e-commerce company for differential pricing and compensation of e-commerce company to consumer by the government. The strict supervision cost is less than the social benefits when controlling differential pricing for the government. And the reputation value produced by the loyal consumer to the platform is less than the cost of the platform information supervision. Then the strategy of each subject is stable at equilibrium point E5 (1, 1, 0, 1). E-commerce company implements nondifferential pricing, the consumer is loyal to the e-commerce company, e-commerce platform implements information nonsupervision, and the government strictly supervises e-commerce platform and e-commerce company. This situation may exist in the period of chaotic pricing for the e-commerce company. Since the e-commerce platform benefits less from the information supervision of e-commerce company, it has no motivation to supervise e-commerce company. Therefore, the government must come forward to supervise differential pricing, safeguard consumer rights and interests, and help e-commerce company gain consumer loyalty.When the condition (b) is met, that is−Pn+Pd+ΔP−M−Ie−F < 0, Cg−R < 0, and Cp−Tp < 0. With the improvement of consumers’ awareness of differential pricing and the reduction of the cost of platform supervising information, the information supervision cost of the platform is less than the reputation value brought by the loyal consumer to the platform, and the e-commerce platform can also join into the supervision of e-commerce company. When the other conditions remain unchanged, the strategy of each subject is stable at equilibrium point E8 (1, 1, 1, 1). The government and e-commerce platform jointly strengthen the supervision of differential pricing of e-commerce company, so that e-commerce company inclined to to be nondifferential pricing, and consumer is loyal to the e-commerce company.
### 4.1.2. ESS Analysis among Four-Party Game Players under the Loose Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp>0, government regulatory department implements loosely supervision. According to the Jacobian matrix shown in Appendix C, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 4.Table 4
Asymptotic stability analysis of equilibrium point of replication dynamic system under the loose supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE9 (0, 0, 0, 0)(+,X, X, X)Instability pointE10 (1, 0, 0, 0)(−, +,X, X)Instability pointE11 (0, 1, 0, 0)(+,X, X, X)Instability pointE12 (0, 0, 1, 0)(+,X, X, X)Instability pointE13 (1, 1, 0, 0)(X,−, X, +V)Instability pointE14 (1, 0, 1, 0)(X, +, +, +)Instability pointE15 (0, 1, 1, 0)(+,X, X, X)Instability pointE16 (1, 1, 1, 0)(−, −, −, −)ESS in condition (c)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.Condition (c):−Pn+Pd+ΔP−αM+Ie−F <0, Cp−Tp <0, and −Cg+R <0.As shown in Table4 that there is a possible stabilization strategy under loose supervision by government regulatory authorities, i.e. E16 (1, 1, 1, 0).When the condition (c) is met, that is,−Pn+Pd+ΔP−αM+Ie−F<0, Cp−Tp<0, and −Cg+R <0. The sum of the benefits of e-commerce company’s differential pricing for the loyal consumer is less than the sum of the benefits of e-commerce company’s nondifferential pricing for consumer, the fines punished by government regulatory department under loosely supervising and the compensation for the consumer for differential pricing of e-commerce company, and the fines imposed by e-commerce platform on the e-commerce company. The reputation value brought by the loyal consumer to the platform is greater than the cost of the platform information supervision. And the strict supervision cost is greater than the social benefits when controlling differential pricing for the government. Then the strategy of each subject is stable at equilibrium point E16 (1, 1, 1, 0). This situation may exist in the normative period of discriminatory pricing by the e-commerce company. At this time, as the proportion of the differential pricing of e-commerce company gradually decreases, the social benefits of the government’s strict supervision of differential pricing decrease. When the social benefit is less than the strictly supervising cost of the government regulatory department, the strategy of the government regulatory department will change from strictly supervising to loosely supervising. The main responsibility of supervision will be transferred from the government to the e-commerce platform and consumer. Supervision and fines by e-commerce platform and consumer enable e-commerce company to conduct nondifferential pricing and promote the virtuous circle of the e-commerce industry ecosystem.
## 4.1.1. ESS Analysis among Four-Party Game Players under the Strict Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp<0, government regulatory department implements strict supervision. According to the Jacobian matrix shown in Appendix B, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 3.Condition (a):−Pn+Pd+ΔP−M−Ie<0, Cg−R<0, and −Cp+Tp<0Condition (b):−Pn+Pd+ΔP−M−Ie−F<0, Cg−R<0, and Cp−Tp<0Table 3
Asymptotic stability analysis of equilibrium point of replication dynamic system under the strict supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE1 (0, 0, 0, 1)(+,X, X, X)Instability pointE2 (1, 0, 0, 1)(−, +, −, −)Instability pointE3 (0, 1, 0, 1)(+,X, X, −)Instability pointE4 (0, 0, 1, 1)(+,X, X, −)Instability pointE5 (1, 1, 0, 1)(−, −, −, −)ESS in condition (a)E6 (1, 0, 1, 1)(−, +, +,−)Instability pointE7 (0, 1, 1, 1)(+,X, X,−)Instability pointE8 (1, 1, 1, 1)(−, −, −, −)ESS in condition (b)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.It can be seen from Table3 that there are two possible stable strategies under strict supervision by the government regulatory department, i.e. E5 (1, 1, 0, 1) and E8 (1, 1, 1, 1).When the condition (a) is met, that is,−Pn+Pd+ΔP−M−Ie < 0, Cg−R < 0, and −Cp+Tp < 0. The sum of the benefits of differential pricing to loyal consumers by e-commerce company is less than the sum of the benefits of nondifferential pricing by e-commerce company to the consumer and the fines to the e-commerce company for differential pricing and compensation of e-commerce company to consumer by the government. The strict supervision cost is less than the social benefits when controlling differential pricing for the government. And the reputation value produced by the loyal consumer to the platform is less than the cost of the platform information supervision. Then the strategy of each subject is stable at equilibrium point E5 (1, 1, 0, 1). E-commerce company implements nondifferential pricing, the consumer is loyal to the e-commerce company, e-commerce platform implements information nonsupervision, and the government strictly supervises e-commerce platform and e-commerce company. This situation may exist in the period of chaotic pricing for the e-commerce company. Since the e-commerce platform benefits less from the information supervision of e-commerce company, it has no motivation to supervise e-commerce company. Therefore, the government must come forward to supervise differential pricing, safeguard consumer rights and interests, and help e-commerce company gain consumer loyalty.When the condition (b) is met, that is−Pn+Pd+ΔP−M−Ie−F < 0, Cg−R < 0, and Cp−Tp < 0. With the improvement of consumers’ awareness of differential pricing and the reduction of the cost of platform supervising information, the information supervision cost of the platform is less than the reputation value brought by the loyal consumer to the platform, and the e-commerce platform can also join into the supervision of e-commerce company. When the other conditions remain unchanged, the strategy of each subject is stable at equilibrium point E8 (1, 1, 1, 1). The government and e-commerce platform jointly strengthen the supervision of differential pricing of e-commerce company, so that e-commerce company inclined to to be nondifferential pricing, and consumer is loyal to the e-commerce company.
## 4.1.2. ESS Analysis among Four-Party Game Players under the Loose Supervision of Government Regulatory Department
WhenCg−xR−1−xIe−1−x1−zIp−1−xN+1−xyαIe+1−zIp>0, government regulatory department implements loosely supervision. According to the Jacobian matrix shown in Appendix C, the equilibrium solution of the four-party evolutionary game can be obtained, and the stability analysis is shown in Table 4.Table 4
Asymptotic stability analysis of equilibrium point of replication dynamic system under the loose supervision of government regulatory department.
Equilibrium pointEigenvalue symbolStability of equilibrium pointE9 (0, 0, 0, 0)(+,X, X, X)Instability pointE10 (1, 0, 0, 0)(−, +,X, X)Instability pointE11 (0, 1, 0, 0)(+,X, X, X)Instability pointE12 (0, 0, 1, 0)(+,X, X, X)Instability pointE13 (1, 1, 0, 0)(X,−, X, +V)Instability pointE14 (1, 0, 1, 0)(X, +, +, +)Instability pointE15 (0, 1, 1, 0)(+,X, X, X)Instability pointE16 (1, 1, 1, 0)(−, −, −, −)ESS in condition (c)Note:X means uncertain of symbol, and ESS means the evolutionarily stable strategy.Condition (c):−Pn+Pd+ΔP−αM+Ie−F <0, Cp−Tp <0, and −Cg+R <0.As shown in Table4 that there is a possible stabilization strategy under loose supervision by government regulatory authorities, i.e. E16 (1, 1, 1, 0).When the condition (c) is met, that is,−Pn+Pd+ΔP−αM+Ie−F<0, Cp−Tp<0, and −Cg+R <0. The sum of the benefits of e-commerce company’s differential pricing for the loyal consumer is less than the sum of the benefits of e-commerce company’s nondifferential pricing for consumer, the fines punished by government regulatory department under loosely supervising and the compensation for the consumer for differential pricing of e-commerce company, and the fines imposed by e-commerce platform on the e-commerce company. The reputation value brought by the loyal consumer to the platform is greater than the cost of the platform information supervision. And the strict supervision cost is greater than the social benefits when controlling differential pricing for the government. Then the strategy of each subject is stable at equilibrium point E16 (1, 1, 1, 0). This situation may exist in the normative period of discriminatory pricing by the e-commerce company. At this time, as the proportion of the differential pricing of e-commerce company gradually decreases, the social benefits of the government’s strict supervision of differential pricing decrease. When the social benefit is less than the strictly supervising cost of the government regulatory department, the strategy of the government regulatory department will change from strictly supervising to loosely supervising. The main responsibility of supervision will be transferred from the government to the e-commerce platform and consumer. Supervision and fines by e-commerce platform and consumer enable e-commerce company to conduct nondifferential pricing and promote the virtuous circle of the e-commerce industry ecosystem.
## 4.2. Numerical Simulation Analysis
In order to test the reliability of the model and more intuitively demonstrate the influence of key factors in the replication dynamic system on the evolutionary trajectory of stakeholders of the multi-party game, the model is given numerical value combined with the actual situation, and the numerical simulation is carried out by MATLAB2021.For the e-commerce company operating in the e-commerce platform, the benefit of nondifferential pricing to the consumer is set asPn = 10, and the benefit of differential pricing to the consumer is set as Pd = 9, and the additional benefit of differential pricing to the loyal consumer is set as ∆P = 5. If differential pricing is discovered by the government, the compensation of the e-commerce company to the consumer is set as M = 4. The reputation value brought by the loyal consumer to the e-commerce company is set as Te = 5, and the reputation value brought by the loyal consumer to the e-commerce platform is set as Tp = 5. The utility obtained by the loyal consumer when purchasing goods from the e-commerce company is set as Ul = 12, and the utility obtained by the disloyal consumer when purchasing goods from the e-commerce company is set as Ud = 11. The probability of loyal consumer discovering differential pricing under government loose supervision is set as α = 0.2 and the complaint cost of the loyal consumer is set as Cc = 3. The social benefit of nondifferential pricing obtained by the government under strict supervision is set as R = 7, and the cost of strictly supervised by the government is set as Cg = 6. The fine by government regulatory department for differential pricing of e-commerce company Ie = 3. The social reputation loss of the government caused by differential pricing under loose supervision is set as N = 8. The normal benefit obtained by the government from the operation of the platform is set as S = 6. The benefit of the platform reasonably providing information to e-commerce company is set as W = 5, and the cost of the platform’s information supervision on e-commerce company is set as Cp = 7. The fine imposed by the platform to e-commerce company for differential pricing during information supervision is set as F = 3, and the proportion of fine imposed by the e-commerce platform for differential pricing of the e-commerce company is set as β = 0.6.
### 4.2.1. The Influence of Government Supervision Mechanism
To test whether the government supervision mechanism is effective in the process of differential pricing of e-commerce company, the proportions of government strict supervision are set asr = 0 and r = 1 to represent the two states of loose supervision and strict supervision of government supervision department. The evolution process of different initial strategies of the e-commercial company, consumer, and e-commerce platform is simulated and analyzed in three-dimensional space, and the simulation results with time are shown in Figure 6.Figure 6
Influence of the establishment of government supervision mechanism on strategy evolution of all parties.
(a)(b)(c)As shown in Figure6(a) that when government regulatory department adopts the strict supervision strategy on the differential pricing of e-commerce company, although the e-commerce platform does not take information supervision strategy on account of the high cost for information supervision, the strategies of the e-commerce company and consumer can still incline to be stable in nondifferential pricing and loyalty. This shows that it is very necessary and effective for the government to adopt the strict supervision strategy. With the reduction of Cp, that is, the information supervision cost reduced, the platform will be inclined to adopt the strategy of information supervision, to achieve coordinated supervision to e-commerce company by the government and platform, then the company adopts nondifferential pricing, and consumer is loyal to the e-commerce company. And the stable strategy portfolio is demonstrated in Figure 6(b). As is exhibited in Figure 6(c) that when government regulatory department implements the loosely supervising to e-commerce company for the differential pricing due to the high cost of strict supervision, if Cp is small, that is, the cost of information supervision on the e-commerce platform is small, and α is at a high level, the consumer can actively discover the differential pricing of the e-commerce company and report it, the e-commerce company will also incline to nondifferential pricing. Therefore, although the government selects the loose supervision strategy, the differential pricing behavior of e-commerce company is supervised collaboratively by the platform and consumer. The strategy equilibrium is consistent with the previous analysis of the stability under different government supervision strategies.
### 4.2.2. The Influence of Information Supervision Cost of E-Commerce Platforms
IfCp = {7, 4, 1}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 7.Figure 7
Influence of information supervision cost of e-commerce platform on strategy evolution of all parties.According to Figure7, with the reduction of the information supervision cost of the e-commerce platform, the supervision strategy of the platform will be transformed from information nonsupervision on e-commerce company to information supervision. Therefore, the platform can join the ranks of the government to regulate the company, and collaboratively supervise the differential pricing of the e-commerce company for loyal consumer. Moreover, the less the information supervision cost of the platform, the faster the stable strategy of information supervision. Therefore, active measures can be adopted to lower the cost for information supervising of e-commerce platform, to stimulate e-commerce platform to supervise the differential pricing behavior of e-commerce company on the platform.
### 4.2.3. The Influence of the Strict Supervision Cost of Government Regulatory Department
IfCg = {6, 8, 10}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 8.Figure 8
Influence of strict supervision cost of government regulatory department on strategy evolution of all parties.According to Figure8, the strict supervision cost of government affects the decision-making of government regulatory department, as well as affects the evolution of decision-making of the other subjects. With the increase of government supervision cost, the supervision strategy of the government regulatory department to the differential pricing of e-commerce company will be transformed from strict supervision to loose supervision, and gradually become the cyclical alternating strategy between strict supervision and loose supervision with medium proportion. The strategy of the e-commerce platform will be also transformed from information supervision to information nonsupervision of e-commerce company when strictly supervising cost of government Increasing. Free from the supervision of government regulatory department and platform, the pricing strategy of the company for the loyal consumer will be transformed from nondifferential pricing to moderate-proportion differential pricing, and the strategy change periodically. With the increase of the strictly supervising cost of government, the strategy of the consumer will be transformed from loyalty to e-commerce company to disloyalty. Therefore, the strict supervision cost of the government regulatory department is the key factor in restricting the differential pricing of the e-commerce company. Measures should be arranged to actively reduce the strictly supervising cost of the government regulatory department at a certain level, to stimulate platform and the consumer to regulate the behavior of e-commerce company in differential pricing.
### 4.2.4. The Influence of the Probability of Loyal Consumer Discovering Differential Pricing under Government's Loose Supervision
Ifα = {0.1, 0.3, 0.5}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 9.Figure 9
Influence of the probability of loyal consumer discovering differential pricing under government loose supervision on strategy evolution of all parties.According to Figure9, with the increase of probability of loyal consumer discovering differential pricing under government loose supervision, the probability of exposure of differential pricing behavior of e-commerce company for loyal consumer increases, which will make e-commerce company gradually improve the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The e-commerce platform can also gradually improve the proportion of information supervision due to the increase of fines for nonsupervision of e-commerce company information resulting in differential pricing, and the behavior stabilizes in the information supervision strategy. The government regulatory department can gradually loose supervision and transfer the responsibility of supervision to e-commerce platform and the consumer. Therefore, measures can be taken to encourage the consumer to report the differential pricing behavior of e-commerce company, to maintain the stable and sustainable progress of e-commerce platform and systems.
### 4.2.5. The Influence of the Penalties for Differential Pricing of E-Commerce Company under Government's Loose Supervision
IfM = {1, 2, 4}, Ie = {1, 2, 4}, and F = {1, 2, 4}, the evolution process and results of the strategy of the four-party game subjects are shown in Figure 10.Figure 10
Influence of the penalties for differential pricing of e-commerce company under government loose supervision on strategy evolution of all parties.According to Figure10, with the increase of the fines given by consumer, e-commerce platform, and government regulatory department for differential pricing of e-commerce company, the e-commerce company will gradually increase the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The consumer will increase the proportion of loyalty to the e-commerce company and the behavior stabilize in the loyalty strategy when the compensation for differential pricing from e-commerce company increases to compensate for the loss of differential pricing. The e-commerce platform will also gradually improve the proportion of information supervision due to the increase of benefits from information supervision fines and the behavior stabilizes in the information supervision strategy. Therefore, the nondifferential pricing behavior of e-commerce company can be promoted by increasing the punishment for differential pricing, to realize the joint dynamic supervision of the e-commerce platform, the consumer, and the government on the pricing of the e-commerce company.
## 4.2.1. The Influence of Government Supervision Mechanism
To test whether the government supervision mechanism is effective in the process of differential pricing of e-commerce company, the proportions of government strict supervision are set asr = 0 and r = 1 to represent the two states of loose supervision and strict supervision of government supervision department. The evolution process of different initial strategies of the e-commercial company, consumer, and e-commerce platform is simulated and analyzed in three-dimensional space, and the simulation results with time are shown in Figure 6.Figure 6
Influence of the establishment of government supervision mechanism on strategy evolution of all parties.
(a)(b)(c)As shown in Figure6(a) that when government regulatory department adopts the strict supervision strategy on the differential pricing of e-commerce company, although the e-commerce platform does not take information supervision strategy on account of the high cost for information supervision, the strategies of the e-commerce company and consumer can still incline to be stable in nondifferential pricing and loyalty. This shows that it is very necessary and effective for the government to adopt the strict supervision strategy. With the reduction of Cp, that is, the information supervision cost reduced, the platform will be inclined to adopt the strategy of information supervision, to achieve coordinated supervision to e-commerce company by the government and platform, then the company adopts nondifferential pricing, and consumer is loyal to the e-commerce company. And the stable strategy portfolio is demonstrated in Figure 6(b). As is exhibited in Figure 6(c) that when government regulatory department implements the loosely supervising to e-commerce company for the differential pricing due to the high cost of strict supervision, if Cp is small, that is, the cost of information supervision on the e-commerce platform is small, and α is at a high level, the consumer can actively discover the differential pricing of the e-commerce company and report it, the e-commerce company will also incline to nondifferential pricing. Therefore, although the government selects the loose supervision strategy, the differential pricing behavior of e-commerce company is supervised collaboratively by the platform and consumer. The strategy equilibrium is consistent with the previous analysis of the stability under different government supervision strategies.
## 4.2.2. The Influence of Information Supervision Cost of E-Commerce Platforms
IfCp = {7, 4, 1}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 7.Figure 7
Influence of information supervision cost of e-commerce platform on strategy evolution of all parties.According to Figure7, with the reduction of the information supervision cost of the e-commerce platform, the supervision strategy of the platform will be transformed from information nonsupervision on e-commerce company to information supervision. Therefore, the platform can join the ranks of the government to regulate the company, and collaboratively supervise the differential pricing of the e-commerce company for loyal consumer. Moreover, the less the information supervision cost of the platform, the faster the stable strategy of information supervision. Therefore, active measures can be adopted to lower the cost for information supervising of e-commerce platform, to stimulate e-commerce platform to supervise the differential pricing behavior of e-commerce company on the platform.
## 4.2.3. The Influence of the Strict Supervision Cost of Government Regulatory Department
IfCg = {6, 8, 10}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 8.Figure 8
Influence of strict supervision cost of government regulatory department on strategy evolution of all parties.According to Figure8, the strict supervision cost of government affects the decision-making of government regulatory department, as well as affects the evolution of decision-making of the other subjects. With the increase of government supervision cost, the supervision strategy of the government regulatory department to the differential pricing of e-commerce company will be transformed from strict supervision to loose supervision, and gradually become the cyclical alternating strategy between strict supervision and loose supervision with medium proportion. The strategy of the e-commerce platform will be also transformed from information supervision to information nonsupervision of e-commerce company when strictly supervising cost of government Increasing. Free from the supervision of government regulatory department and platform, the pricing strategy of the company for the loyal consumer will be transformed from nondifferential pricing to moderate-proportion differential pricing, and the strategy change periodically. With the increase of the strictly supervising cost of government, the strategy of the consumer will be transformed from loyalty to e-commerce company to disloyalty. Therefore, the strict supervision cost of the government regulatory department is the key factor in restricting the differential pricing of the e-commerce company. Measures should be arranged to actively reduce the strictly supervising cost of the government regulatory department at a certain level, to stimulate platform and the consumer to regulate the behavior of e-commerce company in differential pricing.
## 4.2.4. The Influence of the Probability of Loyal Consumer Discovering Differential Pricing under Government's Loose Supervision
Ifα = {0.1, 0.3, 0.5}, the stability of the system evolution of the four-party game subjects and the simulation results are shown in Figure 9.Figure 9
Influence of the probability of loyal consumer discovering differential pricing under government loose supervision on strategy evolution of all parties.According to Figure9, with the increase of probability of loyal consumer discovering differential pricing under government loose supervision, the probability of exposure of differential pricing behavior of e-commerce company for loyal consumer increases, which will make e-commerce company gradually improve the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The e-commerce platform can also gradually improve the proportion of information supervision due to the increase of fines for nonsupervision of e-commerce company information resulting in differential pricing, and the behavior stabilizes in the information supervision strategy. The government regulatory department can gradually loose supervision and transfer the responsibility of supervision to e-commerce platform and the consumer. Therefore, measures can be taken to encourage the consumer to report the differential pricing behavior of e-commerce company, to maintain the stable and sustainable progress of e-commerce platform and systems.
## 4.2.5. The Influence of the Penalties for Differential Pricing of E-Commerce Company under Government's Loose Supervision
IfM = {1, 2, 4}, Ie = {1, 2, 4}, and F = {1, 2, 4}, the evolution process and results of the strategy of the four-party game subjects are shown in Figure 10.Figure 10
Influence of the penalties for differential pricing of e-commerce company under government loose supervision on strategy evolution of all parties.According to Figure10, with the increase of the fines given by consumer, e-commerce platform, and government regulatory department for differential pricing of e-commerce company, the e-commerce company will gradually increase the proportion of nondifferential pricing and stabilize in the nondifferential pricing strategy. The consumer will increase the proportion of loyalty to the e-commerce company and the behavior stabilize in the loyalty strategy when the compensation for differential pricing from e-commerce company increases to compensate for the loss of differential pricing. The e-commerce platform will also gradually improve the proportion of information supervision due to the increase of benefits from information supervision fines and the behavior stabilizes in the information supervision strategy. Therefore, the nondifferential pricing behavior of e-commerce company can be promoted by increasing the punishment for differential pricing, to realize the joint dynamic supervision of the e-commerce platform, the consumer, and the government on the pricing of the e-commerce company.
## 5. Conclusions
Given the phenomenon of “big data killing” that e-commerce companies use customer information in the pricing process, this paper studies how to safeguard consumers’ pricing fairness in the context of the Internet, and builds the four-party evolutionary game model for the supervision on differential pricing of e-commerce company, analyzes the stability of the strategy selection of each subject in the model, and the stability of equilibrium point of the strategic combination in the replication dynamic system, and simulates and analyzes the influence of key elements on the strategy evolution. The main conclusions are as follows:(1)
The government supervision mechanism can play an effective role to limit differential pricing of the e-commerce company. When the proportion of strict government supervision adds, the sum of the benefits of differential pricing for loyal consumers by e-commerce company is less than the penalty cost of e-commerce company, and strict supervision cost of government is less than its social benefits, then e-commerce company inclines more to choose the strategy of nondifferential pricing. Since the reputation value of the e-commerce platform is less than the information supervision cost of platform, the platform inclines more to conduct information nonsupervision. Therefore, the equilibrium strategy of each subject is stable at point E5 (1, 1, 0, 1), which occurs in the early stage of the government’s strict supervision on the e-commerce company. With the reduction of the supervision cost of the platform, it is also willing to join the supervision on differential pricing of e-commerce company for the platform and inclines more to choose information supervision strategy. Therefore, the equilibrium strategy of each subject is stable at point E8 (1, 1, 1, 1), which occurs in the stable stage of the government’s strict supervision of e-commerce company, and the participation of the e-commerce platform relieved the pressure on government supervising on the company. When the strictly supervising cost of government increases, the reputation value of the platform is greater than the supervision cost of the platform, then the government regulatory department inclines more to loose supervision strategy. Therefore, the equilibrium strategy of each subject is stable at point E16 (1, 1, 1, 0), which occurs in the later stage of the government’s strict supervision of e-commerce company. When both e-commerce platform and consumer realize the important role of supervision and conduct strong collaborative supervision, the government can take the way of auxiliary supervision to control the differential pricing of the e-commerce company.(2)
The information supervision cost of the e-commerce platform is the main factor affecting the supervision strategy of the platform. When the supervision cost of the platform is greater than the reputation value of the platform, the platform inclines more to conduct information nonsupervision. However, as the information supervision cost of the platform decreases and is less than the reputation value of the platform, the stable strategy of the e-commerce platform will transform into information supervision and then promote nondifferential pricing for the e-commerce company. Moreover, the less the information supervision cost of the e-commerce platform, the faster the stable strategy of the e-commerce platform can transform into the information supervision strategy.(3)
The strict supervision cost of government is the main factor affecting the strategies of all parties. When the strict supervision cost of government is so small as to be less than the social benefits of government strict supervision on differential pricing of e-commerce company, the equilibrium strategy of all parties is that both government regulatory department and e-commerce platform implement supervision, e-commerce company conduct nondifferential pricing, and consumer is loyal to the e-commerce company. However, when the strict supervision cost of government increases and exceeds the social benefits of government strict supervision on differential pricing of e-commerce company, the government gradually inclines to loose supervision strategy. At this moment, if platform and consumer can supervise the pricing of the e-commerce company to a certain extent, e-commerce company still incline to nondifferential pricing strategy. When the strict supervision cost of government increases to a very high level, not only the government cannot strictly supervise, but also e-commerce platform will not supervise the information used by the e-commerce company. Then e-commerce company will incline to differentiate pricing, and the consumer will be disloyal.(4)
The probability of the consumer discovering differential pricing under the government’s loose supervision policy is an important factor affecting the strategies of all parties. As strict supervision cost of government is at a higher level, and the probability of consumer discovering differential pricing of the e-commerce company is small, neither the government nor the e-commerce platform can incline to the more stable behavioral strategy. Although customer inclines to be loyal to the e-commerce company, the strategies of four subjects cannot maintain the stable equilibrium, and the strategy of e-commerce company become cyclical alternating between differential pricing and nondifferential pricing. When the probability of consumer discovering differential pricing of e-commerce company increases, e-commerce company gradually inclines to nondifferential pricing strategy, e-commerce platform gradually inclines to information supervision strategy, and the government gradually inclines to loose supervision strategy. The equilibrium strategy of four-party behavior achieves. The higher the probability level of consumer discovering differential pricing, the faster the equilibrium strategy of four-party behavior achieves. This conclusion also confirms the conclusion in the research of Yu and Li [9] and Wu et al. [30] that the probability of consumer finding himself killed in price is the important factor affecting the strategy choice of consumer and company.(5)
The penalties for differential pricing of e-commerce company under the government’s loose regulatory are the important factors affecting the strategies of all parties. When consumers, e-commerce platform and government regulatory department impose the fines and compensation on differential pricing of e-commerce companies at a low level, the government and e-commerce platform incline to not supervise, and e-commerce company and consumer cannot maintain a stable equilibrium. When the penalties for differential pricing of e-commerce company is high, e-commerce platform inclines to supervise the information, consumer inclines to be loyal, while e-commerce company inclines to price nondifferentially, the government inclines to loose supervise, and the strategies remains stable. The higher the penalties for differential pricing of e-commerce company, the faster the equilibrium strategy of four-party behavior achieves.In this study, the modeling analysis and simulation of the supervision of “big data killing” of e-commerce company are carried out, which breaks through the limitation of analyzing only two or three parties in the existing “big data killing” problem. It is a beneficial supplement to systematic research on this issue that more participants consider their action strategies under the same system. The four-party evolutionary game model constructed also expands the application scope of the evolutionary game method in the study of pricing supervision of e-commerce company. The research conclusions can provide favorable theoretical support for the “big data killing” problem in practice.Therefore, to better restrain the pricing behavior of e-commerce company, regulate differential pricing, and build a good e-commerce shopping environment, the following measures should be taken by the government regulatory department, e-commerce platform, e-commerce company, and consumer.(1)
From the perspective of the government, the government regulatory department must supervise e-commerce company, especially in the early stage of price discrimination by using customer information. Therefore, the government needs to use economic and policy means to effectively manage the operation of e-commerce platform and company and promote the enthusiasm of e-commerce company to conduct nondifferential pricing. For example, adopting more advanced big data analysis technology to supervise price changes of e-commerce company; establishing more extensive and efficient reporting channels so that consumers can timely price complaints; improving corresponding legal measures to increase the violation cost of the e-commerce company and punishing “big data killing” from the aspects of economy and reputation. While supervising, it is also necessary to pay attention to reducing the strict supervision cost of the government regulatory department.(2)
From the perspective of the e-commerce platform, as the important carrier of e-commerce operation, the e-commerce platform should strengthen information supervising of the e-commerce company. The e-commerce platform is the main body that controls customer information. E-commerce company conducts “big data killing” differential pricing based on the mastery of customer information. Therefore, the e-commerce platform needs to carry out information supervision when providing information for the e-commerce company and formulates policies to punish e-commerce company with differential pricing. It is also necessary to improve the technical management level of the e-commerce platform, and use innovative technology based on big data to monitor e-commerce company and reduce the supervision cost of the e-commerce platform.(3)
From the perspective of consumers, they should actively protect their rights and interests. While online shopping brings convenience to consumers, it may also lead to the possibility of price discrimination with consumer information. In the process of e-commerce shopping, consumers will prefer some e-commerce companies due to path dependence, and then form customer loyalty, but this path dependence should not be the reason for the differential pricing of e-commerce companies. Therefore, consumers should enhance price sensitivity and verify the displayed price of e-commerce companies through various channels, to reduce the infringement of consumer rights and interests by e-commerce companies.(4)
From the perspective of the e-commerce company, although maximizing profits is the important motive of business behavior, the reputation and service in e-commerce shopping are the foundation for the long-term development of the e-commerce company. Under the market conditions where consumers’ transfer costs are getting lower and lower, the e-commerce company can grow gradually mainly based on gaining the loyal customer. Therefore, e-commerce company should not adopt the differential pricing strategy in pursuit of temporary benefits. Although the economic benefits brought by nondifferential pricing of e-commerce company are less in the short term, the reputation benefits and social benefits can create greater economic benefits for the development of the company in the long term, which are the wealth of e-commerce company. The reputation benefits and social benefits brought by nondifferential pricing can be benefit for the more fair and equitable overall development environment for e-commerce.This study systematically analyzes the model on the supervision of “big data killing” in the e-commerce company. However, the mechanism setting of the four-party game in the study has been simplified to a certain extent, and the strategy space needs to be more detailed and in-depth, which should be improved in the future. Moreover, because the simulation data were conducted under simulated conditions according to actual conditions, there may be some deviations in the effectiveness of players’ behavior analysis in the “big data killing” game. In the future, methods such as data mining will be used to collect big data, and empirical analysis of evolutionary game will be carried out, to improve the research on the participants behavior of “big data killing” in e-commerce transactions.
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*Source: 2900286-2022-03-18.xml* | 2022 |
# The Autologous Hematopoietic Stem Cells Transplantation Combination-Based Chimeric Antigen Receptor T-Cell Therapy Improves Outcomes of Relapsed/Refractory Central Nervous System B-Cell Lymphoma
**Authors:** Fei Xue; Peihao Zheng; Rui Liu; Shaomei Feng; Yuelu Guo; Hui Shi; Haidi Liu; Biping Deng; Teng Xu; Xiaoyan Ke; Kai Hu
**Journal:** Journal of Oncology
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2900310
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## Abstract
Objective. The objective is to explore the effectiveness and safety of CAR T-cell therapy in advanced relapsed/refractory central nervous system B-cell lymphoma and compare the impact of autologous stem cell transplantation (ASCT) plus CAR T-cell therapy versus sequential CART therapy on the survival of patients. Methods. The retrospective analysis was based on the data of 17 patients with advanced relapsed/refractory central nervous system B-cell lymphoma. Bridging chemotherapy was applied before CAR T-cell infusion to further reduce the tumor burden. For patients with autologous hematopoietic stem cell successful collection, CD19/20/22CAR T-cell immunotherapy following ASCT was performed with the thiotepa-containing conditioning regimen, while sequential CD19/CD20/CD22CAR T-cell therapy was applied. For lymphodepletion, patients received bendamustine or fludarabine monotherapy or fludarabine combined with cyclophosphamide pre-CART-cell infusion. Results. Out of the 17 patients, 8 completed ASCT plus CART cell therapy, while 9 patients completed CART cell alone therapy. In efficacy assessment at 3 months after infusion, the objective response rate (ORR) was 12/17 (71%) and the complete response rate (CRR) was 11/17 (65%). The CRR of the ASCT group and non-ASCT was 100% and 44.4%, respectively (P<0.01). The median progression-free survival was 16.3 (2.6–24.5) months, and the median overall survival was 19.3 (6–24.5) months. Patients who underwent ASCT plus CART cell therapy had significantly longer PFS (P<0.01) and OS (P<0.01). Grade 3 or higher immune effector cell-associated neurologic toxicity syndrome (≥grade 3 ICANS) and cytokine release syndrome (≥grade 3 CRS) events occurred in 29% and 41% of the patients, respectively. No treatment-related death occurred. Conclusion. The CAR T-cell therapy could augment its efficacy in the treatment of advanced relapsed/refractory CNS B-cell lymphoma, while ASCT in combination with CART can induce durable responses and OS with a manageable side effect.
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## Body
## 1. Background
Central nervous system (CNS) lymphoma includes primary central nervous system lymphoma (PCNSL) and secondary central nervous system lymphoma (SCNSL), both of which are usually treated with the regimen of aggressive high-dose methotrexate (MTX) [1, 2] or thiotepa-based induction chemotherapy and autologous hematopoietic stem cell transplantation (ASCT) or whole-brain radiotherapy consolidation treatment [3, 4]. The complete remission (CR) rate of PCNSL patients has been reported to be approximately 45% [5–7]. However, approximately 35%–60% of patients relapse within 1-2 years, and nearly 10%–15% of patients are not sensitive to therapy [8]. The prognosis of patients with SCNSL is even worse, as long-term survival can be achieved in less than 20% of patients [9]. Although targeted drugs such as Bruton tyrosine kinase inhibitors (BTKis), Lenalidomide, and programmed death-1 inhibitors have improved the outcomes of central nervous system (CNS) lymphoma (the best CR rate 86%), patients tend to develop drug resistance rapidly, and the prognosis of these suffers remains poor [9]. Refraction and recurrence are the major causes of treatment failure in patients with CNS lymphoma [10–13]. Nevertheless, there is no consensus in the standard treatment for relapsed/refractory CNS (r/r CNS) lymphoma, currently. Therefore, it is a pressing issue that searching for a more effective treatment regimen for these challenging patient population.Chimeric antigen receptor-T cell (CART) therapy can effectively improve the complete remission (CR) rate of relapsed/refractory malignant B-cell tumors (range from 39% to 58%) and progression-free survival (median progression-free survival of 5.9 months) [14–18]. Yet, concerns for potential life-threatening neurotoxicity of CART cells and immune privileged of central nervous system, patients with r/r CNS lymphoma are excluded from pivotal cohort studies, and little is known about its effectiveness and treatment-related toxicities [14, 19]. Recently, several studies [20–24] (ranging from case reports or series to cohort studies) reported on the controllability of neurological toxicities and the effectiveness of CART cells in treating r/r CNS B-cell lymphoma. A retrospective study with eight patients diagnosed with secondary CNS B-cell lymphoma treated by CD19CART cells showed encouraging efficacy and manageable adverse events. A total of 4 patients were response to treatment and no patient experienced greater than grade-1 neurotoxicity [22]. Another prospective cohort study related to CAR T-cell immunotherapy in patients with relapsed PCNSL demonstrated that the overall response rate (ORR) is 58% (7/12), and the rate of ICANS is 50% but severe neurotoxicity (≥grade 3) 8% (1/12) [23]. These findings suggest that it is possible to treat r/r CNS B-cell lymphoma by CAR T-cell immunotherapy, but the duration of the responses was relatively short (median PFS ranging from only 3 months to 4.4 months) [25, 26]. Hence, to improve the poor outcome of low long-term remission rate, investors resort to combination with consolidation therapy.For CNS lymphoma, autologous stem cell transplantation (ASCT) and whole-brain radiation therapy (WBRT) have been used as standard consolidation treatments in the past [27]. However, patients with WBRT alone were prone to disabling cognitive dysfunction and devastating consequences on the quality of life [27, 28]. In the prospective study, patients with PCNSL were treated by cranial irradiation following chemotherapy and the incidence of severe neurologic toxicity was 15% [29]. WBRT probably increases the neurotoxicity of CART cells for treating CNS lymphoma. Instead of WBRT, combination with ASCT is naturally selected, this combination therapy has been applied to relapsed/refractory multiple myeloma and non-CNS lymphoma, and conditioning regime pre-ASCT can deeply deplete lymphocytes inhibiting the function of CART cells [30–32]. Recently, CAR T-cell immunotherapy following autologous stem cell transplantation (ASCT) for central nervous system lymphoma has been reported [26, 33]. The overall response rate (ORR) is nearly 82%, and the complete remission rate (CRR) is approximately 55%. The median durable response achieved a relatively longer at 14.03 months [33]. The incidence of severe immune effector cell-associated neurologic toxicity was 8%. However, it is not available for patients who cannot tolerate the toxicity of chemotherapy or without hematopoietic stem cells. In recent years, separate CAR T-cell immunotherapeutic avenues such as “Dual-Target” and “cocktail” CAR T-cell therapies are also administrated to attain ongoing complete remission [20, 26]. The patient in the former report continued CR for more than 17 months, but the median PFS in the latter study was only 3 months, which appeared to be a shorter term than ASCT plus CART. However, very few subjects were included. Therefore, we retrospectively investigated the effectiveness and safety of CART cells in treating 17 patients with r/r CNS B-cell lymphoma in the real-world and firstly compared the impact of ASCT plus CAR T-cell therapy versus sequential multitargeted (CD19, CD20, and CD22) CAR T-cell on durable remission.
## 2. Materials and Methods
### 2.1. Participant Population
Data from 17 patients with advanced r/r CNS B-cell lymphoma enrolled in the clinical- trial “Different B cell-targeted CART sequential infusion for adult patients with relapsed/refractory aggressive B-cell lymphoma (Clinicaltrials.gov registry:ChiCTR1900020980)” in the Beijing Boren Hospital between October 1, 2018, and October 1, 2020, were retrospectively analyzed. On the basis of the 2016 World Health Organization (WHO) guidelines and the diagnosed criteria of SCNSL [34–36], the diagnosis of CNS B-cell lymphoma by stereotactic biopsy and/or lumbar puncture for immunochemistry (IHC) (Figure 1) and/or flow cytometry (FCM) has been confirmed. An imaging examination was performed to clarify the lesion site. Of the 17 patients, 10 had brain parenchymal involvement, 4 had cerebrospinal fluid (CSF) involvement, and 3 had both brain parenchymal and CSF involvement. This study was approved by the Ethics Committee of the Beijing Boren Hospital, and all patients signed an informed consent form.Figure 1
Representative images of three patients with diffuse large B-cell lymphoma with central nervous system involvement are demonstrated (H & E, original magnification x100 and immunohistochemistry, original magnification x100).
### 2.2. Procedures
Peripheral blood mononuclear cells (PBMNCs) were isolated from the eligible patients, and CD3+ T lymphocytes were separated by using antigen-coated immunomagnetic beads. CD19/CD20/CD22 expression in tumor tissues was identified by IHC and FCM, which was the basis for selecting targets for CART cells. The second generation anti-CD19, CD20, and CD22-41BB-CAR lentiviral vector was constructed to transfect purified CD3+ T cells to prepare CART cells. The detailed processes have already been described in previous studies [37–39].Bridging chemotherapy was permitted prior to CAR T-cell transfusion to reduce tumor burden (for patients with CSF involvement, an intrathecal injection of 15 mg methotrexate, 50 mg cytarabine, and 5 mg dexamethasone, twice per week was performed until the minimal residual disease of the CSF showed negative by FCM). For patients with a response to chemotherapy, autologous hematopoietic stem cells were mobilized by granulocyte colony-stimulating factors and collected. Patients with successful stem cell collection received ASCT in combination with CAR T-cell therapy with the TEAM (thiotepa 5 mg/kg, d-8 to d-7; VP-16 200 mg/m2·d, d-6 to d-3;Ara-C 200 mg/m2·d, d-6 to d-3; and melphalan 140 mg/m2·d, d-2) or BEAM (BCNU 300 mg/m2, d-6; VP-16 200 mg/m2·d, d-5 to d-2, Ara-C 200 mg/m2, q12 h, d-5 to d-2; and Mel 140 mg/m2, d-1)-based conditioning regimen. The detailed dosages were adjusted according to the fundamental status and tolerance of the patients. Taking the date of CART transfusion as day 0, ASCT was transfused on day-1.For patients with insufficient/without autologous stem cells, sequentially different (CD19, CD20, and CD22) CART cell therapy was performed, and the sequential interval between different targeted CAR T-cell infusions was within 3 months. For all the patients, bendamustine (90–100 mg/m2) or fludarabine (25–30 mg/m2, d-3 to d-1) monotherapy or in combination with cyclophosphamide (CTX, 250 mg/m2, d-4 to d-2) was administrated for lymphocyte clearing prior to CART cell transfusion (Figure 2).Figure 2
Flow diagram of the 17 patients underwent treatment.A multicolor flow cytometer (FACS Calibur, BD, USA) was used to detect the CAR T-cell concentration in the blood and cerebrospinal fluid (CSF). Enzyme-linked immunosorbent assay (ELISA) was used to dynamically monitor the peripheral serum cytokines (IL-6, IL-10, TNFα, sCD25, and IFN-γ), and chemiluminescence (ECL) was used to monitor ferritin. The laboratory monitoring was done on d0, d3, d7, d14, d21, and d28 and then monthly until 6 months after transfusion of CART. Thereafter, the monitoring was further continued every 3 months until 24 months after the transfusion. The response was assessed by computed tomography (CT) and contrast-enhanced magnetic resonance once per month within 6 months after CART, and positron emission tomography/computed tomography (PET/CT), enhanced magnetic resonance imaging (MRI), or positron emission tomography/magnetic resonance imaging (PET/MRI) every 3 months until 24 months after CART transfusion while CSF assessments are monthly for three months and then quarterly for up to 24 months. The efficacy was assessed by two lymphoma specialists independently according to Lugano criteria (2014) [40]. Progression-free survival (PFS) is defined as the time from enrollment to the date of disease progression or last follow-up or death from any cause. Overall survival (OS) is defined as the time from enrollment to the date of last follow-up or death from any cause.In terms of treatment-related adverse reactions, cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) were graded according to the America Society of Transplantation and Cellular Therapy consensus criteria [41] and were treated according to Lee et al. [41]. In addition, anti-epilepsy drugs were also administered for seizure prophylaxis. Based on the National Cancer Institute CTCAE (Version 5.0), toxicities on organs were assessed. The assessment of engraftment of ASCT was as follows: a neutrophil count ≥0.5 × 109/L for three continuous days was considered granulocyte engraftment, and a platelet count >20 × 109/L for seven continuous days when no platelet infusion was performed was considered platelet engraftment.Fluorescence in situ hybridization (FISH) was used to detect the amplification and ectopic rearrangements ofBCL2/BCL6/MYC in tumor tissues. Next generation sequencing (NGS) was used to detect hotspot mutations in 225 lymphoma-related genes, where the sequencing depth was >1500x.
### 2.3. Statistical Analysis
SPSS 26.0 software and GraphPad Prism 9.0 software were used for statistical analysis. The chi-square (χ2) or Fisher test was used for the analysis of categorical data and the evaluation of associations between variables and efficacy. The Kaplan-Meier method was used for univariate analysis of progression-free survival (PFS) and overall survival (OS). The rank-sum test was used for the analysis of CART cell expansion. P<0.05 was considered statistically significant.
## 2.1. Participant Population
Data from 17 patients with advanced r/r CNS B-cell lymphoma enrolled in the clinical- trial “Different B cell-targeted CART sequential infusion for adult patients with relapsed/refractory aggressive B-cell lymphoma (Clinicaltrials.gov registry:ChiCTR1900020980)” in the Beijing Boren Hospital between October 1, 2018, and October 1, 2020, were retrospectively analyzed. On the basis of the 2016 World Health Organization (WHO) guidelines and the diagnosed criteria of SCNSL [34–36], the diagnosis of CNS B-cell lymphoma by stereotactic biopsy and/or lumbar puncture for immunochemistry (IHC) (Figure 1) and/or flow cytometry (FCM) has been confirmed. An imaging examination was performed to clarify the lesion site. Of the 17 patients, 10 had brain parenchymal involvement, 4 had cerebrospinal fluid (CSF) involvement, and 3 had both brain parenchymal and CSF involvement. This study was approved by the Ethics Committee of the Beijing Boren Hospital, and all patients signed an informed consent form.Figure 1
Representative images of three patients with diffuse large B-cell lymphoma with central nervous system involvement are demonstrated (H & E, original magnification x100 and immunohistochemistry, original magnification x100).
## 2.2. Procedures
Peripheral blood mononuclear cells (PBMNCs) were isolated from the eligible patients, and CD3+ T lymphocytes were separated by using antigen-coated immunomagnetic beads. CD19/CD20/CD22 expression in tumor tissues was identified by IHC and FCM, which was the basis for selecting targets for CART cells. The second generation anti-CD19, CD20, and CD22-41BB-CAR lentiviral vector was constructed to transfect purified CD3+ T cells to prepare CART cells. The detailed processes have already been described in previous studies [37–39].Bridging chemotherapy was permitted prior to CAR T-cell transfusion to reduce tumor burden (for patients with CSF involvement, an intrathecal injection of 15 mg methotrexate, 50 mg cytarabine, and 5 mg dexamethasone, twice per week was performed until the minimal residual disease of the CSF showed negative by FCM). For patients with a response to chemotherapy, autologous hematopoietic stem cells were mobilized by granulocyte colony-stimulating factors and collected. Patients with successful stem cell collection received ASCT in combination with CAR T-cell therapy with the TEAM (thiotepa 5 mg/kg, d-8 to d-7; VP-16 200 mg/m2·d, d-6 to d-3;Ara-C 200 mg/m2·d, d-6 to d-3; and melphalan 140 mg/m2·d, d-2) or BEAM (BCNU 300 mg/m2, d-6; VP-16 200 mg/m2·d, d-5 to d-2, Ara-C 200 mg/m2, q12 h, d-5 to d-2; and Mel 140 mg/m2, d-1)-based conditioning regimen. The detailed dosages were adjusted according to the fundamental status and tolerance of the patients. Taking the date of CART transfusion as day 0, ASCT was transfused on day-1.For patients with insufficient/without autologous stem cells, sequentially different (CD19, CD20, and CD22) CART cell therapy was performed, and the sequential interval between different targeted CAR T-cell infusions was within 3 months. For all the patients, bendamustine (90–100 mg/m2) or fludarabine (25–30 mg/m2, d-3 to d-1) monotherapy or in combination with cyclophosphamide (CTX, 250 mg/m2, d-4 to d-2) was administrated for lymphocyte clearing prior to CART cell transfusion (Figure 2).Figure 2
Flow diagram of the 17 patients underwent treatment.A multicolor flow cytometer (FACS Calibur, BD, USA) was used to detect the CAR T-cell concentration in the blood and cerebrospinal fluid (CSF). Enzyme-linked immunosorbent assay (ELISA) was used to dynamically monitor the peripheral serum cytokines (IL-6, IL-10, TNFα, sCD25, and IFN-γ), and chemiluminescence (ECL) was used to monitor ferritin. The laboratory monitoring was done on d0, d3, d7, d14, d21, and d28 and then monthly until 6 months after transfusion of CART. Thereafter, the monitoring was further continued every 3 months until 24 months after the transfusion. The response was assessed by computed tomography (CT) and contrast-enhanced magnetic resonance once per month within 6 months after CART, and positron emission tomography/computed tomography (PET/CT), enhanced magnetic resonance imaging (MRI), or positron emission tomography/magnetic resonance imaging (PET/MRI) every 3 months until 24 months after CART transfusion while CSF assessments are monthly for three months and then quarterly for up to 24 months. The efficacy was assessed by two lymphoma specialists independently according to Lugano criteria (2014) [40]. Progression-free survival (PFS) is defined as the time from enrollment to the date of disease progression or last follow-up or death from any cause. Overall survival (OS) is defined as the time from enrollment to the date of last follow-up or death from any cause.In terms of treatment-related adverse reactions, cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) were graded according to the America Society of Transplantation and Cellular Therapy consensus criteria [41] and were treated according to Lee et al. [41]. In addition, anti-epilepsy drugs were also administered for seizure prophylaxis. Based on the National Cancer Institute CTCAE (Version 5.0), toxicities on organs were assessed. The assessment of engraftment of ASCT was as follows: a neutrophil count ≥0.5 × 109/L for three continuous days was considered granulocyte engraftment, and a platelet count >20 × 109/L for seven continuous days when no platelet infusion was performed was considered platelet engraftment.Fluorescence in situ hybridization (FISH) was used to detect the amplification and ectopic rearrangements ofBCL2/BCL6/MYC in tumor tissues. Next generation sequencing (NGS) was used to detect hotspot mutations in 225 lymphoma-related genes, where the sequencing depth was >1500x.
## 2.3. Statistical Analysis
SPSS 26.0 software and GraphPad Prism 9.0 software were used for statistical analysis. The chi-square (χ2) or Fisher test was used for the analysis of categorical data and the evaluation of associations between variables and efficacy. The Kaplan-Meier method was used for univariate analysis of progression-free survival (PFS) and overall survival (OS). The rank-sum test was used for the analysis of CART cell expansion. P<0.05 was considered statistically significant.
## 3. Results
### 3.1. Clinical Characteristics
Baseline patient characteristics listed in Table1 indicate that 17 CNS involvement patients, with a median age of 42 years (range of 19 to 66), comprised 9 (53%) males and 8 (47%) females. 15 (88%) patients had secondary CNS B-cell lymphoma (mantle cell lymphoma, n = 1; Burkitt lymphoma, n = 1; diffuse large B-cell lymphoma non-GCB, n = 9; and diffuse large B-cell lymphoma GCB, n = 4), and 2 (12%) had primary central nervous system B-cell lymphoma. All the patients were diagnosed with Ann Arbor stage IV. For 14 patients aged <60 years, the age-adjusted international prognostic index (aaIPI) ≥3 was 8, and for 3 patients aged ≥60 years, the international prognostic index (IPI) was 5, 4, and 4, respectively. Clinical symptoms and signs at the time of enrollment included headache 65% (11/17); blurred vision and diplopia 12% (2/17); nausea and vomiting 18% (3/17); convulsion 6% (1/17); waist pain, lower limb numbness, and reduced muscle strength 24% (4/17); hearing loss 12% (2/17); and distortion of the commissure 12% (2/17). The Eastern Cooperative Oncology Group performance status score ranged from 2 to 4 points. FISH assays for MYC/BCL2/BCL6 in tumor tissues were performed in 11 (65%) patients. Two of them also received P53 measurements (Table 1). The abnormal factors involved MYC/BCL2/BCL6 rearrangement and/or amplification and P53 deletion. Among them, 3 (patient No.1, patient No.7, and patient No.17) were diagnosed double hit lymphoma and one (patient No.3) had P53 deletion. Next-generation sequencing for gene mutation in tumor tissues was performed in 11 patients, and 9 patients had gene mutations positive, including TP53 (5/11), KMT2D (4/11), CD79b (3/11), CCND3 (3/11), CREBBP (2/11), TET2 (2/11), and MYD88 (1/11), as shown in Table 1. A total of 17 patients received ≥2 lines of antineoplastic therapies, and the median number of prior therapies was 11 (range of 5 to 18), as shown in Table 2. In 17 patients, 7 (7/17) were insensitive to chemotherapy and refractory, while the remaining 10 (10/17) patients had relapsed after first-line/second-line therapy, especially in combination with targeted drug therapy (BTKi, n = 9; BCL2 inhibitor, n = 8; and programmed death-1 inhibitor, n = 1). 3 (3/17) patients had progressed after ASCT, 5 (5/17) relapsed after CART therapy, and 6 (6/17) patients had a history of partial radiotherapy. At the time of enrollment, 5 (5/17) patients had isolated central nervous system involvement, and 12 (12/17) had systemic disease progression in addition to central nervous system involvement. Before the initiation of therapy, the disease status was progressive disease (PD) in 15 (15/17) patients and stable disease (SD) in 2 (2/17).Table 1
Clinical characteristics of patients.
IDSexAgeDisease pathologyStageaaIPI/IPIPCNSLSite of CNS disease maximal dimension (mm)Tumor in CSF (%)Tumor in BM (%)NGSFISHPrevious CART therapyPrevious ASCT therapyDisease status1F39DLBCL GCBIVB2NCSF28%60%NegativeMYC/BCL2 rearrangementNNSD2F32DLBCL non-GCBIVB2NCerebellum, left frontal lobe (4)NN∗NA∗NANNPD3M34DLBCL non-GCBIVB3NT3-5 thoracic cord (17)NNTP53 p.W146X; STAT3 p.E616del; TET2 p.Q916X p.R1452X; CD79B p.E185X; CHD8 p.R986X; NFKBIE p.Y254Sfs∗13; BCL10 p.I46Yfs∗24,TP53 deletion. BCL6 rearrangementmCD19CART(PR) hCD22CART(PD)NPD4M48DLBCL non-GCBIVA2NPons, right thalamusNN∗NA∗NANNPD5M66DLBCL non-GCBIVB5NBilateral paraventricular, basal ganglia (4)NN∗NAMYC/BCL6/BCL2 amplificationNNPD6M43DLBCL non-GCBIVA2YLeft frontal lobe, basal gangliaNN∗NA∗NANNSD7F42DLBCL GCBIVA3NCerebellum vermis and hemispheres (41.4)NN∗NAMYC/BCL2 rearrangement. BCL6 amplificationNYESPD8F47DLBCL Non-GCBIVB3YRight frontal lobeNNMYD88 p.L265P; CD79B p.Y196C; KMT2D p.R1702X; ETV6 p.Q7Afs∗54; CCND3 p.Q280X; PIM1 p.S189Vfs∗20; CDKN2A p.A13Lfs∗13;BCL6 rearrangement. MYC/BCL2 amplificationNNPD9M40DLBCL non-GCBIVA2NCSF7.47%NTNFAIP3 p.Q74X; PRDM1 p.L48Vfs∗5; CDKN1B p.L144X; CCND3 p.D286Lfs∗72; CARD11 p.R337Q; PCLO p.Q3300X; NUDT15 p.R139CBCL6 rearrangementmCD19CART(PD) hCD22&CD19CART(PR)NPD10M41DLBCL non-GCBIVA2NCSF21.11%∗NAKMT2D p.Q3915X; CD70 p.Q47X∗NAmCD19-CART(CR)NPD11M58DLBCL non-GCBIVA3NLumbar cord (90 mm)N2.77%IRF4 p.K123RNegativeNYESPD12M64MCLIVB4NCSF16.13%20.50%Negative∗NANNPD13F19BLIVA3NBilateral occipital lobe, left frontal lobeN93.5%TP53 p.R213X, FOXO1 p.S203R, ID3 p.L40Efs∗21, TET2 p.E1151X; MYC p.A59T, CCND3 p.T283A∗NANNPD14F64DLBCL non-GCBIVB4NCerebrumNN∗NANegativemCD19CART(CR)NPD15M33DLBCL GCBIVB3NT4-6 thoracal cord63.32%NTP53 p.N131Y; TNFRSF14 p.M1V; KMT2D p.W315X; CREBBP p.Q2118Sfs∗25; DDX3X p.K13OIfs∗3; RB1 p.Y790X; PTEN p.V191Sfs∗11BCL2/BCL6 rearrangement. MYC amplification;NNPD16F35DLBCL non-GCBIVA3NCorpus callosum, right frontal lobe (20 mm)6.1%10%TP53 c.743G > A, BIRC3 p.R411K, DNMT3A p.R882C, KMT2C p.T2941NegativehCD22CART mCD19CARTYSEPD17F50DLBCL GCBIVA3NLeft occipital lobe, bilateral frontal cortex, (22 mm)18.97%NATP53 p.G245S; CD79B p.Y196S; CREBBP c.3837-2A > G; KMT2D p.A2119Lfs∗25; KMT2C p.C359Vfs∗15; ZMYM3 p.Q175Rfs∗52MYC/BCL2 rearrangement BCL6;NNPDM, male; F, female; aaIPI, age-adjusted International Prognostic Index; IPI, International Prognostic Index; PCNSL, primary central nervous system lymphoma; CNS, central nervous system; DLBCL, diffuse large B-cell lymphoma; GCB, germinal center (GC)-like B-cell type; MCL, Mantle cell lymphoma; BL, Burkitt lymphoma; CSF, cerebrospinal fluid;∗NA, not available; NGS, next generation sequencing; FISH, fluorescence in situ hybridization; tumor in CSF (%), percentage of B lymphoma cells in nuclear cells of cerebrospinal fluid; tumor in BM (%), percentage of B lymphoma cells in nuclear cells of bone marrow; CART, chimeric antigen receptor T cell; ASCT, allogeneic stem cell transplantation; PD, progressive disease; SD, stable disease.Table 2
Treatment and effect of CART cell therapy.
IDPrimary treatmentConditioning regimenLymphodepletionInfused cells (10^6/kg)CRS gradeICANS gradeNeurologic toxicityICANS treatmentCD34+CART1RCHOP × 3 (PD); isolated CNS relapse;R + HD-MTX + temozolomide + BCL2-inhibitor × 2 (SD)TEAMBendamustine5.2mCD19 (3.8)33Angulus oris convulsionMannitol, glucocorticoid, sodium valproate2R-DA-EPOCH × 4 (PR); GVD + PD-1 inhibitor × 2 (PD); isolated CNS relapse; BTKi + HD-MTX + GVD + PD-1 inhibitor × 2 (PD) systemic disease progression and CNS involvementBEAMF2.23mCD19 (1.25)10NoneMannitol3R2-CHOPE (PD); spinal cord involvement; R-MT(SD); R-CHOPE + BCL2-inhibitor (PR); HD-MTX + R-CHOPE × 4 (PD); mCD19CART (PR); hCD22CART (PD); systemic disease progression and CNS involvementBuCy——2.34hCD20 (2.06)30NoneNone4EPOCH × 6 (CR); isolated CNS relapse; HD-MTX + DEX × 2 (PR); isolated CNS relapse. HD-MTX + Idarubicin + DEX (PD); DHAP × 2 (PD); MIDD + BTKi × 6 (PD)TEAMBendamustine3.22hCD22 (5.9)20NoneNone5RCHOP × 3 (PR); RCHOP × 2 (PD); Isolated CNS relapse; MTX + BTKi + Temozolomide × 4 (CR); isolated CNS relapse (PD)TEAMF2.37hCD19 (3.3)30NoneMannitol6R + HD-MTX × 4 (PR); isolated CNS relapse; radiotherapy (PR); systemic disease progression and CNS involvement; ifosfamide + Ara-C × 1 (PD); HD-MTX × 2 (SD); TEDDi-R × 4 (PD); BTKi + BCL2-inhibitor × 4 (SD)TEAMFC2mCD19 (1.93)12ICE score 4; awakens to voiceSodium valproate7RCHOP × 3 (PR); RCHOPE × 4 (CR); ASCT (CR)R × 4 (CR); isolated CNS involvement; R + MTX + temozolomide + BTKi (PD)TEAMFC2mCD19 (2)20NoneMannitol8WBRT (CR); systemic disease progression and CNS involvement; HD-MTX + RCHOP × 3 (CR); systemic disease progression and CNS relapse; HD-MTX + RCHOP × 2 (PD)TEAMBendamustine3.23mCD19 (1.3)44Coma, seizures, hallucinationsMannitol, glucocorticoid, levetiracetam, diazepam9R-CHOPE × 6 (CR); radiation therapy (CR); systemic disease progression. RICE(PD); R2GDP (PD); RDHAP (SD); r-DA-EPOCH(PR); CD19CART (PD); BTKi + radiation (SD); RICE (SD); CD22CART + CD19CART (PR); BCL2-inhibitor + Chidamide (PD) testicular relapse + CNS involvement——————hCD20 (1.57)10NoneNone10RCHOP × 6 (CR); intraocular relapse (PD); RCHOP; radiation therapy (PD) RDHAP × 2 (PD); CD19-CART (CR) systemic disease progression and CSF involvement (PD)——F——hCD20 (0.94)10NoneMannitol, glucocorticoid11R2 + CHOP × 6 (CR); systemic disease progression; REPOCH × 6 (CR); BEAM + ASCT (CR) systemic disease progression and CNS involvement (PD); HD-MTX + DEX (PD); REPOCH (PD); RGDP (PD); MINE (PD)——FC——hCD19 (1.4)10Mannitol, glucocorticoid12RCHOP(PD); RDHAP (SD); BTKi + CHOP (SD); BTKi + DHAP (SD); BTKi + BCL2-inhibitor (PD) EPOCH (PD); GemOx × 2 (PD) systemic disease progression + CSF involvement——FC——mCD19 (1.485)10NoneNone13EPOCH × 2 (PD); decitabine + EPOCH × 2 (PD) COPADM (PD) systemic disease progression and CSF involvement——————mCD19 (0.29)34Coma, seizuresDiazepam, mannitol, glucocorticoid, plasmapheresis14RCHOP × 6 (CR); systemic disease progression; R-DICE × 6 (CRu); systemic disease progression; mCD19CART (CR); systemic disease progression and CNS involvement (PD)——FC——hCD19 (0.22)00NoneNone15RB × 6 (CR); systemic disease progression; R-CHOP (PD); REDOCH × 4 (PD); RDHAP + BCL2 inhibitor (PD)CSF involvement + systemic disease progression.——F——mCD19 (1.9)20NoneMannitol, glucocorticoid16RCHOP × 4 (PR); RCHOP × 2 (CRu); isolated CNS involvement; RCODOX-M × 2; RCDOP × 4 (CR); BEAM + ASCT (CR); CSF + CNS involvement; radiation (PD);R + MTX(PD)R + MTX + BTKi (PD); MTX + temozolomide + VP-16;CD22CART + CD19CART + BCL2-inhibitor (PD)——————hCD20 (1.0)33ICE score 2; Awakens only to tactile stimulus; dystaxiaMannitol, glucocorticoid17RCHOP × 4 (PR); REPOCH (PD); RGDP(PD); RDICE × 2 (PR); RDICE × 2 + BCL2-inhibitor (PD) + BTKi + GemOx(PD); Radiation therapy + Chidamide + lenalidomide (PD); systemic disease progression and CNS involvement (PD)——F——mCD19 (0.26)44Coma; seizuresMannitol, Glucocorticoid, Diazepam, Sodium valproateCRS, cytokine-release syndrome; ICANS, immune effector cells associated neurologic toxicity syndrome; CHOP, cyclophosphamide, doxorubicin, vincristine, dexamethasone; HD-MTX, high-dose methotrexate; DA-EPOCH, dose adjusted etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin; GVD, gemcitabine, vinorelbine, liposomal adriamycin; CHOPE, cyclophosphamide, doxorubicin, vincristine, dexamethasone, etoposide; DEX, dexamethasone; DHAP, dexamethasone, cytarabine, cisplatin; MIDD, methotrexate, ifosfamide, liposomal Adriamycin, dexamethasone; TEDDi, temozolomide, etoposide, liposomal adriamycin, dexamethasone, intrathecal injection(Ara-C); R2, rituximab, lenalidomide; ASCT, autologous stem cell transplant; WBRT, whole brain irradiation treatment; ICE, ifosfamide, carboplatin, etoposide; DICE, dexamethasone, ifosfamide, carboplatin, etoposide; MINE, mitoxantrone, ifosfamide, etoposide; GDP, gemcitabine, dexamethasone, cisplatin; COPADM, vincristine, high-dose methotrexate, doxorubicin, cyclophosphamide, prednisone; RB, rituximab, bendamustine; GemOx; gemcitabine, oxaliplatin; CODOX-M, cyclophosphamide, vincristine, doxorubicin, methotrexate; TEAM, thiotepa, etoposide, cytarabine, melphalan; BEAM, carmustine, etoposide, cytarabine, melphalan; BuCy, busulfan, cyclophosphamide;F, Fludarabine; FC, Fludarabine, cyclophosphamide; BTKi, Bruton’s tyrosine kinase inhibitor; PD-1 inhibitor, programmed death-1 inhibitor; CNS, central nervous system.
### 3.2. CART Transfusion and Dynamics
Among 17 patients, depending on the antigen expression of tumor tissue, 12 underwent CD19 CART cells (including 9 with murine-CD19 and 3 with humanized-CD19), with the median number of CART cells infusion of 1.44×106 cells/kg (rang of 0.22×106 cells/kg to 3.8×106 cells/kg); 4 underwent hCD20 CART cells, with a median number of CART cells infusion of 1.29×106 cells/kg (range of 0.94 × 106 to 2.06 × 106); and 1 underwent hCD22 CART cells, with infusion of 5.9×106 cells/kg. The median peak number of CAR T-cell expansion was 163×106 cells/L (range of 2.32 × 106–920 × 106) and achieved a peak with a median time of 9 days (range of 6 to 67) after CART transfusion, and the median lasting time of CART in peripheral blood was 31 days (range of 11 to 105). Three patients were infused with CART cells with a dose <0.5×106 cells/kg because they had substantial disease burden. Patient No. 13 with Burkitt lymphoma treated by mCD19CART had abdominal bulky mass (13.3 cm × 9.1 cm × 13 cm) and brain parenchyma involvement, with infusion dose of 0.29×106 cells/kg and peak number of 501 × 106/L on +11 days and lasting for 33 days. Patient No. 14 treated by hCD19CART had abdominal bulky mass (8.7 cm × 7 cm) and brain parenchyma involvement, with infusion dose of 0.22×106 cells/kg and peak number of 2.32 × 106/L on +60 days and lasting for 105 days; and Patient No. 17 treated by mCD19CART had breast bulky mass (11 cm × 8.3 cm × 3.2 cm) and both brain parenchyma and CSF involvement, with infusion dose of 0.26×106 cells/kg and peak number of 920 × 106/L on +14 days and lasting for 53 days.Out of 17 patients, lumbar puncture and CART cells in the CSF detection were performed in eight patients at the first month (Figure3). CART cell trafficking into the CSF was noted in patient 1 when the number of CART cells in the PB was 92.6 × 106 cells/L. While cells were not detected in the remaining 7 patients, the number of CART cells in PB dropped below the limit of detecting at that time.Figure 3
Dynamic changes of CART cells in peripheral blood and partial in cerebrospinal fluid after CART cell treatment. (a) Expansion and persistence of CART cells in peripheral blood were quantified by flow cytometry. (b) Percentage of CAR T-cells in lymphocytes(%) in peripheral blood and cerebrospinal fluid after CART cell therapy. (c) Detection of CART cells in the cerebrospinal fluid of patient No. 1 on day +30 by flow cytometry after infusion.
(a)(b)(c)The median number of CART infusion was 3.48×106 cells/kg (range of 1.25 × 106 to 5.9 × 106) vs. 0.94 × 106 cells/kg (range of 0.22 × 106 to 1.9 × 106) (p=0.02), the median peak number of CART was 250.2 × 106/L (range of 12.3 × 106 to 784 × 106) vs. 29.4 × 106/L (range of 2.32 × 106 to 960 × 106) (p=0.054), the median time to peak expansion was 7 days (range of 7 to 15) vs. 12 days (range of 6 to 68) (p=0.16), and median lasting time of CART was 47.5 days (range of 11 to 112) and 33 days (range of 12 to 105) (p=0.88) in the ASCT group and non-ASCT group, respectively.
### 3.3. Efficacy Assessment and Survival Analysis
Sixteen patients received bridging chemotherapy with the R-MA (4/16) and TEDDI (12/16) regimens to reduce the tumor burden prior to CART cell transfusion. At the time of infusion, all patients with CSF involvement had negative CSF by FCM, the symptoms and signs were managed, and the disease status was PD (n = 8), PR (n = 7), and CR (n = 2). 8 (8/17) patients underwent ASCT plus CART, and 9 (9/17) patients received CAR T-cell alone therapy, including 4 patients with single CART administration and 5 patients with short-interval sequential CD19/CD20/CD22CART treatment (within 3 months). The conditioning regimen before ASCT plus CART included the TEAM (75%) and non-TEAM (25%) regimens, and the median dose of CD34 cell transfusion was 2.35 × 106/kg (range of 2 × 106 to 5.2 × 106). It was bendamustine (3/17) or fludarabine (5/17) monotherapy or in combination with cyclophosphamide (5/17) that was performed for lymphodepletion. Still, 4 patients (Patient No. 3, Patient No. 9, Patient No. 13, and Patient No. 16) did not undergo lymphocyte clearing because the absolute lymphocyte count was <0.2 × 109/L. Taking the date of CART transfusion as day 0, ASCT was performed on day -1 in 5 patients, day -30 in 1 patient, and day -60 in 2 patients.According to the three-month assessment after CART cell infusion, responses were observed in 12(12/17) patients and consisted of 11 CRs and 1 partial remission. One (1/17) patient with Burkitt lymphoma had a progressive disease with systemic and CSN involvement. Four (4/17) patients had progressive diseases with only systemic relapse, two of whom had a p53 gene mutation positive. Further analysis, the CRR was significantly higher in the ASCT group than in the non-ASCT group (100% vs. 44%,p<0.01).By September 30, 2021, with a median follow-up of 20.7 months (range of 6 to 24.5), 8 (8/17) patients had achieved sustained remission. The median progression-free survival (PFS) of these challenging patients was 16.3 months (range of 2.6 to24.5 months). The eight patients with durable remission included seven patients treated by ASCT plus CART cells and one patient by CART cells alone (Figures4 and 5). Disease progression occurred in the remaining 9 patients (1 in the ASCT group and 8 in the non-ASCT group), and the median time of progression of the 9 patients was 4.8 months (range of 2.6 to 16.3). For the 9 PD patients, 8 patients (1 in the ASCT group and 7 in the non-ASCT group) died, including 7 who died of disease progression and one (patient No. 9) who received allogeneic hematopoietic stem cell transplantation in the following treatment died of infection by CMV pneumonia. The median overall survival (OS) was 19.3 months (range of 6 to 24.5). Kaplan-Meier survival analysis showed that patients who underwent ASCT plus CART cells had longer PFS (P<0.01) and OS (P<0.01) (Figure 4). The median PFS and median OS in the ASCT group were not reached, while in the non-ASCT is 4.8 months (range of 2.6 to 16.3) and 13.5 months (range of 6 to 19.3).Figure 4
Therapeutic effect of CART treatment and duration of response, progression-free survival (PFS), and overall survival (OS) estimates. (a, b) Kaplan-Meier estimates of progression-free survival and overall survival. (c) Swimmer’s plot of response for all patients on study (n = 17). Different colors represent the disease status. CR, complete remission; PR, partial remission; SD, stable disease; PD, progressive disease. Day 0 shows CAR T-cells infusion. ASCT, autologous stem cell transplantation; PFS, progression-free survival; OS, overall survival.
(a)(b)(c)Figure 5
Pretreatment and post-treatment imaging. Representative MRI imaging before (left) and after (right) therapy (a). The main central invasion sites of patient No.7 are cerebellum vermis and hemispheres. Invasion sites of patient No.16 are corpus callosum and right frontal lobe. The central invasion sites of patient 17 are left occipital lobe and bilateral frontal cortex. The images of patient No. 2 and patient No 3 by PET/CT (b). MRI, magnetic resonance imaging; PET/CT, positron emission computed tomography.
(a)(b)Especially, further analysis of 9 patients who only received CART therapy showed that the median PFS and median OS of 5 patients with sequential different targeted CAR T-cell therapy were 4.8 months (range of 2.6 to 7.7) and 9.9 months (range of 6 to 17), and that of 4 patients who did undergo single targeted CAR T-cell infusion were 10.15 months (range of 3.1 to 16.3) and 15.9 months (range of 9.9 to19.3). For the three patients with double-hit lymphoma, two received ASCT plus CART treatment are in ongoing complete remission, while one with short-interval (within 3 months) sequential infusion of anti-CD19 and anti-CD20CART-cell died in 6 months after enrollment. For these 5 (5/11) patients with P53 gene mutation positive, the prognosis was worse (3 PDs, 1 PR, and 1CR) in three-month assessment after CART infusion, and by September 30, 2021, 3 died of progression diseases and the median OS is 10 months (range of 6 to 16). However, the one treated by ASCT plus CART was in durable remission. We did not find that the other gene mutations such as CD79b\KMT2D have a relationship with the prognosis due to the fewer number of cases.
### 3.4. Toxic Effects
ICANS is the most concerning toxic effect of immunotherapy in r/r CNS lymphoma. In the 17 patients, 6 (35%) patients experienced ICANS, including grade 2 (n = 1), grade 3 (n = 2), and grade 4 (n = 3), and the median time of ICANS occurrence was 6 days (range of 1 to 8) after CART transfusion. The manifestations observed in patients were the following: headache, nausea, and vomiting in 5 patients (5/17), with a median onset of 7 days (range of 2 to 8) after CART; ataxia in 1 patient (1/17), where onset time was 3 days after CART; convulsion in 4 patients (4/17), where the median time of occurrence was 7.5 days (range of 5 to 23) after CART; coma in 3 patients (3/17), where the median time of occurrence was 8 days (range of 7 to 8) after CART; somnolence in 5 patients (5/17), where the median time of occurrence was 8 days (range of 3 to 8) after CART; and visual abnormalities in 2 patients (2/17), where the time of occurrence was 3 and 5 days after CART, respectively. After the intervention, the median duration of ICANS was 4.5 days (range of 3 to 23). The rate of ≥grade 3 ICANS was 29% (5/17). 3 patients developed grade 4 ICANS. Patient No. 8, who had previously underwent whole brain radiotherapy, had fever on d0 after CART cell transfusion. On d5, he suffered from neurological toxicity, which is manifested as hallucination, visual abnormality, somnolence, disorientation, and anomia; and on d24 after a CART transfusion, this patient was in a coma. DEX, mannitol, diazepam, and phenobarbital, which were initiated on d8, were administered for treatment, and the patient completely recovered on d40. Patient No. 17, who previously underwent radiotherapy for breast lymphoma, had a high fever that occurred on d2 after a CART cell transfusion and lasted for 5 days. The patient had neurological toxicity on day 7, and the manifestations included delirium and grand mal epilepsy. After treatment with mannitol, DEX, diazepam, and phenobarbital, the patient completely recovered on d28 after a CART cell transfusion. Patient No. 13, who had Burkitt lymphoma with bone marrow involvement, had a fever that occurred on d0 after CART transfusion and progressed to a high fever on d5, lasting for 4 days. Neurological toxicity occurred on d8, and the manifestations included convulsion of the limbs, urinary incontinence, and coma. After treatment with mannitol, DEX, sodium valproate, and diazepam, the patient completely recovered on day 12 after the CART cell transfusion. All severe ICANS in patients were alleviated, and neurotoxicity-related symptoms were reversible. No treatment-related deaths occurred in this study.CRS is another common adverse reaction to CART cell immunotherapy. It occurred in 16 patients (94%), and the median time of CRS occurrence was 1 day (range of 1 to 8) after CART transfusion. The major manifestations included the following: pyrexia in 16 patients (94%), with the median time of occurrence of 1 day (range of 1to8) after CART transfusion; hypotension in 8 patients (8/17), where the median time of occurrence was 3 days (range of 2 to 9) after CART transfusion; hypoxia in 9 patients (9/17), where the median time of occurrence was 5 days (range of 2 to 15) after CART transfusion; and generalized edema in 6 patients (6/17), where the median time of occurrence was 3 days (range of 2 to 8) after CART transfusion (Figures 6(b)). The median duration of CRS was 10 days (range of 4 to 29) after CART transfusion when corresponding interventions were performed. Grade 3 or higher CRS was observed in 7 (41%) patients, three of whom (patient No. 8, patient No. 16, and patient No. 17) received radiotherapy; three of whom (patient No. 1, patient No. 13, and patient No. 17) had bone marrow involvement; and four of whom (patient No. 1, patient No. 3, patient No. 5, and patient No. 8) had underwent ASCT + CART. Specifically, the incidence of ≥grade 3 CRS was 50% and 33% (p=0.48) and of ≥grade 3 ICANS was 25% and 33% (p=0.14) in the ASCT and non-ASCT groups, respectively.Figure 6
Adverse events associated with CART treatment. (a, b) Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). (a) The grade of cytokine release syndrome- and immune effector cells-associated neurologic toxicity in all patients, and the horizontal line indicates the median. (b) The rate of each symptom of CRS and ICANS in all patients. (c) There are no differences in complications between the ASCT plus CART group and CART alone. (d) Severe ICANS (≥grade 3) has association with IL-6, IFN-γ, and ferritin. Severe CRS (≥grade 3) was related with IL-6 and ferritin.
(a)(b)(c)(d)The common adverse events in the treatment period included agranulocytosis (17/17), infection (15/17), hypogammaglobulinemia (17/17), hepatic dysfunction (12/17), abnormal renal function (2/17), and gastrointestinal hemorrhage (3/17) (Figure6). None of the patients received supportive therapy with growth factors. High-intensity conditioning in the ASCT group did not significantly increase the duration of agranulocytosis (13.38 ± 5.85 days vs. 15.78 ± 6.63 days, p=0.65). The time of neutrophil cell engraftment was 11 days (range of 10 to 30), and platelet engraftment was 12 days (range of 10 to 14) in patients who underwent ASCT plus CART cells, which was consistent with previous findings [42–44]. These results indicated that CART cells did not influence the engraftment of hematopoietic stem cells.The changes in cytokines (IL6, TNFα, IL10, sCD25, and IFN-γ) and ferritin are shown in Figure 7. The median peak time was 7 days (range of 0 to 14), 7 days (range of 0–14), 7 days (range of 0–30), 7 days (range of 0–14), and 7 days (range of 0 to 30) after CART-cell transfusion, respectively. The median levels of IL-6 and ferritin were 76.15 ng/ml (range of 6.67 to 19540) and 2037.25 ng/ml (range of 172.8 to 26143.9), respectively. The severity of ICANS was positively correlated with IL-6 and ferritin levels (Figure 6).Figure 7
Changes of indicators during CART cell therapy. (a–f) IL-6, IL-10, TNFα, IFN-γ, ferritin, and sCD25 levels of the 17 patients during CART cell therapy. The day of first CAR T-cells infusion was day 0.
(a)(b)(c)(d)(e)(f)
## 3.1. Clinical Characteristics
Baseline patient characteristics listed in Table1 indicate that 17 CNS involvement patients, with a median age of 42 years (range of 19 to 66), comprised 9 (53%) males and 8 (47%) females. 15 (88%) patients had secondary CNS B-cell lymphoma (mantle cell lymphoma, n = 1; Burkitt lymphoma, n = 1; diffuse large B-cell lymphoma non-GCB, n = 9; and diffuse large B-cell lymphoma GCB, n = 4), and 2 (12%) had primary central nervous system B-cell lymphoma. All the patients were diagnosed with Ann Arbor stage IV. For 14 patients aged <60 years, the age-adjusted international prognostic index (aaIPI) ≥3 was 8, and for 3 patients aged ≥60 years, the international prognostic index (IPI) was 5, 4, and 4, respectively. Clinical symptoms and signs at the time of enrollment included headache 65% (11/17); blurred vision and diplopia 12% (2/17); nausea and vomiting 18% (3/17); convulsion 6% (1/17); waist pain, lower limb numbness, and reduced muscle strength 24% (4/17); hearing loss 12% (2/17); and distortion of the commissure 12% (2/17). The Eastern Cooperative Oncology Group performance status score ranged from 2 to 4 points. FISH assays for MYC/BCL2/BCL6 in tumor tissues were performed in 11 (65%) patients. Two of them also received P53 measurements (Table 1). The abnormal factors involved MYC/BCL2/BCL6 rearrangement and/or amplification and P53 deletion. Among them, 3 (patient No.1, patient No.7, and patient No.17) were diagnosed double hit lymphoma and one (patient No.3) had P53 deletion. Next-generation sequencing for gene mutation in tumor tissues was performed in 11 patients, and 9 patients had gene mutations positive, including TP53 (5/11), KMT2D (4/11), CD79b (3/11), CCND3 (3/11), CREBBP (2/11), TET2 (2/11), and MYD88 (1/11), as shown in Table 1. A total of 17 patients received ≥2 lines of antineoplastic therapies, and the median number of prior therapies was 11 (range of 5 to 18), as shown in Table 2. In 17 patients, 7 (7/17) were insensitive to chemotherapy and refractory, while the remaining 10 (10/17) patients had relapsed after first-line/second-line therapy, especially in combination with targeted drug therapy (BTKi, n = 9; BCL2 inhibitor, n = 8; and programmed death-1 inhibitor, n = 1). 3 (3/17) patients had progressed after ASCT, 5 (5/17) relapsed after CART therapy, and 6 (6/17) patients had a history of partial radiotherapy. At the time of enrollment, 5 (5/17) patients had isolated central nervous system involvement, and 12 (12/17) had systemic disease progression in addition to central nervous system involvement. Before the initiation of therapy, the disease status was progressive disease (PD) in 15 (15/17) patients and stable disease (SD) in 2 (2/17).Table 1
Clinical characteristics of patients.
IDSexAgeDisease pathologyStageaaIPI/IPIPCNSLSite of CNS disease maximal dimension (mm)Tumor in CSF (%)Tumor in BM (%)NGSFISHPrevious CART therapyPrevious ASCT therapyDisease status1F39DLBCL GCBIVB2NCSF28%60%NegativeMYC/BCL2 rearrangementNNSD2F32DLBCL non-GCBIVB2NCerebellum, left frontal lobe (4)NN∗NA∗NANNPD3M34DLBCL non-GCBIVB3NT3-5 thoracic cord (17)NNTP53 p.W146X; STAT3 p.E616del; TET2 p.Q916X p.R1452X; CD79B p.E185X; CHD8 p.R986X; NFKBIE p.Y254Sfs∗13; BCL10 p.I46Yfs∗24,TP53 deletion. BCL6 rearrangementmCD19CART(PR) hCD22CART(PD)NPD4M48DLBCL non-GCBIVA2NPons, right thalamusNN∗NA∗NANNPD5M66DLBCL non-GCBIVB5NBilateral paraventricular, basal ganglia (4)NN∗NAMYC/BCL6/BCL2 amplificationNNPD6M43DLBCL non-GCBIVA2YLeft frontal lobe, basal gangliaNN∗NA∗NANNSD7F42DLBCL GCBIVA3NCerebellum vermis and hemispheres (41.4)NN∗NAMYC/BCL2 rearrangement. BCL6 amplificationNYESPD8F47DLBCL Non-GCBIVB3YRight frontal lobeNNMYD88 p.L265P; CD79B p.Y196C; KMT2D p.R1702X; ETV6 p.Q7Afs∗54; CCND3 p.Q280X; PIM1 p.S189Vfs∗20; CDKN2A p.A13Lfs∗13;BCL6 rearrangement. MYC/BCL2 amplificationNNPD9M40DLBCL non-GCBIVA2NCSF7.47%NTNFAIP3 p.Q74X; PRDM1 p.L48Vfs∗5; CDKN1B p.L144X; CCND3 p.D286Lfs∗72; CARD11 p.R337Q; PCLO p.Q3300X; NUDT15 p.R139CBCL6 rearrangementmCD19CART(PD) hCD22&CD19CART(PR)NPD10M41DLBCL non-GCBIVA2NCSF21.11%∗NAKMT2D p.Q3915X; CD70 p.Q47X∗NAmCD19-CART(CR)NPD11M58DLBCL non-GCBIVA3NLumbar cord (90 mm)N2.77%IRF4 p.K123RNegativeNYESPD12M64MCLIVB4NCSF16.13%20.50%Negative∗NANNPD13F19BLIVA3NBilateral occipital lobe, left frontal lobeN93.5%TP53 p.R213X, FOXO1 p.S203R, ID3 p.L40Efs∗21, TET2 p.E1151X; MYC p.A59T, CCND3 p.T283A∗NANNPD14F64DLBCL non-GCBIVB4NCerebrumNN∗NANegativemCD19CART(CR)NPD15M33DLBCL GCBIVB3NT4-6 thoracal cord63.32%NTP53 p.N131Y; TNFRSF14 p.M1V; KMT2D p.W315X; CREBBP p.Q2118Sfs∗25; DDX3X p.K13OIfs∗3; RB1 p.Y790X; PTEN p.V191Sfs∗11BCL2/BCL6 rearrangement. MYC amplification;NNPD16F35DLBCL non-GCBIVA3NCorpus callosum, right frontal lobe (20 mm)6.1%10%TP53 c.743G > A, BIRC3 p.R411K, DNMT3A p.R882C, KMT2C p.T2941NegativehCD22CART mCD19CARTYSEPD17F50DLBCL GCBIVA3NLeft occipital lobe, bilateral frontal cortex, (22 mm)18.97%NATP53 p.G245S; CD79B p.Y196S; CREBBP c.3837-2A > G; KMT2D p.A2119Lfs∗25; KMT2C p.C359Vfs∗15; ZMYM3 p.Q175Rfs∗52MYC/BCL2 rearrangement BCL6;NNPDM, male; F, female; aaIPI, age-adjusted International Prognostic Index; IPI, International Prognostic Index; PCNSL, primary central nervous system lymphoma; CNS, central nervous system; DLBCL, diffuse large B-cell lymphoma; GCB, germinal center (GC)-like B-cell type; MCL, Mantle cell lymphoma; BL, Burkitt lymphoma; CSF, cerebrospinal fluid;∗NA, not available; NGS, next generation sequencing; FISH, fluorescence in situ hybridization; tumor in CSF (%), percentage of B lymphoma cells in nuclear cells of cerebrospinal fluid; tumor in BM (%), percentage of B lymphoma cells in nuclear cells of bone marrow; CART, chimeric antigen receptor T cell; ASCT, allogeneic stem cell transplantation; PD, progressive disease; SD, stable disease.Table 2
Treatment and effect of CART cell therapy.
IDPrimary treatmentConditioning regimenLymphodepletionInfused cells (10^6/kg)CRS gradeICANS gradeNeurologic toxicityICANS treatmentCD34+CART1RCHOP × 3 (PD); isolated CNS relapse;R + HD-MTX + temozolomide + BCL2-inhibitor × 2 (SD)TEAMBendamustine5.2mCD19 (3.8)33Angulus oris convulsionMannitol, glucocorticoid, sodium valproate2R-DA-EPOCH × 4 (PR); GVD + PD-1 inhibitor × 2 (PD); isolated CNS relapse; BTKi + HD-MTX + GVD + PD-1 inhibitor × 2 (PD) systemic disease progression and CNS involvementBEAMF2.23mCD19 (1.25)10NoneMannitol3R2-CHOPE (PD); spinal cord involvement; R-MT(SD); R-CHOPE + BCL2-inhibitor (PR); HD-MTX + R-CHOPE × 4 (PD); mCD19CART (PR); hCD22CART (PD); systemic disease progression and CNS involvementBuCy——2.34hCD20 (2.06)30NoneNone4EPOCH × 6 (CR); isolated CNS relapse; HD-MTX + DEX × 2 (PR); isolated CNS relapse. HD-MTX + Idarubicin + DEX (PD); DHAP × 2 (PD); MIDD + BTKi × 6 (PD)TEAMBendamustine3.22hCD22 (5.9)20NoneNone5RCHOP × 3 (PR); RCHOP × 2 (PD); Isolated CNS relapse; MTX + BTKi + Temozolomide × 4 (CR); isolated CNS relapse (PD)TEAMF2.37hCD19 (3.3)30NoneMannitol6R + HD-MTX × 4 (PR); isolated CNS relapse; radiotherapy (PR); systemic disease progression and CNS involvement; ifosfamide + Ara-C × 1 (PD); HD-MTX × 2 (SD); TEDDi-R × 4 (PD); BTKi + BCL2-inhibitor × 4 (SD)TEAMFC2mCD19 (1.93)12ICE score 4; awakens to voiceSodium valproate7RCHOP × 3 (PR); RCHOPE × 4 (CR); ASCT (CR)R × 4 (CR); isolated CNS involvement; R + MTX + temozolomide + BTKi (PD)TEAMFC2mCD19 (2)20NoneMannitol8WBRT (CR); systemic disease progression and CNS involvement; HD-MTX + RCHOP × 3 (CR); systemic disease progression and CNS relapse; HD-MTX + RCHOP × 2 (PD)TEAMBendamustine3.23mCD19 (1.3)44Coma, seizures, hallucinationsMannitol, glucocorticoid, levetiracetam, diazepam9R-CHOPE × 6 (CR); radiation therapy (CR); systemic disease progression. RICE(PD); R2GDP (PD); RDHAP (SD); r-DA-EPOCH(PR); CD19CART (PD); BTKi + radiation (SD); RICE (SD); CD22CART + CD19CART (PR); BCL2-inhibitor + Chidamide (PD) testicular relapse + CNS involvement——————hCD20 (1.57)10NoneNone10RCHOP × 6 (CR); intraocular relapse (PD); RCHOP; radiation therapy (PD) RDHAP × 2 (PD); CD19-CART (CR) systemic disease progression and CSF involvement (PD)——F——hCD20 (0.94)10NoneMannitol, glucocorticoid11R2 + CHOP × 6 (CR); systemic disease progression; REPOCH × 6 (CR); BEAM + ASCT (CR) systemic disease progression and CNS involvement (PD); HD-MTX + DEX (PD); REPOCH (PD); RGDP (PD); MINE (PD)——FC——hCD19 (1.4)10Mannitol, glucocorticoid12RCHOP(PD); RDHAP (SD); BTKi + CHOP (SD); BTKi + DHAP (SD); BTKi + BCL2-inhibitor (PD) EPOCH (PD); GemOx × 2 (PD) systemic disease progression + CSF involvement——FC——mCD19 (1.485)10NoneNone13EPOCH × 2 (PD); decitabine + EPOCH × 2 (PD) COPADM (PD) systemic disease progression and CSF involvement——————mCD19 (0.29)34Coma, seizuresDiazepam, mannitol, glucocorticoid, plasmapheresis14RCHOP × 6 (CR); systemic disease progression; R-DICE × 6 (CRu); systemic disease progression; mCD19CART (CR); systemic disease progression and CNS involvement (PD)——FC——hCD19 (0.22)00NoneNone15RB × 6 (CR); systemic disease progression; R-CHOP (PD); REDOCH × 4 (PD); RDHAP + BCL2 inhibitor (PD)CSF involvement + systemic disease progression.——F——mCD19 (1.9)20NoneMannitol, glucocorticoid16RCHOP × 4 (PR); RCHOP × 2 (CRu); isolated CNS involvement; RCODOX-M × 2; RCDOP × 4 (CR); BEAM + ASCT (CR); CSF + CNS involvement; radiation (PD);R + MTX(PD)R + MTX + BTKi (PD); MTX + temozolomide + VP-16;CD22CART + CD19CART + BCL2-inhibitor (PD)——————hCD20 (1.0)33ICE score 2; Awakens only to tactile stimulus; dystaxiaMannitol, glucocorticoid17RCHOP × 4 (PR); REPOCH (PD); RGDP(PD); RDICE × 2 (PR); RDICE × 2 + BCL2-inhibitor (PD) + BTKi + GemOx(PD); Radiation therapy + Chidamide + lenalidomide (PD); systemic disease progression and CNS involvement (PD)——F——mCD19 (0.26)44Coma; seizuresMannitol, Glucocorticoid, Diazepam, Sodium valproateCRS, cytokine-release syndrome; ICANS, immune effector cells associated neurologic toxicity syndrome; CHOP, cyclophosphamide, doxorubicin, vincristine, dexamethasone; HD-MTX, high-dose methotrexate; DA-EPOCH, dose adjusted etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin; GVD, gemcitabine, vinorelbine, liposomal adriamycin; CHOPE, cyclophosphamide, doxorubicin, vincristine, dexamethasone, etoposide; DEX, dexamethasone; DHAP, dexamethasone, cytarabine, cisplatin; MIDD, methotrexate, ifosfamide, liposomal Adriamycin, dexamethasone; TEDDi, temozolomide, etoposide, liposomal adriamycin, dexamethasone, intrathecal injection(Ara-C); R2, rituximab, lenalidomide; ASCT, autologous stem cell transplant; WBRT, whole brain irradiation treatment; ICE, ifosfamide, carboplatin, etoposide; DICE, dexamethasone, ifosfamide, carboplatin, etoposide; MINE, mitoxantrone, ifosfamide, etoposide; GDP, gemcitabine, dexamethasone, cisplatin; COPADM, vincristine, high-dose methotrexate, doxorubicin, cyclophosphamide, prednisone; RB, rituximab, bendamustine; GemOx; gemcitabine, oxaliplatin; CODOX-M, cyclophosphamide, vincristine, doxorubicin, methotrexate; TEAM, thiotepa, etoposide, cytarabine, melphalan; BEAM, carmustine, etoposide, cytarabine, melphalan; BuCy, busulfan, cyclophosphamide;F, Fludarabine; FC, Fludarabine, cyclophosphamide; BTKi, Bruton’s tyrosine kinase inhibitor; PD-1 inhibitor, programmed death-1 inhibitor; CNS, central nervous system.
## 3.2. CART Transfusion and Dynamics
Among 17 patients, depending on the antigen expression of tumor tissue, 12 underwent CD19 CART cells (including 9 with murine-CD19 and 3 with humanized-CD19), with the median number of CART cells infusion of 1.44×106 cells/kg (rang of 0.22×106 cells/kg to 3.8×106 cells/kg); 4 underwent hCD20 CART cells, with a median number of CART cells infusion of 1.29×106 cells/kg (range of 0.94 × 106 to 2.06 × 106); and 1 underwent hCD22 CART cells, with infusion of 5.9×106 cells/kg. The median peak number of CAR T-cell expansion was 163×106 cells/L (range of 2.32 × 106–920 × 106) and achieved a peak with a median time of 9 days (range of 6 to 67) after CART transfusion, and the median lasting time of CART in peripheral blood was 31 days (range of 11 to 105). Three patients were infused with CART cells with a dose <0.5×106 cells/kg because they had substantial disease burden. Patient No. 13 with Burkitt lymphoma treated by mCD19CART had abdominal bulky mass (13.3 cm × 9.1 cm × 13 cm) and brain parenchyma involvement, with infusion dose of 0.29×106 cells/kg and peak number of 501 × 106/L on +11 days and lasting for 33 days. Patient No. 14 treated by hCD19CART had abdominal bulky mass (8.7 cm × 7 cm) and brain parenchyma involvement, with infusion dose of 0.22×106 cells/kg and peak number of 2.32 × 106/L on +60 days and lasting for 105 days; and Patient No. 17 treated by mCD19CART had breast bulky mass (11 cm × 8.3 cm × 3.2 cm) and both brain parenchyma and CSF involvement, with infusion dose of 0.26×106 cells/kg and peak number of 920 × 106/L on +14 days and lasting for 53 days.Out of 17 patients, lumbar puncture and CART cells in the CSF detection were performed in eight patients at the first month (Figure3). CART cell trafficking into the CSF was noted in patient 1 when the number of CART cells in the PB was 92.6 × 106 cells/L. While cells were not detected in the remaining 7 patients, the number of CART cells in PB dropped below the limit of detecting at that time.Figure 3
Dynamic changes of CART cells in peripheral blood and partial in cerebrospinal fluid after CART cell treatment. (a) Expansion and persistence of CART cells in peripheral blood were quantified by flow cytometry. (b) Percentage of CAR T-cells in lymphocytes(%) in peripheral blood and cerebrospinal fluid after CART cell therapy. (c) Detection of CART cells in the cerebrospinal fluid of patient No. 1 on day +30 by flow cytometry after infusion.
(a)(b)(c)The median number of CART infusion was 3.48×106 cells/kg (range of 1.25 × 106 to 5.9 × 106) vs. 0.94 × 106 cells/kg (range of 0.22 × 106 to 1.9 × 106) (p=0.02), the median peak number of CART was 250.2 × 106/L (range of 12.3 × 106 to 784 × 106) vs. 29.4 × 106/L (range of 2.32 × 106 to 960 × 106) (p=0.054), the median time to peak expansion was 7 days (range of 7 to 15) vs. 12 days (range of 6 to 68) (p=0.16), and median lasting time of CART was 47.5 days (range of 11 to 112) and 33 days (range of 12 to 105) (p=0.88) in the ASCT group and non-ASCT group, respectively.
## 3.3. Efficacy Assessment and Survival Analysis
Sixteen patients received bridging chemotherapy with the R-MA (4/16) and TEDDI (12/16) regimens to reduce the tumor burden prior to CART cell transfusion. At the time of infusion, all patients with CSF involvement had negative CSF by FCM, the symptoms and signs were managed, and the disease status was PD (n = 8), PR (n = 7), and CR (n = 2). 8 (8/17) patients underwent ASCT plus CART, and 9 (9/17) patients received CAR T-cell alone therapy, including 4 patients with single CART administration and 5 patients with short-interval sequential CD19/CD20/CD22CART treatment (within 3 months). The conditioning regimen before ASCT plus CART included the TEAM (75%) and non-TEAM (25%) regimens, and the median dose of CD34 cell transfusion was 2.35 × 106/kg (range of 2 × 106 to 5.2 × 106). It was bendamustine (3/17) or fludarabine (5/17) monotherapy or in combination with cyclophosphamide (5/17) that was performed for lymphodepletion. Still, 4 patients (Patient No. 3, Patient No. 9, Patient No. 13, and Patient No. 16) did not undergo lymphocyte clearing because the absolute lymphocyte count was <0.2 × 109/L. Taking the date of CART transfusion as day 0, ASCT was performed on day -1 in 5 patients, day -30 in 1 patient, and day -60 in 2 patients.According to the three-month assessment after CART cell infusion, responses were observed in 12(12/17) patients and consisted of 11 CRs and 1 partial remission. One (1/17) patient with Burkitt lymphoma had a progressive disease with systemic and CSN involvement. Four (4/17) patients had progressive diseases with only systemic relapse, two of whom had a p53 gene mutation positive. Further analysis, the CRR was significantly higher in the ASCT group than in the non-ASCT group (100% vs. 44%,p<0.01).By September 30, 2021, with a median follow-up of 20.7 months (range of 6 to 24.5), 8 (8/17) patients had achieved sustained remission. The median progression-free survival (PFS) of these challenging patients was 16.3 months (range of 2.6 to24.5 months). The eight patients with durable remission included seven patients treated by ASCT plus CART cells and one patient by CART cells alone (Figures4 and 5). Disease progression occurred in the remaining 9 patients (1 in the ASCT group and 8 in the non-ASCT group), and the median time of progression of the 9 patients was 4.8 months (range of 2.6 to 16.3). For the 9 PD patients, 8 patients (1 in the ASCT group and 7 in the non-ASCT group) died, including 7 who died of disease progression and one (patient No. 9) who received allogeneic hematopoietic stem cell transplantation in the following treatment died of infection by CMV pneumonia. The median overall survival (OS) was 19.3 months (range of 6 to 24.5). Kaplan-Meier survival analysis showed that patients who underwent ASCT plus CART cells had longer PFS (P<0.01) and OS (P<0.01) (Figure 4). The median PFS and median OS in the ASCT group were not reached, while in the non-ASCT is 4.8 months (range of 2.6 to 16.3) and 13.5 months (range of 6 to 19.3).Figure 4
Therapeutic effect of CART treatment and duration of response, progression-free survival (PFS), and overall survival (OS) estimates. (a, b) Kaplan-Meier estimates of progression-free survival and overall survival. (c) Swimmer’s plot of response for all patients on study (n = 17). Different colors represent the disease status. CR, complete remission; PR, partial remission; SD, stable disease; PD, progressive disease. Day 0 shows CAR T-cells infusion. ASCT, autologous stem cell transplantation; PFS, progression-free survival; OS, overall survival.
(a)(b)(c)Figure 5
Pretreatment and post-treatment imaging. Representative MRI imaging before (left) and after (right) therapy (a). The main central invasion sites of patient No.7 are cerebellum vermis and hemispheres. Invasion sites of patient No.16 are corpus callosum and right frontal lobe. The central invasion sites of patient 17 are left occipital lobe and bilateral frontal cortex. The images of patient No. 2 and patient No 3 by PET/CT (b). MRI, magnetic resonance imaging; PET/CT, positron emission computed tomography.
(a)(b)Especially, further analysis of 9 patients who only received CART therapy showed that the median PFS and median OS of 5 patients with sequential different targeted CAR T-cell therapy were 4.8 months (range of 2.6 to 7.7) and 9.9 months (range of 6 to 17), and that of 4 patients who did undergo single targeted CAR T-cell infusion were 10.15 months (range of 3.1 to 16.3) and 15.9 months (range of 9.9 to19.3). For the three patients with double-hit lymphoma, two received ASCT plus CART treatment are in ongoing complete remission, while one with short-interval (within 3 months) sequential infusion of anti-CD19 and anti-CD20CART-cell died in 6 months after enrollment. For these 5 (5/11) patients with P53 gene mutation positive, the prognosis was worse (3 PDs, 1 PR, and 1CR) in three-month assessment after CART infusion, and by September 30, 2021, 3 died of progression diseases and the median OS is 10 months (range of 6 to 16). However, the one treated by ASCT plus CART was in durable remission. We did not find that the other gene mutations such as CD79b\KMT2D have a relationship with the prognosis due to the fewer number of cases.
## 3.4. Toxic Effects
ICANS is the most concerning toxic effect of immunotherapy in r/r CNS lymphoma. In the 17 patients, 6 (35%) patients experienced ICANS, including grade 2 (n = 1), grade 3 (n = 2), and grade 4 (n = 3), and the median time of ICANS occurrence was 6 days (range of 1 to 8) after CART transfusion. The manifestations observed in patients were the following: headache, nausea, and vomiting in 5 patients (5/17), with a median onset of 7 days (range of 2 to 8) after CART; ataxia in 1 patient (1/17), where onset time was 3 days after CART; convulsion in 4 patients (4/17), where the median time of occurrence was 7.5 days (range of 5 to 23) after CART; coma in 3 patients (3/17), where the median time of occurrence was 8 days (range of 7 to 8) after CART; somnolence in 5 patients (5/17), where the median time of occurrence was 8 days (range of 3 to 8) after CART; and visual abnormalities in 2 patients (2/17), where the time of occurrence was 3 and 5 days after CART, respectively. After the intervention, the median duration of ICANS was 4.5 days (range of 3 to 23). The rate of ≥grade 3 ICANS was 29% (5/17). 3 patients developed grade 4 ICANS. Patient No. 8, who had previously underwent whole brain radiotherapy, had fever on d0 after CART cell transfusion. On d5, he suffered from neurological toxicity, which is manifested as hallucination, visual abnormality, somnolence, disorientation, and anomia; and on d24 after a CART transfusion, this patient was in a coma. DEX, mannitol, diazepam, and phenobarbital, which were initiated on d8, were administered for treatment, and the patient completely recovered on d40. Patient No. 17, who previously underwent radiotherapy for breast lymphoma, had a high fever that occurred on d2 after a CART cell transfusion and lasted for 5 days. The patient had neurological toxicity on day 7, and the manifestations included delirium and grand mal epilepsy. After treatment with mannitol, DEX, diazepam, and phenobarbital, the patient completely recovered on d28 after a CART cell transfusion. Patient No. 13, who had Burkitt lymphoma with bone marrow involvement, had a fever that occurred on d0 after CART transfusion and progressed to a high fever on d5, lasting for 4 days. Neurological toxicity occurred on d8, and the manifestations included convulsion of the limbs, urinary incontinence, and coma. After treatment with mannitol, DEX, sodium valproate, and diazepam, the patient completely recovered on day 12 after the CART cell transfusion. All severe ICANS in patients were alleviated, and neurotoxicity-related symptoms were reversible. No treatment-related deaths occurred in this study.CRS is another common adverse reaction to CART cell immunotherapy. It occurred in 16 patients (94%), and the median time of CRS occurrence was 1 day (range of 1 to 8) after CART transfusion. The major manifestations included the following: pyrexia in 16 patients (94%), with the median time of occurrence of 1 day (range of 1to8) after CART transfusion; hypotension in 8 patients (8/17), where the median time of occurrence was 3 days (range of 2 to 9) after CART transfusion; hypoxia in 9 patients (9/17), where the median time of occurrence was 5 days (range of 2 to 15) after CART transfusion; and generalized edema in 6 patients (6/17), where the median time of occurrence was 3 days (range of 2 to 8) after CART transfusion (Figures 6(b)). The median duration of CRS was 10 days (range of 4 to 29) after CART transfusion when corresponding interventions were performed. Grade 3 or higher CRS was observed in 7 (41%) patients, three of whom (patient No. 8, patient No. 16, and patient No. 17) received radiotherapy; three of whom (patient No. 1, patient No. 13, and patient No. 17) had bone marrow involvement; and four of whom (patient No. 1, patient No. 3, patient No. 5, and patient No. 8) had underwent ASCT + CART. Specifically, the incidence of ≥grade 3 CRS was 50% and 33% (p=0.48) and of ≥grade 3 ICANS was 25% and 33% (p=0.14) in the ASCT and non-ASCT groups, respectively.Figure 6
Adverse events associated with CART treatment. (a, b) Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). (a) The grade of cytokine release syndrome- and immune effector cells-associated neurologic toxicity in all patients, and the horizontal line indicates the median. (b) The rate of each symptom of CRS and ICANS in all patients. (c) There are no differences in complications between the ASCT plus CART group and CART alone. (d) Severe ICANS (≥grade 3) has association with IL-6, IFN-γ, and ferritin. Severe CRS (≥grade 3) was related with IL-6 and ferritin.
(a)(b)(c)(d)The common adverse events in the treatment period included agranulocytosis (17/17), infection (15/17), hypogammaglobulinemia (17/17), hepatic dysfunction (12/17), abnormal renal function (2/17), and gastrointestinal hemorrhage (3/17) (Figure6). None of the patients received supportive therapy with growth factors. High-intensity conditioning in the ASCT group did not significantly increase the duration of agranulocytosis (13.38 ± 5.85 days vs. 15.78 ± 6.63 days, p=0.65). The time of neutrophil cell engraftment was 11 days (range of 10 to 30), and platelet engraftment was 12 days (range of 10 to 14) in patients who underwent ASCT plus CART cells, which was consistent with previous findings [42–44]. These results indicated that CART cells did not influence the engraftment of hematopoietic stem cells.The changes in cytokines (IL6, TNFα, IL10, sCD25, and IFN-γ) and ferritin are shown in Figure 7. The median peak time was 7 days (range of 0 to 14), 7 days (range of 0–14), 7 days (range of 0–30), 7 days (range of 0–14), and 7 days (range of 0 to 30) after CART-cell transfusion, respectively. The median levels of IL-6 and ferritin were 76.15 ng/ml (range of 6.67 to 19540) and 2037.25 ng/ml (range of 172.8 to 26143.9), respectively. The severity of ICANS was positively correlated with IL-6 and ferritin levels (Figure 6).Figure 7
Changes of indicators during CART cell therapy. (a–f) IL-6, IL-10, TNFα, IFN-γ, ferritin, and sCD25 levels of the 17 patients during CART cell therapy. The day of first CAR T-cells infusion was day 0.
(a)(b)(c)(d)(e)(f)
## 4. Discussion
Considering that patients with r/r CNS lymphoma have a short survival time and a poor prognosis [10–13], no effective treatment is currently available for it. Over recent years, although CAR T-cell immunotherapy has been demonstrated effective and safe for r/r CNS B-cell lymphoma by several case reports, series, and studies [20–24, 26], disease progression can occur shortly after treatment [25, 26]. Therefore, attempts have been made to explore options for prolonging PFS: one study held that CAR T-cell therapy following ASCT had a long-term response with a median PFS of 14.03 months [33]. While one reported that patient with dual CD19/CD70 CART therapy attains remission lasting for 17 months [20]. Nonetheless, limited data compared the impact of ASCT plus CART versus sequential CD19/CD20/CD22 or targeting other tumor antigen CAR T-cell therapy on advanced r/r CNS lymphoma. In addition, most previous studies were in overall low sample size. This study is a larger sample size for the investigation of the safety and effectiveness of CART cells in the treatment of advanced r/r CNS lymphoma and firstly compared the impacts of ASCT plus CART cells versus short-interval sequential CAR T-cell therapy on sustained remission.The overall response rate (ORR) was 71% (12/17), and the complete remission rate (CRR) was 65% (11/17) at 3 months after CART cell transfusion in our study, which was similar to the CRR in relapsed/refractory B-cell lymphoma patients without CNS involvement who underwent CART cell therapy (58%) [14, 16, 26, 45]. The median PFS of the 17 patients was 16.3 months, and 9 patients (including 7 in the ASCT plus CART group and 2 in the CART group) had a PFS >1 year. 29% (5/17) of patients experienced disease progression, with the median time of PD was 3.8 months (range of 2.6 to 5.2 months). Three of these five patients with PD had a p53 gene mutation-positive, as previous findings report that these patients belong to a population with a poor prognosis and resulted in a nonresponsive outcome [9, 46]. However, in our study, other gene mutations had not been found in correlation with prognosis due to a smaller sample size.In addition, further analysis showed that the remission rate was significantly higher in the ASCT group than in the non-ASCT group, and that the duration of PFS was longer. We speculated that the observed differences could be due to the following: (1) high-dose chemotherapy prior to transplantation could reduce tumor volume and induce remission in patients, while lymphocyte clearing was more complete, which could favor the implantation of adaptive immune cells, enhance the expansion of adoptive T cells, and improve antitumor effects, namely, hematopoietic stem cell-driven lymphocyte proliferation [47–49] and especially the proliferation of CD8+ T cells [49–52]; (2) high-dose conditioning chemotherapy could clear implantation-inhibitory substances in the lymphoma microenvironment, improve the tumor immunosuppressive microenvironment (TME) [53–56], and favor CART cells to kill tumor cells and promote the infiltration of CART cells in tumor tissues. In addition, the treatment regimen ASCT plus CART, i.e., HSCT followed by CART transfusion, could maintain a relatively long duration of sustained remission, which could be associated with the fact that CART cells could purify possibly contaminated autologous hematopoietic stem cells for transplantation, thus effectively reducing the risk of relapse (Figure 5).Interestingly, the prognosis of the three double-hit lymphoma seemed not very bad in our study. 2 (2/3) patients with double-hit lymphoma who received ASCT + CART therapy are in ongoing remission until the cutoff date. Because of the small number of cases, we did not yet conclude that combination therapy is expected to improve the poor outcome of the double strike. However, this is promising. Another attractive phenomenon is that contrary to a previous study (see [20, 45, 57]), for these 9 patients with CART cell therapy alone, we found that the median PFS in 5 patients who underwent sequential CAR T-cell infusion was not better than that in 4 patients who received a single CD19/20/22CART administration, and neither was the OS. These findings demonstrated that sequential CART cells did not benefit patients with early relapse after CART cells. It appears that sequential infusion of CART-cells is not superior to single CAR T-cell treatment for some patients, and it is essential for screening of these patients. Whether it is necessary to sequentially administrate the second or the third different CART cells for a longer durable response, a prospective study with a larger sample size is needed to design, and the further relationship needs more investigation.Flow cytometry was used to monitor CART in this study. Like previous findings [14, 16, 45], the median peak time of CART cell expansion was within 2 weeks in the 17 patients, and the median duration of CART cells in peripheral blood was 31 days. Even in patients with sustained remission, CART cells were not detected, indicating that long-term efficacy may not require the persistent expansion or presence of CART cells, which needs to be further investigated in future studies. In addition, this study also showed that CART cell expansion peaked on day 67 after transfusion in Patient No. 14, who was treated with hCD19CART, lasting for 105 days, but this patient also had short-term disease progression, which indicated that human derived CART cells had longer persistence in vivo.After CART cells infusion, CSF was examined in 8 patients. CART cells in CSF were detected by FCM in patient No. 1, indicating that CART cells could pass the blood-brain barrier (BBB). However, CART cells in CSF were not detected in the remaining 7 patients, which may be associated with lumber puncture, and CSF assessments were not done at earlier days of the CART treatment due to concerns for hypersive intracranial pressure resulted by ICANS. At one month or later after the infusion when patients have passed the crisis, CSF assessment was performed, and meanwhile, the expansion peak of CART cells was dropped. Most of them (7/8) even lower the detectable threshold of quantification of technology in peripheral blood. Safety is an essential precondition for CSF detection. Moreover, patients without CSF-CART detection had good outcomes . The detection of CART in CSF has not been suggested as a clinical routine test (Figure3).Repuncture was performed for relapsed patients (Patient No. 9 and 15, both of whom underwent simple CART therapy) to acquire CSF or tumor tissues for FCM, which showed that the target antigen was still expressed. Contrary to previous studies [26], no CART cells were found in the CSF of the patients, and CART did not appear with the target antigen positive tumor cells. In addition, the CART counts were lower, and the sustained time was shorter in CSF than in peripheral blood, which could be associated with the intracranial immunosuppressant environment.CRS and ICANS are common toxic effects of CART therapy. For patients with r/r CNS lymphoma, the incidence and severity of ICANS are of greater concern. In this study, the incidence of ≥grade 3 ICANS was 29%, which was higher than that of other studies in the noncentral nervous system lymphoma (10%, 12%) [47, 48] but was comparable to the incidence of neurotoxic effects reported in previous studies on CART therapy for CNS lymphoma (ranging from 32% to 40%) [25, 26, 33]. No elevated ICANS incidence or lethal neurotoxicity occurred, all the ICANS symptoms were reversible, and no treatment-related deaths occurred in this study.The dose range of CAR T-cell infusion was wide (from 0.22×106 cells/kg to 5.9×106 cells/kg). Based on concurrent systemic lymphoma, most patients received conventional dose of CART cell infusion, except forthree patients. According to previous studies, patients with a substantial disease burden, in particular those with rapidly progressive disease and/or bulky extramedullary disease, are at risk of severe ICANS. Apart from that, the severe ICANS is associated with CART cell peak expansion and dose of infusion [58–60]. To reduce the incidence of severe neurotoxicity, three patients (Patient No.13, Patient No.14, and Patient No.17) with high disease burden in our study received fewer infusion dose (<0.5×106 cells/kg). However, the expansion peak and persistence of CART cells in these three patients were not affected, and two of them suffered from grade 4 ICANS (one without ICANS may be associated with humanized CAR T-cell therapy). Further analysis demonstrates that infusion dose has no relevant to the occurrence and severity of neurotoxicity but to the efficacy of the treatment. Due to the small sample size, further research is needed.Figure 8
(a) The correlation of dosages of CAR T-cell infusion with the occurrence of complete response (p=0.02). (b, c) The correlation of dosages of CAR T-cell infusion with the occurrence/severity of ICANS (p=0.36 and p=0.20, respectively). Horizontal lines indicate medians.
(a)(b)(c)In the present study, the incidence of ≥grade 3 CRS was 41.17%, which is higher than the results reported in other studies (22%) [15]. It may be associated with conditioning chemotherapy deeply lymphodepleting and enhance to the expansion of CART cells. Three(Patients No. 8, Patients No.13, and Patients No.17) had grade 4 ICANS and CRS, where Patient No. 8 had previously undergone whole-brain radiotherapy, and patient 17 had undergone radiotherapy for the primary tumor (breast involvement). Consequently, these findings could be associated with the destruction of the tumor microenvironment by radiotherapy and the “abscopal effects” [61, 62]. Cytokines and ferritin were positively correlated with the severity of ICANS, which was in line with previous studies [16, 63, 64]. Dynamic monitoring of the cytokine spectrum (IL6, TNFα, IL10, sCD25, and IFN-γ) and ferritin showed that cytokine levels increased with the expansion of CART cells. Our results also showed that the incidence of ≥grade 3 ICANS and CRS was not significantly different between the ASCT plus CART versus CART alone group, indicating that ASCT plus CART combination therapy does not increase the inflammatory toxicity and neurotoxicity of CART.The 17 patients all had different degrees of hypogammaglobulinemia, which could be associated with poor B-cell hyperplasia. Comparing the ASCT plus CART group versus the non-ASCT group showed that high-intensity chemotherapy did not increase in infection or prolong the duration of agranulocytosis in patients. No growth factor was used for supportive therapy in treatment, and the adverse events did not significantly differ between the ASCT group and the non-ASCT group.The comparison between the ASCT and non-ASCT groups showed that the remission rate was higher and PFS/OS was longer in the ASCT group, while the incidence of severe ICANS and CRS was comparable between the two groups. In addition, CART cells in the ASCT group did not influence transplantation, and high-intensity conditioning for transplantation did not prolong the duration of agranulocytosis or increase the incidence of infection. These findings have an important referencing significance for designing treatment strategies for r/r CNS lymphoma as they could provide a new treatment regimen for r/r CNS lymphoma. However, the sample size of this study was relatively small, the follow-up time was relatively short, and the grouping was not randomized. As many clinical factors were involved in the grouping, there could be a bias at baseline. Therefore, more multiple-center studies with longer follow-up times are needed for further investigation. Finally, our findings show that ASCT plus CAR T-cell therapy could be the most effective treatment for r/r CNS B-cell lymphoma but still have higher severe ICANS in CNS lymphoma patients than in non-CNS lymphoma patients. Therefore, CART cells should be applied with caution in the treatment of r/r CNS lymphoma.
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*Source: 2900310-2022-11-29.xml* | 2900310-2022-11-29_2900310-2022-11-29.md | 86,323 | The Autologous Hematopoietic Stem Cells Transplantation Combination-Based Chimeric Antigen Receptor T-Cell Therapy Improves Outcomes of Relapsed/Refractory Central Nervous System B-Cell Lymphoma | Fei Xue; Peihao Zheng; Rui Liu; Shaomei Feng; Yuelu Guo; Hui Shi; Haidi Liu; Biping Deng; Teng Xu; Xiaoyan Ke; Kai Hu | Journal of Oncology
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2900310 | 2900310-2022-11-29.xml | ---
## Abstract
Objective. The objective is to explore the effectiveness and safety of CAR T-cell therapy in advanced relapsed/refractory central nervous system B-cell lymphoma and compare the impact of autologous stem cell transplantation (ASCT) plus CAR T-cell therapy versus sequential CART therapy on the survival of patients. Methods. The retrospective analysis was based on the data of 17 patients with advanced relapsed/refractory central nervous system B-cell lymphoma. Bridging chemotherapy was applied before CAR T-cell infusion to further reduce the tumor burden. For patients with autologous hematopoietic stem cell successful collection, CD19/20/22CAR T-cell immunotherapy following ASCT was performed with the thiotepa-containing conditioning regimen, while sequential CD19/CD20/CD22CAR T-cell therapy was applied. For lymphodepletion, patients received bendamustine or fludarabine monotherapy or fludarabine combined with cyclophosphamide pre-CART-cell infusion. Results. Out of the 17 patients, 8 completed ASCT plus CART cell therapy, while 9 patients completed CART cell alone therapy. In efficacy assessment at 3 months after infusion, the objective response rate (ORR) was 12/17 (71%) and the complete response rate (CRR) was 11/17 (65%). The CRR of the ASCT group and non-ASCT was 100% and 44.4%, respectively (P<0.01). The median progression-free survival was 16.3 (2.6–24.5) months, and the median overall survival was 19.3 (6–24.5) months. Patients who underwent ASCT plus CART cell therapy had significantly longer PFS (P<0.01) and OS (P<0.01). Grade 3 or higher immune effector cell-associated neurologic toxicity syndrome (≥grade 3 ICANS) and cytokine release syndrome (≥grade 3 CRS) events occurred in 29% and 41% of the patients, respectively. No treatment-related death occurred. Conclusion. The CAR T-cell therapy could augment its efficacy in the treatment of advanced relapsed/refractory CNS B-cell lymphoma, while ASCT in combination with CART can induce durable responses and OS with a manageable side effect.
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## Body
## 1. Background
Central nervous system (CNS) lymphoma includes primary central nervous system lymphoma (PCNSL) and secondary central nervous system lymphoma (SCNSL), both of which are usually treated with the regimen of aggressive high-dose methotrexate (MTX) [1, 2] or thiotepa-based induction chemotherapy and autologous hematopoietic stem cell transplantation (ASCT) or whole-brain radiotherapy consolidation treatment [3, 4]. The complete remission (CR) rate of PCNSL patients has been reported to be approximately 45% [5–7]. However, approximately 35%–60% of patients relapse within 1-2 years, and nearly 10%–15% of patients are not sensitive to therapy [8]. The prognosis of patients with SCNSL is even worse, as long-term survival can be achieved in less than 20% of patients [9]. Although targeted drugs such as Bruton tyrosine kinase inhibitors (BTKis), Lenalidomide, and programmed death-1 inhibitors have improved the outcomes of central nervous system (CNS) lymphoma (the best CR rate 86%), patients tend to develop drug resistance rapidly, and the prognosis of these suffers remains poor [9]. Refraction and recurrence are the major causes of treatment failure in patients with CNS lymphoma [10–13]. Nevertheless, there is no consensus in the standard treatment for relapsed/refractory CNS (r/r CNS) lymphoma, currently. Therefore, it is a pressing issue that searching for a more effective treatment regimen for these challenging patient population.Chimeric antigen receptor-T cell (CART) therapy can effectively improve the complete remission (CR) rate of relapsed/refractory malignant B-cell tumors (range from 39% to 58%) and progression-free survival (median progression-free survival of 5.9 months) [14–18]. Yet, concerns for potential life-threatening neurotoxicity of CART cells and immune privileged of central nervous system, patients with r/r CNS lymphoma are excluded from pivotal cohort studies, and little is known about its effectiveness and treatment-related toxicities [14, 19]. Recently, several studies [20–24] (ranging from case reports or series to cohort studies) reported on the controllability of neurological toxicities and the effectiveness of CART cells in treating r/r CNS B-cell lymphoma. A retrospective study with eight patients diagnosed with secondary CNS B-cell lymphoma treated by CD19CART cells showed encouraging efficacy and manageable adverse events. A total of 4 patients were response to treatment and no patient experienced greater than grade-1 neurotoxicity [22]. Another prospective cohort study related to CAR T-cell immunotherapy in patients with relapsed PCNSL demonstrated that the overall response rate (ORR) is 58% (7/12), and the rate of ICANS is 50% but severe neurotoxicity (≥grade 3) 8% (1/12) [23]. These findings suggest that it is possible to treat r/r CNS B-cell lymphoma by CAR T-cell immunotherapy, but the duration of the responses was relatively short (median PFS ranging from only 3 months to 4.4 months) [25, 26]. Hence, to improve the poor outcome of low long-term remission rate, investors resort to combination with consolidation therapy.For CNS lymphoma, autologous stem cell transplantation (ASCT) and whole-brain radiation therapy (WBRT) have been used as standard consolidation treatments in the past [27]. However, patients with WBRT alone were prone to disabling cognitive dysfunction and devastating consequences on the quality of life [27, 28]. In the prospective study, patients with PCNSL were treated by cranial irradiation following chemotherapy and the incidence of severe neurologic toxicity was 15% [29]. WBRT probably increases the neurotoxicity of CART cells for treating CNS lymphoma. Instead of WBRT, combination with ASCT is naturally selected, this combination therapy has been applied to relapsed/refractory multiple myeloma and non-CNS lymphoma, and conditioning regime pre-ASCT can deeply deplete lymphocytes inhibiting the function of CART cells [30–32]. Recently, CAR T-cell immunotherapy following autologous stem cell transplantation (ASCT) for central nervous system lymphoma has been reported [26, 33]. The overall response rate (ORR) is nearly 82%, and the complete remission rate (CRR) is approximately 55%. The median durable response achieved a relatively longer at 14.03 months [33]. The incidence of severe immune effector cell-associated neurologic toxicity was 8%. However, it is not available for patients who cannot tolerate the toxicity of chemotherapy or without hematopoietic stem cells. In recent years, separate CAR T-cell immunotherapeutic avenues such as “Dual-Target” and “cocktail” CAR T-cell therapies are also administrated to attain ongoing complete remission [20, 26]. The patient in the former report continued CR for more than 17 months, but the median PFS in the latter study was only 3 months, which appeared to be a shorter term than ASCT plus CART. However, very few subjects were included. Therefore, we retrospectively investigated the effectiveness and safety of CART cells in treating 17 patients with r/r CNS B-cell lymphoma in the real-world and firstly compared the impact of ASCT plus CAR T-cell therapy versus sequential multitargeted (CD19, CD20, and CD22) CAR T-cell on durable remission.
## 2. Materials and Methods
### 2.1. Participant Population
Data from 17 patients with advanced r/r CNS B-cell lymphoma enrolled in the clinical- trial “Different B cell-targeted CART sequential infusion for adult patients with relapsed/refractory aggressive B-cell lymphoma (Clinicaltrials.gov registry:ChiCTR1900020980)” in the Beijing Boren Hospital between October 1, 2018, and October 1, 2020, were retrospectively analyzed. On the basis of the 2016 World Health Organization (WHO) guidelines and the diagnosed criteria of SCNSL [34–36], the diagnosis of CNS B-cell lymphoma by stereotactic biopsy and/or lumbar puncture for immunochemistry (IHC) (Figure 1) and/or flow cytometry (FCM) has been confirmed. An imaging examination was performed to clarify the lesion site. Of the 17 patients, 10 had brain parenchymal involvement, 4 had cerebrospinal fluid (CSF) involvement, and 3 had both brain parenchymal and CSF involvement. This study was approved by the Ethics Committee of the Beijing Boren Hospital, and all patients signed an informed consent form.Figure 1
Representative images of three patients with diffuse large B-cell lymphoma with central nervous system involvement are demonstrated (H & E, original magnification x100 and immunohistochemistry, original magnification x100).
### 2.2. Procedures
Peripheral blood mononuclear cells (PBMNCs) were isolated from the eligible patients, and CD3+ T lymphocytes were separated by using antigen-coated immunomagnetic beads. CD19/CD20/CD22 expression in tumor tissues was identified by IHC and FCM, which was the basis for selecting targets for CART cells. The second generation anti-CD19, CD20, and CD22-41BB-CAR lentiviral vector was constructed to transfect purified CD3+ T cells to prepare CART cells. The detailed processes have already been described in previous studies [37–39].Bridging chemotherapy was permitted prior to CAR T-cell transfusion to reduce tumor burden (for patients with CSF involvement, an intrathecal injection of 15 mg methotrexate, 50 mg cytarabine, and 5 mg dexamethasone, twice per week was performed until the minimal residual disease of the CSF showed negative by FCM). For patients with a response to chemotherapy, autologous hematopoietic stem cells were mobilized by granulocyte colony-stimulating factors and collected. Patients with successful stem cell collection received ASCT in combination with CAR T-cell therapy with the TEAM (thiotepa 5 mg/kg, d-8 to d-7; VP-16 200 mg/m2·d, d-6 to d-3;Ara-C 200 mg/m2·d, d-6 to d-3; and melphalan 140 mg/m2·d, d-2) or BEAM (BCNU 300 mg/m2, d-6; VP-16 200 mg/m2·d, d-5 to d-2, Ara-C 200 mg/m2, q12 h, d-5 to d-2; and Mel 140 mg/m2, d-1)-based conditioning regimen. The detailed dosages were adjusted according to the fundamental status and tolerance of the patients. Taking the date of CART transfusion as day 0, ASCT was transfused on day-1.For patients with insufficient/without autologous stem cells, sequentially different (CD19, CD20, and CD22) CART cell therapy was performed, and the sequential interval between different targeted CAR T-cell infusions was within 3 months. For all the patients, bendamustine (90–100 mg/m2) or fludarabine (25–30 mg/m2, d-3 to d-1) monotherapy or in combination with cyclophosphamide (CTX, 250 mg/m2, d-4 to d-2) was administrated for lymphocyte clearing prior to CART cell transfusion (Figure 2).Figure 2
Flow diagram of the 17 patients underwent treatment.A multicolor flow cytometer (FACS Calibur, BD, USA) was used to detect the CAR T-cell concentration in the blood and cerebrospinal fluid (CSF). Enzyme-linked immunosorbent assay (ELISA) was used to dynamically monitor the peripheral serum cytokines (IL-6, IL-10, TNFα, sCD25, and IFN-γ), and chemiluminescence (ECL) was used to monitor ferritin. The laboratory monitoring was done on d0, d3, d7, d14, d21, and d28 and then monthly until 6 months after transfusion of CART. Thereafter, the monitoring was further continued every 3 months until 24 months after the transfusion. The response was assessed by computed tomography (CT) and contrast-enhanced magnetic resonance once per month within 6 months after CART, and positron emission tomography/computed tomography (PET/CT), enhanced magnetic resonance imaging (MRI), or positron emission tomography/magnetic resonance imaging (PET/MRI) every 3 months until 24 months after CART transfusion while CSF assessments are monthly for three months and then quarterly for up to 24 months. The efficacy was assessed by two lymphoma specialists independently according to Lugano criteria (2014) [40]. Progression-free survival (PFS) is defined as the time from enrollment to the date of disease progression or last follow-up or death from any cause. Overall survival (OS) is defined as the time from enrollment to the date of last follow-up or death from any cause.In terms of treatment-related adverse reactions, cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) were graded according to the America Society of Transplantation and Cellular Therapy consensus criteria [41] and were treated according to Lee et al. [41]. In addition, anti-epilepsy drugs were also administered for seizure prophylaxis. Based on the National Cancer Institute CTCAE (Version 5.0), toxicities on organs were assessed. The assessment of engraftment of ASCT was as follows: a neutrophil count ≥0.5 × 109/L for three continuous days was considered granulocyte engraftment, and a platelet count >20 × 109/L for seven continuous days when no platelet infusion was performed was considered platelet engraftment.Fluorescence in situ hybridization (FISH) was used to detect the amplification and ectopic rearrangements ofBCL2/BCL6/MYC in tumor tissues. Next generation sequencing (NGS) was used to detect hotspot mutations in 225 lymphoma-related genes, where the sequencing depth was >1500x.
### 2.3. Statistical Analysis
SPSS 26.0 software and GraphPad Prism 9.0 software were used for statistical analysis. The chi-square (χ2) or Fisher test was used for the analysis of categorical data and the evaluation of associations between variables and efficacy. The Kaplan-Meier method was used for univariate analysis of progression-free survival (PFS) and overall survival (OS). The rank-sum test was used for the analysis of CART cell expansion. P<0.05 was considered statistically significant.
## 2.1. Participant Population
Data from 17 patients with advanced r/r CNS B-cell lymphoma enrolled in the clinical- trial “Different B cell-targeted CART sequential infusion for adult patients with relapsed/refractory aggressive B-cell lymphoma (Clinicaltrials.gov registry:ChiCTR1900020980)” in the Beijing Boren Hospital between October 1, 2018, and October 1, 2020, were retrospectively analyzed. On the basis of the 2016 World Health Organization (WHO) guidelines and the diagnosed criteria of SCNSL [34–36], the diagnosis of CNS B-cell lymphoma by stereotactic biopsy and/or lumbar puncture for immunochemistry (IHC) (Figure 1) and/or flow cytometry (FCM) has been confirmed. An imaging examination was performed to clarify the lesion site. Of the 17 patients, 10 had brain parenchymal involvement, 4 had cerebrospinal fluid (CSF) involvement, and 3 had both brain parenchymal and CSF involvement. This study was approved by the Ethics Committee of the Beijing Boren Hospital, and all patients signed an informed consent form.Figure 1
Representative images of three patients with diffuse large B-cell lymphoma with central nervous system involvement are demonstrated (H & E, original magnification x100 and immunohistochemistry, original magnification x100).
## 2.2. Procedures
Peripheral blood mononuclear cells (PBMNCs) were isolated from the eligible patients, and CD3+ T lymphocytes were separated by using antigen-coated immunomagnetic beads. CD19/CD20/CD22 expression in tumor tissues was identified by IHC and FCM, which was the basis for selecting targets for CART cells. The second generation anti-CD19, CD20, and CD22-41BB-CAR lentiviral vector was constructed to transfect purified CD3+ T cells to prepare CART cells. The detailed processes have already been described in previous studies [37–39].Bridging chemotherapy was permitted prior to CAR T-cell transfusion to reduce tumor burden (for patients with CSF involvement, an intrathecal injection of 15 mg methotrexate, 50 mg cytarabine, and 5 mg dexamethasone, twice per week was performed until the minimal residual disease of the CSF showed negative by FCM). For patients with a response to chemotherapy, autologous hematopoietic stem cells were mobilized by granulocyte colony-stimulating factors and collected. Patients with successful stem cell collection received ASCT in combination with CAR T-cell therapy with the TEAM (thiotepa 5 mg/kg, d-8 to d-7; VP-16 200 mg/m2·d, d-6 to d-3;Ara-C 200 mg/m2·d, d-6 to d-3; and melphalan 140 mg/m2·d, d-2) or BEAM (BCNU 300 mg/m2, d-6; VP-16 200 mg/m2·d, d-5 to d-2, Ara-C 200 mg/m2, q12 h, d-5 to d-2; and Mel 140 mg/m2, d-1)-based conditioning regimen. The detailed dosages were adjusted according to the fundamental status and tolerance of the patients. Taking the date of CART transfusion as day 0, ASCT was transfused on day-1.For patients with insufficient/without autologous stem cells, sequentially different (CD19, CD20, and CD22) CART cell therapy was performed, and the sequential interval between different targeted CAR T-cell infusions was within 3 months. For all the patients, bendamustine (90–100 mg/m2) or fludarabine (25–30 mg/m2, d-3 to d-1) monotherapy or in combination with cyclophosphamide (CTX, 250 mg/m2, d-4 to d-2) was administrated for lymphocyte clearing prior to CART cell transfusion (Figure 2).Figure 2
Flow diagram of the 17 patients underwent treatment.A multicolor flow cytometer (FACS Calibur, BD, USA) was used to detect the CAR T-cell concentration in the blood and cerebrospinal fluid (CSF). Enzyme-linked immunosorbent assay (ELISA) was used to dynamically monitor the peripheral serum cytokines (IL-6, IL-10, TNFα, sCD25, and IFN-γ), and chemiluminescence (ECL) was used to monitor ferritin. The laboratory monitoring was done on d0, d3, d7, d14, d21, and d28 and then monthly until 6 months after transfusion of CART. Thereafter, the monitoring was further continued every 3 months until 24 months after the transfusion. The response was assessed by computed tomography (CT) and contrast-enhanced magnetic resonance once per month within 6 months after CART, and positron emission tomography/computed tomography (PET/CT), enhanced magnetic resonance imaging (MRI), or positron emission tomography/magnetic resonance imaging (PET/MRI) every 3 months until 24 months after CART transfusion while CSF assessments are monthly for three months and then quarterly for up to 24 months. The efficacy was assessed by two lymphoma specialists independently according to Lugano criteria (2014) [40]. Progression-free survival (PFS) is defined as the time from enrollment to the date of disease progression or last follow-up or death from any cause. Overall survival (OS) is defined as the time from enrollment to the date of last follow-up or death from any cause.In terms of treatment-related adverse reactions, cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) were graded according to the America Society of Transplantation and Cellular Therapy consensus criteria [41] and were treated according to Lee et al. [41]. In addition, anti-epilepsy drugs were also administered for seizure prophylaxis. Based on the National Cancer Institute CTCAE (Version 5.0), toxicities on organs were assessed. The assessment of engraftment of ASCT was as follows: a neutrophil count ≥0.5 × 109/L for three continuous days was considered granulocyte engraftment, and a platelet count >20 × 109/L for seven continuous days when no platelet infusion was performed was considered platelet engraftment.Fluorescence in situ hybridization (FISH) was used to detect the amplification and ectopic rearrangements ofBCL2/BCL6/MYC in tumor tissues. Next generation sequencing (NGS) was used to detect hotspot mutations in 225 lymphoma-related genes, where the sequencing depth was >1500x.
## 2.3. Statistical Analysis
SPSS 26.0 software and GraphPad Prism 9.0 software were used for statistical analysis. The chi-square (χ2) or Fisher test was used for the analysis of categorical data and the evaluation of associations between variables and efficacy. The Kaplan-Meier method was used for univariate analysis of progression-free survival (PFS) and overall survival (OS). The rank-sum test was used for the analysis of CART cell expansion. P<0.05 was considered statistically significant.
## 3. Results
### 3.1. Clinical Characteristics
Baseline patient characteristics listed in Table1 indicate that 17 CNS involvement patients, with a median age of 42 years (range of 19 to 66), comprised 9 (53%) males and 8 (47%) females. 15 (88%) patients had secondary CNS B-cell lymphoma (mantle cell lymphoma, n = 1; Burkitt lymphoma, n = 1; diffuse large B-cell lymphoma non-GCB, n = 9; and diffuse large B-cell lymphoma GCB, n = 4), and 2 (12%) had primary central nervous system B-cell lymphoma. All the patients were diagnosed with Ann Arbor stage IV. For 14 patients aged <60 years, the age-adjusted international prognostic index (aaIPI) ≥3 was 8, and for 3 patients aged ≥60 years, the international prognostic index (IPI) was 5, 4, and 4, respectively. Clinical symptoms and signs at the time of enrollment included headache 65% (11/17); blurred vision and diplopia 12% (2/17); nausea and vomiting 18% (3/17); convulsion 6% (1/17); waist pain, lower limb numbness, and reduced muscle strength 24% (4/17); hearing loss 12% (2/17); and distortion of the commissure 12% (2/17). The Eastern Cooperative Oncology Group performance status score ranged from 2 to 4 points. FISH assays for MYC/BCL2/BCL6 in tumor tissues were performed in 11 (65%) patients. Two of them also received P53 measurements (Table 1). The abnormal factors involved MYC/BCL2/BCL6 rearrangement and/or amplification and P53 deletion. Among them, 3 (patient No.1, patient No.7, and patient No.17) were diagnosed double hit lymphoma and one (patient No.3) had P53 deletion. Next-generation sequencing for gene mutation in tumor tissues was performed in 11 patients, and 9 patients had gene mutations positive, including TP53 (5/11), KMT2D (4/11), CD79b (3/11), CCND3 (3/11), CREBBP (2/11), TET2 (2/11), and MYD88 (1/11), as shown in Table 1. A total of 17 patients received ≥2 lines of antineoplastic therapies, and the median number of prior therapies was 11 (range of 5 to 18), as shown in Table 2. In 17 patients, 7 (7/17) were insensitive to chemotherapy and refractory, while the remaining 10 (10/17) patients had relapsed after first-line/second-line therapy, especially in combination with targeted drug therapy (BTKi, n = 9; BCL2 inhibitor, n = 8; and programmed death-1 inhibitor, n = 1). 3 (3/17) patients had progressed after ASCT, 5 (5/17) relapsed after CART therapy, and 6 (6/17) patients had a history of partial radiotherapy. At the time of enrollment, 5 (5/17) patients had isolated central nervous system involvement, and 12 (12/17) had systemic disease progression in addition to central nervous system involvement. Before the initiation of therapy, the disease status was progressive disease (PD) in 15 (15/17) patients and stable disease (SD) in 2 (2/17).Table 1
Clinical characteristics of patients.
IDSexAgeDisease pathologyStageaaIPI/IPIPCNSLSite of CNS disease maximal dimension (mm)Tumor in CSF (%)Tumor in BM (%)NGSFISHPrevious CART therapyPrevious ASCT therapyDisease status1F39DLBCL GCBIVB2NCSF28%60%NegativeMYC/BCL2 rearrangementNNSD2F32DLBCL non-GCBIVB2NCerebellum, left frontal lobe (4)NN∗NA∗NANNPD3M34DLBCL non-GCBIVB3NT3-5 thoracic cord (17)NNTP53 p.W146X; STAT3 p.E616del; TET2 p.Q916X p.R1452X; CD79B p.E185X; CHD8 p.R986X; NFKBIE p.Y254Sfs∗13; BCL10 p.I46Yfs∗24,TP53 deletion. BCL6 rearrangementmCD19CART(PR) hCD22CART(PD)NPD4M48DLBCL non-GCBIVA2NPons, right thalamusNN∗NA∗NANNPD5M66DLBCL non-GCBIVB5NBilateral paraventricular, basal ganglia (4)NN∗NAMYC/BCL6/BCL2 amplificationNNPD6M43DLBCL non-GCBIVA2YLeft frontal lobe, basal gangliaNN∗NA∗NANNSD7F42DLBCL GCBIVA3NCerebellum vermis and hemispheres (41.4)NN∗NAMYC/BCL2 rearrangement. BCL6 amplificationNYESPD8F47DLBCL Non-GCBIVB3YRight frontal lobeNNMYD88 p.L265P; CD79B p.Y196C; KMT2D p.R1702X; ETV6 p.Q7Afs∗54; CCND3 p.Q280X; PIM1 p.S189Vfs∗20; CDKN2A p.A13Lfs∗13;BCL6 rearrangement. MYC/BCL2 amplificationNNPD9M40DLBCL non-GCBIVA2NCSF7.47%NTNFAIP3 p.Q74X; PRDM1 p.L48Vfs∗5; CDKN1B p.L144X; CCND3 p.D286Lfs∗72; CARD11 p.R337Q; PCLO p.Q3300X; NUDT15 p.R139CBCL6 rearrangementmCD19CART(PD) hCD22&CD19CART(PR)NPD10M41DLBCL non-GCBIVA2NCSF21.11%∗NAKMT2D p.Q3915X; CD70 p.Q47X∗NAmCD19-CART(CR)NPD11M58DLBCL non-GCBIVA3NLumbar cord (90 mm)N2.77%IRF4 p.K123RNegativeNYESPD12M64MCLIVB4NCSF16.13%20.50%Negative∗NANNPD13F19BLIVA3NBilateral occipital lobe, left frontal lobeN93.5%TP53 p.R213X, FOXO1 p.S203R, ID3 p.L40Efs∗21, TET2 p.E1151X; MYC p.A59T, CCND3 p.T283A∗NANNPD14F64DLBCL non-GCBIVB4NCerebrumNN∗NANegativemCD19CART(CR)NPD15M33DLBCL GCBIVB3NT4-6 thoracal cord63.32%NTP53 p.N131Y; TNFRSF14 p.M1V; KMT2D p.W315X; CREBBP p.Q2118Sfs∗25; DDX3X p.K13OIfs∗3; RB1 p.Y790X; PTEN p.V191Sfs∗11BCL2/BCL6 rearrangement. MYC amplification;NNPD16F35DLBCL non-GCBIVA3NCorpus callosum, right frontal lobe (20 mm)6.1%10%TP53 c.743G > A, BIRC3 p.R411K, DNMT3A p.R882C, KMT2C p.T2941NegativehCD22CART mCD19CARTYSEPD17F50DLBCL GCBIVA3NLeft occipital lobe, bilateral frontal cortex, (22 mm)18.97%NATP53 p.G245S; CD79B p.Y196S; CREBBP c.3837-2A > G; KMT2D p.A2119Lfs∗25; KMT2C p.C359Vfs∗15; ZMYM3 p.Q175Rfs∗52MYC/BCL2 rearrangement BCL6;NNPDM, male; F, female; aaIPI, age-adjusted International Prognostic Index; IPI, International Prognostic Index; PCNSL, primary central nervous system lymphoma; CNS, central nervous system; DLBCL, diffuse large B-cell lymphoma; GCB, germinal center (GC)-like B-cell type; MCL, Mantle cell lymphoma; BL, Burkitt lymphoma; CSF, cerebrospinal fluid;∗NA, not available; NGS, next generation sequencing; FISH, fluorescence in situ hybridization; tumor in CSF (%), percentage of B lymphoma cells in nuclear cells of cerebrospinal fluid; tumor in BM (%), percentage of B lymphoma cells in nuclear cells of bone marrow; CART, chimeric antigen receptor T cell; ASCT, allogeneic stem cell transplantation; PD, progressive disease; SD, stable disease.Table 2
Treatment and effect of CART cell therapy.
IDPrimary treatmentConditioning regimenLymphodepletionInfused cells (10^6/kg)CRS gradeICANS gradeNeurologic toxicityICANS treatmentCD34+CART1RCHOP × 3 (PD); isolated CNS relapse;R + HD-MTX + temozolomide + BCL2-inhibitor × 2 (SD)TEAMBendamustine5.2mCD19 (3.8)33Angulus oris convulsionMannitol, glucocorticoid, sodium valproate2R-DA-EPOCH × 4 (PR); GVD + PD-1 inhibitor × 2 (PD); isolated CNS relapse; BTKi + HD-MTX + GVD + PD-1 inhibitor × 2 (PD) systemic disease progression and CNS involvementBEAMF2.23mCD19 (1.25)10NoneMannitol3R2-CHOPE (PD); spinal cord involvement; R-MT(SD); R-CHOPE + BCL2-inhibitor (PR); HD-MTX + R-CHOPE × 4 (PD); mCD19CART (PR); hCD22CART (PD); systemic disease progression and CNS involvementBuCy——2.34hCD20 (2.06)30NoneNone4EPOCH × 6 (CR); isolated CNS relapse; HD-MTX + DEX × 2 (PR); isolated CNS relapse. HD-MTX + Idarubicin + DEX (PD); DHAP × 2 (PD); MIDD + BTKi × 6 (PD)TEAMBendamustine3.22hCD22 (5.9)20NoneNone5RCHOP × 3 (PR); RCHOP × 2 (PD); Isolated CNS relapse; MTX + BTKi + Temozolomide × 4 (CR); isolated CNS relapse (PD)TEAMF2.37hCD19 (3.3)30NoneMannitol6R + HD-MTX × 4 (PR); isolated CNS relapse; radiotherapy (PR); systemic disease progression and CNS involvement; ifosfamide + Ara-C × 1 (PD); HD-MTX × 2 (SD); TEDDi-R × 4 (PD); BTKi + BCL2-inhibitor × 4 (SD)TEAMFC2mCD19 (1.93)12ICE score 4; awakens to voiceSodium valproate7RCHOP × 3 (PR); RCHOPE × 4 (CR); ASCT (CR)R × 4 (CR); isolated CNS involvement; R + MTX + temozolomide + BTKi (PD)TEAMFC2mCD19 (2)20NoneMannitol8WBRT (CR); systemic disease progression and CNS involvement; HD-MTX + RCHOP × 3 (CR); systemic disease progression and CNS relapse; HD-MTX + RCHOP × 2 (PD)TEAMBendamustine3.23mCD19 (1.3)44Coma, seizures, hallucinationsMannitol, glucocorticoid, levetiracetam, diazepam9R-CHOPE × 6 (CR); radiation therapy (CR); systemic disease progression. RICE(PD); R2GDP (PD); RDHAP (SD); r-DA-EPOCH(PR); CD19CART (PD); BTKi + radiation (SD); RICE (SD); CD22CART + CD19CART (PR); BCL2-inhibitor + Chidamide (PD) testicular relapse + CNS involvement——————hCD20 (1.57)10NoneNone10RCHOP × 6 (CR); intraocular relapse (PD); RCHOP; radiation therapy (PD) RDHAP × 2 (PD); CD19-CART (CR) systemic disease progression and CSF involvement (PD)——F——hCD20 (0.94)10NoneMannitol, glucocorticoid11R2 + CHOP × 6 (CR); systemic disease progression; REPOCH × 6 (CR); BEAM + ASCT (CR) systemic disease progression and CNS involvement (PD); HD-MTX + DEX (PD); REPOCH (PD); RGDP (PD); MINE (PD)——FC——hCD19 (1.4)10Mannitol, glucocorticoid12RCHOP(PD); RDHAP (SD); BTKi + CHOP (SD); BTKi + DHAP (SD); BTKi + BCL2-inhibitor (PD) EPOCH (PD); GemOx × 2 (PD) systemic disease progression + CSF involvement——FC——mCD19 (1.485)10NoneNone13EPOCH × 2 (PD); decitabine + EPOCH × 2 (PD) COPADM (PD) systemic disease progression and CSF involvement——————mCD19 (0.29)34Coma, seizuresDiazepam, mannitol, glucocorticoid, plasmapheresis14RCHOP × 6 (CR); systemic disease progression; R-DICE × 6 (CRu); systemic disease progression; mCD19CART (CR); systemic disease progression and CNS involvement (PD)——FC——hCD19 (0.22)00NoneNone15RB × 6 (CR); systemic disease progression; R-CHOP (PD); REDOCH × 4 (PD); RDHAP + BCL2 inhibitor (PD)CSF involvement + systemic disease progression.——F——mCD19 (1.9)20NoneMannitol, glucocorticoid16RCHOP × 4 (PR); RCHOP × 2 (CRu); isolated CNS involvement; RCODOX-M × 2; RCDOP × 4 (CR); BEAM + ASCT (CR); CSF + CNS involvement; radiation (PD);R + MTX(PD)R + MTX + BTKi (PD); MTX + temozolomide + VP-16;CD22CART + CD19CART + BCL2-inhibitor (PD)——————hCD20 (1.0)33ICE score 2; Awakens only to tactile stimulus; dystaxiaMannitol, glucocorticoid17RCHOP × 4 (PR); REPOCH (PD); RGDP(PD); RDICE × 2 (PR); RDICE × 2 + BCL2-inhibitor (PD) + BTKi + GemOx(PD); Radiation therapy + Chidamide + lenalidomide (PD); systemic disease progression and CNS involvement (PD)——F——mCD19 (0.26)44Coma; seizuresMannitol, Glucocorticoid, Diazepam, Sodium valproateCRS, cytokine-release syndrome; ICANS, immune effector cells associated neurologic toxicity syndrome; CHOP, cyclophosphamide, doxorubicin, vincristine, dexamethasone; HD-MTX, high-dose methotrexate; DA-EPOCH, dose adjusted etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin; GVD, gemcitabine, vinorelbine, liposomal adriamycin; CHOPE, cyclophosphamide, doxorubicin, vincristine, dexamethasone, etoposide; DEX, dexamethasone; DHAP, dexamethasone, cytarabine, cisplatin; MIDD, methotrexate, ifosfamide, liposomal Adriamycin, dexamethasone; TEDDi, temozolomide, etoposide, liposomal adriamycin, dexamethasone, intrathecal injection(Ara-C); R2, rituximab, lenalidomide; ASCT, autologous stem cell transplant; WBRT, whole brain irradiation treatment; ICE, ifosfamide, carboplatin, etoposide; DICE, dexamethasone, ifosfamide, carboplatin, etoposide; MINE, mitoxantrone, ifosfamide, etoposide; GDP, gemcitabine, dexamethasone, cisplatin; COPADM, vincristine, high-dose methotrexate, doxorubicin, cyclophosphamide, prednisone; RB, rituximab, bendamustine; GemOx; gemcitabine, oxaliplatin; CODOX-M, cyclophosphamide, vincristine, doxorubicin, methotrexate; TEAM, thiotepa, etoposide, cytarabine, melphalan; BEAM, carmustine, etoposide, cytarabine, melphalan; BuCy, busulfan, cyclophosphamide;F, Fludarabine; FC, Fludarabine, cyclophosphamide; BTKi, Bruton’s tyrosine kinase inhibitor; PD-1 inhibitor, programmed death-1 inhibitor; CNS, central nervous system.
### 3.2. CART Transfusion and Dynamics
Among 17 patients, depending on the antigen expression of tumor tissue, 12 underwent CD19 CART cells (including 9 with murine-CD19 and 3 with humanized-CD19), with the median number of CART cells infusion of 1.44×106 cells/kg (rang of 0.22×106 cells/kg to 3.8×106 cells/kg); 4 underwent hCD20 CART cells, with a median number of CART cells infusion of 1.29×106 cells/kg (range of 0.94 × 106 to 2.06 × 106); and 1 underwent hCD22 CART cells, with infusion of 5.9×106 cells/kg. The median peak number of CAR T-cell expansion was 163×106 cells/L (range of 2.32 × 106–920 × 106) and achieved a peak with a median time of 9 days (range of 6 to 67) after CART transfusion, and the median lasting time of CART in peripheral blood was 31 days (range of 11 to 105). Three patients were infused with CART cells with a dose <0.5×106 cells/kg because they had substantial disease burden. Patient No. 13 with Burkitt lymphoma treated by mCD19CART had abdominal bulky mass (13.3 cm × 9.1 cm × 13 cm) and brain parenchyma involvement, with infusion dose of 0.29×106 cells/kg and peak number of 501 × 106/L on +11 days and lasting for 33 days. Patient No. 14 treated by hCD19CART had abdominal bulky mass (8.7 cm × 7 cm) and brain parenchyma involvement, with infusion dose of 0.22×106 cells/kg and peak number of 2.32 × 106/L on +60 days and lasting for 105 days; and Patient No. 17 treated by mCD19CART had breast bulky mass (11 cm × 8.3 cm × 3.2 cm) and both brain parenchyma and CSF involvement, with infusion dose of 0.26×106 cells/kg and peak number of 920 × 106/L on +14 days and lasting for 53 days.Out of 17 patients, lumbar puncture and CART cells in the CSF detection were performed in eight patients at the first month (Figure3). CART cell trafficking into the CSF was noted in patient 1 when the number of CART cells in the PB was 92.6 × 106 cells/L. While cells were not detected in the remaining 7 patients, the number of CART cells in PB dropped below the limit of detecting at that time.Figure 3
Dynamic changes of CART cells in peripheral blood and partial in cerebrospinal fluid after CART cell treatment. (a) Expansion and persistence of CART cells in peripheral blood were quantified by flow cytometry. (b) Percentage of CAR T-cells in lymphocytes(%) in peripheral blood and cerebrospinal fluid after CART cell therapy. (c) Detection of CART cells in the cerebrospinal fluid of patient No. 1 on day +30 by flow cytometry after infusion.
(a)(b)(c)The median number of CART infusion was 3.48×106 cells/kg (range of 1.25 × 106 to 5.9 × 106) vs. 0.94 × 106 cells/kg (range of 0.22 × 106 to 1.9 × 106) (p=0.02), the median peak number of CART was 250.2 × 106/L (range of 12.3 × 106 to 784 × 106) vs. 29.4 × 106/L (range of 2.32 × 106 to 960 × 106) (p=0.054), the median time to peak expansion was 7 days (range of 7 to 15) vs. 12 days (range of 6 to 68) (p=0.16), and median lasting time of CART was 47.5 days (range of 11 to 112) and 33 days (range of 12 to 105) (p=0.88) in the ASCT group and non-ASCT group, respectively.
### 3.3. Efficacy Assessment and Survival Analysis
Sixteen patients received bridging chemotherapy with the R-MA (4/16) and TEDDI (12/16) regimens to reduce the tumor burden prior to CART cell transfusion. At the time of infusion, all patients with CSF involvement had negative CSF by FCM, the symptoms and signs were managed, and the disease status was PD (n = 8), PR (n = 7), and CR (n = 2). 8 (8/17) patients underwent ASCT plus CART, and 9 (9/17) patients received CAR T-cell alone therapy, including 4 patients with single CART administration and 5 patients with short-interval sequential CD19/CD20/CD22CART treatment (within 3 months). The conditioning regimen before ASCT plus CART included the TEAM (75%) and non-TEAM (25%) regimens, and the median dose of CD34 cell transfusion was 2.35 × 106/kg (range of 2 × 106 to 5.2 × 106). It was bendamustine (3/17) or fludarabine (5/17) monotherapy or in combination with cyclophosphamide (5/17) that was performed for lymphodepletion. Still, 4 patients (Patient No. 3, Patient No. 9, Patient No. 13, and Patient No. 16) did not undergo lymphocyte clearing because the absolute lymphocyte count was <0.2 × 109/L. Taking the date of CART transfusion as day 0, ASCT was performed on day -1 in 5 patients, day -30 in 1 patient, and day -60 in 2 patients.According to the three-month assessment after CART cell infusion, responses were observed in 12(12/17) patients and consisted of 11 CRs and 1 partial remission. One (1/17) patient with Burkitt lymphoma had a progressive disease with systemic and CSN involvement. Four (4/17) patients had progressive diseases with only systemic relapse, two of whom had a p53 gene mutation positive. Further analysis, the CRR was significantly higher in the ASCT group than in the non-ASCT group (100% vs. 44%,p<0.01).By September 30, 2021, with a median follow-up of 20.7 months (range of 6 to 24.5), 8 (8/17) patients had achieved sustained remission. The median progression-free survival (PFS) of these challenging patients was 16.3 months (range of 2.6 to24.5 months). The eight patients with durable remission included seven patients treated by ASCT plus CART cells and one patient by CART cells alone (Figures4 and 5). Disease progression occurred in the remaining 9 patients (1 in the ASCT group and 8 in the non-ASCT group), and the median time of progression of the 9 patients was 4.8 months (range of 2.6 to 16.3). For the 9 PD patients, 8 patients (1 in the ASCT group and 7 in the non-ASCT group) died, including 7 who died of disease progression and one (patient No. 9) who received allogeneic hematopoietic stem cell transplantation in the following treatment died of infection by CMV pneumonia. The median overall survival (OS) was 19.3 months (range of 6 to 24.5). Kaplan-Meier survival analysis showed that patients who underwent ASCT plus CART cells had longer PFS (P<0.01) and OS (P<0.01) (Figure 4). The median PFS and median OS in the ASCT group were not reached, while in the non-ASCT is 4.8 months (range of 2.6 to 16.3) and 13.5 months (range of 6 to 19.3).Figure 4
Therapeutic effect of CART treatment and duration of response, progression-free survival (PFS), and overall survival (OS) estimates. (a, b) Kaplan-Meier estimates of progression-free survival and overall survival. (c) Swimmer’s plot of response for all patients on study (n = 17). Different colors represent the disease status. CR, complete remission; PR, partial remission; SD, stable disease; PD, progressive disease. Day 0 shows CAR T-cells infusion. ASCT, autologous stem cell transplantation; PFS, progression-free survival; OS, overall survival.
(a)(b)(c)Figure 5
Pretreatment and post-treatment imaging. Representative MRI imaging before (left) and after (right) therapy (a). The main central invasion sites of patient No.7 are cerebellum vermis and hemispheres. Invasion sites of patient No.16 are corpus callosum and right frontal lobe. The central invasion sites of patient 17 are left occipital lobe and bilateral frontal cortex. The images of patient No. 2 and patient No 3 by PET/CT (b). MRI, magnetic resonance imaging; PET/CT, positron emission computed tomography.
(a)(b)Especially, further analysis of 9 patients who only received CART therapy showed that the median PFS and median OS of 5 patients with sequential different targeted CAR T-cell therapy were 4.8 months (range of 2.6 to 7.7) and 9.9 months (range of 6 to 17), and that of 4 patients who did undergo single targeted CAR T-cell infusion were 10.15 months (range of 3.1 to 16.3) and 15.9 months (range of 9.9 to19.3). For the three patients with double-hit lymphoma, two received ASCT plus CART treatment are in ongoing complete remission, while one with short-interval (within 3 months) sequential infusion of anti-CD19 and anti-CD20CART-cell died in 6 months after enrollment. For these 5 (5/11) patients with P53 gene mutation positive, the prognosis was worse (3 PDs, 1 PR, and 1CR) in three-month assessment after CART infusion, and by September 30, 2021, 3 died of progression diseases and the median OS is 10 months (range of 6 to 16). However, the one treated by ASCT plus CART was in durable remission. We did not find that the other gene mutations such as CD79b\KMT2D have a relationship with the prognosis due to the fewer number of cases.
### 3.4. Toxic Effects
ICANS is the most concerning toxic effect of immunotherapy in r/r CNS lymphoma. In the 17 patients, 6 (35%) patients experienced ICANS, including grade 2 (n = 1), grade 3 (n = 2), and grade 4 (n = 3), and the median time of ICANS occurrence was 6 days (range of 1 to 8) after CART transfusion. The manifestations observed in patients were the following: headache, nausea, and vomiting in 5 patients (5/17), with a median onset of 7 days (range of 2 to 8) after CART; ataxia in 1 patient (1/17), where onset time was 3 days after CART; convulsion in 4 patients (4/17), where the median time of occurrence was 7.5 days (range of 5 to 23) after CART; coma in 3 patients (3/17), where the median time of occurrence was 8 days (range of 7 to 8) after CART; somnolence in 5 patients (5/17), where the median time of occurrence was 8 days (range of 3 to 8) after CART; and visual abnormalities in 2 patients (2/17), where the time of occurrence was 3 and 5 days after CART, respectively. After the intervention, the median duration of ICANS was 4.5 days (range of 3 to 23). The rate of ≥grade 3 ICANS was 29% (5/17). 3 patients developed grade 4 ICANS. Patient No. 8, who had previously underwent whole brain radiotherapy, had fever on d0 after CART cell transfusion. On d5, he suffered from neurological toxicity, which is manifested as hallucination, visual abnormality, somnolence, disorientation, and anomia; and on d24 after a CART transfusion, this patient was in a coma. DEX, mannitol, diazepam, and phenobarbital, which were initiated on d8, were administered for treatment, and the patient completely recovered on d40. Patient No. 17, who previously underwent radiotherapy for breast lymphoma, had a high fever that occurred on d2 after a CART cell transfusion and lasted for 5 days. The patient had neurological toxicity on day 7, and the manifestations included delirium and grand mal epilepsy. After treatment with mannitol, DEX, diazepam, and phenobarbital, the patient completely recovered on d28 after a CART cell transfusion. Patient No. 13, who had Burkitt lymphoma with bone marrow involvement, had a fever that occurred on d0 after CART transfusion and progressed to a high fever on d5, lasting for 4 days. Neurological toxicity occurred on d8, and the manifestations included convulsion of the limbs, urinary incontinence, and coma. After treatment with mannitol, DEX, sodium valproate, and diazepam, the patient completely recovered on day 12 after the CART cell transfusion. All severe ICANS in patients were alleviated, and neurotoxicity-related symptoms were reversible. No treatment-related deaths occurred in this study.CRS is another common adverse reaction to CART cell immunotherapy. It occurred in 16 patients (94%), and the median time of CRS occurrence was 1 day (range of 1 to 8) after CART transfusion. The major manifestations included the following: pyrexia in 16 patients (94%), with the median time of occurrence of 1 day (range of 1to8) after CART transfusion; hypotension in 8 patients (8/17), where the median time of occurrence was 3 days (range of 2 to 9) after CART transfusion; hypoxia in 9 patients (9/17), where the median time of occurrence was 5 days (range of 2 to 15) after CART transfusion; and generalized edema in 6 patients (6/17), where the median time of occurrence was 3 days (range of 2 to 8) after CART transfusion (Figures 6(b)). The median duration of CRS was 10 days (range of 4 to 29) after CART transfusion when corresponding interventions were performed. Grade 3 or higher CRS was observed in 7 (41%) patients, three of whom (patient No. 8, patient No. 16, and patient No. 17) received radiotherapy; three of whom (patient No. 1, patient No. 13, and patient No. 17) had bone marrow involvement; and four of whom (patient No. 1, patient No. 3, patient No. 5, and patient No. 8) had underwent ASCT + CART. Specifically, the incidence of ≥grade 3 CRS was 50% and 33% (p=0.48) and of ≥grade 3 ICANS was 25% and 33% (p=0.14) in the ASCT and non-ASCT groups, respectively.Figure 6
Adverse events associated with CART treatment. (a, b) Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). (a) The grade of cytokine release syndrome- and immune effector cells-associated neurologic toxicity in all patients, and the horizontal line indicates the median. (b) The rate of each symptom of CRS and ICANS in all patients. (c) There are no differences in complications between the ASCT plus CART group and CART alone. (d) Severe ICANS (≥grade 3) has association with IL-6, IFN-γ, and ferritin. Severe CRS (≥grade 3) was related with IL-6 and ferritin.
(a)(b)(c)(d)The common adverse events in the treatment period included agranulocytosis (17/17), infection (15/17), hypogammaglobulinemia (17/17), hepatic dysfunction (12/17), abnormal renal function (2/17), and gastrointestinal hemorrhage (3/17) (Figure6). None of the patients received supportive therapy with growth factors. High-intensity conditioning in the ASCT group did not significantly increase the duration of agranulocytosis (13.38 ± 5.85 days vs. 15.78 ± 6.63 days, p=0.65). The time of neutrophil cell engraftment was 11 days (range of 10 to 30), and platelet engraftment was 12 days (range of 10 to 14) in patients who underwent ASCT plus CART cells, which was consistent with previous findings [42–44]. These results indicated that CART cells did not influence the engraftment of hematopoietic stem cells.The changes in cytokines (IL6, TNFα, IL10, sCD25, and IFN-γ) and ferritin are shown in Figure 7. The median peak time was 7 days (range of 0 to 14), 7 days (range of 0–14), 7 days (range of 0–30), 7 days (range of 0–14), and 7 days (range of 0 to 30) after CART-cell transfusion, respectively. The median levels of IL-6 and ferritin were 76.15 ng/ml (range of 6.67 to 19540) and 2037.25 ng/ml (range of 172.8 to 26143.9), respectively. The severity of ICANS was positively correlated with IL-6 and ferritin levels (Figure 6).Figure 7
Changes of indicators during CART cell therapy. (a–f) IL-6, IL-10, TNFα, IFN-γ, ferritin, and sCD25 levels of the 17 patients during CART cell therapy. The day of first CAR T-cells infusion was day 0.
(a)(b)(c)(d)(e)(f)
## 3.1. Clinical Characteristics
Baseline patient characteristics listed in Table1 indicate that 17 CNS involvement patients, with a median age of 42 years (range of 19 to 66), comprised 9 (53%) males and 8 (47%) females. 15 (88%) patients had secondary CNS B-cell lymphoma (mantle cell lymphoma, n = 1; Burkitt lymphoma, n = 1; diffuse large B-cell lymphoma non-GCB, n = 9; and diffuse large B-cell lymphoma GCB, n = 4), and 2 (12%) had primary central nervous system B-cell lymphoma. All the patients were diagnosed with Ann Arbor stage IV. For 14 patients aged <60 years, the age-adjusted international prognostic index (aaIPI) ≥3 was 8, and for 3 patients aged ≥60 years, the international prognostic index (IPI) was 5, 4, and 4, respectively. Clinical symptoms and signs at the time of enrollment included headache 65% (11/17); blurred vision and diplopia 12% (2/17); nausea and vomiting 18% (3/17); convulsion 6% (1/17); waist pain, lower limb numbness, and reduced muscle strength 24% (4/17); hearing loss 12% (2/17); and distortion of the commissure 12% (2/17). The Eastern Cooperative Oncology Group performance status score ranged from 2 to 4 points. FISH assays for MYC/BCL2/BCL6 in tumor tissues were performed in 11 (65%) patients. Two of them also received P53 measurements (Table 1). The abnormal factors involved MYC/BCL2/BCL6 rearrangement and/or amplification and P53 deletion. Among them, 3 (patient No.1, patient No.7, and patient No.17) were diagnosed double hit lymphoma and one (patient No.3) had P53 deletion. Next-generation sequencing for gene mutation in tumor tissues was performed in 11 patients, and 9 patients had gene mutations positive, including TP53 (5/11), KMT2D (4/11), CD79b (3/11), CCND3 (3/11), CREBBP (2/11), TET2 (2/11), and MYD88 (1/11), as shown in Table 1. A total of 17 patients received ≥2 lines of antineoplastic therapies, and the median number of prior therapies was 11 (range of 5 to 18), as shown in Table 2. In 17 patients, 7 (7/17) were insensitive to chemotherapy and refractory, while the remaining 10 (10/17) patients had relapsed after first-line/second-line therapy, especially in combination with targeted drug therapy (BTKi, n = 9; BCL2 inhibitor, n = 8; and programmed death-1 inhibitor, n = 1). 3 (3/17) patients had progressed after ASCT, 5 (5/17) relapsed after CART therapy, and 6 (6/17) patients had a history of partial radiotherapy. At the time of enrollment, 5 (5/17) patients had isolated central nervous system involvement, and 12 (12/17) had systemic disease progression in addition to central nervous system involvement. Before the initiation of therapy, the disease status was progressive disease (PD) in 15 (15/17) patients and stable disease (SD) in 2 (2/17).Table 1
Clinical characteristics of patients.
IDSexAgeDisease pathologyStageaaIPI/IPIPCNSLSite of CNS disease maximal dimension (mm)Tumor in CSF (%)Tumor in BM (%)NGSFISHPrevious CART therapyPrevious ASCT therapyDisease status1F39DLBCL GCBIVB2NCSF28%60%NegativeMYC/BCL2 rearrangementNNSD2F32DLBCL non-GCBIVB2NCerebellum, left frontal lobe (4)NN∗NA∗NANNPD3M34DLBCL non-GCBIVB3NT3-5 thoracic cord (17)NNTP53 p.W146X; STAT3 p.E616del; TET2 p.Q916X p.R1452X; CD79B p.E185X; CHD8 p.R986X; NFKBIE p.Y254Sfs∗13; BCL10 p.I46Yfs∗24,TP53 deletion. BCL6 rearrangementmCD19CART(PR) hCD22CART(PD)NPD4M48DLBCL non-GCBIVA2NPons, right thalamusNN∗NA∗NANNPD5M66DLBCL non-GCBIVB5NBilateral paraventricular, basal ganglia (4)NN∗NAMYC/BCL6/BCL2 amplificationNNPD6M43DLBCL non-GCBIVA2YLeft frontal lobe, basal gangliaNN∗NA∗NANNSD7F42DLBCL GCBIVA3NCerebellum vermis and hemispheres (41.4)NN∗NAMYC/BCL2 rearrangement. BCL6 amplificationNYESPD8F47DLBCL Non-GCBIVB3YRight frontal lobeNNMYD88 p.L265P; CD79B p.Y196C; KMT2D p.R1702X; ETV6 p.Q7Afs∗54; CCND3 p.Q280X; PIM1 p.S189Vfs∗20; CDKN2A p.A13Lfs∗13;BCL6 rearrangement. MYC/BCL2 amplificationNNPD9M40DLBCL non-GCBIVA2NCSF7.47%NTNFAIP3 p.Q74X; PRDM1 p.L48Vfs∗5; CDKN1B p.L144X; CCND3 p.D286Lfs∗72; CARD11 p.R337Q; PCLO p.Q3300X; NUDT15 p.R139CBCL6 rearrangementmCD19CART(PD) hCD22&CD19CART(PR)NPD10M41DLBCL non-GCBIVA2NCSF21.11%∗NAKMT2D p.Q3915X; CD70 p.Q47X∗NAmCD19-CART(CR)NPD11M58DLBCL non-GCBIVA3NLumbar cord (90 mm)N2.77%IRF4 p.K123RNegativeNYESPD12M64MCLIVB4NCSF16.13%20.50%Negative∗NANNPD13F19BLIVA3NBilateral occipital lobe, left frontal lobeN93.5%TP53 p.R213X, FOXO1 p.S203R, ID3 p.L40Efs∗21, TET2 p.E1151X; MYC p.A59T, CCND3 p.T283A∗NANNPD14F64DLBCL non-GCBIVB4NCerebrumNN∗NANegativemCD19CART(CR)NPD15M33DLBCL GCBIVB3NT4-6 thoracal cord63.32%NTP53 p.N131Y; TNFRSF14 p.M1V; KMT2D p.W315X; CREBBP p.Q2118Sfs∗25; DDX3X p.K13OIfs∗3; RB1 p.Y790X; PTEN p.V191Sfs∗11BCL2/BCL6 rearrangement. MYC amplification;NNPD16F35DLBCL non-GCBIVA3NCorpus callosum, right frontal lobe (20 mm)6.1%10%TP53 c.743G > A, BIRC3 p.R411K, DNMT3A p.R882C, KMT2C p.T2941NegativehCD22CART mCD19CARTYSEPD17F50DLBCL GCBIVA3NLeft occipital lobe, bilateral frontal cortex, (22 mm)18.97%NATP53 p.G245S; CD79B p.Y196S; CREBBP c.3837-2A > G; KMT2D p.A2119Lfs∗25; KMT2C p.C359Vfs∗15; ZMYM3 p.Q175Rfs∗52MYC/BCL2 rearrangement BCL6;NNPDM, male; F, female; aaIPI, age-adjusted International Prognostic Index; IPI, International Prognostic Index; PCNSL, primary central nervous system lymphoma; CNS, central nervous system; DLBCL, diffuse large B-cell lymphoma; GCB, germinal center (GC)-like B-cell type; MCL, Mantle cell lymphoma; BL, Burkitt lymphoma; CSF, cerebrospinal fluid;∗NA, not available; NGS, next generation sequencing; FISH, fluorescence in situ hybridization; tumor in CSF (%), percentage of B lymphoma cells in nuclear cells of cerebrospinal fluid; tumor in BM (%), percentage of B lymphoma cells in nuclear cells of bone marrow; CART, chimeric antigen receptor T cell; ASCT, allogeneic stem cell transplantation; PD, progressive disease; SD, stable disease.Table 2
Treatment and effect of CART cell therapy.
IDPrimary treatmentConditioning regimenLymphodepletionInfused cells (10^6/kg)CRS gradeICANS gradeNeurologic toxicityICANS treatmentCD34+CART1RCHOP × 3 (PD); isolated CNS relapse;R + HD-MTX + temozolomide + BCL2-inhibitor × 2 (SD)TEAMBendamustine5.2mCD19 (3.8)33Angulus oris convulsionMannitol, glucocorticoid, sodium valproate2R-DA-EPOCH × 4 (PR); GVD + PD-1 inhibitor × 2 (PD); isolated CNS relapse; BTKi + HD-MTX + GVD + PD-1 inhibitor × 2 (PD) systemic disease progression and CNS involvementBEAMF2.23mCD19 (1.25)10NoneMannitol3R2-CHOPE (PD); spinal cord involvement; R-MT(SD); R-CHOPE + BCL2-inhibitor (PR); HD-MTX + R-CHOPE × 4 (PD); mCD19CART (PR); hCD22CART (PD); systemic disease progression and CNS involvementBuCy——2.34hCD20 (2.06)30NoneNone4EPOCH × 6 (CR); isolated CNS relapse; HD-MTX + DEX × 2 (PR); isolated CNS relapse. HD-MTX + Idarubicin + DEX (PD); DHAP × 2 (PD); MIDD + BTKi × 6 (PD)TEAMBendamustine3.22hCD22 (5.9)20NoneNone5RCHOP × 3 (PR); RCHOP × 2 (PD); Isolated CNS relapse; MTX + BTKi + Temozolomide × 4 (CR); isolated CNS relapse (PD)TEAMF2.37hCD19 (3.3)30NoneMannitol6R + HD-MTX × 4 (PR); isolated CNS relapse; radiotherapy (PR); systemic disease progression and CNS involvement; ifosfamide + Ara-C × 1 (PD); HD-MTX × 2 (SD); TEDDi-R × 4 (PD); BTKi + BCL2-inhibitor × 4 (SD)TEAMFC2mCD19 (1.93)12ICE score 4; awakens to voiceSodium valproate7RCHOP × 3 (PR); RCHOPE × 4 (CR); ASCT (CR)R × 4 (CR); isolated CNS involvement; R + MTX + temozolomide + BTKi (PD)TEAMFC2mCD19 (2)20NoneMannitol8WBRT (CR); systemic disease progression and CNS involvement; HD-MTX + RCHOP × 3 (CR); systemic disease progression and CNS relapse; HD-MTX + RCHOP × 2 (PD)TEAMBendamustine3.23mCD19 (1.3)44Coma, seizures, hallucinationsMannitol, glucocorticoid, levetiracetam, diazepam9R-CHOPE × 6 (CR); radiation therapy (CR); systemic disease progression. RICE(PD); R2GDP (PD); RDHAP (SD); r-DA-EPOCH(PR); CD19CART (PD); BTKi + radiation (SD); RICE (SD); CD22CART + CD19CART (PR); BCL2-inhibitor + Chidamide (PD) testicular relapse + CNS involvement——————hCD20 (1.57)10NoneNone10RCHOP × 6 (CR); intraocular relapse (PD); RCHOP; radiation therapy (PD) RDHAP × 2 (PD); CD19-CART (CR) systemic disease progression and CSF involvement (PD)——F——hCD20 (0.94)10NoneMannitol, glucocorticoid11R2 + CHOP × 6 (CR); systemic disease progression; REPOCH × 6 (CR); BEAM + ASCT (CR) systemic disease progression and CNS involvement (PD); HD-MTX + DEX (PD); REPOCH (PD); RGDP (PD); MINE (PD)——FC——hCD19 (1.4)10Mannitol, glucocorticoid12RCHOP(PD); RDHAP (SD); BTKi + CHOP (SD); BTKi + DHAP (SD); BTKi + BCL2-inhibitor (PD) EPOCH (PD); GemOx × 2 (PD) systemic disease progression + CSF involvement——FC——mCD19 (1.485)10NoneNone13EPOCH × 2 (PD); decitabine + EPOCH × 2 (PD) COPADM (PD) systemic disease progression and CSF involvement——————mCD19 (0.29)34Coma, seizuresDiazepam, mannitol, glucocorticoid, plasmapheresis14RCHOP × 6 (CR); systemic disease progression; R-DICE × 6 (CRu); systemic disease progression; mCD19CART (CR); systemic disease progression and CNS involvement (PD)——FC——hCD19 (0.22)00NoneNone15RB × 6 (CR); systemic disease progression; R-CHOP (PD); REDOCH × 4 (PD); RDHAP + BCL2 inhibitor (PD)CSF involvement + systemic disease progression.——F——mCD19 (1.9)20NoneMannitol, glucocorticoid16RCHOP × 4 (PR); RCHOP × 2 (CRu); isolated CNS involvement; RCODOX-M × 2; RCDOP × 4 (CR); BEAM + ASCT (CR); CSF + CNS involvement; radiation (PD);R + MTX(PD)R + MTX + BTKi (PD); MTX + temozolomide + VP-16;CD22CART + CD19CART + BCL2-inhibitor (PD)——————hCD20 (1.0)33ICE score 2; Awakens only to tactile stimulus; dystaxiaMannitol, glucocorticoid17RCHOP × 4 (PR); REPOCH (PD); RGDP(PD); RDICE × 2 (PR); RDICE × 2 + BCL2-inhibitor (PD) + BTKi + GemOx(PD); Radiation therapy + Chidamide + lenalidomide (PD); systemic disease progression and CNS involvement (PD)——F——mCD19 (0.26)44Coma; seizuresMannitol, Glucocorticoid, Diazepam, Sodium valproateCRS, cytokine-release syndrome; ICANS, immune effector cells associated neurologic toxicity syndrome; CHOP, cyclophosphamide, doxorubicin, vincristine, dexamethasone; HD-MTX, high-dose methotrexate; DA-EPOCH, dose adjusted etoposide, prednisone, vincristine, cyclophosphamide, doxorubicin; GVD, gemcitabine, vinorelbine, liposomal adriamycin; CHOPE, cyclophosphamide, doxorubicin, vincristine, dexamethasone, etoposide; DEX, dexamethasone; DHAP, dexamethasone, cytarabine, cisplatin; MIDD, methotrexate, ifosfamide, liposomal Adriamycin, dexamethasone; TEDDi, temozolomide, etoposide, liposomal adriamycin, dexamethasone, intrathecal injection(Ara-C); R2, rituximab, lenalidomide; ASCT, autologous stem cell transplant; WBRT, whole brain irradiation treatment; ICE, ifosfamide, carboplatin, etoposide; DICE, dexamethasone, ifosfamide, carboplatin, etoposide; MINE, mitoxantrone, ifosfamide, etoposide; GDP, gemcitabine, dexamethasone, cisplatin; COPADM, vincristine, high-dose methotrexate, doxorubicin, cyclophosphamide, prednisone; RB, rituximab, bendamustine; GemOx; gemcitabine, oxaliplatin; CODOX-M, cyclophosphamide, vincristine, doxorubicin, methotrexate; TEAM, thiotepa, etoposide, cytarabine, melphalan; BEAM, carmustine, etoposide, cytarabine, melphalan; BuCy, busulfan, cyclophosphamide;F, Fludarabine; FC, Fludarabine, cyclophosphamide; BTKi, Bruton’s tyrosine kinase inhibitor; PD-1 inhibitor, programmed death-1 inhibitor; CNS, central nervous system.
## 3.2. CART Transfusion and Dynamics
Among 17 patients, depending on the antigen expression of tumor tissue, 12 underwent CD19 CART cells (including 9 with murine-CD19 and 3 with humanized-CD19), with the median number of CART cells infusion of 1.44×106 cells/kg (rang of 0.22×106 cells/kg to 3.8×106 cells/kg); 4 underwent hCD20 CART cells, with a median number of CART cells infusion of 1.29×106 cells/kg (range of 0.94 × 106 to 2.06 × 106); and 1 underwent hCD22 CART cells, with infusion of 5.9×106 cells/kg. The median peak number of CAR T-cell expansion was 163×106 cells/L (range of 2.32 × 106–920 × 106) and achieved a peak with a median time of 9 days (range of 6 to 67) after CART transfusion, and the median lasting time of CART in peripheral blood was 31 days (range of 11 to 105). Three patients were infused with CART cells with a dose <0.5×106 cells/kg because they had substantial disease burden. Patient No. 13 with Burkitt lymphoma treated by mCD19CART had abdominal bulky mass (13.3 cm × 9.1 cm × 13 cm) and brain parenchyma involvement, with infusion dose of 0.29×106 cells/kg and peak number of 501 × 106/L on +11 days and lasting for 33 days. Patient No. 14 treated by hCD19CART had abdominal bulky mass (8.7 cm × 7 cm) and brain parenchyma involvement, with infusion dose of 0.22×106 cells/kg and peak number of 2.32 × 106/L on +60 days and lasting for 105 days; and Patient No. 17 treated by mCD19CART had breast bulky mass (11 cm × 8.3 cm × 3.2 cm) and both brain parenchyma and CSF involvement, with infusion dose of 0.26×106 cells/kg and peak number of 920 × 106/L on +14 days and lasting for 53 days.Out of 17 patients, lumbar puncture and CART cells in the CSF detection were performed in eight patients at the first month (Figure3). CART cell trafficking into the CSF was noted in patient 1 when the number of CART cells in the PB was 92.6 × 106 cells/L. While cells were not detected in the remaining 7 patients, the number of CART cells in PB dropped below the limit of detecting at that time.Figure 3
Dynamic changes of CART cells in peripheral blood and partial in cerebrospinal fluid after CART cell treatment. (a) Expansion and persistence of CART cells in peripheral blood were quantified by flow cytometry. (b) Percentage of CAR T-cells in lymphocytes(%) in peripheral blood and cerebrospinal fluid after CART cell therapy. (c) Detection of CART cells in the cerebrospinal fluid of patient No. 1 on day +30 by flow cytometry after infusion.
(a)(b)(c)The median number of CART infusion was 3.48×106 cells/kg (range of 1.25 × 106 to 5.9 × 106) vs. 0.94 × 106 cells/kg (range of 0.22 × 106 to 1.9 × 106) (p=0.02), the median peak number of CART was 250.2 × 106/L (range of 12.3 × 106 to 784 × 106) vs. 29.4 × 106/L (range of 2.32 × 106 to 960 × 106) (p=0.054), the median time to peak expansion was 7 days (range of 7 to 15) vs. 12 days (range of 6 to 68) (p=0.16), and median lasting time of CART was 47.5 days (range of 11 to 112) and 33 days (range of 12 to 105) (p=0.88) in the ASCT group and non-ASCT group, respectively.
## 3.3. Efficacy Assessment and Survival Analysis
Sixteen patients received bridging chemotherapy with the R-MA (4/16) and TEDDI (12/16) regimens to reduce the tumor burden prior to CART cell transfusion. At the time of infusion, all patients with CSF involvement had negative CSF by FCM, the symptoms and signs were managed, and the disease status was PD (n = 8), PR (n = 7), and CR (n = 2). 8 (8/17) patients underwent ASCT plus CART, and 9 (9/17) patients received CAR T-cell alone therapy, including 4 patients with single CART administration and 5 patients with short-interval sequential CD19/CD20/CD22CART treatment (within 3 months). The conditioning regimen before ASCT plus CART included the TEAM (75%) and non-TEAM (25%) regimens, and the median dose of CD34 cell transfusion was 2.35 × 106/kg (range of 2 × 106 to 5.2 × 106). It was bendamustine (3/17) or fludarabine (5/17) monotherapy or in combination with cyclophosphamide (5/17) that was performed for lymphodepletion. Still, 4 patients (Patient No. 3, Patient No. 9, Patient No. 13, and Patient No. 16) did not undergo lymphocyte clearing because the absolute lymphocyte count was <0.2 × 109/L. Taking the date of CART transfusion as day 0, ASCT was performed on day -1 in 5 patients, day -30 in 1 patient, and day -60 in 2 patients.According to the three-month assessment after CART cell infusion, responses were observed in 12(12/17) patients and consisted of 11 CRs and 1 partial remission. One (1/17) patient with Burkitt lymphoma had a progressive disease with systemic and CSN involvement. Four (4/17) patients had progressive diseases with only systemic relapse, two of whom had a p53 gene mutation positive. Further analysis, the CRR was significantly higher in the ASCT group than in the non-ASCT group (100% vs. 44%,p<0.01).By September 30, 2021, with a median follow-up of 20.7 months (range of 6 to 24.5), 8 (8/17) patients had achieved sustained remission. The median progression-free survival (PFS) of these challenging patients was 16.3 months (range of 2.6 to24.5 months). The eight patients with durable remission included seven patients treated by ASCT plus CART cells and one patient by CART cells alone (Figures4 and 5). Disease progression occurred in the remaining 9 patients (1 in the ASCT group and 8 in the non-ASCT group), and the median time of progression of the 9 patients was 4.8 months (range of 2.6 to 16.3). For the 9 PD patients, 8 patients (1 in the ASCT group and 7 in the non-ASCT group) died, including 7 who died of disease progression and one (patient No. 9) who received allogeneic hematopoietic stem cell transplantation in the following treatment died of infection by CMV pneumonia. The median overall survival (OS) was 19.3 months (range of 6 to 24.5). Kaplan-Meier survival analysis showed that patients who underwent ASCT plus CART cells had longer PFS (P<0.01) and OS (P<0.01) (Figure 4). The median PFS and median OS in the ASCT group were not reached, while in the non-ASCT is 4.8 months (range of 2.6 to 16.3) and 13.5 months (range of 6 to 19.3).Figure 4
Therapeutic effect of CART treatment and duration of response, progression-free survival (PFS), and overall survival (OS) estimates. (a, b) Kaplan-Meier estimates of progression-free survival and overall survival. (c) Swimmer’s plot of response for all patients on study (n = 17). Different colors represent the disease status. CR, complete remission; PR, partial remission; SD, stable disease; PD, progressive disease. Day 0 shows CAR T-cells infusion. ASCT, autologous stem cell transplantation; PFS, progression-free survival; OS, overall survival.
(a)(b)(c)Figure 5
Pretreatment and post-treatment imaging. Representative MRI imaging before (left) and after (right) therapy (a). The main central invasion sites of patient No.7 are cerebellum vermis and hemispheres. Invasion sites of patient No.16 are corpus callosum and right frontal lobe. The central invasion sites of patient 17 are left occipital lobe and bilateral frontal cortex. The images of patient No. 2 and patient No 3 by PET/CT (b). MRI, magnetic resonance imaging; PET/CT, positron emission computed tomography.
(a)(b)Especially, further analysis of 9 patients who only received CART therapy showed that the median PFS and median OS of 5 patients with sequential different targeted CAR T-cell therapy were 4.8 months (range of 2.6 to 7.7) and 9.9 months (range of 6 to 17), and that of 4 patients who did undergo single targeted CAR T-cell infusion were 10.15 months (range of 3.1 to 16.3) and 15.9 months (range of 9.9 to19.3). For the three patients with double-hit lymphoma, two received ASCT plus CART treatment are in ongoing complete remission, while one with short-interval (within 3 months) sequential infusion of anti-CD19 and anti-CD20CART-cell died in 6 months after enrollment. For these 5 (5/11) patients with P53 gene mutation positive, the prognosis was worse (3 PDs, 1 PR, and 1CR) in three-month assessment after CART infusion, and by September 30, 2021, 3 died of progression diseases and the median OS is 10 months (range of 6 to 16). However, the one treated by ASCT plus CART was in durable remission. We did not find that the other gene mutations such as CD79b\KMT2D have a relationship with the prognosis due to the fewer number of cases.
## 3.4. Toxic Effects
ICANS is the most concerning toxic effect of immunotherapy in r/r CNS lymphoma. In the 17 patients, 6 (35%) patients experienced ICANS, including grade 2 (n = 1), grade 3 (n = 2), and grade 4 (n = 3), and the median time of ICANS occurrence was 6 days (range of 1 to 8) after CART transfusion. The manifestations observed in patients were the following: headache, nausea, and vomiting in 5 patients (5/17), with a median onset of 7 days (range of 2 to 8) after CART; ataxia in 1 patient (1/17), where onset time was 3 days after CART; convulsion in 4 patients (4/17), where the median time of occurrence was 7.5 days (range of 5 to 23) after CART; coma in 3 patients (3/17), where the median time of occurrence was 8 days (range of 7 to 8) after CART; somnolence in 5 patients (5/17), where the median time of occurrence was 8 days (range of 3 to 8) after CART; and visual abnormalities in 2 patients (2/17), where the time of occurrence was 3 and 5 days after CART, respectively. After the intervention, the median duration of ICANS was 4.5 days (range of 3 to 23). The rate of ≥grade 3 ICANS was 29% (5/17). 3 patients developed grade 4 ICANS. Patient No. 8, who had previously underwent whole brain radiotherapy, had fever on d0 after CART cell transfusion. On d5, he suffered from neurological toxicity, which is manifested as hallucination, visual abnormality, somnolence, disorientation, and anomia; and on d24 after a CART transfusion, this patient was in a coma. DEX, mannitol, diazepam, and phenobarbital, which were initiated on d8, were administered for treatment, and the patient completely recovered on d40. Patient No. 17, who previously underwent radiotherapy for breast lymphoma, had a high fever that occurred on d2 after a CART cell transfusion and lasted for 5 days. The patient had neurological toxicity on day 7, and the manifestations included delirium and grand mal epilepsy. After treatment with mannitol, DEX, diazepam, and phenobarbital, the patient completely recovered on d28 after a CART cell transfusion. Patient No. 13, who had Burkitt lymphoma with bone marrow involvement, had a fever that occurred on d0 after CART transfusion and progressed to a high fever on d5, lasting for 4 days. Neurological toxicity occurred on d8, and the manifestations included convulsion of the limbs, urinary incontinence, and coma. After treatment with mannitol, DEX, sodium valproate, and diazepam, the patient completely recovered on day 12 after the CART cell transfusion. All severe ICANS in patients were alleviated, and neurotoxicity-related symptoms were reversible. No treatment-related deaths occurred in this study.CRS is another common adverse reaction to CART cell immunotherapy. It occurred in 16 patients (94%), and the median time of CRS occurrence was 1 day (range of 1 to 8) after CART transfusion. The major manifestations included the following: pyrexia in 16 patients (94%), with the median time of occurrence of 1 day (range of 1to8) after CART transfusion; hypotension in 8 patients (8/17), where the median time of occurrence was 3 days (range of 2 to 9) after CART transfusion; hypoxia in 9 patients (9/17), where the median time of occurrence was 5 days (range of 2 to 15) after CART transfusion; and generalized edema in 6 patients (6/17), where the median time of occurrence was 3 days (range of 2 to 8) after CART transfusion (Figures 6(b)). The median duration of CRS was 10 days (range of 4 to 29) after CART transfusion when corresponding interventions were performed. Grade 3 or higher CRS was observed in 7 (41%) patients, three of whom (patient No. 8, patient No. 16, and patient No. 17) received radiotherapy; three of whom (patient No. 1, patient No. 13, and patient No. 17) had bone marrow involvement; and four of whom (patient No. 1, patient No. 3, patient No. 5, and patient No. 8) had underwent ASCT + CART. Specifically, the incidence of ≥grade 3 CRS was 50% and 33% (p=0.48) and of ≥grade 3 ICANS was 25% and 33% (p=0.14) in the ASCT and non-ASCT groups, respectively.Figure 6
Adverse events associated with CART treatment. (a, b) Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS). (a) The grade of cytokine release syndrome- and immune effector cells-associated neurologic toxicity in all patients, and the horizontal line indicates the median. (b) The rate of each symptom of CRS and ICANS in all patients. (c) There are no differences in complications between the ASCT plus CART group and CART alone. (d) Severe ICANS (≥grade 3) has association with IL-6, IFN-γ, and ferritin. Severe CRS (≥grade 3) was related with IL-6 and ferritin.
(a)(b)(c)(d)The common adverse events in the treatment period included agranulocytosis (17/17), infection (15/17), hypogammaglobulinemia (17/17), hepatic dysfunction (12/17), abnormal renal function (2/17), and gastrointestinal hemorrhage (3/17) (Figure6). None of the patients received supportive therapy with growth factors. High-intensity conditioning in the ASCT group did not significantly increase the duration of agranulocytosis (13.38 ± 5.85 days vs. 15.78 ± 6.63 days, p=0.65). The time of neutrophil cell engraftment was 11 days (range of 10 to 30), and platelet engraftment was 12 days (range of 10 to 14) in patients who underwent ASCT plus CART cells, which was consistent with previous findings [42–44]. These results indicated that CART cells did not influence the engraftment of hematopoietic stem cells.The changes in cytokines (IL6, TNFα, IL10, sCD25, and IFN-γ) and ferritin are shown in Figure 7. The median peak time was 7 days (range of 0 to 14), 7 days (range of 0–14), 7 days (range of 0–30), 7 days (range of 0–14), and 7 days (range of 0 to 30) after CART-cell transfusion, respectively. The median levels of IL-6 and ferritin were 76.15 ng/ml (range of 6.67 to 19540) and 2037.25 ng/ml (range of 172.8 to 26143.9), respectively. The severity of ICANS was positively correlated with IL-6 and ferritin levels (Figure 6).Figure 7
Changes of indicators during CART cell therapy. (a–f) IL-6, IL-10, TNFα, IFN-γ, ferritin, and sCD25 levels of the 17 patients during CART cell therapy. The day of first CAR T-cells infusion was day 0.
(a)(b)(c)(d)(e)(f)
## 4. Discussion
Considering that patients with r/r CNS lymphoma have a short survival time and a poor prognosis [10–13], no effective treatment is currently available for it. Over recent years, although CAR T-cell immunotherapy has been demonstrated effective and safe for r/r CNS B-cell lymphoma by several case reports, series, and studies [20–24, 26], disease progression can occur shortly after treatment [25, 26]. Therefore, attempts have been made to explore options for prolonging PFS: one study held that CAR T-cell therapy following ASCT had a long-term response with a median PFS of 14.03 months [33]. While one reported that patient with dual CD19/CD70 CART therapy attains remission lasting for 17 months [20]. Nonetheless, limited data compared the impact of ASCT plus CART versus sequential CD19/CD20/CD22 or targeting other tumor antigen CAR T-cell therapy on advanced r/r CNS lymphoma. In addition, most previous studies were in overall low sample size. This study is a larger sample size for the investigation of the safety and effectiveness of CART cells in the treatment of advanced r/r CNS lymphoma and firstly compared the impacts of ASCT plus CART cells versus short-interval sequential CAR T-cell therapy on sustained remission.The overall response rate (ORR) was 71% (12/17), and the complete remission rate (CRR) was 65% (11/17) at 3 months after CART cell transfusion in our study, which was similar to the CRR in relapsed/refractory B-cell lymphoma patients without CNS involvement who underwent CART cell therapy (58%) [14, 16, 26, 45]. The median PFS of the 17 patients was 16.3 months, and 9 patients (including 7 in the ASCT plus CART group and 2 in the CART group) had a PFS >1 year. 29% (5/17) of patients experienced disease progression, with the median time of PD was 3.8 months (range of 2.6 to 5.2 months). Three of these five patients with PD had a p53 gene mutation-positive, as previous findings report that these patients belong to a population with a poor prognosis and resulted in a nonresponsive outcome [9, 46]. However, in our study, other gene mutations had not been found in correlation with prognosis due to a smaller sample size.In addition, further analysis showed that the remission rate was significantly higher in the ASCT group than in the non-ASCT group, and that the duration of PFS was longer. We speculated that the observed differences could be due to the following: (1) high-dose chemotherapy prior to transplantation could reduce tumor volume and induce remission in patients, while lymphocyte clearing was more complete, which could favor the implantation of adaptive immune cells, enhance the expansion of adoptive T cells, and improve antitumor effects, namely, hematopoietic stem cell-driven lymphocyte proliferation [47–49] and especially the proliferation of CD8+ T cells [49–52]; (2) high-dose conditioning chemotherapy could clear implantation-inhibitory substances in the lymphoma microenvironment, improve the tumor immunosuppressive microenvironment (TME) [53–56], and favor CART cells to kill tumor cells and promote the infiltration of CART cells in tumor tissues. In addition, the treatment regimen ASCT plus CART, i.e., HSCT followed by CART transfusion, could maintain a relatively long duration of sustained remission, which could be associated with the fact that CART cells could purify possibly contaminated autologous hematopoietic stem cells for transplantation, thus effectively reducing the risk of relapse (Figure 5).Interestingly, the prognosis of the three double-hit lymphoma seemed not very bad in our study. 2 (2/3) patients with double-hit lymphoma who received ASCT + CART therapy are in ongoing remission until the cutoff date. Because of the small number of cases, we did not yet conclude that combination therapy is expected to improve the poor outcome of the double strike. However, this is promising. Another attractive phenomenon is that contrary to a previous study (see [20, 45, 57]), for these 9 patients with CART cell therapy alone, we found that the median PFS in 5 patients who underwent sequential CAR T-cell infusion was not better than that in 4 patients who received a single CD19/20/22CART administration, and neither was the OS. These findings demonstrated that sequential CART cells did not benefit patients with early relapse after CART cells. It appears that sequential infusion of CART-cells is not superior to single CAR T-cell treatment for some patients, and it is essential for screening of these patients. Whether it is necessary to sequentially administrate the second or the third different CART cells for a longer durable response, a prospective study with a larger sample size is needed to design, and the further relationship needs more investigation.Flow cytometry was used to monitor CART in this study. Like previous findings [14, 16, 45], the median peak time of CART cell expansion was within 2 weeks in the 17 patients, and the median duration of CART cells in peripheral blood was 31 days. Even in patients with sustained remission, CART cells were not detected, indicating that long-term efficacy may not require the persistent expansion or presence of CART cells, which needs to be further investigated in future studies. In addition, this study also showed that CART cell expansion peaked on day 67 after transfusion in Patient No. 14, who was treated with hCD19CART, lasting for 105 days, but this patient also had short-term disease progression, which indicated that human derived CART cells had longer persistence in vivo.After CART cells infusion, CSF was examined in 8 patients. CART cells in CSF were detected by FCM in patient No. 1, indicating that CART cells could pass the blood-brain barrier (BBB). However, CART cells in CSF were not detected in the remaining 7 patients, which may be associated with lumber puncture, and CSF assessments were not done at earlier days of the CART treatment due to concerns for hypersive intracranial pressure resulted by ICANS. At one month or later after the infusion when patients have passed the crisis, CSF assessment was performed, and meanwhile, the expansion peak of CART cells was dropped. Most of them (7/8) even lower the detectable threshold of quantification of technology in peripheral blood. Safety is an essential precondition for CSF detection. Moreover, patients without CSF-CART detection had good outcomes . The detection of CART in CSF has not been suggested as a clinical routine test (Figure3).Repuncture was performed for relapsed patients (Patient No. 9 and 15, both of whom underwent simple CART therapy) to acquire CSF or tumor tissues for FCM, which showed that the target antigen was still expressed. Contrary to previous studies [26], no CART cells were found in the CSF of the patients, and CART did not appear with the target antigen positive tumor cells. In addition, the CART counts were lower, and the sustained time was shorter in CSF than in peripheral blood, which could be associated with the intracranial immunosuppressant environment.CRS and ICANS are common toxic effects of CART therapy. For patients with r/r CNS lymphoma, the incidence and severity of ICANS are of greater concern. In this study, the incidence of ≥grade 3 ICANS was 29%, which was higher than that of other studies in the noncentral nervous system lymphoma (10%, 12%) [47, 48] but was comparable to the incidence of neurotoxic effects reported in previous studies on CART therapy for CNS lymphoma (ranging from 32% to 40%) [25, 26, 33]. No elevated ICANS incidence or lethal neurotoxicity occurred, all the ICANS symptoms were reversible, and no treatment-related deaths occurred in this study.The dose range of CAR T-cell infusion was wide (from 0.22×106 cells/kg to 5.9×106 cells/kg). Based on concurrent systemic lymphoma, most patients received conventional dose of CART cell infusion, except forthree patients. According to previous studies, patients with a substantial disease burden, in particular those with rapidly progressive disease and/or bulky extramedullary disease, are at risk of severe ICANS. Apart from that, the severe ICANS is associated with CART cell peak expansion and dose of infusion [58–60]. To reduce the incidence of severe neurotoxicity, three patients (Patient No.13, Patient No.14, and Patient No.17) with high disease burden in our study received fewer infusion dose (<0.5×106 cells/kg). However, the expansion peak and persistence of CART cells in these three patients were not affected, and two of them suffered from grade 4 ICANS (one without ICANS may be associated with humanized CAR T-cell therapy). Further analysis demonstrates that infusion dose has no relevant to the occurrence and severity of neurotoxicity but to the efficacy of the treatment. Due to the small sample size, further research is needed.Figure 8
(a) The correlation of dosages of CAR T-cell infusion with the occurrence of complete response (p=0.02). (b, c) The correlation of dosages of CAR T-cell infusion with the occurrence/severity of ICANS (p=0.36 and p=0.20, respectively). Horizontal lines indicate medians.
(a)(b)(c)In the present study, the incidence of ≥grade 3 CRS was 41.17%, which is higher than the results reported in other studies (22%) [15]. It may be associated with conditioning chemotherapy deeply lymphodepleting and enhance to the expansion of CART cells. Three(Patients No. 8, Patients No.13, and Patients No.17) had grade 4 ICANS and CRS, where Patient No. 8 had previously undergone whole-brain radiotherapy, and patient 17 had undergone radiotherapy for the primary tumor (breast involvement). Consequently, these findings could be associated with the destruction of the tumor microenvironment by radiotherapy and the “abscopal effects” [61, 62]. Cytokines and ferritin were positively correlated with the severity of ICANS, which was in line with previous studies [16, 63, 64]. Dynamic monitoring of the cytokine spectrum (IL6, TNFα, IL10, sCD25, and IFN-γ) and ferritin showed that cytokine levels increased with the expansion of CART cells. Our results also showed that the incidence of ≥grade 3 ICANS and CRS was not significantly different between the ASCT plus CART versus CART alone group, indicating that ASCT plus CART combination therapy does not increase the inflammatory toxicity and neurotoxicity of CART.The 17 patients all had different degrees of hypogammaglobulinemia, which could be associated with poor B-cell hyperplasia. Comparing the ASCT plus CART group versus the non-ASCT group showed that high-intensity chemotherapy did not increase in infection or prolong the duration of agranulocytosis in patients. No growth factor was used for supportive therapy in treatment, and the adverse events did not significantly differ between the ASCT group and the non-ASCT group.The comparison between the ASCT and non-ASCT groups showed that the remission rate was higher and PFS/OS was longer in the ASCT group, while the incidence of severe ICANS and CRS was comparable between the two groups. In addition, CART cells in the ASCT group did not influence transplantation, and high-intensity conditioning for transplantation did not prolong the duration of agranulocytosis or increase the incidence of infection. These findings have an important referencing significance for designing treatment strategies for r/r CNS lymphoma as they could provide a new treatment regimen for r/r CNS lymphoma. However, the sample size of this study was relatively small, the follow-up time was relatively short, and the grouping was not randomized. As many clinical factors were involved in the grouping, there could be a bias at baseline. Therefore, more multiple-center studies with longer follow-up times are needed for further investigation. Finally, our findings show that ASCT plus CAR T-cell therapy could be the most effective treatment for r/r CNS B-cell lymphoma but still have higher severe ICANS in CNS lymphoma patients than in non-CNS lymphoma patients. Therefore, CART cells should be applied with caution in the treatment of r/r CNS lymphoma.
---
*Source: 2900310-2022-11-29.xml* | 2022 |
# Ultrasound Comparative Analysis of Coronary Arteries before and after Immune Blocking Therapy with Gamma Globulin in Children with Kawasaki Disease
**Authors:** Yi Yu; Jinhua Hu; Qun Xia; Juxia Huang; Yangmei Cheng; Fangling Wu; Yujing Liu; Jun Wang; Qiong Zhang
**Journal:** Evidence-Based Complementary and Alternative Medicine
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2900378
---
## Abstract
Objective. To investigate the ultrasound characteristics and clinical efficacy of coronary arteries before and after immune blocking therapy with gamma globulin in children with Kawasaki disease. Methods. A total of 64 children with Kawasaki disease who were treated in our hospital from January 2018 to October 2021 were selected. All the children were given immune blocking therapy with gamma globulin on the basis of conventional treatment. The disappearance time of related symptoms and signs (fever, mucosal congestion, cervical lymphadenopathy, and swelling of the hands and feet) in children were counted. The white blood cell count (WBC), platelet count (PLT), C-reactive protein (CRP), and procalcitonin (PCT) levels of the children before and after treatment were compared, and the characteristics of coronary echocardiography before and after treatment were observed for analysis and discussion, to carefully observe whether the coronary artery involvement of the children was improved. Results. The inner diameter of the left and right coronary arteries significantly decreased (P<0.05), and the levels of leukocytes, platelets, CRP, erythrocyte sedimentation rate, vascular endothelial growth factor (VEGF), and endostatin were significantly decreased compared with those before treatment, with a statistical difference (P<0.05). Conclusion. The effect of gamma globulin in the treatment of Kawasaki disease is remarkable, which can improve the blood indexes, VEGF, and endostatin levels in children, significantly reduce coronary dilatation, and reduce the incidence of coronary artery disease. Echocardiography is of high value in the examination of children with Kawasaki disease, which can accurately detect the size, location, and inner diameter of coronary artery lesions, and can effectively evaluate the treatment effect on children.
---
## Body
## 1. Introduction
Kawasaki disease (KD) is a common acute fever disease in pediatrics [1]. The main pathological characteristics are systemic arteritis and arteriolitis, and the most serious harm is cardiovascular damage [2, 3]. It has been shown that the incidence is slightly higher in Asian children than in Europe and the United States and is common not only in children aged 6 months to 5 years but also in school-aged children and rarely in adults, with a male to female ratio of approximately 1.62 : 1 [4]. It is mainly manifested as coronary artery lesions, including coronary artery dilatation and coronary aneurysm, which is the most important factor affecting the prognosis of children. Clinical manifestations include rash, fever, rigid edema of the hands and feet, and ocular conjunctival congestion [5]. KD is a self-limiting disease. Although the prognosis is good, if the correct and effective treatment measures are not received in the early stage, it can affect the small and medium arteries of the whole body, easily induce coronary artery damage, and even induce myocardial infarction and sudden death in severe cases, which seriously threatens the safety and quality of life of children [6, 7].As an immunoglobulin, gamma globulin is mostly used for the treatment of infectious diseases clinically [8]. It can block the Fc receptors on the surface of platelets, mononuclear phagocytes, and vascular endothelial cells and reduce the vascular immune inflammatory response [9, 10]. Immunoglobulin contains various antibodies required by the body to enhance the immune function and prevent infection. It has been widely used in the clinical treatment of KD, and its clinical efficacy is certain, as it can rapidly reduce fever, eliminate acute symptoms, and reduce the incidence of coronary artery lesions [11, 12]. In this study, we observed the characteristics of coronary ultrasound before and after gamma globulin immunoblockade treatment in children with KD, which provides a clinical reference for gamma globulin treatment of KD to inhibit the aggravation of coronary artery damage.
## 2. Materials and Methods
### 2.1. Research Objects
A prospective analysis was performed on 64 children with KD who were treated in our hospital from January 2018 to October 2021. All the children were given gamma globulin immunosuppressive therapy on the basis of conventional treatment. There were 40 males and 24 females; the age ranged from 72 days to 15 years, with an average of (3.04 ± 0.34) years.
#### 2.1.1. Inclusion Criteria
The inclusion criteria were as follows: patients met the clinical diagnostic criteria for Kawasaki disease in the 2017 edition of “Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association” [13], patients did not received relevant treatment before admission, patients had complete clinical data and could cooperate with the whole process of treatment and examination, and patients with no history of hypersensitivity to gamma globulin drugs.
#### 2.1.2. Exclusion Criteria
The exclusion criteria were as follows: patients with congenital heart disease, patients with a history of aspirin or intravenous immunoglobulin therapy, and patients with mental system disease. The above studies were conducted with the informed consent of the families of the children and were approved by the ethics committee of our hospital.
### 2.2. Methods
After admission, all the children received the same routine treatment plan, such as atomization of phlegm, physical cooling, routine use of antibiotics, and nutritional support. On this basis, the treatment was treated by intravenous infusion of gamma globulin (manufacturing company: Guizhou Taibang Biological Products Co., Ltd., Chinese medicine Zhunzi: S20023034, specification: 50 mL: 2.5 g/piece), according to 2 g/kg single dose, intravenous infusion, slowly completed within 10–12 h; if the reaction is poor, the drug can be repeated once on the second day, repeat twice at most; aspirin (Shaanxi Yishengtang Pharmaceutical Co., Ltd., Chinese medicine Zhunzi: H61023268) was taken orally, once a day, 30–50 mg/kg each time. After 3 days of administration, if the child was antipyretic, the dosage was reduced to 4 mg/kg until the coronary artery lesions and erythrocyte sedimentation rate returned to normal.
### 2.3. Evaluation Indicators and Judgment Criteria
(1) Time to disappearance of symptoms and signs and length of hospital stay: during the whole treatment process, the time to disappearance of signs and symptoms, such as fever, mucosal congestion, cervical lymphadenopathy, and swelling of the hands and feet, and hospitalization time of the children were counted. (2) The levels of serum-related indexes were compared before and after treatment. First, 5.0 ml of peripheral venous blood was drawn and centrifuged at 3000 r/min for 5 min by the Beckman Microfuge 20 medical centrifuge. The upper serum was taken and stored in a refrigerator at −20°C. The Beckman Coulter dxh 600 blood routine tester was used to measure the blood routine-related indicators of the children before and after treatment for 2 weeks, including C-reactive protein (CRP), platelets, white blood cells, erythrocyte sedimentation rate, and other indicators. VEGF and endostatin were detected by ELISA. (3) The incidence of coronary artery disease (CAL) was detected by echocardiography. The diagnostic criteria of Kawasaki disease complicated with coronary artery disease are as follows: (i) coronary artery aneurysm (CAA), coronary artery dilation of different shapes, coronary artery diameter 4–7 mm; (ii) giant coronary artery aneurysm (GCAA), coronary artery diameter ≥ 8 mm; and (iii) Coronary artery dilatation, coronary artery ≥ 2.5 mm in younger than 3 years old, coronary artery ≥ 3.0 mm in ≥ 3 years old and < 9 years old, coronary artery ≥ 3.2 mm in ≥ 9 years old and < 14 years old, and 33.5 mm in those aged 14 and older.
### 2.4. Statistical Methods
SPSS 24.0 was used for the statistical analysis of the data. The measurement data were analyzed by thet-test of the opposite samples, represented by (x¯±s), and the enumeration data were represented by the chi-square test, which was represented by the percentage, and P<0.05 indicated that the difference was statistically significant.
## 2.1. Research Objects
A prospective analysis was performed on 64 children with KD who were treated in our hospital from January 2018 to October 2021. All the children were given gamma globulin immunosuppressive therapy on the basis of conventional treatment. There were 40 males and 24 females; the age ranged from 72 days to 15 years, with an average of (3.04 ± 0.34) years.
### 2.1.1. Inclusion Criteria
The inclusion criteria were as follows: patients met the clinical diagnostic criteria for Kawasaki disease in the 2017 edition of “Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association” [13], patients did not received relevant treatment before admission, patients had complete clinical data and could cooperate with the whole process of treatment and examination, and patients with no history of hypersensitivity to gamma globulin drugs.
### 2.1.2. Exclusion Criteria
The exclusion criteria were as follows: patients with congenital heart disease, patients with a history of aspirin or intravenous immunoglobulin therapy, and patients with mental system disease. The above studies were conducted with the informed consent of the families of the children and were approved by the ethics committee of our hospital.
## 2.1.1. Inclusion Criteria
The inclusion criteria were as follows: patients met the clinical diagnostic criteria for Kawasaki disease in the 2017 edition of “Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association” [13], patients did not received relevant treatment before admission, patients had complete clinical data and could cooperate with the whole process of treatment and examination, and patients with no history of hypersensitivity to gamma globulin drugs.
## 2.1.2. Exclusion Criteria
The exclusion criteria were as follows: patients with congenital heart disease, patients with a history of aspirin or intravenous immunoglobulin therapy, and patients with mental system disease. The above studies were conducted with the informed consent of the families of the children and were approved by the ethics committee of our hospital.
## 2.2. Methods
After admission, all the children received the same routine treatment plan, such as atomization of phlegm, physical cooling, routine use of antibiotics, and nutritional support. On this basis, the treatment was treated by intravenous infusion of gamma globulin (manufacturing company: Guizhou Taibang Biological Products Co., Ltd., Chinese medicine Zhunzi: S20023034, specification: 50 mL: 2.5 g/piece), according to 2 g/kg single dose, intravenous infusion, slowly completed within 10–12 h; if the reaction is poor, the drug can be repeated once on the second day, repeat twice at most; aspirin (Shaanxi Yishengtang Pharmaceutical Co., Ltd., Chinese medicine Zhunzi: H61023268) was taken orally, once a day, 30–50 mg/kg each time. After 3 days of administration, if the child was antipyretic, the dosage was reduced to 4 mg/kg until the coronary artery lesions and erythrocyte sedimentation rate returned to normal.
## 2.3. Evaluation Indicators and Judgment Criteria
(1) Time to disappearance of symptoms and signs and length of hospital stay: during the whole treatment process, the time to disappearance of signs and symptoms, such as fever, mucosal congestion, cervical lymphadenopathy, and swelling of the hands and feet, and hospitalization time of the children were counted. (2) The levels of serum-related indexes were compared before and after treatment. First, 5.0 ml of peripheral venous blood was drawn and centrifuged at 3000 r/min for 5 min by the Beckman Microfuge 20 medical centrifuge. The upper serum was taken and stored in a refrigerator at −20°C. The Beckman Coulter dxh 600 blood routine tester was used to measure the blood routine-related indicators of the children before and after treatment for 2 weeks, including C-reactive protein (CRP), platelets, white blood cells, erythrocyte sedimentation rate, and other indicators. VEGF and endostatin were detected by ELISA. (3) The incidence of coronary artery disease (CAL) was detected by echocardiography. The diagnostic criteria of Kawasaki disease complicated with coronary artery disease are as follows: (i) coronary artery aneurysm (CAA), coronary artery dilation of different shapes, coronary artery diameter 4–7 mm; (ii) giant coronary artery aneurysm (GCAA), coronary artery diameter ≥ 8 mm; and (iii) Coronary artery dilatation, coronary artery ≥ 2.5 mm in younger than 3 years old, coronary artery ≥ 3.0 mm in ≥ 3 years old and < 9 years old, coronary artery ≥ 3.2 mm in ≥ 9 years old and < 14 years old, and 33.5 mm in those aged 14 and older.
## 2.4. Statistical Methods
SPSS 24.0 was used for the statistical analysis of the data. The measurement data were analyzed by thet-test of the opposite samples, represented by (x¯±s), and the enumeration data were represented by the chi-square test, which was represented by the percentage, and P<0.05 indicated that the difference was statistically significant.
## 3. Results
### 3.1. Disappearance Time of Symptoms and Signs and Length of Hospital Stay
The time when the symptoms and signs disappeared and the length of hospital stay are given in Table1.Table 1
Disappearance time of symptoms and signs and length of hospital stay.
CasesAntipyretic timeCervical lymphadenopathy resolution timeMucous membrane hyperemia disappearance timeHand and foot swelling subsides timeHospital stay763.79 ± 0.516.81 ± 1.654.03 ± 0.774.19 ± 1.258.67 ± 0.76
### 3.2. Serum-Related Index Levels before and after Treatment in Children
Leukocyte level in the child after gamma globulin treatment was 8.24 ± 2.75 × 109/L compared to 17.14 ± 4.78 × 109/L before treatment. Platelet level in the child after gamma globulin treatment was 230.84 ± 54.81 × 109/L compared to 380.23 ± 109.73 × 109/L before treatment; CRP levels were 70.33 ± 8.66 mg/L before treatment and 70.33 ± 8.66 mg/L after treatment; ESR levels were 99.06 ± 10.24 mm/h before treatment and 99.06 ± 10.24 mm/h after treatment; the serum levels of the relevant indicators decreased in all children after gamma globulin treatment (P<0.001) (Table 2).Table 2
Comparison of serum-related indexes before and after treatment in children.
Leukocyte (×109/L)Platelets (×109/L)CRP (mg/L)ESR (mm/h)Before treatment17.14 ± 4.78380.23 ± 109.7370.33 ± 8.6699.06 ± 10.24After treatment8.24 ± 2.75230.84 ± 54.8120.15 ± 6.0532.41 ± 4.52t14.0710.61841.4151.91P< 0.001< 0.001< 0.001< 0.001
### 3.3. Comparison of VEGF and Endostatin Levels before and after Treatment in Children
After gamma globulin treatment, VEGF levels were 41.73 ± 6.31 pg/L and endothelial inhibitory hormone levels were 16.53 ± 1.47 ng/L. Before treatment, VEGF levels were 198.47 ± 17.36 pg/L and endothelial inhibitory hormone levels were 40.62 ± 2.13 ng/L.Before treatment, VEGF levels were 198.47 ± 17.36 pg/L and endothelial inhibitory hormone levels were 40.62 ± 2.13 ng/L. VEGF and endothelial inhibitory hormone levels decreased significantly after treatment in children (P<0.001). After gamma globulin treatment, VEGF and endostatin were significantly lower than those before treatment (Table 3).Table 3
Comparison of VEGF and endostatin levels before and after treatment in children.
VEGF (pg/L)Endostatin (ng/L)Before treatment198.47 ± 17.3640.62 ± 2.13After treatment41.73 ± 6.3116.53 ± 1.47t73.97681.148P< 0.001< 0.001
### 3.4. Changes of Coronary Artery Diameter in Children before and after Treatment
After gamma globulin treatment, the internal diameter of the left coronary artery was 2.70 ± 0.86 mm and that of the right coronary artery was 2.90 ± 0.35 mm. After treatment, the internal diameter of the left coronary artery was 4.30 ± 1.13 mm and that of the right coronary artery was 3.10 ± 1.02 mm. The coronary artery internal diameter of the children improved significantly after treatment (P<0.001) (Table 4) (Figure 1).Table 4
Changes of coronary artery diameter before and after treatment in children.
Inner diameter of the left coronary artery (mm)Inner diameter of the right coronary artery (mm)Before treatment4.30 ± 1.133.10 ± 1.02After treatment2.70 ± 0.862.90 ± 0.35t9.8231.263P< 0.001< 0.001Figure 1
Changes in the inner diameter of the left and right coronary arteries before and after treatment. (a) The ultrasound results of the left coronary artery and (b) the right coronary artery before treatment. (c) The ultrasound results of the left coronary artery and (d) the right coronary artery three months after gamma globulin immunoblocking therapy.
(a)(b)(c)(d)
## 3.1. Disappearance Time of Symptoms and Signs and Length of Hospital Stay
The time when the symptoms and signs disappeared and the length of hospital stay are given in Table1.Table 1
Disappearance time of symptoms and signs and length of hospital stay.
CasesAntipyretic timeCervical lymphadenopathy resolution timeMucous membrane hyperemia disappearance timeHand and foot swelling subsides timeHospital stay763.79 ± 0.516.81 ± 1.654.03 ± 0.774.19 ± 1.258.67 ± 0.76
## 3.2. Serum-Related Index Levels before and after Treatment in Children
Leukocyte level in the child after gamma globulin treatment was 8.24 ± 2.75 × 109/L compared to 17.14 ± 4.78 × 109/L before treatment. Platelet level in the child after gamma globulin treatment was 230.84 ± 54.81 × 109/L compared to 380.23 ± 109.73 × 109/L before treatment; CRP levels were 70.33 ± 8.66 mg/L before treatment and 70.33 ± 8.66 mg/L after treatment; ESR levels were 99.06 ± 10.24 mm/h before treatment and 99.06 ± 10.24 mm/h after treatment; the serum levels of the relevant indicators decreased in all children after gamma globulin treatment (P<0.001) (Table 2).Table 2
Comparison of serum-related indexes before and after treatment in children.
Leukocyte (×109/L)Platelets (×109/L)CRP (mg/L)ESR (mm/h)Before treatment17.14 ± 4.78380.23 ± 109.7370.33 ± 8.6699.06 ± 10.24After treatment8.24 ± 2.75230.84 ± 54.8120.15 ± 6.0532.41 ± 4.52t14.0710.61841.4151.91P< 0.001< 0.001< 0.001< 0.001
## 3.3. Comparison of VEGF and Endostatin Levels before and after Treatment in Children
After gamma globulin treatment, VEGF levels were 41.73 ± 6.31 pg/L and endothelial inhibitory hormone levels were 16.53 ± 1.47 ng/L. Before treatment, VEGF levels were 198.47 ± 17.36 pg/L and endothelial inhibitory hormone levels were 40.62 ± 2.13 ng/L.Before treatment, VEGF levels were 198.47 ± 17.36 pg/L and endothelial inhibitory hormone levels were 40.62 ± 2.13 ng/L. VEGF and endothelial inhibitory hormone levels decreased significantly after treatment in children (P<0.001). After gamma globulin treatment, VEGF and endostatin were significantly lower than those before treatment (Table 3).Table 3
Comparison of VEGF and endostatin levels before and after treatment in children.
VEGF (pg/L)Endostatin (ng/L)Before treatment198.47 ± 17.3640.62 ± 2.13After treatment41.73 ± 6.3116.53 ± 1.47t73.97681.148P< 0.001< 0.001
## 3.4. Changes of Coronary Artery Diameter in Children before and after Treatment
After gamma globulin treatment, the internal diameter of the left coronary artery was 2.70 ± 0.86 mm and that of the right coronary artery was 2.90 ± 0.35 mm. After treatment, the internal diameter of the left coronary artery was 4.30 ± 1.13 mm and that of the right coronary artery was 3.10 ± 1.02 mm. The coronary artery internal diameter of the children improved significantly after treatment (P<0.001) (Table 4) (Figure 1).Table 4
Changes of coronary artery diameter before and after treatment in children.
Inner diameter of the left coronary artery (mm)Inner diameter of the right coronary artery (mm)Before treatment4.30 ± 1.133.10 ± 1.02After treatment2.70 ± 0.862.90 ± 0.35t9.8231.263P< 0.001< 0.001Figure 1
Changes in the inner diameter of the left and right coronary arteries before and after treatment. (a) The ultrasound results of the left coronary artery and (b) the right coronary artery before treatment. (c) The ultrasound results of the left coronary artery and (d) the right coronary artery three months after gamma globulin immunoblocking therapy.
(a)(b)(c)(d)
## 4. Discussion
KD, also known as cutaneous mucosal lymph node syndrome, is an acute systemic vasculitis and a common autoimmune disease in pediatrics [14]. The incidence of KD is increasing year by year, often impairing cardiac function in children and leading to coronary heart disease, and is gradually attracting widespread medical attention [15]. Although the pathogenesis has not been elucidated, genetic studies have identified several susceptibility genes for KD and its sequelae in different ethnic groups, including FCGR2A and CD40 [16]. Recent studies have found [17] that KD may be induced by the entry of one or more pathogenic microorganisms into the organism and is a systemic vascular inflammatory disease characterized by immune activation or immune dysfunction. Gamma globulin contains multiple antibodies in serum of healthy individuals and is a passive immunotherapy [18, 19]. It has a neutralizing effect on autoantibodies, can relieve the effect of microbial toxins and vascular inflammation, reduce the level of inflammatory factors, promote the negative feedback of immune regulatory cells, improve cellular immunity and humoral disorders, and control the deterioration of symptoms. The application of high-dose gamma globulin in the acute phase can block all immune responses that cause vascular damage and reduce platelet aggregation, thereby reducing coronary artery damage to a certain extent, that is, reducing coronary artery dilatation. Reducing the rate of change and giving gamma globulin therapy to children with KD in a timely manner to prevent complications such as myocardial infarction and impaired coronary artery function in children with KD significantly improves the safety and health of children [20, 21].The results of this study showed that after the children received intravenous gamma globulin, the inner diameter of the left and right coronary arteries was significantly reduced (P<0.05), and the levels of white blood cells, platelets, CRP, ESR, VEGF, and endostatin were significantly decreased compared with those before treatment (P<0.05). The mechanism of action may be the more types and components of antibodies contained in gamma globulin, the more IVIG can inhibit the activity of FC receptors on lymphocytes, monocytes, macrophages, and other immune cell walls. (1) The more types and components of antibodies contained in gamma globulin, the more obvious the inhibitory effect of IVIG on the FC receptor activity of lymphocytes, mononuclear macrophages, and other immune cell walls, thus weakening the activation of a large number of immune cells, which can inhibit the inflammatory response, effectively relieve the toxic reactions in children, reduce the stimulation of inflammatory factors to the endovascular cortex, and reduce the occurrence of coronary artery lesions by improving the level of immune factors in children in the short term [22]; (2) activation of platelet-derived growth factors and their vascular pathways, reducing the degree of endothelial damage and thus the degree of vascular immune damage; (3) inhibition of B cell lymphocyte activity, resistance to toxin damage to children’s vascular cells, and competitive binding requiring relevant receptors on the vessel wall, leading to massive immune complex deposition; (4) reduction of platelet levels, reducing the risk of thrombosis, which can effectively improve coronary artery dilation and reduce damage to the coronary arteries, thus reducing the incidence of coronary artery disease.When gamma globulin preparations are injected, allergic-like reactions may occur, with side effects such as anaphylaxis in severe cases, which may be caused by the presence of traces of IgG aggregates in the preparations, which activate complement and cause basophils to release bioactive substances, such as histamine, or by the formation of immune complexes between antigens in the body and antibodies in the preparations during infection, which activate complement [23–25]. In addition to Western medicine, Kawasaki disease is classified in Chinese medicine as a warm and hot disease, and therefore, Chinese medicine treatment focuses on clearing heat and detoxifying toxins and promoting blood circulation [26]. Kawasaki disease is an external or warm-heat toxin that enters through the nose and mouth, manifesting itself as a transmigration process of the defense (wei), vital energy (qi), nutrient (ying), and blood (xue), with the lung and stomach being the main organs affected, and the liver and kidneys may be involved [27]. The treatment is based on clearing heat and detoxification, activating blood circulation and resolving blood stasis, paying attention to nourishing the stomach and nourishing fluid, and protecting the heart [26,2 8]. In the treatment of KD, Chinese medicine is mainly based on the differentiation of Wei-Qi and Ying-Blood. The treatment can be carried out with Yin Qiao San, Qing Ying Tang, or Bamboo Leaf and Gypsum Tang [28]. As blood stasis is always present in Chuan teratology, blood stasis activators such as Salvia miltiorrhiza and Radix Paeoniae should be used throughout the treatment to control the abnormal increase of platelets, reduce platelet aggregation, lower blood viscosity, prevent coronary aneurysm, and shorten the course of treatment [28, 29].
## 5. Conclusion
To sum up, gamma globulin has a significant effect in the treatment of KD, which can improve the levels of white blood cells, platelets, CRP, ESR, VEGF, and endostatin in children and helps to inhibit the inflammatory response and significantly reduce coronary artery dilation. Echocardiography is of high value in the examination of children with KD. It can accurately detect the size, location, and inner diameter of coronary artery lesions and can effectively evaluate the therapeutic effect on children.
---
*Source: 2900378-2022-08-04.xml* | 2900378-2022-08-04_2900378-2022-08-04.md | 27,538 | Ultrasound Comparative Analysis of Coronary Arteries before and after Immune Blocking Therapy with Gamma Globulin in Children with Kawasaki Disease | Yi Yu; Jinhua Hu; Qun Xia; Juxia Huang; Yangmei Cheng; Fangling Wu; Yujing Liu; Jun Wang; Qiong Zhang | Evidence-Based Complementary and Alternative Medicine
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2900378 | 2900378-2022-08-04.xml | ---
## Abstract
Objective. To investigate the ultrasound characteristics and clinical efficacy of coronary arteries before and after immune blocking therapy with gamma globulin in children with Kawasaki disease. Methods. A total of 64 children with Kawasaki disease who were treated in our hospital from January 2018 to October 2021 were selected. All the children were given immune blocking therapy with gamma globulin on the basis of conventional treatment. The disappearance time of related symptoms and signs (fever, mucosal congestion, cervical lymphadenopathy, and swelling of the hands and feet) in children were counted. The white blood cell count (WBC), platelet count (PLT), C-reactive protein (CRP), and procalcitonin (PCT) levels of the children before and after treatment were compared, and the characteristics of coronary echocardiography before and after treatment were observed for analysis and discussion, to carefully observe whether the coronary artery involvement of the children was improved. Results. The inner diameter of the left and right coronary arteries significantly decreased (P<0.05), and the levels of leukocytes, platelets, CRP, erythrocyte sedimentation rate, vascular endothelial growth factor (VEGF), and endostatin were significantly decreased compared with those before treatment, with a statistical difference (P<0.05). Conclusion. The effect of gamma globulin in the treatment of Kawasaki disease is remarkable, which can improve the blood indexes, VEGF, and endostatin levels in children, significantly reduce coronary dilatation, and reduce the incidence of coronary artery disease. Echocardiography is of high value in the examination of children with Kawasaki disease, which can accurately detect the size, location, and inner diameter of coronary artery lesions, and can effectively evaluate the treatment effect on children.
---
## Body
## 1. Introduction
Kawasaki disease (KD) is a common acute fever disease in pediatrics [1]. The main pathological characteristics are systemic arteritis and arteriolitis, and the most serious harm is cardiovascular damage [2, 3]. It has been shown that the incidence is slightly higher in Asian children than in Europe and the United States and is common not only in children aged 6 months to 5 years but also in school-aged children and rarely in adults, with a male to female ratio of approximately 1.62 : 1 [4]. It is mainly manifested as coronary artery lesions, including coronary artery dilatation and coronary aneurysm, which is the most important factor affecting the prognosis of children. Clinical manifestations include rash, fever, rigid edema of the hands and feet, and ocular conjunctival congestion [5]. KD is a self-limiting disease. Although the prognosis is good, if the correct and effective treatment measures are not received in the early stage, it can affect the small and medium arteries of the whole body, easily induce coronary artery damage, and even induce myocardial infarction and sudden death in severe cases, which seriously threatens the safety and quality of life of children [6, 7].As an immunoglobulin, gamma globulin is mostly used for the treatment of infectious diseases clinically [8]. It can block the Fc receptors on the surface of platelets, mononuclear phagocytes, and vascular endothelial cells and reduce the vascular immune inflammatory response [9, 10]. Immunoglobulin contains various antibodies required by the body to enhance the immune function and prevent infection. It has been widely used in the clinical treatment of KD, and its clinical efficacy is certain, as it can rapidly reduce fever, eliminate acute symptoms, and reduce the incidence of coronary artery lesions [11, 12]. In this study, we observed the characteristics of coronary ultrasound before and after gamma globulin immunoblockade treatment in children with KD, which provides a clinical reference for gamma globulin treatment of KD to inhibit the aggravation of coronary artery damage.
## 2. Materials and Methods
### 2.1. Research Objects
A prospective analysis was performed on 64 children with KD who were treated in our hospital from January 2018 to October 2021. All the children were given gamma globulin immunosuppressive therapy on the basis of conventional treatment. There were 40 males and 24 females; the age ranged from 72 days to 15 years, with an average of (3.04 ± 0.34) years.
#### 2.1.1. Inclusion Criteria
The inclusion criteria were as follows: patients met the clinical diagnostic criteria for Kawasaki disease in the 2017 edition of “Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association” [13], patients did not received relevant treatment before admission, patients had complete clinical data and could cooperate with the whole process of treatment and examination, and patients with no history of hypersensitivity to gamma globulin drugs.
#### 2.1.2. Exclusion Criteria
The exclusion criteria were as follows: patients with congenital heart disease, patients with a history of aspirin or intravenous immunoglobulin therapy, and patients with mental system disease. The above studies were conducted with the informed consent of the families of the children and were approved by the ethics committee of our hospital.
### 2.2. Methods
After admission, all the children received the same routine treatment plan, such as atomization of phlegm, physical cooling, routine use of antibiotics, and nutritional support. On this basis, the treatment was treated by intravenous infusion of gamma globulin (manufacturing company: Guizhou Taibang Biological Products Co., Ltd., Chinese medicine Zhunzi: S20023034, specification: 50 mL: 2.5 g/piece), according to 2 g/kg single dose, intravenous infusion, slowly completed within 10–12 h; if the reaction is poor, the drug can be repeated once on the second day, repeat twice at most; aspirin (Shaanxi Yishengtang Pharmaceutical Co., Ltd., Chinese medicine Zhunzi: H61023268) was taken orally, once a day, 30–50 mg/kg each time. After 3 days of administration, if the child was antipyretic, the dosage was reduced to 4 mg/kg until the coronary artery lesions and erythrocyte sedimentation rate returned to normal.
### 2.3. Evaluation Indicators and Judgment Criteria
(1) Time to disappearance of symptoms and signs and length of hospital stay: during the whole treatment process, the time to disappearance of signs and symptoms, such as fever, mucosal congestion, cervical lymphadenopathy, and swelling of the hands and feet, and hospitalization time of the children were counted. (2) The levels of serum-related indexes were compared before and after treatment. First, 5.0 ml of peripheral venous blood was drawn and centrifuged at 3000 r/min for 5 min by the Beckman Microfuge 20 medical centrifuge. The upper serum was taken and stored in a refrigerator at −20°C. The Beckman Coulter dxh 600 blood routine tester was used to measure the blood routine-related indicators of the children before and after treatment for 2 weeks, including C-reactive protein (CRP), platelets, white blood cells, erythrocyte sedimentation rate, and other indicators. VEGF and endostatin were detected by ELISA. (3) The incidence of coronary artery disease (CAL) was detected by echocardiography. The diagnostic criteria of Kawasaki disease complicated with coronary artery disease are as follows: (i) coronary artery aneurysm (CAA), coronary artery dilation of different shapes, coronary artery diameter 4–7 mm; (ii) giant coronary artery aneurysm (GCAA), coronary artery diameter ≥ 8 mm; and (iii) Coronary artery dilatation, coronary artery ≥ 2.5 mm in younger than 3 years old, coronary artery ≥ 3.0 mm in ≥ 3 years old and < 9 years old, coronary artery ≥ 3.2 mm in ≥ 9 years old and < 14 years old, and 33.5 mm in those aged 14 and older.
### 2.4. Statistical Methods
SPSS 24.0 was used for the statistical analysis of the data. The measurement data were analyzed by thet-test of the opposite samples, represented by (x¯±s), and the enumeration data were represented by the chi-square test, which was represented by the percentage, and P<0.05 indicated that the difference was statistically significant.
## 2.1. Research Objects
A prospective analysis was performed on 64 children with KD who were treated in our hospital from January 2018 to October 2021. All the children were given gamma globulin immunosuppressive therapy on the basis of conventional treatment. There were 40 males and 24 females; the age ranged from 72 days to 15 years, with an average of (3.04 ± 0.34) years.
### 2.1.1. Inclusion Criteria
The inclusion criteria were as follows: patients met the clinical diagnostic criteria for Kawasaki disease in the 2017 edition of “Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association” [13], patients did not received relevant treatment before admission, patients had complete clinical data and could cooperate with the whole process of treatment and examination, and patients with no history of hypersensitivity to gamma globulin drugs.
### 2.1.2. Exclusion Criteria
The exclusion criteria were as follows: patients with congenital heart disease, patients with a history of aspirin or intravenous immunoglobulin therapy, and patients with mental system disease. The above studies were conducted with the informed consent of the families of the children and were approved by the ethics committee of our hospital.
## 2.1.1. Inclusion Criteria
The inclusion criteria were as follows: patients met the clinical diagnostic criteria for Kawasaki disease in the 2017 edition of “Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association” [13], patients did not received relevant treatment before admission, patients had complete clinical data and could cooperate with the whole process of treatment and examination, and patients with no history of hypersensitivity to gamma globulin drugs.
## 2.1.2. Exclusion Criteria
The exclusion criteria were as follows: patients with congenital heart disease, patients with a history of aspirin or intravenous immunoglobulin therapy, and patients with mental system disease. The above studies were conducted with the informed consent of the families of the children and were approved by the ethics committee of our hospital.
## 2.2. Methods
After admission, all the children received the same routine treatment plan, such as atomization of phlegm, physical cooling, routine use of antibiotics, and nutritional support. On this basis, the treatment was treated by intravenous infusion of gamma globulin (manufacturing company: Guizhou Taibang Biological Products Co., Ltd., Chinese medicine Zhunzi: S20023034, specification: 50 mL: 2.5 g/piece), according to 2 g/kg single dose, intravenous infusion, slowly completed within 10–12 h; if the reaction is poor, the drug can be repeated once on the second day, repeat twice at most; aspirin (Shaanxi Yishengtang Pharmaceutical Co., Ltd., Chinese medicine Zhunzi: H61023268) was taken orally, once a day, 30–50 mg/kg each time. After 3 days of administration, if the child was antipyretic, the dosage was reduced to 4 mg/kg until the coronary artery lesions and erythrocyte sedimentation rate returned to normal.
## 2.3. Evaluation Indicators and Judgment Criteria
(1) Time to disappearance of symptoms and signs and length of hospital stay: during the whole treatment process, the time to disappearance of signs and symptoms, such as fever, mucosal congestion, cervical lymphadenopathy, and swelling of the hands and feet, and hospitalization time of the children were counted. (2) The levels of serum-related indexes were compared before and after treatment. First, 5.0 ml of peripheral venous blood was drawn and centrifuged at 3000 r/min for 5 min by the Beckman Microfuge 20 medical centrifuge. The upper serum was taken and stored in a refrigerator at −20°C. The Beckman Coulter dxh 600 blood routine tester was used to measure the blood routine-related indicators of the children before and after treatment for 2 weeks, including C-reactive protein (CRP), platelets, white blood cells, erythrocyte sedimentation rate, and other indicators. VEGF and endostatin were detected by ELISA. (3) The incidence of coronary artery disease (CAL) was detected by echocardiography. The diagnostic criteria of Kawasaki disease complicated with coronary artery disease are as follows: (i) coronary artery aneurysm (CAA), coronary artery dilation of different shapes, coronary artery diameter 4–7 mm; (ii) giant coronary artery aneurysm (GCAA), coronary artery diameter ≥ 8 mm; and (iii) Coronary artery dilatation, coronary artery ≥ 2.5 mm in younger than 3 years old, coronary artery ≥ 3.0 mm in ≥ 3 years old and < 9 years old, coronary artery ≥ 3.2 mm in ≥ 9 years old and < 14 years old, and 33.5 mm in those aged 14 and older.
## 2.4. Statistical Methods
SPSS 24.0 was used for the statistical analysis of the data. The measurement data were analyzed by thet-test of the opposite samples, represented by (x¯±s), and the enumeration data were represented by the chi-square test, which was represented by the percentage, and P<0.05 indicated that the difference was statistically significant.
## 3. Results
### 3.1. Disappearance Time of Symptoms and Signs and Length of Hospital Stay
The time when the symptoms and signs disappeared and the length of hospital stay are given in Table1.Table 1
Disappearance time of symptoms and signs and length of hospital stay.
CasesAntipyretic timeCervical lymphadenopathy resolution timeMucous membrane hyperemia disappearance timeHand and foot swelling subsides timeHospital stay763.79 ± 0.516.81 ± 1.654.03 ± 0.774.19 ± 1.258.67 ± 0.76
### 3.2. Serum-Related Index Levels before and after Treatment in Children
Leukocyte level in the child after gamma globulin treatment was 8.24 ± 2.75 × 109/L compared to 17.14 ± 4.78 × 109/L before treatment. Platelet level in the child after gamma globulin treatment was 230.84 ± 54.81 × 109/L compared to 380.23 ± 109.73 × 109/L before treatment; CRP levels were 70.33 ± 8.66 mg/L before treatment and 70.33 ± 8.66 mg/L after treatment; ESR levels were 99.06 ± 10.24 mm/h before treatment and 99.06 ± 10.24 mm/h after treatment; the serum levels of the relevant indicators decreased in all children after gamma globulin treatment (P<0.001) (Table 2).Table 2
Comparison of serum-related indexes before and after treatment in children.
Leukocyte (×109/L)Platelets (×109/L)CRP (mg/L)ESR (mm/h)Before treatment17.14 ± 4.78380.23 ± 109.7370.33 ± 8.6699.06 ± 10.24After treatment8.24 ± 2.75230.84 ± 54.8120.15 ± 6.0532.41 ± 4.52t14.0710.61841.4151.91P< 0.001< 0.001< 0.001< 0.001
### 3.3. Comparison of VEGF and Endostatin Levels before and after Treatment in Children
After gamma globulin treatment, VEGF levels were 41.73 ± 6.31 pg/L and endothelial inhibitory hormone levels were 16.53 ± 1.47 ng/L. Before treatment, VEGF levels were 198.47 ± 17.36 pg/L and endothelial inhibitory hormone levels were 40.62 ± 2.13 ng/L.Before treatment, VEGF levels were 198.47 ± 17.36 pg/L and endothelial inhibitory hormone levels were 40.62 ± 2.13 ng/L. VEGF and endothelial inhibitory hormone levels decreased significantly after treatment in children (P<0.001). After gamma globulin treatment, VEGF and endostatin were significantly lower than those before treatment (Table 3).Table 3
Comparison of VEGF and endostatin levels before and after treatment in children.
VEGF (pg/L)Endostatin (ng/L)Before treatment198.47 ± 17.3640.62 ± 2.13After treatment41.73 ± 6.3116.53 ± 1.47t73.97681.148P< 0.001< 0.001
### 3.4. Changes of Coronary Artery Diameter in Children before and after Treatment
After gamma globulin treatment, the internal diameter of the left coronary artery was 2.70 ± 0.86 mm and that of the right coronary artery was 2.90 ± 0.35 mm. After treatment, the internal diameter of the left coronary artery was 4.30 ± 1.13 mm and that of the right coronary artery was 3.10 ± 1.02 mm. The coronary artery internal diameter of the children improved significantly after treatment (P<0.001) (Table 4) (Figure 1).Table 4
Changes of coronary artery diameter before and after treatment in children.
Inner diameter of the left coronary artery (mm)Inner diameter of the right coronary artery (mm)Before treatment4.30 ± 1.133.10 ± 1.02After treatment2.70 ± 0.862.90 ± 0.35t9.8231.263P< 0.001< 0.001Figure 1
Changes in the inner diameter of the left and right coronary arteries before and after treatment. (a) The ultrasound results of the left coronary artery and (b) the right coronary artery before treatment. (c) The ultrasound results of the left coronary artery and (d) the right coronary artery three months after gamma globulin immunoblocking therapy.
(a)(b)(c)(d)
## 3.1. Disappearance Time of Symptoms and Signs and Length of Hospital Stay
The time when the symptoms and signs disappeared and the length of hospital stay are given in Table1.Table 1
Disappearance time of symptoms and signs and length of hospital stay.
CasesAntipyretic timeCervical lymphadenopathy resolution timeMucous membrane hyperemia disappearance timeHand and foot swelling subsides timeHospital stay763.79 ± 0.516.81 ± 1.654.03 ± 0.774.19 ± 1.258.67 ± 0.76
## 3.2. Serum-Related Index Levels before and after Treatment in Children
Leukocyte level in the child after gamma globulin treatment was 8.24 ± 2.75 × 109/L compared to 17.14 ± 4.78 × 109/L before treatment. Platelet level in the child after gamma globulin treatment was 230.84 ± 54.81 × 109/L compared to 380.23 ± 109.73 × 109/L before treatment; CRP levels were 70.33 ± 8.66 mg/L before treatment and 70.33 ± 8.66 mg/L after treatment; ESR levels were 99.06 ± 10.24 mm/h before treatment and 99.06 ± 10.24 mm/h after treatment; the serum levels of the relevant indicators decreased in all children after gamma globulin treatment (P<0.001) (Table 2).Table 2
Comparison of serum-related indexes before and after treatment in children.
Leukocyte (×109/L)Platelets (×109/L)CRP (mg/L)ESR (mm/h)Before treatment17.14 ± 4.78380.23 ± 109.7370.33 ± 8.6699.06 ± 10.24After treatment8.24 ± 2.75230.84 ± 54.8120.15 ± 6.0532.41 ± 4.52t14.0710.61841.4151.91P< 0.001< 0.001< 0.001< 0.001
## 3.3. Comparison of VEGF and Endostatin Levels before and after Treatment in Children
After gamma globulin treatment, VEGF levels were 41.73 ± 6.31 pg/L and endothelial inhibitory hormone levels were 16.53 ± 1.47 ng/L. Before treatment, VEGF levels were 198.47 ± 17.36 pg/L and endothelial inhibitory hormone levels were 40.62 ± 2.13 ng/L.Before treatment, VEGF levels were 198.47 ± 17.36 pg/L and endothelial inhibitory hormone levels were 40.62 ± 2.13 ng/L. VEGF and endothelial inhibitory hormone levels decreased significantly after treatment in children (P<0.001). After gamma globulin treatment, VEGF and endostatin were significantly lower than those before treatment (Table 3).Table 3
Comparison of VEGF and endostatin levels before and after treatment in children.
VEGF (pg/L)Endostatin (ng/L)Before treatment198.47 ± 17.3640.62 ± 2.13After treatment41.73 ± 6.3116.53 ± 1.47t73.97681.148P< 0.001< 0.001
## 3.4. Changes of Coronary Artery Diameter in Children before and after Treatment
After gamma globulin treatment, the internal diameter of the left coronary artery was 2.70 ± 0.86 mm and that of the right coronary artery was 2.90 ± 0.35 mm. After treatment, the internal diameter of the left coronary artery was 4.30 ± 1.13 mm and that of the right coronary artery was 3.10 ± 1.02 mm. The coronary artery internal diameter of the children improved significantly after treatment (P<0.001) (Table 4) (Figure 1).Table 4
Changes of coronary artery diameter before and after treatment in children.
Inner diameter of the left coronary artery (mm)Inner diameter of the right coronary artery (mm)Before treatment4.30 ± 1.133.10 ± 1.02After treatment2.70 ± 0.862.90 ± 0.35t9.8231.263P< 0.001< 0.001Figure 1
Changes in the inner diameter of the left and right coronary arteries before and after treatment. (a) The ultrasound results of the left coronary artery and (b) the right coronary artery before treatment. (c) The ultrasound results of the left coronary artery and (d) the right coronary artery three months after gamma globulin immunoblocking therapy.
(a)(b)(c)(d)
## 4. Discussion
KD, also known as cutaneous mucosal lymph node syndrome, is an acute systemic vasculitis and a common autoimmune disease in pediatrics [14]. The incidence of KD is increasing year by year, often impairing cardiac function in children and leading to coronary heart disease, and is gradually attracting widespread medical attention [15]. Although the pathogenesis has not been elucidated, genetic studies have identified several susceptibility genes for KD and its sequelae in different ethnic groups, including FCGR2A and CD40 [16]. Recent studies have found [17] that KD may be induced by the entry of one or more pathogenic microorganisms into the organism and is a systemic vascular inflammatory disease characterized by immune activation or immune dysfunction. Gamma globulin contains multiple antibodies in serum of healthy individuals and is a passive immunotherapy [18, 19]. It has a neutralizing effect on autoantibodies, can relieve the effect of microbial toxins and vascular inflammation, reduce the level of inflammatory factors, promote the negative feedback of immune regulatory cells, improve cellular immunity and humoral disorders, and control the deterioration of symptoms. The application of high-dose gamma globulin in the acute phase can block all immune responses that cause vascular damage and reduce platelet aggregation, thereby reducing coronary artery damage to a certain extent, that is, reducing coronary artery dilatation. Reducing the rate of change and giving gamma globulin therapy to children with KD in a timely manner to prevent complications such as myocardial infarction and impaired coronary artery function in children with KD significantly improves the safety and health of children [20, 21].The results of this study showed that after the children received intravenous gamma globulin, the inner diameter of the left and right coronary arteries was significantly reduced (P<0.05), and the levels of white blood cells, platelets, CRP, ESR, VEGF, and endostatin were significantly decreased compared with those before treatment (P<0.05). The mechanism of action may be the more types and components of antibodies contained in gamma globulin, the more IVIG can inhibit the activity of FC receptors on lymphocytes, monocytes, macrophages, and other immune cell walls. (1) The more types and components of antibodies contained in gamma globulin, the more obvious the inhibitory effect of IVIG on the FC receptor activity of lymphocytes, mononuclear macrophages, and other immune cell walls, thus weakening the activation of a large number of immune cells, which can inhibit the inflammatory response, effectively relieve the toxic reactions in children, reduce the stimulation of inflammatory factors to the endovascular cortex, and reduce the occurrence of coronary artery lesions by improving the level of immune factors in children in the short term [22]; (2) activation of platelet-derived growth factors and their vascular pathways, reducing the degree of endothelial damage and thus the degree of vascular immune damage; (3) inhibition of B cell lymphocyte activity, resistance to toxin damage to children’s vascular cells, and competitive binding requiring relevant receptors on the vessel wall, leading to massive immune complex deposition; (4) reduction of platelet levels, reducing the risk of thrombosis, which can effectively improve coronary artery dilation and reduce damage to the coronary arteries, thus reducing the incidence of coronary artery disease.When gamma globulin preparations are injected, allergic-like reactions may occur, with side effects such as anaphylaxis in severe cases, which may be caused by the presence of traces of IgG aggregates in the preparations, which activate complement and cause basophils to release bioactive substances, such as histamine, or by the formation of immune complexes between antigens in the body and antibodies in the preparations during infection, which activate complement [23–25]. In addition to Western medicine, Kawasaki disease is classified in Chinese medicine as a warm and hot disease, and therefore, Chinese medicine treatment focuses on clearing heat and detoxifying toxins and promoting blood circulation [26]. Kawasaki disease is an external or warm-heat toxin that enters through the nose and mouth, manifesting itself as a transmigration process of the defense (wei), vital energy (qi), nutrient (ying), and blood (xue), with the lung and stomach being the main organs affected, and the liver and kidneys may be involved [27]. The treatment is based on clearing heat and detoxification, activating blood circulation and resolving blood stasis, paying attention to nourishing the stomach and nourishing fluid, and protecting the heart [26,2 8]. In the treatment of KD, Chinese medicine is mainly based on the differentiation of Wei-Qi and Ying-Blood. The treatment can be carried out with Yin Qiao San, Qing Ying Tang, or Bamboo Leaf and Gypsum Tang [28]. As blood stasis is always present in Chuan teratology, blood stasis activators such as Salvia miltiorrhiza and Radix Paeoniae should be used throughout the treatment to control the abnormal increase of platelets, reduce platelet aggregation, lower blood viscosity, prevent coronary aneurysm, and shorten the course of treatment [28, 29].
## 5. Conclusion
To sum up, gamma globulin has a significant effect in the treatment of KD, which can improve the levels of white blood cells, platelets, CRP, ESR, VEGF, and endostatin in children and helps to inhibit the inflammatory response and significantly reduce coronary artery dilation. Echocardiography is of high value in the examination of children with KD. It can accurately detect the size, location, and inner diameter of coronary artery lesions and can effectively evaluate the therapeutic effect on children.
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*Source: 2900378-2022-08-04.xml* | 2022 |
# Design of a Regional Economic Forecasting Model Using Optimal Nonlinear Support Vector Machines
**Authors:** Tong Zhang
**Journal:** Computational Intelligence and Neuroscience
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2900434
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## Abstract
Forecasting regional economic activity is a progressively significant element of regional economic research. Regional economic prediction can directly assist local, national, and subnational policymakers. Regional economic activity forecast can be employed for defining macroeconomic forces, such as prediction of stock market and cyclicality of national labor market movement. The recent advances of machine learning (ML) models can be employed to solve the time series prediction problem. Since the parameters involved in the ML model considerably influence the performance, the parameter tuning process also becomes essential. With this motivation, this study develops a quasioppositional cuckoo search algorithm (QOCSA) with a nonlinear support vector machine (SVM)-based prediction model, called QOCSO-NLSVM for regional economic prediction. The goal of the QOCSO-NLSVM technique is to identify the present regional economic status. The QOCSO-NLSVM technique has different stages such as clustering, preprocessing, prediction, and optimization. Besides, the QOCSO-NLSVM technique employs the density-based clustering algorithm (DBSCAN) to determine identical states depending upon the per capita NSDP growth trends and socio-economic-demographic features in a state. Moreover, the NLSVM model is employed for the time series prediction process and the parameters involved in it are optimally tuned by the use of the QOCSO algorithm. To showcase the effective performance of the QOCSO-NLSVM technique, a wide range of simulations take place using regional economic data. To determine the current economic situation in a region, the QOCSO-NLSVM technique is used. The simulation results reported the better performance of the QOCSO-NLSVM technique over recent approaches. The QOCSO-NLSVM technique generated effective results with a minimal mean square error of 70.548 or greater. Astonishingly good results were obtained using the QOCSO-NLSVM approach, which had the lowest root mean square error (RMSE) of 8.399.
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## Body
## 1. Introduction
The forecasting method predicts future value based on a provided time series data set by making assumptions on future trends and estimating historical data. This is employed for several regions of the decision-making process, like industrial process control, risk management, operations management, demography, and economics [1]. Forecasting is an important problem spanning several domains, involving finance, social science, government, economics, environmental science, politics, medicine, business, and industry. The forecasting problem is categorized as long-term, short-term, and medium-term [2, 3].Forecasting regional economic activity is an essential component of regional economic study. The regional economic prediction could directly assist business executives, local, subnational, and national policymakers. These two business executives and policymakers require precise prediction of key economic aggregates, namely, employment, output, and income for medium-long term planning purposes [4]. Regional economic activity forecasts have been employed for explaining macroeconomic forces, involving the cyclicality of national labour market movements and predicting the stock market. Further, multinational agencies and international investors engaged in megaprojects at a regional level also require precise predictions for investment planning reasons [5]. When there is no paucity of research on predicting national economic indicators, the research on regional economic prediction is limited for innovative economies, and in the case of developing nations, zilch [6]. Problems with short-term forecasting are those that deal with predicting events in a shorter period of time (months, days, and weeks). Forecasting concerns could go much beyond 1-2 years into the future, with medium-term forecasts extending into the future as well.The forecasting method connected to economic problems is utilized for predicting economic variables in several countries. The industry volatility prediction, critical to several important problems in business [7], and the prediction of the unemployment rates that define the country’s economic and social development [8, 9]. Radial basis function networks (RBF) and backpropagation are the ANN architectures that are used in economic fields. The artificial neural networks (ANN) technique was broadly examined in economic analysis. The ANN is a computation system that is performed in hardware or software under the effect of biological studies about the human brain. Several authors admit that the ANN method is the better performing nonlinear analysis technique as well as one of the best predictors [10]. The ANN architecture employed in economic fields is radial basis function networks (RBF) and backpropagation.This study designs a quasioppositional cuckoo search algorithm (QOCSA) with a nonlinear support vector machine (SVM)-based prediction model, called QOCSO-NLSVM for regional economic prediction. The QOCSO-NLSVM technique involves the design of the density-based clustering algorithm (DBSCAN) to determine the identical states depending upon the per capita NSDP growth trends and socioeconomic-demographic features in a state. Besides, the NLSVM model is elected for the time series prediction process and the parameters involved in it are optimally tuned by the use of the QOCSO algorithm. The experimental validation of the QOCSO-NLSVM technique and the results are examined in various aspects.The rest of the research work is organized as follows. Section2 provides the recently developed techniques, Section 3 elaborates the QOCSO-NLSVM technique. Then, Section 4 provides the performance validation, and Section 5 concludes the outcomes of the research.
## 2. Literature Review
Mishra and Ayyub [11] introduced a DL architecture in which the hierarchical clustering analysis (HCA) is utilized for predicting growth. The presented method comprises HCA and DTW techniques that are initially applied for identifying similar socio-economic-demographic features within a provided state and similar states according to per capita NSDP growth trends, to create a fine-tuned training dataset for predicting all the states’ NSDP per capita growth. Lv et al. [12] developed a LightGBM-enhanced LSTM for realizing stock price prediction, and LSTM is utilized for predicting the Shenzhen and Shanghai 300 indexes, respectively. The simulation result shows that the LightGBM-LSTM has a better capacity for tracking stock index price trends and the maximum prediction performance, and its effects are superior to the RNN and GRU methods. LightGBM-optimized LSTM for short-term stock price forecasting. To compare its performance with other deep network models such as RNN (recurrent neural network) and GRU (gated recurrent unit), the LightGBM-LSTM, RNN, and GRU are used to predict the Shanghai and Shenzhen 300 indexes, respectively. Experiment results demonstrate that the LightGBM-LSTM has the highest prediction accuracy and the best ability to track stock index price trends.Zhu et al. [13] designed an experiment whose samples originated from information on 7 quoted core enterprises (CEs) and 46 quoted SMEs in the Chinese security markets. Matta et al. [14] introduced a relative assessment of various prediction techniques using the Gaussian process regression and ANN methods (MLP and RBFNN). Two real-time datasets were utilized for evaluating the prediction method presented in the study. These datasets were normalized to values amongst one and zero. Next, the data training was implemented and, when it was constructed, a system was utilized for generating the predictions. Therefore, observations were made to validate how precisely the fitted method predicts the values.Chatzis et al. [15] integrated distinct ML methods that were proposed with daily currency, stock, and bond data from thirty-nine countries that cover a larger spectrum of economies. It especially leverages the advantages of a sequence of techniques that includes Classifier Trees, SVM, NN, RF, XGBoost, and DNN. Sun et al. [16] verified the cointegration relationships and Granger causality between tourist arrivals in Beijing and the internet search index. This experiment result suggests that compared to standard methods, the presented KELM model that incorporates tourist volume series with Google and Baidu Index could significantly enhance the prediction performances in terms of robustness analysis and forecasting accuracy.
## 3. The Proposed Model
In this study, an effective QOCSO-NLSVM technique has been developed for regional economic prediction. The QOCSO-NLSVM technique encompasses several subprocesses, namely, DTW-based preprocessing, DBSCAN-based clustering, NLSVM-based prediction, and QOCSO-based parameter optimization. Figure1 illustrates the overall working process of the QOCSO-NLSVM technique.Figure 1
System architecture of the QOCSO-NLSVM method.
### 3.1. Data Preprocessing
One of the primary methods used to capture similarities among two regions, or among pairs of factors within a provided region according to time-series data is named dynamic time warping (DTW). DTW is an effective method utilized for learning similarity based on distance between two sequences that might differ in speed and quantifying time-based similarities among any two pairs. Generally, DTW is an ML method which estimates an optimum match between two provided sequences with some restrictions. The sequence is “warped” nonlinearly in the time dimension to define measures of their similarity, independent of nonlinear variation in the time dimension. The Euclidean distance uses the distance among every pair of the time series and compares it with the Euclidean distance. Simultaneously, the DTW searches for optimal alignments among the two-time series. Furthermore, all the points are utilized for comparing the points to make the best possible alignments among the two-time series according to their distance matrix.
### 3.2. Process Involved in the DBSCAN Technique
DBSCAN might find distinct clusters based on the assessed density distribution. It could recognise structured groupings without knowing their numbers. The following illustrates DBSCAN’s basic premise: DBSCAN finds each point in the neighbourhood of a random unvisited pointp, where it denotes the neighbourhood’s maximum radius from p. To construct a dense zone, MinPts is the minimum number of points required. When MinPts is in the distance, p denotes a core point. When p is a core point, all points in its vicinity are grouped together. DBSCAN detects each density-reachable point in the cluster and adds it to a comparable cluster. When a point q is densely approachable from other core points but its neighbourhood is less than MinPts, it is a border point. An outlier or noisy point is one that is not accessible from other locations. DBSCAN achieves clustering by extracting clusters consecutively. Rep until no more density-reachable points are identified, and the final cluster is reached. DBSCAN divides a set of points into low-noise border points and high-density. The purpose of DBSCAN is to identify identical states based on a state's per capita NSDP growth trends and socioeconomic-demographic characteristics. DBSCAN was capable of detecting a variety of clusters based on the density distribution that was assessed. The DBSCAN methodology permits the calculation of identical states based on per capita income.Assume two pointsx and y, dx,y represent the similarities among them, Γεx denotes the ε-neighbourhood of x, in which Γεx=y∈V|dx,y≤ε⋅ρx=Γεx indicates the density value of x:(1)Sx=1,core point withρx≥MinPts,0,border point with1<ρx<MinPts,−1,noise withρx=1.
### 3.3. Structure of the NLSVM Model
During the prediction process, the NLSVM model receives the clustered data as input to predict the output. Assume a trained setxk,ykk=1N with input data xk∈ℝn and respective binary class label yk∈−1,+1, the SVM classification initiates from the subsequent assumption:(2)wTφxk+b≥+1,ifyk=+1,wTφxk+b≤−1,ifyk=−1.That is equal to(3)ykwTφxk+b≥1,k=1,…,N.Now, the nonlinear functionφ·:ℝn⟶ℝnh maps the input space to a high-dimensional feature space. It is noteworthy that the nh dimension of this space is determined in an implicit manner (it is an infinite dimension). The b represent a bias as follows:(4)yx=signwTφx+b.But, at the same time, it is never evaluated in this form. One determines the optimization issue:(5)minJw,ξ=12wTw+c∑k=1Nξk,subjected to(6)ykwTφxk+b≥1−ξk,k=1,…,N,ξk≥0,k=1,…,N.To permit misclassification in the subset of inequalities (because of overlapping distribution), the minimalization ofw2 corresponds to a maximalization of the margin among the two classes. c indicates a positive real constant and must be taken into account as a tuning parameter. The Lagrangian can be expressed as follows [17]:(7)Lw,b,ξ;α,ν=Jw,ξ−∑k=1NαkykwTφxk+b−1+ξk−∑k=1Nνkξk.The Lagrange multiplier isαk≥0,νk≥0,k=1,N. Figure 2 depicts the SVM hyperplane. It is familiar from the optimization concept that the solutions are considered by the saddle points of the Lagrangian:(8)maxα,vminw,b,ξℒw,b,ξ;α,ν.Figure 2
SVM hyperplane.One attains(9)∂L∂w=0⟶w=∑k=1Nαkykφxk,∂L∂b=0⟶∑k=1Nαkyk=0,∂L∂ξk=0⟶0≤αk≤c,k=1,…,N.By substitutingw in the Lagrangian, one attains the subsequent binary problems (in the Lagrange multiplier α), i.e., the quadratic programming problems:(10)maxαQα=−12∑k,l=1NykylKxk,xlαkαl+∑k=1Nαk.Thus,(11)∑k=1Nαkyk=0,0≤αk≤c,k=1,…,N.Noww and φxk are not estimated. According to the Mercer condition, one takes a kernel as(12)Kxk,xl=φxkTφxl.Lastly, in binary space, the nonlinear SVM classifiers become(13)yx=sign∑k=1NαkykKx,xk+b.αk is a positive real constant, and b is a real constant. The nonzero Lagrange multiplier αk is known as support value. The respective data point is known as a support vector and is placed near the decision boundary. This is the data point that contributes to the classification method. The bias b follows from the KKT condition that isn’t considered further.Various selections for the kernelK·,· are feasible.(i)
Kx,xk=xkTx (linear SVM)(ii)
Kx,xk=xkTx+1d (polynomial SVM of degree d)(iii)
Kx,xk=exp−x−xk22/σ2 (RBF kemel)(iv)
Kx,xk=tanhκxkTx+θ (MLP SVM)The Mercer conditions hold for eachσ value in the RBF case, but not for each feasible selection of κ,θ in the MLP case. In the case of an MLP or RBF kernel, the amount of hidden units corresponds to the number of support vectors.
### 3.4. Design of the QOCSO Algorithm for Parameter Tuning
For optimally tuning the weight values of the NLSVM model, the QOCSO algorithm is utilized. The CSO algorithm is assumed as a metaheuristic technique that was primarily established by Yang and Deb [18]. Actually, this CSO method simulates the breeding performance of cuckoo birds that are supposed to be a type of parasitism. The cuckoo birds place their eggs from other nests and play to host the egg. The cuckoo birds attempt for raising the hatch possibility of their individual eggs by generating them the same as the host egg with respect to size, shape, and colour, or by throwing other native eggs (Algorithm 1).Algorithm 1: Pseudocode of the CSO algorithm.
Begin.Objective functions off(x), x = (x1, x2, …, xd)TPopulations initialization ofn host nests xi,While (t < Maximum_iteration) or (termination condition)Get a cuckoo arbitrarily via Lévy flightDetermine the qualities/fitness asFiSelect nest amongst (n, j) arbitrarilyIf (Fi ≥ Fj),Substitutej in newly attained solution;EndAn fraction (pa), poor nests are discarded and new one is derived;Retain optimal solution, (with quality solution);Sort the solutions and determine current bestEndPostprocess and visualize resultsEndIn the CSO technique, cuckoo eggs from distinct nests signify the generation of candidate solutions to optimize problems. Actually, the search starts with particular nests with a solution per nest. This solution was progressed dependent upon the model of cuckoo’s recognition (p) which was inspired by eliminating the solution of exchanging novel ones.In the CSO method, a random walk was utilized dependent upon the Lévy flight distribution for producing novel candidate solutions (cuckoos) in the present one as follows:(14)cuckooit+1=cuckooit+a⊕Levyλ,where cuckooit+1 refers the ith cuckoo value t. An a and λ stand for step sizes (generally fixed to one) and coefficients 1<λ<3 correspondingly. A number of novel solutions were created in the optimum present ones by Lévy walks for performing a local search with self‐improvement [19]. Besides, a few novel solutions were created away from the optimum present ones. This reduces the chance of getting stuck from the local minimal and ensures the searching ability. The CS execution also makes sure elitism as the optimal nest is retained under the iteration.The OBL method was proposed with the aim of decreasing the computation time and improving the ability of various EAs [20]. Therefore, the comparisons among an arbitrary CSO algorithm and its opposite might result in the global optimal with fast convergence rates. Further, the quasiopposite number and showed that it is nearer to the optimum solution when compared to the opposite number. Therefore, the population initialization of this method is created according to the QOBL concept. For arbitrary number χ∈a,b , its opposite number χ0 is represented as follows:(15)x0=a+b−x.However, the opposite point for multidimensional searching space (dimension) is determined by the following equation:(16)x0i=aj+bi−xi,i=1,2,…,d.The quasiopposite no.xqo of arbitrary no. χ∈a,b is represented as follows [21]:(17)xqo=randa+b2,x0.Likewise, the quasiopposite point for multidimensional searching space (d dimension) is determined by the following equation:(18)xqoi=randai+bi2,x0i.For obtaining an objective function that could generalize the SVM outcome with no utilization of testing data, the cross validation approach is utilized. The cross validation process partitions the training datasetD randomly into S different parts Gs,s=1,…,S, and utilizes (S − 1) parts to train the model and to test the model. This process gets iterated for S times by varying the lasting parts, and the generalization efficiency can be determined by the use of MSE (mean squared error) over every test result.(19)MSECV=1N∑s=1S∑i∈Gsyi−fxi|θs2,where Gs indicates the s-th part for the testing process and θs signifies the solution vector attained at the time of training process.
## 3.1. Data Preprocessing
One of the primary methods used to capture similarities among two regions, or among pairs of factors within a provided region according to time-series data is named dynamic time warping (DTW). DTW is an effective method utilized for learning similarity based on distance between two sequences that might differ in speed and quantifying time-based similarities among any two pairs. Generally, DTW is an ML method which estimates an optimum match between two provided sequences with some restrictions. The sequence is “warped” nonlinearly in the time dimension to define measures of their similarity, independent of nonlinear variation in the time dimension. The Euclidean distance uses the distance among every pair of the time series and compares it with the Euclidean distance. Simultaneously, the DTW searches for optimal alignments among the two-time series. Furthermore, all the points are utilized for comparing the points to make the best possible alignments among the two-time series according to their distance matrix.
## 3.2. Process Involved in the DBSCAN Technique
DBSCAN might find distinct clusters based on the assessed density distribution. It could recognise structured groupings without knowing their numbers. The following illustrates DBSCAN’s basic premise: DBSCAN finds each point in the neighbourhood of a random unvisited pointp, where it denotes the neighbourhood’s maximum radius from p. To construct a dense zone, MinPts is the minimum number of points required. When MinPts is in the distance, p denotes a core point. When p is a core point, all points in its vicinity are grouped together. DBSCAN detects each density-reachable point in the cluster and adds it to a comparable cluster. When a point q is densely approachable from other core points but its neighbourhood is less than MinPts, it is a border point. An outlier or noisy point is one that is not accessible from other locations. DBSCAN achieves clustering by extracting clusters consecutively. Rep until no more density-reachable points are identified, and the final cluster is reached. DBSCAN divides a set of points into low-noise border points and high-density. The purpose of DBSCAN is to identify identical states based on a state's per capita NSDP growth trends and socioeconomic-demographic characteristics. DBSCAN was capable of detecting a variety of clusters based on the density distribution that was assessed. The DBSCAN methodology permits the calculation of identical states based on per capita income.Assume two pointsx and y, dx,y represent the similarities among them, Γεx denotes the ε-neighbourhood of x, in which Γεx=y∈V|dx,y≤ε⋅ρx=Γεx indicates the density value of x:(1)Sx=1,core point withρx≥MinPts,0,border point with1<ρx<MinPts,−1,noise withρx=1.
## 3.3. Structure of the NLSVM Model
During the prediction process, the NLSVM model receives the clustered data as input to predict the output. Assume a trained setxk,ykk=1N with input data xk∈ℝn and respective binary class label yk∈−1,+1, the SVM classification initiates from the subsequent assumption:(2)wTφxk+b≥+1,ifyk=+1,wTφxk+b≤−1,ifyk=−1.That is equal to(3)ykwTφxk+b≥1,k=1,…,N.Now, the nonlinear functionφ·:ℝn⟶ℝnh maps the input space to a high-dimensional feature space. It is noteworthy that the nh dimension of this space is determined in an implicit manner (it is an infinite dimension). The b represent a bias as follows:(4)yx=signwTφx+b.But, at the same time, it is never evaluated in this form. One determines the optimization issue:(5)minJw,ξ=12wTw+c∑k=1Nξk,subjected to(6)ykwTφxk+b≥1−ξk,k=1,…,N,ξk≥0,k=1,…,N.To permit misclassification in the subset of inequalities (because of overlapping distribution), the minimalization ofw2 corresponds to a maximalization of the margin among the two classes. c indicates a positive real constant and must be taken into account as a tuning parameter. The Lagrangian can be expressed as follows [17]:(7)Lw,b,ξ;α,ν=Jw,ξ−∑k=1NαkykwTφxk+b−1+ξk−∑k=1Nνkξk.The Lagrange multiplier isαk≥0,νk≥0,k=1,N. Figure 2 depicts the SVM hyperplane. It is familiar from the optimization concept that the solutions are considered by the saddle points of the Lagrangian:(8)maxα,vminw,b,ξℒw,b,ξ;α,ν.Figure 2
SVM hyperplane.One attains(9)∂L∂w=0⟶w=∑k=1Nαkykφxk,∂L∂b=0⟶∑k=1Nαkyk=0,∂L∂ξk=0⟶0≤αk≤c,k=1,…,N.By substitutingw in the Lagrangian, one attains the subsequent binary problems (in the Lagrange multiplier α), i.e., the quadratic programming problems:(10)maxαQα=−12∑k,l=1NykylKxk,xlαkαl+∑k=1Nαk.Thus,(11)∑k=1Nαkyk=0,0≤αk≤c,k=1,…,N.Noww and φxk are not estimated. According to the Mercer condition, one takes a kernel as(12)Kxk,xl=φxkTφxl.Lastly, in binary space, the nonlinear SVM classifiers become(13)yx=sign∑k=1NαkykKx,xk+b.αk is a positive real constant, and b is a real constant. The nonzero Lagrange multiplier αk is known as support value. The respective data point is known as a support vector and is placed near the decision boundary. This is the data point that contributes to the classification method. The bias b follows from the KKT condition that isn’t considered further.Various selections for the kernelK·,· are feasible.(i)
Kx,xk=xkTx (linear SVM)(ii)
Kx,xk=xkTx+1d (polynomial SVM of degree d)(iii)
Kx,xk=exp−x−xk22/σ2 (RBF kemel)(iv)
Kx,xk=tanhκxkTx+θ (MLP SVM)The Mercer conditions hold for eachσ value in the RBF case, but not for each feasible selection of κ,θ in the MLP case. In the case of an MLP or RBF kernel, the amount of hidden units corresponds to the number of support vectors.
## 3.4. Design of the QOCSO Algorithm for Parameter Tuning
For optimally tuning the weight values of the NLSVM model, the QOCSO algorithm is utilized. The CSO algorithm is assumed as a metaheuristic technique that was primarily established by Yang and Deb [18]. Actually, this CSO method simulates the breeding performance of cuckoo birds that are supposed to be a type of parasitism. The cuckoo birds place their eggs from other nests and play to host the egg. The cuckoo birds attempt for raising the hatch possibility of their individual eggs by generating them the same as the host egg with respect to size, shape, and colour, or by throwing other native eggs (Algorithm 1).Algorithm 1: Pseudocode of the CSO algorithm.
Begin.Objective functions off(x), x = (x1, x2, …, xd)TPopulations initialization ofn host nests xi,While (t < Maximum_iteration) or (termination condition)Get a cuckoo arbitrarily via Lévy flightDetermine the qualities/fitness asFiSelect nest amongst (n, j) arbitrarilyIf (Fi ≥ Fj),Substitutej in newly attained solution;EndAn fraction (pa), poor nests are discarded and new one is derived;Retain optimal solution, (with quality solution);Sort the solutions and determine current bestEndPostprocess and visualize resultsEndIn the CSO technique, cuckoo eggs from distinct nests signify the generation of candidate solutions to optimize problems. Actually, the search starts with particular nests with a solution per nest. This solution was progressed dependent upon the model of cuckoo’s recognition (p) which was inspired by eliminating the solution of exchanging novel ones.In the CSO method, a random walk was utilized dependent upon the Lévy flight distribution for producing novel candidate solutions (cuckoos) in the present one as follows:(14)cuckooit+1=cuckooit+a⊕Levyλ,where cuckooit+1 refers the ith cuckoo value t. An a and λ stand for step sizes (generally fixed to one) and coefficients 1<λ<3 correspondingly. A number of novel solutions were created in the optimum present ones by Lévy walks for performing a local search with self‐improvement [19]. Besides, a few novel solutions were created away from the optimum present ones. This reduces the chance of getting stuck from the local minimal and ensures the searching ability. The CS execution also makes sure elitism as the optimal nest is retained under the iteration.The OBL method was proposed with the aim of decreasing the computation time and improving the ability of various EAs [20]. Therefore, the comparisons among an arbitrary CSO algorithm and its opposite might result in the global optimal with fast convergence rates. Further, the quasiopposite number and showed that it is nearer to the optimum solution when compared to the opposite number. Therefore, the population initialization of this method is created according to the QOBL concept. For arbitrary number χ∈a,b , its opposite number χ0 is represented as follows:(15)x0=a+b−x.However, the opposite point for multidimensional searching space (dimension) is determined by the following equation:(16)x0i=aj+bi−xi,i=1,2,…,d.The quasiopposite no.xqo of arbitrary no. χ∈a,b is represented as follows [21]:(17)xqo=randa+b2,x0.Likewise, the quasiopposite point for multidimensional searching space (d dimension) is determined by the following equation:(18)xqoi=randai+bi2,x0i.For obtaining an objective function that could generalize the SVM outcome with no utilization of testing data, the cross validation approach is utilized. The cross validation process partitions the training datasetD randomly into S different parts Gs,s=1,…,S, and utilizes (S − 1) parts to train the model and to test the model. This process gets iterated for S times by varying the lasting parts, and the generalization efficiency can be determined by the use of MSE (mean squared error) over every test result.(19)MSECV=1N∑s=1S∑i∈Gsyi−fxi|θs2,where Gs indicates the s-th part for the testing process and θs signifies the solution vector attained at the time of training process.
## 4. Performance Evaluation and Discussion
The performance validation of the QOCSO-NLSVM technique using the economic data from the Niti Aayog website and the Reserve Bank of India were inspected. The data includes several features such as fiscal deficits, revenue deficits, interest payments, capital expenditure, nominal NSDP series, social sector expenditure, electricity generation, infrastructure projects, per capita NSDP at factor cost (at constant prices), per capita NSDP, number of factories, state-wise fixed capital, sectoral growth rate, and pattern of land use. Table1 and Figure 3 investigate the actual and predicted result analysis of the QOCSO-NLSVM technique over distinct years. The results portrayed that the QOCSO-NLSVM technique predicted the economic status much closer to the actual value under all runs.Table 1
Actual and predicted analysis of the QOCSO-NLSVM technique with varying years.
YearsActualsRun: 1Run: 2Run: 3Run: 4Run: 5201216855.71216854.7216784.7116716.7216799.7216851.73201317037.95717134.9917056.9417098.9717102.9617028.95201417675.81617767.8017563.8017820.8117781.8117734.82201518176.99118110.0218125.9818285.9818211.0118294.03201618860.41118924.4118782.4118806.4218750.4418970.43201719999.44519966.4820106.4519960.4519859.4419874.43201821138.47821028.5021282.4921097.4721184.4821098.48201921730.77621822.7721680.8021651.7621680.7621627.80202022231.95122310.9622177.9522379.9622330.9622374.97Figure 3
Actual and prediction analysis of the QOCSO-NLSVM technique.For instance, with an actual value of 16855.712, the QOCSO-NLSVM technique has attained predicted values of 16854.72, 16784.71, 16716.72, 16799.72, and 16851.73 under runs 1–5, respectively. At the same time, with the actual values of 18176.991, the QOCSO-NLSVM system has accomplished forecasted values of 18110.02, 18125.98, 18285.98, 18211.01, and 18294.03 under runs 1–5 correspondingly. Furthermore, with the actual values of 21138.478, the QOCSO-NLSVM method has achieved forecasted values of 21028.50, 21282.49, 21097.47, 21184.48, and 21098.48 under runs 1–5 correspondingly. Moreover, with the actual values of 22231.951, the QOCSO-NLSVM algorithm has reached predicted values of 22310.96, 22177.95, 22379.96, 22330.96, and 22374.97 under runs 1–5 correspondingly.A brief MSE analysis of the QOCSO-NLSVM technique under various runs and years is provided in Figure4 and Table 2. The experimental values are denoted by the QOCSO-NLSVM technique, which has resulted in an effective outcome with minimal MSE values. For instance, in the year 2012, the QOCSO-NLSVM technique resulted in at least MSE of 70.997, 138.996, 55.994, 3.979, and 0.995, respectively. Simultaneously, in the year 2015, the QOCSO-NLSVM system has resulted in a minimum MSE of 51.009, 108.987, 34.014, 117.037, and 66.972 correspondingly. Simultaneously, in the year 2018, the QOCSO-NLSVM model has resulted in a minimum MSE of 144.010, 41.006, 46.005, 39.996, and 109.978 correspondingly. Likewise, in the year 2020, the QOCSO-NLSVM method has resulted in a minimum MSE of 54.003, 148.011, 99.014, 143.021, and 79.009 correspondingly.Figure 4
MSE analysis of the QOCSO-NLSVM technique with distinct runs.Table 2
MSE analysis of the QOCSO-NLSVM technique with distinct runs.
YearsRun: 1Run: 2Run: 3Run: 4Run: 5201270.997138.99655.9943.9790.995201318.98761.01765.0009.00697.0282014112.011144.993105.99759.00491.982201551.009108.98734.014117.03766.972201677.99953.994109.975110.01964.0002017107.00138.997140.001125.01832.9672018144.01041.00646.00539.996109.978201949.97779.01450.013102.97891.997202054.003148.01199.014143.02179.009Average76.22290.55778.44678.89570.548A brief RMSE analysis of the QOCSO-NLSVM method over many years and runs has been demonstrated in Table3 and Figure 5. The experiment values showed that the QOCSO-NLSVM method has resulted in outstanding results with the smallest RMSE value. For example, in the year 2012, the QOCSO-NLSVM system resulted in a minimal RMSE of 8.426, 22.790, 7.483, 1.995, and 0.997 correspondingly. Concurrently, in the year 2015, the QOCSO-NLSVM approach resulted in a minimum RMSE of 7.142, 10.440, 5.832, 10.818, and 8.184 correspondingly. Simultaneously, in the year 2018, the QOCSO-NLSVM process has resulted in the smallest RMSE of 12.000, 6.404, 6.783, 6.324, and 10.487 correspondingly. Likewise, in the year 2020, the QOCSO-NLSVM method has resulted in a minimal RMSE of 7.349, 12.166, 9.951, 11.959, and 8.889 correspondingly.Table 3
RMSE analysis of the QOCSO-NLSVM technique with distinct runs.
YearsRun: 1Run: 2Run: 3Run: 4Run: 520128.42611.7907.4831.9950.99720134.3577.8118.0623.0019.850201410.58412.04110.2967.6819.59120157.14210.4405.83210.8188.18420168.8327.34810.48710.4898.000201710.3446.24511.83211.1815.742201812.0006.4046.7836.32410.48720197.0698.8897.07210.1489.59220207.34912.1669.95111.9598.889Average8.4569.2378.6448.1777.926Figure 5
RMSE analysis of the QOCSO-NLSVM technique with distinct runs.Table4 presents a full comparison study of the QOCSO-NLSVM approach.Table 4
Comparative analysis of the QOCSO-NLSVM technique with existing approaches.
MSERMSELSTM149.99712.247ARIMA142.23511.926GRU128.35711.329Multivariate LSTM095.18409.756QOCSO-NLSVM070.54808.399Figure6 offers the MSE analysis of the QOCSO-NLSVM technique with recent methods. The figure shows that the LSTM and ARIMA models have obtained poor performance with a higher MSE of 149.997 and 142.235, respectively. Similarly, the GRU and multivariate LSTM models reached a moderate MSE of 128.357 and 95.184, respectively. However, the QOCSO-NLSVM technique has accomplished effective outcomes with a minimal MSE of 70.548.Figure 6
MSE analysis of the QOCSO-NLSVM technique with existing approaches.Figure7 provides the RMSE of the QOCSO-NLSVM model with current methodologies. The abovementioned figure exhibits that the ARIMA and LSTM systems have gained poor performance with a high RMSE of 11.926 and 12.247 correspondingly. Simultaneously, the multivariate LSTM and GRU methods have attained reasonable RMSE of 9.756 and 11.329, respectively. But, the QOCSO-NLSVM process has gained remarkable results with the smallest RMSE of 8.399.Figure 7
RMSE analysis of the QOCSO-NLSVM technique with existing approaches.From the abovementioned figures, it is ensured that the QOCSO-NLSVM model is an effective regional economic prediction method over the other existing techniques.
## 5. Conclusion
In this research, a proposed QOCSO-NLSVM technique has been developed for regional economic prediction. The QOCSO-NLSVM technique encompasses several subprocesses, namely, DTW based preprocessing, DBSCAN-based clustering, NLSVM-based prediction, and QOCSO-based parameter optimization. The use of the DBSCAN model enables the computation of identical states depending upon the per capita NSDP growth trends and socioeconomic-demographic features in a state. In addition, the application of the QOCSO algorithm helps to properly select the parameter values and thereby reaches the maximum predictive outcomes. The QOCSO-NLSVM technique is used to discover identical states based on per capita NSDP growth trends and socioeconomic-demographic characteristics in a state. QOCSO-NLSVM is used to run a variety of simulations on regional economic data and is also used to assess a region’s present economic position. The experimental validation of the QOCSO-NLSVM technique and the results are examined in various aspects. The comparative analysis revealed the enhanced outcomes of the QOCSO-NLSVM technique over the recent approaches. With a minimum MSE of 70.548, the QOCSO-NLSVM approach produced effective results. The QOCSO-NLSVM technique had remarkable results, achieving the lowest root mean square error (RMSE) of 8.399. In the future, advanced DL models can be used to improve the overall prediction outcomes.
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*Source: 2900434-2022-01-30.xml* | 2900434-2022-01-30_2900434-2022-01-30.md | 36,809 | Design of a Regional Economic Forecasting Model Using Optimal Nonlinear Support Vector Machines | Tong Zhang | Computational Intelligence and Neuroscience
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2900434 | 2900434-2022-01-30.xml | ---
## Abstract
Forecasting regional economic activity is a progressively significant element of regional economic research. Regional economic prediction can directly assist local, national, and subnational policymakers. Regional economic activity forecast can be employed for defining macroeconomic forces, such as prediction of stock market and cyclicality of national labor market movement. The recent advances of machine learning (ML) models can be employed to solve the time series prediction problem. Since the parameters involved in the ML model considerably influence the performance, the parameter tuning process also becomes essential. With this motivation, this study develops a quasioppositional cuckoo search algorithm (QOCSA) with a nonlinear support vector machine (SVM)-based prediction model, called QOCSO-NLSVM for regional economic prediction. The goal of the QOCSO-NLSVM technique is to identify the present regional economic status. The QOCSO-NLSVM technique has different stages such as clustering, preprocessing, prediction, and optimization. Besides, the QOCSO-NLSVM technique employs the density-based clustering algorithm (DBSCAN) to determine identical states depending upon the per capita NSDP growth trends and socio-economic-demographic features in a state. Moreover, the NLSVM model is employed for the time series prediction process and the parameters involved in it are optimally tuned by the use of the QOCSO algorithm. To showcase the effective performance of the QOCSO-NLSVM technique, a wide range of simulations take place using regional economic data. To determine the current economic situation in a region, the QOCSO-NLSVM technique is used. The simulation results reported the better performance of the QOCSO-NLSVM technique over recent approaches. The QOCSO-NLSVM technique generated effective results with a minimal mean square error of 70.548 or greater. Astonishingly good results were obtained using the QOCSO-NLSVM approach, which had the lowest root mean square error (RMSE) of 8.399.
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## Body
## 1. Introduction
The forecasting method predicts future value based on a provided time series data set by making assumptions on future trends and estimating historical data. This is employed for several regions of the decision-making process, like industrial process control, risk management, operations management, demography, and economics [1]. Forecasting is an important problem spanning several domains, involving finance, social science, government, economics, environmental science, politics, medicine, business, and industry. The forecasting problem is categorized as long-term, short-term, and medium-term [2, 3].Forecasting regional economic activity is an essential component of regional economic study. The regional economic prediction could directly assist business executives, local, subnational, and national policymakers. These two business executives and policymakers require precise prediction of key economic aggregates, namely, employment, output, and income for medium-long term planning purposes [4]. Regional economic activity forecasts have been employed for explaining macroeconomic forces, involving the cyclicality of national labour market movements and predicting the stock market. Further, multinational agencies and international investors engaged in megaprojects at a regional level also require precise predictions for investment planning reasons [5]. When there is no paucity of research on predicting national economic indicators, the research on regional economic prediction is limited for innovative economies, and in the case of developing nations, zilch [6]. Problems with short-term forecasting are those that deal with predicting events in a shorter period of time (months, days, and weeks). Forecasting concerns could go much beyond 1-2 years into the future, with medium-term forecasts extending into the future as well.The forecasting method connected to economic problems is utilized for predicting economic variables in several countries. The industry volatility prediction, critical to several important problems in business [7], and the prediction of the unemployment rates that define the country’s economic and social development [8, 9]. Radial basis function networks (RBF) and backpropagation are the ANN architectures that are used in economic fields. The artificial neural networks (ANN) technique was broadly examined in economic analysis. The ANN is a computation system that is performed in hardware or software under the effect of biological studies about the human brain. Several authors admit that the ANN method is the better performing nonlinear analysis technique as well as one of the best predictors [10]. The ANN architecture employed in economic fields is radial basis function networks (RBF) and backpropagation.This study designs a quasioppositional cuckoo search algorithm (QOCSA) with a nonlinear support vector machine (SVM)-based prediction model, called QOCSO-NLSVM for regional economic prediction. The QOCSO-NLSVM technique involves the design of the density-based clustering algorithm (DBSCAN) to determine the identical states depending upon the per capita NSDP growth trends and socioeconomic-demographic features in a state. Besides, the NLSVM model is elected for the time series prediction process and the parameters involved in it are optimally tuned by the use of the QOCSO algorithm. The experimental validation of the QOCSO-NLSVM technique and the results are examined in various aspects.The rest of the research work is organized as follows. Section2 provides the recently developed techniques, Section 3 elaborates the QOCSO-NLSVM technique. Then, Section 4 provides the performance validation, and Section 5 concludes the outcomes of the research.
## 2. Literature Review
Mishra and Ayyub [11] introduced a DL architecture in which the hierarchical clustering analysis (HCA) is utilized for predicting growth. The presented method comprises HCA and DTW techniques that are initially applied for identifying similar socio-economic-demographic features within a provided state and similar states according to per capita NSDP growth trends, to create a fine-tuned training dataset for predicting all the states’ NSDP per capita growth. Lv et al. [12] developed a LightGBM-enhanced LSTM for realizing stock price prediction, and LSTM is utilized for predicting the Shenzhen and Shanghai 300 indexes, respectively. The simulation result shows that the LightGBM-LSTM has a better capacity for tracking stock index price trends and the maximum prediction performance, and its effects are superior to the RNN and GRU methods. LightGBM-optimized LSTM for short-term stock price forecasting. To compare its performance with other deep network models such as RNN (recurrent neural network) and GRU (gated recurrent unit), the LightGBM-LSTM, RNN, and GRU are used to predict the Shanghai and Shenzhen 300 indexes, respectively. Experiment results demonstrate that the LightGBM-LSTM has the highest prediction accuracy and the best ability to track stock index price trends.Zhu et al. [13] designed an experiment whose samples originated from information on 7 quoted core enterprises (CEs) and 46 quoted SMEs in the Chinese security markets. Matta et al. [14] introduced a relative assessment of various prediction techniques using the Gaussian process regression and ANN methods (MLP and RBFNN). Two real-time datasets were utilized for evaluating the prediction method presented in the study. These datasets were normalized to values amongst one and zero. Next, the data training was implemented and, when it was constructed, a system was utilized for generating the predictions. Therefore, observations were made to validate how precisely the fitted method predicts the values.Chatzis et al. [15] integrated distinct ML methods that were proposed with daily currency, stock, and bond data from thirty-nine countries that cover a larger spectrum of economies. It especially leverages the advantages of a sequence of techniques that includes Classifier Trees, SVM, NN, RF, XGBoost, and DNN. Sun et al. [16] verified the cointegration relationships and Granger causality between tourist arrivals in Beijing and the internet search index. This experiment result suggests that compared to standard methods, the presented KELM model that incorporates tourist volume series with Google and Baidu Index could significantly enhance the prediction performances in terms of robustness analysis and forecasting accuracy.
## 3. The Proposed Model
In this study, an effective QOCSO-NLSVM technique has been developed for regional economic prediction. The QOCSO-NLSVM technique encompasses several subprocesses, namely, DTW-based preprocessing, DBSCAN-based clustering, NLSVM-based prediction, and QOCSO-based parameter optimization. Figure1 illustrates the overall working process of the QOCSO-NLSVM technique.Figure 1
System architecture of the QOCSO-NLSVM method.
### 3.1. Data Preprocessing
One of the primary methods used to capture similarities among two regions, or among pairs of factors within a provided region according to time-series data is named dynamic time warping (DTW). DTW is an effective method utilized for learning similarity based on distance between two sequences that might differ in speed and quantifying time-based similarities among any two pairs. Generally, DTW is an ML method which estimates an optimum match between two provided sequences with some restrictions. The sequence is “warped” nonlinearly in the time dimension to define measures of their similarity, independent of nonlinear variation in the time dimension. The Euclidean distance uses the distance among every pair of the time series and compares it with the Euclidean distance. Simultaneously, the DTW searches for optimal alignments among the two-time series. Furthermore, all the points are utilized for comparing the points to make the best possible alignments among the two-time series according to their distance matrix.
### 3.2. Process Involved in the DBSCAN Technique
DBSCAN might find distinct clusters based on the assessed density distribution. It could recognise structured groupings without knowing their numbers. The following illustrates DBSCAN’s basic premise: DBSCAN finds each point in the neighbourhood of a random unvisited pointp, where it denotes the neighbourhood’s maximum radius from p. To construct a dense zone, MinPts is the minimum number of points required. When MinPts is in the distance, p denotes a core point. When p is a core point, all points in its vicinity are grouped together. DBSCAN detects each density-reachable point in the cluster and adds it to a comparable cluster. When a point q is densely approachable from other core points but its neighbourhood is less than MinPts, it is a border point. An outlier or noisy point is one that is not accessible from other locations. DBSCAN achieves clustering by extracting clusters consecutively. Rep until no more density-reachable points are identified, and the final cluster is reached. DBSCAN divides a set of points into low-noise border points and high-density. The purpose of DBSCAN is to identify identical states based on a state's per capita NSDP growth trends and socioeconomic-demographic characteristics. DBSCAN was capable of detecting a variety of clusters based on the density distribution that was assessed. The DBSCAN methodology permits the calculation of identical states based on per capita income.Assume two pointsx and y, dx,y represent the similarities among them, Γεx denotes the ε-neighbourhood of x, in which Γεx=y∈V|dx,y≤ε⋅ρx=Γεx indicates the density value of x:(1)Sx=1,core point withρx≥MinPts,0,border point with1<ρx<MinPts,−1,noise withρx=1.
### 3.3. Structure of the NLSVM Model
During the prediction process, the NLSVM model receives the clustered data as input to predict the output. Assume a trained setxk,ykk=1N with input data xk∈ℝn and respective binary class label yk∈−1,+1, the SVM classification initiates from the subsequent assumption:(2)wTφxk+b≥+1,ifyk=+1,wTφxk+b≤−1,ifyk=−1.That is equal to(3)ykwTφxk+b≥1,k=1,…,N.Now, the nonlinear functionφ·:ℝn⟶ℝnh maps the input space to a high-dimensional feature space. It is noteworthy that the nh dimension of this space is determined in an implicit manner (it is an infinite dimension). The b represent a bias as follows:(4)yx=signwTφx+b.But, at the same time, it is never evaluated in this form. One determines the optimization issue:(5)minJw,ξ=12wTw+c∑k=1Nξk,subjected to(6)ykwTφxk+b≥1−ξk,k=1,…,N,ξk≥0,k=1,…,N.To permit misclassification in the subset of inequalities (because of overlapping distribution), the minimalization ofw2 corresponds to a maximalization of the margin among the two classes. c indicates a positive real constant and must be taken into account as a tuning parameter. The Lagrangian can be expressed as follows [17]:(7)Lw,b,ξ;α,ν=Jw,ξ−∑k=1NαkykwTφxk+b−1+ξk−∑k=1Nνkξk.The Lagrange multiplier isαk≥0,νk≥0,k=1,N. Figure 2 depicts the SVM hyperplane. It is familiar from the optimization concept that the solutions are considered by the saddle points of the Lagrangian:(8)maxα,vminw,b,ξℒw,b,ξ;α,ν.Figure 2
SVM hyperplane.One attains(9)∂L∂w=0⟶w=∑k=1Nαkykφxk,∂L∂b=0⟶∑k=1Nαkyk=0,∂L∂ξk=0⟶0≤αk≤c,k=1,…,N.By substitutingw in the Lagrangian, one attains the subsequent binary problems (in the Lagrange multiplier α), i.e., the quadratic programming problems:(10)maxαQα=−12∑k,l=1NykylKxk,xlαkαl+∑k=1Nαk.Thus,(11)∑k=1Nαkyk=0,0≤αk≤c,k=1,…,N.Noww and φxk are not estimated. According to the Mercer condition, one takes a kernel as(12)Kxk,xl=φxkTφxl.Lastly, in binary space, the nonlinear SVM classifiers become(13)yx=sign∑k=1NαkykKx,xk+b.αk is a positive real constant, and b is a real constant. The nonzero Lagrange multiplier αk is known as support value. The respective data point is known as a support vector and is placed near the decision boundary. This is the data point that contributes to the classification method. The bias b follows from the KKT condition that isn’t considered further.Various selections for the kernelK·,· are feasible.(i)
Kx,xk=xkTx (linear SVM)(ii)
Kx,xk=xkTx+1d (polynomial SVM of degree d)(iii)
Kx,xk=exp−x−xk22/σ2 (RBF kemel)(iv)
Kx,xk=tanhκxkTx+θ (MLP SVM)The Mercer conditions hold for eachσ value in the RBF case, but not for each feasible selection of κ,θ in the MLP case. In the case of an MLP or RBF kernel, the amount of hidden units corresponds to the number of support vectors.
### 3.4. Design of the QOCSO Algorithm for Parameter Tuning
For optimally tuning the weight values of the NLSVM model, the QOCSO algorithm is utilized. The CSO algorithm is assumed as a metaheuristic technique that was primarily established by Yang and Deb [18]. Actually, this CSO method simulates the breeding performance of cuckoo birds that are supposed to be a type of parasitism. The cuckoo birds place their eggs from other nests and play to host the egg. The cuckoo birds attempt for raising the hatch possibility of their individual eggs by generating them the same as the host egg with respect to size, shape, and colour, or by throwing other native eggs (Algorithm 1).Algorithm 1: Pseudocode of the CSO algorithm.
Begin.Objective functions off(x), x = (x1, x2, …, xd)TPopulations initialization ofn host nests xi,While (t < Maximum_iteration) or (termination condition)Get a cuckoo arbitrarily via Lévy flightDetermine the qualities/fitness asFiSelect nest amongst (n, j) arbitrarilyIf (Fi ≥ Fj),Substitutej in newly attained solution;EndAn fraction (pa), poor nests are discarded and new one is derived;Retain optimal solution, (with quality solution);Sort the solutions and determine current bestEndPostprocess and visualize resultsEndIn the CSO technique, cuckoo eggs from distinct nests signify the generation of candidate solutions to optimize problems. Actually, the search starts with particular nests with a solution per nest. This solution was progressed dependent upon the model of cuckoo’s recognition (p) which was inspired by eliminating the solution of exchanging novel ones.In the CSO method, a random walk was utilized dependent upon the Lévy flight distribution for producing novel candidate solutions (cuckoos) in the present one as follows:(14)cuckooit+1=cuckooit+a⊕Levyλ,where cuckooit+1 refers the ith cuckoo value t. An a and λ stand for step sizes (generally fixed to one) and coefficients 1<λ<3 correspondingly. A number of novel solutions were created in the optimum present ones by Lévy walks for performing a local search with self‐improvement [19]. Besides, a few novel solutions were created away from the optimum present ones. This reduces the chance of getting stuck from the local minimal and ensures the searching ability. The CS execution also makes sure elitism as the optimal nest is retained under the iteration.The OBL method was proposed with the aim of decreasing the computation time and improving the ability of various EAs [20]. Therefore, the comparisons among an arbitrary CSO algorithm and its opposite might result in the global optimal with fast convergence rates. Further, the quasiopposite number and showed that it is nearer to the optimum solution when compared to the opposite number. Therefore, the population initialization of this method is created according to the QOBL concept. For arbitrary number χ∈a,b , its opposite number χ0 is represented as follows:(15)x0=a+b−x.However, the opposite point for multidimensional searching space (dimension) is determined by the following equation:(16)x0i=aj+bi−xi,i=1,2,…,d.The quasiopposite no.xqo of arbitrary no. χ∈a,b is represented as follows [21]:(17)xqo=randa+b2,x0.Likewise, the quasiopposite point for multidimensional searching space (d dimension) is determined by the following equation:(18)xqoi=randai+bi2,x0i.For obtaining an objective function that could generalize the SVM outcome with no utilization of testing data, the cross validation approach is utilized. The cross validation process partitions the training datasetD randomly into S different parts Gs,s=1,…,S, and utilizes (S − 1) parts to train the model and to test the model. This process gets iterated for S times by varying the lasting parts, and the generalization efficiency can be determined by the use of MSE (mean squared error) over every test result.(19)MSECV=1N∑s=1S∑i∈Gsyi−fxi|θs2,where Gs indicates the s-th part for the testing process and θs signifies the solution vector attained at the time of training process.
## 3.1. Data Preprocessing
One of the primary methods used to capture similarities among two regions, or among pairs of factors within a provided region according to time-series data is named dynamic time warping (DTW). DTW is an effective method utilized for learning similarity based on distance between two sequences that might differ in speed and quantifying time-based similarities among any two pairs. Generally, DTW is an ML method which estimates an optimum match between two provided sequences with some restrictions. The sequence is “warped” nonlinearly in the time dimension to define measures of their similarity, independent of nonlinear variation in the time dimension. The Euclidean distance uses the distance among every pair of the time series and compares it with the Euclidean distance. Simultaneously, the DTW searches for optimal alignments among the two-time series. Furthermore, all the points are utilized for comparing the points to make the best possible alignments among the two-time series according to their distance matrix.
## 3.2. Process Involved in the DBSCAN Technique
DBSCAN might find distinct clusters based on the assessed density distribution. It could recognise structured groupings without knowing their numbers. The following illustrates DBSCAN’s basic premise: DBSCAN finds each point in the neighbourhood of a random unvisited pointp, where it denotes the neighbourhood’s maximum radius from p. To construct a dense zone, MinPts is the minimum number of points required. When MinPts is in the distance, p denotes a core point. When p is a core point, all points in its vicinity are grouped together. DBSCAN detects each density-reachable point in the cluster and adds it to a comparable cluster. When a point q is densely approachable from other core points but its neighbourhood is less than MinPts, it is a border point. An outlier or noisy point is one that is not accessible from other locations. DBSCAN achieves clustering by extracting clusters consecutively. Rep until no more density-reachable points are identified, and the final cluster is reached. DBSCAN divides a set of points into low-noise border points and high-density. The purpose of DBSCAN is to identify identical states based on a state's per capita NSDP growth trends and socioeconomic-demographic characteristics. DBSCAN was capable of detecting a variety of clusters based on the density distribution that was assessed. The DBSCAN methodology permits the calculation of identical states based on per capita income.Assume two pointsx and y, dx,y represent the similarities among them, Γεx denotes the ε-neighbourhood of x, in which Γεx=y∈V|dx,y≤ε⋅ρx=Γεx indicates the density value of x:(1)Sx=1,core point withρx≥MinPts,0,border point with1<ρx<MinPts,−1,noise withρx=1.
## 3.3. Structure of the NLSVM Model
During the prediction process, the NLSVM model receives the clustered data as input to predict the output. Assume a trained setxk,ykk=1N with input data xk∈ℝn and respective binary class label yk∈−1,+1, the SVM classification initiates from the subsequent assumption:(2)wTφxk+b≥+1,ifyk=+1,wTφxk+b≤−1,ifyk=−1.That is equal to(3)ykwTφxk+b≥1,k=1,…,N.Now, the nonlinear functionφ·:ℝn⟶ℝnh maps the input space to a high-dimensional feature space. It is noteworthy that the nh dimension of this space is determined in an implicit manner (it is an infinite dimension). The b represent a bias as follows:(4)yx=signwTφx+b.But, at the same time, it is never evaluated in this form. One determines the optimization issue:(5)minJw,ξ=12wTw+c∑k=1Nξk,subjected to(6)ykwTφxk+b≥1−ξk,k=1,…,N,ξk≥0,k=1,…,N.To permit misclassification in the subset of inequalities (because of overlapping distribution), the minimalization ofw2 corresponds to a maximalization of the margin among the two classes. c indicates a positive real constant and must be taken into account as a tuning parameter. The Lagrangian can be expressed as follows [17]:(7)Lw,b,ξ;α,ν=Jw,ξ−∑k=1NαkykwTφxk+b−1+ξk−∑k=1Nνkξk.The Lagrange multiplier isαk≥0,νk≥0,k=1,N. Figure 2 depicts the SVM hyperplane. It is familiar from the optimization concept that the solutions are considered by the saddle points of the Lagrangian:(8)maxα,vminw,b,ξℒw,b,ξ;α,ν.Figure 2
SVM hyperplane.One attains(9)∂L∂w=0⟶w=∑k=1Nαkykφxk,∂L∂b=0⟶∑k=1Nαkyk=0,∂L∂ξk=0⟶0≤αk≤c,k=1,…,N.By substitutingw in the Lagrangian, one attains the subsequent binary problems (in the Lagrange multiplier α), i.e., the quadratic programming problems:(10)maxαQα=−12∑k,l=1NykylKxk,xlαkαl+∑k=1Nαk.Thus,(11)∑k=1Nαkyk=0,0≤αk≤c,k=1,…,N.Noww and φxk are not estimated. According to the Mercer condition, one takes a kernel as(12)Kxk,xl=φxkTφxl.Lastly, in binary space, the nonlinear SVM classifiers become(13)yx=sign∑k=1NαkykKx,xk+b.αk is a positive real constant, and b is a real constant. The nonzero Lagrange multiplier αk is known as support value. The respective data point is known as a support vector and is placed near the decision boundary. This is the data point that contributes to the classification method. The bias b follows from the KKT condition that isn’t considered further.Various selections for the kernelK·,· are feasible.(i)
Kx,xk=xkTx (linear SVM)(ii)
Kx,xk=xkTx+1d (polynomial SVM of degree d)(iii)
Kx,xk=exp−x−xk22/σ2 (RBF kemel)(iv)
Kx,xk=tanhκxkTx+θ (MLP SVM)The Mercer conditions hold for eachσ value in the RBF case, but not for each feasible selection of κ,θ in the MLP case. In the case of an MLP or RBF kernel, the amount of hidden units corresponds to the number of support vectors.
## 3.4. Design of the QOCSO Algorithm for Parameter Tuning
For optimally tuning the weight values of the NLSVM model, the QOCSO algorithm is utilized. The CSO algorithm is assumed as a metaheuristic technique that was primarily established by Yang and Deb [18]. Actually, this CSO method simulates the breeding performance of cuckoo birds that are supposed to be a type of parasitism. The cuckoo birds place their eggs from other nests and play to host the egg. The cuckoo birds attempt for raising the hatch possibility of their individual eggs by generating them the same as the host egg with respect to size, shape, and colour, or by throwing other native eggs (Algorithm 1).Algorithm 1: Pseudocode of the CSO algorithm.
Begin.Objective functions off(x), x = (x1, x2, …, xd)TPopulations initialization ofn host nests xi,While (t < Maximum_iteration) or (termination condition)Get a cuckoo arbitrarily via Lévy flightDetermine the qualities/fitness asFiSelect nest amongst (n, j) arbitrarilyIf (Fi ≥ Fj),Substitutej in newly attained solution;EndAn fraction (pa), poor nests are discarded and new one is derived;Retain optimal solution, (with quality solution);Sort the solutions and determine current bestEndPostprocess and visualize resultsEndIn the CSO technique, cuckoo eggs from distinct nests signify the generation of candidate solutions to optimize problems. Actually, the search starts with particular nests with a solution per nest. This solution was progressed dependent upon the model of cuckoo’s recognition (p) which was inspired by eliminating the solution of exchanging novel ones.In the CSO method, a random walk was utilized dependent upon the Lévy flight distribution for producing novel candidate solutions (cuckoos) in the present one as follows:(14)cuckooit+1=cuckooit+a⊕Levyλ,where cuckooit+1 refers the ith cuckoo value t. An a and λ stand for step sizes (generally fixed to one) and coefficients 1<λ<3 correspondingly. A number of novel solutions were created in the optimum present ones by Lévy walks for performing a local search with self‐improvement [19]. Besides, a few novel solutions were created away from the optimum present ones. This reduces the chance of getting stuck from the local minimal and ensures the searching ability. The CS execution also makes sure elitism as the optimal nest is retained under the iteration.The OBL method was proposed with the aim of decreasing the computation time and improving the ability of various EAs [20]. Therefore, the comparisons among an arbitrary CSO algorithm and its opposite might result in the global optimal with fast convergence rates. Further, the quasiopposite number and showed that it is nearer to the optimum solution when compared to the opposite number. Therefore, the population initialization of this method is created according to the QOBL concept. For arbitrary number χ∈a,b , its opposite number χ0 is represented as follows:(15)x0=a+b−x.However, the opposite point for multidimensional searching space (dimension) is determined by the following equation:(16)x0i=aj+bi−xi,i=1,2,…,d.The quasiopposite no.xqo of arbitrary no. χ∈a,b is represented as follows [21]:(17)xqo=randa+b2,x0.Likewise, the quasiopposite point for multidimensional searching space (d dimension) is determined by the following equation:(18)xqoi=randai+bi2,x0i.For obtaining an objective function that could generalize the SVM outcome with no utilization of testing data, the cross validation approach is utilized. The cross validation process partitions the training datasetD randomly into S different parts Gs,s=1,…,S, and utilizes (S − 1) parts to train the model and to test the model. This process gets iterated for S times by varying the lasting parts, and the generalization efficiency can be determined by the use of MSE (mean squared error) over every test result.(19)MSECV=1N∑s=1S∑i∈Gsyi−fxi|θs2,where Gs indicates the s-th part for the testing process and θs signifies the solution vector attained at the time of training process.
## 4. Performance Evaluation and Discussion
The performance validation of the QOCSO-NLSVM technique using the economic data from the Niti Aayog website and the Reserve Bank of India were inspected. The data includes several features such as fiscal deficits, revenue deficits, interest payments, capital expenditure, nominal NSDP series, social sector expenditure, electricity generation, infrastructure projects, per capita NSDP at factor cost (at constant prices), per capita NSDP, number of factories, state-wise fixed capital, sectoral growth rate, and pattern of land use. Table1 and Figure 3 investigate the actual and predicted result analysis of the QOCSO-NLSVM technique over distinct years. The results portrayed that the QOCSO-NLSVM technique predicted the economic status much closer to the actual value under all runs.Table 1
Actual and predicted analysis of the QOCSO-NLSVM technique with varying years.
YearsActualsRun: 1Run: 2Run: 3Run: 4Run: 5201216855.71216854.7216784.7116716.7216799.7216851.73201317037.95717134.9917056.9417098.9717102.9617028.95201417675.81617767.8017563.8017820.8117781.8117734.82201518176.99118110.0218125.9818285.9818211.0118294.03201618860.41118924.4118782.4118806.4218750.4418970.43201719999.44519966.4820106.4519960.4519859.4419874.43201821138.47821028.5021282.4921097.4721184.4821098.48201921730.77621822.7721680.8021651.7621680.7621627.80202022231.95122310.9622177.9522379.9622330.9622374.97Figure 3
Actual and prediction analysis of the QOCSO-NLSVM technique.For instance, with an actual value of 16855.712, the QOCSO-NLSVM technique has attained predicted values of 16854.72, 16784.71, 16716.72, 16799.72, and 16851.73 under runs 1–5, respectively. At the same time, with the actual values of 18176.991, the QOCSO-NLSVM system has accomplished forecasted values of 18110.02, 18125.98, 18285.98, 18211.01, and 18294.03 under runs 1–5 correspondingly. Furthermore, with the actual values of 21138.478, the QOCSO-NLSVM method has achieved forecasted values of 21028.50, 21282.49, 21097.47, 21184.48, and 21098.48 under runs 1–5 correspondingly. Moreover, with the actual values of 22231.951, the QOCSO-NLSVM algorithm has reached predicted values of 22310.96, 22177.95, 22379.96, 22330.96, and 22374.97 under runs 1–5 correspondingly.A brief MSE analysis of the QOCSO-NLSVM technique under various runs and years is provided in Figure4 and Table 2. The experimental values are denoted by the QOCSO-NLSVM technique, which has resulted in an effective outcome with minimal MSE values. For instance, in the year 2012, the QOCSO-NLSVM technique resulted in at least MSE of 70.997, 138.996, 55.994, 3.979, and 0.995, respectively. Simultaneously, in the year 2015, the QOCSO-NLSVM system has resulted in a minimum MSE of 51.009, 108.987, 34.014, 117.037, and 66.972 correspondingly. Simultaneously, in the year 2018, the QOCSO-NLSVM model has resulted in a minimum MSE of 144.010, 41.006, 46.005, 39.996, and 109.978 correspondingly. Likewise, in the year 2020, the QOCSO-NLSVM method has resulted in a minimum MSE of 54.003, 148.011, 99.014, 143.021, and 79.009 correspondingly.Figure 4
MSE analysis of the QOCSO-NLSVM technique with distinct runs.Table 2
MSE analysis of the QOCSO-NLSVM technique with distinct runs.
YearsRun: 1Run: 2Run: 3Run: 4Run: 5201270.997138.99655.9943.9790.995201318.98761.01765.0009.00697.0282014112.011144.993105.99759.00491.982201551.009108.98734.014117.03766.972201677.99953.994109.975110.01964.0002017107.00138.997140.001125.01832.9672018144.01041.00646.00539.996109.978201949.97779.01450.013102.97891.997202054.003148.01199.014143.02179.009Average76.22290.55778.44678.89570.548A brief RMSE analysis of the QOCSO-NLSVM method over many years and runs has been demonstrated in Table3 and Figure 5. The experiment values showed that the QOCSO-NLSVM method has resulted in outstanding results with the smallest RMSE value. For example, in the year 2012, the QOCSO-NLSVM system resulted in a minimal RMSE of 8.426, 22.790, 7.483, 1.995, and 0.997 correspondingly. Concurrently, in the year 2015, the QOCSO-NLSVM approach resulted in a minimum RMSE of 7.142, 10.440, 5.832, 10.818, and 8.184 correspondingly. Simultaneously, in the year 2018, the QOCSO-NLSVM process has resulted in the smallest RMSE of 12.000, 6.404, 6.783, 6.324, and 10.487 correspondingly. Likewise, in the year 2020, the QOCSO-NLSVM method has resulted in a minimal RMSE of 7.349, 12.166, 9.951, 11.959, and 8.889 correspondingly.Table 3
RMSE analysis of the QOCSO-NLSVM technique with distinct runs.
YearsRun: 1Run: 2Run: 3Run: 4Run: 520128.42611.7907.4831.9950.99720134.3577.8118.0623.0019.850201410.58412.04110.2967.6819.59120157.14210.4405.83210.8188.18420168.8327.34810.48710.4898.000201710.3446.24511.83211.1815.742201812.0006.4046.7836.32410.48720197.0698.8897.07210.1489.59220207.34912.1669.95111.9598.889Average8.4569.2378.6448.1777.926Figure 5
RMSE analysis of the QOCSO-NLSVM technique with distinct runs.Table4 presents a full comparison study of the QOCSO-NLSVM approach.Table 4
Comparative analysis of the QOCSO-NLSVM technique with existing approaches.
MSERMSELSTM149.99712.247ARIMA142.23511.926GRU128.35711.329Multivariate LSTM095.18409.756QOCSO-NLSVM070.54808.399Figure6 offers the MSE analysis of the QOCSO-NLSVM technique with recent methods. The figure shows that the LSTM and ARIMA models have obtained poor performance with a higher MSE of 149.997 and 142.235, respectively. Similarly, the GRU and multivariate LSTM models reached a moderate MSE of 128.357 and 95.184, respectively. However, the QOCSO-NLSVM technique has accomplished effective outcomes with a minimal MSE of 70.548.Figure 6
MSE analysis of the QOCSO-NLSVM technique with existing approaches.Figure7 provides the RMSE of the QOCSO-NLSVM model with current methodologies. The abovementioned figure exhibits that the ARIMA and LSTM systems have gained poor performance with a high RMSE of 11.926 and 12.247 correspondingly. Simultaneously, the multivariate LSTM and GRU methods have attained reasonable RMSE of 9.756 and 11.329, respectively. But, the QOCSO-NLSVM process has gained remarkable results with the smallest RMSE of 8.399.Figure 7
RMSE analysis of the QOCSO-NLSVM technique with existing approaches.From the abovementioned figures, it is ensured that the QOCSO-NLSVM model is an effective regional economic prediction method over the other existing techniques.
## 5. Conclusion
In this research, a proposed QOCSO-NLSVM technique has been developed for regional economic prediction. The QOCSO-NLSVM technique encompasses several subprocesses, namely, DTW based preprocessing, DBSCAN-based clustering, NLSVM-based prediction, and QOCSO-based parameter optimization. The use of the DBSCAN model enables the computation of identical states depending upon the per capita NSDP growth trends and socioeconomic-demographic features in a state. In addition, the application of the QOCSO algorithm helps to properly select the parameter values and thereby reaches the maximum predictive outcomes. The QOCSO-NLSVM technique is used to discover identical states based on per capita NSDP growth trends and socioeconomic-demographic characteristics in a state. QOCSO-NLSVM is used to run a variety of simulations on regional economic data and is also used to assess a region’s present economic position. The experimental validation of the QOCSO-NLSVM technique and the results are examined in various aspects. The comparative analysis revealed the enhanced outcomes of the QOCSO-NLSVM technique over the recent approaches. With a minimum MSE of 70.548, the QOCSO-NLSVM approach produced effective results. The QOCSO-NLSVM technique had remarkable results, achieving the lowest root mean square error (RMSE) of 8.399. In the future, advanced DL models can be used to improve the overall prediction outcomes.
---
*Source: 2900434-2022-01-30.xml* | 2022 |
# Exercise Improves Spatial Learning and Memory Performance through the Central GLP-1 Receptors
**Authors:** Majid Taati; Peyman Esmaeili Fard Barzegar; Abbas Raisi
**Journal:** Behavioural Neurology
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2900628
---
## Abstract
The glucagon-like peptide 1 (GLP-1) is a hormone which is produced in the enteroendocrine L-cells in the ileum and the neurons of nucleus tractus solitarius (NTS) in the brain which has numerous metabolic effects. The central GLP-1R’s role in cognitive functioning is well known. On the contrary, it has been shown that exercise has positive effects on brain function. So, we decided to elucidate whether the central GLP-1 has a role in memory and learning. Thirty-two rats were used in this experiment in 4 groups. After anesthetizing the rats, the right lateral ventricle was detected, and a cannula was directed to the ventricle. Ten micrograms of exendin-3 or sterile saline, according to the group, was injected via ICV once daily for seven days. The rats in the exercise group considered an exercise period of one hour each day (17 meters per minute) for seven consecutive days. To evaluate the performance of memory and learning, a standard Morris water maze (MWM) tank was utilized. According to the results, the TE-exendin group showed a statistically significant difference from the TE-SAL group in both parameters of latency and time in the zone. In summary, memory and learning were improved by GLP-1R in the exercise group, but not in the sedentary group, which we can hypothesize that exercise can affect memory and learning through this pathway.
---
## Body
## 1. Introduction
Memory and learning loss is regarded as one of the world’s greatest issues brought on by age, accidents, and even some pharmaceuticals. Although several research have been conducted on medicines to prevent age-related cognitive decline, effective treatments for cognition and memory enhancement are not yet available (Coppi et al. [1]). The glucagon-like peptide 1 (GLP-1) is mainly composed of 160-amino acid proglucagon precursor protein (Bell et al. [2]; Ye et al. [3]) in the enteroendocrine L-cells found in the ileum of distal small intestine and large intestine. This hormone has numerous metabolic effects, such as decreasing stomach emptying, lowering the appetite, and glucose-dependent stimulation of insulin secretion. Moreover, GLP-1 protects neurons and decreases inflammation and apoptosis (Müller et al., [4]). GLP-1 is also known to originate in the brain, where it functions as a neurotransmitter (Paternoster and Falasca [5]). GLP-1 is released by neurons of the nucleus tractus solitarius (NTS) of the brainstem, hypothalamus, and cortical brain regions, which also express GLP-1 receptors (GLP-1R) (Llewellyn-Smith et al., [6]). The biological actions of GLP-1 are mediated by a G-protein coupled receptor (GLP-1 receptor) which acts via the adenylyl cyclase (AC) system (Whiting et al.,[7]). CNS and peripheral tissues express receptors of the GLP-1 (Bullock et al., [8]).The central GLP-1R in cognitive functions is involved, and it is studied (Müller et al. [4]). Several studies have proved that GLP-1R receptor agonism has a promising role to improve cognitive functions (Athauda et al. [9]). Improving associative and spatial learning after activation of CNS GLP-1R signaling was shown by During et al. According to their results, the learning deficit in mice with GLP-1R-deficient was ameliorated after transferring GLP-1R gene to the hippocampus (During et al. [10]). GLP-1R is expressed in the hippocampus of rodents (Rebosio et al. [11]), a part of the brain that incorporates spatial learning and memory (L&M) (Lamsa and Lau [12]). Some features of L&M, including performance in the Morris water maze (MWM) and latency in the passive avoidance test, have improved in rats after intracerebroventricular (ICV) treatment of GLP-1R agonists (Zhou et al. [13]). This effect of GLP-1 on L&M can be diminished by exendin-3 (9-39) which is a GLP-1R antagonist (During et al. [10]). Moreover, the administration of GLP-1R agonists into the hippocampus has led to improve the spatial L&M performances in Alzheimer’s disease (Qi et al. [14]; Wang et al. [15]).It is well accepted that physical activity has beneficial effects on brain activities (Erickson and Kramer, [16]). However, the underlying mechanisms of physical activity which affect the brain largely remain unclear. Previous studies have suggested some mechanisms that, through them, exercise plays a promising role in the brain, such as noradrenergic, serotonergic, and histaminergic neurotransmission (Taati et al., [17]), brain-derived neurotrophic factor (BDNF) (Chen and Russo-Neustadt [18]), insulin-like growth factor I (IGF-1), and vascular endothelial growth factor (VEGF) (Fabel et al. [19]).Evidence suggests that exercise increases the GLP-1 levels (Ueda et al. [20]). It was indicated that some levels of exercise, from moderate to high-intensity, can enhance GLP-1 levels (Holliday and Blannin [21]). For instance, Ueda et al. have reported that significant increases in GLP-1 plasma levels occurred in terms of exercise (Ueda et al. [22]).Based on these investigations, we decided to elucidate whether the central GLP-1 receptors have a role in the beneficial effects of exercise on L&M. Simultaneously, we revalidate the previously reported positive effects of GLP-1 on L&M performance.
## 2. Materials and Methods
### 2.1. Animals and Drugs
Thirty-two male Wistar rats (4 months old, an average weight of 300-350 g approximately) were obtained from the Teb Azma animal institute for biological sciences. All animals were maintained in a 12 h light/dark cycle at 21–25°C. Rats were individually housed in standard polycarbonate cages with standard sawdust as bedding. Animals were fed a standard pellet diet which had ad libitum access to water. The current research was authorized by the Lorestan University Ethics Committee (LU. ECRA.2021.7) and conducted in accordance with the National Institutes of Health Guide for the care and use of laboratory animals. Exendin-3 (9-39) (10μg/rat, 10 μl) (Tocris Co., UK) was mixed in normal saline and injected in intracerebroventricular (ICV) manner (Bell et al. [2]). Rats in saline-treated groups received the same volume of normal saline (10 μl).
### 2.2. Surgical Technique
Anesthesia of animals was performed by intraperitoneal administration of ketamine/xylazine (75 mg/kg-10 mg/kg), and rats were placed on a stereotaxic apparatus (RWD stereotaxic device, serial number: D00751-001, made in China). The method described by Paxinos and Watson (1987) was followed, and a stainless steel guide cannula (gauge 23) was cautiously placed in the right lateral ventricle (Herman and Watson [23]). The stereotaxic coordinates were AP=0.8, L=1.5, and V=3.2 mm. After properly inserting the cannula, it was secured with three stainless steel screws encircling each guiding cannula. Dental methyl methacrylate was then used to secure the cannula and screws to the skull. After surgical treatments, the rats were placed in their respective cages. Prior to conducting tests on rats, a five-day recovery period was accounted for.
### 2.3. Physical Exercise Protocol
After complete recovery, all animals of the exercise group experienced a 17 meters/min exercise for one hour each day, for seven consecutive days, as a mild exercise (Schemmel et al. [24]). To familiarize the animals with the treadmill apparatus and minimize stress, four days before the experiment period, all animals were placed in the treadmill apparatus for 10 min. Treadmill exercise was performed on a rodent treadmill (Tajhiz Gostar Omid Iranian. Co, Karaj, Iran). Running sessions on the treadmill were performed at noon every day. Each exercise began with a 10-minute warm-up (gradual acceleration), and the running pace was raised to 17 meters per minute. The last 10 minutes of the workout consisted of a gradual deceleration. Control group animals were placed on the treadmill for one hour; however, they did not experience an exercise program.
### 2.4. Experimental Design
All animals were randomly divided into four groups (n=8):
(1)
Sedentary saline (SED-SAL) group(2)
Sedentary-exendin-3 (SED-exendin) group(3)
3) Treadmill exercise-saline (TE-SAL) group(4)
4) Treadmill exercise-exendin-3 (TE-exendin) groupAll rats received the injections just before the exercise manually by hand at a flow rate of 10μl/minute using a Hamilton syringe (Hamilton 10 μl 701 RN Syringe, USA), daily for seven-day running period. After the last day of running, the animals were tested for L&M tests using Morris water maze (MWM) task.
### 2.5. Morris Water Maze (MWM) Test
We used a standard MWM task which was given in previous reports (Taati et al., [17]). MWM protocol is an acceptable test to evaluate L&M performance (O’Callaghan et al. [25]). The water maze tank was a circular tank with a diameter of 2 m and a depth of 0.4 m that was filled with tap water (23±1°C) on a daily basis. It was placed in a specific room with visual signals on the wall next to the pool. The pool was conceptually separated into four sections, and they were shown by four big marks made by foam for each direction (a star for N, a triangle for S, a rectangle for W, and a circle for E) visible from the surface of tank. An escape square platform (11 cm border), which was considered the target zone, was placed in the northwest quadrant in a permanent position 2 cm under the water surface during the test, except for the last day (measuring the latency). The rats experienced four trials each day for four days. At each trial, the rats were gently placed into the water at a different quadrant chosen randomly. The rat swam to find and locate the hidden platform. If the rats did not find the platform within one minute, they were guided to the platform by hand. A 20 second was considered for rats to rest on the escape platform; therefore, they were taken back to their cages for one minute. A video camera mounted above the center section of the tank recorded the swimming route and the time it took to reach the platform (latency), which was then evaluated using a video tracking path and analysis system. The day following the fourth trial, rats were tested on a probe trial that the escape platform was taken out, and rats swam for one minute. The time that the rats spent in the target zone was recorded for 60 seconds.
### 2.6. Statistical Analysis
The statistical analysis was performed using SPSS software for Windows (SPSS Inc., Chicago, USA, Ver. 25). To examine the interaction among groups and days in 4 levels and to ascertain the significant effects (“group” effect and “day” effect) on escape latency, a two-way ANOVA with repeated measures (days) was utilized for data in the learning phase. Moreover, data regarding memory retention test were analyzed using a two-way ANOVA to specify the significant main effects (“group” effect and “zone” effect) on time spent percentage and the interaction among groups in 4 levels and zones in 2 levels of the target and opposite zones. All analyses were followed by a post hoc Tukey’s test regarding the multiple comparison evaluation. All data were expressed asmeans±SEM. P<0.5 is considered a statistically significant difference.
## 2.1. Animals and Drugs
Thirty-two male Wistar rats (4 months old, an average weight of 300-350 g approximately) were obtained from the Teb Azma animal institute for biological sciences. All animals were maintained in a 12 h light/dark cycle at 21–25°C. Rats were individually housed in standard polycarbonate cages with standard sawdust as bedding. Animals were fed a standard pellet diet which had ad libitum access to water. The current research was authorized by the Lorestan University Ethics Committee (LU. ECRA.2021.7) and conducted in accordance with the National Institutes of Health Guide for the care and use of laboratory animals. Exendin-3 (9-39) (10μg/rat, 10 μl) (Tocris Co., UK) was mixed in normal saline and injected in intracerebroventricular (ICV) manner (Bell et al. [2]). Rats in saline-treated groups received the same volume of normal saline (10 μl).
## 2.2. Surgical Technique
Anesthesia of animals was performed by intraperitoneal administration of ketamine/xylazine (75 mg/kg-10 mg/kg), and rats were placed on a stereotaxic apparatus (RWD stereotaxic device, serial number: D00751-001, made in China). The method described by Paxinos and Watson (1987) was followed, and a stainless steel guide cannula (gauge 23) was cautiously placed in the right lateral ventricle (Herman and Watson [23]). The stereotaxic coordinates were AP=0.8, L=1.5, and V=3.2 mm. After properly inserting the cannula, it was secured with three stainless steel screws encircling each guiding cannula. Dental methyl methacrylate was then used to secure the cannula and screws to the skull. After surgical treatments, the rats were placed in their respective cages. Prior to conducting tests on rats, a five-day recovery period was accounted for.
## 2.3. Physical Exercise Protocol
After complete recovery, all animals of the exercise group experienced a 17 meters/min exercise for one hour each day, for seven consecutive days, as a mild exercise (Schemmel et al. [24]). To familiarize the animals with the treadmill apparatus and minimize stress, four days before the experiment period, all animals were placed in the treadmill apparatus for 10 min. Treadmill exercise was performed on a rodent treadmill (Tajhiz Gostar Omid Iranian. Co, Karaj, Iran). Running sessions on the treadmill were performed at noon every day. Each exercise began with a 10-minute warm-up (gradual acceleration), and the running pace was raised to 17 meters per minute. The last 10 minutes of the workout consisted of a gradual deceleration. Control group animals were placed on the treadmill for one hour; however, they did not experience an exercise program.
## 2.4. Experimental Design
All animals were randomly divided into four groups (n=8):
(1)
Sedentary saline (SED-SAL) group(2)
Sedentary-exendin-3 (SED-exendin) group(3)
3) Treadmill exercise-saline (TE-SAL) group(4)
4) Treadmill exercise-exendin-3 (TE-exendin) groupAll rats received the injections just before the exercise manually by hand at a flow rate of 10μl/minute using a Hamilton syringe (Hamilton 10 μl 701 RN Syringe, USA), daily for seven-day running period. After the last day of running, the animals were tested for L&M tests using Morris water maze (MWM) task.
## 2.5. Morris Water Maze (MWM) Test
We used a standard MWM task which was given in previous reports (Taati et al., [17]). MWM protocol is an acceptable test to evaluate L&M performance (O’Callaghan et al. [25]). The water maze tank was a circular tank with a diameter of 2 m and a depth of 0.4 m that was filled with tap water (23±1°C) on a daily basis. It was placed in a specific room with visual signals on the wall next to the pool. The pool was conceptually separated into four sections, and they were shown by four big marks made by foam for each direction (a star for N, a triangle for S, a rectangle for W, and a circle for E) visible from the surface of tank. An escape square platform (11 cm border), which was considered the target zone, was placed in the northwest quadrant in a permanent position 2 cm under the water surface during the test, except for the last day (measuring the latency). The rats experienced four trials each day for four days. At each trial, the rats were gently placed into the water at a different quadrant chosen randomly. The rat swam to find and locate the hidden platform. If the rats did not find the platform within one minute, they were guided to the platform by hand. A 20 second was considered for rats to rest on the escape platform; therefore, they were taken back to their cages for one minute. A video camera mounted above the center section of the tank recorded the swimming route and the time it took to reach the platform (latency), which was then evaluated using a video tracking path and analysis system. The day following the fourth trial, rats were tested on a probe trial that the escape platform was taken out, and rats swam for one minute. The time that the rats spent in the target zone was recorded for 60 seconds.
## 2.6. Statistical Analysis
The statistical analysis was performed using SPSS software for Windows (SPSS Inc., Chicago, USA, Ver. 25). To examine the interaction among groups and days in 4 levels and to ascertain the significant effects (“group” effect and “day” effect) on escape latency, a two-way ANOVA with repeated measures (days) was utilized for data in the learning phase. Moreover, data regarding memory retention test were analyzed using a two-way ANOVA to specify the significant main effects (“group” effect and “zone” effect) on time spent percentage and the interaction among groups in 4 levels and zones in 2 levels of the target and opposite zones. All analyses were followed by a post hoc Tukey’s test regarding the multiple comparison evaluation. All data were expressed asmeans±SEM. P<0.5 is considered a statistically significant difference.
## 3. Results
Acquisition data analysis of all groups is shown in Figure1 for four days of the trial test. Based on two-way ANOVA test, a significant effect of groups (F3,432=1.707, P<0.01) and days (F3,432=0.804, P<0.01) was revealed on the escape latencies. The results revealed that data regarding escape latencies of treadmill exercise-saline group were remarkably lower than that of sedentary saline group on the third and fourth days of the experiment. The TE-exendin group had a significantly longer escape latency than the TE-SAL group on the second, third, and fourth day (P<0.05). The result of the memory retention test is shown in Figure 2(a). The escape latency of treadmill exercise-saline group was significantly low compared to that of other experimental groups (P<0.05). As shown in Figure 2(b), spent time in the target zone was significantly increased in the treadmill exercise-saline group compared to the sedentary saline group (P<0.05).Figure 1
Effects of using the GLP-1 receptors antagonist (exendine-3) during treadmill exercise on learning tested by the MWM task. Data are expressed as themean±SEM. ∗ is for P<0.05 and # is for P<0.01.Figure 2
Effect of using the GLP-1-receptors antagonist (exendin-3) during treadmill exercise on memory tested by the MWM task. (a) Mean escape latencies. (b) Meantime spent in the target zone. Data are expressed as themean±SEM. ∗ is for P<0.05 and # is for P<0.01.
(a)(b)
## 4. Discussion
In rats, moderate treadmill activity improves L&M performance via the MWM task, and ICV injection of exendin-3 blocks these favorable effects of exercise (9-39). These findings indicate that central GLP-1 receptors may mediate the effects of exercise on L&M. This is the first study we are aware of that has shown that exercise may exert its beneficial effects on cognitive functions via central GLP-1 receptors. This finding that exercise improves L&M confirms our previous study and other research indicating the beneficial effects of exercise on L&M (Liu et al. [26]; Hajisoltani et al. [27]). Treadmill running remains one of the most acceptable samples of physical exercise in rat investigations (Liu et al. [26]).It is evident that blocking the central GLP-1R by ICV injection of exendin-3 had no significant effect on L&M in sedentary (nonexercised) rats. Since ICV injection of exendin-3 had not shown adverse effects on L&M in normal situations and its use in exercised rats impaired the beneficial effects of exercise on L&M, it is likely to hypothesize that the valuable effects of exercise on L&M may be triggered by the central GLP-1R.Many reports hypothesized that exercise leads to improve brain function via regulating the GLP-1 release. It is shown that mild and moderate exercise increases GLP-1 concentrations in plasma. For instance, Ueda et al. indicated that an aerobic exercise protocol significantly increased GLP-1 concentration in blood (Ueda et al. [22]). Its physiological processes, however, were unclear. The rise in GLP-1 concentration seen after exercise has been linked to skeletal muscle-derived interleukin-6 or a sciatic nerve afferent route through a humoral pathway in one research (Ellingsgaard et al. [28]). On the other hand, it is proven that the administration of GLP-1R agonists improves L&M (Isacson et al. [29]; Gengler et al. [30]). GLP-1R expression was detected in the brain-specific cellular subtypes, which play a critical role in L&M, such as granule cells of the dentate gyrus in the hippocampus and pyramidal neurons of the CA1 region (Hamilton and Hölscher [31]). Furthermore, since GLP-1’s involvement in synaptic plasticity is well understood, it is thought that GLP-1 may have a role in the regulation of many signaling pathways involved in L&M and other synaptic activities (Gault and Hölscher [32]; Simsir et al. [33]). Its glycemic normalization has no influence on these effects (Grieco et al. [34]).Several mechanisms seem to play a role in exercise-induced enhancement of L&M via GLP-1 receptors. One possibility is an interaction between GLP-1 and hippocampal LTP. Presently, much evidence demonstrates that synaptic plasticity, including LTP, mediates hippocampal-dependent memory (O’Callaghan et al. [25]). On the other hand, it is well accepted that exercise enhances LTP, neurotransmission, cell proliferation, neurogenesis, and expression of genes relating to growth factors in the hippocampus of rats (Cotman and Berchtold [35]). GLP-1 has considerable cognitive-related benefits in the hippocampus, which is an important brain area for L&M, according to data. GLP-1 improves hippocampus LTP production in mice, according to Day et al. (Day et al. [36]). The GLP-1 agonist was discovered to lower potassium channel (Kv4.2) values in the hippocampus, increasing dendritic membrane excitability (Chen et al. [37]). Moreover, Taha et al. (Taha et al. [38]) showed that GLP-1 agonists impede phosphorylation of the mRNA translational factor eEF2 increasing protein synthesis. Hippocampal neurons express Kv4.2 channels, and they act as a regulator in the generation of the backpropagating action potential, which is essential for LTP induction at the hippocampus in physiological situations. Previous research has proven that Kv4.2 inhibits mice from an exhibition of hippocampal LTP production (Chen et al. [37]), and therefore a potential mechanism underlying the early LTP-enhancing effects by GLP-1.Furthermore, it was emphasized that GLP-1 can enhance BDNF in the brain. It has been clarified in several studies that there is an association between exercise and an increased BDNF level in the brain (Bekinschtein et al. [39]). The role of GLP-1 to inhibit apoptosis, neuronal growth, cell proliferation, and decreasing oxidative damage in the CNS has been recently revealed (Athauda and Foltynie [40]). GLP-1 binding to its receptors which are widely expressed in the brain (Alvarez et al. [41]) increases cAMP and activates the PI3 K (phosphoinositide 3-kinase) signaling pathway, which leads to the activation of AKT (protein kinase B) signaling pathways (Kim et al. [42]). The activation of these pathways results in the production of multiple targets (Athauda and Foltynie [43]), such as GSK-3β (glycogen synthase kinase-3β), NFκB (nuclear factor-κB), and CREB (cyclic adenosine monophosphate response element-binding protein). Of note, CREB is a crucial player in modulating BDNF production. BDNF was widely studied in cognition, inflammation, and neurogenerative disorders. GLP-1 analogs, such as exenatide and liraglutide, have neuroprotective effects in animal models of Alzheimer’s disease (AD) (Athauda and Foltynie [44]).
## 5. Conclusion
In general, we concluded that exercise-induced enhancement of spatial L&M function in rats was prevented by blockade of central GLP-1R using exendin-3. This result indicates that GLP-1 has a significant role to mediate the beneficial effects of physical exercise on cognitive functions.
---
*Source: 2900628-2022-06-21.xml* | 2900628-2022-06-21_2900628-2022-06-21.md | 24,459 | Exercise Improves Spatial Learning and Memory Performance through the Central GLP-1 Receptors | Majid Taati; Peyman Esmaeili Fard Barzegar; Abbas Raisi | Behavioural Neurology
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2900628 | 2900628-2022-06-21.xml | ---
## Abstract
The glucagon-like peptide 1 (GLP-1) is a hormone which is produced in the enteroendocrine L-cells in the ileum and the neurons of nucleus tractus solitarius (NTS) in the brain which has numerous metabolic effects. The central GLP-1R’s role in cognitive functioning is well known. On the contrary, it has been shown that exercise has positive effects on brain function. So, we decided to elucidate whether the central GLP-1 has a role in memory and learning. Thirty-two rats were used in this experiment in 4 groups. After anesthetizing the rats, the right lateral ventricle was detected, and a cannula was directed to the ventricle. Ten micrograms of exendin-3 or sterile saline, according to the group, was injected via ICV once daily for seven days. The rats in the exercise group considered an exercise period of one hour each day (17 meters per minute) for seven consecutive days. To evaluate the performance of memory and learning, a standard Morris water maze (MWM) tank was utilized. According to the results, the TE-exendin group showed a statistically significant difference from the TE-SAL group in both parameters of latency and time in the zone. In summary, memory and learning were improved by GLP-1R in the exercise group, but not in the sedentary group, which we can hypothesize that exercise can affect memory and learning through this pathway.
---
## Body
## 1. Introduction
Memory and learning loss is regarded as one of the world’s greatest issues brought on by age, accidents, and even some pharmaceuticals. Although several research have been conducted on medicines to prevent age-related cognitive decline, effective treatments for cognition and memory enhancement are not yet available (Coppi et al. [1]). The glucagon-like peptide 1 (GLP-1) is mainly composed of 160-amino acid proglucagon precursor protein (Bell et al. [2]; Ye et al. [3]) in the enteroendocrine L-cells found in the ileum of distal small intestine and large intestine. This hormone has numerous metabolic effects, such as decreasing stomach emptying, lowering the appetite, and glucose-dependent stimulation of insulin secretion. Moreover, GLP-1 protects neurons and decreases inflammation and apoptosis (Müller et al., [4]). GLP-1 is also known to originate in the brain, where it functions as a neurotransmitter (Paternoster and Falasca [5]). GLP-1 is released by neurons of the nucleus tractus solitarius (NTS) of the brainstem, hypothalamus, and cortical brain regions, which also express GLP-1 receptors (GLP-1R) (Llewellyn-Smith et al., [6]). The biological actions of GLP-1 are mediated by a G-protein coupled receptor (GLP-1 receptor) which acts via the adenylyl cyclase (AC) system (Whiting et al.,[7]). CNS and peripheral tissues express receptors of the GLP-1 (Bullock et al., [8]).The central GLP-1R in cognitive functions is involved, and it is studied (Müller et al. [4]). Several studies have proved that GLP-1R receptor agonism has a promising role to improve cognitive functions (Athauda et al. [9]). Improving associative and spatial learning after activation of CNS GLP-1R signaling was shown by During et al. According to their results, the learning deficit in mice with GLP-1R-deficient was ameliorated after transferring GLP-1R gene to the hippocampus (During et al. [10]). GLP-1R is expressed in the hippocampus of rodents (Rebosio et al. [11]), a part of the brain that incorporates spatial learning and memory (L&M) (Lamsa and Lau [12]). Some features of L&M, including performance in the Morris water maze (MWM) and latency in the passive avoidance test, have improved in rats after intracerebroventricular (ICV) treatment of GLP-1R agonists (Zhou et al. [13]). This effect of GLP-1 on L&M can be diminished by exendin-3 (9-39) which is a GLP-1R antagonist (During et al. [10]). Moreover, the administration of GLP-1R agonists into the hippocampus has led to improve the spatial L&M performances in Alzheimer’s disease (Qi et al. [14]; Wang et al. [15]).It is well accepted that physical activity has beneficial effects on brain activities (Erickson and Kramer, [16]). However, the underlying mechanisms of physical activity which affect the brain largely remain unclear. Previous studies have suggested some mechanisms that, through them, exercise plays a promising role in the brain, such as noradrenergic, serotonergic, and histaminergic neurotransmission (Taati et al., [17]), brain-derived neurotrophic factor (BDNF) (Chen and Russo-Neustadt [18]), insulin-like growth factor I (IGF-1), and vascular endothelial growth factor (VEGF) (Fabel et al. [19]).Evidence suggests that exercise increases the GLP-1 levels (Ueda et al. [20]). It was indicated that some levels of exercise, from moderate to high-intensity, can enhance GLP-1 levels (Holliday and Blannin [21]). For instance, Ueda et al. have reported that significant increases in GLP-1 plasma levels occurred in terms of exercise (Ueda et al. [22]).Based on these investigations, we decided to elucidate whether the central GLP-1 receptors have a role in the beneficial effects of exercise on L&M. Simultaneously, we revalidate the previously reported positive effects of GLP-1 on L&M performance.
## 2. Materials and Methods
### 2.1. Animals and Drugs
Thirty-two male Wistar rats (4 months old, an average weight of 300-350 g approximately) were obtained from the Teb Azma animal institute for biological sciences. All animals were maintained in a 12 h light/dark cycle at 21–25°C. Rats were individually housed in standard polycarbonate cages with standard sawdust as bedding. Animals were fed a standard pellet diet which had ad libitum access to water. The current research was authorized by the Lorestan University Ethics Committee (LU. ECRA.2021.7) and conducted in accordance with the National Institutes of Health Guide for the care and use of laboratory animals. Exendin-3 (9-39) (10μg/rat, 10 μl) (Tocris Co., UK) was mixed in normal saline and injected in intracerebroventricular (ICV) manner (Bell et al. [2]). Rats in saline-treated groups received the same volume of normal saline (10 μl).
### 2.2. Surgical Technique
Anesthesia of animals was performed by intraperitoneal administration of ketamine/xylazine (75 mg/kg-10 mg/kg), and rats were placed on a stereotaxic apparatus (RWD stereotaxic device, serial number: D00751-001, made in China). The method described by Paxinos and Watson (1987) was followed, and a stainless steel guide cannula (gauge 23) was cautiously placed in the right lateral ventricle (Herman and Watson [23]). The stereotaxic coordinates were AP=0.8, L=1.5, and V=3.2 mm. After properly inserting the cannula, it was secured with three stainless steel screws encircling each guiding cannula. Dental methyl methacrylate was then used to secure the cannula and screws to the skull. After surgical treatments, the rats were placed in their respective cages. Prior to conducting tests on rats, a five-day recovery period was accounted for.
### 2.3. Physical Exercise Protocol
After complete recovery, all animals of the exercise group experienced a 17 meters/min exercise for one hour each day, for seven consecutive days, as a mild exercise (Schemmel et al. [24]). To familiarize the animals with the treadmill apparatus and minimize stress, four days before the experiment period, all animals were placed in the treadmill apparatus for 10 min. Treadmill exercise was performed on a rodent treadmill (Tajhiz Gostar Omid Iranian. Co, Karaj, Iran). Running sessions on the treadmill were performed at noon every day. Each exercise began with a 10-minute warm-up (gradual acceleration), and the running pace was raised to 17 meters per minute. The last 10 minutes of the workout consisted of a gradual deceleration. Control group animals were placed on the treadmill for one hour; however, they did not experience an exercise program.
### 2.4. Experimental Design
All animals were randomly divided into four groups (n=8):
(1)
Sedentary saline (SED-SAL) group(2)
Sedentary-exendin-3 (SED-exendin) group(3)
3) Treadmill exercise-saline (TE-SAL) group(4)
4) Treadmill exercise-exendin-3 (TE-exendin) groupAll rats received the injections just before the exercise manually by hand at a flow rate of 10μl/minute using a Hamilton syringe (Hamilton 10 μl 701 RN Syringe, USA), daily for seven-day running period. After the last day of running, the animals were tested for L&M tests using Morris water maze (MWM) task.
### 2.5. Morris Water Maze (MWM) Test
We used a standard MWM task which was given in previous reports (Taati et al., [17]). MWM protocol is an acceptable test to evaluate L&M performance (O’Callaghan et al. [25]). The water maze tank was a circular tank with a diameter of 2 m and a depth of 0.4 m that was filled with tap water (23±1°C) on a daily basis. It was placed in a specific room with visual signals on the wall next to the pool. The pool was conceptually separated into four sections, and they were shown by four big marks made by foam for each direction (a star for N, a triangle for S, a rectangle for W, and a circle for E) visible from the surface of tank. An escape square platform (11 cm border), which was considered the target zone, was placed in the northwest quadrant in a permanent position 2 cm under the water surface during the test, except for the last day (measuring the latency). The rats experienced four trials each day for four days. At each trial, the rats were gently placed into the water at a different quadrant chosen randomly. The rat swam to find and locate the hidden platform. If the rats did not find the platform within one minute, they were guided to the platform by hand. A 20 second was considered for rats to rest on the escape platform; therefore, they were taken back to their cages for one minute. A video camera mounted above the center section of the tank recorded the swimming route and the time it took to reach the platform (latency), which was then evaluated using a video tracking path and analysis system. The day following the fourth trial, rats were tested on a probe trial that the escape platform was taken out, and rats swam for one minute. The time that the rats spent in the target zone was recorded for 60 seconds.
### 2.6. Statistical Analysis
The statistical analysis was performed using SPSS software for Windows (SPSS Inc., Chicago, USA, Ver. 25). To examine the interaction among groups and days in 4 levels and to ascertain the significant effects (“group” effect and “day” effect) on escape latency, a two-way ANOVA with repeated measures (days) was utilized for data in the learning phase. Moreover, data regarding memory retention test were analyzed using a two-way ANOVA to specify the significant main effects (“group” effect and “zone” effect) on time spent percentage and the interaction among groups in 4 levels and zones in 2 levels of the target and opposite zones. All analyses were followed by a post hoc Tukey’s test regarding the multiple comparison evaluation. All data were expressed asmeans±SEM. P<0.5 is considered a statistically significant difference.
## 2.1. Animals and Drugs
Thirty-two male Wistar rats (4 months old, an average weight of 300-350 g approximately) were obtained from the Teb Azma animal institute for biological sciences. All animals were maintained in a 12 h light/dark cycle at 21–25°C. Rats were individually housed in standard polycarbonate cages with standard sawdust as bedding. Animals were fed a standard pellet diet which had ad libitum access to water. The current research was authorized by the Lorestan University Ethics Committee (LU. ECRA.2021.7) and conducted in accordance with the National Institutes of Health Guide for the care and use of laboratory animals. Exendin-3 (9-39) (10μg/rat, 10 μl) (Tocris Co., UK) was mixed in normal saline and injected in intracerebroventricular (ICV) manner (Bell et al. [2]). Rats in saline-treated groups received the same volume of normal saline (10 μl).
## 2.2. Surgical Technique
Anesthesia of animals was performed by intraperitoneal administration of ketamine/xylazine (75 mg/kg-10 mg/kg), and rats were placed on a stereotaxic apparatus (RWD stereotaxic device, serial number: D00751-001, made in China). The method described by Paxinos and Watson (1987) was followed, and a stainless steel guide cannula (gauge 23) was cautiously placed in the right lateral ventricle (Herman and Watson [23]). The stereotaxic coordinates were AP=0.8, L=1.5, and V=3.2 mm. After properly inserting the cannula, it was secured with three stainless steel screws encircling each guiding cannula. Dental methyl methacrylate was then used to secure the cannula and screws to the skull. After surgical treatments, the rats were placed in their respective cages. Prior to conducting tests on rats, a five-day recovery period was accounted for.
## 2.3. Physical Exercise Protocol
After complete recovery, all animals of the exercise group experienced a 17 meters/min exercise for one hour each day, for seven consecutive days, as a mild exercise (Schemmel et al. [24]). To familiarize the animals with the treadmill apparatus and minimize stress, four days before the experiment period, all animals were placed in the treadmill apparatus for 10 min. Treadmill exercise was performed on a rodent treadmill (Tajhiz Gostar Omid Iranian. Co, Karaj, Iran). Running sessions on the treadmill were performed at noon every day. Each exercise began with a 10-minute warm-up (gradual acceleration), and the running pace was raised to 17 meters per minute. The last 10 minutes of the workout consisted of a gradual deceleration. Control group animals were placed on the treadmill for one hour; however, they did not experience an exercise program.
## 2.4. Experimental Design
All animals were randomly divided into four groups (n=8):
(1)
Sedentary saline (SED-SAL) group(2)
Sedentary-exendin-3 (SED-exendin) group(3)
3) Treadmill exercise-saline (TE-SAL) group(4)
4) Treadmill exercise-exendin-3 (TE-exendin) groupAll rats received the injections just before the exercise manually by hand at a flow rate of 10μl/minute using a Hamilton syringe (Hamilton 10 μl 701 RN Syringe, USA), daily for seven-day running period. After the last day of running, the animals were tested for L&M tests using Morris water maze (MWM) task.
## 2.5. Morris Water Maze (MWM) Test
We used a standard MWM task which was given in previous reports (Taati et al., [17]). MWM protocol is an acceptable test to evaluate L&M performance (O’Callaghan et al. [25]). The water maze tank was a circular tank with a diameter of 2 m and a depth of 0.4 m that was filled with tap water (23±1°C) on a daily basis. It was placed in a specific room with visual signals on the wall next to the pool. The pool was conceptually separated into four sections, and they were shown by four big marks made by foam for each direction (a star for N, a triangle for S, a rectangle for W, and a circle for E) visible from the surface of tank. An escape square platform (11 cm border), which was considered the target zone, was placed in the northwest quadrant in a permanent position 2 cm under the water surface during the test, except for the last day (measuring the latency). The rats experienced four trials each day for four days. At each trial, the rats were gently placed into the water at a different quadrant chosen randomly. The rat swam to find and locate the hidden platform. If the rats did not find the platform within one minute, they were guided to the platform by hand. A 20 second was considered for rats to rest on the escape platform; therefore, they were taken back to their cages for one minute. A video camera mounted above the center section of the tank recorded the swimming route and the time it took to reach the platform (latency), which was then evaluated using a video tracking path and analysis system. The day following the fourth trial, rats were tested on a probe trial that the escape platform was taken out, and rats swam for one minute. The time that the rats spent in the target zone was recorded for 60 seconds.
## 2.6. Statistical Analysis
The statistical analysis was performed using SPSS software for Windows (SPSS Inc., Chicago, USA, Ver. 25). To examine the interaction among groups and days in 4 levels and to ascertain the significant effects (“group” effect and “day” effect) on escape latency, a two-way ANOVA with repeated measures (days) was utilized for data in the learning phase. Moreover, data regarding memory retention test were analyzed using a two-way ANOVA to specify the significant main effects (“group” effect and “zone” effect) on time spent percentage and the interaction among groups in 4 levels and zones in 2 levels of the target and opposite zones. All analyses were followed by a post hoc Tukey’s test regarding the multiple comparison evaluation. All data were expressed asmeans±SEM. P<0.5 is considered a statistically significant difference.
## 3. Results
Acquisition data analysis of all groups is shown in Figure1 for four days of the trial test. Based on two-way ANOVA test, a significant effect of groups (F3,432=1.707, P<0.01) and days (F3,432=0.804, P<0.01) was revealed on the escape latencies. The results revealed that data regarding escape latencies of treadmill exercise-saline group were remarkably lower than that of sedentary saline group on the third and fourth days of the experiment. The TE-exendin group had a significantly longer escape latency than the TE-SAL group on the second, third, and fourth day (P<0.05). The result of the memory retention test is shown in Figure 2(a). The escape latency of treadmill exercise-saline group was significantly low compared to that of other experimental groups (P<0.05). As shown in Figure 2(b), spent time in the target zone was significantly increased in the treadmill exercise-saline group compared to the sedentary saline group (P<0.05).Figure 1
Effects of using the GLP-1 receptors antagonist (exendine-3) during treadmill exercise on learning tested by the MWM task. Data are expressed as themean±SEM. ∗ is for P<0.05 and # is for P<0.01.Figure 2
Effect of using the GLP-1-receptors antagonist (exendin-3) during treadmill exercise on memory tested by the MWM task. (a) Mean escape latencies. (b) Meantime spent in the target zone. Data are expressed as themean±SEM. ∗ is for P<0.05 and # is for P<0.01.
(a)(b)
## 4. Discussion
In rats, moderate treadmill activity improves L&M performance via the MWM task, and ICV injection of exendin-3 blocks these favorable effects of exercise (9-39). These findings indicate that central GLP-1 receptors may mediate the effects of exercise on L&M. This is the first study we are aware of that has shown that exercise may exert its beneficial effects on cognitive functions via central GLP-1 receptors. This finding that exercise improves L&M confirms our previous study and other research indicating the beneficial effects of exercise on L&M (Liu et al. [26]; Hajisoltani et al. [27]). Treadmill running remains one of the most acceptable samples of physical exercise in rat investigations (Liu et al. [26]).It is evident that blocking the central GLP-1R by ICV injection of exendin-3 had no significant effect on L&M in sedentary (nonexercised) rats. Since ICV injection of exendin-3 had not shown adverse effects on L&M in normal situations and its use in exercised rats impaired the beneficial effects of exercise on L&M, it is likely to hypothesize that the valuable effects of exercise on L&M may be triggered by the central GLP-1R.Many reports hypothesized that exercise leads to improve brain function via regulating the GLP-1 release. It is shown that mild and moderate exercise increases GLP-1 concentrations in plasma. For instance, Ueda et al. indicated that an aerobic exercise protocol significantly increased GLP-1 concentration in blood (Ueda et al. [22]). Its physiological processes, however, were unclear. The rise in GLP-1 concentration seen after exercise has been linked to skeletal muscle-derived interleukin-6 or a sciatic nerve afferent route through a humoral pathway in one research (Ellingsgaard et al. [28]). On the other hand, it is proven that the administration of GLP-1R agonists improves L&M (Isacson et al. [29]; Gengler et al. [30]). GLP-1R expression was detected in the brain-specific cellular subtypes, which play a critical role in L&M, such as granule cells of the dentate gyrus in the hippocampus and pyramidal neurons of the CA1 region (Hamilton and Hölscher [31]). Furthermore, since GLP-1’s involvement in synaptic plasticity is well understood, it is thought that GLP-1 may have a role in the regulation of many signaling pathways involved in L&M and other synaptic activities (Gault and Hölscher [32]; Simsir et al. [33]). Its glycemic normalization has no influence on these effects (Grieco et al. [34]).Several mechanisms seem to play a role in exercise-induced enhancement of L&M via GLP-1 receptors. One possibility is an interaction between GLP-1 and hippocampal LTP. Presently, much evidence demonstrates that synaptic plasticity, including LTP, mediates hippocampal-dependent memory (O’Callaghan et al. [25]). On the other hand, it is well accepted that exercise enhances LTP, neurotransmission, cell proliferation, neurogenesis, and expression of genes relating to growth factors in the hippocampus of rats (Cotman and Berchtold [35]). GLP-1 has considerable cognitive-related benefits in the hippocampus, which is an important brain area for L&M, according to data. GLP-1 improves hippocampus LTP production in mice, according to Day et al. (Day et al. [36]). The GLP-1 agonist was discovered to lower potassium channel (Kv4.2) values in the hippocampus, increasing dendritic membrane excitability (Chen et al. [37]). Moreover, Taha et al. (Taha et al. [38]) showed that GLP-1 agonists impede phosphorylation of the mRNA translational factor eEF2 increasing protein synthesis. Hippocampal neurons express Kv4.2 channels, and they act as a regulator in the generation of the backpropagating action potential, which is essential for LTP induction at the hippocampus in physiological situations. Previous research has proven that Kv4.2 inhibits mice from an exhibition of hippocampal LTP production (Chen et al. [37]), and therefore a potential mechanism underlying the early LTP-enhancing effects by GLP-1.Furthermore, it was emphasized that GLP-1 can enhance BDNF in the brain. It has been clarified in several studies that there is an association between exercise and an increased BDNF level in the brain (Bekinschtein et al. [39]). The role of GLP-1 to inhibit apoptosis, neuronal growth, cell proliferation, and decreasing oxidative damage in the CNS has been recently revealed (Athauda and Foltynie [40]). GLP-1 binding to its receptors which are widely expressed in the brain (Alvarez et al. [41]) increases cAMP and activates the PI3 K (phosphoinositide 3-kinase) signaling pathway, which leads to the activation of AKT (protein kinase B) signaling pathways (Kim et al. [42]). The activation of these pathways results in the production of multiple targets (Athauda and Foltynie [43]), such as GSK-3β (glycogen synthase kinase-3β), NFκB (nuclear factor-κB), and CREB (cyclic adenosine monophosphate response element-binding protein). Of note, CREB is a crucial player in modulating BDNF production. BDNF was widely studied in cognition, inflammation, and neurogenerative disorders. GLP-1 analogs, such as exenatide and liraglutide, have neuroprotective effects in animal models of Alzheimer’s disease (AD) (Athauda and Foltynie [44]).
## 5. Conclusion
In general, we concluded that exercise-induced enhancement of spatial L&M function in rats was prevented by blockade of central GLP-1R using exendin-3. This result indicates that GLP-1 has a significant role to mediate the beneficial effects of physical exercise on cognitive functions.
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*Source: 2900628-2022-06-21.xml* | 2022 |
# Presynaptic NMDA Receptors Influence Ca2+ Dynamics by Interacting with Voltage-Dependent Calcium Channels during the Induction of Long-Term Depression
**Authors:** Florian B. Neubauer; Rogier Min; Thomas Nevian
**Journal:** Neural Plasticity
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2900875
---
## Abstract
Spike-timing-dependent long-term depression (t-LTD) of glutamatergic layer (L)4-L2/3 synapses in developing neocortex requires activation of astrocytes by endocannabinoids (eCBs), which release glutamate onto presynaptic NMDA receptors (preNMDARs). The exact function of preNMDARs in this context is still elusive and strongly debated. To elucidate their function, we show that bath application of the eCB 2-arachidonylglycerol (2-AG) induces a preNMDAR-dependent form of chemically induced LTD (eCB-LTD) in L2/3 pyramidal neurons in the juvenile somatosensory cortex of rats. Presynaptic Ca2+ imaging from L4 spiny stellate axons revealed that action potential (AP) evoked Ca2+ transients show a preNMDAR-dependent broadening during eCB-LTD induction. However, blockade of voltage-dependent Ca2+ channels (VDCCs) did not uncover direct preNMDAR-mediated Ca2+ transients in the axon. This suggests that astrocyte-mediated glutamate release onto preNMDARs does not result in a direct Ca2+ influx, but that it instead leads to an indirect interaction with presynaptic VDCCs, boosting axonal Ca2+ influx. These results reveal one of the main remaining missing pieces in the signaling cascade of t-LTD at developing cortical synapses.
---
## Body
## 1. Introduction
Presynaptic NMDA receptors (preNMDARs) have important functions in synaptic transmission, information processing, and long-term plasticity in several regions of the brain [1–3]. Particularly, preNMDARs are thought to be required for the induction of spike-timing-dependent LTD (t-LTD) at developing neocortical synapses [4–7]. Recently, we suggested that t-LTD in the developing rat barrel cortex requires eCB-dependent activation of astrocytes, which results in the release of glutamate onto preNMDARs [8, 9]. Importantly, we showed that astrocyte activity alone is not sufficient for the induction of LTD. Simultaneous presynaptic APs concomitant with astrocyte activation are required [8]. This suggests that axonal APs interact with preNMDARs in a yet unknown way leading to the induction of t-LTD.Under certain conditions, preNMDARs in barrel cortex can also function as autoreceptors for presynaptically released glutamate. Bursts of APs followed by a correctly timed additional AP can induce pattern-dependent LTD at the L4-L2/3 synapse [10]. Importantly, since this form of LTD requires presynaptic release of glutamate, it bypasses the need for astrocyte activation. Similarly, bursts of APs in the visual cortex can induce preNMDAR dependent LTD at L4-L4 connections [11]. Therefore, preNMDAR-mediated LTD always requires presynaptic activity, whereas the source of the glutamate (astrocytic or presynaptic) might vary. This implies that there should be a presynaptic coincidence detection mechanism involving both presynaptic activity and preNMDAR activation.Despite the studies highlighted above, there is an active debate about the existence and function of preNMDARs. This debate is mainly fueled by contradictory findings on presynaptic Ca2+ signals mediated by preNMDARs. Lack of axonal Ca2+ signals in boutons of L5 and L4 neurons in developing neocortex upon iontophoresis of aspartate or upon MNI-glutamate uncaging, and lack of an APV sensitive component in single AP-evoked Ca2+ transients argue against the existence of preNMDARs [12–14]. On the other hand, there is ample anatomical and physiological evidence for the presence of preNMDARs [1, 2]. Yet, their mechanism of function remains elusive. It has been hypothesized that either a direct presynaptic Ca2+ influx through preNMDARs, a presynaptic depolarization mediated by Na+ influx through preNMDARs [15] or a metabotropic effect [16], could be the mechanism of preNMDAR function. The properties of preNMDARs strongly depend on their subunit composition, which can influence permeability for Ca2+, voltage-sensitive Mg2+ block, subcellular location, and gating kinetics. preNMDARs at cortical synapses contain GluN2C, GluN2D, or GluN3A subunits, rendering them relatively Mg2+ insensitive with low permeability for Ca2+ [17, 18]. Consistently, a direct presynaptic Ca2+ influx through preNMDARs at cortical synapses has rarely been observed. At a fraction of cortical L5 boutons, pairing activation of preNMDARs by glutamate uncaging and high-frequency AP firing causes an enhancement of axonal Ca2+ influx [19]. In contrast, preNMDARs located on parallel fibres in the cerebellum seem to be permeable for Ca2+, and a direct preNMDAR-mediated Ca2+ influx has been reported [20].Here, we hypothesize that the activation of preNMDARs alone is not sufficient to evoke a detectable Ca2+ signal in L4 boutons in developing barrel cortex, but that the interaction with axonal APs is required. To investigate this hypothesis, we utilized a form of chemical LTD mediated by bath application of 2-AG combined with presynaptic Ca2+ imaging. First, we showed that eCB-LTD depended on astrocyte and preNMDAR activation. Bath application of 2-AG should globally activate astrocytes that innervate preNMDARs, thus, increasing the probability to detect an influence on presynaptic Ca2+ dynamics. Indeed, we observed an APV-sensitive broadening of AP-evoked Ca2+ transients. Investigation of the underlying mechanism suggested that preNMDARs have little Ca2+ permeability and that their major mechanism of function is to interact with voltage-dependent Ca2+ channels (VDCCs) to prolong AP-evoked Ca2+ influx in presynaptic boutons. Our data is consistent with previous results and can help to reconcile apparent contradictory observations, thereby contributing to a better mechanistic understanding of preNMDAR function.
## 2. Material and Methods
### 2.1. Slice Preparation
Experiments were approved by the Veterinary Office of the Canton of Bern, Switzerland. Thalamocortical brain slices containing the barrel subfield of somatosensory cortex were prepared from 12–21 d old Wistar rats of either sex [21]. Rats were decapitated, and their brains were quickly removed into cold (0–4°C) oxygenated physiological solution containing 125 mM NaCl, 2.5 mM KCl, 1.25 mM NaH2PO4, 25 mM NaHCO3, 1 mM MgCl2, 2 mM CaCl2, and 25 mM glucose. Slices, 300 μm thick, were cut from the tissue block with a vibratome (Microm) and kept at 37°C for 30 min and then at room temperature until use.
### 2.2. Electrophysiology
All experiments were performed at 30–34°C. For recording, slices were transferred to a recording chamber perfused with oxygenated physiological solution (same as above). The barrel subfield of somatosensory cortex was identified by the presence of barrels in L4, visible under trans-illumination. A monopolar glass stimulation electrode was placed in a L4 barrel, and whole-cell recordings for plasticity experiments were performed from L2/3 pyramidal neurons right above the corresponding barrel. Cells were identified using infrared gradient contrast video microscopy. Recording electrodes with a resistance of 4–7 MΩ were made using borosilicate glass capillaries. Recordings were performed using Dagan BVC-700A amplifiers (Dagan). Data were acquired with an ITC-16 AD-DA board (Instrutech) and using Igor software (Wavemetrics). The intracellular solution for recording neurons contained 130 mM potassium gluconate, 10 mM potassium HEPES, 10 mM sodium phosphocreatine, 4 mM Mg-ATP, 0.3 mM Na-GTP, 4 mM NaCl, 10 mM sodium gluconate (pH 7.3 with KOH), and biocytin (0.2% w/v).Single component EPSPs in the pyramidal neuron with amplitudes between 1 and 5 mV were evoked by stimulation in L4. After obtaining a stable baseline for 10 min at 0.1 Hz stimulation, the endocannabinoid 2-AG (10-20μM) was bath applied for 20 min, while continuing the extracellular stimulation. During wash-out, EPSPs were recorded for an additional 40 min. Experiments were discarded if the baseline EPSP slope was unstable (>10% change between first 15 and last 15 EPSP slopes of the baseline period), or if the pyramidal neuron input resistance or membrane potential changed by >15% during the course of the experiment.To investigate the influence of astrocytes on synaptic depression, whole-cell patch clamp recordings were performed from astrocytes adjacent to the recorded pyramidal neuron in L2/3. The intracellular solution for recording astrocytes contained 135 mM KCH3O3S, 10 mM HEPES, 10 mM sodium phosphocreatine, 4 mM MgCl2, 4 mM Na2-ATP, and 0.4 mM Na-GTP (pH 7.2 with KOH). Astrocytes were characterized by a low resting membrane potential, passive responses to both negative and positive current injections, and a low membrane resistance [8]. For astrocyte Ca2+ clamp experiments, 200 μM OGB-1, 0.45 mM EGTA, and 0.14 mM CaCl2 were added to the astrocyte intracellular solution to clamp intracellular free Ca2+ at a steady-state concentration of 50–80 nM [22].For axonal Ca2+ imaging experiments, recordings from spiny stellate neurons in L4 of the barrel cortex were performed in the whole-cell current clamp configuration. The intracellular solution was supplemented with the Ca2+ indicator Oregon Green Bapta-1 (OGB-1, 200 μM) and the morphological dye Alexa-594 (50 μM). APs were evoked by suprathreshold somatic current injections (5 ms) at varying frequencies.Ionotophoresis of glutamate (100μM) through a high resistance (>100 MΩ) application glass pipette was performed with an AxoClamp 2B amplifier in current clamp mode. A small retain current was applied to prevent leakage of glutamate. Brief (1 ms) current pulses were used to iontophorese the glutamate in close proximity to dendrites or axons of L4 spiny stellate neurons.
### 2.3. Ca2+ Imaging
For two-photon excitation fluorescence microscopy, an infrared femtosecond-pulsed titanium sapphire laser (MaiTai, Spectraphysics) was coupled to a home-built laser scanning microscope equipped with a water-immersion objective (W63x HCX APO UVI, 0.9 NA, Leica). Excitation infrared laser light and fluorescence emission light were separated at 670 nm (excitation filter 670DCXXR, AHF Analysentechnik). The emission spectra were separated by a dichroic mirror at 560 nm (beam splitter 560DCXR, AHF) and corresponding bandpass (HQ525/50, HQ610/75, AHF) and infrared-block filters (700SP-2P, AHF) and were detected using nondescanned detection behind the objective. Dyes were excited atλ=920nm. Data was acquired using custom-written laser-scanning software in LabView (National Instruments) [23]. Axonal Ca2+ imaging was performed in frame scan mode (30×30μm2) at 3 Hz for 1 min duration and repeated every 5 min. Astrocytic Ca2+ signals were acquired from astrocytes loaded with Rhod2-AM by pressure ejection of the dye-containing solution into the brain slice under visual control with a 10× objective. For dye preparation, 50 μg Rhod2-AM was dissolved in 5 μl of 80% DMSO and 20% pluronic acid F127 (w/v; Sigma) and diluted 1 : 19 in a HEPES-buffered solution containing 125 mM NaCl, 2.5 mM KCl, and 10 mM HEPES. This procedure resulted in specific uptake of the Rhod2 in astrocytes in the injected area. Frame scans (35×35μm2) at 3 Hz for 2 min duration, repeated every 5 min containing one astrocyte, were performed before, during, and after bath application of 2-AG.
### 2.4. Data Analysis
Electrophysiological data were analyzed using custom-written procedures in Igor Pro (Wavemetrics). EPSP slope was measured as a linear fit between time points on the rising phase of the EPSP corresponding to 20 and 60% of the EPSP peak amplitude. The change in EPSP slope was evaluated 20–40 min after the end of the pairing period and normalized to the baseline EPSP slope. Axonal and astrocyte imaging data were analyzed using custom-written procedures in Matlab. Regions of interest containing the axon segment were automatically detected and fluorescence traces extracted. Relative fluorescence changes were calculated asΔF/F=Ft−F0/F0, where Ft denotes fluorescence over time and F0 baseline fluorescence. AP-evoked Ca2+ transients were normalized and averaged. Single exponential fits to the decay of the Ca2+ transients yielded the decay time constants for the different conditions.
### 2.5. Statistical Analysis
Statistical analysis was done using paired or unpaired Student’st-test (for single comparisons) or ANOVA with post hoc Bonferroni correction (for multiple comparisons to the same control). Statistical significance was asserted for p<0.05. Data are presented as mean±s.e.m.
### 2.6. Histology
During experiments, cells were filled with biocytin and fixed in 4% paraformaldehyde. Slices were developed with the avidin-biotin-peroxidase method and mounted on cover slides for reconstruction with Neurolucida [24, 25].
### 2.7. Chemicals
Chemicals were obtained from the following sources: 2-AG and cyclosporin-A from Sigma-Aldrich, 1-(2,4-dichlorophenyl)-5-(4-iodophenyl)-4-methyl-N-(piperidin-1-yl)-1H-pyrazole-3-carboxamide (AM251), d-AP5 from Ascent Scientific, (+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine maleate (MK-801), and L-glutamic acid from Tocris, FK506 from Abmole Bioscience.
## 2.1. Slice Preparation
Experiments were approved by the Veterinary Office of the Canton of Bern, Switzerland. Thalamocortical brain slices containing the barrel subfield of somatosensory cortex were prepared from 12–21 d old Wistar rats of either sex [21]. Rats were decapitated, and their brains were quickly removed into cold (0–4°C) oxygenated physiological solution containing 125 mM NaCl, 2.5 mM KCl, 1.25 mM NaH2PO4, 25 mM NaHCO3, 1 mM MgCl2, 2 mM CaCl2, and 25 mM glucose. Slices, 300 μm thick, were cut from the tissue block with a vibratome (Microm) and kept at 37°C for 30 min and then at room temperature until use.
## 2.2. Electrophysiology
All experiments were performed at 30–34°C. For recording, slices were transferred to a recording chamber perfused with oxygenated physiological solution (same as above). The barrel subfield of somatosensory cortex was identified by the presence of barrels in L4, visible under trans-illumination. A monopolar glass stimulation electrode was placed in a L4 barrel, and whole-cell recordings for plasticity experiments were performed from L2/3 pyramidal neurons right above the corresponding barrel. Cells were identified using infrared gradient contrast video microscopy. Recording electrodes with a resistance of 4–7 MΩ were made using borosilicate glass capillaries. Recordings were performed using Dagan BVC-700A amplifiers (Dagan). Data were acquired with an ITC-16 AD-DA board (Instrutech) and using Igor software (Wavemetrics). The intracellular solution for recording neurons contained 130 mM potassium gluconate, 10 mM potassium HEPES, 10 mM sodium phosphocreatine, 4 mM Mg-ATP, 0.3 mM Na-GTP, 4 mM NaCl, 10 mM sodium gluconate (pH 7.3 with KOH), and biocytin (0.2% w/v).Single component EPSPs in the pyramidal neuron with amplitudes between 1 and 5 mV were evoked by stimulation in L4. After obtaining a stable baseline for 10 min at 0.1 Hz stimulation, the endocannabinoid 2-AG (10-20μM) was bath applied for 20 min, while continuing the extracellular stimulation. During wash-out, EPSPs were recorded for an additional 40 min. Experiments were discarded if the baseline EPSP slope was unstable (>10% change between first 15 and last 15 EPSP slopes of the baseline period), or if the pyramidal neuron input resistance or membrane potential changed by >15% during the course of the experiment.To investigate the influence of astrocytes on synaptic depression, whole-cell patch clamp recordings were performed from astrocytes adjacent to the recorded pyramidal neuron in L2/3. The intracellular solution for recording astrocytes contained 135 mM KCH3O3S, 10 mM HEPES, 10 mM sodium phosphocreatine, 4 mM MgCl2, 4 mM Na2-ATP, and 0.4 mM Na-GTP (pH 7.2 with KOH). Astrocytes were characterized by a low resting membrane potential, passive responses to both negative and positive current injections, and a low membrane resistance [8]. For astrocyte Ca2+ clamp experiments, 200 μM OGB-1, 0.45 mM EGTA, and 0.14 mM CaCl2 were added to the astrocyte intracellular solution to clamp intracellular free Ca2+ at a steady-state concentration of 50–80 nM [22].For axonal Ca2+ imaging experiments, recordings from spiny stellate neurons in L4 of the barrel cortex were performed in the whole-cell current clamp configuration. The intracellular solution was supplemented with the Ca2+ indicator Oregon Green Bapta-1 (OGB-1, 200 μM) and the morphological dye Alexa-594 (50 μM). APs were evoked by suprathreshold somatic current injections (5 ms) at varying frequencies.Ionotophoresis of glutamate (100μM) through a high resistance (>100 MΩ) application glass pipette was performed with an AxoClamp 2B amplifier in current clamp mode. A small retain current was applied to prevent leakage of glutamate. Brief (1 ms) current pulses were used to iontophorese the glutamate in close proximity to dendrites or axons of L4 spiny stellate neurons.
## 2.3. Ca2+ Imaging
For two-photon excitation fluorescence microscopy, an infrared femtosecond-pulsed titanium sapphire laser (MaiTai, Spectraphysics) was coupled to a home-built laser scanning microscope equipped with a water-immersion objective (W63x HCX APO UVI, 0.9 NA, Leica). Excitation infrared laser light and fluorescence emission light were separated at 670 nm (excitation filter 670DCXXR, AHF Analysentechnik). The emission spectra were separated by a dichroic mirror at 560 nm (beam splitter 560DCXR, AHF) and corresponding bandpass (HQ525/50, HQ610/75, AHF) and infrared-block filters (700SP-2P, AHF) and were detected using nondescanned detection behind the objective. Dyes were excited atλ=920nm. Data was acquired using custom-written laser-scanning software in LabView (National Instruments) [23]. Axonal Ca2+ imaging was performed in frame scan mode (30×30μm2) at 3 Hz for 1 min duration and repeated every 5 min. Astrocytic Ca2+ signals were acquired from astrocytes loaded with Rhod2-AM by pressure ejection of the dye-containing solution into the brain slice under visual control with a 10× objective. For dye preparation, 50 μg Rhod2-AM was dissolved in 5 μl of 80% DMSO and 20% pluronic acid F127 (w/v; Sigma) and diluted 1 : 19 in a HEPES-buffered solution containing 125 mM NaCl, 2.5 mM KCl, and 10 mM HEPES. This procedure resulted in specific uptake of the Rhod2 in astrocytes in the injected area. Frame scans (35×35μm2) at 3 Hz for 2 min duration, repeated every 5 min containing one astrocyte, were performed before, during, and after bath application of 2-AG.
## 2.4. Data Analysis
Electrophysiological data were analyzed using custom-written procedures in Igor Pro (Wavemetrics). EPSP slope was measured as a linear fit between time points on the rising phase of the EPSP corresponding to 20 and 60% of the EPSP peak amplitude. The change in EPSP slope was evaluated 20–40 min after the end of the pairing period and normalized to the baseline EPSP slope. Axonal and astrocyte imaging data were analyzed using custom-written procedures in Matlab. Regions of interest containing the axon segment were automatically detected and fluorescence traces extracted. Relative fluorescence changes were calculated asΔF/F=Ft−F0/F0, where Ft denotes fluorescence over time and F0 baseline fluorescence. AP-evoked Ca2+ transients were normalized and averaged. Single exponential fits to the decay of the Ca2+ transients yielded the decay time constants for the different conditions.
## 2.5. Statistical Analysis
Statistical analysis was done using paired or unpaired Student’st-test (for single comparisons) or ANOVA with post hoc Bonferroni correction (for multiple comparisons to the same control). Statistical significance was asserted for p<0.05. Data are presented as mean±s.e.m.
## 2.6. Histology
During experiments, cells were filled with biocytin and fixed in 4% paraformaldehyde. Slices were developed with the avidin-biotin-peroxidase method and mounted on cover slides for reconstruction with Neurolucida [24, 25].
## 2.7. Chemicals
Chemicals were obtained from the following sources: 2-AG and cyclosporin-A from Sigma-Aldrich, 1-(2,4-dichlorophenyl)-5-(4-iodophenyl)-4-methyl-N-(piperidin-1-yl)-1H-pyrazole-3-carboxamide (AM251), d-AP5 from Ascent Scientific, (+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine maleate (MK-801), and L-glutamic acid from Tocris, FK506 from Abmole Bioscience.
## 3. Results
### 3.1. Endocannabinoid-Dependent LTD Requires Activation of Astrocytes and preNMDARs
t-LTD at L4-L2/3 excitatory synapses in rat barrel cortex depends on the activation of astrocytes by 2-AG that is synthetized postsynaptically. This synthesis occurs at synapses which are activated within a time window of about 50 ms after the generation of a postsynaptic AP. Astrocyte activation results in the release of glutamate onto preNMDARs which interact with presynaptic APs to trigger a reduction in release probability [8]. To further understand the presynaptic signaling cascade leading to t-LTD, Ca2+ imaging from presynaptic boutons during t-LTD induction would be the best approach. However, this is technically challenging, since it requires imaging from the presynaptic bouton of an identified synaptic connection while at the same time controlling AP firing in the pre- and postsynaptic neuron. As an alternative approach, we tested if direct bath-application of 2-AG resulted in synaptic depression without postsynaptic activity at L4-L2/3 synapses, similar to what was previously described for L5-L5 synapses [4]. We performed whole-cell patch-clamp recordings from L2/3 pyramidal neurons in the somatosensory cortex of juvenile rats and activated L4 spiny stellate neuron axons by extracellular stimulation in L4. After recording a baseline of EPSPs for 10 min, we bath-applied 2-AG (10 μM) for 20 min while continuing presynaptic stimulation at 0.1 Hz. We observed a long-lasting depression of the EPSPs 10–30 min after the washout of 2-AG (0.58±0.09, n=13, p<0.01 for the effect of time on EPSP slope by Student’s paired t-test; Figure 1(a)). This form of LTD was presynaptic as the reduction in normalized EPSP amplitude correlated with a reduction in the normalized coefficient of variation (Figure 1(b)).Figure 1
2-AG mediated LTD requires astrocyte Ca2+ signaling and preNMDARs. (a) Time course of normalized and averaged EPSP slope measured in L2/3 pyramidal neurons before, during (0–20 min, shaded area) and after bath application of 2-AG (n=13). Inset, representative average EPSP during baseline (black) and after 2-AG (grey). (b) Relative change of coefficient of variation of EPSP slope after bath application of 2-AG as a function of corresponding changes in EPSP slope. The relation is almost linear, indicating a presynaptic locus of eCB-LTD expression. Open circles represent individual experiments, and filled circle represents the average (n=13). (c) Two-photon fluorescence image of an astrocyte in L2/3 of the somatosensory cortex loaded with the Ca2+ indicator Rhod-2. Traces to the right show Ca2+ fluctuations in the astrocyte before, during, and after bath application of 2-AG (shaded area). (d) Summary of the average number of Ca2+ transients during the time course of the experiment (n=12). ∗p<0.05 for the effect of time on Ca2+ transient number by Student’s paired t-test. (e) Normalized and averaged EPSP slope over time in L2/3 pyramidal neurons, while an adjacent astrocyte was infused in the whole-cell recording configuration with either a control (Ctrl, n=8) and or Ca2+ clamp solution (n=9). Inset, representative average EPSP during baseline (black) and after 2-AG in control (light green) or Ca2+ clamp (dark green) conditions. (f) Normalized and averaged EPSP slope over time during bath application of APV (n=13) or intracellular infusion of MK801 (n=24) into the pyramidal neuron (iMK801). Inset, representative average EPSP during baseline (black) and after 2-AG in the presence of APV (purple) or iMK801 (blue). (g) Normalized and averaged EPSP slope in the presence of the calcineurin inhibitors FK506 and cyclosporin-A (n=2). Inset, representative average EPSP during baseline (black) and after 2-AG (orange). (h) Bar graph summary of experiments shown in (e) and (f). In the astrocyte Ca2+ clamp condition, eCB-LTD was abolished. APV blocked eCB-LTD, while intracellular block of postsynaptic NMDARs with MK801 had no effect. #p<0.05 by one-way ANOVA. All data are represented as mean±SEM. All scale bars for average EPSPs represent 40 ms and 2 mV, respectively.
(a)(b)(c)(d)(e)(f)(g)(h)Next, we confirmed that 2-AG activated cortical astrocytes in L2/3. Bulk-loading of astrocytes with Rhod2-AM, which is preferentially taken up by astrocytes, allowed to measure the intracellular Ca2+ dynamics during bath-application of 2-AG (Figure 1(c)). We observed a significant increase in the number of Ca2+ transients by 2-AG (from 0.75±0.26min−1 to 1.08±0.20min−1, n=12, p<0.05 for the effect of time on Ca2+ transient number by Student’s paired t-test) that decayed back to baseline levels after wash-out (Figure 1(d)). This experiment confirmed previous results showing that eCBs modulate astrocytic Ca2+ dynamics [8, 26]. Infusing an astrocyte with a solution that clamped the intracellular Ca2+ concentration to a constant level abolished eCB-LTD in adjacent pyramidal neurons (1.00±0.10, n=9, p=0.87 for the effect of time on EPSP slope by Student’s paired t-test), while infusing a control intracellular solution into the astrocytes resulted in eCB-LTD (0.74±0.06, n=8, p<0.05 for the effect of time on EPSP slope by Student’s paired t-test; comparison control vs. Ca2+ clamp, p<0.05 by one-way ANOVA; Figures 1(e) and 1(h)). Thus, similar to t-LTD, the increase in Ca2+ signaling in the astrocytes was required for the induction of eCB-LTD.Then, we tested the involvement of NMDARs in eCB-LTD. Bath-application of APV blocked the 2-AG mediated LTD (0.90±0.05, n=13, p=0.06 for the effect of time on EPSP slope by Student’s paired t-test), while infusion of MK801 into the postsynaptic cell had no effect on eCB-LTD (0.70±0.05, n=24, p<0.001 for the effect of time on EPSP slope by Student’s paired t-test; comparison APV vs. MK801, p<0.05 by one-way ANOVA; Figures 1(f) and 1(h)). These results suggested that downstream of astrocyte signaling, eCB-LTD required the activation of presynaptic NMDARs.PreNMDAR-dependent LTD at cortical synapses [10] and eCB-mediated LTD at both excitatory and inhibitory synapses in the hippocampus [27, 28] require the activation of the Ca2+ dependent protein phosphatase calcineurin [29]. In order to test a similar involvement in our case, we blocked calcineurin activity by incubating the brain slices in FK506 (50 μM) and cyclosporin-A (25 μM) at least for 1 h before the start of the experiment and with 20 μM and 10 μM, respectively, during the experiment. EPSPs were evoked by extracellular stimulation in L4, and 2-AG was washed-in for 20 min as described above. In the condition of blocked calcineurin activity, no eCB-LTD was induced (0.95±0.01, n=2, Figure 1(g)). These results indicate that calcineurin is involved in the induction of eCB-LTD.In summary, our experiments show that eCB-LTD and t-LTD share a similar induction mechanism, since both are dependent on astrocyte activation by eCBs and on activation of preNMDARs. The involvement of calcineurin suggests that an elevation in presynaptic Ca2+ is essential for these forms of LTD.
### 3.2. Presynaptic NMDARs Broaden AP-Evoked Ca2+ Transients in L4 Spiny Stellate Axons
We sought to investigate the functional consequence of preNMDAR activation and thus the potential source of Ca2+ required for LTD in L4 spiny stellate axons while they were activated by glutamate release from 2-AG activated astrocytes. We loaded L4 spiny stellate neurons with the Ca2+ indicator Oregon Green Bapta-1 (OGB-1, 200 μM) and the morphological dye Alexa-594 (50 μM) to trace the axon to L2/3 (Figures 2(a) and 2(b)). Frame scans of 1 min duration (3 Hz) from a stretch of axon were performed to measure the local Ca2+ signals before and during bath application of 2-AG. A single somatically evoked AP resulted in a stereotyped Ca2+ transient in the axonal compartment. Bath application of 2-AG did not cause a significant number of spontaneous, local Ca2+ transients in the axon as might have been hypothesized from an activation of preNMDARs (Figures 2(c) and 2(d)). We found a total of 12 spontaneous Ca2+ transients in 60 min of observation time (n=9 cells) in the presence of 2-AG. This number was not different from spontaneous events before 2-AG application (8 events in 40 min). However, comparing the time course of the presynaptic AP-evoked Ca2+ transients before and after 2-AG application revealed a prolongation of the AP-evoked Ca2+ signal in the presence of 2-AG (Figure 2(e)). We concluded from this experiment that glutamate release from astrocytes does not activate preNMDARs in a similar manner as axonal glutamate release activates postsynaptic NMDARs, which results in clear and distinct Ca2+ transients in postsynaptic spines [30]. This result is consistent with observations that glutamate iontophoresis or uncaging onto presynaptic boutons does not cause a Ca2+ influx [13, 14]. We reconfirmed these findings by iontophoresis of glutamate (100 mM) onto dendrites and boutons of L4 spiny stellate neurons (Figure 3). We observed clear increases in Ca2+ in dendritic spines, but in contrast, we could not detect any Ca2+ elevations in the axonal compartment (n=5 cells). Furthermore, single AP-evoked presynaptic Ca2+ signals alone were not influenced by blocking NMDA receptors. Bath-application of APV did not change the peak amplitude of the Ca2+ transients (ΔF/FBaseline=0.013±0.003, ΔF/FAPV=0.015±0.003, n=6, p=0.22 by Student’s paired t-test), nor its decay (τBaseline=0.68±0.12s, τAPV=0.77±0.08s, n=6, p=0.55 by Student’s paired t-test; Figure 4). Thus, preNMDARs caused no direct Ca2+ influx into boutons, and they also did not contribute to the normal AP-evoked presynaptic Ca2+ dynamics in the absence of 2-AG.Figure 2
Presynaptic Ca2+ imaging in L4 spiny stellate axons. (a) Two-photon fluorescence image of a spiny stellate neuron in L4 of the somatosensory cortex loaded with OGB-1 and Alexa-594. (b) Imaged axon segment in L2/3 indicated in (a) by the dashed box. (c) Consecutive fluorescence traces of 1 min duration repeated every 5 min before, during (shaded area) and after bath application of 2-AG. An arrowhead indicates the time point of a somatically evoked AP. (d) Spontaneous axonal Ca2+ transient marked by a cross in (c) on an expanded scale. The Ca2+ transient was unrelated to somatic activity. (e) AP-evoked Ca2+ transient in the presence of 2-AG marked by an asterisk in (c) on an expanded scale (black) compared to an AP-evoked Ca2+ transient during baseline (grey). Dashed lines present single exponential fits to the decay of the Ca2+ transients.
(a)(b)(c)(d)(e)Figure 3
Iontophoresis of glutamate does not evoke Ca2+ signals in boutons. (a) Two-photon fluorescence image of a dendrite of a spiny stellate neuron loaded with the Ca2+ indicator OGB-1 (200 μM) and the morphological dye Alexa 594 (50 μM). The position of the iontophoresis pipette for glutamate application is indicated. To the right, three fluorescence images taken before, 1 s after and 5 s after glutamate application, are shown. Below, the time-course of the fluorescence change in the region of interest indicated by the red, dashed circle (upper trace) and the somatic membrane potential (lower trace) are presented. Grey bar represents time of glutamate application. (b) Left, line-scan through a spine of another cell and the corresponding Ca2+ transient evoked by a burst of 5 APs at 50 Hz. Right, line-scan through the same spine during iontophoresis of glutamate. A clear increase in Ca2+ can be seen upon iontophoresis. (c) Two-photon fluorescence image of an axon of a spiny stellate neuron located in L2/3 loaded with the Ca2+ indicator OGB-1 (200 μM) and the morphological dye Alexa 594 (50 μM). The position of the iontophoresis pipette for glutamate application is indicated. To the right, three fluorescence images taken before, 1 s after and 3 s after glutamate application, are shown. Below, the time-course of the fluorescence change in the region of interest indicated by the red, dashed circle (upper trace) and the somatic membrane potential (lower trace) is presented. Grey bar represents time of glutamate application. No increase in Ca2+ is apparent upon iontophoresis of glutamate onto the axon. (d) Left, line-scan through a bouton of another cell and the corresponding Ca2+ transient evoked by a burst of 5 APs at 50 Hz. Right, line-scan through the same bouton during iontophoresis of glutamate. An increase in Ca2+ is evoked by the APs, but not by iontophoresis of glutamate.
(a)(b)(c)(d)Figure 4
APV has no influence on presynaptic AP-evoked Ca2+ transients. (a) Axonal Ca2+ transients evoked by a single AP in a spiny stellate axon recorded in L2/3 during baseline (black) and in the presence of the NMDAR blocker APV (purple). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. Lower trace represents the difference between the baseline and APV Ca2+ transients. Dashed line indicates zero and light shaded area indicates the baseline noise level (±SD). (b) Bar graph summary of the peak Ca2+ transient amplitudes (left) and decay time constants (right) for baseline and in the presence of APV. All data are represented as mean±SEM.
(a)(b)Therefore, in order to investigate the phenomenon of the specific 2-AG induced broadening of the AP-evoked Ca2+ signals in more detail, we measured single AP-evoked Ca2+ transients elicited at 0.1 Hz, corresponding to the stimulation frequency used for the LTD experiments (instead of stimulating at 0.003 Hz as in the previous imaging experiments) in spiny stellate axons before and during bath application of 2-AG (Figures 5(a) and 5(b)). We normalized and averaged the corresponding Ca2+ transients for comparison. We confirmed that 2-AG broadened the AP-evoked Ca2+ transients (Figure 5(b)). In contrast, in the presence of APV, 2-AG had no effect on the presynaptic Ca2+ signal (Figure 5(b)). Fitting a single exponential to the decay of the AP-evoked Ca2+ transients revealed a significantly slower decay in the presence of 2-AG as compared to the effect of 2-AG in the presence of APV (2-AG: normalized τ2−AG=1.23±0.07, n=15, p<0.01 for the effect of time on τ by paired Student’s t-test; 2-AG + APV: normalized τ2−AG=1.02±0.02, n=11, p=0.26 for the effect of time on τ by paired Student’s t-test; 2-AG control vs. 2-AG + APV, p<0.05 by one-way ANOVA; Figure 5(c)). The distribution of the normalized decay time constants revealed that 2-AG broadened the AP-evoked Ca2+ transients in 53% of the axons investigated (8 out of 15 axons; average change 1.40±0.08), while having no effect on the rest (7 out of 15; average change 1.03±0.01; Figure 5(d)). This observation suggests that not all axons and boutons were influenced by astrocyte activation, arguing for a compartmentalized astrocytic innervation and/or for synapse-specific expression of preNMDARs. The CB1 receptor antagonist AM251 (5 μM) abolished the effect of bath-application of 2-AG on the AP-evoked Ca2+ transients (AM251: normalized τ2−AG=0.97±0.04, n=5, p=0.40 for the effect of time on τ by paired Student’s t-test), excluding a nonspecific effect of 2-AG. Furthermore, repeating the experiment without any drug application had no effect on the AP-evoked Ca2+ transients (no drugs: normalized τ=1.02±0.06, n=4, p=0.51 for the effect of time on τ by paired Student’s t-test) demonstrating long-term stability of the experimental design and ruling out any time-dependent changes in axonal Ca2+ buffering due to the Ca2+ indicator.Figure 5
2-AG broadens AP-evoked Ca2+ transients in L4 axons. (a) Neurolucida reconstruction of a spiny stellate neuron. Dendrites are represented in blue and the axonal arborization in black. Inset, two-photon fluorescence image of the axon segment imaged in L2/3 indicated by the dashed box. (b) Left, averaged and normalized AP-evoked Ca2+ transients during baseline (grey) and after bath application of 2-AG (black). Upper trace represents the difference between the baseline and 2-AG Ca2+ transients. Dashed line indicates zero, and light-shaded area indicates the baseline noise level (±SD). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. There is an apparent difference between the two transients. Inset shows somatic APs before and after bath application of 2-AG. Right, experiment in which the NMDAR-blocker APV was present in the bath. No difference between the two transients was observed in this condition. (c) Normalized decay time constant in the presence of 2-AG for different conditions. 2-AG significantly broadened the Ca2+ transients (n=15). ##p<0.01 for the effect of time on τ by paired Student’s t-test. In contrast, no broadening was observed in the presence of APV (n=11), AM251 (n=5), or in control conditions without application of any drug (Ctrl, n=4). APV had a significant effect on τ in the presence of 2-AG. ∗p<0.05 by one-way ANOVA. All data are represented as mean±SEM. (d) Distribution of normalized decay time constants in the presence of 2-AG. Solid black lines represent Gaussian fits to the subsets that showed either no (light grey) or significant (dark grey) broadening of the Ca2+ transients.
(a)(b)(c)(d)2-AG evoked release of glutamate might activate dendritic NMDARs on the recorded neuron, which could potentially influence somatic membrane potential, AP generation, and somatic AP properties. Previously, such somato-dendritic NMDAR activation was shown to influence presynaptic Ca2+ signaling in cerebellar stellate cells [12]. However, when we analyzed the somatic resting membrane potential, AP amplitude, and AP width at the soma of the imaged spiny stellate neurons, we found no influence of 2-AG on either somatic parameter (Figure 6). Therefore, we can rule out an effect of somato-dendritic NMDARs on the presynaptic Ca2+ dynamics. Thus, our experiments revealed an APV-sensitive presynaptic Ca2+ component that manifested itself in a broadening of AP-evoked Ca2+ transients.Figure 6
AP properties are unaffected by 2-AG. (a) Neurolucida reconstruction of a spiny stellate neuron. Dendrites are represented in blue and the axonal arborization in black. (b) Upper traces, averaged and normalized AP-evoked Ca2+ transients during baseline (grey) and after bath application of 2-AG (black). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. Lower traces, corresponding somatic APs before (grey) and after (black) bath application of 2-AG. (c) Average bar graphs of resting membrane potential, AP amplitude, and AP width before and after bath application of 2-AG (n=12). None of the parameters changed significantly (p>0.1 by paired Student’s t-test). All data are represented as mean±SEM.
(a)(b)(c)Recently, it was shown that specific patterns of presynaptic activity alone, consisting of a burst of APs at 100 Hz or above, followed by a single AP between 50 and 200 ms later, can induce LTD. This form of LTD requires the activation of preNMDARs, but does not depend on astrocyte activation [10]. We tested whether this activity pattern also resulted in an APV-sensitive broadening of the presynaptic Ca2+ signal. A burst of APs at 100 Hz followed by a single AP 50 ms later evoked an axonal Ca2+ transient that was more rapidly decaying after wash-in of APV (Figure 7(a)). The difference between the Ca2+ transients under baseline conditions and in the presence of APV revealed an APV-sensitive Ca2+ component for this presynaptic stimulation pattern (peak difference baseline to APV: 0.04±0.02, n=6, p<0.05 by paired Student’s t-test; Figures 7(b) and 7(c)). Ca2+ transients evoked by 3 APs at 100 Hz alone showed no APV-sensitive Ca2+ component (−0.01±0.02, n=6, p=0.56 by paired Student’s t-test). Thus, the additional AP that followed 50 ms after the burst of 3 APs leads to a significant (p<0.05 by one-way ANOVA) additional presynaptic Ca2+ influx that was abolished by APV. The requirement of the presence of this delayed 4th AP suggests an interaction of the preNMDARs with a voltage-dependent mechanism initiated by the additional AP.Figure 7
Presynaptic burst patterns evoke an APV-sensitive Ca2+ transient component. (a) Example of the AP burst patterns that were used to evoke presynaptic Ca2+ transients in L4 spiny stellate axons. Left, 3 APs at 100 Hz. Right, 3 APs at 100 Hz followed 50 ms later by a single AP. (b) Axonal Ca2+ transients evoked by the activity patterns shown in (a) during baseline (black) and after bath application of APV (purple). Lower traces show the difference between the corresponding transients. (c) Comparison of the peak difference between the Ca2+ transients before and after bath application of APV (n=6). The 3AP+1AP activity pattern showed a significant effect of APV on the evoked Ca2+ transients, while the Ca2+ transients evoked by a burst of 3 APs alone were unaffected by APV. #p<0.05 by paired Student’s t-test. ∗p<0.05 by one-way ANOVA. All data are represented as mean±SEM.
(a)(b)(c)In summary, our experiments suggest that the activation of preNMDARs causes a slowing of the decay of AP-evoked Ca2+ transients, which results in an additional axonal Ca2+ influx that is intrinsically linked to the presence of the presynaptic AP. The source of the glutamate that activates the preNMDARs can either originate from 2-AG activated astrocytes or from glutamate spillover by a specifically timed presynaptic burst of APs.
### 3.3. preNMDARs Interact with Voltage-Dependent Ca2+ Channels
The broadening of the AP-evoked presynaptic Ca2+ transient could directly be due to the preNMDARs, which could contribute to Ca2+ influx during the AP-evoked axonal membrane depolarization and the subsequent relief of the Mg2+ block. In this scenario, preNMDARs would function as classical coincidence detectors, similar to what has been suggested for postsynaptic NMDARs. However, it has been shown that preNMDARs during early development might contain the GluN3A subunit, which renders them largely insensitive to Mg2+ block and with low permeability for Ca2+ [18]. An alternative function of the preNMDARs might be to contribute to the axonal membrane depolarization by Na+ influx or to exert a metabotropic effect during their activation. Both mechanisms could activate voltage-dependent Ca2+ channels (VDCCs) beyond the membrane depolarization caused by the axonal AP and contribute to an additional Ca2+ influx. To distinguish between a direct Ca2+ influx through preNMDARs and an interaction with VDCCs, we performed axonal Ca2+ imaging as described above and blocked VDCCs (Figure 8). Somatic APs evoked a consistent axonal Ca2+ transient which was abolished in the presence of the VDCC-blockers Cd2+ (100 μM) and Ni+ (50 μM) even though the somatic AP waveform was unchanged (ΔF/FBaseline=0.047±0.004, ΔF/FCd,Ni=0.008±0.001, n=4, p<0.01 by Student’s paired t-test with Bonferroni correction for multiple comparisons). Subsequent continuation of somatic AP stimulation during bath application of 2-AG, but still in the presence of Cd2+/Ni+ did not uncover an AP-evoked Ca2+ transient through preNMDARs (ΔF/F2−AG=0.002±0.001, p=0.32 by Student’s paired t-test with Bonferroni correction for multiple comparisons). This observation suggests that axonal membrane depolarization is not required for unblocking preNMDARs from a putative Mg2+ block to render them permeable for Ca2+. Contrary, we conclude that functional VDCCs are required so that preNMDARs can interact with them to prolong the axonal Ca2+ influx.Figure 8
Block of VDCCs does not uncover preNMDAR-dependent Ca2+ transients. (a) Axonal Ca2+ transients evoked by a single AP in a spiny stellate axon recorded in L2/3 during baseline (black) and in the presence of the VDCC blockers Cd2+ and Ni+ (blue). Subsequent bath application of 2-AG did not result in an AP-evoked Ca2+ transient (green). Shaded areas represent ±SEM and dashed lines ±SD of the basal fluorescence before stimulation. (b) Bar graph summary of the peak Ca2+ transient amplitudes in the different conditions (n=4). ∗∗p<0.01 by Student’s paired t-test with Bonferroni correction for multiple comparisons. All data are represented as mean±SEM.
(a)(b)
## 3.1. Endocannabinoid-Dependent LTD Requires Activation of Astrocytes and preNMDARs
t-LTD at L4-L2/3 excitatory synapses in rat barrel cortex depends on the activation of astrocytes by 2-AG that is synthetized postsynaptically. This synthesis occurs at synapses which are activated within a time window of about 50 ms after the generation of a postsynaptic AP. Astrocyte activation results in the release of glutamate onto preNMDARs which interact with presynaptic APs to trigger a reduction in release probability [8]. To further understand the presynaptic signaling cascade leading to t-LTD, Ca2+ imaging from presynaptic boutons during t-LTD induction would be the best approach. However, this is technically challenging, since it requires imaging from the presynaptic bouton of an identified synaptic connection while at the same time controlling AP firing in the pre- and postsynaptic neuron. As an alternative approach, we tested if direct bath-application of 2-AG resulted in synaptic depression without postsynaptic activity at L4-L2/3 synapses, similar to what was previously described for L5-L5 synapses [4]. We performed whole-cell patch-clamp recordings from L2/3 pyramidal neurons in the somatosensory cortex of juvenile rats and activated L4 spiny stellate neuron axons by extracellular stimulation in L4. After recording a baseline of EPSPs for 10 min, we bath-applied 2-AG (10 μM) for 20 min while continuing presynaptic stimulation at 0.1 Hz. We observed a long-lasting depression of the EPSPs 10–30 min after the washout of 2-AG (0.58±0.09, n=13, p<0.01 for the effect of time on EPSP slope by Student’s paired t-test; Figure 1(a)). This form of LTD was presynaptic as the reduction in normalized EPSP amplitude correlated with a reduction in the normalized coefficient of variation (Figure 1(b)).Figure 1
2-AG mediated LTD requires astrocyte Ca2+ signaling and preNMDARs. (a) Time course of normalized and averaged EPSP slope measured in L2/3 pyramidal neurons before, during (0–20 min, shaded area) and after bath application of 2-AG (n=13). Inset, representative average EPSP during baseline (black) and after 2-AG (grey). (b) Relative change of coefficient of variation of EPSP slope after bath application of 2-AG as a function of corresponding changes in EPSP slope. The relation is almost linear, indicating a presynaptic locus of eCB-LTD expression. Open circles represent individual experiments, and filled circle represents the average (n=13). (c) Two-photon fluorescence image of an astrocyte in L2/3 of the somatosensory cortex loaded with the Ca2+ indicator Rhod-2. Traces to the right show Ca2+ fluctuations in the astrocyte before, during, and after bath application of 2-AG (shaded area). (d) Summary of the average number of Ca2+ transients during the time course of the experiment (n=12). ∗p<0.05 for the effect of time on Ca2+ transient number by Student’s paired t-test. (e) Normalized and averaged EPSP slope over time in L2/3 pyramidal neurons, while an adjacent astrocyte was infused in the whole-cell recording configuration with either a control (Ctrl, n=8) and or Ca2+ clamp solution (n=9). Inset, representative average EPSP during baseline (black) and after 2-AG in control (light green) or Ca2+ clamp (dark green) conditions. (f) Normalized and averaged EPSP slope over time during bath application of APV (n=13) or intracellular infusion of MK801 (n=24) into the pyramidal neuron (iMK801). Inset, representative average EPSP during baseline (black) and after 2-AG in the presence of APV (purple) or iMK801 (blue). (g) Normalized and averaged EPSP slope in the presence of the calcineurin inhibitors FK506 and cyclosporin-A (n=2). Inset, representative average EPSP during baseline (black) and after 2-AG (orange). (h) Bar graph summary of experiments shown in (e) and (f). In the astrocyte Ca2+ clamp condition, eCB-LTD was abolished. APV blocked eCB-LTD, while intracellular block of postsynaptic NMDARs with MK801 had no effect. #p<0.05 by one-way ANOVA. All data are represented as mean±SEM. All scale bars for average EPSPs represent 40 ms and 2 mV, respectively.
(a)(b)(c)(d)(e)(f)(g)(h)Next, we confirmed that 2-AG activated cortical astrocytes in L2/3. Bulk-loading of astrocytes with Rhod2-AM, which is preferentially taken up by astrocytes, allowed to measure the intracellular Ca2+ dynamics during bath-application of 2-AG (Figure 1(c)). We observed a significant increase in the number of Ca2+ transients by 2-AG (from 0.75±0.26min−1 to 1.08±0.20min−1, n=12, p<0.05 for the effect of time on Ca2+ transient number by Student’s paired t-test) that decayed back to baseline levels after wash-out (Figure 1(d)). This experiment confirmed previous results showing that eCBs modulate astrocytic Ca2+ dynamics [8, 26]. Infusing an astrocyte with a solution that clamped the intracellular Ca2+ concentration to a constant level abolished eCB-LTD in adjacent pyramidal neurons (1.00±0.10, n=9, p=0.87 for the effect of time on EPSP slope by Student’s paired t-test), while infusing a control intracellular solution into the astrocytes resulted in eCB-LTD (0.74±0.06, n=8, p<0.05 for the effect of time on EPSP slope by Student’s paired t-test; comparison control vs. Ca2+ clamp, p<0.05 by one-way ANOVA; Figures 1(e) and 1(h)). Thus, similar to t-LTD, the increase in Ca2+ signaling in the astrocytes was required for the induction of eCB-LTD.Then, we tested the involvement of NMDARs in eCB-LTD. Bath-application of APV blocked the 2-AG mediated LTD (0.90±0.05, n=13, p=0.06 for the effect of time on EPSP slope by Student’s paired t-test), while infusion of MK801 into the postsynaptic cell had no effect on eCB-LTD (0.70±0.05, n=24, p<0.001 for the effect of time on EPSP slope by Student’s paired t-test; comparison APV vs. MK801, p<0.05 by one-way ANOVA; Figures 1(f) and 1(h)). These results suggested that downstream of astrocyte signaling, eCB-LTD required the activation of presynaptic NMDARs.PreNMDAR-dependent LTD at cortical synapses [10] and eCB-mediated LTD at both excitatory and inhibitory synapses in the hippocampus [27, 28] require the activation of the Ca2+ dependent protein phosphatase calcineurin [29]. In order to test a similar involvement in our case, we blocked calcineurin activity by incubating the brain slices in FK506 (50 μM) and cyclosporin-A (25 μM) at least for 1 h before the start of the experiment and with 20 μM and 10 μM, respectively, during the experiment. EPSPs were evoked by extracellular stimulation in L4, and 2-AG was washed-in for 20 min as described above. In the condition of blocked calcineurin activity, no eCB-LTD was induced (0.95±0.01, n=2, Figure 1(g)). These results indicate that calcineurin is involved in the induction of eCB-LTD.In summary, our experiments show that eCB-LTD and t-LTD share a similar induction mechanism, since both are dependent on astrocyte activation by eCBs and on activation of preNMDARs. The involvement of calcineurin suggests that an elevation in presynaptic Ca2+ is essential for these forms of LTD.
## 3.2. Presynaptic NMDARs Broaden AP-Evoked Ca2+ Transients in L4 Spiny Stellate Axons
We sought to investigate the functional consequence of preNMDAR activation and thus the potential source of Ca2+ required for LTD in L4 spiny stellate axons while they were activated by glutamate release from 2-AG activated astrocytes. We loaded L4 spiny stellate neurons with the Ca2+ indicator Oregon Green Bapta-1 (OGB-1, 200 μM) and the morphological dye Alexa-594 (50 μM) to trace the axon to L2/3 (Figures 2(a) and 2(b)). Frame scans of 1 min duration (3 Hz) from a stretch of axon were performed to measure the local Ca2+ signals before and during bath application of 2-AG. A single somatically evoked AP resulted in a stereotyped Ca2+ transient in the axonal compartment. Bath application of 2-AG did not cause a significant number of spontaneous, local Ca2+ transients in the axon as might have been hypothesized from an activation of preNMDARs (Figures 2(c) and 2(d)). We found a total of 12 spontaneous Ca2+ transients in 60 min of observation time (n=9 cells) in the presence of 2-AG. This number was not different from spontaneous events before 2-AG application (8 events in 40 min). However, comparing the time course of the presynaptic AP-evoked Ca2+ transients before and after 2-AG application revealed a prolongation of the AP-evoked Ca2+ signal in the presence of 2-AG (Figure 2(e)). We concluded from this experiment that glutamate release from astrocytes does not activate preNMDARs in a similar manner as axonal glutamate release activates postsynaptic NMDARs, which results in clear and distinct Ca2+ transients in postsynaptic spines [30]. This result is consistent with observations that glutamate iontophoresis or uncaging onto presynaptic boutons does not cause a Ca2+ influx [13, 14]. We reconfirmed these findings by iontophoresis of glutamate (100 mM) onto dendrites and boutons of L4 spiny stellate neurons (Figure 3). We observed clear increases in Ca2+ in dendritic spines, but in contrast, we could not detect any Ca2+ elevations in the axonal compartment (n=5 cells). Furthermore, single AP-evoked presynaptic Ca2+ signals alone were not influenced by blocking NMDA receptors. Bath-application of APV did not change the peak amplitude of the Ca2+ transients (ΔF/FBaseline=0.013±0.003, ΔF/FAPV=0.015±0.003, n=6, p=0.22 by Student’s paired t-test), nor its decay (τBaseline=0.68±0.12s, τAPV=0.77±0.08s, n=6, p=0.55 by Student’s paired t-test; Figure 4). Thus, preNMDARs caused no direct Ca2+ influx into boutons, and they also did not contribute to the normal AP-evoked presynaptic Ca2+ dynamics in the absence of 2-AG.Figure 2
Presynaptic Ca2+ imaging in L4 spiny stellate axons. (a) Two-photon fluorescence image of a spiny stellate neuron in L4 of the somatosensory cortex loaded with OGB-1 and Alexa-594. (b) Imaged axon segment in L2/3 indicated in (a) by the dashed box. (c) Consecutive fluorescence traces of 1 min duration repeated every 5 min before, during (shaded area) and after bath application of 2-AG. An arrowhead indicates the time point of a somatically evoked AP. (d) Spontaneous axonal Ca2+ transient marked by a cross in (c) on an expanded scale. The Ca2+ transient was unrelated to somatic activity. (e) AP-evoked Ca2+ transient in the presence of 2-AG marked by an asterisk in (c) on an expanded scale (black) compared to an AP-evoked Ca2+ transient during baseline (grey). Dashed lines present single exponential fits to the decay of the Ca2+ transients.
(a)(b)(c)(d)(e)Figure 3
Iontophoresis of glutamate does not evoke Ca2+ signals in boutons. (a) Two-photon fluorescence image of a dendrite of a spiny stellate neuron loaded with the Ca2+ indicator OGB-1 (200 μM) and the morphological dye Alexa 594 (50 μM). The position of the iontophoresis pipette for glutamate application is indicated. To the right, three fluorescence images taken before, 1 s after and 5 s after glutamate application, are shown. Below, the time-course of the fluorescence change in the region of interest indicated by the red, dashed circle (upper trace) and the somatic membrane potential (lower trace) are presented. Grey bar represents time of glutamate application. (b) Left, line-scan through a spine of another cell and the corresponding Ca2+ transient evoked by a burst of 5 APs at 50 Hz. Right, line-scan through the same spine during iontophoresis of glutamate. A clear increase in Ca2+ can be seen upon iontophoresis. (c) Two-photon fluorescence image of an axon of a spiny stellate neuron located in L2/3 loaded with the Ca2+ indicator OGB-1 (200 μM) and the morphological dye Alexa 594 (50 μM). The position of the iontophoresis pipette for glutamate application is indicated. To the right, three fluorescence images taken before, 1 s after and 3 s after glutamate application, are shown. Below, the time-course of the fluorescence change in the region of interest indicated by the red, dashed circle (upper trace) and the somatic membrane potential (lower trace) is presented. Grey bar represents time of glutamate application. No increase in Ca2+ is apparent upon iontophoresis of glutamate onto the axon. (d) Left, line-scan through a bouton of another cell and the corresponding Ca2+ transient evoked by a burst of 5 APs at 50 Hz. Right, line-scan through the same bouton during iontophoresis of glutamate. An increase in Ca2+ is evoked by the APs, but not by iontophoresis of glutamate.
(a)(b)(c)(d)Figure 4
APV has no influence on presynaptic AP-evoked Ca2+ transients. (a) Axonal Ca2+ transients evoked by a single AP in a spiny stellate axon recorded in L2/3 during baseline (black) and in the presence of the NMDAR blocker APV (purple). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. Lower trace represents the difference between the baseline and APV Ca2+ transients. Dashed line indicates zero and light shaded area indicates the baseline noise level (±SD). (b) Bar graph summary of the peak Ca2+ transient amplitudes (left) and decay time constants (right) for baseline and in the presence of APV. All data are represented as mean±SEM.
(a)(b)Therefore, in order to investigate the phenomenon of the specific 2-AG induced broadening of the AP-evoked Ca2+ signals in more detail, we measured single AP-evoked Ca2+ transients elicited at 0.1 Hz, corresponding to the stimulation frequency used for the LTD experiments (instead of stimulating at 0.003 Hz as in the previous imaging experiments) in spiny stellate axons before and during bath application of 2-AG (Figures 5(a) and 5(b)). We normalized and averaged the corresponding Ca2+ transients for comparison. We confirmed that 2-AG broadened the AP-evoked Ca2+ transients (Figure 5(b)). In contrast, in the presence of APV, 2-AG had no effect on the presynaptic Ca2+ signal (Figure 5(b)). Fitting a single exponential to the decay of the AP-evoked Ca2+ transients revealed a significantly slower decay in the presence of 2-AG as compared to the effect of 2-AG in the presence of APV (2-AG: normalized τ2−AG=1.23±0.07, n=15, p<0.01 for the effect of time on τ by paired Student’s t-test; 2-AG + APV: normalized τ2−AG=1.02±0.02, n=11, p=0.26 for the effect of time on τ by paired Student’s t-test; 2-AG control vs. 2-AG + APV, p<0.05 by one-way ANOVA; Figure 5(c)). The distribution of the normalized decay time constants revealed that 2-AG broadened the AP-evoked Ca2+ transients in 53% of the axons investigated (8 out of 15 axons; average change 1.40±0.08), while having no effect on the rest (7 out of 15; average change 1.03±0.01; Figure 5(d)). This observation suggests that not all axons and boutons were influenced by astrocyte activation, arguing for a compartmentalized astrocytic innervation and/or for synapse-specific expression of preNMDARs. The CB1 receptor antagonist AM251 (5 μM) abolished the effect of bath-application of 2-AG on the AP-evoked Ca2+ transients (AM251: normalized τ2−AG=0.97±0.04, n=5, p=0.40 for the effect of time on τ by paired Student’s t-test), excluding a nonspecific effect of 2-AG. Furthermore, repeating the experiment without any drug application had no effect on the AP-evoked Ca2+ transients (no drugs: normalized τ=1.02±0.06, n=4, p=0.51 for the effect of time on τ by paired Student’s t-test) demonstrating long-term stability of the experimental design and ruling out any time-dependent changes in axonal Ca2+ buffering due to the Ca2+ indicator.Figure 5
2-AG broadens AP-evoked Ca2+ transients in L4 axons. (a) Neurolucida reconstruction of a spiny stellate neuron. Dendrites are represented in blue and the axonal arborization in black. Inset, two-photon fluorescence image of the axon segment imaged in L2/3 indicated by the dashed box. (b) Left, averaged and normalized AP-evoked Ca2+ transients during baseline (grey) and after bath application of 2-AG (black). Upper trace represents the difference between the baseline and 2-AG Ca2+ transients. Dashed line indicates zero, and light-shaded area indicates the baseline noise level (±SD). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. There is an apparent difference between the two transients. Inset shows somatic APs before and after bath application of 2-AG. Right, experiment in which the NMDAR-blocker APV was present in the bath. No difference between the two transients was observed in this condition. (c) Normalized decay time constant in the presence of 2-AG for different conditions. 2-AG significantly broadened the Ca2+ transients (n=15). ##p<0.01 for the effect of time on τ by paired Student’s t-test. In contrast, no broadening was observed in the presence of APV (n=11), AM251 (n=5), or in control conditions without application of any drug (Ctrl, n=4). APV had a significant effect on τ in the presence of 2-AG. ∗p<0.05 by one-way ANOVA. All data are represented as mean±SEM. (d) Distribution of normalized decay time constants in the presence of 2-AG. Solid black lines represent Gaussian fits to the subsets that showed either no (light grey) or significant (dark grey) broadening of the Ca2+ transients.
(a)(b)(c)(d)2-AG evoked release of glutamate might activate dendritic NMDARs on the recorded neuron, which could potentially influence somatic membrane potential, AP generation, and somatic AP properties. Previously, such somato-dendritic NMDAR activation was shown to influence presynaptic Ca2+ signaling in cerebellar stellate cells [12]. However, when we analyzed the somatic resting membrane potential, AP amplitude, and AP width at the soma of the imaged spiny stellate neurons, we found no influence of 2-AG on either somatic parameter (Figure 6). Therefore, we can rule out an effect of somato-dendritic NMDARs on the presynaptic Ca2+ dynamics. Thus, our experiments revealed an APV-sensitive presynaptic Ca2+ component that manifested itself in a broadening of AP-evoked Ca2+ transients.Figure 6
AP properties are unaffected by 2-AG. (a) Neurolucida reconstruction of a spiny stellate neuron. Dendrites are represented in blue and the axonal arborization in black. (b) Upper traces, averaged and normalized AP-evoked Ca2+ transients during baseline (grey) and after bath application of 2-AG (black). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. Lower traces, corresponding somatic APs before (grey) and after (black) bath application of 2-AG. (c) Average bar graphs of resting membrane potential, AP amplitude, and AP width before and after bath application of 2-AG (n=12). None of the parameters changed significantly (p>0.1 by paired Student’s t-test). All data are represented as mean±SEM.
(a)(b)(c)Recently, it was shown that specific patterns of presynaptic activity alone, consisting of a burst of APs at 100 Hz or above, followed by a single AP between 50 and 200 ms later, can induce LTD. This form of LTD requires the activation of preNMDARs, but does not depend on astrocyte activation [10]. We tested whether this activity pattern also resulted in an APV-sensitive broadening of the presynaptic Ca2+ signal. A burst of APs at 100 Hz followed by a single AP 50 ms later evoked an axonal Ca2+ transient that was more rapidly decaying after wash-in of APV (Figure 7(a)). The difference between the Ca2+ transients under baseline conditions and in the presence of APV revealed an APV-sensitive Ca2+ component for this presynaptic stimulation pattern (peak difference baseline to APV: 0.04±0.02, n=6, p<0.05 by paired Student’s t-test; Figures 7(b) and 7(c)). Ca2+ transients evoked by 3 APs at 100 Hz alone showed no APV-sensitive Ca2+ component (−0.01±0.02, n=6, p=0.56 by paired Student’s t-test). Thus, the additional AP that followed 50 ms after the burst of 3 APs leads to a significant (p<0.05 by one-way ANOVA) additional presynaptic Ca2+ influx that was abolished by APV. The requirement of the presence of this delayed 4th AP suggests an interaction of the preNMDARs with a voltage-dependent mechanism initiated by the additional AP.Figure 7
Presynaptic burst patterns evoke an APV-sensitive Ca2+ transient component. (a) Example of the AP burst patterns that were used to evoke presynaptic Ca2+ transients in L4 spiny stellate axons. Left, 3 APs at 100 Hz. Right, 3 APs at 100 Hz followed 50 ms later by a single AP. (b) Axonal Ca2+ transients evoked by the activity patterns shown in (a) during baseline (black) and after bath application of APV (purple). Lower traces show the difference between the corresponding transients. (c) Comparison of the peak difference between the Ca2+ transients before and after bath application of APV (n=6). The 3AP+1AP activity pattern showed a significant effect of APV on the evoked Ca2+ transients, while the Ca2+ transients evoked by a burst of 3 APs alone were unaffected by APV. #p<0.05 by paired Student’s t-test. ∗p<0.05 by one-way ANOVA. All data are represented as mean±SEM.
(a)(b)(c)In summary, our experiments suggest that the activation of preNMDARs causes a slowing of the decay of AP-evoked Ca2+ transients, which results in an additional axonal Ca2+ influx that is intrinsically linked to the presence of the presynaptic AP. The source of the glutamate that activates the preNMDARs can either originate from 2-AG activated astrocytes or from glutamate spillover by a specifically timed presynaptic burst of APs.
## 3.3. preNMDARs Interact with Voltage-Dependent Ca2+ Channels
The broadening of the AP-evoked presynaptic Ca2+ transient could directly be due to the preNMDARs, which could contribute to Ca2+ influx during the AP-evoked axonal membrane depolarization and the subsequent relief of the Mg2+ block. In this scenario, preNMDARs would function as classical coincidence detectors, similar to what has been suggested for postsynaptic NMDARs. However, it has been shown that preNMDARs during early development might contain the GluN3A subunit, which renders them largely insensitive to Mg2+ block and with low permeability for Ca2+ [18]. An alternative function of the preNMDARs might be to contribute to the axonal membrane depolarization by Na+ influx or to exert a metabotropic effect during their activation. Both mechanisms could activate voltage-dependent Ca2+ channels (VDCCs) beyond the membrane depolarization caused by the axonal AP and contribute to an additional Ca2+ influx. To distinguish between a direct Ca2+ influx through preNMDARs and an interaction with VDCCs, we performed axonal Ca2+ imaging as described above and blocked VDCCs (Figure 8). Somatic APs evoked a consistent axonal Ca2+ transient which was abolished in the presence of the VDCC-blockers Cd2+ (100 μM) and Ni+ (50 μM) even though the somatic AP waveform was unchanged (ΔF/FBaseline=0.047±0.004, ΔF/FCd,Ni=0.008±0.001, n=4, p<0.01 by Student’s paired t-test with Bonferroni correction for multiple comparisons). Subsequent continuation of somatic AP stimulation during bath application of 2-AG, but still in the presence of Cd2+/Ni+ did not uncover an AP-evoked Ca2+ transient through preNMDARs (ΔF/F2−AG=0.002±0.001, p=0.32 by Student’s paired t-test with Bonferroni correction for multiple comparisons). This observation suggests that axonal membrane depolarization is not required for unblocking preNMDARs from a putative Mg2+ block to render them permeable for Ca2+. Contrary, we conclude that functional VDCCs are required so that preNMDARs can interact with them to prolong the axonal Ca2+ influx.Figure 8
Block of VDCCs does not uncover preNMDAR-dependent Ca2+ transients. (a) Axonal Ca2+ transients evoked by a single AP in a spiny stellate axon recorded in L2/3 during baseline (black) and in the presence of the VDCC blockers Cd2+ and Ni+ (blue). Subsequent bath application of 2-AG did not result in an AP-evoked Ca2+ transient (green). Shaded areas represent ±SEM and dashed lines ±SD of the basal fluorescence before stimulation. (b) Bar graph summary of the peak Ca2+ transient amplitudes in the different conditions (n=4). ∗∗p<0.01 by Student’s paired t-test with Bonferroni correction for multiple comparisons. All data are represented as mean±SEM.
(a)(b)
## 4. Discussion
NMDARs are essential ionotropic glutamate receptors for synaptic transmission, information processing, and synaptic plasticity. While classically thought to be located mainly postsynaptically, there is growing anatomical and physiological evidence that NMDARs also have important functions at presynaptic sites [2, 31–38]. We investigated the function of preNMDARs in juvenile L4-to-L2/3 glutamatergic connections in the somatosensory cortex. First, we showed that activation of astrocytes with the endocannabinoid 2-AG resulted in a form of presynaptic LTD (eCB-LTD) that depended on astrocyte Ca2+ signaling and the activation of preNMDARs, thereby showing an overlapping mechanism of induction with t-LTD [8]. Recording presynaptic Ca2+ dynamics during the induction of eCB-LTD allowed us to investigate the functional consequences of preNMDAR activation. In line with other studies, we found no evidence for a direct Ca2+ influx through preNMDARs during eCB-LTD induction or glutamate iontophoresis [13, 14]. Instead, our results suggest that the activation of preNMDARs leads to a prolonged activity of VDCCs resulting in an additional AP-evoked Ca2+ influx through these channels. Thus, we conclude that the action of preNMDARs has an indirect influence on presynaptic Ca2+ transients by interacting with VDCCs. These findings can reconcile some of the controversial results regarding preNMDARs and are consistent with the electrophysiological evidence for their influence in t-LTD.
### 4.1. Signaling Cascade for the Induction of t-LTD at Developing Cortical Synapses
The chemically induced eCB-LTD presented here shares the same signaling cascade as found in t-LTD. In t-LTD, the eCB 2-AG is synthetized by postsynaptic AP firing followed by presynaptic glutamate release. The postsynaptic backpropagating AP evokes an increase in postsynaptic Ca2+ through VDCCs, which is thought to prime phospholipase C (PLC), which is subsequently activated by the presynaptic release of glutamate binding to the metabotropic glutamate receptor type 5 (mGluR5) [6, 7]. In eCB-LTD, this postsynaptic signaling cascade is circumvented. However, the pathway downstream from eCB production is the same: in both cases, the activation of astrocytes by 2-AG resulting in an increase in astrocyte Ca2+ activity is necessary. Furthermore, preNMDARs are required for both t-LTD and eCB-LTD. preNMDARs are expressed in a target-cell-specific way only at a subset of synapses. This suggests that preNMDAR-mediated plasticity is limited to specific neuronal connections [19, 39–41]. Accordingly, we only found a 2-AG induced broadening of the Ca2+ transients in a subset of the investigated axonal boutons.The presynaptic AP is an essential component for eCB-LTD induction, since without the interaction of the AP with preNMDAR activation, there is no change in the presynaptic Ca2+ signal. This is in line with our earlier observation that when LTD is induced by direct electrical stimulation of astrocytes (thereby circumventing the necessity of endocannabinoid signaling), this LTD still requires presynaptic AP firing during the astrocyte activation [8]. This observation can now be explained, since only the interaction of the preNMDAR with VDCCs, activated by the axonal AP, changes the presynaptic Ca2+ dynamics. This in turn presumably leads to calcineurin modulation and LTD. Interestingly, very similar results have been obtained by others. In the first study showing involvement of eCBs and preNMDARs in t-LTD, it was already shown that eCB application only led to LTD if it was paired with presynaptic activity [4]. Furthermore, eCB-mediated LTD at inhibitory synapses in the hippocampus, which also requires calcineurin activity, shares the requirement for AP firing in the presynaptic neuron for its induction [27].A similar interaction of a presynaptic ionotropic glutamate receptor being activated by astrocytes and influencing synaptic release has recently been demonstrated [42]. In this case, axonal AMPARs were shown to be activated by astrocytes and contributed to axonal depolarization, broadening the axonal AP and thus influencing the Ca2+ dynamics at presynaptic sites. Furthermore, several studies have shown that somatic depolarization can lead to an additional axonal depolarization that gives rise to graded, analog release of transmitter [43, 44]. Importantly, we did not find an influence of 2-AG on the somatic membrane potential nor on AP properties, thereby ruling out such an influence on the axonal Ca2+ signals in our experiments.It should be noted that an intriguing interaction of postsynaptic NMDAR activation with presynaptic Ca2+ dynamics has also been described [45]. At hippocampal CA3-CA1 synapses, the efflux of potassium through postsynaptic NMDARs provides a retrograde signal to the presynaptic bouton, which can boost the presynaptic AP-evoked Ca2+ transient and increase neurotransmitter release. However, we deem it unlikely that a similar mechanism involving postsynaptic NMDAR activation can explain our observations. First, experiments with MK801 in the pre- or postsynaptic neuron show that both t-LTD [5, 8] and eCB-LTD (this study) require presynaptic, not postsynaptic, NMDAR activation. These results are supported by the finding that t-LTD at L4-L2/3 synapses in developing visual cortex is disrupted by cell-type-specific removal of NMDARs specifically from presynaptic L4 neurons [40]. Therefore, evidence for involvement of pre- rather than postsynaptic NMDARs in L4-L2/3 LTD is quite strong. Furthermore, when potassium-mediated retrograde signaling at CA3-CA1 axons was studied a Ca2+ transient broadening mediated by postsynaptic NMDARs was only observed with repetitive AP firing in the absence of extracellular Mg2+ [45]. In contrast, in our experiments, the 2-AG-mediated broadening of Ca2+ transients in L4 boutons occurred with single AP firing in the presence of 1 mM extracellular Mg2+. Under our experimental conditions, the potassium efflux through postsynaptic NMDARs is likely minimal due to Mg2+ block of these receptors. Finally, we observed that not all L4 boutons were showing a 2-AG induced broadening of the presynaptic Ca2+ transient. This is similar to what was observed in excitatory boutons in L5 of developing neocortex [35]. It indicates that not all L4 boutons contain preNMDARs. If postsynaptic NMDARs would be responsible for the presynaptic Ca2+ transient broadening such a lack of effect in some boutons is harder to explain, since postsynaptic NMDARs are ubiquitously expressed at most glutamatergic synapses [46–49].It was recently shown that a presynaptic burst of APs followed by a single AP between 50–200 ms later can also trigger LTD (termed pattern dependent LTD, p-LTD) [10]. The presynaptic burst of APs is probably sufficient to cause spillover of presynaptically released glutamate onto preNMDARs, supported by the findings that p-LTD no longer requires astrocyte activation, but still depends on preNMDARs. Presumably, the single AP occurring with a delay comes at the time when the presynaptically released glutamate from the preceding burst has activated preNMDARs. Consistently, when we performed presynaptic Ca2+ imaging, we were able to show that the p-LTD presynaptic activity pattern evoked an APV-sensitive Ca2+ component, whereas a burst of 3 APs alone did not. Thus, preNMDARs can differentially be activated depending on the pattern of presynaptic activity and only contribute to an additional Ca2+ influx under certain conditions.An interesting question in this context is which type of VDCC is modulated by the preNMDARs? Previous experiments suggest that neither L-type nor R-and T-type VDCCs are required, because t-LTD can be induced in the presence of blockers of these channels using a burst of 3 postsynaptic APs followed by a single presynaptic AP at -10 ms [6]. Single postprepairings are sensitive to these blockers suggesting a role of these VDCCs in the postsynaptic signaling cascade [6, 7]. Thus, N- and P/Q-type VDCCs might interact with the preNMDARs.Our data is in line with the idea that preNMDAR-mediated depolarization of the terminal carried by axonal Na+ influx through the receptor plays a role in the interaction of preNMDARs with VDCCs. A similar conclusion on the importance of NMDAR-mediated Na+ influx was reached for the effect of preNMDARs on spontaneous synaptic release [15]. This ionotropic effect of preNMDARs is further supported by the finding that presynaptically applied MK801, which acts as an open channels blocker and preventing ion flow through the NMDAR, is effective in blocking t-LTD [5, 50]. Similarly, presynaptic MK801 application also affects direct modulation of release through preNMDARs [19]. This efficacy of MK801 in blocking preNMDAR effects makes a metabotropic role as has been suggested recently for hippocampal LTD for these receptors [16, 51] unlikely since lack of MK801 block is seen as a hallmark for metabotropic NMDAR function (but see below for an alternative interpretation).
### 4.2. Conflicting Data on the Existence of preNMDARs
Several studies to date have sought for functional evidence of preNMDARs in neocortex and have come to the conclusion that these receptors do not exist [13, 14]. Our current results, together with earlier findings, offer an alternative explanation for this apparent controversy. Our study suggests that the function of preNMDARs differs from the classical coincidence detector role as described for postsynaptic NMDARs. Postsynaptic NMDAR activation requires the relieve of the Mg2+ block by a backpropagating AP to supralinearly enhance postsynaptic Ca2+ influx [30]. In contrast, we find little evidence for a direct preNMDAR-mediated Ca2+ signal. This is in line with several findings about the subunit composition of preNMDARs at developing synapses in the neocortex. In the developing visual cortex, preNMDARs contain the NR3A subunit rendering these NMDARs insensitive to Mg2+ and little Ca2+ permeable [18, 40]. Both properties agree with our findings that without a presynaptic AP, there is no substantial Ca2+ influx through preNMDARs. The lack of a presynaptic Ca2+ signal by iontophoresing glutamate onto presynaptic boutons or by uncaging of MNI-glutamate was interpreted by others as a lack of preNMDARs [13, 14]. However, our findings suggest that the effect of the preNMDARs on axonal Ca2+ signaling is rather subtle and becomes only apparent in the presence of specific patterns of presynaptic APs, thereby explaining the apparent lack of preNMDAR activity in other studies. Similar results were obtained by others when performing Ca2+ imaging experiments at glutamatergic synapses onto cortical interneurons: only prolonged axonal activation with sustained bursts of APs clearly uncovered an APV-sensitive component in the Ca2+ transient [19]. At other central synapses, direct Ca2+ influx has been observed through preNMDARs suggesting that there is a synapse-specific differential subunit composition of preNMDARs [20].Importantly, the recent conclusion that t-LTD requires post- rather than presynaptic NMDARs was not just based on negative Ca2+ imaging data but also on the absence of L4-L2/3 t-LTD in a transgenic mouse in which L2/3 NMDARs were selectively disrupted [14]. Although we cannot explain this apparent discrepancy, it should be noted that another study using a transgenic mouse in which L4 NMDARs were instead selectively disrupted also showed a disruption of L4-L2/3 t-LTD [40], thereby illustrating the potential developmental, species-specific, and brain-region specific differences, which are observed in these experiments.Finally, pharmacological evidence presented recently by Carter and Jahr [14] suggests that the mechanism of action of NMDARs involved in t-LTD is metabotropic. This conclusion was based on the inability of extracellularly applied MK-801 to block t-LTD, as well as on a lack of block by the glycine-site antagonists 7-CK and 5,7-DCK. The finding that extracellular MK-801 does not block t-LTD is in direct contradiction with studies showing effective t-LTD block by intracellularly applied MK-801 [5, 50]. In this respect, it is important to note again that the pharmacological profile of preNMDARs might differ from that of “classical” postsynaptic (NR1 and NR2 containing) NMDARs. Incorporation of the NR3A subunit (presumably in triheteromeric NR1-NR2B-NR3A receptors [18]) might alter receptor pharmacology (e.g., of MK801), possibly explaining such contradictory results [52]. However, our findings cannot distinguish between an ionotropic or a metabotropic role for preNMDARs [53]. If preNMDARs have a metabotropic function, they could exert their effect by a direct interaction with VDCCs to facilitate Ca2+ influx or by an inactivation of presynaptic K+ channels, both of which could broaden the AP locally and thus enhance presynaptic Ca2+ influx [54], which would be the required signal for calcineurin activation.
## 4.1. Signaling Cascade for the Induction of t-LTD at Developing Cortical Synapses
The chemically induced eCB-LTD presented here shares the same signaling cascade as found in t-LTD. In t-LTD, the eCB 2-AG is synthetized by postsynaptic AP firing followed by presynaptic glutamate release. The postsynaptic backpropagating AP evokes an increase in postsynaptic Ca2+ through VDCCs, which is thought to prime phospholipase C (PLC), which is subsequently activated by the presynaptic release of glutamate binding to the metabotropic glutamate receptor type 5 (mGluR5) [6, 7]. In eCB-LTD, this postsynaptic signaling cascade is circumvented. However, the pathway downstream from eCB production is the same: in both cases, the activation of astrocytes by 2-AG resulting in an increase in astrocyte Ca2+ activity is necessary. Furthermore, preNMDARs are required for both t-LTD and eCB-LTD. preNMDARs are expressed in a target-cell-specific way only at a subset of synapses. This suggests that preNMDAR-mediated plasticity is limited to specific neuronal connections [19, 39–41]. Accordingly, we only found a 2-AG induced broadening of the Ca2+ transients in a subset of the investigated axonal boutons.The presynaptic AP is an essential component for eCB-LTD induction, since without the interaction of the AP with preNMDAR activation, there is no change in the presynaptic Ca2+ signal. This is in line with our earlier observation that when LTD is induced by direct electrical stimulation of astrocytes (thereby circumventing the necessity of endocannabinoid signaling), this LTD still requires presynaptic AP firing during the astrocyte activation [8]. This observation can now be explained, since only the interaction of the preNMDAR with VDCCs, activated by the axonal AP, changes the presynaptic Ca2+ dynamics. This in turn presumably leads to calcineurin modulation and LTD. Interestingly, very similar results have been obtained by others. In the first study showing involvement of eCBs and preNMDARs in t-LTD, it was already shown that eCB application only led to LTD if it was paired with presynaptic activity [4]. Furthermore, eCB-mediated LTD at inhibitory synapses in the hippocampus, which also requires calcineurin activity, shares the requirement for AP firing in the presynaptic neuron for its induction [27].A similar interaction of a presynaptic ionotropic glutamate receptor being activated by astrocytes and influencing synaptic release has recently been demonstrated [42]. In this case, axonal AMPARs were shown to be activated by astrocytes and contributed to axonal depolarization, broadening the axonal AP and thus influencing the Ca2+ dynamics at presynaptic sites. Furthermore, several studies have shown that somatic depolarization can lead to an additional axonal depolarization that gives rise to graded, analog release of transmitter [43, 44]. Importantly, we did not find an influence of 2-AG on the somatic membrane potential nor on AP properties, thereby ruling out such an influence on the axonal Ca2+ signals in our experiments.It should be noted that an intriguing interaction of postsynaptic NMDAR activation with presynaptic Ca2+ dynamics has also been described [45]. At hippocampal CA3-CA1 synapses, the efflux of potassium through postsynaptic NMDARs provides a retrograde signal to the presynaptic bouton, which can boost the presynaptic AP-evoked Ca2+ transient and increase neurotransmitter release. However, we deem it unlikely that a similar mechanism involving postsynaptic NMDAR activation can explain our observations. First, experiments with MK801 in the pre- or postsynaptic neuron show that both t-LTD [5, 8] and eCB-LTD (this study) require presynaptic, not postsynaptic, NMDAR activation. These results are supported by the finding that t-LTD at L4-L2/3 synapses in developing visual cortex is disrupted by cell-type-specific removal of NMDARs specifically from presynaptic L4 neurons [40]. Therefore, evidence for involvement of pre- rather than postsynaptic NMDARs in L4-L2/3 LTD is quite strong. Furthermore, when potassium-mediated retrograde signaling at CA3-CA1 axons was studied a Ca2+ transient broadening mediated by postsynaptic NMDARs was only observed with repetitive AP firing in the absence of extracellular Mg2+ [45]. In contrast, in our experiments, the 2-AG-mediated broadening of Ca2+ transients in L4 boutons occurred with single AP firing in the presence of 1 mM extracellular Mg2+. Under our experimental conditions, the potassium efflux through postsynaptic NMDARs is likely minimal due to Mg2+ block of these receptors. Finally, we observed that not all L4 boutons were showing a 2-AG induced broadening of the presynaptic Ca2+ transient. This is similar to what was observed in excitatory boutons in L5 of developing neocortex [35]. It indicates that not all L4 boutons contain preNMDARs. If postsynaptic NMDARs would be responsible for the presynaptic Ca2+ transient broadening such a lack of effect in some boutons is harder to explain, since postsynaptic NMDARs are ubiquitously expressed at most glutamatergic synapses [46–49].It was recently shown that a presynaptic burst of APs followed by a single AP between 50–200 ms later can also trigger LTD (termed pattern dependent LTD, p-LTD) [10]. The presynaptic burst of APs is probably sufficient to cause spillover of presynaptically released glutamate onto preNMDARs, supported by the findings that p-LTD no longer requires astrocyte activation, but still depends on preNMDARs. Presumably, the single AP occurring with a delay comes at the time when the presynaptically released glutamate from the preceding burst has activated preNMDARs. Consistently, when we performed presynaptic Ca2+ imaging, we were able to show that the p-LTD presynaptic activity pattern evoked an APV-sensitive Ca2+ component, whereas a burst of 3 APs alone did not. Thus, preNMDARs can differentially be activated depending on the pattern of presynaptic activity and only contribute to an additional Ca2+ influx under certain conditions.An interesting question in this context is which type of VDCC is modulated by the preNMDARs? Previous experiments suggest that neither L-type nor R-and T-type VDCCs are required, because t-LTD can be induced in the presence of blockers of these channels using a burst of 3 postsynaptic APs followed by a single presynaptic AP at -10 ms [6]. Single postprepairings are sensitive to these blockers suggesting a role of these VDCCs in the postsynaptic signaling cascade [6, 7]. Thus, N- and P/Q-type VDCCs might interact with the preNMDARs.Our data is in line with the idea that preNMDAR-mediated depolarization of the terminal carried by axonal Na+ influx through the receptor plays a role in the interaction of preNMDARs with VDCCs. A similar conclusion on the importance of NMDAR-mediated Na+ influx was reached for the effect of preNMDARs on spontaneous synaptic release [15]. This ionotropic effect of preNMDARs is further supported by the finding that presynaptically applied MK801, which acts as an open channels blocker and preventing ion flow through the NMDAR, is effective in blocking t-LTD [5, 50]. Similarly, presynaptic MK801 application also affects direct modulation of release through preNMDARs [19]. This efficacy of MK801 in blocking preNMDAR effects makes a metabotropic role as has been suggested recently for hippocampal LTD for these receptors [16, 51] unlikely since lack of MK801 block is seen as a hallmark for metabotropic NMDAR function (but see below for an alternative interpretation).
## 4.2. Conflicting Data on the Existence of preNMDARs
Several studies to date have sought for functional evidence of preNMDARs in neocortex and have come to the conclusion that these receptors do not exist [13, 14]. Our current results, together with earlier findings, offer an alternative explanation for this apparent controversy. Our study suggests that the function of preNMDARs differs from the classical coincidence detector role as described for postsynaptic NMDARs. Postsynaptic NMDAR activation requires the relieve of the Mg2+ block by a backpropagating AP to supralinearly enhance postsynaptic Ca2+ influx [30]. In contrast, we find little evidence for a direct preNMDAR-mediated Ca2+ signal. This is in line with several findings about the subunit composition of preNMDARs at developing synapses in the neocortex. In the developing visual cortex, preNMDARs contain the NR3A subunit rendering these NMDARs insensitive to Mg2+ and little Ca2+ permeable [18, 40]. Both properties agree with our findings that without a presynaptic AP, there is no substantial Ca2+ influx through preNMDARs. The lack of a presynaptic Ca2+ signal by iontophoresing glutamate onto presynaptic boutons or by uncaging of MNI-glutamate was interpreted by others as a lack of preNMDARs [13, 14]. However, our findings suggest that the effect of the preNMDARs on axonal Ca2+ signaling is rather subtle and becomes only apparent in the presence of specific patterns of presynaptic APs, thereby explaining the apparent lack of preNMDAR activity in other studies. Similar results were obtained by others when performing Ca2+ imaging experiments at glutamatergic synapses onto cortical interneurons: only prolonged axonal activation with sustained bursts of APs clearly uncovered an APV-sensitive component in the Ca2+ transient [19]. At other central synapses, direct Ca2+ influx has been observed through preNMDARs suggesting that there is a synapse-specific differential subunit composition of preNMDARs [20].Importantly, the recent conclusion that t-LTD requires post- rather than presynaptic NMDARs was not just based on negative Ca2+ imaging data but also on the absence of L4-L2/3 t-LTD in a transgenic mouse in which L2/3 NMDARs were selectively disrupted [14]. Although we cannot explain this apparent discrepancy, it should be noted that another study using a transgenic mouse in which L4 NMDARs were instead selectively disrupted also showed a disruption of L4-L2/3 t-LTD [40], thereby illustrating the potential developmental, species-specific, and brain-region specific differences, which are observed in these experiments.Finally, pharmacological evidence presented recently by Carter and Jahr [14] suggests that the mechanism of action of NMDARs involved in t-LTD is metabotropic. This conclusion was based on the inability of extracellularly applied MK-801 to block t-LTD, as well as on a lack of block by the glycine-site antagonists 7-CK and 5,7-DCK. The finding that extracellular MK-801 does not block t-LTD is in direct contradiction with studies showing effective t-LTD block by intracellularly applied MK-801 [5, 50]. In this respect, it is important to note again that the pharmacological profile of preNMDARs might differ from that of “classical” postsynaptic (NR1 and NR2 containing) NMDARs. Incorporation of the NR3A subunit (presumably in triheteromeric NR1-NR2B-NR3A receptors [18]) might alter receptor pharmacology (e.g., of MK801), possibly explaining such contradictory results [52]. However, our findings cannot distinguish between an ionotropic or a metabotropic role for preNMDARs [53]. If preNMDARs have a metabotropic function, they could exert their effect by a direct interaction with VDCCs to facilitate Ca2+ influx or by an inactivation of presynaptic K+ channels, both of which could broaden the AP locally and thus enhance presynaptic Ca2+ influx [54], which would be the required signal for calcineurin activation.
## 5. Conclusion
In summary, we show evidence for the existence of functional preNMDARs in spiny stellate axons at L4-L2/3 synapses in the developing rat barrel cortex. Their function is to sense glutamate either released from astrocytes or from spill-over by enhanced presynaptic activity and then to modulate the local axonal Ca2+ influx. This modulation could be either by contributing to the local membrane depolarization or by a metabotropic action affecting VDCCs or other presynaptic ionic conductances. Either mechanism would affect subsequent axonal APs by modifying AP-induced Ca2+ dynamics, thereby leading to the induction of LTD. The elucidation of the mode of action of preNMDARs is one of the remaining missing pieces to understand the signaling cascade of t-LTD at developing cortical synapses.
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*Source: 2900875-2022-02-07.xml* | 2900875-2022-02-07_2900875-2022-02-07.md | 95,218 | Presynaptic NMDA Receptors Influence Ca2+ Dynamics by Interacting with Voltage-Dependent Calcium Channels during the Induction of Long-Term Depression | Florian B. Neubauer; Rogier Min; Thomas Nevian | Neural Plasticity
(2022) | Biological Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2900875 | 2900875-2022-02-07.xml | ---
## Abstract
Spike-timing-dependent long-term depression (t-LTD) of glutamatergic layer (L)4-L2/3 synapses in developing neocortex requires activation of astrocytes by endocannabinoids (eCBs), which release glutamate onto presynaptic NMDA receptors (preNMDARs). The exact function of preNMDARs in this context is still elusive and strongly debated. To elucidate their function, we show that bath application of the eCB 2-arachidonylglycerol (2-AG) induces a preNMDAR-dependent form of chemically induced LTD (eCB-LTD) in L2/3 pyramidal neurons in the juvenile somatosensory cortex of rats. Presynaptic Ca2+ imaging from L4 spiny stellate axons revealed that action potential (AP) evoked Ca2+ transients show a preNMDAR-dependent broadening during eCB-LTD induction. However, blockade of voltage-dependent Ca2+ channels (VDCCs) did not uncover direct preNMDAR-mediated Ca2+ transients in the axon. This suggests that astrocyte-mediated glutamate release onto preNMDARs does not result in a direct Ca2+ influx, but that it instead leads to an indirect interaction with presynaptic VDCCs, boosting axonal Ca2+ influx. These results reveal one of the main remaining missing pieces in the signaling cascade of t-LTD at developing cortical synapses.
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## Body
## 1. Introduction
Presynaptic NMDA receptors (preNMDARs) have important functions in synaptic transmission, information processing, and long-term plasticity in several regions of the brain [1–3]. Particularly, preNMDARs are thought to be required for the induction of spike-timing-dependent LTD (t-LTD) at developing neocortical synapses [4–7]. Recently, we suggested that t-LTD in the developing rat barrel cortex requires eCB-dependent activation of astrocytes, which results in the release of glutamate onto preNMDARs [8, 9]. Importantly, we showed that astrocyte activity alone is not sufficient for the induction of LTD. Simultaneous presynaptic APs concomitant with astrocyte activation are required [8]. This suggests that axonal APs interact with preNMDARs in a yet unknown way leading to the induction of t-LTD.Under certain conditions, preNMDARs in barrel cortex can also function as autoreceptors for presynaptically released glutamate. Bursts of APs followed by a correctly timed additional AP can induce pattern-dependent LTD at the L4-L2/3 synapse [10]. Importantly, since this form of LTD requires presynaptic release of glutamate, it bypasses the need for astrocyte activation. Similarly, bursts of APs in the visual cortex can induce preNMDAR dependent LTD at L4-L4 connections [11]. Therefore, preNMDAR-mediated LTD always requires presynaptic activity, whereas the source of the glutamate (astrocytic or presynaptic) might vary. This implies that there should be a presynaptic coincidence detection mechanism involving both presynaptic activity and preNMDAR activation.Despite the studies highlighted above, there is an active debate about the existence and function of preNMDARs. This debate is mainly fueled by contradictory findings on presynaptic Ca2+ signals mediated by preNMDARs. Lack of axonal Ca2+ signals in boutons of L5 and L4 neurons in developing neocortex upon iontophoresis of aspartate or upon MNI-glutamate uncaging, and lack of an APV sensitive component in single AP-evoked Ca2+ transients argue against the existence of preNMDARs [12–14]. On the other hand, there is ample anatomical and physiological evidence for the presence of preNMDARs [1, 2]. Yet, their mechanism of function remains elusive. It has been hypothesized that either a direct presynaptic Ca2+ influx through preNMDARs, a presynaptic depolarization mediated by Na+ influx through preNMDARs [15] or a metabotropic effect [16], could be the mechanism of preNMDAR function. The properties of preNMDARs strongly depend on their subunit composition, which can influence permeability for Ca2+, voltage-sensitive Mg2+ block, subcellular location, and gating kinetics. preNMDARs at cortical synapses contain GluN2C, GluN2D, or GluN3A subunits, rendering them relatively Mg2+ insensitive with low permeability for Ca2+ [17, 18]. Consistently, a direct presynaptic Ca2+ influx through preNMDARs at cortical synapses has rarely been observed. At a fraction of cortical L5 boutons, pairing activation of preNMDARs by glutamate uncaging and high-frequency AP firing causes an enhancement of axonal Ca2+ influx [19]. In contrast, preNMDARs located on parallel fibres in the cerebellum seem to be permeable for Ca2+, and a direct preNMDAR-mediated Ca2+ influx has been reported [20].Here, we hypothesize that the activation of preNMDARs alone is not sufficient to evoke a detectable Ca2+ signal in L4 boutons in developing barrel cortex, but that the interaction with axonal APs is required. To investigate this hypothesis, we utilized a form of chemical LTD mediated by bath application of 2-AG combined with presynaptic Ca2+ imaging. First, we showed that eCB-LTD depended on astrocyte and preNMDAR activation. Bath application of 2-AG should globally activate astrocytes that innervate preNMDARs, thus, increasing the probability to detect an influence on presynaptic Ca2+ dynamics. Indeed, we observed an APV-sensitive broadening of AP-evoked Ca2+ transients. Investigation of the underlying mechanism suggested that preNMDARs have little Ca2+ permeability and that their major mechanism of function is to interact with voltage-dependent Ca2+ channels (VDCCs) to prolong AP-evoked Ca2+ influx in presynaptic boutons. Our data is consistent with previous results and can help to reconcile apparent contradictory observations, thereby contributing to a better mechanistic understanding of preNMDAR function.
## 2. Material and Methods
### 2.1. Slice Preparation
Experiments were approved by the Veterinary Office of the Canton of Bern, Switzerland. Thalamocortical brain slices containing the barrel subfield of somatosensory cortex were prepared from 12–21 d old Wistar rats of either sex [21]. Rats were decapitated, and their brains were quickly removed into cold (0–4°C) oxygenated physiological solution containing 125 mM NaCl, 2.5 mM KCl, 1.25 mM NaH2PO4, 25 mM NaHCO3, 1 mM MgCl2, 2 mM CaCl2, and 25 mM glucose. Slices, 300 μm thick, were cut from the tissue block with a vibratome (Microm) and kept at 37°C for 30 min and then at room temperature until use.
### 2.2. Electrophysiology
All experiments were performed at 30–34°C. For recording, slices were transferred to a recording chamber perfused with oxygenated physiological solution (same as above). The barrel subfield of somatosensory cortex was identified by the presence of barrels in L4, visible under trans-illumination. A monopolar glass stimulation electrode was placed in a L4 barrel, and whole-cell recordings for plasticity experiments were performed from L2/3 pyramidal neurons right above the corresponding barrel. Cells were identified using infrared gradient contrast video microscopy. Recording electrodes with a resistance of 4–7 MΩ were made using borosilicate glass capillaries. Recordings were performed using Dagan BVC-700A amplifiers (Dagan). Data were acquired with an ITC-16 AD-DA board (Instrutech) and using Igor software (Wavemetrics). The intracellular solution for recording neurons contained 130 mM potassium gluconate, 10 mM potassium HEPES, 10 mM sodium phosphocreatine, 4 mM Mg-ATP, 0.3 mM Na-GTP, 4 mM NaCl, 10 mM sodium gluconate (pH 7.3 with KOH), and biocytin (0.2% w/v).Single component EPSPs in the pyramidal neuron with amplitudes between 1 and 5 mV were evoked by stimulation in L4. After obtaining a stable baseline for 10 min at 0.1 Hz stimulation, the endocannabinoid 2-AG (10-20μM) was bath applied for 20 min, while continuing the extracellular stimulation. During wash-out, EPSPs were recorded for an additional 40 min. Experiments were discarded if the baseline EPSP slope was unstable (>10% change between first 15 and last 15 EPSP slopes of the baseline period), or if the pyramidal neuron input resistance or membrane potential changed by >15% during the course of the experiment.To investigate the influence of astrocytes on synaptic depression, whole-cell patch clamp recordings were performed from astrocytes adjacent to the recorded pyramidal neuron in L2/3. The intracellular solution for recording astrocytes contained 135 mM KCH3O3S, 10 mM HEPES, 10 mM sodium phosphocreatine, 4 mM MgCl2, 4 mM Na2-ATP, and 0.4 mM Na-GTP (pH 7.2 with KOH). Astrocytes were characterized by a low resting membrane potential, passive responses to both negative and positive current injections, and a low membrane resistance [8]. For astrocyte Ca2+ clamp experiments, 200 μM OGB-1, 0.45 mM EGTA, and 0.14 mM CaCl2 were added to the astrocyte intracellular solution to clamp intracellular free Ca2+ at a steady-state concentration of 50–80 nM [22].For axonal Ca2+ imaging experiments, recordings from spiny stellate neurons in L4 of the barrel cortex were performed in the whole-cell current clamp configuration. The intracellular solution was supplemented with the Ca2+ indicator Oregon Green Bapta-1 (OGB-1, 200 μM) and the morphological dye Alexa-594 (50 μM). APs were evoked by suprathreshold somatic current injections (5 ms) at varying frequencies.Ionotophoresis of glutamate (100μM) through a high resistance (>100 MΩ) application glass pipette was performed with an AxoClamp 2B amplifier in current clamp mode. A small retain current was applied to prevent leakage of glutamate. Brief (1 ms) current pulses were used to iontophorese the glutamate in close proximity to dendrites or axons of L4 spiny stellate neurons.
### 2.3. Ca2+ Imaging
For two-photon excitation fluorescence microscopy, an infrared femtosecond-pulsed titanium sapphire laser (MaiTai, Spectraphysics) was coupled to a home-built laser scanning microscope equipped with a water-immersion objective (W63x HCX APO UVI, 0.9 NA, Leica). Excitation infrared laser light and fluorescence emission light were separated at 670 nm (excitation filter 670DCXXR, AHF Analysentechnik). The emission spectra were separated by a dichroic mirror at 560 nm (beam splitter 560DCXR, AHF) and corresponding bandpass (HQ525/50, HQ610/75, AHF) and infrared-block filters (700SP-2P, AHF) and were detected using nondescanned detection behind the objective. Dyes were excited atλ=920nm. Data was acquired using custom-written laser-scanning software in LabView (National Instruments) [23]. Axonal Ca2+ imaging was performed in frame scan mode (30×30μm2) at 3 Hz for 1 min duration and repeated every 5 min. Astrocytic Ca2+ signals were acquired from astrocytes loaded with Rhod2-AM by pressure ejection of the dye-containing solution into the brain slice under visual control with a 10× objective. For dye preparation, 50 μg Rhod2-AM was dissolved in 5 μl of 80% DMSO and 20% pluronic acid F127 (w/v; Sigma) and diluted 1 : 19 in a HEPES-buffered solution containing 125 mM NaCl, 2.5 mM KCl, and 10 mM HEPES. This procedure resulted in specific uptake of the Rhod2 in astrocytes in the injected area. Frame scans (35×35μm2) at 3 Hz for 2 min duration, repeated every 5 min containing one astrocyte, were performed before, during, and after bath application of 2-AG.
### 2.4. Data Analysis
Electrophysiological data were analyzed using custom-written procedures in Igor Pro (Wavemetrics). EPSP slope was measured as a linear fit between time points on the rising phase of the EPSP corresponding to 20 and 60% of the EPSP peak amplitude. The change in EPSP slope was evaluated 20–40 min after the end of the pairing period and normalized to the baseline EPSP slope. Axonal and astrocyte imaging data were analyzed using custom-written procedures in Matlab. Regions of interest containing the axon segment were automatically detected and fluorescence traces extracted. Relative fluorescence changes were calculated asΔF/F=Ft−F0/F0, where Ft denotes fluorescence over time and F0 baseline fluorescence. AP-evoked Ca2+ transients were normalized and averaged. Single exponential fits to the decay of the Ca2+ transients yielded the decay time constants for the different conditions.
### 2.5. Statistical Analysis
Statistical analysis was done using paired or unpaired Student’st-test (for single comparisons) or ANOVA with post hoc Bonferroni correction (for multiple comparisons to the same control). Statistical significance was asserted for p<0.05. Data are presented as mean±s.e.m.
### 2.6. Histology
During experiments, cells were filled with biocytin and fixed in 4% paraformaldehyde. Slices were developed with the avidin-biotin-peroxidase method and mounted on cover slides for reconstruction with Neurolucida [24, 25].
### 2.7. Chemicals
Chemicals were obtained from the following sources: 2-AG and cyclosporin-A from Sigma-Aldrich, 1-(2,4-dichlorophenyl)-5-(4-iodophenyl)-4-methyl-N-(piperidin-1-yl)-1H-pyrazole-3-carboxamide (AM251), d-AP5 from Ascent Scientific, (+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine maleate (MK-801), and L-glutamic acid from Tocris, FK506 from Abmole Bioscience.
## 2.1. Slice Preparation
Experiments were approved by the Veterinary Office of the Canton of Bern, Switzerland. Thalamocortical brain slices containing the barrel subfield of somatosensory cortex were prepared from 12–21 d old Wistar rats of either sex [21]. Rats were decapitated, and their brains were quickly removed into cold (0–4°C) oxygenated physiological solution containing 125 mM NaCl, 2.5 mM KCl, 1.25 mM NaH2PO4, 25 mM NaHCO3, 1 mM MgCl2, 2 mM CaCl2, and 25 mM glucose. Slices, 300 μm thick, were cut from the tissue block with a vibratome (Microm) and kept at 37°C for 30 min and then at room temperature until use.
## 2.2. Electrophysiology
All experiments were performed at 30–34°C. For recording, slices were transferred to a recording chamber perfused with oxygenated physiological solution (same as above). The barrel subfield of somatosensory cortex was identified by the presence of barrels in L4, visible under trans-illumination. A monopolar glass stimulation electrode was placed in a L4 barrel, and whole-cell recordings for plasticity experiments were performed from L2/3 pyramidal neurons right above the corresponding barrel. Cells were identified using infrared gradient contrast video microscopy. Recording electrodes with a resistance of 4–7 MΩ were made using borosilicate glass capillaries. Recordings were performed using Dagan BVC-700A amplifiers (Dagan). Data were acquired with an ITC-16 AD-DA board (Instrutech) and using Igor software (Wavemetrics). The intracellular solution for recording neurons contained 130 mM potassium gluconate, 10 mM potassium HEPES, 10 mM sodium phosphocreatine, 4 mM Mg-ATP, 0.3 mM Na-GTP, 4 mM NaCl, 10 mM sodium gluconate (pH 7.3 with KOH), and biocytin (0.2% w/v).Single component EPSPs in the pyramidal neuron with amplitudes between 1 and 5 mV were evoked by stimulation in L4. After obtaining a stable baseline for 10 min at 0.1 Hz stimulation, the endocannabinoid 2-AG (10-20μM) was bath applied for 20 min, while continuing the extracellular stimulation. During wash-out, EPSPs were recorded for an additional 40 min. Experiments were discarded if the baseline EPSP slope was unstable (>10% change between first 15 and last 15 EPSP slopes of the baseline period), or if the pyramidal neuron input resistance or membrane potential changed by >15% during the course of the experiment.To investigate the influence of astrocytes on synaptic depression, whole-cell patch clamp recordings were performed from astrocytes adjacent to the recorded pyramidal neuron in L2/3. The intracellular solution for recording astrocytes contained 135 mM KCH3O3S, 10 mM HEPES, 10 mM sodium phosphocreatine, 4 mM MgCl2, 4 mM Na2-ATP, and 0.4 mM Na-GTP (pH 7.2 with KOH). Astrocytes were characterized by a low resting membrane potential, passive responses to both negative and positive current injections, and a low membrane resistance [8]. For astrocyte Ca2+ clamp experiments, 200 μM OGB-1, 0.45 mM EGTA, and 0.14 mM CaCl2 were added to the astrocyte intracellular solution to clamp intracellular free Ca2+ at a steady-state concentration of 50–80 nM [22].For axonal Ca2+ imaging experiments, recordings from spiny stellate neurons in L4 of the barrel cortex were performed in the whole-cell current clamp configuration. The intracellular solution was supplemented with the Ca2+ indicator Oregon Green Bapta-1 (OGB-1, 200 μM) and the morphological dye Alexa-594 (50 μM). APs were evoked by suprathreshold somatic current injections (5 ms) at varying frequencies.Ionotophoresis of glutamate (100μM) through a high resistance (>100 MΩ) application glass pipette was performed with an AxoClamp 2B amplifier in current clamp mode. A small retain current was applied to prevent leakage of glutamate. Brief (1 ms) current pulses were used to iontophorese the glutamate in close proximity to dendrites or axons of L4 spiny stellate neurons.
## 2.3. Ca2+ Imaging
For two-photon excitation fluorescence microscopy, an infrared femtosecond-pulsed titanium sapphire laser (MaiTai, Spectraphysics) was coupled to a home-built laser scanning microscope equipped with a water-immersion objective (W63x HCX APO UVI, 0.9 NA, Leica). Excitation infrared laser light and fluorescence emission light were separated at 670 nm (excitation filter 670DCXXR, AHF Analysentechnik). The emission spectra were separated by a dichroic mirror at 560 nm (beam splitter 560DCXR, AHF) and corresponding bandpass (HQ525/50, HQ610/75, AHF) and infrared-block filters (700SP-2P, AHF) and were detected using nondescanned detection behind the objective. Dyes were excited atλ=920nm. Data was acquired using custom-written laser-scanning software in LabView (National Instruments) [23]. Axonal Ca2+ imaging was performed in frame scan mode (30×30μm2) at 3 Hz for 1 min duration and repeated every 5 min. Astrocytic Ca2+ signals were acquired from astrocytes loaded with Rhod2-AM by pressure ejection of the dye-containing solution into the brain slice under visual control with a 10× objective. For dye preparation, 50 μg Rhod2-AM was dissolved in 5 μl of 80% DMSO and 20% pluronic acid F127 (w/v; Sigma) and diluted 1 : 19 in a HEPES-buffered solution containing 125 mM NaCl, 2.5 mM KCl, and 10 mM HEPES. This procedure resulted in specific uptake of the Rhod2 in astrocytes in the injected area. Frame scans (35×35μm2) at 3 Hz for 2 min duration, repeated every 5 min containing one astrocyte, were performed before, during, and after bath application of 2-AG.
## 2.4. Data Analysis
Electrophysiological data were analyzed using custom-written procedures in Igor Pro (Wavemetrics). EPSP slope was measured as a linear fit between time points on the rising phase of the EPSP corresponding to 20 and 60% of the EPSP peak amplitude. The change in EPSP slope was evaluated 20–40 min after the end of the pairing period and normalized to the baseline EPSP slope. Axonal and astrocyte imaging data were analyzed using custom-written procedures in Matlab. Regions of interest containing the axon segment were automatically detected and fluorescence traces extracted. Relative fluorescence changes were calculated asΔF/F=Ft−F0/F0, where Ft denotes fluorescence over time and F0 baseline fluorescence. AP-evoked Ca2+ transients were normalized and averaged. Single exponential fits to the decay of the Ca2+ transients yielded the decay time constants for the different conditions.
## 2.5. Statistical Analysis
Statistical analysis was done using paired or unpaired Student’st-test (for single comparisons) or ANOVA with post hoc Bonferroni correction (for multiple comparisons to the same control). Statistical significance was asserted for p<0.05. Data are presented as mean±s.e.m.
## 2.6. Histology
During experiments, cells were filled with biocytin and fixed in 4% paraformaldehyde. Slices were developed with the avidin-biotin-peroxidase method and mounted on cover slides for reconstruction with Neurolucida [24, 25].
## 2.7. Chemicals
Chemicals were obtained from the following sources: 2-AG and cyclosporin-A from Sigma-Aldrich, 1-(2,4-dichlorophenyl)-5-(4-iodophenyl)-4-methyl-N-(piperidin-1-yl)-1H-pyrazole-3-carboxamide (AM251), d-AP5 from Ascent Scientific, (+)-5-methyl-10,11-dihydro-5H-dibenzo[a,d]cyclohepten-5,10-imine maleate (MK-801), and L-glutamic acid from Tocris, FK506 from Abmole Bioscience.
## 3. Results
### 3.1. Endocannabinoid-Dependent LTD Requires Activation of Astrocytes and preNMDARs
t-LTD at L4-L2/3 excitatory synapses in rat barrel cortex depends on the activation of astrocytes by 2-AG that is synthetized postsynaptically. This synthesis occurs at synapses which are activated within a time window of about 50 ms after the generation of a postsynaptic AP. Astrocyte activation results in the release of glutamate onto preNMDARs which interact with presynaptic APs to trigger a reduction in release probability [8]. To further understand the presynaptic signaling cascade leading to t-LTD, Ca2+ imaging from presynaptic boutons during t-LTD induction would be the best approach. However, this is technically challenging, since it requires imaging from the presynaptic bouton of an identified synaptic connection while at the same time controlling AP firing in the pre- and postsynaptic neuron. As an alternative approach, we tested if direct bath-application of 2-AG resulted in synaptic depression without postsynaptic activity at L4-L2/3 synapses, similar to what was previously described for L5-L5 synapses [4]. We performed whole-cell patch-clamp recordings from L2/3 pyramidal neurons in the somatosensory cortex of juvenile rats and activated L4 spiny stellate neuron axons by extracellular stimulation in L4. After recording a baseline of EPSPs for 10 min, we bath-applied 2-AG (10 μM) for 20 min while continuing presynaptic stimulation at 0.1 Hz. We observed a long-lasting depression of the EPSPs 10–30 min after the washout of 2-AG (0.58±0.09, n=13, p<0.01 for the effect of time on EPSP slope by Student’s paired t-test; Figure 1(a)). This form of LTD was presynaptic as the reduction in normalized EPSP amplitude correlated with a reduction in the normalized coefficient of variation (Figure 1(b)).Figure 1
2-AG mediated LTD requires astrocyte Ca2+ signaling and preNMDARs. (a) Time course of normalized and averaged EPSP slope measured in L2/3 pyramidal neurons before, during (0–20 min, shaded area) and after bath application of 2-AG (n=13). Inset, representative average EPSP during baseline (black) and after 2-AG (grey). (b) Relative change of coefficient of variation of EPSP slope after bath application of 2-AG as a function of corresponding changes in EPSP slope. The relation is almost linear, indicating a presynaptic locus of eCB-LTD expression. Open circles represent individual experiments, and filled circle represents the average (n=13). (c) Two-photon fluorescence image of an astrocyte in L2/3 of the somatosensory cortex loaded with the Ca2+ indicator Rhod-2. Traces to the right show Ca2+ fluctuations in the astrocyte before, during, and after bath application of 2-AG (shaded area). (d) Summary of the average number of Ca2+ transients during the time course of the experiment (n=12). ∗p<0.05 for the effect of time on Ca2+ transient number by Student’s paired t-test. (e) Normalized and averaged EPSP slope over time in L2/3 pyramidal neurons, while an adjacent astrocyte was infused in the whole-cell recording configuration with either a control (Ctrl, n=8) and or Ca2+ clamp solution (n=9). Inset, representative average EPSP during baseline (black) and after 2-AG in control (light green) or Ca2+ clamp (dark green) conditions. (f) Normalized and averaged EPSP slope over time during bath application of APV (n=13) or intracellular infusion of MK801 (n=24) into the pyramidal neuron (iMK801). Inset, representative average EPSP during baseline (black) and after 2-AG in the presence of APV (purple) or iMK801 (blue). (g) Normalized and averaged EPSP slope in the presence of the calcineurin inhibitors FK506 and cyclosporin-A (n=2). Inset, representative average EPSP during baseline (black) and after 2-AG (orange). (h) Bar graph summary of experiments shown in (e) and (f). In the astrocyte Ca2+ clamp condition, eCB-LTD was abolished. APV blocked eCB-LTD, while intracellular block of postsynaptic NMDARs with MK801 had no effect. #p<0.05 by one-way ANOVA. All data are represented as mean±SEM. All scale bars for average EPSPs represent 40 ms and 2 mV, respectively.
(a)(b)(c)(d)(e)(f)(g)(h)Next, we confirmed that 2-AG activated cortical astrocytes in L2/3. Bulk-loading of astrocytes with Rhod2-AM, which is preferentially taken up by astrocytes, allowed to measure the intracellular Ca2+ dynamics during bath-application of 2-AG (Figure 1(c)). We observed a significant increase in the number of Ca2+ transients by 2-AG (from 0.75±0.26min−1 to 1.08±0.20min−1, n=12, p<0.05 for the effect of time on Ca2+ transient number by Student’s paired t-test) that decayed back to baseline levels after wash-out (Figure 1(d)). This experiment confirmed previous results showing that eCBs modulate astrocytic Ca2+ dynamics [8, 26]. Infusing an astrocyte with a solution that clamped the intracellular Ca2+ concentration to a constant level abolished eCB-LTD in adjacent pyramidal neurons (1.00±0.10, n=9, p=0.87 for the effect of time on EPSP slope by Student’s paired t-test), while infusing a control intracellular solution into the astrocytes resulted in eCB-LTD (0.74±0.06, n=8, p<0.05 for the effect of time on EPSP slope by Student’s paired t-test; comparison control vs. Ca2+ clamp, p<0.05 by one-way ANOVA; Figures 1(e) and 1(h)). Thus, similar to t-LTD, the increase in Ca2+ signaling in the astrocytes was required for the induction of eCB-LTD.Then, we tested the involvement of NMDARs in eCB-LTD. Bath-application of APV blocked the 2-AG mediated LTD (0.90±0.05, n=13, p=0.06 for the effect of time on EPSP slope by Student’s paired t-test), while infusion of MK801 into the postsynaptic cell had no effect on eCB-LTD (0.70±0.05, n=24, p<0.001 for the effect of time on EPSP slope by Student’s paired t-test; comparison APV vs. MK801, p<0.05 by one-way ANOVA; Figures 1(f) and 1(h)). These results suggested that downstream of astrocyte signaling, eCB-LTD required the activation of presynaptic NMDARs.PreNMDAR-dependent LTD at cortical synapses [10] and eCB-mediated LTD at both excitatory and inhibitory synapses in the hippocampus [27, 28] require the activation of the Ca2+ dependent protein phosphatase calcineurin [29]. In order to test a similar involvement in our case, we blocked calcineurin activity by incubating the brain slices in FK506 (50 μM) and cyclosporin-A (25 μM) at least for 1 h before the start of the experiment and with 20 μM and 10 μM, respectively, during the experiment. EPSPs were evoked by extracellular stimulation in L4, and 2-AG was washed-in for 20 min as described above. In the condition of blocked calcineurin activity, no eCB-LTD was induced (0.95±0.01, n=2, Figure 1(g)). These results indicate that calcineurin is involved in the induction of eCB-LTD.In summary, our experiments show that eCB-LTD and t-LTD share a similar induction mechanism, since both are dependent on astrocyte activation by eCBs and on activation of preNMDARs. The involvement of calcineurin suggests that an elevation in presynaptic Ca2+ is essential for these forms of LTD.
### 3.2. Presynaptic NMDARs Broaden AP-Evoked Ca2+ Transients in L4 Spiny Stellate Axons
We sought to investigate the functional consequence of preNMDAR activation and thus the potential source of Ca2+ required for LTD in L4 spiny stellate axons while they were activated by glutamate release from 2-AG activated astrocytes. We loaded L4 spiny stellate neurons with the Ca2+ indicator Oregon Green Bapta-1 (OGB-1, 200 μM) and the morphological dye Alexa-594 (50 μM) to trace the axon to L2/3 (Figures 2(a) and 2(b)). Frame scans of 1 min duration (3 Hz) from a stretch of axon were performed to measure the local Ca2+ signals before and during bath application of 2-AG. A single somatically evoked AP resulted in a stereotyped Ca2+ transient in the axonal compartment. Bath application of 2-AG did not cause a significant number of spontaneous, local Ca2+ transients in the axon as might have been hypothesized from an activation of preNMDARs (Figures 2(c) and 2(d)). We found a total of 12 spontaneous Ca2+ transients in 60 min of observation time (n=9 cells) in the presence of 2-AG. This number was not different from spontaneous events before 2-AG application (8 events in 40 min). However, comparing the time course of the presynaptic AP-evoked Ca2+ transients before and after 2-AG application revealed a prolongation of the AP-evoked Ca2+ signal in the presence of 2-AG (Figure 2(e)). We concluded from this experiment that glutamate release from astrocytes does not activate preNMDARs in a similar manner as axonal glutamate release activates postsynaptic NMDARs, which results in clear and distinct Ca2+ transients in postsynaptic spines [30]. This result is consistent with observations that glutamate iontophoresis or uncaging onto presynaptic boutons does not cause a Ca2+ influx [13, 14]. We reconfirmed these findings by iontophoresis of glutamate (100 mM) onto dendrites and boutons of L4 spiny stellate neurons (Figure 3). We observed clear increases in Ca2+ in dendritic spines, but in contrast, we could not detect any Ca2+ elevations in the axonal compartment (n=5 cells). Furthermore, single AP-evoked presynaptic Ca2+ signals alone were not influenced by blocking NMDA receptors. Bath-application of APV did not change the peak amplitude of the Ca2+ transients (ΔF/FBaseline=0.013±0.003, ΔF/FAPV=0.015±0.003, n=6, p=0.22 by Student’s paired t-test), nor its decay (τBaseline=0.68±0.12s, τAPV=0.77±0.08s, n=6, p=0.55 by Student’s paired t-test; Figure 4). Thus, preNMDARs caused no direct Ca2+ influx into boutons, and they also did not contribute to the normal AP-evoked presynaptic Ca2+ dynamics in the absence of 2-AG.Figure 2
Presynaptic Ca2+ imaging in L4 spiny stellate axons. (a) Two-photon fluorescence image of a spiny stellate neuron in L4 of the somatosensory cortex loaded with OGB-1 and Alexa-594. (b) Imaged axon segment in L2/3 indicated in (a) by the dashed box. (c) Consecutive fluorescence traces of 1 min duration repeated every 5 min before, during (shaded area) and after bath application of 2-AG. An arrowhead indicates the time point of a somatically evoked AP. (d) Spontaneous axonal Ca2+ transient marked by a cross in (c) on an expanded scale. The Ca2+ transient was unrelated to somatic activity. (e) AP-evoked Ca2+ transient in the presence of 2-AG marked by an asterisk in (c) on an expanded scale (black) compared to an AP-evoked Ca2+ transient during baseline (grey). Dashed lines present single exponential fits to the decay of the Ca2+ transients.
(a)(b)(c)(d)(e)Figure 3
Iontophoresis of glutamate does not evoke Ca2+ signals in boutons. (a) Two-photon fluorescence image of a dendrite of a spiny stellate neuron loaded with the Ca2+ indicator OGB-1 (200 μM) and the morphological dye Alexa 594 (50 μM). The position of the iontophoresis pipette for glutamate application is indicated. To the right, three fluorescence images taken before, 1 s after and 5 s after glutamate application, are shown. Below, the time-course of the fluorescence change in the region of interest indicated by the red, dashed circle (upper trace) and the somatic membrane potential (lower trace) are presented. Grey bar represents time of glutamate application. (b) Left, line-scan through a spine of another cell and the corresponding Ca2+ transient evoked by a burst of 5 APs at 50 Hz. Right, line-scan through the same spine during iontophoresis of glutamate. A clear increase in Ca2+ can be seen upon iontophoresis. (c) Two-photon fluorescence image of an axon of a spiny stellate neuron located in L2/3 loaded with the Ca2+ indicator OGB-1 (200 μM) and the morphological dye Alexa 594 (50 μM). The position of the iontophoresis pipette for glutamate application is indicated. To the right, three fluorescence images taken before, 1 s after and 3 s after glutamate application, are shown. Below, the time-course of the fluorescence change in the region of interest indicated by the red, dashed circle (upper trace) and the somatic membrane potential (lower trace) is presented. Grey bar represents time of glutamate application. No increase in Ca2+ is apparent upon iontophoresis of glutamate onto the axon. (d) Left, line-scan through a bouton of another cell and the corresponding Ca2+ transient evoked by a burst of 5 APs at 50 Hz. Right, line-scan through the same bouton during iontophoresis of glutamate. An increase in Ca2+ is evoked by the APs, but not by iontophoresis of glutamate.
(a)(b)(c)(d)Figure 4
APV has no influence on presynaptic AP-evoked Ca2+ transients. (a) Axonal Ca2+ transients evoked by a single AP in a spiny stellate axon recorded in L2/3 during baseline (black) and in the presence of the NMDAR blocker APV (purple). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. Lower trace represents the difference between the baseline and APV Ca2+ transients. Dashed line indicates zero and light shaded area indicates the baseline noise level (±SD). (b) Bar graph summary of the peak Ca2+ transient amplitudes (left) and decay time constants (right) for baseline and in the presence of APV. All data are represented as mean±SEM.
(a)(b)Therefore, in order to investigate the phenomenon of the specific 2-AG induced broadening of the AP-evoked Ca2+ signals in more detail, we measured single AP-evoked Ca2+ transients elicited at 0.1 Hz, corresponding to the stimulation frequency used for the LTD experiments (instead of stimulating at 0.003 Hz as in the previous imaging experiments) in spiny stellate axons before and during bath application of 2-AG (Figures 5(a) and 5(b)). We normalized and averaged the corresponding Ca2+ transients for comparison. We confirmed that 2-AG broadened the AP-evoked Ca2+ transients (Figure 5(b)). In contrast, in the presence of APV, 2-AG had no effect on the presynaptic Ca2+ signal (Figure 5(b)). Fitting a single exponential to the decay of the AP-evoked Ca2+ transients revealed a significantly slower decay in the presence of 2-AG as compared to the effect of 2-AG in the presence of APV (2-AG: normalized τ2−AG=1.23±0.07, n=15, p<0.01 for the effect of time on τ by paired Student’s t-test; 2-AG + APV: normalized τ2−AG=1.02±0.02, n=11, p=0.26 for the effect of time on τ by paired Student’s t-test; 2-AG control vs. 2-AG + APV, p<0.05 by one-way ANOVA; Figure 5(c)). The distribution of the normalized decay time constants revealed that 2-AG broadened the AP-evoked Ca2+ transients in 53% of the axons investigated (8 out of 15 axons; average change 1.40±0.08), while having no effect on the rest (7 out of 15; average change 1.03±0.01; Figure 5(d)). This observation suggests that not all axons and boutons were influenced by astrocyte activation, arguing for a compartmentalized astrocytic innervation and/or for synapse-specific expression of preNMDARs. The CB1 receptor antagonist AM251 (5 μM) abolished the effect of bath-application of 2-AG on the AP-evoked Ca2+ transients (AM251: normalized τ2−AG=0.97±0.04, n=5, p=0.40 for the effect of time on τ by paired Student’s t-test), excluding a nonspecific effect of 2-AG. Furthermore, repeating the experiment without any drug application had no effect on the AP-evoked Ca2+ transients (no drugs: normalized τ=1.02±0.06, n=4, p=0.51 for the effect of time on τ by paired Student’s t-test) demonstrating long-term stability of the experimental design and ruling out any time-dependent changes in axonal Ca2+ buffering due to the Ca2+ indicator.Figure 5
2-AG broadens AP-evoked Ca2+ transients in L4 axons. (a) Neurolucida reconstruction of a spiny stellate neuron. Dendrites are represented in blue and the axonal arborization in black. Inset, two-photon fluorescence image of the axon segment imaged in L2/3 indicated by the dashed box. (b) Left, averaged and normalized AP-evoked Ca2+ transients during baseline (grey) and after bath application of 2-AG (black). Upper trace represents the difference between the baseline and 2-AG Ca2+ transients. Dashed line indicates zero, and light-shaded area indicates the baseline noise level (±SD). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. There is an apparent difference between the two transients. Inset shows somatic APs before and after bath application of 2-AG. Right, experiment in which the NMDAR-blocker APV was present in the bath. No difference between the two transients was observed in this condition. (c) Normalized decay time constant in the presence of 2-AG for different conditions. 2-AG significantly broadened the Ca2+ transients (n=15). ##p<0.01 for the effect of time on τ by paired Student’s t-test. In contrast, no broadening was observed in the presence of APV (n=11), AM251 (n=5), or in control conditions without application of any drug (Ctrl, n=4). APV had a significant effect on τ in the presence of 2-AG. ∗p<0.05 by one-way ANOVA. All data are represented as mean±SEM. (d) Distribution of normalized decay time constants in the presence of 2-AG. Solid black lines represent Gaussian fits to the subsets that showed either no (light grey) or significant (dark grey) broadening of the Ca2+ transients.
(a)(b)(c)(d)2-AG evoked release of glutamate might activate dendritic NMDARs on the recorded neuron, which could potentially influence somatic membrane potential, AP generation, and somatic AP properties. Previously, such somato-dendritic NMDAR activation was shown to influence presynaptic Ca2+ signaling in cerebellar stellate cells [12]. However, when we analyzed the somatic resting membrane potential, AP amplitude, and AP width at the soma of the imaged spiny stellate neurons, we found no influence of 2-AG on either somatic parameter (Figure 6). Therefore, we can rule out an effect of somato-dendritic NMDARs on the presynaptic Ca2+ dynamics. Thus, our experiments revealed an APV-sensitive presynaptic Ca2+ component that manifested itself in a broadening of AP-evoked Ca2+ transients.Figure 6
AP properties are unaffected by 2-AG. (a) Neurolucida reconstruction of a spiny stellate neuron. Dendrites are represented in blue and the axonal arborization in black. (b) Upper traces, averaged and normalized AP-evoked Ca2+ transients during baseline (grey) and after bath application of 2-AG (black). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. Lower traces, corresponding somatic APs before (grey) and after (black) bath application of 2-AG. (c) Average bar graphs of resting membrane potential, AP amplitude, and AP width before and after bath application of 2-AG (n=12). None of the parameters changed significantly (p>0.1 by paired Student’s t-test). All data are represented as mean±SEM.
(a)(b)(c)Recently, it was shown that specific patterns of presynaptic activity alone, consisting of a burst of APs at 100 Hz or above, followed by a single AP between 50 and 200 ms later, can induce LTD. This form of LTD requires the activation of preNMDARs, but does not depend on astrocyte activation [10]. We tested whether this activity pattern also resulted in an APV-sensitive broadening of the presynaptic Ca2+ signal. A burst of APs at 100 Hz followed by a single AP 50 ms later evoked an axonal Ca2+ transient that was more rapidly decaying after wash-in of APV (Figure 7(a)). The difference between the Ca2+ transients under baseline conditions and in the presence of APV revealed an APV-sensitive Ca2+ component for this presynaptic stimulation pattern (peak difference baseline to APV: 0.04±0.02, n=6, p<0.05 by paired Student’s t-test; Figures 7(b) and 7(c)). Ca2+ transients evoked by 3 APs at 100 Hz alone showed no APV-sensitive Ca2+ component (−0.01±0.02, n=6, p=0.56 by paired Student’s t-test). Thus, the additional AP that followed 50 ms after the burst of 3 APs leads to a significant (p<0.05 by one-way ANOVA) additional presynaptic Ca2+ influx that was abolished by APV. The requirement of the presence of this delayed 4th AP suggests an interaction of the preNMDARs with a voltage-dependent mechanism initiated by the additional AP.Figure 7
Presynaptic burst patterns evoke an APV-sensitive Ca2+ transient component. (a) Example of the AP burst patterns that were used to evoke presynaptic Ca2+ transients in L4 spiny stellate axons. Left, 3 APs at 100 Hz. Right, 3 APs at 100 Hz followed 50 ms later by a single AP. (b) Axonal Ca2+ transients evoked by the activity patterns shown in (a) during baseline (black) and after bath application of APV (purple). Lower traces show the difference between the corresponding transients. (c) Comparison of the peak difference between the Ca2+ transients before and after bath application of APV (n=6). The 3AP+1AP activity pattern showed a significant effect of APV on the evoked Ca2+ transients, while the Ca2+ transients evoked by a burst of 3 APs alone were unaffected by APV. #p<0.05 by paired Student’s t-test. ∗p<0.05 by one-way ANOVA. All data are represented as mean±SEM.
(a)(b)(c)In summary, our experiments suggest that the activation of preNMDARs causes a slowing of the decay of AP-evoked Ca2+ transients, which results in an additional axonal Ca2+ influx that is intrinsically linked to the presence of the presynaptic AP. The source of the glutamate that activates the preNMDARs can either originate from 2-AG activated astrocytes or from glutamate spillover by a specifically timed presynaptic burst of APs.
### 3.3. preNMDARs Interact with Voltage-Dependent Ca2+ Channels
The broadening of the AP-evoked presynaptic Ca2+ transient could directly be due to the preNMDARs, which could contribute to Ca2+ influx during the AP-evoked axonal membrane depolarization and the subsequent relief of the Mg2+ block. In this scenario, preNMDARs would function as classical coincidence detectors, similar to what has been suggested for postsynaptic NMDARs. However, it has been shown that preNMDARs during early development might contain the GluN3A subunit, which renders them largely insensitive to Mg2+ block and with low permeability for Ca2+ [18]. An alternative function of the preNMDARs might be to contribute to the axonal membrane depolarization by Na+ influx or to exert a metabotropic effect during their activation. Both mechanisms could activate voltage-dependent Ca2+ channels (VDCCs) beyond the membrane depolarization caused by the axonal AP and contribute to an additional Ca2+ influx. To distinguish between a direct Ca2+ influx through preNMDARs and an interaction with VDCCs, we performed axonal Ca2+ imaging as described above and blocked VDCCs (Figure 8). Somatic APs evoked a consistent axonal Ca2+ transient which was abolished in the presence of the VDCC-blockers Cd2+ (100 μM) and Ni+ (50 μM) even though the somatic AP waveform was unchanged (ΔF/FBaseline=0.047±0.004, ΔF/FCd,Ni=0.008±0.001, n=4, p<0.01 by Student’s paired t-test with Bonferroni correction for multiple comparisons). Subsequent continuation of somatic AP stimulation during bath application of 2-AG, but still in the presence of Cd2+/Ni+ did not uncover an AP-evoked Ca2+ transient through preNMDARs (ΔF/F2−AG=0.002±0.001, p=0.32 by Student’s paired t-test with Bonferroni correction for multiple comparisons). This observation suggests that axonal membrane depolarization is not required for unblocking preNMDARs from a putative Mg2+ block to render them permeable for Ca2+. Contrary, we conclude that functional VDCCs are required so that preNMDARs can interact with them to prolong the axonal Ca2+ influx.Figure 8
Block of VDCCs does not uncover preNMDAR-dependent Ca2+ transients. (a) Axonal Ca2+ transients evoked by a single AP in a spiny stellate axon recorded in L2/3 during baseline (black) and in the presence of the VDCC blockers Cd2+ and Ni+ (blue). Subsequent bath application of 2-AG did not result in an AP-evoked Ca2+ transient (green). Shaded areas represent ±SEM and dashed lines ±SD of the basal fluorescence before stimulation. (b) Bar graph summary of the peak Ca2+ transient amplitudes in the different conditions (n=4). ∗∗p<0.01 by Student’s paired t-test with Bonferroni correction for multiple comparisons. All data are represented as mean±SEM.
(a)(b)
## 3.1. Endocannabinoid-Dependent LTD Requires Activation of Astrocytes and preNMDARs
t-LTD at L4-L2/3 excitatory synapses in rat barrel cortex depends on the activation of astrocytes by 2-AG that is synthetized postsynaptically. This synthesis occurs at synapses which are activated within a time window of about 50 ms after the generation of a postsynaptic AP. Astrocyte activation results in the release of glutamate onto preNMDARs which interact with presynaptic APs to trigger a reduction in release probability [8]. To further understand the presynaptic signaling cascade leading to t-LTD, Ca2+ imaging from presynaptic boutons during t-LTD induction would be the best approach. However, this is technically challenging, since it requires imaging from the presynaptic bouton of an identified synaptic connection while at the same time controlling AP firing in the pre- and postsynaptic neuron. As an alternative approach, we tested if direct bath-application of 2-AG resulted in synaptic depression without postsynaptic activity at L4-L2/3 synapses, similar to what was previously described for L5-L5 synapses [4]. We performed whole-cell patch-clamp recordings from L2/3 pyramidal neurons in the somatosensory cortex of juvenile rats and activated L4 spiny stellate neuron axons by extracellular stimulation in L4. After recording a baseline of EPSPs for 10 min, we bath-applied 2-AG (10 μM) for 20 min while continuing presynaptic stimulation at 0.1 Hz. We observed a long-lasting depression of the EPSPs 10–30 min after the washout of 2-AG (0.58±0.09, n=13, p<0.01 for the effect of time on EPSP slope by Student’s paired t-test; Figure 1(a)). This form of LTD was presynaptic as the reduction in normalized EPSP amplitude correlated with a reduction in the normalized coefficient of variation (Figure 1(b)).Figure 1
2-AG mediated LTD requires astrocyte Ca2+ signaling and preNMDARs. (a) Time course of normalized and averaged EPSP slope measured in L2/3 pyramidal neurons before, during (0–20 min, shaded area) and after bath application of 2-AG (n=13). Inset, representative average EPSP during baseline (black) and after 2-AG (grey). (b) Relative change of coefficient of variation of EPSP slope after bath application of 2-AG as a function of corresponding changes in EPSP slope. The relation is almost linear, indicating a presynaptic locus of eCB-LTD expression. Open circles represent individual experiments, and filled circle represents the average (n=13). (c) Two-photon fluorescence image of an astrocyte in L2/3 of the somatosensory cortex loaded with the Ca2+ indicator Rhod-2. Traces to the right show Ca2+ fluctuations in the astrocyte before, during, and after bath application of 2-AG (shaded area). (d) Summary of the average number of Ca2+ transients during the time course of the experiment (n=12). ∗p<0.05 for the effect of time on Ca2+ transient number by Student’s paired t-test. (e) Normalized and averaged EPSP slope over time in L2/3 pyramidal neurons, while an adjacent astrocyte was infused in the whole-cell recording configuration with either a control (Ctrl, n=8) and or Ca2+ clamp solution (n=9). Inset, representative average EPSP during baseline (black) and after 2-AG in control (light green) or Ca2+ clamp (dark green) conditions. (f) Normalized and averaged EPSP slope over time during bath application of APV (n=13) or intracellular infusion of MK801 (n=24) into the pyramidal neuron (iMK801). Inset, representative average EPSP during baseline (black) and after 2-AG in the presence of APV (purple) or iMK801 (blue). (g) Normalized and averaged EPSP slope in the presence of the calcineurin inhibitors FK506 and cyclosporin-A (n=2). Inset, representative average EPSP during baseline (black) and after 2-AG (orange). (h) Bar graph summary of experiments shown in (e) and (f). In the astrocyte Ca2+ clamp condition, eCB-LTD was abolished. APV blocked eCB-LTD, while intracellular block of postsynaptic NMDARs with MK801 had no effect. #p<0.05 by one-way ANOVA. All data are represented as mean±SEM. All scale bars for average EPSPs represent 40 ms and 2 mV, respectively.
(a)(b)(c)(d)(e)(f)(g)(h)Next, we confirmed that 2-AG activated cortical astrocytes in L2/3. Bulk-loading of astrocytes with Rhod2-AM, which is preferentially taken up by astrocytes, allowed to measure the intracellular Ca2+ dynamics during bath-application of 2-AG (Figure 1(c)). We observed a significant increase in the number of Ca2+ transients by 2-AG (from 0.75±0.26min−1 to 1.08±0.20min−1, n=12, p<0.05 for the effect of time on Ca2+ transient number by Student’s paired t-test) that decayed back to baseline levels after wash-out (Figure 1(d)). This experiment confirmed previous results showing that eCBs modulate astrocytic Ca2+ dynamics [8, 26]. Infusing an astrocyte with a solution that clamped the intracellular Ca2+ concentration to a constant level abolished eCB-LTD in adjacent pyramidal neurons (1.00±0.10, n=9, p=0.87 for the effect of time on EPSP slope by Student’s paired t-test), while infusing a control intracellular solution into the astrocytes resulted in eCB-LTD (0.74±0.06, n=8, p<0.05 for the effect of time on EPSP slope by Student’s paired t-test; comparison control vs. Ca2+ clamp, p<0.05 by one-way ANOVA; Figures 1(e) and 1(h)). Thus, similar to t-LTD, the increase in Ca2+ signaling in the astrocytes was required for the induction of eCB-LTD.Then, we tested the involvement of NMDARs in eCB-LTD. Bath-application of APV blocked the 2-AG mediated LTD (0.90±0.05, n=13, p=0.06 for the effect of time on EPSP slope by Student’s paired t-test), while infusion of MK801 into the postsynaptic cell had no effect on eCB-LTD (0.70±0.05, n=24, p<0.001 for the effect of time on EPSP slope by Student’s paired t-test; comparison APV vs. MK801, p<0.05 by one-way ANOVA; Figures 1(f) and 1(h)). These results suggested that downstream of astrocyte signaling, eCB-LTD required the activation of presynaptic NMDARs.PreNMDAR-dependent LTD at cortical synapses [10] and eCB-mediated LTD at both excitatory and inhibitory synapses in the hippocampus [27, 28] require the activation of the Ca2+ dependent protein phosphatase calcineurin [29]. In order to test a similar involvement in our case, we blocked calcineurin activity by incubating the brain slices in FK506 (50 μM) and cyclosporin-A (25 μM) at least for 1 h before the start of the experiment and with 20 μM and 10 μM, respectively, during the experiment. EPSPs were evoked by extracellular stimulation in L4, and 2-AG was washed-in for 20 min as described above. In the condition of blocked calcineurin activity, no eCB-LTD was induced (0.95±0.01, n=2, Figure 1(g)). These results indicate that calcineurin is involved in the induction of eCB-LTD.In summary, our experiments show that eCB-LTD and t-LTD share a similar induction mechanism, since both are dependent on astrocyte activation by eCBs and on activation of preNMDARs. The involvement of calcineurin suggests that an elevation in presynaptic Ca2+ is essential for these forms of LTD.
## 3.2. Presynaptic NMDARs Broaden AP-Evoked Ca2+ Transients in L4 Spiny Stellate Axons
We sought to investigate the functional consequence of preNMDAR activation and thus the potential source of Ca2+ required for LTD in L4 spiny stellate axons while they were activated by glutamate release from 2-AG activated astrocytes. We loaded L4 spiny stellate neurons with the Ca2+ indicator Oregon Green Bapta-1 (OGB-1, 200 μM) and the morphological dye Alexa-594 (50 μM) to trace the axon to L2/3 (Figures 2(a) and 2(b)). Frame scans of 1 min duration (3 Hz) from a stretch of axon were performed to measure the local Ca2+ signals before and during bath application of 2-AG. A single somatically evoked AP resulted in a stereotyped Ca2+ transient in the axonal compartment. Bath application of 2-AG did not cause a significant number of spontaneous, local Ca2+ transients in the axon as might have been hypothesized from an activation of preNMDARs (Figures 2(c) and 2(d)). We found a total of 12 spontaneous Ca2+ transients in 60 min of observation time (n=9 cells) in the presence of 2-AG. This number was not different from spontaneous events before 2-AG application (8 events in 40 min). However, comparing the time course of the presynaptic AP-evoked Ca2+ transients before and after 2-AG application revealed a prolongation of the AP-evoked Ca2+ signal in the presence of 2-AG (Figure 2(e)). We concluded from this experiment that glutamate release from astrocytes does not activate preNMDARs in a similar manner as axonal glutamate release activates postsynaptic NMDARs, which results in clear and distinct Ca2+ transients in postsynaptic spines [30]. This result is consistent with observations that glutamate iontophoresis or uncaging onto presynaptic boutons does not cause a Ca2+ influx [13, 14]. We reconfirmed these findings by iontophoresis of glutamate (100 mM) onto dendrites and boutons of L4 spiny stellate neurons (Figure 3). We observed clear increases in Ca2+ in dendritic spines, but in contrast, we could not detect any Ca2+ elevations in the axonal compartment (n=5 cells). Furthermore, single AP-evoked presynaptic Ca2+ signals alone were not influenced by blocking NMDA receptors. Bath-application of APV did not change the peak amplitude of the Ca2+ transients (ΔF/FBaseline=0.013±0.003, ΔF/FAPV=0.015±0.003, n=6, p=0.22 by Student’s paired t-test), nor its decay (τBaseline=0.68±0.12s, τAPV=0.77±0.08s, n=6, p=0.55 by Student’s paired t-test; Figure 4). Thus, preNMDARs caused no direct Ca2+ influx into boutons, and they also did not contribute to the normal AP-evoked presynaptic Ca2+ dynamics in the absence of 2-AG.Figure 2
Presynaptic Ca2+ imaging in L4 spiny stellate axons. (a) Two-photon fluorescence image of a spiny stellate neuron in L4 of the somatosensory cortex loaded with OGB-1 and Alexa-594. (b) Imaged axon segment in L2/3 indicated in (a) by the dashed box. (c) Consecutive fluorescence traces of 1 min duration repeated every 5 min before, during (shaded area) and after bath application of 2-AG. An arrowhead indicates the time point of a somatically evoked AP. (d) Spontaneous axonal Ca2+ transient marked by a cross in (c) on an expanded scale. The Ca2+ transient was unrelated to somatic activity. (e) AP-evoked Ca2+ transient in the presence of 2-AG marked by an asterisk in (c) on an expanded scale (black) compared to an AP-evoked Ca2+ transient during baseline (grey). Dashed lines present single exponential fits to the decay of the Ca2+ transients.
(a)(b)(c)(d)(e)Figure 3
Iontophoresis of glutamate does not evoke Ca2+ signals in boutons. (a) Two-photon fluorescence image of a dendrite of a spiny stellate neuron loaded with the Ca2+ indicator OGB-1 (200 μM) and the morphological dye Alexa 594 (50 μM). The position of the iontophoresis pipette for glutamate application is indicated. To the right, three fluorescence images taken before, 1 s after and 5 s after glutamate application, are shown. Below, the time-course of the fluorescence change in the region of interest indicated by the red, dashed circle (upper trace) and the somatic membrane potential (lower trace) are presented. Grey bar represents time of glutamate application. (b) Left, line-scan through a spine of another cell and the corresponding Ca2+ transient evoked by a burst of 5 APs at 50 Hz. Right, line-scan through the same spine during iontophoresis of glutamate. A clear increase in Ca2+ can be seen upon iontophoresis. (c) Two-photon fluorescence image of an axon of a spiny stellate neuron located in L2/3 loaded with the Ca2+ indicator OGB-1 (200 μM) and the morphological dye Alexa 594 (50 μM). The position of the iontophoresis pipette for glutamate application is indicated. To the right, three fluorescence images taken before, 1 s after and 3 s after glutamate application, are shown. Below, the time-course of the fluorescence change in the region of interest indicated by the red, dashed circle (upper trace) and the somatic membrane potential (lower trace) is presented. Grey bar represents time of glutamate application. No increase in Ca2+ is apparent upon iontophoresis of glutamate onto the axon. (d) Left, line-scan through a bouton of another cell and the corresponding Ca2+ transient evoked by a burst of 5 APs at 50 Hz. Right, line-scan through the same bouton during iontophoresis of glutamate. An increase in Ca2+ is evoked by the APs, but not by iontophoresis of glutamate.
(a)(b)(c)(d)Figure 4
APV has no influence on presynaptic AP-evoked Ca2+ transients. (a) Axonal Ca2+ transients evoked by a single AP in a spiny stellate axon recorded in L2/3 during baseline (black) and in the presence of the NMDAR blocker APV (purple). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. Lower trace represents the difference between the baseline and APV Ca2+ transients. Dashed line indicates zero and light shaded area indicates the baseline noise level (±SD). (b) Bar graph summary of the peak Ca2+ transient amplitudes (left) and decay time constants (right) for baseline and in the presence of APV. All data are represented as mean±SEM.
(a)(b)Therefore, in order to investigate the phenomenon of the specific 2-AG induced broadening of the AP-evoked Ca2+ signals in more detail, we measured single AP-evoked Ca2+ transients elicited at 0.1 Hz, corresponding to the stimulation frequency used for the LTD experiments (instead of stimulating at 0.003 Hz as in the previous imaging experiments) in spiny stellate axons before and during bath application of 2-AG (Figures 5(a) and 5(b)). We normalized and averaged the corresponding Ca2+ transients for comparison. We confirmed that 2-AG broadened the AP-evoked Ca2+ transients (Figure 5(b)). In contrast, in the presence of APV, 2-AG had no effect on the presynaptic Ca2+ signal (Figure 5(b)). Fitting a single exponential to the decay of the AP-evoked Ca2+ transients revealed a significantly slower decay in the presence of 2-AG as compared to the effect of 2-AG in the presence of APV (2-AG: normalized τ2−AG=1.23±0.07, n=15, p<0.01 for the effect of time on τ by paired Student’s t-test; 2-AG + APV: normalized τ2−AG=1.02±0.02, n=11, p=0.26 for the effect of time on τ by paired Student’s t-test; 2-AG control vs. 2-AG + APV, p<0.05 by one-way ANOVA; Figure 5(c)). The distribution of the normalized decay time constants revealed that 2-AG broadened the AP-evoked Ca2+ transients in 53% of the axons investigated (8 out of 15 axons; average change 1.40±0.08), while having no effect on the rest (7 out of 15; average change 1.03±0.01; Figure 5(d)). This observation suggests that not all axons and boutons were influenced by astrocyte activation, arguing for a compartmentalized astrocytic innervation and/or for synapse-specific expression of preNMDARs. The CB1 receptor antagonist AM251 (5 μM) abolished the effect of bath-application of 2-AG on the AP-evoked Ca2+ transients (AM251: normalized τ2−AG=0.97±0.04, n=5, p=0.40 for the effect of time on τ by paired Student’s t-test), excluding a nonspecific effect of 2-AG. Furthermore, repeating the experiment without any drug application had no effect on the AP-evoked Ca2+ transients (no drugs: normalized τ=1.02±0.06, n=4, p=0.51 for the effect of time on τ by paired Student’s t-test) demonstrating long-term stability of the experimental design and ruling out any time-dependent changes in axonal Ca2+ buffering due to the Ca2+ indicator.Figure 5
2-AG broadens AP-evoked Ca2+ transients in L4 axons. (a) Neurolucida reconstruction of a spiny stellate neuron. Dendrites are represented in blue and the axonal arborization in black. Inset, two-photon fluorescence image of the axon segment imaged in L2/3 indicated by the dashed box. (b) Left, averaged and normalized AP-evoked Ca2+ transients during baseline (grey) and after bath application of 2-AG (black). Upper trace represents the difference between the baseline and 2-AG Ca2+ transients. Dashed line indicates zero, and light-shaded area indicates the baseline noise level (±SD). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. There is an apparent difference between the two transients. Inset shows somatic APs before and after bath application of 2-AG. Right, experiment in which the NMDAR-blocker APV was present in the bath. No difference between the two transients was observed in this condition. (c) Normalized decay time constant in the presence of 2-AG for different conditions. 2-AG significantly broadened the Ca2+ transients (n=15). ##p<0.01 for the effect of time on τ by paired Student’s t-test. In contrast, no broadening was observed in the presence of APV (n=11), AM251 (n=5), or in control conditions without application of any drug (Ctrl, n=4). APV had a significant effect on τ in the presence of 2-AG. ∗p<0.05 by one-way ANOVA. All data are represented as mean±SEM. (d) Distribution of normalized decay time constants in the presence of 2-AG. Solid black lines represent Gaussian fits to the subsets that showed either no (light grey) or significant (dark grey) broadening of the Ca2+ transients.
(a)(b)(c)(d)2-AG evoked release of glutamate might activate dendritic NMDARs on the recorded neuron, which could potentially influence somatic membrane potential, AP generation, and somatic AP properties. Previously, such somato-dendritic NMDAR activation was shown to influence presynaptic Ca2+ signaling in cerebellar stellate cells [12]. However, when we analyzed the somatic resting membrane potential, AP amplitude, and AP width at the soma of the imaged spiny stellate neurons, we found no influence of 2-AG on either somatic parameter (Figure 6). Therefore, we can rule out an effect of somato-dendritic NMDARs on the presynaptic Ca2+ dynamics. Thus, our experiments revealed an APV-sensitive presynaptic Ca2+ component that manifested itself in a broadening of AP-evoked Ca2+ transients.Figure 6
AP properties are unaffected by 2-AG. (a) Neurolucida reconstruction of a spiny stellate neuron. Dendrites are represented in blue and the axonal arborization in black. (b) Upper traces, averaged and normalized AP-evoked Ca2+ transients during baseline (grey) and after bath application of 2-AG (black). Dashed lines represent single exponential fits to the decay of the Ca2+ transients. Lower traces, corresponding somatic APs before (grey) and after (black) bath application of 2-AG. (c) Average bar graphs of resting membrane potential, AP amplitude, and AP width before and after bath application of 2-AG (n=12). None of the parameters changed significantly (p>0.1 by paired Student’s t-test). All data are represented as mean±SEM.
(a)(b)(c)Recently, it was shown that specific patterns of presynaptic activity alone, consisting of a burst of APs at 100 Hz or above, followed by a single AP between 50 and 200 ms later, can induce LTD. This form of LTD requires the activation of preNMDARs, but does not depend on astrocyte activation [10]. We tested whether this activity pattern also resulted in an APV-sensitive broadening of the presynaptic Ca2+ signal. A burst of APs at 100 Hz followed by a single AP 50 ms later evoked an axonal Ca2+ transient that was more rapidly decaying after wash-in of APV (Figure 7(a)). The difference between the Ca2+ transients under baseline conditions and in the presence of APV revealed an APV-sensitive Ca2+ component for this presynaptic stimulation pattern (peak difference baseline to APV: 0.04±0.02, n=6, p<0.05 by paired Student’s t-test; Figures 7(b) and 7(c)). Ca2+ transients evoked by 3 APs at 100 Hz alone showed no APV-sensitive Ca2+ component (−0.01±0.02, n=6, p=0.56 by paired Student’s t-test). Thus, the additional AP that followed 50 ms after the burst of 3 APs leads to a significant (p<0.05 by one-way ANOVA) additional presynaptic Ca2+ influx that was abolished by APV. The requirement of the presence of this delayed 4th AP suggests an interaction of the preNMDARs with a voltage-dependent mechanism initiated by the additional AP.Figure 7
Presynaptic burst patterns evoke an APV-sensitive Ca2+ transient component. (a) Example of the AP burst patterns that were used to evoke presynaptic Ca2+ transients in L4 spiny stellate axons. Left, 3 APs at 100 Hz. Right, 3 APs at 100 Hz followed 50 ms later by a single AP. (b) Axonal Ca2+ transients evoked by the activity patterns shown in (a) during baseline (black) and after bath application of APV (purple). Lower traces show the difference between the corresponding transients. (c) Comparison of the peak difference between the Ca2+ transients before and after bath application of APV (n=6). The 3AP+1AP activity pattern showed a significant effect of APV on the evoked Ca2+ transients, while the Ca2+ transients evoked by a burst of 3 APs alone were unaffected by APV. #p<0.05 by paired Student’s t-test. ∗p<0.05 by one-way ANOVA. All data are represented as mean±SEM.
(a)(b)(c)In summary, our experiments suggest that the activation of preNMDARs causes a slowing of the decay of AP-evoked Ca2+ transients, which results in an additional axonal Ca2+ influx that is intrinsically linked to the presence of the presynaptic AP. The source of the glutamate that activates the preNMDARs can either originate from 2-AG activated astrocytes or from glutamate spillover by a specifically timed presynaptic burst of APs.
## 3.3. preNMDARs Interact with Voltage-Dependent Ca2+ Channels
The broadening of the AP-evoked presynaptic Ca2+ transient could directly be due to the preNMDARs, which could contribute to Ca2+ influx during the AP-evoked axonal membrane depolarization and the subsequent relief of the Mg2+ block. In this scenario, preNMDARs would function as classical coincidence detectors, similar to what has been suggested for postsynaptic NMDARs. However, it has been shown that preNMDARs during early development might contain the GluN3A subunit, which renders them largely insensitive to Mg2+ block and with low permeability for Ca2+ [18]. An alternative function of the preNMDARs might be to contribute to the axonal membrane depolarization by Na+ influx or to exert a metabotropic effect during their activation. Both mechanisms could activate voltage-dependent Ca2+ channels (VDCCs) beyond the membrane depolarization caused by the axonal AP and contribute to an additional Ca2+ influx. To distinguish between a direct Ca2+ influx through preNMDARs and an interaction with VDCCs, we performed axonal Ca2+ imaging as described above and blocked VDCCs (Figure 8). Somatic APs evoked a consistent axonal Ca2+ transient which was abolished in the presence of the VDCC-blockers Cd2+ (100 μM) and Ni+ (50 μM) even though the somatic AP waveform was unchanged (ΔF/FBaseline=0.047±0.004, ΔF/FCd,Ni=0.008±0.001, n=4, p<0.01 by Student’s paired t-test with Bonferroni correction for multiple comparisons). Subsequent continuation of somatic AP stimulation during bath application of 2-AG, but still in the presence of Cd2+/Ni+ did not uncover an AP-evoked Ca2+ transient through preNMDARs (ΔF/F2−AG=0.002±0.001, p=0.32 by Student’s paired t-test with Bonferroni correction for multiple comparisons). This observation suggests that axonal membrane depolarization is not required for unblocking preNMDARs from a putative Mg2+ block to render them permeable for Ca2+. Contrary, we conclude that functional VDCCs are required so that preNMDARs can interact with them to prolong the axonal Ca2+ influx.Figure 8
Block of VDCCs does not uncover preNMDAR-dependent Ca2+ transients. (a) Axonal Ca2+ transients evoked by a single AP in a spiny stellate axon recorded in L2/3 during baseline (black) and in the presence of the VDCC blockers Cd2+ and Ni+ (blue). Subsequent bath application of 2-AG did not result in an AP-evoked Ca2+ transient (green). Shaded areas represent ±SEM and dashed lines ±SD of the basal fluorescence before stimulation. (b) Bar graph summary of the peak Ca2+ transient amplitudes in the different conditions (n=4). ∗∗p<0.01 by Student’s paired t-test with Bonferroni correction for multiple comparisons. All data are represented as mean±SEM.
(a)(b)
## 4. Discussion
NMDARs are essential ionotropic glutamate receptors for synaptic transmission, information processing, and synaptic plasticity. While classically thought to be located mainly postsynaptically, there is growing anatomical and physiological evidence that NMDARs also have important functions at presynaptic sites [2, 31–38]. We investigated the function of preNMDARs in juvenile L4-to-L2/3 glutamatergic connections in the somatosensory cortex. First, we showed that activation of astrocytes with the endocannabinoid 2-AG resulted in a form of presynaptic LTD (eCB-LTD) that depended on astrocyte Ca2+ signaling and the activation of preNMDARs, thereby showing an overlapping mechanism of induction with t-LTD [8]. Recording presynaptic Ca2+ dynamics during the induction of eCB-LTD allowed us to investigate the functional consequences of preNMDAR activation. In line with other studies, we found no evidence for a direct Ca2+ influx through preNMDARs during eCB-LTD induction or glutamate iontophoresis [13, 14]. Instead, our results suggest that the activation of preNMDARs leads to a prolonged activity of VDCCs resulting in an additional AP-evoked Ca2+ influx through these channels. Thus, we conclude that the action of preNMDARs has an indirect influence on presynaptic Ca2+ transients by interacting with VDCCs. These findings can reconcile some of the controversial results regarding preNMDARs and are consistent with the electrophysiological evidence for their influence in t-LTD.
### 4.1. Signaling Cascade for the Induction of t-LTD at Developing Cortical Synapses
The chemically induced eCB-LTD presented here shares the same signaling cascade as found in t-LTD. In t-LTD, the eCB 2-AG is synthetized by postsynaptic AP firing followed by presynaptic glutamate release. The postsynaptic backpropagating AP evokes an increase in postsynaptic Ca2+ through VDCCs, which is thought to prime phospholipase C (PLC), which is subsequently activated by the presynaptic release of glutamate binding to the metabotropic glutamate receptor type 5 (mGluR5) [6, 7]. In eCB-LTD, this postsynaptic signaling cascade is circumvented. However, the pathway downstream from eCB production is the same: in both cases, the activation of astrocytes by 2-AG resulting in an increase in astrocyte Ca2+ activity is necessary. Furthermore, preNMDARs are required for both t-LTD and eCB-LTD. preNMDARs are expressed in a target-cell-specific way only at a subset of synapses. This suggests that preNMDAR-mediated plasticity is limited to specific neuronal connections [19, 39–41]. Accordingly, we only found a 2-AG induced broadening of the Ca2+ transients in a subset of the investigated axonal boutons.The presynaptic AP is an essential component for eCB-LTD induction, since without the interaction of the AP with preNMDAR activation, there is no change in the presynaptic Ca2+ signal. This is in line with our earlier observation that when LTD is induced by direct electrical stimulation of astrocytes (thereby circumventing the necessity of endocannabinoid signaling), this LTD still requires presynaptic AP firing during the astrocyte activation [8]. This observation can now be explained, since only the interaction of the preNMDAR with VDCCs, activated by the axonal AP, changes the presynaptic Ca2+ dynamics. This in turn presumably leads to calcineurin modulation and LTD. Interestingly, very similar results have been obtained by others. In the first study showing involvement of eCBs and preNMDARs in t-LTD, it was already shown that eCB application only led to LTD if it was paired with presynaptic activity [4]. Furthermore, eCB-mediated LTD at inhibitory synapses in the hippocampus, which also requires calcineurin activity, shares the requirement for AP firing in the presynaptic neuron for its induction [27].A similar interaction of a presynaptic ionotropic glutamate receptor being activated by astrocytes and influencing synaptic release has recently been demonstrated [42]. In this case, axonal AMPARs were shown to be activated by astrocytes and contributed to axonal depolarization, broadening the axonal AP and thus influencing the Ca2+ dynamics at presynaptic sites. Furthermore, several studies have shown that somatic depolarization can lead to an additional axonal depolarization that gives rise to graded, analog release of transmitter [43, 44]. Importantly, we did not find an influence of 2-AG on the somatic membrane potential nor on AP properties, thereby ruling out such an influence on the axonal Ca2+ signals in our experiments.It should be noted that an intriguing interaction of postsynaptic NMDAR activation with presynaptic Ca2+ dynamics has also been described [45]. At hippocampal CA3-CA1 synapses, the efflux of potassium through postsynaptic NMDARs provides a retrograde signal to the presynaptic bouton, which can boost the presynaptic AP-evoked Ca2+ transient and increase neurotransmitter release. However, we deem it unlikely that a similar mechanism involving postsynaptic NMDAR activation can explain our observations. First, experiments with MK801 in the pre- or postsynaptic neuron show that both t-LTD [5, 8] and eCB-LTD (this study) require presynaptic, not postsynaptic, NMDAR activation. These results are supported by the finding that t-LTD at L4-L2/3 synapses in developing visual cortex is disrupted by cell-type-specific removal of NMDARs specifically from presynaptic L4 neurons [40]. Therefore, evidence for involvement of pre- rather than postsynaptic NMDARs in L4-L2/3 LTD is quite strong. Furthermore, when potassium-mediated retrograde signaling at CA3-CA1 axons was studied a Ca2+ transient broadening mediated by postsynaptic NMDARs was only observed with repetitive AP firing in the absence of extracellular Mg2+ [45]. In contrast, in our experiments, the 2-AG-mediated broadening of Ca2+ transients in L4 boutons occurred with single AP firing in the presence of 1 mM extracellular Mg2+. Under our experimental conditions, the potassium efflux through postsynaptic NMDARs is likely minimal due to Mg2+ block of these receptors. Finally, we observed that not all L4 boutons were showing a 2-AG induced broadening of the presynaptic Ca2+ transient. This is similar to what was observed in excitatory boutons in L5 of developing neocortex [35]. It indicates that not all L4 boutons contain preNMDARs. If postsynaptic NMDARs would be responsible for the presynaptic Ca2+ transient broadening such a lack of effect in some boutons is harder to explain, since postsynaptic NMDARs are ubiquitously expressed at most glutamatergic synapses [46–49].It was recently shown that a presynaptic burst of APs followed by a single AP between 50–200 ms later can also trigger LTD (termed pattern dependent LTD, p-LTD) [10]. The presynaptic burst of APs is probably sufficient to cause spillover of presynaptically released glutamate onto preNMDARs, supported by the findings that p-LTD no longer requires astrocyte activation, but still depends on preNMDARs. Presumably, the single AP occurring with a delay comes at the time when the presynaptically released glutamate from the preceding burst has activated preNMDARs. Consistently, when we performed presynaptic Ca2+ imaging, we were able to show that the p-LTD presynaptic activity pattern evoked an APV-sensitive Ca2+ component, whereas a burst of 3 APs alone did not. Thus, preNMDARs can differentially be activated depending on the pattern of presynaptic activity and only contribute to an additional Ca2+ influx under certain conditions.An interesting question in this context is which type of VDCC is modulated by the preNMDARs? Previous experiments suggest that neither L-type nor R-and T-type VDCCs are required, because t-LTD can be induced in the presence of blockers of these channels using a burst of 3 postsynaptic APs followed by a single presynaptic AP at -10 ms [6]. Single postprepairings are sensitive to these blockers suggesting a role of these VDCCs in the postsynaptic signaling cascade [6, 7]. Thus, N- and P/Q-type VDCCs might interact with the preNMDARs.Our data is in line with the idea that preNMDAR-mediated depolarization of the terminal carried by axonal Na+ influx through the receptor plays a role in the interaction of preNMDARs with VDCCs. A similar conclusion on the importance of NMDAR-mediated Na+ influx was reached for the effect of preNMDARs on spontaneous synaptic release [15]. This ionotropic effect of preNMDARs is further supported by the finding that presynaptically applied MK801, which acts as an open channels blocker and preventing ion flow through the NMDAR, is effective in blocking t-LTD [5, 50]. Similarly, presynaptic MK801 application also affects direct modulation of release through preNMDARs [19]. This efficacy of MK801 in blocking preNMDAR effects makes a metabotropic role as has been suggested recently for hippocampal LTD for these receptors [16, 51] unlikely since lack of MK801 block is seen as a hallmark for metabotropic NMDAR function (but see below for an alternative interpretation).
### 4.2. Conflicting Data on the Existence of preNMDARs
Several studies to date have sought for functional evidence of preNMDARs in neocortex and have come to the conclusion that these receptors do not exist [13, 14]. Our current results, together with earlier findings, offer an alternative explanation for this apparent controversy. Our study suggests that the function of preNMDARs differs from the classical coincidence detector role as described for postsynaptic NMDARs. Postsynaptic NMDAR activation requires the relieve of the Mg2+ block by a backpropagating AP to supralinearly enhance postsynaptic Ca2+ influx [30]. In contrast, we find little evidence for a direct preNMDAR-mediated Ca2+ signal. This is in line with several findings about the subunit composition of preNMDARs at developing synapses in the neocortex. In the developing visual cortex, preNMDARs contain the NR3A subunit rendering these NMDARs insensitive to Mg2+ and little Ca2+ permeable [18, 40]. Both properties agree with our findings that without a presynaptic AP, there is no substantial Ca2+ influx through preNMDARs. The lack of a presynaptic Ca2+ signal by iontophoresing glutamate onto presynaptic boutons or by uncaging of MNI-glutamate was interpreted by others as a lack of preNMDARs [13, 14]. However, our findings suggest that the effect of the preNMDARs on axonal Ca2+ signaling is rather subtle and becomes only apparent in the presence of specific patterns of presynaptic APs, thereby explaining the apparent lack of preNMDAR activity in other studies. Similar results were obtained by others when performing Ca2+ imaging experiments at glutamatergic synapses onto cortical interneurons: only prolonged axonal activation with sustained bursts of APs clearly uncovered an APV-sensitive component in the Ca2+ transient [19]. At other central synapses, direct Ca2+ influx has been observed through preNMDARs suggesting that there is a synapse-specific differential subunit composition of preNMDARs [20].Importantly, the recent conclusion that t-LTD requires post- rather than presynaptic NMDARs was not just based on negative Ca2+ imaging data but also on the absence of L4-L2/3 t-LTD in a transgenic mouse in which L2/3 NMDARs were selectively disrupted [14]. Although we cannot explain this apparent discrepancy, it should be noted that another study using a transgenic mouse in which L4 NMDARs were instead selectively disrupted also showed a disruption of L4-L2/3 t-LTD [40], thereby illustrating the potential developmental, species-specific, and brain-region specific differences, which are observed in these experiments.Finally, pharmacological evidence presented recently by Carter and Jahr [14] suggests that the mechanism of action of NMDARs involved in t-LTD is metabotropic. This conclusion was based on the inability of extracellularly applied MK-801 to block t-LTD, as well as on a lack of block by the glycine-site antagonists 7-CK and 5,7-DCK. The finding that extracellular MK-801 does not block t-LTD is in direct contradiction with studies showing effective t-LTD block by intracellularly applied MK-801 [5, 50]. In this respect, it is important to note again that the pharmacological profile of preNMDARs might differ from that of “classical” postsynaptic (NR1 and NR2 containing) NMDARs. Incorporation of the NR3A subunit (presumably in triheteromeric NR1-NR2B-NR3A receptors [18]) might alter receptor pharmacology (e.g., of MK801), possibly explaining such contradictory results [52]. However, our findings cannot distinguish between an ionotropic or a metabotropic role for preNMDARs [53]. If preNMDARs have a metabotropic function, they could exert their effect by a direct interaction with VDCCs to facilitate Ca2+ influx or by an inactivation of presynaptic K+ channels, both of which could broaden the AP locally and thus enhance presynaptic Ca2+ influx [54], which would be the required signal for calcineurin activation.
## 4.1. Signaling Cascade for the Induction of t-LTD at Developing Cortical Synapses
The chemically induced eCB-LTD presented here shares the same signaling cascade as found in t-LTD. In t-LTD, the eCB 2-AG is synthetized by postsynaptic AP firing followed by presynaptic glutamate release. The postsynaptic backpropagating AP evokes an increase in postsynaptic Ca2+ through VDCCs, which is thought to prime phospholipase C (PLC), which is subsequently activated by the presynaptic release of glutamate binding to the metabotropic glutamate receptor type 5 (mGluR5) [6, 7]. In eCB-LTD, this postsynaptic signaling cascade is circumvented. However, the pathway downstream from eCB production is the same: in both cases, the activation of astrocytes by 2-AG resulting in an increase in astrocyte Ca2+ activity is necessary. Furthermore, preNMDARs are required for both t-LTD and eCB-LTD. preNMDARs are expressed in a target-cell-specific way only at a subset of synapses. This suggests that preNMDAR-mediated plasticity is limited to specific neuronal connections [19, 39–41]. Accordingly, we only found a 2-AG induced broadening of the Ca2+ transients in a subset of the investigated axonal boutons.The presynaptic AP is an essential component for eCB-LTD induction, since without the interaction of the AP with preNMDAR activation, there is no change in the presynaptic Ca2+ signal. This is in line with our earlier observation that when LTD is induced by direct electrical stimulation of astrocytes (thereby circumventing the necessity of endocannabinoid signaling), this LTD still requires presynaptic AP firing during the astrocyte activation [8]. This observation can now be explained, since only the interaction of the preNMDAR with VDCCs, activated by the axonal AP, changes the presynaptic Ca2+ dynamics. This in turn presumably leads to calcineurin modulation and LTD. Interestingly, very similar results have been obtained by others. In the first study showing involvement of eCBs and preNMDARs in t-LTD, it was already shown that eCB application only led to LTD if it was paired with presynaptic activity [4]. Furthermore, eCB-mediated LTD at inhibitory synapses in the hippocampus, which also requires calcineurin activity, shares the requirement for AP firing in the presynaptic neuron for its induction [27].A similar interaction of a presynaptic ionotropic glutamate receptor being activated by astrocytes and influencing synaptic release has recently been demonstrated [42]. In this case, axonal AMPARs were shown to be activated by astrocytes and contributed to axonal depolarization, broadening the axonal AP and thus influencing the Ca2+ dynamics at presynaptic sites. Furthermore, several studies have shown that somatic depolarization can lead to an additional axonal depolarization that gives rise to graded, analog release of transmitter [43, 44]. Importantly, we did not find an influence of 2-AG on the somatic membrane potential nor on AP properties, thereby ruling out such an influence on the axonal Ca2+ signals in our experiments.It should be noted that an intriguing interaction of postsynaptic NMDAR activation with presynaptic Ca2+ dynamics has also been described [45]. At hippocampal CA3-CA1 synapses, the efflux of potassium through postsynaptic NMDARs provides a retrograde signal to the presynaptic bouton, which can boost the presynaptic AP-evoked Ca2+ transient and increase neurotransmitter release. However, we deem it unlikely that a similar mechanism involving postsynaptic NMDAR activation can explain our observations. First, experiments with MK801 in the pre- or postsynaptic neuron show that both t-LTD [5, 8] and eCB-LTD (this study) require presynaptic, not postsynaptic, NMDAR activation. These results are supported by the finding that t-LTD at L4-L2/3 synapses in developing visual cortex is disrupted by cell-type-specific removal of NMDARs specifically from presynaptic L4 neurons [40]. Therefore, evidence for involvement of pre- rather than postsynaptic NMDARs in L4-L2/3 LTD is quite strong. Furthermore, when potassium-mediated retrograde signaling at CA3-CA1 axons was studied a Ca2+ transient broadening mediated by postsynaptic NMDARs was only observed with repetitive AP firing in the absence of extracellular Mg2+ [45]. In contrast, in our experiments, the 2-AG-mediated broadening of Ca2+ transients in L4 boutons occurred with single AP firing in the presence of 1 mM extracellular Mg2+. Under our experimental conditions, the potassium efflux through postsynaptic NMDARs is likely minimal due to Mg2+ block of these receptors. Finally, we observed that not all L4 boutons were showing a 2-AG induced broadening of the presynaptic Ca2+ transient. This is similar to what was observed in excitatory boutons in L5 of developing neocortex [35]. It indicates that not all L4 boutons contain preNMDARs. If postsynaptic NMDARs would be responsible for the presynaptic Ca2+ transient broadening such a lack of effect in some boutons is harder to explain, since postsynaptic NMDARs are ubiquitously expressed at most glutamatergic synapses [46–49].It was recently shown that a presynaptic burst of APs followed by a single AP between 50–200 ms later can also trigger LTD (termed pattern dependent LTD, p-LTD) [10]. The presynaptic burst of APs is probably sufficient to cause spillover of presynaptically released glutamate onto preNMDARs, supported by the findings that p-LTD no longer requires astrocyte activation, but still depends on preNMDARs. Presumably, the single AP occurring with a delay comes at the time when the presynaptically released glutamate from the preceding burst has activated preNMDARs. Consistently, when we performed presynaptic Ca2+ imaging, we were able to show that the p-LTD presynaptic activity pattern evoked an APV-sensitive Ca2+ component, whereas a burst of 3 APs alone did not. Thus, preNMDARs can differentially be activated depending on the pattern of presynaptic activity and only contribute to an additional Ca2+ influx under certain conditions.An interesting question in this context is which type of VDCC is modulated by the preNMDARs? Previous experiments suggest that neither L-type nor R-and T-type VDCCs are required, because t-LTD can be induced in the presence of blockers of these channels using a burst of 3 postsynaptic APs followed by a single presynaptic AP at -10 ms [6]. Single postprepairings are sensitive to these blockers suggesting a role of these VDCCs in the postsynaptic signaling cascade [6, 7]. Thus, N- and P/Q-type VDCCs might interact with the preNMDARs.Our data is in line with the idea that preNMDAR-mediated depolarization of the terminal carried by axonal Na+ influx through the receptor plays a role in the interaction of preNMDARs with VDCCs. A similar conclusion on the importance of NMDAR-mediated Na+ influx was reached for the effect of preNMDARs on spontaneous synaptic release [15]. This ionotropic effect of preNMDARs is further supported by the finding that presynaptically applied MK801, which acts as an open channels blocker and preventing ion flow through the NMDAR, is effective in blocking t-LTD [5, 50]. Similarly, presynaptic MK801 application also affects direct modulation of release through preNMDARs [19]. This efficacy of MK801 in blocking preNMDAR effects makes a metabotropic role as has been suggested recently for hippocampal LTD for these receptors [16, 51] unlikely since lack of MK801 block is seen as a hallmark for metabotropic NMDAR function (but see below for an alternative interpretation).
## 4.2. Conflicting Data on the Existence of preNMDARs
Several studies to date have sought for functional evidence of preNMDARs in neocortex and have come to the conclusion that these receptors do not exist [13, 14]. Our current results, together with earlier findings, offer an alternative explanation for this apparent controversy. Our study suggests that the function of preNMDARs differs from the classical coincidence detector role as described for postsynaptic NMDARs. Postsynaptic NMDAR activation requires the relieve of the Mg2+ block by a backpropagating AP to supralinearly enhance postsynaptic Ca2+ influx [30]. In contrast, we find little evidence for a direct preNMDAR-mediated Ca2+ signal. This is in line with several findings about the subunit composition of preNMDARs at developing synapses in the neocortex. In the developing visual cortex, preNMDARs contain the NR3A subunit rendering these NMDARs insensitive to Mg2+ and little Ca2+ permeable [18, 40]. Both properties agree with our findings that without a presynaptic AP, there is no substantial Ca2+ influx through preNMDARs. The lack of a presynaptic Ca2+ signal by iontophoresing glutamate onto presynaptic boutons or by uncaging of MNI-glutamate was interpreted by others as a lack of preNMDARs [13, 14]. However, our findings suggest that the effect of the preNMDARs on axonal Ca2+ signaling is rather subtle and becomes only apparent in the presence of specific patterns of presynaptic APs, thereby explaining the apparent lack of preNMDAR activity in other studies. Similar results were obtained by others when performing Ca2+ imaging experiments at glutamatergic synapses onto cortical interneurons: only prolonged axonal activation with sustained bursts of APs clearly uncovered an APV-sensitive component in the Ca2+ transient [19]. At other central synapses, direct Ca2+ influx has been observed through preNMDARs suggesting that there is a synapse-specific differential subunit composition of preNMDARs [20].Importantly, the recent conclusion that t-LTD requires post- rather than presynaptic NMDARs was not just based on negative Ca2+ imaging data but also on the absence of L4-L2/3 t-LTD in a transgenic mouse in which L2/3 NMDARs were selectively disrupted [14]. Although we cannot explain this apparent discrepancy, it should be noted that another study using a transgenic mouse in which L4 NMDARs were instead selectively disrupted also showed a disruption of L4-L2/3 t-LTD [40], thereby illustrating the potential developmental, species-specific, and brain-region specific differences, which are observed in these experiments.Finally, pharmacological evidence presented recently by Carter and Jahr [14] suggests that the mechanism of action of NMDARs involved in t-LTD is metabotropic. This conclusion was based on the inability of extracellularly applied MK-801 to block t-LTD, as well as on a lack of block by the glycine-site antagonists 7-CK and 5,7-DCK. The finding that extracellular MK-801 does not block t-LTD is in direct contradiction with studies showing effective t-LTD block by intracellularly applied MK-801 [5, 50]. In this respect, it is important to note again that the pharmacological profile of preNMDARs might differ from that of “classical” postsynaptic (NR1 and NR2 containing) NMDARs. Incorporation of the NR3A subunit (presumably in triheteromeric NR1-NR2B-NR3A receptors [18]) might alter receptor pharmacology (e.g., of MK801), possibly explaining such contradictory results [52]. However, our findings cannot distinguish between an ionotropic or a metabotropic role for preNMDARs [53]. If preNMDARs have a metabotropic function, they could exert their effect by a direct interaction with VDCCs to facilitate Ca2+ influx or by an inactivation of presynaptic K+ channels, both of which could broaden the AP locally and thus enhance presynaptic Ca2+ influx [54], which would be the required signal for calcineurin activation.
## 5. Conclusion
In summary, we show evidence for the existence of functional preNMDARs in spiny stellate axons at L4-L2/3 synapses in the developing rat barrel cortex. Their function is to sense glutamate either released from astrocytes or from spill-over by enhanced presynaptic activity and then to modulate the local axonal Ca2+ influx. This modulation could be either by contributing to the local membrane depolarization or by a metabotropic action affecting VDCCs or other presynaptic ionic conductances. Either mechanism would affect subsequent axonal APs by modifying AP-induced Ca2+ dynamics, thereby leading to the induction of LTD. The elucidation of the mode of action of preNMDARs is one of the remaining missing pieces to understand the signaling cascade of t-LTD at developing cortical synapses.
---
*Source: 2900875-2022-02-07.xml* | 2022 |
# Evaluation of Senior Dental Students’ General Attitude towards the Use of Rubber Dam: A Survey among Two Dental Schools
**Authors:** Jale Tanalp; Müzeyyen Kayataş; Elif Delve Başer Can; Mehmet Baybora Kayahan; Tuğçe Timur
**Journal:** The Scientific World Journal
(2014)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2014/290101
---
## Abstract
The purpose of this study was to evaluate the general attitude of senior dental students towards rubber dam use, specifically focusing on endodontic practices prior to starting to serve community. Questionnaires were distributed to senior year students of a private school and a state school in Istanbul. Questions were asked about areas where the students used rubber dam, its advantages and difficulties, and whether they agreed or disagreed with some aspects of the rubber dam. The private school students rated isolation whereas those of the state school selected prevention of aspiration which the top advantage rubber dam provides. Students of the state school agreed with the opinion that isolation cannot be achieved without rubber dam and it extended the procedure with a significantly higher ratio compared to the private school. Within the limitations of the present study, it can be concluded that the perceptions of dental students on rubber dam needs to be improved and strategies should be developed so that this valuable adjunct will comprise one of the indispensable elements of dental care.
---
## Body
## 1. Introduction
Rubber dam is universally acknowledged as a mandatory adjunct particularly during endodontic treatment. Many authorities advocate its usage and encourage practitioners to adopt it in routine practice, stressing that it is an indispensable element of contemporary health service [1]. The rubber dam offers the practitioner with a wide variety of advantages such as isolation of the operative area, provision of aseptic field, prevention of infection transfer, ingestion or aspiration of instruments, and materials or irrigants, as well as protection and retraction of soft tissue during operative procedures [2–5]. Provision of patient comfort is an additional advantage and studies revealed that most patients have a positive opinion about rubber dam experience [6].Endodontic treatment and operative dentistry are two major areas where rubber dam is used. Specifically, endodontic textbooks and specialty organizations endorse rubber dam use during endodontic procedures, indicating it as a standard of care [1, 7]. Moreover, rubber dam use should be reevaluated from a medicolegal point of view, considering increase in malpractices, directed against general practitioners. Failure to use rubber dam has been described as a serious departure from standard of care [8].With all these advantages as well as legal aspects favoring rubber dam, there still seem to be reluctance and some resistance by practitioners to use it in routine care. This issue has been drawing attention by authors who determined a significant underuse in general practice [9–13]. It has been indicated that dentists believe that rubber dam is too time consuming and cumbersome and patients do not like rubber dam experience [14].Contemporary dental education’s primary mission is to produce dentists who fulfill all competencies expected from qualified healthcare personnel. This mission can be accomplished by creating a strong foundation by the delivery of information and implementing basic aspects of dental care related with safety and high quality treatment. Rubber dam usage definitely falls into this latter category and the dental student is expected to have acquired the skills of rubber dam placement and adopted the philosophy of safe and high quality service prior to working independently.It is evident that dental schools put special emphasis on rubber dam application ever since the students’ first encounter with patients. On the other hand, what really matters is whether they will strongly adopt using rubber dam after graduation. Since surveys among dental students are helpful tools to draw the outline of future dental workforce, investigating dental students’ perceptions and attitudes towards rubber dam use will contribute to underlining the inherent problems related with implementation of this worldwide acknowledged methodology. Depending on the results, strategies can be developed to enhance the way contemporary and high quality aspects of clinical dentistry are delivered and instilled.The purpose of the present study was to determine the general attitude of a group of Turkish senior dental students enrolled in 2 different schools towards rubber dam application, specifically focusing on endodontic treatment, evaluate the problems they encounter related with this tool, and gather information about their prospective presumptions about using it in the future.
## 2. Methods
Anonymous survey questionnaires were distributed to senior students enrolled in two prominent dental schools in Istanbul, one state (Istanbul University Faculty of Dentistry) school and one private (Yeditepe University, Faculty of Dentistry) school. During the preparation of the questionnaire, the study by Mala et al. [2] was taken as the main reference with some modifications. Prior to the study, anonymity of the respondents was confirmed. A total of 147 survey forms were handed out, 47 to the senior students of the private school and 100 to their peers in the state school. The students were not held obliged to return the forms. In the first part of the questionnaire, students were asked about areas of dental practice other than endodontic treatment where they used rubber dam. The survey continued with questions regarding students’ opinion about rubber dam’s advantages, as well as difficulties. They were asked whether they agreed or disagreed with certain aspects of rubber dam and whether they use it because they believe in its positive influence or because they are obliged to during education. They were also inquired whether they intend to integrate rubber dam as a mandatory tool in the future and during which procedures they plan to use it. Those who answered this question negatively were asked about the reason.Statistical analysis was performed using NCSS (Number Cruncher Statistical System) 2007 Statistical Software (Utah, USA) pocket program. In addition to descriptive statistical methods, chi-square test was used for the comparison of qualitative data. Results were evaluated at a significance level ofP
<
0.05.
## 3. Results
All the respondents returned the forms with an overall response rate of 100%. Altogether, eighty-four (57.1%) were females whereas 63 (42.9%) were males. There were no significant differences between males and females in terms of rubber dam selection (P
>
0.05).In general, 57.1% of the students did not ask patients about latex allergy. The majority did not use rubber dam for pedodontics (89.1%) and restorative procedures (82.3% and 81%, resp.). Most students (72.1%) applied rubber dam after determining root canal accesses during endodontic treatment. One hundred and nine (74.1%) of the students believed they received satisfactory education regarding rubber dam usage. Furthermore, a major proportion (75.5%) never used rubber dam while working on teeth with extensive tissue loss. The remaining students indicated that they perform a restoration and then apply the rubber dam in case they are dealing with severely damaged teeth.In terms of the greatest advantage offered by rubber dam, provision of isolation and an aseptic field was the top ranked benefit. As for the most difficult stage of rubber dam application, clamp placement seemed to be the predominant answer (66.7%).Most students agreed with the opinion that treatments performed using the rubber dam were more successful than those where it was not used (71.4%). Most students also shared the opinion that adequate isolation cannot be achieved without rubber dam (66%). On the other hand, students rather disagreed with the opinion that rubber dam use would ease access to root canals (60.50%). The majority of students thought rubber dam usage posed difficulty in taking radiographs (88.4%). Most students also shared the opinion that application of the dam was difficult and it consisted of too many components (79.6% and 76.9%, resp.). The majority also thought that rubber dam use would increase the duration of the procedure (87.8%). The mandible was ranked as the jaw where rubber dam placement was more necessary by most students (92.5%). The students generally thought that assistance was not required for the placement of the dam. A high proportion of the respondents agreed that patients disliked the rubber dam (87.8%). A higher proportion (62.6%) indicated that they use the rubber dam at the students clinic because they were obliged to, compared to the 37.4% who really believed in its usefulness. 25.2% of the students declared they would never use a rubber dam after graduation whereas 25.2% indicated that they would use it when necessary. The majority of the remaining students (49%) indicated that they would use the rubber dam only for endodontics. When the students who would not use rubber dam were questioned about the reasons, spending extra time for its placement, the belief that it is not necessary, difficulty in application, and patients’ dislike were declared as factors for such a decision.Information obtained when the two schools were analyzed individually is summarized in Tables1, 2, 3, 4, 5, and 6. School A stands for the state school where School B stands for the private school. Significant differences were noted between the two dental schools in terms of the following aspects. Patients were inquired about the presence of latex allergy by a higher percentage of students from the state school (56%), with a statistical significance (P
=
0.0001). Rubber dam was not used by any student from the private school for pedodontics with a statistical significance (P
=
0.004). Though there was a general underuse of rubber dam by both schools during restorative procedures, the state school’s students used it during composite placement with a higher percentage and a statistically significant difference (P
=
0.027). The ratio of placement of the rubber dam during opening access cavity by the state school was significantly lower than the private school. In the state school, rubber dam placement during root canal shaping was more frequently performed with a statistical significance (P
=
0.003). The students of the private school believed they received adequate education regarding rubber dam with a higher percentage compared to the state school and a statistically significant difference (P
=
0.013).Table 1
Answers given by students to questions regarding utilization of rubber dam.
School A
School B
Significance
Gender
Male
55
55.00%
29
61.70%
χ
2: 0.59
Female
45
45.00%
18
38.30%
P
=
0.444
Do you ask your patients whether they have latex allergy prior to rubber dam use?
Yes
56
56.00%
7
14.90%
χ
2: 22.06
No
44
44.00%
40
85.10%
P
=
0.0001
Do you use rubber dam in paediatric patients?
Yes
16
16.00%
0
0.00%
χ
2: 8.44
No
84
84.00%
47
100.00%
P
=
0.004
Do you use rubber dam during amalgam restorations?
Never
79
79.00%
42
89.40%
Rarely
16
16.00%
4
8.50%
Sometimes
4
4.00%
1
2.10%
χ
2: 2.54
Always
1
1.00%
0
0.00%
P
=
0.469
Do you use rubber dam during composite restorations?
Never
75
75.00%
44
93.60%
Rarely
18
18.00%
2
4.30%
χ
2: 7.2
Sometimes
7
7.00%
1
2.10%
P
=
0.027
During which stage of endodontic treatment do you use rubber dam?
Following anesthesia
4
4.00%
2
4.30%
During access cavity preparation
1
1.00%
7
14.90%
Following identification of root canal orifices
72
72.00%
34
72.30%
During root canal shaping
22
22.00%
3
6.40%
χ
2: 16.23
During root canal filling
1
1.00%
1
2.10%
P
=
0.003
Do you think you have been given adequate and satisfactory education regarding rubber dam?
Yes
68
68.00%
41
87.20%
χ
2: 6.17
No
32
32.00%
6
12.80%
P
=
0.013
During endodontic treatment of teeth with extensive tissue loss
I don’t use rubber dam
74
74.00%
37
78.70%
χ
2: 0.39
I perform a restoration so that I can place the rubber dam
26
26.00%
10
21.30%
P
=
0.535Table 2
Opinions of students about the usage of rubber dam.
What in your opinion is the greatest advantage offered by the rubber dam?
School A
School B
Significance
Provision of isolation and an aseptic working area
44
44.00%
32
68.10%
Prevention of swallowing or aspirating instruments
51
51.00%
13
27.70%
χ
2: 7.63
Prevention of ingestion of irrigants
5
5.00%
2
4.30%
P
=
0.022Table 3
Opinions of students about the most difficult aspect regarding rubber dam usage.
What is the major factor that makes rubber dam application a difficult procedure?
School A
School B
Significance
Selection of the clamp and its adaptation
73
73.00%
25
53.20%
Placement of the rubber dam
25
25.00%
22
46.80%
χ
2: 7.58
Placement of the frame
2
2.00%
0
0.00%
P
=
0.023Table 4
Agreement or disagreement of students regarding various aspects of rubber dam.
School A
School B
Significance
Rubber dam eases the restoration stage
I agree
57
57.00%
27
57.40%
χ
2: 0
I disagree
43
43.00%
20
42.60%
P
=
0.959
Treatments performed using the rubber dam are more successful than those performed without using it
I agree
71
71.00%
34
72.30%
χ
2: 0.03
I disagree
29
29.00%
13
27.70%
P
=
0.867
An adequate isolation cannot be achieved in case rubber dam is not used
I agree
73
73.00%
24
51.10%
χ
2: 6.86
I disagree
27
27.00%
23
48.90%
P
=
0.009
Rubber dam eases access to root canals
I agree
41
41.00%
17
36.20%
χ
2: 0.31
I disagree
59
59.00%
30
63.80%
P
=
0.576
Rubber dam makes radiograph taking procedure difficult
I agree
87
87.00%
43
91.50%
χ
2: 0.63
I disagree
13
13.00%
4
8.50%
P
=
0.427
Rubber dam is difficult to apply
I agree
81
81.00%
36
76.60%
χ
2: 0.38
I disagree
19
19.00%
11
23.40%
P
=
0.537
Rubber dam consists of too many components
I agree
86
86.00%
27
57.40%
χ
2: 14.66
I disagree
14
14.00%
20
42.60%
P
=
0.0001
Rubber dam shortens/extends treatment period
Extends
92
92.00%
37
78.70%
χ
2: 5.25
Shortens
8
8.00%
10
21.30%
P
=
0.022
Rubber dam is more necessary while working in the
Mandible
90
90.00%
46
97.90%
χ
2: 2.86
Maxilla
10
10.00%
1
2.10%
P
=
0.091
Assistance is necessary during rubber dam application
I agree
33
33.00%
20
42.60%
χ
2: 1.27
I disagree
67
67.00%
27
57.40%
P
=
0.261
Patients do not like the rubber dam
I agree
87
87.00%
42
89.40%
χ
2: 0.17
I disagree
13
13.00%
5
10.60%
P
=
0.684Table 5
Opinion of students about the present and future usage of rubber dam.
School A
School B
Significance
I use the rubber dam in the clinic, because
I strongly believe that it is a helpful tool
38
38.00%
17
36.20%
χ
2: 0.05
I only use it because I am obliged to
62
62.00%
30
63.80%
P
=
0.831
Following graduation
I intend to use the rubber dam during all procedures indicated
25
25.00%
12
25.50%
I intend to use it only during restorative procedures
1
1.00%
0
0.00%
I intend to use it only during root canal treatment
45
45.00%
27
57.40%
χ
2: 3.31
I will never use it
29
29.00%
8
17.00%
P
=
0.347Table 6
Major reasons for not planning to use the rubber dam in future practice.
School A
School B
Significance
I do not believe that it is a helpful adjunct
6
19.40%
7
50.00%
I experience difficulty during application
8
25.80%
4
28.60%
I believe that it consumes time
14
45.20%
3
21.40%
χ
2: 5.96
I believe that patients do not like it
3
9.70%
0
0.00%
P
=
0.114The selection of advantage rating of rubber dam yielded differences when the two schools were compared. The state school students rated isolating effect as the top advantage lower than the private school with a statistical difference. On the other hand, the students of the state school selected the prevention of ingestion and aspiration as the top advantage with a significantly higher ratio (P
=
0.022).The students of the state school agreed with the suggestion that adequate isolation cannot be achieved without rubber dam with a higher ratio and the difference was statistically significant (P
=
0.009).The students of the state school agreed that rubber dam consisted of too many components with a higher ratio compared to the private school and the difference was statistically significant (P
=
0.0001).The students of the state school agreed that usage of rubber dam extends the treatment period with a higher ratio compared to the private school, with a statistically significant difference (P
=
0.022).No statistically significant differences were determined between the two schools in terms of the other evaluated parameters, including the intention of rubber dam usage in the future and reasons in case the question was responded negatively (P
>
0.05).
## 4. Discussion
The students surveyed in the present study were not asked whether they use rubber dam during endodontic treatment, because it is already known that rubber dam use for endodontics is mandatory in both schools. Hill and Rubel [15] stated that it is rather difficult to conduct a survey on such a topic without external influence and one may be tempted to give what is perceived as the correct answer as opposed to an honest answer, if the survey was attempted at a large meeting or organization. Such an impact was not expected in the present study as all the participants were handed out the questionnaires prior to an examination when all answers could be kept confidential. Meanwhile, it can be presumed that students are likely to give more realistic and honest answers as they are at the education phase of their lives when they are confronted with identical circumstances, contrary to practicing dentists working in a more competitive and challenging environment who may feel more peer pressure.The majority of dental schools teach their students that the use of rubber dam is mandatory for procedures such as endodontic therapy and adhesive dentistry [16]. On the other hand, it is surprising that rubber dam is believed to generate more controversy than any other dental device or technique, despite its advantages [17]. Some results obtained from the present survey support this hypothesis. Although a higher proportion of students indicated that they are planning to include rubber dam in the future, the finding that the majority of students (62.6%) place the rubber dam at the student clinic because of obligation is rather disappointing. Furthermore, a major proportion, who declared that they would use the rubber dam, mainly planned to use it during endodontics, only. This may indicate a belief among future dentists that rubber dam is basically derived for root canal procedures. Although rubber dam is generally preferred during endodontics, its usefulness during restorative treatment cannot be overlooked. The present study basically concentrated on the endodontic relevance of the rubber dam. Meanwhile, dental curriculum’s greater emphasis on rubber dam being a significant component of endodontic rather than restorative procedures may be another reason for this result. It is evident from the obtained data that though students are held obliged to use the rubber dam during endodontics, there is no such requirement for restorative procedures.Selection of the clamp and adaptation were regarded as the most difficult steps of rubber dam application by most students. This may be in part due to the fact that students may not have supplied their armamentarium with adequate numbers and types of clamps, suitable for each specific case. Furthermore, extensive loss of tooth structure may pose difficulty in adapting a regular clamp. It was interesting that the majority of students did not prefer to use the dam in severely damaged teeth. This brings into mind the reality that clinic instructors are more flexible in rubber dam application in case students are confronted with teeth with extensive tissue loss.Another disadvantage of rubber dam has been reported as the difficulty of mounting radiographs in the proper position with the dam in place. On the other hand, removal of the dam during radiography cannot be accepted as this step is specifically performed with an instrument within the root canal to determine the working length. During this step, the patient is generally left alone at the radiography site and there is no possibility of intervention in case hazards occur. Therefore, radiographs should definitely be taken with the rubber dam placed in position.Whitworth et al. [12] regarded it as disappointing that majority of UK dentists never used the rubber dam for endodontics. The results of the present study are similar to theirs in terms of the disincentives for rubber dam usage. For the respondents who indicated they are not willing to use the rubber dam in future practice, extension of the treatment period, patients’ dislike, and high cost were also regarded as the major disincentives. There are disappointing results in the literature regarding the adaption of rubber dam in clinical use. Unal et al. [18] determined the use of rubber dam by Turkish dental practitioners as low as 5.1%. A supporting result was determined by Peciuliene et al.[19] who reported that 66% of surveyed dentists never used a rubber dam. Similarly in Belgium, 64.5% of practitioners did not use rubber dam routinely while only a very minor proportion (3.4%) believed rubber dam to be a standard procedure [20]. The highest percentage of use is so for as reported by Whitten et al. [21] who surveyed amongst American general dental practitioners. It can be speculated that the strict malpractice regulations executed in USA might be effective in such a result. Malpractice law has just been implemented in Turkey and prohibition of dentists from deviation from standard of care by strictly established regulations might be influential in the future for the adoption of basic principles of standard of care, one of which is rubber dam usage.There is a general belief supported by dental practitioners that patients dislike rubber dam usage. However, this statement has been contradicted by studies concluding that rubber dam is an accepted element of dental care by patients [6, 22–24]. Whitworth et al. [12] stated that the negative perception regarding patients’ dislike towards rubber dam may be related more strongly to practitioner attitude. Stewardson and McHugh [6] also indicated that the experience of the dentist and their level of skill influence the patient’s opinion and suggested that proficiency regarding the utilization of rubber dam must be gained through frequent usage.It is also noteworthy to mention that dental students may display more idealistic views about contemporary methodologies upon graduation. With the progression of years of dental service, there might be some alterations in their views. This was further emphasized with anticipation by Mala et al. [2] in terms of reevaluating students’ answers after a 5-year elapse to see whether their initial enthusiasm remained.Hill and Rubel [15] determined that the most common reasons of not using a dam were inconvenience and belief that it is unnecessary. With this result, one may question the credibility and the way emphasis is placed concerning rubber dam usage in dental schools. This result may originate from lack of adequate emphasis and conveying the significance of rubber dam as a safety measure in a theoretical basis, only. The role rubber dam plays in safety measures during dental care can be further emphasized by showing complications arising from lack of usage and aftermath.In general, presence of latex allergy was not asked to the patients by almost half of the students, higher than the ratio reported by Mala et al. [2]. This result may suggest that more attention must be directed towards the possibility of latex allergy prior to application of the rubber dam considering some cases published [25, 26]. On the other hand, students from the private school indicated that they received a better education in terms of rubber dam with a statistical significance. This, however, should be interpreted with caution as opinions may differ between individuals in terms of evaluating conveyance of information by instructors. The high percentage of students who did not use rubber dam for child patients (89.1%) also exceeded the ratio (68%) reported by Mala et al. [2]. This issue however needs to be considered from a pedodontic standpoint, probably in a future study focusing on this group of patients.It was rather disappointing to determine that a proportion of students are not planning to use the rubber dam in the future. Percentages of students with this opinion were higher than those reported by Mala et al. [2]. Recently, there has been increasing effort to implement a malpractice law in the country, encompassing all healthcare givers. This will necessitate taking more intensive measures by both practitioners as well as authorities for the provision of patient safety. Dental schools undertaking the mission of bringing up future’s dentists bear an important responsibility in that respect. In case correct strategies are followed in terms of implementing safety precautions such as rubber dam, these helpful adjuncts will definitely be regarded as tools that ease dentists’ duties rather than devices that pose difficulty. Future surveys encompassing students as well as general practitioners will be helpful in drawing general conclusions regarding the position of rubber dam in dental use.
## 5. Conclusion
Within the limitations of this study, it can be concluded that although students at the final year of education cannot be criticized in terms of awareness of rubber dam’s advantages, there is some doubt about future integration of this tool in routine practice. This result is in line with other studies which indicate a general reluctance of using rubber dam amongst dental practitioners and can be regarded as a universal issue that requires further attention.
---
*Source: 290101-2014-03-03.xml* | 290101-2014-03-03_290101-2014-03-03.md | 26,166 | Evaluation of Senior Dental Students’ General Attitude towards the Use of Rubber Dam: A Survey among Two Dental Schools | Jale Tanalp; Müzeyyen Kayataş; Elif Delve Başer Can; Mehmet Baybora Kayahan; Tuğçe Timur | The Scientific World Journal
(2014) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2014/290101 | 290101-2014-03-03.xml | ---
## Abstract
The purpose of this study was to evaluate the general attitude of senior dental students towards rubber dam use, specifically focusing on endodontic practices prior to starting to serve community. Questionnaires were distributed to senior year students of a private school and a state school in Istanbul. Questions were asked about areas where the students used rubber dam, its advantages and difficulties, and whether they agreed or disagreed with some aspects of the rubber dam. The private school students rated isolation whereas those of the state school selected prevention of aspiration which the top advantage rubber dam provides. Students of the state school agreed with the opinion that isolation cannot be achieved without rubber dam and it extended the procedure with a significantly higher ratio compared to the private school. Within the limitations of the present study, it can be concluded that the perceptions of dental students on rubber dam needs to be improved and strategies should be developed so that this valuable adjunct will comprise one of the indispensable elements of dental care.
---
## Body
## 1. Introduction
Rubber dam is universally acknowledged as a mandatory adjunct particularly during endodontic treatment. Many authorities advocate its usage and encourage practitioners to adopt it in routine practice, stressing that it is an indispensable element of contemporary health service [1]. The rubber dam offers the practitioner with a wide variety of advantages such as isolation of the operative area, provision of aseptic field, prevention of infection transfer, ingestion or aspiration of instruments, and materials or irrigants, as well as protection and retraction of soft tissue during operative procedures [2–5]. Provision of patient comfort is an additional advantage and studies revealed that most patients have a positive opinion about rubber dam experience [6].Endodontic treatment and operative dentistry are two major areas where rubber dam is used. Specifically, endodontic textbooks and specialty organizations endorse rubber dam use during endodontic procedures, indicating it as a standard of care [1, 7]. Moreover, rubber dam use should be reevaluated from a medicolegal point of view, considering increase in malpractices, directed against general practitioners. Failure to use rubber dam has been described as a serious departure from standard of care [8].With all these advantages as well as legal aspects favoring rubber dam, there still seem to be reluctance and some resistance by practitioners to use it in routine care. This issue has been drawing attention by authors who determined a significant underuse in general practice [9–13]. It has been indicated that dentists believe that rubber dam is too time consuming and cumbersome and patients do not like rubber dam experience [14].Contemporary dental education’s primary mission is to produce dentists who fulfill all competencies expected from qualified healthcare personnel. This mission can be accomplished by creating a strong foundation by the delivery of information and implementing basic aspects of dental care related with safety and high quality treatment. Rubber dam usage definitely falls into this latter category and the dental student is expected to have acquired the skills of rubber dam placement and adopted the philosophy of safe and high quality service prior to working independently.It is evident that dental schools put special emphasis on rubber dam application ever since the students’ first encounter with patients. On the other hand, what really matters is whether they will strongly adopt using rubber dam after graduation. Since surveys among dental students are helpful tools to draw the outline of future dental workforce, investigating dental students’ perceptions and attitudes towards rubber dam use will contribute to underlining the inherent problems related with implementation of this worldwide acknowledged methodology. Depending on the results, strategies can be developed to enhance the way contemporary and high quality aspects of clinical dentistry are delivered and instilled.The purpose of the present study was to determine the general attitude of a group of Turkish senior dental students enrolled in 2 different schools towards rubber dam application, specifically focusing on endodontic treatment, evaluate the problems they encounter related with this tool, and gather information about their prospective presumptions about using it in the future.
## 2. Methods
Anonymous survey questionnaires were distributed to senior students enrolled in two prominent dental schools in Istanbul, one state (Istanbul University Faculty of Dentistry) school and one private (Yeditepe University, Faculty of Dentistry) school. During the preparation of the questionnaire, the study by Mala et al. [2] was taken as the main reference with some modifications. Prior to the study, anonymity of the respondents was confirmed. A total of 147 survey forms were handed out, 47 to the senior students of the private school and 100 to their peers in the state school. The students were not held obliged to return the forms. In the first part of the questionnaire, students were asked about areas of dental practice other than endodontic treatment where they used rubber dam. The survey continued with questions regarding students’ opinion about rubber dam’s advantages, as well as difficulties. They were asked whether they agreed or disagreed with certain aspects of rubber dam and whether they use it because they believe in its positive influence or because they are obliged to during education. They were also inquired whether they intend to integrate rubber dam as a mandatory tool in the future and during which procedures they plan to use it. Those who answered this question negatively were asked about the reason.Statistical analysis was performed using NCSS (Number Cruncher Statistical System) 2007 Statistical Software (Utah, USA) pocket program. In addition to descriptive statistical methods, chi-square test was used for the comparison of qualitative data. Results were evaluated at a significance level ofP
<
0.05.
## 3. Results
All the respondents returned the forms with an overall response rate of 100%. Altogether, eighty-four (57.1%) were females whereas 63 (42.9%) were males. There were no significant differences between males and females in terms of rubber dam selection (P
>
0.05).In general, 57.1% of the students did not ask patients about latex allergy. The majority did not use rubber dam for pedodontics (89.1%) and restorative procedures (82.3% and 81%, resp.). Most students (72.1%) applied rubber dam after determining root canal accesses during endodontic treatment. One hundred and nine (74.1%) of the students believed they received satisfactory education regarding rubber dam usage. Furthermore, a major proportion (75.5%) never used rubber dam while working on teeth with extensive tissue loss. The remaining students indicated that they perform a restoration and then apply the rubber dam in case they are dealing with severely damaged teeth.In terms of the greatest advantage offered by rubber dam, provision of isolation and an aseptic field was the top ranked benefit. As for the most difficult stage of rubber dam application, clamp placement seemed to be the predominant answer (66.7%).Most students agreed with the opinion that treatments performed using the rubber dam were more successful than those where it was not used (71.4%). Most students also shared the opinion that adequate isolation cannot be achieved without rubber dam (66%). On the other hand, students rather disagreed with the opinion that rubber dam use would ease access to root canals (60.50%). The majority of students thought rubber dam usage posed difficulty in taking radiographs (88.4%). Most students also shared the opinion that application of the dam was difficult and it consisted of too many components (79.6% and 76.9%, resp.). The majority also thought that rubber dam use would increase the duration of the procedure (87.8%). The mandible was ranked as the jaw where rubber dam placement was more necessary by most students (92.5%). The students generally thought that assistance was not required for the placement of the dam. A high proportion of the respondents agreed that patients disliked the rubber dam (87.8%). A higher proportion (62.6%) indicated that they use the rubber dam at the students clinic because they were obliged to, compared to the 37.4% who really believed in its usefulness. 25.2% of the students declared they would never use a rubber dam after graduation whereas 25.2% indicated that they would use it when necessary. The majority of the remaining students (49%) indicated that they would use the rubber dam only for endodontics. When the students who would not use rubber dam were questioned about the reasons, spending extra time for its placement, the belief that it is not necessary, difficulty in application, and patients’ dislike were declared as factors for such a decision.Information obtained when the two schools were analyzed individually is summarized in Tables1, 2, 3, 4, 5, and 6. School A stands for the state school where School B stands for the private school. Significant differences were noted between the two dental schools in terms of the following aspects. Patients were inquired about the presence of latex allergy by a higher percentage of students from the state school (56%), with a statistical significance (P
=
0.0001). Rubber dam was not used by any student from the private school for pedodontics with a statistical significance (P
=
0.004). Though there was a general underuse of rubber dam by both schools during restorative procedures, the state school’s students used it during composite placement with a higher percentage and a statistically significant difference (P
=
0.027). The ratio of placement of the rubber dam during opening access cavity by the state school was significantly lower than the private school. In the state school, rubber dam placement during root canal shaping was more frequently performed with a statistical significance (P
=
0.003). The students of the private school believed they received adequate education regarding rubber dam with a higher percentage compared to the state school and a statistically significant difference (P
=
0.013).Table 1
Answers given by students to questions regarding utilization of rubber dam.
School A
School B
Significance
Gender
Male
55
55.00%
29
61.70%
χ
2: 0.59
Female
45
45.00%
18
38.30%
P
=
0.444
Do you ask your patients whether they have latex allergy prior to rubber dam use?
Yes
56
56.00%
7
14.90%
χ
2: 22.06
No
44
44.00%
40
85.10%
P
=
0.0001
Do you use rubber dam in paediatric patients?
Yes
16
16.00%
0
0.00%
χ
2: 8.44
No
84
84.00%
47
100.00%
P
=
0.004
Do you use rubber dam during amalgam restorations?
Never
79
79.00%
42
89.40%
Rarely
16
16.00%
4
8.50%
Sometimes
4
4.00%
1
2.10%
χ
2: 2.54
Always
1
1.00%
0
0.00%
P
=
0.469
Do you use rubber dam during composite restorations?
Never
75
75.00%
44
93.60%
Rarely
18
18.00%
2
4.30%
χ
2: 7.2
Sometimes
7
7.00%
1
2.10%
P
=
0.027
During which stage of endodontic treatment do you use rubber dam?
Following anesthesia
4
4.00%
2
4.30%
During access cavity preparation
1
1.00%
7
14.90%
Following identification of root canal orifices
72
72.00%
34
72.30%
During root canal shaping
22
22.00%
3
6.40%
χ
2: 16.23
During root canal filling
1
1.00%
1
2.10%
P
=
0.003
Do you think you have been given adequate and satisfactory education regarding rubber dam?
Yes
68
68.00%
41
87.20%
χ
2: 6.17
No
32
32.00%
6
12.80%
P
=
0.013
During endodontic treatment of teeth with extensive tissue loss
I don’t use rubber dam
74
74.00%
37
78.70%
χ
2: 0.39
I perform a restoration so that I can place the rubber dam
26
26.00%
10
21.30%
P
=
0.535Table 2
Opinions of students about the usage of rubber dam.
What in your opinion is the greatest advantage offered by the rubber dam?
School A
School B
Significance
Provision of isolation and an aseptic working area
44
44.00%
32
68.10%
Prevention of swallowing or aspirating instruments
51
51.00%
13
27.70%
χ
2: 7.63
Prevention of ingestion of irrigants
5
5.00%
2
4.30%
P
=
0.022Table 3
Opinions of students about the most difficult aspect regarding rubber dam usage.
What is the major factor that makes rubber dam application a difficult procedure?
School A
School B
Significance
Selection of the clamp and its adaptation
73
73.00%
25
53.20%
Placement of the rubber dam
25
25.00%
22
46.80%
χ
2: 7.58
Placement of the frame
2
2.00%
0
0.00%
P
=
0.023Table 4
Agreement or disagreement of students regarding various aspects of rubber dam.
School A
School B
Significance
Rubber dam eases the restoration stage
I agree
57
57.00%
27
57.40%
χ
2: 0
I disagree
43
43.00%
20
42.60%
P
=
0.959
Treatments performed using the rubber dam are more successful than those performed without using it
I agree
71
71.00%
34
72.30%
χ
2: 0.03
I disagree
29
29.00%
13
27.70%
P
=
0.867
An adequate isolation cannot be achieved in case rubber dam is not used
I agree
73
73.00%
24
51.10%
χ
2: 6.86
I disagree
27
27.00%
23
48.90%
P
=
0.009
Rubber dam eases access to root canals
I agree
41
41.00%
17
36.20%
χ
2: 0.31
I disagree
59
59.00%
30
63.80%
P
=
0.576
Rubber dam makes radiograph taking procedure difficult
I agree
87
87.00%
43
91.50%
χ
2: 0.63
I disagree
13
13.00%
4
8.50%
P
=
0.427
Rubber dam is difficult to apply
I agree
81
81.00%
36
76.60%
χ
2: 0.38
I disagree
19
19.00%
11
23.40%
P
=
0.537
Rubber dam consists of too many components
I agree
86
86.00%
27
57.40%
χ
2: 14.66
I disagree
14
14.00%
20
42.60%
P
=
0.0001
Rubber dam shortens/extends treatment period
Extends
92
92.00%
37
78.70%
χ
2: 5.25
Shortens
8
8.00%
10
21.30%
P
=
0.022
Rubber dam is more necessary while working in the
Mandible
90
90.00%
46
97.90%
χ
2: 2.86
Maxilla
10
10.00%
1
2.10%
P
=
0.091
Assistance is necessary during rubber dam application
I agree
33
33.00%
20
42.60%
χ
2: 1.27
I disagree
67
67.00%
27
57.40%
P
=
0.261
Patients do not like the rubber dam
I agree
87
87.00%
42
89.40%
χ
2: 0.17
I disagree
13
13.00%
5
10.60%
P
=
0.684Table 5
Opinion of students about the present and future usage of rubber dam.
School A
School B
Significance
I use the rubber dam in the clinic, because
I strongly believe that it is a helpful tool
38
38.00%
17
36.20%
χ
2: 0.05
I only use it because I am obliged to
62
62.00%
30
63.80%
P
=
0.831
Following graduation
I intend to use the rubber dam during all procedures indicated
25
25.00%
12
25.50%
I intend to use it only during restorative procedures
1
1.00%
0
0.00%
I intend to use it only during root canal treatment
45
45.00%
27
57.40%
χ
2: 3.31
I will never use it
29
29.00%
8
17.00%
P
=
0.347Table 6
Major reasons for not planning to use the rubber dam in future practice.
School A
School B
Significance
I do not believe that it is a helpful adjunct
6
19.40%
7
50.00%
I experience difficulty during application
8
25.80%
4
28.60%
I believe that it consumes time
14
45.20%
3
21.40%
χ
2: 5.96
I believe that patients do not like it
3
9.70%
0
0.00%
P
=
0.114The selection of advantage rating of rubber dam yielded differences when the two schools were compared. The state school students rated isolating effect as the top advantage lower than the private school with a statistical difference. On the other hand, the students of the state school selected the prevention of ingestion and aspiration as the top advantage with a significantly higher ratio (P
=
0.022).The students of the state school agreed with the suggestion that adequate isolation cannot be achieved without rubber dam with a higher ratio and the difference was statistically significant (P
=
0.009).The students of the state school agreed that rubber dam consisted of too many components with a higher ratio compared to the private school and the difference was statistically significant (P
=
0.0001).The students of the state school agreed that usage of rubber dam extends the treatment period with a higher ratio compared to the private school, with a statistically significant difference (P
=
0.022).No statistically significant differences were determined between the two schools in terms of the other evaluated parameters, including the intention of rubber dam usage in the future and reasons in case the question was responded negatively (P
>
0.05).
## 4. Discussion
The students surveyed in the present study were not asked whether they use rubber dam during endodontic treatment, because it is already known that rubber dam use for endodontics is mandatory in both schools. Hill and Rubel [15] stated that it is rather difficult to conduct a survey on such a topic without external influence and one may be tempted to give what is perceived as the correct answer as opposed to an honest answer, if the survey was attempted at a large meeting or organization. Such an impact was not expected in the present study as all the participants were handed out the questionnaires prior to an examination when all answers could be kept confidential. Meanwhile, it can be presumed that students are likely to give more realistic and honest answers as they are at the education phase of their lives when they are confronted with identical circumstances, contrary to practicing dentists working in a more competitive and challenging environment who may feel more peer pressure.The majority of dental schools teach their students that the use of rubber dam is mandatory for procedures such as endodontic therapy and adhesive dentistry [16]. On the other hand, it is surprising that rubber dam is believed to generate more controversy than any other dental device or technique, despite its advantages [17]. Some results obtained from the present survey support this hypothesis. Although a higher proportion of students indicated that they are planning to include rubber dam in the future, the finding that the majority of students (62.6%) place the rubber dam at the student clinic because of obligation is rather disappointing. Furthermore, a major proportion, who declared that they would use the rubber dam, mainly planned to use it during endodontics, only. This may indicate a belief among future dentists that rubber dam is basically derived for root canal procedures. Although rubber dam is generally preferred during endodontics, its usefulness during restorative treatment cannot be overlooked. The present study basically concentrated on the endodontic relevance of the rubber dam. Meanwhile, dental curriculum’s greater emphasis on rubber dam being a significant component of endodontic rather than restorative procedures may be another reason for this result. It is evident from the obtained data that though students are held obliged to use the rubber dam during endodontics, there is no such requirement for restorative procedures.Selection of the clamp and adaptation were regarded as the most difficult steps of rubber dam application by most students. This may be in part due to the fact that students may not have supplied their armamentarium with adequate numbers and types of clamps, suitable for each specific case. Furthermore, extensive loss of tooth structure may pose difficulty in adapting a regular clamp. It was interesting that the majority of students did not prefer to use the dam in severely damaged teeth. This brings into mind the reality that clinic instructors are more flexible in rubber dam application in case students are confronted with teeth with extensive tissue loss.Another disadvantage of rubber dam has been reported as the difficulty of mounting radiographs in the proper position with the dam in place. On the other hand, removal of the dam during radiography cannot be accepted as this step is specifically performed with an instrument within the root canal to determine the working length. During this step, the patient is generally left alone at the radiography site and there is no possibility of intervention in case hazards occur. Therefore, radiographs should definitely be taken with the rubber dam placed in position.Whitworth et al. [12] regarded it as disappointing that majority of UK dentists never used the rubber dam for endodontics. The results of the present study are similar to theirs in terms of the disincentives for rubber dam usage. For the respondents who indicated they are not willing to use the rubber dam in future practice, extension of the treatment period, patients’ dislike, and high cost were also regarded as the major disincentives. There are disappointing results in the literature regarding the adaption of rubber dam in clinical use. Unal et al. [18] determined the use of rubber dam by Turkish dental practitioners as low as 5.1%. A supporting result was determined by Peciuliene et al.[19] who reported that 66% of surveyed dentists never used a rubber dam. Similarly in Belgium, 64.5% of practitioners did not use rubber dam routinely while only a very minor proportion (3.4%) believed rubber dam to be a standard procedure [20]. The highest percentage of use is so for as reported by Whitten et al. [21] who surveyed amongst American general dental practitioners. It can be speculated that the strict malpractice regulations executed in USA might be effective in such a result. Malpractice law has just been implemented in Turkey and prohibition of dentists from deviation from standard of care by strictly established regulations might be influential in the future for the adoption of basic principles of standard of care, one of which is rubber dam usage.There is a general belief supported by dental practitioners that patients dislike rubber dam usage. However, this statement has been contradicted by studies concluding that rubber dam is an accepted element of dental care by patients [6, 22–24]. Whitworth et al. [12] stated that the negative perception regarding patients’ dislike towards rubber dam may be related more strongly to practitioner attitude. Stewardson and McHugh [6] also indicated that the experience of the dentist and their level of skill influence the patient’s opinion and suggested that proficiency regarding the utilization of rubber dam must be gained through frequent usage.It is also noteworthy to mention that dental students may display more idealistic views about contemporary methodologies upon graduation. With the progression of years of dental service, there might be some alterations in their views. This was further emphasized with anticipation by Mala et al. [2] in terms of reevaluating students’ answers after a 5-year elapse to see whether their initial enthusiasm remained.Hill and Rubel [15] determined that the most common reasons of not using a dam were inconvenience and belief that it is unnecessary. With this result, one may question the credibility and the way emphasis is placed concerning rubber dam usage in dental schools. This result may originate from lack of adequate emphasis and conveying the significance of rubber dam as a safety measure in a theoretical basis, only. The role rubber dam plays in safety measures during dental care can be further emphasized by showing complications arising from lack of usage and aftermath.In general, presence of latex allergy was not asked to the patients by almost half of the students, higher than the ratio reported by Mala et al. [2]. This result may suggest that more attention must be directed towards the possibility of latex allergy prior to application of the rubber dam considering some cases published [25, 26]. On the other hand, students from the private school indicated that they received a better education in terms of rubber dam with a statistical significance. This, however, should be interpreted with caution as opinions may differ between individuals in terms of evaluating conveyance of information by instructors. The high percentage of students who did not use rubber dam for child patients (89.1%) also exceeded the ratio (68%) reported by Mala et al. [2]. This issue however needs to be considered from a pedodontic standpoint, probably in a future study focusing on this group of patients.It was rather disappointing to determine that a proportion of students are not planning to use the rubber dam in the future. Percentages of students with this opinion were higher than those reported by Mala et al. [2]. Recently, there has been increasing effort to implement a malpractice law in the country, encompassing all healthcare givers. This will necessitate taking more intensive measures by both practitioners as well as authorities for the provision of patient safety. Dental schools undertaking the mission of bringing up future’s dentists bear an important responsibility in that respect. In case correct strategies are followed in terms of implementing safety precautions such as rubber dam, these helpful adjuncts will definitely be regarded as tools that ease dentists’ duties rather than devices that pose difficulty. Future surveys encompassing students as well as general practitioners will be helpful in drawing general conclusions regarding the position of rubber dam in dental use.
## 5. Conclusion
Within the limitations of this study, it can be concluded that although students at the final year of education cannot be criticized in terms of awareness of rubber dam’s advantages, there is some doubt about future integration of this tool in routine practice. This result is in line with other studies which indicate a general reluctance of using rubber dam amongst dental practitioners and can be regarded as a universal issue that requires further attention.
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*Source: 290101-2014-03-03.xml* | 2014 |
# Biology ofOmaspides pallidipennis Boheman, 1854 (Coleoptera: Chrysomelidae: Cassidinae)
**Authors:** Paula A. A. Gomes; Fábio Prezoto; Fernando A. Frieiro-Costa
**Journal:** Psyche
(2012)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2012/290102
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## Abstract
The biology and the feeding habits of the subsocial speciesOmaspides pallidipennis were studied at the Floresta Nacional de Passa Quatro, MG, Brazil, during the period from October 2010 to April 2011. The species was bivoltine, beginning its reproductive and food cycle in October (spring) and seeking its diapause sites in April (autumn). The juveniles took 54.4 days on average to complete their development, a period in which the female remained close to offspring, only feeding during the larval stage of the juveniles. It is a monophagous species, feeding only on Ipomoea alba Linnaeus (Convolvulaceae). In the first cycle, the average number of eggs was 55.7±15.5 eggs per egg cluster (n=1,837 eggs in 33 clusters) and in the second it was 61.6±14.2 eggs per egg cluster (n=5,607 eggs in 91 clusters). Oviposition peaks were observed in the months of November and February. The average durations of the incubation period and the larval and the pupal development in the first cycle were 19.2±1.4; 26.0±1.5; 8.7±0.8 days, respectively. In the second cycle they wrere 16.7±1.4; 27.0±2.4; 10.2±1.5 days, respectively.
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## Body
## 1. Introduction
The family Chrysomelidae is one of the largest among the insects of the order Coleoptera [1]. Due to its diversity of representatives it is subdivided into 19 subfamilies [2]. Among these Cassidinae stands out for being the second largest in number of species (ca. 6,000 species), with approximately 16% of the diversity [3]. Its representatives also stand out for having unique morphological, ecological and biological characteristics [4]. However, an evident problem that exists regarding that subfamily is the shortage of information regarding the biology of many of its species. Although the majority is solitary, various species are subsocial. The study of those characteristics can explain the determination of the sequence and exact number of transitions among the way of life of the solitary, gregarious, and subsocial species [5]. Moreover, to know the relationship between the performance of the offspring and the egg laying preference, it is essential to understand the population dynamics of herbivore insects, as well as their distribution [6].The majority of existing research on Cassidinae about the biology of the species, solitary or subsocial, was conducted in laboratory [7–10]. In field, the biology of subsocial species is described, minutely, for Acromis sparsa Boheman, 1854 (see, e.g., [11, 12]) and Omaspides tricolorata Boheman, 1854 [13, 14]. However, the number of species that exhibiting that behavior is much higher (16 species described, for the Stolaini and Eugenysini tribes) and should increase, due higher number of researchers working with this theme.For the subsocial speciesOmaspides pallidipennis Boheman, 1854, no data was found on its biology. Information about the description of the pupa and adults were given by Costa Lima [15], also registering the presence of the subsocial behavior [11, 15–18]. As for its distribution in Brazil, the species is found in the states of Espírito Santo, Minas Gerais, Paraná, Rio Grande do Sul, Rio de Janeiro, Santa Catarina, and São Paulo [19], in environment of Atlantic forest, riparian forest, and savanna (Fernando Frieiro-Costa, personal information). In relation to the host plant, information is also scarce. Few information exists of Ipomoea alba Linnaeus, 1753 (Convolvulaceae) as host plant [19, 20]. Although most of the subsocial Cassidinae have been observed in only one type of host plant, some species can be found on different host plants genus. For O. pallidipennis,this fact has not been observed (Fernando Frieiro-Costa, personal information).The objective of the present work was describe the biology ofOmaspides pallidipennisBoheman, 1854 (Coleoptera: Chrysomelidae: Cassidinae) and its relation with host plant, in a natural environment in the Atlantic Forest biome.
## 2. Material and Methods
### 2.1. Study Area
The research was conducted in the Floresta Nacional (FLONA) de Passa Quatro, Municipal district of Passa Quatro, Minas Gerais State, Brazil (22° 23′ S, 44° 56′ O); altitude of 900 m; 335 ha), in an Atlantic Forest recovery area. The Conservation Unit (CU) contains roads that are used by tourists for visitation and by the guards for local patrols. The study was conducted on the host plants that grew on the edge of one of those roadsides.The vegetation of CU is characterized by the insertion of a Semidecidual Seasonal Forest in the Atlantic Forest Biome, with a prevalence of planted plant coverings of pine, araucaria, and eucalyptus. Regionally, besides the Semidecidual Seasonal Forest, the Dense Ombrophylous Forest and Mixed Ombrophylous Forest typologies are found in the area [21]. The climate of the area, according to the Köppen classification, is Cwa-moderate temperatures with hot and rainy summers and dry winters. The climatic data were supplied by the National Institute of Meteorology (INMET) and presented an average temperature of 21.4°C, with precipitation and relative humidity of 291.9 mm and 76%, respectively, for the first life cycle of the species (October/January). For the second cycle (February/April) the temperature, precipitation, and relative humidity averages were 21.6°C, 116.9 mm, and 75%, respectively.
### 2.2. Biological Study ofO. pallidipennis
The population ofO. pallidipennis was observed daily, in the morning and in the afternoon (at alternate times), during the period between the months of October 2010 to April 2011. In this period 170 females with egg masses were accompanied and marked. The females received a mark on their elytron, facilitating the observation of parental care, of number of eggs deposited in each cycle, and of the development duration of the juvenile stages. For the marking of the females the Frieiro-Costa and Vasconcellos-Neto methodology was used [14]. Photographs of the egg masses, when the guardian was not over them, facilitated the obtaining of the average number of eggs. The oviposition and eclosion times were logged. Daylight saving time was not taken into account at any time.
### 2.3. Host Plant
The latescentI. albavine frequently occurs in forest borders.It can also be found in crop areas, where it is a serious competitor of cultivated plants [22]. The flowers are solitary or gathered in groups, with a white or pinkish coloration [23–26]. In the lamina/petiole intersection there are extrafloral nectaries (EFNs) which are constantly visited by various insect species, especially ants. In Brazil this plant can be found in the states of Bahia, Rio de Janeiro, São Paulo, Paraná, Santa Catarina, Rio Grande do Sul, and Ceará [23].
### 2.4. Statistical Analysis
The data were submitted to the Kolmogorov-Smirnov test, to verify the distribution type, being expressed as the average ± standard deviation (SD). To compare the data of number of eggs and developmental time of immatures between one cycle and another, the Student’st-test was used for normal distribution data and the Mann-Whitney test for free distribution. For these analysis the Bioestat version 5.3 software was used [27].
## 2.1. Study Area
The research was conducted in the Floresta Nacional (FLONA) de Passa Quatro, Municipal district of Passa Quatro, Minas Gerais State, Brazil (22° 23′ S, 44° 56′ O); altitude of 900 m; 335 ha), in an Atlantic Forest recovery area. The Conservation Unit (CU) contains roads that are used by tourists for visitation and by the guards for local patrols. The study was conducted on the host plants that grew on the edge of one of those roadsides.The vegetation of CU is characterized by the insertion of a Semidecidual Seasonal Forest in the Atlantic Forest Biome, with a prevalence of planted plant coverings of pine, araucaria, and eucalyptus. Regionally, besides the Semidecidual Seasonal Forest, the Dense Ombrophylous Forest and Mixed Ombrophylous Forest typologies are found in the area [21]. The climate of the area, according to the Köppen classification, is Cwa-moderate temperatures with hot and rainy summers and dry winters. The climatic data were supplied by the National Institute of Meteorology (INMET) and presented an average temperature of 21.4°C, with precipitation and relative humidity of 291.9 mm and 76%, respectively, for the first life cycle of the species (October/January). For the second cycle (February/April) the temperature, precipitation, and relative humidity averages were 21.6°C, 116.9 mm, and 75%, respectively.
## 2.2. Biological Study ofO. pallidipennis
The population ofO. pallidipennis was observed daily, in the morning and in the afternoon (at alternate times), during the period between the months of October 2010 to April 2011. In this period 170 females with egg masses were accompanied and marked. The females received a mark on their elytron, facilitating the observation of parental care, of number of eggs deposited in each cycle, and of the development duration of the juvenile stages. For the marking of the females the Frieiro-Costa and Vasconcellos-Neto methodology was used [14]. Photographs of the egg masses, when the guardian was not over them, facilitated the obtaining of the average number of eggs. The oviposition and eclosion times were logged. Daylight saving time was not taken into account at any time.
## 2.3. Host Plant
The latescentI. albavine frequently occurs in forest borders.It can also be found in crop areas, where it is a serious competitor of cultivated plants [22]. The flowers are solitary or gathered in groups, with a white or pinkish coloration [23–26]. In the lamina/petiole intersection there are extrafloral nectaries (EFNs) which are constantly visited by various insect species, especially ants. In Brazil this plant can be found in the states of Bahia, Rio de Janeiro, São Paulo, Paraná, Santa Catarina, Rio Grande do Sul, and Ceará [23].
## 2.4. Statistical Analysis
The data were submitted to the Kolmogorov-Smirnov test, to verify the distribution type, being expressed as the average ± standard deviation (SD). To compare the data of number of eggs and developmental time of immatures between one cycle and another, the Student’st-test was used for normal distribution data and the Mann-Whitney test for free distribution. For these analysis the Bioestat version 5.3 software was used [27].
## 3. Results and Discussion
### 3.1. General Aspects of Biology ofO. pallidipennis
Bivoltine Coleoptera,O. pallidipennis began their reproductive and feeding activities in October (spring) and they sought the diapause sites in the middle of April (autumn). During the whole cycle the juveniles only received care by the female that protected them from any imminent danger.Species of subsocial tropical Cassidinae, likeO. pallidipennis, O. tricolorata [14] and Omaspides brunneosignata Boheman, 1854, do not usually present more than two annual generations, because they spend much time and energy taking care of a single group of offspring. For not being exposed to the seasonal extremes that impede reproduction and growth, tropical and subtropical Cassidinae, subsocial or not, can present a greater number of generations [28, 29], if compared to temperate region species that are usually univoltine [30, 31]. Nevertheless, they are exposed to the alterations of the dry and rainy stations, related to the adequate availability of food [32]. In some of those tropical species, the synchronization of the life cycle with the variable conditions is enabled through the diapause [32].In the FLONA of Passa Quatro,O. pallidipennispresented monophagous habits.Adults as well as juveniles only fed on I. alba.Although other plants of the same family and same genus have been found in the CU, those Cassidinae were never observed on another host plant species. Besides O. pallidipennis,egg masses and adults of the solitary species Chelymorpha inflataBoheman, 1854 (Cassidinae: Stolaini) were found also feeding on I. alba.At no time were both species observed feeding on the same leaf. Besides C. inflata,grasshoppers and Chrysomelinae and Lepidoptera larvae were found feeding on the leaves of the chosen host.I. albawas observed in FLONA of Passa Quatro, in an open field area as well as roadside. The specimens of the host plant remained under direct sunlight most of the day, with few shaded portions.
### 3.2. Immature Stages
These insects are holometabolic, their cycle being completed in approximately two months (54.4 days on average, from egg to adult).
#### 3.2.1. Eggs
The egg clusters ofO. pallidipennis presents a diamond-shaped format that, with elongated eggs, approximately 2.8 times longer than their highest width and without any covering (Figure 1(a)). When recently laid they presented an amber coloration (Figure 2(a)) later becoming straw-yellow as the hardening of the chorion occurred (Figure 2(b)). That difference in the coloration allowed the distinction of the oldest egg clusters from the most recent. In the first cycle (October to December) the oviposition presented, on average, 55.7±15.5 eggs/egg clusters (n=1,837 eggs in 33 clusters; range 12–80 eggs), and in the second cycle (February to April) the average corresponded to 61.6±14.2 eggs/egg clusters (n=5,607 eggs in 91 clusters; range 13–80 eggs). The ratio between the number of egg masses in the first and second cycles was significantly different (U=1106.00; P=0.0253). The factors for this difference can be attributed to the disparity existent between one female and another regarding their physiological and nutritional state, the nutritional state of the host plant leaves (young leaves, under growth have higher level of nitrogen than the mature leaf) [33], and to the abiotic factors, as the temperature. In many insects, the production of eggs is controlled by one or more hormones produced in the corpora allata, that control the initial stages of oogenesis and the yolk deposition. Factors such as the temperature can act on these structures, thus affecting the egg production [34].Immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae). (a) Egg cluster, (b) dorsal view of last instar larvae, (c) exuvial-fecal shield, (d) pupae in dorsal view. Photos: (a), (b), and (d): Flávia Fernandes.
(a)
(b)
(c)
(d)Omaspides pallidipennis Boheman, 1854 (Chrysomelidae) female (a) on recently laid egg cluster (b) after a few days. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
(a)
(b)Subsocial species of the same genus, likeO. tricolorata [14] and Omaspides convexicollisSpaeth, 1909 [35], also present a large number of eggs per cluster (average of 55.1 and 48.8, resp.), if compared to other non-subsocial species such as Anacassis dubia Boheman, 1854 with an average of 9.1 eggs per cluster and Anacassis languida Boheman, 1854 with an average of 6.7 eggs per cluster [9, 36]. The female of Charidotis punctatostriata Boheman, 1856 produces, annually, an average of 235.5±41 eggs per female [8], a quantity that can be attributed to the high reproductive effort due to the semelparity presented.The large number of eggs in subsocial species can also be explained by the high reproductive effort, because they spend most of their time investing in the defense of the offspring and in resource allocation, instead of going through various ovipositions. However, the subsociality is one of several adaptations aimed at facing adverse conditions [37]. Unlike the physical protection provided to the eggs by the mother, as in Acromis sparsa Boheman, 1854 [38], the non-subsocial Cassidinae can make use of different adaptations, such as the protection of the eggs through an ootheca [39–41] and oootheca and feces [42] or a gelatinous matrix with feces, as in Hemisphaerota cyanea Say, 1824 [43], thus making access more difficult for the natural enemies.Regarding the egg laying site, the ovipositions ofO. pallidipennis were all deposited on the abaxial surface of I. alba, a behavior also present in other subsocial [11, 13, 44, 45] and non-subsocial species [39, 40]. For the species Gratiana spadicea Klug, 1829 and O. tricoloratathis behavioral pattern is related to the temperature [14, 46]. Although it had not been measured, the temperature was also pointed to as a decisive factor of this behavior, because the majority of the host plant leaves were under direct sunlight several hours a day.The choice of the female for the egg laying site is an important factor for the growth and the survival of their larvae [47]. When ovipositing, the female should consider an appropriate place for the development of the juveniles, thus maximizing their adaptive value. Factors such as the predation risk [47, 48], host plant quality or quantity [33, 49], larval mobility [50], and the intraspecific and interspecific competition [51] should be considered. Of the 170 egg masses observed, 159 allowed to know the oviposition site with certainty. Of these, 116 (73%) were found along the midrib and 43 (27%) in other parts of the leaf blade, no egg masses being placed in the proximal half of the petiole. That preference to oviposit in the distal portions can be explained by the presence of predator ants that constantly visited host plant EFNs. Among them several ants of the genus Pseudomyrmex sp. (Formicidae) and Crematogaster sp. (Formicidae) preying on eggs and larvae were found. The oviposition preference on the host plant was not altered by the intraspecific competition, not finding more than one egg mass of the species or of other Cassidinae species on the same leaf.The oviposition peaks occurred during the months of November and February, not observing any new egg masses, in December, January, and April. The average of incubation period of the eggs was19.2±1.4 days (n=31 offspring) for the first cycle and 16.7±1.4 days (n=71 offspring) for the second cycle (Table 1). The incubation time differed significantly in the two cycles (U=239.00; P<0.0001). Characteristics such as abiotic factor variations can explain such difference. In Metriona elatior Klug, 1829 the average incubation time of the eggs is lower at 30°C (5.6 days) than at 20°C (11.3 days) [52]. Another factor to be considered is the quality and the quantity of the host plant that can alter nutrient acquisition, thus interfering in the production of eggs [53]. However, more research is necessary to explain these characteristics.Table 1
Duration of the developmental immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae), for the first and second cycle in a fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
First cycle
Second cycle
Mean ± SD
Mean ± SD
Egg
19.2
±
1.4 (n=31)
16.7
±
1.4 (n=71)
Larvae
26.0
±
1.5 (n=19)
27.0
±
2.4 (n=35)
Pupae
8.7
±
0.8 (n=20)
10.2
±
1.5 (n=30)
Total time
54.3
±
9.0
54.4
±
8.7During the biological cycles, three females oviposited twice during the same cycle. In all those cases their first oviposition had been preyed upon. The time spent between one oviposition and the other varied from 1 to 19 days.
#### 3.2.2. Larvae
The larvae ofO. pallidipennisare light yellow, presenting a slightly dorsal-ventrally flat body. There are nine pairs of lateral scoli and a caudal furcae (Figure 1(b)) where the exuvial-fecal shield is attached [18] (Figure 1(c)). In some species of Cassidinae s.str., this structure works as physical protection against dissection and predation [54, 55]. A chemical defense function, through compounds that are present in this attachment, is evidenced, also, in other species [56–58]. Eurypedus nigrosignatusBoheman, 1854 (Cassidinae: Physonotini) obtains those chemical compounds from its host plantCordia curassavica(Jacques) Roemer and Schultes [59]. Studies evidence that these structures have been shown to be efficient against some natural enemies, but not against others. In Cassida rubiginosa Müller, 1776 the exuvial-fecal shield was effective against Formica exsectoides, Forel 1886 (Hymenoptera: Formicidae) [54] but not against Polistes dominulusChrist, 1791 (Hymenoptera: Vespidae) [60]. The fecal shield was also not effective for Chelymorpha reimoseriSpaeth, 1928 against Polistes sp. and Piaya cayana Linnaeus, 1766 (Cuculiformes: Coccyzidae) [61]. However, in H. cyanea, the fecal attachment was efficient against the coccinellid Cycloneda sanguinea Linnaeus, 1763 and the hemipteran Stiretrus anchorago Fabricius, 1775 but not against Calleida viridipennis Say, 1823 (Coleoptera: Carabidae) [43].In relation to the scoli, Eisner et al. [54] found evidences in C. rubiginosa that they act in the defense, because when they are touched, the larvae respond by quickly raising their fecal attachment.Most of the Cassidinae larvae seem to have five development stages, likeO. pallidipennis, O. tricolorata [14], Cassida obtusata Boheman, 1854 [62], and M. elatior [10]. However, some species present wide variation in the larval stages [3], arriving in Chelobasis perplexa Baly, 1858 (Hispinae s.str.) at eight development stages. That determination of the number of stages can be made through the measurement of the cephalic capsule [9, 63] or by counting the accumulated exuviae in the exuvial-fecal shield [14].Soon after eclosion, the larvae begin to feed around the egg mass, moving towards the distal end of the leaf. In all of the larval stages feeding on the borders of the leaf towards the petiole was always observed. In the first stages, “they scraped” the parts between the ribbing, leaving the leaf with lacy aspect (Figure3). Starting from the third stage, they fed on the whole leaf (primary and secondary ribs and petiole), changing to another leaf only when the previous was totally eaten. The larvae feed from the abaxial surface, as well as the adaxial surface, always joining after the feeding in cycloalexy, a form of gregariousness [64]. The larval gregariousness provides some advantages to the initial stage larvae, such as ease of feeding, economic use of restricted resource and group protection against their natural enemies [65, 66] thus not having interference of the intraspecific competition, as already mentioned, in the choice of the egg laying site for the female. During the whole developmental period of the juveniles, the female was only observed just feeding when the offspring were in the larval stage. At the end of the fifth stage, the larvae moved via the plant stem and were positioned in a clustered, imbricated manner, fastening the end portion of the abdomen to the branch, to then pupate (Figure 4).Figure 3
Leaf with signs of herbivory caused byOmaspides pallidipennis Boheman, 1854 (Chrysomelidae) in first stages. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).Figure 4
Imbricated pupae ofOmaspides pallidipennis Boheman, 1854 in stem of its host plant Ipomoea alba L. (Convolvulaceae). A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).The larval stage is the longest juvenile stage. For the first cycle, the larval development was26.0±1.5 days (n=19 offspring), counted from eclosion to reaching the pupal stage. In the second cycle the duration was 27.0±2.4 days (n=35 offspring; Table 1). The n sample corresponds to the group of larvae that reached the pupal stage. The time of larval development among the two cycles did not show significant difference (t-test, P=0.0555; df=50.69).During the research, offsprings were seen with number of visibly smaller individuals. It can be considered another factor, besides the predation. Because theO. pallidipennis host plant was under constant sunlight exposure, it is possible that death by dehydration had occurred. Gandolfo et al. [52] reared M. elatior under different temperatures (20°C, 25°C, and 30°C) and their juveniles had faster development at higher temperatures. However, at 30°C the larvae suffered damage, not reaching the pupal stage. Frieiro-Costa and Vasconcellos-Neto [14] suggest that the larvae of O. tricolorataexposed to high temperatures can dehydrate and die.
#### 3.2.3. Pupae
Soon after reaching the pupal stage they presented yellowish coloration, becoming yellowish brown with dispersed dark patches on the body after a period of 24 hours (Figures1(d) and 4). As in the A. languida [36] species O. pallidipennisdid not retain the exuvial-fecal shield at pupation. However, there are Cassidinae species that keep the exuvial-fecal attachment [67] or only the exuviae [68].The pupal stage was the shortest of the development stages. In the first cycle, the duration was8.7±0.8 days (n=20 offspring), presenting an average of 10.2±1.5 days (n=30 offspring) for the following cycle (Table 1). The difference in the time of development between the cycles was highly significant (t-test, P<0.0001; df=45.97), a reason that can be attributed here, as well as in the incubation period, to the variation of the abiotic factors. In the duration of the pupal development time, the larval stage group individuals that reached the subsequent stage were used as a basis. The pre-pupal period was not considered due to the short duration of that stage, which did not allow precise verification.Of 43 studied groups, 35 pupated on the stem, and seven of these pupated on plants other than the host, which were support forI. alba.The eight groups remained pupated on the abaxial leaf surface. Of the groups, 19 were found pupated in areas under sunlight and the others in shaded locations. When the pupas stayed under direct sunlight, they protruded out, probably to increase the air circulation among them. High temperatures can hinder or impede the development of juvenile stages [52].
### 3.3. Adults
The adults are gregarious and they show no apparent sexual dimorphism. Upon emergence, the elytra and pronotum were a translucent yellow color, becoming straw-yellow after total sclerotization, that occurred in approximately seven days. During this period the female stayed close to juveniles on the abaxial leaf surface of the host plant. InH. cyanea, the adult, when emerging, was under its exuvial-fecal shield until total sclerotization of the elytra [43]. Recently emerged adults were not found mating.Juveniles feeding started after about seven days. The adults started feeding from the edges of theI. alba leaf or preexisting holes in the leaf blade.This paper explains the importance of observational studies in the field to understand the biology and ecology of the species. Subsocial Cassidinae provide excellent study material, because they are easily observed since they remain restricted to the development site of the juveniles throughout their development. However, further research should be conducted to further elucidate the relationship between subsocial or non-subsocial Cassidinae and their host plants.
## 3.1. General Aspects of Biology ofO. pallidipennis
Bivoltine Coleoptera,O. pallidipennis began their reproductive and feeding activities in October (spring) and they sought the diapause sites in the middle of April (autumn). During the whole cycle the juveniles only received care by the female that protected them from any imminent danger.Species of subsocial tropical Cassidinae, likeO. pallidipennis, O. tricolorata [14] and Omaspides brunneosignata Boheman, 1854, do not usually present more than two annual generations, because they spend much time and energy taking care of a single group of offspring. For not being exposed to the seasonal extremes that impede reproduction and growth, tropical and subtropical Cassidinae, subsocial or not, can present a greater number of generations [28, 29], if compared to temperate region species that are usually univoltine [30, 31]. Nevertheless, they are exposed to the alterations of the dry and rainy stations, related to the adequate availability of food [32]. In some of those tropical species, the synchronization of the life cycle with the variable conditions is enabled through the diapause [32].In the FLONA of Passa Quatro,O. pallidipennispresented monophagous habits.Adults as well as juveniles only fed on I. alba.Although other plants of the same family and same genus have been found in the CU, those Cassidinae were never observed on another host plant species. Besides O. pallidipennis,egg masses and adults of the solitary species Chelymorpha inflataBoheman, 1854 (Cassidinae: Stolaini) were found also feeding on I. alba.At no time were both species observed feeding on the same leaf. Besides C. inflata,grasshoppers and Chrysomelinae and Lepidoptera larvae were found feeding on the leaves of the chosen host.I. albawas observed in FLONA of Passa Quatro, in an open field area as well as roadside. The specimens of the host plant remained under direct sunlight most of the day, with few shaded portions.
## 3.2. Immature Stages
These insects are holometabolic, their cycle being completed in approximately two months (54.4 days on average, from egg to adult).
### 3.2.1. Eggs
The egg clusters ofO. pallidipennis presents a diamond-shaped format that, with elongated eggs, approximately 2.8 times longer than their highest width and without any covering (Figure 1(a)). When recently laid they presented an amber coloration (Figure 2(a)) later becoming straw-yellow as the hardening of the chorion occurred (Figure 2(b)). That difference in the coloration allowed the distinction of the oldest egg clusters from the most recent. In the first cycle (October to December) the oviposition presented, on average, 55.7±15.5 eggs/egg clusters (n=1,837 eggs in 33 clusters; range 12–80 eggs), and in the second cycle (February to April) the average corresponded to 61.6±14.2 eggs/egg clusters (n=5,607 eggs in 91 clusters; range 13–80 eggs). The ratio between the number of egg masses in the first and second cycles was significantly different (U=1106.00; P=0.0253). The factors for this difference can be attributed to the disparity existent between one female and another regarding their physiological and nutritional state, the nutritional state of the host plant leaves (young leaves, under growth have higher level of nitrogen than the mature leaf) [33], and to the abiotic factors, as the temperature. In many insects, the production of eggs is controlled by one or more hormones produced in the corpora allata, that control the initial stages of oogenesis and the yolk deposition. Factors such as the temperature can act on these structures, thus affecting the egg production [34].Immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae). (a) Egg cluster, (b) dorsal view of last instar larvae, (c) exuvial-fecal shield, (d) pupae in dorsal view. Photos: (a), (b), and (d): Flávia Fernandes.
(a)
(b)
(c)
(d)Omaspides pallidipennis Boheman, 1854 (Chrysomelidae) female (a) on recently laid egg cluster (b) after a few days. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
(a)
(b)Subsocial species of the same genus, likeO. tricolorata [14] and Omaspides convexicollisSpaeth, 1909 [35], also present a large number of eggs per cluster (average of 55.1 and 48.8, resp.), if compared to other non-subsocial species such as Anacassis dubia Boheman, 1854 with an average of 9.1 eggs per cluster and Anacassis languida Boheman, 1854 with an average of 6.7 eggs per cluster [9, 36]. The female of Charidotis punctatostriata Boheman, 1856 produces, annually, an average of 235.5±41 eggs per female [8], a quantity that can be attributed to the high reproductive effort due to the semelparity presented.The large number of eggs in subsocial species can also be explained by the high reproductive effort, because they spend most of their time investing in the defense of the offspring and in resource allocation, instead of going through various ovipositions. However, the subsociality is one of several adaptations aimed at facing adverse conditions [37]. Unlike the physical protection provided to the eggs by the mother, as in Acromis sparsa Boheman, 1854 [38], the non-subsocial Cassidinae can make use of different adaptations, such as the protection of the eggs through an ootheca [39–41] and oootheca and feces [42] or a gelatinous matrix with feces, as in Hemisphaerota cyanea Say, 1824 [43], thus making access more difficult for the natural enemies.Regarding the egg laying site, the ovipositions ofO. pallidipennis were all deposited on the abaxial surface of I. alba, a behavior also present in other subsocial [11, 13, 44, 45] and non-subsocial species [39, 40]. For the species Gratiana spadicea Klug, 1829 and O. tricoloratathis behavioral pattern is related to the temperature [14, 46]. Although it had not been measured, the temperature was also pointed to as a decisive factor of this behavior, because the majority of the host plant leaves were under direct sunlight several hours a day.The choice of the female for the egg laying site is an important factor for the growth and the survival of their larvae [47]. When ovipositing, the female should consider an appropriate place for the development of the juveniles, thus maximizing their adaptive value. Factors such as the predation risk [47, 48], host plant quality or quantity [33, 49], larval mobility [50], and the intraspecific and interspecific competition [51] should be considered. Of the 170 egg masses observed, 159 allowed to know the oviposition site with certainty. Of these, 116 (73%) were found along the midrib and 43 (27%) in other parts of the leaf blade, no egg masses being placed in the proximal half of the petiole. That preference to oviposit in the distal portions can be explained by the presence of predator ants that constantly visited host plant EFNs. Among them several ants of the genus Pseudomyrmex sp. (Formicidae) and Crematogaster sp. (Formicidae) preying on eggs and larvae were found. The oviposition preference on the host plant was not altered by the intraspecific competition, not finding more than one egg mass of the species or of other Cassidinae species on the same leaf.The oviposition peaks occurred during the months of November and February, not observing any new egg masses, in December, January, and April. The average of incubation period of the eggs was19.2±1.4 days (n=31 offspring) for the first cycle and 16.7±1.4 days (n=71 offspring) for the second cycle (Table 1). The incubation time differed significantly in the two cycles (U=239.00; P<0.0001). Characteristics such as abiotic factor variations can explain such difference. In Metriona elatior Klug, 1829 the average incubation time of the eggs is lower at 30°C (5.6 days) than at 20°C (11.3 days) [52]. Another factor to be considered is the quality and the quantity of the host plant that can alter nutrient acquisition, thus interfering in the production of eggs [53]. However, more research is necessary to explain these characteristics.Table 1
Duration of the developmental immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae), for the first and second cycle in a fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
First cycle
Second cycle
Mean ± SD
Mean ± SD
Egg
19.2
±
1.4 (n=31)
16.7
±
1.4 (n=71)
Larvae
26.0
±
1.5 (n=19)
27.0
±
2.4 (n=35)
Pupae
8.7
±
0.8 (n=20)
10.2
±
1.5 (n=30)
Total time
54.3
±
9.0
54.4
±
8.7During the biological cycles, three females oviposited twice during the same cycle. In all those cases their first oviposition had been preyed upon. The time spent between one oviposition and the other varied from 1 to 19 days.
### 3.2.2. Larvae
The larvae ofO. pallidipennisare light yellow, presenting a slightly dorsal-ventrally flat body. There are nine pairs of lateral scoli and a caudal furcae (Figure 1(b)) where the exuvial-fecal shield is attached [18] (Figure 1(c)). In some species of Cassidinae s.str., this structure works as physical protection against dissection and predation [54, 55]. A chemical defense function, through compounds that are present in this attachment, is evidenced, also, in other species [56–58]. Eurypedus nigrosignatusBoheman, 1854 (Cassidinae: Physonotini) obtains those chemical compounds from its host plantCordia curassavica(Jacques) Roemer and Schultes [59]. Studies evidence that these structures have been shown to be efficient against some natural enemies, but not against others. In Cassida rubiginosa Müller, 1776 the exuvial-fecal shield was effective against Formica exsectoides, Forel 1886 (Hymenoptera: Formicidae) [54] but not against Polistes dominulusChrist, 1791 (Hymenoptera: Vespidae) [60]. The fecal shield was also not effective for Chelymorpha reimoseriSpaeth, 1928 against Polistes sp. and Piaya cayana Linnaeus, 1766 (Cuculiformes: Coccyzidae) [61]. However, in H. cyanea, the fecal attachment was efficient against the coccinellid Cycloneda sanguinea Linnaeus, 1763 and the hemipteran Stiretrus anchorago Fabricius, 1775 but not against Calleida viridipennis Say, 1823 (Coleoptera: Carabidae) [43].In relation to the scoli, Eisner et al. [54] found evidences in C. rubiginosa that they act in the defense, because when they are touched, the larvae respond by quickly raising their fecal attachment.Most of the Cassidinae larvae seem to have five development stages, likeO. pallidipennis, O. tricolorata [14], Cassida obtusata Boheman, 1854 [62], and M. elatior [10]. However, some species present wide variation in the larval stages [3], arriving in Chelobasis perplexa Baly, 1858 (Hispinae s.str.) at eight development stages. That determination of the number of stages can be made through the measurement of the cephalic capsule [9, 63] or by counting the accumulated exuviae in the exuvial-fecal shield [14].Soon after eclosion, the larvae begin to feed around the egg mass, moving towards the distal end of the leaf. In all of the larval stages feeding on the borders of the leaf towards the petiole was always observed. In the first stages, “they scraped” the parts between the ribbing, leaving the leaf with lacy aspect (Figure3). Starting from the third stage, they fed on the whole leaf (primary and secondary ribs and petiole), changing to another leaf only when the previous was totally eaten. The larvae feed from the abaxial surface, as well as the adaxial surface, always joining after the feeding in cycloalexy, a form of gregariousness [64]. The larval gregariousness provides some advantages to the initial stage larvae, such as ease of feeding, economic use of restricted resource and group protection against their natural enemies [65, 66] thus not having interference of the intraspecific competition, as already mentioned, in the choice of the egg laying site for the female. During the whole developmental period of the juveniles, the female was only observed just feeding when the offspring were in the larval stage. At the end of the fifth stage, the larvae moved via the plant stem and were positioned in a clustered, imbricated manner, fastening the end portion of the abdomen to the branch, to then pupate (Figure 4).Figure 3
Leaf with signs of herbivory caused byOmaspides pallidipennis Boheman, 1854 (Chrysomelidae) in first stages. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).Figure 4
Imbricated pupae ofOmaspides pallidipennis Boheman, 1854 in stem of its host plant Ipomoea alba L. (Convolvulaceae). A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).The larval stage is the longest juvenile stage. For the first cycle, the larval development was26.0±1.5 days (n=19 offspring), counted from eclosion to reaching the pupal stage. In the second cycle the duration was 27.0±2.4 days (n=35 offspring; Table 1). The n sample corresponds to the group of larvae that reached the pupal stage. The time of larval development among the two cycles did not show significant difference (t-test, P=0.0555; df=50.69).During the research, offsprings were seen with number of visibly smaller individuals. It can be considered another factor, besides the predation. Because theO. pallidipennis host plant was under constant sunlight exposure, it is possible that death by dehydration had occurred. Gandolfo et al. [52] reared M. elatior under different temperatures (20°C, 25°C, and 30°C) and their juveniles had faster development at higher temperatures. However, at 30°C the larvae suffered damage, not reaching the pupal stage. Frieiro-Costa and Vasconcellos-Neto [14] suggest that the larvae of O. tricolorataexposed to high temperatures can dehydrate and die.
### 3.2.3. Pupae
Soon after reaching the pupal stage they presented yellowish coloration, becoming yellowish brown with dispersed dark patches on the body after a period of 24 hours (Figures1(d) and 4). As in the A. languida [36] species O. pallidipennisdid not retain the exuvial-fecal shield at pupation. However, there are Cassidinae species that keep the exuvial-fecal attachment [67] or only the exuviae [68].The pupal stage was the shortest of the development stages. In the first cycle, the duration was8.7±0.8 days (n=20 offspring), presenting an average of 10.2±1.5 days (n=30 offspring) for the following cycle (Table 1). The difference in the time of development between the cycles was highly significant (t-test, P<0.0001; df=45.97), a reason that can be attributed here, as well as in the incubation period, to the variation of the abiotic factors. In the duration of the pupal development time, the larval stage group individuals that reached the subsequent stage were used as a basis. The pre-pupal period was not considered due to the short duration of that stage, which did not allow precise verification.Of 43 studied groups, 35 pupated on the stem, and seven of these pupated on plants other than the host, which were support forI. alba.The eight groups remained pupated on the abaxial leaf surface. Of the groups, 19 were found pupated in areas under sunlight and the others in shaded locations. When the pupas stayed under direct sunlight, they protruded out, probably to increase the air circulation among them. High temperatures can hinder or impede the development of juvenile stages [52].
## 3.2.1. Eggs
The egg clusters ofO. pallidipennis presents a diamond-shaped format that, with elongated eggs, approximately 2.8 times longer than their highest width and without any covering (Figure 1(a)). When recently laid they presented an amber coloration (Figure 2(a)) later becoming straw-yellow as the hardening of the chorion occurred (Figure 2(b)). That difference in the coloration allowed the distinction of the oldest egg clusters from the most recent. In the first cycle (October to December) the oviposition presented, on average, 55.7±15.5 eggs/egg clusters (n=1,837 eggs in 33 clusters; range 12–80 eggs), and in the second cycle (February to April) the average corresponded to 61.6±14.2 eggs/egg clusters (n=5,607 eggs in 91 clusters; range 13–80 eggs). The ratio between the number of egg masses in the first and second cycles was significantly different (U=1106.00; P=0.0253). The factors for this difference can be attributed to the disparity existent between one female and another regarding their physiological and nutritional state, the nutritional state of the host plant leaves (young leaves, under growth have higher level of nitrogen than the mature leaf) [33], and to the abiotic factors, as the temperature. In many insects, the production of eggs is controlled by one or more hormones produced in the corpora allata, that control the initial stages of oogenesis and the yolk deposition. Factors such as the temperature can act on these structures, thus affecting the egg production [34].Immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae). (a) Egg cluster, (b) dorsal view of last instar larvae, (c) exuvial-fecal shield, (d) pupae in dorsal view. Photos: (a), (b), and (d): Flávia Fernandes.
(a)
(b)
(c)
(d)Omaspides pallidipennis Boheman, 1854 (Chrysomelidae) female (a) on recently laid egg cluster (b) after a few days. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
(a)
(b)Subsocial species of the same genus, likeO. tricolorata [14] and Omaspides convexicollisSpaeth, 1909 [35], also present a large number of eggs per cluster (average of 55.1 and 48.8, resp.), if compared to other non-subsocial species such as Anacassis dubia Boheman, 1854 with an average of 9.1 eggs per cluster and Anacassis languida Boheman, 1854 with an average of 6.7 eggs per cluster [9, 36]. The female of Charidotis punctatostriata Boheman, 1856 produces, annually, an average of 235.5±41 eggs per female [8], a quantity that can be attributed to the high reproductive effort due to the semelparity presented.The large number of eggs in subsocial species can also be explained by the high reproductive effort, because they spend most of their time investing in the defense of the offspring and in resource allocation, instead of going through various ovipositions. However, the subsociality is one of several adaptations aimed at facing adverse conditions [37]. Unlike the physical protection provided to the eggs by the mother, as in Acromis sparsa Boheman, 1854 [38], the non-subsocial Cassidinae can make use of different adaptations, such as the protection of the eggs through an ootheca [39–41] and oootheca and feces [42] or a gelatinous matrix with feces, as in Hemisphaerota cyanea Say, 1824 [43], thus making access more difficult for the natural enemies.Regarding the egg laying site, the ovipositions ofO. pallidipennis were all deposited on the abaxial surface of I. alba, a behavior also present in other subsocial [11, 13, 44, 45] and non-subsocial species [39, 40]. For the species Gratiana spadicea Klug, 1829 and O. tricoloratathis behavioral pattern is related to the temperature [14, 46]. Although it had not been measured, the temperature was also pointed to as a decisive factor of this behavior, because the majority of the host plant leaves were under direct sunlight several hours a day.The choice of the female for the egg laying site is an important factor for the growth and the survival of their larvae [47]. When ovipositing, the female should consider an appropriate place for the development of the juveniles, thus maximizing their adaptive value. Factors such as the predation risk [47, 48], host plant quality or quantity [33, 49], larval mobility [50], and the intraspecific and interspecific competition [51] should be considered. Of the 170 egg masses observed, 159 allowed to know the oviposition site with certainty. Of these, 116 (73%) were found along the midrib and 43 (27%) in other parts of the leaf blade, no egg masses being placed in the proximal half of the petiole. That preference to oviposit in the distal portions can be explained by the presence of predator ants that constantly visited host plant EFNs. Among them several ants of the genus Pseudomyrmex sp. (Formicidae) and Crematogaster sp. (Formicidae) preying on eggs and larvae were found. The oviposition preference on the host plant was not altered by the intraspecific competition, not finding more than one egg mass of the species or of other Cassidinae species on the same leaf.The oviposition peaks occurred during the months of November and February, not observing any new egg masses, in December, January, and April. The average of incubation period of the eggs was19.2±1.4 days (n=31 offspring) for the first cycle and 16.7±1.4 days (n=71 offspring) for the second cycle (Table 1). The incubation time differed significantly in the two cycles (U=239.00; P<0.0001). Characteristics such as abiotic factor variations can explain such difference. In Metriona elatior Klug, 1829 the average incubation time of the eggs is lower at 30°C (5.6 days) than at 20°C (11.3 days) [52]. Another factor to be considered is the quality and the quantity of the host plant that can alter nutrient acquisition, thus interfering in the production of eggs [53]. However, more research is necessary to explain these characteristics.Table 1
Duration of the developmental immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae), for the first and second cycle in a fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
First cycle
Second cycle
Mean ± SD
Mean ± SD
Egg
19.2
±
1.4 (n=31)
16.7
±
1.4 (n=71)
Larvae
26.0
±
1.5 (n=19)
27.0
±
2.4 (n=35)
Pupae
8.7
±
0.8 (n=20)
10.2
±
1.5 (n=30)
Total time
54.3
±
9.0
54.4
±
8.7During the biological cycles, three females oviposited twice during the same cycle. In all those cases their first oviposition had been preyed upon. The time spent between one oviposition and the other varied from 1 to 19 days.
## 3.2.2. Larvae
The larvae ofO. pallidipennisare light yellow, presenting a slightly dorsal-ventrally flat body. There are nine pairs of lateral scoli and a caudal furcae (Figure 1(b)) where the exuvial-fecal shield is attached [18] (Figure 1(c)). In some species of Cassidinae s.str., this structure works as physical protection against dissection and predation [54, 55]. A chemical defense function, through compounds that are present in this attachment, is evidenced, also, in other species [56–58]. Eurypedus nigrosignatusBoheman, 1854 (Cassidinae: Physonotini) obtains those chemical compounds from its host plantCordia curassavica(Jacques) Roemer and Schultes [59]. Studies evidence that these structures have been shown to be efficient against some natural enemies, but not against others. In Cassida rubiginosa Müller, 1776 the exuvial-fecal shield was effective against Formica exsectoides, Forel 1886 (Hymenoptera: Formicidae) [54] but not against Polistes dominulusChrist, 1791 (Hymenoptera: Vespidae) [60]. The fecal shield was also not effective for Chelymorpha reimoseriSpaeth, 1928 against Polistes sp. and Piaya cayana Linnaeus, 1766 (Cuculiformes: Coccyzidae) [61]. However, in H. cyanea, the fecal attachment was efficient against the coccinellid Cycloneda sanguinea Linnaeus, 1763 and the hemipteran Stiretrus anchorago Fabricius, 1775 but not against Calleida viridipennis Say, 1823 (Coleoptera: Carabidae) [43].In relation to the scoli, Eisner et al. [54] found evidences in C. rubiginosa that they act in the defense, because when they are touched, the larvae respond by quickly raising their fecal attachment.Most of the Cassidinae larvae seem to have five development stages, likeO. pallidipennis, O. tricolorata [14], Cassida obtusata Boheman, 1854 [62], and M. elatior [10]. However, some species present wide variation in the larval stages [3], arriving in Chelobasis perplexa Baly, 1858 (Hispinae s.str.) at eight development stages. That determination of the number of stages can be made through the measurement of the cephalic capsule [9, 63] or by counting the accumulated exuviae in the exuvial-fecal shield [14].Soon after eclosion, the larvae begin to feed around the egg mass, moving towards the distal end of the leaf. In all of the larval stages feeding on the borders of the leaf towards the petiole was always observed. In the first stages, “they scraped” the parts between the ribbing, leaving the leaf with lacy aspect (Figure3). Starting from the third stage, they fed on the whole leaf (primary and secondary ribs and petiole), changing to another leaf only when the previous was totally eaten. The larvae feed from the abaxial surface, as well as the adaxial surface, always joining after the feeding in cycloalexy, a form of gregariousness [64]. The larval gregariousness provides some advantages to the initial stage larvae, such as ease of feeding, economic use of restricted resource and group protection against their natural enemies [65, 66] thus not having interference of the intraspecific competition, as already mentioned, in the choice of the egg laying site for the female. During the whole developmental period of the juveniles, the female was only observed just feeding when the offspring were in the larval stage. At the end of the fifth stage, the larvae moved via the plant stem and were positioned in a clustered, imbricated manner, fastening the end portion of the abdomen to the branch, to then pupate (Figure 4).Figure 3
Leaf with signs of herbivory caused byOmaspides pallidipennis Boheman, 1854 (Chrysomelidae) in first stages. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).Figure 4
Imbricated pupae ofOmaspides pallidipennis Boheman, 1854 in stem of its host plant Ipomoea alba L. (Convolvulaceae). A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).The larval stage is the longest juvenile stage. For the first cycle, the larval development was26.0±1.5 days (n=19 offspring), counted from eclosion to reaching the pupal stage. In the second cycle the duration was 27.0±2.4 days (n=35 offspring; Table 1). The n sample corresponds to the group of larvae that reached the pupal stage. The time of larval development among the two cycles did not show significant difference (t-test, P=0.0555; df=50.69).During the research, offsprings were seen with number of visibly smaller individuals. It can be considered another factor, besides the predation. Because theO. pallidipennis host plant was under constant sunlight exposure, it is possible that death by dehydration had occurred. Gandolfo et al. [52] reared M. elatior under different temperatures (20°C, 25°C, and 30°C) and their juveniles had faster development at higher temperatures. However, at 30°C the larvae suffered damage, not reaching the pupal stage. Frieiro-Costa and Vasconcellos-Neto [14] suggest that the larvae of O. tricolorataexposed to high temperatures can dehydrate and die.
## 3.2.3. Pupae
Soon after reaching the pupal stage they presented yellowish coloration, becoming yellowish brown with dispersed dark patches on the body after a period of 24 hours (Figures1(d) and 4). As in the A. languida [36] species O. pallidipennisdid not retain the exuvial-fecal shield at pupation. However, there are Cassidinae species that keep the exuvial-fecal attachment [67] or only the exuviae [68].The pupal stage was the shortest of the development stages. In the first cycle, the duration was8.7±0.8 days (n=20 offspring), presenting an average of 10.2±1.5 days (n=30 offspring) for the following cycle (Table 1). The difference in the time of development between the cycles was highly significant (t-test, P<0.0001; df=45.97), a reason that can be attributed here, as well as in the incubation period, to the variation of the abiotic factors. In the duration of the pupal development time, the larval stage group individuals that reached the subsequent stage were used as a basis. The pre-pupal period was not considered due to the short duration of that stage, which did not allow precise verification.Of 43 studied groups, 35 pupated on the stem, and seven of these pupated on plants other than the host, which were support forI. alba.The eight groups remained pupated on the abaxial leaf surface. Of the groups, 19 were found pupated in areas under sunlight and the others in shaded locations. When the pupas stayed under direct sunlight, they protruded out, probably to increase the air circulation among them. High temperatures can hinder or impede the development of juvenile stages [52].
## 3.3. Adults
The adults are gregarious and they show no apparent sexual dimorphism. Upon emergence, the elytra and pronotum were a translucent yellow color, becoming straw-yellow after total sclerotization, that occurred in approximately seven days. During this period the female stayed close to juveniles on the abaxial leaf surface of the host plant. InH. cyanea, the adult, when emerging, was under its exuvial-fecal shield until total sclerotization of the elytra [43]. Recently emerged adults were not found mating.Juveniles feeding started after about seven days. The adults started feeding from the edges of theI. alba leaf or preexisting holes in the leaf blade.This paper explains the importance of observational studies in the field to understand the biology and ecology of the species. Subsocial Cassidinae provide excellent study material, because they are easily observed since they remain restricted to the development site of the juveniles throughout their development. However, further research should be conducted to further elucidate the relationship between subsocial or non-subsocial Cassidinae and their host plants.
---
*Source: 290102-2012-11-27.xml* | 290102-2012-11-27_290102-2012-11-27.md | 57,169 | Biology ofOmaspides pallidipennis Boheman, 1854 (Coleoptera: Chrysomelidae: Cassidinae) | Paula A. A. Gomes; Fábio Prezoto; Fernando A. Frieiro-Costa | Psyche
(2012) | Social Sciences & Business | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2012/290102 | 290102-2012-11-27.xml | ---
## Abstract
The biology and the feeding habits of the subsocial speciesOmaspides pallidipennis were studied at the Floresta Nacional de Passa Quatro, MG, Brazil, during the period from October 2010 to April 2011. The species was bivoltine, beginning its reproductive and food cycle in October (spring) and seeking its diapause sites in April (autumn). The juveniles took 54.4 days on average to complete their development, a period in which the female remained close to offspring, only feeding during the larval stage of the juveniles. It is a monophagous species, feeding only on Ipomoea alba Linnaeus (Convolvulaceae). In the first cycle, the average number of eggs was 55.7±15.5 eggs per egg cluster (n=1,837 eggs in 33 clusters) and in the second it was 61.6±14.2 eggs per egg cluster (n=5,607 eggs in 91 clusters). Oviposition peaks were observed in the months of November and February. The average durations of the incubation period and the larval and the pupal development in the first cycle were 19.2±1.4; 26.0±1.5; 8.7±0.8 days, respectively. In the second cycle they wrere 16.7±1.4; 27.0±2.4; 10.2±1.5 days, respectively.
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## Body
## 1. Introduction
The family Chrysomelidae is one of the largest among the insects of the order Coleoptera [1]. Due to its diversity of representatives it is subdivided into 19 subfamilies [2]. Among these Cassidinae stands out for being the second largest in number of species (ca. 6,000 species), with approximately 16% of the diversity [3]. Its representatives also stand out for having unique morphological, ecological and biological characteristics [4]. However, an evident problem that exists regarding that subfamily is the shortage of information regarding the biology of many of its species. Although the majority is solitary, various species are subsocial. The study of those characteristics can explain the determination of the sequence and exact number of transitions among the way of life of the solitary, gregarious, and subsocial species [5]. Moreover, to know the relationship between the performance of the offspring and the egg laying preference, it is essential to understand the population dynamics of herbivore insects, as well as their distribution [6].The majority of existing research on Cassidinae about the biology of the species, solitary or subsocial, was conducted in laboratory [7–10]. In field, the biology of subsocial species is described, minutely, for Acromis sparsa Boheman, 1854 (see, e.g., [11, 12]) and Omaspides tricolorata Boheman, 1854 [13, 14]. However, the number of species that exhibiting that behavior is much higher (16 species described, for the Stolaini and Eugenysini tribes) and should increase, due higher number of researchers working with this theme.For the subsocial speciesOmaspides pallidipennis Boheman, 1854, no data was found on its biology. Information about the description of the pupa and adults were given by Costa Lima [15], also registering the presence of the subsocial behavior [11, 15–18]. As for its distribution in Brazil, the species is found in the states of Espírito Santo, Minas Gerais, Paraná, Rio Grande do Sul, Rio de Janeiro, Santa Catarina, and São Paulo [19], in environment of Atlantic forest, riparian forest, and savanna (Fernando Frieiro-Costa, personal information). In relation to the host plant, information is also scarce. Few information exists of Ipomoea alba Linnaeus, 1753 (Convolvulaceae) as host plant [19, 20]. Although most of the subsocial Cassidinae have been observed in only one type of host plant, some species can be found on different host plants genus. For O. pallidipennis,this fact has not been observed (Fernando Frieiro-Costa, personal information).The objective of the present work was describe the biology ofOmaspides pallidipennisBoheman, 1854 (Coleoptera: Chrysomelidae: Cassidinae) and its relation with host plant, in a natural environment in the Atlantic Forest biome.
## 2. Material and Methods
### 2.1. Study Area
The research was conducted in the Floresta Nacional (FLONA) de Passa Quatro, Municipal district of Passa Quatro, Minas Gerais State, Brazil (22° 23′ S, 44° 56′ O); altitude of 900 m; 335 ha), in an Atlantic Forest recovery area. The Conservation Unit (CU) contains roads that are used by tourists for visitation and by the guards for local patrols. The study was conducted on the host plants that grew on the edge of one of those roadsides.The vegetation of CU is characterized by the insertion of a Semidecidual Seasonal Forest in the Atlantic Forest Biome, with a prevalence of planted plant coverings of pine, araucaria, and eucalyptus. Regionally, besides the Semidecidual Seasonal Forest, the Dense Ombrophylous Forest and Mixed Ombrophylous Forest typologies are found in the area [21]. The climate of the area, according to the Köppen classification, is Cwa-moderate temperatures with hot and rainy summers and dry winters. The climatic data were supplied by the National Institute of Meteorology (INMET) and presented an average temperature of 21.4°C, with precipitation and relative humidity of 291.9 mm and 76%, respectively, for the first life cycle of the species (October/January). For the second cycle (February/April) the temperature, precipitation, and relative humidity averages were 21.6°C, 116.9 mm, and 75%, respectively.
### 2.2. Biological Study ofO. pallidipennis
The population ofO. pallidipennis was observed daily, in the morning and in the afternoon (at alternate times), during the period between the months of October 2010 to April 2011. In this period 170 females with egg masses were accompanied and marked. The females received a mark on their elytron, facilitating the observation of parental care, of number of eggs deposited in each cycle, and of the development duration of the juvenile stages. For the marking of the females the Frieiro-Costa and Vasconcellos-Neto methodology was used [14]. Photographs of the egg masses, when the guardian was not over them, facilitated the obtaining of the average number of eggs. The oviposition and eclosion times were logged. Daylight saving time was not taken into account at any time.
### 2.3. Host Plant
The latescentI. albavine frequently occurs in forest borders.It can also be found in crop areas, where it is a serious competitor of cultivated plants [22]. The flowers are solitary or gathered in groups, with a white or pinkish coloration [23–26]. In the lamina/petiole intersection there are extrafloral nectaries (EFNs) which are constantly visited by various insect species, especially ants. In Brazil this plant can be found in the states of Bahia, Rio de Janeiro, São Paulo, Paraná, Santa Catarina, Rio Grande do Sul, and Ceará [23].
### 2.4. Statistical Analysis
The data were submitted to the Kolmogorov-Smirnov test, to verify the distribution type, being expressed as the average ± standard deviation (SD). To compare the data of number of eggs and developmental time of immatures between one cycle and another, the Student’st-test was used for normal distribution data and the Mann-Whitney test for free distribution. For these analysis the Bioestat version 5.3 software was used [27].
## 2.1. Study Area
The research was conducted in the Floresta Nacional (FLONA) de Passa Quatro, Municipal district of Passa Quatro, Minas Gerais State, Brazil (22° 23′ S, 44° 56′ O); altitude of 900 m; 335 ha), in an Atlantic Forest recovery area. The Conservation Unit (CU) contains roads that are used by tourists for visitation and by the guards for local patrols. The study was conducted on the host plants that grew on the edge of one of those roadsides.The vegetation of CU is characterized by the insertion of a Semidecidual Seasonal Forest in the Atlantic Forest Biome, with a prevalence of planted plant coverings of pine, araucaria, and eucalyptus. Regionally, besides the Semidecidual Seasonal Forest, the Dense Ombrophylous Forest and Mixed Ombrophylous Forest typologies are found in the area [21]. The climate of the area, according to the Köppen classification, is Cwa-moderate temperatures with hot and rainy summers and dry winters. The climatic data were supplied by the National Institute of Meteorology (INMET) and presented an average temperature of 21.4°C, with precipitation and relative humidity of 291.9 mm and 76%, respectively, for the first life cycle of the species (October/January). For the second cycle (February/April) the temperature, precipitation, and relative humidity averages were 21.6°C, 116.9 mm, and 75%, respectively.
## 2.2. Biological Study ofO. pallidipennis
The population ofO. pallidipennis was observed daily, in the morning and in the afternoon (at alternate times), during the period between the months of October 2010 to April 2011. In this period 170 females with egg masses were accompanied and marked. The females received a mark on their elytron, facilitating the observation of parental care, of number of eggs deposited in each cycle, and of the development duration of the juvenile stages. For the marking of the females the Frieiro-Costa and Vasconcellos-Neto methodology was used [14]. Photographs of the egg masses, when the guardian was not over them, facilitated the obtaining of the average number of eggs. The oviposition and eclosion times were logged. Daylight saving time was not taken into account at any time.
## 2.3. Host Plant
The latescentI. albavine frequently occurs in forest borders.It can also be found in crop areas, where it is a serious competitor of cultivated plants [22]. The flowers are solitary or gathered in groups, with a white or pinkish coloration [23–26]. In the lamina/petiole intersection there are extrafloral nectaries (EFNs) which are constantly visited by various insect species, especially ants. In Brazil this plant can be found in the states of Bahia, Rio de Janeiro, São Paulo, Paraná, Santa Catarina, Rio Grande do Sul, and Ceará [23].
## 2.4. Statistical Analysis
The data were submitted to the Kolmogorov-Smirnov test, to verify the distribution type, being expressed as the average ± standard deviation (SD). To compare the data of number of eggs and developmental time of immatures between one cycle and another, the Student’st-test was used for normal distribution data and the Mann-Whitney test for free distribution. For these analysis the Bioestat version 5.3 software was used [27].
## 3. Results and Discussion
### 3.1. General Aspects of Biology ofO. pallidipennis
Bivoltine Coleoptera,O. pallidipennis began their reproductive and feeding activities in October (spring) and they sought the diapause sites in the middle of April (autumn). During the whole cycle the juveniles only received care by the female that protected them from any imminent danger.Species of subsocial tropical Cassidinae, likeO. pallidipennis, O. tricolorata [14] and Omaspides brunneosignata Boheman, 1854, do not usually present more than two annual generations, because they spend much time and energy taking care of a single group of offspring. For not being exposed to the seasonal extremes that impede reproduction and growth, tropical and subtropical Cassidinae, subsocial or not, can present a greater number of generations [28, 29], if compared to temperate region species that are usually univoltine [30, 31]. Nevertheless, they are exposed to the alterations of the dry and rainy stations, related to the adequate availability of food [32]. In some of those tropical species, the synchronization of the life cycle with the variable conditions is enabled through the diapause [32].In the FLONA of Passa Quatro,O. pallidipennispresented monophagous habits.Adults as well as juveniles only fed on I. alba.Although other plants of the same family and same genus have been found in the CU, those Cassidinae were never observed on another host plant species. Besides O. pallidipennis,egg masses and adults of the solitary species Chelymorpha inflataBoheman, 1854 (Cassidinae: Stolaini) were found also feeding on I. alba.At no time were both species observed feeding on the same leaf. Besides C. inflata,grasshoppers and Chrysomelinae and Lepidoptera larvae were found feeding on the leaves of the chosen host.I. albawas observed in FLONA of Passa Quatro, in an open field area as well as roadside. The specimens of the host plant remained under direct sunlight most of the day, with few shaded portions.
### 3.2. Immature Stages
These insects are holometabolic, their cycle being completed in approximately two months (54.4 days on average, from egg to adult).
#### 3.2.1. Eggs
The egg clusters ofO. pallidipennis presents a diamond-shaped format that, with elongated eggs, approximately 2.8 times longer than their highest width and without any covering (Figure 1(a)). When recently laid they presented an amber coloration (Figure 2(a)) later becoming straw-yellow as the hardening of the chorion occurred (Figure 2(b)). That difference in the coloration allowed the distinction of the oldest egg clusters from the most recent. In the first cycle (October to December) the oviposition presented, on average, 55.7±15.5 eggs/egg clusters (n=1,837 eggs in 33 clusters; range 12–80 eggs), and in the second cycle (February to April) the average corresponded to 61.6±14.2 eggs/egg clusters (n=5,607 eggs in 91 clusters; range 13–80 eggs). The ratio between the number of egg masses in the first and second cycles was significantly different (U=1106.00; P=0.0253). The factors for this difference can be attributed to the disparity existent between one female and another regarding their physiological and nutritional state, the nutritional state of the host plant leaves (young leaves, under growth have higher level of nitrogen than the mature leaf) [33], and to the abiotic factors, as the temperature. In many insects, the production of eggs is controlled by one or more hormones produced in the corpora allata, that control the initial stages of oogenesis and the yolk deposition. Factors such as the temperature can act on these structures, thus affecting the egg production [34].Immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae). (a) Egg cluster, (b) dorsal view of last instar larvae, (c) exuvial-fecal shield, (d) pupae in dorsal view. Photos: (a), (b), and (d): Flávia Fernandes.
(a)
(b)
(c)
(d)Omaspides pallidipennis Boheman, 1854 (Chrysomelidae) female (a) on recently laid egg cluster (b) after a few days. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
(a)
(b)Subsocial species of the same genus, likeO. tricolorata [14] and Omaspides convexicollisSpaeth, 1909 [35], also present a large number of eggs per cluster (average of 55.1 and 48.8, resp.), if compared to other non-subsocial species such as Anacassis dubia Boheman, 1854 with an average of 9.1 eggs per cluster and Anacassis languida Boheman, 1854 with an average of 6.7 eggs per cluster [9, 36]. The female of Charidotis punctatostriata Boheman, 1856 produces, annually, an average of 235.5±41 eggs per female [8], a quantity that can be attributed to the high reproductive effort due to the semelparity presented.The large number of eggs in subsocial species can also be explained by the high reproductive effort, because they spend most of their time investing in the defense of the offspring and in resource allocation, instead of going through various ovipositions. However, the subsociality is one of several adaptations aimed at facing adverse conditions [37]. Unlike the physical protection provided to the eggs by the mother, as in Acromis sparsa Boheman, 1854 [38], the non-subsocial Cassidinae can make use of different adaptations, such as the protection of the eggs through an ootheca [39–41] and oootheca and feces [42] or a gelatinous matrix with feces, as in Hemisphaerota cyanea Say, 1824 [43], thus making access more difficult for the natural enemies.Regarding the egg laying site, the ovipositions ofO. pallidipennis were all deposited on the abaxial surface of I. alba, a behavior also present in other subsocial [11, 13, 44, 45] and non-subsocial species [39, 40]. For the species Gratiana spadicea Klug, 1829 and O. tricoloratathis behavioral pattern is related to the temperature [14, 46]. Although it had not been measured, the temperature was also pointed to as a decisive factor of this behavior, because the majority of the host plant leaves were under direct sunlight several hours a day.The choice of the female for the egg laying site is an important factor for the growth and the survival of their larvae [47]. When ovipositing, the female should consider an appropriate place for the development of the juveniles, thus maximizing their adaptive value. Factors such as the predation risk [47, 48], host plant quality or quantity [33, 49], larval mobility [50], and the intraspecific and interspecific competition [51] should be considered. Of the 170 egg masses observed, 159 allowed to know the oviposition site with certainty. Of these, 116 (73%) were found along the midrib and 43 (27%) in other parts of the leaf blade, no egg masses being placed in the proximal half of the petiole. That preference to oviposit in the distal portions can be explained by the presence of predator ants that constantly visited host plant EFNs. Among them several ants of the genus Pseudomyrmex sp. (Formicidae) and Crematogaster sp. (Formicidae) preying on eggs and larvae were found. The oviposition preference on the host plant was not altered by the intraspecific competition, not finding more than one egg mass of the species or of other Cassidinae species on the same leaf.The oviposition peaks occurred during the months of November and February, not observing any new egg masses, in December, January, and April. The average of incubation period of the eggs was19.2±1.4 days (n=31 offspring) for the first cycle and 16.7±1.4 days (n=71 offspring) for the second cycle (Table 1). The incubation time differed significantly in the two cycles (U=239.00; P<0.0001). Characteristics such as abiotic factor variations can explain such difference. In Metriona elatior Klug, 1829 the average incubation time of the eggs is lower at 30°C (5.6 days) than at 20°C (11.3 days) [52]. Another factor to be considered is the quality and the quantity of the host plant that can alter nutrient acquisition, thus interfering in the production of eggs [53]. However, more research is necessary to explain these characteristics.Table 1
Duration of the developmental immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae), for the first and second cycle in a fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
First cycle
Second cycle
Mean ± SD
Mean ± SD
Egg
19.2
±
1.4 (n=31)
16.7
±
1.4 (n=71)
Larvae
26.0
±
1.5 (n=19)
27.0
±
2.4 (n=35)
Pupae
8.7
±
0.8 (n=20)
10.2
±
1.5 (n=30)
Total time
54.3
±
9.0
54.4
±
8.7During the biological cycles, three females oviposited twice during the same cycle. In all those cases their first oviposition had been preyed upon. The time spent between one oviposition and the other varied from 1 to 19 days.
#### 3.2.2. Larvae
The larvae ofO. pallidipennisare light yellow, presenting a slightly dorsal-ventrally flat body. There are nine pairs of lateral scoli and a caudal furcae (Figure 1(b)) where the exuvial-fecal shield is attached [18] (Figure 1(c)). In some species of Cassidinae s.str., this structure works as physical protection against dissection and predation [54, 55]. A chemical defense function, through compounds that are present in this attachment, is evidenced, also, in other species [56–58]. Eurypedus nigrosignatusBoheman, 1854 (Cassidinae: Physonotini) obtains those chemical compounds from its host plantCordia curassavica(Jacques) Roemer and Schultes [59]. Studies evidence that these structures have been shown to be efficient against some natural enemies, but not against others. In Cassida rubiginosa Müller, 1776 the exuvial-fecal shield was effective against Formica exsectoides, Forel 1886 (Hymenoptera: Formicidae) [54] but not against Polistes dominulusChrist, 1791 (Hymenoptera: Vespidae) [60]. The fecal shield was also not effective for Chelymorpha reimoseriSpaeth, 1928 against Polistes sp. and Piaya cayana Linnaeus, 1766 (Cuculiformes: Coccyzidae) [61]. However, in H. cyanea, the fecal attachment was efficient against the coccinellid Cycloneda sanguinea Linnaeus, 1763 and the hemipteran Stiretrus anchorago Fabricius, 1775 but not against Calleida viridipennis Say, 1823 (Coleoptera: Carabidae) [43].In relation to the scoli, Eisner et al. [54] found evidences in C. rubiginosa that they act in the defense, because when they are touched, the larvae respond by quickly raising their fecal attachment.Most of the Cassidinae larvae seem to have five development stages, likeO. pallidipennis, O. tricolorata [14], Cassida obtusata Boheman, 1854 [62], and M. elatior [10]. However, some species present wide variation in the larval stages [3], arriving in Chelobasis perplexa Baly, 1858 (Hispinae s.str.) at eight development stages. That determination of the number of stages can be made through the measurement of the cephalic capsule [9, 63] or by counting the accumulated exuviae in the exuvial-fecal shield [14].Soon after eclosion, the larvae begin to feed around the egg mass, moving towards the distal end of the leaf. In all of the larval stages feeding on the borders of the leaf towards the petiole was always observed. In the first stages, “they scraped” the parts between the ribbing, leaving the leaf with lacy aspect (Figure3). Starting from the third stage, they fed on the whole leaf (primary and secondary ribs and petiole), changing to another leaf only when the previous was totally eaten. The larvae feed from the abaxial surface, as well as the adaxial surface, always joining after the feeding in cycloalexy, a form of gregariousness [64]. The larval gregariousness provides some advantages to the initial stage larvae, such as ease of feeding, economic use of restricted resource and group protection against their natural enemies [65, 66] thus not having interference of the intraspecific competition, as already mentioned, in the choice of the egg laying site for the female. During the whole developmental period of the juveniles, the female was only observed just feeding when the offspring were in the larval stage. At the end of the fifth stage, the larvae moved via the plant stem and were positioned in a clustered, imbricated manner, fastening the end portion of the abdomen to the branch, to then pupate (Figure 4).Figure 3
Leaf with signs of herbivory caused byOmaspides pallidipennis Boheman, 1854 (Chrysomelidae) in first stages. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).Figure 4
Imbricated pupae ofOmaspides pallidipennis Boheman, 1854 in stem of its host plant Ipomoea alba L. (Convolvulaceae). A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).The larval stage is the longest juvenile stage. For the first cycle, the larval development was26.0±1.5 days (n=19 offspring), counted from eclosion to reaching the pupal stage. In the second cycle the duration was 27.0±2.4 days (n=35 offspring; Table 1). The n sample corresponds to the group of larvae that reached the pupal stage. The time of larval development among the two cycles did not show significant difference (t-test, P=0.0555; df=50.69).During the research, offsprings were seen with number of visibly smaller individuals. It can be considered another factor, besides the predation. Because theO. pallidipennis host plant was under constant sunlight exposure, it is possible that death by dehydration had occurred. Gandolfo et al. [52] reared M. elatior under different temperatures (20°C, 25°C, and 30°C) and their juveniles had faster development at higher temperatures. However, at 30°C the larvae suffered damage, not reaching the pupal stage. Frieiro-Costa and Vasconcellos-Neto [14] suggest that the larvae of O. tricolorataexposed to high temperatures can dehydrate and die.
#### 3.2.3. Pupae
Soon after reaching the pupal stage they presented yellowish coloration, becoming yellowish brown with dispersed dark patches on the body after a period of 24 hours (Figures1(d) and 4). As in the A. languida [36] species O. pallidipennisdid not retain the exuvial-fecal shield at pupation. However, there are Cassidinae species that keep the exuvial-fecal attachment [67] or only the exuviae [68].The pupal stage was the shortest of the development stages. In the first cycle, the duration was8.7±0.8 days (n=20 offspring), presenting an average of 10.2±1.5 days (n=30 offspring) for the following cycle (Table 1). The difference in the time of development between the cycles was highly significant (t-test, P<0.0001; df=45.97), a reason that can be attributed here, as well as in the incubation period, to the variation of the abiotic factors. In the duration of the pupal development time, the larval stage group individuals that reached the subsequent stage were used as a basis. The pre-pupal period was not considered due to the short duration of that stage, which did not allow precise verification.Of 43 studied groups, 35 pupated on the stem, and seven of these pupated on plants other than the host, which were support forI. alba.The eight groups remained pupated on the abaxial leaf surface. Of the groups, 19 were found pupated in areas under sunlight and the others in shaded locations. When the pupas stayed under direct sunlight, they protruded out, probably to increase the air circulation among them. High temperatures can hinder or impede the development of juvenile stages [52].
### 3.3. Adults
The adults are gregarious and they show no apparent sexual dimorphism. Upon emergence, the elytra and pronotum were a translucent yellow color, becoming straw-yellow after total sclerotization, that occurred in approximately seven days. During this period the female stayed close to juveniles on the abaxial leaf surface of the host plant. InH. cyanea, the adult, when emerging, was under its exuvial-fecal shield until total sclerotization of the elytra [43]. Recently emerged adults were not found mating.Juveniles feeding started after about seven days. The adults started feeding from the edges of theI. alba leaf or preexisting holes in the leaf blade.This paper explains the importance of observational studies in the field to understand the biology and ecology of the species. Subsocial Cassidinae provide excellent study material, because they are easily observed since they remain restricted to the development site of the juveniles throughout their development. However, further research should be conducted to further elucidate the relationship between subsocial or non-subsocial Cassidinae and their host plants.
## 3.1. General Aspects of Biology ofO. pallidipennis
Bivoltine Coleoptera,O. pallidipennis began their reproductive and feeding activities in October (spring) and they sought the diapause sites in the middle of April (autumn). During the whole cycle the juveniles only received care by the female that protected them from any imminent danger.Species of subsocial tropical Cassidinae, likeO. pallidipennis, O. tricolorata [14] and Omaspides brunneosignata Boheman, 1854, do not usually present more than two annual generations, because they spend much time and energy taking care of a single group of offspring. For not being exposed to the seasonal extremes that impede reproduction and growth, tropical and subtropical Cassidinae, subsocial or not, can present a greater number of generations [28, 29], if compared to temperate region species that are usually univoltine [30, 31]. Nevertheless, they are exposed to the alterations of the dry and rainy stations, related to the adequate availability of food [32]. In some of those tropical species, the synchronization of the life cycle with the variable conditions is enabled through the diapause [32].In the FLONA of Passa Quatro,O. pallidipennispresented monophagous habits.Adults as well as juveniles only fed on I. alba.Although other plants of the same family and same genus have been found in the CU, those Cassidinae were never observed on another host plant species. Besides O. pallidipennis,egg masses and adults of the solitary species Chelymorpha inflataBoheman, 1854 (Cassidinae: Stolaini) were found also feeding on I. alba.At no time were both species observed feeding on the same leaf. Besides C. inflata,grasshoppers and Chrysomelinae and Lepidoptera larvae were found feeding on the leaves of the chosen host.I. albawas observed in FLONA of Passa Quatro, in an open field area as well as roadside. The specimens of the host plant remained under direct sunlight most of the day, with few shaded portions.
## 3.2. Immature Stages
These insects are holometabolic, their cycle being completed in approximately two months (54.4 days on average, from egg to adult).
### 3.2.1. Eggs
The egg clusters ofO. pallidipennis presents a diamond-shaped format that, with elongated eggs, approximately 2.8 times longer than their highest width and without any covering (Figure 1(a)). When recently laid they presented an amber coloration (Figure 2(a)) later becoming straw-yellow as the hardening of the chorion occurred (Figure 2(b)). That difference in the coloration allowed the distinction of the oldest egg clusters from the most recent. In the first cycle (October to December) the oviposition presented, on average, 55.7±15.5 eggs/egg clusters (n=1,837 eggs in 33 clusters; range 12–80 eggs), and in the second cycle (February to April) the average corresponded to 61.6±14.2 eggs/egg clusters (n=5,607 eggs in 91 clusters; range 13–80 eggs). The ratio between the number of egg masses in the first and second cycles was significantly different (U=1106.00; P=0.0253). The factors for this difference can be attributed to the disparity existent between one female and another regarding their physiological and nutritional state, the nutritional state of the host plant leaves (young leaves, under growth have higher level of nitrogen than the mature leaf) [33], and to the abiotic factors, as the temperature. In many insects, the production of eggs is controlled by one or more hormones produced in the corpora allata, that control the initial stages of oogenesis and the yolk deposition. Factors such as the temperature can act on these structures, thus affecting the egg production [34].Immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae). (a) Egg cluster, (b) dorsal view of last instar larvae, (c) exuvial-fecal shield, (d) pupae in dorsal view. Photos: (a), (b), and (d): Flávia Fernandes.
(a)
(b)
(c)
(d)Omaspides pallidipennis Boheman, 1854 (Chrysomelidae) female (a) on recently laid egg cluster (b) after a few days. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
(a)
(b)Subsocial species of the same genus, likeO. tricolorata [14] and Omaspides convexicollisSpaeth, 1909 [35], also present a large number of eggs per cluster (average of 55.1 and 48.8, resp.), if compared to other non-subsocial species such as Anacassis dubia Boheman, 1854 with an average of 9.1 eggs per cluster and Anacassis languida Boheman, 1854 with an average of 6.7 eggs per cluster [9, 36]. The female of Charidotis punctatostriata Boheman, 1856 produces, annually, an average of 235.5±41 eggs per female [8], a quantity that can be attributed to the high reproductive effort due to the semelparity presented.The large number of eggs in subsocial species can also be explained by the high reproductive effort, because they spend most of their time investing in the defense of the offspring and in resource allocation, instead of going through various ovipositions. However, the subsociality is one of several adaptations aimed at facing adverse conditions [37]. Unlike the physical protection provided to the eggs by the mother, as in Acromis sparsa Boheman, 1854 [38], the non-subsocial Cassidinae can make use of different adaptations, such as the protection of the eggs through an ootheca [39–41] and oootheca and feces [42] or a gelatinous matrix with feces, as in Hemisphaerota cyanea Say, 1824 [43], thus making access more difficult for the natural enemies.Regarding the egg laying site, the ovipositions ofO. pallidipennis were all deposited on the abaxial surface of I. alba, a behavior also present in other subsocial [11, 13, 44, 45] and non-subsocial species [39, 40]. For the species Gratiana spadicea Klug, 1829 and O. tricoloratathis behavioral pattern is related to the temperature [14, 46]. Although it had not been measured, the temperature was also pointed to as a decisive factor of this behavior, because the majority of the host plant leaves were under direct sunlight several hours a day.The choice of the female for the egg laying site is an important factor for the growth and the survival of their larvae [47]. When ovipositing, the female should consider an appropriate place for the development of the juveniles, thus maximizing their adaptive value. Factors such as the predation risk [47, 48], host plant quality or quantity [33, 49], larval mobility [50], and the intraspecific and interspecific competition [51] should be considered. Of the 170 egg masses observed, 159 allowed to know the oviposition site with certainty. Of these, 116 (73%) were found along the midrib and 43 (27%) in other parts of the leaf blade, no egg masses being placed in the proximal half of the petiole. That preference to oviposit in the distal portions can be explained by the presence of predator ants that constantly visited host plant EFNs. Among them several ants of the genus Pseudomyrmex sp. (Formicidae) and Crematogaster sp. (Formicidae) preying on eggs and larvae were found. The oviposition preference on the host plant was not altered by the intraspecific competition, not finding more than one egg mass of the species or of other Cassidinae species on the same leaf.The oviposition peaks occurred during the months of November and February, not observing any new egg masses, in December, January, and April. The average of incubation period of the eggs was19.2±1.4 days (n=31 offspring) for the first cycle and 16.7±1.4 days (n=71 offspring) for the second cycle (Table 1). The incubation time differed significantly in the two cycles (U=239.00; P<0.0001). Characteristics such as abiotic factor variations can explain such difference. In Metriona elatior Klug, 1829 the average incubation time of the eggs is lower at 30°C (5.6 days) than at 20°C (11.3 days) [52]. Another factor to be considered is the quality and the quantity of the host plant that can alter nutrient acquisition, thus interfering in the production of eggs [53]. However, more research is necessary to explain these characteristics.Table 1
Duration of the developmental immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae), for the first and second cycle in a fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
First cycle
Second cycle
Mean ± SD
Mean ± SD
Egg
19.2
±
1.4 (n=31)
16.7
±
1.4 (n=71)
Larvae
26.0
±
1.5 (n=19)
27.0
±
2.4 (n=35)
Pupae
8.7
±
0.8 (n=20)
10.2
±
1.5 (n=30)
Total time
54.3
±
9.0
54.4
±
8.7During the biological cycles, three females oviposited twice during the same cycle. In all those cases their first oviposition had been preyed upon. The time spent between one oviposition and the other varied from 1 to 19 days.
### 3.2.2. Larvae
The larvae ofO. pallidipennisare light yellow, presenting a slightly dorsal-ventrally flat body. There are nine pairs of lateral scoli and a caudal furcae (Figure 1(b)) where the exuvial-fecal shield is attached [18] (Figure 1(c)). In some species of Cassidinae s.str., this structure works as physical protection against dissection and predation [54, 55]. A chemical defense function, through compounds that are present in this attachment, is evidenced, also, in other species [56–58]. Eurypedus nigrosignatusBoheman, 1854 (Cassidinae: Physonotini) obtains those chemical compounds from its host plantCordia curassavica(Jacques) Roemer and Schultes [59]. Studies evidence that these structures have been shown to be efficient against some natural enemies, but not against others. In Cassida rubiginosa Müller, 1776 the exuvial-fecal shield was effective against Formica exsectoides, Forel 1886 (Hymenoptera: Formicidae) [54] but not against Polistes dominulusChrist, 1791 (Hymenoptera: Vespidae) [60]. The fecal shield was also not effective for Chelymorpha reimoseriSpaeth, 1928 against Polistes sp. and Piaya cayana Linnaeus, 1766 (Cuculiformes: Coccyzidae) [61]. However, in H. cyanea, the fecal attachment was efficient against the coccinellid Cycloneda sanguinea Linnaeus, 1763 and the hemipteran Stiretrus anchorago Fabricius, 1775 but not against Calleida viridipennis Say, 1823 (Coleoptera: Carabidae) [43].In relation to the scoli, Eisner et al. [54] found evidences in C. rubiginosa that they act in the defense, because when they are touched, the larvae respond by quickly raising their fecal attachment.Most of the Cassidinae larvae seem to have five development stages, likeO. pallidipennis, O. tricolorata [14], Cassida obtusata Boheman, 1854 [62], and M. elatior [10]. However, some species present wide variation in the larval stages [3], arriving in Chelobasis perplexa Baly, 1858 (Hispinae s.str.) at eight development stages. That determination of the number of stages can be made through the measurement of the cephalic capsule [9, 63] or by counting the accumulated exuviae in the exuvial-fecal shield [14].Soon after eclosion, the larvae begin to feed around the egg mass, moving towards the distal end of the leaf. In all of the larval stages feeding on the borders of the leaf towards the petiole was always observed. In the first stages, “they scraped” the parts between the ribbing, leaving the leaf with lacy aspect (Figure3). Starting from the third stage, they fed on the whole leaf (primary and secondary ribs and petiole), changing to another leaf only when the previous was totally eaten. The larvae feed from the abaxial surface, as well as the adaxial surface, always joining after the feeding in cycloalexy, a form of gregariousness [64]. The larval gregariousness provides some advantages to the initial stage larvae, such as ease of feeding, economic use of restricted resource and group protection against their natural enemies [65, 66] thus not having interference of the intraspecific competition, as already mentioned, in the choice of the egg laying site for the female. During the whole developmental period of the juveniles, the female was only observed just feeding when the offspring were in the larval stage. At the end of the fifth stage, the larvae moved via the plant stem and were positioned in a clustered, imbricated manner, fastening the end portion of the abdomen to the branch, to then pupate (Figure 4).Figure 3
Leaf with signs of herbivory caused byOmaspides pallidipennis Boheman, 1854 (Chrysomelidae) in first stages. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).Figure 4
Imbricated pupae ofOmaspides pallidipennis Boheman, 1854 in stem of its host plant Ipomoea alba L. (Convolvulaceae). A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).The larval stage is the longest juvenile stage. For the first cycle, the larval development was26.0±1.5 days (n=19 offspring), counted from eclosion to reaching the pupal stage. In the second cycle the duration was 27.0±2.4 days (n=35 offspring; Table 1). The n sample corresponds to the group of larvae that reached the pupal stage. The time of larval development among the two cycles did not show significant difference (t-test, P=0.0555; df=50.69).During the research, offsprings were seen with number of visibly smaller individuals. It can be considered another factor, besides the predation. Because theO. pallidipennis host plant was under constant sunlight exposure, it is possible that death by dehydration had occurred. Gandolfo et al. [52] reared M. elatior under different temperatures (20°C, 25°C, and 30°C) and their juveniles had faster development at higher temperatures. However, at 30°C the larvae suffered damage, not reaching the pupal stage. Frieiro-Costa and Vasconcellos-Neto [14] suggest that the larvae of O. tricolorataexposed to high temperatures can dehydrate and die.
### 3.2.3. Pupae
Soon after reaching the pupal stage they presented yellowish coloration, becoming yellowish brown with dispersed dark patches on the body after a period of 24 hours (Figures1(d) and 4). As in the A. languida [36] species O. pallidipennisdid not retain the exuvial-fecal shield at pupation. However, there are Cassidinae species that keep the exuvial-fecal attachment [67] or only the exuviae [68].The pupal stage was the shortest of the development stages. In the first cycle, the duration was8.7±0.8 days (n=20 offspring), presenting an average of 10.2±1.5 days (n=30 offspring) for the following cycle (Table 1). The difference in the time of development between the cycles was highly significant (t-test, P<0.0001; df=45.97), a reason that can be attributed here, as well as in the incubation period, to the variation of the abiotic factors. In the duration of the pupal development time, the larval stage group individuals that reached the subsequent stage were used as a basis. The pre-pupal period was not considered due to the short duration of that stage, which did not allow precise verification.Of 43 studied groups, 35 pupated on the stem, and seven of these pupated on plants other than the host, which were support forI. alba.The eight groups remained pupated on the abaxial leaf surface. Of the groups, 19 were found pupated in areas under sunlight and the others in shaded locations. When the pupas stayed under direct sunlight, they protruded out, probably to increase the air circulation among them. High temperatures can hinder or impede the development of juvenile stages [52].
## 3.2.1. Eggs
The egg clusters ofO. pallidipennis presents a diamond-shaped format that, with elongated eggs, approximately 2.8 times longer than their highest width and without any covering (Figure 1(a)). When recently laid they presented an amber coloration (Figure 2(a)) later becoming straw-yellow as the hardening of the chorion occurred (Figure 2(b)). That difference in the coloration allowed the distinction of the oldest egg clusters from the most recent. In the first cycle (October to December) the oviposition presented, on average, 55.7±15.5 eggs/egg clusters (n=1,837 eggs in 33 clusters; range 12–80 eggs), and in the second cycle (February to April) the average corresponded to 61.6±14.2 eggs/egg clusters (n=5,607 eggs in 91 clusters; range 13–80 eggs). The ratio between the number of egg masses in the first and second cycles was significantly different (U=1106.00; P=0.0253). The factors for this difference can be attributed to the disparity existent between one female and another regarding their physiological and nutritional state, the nutritional state of the host plant leaves (young leaves, under growth have higher level of nitrogen than the mature leaf) [33], and to the abiotic factors, as the temperature. In many insects, the production of eggs is controlled by one or more hormones produced in the corpora allata, that control the initial stages of oogenesis and the yolk deposition. Factors such as the temperature can act on these structures, thus affecting the egg production [34].Immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae). (a) Egg cluster, (b) dorsal view of last instar larvae, (c) exuvial-fecal shield, (d) pupae in dorsal view. Photos: (a), (b), and (d): Flávia Fernandes.
(a)
(b)
(c)
(d)Omaspides pallidipennis Boheman, 1854 (Chrysomelidae) female (a) on recently laid egg cluster (b) after a few days. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
(a)
(b)Subsocial species of the same genus, likeO. tricolorata [14] and Omaspides convexicollisSpaeth, 1909 [35], also present a large number of eggs per cluster (average of 55.1 and 48.8, resp.), if compared to other non-subsocial species such as Anacassis dubia Boheman, 1854 with an average of 9.1 eggs per cluster and Anacassis languida Boheman, 1854 with an average of 6.7 eggs per cluster [9, 36]. The female of Charidotis punctatostriata Boheman, 1856 produces, annually, an average of 235.5±41 eggs per female [8], a quantity that can be attributed to the high reproductive effort due to the semelparity presented.The large number of eggs in subsocial species can also be explained by the high reproductive effort, because they spend most of their time investing in the defense of the offspring and in resource allocation, instead of going through various ovipositions. However, the subsociality is one of several adaptations aimed at facing adverse conditions [37]. Unlike the physical protection provided to the eggs by the mother, as in Acromis sparsa Boheman, 1854 [38], the non-subsocial Cassidinae can make use of different adaptations, such as the protection of the eggs through an ootheca [39–41] and oootheca and feces [42] or a gelatinous matrix with feces, as in Hemisphaerota cyanea Say, 1824 [43], thus making access more difficult for the natural enemies.Regarding the egg laying site, the ovipositions ofO. pallidipennis were all deposited on the abaxial surface of I. alba, a behavior also present in other subsocial [11, 13, 44, 45] and non-subsocial species [39, 40]. For the species Gratiana spadicea Klug, 1829 and O. tricoloratathis behavioral pattern is related to the temperature [14, 46]. Although it had not been measured, the temperature was also pointed to as a decisive factor of this behavior, because the majority of the host plant leaves were under direct sunlight several hours a day.The choice of the female for the egg laying site is an important factor for the growth and the survival of their larvae [47]. When ovipositing, the female should consider an appropriate place for the development of the juveniles, thus maximizing their adaptive value. Factors such as the predation risk [47, 48], host plant quality or quantity [33, 49], larval mobility [50], and the intraspecific and interspecific competition [51] should be considered. Of the 170 egg masses observed, 159 allowed to know the oviposition site with certainty. Of these, 116 (73%) were found along the midrib and 43 (27%) in other parts of the leaf blade, no egg masses being placed in the proximal half of the petiole. That preference to oviposit in the distal portions can be explained by the presence of predator ants that constantly visited host plant EFNs. Among them several ants of the genus Pseudomyrmex sp. (Formicidae) and Crematogaster sp. (Formicidae) preying on eggs and larvae were found. The oviposition preference on the host plant was not altered by the intraspecific competition, not finding more than one egg mass of the species or of other Cassidinae species on the same leaf.The oviposition peaks occurred during the months of November and February, not observing any new egg masses, in December, January, and April. The average of incubation period of the eggs was19.2±1.4 days (n=31 offspring) for the first cycle and 16.7±1.4 days (n=71 offspring) for the second cycle (Table 1). The incubation time differed significantly in the two cycles (U=239.00; P<0.0001). Characteristics such as abiotic factor variations can explain such difference. In Metriona elatior Klug, 1829 the average incubation time of the eggs is lower at 30°C (5.6 days) than at 20°C (11.3 days) [52]. Another factor to be considered is the quality and the quantity of the host plant that can alter nutrient acquisition, thus interfering in the production of eggs [53]. However, more research is necessary to explain these characteristics.Table 1
Duration of the developmental immature stages ofOmaspides pallidipennis Boheman, 1854 (Chrysomelidae), for the first and second cycle in a fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).
First cycle
Second cycle
Mean ± SD
Mean ± SD
Egg
19.2
±
1.4 (n=31)
16.7
±
1.4 (n=71)
Larvae
26.0
±
1.5 (n=19)
27.0
±
2.4 (n=35)
Pupae
8.7
±
0.8 (n=20)
10.2
±
1.5 (n=30)
Total time
54.3
±
9.0
54.4
±
8.7During the biological cycles, three females oviposited twice during the same cycle. In all those cases their first oviposition had been preyed upon. The time spent between one oviposition and the other varied from 1 to 19 days.
## 3.2.2. Larvae
The larvae ofO. pallidipennisare light yellow, presenting a slightly dorsal-ventrally flat body. There are nine pairs of lateral scoli and a caudal furcae (Figure 1(b)) where the exuvial-fecal shield is attached [18] (Figure 1(c)). In some species of Cassidinae s.str., this structure works as physical protection against dissection and predation [54, 55]. A chemical defense function, through compounds that are present in this attachment, is evidenced, also, in other species [56–58]. Eurypedus nigrosignatusBoheman, 1854 (Cassidinae: Physonotini) obtains those chemical compounds from its host plantCordia curassavica(Jacques) Roemer and Schultes [59]. Studies evidence that these structures have been shown to be efficient against some natural enemies, but not against others. In Cassida rubiginosa Müller, 1776 the exuvial-fecal shield was effective against Formica exsectoides, Forel 1886 (Hymenoptera: Formicidae) [54] but not against Polistes dominulusChrist, 1791 (Hymenoptera: Vespidae) [60]. The fecal shield was also not effective for Chelymorpha reimoseriSpaeth, 1928 against Polistes sp. and Piaya cayana Linnaeus, 1766 (Cuculiformes: Coccyzidae) [61]. However, in H. cyanea, the fecal attachment was efficient against the coccinellid Cycloneda sanguinea Linnaeus, 1763 and the hemipteran Stiretrus anchorago Fabricius, 1775 but not against Calleida viridipennis Say, 1823 (Coleoptera: Carabidae) [43].In relation to the scoli, Eisner et al. [54] found evidences in C. rubiginosa that they act in the defense, because when they are touched, the larvae respond by quickly raising their fecal attachment.Most of the Cassidinae larvae seem to have five development stages, likeO. pallidipennis, O. tricolorata [14], Cassida obtusata Boheman, 1854 [62], and M. elatior [10]. However, some species present wide variation in the larval stages [3], arriving in Chelobasis perplexa Baly, 1858 (Hispinae s.str.) at eight development stages. That determination of the number of stages can be made through the measurement of the cephalic capsule [9, 63] or by counting the accumulated exuviae in the exuvial-fecal shield [14].Soon after eclosion, the larvae begin to feed around the egg mass, moving towards the distal end of the leaf. In all of the larval stages feeding on the borders of the leaf towards the petiole was always observed. In the first stages, “they scraped” the parts between the ribbing, leaving the leaf with lacy aspect (Figure3). Starting from the third stage, they fed on the whole leaf (primary and secondary ribs and petiole), changing to another leaf only when the previous was totally eaten. The larvae feed from the abaxial surface, as well as the adaxial surface, always joining after the feeding in cycloalexy, a form of gregariousness [64]. The larval gregariousness provides some advantages to the initial stage larvae, such as ease of feeding, economic use of restricted resource and group protection against their natural enemies [65, 66] thus not having interference of the intraspecific competition, as already mentioned, in the choice of the egg laying site for the female. During the whole developmental period of the juveniles, the female was only observed just feeding when the offspring were in the larval stage. At the end of the fifth stage, the larvae moved via the plant stem and were positioned in a clustered, imbricated manner, fastening the end portion of the abdomen to the branch, to then pupate (Figure 4).Figure 3
Leaf with signs of herbivory caused byOmaspides pallidipennis Boheman, 1854 (Chrysomelidae) in first stages. A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).Figure 4
Imbricated pupae ofOmaspides pallidipennis Boheman, 1854 in stem of its host plant Ipomoea alba L. (Convolvulaceae). A fragment of Atlantic Forest (Floresta Nacional de Passa Quatro, Minas Gerais State, Brazil).The larval stage is the longest juvenile stage. For the first cycle, the larval development was26.0±1.5 days (n=19 offspring), counted from eclosion to reaching the pupal stage. In the second cycle the duration was 27.0±2.4 days (n=35 offspring; Table 1). The n sample corresponds to the group of larvae that reached the pupal stage. The time of larval development among the two cycles did not show significant difference (t-test, P=0.0555; df=50.69).During the research, offsprings were seen with number of visibly smaller individuals. It can be considered another factor, besides the predation. Because theO. pallidipennis host plant was under constant sunlight exposure, it is possible that death by dehydration had occurred. Gandolfo et al. [52] reared M. elatior under different temperatures (20°C, 25°C, and 30°C) and their juveniles had faster development at higher temperatures. However, at 30°C the larvae suffered damage, not reaching the pupal stage. Frieiro-Costa and Vasconcellos-Neto [14] suggest that the larvae of O. tricolorataexposed to high temperatures can dehydrate and die.
## 3.2.3. Pupae
Soon after reaching the pupal stage they presented yellowish coloration, becoming yellowish brown with dispersed dark patches on the body after a period of 24 hours (Figures1(d) and 4). As in the A. languida [36] species O. pallidipennisdid not retain the exuvial-fecal shield at pupation. However, there are Cassidinae species that keep the exuvial-fecal attachment [67] or only the exuviae [68].The pupal stage was the shortest of the development stages. In the first cycle, the duration was8.7±0.8 days (n=20 offspring), presenting an average of 10.2±1.5 days (n=30 offspring) for the following cycle (Table 1). The difference in the time of development between the cycles was highly significant (t-test, P<0.0001; df=45.97), a reason that can be attributed here, as well as in the incubation period, to the variation of the abiotic factors. In the duration of the pupal development time, the larval stage group individuals that reached the subsequent stage were used as a basis. The pre-pupal period was not considered due to the short duration of that stage, which did not allow precise verification.Of 43 studied groups, 35 pupated on the stem, and seven of these pupated on plants other than the host, which were support forI. alba.The eight groups remained pupated on the abaxial leaf surface. Of the groups, 19 were found pupated in areas under sunlight and the others in shaded locations. When the pupas stayed under direct sunlight, they protruded out, probably to increase the air circulation among them. High temperatures can hinder or impede the development of juvenile stages [52].
## 3.3. Adults
The adults are gregarious and they show no apparent sexual dimorphism. Upon emergence, the elytra and pronotum were a translucent yellow color, becoming straw-yellow after total sclerotization, that occurred in approximately seven days. During this period the female stayed close to juveniles on the abaxial leaf surface of the host plant. InH. cyanea, the adult, when emerging, was under its exuvial-fecal shield until total sclerotization of the elytra [43]. Recently emerged adults were not found mating.Juveniles feeding started after about seven days. The adults started feeding from the edges of theI. alba leaf or preexisting holes in the leaf blade.This paper explains the importance of observational studies in the field to understand the biology and ecology of the species. Subsocial Cassidinae provide excellent study material, because they are easily observed since they remain restricted to the development site of the juveniles throughout their development. However, further research should be conducted to further elucidate the relationship between subsocial or non-subsocial Cassidinae and their host plants.
---
*Source: 290102-2012-11-27.xml* | 2012 |
# Improvement in Cerebral and Ocular Hemodynamics Early after Carotid Endarterectomy in Patients of Severe Carotid Artery Stenosis with or without Contralateral Carotid Occlusion
**Authors:** Jian Wang; Weici Wang; Bi Jin; Yanrong Zhang; Ping Xu; Feixiang Xiang; Yi Zheng; Juan Chen; Shi Sheng; Chenxi Ouyang; Yiqing Li
**Journal:** BioMed Research International
(2016)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2016/2901028
---
## Abstract
Purpose. To investigate the alternation in cerebral and ocular blood flow velocity (BFV) in patients of carotid stenosis (CS) with or without contralateral carotid occlusion (CO) early after carotid endarterectomy (CEA).Patients and Methods. Nineteen patients underwent CEA for ≥50% CS. Fourteen patients had the unilateral CS, and five patients had the ipsilateral CS and the contralateral CO. Transcranial Doppler (TCD) and Color Doppler Imaging (CDI) were performed before and early after CEA.Results. In patients with unilateral CS, significant improvements in BFV were observed in anterior cerebral artery (ACA) and middle cerebral artery (MCA) on the ipsilateral side after CEA. In patients of ipsilateral CS and contralateral CO, significant improvements in BFV were observed in the ACA and MCA not only on the ipsilateral side but also on the contralateral side postoperatively. The ipsilateral ophthalmic artery (OA) retrograde flows in two patients were recovered to anterograde direction following CEA. The BFV in short posterior ciliary artery (SPCA) of the ipsilateral side significantly increased postoperatively irrespective of the presence of contralateral CO.Conclusions. CEA improved cerebral anterior circulation hemodynamics especially in patients of unilateral CS and contralateral CO, normalized the OA reverse flow, and increased the blood perfusion of SPCA.
---
## Body
## 1. Introduction
In patients with severe stenosis of internal carotid artery (ICA), carotid endarterectomy (CEA) has been shown to reduce embolic stroke risk [1, 2]. CEA certainly removes the atheromatous plaque in the carotid bifurcation, a possible source of cerebral emboli, and may prevent the progression of a stenosis to occlusion [3, 4]. Moreover, improvement of cerebral perfusion after CEA may further decrease stroke risk by a better washout of cerebral emboli from the border-zone areas [5].Most reports have investigated the cerebral hemodynamic effect of CEA with interest being focused on the side of the operation in patients with unilateral carotid stenosis (CS) [6–8]. Contralateral carotid occlusion (CO) may be considered as a significant risk factor in CEA and results in the opening of cross flow through collateral pathways between two hemispheres. The hemodynamic changes in the hemisphere contralateral to the carotid stenosis (CS) early after CEA have been less studied [9], especially in patients of the severe CS with the contralateral CO [10–12]. The ophthalmic artery (OA) is the first branch of the ICA and can be an important collateral pathway between ICA and external carotid artery (ECA) in conditions of the severe CS and CO [13]. The reverse OA flow from ECA supplies the ipsilateral brain in response to reduced inflow pressure in the OA [14]. Previous studies reported that CEA resulted in significantly increased flow in the OA and that it corrected reversed flow in the OA in patients of severe CS [15–17]. Central retinal artery (CRA) and short posterior ciliary artery (SPCA) are two major terminal branches of OA, supplying all the structures in the orbit. To date, there are no available data on the changes of BFVs in the bilateral CRA and SPCA early after CEA, especially in patients of severe CS with contralateral CO.The purpose of the study was to investigate alterations in cerebral and ocular blood flow in patients of the severe CS with or without the contralateral CO before and early after CEA. Additionally, the influence that ipsilateral CEA exerted on the occluded side was examined. Hemodynamic improvement was determined in the two hemispheres. Cerebral and ocular blood flow can be evaluated by transcranial Doppler (TCD) and Color Doppler Imaging (CDI), respectively. These simple noninvasive techniques provide information on blood flow velocities (BFVs) in cerebral and ocular artery vessels.
## 2. Methods
### 2.1. Subjects
Twenty-four consecutive patients with symptomatic ICA stenosis underwent CEA from November 2012 to October 2015 in our department. Five patients were excluded from this study because of the concurrent vertebral artery stenosis (≥30% diameter reduction). The remaining nineteen patients were finally enrolled in the study. Fourteen patients of the 19 (12 men and 2 women, age 66.2 ± 6.7 years) had unilateral CS (≥50%) with no or mild (<50%) stenosis on the contralateral side. The degree of the ipsilateral CS was 70% ± 12.4%, ranging from 53% to 90%. Five patients of the 19 (3 men and 2 women, age 58.3 ± 9.3 years) had the ipsilateral CS (≥50%) and the contralateral CO. The degree of the ipsilateral CS was 76% ± 15%, ranging from 60% to 91%. Eleven patients were operated on on the right side and eight on the left side. The hospital ethics committee approved the project, and all patients gave their informed consent. Clinical and angiographic manifestations of the patients were shown in Table1.Table 1
Demographic data, risk factor, symptomatic characteristics, and degree of stenosis in the patients.
Patients (n=14)with the unilateral CS
Patients (n=5)with the ipsilateral CS and contralateral CO
Age (years)
66.2 ± 6.7
58.3 ± 9.3
Sex (M/F)
12/2
3/2
Risk factors
Smoking
10 (71.4%)
3 (60%)
Hypertension
9 (64.2%)
3 (60%)
Hyperlipidemia
7 (50%)
3 (60%)
Diabetes mellitus
4 (28.5%)
2 (40%)
CAD
4 (28.5%)
POAD
4 (28.5)
Symptom
TIA including AF
9 (64.2%)
1 (20%)
Minor stroke
5 (35.7%)
3 (60%)
Major stroke
1 (20%)
Degree of CS
50%–60%
4 (28.5%)
60%–70%
3 (21.4%)
2 (40%)
70%–80%
4 (28.5%)
1 (20%)
80%–90%
3 (21.4%)
2 (40%)
CS, carotid stenosis; CO, carotid occlusion; CAD, coronary artery disease; POAD, peripheral obliterative atherosclerotic disease; TIA, transient ischemic attacks; AF, amaurosis fugax.The CS was assessed by duplex ultrasound and confirmed by CT angiography (CTA) of the supraaortic trunks. The degree of CS was calculated as the percentage of diameter reduction on the preoperative CTA. TCD and CDI examination before and 4.48 ± 2.59 days after CEA was a part of routine protocol accepted in our institution. CTA of carotid artery was also performed on the approximately 4th postoperative day to confirm the patent ICA. Neurologic complications during and after CEA were classified as transient ischemic attacks (TIA), minor disabling stroke or stroke lasting less than 7 days, and major stroke. We also registered symptoms of hyperperfusion syndrome (HS), such as headache, seizures, confusion, neurologic deficit, and high blood pressure (systolic blood pressure >150 mmHg/or diastolic blood pressure >90 mmHg). The intra- and perioperative cerebrovascular complications consisted of 2 patients with minor disabling stroke and no patients with HS.
### 2.2. Carotid Endarterectomy
All patients underwent surgery under general anesthesia more than one month after last ischemic attack. A longitudinal incision was made along anterior border of the sternocleidomastoid muscle to expose carotid sheath. Vascular clumps were used to occlude common carotid artery (CCA), ICA, and ECA. CCA and ICA were longitudinally opened along the anterior vessel walls. The atheromatous plaque and nearby intima were carefully removed from the carotid bifurcation. The arterial cutting was closed using patch and then vascular clamps were released. An intraluminal shunt was routinely used during the surgical procedure. The skin incision was eventually closed after ensuing vascular patency.
### 2.3. Transcranial Doppler
Transcranial Doppler sonography was performed by the same person to maintain a constant angle of insonation, with the patient lying in a comfortable supine position, with no visual or acoustic stimulation, in a quiet room. Recording was made using commercially available equipment (DWL Elektronische Systeme GmbH, Sipplingen, Germany) using a 2 Mhz pulsed Doppler probe. Anterior cerebral arteries (ACA), middle cerebral arteries (MCA), and posterior cerebral arteries (PCA) were insonated through the temporal window above the zygomatic arch at depths of 65–75, 50–60, and 60–75 mm, respectively. Basilar artery (BA) were insonated through the foramen magnum at a depth of 60–75 mm. BFV was expressed in cm/s as the peak value of the Doppler velocity spectrum outline (representing maximal flow velocity) over 4.5 s (Vpeak).
### 2.4. Color Doppler Imaging
The same experienced sonographer performed all retrobulbar CDI examinations by means of a color Doppler Imaging device (General Electric, Tokyo, Japan) using a 7.5 Hz multifrequency transducer. Patients were in the supine position with the upper body titled upward at about a 30-degree angle. Peak systolic velocity, defined as the BFV during the systolic phase of the cardiac cycle, and the end diastolic velocity, defined as the BFV at the end of the diastolic phase of the cardiac cycle, were measured in OA, CRA, and SPCA. The OA was identified as the vessel parallel to the nasal border of the optic nerve just after crossing it, the CRA as the vessel within the optic nerve and approximately 2–5 mm behind the globe, and the SPCA as the vessel on the temporal side of the optic nerve approximately 10–15 mm behind the globe.
### 2.5. Statistical Analysis
Pre-CEA and post-CEA parameters were compared separately using two-tailed pairedt-test. AP value of < 0.05 was considered statistically significant.
## 2.1. Subjects
Twenty-four consecutive patients with symptomatic ICA stenosis underwent CEA from November 2012 to October 2015 in our department. Five patients were excluded from this study because of the concurrent vertebral artery stenosis (≥30% diameter reduction). The remaining nineteen patients were finally enrolled in the study. Fourteen patients of the 19 (12 men and 2 women, age 66.2 ± 6.7 years) had unilateral CS (≥50%) with no or mild (<50%) stenosis on the contralateral side. The degree of the ipsilateral CS was 70% ± 12.4%, ranging from 53% to 90%. Five patients of the 19 (3 men and 2 women, age 58.3 ± 9.3 years) had the ipsilateral CS (≥50%) and the contralateral CO. The degree of the ipsilateral CS was 76% ± 15%, ranging from 60% to 91%. Eleven patients were operated on on the right side and eight on the left side. The hospital ethics committee approved the project, and all patients gave their informed consent. Clinical and angiographic manifestations of the patients were shown in Table1.Table 1
Demographic data, risk factor, symptomatic characteristics, and degree of stenosis in the patients.
Patients (n=14)with the unilateral CS
Patients (n=5)with the ipsilateral CS and contralateral CO
Age (years)
66.2 ± 6.7
58.3 ± 9.3
Sex (M/F)
12/2
3/2
Risk factors
Smoking
10 (71.4%)
3 (60%)
Hypertension
9 (64.2%)
3 (60%)
Hyperlipidemia
7 (50%)
3 (60%)
Diabetes mellitus
4 (28.5%)
2 (40%)
CAD
4 (28.5%)
POAD
4 (28.5)
Symptom
TIA including AF
9 (64.2%)
1 (20%)
Minor stroke
5 (35.7%)
3 (60%)
Major stroke
1 (20%)
Degree of CS
50%–60%
4 (28.5%)
60%–70%
3 (21.4%)
2 (40%)
70%–80%
4 (28.5%)
1 (20%)
80%–90%
3 (21.4%)
2 (40%)
CS, carotid stenosis; CO, carotid occlusion; CAD, coronary artery disease; POAD, peripheral obliterative atherosclerotic disease; TIA, transient ischemic attacks; AF, amaurosis fugax.The CS was assessed by duplex ultrasound and confirmed by CT angiography (CTA) of the supraaortic trunks. The degree of CS was calculated as the percentage of diameter reduction on the preoperative CTA. TCD and CDI examination before and 4.48 ± 2.59 days after CEA was a part of routine protocol accepted in our institution. CTA of carotid artery was also performed on the approximately 4th postoperative day to confirm the patent ICA. Neurologic complications during and after CEA were classified as transient ischemic attacks (TIA), minor disabling stroke or stroke lasting less than 7 days, and major stroke. We also registered symptoms of hyperperfusion syndrome (HS), such as headache, seizures, confusion, neurologic deficit, and high blood pressure (systolic blood pressure >150 mmHg/or diastolic blood pressure >90 mmHg). The intra- and perioperative cerebrovascular complications consisted of 2 patients with minor disabling stroke and no patients with HS.
## 2.2. Carotid Endarterectomy
All patients underwent surgery under general anesthesia more than one month after last ischemic attack. A longitudinal incision was made along anterior border of the sternocleidomastoid muscle to expose carotid sheath. Vascular clumps were used to occlude common carotid artery (CCA), ICA, and ECA. CCA and ICA were longitudinally opened along the anterior vessel walls. The atheromatous plaque and nearby intima were carefully removed from the carotid bifurcation. The arterial cutting was closed using patch and then vascular clamps were released. An intraluminal shunt was routinely used during the surgical procedure. The skin incision was eventually closed after ensuing vascular patency.
## 2.3. Transcranial Doppler
Transcranial Doppler sonography was performed by the same person to maintain a constant angle of insonation, with the patient lying in a comfortable supine position, with no visual or acoustic stimulation, in a quiet room. Recording was made using commercially available equipment (DWL Elektronische Systeme GmbH, Sipplingen, Germany) using a 2 Mhz pulsed Doppler probe. Anterior cerebral arteries (ACA), middle cerebral arteries (MCA), and posterior cerebral arteries (PCA) were insonated through the temporal window above the zygomatic arch at depths of 65–75, 50–60, and 60–75 mm, respectively. Basilar artery (BA) were insonated through the foramen magnum at a depth of 60–75 mm. BFV was expressed in cm/s as the peak value of the Doppler velocity spectrum outline (representing maximal flow velocity) over 4.5 s (Vpeak).
## 2.4. Color Doppler Imaging
The same experienced sonographer performed all retrobulbar CDI examinations by means of a color Doppler Imaging device (General Electric, Tokyo, Japan) using a 7.5 Hz multifrequency transducer. Patients were in the supine position with the upper body titled upward at about a 30-degree angle. Peak systolic velocity, defined as the BFV during the systolic phase of the cardiac cycle, and the end diastolic velocity, defined as the BFV at the end of the diastolic phase of the cardiac cycle, were measured in OA, CRA, and SPCA. The OA was identified as the vessel parallel to the nasal border of the optic nerve just after crossing it, the CRA as the vessel within the optic nerve and approximately 2–5 mm behind the globe, and the SPCA as the vessel on the temporal side of the optic nerve approximately 10–15 mm behind the globe.
## 2.5. Statistical Analysis
Pre-CEA and post-CEA parameters were compared separately using two-tailed pairedt-test. AP value of < 0.05 was considered statistically significant.
## 3. Results
### 3.1. The Effect of CEA on Cerebral and Ocular Blood Flow in Patients with Unilateral CS
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA were illustrated in Table2. After CEA, the BFVs in the ipsilateral ACA and MCA increased from 108.02 ± 46.48 and 148.97 ± 77.06 to 126.91 ± 49.38 and 170.45 ± 83.82 cm/s, respectively. No significant differences in BFVs in the contralateral ACA and MCA were found between pre-CEA and post-CEA. Furthermore, no significant changes were seen in the BA and bilateral PCA after CEA.Table 2
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA.
ACA (cm/s)
MCA (cm/s)
PCA (cm/s)
BA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
108.02 ± 46.48
148.97 ± 77.06
64.95 ± 17.73
75.05 ± 14.83
Post-CEA
126.91 ± 49.38#
170.45 ± 83.82#
68.63 ± 17.28
76.07 ± 16.63
P value
0.04406
0.02649
0.36967
0.77792
Contralateral to ICA stenosis
Pre-CEA
121.24 ± 56.10
157.83 ± 57.29
64.61 ± 17.81
75.05 ± 14.83
Post-CEA
122.68 ± 32.08
163.81 ± 56.75
66.71 ± 21.27
76.07 ± 16.63
P value
0.89419
0.35183
0.68156
0.77792
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CEA, carotid endarterectomy; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery; BA, basilar artery.
#
P
<
0.05 versus pre-CEA.Ocular BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA were illustrated in Table3. In one patient undergoing CEA, retrograde flow in the ipsilateral OA was completely recovered to anterograde direction postoperatively. After CEA, the BFV in the ipsilateral SPCA increased from 9.39 ± 2.71 to 12.92 ± 4.01 cm/s. Nonetheless, no significant differences in BFVs in the contralateral SPCA and bilateral CRA were found between pre-CEA and post-CEA.Table 3
Ocular BFV ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA.
OA with retrograde flow (%)
CRA (cm/s)
SPCA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
1/13 (7.6%)
9.81 ± 2.95
9.39 ± 2.71
Post-CEA
0/13 (0%)
12.07 ± 5.10
12.92 ± 4.01#
P value
NA
0.07033
0.00996
Contralateral to ICA stenosis
Pre-CEA
0/13 (0%)
10.67 ± 3.33
10.53 ± 3.75
Post-CEA
0/13 (0%)
12.13 ± 4.31
12.28 ± 4.21
P value
NA
0.25332
0.11588
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CEA, carotid endarterectomy; CRA, central retinal artery; SPCA, short posterior ciliary arteries; OA, ophthalmic artery; NA, not applicable.
#
P
<
0.05 versus pre-CEA.Figure1 showed the CTA of carotid artery, TCD, and ocular CDI of a 67-year-old woman before and after CEA. The patient had an 83% stenosis in the right ICA and underwent the successful right CEA. TCD showed that BFVs in the right ACA and MCA significantly increased postoperatively. CDI demonstrated the recovery of the reverse right OA flow and the markedly increased BFVs in the right SPCA after CEA.Figure 1
A 67-year-old woman complained of the amaurosis fugax and repeated transit ischemic attacks. (a) The patient had an 83% stenosis in the right ICA and experienced the uneventful right CEA. (b) CEA significantly improved the BFVs in the right ACA and MCA. (c) CEA normalized the reverse OA flow from right ECA. (d) CEA substantially improved the BFVs in the right SPCA.
(a)
(b)
(c)
(d)
### 3.2. The Effect of CEA on Cerebral and Ocular Blood Flow in Patients of the Severe CS with the Contralateral CO
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA were shown in Table4. After CEA, the BFVs in the ipsilateral ACA and MCA increased from 95.38 ± 17.17 and 119.01 ± 54.71 to 128.03 ± 29.88 and 154.12 ± 59.54 cm/s, respectively. Similarly, the BFVs in the contralateral ACA and MCA (95.47 ± 20.71 and 114.72 ± 78.33) also significantly increased postoperatively (131.46 ± 47.09 and 153.53 ± 85.06 cm/s). However, no significant changes were seen in the BA and bilateral PCA after CEA.Table 4
Cerebral BFV ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA.
ACA (cm/s)
MCA (cm/s)
PCA (cm/s)
BA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
95.38 ± 17.17
119.01 ± 54.71
60.99 ± 12.45
94.61 ± 21.55
Post-CEA
128.03 ± 29.88#
154.12 ± 59.54#
70.21 ± 24.42
102.94 ± 33.86
P value
0.03489
0.00241
0.19174
0.50623
Contralateral to ICA stenosis
Pre-CEA
95.47 ± 20.71
114.72 ± 78.33
67.02 ± 11.77
94.61 ± 21.55
Post-CEA
131.46 ± 47.09#
153.53 ± 85.06#
70.74 ± 18.99
102.94 ± 33.86
P value
0.04011
0.03536
0.35679
0.50623
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CO, carotid occlusion; CEA, carotid endarterectomy; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery; BA, basilar artery.
#
P
<
0.05 versus pre-CEA.Ocular BFVs ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA were shown in Table5. In one patient undergoing CEA, retrograde OA flow in the ipsilateral side was completely changed to anterograde direction postoperatively. After CEA, the BFVs in the ipsilateral SPCA increased from 7.35 ± 1.36 to 12.4 ± 4.31 cm/s. Nonetheless, no significant differences in BFVs in the contralateral SPCA and bilateral CRA were found between pre-CEA and post-CEA.Table 5
Ocular BFV ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA.
OA with retrograde flow (%)
CRA (cm/s)
SPCA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
1/5 (20%)
7.51 ± 2.02
7.35 ± 1.36
Post-CEA
0/5 (0%)
8.85 ± 2.25
12.4 ± 4.31#
P value
NA
0.38402
0.03723
Contralateral to ICA stenosis
Pre-CEA
1/5 (20%)
6.67 ± 3.06
6.11 ± 1.29
Post-CEA
0/5 (0%)
7.66 ± 3.01
7.56 ± 1.97
P value
NA
0.08432
0.12419
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CO, carotid occlusion; CEA, carotid endarterectomy; CRA, central retinal artery; SPCA, short posterior ciliary arteries; OA, ophthalmic artery; NA, not applicable.
#
P
<
0.05 versus pre-CEA.Figure2 showed the CTA of carotid artery, TCD, and ocular CDI of a 56-year-old man before and after CEA. The patient had an 89% stenosis in the right ICA and a complete occlusion in the left ICA and underwent the successful right CEA. TCD showed that a significant improvement in cerebral BFVs of the ACA and MCA was observed not only in the right treated side but also in the left occluded side after CEA. CDI demonstrated the reversal of the retrograde flow in right OA and the markedly increased BFVs in the right SPCA postoperatively.Figure 2
A 56-year-old man presented with vertigo, dizziness, and hemispheric stroke. (a) The patient had an 89% stenosis in the right ICA and the left ICA total occlusion and experienced the successful right CEA. (b) CEA significantly improved the BFVs in the right and left ACA and MCA. (c) CEA normalized the reverse OA flow from right ECA. (d) CEA substantially improved the BFVs in the right SPCA.
(a)
(b)
(c)
(d)
## 3.1. The Effect of CEA on Cerebral and Ocular Blood Flow in Patients with Unilateral CS
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA were illustrated in Table2. After CEA, the BFVs in the ipsilateral ACA and MCA increased from 108.02 ± 46.48 and 148.97 ± 77.06 to 126.91 ± 49.38 and 170.45 ± 83.82 cm/s, respectively. No significant differences in BFVs in the contralateral ACA and MCA were found between pre-CEA and post-CEA. Furthermore, no significant changes were seen in the BA and bilateral PCA after CEA.Table 2
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA.
ACA (cm/s)
MCA (cm/s)
PCA (cm/s)
BA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
108.02 ± 46.48
148.97 ± 77.06
64.95 ± 17.73
75.05 ± 14.83
Post-CEA
126.91 ± 49.38#
170.45 ± 83.82#
68.63 ± 17.28
76.07 ± 16.63
P value
0.04406
0.02649
0.36967
0.77792
Contralateral to ICA stenosis
Pre-CEA
121.24 ± 56.10
157.83 ± 57.29
64.61 ± 17.81
75.05 ± 14.83
Post-CEA
122.68 ± 32.08
163.81 ± 56.75
66.71 ± 21.27
76.07 ± 16.63
P value
0.89419
0.35183
0.68156
0.77792
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CEA, carotid endarterectomy; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery; BA, basilar artery.
#
P
<
0.05 versus pre-CEA.Ocular BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA were illustrated in Table3. In one patient undergoing CEA, retrograde flow in the ipsilateral OA was completely recovered to anterograde direction postoperatively. After CEA, the BFV in the ipsilateral SPCA increased from 9.39 ± 2.71 to 12.92 ± 4.01 cm/s. Nonetheless, no significant differences in BFVs in the contralateral SPCA and bilateral CRA were found between pre-CEA and post-CEA.Table 3
Ocular BFV ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA.
OA with retrograde flow (%)
CRA (cm/s)
SPCA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
1/13 (7.6%)
9.81 ± 2.95
9.39 ± 2.71
Post-CEA
0/13 (0%)
12.07 ± 5.10
12.92 ± 4.01#
P value
NA
0.07033
0.00996
Contralateral to ICA stenosis
Pre-CEA
0/13 (0%)
10.67 ± 3.33
10.53 ± 3.75
Post-CEA
0/13 (0%)
12.13 ± 4.31
12.28 ± 4.21
P value
NA
0.25332
0.11588
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CEA, carotid endarterectomy; CRA, central retinal artery; SPCA, short posterior ciliary arteries; OA, ophthalmic artery; NA, not applicable.
#
P
<
0.05 versus pre-CEA.Figure1 showed the CTA of carotid artery, TCD, and ocular CDI of a 67-year-old woman before and after CEA. The patient had an 83% stenosis in the right ICA and underwent the successful right CEA. TCD showed that BFVs in the right ACA and MCA significantly increased postoperatively. CDI demonstrated the recovery of the reverse right OA flow and the markedly increased BFVs in the right SPCA after CEA.Figure 1
A 67-year-old woman complained of the amaurosis fugax and repeated transit ischemic attacks. (a) The patient had an 83% stenosis in the right ICA and experienced the uneventful right CEA. (b) CEA significantly improved the BFVs in the right ACA and MCA. (c) CEA normalized the reverse OA flow from right ECA. (d) CEA substantially improved the BFVs in the right SPCA.
(a)
(b)
(c)
(d)
## 3.2. The Effect of CEA on Cerebral and Ocular Blood Flow in Patients of the Severe CS with the Contralateral CO
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA were shown in Table4. After CEA, the BFVs in the ipsilateral ACA and MCA increased from 95.38 ± 17.17 and 119.01 ± 54.71 to 128.03 ± 29.88 and 154.12 ± 59.54 cm/s, respectively. Similarly, the BFVs in the contralateral ACA and MCA (95.47 ± 20.71 and 114.72 ± 78.33) also significantly increased postoperatively (131.46 ± 47.09 and 153.53 ± 85.06 cm/s). However, no significant changes were seen in the BA and bilateral PCA after CEA.Table 4
Cerebral BFV ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA.
ACA (cm/s)
MCA (cm/s)
PCA (cm/s)
BA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
95.38 ± 17.17
119.01 ± 54.71
60.99 ± 12.45
94.61 ± 21.55
Post-CEA
128.03 ± 29.88#
154.12 ± 59.54#
70.21 ± 24.42
102.94 ± 33.86
P value
0.03489
0.00241
0.19174
0.50623
Contralateral to ICA stenosis
Pre-CEA
95.47 ± 20.71
114.72 ± 78.33
67.02 ± 11.77
94.61 ± 21.55
Post-CEA
131.46 ± 47.09#
153.53 ± 85.06#
70.74 ± 18.99
102.94 ± 33.86
P value
0.04011
0.03536
0.35679
0.50623
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CO, carotid occlusion; CEA, carotid endarterectomy; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery; BA, basilar artery.
#
P
<
0.05 versus pre-CEA.Ocular BFVs ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA were shown in Table5. In one patient undergoing CEA, retrograde OA flow in the ipsilateral side was completely changed to anterograde direction postoperatively. After CEA, the BFVs in the ipsilateral SPCA increased from 7.35 ± 1.36 to 12.4 ± 4.31 cm/s. Nonetheless, no significant differences in BFVs in the contralateral SPCA and bilateral CRA were found between pre-CEA and post-CEA.Table 5
Ocular BFV ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA.
OA with retrograde flow (%)
CRA (cm/s)
SPCA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
1/5 (20%)
7.51 ± 2.02
7.35 ± 1.36
Post-CEA
0/5 (0%)
8.85 ± 2.25
12.4 ± 4.31#
P value
NA
0.38402
0.03723
Contralateral to ICA stenosis
Pre-CEA
1/5 (20%)
6.67 ± 3.06
6.11 ± 1.29
Post-CEA
0/5 (0%)
7.66 ± 3.01
7.56 ± 1.97
P value
NA
0.08432
0.12419
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CO, carotid occlusion; CEA, carotid endarterectomy; CRA, central retinal artery; SPCA, short posterior ciliary arteries; OA, ophthalmic artery; NA, not applicable.
#
P
<
0.05 versus pre-CEA.Figure2 showed the CTA of carotid artery, TCD, and ocular CDI of a 56-year-old man before and after CEA. The patient had an 89% stenosis in the right ICA and a complete occlusion in the left ICA and underwent the successful right CEA. TCD showed that a significant improvement in cerebral BFVs of the ACA and MCA was observed not only in the right treated side but also in the left occluded side after CEA. CDI demonstrated the reversal of the retrograde flow in right OA and the markedly increased BFVs in the right SPCA postoperatively.Figure 2
A 56-year-old man presented with vertigo, dizziness, and hemispheric stroke. (a) The patient had an 89% stenosis in the right ICA and the left ICA total occlusion and experienced the successful right CEA. (b) CEA significantly improved the BFVs in the right and left ACA and MCA. (c) CEA normalized the reverse OA flow from right ECA. (d) CEA substantially improved the BFVs in the right SPCA.
(a)
(b)
(c)
(d)
## 4. Discussion
Severe stenosis of the ICA resulted in a decreased arterial pressure distal to stenosis. Under normal circumstances, a decrease in regional cerebral perfusion pressure (CPP) is compensated for by a decrease in peripheral vascular resistance, by means of vasodilation (autoregulation) [18, 19]. As a result, the cerebral blood flow (CBF) can be maintained. Nonetheless, high-grade CS may be associated with the malfunction of vasodilation autoregulation and the exhaustion of the cerebral autoregulatory reserve capacity. Hino et al. reported that significant reduction in CBF was observed in the hemisphere not only ipsilateral but also contralateral to the stenosis in patients with severe ICA stenosis [20]. Van Laar et al. reported that regional CBF in the ipsilateral hemisphere (60.9 ± 16.9 mL/min/100 g) was significantly lower than in the contralateral hemisphere (70.9 ± 11.5) and control subjects (78.7 ± 18.4) in patients with unilateral high-grade ICA stenosis [8]. Meaningfully, CEA for unilateral CS resulted in a significant recovery increase in BFVs of ipsilateral ACA and MCA; and no significant changes were seen in the contralateral ICA, BA, and bilateral PCA in patients of severe unilateral CS. These changes can be interpreted as a consequence of the recovery of normal diameter, blood flow, and CPP in the ipsilateral ICA after CEA.Similar results have been reported on the patients with unilateral severe CS after CEA. Jones et al. reported that ipsilateral supply to the MCA territory increased from 57.3 ± 5.7 to 67.3 ± 5.4 mL/100 g/min immediately after CEA and that a positive correlation was observed between obstruction ratio of ICA and change in supply to the ipsilateral MCA territory from the ipsilateral ICA [6]. van Laar et al. in 2006 reported that volume flow in the ipsilateral ICA increased from 114 ± 17 to 213 ± 17 mL/min, and no significant changes were seen in the contralateral ICA and BA one month after CEA [7]. They were also indicative of a positive correlation between the degree of stenosis and volume flow increase in the treated ICA [7]. van Laar et al. in 2007 demonstrated that regional CBF in the ipsilateral hemisphere increased from 60.9 ± 13.7 to 71.2 ± 13.9 mL/min/100 g one month after CEA [8]. Similarly, Sánchez-Arjona et al. found that MCA flow velocity on the ipsilateral side increased from 49.7 to 62.5 cm/s, and nonsignificant changes were seen on MCA of the contralateral side thirty days after carotid angioplasty stent placement (CAS) for ≥70% unilateral ICA stenosis [21].When the patients suffered from the ipsilateral CS and the contralateral CO, differences in bilateral CPP promote the recruitment of collateral pathways. The ipsilateral ICA can compensate for decreased CPP via the circle of Willis in the contralateral CO. Primary collateral pathways are considered to be contralateral-to-ipsilateral cross flow via the anterior communicating artery and posterior-to-anterior flow via the posterior communicating artery; flow via the OA and leptomeningeal vessels are thought to be secondary collateral pathways recruited when collateral flow through the circle of Willis is inadequate. This study demonstrated a significant increase in bilateral ACA and MCA, and no significant changes were noted in the BA and bilateral PCA after CEA for the ipsilateral CS with the contralateral CO. The increased flow in anterior circulation not in posterior circulation suggests that collateral flow through the anterior circulation is important in the case of CEA-treated CS with the contralateral CO. CEA contralateral to CO increases the CPP in the ipsilateral hemisphere and enhances collateral flow via the anterior communicating artery to the hemisphere on the occluded side.Our findings agreed with some previous studies on cases of severe CS with contralateral CO after CEA. Baracchini et al. found that CEA of the ipsilateral ICA stenosis improved CBF not only on the surgical side but also on the contralateral side of CO, and the proportion of patients with collateral flow via the anterior communicating artery increased significantly from 61.5% before to 89.7% within three months after CEA [10]. Kataoka et al. reported that the mean CBF of the treated side rose from 30.0 ± 7.1 to 34.4 ± 8.3 mL/min/100 g, and the mean CBF of the occluded side similarly rose from 28.3 ± 6.1 to 31.7 ± 6.4 mL/min/100 g eight to ten days after CEA [11]. They also indicated that there are significantly developed cross flow from the anterior communicating artery contributing to the improved CBF of the occluded side after CEA [11]. Rutgers et al. demonstrated that the BFV in the MCA of the occlusion side increased significantly from 71 to 85 mL/min at six months after CEA of the severe CS of the treated side, and the prevalence of collateral flow via the anterior communicating artery to the occlusion side increased significantly from 47% before to 84% after CEA [12].In the study, a significant ocular hemodynamic improvement was observed after CEA, evidenced by the reversal of OA with retrograde flow and the increase in the BFVs of the ipsilateral SPCA. Ocular blood flow alteration occurred in the ipsilateral hemisphere in patients undergoing CEA for the severe CS irrespective of the contralateral CO. The hemodynamic effect of CEA, after removal of an atherosclerotic plaque, is an increase in CPP in the distal ICA. The OA is located downstream of the ICA, and the inflow artery for the OA is the ICA. Severe CS was associated with a marked reduction in OA and CRA flow velocities, which were corrected with successful CEA [15]. Kawaguchi et al. demonstrated that the BFV in OA increased from 9 ± 5 cm/s to 21 ± 5 cm/s one week after CEA [16]. Retrograde OA flow is suggestive of high-grade ICA stenosis and ipsilateral ECA collateralization of the OA with absence of a circle of Willis contribution. Rutgers et al. indicated that the proportion of reversed OA flow ipsilateral to severe CS decreased significantly from 42% before to 5% at six months after CEA [12]. Cohn Jr. et al. reported that eight patients with preoperative OA flow reversal had a return of normal OA flow within one month following CEA [15]. Zbornikova and Skoglund demonstrated that a change in the flow direction from being retrograde to antegrade was noted in 9/10 patients (90%) within forty-eight hours after CEA [17]. As a result, CEA improved chronic ocular ischemic syndrome associated with severe CS by increasing the OA blood flow and correcting the reversed OA flow [16].Asymptomatic patients with substantial CS but no recent neurological symptoms are at increased long-term risk of the stroke, especially in the hemisphere ipsilateral to the CS. CEA has been shown to reduce the risk of ischemic stroke in patients with CS of ≥50% [22, 23]. A multicenter randomised trial involving 3120 patients demonstrated that stroke risks (immediate versus deferred CEA) were 4.1% versus 10.0% at 5-year follow-up and 10.8% versus 16.9% at 10-year follow-up [22]. The reduction in stroke risk following CEA has been correlated with the severity of CS ipsilaterally. Patients with severe CS of ≥70% had a dramatically reduced risk of ipsilateral stroke at eight years of follow-up [23]. CEA in patients with moderate CS of 50–69% yielded a moderate reduction in the risks of stroke [23]. Conversely, patients with stenosis of <50% did not benefit from the CEA [23]. The favorable benefit of CEA is attributable to the removal of the atheromatous plaque, which can be a source of cerebral emboli [3, 4]. Moreover, the improved CBF after CEA augmented the ability of the bloodstream to clear or wash out emboli and microemboli and restored available blood flow to regions rendered ischemic by emboli that block supply arteries [5].The asymptomatic subjects with severe unilateral CS may be associated with an increased rate of cognitive impairment in the hemisphere ipsilateral to CS [24]. The presence of severe unilateral CS had an increased probability of developing cognitive deterioration especially in subjects with an associated hemodynamic impairment [25]. Furthermore, the subjects with asymptomatic bilateral severe CS were more likely to develop cognitive dysfunction compared to subjects with unilateral CS [26, 27]. The main mechanism linking CS and cognitive deterioration may be a result of chronic brain cortex hypoperfusion and impaired cerebrovascular autoregulation due to unfavorable hemodynamic changes [25–27]. CEA removes the atheromatous plaque, restores the CPP, improves the cerebral hemodynamics, and normalizes the cerebral metabolism. It was inferred that this cognitive impairment was improved with CEA [28, 29]. Heyer et al. indicated that CEA resulted in significantly increased CBF and improved cognitive performance as early as one day postoperatively [30]. Fearn et al. found that CEA restored the impaired cerebrovascular reserve and improved cognitive function at two months postoperatively [31]. Picchetto et al. demonstrated that the recanalization of a stenotic carotid improved brain cognitive function by resolving the chronic hypoperfusion at three months following CEA [32].Our study has several limitations. First, the present study is the relatively small sample size. However, the sample size was enough to demonstrate significant improvement in cerebral and ocular hemodynamics after CEA. Second, cerebral and ocular hemodynamics were evaluated four days early after CEA. Further investigation needs to be carried out to clarify the long-term effect of CEA on cerebral and ocular BFVs.
## 5. Conclusions
In patients with unilateral CS undergoing CEA, ipsilateral hemodynamics of anterior circulation were significantly improved postoperatively. CEA contralateral to CO resulted in the significant improvement in hemodynamic of anterior circulation not only on the treated side but also on the occluded side. After CEA for the ipsilateral CS, collateral flow through anterior communicating artery compensated for the hemisphere on the occluded side in patients with the contralateral CO. CEA normalized the OA retrograde flow on the stenotic side and improved the blood flow in the ipsilateral SRCA irrespective of the contralateral CO.
---
*Source: 2901028-2016-08-23.xml* | 2901028-2016-08-23_2901028-2016-08-23.md | 40,186 | Improvement in Cerebral and Ocular Hemodynamics Early after Carotid Endarterectomy in Patients of Severe Carotid Artery Stenosis with or without Contralateral Carotid Occlusion | Jian Wang; Weici Wang; Bi Jin; Yanrong Zhang; Ping Xu; Feixiang Xiang; Yi Zheng; Juan Chen; Shi Sheng; Chenxi Ouyang; Yiqing Li | BioMed Research International
(2016) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2016/2901028 | 2901028-2016-08-23.xml | ---
## Abstract
Purpose. To investigate the alternation in cerebral and ocular blood flow velocity (BFV) in patients of carotid stenosis (CS) with or without contralateral carotid occlusion (CO) early after carotid endarterectomy (CEA).Patients and Methods. Nineteen patients underwent CEA for ≥50% CS. Fourteen patients had the unilateral CS, and five patients had the ipsilateral CS and the contralateral CO. Transcranial Doppler (TCD) and Color Doppler Imaging (CDI) were performed before and early after CEA.Results. In patients with unilateral CS, significant improvements in BFV were observed in anterior cerebral artery (ACA) and middle cerebral artery (MCA) on the ipsilateral side after CEA. In patients of ipsilateral CS and contralateral CO, significant improvements in BFV were observed in the ACA and MCA not only on the ipsilateral side but also on the contralateral side postoperatively. The ipsilateral ophthalmic artery (OA) retrograde flows in two patients were recovered to anterograde direction following CEA. The BFV in short posterior ciliary artery (SPCA) of the ipsilateral side significantly increased postoperatively irrespective of the presence of contralateral CO.Conclusions. CEA improved cerebral anterior circulation hemodynamics especially in patients of unilateral CS and contralateral CO, normalized the OA reverse flow, and increased the blood perfusion of SPCA.
---
## Body
## 1. Introduction
In patients with severe stenosis of internal carotid artery (ICA), carotid endarterectomy (CEA) has been shown to reduce embolic stroke risk [1, 2]. CEA certainly removes the atheromatous plaque in the carotid bifurcation, a possible source of cerebral emboli, and may prevent the progression of a stenosis to occlusion [3, 4]. Moreover, improvement of cerebral perfusion after CEA may further decrease stroke risk by a better washout of cerebral emboli from the border-zone areas [5].Most reports have investigated the cerebral hemodynamic effect of CEA with interest being focused on the side of the operation in patients with unilateral carotid stenosis (CS) [6–8]. Contralateral carotid occlusion (CO) may be considered as a significant risk factor in CEA and results in the opening of cross flow through collateral pathways between two hemispheres. The hemodynamic changes in the hemisphere contralateral to the carotid stenosis (CS) early after CEA have been less studied [9], especially in patients of the severe CS with the contralateral CO [10–12]. The ophthalmic artery (OA) is the first branch of the ICA and can be an important collateral pathway between ICA and external carotid artery (ECA) in conditions of the severe CS and CO [13]. The reverse OA flow from ECA supplies the ipsilateral brain in response to reduced inflow pressure in the OA [14]. Previous studies reported that CEA resulted in significantly increased flow in the OA and that it corrected reversed flow in the OA in patients of severe CS [15–17]. Central retinal artery (CRA) and short posterior ciliary artery (SPCA) are two major terminal branches of OA, supplying all the structures in the orbit. To date, there are no available data on the changes of BFVs in the bilateral CRA and SPCA early after CEA, especially in patients of severe CS with contralateral CO.The purpose of the study was to investigate alterations in cerebral and ocular blood flow in patients of the severe CS with or without the contralateral CO before and early after CEA. Additionally, the influence that ipsilateral CEA exerted on the occluded side was examined. Hemodynamic improvement was determined in the two hemispheres. Cerebral and ocular blood flow can be evaluated by transcranial Doppler (TCD) and Color Doppler Imaging (CDI), respectively. These simple noninvasive techniques provide information on blood flow velocities (BFVs) in cerebral and ocular artery vessels.
## 2. Methods
### 2.1. Subjects
Twenty-four consecutive patients with symptomatic ICA stenosis underwent CEA from November 2012 to October 2015 in our department. Five patients were excluded from this study because of the concurrent vertebral artery stenosis (≥30% diameter reduction). The remaining nineteen patients were finally enrolled in the study. Fourteen patients of the 19 (12 men and 2 women, age 66.2 ± 6.7 years) had unilateral CS (≥50%) with no or mild (<50%) stenosis on the contralateral side. The degree of the ipsilateral CS was 70% ± 12.4%, ranging from 53% to 90%. Five patients of the 19 (3 men and 2 women, age 58.3 ± 9.3 years) had the ipsilateral CS (≥50%) and the contralateral CO. The degree of the ipsilateral CS was 76% ± 15%, ranging from 60% to 91%. Eleven patients were operated on on the right side and eight on the left side. The hospital ethics committee approved the project, and all patients gave their informed consent. Clinical and angiographic manifestations of the patients were shown in Table1.Table 1
Demographic data, risk factor, symptomatic characteristics, and degree of stenosis in the patients.
Patients (n=14)with the unilateral CS
Patients (n=5)with the ipsilateral CS and contralateral CO
Age (years)
66.2 ± 6.7
58.3 ± 9.3
Sex (M/F)
12/2
3/2
Risk factors
Smoking
10 (71.4%)
3 (60%)
Hypertension
9 (64.2%)
3 (60%)
Hyperlipidemia
7 (50%)
3 (60%)
Diabetes mellitus
4 (28.5%)
2 (40%)
CAD
4 (28.5%)
POAD
4 (28.5)
Symptom
TIA including AF
9 (64.2%)
1 (20%)
Minor stroke
5 (35.7%)
3 (60%)
Major stroke
1 (20%)
Degree of CS
50%–60%
4 (28.5%)
60%–70%
3 (21.4%)
2 (40%)
70%–80%
4 (28.5%)
1 (20%)
80%–90%
3 (21.4%)
2 (40%)
CS, carotid stenosis; CO, carotid occlusion; CAD, coronary artery disease; POAD, peripheral obliterative atherosclerotic disease; TIA, transient ischemic attacks; AF, amaurosis fugax.The CS was assessed by duplex ultrasound and confirmed by CT angiography (CTA) of the supraaortic trunks. The degree of CS was calculated as the percentage of diameter reduction on the preoperative CTA. TCD and CDI examination before and 4.48 ± 2.59 days after CEA was a part of routine protocol accepted in our institution. CTA of carotid artery was also performed on the approximately 4th postoperative day to confirm the patent ICA. Neurologic complications during and after CEA were classified as transient ischemic attacks (TIA), minor disabling stroke or stroke lasting less than 7 days, and major stroke. We also registered symptoms of hyperperfusion syndrome (HS), such as headache, seizures, confusion, neurologic deficit, and high blood pressure (systolic blood pressure >150 mmHg/or diastolic blood pressure >90 mmHg). The intra- and perioperative cerebrovascular complications consisted of 2 patients with minor disabling stroke and no patients with HS.
### 2.2. Carotid Endarterectomy
All patients underwent surgery under general anesthesia more than one month after last ischemic attack. A longitudinal incision was made along anterior border of the sternocleidomastoid muscle to expose carotid sheath. Vascular clumps were used to occlude common carotid artery (CCA), ICA, and ECA. CCA and ICA were longitudinally opened along the anterior vessel walls. The atheromatous plaque and nearby intima were carefully removed from the carotid bifurcation. The arterial cutting was closed using patch and then vascular clamps were released. An intraluminal shunt was routinely used during the surgical procedure. The skin incision was eventually closed after ensuing vascular patency.
### 2.3. Transcranial Doppler
Transcranial Doppler sonography was performed by the same person to maintain a constant angle of insonation, with the patient lying in a comfortable supine position, with no visual or acoustic stimulation, in a quiet room. Recording was made using commercially available equipment (DWL Elektronische Systeme GmbH, Sipplingen, Germany) using a 2 Mhz pulsed Doppler probe. Anterior cerebral arteries (ACA), middle cerebral arteries (MCA), and posterior cerebral arteries (PCA) were insonated through the temporal window above the zygomatic arch at depths of 65–75, 50–60, and 60–75 mm, respectively. Basilar artery (BA) were insonated through the foramen magnum at a depth of 60–75 mm. BFV was expressed in cm/s as the peak value of the Doppler velocity spectrum outline (representing maximal flow velocity) over 4.5 s (Vpeak).
### 2.4. Color Doppler Imaging
The same experienced sonographer performed all retrobulbar CDI examinations by means of a color Doppler Imaging device (General Electric, Tokyo, Japan) using a 7.5 Hz multifrequency transducer. Patients were in the supine position with the upper body titled upward at about a 30-degree angle. Peak systolic velocity, defined as the BFV during the systolic phase of the cardiac cycle, and the end diastolic velocity, defined as the BFV at the end of the diastolic phase of the cardiac cycle, were measured in OA, CRA, and SPCA. The OA was identified as the vessel parallel to the nasal border of the optic nerve just after crossing it, the CRA as the vessel within the optic nerve and approximately 2–5 mm behind the globe, and the SPCA as the vessel on the temporal side of the optic nerve approximately 10–15 mm behind the globe.
### 2.5. Statistical Analysis
Pre-CEA and post-CEA parameters were compared separately using two-tailed pairedt-test. AP value of < 0.05 was considered statistically significant.
## 2.1. Subjects
Twenty-four consecutive patients with symptomatic ICA stenosis underwent CEA from November 2012 to October 2015 in our department. Five patients were excluded from this study because of the concurrent vertebral artery stenosis (≥30% diameter reduction). The remaining nineteen patients were finally enrolled in the study. Fourteen patients of the 19 (12 men and 2 women, age 66.2 ± 6.7 years) had unilateral CS (≥50%) with no or mild (<50%) stenosis on the contralateral side. The degree of the ipsilateral CS was 70% ± 12.4%, ranging from 53% to 90%. Five patients of the 19 (3 men and 2 women, age 58.3 ± 9.3 years) had the ipsilateral CS (≥50%) and the contralateral CO. The degree of the ipsilateral CS was 76% ± 15%, ranging from 60% to 91%. Eleven patients were operated on on the right side and eight on the left side. The hospital ethics committee approved the project, and all patients gave their informed consent. Clinical and angiographic manifestations of the patients were shown in Table1.Table 1
Demographic data, risk factor, symptomatic characteristics, and degree of stenosis in the patients.
Patients (n=14)with the unilateral CS
Patients (n=5)with the ipsilateral CS and contralateral CO
Age (years)
66.2 ± 6.7
58.3 ± 9.3
Sex (M/F)
12/2
3/2
Risk factors
Smoking
10 (71.4%)
3 (60%)
Hypertension
9 (64.2%)
3 (60%)
Hyperlipidemia
7 (50%)
3 (60%)
Diabetes mellitus
4 (28.5%)
2 (40%)
CAD
4 (28.5%)
POAD
4 (28.5)
Symptom
TIA including AF
9 (64.2%)
1 (20%)
Minor stroke
5 (35.7%)
3 (60%)
Major stroke
1 (20%)
Degree of CS
50%–60%
4 (28.5%)
60%–70%
3 (21.4%)
2 (40%)
70%–80%
4 (28.5%)
1 (20%)
80%–90%
3 (21.4%)
2 (40%)
CS, carotid stenosis; CO, carotid occlusion; CAD, coronary artery disease; POAD, peripheral obliterative atherosclerotic disease; TIA, transient ischemic attacks; AF, amaurosis fugax.The CS was assessed by duplex ultrasound and confirmed by CT angiography (CTA) of the supraaortic trunks. The degree of CS was calculated as the percentage of diameter reduction on the preoperative CTA. TCD and CDI examination before and 4.48 ± 2.59 days after CEA was a part of routine protocol accepted in our institution. CTA of carotid artery was also performed on the approximately 4th postoperative day to confirm the patent ICA. Neurologic complications during and after CEA were classified as transient ischemic attacks (TIA), minor disabling stroke or stroke lasting less than 7 days, and major stroke. We also registered symptoms of hyperperfusion syndrome (HS), such as headache, seizures, confusion, neurologic deficit, and high blood pressure (systolic blood pressure >150 mmHg/or diastolic blood pressure >90 mmHg). The intra- and perioperative cerebrovascular complications consisted of 2 patients with minor disabling stroke and no patients with HS.
## 2.2. Carotid Endarterectomy
All patients underwent surgery under general anesthesia more than one month after last ischemic attack. A longitudinal incision was made along anterior border of the sternocleidomastoid muscle to expose carotid sheath. Vascular clumps were used to occlude common carotid artery (CCA), ICA, and ECA. CCA and ICA were longitudinally opened along the anterior vessel walls. The atheromatous plaque and nearby intima were carefully removed from the carotid bifurcation. The arterial cutting was closed using patch and then vascular clamps were released. An intraluminal shunt was routinely used during the surgical procedure. The skin incision was eventually closed after ensuing vascular patency.
## 2.3. Transcranial Doppler
Transcranial Doppler sonography was performed by the same person to maintain a constant angle of insonation, with the patient lying in a comfortable supine position, with no visual or acoustic stimulation, in a quiet room. Recording was made using commercially available equipment (DWL Elektronische Systeme GmbH, Sipplingen, Germany) using a 2 Mhz pulsed Doppler probe. Anterior cerebral arteries (ACA), middle cerebral arteries (MCA), and posterior cerebral arteries (PCA) were insonated through the temporal window above the zygomatic arch at depths of 65–75, 50–60, and 60–75 mm, respectively. Basilar artery (BA) were insonated through the foramen magnum at a depth of 60–75 mm. BFV was expressed in cm/s as the peak value of the Doppler velocity spectrum outline (representing maximal flow velocity) over 4.5 s (Vpeak).
## 2.4. Color Doppler Imaging
The same experienced sonographer performed all retrobulbar CDI examinations by means of a color Doppler Imaging device (General Electric, Tokyo, Japan) using a 7.5 Hz multifrequency transducer. Patients were in the supine position with the upper body titled upward at about a 30-degree angle. Peak systolic velocity, defined as the BFV during the systolic phase of the cardiac cycle, and the end diastolic velocity, defined as the BFV at the end of the diastolic phase of the cardiac cycle, were measured in OA, CRA, and SPCA. The OA was identified as the vessel parallel to the nasal border of the optic nerve just after crossing it, the CRA as the vessel within the optic nerve and approximately 2–5 mm behind the globe, and the SPCA as the vessel on the temporal side of the optic nerve approximately 10–15 mm behind the globe.
## 2.5. Statistical Analysis
Pre-CEA and post-CEA parameters were compared separately using two-tailed pairedt-test. AP value of < 0.05 was considered statistically significant.
## 3. Results
### 3.1. The Effect of CEA on Cerebral and Ocular Blood Flow in Patients with Unilateral CS
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA were illustrated in Table2. After CEA, the BFVs in the ipsilateral ACA and MCA increased from 108.02 ± 46.48 and 148.97 ± 77.06 to 126.91 ± 49.38 and 170.45 ± 83.82 cm/s, respectively. No significant differences in BFVs in the contralateral ACA and MCA were found between pre-CEA and post-CEA. Furthermore, no significant changes were seen in the BA and bilateral PCA after CEA.Table 2
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA.
ACA (cm/s)
MCA (cm/s)
PCA (cm/s)
BA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
108.02 ± 46.48
148.97 ± 77.06
64.95 ± 17.73
75.05 ± 14.83
Post-CEA
126.91 ± 49.38#
170.45 ± 83.82#
68.63 ± 17.28
76.07 ± 16.63
P value
0.04406
0.02649
0.36967
0.77792
Contralateral to ICA stenosis
Pre-CEA
121.24 ± 56.10
157.83 ± 57.29
64.61 ± 17.81
75.05 ± 14.83
Post-CEA
122.68 ± 32.08
163.81 ± 56.75
66.71 ± 21.27
76.07 ± 16.63
P value
0.89419
0.35183
0.68156
0.77792
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CEA, carotid endarterectomy; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery; BA, basilar artery.
#
P
<
0.05 versus pre-CEA.Ocular BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA were illustrated in Table3. In one patient undergoing CEA, retrograde flow in the ipsilateral OA was completely recovered to anterograde direction postoperatively. After CEA, the BFV in the ipsilateral SPCA increased from 9.39 ± 2.71 to 12.92 ± 4.01 cm/s. Nonetheless, no significant differences in BFVs in the contralateral SPCA and bilateral CRA were found between pre-CEA and post-CEA.Table 3
Ocular BFV ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA.
OA with retrograde flow (%)
CRA (cm/s)
SPCA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
1/13 (7.6%)
9.81 ± 2.95
9.39 ± 2.71
Post-CEA
0/13 (0%)
12.07 ± 5.10
12.92 ± 4.01#
P value
NA
0.07033
0.00996
Contralateral to ICA stenosis
Pre-CEA
0/13 (0%)
10.67 ± 3.33
10.53 ± 3.75
Post-CEA
0/13 (0%)
12.13 ± 4.31
12.28 ± 4.21
P value
NA
0.25332
0.11588
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CEA, carotid endarterectomy; CRA, central retinal artery; SPCA, short posterior ciliary arteries; OA, ophthalmic artery; NA, not applicable.
#
P
<
0.05 versus pre-CEA.Figure1 showed the CTA of carotid artery, TCD, and ocular CDI of a 67-year-old woman before and after CEA. The patient had an 83% stenosis in the right ICA and underwent the successful right CEA. TCD showed that BFVs in the right ACA and MCA significantly increased postoperatively. CDI demonstrated the recovery of the reverse right OA flow and the markedly increased BFVs in the right SPCA after CEA.Figure 1
A 67-year-old woman complained of the amaurosis fugax and repeated transit ischemic attacks. (a) The patient had an 83% stenosis in the right ICA and experienced the uneventful right CEA. (b) CEA significantly improved the BFVs in the right ACA and MCA. (c) CEA normalized the reverse OA flow from right ECA. (d) CEA substantially improved the BFVs in the right SPCA.
(a)
(b)
(c)
(d)
### 3.2. The Effect of CEA on Cerebral and Ocular Blood Flow in Patients of the Severe CS with the Contralateral CO
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA were shown in Table4. After CEA, the BFVs in the ipsilateral ACA and MCA increased from 95.38 ± 17.17 and 119.01 ± 54.71 to 128.03 ± 29.88 and 154.12 ± 59.54 cm/s, respectively. Similarly, the BFVs in the contralateral ACA and MCA (95.47 ± 20.71 and 114.72 ± 78.33) also significantly increased postoperatively (131.46 ± 47.09 and 153.53 ± 85.06 cm/s). However, no significant changes were seen in the BA and bilateral PCA after CEA.Table 4
Cerebral BFV ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA.
ACA (cm/s)
MCA (cm/s)
PCA (cm/s)
BA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
95.38 ± 17.17
119.01 ± 54.71
60.99 ± 12.45
94.61 ± 21.55
Post-CEA
128.03 ± 29.88#
154.12 ± 59.54#
70.21 ± 24.42
102.94 ± 33.86
P value
0.03489
0.00241
0.19174
0.50623
Contralateral to ICA stenosis
Pre-CEA
95.47 ± 20.71
114.72 ± 78.33
67.02 ± 11.77
94.61 ± 21.55
Post-CEA
131.46 ± 47.09#
153.53 ± 85.06#
70.74 ± 18.99
102.94 ± 33.86
P value
0.04011
0.03536
0.35679
0.50623
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CO, carotid occlusion; CEA, carotid endarterectomy; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery; BA, basilar artery.
#
P
<
0.05 versus pre-CEA.Ocular BFVs ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA were shown in Table5. In one patient undergoing CEA, retrograde OA flow in the ipsilateral side was completely changed to anterograde direction postoperatively. After CEA, the BFVs in the ipsilateral SPCA increased from 7.35 ± 1.36 to 12.4 ± 4.31 cm/s. Nonetheless, no significant differences in BFVs in the contralateral SPCA and bilateral CRA were found between pre-CEA and post-CEA.Table 5
Ocular BFV ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA.
OA with retrograde flow (%)
CRA (cm/s)
SPCA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
1/5 (20%)
7.51 ± 2.02
7.35 ± 1.36
Post-CEA
0/5 (0%)
8.85 ± 2.25
12.4 ± 4.31#
P value
NA
0.38402
0.03723
Contralateral to ICA stenosis
Pre-CEA
1/5 (20%)
6.67 ± 3.06
6.11 ± 1.29
Post-CEA
0/5 (0%)
7.66 ± 3.01
7.56 ± 1.97
P value
NA
0.08432
0.12419
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CO, carotid occlusion; CEA, carotid endarterectomy; CRA, central retinal artery; SPCA, short posterior ciliary arteries; OA, ophthalmic artery; NA, not applicable.
#
P
<
0.05 versus pre-CEA.Figure2 showed the CTA of carotid artery, TCD, and ocular CDI of a 56-year-old man before and after CEA. The patient had an 89% stenosis in the right ICA and a complete occlusion in the left ICA and underwent the successful right CEA. TCD showed that a significant improvement in cerebral BFVs of the ACA and MCA was observed not only in the right treated side but also in the left occluded side after CEA. CDI demonstrated the reversal of the retrograde flow in right OA and the markedly increased BFVs in the right SPCA postoperatively.Figure 2
A 56-year-old man presented with vertigo, dizziness, and hemispheric stroke. (a) The patient had an 89% stenosis in the right ICA and the left ICA total occlusion and experienced the successful right CEA. (b) CEA significantly improved the BFVs in the right and left ACA and MCA. (c) CEA normalized the reverse OA flow from right ECA. (d) CEA substantially improved the BFVs in the right SPCA.
(a)
(b)
(c)
(d)
## 3.1. The Effect of CEA on Cerebral and Ocular Blood Flow in Patients with Unilateral CS
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA were illustrated in Table2. After CEA, the BFVs in the ipsilateral ACA and MCA increased from 108.02 ± 46.48 and 148.97 ± 77.06 to 126.91 ± 49.38 and 170.45 ± 83.82 cm/s, respectively. No significant differences in BFVs in the contralateral ACA and MCA were found between pre-CEA and post-CEA. Furthermore, no significant changes were seen in the BA and bilateral PCA after CEA.Table 2
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA.
ACA (cm/s)
MCA (cm/s)
PCA (cm/s)
BA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
108.02 ± 46.48
148.97 ± 77.06
64.95 ± 17.73
75.05 ± 14.83
Post-CEA
126.91 ± 49.38#
170.45 ± 83.82#
68.63 ± 17.28
76.07 ± 16.63
P value
0.04406
0.02649
0.36967
0.77792
Contralateral to ICA stenosis
Pre-CEA
121.24 ± 56.10
157.83 ± 57.29
64.61 ± 17.81
75.05 ± 14.83
Post-CEA
122.68 ± 32.08
163.81 ± 56.75
66.71 ± 21.27
76.07 ± 16.63
P value
0.89419
0.35183
0.68156
0.77792
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CEA, carotid endarterectomy; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery; BA, basilar artery.
#
P
<
0.05 versus pre-CEA.Ocular BFVs ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA were illustrated in Table3. In one patient undergoing CEA, retrograde flow in the ipsilateral OA was completely recovered to anterograde direction postoperatively. After CEA, the BFV in the ipsilateral SPCA increased from 9.39 ± 2.71 to 12.92 ± 4.01 cm/s. Nonetheless, no significant differences in BFVs in the contralateral SPCA and bilateral CRA were found between pre-CEA and post-CEA.Table 3
Ocular BFV ipsilateral and contralateral to ICA stenosis in patients with unilateral CS after and before CEA.
OA with retrograde flow (%)
CRA (cm/s)
SPCA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
1/13 (7.6%)
9.81 ± 2.95
9.39 ± 2.71
Post-CEA
0/13 (0%)
12.07 ± 5.10
12.92 ± 4.01#
P value
NA
0.07033
0.00996
Contralateral to ICA stenosis
Pre-CEA
0/13 (0%)
10.67 ± 3.33
10.53 ± 3.75
Post-CEA
0/13 (0%)
12.13 ± 4.31
12.28 ± 4.21
P value
NA
0.25332
0.11588
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CEA, carotid endarterectomy; CRA, central retinal artery; SPCA, short posterior ciliary arteries; OA, ophthalmic artery; NA, not applicable.
#
P
<
0.05 versus pre-CEA.Figure1 showed the CTA of carotid artery, TCD, and ocular CDI of a 67-year-old woman before and after CEA. The patient had an 83% stenosis in the right ICA and underwent the successful right CEA. TCD showed that BFVs in the right ACA and MCA significantly increased postoperatively. CDI demonstrated the recovery of the reverse right OA flow and the markedly increased BFVs in the right SPCA after CEA.Figure 1
A 67-year-old woman complained of the amaurosis fugax and repeated transit ischemic attacks. (a) The patient had an 83% stenosis in the right ICA and experienced the uneventful right CEA. (b) CEA significantly improved the BFVs in the right ACA and MCA. (c) CEA normalized the reverse OA flow from right ECA. (d) CEA substantially improved the BFVs in the right SPCA.
(a)
(b)
(c)
(d)
## 3.2. The Effect of CEA on Cerebral and Ocular Blood Flow in Patients of the Severe CS with the Contralateral CO
Cerebral BFVs ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA were shown in Table4. After CEA, the BFVs in the ipsilateral ACA and MCA increased from 95.38 ± 17.17 and 119.01 ± 54.71 to 128.03 ± 29.88 and 154.12 ± 59.54 cm/s, respectively. Similarly, the BFVs in the contralateral ACA and MCA (95.47 ± 20.71 and 114.72 ± 78.33) also significantly increased postoperatively (131.46 ± 47.09 and 153.53 ± 85.06 cm/s). However, no significant changes were seen in the BA and bilateral PCA after CEA.Table 4
Cerebral BFV ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA.
ACA (cm/s)
MCA (cm/s)
PCA (cm/s)
BA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
95.38 ± 17.17
119.01 ± 54.71
60.99 ± 12.45
94.61 ± 21.55
Post-CEA
128.03 ± 29.88#
154.12 ± 59.54#
70.21 ± 24.42
102.94 ± 33.86
P value
0.03489
0.00241
0.19174
0.50623
Contralateral to ICA stenosis
Pre-CEA
95.47 ± 20.71
114.72 ± 78.33
67.02 ± 11.77
94.61 ± 21.55
Post-CEA
131.46 ± 47.09#
153.53 ± 85.06#
70.74 ± 18.99
102.94 ± 33.86
P value
0.04011
0.03536
0.35679
0.50623
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CO, carotid occlusion; CEA, carotid endarterectomy; ACA, anterior cerebral artery; MCA, middle cerebral artery; PCA, posterior cerebral artery; BA, basilar artery.
#
P
<
0.05 versus pre-CEA.Ocular BFVs ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA were shown in Table5. In one patient undergoing CEA, retrograde OA flow in the ipsilateral side was completely changed to anterograde direction postoperatively. After CEA, the BFVs in the ipsilateral SPCA increased from 7.35 ± 1.36 to 12.4 ± 4.31 cm/s. Nonetheless, no significant differences in BFVs in the contralateral SPCA and bilateral CRA were found between pre-CEA and post-CEA.Table 5
Ocular BFV ipsilateral and contralateral to ICA stenosis in patients with severe CS and contralateral CO after and before CEA.
OA with retrograde flow (%)
CRA (cm/s)
SPCA (cm/s)
Ipsilateral to ICA stenosis
Pre-CEA
1/5 (20%)
7.51 ± 2.02
7.35 ± 1.36
Post-CEA
0/5 (0%)
8.85 ± 2.25
12.4 ± 4.31#
P value
NA
0.38402
0.03723
Contralateral to ICA stenosis
Pre-CEA
1/5 (20%)
6.67 ± 3.06
6.11 ± 1.29
Post-CEA
0/5 (0%)
7.66 ± 3.01
7.56 ± 1.97
P value
NA
0.08432
0.12419
BFV, blood flow velocity; ICA, internal carotid artery; CS, carotid stenosis; CO, carotid occlusion; CEA, carotid endarterectomy; CRA, central retinal artery; SPCA, short posterior ciliary arteries; OA, ophthalmic artery; NA, not applicable.
#
P
<
0.05 versus pre-CEA.Figure2 showed the CTA of carotid artery, TCD, and ocular CDI of a 56-year-old man before and after CEA. The patient had an 89% stenosis in the right ICA and a complete occlusion in the left ICA and underwent the successful right CEA. TCD showed that a significant improvement in cerebral BFVs of the ACA and MCA was observed not only in the right treated side but also in the left occluded side after CEA. CDI demonstrated the reversal of the retrograde flow in right OA and the markedly increased BFVs in the right SPCA postoperatively.Figure 2
A 56-year-old man presented with vertigo, dizziness, and hemispheric stroke. (a) The patient had an 89% stenosis in the right ICA and the left ICA total occlusion and experienced the successful right CEA. (b) CEA significantly improved the BFVs in the right and left ACA and MCA. (c) CEA normalized the reverse OA flow from right ECA. (d) CEA substantially improved the BFVs in the right SPCA.
(a)
(b)
(c)
(d)
## 4. Discussion
Severe stenosis of the ICA resulted in a decreased arterial pressure distal to stenosis. Under normal circumstances, a decrease in regional cerebral perfusion pressure (CPP) is compensated for by a decrease in peripheral vascular resistance, by means of vasodilation (autoregulation) [18, 19]. As a result, the cerebral blood flow (CBF) can be maintained. Nonetheless, high-grade CS may be associated with the malfunction of vasodilation autoregulation and the exhaustion of the cerebral autoregulatory reserve capacity. Hino et al. reported that significant reduction in CBF was observed in the hemisphere not only ipsilateral but also contralateral to the stenosis in patients with severe ICA stenosis [20]. Van Laar et al. reported that regional CBF in the ipsilateral hemisphere (60.9 ± 16.9 mL/min/100 g) was significantly lower than in the contralateral hemisphere (70.9 ± 11.5) and control subjects (78.7 ± 18.4) in patients with unilateral high-grade ICA stenosis [8]. Meaningfully, CEA for unilateral CS resulted in a significant recovery increase in BFVs of ipsilateral ACA and MCA; and no significant changes were seen in the contralateral ICA, BA, and bilateral PCA in patients of severe unilateral CS. These changes can be interpreted as a consequence of the recovery of normal diameter, blood flow, and CPP in the ipsilateral ICA after CEA.Similar results have been reported on the patients with unilateral severe CS after CEA. Jones et al. reported that ipsilateral supply to the MCA territory increased from 57.3 ± 5.7 to 67.3 ± 5.4 mL/100 g/min immediately after CEA and that a positive correlation was observed between obstruction ratio of ICA and change in supply to the ipsilateral MCA territory from the ipsilateral ICA [6]. van Laar et al. in 2006 reported that volume flow in the ipsilateral ICA increased from 114 ± 17 to 213 ± 17 mL/min, and no significant changes were seen in the contralateral ICA and BA one month after CEA [7]. They were also indicative of a positive correlation between the degree of stenosis and volume flow increase in the treated ICA [7]. van Laar et al. in 2007 demonstrated that regional CBF in the ipsilateral hemisphere increased from 60.9 ± 13.7 to 71.2 ± 13.9 mL/min/100 g one month after CEA [8]. Similarly, Sánchez-Arjona et al. found that MCA flow velocity on the ipsilateral side increased from 49.7 to 62.5 cm/s, and nonsignificant changes were seen on MCA of the contralateral side thirty days after carotid angioplasty stent placement (CAS) for ≥70% unilateral ICA stenosis [21].When the patients suffered from the ipsilateral CS and the contralateral CO, differences in bilateral CPP promote the recruitment of collateral pathways. The ipsilateral ICA can compensate for decreased CPP via the circle of Willis in the contralateral CO. Primary collateral pathways are considered to be contralateral-to-ipsilateral cross flow via the anterior communicating artery and posterior-to-anterior flow via the posterior communicating artery; flow via the OA and leptomeningeal vessels are thought to be secondary collateral pathways recruited when collateral flow through the circle of Willis is inadequate. This study demonstrated a significant increase in bilateral ACA and MCA, and no significant changes were noted in the BA and bilateral PCA after CEA for the ipsilateral CS with the contralateral CO. The increased flow in anterior circulation not in posterior circulation suggests that collateral flow through the anterior circulation is important in the case of CEA-treated CS with the contralateral CO. CEA contralateral to CO increases the CPP in the ipsilateral hemisphere and enhances collateral flow via the anterior communicating artery to the hemisphere on the occluded side.Our findings agreed with some previous studies on cases of severe CS with contralateral CO after CEA. Baracchini et al. found that CEA of the ipsilateral ICA stenosis improved CBF not only on the surgical side but also on the contralateral side of CO, and the proportion of patients with collateral flow via the anterior communicating artery increased significantly from 61.5% before to 89.7% within three months after CEA [10]. Kataoka et al. reported that the mean CBF of the treated side rose from 30.0 ± 7.1 to 34.4 ± 8.3 mL/min/100 g, and the mean CBF of the occluded side similarly rose from 28.3 ± 6.1 to 31.7 ± 6.4 mL/min/100 g eight to ten days after CEA [11]. They also indicated that there are significantly developed cross flow from the anterior communicating artery contributing to the improved CBF of the occluded side after CEA [11]. Rutgers et al. demonstrated that the BFV in the MCA of the occlusion side increased significantly from 71 to 85 mL/min at six months after CEA of the severe CS of the treated side, and the prevalence of collateral flow via the anterior communicating artery to the occlusion side increased significantly from 47% before to 84% after CEA [12].In the study, a significant ocular hemodynamic improvement was observed after CEA, evidenced by the reversal of OA with retrograde flow and the increase in the BFVs of the ipsilateral SPCA. Ocular blood flow alteration occurred in the ipsilateral hemisphere in patients undergoing CEA for the severe CS irrespective of the contralateral CO. The hemodynamic effect of CEA, after removal of an atherosclerotic plaque, is an increase in CPP in the distal ICA. The OA is located downstream of the ICA, and the inflow artery for the OA is the ICA. Severe CS was associated with a marked reduction in OA and CRA flow velocities, which were corrected with successful CEA [15]. Kawaguchi et al. demonstrated that the BFV in OA increased from 9 ± 5 cm/s to 21 ± 5 cm/s one week after CEA [16]. Retrograde OA flow is suggestive of high-grade ICA stenosis and ipsilateral ECA collateralization of the OA with absence of a circle of Willis contribution. Rutgers et al. indicated that the proportion of reversed OA flow ipsilateral to severe CS decreased significantly from 42% before to 5% at six months after CEA [12]. Cohn Jr. et al. reported that eight patients with preoperative OA flow reversal had a return of normal OA flow within one month following CEA [15]. Zbornikova and Skoglund demonstrated that a change in the flow direction from being retrograde to antegrade was noted in 9/10 patients (90%) within forty-eight hours after CEA [17]. As a result, CEA improved chronic ocular ischemic syndrome associated with severe CS by increasing the OA blood flow and correcting the reversed OA flow [16].Asymptomatic patients with substantial CS but no recent neurological symptoms are at increased long-term risk of the stroke, especially in the hemisphere ipsilateral to the CS. CEA has been shown to reduce the risk of ischemic stroke in patients with CS of ≥50% [22, 23]. A multicenter randomised trial involving 3120 patients demonstrated that stroke risks (immediate versus deferred CEA) were 4.1% versus 10.0% at 5-year follow-up and 10.8% versus 16.9% at 10-year follow-up [22]. The reduction in stroke risk following CEA has been correlated with the severity of CS ipsilaterally. Patients with severe CS of ≥70% had a dramatically reduced risk of ipsilateral stroke at eight years of follow-up [23]. CEA in patients with moderate CS of 50–69% yielded a moderate reduction in the risks of stroke [23]. Conversely, patients with stenosis of <50% did not benefit from the CEA [23]. The favorable benefit of CEA is attributable to the removal of the atheromatous plaque, which can be a source of cerebral emboli [3, 4]. Moreover, the improved CBF after CEA augmented the ability of the bloodstream to clear or wash out emboli and microemboli and restored available blood flow to regions rendered ischemic by emboli that block supply arteries [5].The asymptomatic subjects with severe unilateral CS may be associated with an increased rate of cognitive impairment in the hemisphere ipsilateral to CS [24]. The presence of severe unilateral CS had an increased probability of developing cognitive deterioration especially in subjects with an associated hemodynamic impairment [25]. Furthermore, the subjects with asymptomatic bilateral severe CS were more likely to develop cognitive dysfunction compared to subjects with unilateral CS [26, 27]. The main mechanism linking CS and cognitive deterioration may be a result of chronic brain cortex hypoperfusion and impaired cerebrovascular autoregulation due to unfavorable hemodynamic changes [25–27]. CEA removes the atheromatous plaque, restores the CPP, improves the cerebral hemodynamics, and normalizes the cerebral metabolism. It was inferred that this cognitive impairment was improved with CEA [28, 29]. Heyer et al. indicated that CEA resulted in significantly increased CBF and improved cognitive performance as early as one day postoperatively [30]. Fearn et al. found that CEA restored the impaired cerebrovascular reserve and improved cognitive function at two months postoperatively [31]. Picchetto et al. demonstrated that the recanalization of a stenotic carotid improved brain cognitive function by resolving the chronic hypoperfusion at three months following CEA [32].Our study has several limitations. First, the present study is the relatively small sample size. However, the sample size was enough to demonstrate significant improvement in cerebral and ocular hemodynamics after CEA. Second, cerebral and ocular hemodynamics were evaluated four days early after CEA. Further investigation needs to be carried out to clarify the long-term effect of CEA on cerebral and ocular BFVs.
## 5. Conclusions
In patients with unilateral CS undergoing CEA, ipsilateral hemodynamics of anterior circulation were significantly improved postoperatively. CEA contralateral to CO resulted in the significant improvement in hemodynamic of anterior circulation not only on the treated side but also on the occluded side. After CEA for the ipsilateral CS, collateral flow through anterior communicating artery compensated for the hemisphere on the occluded side in patients with the contralateral CO. CEA normalized the OA retrograde flow on the stenotic side and improved the blood flow in the ipsilateral SRCA irrespective of the contralateral CO.
---
*Source: 2901028-2016-08-23.xml* | 2016 |
# Carvacrol Protects against Hepatic Steatosis in Mice Fed a High-Fat Diet by Enhancing SIRT1-AMPK Signaling
**Authors:** Eunkyung Kim; Youngshim Choi; Jihee Jang; Taesun Park
**Journal:** Evidence-Based Complementary and Alternative Medicine
(2013)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2013/290104
---
## Abstract
We investigated the protective effect of carvacrol against high-fat-diet-induced hepatic steatosis in mice and the potential underlying molecular mechanisms. Mice were fed a normal diet, high-fat diet, or carvacrol-supplemented high-fat diet for 10 weeks. Compared to mice fed the high-fat diet, those fed the carvacrol-supplemented diet showed significantly lower hepatic lipid levels and reduced plasma activities of alanine aminotransferase and aspartate aminotransferase and plasma concentrations of monocyte chemoattractant protein 1 and tumor necrosis factorα. Carvacrol decreased the expression of LXRα, SREBP1c, FAS, leptin, and CD36 genes and phosphorylation of S6 kinase 1 protein involved in lipogenesis, whereas it increased the expression of SIRT1 and CPT1 genes and phosphorylation of liver kinase B1, AMP-activated protein kinase, and acetyl-CoA carboxylase proteins involved in fatty acid oxidation in the liver of mice fed the high-fat diet. These results suggest that carvacrol prevents HFD-induced hepatic steatosis by activating SIRT1-AMPK signaling.
---
## Body
## 1. Introduction
Simple hepatic steatosis, once considered benign, is now being recognized as a condition that may lead to steatohepatitis (hepatic steatosis with inflammation), fibrosis, and ultimately cirrhosis. The risk factors associated with hepatic steatosis are varied and include diabetes mellitus [1], hypertension [2], and obesity [3]. Several studies suggest that excessive fat accumulation in the liver occurs due to increased hepatic de novo lipogenesis, impaired fatty acid oxidation, or export of triglycerides. Mounting evidence suggests that a high-fat diet (HFD) causes enhanced lipogenesis and impaired fatty acid oxidation by inhibiting AMP-activated protein kinase (AMPK) activation through Sirtuin 1 (SIRT1), leading to the development of hepatic steatosis.The role of dietary cholesterol, with the subsequent increased hepatic esterification of cholesterol and its association to hepatic triglyceride accumulation, is a new paradigm for hepatic steatosis [4]. Cholesterol is accumulated in the liver under excess dietary cholesterol intake by disrupting the balance among steroid hormone synthesis, cholesterol uptake, and cholesterol efflux [5]. Accumulated cholesterol is esterified by acyl-coenzyme A:cholesterol acyltransferase (ACAT) in the liver, where some of it can be stored within hepatocytes in lipid droplets as cholesterol esters. When excess stored cholesterol ester molecules are present in the liver, the mobilization of hepatic triglyceride is limited and triglyceride secretion is reduced, resulting in the retention of neutral lipids as lipid droplets within the liver [4].Carvacrol [isopropyl-ortho-cresol, C6H3(OH)(C3H7)] is a predominant monoterpene phenol which occurs in many essential oils of the family Labiatae including Origanum, Satureja, Thymbra, Thymus, and Coridothymus species [6]. Carvacrol is a food additive approved by the US Food and Drug Administration and is a legally registered flavoring and foodstuff in the Council of Europe (2000). It is reported that carvacrol appears to be slowly adsorbed into the rabbit intestine after oral administration [7]. After 22 h, about 30% of 1.5 g carvacrol was still in the gastrointestinal tract while 45% was absorbed into the intestines in rabbit [7]. Previous in vitro studies demonstrated positive effects of carvacrol on inflammation, cancer, and oxidants [8–10]. It was found to decrease cyclooxygenase-2 expression in human macrophage-like U937 cells [8], Bcl2/Bax ratio and poly(ADP-ribose) polymerase-1 cleavage in breast cancer cells [9], and lipid peroxidation induced by reactive free radicals [10]. Several rodent studies have shown that carvacrol provides protection against various pharmacological properties, including antidepressant [11], anxiolytic-like [12], antinociceptive [10], and hypotensive [13] activities. Furthermore, Aristatile et al. reported that carvacrol exerted a beneficial effect in hepatotoxicity through decreased activities of plasma alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in D-galactosamine-induced hepatotoxic rats [6, 14]. Although a number of studies have been carried out to investigate the biochemical roles of carvacrol, the protective activity of carvacrol against hepatic steatosis has never been reported. Therefore, the main objective of this study was to investigate the protective effects of carvacrol against HFD-induced simple hepatic steatosis in mice and to study potential molecular mechanisms, focusing on the expression of genes involved in lipogenesis and fatty acid oxidation in the liver.
## 2. Experimental Procedures
### 2.1. Animal Studies
Male C57BL/6N mice (5 weeks old) were obtained from Orient Bio (Gyeonggi-do, South Korea) and maintained under 12 h light-dark cycles with free access to food and water. They were divided into 3 experimental diet groups (n=8 per group): normal diet (ND), HFD, and carvacrol-supplemented diet (CSD). The ND was a purified diet based on the AIN-76 rodent diet composition. The HFD was identical to the ND, except that 200 g fat/kg (170 g lard plus 30 g corn oil) and 1% cholesterol were added to it. The CSD was identical to the HFD and contained 0.1% (w/w) carvacrol (Sigma, MO, USA). The experimental diets were given ad libitum for 10 weeks in the form of pellets. At the end of the experiment, all animals were anesthetized with ether, blood was collected in EDTA-coated tubes and centrifuged, and plasma was stored at −70°C. Livers were removed, weighed, and stored at −70°C. All mice were housed in the specific pathogen-free facility of the Yonsei University, Seoul, Korea. This study was approved by the Institutional Animal Care and Use Committee of Yonsei University.
### 2.2. Biochemical Analysis
Plasma activities of ALT and AST were measured using commercial kits (Bio-Clinical System, Gyeonggi-do, South Korea). Hepatic lipids were extracted from whole liver homogenates using a modified Folch extraction. Levels of triglycerides, free fatty acids, and cholesterol in hepatic lipid extracts were measured using commercial kits (Bio-Clinical System, Gyeonggi-do, South Korea). For measurement of hepatic cholesteryl esters, lipids were extracted from frozen liver tissues by thawing and homogenizing in chloroform (Sigma) : isopropanol (Sigma) : NP40 (Sigma) (7 : 11 : 0.1). The tissue homogenates were centrifuged (15,000 ×g, 10 min, 4°C) and the resulting supernatants (organic phase) were used for the cholesterol ester analysis. Total cholesterol and free cholesterol levels were measured using commercially available kits (ABCAM, Cambridge, UK). The level of cholesteryl esters was calculated by subtraction of the obtained values of free cholesterol from total cholesterol. Plasma levels of tumor necrosis factor-alpha (TNFα) and monocyte chemoattractant protein-1 (MCP1) were measured using ELISA kits (ID Labs, MA, USA).
### 2.3. Liver Histology
Liver sections were formalin fixed and paraffin embedded prior to sectioning. All sections were then stained with hematoxylin (Sigma) and eosin (Sigma), encoded, and assessed for steatosis and inflammation, by an expert liver pathologist blinded to the identity of the groups. The grade of steatosis was scored as 0 = no steatosis; 1 = minimal steatosis; 2 = slight steatosis; 3 = moderate steatosis; 4 = marked steatosis; 5 = severe steatosis. The grade of lobular inflammation was scored as 0 = no inflammatory foci; 1 = 1-2 inflammatory foci; 2 = 3-4 inflammatory foci; 3 = <4 inflammatory foci.
### 2.4. Hepatic Gene Expression Analysis
Total RNA was isolated from liver tissue by acid guanidinium thiocyanate-phenol chloroform extraction using Trizol reagent (Invitrogen, CA, USA). Four micrograms of total RNA were reverse transcribed using the Superscript II kit (Invitrogen, CA, USA) according to the manufacturer’s recommendations. Primers used for polymerase chain reaction (PCR) are listed in Table1. Taq DNA polymerase was used to amplify transcribed genes using a PCR program of a denaturation step of 10 min at 94°C, followed by 30 cycles of 30 s at 94°C, 30 s at 55°C, and 1 min at 72°C, then 10 min at 72°C, and terminated by an elongation step at 72°C for 10 min. PCR products were size fractionated on a 2% agarose gel and stained with ethidium bromide.Table 1
Primer sequences and PCR conditions.
Gene description
Primers
Sequences (5′ → 3′)
Annealingtemperature (°C)
PCRproduct (bp)
Sirtuin1 (SIRT1)
F
CAGAACCACCAAAGCGGAAA
55
693
R
GGCACTTCATGGGGTATAGA
Liver X receptor(LXRα)
F
TCCTACACGAGGATCAAGCG
55
119
R
AGTCGCAATGCAAACACCTG
SREBP1c (SREBP1c)
F
TTGTGGAGCTCAAAGACCTG
55
94
R
TGCAAGAAGCGGATGTAGTC
CD36 antigen (CD36)
F
ATGACGTGGCAAAGAACAGC
55
160
R
GAAGGCTCAAAGATGGCTCC
Lipoprotein lipase (leptin)
F
CTCCAAGGTTGTCCAGGGTT
55
143
R
AAAACTCCCCACAGAATGGG
Fatty acid synthase (FAS)
F
AGGGGTCGACCTGGTCCTCA
65
132
R
GCCATGCCCAGAGGGTGGTT
Carnitine palmitoyltransferase I (CPT1)
F
CTCTGCTGGCCGTTGTTGT
55
120
R
GGCAAGTTCTGCCTCACGTA
Sterol regulatory element-binding protein-2 (SREBP2)
F
CACAATATCATTGAAAAGCG
60
200
R
TTTTTCTGATTGGCCAGCTT
3-Hydroxy-3-methylglutaryl-CoA reductase (HMGCR)
F
TAAGATTCAACAACTCTGCT
55
101
R
TGTGGCCAGGAGTTTGGTGA
Farnesyl diphosphate synthase (FDPS)
F
ATGGAGATGGGCGAGTTCTT
60
80
R
CCGACCTTTCCCGTCACA
Cytochrome P450, family 51 (CYP51)
F
ACGCTGCCTGGCTATTGC
55
76
R
TTGATCTCTCGATGGGCTCTATC
Low-density lipoprotein receptor (LDLR)
F
AGGCTGTGGGCTCCATAGG
60
72
R
TGCGGTCCAGGGTCATCT
ATP-binding cassette, sub-family G, member 5 (ABCG5)
F
CGTGGCGGACCAAATGA
55
155
R
CGCTCGCCACTGGAAATT
ATP-binding cassette, sub-family G, member 8 (ABCG8)
F
TGCCCACCTTCCACATGTC
60
60
R
ATGAAGCCGGCAGTAAGGTAGA
Cytochrome P450, family 7, subfamily A, polypeptide 1 (CYP7A1)
F
CAGGGAGATGCTCTGTGTTCA
60
121
R
AGGCATACATCCCTTCCGTGA
Cytochrome P450, family 8, subfamily A, polypeptide 1 (CYP8B1)
F
AAGGCTGGCTTCCTGAGCTT
60
74
R
AACAGCTCATCGGCCTCATC
Acyl-coenzyme A: cholesterol acyltransferase (ACAT1)
F
AGCGAGACAGATGCTCATGC
55
107
R
CAACCAAACCTCCGTCACTG
Toll-like receptor 2 (TLR2)
F
GAGCATCCGAATTGCATCAC
55
120
R
TATGGCCACCAAGATCCAGA
Toll-like receptor 4 (TLR4)
F
TCGAATCCTGAGCAAACAGC
55
199
R
CCCGGTAAGGTCCATGCTAT
Toll-interleukin 1 receptor domain-containing adaptor protein (Tirap)
F
GCTTCCAGGGGATCTGATGT
55
183
R
AAGCAAGCCTACCACGGACT
TIR-domain-containing adapter-inducing interferon-β (TRIF)
F
ATGGATAACCCAGGGCCTT
55
528
R
TTCTGGTCACTGCAGGGGAT
Interferon regulatory factor 5 (IRF5)
F
ACCCGGATCTCAAAGACCAC
55
166
R
TTATTGCATGCCAACTGGGT
TNF alpha (TNFα)
F
TGTCTCAGCCTCTTCTCATT
55
156
R
AGATGATCTGAGTGTGAGGG
Interleukin 1 beta (IL-1β)
F
GTTGACGGACCCCAAAAGAT
55
129
R
TGATACTGCCTGCCTGAAGC
Interferon beta (IFNβ)
F
TGGAGCAGCTGAATGGAAAG
55
122
R
GAGCATCTCTTGGATGGCAA
Glyceraldehyde-3-phosphate dehydrogenase (GAPDH)
F
CCCATGTTTGTGATGGGTGT
55
161
R
GTGATGGCATGGACTGTGGT
### 2.5. Western Blot Analysis
Liver tissues of each mouse were homogenized at 4°C in an extraction buffer containing 100 mM Tris-HCl, pH 7.4, 5 mM EDTA, 50 mM NaCl, 50 mM sodium pyrophosphate, 50 mM NaF, 100 mM orthovanadate, 1% Triton X-100, 1 mM phenylmethanesulfonyl fluoride, 2μg/mL aprotinin, 1 μg/mL pepstatin A, and 1 μg/mL leupeptin. The tissue homogenates were centrifuged (1300 ×g, 20 min, 4°C) and the resulting supernatants (whole-tissue extracts) were used for western blot analysis. The total protein concentrations of the whole-tissue extracts were determined by Bradford assay (Bio-Rad, CA, USA). Protein samples were separated with 8% sodium dodecyl sulfate-polyacrylamide gel electrophoresis, transferred onto a nitrocellulose membrane (Amersham, Buckinghamshire, UK), and hybridized with primary antibodies (diluted 1 : 1000) overnight at 4°C. The membrane was then incubated with the appropriate secondary antibody and immunoreactive signals were detected using a chemiluminescent detection system (Amersham, Buckinghamshire, UK). The signals were quantified using the Quantity One analysis software (Bio-Rad, CA, USA). Antibodies to liver kinase B1 (LKB1), phospho-LKB (Ser428), AMP-activated protein kinase (AMPK), phospho-AMPK (Thr172), acetyl-CoA carboxylase (ACC), phospho-ACC (Ser79), S6 kinase 1 (S6K1), phospho-S6K1 (Thr389), interferon regulatory factor 3 (IRF3), phospho-IRF3 (Ser396), and β-catenin were purchased from Cell Signaling Technology (Cell Signaling Technology, MA, USA) and antibody to β-actin was obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA).
### 2.6. Statistical Analysis
The mean ± SEM of body weight gain, liver weight, and plasma and hepatic biochemistries was determined from 3 independent experiments. Reverse transcription (RT)-PCR and Western blot data were presented as mean ± SEM of at least 3 separate experiments. All of the analyses were performed using SPSS statistical software. Statistical analysis of results was performed using one-way analysis of variance (one-way ANOVA test), followed by Duncan’s multiple-range tests. Statistical significance was set atP<0.05.
## 2.1. Animal Studies
Male C57BL/6N mice (5 weeks old) were obtained from Orient Bio (Gyeonggi-do, South Korea) and maintained under 12 h light-dark cycles with free access to food and water. They were divided into 3 experimental diet groups (n=8 per group): normal diet (ND), HFD, and carvacrol-supplemented diet (CSD). The ND was a purified diet based on the AIN-76 rodent diet composition. The HFD was identical to the ND, except that 200 g fat/kg (170 g lard plus 30 g corn oil) and 1% cholesterol were added to it. The CSD was identical to the HFD and contained 0.1% (w/w) carvacrol (Sigma, MO, USA). The experimental diets were given ad libitum for 10 weeks in the form of pellets. At the end of the experiment, all animals were anesthetized with ether, blood was collected in EDTA-coated tubes and centrifuged, and plasma was stored at −70°C. Livers were removed, weighed, and stored at −70°C. All mice were housed in the specific pathogen-free facility of the Yonsei University, Seoul, Korea. This study was approved by the Institutional Animal Care and Use Committee of Yonsei University.
## 2.2. Biochemical Analysis
Plasma activities of ALT and AST were measured using commercial kits (Bio-Clinical System, Gyeonggi-do, South Korea). Hepatic lipids were extracted from whole liver homogenates using a modified Folch extraction. Levels of triglycerides, free fatty acids, and cholesterol in hepatic lipid extracts were measured using commercial kits (Bio-Clinical System, Gyeonggi-do, South Korea). For measurement of hepatic cholesteryl esters, lipids were extracted from frozen liver tissues by thawing and homogenizing in chloroform (Sigma) : isopropanol (Sigma) : NP40 (Sigma) (7 : 11 : 0.1). The tissue homogenates were centrifuged (15,000 ×g, 10 min, 4°C) and the resulting supernatants (organic phase) were used for the cholesterol ester analysis. Total cholesterol and free cholesterol levels were measured using commercially available kits (ABCAM, Cambridge, UK). The level of cholesteryl esters was calculated by subtraction of the obtained values of free cholesterol from total cholesterol. Plasma levels of tumor necrosis factor-alpha (TNFα) and monocyte chemoattractant protein-1 (MCP1) were measured using ELISA kits (ID Labs, MA, USA).
## 2.3. Liver Histology
Liver sections were formalin fixed and paraffin embedded prior to sectioning. All sections were then stained with hematoxylin (Sigma) and eosin (Sigma), encoded, and assessed for steatosis and inflammation, by an expert liver pathologist blinded to the identity of the groups. The grade of steatosis was scored as 0 = no steatosis; 1 = minimal steatosis; 2 = slight steatosis; 3 = moderate steatosis; 4 = marked steatosis; 5 = severe steatosis. The grade of lobular inflammation was scored as 0 = no inflammatory foci; 1 = 1-2 inflammatory foci; 2 = 3-4 inflammatory foci; 3 = <4 inflammatory foci.
## 2.4. Hepatic Gene Expression Analysis
Total RNA was isolated from liver tissue by acid guanidinium thiocyanate-phenol chloroform extraction using Trizol reagent (Invitrogen, CA, USA). Four micrograms of total RNA were reverse transcribed using the Superscript II kit (Invitrogen, CA, USA) according to the manufacturer’s recommendations. Primers used for polymerase chain reaction (PCR) are listed in Table1. Taq DNA polymerase was used to amplify transcribed genes using a PCR program of a denaturation step of 10 min at 94°C, followed by 30 cycles of 30 s at 94°C, 30 s at 55°C, and 1 min at 72°C, then 10 min at 72°C, and terminated by an elongation step at 72°C for 10 min. PCR products were size fractionated on a 2% agarose gel and stained with ethidium bromide.Table 1
Primer sequences and PCR conditions.
Gene description
Primers
Sequences (5′ → 3′)
Annealingtemperature (°C)
PCRproduct (bp)
Sirtuin1 (SIRT1)
F
CAGAACCACCAAAGCGGAAA
55
693
R
GGCACTTCATGGGGTATAGA
Liver X receptor(LXRα)
F
TCCTACACGAGGATCAAGCG
55
119
R
AGTCGCAATGCAAACACCTG
SREBP1c (SREBP1c)
F
TTGTGGAGCTCAAAGACCTG
55
94
R
TGCAAGAAGCGGATGTAGTC
CD36 antigen (CD36)
F
ATGACGTGGCAAAGAACAGC
55
160
R
GAAGGCTCAAAGATGGCTCC
Lipoprotein lipase (leptin)
F
CTCCAAGGTTGTCCAGGGTT
55
143
R
AAAACTCCCCACAGAATGGG
Fatty acid synthase (FAS)
F
AGGGGTCGACCTGGTCCTCA
65
132
R
GCCATGCCCAGAGGGTGGTT
Carnitine palmitoyltransferase I (CPT1)
F
CTCTGCTGGCCGTTGTTGT
55
120
R
GGCAAGTTCTGCCTCACGTA
Sterol regulatory element-binding protein-2 (SREBP2)
F
CACAATATCATTGAAAAGCG
60
200
R
TTTTTCTGATTGGCCAGCTT
3-Hydroxy-3-methylglutaryl-CoA reductase (HMGCR)
F
TAAGATTCAACAACTCTGCT
55
101
R
TGTGGCCAGGAGTTTGGTGA
Farnesyl diphosphate synthase (FDPS)
F
ATGGAGATGGGCGAGTTCTT
60
80
R
CCGACCTTTCCCGTCACA
Cytochrome P450, family 51 (CYP51)
F
ACGCTGCCTGGCTATTGC
55
76
R
TTGATCTCTCGATGGGCTCTATC
Low-density lipoprotein receptor (LDLR)
F
AGGCTGTGGGCTCCATAGG
60
72
R
TGCGGTCCAGGGTCATCT
ATP-binding cassette, sub-family G, member 5 (ABCG5)
F
CGTGGCGGACCAAATGA
55
155
R
CGCTCGCCACTGGAAATT
ATP-binding cassette, sub-family G, member 8 (ABCG8)
F
TGCCCACCTTCCACATGTC
60
60
R
ATGAAGCCGGCAGTAAGGTAGA
Cytochrome P450, family 7, subfamily A, polypeptide 1 (CYP7A1)
F
CAGGGAGATGCTCTGTGTTCA
60
121
R
AGGCATACATCCCTTCCGTGA
Cytochrome P450, family 8, subfamily A, polypeptide 1 (CYP8B1)
F
AAGGCTGGCTTCCTGAGCTT
60
74
R
AACAGCTCATCGGCCTCATC
Acyl-coenzyme A: cholesterol acyltransferase (ACAT1)
F
AGCGAGACAGATGCTCATGC
55
107
R
CAACCAAACCTCCGTCACTG
Toll-like receptor 2 (TLR2)
F
GAGCATCCGAATTGCATCAC
55
120
R
TATGGCCACCAAGATCCAGA
Toll-like receptor 4 (TLR4)
F
TCGAATCCTGAGCAAACAGC
55
199
R
CCCGGTAAGGTCCATGCTAT
Toll-interleukin 1 receptor domain-containing adaptor protein (Tirap)
F
GCTTCCAGGGGATCTGATGT
55
183
R
AAGCAAGCCTACCACGGACT
TIR-domain-containing adapter-inducing interferon-β (TRIF)
F
ATGGATAACCCAGGGCCTT
55
528
R
TTCTGGTCACTGCAGGGGAT
Interferon regulatory factor 5 (IRF5)
F
ACCCGGATCTCAAAGACCAC
55
166
R
TTATTGCATGCCAACTGGGT
TNF alpha (TNFα)
F
TGTCTCAGCCTCTTCTCATT
55
156
R
AGATGATCTGAGTGTGAGGG
Interleukin 1 beta (IL-1β)
F
GTTGACGGACCCCAAAAGAT
55
129
R
TGATACTGCCTGCCTGAAGC
Interferon beta (IFNβ)
F
TGGAGCAGCTGAATGGAAAG
55
122
R
GAGCATCTCTTGGATGGCAA
Glyceraldehyde-3-phosphate dehydrogenase (GAPDH)
F
CCCATGTTTGTGATGGGTGT
55
161
R
GTGATGGCATGGACTGTGGT
## 2.5. Western Blot Analysis
Liver tissues of each mouse were homogenized at 4°C in an extraction buffer containing 100 mM Tris-HCl, pH 7.4, 5 mM EDTA, 50 mM NaCl, 50 mM sodium pyrophosphate, 50 mM NaF, 100 mM orthovanadate, 1% Triton X-100, 1 mM phenylmethanesulfonyl fluoride, 2μg/mL aprotinin, 1 μg/mL pepstatin A, and 1 μg/mL leupeptin. The tissue homogenates were centrifuged (1300 ×g, 20 min, 4°C) and the resulting supernatants (whole-tissue extracts) were used for western blot analysis. The total protein concentrations of the whole-tissue extracts were determined by Bradford assay (Bio-Rad, CA, USA). Protein samples were separated with 8% sodium dodecyl sulfate-polyacrylamide gel electrophoresis, transferred onto a nitrocellulose membrane (Amersham, Buckinghamshire, UK), and hybridized with primary antibodies (diluted 1 : 1000) overnight at 4°C. The membrane was then incubated with the appropriate secondary antibody and immunoreactive signals were detected using a chemiluminescent detection system (Amersham, Buckinghamshire, UK). The signals were quantified using the Quantity One analysis software (Bio-Rad, CA, USA). Antibodies to liver kinase B1 (LKB1), phospho-LKB (Ser428), AMP-activated protein kinase (AMPK), phospho-AMPK (Thr172), acetyl-CoA carboxylase (ACC), phospho-ACC (Ser79), S6 kinase 1 (S6K1), phospho-S6K1 (Thr389), interferon regulatory factor 3 (IRF3), phospho-IRF3 (Ser396), and β-catenin were purchased from Cell Signaling Technology (Cell Signaling Technology, MA, USA) and antibody to β-actin was obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA).
## 2.6. Statistical Analysis
The mean ± SEM of body weight gain, liver weight, and plasma and hepatic biochemistries was determined from 3 independent experiments. Reverse transcription (RT)-PCR and Western blot data were presented as mean ± SEM of at least 3 separate experiments. All of the analyses were performed using SPSS statistical software. Statistical analysis of results was performed using one-way analysis of variance (one-way ANOVA test), followed by Duncan’s multiple-range tests. Statistical significance was set atP<0.05.
## 3. Results
### 3.1. Carvacrol Reverses HFD-Induced Hepatic Steatosis
At week 10, male mice fed the CSD displayed a significant reduction in final body weight compared with HFD-fed mice (Figure1(a)). There was no difference in the food consumption among groups (data not shown). CSD-fed mice showed significant decreases in liver weight (43%, P<0.05) compared to HFD-fed mice (Figure 1(b)). Hepatic triglycerides (37%, P<0.05), free fatty acids (57%, P<0.05), total cholesterol (26%, P<0.05), and cholesteryl ester (41%, P<0.05) levels were significantly higher in HFD-fed mice than in ND-fed mice, whereas CSD-fed mice were completely resistant to HFD-induced hepatic lipid accumulation (Figures 1(c)–1(f)). Histological sections of liver tissue from HFD-fed mice showed predominantly large lipid-filled vacuoles. Liver sections from CSD-fed mice revealed a reduction of lipid accumulation in the form of lipid droplets, or even small lipid droplets (Figure 2(a)). The hepatic steatosis scores in CSD-fed mice were significantly lower than scores in HFD-fed mice (Figure 2(b)). Evaluation of hepatic inflammation using hematoxylin and eosin liver staining revealed no significant differences between CSD- and HFD-fed mice (Figure 2(c)). As expected, plasma activities of ALT (47%, P<0.05) and AST (47%, P<0.05) were both substantially elevated by the HFD, and the CSD resulted in significant reductions in these plasma activities (Figure 2(d)).CSD mice are resistant to HFD-induced liver enlargement and hepatic lipid levels. (a) Final body weight of mice on ND, HFD, or CSD. (b) Weights of livers and (c–f) hepatic triglyceride, FFA, total cholesterol, and cholesterol ester levels. Data are mean ± SEM,n=8. *P<0.05.
(a)
(b)
(c)
(d)
(e)
(f)Carvacrol reduced hepatic lipid droplet and activities of ALT and AST. (a) Hematoxylin and eosin staining of representative liver section (magnification ×100). (b) Mean steatosis score. (c) Mean inflammation score. (d) Plasma ALT and AST activities. Data are mean ± SEM,n=8. *P<0.05.
(a)
(b)
(c)
(d)
### 3.2. Carvacrol Modulates the Expression of Genes Involved in Lipid Metabolism
To gain insight into the protective mechanisms of carvacrol against hepatic steatosis in HFD-fed mice, we examined hepatic mRNA levels for genes involved in lipogenesis and fatty acid oxidation by RT-PCR analysis. SIRT1 and AMPK are key regulators of both lipogenesis and fatty acid oxidation in the liver. Expression of SIRT1 and phosphorylation of AMPK protein were significantly increased in the livers of CSD-fed mice compared with HFD-fed mice (Figures3(a) and 3(b)). Hepatic mRNA levels of the lipogenic genes, including liver X receptor alpha (LXRα), sterol regulatory element binding transcription factor 1 (SREBP1c), fatty acid synthase (FAS), leptin, and CD36, were also significantly lower in CSD-fed mice than in HFD-fed mice (Figure 3(a)). In addition, expression of carnitine palmitoyltransferase 1 (CPT1), a reflection of mitochondrial β-fatty acid oxidation capacity, was significantly increased in the liver of CSD-fed mice compared with HFD-fed mice (Figure 3(a)).Enhanced hepatic SIRT1-AMPK signaling in CSD-fed mice. (a) Hepatic mRNA expression levels of SIRT1, LXRα, SREBP1c, FAS, leptin, CD36, and CPT1 normalized to GAPDH relative to ND-fed mice. (b) Upper, representative western blot of phospho- and total AMPK in livers of ND, HFD, and CSD-fed mice. Lower, densitometric analysis of AMPK phosphorylation expressed as change relative to each control band. Data are shown as the mean ± SEM, n=8. *P<0.05.
(a)
(b)We also examined the effect of carvacrol on the expression of genes involved in cholesterol homeostasis in the liver. Hepatic mRNA levels of SREBP2 and its target gene LDLR, an important cholesterol influx transporter, were higher in CSD-fed mice than HFD-fed mice. CSD-fed mice had increased mRNA levels of genes involved in cholesterol synthesis, including 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), Farnesyl diphosphate synthase (FDPS), and Cytochrome P450, family 51 (CYP51) in the liver compared with HFD-fed mice. Expression of ACAT1 was significantly decreased in the livers of CSD-fed mice compared with HFD-fed mice (Figure4(a)). Expressions of ATP-binding cassette, subfamily G, members 5 and 8 (ABCG5, ABCG8) genes involved in cholesterol efflux, Cytochrome P450, family 7, subfamily A, polypeptide 1 (CYP7A1), and Cytochrome P450, family 8, subfamily A, polypeptide 1 (CYP8B1) genes involved in bile acid synthesis, were also higher in CSD-fed mice compared with HFD-fed mice (Figures 4(a) and 4(b)).Enhanced hepatic cholesterol metabolism in CSD-fed mice. (a and b) Hepatic mRNA expression levels of SREBP2, HMGCR, FDPS, CYP51, LDLR, ABCG5, ABCG8, ACAT1, CYP7A1, and CYP8B1 normalized to GAPDH relative to ND-fed mice. Data are shown as the mean ± SEM,n=8. *P<0.05.
(a)
(b)
### 3.3. Carvacrol Inhibited the Expression of Genes Involved in Inflammation
In the livers of CSD-fed mice, levels of Toll-like receptors 2 and 4 (TLR2, TLR4) and their adaptor proteins (Toll-interleukin 1 receptor domain-containing adaptor protein (TIRAP) and TIR domain-containing adapter protein inducing interferon beta (TRIF)) were significantly reduced compared with their corresponding levels in HFD-fed mice (Figure5(a)). Phosphorylation of interferon regulatory factor-3 (IRF3) protein, a key transcriptional factor in interferon beta (IFNβ) induction, was decreased in the livers of CSD-fed mice compared to HFD-fed mice (Figure 5(b)). Significantly, higher levels of transcription factor interferon regulatory factor-5 (IRF5) and proinflammatory cytokines (interleukin [IL]-1β, IFNβ, and TNFα) were also found in the livers of CSD-fed mice, as compared to those in HFD-fed mice (Figure 5(a)). Mice that received carvacrol showed significantly lower plasma concentrations of MCP1 (−67%) and TNFα (−35%) in comparison with the values for HFD control mice (Figures 5(c) and 5(d)).Reduced hepatic TLR2- and 4-mediated signaling and plasma levels of inflammatory markers in CSD-fed mice. (a) Hepatic mRNA expression levels of TLR2, TLR4 and related genes normalized to GAPDH expression relative to ND-fed mice. (b) Representative blots of hepatic IRF3 and phosphorylated IRF3 proteins in total liver extracts from the ND-, HFD-, and CSD-fed mice. Blots were quantified and the data are presented as the ratio of phosphorylated IRF3 to native protein, with values normalized to ND-fed mice. (c and d) Plasma MCP1 and TNFα levels. Values are means ± SEM from 8 animals, *P<0.05.
(a)
(b)
(c)
(d)
## 3.1. Carvacrol Reverses HFD-Induced Hepatic Steatosis
At week 10, male mice fed the CSD displayed a significant reduction in final body weight compared with HFD-fed mice (Figure1(a)). There was no difference in the food consumption among groups (data not shown). CSD-fed mice showed significant decreases in liver weight (43%, P<0.05) compared to HFD-fed mice (Figure 1(b)). Hepatic triglycerides (37%, P<0.05), free fatty acids (57%, P<0.05), total cholesterol (26%, P<0.05), and cholesteryl ester (41%, P<0.05) levels were significantly higher in HFD-fed mice than in ND-fed mice, whereas CSD-fed mice were completely resistant to HFD-induced hepatic lipid accumulation (Figures 1(c)–1(f)). Histological sections of liver tissue from HFD-fed mice showed predominantly large lipid-filled vacuoles. Liver sections from CSD-fed mice revealed a reduction of lipid accumulation in the form of lipid droplets, or even small lipid droplets (Figure 2(a)). The hepatic steatosis scores in CSD-fed mice were significantly lower than scores in HFD-fed mice (Figure 2(b)). Evaluation of hepatic inflammation using hematoxylin and eosin liver staining revealed no significant differences between CSD- and HFD-fed mice (Figure 2(c)). As expected, plasma activities of ALT (47%, P<0.05) and AST (47%, P<0.05) were both substantially elevated by the HFD, and the CSD resulted in significant reductions in these plasma activities (Figure 2(d)).CSD mice are resistant to HFD-induced liver enlargement and hepatic lipid levels. (a) Final body weight of mice on ND, HFD, or CSD. (b) Weights of livers and (c–f) hepatic triglyceride, FFA, total cholesterol, and cholesterol ester levels. Data are mean ± SEM,n=8. *P<0.05.
(a)
(b)
(c)
(d)
(e)
(f)Carvacrol reduced hepatic lipid droplet and activities of ALT and AST. (a) Hematoxylin and eosin staining of representative liver section (magnification ×100). (b) Mean steatosis score. (c) Mean inflammation score. (d) Plasma ALT and AST activities. Data are mean ± SEM,n=8. *P<0.05.
(a)
(b)
(c)
(d)
## 3.2. Carvacrol Modulates the Expression of Genes Involved in Lipid Metabolism
To gain insight into the protective mechanisms of carvacrol against hepatic steatosis in HFD-fed mice, we examined hepatic mRNA levels for genes involved in lipogenesis and fatty acid oxidation by RT-PCR analysis. SIRT1 and AMPK are key regulators of both lipogenesis and fatty acid oxidation in the liver. Expression of SIRT1 and phosphorylation of AMPK protein were significantly increased in the livers of CSD-fed mice compared with HFD-fed mice (Figures3(a) and 3(b)). Hepatic mRNA levels of the lipogenic genes, including liver X receptor alpha (LXRα), sterol regulatory element binding transcription factor 1 (SREBP1c), fatty acid synthase (FAS), leptin, and CD36, were also significantly lower in CSD-fed mice than in HFD-fed mice (Figure 3(a)). In addition, expression of carnitine palmitoyltransferase 1 (CPT1), a reflection of mitochondrial β-fatty acid oxidation capacity, was significantly increased in the liver of CSD-fed mice compared with HFD-fed mice (Figure 3(a)).Enhanced hepatic SIRT1-AMPK signaling in CSD-fed mice. (a) Hepatic mRNA expression levels of SIRT1, LXRα, SREBP1c, FAS, leptin, CD36, and CPT1 normalized to GAPDH relative to ND-fed mice. (b) Upper, representative western blot of phospho- and total AMPK in livers of ND, HFD, and CSD-fed mice. Lower, densitometric analysis of AMPK phosphorylation expressed as change relative to each control band. Data are shown as the mean ± SEM, n=8. *P<0.05.
(a)
(b)We also examined the effect of carvacrol on the expression of genes involved in cholesterol homeostasis in the liver. Hepatic mRNA levels of SREBP2 and its target gene LDLR, an important cholesterol influx transporter, were higher in CSD-fed mice than HFD-fed mice. CSD-fed mice had increased mRNA levels of genes involved in cholesterol synthesis, including 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), Farnesyl diphosphate synthase (FDPS), and Cytochrome P450, family 51 (CYP51) in the liver compared with HFD-fed mice. Expression of ACAT1 was significantly decreased in the livers of CSD-fed mice compared with HFD-fed mice (Figure4(a)). Expressions of ATP-binding cassette, subfamily G, members 5 and 8 (ABCG5, ABCG8) genes involved in cholesterol efflux, Cytochrome P450, family 7, subfamily A, polypeptide 1 (CYP7A1), and Cytochrome P450, family 8, subfamily A, polypeptide 1 (CYP8B1) genes involved in bile acid synthesis, were also higher in CSD-fed mice compared with HFD-fed mice (Figures 4(a) and 4(b)).Enhanced hepatic cholesterol metabolism in CSD-fed mice. (a and b) Hepatic mRNA expression levels of SREBP2, HMGCR, FDPS, CYP51, LDLR, ABCG5, ABCG8, ACAT1, CYP7A1, and CYP8B1 normalized to GAPDH relative to ND-fed mice. Data are shown as the mean ± SEM,n=8. *P<0.05.
(a)
(b)
## 3.3. Carvacrol Inhibited the Expression of Genes Involved in Inflammation
In the livers of CSD-fed mice, levels of Toll-like receptors 2 and 4 (TLR2, TLR4) and their adaptor proteins (Toll-interleukin 1 receptor domain-containing adaptor protein (TIRAP) and TIR domain-containing adapter protein inducing interferon beta (TRIF)) were significantly reduced compared with their corresponding levels in HFD-fed mice (Figure5(a)). Phosphorylation of interferon regulatory factor-3 (IRF3) protein, a key transcriptional factor in interferon beta (IFNβ) induction, was decreased in the livers of CSD-fed mice compared to HFD-fed mice (Figure 5(b)). Significantly, higher levels of transcription factor interferon regulatory factor-5 (IRF5) and proinflammatory cytokines (interleukin [IL]-1β, IFNβ, and TNFα) were also found in the livers of CSD-fed mice, as compared to those in HFD-fed mice (Figure 5(a)). Mice that received carvacrol showed significantly lower plasma concentrations of MCP1 (−67%) and TNFα (−35%) in comparison with the values for HFD control mice (Figures 5(c) and 5(d)).Reduced hepatic TLR2- and 4-mediated signaling and plasma levels of inflammatory markers in CSD-fed mice. (a) Hepatic mRNA expression levels of TLR2, TLR4 and related genes normalized to GAPDH expression relative to ND-fed mice. (b) Representative blots of hepatic IRF3 and phosphorylated IRF3 proteins in total liver extracts from the ND-, HFD-, and CSD-fed mice. Blots were quantified and the data are presented as the ratio of phosphorylated IRF3 to native protein, with values normalized to ND-fed mice. (c and d) Plasma MCP1 and TNFα levels. Values are means ± SEM from 8 animals, *P<0.05.
(a)
(b)
(c)
(d)
## 4. Discussion
The 0.1% carvacrol dosage (equivalent to 100 mg/kg body weight) given to mice in our study was chosen on the basis of previous reports. In these reports,D-galactosamine-induced hepatotoxic rats treated with carvacrol (80 mg/kg body weight) had significantly decreased plasma ALT and AST activities, as well as hepatic free fatty acid and cholesterol levels in comparison with saline-treated hepatotoxic rats [6, 14]. Mice treated with carvacrol (100 mg/kg body weight) showed reduced nociceptive behaviors induced by acetic acid as compared to vehicle-treated controls [10]. In our preliminary study, carvacrol supplemented to the HFD at 0.01, 0.05, and 0.1% levels for 28 days resulted in a dose-dependent reduction in the body weight of mice (data not shown). On the basis of these results, animals were fed 0.1% carvacrol for a longer period in the present study. Considering that the LD50 value for a single i.g. administration of carvacrol to rat was 810 mg/kg body weight in an acute toxicity study [15], the 0.1% carvacrol supplemented in the diet (equivalent to 100 mg/kg body weight) appears to have no harmful effect. The daily carvacrol intake of the mice in our study (100 mg/kg body weight) was equivalent to an intake of approximately 8.1 mg/kg human body weight (486 mg/60 kg person), when calculated on the basis of normalization to body surface area as recommended by Reagan-Shaw et al. and the US Food and Drug Administration (http://www.fda.gov/cder/cancer/animalframe.htm). The daily doses of commercial dietary supplements range from 9 to 288 mg carvacrol (0.15–4.8 mg/kg body weight) for a 60 kg human.Several studies have demonstrated that the inactivation of SIRT1-AMPK signaling increases lipogenesis and represses rates of fatty acid oxidation in the livers of HFD-fed mice. Inactivation of SIRT1 leads to decreased deacetylation of Lys48 and possibly other key lysine residues on LKB1. This, in turn, inhibits LKB1 binding to STE20-related adaptor protein and mouse embryo scaffold protein, which inactivates its kinase activity and leads to the inhibition of AMPK phosphorylation [16]. Inactivation of AMPK through S6K1 activates LXRα, leading to the expression of target genes such as CD36, leptin, and FAS, which may contribute to increased fat accumulation in the liver. At the same time, inactivated AMPK increases ACC phosphorylation, subsequently decreasing the level of CPT1 in the liver. The consequence of this may be a decrease in fatty acid oxidation rates in the liver. In the present study, carvacrol reversed the HFD-induced upregulation of hepatic genes involved in lipogenesis (S6K1, LXRα, SREBP1c, FAS, leptin, and CD36) and HFD-induced downregulation of hepatic genes involved in fatty acid oxidation (SIRT1, AMPK, and CPT1). Accordingly, changes in expression of genes involved in lipogenesis and fatty acid oxidation may have contributed to the reduction of hepatic triglyceride and free fatty acid concentrations in CSD-fed mice.The cells that internalize exogenous cholesterol repress endogenous cholesterol biosynthesis and LDLR expression in response to cholesterol loading. The hepatic cholesterol depletion was associated with compensatory mechanisms aimed at increasing hepatic cholesterol, including upregulation of HMGCR and LDLR [5]. In the present study, carvacrol decreased the HFD-induced increase in hepatic cholesterol concentrations and, simultaneously, increased the mRNA expression of hepatic HMGCR and LDLR. The elevated HMGCR and LDLR mRNA levels may be secondary to the reduced hepatic cholesterol concentrations induced by carvacrol supplementation. Another important protective mechanism against hepatic cholesterol accumulation is cellular efflux of cholesterol and bile acid biosynthesis [17, 18]. In the present study, carvacrol reversed the HFD-induced downregulation of CYP7A1 and CYP8B1 genes involved in bile acid biosynthesis and ABCG5 and ABCG8 genes involved in cholesterol efflux in the liver of mice. Therefore, the increased expression of these genes might contribute to the lower cholesterol concentration in the liver of CSD-fed mice.The present study showed that carvacrol reversed the HFD-induced increase in free cholesterol and cholesterol ester concentrations in the liver of mice. In the hepatocyte, cholesterol exists as free cholesterol and as cholesterol esters [19]. It has been suggested that an increase in the intrahepatic free cholesterol concentration is rapidly balanced by an increase in the rate of cholesterol esterification to prevent excess cellular free cholesterol accumulation [20]. A recent study showed that the increased cholesterol ester in lipid droplets could limit the hydrolysis of triglycerides and decrease hepatic triglyceride secretion out of cells, leading to hepatic steatosis in the liver of mice fed a low-fat diet containing cholesterol [4]. Therefore, the protective action of carvacrol against hepatic steatosis might involve not only enhanced SIRT1-AMPK signaling, but also a decreased concentration of cholesterol ester.TLRs play an important role in the innate immune system by activating inflammatory pathways in response to microbial agents [21]. TLR2 and 4 initiate shared and distinct signaling pathways by recruiting various combinations of the Toll-interleukin 1 receptor domain-containing adaptor proteins MyD88, TIRAP (Mal), TRIF, and TRAM. These signaling pathways activate the transcription factor IRF5, leading to the production of inflammatory cytokines. TLR4 also activates the transcription factor IRF3, leading to the production of type I interferons [21, 22]. TLR2- and 4-mediated signaling has emerged as a major mechanism involved in regulating inflammatory responses in mouse models of HFD-induced steatosis [23, 24]. Although no infiltration of inflammatory cells was detected in the livers of CSD- and HFD-fed mice, the expressions of proinflammatory cytokines (TNFα, IFNα, and IL-6) and their upstream signaling molecules (TLR2/4, TIRAP, TRIF, TRAF6, and IRF5) were decreased in CSD-fed mice compared with HFD-fed mice. The HFD-induced elevations in plasma TNFα and MCP1 concentrations were also significantly reversed by carvacrol supplementation. These findings support the recent in vivo studies on the anti-inflammatory activity of carvacrol. Guimaraes et al. [25] revealed that carvacrol significantly decreased TNF-α levels in pleural lavage and suppressed the recruitment of leukocytes without altering the morphological profile of these cells. Carvacrol has been reported to cause anti-inflammatory effects by reducing the production of inflammatory mediators, such as IL-1β and prostanoids, possibly through the induction of IL-10 release in a classical inflammation mouse model [26].Our results are in accordance with previous studies showing that at the early stage of obesity induced by the HFD, the expression levels of the proinflammatory cytokines were increased prior to macrophage infiltration [23, 27]. HFD-induced fatty liver diseases can progress from simple steatosis to nonalcoholic steatohepatitis (NASH, fatty changes with inflammation and hepatocellular injury or fibrosis). It is well established that mice fed the HFD for 10 weeks showed simple steatosis with the absence of necrosis or signs of inflammation [28]. Although NASH did not develop in our 10-week experiment, upregulation of proinflammatory cytokines and profibrotic genes could have facilitated the deterioration of steatosis to NASH if the experiment had been conducted for a longer duration. Accordingly, the carvacrol-mediated reduction in the expressions of proinflammatory cytokines and plasma MCP1 and TNFα concentrations in the livers of HFD-fed mice may contribute to decreased infiltration of macrophage into the liver.In conclusion, carvacrol supplementation (0.1%) suppressed the HFD-induced increases in liver weight, hepatic lipid levels, plasma activities of ALT and AST, and the steatosis score in mice. The protective action of carvacrol against HFD-induced hepatic steatosis in mice appears to be mediated through the downregulation of genes involved in lipogenesis and upregulation of genes involved in fatty acid oxidation via SIRT1-AMPK signaling. Furthermore, carvacrol supplementation also provoked decreased expression of genes involved in TLR-mediated signaling cascades and reduced concentrations of plasma TNFα and MCP1, which may diminish hepatic inflammatory stress (Figure 6).(a) Proposed mechanism for the protective effects of carvacrol against hepatic steatosis in mice. Carvacrol decreased the expression of genes and phosphorylation of protein involved in lipogenesis, whereas it increased the expression of genes and phosphorylation of proteins involved in fatty acid oxidation in the livers of HFD-fed mice. (b) Schematic overview of cholesterol homeostasis and the effects of carvacrol in the livers of HFD-fed mice. Carvacrol lowers cholesterol content by reversing the HFD-induced downregulation of genes involved in cholesterol homeostasis. (c) Schematic overview of the genes regulated by carvacrol in TLR2- and 4-signaling pathway.
(a)
Lipogenesis and fatty acid oxidation
(b)
Cholesterol homeostasis
(c)
TLR 2-, 4-mediated signaling
---
*Source: 290104-2013-02-20.xml* | 290104-2013-02-20_290104-2013-02-20.md | 44,458 | Carvacrol Protects against Hepatic Steatosis in Mice Fed a High-Fat Diet by Enhancing SIRT1-AMPK Signaling | Eunkyung Kim; Youngshim Choi; Jihee Jang; Taesun Park | Evidence-Based Complementary and Alternative Medicine
(2013) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2013/290104 | 290104-2013-02-20.xml | ---
## Abstract
We investigated the protective effect of carvacrol against high-fat-diet-induced hepatic steatosis in mice and the potential underlying molecular mechanisms. Mice were fed a normal diet, high-fat diet, or carvacrol-supplemented high-fat diet for 10 weeks. Compared to mice fed the high-fat diet, those fed the carvacrol-supplemented diet showed significantly lower hepatic lipid levels and reduced plasma activities of alanine aminotransferase and aspartate aminotransferase and plasma concentrations of monocyte chemoattractant protein 1 and tumor necrosis factorα. Carvacrol decreased the expression of LXRα, SREBP1c, FAS, leptin, and CD36 genes and phosphorylation of S6 kinase 1 protein involved in lipogenesis, whereas it increased the expression of SIRT1 and CPT1 genes and phosphorylation of liver kinase B1, AMP-activated protein kinase, and acetyl-CoA carboxylase proteins involved in fatty acid oxidation in the liver of mice fed the high-fat diet. These results suggest that carvacrol prevents HFD-induced hepatic steatosis by activating SIRT1-AMPK signaling.
---
## Body
## 1. Introduction
Simple hepatic steatosis, once considered benign, is now being recognized as a condition that may lead to steatohepatitis (hepatic steatosis with inflammation), fibrosis, and ultimately cirrhosis. The risk factors associated with hepatic steatosis are varied and include diabetes mellitus [1], hypertension [2], and obesity [3]. Several studies suggest that excessive fat accumulation in the liver occurs due to increased hepatic de novo lipogenesis, impaired fatty acid oxidation, or export of triglycerides. Mounting evidence suggests that a high-fat diet (HFD) causes enhanced lipogenesis and impaired fatty acid oxidation by inhibiting AMP-activated protein kinase (AMPK) activation through Sirtuin 1 (SIRT1), leading to the development of hepatic steatosis.The role of dietary cholesterol, with the subsequent increased hepatic esterification of cholesterol and its association to hepatic triglyceride accumulation, is a new paradigm for hepatic steatosis [4]. Cholesterol is accumulated in the liver under excess dietary cholesterol intake by disrupting the balance among steroid hormone synthesis, cholesterol uptake, and cholesterol efflux [5]. Accumulated cholesterol is esterified by acyl-coenzyme A:cholesterol acyltransferase (ACAT) in the liver, where some of it can be stored within hepatocytes in lipid droplets as cholesterol esters. When excess stored cholesterol ester molecules are present in the liver, the mobilization of hepatic triglyceride is limited and triglyceride secretion is reduced, resulting in the retention of neutral lipids as lipid droplets within the liver [4].Carvacrol [isopropyl-ortho-cresol, C6H3(OH)(C3H7)] is a predominant monoterpene phenol which occurs in many essential oils of the family Labiatae including Origanum, Satureja, Thymbra, Thymus, and Coridothymus species [6]. Carvacrol is a food additive approved by the US Food and Drug Administration and is a legally registered flavoring and foodstuff in the Council of Europe (2000). It is reported that carvacrol appears to be slowly adsorbed into the rabbit intestine after oral administration [7]. After 22 h, about 30% of 1.5 g carvacrol was still in the gastrointestinal tract while 45% was absorbed into the intestines in rabbit [7]. Previous in vitro studies demonstrated positive effects of carvacrol on inflammation, cancer, and oxidants [8–10]. It was found to decrease cyclooxygenase-2 expression in human macrophage-like U937 cells [8], Bcl2/Bax ratio and poly(ADP-ribose) polymerase-1 cleavage in breast cancer cells [9], and lipid peroxidation induced by reactive free radicals [10]. Several rodent studies have shown that carvacrol provides protection against various pharmacological properties, including antidepressant [11], anxiolytic-like [12], antinociceptive [10], and hypotensive [13] activities. Furthermore, Aristatile et al. reported that carvacrol exerted a beneficial effect in hepatotoxicity through decreased activities of plasma alanine aminotransferase (ALT) and aspartate aminotransferase (AST) in D-galactosamine-induced hepatotoxic rats [6, 14]. Although a number of studies have been carried out to investigate the biochemical roles of carvacrol, the protective activity of carvacrol against hepatic steatosis has never been reported. Therefore, the main objective of this study was to investigate the protective effects of carvacrol against HFD-induced simple hepatic steatosis in mice and to study potential molecular mechanisms, focusing on the expression of genes involved in lipogenesis and fatty acid oxidation in the liver.
## 2. Experimental Procedures
### 2.1. Animal Studies
Male C57BL/6N mice (5 weeks old) were obtained from Orient Bio (Gyeonggi-do, South Korea) and maintained under 12 h light-dark cycles with free access to food and water. They were divided into 3 experimental diet groups (n=8 per group): normal diet (ND), HFD, and carvacrol-supplemented diet (CSD). The ND was a purified diet based on the AIN-76 rodent diet composition. The HFD was identical to the ND, except that 200 g fat/kg (170 g lard plus 30 g corn oil) and 1% cholesterol were added to it. The CSD was identical to the HFD and contained 0.1% (w/w) carvacrol (Sigma, MO, USA). The experimental diets were given ad libitum for 10 weeks in the form of pellets. At the end of the experiment, all animals were anesthetized with ether, blood was collected in EDTA-coated tubes and centrifuged, and plasma was stored at −70°C. Livers were removed, weighed, and stored at −70°C. All mice were housed in the specific pathogen-free facility of the Yonsei University, Seoul, Korea. This study was approved by the Institutional Animal Care and Use Committee of Yonsei University.
### 2.2. Biochemical Analysis
Plasma activities of ALT and AST were measured using commercial kits (Bio-Clinical System, Gyeonggi-do, South Korea). Hepatic lipids were extracted from whole liver homogenates using a modified Folch extraction. Levels of triglycerides, free fatty acids, and cholesterol in hepatic lipid extracts were measured using commercial kits (Bio-Clinical System, Gyeonggi-do, South Korea). For measurement of hepatic cholesteryl esters, lipids were extracted from frozen liver tissues by thawing and homogenizing in chloroform (Sigma) : isopropanol (Sigma) : NP40 (Sigma) (7 : 11 : 0.1). The tissue homogenates were centrifuged (15,000 ×g, 10 min, 4°C) and the resulting supernatants (organic phase) were used for the cholesterol ester analysis. Total cholesterol and free cholesterol levels were measured using commercially available kits (ABCAM, Cambridge, UK). The level of cholesteryl esters was calculated by subtraction of the obtained values of free cholesterol from total cholesterol. Plasma levels of tumor necrosis factor-alpha (TNFα) and monocyte chemoattractant protein-1 (MCP1) were measured using ELISA kits (ID Labs, MA, USA).
### 2.3. Liver Histology
Liver sections were formalin fixed and paraffin embedded prior to sectioning. All sections were then stained with hematoxylin (Sigma) and eosin (Sigma), encoded, and assessed for steatosis and inflammation, by an expert liver pathologist blinded to the identity of the groups. The grade of steatosis was scored as 0 = no steatosis; 1 = minimal steatosis; 2 = slight steatosis; 3 = moderate steatosis; 4 = marked steatosis; 5 = severe steatosis. The grade of lobular inflammation was scored as 0 = no inflammatory foci; 1 = 1-2 inflammatory foci; 2 = 3-4 inflammatory foci; 3 = <4 inflammatory foci.
### 2.4. Hepatic Gene Expression Analysis
Total RNA was isolated from liver tissue by acid guanidinium thiocyanate-phenol chloroform extraction using Trizol reagent (Invitrogen, CA, USA). Four micrograms of total RNA were reverse transcribed using the Superscript II kit (Invitrogen, CA, USA) according to the manufacturer’s recommendations. Primers used for polymerase chain reaction (PCR) are listed in Table1. Taq DNA polymerase was used to amplify transcribed genes using a PCR program of a denaturation step of 10 min at 94°C, followed by 30 cycles of 30 s at 94°C, 30 s at 55°C, and 1 min at 72°C, then 10 min at 72°C, and terminated by an elongation step at 72°C for 10 min. PCR products were size fractionated on a 2% agarose gel and stained with ethidium bromide.Table 1
Primer sequences and PCR conditions.
Gene description
Primers
Sequences (5′ → 3′)
Annealingtemperature (°C)
PCRproduct (bp)
Sirtuin1 (SIRT1)
F
CAGAACCACCAAAGCGGAAA
55
693
R
GGCACTTCATGGGGTATAGA
Liver X receptor(LXRα)
F
TCCTACACGAGGATCAAGCG
55
119
R
AGTCGCAATGCAAACACCTG
SREBP1c (SREBP1c)
F
TTGTGGAGCTCAAAGACCTG
55
94
R
TGCAAGAAGCGGATGTAGTC
CD36 antigen (CD36)
F
ATGACGTGGCAAAGAACAGC
55
160
R
GAAGGCTCAAAGATGGCTCC
Lipoprotein lipase (leptin)
F
CTCCAAGGTTGTCCAGGGTT
55
143
R
AAAACTCCCCACAGAATGGG
Fatty acid synthase (FAS)
F
AGGGGTCGACCTGGTCCTCA
65
132
R
GCCATGCCCAGAGGGTGGTT
Carnitine palmitoyltransferase I (CPT1)
F
CTCTGCTGGCCGTTGTTGT
55
120
R
GGCAAGTTCTGCCTCACGTA
Sterol regulatory element-binding protein-2 (SREBP2)
F
CACAATATCATTGAAAAGCG
60
200
R
TTTTTCTGATTGGCCAGCTT
3-Hydroxy-3-methylglutaryl-CoA reductase (HMGCR)
F
TAAGATTCAACAACTCTGCT
55
101
R
TGTGGCCAGGAGTTTGGTGA
Farnesyl diphosphate synthase (FDPS)
F
ATGGAGATGGGCGAGTTCTT
60
80
R
CCGACCTTTCCCGTCACA
Cytochrome P450, family 51 (CYP51)
F
ACGCTGCCTGGCTATTGC
55
76
R
TTGATCTCTCGATGGGCTCTATC
Low-density lipoprotein receptor (LDLR)
F
AGGCTGTGGGCTCCATAGG
60
72
R
TGCGGTCCAGGGTCATCT
ATP-binding cassette, sub-family G, member 5 (ABCG5)
F
CGTGGCGGACCAAATGA
55
155
R
CGCTCGCCACTGGAAATT
ATP-binding cassette, sub-family G, member 8 (ABCG8)
F
TGCCCACCTTCCACATGTC
60
60
R
ATGAAGCCGGCAGTAAGGTAGA
Cytochrome P450, family 7, subfamily A, polypeptide 1 (CYP7A1)
F
CAGGGAGATGCTCTGTGTTCA
60
121
R
AGGCATACATCCCTTCCGTGA
Cytochrome P450, family 8, subfamily A, polypeptide 1 (CYP8B1)
F
AAGGCTGGCTTCCTGAGCTT
60
74
R
AACAGCTCATCGGCCTCATC
Acyl-coenzyme A: cholesterol acyltransferase (ACAT1)
F
AGCGAGACAGATGCTCATGC
55
107
R
CAACCAAACCTCCGTCACTG
Toll-like receptor 2 (TLR2)
F
GAGCATCCGAATTGCATCAC
55
120
R
TATGGCCACCAAGATCCAGA
Toll-like receptor 4 (TLR4)
F
TCGAATCCTGAGCAAACAGC
55
199
R
CCCGGTAAGGTCCATGCTAT
Toll-interleukin 1 receptor domain-containing adaptor protein (Tirap)
F
GCTTCCAGGGGATCTGATGT
55
183
R
AAGCAAGCCTACCACGGACT
TIR-domain-containing adapter-inducing interferon-β (TRIF)
F
ATGGATAACCCAGGGCCTT
55
528
R
TTCTGGTCACTGCAGGGGAT
Interferon regulatory factor 5 (IRF5)
F
ACCCGGATCTCAAAGACCAC
55
166
R
TTATTGCATGCCAACTGGGT
TNF alpha (TNFα)
F
TGTCTCAGCCTCTTCTCATT
55
156
R
AGATGATCTGAGTGTGAGGG
Interleukin 1 beta (IL-1β)
F
GTTGACGGACCCCAAAAGAT
55
129
R
TGATACTGCCTGCCTGAAGC
Interferon beta (IFNβ)
F
TGGAGCAGCTGAATGGAAAG
55
122
R
GAGCATCTCTTGGATGGCAA
Glyceraldehyde-3-phosphate dehydrogenase (GAPDH)
F
CCCATGTTTGTGATGGGTGT
55
161
R
GTGATGGCATGGACTGTGGT
### 2.5. Western Blot Analysis
Liver tissues of each mouse were homogenized at 4°C in an extraction buffer containing 100 mM Tris-HCl, pH 7.4, 5 mM EDTA, 50 mM NaCl, 50 mM sodium pyrophosphate, 50 mM NaF, 100 mM orthovanadate, 1% Triton X-100, 1 mM phenylmethanesulfonyl fluoride, 2μg/mL aprotinin, 1 μg/mL pepstatin A, and 1 μg/mL leupeptin. The tissue homogenates were centrifuged (1300 ×g, 20 min, 4°C) and the resulting supernatants (whole-tissue extracts) were used for western blot analysis. The total protein concentrations of the whole-tissue extracts were determined by Bradford assay (Bio-Rad, CA, USA). Protein samples were separated with 8% sodium dodecyl sulfate-polyacrylamide gel electrophoresis, transferred onto a nitrocellulose membrane (Amersham, Buckinghamshire, UK), and hybridized with primary antibodies (diluted 1 : 1000) overnight at 4°C. The membrane was then incubated with the appropriate secondary antibody and immunoreactive signals were detected using a chemiluminescent detection system (Amersham, Buckinghamshire, UK). The signals were quantified using the Quantity One analysis software (Bio-Rad, CA, USA). Antibodies to liver kinase B1 (LKB1), phospho-LKB (Ser428), AMP-activated protein kinase (AMPK), phospho-AMPK (Thr172), acetyl-CoA carboxylase (ACC), phospho-ACC (Ser79), S6 kinase 1 (S6K1), phospho-S6K1 (Thr389), interferon regulatory factor 3 (IRF3), phospho-IRF3 (Ser396), and β-catenin were purchased from Cell Signaling Technology (Cell Signaling Technology, MA, USA) and antibody to β-actin was obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA).
### 2.6. Statistical Analysis
The mean ± SEM of body weight gain, liver weight, and plasma and hepatic biochemistries was determined from 3 independent experiments. Reverse transcription (RT)-PCR and Western blot data were presented as mean ± SEM of at least 3 separate experiments. All of the analyses were performed using SPSS statistical software. Statistical analysis of results was performed using one-way analysis of variance (one-way ANOVA test), followed by Duncan’s multiple-range tests. Statistical significance was set atP<0.05.
## 2.1. Animal Studies
Male C57BL/6N mice (5 weeks old) were obtained from Orient Bio (Gyeonggi-do, South Korea) and maintained under 12 h light-dark cycles with free access to food and water. They were divided into 3 experimental diet groups (n=8 per group): normal diet (ND), HFD, and carvacrol-supplemented diet (CSD). The ND was a purified diet based on the AIN-76 rodent diet composition. The HFD was identical to the ND, except that 200 g fat/kg (170 g lard plus 30 g corn oil) and 1% cholesterol were added to it. The CSD was identical to the HFD and contained 0.1% (w/w) carvacrol (Sigma, MO, USA). The experimental diets were given ad libitum for 10 weeks in the form of pellets. At the end of the experiment, all animals were anesthetized with ether, blood was collected in EDTA-coated tubes and centrifuged, and plasma was stored at −70°C. Livers were removed, weighed, and stored at −70°C. All mice were housed in the specific pathogen-free facility of the Yonsei University, Seoul, Korea. This study was approved by the Institutional Animal Care and Use Committee of Yonsei University.
## 2.2. Biochemical Analysis
Plasma activities of ALT and AST were measured using commercial kits (Bio-Clinical System, Gyeonggi-do, South Korea). Hepatic lipids were extracted from whole liver homogenates using a modified Folch extraction. Levels of triglycerides, free fatty acids, and cholesterol in hepatic lipid extracts were measured using commercial kits (Bio-Clinical System, Gyeonggi-do, South Korea). For measurement of hepatic cholesteryl esters, lipids were extracted from frozen liver tissues by thawing and homogenizing in chloroform (Sigma) : isopropanol (Sigma) : NP40 (Sigma) (7 : 11 : 0.1). The tissue homogenates were centrifuged (15,000 ×g, 10 min, 4°C) and the resulting supernatants (organic phase) were used for the cholesterol ester analysis. Total cholesterol and free cholesterol levels were measured using commercially available kits (ABCAM, Cambridge, UK). The level of cholesteryl esters was calculated by subtraction of the obtained values of free cholesterol from total cholesterol. Plasma levels of tumor necrosis factor-alpha (TNFα) and monocyte chemoattractant protein-1 (MCP1) were measured using ELISA kits (ID Labs, MA, USA).
## 2.3. Liver Histology
Liver sections were formalin fixed and paraffin embedded prior to sectioning. All sections were then stained with hematoxylin (Sigma) and eosin (Sigma), encoded, and assessed for steatosis and inflammation, by an expert liver pathologist blinded to the identity of the groups. The grade of steatosis was scored as 0 = no steatosis; 1 = minimal steatosis; 2 = slight steatosis; 3 = moderate steatosis; 4 = marked steatosis; 5 = severe steatosis. The grade of lobular inflammation was scored as 0 = no inflammatory foci; 1 = 1-2 inflammatory foci; 2 = 3-4 inflammatory foci; 3 = <4 inflammatory foci.
## 2.4. Hepatic Gene Expression Analysis
Total RNA was isolated from liver tissue by acid guanidinium thiocyanate-phenol chloroform extraction using Trizol reagent (Invitrogen, CA, USA). Four micrograms of total RNA were reverse transcribed using the Superscript II kit (Invitrogen, CA, USA) according to the manufacturer’s recommendations. Primers used for polymerase chain reaction (PCR) are listed in Table1. Taq DNA polymerase was used to amplify transcribed genes using a PCR program of a denaturation step of 10 min at 94°C, followed by 30 cycles of 30 s at 94°C, 30 s at 55°C, and 1 min at 72°C, then 10 min at 72°C, and terminated by an elongation step at 72°C for 10 min. PCR products were size fractionated on a 2% agarose gel and stained with ethidium bromide.Table 1
Primer sequences and PCR conditions.
Gene description
Primers
Sequences (5′ → 3′)
Annealingtemperature (°C)
PCRproduct (bp)
Sirtuin1 (SIRT1)
F
CAGAACCACCAAAGCGGAAA
55
693
R
GGCACTTCATGGGGTATAGA
Liver X receptor(LXRα)
F
TCCTACACGAGGATCAAGCG
55
119
R
AGTCGCAATGCAAACACCTG
SREBP1c (SREBP1c)
F
TTGTGGAGCTCAAAGACCTG
55
94
R
TGCAAGAAGCGGATGTAGTC
CD36 antigen (CD36)
F
ATGACGTGGCAAAGAACAGC
55
160
R
GAAGGCTCAAAGATGGCTCC
Lipoprotein lipase (leptin)
F
CTCCAAGGTTGTCCAGGGTT
55
143
R
AAAACTCCCCACAGAATGGG
Fatty acid synthase (FAS)
F
AGGGGTCGACCTGGTCCTCA
65
132
R
GCCATGCCCAGAGGGTGGTT
Carnitine palmitoyltransferase I (CPT1)
F
CTCTGCTGGCCGTTGTTGT
55
120
R
GGCAAGTTCTGCCTCACGTA
Sterol regulatory element-binding protein-2 (SREBP2)
F
CACAATATCATTGAAAAGCG
60
200
R
TTTTTCTGATTGGCCAGCTT
3-Hydroxy-3-methylglutaryl-CoA reductase (HMGCR)
F
TAAGATTCAACAACTCTGCT
55
101
R
TGTGGCCAGGAGTTTGGTGA
Farnesyl diphosphate synthase (FDPS)
F
ATGGAGATGGGCGAGTTCTT
60
80
R
CCGACCTTTCCCGTCACA
Cytochrome P450, family 51 (CYP51)
F
ACGCTGCCTGGCTATTGC
55
76
R
TTGATCTCTCGATGGGCTCTATC
Low-density lipoprotein receptor (LDLR)
F
AGGCTGTGGGCTCCATAGG
60
72
R
TGCGGTCCAGGGTCATCT
ATP-binding cassette, sub-family G, member 5 (ABCG5)
F
CGTGGCGGACCAAATGA
55
155
R
CGCTCGCCACTGGAAATT
ATP-binding cassette, sub-family G, member 8 (ABCG8)
F
TGCCCACCTTCCACATGTC
60
60
R
ATGAAGCCGGCAGTAAGGTAGA
Cytochrome P450, family 7, subfamily A, polypeptide 1 (CYP7A1)
F
CAGGGAGATGCTCTGTGTTCA
60
121
R
AGGCATACATCCCTTCCGTGA
Cytochrome P450, family 8, subfamily A, polypeptide 1 (CYP8B1)
F
AAGGCTGGCTTCCTGAGCTT
60
74
R
AACAGCTCATCGGCCTCATC
Acyl-coenzyme A: cholesterol acyltransferase (ACAT1)
F
AGCGAGACAGATGCTCATGC
55
107
R
CAACCAAACCTCCGTCACTG
Toll-like receptor 2 (TLR2)
F
GAGCATCCGAATTGCATCAC
55
120
R
TATGGCCACCAAGATCCAGA
Toll-like receptor 4 (TLR4)
F
TCGAATCCTGAGCAAACAGC
55
199
R
CCCGGTAAGGTCCATGCTAT
Toll-interleukin 1 receptor domain-containing adaptor protein (Tirap)
F
GCTTCCAGGGGATCTGATGT
55
183
R
AAGCAAGCCTACCACGGACT
TIR-domain-containing adapter-inducing interferon-β (TRIF)
F
ATGGATAACCCAGGGCCTT
55
528
R
TTCTGGTCACTGCAGGGGAT
Interferon regulatory factor 5 (IRF5)
F
ACCCGGATCTCAAAGACCAC
55
166
R
TTATTGCATGCCAACTGGGT
TNF alpha (TNFα)
F
TGTCTCAGCCTCTTCTCATT
55
156
R
AGATGATCTGAGTGTGAGGG
Interleukin 1 beta (IL-1β)
F
GTTGACGGACCCCAAAAGAT
55
129
R
TGATACTGCCTGCCTGAAGC
Interferon beta (IFNβ)
F
TGGAGCAGCTGAATGGAAAG
55
122
R
GAGCATCTCTTGGATGGCAA
Glyceraldehyde-3-phosphate dehydrogenase (GAPDH)
F
CCCATGTTTGTGATGGGTGT
55
161
R
GTGATGGCATGGACTGTGGT
## 2.5. Western Blot Analysis
Liver tissues of each mouse were homogenized at 4°C in an extraction buffer containing 100 mM Tris-HCl, pH 7.4, 5 mM EDTA, 50 mM NaCl, 50 mM sodium pyrophosphate, 50 mM NaF, 100 mM orthovanadate, 1% Triton X-100, 1 mM phenylmethanesulfonyl fluoride, 2μg/mL aprotinin, 1 μg/mL pepstatin A, and 1 μg/mL leupeptin. The tissue homogenates were centrifuged (1300 ×g, 20 min, 4°C) and the resulting supernatants (whole-tissue extracts) were used for western blot analysis. The total protein concentrations of the whole-tissue extracts were determined by Bradford assay (Bio-Rad, CA, USA). Protein samples were separated with 8% sodium dodecyl sulfate-polyacrylamide gel electrophoresis, transferred onto a nitrocellulose membrane (Amersham, Buckinghamshire, UK), and hybridized with primary antibodies (diluted 1 : 1000) overnight at 4°C. The membrane was then incubated with the appropriate secondary antibody and immunoreactive signals were detected using a chemiluminescent detection system (Amersham, Buckinghamshire, UK). The signals were quantified using the Quantity One analysis software (Bio-Rad, CA, USA). Antibodies to liver kinase B1 (LKB1), phospho-LKB (Ser428), AMP-activated protein kinase (AMPK), phospho-AMPK (Thr172), acetyl-CoA carboxylase (ACC), phospho-ACC (Ser79), S6 kinase 1 (S6K1), phospho-S6K1 (Thr389), interferon regulatory factor 3 (IRF3), phospho-IRF3 (Ser396), and β-catenin were purchased from Cell Signaling Technology (Cell Signaling Technology, MA, USA) and antibody to β-actin was obtained from Santa Cruz Biotechnology (Santa Cruz, CA, USA).
## 2.6. Statistical Analysis
The mean ± SEM of body weight gain, liver weight, and plasma and hepatic biochemistries was determined from 3 independent experiments. Reverse transcription (RT)-PCR and Western blot data were presented as mean ± SEM of at least 3 separate experiments. All of the analyses were performed using SPSS statistical software. Statistical analysis of results was performed using one-way analysis of variance (one-way ANOVA test), followed by Duncan’s multiple-range tests. Statistical significance was set atP<0.05.
## 3. Results
### 3.1. Carvacrol Reverses HFD-Induced Hepatic Steatosis
At week 10, male mice fed the CSD displayed a significant reduction in final body weight compared with HFD-fed mice (Figure1(a)). There was no difference in the food consumption among groups (data not shown). CSD-fed mice showed significant decreases in liver weight (43%, P<0.05) compared to HFD-fed mice (Figure 1(b)). Hepatic triglycerides (37%, P<0.05), free fatty acids (57%, P<0.05), total cholesterol (26%, P<0.05), and cholesteryl ester (41%, P<0.05) levels were significantly higher in HFD-fed mice than in ND-fed mice, whereas CSD-fed mice were completely resistant to HFD-induced hepatic lipid accumulation (Figures 1(c)–1(f)). Histological sections of liver tissue from HFD-fed mice showed predominantly large lipid-filled vacuoles. Liver sections from CSD-fed mice revealed a reduction of lipid accumulation in the form of lipid droplets, or even small lipid droplets (Figure 2(a)). The hepatic steatosis scores in CSD-fed mice were significantly lower than scores in HFD-fed mice (Figure 2(b)). Evaluation of hepatic inflammation using hematoxylin and eosin liver staining revealed no significant differences between CSD- and HFD-fed mice (Figure 2(c)). As expected, plasma activities of ALT (47%, P<0.05) and AST (47%, P<0.05) were both substantially elevated by the HFD, and the CSD resulted in significant reductions in these plasma activities (Figure 2(d)).CSD mice are resistant to HFD-induced liver enlargement and hepatic lipid levels. (a) Final body weight of mice on ND, HFD, or CSD. (b) Weights of livers and (c–f) hepatic triglyceride, FFA, total cholesterol, and cholesterol ester levels. Data are mean ± SEM,n=8. *P<0.05.
(a)
(b)
(c)
(d)
(e)
(f)Carvacrol reduced hepatic lipid droplet and activities of ALT and AST. (a) Hematoxylin and eosin staining of representative liver section (magnification ×100). (b) Mean steatosis score. (c) Mean inflammation score. (d) Plasma ALT and AST activities. Data are mean ± SEM,n=8. *P<0.05.
(a)
(b)
(c)
(d)
### 3.2. Carvacrol Modulates the Expression of Genes Involved in Lipid Metabolism
To gain insight into the protective mechanisms of carvacrol against hepatic steatosis in HFD-fed mice, we examined hepatic mRNA levels for genes involved in lipogenesis and fatty acid oxidation by RT-PCR analysis. SIRT1 and AMPK are key regulators of both lipogenesis and fatty acid oxidation in the liver. Expression of SIRT1 and phosphorylation of AMPK protein were significantly increased in the livers of CSD-fed mice compared with HFD-fed mice (Figures3(a) and 3(b)). Hepatic mRNA levels of the lipogenic genes, including liver X receptor alpha (LXRα), sterol regulatory element binding transcription factor 1 (SREBP1c), fatty acid synthase (FAS), leptin, and CD36, were also significantly lower in CSD-fed mice than in HFD-fed mice (Figure 3(a)). In addition, expression of carnitine palmitoyltransferase 1 (CPT1), a reflection of mitochondrial β-fatty acid oxidation capacity, was significantly increased in the liver of CSD-fed mice compared with HFD-fed mice (Figure 3(a)).Enhanced hepatic SIRT1-AMPK signaling in CSD-fed mice. (a) Hepatic mRNA expression levels of SIRT1, LXRα, SREBP1c, FAS, leptin, CD36, and CPT1 normalized to GAPDH relative to ND-fed mice. (b) Upper, representative western blot of phospho- and total AMPK in livers of ND, HFD, and CSD-fed mice. Lower, densitometric analysis of AMPK phosphorylation expressed as change relative to each control band. Data are shown as the mean ± SEM, n=8. *P<0.05.
(a)
(b)We also examined the effect of carvacrol on the expression of genes involved in cholesterol homeostasis in the liver. Hepatic mRNA levels of SREBP2 and its target gene LDLR, an important cholesterol influx transporter, were higher in CSD-fed mice than HFD-fed mice. CSD-fed mice had increased mRNA levels of genes involved in cholesterol synthesis, including 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), Farnesyl diphosphate synthase (FDPS), and Cytochrome P450, family 51 (CYP51) in the liver compared with HFD-fed mice. Expression of ACAT1 was significantly decreased in the livers of CSD-fed mice compared with HFD-fed mice (Figure4(a)). Expressions of ATP-binding cassette, subfamily G, members 5 and 8 (ABCG5, ABCG8) genes involved in cholesterol efflux, Cytochrome P450, family 7, subfamily A, polypeptide 1 (CYP7A1), and Cytochrome P450, family 8, subfamily A, polypeptide 1 (CYP8B1) genes involved in bile acid synthesis, were also higher in CSD-fed mice compared with HFD-fed mice (Figures 4(a) and 4(b)).Enhanced hepatic cholesterol metabolism in CSD-fed mice. (a and b) Hepatic mRNA expression levels of SREBP2, HMGCR, FDPS, CYP51, LDLR, ABCG5, ABCG8, ACAT1, CYP7A1, and CYP8B1 normalized to GAPDH relative to ND-fed mice. Data are shown as the mean ± SEM,n=8. *P<0.05.
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### 3.3. Carvacrol Inhibited the Expression of Genes Involved in Inflammation
In the livers of CSD-fed mice, levels of Toll-like receptors 2 and 4 (TLR2, TLR4) and their adaptor proteins (Toll-interleukin 1 receptor domain-containing adaptor protein (TIRAP) and TIR domain-containing adapter protein inducing interferon beta (TRIF)) were significantly reduced compared with their corresponding levels in HFD-fed mice (Figure5(a)). Phosphorylation of interferon regulatory factor-3 (IRF3) protein, a key transcriptional factor in interferon beta (IFNβ) induction, was decreased in the livers of CSD-fed mice compared to HFD-fed mice (Figure 5(b)). Significantly, higher levels of transcription factor interferon regulatory factor-5 (IRF5) and proinflammatory cytokines (interleukin [IL]-1β, IFNβ, and TNFα) were also found in the livers of CSD-fed mice, as compared to those in HFD-fed mice (Figure 5(a)). Mice that received carvacrol showed significantly lower plasma concentrations of MCP1 (−67%) and TNFα (−35%) in comparison with the values for HFD control mice (Figures 5(c) and 5(d)).Reduced hepatic TLR2- and 4-mediated signaling and plasma levels of inflammatory markers in CSD-fed mice. (a) Hepatic mRNA expression levels of TLR2, TLR4 and related genes normalized to GAPDH expression relative to ND-fed mice. (b) Representative blots of hepatic IRF3 and phosphorylated IRF3 proteins in total liver extracts from the ND-, HFD-, and CSD-fed mice. Blots were quantified and the data are presented as the ratio of phosphorylated IRF3 to native protein, with values normalized to ND-fed mice. (c and d) Plasma MCP1 and TNFα levels. Values are means ± SEM from 8 animals, *P<0.05.
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## 3.1. Carvacrol Reverses HFD-Induced Hepatic Steatosis
At week 10, male mice fed the CSD displayed a significant reduction in final body weight compared with HFD-fed mice (Figure1(a)). There was no difference in the food consumption among groups (data not shown). CSD-fed mice showed significant decreases in liver weight (43%, P<0.05) compared to HFD-fed mice (Figure 1(b)). Hepatic triglycerides (37%, P<0.05), free fatty acids (57%, P<0.05), total cholesterol (26%, P<0.05), and cholesteryl ester (41%, P<0.05) levels were significantly higher in HFD-fed mice than in ND-fed mice, whereas CSD-fed mice were completely resistant to HFD-induced hepatic lipid accumulation (Figures 1(c)–1(f)). Histological sections of liver tissue from HFD-fed mice showed predominantly large lipid-filled vacuoles. Liver sections from CSD-fed mice revealed a reduction of lipid accumulation in the form of lipid droplets, or even small lipid droplets (Figure 2(a)). The hepatic steatosis scores in CSD-fed mice were significantly lower than scores in HFD-fed mice (Figure 2(b)). Evaluation of hepatic inflammation using hematoxylin and eosin liver staining revealed no significant differences between CSD- and HFD-fed mice (Figure 2(c)). As expected, plasma activities of ALT (47%, P<0.05) and AST (47%, P<0.05) were both substantially elevated by the HFD, and the CSD resulted in significant reductions in these plasma activities (Figure 2(d)).CSD mice are resistant to HFD-induced liver enlargement and hepatic lipid levels. (a) Final body weight of mice on ND, HFD, or CSD. (b) Weights of livers and (c–f) hepatic triglyceride, FFA, total cholesterol, and cholesterol ester levels. Data are mean ± SEM,n=8. *P<0.05.
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(f)Carvacrol reduced hepatic lipid droplet and activities of ALT and AST. (a) Hematoxylin and eosin staining of representative liver section (magnification ×100). (b) Mean steatosis score. (c) Mean inflammation score. (d) Plasma ALT and AST activities. Data are mean ± SEM,n=8. *P<0.05.
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## 3.2. Carvacrol Modulates the Expression of Genes Involved in Lipid Metabolism
To gain insight into the protective mechanisms of carvacrol against hepatic steatosis in HFD-fed mice, we examined hepatic mRNA levels for genes involved in lipogenesis and fatty acid oxidation by RT-PCR analysis. SIRT1 and AMPK are key regulators of both lipogenesis and fatty acid oxidation in the liver. Expression of SIRT1 and phosphorylation of AMPK protein were significantly increased in the livers of CSD-fed mice compared with HFD-fed mice (Figures3(a) and 3(b)). Hepatic mRNA levels of the lipogenic genes, including liver X receptor alpha (LXRα), sterol regulatory element binding transcription factor 1 (SREBP1c), fatty acid synthase (FAS), leptin, and CD36, were also significantly lower in CSD-fed mice than in HFD-fed mice (Figure 3(a)). In addition, expression of carnitine palmitoyltransferase 1 (CPT1), a reflection of mitochondrial β-fatty acid oxidation capacity, was significantly increased in the liver of CSD-fed mice compared with HFD-fed mice (Figure 3(a)).Enhanced hepatic SIRT1-AMPK signaling in CSD-fed mice. (a) Hepatic mRNA expression levels of SIRT1, LXRα, SREBP1c, FAS, leptin, CD36, and CPT1 normalized to GAPDH relative to ND-fed mice. (b) Upper, representative western blot of phospho- and total AMPK in livers of ND, HFD, and CSD-fed mice. Lower, densitometric analysis of AMPK phosphorylation expressed as change relative to each control band. Data are shown as the mean ± SEM, n=8. *P<0.05.
(a)
(b)We also examined the effect of carvacrol on the expression of genes involved in cholesterol homeostasis in the liver. Hepatic mRNA levels of SREBP2 and its target gene LDLR, an important cholesterol influx transporter, were higher in CSD-fed mice than HFD-fed mice. CSD-fed mice had increased mRNA levels of genes involved in cholesterol synthesis, including 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR), Farnesyl diphosphate synthase (FDPS), and Cytochrome P450, family 51 (CYP51) in the liver compared with HFD-fed mice. Expression of ACAT1 was significantly decreased in the livers of CSD-fed mice compared with HFD-fed mice (Figure4(a)). Expressions of ATP-binding cassette, subfamily G, members 5 and 8 (ABCG5, ABCG8) genes involved in cholesterol efflux, Cytochrome P450, family 7, subfamily A, polypeptide 1 (CYP7A1), and Cytochrome P450, family 8, subfamily A, polypeptide 1 (CYP8B1) genes involved in bile acid synthesis, were also higher in CSD-fed mice compared with HFD-fed mice (Figures 4(a) and 4(b)).Enhanced hepatic cholesterol metabolism in CSD-fed mice. (a and b) Hepatic mRNA expression levels of SREBP2, HMGCR, FDPS, CYP51, LDLR, ABCG5, ABCG8, ACAT1, CYP7A1, and CYP8B1 normalized to GAPDH relative to ND-fed mice. Data are shown as the mean ± SEM,n=8. *P<0.05.
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(b)
## 3.3. Carvacrol Inhibited the Expression of Genes Involved in Inflammation
In the livers of CSD-fed mice, levels of Toll-like receptors 2 and 4 (TLR2, TLR4) and their adaptor proteins (Toll-interleukin 1 receptor domain-containing adaptor protein (TIRAP) and TIR domain-containing adapter protein inducing interferon beta (TRIF)) were significantly reduced compared with their corresponding levels in HFD-fed mice (Figure5(a)). Phosphorylation of interferon regulatory factor-3 (IRF3) protein, a key transcriptional factor in interferon beta (IFNβ) induction, was decreased in the livers of CSD-fed mice compared to HFD-fed mice (Figure 5(b)). Significantly, higher levels of transcription factor interferon regulatory factor-5 (IRF5) and proinflammatory cytokines (interleukin [IL]-1β, IFNβ, and TNFα) were also found in the livers of CSD-fed mice, as compared to those in HFD-fed mice (Figure 5(a)). Mice that received carvacrol showed significantly lower plasma concentrations of MCP1 (−67%) and TNFα (−35%) in comparison with the values for HFD control mice (Figures 5(c) and 5(d)).Reduced hepatic TLR2- and 4-mediated signaling and plasma levels of inflammatory markers in CSD-fed mice. (a) Hepatic mRNA expression levels of TLR2, TLR4 and related genes normalized to GAPDH expression relative to ND-fed mice. (b) Representative blots of hepatic IRF3 and phosphorylated IRF3 proteins in total liver extracts from the ND-, HFD-, and CSD-fed mice. Blots were quantified and the data are presented as the ratio of phosphorylated IRF3 to native protein, with values normalized to ND-fed mice. (c and d) Plasma MCP1 and TNFα levels. Values are means ± SEM from 8 animals, *P<0.05.
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## 4. Discussion
The 0.1% carvacrol dosage (equivalent to 100 mg/kg body weight) given to mice in our study was chosen on the basis of previous reports. In these reports,D-galactosamine-induced hepatotoxic rats treated with carvacrol (80 mg/kg body weight) had significantly decreased plasma ALT and AST activities, as well as hepatic free fatty acid and cholesterol levels in comparison with saline-treated hepatotoxic rats [6, 14]. Mice treated with carvacrol (100 mg/kg body weight) showed reduced nociceptive behaviors induced by acetic acid as compared to vehicle-treated controls [10]. In our preliminary study, carvacrol supplemented to the HFD at 0.01, 0.05, and 0.1% levels for 28 days resulted in a dose-dependent reduction in the body weight of mice (data not shown). On the basis of these results, animals were fed 0.1% carvacrol for a longer period in the present study. Considering that the LD50 value for a single i.g. administration of carvacrol to rat was 810 mg/kg body weight in an acute toxicity study [15], the 0.1% carvacrol supplemented in the diet (equivalent to 100 mg/kg body weight) appears to have no harmful effect. The daily carvacrol intake of the mice in our study (100 mg/kg body weight) was equivalent to an intake of approximately 8.1 mg/kg human body weight (486 mg/60 kg person), when calculated on the basis of normalization to body surface area as recommended by Reagan-Shaw et al. and the US Food and Drug Administration (http://www.fda.gov/cder/cancer/animalframe.htm). The daily doses of commercial dietary supplements range from 9 to 288 mg carvacrol (0.15–4.8 mg/kg body weight) for a 60 kg human.Several studies have demonstrated that the inactivation of SIRT1-AMPK signaling increases lipogenesis and represses rates of fatty acid oxidation in the livers of HFD-fed mice. Inactivation of SIRT1 leads to decreased deacetylation of Lys48 and possibly other key lysine residues on LKB1. This, in turn, inhibits LKB1 binding to STE20-related adaptor protein and mouse embryo scaffold protein, which inactivates its kinase activity and leads to the inhibition of AMPK phosphorylation [16]. Inactivation of AMPK through S6K1 activates LXRα, leading to the expression of target genes such as CD36, leptin, and FAS, which may contribute to increased fat accumulation in the liver. At the same time, inactivated AMPK increases ACC phosphorylation, subsequently decreasing the level of CPT1 in the liver. The consequence of this may be a decrease in fatty acid oxidation rates in the liver. In the present study, carvacrol reversed the HFD-induced upregulation of hepatic genes involved in lipogenesis (S6K1, LXRα, SREBP1c, FAS, leptin, and CD36) and HFD-induced downregulation of hepatic genes involved in fatty acid oxidation (SIRT1, AMPK, and CPT1). Accordingly, changes in expression of genes involved in lipogenesis and fatty acid oxidation may have contributed to the reduction of hepatic triglyceride and free fatty acid concentrations in CSD-fed mice.The cells that internalize exogenous cholesterol repress endogenous cholesterol biosynthesis and LDLR expression in response to cholesterol loading. The hepatic cholesterol depletion was associated with compensatory mechanisms aimed at increasing hepatic cholesterol, including upregulation of HMGCR and LDLR [5]. In the present study, carvacrol decreased the HFD-induced increase in hepatic cholesterol concentrations and, simultaneously, increased the mRNA expression of hepatic HMGCR and LDLR. The elevated HMGCR and LDLR mRNA levels may be secondary to the reduced hepatic cholesterol concentrations induced by carvacrol supplementation. Another important protective mechanism against hepatic cholesterol accumulation is cellular efflux of cholesterol and bile acid biosynthesis [17, 18]. In the present study, carvacrol reversed the HFD-induced downregulation of CYP7A1 and CYP8B1 genes involved in bile acid biosynthesis and ABCG5 and ABCG8 genes involved in cholesterol efflux in the liver of mice. Therefore, the increased expression of these genes might contribute to the lower cholesterol concentration in the liver of CSD-fed mice.The present study showed that carvacrol reversed the HFD-induced increase in free cholesterol and cholesterol ester concentrations in the liver of mice. In the hepatocyte, cholesterol exists as free cholesterol and as cholesterol esters [19]. It has been suggested that an increase in the intrahepatic free cholesterol concentration is rapidly balanced by an increase in the rate of cholesterol esterification to prevent excess cellular free cholesterol accumulation [20]. A recent study showed that the increased cholesterol ester in lipid droplets could limit the hydrolysis of triglycerides and decrease hepatic triglyceride secretion out of cells, leading to hepatic steatosis in the liver of mice fed a low-fat diet containing cholesterol [4]. Therefore, the protective action of carvacrol against hepatic steatosis might involve not only enhanced SIRT1-AMPK signaling, but also a decreased concentration of cholesterol ester.TLRs play an important role in the innate immune system by activating inflammatory pathways in response to microbial agents [21]. TLR2 and 4 initiate shared and distinct signaling pathways by recruiting various combinations of the Toll-interleukin 1 receptor domain-containing adaptor proteins MyD88, TIRAP (Mal), TRIF, and TRAM. These signaling pathways activate the transcription factor IRF5, leading to the production of inflammatory cytokines. TLR4 also activates the transcription factor IRF3, leading to the production of type I interferons [21, 22]. TLR2- and 4-mediated signaling has emerged as a major mechanism involved in regulating inflammatory responses in mouse models of HFD-induced steatosis [23, 24]. Although no infiltration of inflammatory cells was detected in the livers of CSD- and HFD-fed mice, the expressions of proinflammatory cytokines (TNFα, IFNα, and IL-6) and their upstream signaling molecules (TLR2/4, TIRAP, TRIF, TRAF6, and IRF5) were decreased in CSD-fed mice compared with HFD-fed mice. The HFD-induced elevations in plasma TNFα and MCP1 concentrations were also significantly reversed by carvacrol supplementation. These findings support the recent in vivo studies on the anti-inflammatory activity of carvacrol. Guimaraes et al. [25] revealed that carvacrol significantly decreased TNF-α levels in pleural lavage and suppressed the recruitment of leukocytes without altering the morphological profile of these cells. Carvacrol has been reported to cause anti-inflammatory effects by reducing the production of inflammatory mediators, such as IL-1β and prostanoids, possibly through the induction of IL-10 release in a classical inflammation mouse model [26].Our results are in accordance with previous studies showing that at the early stage of obesity induced by the HFD, the expression levels of the proinflammatory cytokines were increased prior to macrophage infiltration [23, 27]. HFD-induced fatty liver diseases can progress from simple steatosis to nonalcoholic steatohepatitis (NASH, fatty changes with inflammation and hepatocellular injury or fibrosis). It is well established that mice fed the HFD for 10 weeks showed simple steatosis with the absence of necrosis or signs of inflammation [28]. Although NASH did not develop in our 10-week experiment, upregulation of proinflammatory cytokines and profibrotic genes could have facilitated the deterioration of steatosis to NASH if the experiment had been conducted for a longer duration. Accordingly, the carvacrol-mediated reduction in the expressions of proinflammatory cytokines and plasma MCP1 and TNFα concentrations in the livers of HFD-fed mice may contribute to decreased infiltration of macrophage into the liver.In conclusion, carvacrol supplementation (0.1%) suppressed the HFD-induced increases in liver weight, hepatic lipid levels, plasma activities of ALT and AST, and the steatosis score in mice. The protective action of carvacrol against HFD-induced hepatic steatosis in mice appears to be mediated through the downregulation of genes involved in lipogenesis and upregulation of genes involved in fatty acid oxidation via SIRT1-AMPK signaling. Furthermore, carvacrol supplementation also provoked decreased expression of genes involved in TLR-mediated signaling cascades and reduced concentrations of plasma TNFα and MCP1, which may diminish hepatic inflammatory stress (Figure 6).(a) Proposed mechanism for the protective effects of carvacrol against hepatic steatosis in mice. Carvacrol decreased the expression of genes and phosphorylation of protein involved in lipogenesis, whereas it increased the expression of genes and phosphorylation of proteins involved in fatty acid oxidation in the livers of HFD-fed mice. (b) Schematic overview of cholesterol homeostasis and the effects of carvacrol in the livers of HFD-fed mice. Carvacrol lowers cholesterol content by reversing the HFD-induced downregulation of genes involved in cholesterol homeostasis. (c) Schematic overview of the genes regulated by carvacrol in TLR2- and 4-signaling pathway.
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Lipogenesis and fatty acid oxidation
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Cholesterol homeostasis
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TLR 2-, 4-mediated signaling
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*Source: 290104-2013-02-20.xml* | 2013 |
# New C-Terminal Conserved Regions of Tafazzin, a Catalyst of Cardiolipin Remodeling
**Authors:** Gregory A. Shilovsky; Oleg A. Zverkov; Alexandr V. Seliverstov; Vasily V. Ashapkin; Tatyana S. Putyatina; Lev I. Rubanov; Vassily A. Lyubetsky
**Journal:** Oxidative Medicine and Cellular Longevity
(2019)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2019/2901057
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## Abstract
Cardiolipin interacts with many proteins of the mitochondrial inner membrane and, together with cytochrome C and creatine kinase, activates them. It can be considered as an integrating factor for components of the mitochondrial respiratory chain, which provides for an efficient transfer of electrons and protons. The major, if not the only, factor of cardiolipin maturation is tafazzin. Variations of isoform proportions of this enzyme can cause severe diseases such as Barth syndrome. Using bioinformatic methods, we have found conserved C-terminal regions in many tafazzin isoforms and identified new mammalian species that acquired exon 5 as well as rare occasions of intron retention between exons 8 and 9. The regions in the C-terminal part arise from frameshifts relative to the full-lengthTAZ transcript after skipping exon 9 or retention of the intron between exons 10 and 11. These modifications demonstrate specific distribution among the orders of mammals. The dependence of the species maximum lifespan, body weight, and mitochondrial metabolic rate on the modifications has been demonstrated. Arguably, unconventional tafazzin isoforms provide for the optimal balance between the increased biochemical activity of mitochondria (resulting from specific environmental or nutritional conditions) and lifespan maintenance; and the functional role of such isoforms is linked to the modification of the primary and secondary structures at their C-termini.
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## Body
## 1. Introduction
Cardiolipin (CL) is a phospholipid of mitochondrial membranes that directly interacts with several mitochondrial proteins to increase the efficiency of the respiratory chain and ADP/ATP exchange ([1] and references therein). It is also involved in protein import into mitochondria and modulates the mitochondrial retention and activity of many proteins and enzymes. CL oxidation triggers cell death and occurs in many pathologies [2]. Abnormal CL metabolism alters the structure of mitochondria including cristae loss and decreases the mitochondrial rate of divisions, fusions, and mitophagy. Altered CL metabolism can cause various forms of heart failure. These disturbances are particularly pronounced in Barth syndrome (BS), a rare X-linked genetic disorder with cardiomyopathy, skeletal myopathy, and growth delay [3]. The mutation associated with BS was mapped to the TAZ gene on the X chromosome [4]. More than 100 mutations in TAZ that induce BS have been reported [3]. They are scattered among all 11 exons of the gene and most of them are missense mutations or short indels, but frameshift and splicing site mutations, as well as large deletions of exons or the whole gene, also occur. No clear correlation between the mutation type and BS symptoms has been revealed.Studies on human and animal models demonstrated thatTAZ mutations decrease the level of mature CL and increase that of monolyso-CL (MLCL). The MLCL/CL ratio in the blood, together with TAZ mutations, is the main diagnostic features of BS. The presence of the conserved motif HXXXXD (histidine and aspartic acid separated by any four amino acids) typical of glycerolipid acyltransferases pointed to the possible involvement of tafazzin in the remodeling of nascent CL. Indeed, BS patients demonstrated low linoleic acid (C18:2) incorporation into CL in contrast to other fatty acids. Moreover, the mitochondria from rat hepatocytes and human lymphoblasts realized ex vivo transfer of [14C]linoleoyl-phosphatidylcholine to tetraoleoyl-CL, thus replacing all four acyl groups with linoleic ones [5]. Purified drosophila tafazzin efficiently transferred in vitro linoleic acid chains from 1-palmitoyl-2-[14C]linoleoyl-phosphatidylcholine to MLCL to form CL and lysophosphatidylcholine (lysoPC, LPC).The structure of CL is unique among phospholipids; it comprises four acyl chains derived from two molecules of phosphatidic acid linked by the central glycerol backbone [6]. In most tissues, CL has one or two dominant acyl groups, which makes it structurally uniform and molecularly symmetric [7]. Residues of unsaturated fatty acids are common dominant groups. These structural properties of mature CL forms stem from its postsynthetic modification. This remodeling starts from MLCL formation through the removal of one of four acyl groups, which is catalyzed by calcium-independent phospholipase A2 in mammals. MLCL reacetylation is mediated by three enzymes: monolysocardiolipin acyltransferase, acyl-CoA:lysocardiolipin acyltransferase, and tafazzin. The substrate specificity and specific CL remodeling remain underexplored for the first two enzymes. Tafazzin is indispensable for the maintenance of the normal composition and concentration of CL. BS induction by TAZ mutations indicates the importance of CL remodeling and the significance of tafazzin in mitochondrial function. Tafazzins were found in all studied eukaryotes as components of the mitochondrial intermembrane compartment [7]. The topological organization of the tafazzin molecule in mitochondria remains obscure; however, it was shown to associate with 105-106 Da multiprotein complexes. It remains unclear which proteins comprise these complexes and directly interact with tafazzin; however, this association of tafazzin with other proteins is significant for its function.Sequence comparison of theTAZ gene and several of its transcripts has revealed two alternative transcription initiation sites and several splicing variants, which give rise to several tafazzin isoforms [4]. Tafazzin sequence has no explicit similarity to other known proteins; it contains two functionally important regions: a very hydrophobic sequence of 30 amino acids in the N-terminal region, apparently, a membrane anchor, and a hydrophilic domain in the central part, apparently, interacting with other proteins. The shortest tafazzin forms lack the hydrophobic region and are likely cytoplasmic proteins, while several longer variants of alternative splicing of exons 5-7 differ by the hydrophilic domain length. It is not improbable that the diversity of the hydrophilic domains modulates their affinity to different proteins. Most common isoforms are the full-length one and the one lacking exon 5. In Drosophila, which also has several tafazzin isoforms, they have different intracellular localization: the dominant tafazzin-A resides in mitochondria while tafazzin-B is localized in different compartments including the mitochondria, endoplasmic reticulum, and Golgi complex.The purified recombinant tafazzin demonstrates transacylase activity towards CL and a variety of phospholipids, such as phosphatidic acid, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, and phosphatidylserine, as well as their lyso-L-derivatives. The recombinant tafazzin can transfer acyl groups of 7-19 carbon atoms with 0 to 3 unsaturated double bonds. Tafazzin function is not only the conversion of a pair of phospholipids into another pair (PL1+LPL2 → LPL1+PL2) but also keeping a balance between the PL and LPL molecules. At first sight, this wide specificity of tafazzin should level the acyl composition of all phospholipids in the corresponding membrane compartments. Actually, thein vivo effect of tafazzin is quite specific, primarily, towards CL of the mitochondrial compartment. Apparently, the specificity of in vivo transacylation is largely determined by the organization of mitochondrial membranes and the availability of acyl groups rather than by the tafazzin properties. It was suggested that the major tafazzin function is to optimize the packing of phospholipids in the membranes through the thermodynamic remodeling that facilitates dynamic conformational transitions in mitochondrial membranes [7].A deficiency of tafazzin decreases the CL concentration, alters its acyl composition, and increases the MLCL concentration. At the same time, multiprotein complexes in the inner mitochondrial membrane degrade, which can result directly from decreased CL level or indirectly from altered conformational dynamics of the membranes. Overall, this gives an insight into the origins of abnormal functional activity of mitochondria, such as decreased membrane potential, partial oxidative uncoupling, and increased oxidative stress. A further link to the phenotypic manifestations ofTAZ mutations is not as clear. The described molecular mechanism is universal; however, the phenotypic abnormalities in BS apply to certain tissues only. For instance, morphological abnormalities in mitochondria are observed in embryonic stem cells only after their differentiation into cardiomyocytes [8]. Apparently, highly active mitochondria with high cristae density might be most sensitive to tafazzin defects. Whatever the truth, the tafazzin deficiency does not necessarily lead to defects in the mitochondrial structural organization; rather, only the proportion of defective mitochondria increases. This effect can underlie the variation of phenotypic defects in BS.Thus, CL is a unique dimeric phospholipid specific for mitochondria, which makes it a reliable mitochondrial marker. Tissues with high oxidative capacity such as slow-twitch skeletal and cardiac muscle have high CL content ranging from 10 to 20% of the total mitochondrial phospholipids; and this is known to be critical for mitochondrial respiration and energy metabolism [9, 10]. Specifically, CL physically interacts with and activates a large number of mitochondrial proteins including most, if not all, of the inner mitochondrial membrane enzymes, along with cytochrome c and creatine kinase [11, 12]. Actually, CL can be considered as a factor integrating components of the mitochondrial respiratory chain, which provides efficient transfer of electrons and protons [11, 12]. Not only the presence of CL but also its acylation are critical for the functional activity of mitochondria. The nature of CL acyl chains can vary between tissues; however, the dominant form in the skeletal and cardiac muscles has linoleic acid (18:2n-6). A decreased proportion of this modification can interfere with the oxidase activity of cytochrome C. The main, if not the only, factor controlling the 18:2n-6 composition of CL is tafazzin, which catalyzes the transfer of 18:2n-6 from donor phospholipids such as phosphatidylcholine, thus completing CL maturation. Accordingly, mutations in the human tafazzin gene (TAZ) induce BS, a form of congenital myopathy featuring structural and functional abnormalities of mitochondria, cardiac and skeletal myopathy, physical load intolerance, and increased production of reactive oxygen species [13].The tafazzin gene was first described in 1996 as a target for mutations causing BS [4, 14]. Alternative splicing of the TAZ primary transcript gives rise to four different experimentally observed mRNAs: full-length (FL), lacking exon 5 (Δ5), exon 7 (Δ7), or both (Δ5Δ7) [15]. The CL acyl chain varies between cell types and tissues in the same species. The FL and Δ5 tafazzin forms demonstrate transacylase activity but have different topology (immersion into the membrane) [16]. It remains unclear if CL remodeling is the only function of tafazzin. TAZ mutations decrease the synthesis of tetra-linoleoyl cardiolipin in favor of CL molecules with a different acyl composition. This change affects the structural and functional activity of mitochondria. Analysis of the patterns and proportions of tafazzin forms in the blood of BS patients and normal subjects has demonstrated, in addition to the two functional isoforms (FL and Δ5), a variety of mRNA species encoding nonfunctional protein forms.A recent phylogenetic analysis of mitochondrial proteins in mammals and birds with significantly different maximum lifespan (MLS) [17] has demonstrated that it substantially depends on the taxon-specific numeric parameter α, which is a component of the equation of mitochondrial metabolic rate; mtMR=А·MB−1/α (the dimension constant A will be omitted farther on). The parameter α characterizes the stability of proteins of the mitochondrial inner membrane. Another convenient index of mitochondrial metabolic rate is the basal rate of oxygen consumption per body weight per time (mtBRO2). Disregarding the constant A, these parameters are related by the equation mtMRα=mtBRO2, where 1≤α≤8. Overall, mtMR describes the energy requirements corresponding to species living in a particular ecological niche, while α is determined by specific amino acid composition of mitochondrial proteins and interactions between mitochondrial membrane proteins. CL, a critical integrative component of the inner membrane, should, to a large extent, determine the value of α and, hence, of species-specific MLS and mtMR. As mentioned above, acyl modification of CL by tafazzin is among the main mechanisms that control the functional activity of CL. Thus, the structural and functional properties of tafazzin can be a factor of species-specific MLS and respiratory functions of mitochondria.Hereafter, tafazzin exons are numbered according to the FL isoform of human tafazzin (NP_000107; 292 amino acids). Without going into the description of classic tafazzins, note that their C-termini correspond to the motif shown in Figure1, which was generated from the alignment of the C-terminal sequence of the mammalian proteins to exon 11 of the human FL tafazzin. The C-terminal sequences are aligned without deletions, and the secondary structure is preserved not only in mammals and other vertebrates but also in model protostomes (Drosophila melanogaster, Caenorhabditis elegans), fungi (Saccharomyces cerevisiae), etc. (see Figure 1 in [13]).Figure 1
The C-terminal motif of classic tafazzins (aligned to exon 11 of human FL tafazzin).We bioinformatically analyzed the modifications in mammalian tafazzins in exons 5, 8–9, and 9–11. Specifically, the regions conserved among mammals have been identified in the C-terminal region of many isoforms of unconventional tafazzin as well as new species that acquired exon 5 in the tafazzin gene (apart from human and great apes; Hominidae). The first case tafazzins are referred to as unconventional (UTs), which are divided into two types (T1 and T2) distinguished by their motifs. The former motif results from the omission of exon 9 and a frameshift, while the second one results from intron retention between exons 10 and 11 and also a frameshift. The latter case when exon 5 is acquired is referred to as E5 tafazzins. In the rare cases, intron retention is observed between exons 8 and 9. These modifications have specific distribution among mammalian orders and correlate to the maximum lifespan and body weight as well as to the rate of mitochondrial metabolism. We propose the functional role of such changes.
## 2. Materials and Methods
Amino acid sequences were extracted from the RefSeq database [18] and supplemented with those from Ensembl v96 [19]. T1 isoforms of tafazzin were identified by PSI-BLAST [20] in RefSeq. The sequence ENHRADWEALQCPACARAAPGREQVSCGDSQSPD, a region of tafazzin matching in the Pacific white-sided dolphin (Lagenorhynchus obliquidens, isoform Х5) and the narrow-ridged finless porpoise (Neophocaena asiaeorientalis, isoform Х2), was used as the query. At the second iteration, the T1 set was supplemented only by tafazzins of the naked mole-rat (NMR, Heterocephalus glaber) as well as additional tafazzin isoforms of the giant panda (Ailuropoda melanoleuca) and African bush elephant (Loxodonta africana); these tafazzins have a lower similarity to the query. Subsequent iterations yielded no new proteins. Eventually, 50 tafazzin sequences have been identified (listed at sheet T1 of Table S1). The E value cutoff was 0.005; however, the same results were obtained for the values from 0.0001 to 0.1. Hereafter, the default values were used for all unmentioned BLAST parameters.T2 isoforms of tafazzin were identified in a similar way but using BLAST (PSI-BLAST yielded the same results). The query was the sequence PGRSSLRAAGQPQSFPSGGDSQSPD, a tafazzin region matching in the Pacific white-sided dolphin (Lagenorhynchus obliquidens, isoforms Х1–X4) and the narrow-ridged finless porpoise (Neophocaena asiaeorientalis, isoform Х1). The same results were obtained for E value cutoffs from 5·10−5 to 10, namely, 28 tafazzins listed at sheet T2 of Table S1 together with the query, which matches all identified regions in cetaceans. The tafazzin XP_028342714 (isoform Х1) of the sperm whale (Physeter catodon) corresponds to both T1 and T2 types. Its tafazzin XP_028342715 (Х2) matches the T1 and T2 types with E values of 10-12 and 2·10−5 and was assigned to T1. Table S1 includes a single tafazzin (XP_028342714) assigned to both T1 and T2 types.E5 isoforms of tafazzin were identified by BLAST in RefSeq. The query was the human tafazzin region encoded by exons 4, 5, and 6 (underlined are the exon boundaries): TPAAADICFTKELHSHFFSLGKCVPVCRGAEFFQAENEGKGVLDTGRHMPGAGKRREKGDGVYQKGMDFILEKLNHGDWVHIFPE. The results remain unaltered for E value cutoffs from 10-35 to 10-31. The identified proteins contain a region between exons 4 and 6 homologous to tafazzin exon 5 of apes (Hominidae, E5 tafazzins). Higher E values yield amino acid regions lacking the exon 5 region that cannot be assigned to E5 tafazzins. According to Table S1, E5 and T1 types do not overlap. Some species (sooty mangabey Cercocebus atys, green monkey Chlorocebus sabaeus, crab-eating macaque Macaca fascicularis, black snub-nosed monkey Rhinopithecus bieti, and African bush elephant Loxodonta africana) have both types, but none of their proteins belongs to both types. Thus, these three types have a single overlap (XP_028342714) for types T1 and T2, although there is no obvious reason why the loss of exon 9 cannot be combined with the acquisition of exon 5. All identified E5 tafazzins are classic (they conform to the logo in Figure 1).For the generation of the sequence logos presented in Figure2, a single region of each type (marked by an asterisk in Table S1) was used for each species to provide for even representation of species with a different number of tafazzin isoforms. The region most similar to the above queries for T1 or T2, respectively, was selected. Sequence logos were generated using the WebLogo service [21]. The protein secondary structures were predicted by JPred4 [22].Figure 2
Motifs specific for unconventional tafazzin isoforms: (a) type 1 (T1) and (b) type 2 (T2).
(a)
(b)
## 3. Results and Discussion
By analyzing data available in major databases, we have identified conserved C-terminal regions missing in the classic tafazzin in the amino acid sequences of mammalian tafazzin isoforms. Their motifs (sequence logos) are shown in Figures2(a) and 2(b), and the corresponding protein sequences are presented in Table S1. This table also presents the taxonomy and Latin name of species to facilitate using their common names. Unconventional tafazzins (UTs) apply to tafazzin isoforms containing the first or the second motifs (T1 and T2).The T1 motif was found in 23 mammalian species of 7 orders (or higher taxa): Afrotheria, Glires, Primates, Scandentia, Carnivora, Cetacea, and Artiodactyla, specifically in naked mole-rat (Heterocephalus glaber), Arctic ground squirrel (Urocitellus parryii), sooty mangabey (Cercocebus atys), green monkey (Chlorocebus sabaeus), crab-eating macaque (Macaca fascicularis), black snub-nosed monkey (Rhinopithecus bieti), golden snub-nosed monkey (Rhinopithecus roxellana), Chinese tree shrew (Tupaia belangeri chinensis), northern fur seal (Callorhinus ursinus), Steller sea lion (Eumetopias jubatus), California sea lion (Zalophus californianus), Hawaiian monk seal (Neomonachus schauinslandi), giant panda (Ailuropoda melanoleuca), Pacific white-sided dolphin (Lagenorhynchus obliquidens), narrow-ridged finless porpoise (Neophocaena asiaeorientalis), sperm whale (Physeter catodon), zebu (Bos indicus), cattle (Bos taurus), the hybrid of the two latter (Bos indicus × Bos taurus, NCBI:txid30522), white-tailed deer (Odocoileus virginianus), wild boar (Sus scrofa), Bactrian camel (Camelus bactrianus), and African bush elephant (Loxodonta africana).The T2 motif coincides completely in 12 species, specifically, in nearly all cetaceans and aquatic carnivores. It was found in walrus (Odobenus rosmarus), Weddell seal (Leptonychotes weddellii), Hawaiian monk seal (Neomonachus schauinslandi), brown and polar bears (Ursus arctos and Ursus maritimus) as well as American black bear (Ursus americanus, data from Ensembl), Pacific white-sided dolphin (Lagenorhynchus obliquidens), killer whale (Orcinus orca), common bottlenose dolphin (Tursiops truncatus), beluga whale (Delphinapterus leucas), narrow-ridged finless porpoise (Neophocaena asiaeorientalis), and sperm whale (Physeter catodon). It was also found in two chiropterans, black flying fox (Pteropus alecto) and Egyptian fruit bat (Rousettus aegyptiacus), as well as in a perissodactyl, white rhinoceros (Ceratotherium simum).According to MobiDB [23], the conserved UT regions overlap with long disordered regions usually up to the C-terminus. These disordered regions sometimes occur in other regions of proteins but are not typical for tafazzins without the specified T1 and T2 motifs. The identified regions cannot be aligned to domains involved in enzyme activity, which gives no grounds to assume their participation in protein attachment to the mitochondrial inner membrane or being a part of the catalytic center. Similarly, disordered regions have been found at the N termini of microtubule-binding and tubulin-sequestering proteins [24].Although RefSeq is extensive, other databases still contain proteomes missing in RefSeq. For instance, Ensembl contains the proteome of the American black bear (Ursus americanus) with the tafazzin containing a region matching T1; accordingly, Table S1 was supplemented with this species and the region.In addition to the tafazzins presented in TableS1, we have found tafazzins with the C-terminal region shared in the motifs, specifically, seven C-terminal amino acids as shown in the logo (Figure 2). These can be exemplified by the North American beaver (Castor canadensis), whose isoforms Х1, X2, and X5–X8 contain a region that partially matches both T1 and T2: VSFLPDSPKLSSVLPVPSDSQGTLAKVHEGCRPAPSLSAGGDAQSSD. The beaver can also be assigned to E5. Similarly, all isoforms (X1–X4) of the European rabbit (Oryctolagus cuniculus) include shortened T1 or T2; these are similar regions LPQGCGPTVSLSSGGDAQSPH (isoforms Х1 and X4), GCGPTVSLSSGGDAQSPH (Х2), and LPQGCGLSSGGDAQSPH (Х3), which allow us to call such proteins shortened UTs. Isoform X1 in naked mole-rat (Heterocephalus glaber) also contains the sequence GDAQGPD. Also, its T1 is represented by isoforms X2 and X3 while classic tafazzins include isoforms X4 and X5. The list of such examples goes on.There are regions with very weak similarity to T1 or T2. For instance, isoform X1 of the Colombian white-faced capuchin (Cebus capucinus) is similar to T1: ALWRPDAGGAEREAAARDRVEHRDFLAPRH; isoform X2 of the domestic sheep (Ovis aries) is similar to T2: VSFSLGLSSPFSLGLSSP; tafazzin of the dromedary (Camelus dromedarius) is similar to T2: VSSSPRQSCSCPSPSSP. To our knowledge, the capuchin has no classic tafazzin.It is of interest that the regions GDAQSPD, GDAQSSD, GDAQSPH, GDSQSPD, GDAESPD, and GDAQGPD corresponding to the last seven positions in Figure2 occur exclusively in unconventional tafazzins including shortened ones. Among 4 million proteins in RefSeq, there are only three exceptions, XP_007521742, XP_004712810, and XP_016049842 of European hedgehog (Erinaceus europaeus) and lesser hedgehog tenrec (Echinops telfairi), that are not tafazzins but include regions 2, 4, and 5 above. Specifically, the exact GDAQSPD sequence is present in as low as 28 mammalian proteins: 23 T1s and 5 T2s. GDSQSPD is present in 17 mammalian proteins: 4 T1s, 12 T2s, and 1 nontafazzin XP_016049842 of the hedgehog (Erinaceus europaeus). GDAQSSD is present in 20 mammalian proteins: 6 T1s, 8 T2s, 6 shortened UTs of the beaver (X1, X2, and X5–X8), and 1 nontafazzin XP_007521742 of the hedgehog. GDAESPD is present in 7 mammalian proteins: 4 T1s, 2 T2s, and 1 nontafazzin XP_004712810 of the tenrec (Echinops telfairi). GDAQSPH is present in 5 mammalian proteins: 1 T1 of Arctic ground squirrel (Urocitellus parryii) and 4 shortened UTs of the European rabbit (Oryctolagus cuniculus, X1–X4). GDAQGPD is present in 2 mammalian proteins: 2 T1s of the naked mole-rat (Heterocephalus glaber). RDAQSPD is present in 3 T1s of the African bush elephant (Loxodonta africana) and in more than a hundred nontafazzins of the family of sister chromatid cohesion protein PDS5 homolog A. Thus, these six regions largely mark unconventional tafazzins.Hereafter,patterns refer to tafazzin regions specified in Materials and Methods as queries. It is natural to define the threshold segregating true T1 and T2 proteins from those with only a remote resemblance to these types. In the case of T2, at least 19 out of 25 amino acids have to match, i.e., more than 3/4. In the case of T1, it seems that true regions match at least 2/3 of the pattern (more than 22 out of 34 amino acids), although some isoforms with a lower similarity were included in the list in Table S1. For instance, there is a region with a 50% identity (17 out of 34 amino acids) in isoform X14 (XP_023396534) of the African bush elephant (Loxodonta africana); however, another isoform of this species (X10) used in the logo generation has more than 2/3 of matches (23 out of 34). The challenges of such a threshold definition are shown below. The prairie deer mouse (Peromyscus maniculatus bairdii) represented in Ensembl but not in RefSeq has a sequence matching almost a half of the first part of the T1 pattern (16 out of 34 amino acids). Such shortened T1 is typical of many rodents (the number of unconventional isoforms in RefSeq is given in parentheses): house mouse (Mus musculus, 6), Gairdner’s shrewmouse (Mus pahari, 3), Ryukyu mouse (Mus caroli, 2), Chinese hamster (Cricetulus griseus, 4), Golden hamster (Mesocricetus auratus, 2), lesser Egyptian jerboa (Jaculus jaculus, 2), and guinea pig (Cavia porcellus, 1). At the same time, the alignment of the region of tafazzin of the prairie deer mouse demonstrates a convincing similarity, and the absence of such tafazzins in Table S1 is due to the similarity shortness, which we consider significant. The asterisk in the prairie deer mouse sequence indicates the stop codon:Query: ENHRADWEALQCPACARAAPGREQVSCGDSQSPDSubject:ENHRADREALQCTPCA∗Note that arginine at position 7 is not uncommon in mammals.The absence of the major part of the patterns in shortened tafazzins does not allow us to assign them to UTs, although the threshold similarity length has not been defined explicitly.In addition, new tafazzin isoforms that contain exon 5 have been found in the following orders (or higher taxa): Afrotheria, Glires, Primates, Carnivora, Cetacea, Artiodactyla, and Chiroptera. Previously, such E5 tafazzins have been found in hominids (Homo sapiens, Pan paniscus, Pan troglodytes, Gorilla gorilla, and Pongo abelii). Apart from these, we have identified E5 tafazzins in many Old World monkeys (Cercopithecidae): Cercocebus atys, Chlorocebus sabaeus, Macaca fascicularis, M. mulatta, M. nemestrina, Mandrillus leucophaeus, Papio anubis, Theropithecus gelada, and Rhinopithecus bieti as well as in the northern greater galago Otolemur garnettii. Occasional E5 tafazzins can be found beyond primates: in rodents (Ochotona princeps and Castor canadensis), laurasiatherians (Pantholops hodgsonii, Phyllostomus discolor, Balaenoptera acutorostrata, and Puma concolor), and afrotherians (Loxodonta africana). All identified E5 proteins are given in Table S1 (sheet E5).Complementation test in yeast has demonstrated the functional activity only for theΔ5 variant, which raises the question as to why exon 5 was preserved in evolution [25]. The full-length human tafazzin proved to complement the deletion of TAZ gene in Drosophila [16]. Schlame claimed that exon 5 could be found in the TAZ gene only in primates [7]; however, we have found many new instances of this exon.Figure3 shows the number of considered species, the number of species containing each unconventional type or E5 tafazzins, and their total number per taxon (these data are given in more detail in Table S1).Figure 3
Distribution of species containing each unconventional type or E5 tafazzins and their total number per taxon. The following indices are given for each taxon (left to right): total number of considered species, numbers of species with T1, T2, and E5, the total number of unconventional tafazzins, and this number supplemented with E5 tafazzins.In isolated cases, classic tafazzins conforming the description in Introduction preserve the intron between exons 8 and 9; such tafazzins will be referred to as CT+. Nine such cases have been found in RefSeq in the following primates:Homo sapiens, isoforms X2, X3, and X5 (XP_006724900, XP_016885250, and XP_024308199, respectively); bonobo (Pan paniscus), X2 (XP_008950941), Sumatran orangutan (Pongo abelii), X1 (XP_024096396), black-capped squirrel monkey (Saimiri boliviensis), X1, X2, and X5 (XP_010330095, XP_010330096, and XP_010330098), and chimpanzee (Pan troglodytes), X5, (XP_016798103). Specifically, the glycine (underlined) at the boundary of these exons, WHVGMND, is replaced with one of the following regions corresponding to a 117 bp intron insertion: GEPGDGDREMASGVGGLGLPLVPGCPAPPHVWPSVHCAAG (human, bonobo, and chimpanzee), GEPGDGDREMASGVGGLGVPLVPGCPAPPHVWPSVHCAAG (orangutan), and GEPGDGDRDKASGVGSLGLPLVPGCPAPPHVWPFVHCAAG (squirrel monkey).Noteworthily, this intron retention exists in the human and orangutan but is missing, e.g., in the gorilla.The exon-intron structures of the discussed tafazzin types are schematically shown in Figure4.Figure 4
The exon-intron structures of the considered tafazzin types. Usual exons (i.e., as in CL) are depicted by blue rectangles, retained introns are shown in green, and frameshifted exons are shown in red. The black outlines emphasize the distinguishing features of the tafazzin types.As already noted, the current work is devoted to the bioinformatic study of tafazzin isoforms. Experimental verification that such tafazzin isoforms are actually expressed will be performed in a separate work.Scatter plots for maximum lifespan (MLS, years) vs. body weight (M, kg) were generated for all classic and identified unconventional tafazzins (Figure5). MLS data were retrieved from the AnAge database [26]. The diagram in Figure 5(a) demonstrates that species with T2 and, to a lesser extent, T1 tend towards high body weights relative to those with the classic tafazzin. Specifically, T2 is observed in the case of body weights exceeding 100 kg except large bats: Egyptian fruit bat (Rousettus aegyptiacus, 125 g) and black flying fox (Pteropus alecto, 672 g) as well as narrow-ridged finless porpoise (Neophocaena asiaeorientalis, 32.5 kg). T1 is observed in the case of body weights exceeding 5.5 kg with the exception of naked mole-rat (Heterocephalus glaber, 35 g), blind mole-rat (Nannospalax galili, 160 g), and tree shrew (Tupaia chinensis, 200 g). Е5 (Figure 5(b)) is observed in the case of body weights exceeding 5.5 kg with the exception of pale spear-nosed bat (Phyllostomus discolor, 43 g), American pika (Ochotona princeps, 100 g), and northern greater galago (Otolemur garnettii, 1.3 kg). Similarly, MLS vs. longevity quotient (LQ) was considered (Figures 5(c) and 5(d)). T2 is characterized by a long lifespan (20 years or more even in the wild) and average LQ, while E5 features long lifespan and high (Hominidae) or average (the rest in Figures 5(c) and 5(d)) LQ. T1 has a wide range of LQ values but tends towards average LQ and long lifespan (more than 11 years).Figure 5
Distribution of mammalian tafazzins over lifespan and body weight (a, b) or longevity quotient (c, d) for classic tafazzin (CT) and unconventional T1 and T2 ones (a, c) or E5, T1, and T2 tafazzins (b, d).
(a)
(b)
(c)
(d)Not much data are available on the rate of mitochondrial metabolism for the considered species. These include the data on the mitochondrial metabolic rate (mtMR) [17], basal rate of oxygen consumption (BRO2) [27, 28], and (the most complete) mass-specific basal metabolic rate (msBMR) from the AnAge database [26] and elsewhere [29]. Several indices are available for certain species, which allowed us to reduce the available data to a single characteristic (Figure 6). The figure suggests that unconventional tafazzin isoforms focus on the optimal balance between the increased biochemical activity of mitochondria related to environmental or nutritional conditions and longevity maintenance. These unconventional tafazzins form two clusters with a significant difference in the body weight; the first one includes three artiodactyls (cattle, wild boar, and white-tailed deer; yellow squares), chimpanzee, orangutan, and human (neighboring bright-green and blue circles; according to E5 and CT+); while the second one includes the naked and blind mole-rats (yellow triangles), the microbats (Microchiroptera; 33.5 and 146 g; bright-green and bright-red diamonds), American pika (bright-green triangle), New World monkeys (squirrel monkey, blue circle above the curve; according to CT+), and northern greater galago (bright-green circles). In the second cluster, the body weight is nearly 100 times lower; however, the rate of oxygen consumption per body weight is 4-5 times higher. This is in a good agreement with the Kleiber equation V̇O2/m=3.42⋅m−0.25 [30] presented as a straight line in the figure. One can propose that the emergence of UTs in addition to E5 was a response to the increased mass-specific oxygen consumption considering that it is found in aquatic mammals, large bats, and white rhinoceros.Figure 6
Oxygen consumption by mammals. Unconventional tafazzins T1 and T2 as well as E5 and CT+ are marked in yellow, bright-red, bright-green, and blue, respectively (the data for the CT+ species are from [28]). The line labeled K is the Kleiber relation.(1) Conservation of Cardiolipin Synthase and Variability of Tafazzin. Cardiolipin synthase 1 encoded by the gene CRLS1 (ENSG00000088766) in human is highly conserved. A single isoform exists in most species. The reaction catalyzed by it yields a variety of cardiolipins whose transformation is mediated by the classic and unconventional isoforms of tafazzin. One can propose that these isoforms modulate the acyl composition of cardiolipins as a function of environmental conditions.(2) The Possible Relationship between T1 and T2. In addition to the discussed above sperm whale tafazzin XP_028342715 (X2) to a different extent applying to the T1 and T2 types, there is another sperm whale protein XP_028342714 (X1) fully applying to T2 and satisfactorily applying to T1. It is the only known tafazzin with a complete T2 motif preceded at a distance of 16 amino acids by an almost complete T1 motif (lacking the terminal GDSQSPD). This isoform was assigned to both types, T1 and T2. These three isoforms illustrate a possible transition from the “intermediate” T1 type to the “new” T2 type. Specifically,Here, X3 is a typical T1; X2 is a T1 with insertion from T2 (turquoise); and X1 is a T1 with an insertion converting it into T2 (T2-specific motif is underlined). Apparently, the loss of exon 9 is more common than the intron fixation here. Coupled with the high number of T1 tafazzins, this points to the emergence of T2 after T1.(3) Relationship between UT and Exons. In the classic tafazzin, the translation of exon 10 starts in phase 0 (i.e., the first exon nucleotide is the first codon nucleotide). The T1 tafazzin results from skipping exon 9 (see Figure 4) so that the spliced out region is not a multiple of three. After exon 9 splicing, the translation of exon 10 starts in phase 1 (the first nucleotide of the exon is the second nucleotide in the codon) and the first 26 amino acids of T1 motif are synthesized. The remaining 8 amino acids of the motif result from the translation of the subsequent exon eleven (also in phase 1 since the length of exon 10 is a multiple of three).This mechanism can be demonstrated on mouse tafazzin isoforms from Ensembl. The isoform ENSMUSP00000065270 corresponds to the classic tafazzin, while the other one (ENSMUSP00000134745) lacks exon 9 (ENSMUSE00000209157). In the first case, exon 10 translation yields amino acid sequence KITVLIGKPFSTLPVLERLRAENKSA; in the second case, ENHRADWEALQYTPCA, which corresponds to the onset of T1 motif. The mouse protein terminates here due to a stop codon; in the absence of it, the following sequence corresponds to T1 motif. This can be illustrated by the human FL isoform of tafazzin ENSP00000469981. After deletion of exon 9 (ENSE00003724812) from its transcript (ENST00000601016), the amino acid sequence corresponding to exon 10 and beginning of exon 11, KITVLIGKPFSALPVLERLRAENKSAVEMRKALT…, is replaced with ENHCADREALQCPACTRAAPGGEQVGCGDAESPD…, which corresponds to T1 motif. No exon 9 splicing has been reported for human; however, such proteins were experimentally demonstrated in mouse (e.g., Q810E8 in UniProt). It is not unlikely that the stop codon of the primary transcript is edited and translated as an amino acid in certain species.Similarly, it can be shown that T2 results from intron retention between exons 10 and 11 (see Figure4). This can be illustrated by two tafazzin isoforms of the polar bear. The first transcript (ENSUMAT00000031820), a classic tafazzin, has no introns; and translation of exons 10 and 11 generates the classic C-terminus: KITVLIGKPFSALPVLERLRAENKSAVEMRKALTDFIQEEFQRLKTQAEQLHNQLQRGR. In the second transcript (ENSUMAT00000031828), intron retention between exons 10 and 11 gives rise to the C-terminus with a typical T2 motif: KITVLIGKPFSALPVLERLRAENKSAVSCLSPLYHPPFPGLPCSCLSLSRHLQPPRAPGSSSPGPGSPRAAVQPQSFPSGGDAQSSD…. The sequence encoded by the retained intron is underlined and T2 motif is in bold. Notice that, similar to T1, exon 11 is translated in phase 1 rather than the natural phase 0, which explains the coincidence of the last seven amino acids in these two motifs (see Figure 2).(4) Special Features of C-Termini of UTs. The mechanism of UT realization, i.e., the functional role of the revealed conserved C-terminal regions of tafazzin, is of great interest. In this context, it should be noted that the C-terminal secondary structure differs in UTs and classic tafazzins (CTs) (Figure 7). For instance, the house mouse CT (ENSMUSP00000065270.6) has a single long helix at the C-terminus, while in shortened UTs it is broken into two (walrus, beaver, and rabbit) or more (naked mole-rat) parts. One can propose that these C-terminal helices in UTs do not interact with the membrane since they are rich in polar amino acids. Specifically, the C-terminus of these tafazzins following the RAENKSA motif contains 2-5 times more polar amino acids, which decreases the C-terminal hydrophobicity.Figure 7
Secondary structure of tafazzin. Helices and extended regions predicted by JPred4 are marked green and blue, respectively. Mouse, CT; walrus, seal, bear, orca, bat, and rhino, T2; beaver, rabbit, and NMR, shortened UT where underlined regions support their assignment to UT (beaver and NMR also have different isoforms listed in TableS1). Abbreviations: mouse: NP_852657.1, isoform 2 (Mus musculus); walrus: XP_004414556.1, X1 (Odobenus rosmarus); seal: XP_006739411.1, X1 (Leptonychotes weddellii); orca: XP_012394911.1, X1 (Orcinus orca); bear: XP_026344949.1, X1 (Ursus arctos); bat: XP_015979168.1, X1 (Rousettus aegyptiacus); rhino: XP_014653014.1, X1 (Ceratotherium simum); beaver: XP_020040765.1, X1 (Castor canadensis); rabbit: XP_017194047.1, X1 (Oryctolagus cuniculus); NMR: XP_004875054.1, X1 (Heterocephalus glaber). Entirely conserved positions are labeled with asterisks.(5) The Specificity of UT Taxonomic Distribution. UTs demonstrate highly uneven distribution in Euarchontoglires and Laurasiatheria. This is systemically shown in Figure 3 and briefly exemplified here. UTs are not found in monotremes and marsupials and are rare in afrotherians (1 out of 6=17%); this is also true for Е5. A similar UT distribution is observed in Euarchontoglires (9/51=18%), specifically, in Glires, Old World monkeys, and tree shrew; Е5 is more common (17/51=33%) in the same orders and families plus hominids and lemuriform primates (Strepsirrhini). UTs are found in Laurasiatheria in a much higher proportion, specifically, in pinnipeds, bears, toothed whales, ruminants, swines, camelids, perissodactyls, and fruit bats, while the proportion of E5 is much lower (4/62=6%). Neither UT nor E5 has been found in insectivores, pangolins, and anteaters and sloths. Usually, one of the types (T1 or T2) is represented in a family excluding earless seals and bears (Carnivora) and toothed whales. T2 was found in the polar, American black, and brown bears, while their remote relative, the giant panda, has Т1. Т2 was also found in fruit bats but is missing in considered microbat species of the Myotis genus.(6) UTs and MLS. The presence of UTs somewhat correlates with MLS as indicated by the examples below. Among long-lived rodents, unconventional T1 is found in the naked and blind mole-rats but is missing in the Damaraland mole-rat. No UTs have been found among other rodents except for the Arctic ground squirrel. Among primates, T1 was found only in certain Old World monkeys with low MLS as well as in a close relative of primates, the tree shrew (Euarchonta). Among afrotherians, T1 was found only in the African bush elephant. Among artiodactyls, T1 was found in species with both high (zebu, cattle, and Bactrian camel) and lesser MLS (white-tailed deer and wild boar). Many aquatic mammals with high MLS proved to have T1 or T2 or both. Overall, many long-lived species belong to orders where unconventional or E5 tafazzins were identified (primates, carnivores, perissodactyls, and cetartiodactyls).(7) UTs and Body Weight. UTs demonstrate an interesting distribution across taxonomic groups as a function of body weight. Irrespective of taxonomic groups, considered mammals with body weight exceeding 1000 kg had T1 (sperm whale and elephant) or T2 (walrus, killer whale, beluga whale, and sperm whale) (Figure 3) with a single exception: no UT has been found in the common minke whale; however, the group of baleen whales remains underexplored and its only classic tafazzin is marked as a low-quality protein in NCBI.In the range from 500 to 1000 kg, T2 has not been found among considered species. In ruminants, T1 was found only in the cattle and zebu (livestock), which can be attributed to increased biodiversity after natural selection was replaced with artificial one, whose rate is much higher [31]. Only classic tafazzin was found in the wild yak, bison, and wild water buffalo.Nearly a half (7/15=47%) of species with T2 fall into the range from 100 to 500 kg; these include cetaceans and carnivores. In tylopods, T1 was found in the domestic Bactrian camel but is missing in the wild Bactrian camel, which are considered different species [32]. This agrees with the above pattern for domestic and wild ruminants. In perissodactyls, UTs are absent in the common donkey, domesticated horse, and Przewalski’s horse. Their tafazzins have RAENKSA sequence at the end of exon 10; however, the following sequences does not allow them to be assigned to T2.In monkeys weighing less than 100 kg, T1 is found in about a half of the Old World monkeys (5/12=42%) with the terminal sequence GDAQSPD (except isoform X5 in the sooty mangabey Cercocebus atys); apparently, it competes with the classic monkey tafazzin with the exon 5 insertion. All hominids have only the classic tafazzin (with the exon 5 insertion).UTs are found in marine carnivores with the body weight from 165 to 1012 kg, i.e., within 2- to 3-fold variation from 500 kg; the latter value corresponds to the optimal balance between heat exchange and food resources [33]. No UTs were found in mustelids and baleen whales, whose body weight differs from 500 kg by order of magnitude, which can reflect different energy expenditures related to the food resources or a different evolutionary pathway. The manatee (Afrotheria) weighing 322 kg is the exception.(8) UTs and Evolution of Species. The relationship between UTs and evolution of species requires further analysis. However, the following observations deserve to be mentioned. No UTs were found in bats except T2 in two species that lack echolocation. Microbats followed their own evolutionary pathway resulting in decreased body size, special skills (echolocation, etc.), and improved flight performance [34]. Also, they have a higher metabolic activity owing to genes of the oxidative phosphorylation pathway and DNA repair efficiency [35]. In Old World primates, UTs are absent in hominids, T1 is found in monkeys, and both taxa have E5. UT and E5 are missing in New World monkeys. UTs are absent in lemuriformes. Apart from T1, which occurs in many mammals, more than half of marine mammals have T2. UTs have not been found in monotremes and marsupials as well as in early diverged placentals (Hoffmann’s two-toed sloth and armadillo); T1 UT was found only in the African bush elephant among afrotherians. Thus, one can conclude that UTs emerged late in evolution: they are absent in monotremes (218 MYA), marsupials (169 MYA), anteaters and sloths (99 MYA), and afrotherians (94 MYA) excluding the African bush elephant and later in insectivores (81 MYA) and pangolins (74 MYA) [36].
## 4. Conclusions
A wide but specific distribution of tafazzin (a cardiolipin remodeler) with altered C-terminus or intron insertions across orders and other taxa was demonstrated in Euarchontoglires and Laurasiatheria. Specifically, we have found conserved regions closer to the C-terminus in many unconventional isoforms, rare cases of intron retention between exons 8 and 9, and new species that acquired exon 5 in the tafazzin gene (apart from Hominidae). The C-terminal regions result from a frameshift relative to the full-lengthTAZ transcript after skipping exon 9 or retention of the intron between exons 10 and 11. The altered ratio between tafazzin isoforms can cause severe diseases such as Barth syndrome. These alterations demonstrate specific distribution among mammalian orders. The dependence of the species maximum lifespan, body weight, and mitochondrial metabolic rate on the alterations has been demonstrated. Arguably, unconventional tafazzin isoforms provide for the optimal balance between the increased biochemical activity of mitochondria (resulting from specific environmental or nutritional conditions) and lifespan maintenance, and the functional role of such isoforms is linked to the modification of the primary and secondary structures of their C-termini.
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*Source: 2901057-2019-10-24.xml* | 2901057-2019-10-24_2901057-2019-10-24.md | 47,753 | New C-Terminal Conserved Regions of Tafazzin, a Catalyst of Cardiolipin Remodeling | Gregory A. Shilovsky; Oleg A. Zverkov; Alexandr V. Seliverstov; Vasily V. Ashapkin; Tatyana S. Putyatina; Lev I. Rubanov; Vassily A. Lyubetsky | Oxidative Medicine and Cellular Longevity
(2019) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2019/2901057 | 2901057-2019-10-24.xml | ---
## Abstract
Cardiolipin interacts with many proteins of the mitochondrial inner membrane and, together with cytochrome C and creatine kinase, activates them. It can be considered as an integrating factor for components of the mitochondrial respiratory chain, which provides for an efficient transfer of electrons and protons. The major, if not the only, factor of cardiolipin maturation is tafazzin. Variations of isoform proportions of this enzyme can cause severe diseases such as Barth syndrome. Using bioinformatic methods, we have found conserved C-terminal regions in many tafazzin isoforms and identified new mammalian species that acquired exon 5 as well as rare occasions of intron retention between exons 8 and 9. The regions in the C-terminal part arise from frameshifts relative to the full-lengthTAZ transcript after skipping exon 9 or retention of the intron between exons 10 and 11. These modifications demonstrate specific distribution among the orders of mammals. The dependence of the species maximum lifespan, body weight, and mitochondrial metabolic rate on the modifications has been demonstrated. Arguably, unconventional tafazzin isoforms provide for the optimal balance between the increased biochemical activity of mitochondria (resulting from specific environmental or nutritional conditions) and lifespan maintenance; and the functional role of such isoforms is linked to the modification of the primary and secondary structures at their C-termini.
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## Body
## 1. Introduction
Cardiolipin (CL) is a phospholipid of mitochondrial membranes that directly interacts with several mitochondrial proteins to increase the efficiency of the respiratory chain and ADP/ATP exchange ([1] and references therein). It is also involved in protein import into mitochondria and modulates the mitochondrial retention and activity of many proteins and enzymes. CL oxidation triggers cell death and occurs in many pathologies [2]. Abnormal CL metabolism alters the structure of mitochondria including cristae loss and decreases the mitochondrial rate of divisions, fusions, and mitophagy. Altered CL metabolism can cause various forms of heart failure. These disturbances are particularly pronounced in Barth syndrome (BS), a rare X-linked genetic disorder with cardiomyopathy, skeletal myopathy, and growth delay [3]. The mutation associated with BS was mapped to the TAZ gene on the X chromosome [4]. More than 100 mutations in TAZ that induce BS have been reported [3]. They are scattered among all 11 exons of the gene and most of them are missense mutations or short indels, but frameshift and splicing site mutations, as well as large deletions of exons or the whole gene, also occur. No clear correlation between the mutation type and BS symptoms has been revealed.Studies on human and animal models demonstrated thatTAZ mutations decrease the level of mature CL and increase that of monolyso-CL (MLCL). The MLCL/CL ratio in the blood, together with TAZ mutations, is the main diagnostic features of BS. The presence of the conserved motif HXXXXD (histidine and aspartic acid separated by any four amino acids) typical of glycerolipid acyltransferases pointed to the possible involvement of tafazzin in the remodeling of nascent CL. Indeed, BS patients demonstrated low linoleic acid (C18:2) incorporation into CL in contrast to other fatty acids. Moreover, the mitochondria from rat hepatocytes and human lymphoblasts realized ex vivo transfer of [14C]linoleoyl-phosphatidylcholine to tetraoleoyl-CL, thus replacing all four acyl groups with linoleic ones [5]. Purified drosophila tafazzin efficiently transferred in vitro linoleic acid chains from 1-palmitoyl-2-[14C]linoleoyl-phosphatidylcholine to MLCL to form CL and lysophosphatidylcholine (lysoPC, LPC).The structure of CL is unique among phospholipids; it comprises four acyl chains derived from two molecules of phosphatidic acid linked by the central glycerol backbone [6]. In most tissues, CL has one or two dominant acyl groups, which makes it structurally uniform and molecularly symmetric [7]. Residues of unsaturated fatty acids are common dominant groups. These structural properties of mature CL forms stem from its postsynthetic modification. This remodeling starts from MLCL formation through the removal of one of four acyl groups, which is catalyzed by calcium-independent phospholipase A2 in mammals. MLCL reacetylation is mediated by three enzymes: monolysocardiolipin acyltransferase, acyl-CoA:lysocardiolipin acyltransferase, and tafazzin. The substrate specificity and specific CL remodeling remain underexplored for the first two enzymes. Tafazzin is indispensable for the maintenance of the normal composition and concentration of CL. BS induction by TAZ mutations indicates the importance of CL remodeling and the significance of tafazzin in mitochondrial function. Tafazzins were found in all studied eukaryotes as components of the mitochondrial intermembrane compartment [7]. The topological organization of the tafazzin molecule in mitochondria remains obscure; however, it was shown to associate with 105-106 Da multiprotein complexes. It remains unclear which proteins comprise these complexes and directly interact with tafazzin; however, this association of tafazzin with other proteins is significant for its function.Sequence comparison of theTAZ gene and several of its transcripts has revealed two alternative transcription initiation sites and several splicing variants, which give rise to several tafazzin isoforms [4]. Tafazzin sequence has no explicit similarity to other known proteins; it contains two functionally important regions: a very hydrophobic sequence of 30 amino acids in the N-terminal region, apparently, a membrane anchor, and a hydrophilic domain in the central part, apparently, interacting with other proteins. The shortest tafazzin forms lack the hydrophobic region and are likely cytoplasmic proteins, while several longer variants of alternative splicing of exons 5-7 differ by the hydrophilic domain length. It is not improbable that the diversity of the hydrophilic domains modulates their affinity to different proteins. Most common isoforms are the full-length one and the one lacking exon 5. In Drosophila, which also has several tafazzin isoforms, they have different intracellular localization: the dominant tafazzin-A resides in mitochondria while tafazzin-B is localized in different compartments including the mitochondria, endoplasmic reticulum, and Golgi complex.The purified recombinant tafazzin demonstrates transacylase activity towards CL and a variety of phospholipids, such as phosphatidic acid, phosphatidylcholine, phosphatidylethanolamine, phosphatidylglycerol, and phosphatidylserine, as well as their lyso-L-derivatives. The recombinant tafazzin can transfer acyl groups of 7-19 carbon atoms with 0 to 3 unsaturated double bonds. Tafazzin function is not only the conversion of a pair of phospholipids into another pair (PL1+LPL2 → LPL1+PL2) but also keeping a balance between the PL and LPL molecules. At first sight, this wide specificity of tafazzin should level the acyl composition of all phospholipids in the corresponding membrane compartments. Actually, thein vivo effect of tafazzin is quite specific, primarily, towards CL of the mitochondrial compartment. Apparently, the specificity of in vivo transacylation is largely determined by the organization of mitochondrial membranes and the availability of acyl groups rather than by the tafazzin properties. It was suggested that the major tafazzin function is to optimize the packing of phospholipids in the membranes through the thermodynamic remodeling that facilitates dynamic conformational transitions in mitochondrial membranes [7].A deficiency of tafazzin decreases the CL concentration, alters its acyl composition, and increases the MLCL concentration. At the same time, multiprotein complexes in the inner mitochondrial membrane degrade, which can result directly from decreased CL level or indirectly from altered conformational dynamics of the membranes. Overall, this gives an insight into the origins of abnormal functional activity of mitochondria, such as decreased membrane potential, partial oxidative uncoupling, and increased oxidative stress. A further link to the phenotypic manifestations ofTAZ mutations is not as clear. The described molecular mechanism is universal; however, the phenotypic abnormalities in BS apply to certain tissues only. For instance, morphological abnormalities in mitochondria are observed in embryonic stem cells only after their differentiation into cardiomyocytes [8]. Apparently, highly active mitochondria with high cristae density might be most sensitive to tafazzin defects. Whatever the truth, the tafazzin deficiency does not necessarily lead to defects in the mitochondrial structural organization; rather, only the proportion of defective mitochondria increases. This effect can underlie the variation of phenotypic defects in BS.Thus, CL is a unique dimeric phospholipid specific for mitochondria, which makes it a reliable mitochondrial marker. Tissues with high oxidative capacity such as slow-twitch skeletal and cardiac muscle have high CL content ranging from 10 to 20% of the total mitochondrial phospholipids; and this is known to be critical for mitochondrial respiration and energy metabolism [9, 10]. Specifically, CL physically interacts with and activates a large number of mitochondrial proteins including most, if not all, of the inner mitochondrial membrane enzymes, along with cytochrome c and creatine kinase [11, 12]. Actually, CL can be considered as a factor integrating components of the mitochondrial respiratory chain, which provides efficient transfer of electrons and protons [11, 12]. Not only the presence of CL but also its acylation are critical for the functional activity of mitochondria. The nature of CL acyl chains can vary between tissues; however, the dominant form in the skeletal and cardiac muscles has linoleic acid (18:2n-6). A decreased proportion of this modification can interfere with the oxidase activity of cytochrome C. The main, if not the only, factor controlling the 18:2n-6 composition of CL is tafazzin, which catalyzes the transfer of 18:2n-6 from donor phospholipids such as phosphatidylcholine, thus completing CL maturation. Accordingly, mutations in the human tafazzin gene (TAZ) induce BS, a form of congenital myopathy featuring structural and functional abnormalities of mitochondria, cardiac and skeletal myopathy, physical load intolerance, and increased production of reactive oxygen species [13].The tafazzin gene was first described in 1996 as a target for mutations causing BS [4, 14]. Alternative splicing of the TAZ primary transcript gives rise to four different experimentally observed mRNAs: full-length (FL), lacking exon 5 (Δ5), exon 7 (Δ7), or both (Δ5Δ7) [15]. The CL acyl chain varies between cell types and tissues in the same species. The FL and Δ5 tafazzin forms demonstrate transacylase activity but have different topology (immersion into the membrane) [16]. It remains unclear if CL remodeling is the only function of tafazzin. TAZ mutations decrease the synthesis of tetra-linoleoyl cardiolipin in favor of CL molecules with a different acyl composition. This change affects the structural and functional activity of mitochondria. Analysis of the patterns and proportions of tafazzin forms in the blood of BS patients and normal subjects has demonstrated, in addition to the two functional isoforms (FL and Δ5), a variety of mRNA species encoding nonfunctional protein forms.A recent phylogenetic analysis of mitochondrial proteins in mammals and birds with significantly different maximum lifespan (MLS) [17] has demonstrated that it substantially depends on the taxon-specific numeric parameter α, which is a component of the equation of mitochondrial metabolic rate; mtMR=А·MB−1/α (the dimension constant A will be omitted farther on). The parameter α characterizes the stability of proteins of the mitochondrial inner membrane. Another convenient index of mitochondrial metabolic rate is the basal rate of oxygen consumption per body weight per time (mtBRO2). Disregarding the constant A, these parameters are related by the equation mtMRα=mtBRO2, where 1≤α≤8. Overall, mtMR describes the energy requirements corresponding to species living in a particular ecological niche, while α is determined by specific amino acid composition of mitochondrial proteins and interactions between mitochondrial membrane proteins. CL, a critical integrative component of the inner membrane, should, to a large extent, determine the value of α and, hence, of species-specific MLS and mtMR. As mentioned above, acyl modification of CL by tafazzin is among the main mechanisms that control the functional activity of CL. Thus, the structural and functional properties of tafazzin can be a factor of species-specific MLS and respiratory functions of mitochondria.Hereafter, tafazzin exons are numbered according to the FL isoform of human tafazzin (NP_000107; 292 amino acids). Without going into the description of classic tafazzins, note that their C-termini correspond to the motif shown in Figure1, which was generated from the alignment of the C-terminal sequence of the mammalian proteins to exon 11 of the human FL tafazzin. The C-terminal sequences are aligned without deletions, and the secondary structure is preserved not only in mammals and other vertebrates but also in model protostomes (Drosophila melanogaster, Caenorhabditis elegans), fungi (Saccharomyces cerevisiae), etc. (see Figure 1 in [13]).Figure 1
The C-terminal motif of classic tafazzins (aligned to exon 11 of human FL tafazzin).We bioinformatically analyzed the modifications in mammalian tafazzins in exons 5, 8–9, and 9–11. Specifically, the regions conserved among mammals have been identified in the C-terminal region of many isoforms of unconventional tafazzin as well as new species that acquired exon 5 in the tafazzin gene (apart from human and great apes; Hominidae). The first case tafazzins are referred to as unconventional (UTs), which are divided into two types (T1 and T2) distinguished by their motifs. The former motif results from the omission of exon 9 and a frameshift, while the second one results from intron retention between exons 10 and 11 and also a frameshift. The latter case when exon 5 is acquired is referred to as E5 tafazzins. In the rare cases, intron retention is observed between exons 8 and 9. These modifications have specific distribution among mammalian orders and correlate to the maximum lifespan and body weight as well as to the rate of mitochondrial metabolism. We propose the functional role of such changes.
## 2. Materials and Methods
Amino acid sequences were extracted from the RefSeq database [18] and supplemented with those from Ensembl v96 [19]. T1 isoforms of tafazzin were identified by PSI-BLAST [20] in RefSeq. The sequence ENHRADWEALQCPACARAAPGREQVSCGDSQSPD, a region of tafazzin matching in the Pacific white-sided dolphin (Lagenorhynchus obliquidens, isoform Х5) and the narrow-ridged finless porpoise (Neophocaena asiaeorientalis, isoform Х2), was used as the query. At the second iteration, the T1 set was supplemented only by tafazzins of the naked mole-rat (NMR, Heterocephalus glaber) as well as additional tafazzin isoforms of the giant panda (Ailuropoda melanoleuca) and African bush elephant (Loxodonta africana); these tafazzins have a lower similarity to the query. Subsequent iterations yielded no new proteins. Eventually, 50 tafazzin sequences have been identified (listed at sheet T1 of Table S1). The E value cutoff was 0.005; however, the same results were obtained for the values from 0.0001 to 0.1. Hereafter, the default values were used for all unmentioned BLAST parameters.T2 isoforms of tafazzin were identified in a similar way but using BLAST (PSI-BLAST yielded the same results). The query was the sequence PGRSSLRAAGQPQSFPSGGDSQSPD, a tafazzin region matching in the Pacific white-sided dolphin (Lagenorhynchus obliquidens, isoforms Х1–X4) and the narrow-ridged finless porpoise (Neophocaena asiaeorientalis, isoform Х1). The same results were obtained for E value cutoffs from 5·10−5 to 10, namely, 28 tafazzins listed at sheet T2 of Table S1 together with the query, which matches all identified regions in cetaceans. The tafazzin XP_028342714 (isoform Х1) of the sperm whale (Physeter catodon) corresponds to both T1 and T2 types. Its tafazzin XP_028342715 (Х2) matches the T1 and T2 types with E values of 10-12 and 2·10−5 and was assigned to T1. Table S1 includes a single tafazzin (XP_028342714) assigned to both T1 and T2 types.E5 isoforms of tafazzin were identified by BLAST in RefSeq. The query was the human tafazzin region encoded by exons 4, 5, and 6 (underlined are the exon boundaries): TPAAADICFTKELHSHFFSLGKCVPVCRGAEFFQAENEGKGVLDTGRHMPGAGKRREKGDGVYQKGMDFILEKLNHGDWVHIFPE. The results remain unaltered for E value cutoffs from 10-35 to 10-31. The identified proteins contain a region between exons 4 and 6 homologous to tafazzin exon 5 of apes (Hominidae, E5 tafazzins). Higher E values yield amino acid regions lacking the exon 5 region that cannot be assigned to E5 tafazzins. According to Table S1, E5 and T1 types do not overlap. Some species (sooty mangabey Cercocebus atys, green monkey Chlorocebus sabaeus, crab-eating macaque Macaca fascicularis, black snub-nosed monkey Rhinopithecus bieti, and African bush elephant Loxodonta africana) have both types, but none of their proteins belongs to both types. Thus, these three types have a single overlap (XP_028342714) for types T1 and T2, although there is no obvious reason why the loss of exon 9 cannot be combined with the acquisition of exon 5. All identified E5 tafazzins are classic (they conform to the logo in Figure 1).For the generation of the sequence logos presented in Figure2, a single region of each type (marked by an asterisk in Table S1) was used for each species to provide for even representation of species with a different number of tafazzin isoforms. The region most similar to the above queries for T1 or T2, respectively, was selected. Sequence logos were generated using the WebLogo service [21]. The protein secondary structures were predicted by JPred4 [22].Figure 2
Motifs specific for unconventional tafazzin isoforms: (a) type 1 (T1) and (b) type 2 (T2).
(a)
(b)
## 3. Results and Discussion
By analyzing data available in major databases, we have identified conserved C-terminal regions missing in the classic tafazzin in the amino acid sequences of mammalian tafazzin isoforms. Their motifs (sequence logos) are shown in Figures2(a) and 2(b), and the corresponding protein sequences are presented in Table S1. This table also presents the taxonomy and Latin name of species to facilitate using their common names. Unconventional tafazzins (UTs) apply to tafazzin isoforms containing the first or the second motifs (T1 and T2).The T1 motif was found in 23 mammalian species of 7 orders (or higher taxa): Afrotheria, Glires, Primates, Scandentia, Carnivora, Cetacea, and Artiodactyla, specifically in naked mole-rat (Heterocephalus glaber), Arctic ground squirrel (Urocitellus parryii), sooty mangabey (Cercocebus atys), green monkey (Chlorocebus sabaeus), crab-eating macaque (Macaca fascicularis), black snub-nosed monkey (Rhinopithecus bieti), golden snub-nosed monkey (Rhinopithecus roxellana), Chinese tree shrew (Tupaia belangeri chinensis), northern fur seal (Callorhinus ursinus), Steller sea lion (Eumetopias jubatus), California sea lion (Zalophus californianus), Hawaiian monk seal (Neomonachus schauinslandi), giant panda (Ailuropoda melanoleuca), Pacific white-sided dolphin (Lagenorhynchus obliquidens), narrow-ridged finless porpoise (Neophocaena asiaeorientalis), sperm whale (Physeter catodon), zebu (Bos indicus), cattle (Bos taurus), the hybrid of the two latter (Bos indicus × Bos taurus, NCBI:txid30522), white-tailed deer (Odocoileus virginianus), wild boar (Sus scrofa), Bactrian camel (Camelus bactrianus), and African bush elephant (Loxodonta africana).The T2 motif coincides completely in 12 species, specifically, in nearly all cetaceans and aquatic carnivores. It was found in walrus (Odobenus rosmarus), Weddell seal (Leptonychotes weddellii), Hawaiian monk seal (Neomonachus schauinslandi), brown and polar bears (Ursus arctos and Ursus maritimus) as well as American black bear (Ursus americanus, data from Ensembl), Pacific white-sided dolphin (Lagenorhynchus obliquidens), killer whale (Orcinus orca), common bottlenose dolphin (Tursiops truncatus), beluga whale (Delphinapterus leucas), narrow-ridged finless porpoise (Neophocaena asiaeorientalis), and sperm whale (Physeter catodon). It was also found in two chiropterans, black flying fox (Pteropus alecto) and Egyptian fruit bat (Rousettus aegyptiacus), as well as in a perissodactyl, white rhinoceros (Ceratotherium simum).According to MobiDB [23], the conserved UT regions overlap with long disordered regions usually up to the C-terminus. These disordered regions sometimes occur in other regions of proteins but are not typical for tafazzins without the specified T1 and T2 motifs. The identified regions cannot be aligned to domains involved in enzyme activity, which gives no grounds to assume their participation in protein attachment to the mitochondrial inner membrane or being a part of the catalytic center. Similarly, disordered regions have been found at the N termini of microtubule-binding and tubulin-sequestering proteins [24].Although RefSeq is extensive, other databases still contain proteomes missing in RefSeq. For instance, Ensembl contains the proteome of the American black bear (Ursus americanus) with the tafazzin containing a region matching T1; accordingly, Table S1 was supplemented with this species and the region.In addition to the tafazzins presented in TableS1, we have found tafazzins with the C-terminal region shared in the motifs, specifically, seven C-terminal amino acids as shown in the logo (Figure 2). These can be exemplified by the North American beaver (Castor canadensis), whose isoforms Х1, X2, and X5–X8 contain a region that partially matches both T1 and T2: VSFLPDSPKLSSVLPVPSDSQGTLAKVHEGCRPAPSLSAGGDAQSSD. The beaver can also be assigned to E5. Similarly, all isoforms (X1–X4) of the European rabbit (Oryctolagus cuniculus) include shortened T1 or T2; these are similar regions LPQGCGPTVSLSSGGDAQSPH (isoforms Х1 and X4), GCGPTVSLSSGGDAQSPH (Х2), and LPQGCGLSSGGDAQSPH (Х3), which allow us to call such proteins shortened UTs. Isoform X1 in naked mole-rat (Heterocephalus glaber) also contains the sequence GDAQGPD. Also, its T1 is represented by isoforms X2 and X3 while classic tafazzins include isoforms X4 and X5. The list of such examples goes on.There are regions with very weak similarity to T1 or T2. For instance, isoform X1 of the Colombian white-faced capuchin (Cebus capucinus) is similar to T1: ALWRPDAGGAEREAAARDRVEHRDFLAPRH; isoform X2 of the domestic sheep (Ovis aries) is similar to T2: VSFSLGLSSPFSLGLSSP; tafazzin of the dromedary (Camelus dromedarius) is similar to T2: VSSSPRQSCSCPSPSSP. To our knowledge, the capuchin has no classic tafazzin.It is of interest that the regions GDAQSPD, GDAQSSD, GDAQSPH, GDSQSPD, GDAESPD, and GDAQGPD corresponding to the last seven positions in Figure2 occur exclusively in unconventional tafazzins including shortened ones. Among 4 million proteins in RefSeq, there are only three exceptions, XP_007521742, XP_004712810, and XP_016049842 of European hedgehog (Erinaceus europaeus) and lesser hedgehog tenrec (Echinops telfairi), that are not tafazzins but include regions 2, 4, and 5 above. Specifically, the exact GDAQSPD sequence is present in as low as 28 mammalian proteins: 23 T1s and 5 T2s. GDSQSPD is present in 17 mammalian proteins: 4 T1s, 12 T2s, and 1 nontafazzin XP_016049842 of the hedgehog (Erinaceus europaeus). GDAQSSD is present in 20 mammalian proteins: 6 T1s, 8 T2s, 6 shortened UTs of the beaver (X1, X2, and X5–X8), and 1 nontafazzin XP_007521742 of the hedgehog. GDAESPD is present in 7 mammalian proteins: 4 T1s, 2 T2s, and 1 nontafazzin XP_004712810 of the tenrec (Echinops telfairi). GDAQSPH is present in 5 mammalian proteins: 1 T1 of Arctic ground squirrel (Urocitellus parryii) and 4 shortened UTs of the European rabbit (Oryctolagus cuniculus, X1–X4). GDAQGPD is present in 2 mammalian proteins: 2 T1s of the naked mole-rat (Heterocephalus glaber). RDAQSPD is present in 3 T1s of the African bush elephant (Loxodonta africana) and in more than a hundred nontafazzins of the family of sister chromatid cohesion protein PDS5 homolog A. Thus, these six regions largely mark unconventional tafazzins.Hereafter,patterns refer to tafazzin regions specified in Materials and Methods as queries. It is natural to define the threshold segregating true T1 and T2 proteins from those with only a remote resemblance to these types. In the case of T2, at least 19 out of 25 amino acids have to match, i.e., more than 3/4. In the case of T1, it seems that true regions match at least 2/3 of the pattern (more than 22 out of 34 amino acids), although some isoforms with a lower similarity were included in the list in Table S1. For instance, there is a region with a 50% identity (17 out of 34 amino acids) in isoform X14 (XP_023396534) of the African bush elephant (Loxodonta africana); however, another isoform of this species (X10) used in the logo generation has more than 2/3 of matches (23 out of 34). The challenges of such a threshold definition are shown below. The prairie deer mouse (Peromyscus maniculatus bairdii) represented in Ensembl but not in RefSeq has a sequence matching almost a half of the first part of the T1 pattern (16 out of 34 amino acids). Such shortened T1 is typical of many rodents (the number of unconventional isoforms in RefSeq is given in parentheses): house mouse (Mus musculus, 6), Gairdner’s shrewmouse (Mus pahari, 3), Ryukyu mouse (Mus caroli, 2), Chinese hamster (Cricetulus griseus, 4), Golden hamster (Mesocricetus auratus, 2), lesser Egyptian jerboa (Jaculus jaculus, 2), and guinea pig (Cavia porcellus, 1). At the same time, the alignment of the region of tafazzin of the prairie deer mouse demonstrates a convincing similarity, and the absence of such tafazzins in Table S1 is due to the similarity shortness, which we consider significant. The asterisk in the prairie deer mouse sequence indicates the stop codon:Query: ENHRADWEALQCPACARAAPGREQVSCGDSQSPDSubject:ENHRADREALQCTPCA∗Note that arginine at position 7 is not uncommon in mammals.The absence of the major part of the patterns in shortened tafazzins does not allow us to assign them to UTs, although the threshold similarity length has not been defined explicitly.In addition, new tafazzin isoforms that contain exon 5 have been found in the following orders (or higher taxa): Afrotheria, Glires, Primates, Carnivora, Cetacea, Artiodactyla, and Chiroptera. Previously, such E5 tafazzins have been found in hominids (Homo sapiens, Pan paniscus, Pan troglodytes, Gorilla gorilla, and Pongo abelii). Apart from these, we have identified E5 tafazzins in many Old World monkeys (Cercopithecidae): Cercocebus atys, Chlorocebus sabaeus, Macaca fascicularis, M. mulatta, M. nemestrina, Mandrillus leucophaeus, Papio anubis, Theropithecus gelada, and Rhinopithecus bieti as well as in the northern greater galago Otolemur garnettii. Occasional E5 tafazzins can be found beyond primates: in rodents (Ochotona princeps and Castor canadensis), laurasiatherians (Pantholops hodgsonii, Phyllostomus discolor, Balaenoptera acutorostrata, and Puma concolor), and afrotherians (Loxodonta africana). All identified E5 proteins are given in Table S1 (sheet E5).Complementation test in yeast has demonstrated the functional activity only for theΔ5 variant, which raises the question as to why exon 5 was preserved in evolution [25]. The full-length human tafazzin proved to complement the deletion of TAZ gene in Drosophila [16]. Schlame claimed that exon 5 could be found in the TAZ gene only in primates [7]; however, we have found many new instances of this exon.Figure3 shows the number of considered species, the number of species containing each unconventional type or E5 tafazzins, and their total number per taxon (these data are given in more detail in Table S1).Figure 3
Distribution of species containing each unconventional type or E5 tafazzins and their total number per taxon. The following indices are given for each taxon (left to right): total number of considered species, numbers of species with T1, T2, and E5, the total number of unconventional tafazzins, and this number supplemented with E5 tafazzins.In isolated cases, classic tafazzins conforming the description in Introduction preserve the intron between exons 8 and 9; such tafazzins will be referred to as CT+. Nine such cases have been found in RefSeq in the following primates:Homo sapiens, isoforms X2, X3, and X5 (XP_006724900, XP_016885250, and XP_024308199, respectively); bonobo (Pan paniscus), X2 (XP_008950941), Sumatran orangutan (Pongo abelii), X1 (XP_024096396), black-capped squirrel monkey (Saimiri boliviensis), X1, X2, and X5 (XP_010330095, XP_010330096, and XP_010330098), and chimpanzee (Pan troglodytes), X5, (XP_016798103). Specifically, the glycine (underlined) at the boundary of these exons, WHVGMND, is replaced with one of the following regions corresponding to a 117 bp intron insertion: GEPGDGDREMASGVGGLGLPLVPGCPAPPHVWPSVHCAAG (human, bonobo, and chimpanzee), GEPGDGDREMASGVGGLGVPLVPGCPAPPHVWPSVHCAAG (orangutan), and GEPGDGDRDKASGVGSLGLPLVPGCPAPPHVWPFVHCAAG (squirrel monkey).Noteworthily, this intron retention exists in the human and orangutan but is missing, e.g., in the gorilla.The exon-intron structures of the discussed tafazzin types are schematically shown in Figure4.Figure 4
The exon-intron structures of the considered tafazzin types. Usual exons (i.e., as in CL) are depicted by blue rectangles, retained introns are shown in green, and frameshifted exons are shown in red. The black outlines emphasize the distinguishing features of the tafazzin types.As already noted, the current work is devoted to the bioinformatic study of tafazzin isoforms. Experimental verification that such tafazzin isoforms are actually expressed will be performed in a separate work.Scatter plots for maximum lifespan (MLS, years) vs. body weight (M, kg) were generated for all classic and identified unconventional tafazzins (Figure5). MLS data were retrieved from the AnAge database [26]. The diagram in Figure 5(a) demonstrates that species with T2 and, to a lesser extent, T1 tend towards high body weights relative to those with the classic tafazzin. Specifically, T2 is observed in the case of body weights exceeding 100 kg except large bats: Egyptian fruit bat (Rousettus aegyptiacus, 125 g) and black flying fox (Pteropus alecto, 672 g) as well as narrow-ridged finless porpoise (Neophocaena asiaeorientalis, 32.5 kg). T1 is observed in the case of body weights exceeding 5.5 kg with the exception of naked mole-rat (Heterocephalus glaber, 35 g), blind mole-rat (Nannospalax galili, 160 g), and tree shrew (Tupaia chinensis, 200 g). Е5 (Figure 5(b)) is observed in the case of body weights exceeding 5.5 kg with the exception of pale spear-nosed bat (Phyllostomus discolor, 43 g), American pika (Ochotona princeps, 100 g), and northern greater galago (Otolemur garnettii, 1.3 kg). Similarly, MLS vs. longevity quotient (LQ) was considered (Figures 5(c) and 5(d)). T2 is characterized by a long lifespan (20 years or more even in the wild) and average LQ, while E5 features long lifespan and high (Hominidae) or average (the rest in Figures 5(c) and 5(d)) LQ. T1 has a wide range of LQ values but tends towards average LQ and long lifespan (more than 11 years).Figure 5
Distribution of mammalian tafazzins over lifespan and body weight (a, b) or longevity quotient (c, d) for classic tafazzin (CT) and unconventional T1 and T2 ones (a, c) or E5, T1, and T2 tafazzins (b, d).
(a)
(b)
(c)
(d)Not much data are available on the rate of mitochondrial metabolism for the considered species. These include the data on the mitochondrial metabolic rate (mtMR) [17], basal rate of oxygen consumption (BRO2) [27, 28], and (the most complete) mass-specific basal metabolic rate (msBMR) from the AnAge database [26] and elsewhere [29]. Several indices are available for certain species, which allowed us to reduce the available data to a single characteristic (Figure 6). The figure suggests that unconventional tafazzin isoforms focus on the optimal balance between the increased biochemical activity of mitochondria related to environmental or nutritional conditions and longevity maintenance. These unconventional tafazzins form two clusters with a significant difference in the body weight; the first one includes three artiodactyls (cattle, wild boar, and white-tailed deer; yellow squares), chimpanzee, orangutan, and human (neighboring bright-green and blue circles; according to E5 and CT+); while the second one includes the naked and blind mole-rats (yellow triangles), the microbats (Microchiroptera; 33.5 and 146 g; bright-green and bright-red diamonds), American pika (bright-green triangle), New World monkeys (squirrel monkey, blue circle above the curve; according to CT+), and northern greater galago (bright-green circles). In the second cluster, the body weight is nearly 100 times lower; however, the rate of oxygen consumption per body weight is 4-5 times higher. This is in a good agreement with the Kleiber equation V̇O2/m=3.42⋅m−0.25 [30] presented as a straight line in the figure. One can propose that the emergence of UTs in addition to E5 was a response to the increased mass-specific oxygen consumption considering that it is found in aquatic mammals, large bats, and white rhinoceros.Figure 6
Oxygen consumption by mammals. Unconventional tafazzins T1 and T2 as well as E5 and CT+ are marked in yellow, bright-red, bright-green, and blue, respectively (the data for the CT+ species are from [28]). The line labeled K is the Kleiber relation.(1) Conservation of Cardiolipin Synthase and Variability of Tafazzin. Cardiolipin synthase 1 encoded by the gene CRLS1 (ENSG00000088766) in human is highly conserved. A single isoform exists in most species. The reaction catalyzed by it yields a variety of cardiolipins whose transformation is mediated by the classic and unconventional isoforms of tafazzin. One can propose that these isoforms modulate the acyl composition of cardiolipins as a function of environmental conditions.(2) The Possible Relationship between T1 and T2. In addition to the discussed above sperm whale tafazzin XP_028342715 (X2) to a different extent applying to the T1 and T2 types, there is another sperm whale protein XP_028342714 (X1) fully applying to T2 and satisfactorily applying to T1. It is the only known tafazzin with a complete T2 motif preceded at a distance of 16 amino acids by an almost complete T1 motif (lacking the terminal GDSQSPD). This isoform was assigned to both types, T1 and T2. These three isoforms illustrate a possible transition from the “intermediate” T1 type to the “new” T2 type. Specifically,Here, X3 is a typical T1; X2 is a T1 with insertion from T2 (turquoise); and X1 is a T1 with an insertion converting it into T2 (T2-specific motif is underlined). Apparently, the loss of exon 9 is more common than the intron fixation here. Coupled with the high number of T1 tafazzins, this points to the emergence of T2 after T1.(3) Relationship between UT and Exons. In the classic tafazzin, the translation of exon 10 starts in phase 0 (i.e., the first exon nucleotide is the first codon nucleotide). The T1 tafazzin results from skipping exon 9 (see Figure 4) so that the spliced out region is not a multiple of three. After exon 9 splicing, the translation of exon 10 starts in phase 1 (the first nucleotide of the exon is the second nucleotide in the codon) and the first 26 amino acids of T1 motif are synthesized. The remaining 8 amino acids of the motif result from the translation of the subsequent exon eleven (also in phase 1 since the length of exon 10 is a multiple of three).This mechanism can be demonstrated on mouse tafazzin isoforms from Ensembl. The isoform ENSMUSP00000065270 corresponds to the classic tafazzin, while the other one (ENSMUSP00000134745) lacks exon 9 (ENSMUSE00000209157). In the first case, exon 10 translation yields amino acid sequence KITVLIGKPFSTLPVLERLRAENKSA; in the second case, ENHRADWEALQYTPCA, which corresponds to the onset of T1 motif. The mouse protein terminates here due to a stop codon; in the absence of it, the following sequence corresponds to T1 motif. This can be illustrated by the human FL isoform of tafazzin ENSP00000469981. After deletion of exon 9 (ENSE00003724812) from its transcript (ENST00000601016), the amino acid sequence corresponding to exon 10 and beginning of exon 11, KITVLIGKPFSALPVLERLRAENKSAVEMRKALT…, is replaced with ENHCADREALQCPACTRAAPGGEQVGCGDAESPD…, which corresponds to T1 motif. No exon 9 splicing has been reported for human; however, such proteins were experimentally demonstrated in mouse (e.g., Q810E8 in UniProt). It is not unlikely that the stop codon of the primary transcript is edited and translated as an amino acid in certain species.Similarly, it can be shown that T2 results from intron retention between exons 10 and 11 (see Figure4). This can be illustrated by two tafazzin isoforms of the polar bear. The first transcript (ENSUMAT00000031820), a classic tafazzin, has no introns; and translation of exons 10 and 11 generates the classic C-terminus: KITVLIGKPFSALPVLERLRAENKSAVEMRKALTDFIQEEFQRLKTQAEQLHNQLQRGR. In the second transcript (ENSUMAT00000031828), intron retention between exons 10 and 11 gives rise to the C-terminus with a typical T2 motif: KITVLIGKPFSALPVLERLRAENKSAVSCLSPLYHPPFPGLPCSCLSLSRHLQPPRAPGSSSPGPGSPRAAVQPQSFPSGGDAQSSD…. The sequence encoded by the retained intron is underlined and T2 motif is in bold. Notice that, similar to T1, exon 11 is translated in phase 1 rather than the natural phase 0, which explains the coincidence of the last seven amino acids in these two motifs (see Figure 2).(4) Special Features of C-Termini of UTs. The mechanism of UT realization, i.e., the functional role of the revealed conserved C-terminal regions of tafazzin, is of great interest. In this context, it should be noted that the C-terminal secondary structure differs in UTs and classic tafazzins (CTs) (Figure 7). For instance, the house mouse CT (ENSMUSP00000065270.6) has a single long helix at the C-terminus, while in shortened UTs it is broken into two (walrus, beaver, and rabbit) or more (naked mole-rat) parts. One can propose that these C-terminal helices in UTs do not interact with the membrane since they are rich in polar amino acids. Specifically, the C-terminus of these tafazzins following the RAENKSA motif contains 2-5 times more polar amino acids, which decreases the C-terminal hydrophobicity.Figure 7
Secondary structure of tafazzin. Helices and extended regions predicted by JPred4 are marked green and blue, respectively. Mouse, CT; walrus, seal, bear, orca, bat, and rhino, T2; beaver, rabbit, and NMR, shortened UT where underlined regions support their assignment to UT (beaver and NMR also have different isoforms listed in TableS1). Abbreviations: mouse: NP_852657.1, isoform 2 (Mus musculus); walrus: XP_004414556.1, X1 (Odobenus rosmarus); seal: XP_006739411.1, X1 (Leptonychotes weddellii); orca: XP_012394911.1, X1 (Orcinus orca); bear: XP_026344949.1, X1 (Ursus arctos); bat: XP_015979168.1, X1 (Rousettus aegyptiacus); rhino: XP_014653014.1, X1 (Ceratotherium simum); beaver: XP_020040765.1, X1 (Castor canadensis); rabbit: XP_017194047.1, X1 (Oryctolagus cuniculus); NMR: XP_004875054.1, X1 (Heterocephalus glaber). Entirely conserved positions are labeled with asterisks.(5) The Specificity of UT Taxonomic Distribution. UTs demonstrate highly uneven distribution in Euarchontoglires and Laurasiatheria. This is systemically shown in Figure 3 and briefly exemplified here. UTs are not found in monotremes and marsupials and are rare in afrotherians (1 out of 6=17%); this is also true for Е5. A similar UT distribution is observed in Euarchontoglires (9/51=18%), specifically, in Glires, Old World monkeys, and tree shrew; Е5 is more common (17/51=33%) in the same orders and families plus hominids and lemuriform primates (Strepsirrhini). UTs are found in Laurasiatheria in a much higher proportion, specifically, in pinnipeds, bears, toothed whales, ruminants, swines, camelids, perissodactyls, and fruit bats, while the proportion of E5 is much lower (4/62=6%). Neither UT nor E5 has been found in insectivores, pangolins, and anteaters and sloths. Usually, one of the types (T1 or T2) is represented in a family excluding earless seals and bears (Carnivora) and toothed whales. T2 was found in the polar, American black, and brown bears, while their remote relative, the giant panda, has Т1. Т2 was also found in fruit bats but is missing in considered microbat species of the Myotis genus.(6) UTs and MLS. The presence of UTs somewhat correlates with MLS as indicated by the examples below. Among long-lived rodents, unconventional T1 is found in the naked and blind mole-rats but is missing in the Damaraland mole-rat. No UTs have been found among other rodents except for the Arctic ground squirrel. Among primates, T1 was found only in certain Old World monkeys with low MLS as well as in a close relative of primates, the tree shrew (Euarchonta). Among afrotherians, T1 was found only in the African bush elephant. Among artiodactyls, T1 was found in species with both high (zebu, cattle, and Bactrian camel) and lesser MLS (white-tailed deer and wild boar). Many aquatic mammals with high MLS proved to have T1 or T2 or both. Overall, many long-lived species belong to orders where unconventional or E5 tafazzins were identified (primates, carnivores, perissodactyls, and cetartiodactyls).(7) UTs and Body Weight. UTs demonstrate an interesting distribution across taxonomic groups as a function of body weight. Irrespective of taxonomic groups, considered mammals with body weight exceeding 1000 kg had T1 (sperm whale and elephant) or T2 (walrus, killer whale, beluga whale, and sperm whale) (Figure 3) with a single exception: no UT has been found in the common minke whale; however, the group of baleen whales remains underexplored and its only classic tafazzin is marked as a low-quality protein in NCBI.In the range from 500 to 1000 kg, T2 has not been found among considered species. In ruminants, T1 was found only in the cattle and zebu (livestock), which can be attributed to increased biodiversity after natural selection was replaced with artificial one, whose rate is much higher [31]. Only classic tafazzin was found in the wild yak, bison, and wild water buffalo.Nearly a half (7/15=47%) of species with T2 fall into the range from 100 to 500 kg; these include cetaceans and carnivores. In tylopods, T1 was found in the domestic Bactrian camel but is missing in the wild Bactrian camel, which are considered different species [32]. This agrees with the above pattern for domestic and wild ruminants. In perissodactyls, UTs are absent in the common donkey, domesticated horse, and Przewalski’s horse. Their tafazzins have RAENKSA sequence at the end of exon 10; however, the following sequences does not allow them to be assigned to T2.In monkeys weighing less than 100 kg, T1 is found in about a half of the Old World monkeys (5/12=42%) with the terminal sequence GDAQSPD (except isoform X5 in the sooty mangabey Cercocebus atys); apparently, it competes with the classic monkey tafazzin with the exon 5 insertion. All hominids have only the classic tafazzin (with the exon 5 insertion).UTs are found in marine carnivores with the body weight from 165 to 1012 kg, i.e., within 2- to 3-fold variation from 500 kg; the latter value corresponds to the optimal balance between heat exchange and food resources [33]. No UTs were found in mustelids and baleen whales, whose body weight differs from 500 kg by order of magnitude, which can reflect different energy expenditures related to the food resources or a different evolutionary pathway. The manatee (Afrotheria) weighing 322 kg is the exception.(8) UTs and Evolution of Species. The relationship between UTs and evolution of species requires further analysis. However, the following observations deserve to be mentioned. No UTs were found in bats except T2 in two species that lack echolocation. Microbats followed their own evolutionary pathway resulting in decreased body size, special skills (echolocation, etc.), and improved flight performance [34]. Also, they have a higher metabolic activity owing to genes of the oxidative phosphorylation pathway and DNA repair efficiency [35]. In Old World primates, UTs are absent in hominids, T1 is found in monkeys, and both taxa have E5. UT and E5 are missing in New World monkeys. UTs are absent in lemuriformes. Apart from T1, which occurs in many mammals, more than half of marine mammals have T2. UTs have not been found in monotremes and marsupials as well as in early diverged placentals (Hoffmann’s two-toed sloth and armadillo); T1 UT was found only in the African bush elephant among afrotherians. Thus, one can conclude that UTs emerged late in evolution: they are absent in monotremes (218 MYA), marsupials (169 MYA), anteaters and sloths (99 MYA), and afrotherians (94 MYA) excluding the African bush elephant and later in insectivores (81 MYA) and pangolins (74 MYA) [36].
## 4. Conclusions
A wide but specific distribution of tafazzin (a cardiolipin remodeler) with altered C-terminus or intron insertions across orders and other taxa was demonstrated in Euarchontoglires and Laurasiatheria. Specifically, we have found conserved regions closer to the C-terminus in many unconventional isoforms, rare cases of intron retention between exons 8 and 9, and new species that acquired exon 5 in the tafazzin gene (apart from Hominidae). The C-terminal regions result from a frameshift relative to the full-lengthTAZ transcript after skipping exon 9 or retention of the intron between exons 10 and 11. The altered ratio between tafazzin isoforms can cause severe diseases such as Barth syndrome. These alterations demonstrate specific distribution among mammalian orders. The dependence of the species maximum lifespan, body weight, and mitochondrial metabolic rate on the alterations has been demonstrated. Arguably, unconventional tafazzin isoforms provide for the optimal balance between the increased biochemical activity of mitochondria (resulting from specific environmental or nutritional conditions) and lifespan maintenance, and the functional role of such isoforms is linked to the modification of the primary and secondary structures of their C-termini.
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*Source: 2901057-2019-10-24.xml* | 2019 |
# Research on Financial Cost Accounting and Control of Small- and Medium-Sized Enterprises under the Background of Data Mining
**Authors:** Wenyan Wang
**Journal:** Computational Intelligence and Neuroscience
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2901167
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## Abstract
In the time of data blast and the ascent of the Web, the dramatic development of information and the data needs of small- and medium-sized endeavors affect the customary expense of the executives. Instructions to all the more likely mine viable data in information to give effective ways and technique merits considering. As the center innovation of handling enormous information, information mining can deal with a lot of mind-boggling information effectively. Accordingly, this paper talks about the cycle and technique for applying information mining at the expense of the executives of small- and medium-sized endeavors, to work on the seriousness of small- and medium-sized undertakings. This examination depends on the exploration and examination of the monetary information of small- and medium-sized ventures, joined with information mining innovation, extricates and uses the immense monetary information produced in the day-to-day administration cycle of the monetary division of the small- and medium-sized undertakings, plans and executes an information mining-based monetary information examination of small- and medium-sized endeavors framework. Joined with programming plan thoughts, through fundamental interest exploration and examination and many benefits of the ongoing B/S design, it was chosen to utilize the Java programming language, MyEclipse11 programming apparatus, Microsoft SQL Server 2008 data set administration instrument, J2EE advancement stage, and the exemplary Apriori in information mining. Mining techniques, for example, affiliation rules, bunching calculations, and choice tree calculations, have completely dissected the monetary information of small- and medium-sized undertakings, naturally and dependably give monetary administration branches of small- and medium-sized endeavors and ranking directors of small- and medium-sized ventures with helpful monetary data, and can help small- and medium-sized endeavors. Business pioneers pursue speedy choices. The planned and executed monetary examination framework in light of information mining incorporates the fundamental elements of SME monetary administration, resource stock administration, resource designation of the board, resource deterioration and discount, resource information upkeep of the executives, and so on. Small- and medium-sized undertakings’ monetary administration framework is a mix of information mining innovation, programming innovation, and small- and medium-sized monetary administration. The effective, solid, and helpful way has further developed the center seriousness of small- and medium-sized undertakings partially and accomplished a definitive objective of the framework plan.
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## Body
## 1. Introduction
In the period of data blast, individuals have a more extensive scope of ways of getting data. Getting different required data from the Web has turned into the primary wellspring of data. Financial backers attempt to acquire significant data to give information backing to future speculation choices. Undertakings have collected a lot of information in activity and from the executives, and different monetary sites likewise distribute letters of major recorded organizations consistently. Chiefs need to examine this information and go with different choices. In spite of the fact that data frameworks are increasingly more generally utilized in the business of the executive exercises, how to productively look for helpful data is as yet a major issue for business supervisors. To settle on choices more sensible and powerful, supervisors need to specifically deal with enormous measures of information, which is likewise incredibly tedious. Mass data carries many pessimistic impacts on individuals, the most significant is that there is an excess of futile data, and extricating compelling information is troublesome. A lot of futile data will definitely influence the idealness of supervisors’ independent direction and will unavoidably cause data contortion. It is hard to separate viable data and will definitely prompt a significant expansion in administration costs. Undertakings critically need to direct inside and out investigation of gigantic monetary information to extricate possibly compelling data so that endeavors can utilize it. Is it conceivable to track down another strategy to rapidly handle a lot of boisterous and deficient information to mine valuable data, create powerful data to help independent direction, and deliberately produce a particular model, which undertaking supervisors can utilize just to What might be said about recreating genuine working outcomes? The boundless utilization of information mining innovation is to tackle such issues. Mining helpful data from gigantic information is the basic utilization of information mining innovation. Supervisors can utilize the mining results to lay out target models and afterward lay out a total arrangement of dynamic frameworks, which is valuable for directors to really control dynamic data and pursue the right choices, in order to work on the seriousness of ventures [1–8].Notwithstanding, the complicated issues achieved by information additionally bring new difficulties for SMEs. The first is the adjustment of the size of information. With the approach of the information period, SMEs should not just complete the assortment, arranging and examination of inside information of SMEs, yet additionally outside natural information, industry information, modern chain information, contender information, utilization information of SMEs. SMEs need to gather, distinguish, sort and store sensibly. The second is the difference in information types. Small- and medium-sized undertakings will create a lot of information during the time spent in creation and activity exercises, including organized information utilized for conventional monetary direction, as well as unstructured information that tremendously affects the monetary decision-production of SME partners’ information. Sensible capacity and use of unstructured information and the utilization of unstructured information to help monetary information in direction are the subsequent test brought by the information age. Obviously, traditional financial analysis methods have shown difficulty in meeting the decision-making needs of modern SMEs. In the process of financial analysis, data mining technology needs to be used reasonably to help SMEs meet the above challenges smoothly. So how to effectively combine data mining technology with financial analysis methods, how to complete the collection, sorting, and storage of huge data sets, and conduct reasonable screening, analysis, and research on these data, so that the value of the data can be brought into play, reflecting the valuable business information, and then help SME managers to make financial and strategic decisions that adapt to the development environment, make SMEs develop in the right direction, and improve the market competitiveness of SMEs is an urgent problem to be solved.
## 2. Related Work
With the quick advancement of Web innovation, PC applications, computerized reasoning, and other data innovations, data innovation has entered into varying backgrounds and furthermore includes all parts of individuals’ everyday creation and life. Endeavor monetary data development is no exemption. With the ceaseless expansion in the business field of endeavors, enormous medium and little undertakings, for example, state-claimed ventures, confidential undertakings, and global endeavors, are creating increasingly huge scope fiscal summary information consistently. The sporadic and outlandish administration of this monetary information has turned into a difficult issue that influences the typical improvement of corporate money. Notwithstanding, the monetary information board of certain endeavors actually stays at the degree of conventional succeed reports or independent administration programming, and, surprisingly, a few little undertakings actually hold the paper-based administration of corporate monetary information. These conventional and in-reverse administration techniques truly confine the speed of big business advancement. With the rising number of corporate monetary information, the utilization of data and deliberate administration of corporate monetary information has become one of the critical worries of corporate pioneers.Information mining arose in 1989. It is the study of finding regulations from tremendous informational collections. It incorporates a wide range of exploration fields and primarily brings about the bearing of data sets, measurements, AI, computerized reasoning, and so on. Utilizing “information mining” as the watchword to look on CNKI, beyond 140,000 related papers can be found. Information mining innovation is presently broadly utilized in designing, medication, financial matters, and different fields. Carlos fabricated a monetary choice emotionally supportive network for undertakings in view of the brain network model, and the framework takes monetary proportion file as the primary exploration object to give monetary information backing to corporate monetary direction. Through the brain network model, the effect of corporate monetary choices on pointers can be judged, and the related monetary choices can be chosen in light of the advancement assumptions for monetary markers. This paper centers around the use of brain network models in the monetary field and represents the reasonableness and adequacy of information mining innovation in the monetary field. Tae Kyung Sung utilizes the choice tree model in information mining innovation to complete the monetary examination of endeavors in various outer climates. This study utilizes the choice tree technique to create different monetary conjecture results when the outside conditions change, and the monetary gauge part is improved somewhat. Wang Qing laid out an information mining strategy in light of the dim framework hypothesis and joined with the information on monetary examination, to mine the current monetary information of recorded organizations. Through group examination, the relationship and similitude of corporate monetary pointers were mined, and the connection between monetary markers in a specific industry in a specific period was closed. Nonetheless, the ends drawn by this calculation might be impacted by the possibility of the information, and whether it very well may be utilized as a reason for monetary examination is as yet worth investigating. Cao Zhong accepts that monetary exercises are a significant piece of the financial exercises of endeavors, and the advancement of big business data should be planned with a monetary data framework as the center, with requirements to finish the assortment, handling, and criticism of information on time. Utilizing information mining innovation to manage the huge measure of data and quick handling pace can meet the plan prerequisites of the monetary data framework. Important data can be found from a lot of monetary information and ideal input can be finished. This study applies information mining innovation to the monetary examination framework and utilizes the benefits of information mining innovation to assist the framework with handling a lot of information and rapid criticism results, demonstrating that information mining innovation has high application esteem in the field of monetary investigation. In any case, this study accentuates the job of information mining innovation in information assortment and handling and has not been executed in unambiguous monetary examination and monetary direction. Gan Weiping accepts that according to the viewpoint of monetary examination, information mining innovation can assist its clients with rapidly acquiring important data and information. Through this innovation, undertaking business data can be immediately handled and the proficient transmission of inner data can be accomplished simultaneously. Assist undertakings with investigating expected markets and clients, and give dynamic premise to the executives' independent direction. Simultaneously, he additionally applied information mining innovation to showcasing different fields and added reasonable experience in information mining innovation. This study consolidates information mining innovation with business exercises, which gives an incredible premise to board navigation. It is the pattern of future exploration to utilize information digging to offer help for business navigation. Yu Cuijing and Qian Xiaojiang applied information mining innovation to the ERP board framework and accomplished good outcomes. Information mining innovation can actually engage the ERP framework and simultaneously complete the viable blend of the inward information of the ERP framework and the outer information of the venture, help the ERP framework to procure, process, and investigate the outside information of the undertaking, and further develop the ERP framework’s presentation. In this study, the information mining innovation is applied to the ERP board framework and has accomplished great outcomes, as yet profiting from the benefits of information mining innovation handling information in huge request and quick speed. Zhao Xuanyuan and Xue Jianlou take the country’s land industry as the exploration item and utilize the group investigation strategy to do a point-by-point bunch examination of corporate monetary markers to furnish financial backers with a dynamic premise. According to the point of view of financial backers, this study leads monetary examination and shows the application worth of information mining innovation. Cao Zhihua summed up the generally utilized information mining strategies, essentially including brain organizations, fluffy sets, and choice trees. He accepted that information mining innovation could not tackle the issues of conventional monetary investigation techniques assuming handling monetary data was just utilized. Future information mining innovation ought to make forward leaps from the two elements of information obtaining and examination objects. According to the point of view of information securing, information mining innovation is utilized to acquire unstructured information. The examination object point ought to be joined with nonmonetary information and unstructured information for joint investigation. Li Rongli accepts that information mining innovation enjoys the benefits of exhaustiveness and profundity, which is truly appropriate for big business monetary information investigation. She consolidated information mining innovation with corporate monetary investigation and developed a monetary examination model by utilizing information mining strategies based on symptomatic information obtained from general judgment and exceptional judgment. This study joins information mining techniques with the monetary examination hypothesis and utilizes bunching investigation, choice tree model, and other computational strategies to help the monetary investigation process, making the examination results more significant.From the above writing survey, it very well may be seen that the utilization of information mining innovation in the field of monetary examination has been moderately full grown, and researchers in our nation have likewise accomplished a great deal of results in the use of information mining in the field of monetary examination. An agreement has been reached according to the point of view of certain burdens of monetary examination. Later on, information mining innovation is not just utilized in information assortment and handling, yet in addition gives commonsense choice help to pertinent partners of undertakings according to the viewpoint of information mining results [9–15].
## 3. Construction of the Financial Cost Control System for Small and Medium Enterprises Based on Data Mining Technology
### 3.1. Cost Accounting and Control System Architecture Design
#### 3.1.1. Physical Architecture Design
The monetary examination framework in view of information mining is mostly planned and carried out in light of B/S engineering. The B/S design has numerous qualities, such as simple organization, simple upkeep, and client accommodation, and understands the detachment of the client side and the server side. Considering the significance and secrecy of the monetary information of small- and medium-sized ventures, the monetary examination framework to be created will be sent to the intranet and introduced in the neighborhood of small- and medium-sized undertakings and it can accomplish total actual separation from the outside network through the firewall and forestall the assault of unfamiliar unlawful gatecrashers.
#### 3.1.2. Software Architecture Design
The actual engineering configuration chart of the monetary investigation framework for small- and medium-sized endeavors in light of information mining predominantly incorporates the UI Layer (UIL), the Business Rationale Layer (BLL) that carries out client login and UI activities, and the information access layer. It understands the trade and shared calling of monetary information of small- and medium-sized endeavors. The information mining layer conducts inside and out mining and investigation of the monetary information of small- and medium-sized ventures to extricate possibly helpful worth data. The important part of the information foundation layer mainly includes dataset arrangement records and SQL Server 2008 dataset management device to ensure the validity of financial information of small and medium-sized enterprises. In Figure1, the product engineering configuration graph of the monetary examination framework for small- and medium-sized endeavors is given [16].Figure 1
Software architecture design diagram.
### 3.2. Design of Functional Modules of Cost Accounting and the Control System
#### 3.2.1. Financial Management Function of SMEs
The SME account management functions include financial card management operations, SME asset addition operations, general ledger management operations, and subsidiary ledger management operations. The design of the financial management function module of SMEs is shown in Figure2 [17] and Table 1.Figure 2
Financial management functional modules of small- and medium-sized enterprises including a detailed description of the functional modules of SME financial management.Table 1
Detailed description of financial management functions of small- and medium-sized enterprises.
NumberingAction nameFunction descriptionF1Financial card managementFinancial card management is the comprehensive management of system cards. Including adding, modifying, querying, deleting, and printing financial cards.F2Corporate finances increaseMainly complete the functions of adding, saving, modifying, deleting, locating, and copying financial cards of newly added fixed assets and deferred assets. When “assets are added,” the system automatically pops up a window for adding assets: you can add, modify, delete, and copy asset cards. Copying is a quick way to input multiple cards with similar card content when inputting.F3Financial ledger managementIn the process of fixed asset management, it is necessary to grasp the statistics, summary, and other information of assets in a timely manner. The main operations of general ledger management include setting common query conditions, selecting query units, and displaying impairment reserves.F4Financial ledger managementA subsidiary ledger is an account book used to classify and register detailed changes in assets within a certain period. Its main operations include setting common query conditions, selecting query units, displaying impairment reserves, displaying usage status and departments, displaying voucher numbers, displaying other card items, and printing detailed ledgers.
#### 3.2.2. Asset Inventory Management Function
Asset inventory management mainly includes asset inventory, inventory surplus assets, inventory difference adjustment, multiaccount book management, change order management, and other major operations. Figure3 shows the design of the asset inventory management function [18].Figure 3
Asset inventory management function design.The detailed description of the SME asset inventory management function is shown in Table2.Table 2
Detailed description of asset inventory management functions.
NumberingAction nameFunction descriptionF1Property assessmentThe business documents for asset count are processed here, and document maintenance and approval are performed. The inventory function only supports the information of the inventory business, and the generated reduction document and difference adjustment document are all documents under the business account book.F2Profitable assetsDocuments for inventory surplus assets are automatically generated by the system based on the final inventory check-list after review. The subledger is an inventory difference for classifying and registering the detailed changes of assets within a certain period.F3Inventory difference adjustmentThe adjustment sheet is automatically generated from the non-conforming assets after the inventory is reviewed. In the account book query, add a query “asset account book” button, and use this button to select the desiredF4Multi-book managementQuestion data. Account books must be chosen independently; the default is the primary record book, which upholds the multibranch question of one record book. Change request from the executives is the complete administration of progress orders made by the framework. Predominantly incorporate requestsF5Change order managementChange order, joint check asset card, and joint check specific change order.
#### 3.2.3. Asset Allocation Management Function
The management functions of asset transfer are mainly operations such as asset transfer, asset transfer, asset reduction, moving joint construction assets, and asset depreciation adjustment. The design of the asset allocation management function is shown in Figure4 [19].Figure 4
Design of asset allocation management function.The specific description of the asset allocation management function is shown in Table3.Table 3
Asset allocation management function specific description table.
NumberingAction nameFunction descriptionF1Asset call outThe approval of the transfer of assets is mainly to complete the maintenance and approval of the transfer of fixed assets among the enterprises within the group. It mainly includes adding an approval document, modifying an approval document, reviewing an approval document, a card for a joint investigation and issuing a document, and transferring assets.F2Asset transferAsset transfer approval mainly completes the maintenance and approval of transferred fixed assets among the enterprises within the group. It mainly includes modifying the transfer approval document, approval document, and asset transfer.F3Assets decreaseAsset reduction processing is different from asset card deletion: card deletion means that in the month of card entry, the card entry error is found, and the card information is completely removed from the system. It mainly includes cards for adding asset reduction documents, modifying asset reduction documents, deleting asset reduction documents, reviewing asset reduction documents, performing asset reduction, querying asset reduction documents, and checking asset reduction documents jointly.F4Mobile co-construction assetsAccording to the original value of fixed assets, impairment provision, and accumulated depreciation derived from the mobile ERP system, a mobile co-constructed fixed asset card is formed. The business attributes of the card such as asset name, storage location, user department, management department, and user must be lost. Attributes can be set according to the actual situation and imported after forming the fixed asset card ledger of mobile joint construction assets.F5Asset depreciation adjustmentAfter the mobile joint asset card is added, the system does not accrue depreciation. By synchronizing the depreciation accrued in each period of the mobile ERP system to the enterprise asset management system through the adjustment of accumulated depreciation. The adjustment of asset depreciation mainly includes adjustment to increase the original value of assets, adjustment of asset depreciation, and provision for impairment.
#### 3.2.4. Asset Depreciation and Write-Off Function
Asset depreciation and write-off mainly include operations such as asset depreciation and amortization, detailed depreciation calculation table, departmental depreciation summary table, asset depreciation adjustment, and provision for impairment. The asset depreciation and write-off function design are shown in Figure5 [20].Figure 5
Asset depreciation and write-off management function design.The detailed description of asset depreciation and write-off management functions is shown in Table4.Table 4
Detailed description of asset depreciation and write-off management functions.
<!—Col Count:3 NumberingAction nameFunction descriptionF1Depreciation and amortization of assetsThe list of depreciation amounts for all assets accrued for depreciation displayed in the depreciation list. The depreciation list for a single period lists the card number, asset name, original accrued value, asset number, accumulated depreciation, monthly depreciation, and monthly depreciation. Rate, unit depreciation, monthly workload, and cumulative workload information. It mainly includes accruing depreciation, querying depreciation list, modifying depreciation list, querying depreciation allocation summary table, and filtering depreciation list.F2Depreciation calculation scheduleThe detailed list of depreciation calculation of fixed assets is a detailed list of the original value accrued in the previous month, the depreciation accrued in the previous month, the increase or decrease of the original value in the previous month, the original value accrued in this month, and the depreciation accrual in this month according to the specified classification, including setting up depreciation schedule query, unit query, detail (summary) query, and depreciation calculation schedule.F3Departmental depreciation summaryAlthough each fixed-capital card has a management department, a user department, and a depreciation bearing department, the depreciation allocation will eventually be carried out according to the department pointed by the depreciation bearing department, that is, the depreciation of each asset will eventually be allocated to the department pointed by the bearing department. In this table, the displayed department refers to the department to which the depreciation charge will eventually be allocated. For example, if an asset management department is the finance department, the user department is the administration department, and the depreciation undertaking department is the user department, the information found in this table is the depreciation information undertaken by the administration department; the administration department refers to the depreciation undertaking department.F4Asset depreciation assessmentThe asset evaluation summary sheet is an account sheet that categorizes and summarizes the appraisal of fixed assets within a certain period. Including setting evaluation conditions and selecting evaluation units.F5Provision for impairmentThe mobile co-construction assets shall be accrued for impairment at the end of the year, and each unit shall adjust the depreciation reserves before the settlement of fixed assets at the end of the year (December 31). Reasons for changes in the template: co-construction assets are depreciated; the type of change is the adjustment for impairment allowances.
#### 3.2.5. Asset Data Maintenance Management Function
The maintenance and management functions of asset data include asset changes, asset appraisals, asset impairments, asset splits, and asset consolidation operations. The asset data maintenance management function design is shown in Figure6 [21].Figure 6
Asset data maintenance function design.The specific description of asset data maintenance and management functions is shown in Table5.Table 5
Detailed description of asset data maintenance and management functions.
NumberingAction nameFunction descriptionF1Asset changesUsing the asset change document, you can realize the addition of card number, net value, net amount, provision for impairment, monthly depreciation amount, monthly depreciation rate, accrued month, currency, start date of use, depreciation auxiliary exchange rate, unit depreciation, depreciation exchange rate, cumulative workload, monthly workload, and trace changes of all other card items outside the multi-use department.F2_Asset valuationThe asset assessment function of this system is to provide assessable assets including original value, accumulated depreciation, net value, total work, service life, and net residual value rate. It mainly includes selecting assets to be assessed, defining formulas and production valuation data, manually entering and modifying valuation data, and making valuation sheets.Asset impairmentIf the assets of the enterprise have actually been impaired, provision for impairment should be made. Specifically, it includes adding an impairment provision document, selecting assets to be depreciated, creating an impairment provision document, modifying an impairment provision document, and querying an impairment provision document.Asset splitIn the asset split interface, click the “add” button, enter the “split card no.” in the header to bring out the corresponding data of the split card, and the table body will be split through operations such as “add row” and “delete row.” The number and amount of divided cards are divided into asset cards in different meter bodies. It includes adding split orders, cancelling asset splits, reviewing split orders, executing asset splits, modifying split orders, and making balance adjustments.Asset consolidationAsset merging is implemented through document templates. The first line of the document table body is merged into the main card, and most of the items that form a new card after merging are consistent with this card. Therefore, before merging assets, you need to select the main card to be merged. The purpose is to save follow-up = workload.
### 3.3. Database Design of Cost Accounting and the Control System
#### 3.3.1. Conceptual Structure Design
The SME financial analysis system based on data mining is mainly aimed at leaders or investment elites in the fields of SME financial management, SME management, financial analysis, and so on, such as SME leaders, financial department managers, financial analysts, and investors [22]:(1)
SME entity attributes include SME code, SME name, SME legal person, SME address, contact person, contact number, registered capital, SME attributes, industry, social unified credit code, business Scope, activity area, business supervisory unit, whether it has subordinate departments, number of departments, issuing authority, issuing date, registration date, and remarks(2)
Department entity attributes include department code, department name, department abbreviation, display order, department attribute, auxiliary login, department type, establishment time, inventory organization, department level, telephone, superior department, department head, whether for retail, address, and notes(3)
Customer entity attributes include customer code, customer name, customer abbreviation, foreign language name, industry, whether it is a retail investor, whether it is a DRP node, whether it is a channel member, unit address, contact person, contact number, region, customer person in charge, head office code of the merchant, type of merchant, corresponding department, region, taxpayer registration number, registered capital, economic type, legal person, price group, and remarks(4)
Cash account attributes include account code, account name, mnemonic code, account opening company, currency, account opening date, contact person, contact number, account status, sealing date, account cancellation date, whether the minimum balance is controlled, minimum balance, minimum balance control scheme, whether maximum balance control, maximum balance, maximum balance control scheme, and remarks(5)
Item attributes of financial documents include document number, document status, card code, account code, account name, account type, specification model, management department, user department, start time, service life, and withdrawal month, original value in original currency, original value in local currency, accumulated depreciation, net value, provision for impairment, net amount, net residual value, reduction method, and remarks(6)
Budget report credits incorporate monetary number, monetary classification, division, utilizing division, money, subordinate, move date, approaching sum, account balance, business archive number, voucher number, outline, input charge, current month to month affirmation of record section, account status, account move, account type, administrator, whether to make a record, and comments(7)
Data credits of SME representatives incorporate worker number, name, ID number, work number, orientation, date of birth, kind of work, division, marriage, personal residence, bank card number, account opening bank, section time, working years, whether it is an extraordinary sort of work, rank, and comments
#### 3.3.2. Logic Structure Design
The financial analysis system based on data mining mainly includes seven data tables, which are SME entity attribute table, department entity attribute table, customer entity attribute table, cash account attribute table, financial document item attribute table, financial statement attribute table, small- and medium-sized enterprise attribute table, and employee information attribute table [23].
## 3.1. Cost Accounting and Control System Architecture Design
### 3.1.1. Physical Architecture Design
The monetary examination framework in view of information mining is mostly planned and carried out in light of B/S engineering. The B/S design has numerous qualities, such as simple organization, simple upkeep, and client accommodation, and understands the detachment of the client side and the server side. Considering the significance and secrecy of the monetary information of small- and medium-sized ventures, the monetary examination framework to be created will be sent to the intranet and introduced in the neighborhood of small- and medium-sized undertakings and it can accomplish total actual separation from the outside network through the firewall and forestall the assault of unfamiliar unlawful gatecrashers.
### 3.1.2. Software Architecture Design
The actual engineering configuration chart of the monetary investigation framework for small- and medium-sized endeavors in light of information mining predominantly incorporates the UI Layer (UIL), the Business Rationale Layer (BLL) that carries out client login and UI activities, and the information access layer. It understands the trade and shared calling of monetary information of small- and medium-sized endeavors. The information mining layer conducts inside and out mining and investigation of the monetary information of small- and medium-sized ventures to extricate possibly helpful worth data. The important part of the information foundation layer mainly includes dataset arrangement records and SQL Server 2008 dataset management device to ensure the validity of financial information of small and medium-sized enterprises. In Figure1, the product engineering configuration graph of the monetary examination framework for small- and medium-sized endeavors is given [16].Figure 1
Software architecture design diagram.
## 3.1.1. Physical Architecture Design
The monetary examination framework in view of information mining is mostly planned and carried out in light of B/S engineering. The B/S design has numerous qualities, such as simple organization, simple upkeep, and client accommodation, and understands the detachment of the client side and the server side. Considering the significance and secrecy of the monetary information of small- and medium-sized ventures, the monetary examination framework to be created will be sent to the intranet and introduced in the neighborhood of small- and medium-sized undertakings and it can accomplish total actual separation from the outside network through the firewall and forestall the assault of unfamiliar unlawful gatecrashers.
## 3.1.2. Software Architecture Design
The actual engineering configuration chart of the monetary investigation framework for small- and medium-sized endeavors in light of information mining predominantly incorporates the UI Layer (UIL), the Business Rationale Layer (BLL) that carries out client login and UI activities, and the information access layer. It understands the trade and shared calling of monetary information of small- and medium-sized endeavors. The information mining layer conducts inside and out mining and investigation of the monetary information of small- and medium-sized ventures to extricate possibly helpful worth data. The important part of the information foundation layer mainly includes dataset arrangement records and SQL Server 2008 dataset management device to ensure the validity of financial information of small and medium-sized enterprises. In Figure1, the product engineering configuration graph of the monetary examination framework for small- and medium-sized endeavors is given [16].Figure 1
Software architecture design diagram.
## 3.2. Design of Functional Modules of Cost Accounting and the Control System
### 3.2.1. Financial Management Function of SMEs
The SME account management functions include financial card management operations, SME asset addition operations, general ledger management operations, and subsidiary ledger management operations. The design of the financial management function module of SMEs is shown in Figure2 [17] and Table 1.Figure 2
Financial management functional modules of small- and medium-sized enterprises including a detailed description of the functional modules of SME financial management.Table 1
Detailed description of financial management functions of small- and medium-sized enterprises.
NumberingAction nameFunction descriptionF1Financial card managementFinancial card management is the comprehensive management of system cards. Including adding, modifying, querying, deleting, and printing financial cards.F2Corporate finances increaseMainly complete the functions of adding, saving, modifying, deleting, locating, and copying financial cards of newly added fixed assets and deferred assets. When “assets are added,” the system automatically pops up a window for adding assets: you can add, modify, delete, and copy asset cards. Copying is a quick way to input multiple cards with similar card content when inputting.F3Financial ledger managementIn the process of fixed asset management, it is necessary to grasp the statistics, summary, and other information of assets in a timely manner. The main operations of general ledger management include setting common query conditions, selecting query units, and displaying impairment reserves.F4Financial ledger managementA subsidiary ledger is an account book used to classify and register detailed changes in assets within a certain period. Its main operations include setting common query conditions, selecting query units, displaying impairment reserves, displaying usage status and departments, displaying voucher numbers, displaying other card items, and printing detailed ledgers.
### 3.2.2. Asset Inventory Management Function
Asset inventory management mainly includes asset inventory, inventory surplus assets, inventory difference adjustment, multiaccount book management, change order management, and other major operations. Figure3 shows the design of the asset inventory management function [18].Figure 3
Asset inventory management function design.The detailed description of the SME asset inventory management function is shown in Table2.Table 2
Detailed description of asset inventory management functions.
NumberingAction nameFunction descriptionF1Property assessmentThe business documents for asset count are processed here, and document maintenance and approval are performed. The inventory function only supports the information of the inventory business, and the generated reduction document and difference adjustment document are all documents under the business account book.F2Profitable assetsDocuments for inventory surplus assets are automatically generated by the system based on the final inventory check-list after review. The subledger is an inventory difference for classifying and registering the detailed changes of assets within a certain period.F3Inventory difference adjustmentThe adjustment sheet is automatically generated from the non-conforming assets after the inventory is reviewed. In the account book query, add a query “asset account book” button, and use this button to select the desiredF4Multi-book managementQuestion data. Account books must be chosen independently; the default is the primary record book, which upholds the multibranch question of one record book. Change request from the executives is the complete administration of progress orders made by the framework. Predominantly incorporate requestsF5Change order managementChange order, joint check asset card, and joint check specific change order.
### 3.2.3. Asset Allocation Management Function
The management functions of asset transfer are mainly operations such as asset transfer, asset transfer, asset reduction, moving joint construction assets, and asset depreciation adjustment. The design of the asset allocation management function is shown in Figure4 [19].Figure 4
Design of asset allocation management function.The specific description of the asset allocation management function is shown in Table3.Table 3
Asset allocation management function specific description table.
NumberingAction nameFunction descriptionF1Asset call outThe approval of the transfer of assets is mainly to complete the maintenance and approval of the transfer of fixed assets among the enterprises within the group. It mainly includes adding an approval document, modifying an approval document, reviewing an approval document, a card for a joint investigation and issuing a document, and transferring assets.F2Asset transferAsset transfer approval mainly completes the maintenance and approval of transferred fixed assets among the enterprises within the group. It mainly includes modifying the transfer approval document, approval document, and asset transfer.F3Assets decreaseAsset reduction processing is different from asset card deletion: card deletion means that in the month of card entry, the card entry error is found, and the card information is completely removed from the system. It mainly includes cards for adding asset reduction documents, modifying asset reduction documents, deleting asset reduction documents, reviewing asset reduction documents, performing asset reduction, querying asset reduction documents, and checking asset reduction documents jointly.F4Mobile co-construction assetsAccording to the original value of fixed assets, impairment provision, and accumulated depreciation derived from the mobile ERP system, a mobile co-constructed fixed asset card is formed. The business attributes of the card such as asset name, storage location, user department, management department, and user must be lost. Attributes can be set according to the actual situation and imported after forming the fixed asset card ledger of mobile joint construction assets.F5Asset depreciation adjustmentAfter the mobile joint asset card is added, the system does not accrue depreciation. By synchronizing the depreciation accrued in each period of the mobile ERP system to the enterprise asset management system through the adjustment of accumulated depreciation. The adjustment of asset depreciation mainly includes adjustment to increase the original value of assets, adjustment of asset depreciation, and provision for impairment.
### 3.2.4. Asset Depreciation and Write-Off Function
Asset depreciation and write-off mainly include operations such as asset depreciation and amortization, detailed depreciation calculation table, departmental depreciation summary table, asset depreciation adjustment, and provision for impairment. The asset depreciation and write-off function design are shown in Figure5 [20].Figure 5
Asset depreciation and write-off management function design.The detailed description of asset depreciation and write-off management functions is shown in Table4.Table 4
Detailed description of asset depreciation and write-off management functions.
<!—Col Count:3 NumberingAction nameFunction descriptionF1Depreciation and amortization of assetsThe list of depreciation amounts for all assets accrued for depreciation displayed in the depreciation list. The depreciation list for a single period lists the card number, asset name, original accrued value, asset number, accumulated depreciation, monthly depreciation, and monthly depreciation. Rate, unit depreciation, monthly workload, and cumulative workload information. It mainly includes accruing depreciation, querying depreciation list, modifying depreciation list, querying depreciation allocation summary table, and filtering depreciation list.F2Depreciation calculation scheduleThe detailed list of depreciation calculation of fixed assets is a detailed list of the original value accrued in the previous month, the depreciation accrued in the previous month, the increase or decrease of the original value in the previous month, the original value accrued in this month, and the depreciation accrual in this month according to the specified classification, including setting up depreciation schedule query, unit query, detail (summary) query, and depreciation calculation schedule.F3Departmental depreciation summaryAlthough each fixed-capital card has a management department, a user department, and a depreciation bearing department, the depreciation allocation will eventually be carried out according to the department pointed by the depreciation bearing department, that is, the depreciation of each asset will eventually be allocated to the department pointed by the bearing department. In this table, the displayed department refers to the department to which the depreciation charge will eventually be allocated. For example, if an asset management department is the finance department, the user department is the administration department, and the depreciation undertaking department is the user department, the information found in this table is the depreciation information undertaken by the administration department; the administration department refers to the depreciation undertaking department.F4Asset depreciation assessmentThe asset evaluation summary sheet is an account sheet that categorizes and summarizes the appraisal of fixed assets within a certain period. Including setting evaluation conditions and selecting evaluation units.F5Provision for impairmentThe mobile co-construction assets shall be accrued for impairment at the end of the year, and each unit shall adjust the depreciation reserves before the settlement of fixed assets at the end of the year (December 31). Reasons for changes in the template: co-construction assets are depreciated; the type of change is the adjustment for impairment allowances.
### 3.2.5. Asset Data Maintenance Management Function
The maintenance and management functions of asset data include asset changes, asset appraisals, asset impairments, asset splits, and asset consolidation operations. The asset data maintenance management function design is shown in Figure6 [21].Figure 6
Asset data maintenance function design.The specific description of asset data maintenance and management functions is shown in Table5.Table 5
Detailed description of asset data maintenance and management functions.
NumberingAction nameFunction descriptionF1Asset changesUsing the asset change document, you can realize the addition of card number, net value, net amount, provision for impairment, monthly depreciation amount, monthly depreciation rate, accrued month, currency, start date of use, depreciation auxiliary exchange rate, unit depreciation, depreciation exchange rate, cumulative workload, monthly workload, and trace changes of all other card items outside the multi-use department.F2_Asset valuationThe asset assessment function of this system is to provide assessable assets including original value, accumulated depreciation, net value, total work, service life, and net residual value rate. It mainly includes selecting assets to be assessed, defining formulas and production valuation data, manually entering and modifying valuation data, and making valuation sheets.Asset impairmentIf the assets of the enterprise have actually been impaired, provision for impairment should be made. Specifically, it includes adding an impairment provision document, selecting assets to be depreciated, creating an impairment provision document, modifying an impairment provision document, and querying an impairment provision document.Asset splitIn the asset split interface, click the “add” button, enter the “split card no.” in the header to bring out the corresponding data of the split card, and the table body will be split through operations such as “add row” and “delete row.” The number and amount of divided cards are divided into asset cards in different meter bodies. It includes adding split orders, cancelling asset splits, reviewing split orders, executing asset splits, modifying split orders, and making balance adjustments.Asset consolidationAsset merging is implemented through document templates. The first line of the document table body is merged into the main card, and most of the items that form a new card after merging are consistent with this card. Therefore, before merging assets, you need to select the main card to be merged. The purpose is to save follow-up = workload.
## 3.2.1. Financial Management Function of SMEs
The SME account management functions include financial card management operations, SME asset addition operations, general ledger management operations, and subsidiary ledger management operations. The design of the financial management function module of SMEs is shown in Figure2 [17] and Table 1.Figure 2
Financial management functional modules of small- and medium-sized enterprises including a detailed description of the functional modules of SME financial management.Table 1
Detailed description of financial management functions of small- and medium-sized enterprises.
NumberingAction nameFunction descriptionF1Financial card managementFinancial card management is the comprehensive management of system cards. Including adding, modifying, querying, deleting, and printing financial cards.F2Corporate finances increaseMainly complete the functions of adding, saving, modifying, deleting, locating, and copying financial cards of newly added fixed assets and deferred assets. When “assets are added,” the system automatically pops up a window for adding assets: you can add, modify, delete, and copy asset cards. Copying is a quick way to input multiple cards with similar card content when inputting.F3Financial ledger managementIn the process of fixed asset management, it is necessary to grasp the statistics, summary, and other information of assets in a timely manner. The main operations of general ledger management include setting common query conditions, selecting query units, and displaying impairment reserves.F4Financial ledger managementA subsidiary ledger is an account book used to classify and register detailed changes in assets within a certain period. Its main operations include setting common query conditions, selecting query units, displaying impairment reserves, displaying usage status and departments, displaying voucher numbers, displaying other card items, and printing detailed ledgers.
## 3.2.2. Asset Inventory Management Function
Asset inventory management mainly includes asset inventory, inventory surplus assets, inventory difference adjustment, multiaccount book management, change order management, and other major operations. Figure3 shows the design of the asset inventory management function [18].Figure 3
Asset inventory management function design.The detailed description of the SME asset inventory management function is shown in Table2.Table 2
Detailed description of asset inventory management functions.
NumberingAction nameFunction descriptionF1Property assessmentThe business documents for asset count are processed here, and document maintenance and approval are performed. The inventory function only supports the information of the inventory business, and the generated reduction document and difference adjustment document are all documents under the business account book.F2Profitable assetsDocuments for inventory surplus assets are automatically generated by the system based on the final inventory check-list after review. The subledger is an inventory difference for classifying and registering the detailed changes of assets within a certain period.F3Inventory difference adjustmentThe adjustment sheet is automatically generated from the non-conforming assets after the inventory is reviewed. In the account book query, add a query “asset account book” button, and use this button to select the desiredF4Multi-book managementQuestion data. Account books must be chosen independently; the default is the primary record book, which upholds the multibranch question of one record book. Change request from the executives is the complete administration of progress orders made by the framework. Predominantly incorporate requestsF5Change order managementChange order, joint check asset card, and joint check specific change order.
## 3.2.3. Asset Allocation Management Function
The management functions of asset transfer are mainly operations such as asset transfer, asset transfer, asset reduction, moving joint construction assets, and asset depreciation adjustment. The design of the asset allocation management function is shown in Figure4 [19].Figure 4
Design of asset allocation management function.The specific description of the asset allocation management function is shown in Table3.Table 3
Asset allocation management function specific description table.
NumberingAction nameFunction descriptionF1Asset call outThe approval of the transfer of assets is mainly to complete the maintenance and approval of the transfer of fixed assets among the enterprises within the group. It mainly includes adding an approval document, modifying an approval document, reviewing an approval document, a card for a joint investigation and issuing a document, and transferring assets.F2Asset transferAsset transfer approval mainly completes the maintenance and approval of transferred fixed assets among the enterprises within the group. It mainly includes modifying the transfer approval document, approval document, and asset transfer.F3Assets decreaseAsset reduction processing is different from asset card deletion: card deletion means that in the month of card entry, the card entry error is found, and the card information is completely removed from the system. It mainly includes cards for adding asset reduction documents, modifying asset reduction documents, deleting asset reduction documents, reviewing asset reduction documents, performing asset reduction, querying asset reduction documents, and checking asset reduction documents jointly.F4Mobile co-construction assetsAccording to the original value of fixed assets, impairment provision, and accumulated depreciation derived from the mobile ERP system, a mobile co-constructed fixed asset card is formed. The business attributes of the card such as asset name, storage location, user department, management department, and user must be lost. Attributes can be set according to the actual situation and imported after forming the fixed asset card ledger of mobile joint construction assets.F5Asset depreciation adjustmentAfter the mobile joint asset card is added, the system does not accrue depreciation. By synchronizing the depreciation accrued in each period of the mobile ERP system to the enterprise asset management system through the adjustment of accumulated depreciation. The adjustment of asset depreciation mainly includes adjustment to increase the original value of assets, adjustment of asset depreciation, and provision for impairment.
## 3.2.4. Asset Depreciation and Write-Off Function
Asset depreciation and write-off mainly include operations such as asset depreciation and amortization, detailed depreciation calculation table, departmental depreciation summary table, asset depreciation adjustment, and provision for impairment. The asset depreciation and write-off function design are shown in Figure5 [20].Figure 5
Asset depreciation and write-off management function design.The detailed description of asset depreciation and write-off management functions is shown in Table4.Table 4
Detailed description of asset depreciation and write-off management functions.
<!—Col Count:3 NumberingAction nameFunction descriptionF1Depreciation and amortization of assetsThe list of depreciation amounts for all assets accrued for depreciation displayed in the depreciation list. The depreciation list for a single period lists the card number, asset name, original accrued value, asset number, accumulated depreciation, monthly depreciation, and monthly depreciation. Rate, unit depreciation, monthly workload, and cumulative workload information. It mainly includes accruing depreciation, querying depreciation list, modifying depreciation list, querying depreciation allocation summary table, and filtering depreciation list.F2Depreciation calculation scheduleThe detailed list of depreciation calculation of fixed assets is a detailed list of the original value accrued in the previous month, the depreciation accrued in the previous month, the increase or decrease of the original value in the previous month, the original value accrued in this month, and the depreciation accrual in this month according to the specified classification, including setting up depreciation schedule query, unit query, detail (summary) query, and depreciation calculation schedule.F3Departmental depreciation summaryAlthough each fixed-capital card has a management department, a user department, and a depreciation bearing department, the depreciation allocation will eventually be carried out according to the department pointed by the depreciation bearing department, that is, the depreciation of each asset will eventually be allocated to the department pointed by the bearing department. In this table, the displayed department refers to the department to which the depreciation charge will eventually be allocated. For example, if an asset management department is the finance department, the user department is the administration department, and the depreciation undertaking department is the user department, the information found in this table is the depreciation information undertaken by the administration department; the administration department refers to the depreciation undertaking department.F4Asset depreciation assessmentThe asset evaluation summary sheet is an account sheet that categorizes and summarizes the appraisal of fixed assets within a certain period. Including setting evaluation conditions and selecting evaluation units.F5Provision for impairmentThe mobile co-construction assets shall be accrued for impairment at the end of the year, and each unit shall adjust the depreciation reserves before the settlement of fixed assets at the end of the year (December 31). Reasons for changes in the template: co-construction assets are depreciated; the type of change is the adjustment for impairment allowances.
## 3.2.5. Asset Data Maintenance Management Function
The maintenance and management functions of asset data include asset changes, asset appraisals, asset impairments, asset splits, and asset consolidation operations. The asset data maintenance management function design is shown in Figure6 [21].Figure 6
Asset data maintenance function design.The specific description of asset data maintenance and management functions is shown in Table5.Table 5
Detailed description of asset data maintenance and management functions.
NumberingAction nameFunction descriptionF1Asset changesUsing the asset change document, you can realize the addition of card number, net value, net amount, provision for impairment, monthly depreciation amount, monthly depreciation rate, accrued month, currency, start date of use, depreciation auxiliary exchange rate, unit depreciation, depreciation exchange rate, cumulative workload, monthly workload, and trace changes of all other card items outside the multi-use department.F2_Asset valuationThe asset assessment function of this system is to provide assessable assets including original value, accumulated depreciation, net value, total work, service life, and net residual value rate. It mainly includes selecting assets to be assessed, defining formulas and production valuation data, manually entering and modifying valuation data, and making valuation sheets.Asset impairmentIf the assets of the enterprise have actually been impaired, provision for impairment should be made. Specifically, it includes adding an impairment provision document, selecting assets to be depreciated, creating an impairment provision document, modifying an impairment provision document, and querying an impairment provision document.Asset splitIn the asset split interface, click the “add” button, enter the “split card no.” in the header to bring out the corresponding data of the split card, and the table body will be split through operations such as “add row” and “delete row.” The number and amount of divided cards are divided into asset cards in different meter bodies. It includes adding split orders, cancelling asset splits, reviewing split orders, executing asset splits, modifying split orders, and making balance adjustments.Asset consolidationAsset merging is implemented through document templates. The first line of the document table body is merged into the main card, and most of the items that form a new card after merging are consistent with this card. Therefore, before merging assets, you need to select the main card to be merged. The purpose is to save follow-up = workload.
## 3.3. Database Design of Cost Accounting and the Control System
### 3.3.1. Conceptual Structure Design
The SME financial analysis system based on data mining is mainly aimed at leaders or investment elites in the fields of SME financial management, SME management, financial analysis, and so on, such as SME leaders, financial department managers, financial analysts, and investors [22]:(1)
SME entity attributes include SME code, SME name, SME legal person, SME address, contact person, contact number, registered capital, SME attributes, industry, social unified credit code, business Scope, activity area, business supervisory unit, whether it has subordinate departments, number of departments, issuing authority, issuing date, registration date, and remarks(2)
Department entity attributes include department code, department name, department abbreviation, display order, department attribute, auxiliary login, department type, establishment time, inventory organization, department level, telephone, superior department, department head, whether for retail, address, and notes(3)
Customer entity attributes include customer code, customer name, customer abbreviation, foreign language name, industry, whether it is a retail investor, whether it is a DRP node, whether it is a channel member, unit address, contact person, contact number, region, customer person in charge, head office code of the merchant, type of merchant, corresponding department, region, taxpayer registration number, registered capital, economic type, legal person, price group, and remarks(4)
Cash account attributes include account code, account name, mnemonic code, account opening company, currency, account opening date, contact person, contact number, account status, sealing date, account cancellation date, whether the minimum balance is controlled, minimum balance, minimum balance control scheme, whether maximum balance control, maximum balance, maximum balance control scheme, and remarks(5)
Item attributes of financial documents include document number, document status, card code, account code, account name, account type, specification model, management department, user department, start time, service life, and withdrawal month, original value in original currency, original value in local currency, accumulated depreciation, net value, provision for impairment, net amount, net residual value, reduction method, and remarks(6)
Budget report credits incorporate monetary number, monetary classification, division, utilizing division, money, subordinate, move date, approaching sum, account balance, business archive number, voucher number, outline, input charge, current month to month affirmation of record section, account status, account move, account type, administrator, whether to make a record, and comments(7)
Data credits of SME representatives incorporate worker number, name, ID number, work number, orientation, date of birth, kind of work, division, marriage, personal residence, bank card number, account opening bank, section time, working years, whether it is an extraordinary sort of work, rank, and comments
### 3.3.2. Logic Structure Design
The financial analysis system based on data mining mainly includes seven data tables, which are SME entity attribute table, department entity attribute table, customer entity attribute table, cash account attribute table, financial document item attribute table, financial statement attribute table, small- and medium-sized enterprise attribute table, and employee information attribute table [23].
## 3.3.1. Conceptual Structure Design
The SME financial analysis system based on data mining is mainly aimed at leaders or investment elites in the fields of SME financial management, SME management, financial analysis, and so on, such as SME leaders, financial department managers, financial analysts, and investors [22]:(1)
SME entity attributes include SME code, SME name, SME legal person, SME address, contact person, contact number, registered capital, SME attributes, industry, social unified credit code, business Scope, activity area, business supervisory unit, whether it has subordinate departments, number of departments, issuing authority, issuing date, registration date, and remarks(2)
Department entity attributes include department code, department name, department abbreviation, display order, department attribute, auxiliary login, department type, establishment time, inventory organization, department level, telephone, superior department, department head, whether for retail, address, and notes(3)
Customer entity attributes include customer code, customer name, customer abbreviation, foreign language name, industry, whether it is a retail investor, whether it is a DRP node, whether it is a channel member, unit address, contact person, contact number, region, customer person in charge, head office code of the merchant, type of merchant, corresponding department, region, taxpayer registration number, registered capital, economic type, legal person, price group, and remarks(4)
Cash account attributes include account code, account name, mnemonic code, account opening company, currency, account opening date, contact person, contact number, account status, sealing date, account cancellation date, whether the minimum balance is controlled, minimum balance, minimum balance control scheme, whether maximum balance control, maximum balance, maximum balance control scheme, and remarks(5)
Item attributes of financial documents include document number, document status, card code, account code, account name, account type, specification model, management department, user department, start time, service life, and withdrawal month, original value in original currency, original value in local currency, accumulated depreciation, net value, provision for impairment, net amount, net residual value, reduction method, and remarks(6)
Budget report credits incorporate monetary number, monetary classification, division, utilizing division, money, subordinate, move date, approaching sum, account balance, business archive number, voucher number, outline, input charge, current month to month affirmation of record section, account status, account move, account type, administrator, whether to make a record, and comments(7)
Data credits of SME representatives incorporate worker number, name, ID number, work number, orientation, date of birth, kind of work, division, marriage, personal residence, bank card number, account opening bank, section time, working years, whether it is an extraordinary sort of work, rank, and comments
## 3.3.2. Logic Structure Design
The financial analysis system based on data mining mainly includes seven data tables, which are SME entity attribute table, department entity attribute table, customer entity attribute table, cash account attribute table, financial document item attribute table, financial statement attribute table, small- and medium-sized enterprise attribute table, and employee information attribute table [23].
## 4. Realization of Financial Cost Accounting and the Control System Based on Data Mining Technology
The chapter on the realization and testing of the financial analysis system based on data mining is also an important part of the realization of each function in the software engineering development process. This research will combine the clustering algorithm commonly used in data mining technology to analyze a large amount of financial data and mine potential, important, and valuable financial data information from it, as shown in Figure7.Figure 7
Structure diagram of financial analysis system components.As per the ongoing improvement of monetary information of small- and medium-sized ventures, the utilization of customary succeed tables and information insights programming can help in understanding the rundown of monetary information and the examination and investigation of general monetary information. With the consistent extension of SMEs, the monetary information of small- and medium-sized ventures has turned into a remarkable development strategy and it is as yet expanding. Different monetary information is created and gathered. With the rising consciousness of data innovation among pioneers and monetary directors of small- and medium-sized undertakings, they are anxious to find a few regulations that are helpful to the improvement of small- and medium-sized ventures from the monetary information produced by small- and medium-sized endeavors for a long time. Be that as it may, to understand the powerful examination of a lot of monetary information, the related programming instruments should be utilized to understand the fast and viable investigation of the monetary information and to find the secret significant information data rapidly.This examination accepts and dissects the monetary information created by the small- and medium-sized endeavors in the one-year creation and activity process. Through measurable examination, around 14,000 bits of monetary information in the one-year creation and activity exercises of the small- and medium-sized undertakings are obtained. Thusly, the size of information investigation acknowledged by this monetary examination framework is at the 10,000-digit level. Obviously, with the quick and inside and out improvement of information mining innovation, the size of information investigation generally arrives at the degree of 100,000 or 1,000,000 (M). Obviously, the monetary examination framework is a long way from the ongoing degree of 100,000 or 1,000,000 (M) in the information mining process. Thus, somewhat, the all-inclusiveness of information investigation and information mining has specific constraints. In the subsequent examination work, this paper will lead top to bottom check and exploration on the monetary examination framework in blend with a bigger information level, to work on the presentation and productivity of the monetary examination framework [24].
### 4.1. SME Case Selection
This examination takes grain creation undertakings as an illustration to do related research work regarding the matter. Among the numerous assortments of grain, this study centers around examining the monetary information circumstance during the time spent in grain creation undertakings. The examination in this paper is that the first information comes from the yearly monetary information and fiscal reports of small- and medium-sized undertakings distributed by the Grain and Oil Affiliation and different divisions. In the wake of summing up the accounting reports of the above grain ventures, the general monetary record of grain creation undertakings in Xinjiang is shaped. Simultaneously, the totaled information sheets are placed into the SQL Server 2008 data set and broke down involving the examination administration in the OLAP device, shaping into a time-sensitive report.
### 4.2. Algorithm Selection and Application
This study will direct bunch investigation on the monetary information of the above-chosen small- and medium-sized grain creation ventures. For the most part, the monetary status of an organization can be by and large isolated into four sorts: great monetary status (A), great monetary status (B), normal monetary status (C), and poor monetary status (D). In the group examination process in this segment, the circulation bunching apparatus in MATLAB programming is utilized to understand the monetary group investigation of grain endeavors. The means of the examination are displayed in Figure 8.Figure 8
Cluster analysis process.Through programming with MATLAB software, the operation results are obtained. In this paper, the data is directly converted into a columnar graph, as shown in Figure9.Figure 9
Cluster analysis results.According to the above cluster analysis results, among the selected small- and medium-sized grain production enterprises, 1 enterprise has a good financial status of A-type enterprise, which isM23; a total of 3 enterprises has a good financial status of B-type enterprises, which are M1, M4, and M10; a total of 3 enterprises whose financial status is general C-type enterprises, namely, M2, M8, and M15; M20 and M25, two grain production enterprises, whose financial status is poor, belong to D category.
## 4.1. SME Case Selection
This examination takes grain creation undertakings as an illustration to do related research work regarding the matter. Among the numerous assortments of grain, this study centers around examining the monetary information circumstance during the time spent in grain creation undertakings. The examination in this paper is that the first information comes from the yearly monetary information and fiscal reports of small- and medium-sized undertakings distributed by the Grain and Oil Affiliation and different divisions. In the wake of summing up the accounting reports of the above grain ventures, the general monetary record of grain creation undertakings in Xinjiang is shaped. Simultaneously, the totaled information sheets are placed into the SQL Server 2008 data set and broke down involving the examination administration in the OLAP device, shaping into a time-sensitive report.
## 4.2. Algorithm Selection and Application
This study will direct bunch investigation on the monetary information of the above-chosen small- and medium-sized grain creation ventures. For the most part, the monetary status of an organization can be by and large isolated into four sorts: great monetary status (A), great monetary status (B), normal monetary status (C), and poor monetary status (D). In the group examination process in this segment, the circulation bunching apparatus in MATLAB programming is utilized to understand the monetary group investigation of grain endeavors. The means of the examination are displayed in Figure 8.Figure 8
Cluster analysis process.Through programming with MATLAB software, the operation results are obtained. In this paper, the data is directly converted into a columnar graph, as shown in Figure9.Figure 9
Cluster analysis results.According to the above cluster analysis results, among the selected small- and medium-sized grain production enterprises, 1 enterprise has a good financial status of A-type enterprise, which isM23; a total of 3 enterprises has a good financial status of B-type enterprises, which are M1, M4, and M10; a total of 3 enterprises whose financial status is general C-type enterprises, namely, M2, M8, and M15; M20 and M25, two grain production enterprises, whose financial status is poor, belong to D category.
## 5. Conclusion
This examination breaks down the utilization of facts mining innovation in huge commercial enterprise financial examination framework and plans and executes a financial examination framework in view of data digging for the variables like lengthy haul disposing of and forgetting of economic records of a particular venture. This study elucidates the examination basis of the challenge in view of statistics mining innovation and recommends that the use of statistics mining innovation to the examination of massive enterprise economic facts has imperative well worth and exhibits importance. In the sketch phase of the economic examination framework, the objectives and requirements of the framework configuration are clarified, the engineering format of the framework is shown, and the specific factors of the economic investigation framework and the facts set layout ideas are defined in realistic modules. At last, through the economic statistics of the selected small- and medium-sized grain introduction endeavors, joined with the bunching calculation and aggregate, the financial popularity of the above grain advent undertakings is dissected, and the future enhancement layout of the project and the impact on the task are outwardly proven as exceptional graphs. The internal variables of extra enhancement provide a stable dynamic premise to enterprise pioneers and journey monetary backers.
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*Source: 2901167-2022-10-12.xml* | 2901167-2022-10-12_2901167-2022-10-12.md | 79,503 | Research on Financial Cost Accounting and Control of Small- and Medium-Sized Enterprises under the Background of Data Mining | Wenyan Wang | Computational Intelligence and Neuroscience
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2901167 | 2901167-2022-10-12.xml | ---
## Abstract
In the time of data blast and the ascent of the Web, the dramatic development of information and the data needs of small- and medium-sized endeavors affect the customary expense of the executives. Instructions to all the more likely mine viable data in information to give effective ways and technique merits considering. As the center innovation of handling enormous information, information mining can deal with a lot of mind-boggling information effectively. Accordingly, this paper talks about the cycle and technique for applying information mining at the expense of the executives of small- and medium-sized endeavors, to work on the seriousness of small- and medium-sized undertakings. This examination depends on the exploration and examination of the monetary information of small- and medium-sized ventures, joined with information mining innovation, extricates and uses the immense monetary information produced in the day-to-day administration cycle of the monetary division of the small- and medium-sized undertakings, plans and executes an information mining-based monetary information examination of small- and medium-sized endeavors framework. Joined with programming plan thoughts, through fundamental interest exploration and examination and many benefits of the ongoing B/S design, it was chosen to utilize the Java programming language, MyEclipse11 programming apparatus, Microsoft SQL Server 2008 data set administration instrument, J2EE advancement stage, and the exemplary Apriori in information mining. Mining techniques, for example, affiliation rules, bunching calculations, and choice tree calculations, have completely dissected the monetary information of small- and medium-sized undertakings, naturally and dependably give monetary administration branches of small- and medium-sized endeavors and ranking directors of small- and medium-sized ventures with helpful monetary data, and can help small- and medium-sized endeavors. Business pioneers pursue speedy choices. The planned and executed monetary examination framework in light of information mining incorporates the fundamental elements of SME monetary administration, resource stock administration, resource designation of the board, resource deterioration and discount, resource information upkeep of the executives, and so on. Small- and medium-sized undertakings’ monetary administration framework is a mix of information mining innovation, programming innovation, and small- and medium-sized monetary administration. The effective, solid, and helpful way has further developed the center seriousness of small- and medium-sized undertakings partially and accomplished a definitive objective of the framework plan.
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## Body
## 1. Introduction
In the period of data blast, individuals have a more extensive scope of ways of getting data. Getting different required data from the Web has turned into the primary wellspring of data. Financial backers attempt to acquire significant data to give information backing to future speculation choices. Undertakings have collected a lot of information in activity and from the executives, and different monetary sites likewise distribute letters of major recorded organizations consistently. Chiefs need to examine this information and go with different choices. In spite of the fact that data frameworks are increasingly more generally utilized in the business of the executive exercises, how to productively look for helpful data is as yet a major issue for business supervisors. To settle on choices more sensible and powerful, supervisors need to specifically deal with enormous measures of information, which is likewise incredibly tedious. Mass data carries many pessimistic impacts on individuals, the most significant is that there is an excess of futile data, and extricating compelling information is troublesome. A lot of futile data will definitely influence the idealness of supervisors’ independent direction and will unavoidably cause data contortion. It is hard to separate viable data and will definitely prompt a significant expansion in administration costs. Undertakings critically need to direct inside and out investigation of gigantic monetary information to extricate possibly compelling data so that endeavors can utilize it. Is it conceivable to track down another strategy to rapidly handle a lot of boisterous and deficient information to mine valuable data, create powerful data to help independent direction, and deliberately produce a particular model, which undertaking supervisors can utilize just to What might be said about recreating genuine working outcomes? The boundless utilization of information mining innovation is to tackle such issues. Mining helpful data from gigantic information is the basic utilization of information mining innovation. Supervisors can utilize the mining results to lay out target models and afterward lay out a total arrangement of dynamic frameworks, which is valuable for directors to really control dynamic data and pursue the right choices, in order to work on the seriousness of ventures [1–8].Notwithstanding, the complicated issues achieved by information additionally bring new difficulties for SMEs. The first is the adjustment of the size of information. With the approach of the information period, SMEs should not just complete the assortment, arranging and examination of inside information of SMEs, yet additionally outside natural information, industry information, modern chain information, contender information, utilization information of SMEs. SMEs need to gather, distinguish, sort and store sensibly. The second is the difference in information types. Small- and medium-sized undertakings will create a lot of information during the time spent in creation and activity exercises, including organized information utilized for conventional monetary direction, as well as unstructured information that tremendously affects the monetary decision-production of SME partners’ information. Sensible capacity and use of unstructured information and the utilization of unstructured information to help monetary information in direction are the subsequent test brought by the information age. Obviously, traditional financial analysis methods have shown difficulty in meeting the decision-making needs of modern SMEs. In the process of financial analysis, data mining technology needs to be used reasonably to help SMEs meet the above challenges smoothly. So how to effectively combine data mining technology with financial analysis methods, how to complete the collection, sorting, and storage of huge data sets, and conduct reasonable screening, analysis, and research on these data, so that the value of the data can be brought into play, reflecting the valuable business information, and then help SME managers to make financial and strategic decisions that adapt to the development environment, make SMEs develop in the right direction, and improve the market competitiveness of SMEs is an urgent problem to be solved.
## 2. Related Work
With the quick advancement of Web innovation, PC applications, computerized reasoning, and other data innovations, data innovation has entered into varying backgrounds and furthermore includes all parts of individuals’ everyday creation and life. Endeavor monetary data development is no exemption. With the ceaseless expansion in the business field of endeavors, enormous medium and little undertakings, for example, state-claimed ventures, confidential undertakings, and global endeavors, are creating increasingly huge scope fiscal summary information consistently. The sporadic and outlandish administration of this monetary information has turned into a difficult issue that influences the typical improvement of corporate money. Notwithstanding, the monetary information board of certain endeavors actually stays at the degree of conventional succeed reports or independent administration programming, and, surprisingly, a few little undertakings actually hold the paper-based administration of corporate monetary information. These conventional and in-reverse administration techniques truly confine the speed of big business advancement. With the rising number of corporate monetary information, the utilization of data and deliberate administration of corporate monetary information has become one of the critical worries of corporate pioneers.Information mining arose in 1989. It is the study of finding regulations from tremendous informational collections. It incorporates a wide range of exploration fields and primarily brings about the bearing of data sets, measurements, AI, computerized reasoning, and so on. Utilizing “information mining” as the watchword to look on CNKI, beyond 140,000 related papers can be found. Information mining innovation is presently broadly utilized in designing, medication, financial matters, and different fields. Carlos fabricated a monetary choice emotionally supportive network for undertakings in view of the brain network model, and the framework takes monetary proportion file as the primary exploration object to give monetary information backing to corporate monetary direction. Through the brain network model, the effect of corporate monetary choices on pointers can be judged, and the related monetary choices can be chosen in light of the advancement assumptions for monetary markers. This paper centers around the use of brain network models in the monetary field and represents the reasonableness and adequacy of information mining innovation in the monetary field. Tae Kyung Sung utilizes the choice tree model in information mining innovation to complete the monetary examination of endeavors in various outer climates. This study utilizes the choice tree technique to create different monetary conjecture results when the outside conditions change, and the monetary gauge part is improved somewhat. Wang Qing laid out an information mining strategy in light of the dim framework hypothesis and joined with the information on monetary examination, to mine the current monetary information of recorded organizations. Through group examination, the relationship and similitude of corporate monetary pointers were mined, and the connection between monetary markers in a specific industry in a specific period was closed. Nonetheless, the ends drawn by this calculation might be impacted by the possibility of the information, and whether it very well may be utilized as a reason for monetary examination is as yet worth investigating. Cao Zhong accepts that monetary exercises are a significant piece of the financial exercises of endeavors, and the advancement of big business data should be planned with a monetary data framework as the center, with requirements to finish the assortment, handling, and criticism of information on time. Utilizing information mining innovation to manage the huge measure of data and quick handling pace can meet the plan prerequisites of the monetary data framework. Important data can be found from a lot of monetary information and ideal input can be finished. This study applies information mining innovation to the monetary examination framework and utilizes the benefits of information mining innovation to assist the framework with handling a lot of information and rapid criticism results, demonstrating that information mining innovation has high application esteem in the field of monetary investigation. In any case, this study accentuates the job of information mining innovation in information assortment and handling and has not been executed in unambiguous monetary examination and monetary direction. Gan Weiping accepts that according to the viewpoint of monetary examination, information mining innovation can assist its clients with rapidly acquiring important data and information. Through this innovation, undertaking business data can be immediately handled and the proficient transmission of inner data can be accomplished simultaneously. Assist undertakings with investigating expected markets and clients, and give dynamic premise to the executives' independent direction. Simultaneously, he additionally applied information mining innovation to showcasing different fields and added reasonable experience in information mining innovation. This study consolidates information mining innovation with business exercises, which gives an incredible premise to board navigation. It is the pattern of future exploration to utilize information digging to offer help for business navigation. Yu Cuijing and Qian Xiaojiang applied information mining innovation to the ERP board framework and accomplished good outcomes. Information mining innovation can actually engage the ERP framework and simultaneously complete the viable blend of the inward information of the ERP framework and the outer information of the venture, help the ERP framework to procure, process, and investigate the outside information of the undertaking, and further develop the ERP framework’s presentation. In this study, the information mining innovation is applied to the ERP board framework and has accomplished great outcomes, as yet profiting from the benefits of information mining innovation handling information in huge request and quick speed. Zhao Xuanyuan and Xue Jianlou take the country’s land industry as the exploration item and utilize the group investigation strategy to do a point-by-point bunch examination of corporate monetary markers to furnish financial backers with a dynamic premise. According to the point of view of financial backers, this study leads monetary examination and shows the application worth of information mining innovation. Cao Zhihua summed up the generally utilized information mining strategies, essentially including brain organizations, fluffy sets, and choice trees. He accepted that information mining innovation could not tackle the issues of conventional monetary investigation techniques assuming handling monetary data was just utilized. Future information mining innovation ought to make forward leaps from the two elements of information obtaining and examination objects. According to the point of view of information securing, information mining innovation is utilized to acquire unstructured information. The examination object point ought to be joined with nonmonetary information and unstructured information for joint investigation. Li Rongli accepts that information mining innovation enjoys the benefits of exhaustiveness and profundity, which is truly appropriate for big business monetary information investigation. She consolidated information mining innovation with corporate monetary investigation and developed a monetary examination model by utilizing information mining strategies based on symptomatic information obtained from general judgment and exceptional judgment. This study joins information mining techniques with the monetary examination hypothesis and utilizes bunching investigation, choice tree model, and other computational strategies to help the monetary investigation process, making the examination results more significant.From the above writing survey, it very well may be seen that the utilization of information mining innovation in the field of monetary examination has been moderately full grown, and researchers in our nation have likewise accomplished a great deal of results in the use of information mining in the field of monetary examination. An agreement has been reached according to the point of view of certain burdens of monetary examination. Later on, information mining innovation is not just utilized in information assortment and handling, yet in addition gives commonsense choice help to pertinent partners of undertakings according to the viewpoint of information mining results [9–15].
## 3. Construction of the Financial Cost Control System for Small and Medium Enterprises Based on Data Mining Technology
### 3.1. Cost Accounting and Control System Architecture Design
#### 3.1.1. Physical Architecture Design
The monetary examination framework in view of information mining is mostly planned and carried out in light of B/S engineering. The B/S design has numerous qualities, such as simple organization, simple upkeep, and client accommodation, and understands the detachment of the client side and the server side. Considering the significance and secrecy of the monetary information of small- and medium-sized ventures, the monetary examination framework to be created will be sent to the intranet and introduced in the neighborhood of small- and medium-sized undertakings and it can accomplish total actual separation from the outside network through the firewall and forestall the assault of unfamiliar unlawful gatecrashers.
#### 3.1.2. Software Architecture Design
The actual engineering configuration chart of the monetary investigation framework for small- and medium-sized endeavors in light of information mining predominantly incorporates the UI Layer (UIL), the Business Rationale Layer (BLL) that carries out client login and UI activities, and the information access layer. It understands the trade and shared calling of monetary information of small- and medium-sized endeavors. The information mining layer conducts inside and out mining and investigation of the monetary information of small- and medium-sized ventures to extricate possibly helpful worth data. The important part of the information foundation layer mainly includes dataset arrangement records and SQL Server 2008 dataset management device to ensure the validity of financial information of small and medium-sized enterprises. In Figure1, the product engineering configuration graph of the monetary examination framework for small- and medium-sized endeavors is given [16].Figure 1
Software architecture design diagram.
### 3.2. Design of Functional Modules of Cost Accounting and the Control System
#### 3.2.1. Financial Management Function of SMEs
The SME account management functions include financial card management operations, SME asset addition operations, general ledger management operations, and subsidiary ledger management operations. The design of the financial management function module of SMEs is shown in Figure2 [17] and Table 1.Figure 2
Financial management functional modules of small- and medium-sized enterprises including a detailed description of the functional modules of SME financial management.Table 1
Detailed description of financial management functions of small- and medium-sized enterprises.
NumberingAction nameFunction descriptionF1Financial card managementFinancial card management is the comprehensive management of system cards. Including adding, modifying, querying, deleting, and printing financial cards.F2Corporate finances increaseMainly complete the functions of adding, saving, modifying, deleting, locating, and copying financial cards of newly added fixed assets and deferred assets. When “assets are added,” the system automatically pops up a window for adding assets: you can add, modify, delete, and copy asset cards. Copying is a quick way to input multiple cards with similar card content when inputting.F3Financial ledger managementIn the process of fixed asset management, it is necessary to grasp the statistics, summary, and other information of assets in a timely manner. The main operations of general ledger management include setting common query conditions, selecting query units, and displaying impairment reserves.F4Financial ledger managementA subsidiary ledger is an account book used to classify and register detailed changes in assets within a certain period. Its main operations include setting common query conditions, selecting query units, displaying impairment reserves, displaying usage status and departments, displaying voucher numbers, displaying other card items, and printing detailed ledgers.
#### 3.2.2. Asset Inventory Management Function
Asset inventory management mainly includes asset inventory, inventory surplus assets, inventory difference adjustment, multiaccount book management, change order management, and other major operations. Figure3 shows the design of the asset inventory management function [18].Figure 3
Asset inventory management function design.The detailed description of the SME asset inventory management function is shown in Table2.Table 2
Detailed description of asset inventory management functions.
NumberingAction nameFunction descriptionF1Property assessmentThe business documents for asset count are processed here, and document maintenance and approval are performed. The inventory function only supports the information of the inventory business, and the generated reduction document and difference adjustment document are all documents under the business account book.F2Profitable assetsDocuments for inventory surplus assets are automatically generated by the system based on the final inventory check-list after review. The subledger is an inventory difference for classifying and registering the detailed changes of assets within a certain period.F3Inventory difference adjustmentThe adjustment sheet is automatically generated from the non-conforming assets after the inventory is reviewed. In the account book query, add a query “asset account book” button, and use this button to select the desiredF4Multi-book managementQuestion data. Account books must be chosen independently; the default is the primary record book, which upholds the multibranch question of one record book. Change request from the executives is the complete administration of progress orders made by the framework. Predominantly incorporate requestsF5Change order managementChange order, joint check asset card, and joint check specific change order.
#### 3.2.3. Asset Allocation Management Function
The management functions of asset transfer are mainly operations such as asset transfer, asset transfer, asset reduction, moving joint construction assets, and asset depreciation adjustment. The design of the asset allocation management function is shown in Figure4 [19].Figure 4
Design of asset allocation management function.The specific description of the asset allocation management function is shown in Table3.Table 3
Asset allocation management function specific description table.
NumberingAction nameFunction descriptionF1Asset call outThe approval of the transfer of assets is mainly to complete the maintenance and approval of the transfer of fixed assets among the enterprises within the group. It mainly includes adding an approval document, modifying an approval document, reviewing an approval document, a card for a joint investigation and issuing a document, and transferring assets.F2Asset transferAsset transfer approval mainly completes the maintenance and approval of transferred fixed assets among the enterprises within the group. It mainly includes modifying the transfer approval document, approval document, and asset transfer.F3Assets decreaseAsset reduction processing is different from asset card deletion: card deletion means that in the month of card entry, the card entry error is found, and the card information is completely removed from the system. It mainly includes cards for adding asset reduction documents, modifying asset reduction documents, deleting asset reduction documents, reviewing asset reduction documents, performing asset reduction, querying asset reduction documents, and checking asset reduction documents jointly.F4Mobile co-construction assetsAccording to the original value of fixed assets, impairment provision, and accumulated depreciation derived from the mobile ERP system, a mobile co-constructed fixed asset card is formed. The business attributes of the card such as asset name, storage location, user department, management department, and user must be lost. Attributes can be set according to the actual situation and imported after forming the fixed asset card ledger of mobile joint construction assets.F5Asset depreciation adjustmentAfter the mobile joint asset card is added, the system does not accrue depreciation. By synchronizing the depreciation accrued in each period of the mobile ERP system to the enterprise asset management system through the adjustment of accumulated depreciation. The adjustment of asset depreciation mainly includes adjustment to increase the original value of assets, adjustment of asset depreciation, and provision for impairment.
#### 3.2.4. Asset Depreciation and Write-Off Function
Asset depreciation and write-off mainly include operations such as asset depreciation and amortization, detailed depreciation calculation table, departmental depreciation summary table, asset depreciation adjustment, and provision for impairment. The asset depreciation and write-off function design are shown in Figure5 [20].Figure 5
Asset depreciation and write-off management function design.The detailed description of asset depreciation and write-off management functions is shown in Table4.Table 4
Detailed description of asset depreciation and write-off management functions.
<!—Col Count:3 NumberingAction nameFunction descriptionF1Depreciation and amortization of assetsThe list of depreciation amounts for all assets accrued for depreciation displayed in the depreciation list. The depreciation list for a single period lists the card number, asset name, original accrued value, asset number, accumulated depreciation, monthly depreciation, and monthly depreciation. Rate, unit depreciation, monthly workload, and cumulative workload information. It mainly includes accruing depreciation, querying depreciation list, modifying depreciation list, querying depreciation allocation summary table, and filtering depreciation list.F2Depreciation calculation scheduleThe detailed list of depreciation calculation of fixed assets is a detailed list of the original value accrued in the previous month, the depreciation accrued in the previous month, the increase or decrease of the original value in the previous month, the original value accrued in this month, and the depreciation accrual in this month according to the specified classification, including setting up depreciation schedule query, unit query, detail (summary) query, and depreciation calculation schedule.F3Departmental depreciation summaryAlthough each fixed-capital card has a management department, a user department, and a depreciation bearing department, the depreciation allocation will eventually be carried out according to the department pointed by the depreciation bearing department, that is, the depreciation of each asset will eventually be allocated to the department pointed by the bearing department. In this table, the displayed department refers to the department to which the depreciation charge will eventually be allocated. For example, if an asset management department is the finance department, the user department is the administration department, and the depreciation undertaking department is the user department, the information found in this table is the depreciation information undertaken by the administration department; the administration department refers to the depreciation undertaking department.F4Asset depreciation assessmentThe asset evaluation summary sheet is an account sheet that categorizes and summarizes the appraisal of fixed assets within a certain period. Including setting evaluation conditions and selecting evaluation units.F5Provision for impairmentThe mobile co-construction assets shall be accrued for impairment at the end of the year, and each unit shall adjust the depreciation reserves before the settlement of fixed assets at the end of the year (December 31). Reasons for changes in the template: co-construction assets are depreciated; the type of change is the adjustment for impairment allowances.
#### 3.2.5. Asset Data Maintenance Management Function
The maintenance and management functions of asset data include asset changes, asset appraisals, asset impairments, asset splits, and asset consolidation operations. The asset data maintenance management function design is shown in Figure6 [21].Figure 6
Asset data maintenance function design.The specific description of asset data maintenance and management functions is shown in Table5.Table 5
Detailed description of asset data maintenance and management functions.
NumberingAction nameFunction descriptionF1Asset changesUsing the asset change document, you can realize the addition of card number, net value, net amount, provision for impairment, monthly depreciation amount, monthly depreciation rate, accrued month, currency, start date of use, depreciation auxiliary exchange rate, unit depreciation, depreciation exchange rate, cumulative workload, monthly workload, and trace changes of all other card items outside the multi-use department.F2_Asset valuationThe asset assessment function of this system is to provide assessable assets including original value, accumulated depreciation, net value, total work, service life, and net residual value rate. It mainly includes selecting assets to be assessed, defining formulas and production valuation data, manually entering and modifying valuation data, and making valuation sheets.Asset impairmentIf the assets of the enterprise have actually been impaired, provision for impairment should be made. Specifically, it includes adding an impairment provision document, selecting assets to be depreciated, creating an impairment provision document, modifying an impairment provision document, and querying an impairment provision document.Asset splitIn the asset split interface, click the “add” button, enter the “split card no.” in the header to bring out the corresponding data of the split card, and the table body will be split through operations such as “add row” and “delete row.” The number and amount of divided cards are divided into asset cards in different meter bodies. It includes adding split orders, cancelling asset splits, reviewing split orders, executing asset splits, modifying split orders, and making balance adjustments.Asset consolidationAsset merging is implemented through document templates. The first line of the document table body is merged into the main card, and most of the items that form a new card after merging are consistent with this card. Therefore, before merging assets, you need to select the main card to be merged. The purpose is to save follow-up = workload.
### 3.3. Database Design of Cost Accounting and the Control System
#### 3.3.1. Conceptual Structure Design
The SME financial analysis system based on data mining is mainly aimed at leaders or investment elites in the fields of SME financial management, SME management, financial analysis, and so on, such as SME leaders, financial department managers, financial analysts, and investors [22]:(1)
SME entity attributes include SME code, SME name, SME legal person, SME address, contact person, contact number, registered capital, SME attributes, industry, social unified credit code, business Scope, activity area, business supervisory unit, whether it has subordinate departments, number of departments, issuing authority, issuing date, registration date, and remarks(2)
Department entity attributes include department code, department name, department abbreviation, display order, department attribute, auxiliary login, department type, establishment time, inventory organization, department level, telephone, superior department, department head, whether for retail, address, and notes(3)
Customer entity attributes include customer code, customer name, customer abbreviation, foreign language name, industry, whether it is a retail investor, whether it is a DRP node, whether it is a channel member, unit address, contact person, contact number, region, customer person in charge, head office code of the merchant, type of merchant, corresponding department, region, taxpayer registration number, registered capital, economic type, legal person, price group, and remarks(4)
Cash account attributes include account code, account name, mnemonic code, account opening company, currency, account opening date, contact person, contact number, account status, sealing date, account cancellation date, whether the minimum balance is controlled, minimum balance, minimum balance control scheme, whether maximum balance control, maximum balance, maximum balance control scheme, and remarks(5)
Item attributes of financial documents include document number, document status, card code, account code, account name, account type, specification model, management department, user department, start time, service life, and withdrawal month, original value in original currency, original value in local currency, accumulated depreciation, net value, provision for impairment, net amount, net residual value, reduction method, and remarks(6)
Budget report credits incorporate monetary number, monetary classification, division, utilizing division, money, subordinate, move date, approaching sum, account balance, business archive number, voucher number, outline, input charge, current month to month affirmation of record section, account status, account move, account type, administrator, whether to make a record, and comments(7)
Data credits of SME representatives incorporate worker number, name, ID number, work number, orientation, date of birth, kind of work, division, marriage, personal residence, bank card number, account opening bank, section time, working years, whether it is an extraordinary sort of work, rank, and comments
#### 3.3.2. Logic Structure Design
The financial analysis system based on data mining mainly includes seven data tables, which are SME entity attribute table, department entity attribute table, customer entity attribute table, cash account attribute table, financial document item attribute table, financial statement attribute table, small- and medium-sized enterprise attribute table, and employee information attribute table [23].
## 3.1. Cost Accounting and Control System Architecture Design
### 3.1.1. Physical Architecture Design
The monetary examination framework in view of information mining is mostly planned and carried out in light of B/S engineering. The B/S design has numerous qualities, such as simple organization, simple upkeep, and client accommodation, and understands the detachment of the client side and the server side. Considering the significance and secrecy of the monetary information of small- and medium-sized ventures, the monetary examination framework to be created will be sent to the intranet and introduced in the neighborhood of small- and medium-sized undertakings and it can accomplish total actual separation from the outside network through the firewall and forestall the assault of unfamiliar unlawful gatecrashers.
### 3.1.2. Software Architecture Design
The actual engineering configuration chart of the monetary investigation framework for small- and medium-sized endeavors in light of information mining predominantly incorporates the UI Layer (UIL), the Business Rationale Layer (BLL) that carries out client login and UI activities, and the information access layer. It understands the trade and shared calling of monetary information of small- and medium-sized endeavors. The information mining layer conducts inside and out mining and investigation of the monetary information of small- and medium-sized ventures to extricate possibly helpful worth data. The important part of the information foundation layer mainly includes dataset arrangement records and SQL Server 2008 dataset management device to ensure the validity of financial information of small and medium-sized enterprises. In Figure1, the product engineering configuration graph of the monetary examination framework for small- and medium-sized endeavors is given [16].Figure 1
Software architecture design diagram.
## 3.1.1. Physical Architecture Design
The monetary examination framework in view of information mining is mostly planned and carried out in light of B/S engineering. The B/S design has numerous qualities, such as simple organization, simple upkeep, and client accommodation, and understands the detachment of the client side and the server side. Considering the significance and secrecy of the monetary information of small- and medium-sized ventures, the monetary examination framework to be created will be sent to the intranet and introduced in the neighborhood of small- and medium-sized undertakings and it can accomplish total actual separation from the outside network through the firewall and forestall the assault of unfamiliar unlawful gatecrashers.
## 3.1.2. Software Architecture Design
The actual engineering configuration chart of the monetary investigation framework for small- and medium-sized endeavors in light of information mining predominantly incorporates the UI Layer (UIL), the Business Rationale Layer (BLL) that carries out client login and UI activities, and the information access layer. It understands the trade and shared calling of monetary information of small- and medium-sized endeavors. The information mining layer conducts inside and out mining and investigation of the monetary information of small- and medium-sized ventures to extricate possibly helpful worth data. The important part of the information foundation layer mainly includes dataset arrangement records and SQL Server 2008 dataset management device to ensure the validity of financial information of small and medium-sized enterprises. In Figure1, the product engineering configuration graph of the monetary examination framework for small- and medium-sized endeavors is given [16].Figure 1
Software architecture design diagram.
## 3.2. Design of Functional Modules of Cost Accounting and the Control System
### 3.2.1. Financial Management Function of SMEs
The SME account management functions include financial card management operations, SME asset addition operations, general ledger management operations, and subsidiary ledger management operations. The design of the financial management function module of SMEs is shown in Figure2 [17] and Table 1.Figure 2
Financial management functional modules of small- and medium-sized enterprises including a detailed description of the functional modules of SME financial management.Table 1
Detailed description of financial management functions of small- and medium-sized enterprises.
NumberingAction nameFunction descriptionF1Financial card managementFinancial card management is the comprehensive management of system cards. Including adding, modifying, querying, deleting, and printing financial cards.F2Corporate finances increaseMainly complete the functions of adding, saving, modifying, deleting, locating, and copying financial cards of newly added fixed assets and deferred assets. When “assets are added,” the system automatically pops up a window for adding assets: you can add, modify, delete, and copy asset cards. Copying is a quick way to input multiple cards with similar card content when inputting.F3Financial ledger managementIn the process of fixed asset management, it is necessary to grasp the statistics, summary, and other information of assets in a timely manner. The main operations of general ledger management include setting common query conditions, selecting query units, and displaying impairment reserves.F4Financial ledger managementA subsidiary ledger is an account book used to classify and register detailed changes in assets within a certain period. Its main operations include setting common query conditions, selecting query units, displaying impairment reserves, displaying usage status and departments, displaying voucher numbers, displaying other card items, and printing detailed ledgers.
### 3.2.2. Asset Inventory Management Function
Asset inventory management mainly includes asset inventory, inventory surplus assets, inventory difference adjustment, multiaccount book management, change order management, and other major operations. Figure3 shows the design of the asset inventory management function [18].Figure 3
Asset inventory management function design.The detailed description of the SME asset inventory management function is shown in Table2.Table 2
Detailed description of asset inventory management functions.
NumberingAction nameFunction descriptionF1Property assessmentThe business documents for asset count are processed here, and document maintenance and approval are performed. The inventory function only supports the information of the inventory business, and the generated reduction document and difference adjustment document are all documents under the business account book.F2Profitable assetsDocuments for inventory surplus assets are automatically generated by the system based on the final inventory check-list after review. The subledger is an inventory difference for classifying and registering the detailed changes of assets within a certain period.F3Inventory difference adjustmentThe adjustment sheet is automatically generated from the non-conforming assets after the inventory is reviewed. In the account book query, add a query “asset account book” button, and use this button to select the desiredF4Multi-book managementQuestion data. Account books must be chosen independently; the default is the primary record book, which upholds the multibranch question of one record book. Change request from the executives is the complete administration of progress orders made by the framework. Predominantly incorporate requestsF5Change order managementChange order, joint check asset card, and joint check specific change order.
### 3.2.3. Asset Allocation Management Function
The management functions of asset transfer are mainly operations such as asset transfer, asset transfer, asset reduction, moving joint construction assets, and asset depreciation adjustment. The design of the asset allocation management function is shown in Figure4 [19].Figure 4
Design of asset allocation management function.The specific description of the asset allocation management function is shown in Table3.Table 3
Asset allocation management function specific description table.
NumberingAction nameFunction descriptionF1Asset call outThe approval of the transfer of assets is mainly to complete the maintenance and approval of the transfer of fixed assets among the enterprises within the group. It mainly includes adding an approval document, modifying an approval document, reviewing an approval document, a card for a joint investigation and issuing a document, and transferring assets.F2Asset transferAsset transfer approval mainly completes the maintenance and approval of transferred fixed assets among the enterprises within the group. It mainly includes modifying the transfer approval document, approval document, and asset transfer.F3Assets decreaseAsset reduction processing is different from asset card deletion: card deletion means that in the month of card entry, the card entry error is found, and the card information is completely removed from the system. It mainly includes cards for adding asset reduction documents, modifying asset reduction documents, deleting asset reduction documents, reviewing asset reduction documents, performing asset reduction, querying asset reduction documents, and checking asset reduction documents jointly.F4Mobile co-construction assetsAccording to the original value of fixed assets, impairment provision, and accumulated depreciation derived from the mobile ERP system, a mobile co-constructed fixed asset card is formed. The business attributes of the card such as asset name, storage location, user department, management department, and user must be lost. Attributes can be set according to the actual situation and imported after forming the fixed asset card ledger of mobile joint construction assets.F5Asset depreciation adjustmentAfter the mobile joint asset card is added, the system does not accrue depreciation. By synchronizing the depreciation accrued in each period of the mobile ERP system to the enterprise asset management system through the adjustment of accumulated depreciation. The adjustment of asset depreciation mainly includes adjustment to increase the original value of assets, adjustment of asset depreciation, and provision for impairment.
### 3.2.4. Asset Depreciation and Write-Off Function
Asset depreciation and write-off mainly include operations such as asset depreciation and amortization, detailed depreciation calculation table, departmental depreciation summary table, asset depreciation adjustment, and provision for impairment. The asset depreciation and write-off function design are shown in Figure5 [20].Figure 5
Asset depreciation and write-off management function design.The detailed description of asset depreciation and write-off management functions is shown in Table4.Table 4
Detailed description of asset depreciation and write-off management functions.
<!—Col Count:3 NumberingAction nameFunction descriptionF1Depreciation and amortization of assetsThe list of depreciation amounts for all assets accrued for depreciation displayed in the depreciation list. The depreciation list for a single period lists the card number, asset name, original accrued value, asset number, accumulated depreciation, monthly depreciation, and monthly depreciation. Rate, unit depreciation, monthly workload, and cumulative workload information. It mainly includes accruing depreciation, querying depreciation list, modifying depreciation list, querying depreciation allocation summary table, and filtering depreciation list.F2Depreciation calculation scheduleThe detailed list of depreciation calculation of fixed assets is a detailed list of the original value accrued in the previous month, the depreciation accrued in the previous month, the increase or decrease of the original value in the previous month, the original value accrued in this month, and the depreciation accrual in this month according to the specified classification, including setting up depreciation schedule query, unit query, detail (summary) query, and depreciation calculation schedule.F3Departmental depreciation summaryAlthough each fixed-capital card has a management department, a user department, and a depreciation bearing department, the depreciation allocation will eventually be carried out according to the department pointed by the depreciation bearing department, that is, the depreciation of each asset will eventually be allocated to the department pointed by the bearing department. In this table, the displayed department refers to the department to which the depreciation charge will eventually be allocated. For example, if an asset management department is the finance department, the user department is the administration department, and the depreciation undertaking department is the user department, the information found in this table is the depreciation information undertaken by the administration department; the administration department refers to the depreciation undertaking department.F4Asset depreciation assessmentThe asset evaluation summary sheet is an account sheet that categorizes and summarizes the appraisal of fixed assets within a certain period. Including setting evaluation conditions and selecting evaluation units.F5Provision for impairmentThe mobile co-construction assets shall be accrued for impairment at the end of the year, and each unit shall adjust the depreciation reserves before the settlement of fixed assets at the end of the year (December 31). Reasons for changes in the template: co-construction assets are depreciated; the type of change is the adjustment for impairment allowances.
### 3.2.5. Asset Data Maintenance Management Function
The maintenance and management functions of asset data include asset changes, asset appraisals, asset impairments, asset splits, and asset consolidation operations. The asset data maintenance management function design is shown in Figure6 [21].Figure 6
Asset data maintenance function design.The specific description of asset data maintenance and management functions is shown in Table5.Table 5
Detailed description of asset data maintenance and management functions.
NumberingAction nameFunction descriptionF1Asset changesUsing the asset change document, you can realize the addition of card number, net value, net amount, provision for impairment, monthly depreciation amount, monthly depreciation rate, accrued month, currency, start date of use, depreciation auxiliary exchange rate, unit depreciation, depreciation exchange rate, cumulative workload, monthly workload, and trace changes of all other card items outside the multi-use department.F2_Asset valuationThe asset assessment function of this system is to provide assessable assets including original value, accumulated depreciation, net value, total work, service life, and net residual value rate. It mainly includes selecting assets to be assessed, defining formulas and production valuation data, manually entering and modifying valuation data, and making valuation sheets.Asset impairmentIf the assets of the enterprise have actually been impaired, provision for impairment should be made. Specifically, it includes adding an impairment provision document, selecting assets to be depreciated, creating an impairment provision document, modifying an impairment provision document, and querying an impairment provision document.Asset splitIn the asset split interface, click the “add” button, enter the “split card no.” in the header to bring out the corresponding data of the split card, and the table body will be split through operations such as “add row” and “delete row.” The number and amount of divided cards are divided into asset cards in different meter bodies. It includes adding split orders, cancelling asset splits, reviewing split orders, executing asset splits, modifying split orders, and making balance adjustments.Asset consolidationAsset merging is implemented through document templates. The first line of the document table body is merged into the main card, and most of the items that form a new card after merging are consistent with this card. Therefore, before merging assets, you need to select the main card to be merged. The purpose is to save follow-up = workload.
## 3.2.1. Financial Management Function of SMEs
The SME account management functions include financial card management operations, SME asset addition operations, general ledger management operations, and subsidiary ledger management operations. The design of the financial management function module of SMEs is shown in Figure2 [17] and Table 1.Figure 2
Financial management functional modules of small- and medium-sized enterprises including a detailed description of the functional modules of SME financial management.Table 1
Detailed description of financial management functions of small- and medium-sized enterprises.
NumberingAction nameFunction descriptionF1Financial card managementFinancial card management is the comprehensive management of system cards. Including adding, modifying, querying, deleting, and printing financial cards.F2Corporate finances increaseMainly complete the functions of adding, saving, modifying, deleting, locating, and copying financial cards of newly added fixed assets and deferred assets. When “assets are added,” the system automatically pops up a window for adding assets: you can add, modify, delete, and copy asset cards. Copying is a quick way to input multiple cards with similar card content when inputting.F3Financial ledger managementIn the process of fixed asset management, it is necessary to grasp the statistics, summary, and other information of assets in a timely manner. The main operations of general ledger management include setting common query conditions, selecting query units, and displaying impairment reserves.F4Financial ledger managementA subsidiary ledger is an account book used to classify and register detailed changes in assets within a certain period. Its main operations include setting common query conditions, selecting query units, displaying impairment reserves, displaying usage status and departments, displaying voucher numbers, displaying other card items, and printing detailed ledgers.
## 3.2.2. Asset Inventory Management Function
Asset inventory management mainly includes asset inventory, inventory surplus assets, inventory difference adjustment, multiaccount book management, change order management, and other major operations. Figure3 shows the design of the asset inventory management function [18].Figure 3
Asset inventory management function design.The detailed description of the SME asset inventory management function is shown in Table2.Table 2
Detailed description of asset inventory management functions.
NumberingAction nameFunction descriptionF1Property assessmentThe business documents for asset count are processed here, and document maintenance and approval are performed. The inventory function only supports the information of the inventory business, and the generated reduction document and difference adjustment document are all documents under the business account book.F2Profitable assetsDocuments for inventory surplus assets are automatically generated by the system based on the final inventory check-list after review. The subledger is an inventory difference for classifying and registering the detailed changes of assets within a certain period.F3Inventory difference adjustmentThe adjustment sheet is automatically generated from the non-conforming assets after the inventory is reviewed. In the account book query, add a query “asset account book” button, and use this button to select the desiredF4Multi-book managementQuestion data. Account books must be chosen independently; the default is the primary record book, which upholds the multibranch question of one record book. Change request from the executives is the complete administration of progress orders made by the framework. Predominantly incorporate requestsF5Change order managementChange order, joint check asset card, and joint check specific change order.
## 3.2.3. Asset Allocation Management Function
The management functions of asset transfer are mainly operations such as asset transfer, asset transfer, asset reduction, moving joint construction assets, and asset depreciation adjustment. The design of the asset allocation management function is shown in Figure4 [19].Figure 4
Design of asset allocation management function.The specific description of the asset allocation management function is shown in Table3.Table 3
Asset allocation management function specific description table.
NumberingAction nameFunction descriptionF1Asset call outThe approval of the transfer of assets is mainly to complete the maintenance and approval of the transfer of fixed assets among the enterprises within the group. It mainly includes adding an approval document, modifying an approval document, reviewing an approval document, a card for a joint investigation and issuing a document, and transferring assets.F2Asset transferAsset transfer approval mainly completes the maintenance and approval of transferred fixed assets among the enterprises within the group. It mainly includes modifying the transfer approval document, approval document, and asset transfer.F3Assets decreaseAsset reduction processing is different from asset card deletion: card deletion means that in the month of card entry, the card entry error is found, and the card information is completely removed from the system. It mainly includes cards for adding asset reduction documents, modifying asset reduction documents, deleting asset reduction documents, reviewing asset reduction documents, performing asset reduction, querying asset reduction documents, and checking asset reduction documents jointly.F4Mobile co-construction assetsAccording to the original value of fixed assets, impairment provision, and accumulated depreciation derived from the mobile ERP system, a mobile co-constructed fixed asset card is formed. The business attributes of the card such as asset name, storage location, user department, management department, and user must be lost. Attributes can be set according to the actual situation and imported after forming the fixed asset card ledger of mobile joint construction assets.F5Asset depreciation adjustmentAfter the mobile joint asset card is added, the system does not accrue depreciation. By synchronizing the depreciation accrued in each period of the mobile ERP system to the enterprise asset management system through the adjustment of accumulated depreciation. The adjustment of asset depreciation mainly includes adjustment to increase the original value of assets, adjustment of asset depreciation, and provision for impairment.
## 3.2.4. Asset Depreciation and Write-Off Function
Asset depreciation and write-off mainly include operations such as asset depreciation and amortization, detailed depreciation calculation table, departmental depreciation summary table, asset depreciation adjustment, and provision for impairment. The asset depreciation and write-off function design are shown in Figure5 [20].Figure 5
Asset depreciation and write-off management function design.The detailed description of asset depreciation and write-off management functions is shown in Table4.Table 4
Detailed description of asset depreciation and write-off management functions.
<!—Col Count:3 NumberingAction nameFunction descriptionF1Depreciation and amortization of assetsThe list of depreciation amounts for all assets accrued for depreciation displayed in the depreciation list. The depreciation list for a single period lists the card number, asset name, original accrued value, asset number, accumulated depreciation, monthly depreciation, and monthly depreciation. Rate, unit depreciation, monthly workload, and cumulative workload information. It mainly includes accruing depreciation, querying depreciation list, modifying depreciation list, querying depreciation allocation summary table, and filtering depreciation list.F2Depreciation calculation scheduleThe detailed list of depreciation calculation of fixed assets is a detailed list of the original value accrued in the previous month, the depreciation accrued in the previous month, the increase or decrease of the original value in the previous month, the original value accrued in this month, and the depreciation accrual in this month according to the specified classification, including setting up depreciation schedule query, unit query, detail (summary) query, and depreciation calculation schedule.F3Departmental depreciation summaryAlthough each fixed-capital card has a management department, a user department, and a depreciation bearing department, the depreciation allocation will eventually be carried out according to the department pointed by the depreciation bearing department, that is, the depreciation of each asset will eventually be allocated to the department pointed by the bearing department. In this table, the displayed department refers to the department to which the depreciation charge will eventually be allocated. For example, if an asset management department is the finance department, the user department is the administration department, and the depreciation undertaking department is the user department, the information found in this table is the depreciation information undertaken by the administration department; the administration department refers to the depreciation undertaking department.F4Asset depreciation assessmentThe asset evaluation summary sheet is an account sheet that categorizes and summarizes the appraisal of fixed assets within a certain period. Including setting evaluation conditions and selecting evaluation units.F5Provision for impairmentThe mobile co-construction assets shall be accrued for impairment at the end of the year, and each unit shall adjust the depreciation reserves before the settlement of fixed assets at the end of the year (December 31). Reasons for changes in the template: co-construction assets are depreciated; the type of change is the adjustment for impairment allowances.
## 3.2.5. Asset Data Maintenance Management Function
The maintenance and management functions of asset data include asset changes, asset appraisals, asset impairments, asset splits, and asset consolidation operations. The asset data maintenance management function design is shown in Figure6 [21].Figure 6
Asset data maintenance function design.The specific description of asset data maintenance and management functions is shown in Table5.Table 5
Detailed description of asset data maintenance and management functions.
NumberingAction nameFunction descriptionF1Asset changesUsing the asset change document, you can realize the addition of card number, net value, net amount, provision for impairment, monthly depreciation amount, monthly depreciation rate, accrued month, currency, start date of use, depreciation auxiliary exchange rate, unit depreciation, depreciation exchange rate, cumulative workload, monthly workload, and trace changes of all other card items outside the multi-use department.F2_Asset valuationThe asset assessment function of this system is to provide assessable assets including original value, accumulated depreciation, net value, total work, service life, and net residual value rate. It mainly includes selecting assets to be assessed, defining formulas and production valuation data, manually entering and modifying valuation data, and making valuation sheets.Asset impairmentIf the assets of the enterprise have actually been impaired, provision for impairment should be made. Specifically, it includes adding an impairment provision document, selecting assets to be depreciated, creating an impairment provision document, modifying an impairment provision document, and querying an impairment provision document.Asset splitIn the asset split interface, click the “add” button, enter the “split card no.” in the header to bring out the corresponding data of the split card, and the table body will be split through operations such as “add row” and “delete row.” The number and amount of divided cards are divided into asset cards in different meter bodies. It includes adding split orders, cancelling asset splits, reviewing split orders, executing asset splits, modifying split orders, and making balance adjustments.Asset consolidationAsset merging is implemented through document templates. The first line of the document table body is merged into the main card, and most of the items that form a new card after merging are consistent with this card. Therefore, before merging assets, you need to select the main card to be merged. The purpose is to save follow-up = workload.
## 3.3. Database Design of Cost Accounting and the Control System
### 3.3.1. Conceptual Structure Design
The SME financial analysis system based on data mining is mainly aimed at leaders or investment elites in the fields of SME financial management, SME management, financial analysis, and so on, such as SME leaders, financial department managers, financial analysts, and investors [22]:(1)
SME entity attributes include SME code, SME name, SME legal person, SME address, contact person, contact number, registered capital, SME attributes, industry, social unified credit code, business Scope, activity area, business supervisory unit, whether it has subordinate departments, number of departments, issuing authority, issuing date, registration date, and remarks(2)
Department entity attributes include department code, department name, department abbreviation, display order, department attribute, auxiliary login, department type, establishment time, inventory organization, department level, telephone, superior department, department head, whether for retail, address, and notes(3)
Customer entity attributes include customer code, customer name, customer abbreviation, foreign language name, industry, whether it is a retail investor, whether it is a DRP node, whether it is a channel member, unit address, contact person, contact number, region, customer person in charge, head office code of the merchant, type of merchant, corresponding department, region, taxpayer registration number, registered capital, economic type, legal person, price group, and remarks(4)
Cash account attributes include account code, account name, mnemonic code, account opening company, currency, account opening date, contact person, contact number, account status, sealing date, account cancellation date, whether the minimum balance is controlled, minimum balance, minimum balance control scheme, whether maximum balance control, maximum balance, maximum balance control scheme, and remarks(5)
Item attributes of financial documents include document number, document status, card code, account code, account name, account type, specification model, management department, user department, start time, service life, and withdrawal month, original value in original currency, original value in local currency, accumulated depreciation, net value, provision for impairment, net amount, net residual value, reduction method, and remarks(6)
Budget report credits incorporate monetary number, monetary classification, division, utilizing division, money, subordinate, move date, approaching sum, account balance, business archive number, voucher number, outline, input charge, current month to month affirmation of record section, account status, account move, account type, administrator, whether to make a record, and comments(7)
Data credits of SME representatives incorporate worker number, name, ID number, work number, orientation, date of birth, kind of work, division, marriage, personal residence, bank card number, account opening bank, section time, working years, whether it is an extraordinary sort of work, rank, and comments
### 3.3.2. Logic Structure Design
The financial analysis system based on data mining mainly includes seven data tables, which are SME entity attribute table, department entity attribute table, customer entity attribute table, cash account attribute table, financial document item attribute table, financial statement attribute table, small- and medium-sized enterprise attribute table, and employee information attribute table [23].
## 3.3.1. Conceptual Structure Design
The SME financial analysis system based on data mining is mainly aimed at leaders or investment elites in the fields of SME financial management, SME management, financial analysis, and so on, such as SME leaders, financial department managers, financial analysts, and investors [22]:(1)
SME entity attributes include SME code, SME name, SME legal person, SME address, contact person, contact number, registered capital, SME attributes, industry, social unified credit code, business Scope, activity area, business supervisory unit, whether it has subordinate departments, number of departments, issuing authority, issuing date, registration date, and remarks(2)
Department entity attributes include department code, department name, department abbreviation, display order, department attribute, auxiliary login, department type, establishment time, inventory organization, department level, telephone, superior department, department head, whether for retail, address, and notes(3)
Customer entity attributes include customer code, customer name, customer abbreviation, foreign language name, industry, whether it is a retail investor, whether it is a DRP node, whether it is a channel member, unit address, contact person, contact number, region, customer person in charge, head office code of the merchant, type of merchant, corresponding department, region, taxpayer registration number, registered capital, economic type, legal person, price group, and remarks(4)
Cash account attributes include account code, account name, mnemonic code, account opening company, currency, account opening date, contact person, contact number, account status, sealing date, account cancellation date, whether the minimum balance is controlled, minimum balance, minimum balance control scheme, whether maximum balance control, maximum balance, maximum balance control scheme, and remarks(5)
Item attributes of financial documents include document number, document status, card code, account code, account name, account type, specification model, management department, user department, start time, service life, and withdrawal month, original value in original currency, original value in local currency, accumulated depreciation, net value, provision for impairment, net amount, net residual value, reduction method, and remarks(6)
Budget report credits incorporate monetary number, monetary classification, division, utilizing division, money, subordinate, move date, approaching sum, account balance, business archive number, voucher number, outline, input charge, current month to month affirmation of record section, account status, account move, account type, administrator, whether to make a record, and comments(7)
Data credits of SME representatives incorporate worker number, name, ID number, work number, orientation, date of birth, kind of work, division, marriage, personal residence, bank card number, account opening bank, section time, working years, whether it is an extraordinary sort of work, rank, and comments
## 3.3.2. Logic Structure Design
The financial analysis system based on data mining mainly includes seven data tables, which are SME entity attribute table, department entity attribute table, customer entity attribute table, cash account attribute table, financial document item attribute table, financial statement attribute table, small- and medium-sized enterprise attribute table, and employee information attribute table [23].
## 4. Realization of Financial Cost Accounting and the Control System Based on Data Mining Technology
The chapter on the realization and testing of the financial analysis system based on data mining is also an important part of the realization of each function in the software engineering development process. This research will combine the clustering algorithm commonly used in data mining technology to analyze a large amount of financial data and mine potential, important, and valuable financial data information from it, as shown in Figure7.Figure 7
Structure diagram of financial analysis system components.As per the ongoing improvement of monetary information of small- and medium-sized ventures, the utilization of customary succeed tables and information insights programming can help in understanding the rundown of monetary information and the examination and investigation of general monetary information. With the consistent extension of SMEs, the monetary information of small- and medium-sized ventures has turned into a remarkable development strategy and it is as yet expanding. Different monetary information is created and gathered. With the rising consciousness of data innovation among pioneers and monetary directors of small- and medium-sized undertakings, they are anxious to find a few regulations that are helpful to the improvement of small- and medium-sized ventures from the monetary information produced by small- and medium-sized endeavors for a long time. Be that as it may, to understand the powerful examination of a lot of monetary information, the related programming instruments should be utilized to understand the fast and viable investigation of the monetary information and to find the secret significant information data rapidly.This examination accepts and dissects the monetary information created by the small- and medium-sized endeavors in the one-year creation and activity process. Through measurable examination, around 14,000 bits of monetary information in the one-year creation and activity exercises of the small- and medium-sized undertakings are obtained. Thusly, the size of information investigation acknowledged by this monetary examination framework is at the 10,000-digit level. Obviously, with the quick and inside and out improvement of information mining innovation, the size of information investigation generally arrives at the degree of 100,000 or 1,000,000 (M). Obviously, the monetary examination framework is a long way from the ongoing degree of 100,000 or 1,000,000 (M) in the information mining process. Thus, somewhat, the all-inclusiveness of information investigation and information mining has specific constraints. In the subsequent examination work, this paper will lead top to bottom check and exploration on the monetary examination framework in blend with a bigger information level, to work on the presentation and productivity of the monetary examination framework [24].
### 4.1. SME Case Selection
This examination takes grain creation undertakings as an illustration to do related research work regarding the matter. Among the numerous assortments of grain, this study centers around examining the monetary information circumstance during the time spent in grain creation undertakings. The examination in this paper is that the first information comes from the yearly monetary information and fiscal reports of small- and medium-sized undertakings distributed by the Grain and Oil Affiliation and different divisions. In the wake of summing up the accounting reports of the above grain ventures, the general monetary record of grain creation undertakings in Xinjiang is shaped. Simultaneously, the totaled information sheets are placed into the SQL Server 2008 data set and broke down involving the examination administration in the OLAP device, shaping into a time-sensitive report.
### 4.2. Algorithm Selection and Application
This study will direct bunch investigation on the monetary information of the above-chosen small- and medium-sized grain creation ventures. For the most part, the monetary status of an organization can be by and large isolated into four sorts: great monetary status (A), great monetary status (B), normal monetary status (C), and poor monetary status (D). In the group examination process in this segment, the circulation bunching apparatus in MATLAB programming is utilized to understand the monetary group investigation of grain endeavors. The means of the examination are displayed in Figure 8.Figure 8
Cluster analysis process.Through programming with MATLAB software, the operation results are obtained. In this paper, the data is directly converted into a columnar graph, as shown in Figure9.Figure 9
Cluster analysis results.According to the above cluster analysis results, among the selected small- and medium-sized grain production enterprises, 1 enterprise has a good financial status of A-type enterprise, which isM23; a total of 3 enterprises has a good financial status of B-type enterprises, which are M1, M4, and M10; a total of 3 enterprises whose financial status is general C-type enterprises, namely, M2, M8, and M15; M20 and M25, two grain production enterprises, whose financial status is poor, belong to D category.
## 4.1. SME Case Selection
This examination takes grain creation undertakings as an illustration to do related research work regarding the matter. Among the numerous assortments of grain, this study centers around examining the monetary information circumstance during the time spent in grain creation undertakings. The examination in this paper is that the first information comes from the yearly monetary information and fiscal reports of small- and medium-sized undertakings distributed by the Grain and Oil Affiliation and different divisions. In the wake of summing up the accounting reports of the above grain ventures, the general monetary record of grain creation undertakings in Xinjiang is shaped. Simultaneously, the totaled information sheets are placed into the SQL Server 2008 data set and broke down involving the examination administration in the OLAP device, shaping into a time-sensitive report.
## 4.2. Algorithm Selection and Application
This study will direct bunch investigation on the monetary information of the above-chosen small- and medium-sized grain creation ventures. For the most part, the monetary status of an organization can be by and large isolated into four sorts: great monetary status (A), great monetary status (B), normal monetary status (C), and poor monetary status (D). In the group examination process in this segment, the circulation bunching apparatus in MATLAB programming is utilized to understand the monetary group investigation of grain endeavors. The means of the examination are displayed in Figure 8.Figure 8
Cluster analysis process.Through programming with MATLAB software, the operation results are obtained. In this paper, the data is directly converted into a columnar graph, as shown in Figure9.Figure 9
Cluster analysis results.According to the above cluster analysis results, among the selected small- and medium-sized grain production enterprises, 1 enterprise has a good financial status of A-type enterprise, which isM23; a total of 3 enterprises has a good financial status of B-type enterprises, which are M1, M4, and M10; a total of 3 enterprises whose financial status is general C-type enterprises, namely, M2, M8, and M15; M20 and M25, two grain production enterprises, whose financial status is poor, belong to D category.
## 5. Conclusion
This examination breaks down the utilization of facts mining innovation in huge commercial enterprise financial examination framework and plans and executes a financial examination framework in view of data digging for the variables like lengthy haul disposing of and forgetting of economic records of a particular venture. This study elucidates the examination basis of the challenge in view of statistics mining innovation and recommends that the use of statistics mining innovation to the examination of massive enterprise economic facts has imperative well worth and exhibits importance. In the sketch phase of the economic examination framework, the objectives and requirements of the framework configuration are clarified, the engineering format of the framework is shown, and the specific factors of the economic investigation framework and the facts set layout ideas are defined in realistic modules. At last, through the economic statistics of the selected small- and medium-sized grain introduction endeavors, joined with the bunching calculation and aggregate, the financial popularity of the above grain advent undertakings is dissected, and the future enhancement layout of the project and the impact on the task are outwardly proven as exceptional graphs. The internal variables of extra enhancement provide a stable dynamic premise to enterprise pioneers and journey monetary backers.
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*Source: 2901167-2022-10-12.xml* | 2022 |
# Preoperative Nutritional Risk Assessment for Predicting Complications after Radical Cystectomy plus Urinary Diversion for Bladder Cancer
**Authors:** Xing Wei; Jia Wang; Haitao Liu; Weizhe Fan; Gang Guo
**Journal:** Emergency Medicine International
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2901189
---
## Abstract
Objective. To investigate the predictive value of preoperative nutritional risk assessment on the occurrence of complications after radical cystectomy plus urinary diversion for bladder cancer. Methods. Retrospective analysis of 178 patients with bladder cancer between July 2010 and March 2022 who underwent elective radical cystectomy plus urinary diversion was conducted. The occurrence of complications within 90 days after surgery was counted for all patients, and the postoperative complication rates of patients with and without nutritional risk were compared and analyzed. Also, logistic regression analysis was used to assess the relative risk coefficients of NRS-2002 and the occurrence of postoperative complications. Results. Comparison of clinicopathological characteristics and surgical conditions between the two groups showed that the proportion of combined diabetes mellitus, operative time, and postoperative hospital stay were higher in the nutritional risk group (NRS ≥3 score) than in the no nutritional risk group (NRS <3 score), while the preoperative blood albumin (ALB) level was lower than that in the no nutritional risk group (NRS <3 score). The results of multifactorial risk regression analysis showed that low preoperative ALB level and high NRS score were independent risk factors for postoperative complications in bladder cancer (P<0.05). Conclusion. The NRS-2002 nutritional risk score has good predictive value for the incidence of postoperative complications in patients with bladder cancer and provides a scientific basis for perioperative nutritional support.
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## Body
## 1. Preface
Bladder cancer is the most common malignant tumor in urology, which is divided into two types, non-muscle layer invasive bladder cancer (NMIBC) and muscle layer invasive bladder cancer (MIBC) [1, 2]. Under normal circumstances, the clinical symptom of bladder cancer is mainly manifested as intermittent painless hematuria which occurs throughout the urination, while some patients take bladder irritation symptoms (i.e., frequency, urgency, painful urination, and so on) or pelvic pain as the main symptoms [3, 4]. Currently, radical cystectomy combined with urinary diversion has become the main surgical method for MIBC and recurrent high-risk NMIBC [5]. This technique can reduce the recurrence rate and mortality of bladder cancer after surgery and improve the survival rate. However, due to the complexity of the combined surgery, the long operation time, and the large trauma to the patient’s body, the incidence of postoperative complications is at a high level, which is detrimental to the patient’s postoperative recovery and adversely affects the surgical outcome. Therefore, finding reliable indicators to predict the incidence of postoperative complications in patients with bladder cancer has become one of the hot spots in clinical research [6].The NRS-2002 nutritional risk scoring system is a simple and easy tool for nutritional risk screening, which was already recommended by ESPEN in 2002 as the tool of choice for nutritional risk screening in hospitalized patients, and has since been gradually promoted worldwide [7]. In 2006, the Chinese Society of Parenteral and Enteral Nutrition (CSPEN) recommended the “current recommendation of the NRS-2002 as a tool for assessing nutritional risk” as level A evidence [8]. There is existing evidence that complications may decrease nutritional status of patients [9]. But whether changes of NRS-2002 nutritional risk score are related to complications after bladder cancer surgery is still not scientifically reported. On this basis, this study analyzed the value of NRS-2002 nutritional risk scoring system in predicting the complications after bladder cancer surgery. The results are now reported as follows.
## 2. Information and Methods
### 2.1. Study Population and Grouping
The method of this study was retrospective case analysis, and we retrospectively searched electronic medical record database system, and the time interval of the search was set from July 2010 to March 2022. A total of 207 adult patients who underwent inpatient treatment in our urology department during this period were retrieved, and all of them were clinically diagnosed with bladder cancer and had detailed clinical and follow-up records. All patients were then screened according to predefined inclusion and exclusion criteria, and a total of 178 patients were eventually enrolled in this study.
#### 2.1.1. Inclusion Criteria
(1)
Adult patients with clinical and first confirmed diagnosis of bladder cancer.(2)
Received surgical treatment for the first time.(3)
Surgical treatment option chosen as radical total bladder dissection combined with urinary flow diversion.(4)
Patients with preoperative perfection of relevant laboratory, imaging, pathology, and other tests.(5)
At least 18 years old.
#### 2.1.2. Exclusion Criteria
(1)
Pediatric patients.(2)
Those with relapsed bladder cancer.(3)
Patients who had received adjuvant radiotherapy or bladder irrigation prior to surgery.(4)
The first surgical treatment plan was partial cystectomy or radical cystectomy for bladder cancer.(5)
Intraoperative conversion to open surgery for radical cystectomy plus urinary diversion.
### 2.2. Methodology
#### 2.2.1. Data Collection
Patient data were collected through the hospital information management system, which included (1) preoperative general information: patient gender, age, BMI, NRS-2002 score, presence of hypertension, diabetes mellitus (DM), coronary heart disease (CHD), preoperative serum albumin (ALB), and hemoglobin (HB); (2) surgery-related information: operation time, intraoperative bleeding, intraoperative blood transfusion, surgical procedure (transabdominal open and transabdominal laparoscopic), urethral diversion method (ileal neobladder (IN) and ileal cystectomy (IC)), tumor site, postoperative pathological staging; and (3) prognostic information: postoperative complications, hospitalization time, etc.
#### 2.2.2. Preoperative Nutritional Assessment
NRS-2002 was used for preoperative nutritional assessment, which included three aspects: disease severity score (0∼3), impaired nutritional status score (0∼3), and age score (0∼1). The final nutritional risk score was the sum of age score, impaired nutritional status score, and disease severity score. Those with a final score greater than or equal to 3 were considered to be at nutritional risk. Those with a final score less than 3 were considered to be patients without nutritional risk (the specific investigation methods are shown in Table1).Table 1
NRS scores.
ScoreNutritional statusSeverity of diseaseAge0 pointsNormal.Normal.＜70 years old1 pointWeight loss of more than 5% in 3 months or eating 25% to 50% less than normal requirements in the previous week.Fractures, chronic diseases such as liver cirrhosis, hemodialysis, general malignancies, diabetes, etc.≥70 years old2 pointsWeight loss of more than 5% in 2 months or eating 50% to 75% less than normal requirements in the previous week.Severe pneumonia, major abdominal surgery, shock, stroke, etc.—3 pointsWeight loss of more than 5% in 1 month or more than 15% in 3 months or eating 75% to 100% less than normal requirement in the previous week or body mass index less than 18.50 Kg/m2.Craniosynostosis, bone marrow transplantation, and ICU patients.—
#### 2.2.3. Definition of Postoperative Complications
The severity of postoperative complications was classified according to the Clavien–Dindo grading criteria: grade I did not require surgery, drugs, intervention, or endoscopy; grade II required drugs, blood transfusion, or total parenteral nutrition therapy; grade III required surgery, endoscopy, or intervention; grade IV could endanger the patient’s life and required intensive care; and grade V led to the patient’s death. Among them, grades I and II were defined as minor complications, and grades III to V were defined as serious complications [10].
### 2.3. Statistical Methods
SPSS 17.0 statistical software was used for data processing. Measurement data are expressed as mean ± standard deviation (x¯ ± s), independent sample t-test is used for comparison between groups, count data are expressed as [n (%)], and chi-square (χ2) test is performed. Logistic regression analysis was used for multifactorial analysis of the risk of postoperative complications. The difference is statistically significant when P<0.05.
## 2.1. Study Population and Grouping
The method of this study was retrospective case analysis, and we retrospectively searched electronic medical record database system, and the time interval of the search was set from July 2010 to March 2022. A total of 207 adult patients who underwent inpatient treatment in our urology department during this period were retrieved, and all of them were clinically diagnosed with bladder cancer and had detailed clinical and follow-up records. All patients were then screened according to predefined inclusion and exclusion criteria, and a total of 178 patients were eventually enrolled in this study.
### 2.1.1. Inclusion Criteria
(1)
Adult patients with clinical and first confirmed diagnosis of bladder cancer.(2)
Received surgical treatment for the first time.(3)
Surgical treatment option chosen as radical total bladder dissection combined with urinary flow diversion.(4)
Patients with preoperative perfection of relevant laboratory, imaging, pathology, and other tests.(5)
At least 18 years old.
### 2.1.2. Exclusion Criteria
(1)
Pediatric patients.(2)
Those with relapsed bladder cancer.(3)
Patients who had received adjuvant radiotherapy or bladder irrigation prior to surgery.(4)
The first surgical treatment plan was partial cystectomy or radical cystectomy for bladder cancer.(5)
Intraoperative conversion to open surgery for radical cystectomy plus urinary diversion.
## 2.1.1. Inclusion Criteria
(1)
Adult patients with clinical and first confirmed diagnosis of bladder cancer.(2)
Received surgical treatment for the first time.(3)
Surgical treatment option chosen as radical total bladder dissection combined with urinary flow diversion.(4)
Patients with preoperative perfection of relevant laboratory, imaging, pathology, and other tests.(5)
At least 18 years old.
## 2.1.2. Exclusion Criteria
(1)
Pediatric patients.(2)
Those with relapsed bladder cancer.(3)
Patients who had received adjuvant radiotherapy or bladder irrigation prior to surgery.(4)
The first surgical treatment plan was partial cystectomy or radical cystectomy for bladder cancer.(5)
Intraoperative conversion to open surgery for radical cystectomy plus urinary diversion.
## 2.2. Methodology
### 2.2.1. Data Collection
Patient data were collected through the hospital information management system, which included (1) preoperative general information: patient gender, age, BMI, NRS-2002 score, presence of hypertension, diabetes mellitus (DM), coronary heart disease (CHD), preoperative serum albumin (ALB), and hemoglobin (HB); (2) surgery-related information: operation time, intraoperative bleeding, intraoperative blood transfusion, surgical procedure (transabdominal open and transabdominal laparoscopic), urethral diversion method (ileal neobladder (IN) and ileal cystectomy (IC)), tumor site, postoperative pathological staging; and (3) prognostic information: postoperative complications, hospitalization time, etc.
### 2.2.2. Preoperative Nutritional Assessment
NRS-2002 was used for preoperative nutritional assessment, which included three aspects: disease severity score (0∼3), impaired nutritional status score (0∼3), and age score (0∼1). The final nutritional risk score was the sum of age score, impaired nutritional status score, and disease severity score. Those with a final score greater than or equal to 3 were considered to be at nutritional risk. Those with a final score less than 3 were considered to be patients without nutritional risk (the specific investigation methods are shown in Table1).Table 1
NRS scores.
ScoreNutritional statusSeverity of diseaseAge0 pointsNormal.Normal.＜70 years old1 pointWeight loss of more than 5% in 3 months or eating 25% to 50% less than normal requirements in the previous week.Fractures, chronic diseases such as liver cirrhosis, hemodialysis, general malignancies, diabetes, etc.≥70 years old2 pointsWeight loss of more than 5% in 2 months or eating 50% to 75% less than normal requirements in the previous week.Severe pneumonia, major abdominal surgery, shock, stroke, etc.—3 pointsWeight loss of more than 5% in 1 month or more than 15% in 3 months or eating 75% to 100% less than normal requirement in the previous week or body mass index less than 18.50 Kg/m2.Craniosynostosis, bone marrow transplantation, and ICU patients.—
### 2.2.3. Definition of Postoperative Complications
The severity of postoperative complications was classified according to the Clavien–Dindo grading criteria: grade I did not require surgery, drugs, intervention, or endoscopy; grade II required drugs, blood transfusion, or total parenteral nutrition therapy; grade III required surgery, endoscopy, or intervention; grade IV could endanger the patient’s life and required intensive care; and grade V led to the patient’s death. Among them, grades I and II were defined as minor complications, and grades III to V were defined as serious complications [10].
## 2.2.1. Data Collection
Patient data were collected through the hospital information management system, which included (1) preoperative general information: patient gender, age, BMI, NRS-2002 score, presence of hypertension, diabetes mellitus (DM), coronary heart disease (CHD), preoperative serum albumin (ALB), and hemoglobin (HB); (2) surgery-related information: operation time, intraoperative bleeding, intraoperative blood transfusion, surgical procedure (transabdominal open and transabdominal laparoscopic), urethral diversion method (ileal neobladder (IN) and ileal cystectomy (IC)), tumor site, postoperative pathological staging; and (3) prognostic information: postoperative complications, hospitalization time, etc.
## 2.2.2. Preoperative Nutritional Assessment
NRS-2002 was used for preoperative nutritional assessment, which included three aspects: disease severity score (0∼3), impaired nutritional status score (0∼3), and age score (0∼1). The final nutritional risk score was the sum of age score, impaired nutritional status score, and disease severity score. Those with a final score greater than or equal to 3 were considered to be at nutritional risk. Those with a final score less than 3 were considered to be patients without nutritional risk (the specific investigation methods are shown in Table1).Table 1
NRS scores.
ScoreNutritional statusSeverity of diseaseAge0 pointsNormal.Normal.＜70 years old1 pointWeight loss of more than 5% in 3 months or eating 25% to 50% less than normal requirements in the previous week.Fractures, chronic diseases such as liver cirrhosis, hemodialysis, general malignancies, diabetes, etc.≥70 years old2 pointsWeight loss of more than 5% in 2 months or eating 50% to 75% less than normal requirements in the previous week.Severe pneumonia, major abdominal surgery, shock, stroke, etc.—3 pointsWeight loss of more than 5% in 1 month or more than 15% in 3 months or eating 75% to 100% less than normal requirement in the previous week or body mass index less than 18.50 Kg/m2.Craniosynostosis, bone marrow transplantation, and ICU patients.—
## 2.2.3. Definition of Postoperative Complications
The severity of postoperative complications was classified according to the Clavien–Dindo grading criteria: grade I did not require surgery, drugs, intervention, or endoscopy; grade II required drugs, blood transfusion, or total parenteral nutrition therapy; grade III required surgery, endoscopy, or intervention; grade IV could endanger the patient’s life and required intensive care; and grade V led to the patient’s death. Among them, grades I and II were defined as minor complications, and grades III to V were defined as serious complications [10].
## 2.3. Statistical Methods
SPSS 17.0 statistical software was used for data processing. Measurement data are expressed as mean ± standard deviation (x¯ ± s), independent sample t-test is used for comparison between groups, count data are expressed as [n (%)], and chi-square (χ2) test is performed. Logistic regression analysis was used for multifactorial analysis of the risk of postoperative complications. The difference is statistically significant when P<0.05.
## 3. Results
### 3.1. Comparison of Clinicopathological Characteristics
The 178 bladder cancer patients were grouped according to the NRS-2002 score, and those with NRS ≥3 were included in the nutritional risk group (62 patients, 34.83%), and those with NRS <3 were included in the no nutritional risk group (116 patients, 65.17%). There were no statistically significant differences in gender, age, BMI, presence of hypertension, coronary artery disease, ASA classification, preoperative hemoglobin, pathological grade, tumor size, and tumor location between the two groups (P>0.05). The proportion of patients with combined diabetes mellitus and preoperative blood albumin levels were higher in patients with NRS ≥3 than in patients with NRS <3 (P<0.05) (Table 2).Table 2
Comparison of clinicopathological characteristics.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)t/χ2 valueP valueAge (years)68.19 ± 9.4466.40 ± 8.501.2470.214Gender (n, %)1.3670.242Male98 (84.48)48 (77.42)Female18 (15.52)14 (25.81)BMI (kg/m2)22.80 ± 5.4221.79 ± 4.731.2370.218Hypertension (n, %)43 (37.07)16 (25.81)2.3130.128DM (n, %)7 (6.03)10 (16.13)4.7660.029CHD (n, %)6 (51.72)1 (1.61)1.3550.244ASA grading (n, %)0.5170.772Grade I53 (45.69)29 (46.77)Grade II52 (44.83)26 (41.94)Grade III∼IV11 (9.48)8 (12.90)Preoperative ALB (g/L)42.23 ± 5.4637.25 ± 4.036.3180.000Preoperative HB (g/L)133.14 ± 12.30130.58 ± 16.421.1730.242Pathological grade (n, %)0.3670.545Low level31 (26.72)14 (22.58)High level85 (73.28)48 (77.42)Tumor size (cm)4.70 ± 0.844.74 ± 0.630.3290.743Tumor site (n, %)0.0410.980Side wall89 (76.72)46 (74.19)Triangle20 (17.24)11 (17.74)Bladder neck7 (6.03)4 (6.45)
### 3.2. Comparison of Surgical Treatment
The operative times of patients in the nutritional risk group (NRS ≥3 points) and the patients in the no nutritional risk group (NRS <3 points) were (322.19 ± 46.04) min and (301.27 ± 40.12) min, respectively, and the postoperative hospital stays were (17.80 ± 4.90) d and (15.25 ± 4.02) d, respectively, and the differences between the two groups were statistically significant (P<0.05). The differences in intraoperative bleeding, intraoperative blood transfusion, surgical procedure, urethral diversion method, and other surgical treatments between the two groups were not statistically significant (P>0.05) (Table 3).Table 3
Comparison of surgical treatment.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)t/χ2 valueP valueOperating time (min)301.27 ± 40.12322.19 ± 46.043.1460.002Intraoperative bleeding volume (mL)397.59 ± 100.08402.27 ± 103.300.2940.769Intraoperative blood transfusion (n, %)0.2580.612Yes26 (22.41)16 (25.81)No90 (77.59)46 (74.19)Operation style (n, %)0.8540.356Transabdominal open10 (8.62)3 (4.84)Transabdominal laparoscopic106 (91.38)59 (95.16)Urethral diversion method (n, %)0.1660.684IN34 (29.31)20 (32.26)IC82 (70.69)42 (67.74)Postoperative hospital stay (d)15.25 ± 4.0217.80 ± 4.903.7300.000
### 3.3. Comparison of Postoperative Complications
The complication rates in the NRS-2002 score ≥3 subgroup and the NRS-2002 score <3 subgroup were 54.84% (34/62) and 23.28% (27/116), respectively, and the differences were statistically significant (P<0.05) when comparing the two groups (Table 4).Table 4
Comparison of postoperative complications.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)χ2 valueP valueGrade I∼ II (n, %)Leaking of urine2 (1.72)3 (4.84)1.4360.231Lung infection2 (1.72)2 (3.23)0.4150.520Deep venous thrombosis4 (3.45)2 (3.23)0.0060.938Electrolyte disturbance5 (4.31)3 (4.84)0.0260.871Poor incision healing3 (2.59)3 (4.84)0.6290.428Abdominal infection2 (1.72)2 (3.23)0.4150.520Renal insufficiency3 (2.59)2 (3.23)0.0610.806Grade III (n, %)Intestinal fistula0 (0.00)1 (1.61)1.8820.170Intestinal obstruction5 (4.31)9 (14.52)5.8070.016Grade IV (n, %)Infectious shock1 (0.86)1 (1.61)0.2050.651Pulmonary embolism0 (0.00)2 (3.23)3.7850.052Sepsis0 (0.00)1 (1.61)1.8820.170Grade V (n, %)Postoperative death0 (0.00)1 (1.61)1.8820.170Total complications (n, %)27 (23.28)34 (54.84)17.8690.000
### 3.4. Analysis of Risk Factors for Postoperative Complications in Patients
The presence of postoperative complications in bladder cancer was used as the dependent variable, and five variables such as time to surgery, comorbid diabetes mellitus, preoperative blood albumin level, NRS score, and postoperative length of stay were used as independent variables in Tables1–3 at P<0.05 for regression analysis. The occurrence of postoperative complications was significantly correlated with patients’ preoperative ALB levels (OR = 1.670, 95% CI: 1.331–2.097, P = 0.005) and NRS scores (OR = 2.787, 95% CI: 1.457–5.332, P<0.001). Low preoperative ALB level and high NRS score were high risk factors for the development of postoperative complications in bladder cancer (Table 5).Table 5
Analysis of risk factors for postoperative complications in patients.
IndicatorsBSEWaldχ2P valueOR95% CISurgery time0.2450.1821.2580.2301.2780.894∼1.825DM0.0130.0073.2310.0701.0130.997∼1.029Preoperative ALB0.5130.1168.1360.0051.6701.331∼2.097NRS score1.0250.33115.587＜0.0012.7871.457∼5.332Postoperative hospital stay0.4120.3832.2400.1101.5100.713∼3.198
## 3.1. Comparison of Clinicopathological Characteristics
The 178 bladder cancer patients were grouped according to the NRS-2002 score, and those with NRS ≥3 were included in the nutritional risk group (62 patients, 34.83%), and those with NRS <3 were included in the no nutritional risk group (116 patients, 65.17%). There were no statistically significant differences in gender, age, BMI, presence of hypertension, coronary artery disease, ASA classification, preoperative hemoglobin, pathological grade, tumor size, and tumor location between the two groups (P>0.05). The proportion of patients with combined diabetes mellitus and preoperative blood albumin levels were higher in patients with NRS ≥3 than in patients with NRS <3 (P<0.05) (Table 2).Table 2
Comparison of clinicopathological characteristics.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)t/χ2 valueP valueAge (years)68.19 ± 9.4466.40 ± 8.501.2470.214Gender (n, %)1.3670.242Male98 (84.48)48 (77.42)Female18 (15.52)14 (25.81)BMI (kg/m2)22.80 ± 5.4221.79 ± 4.731.2370.218Hypertension (n, %)43 (37.07)16 (25.81)2.3130.128DM (n, %)7 (6.03)10 (16.13)4.7660.029CHD (n, %)6 (51.72)1 (1.61)1.3550.244ASA grading (n, %)0.5170.772Grade I53 (45.69)29 (46.77)Grade II52 (44.83)26 (41.94)Grade III∼IV11 (9.48)8 (12.90)Preoperative ALB (g/L)42.23 ± 5.4637.25 ± 4.036.3180.000Preoperative HB (g/L)133.14 ± 12.30130.58 ± 16.421.1730.242Pathological grade (n, %)0.3670.545Low level31 (26.72)14 (22.58)High level85 (73.28)48 (77.42)Tumor size (cm)4.70 ± 0.844.74 ± 0.630.3290.743Tumor site (n, %)0.0410.980Side wall89 (76.72)46 (74.19)Triangle20 (17.24)11 (17.74)Bladder neck7 (6.03)4 (6.45)
## 3.2. Comparison of Surgical Treatment
The operative times of patients in the nutritional risk group (NRS ≥3 points) and the patients in the no nutritional risk group (NRS <3 points) were (322.19 ± 46.04) min and (301.27 ± 40.12) min, respectively, and the postoperative hospital stays were (17.80 ± 4.90) d and (15.25 ± 4.02) d, respectively, and the differences between the two groups were statistically significant (P<0.05). The differences in intraoperative bleeding, intraoperative blood transfusion, surgical procedure, urethral diversion method, and other surgical treatments between the two groups were not statistically significant (P>0.05) (Table 3).Table 3
Comparison of surgical treatment.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)t/χ2 valueP valueOperating time (min)301.27 ± 40.12322.19 ± 46.043.1460.002Intraoperative bleeding volume (mL)397.59 ± 100.08402.27 ± 103.300.2940.769Intraoperative blood transfusion (n, %)0.2580.612Yes26 (22.41)16 (25.81)No90 (77.59)46 (74.19)Operation style (n, %)0.8540.356Transabdominal open10 (8.62)3 (4.84)Transabdominal laparoscopic106 (91.38)59 (95.16)Urethral diversion method (n, %)0.1660.684IN34 (29.31)20 (32.26)IC82 (70.69)42 (67.74)Postoperative hospital stay (d)15.25 ± 4.0217.80 ± 4.903.7300.000
## 3.3. Comparison of Postoperative Complications
The complication rates in the NRS-2002 score ≥3 subgroup and the NRS-2002 score <3 subgroup were 54.84% (34/62) and 23.28% (27/116), respectively, and the differences were statistically significant (P<0.05) when comparing the two groups (Table 4).Table 4
Comparison of postoperative complications.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)χ2 valueP valueGrade I∼ II (n, %)Leaking of urine2 (1.72)3 (4.84)1.4360.231Lung infection2 (1.72)2 (3.23)0.4150.520Deep venous thrombosis4 (3.45)2 (3.23)0.0060.938Electrolyte disturbance5 (4.31)3 (4.84)0.0260.871Poor incision healing3 (2.59)3 (4.84)0.6290.428Abdominal infection2 (1.72)2 (3.23)0.4150.520Renal insufficiency3 (2.59)2 (3.23)0.0610.806Grade III (n, %)Intestinal fistula0 (0.00)1 (1.61)1.8820.170Intestinal obstruction5 (4.31)9 (14.52)5.8070.016Grade IV (n, %)Infectious shock1 (0.86)1 (1.61)0.2050.651Pulmonary embolism0 (0.00)2 (3.23)3.7850.052Sepsis0 (0.00)1 (1.61)1.8820.170Grade V (n, %)Postoperative death0 (0.00)1 (1.61)1.8820.170Total complications (n, %)27 (23.28)34 (54.84)17.8690.000
## 3.4. Analysis of Risk Factors for Postoperative Complications in Patients
The presence of postoperative complications in bladder cancer was used as the dependent variable, and five variables such as time to surgery, comorbid diabetes mellitus, preoperative blood albumin level, NRS score, and postoperative length of stay were used as independent variables in Tables1–3 at P<0.05 for regression analysis. The occurrence of postoperative complications was significantly correlated with patients’ preoperative ALB levels (OR = 1.670, 95% CI: 1.331–2.097, P = 0.005) and NRS scores (OR = 2.787, 95% CI: 1.457–5.332, P<0.001). Low preoperative ALB level and high NRS score were high risk factors for the development of postoperative complications in bladder cancer (Table 5).Table 5
Analysis of risk factors for postoperative complications in patients.
IndicatorsBSEWaldχ2P valueOR95% CISurgery time0.2450.1821.2580.2301.2780.894∼1.825DM0.0130.0073.2310.0701.0130.997∼1.029Preoperative ALB0.5130.1168.1360.0051.6701.331∼2.097NRS score1.0250.33115.587＜0.0012.7871.457∼5.332Postoperative hospital stay0.4120.3832.2400.1101.5100.713∼3.198
## 4. Conclusion
As the most common malignant tumor in urinary system, bladder cancer patients with abnormal nutritional status are very common [11]. The reason is that with the proliferation of cancer cells, the body’s nutritional consumption gradually increases. Moreover, after suffering from malignant tumor, the body has a series of stress reactions, which can cause metabolic abnormalities such as accelerated glucose utilization, insulin resistance, decreased muscle protein synthesis, and enhanced amino acid gluconeogenesis, thus aggravating nutritional abnormalities [12]. Radical cystectomy plus urinary diversion includes cystectomy, pelvic lymph node dissection, and urinary diversion, which is a complex procedure with a high incidence of postoperative complications that can seriously affect patients’ physical recovery and even cause life-threatening conditions. In addition, patients at risk of abnormal nutritional status lack sufficient energy reserve, resulting in low immunity and poor anti-stress ability, so postoperative healing is slow and the incidence of complications is also increased [13]. A vicious circle can thus be formed between nutritional status and complications. So, preoperative assessment of patients’ risk of postoperative complications and prognosis is particularly important [13].More studies have pointed out age, BMI, duration of surgery, and urinary diversion method as risk factors associated with the occurrence of postoperative complications, and more factors are not modifiable and not very accurate [14, 15]. A study concluded that untimely albumin supplementation is a high risk factor for complications in patients in the perioperative period [16]. The results of our study showed that low preoperative serum albumin level is the high risk factor for postoperative complications of bladder cancer (P<0.05). Serum albumin is one of the indicators of the nutritional status of the body, and its decrease can cause low immune function of the body, which can lead to symptoms such as delayed wound healing and infection [17]. This suggests that strict clinical monitoring of preoperative blood protein levels in patients with bladder cancer may help to reduce the incidence of postoperative complications.Notably, the results of this study also showed that high NRS score was also a high risk factor for postoperative complications of bladder cancer (P<0.05). This indicates that the nutritional status of the body is closely related to the incidence of postoperative complications in patients with malignant tumors [18, 19]. Further comparison of the severity of complications among patients with different NRS-2002 scores showed that the incidence of intestinal obstruction and the total incidence of complications in the NRS ≥3 group were significantly higher than those in the NRS <3 group (P<0.05), with no significant differences in other groups.NRS-2002 is the first nutritional risk screening tool developed on the basis of evidence-based medicine [20]. The scale was simple to operate and could be quickly evaluated in a short time through simple counseling. At the same time, the scale was less affected by subjective factors in the evaluation process, and the degree of acceptance by patients was high, so it had the advantage of high accuracy [21]. Karateke et al.’s study [22] demonstrated that the results of the clinical application of NRS-2002 were superior to other screening tools in terms of specificity and sensitivity. Raslan et al. [23] evaluated NRS-2002, MNA, and MUST nutritional screening in 705 patients and compared their ability to predict complications, mortality, and length of stay, respectively, and showed that NRS-2002 and MNA were superior to MUST in predicting clinical outcomes, while showing that NRS-2002 had better predictive power. This study further used logistic regression analysis to assess the relative risk coefficients of each clinical variable with the development of postoperative intestinal obstruction and found that low preoperative blood albumin levels and high NRS scores were high risk factors for the development of postoperative complications. This indicates that the NRS-2002 score has a good predictive value for complications after radical cystectomy combined with urethral diversion for bladder cancer.In conclusion, the NRS-2002 nutritional risk score has good predictive value for the incidence of postoperative complications in bladder cancer patients and provides a scientific basis for perioperative nutritional support, which is recommended to be promoted. However, considering the relatively small sample included in this study, more randomized controlled studies with multiple samples are still needed to support the study, which is the direction of further research in this topic.
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*Source: 2901189-2022-08-16.xml* | 2901189-2022-08-16_2901189-2022-08-16.md | 32,617 | Preoperative Nutritional Risk Assessment for Predicting Complications after Radical Cystectomy plus Urinary Diversion for Bladder Cancer | Xing Wei; Jia Wang; Haitao Liu; Weizhe Fan; Gang Guo | Emergency Medicine International
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2901189 | 2901189-2022-08-16.xml | ---
## Abstract
Objective. To investigate the predictive value of preoperative nutritional risk assessment on the occurrence of complications after radical cystectomy plus urinary diversion for bladder cancer. Methods. Retrospective analysis of 178 patients with bladder cancer between July 2010 and March 2022 who underwent elective radical cystectomy plus urinary diversion was conducted. The occurrence of complications within 90 days after surgery was counted for all patients, and the postoperative complication rates of patients with and without nutritional risk were compared and analyzed. Also, logistic regression analysis was used to assess the relative risk coefficients of NRS-2002 and the occurrence of postoperative complications. Results. Comparison of clinicopathological characteristics and surgical conditions between the two groups showed that the proportion of combined diabetes mellitus, operative time, and postoperative hospital stay were higher in the nutritional risk group (NRS ≥3 score) than in the no nutritional risk group (NRS <3 score), while the preoperative blood albumin (ALB) level was lower than that in the no nutritional risk group (NRS <3 score). The results of multifactorial risk regression analysis showed that low preoperative ALB level and high NRS score were independent risk factors for postoperative complications in bladder cancer (P<0.05). Conclusion. The NRS-2002 nutritional risk score has good predictive value for the incidence of postoperative complications in patients with bladder cancer and provides a scientific basis for perioperative nutritional support.
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## Body
## 1. Preface
Bladder cancer is the most common malignant tumor in urology, which is divided into two types, non-muscle layer invasive bladder cancer (NMIBC) and muscle layer invasive bladder cancer (MIBC) [1, 2]. Under normal circumstances, the clinical symptom of bladder cancer is mainly manifested as intermittent painless hematuria which occurs throughout the urination, while some patients take bladder irritation symptoms (i.e., frequency, urgency, painful urination, and so on) or pelvic pain as the main symptoms [3, 4]. Currently, radical cystectomy combined with urinary diversion has become the main surgical method for MIBC and recurrent high-risk NMIBC [5]. This technique can reduce the recurrence rate and mortality of bladder cancer after surgery and improve the survival rate. However, due to the complexity of the combined surgery, the long operation time, and the large trauma to the patient’s body, the incidence of postoperative complications is at a high level, which is detrimental to the patient’s postoperative recovery and adversely affects the surgical outcome. Therefore, finding reliable indicators to predict the incidence of postoperative complications in patients with bladder cancer has become one of the hot spots in clinical research [6].The NRS-2002 nutritional risk scoring system is a simple and easy tool for nutritional risk screening, which was already recommended by ESPEN in 2002 as the tool of choice for nutritional risk screening in hospitalized patients, and has since been gradually promoted worldwide [7]. In 2006, the Chinese Society of Parenteral and Enteral Nutrition (CSPEN) recommended the “current recommendation of the NRS-2002 as a tool for assessing nutritional risk” as level A evidence [8]. There is existing evidence that complications may decrease nutritional status of patients [9]. But whether changes of NRS-2002 nutritional risk score are related to complications after bladder cancer surgery is still not scientifically reported. On this basis, this study analyzed the value of NRS-2002 nutritional risk scoring system in predicting the complications after bladder cancer surgery. The results are now reported as follows.
## 2. Information and Methods
### 2.1. Study Population and Grouping
The method of this study was retrospective case analysis, and we retrospectively searched electronic medical record database system, and the time interval of the search was set from July 2010 to March 2022. A total of 207 adult patients who underwent inpatient treatment in our urology department during this period were retrieved, and all of them were clinically diagnosed with bladder cancer and had detailed clinical and follow-up records. All patients were then screened according to predefined inclusion and exclusion criteria, and a total of 178 patients were eventually enrolled in this study.
#### 2.1.1. Inclusion Criteria
(1)
Adult patients with clinical and first confirmed diagnosis of bladder cancer.(2)
Received surgical treatment for the first time.(3)
Surgical treatment option chosen as radical total bladder dissection combined with urinary flow diversion.(4)
Patients with preoperative perfection of relevant laboratory, imaging, pathology, and other tests.(5)
At least 18 years old.
#### 2.1.2. Exclusion Criteria
(1)
Pediatric patients.(2)
Those with relapsed bladder cancer.(3)
Patients who had received adjuvant radiotherapy or bladder irrigation prior to surgery.(4)
The first surgical treatment plan was partial cystectomy or radical cystectomy for bladder cancer.(5)
Intraoperative conversion to open surgery for radical cystectomy plus urinary diversion.
### 2.2. Methodology
#### 2.2.1. Data Collection
Patient data were collected through the hospital information management system, which included (1) preoperative general information: patient gender, age, BMI, NRS-2002 score, presence of hypertension, diabetes mellitus (DM), coronary heart disease (CHD), preoperative serum albumin (ALB), and hemoglobin (HB); (2) surgery-related information: operation time, intraoperative bleeding, intraoperative blood transfusion, surgical procedure (transabdominal open and transabdominal laparoscopic), urethral diversion method (ileal neobladder (IN) and ileal cystectomy (IC)), tumor site, postoperative pathological staging; and (3) prognostic information: postoperative complications, hospitalization time, etc.
#### 2.2.2. Preoperative Nutritional Assessment
NRS-2002 was used for preoperative nutritional assessment, which included three aspects: disease severity score (0∼3), impaired nutritional status score (0∼3), and age score (0∼1). The final nutritional risk score was the sum of age score, impaired nutritional status score, and disease severity score. Those with a final score greater than or equal to 3 were considered to be at nutritional risk. Those with a final score less than 3 were considered to be patients without nutritional risk (the specific investigation methods are shown in Table1).Table 1
NRS scores.
ScoreNutritional statusSeverity of diseaseAge0 pointsNormal.Normal.＜70 years old1 pointWeight loss of more than 5% in 3 months or eating 25% to 50% less than normal requirements in the previous week.Fractures, chronic diseases such as liver cirrhosis, hemodialysis, general malignancies, diabetes, etc.≥70 years old2 pointsWeight loss of more than 5% in 2 months or eating 50% to 75% less than normal requirements in the previous week.Severe pneumonia, major abdominal surgery, shock, stroke, etc.—3 pointsWeight loss of more than 5% in 1 month or more than 15% in 3 months or eating 75% to 100% less than normal requirement in the previous week or body mass index less than 18.50 Kg/m2.Craniosynostosis, bone marrow transplantation, and ICU patients.—
#### 2.2.3. Definition of Postoperative Complications
The severity of postoperative complications was classified according to the Clavien–Dindo grading criteria: grade I did not require surgery, drugs, intervention, or endoscopy; grade II required drugs, blood transfusion, or total parenteral nutrition therapy; grade III required surgery, endoscopy, or intervention; grade IV could endanger the patient’s life and required intensive care; and grade V led to the patient’s death. Among them, grades I and II were defined as minor complications, and grades III to V were defined as serious complications [10].
### 2.3. Statistical Methods
SPSS 17.0 statistical software was used for data processing. Measurement data are expressed as mean ± standard deviation (x¯ ± s), independent sample t-test is used for comparison between groups, count data are expressed as [n (%)], and chi-square (χ2) test is performed. Logistic regression analysis was used for multifactorial analysis of the risk of postoperative complications. The difference is statistically significant when P<0.05.
## 2.1. Study Population and Grouping
The method of this study was retrospective case analysis, and we retrospectively searched electronic medical record database system, and the time interval of the search was set from July 2010 to March 2022. A total of 207 adult patients who underwent inpatient treatment in our urology department during this period were retrieved, and all of them were clinically diagnosed with bladder cancer and had detailed clinical and follow-up records. All patients were then screened according to predefined inclusion and exclusion criteria, and a total of 178 patients were eventually enrolled in this study.
### 2.1.1. Inclusion Criteria
(1)
Adult patients with clinical and first confirmed diagnosis of bladder cancer.(2)
Received surgical treatment for the first time.(3)
Surgical treatment option chosen as radical total bladder dissection combined with urinary flow diversion.(4)
Patients with preoperative perfection of relevant laboratory, imaging, pathology, and other tests.(5)
At least 18 years old.
### 2.1.2. Exclusion Criteria
(1)
Pediatric patients.(2)
Those with relapsed bladder cancer.(3)
Patients who had received adjuvant radiotherapy or bladder irrigation prior to surgery.(4)
The first surgical treatment plan was partial cystectomy or radical cystectomy for bladder cancer.(5)
Intraoperative conversion to open surgery for radical cystectomy plus urinary diversion.
## 2.1.1. Inclusion Criteria
(1)
Adult patients with clinical and first confirmed diagnosis of bladder cancer.(2)
Received surgical treatment for the first time.(3)
Surgical treatment option chosen as radical total bladder dissection combined with urinary flow diversion.(4)
Patients with preoperative perfection of relevant laboratory, imaging, pathology, and other tests.(5)
At least 18 years old.
## 2.1.2. Exclusion Criteria
(1)
Pediatric patients.(2)
Those with relapsed bladder cancer.(3)
Patients who had received adjuvant radiotherapy or bladder irrigation prior to surgery.(4)
The first surgical treatment plan was partial cystectomy or radical cystectomy for bladder cancer.(5)
Intraoperative conversion to open surgery for radical cystectomy plus urinary diversion.
## 2.2. Methodology
### 2.2.1. Data Collection
Patient data were collected through the hospital information management system, which included (1) preoperative general information: patient gender, age, BMI, NRS-2002 score, presence of hypertension, diabetes mellitus (DM), coronary heart disease (CHD), preoperative serum albumin (ALB), and hemoglobin (HB); (2) surgery-related information: operation time, intraoperative bleeding, intraoperative blood transfusion, surgical procedure (transabdominal open and transabdominal laparoscopic), urethral diversion method (ileal neobladder (IN) and ileal cystectomy (IC)), tumor site, postoperative pathological staging; and (3) prognostic information: postoperative complications, hospitalization time, etc.
### 2.2.2. Preoperative Nutritional Assessment
NRS-2002 was used for preoperative nutritional assessment, which included three aspects: disease severity score (0∼3), impaired nutritional status score (0∼3), and age score (0∼1). The final nutritional risk score was the sum of age score, impaired nutritional status score, and disease severity score. Those with a final score greater than or equal to 3 were considered to be at nutritional risk. Those with a final score less than 3 were considered to be patients without nutritional risk (the specific investigation methods are shown in Table1).Table 1
NRS scores.
ScoreNutritional statusSeverity of diseaseAge0 pointsNormal.Normal.＜70 years old1 pointWeight loss of more than 5% in 3 months or eating 25% to 50% less than normal requirements in the previous week.Fractures, chronic diseases such as liver cirrhosis, hemodialysis, general malignancies, diabetes, etc.≥70 years old2 pointsWeight loss of more than 5% in 2 months or eating 50% to 75% less than normal requirements in the previous week.Severe pneumonia, major abdominal surgery, shock, stroke, etc.—3 pointsWeight loss of more than 5% in 1 month or more than 15% in 3 months or eating 75% to 100% less than normal requirement in the previous week or body mass index less than 18.50 Kg/m2.Craniosynostosis, bone marrow transplantation, and ICU patients.—
### 2.2.3. Definition of Postoperative Complications
The severity of postoperative complications was classified according to the Clavien–Dindo grading criteria: grade I did not require surgery, drugs, intervention, or endoscopy; grade II required drugs, blood transfusion, or total parenteral nutrition therapy; grade III required surgery, endoscopy, or intervention; grade IV could endanger the patient’s life and required intensive care; and grade V led to the patient’s death. Among them, grades I and II were defined as minor complications, and grades III to V were defined as serious complications [10].
## 2.2.1. Data Collection
Patient data were collected through the hospital information management system, which included (1) preoperative general information: patient gender, age, BMI, NRS-2002 score, presence of hypertension, diabetes mellitus (DM), coronary heart disease (CHD), preoperative serum albumin (ALB), and hemoglobin (HB); (2) surgery-related information: operation time, intraoperative bleeding, intraoperative blood transfusion, surgical procedure (transabdominal open and transabdominal laparoscopic), urethral diversion method (ileal neobladder (IN) and ileal cystectomy (IC)), tumor site, postoperative pathological staging; and (3) prognostic information: postoperative complications, hospitalization time, etc.
## 2.2.2. Preoperative Nutritional Assessment
NRS-2002 was used for preoperative nutritional assessment, which included three aspects: disease severity score (0∼3), impaired nutritional status score (0∼3), and age score (0∼1). The final nutritional risk score was the sum of age score, impaired nutritional status score, and disease severity score. Those with a final score greater than or equal to 3 were considered to be at nutritional risk. Those with a final score less than 3 were considered to be patients without nutritional risk (the specific investigation methods are shown in Table1).Table 1
NRS scores.
ScoreNutritional statusSeverity of diseaseAge0 pointsNormal.Normal.＜70 years old1 pointWeight loss of more than 5% in 3 months or eating 25% to 50% less than normal requirements in the previous week.Fractures, chronic diseases such as liver cirrhosis, hemodialysis, general malignancies, diabetes, etc.≥70 years old2 pointsWeight loss of more than 5% in 2 months or eating 50% to 75% less than normal requirements in the previous week.Severe pneumonia, major abdominal surgery, shock, stroke, etc.—3 pointsWeight loss of more than 5% in 1 month or more than 15% in 3 months or eating 75% to 100% less than normal requirement in the previous week or body mass index less than 18.50 Kg/m2.Craniosynostosis, bone marrow transplantation, and ICU patients.—
## 2.2.3. Definition of Postoperative Complications
The severity of postoperative complications was classified according to the Clavien–Dindo grading criteria: grade I did not require surgery, drugs, intervention, or endoscopy; grade II required drugs, blood transfusion, or total parenteral nutrition therapy; grade III required surgery, endoscopy, or intervention; grade IV could endanger the patient’s life and required intensive care; and grade V led to the patient’s death. Among them, grades I and II were defined as minor complications, and grades III to V were defined as serious complications [10].
## 2.3. Statistical Methods
SPSS 17.0 statistical software was used for data processing. Measurement data are expressed as mean ± standard deviation (x¯ ± s), independent sample t-test is used for comparison between groups, count data are expressed as [n (%)], and chi-square (χ2) test is performed. Logistic regression analysis was used for multifactorial analysis of the risk of postoperative complications. The difference is statistically significant when P<0.05.
## 3. Results
### 3.1. Comparison of Clinicopathological Characteristics
The 178 bladder cancer patients were grouped according to the NRS-2002 score, and those with NRS ≥3 were included in the nutritional risk group (62 patients, 34.83%), and those with NRS <3 were included in the no nutritional risk group (116 patients, 65.17%). There were no statistically significant differences in gender, age, BMI, presence of hypertension, coronary artery disease, ASA classification, preoperative hemoglobin, pathological grade, tumor size, and tumor location between the two groups (P>0.05). The proportion of patients with combined diabetes mellitus and preoperative blood albumin levels were higher in patients with NRS ≥3 than in patients with NRS <3 (P<0.05) (Table 2).Table 2
Comparison of clinicopathological characteristics.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)t/χ2 valueP valueAge (years)68.19 ± 9.4466.40 ± 8.501.2470.214Gender (n, %)1.3670.242Male98 (84.48)48 (77.42)Female18 (15.52)14 (25.81)BMI (kg/m2)22.80 ± 5.4221.79 ± 4.731.2370.218Hypertension (n, %)43 (37.07)16 (25.81)2.3130.128DM (n, %)7 (6.03)10 (16.13)4.7660.029CHD (n, %)6 (51.72)1 (1.61)1.3550.244ASA grading (n, %)0.5170.772Grade I53 (45.69)29 (46.77)Grade II52 (44.83)26 (41.94)Grade III∼IV11 (9.48)8 (12.90)Preoperative ALB (g/L)42.23 ± 5.4637.25 ± 4.036.3180.000Preoperative HB (g/L)133.14 ± 12.30130.58 ± 16.421.1730.242Pathological grade (n, %)0.3670.545Low level31 (26.72)14 (22.58)High level85 (73.28)48 (77.42)Tumor size (cm)4.70 ± 0.844.74 ± 0.630.3290.743Tumor site (n, %)0.0410.980Side wall89 (76.72)46 (74.19)Triangle20 (17.24)11 (17.74)Bladder neck7 (6.03)4 (6.45)
### 3.2. Comparison of Surgical Treatment
The operative times of patients in the nutritional risk group (NRS ≥3 points) and the patients in the no nutritional risk group (NRS <3 points) were (322.19 ± 46.04) min and (301.27 ± 40.12) min, respectively, and the postoperative hospital stays were (17.80 ± 4.90) d and (15.25 ± 4.02) d, respectively, and the differences between the two groups were statistically significant (P<0.05). The differences in intraoperative bleeding, intraoperative blood transfusion, surgical procedure, urethral diversion method, and other surgical treatments between the two groups were not statistically significant (P>0.05) (Table 3).Table 3
Comparison of surgical treatment.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)t/χ2 valueP valueOperating time (min)301.27 ± 40.12322.19 ± 46.043.1460.002Intraoperative bleeding volume (mL)397.59 ± 100.08402.27 ± 103.300.2940.769Intraoperative blood transfusion (n, %)0.2580.612Yes26 (22.41)16 (25.81)No90 (77.59)46 (74.19)Operation style (n, %)0.8540.356Transabdominal open10 (8.62)3 (4.84)Transabdominal laparoscopic106 (91.38)59 (95.16)Urethral diversion method (n, %)0.1660.684IN34 (29.31)20 (32.26)IC82 (70.69)42 (67.74)Postoperative hospital stay (d)15.25 ± 4.0217.80 ± 4.903.7300.000
### 3.3. Comparison of Postoperative Complications
The complication rates in the NRS-2002 score ≥3 subgroup and the NRS-2002 score <3 subgroup were 54.84% (34/62) and 23.28% (27/116), respectively, and the differences were statistically significant (P<0.05) when comparing the two groups (Table 4).Table 4
Comparison of postoperative complications.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)χ2 valueP valueGrade I∼ II (n, %)Leaking of urine2 (1.72)3 (4.84)1.4360.231Lung infection2 (1.72)2 (3.23)0.4150.520Deep venous thrombosis4 (3.45)2 (3.23)0.0060.938Electrolyte disturbance5 (4.31)3 (4.84)0.0260.871Poor incision healing3 (2.59)3 (4.84)0.6290.428Abdominal infection2 (1.72)2 (3.23)0.4150.520Renal insufficiency3 (2.59)2 (3.23)0.0610.806Grade III (n, %)Intestinal fistula0 (0.00)1 (1.61)1.8820.170Intestinal obstruction5 (4.31)9 (14.52)5.8070.016Grade IV (n, %)Infectious shock1 (0.86)1 (1.61)0.2050.651Pulmonary embolism0 (0.00)2 (3.23)3.7850.052Sepsis0 (0.00)1 (1.61)1.8820.170Grade V (n, %)Postoperative death0 (0.00)1 (1.61)1.8820.170Total complications (n, %)27 (23.28)34 (54.84)17.8690.000
### 3.4. Analysis of Risk Factors for Postoperative Complications in Patients
The presence of postoperative complications in bladder cancer was used as the dependent variable, and five variables such as time to surgery, comorbid diabetes mellitus, preoperative blood albumin level, NRS score, and postoperative length of stay were used as independent variables in Tables1–3 at P<0.05 for regression analysis. The occurrence of postoperative complications was significantly correlated with patients’ preoperative ALB levels (OR = 1.670, 95% CI: 1.331–2.097, P = 0.005) and NRS scores (OR = 2.787, 95% CI: 1.457–5.332, P<0.001). Low preoperative ALB level and high NRS score were high risk factors for the development of postoperative complications in bladder cancer (Table 5).Table 5
Analysis of risk factors for postoperative complications in patients.
IndicatorsBSEWaldχ2P valueOR95% CISurgery time0.2450.1821.2580.2301.2780.894∼1.825DM0.0130.0073.2310.0701.0130.997∼1.029Preoperative ALB0.5130.1168.1360.0051.6701.331∼2.097NRS score1.0250.33115.587＜0.0012.7871.457∼5.332Postoperative hospital stay0.4120.3832.2400.1101.5100.713∼3.198
## 3.1. Comparison of Clinicopathological Characteristics
The 178 bladder cancer patients were grouped according to the NRS-2002 score, and those with NRS ≥3 were included in the nutritional risk group (62 patients, 34.83%), and those with NRS <3 were included in the no nutritional risk group (116 patients, 65.17%). There were no statistically significant differences in gender, age, BMI, presence of hypertension, coronary artery disease, ASA classification, preoperative hemoglobin, pathological grade, tumor size, and tumor location between the two groups (P>0.05). The proportion of patients with combined diabetes mellitus and preoperative blood albumin levels were higher in patients with NRS ≥3 than in patients with NRS <3 (P<0.05) (Table 2).Table 2
Comparison of clinicopathological characteristics.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)t/χ2 valueP valueAge (years)68.19 ± 9.4466.40 ± 8.501.2470.214Gender (n, %)1.3670.242Male98 (84.48)48 (77.42)Female18 (15.52)14 (25.81)BMI (kg/m2)22.80 ± 5.4221.79 ± 4.731.2370.218Hypertension (n, %)43 (37.07)16 (25.81)2.3130.128DM (n, %)7 (6.03)10 (16.13)4.7660.029CHD (n, %)6 (51.72)1 (1.61)1.3550.244ASA grading (n, %)0.5170.772Grade I53 (45.69)29 (46.77)Grade II52 (44.83)26 (41.94)Grade III∼IV11 (9.48)8 (12.90)Preoperative ALB (g/L)42.23 ± 5.4637.25 ± 4.036.3180.000Preoperative HB (g/L)133.14 ± 12.30130.58 ± 16.421.1730.242Pathological grade (n, %)0.3670.545Low level31 (26.72)14 (22.58)High level85 (73.28)48 (77.42)Tumor size (cm)4.70 ± 0.844.74 ± 0.630.3290.743Tumor site (n, %)0.0410.980Side wall89 (76.72)46 (74.19)Triangle20 (17.24)11 (17.74)Bladder neck7 (6.03)4 (6.45)
## 3.2. Comparison of Surgical Treatment
The operative times of patients in the nutritional risk group (NRS ≥3 points) and the patients in the no nutritional risk group (NRS <3 points) were (322.19 ± 46.04) min and (301.27 ± 40.12) min, respectively, and the postoperative hospital stays were (17.80 ± 4.90) d and (15.25 ± 4.02) d, respectively, and the differences between the two groups were statistically significant (P<0.05). The differences in intraoperative bleeding, intraoperative blood transfusion, surgical procedure, urethral diversion method, and other surgical treatments between the two groups were not statistically significant (P>0.05) (Table 3).Table 3
Comparison of surgical treatment.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)t/χ2 valueP valueOperating time (min)301.27 ± 40.12322.19 ± 46.043.1460.002Intraoperative bleeding volume (mL)397.59 ± 100.08402.27 ± 103.300.2940.769Intraoperative blood transfusion (n, %)0.2580.612Yes26 (22.41)16 (25.81)No90 (77.59)46 (74.19)Operation style (n, %)0.8540.356Transabdominal open10 (8.62)3 (4.84)Transabdominal laparoscopic106 (91.38)59 (95.16)Urethral diversion method (n, %)0.1660.684IN34 (29.31)20 (32.26)IC82 (70.69)42 (67.74)Postoperative hospital stay (d)15.25 ± 4.0217.80 ± 4.903.7300.000
## 3.3. Comparison of Postoperative Complications
The complication rates in the NRS-2002 score ≥3 subgroup and the NRS-2002 score <3 subgroup were 54.84% (34/62) and 23.28% (27/116), respectively, and the differences were statistically significant (P<0.05) when comparing the two groups (Table 4).Table 4
Comparison of postoperative complications.
InformationNRS <3 (n = 116)NRS≥3 (n = 62)χ2 valueP valueGrade I∼ II (n, %)Leaking of urine2 (1.72)3 (4.84)1.4360.231Lung infection2 (1.72)2 (3.23)0.4150.520Deep venous thrombosis4 (3.45)2 (3.23)0.0060.938Electrolyte disturbance5 (4.31)3 (4.84)0.0260.871Poor incision healing3 (2.59)3 (4.84)0.6290.428Abdominal infection2 (1.72)2 (3.23)0.4150.520Renal insufficiency3 (2.59)2 (3.23)0.0610.806Grade III (n, %)Intestinal fistula0 (0.00)1 (1.61)1.8820.170Intestinal obstruction5 (4.31)9 (14.52)5.8070.016Grade IV (n, %)Infectious shock1 (0.86)1 (1.61)0.2050.651Pulmonary embolism0 (0.00)2 (3.23)3.7850.052Sepsis0 (0.00)1 (1.61)1.8820.170Grade V (n, %)Postoperative death0 (0.00)1 (1.61)1.8820.170Total complications (n, %)27 (23.28)34 (54.84)17.8690.000
## 3.4. Analysis of Risk Factors for Postoperative Complications in Patients
The presence of postoperative complications in bladder cancer was used as the dependent variable, and five variables such as time to surgery, comorbid diabetes mellitus, preoperative blood albumin level, NRS score, and postoperative length of stay were used as independent variables in Tables1–3 at P<0.05 for regression analysis. The occurrence of postoperative complications was significantly correlated with patients’ preoperative ALB levels (OR = 1.670, 95% CI: 1.331–2.097, P = 0.005) and NRS scores (OR = 2.787, 95% CI: 1.457–5.332, P<0.001). Low preoperative ALB level and high NRS score were high risk factors for the development of postoperative complications in bladder cancer (Table 5).Table 5
Analysis of risk factors for postoperative complications in patients.
IndicatorsBSEWaldχ2P valueOR95% CISurgery time0.2450.1821.2580.2301.2780.894∼1.825DM0.0130.0073.2310.0701.0130.997∼1.029Preoperative ALB0.5130.1168.1360.0051.6701.331∼2.097NRS score1.0250.33115.587＜0.0012.7871.457∼5.332Postoperative hospital stay0.4120.3832.2400.1101.5100.713∼3.198
## 4. Conclusion
As the most common malignant tumor in urinary system, bladder cancer patients with abnormal nutritional status are very common [11]. The reason is that with the proliferation of cancer cells, the body’s nutritional consumption gradually increases. Moreover, after suffering from malignant tumor, the body has a series of stress reactions, which can cause metabolic abnormalities such as accelerated glucose utilization, insulin resistance, decreased muscle protein synthesis, and enhanced amino acid gluconeogenesis, thus aggravating nutritional abnormalities [12]. Radical cystectomy plus urinary diversion includes cystectomy, pelvic lymph node dissection, and urinary diversion, which is a complex procedure with a high incidence of postoperative complications that can seriously affect patients’ physical recovery and even cause life-threatening conditions. In addition, patients at risk of abnormal nutritional status lack sufficient energy reserve, resulting in low immunity and poor anti-stress ability, so postoperative healing is slow and the incidence of complications is also increased [13]. A vicious circle can thus be formed between nutritional status and complications. So, preoperative assessment of patients’ risk of postoperative complications and prognosis is particularly important [13].More studies have pointed out age, BMI, duration of surgery, and urinary diversion method as risk factors associated with the occurrence of postoperative complications, and more factors are not modifiable and not very accurate [14, 15]. A study concluded that untimely albumin supplementation is a high risk factor for complications in patients in the perioperative period [16]. The results of our study showed that low preoperative serum albumin level is the high risk factor for postoperative complications of bladder cancer (P<0.05). Serum albumin is one of the indicators of the nutritional status of the body, and its decrease can cause low immune function of the body, which can lead to symptoms such as delayed wound healing and infection [17]. This suggests that strict clinical monitoring of preoperative blood protein levels in patients with bladder cancer may help to reduce the incidence of postoperative complications.Notably, the results of this study also showed that high NRS score was also a high risk factor for postoperative complications of bladder cancer (P<0.05). This indicates that the nutritional status of the body is closely related to the incidence of postoperative complications in patients with malignant tumors [18, 19]. Further comparison of the severity of complications among patients with different NRS-2002 scores showed that the incidence of intestinal obstruction and the total incidence of complications in the NRS ≥3 group were significantly higher than those in the NRS <3 group (P<0.05), with no significant differences in other groups.NRS-2002 is the first nutritional risk screening tool developed on the basis of evidence-based medicine [20]. The scale was simple to operate and could be quickly evaluated in a short time through simple counseling. At the same time, the scale was less affected by subjective factors in the evaluation process, and the degree of acceptance by patients was high, so it had the advantage of high accuracy [21]. Karateke et al.’s study [22] demonstrated that the results of the clinical application of NRS-2002 were superior to other screening tools in terms of specificity and sensitivity. Raslan et al. [23] evaluated NRS-2002, MNA, and MUST nutritional screening in 705 patients and compared their ability to predict complications, mortality, and length of stay, respectively, and showed that NRS-2002 and MNA were superior to MUST in predicting clinical outcomes, while showing that NRS-2002 had better predictive power. This study further used logistic regression analysis to assess the relative risk coefficients of each clinical variable with the development of postoperative intestinal obstruction and found that low preoperative blood albumin levels and high NRS scores were high risk factors for the development of postoperative complications. This indicates that the NRS-2002 score has a good predictive value for complications after radical cystectomy combined with urethral diversion for bladder cancer.In conclusion, the NRS-2002 nutritional risk score has good predictive value for the incidence of postoperative complications in bladder cancer patients and provides a scientific basis for perioperative nutritional support, which is recommended to be promoted. However, considering the relatively small sample included in this study, more randomized controlled studies with multiple samples are still needed to support the study, which is the direction of further research in this topic.
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*Source: 2901189-2022-08-16.xml* | 2022 |
# Preparation of ACE Inhibitory Peptides fromMytilus coruscus Hydrolysate Using Uniform Design
**Authors:** Jin-Chao Wu; Jie Cheng; Xiao-lai Shi
**Journal:** BioMed Research International
(2013)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2013/290120
---
## Abstract
The angiotensin-I-converting enzyme (ACE) inhibitory peptides from mussel,Mytilus coruscus, were investigated and the variable factors, protease concentration, hydrolysis time, pH, and temperature, were optimized using Uniform Design, a new statistical experimental method. The results proved that the hydrolysate of alkali proteases had high ACE-inhibitory activity, especially the alkali protease E1. Optimization by Uniform Design showed that the best hydrolysis conditions for preparation of ACE-inhibitory peptides from Mytilus coruscus were protease concentration of 36.0 U/mL, hydrolysis time of 2.7 hours, pH 8.2, and Temperature at 59.5°C, respectively. The verification experiments under optimum conditions showed that the ACE-inhibitory activity (91.3%) were agreed closely with the predicted activity of 90.7%. The amino acid composition analysis of Mytilus coruscus ACE-inhibitory peptides proved that it had high percent of lysine, leucine, glycine, aspartic acid, and glutamic acid.
---
## Body
## 1. Introduction
About 30% of Americans are suffering hypertension and risk of cardiovascular disease development as an independent factor [1]. Hypertension is one of the most frequent chronic diseases and the incidence of this disease was increased in recent years. This disease affected about 65% of 65–75-year-old people in Western developed countries and its incidence was increased with age [2]. Angiotensin-I-converting enzyme (EC 3.4.15.1; ACE) is one of the metalloproteases and zinc is neccessary for its activity [3]. ACE cleaves dipeptides from oligopeptide’s carboxylic terminus, which plays important physiological role in blood pressure regulation [4]. Functional foods, containing ACE inhibitory peptides, may control blood pressure moderately. Many ACE inhibitory peptides in vitro have been isolated from various food derived proteins hydrolysate, such as milk [5], seed protein [6], blue mussel protein [7], bovine blood plasma [8], casein [9–11], zein [12], sardine [13], and tuna muscle [14]. ACE inhibitors have also been isolated from fermented foods, such as yoghourt [15], soy sauce [16], and soybean [17].Mytilus coruscus is one of the most important bivalves in both Chinese aquaculture and Chinese market [18]. Like other marine animals, some biactive peptides have been reported from Mytilus mussel protein, such as Mytilus inhibitory peptides [19], antimicrobial peptides [20], and anticoagulant peptide [21]. In addition, an ACE inhibitory peptide has been purified by chromatography method and identified from blue mussel sauce [7]. However, there was no report to obtain ACE inhibitory peptides from Mytilus coruscus mussel protein hydrolysate.Uniform Design method, a new experimental technique, is established together by Fang [22]. One of the most important advantages of the Uniform Design is that many factors and levels can be desined simulataneously. Uniform Design offers many convenient experimental tables [23]. But, unlike orthogonal design, the largest possible amount of levels for each factor can be allowed in Uniform Design, and so much so that the number of levels sometimes can be equal to the number of experiment runs [24]. As a statistical and experiment design technique, Uniform Design method has been successfully used for many experiments, especially in optimizing processes [23, 25, 26].In the present study, we want to optimize the hydrolysis conditions for achieving ACE inhibitory peptides fromMytilus coruscus muscle protein. Uniform Design method was applied to investigate the effects of protease concentration, hydrolysis time, hydrolysis temperature, and hydrolysis pH for the ACE inhibitory activity of hydrolysates from Mytilus coruscus.
## 2. Materials and Methods: ACE from Rabbit Lung
### 2.1. Materials
Mussel,Mytilus coruscus, was obtained from local aquatic product market (Hangzhou, China). Hippuryl-histidyl-leucine (HHL) was used as substrate of ACE. The HHL and ACE were purchased from local chemical company (Hangzhou, China). Five kinds of proteases (E1 to E5) were purchased from local food additives market (Hangzhou, China). The labeled optimum hydrolysis temperature and pH were shown in Table 1. All other reagents were analytical grade chemicals.Table 1
Hydrolysis conditions of the five proteases for producing ACE inhibitory peptides fromMytilus coruscus.
Protease
Temperature (°C)
pH
Time (h)
Protease E1
55
8.5
4.0
Protease E2
55
8.5
4.0
Protease E3
55
7.0
4.0
Protease E4
55
3.0
4.0
Protease E5
55
9.0
4.0
### 2.2. Preparation of Hydrolysates
Mussels,Mytilus coruscus, were washed with water to remove salt and other materials. The mussels were filleted and defatted with petroleum ether at 50°C by reflux extraction. Then the mussels were minced and mixed with distilled water (ratio of 1 : 10). The mixture was homogenate and then was boiled for 10 minutes to inactive the inner protease. Then the mixture was digested by five proteases at designed conditions, respectively. The pH of the reaction mixture was maintained stably by addition of either 1 N NaOH or HCl. Then, the mixture was incubated at 90°C for 10 min to terminate the reaction. After centrifugation (12,000 ×g, 4°C) for 10 min, the supernatant of the hydrolysate was collected for test the ACE inhibitory activity.
### 2.3. Determination of ACE Inhibitory Activity
The ACE inhibitory activity was determined by Wang et al. method [27] with slight modifications. All samples were diluted to the same protein content (1.0 mg/mL), which was determined by Biuret assay method [28]. Sample solution (10 μL) and ACE solution (50 units/mL, 30 μL) were mixed together. After the mixture being preincubated at 37°C for 5 min, 50 μL 7.6 mmol/L HHL substrate solution, which was solved in 50 mM sodium borate buffer and 6.8 mM NaCl at pH 8.3, was added. The mixture was incubated at 37°C for 25 min. The reaction was terminated after addition of 10 μL of 20% trifluoroacetic acid (TFA). The solution was filtrated through 0.22 μm membrane. The hippuric acid liberated by ACE was analyzed by reversed-phase high performance liquid chromatography (RP-HPLC) on an Inertsil ODS C18 (4.6 mm × 300 mm, 5 μm) column. The mobile phase was 30% methanol, which contained 0.1% TFA and 0.05% acetic acid. The flow rate was 1.0 mL/min. The UV detection wavelength was 228 nm. The ACE inhibitory activity was obtained from peak area and expressed as percent.
### 2.4. Choice of Protease
Five kinds of proteases were used for hydrolysis at their labeled optimum temperature and pH (shown in Table1). And the protease was added at 50 U per mL mixture and the hydrolysis time was fixed at 4.0 h. Then ACE inhibitory activity of hydrolysate was determined.
### 2.5. Uniform Design
A Uniform Design table of U7(74) was applied to determine the optimum hydrolysis conditions for obtaining ACE inhibitory activity peptides from Mytilus coruscus. The combination effects of independent variables X1 (protease concentration, U/mL), X2 (hydrolysis time, h), X3 (hydrolysis pH), and X4 (hydrolysis temperature, °C) at 7 variation levels in the hydrolysis process were shown in Table 2. A total of 21 combinations (three replicates) for four factors were chosen according to Uniform Design table. The actual values were also shown in Table 2. The responses functions (Y) were ACE inhibitory activity. These values were related to the variables by a second-order polynomial (1) below:
(1)Y=β0+∑i-1mβiXi+∑i-1mβiiXi2+∑i<jβijXiXj,
where Y is the predicted response. Xi and Xjare the independent variables. β0, βi, βii, and βij were the regression coefficients.Table 2
Uniform Design with the observed responses and predicted values.
Treat
Variable levels
ExperimentalYe
PredictedY
LRE (%)
X
1
X
2
X
3
X
4
1
25
2
7.0
60
87.98
±
3.14
88.08
4.8
2
50
4
8.5
55
77.21
±
2.18
77.49
3.7
3
75
6
6.5
50
36.92
±
1.91
36.83
5.0
4
100
1
8.0
45
26.54
±
1.47
26.28
2.1
5
125
3
6.0
40
39.46
±
2.31
39.02
3.6
6
150
5
7.5
35
58.13
±
2.35
58.47
4.4
7
175
7
9.0
65
20.17
±
1.17
20.46
3.2
X
1: protease concentration, U/mL; X2: hydrolysis time, h; X3: hydrolysis pH; X4: hydrolysis temperature, °C; experimental Ye was expressed as mean ± standard deviation of three determinations; LRE: largest relative error = 100×|the largest or the lowestYe-Y|/average Ye.The significance was evaluated by Student’st-test. The actual values were compared with model predictions. The optimum hydrolysis conditions were verified by additional triplicate experiments under these conditions.
### 2.6. Amino Acid Composition Analysis
The amino acid analyses were conducted by the method of Noreen and Salim [29]. Briefly, the 10 mL of the sample was hydrolyzed under vacuum by addition of 10 mL concentrated HCl at 110°C for 24 h. When the free amino acids were analyzed, the sample did not hydrolyzed by HCl. Amino acids were analyzed in a Shimadzu HPLC system by separation in an ion-exchange column and post-column reaction with ninhydrin.
### 2.7. Statistical Analysis
Data were expressed as means ± standard deviation of triplicate. A probability value ofP<0.05 was considered significantly.
## 2.1. Materials
Mussel,Mytilus coruscus, was obtained from local aquatic product market (Hangzhou, China). Hippuryl-histidyl-leucine (HHL) was used as substrate of ACE. The HHL and ACE were purchased from local chemical company (Hangzhou, China). Five kinds of proteases (E1 to E5) were purchased from local food additives market (Hangzhou, China). The labeled optimum hydrolysis temperature and pH were shown in Table 1. All other reagents were analytical grade chemicals.Table 1
Hydrolysis conditions of the five proteases for producing ACE inhibitory peptides fromMytilus coruscus.
Protease
Temperature (°C)
pH
Time (h)
Protease E1
55
8.5
4.0
Protease E2
55
8.5
4.0
Protease E3
55
7.0
4.0
Protease E4
55
3.0
4.0
Protease E5
55
9.0
4.0
## 2.2. Preparation of Hydrolysates
Mussels,Mytilus coruscus, were washed with water to remove salt and other materials. The mussels were filleted and defatted with petroleum ether at 50°C by reflux extraction. Then the mussels were minced and mixed with distilled water (ratio of 1 : 10). The mixture was homogenate and then was boiled for 10 minutes to inactive the inner protease. Then the mixture was digested by five proteases at designed conditions, respectively. The pH of the reaction mixture was maintained stably by addition of either 1 N NaOH or HCl. Then, the mixture was incubated at 90°C for 10 min to terminate the reaction. After centrifugation (12,000 ×g, 4°C) for 10 min, the supernatant of the hydrolysate was collected for test the ACE inhibitory activity.
## 2.3. Determination of ACE Inhibitory Activity
The ACE inhibitory activity was determined by Wang et al. method [27] with slight modifications. All samples were diluted to the same protein content (1.0 mg/mL), which was determined by Biuret assay method [28]. Sample solution (10 μL) and ACE solution (50 units/mL, 30 μL) were mixed together. After the mixture being preincubated at 37°C for 5 min, 50 μL 7.6 mmol/L HHL substrate solution, which was solved in 50 mM sodium borate buffer and 6.8 mM NaCl at pH 8.3, was added. The mixture was incubated at 37°C for 25 min. The reaction was terminated after addition of 10 μL of 20% trifluoroacetic acid (TFA). The solution was filtrated through 0.22 μm membrane. The hippuric acid liberated by ACE was analyzed by reversed-phase high performance liquid chromatography (RP-HPLC) on an Inertsil ODS C18 (4.6 mm × 300 mm, 5 μm) column. The mobile phase was 30% methanol, which contained 0.1% TFA and 0.05% acetic acid. The flow rate was 1.0 mL/min. The UV detection wavelength was 228 nm. The ACE inhibitory activity was obtained from peak area and expressed as percent.
## 2.4. Choice of Protease
Five kinds of proteases were used for hydrolysis at their labeled optimum temperature and pH (shown in Table1). And the protease was added at 50 U per mL mixture and the hydrolysis time was fixed at 4.0 h. Then ACE inhibitory activity of hydrolysate was determined.
## 2.5. Uniform Design
A Uniform Design table of U7(74) was applied to determine the optimum hydrolysis conditions for obtaining ACE inhibitory activity peptides from Mytilus coruscus. The combination effects of independent variables X1 (protease concentration, U/mL), X2 (hydrolysis time, h), X3 (hydrolysis pH), and X4 (hydrolysis temperature, °C) at 7 variation levels in the hydrolysis process were shown in Table 2. A total of 21 combinations (three replicates) for four factors were chosen according to Uniform Design table. The actual values were also shown in Table 2. The responses functions (Y) were ACE inhibitory activity. These values were related to the variables by a second-order polynomial (1) below:
(1)Y=β0+∑i-1mβiXi+∑i-1mβiiXi2+∑i<jβijXiXj,
where Y is the predicted response. Xi and Xjare the independent variables. β0, βi, βii, and βij were the regression coefficients.Table 2
Uniform Design with the observed responses and predicted values.
Treat
Variable levels
ExperimentalYe
PredictedY
LRE (%)
X
1
X
2
X
3
X
4
1
25
2
7.0
60
87.98
±
3.14
88.08
4.8
2
50
4
8.5
55
77.21
±
2.18
77.49
3.7
3
75
6
6.5
50
36.92
±
1.91
36.83
5.0
4
100
1
8.0
45
26.54
±
1.47
26.28
2.1
5
125
3
6.0
40
39.46
±
2.31
39.02
3.6
6
150
5
7.5
35
58.13
±
2.35
58.47
4.4
7
175
7
9.0
65
20.17
±
1.17
20.46
3.2
X
1: protease concentration, U/mL; X2: hydrolysis time, h; X3: hydrolysis pH; X4: hydrolysis temperature, °C; experimental Ye was expressed as mean ± standard deviation of three determinations; LRE: largest relative error = 100×|the largest or the lowestYe-Y|/average Ye.The significance was evaluated by Student’st-test. The actual values were compared with model predictions. The optimum hydrolysis conditions were verified by additional triplicate experiments under these conditions.
## 2.6. Amino Acid Composition Analysis
The amino acid analyses were conducted by the method of Noreen and Salim [29]. Briefly, the 10 mL of the sample was hydrolyzed under vacuum by addition of 10 mL concentrated HCl at 110°C for 24 h. When the free amino acids were analyzed, the sample did not hydrolyzed by HCl. Amino acids were analyzed in a Shimadzu HPLC system by separation in an ion-exchange column and post-column reaction with ninhydrin.
## 2.7. Statistical Analysis
Data were expressed as means ± standard deviation of triplicate. A probability value ofP<0.05 was considered significantly.
## 3. Results and Discussion
### 3.1. Choice of Protease
ACE inhibitory peptides generally were short peptides and enzymatic hydrolysis of food derived protein was one of important measures to obtain ACE inhibitory peptides. A lot of ACE inhibitory peptides had been reported from food derived proteins hydrolysates. In this investigation, five kinds of commercial proteases, including three alkali proteases, one neutral protease, and one acid protease, were chosen to obtain ACE inhibitory peptides fromMytilus coruscus. The ACE inhibitory activity of various enzymatic hydrolysates was shown in Figure 1. From the results, it was shown that the hydrolysate produced by alkali protease E1 had the highest ACE inhibitory activity. In addition, alkali proteases (E1, E2 and E3) were more effective for hydrolysis Mytilus coruscus mussel protein to obtain ACE inhibitory peptides than other two proteases (E4 and E5). Therefore, alkali protease E1 was chosen to next experiments to optimize hydrolysis conditions for producing ACE inhibitory peptides from Mytilus coruscus.Figure 1
The ACE inhibitory activity of hydrolysates by five commercial proteases. The data was expressed as mean ± standard deviation of three determinations. Means sharing the same lowercase letter was not significantly different atP<0.05.
### 3.2. Data Analysis of Uniform Design
A regression analysis was conducted to fit a mathematical model to the experimental data. The results of regression analysis were summarized (Table2), and a regression equation was given in
(2)Y=0.1023+0.2626X1+0.1083X2+0.1100X3+0.1592X4+0.0114X12+0.0937X22+0.1751X32+0.0020X42-0.1404X1X2-0.0829X1X3-0.0314X1X4+0.1561X1X3+0.2367X2X4+0.1960X3X4.The statistical analysis indicated the predicted model was adequate, possessing significantP value (P=0.047<0.05) and satisfactory values of the regression coefficient R2 (R2=0.9712) for the response. The high regression coefficient make clear that the experimental values of the ACE inhibitory activity agreed with predicted values, which meant that the predicted model seemed to reasonably represent the observed values. The largest relative error of predicted value was less than 5% shown in Table 2. The significance was tested by Student’s t-test and P value in Table 3. It was shown that temperature, pH, and protease added quantity affected significantly the ACE inhibitory activity of hydrolysates.Table 3
Significance of regression coefficient for the ACE inhibitory activity.
Variables
Standard error
Computedt value
Significance levelP value
X
1
0.6374
5.2987
0.0501
X
2
1.0897
0.9872
0.4619
X
3
1.2345
5.6426
0.0478
X
4
0.8766
7.2358
0.0342
X
1
X
2
−0.9234
4.4760
0.0323
X
1
X
3
−0.8768
3.9765
0.05926
X
1
X
4
−1.0236
7.0626
0.0355
X
2
X
3
0.7931
3.2617
0.0635
X
2
X
4
0.8942
6.2932
0.0433
X
3
X
4
0.6745
6.7869
0.0408
X
1
2
0.5679
5.4876
0.0496
X
2
2
0.9236
1.2381
0.3763
X
3
2
1.0111
4.2635
0.0543
X
4
2
0.8765
6.9367
0.0374
### 3.3. Verification Experiments
Then the optimum hydrolysis conditions of protease E1 and the prediction ACE inhibitory activity were obtained by (2). The optimum hydrolysis conditions of protease E1 were protease concentration (X1): 36.0 U/mL; hydrolysis time (X2): 2.7 h; hydrolysis pH (X3): 8.2; hydrolysis temperature (X4): 59.5°C. The predicted ACE inhibitory activity was 90.7% at optimum hydrolysis conditions. Under this optimum hydrolysis conditions, other three verification experiments were conducted and the average actual ACE inhibitory activity was 91.3%, which was in agreement with the predicted values of 90.7%.
### 3.4. Amino Acid Composition
The compositions of free amino acid and amino acid in peptides of the ACE inhibitory peptides fromMytilus coruscus were determined and the results were shown in Table 4. From the results, it was seen that the ACE inhibitory peptides solution had only a few free amino acid content, not equal with amino acid in peptides. The peptides, not amino acid, might contributed to high activity. The ACE inhibitory peptides had high percent of glutamic acid, taking 0.578 mmol/g, which could improve the breath ability of brain cell and be favorable to the expulsion of ammonia in brain and regulation of body metabolism, and these phases could impact the blood pressure directly. Also the ACE inhibitory peptides had high percent of lysine, leucine, glycine, and aspartic acid. These amino acids might play crucial role in the inhibitory activity. Cheung et al. [30] reported that dipeptides having hydrophobic amino acids such as valine (Val) and isoleucine (Ile) at the amino temerninus have higher ACE inhibitory activities. The amino acids, such as lysine, leucine, glycine, aspartic acid, and glutamic acid, were key constitutes with tall frequency appeared among many reported ACE inhibitory peptides [31–35].Table 4
Amino acid compositions of ACE inhibitory peptides fromMytilus coruscus.
Amino acid
Free amino acid content (mmol/g)
Amino acid in peptides (mmol/g)
Aspartic acid
0.009
0.449
Threonine
0.016
0.209
Serine
0.012
0.246
Glutamatic acid
0.013
0.578
Glycine
0.052
0.565
Alanine
0.027
0.558
Valine
0.009
0.155
Methionine
0.013
0.359
Isoleucine
0.018
0.157
Leucine
0.069
0.336
Tyrosine
0.000
0.089
Phenylalanine
0.020
0.146
Histidine
0.104
0.106
Lysine
0.068
0.419
Arginine
0.029
0.230
Cysteine
Not detected
Not detected
Proline
Not detected
Not detected
Tryphtophan
Not detected
Not detected
## 3.1. Choice of Protease
ACE inhibitory peptides generally were short peptides and enzymatic hydrolysis of food derived protein was one of important measures to obtain ACE inhibitory peptides. A lot of ACE inhibitory peptides had been reported from food derived proteins hydrolysates. In this investigation, five kinds of commercial proteases, including three alkali proteases, one neutral protease, and one acid protease, were chosen to obtain ACE inhibitory peptides fromMytilus coruscus. The ACE inhibitory activity of various enzymatic hydrolysates was shown in Figure 1. From the results, it was shown that the hydrolysate produced by alkali protease E1 had the highest ACE inhibitory activity. In addition, alkali proteases (E1, E2 and E3) were more effective for hydrolysis Mytilus coruscus mussel protein to obtain ACE inhibitory peptides than other two proteases (E4 and E5). Therefore, alkali protease E1 was chosen to next experiments to optimize hydrolysis conditions for producing ACE inhibitory peptides from Mytilus coruscus.Figure 1
The ACE inhibitory activity of hydrolysates by five commercial proteases. The data was expressed as mean ± standard deviation of three determinations. Means sharing the same lowercase letter was not significantly different atP<0.05.
## 3.2. Data Analysis of Uniform Design
A regression analysis was conducted to fit a mathematical model to the experimental data. The results of regression analysis were summarized (Table2), and a regression equation was given in
(2)Y=0.1023+0.2626X1+0.1083X2+0.1100X3+0.1592X4+0.0114X12+0.0937X22+0.1751X32+0.0020X42-0.1404X1X2-0.0829X1X3-0.0314X1X4+0.1561X1X3+0.2367X2X4+0.1960X3X4.The statistical analysis indicated the predicted model was adequate, possessing significantP value (P=0.047<0.05) and satisfactory values of the regression coefficient R2 (R2=0.9712) for the response. The high regression coefficient make clear that the experimental values of the ACE inhibitory activity agreed with predicted values, which meant that the predicted model seemed to reasonably represent the observed values. The largest relative error of predicted value was less than 5% shown in Table 2. The significance was tested by Student’s t-test and P value in Table 3. It was shown that temperature, pH, and protease added quantity affected significantly the ACE inhibitory activity of hydrolysates.Table 3
Significance of regression coefficient for the ACE inhibitory activity.
Variables
Standard error
Computedt value
Significance levelP value
X
1
0.6374
5.2987
0.0501
X
2
1.0897
0.9872
0.4619
X
3
1.2345
5.6426
0.0478
X
4
0.8766
7.2358
0.0342
X
1
X
2
−0.9234
4.4760
0.0323
X
1
X
3
−0.8768
3.9765
0.05926
X
1
X
4
−1.0236
7.0626
0.0355
X
2
X
3
0.7931
3.2617
0.0635
X
2
X
4
0.8942
6.2932
0.0433
X
3
X
4
0.6745
6.7869
0.0408
X
1
2
0.5679
5.4876
0.0496
X
2
2
0.9236
1.2381
0.3763
X
3
2
1.0111
4.2635
0.0543
X
4
2
0.8765
6.9367
0.0374
## 3.3. Verification Experiments
Then the optimum hydrolysis conditions of protease E1 and the prediction ACE inhibitory activity were obtained by (2). The optimum hydrolysis conditions of protease E1 were protease concentration (X1): 36.0 U/mL; hydrolysis time (X2): 2.7 h; hydrolysis pH (X3): 8.2; hydrolysis temperature (X4): 59.5°C. The predicted ACE inhibitory activity was 90.7% at optimum hydrolysis conditions. Under this optimum hydrolysis conditions, other three verification experiments were conducted and the average actual ACE inhibitory activity was 91.3%, which was in agreement with the predicted values of 90.7%.
## 3.4. Amino Acid Composition
The compositions of free amino acid and amino acid in peptides of the ACE inhibitory peptides fromMytilus coruscus were determined and the results were shown in Table 4. From the results, it was seen that the ACE inhibitory peptides solution had only a few free amino acid content, not equal with amino acid in peptides. The peptides, not amino acid, might contributed to high activity. The ACE inhibitory peptides had high percent of glutamic acid, taking 0.578 mmol/g, which could improve the breath ability of brain cell and be favorable to the expulsion of ammonia in brain and regulation of body metabolism, and these phases could impact the blood pressure directly. Also the ACE inhibitory peptides had high percent of lysine, leucine, glycine, and aspartic acid. These amino acids might play crucial role in the inhibitory activity. Cheung et al. [30] reported that dipeptides having hydrophobic amino acids such as valine (Val) and isoleucine (Ile) at the amino temerninus have higher ACE inhibitory activities. The amino acids, such as lysine, leucine, glycine, aspartic acid, and glutamic acid, were key constitutes with tall frequency appeared among many reported ACE inhibitory peptides [31–35].Table 4
Amino acid compositions of ACE inhibitory peptides fromMytilus coruscus.
Amino acid
Free amino acid content (mmol/g)
Amino acid in peptides (mmol/g)
Aspartic acid
0.009
0.449
Threonine
0.016
0.209
Serine
0.012
0.246
Glutamatic acid
0.013
0.578
Glycine
0.052
0.565
Alanine
0.027
0.558
Valine
0.009
0.155
Methionine
0.013
0.359
Isoleucine
0.018
0.157
Leucine
0.069
0.336
Tyrosine
0.000
0.089
Phenylalanine
0.020
0.146
Histidine
0.104
0.106
Lysine
0.068
0.419
Arginine
0.029
0.230
Cysteine
Not detected
Not detected
Proline
Not detected
Not detected
Tryphtophan
Not detected
Not detected
## 4. Conclusions
Alkali protease was a good choice for hydrolyzingMytilus coruscus protein for producing ACE inhibitory peptides. The factors, including protease concentration, hydrolysis time, hydrolysis pH, and temperature, affected the ACE inhibitory peptides of hydrolysates. Uniform Design was chosen to investigate the effects of preceding variables on ACE inhibitory activity. And the best hydrolysis conditions of alkali protease E1 optimized by Uniform Design were protease concentration of 36.0 U/mL, hydrolysis time of 2.7 hours, pH 8.2, temperature at 59.5°C. The optimal predicted ACE inhibitory activity of 90.7% was obtained at the optimum conditions. The experimental activity (91.3%) under optimized conditions was agreed closely with the predicted activity. The amino acid composition analysis of the ACE inhibitory peptides proved that it had high percent of lysine, leucine, glycine, aspartic acid, and glutamic acid. It was suggested that the ACE inhibitory peptides derived from Mytilus coruscus could be utilized to develop nutraceuticals and pharmaceuticals.
---
*Source: 290120-2012-12-26.xml* | 290120-2012-12-26_290120-2012-12-26.md | 27,019 | Preparation of ACE Inhibitory Peptides fromMytilus coruscus Hydrolysate Using Uniform Design | Jin-Chao Wu; Jie Cheng; Xiao-lai Shi | BioMed Research International
(2013) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2013/290120 | 290120-2012-12-26.xml | ---
## Abstract
The angiotensin-I-converting enzyme (ACE) inhibitory peptides from mussel,Mytilus coruscus, were investigated and the variable factors, protease concentration, hydrolysis time, pH, and temperature, were optimized using Uniform Design, a new statistical experimental method. The results proved that the hydrolysate of alkali proteases had high ACE-inhibitory activity, especially the alkali protease E1. Optimization by Uniform Design showed that the best hydrolysis conditions for preparation of ACE-inhibitory peptides from Mytilus coruscus were protease concentration of 36.0 U/mL, hydrolysis time of 2.7 hours, pH 8.2, and Temperature at 59.5°C, respectively. The verification experiments under optimum conditions showed that the ACE-inhibitory activity (91.3%) were agreed closely with the predicted activity of 90.7%. The amino acid composition analysis of Mytilus coruscus ACE-inhibitory peptides proved that it had high percent of lysine, leucine, glycine, aspartic acid, and glutamic acid.
---
## Body
## 1. Introduction
About 30% of Americans are suffering hypertension and risk of cardiovascular disease development as an independent factor [1]. Hypertension is one of the most frequent chronic diseases and the incidence of this disease was increased in recent years. This disease affected about 65% of 65–75-year-old people in Western developed countries and its incidence was increased with age [2]. Angiotensin-I-converting enzyme (EC 3.4.15.1; ACE) is one of the metalloproteases and zinc is neccessary for its activity [3]. ACE cleaves dipeptides from oligopeptide’s carboxylic terminus, which plays important physiological role in blood pressure regulation [4]. Functional foods, containing ACE inhibitory peptides, may control blood pressure moderately. Many ACE inhibitory peptides in vitro have been isolated from various food derived proteins hydrolysate, such as milk [5], seed protein [6], blue mussel protein [7], bovine blood plasma [8], casein [9–11], zein [12], sardine [13], and tuna muscle [14]. ACE inhibitors have also been isolated from fermented foods, such as yoghourt [15], soy sauce [16], and soybean [17].Mytilus coruscus is one of the most important bivalves in both Chinese aquaculture and Chinese market [18]. Like other marine animals, some biactive peptides have been reported from Mytilus mussel protein, such as Mytilus inhibitory peptides [19], antimicrobial peptides [20], and anticoagulant peptide [21]. In addition, an ACE inhibitory peptide has been purified by chromatography method and identified from blue mussel sauce [7]. However, there was no report to obtain ACE inhibitory peptides from Mytilus coruscus mussel protein hydrolysate.Uniform Design method, a new experimental technique, is established together by Fang [22]. One of the most important advantages of the Uniform Design is that many factors and levels can be desined simulataneously. Uniform Design offers many convenient experimental tables [23]. But, unlike orthogonal design, the largest possible amount of levels for each factor can be allowed in Uniform Design, and so much so that the number of levels sometimes can be equal to the number of experiment runs [24]. As a statistical and experiment design technique, Uniform Design method has been successfully used for many experiments, especially in optimizing processes [23, 25, 26].In the present study, we want to optimize the hydrolysis conditions for achieving ACE inhibitory peptides fromMytilus coruscus muscle protein. Uniform Design method was applied to investigate the effects of protease concentration, hydrolysis time, hydrolysis temperature, and hydrolysis pH for the ACE inhibitory activity of hydrolysates from Mytilus coruscus.
## 2. Materials and Methods: ACE from Rabbit Lung
### 2.1. Materials
Mussel,Mytilus coruscus, was obtained from local aquatic product market (Hangzhou, China). Hippuryl-histidyl-leucine (HHL) was used as substrate of ACE. The HHL and ACE were purchased from local chemical company (Hangzhou, China). Five kinds of proteases (E1 to E5) were purchased from local food additives market (Hangzhou, China). The labeled optimum hydrolysis temperature and pH were shown in Table 1. All other reagents were analytical grade chemicals.Table 1
Hydrolysis conditions of the five proteases for producing ACE inhibitory peptides fromMytilus coruscus.
Protease
Temperature (°C)
pH
Time (h)
Protease E1
55
8.5
4.0
Protease E2
55
8.5
4.0
Protease E3
55
7.0
4.0
Protease E4
55
3.0
4.0
Protease E5
55
9.0
4.0
### 2.2. Preparation of Hydrolysates
Mussels,Mytilus coruscus, were washed with water to remove salt and other materials. The mussels were filleted and defatted with petroleum ether at 50°C by reflux extraction. Then the mussels were minced and mixed with distilled water (ratio of 1 : 10). The mixture was homogenate and then was boiled for 10 minutes to inactive the inner protease. Then the mixture was digested by five proteases at designed conditions, respectively. The pH of the reaction mixture was maintained stably by addition of either 1 N NaOH or HCl. Then, the mixture was incubated at 90°C for 10 min to terminate the reaction. After centrifugation (12,000 ×g, 4°C) for 10 min, the supernatant of the hydrolysate was collected for test the ACE inhibitory activity.
### 2.3. Determination of ACE Inhibitory Activity
The ACE inhibitory activity was determined by Wang et al. method [27] with slight modifications. All samples were diluted to the same protein content (1.0 mg/mL), which was determined by Biuret assay method [28]. Sample solution (10 μL) and ACE solution (50 units/mL, 30 μL) were mixed together. After the mixture being preincubated at 37°C for 5 min, 50 μL 7.6 mmol/L HHL substrate solution, which was solved in 50 mM sodium borate buffer and 6.8 mM NaCl at pH 8.3, was added. The mixture was incubated at 37°C for 25 min. The reaction was terminated after addition of 10 μL of 20% trifluoroacetic acid (TFA). The solution was filtrated through 0.22 μm membrane. The hippuric acid liberated by ACE was analyzed by reversed-phase high performance liquid chromatography (RP-HPLC) on an Inertsil ODS C18 (4.6 mm × 300 mm, 5 μm) column. The mobile phase was 30% methanol, which contained 0.1% TFA and 0.05% acetic acid. The flow rate was 1.0 mL/min. The UV detection wavelength was 228 nm. The ACE inhibitory activity was obtained from peak area and expressed as percent.
### 2.4. Choice of Protease
Five kinds of proteases were used for hydrolysis at their labeled optimum temperature and pH (shown in Table1). And the protease was added at 50 U per mL mixture and the hydrolysis time was fixed at 4.0 h. Then ACE inhibitory activity of hydrolysate was determined.
### 2.5. Uniform Design
A Uniform Design table of U7(74) was applied to determine the optimum hydrolysis conditions for obtaining ACE inhibitory activity peptides from Mytilus coruscus. The combination effects of independent variables X1 (protease concentration, U/mL), X2 (hydrolysis time, h), X3 (hydrolysis pH), and X4 (hydrolysis temperature, °C) at 7 variation levels in the hydrolysis process were shown in Table 2. A total of 21 combinations (three replicates) for four factors were chosen according to Uniform Design table. The actual values were also shown in Table 2. The responses functions (Y) were ACE inhibitory activity. These values were related to the variables by a second-order polynomial (1) below:
(1)Y=β0+∑i-1mβiXi+∑i-1mβiiXi2+∑i<jβijXiXj,
where Y is the predicted response. Xi and Xjare the independent variables. β0, βi, βii, and βij were the regression coefficients.Table 2
Uniform Design with the observed responses and predicted values.
Treat
Variable levels
ExperimentalYe
PredictedY
LRE (%)
X
1
X
2
X
3
X
4
1
25
2
7.0
60
87.98
±
3.14
88.08
4.8
2
50
4
8.5
55
77.21
±
2.18
77.49
3.7
3
75
6
6.5
50
36.92
±
1.91
36.83
5.0
4
100
1
8.0
45
26.54
±
1.47
26.28
2.1
5
125
3
6.0
40
39.46
±
2.31
39.02
3.6
6
150
5
7.5
35
58.13
±
2.35
58.47
4.4
7
175
7
9.0
65
20.17
±
1.17
20.46
3.2
X
1: protease concentration, U/mL; X2: hydrolysis time, h; X3: hydrolysis pH; X4: hydrolysis temperature, °C; experimental Ye was expressed as mean ± standard deviation of three determinations; LRE: largest relative error = 100×|the largest or the lowestYe-Y|/average Ye.The significance was evaluated by Student’st-test. The actual values were compared with model predictions. The optimum hydrolysis conditions were verified by additional triplicate experiments under these conditions.
### 2.6. Amino Acid Composition Analysis
The amino acid analyses were conducted by the method of Noreen and Salim [29]. Briefly, the 10 mL of the sample was hydrolyzed under vacuum by addition of 10 mL concentrated HCl at 110°C for 24 h. When the free amino acids were analyzed, the sample did not hydrolyzed by HCl. Amino acids were analyzed in a Shimadzu HPLC system by separation in an ion-exchange column and post-column reaction with ninhydrin.
### 2.7. Statistical Analysis
Data were expressed as means ± standard deviation of triplicate. A probability value ofP<0.05 was considered significantly.
## 2.1. Materials
Mussel,Mytilus coruscus, was obtained from local aquatic product market (Hangzhou, China). Hippuryl-histidyl-leucine (HHL) was used as substrate of ACE. The HHL and ACE were purchased from local chemical company (Hangzhou, China). Five kinds of proteases (E1 to E5) were purchased from local food additives market (Hangzhou, China). The labeled optimum hydrolysis temperature and pH were shown in Table 1. All other reagents were analytical grade chemicals.Table 1
Hydrolysis conditions of the five proteases for producing ACE inhibitory peptides fromMytilus coruscus.
Protease
Temperature (°C)
pH
Time (h)
Protease E1
55
8.5
4.0
Protease E2
55
8.5
4.0
Protease E3
55
7.0
4.0
Protease E4
55
3.0
4.0
Protease E5
55
9.0
4.0
## 2.2. Preparation of Hydrolysates
Mussels,Mytilus coruscus, were washed with water to remove salt and other materials. The mussels were filleted and defatted with petroleum ether at 50°C by reflux extraction. Then the mussels were minced and mixed with distilled water (ratio of 1 : 10). The mixture was homogenate and then was boiled for 10 minutes to inactive the inner protease. Then the mixture was digested by five proteases at designed conditions, respectively. The pH of the reaction mixture was maintained stably by addition of either 1 N NaOH or HCl. Then, the mixture was incubated at 90°C for 10 min to terminate the reaction. After centrifugation (12,000 ×g, 4°C) for 10 min, the supernatant of the hydrolysate was collected for test the ACE inhibitory activity.
## 2.3. Determination of ACE Inhibitory Activity
The ACE inhibitory activity was determined by Wang et al. method [27] with slight modifications. All samples were diluted to the same protein content (1.0 mg/mL), which was determined by Biuret assay method [28]. Sample solution (10 μL) and ACE solution (50 units/mL, 30 μL) were mixed together. After the mixture being preincubated at 37°C for 5 min, 50 μL 7.6 mmol/L HHL substrate solution, which was solved in 50 mM sodium borate buffer and 6.8 mM NaCl at pH 8.3, was added. The mixture was incubated at 37°C for 25 min. The reaction was terminated after addition of 10 μL of 20% trifluoroacetic acid (TFA). The solution was filtrated through 0.22 μm membrane. The hippuric acid liberated by ACE was analyzed by reversed-phase high performance liquid chromatography (RP-HPLC) on an Inertsil ODS C18 (4.6 mm × 300 mm, 5 μm) column. The mobile phase was 30% methanol, which contained 0.1% TFA and 0.05% acetic acid. The flow rate was 1.0 mL/min. The UV detection wavelength was 228 nm. The ACE inhibitory activity was obtained from peak area and expressed as percent.
## 2.4. Choice of Protease
Five kinds of proteases were used for hydrolysis at their labeled optimum temperature and pH (shown in Table1). And the protease was added at 50 U per mL mixture and the hydrolysis time was fixed at 4.0 h. Then ACE inhibitory activity of hydrolysate was determined.
## 2.5. Uniform Design
A Uniform Design table of U7(74) was applied to determine the optimum hydrolysis conditions for obtaining ACE inhibitory activity peptides from Mytilus coruscus. The combination effects of independent variables X1 (protease concentration, U/mL), X2 (hydrolysis time, h), X3 (hydrolysis pH), and X4 (hydrolysis temperature, °C) at 7 variation levels in the hydrolysis process were shown in Table 2. A total of 21 combinations (three replicates) for four factors were chosen according to Uniform Design table. The actual values were also shown in Table 2. The responses functions (Y) were ACE inhibitory activity. These values were related to the variables by a second-order polynomial (1) below:
(1)Y=β0+∑i-1mβiXi+∑i-1mβiiXi2+∑i<jβijXiXj,
where Y is the predicted response. Xi and Xjare the independent variables. β0, βi, βii, and βij were the regression coefficients.Table 2
Uniform Design with the observed responses and predicted values.
Treat
Variable levels
ExperimentalYe
PredictedY
LRE (%)
X
1
X
2
X
3
X
4
1
25
2
7.0
60
87.98
±
3.14
88.08
4.8
2
50
4
8.5
55
77.21
±
2.18
77.49
3.7
3
75
6
6.5
50
36.92
±
1.91
36.83
5.0
4
100
1
8.0
45
26.54
±
1.47
26.28
2.1
5
125
3
6.0
40
39.46
±
2.31
39.02
3.6
6
150
5
7.5
35
58.13
±
2.35
58.47
4.4
7
175
7
9.0
65
20.17
±
1.17
20.46
3.2
X
1: protease concentration, U/mL; X2: hydrolysis time, h; X3: hydrolysis pH; X4: hydrolysis temperature, °C; experimental Ye was expressed as mean ± standard deviation of three determinations; LRE: largest relative error = 100×|the largest or the lowestYe-Y|/average Ye.The significance was evaluated by Student’st-test. The actual values were compared with model predictions. The optimum hydrolysis conditions were verified by additional triplicate experiments under these conditions.
## 2.6. Amino Acid Composition Analysis
The amino acid analyses were conducted by the method of Noreen and Salim [29]. Briefly, the 10 mL of the sample was hydrolyzed under vacuum by addition of 10 mL concentrated HCl at 110°C for 24 h. When the free amino acids were analyzed, the sample did not hydrolyzed by HCl. Amino acids were analyzed in a Shimadzu HPLC system by separation in an ion-exchange column and post-column reaction with ninhydrin.
## 2.7. Statistical Analysis
Data were expressed as means ± standard deviation of triplicate. A probability value ofP<0.05 was considered significantly.
## 3. Results and Discussion
### 3.1. Choice of Protease
ACE inhibitory peptides generally were short peptides and enzymatic hydrolysis of food derived protein was one of important measures to obtain ACE inhibitory peptides. A lot of ACE inhibitory peptides had been reported from food derived proteins hydrolysates. In this investigation, five kinds of commercial proteases, including three alkali proteases, one neutral protease, and one acid protease, were chosen to obtain ACE inhibitory peptides fromMytilus coruscus. The ACE inhibitory activity of various enzymatic hydrolysates was shown in Figure 1. From the results, it was shown that the hydrolysate produced by alkali protease E1 had the highest ACE inhibitory activity. In addition, alkali proteases (E1, E2 and E3) were more effective for hydrolysis Mytilus coruscus mussel protein to obtain ACE inhibitory peptides than other two proteases (E4 and E5). Therefore, alkali protease E1 was chosen to next experiments to optimize hydrolysis conditions for producing ACE inhibitory peptides from Mytilus coruscus.Figure 1
The ACE inhibitory activity of hydrolysates by five commercial proteases. The data was expressed as mean ± standard deviation of three determinations. Means sharing the same lowercase letter was not significantly different atP<0.05.
### 3.2. Data Analysis of Uniform Design
A regression analysis was conducted to fit a mathematical model to the experimental data. The results of regression analysis were summarized (Table2), and a regression equation was given in
(2)Y=0.1023+0.2626X1+0.1083X2+0.1100X3+0.1592X4+0.0114X12+0.0937X22+0.1751X32+0.0020X42-0.1404X1X2-0.0829X1X3-0.0314X1X4+0.1561X1X3+0.2367X2X4+0.1960X3X4.The statistical analysis indicated the predicted model was adequate, possessing significantP value (P=0.047<0.05) and satisfactory values of the regression coefficient R2 (R2=0.9712) for the response. The high regression coefficient make clear that the experimental values of the ACE inhibitory activity agreed with predicted values, which meant that the predicted model seemed to reasonably represent the observed values. The largest relative error of predicted value was less than 5% shown in Table 2. The significance was tested by Student’s t-test and P value in Table 3. It was shown that temperature, pH, and protease added quantity affected significantly the ACE inhibitory activity of hydrolysates.Table 3
Significance of regression coefficient for the ACE inhibitory activity.
Variables
Standard error
Computedt value
Significance levelP value
X
1
0.6374
5.2987
0.0501
X
2
1.0897
0.9872
0.4619
X
3
1.2345
5.6426
0.0478
X
4
0.8766
7.2358
0.0342
X
1
X
2
−0.9234
4.4760
0.0323
X
1
X
3
−0.8768
3.9765
0.05926
X
1
X
4
−1.0236
7.0626
0.0355
X
2
X
3
0.7931
3.2617
0.0635
X
2
X
4
0.8942
6.2932
0.0433
X
3
X
4
0.6745
6.7869
0.0408
X
1
2
0.5679
5.4876
0.0496
X
2
2
0.9236
1.2381
0.3763
X
3
2
1.0111
4.2635
0.0543
X
4
2
0.8765
6.9367
0.0374
### 3.3. Verification Experiments
Then the optimum hydrolysis conditions of protease E1 and the prediction ACE inhibitory activity were obtained by (2). The optimum hydrolysis conditions of protease E1 were protease concentration (X1): 36.0 U/mL; hydrolysis time (X2): 2.7 h; hydrolysis pH (X3): 8.2; hydrolysis temperature (X4): 59.5°C. The predicted ACE inhibitory activity was 90.7% at optimum hydrolysis conditions. Under this optimum hydrolysis conditions, other three verification experiments were conducted and the average actual ACE inhibitory activity was 91.3%, which was in agreement with the predicted values of 90.7%.
### 3.4. Amino Acid Composition
The compositions of free amino acid and amino acid in peptides of the ACE inhibitory peptides fromMytilus coruscus were determined and the results were shown in Table 4. From the results, it was seen that the ACE inhibitory peptides solution had only a few free amino acid content, not equal with amino acid in peptides. The peptides, not amino acid, might contributed to high activity. The ACE inhibitory peptides had high percent of glutamic acid, taking 0.578 mmol/g, which could improve the breath ability of brain cell and be favorable to the expulsion of ammonia in brain and regulation of body metabolism, and these phases could impact the blood pressure directly. Also the ACE inhibitory peptides had high percent of lysine, leucine, glycine, and aspartic acid. These amino acids might play crucial role in the inhibitory activity. Cheung et al. [30] reported that dipeptides having hydrophobic amino acids such as valine (Val) and isoleucine (Ile) at the amino temerninus have higher ACE inhibitory activities. The amino acids, such as lysine, leucine, glycine, aspartic acid, and glutamic acid, were key constitutes with tall frequency appeared among many reported ACE inhibitory peptides [31–35].Table 4
Amino acid compositions of ACE inhibitory peptides fromMytilus coruscus.
Amino acid
Free amino acid content (mmol/g)
Amino acid in peptides (mmol/g)
Aspartic acid
0.009
0.449
Threonine
0.016
0.209
Serine
0.012
0.246
Glutamatic acid
0.013
0.578
Glycine
0.052
0.565
Alanine
0.027
0.558
Valine
0.009
0.155
Methionine
0.013
0.359
Isoleucine
0.018
0.157
Leucine
0.069
0.336
Tyrosine
0.000
0.089
Phenylalanine
0.020
0.146
Histidine
0.104
0.106
Lysine
0.068
0.419
Arginine
0.029
0.230
Cysteine
Not detected
Not detected
Proline
Not detected
Not detected
Tryphtophan
Not detected
Not detected
## 3.1. Choice of Protease
ACE inhibitory peptides generally were short peptides and enzymatic hydrolysis of food derived protein was one of important measures to obtain ACE inhibitory peptides. A lot of ACE inhibitory peptides had been reported from food derived proteins hydrolysates. In this investigation, five kinds of commercial proteases, including three alkali proteases, one neutral protease, and one acid protease, were chosen to obtain ACE inhibitory peptides fromMytilus coruscus. The ACE inhibitory activity of various enzymatic hydrolysates was shown in Figure 1. From the results, it was shown that the hydrolysate produced by alkali protease E1 had the highest ACE inhibitory activity. In addition, alkali proteases (E1, E2 and E3) were more effective for hydrolysis Mytilus coruscus mussel protein to obtain ACE inhibitory peptides than other two proteases (E4 and E5). Therefore, alkali protease E1 was chosen to next experiments to optimize hydrolysis conditions for producing ACE inhibitory peptides from Mytilus coruscus.Figure 1
The ACE inhibitory activity of hydrolysates by five commercial proteases. The data was expressed as mean ± standard deviation of three determinations. Means sharing the same lowercase letter was not significantly different atP<0.05.
## 3.2. Data Analysis of Uniform Design
A regression analysis was conducted to fit a mathematical model to the experimental data. The results of regression analysis were summarized (Table2), and a regression equation was given in
(2)Y=0.1023+0.2626X1+0.1083X2+0.1100X3+0.1592X4+0.0114X12+0.0937X22+0.1751X32+0.0020X42-0.1404X1X2-0.0829X1X3-0.0314X1X4+0.1561X1X3+0.2367X2X4+0.1960X3X4.The statistical analysis indicated the predicted model was adequate, possessing significantP value (P=0.047<0.05) and satisfactory values of the regression coefficient R2 (R2=0.9712) for the response. The high regression coefficient make clear that the experimental values of the ACE inhibitory activity agreed with predicted values, which meant that the predicted model seemed to reasonably represent the observed values. The largest relative error of predicted value was less than 5% shown in Table 2. The significance was tested by Student’s t-test and P value in Table 3. It was shown that temperature, pH, and protease added quantity affected significantly the ACE inhibitory activity of hydrolysates.Table 3
Significance of regression coefficient for the ACE inhibitory activity.
Variables
Standard error
Computedt value
Significance levelP value
X
1
0.6374
5.2987
0.0501
X
2
1.0897
0.9872
0.4619
X
3
1.2345
5.6426
0.0478
X
4
0.8766
7.2358
0.0342
X
1
X
2
−0.9234
4.4760
0.0323
X
1
X
3
−0.8768
3.9765
0.05926
X
1
X
4
−1.0236
7.0626
0.0355
X
2
X
3
0.7931
3.2617
0.0635
X
2
X
4
0.8942
6.2932
0.0433
X
3
X
4
0.6745
6.7869
0.0408
X
1
2
0.5679
5.4876
0.0496
X
2
2
0.9236
1.2381
0.3763
X
3
2
1.0111
4.2635
0.0543
X
4
2
0.8765
6.9367
0.0374
## 3.3. Verification Experiments
Then the optimum hydrolysis conditions of protease E1 and the prediction ACE inhibitory activity were obtained by (2). The optimum hydrolysis conditions of protease E1 were protease concentration (X1): 36.0 U/mL; hydrolysis time (X2): 2.7 h; hydrolysis pH (X3): 8.2; hydrolysis temperature (X4): 59.5°C. The predicted ACE inhibitory activity was 90.7% at optimum hydrolysis conditions. Under this optimum hydrolysis conditions, other three verification experiments were conducted and the average actual ACE inhibitory activity was 91.3%, which was in agreement with the predicted values of 90.7%.
## 3.4. Amino Acid Composition
The compositions of free amino acid and amino acid in peptides of the ACE inhibitory peptides fromMytilus coruscus were determined and the results were shown in Table 4. From the results, it was seen that the ACE inhibitory peptides solution had only a few free amino acid content, not equal with amino acid in peptides. The peptides, not amino acid, might contributed to high activity. The ACE inhibitory peptides had high percent of glutamic acid, taking 0.578 mmol/g, which could improve the breath ability of brain cell and be favorable to the expulsion of ammonia in brain and regulation of body metabolism, and these phases could impact the blood pressure directly. Also the ACE inhibitory peptides had high percent of lysine, leucine, glycine, and aspartic acid. These amino acids might play crucial role in the inhibitory activity. Cheung et al. [30] reported that dipeptides having hydrophobic amino acids such as valine (Val) and isoleucine (Ile) at the amino temerninus have higher ACE inhibitory activities. The amino acids, such as lysine, leucine, glycine, aspartic acid, and glutamic acid, were key constitutes with tall frequency appeared among many reported ACE inhibitory peptides [31–35].Table 4
Amino acid compositions of ACE inhibitory peptides fromMytilus coruscus.
Amino acid
Free amino acid content (mmol/g)
Amino acid in peptides (mmol/g)
Aspartic acid
0.009
0.449
Threonine
0.016
0.209
Serine
0.012
0.246
Glutamatic acid
0.013
0.578
Glycine
0.052
0.565
Alanine
0.027
0.558
Valine
0.009
0.155
Methionine
0.013
0.359
Isoleucine
0.018
0.157
Leucine
0.069
0.336
Tyrosine
0.000
0.089
Phenylalanine
0.020
0.146
Histidine
0.104
0.106
Lysine
0.068
0.419
Arginine
0.029
0.230
Cysteine
Not detected
Not detected
Proline
Not detected
Not detected
Tryphtophan
Not detected
Not detected
## 4. Conclusions
Alkali protease was a good choice for hydrolyzingMytilus coruscus protein for producing ACE inhibitory peptides. The factors, including protease concentration, hydrolysis time, hydrolysis pH, and temperature, affected the ACE inhibitory peptides of hydrolysates. Uniform Design was chosen to investigate the effects of preceding variables on ACE inhibitory activity. And the best hydrolysis conditions of alkali protease E1 optimized by Uniform Design were protease concentration of 36.0 U/mL, hydrolysis time of 2.7 hours, pH 8.2, temperature at 59.5°C. The optimal predicted ACE inhibitory activity of 90.7% was obtained at the optimum conditions. The experimental activity (91.3%) under optimized conditions was agreed closely with the predicted activity. The amino acid composition analysis of the ACE inhibitory peptides proved that it had high percent of lysine, leucine, glycine, aspartic acid, and glutamic acid. It was suggested that the ACE inhibitory peptides derived from Mytilus coruscus could be utilized to develop nutraceuticals and pharmaceuticals.
---
*Source: 290120-2012-12-26.xml* | 2013 |
# Fuzzy Covering-Based Three-Way Clustering
**Authors:** Dandan Yang
**Journal:** Mathematical Problems in Engineering
(2020)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2020/2901210
---
## Abstract
This paper investigates the three-way clustering involving fuzzy covering, thresholds acquisition, and boundary region processing. First of all, a valid fuzzy covering of the universe is constructed on the basis of an appropriate fuzzy similarity relation, which helps capture the structural information and the internal connections of the dataset from the global perspective. Due to the advantages of valid fuzzy covering, we explore the valid fuzzy covering instead of the raw dataset for RFCM algorithm-based three-way clustering. Subsequently, from the perspective of semantic interpretation of balancing the uncertainty changes in fuzzy sets, a method of partition thresholds acquisition combining linear and nonlinear fuzzy entropy theory is proposed. Furthermore, boundary regions in three-way clustering correspond to the abstaining decisions and generate uncertain rules. In order to improve the classification accuracy, thek-nearest neighbor (kNN) algorithm is utilized to reduce the objects in the boundary regions. The experimental results show that the performance of the proposed three-way clustering based on fuzzy covering and kNN-FRFCM algorithm is better than the compared algorithms in most cases.
---
## Body
## 1. Introduction
Three-way decisions (3WD) proposed by Yao [1, 2] is a hot topic in various fields in recent years. Since it was put forward, the idea of tripartition has attracted many scholars to do research. Especially recently, great progress has been made in the theoretical research and model building of three-way decisions based on rough sets. For example, Liang and Liu et al. [3–6] proposed fuzzy three-way decision models and stochastic three-way decision models to deal with real-valued or linguistic-valued decision-making problems. Qian et al. [7] established multigranulation decision-theoretic rough set model based on granular computing theory. Hu [8, 9] introduced the concept of three-way decision space and established a three-way decision model based on partially ordered sets. Qi et al. [10] investigated the 3WD model in the framework of lattice theory. Li et al. [11] have constructed a cost-sensitive sequential three-way decision model to simulate the decision-making process from coarse granularity (high cost) to fine granularity (low cost) and please refer [12–14] for further generalizations and applications of this model. Yao et al. [15] construct an optimization-based framework for three-way approximations of fuzzy sets. In the meanwhile, for dynamic objects and attributes, some algorithms and incremental 3WD models are designed for classification of dynamic data [16, 17]. From the viewpoint of application, three-way decisions have been widely used in research fields such as pattern recognition [18, 19], artificial intelligence [20–22], engineering, managements [23], and social communities [24].Based on the above backgrounds and work in three-way decisions, a novel method for three-way clustering based on fuzzy covering is discussed. First, the fuzzy covering of the dataset according to the reasonable fuzzy similarity relation is constructed. The fuzzy covering of the universe requires that the more similar the objects in the universe are, the more similar the corresponding fuzzy classes are. The fuzzy covering established in this way can better reflect the intrinsic relationship between objects in the universe. Therefore, clustering results will have more accuracy with valid fuzzy covering. One of the inevitable problems of clustering is threshold calculation. As is well known, for most of the three-way decision models mentioned above, we first need to obtain the pair of partition thresholdsα and β. Different thresholds lead to different decision results. The appropriate partition thresholds make the decision more accurate, whereas the inappropriate thresholds distort the decision. Traditionally, the partition thresholds are usually selected according to the experts experience in advance [25–27]. According to the loss function, Yao et al. [1] proposed a method to determine the thresholds by Bayesian risk decision theory. By using Shannon entropy as a measure of uncertainty, Deng et al. [28] present an information-theoretic approach to explain and calculate the thresholds. Zhou et al. [29] explore the shadowed set to automatically obtain the partition thresholds of the three-way decisions but cannot theoretically give a reasonable semantic explanation. To address this issue, inspired by the idea of balancing the uncertainty change of fuzzy sets, a threshold calculation method combining linear fuzzy entropy with nonlinear fuzzy entropy is proposed. This method provides a new scientific explanation for the generation of thresholds. And then, the boundary regions of three-way clustering are processed by the kNN algorithm to reduce uncertainty and improve decision accuracy.The structure of the rest of this paper is as follows:Section 2 briefly introduces the necessary notions of three-way decisions. Section 3 focuses on constructing the fuzzy covering of the raw dataset according to the fuzzy similarity relation and some necessary conditions and discusses its related properties. In Section 4, a novel rough fuzzy C-means (FRFCM) algorithm based on valid fuzzy covering is established. Then, we investigate the partition thresholds by combining the linear and nonlinear fuzzy entropy. Furthermore, the framework for processing the boundary region of three-way clustering using the kNN algorithm is introduced. In Section 5, the validity and practicability of the algorithm are evaluated by experiment. Concluding remarks are given in Section 6.
## 2. Preliminaries
The basic concepts on three-way decisions are briefly reviewed in this section.An information system is defined as a 4-tupleS=U,At=C∪D,V,f, where U=x1,x2,…,xn denotes a finite nonempty universe, C is a nonempty finite of condition attributes, D is a nonempty finite of decision attributes, and V=∪a∈AtVa, where Va is a domain of attribute a; f:U×C⟶V is an information function such that fx,a∈Va for every x∈U,a∈At. If Va is a membership function value, then the value of object x under attribute a can be expressed as μax∈0,1.The trisecting-and-acting framework of three-way decisions is an extension of binary decision in order to overcome some shortcomings of binary decision. The traditional binary decision model only has acceptance and rejection options, which can easily lead to errors when the information available is insufficient to make an accurate judgment. Sometimes, the cost of wrong decisions is very high. Therefore, deferment decision is necessary, which allows decision makers to collect more information and make more accurate judgment. This is a strategy that people often adopt in the decision-making process, and deferment decision is consistent with human cognition. A three-way decision model based on the evaluation function and a pair of thresholds is shown as follows.Definition 1.
(see [30]). Let U be a finite nonempty universe, v be an evaluation function, and α,β a pair of thresholds, 0≤β<α≤1, then the positive, negative, and boundary regions of any subset A⊆U are defined as follows:(1)POSα,βA=x∈UvAx≥α,NEGα,βA=x∈UvAx≤β,BNDα,βA=x∈Uβ<vAx<α.
Evaluation function is the key of decision. The result of decision-making is different with different evaluation functions. There are various evaluation functions that can be adopted. If a fuzzy membership functionμA is used as an evaluation function, then the induced three regions are defined by the following equations [31]:(2)POSα,βμA=x∈UμAx≥α,NEGα,βμA=x∈UμAx≤β,BNDα,βμA=x∈Uβ<μAx<α.
The three-valued approximations of a fuzzy set is described by Zadeh [32] as follows: (1) xbelongs toA, if μAx≥α; (2) x does not belong to A, if μAx≤β; (3) and x has an indeterminate status relative to A, if β<μAx<α. These three cases correspond to the three-way decisions of the above fuzzy set. When α=1 and β=0, we obtain the qualitative three-way decisions of a fuzzy set. However, the qualitative decision model of fuzzy set is very restrictive, and we generally do not select these two thresholds.
## 3. Fuzzy Covering and Its Validity
The focus of this section is on the method of constructing valid fuzzy covering of raw data and discusses the properties of the fuzzy covering. Let us first recall some concepts that help us to better understand fuzzy covering.Definition 2.
(see [33, 34]). Let U=x1,x2,…,xN be a finite universe and FU be the fuzzy power set of U. For each γ∈0,1, we call P=P1,P2,…,Pm with Pi∈FUi=1,2,…,m, a fuzzy γ-covering of U, if ∪i=1mPix≥γ for each x∈U. U,P is called a fuzzy γ-covering approximation space. If ∑i=1mPix≥1 for each x∈U, then P is called a fuzzy covering of U. U,P is called a fuzzy covering approximation space. ∑i=1mPix=1 for each x∈U, then P is called a fuzzy partition of U. We call U,P a fuzzy partition approximation space.Definition 3.
(see [35]). Let σ be a mapping σ:FU×FU⟶0,1. σA,B is called the degree of similarity between fuzzy sets A and B, if σA,B satisfies the following properties:(1)
σA,A=1,∀A∈FU(2)
σA,B = σB,A(3)
ifA⊆B⊆C, then σA,C≤σA,B∧σB,C
Some similarity measures are listed as follows:(3)σ1A,B=∑i=1NμAxi∧μBxi∑i=1NμAxi∨μBxi,σ2A,B=2∑i=1NμAxi∧μBxi∑i=1NμAxi+μBxi,σ3A,B=1−1N∑i=1NμAxi−μBxi.
The fuzzy set in this paper is constructed by fuzzy similarity relationR which satisfies the following properties. For any x,y∈U,(1)
0≤Rx,y≤1(2)
Rx,y=Ry,x
For a fuzzy similarity relationR∈FU×U, ∀xi∈U, and xiR∈FU, the membership of xj belonging to fuzzy set xiR is denoted as(4)xiRxj=Rxi,xj,xj∈U.
Obviously, ifRxi,xj=1, it means that xj certainly belongs to xiR. Conversely, if Rxi,xj=0, it indicates that xj certainly does not belong to xiR. xiR is also called a fuzzy similarity class associated with R on U. Therefore, the set of fuzzy similarity classes xiR:i=1,2,…,U constructed by relation R is a fuzzy covering of universe U.
In the following, we investigate the validity and related properties of the fuzzy covering of the raw dataset.Definition 4.
LetU=x1,x2,…,xN be a universe. R is the fuzzy similarity relation on U, and σ is the similarity relation on FU. P=x1,x2,…,xN is a fuzzy covering of U constructed by fuzzy similarity relation R. For any xi∈U, Mi=xjRσxi,xj,Rxi,xj≥φ,xj∈U,j≥i,φ∈0.5,1 is the set of similarity objects with xi. P is defined as a valid fuzzy covering of U with respect to θ, if the following condition holds:(5)IP=2⋅∑i=1NcardMiNN+1≥θ,where θ∈0.5,1.
It is easy to know that the value ofIP depends on σ and R and the choice of φ. φ is generally assigned no less than 0.8. The closer the IP is to 1, the more relation the R expresses the structure of sample space. If θ is less than 0.5, the fuzzy covering of the universe is invalid. The fuzzy covering P=x1,x2,…,xN satisfies that similar objects in U have corresponding similar fuzzy classes, so the fuzzy covering P more fully reflects the original distribution of objects in U.Proposition 1.
Letφ1<φ2, then Iφ1C≥Iφ2C.Proof.
It can be easily verified by the definition.Remark 1.
LetP1 and P2 be two valid fuzzy coverings of U with respect to the same θ. We choose fuzzy covering with a larger validity index I. as research data.
## 4. Three-Way Clustering
### 4.1. Rough Fuzzy C-Means Algorithm Based on Fuzzy Covering
In this section, we discuss the rough fuzzy C-means algorithm with fuzzy covering. The reason for clustering with fuzzy covering is that each fuzzy similarity class can reflect the relationship with the whole dataset, avoiding the disadvantage of excessive loss of clustering information with raw data.The combination of fuzzy set and rough set provides an important direction for uncertain reasoning. Lingras [36] developed rough C-means (RCM) by combining the C-means clustering algorithm with rough set theory. The new clustering center is only related to the positive region and the boundary region, unlike fuzzy C-means (FCM) [37], which is related to all objects. Since there is no membership involved, rough C-means (RCM) cannot effectively deal with the uncertainty caused by overlapping boundaries. In such circumstances, Mitra et al. [25] proposed a rough fuzzy C-means (RFCM) algorithm in which it combines the advantages of both fuzzy set and rough set into the framework of the C-means clustering algorithm. When dividing objects into approximation regions, replacing the absolute distance with a fuzzy membership is the innovation of the rough fuzzy C-means. This adjustment enhances the robustness of the clustering to deal with overlapping situations. Maji et al. [26] modified the calculation of the new clustering center in the RFCM model by assuming that the objects in the lower approximation have definite weights and the objects in the boundary have fuzzy weights. In what follows, we discuss the rough fuzzy C-means of fuzzy covering (FRFCM) algorithm, which is an RFCM algorithm based on fuzzy covering of the universe.SupposeSA=x1,x2,…,xNT is a valid fuzzy covering of U=x1,x2,…,xN. The cluster centers are denoted as V=v1,v2,…,vC⊂ℜN. In the FRFCM algorithm, SA is divided into C clusters Q1,Q2,…,QC. The membership of xj to the cluster i is(6)μij=1∑k=1Cdij/dkj2/m−1,where dij is the distance between xj and vi, μij∈0,1, and ∑i=1Cμij=1. The parameter m is the fuzzifier greater than 1.A two-category dataset is taken to explain the influence of different parametersm on classification. The membership degree of each object belonging to each cluster can be considered as a function which is related to relative distances and the fuzzifier parameter. Then, formula (6) translates to the following form:(7)μa,m=11+a/1−a2/m−1,a∈0,1,0,a=1,where a denotes the relative distance of an object with respect to one of the clusters.The uncertainty caused by different fuzzifier parameterm can be illustrated in Figure 1.Figure 1
The approximate regions with different values ofm.It is easily to obtain that if the value ofm tends to 1, the memberships are most crisp, as well as the uncertainty of the system is reduced which is suitable for three-way clustering. In this circumstance, only objects that are approximately the same distance from each cluster center are divided into boundary regions. In addition, the parameter m cannot be assigned with a very large value because as the value increases, the memberships of objects around the center of the cluster will be assigned to 1 and most objects are divided into boundary region which will increase the uncertainty of the system and the error rate of decision-making. Furthermore, the positive region of cluster may become empty.The center vectorsv1,v2,…,vC are updated as follows:(8)vi=wilAi+wibBi,ifR¯Qi≠∅∧RbQi≠∅,Bi,ifR¯Qi=∅∧RbQi≠∅,Ai,ifR¯Qi≠∅∧RbQi=∅,where Ai=∑xj∈R¯Qiμijmxj/∑xj∈R¯Qiμijm and Bi=∑xj∈RbQiμijmxj/∑xj∈RbQiμijm can be considered as the contributions to the center vi by the fuzzy lower region and fuzzy boundary region, respectively. RbQi=R¯Qi−R¯Qi denotes the boundary region of cluster Gi, where R¯Qi and R¯Qi are the lower and upper approximations of cluster Qi with respect to relation R, respectively. The weighted values wil and wib usually satisfy wil+wib=1 and wil>wib. In this paper, we take wil=cardR¯Qi/cardR¯Qi+cardRbQi and wib=cardRbQi/cardR¯Qi+cardRbQi.The approximation regions are determined by the FRFCM algorithm with the following principles: ifμpj−μqj≤δ, where p=minldvl,xj and q=minl≠pdvl,xj, then xj∈R¯Qpandxj∈R¯Qq, It also means xj∈R¯Qpandxj∈R¯Qq. In this case, xj cannot be divided into the positive region of any clusters. Otherwise, xj∈R¯Qp and xj∈R¯Qp. Due to the particularity structure of the fuzzy covering of U, the results of fuzzy covering clustering can well reflect the clustering results of the raw dataset through the above FRFCM algorithm.
### 4.2. Acquisition of Thresholds for Three-Way Clustering
In this section, we firstly review the shadowed set model for computing thresholds. Then, a novel method of calculating thresholds is proposed by combining the linear and nonlinear fuzzy entropy.The FRFCM algorithm is an important tool to deal with imprecise, incomplete, and inconsistent data. The thresholds in FRFCM which determines the formation of approximation regions should be carefully selected. The unreasonable thresholds may cause the partition of approximate regions to be distorted, and clustering centers may deviate from the expected locations. Therefore, we should compute the partition thresholds scientifically according to some principles.There are many methods to obtain the thresholds, and the most popular method is the shadowed set [38]. In fact, the shadowed set adopts the method of elevating and reducing membership degree, which divides the domain of fuzzy set into three regions. The corresponding membership function is as follows:(9)SAx=1,μAx≥α,0,μAx≤β,0,1,β<μAx<α,where μA is the membership function of fuzzy set A.In the following study, only discrete fuzzy systems are considered, and similar models and conclusions can be obtained for continuous fuzzy systems. According to shadowed sets theory, the following formula is proposed to calculate the minimumV value to obtain the optimal thresholds α and β:(10)V=∑μAx≤βμAxdx+∑μAx≥α1−μAxdx−cardx|β<μAx<α.However, the semantic interpretation of obtaining threshold pairs by using the above method is not very clear. Because the shadowed set model can not reasonably explain the relationship between the obtained shadowed set and the fuzziness of the raw fuzzy set, further research is needed. Various methods for measuring uncertainty are described in the literature [39]. Fuzzy entropy is an important tool to measure the uncertainty of fuzzy set and meets the following requirements.Definition 5.
(see [40]). Let A=xi,μAxi,xi∈U be a fuzzy set on the universe of discourse U=x1,x2,...,xN. The fuzzy entropy of fuzzy set A is the mapping E:FU⟶R+, which satisfies the following four conditions:(1)
EA=0 if A∈PU(2)
E1/2U=maxA∈FUEA(3)
∀A,B∈FU, if μB≥μA≥1/2 or μB≤μA≤1/2, then EA≥EB(4)
EAc=EA,∀A∈FU
It is easy to verify that, for anyxi∈U, μAxi=0 or μAxi=1, the value of corresponding entropy function is 0, then the fuzzy entropy of the fuzzy set equals 0; i.e., the uncertainty of the fuzzy set is the minimum. When μAxi=1/2 holds for any xi∈U, the value of corresponding entropy function is 1, then the fuzzy set has maximum uncertainty. The commonly used linear and nonlinear fuzzy entropy functions are listed as follows [41–43]:(11)EA1x=1−2μAx−1,x∈U,EA2x=sinπμAx,x∈U,EA3x=2minμAx,1−μAx,x∈U,EA4x=−1log2μAxlogμAx+1−μAxlog1−μAx,x∈U.
With the above fuzzy entropy functions of fuzzy measure, the corresponding fuzzy entropy of the fuzzy setA can be easily obtained as follows:(12)EjA=∑x∈UEAjx,j=1,2,3,4.
The basic idea of calculating the thresholds by fuzzy entropy is to reduce the uncertainty of the membership of the objects which are the elevating or reducing operation in the shadowed set to 0, while the membership of objects corresponding to the middle part in the shadowed set is adjusted to the maximal uncertainty; i.e., the fuzzy degree increases to 1. In what follows, we propose a flexible fuzzy entropy method which combines the linear fuzzy entropy functionEA1xi and nonlinear fuzzy entropy function EA2xi to obtain the clustering thresholds. Then, the calculation model is as follows:(13)αopt,βopt=argminα,βλ∑xi∈UμAxi≥αμAxi≤βEA1xi−∑xi∈Uβ<μAxi<α1−EA1xi+1−λ∑xi∈UμAxi≥αμAxi≤βEA2xi−∑xi∈Uβ<μAxi<α1−EA2xi,where λ∈0,1 is a parameter adjusting the impacts of linear entropy and nonlinear entropy.
In equation (13), when λ=1, only linear fuzzy entropy function EA1xi is used to calculate the thresholds. If λ=0, only nonlinear fuzzy entropy function EA2xi is used to calculate the thresholds. The smaller the value of λ, the more the influence brought from the linear fuzzy entropy, and vice versa. In the subsequent experiments of this study, we assign λ=0.5.
Figure2 illustrates the increase and decrease in fuzzy degree of the fuzzy entropy function by taking the linear fuzzy entropy function EA1x, the nonlinear fuzzy entropy function EA2x, and the fuzzy entropy function EACx which is combined by EA1x and EA2x with equal weight as examples.
It can be seen from Figure2 that the curve of flexible fuzzy entropy function lies between the curve of linear and nonlinear entropy functions. The method of using flexible fuzzy entropy to obtain the thresholds can prevent the uncertainty of fuzzy set measured by linear or nonlinear fuzzy entropy from being too small or too large, which leads to the partition thresholds unreasonable.
Thresholds used in RFCM and its related algorithms are usually user-defined. However, the threshold calculated by the above model can not only be interpreted from the change in fuzzy degree of fuzzy set but also be adjusted and optimized automatically.
According toαopt and βopt, the positive, boundary, and negative regions of each cluster Qi can be expressed as(14)POSQi=xjμij≥αopt,BNDQi=xjβopt<μij<αopt,NEGQi=U−POSQi−BNDQi=xjμij≤βopt,where μij is the membership degree of the jth object belonging to the ith class.Figure 2
The operations of fuzzy entropy functionsEA1x, EA2x, and EACx.
### 4.3. Boundary Region Processing of Three-Way Clustering Based on kNN Algorithm
Following the above discussion on automatically selecting the optimal partition thresholds based on fuzzy entropy theory, this section will present the object processing in the boundary regions of three-way clustering.In the three-way clustering, the boundary region objects are rarely further processed.k-nearest neighbor (kNN) algorithm [44] is a well-known nonparametric classifier, which is considered as one of the simplest methods in data mining and pattern recognition. The principle of the kNN algorithm is to find k nearest neighbors of a query in dataset and then predicts the query with the major class in the k nearest neighbors. In this paper, the kNN algorithm will be utilized to process the objects in the boundary regions. If the object does not find a positive region, it is still classified to the boundary region. Therefore, the uncertainty of the boundary region decreases with the decrease in the number of objects in the boundary region, and reclassifying the objects in the boundary region can improve the accuracy of the three-way clustering.The details of updating the boundary region with the kNN algorithm are as follows.Because the kNN algorithm mainly relies on limited adjacent objects for classification, it is more suitable than other methods for the overlap of class domain or the object set to be classified at the boundary region. Therefore, Algorithm1 can handle the uncertain arising from the boundary region. Of course, dealing with the boundary region with the k-nearest neighbor algorithm will add extra computing burden and may also face the risk of misclassification of objects.Algorithm 1: Processing the boundary regions of three-way clustering based on the kNN algorithm.
Input: a set of objects U=x1,x2,⋯,xN, the cluster centers V=v1,v2,…,vC, the positive region POS=∪i=1CPOSQi, boundary region BND=∪i=1CBNDQi, and the optimal value of k.Output: the updated positive region POSX and boundary region BNDXStep1: calculate the distance between xi and other objects, where xi∈BND;Step2: find the region where the k points with the smallest distance are located;Step3: nQi is the number of k objects in the positive region of class Qi, where i=1,2,⋯C. nQC+1 is the number of k objects in the boundary region, and nQ1+nQ2+⋯+nQC+nQC+1=k. If there is only one cluster Qj, such that nQj=maxi∈1,2,…,C+1nQi, then POSQj=POSQj∪xi and BND=BND−xi else xi∈BNDStep4: repeat Steps 1–3 until all boundary objects have been computed.In what follows, based on valid fuzzy covering, FRFCM and kNN algorithms, we proposed a three-way clustering algorithm, which is called the kNN-FRFCM algorithm, and it can be formed, as shown in Algorithm2.Algorithm 2: kNN-FRFCM algorithm-based three-way clustering.
Input: the valid fuzzy covering of universe xii=1,2,…,N, the cluster centers vii=1,2,…,C, and the initial fuzzy membership degrees μiji=1,2,…,C,j=1,2,…,N;Output: the positive, boundary, and negative regions of each cluster, respectively.Step1: compute the optimal partition thresholds αiopt and βiopt for each cluster Qi using formula (13);Step2: according to formula (14), determine the positive region POSQi, boundary region BNDQi, and NEGQi for each cluster Qi by αiopt, βiopt, and fuzzy partition matrix μijC×N;Step3: update each clustering region by Algorithm 1;Step4: update the membership partition matrix μijN×N by formula (6);Step5: update the cluster center vii=1,2,…,C with formula (8);Step6: repeat Step 1 to Step 5 until convergence is reached;Step7: the results of fuzzy covering clustering are replaced by the corresponding objects in the universe.Thus, according to Algorithm2, we obtain three-way clustering results of the original dataset by using the valid fuzzy covering.
## 4.1. Rough Fuzzy C-Means Algorithm Based on Fuzzy Covering
In this section, we discuss the rough fuzzy C-means algorithm with fuzzy covering. The reason for clustering with fuzzy covering is that each fuzzy similarity class can reflect the relationship with the whole dataset, avoiding the disadvantage of excessive loss of clustering information with raw data.The combination of fuzzy set and rough set provides an important direction for uncertain reasoning. Lingras [36] developed rough C-means (RCM) by combining the C-means clustering algorithm with rough set theory. The new clustering center is only related to the positive region and the boundary region, unlike fuzzy C-means (FCM) [37], which is related to all objects. Since there is no membership involved, rough C-means (RCM) cannot effectively deal with the uncertainty caused by overlapping boundaries. In such circumstances, Mitra et al. [25] proposed a rough fuzzy C-means (RFCM) algorithm in which it combines the advantages of both fuzzy set and rough set into the framework of the C-means clustering algorithm. When dividing objects into approximation regions, replacing the absolute distance with a fuzzy membership is the innovation of the rough fuzzy C-means. This adjustment enhances the robustness of the clustering to deal with overlapping situations. Maji et al. [26] modified the calculation of the new clustering center in the RFCM model by assuming that the objects in the lower approximation have definite weights and the objects in the boundary have fuzzy weights. In what follows, we discuss the rough fuzzy C-means of fuzzy covering (FRFCM) algorithm, which is an RFCM algorithm based on fuzzy covering of the universe.SupposeSA=x1,x2,…,xNT is a valid fuzzy covering of U=x1,x2,…,xN. The cluster centers are denoted as V=v1,v2,…,vC⊂ℜN. In the FRFCM algorithm, SA is divided into C clusters Q1,Q2,…,QC. The membership of xj to the cluster i is(6)μij=1∑k=1Cdij/dkj2/m−1,where dij is the distance between xj and vi, μij∈0,1, and ∑i=1Cμij=1. The parameter m is the fuzzifier greater than 1.A two-category dataset is taken to explain the influence of different parametersm on classification. The membership degree of each object belonging to each cluster can be considered as a function which is related to relative distances and the fuzzifier parameter. Then, formula (6) translates to the following form:(7)μa,m=11+a/1−a2/m−1,a∈0,1,0,a=1,where a denotes the relative distance of an object with respect to one of the clusters.The uncertainty caused by different fuzzifier parameterm can be illustrated in Figure 1.Figure 1
The approximate regions with different values ofm.It is easily to obtain that if the value ofm tends to 1, the memberships are most crisp, as well as the uncertainty of the system is reduced which is suitable for three-way clustering. In this circumstance, only objects that are approximately the same distance from each cluster center are divided into boundary regions. In addition, the parameter m cannot be assigned with a very large value because as the value increases, the memberships of objects around the center of the cluster will be assigned to 1 and most objects are divided into boundary region which will increase the uncertainty of the system and the error rate of decision-making. Furthermore, the positive region of cluster may become empty.The center vectorsv1,v2,…,vC are updated as follows:(8)vi=wilAi+wibBi,ifR¯Qi≠∅∧RbQi≠∅,Bi,ifR¯Qi=∅∧RbQi≠∅,Ai,ifR¯Qi≠∅∧RbQi=∅,where Ai=∑xj∈R¯Qiμijmxj/∑xj∈R¯Qiμijm and Bi=∑xj∈RbQiμijmxj/∑xj∈RbQiμijm can be considered as the contributions to the center vi by the fuzzy lower region and fuzzy boundary region, respectively. RbQi=R¯Qi−R¯Qi denotes the boundary region of cluster Gi, where R¯Qi and R¯Qi are the lower and upper approximations of cluster Qi with respect to relation R, respectively. The weighted values wil and wib usually satisfy wil+wib=1 and wil>wib. In this paper, we take wil=cardR¯Qi/cardR¯Qi+cardRbQi and wib=cardRbQi/cardR¯Qi+cardRbQi.The approximation regions are determined by the FRFCM algorithm with the following principles: ifμpj−μqj≤δ, where p=minldvl,xj and q=minl≠pdvl,xj, then xj∈R¯Qpandxj∈R¯Qq, It also means xj∈R¯Qpandxj∈R¯Qq. In this case, xj cannot be divided into the positive region of any clusters. Otherwise, xj∈R¯Qp and xj∈R¯Qp. Due to the particularity structure of the fuzzy covering of U, the results of fuzzy covering clustering can well reflect the clustering results of the raw dataset through the above FRFCM algorithm.
## 4.2. Acquisition of Thresholds for Three-Way Clustering
In this section, we firstly review the shadowed set model for computing thresholds. Then, a novel method of calculating thresholds is proposed by combining the linear and nonlinear fuzzy entropy.The FRFCM algorithm is an important tool to deal with imprecise, incomplete, and inconsistent data. The thresholds in FRFCM which determines the formation of approximation regions should be carefully selected. The unreasonable thresholds may cause the partition of approximate regions to be distorted, and clustering centers may deviate from the expected locations. Therefore, we should compute the partition thresholds scientifically according to some principles.There are many methods to obtain the thresholds, and the most popular method is the shadowed set [38]. In fact, the shadowed set adopts the method of elevating and reducing membership degree, which divides the domain of fuzzy set into three regions. The corresponding membership function is as follows:(9)SAx=1,μAx≥α,0,μAx≤β,0,1,β<μAx<α,where μA is the membership function of fuzzy set A.In the following study, only discrete fuzzy systems are considered, and similar models and conclusions can be obtained for continuous fuzzy systems. According to shadowed sets theory, the following formula is proposed to calculate the minimumV value to obtain the optimal thresholds α and β:(10)V=∑μAx≤βμAxdx+∑μAx≥α1−μAxdx−cardx|β<μAx<α.However, the semantic interpretation of obtaining threshold pairs by using the above method is not very clear. Because the shadowed set model can not reasonably explain the relationship between the obtained shadowed set and the fuzziness of the raw fuzzy set, further research is needed. Various methods for measuring uncertainty are described in the literature [39]. Fuzzy entropy is an important tool to measure the uncertainty of fuzzy set and meets the following requirements.Definition 5.
(see [40]). Let A=xi,μAxi,xi∈U be a fuzzy set on the universe of discourse U=x1,x2,...,xN. The fuzzy entropy of fuzzy set A is the mapping E:FU⟶R+, which satisfies the following four conditions:(1)
EA=0 if A∈PU(2)
E1/2U=maxA∈FUEA(3)
∀A,B∈FU, if μB≥μA≥1/2 or μB≤μA≤1/2, then EA≥EB(4)
EAc=EA,∀A∈FU
It is easy to verify that, for anyxi∈U, μAxi=0 or μAxi=1, the value of corresponding entropy function is 0, then the fuzzy entropy of the fuzzy set equals 0; i.e., the uncertainty of the fuzzy set is the minimum. When μAxi=1/2 holds for any xi∈U, the value of corresponding entropy function is 1, then the fuzzy set has maximum uncertainty. The commonly used linear and nonlinear fuzzy entropy functions are listed as follows [41–43]:(11)EA1x=1−2μAx−1,x∈U,EA2x=sinπμAx,x∈U,EA3x=2minμAx,1−μAx,x∈U,EA4x=−1log2μAxlogμAx+1−μAxlog1−μAx,x∈U.
With the above fuzzy entropy functions of fuzzy measure, the corresponding fuzzy entropy of the fuzzy setA can be easily obtained as follows:(12)EjA=∑x∈UEAjx,j=1,2,3,4.
The basic idea of calculating the thresholds by fuzzy entropy is to reduce the uncertainty of the membership of the objects which are the elevating or reducing operation in the shadowed set to 0, while the membership of objects corresponding to the middle part in the shadowed set is adjusted to the maximal uncertainty; i.e., the fuzzy degree increases to 1. In what follows, we propose a flexible fuzzy entropy method which combines the linear fuzzy entropy functionEA1xi and nonlinear fuzzy entropy function EA2xi to obtain the clustering thresholds. Then, the calculation model is as follows:(13)αopt,βopt=argminα,βλ∑xi∈UμAxi≥αμAxi≤βEA1xi−∑xi∈Uβ<μAxi<α1−EA1xi+1−λ∑xi∈UμAxi≥αμAxi≤βEA2xi−∑xi∈Uβ<μAxi<α1−EA2xi,where λ∈0,1 is a parameter adjusting the impacts of linear entropy and nonlinear entropy.
In equation (13), when λ=1, only linear fuzzy entropy function EA1xi is used to calculate the thresholds. If λ=0, only nonlinear fuzzy entropy function EA2xi is used to calculate the thresholds. The smaller the value of λ, the more the influence brought from the linear fuzzy entropy, and vice versa. In the subsequent experiments of this study, we assign λ=0.5.
Figure2 illustrates the increase and decrease in fuzzy degree of the fuzzy entropy function by taking the linear fuzzy entropy function EA1x, the nonlinear fuzzy entropy function EA2x, and the fuzzy entropy function EACx which is combined by EA1x and EA2x with equal weight as examples.
It can be seen from Figure2 that the curve of flexible fuzzy entropy function lies between the curve of linear and nonlinear entropy functions. The method of using flexible fuzzy entropy to obtain the thresholds can prevent the uncertainty of fuzzy set measured by linear or nonlinear fuzzy entropy from being too small or too large, which leads to the partition thresholds unreasonable.
Thresholds used in RFCM and its related algorithms are usually user-defined. However, the threshold calculated by the above model can not only be interpreted from the change in fuzzy degree of fuzzy set but also be adjusted and optimized automatically.
According toαopt and βopt, the positive, boundary, and negative regions of each cluster Qi can be expressed as(14)POSQi=xjμij≥αopt,BNDQi=xjβopt<μij<αopt,NEGQi=U−POSQi−BNDQi=xjμij≤βopt,where μij is the membership degree of the jth object belonging to the ith class.Figure 2
The operations of fuzzy entropy functionsEA1x, EA2x, and EACx.
## 4.3. Boundary Region Processing of Three-Way Clustering Based on kNN Algorithm
Following the above discussion on automatically selecting the optimal partition thresholds based on fuzzy entropy theory, this section will present the object processing in the boundary regions of three-way clustering.In the three-way clustering, the boundary region objects are rarely further processed.k-nearest neighbor (kNN) algorithm [44] is a well-known nonparametric classifier, which is considered as one of the simplest methods in data mining and pattern recognition. The principle of the kNN algorithm is to find k nearest neighbors of a query in dataset and then predicts the query with the major class in the k nearest neighbors. In this paper, the kNN algorithm will be utilized to process the objects in the boundary regions. If the object does not find a positive region, it is still classified to the boundary region. Therefore, the uncertainty of the boundary region decreases with the decrease in the number of objects in the boundary region, and reclassifying the objects in the boundary region can improve the accuracy of the three-way clustering.The details of updating the boundary region with the kNN algorithm are as follows.Because the kNN algorithm mainly relies on limited adjacent objects for classification, it is more suitable than other methods for the overlap of class domain or the object set to be classified at the boundary region. Therefore, Algorithm1 can handle the uncertain arising from the boundary region. Of course, dealing with the boundary region with the k-nearest neighbor algorithm will add extra computing burden and may also face the risk of misclassification of objects.Algorithm 1: Processing the boundary regions of three-way clustering based on the kNN algorithm.
Input: a set of objects U=x1,x2,⋯,xN, the cluster centers V=v1,v2,…,vC, the positive region POS=∪i=1CPOSQi, boundary region BND=∪i=1CBNDQi, and the optimal value of k.Output: the updated positive region POSX and boundary region BNDXStep1: calculate the distance between xi and other objects, where xi∈BND;Step2: find the region where the k points with the smallest distance are located;Step3: nQi is the number of k objects in the positive region of class Qi, where i=1,2,⋯C. nQC+1 is the number of k objects in the boundary region, and nQ1+nQ2+⋯+nQC+nQC+1=k. If there is only one cluster Qj, such that nQj=maxi∈1,2,…,C+1nQi, then POSQj=POSQj∪xi and BND=BND−xi else xi∈BNDStep4: repeat Steps 1–3 until all boundary objects have been computed.In what follows, based on valid fuzzy covering, FRFCM and kNN algorithms, we proposed a three-way clustering algorithm, which is called the kNN-FRFCM algorithm, and it can be formed, as shown in Algorithm2.Algorithm 2: kNN-FRFCM algorithm-based three-way clustering.
Input: the valid fuzzy covering of universe xii=1,2,…,N, the cluster centers vii=1,2,…,C, and the initial fuzzy membership degrees μiji=1,2,…,C,j=1,2,…,N;Output: the positive, boundary, and negative regions of each cluster, respectively.Step1: compute the optimal partition thresholds αiopt and βiopt for each cluster Qi using formula (13);Step2: according to formula (14), determine the positive region POSQi, boundary region BNDQi, and NEGQi for each cluster Qi by αiopt, βiopt, and fuzzy partition matrix μijC×N;Step3: update each clustering region by Algorithm 1;Step4: update the membership partition matrix μijN×N by formula (6);Step5: update the cluster center vii=1,2,…,C with formula (8);Step6: repeat Step 1 to Step 5 until convergence is reached;Step7: the results of fuzzy covering clustering are replaced by the corresponding objects in the universe.Thus, according to Algorithm2, we obtain three-way clustering results of the original dataset by using the valid fuzzy covering.
## 5. Experiment Analysis
Three-way clustering method based on fuzzy covering proposed in this paper is suitable for dataset with less data and dimension or data with similar amount of data and dimension. Otherwise, clustering with the fuzzy covering constructing by the data with a large amount of data and few dimension will cause the curse of dimensionality. In this paper, six datasets include Iris, Breast Cancer Wisconsin (Original) (BCWO) which eliminates the missing data, New thyroid, Seeds, Forest-type mapping (FTM), and CT from UCI Machine Learning Repository [45] for empirical study. On these datasets and their corresponding fuzzy covering, the results of clustering methods including FCM, RCM, RFCM, kNN-RCM, and kNN-RFCM are compared. In order to distinguish the results of the raw dataset and the fuzzy covering with the same algorithm, the clustering algorithms of the fuzzy covering are expressed as FFCM, FRCM, FRFCM, kNN-FRCM, and kNN-FRFCM, respectively. Details of the six datasets are described in Table 1.Table 1
Description of datasets.
No.Datasets# objects# attributes# classes1Iris150432BCWO6831023New thyroid215534Seeds210735FTM3262746CT221362The partition threshold related to RCM and its related algorithms is set as 0.001.φ and θ involved in fuzzy covering are set as 0.8 and 0.9, respectively. The value of k in the kNN algorithm is assigned as 7, and the evaluation indexes such as the normalized mutual information (NMI) [47], ACC [48], and rand index (RI) [49] are utilized to investigate the validity of the algorithm. Furthermore, the reasonable values of fuzzifier m involved in all comparison algorithms are greater than 1. m=1.03 and m=1.1 are selected, and the experimental comparison results are listed in Tables 2–7.Table 2
The comparative validity results (m = 1.03).
IrisSeedsNMIACCRINMIACCRIFCM0.74190.88670.87370.69490.89520.8744RCM0.73280.84000.88910.66700.88570.8666RFCM0.74190.88670.87370.66700.88570.8666kNN-RCM0.77770.90000.88590.67430.89050.8693kNN-RFCM0.74190.88670.87370.67430.89050.8693FFCM0.82260.93330.91950.67480.89520.8713FRCM0.77670.91330.91240.67480.89520.8713FRFCM0.81120.92670.91600.67770.89520.8742kNN-FRCM0.79190.92670.91240.67480.89520.8713kNN-FRFCM0.82260.93330.91950.68520.90000.8770Table 3
The comparative validity results (m = 1.03).
BCWONew thyroidNMIACCRINMIACCRIFCM0.74780.96050.92400.49450.86050.7908RCM0.73680.95020.92770.55850.87440.8203RFCM0.75850.96050.93120.59660.88840.8180kNN-RCM0.73680.95900.92770.55630.90230.7913kNN-RFCM0.75460.96190.92670.59660.88840.8180FFCM0.77590.96490.93210.62450.89770.8329FRCM0.77590.96490.93210.65010.90700.8531FRFCM0.77590.96490.93210.64480.90230.8523kNN-FRCM0.77590.96490.93210.65830.91160.8540kNN-FRFCM0.77590.96490.93210.65830.91160.8540Table 4
The comparative validity results (m = 1.03).
FTMCTNMIACCRINMIACCRIFCM0.72710.89390.90310.31180.81450.6964RCM0.74750.89900.90390.32960.82350.7080RFCM0.74110.89900.90180.33090.81900.7133kNN-RCM0.74750.89900.90390.32960.82350.7080kNN-RFCM0.74110.89900.90180.35500.83260.7234FFCM0.78230.90910.91530.43270.83710.7260FRCM0.78230.90910.91530.43270.83710.7260FRFCM0.76770.89900.91280.42670.82810.7234kNN-FRCM0.78230.90910.91530.43270.83710.7260kNN-FRFCM0.79060.91410.92000.42440.83260.7200Table 5
The comparative validity results (m = 1.1).
IrisSeedsNMIACCRINMIACCRIFCM0.75820.89330.87970.69490.89520.8744RCM0.73280.84000.88910.66700.88570.8666RFCM0.73600.87330.87140.67690.88570.8746kNN-RCM0.77770.90000.88590.67430.89050.8693kNN-RFCM0.75820.89330.87970.67280.89050.8740FFCM0.80240.92670.91240.66290.89050.8694FRCM0.77670.91330.91240.67480.89520.8713FRFCM0.79910.92000.91970.63450.87620.8643kNN-FRCM0.79190.92670.91240.67480.89520.8713kNN-FRFCM0.81360.93330.91970.64800.88570.8622Table 6
The comparative validity results (m = 1.1).
BCWONew thyroidNMIACCRINMIACCRIFCM0.74780.96050.92400.49450.86050.7908RCM0.73680.95020.92770.55850.87440.8203RFCM0.73910.95170.92680.60580.88840.8250kNN-RCM0.73680.95900.92770.55630.90230.7913kNN-RFCM0.73470.95750.91860.60580.88840.8250FFCM0.77590.96490.93210.62450.89770.8329FRCM0.77590.96490.93210.65010.90700.8531FRFCM0.77780.96490.93400.64480.90230.8523kNN-FRCM0.77590.96490.93210.65830.91160.8540kNN-FRFCM0.78890.96780.93760.65830.91160.8540Table 7
The comparative validity results (m = 1.1).
FTMCTNMIACCRINMIACCRIFCM0.72710.89390.90310.31180.81450.6964RCM0.74750.89900.90390.32960.82350.7080RFCM0.74110.89900.90180.30230.79190.6954kNN-RCM0.74750.89900.90390.32960.82350.7080kNN-RFCM0.74110.89900.90180.32740.81900.7055FFCM0.77460.90400.91070.43270.83710.7260FRCM0.78230.90910.91530.43270.83710.7260FRFCM0.76320.88380.91100.43380.81000.7374kNN-FRCM0.78230.90910.91530.43270.83710.7260kNN-FRFCM0.80740.91920.92460.47250.84160.7350From Tables2–7, it can be easily concluded that the selected fuzzy parameters have a significant impact on the performance of all comparison algorithms when dealing with the same dataset. Since the boundary region is the main cause of system uncertainty, thus, too large boundary regions are not required for three-way clustering and we need to pay attention to the uncertainty caused by the fuzzifier m in the implementation of the algorithms. Moreover, the clustering results show that kNN-FRFCM algorithm has better performance than the other algorithms in most of cases. This is mainly because it can reduce the uncertainty of the system by reprocessing the objects in the boundary regions. From the clustering results, we can also obtain that the results of clustering based on fuzzy covering are mostly better than the results of clustering with raw data. Therefore, the valid fuzzy covering can replace the raw dataset for clustering, and the clustering results are better than the raw dataset. The premise that fuzzy covering can replace the raw dataset for clustering is to select the appropriate fuzzy similarity relation [46].
## 6. Conclusions
In this paper, a valid fuzzy covering of the raw dataset is constructed by some principles. Because the similarity between fuzzy similarity classes in the valid fuzzy covering can be used to measure the similarity between objects in the raw dataset, each fuzzy similarity class reflects the connection with the whole dataset, so valid fuzzy covering instead of the raw data for clustering can improve the precision of clustering. From the perspective of semantic explanation of uncertainty change in fuzzy sets, we investigate the method of combining linear fuzzy entropy with nonlinear fuzzy entropy to obtain decision threshold pairs. The advantage of calculating thresholds method in this paper not only objectively obtains the classification thresholds based on the objects intrinsic relations but also the formula is simple and easy to understand, as well as the method of calculating the thresholds avoids the inappropriate subjective assignment. Additionally, the objects in the boundary region obtained by the FRFCM algorithm are reprocessed by the kNN algorithm to reduce the uncertainty of the system.Furthermore, we will continue to investigate the method of thresholds acquisition and the processing method of boundary region for three-way clustering following the idea of this paper. The three-way clustering in incremental information system is one of the future research directions too.
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*Source: 2901210-2020-07-31.xml* | 2901210-2020-07-31_2901210-2020-07-31.md | 47,224 | Fuzzy Covering-Based Three-Way Clustering | Dandan Yang | Mathematical Problems in Engineering
(2020) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2020/2901210 | 2901210-2020-07-31.xml | ---
## Abstract
This paper investigates the three-way clustering involving fuzzy covering, thresholds acquisition, and boundary region processing. First of all, a valid fuzzy covering of the universe is constructed on the basis of an appropriate fuzzy similarity relation, which helps capture the structural information and the internal connections of the dataset from the global perspective. Due to the advantages of valid fuzzy covering, we explore the valid fuzzy covering instead of the raw dataset for RFCM algorithm-based three-way clustering. Subsequently, from the perspective of semantic interpretation of balancing the uncertainty changes in fuzzy sets, a method of partition thresholds acquisition combining linear and nonlinear fuzzy entropy theory is proposed. Furthermore, boundary regions in three-way clustering correspond to the abstaining decisions and generate uncertain rules. In order to improve the classification accuracy, thek-nearest neighbor (kNN) algorithm is utilized to reduce the objects in the boundary regions. The experimental results show that the performance of the proposed three-way clustering based on fuzzy covering and kNN-FRFCM algorithm is better than the compared algorithms in most cases.
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## Body
## 1. Introduction
Three-way decisions (3WD) proposed by Yao [1, 2] is a hot topic in various fields in recent years. Since it was put forward, the idea of tripartition has attracted many scholars to do research. Especially recently, great progress has been made in the theoretical research and model building of three-way decisions based on rough sets. For example, Liang and Liu et al. [3–6] proposed fuzzy three-way decision models and stochastic three-way decision models to deal with real-valued or linguistic-valued decision-making problems. Qian et al. [7] established multigranulation decision-theoretic rough set model based on granular computing theory. Hu [8, 9] introduced the concept of three-way decision space and established a three-way decision model based on partially ordered sets. Qi et al. [10] investigated the 3WD model in the framework of lattice theory. Li et al. [11] have constructed a cost-sensitive sequential three-way decision model to simulate the decision-making process from coarse granularity (high cost) to fine granularity (low cost) and please refer [12–14] for further generalizations and applications of this model. Yao et al. [15] construct an optimization-based framework for three-way approximations of fuzzy sets. In the meanwhile, for dynamic objects and attributes, some algorithms and incremental 3WD models are designed for classification of dynamic data [16, 17]. From the viewpoint of application, three-way decisions have been widely used in research fields such as pattern recognition [18, 19], artificial intelligence [20–22], engineering, managements [23], and social communities [24].Based on the above backgrounds and work in three-way decisions, a novel method for three-way clustering based on fuzzy covering is discussed. First, the fuzzy covering of the dataset according to the reasonable fuzzy similarity relation is constructed. The fuzzy covering of the universe requires that the more similar the objects in the universe are, the more similar the corresponding fuzzy classes are. The fuzzy covering established in this way can better reflect the intrinsic relationship between objects in the universe. Therefore, clustering results will have more accuracy with valid fuzzy covering. One of the inevitable problems of clustering is threshold calculation. As is well known, for most of the three-way decision models mentioned above, we first need to obtain the pair of partition thresholdsα and β. Different thresholds lead to different decision results. The appropriate partition thresholds make the decision more accurate, whereas the inappropriate thresholds distort the decision. Traditionally, the partition thresholds are usually selected according to the experts experience in advance [25–27]. According to the loss function, Yao et al. [1] proposed a method to determine the thresholds by Bayesian risk decision theory. By using Shannon entropy as a measure of uncertainty, Deng et al. [28] present an information-theoretic approach to explain and calculate the thresholds. Zhou et al. [29] explore the shadowed set to automatically obtain the partition thresholds of the three-way decisions but cannot theoretically give a reasonable semantic explanation. To address this issue, inspired by the idea of balancing the uncertainty change of fuzzy sets, a threshold calculation method combining linear fuzzy entropy with nonlinear fuzzy entropy is proposed. This method provides a new scientific explanation for the generation of thresholds. And then, the boundary regions of three-way clustering are processed by the kNN algorithm to reduce uncertainty and improve decision accuracy.The structure of the rest of this paper is as follows:Section 2 briefly introduces the necessary notions of three-way decisions. Section 3 focuses on constructing the fuzzy covering of the raw dataset according to the fuzzy similarity relation and some necessary conditions and discusses its related properties. In Section 4, a novel rough fuzzy C-means (FRFCM) algorithm based on valid fuzzy covering is established. Then, we investigate the partition thresholds by combining the linear and nonlinear fuzzy entropy. Furthermore, the framework for processing the boundary region of three-way clustering using the kNN algorithm is introduced. In Section 5, the validity and practicability of the algorithm are evaluated by experiment. Concluding remarks are given in Section 6.
## 2. Preliminaries
The basic concepts on three-way decisions are briefly reviewed in this section.An information system is defined as a 4-tupleS=U,At=C∪D,V,f, where U=x1,x2,…,xn denotes a finite nonempty universe, C is a nonempty finite of condition attributes, D is a nonempty finite of decision attributes, and V=∪a∈AtVa, where Va is a domain of attribute a; f:U×C⟶V is an information function such that fx,a∈Va for every x∈U,a∈At. If Va is a membership function value, then the value of object x under attribute a can be expressed as μax∈0,1.The trisecting-and-acting framework of three-way decisions is an extension of binary decision in order to overcome some shortcomings of binary decision. The traditional binary decision model only has acceptance and rejection options, which can easily lead to errors when the information available is insufficient to make an accurate judgment. Sometimes, the cost of wrong decisions is very high. Therefore, deferment decision is necessary, which allows decision makers to collect more information and make more accurate judgment. This is a strategy that people often adopt in the decision-making process, and deferment decision is consistent with human cognition. A three-way decision model based on the evaluation function and a pair of thresholds is shown as follows.Definition 1.
(see [30]). Let U be a finite nonempty universe, v be an evaluation function, and α,β a pair of thresholds, 0≤β<α≤1, then the positive, negative, and boundary regions of any subset A⊆U are defined as follows:(1)POSα,βA=x∈UvAx≥α,NEGα,βA=x∈UvAx≤β,BNDα,βA=x∈Uβ<vAx<α.
Evaluation function is the key of decision. The result of decision-making is different with different evaluation functions. There are various evaluation functions that can be adopted. If a fuzzy membership functionμA is used as an evaluation function, then the induced three regions are defined by the following equations [31]:(2)POSα,βμA=x∈UμAx≥α,NEGα,βμA=x∈UμAx≤β,BNDα,βμA=x∈Uβ<μAx<α.
The three-valued approximations of a fuzzy set is described by Zadeh [32] as follows: (1) xbelongs toA, if μAx≥α; (2) x does not belong to A, if μAx≤β; (3) and x has an indeterminate status relative to A, if β<μAx<α. These three cases correspond to the three-way decisions of the above fuzzy set. When α=1 and β=0, we obtain the qualitative three-way decisions of a fuzzy set. However, the qualitative decision model of fuzzy set is very restrictive, and we generally do not select these two thresholds.
## 3. Fuzzy Covering and Its Validity
The focus of this section is on the method of constructing valid fuzzy covering of raw data and discusses the properties of the fuzzy covering. Let us first recall some concepts that help us to better understand fuzzy covering.Definition 2.
(see [33, 34]). Let U=x1,x2,…,xN be a finite universe and FU be the fuzzy power set of U. For each γ∈0,1, we call P=P1,P2,…,Pm with Pi∈FUi=1,2,…,m, a fuzzy γ-covering of U, if ∪i=1mPix≥γ for each x∈U. U,P is called a fuzzy γ-covering approximation space. If ∑i=1mPix≥1 for each x∈U, then P is called a fuzzy covering of U. U,P is called a fuzzy covering approximation space. ∑i=1mPix=1 for each x∈U, then P is called a fuzzy partition of U. We call U,P a fuzzy partition approximation space.Definition 3.
(see [35]). Let σ be a mapping σ:FU×FU⟶0,1. σA,B is called the degree of similarity between fuzzy sets A and B, if σA,B satisfies the following properties:(1)
σA,A=1,∀A∈FU(2)
σA,B = σB,A(3)
ifA⊆B⊆C, then σA,C≤σA,B∧σB,C
Some similarity measures are listed as follows:(3)σ1A,B=∑i=1NμAxi∧μBxi∑i=1NμAxi∨μBxi,σ2A,B=2∑i=1NμAxi∧μBxi∑i=1NμAxi+μBxi,σ3A,B=1−1N∑i=1NμAxi−μBxi.
The fuzzy set in this paper is constructed by fuzzy similarity relationR which satisfies the following properties. For any x,y∈U,(1)
0≤Rx,y≤1(2)
Rx,y=Ry,x
For a fuzzy similarity relationR∈FU×U, ∀xi∈U, and xiR∈FU, the membership of xj belonging to fuzzy set xiR is denoted as(4)xiRxj=Rxi,xj,xj∈U.
Obviously, ifRxi,xj=1, it means that xj certainly belongs to xiR. Conversely, if Rxi,xj=0, it indicates that xj certainly does not belong to xiR. xiR is also called a fuzzy similarity class associated with R on U. Therefore, the set of fuzzy similarity classes xiR:i=1,2,…,U constructed by relation R is a fuzzy covering of universe U.
In the following, we investigate the validity and related properties of the fuzzy covering of the raw dataset.Definition 4.
LetU=x1,x2,…,xN be a universe. R is the fuzzy similarity relation on U, and σ is the similarity relation on FU. P=x1,x2,…,xN is a fuzzy covering of U constructed by fuzzy similarity relation R. For any xi∈U, Mi=xjRσxi,xj,Rxi,xj≥φ,xj∈U,j≥i,φ∈0.5,1 is the set of similarity objects with xi. P is defined as a valid fuzzy covering of U with respect to θ, if the following condition holds:(5)IP=2⋅∑i=1NcardMiNN+1≥θ,where θ∈0.5,1.
It is easy to know that the value ofIP depends on σ and R and the choice of φ. φ is generally assigned no less than 0.8. The closer the IP is to 1, the more relation the R expresses the structure of sample space. If θ is less than 0.5, the fuzzy covering of the universe is invalid. The fuzzy covering P=x1,x2,…,xN satisfies that similar objects in U have corresponding similar fuzzy classes, so the fuzzy covering P more fully reflects the original distribution of objects in U.Proposition 1.
Letφ1<φ2, then Iφ1C≥Iφ2C.Proof.
It can be easily verified by the definition.Remark 1.
LetP1 and P2 be two valid fuzzy coverings of U with respect to the same θ. We choose fuzzy covering with a larger validity index I. as research data.
## 4. Three-Way Clustering
### 4.1. Rough Fuzzy C-Means Algorithm Based on Fuzzy Covering
In this section, we discuss the rough fuzzy C-means algorithm with fuzzy covering. The reason for clustering with fuzzy covering is that each fuzzy similarity class can reflect the relationship with the whole dataset, avoiding the disadvantage of excessive loss of clustering information with raw data.The combination of fuzzy set and rough set provides an important direction for uncertain reasoning. Lingras [36] developed rough C-means (RCM) by combining the C-means clustering algorithm with rough set theory. The new clustering center is only related to the positive region and the boundary region, unlike fuzzy C-means (FCM) [37], which is related to all objects. Since there is no membership involved, rough C-means (RCM) cannot effectively deal with the uncertainty caused by overlapping boundaries. In such circumstances, Mitra et al. [25] proposed a rough fuzzy C-means (RFCM) algorithm in which it combines the advantages of both fuzzy set and rough set into the framework of the C-means clustering algorithm. When dividing objects into approximation regions, replacing the absolute distance with a fuzzy membership is the innovation of the rough fuzzy C-means. This adjustment enhances the robustness of the clustering to deal with overlapping situations. Maji et al. [26] modified the calculation of the new clustering center in the RFCM model by assuming that the objects in the lower approximation have definite weights and the objects in the boundary have fuzzy weights. In what follows, we discuss the rough fuzzy C-means of fuzzy covering (FRFCM) algorithm, which is an RFCM algorithm based on fuzzy covering of the universe.SupposeSA=x1,x2,…,xNT is a valid fuzzy covering of U=x1,x2,…,xN. The cluster centers are denoted as V=v1,v2,…,vC⊂ℜN. In the FRFCM algorithm, SA is divided into C clusters Q1,Q2,…,QC. The membership of xj to the cluster i is(6)μij=1∑k=1Cdij/dkj2/m−1,where dij is the distance between xj and vi, μij∈0,1, and ∑i=1Cμij=1. The parameter m is the fuzzifier greater than 1.A two-category dataset is taken to explain the influence of different parametersm on classification. The membership degree of each object belonging to each cluster can be considered as a function which is related to relative distances and the fuzzifier parameter. Then, formula (6) translates to the following form:(7)μa,m=11+a/1−a2/m−1,a∈0,1,0,a=1,where a denotes the relative distance of an object with respect to one of the clusters.The uncertainty caused by different fuzzifier parameterm can be illustrated in Figure 1.Figure 1
The approximate regions with different values ofm.It is easily to obtain that if the value ofm tends to 1, the memberships are most crisp, as well as the uncertainty of the system is reduced which is suitable for three-way clustering. In this circumstance, only objects that are approximately the same distance from each cluster center are divided into boundary regions. In addition, the parameter m cannot be assigned with a very large value because as the value increases, the memberships of objects around the center of the cluster will be assigned to 1 and most objects are divided into boundary region which will increase the uncertainty of the system and the error rate of decision-making. Furthermore, the positive region of cluster may become empty.The center vectorsv1,v2,…,vC are updated as follows:(8)vi=wilAi+wibBi,ifR¯Qi≠∅∧RbQi≠∅,Bi,ifR¯Qi=∅∧RbQi≠∅,Ai,ifR¯Qi≠∅∧RbQi=∅,where Ai=∑xj∈R¯Qiμijmxj/∑xj∈R¯Qiμijm and Bi=∑xj∈RbQiμijmxj/∑xj∈RbQiμijm can be considered as the contributions to the center vi by the fuzzy lower region and fuzzy boundary region, respectively. RbQi=R¯Qi−R¯Qi denotes the boundary region of cluster Gi, where R¯Qi and R¯Qi are the lower and upper approximations of cluster Qi with respect to relation R, respectively. The weighted values wil and wib usually satisfy wil+wib=1 and wil>wib. In this paper, we take wil=cardR¯Qi/cardR¯Qi+cardRbQi and wib=cardRbQi/cardR¯Qi+cardRbQi.The approximation regions are determined by the FRFCM algorithm with the following principles: ifμpj−μqj≤δ, where p=minldvl,xj and q=minl≠pdvl,xj, then xj∈R¯Qpandxj∈R¯Qq, It also means xj∈R¯Qpandxj∈R¯Qq. In this case, xj cannot be divided into the positive region of any clusters. Otherwise, xj∈R¯Qp and xj∈R¯Qp. Due to the particularity structure of the fuzzy covering of U, the results of fuzzy covering clustering can well reflect the clustering results of the raw dataset through the above FRFCM algorithm.
### 4.2. Acquisition of Thresholds for Three-Way Clustering
In this section, we firstly review the shadowed set model for computing thresholds. Then, a novel method of calculating thresholds is proposed by combining the linear and nonlinear fuzzy entropy.The FRFCM algorithm is an important tool to deal with imprecise, incomplete, and inconsistent data. The thresholds in FRFCM which determines the formation of approximation regions should be carefully selected. The unreasonable thresholds may cause the partition of approximate regions to be distorted, and clustering centers may deviate from the expected locations. Therefore, we should compute the partition thresholds scientifically according to some principles.There are many methods to obtain the thresholds, and the most popular method is the shadowed set [38]. In fact, the shadowed set adopts the method of elevating and reducing membership degree, which divides the domain of fuzzy set into three regions. The corresponding membership function is as follows:(9)SAx=1,μAx≥α,0,μAx≤β,0,1,β<μAx<α,where μA is the membership function of fuzzy set A.In the following study, only discrete fuzzy systems are considered, and similar models and conclusions can be obtained for continuous fuzzy systems. According to shadowed sets theory, the following formula is proposed to calculate the minimumV value to obtain the optimal thresholds α and β:(10)V=∑μAx≤βμAxdx+∑μAx≥α1−μAxdx−cardx|β<μAx<α.However, the semantic interpretation of obtaining threshold pairs by using the above method is not very clear. Because the shadowed set model can not reasonably explain the relationship between the obtained shadowed set and the fuzziness of the raw fuzzy set, further research is needed. Various methods for measuring uncertainty are described in the literature [39]. Fuzzy entropy is an important tool to measure the uncertainty of fuzzy set and meets the following requirements.Definition 5.
(see [40]). Let A=xi,μAxi,xi∈U be a fuzzy set on the universe of discourse U=x1,x2,...,xN. The fuzzy entropy of fuzzy set A is the mapping E:FU⟶R+, which satisfies the following four conditions:(1)
EA=0 if A∈PU(2)
E1/2U=maxA∈FUEA(3)
∀A,B∈FU, if μB≥μA≥1/2 or μB≤μA≤1/2, then EA≥EB(4)
EAc=EA,∀A∈FU
It is easy to verify that, for anyxi∈U, μAxi=0 or μAxi=1, the value of corresponding entropy function is 0, then the fuzzy entropy of the fuzzy set equals 0; i.e., the uncertainty of the fuzzy set is the minimum. When μAxi=1/2 holds for any xi∈U, the value of corresponding entropy function is 1, then the fuzzy set has maximum uncertainty. The commonly used linear and nonlinear fuzzy entropy functions are listed as follows [41–43]:(11)EA1x=1−2μAx−1,x∈U,EA2x=sinπμAx,x∈U,EA3x=2minμAx,1−μAx,x∈U,EA4x=−1log2μAxlogμAx+1−μAxlog1−μAx,x∈U.
With the above fuzzy entropy functions of fuzzy measure, the corresponding fuzzy entropy of the fuzzy setA can be easily obtained as follows:(12)EjA=∑x∈UEAjx,j=1,2,3,4.
The basic idea of calculating the thresholds by fuzzy entropy is to reduce the uncertainty of the membership of the objects which are the elevating or reducing operation in the shadowed set to 0, while the membership of objects corresponding to the middle part in the shadowed set is adjusted to the maximal uncertainty; i.e., the fuzzy degree increases to 1. In what follows, we propose a flexible fuzzy entropy method which combines the linear fuzzy entropy functionEA1xi and nonlinear fuzzy entropy function EA2xi to obtain the clustering thresholds. Then, the calculation model is as follows:(13)αopt,βopt=argminα,βλ∑xi∈UμAxi≥αμAxi≤βEA1xi−∑xi∈Uβ<μAxi<α1−EA1xi+1−λ∑xi∈UμAxi≥αμAxi≤βEA2xi−∑xi∈Uβ<μAxi<α1−EA2xi,where λ∈0,1 is a parameter adjusting the impacts of linear entropy and nonlinear entropy.
In equation (13), when λ=1, only linear fuzzy entropy function EA1xi is used to calculate the thresholds. If λ=0, only nonlinear fuzzy entropy function EA2xi is used to calculate the thresholds. The smaller the value of λ, the more the influence brought from the linear fuzzy entropy, and vice versa. In the subsequent experiments of this study, we assign λ=0.5.
Figure2 illustrates the increase and decrease in fuzzy degree of the fuzzy entropy function by taking the linear fuzzy entropy function EA1x, the nonlinear fuzzy entropy function EA2x, and the fuzzy entropy function EACx which is combined by EA1x and EA2x with equal weight as examples.
It can be seen from Figure2 that the curve of flexible fuzzy entropy function lies between the curve of linear and nonlinear entropy functions. The method of using flexible fuzzy entropy to obtain the thresholds can prevent the uncertainty of fuzzy set measured by linear or nonlinear fuzzy entropy from being too small or too large, which leads to the partition thresholds unreasonable.
Thresholds used in RFCM and its related algorithms are usually user-defined. However, the threshold calculated by the above model can not only be interpreted from the change in fuzzy degree of fuzzy set but also be adjusted and optimized automatically.
According toαopt and βopt, the positive, boundary, and negative regions of each cluster Qi can be expressed as(14)POSQi=xjμij≥αopt,BNDQi=xjβopt<μij<αopt,NEGQi=U−POSQi−BNDQi=xjμij≤βopt,where μij is the membership degree of the jth object belonging to the ith class.Figure 2
The operations of fuzzy entropy functionsEA1x, EA2x, and EACx.
### 4.3. Boundary Region Processing of Three-Way Clustering Based on kNN Algorithm
Following the above discussion on automatically selecting the optimal partition thresholds based on fuzzy entropy theory, this section will present the object processing in the boundary regions of three-way clustering.In the three-way clustering, the boundary region objects are rarely further processed.k-nearest neighbor (kNN) algorithm [44] is a well-known nonparametric classifier, which is considered as one of the simplest methods in data mining and pattern recognition. The principle of the kNN algorithm is to find k nearest neighbors of a query in dataset and then predicts the query with the major class in the k nearest neighbors. In this paper, the kNN algorithm will be utilized to process the objects in the boundary regions. If the object does not find a positive region, it is still classified to the boundary region. Therefore, the uncertainty of the boundary region decreases with the decrease in the number of objects in the boundary region, and reclassifying the objects in the boundary region can improve the accuracy of the three-way clustering.The details of updating the boundary region with the kNN algorithm are as follows.Because the kNN algorithm mainly relies on limited adjacent objects for classification, it is more suitable than other methods for the overlap of class domain or the object set to be classified at the boundary region. Therefore, Algorithm1 can handle the uncertain arising from the boundary region. Of course, dealing with the boundary region with the k-nearest neighbor algorithm will add extra computing burden and may also face the risk of misclassification of objects.Algorithm 1: Processing the boundary regions of three-way clustering based on the kNN algorithm.
Input: a set of objects U=x1,x2,⋯,xN, the cluster centers V=v1,v2,…,vC, the positive region POS=∪i=1CPOSQi, boundary region BND=∪i=1CBNDQi, and the optimal value of k.Output: the updated positive region POSX and boundary region BNDXStep1: calculate the distance between xi and other objects, where xi∈BND;Step2: find the region where the k points with the smallest distance are located;Step3: nQi is the number of k objects in the positive region of class Qi, where i=1,2,⋯C. nQC+1 is the number of k objects in the boundary region, and nQ1+nQ2+⋯+nQC+nQC+1=k. If there is only one cluster Qj, such that nQj=maxi∈1,2,…,C+1nQi, then POSQj=POSQj∪xi and BND=BND−xi else xi∈BNDStep4: repeat Steps 1–3 until all boundary objects have been computed.In what follows, based on valid fuzzy covering, FRFCM and kNN algorithms, we proposed a three-way clustering algorithm, which is called the kNN-FRFCM algorithm, and it can be formed, as shown in Algorithm2.Algorithm 2: kNN-FRFCM algorithm-based three-way clustering.
Input: the valid fuzzy covering of universe xii=1,2,…,N, the cluster centers vii=1,2,…,C, and the initial fuzzy membership degrees μiji=1,2,…,C,j=1,2,…,N;Output: the positive, boundary, and negative regions of each cluster, respectively.Step1: compute the optimal partition thresholds αiopt and βiopt for each cluster Qi using formula (13);Step2: according to formula (14), determine the positive region POSQi, boundary region BNDQi, and NEGQi for each cluster Qi by αiopt, βiopt, and fuzzy partition matrix μijC×N;Step3: update each clustering region by Algorithm 1;Step4: update the membership partition matrix μijN×N by formula (6);Step5: update the cluster center vii=1,2,…,C with formula (8);Step6: repeat Step 1 to Step 5 until convergence is reached;Step7: the results of fuzzy covering clustering are replaced by the corresponding objects in the universe.Thus, according to Algorithm2, we obtain three-way clustering results of the original dataset by using the valid fuzzy covering.
## 4.1. Rough Fuzzy C-Means Algorithm Based on Fuzzy Covering
In this section, we discuss the rough fuzzy C-means algorithm with fuzzy covering. The reason for clustering with fuzzy covering is that each fuzzy similarity class can reflect the relationship with the whole dataset, avoiding the disadvantage of excessive loss of clustering information with raw data.The combination of fuzzy set and rough set provides an important direction for uncertain reasoning. Lingras [36] developed rough C-means (RCM) by combining the C-means clustering algorithm with rough set theory. The new clustering center is only related to the positive region and the boundary region, unlike fuzzy C-means (FCM) [37], which is related to all objects. Since there is no membership involved, rough C-means (RCM) cannot effectively deal with the uncertainty caused by overlapping boundaries. In such circumstances, Mitra et al. [25] proposed a rough fuzzy C-means (RFCM) algorithm in which it combines the advantages of both fuzzy set and rough set into the framework of the C-means clustering algorithm. When dividing objects into approximation regions, replacing the absolute distance with a fuzzy membership is the innovation of the rough fuzzy C-means. This adjustment enhances the robustness of the clustering to deal with overlapping situations. Maji et al. [26] modified the calculation of the new clustering center in the RFCM model by assuming that the objects in the lower approximation have definite weights and the objects in the boundary have fuzzy weights. In what follows, we discuss the rough fuzzy C-means of fuzzy covering (FRFCM) algorithm, which is an RFCM algorithm based on fuzzy covering of the universe.SupposeSA=x1,x2,…,xNT is a valid fuzzy covering of U=x1,x2,…,xN. The cluster centers are denoted as V=v1,v2,…,vC⊂ℜN. In the FRFCM algorithm, SA is divided into C clusters Q1,Q2,…,QC. The membership of xj to the cluster i is(6)μij=1∑k=1Cdij/dkj2/m−1,where dij is the distance between xj and vi, μij∈0,1, and ∑i=1Cμij=1. The parameter m is the fuzzifier greater than 1.A two-category dataset is taken to explain the influence of different parametersm on classification. The membership degree of each object belonging to each cluster can be considered as a function which is related to relative distances and the fuzzifier parameter. Then, formula (6) translates to the following form:(7)μa,m=11+a/1−a2/m−1,a∈0,1,0,a=1,where a denotes the relative distance of an object with respect to one of the clusters.The uncertainty caused by different fuzzifier parameterm can be illustrated in Figure 1.Figure 1
The approximate regions with different values ofm.It is easily to obtain that if the value ofm tends to 1, the memberships are most crisp, as well as the uncertainty of the system is reduced which is suitable for three-way clustering. In this circumstance, only objects that are approximately the same distance from each cluster center are divided into boundary regions. In addition, the parameter m cannot be assigned with a very large value because as the value increases, the memberships of objects around the center of the cluster will be assigned to 1 and most objects are divided into boundary region which will increase the uncertainty of the system and the error rate of decision-making. Furthermore, the positive region of cluster may become empty.The center vectorsv1,v2,…,vC are updated as follows:(8)vi=wilAi+wibBi,ifR¯Qi≠∅∧RbQi≠∅,Bi,ifR¯Qi=∅∧RbQi≠∅,Ai,ifR¯Qi≠∅∧RbQi=∅,where Ai=∑xj∈R¯Qiμijmxj/∑xj∈R¯Qiμijm and Bi=∑xj∈RbQiμijmxj/∑xj∈RbQiμijm can be considered as the contributions to the center vi by the fuzzy lower region and fuzzy boundary region, respectively. RbQi=R¯Qi−R¯Qi denotes the boundary region of cluster Gi, where R¯Qi and R¯Qi are the lower and upper approximations of cluster Qi with respect to relation R, respectively. The weighted values wil and wib usually satisfy wil+wib=1 and wil>wib. In this paper, we take wil=cardR¯Qi/cardR¯Qi+cardRbQi and wib=cardRbQi/cardR¯Qi+cardRbQi.The approximation regions are determined by the FRFCM algorithm with the following principles: ifμpj−μqj≤δ, where p=minldvl,xj and q=minl≠pdvl,xj, then xj∈R¯Qpandxj∈R¯Qq, It also means xj∈R¯Qpandxj∈R¯Qq. In this case, xj cannot be divided into the positive region of any clusters. Otherwise, xj∈R¯Qp and xj∈R¯Qp. Due to the particularity structure of the fuzzy covering of U, the results of fuzzy covering clustering can well reflect the clustering results of the raw dataset through the above FRFCM algorithm.
## 4.2. Acquisition of Thresholds for Three-Way Clustering
In this section, we firstly review the shadowed set model for computing thresholds. Then, a novel method of calculating thresholds is proposed by combining the linear and nonlinear fuzzy entropy.The FRFCM algorithm is an important tool to deal with imprecise, incomplete, and inconsistent data. The thresholds in FRFCM which determines the formation of approximation regions should be carefully selected. The unreasonable thresholds may cause the partition of approximate regions to be distorted, and clustering centers may deviate from the expected locations. Therefore, we should compute the partition thresholds scientifically according to some principles.There are many methods to obtain the thresholds, and the most popular method is the shadowed set [38]. In fact, the shadowed set adopts the method of elevating and reducing membership degree, which divides the domain of fuzzy set into three regions. The corresponding membership function is as follows:(9)SAx=1,μAx≥α,0,μAx≤β,0,1,β<μAx<α,where μA is the membership function of fuzzy set A.In the following study, only discrete fuzzy systems are considered, and similar models and conclusions can be obtained for continuous fuzzy systems. According to shadowed sets theory, the following formula is proposed to calculate the minimumV value to obtain the optimal thresholds α and β:(10)V=∑μAx≤βμAxdx+∑μAx≥α1−μAxdx−cardx|β<μAx<α.However, the semantic interpretation of obtaining threshold pairs by using the above method is not very clear. Because the shadowed set model can not reasonably explain the relationship between the obtained shadowed set and the fuzziness of the raw fuzzy set, further research is needed. Various methods for measuring uncertainty are described in the literature [39]. Fuzzy entropy is an important tool to measure the uncertainty of fuzzy set and meets the following requirements.Definition 5.
(see [40]). Let A=xi,μAxi,xi∈U be a fuzzy set on the universe of discourse U=x1,x2,...,xN. The fuzzy entropy of fuzzy set A is the mapping E:FU⟶R+, which satisfies the following four conditions:(1)
EA=0 if A∈PU(2)
E1/2U=maxA∈FUEA(3)
∀A,B∈FU, if μB≥μA≥1/2 or μB≤μA≤1/2, then EA≥EB(4)
EAc=EA,∀A∈FU
It is easy to verify that, for anyxi∈U, μAxi=0 or μAxi=1, the value of corresponding entropy function is 0, then the fuzzy entropy of the fuzzy set equals 0; i.e., the uncertainty of the fuzzy set is the minimum. When μAxi=1/2 holds for any xi∈U, the value of corresponding entropy function is 1, then the fuzzy set has maximum uncertainty. The commonly used linear and nonlinear fuzzy entropy functions are listed as follows [41–43]:(11)EA1x=1−2μAx−1,x∈U,EA2x=sinπμAx,x∈U,EA3x=2minμAx,1−μAx,x∈U,EA4x=−1log2μAxlogμAx+1−μAxlog1−μAx,x∈U.
With the above fuzzy entropy functions of fuzzy measure, the corresponding fuzzy entropy of the fuzzy setA can be easily obtained as follows:(12)EjA=∑x∈UEAjx,j=1,2,3,4.
The basic idea of calculating the thresholds by fuzzy entropy is to reduce the uncertainty of the membership of the objects which are the elevating or reducing operation in the shadowed set to 0, while the membership of objects corresponding to the middle part in the shadowed set is adjusted to the maximal uncertainty; i.e., the fuzzy degree increases to 1. In what follows, we propose a flexible fuzzy entropy method which combines the linear fuzzy entropy functionEA1xi and nonlinear fuzzy entropy function EA2xi to obtain the clustering thresholds. Then, the calculation model is as follows:(13)αopt,βopt=argminα,βλ∑xi∈UμAxi≥αμAxi≤βEA1xi−∑xi∈Uβ<μAxi<α1−EA1xi+1−λ∑xi∈UμAxi≥αμAxi≤βEA2xi−∑xi∈Uβ<μAxi<α1−EA2xi,where λ∈0,1 is a parameter adjusting the impacts of linear entropy and nonlinear entropy.
In equation (13), when λ=1, only linear fuzzy entropy function EA1xi is used to calculate the thresholds. If λ=0, only nonlinear fuzzy entropy function EA2xi is used to calculate the thresholds. The smaller the value of λ, the more the influence brought from the linear fuzzy entropy, and vice versa. In the subsequent experiments of this study, we assign λ=0.5.
Figure2 illustrates the increase and decrease in fuzzy degree of the fuzzy entropy function by taking the linear fuzzy entropy function EA1x, the nonlinear fuzzy entropy function EA2x, and the fuzzy entropy function EACx which is combined by EA1x and EA2x with equal weight as examples.
It can be seen from Figure2 that the curve of flexible fuzzy entropy function lies between the curve of linear and nonlinear entropy functions. The method of using flexible fuzzy entropy to obtain the thresholds can prevent the uncertainty of fuzzy set measured by linear or nonlinear fuzzy entropy from being too small or too large, which leads to the partition thresholds unreasonable.
Thresholds used in RFCM and its related algorithms are usually user-defined. However, the threshold calculated by the above model can not only be interpreted from the change in fuzzy degree of fuzzy set but also be adjusted and optimized automatically.
According toαopt and βopt, the positive, boundary, and negative regions of each cluster Qi can be expressed as(14)POSQi=xjμij≥αopt,BNDQi=xjβopt<μij<αopt,NEGQi=U−POSQi−BNDQi=xjμij≤βopt,where μij is the membership degree of the jth object belonging to the ith class.Figure 2
The operations of fuzzy entropy functionsEA1x, EA2x, and EACx.
## 4.3. Boundary Region Processing of Three-Way Clustering Based on kNN Algorithm
Following the above discussion on automatically selecting the optimal partition thresholds based on fuzzy entropy theory, this section will present the object processing in the boundary regions of three-way clustering.In the three-way clustering, the boundary region objects are rarely further processed.k-nearest neighbor (kNN) algorithm [44] is a well-known nonparametric classifier, which is considered as one of the simplest methods in data mining and pattern recognition. The principle of the kNN algorithm is to find k nearest neighbors of a query in dataset and then predicts the query with the major class in the k nearest neighbors. In this paper, the kNN algorithm will be utilized to process the objects in the boundary regions. If the object does not find a positive region, it is still classified to the boundary region. Therefore, the uncertainty of the boundary region decreases with the decrease in the number of objects in the boundary region, and reclassifying the objects in the boundary region can improve the accuracy of the three-way clustering.The details of updating the boundary region with the kNN algorithm are as follows.Because the kNN algorithm mainly relies on limited adjacent objects for classification, it is more suitable than other methods for the overlap of class domain or the object set to be classified at the boundary region. Therefore, Algorithm1 can handle the uncertain arising from the boundary region. Of course, dealing with the boundary region with the k-nearest neighbor algorithm will add extra computing burden and may also face the risk of misclassification of objects.Algorithm 1: Processing the boundary regions of three-way clustering based on the kNN algorithm.
Input: a set of objects U=x1,x2,⋯,xN, the cluster centers V=v1,v2,…,vC, the positive region POS=∪i=1CPOSQi, boundary region BND=∪i=1CBNDQi, and the optimal value of k.Output: the updated positive region POSX and boundary region BNDXStep1: calculate the distance between xi and other objects, where xi∈BND;Step2: find the region where the k points with the smallest distance are located;Step3: nQi is the number of k objects in the positive region of class Qi, where i=1,2,⋯C. nQC+1 is the number of k objects in the boundary region, and nQ1+nQ2+⋯+nQC+nQC+1=k. If there is only one cluster Qj, such that nQj=maxi∈1,2,…,C+1nQi, then POSQj=POSQj∪xi and BND=BND−xi else xi∈BNDStep4: repeat Steps 1–3 until all boundary objects have been computed.In what follows, based on valid fuzzy covering, FRFCM and kNN algorithms, we proposed a three-way clustering algorithm, which is called the kNN-FRFCM algorithm, and it can be formed, as shown in Algorithm2.Algorithm 2: kNN-FRFCM algorithm-based three-way clustering.
Input: the valid fuzzy covering of universe xii=1,2,…,N, the cluster centers vii=1,2,…,C, and the initial fuzzy membership degrees μiji=1,2,…,C,j=1,2,…,N;Output: the positive, boundary, and negative regions of each cluster, respectively.Step1: compute the optimal partition thresholds αiopt and βiopt for each cluster Qi using formula (13);Step2: according to formula (14), determine the positive region POSQi, boundary region BNDQi, and NEGQi for each cluster Qi by αiopt, βiopt, and fuzzy partition matrix μijC×N;Step3: update each clustering region by Algorithm 1;Step4: update the membership partition matrix μijN×N by formula (6);Step5: update the cluster center vii=1,2,…,C with formula (8);Step6: repeat Step 1 to Step 5 until convergence is reached;Step7: the results of fuzzy covering clustering are replaced by the corresponding objects in the universe.Thus, according to Algorithm2, we obtain three-way clustering results of the original dataset by using the valid fuzzy covering.
## 5. Experiment Analysis
Three-way clustering method based on fuzzy covering proposed in this paper is suitable for dataset with less data and dimension or data with similar amount of data and dimension. Otherwise, clustering with the fuzzy covering constructing by the data with a large amount of data and few dimension will cause the curse of dimensionality. In this paper, six datasets include Iris, Breast Cancer Wisconsin (Original) (BCWO) which eliminates the missing data, New thyroid, Seeds, Forest-type mapping (FTM), and CT from UCI Machine Learning Repository [45] for empirical study. On these datasets and their corresponding fuzzy covering, the results of clustering methods including FCM, RCM, RFCM, kNN-RCM, and kNN-RFCM are compared. In order to distinguish the results of the raw dataset and the fuzzy covering with the same algorithm, the clustering algorithms of the fuzzy covering are expressed as FFCM, FRCM, FRFCM, kNN-FRCM, and kNN-FRFCM, respectively. Details of the six datasets are described in Table 1.Table 1
Description of datasets.
No.Datasets# objects# attributes# classes1Iris150432BCWO6831023New thyroid215534Seeds210735FTM3262746CT221362The partition threshold related to RCM and its related algorithms is set as 0.001.φ and θ involved in fuzzy covering are set as 0.8 and 0.9, respectively. The value of k in the kNN algorithm is assigned as 7, and the evaluation indexes such as the normalized mutual information (NMI) [47], ACC [48], and rand index (RI) [49] are utilized to investigate the validity of the algorithm. Furthermore, the reasonable values of fuzzifier m involved in all comparison algorithms are greater than 1. m=1.03 and m=1.1 are selected, and the experimental comparison results are listed in Tables 2–7.Table 2
The comparative validity results (m = 1.03).
IrisSeedsNMIACCRINMIACCRIFCM0.74190.88670.87370.69490.89520.8744RCM0.73280.84000.88910.66700.88570.8666RFCM0.74190.88670.87370.66700.88570.8666kNN-RCM0.77770.90000.88590.67430.89050.8693kNN-RFCM0.74190.88670.87370.67430.89050.8693FFCM0.82260.93330.91950.67480.89520.8713FRCM0.77670.91330.91240.67480.89520.8713FRFCM0.81120.92670.91600.67770.89520.8742kNN-FRCM0.79190.92670.91240.67480.89520.8713kNN-FRFCM0.82260.93330.91950.68520.90000.8770Table 3
The comparative validity results (m = 1.03).
BCWONew thyroidNMIACCRINMIACCRIFCM0.74780.96050.92400.49450.86050.7908RCM0.73680.95020.92770.55850.87440.8203RFCM0.75850.96050.93120.59660.88840.8180kNN-RCM0.73680.95900.92770.55630.90230.7913kNN-RFCM0.75460.96190.92670.59660.88840.8180FFCM0.77590.96490.93210.62450.89770.8329FRCM0.77590.96490.93210.65010.90700.8531FRFCM0.77590.96490.93210.64480.90230.8523kNN-FRCM0.77590.96490.93210.65830.91160.8540kNN-FRFCM0.77590.96490.93210.65830.91160.8540Table 4
The comparative validity results (m = 1.03).
FTMCTNMIACCRINMIACCRIFCM0.72710.89390.90310.31180.81450.6964RCM0.74750.89900.90390.32960.82350.7080RFCM0.74110.89900.90180.33090.81900.7133kNN-RCM0.74750.89900.90390.32960.82350.7080kNN-RFCM0.74110.89900.90180.35500.83260.7234FFCM0.78230.90910.91530.43270.83710.7260FRCM0.78230.90910.91530.43270.83710.7260FRFCM0.76770.89900.91280.42670.82810.7234kNN-FRCM0.78230.90910.91530.43270.83710.7260kNN-FRFCM0.79060.91410.92000.42440.83260.7200Table 5
The comparative validity results (m = 1.1).
IrisSeedsNMIACCRINMIACCRIFCM0.75820.89330.87970.69490.89520.8744RCM0.73280.84000.88910.66700.88570.8666RFCM0.73600.87330.87140.67690.88570.8746kNN-RCM0.77770.90000.88590.67430.89050.8693kNN-RFCM0.75820.89330.87970.67280.89050.8740FFCM0.80240.92670.91240.66290.89050.8694FRCM0.77670.91330.91240.67480.89520.8713FRFCM0.79910.92000.91970.63450.87620.8643kNN-FRCM0.79190.92670.91240.67480.89520.8713kNN-FRFCM0.81360.93330.91970.64800.88570.8622Table 6
The comparative validity results (m = 1.1).
BCWONew thyroidNMIACCRINMIACCRIFCM0.74780.96050.92400.49450.86050.7908RCM0.73680.95020.92770.55850.87440.8203RFCM0.73910.95170.92680.60580.88840.8250kNN-RCM0.73680.95900.92770.55630.90230.7913kNN-RFCM0.73470.95750.91860.60580.88840.8250FFCM0.77590.96490.93210.62450.89770.8329FRCM0.77590.96490.93210.65010.90700.8531FRFCM0.77780.96490.93400.64480.90230.8523kNN-FRCM0.77590.96490.93210.65830.91160.8540kNN-FRFCM0.78890.96780.93760.65830.91160.8540Table 7
The comparative validity results (m = 1.1).
FTMCTNMIACCRINMIACCRIFCM0.72710.89390.90310.31180.81450.6964RCM0.74750.89900.90390.32960.82350.7080RFCM0.74110.89900.90180.30230.79190.6954kNN-RCM0.74750.89900.90390.32960.82350.7080kNN-RFCM0.74110.89900.90180.32740.81900.7055FFCM0.77460.90400.91070.43270.83710.7260FRCM0.78230.90910.91530.43270.83710.7260FRFCM0.76320.88380.91100.43380.81000.7374kNN-FRCM0.78230.90910.91530.43270.83710.7260kNN-FRFCM0.80740.91920.92460.47250.84160.7350From Tables2–7, it can be easily concluded that the selected fuzzy parameters have a significant impact on the performance of all comparison algorithms when dealing with the same dataset. Since the boundary region is the main cause of system uncertainty, thus, too large boundary regions are not required for three-way clustering and we need to pay attention to the uncertainty caused by the fuzzifier m in the implementation of the algorithms. Moreover, the clustering results show that kNN-FRFCM algorithm has better performance than the other algorithms in most of cases. This is mainly because it can reduce the uncertainty of the system by reprocessing the objects in the boundary regions. From the clustering results, we can also obtain that the results of clustering based on fuzzy covering are mostly better than the results of clustering with raw data. Therefore, the valid fuzzy covering can replace the raw dataset for clustering, and the clustering results are better than the raw dataset. The premise that fuzzy covering can replace the raw dataset for clustering is to select the appropriate fuzzy similarity relation [46].
## 6. Conclusions
In this paper, a valid fuzzy covering of the raw dataset is constructed by some principles. Because the similarity between fuzzy similarity classes in the valid fuzzy covering can be used to measure the similarity between objects in the raw dataset, each fuzzy similarity class reflects the connection with the whole dataset, so valid fuzzy covering instead of the raw data for clustering can improve the precision of clustering. From the perspective of semantic explanation of uncertainty change in fuzzy sets, we investigate the method of combining linear fuzzy entropy with nonlinear fuzzy entropy to obtain decision threshold pairs. The advantage of calculating thresholds method in this paper not only objectively obtains the classification thresholds based on the objects intrinsic relations but also the formula is simple and easy to understand, as well as the method of calculating the thresholds avoids the inappropriate subjective assignment. Additionally, the objects in the boundary region obtained by the FRFCM algorithm are reprocessed by the kNN algorithm to reduce the uncertainty of the system.Furthermore, we will continue to investigate the method of thresholds acquisition and the processing method of boundary region for three-way clustering following the idea of this paper. The three-way clustering in incremental information system is one of the future research directions too.
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*Source: 2901210-2020-07-31.xml* | 2020 |
# Harvesting of a Single-Species System Incorporating Stage Structure and Toxicity
**Authors:** Huiling Wu; Fengde Chen
**Journal:** Discrete Dynamics in Nature and Society
(2009)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2009/290123
---
## Abstract
A single species stage-structured model incorporating both toxicant and
harvesting is proposed and studied. It is shown that toxicant has no influence on the persistent property of the system. The existence of the bionomic equilibrium is also studied. After that, we consider the system with variable harvest effect; sufficient conditions are obtained for the global stability of bionomic equilibrium by constructing
a suitable Lyapunov function. The optimal policy is also investigated by using Pontryagin's maximal principle. Some numeric simulations are carried out to illustrate the feasibility of the main results. We end this paper by a brief discussion.
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## Body
## 1. Introduction
As the development of industry, the influence of toxicant becomes more and more serious; toxicant which was produced by water pollution, air pollution, heavy metal pollution and organisms themselves, and so on, has great effects on the ecological communities.Mathematical models which concerned with the influence of toxicant were first studied by Hallam and his colleagues [1–3]. After that, Freedman and Shukla [4] studied the single-species and predator-prey model; Chattopadhyay [5] and many scholars paid attention to the competition model [6–10]; Ma et al. [11], Das et al. [12], and Saha and Bandyopadhyay [13] laid emphasis on the predator-prey models. However, seldom did scholars investigated the stage-structured models with toxicant effects; to the best of authors' knowledge, only Xiao and Chen [14] explored a single-species model with stage-structured and toxicant substance. It is well known that many species in the natural world have a lifetime going through many stages, and in different stages, they have different reactions to the environment. For example, the immature may be more susceptible to the toxicant than the mature. Although there are many works on the stage-structured model (see [15–19] and the references cited therein), seldom did scholars consider the influence of the toxicant substance on the immature species.In this paper, we study the single-species model with simplified toxicant effect, and we also take the commercially exploit into account. Since many species can be resources as human food, harvesting has a great influence both on the species population and on the economic revenue. There are many papers that deal with the effects of harvesting [10, 12, 20–22]; such topics as the optimal harvesting policy and the bionomic equilibrium are well studied by them. However, only recently scholars considered the ecosystem with both harvesting and toxicant effects (see [10, 12]), while no scholar investigated the stage structure population dynamics with both harvesting and toxicant effect.We will study the following singe species stage structure ecosystem with both toxicant effect and harvesting:(1.1)x1′(t)=ax2-d1x1-d2x12-βx1-r1x13,x2′(t)=βx1-b1x2-c2Ex2,
where x1(t),x2(t) represent the population density of the immature and the mature at time t, respectively, r1x13 is the effects of toxicant on the immature, E is the harvesting effort, c2 is the catchability coefficient. We assume that the immature is density restriction, toxicant affects the immature population and only harvesting the mature species.The paper is arranged as follows The stability property of equilibria is studied in the next section, and the existence of the bionomic equilibrium is explored in Section3. In order to investigate the stability of the bionomic equilibrium and discuss how the population will be changed according to the the variable harvest effects, we assume that the E′ is proportion to the economic revenue [23], that is,(1.2)E′(t)=kE(p2c2x2-c).
Sufficient condition which ensures the global stability of bionomic equilibrium is then investigated in Section 4. The optimal harvesting policy is studied in Section 5 and some numeric simulations are carried out in Section 6 to illustrate the feasibility of the main results. We end this paper by a briefly discussion.
## 2. The Steady States and Stability
It can be calculated that system (1.1) has two possible equilibriums:(i)
the trivial EquilibriumE0(0,0),(ii)
the equilibriumE*(x1*,x2*), where(2.1)ax2*-d1x1*-d2x1*2-βx1*-r1x1*3=0,βx1*-b1x2*-c2Ex2*=0.
By simple calculation we have(2.2)x1*=-d2+d22+4r1(aβ/(b1+c2E)-d1-β)2r1,x2*=βb1+c2Ex1*.
To ensure the positivity of the equilibrium E*(x1*,x2*), we assume that(2.3)aβ>(b1+c2E)(d1+β)
holds. We can see that x1*,x2* decrease as r1 increases.Next, we use the Jacobian matrix to determine the locally stability of the equilibriums. By simple calculation, we see that the Jacobian matrix of system (1.1) is(2.4)[-d1-β-2d2x1-3r1x12aβ-b1-c2E].
For E0(0,0), the characteristic equation is
(2.5)λ2+(d1+β+b1+c2E)λ+(d1+β)(b1+c2E)-aβ=0.
It is not hard to see that when aβ<(d1+β)(b1+c2E), (2.5) has two negative roots or two complex roots with negative real parts; thus E0(0,0) is locally asymptotically stable; when aβ>(d1+β)(b1+c2E), E0(0,0) is a saddle point.ForE*(x1*,x2*), the characteristic equation is(2.6)λ2+(d1+β+b1+c2E+2d2x1*+3r1x1*2)λ+(d1+β+2d2x1*+3r1x1*2)(b1+c2E)-aβ=0.
By applying (2.1), we have(2.7)(d1+β+2d2x1*+3r1x1*2)(b1+c2E)-aβ=(b1+c2E)(d2x1*+2r1x1*2)>0.
Therefore, the characteristic equation of E*(x1*,x2*) has two negative roots or two complex roots with negative real parts; thus E*(x1*,x2*) is locally asymptotically stable.Following we will take the idea and method of Xiao and Chen [14] to investigate the globally asymptotically stability property of the equilibriums, and we need to determine the existence or nonexistence of the limit cycle in the first quadrant.ForE*(x1*,x2*), it exists if aβ>(b1+c2E)(d1+β); in this case E0(0,0) is a saddle point; thus, E*(x1*,x2*) is the unique stable equilibrium in the first quadrant if it exists. Let AB be the line segment of L1:x1=p and BC the line segment of L2:x2=q, where A(p,0),B(p,q),C(0,q), and p,q are positive constants which satisfy p>x1*, and(2.8)βpb1+c2E<q<p(d1+β+d2p+r1p2)a.
By simple calculation, we have(2.9)ẋ1∣AB=ax2-d1p-d2p2-βp-r1p3∣0≤x2≤q<0,ẋ2∣BC=βx1-(b1+c2E)q∣0≤x1≤p<0.
Thus AB,BC are the transversals of system (1.1). It is no hard to check that OA,OC are the transversals of system (1.1), and any trajectory enters region OABCO from its exterior to interior (see Figure 1).Figure 1
Trajectories enter rectangleOABCO from exterior to interior.Denote(2.10)x1′(t)=ax2-d1x1-d2x12-βx1-r1x13-c1Ex1=P(x1,x2),x2′(t)=βx1-b1x2-c2Ex2=Q(x1,x2).
It is easy to see that(2.11)∂P∂x1+∂Q∂x2=-d1-β-2d2x1-3r1x12-b1-c2E<0.
By Poincare-Bendixson theorem, there are no limit cycles in the first quadrant; thus E*(x1*,x2*) is globally asymptotically stable if it exists.ForE0(0,0), it is a unique equilibrium which is locally asymptotical stable if aβ<(b1+c2E)(d1+β). Similarly to the above analysis we can show that E0(0,0) is globally asymptotically stable if aβ<(b1+c2E)(d1+β) holds.Therefore, we have the following.(i)
Ifaβ<(d1+β)(b1+c2E), the trivial equilibrium E0(0,0) is globally asymptotically stable.(ii)
Ifaβ>(d1+β)(b1+c2E), the positive equilibrium E*(x1*,x2*) is globally asymptotically stable.We mention here that since condition (2.3) is independent of the toxicant of the system, thus, the globally asymptotically stability of the systems is independent of the intensities of toxicant, but from the expression of positive equilibrium we know that the density of both the immature and the mature species decreases while the toxicant increases; specially, the density of species will tend to indefinitely small if the toxicant substance is large enough.
## 3. Bionomic Equilibrium
For simplicity, we assume that the harvesting cost is a constant. Letc be the constant fishing cost per unit effort, and let p2 be the constant price per unit biomass of the mature. The net revenue of harvesting at any time is given by:(3.1)P(x1,x2,E)=p2c2Ex2-cE.
A bionomic equilibrium is both a biological equilibrium and a economic equilibrium, the biological equilibrium is given by x1′(t)=x2′(t)=0, and the economic equilibrium occurs when the economic rent is P=0, thus the bionomic equilibrium E¯(x1∞,x2∞,E∞) satisfying(3.2)ax2∞-d1x1∞-d2x1∞2-βx1∞-r1x1∞3=0,(3.3)βx1∞-b1x2∞-c2x2∞E∞=0,(3.4)p2c2x2∞-c=0.
From (3.4) we get x2∞=c/p2c2. Combining (3.4) and (3.2) we can obtain that x1∞ is one of the roots of the following equation:(3.5)r1x13+d2x12+(d1+β)x1-acp2c2=0.
Denoting f(x)=r1x3+d2x2+(d1+β)x-acp2c2, we have(3.6)f(0)=-acp2c2<0,f(+∞)=+∞,f'(x)>0(x∈[0,∞)).
Hence, by the continuity of f(x), there exists exactly one root in (0,+∞). From (3.3) and (3.4), to ensure the positivity of E∞, one needs(3.7)x1∞>b1cβp2c2,
Thus we need to find a solution of f(x) in (b1c/βp2c2,+∞). Since (3.6) always holds, we only need(3.8)f(b1cβp2c2)<0.
Thus, there exists a unique bionomic equilibrium if inequality (3.8) holds.The existence of the bionomic equilibrium means that (i) Harvesting effortsE>E∞ cannot be maintained all the time, it will decrease because the total cost of harvesting exceed the total revenues; (ii) E<E∞ cannot be maintained indefinitely, harvesting is profitable in this occasion, and it will make the harvesting effort increases. Hence, the harvesting effort is always oscillating around E∞. However, there is no answer about whether it will become stable or not because of the complex changing of E.
## 4. Globally Stability of the Bionomic Equilibrium
In this section, we study system (1.1) with variable harvest effects; sufficient condition for the globally asymptotically stability of the bionomic equilibrium will be derived. We assume that E′(t)=kE(p2c2x2-c); then system (1.1) becomes(4.1)x1′(t)=ax2-d1x1-d2x12-βx1-r1x13,x2′(t)=βx1-b1x2-c2Ex2,E′(t)=kE(p2c2x2-c).
System (4.1) has three possible equilibrium:(i)
the trivial equilibriumV0(0,0,0),(ii)
equilibrium in the absence of harvestingV1(x̃1,x̃2,0), where
(4.2)x̃1=-d2+d22+4r1(βa/b1-d1-β)2r1,x̃2=βb1x̃1,
and for the positiveness of x̃1,x̃2, we need(4.3)βa>(d1+β)b1,(iii)
the interior equilibriumE¯(x1∞,x2∞,E∞), which is the bionomic equilibrium in Section 3; it exists if (3.8) holds.ForV0(0,0,0), the characteristic equation is given by(4.4)(λ+kc)((λ+d1+β)(λ+b1)-βa)=0.
It is easy to see that all of the roots of (4.4) are negative if βa<b1(d1+β) holds; thus V0(0,0,0) is locally asymptotically stable if βa<b1(d1+β), and unstable if βa>b1(d1+β).ForV1(x̃1,x̃2,0), the characteristic equation is given by(4.5)(λ-k(p2c2x̃2-c))((λ+d1+β+2d2x̃1+3r1x̃12)(λ+b1)-aβ)=0.
It is no hard to see that V1(x̃1,x̃2,0) is locally asymptotically stable if p2c2x̃2-c<0, and unstable if p2c2x̃2-c>0.From the condition for the stability ofV0,V1, we can see that low birth rate can make the population be driven to extinction, high harvesting cost has negative effect on fishing effort, and it can make the harvesting effect approach zero.ForE¯(x1∞,x2∞,E∞), the characteristic equation is(4.6)λ3+Uλ2+Vλ+L=0,
where(4.7)U=b1+c2E∞+d1+β+2d2x1∞+3r1x1∞2>0,V=(b1+c2E∞)(d1+β+2d2x1∞+3r1x1∞2)+c22kp2x2∞E∞-aβ=(b1+c2E∞)(d2x1∞+2r1x1∞2)+c22kp2x2∞E∞>0,L=c22kp2x2∞E∞(d1+β+2d2x1∞+3r1x1∞2)>0.
By Routh-Hurwitz criterion, all roots of (4.6) have negative real parts if and only if(4.8)U>0,L>0,UV>L.
By simple calculation, we know that condition (4.8) holds always, Thus, E¯(x1∞,x2∞,E∞) is locally asymptotically stable.For the global stability ofE¯(x1∞,x2∞,E∞), we construct the following Lyapunov function:(4.9)V=x1-x1∞-x1∞lnx1x1∞+(x2-x2∞-x2∞lnx2x2∞)+n(E-E∞-lnEE∞).
The time derivative of V along the positive solution of system (4.1) is(4.10)V̇=x1-x1∞x1x1′(t)+x2-x2∞x2x2′(t)+nE-E∞EE'(t)=x1-x1∞x1{a(x2-x2∞)-(d1+β)(x1-x1∞)-d2(x12-x1∞2)-r1(x13-x1∞3)}+x2-x2∞x2{β(x1-x1∞)-b1(x2-x2∞)-c2(Ex2-E∞x2∞)}+nkE-E∞EE{p2c2(x2-x2∞)}=-(x1-x1∞)2x1{d1+β+d2(x1+x1∞)+r1(x12+x1x1∞+x1∞2)}-(x2-x2∞)2x2(b1+c2E∞)+(ax1+βx2)(x1-x1∞)(x2-x2∞)+(-c2+nkp2c2)(x2-x2∞)(E-E∞).
Let nkp1=1, then we have(4.11)V̇=-(x1-x1∞)2x1{d1+β+d2(x1+x1∞)+r1(x12+x1x1∞+x1∞2)}-(x2-x2∞)2x2(b1+c2E∞)+(ax1+βx2)(x1-x1∞)(x2-x2∞).
If inequality(4.12)1x1x2(d1+β+d2(x1+x1∞)+r1(x12+x1x1∞+x1∞2))(b1+c2E)>14(ax1+βx2)2
holds, then V̇(t)<0 in set Ω={x1>0,x2>0}. Set(4.13)g(x1,x2)=x1x2(d1+β+d2(x1+x1∞)+r1(x12+x1x1∞+x1∞2))(b1+c2E)-14(ax2+βx1)2,
then (4.12) holds in set Ω if g(x1,x2)>0. By applying (3.2) and (3.3), we have(4.14)g(x1,x2)=12aβx1x2+x1x2(d1x1+r1x12+r1x1x1∞)(b1+c2E)-14a2x22-14β2x12.
If x1≥x2, then(4.15)g(x1,x2)≥12aβx22+x22(d1x2+r1x22+r1x2x1∞)(b1+c2E)-14(a2+β2)x12.
Thus, we can get that if(4.16)x2≤x1<h2(x2)
holds, then g(x1,x2)>0, where(4.17)h2(x2)=x22aβ+4(d1x2+r1x22+r1x2x1∞)(b1+c2E∞)a2+β2.
If x1<x2, by the same way above, we can get the other sufficient condition for g(x1,x2)>0, that is,(4.18)x1<x2<h1(x1),
where(4.19)h1(x1)=x12aβ+4(d1x1+r1x12+r1x1x1∞)(b1+c2E∞)a2+β2.
Therefore, if (4.16) or (4.18) holds, then V̇(t)<0 and the bionomic equilibrium is globally asymptotically stable.The globally asymptotically stability of the bionomic equilibrium means that harvesting effectE which changes along (1.2) will make system (4.1) drive to the “bionomic equilibrium” and keep stable in the bionomic equilibrium.
## 5. Optimal Harvesting Policy
In this section, we study the optimal harvesting policy of system (1.1), and we consider the following present value J of a continuous time-stream:(5.1)J=∫0∞P(x1,x2,E,t)e-δtdt,
where P is the net revenue given by P(x1,x2,E,t)=p2c2Ex2-cE, and δ denotes the instantaneous annual rate of discount; the aim of this section is to maximize J subjected to state equation (1.1). Firstly we construct the following Hamiltonian function:(5.2)H=(p2c2x2-c)Ee-δt+λ1(ax2-d1x1-d2x12-βx1-r1x13)+λ2(βx1-b1x2-c2Ex2),
where λ1(t),λ2(t) are the adjoint variables, E is the control variable satisfying the constraints 0≤E≤Emax, and ϕ(t)=e-δt(p2c2x2-c)-λ2c2x2 is called the switching function [23]. We aim to find an optimal equilibrium (x1δ,x2δ,Eδ) to maximize Hamiltonian H; since Hamiltonian H is linear in the control variable E, the optimal control can be the extreme controls or the singular controls; thus, we have(5.3)E=Emax,whenϕ(t)>0,thatis,whenλ2(t)eδt<p2-cc2x2;E=0,whenϕ(t)<0,thatis,whenλ2(t)eδt>p2-cc2x2.
When ϕ(t)=0, that is,(5.4)λ2(t)eδt=p2-cc2x2,or∂H∂E=0.
In this case, the optimal control is called the singular control [23], and (5.4) is the necessary condition for the maximization of Hamiltonian H. By Pontrayagin’s maximal principle, the adjoint equations are(5.5)dλ1dt=-∂H∂x1=λ1(d1+2d2x1+β+3r1x12)-λ2β,dλ2dt=-∂H∂x2=-p2c2Ee-δt+λ2(b1+c2E)-λ1a.
From (5.4) and (5.5), we have(5.6)dλ1dt-Bλ1=Ae-δt,
where B=d1+2d2x1+β+3r1x12,A=β(c/c2x2-p2). We can calculate that(5.7)λ1=-AB+δe-δt.
Substituting (5.7) into the second equation of (5.5), we get(5.8)dλ2dt-Gλ2=De-δt,
where G=b1+c2E,D=-p2c2E+A/(B+δ). Therefore, we have(5.9)λ2=-DG+δe-δt.
It is obviously that λ1(t),λ2(t) are bounded as t→∞.Substituting (5.9) into (5.4), we obtain(5.10)p2-cc2x2=-DG+δ.
Our purpose is to find an optimal equilibrium solution; so we have(5.11)x1δ=x1*=-d2+d22+4r1(aβ/(b1+c2E)-d1-β)2r1,x2δ=x2*=βb1+c2Ex1*.
By (5.10) and (5.11), we can get x1δ,x2δ, andEδ. Thus, the optimal policy is(5.12)E={Emax,whenλ2(t)eδt<p2-cc2x2,Eδ,whenλ2(t)eδt=p2-cc2x2,0,whenλ2(t)eδt>p2-cc2x2.
Again, from (5.10) we have(5.13)P=(p2c2x2-c)E=-Dc2x2G+δE.
When δ→∞, P~o(δ-1). Therefore, δ=0 leads to the maximization of P.
## 6. Number Simulations
In the following examples, we take the parameters values asa=2,d1=0.1,d2=0.1,c2=0.2,b1=0.1,andβ=0.2. We will see how the system behavior is while the toxicant effect changes.Example 6.1.
E=1; in this case, aβ=0.4>0.09=(d1+β)(b1+c2E). From the results in Section 2, we know that for a given r1, the system admits a unique global stable positive equilibrium. Indeed, considering system (1.1) and the initial conditions (6,2),(5,10), and(1,5), respectively, we can see that(i)
r1=0, E*(10.33,6.89) is global stable;(ii)
r1=0.01, E*(6.33,4.22) is global stable (Figure 2);(iii)
r1=1, E*(0.97,0.65) is global stable (see Figure 3);(iv)
r1=100, E*(0.01,0.07) is global stable (Figure 4).Figure 2
Solution curves of system (1.1) with the parameters given by Example 6.1 when r1=0.01.Figure 3
Solution curves of system (1.1) with the parameters given by Example 6.1 when r1=1.Figure 4
Solution curves of system (1.1) with the parameters given by Example 6.1 when r1=100.Example 6.2.
k=0.1,p2=2,c=0.2,δ=0.01, and E'(t)=0.1E(0.4x2-0.2). Considering system (4.1) with initial condition (2,3,3),(4,5,6), and (1,1,1), we have the following.(i)
r1=0; the bionomic equilibrium E¯(2,0.5,3.5) is globally stable (Figure 5). The optimal equilibrium (10.32,6.87,1) is far away from the bionomic equilibrium.(ii)
r1=1; the bionomic equilibrium E¯(0.87,0.5,1.24) is globally stable (Figure 6). The optimal equilibrium is (1.26,1.28,0.49).(iii)
r1=10; the bionomic equilibrium E¯(0.44,0.5,0.38) is globally stable (Figure 7). The optimal equilibrium is (0.51,0.74,0.18).(iv)
r1=100; both the bionomic equilibrium E¯(0.2,0.5,-0.08) and the optimal equilibrium (0.20,0.44,-0.046) are unfeasible.Figure 5
Solution curves of system (4.1) with the parameters given by Example 6.2 when r1=0.Figure 6
Solution curves of system (4.1) with the parameters given by Example 6.2 when r1=1.Figure 7
Solution curves of system (4.1) with the parameters given by Example 6.2 when r1=10.From the above examples we can found the following phenomena:(i)
Increasing of toxicant will make the population of both mature and immature decrease.(ii)
The bionomic equilibrium exists and globally stable both in the absence of toxicant and in the present of toxicant; however, with the increase of toxicant, the immature populationx1∞ and the harvesting effect E decrease while the mature population x2∞ remains as the same.(iii)
The bionomic equilibrium and the optimal equilibrium will become unfeasible if the toxicant is large enough.(iv)
The immature, mature populations, and the harvesting effect in the optimal equilibrium are decreasing as the toxicant is increasing.(v)
The optimal equilibrium becomes more and more close to the bionomic equilibrium as the toxicant effect increases.
## 7. Discussion
In this paper, we consider the single-species stage structure model incorporating both toxicant and harvesting, and we assume that only the immature affected by the toxicant.Firstly, we explore the local and global stability properties of the equilibria of the system. Next, we investigate the existence and stability properties of the bionomic equilibrium. Finally, the optimal harvesting is studied, and it is found that there exists two optimal equilibria when the toxicant varies in a certain set. Some numeric examples to illustrate how the equilibrium (include bionomic equilibrium and optimal equilibrium) changes with the toxicant are also given.Nevertheless, as we know, the immature needs a certain time to develop to mature stage, the model incorporating time delay may be more reasonable and worth further study, and we leave this for future study.
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*Source: 290123-2010-01-26.xml* | 290123-2010-01-26_290123-2010-01-26.md | 19,755 | Harvesting of a Single-Species System Incorporating Stage Structure and Toxicity | Huiling Wu; Fengde Chen | Discrete Dynamics in Nature and Society
(2009) | Engineering & Technology | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2009/290123 | 290123-2010-01-26.xml | ---
## Abstract
A single species stage-structured model incorporating both toxicant and
harvesting is proposed and studied. It is shown that toxicant has no influence on the persistent property of the system. The existence of the bionomic equilibrium is also studied. After that, we consider the system with variable harvest effect; sufficient conditions are obtained for the global stability of bionomic equilibrium by constructing
a suitable Lyapunov function. The optimal policy is also investigated by using Pontryagin's maximal principle. Some numeric simulations are carried out to illustrate the feasibility of the main results. We end this paper by a brief discussion.
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## Body
## 1. Introduction
As the development of industry, the influence of toxicant becomes more and more serious; toxicant which was produced by water pollution, air pollution, heavy metal pollution and organisms themselves, and so on, has great effects on the ecological communities.Mathematical models which concerned with the influence of toxicant were first studied by Hallam and his colleagues [1–3]. After that, Freedman and Shukla [4] studied the single-species and predator-prey model; Chattopadhyay [5] and many scholars paid attention to the competition model [6–10]; Ma et al. [11], Das et al. [12], and Saha and Bandyopadhyay [13] laid emphasis on the predator-prey models. However, seldom did scholars investigated the stage-structured models with toxicant effects; to the best of authors' knowledge, only Xiao and Chen [14] explored a single-species model with stage-structured and toxicant substance. It is well known that many species in the natural world have a lifetime going through many stages, and in different stages, they have different reactions to the environment. For example, the immature may be more susceptible to the toxicant than the mature. Although there are many works on the stage-structured model (see [15–19] and the references cited therein), seldom did scholars consider the influence of the toxicant substance on the immature species.In this paper, we study the single-species model with simplified toxicant effect, and we also take the commercially exploit into account. Since many species can be resources as human food, harvesting has a great influence both on the species population and on the economic revenue. There are many papers that deal with the effects of harvesting [10, 12, 20–22]; such topics as the optimal harvesting policy and the bionomic equilibrium are well studied by them. However, only recently scholars considered the ecosystem with both harvesting and toxicant effects (see [10, 12]), while no scholar investigated the stage structure population dynamics with both harvesting and toxicant effect.We will study the following singe species stage structure ecosystem with both toxicant effect and harvesting:(1.1)x1′(t)=ax2-d1x1-d2x12-βx1-r1x13,x2′(t)=βx1-b1x2-c2Ex2,
where x1(t),x2(t) represent the population density of the immature and the mature at time t, respectively, r1x13 is the effects of toxicant on the immature, E is the harvesting effort, c2 is the catchability coefficient. We assume that the immature is density restriction, toxicant affects the immature population and only harvesting the mature species.The paper is arranged as follows The stability property of equilibria is studied in the next section, and the existence of the bionomic equilibrium is explored in Section3. In order to investigate the stability of the bionomic equilibrium and discuss how the population will be changed according to the the variable harvest effects, we assume that the E′ is proportion to the economic revenue [23], that is,(1.2)E′(t)=kE(p2c2x2-c).
Sufficient condition which ensures the global stability of bionomic equilibrium is then investigated in Section 4. The optimal harvesting policy is studied in Section 5 and some numeric simulations are carried out in Section 6 to illustrate the feasibility of the main results. We end this paper by a briefly discussion.
## 2. The Steady States and Stability
It can be calculated that system (1.1) has two possible equilibriums:(i)
the trivial EquilibriumE0(0,0),(ii)
the equilibriumE*(x1*,x2*), where(2.1)ax2*-d1x1*-d2x1*2-βx1*-r1x1*3=0,βx1*-b1x2*-c2Ex2*=0.
By simple calculation we have(2.2)x1*=-d2+d22+4r1(aβ/(b1+c2E)-d1-β)2r1,x2*=βb1+c2Ex1*.
To ensure the positivity of the equilibrium E*(x1*,x2*), we assume that(2.3)aβ>(b1+c2E)(d1+β)
holds. We can see that x1*,x2* decrease as r1 increases.Next, we use the Jacobian matrix to determine the locally stability of the equilibriums. By simple calculation, we see that the Jacobian matrix of system (1.1) is(2.4)[-d1-β-2d2x1-3r1x12aβ-b1-c2E].
For E0(0,0), the characteristic equation is
(2.5)λ2+(d1+β+b1+c2E)λ+(d1+β)(b1+c2E)-aβ=0.
It is not hard to see that when aβ<(d1+β)(b1+c2E), (2.5) has two negative roots or two complex roots with negative real parts; thus E0(0,0) is locally asymptotically stable; when aβ>(d1+β)(b1+c2E), E0(0,0) is a saddle point.ForE*(x1*,x2*), the characteristic equation is(2.6)λ2+(d1+β+b1+c2E+2d2x1*+3r1x1*2)λ+(d1+β+2d2x1*+3r1x1*2)(b1+c2E)-aβ=0.
By applying (2.1), we have(2.7)(d1+β+2d2x1*+3r1x1*2)(b1+c2E)-aβ=(b1+c2E)(d2x1*+2r1x1*2)>0.
Therefore, the characteristic equation of E*(x1*,x2*) has two negative roots or two complex roots with negative real parts; thus E*(x1*,x2*) is locally asymptotically stable.Following we will take the idea and method of Xiao and Chen [14] to investigate the globally asymptotically stability property of the equilibriums, and we need to determine the existence or nonexistence of the limit cycle in the first quadrant.ForE*(x1*,x2*), it exists if aβ>(b1+c2E)(d1+β); in this case E0(0,0) is a saddle point; thus, E*(x1*,x2*) is the unique stable equilibrium in the first quadrant if it exists. Let AB be the line segment of L1:x1=p and BC the line segment of L2:x2=q, where A(p,0),B(p,q),C(0,q), and p,q are positive constants which satisfy p>x1*, and(2.8)βpb1+c2E<q<p(d1+β+d2p+r1p2)a.
By simple calculation, we have(2.9)ẋ1∣AB=ax2-d1p-d2p2-βp-r1p3∣0≤x2≤q<0,ẋ2∣BC=βx1-(b1+c2E)q∣0≤x1≤p<0.
Thus AB,BC are the transversals of system (1.1). It is no hard to check that OA,OC are the transversals of system (1.1), and any trajectory enters region OABCO from its exterior to interior (see Figure 1).Figure 1
Trajectories enter rectangleOABCO from exterior to interior.Denote(2.10)x1′(t)=ax2-d1x1-d2x12-βx1-r1x13-c1Ex1=P(x1,x2),x2′(t)=βx1-b1x2-c2Ex2=Q(x1,x2).
It is easy to see that(2.11)∂P∂x1+∂Q∂x2=-d1-β-2d2x1-3r1x12-b1-c2E<0.
By Poincare-Bendixson theorem, there are no limit cycles in the first quadrant; thus E*(x1*,x2*) is globally asymptotically stable if it exists.ForE0(0,0), it is a unique equilibrium which is locally asymptotical stable if aβ<(b1+c2E)(d1+β). Similarly to the above analysis we can show that E0(0,0) is globally asymptotically stable if aβ<(b1+c2E)(d1+β) holds.Therefore, we have the following.(i)
Ifaβ<(d1+β)(b1+c2E), the trivial equilibrium E0(0,0) is globally asymptotically stable.(ii)
Ifaβ>(d1+β)(b1+c2E), the positive equilibrium E*(x1*,x2*) is globally asymptotically stable.We mention here that since condition (2.3) is independent of the toxicant of the system, thus, the globally asymptotically stability of the systems is independent of the intensities of toxicant, but from the expression of positive equilibrium we know that the density of both the immature and the mature species decreases while the toxicant increases; specially, the density of species will tend to indefinitely small if the toxicant substance is large enough.
## 3. Bionomic Equilibrium
For simplicity, we assume that the harvesting cost is a constant. Letc be the constant fishing cost per unit effort, and let p2 be the constant price per unit biomass of the mature. The net revenue of harvesting at any time is given by:(3.1)P(x1,x2,E)=p2c2Ex2-cE.
A bionomic equilibrium is both a biological equilibrium and a economic equilibrium, the biological equilibrium is given by x1′(t)=x2′(t)=0, and the economic equilibrium occurs when the economic rent is P=0, thus the bionomic equilibrium E¯(x1∞,x2∞,E∞) satisfying(3.2)ax2∞-d1x1∞-d2x1∞2-βx1∞-r1x1∞3=0,(3.3)βx1∞-b1x2∞-c2x2∞E∞=0,(3.4)p2c2x2∞-c=0.
From (3.4) we get x2∞=c/p2c2. Combining (3.4) and (3.2) we can obtain that x1∞ is one of the roots of the following equation:(3.5)r1x13+d2x12+(d1+β)x1-acp2c2=0.
Denoting f(x)=r1x3+d2x2+(d1+β)x-acp2c2, we have(3.6)f(0)=-acp2c2<0,f(+∞)=+∞,f'(x)>0(x∈[0,∞)).
Hence, by the continuity of f(x), there exists exactly one root in (0,+∞). From (3.3) and (3.4), to ensure the positivity of E∞, one needs(3.7)x1∞>b1cβp2c2,
Thus we need to find a solution of f(x) in (b1c/βp2c2,+∞). Since (3.6) always holds, we only need(3.8)f(b1cβp2c2)<0.
Thus, there exists a unique bionomic equilibrium if inequality (3.8) holds.The existence of the bionomic equilibrium means that (i) Harvesting effortsE>E∞ cannot be maintained all the time, it will decrease because the total cost of harvesting exceed the total revenues; (ii) E<E∞ cannot be maintained indefinitely, harvesting is profitable in this occasion, and it will make the harvesting effort increases. Hence, the harvesting effort is always oscillating around E∞. However, there is no answer about whether it will become stable or not because of the complex changing of E.
## 4. Globally Stability of the Bionomic Equilibrium
In this section, we study system (1.1) with variable harvest effects; sufficient condition for the globally asymptotically stability of the bionomic equilibrium will be derived. We assume that E′(t)=kE(p2c2x2-c); then system (1.1) becomes(4.1)x1′(t)=ax2-d1x1-d2x12-βx1-r1x13,x2′(t)=βx1-b1x2-c2Ex2,E′(t)=kE(p2c2x2-c).
System (4.1) has three possible equilibrium:(i)
the trivial equilibriumV0(0,0,0),(ii)
equilibrium in the absence of harvestingV1(x̃1,x̃2,0), where
(4.2)x̃1=-d2+d22+4r1(βa/b1-d1-β)2r1,x̃2=βb1x̃1,
and for the positiveness of x̃1,x̃2, we need(4.3)βa>(d1+β)b1,(iii)
the interior equilibriumE¯(x1∞,x2∞,E∞), which is the bionomic equilibrium in Section 3; it exists if (3.8) holds.ForV0(0,0,0), the characteristic equation is given by(4.4)(λ+kc)((λ+d1+β)(λ+b1)-βa)=0.
It is easy to see that all of the roots of (4.4) are negative if βa<b1(d1+β) holds; thus V0(0,0,0) is locally asymptotically stable if βa<b1(d1+β), and unstable if βa>b1(d1+β).ForV1(x̃1,x̃2,0), the characteristic equation is given by(4.5)(λ-k(p2c2x̃2-c))((λ+d1+β+2d2x̃1+3r1x̃12)(λ+b1)-aβ)=0.
It is no hard to see that V1(x̃1,x̃2,0) is locally asymptotically stable if p2c2x̃2-c<0, and unstable if p2c2x̃2-c>0.From the condition for the stability ofV0,V1, we can see that low birth rate can make the population be driven to extinction, high harvesting cost has negative effect on fishing effort, and it can make the harvesting effect approach zero.ForE¯(x1∞,x2∞,E∞), the characteristic equation is(4.6)λ3+Uλ2+Vλ+L=0,
where(4.7)U=b1+c2E∞+d1+β+2d2x1∞+3r1x1∞2>0,V=(b1+c2E∞)(d1+β+2d2x1∞+3r1x1∞2)+c22kp2x2∞E∞-aβ=(b1+c2E∞)(d2x1∞+2r1x1∞2)+c22kp2x2∞E∞>0,L=c22kp2x2∞E∞(d1+β+2d2x1∞+3r1x1∞2)>0.
By Routh-Hurwitz criterion, all roots of (4.6) have negative real parts if and only if(4.8)U>0,L>0,UV>L.
By simple calculation, we know that condition (4.8) holds always, Thus, E¯(x1∞,x2∞,E∞) is locally asymptotically stable.For the global stability ofE¯(x1∞,x2∞,E∞), we construct the following Lyapunov function:(4.9)V=x1-x1∞-x1∞lnx1x1∞+(x2-x2∞-x2∞lnx2x2∞)+n(E-E∞-lnEE∞).
The time derivative of V along the positive solution of system (4.1) is(4.10)V̇=x1-x1∞x1x1′(t)+x2-x2∞x2x2′(t)+nE-E∞EE'(t)=x1-x1∞x1{a(x2-x2∞)-(d1+β)(x1-x1∞)-d2(x12-x1∞2)-r1(x13-x1∞3)}+x2-x2∞x2{β(x1-x1∞)-b1(x2-x2∞)-c2(Ex2-E∞x2∞)}+nkE-E∞EE{p2c2(x2-x2∞)}=-(x1-x1∞)2x1{d1+β+d2(x1+x1∞)+r1(x12+x1x1∞+x1∞2)}-(x2-x2∞)2x2(b1+c2E∞)+(ax1+βx2)(x1-x1∞)(x2-x2∞)+(-c2+nkp2c2)(x2-x2∞)(E-E∞).
Let nkp1=1, then we have(4.11)V̇=-(x1-x1∞)2x1{d1+β+d2(x1+x1∞)+r1(x12+x1x1∞+x1∞2)}-(x2-x2∞)2x2(b1+c2E∞)+(ax1+βx2)(x1-x1∞)(x2-x2∞).
If inequality(4.12)1x1x2(d1+β+d2(x1+x1∞)+r1(x12+x1x1∞+x1∞2))(b1+c2E)>14(ax1+βx2)2
holds, then V̇(t)<0 in set Ω={x1>0,x2>0}. Set(4.13)g(x1,x2)=x1x2(d1+β+d2(x1+x1∞)+r1(x12+x1x1∞+x1∞2))(b1+c2E)-14(ax2+βx1)2,
then (4.12) holds in set Ω if g(x1,x2)>0. By applying (3.2) and (3.3), we have(4.14)g(x1,x2)=12aβx1x2+x1x2(d1x1+r1x12+r1x1x1∞)(b1+c2E)-14a2x22-14β2x12.
If x1≥x2, then(4.15)g(x1,x2)≥12aβx22+x22(d1x2+r1x22+r1x2x1∞)(b1+c2E)-14(a2+β2)x12.
Thus, we can get that if(4.16)x2≤x1<h2(x2)
holds, then g(x1,x2)>0, where(4.17)h2(x2)=x22aβ+4(d1x2+r1x22+r1x2x1∞)(b1+c2E∞)a2+β2.
If x1<x2, by the same way above, we can get the other sufficient condition for g(x1,x2)>0, that is,(4.18)x1<x2<h1(x1),
where(4.19)h1(x1)=x12aβ+4(d1x1+r1x12+r1x1x1∞)(b1+c2E∞)a2+β2.
Therefore, if (4.16) or (4.18) holds, then V̇(t)<0 and the bionomic equilibrium is globally asymptotically stable.The globally asymptotically stability of the bionomic equilibrium means that harvesting effectE which changes along (1.2) will make system (4.1) drive to the “bionomic equilibrium” and keep stable in the bionomic equilibrium.
## 5. Optimal Harvesting Policy
In this section, we study the optimal harvesting policy of system (1.1), and we consider the following present value J of a continuous time-stream:(5.1)J=∫0∞P(x1,x2,E,t)e-δtdt,
where P is the net revenue given by P(x1,x2,E,t)=p2c2Ex2-cE, and δ denotes the instantaneous annual rate of discount; the aim of this section is to maximize J subjected to state equation (1.1). Firstly we construct the following Hamiltonian function:(5.2)H=(p2c2x2-c)Ee-δt+λ1(ax2-d1x1-d2x12-βx1-r1x13)+λ2(βx1-b1x2-c2Ex2),
where λ1(t),λ2(t) are the adjoint variables, E is the control variable satisfying the constraints 0≤E≤Emax, and ϕ(t)=e-δt(p2c2x2-c)-λ2c2x2 is called the switching function [23]. We aim to find an optimal equilibrium (x1δ,x2δ,Eδ) to maximize Hamiltonian H; since Hamiltonian H is linear in the control variable E, the optimal control can be the extreme controls or the singular controls; thus, we have(5.3)E=Emax,whenϕ(t)>0,thatis,whenλ2(t)eδt<p2-cc2x2;E=0,whenϕ(t)<0,thatis,whenλ2(t)eδt>p2-cc2x2.
When ϕ(t)=0, that is,(5.4)λ2(t)eδt=p2-cc2x2,or∂H∂E=0.
In this case, the optimal control is called the singular control [23], and (5.4) is the necessary condition for the maximization of Hamiltonian H. By Pontrayagin’s maximal principle, the adjoint equations are(5.5)dλ1dt=-∂H∂x1=λ1(d1+2d2x1+β+3r1x12)-λ2β,dλ2dt=-∂H∂x2=-p2c2Ee-δt+λ2(b1+c2E)-λ1a.
From (5.4) and (5.5), we have(5.6)dλ1dt-Bλ1=Ae-δt,
where B=d1+2d2x1+β+3r1x12,A=β(c/c2x2-p2). We can calculate that(5.7)λ1=-AB+δe-δt.
Substituting (5.7) into the second equation of (5.5), we get(5.8)dλ2dt-Gλ2=De-δt,
where G=b1+c2E,D=-p2c2E+A/(B+δ). Therefore, we have(5.9)λ2=-DG+δe-δt.
It is obviously that λ1(t),λ2(t) are bounded as t→∞.Substituting (5.9) into (5.4), we obtain(5.10)p2-cc2x2=-DG+δ.
Our purpose is to find an optimal equilibrium solution; so we have(5.11)x1δ=x1*=-d2+d22+4r1(aβ/(b1+c2E)-d1-β)2r1,x2δ=x2*=βb1+c2Ex1*.
By (5.10) and (5.11), we can get x1δ,x2δ, andEδ. Thus, the optimal policy is(5.12)E={Emax,whenλ2(t)eδt<p2-cc2x2,Eδ,whenλ2(t)eδt=p2-cc2x2,0,whenλ2(t)eδt>p2-cc2x2.
Again, from (5.10) we have(5.13)P=(p2c2x2-c)E=-Dc2x2G+δE.
When δ→∞, P~o(δ-1). Therefore, δ=0 leads to the maximization of P.
## 6. Number Simulations
In the following examples, we take the parameters values asa=2,d1=0.1,d2=0.1,c2=0.2,b1=0.1,andβ=0.2. We will see how the system behavior is while the toxicant effect changes.Example 6.1.
E=1; in this case, aβ=0.4>0.09=(d1+β)(b1+c2E). From the results in Section 2, we know that for a given r1, the system admits a unique global stable positive equilibrium. Indeed, considering system (1.1) and the initial conditions (6,2),(5,10), and(1,5), respectively, we can see that(i)
r1=0, E*(10.33,6.89) is global stable;(ii)
r1=0.01, E*(6.33,4.22) is global stable (Figure 2);(iii)
r1=1, E*(0.97,0.65) is global stable (see Figure 3);(iv)
r1=100, E*(0.01,0.07) is global stable (Figure 4).Figure 2
Solution curves of system (1.1) with the parameters given by Example 6.1 when r1=0.01.Figure 3
Solution curves of system (1.1) with the parameters given by Example 6.1 when r1=1.Figure 4
Solution curves of system (1.1) with the parameters given by Example 6.1 when r1=100.Example 6.2.
k=0.1,p2=2,c=0.2,δ=0.01, and E'(t)=0.1E(0.4x2-0.2). Considering system (4.1) with initial condition (2,3,3),(4,5,6), and (1,1,1), we have the following.(i)
r1=0; the bionomic equilibrium E¯(2,0.5,3.5) is globally stable (Figure 5). The optimal equilibrium (10.32,6.87,1) is far away from the bionomic equilibrium.(ii)
r1=1; the bionomic equilibrium E¯(0.87,0.5,1.24) is globally stable (Figure 6). The optimal equilibrium is (1.26,1.28,0.49).(iii)
r1=10; the bionomic equilibrium E¯(0.44,0.5,0.38) is globally stable (Figure 7). The optimal equilibrium is (0.51,0.74,0.18).(iv)
r1=100; both the bionomic equilibrium E¯(0.2,0.5,-0.08) and the optimal equilibrium (0.20,0.44,-0.046) are unfeasible.Figure 5
Solution curves of system (4.1) with the parameters given by Example 6.2 when r1=0.Figure 6
Solution curves of system (4.1) with the parameters given by Example 6.2 when r1=1.Figure 7
Solution curves of system (4.1) with the parameters given by Example 6.2 when r1=10.From the above examples we can found the following phenomena:(i)
Increasing of toxicant will make the population of both mature and immature decrease.(ii)
The bionomic equilibrium exists and globally stable both in the absence of toxicant and in the present of toxicant; however, with the increase of toxicant, the immature populationx1∞ and the harvesting effect E decrease while the mature population x2∞ remains as the same.(iii)
The bionomic equilibrium and the optimal equilibrium will become unfeasible if the toxicant is large enough.(iv)
The immature, mature populations, and the harvesting effect in the optimal equilibrium are decreasing as the toxicant is increasing.(v)
The optimal equilibrium becomes more and more close to the bionomic equilibrium as the toxicant effect increases.
## 7. Discussion
In this paper, we consider the single-species stage structure model incorporating both toxicant and harvesting, and we assume that only the immature affected by the toxicant.Firstly, we explore the local and global stability properties of the equilibria of the system. Next, we investigate the existence and stability properties of the bionomic equilibrium. Finally, the optimal harvesting is studied, and it is found that there exists two optimal equilibria when the toxicant varies in a certain set. Some numeric examples to illustrate how the equilibrium (include bionomic equilibrium and optimal equilibrium) changes with the toxicant are also given.Nevertheless, as we know, the immature needs a certain time to develop to mature stage, the model incorporating time delay may be more reasonable and worth further study, and we leave this for future study.
---
*Source: 290123-2010-01-26.xml* | 2009 |
# Comparison of Back Propagation Neural Network and Genetic Algorithm Neural Network for Stream Flow Prediction
**Authors:** C. Chandre Gowda; S. G. Mayya
**Journal:** Journal of Computational Environmental Sciences
(2014)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2014/290127
---
## Abstract
Comparison of stream flow prediction models has been presented. Stream flow prediction model was developed using typical back propagation neural network (BPNN) and genetic algorithm coupled with neural network (GANN). The study uses daily data from Nethravathi River basin (Karnataka, India). The study demonstrates the prediction ability of GANN. The statistical tests show that GANN model performs much better when compared to BPNN model.
---
## Body
## 1. Introduction
Stream flow prediction for a river has been one of the most explored areas of research during recent days. Predicting the flow may facilitate its monitoring. Prediction of stream flows with good probability and reliability is of great concern. Precise prediction of stream flow gives a clear picture of the available water resources. It may also facilitate improved planning and optimum utilization of water. Many factors influence stream flow such as catchment characteristics and geographical and meteorological factors. Stream flow models may show high nonlinearity. From the second half of the last century, different methods such as physical, empirical, and numerical methods and other hybrid black box models have been practised for stream flow prediction. Main drawbacks observed in using physical model are the requirement of a more accurate and large data set which is tedious to acquire. The black box models may have an advantage at this context as they require minimum data and may provide satisfactory results. Neural network (NN), genetic algorithm, and fuzzy and hybrid algorithms are some of the methods which have received lots of attention among all modelling techniques during recent decades.The potential of NN had already been demonstrated in the context of river flow [1, 2] and dissolution kinetics [3] emphasizing the prediction ability of NN models. NN models were capable of reconstructing rainfall runoff relationships [4]. NN has proven an alternative to conventional rainfall runoff models and its strength in adaptive learning was shown for flow forecasting in the study [5]. Probabilistic forecasting accuracy was achieved using NN [6]. Modelling potential of NN was compared to a physical model and it was proven that NN has good prediction capability [7]. Good prediction accuracy and flexibility of NN were demonstrated in the studies [8, 9]. The ability of neuroemulation to imitate the behaviour of real cases and capture nonlinearity has made it a suitable method for modelling. Back propagation learning algorithm using gradient (steepest descent) based approach is widely used in the neural network training. The training of NN is done by minimizing the error function (Mean Square Error or Root Mean Square Error) between the predicted and the observed value. However, a back propagation learning algorithm with gradient based approach in neural network training has numerous drawbacks such as the fact that performance depends on initial weights and that the likelihood of solution reaching global optimum is not assured. In order to overcome these limitations, it is essential to develop an efficient method to optimize the NN. Genetic algorithm (GA) has been successfully employed in overcoming the limitations of back propagation learning algorithm in recent investigations [10, 11]. Thus, this study shows the implementation of GA into a neural network for stream flow prediction.In the present study, two models, back propagation neural network (BPNN) and genetic algorithm neural network (GANN), are developed and compared in predicting stream flow in natural rivers. BPNN was trained using the steepest descent method to optimize connecting weights for fixed network parameters. BPNN architecture parameters (number of neurons in hidden layer, bias, momentum, and learning rate) are obtained by trial and error. In GANN model, genetic algorithm was used to optimize both neural network (NN) parameters and connecting weights, which has not been attempted in the previous studies.
## 2. Methodology
### 2.1. Neural Network
Neural network (NN) models are parallel computing networks inspired by animal nervous system. They are adopted more commonly for forecasting and prediction in many fields. A neural network typically consists of input layer (with “n” input neurons), one or many hidden layers (with “m” number of hidden layers and “o” number of hidden neurons), and an output layer (with “p” number of output neurons). The neural network vectors are shown below:
(1)
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input layer
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⋮
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hidden layer
(
o
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o
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o
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output layer
.Each layer will be interconnected with the weights (randomly generated). The information has to be feed-forwarded from each input neuron to all hidden neurons through these weights. Then, information processes use transfer function (linear or sigmoid) at each hidden neuron. Then, all the processed values have to be summed up at each hidden neuron and information to be passed on to the output neuron through connecting weights. Then again, the information is to be processed through transfer function at output neuron to get final value. Bias is considered in order to eliminate or offset the dominant solutions at hidden layer and at output layer. The whole process of feed-forward from input layer to output layer is termed as feed-forward process.The final observed value at the output layer is compared with the target value. The difference in error between the observed and predicted value is then evaluated. Then, a back propagation process is used to back-propagate errors until the weights are optimized to obtain minimum error between the observed and predicted value. In back propagation, partial derivatives with respect to the connected weights are calculated. Chain rule is used to get the updated weights [12].The updating continues until the stopping criteria are met (for thousand iterations or minimum difference in error is obtained). Different learning techniques, like steepest descent method, Scaled Conjugate, Levenberg Marquardt, and others, are available. Learning rate accelerates the learning process and momentum pushes the solution towards convergence. Minimization of (MSE, RMSE) error is considered as the objective of the neural network.In the current study, neural network with an input layer (with 5 input neurons), single hidden layer (with 10 hidden neurons and tan sigmoid as activation function), and output layer (with 1 hidden neuron and tan sigmoid as activation function) was adopted. Bias, learning rate, momentum, activation constant, and number of hidden neurons were considered as the parameters of neural network architecture. The optimal value of network parameters was selected by trial and error. The best combination of the network parameters was used to optimize the network weights. The error between the predicted and the observed value was computed from (2). Steepest descent method was adopted as a learning technique to optimize the weights. The model was termed as back propagation neural network (BPNN) in the study:
(2)
E
=
1
2
(
T
o
-
O
o
)
2
,
where T
o
= predicted output, O
o
= observed output, and E
= error function.
### 2.2. Genetic Algorithm
Genetic algorithm (GA) is a heuristic search technique that works on the principle of natural genetics and natural selection [13]. It has been proven that genetic algorithms are able to find the global optimum solution in many research problems. The working procedure of GA usually starts with random strings representing design or decision variables. Later, each string is evaluated (checking objective and constraint conditions) to allocate the fitness value. Then termination condition is verified in the algorithm. In case if termination criterion is not met, then population has to be operated by the crossover, reproduction, and mutation functions. These three functions are used to create a new population. The new population is then evaluated and tested for fitness function. Reproduction duplicates the good strings. Roulette wheel, rank selection, and tournament selection are the three types of reproduction operator (in the study, rank selection has been adopted). Crossover operation creates new strings. Mutation operator takes care of diversity (to avoid the trapping of the good strings) in the population. The iterative operation is continued till the last generation in the population or till the desired solution is obtained.In the current study, genetic algorithm was used to optimize network parameters (bias, learning rate, momentum, activation constant, and number of hidden neurons) and weights in neural network algorithm. The GA parameters (mutation probability, number of generations, and number of populations) were selected by trial-and-error method. This method was named as genetic algorithm neural network (GANN) in the study.
## 2.1. Neural Network
Neural network (NN) models are parallel computing networks inspired by animal nervous system. They are adopted more commonly for forecasting and prediction in many fields. A neural network typically consists of input layer (with “n” input neurons), one or many hidden layers (with “m” number of hidden layers and “o” number of hidden neurons), and an output layer (with “p” number of output neurons). The neural network vectors are shown below:
(1)
(
i
1
i
2
⋮
i
n
)
︸
input layer
(
h
11
h
12
⋯
h
1
m
h
21
h
22
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h
2
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⋮
⋮
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h
o
m
)
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hidden layer
(
o
1
o
2
⋮
o
p
)
︸
output layer
.Each layer will be interconnected with the weights (randomly generated). The information has to be feed-forwarded from each input neuron to all hidden neurons through these weights. Then, information processes use transfer function (linear or sigmoid) at each hidden neuron. Then, all the processed values have to be summed up at each hidden neuron and information to be passed on to the output neuron through connecting weights. Then again, the information is to be processed through transfer function at output neuron to get final value. Bias is considered in order to eliminate or offset the dominant solutions at hidden layer and at output layer. The whole process of feed-forward from input layer to output layer is termed as feed-forward process.The final observed value at the output layer is compared with the target value. The difference in error between the observed and predicted value is then evaluated. Then, a back propagation process is used to back-propagate errors until the weights are optimized to obtain minimum error between the observed and predicted value. In back propagation, partial derivatives with respect to the connected weights are calculated. Chain rule is used to get the updated weights [12].The updating continues until the stopping criteria are met (for thousand iterations or minimum difference in error is obtained). Different learning techniques, like steepest descent method, Scaled Conjugate, Levenberg Marquardt, and others, are available. Learning rate accelerates the learning process and momentum pushes the solution towards convergence. Minimization of (MSE, RMSE) error is considered as the objective of the neural network.In the current study, neural network with an input layer (with 5 input neurons), single hidden layer (with 10 hidden neurons and tan sigmoid as activation function), and output layer (with 1 hidden neuron and tan sigmoid as activation function) was adopted. Bias, learning rate, momentum, activation constant, and number of hidden neurons were considered as the parameters of neural network architecture. The optimal value of network parameters was selected by trial and error. The best combination of the network parameters was used to optimize the network weights. The error between the predicted and the observed value was computed from (2). Steepest descent method was adopted as a learning technique to optimize the weights. The model was termed as back propagation neural network (BPNN) in the study:
(2)
E
=
1
2
(
T
o
-
O
o
)
2
,
where T
o
= predicted output, O
o
= observed output, and E
= error function.
## 2.2. Genetic Algorithm
Genetic algorithm (GA) is a heuristic search technique that works on the principle of natural genetics and natural selection [13]. It has been proven that genetic algorithms are able to find the global optimum solution in many research problems. The working procedure of GA usually starts with random strings representing design or decision variables. Later, each string is evaluated (checking objective and constraint conditions) to allocate the fitness value. Then termination condition is verified in the algorithm. In case if termination criterion is not met, then population has to be operated by the crossover, reproduction, and mutation functions. These three functions are used to create a new population. The new population is then evaluated and tested for fitness function. Reproduction duplicates the good strings. Roulette wheel, rank selection, and tournament selection are the three types of reproduction operator (in the study, rank selection has been adopted). Crossover operation creates new strings. Mutation operator takes care of diversity (to avoid the trapping of the good strings) in the population. The iterative operation is continued till the last generation in the population or till the desired solution is obtained.In the current study, genetic algorithm was used to optimize network parameters (bias, learning rate, momentum, activation constant, and number of hidden neurons) and weights in neural network algorithm. The GA parameters (mutation probability, number of generations, and number of populations) were selected by trial-and-error method. This method was named as genetic algorithm neural network (GANN) in the study.
## 3. Study Area
Nethravathi River basin is situated in Karnataka, India. It is located between 74° 45′ E and 75° 45′ E longitude and 12° 30′ N and 13° 10′ N latitude on Western Ghats (Figure1). Catchment stretches around 3184 km2. The annual rainfall over the area varies between 1500 mm and 4500 mm, receives rainfall mainly during monsoon months (June to September), and continues till November. The daily rainfall data and stream flow data used in the study are obtained from Indian Meteorological Department (IMD) and Central Water Commission (CWC).Figure 1
Nethravathi River basin in Karnataka, India.Twelve rain gauge stations in the Nethravathi River basin were selected and their corresponding Thiessen weights were found. Since the rainfall in nonmonsoon periods in the river basin is zero, only the monsoon days are considered. Lag time, precipitationP
t, P
t
-
1, and P
t
-
2, and runoff Q
t
-
1, Q
t
-
2 were considered as the input for modelling purposes. Evaporation and base flow were not considered in the analysis. The current runoff Q
t was considered as the output model variable, with t being current time period, t
-
1 being lag of 1 day, and t
-
2 being lag of 2 days. The inputs were selected by partial autocorrelation analysis, which showed good correlation values up to two days’ lag.The daily rainfall and daily runoff data were used for modelling. 80% of the data was used for training and 20% of the data for testing. The stream flow and rainfall data were normalized in the range from 0.1 to 0.9 from(3)
x
s
=
0.1
+
0.8
(
x
i
x
max
)
,
where x
s is normalized value of x
i, x
i is the observed value, and x
max
is the maximum value of the data set used.
## 4. Prediction Model
Daily stream flow modelling was carried out using back propagation neural network (BPNN) and genetic algorithm neural network (GANN). The parameters of BPNN architecture were number of neurons (at hidden layer), learning rate (at hidden layer and output layer), bias, momentum or alpha (at hidden layer and output layer), and activation constant (at hidden layer and output layer), as shown in Table1. BPNN architecture was selected by trial and error. After selecting the best suitable architecture, network was simulated to update weights. Steepest descent method was adopted to train the network and to optimize the weights in the BPNN model. The parameters selected in GANN model are mutation probability, population size, and number of generations, shown in Table 2. In GANN, the genetic algorithm parameters were also selected by trial and error. In the study, the adopted neural network consists of an input layer (with 5 input neurons), single hidden layer (with 10 hidden neurons), and output layer (with one output neuron), shown in Figure 2.Table 1
Parameter range of NN architecture.
Parameter
Range
Minimum
Maximum
Optimum(from trial and error)
Number of hidden neurons
2.0
25.00
10.00
Learning rate at hidden layer
0.1
0.99
00.500
Learning rate at output layer
0.1
0.99
00.550
Momentum rate
0.1
0.99
00.445
Hidden layer activation constant
1.0
10.00
05.500
Output layer activation constant
1.0
10.00
05.500
Bias
0.000001
0.00001
0.000085Table 2
Parameter range of GANN.
Parameter
Range
Minimum
Maximum
Optimum(from trial and error)
Mutation probability
0.00001515
0.0001515
0.0000424
Number of population
50
300
190
Number of Generations
100
500
210Figure 2
Neural network architecture.In genetic algorithm, neural network model (GANN) genetic algorithm was adopted to optimize the weights and neural network parameters. The program was written in C++ language for BPNN and GANN (binary coded genetic algorithm integrated with neural network).The GANN and BPNN performances were compared. Nash Sutcliffe efficiency (NS), coefficient of determination (R
2), Mean Absolute Percentage error (MAPE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) were used to check the performances of the models.
## 5. Results and Discussion
One day ahead stream flow prediction model was developed using BPNN and GANN. Rainfall lag time and stream flow lag time (i.e., one-day lag and two-day lag) were used as input to predict one day ahead stream flow. BPNN and GANN models were tested using NS,R
2, MAE, RMSE, and MAPE, shown in Table 3.Table 3
Efficiency for test cases of the models developed.
GANN
BPNN
Nash Sutcliffe (NS)
0.847
0.815
Coefficient of determination (R
2)
0.901
0.881
Mean Absolute Error (MAE) m3/s
167
182
Root Mean Square Error (RMSE) m3/s
220
242
Mean Absolute Percentage Error (MAPE) %
15.68
17.29Scatter plots in Figures3 and 4 show the comparison between the model predicted and the model observed flow values for BPNN and GANN models, respectively. In particular, results in Figure 3 show the BPNN model to overestimate the predicted values of flow with respect to the observed values when stream flow range is less than 1300 m3/s. Oppositely, when stream flow range is higher than 1300 m3/s, the BPNN model underestimates the observed flow values. Very similar results are observed in Figure 4 for simulations concerning the GANN model.Figure 3
Scatter plot of the observed stream flow against the BPNN model predicted stream flow.Figure 4
Scatter plot of the observed stream flow against the GANN model predicted stream flow.The time series plot of BPNN and GANN is plotted in Figures5 and 6. It was observed that both of the models have not captured extreme values properly. However, GANN follows the trend of the observed flow and has captured more extremities when compared to BPNN (Figures 5 and 6).Figure 5
Time series plot of the observed stream flow and the BPNN model predicted stream flow.Figure 6
Time series plot of the observed stream flow and the GANN model predicted stream flow.Table3 shows that MAE, MAPE, and RMSE of the GANN model were much lower compared to those of the BPNN model. MAPE of GANN was nearly 2% lower than BPNN values. MAE of GANN model was nearly 10% lower than MAE of BPNN model. Both BPNN and GANN show good Nash Sutcliffe efficiency but GANN shows a better coefficient of determination than BPNN (Table 3). RMSE of BPNN model was 10% higher than RMSE of GANN model. Due to the effective random search and flexible problem solving method of GANN, it was able to predict better than BPNN. It was observed that GANN model has outperformed BPNN model by showing good efficiency during testing. The limitations of BPNN must have contributed for its lower performance when compared with GANN.
## 6. Summary and Conclusion
Two NN based models, namely, BPNN and GANN, were developed for the prediction of daily stream flows. The performances of the models were evaluated using statistical analysis. From their analysis, GANN model’s predicted values were found to be very close to the observed values in comparison to BPNN model. This indicates that GANN shows greater potential to capture the existing nonlinearity in stream flows. The improved performance of GANN might be due to heuristic search for the optimal solution at many distinct locations simultaneously. Thus, the GA has a greater probability to reach the global minima. Conversely, back propagation algorithm training on steepest descent approach having fallen behind GANN model might be due to the trapping of good solutions in local optima, when the error surface is multimodal. Therefore, GANN model is considered to be more useful for hydrological forecasting and water resource management.
---
*Source: 290127-2014-08-28.xml* | 290127-2014-08-28_290127-2014-08-28.md | 21,840 | Comparison of Back Propagation Neural Network and Genetic Algorithm Neural Network for Stream Flow Prediction | C. Chandre Gowda; S. G. Mayya | Journal of Computational Environmental Sciences
(2014) | Engineering & Technology | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2014/290127 | 290127-2014-08-28.xml | ---
## Abstract
Comparison of stream flow prediction models has been presented. Stream flow prediction model was developed using typical back propagation neural network (BPNN) and genetic algorithm coupled with neural network (GANN). The study uses daily data from Nethravathi River basin (Karnataka, India). The study demonstrates the prediction ability of GANN. The statistical tests show that GANN model performs much better when compared to BPNN model.
---
## Body
## 1. Introduction
Stream flow prediction for a river has been one of the most explored areas of research during recent days. Predicting the flow may facilitate its monitoring. Prediction of stream flows with good probability and reliability is of great concern. Precise prediction of stream flow gives a clear picture of the available water resources. It may also facilitate improved planning and optimum utilization of water. Many factors influence stream flow such as catchment characteristics and geographical and meteorological factors. Stream flow models may show high nonlinearity. From the second half of the last century, different methods such as physical, empirical, and numerical methods and other hybrid black box models have been practised for stream flow prediction. Main drawbacks observed in using physical model are the requirement of a more accurate and large data set which is tedious to acquire. The black box models may have an advantage at this context as they require minimum data and may provide satisfactory results. Neural network (NN), genetic algorithm, and fuzzy and hybrid algorithms are some of the methods which have received lots of attention among all modelling techniques during recent decades.The potential of NN had already been demonstrated in the context of river flow [1, 2] and dissolution kinetics [3] emphasizing the prediction ability of NN models. NN models were capable of reconstructing rainfall runoff relationships [4]. NN has proven an alternative to conventional rainfall runoff models and its strength in adaptive learning was shown for flow forecasting in the study [5]. Probabilistic forecasting accuracy was achieved using NN [6]. Modelling potential of NN was compared to a physical model and it was proven that NN has good prediction capability [7]. Good prediction accuracy and flexibility of NN were demonstrated in the studies [8, 9]. The ability of neuroemulation to imitate the behaviour of real cases and capture nonlinearity has made it a suitable method for modelling. Back propagation learning algorithm using gradient (steepest descent) based approach is widely used in the neural network training. The training of NN is done by minimizing the error function (Mean Square Error or Root Mean Square Error) between the predicted and the observed value. However, a back propagation learning algorithm with gradient based approach in neural network training has numerous drawbacks such as the fact that performance depends on initial weights and that the likelihood of solution reaching global optimum is not assured. In order to overcome these limitations, it is essential to develop an efficient method to optimize the NN. Genetic algorithm (GA) has been successfully employed in overcoming the limitations of back propagation learning algorithm in recent investigations [10, 11]. Thus, this study shows the implementation of GA into a neural network for stream flow prediction.In the present study, two models, back propagation neural network (BPNN) and genetic algorithm neural network (GANN), are developed and compared in predicting stream flow in natural rivers. BPNN was trained using the steepest descent method to optimize connecting weights for fixed network parameters. BPNN architecture parameters (number of neurons in hidden layer, bias, momentum, and learning rate) are obtained by trial and error. In GANN model, genetic algorithm was used to optimize both neural network (NN) parameters and connecting weights, which has not been attempted in the previous studies.
## 2. Methodology
### 2.1. Neural Network
Neural network (NN) models are parallel computing networks inspired by animal nervous system. They are adopted more commonly for forecasting and prediction in many fields. A neural network typically consists of input layer (with “n” input neurons), one or many hidden layers (with “m” number of hidden layers and “o” number of hidden neurons), and an output layer (with “p” number of output neurons). The neural network vectors are shown below:
(1)
(
i
1
i
2
⋮
i
n
)
︸
input layer
(
h
11
h
12
⋯
h
1
m
h
21
h
22
⋯
h
2
m
⋮
⋮
⋮
⋮
h
o
1
h
o
2
⋯
h
o
m
)
︸
hidden layer
(
o
1
o
2
⋮
o
p
)
︸
output layer
.Each layer will be interconnected with the weights (randomly generated). The information has to be feed-forwarded from each input neuron to all hidden neurons through these weights. Then, information processes use transfer function (linear or sigmoid) at each hidden neuron. Then, all the processed values have to be summed up at each hidden neuron and information to be passed on to the output neuron through connecting weights. Then again, the information is to be processed through transfer function at output neuron to get final value. Bias is considered in order to eliminate or offset the dominant solutions at hidden layer and at output layer. The whole process of feed-forward from input layer to output layer is termed as feed-forward process.The final observed value at the output layer is compared with the target value. The difference in error between the observed and predicted value is then evaluated. Then, a back propagation process is used to back-propagate errors until the weights are optimized to obtain minimum error between the observed and predicted value. In back propagation, partial derivatives with respect to the connected weights are calculated. Chain rule is used to get the updated weights [12].The updating continues until the stopping criteria are met (for thousand iterations or minimum difference in error is obtained). Different learning techniques, like steepest descent method, Scaled Conjugate, Levenberg Marquardt, and others, are available. Learning rate accelerates the learning process and momentum pushes the solution towards convergence. Minimization of (MSE, RMSE) error is considered as the objective of the neural network.In the current study, neural network with an input layer (with 5 input neurons), single hidden layer (with 10 hidden neurons and tan sigmoid as activation function), and output layer (with 1 hidden neuron and tan sigmoid as activation function) was adopted. Bias, learning rate, momentum, activation constant, and number of hidden neurons were considered as the parameters of neural network architecture. The optimal value of network parameters was selected by trial and error. The best combination of the network parameters was used to optimize the network weights. The error between the predicted and the observed value was computed from (2). Steepest descent method was adopted as a learning technique to optimize the weights. The model was termed as back propagation neural network (BPNN) in the study:
(2)
E
=
1
2
(
T
o
-
O
o
)
2
,
where T
o
= predicted output, O
o
= observed output, and E
= error function.
### 2.2. Genetic Algorithm
Genetic algorithm (GA) is a heuristic search technique that works on the principle of natural genetics and natural selection [13]. It has been proven that genetic algorithms are able to find the global optimum solution in many research problems. The working procedure of GA usually starts with random strings representing design or decision variables. Later, each string is evaluated (checking objective and constraint conditions) to allocate the fitness value. Then termination condition is verified in the algorithm. In case if termination criterion is not met, then population has to be operated by the crossover, reproduction, and mutation functions. These three functions are used to create a new population. The new population is then evaluated and tested for fitness function. Reproduction duplicates the good strings. Roulette wheel, rank selection, and tournament selection are the three types of reproduction operator (in the study, rank selection has been adopted). Crossover operation creates new strings. Mutation operator takes care of diversity (to avoid the trapping of the good strings) in the population. The iterative operation is continued till the last generation in the population or till the desired solution is obtained.In the current study, genetic algorithm was used to optimize network parameters (bias, learning rate, momentum, activation constant, and number of hidden neurons) and weights in neural network algorithm. The GA parameters (mutation probability, number of generations, and number of populations) were selected by trial-and-error method. This method was named as genetic algorithm neural network (GANN) in the study.
## 2.1. Neural Network
Neural network (NN) models are parallel computing networks inspired by animal nervous system. They are adopted more commonly for forecasting and prediction in many fields. A neural network typically consists of input layer (with “n” input neurons), one or many hidden layers (with “m” number of hidden layers and “o” number of hidden neurons), and an output layer (with “p” number of output neurons). The neural network vectors are shown below:
(1)
(
i
1
i
2
⋮
i
n
)
︸
input layer
(
h
11
h
12
⋯
h
1
m
h
21
h
22
⋯
h
2
m
⋮
⋮
⋮
⋮
h
o
1
h
o
2
⋯
h
o
m
)
︸
hidden layer
(
o
1
o
2
⋮
o
p
)
︸
output layer
.Each layer will be interconnected with the weights (randomly generated). The information has to be feed-forwarded from each input neuron to all hidden neurons through these weights. Then, information processes use transfer function (linear or sigmoid) at each hidden neuron. Then, all the processed values have to be summed up at each hidden neuron and information to be passed on to the output neuron through connecting weights. Then again, the information is to be processed through transfer function at output neuron to get final value. Bias is considered in order to eliminate or offset the dominant solutions at hidden layer and at output layer. The whole process of feed-forward from input layer to output layer is termed as feed-forward process.The final observed value at the output layer is compared with the target value. The difference in error between the observed and predicted value is then evaluated. Then, a back propagation process is used to back-propagate errors until the weights are optimized to obtain minimum error between the observed and predicted value. In back propagation, partial derivatives with respect to the connected weights are calculated. Chain rule is used to get the updated weights [12].The updating continues until the stopping criteria are met (for thousand iterations or minimum difference in error is obtained). Different learning techniques, like steepest descent method, Scaled Conjugate, Levenberg Marquardt, and others, are available. Learning rate accelerates the learning process and momentum pushes the solution towards convergence. Minimization of (MSE, RMSE) error is considered as the objective of the neural network.In the current study, neural network with an input layer (with 5 input neurons), single hidden layer (with 10 hidden neurons and tan sigmoid as activation function), and output layer (with 1 hidden neuron and tan sigmoid as activation function) was adopted. Bias, learning rate, momentum, activation constant, and number of hidden neurons were considered as the parameters of neural network architecture. The optimal value of network parameters was selected by trial and error. The best combination of the network parameters was used to optimize the network weights. The error between the predicted and the observed value was computed from (2). Steepest descent method was adopted as a learning technique to optimize the weights. The model was termed as back propagation neural network (BPNN) in the study:
(2)
E
=
1
2
(
T
o
-
O
o
)
2
,
where T
o
= predicted output, O
o
= observed output, and E
= error function.
## 2.2. Genetic Algorithm
Genetic algorithm (GA) is a heuristic search technique that works on the principle of natural genetics and natural selection [13]. It has been proven that genetic algorithms are able to find the global optimum solution in many research problems. The working procedure of GA usually starts with random strings representing design or decision variables. Later, each string is evaluated (checking objective and constraint conditions) to allocate the fitness value. Then termination condition is verified in the algorithm. In case if termination criterion is not met, then population has to be operated by the crossover, reproduction, and mutation functions. These three functions are used to create a new population. The new population is then evaluated and tested for fitness function. Reproduction duplicates the good strings. Roulette wheel, rank selection, and tournament selection are the three types of reproduction operator (in the study, rank selection has been adopted). Crossover operation creates new strings. Mutation operator takes care of diversity (to avoid the trapping of the good strings) in the population. The iterative operation is continued till the last generation in the population or till the desired solution is obtained.In the current study, genetic algorithm was used to optimize network parameters (bias, learning rate, momentum, activation constant, and number of hidden neurons) and weights in neural network algorithm. The GA parameters (mutation probability, number of generations, and number of populations) were selected by trial-and-error method. This method was named as genetic algorithm neural network (GANN) in the study.
## 3. Study Area
Nethravathi River basin is situated in Karnataka, India. It is located between 74° 45′ E and 75° 45′ E longitude and 12° 30′ N and 13° 10′ N latitude on Western Ghats (Figure1). Catchment stretches around 3184 km2. The annual rainfall over the area varies between 1500 mm and 4500 mm, receives rainfall mainly during monsoon months (June to September), and continues till November. The daily rainfall data and stream flow data used in the study are obtained from Indian Meteorological Department (IMD) and Central Water Commission (CWC).Figure 1
Nethravathi River basin in Karnataka, India.Twelve rain gauge stations in the Nethravathi River basin were selected and their corresponding Thiessen weights were found. Since the rainfall in nonmonsoon periods in the river basin is zero, only the monsoon days are considered. Lag time, precipitationP
t, P
t
-
1, and P
t
-
2, and runoff Q
t
-
1, Q
t
-
2 were considered as the input for modelling purposes. Evaporation and base flow were not considered in the analysis. The current runoff Q
t was considered as the output model variable, with t being current time period, t
-
1 being lag of 1 day, and t
-
2 being lag of 2 days. The inputs were selected by partial autocorrelation analysis, which showed good correlation values up to two days’ lag.The daily rainfall and daily runoff data were used for modelling. 80% of the data was used for training and 20% of the data for testing. The stream flow and rainfall data were normalized in the range from 0.1 to 0.9 from(3)
x
s
=
0.1
+
0.8
(
x
i
x
max
)
,
where x
s is normalized value of x
i, x
i is the observed value, and x
max
is the maximum value of the data set used.
## 4. Prediction Model
Daily stream flow modelling was carried out using back propagation neural network (BPNN) and genetic algorithm neural network (GANN). The parameters of BPNN architecture were number of neurons (at hidden layer), learning rate (at hidden layer and output layer), bias, momentum or alpha (at hidden layer and output layer), and activation constant (at hidden layer and output layer), as shown in Table1. BPNN architecture was selected by trial and error. After selecting the best suitable architecture, network was simulated to update weights. Steepest descent method was adopted to train the network and to optimize the weights in the BPNN model. The parameters selected in GANN model are mutation probability, population size, and number of generations, shown in Table 2. In GANN, the genetic algorithm parameters were also selected by trial and error. In the study, the adopted neural network consists of an input layer (with 5 input neurons), single hidden layer (with 10 hidden neurons), and output layer (with one output neuron), shown in Figure 2.Table 1
Parameter range of NN architecture.
Parameter
Range
Minimum
Maximum
Optimum(from trial and error)
Number of hidden neurons
2.0
25.00
10.00
Learning rate at hidden layer
0.1
0.99
00.500
Learning rate at output layer
0.1
0.99
00.550
Momentum rate
0.1
0.99
00.445
Hidden layer activation constant
1.0
10.00
05.500
Output layer activation constant
1.0
10.00
05.500
Bias
0.000001
0.00001
0.000085Table 2
Parameter range of GANN.
Parameter
Range
Minimum
Maximum
Optimum(from trial and error)
Mutation probability
0.00001515
0.0001515
0.0000424
Number of population
50
300
190
Number of Generations
100
500
210Figure 2
Neural network architecture.In genetic algorithm, neural network model (GANN) genetic algorithm was adopted to optimize the weights and neural network parameters. The program was written in C++ language for BPNN and GANN (binary coded genetic algorithm integrated with neural network).The GANN and BPNN performances were compared. Nash Sutcliffe efficiency (NS), coefficient of determination (R
2), Mean Absolute Percentage error (MAPE), Root Mean Square Error (RMSE), and Mean Absolute Error (MAE) were used to check the performances of the models.
## 5. Results and Discussion
One day ahead stream flow prediction model was developed using BPNN and GANN. Rainfall lag time and stream flow lag time (i.e., one-day lag and two-day lag) were used as input to predict one day ahead stream flow. BPNN and GANN models were tested using NS,R
2, MAE, RMSE, and MAPE, shown in Table 3.Table 3
Efficiency for test cases of the models developed.
GANN
BPNN
Nash Sutcliffe (NS)
0.847
0.815
Coefficient of determination (R
2)
0.901
0.881
Mean Absolute Error (MAE) m3/s
167
182
Root Mean Square Error (RMSE) m3/s
220
242
Mean Absolute Percentage Error (MAPE) %
15.68
17.29Scatter plots in Figures3 and 4 show the comparison between the model predicted and the model observed flow values for BPNN and GANN models, respectively. In particular, results in Figure 3 show the BPNN model to overestimate the predicted values of flow with respect to the observed values when stream flow range is less than 1300 m3/s. Oppositely, when stream flow range is higher than 1300 m3/s, the BPNN model underestimates the observed flow values. Very similar results are observed in Figure 4 for simulations concerning the GANN model.Figure 3
Scatter plot of the observed stream flow against the BPNN model predicted stream flow.Figure 4
Scatter plot of the observed stream flow against the GANN model predicted stream flow.The time series plot of BPNN and GANN is plotted in Figures5 and 6. It was observed that both of the models have not captured extreme values properly. However, GANN follows the trend of the observed flow and has captured more extremities when compared to BPNN (Figures 5 and 6).Figure 5
Time series plot of the observed stream flow and the BPNN model predicted stream flow.Figure 6
Time series plot of the observed stream flow and the GANN model predicted stream flow.Table3 shows that MAE, MAPE, and RMSE of the GANN model were much lower compared to those of the BPNN model. MAPE of GANN was nearly 2% lower than BPNN values. MAE of GANN model was nearly 10% lower than MAE of BPNN model. Both BPNN and GANN show good Nash Sutcliffe efficiency but GANN shows a better coefficient of determination than BPNN (Table 3). RMSE of BPNN model was 10% higher than RMSE of GANN model. Due to the effective random search and flexible problem solving method of GANN, it was able to predict better than BPNN. It was observed that GANN model has outperformed BPNN model by showing good efficiency during testing. The limitations of BPNN must have contributed for its lower performance when compared with GANN.
## 6. Summary and Conclusion
Two NN based models, namely, BPNN and GANN, were developed for the prediction of daily stream flows. The performances of the models were evaluated using statistical analysis. From their analysis, GANN model’s predicted values were found to be very close to the observed values in comparison to BPNN model. This indicates that GANN shows greater potential to capture the existing nonlinearity in stream flows. The improved performance of GANN might be due to heuristic search for the optimal solution at many distinct locations simultaneously. Thus, the GA has a greater probability to reach the global minima. Conversely, back propagation algorithm training on steepest descent approach having fallen behind GANN model might be due to the trapping of good solutions in local optima, when the error surface is multimodal. Therefore, GANN model is considered to be more useful for hydrological forecasting and water resource management.
---
*Source: 290127-2014-08-28.xml* | 2014 |
# Relationship betweenHelicobacter pylori Infections in Diabetic Patients and Inflammations, Metabolic Syndrome, and Complications
**Authors:** Yusuf Kayar; Özgül Pamukçu; Hatice Eroğlu; Kübra Kalkan Erol; Aysegul Ilhan; Orhan Kocaman
**Journal:** International Journal of Chronic Diseases
(2015)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2015/290128
---
## Abstract
Helicobacter pylori infection and diabetes mellitus are two independent common diseases. It is showed that the worsening glycemic and metabolic control increases the rates ofHelicobacter pylori infections andHelicobacter pylori is shown as one of the common problems in diabetic patients with complaints of gastrointestinal diseases. In this study, we aimed to investigate the prevalence and eradication rates ofHelicobacter pylori in diabetic patients and the relationship ofHelicobacter pylori with the risk factors and diabetic complications. In our study, in which we have included 133 patients, we have shown a significant relationship betweenHelicobacter pylori infections and metabolic syndrome, insulin resistance, inflammations, and diabetic complications.
---
## Body
## 1. Introduction
Helicobacter pylori (HP) infections are very common worldwide, affecting approximately 50% of the world’s population, and are more common especially in developing countries [1]. Although the findings of various studies are inconsistent, the presence ofH. pylori is found to be higher in diabetic patients compared to nondiabetic patients [2–4].H. pylori colonizes in the gastric antrum in all patients, particularly in diabetic patients with impaired metabolic control [2–5]. Beside the well-defined gastric effects ofH. pylori infection, some studies are also published pointing the extragastric effects ofH. pylori infection which plays an additional role for the vascular damage in course of atherosclerosis [5, 6].The presence ofH. pylori and diabetes mellitus (DM) is one of the main causes of gastrointestinal diseases [2, 7]. Additionally, the presence ofH. pylori in DM cases plays an important role in the development of gastrointestinal diseases [7]. In particular, the worsening of glycemic and metabolic control increases the incidence ofH. pylori infections and complaints of dyspepsia [2, 7]. A significant relationship between dyslipidemia andH. pylori has been reported. In prospective studies, it has been shown thatH. pylori eradication improves dyslipidemia and insulin resistance and decreases inflammation [6]. Although the relationship betweenH. pylori infection and DM and the complications secondary to diabetes is not clear, it is known that neuropathy and hyperglycemia play an important role inH. pylori colonization in the gastric epithelium [8]. Although the findings of various studies are inconsistent, it has been shown that there is a significant relationship between microvascular complications (nephropathy, neuropathy, and retinopathy) andH. pylori [6, 9, 10].Although there is no clear-cut consensus in the literature, it has been reported that HPeradication is noticeably lower in diabetic patients. There are a limited number of studies on the factors that play a role in HPeradication. We investigated the HP prevalence, HP eradication rates, and confounding factors affecting HP eradication in diabetic patients.
## 2. Materials and Methods
133 dyspeptic patients aged 18 to 65 and recruited from the internal medicine outpatient clinic were included into the study. All patients provided written informed consent to participate. 62 out of 133 patients had Type 2 DM. Exclusion criteria were (1) patients over 65 years; (2) patients having diabetes for more than 5 years; (3) patients with apparent proteinuria, creatinine values of >1.2 mg/dL, triglyceride levels of >400 mg/dL, and HbA1C of >8% with positive urine culture; (4) patients who received ulcer treatment within the last three months; (5) patients currently using proton pump inhibitor or H2 receptor blockers; (6) patients with a history ofH. pylori eradication treatment; and (7) patients with vascular and inflammatory diseases.Demographics (age, gender, and duration of disease) of the patients were documented. Height, weight, and waist circumference were measured and BMI was calculated as weight/height2 (kg/m2). Systolic and diastolic blood pressure measurements using standard sphygmomanometry were performed. Biochemical investigation including hemoglobin A1C (HbA1C), cholesterol, triglyceride, HDL, LDL, fasting blood glucose, leukocyte count, thrombocyte count, erythrocyte sedimentation rate, C reactive protein, and fibrinogen levels was performed in all patients. Approval of the local ethics committee was obtained for the study.Peripheral vascular disease was assessed based on the presence of intermittent claudication clinically and the absence of pulse in physical examinations. Retinopathy was determined with standard fundus examination. The presence of neuropathy was determined as per abnormal sensorimotor findings in examinations. Patients with a protein amount of 30 to 300 mg in 24-hour urine were considered cases with microalbuminuria, and those with ≥300 mg were considered cases with apparent proteinuria. In order to determine HP infection, the HPantigen stool test was used as it is a useful method for detection of active and repetitive HP infections [11]. The success rate of eradication was checked four weeks after the end of all treatments.In all patients with dyspeptic complaints, the presence ofH. pylori was investigated by theH. pylori antigen stool test, and the patients were compared by dividing them into two groups (Type 2 DM patients and nondiabetic patients). The relationship betweenH. pylori positivity and demographic clinical anthropometric and inflammatory parameters was investigated in all patients. The relationship betweenH. pylori positivity and retinopathy, nephropathy, neuropathy, and HbA1C was investigated in diabetic patients.Eradication treatment (clarithromycin, amoxicillin, and omeprazole) was given toH. pylori positive patients for two weeks. Additional omeprazole treatment without antibiotics was continued for 4 weeks. Two weeks after cessation of all treatments, eradication rates were determined by stool antigen test and a comparison was made.
### 2.1. Statistical Analysis
SPSS 17.0 package program was used for statistical analysis of data. The data were summarized in percentage, mean ± SD, and median values. The presence ofH. pylori and eradication ofH. pylori, as well as the relationship with demographic clinical anthropometric and inflammatory parameters, were analyzed using chi-square test, Fischer’s exact test, and independent T-sample test. The relationship between the presence ofH. pylori and eradication ofH. pylori in diabetic patients was analyzed using chi-square test and Fischer’s exact test. The results were assessed with hazard ratio and in a 95% confidence interval. A P
<
0.05 value was considered statistically meaningful in the analyses.
## 2.1. Statistical Analysis
SPSS 17.0 package program was used for statistical analysis of data. The data were summarized in percentage, mean ± SD, and median values. The presence ofH. pylori and eradication ofH. pylori, as well as the relationship with demographic clinical anthropometric and inflammatory parameters, were analyzed using chi-square test, Fischer’s exact test, and independent T-sample test. The relationship between the presence ofH. pylori and eradication ofH. pylori in diabetic patients was analyzed using chi-square test and Fischer’s exact test. The results were assessed with hazard ratio and in a 95% confidence interval. A P
<
0.05 value was considered statistically meaningful in the analyses.
## 3. Results
H. pylori positivity was detected in 64.5% of the diabetic patients and in 43.6% of the control group.H. pylori positivity was detected in 53.4% of all patients. The relationship betweenH. pylori positivity and inflammatory, demographic, clinical, and anthropometric parameters was shown in Tables 1 and 2.Table 1
The relationship betweenH. pylori positivity and inflammatory parameters.
Variables
Total
H. pylori (+) subjects
H. pylori (−) subjects
P value
CRP*
4.8 ± 3.4
5.5 ± 3.9
3.9 ± 2.3
<0.05
Leukocytes
7.0 ± 1.8
7.1 ± 1.6
6.9 ± .9
NS
Thrombocytes
250 ± 65
252 ± 69
248 ± 61
NS
Sedimentation*
9.4 ± 8.2
11.3 ± 8.9
7.3 ± 6.8
<0.05
Ferritin*
86.5 ± 91.7
122 ± 105
45.6 ± 47
<0.05
Fibrinogen*
321 ± 77
336 ± 82
303 ± 67
<0.05
*Significant variables.Table 2
The relationship betweenH. pylori positivity and demographic, clinical, and anthropometric parameters.
Variables
Total
H. pylori (+) subjects
H. pylori (−) subjects
P value
Gender
Female
70
34 (48.5%)
36 (51.5%)
NS
Male
63
37 (58.7%)
26 (41.3%)
NS
Age
47 ± 12
48.7 ± 12.1
46.9 ± 13.1
NS
Body mass index
NS
Normal
30
12 (40%)
18 (60%)
NS
Overweight
53
31 (58.4%)
22 (41.6%)
NS
Obese
50
28 (56%)
22 (44%)
NS
Waistline*
94 ± 11
95.7 ± 10
91.9 ± 11.8
<0.05
Hypertension
Yes*
49
34 (69.3%)
15 (30.7%)
<0.05
No
84
37 (44%)
47 (56%)
NS
Cholesterol
NS
≥200
67
38 (56.7%)
29 (43.3%)
NS
<200
66
33 (50%)
33 (50%)
NS
Triglyceride
≥150*
42
30 (71.4%)
12 (28.6%)
<0.05
<150
91
41 (45%)
50 (55%)
NS
Low density lipoprotein
≥100
87
51 (58.6%)
36 (41.4%)
NS
<100
46
20 (43.4%)
26 (56.6%)
NS
High density lipoprotein
Male ≥40, female ≥50
98
47 (%47.9)
51 (52.1%)
NS
Male <40, female <50*
35
24 (68.5%)
11 (31.5%)
<0.05
Glucose*
106 ± 35
117 ± 41
93 ± 21
<0.05
Creatinine
0.8 ± 0.2
0.84 ± 0.23
0.78 ± 0.19
NS
Patient groups
DM*
62
40 (64.5%)
20 (35.5%)
<0.05
Non-DM
71
31 (43.6%)
40 (56.7%)
NS
*Significant variables.When the relationship between the complications in diabetic patients andH. pylori positivity was evaluated,H. pylori positivity was significantly associated with the presence of nephropathy and neuropathy. Although retinopathy was more common in patients withH. pylori positivity, no statistical significance was found between groups. Additionally, a significant relationship between glycemic control and the presence ofH. pylori was detected. While 48.5% of the patients with HbA1C ≤7 wereH. pylori positive, 82.8% of the patients with HbA1C >7 were found to beH. pylori positive (Table 3).Table 3
The relationship between the complications in diabetic patients andH. pylori positivity.
Variables
TotalDM
H. pylori (+) subjects
H. pylori (−) subjects
P value
Nephropathy
Yes*
23
21 (91.3%)
2 (8.7%)
<0.05
No
39
19 (48.7%)
20 (51.3%)
Neuropathy
Yes*
29
24 (82.8%)
5 (18.2%)
<0.05
No
33
16 (48.4%)
17 (51.6%)
Retinopathy
Yes
20
14 (70%)
6 (30%)
NS
No
42
24 (57.1%)
18 (42.9%)
HbA1C
6-7*
33
16 (48.5%)
17 (51.5%)
<0.05
7-8
29
24 (82.8%)
5 (17.2%)
*Significant variables.The rate ofH. pylori eradication in diabetic and control groups was 62.5% and 93.5%, respectively. The factors affecting the rate ofH. pylori eradication were shown in Table 4.Table 4
The factors affecting the rate ofH. pylori eradication.
Variables
Total
Those eradicated
Those not eradicated
P value
Gender
Female
34
25 (73.5%)
9 (26.5%)
NS
Male
37
29 (78.3%)
8 (21.7%)
Age
48.7 ± 12.1
48.1 ± 13.3
50.8 ± 7.2
NS
Body mass index
Normal
12
12 (100%)
0 (0%)
Overweight
31
28 (90.3%)
3 (9.7%)
Obese*
28
14 (50%)
14 (50%)
<0.05
Waistline*
95.7 ± 10
94.3 ± 9.8
100 ± 9.4
<0.05
Hypertension
Yes*
34
22 (64.7%)
12 (35.3%)
<0.05
No
37
32 (86.4%)
5 (13.6%)
Cholesterol
≥200*
38
24 (63.1%)
14 (36.9%)
<0.05
<200
33
30 (90.9%)
3 (9.1%)
Triglyceride
≥150*
30
19 (63.3%)
11 (36.7%)
<0.05
<150
41
35 (85.3%)
6 (14.7%)
Low density lipoprotein
NS
≥100
51
37 (72.5%)
14 (27.5%)
<100
20
17 (85%)
3 (15%)
High density lipoprotein
NS
Male ≥40, female ≥50
47
38 (80.8%)
9 (19.2%)
Male <40, female <50
24
16 (66.6%)
8 (33.4%)
Glucose*
117 ± 42
110 ± 39
140 ± 41
<0.05
Patient groups
DM*
40
25 (62.5%)
15 (37.5%)
<0.05
Non-DM
31
29 (93.5%)
2 (6.5%)
*Significant variables.When the relationship between the complications in diabetic patients andH. pylori eradication was evaluated, a significant relationship between nephropathy and neuropathy with successful eradication ofH. pylori was detected. Although retinopathy is more common in patients withoutH. pylori eradication, no statistical significance was detected. Additionally, a significant relationship between glycemic control and the presence ofH. pylori eradication was detected. WhileH. pylori were successfully eradicated in 81.2% of the patients with HbA1C ≤7,H. pylori could be eradicated in 50% of the patients with HbA1C (Table 5).Table 5
The relationship between the complications in diabetic patients andH. pylori eradication.
Variables
TotalDM
Those eradicated
Those not eradicated
P value
Nephropathy
Yes*
22
10 (45.4%)
12 (54.6%)
<0.05
No
18
15 (83.8%)
3 (16.7%)
Neuropathy
Yes*
24
11 (45.8%)
13 (54.2%)
<0.05
No
16
14 (87.5%)
2 (22.5%)
Retinopathy
Yes
16
9 (56%)
7 (44%)
NS
No
24
16 (66.6%)
8 (33.4%)
HbA1C
6-7*
16
13 (81.2%)
3 (18.8%)
<0.05
7-8
24
12 (50%)
12 (50%)
*Significant variables.
## 4. Discussion
DM patients are usually prone to chronic infections. While the findings of studies on the prevalence ofH. pylori in DM patients are contradictory, in our study,H. pylori positivity was detected in 64.5% of the DM patients and in 43.6% of the control group (P
<
0.05). While Gentile et al. found that the prevalence ofH. pylori infection was 74.4% in DM patients and 50% in the control group (P
<
0.01), Gentile et al. found that the prevalence ofH. pylori was significantly higher in the DM group compared to the control group [12, 13]. However, some studies did not find any significant difference in the DM group and the control group with regard toH. pylori infections [9, 14]. It is well known that diabetic patients are prone to chronic infections because of cellular and humoral immune deficiency. As a result of delayed gastric emptying due to gastroparesis diabeticorum, bacterial overgrowth occurs and this poses a risk forH. pylori infections. Achlorhydria and reduced acid secretion are a negative factor forH. pylori infections. Additionally, leukocyte dysfunction and hyperglycemia are a predisposing factor for infections and facilitate secondaryH. pylori colonization to antibiotics taken. Based on all these factors, it can be said that the prevalence ofH. pylori is increased in diabetics [9].Studies report that HP infections cause microvascular damage and trigger premature development of atherosclerosis in patients [5, 6]. Although the underlying mechanism is not fully known, there are many findings which support this [5]. First of all, it has been shown that HP plays a role in the thickening of the intima media, atherosclerotic plaque destabilization, and atherosclerotic plaque development after vessel wall invasion [5, 15]. Due to vessel wall invasion of the bacteria, an increase in maturation and activation of monocytes and an increase in the proliferation of smooth muscle or endothelial cells occur, and, as a result, thrombosis and ischemia develop. It is thought that the endotoxins produced by the bacteria play a role in the maturation of monocytes. Activation of monocytes leads to the production of inflammatory cytokines, after which it triggers platelet aggregation and procoagulant activity [16]. Secondly, atherosclerotic plaques due to HP trigger high amounts of IL-6 and TNF-α. An increase in these cytokines causes endothelial dysfunction and insulin resistance. While IL-6 increases the production of hepatic gluconeogenesis and triglycerides, TNF-α modifies the lipid levels by inhibiting the lipoprotein lipase activity and activating hepatic lipogenesis [17]. Thirdly, the inflammation secondary to the plaque which forms due to HP triggers the peroxidation of membrane lipids, oxidation of LDL cholesterol, antioxidant loss, an increase in production of various superoxidases, and activation of macrophages, T-lymphocytes, and lipoprotein-a [18]. Additionally, chronic HP infection causes atrophic gastritis, and, as a result of this, it reduces absorption of folate and B12. B12 and folate are required for conversion of homocysteine to methionine. However, the homocysteine level increases due to the deficiency of B12 and folate in HP infections. Homocysteine plays a role in vascular endothelial damage and increases atherogenesis and thrombogenesis. It also increases platelet functions, coagulation, and LDL oxidation [19]. Similar to our study, many other studies have shown that, in the presence of HP infection, inflammatory indicators increase significantly [5, 20]. It has been reported that, as a result of an increase in inflammation due to HP infection and the triggering of arthrosclerosis, insulin resistance and metabolic syndrome increase, and the complications also increase in diabetic patients. A study on the Japanese population has shown that metabolic syndrome increases in HP infection [21]. Gunji et al. have shown in their study that HP infection significantly increases insulin resistance in asymptomatic patients [22]. Similar to the said studies, our study has also shown that metabolic syndrome significantly increases in patients with HP infection. Hamed et al. have shown in their study that, in HP-positive diabetic patients, the prevalence of macrovascular (cardiovascular and cerebrovascular diseases) and microvascular (nephropathy, neuropathy, and retinopathy) complications is significantly higher [5]. Furthermore, there are studies which report that microalbuminuria is significantly higher in HP-positive patients, regardless of the development of diabetes [6]. Demir et al. have reported that there is a significant relationship between HP-positivity and neuropathy, but there is no significant relationship between HP-positivity and retinopathy and neuropathy [9]. Similar to the said studies, our study has found a significant relationship between HP-positivity and neuropathy but has not found a significant relationship between HP-positivity and retinopathy.HP eradication is more difficult in diabetic patients. Sargýn et al. attained 50% HP eradication in DM patients and 85% HP eradication in non-DM patients [7]. Zojaji et al. attained successful eradication in 62% of DM patients, and a significant relationship was found between eradication and HbA1C [23]. In a study by Tseng, it was reported that comorbid conditions such as obesity, dyslipidemia, retinopathy, and neuropathy were significantly associated with HP eradication [10]. Our study has also shown that HP eradication is significantly lower in diabetic patients with retinopathy and neuropathy and with impaired glycemic and metabolic control. The fact that the HP eradication percentage is low in diabetic patients can be explained by the immunosuppressive condition in DM patients. Additionally, frequent bacterial and mycotic infections and the development of resistance due to drug use also play an important role [24].As a result, we have shown in our study that there is a significant relationship between HP infections and metabolic syndrome, insulin resistance, inflammations, and diabetic complications. We have also shown that similar parameters are effective in HP eradication. In the light of the studies, we think that patients with impaired metabolic and glycemic control should be treated in case of HP infection.
---
*Source: 290128-2015-01-22.xml* | 290128-2015-01-22_290128-2015-01-22.md | 19,491 | Relationship betweenHelicobacter pylori Infections in Diabetic Patients and Inflammations, Metabolic Syndrome, and Complications | Yusuf Kayar; Özgül Pamukçu; Hatice Eroğlu; Kübra Kalkan Erol; Aysegul Ilhan; Orhan Kocaman | International Journal of Chronic Diseases
(2015) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2015/290128 | 290128-2015-01-22.xml | ---
## Abstract
Helicobacter pylori infection and diabetes mellitus are two independent common diseases. It is showed that the worsening glycemic and metabolic control increases the rates ofHelicobacter pylori infections andHelicobacter pylori is shown as one of the common problems in diabetic patients with complaints of gastrointestinal diseases. In this study, we aimed to investigate the prevalence and eradication rates ofHelicobacter pylori in diabetic patients and the relationship ofHelicobacter pylori with the risk factors and diabetic complications. In our study, in which we have included 133 patients, we have shown a significant relationship betweenHelicobacter pylori infections and metabolic syndrome, insulin resistance, inflammations, and diabetic complications.
---
## Body
## 1. Introduction
Helicobacter pylori (HP) infections are very common worldwide, affecting approximately 50% of the world’s population, and are more common especially in developing countries [1]. Although the findings of various studies are inconsistent, the presence ofH. pylori is found to be higher in diabetic patients compared to nondiabetic patients [2–4].H. pylori colonizes in the gastric antrum in all patients, particularly in diabetic patients with impaired metabolic control [2–5]. Beside the well-defined gastric effects ofH. pylori infection, some studies are also published pointing the extragastric effects ofH. pylori infection which plays an additional role for the vascular damage in course of atherosclerosis [5, 6].The presence ofH. pylori and diabetes mellitus (DM) is one of the main causes of gastrointestinal diseases [2, 7]. Additionally, the presence ofH. pylori in DM cases plays an important role in the development of gastrointestinal diseases [7]. In particular, the worsening of glycemic and metabolic control increases the incidence ofH. pylori infections and complaints of dyspepsia [2, 7]. A significant relationship between dyslipidemia andH. pylori has been reported. In prospective studies, it has been shown thatH. pylori eradication improves dyslipidemia and insulin resistance and decreases inflammation [6]. Although the relationship betweenH. pylori infection and DM and the complications secondary to diabetes is not clear, it is known that neuropathy and hyperglycemia play an important role inH. pylori colonization in the gastric epithelium [8]. Although the findings of various studies are inconsistent, it has been shown that there is a significant relationship between microvascular complications (nephropathy, neuropathy, and retinopathy) andH. pylori [6, 9, 10].Although there is no clear-cut consensus in the literature, it has been reported that HPeradication is noticeably lower in diabetic patients. There are a limited number of studies on the factors that play a role in HPeradication. We investigated the HP prevalence, HP eradication rates, and confounding factors affecting HP eradication in diabetic patients.
## 2. Materials and Methods
133 dyspeptic patients aged 18 to 65 and recruited from the internal medicine outpatient clinic were included into the study. All patients provided written informed consent to participate. 62 out of 133 patients had Type 2 DM. Exclusion criteria were (1) patients over 65 years; (2) patients having diabetes for more than 5 years; (3) patients with apparent proteinuria, creatinine values of >1.2 mg/dL, triglyceride levels of >400 mg/dL, and HbA1C of >8% with positive urine culture; (4) patients who received ulcer treatment within the last three months; (5) patients currently using proton pump inhibitor or H2 receptor blockers; (6) patients with a history ofH. pylori eradication treatment; and (7) patients with vascular and inflammatory diseases.Demographics (age, gender, and duration of disease) of the patients were documented. Height, weight, and waist circumference were measured and BMI was calculated as weight/height2 (kg/m2). Systolic and diastolic blood pressure measurements using standard sphygmomanometry were performed. Biochemical investigation including hemoglobin A1C (HbA1C), cholesterol, triglyceride, HDL, LDL, fasting blood glucose, leukocyte count, thrombocyte count, erythrocyte sedimentation rate, C reactive protein, and fibrinogen levels was performed in all patients. Approval of the local ethics committee was obtained for the study.Peripheral vascular disease was assessed based on the presence of intermittent claudication clinically and the absence of pulse in physical examinations. Retinopathy was determined with standard fundus examination. The presence of neuropathy was determined as per abnormal sensorimotor findings in examinations. Patients with a protein amount of 30 to 300 mg in 24-hour urine were considered cases with microalbuminuria, and those with ≥300 mg were considered cases with apparent proteinuria. In order to determine HP infection, the HPantigen stool test was used as it is a useful method for detection of active and repetitive HP infections [11]. The success rate of eradication was checked four weeks after the end of all treatments.In all patients with dyspeptic complaints, the presence ofH. pylori was investigated by theH. pylori antigen stool test, and the patients were compared by dividing them into two groups (Type 2 DM patients and nondiabetic patients). The relationship betweenH. pylori positivity and demographic clinical anthropometric and inflammatory parameters was investigated in all patients. The relationship betweenH. pylori positivity and retinopathy, nephropathy, neuropathy, and HbA1C was investigated in diabetic patients.Eradication treatment (clarithromycin, amoxicillin, and omeprazole) was given toH. pylori positive patients for two weeks. Additional omeprazole treatment without antibiotics was continued for 4 weeks. Two weeks after cessation of all treatments, eradication rates were determined by stool antigen test and a comparison was made.
### 2.1. Statistical Analysis
SPSS 17.0 package program was used for statistical analysis of data. The data were summarized in percentage, mean ± SD, and median values. The presence ofH. pylori and eradication ofH. pylori, as well as the relationship with demographic clinical anthropometric and inflammatory parameters, were analyzed using chi-square test, Fischer’s exact test, and independent T-sample test. The relationship between the presence ofH. pylori and eradication ofH. pylori in diabetic patients was analyzed using chi-square test and Fischer’s exact test. The results were assessed with hazard ratio and in a 95% confidence interval. A P
<
0.05 value was considered statistically meaningful in the analyses.
## 2.1. Statistical Analysis
SPSS 17.0 package program was used for statistical analysis of data. The data were summarized in percentage, mean ± SD, and median values. The presence ofH. pylori and eradication ofH. pylori, as well as the relationship with demographic clinical anthropometric and inflammatory parameters, were analyzed using chi-square test, Fischer’s exact test, and independent T-sample test. The relationship between the presence ofH. pylori and eradication ofH. pylori in diabetic patients was analyzed using chi-square test and Fischer’s exact test. The results were assessed with hazard ratio and in a 95% confidence interval. A P
<
0.05 value was considered statistically meaningful in the analyses.
## 3. Results
H. pylori positivity was detected in 64.5% of the diabetic patients and in 43.6% of the control group.H. pylori positivity was detected in 53.4% of all patients. The relationship betweenH. pylori positivity and inflammatory, demographic, clinical, and anthropometric parameters was shown in Tables 1 and 2.Table 1
The relationship betweenH. pylori positivity and inflammatory parameters.
Variables
Total
H. pylori (+) subjects
H. pylori (−) subjects
P value
CRP*
4.8 ± 3.4
5.5 ± 3.9
3.9 ± 2.3
<0.05
Leukocytes
7.0 ± 1.8
7.1 ± 1.6
6.9 ± .9
NS
Thrombocytes
250 ± 65
252 ± 69
248 ± 61
NS
Sedimentation*
9.4 ± 8.2
11.3 ± 8.9
7.3 ± 6.8
<0.05
Ferritin*
86.5 ± 91.7
122 ± 105
45.6 ± 47
<0.05
Fibrinogen*
321 ± 77
336 ± 82
303 ± 67
<0.05
*Significant variables.Table 2
The relationship betweenH. pylori positivity and demographic, clinical, and anthropometric parameters.
Variables
Total
H. pylori (+) subjects
H. pylori (−) subjects
P value
Gender
Female
70
34 (48.5%)
36 (51.5%)
NS
Male
63
37 (58.7%)
26 (41.3%)
NS
Age
47 ± 12
48.7 ± 12.1
46.9 ± 13.1
NS
Body mass index
NS
Normal
30
12 (40%)
18 (60%)
NS
Overweight
53
31 (58.4%)
22 (41.6%)
NS
Obese
50
28 (56%)
22 (44%)
NS
Waistline*
94 ± 11
95.7 ± 10
91.9 ± 11.8
<0.05
Hypertension
Yes*
49
34 (69.3%)
15 (30.7%)
<0.05
No
84
37 (44%)
47 (56%)
NS
Cholesterol
NS
≥200
67
38 (56.7%)
29 (43.3%)
NS
<200
66
33 (50%)
33 (50%)
NS
Triglyceride
≥150*
42
30 (71.4%)
12 (28.6%)
<0.05
<150
91
41 (45%)
50 (55%)
NS
Low density lipoprotein
≥100
87
51 (58.6%)
36 (41.4%)
NS
<100
46
20 (43.4%)
26 (56.6%)
NS
High density lipoprotein
Male ≥40, female ≥50
98
47 (%47.9)
51 (52.1%)
NS
Male <40, female <50*
35
24 (68.5%)
11 (31.5%)
<0.05
Glucose*
106 ± 35
117 ± 41
93 ± 21
<0.05
Creatinine
0.8 ± 0.2
0.84 ± 0.23
0.78 ± 0.19
NS
Patient groups
DM*
62
40 (64.5%)
20 (35.5%)
<0.05
Non-DM
71
31 (43.6%)
40 (56.7%)
NS
*Significant variables.When the relationship between the complications in diabetic patients andH. pylori positivity was evaluated,H. pylori positivity was significantly associated with the presence of nephropathy and neuropathy. Although retinopathy was more common in patients withH. pylori positivity, no statistical significance was found between groups. Additionally, a significant relationship between glycemic control and the presence ofH. pylori was detected. While 48.5% of the patients with HbA1C ≤7 wereH. pylori positive, 82.8% of the patients with HbA1C >7 were found to beH. pylori positive (Table 3).Table 3
The relationship between the complications in diabetic patients andH. pylori positivity.
Variables
TotalDM
H. pylori (+) subjects
H. pylori (−) subjects
P value
Nephropathy
Yes*
23
21 (91.3%)
2 (8.7%)
<0.05
No
39
19 (48.7%)
20 (51.3%)
Neuropathy
Yes*
29
24 (82.8%)
5 (18.2%)
<0.05
No
33
16 (48.4%)
17 (51.6%)
Retinopathy
Yes
20
14 (70%)
6 (30%)
NS
No
42
24 (57.1%)
18 (42.9%)
HbA1C
6-7*
33
16 (48.5%)
17 (51.5%)
<0.05
7-8
29
24 (82.8%)
5 (17.2%)
*Significant variables.The rate ofH. pylori eradication in diabetic and control groups was 62.5% and 93.5%, respectively. The factors affecting the rate ofH. pylori eradication were shown in Table 4.Table 4
The factors affecting the rate ofH. pylori eradication.
Variables
Total
Those eradicated
Those not eradicated
P value
Gender
Female
34
25 (73.5%)
9 (26.5%)
NS
Male
37
29 (78.3%)
8 (21.7%)
Age
48.7 ± 12.1
48.1 ± 13.3
50.8 ± 7.2
NS
Body mass index
Normal
12
12 (100%)
0 (0%)
Overweight
31
28 (90.3%)
3 (9.7%)
Obese*
28
14 (50%)
14 (50%)
<0.05
Waistline*
95.7 ± 10
94.3 ± 9.8
100 ± 9.4
<0.05
Hypertension
Yes*
34
22 (64.7%)
12 (35.3%)
<0.05
No
37
32 (86.4%)
5 (13.6%)
Cholesterol
≥200*
38
24 (63.1%)
14 (36.9%)
<0.05
<200
33
30 (90.9%)
3 (9.1%)
Triglyceride
≥150*
30
19 (63.3%)
11 (36.7%)
<0.05
<150
41
35 (85.3%)
6 (14.7%)
Low density lipoprotein
NS
≥100
51
37 (72.5%)
14 (27.5%)
<100
20
17 (85%)
3 (15%)
High density lipoprotein
NS
Male ≥40, female ≥50
47
38 (80.8%)
9 (19.2%)
Male <40, female <50
24
16 (66.6%)
8 (33.4%)
Glucose*
117 ± 42
110 ± 39
140 ± 41
<0.05
Patient groups
DM*
40
25 (62.5%)
15 (37.5%)
<0.05
Non-DM
31
29 (93.5%)
2 (6.5%)
*Significant variables.When the relationship between the complications in diabetic patients andH. pylori eradication was evaluated, a significant relationship between nephropathy and neuropathy with successful eradication ofH. pylori was detected. Although retinopathy is more common in patients withoutH. pylori eradication, no statistical significance was detected. Additionally, a significant relationship between glycemic control and the presence ofH. pylori eradication was detected. WhileH. pylori were successfully eradicated in 81.2% of the patients with HbA1C ≤7,H. pylori could be eradicated in 50% of the patients with HbA1C (Table 5).Table 5
The relationship between the complications in diabetic patients andH. pylori eradication.
Variables
TotalDM
Those eradicated
Those not eradicated
P value
Nephropathy
Yes*
22
10 (45.4%)
12 (54.6%)
<0.05
No
18
15 (83.8%)
3 (16.7%)
Neuropathy
Yes*
24
11 (45.8%)
13 (54.2%)
<0.05
No
16
14 (87.5%)
2 (22.5%)
Retinopathy
Yes
16
9 (56%)
7 (44%)
NS
No
24
16 (66.6%)
8 (33.4%)
HbA1C
6-7*
16
13 (81.2%)
3 (18.8%)
<0.05
7-8
24
12 (50%)
12 (50%)
*Significant variables.
## 4. Discussion
DM patients are usually prone to chronic infections. While the findings of studies on the prevalence ofH. pylori in DM patients are contradictory, in our study,H. pylori positivity was detected in 64.5% of the DM patients and in 43.6% of the control group (P
<
0.05). While Gentile et al. found that the prevalence ofH. pylori infection was 74.4% in DM patients and 50% in the control group (P
<
0.01), Gentile et al. found that the prevalence ofH. pylori was significantly higher in the DM group compared to the control group [12, 13]. However, some studies did not find any significant difference in the DM group and the control group with regard toH. pylori infections [9, 14]. It is well known that diabetic patients are prone to chronic infections because of cellular and humoral immune deficiency. As a result of delayed gastric emptying due to gastroparesis diabeticorum, bacterial overgrowth occurs and this poses a risk forH. pylori infections. Achlorhydria and reduced acid secretion are a negative factor forH. pylori infections. Additionally, leukocyte dysfunction and hyperglycemia are a predisposing factor for infections and facilitate secondaryH. pylori colonization to antibiotics taken. Based on all these factors, it can be said that the prevalence ofH. pylori is increased in diabetics [9].Studies report that HP infections cause microvascular damage and trigger premature development of atherosclerosis in patients [5, 6]. Although the underlying mechanism is not fully known, there are many findings which support this [5]. First of all, it has been shown that HP plays a role in the thickening of the intima media, atherosclerotic plaque destabilization, and atherosclerotic plaque development after vessel wall invasion [5, 15]. Due to vessel wall invasion of the bacteria, an increase in maturation and activation of monocytes and an increase in the proliferation of smooth muscle or endothelial cells occur, and, as a result, thrombosis and ischemia develop. It is thought that the endotoxins produced by the bacteria play a role in the maturation of monocytes. Activation of monocytes leads to the production of inflammatory cytokines, after which it triggers platelet aggregation and procoagulant activity [16]. Secondly, atherosclerotic plaques due to HP trigger high amounts of IL-6 and TNF-α. An increase in these cytokines causes endothelial dysfunction and insulin resistance. While IL-6 increases the production of hepatic gluconeogenesis and triglycerides, TNF-α modifies the lipid levels by inhibiting the lipoprotein lipase activity and activating hepatic lipogenesis [17]. Thirdly, the inflammation secondary to the plaque which forms due to HP triggers the peroxidation of membrane lipids, oxidation of LDL cholesterol, antioxidant loss, an increase in production of various superoxidases, and activation of macrophages, T-lymphocytes, and lipoprotein-a [18]. Additionally, chronic HP infection causes atrophic gastritis, and, as a result of this, it reduces absorption of folate and B12. B12 and folate are required for conversion of homocysteine to methionine. However, the homocysteine level increases due to the deficiency of B12 and folate in HP infections. Homocysteine plays a role in vascular endothelial damage and increases atherogenesis and thrombogenesis. It also increases platelet functions, coagulation, and LDL oxidation [19]. Similar to our study, many other studies have shown that, in the presence of HP infection, inflammatory indicators increase significantly [5, 20]. It has been reported that, as a result of an increase in inflammation due to HP infection and the triggering of arthrosclerosis, insulin resistance and metabolic syndrome increase, and the complications also increase in diabetic patients. A study on the Japanese population has shown that metabolic syndrome increases in HP infection [21]. Gunji et al. have shown in their study that HP infection significantly increases insulin resistance in asymptomatic patients [22]. Similar to the said studies, our study has also shown that metabolic syndrome significantly increases in patients with HP infection. Hamed et al. have shown in their study that, in HP-positive diabetic patients, the prevalence of macrovascular (cardiovascular and cerebrovascular diseases) and microvascular (nephropathy, neuropathy, and retinopathy) complications is significantly higher [5]. Furthermore, there are studies which report that microalbuminuria is significantly higher in HP-positive patients, regardless of the development of diabetes [6]. Demir et al. have reported that there is a significant relationship between HP-positivity and neuropathy, but there is no significant relationship between HP-positivity and retinopathy and neuropathy [9]. Similar to the said studies, our study has found a significant relationship between HP-positivity and neuropathy but has not found a significant relationship between HP-positivity and retinopathy.HP eradication is more difficult in diabetic patients. Sargýn et al. attained 50% HP eradication in DM patients and 85% HP eradication in non-DM patients [7]. Zojaji et al. attained successful eradication in 62% of DM patients, and a significant relationship was found between eradication and HbA1C [23]. In a study by Tseng, it was reported that comorbid conditions such as obesity, dyslipidemia, retinopathy, and neuropathy were significantly associated with HP eradication [10]. Our study has also shown that HP eradication is significantly lower in diabetic patients with retinopathy and neuropathy and with impaired glycemic and metabolic control. The fact that the HP eradication percentage is low in diabetic patients can be explained by the immunosuppressive condition in DM patients. Additionally, frequent bacterial and mycotic infections and the development of resistance due to drug use also play an important role [24].As a result, we have shown in our study that there is a significant relationship between HP infections and metabolic syndrome, insulin resistance, inflammations, and diabetic complications. We have also shown that similar parameters are effective in HP eradication. In the light of the studies, we think that patients with impaired metabolic and glycemic control should be treated in case of HP infection.
---
*Source: 290128-2015-01-22.xml* | 2015 |
# The Frequency of Epidermal Growth Factor Receptor Mutation of Nonsmall Cell Lung Cancer according to the Underlying Pulmonary Diseases
**Authors:** Kazuhiro Usui; Tomonori Ushijima; Yoshiaki Tanaka; Chiharu Tanai; Hiromichi Noda; Norifumi Abe; Hajime Horiuchi; Teruo Ishihara
**Journal:** Pulmonary Medicine
(2011)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2011/290132
---
## Abstract
Background. Although epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are effective in patients with nonsmall cell lung cancer with epidermal growth factor receptor (EGFR) mutation, EGFR-TKIs have a risk of inducing fatal interstitial lung disease (ILD). The selection of chemotherapy based on the EGFR mutation status is recommended, however, the frequency of EGFR mutation in patients with ILD and the efficacy and safety of EGFR-TKI in patients with ILD and EGFR mutation are unknown. Methods. We retrospectively reviewed the association of the EGFR mutation status of nonsmall cell lung cancer and pulmonary diseases. Based on high-resolution computed tomography (HRCT) performed at diagnosis of lung cancer, patients were categorized into three groups: normal, emphysema, and fibrosis.
Results. Of 198 patients with nonsmall cell lung cancer, we identified 52 (26.3%) patients with an EGFR mutation. EGFR mutations were identified in 43 (35.2%) of 122 patients with normal lungs, 8 (13.6%) of 59 with emphysema, and 1 (5.9%) of 17 with pulmonary fibrosis. Of the 52 patients with EGFR mutation, 43 patients received gefitinib. One patient with an EGFR mutation and fibrosis developed fatal ILD. There was not a significant difference in median overall survival from gefitinib treatment between never-smokers and smokers (797 days versus not reached; P=0.96).
Conclusions. Patients with sensitive EGFR mutation and normal lungs may benefit from an EGFR-TKI treatment even if they have smoking history.
---
## Body
## 1. Introduction
Gefitinib is a reversible epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) used for the treatment of nonsmall cell lung cancer patients [1]. Although demographic and clinical factors such as East-Asian race, female gender, nonsmoking status, and adenocarcinoma were shown to be predictive of the efficacy of gefitinib, two pivotal studies showed that the presence of somatic mutations in the kinase domain of epidermal growth factor receptor (EGFR) strongly correlates with increased responsiveness to EGFR-TKIs in patients with nonsmall cell lung cancer [2, 3]. It was later found that the subgroups of patients with nonsmall cell lung cancer who had sensitivity to gefitinib had a high incidence of EGFR mutations [4, 5]. Selecting patients on the basis of EGFR mutations, rather than clinical factors, would likely result in a population with a greater sensitivity to gefitinib. First-line gefitinib for patients with advanced nonsmall cell lung cancer who are selected on the basis of EGFR mutations improves progression-free survival, with acceptable toxicity, compared with standard chemotherapy, although it failed to prolong overall survival [6, 7].However, EGFR-TKI increases the risk of developing life-threatening interstitial lung diseases (ILDs). The estimated incidence of ILD is low in many countries (e.g., 0.3% in the United States) [8] but is relatively high (4 to 6%) in Japan [9, 10]. An older age, poor World Health Organization performance status, reduced normal lung area on computed tomography scans, preexisting chronic ILD, and concurrent cardiac diseases are known as risk factors for ILD in gefitinib treatment [10]. Although an assessment of pulmonary comorbidities, especially ILDs, is important to decrease the incidence of ILD induced by chemotherapy, the frequency of EGFR mutation in patients with pulmonary fibrosis and the clinical feature of these patients are not clear.We reviewed 198 patients who were examined for EGFR mutation status and assessed the association of EGFR mutations with the underlying pulmonary diseases on chest high-resolution computed tomography (HRCT).
## 2. Methods
The medical records of a series of consecutive patients with histologically- or cytologically-proven lung cancer, who were tested for EGFR mutation status in the Division of Diagnostic Pathology, NTT Medical Center Tokyo between April 2008 and November 2010, were retrospectively reviewed. The status of EGFR mutation was examined in a clinical practice, not investigational setting, to decide the indication of EGFR-TKI treatment. Although most patients with severe pulmonary fibrosis or squamous cell carcinoma were excluded from the EGFR mutation test in this period, gender, smoking status, and the existence of emphysema were not considered as the exclusion criteria of the test. Patients with emphysema and fibrosis on chest HRCT at the diagnosis of lung cancer were prospectively identified, and the data before lung cancer treatment was recorded to assess their risk of ILD. Only patients who had a chest HRCT scan, which was performed at diagnosis of lung cancer and was available for review, were included in the study. The study protocol was reviewed and approved by the Ethics Committee of NTT Medical Center Tokyo.Patients were categorized into three groups; those with normal lungs (except for the tumor), emphysematous lungs, or fibrotic lungs, based on chest CT findings as described previously [11, 12]. Patients who met the following criteria were categorized as having emphysema: the presence of emphysema on CT, defined as well-demarcated areas of decreased attenuation in comparison with contiguous normal lung, and marginated by a very thin (<1 mm) wall or no wall, and/or multiple bullae (>1 cm) with upper zone predominance. Patients who met the following criteria were categorized as having fibrosis: the presence of diffuse parenchymal lung disease with significant pulmonary fibrosis on CT, defined as reticular opacities with peripheral and basal predominance, honeycombing, architectural distortion, and/or traction bronchiectasis or bronchiolectasis; focal ground-glass opacities and/or areas of alveolar condensation may be associated, but should not be prominent. Patients who met neither criterion emphysema nor fibrosis were categorized as normal. The electronic medical records were reviewed to obtain clinical and demographic data, including gender, age, smoking history, histology results, clinical stage of lung cancer, treatment, treatment-related toxicities, and survival.
### 2.1. EGFR Mutation Analysis
The presence of EGFR mutations was determined by the peptide nucleic acid-locked nucleic acid PCR clamp method as described previously [13]. The investigated EGFR-TKI sensitive mutations included G719C, G719S, G719A, L858R, L861Q, and exon 19 deletions, as well as a gefitinib-resistant mutation, T790M.
### 2.2. Statistical Analysis
Differences among the categorized groups were compared using either the two-sided chi-square test or Fisher’s exact test. The survival was estimated by the Kaplan-Meier method, and differences in survival between the subgroups were analyzed by the log rank test. Data were analyzed using the StatView version 5.0J software package (Statistical Analysis Systems, Cary, NC, USA).
## 2.1. EGFR Mutation Analysis
The presence of EGFR mutations was determined by the peptide nucleic acid-locked nucleic acid PCR clamp method as described previously [13]. The investigated EGFR-TKI sensitive mutations included G719C, G719S, G719A, L858R, L861Q, and exon 19 deletions, as well as a gefitinib-resistant mutation, T790M.
## 2.2. Statistical Analysis
Differences among the categorized groups were compared using either the two-sided chi-square test or Fisher’s exact test. The survival was estimated by the Kaplan-Meier method, and differences in survival between the subgroups were analyzed by the log rank test. Data were analyzed using the StatView version 5.0J software package (Statistical Analysis Systems, Cary, NC, USA).
## 3. Results
### 3.1. Subtypes of EGFR Mutations
We examined the EGFR mutation status in 202 patients between April 2008 and November 2010. We excluded 4 patients from this study for the following reasons: one had small cell lung cancer, two had gastric cancer, and one had parotid cancer. Of the 198 patients with nonsmall cell lung cancer, 52 patients (26.3%) had EGFR-TKI-sensitive EGFR mutations, and one patient had an EGFR-TKI-resistant mutation (T790M) with an EGFR-TKI-sensitive mutation (Exon 19 deletion). The patient population in this analysis (Table1) was a little young, including more female, less never-smoker, and less squamous cell carcinoma of the lung in comparison with the lung cancer cohort that we previously published [12].Table 1
Patient characteristics NSCLC: nonsmall cell lung cancer: LCNEC; large cell neuroendocrine carcinoma.
Total number of patients198Age (median, range)68, 28–92GenderFemale86Male112Smoking-statusNever74Ex/Current124HistologyAdenocarcinoma169Squamous cell carcinoma9Other NSCLC15LCNEC4Clinical stage of NSCLCIA29IB14IIA2IIB6IIIA12IIIB30IV105Chest CTNormal122Emphysema59Fibrosis17EGFR mutationWild type147Ex18 G718S1Ex19 del34Ex21 L858R15EX19 del + Ex21 L858R1Ex 19del + T790M1
### 3.2. The Variables Associated with the EGFR Mutation Status
We investigated the association of several variables with the EGFR mutations (Table2). A two-sided chi-square test showed that gender (female), smoking status (never smoker), histology (adenocarcinoma), and chest CT findings (normal) were significantly associated with the presence of an EGFR mutation. Of 122 patients with normal lungs, 69 patients had no history of smoking and 53 patients had a history of smoking. The frequency of EGFR mutations (n, %) in patients with normal lungs did not differ between smokers (17, 32.1%) and never-smokers (26, 37.7%) (P=0.5698).Table 2
Patient characteristics and EGFR mutation status.
NumberEGFR mutation (n, %)P-valueGenderMale11217, 15.2%P<0.0001Female8635, 40.7%Age<658023, 28.8%P=0.515665≤11829, 24.6%HistologyAdenocarcinoma16950, 29.6%P=0.0107Nonadenocarcinoma292, 6.9%Smoking statusNever7429, 39.2%P=0.0139Ex/Current12423, 18.5%Clinical stage of NSCLCI-IIIA6321, 33.3%P=0.1649IIIB-IV13531, 22.9%Chest CTNormal12243, 35.2%P=0.0011Emphysema598, 13.6%Fibrosis171, 5.8%
### 3.3. Prognosis of Patients with EGFR Mutations Treated with Gefitinib
All patients with an EGFR mutation were treated in the Division of Respirology and Chest Surgery, NTT Medical Center Tokyo. Of the 52 patients with EGFR mutation, 43 patients received gefitinib. The clinical characteristics of the patients with an EGFR mutation treated with gefitinib are shown in Table3. The median survival after gefitinib treatment was 797 days. We identified ILD in two patients during gefitinib treatment; one had no ILD before gefitinib treatment and one had pulmonary fibrosis. The patient with pulmonary fibrosis developed acute exacerbation of preexisting ILD on day 7 of gefitinib treatment and died on day 14 because of ILD. The survival curves of the 42 patients, excluding the patient with pulmonary fibrosis, according to smoking status and chest CT results, are shown in Figures 1(a) and 1(b), respectively. No differences in survival were observed between smokers (n=18, MST not reached) and never-smokers (n=24, MST 797 days) or between patients with normal lung (n=36, MST 874 days) and those with emphysematous lungs (n=6, MST 749 days) on chest CT.Table 3
Characteristics of patients with an EGFR mutation treated with gefitinib.
Total number43Age (median, range)67, 28–92GenderMale13Female30Smoking-statusNever24Ex/Current19Pack-years of smokers (median, range)33, 2.5–225HistologyAdenocarcinoma42Squamous cell carcinoma1Clinical stage of NSCLCIB2IIIA1IIIB7IV22Recurrence11History of chemotherapy before gefitinib treatmentNo28Yes15EGFR mutationEx18 G719C1Ex19 del30Ex21 L858R10Ex19 del + Ex21L858R1Ex19 del + Ex20 T790M1Chest CTNormal36Emphysema6Fibrosis1(a) Overall survival of patients with an EGFR mutation treated with gefitinib, according to smoking status (never smokers: solid line; smokers: dotted line). +: censored patient. (b) Overall survival of patients with an EGFR mutation treated with gefitinib, according to underlying pulmonary disease (normal: solid line; emphysema: dotted line). +: censored patient.
(a)(b)
## 3.1. Subtypes of EGFR Mutations
We examined the EGFR mutation status in 202 patients between April 2008 and November 2010. We excluded 4 patients from this study for the following reasons: one had small cell lung cancer, two had gastric cancer, and one had parotid cancer. Of the 198 patients with nonsmall cell lung cancer, 52 patients (26.3%) had EGFR-TKI-sensitive EGFR mutations, and one patient had an EGFR-TKI-resistant mutation (T790M) with an EGFR-TKI-sensitive mutation (Exon 19 deletion). The patient population in this analysis (Table1) was a little young, including more female, less never-smoker, and less squamous cell carcinoma of the lung in comparison with the lung cancer cohort that we previously published [12].Table 1
Patient characteristics NSCLC: nonsmall cell lung cancer: LCNEC; large cell neuroendocrine carcinoma.
Total number of patients198Age (median, range)68, 28–92GenderFemale86Male112Smoking-statusNever74Ex/Current124HistologyAdenocarcinoma169Squamous cell carcinoma9Other NSCLC15LCNEC4Clinical stage of NSCLCIA29IB14IIA2IIB6IIIA12IIIB30IV105Chest CTNormal122Emphysema59Fibrosis17EGFR mutationWild type147Ex18 G718S1Ex19 del34Ex21 L858R15EX19 del + Ex21 L858R1Ex 19del + T790M1
## 3.2. The Variables Associated with the EGFR Mutation Status
We investigated the association of several variables with the EGFR mutations (Table2). A two-sided chi-square test showed that gender (female), smoking status (never smoker), histology (adenocarcinoma), and chest CT findings (normal) were significantly associated with the presence of an EGFR mutation. Of 122 patients with normal lungs, 69 patients had no history of smoking and 53 patients had a history of smoking. The frequency of EGFR mutations (n, %) in patients with normal lungs did not differ between smokers (17, 32.1%) and never-smokers (26, 37.7%) (P=0.5698).Table 2
Patient characteristics and EGFR mutation status.
NumberEGFR mutation (n, %)P-valueGenderMale11217, 15.2%P<0.0001Female8635, 40.7%Age<658023, 28.8%P=0.515665≤11829, 24.6%HistologyAdenocarcinoma16950, 29.6%P=0.0107Nonadenocarcinoma292, 6.9%Smoking statusNever7429, 39.2%P=0.0139Ex/Current12423, 18.5%Clinical stage of NSCLCI-IIIA6321, 33.3%P=0.1649IIIB-IV13531, 22.9%Chest CTNormal12243, 35.2%P=0.0011Emphysema598, 13.6%Fibrosis171, 5.8%
## 3.3. Prognosis of Patients with EGFR Mutations Treated with Gefitinib
All patients with an EGFR mutation were treated in the Division of Respirology and Chest Surgery, NTT Medical Center Tokyo. Of the 52 patients with EGFR mutation, 43 patients received gefitinib. The clinical characteristics of the patients with an EGFR mutation treated with gefitinib are shown in Table3. The median survival after gefitinib treatment was 797 days. We identified ILD in two patients during gefitinib treatment; one had no ILD before gefitinib treatment and one had pulmonary fibrosis. The patient with pulmonary fibrosis developed acute exacerbation of preexisting ILD on day 7 of gefitinib treatment and died on day 14 because of ILD. The survival curves of the 42 patients, excluding the patient with pulmonary fibrosis, according to smoking status and chest CT results, are shown in Figures 1(a) and 1(b), respectively. No differences in survival were observed between smokers (n=18, MST not reached) and never-smokers (n=24, MST 797 days) or between patients with normal lung (n=36, MST 874 days) and those with emphysematous lungs (n=6, MST 749 days) on chest CT.Table 3
Characteristics of patients with an EGFR mutation treated with gefitinib.
Total number43Age (median, range)67, 28–92GenderMale13Female30Smoking-statusNever24Ex/Current19Pack-years of smokers (median, range)33, 2.5–225HistologyAdenocarcinoma42Squamous cell carcinoma1Clinical stage of NSCLCIB2IIIA1IIIB7IV22Recurrence11History of chemotherapy before gefitinib treatmentNo28Yes15EGFR mutationEx18 G719C1Ex19 del30Ex21 L858R10Ex19 del + Ex21L858R1Ex19 del + Ex20 T790M1Chest CTNormal36Emphysema6Fibrosis1(a) Overall survival of patients with an EGFR mutation treated with gefitinib, according to smoking status (never smokers: solid line; smokers: dotted line). +: censored patient. (b) Overall survival of patients with an EGFR mutation treated with gefitinib, according to underlying pulmonary disease (normal: solid line; emphysema: dotted line). +: censored patient.
(a)(b)
## 4. Discussion
We herein showed the frequency of EGFR mutation in nonsmall cell lung cancer to be high in patients with the following factors: female gender, no history of smoking, adenocarcinoma, and normal lungs on chest CT. A survival analysis of the patients with EGFR mutations, excluding one patient with pulmonary fibrosis, showed no differences between smokers and never-smokers or between patients with emphysema and those with normal lungs on chest CT.There is considerable variability in the susceptibility of smokers to developing smoking-related pulmonary diseases [14–16]. The incidence of lung cancer is increased in patients with emphysema and fibrosis, and this effect is independent of the effect of cigarette smoking [17, 18]. We consider that smokers with emphysema or fibrosis are more susceptible to smoking-related inflammation compared to those with normal lungs. Although the frequency of EGFR mutation was low in patients with emphysema and fibrosis, the frequency in those with normal lungs was not different between smokers and never-smokers. Our data suggested that smokers with normal lungs were not susceptible to smoking-related inflammation, and that nonsmall cell lung cancer in smokers with normal lungs showed the same biological features to that in never-smokers. Further investigations are necessary to elucidate whether smoking-related pulmonary diseases and lung cancer might result from overlapping or associated genetic variants implicated in smoking-related inflammation.Although a history of smoking and the coexistence of emphysema were negatively associated with the frequency of EGFR mutations, these clinical factors did not affect the prognosis of the patients with EGFR mutations treated with gefitinib. Toyooka et al. showed that epidermal growth factor receptor mutation, but not sex or smoking, is independently associated with a favorable prognosis of gefitinib-treated patients with lung adenocarcinoma [5]. EGFR-TKI treatment should be considered in patients with an EGFR mutation, even if they have a history of smoking or emphysema without fibrosis.The presence of EGFR mutations in patients with pulmonary fibrosis was rare in this study. Only one (5.9%) of 17 patients with pulmonary fibrosis had an EGFR mutation. Preexisting chronic ILD is known as a risk factor for ILD in gefitinib treatment [10]. In this study, one patient with pulmonary fibrosis and an EGFR mutation treated with gefitinib developed fatal ILD.The present study had several limitations, including the fact that it was observational and uncontrolled in design and was performed at a single institution, with retrospective collection of data. The results may have been subject to some selection and treatment bias. The indications for therapy and the selection of treatment were not uniform for all patients, thereby limiting the evaluation of the effects of treatment. The data presented herein should not be interpreted as providing an appropriate evaluation of the efficacy of treatment, which will require randomized prospective studies. A multivariate analysis could not be performed due to the small sample size, and it was therefore not possible to evaluate the potential confounding effects of various other variables related to survival. However, the existence of emphysema and fibrosis on chest CT were prospectively identified at the diagnosis of lung cancer. The EGFR mutation status was identified before the EGFR-TKI treatment. Data on the demographic characteristics and survival of patients were unlikely to be affected by the study design.In summary, the frequency of EGFR mutations in patients with normal lungs on chest CT was not different between smokers and never-smokers. Of patients with sensitive EGFR mutations and normal lungs on chest CT, smokers had a comparable prognosis with never-smokers. Selecting patients on the basis of chest CT, rather than the smoking status, would likely result in a population with a greater sensitivity to gefitinib.
---
*Source: 290132-2011-11-28.xml* | 290132-2011-11-28_290132-2011-11-28.md | 20,893 | The Frequency of Epidermal Growth Factor Receptor Mutation of Nonsmall Cell Lung Cancer according to the Underlying Pulmonary Diseases | Kazuhiro Usui; Tomonori Ushijima; Yoshiaki Tanaka; Chiharu Tanai; Hiromichi Noda; Norifumi Abe; Hajime Horiuchi; Teruo Ishihara | Pulmonary Medicine
(2011) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2011/290132 | 290132-2011-11-28.xml | ---
## Abstract
Background. Although epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are effective in patients with nonsmall cell lung cancer with epidermal growth factor receptor (EGFR) mutation, EGFR-TKIs have a risk of inducing fatal interstitial lung disease (ILD). The selection of chemotherapy based on the EGFR mutation status is recommended, however, the frequency of EGFR mutation in patients with ILD and the efficacy and safety of EGFR-TKI in patients with ILD and EGFR mutation are unknown. Methods. We retrospectively reviewed the association of the EGFR mutation status of nonsmall cell lung cancer and pulmonary diseases. Based on high-resolution computed tomography (HRCT) performed at diagnosis of lung cancer, patients were categorized into three groups: normal, emphysema, and fibrosis.
Results. Of 198 patients with nonsmall cell lung cancer, we identified 52 (26.3%) patients with an EGFR mutation. EGFR mutations were identified in 43 (35.2%) of 122 patients with normal lungs, 8 (13.6%) of 59 with emphysema, and 1 (5.9%) of 17 with pulmonary fibrosis. Of the 52 patients with EGFR mutation, 43 patients received gefitinib. One patient with an EGFR mutation and fibrosis developed fatal ILD. There was not a significant difference in median overall survival from gefitinib treatment between never-smokers and smokers (797 days versus not reached; P=0.96).
Conclusions. Patients with sensitive EGFR mutation and normal lungs may benefit from an EGFR-TKI treatment even if they have smoking history.
---
## Body
## 1. Introduction
Gefitinib is a reversible epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) used for the treatment of nonsmall cell lung cancer patients [1]. Although demographic and clinical factors such as East-Asian race, female gender, nonsmoking status, and adenocarcinoma were shown to be predictive of the efficacy of gefitinib, two pivotal studies showed that the presence of somatic mutations in the kinase domain of epidermal growth factor receptor (EGFR) strongly correlates with increased responsiveness to EGFR-TKIs in patients with nonsmall cell lung cancer [2, 3]. It was later found that the subgroups of patients with nonsmall cell lung cancer who had sensitivity to gefitinib had a high incidence of EGFR mutations [4, 5]. Selecting patients on the basis of EGFR mutations, rather than clinical factors, would likely result in a population with a greater sensitivity to gefitinib. First-line gefitinib for patients with advanced nonsmall cell lung cancer who are selected on the basis of EGFR mutations improves progression-free survival, with acceptable toxicity, compared with standard chemotherapy, although it failed to prolong overall survival [6, 7].However, EGFR-TKI increases the risk of developing life-threatening interstitial lung diseases (ILDs). The estimated incidence of ILD is low in many countries (e.g., 0.3% in the United States) [8] but is relatively high (4 to 6%) in Japan [9, 10]. An older age, poor World Health Organization performance status, reduced normal lung area on computed tomography scans, preexisting chronic ILD, and concurrent cardiac diseases are known as risk factors for ILD in gefitinib treatment [10]. Although an assessment of pulmonary comorbidities, especially ILDs, is important to decrease the incidence of ILD induced by chemotherapy, the frequency of EGFR mutation in patients with pulmonary fibrosis and the clinical feature of these patients are not clear.We reviewed 198 patients who were examined for EGFR mutation status and assessed the association of EGFR mutations with the underlying pulmonary diseases on chest high-resolution computed tomography (HRCT).
## 2. Methods
The medical records of a series of consecutive patients with histologically- or cytologically-proven lung cancer, who were tested for EGFR mutation status in the Division of Diagnostic Pathology, NTT Medical Center Tokyo between April 2008 and November 2010, were retrospectively reviewed. The status of EGFR mutation was examined in a clinical practice, not investigational setting, to decide the indication of EGFR-TKI treatment. Although most patients with severe pulmonary fibrosis or squamous cell carcinoma were excluded from the EGFR mutation test in this period, gender, smoking status, and the existence of emphysema were not considered as the exclusion criteria of the test. Patients with emphysema and fibrosis on chest HRCT at the diagnosis of lung cancer were prospectively identified, and the data before lung cancer treatment was recorded to assess their risk of ILD. Only patients who had a chest HRCT scan, which was performed at diagnosis of lung cancer and was available for review, were included in the study. The study protocol was reviewed and approved by the Ethics Committee of NTT Medical Center Tokyo.Patients were categorized into three groups; those with normal lungs (except for the tumor), emphysematous lungs, or fibrotic lungs, based on chest CT findings as described previously [11, 12]. Patients who met the following criteria were categorized as having emphysema: the presence of emphysema on CT, defined as well-demarcated areas of decreased attenuation in comparison with contiguous normal lung, and marginated by a very thin (<1 mm) wall or no wall, and/or multiple bullae (>1 cm) with upper zone predominance. Patients who met the following criteria were categorized as having fibrosis: the presence of diffuse parenchymal lung disease with significant pulmonary fibrosis on CT, defined as reticular opacities with peripheral and basal predominance, honeycombing, architectural distortion, and/or traction bronchiectasis or bronchiolectasis; focal ground-glass opacities and/or areas of alveolar condensation may be associated, but should not be prominent. Patients who met neither criterion emphysema nor fibrosis were categorized as normal. The electronic medical records were reviewed to obtain clinical and demographic data, including gender, age, smoking history, histology results, clinical stage of lung cancer, treatment, treatment-related toxicities, and survival.
### 2.1. EGFR Mutation Analysis
The presence of EGFR mutations was determined by the peptide nucleic acid-locked nucleic acid PCR clamp method as described previously [13]. The investigated EGFR-TKI sensitive mutations included G719C, G719S, G719A, L858R, L861Q, and exon 19 deletions, as well as a gefitinib-resistant mutation, T790M.
### 2.2. Statistical Analysis
Differences among the categorized groups were compared using either the two-sided chi-square test or Fisher’s exact test. The survival was estimated by the Kaplan-Meier method, and differences in survival between the subgroups were analyzed by the log rank test. Data were analyzed using the StatView version 5.0J software package (Statistical Analysis Systems, Cary, NC, USA).
## 2.1. EGFR Mutation Analysis
The presence of EGFR mutations was determined by the peptide nucleic acid-locked nucleic acid PCR clamp method as described previously [13]. The investigated EGFR-TKI sensitive mutations included G719C, G719S, G719A, L858R, L861Q, and exon 19 deletions, as well as a gefitinib-resistant mutation, T790M.
## 2.2. Statistical Analysis
Differences among the categorized groups were compared using either the two-sided chi-square test or Fisher’s exact test. The survival was estimated by the Kaplan-Meier method, and differences in survival between the subgroups were analyzed by the log rank test. Data were analyzed using the StatView version 5.0J software package (Statistical Analysis Systems, Cary, NC, USA).
## 3. Results
### 3.1. Subtypes of EGFR Mutations
We examined the EGFR mutation status in 202 patients between April 2008 and November 2010. We excluded 4 patients from this study for the following reasons: one had small cell lung cancer, two had gastric cancer, and one had parotid cancer. Of the 198 patients with nonsmall cell lung cancer, 52 patients (26.3%) had EGFR-TKI-sensitive EGFR mutations, and one patient had an EGFR-TKI-resistant mutation (T790M) with an EGFR-TKI-sensitive mutation (Exon 19 deletion). The patient population in this analysis (Table1) was a little young, including more female, less never-smoker, and less squamous cell carcinoma of the lung in comparison with the lung cancer cohort that we previously published [12].Table 1
Patient characteristics NSCLC: nonsmall cell lung cancer: LCNEC; large cell neuroendocrine carcinoma.
Total number of patients198Age (median, range)68, 28–92GenderFemale86Male112Smoking-statusNever74Ex/Current124HistologyAdenocarcinoma169Squamous cell carcinoma9Other NSCLC15LCNEC4Clinical stage of NSCLCIA29IB14IIA2IIB6IIIA12IIIB30IV105Chest CTNormal122Emphysema59Fibrosis17EGFR mutationWild type147Ex18 G718S1Ex19 del34Ex21 L858R15EX19 del + Ex21 L858R1Ex 19del + T790M1
### 3.2. The Variables Associated with the EGFR Mutation Status
We investigated the association of several variables with the EGFR mutations (Table2). A two-sided chi-square test showed that gender (female), smoking status (never smoker), histology (adenocarcinoma), and chest CT findings (normal) were significantly associated with the presence of an EGFR mutation. Of 122 patients with normal lungs, 69 patients had no history of smoking and 53 patients had a history of smoking. The frequency of EGFR mutations (n, %) in patients with normal lungs did not differ between smokers (17, 32.1%) and never-smokers (26, 37.7%) (P=0.5698).Table 2
Patient characteristics and EGFR mutation status.
NumberEGFR mutation (n, %)P-valueGenderMale11217, 15.2%P<0.0001Female8635, 40.7%Age<658023, 28.8%P=0.515665≤11829, 24.6%HistologyAdenocarcinoma16950, 29.6%P=0.0107Nonadenocarcinoma292, 6.9%Smoking statusNever7429, 39.2%P=0.0139Ex/Current12423, 18.5%Clinical stage of NSCLCI-IIIA6321, 33.3%P=0.1649IIIB-IV13531, 22.9%Chest CTNormal12243, 35.2%P=0.0011Emphysema598, 13.6%Fibrosis171, 5.8%
### 3.3. Prognosis of Patients with EGFR Mutations Treated with Gefitinib
All patients with an EGFR mutation were treated in the Division of Respirology and Chest Surgery, NTT Medical Center Tokyo. Of the 52 patients with EGFR mutation, 43 patients received gefitinib. The clinical characteristics of the patients with an EGFR mutation treated with gefitinib are shown in Table3. The median survival after gefitinib treatment was 797 days. We identified ILD in two patients during gefitinib treatment; one had no ILD before gefitinib treatment and one had pulmonary fibrosis. The patient with pulmonary fibrosis developed acute exacerbation of preexisting ILD on day 7 of gefitinib treatment and died on day 14 because of ILD. The survival curves of the 42 patients, excluding the patient with pulmonary fibrosis, according to smoking status and chest CT results, are shown in Figures 1(a) and 1(b), respectively. No differences in survival were observed between smokers (n=18, MST not reached) and never-smokers (n=24, MST 797 days) or between patients with normal lung (n=36, MST 874 days) and those with emphysematous lungs (n=6, MST 749 days) on chest CT.Table 3
Characteristics of patients with an EGFR mutation treated with gefitinib.
Total number43Age (median, range)67, 28–92GenderMale13Female30Smoking-statusNever24Ex/Current19Pack-years of smokers (median, range)33, 2.5–225HistologyAdenocarcinoma42Squamous cell carcinoma1Clinical stage of NSCLCIB2IIIA1IIIB7IV22Recurrence11History of chemotherapy before gefitinib treatmentNo28Yes15EGFR mutationEx18 G719C1Ex19 del30Ex21 L858R10Ex19 del + Ex21L858R1Ex19 del + Ex20 T790M1Chest CTNormal36Emphysema6Fibrosis1(a) Overall survival of patients with an EGFR mutation treated with gefitinib, according to smoking status (never smokers: solid line; smokers: dotted line). +: censored patient. (b) Overall survival of patients with an EGFR mutation treated with gefitinib, according to underlying pulmonary disease (normal: solid line; emphysema: dotted line). +: censored patient.
(a)(b)
## 3.1. Subtypes of EGFR Mutations
We examined the EGFR mutation status in 202 patients between April 2008 and November 2010. We excluded 4 patients from this study for the following reasons: one had small cell lung cancer, two had gastric cancer, and one had parotid cancer. Of the 198 patients with nonsmall cell lung cancer, 52 patients (26.3%) had EGFR-TKI-sensitive EGFR mutations, and one patient had an EGFR-TKI-resistant mutation (T790M) with an EGFR-TKI-sensitive mutation (Exon 19 deletion). The patient population in this analysis (Table1) was a little young, including more female, less never-smoker, and less squamous cell carcinoma of the lung in comparison with the lung cancer cohort that we previously published [12].Table 1
Patient characteristics NSCLC: nonsmall cell lung cancer: LCNEC; large cell neuroendocrine carcinoma.
Total number of patients198Age (median, range)68, 28–92GenderFemale86Male112Smoking-statusNever74Ex/Current124HistologyAdenocarcinoma169Squamous cell carcinoma9Other NSCLC15LCNEC4Clinical stage of NSCLCIA29IB14IIA2IIB6IIIA12IIIB30IV105Chest CTNormal122Emphysema59Fibrosis17EGFR mutationWild type147Ex18 G718S1Ex19 del34Ex21 L858R15EX19 del + Ex21 L858R1Ex 19del + T790M1
## 3.2. The Variables Associated with the EGFR Mutation Status
We investigated the association of several variables with the EGFR mutations (Table2). A two-sided chi-square test showed that gender (female), smoking status (never smoker), histology (adenocarcinoma), and chest CT findings (normal) were significantly associated with the presence of an EGFR mutation. Of 122 patients with normal lungs, 69 patients had no history of smoking and 53 patients had a history of smoking. The frequency of EGFR mutations (n, %) in patients with normal lungs did not differ between smokers (17, 32.1%) and never-smokers (26, 37.7%) (P=0.5698).Table 2
Patient characteristics and EGFR mutation status.
NumberEGFR mutation (n, %)P-valueGenderMale11217, 15.2%P<0.0001Female8635, 40.7%Age<658023, 28.8%P=0.515665≤11829, 24.6%HistologyAdenocarcinoma16950, 29.6%P=0.0107Nonadenocarcinoma292, 6.9%Smoking statusNever7429, 39.2%P=0.0139Ex/Current12423, 18.5%Clinical stage of NSCLCI-IIIA6321, 33.3%P=0.1649IIIB-IV13531, 22.9%Chest CTNormal12243, 35.2%P=0.0011Emphysema598, 13.6%Fibrosis171, 5.8%
## 3.3. Prognosis of Patients with EGFR Mutations Treated with Gefitinib
All patients with an EGFR mutation were treated in the Division of Respirology and Chest Surgery, NTT Medical Center Tokyo. Of the 52 patients with EGFR mutation, 43 patients received gefitinib. The clinical characteristics of the patients with an EGFR mutation treated with gefitinib are shown in Table3. The median survival after gefitinib treatment was 797 days. We identified ILD in two patients during gefitinib treatment; one had no ILD before gefitinib treatment and one had pulmonary fibrosis. The patient with pulmonary fibrosis developed acute exacerbation of preexisting ILD on day 7 of gefitinib treatment and died on day 14 because of ILD. The survival curves of the 42 patients, excluding the patient with pulmonary fibrosis, according to smoking status and chest CT results, are shown in Figures 1(a) and 1(b), respectively. No differences in survival were observed between smokers (n=18, MST not reached) and never-smokers (n=24, MST 797 days) or between patients with normal lung (n=36, MST 874 days) and those with emphysematous lungs (n=6, MST 749 days) on chest CT.Table 3
Characteristics of patients with an EGFR mutation treated with gefitinib.
Total number43Age (median, range)67, 28–92GenderMale13Female30Smoking-statusNever24Ex/Current19Pack-years of smokers (median, range)33, 2.5–225HistologyAdenocarcinoma42Squamous cell carcinoma1Clinical stage of NSCLCIB2IIIA1IIIB7IV22Recurrence11History of chemotherapy before gefitinib treatmentNo28Yes15EGFR mutationEx18 G719C1Ex19 del30Ex21 L858R10Ex19 del + Ex21L858R1Ex19 del + Ex20 T790M1Chest CTNormal36Emphysema6Fibrosis1(a) Overall survival of patients with an EGFR mutation treated with gefitinib, according to smoking status (never smokers: solid line; smokers: dotted line). +: censored patient. (b) Overall survival of patients with an EGFR mutation treated with gefitinib, according to underlying pulmonary disease (normal: solid line; emphysema: dotted line). +: censored patient.
(a)(b)
## 4. Discussion
We herein showed the frequency of EGFR mutation in nonsmall cell lung cancer to be high in patients with the following factors: female gender, no history of smoking, adenocarcinoma, and normal lungs on chest CT. A survival analysis of the patients with EGFR mutations, excluding one patient with pulmonary fibrosis, showed no differences between smokers and never-smokers or between patients with emphysema and those with normal lungs on chest CT.There is considerable variability in the susceptibility of smokers to developing smoking-related pulmonary diseases [14–16]. The incidence of lung cancer is increased in patients with emphysema and fibrosis, and this effect is independent of the effect of cigarette smoking [17, 18]. We consider that smokers with emphysema or fibrosis are more susceptible to smoking-related inflammation compared to those with normal lungs. Although the frequency of EGFR mutation was low in patients with emphysema and fibrosis, the frequency in those with normal lungs was not different between smokers and never-smokers. Our data suggested that smokers with normal lungs were not susceptible to smoking-related inflammation, and that nonsmall cell lung cancer in smokers with normal lungs showed the same biological features to that in never-smokers. Further investigations are necessary to elucidate whether smoking-related pulmonary diseases and lung cancer might result from overlapping or associated genetic variants implicated in smoking-related inflammation.Although a history of smoking and the coexistence of emphysema were negatively associated with the frequency of EGFR mutations, these clinical factors did not affect the prognosis of the patients with EGFR mutations treated with gefitinib. Toyooka et al. showed that epidermal growth factor receptor mutation, but not sex or smoking, is independently associated with a favorable prognosis of gefitinib-treated patients with lung adenocarcinoma [5]. EGFR-TKI treatment should be considered in patients with an EGFR mutation, even if they have a history of smoking or emphysema without fibrosis.The presence of EGFR mutations in patients with pulmonary fibrosis was rare in this study. Only one (5.9%) of 17 patients with pulmonary fibrosis had an EGFR mutation. Preexisting chronic ILD is known as a risk factor for ILD in gefitinib treatment [10]. In this study, one patient with pulmonary fibrosis and an EGFR mutation treated with gefitinib developed fatal ILD.The present study had several limitations, including the fact that it was observational and uncontrolled in design and was performed at a single institution, with retrospective collection of data. The results may have been subject to some selection and treatment bias. The indications for therapy and the selection of treatment were not uniform for all patients, thereby limiting the evaluation of the effects of treatment. The data presented herein should not be interpreted as providing an appropriate evaluation of the efficacy of treatment, which will require randomized prospective studies. A multivariate analysis could not be performed due to the small sample size, and it was therefore not possible to evaluate the potential confounding effects of various other variables related to survival. However, the existence of emphysema and fibrosis on chest CT were prospectively identified at the diagnosis of lung cancer. The EGFR mutation status was identified before the EGFR-TKI treatment. Data on the demographic characteristics and survival of patients were unlikely to be affected by the study design.In summary, the frequency of EGFR mutations in patients with normal lungs on chest CT was not different between smokers and never-smokers. Of patients with sensitive EGFR mutations and normal lungs on chest CT, smokers had a comparable prognosis with never-smokers. Selecting patients on the basis of chest CT, rather than the smoking status, would likely result in a population with a greater sensitivity to gefitinib.
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*Source: 290132-2011-11-28.xml* | 2011 |
# Clinical and Metabolic Effects of Alpha-Lipoic Acid Associated with Two Different Doses of Myo-Inositol in Women with Polycystic Ovary Syndrome
**Authors:** Franca Fruzzetti; Elena Benelli; Tiziana Fidecicchi; Massimo Tonacchera
**Journal:** International Journal of Endocrinology
(2020)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2020/2901393
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## Abstract
The aim of this retrospective study was to evaluate the effects of a treatment withα-lipoic acid (ALA) associated with two different doses of myo-inositol (MI) on clinical and metabolic features of women with polycystic ovary syndrome (PCOS). Eighty-eight women received the treatment, and 71 among them had complete clinical charts and were considered eligible for this study. All women were treated with 800 mg of ALA per day: 43 patients received 2000 mg of MI and 28 received 1000 mg of MI per day. Menstrual cyclicity, BMI, FSH, LH, estradiol, testosterone, androstenedione, fasting insulin, HOMA-IR, and insulin response to a 2 h OGTT were evaluated before and after 6 months of treatment. The presence of diabetic relatives (DRs) was investigated. Cycle regularity was improved in 71.2% of women. The improvement of menstrual cyclicity occurred regardless of the state of IR and the presence of DRs of the patients. Women with IR mainly showed a significant improvement of metabolic parameters, while those without IR had significant changes of reproductive hormones. Patients with DRs did not show significant changes after the treatment. 85.7% of women taking 2000 mg of MI reported a higher improvement of menstrual regularity than those taking 1000 mg of MI (50%; p<0.01). In conclusion, ALA + MI positively affects the menstrual regularity of women with PCOS, regardless of their metabolic phenotype, with a more evident effect with a higher dose of MI. This effect seems to be insulin independent. The presence of IR seems to be a predictor of responsivity to the treatment in terms of an improvement of the metabolic profile.
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## Body
## 1. Introduction
Polycystic ovary syndrome (PCOS) is a very common endocrine disease of the reproductive age that is defined by the modified Rotterdam criteria of 2003 as the presence of at least two of the following: clinical or biochemical signs of hyperandrogenism, chronic anovulation, and polycystic ovary morphology [1]. Beside these criteria, the metabolic pattern of women with PCOS is a very important feature of the syndrome [2, 3]. Considering the pivotal role of hyperinsulinemia and insulin resistance (IR) in the pathogenesis of PCOS [4], insulin sensitizers have been proposed for the management of these patients [5, 6].Inositols are involved in the postreceptor signal transmission of several receptors, such as insulin, follicle-stimulating hormone (FSH), and thyroid-stimulating hormone (TSH), and myo-inositol (MI) is one of the most commonly used isoforms of inositol [7, 8]. MI can be incorporated in the inositol phosphoglycan (IPG), a membrane phospholipid that is involved in insulin signal transduction. Insulin interaction with its receptor can activate this transduction pathway mediated by inositols, bringing the constitution of intracellular messengers that are involved in glucose oxidative metabolism instead of nonoxidative metabolism. The MI-IPG can reduce IR and improve glucose metabolism [9]. In fact, it regulates the translocation of GLUT4 to the cellular membrane, and it downregulates the release of free fatty acids by modulating the enzyme adenylate cyclase [10].Normally, MI is enzymatically converted into another important inositol, D-chiro-inositol (DCI), by an epimerase stimulated by insulin [11]. In PCOS women with IR, the epimerase activity is dysregulated, causing an alteration of the normal balance of these two isomers both in plasma and in peripheral tissues [12]. As a result, the altered balance of inositols in PCOS patients might contribute to both IR and reproductive problems [12–14]. Many studies have been performed to assess the efficacy of MI in improving insulin sensitivity and ovarian function in women with PCOS and IR [8, 15–17]. MI supplementation at the dose of 2–4 g has shown to be effective in ameliorating both metabolic and reproductive features in PCOS women, reducing insulin plasma levels and IR, and improving the oocyte quality and menstrual cycle [8, 18–21].In very recent times,α-lipoic acid (ALA) has been considered a possible therapeutic approach to PCOS and IR [22, 23]. ALA and its reduced form, dihydro-lipoic acid (DHLA), are powerful antioxidant molecules that can act as a scavenger of the reactive oxygen species (ROS) and can regenerate other antioxidant molecules [24]. Moreover, ALA is an inhibitor of the inflammatory pattern mediated by the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) [25], and it also has an immunomodulatory function [26].In the metabolic field, ALA can improve insulin sensitivity through the activation of the expression of5′-adenosine monophosphate-activated protein kinase (AMPK), a cellular energy sensor that induces the translocation of GLUT4 (glucose transporter 4) to the plasma membrane with an insulin-independent mechanism [27–30]. A reduced ALA synthesis, probably due to the downregulation of the lipoic acid synthase (LASY) that occurs during diabetes mellitus (DM) and IR, is supposed to affect the normal glucose uptake and utilization in skeletal muscle cells [31]. In one study performed on lean, nondiabetic PCOS women, Masharani et al. demonstrated that 1200 mg/die of ALA could improve insulin sensitivity and other metabolic features [32]. The hypothesis is that ALA and MI may potentiate each other in improving IR and then the clinical features of PCOS women (menstrual cyclicity/ovarian function).Nowadays, only few studies investigated the effects of a combined approach with ALA and MI on women with PCOS, and even less is known about how IR and the presence of familiarity for DM affect the results of the treatment [33–36]. The majority of them were performed administering 800 mg of ALA and 2000 mg of MI daily [33, 34, 36], but some studies used half the dose of MI [35, 37]. No comparative studies have been performed to understand which dose works better in improving the clinical and metabolic features of PCOS women.Considering the described biological effects of MI and ALA, we may hypothesize that higher doses of MI may be able to improve the effect of ALA and that this combination of molecules could bring better results especially in those women with a higher impairment of insulin metabolism.This study aims to enlarge the actual knowledge about the efficacy of ALA in PCOS women when associated with MI. First, we studied the changes of reproductive, androgenic, and metabolic parameters of PCOS women after 6 months of treatment with 800 mg of ALA per day combined with MI, subsequently evaluating if the presence of IR and/or of familiarity for type 2 diabetes mellitus influenced the results. Then, we investigated if the same dose of ALA (800 mg) elicits different results when associated with different doses of MI (1000 mg or 2000 mg per day).
## 2. Materials and Methods
In this retrospective study, subjects were selected among patients referred to the Department of Clinical and Experimental Medicine, Sections of Gynaecological Endocrinology and of Endocrinology of the University of Pisa. This study was approved by the local ethical committee (No. 4268).All the subjects considered had a diagnosis of PCOS according to the Rotterdam criteria [1]. Women with hyperprolactinemia, hypo- or hyperthyroidism, congenital adrenal hyperplasia, Cushing’s syndrome, or androgen-secreting tumours were excluded from this study. Women gave their informed consent to drug prescription and data collection and for the use of their anonymous data for clinical publication.All women received a treatment with ALA and MI (Sinopol®, Laborest S. r. l., Italy) for 6 months and were studied before and after the drug intake. Eighty-eight women who received the prescription were initially selected, and 17 patients were dropped out from this study: 8 women were not compliant with the treatment and 9 women did not provide complete data. Seventy-one patients out of the 88 were considered eligible for this study. All women were treated with the same dose of ALA (800 mg per day). Among them, 43 patients (group A) received 2000 mg of MI per day, while 28 (group B) received 1000 mg of MI per day. Both the formulations of ALA + MI were divided into two oral administrations per day.All women were asked if they had diabetic relatives (DRs). Body mass index (BMI) (kg/m2) was calculated for all 71 women before and after the treatment. Blood samples for the laboratory tests were taken once before starting the treatment and once after 6 months of treatment, and all the samples were immediately analysed. Plasma levels of FSH (mIU/mL), luteinizing hormone (LH) (mIU/mL), estradiol (E2) (pmol/L), total testosterone (T) (nmol/L), and androstenedione (A) (nmol/L) were determined in the follicular phase. A 2 h oral glucose tolerance test (OGTT) was performed to assess glucose and insulin concentrations. Insulin response was expressed as the area under the curve (AUC), calculated using the trapezoidal rule and expressed as pmol/L × 120 min. As an indicator of insulin resistance, the homeostasis model assessment of insulin resistance (HOMA-IR) was calculated [38]. A cutoff of 2.5 was used to assess the presence of IR. Forty women had complete laboratory parameters both before and after 6 months of treatment.Plasma LH, FSH, and E2 concentrations were determined by immunometric assays (Johnson & Johnson S. p. A-Ortho Clinical Inc., Rochester, NY). Plasma levels of A were determined by using a radioimmunoassay (Biosource Europe S. A., Nivelles, Belgium). The intra-assay and interassay coefficient of variation (CV) for the A assay was 3.2% to 4.5% and 5.9% to 9.0%, respectively. T concentrations were determined by using a competitive immunoassay (Johnson & Johnson S. p. A-Ortho Clinical Inc.). The intra-assay and interassay CV of T was 2.3% to 3.1% and 4.9% to 7.0%, respectively. Insulin was determined by an immunoradiometric assay (DiaSorin S. p. A., Vercelli, Italy). The intra-assay and interassay CV for the insulin assay was 2.1% to 2.6% and 2.9% to 4.7%, respectively. Glucose levels were assessed by enzymatic methods (Roche Diagnostics, Basel, Switzerland).All women were asked about their menstrual cyclicity before and after the treatment. Women who basally reported the presence of oligomenorrhea were asked if they had an improvement or no change of cycle length after the treatment. Women who reported hirsutism at the baseline were asked if there was no change, improvement, or worsening of it after the treatment. The patients were submitted to a pelvic transabdominal or transvaginal ultrasound before and after 6 months of treatment, and ovarian morphology (reported as normal or PCO-like [1]) was evaluated.Seventeen women had IR before the treatment, 49 women had an HOMA-IR < 2.5, and 5 did not have a basal OGTT. Twenty-six women were reported to have one or more DRs. Forty-five women did not have familiarity for type 2 diabetes mellitus. Considering their BMI, 30 women were normal weight, 24 were overweight, and 17 were obese.Thirty healthy subjects with normal cycles and no symptoms of hyperandrogenism were included as controls for baseline characteristics.
### 2.1. Statistical Analysis
Continuous variables were reported as the mean ± standard deviation (SD), while nominal variables were reported as percentages (%). The differences between the group of patients and the controls at the baseline were calculated using Student’st-test for unpaired data. The Shapiro–Wilk test was used to test normality. To evaluate the effect of the treatment, Student’s t-test for paired data or the Wilcoxon signed-rank test was used, as appropriate. The differences in the effects on the menstrual cycle between the subgroups of patients were tested with the χ2 test. For all the analysis, a value of p<0.05 was considered statistically significant. IBM® SPSS Statistics® software, version 25, was used for the statistical analysis.
## 2.1. Statistical Analysis
Continuous variables were reported as the mean ± standard deviation (SD), while nominal variables were reported as percentages (%). The differences between the group of patients and the controls at the baseline were calculated using Student’st-test for unpaired data. The Shapiro–Wilk test was used to test normality. To evaluate the effect of the treatment, Student’s t-test for paired data or the Wilcoxon signed-rank test was used, as appropriate. The differences in the effects on the menstrual cycle between the subgroups of patients were tested with the χ2 test. For all the analysis, a value of p<0.05 was considered statistically significant. IBM® SPSS Statistics® software, version 25, was used for the statistical analysis.
## 3. Results
### 3.1. Baseline Characteristics
The characteristics of the patients and the controls at the baseline are reported in Table1. Patients with PCOS had higher androgen levels than controls, and reproductive and metabolic parameters were generally compromised. Before the treatment, 59 patients (83.1%) had oligomenorrhea, 46 (64.8%) had hirsutism, and 47 (66.2%) had PCO-like ovaries.Table 1
Characteristics of the entire group of women at the baseline and after six months of treatment with ALA plus MI.
Controls
ALA + MI
Baseline
6 months
Age (years)
23.1 ± 5.4
21.56 ± 4.77
—
BMI (kg/m2)
27.17 ± 3.93
26.97 ± 5.15
26.47 ± 4.95∗
FSH (mIU/mL)
4.17 ± 0.24
6.86 ± 3.05b
5.19 ± 2.44∗∗
LH (mIU/mL)
4.52 ± 1.49
12.55 ± 7.16b
10.26 ± 6.79
Estradiol (pmol/L)
265.07 ± 132.57
272.19 ± 273.26
412.40 ± 339.01∗∗
Total testosterone (nmol/L)
1.18 ± 0.38
2.39 ± 0.66b
2.32 ± 0.69
Androstenedione (nmol/L)
5.76 ± 2.13
11.70 ± 4.64b
12.53 ± 4.36
Fasting insulin (pmol/L)
52.08 ± 15.63
66.25 ± 31.60a
61.60 ± 24.86
HOMA-IR
1.50 ± 0.19
1.99 ± 1.03b
1.79 ± 0.73
AUC-insulin (pmol/L × 120 min)
40884.37 ± 14743.89
55110.14 ± 33112.92a
49892.78 ± 22061.11
Baseline parameters were compared with those of a control group (N = 30) without PCOS. Age and BMI of PCOS women were calculated on 71 women, while laboratory parameters were available both before and after the treatment in 40 patients. All data are reported as the mean ± SD. ap<0.05 vs. control; bp<0.001 vs. control; ∗p<0.05 vs. baseline; ∗∗p<0.01 vs. baseline. ALA: α-lipoic acid; AUC: area under the curve; BMI: body mass index; FSH: follicle-stimulating hormone; HOMA-IR: homeostasis model assessment of insulin resistance; LH: luteinizing hormone; MI: myo-inositol; PCOS: polycystic ovary syndrome; SD: standard deviation.Only 17 women (23.9%) had IR before the treatment. Twenty-six women (36.6%) were reported to have one or more DRs.
## 3.1. Baseline Characteristics
The characteristics of the patients and the controls at the baseline are reported in Table1. Patients with PCOS had higher androgen levels than controls, and reproductive and metabolic parameters were generally compromised. Before the treatment, 59 patients (83.1%) had oligomenorrhea, 46 (64.8%) had hirsutism, and 47 (66.2%) had PCO-like ovaries.Table 1
Characteristics of the entire group of women at the baseline and after six months of treatment with ALA plus MI.
Controls
ALA + MI
Baseline
6 months
Age (years)
23.1 ± 5.4
21.56 ± 4.77
—
BMI (kg/m2)
27.17 ± 3.93
26.97 ± 5.15
26.47 ± 4.95∗
FSH (mIU/mL)
4.17 ± 0.24
6.86 ± 3.05b
5.19 ± 2.44∗∗
LH (mIU/mL)
4.52 ± 1.49
12.55 ± 7.16b
10.26 ± 6.79
Estradiol (pmol/L)
265.07 ± 132.57
272.19 ± 273.26
412.40 ± 339.01∗∗
Total testosterone (nmol/L)
1.18 ± 0.38
2.39 ± 0.66b
2.32 ± 0.69
Androstenedione (nmol/L)
5.76 ± 2.13
11.70 ± 4.64b
12.53 ± 4.36
Fasting insulin (pmol/L)
52.08 ± 15.63
66.25 ± 31.60a
61.60 ± 24.86
HOMA-IR
1.50 ± 0.19
1.99 ± 1.03b
1.79 ± 0.73
AUC-insulin (pmol/L × 120 min)
40884.37 ± 14743.89
55110.14 ± 33112.92a
49892.78 ± 22061.11
Baseline parameters were compared with those of a control group (N = 30) without PCOS. Age and BMI of PCOS women were calculated on 71 women, while laboratory parameters were available both before and after the treatment in 40 patients. All data are reported as the mean ± SD. ap<0.05 vs. control; bp<0.001 vs. control; ∗p<0.05 vs. baseline; ∗∗p<0.01 vs. baseline. ALA: α-lipoic acid; AUC: area under the curve; BMI: body mass index; FSH: follicle-stimulating hormone; HOMA-IR: homeostasis model assessment of insulin resistance; LH: luteinizing hormone; MI: myo-inositol; PCOS: polycystic ovary syndrome; SD: standard deviation.Only 17 women (23.9%) had IR before the treatment. Twenty-six women (36.6%) were reported to have one or more DRs.
## 4. Results of the Treatment
The results of the treatment in the entire group of women are reported in Table1. BMI was significantly reduced (p<0.05). Moreover, significant results were highlighted only in reproductive parameters, with a reduction of FSH (p<0.01) and an increase of E2 (p<0.01). Among the 59 women with oligomenorrhea, 71.2% reported a relevant improvement of menstrual regularity, with a shortening of the menstrual length, while 28.8% reported no change of the cycle after the treatment. 50% of women reported no change of their hirsutism, 39.1% reported an improvement, and 10.9% reported a worsening of it. Only 19.2% normalized their ovarian morphology after the treatment.Table2 summarizes the results obtained dividing patients according to the presence of IR and of DRs. Women with IR showed a significant reduction of BMI (p<0.05) and an increase of E2 (p<0.05). Moreover, they showed a relevant improvement of the metabolic pattern, with a reduction of fasting insulin and of HOMA-IR (p<0.01): 80% of them had a normal HOMA-IR after the treatment. Women without IR only showed a significant reduction of FSH (p<0.01) and an increase of E2 (p<0.05). Cycle length was improved in 80.0% of patients with IR and in 70.8% of those without IR (p=NS) (Figure 1).Table 2
Results of the treatment with ALA plus MI in the patients divided into subgroups according to the presence of IR and of DRs.
BMI (kg/m2)
FSH (mIU/mL)
LH (mIU/mL)
Estradiol (pmol/L)
Total testosterone (ng/mL)
Androstenedione (ng/mL)
Fasting insulin (pmol/L)
HOMA-IR
AUC-insulin (pmol/L × 120 min)
IR
Baseline
31.08 ± 5.81
5.49 ± 1.70
11.08 ± 4.95
253.32 ± 216.13
2.32 ± 0.42
11.49 ± 4.33
108.40 ± 25.21
3.31 ± 0.91
76749.93 ± 44293.96
6 months
30.25 ± 6.31∗
4.90 ± 2.79
9.07 ± 6.50
394.89 ± 314.82∗
2.22 ± 0.55
10.86 ± 4.22
74.72 ± 20.21∗∗
2.13 ± 0.66∗∗
61385.76 ± 19343.06
No IR
Baseline
25.74 ± 4.34
7.38 ± 3.30
13.08 ± 7.83
278.47 ± 293.23
2.39 ± 0.73
11.77 ± 4.82
51.74 ± 17.22
1.51 ± 0.57
47095.35 ± 24335.69
6 months
25.32 ± 3.89
5.30 ± 2.35∗∗
10.69 ± 6.97
418.28 ± 353.26∗
2.36 ± 0.73
13.02 ± 4.40
57.01 ± 25.07
1.67 ± 0.73
45636.11 ± 21788.68
With DRs
Baseline
26.47 ± 4.54
7.47 ± 4.64
10.44 ± 4.84
341.99 ± 389.93
2.29 ± 0.76
11.42 ± 1.86
63.89 ± 29.58
1.85 ± 0.89
64158.06 ± 49596.88
6 months
25.61 ± 4.14∗
5.61 ± 2.33
11.22 ± 7.40
440.85 ± 375.32
2.29 ± 0.73
13.55 ± 4.85
61.53 ± 20.63
1.80 ± 0.64
49730.97 ± 19476.60
Without DRs
Baseline
27.27 ± 5.50
6.52 ± 1.64
13.70 ± 8.03
232.73 ± 177.07
2.43 ± 0.62
11.87 ± 3.42
67.43 ± 33.06
2.05 ± 1.10
50767.08 ± 21370.14
6 months
26.91 ± 5.37
4.95 ± 2.52∗
9.74 ± 6.56∗
396.36 ± 324.47∗∗
2.36 ± 0.66
12.01 ± 4.12
61.60 ± 27.15
1.78 ± 0.78a
49970.42 ± 23582.92
All data are reported as the mean ± SD. 17 women had IR, and 49 did not. Women with IR showed a reduction of BMI, fasting insulin, and HOMA-IR and an increase in estradiol, while women without IR showed an increase in estradiol and a reduction of FSH. 26 women had DRs, and 45 did not. Women with DRs only showed a significant reduction of BMI, while women without DRs showed a significant reduction of FSH and LH and an increase of estradiol, with a tendency to a reduction of HOMA-IR.∗p<0.05 vs. baseline; ∗∗p<0.01 vs. baseline; ap=0.052. ALA: α-lipoic acid; AUC: area under the curve; BMI: body mass index; DRs: diabetic relatives; FSH: follicle-stimulating hormone; HOMA-IR: homeostasis model assessment of insulin resistance; IR: insulin resistance; LH: luteinizing hormone; MI: myo-inositol; PCOS: polycystic ovary syndrome; SD: standard deviation.Figure 1
Percentages of women who reported an improvement of menstrual regularity after the treatment. (a) Women with insulin resistance (IR) reported similar changes of menstrual cyclicity than those without IR. (b) Women with diabetic relatives (DRs) reported similar changes of menstrual cyclicity than those without DRs. (c) A higher percentage of women of group A (2000 mg of MI + 800 mg of ALA) reported an improvement of menstrual cyclicity than those of group B (1000 mg of MI + 800 mg of ALA).∗p<0.01 (group A vs. group B).
(a)
(b)
(c)DRs did not significantly influence the results. On the contrary, women without DRs showed a relevant improvement of reproductive parameters (FSH, LH, and E2), while BMI (p=0.06) and HOMA-IR (p=0.052) only showed a tendency to a reduction (Table 2). Both the groups of women reported similar results on menstrual regularity, with a reduction of cycle length in 73% of women without DRs and in 68.2% of women with DRs (p=NS) (Figure 1).Table3 summarizes the results obtained dividing the patients according to the different doses of MI that they received in combination with the same dose of ALA. Group A (800 mg ALA + 2000 mg MI per day) showed a significant change of BMI (p<0.01) and E2 and AUC-insulin (p<0.05) after 6 months of treatment, while group B (800 mg ALA + 1000 mg MI per day) showed a significant change of FSH (p<0.01) and LH and E2 (p<0.05) but no changes in the metabolic parameters. Cycle length was improved in 85.7% of patients in group A and in 50% of those in group B (p<0.01) (Figure 1).Table 3
Results of the treatment in two subgroups of women taking the same dose of ALA (800 mg) and two different doses of MI per day (group A 2000 mg; group B 1000 mg).
Group A
Group B
Baseline
6 months
Baseline
6 months
BMI (kg/m2)
27.10 ± 4.19
25.02 ± 4.03∗∗
26.79 ± 6.43
27.15 ± 6.12.62
FSH (mIU/mL)
5.73 ± 1.85
4.88 ± 1.45
7.11 ± 3.23
5.26 ± 2.62∗∗
LH (mIU/mL)
14.73 ± 8.42
13.42 ± 6.32
12.09 ± 6.95
9.59 ± 6.80∗
Estradiol (pmol/L)
255.16 ± 219.14
402.01 ± 339.38∗
277.04 ± 290.22
415.38 ± 345.11∗
Total testosterone (ng/mL)
2.88 ± 0.73
2.70 ± 0.80
2.18 ± 0.55
2.18 ± 0.59
Fasting insulin (pmol/L)
66.81 ± 30.00
71.04 ± 29.17
61.60 ± 24.86
55.63 ± 20.21
HOMA-IR
1.93 ± 0.91
2.00 ± 0.84
1.79 ± 0.73
1.66 ± 0.64
AUC-insulin (pmol/L × 120 min)
60833.82 ± 19899.02
51441.04 ± 22941.46∗
52009.79 ± 38484.58
49054.10 ± 22024.79
The higher dose of MI caused changes in BMI, estradiol levels, and AUC-insulin, while the lowest dose caused changes in FSH, LH, and estradiol levels. All data are reported as the mean ± SD.∗p<0.05 vs. baseline of the same group; ∗∗p<0.01 vs. baseline of the same group. ALA: α-lipoic acid; AUC: area under the curve; BMI: body mass index; FSH: follicle-stimulating hormone; HOMA-IR: homeostasis model assessment of insulin resistance; IR: insulin resistance; LH: luteinizing hormone; MI: myo-inositol; SD: standard deviation.
## 5. Discussion
This study shows the ability of a combination of ALA and MI to restore a normal menstrual cyclicity in women with PCOS, acting on hormonal or on metabolic parameters. The better results were obtained when ALA was associated with a higher dose of MI.We observed that the improvement of menstrual cyclicity occurs regardless of the state of IR and of the presence of DRs of the patients: every subgroup showed a similar percentage of women (between 68 and 80%) that reported a better condition after 6 months of treatment. Comparing women with and without IR, we found that menstrual cyclicity was restored in both groups, but IR women only also showed an improvement of metabolic parameters. On the contrary, hormonal parameters (FSH and E2) seem to be affected by the treatment only in women without IR.The results obtained in not-IR women are similar to those of De Cicco et al. They studied a group of obese PCOS women without IR treated with MI and ALA for six months, and they found an improvement of cycle length, BMI, hyperandrogenism, and ovarian volume without effects on HOMA-IR and AUC-insulin (both in a normal range at the baseline).A mandatory role in the improvement of menstrual cyclicity seems to be exerted by the presence of MI in the association. The hypothesis that the effects are mainly MI-mediated is supported by the fact that the only difference in the improvement of menstrual cyclicity was found comparing women who took 2000 mg of MI with those taking 1000 mg of MI: a higher dose of MI associated with the same dose of ALA demonstrated to be more effective in the regularization of the menstrual cycle than the administration of the ALA itself. Anyway, we found also that a low dose of MI can be sufficient to improve the menstrual cyclicity in 50% of women, so maybe this feature is very sensitive to the administration of inositol. Considering the results in women without IR, we can hypothesize that MI can act independently from the IR state. In fact, MI has been recognized to directly facilitate the activity of FSH, acting as a second messenger also for this hormone’s receptor [39, 40]. Consequently, in women without IR, MI may be able to act improving FSH response in granulosa cells, thus promoting the normal maturation of the follicle and contributing to normalizing E2 levels.The mechanism through which ALA may have a role in the normalization of the ovarian function is less clear. This is supported also by the results of other studies in the literature. Genazzani et al. in 2018 [41], and again in 2019 [37], demonstrated that ALA alone is not able to affect the reproductive features of PCOS women. In particular, it is difficult to explain which could be its exact role in the improvement of menstrual cyclicity in women without IR. The mechanism seems to be insulin-independent. However, it cannot be excluded that ALA, thanks to its biological activity, may participate in the restoration of the wellbeing of the ovary with an anti-inflammatory action. PCOS is associated with decreased antioxidant concentrations, and it can be considered an oxidative state [42]. WNT5a, a proinflammatory marker, is increased in granulosa cells of both lean and obese PCOS women, and it contributes to the chronic inflammation and to the production of ROS through the activation of the expression of NF-κB [43]. ALA can modulate the NF-κB expression [25]. It is possible that ALA could reduce inflammation and oxidative stress also in the ovary. We may speculate that ALA might contribute to the restoration of a normal environment in the ovary increasing the positive effect of MI.Women with IR experienced a completely different response to the same treatment. When IR was present, the treatment with ALA and MI reduced fasting insulin and HOMA-IR, restoring a normal insulin sensitivity in almost 80% of the women. This may be due to a synergistic effect displayed by the two insulin-sensitizing molecules: ALA increases the translocation of GLUT4 to the membrane in an insulin-independent way, while MI acts as a second messenger in the pathway of the insulin receptor. When IR is present, high insulin levels impair the normal secretion of LH and FSH from pituitary cells and their function in the ovaries, promoting premature luteinization of follicles [4, 44] Although their effects on gonadotropins and on inflammation, the ability of ALA and MI to restore normal levels of insulin in PCOS women with IR may be another mechanism and probably the condition conditio sine qua non, by which these molecules are able to improve menstrual regularity in women with IR.The clinical efficacy of ALA and MI was not influenced by the presence of DRs. Menstrual cyclicity was similarly improved in both groups, but only women without DRs showed positive results on the reproductive parameters. These results are in contrast with those obtained by other authors, who hypothesized that women with PCOS and DRs had a defect of the LASY similarly to overt diabetes [35, 41]. Therefore, more accurate studies should be performed to understand which alterations are present in PCOS women with DRs, in order to customize the treatment used. Our results suggest that the defect of the LASY is not the only alteration present in this group of women: other mechanisms should be involved, and ALA seems not to be sufficient to act against all of them.In conclusion, our study demonstrated that the association of ALA and MI can positively affect the menstrual regularity of women with PCOS, with a more evident effect with a higher dose of MI. The presence of IR seems to be a predictor of responsivity to the treatment in terms of an improvement of the metabolic profile, but not in terms of menstrual cyclicity. At present, no explanation seems to be exhaustive, and more studies should be needed to better investigate the mechanisms through which ALA and MI exert their action in women with and without IR.
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*Source: 2901393-2020-03-19.xml* | 2901393-2020-03-19_2901393-2020-03-19.md | 30,472 | Clinical and Metabolic Effects of Alpha-Lipoic Acid Associated with Two Different Doses of Myo-Inositol in Women with Polycystic Ovary Syndrome | Franca Fruzzetti; Elena Benelli; Tiziana Fidecicchi; Massimo Tonacchera | International Journal of Endocrinology
(2020) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2020/2901393 | 2901393-2020-03-19.xml | ---
## Abstract
The aim of this retrospective study was to evaluate the effects of a treatment withα-lipoic acid (ALA) associated with two different doses of myo-inositol (MI) on clinical and metabolic features of women with polycystic ovary syndrome (PCOS). Eighty-eight women received the treatment, and 71 among them had complete clinical charts and were considered eligible for this study. All women were treated with 800 mg of ALA per day: 43 patients received 2000 mg of MI and 28 received 1000 mg of MI per day. Menstrual cyclicity, BMI, FSH, LH, estradiol, testosterone, androstenedione, fasting insulin, HOMA-IR, and insulin response to a 2 h OGTT were evaluated before and after 6 months of treatment. The presence of diabetic relatives (DRs) was investigated. Cycle regularity was improved in 71.2% of women. The improvement of menstrual cyclicity occurred regardless of the state of IR and the presence of DRs of the patients. Women with IR mainly showed a significant improvement of metabolic parameters, while those without IR had significant changes of reproductive hormones. Patients with DRs did not show significant changes after the treatment. 85.7% of women taking 2000 mg of MI reported a higher improvement of menstrual regularity than those taking 1000 mg of MI (50%; p<0.01). In conclusion, ALA + MI positively affects the menstrual regularity of women with PCOS, regardless of their metabolic phenotype, with a more evident effect with a higher dose of MI. This effect seems to be insulin independent. The presence of IR seems to be a predictor of responsivity to the treatment in terms of an improvement of the metabolic profile.
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## Body
## 1. Introduction
Polycystic ovary syndrome (PCOS) is a very common endocrine disease of the reproductive age that is defined by the modified Rotterdam criteria of 2003 as the presence of at least two of the following: clinical or biochemical signs of hyperandrogenism, chronic anovulation, and polycystic ovary morphology [1]. Beside these criteria, the metabolic pattern of women with PCOS is a very important feature of the syndrome [2, 3]. Considering the pivotal role of hyperinsulinemia and insulin resistance (IR) in the pathogenesis of PCOS [4], insulin sensitizers have been proposed for the management of these patients [5, 6].Inositols are involved in the postreceptor signal transmission of several receptors, such as insulin, follicle-stimulating hormone (FSH), and thyroid-stimulating hormone (TSH), and myo-inositol (MI) is one of the most commonly used isoforms of inositol [7, 8]. MI can be incorporated in the inositol phosphoglycan (IPG), a membrane phospholipid that is involved in insulin signal transduction. Insulin interaction with its receptor can activate this transduction pathway mediated by inositols, bringing the constitution of intracellular messengers that are involved in glucose oxidative metabolism instead of nonoxidative metabolism. The MI-IPG can reduce IR and improve glucose metabolism [9]. In fact, it regulates the translocation of GLUT4 to the cellular membrane, and it downregulates the release of free fatty acids by modulating the enzyme adenylate cyclase [10].Normally, MI is enzymatically converted into another important inositol, D-chiro-inositol (DCI), by an epimerase stimulated by insulin [11]. In PCOS women with IR, the epimerase activity is dysregulated, causing an alteration of the normal balance of these two isomers both in plasma and in peripheral tissues [12]. As a result, the altered balance of inositols in PCOS patients might contribute to both IR and reproductive problems [12–14]. Many studies have been performed to assess the efficacy of MI in improving insulin sensitivity and ovarian function in women with PCOS and IR [8, 15–17]. MI supplementation at the dose of 2–4 g has shown to be effective in ameliorating both metabolic and reproductive features in PCOS women, reducing insulin plasma levels and IR, and improving the oocyte quality and menstrual cycle [8, 18–21].In very recent times,α-lipoic acid (ALA) has been considered a possible therapeutic approach to PCOS and IR [22, 23]. ALA and its reduced form, dihydro-lipoic acid (DHLA), are powerful antioxidant molecules that can act as a scavenger of the reactive oxygen species (ROS) and can regenerate other antioxidant molecules [24]. Moreover, ALA is an inhibitor of the inflammatory pattern mediated by the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) [25], and it also has an immunomodulatory function [26].In the metabolic field, ALA can improve insulin sensitivity through the activation of the expression of5′-adenosine monophosphate-activated protein kinase (AMPK), a cellular energy sensor that induces the translocation of GLUT4 (glucose transporter 4) to the plasma membrane with an insulin-independent mechanism [27–30]. A reduced ALA synthesis, probably due to the downregulation of the lipoic acid synthase (LASY) that occurs during diabetes mellitus (DM) and IR, is supposed to affect the normal glucose uptake and utilization in skeletal muscle cells [31]. In one study performed on lean, nondiabetic PCOS women, Masharani et al. demonstrated that 1200 mg/die of ALA could improve insulin sensitivity and other metabolic features [32]. The hypothesis is that ALA and MI may potentiate each other in improving IR and then the clinical features of PCOS women (menstrual cyclicity/ovarian function).Nowadays, only few studies investigated the effects of a combined approach with ALA and MI on women with PCOS, and even less is known about how IR and the presence of familiarity for DM affect the results of the treatment [33–36]. The majority of them were performed administering 800 mg of ALA and 2000 mg of MI daily [33, 34, 36], but some studies used half the dose of MI [35, 37]. No comparative studies have been performed to understand which dose works better in improving the clinical and metabolic features of PCOS women.Considering the described biological effects of MI and ALA, we may hypothesize that higher doses of MI may be able to improve the effect of ALA and that this combination of molecules could bring better results especially in those women with a higher impairment of insulin metabolism.This study aims to enlarge the actual knowledge about the efficacy of ALA in PCOS women when associated with MI. First, we studied the changes of reproductive, androgenic, and metabolic parameters of PCOS women after 6 months of treatment with 800 mg of ALA per day combined with MI, subsequently evaluating if the presence of IR and/or of familiarity for type 2 diabetes mellitus influenced the results. Then, we investigated if the same dose of ALA (800 mg) elicits different results when associated with different doses of MI (1000 mg or 2000 mg per day).
## 2. Materials and Methods
In this retrospective study, subjects were selected among patients referred to the Department of Clinical and Experimental Medicine, Sections of Gynaecological Endocrinology and of Endocrinology of the University of Pisa. This study was approved by the local ethical committee (No. 4268).All the subjects considered had a diagnosis of PCOS according to the Rotterdam criteria [1]. Women with hyperprolactinemia, hypo- or hyperthyroidism, congenital adrenal hyperplasia, Cushing’s syndrome, or androgen-secreting tumours were excluded from this study. Women gave their informed consent to drug prescription and data collection and for the use of their anonymous data for clinical publication.All women received a treatment with ALA and MI (Sinopol®, Laborest S. r. l., Italy) for 6 months and were studied before and after the drug intake. Eighty-eight women who received the prescription were initially selected, and 17 patients were dropped out from this study: 8 women were not compliant with the treatment and 9 women did not provide complete data. Seventy-one patients out of the 88 were considered eligible for this study. All women were treated with the same dose of ALA (800 mg per day). Among them, 43 patients (group A) received 2000 mg of MI per day, while 28 (group B) received 1000 mg of MI per day. Both the formulations of ALA + MI were divided into two oral administrations per day.All women were asked if they had diabetic relatives (DRs). Body mass index (BMI) (kg/m2) was calculated for all 71 women before and after the treatment. Blood samples for the laboratory tests were taken once before starting the treatment and once after 6 months of treatment, and all the samples were immediately analysed. Plasma levels of FSH (mIU/mL), luteinizing hormone (LH) (mIU/mL), estradiol (E2) (pmol/L), total testosterone (T) (nmol/L), and androstenedione (A) (nmol/L) were determined in the follicular phase. A 2 h oral glucose tolerance test (OGTT) was performed to assess glucose and insulin concentrations. Insulin response was expressed as the area under the curve (AUC), calculated using the trapezoidal rule and expressed as pmol/L × 120 min. As an indicator of insulin resistance, the homeostasis model assessment of insulin resistance (HOMA-IR) was calculated [38]. A cutoff of 2.5 was used to assess the presence of IR. Forty women had complete laboratory parameters both before and after 6 months of treatment.Plasma LH, FSH, and E2 concentrations were determined by immunometric assays (Johnson & Johnson S. p. A-Ortho Clinical Inc., Rochester, NY). Plasma levels of A were determined by using a radioimmunoassay (Biosource Europe S. A., Nivelles, Belgium). The intra-assay and interassay coefficient of variation (CV) for the A assay was 3.2% to 4.5% and 5.9% to 9.0%, respectively. T concentrations were determined by using a competitive immunoassay (Johnson & Johnson S. p. A-Ortho Clinical Inc.). The intra-assay and interassay CV of T was 2.3% to 3.1% and 4.9% to 7.0%, respectively. Insulin was determined by an immunoradiometric assay (DiaSorin S. p. A., Vercelli, Italy). The intra-assay and interassay CV for the insulin assay was 2.1% to 2.6% and 2.9% to 4.7%, respectively. Glucose levels were assessed by enzymatic methods (Roche Diagnostics, Basel, Switzerland).All women were asked about their menstrual cyclicity before and after the treatment. Women who basally reported the presence of oligomenorrhea were asked if they had an improvement or no change of cycle length after the treatment. Women who reported hirsutism at the baseline were asked if there was no change, improvement, or worsening of it after the treatment. The patients were submitted to a pelvic transabdominal or transvaginal ultrasound before and after 6 months of treatment, and ovarian morphology (reported as normal or PCO-like [1]) was evaluated.Seventeen women had IR before the treatment, 49 women had an HOMA-IR < 2.5, and 5 did not have a basal OGTT. Twenty-six women were reported to have one or more DRs. Forty-five women did not have familiarity for type 2 diabetes mellitus. Considering their BMI, 30 women were normal weight, 24 were overweight, and 17 were obese.Thirty healthy subjects with normal cycles and no symptoms of hyperandrogenism were included as controls for baseline characteristics.
### 2.1. Statistical Analysis
Continuous variables were reported as the mean ± standard deviation (SD), while nominal variables were reported as percentages (%). The differences between the group of patients and the controls at the baseline were calculated using Student’st-test for unpaired data. The Shapiro–Wilk test was used to test normality. To evaluate the effect of the treatment, Student’s t-test for paired data or the Wilcoxon signed-rank test was used, as appropriate. The differences in the effects on the menstrual cycle between the subgroups of patients were tested with the χ2 test. For all the analysis, a value of p<0.05 was considered statistically significant. IBM® SPSS Statistics® software, version 25, was used for the statistical analysis.
## 2.1. Statistical Analysis
Continuous variables were reported as the mean ± standard deviation (SD), while nominal variables were reported as percentages (%). The differences between the group of patients and the controls at the baseline were calculated using Student’st-test for unpaired data. The Shapiro–Wilk test was used to test normality. To evaluate the effect of the treatment, Student’s t-test for paired data or the Wilcoxon signed-rank test was used, as appropriate. The differences in the effects on the menstrual cycle between the subgroups of patients were tested with the χ2 test. For all the analysis, a value of p<0.05 was considered statistically significant. IBM® SPSS Statistics® software, version 25, was used for the statistical analysis.
## 3. Results
### 3.1. Baseline Characteristics
The characteristics of the patients and the controls at the baseline are reported in Table1. Patients with PCOS had higher androgen levels than controls, and reproductive and metabolic parameters were generally compromised. Before the treatment, 59 patients (83.1%) had oligomenorrhea, 46 (64.8%) had hirsutism, and 47 (66.2%) had PCO-like ovaries.Table 1
Characteristics of the entire group of women at the baseline and after six months of treatment with ALA plus MI.
Controls
ALA + MI
Baseline
6 months
Age (years)
23.1 ± 5.4
21.56 ± 4.77
—
BMI (kg/m2)
27.17 ± 3.93
26.97 ± 5.15
26.47 ± 4.95∗
FSH (mIU/mL)
4.17 ± 0.24
6.86 ± 3.05b
5.19 ± 2.44∗∗
LH (mIU/mL)
4.52 ± 1.49
12.55 ± 7.16b
10.26 ± 6.79
Estradiol (pmol/L)
265.07 ± 132.57
272.19 ± 273.26
412.40 ± 339.01∗∗
Total testosterone (nmol/L)
1.18 ± 0.38
2.39 ± 0.66b
2.32 ± 0.69
Androstenedione (nmol/L)
5.76 ± 2.13
11.70 ± 4.64b
12.53 ± 4.36
Fasting insulin (pmol/L)
52.08 ± 15.63
66.25 ± 31.60a
61.60 ± 24.86
HOMA-IR
1.50 ± 0.19
1.99 ± 1.03b
1.79 ± 0.73
AUC-insulin (pmol/L × 120 min)
40884.37 ± 14743.89
55110.14 ± 33112.92a
49892.78 ± 22061.11
Baseline parameters were compared with those of a control group (N = 30) without PCOS. Age and BMI of PCOS women were calculated on 71 women, while laboratory parameters were available both before and after the treatment in 40 patients. All data are reported as the mean ± SD. ap<0.05 vs. control; bp<0.001 vs. control; ∗p<0.05 vs. baseline; ∗∗p<0.01 vs. baseline. ALA: α-lipoic acid; AUC: area under the curve; BMI: body mass index; FSH: follicle-stimulating hormone; HOMA-IR: homeostasis model assessment of insulin resistance; LH: luteinizing hormone; MI: myo-inositol; PCOS: polycystic ovary syndrome; SD: standard deviation.Only 17 women (23.9%) had IR before the treatment. Twenty-six women (36.6%) were reported to have one or more DRs.
## 3.1. Baseline Characteristics
The characteristics of the patients and the controls at the baseline are reported in Table1. Patients with PCOS had higher androgen levels than controls, and reproductive and metabolic parameters were generally compromised. Before the treatment, 59 patients (83.1%) had oligomenorrhea, 46 (64.8%) had hirsutism, and 47 (66.2%) had PCO-like ovaries.Table 1
Characteristics of the entire group of women at the baseline and after six months of treatment with ALA plus MI.
Controls
ALA + MI
Baseline
6 months
Age (years)
23.1 ± 5.4
21.56 ± 4.77
—
BMI (kg/m2)
27.17 ± 3.93
26.97 ± 5.15
26.47 ± 4.95∗
FSH (mIU/mL)
4.17 ± 0.24
6.86 ± 3.05b
5.19 ± 2.44∗∗
LH (mIU/mL)
4.52 ± 1.49
12.55 ± 7.16b
10.26 ± 6.79
Estradiol (pmol/L)
265.07 ± 132.57
272.19 ± 273.26
412.40 ± 339.01∗∗
Total testosterone (nmol/L)
1.18 ± 0.38
2.39 ± 0.66b
2.32 ± 0.69
Androstenedione (nmol/L)
5.76 ± 2.13
11.70 ± 4.64b
12.53 ± 4.36
Fasting insulin (pmol/L)
52.08 ± 15.63
66.25 ± 31.60a
61.60 ± 24.86
HOMA-IR
1.50 ± 0.19
1.99 ± 1.03b
1.79 ± 0.73
AUC-insulin (pmol/L × 120 min)
40884.37 ± 14743.89
55110.14 ± 33112.92a
49892.78 ± 22061.11
Baseline parameters were compared with those of a control group (N = 30) without PCOS. Age and BMI of PCOS women were calculated on 71 women, while laboratory parameters were available both before and after the treatment in 40 patients. All data are reported as the mean ± SD. ap<0.05 vs. control; bp<0.001 vs. control; ∗p<0.05 vs. baseline; ∗∗p<0.01 vs. baseline. ALA: α-lipoic acid; AUC: area under the curve; BMI: body mass index; FSH: follicle-stimulating hormone; HOMA-IR: homeostasis model assessment of insulin resistance; LH: luteinizing hormone; MI: myo-inositol; PCOS: polycystic ovary syndrome; SD: standard deviation.Only 17 women (23.9%) had IR before the treatment. Twenty-six women (36.6%) were reported to have one or more DRs.
## 4. Results of the Treatment
The results of the treatment in the entire group of women are reported in Table1. BMI was significantly reduced (p<0.05). Moreover, significant results were highlighted only in reproductive parameters, with a reduction of FSH (p<0.01) and an increase of E2 (p<0.01). Among the 59 women with oligomenorrhea, 71.2% reported a relevant improvement of menstrual regularity, with a shortening of the menstrual length, while 28.8% reported no change of the cycle after the treatment. 50% of women reported no change of their hirsutism, 39.1% reported an improvement, and 10.9% reported a worsening of it. Only 19.2% normalized their ovarian morphology after the treatment.Table2 summarizes the results obtained dividing patients according to the presence of IR and of DRs. Women with IR showed a significant reduction of BMI (p<0.05) and an increase of E2 (p<0.05). Moreover, they showed a relevant improvement of the metabolic pattern, with a reduction of fasting insulin and of HOMA-IR (p<0.01): 80% of them had a normal HOMA-IR after the treatment. Women without IR only showed a significant reduction of FSH (p<0.01) and an increase of E2 (p<0.05). Cycle length was improved in 80.0% of patients with IR and in 70.8% of those without IR (p=NS) (Figure 1).Table 2
Results of the treatment with ALA plus MI in the patients divided into subgroups according to the presence of IR and of DRs.
BMI (kg/m2)
FSH (mIU/mL)
LH (mIU/mL)
Estradiol (pmol/L)
Total testosterone (ng/mL)
Androstenedione (ng/mL)
Fasting insulin (pmol/L)
HOMA-IR
AUC-insulin (pmol/L × 120 min)
IR
Baseline
31.08 ± 5.81
5.49 ± 1.70
11.08 ± 4.95
253.32 ± 216.13
2.32 ± 0.42
11.49 ± 4.33
108.40 ± 25.21
3.31 ± 0.91
76749.93 ± 44293.96
6 months
30.25 ± 6.31∗
4.90 ± 2.79
9.07 ± 6.50
394.89 ± 314.82∗
2.22 ± 0.55
10.86 ± 4.22
74.72 ± 20.21∗∗
2.13 ± 0.66∗∗
61385.76 ± 19343.06
No IR
Baseline
25.74 ± 4.34
7.38 ± 3.30
13.08 ± 7.83
278.47 ± 293.23
2.39 ± 0.73
11.77 ± 4.82
51.74 ± 17.22
1.51 ± 0.57
47095.35 ± 24335.69
6 months
25.32 ± 3.89
5.30 ± 2.35∗∗
10.69 ± 6.97
418.28 ± 353.26∗
2.36 ± 0.73
13.02 ± 4.40
57.01 ± 25.07
1.67 ± 0.73
45636.11 ± 21788.68
With DRs
Baseline
26.47 ± 4.54
7.47 ± 4.64
10.44 ± 4.84
341.99 ± 389.93
2.29 ± 0.76
11.42 ± 1.86
63.89 ± 29.58
1.85 ± 0.89
64158.06 ± 49596.88
6 months
25.61 ± 4.14∗
5.61 ± 2.33
11.22 ± 7.40
440.85 ± 375.32
2.29 ± 0.73
13.55 ± 4.85
61.53 ± 20.63
1.80 ± 0.64
49730.97 ± 19476.60
Without DRs
Baseline
27.27 ± 5.50
6.52 ± 1.64
13.70 ± 8.03
232.73 ± 177.07
2.43 ± 0.62
11.87 ± 3.42
67.43 ± 33.06
2.05 ± 1.10
50767.08 ± 21370.14
6 months
26.91 ± 5.37
4.95 ± 2.52∗
9.74 ± 6.56∗
396.36 ± 324.47∗∗
2.36 ± 0.66
12.01 ± 4.12
61.60 ± 27.15
1.78 ± 0.78a
49970.42 ± 23582.92
All data are reported as the mean ± SD. 17 women had IR, and 49 did not. Women with IR showed a reduction of BMI, fasting insulin, and HOMA-IR and an increase in estradiol, while women without IR showed an increase in estradiol and a reduction of FSH. 26 women had DRs, and 45 did not. Women with DRs only showed a significant reduction of BMI, while women without DRs showed a significant reduction of FSH and LH and an increase of estradiol, with a tendency to a reduction of HOMA-IR.∗p<0.05 vs. baseline; ∗∗p<0.01 vs. baseline; ap=0.052. ALA: α-lipoic acid; AUC: area under the curve; BMI: body mass index; DRs: diabetic relatives; FSH: follicle-stimulating hormone; HOMA-IR: homeostasis model assessment of insulin resistance; IR: insulin resistance; LH: luteinizing hormone; MI: myo-inositol; PCOS: polycystic ovary syndrome; SD: standard deviation.Figure 1
Percentages of women who reported an improvement of menstrual regularity after the treatment. (a) Women with insulin resistance (IR) reported similar changes of menstrual cyclicity than those without IR. (b) Women with diabetic relatives (DRs) reported similar changes of menstrual cyclicity than those without DRs. (c) A higher percentage of women of group A (2000 mg of MI + 800 mg of ALA) reported an improvement of menstrual cyclicity than those of group B (1000 mg of MI + 800 mg of ALA).∗p<0.01 (group A vs. group B).
(a)
(b)
(c)DRs did not significantly influence the results. On the contrary, women without DRs showed a relevant improvement of reproductive parameters (FSH, LH, and E2), while BMI (p=0.06) and HOMA-IR (p=0.052) only showed a tendency to a reduction (Table 2). Both the groups of women reported similar results on menstrual regularity, with a reduction of cycle length in 73% of women without DRs and in 68.2% of women with DRs (p=NS) (Figure 1).Table3 summarizes the results obtained dividing the patients according to the different doses of MI that they received in combination with the same dose of ALA. Group A (800 mg ALA + 2000 mg MI per day) showed a significant change of BMI (p<0.01) and E2 and AUC-insulin (p<0.05) after 6 months of treatment, while group B (800 mg ALA + 1000 mg MI per day) showed a significant change of FSH (p<0.01) and LH and E2 (p<0.05) but no changes in the metabolic parameters. Cycle length was improved in 85.7% of patients in group A and in 50% of those in group B (p<0.01) (Figure 1).Table 3
Results of the treatment in two subgroups of women taking the same dose of ALA (800 mg) and two different doses of MI per day (group A 2000 mg; group B 1000 mg).
Group A
Group B
Baseline
6 months
Baseline
6 months
BMI (kg/m2)
27.10 ± 4.19
25.02 ± 4.03∗∗
26.79 ± 6.43
27.15 ± 6.12.62
FSH (mIU/mL)
5.73 ± 1.85
4.88 ± 1.45
7.11 ± 3.23
5.26 ± 2.62∗∗
LH (mIU/mL)
14.73 ± 8.42
13.42 ± 6.32
12.09 ± 6.95
9.59 ± 6.80∗
Estradiol (pmol/L)
255.16 ± 219.14
402.01 ± 339.38∗
277.04 ± 290.22
415.38 ± 345.11∗
Total testosterone (ng/mL)
2.88 ± 0.73
2.70 ± 0.80
2.18 ± 0.55
2.18 ± 0.59
Fasting insulin (pmol/L)
66.81 ± 30.00
71.04 ± 29.17
61.60 ± 24.86
55.63 ± 20.21
HOMA-IR
1.93 ± 0.91
2.00 ± 0.84
1.79 ± 0.73
1.66 ± 0.64
AUC-insulin (pmol/L × 120 min)
60833.82 ± 19899.02
51441.04 ± 22941.46∗
52009.79 ± 38484.58
49054.10 ± 22024.79
The higher dose of MI caused changes in BMI, estradiol levels, and AUC-insulin, while the lowest dose caused changes in FSH, LH, and estradiol levels. All data are reported as the mean ± SD.∗p<0.05 vs. baseline of the same group; ∗∗p<0.01 vs. baseline of the same group. ALA: α-lipoic acid; AUC: area under the curve; BMI: body mass index; FSH: follicle-stimulating hormone; HOMA-IR: homeostasis model assessment of insulin resistance; IR: insulin resistance; LH: luteinizing hormone; MI: myo-inositol; SD: standard deviation.
## 5. Discussion
This study shows the ability of a combination of ALA and MI to restore a normal menstrual cyclicity in women with PCOS, acting on hormonal or on metabolic parameters. The better results were obtained when ALA was associated with a higher dose of MI.We observed that the improvement of menstrual cyclicity occurs regardless of the state of IR and of the presence of DRs of the patients: every subgroup showed a similar percentage of women (between 68 and 80%) that reported a better condition after 6 months of treatment. Comparing women with and without IR, we found that menstrual cyclicity was restored in both groups, but IR women only also showed an improvement of metabolic parameters. On the contrary, hormonal parameters (FSH and E2) seem to be affected by the treatment only in women without IR.The results obtained in not-IR women are similar to those of De Cicco et al. They studied a group of obese PCOS women without IR treated with MI and ALA for six months, and they found an improvement of cycle length, BMI, hyperandrogenism, and ovarian volume without effects on HOMA-IR and AUC-insulin (both in a normal range at the baseline).A mandatory role in the improvement of menstrual cyclicity seems to be exerted by the presence of MI in the association. The hypothesis that the effects are mainly MI-mediated is supported by the fact that the only difference in the improvement of menstrual cyclicity was found comparing women who took 2000 mg of MI with those taking 1000 mg of MI: a higher dose of MI associated with the same dose of ALA demonstrated to be more effective in the regularization of the menstrual cycle than the administration of the ALA itself. Anyway, we found also that a low dose of MI can be sufficient to improve the menstrual cyclicity in 50% of women, so maybe this feature is very sensitive to the administration of inositol. Considering the results in women without IR, we can hypothesize that MI can act independently from the IR state. In fact, MI has been recognized to directly facilitate the activity of FSH, acting as a second messenger also for this hormone’s receptor [39, 40]. Consequently, in women without IR, MI may be able to act improving FSH response in granulosa cells, thus promoting the normal maturation of the follicle and contributing to normalizing E2 levels.The mechanism through which ALA may have a role in the normalization of the ovarian function is less clear. This is supported also by the results of other studies in the literature. Genazzani et al. in 2018 [41], and again in 2019 [37], demonstrated that ALA alone is not able to affect the reproductive features of PCOS women. In particular, it is difficult to explain which could be its exact role in the improvement of menstrual cyclicity in women without IR. The mechanism seems to be insulin-independent. However, it cannot be excluded that ALA, thanks to its biological activity, may participate in the restoration of the wellbeing of the ovary with an anti-inflammatory action. PCOS is associated with decreased antioxidant concentrations, and it can be considered an oxidative state [42]. WNT5a, a proinflammatory marker, is increased in granulosa cells of both lean and obese PCOS women, and it contributes to the chronic inflammation and to the production of ROS through the activation of the expression of NF-κB [43]. ALA can modulate the NF-κB expression [25]. It is possible that ALA could reduce inflammation and oxidative stress also in the ovary. We may speculate that ALA might contribute to the restoration of a normal environment in the ovary increasing the positive effect of MI.Women with IR experienced a completely different response to the same treatment. When IR was present, the treatment with ALA and MI reduced fasting insulin and HOMA-IR, restoring a normal insulin sensitivity in almost 80% of the women. This may be due to a synergistic effect displayed by the two insulin-sensitizing molecules: ALA increases the translocation of GLUT4 to the membrane in an insulin-independent way, while MI acts as a second messenger in the pathway of the insulin receptor. When IR is present, high insulin levels impair the normal secretion of LH and FSH from pituitary cells and their function in the ovaries, promoting premature luteinization of follicles [4, 44] Although their effects on gonadotropins and on inflammation, the ability of ALA and MI to restore normal levels of insulin in PCOS women with IR may be another mechanism and probably the condition conditio sine qua non, by which these molecules are able to improve menstrual regularity in women with IR.The clinical efficacy of ALA and MI was not influenced by the presence of DRs. Menstrual cyclicity was similarly improved in both groups, but only women without DRs showed positive results on the reproductive parameters. These results are in contrast with those obtained by other authors, who hypothesized that women with PCOS and DRs had a defect of the LASY similarly to overt diabetes [35, 41]. Therefore, more accurate studies should be performed to understand which alterations are present in PCOS women with DRs, in order to customize the treatment used. Our results suggest that the defect of the LASY is not the only alteration present in this group of women: other mechanisms should be involved, and ALA seems not to be sufficient to act against all of them.In conclusion, our study demonstrated that the association of ALA and MI can positively affect the menstrual regularity of women with PCOS, with a more evident effect with a higher dose of MI. The presence of IR seems to be a predictor of responsivity to the treatment in terms of an improvement of the metabolic profile, but not in terms of menstrual cyclicity. At present, no explanation seems to be exhaustive, and more studies should be needed to better investigate the mechanisms through which ALA and MI exert their action in women with and without IR.
---
*Source: 2901393-2020-03-19.xml* | 2020 |
# Beyond Fat Mass: Exploring the Role of Adipokines in Rheumatic Diseases
**Authors:** Morena Scotece; Javier Conde; Rodolfo Gómez; Veronica López; Francisca Lago; Juan Jesus Gómez-Reino; Oreste Gualillo
**Journal:** TheScientificWorldJOURNAL
(2011)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1100/2011/290142
**Keywords:** white adipose tissue (WAT); adipokines; cytokines; rheumatic diseases; immune response; immune tolerance; metabolism; energetic homeostasis
---
## Abstract
The cloning of leptin in 1994 by Zhang et al. introduced a novel concept about white adipose tissue (WAT) as a very dynamic organ that releases a plethora of immune and inflammatory mediators, such as adipokines and cytokines, which are involved in multiple diseases. Actually, adipokines exert potent modulatory actions on target tissues involved in rheumatic diseases including cartilage, synovial, bone and immune cells. The goal of this paper is to elucidate the recent findings concerning the involvement of adipokines in rheumatic diseases, such as rheumatoid arthritis (RA), osteoarthritis (OA), and systemic lupus erythematosus (SLE).
---
## Body
## 1. INTRODUCTION
In addition to the central role of lipid storage, white adipose tissue (WAT) is now recognized to be a multifactorial organ. It has a major endocrine function secreting several hormones, most notably leptin and adiponectin, together with a diverse range of other protein signals and factors. These adipose-derived peptides have been termed collectively “adipokines.” It is important to underline that these factors might be also synthesized in other tissues, rather than WAT, and participate in other relevant functions correlated with energy homeostasis and metabolism [1].Adipokines include a variety of proinflammatory peptides. These proinflammatory adipokines are increased in obesity and appear to contribute to the so-called “low-grade inflammatory state” of obese subjects creating a cluster of metabolic aberrations including cardiovascular complications and autoimmune inflammatory diseases.Initially restricted to metabolic activities, adipokines represent a new family of compounds that can be currently considered as key players of the complex network of soluble mediators involved in the pathophysiology of rheumatic diseases. For instance, obesity has long been considered as a risk factor for osteoarthritis (OA). It has been reported that obesity increases the incidence of OA, particularly in weight-bearing joints such as knees, and weight reduction is correlated with decreased progression of OA. A prevailing hypothesis is that obesity increases mechanical loading across the articular cartilage that leads to its degeneration. However, obesity is also associated with OA in non-weight-bearing joints such as finger joints and wrists, which suggest that these metabolic factors contribute to the high prevalence of OA in obese subjects [2].This paper addresses current data concerning the involvement of adipokines in the rheumatic diseases, focussing on the role of adipokines played in the pathophysiology of OA, rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE).
## 2. LEPTIN AND ADIPONECTIN: A TALE OF TWO GIANTS
### 2.1. Leptin: A Short Overview
Leptin is the protein product of theobgene, the murine homologue of the human gene LEP, cloned in 1994 [3]. White adipose tissue cells mainly produce this adipokine, and its plasma concentration is directly correlated with the body-fat stores. It has a central role in fat metabolism; in fact leptin is considered a major regulator of body weight by suppressing appetite and stimulating energy expenditure via hypothalamic receptors. This hormone decreases food intake by inducing anorexigenic factors as cocaine-amphetamine-related transcript (CART) and increases energy consumption by suppressing orexigenic neuropeptides such as neuropeptide Y (NPY). The biological activity of leptin is mediated by specific receptors (Ob-R), which belong to the class 1 cytokine receptor superfamily and are encoded by the gene diabetes (db). Alternative splicing of the db gene produces multiple isoforms, but only the long isoform Ob-Rb appears to be capable of transducing the leptin signal.Leptin is a hormone with pleiotropic actions. In fact, in addition to regulation of food intake, it also affects a variety of other physiological functions, including fertility, bone metabolism, inflammation, infection, and immune responses.In the last years, important advancements have been added to clarify the involvement of leptin in promoting autoimmune and rheumatic pathologies, particularly rheumatoid arthritis, osteoarthritis, and systemic lupus erythematosus (SLE).
### 2.2. Leptin and Osteoarthritis
It is increasingly evident that this hormone plays a key role in the OA pathophysiology. Leptin expression is much higher in osteoarthritic human cartilage than in normal cartilage, and there exists a strong correlation of synovial fluid leptin levels with body mass index (BMI) in people with severe osteoarthritis [4]. The first findings have suggested that high circulating leptin levels in obese individuals may protect cartilage from osteoarthritic degeneration. Actually, Dumond et al. have demonstrated that the intra-articular injection of leptin can strongly stimulate the synthesis of insulin-like growth factor-1 (IGF-1) and transforming growth factor-β (TGF-β) at both the messenger RNA (mRNA) and protein levels which can exert anabolic activities in cartilage metabolism [4].By contrast, leptin has been demonstrated to act as a proinflammatory agent in osteoarthritis. Otero et al. showed that, in cultured human and murine chondrocytes, type 2 nitric oxide synthase (NOS2) is activated by the combination of leptin plus IFNγ, and NOS2 activation by IL1 is increased by leptin via a mechanism involving JAK2, PI3K, MEK1, and p38 [5–7]. The costimulation of leptin plus IFNγ induces nitric oxide, a well-known proinflammatory mediator on joint cartilage, where it triggers chondrocyte phenotype loss, apoptosis, and metalloproteinases (MMPs) activation.Leptin, per se, is able to induce also the expression of MMPs involved in OA cartilage damage, such as MMP-9 and MMP-13 [8]. Recently, Koskinen et al. have suggested that leptin alone or in combination with IL-1β upregulates MMP-1 and MMP-3 production in human OA cartilage through the transcription factor NF-κB, protein kinase C, and MAP kinase pathways, and its levels correlate positively with MMP-1 and MMP-3 in synovial fluid (SF) from OA patients [9].Noteworthily, very recently, Gómez et al. have showed that in human chondrocytes leptin increased IL-8 production, which is one of the major mediators of the inflammatory response [10].Moreover, in articular cartilage of rats, gene expression of ADAMTS-4 and ADAMTS-5 (a disintegrin and metalloproteinase with thrombospondin motifs) was markedly increased after treatment with leptin inducing also a depletion of proteoglycans [11].Leptin could also contribute to abnormal osteoblast function in OA. Indeed, the elevated production of leptin in OA abnormal subchondral osteoblast is correlated with the increased levels of ALP (alkaline phosphatase), OC (osteocalcin), collagen type I, and TGF-β1, inducing a dysregulation of osteoblast function [12]. Very recently, Griffin et al. showed that the incidence of OA was not higher in ob/ob and db/db female obese mice than in control background strain (C57BL/6J) [13]. Nevertheless, in this study, no standard was set for the incidence of OA in obese control mice (without leptin mutation) [12].This recent finding suggests that obesity, as dysregulated body fat accumulation, per se, is not a risk factor for joint degeneration since adiposity in the absence of leptin signaling is insufficient to induce systemic inflammation and knee osteoarthritis in female mice.
### 2.3. Leptin and Rheumatoid Arthritis
Together with other neuroendocrine signals, leptin seems to play a role in autoimmune diseases such as RA, but whether leptin can harm or protect joint structures in RA is still unclear. In patients with RA, circulating leptin levels have been described as either higher or unmodified in comparison to healthy controls [8, 14]. In RA patients, a fasting-induced fall in circulating leptin is associated with CD4+ lymphocyte hyporeactivity and increased IL-4 secretion [15]. Experimental antigen-induced arthritis is less severe in leptin-deficient ob/ob mice than in wild-type mice, whereas leptin-deficient mice and leptin-receptor-deficient mice exhibited a delayed resolution of the inflammatory process in zymosan-induced experimental arthritis. Notably, leptin decreased the severity of septic arthritis in wild type mice. So, in the light of the present results it seems difficult to make an unambiguous conclusion about a potential role of leptin in RA [16]. Several authors have also demonstrated that there may exist a close dependence between the risk of aggressive course of RA and leptin levels [17, 18]. In addition, a correlation between serum leptin and synovial fluid/serum leptin ratio and disease duration and parameters of RA activity has been reported [19].The action of leptin in RA is not only targeted to articular tissue, but this adipokine also exerts direct modulatory effects on activation, proliferation, maturation, and production of inflammatory mediators in a variety of immune cells, including lymphocytes, natural killer cells, monocytes/macrophages, dentritic cells, neutrophils, and eosinophils [20].In particular, it is known that leptin is able to modulate T regulatory cells that are potent suppressors of autoimmunity. The group of Matarese has recently demonstrated that leptin secreted by adipocytes sustains Th1 immunity by promoting effector T cell proliferation and by constraining TReg cells expansion. Weight loss, with concomitant reduction in leptin levels, induces a reduction in effector T cells proliferation and an increased expansion of TReg cells leading to a downregulation of Th1 immunity and cell-mediated autoimmune diseases associated with increased susceptibility to infections. On the contrary, an increase in adipocyte mass leads to high leptin secretion, which results in expansion of effector T cells and reduction of TReg cells. This fact determines an overall enhancement of the proinflammatory immunity and of T-cell-mediated autoimmune disorders. Though, leptin can be considered as a link among immune tolerance, metabolic function, and autoimmunity and future strategies aimed at interfering with leptin signaling may represent innovative therapeutic tools for autoimmune disorders.Very recently it has been demonstrated that leptin can activate mammalian target of rapamycin (mTOR) and regulate the proliferative capacity of regulatory T (TReg) cells. This study suggests that the leptin-mTOR signalling pathway is an important link between host energy status and TReg cell activity. Authors conclude that oscillating mTOR activity is necessary for TReg cell activation and suggest that this might explain why TReg cells are unresponsive to TCR stimulation in vitro when high levels of leptin and nutrients may sustain mTOR activation [21, 22]. To note, both direct and indirect effects of leptin on the immune system have been described to account for the immune defects observed in leptin- and leptin-receptor-deficient rodents. Actually, Palmer et al. have also showed an indirect effect of leptin on the immune system, demonstrating that leptin receptor deficiency affects the immune system indirectly via changes in the systemic environment [23].
### 2.4. Leptin and Systemic Lupus Erythematosus (SLE)
Leptin has been suggested to have a role also in other rheumatic diseases such as systemic lupus erythematosus (SLE), in particular modulating the cardiovascular risk of SLE patients. Recently, the group of La Cava demonstrated that leptin and high-fat diet are able to induce proinflammatory high-density lipoproteins and atherosclerosis in BWF1 lupus-prone mice. These data suggest that environmental factors associated with obesity and metabolic syndrome can accelerate atherosclerosis and disease in a lupus-prone background [24].A relationship between leptin and lupus-disease-related factors is also found. In fact, patients with SLE have increased concentrations of leptin and these concentrations are associated with insulin resistance, BMI (body mass index), and CRP (C-reactive protein) in these patients [25].
## 2.1. Leptin: A Short Overview
Leptin is the protein product of theobgene, the murine homologue of the human gene LEP, cloned in 1994 [3]. White adipose tissue cells mainly produce this adipokine, and its plasma concentration is directly correlated with the body-fat stores. It has a central role in fat metabolism; in fact leptin is considered a major regulator of body weight by suppressing appetite and stimulating energy expenditure via hypothalamic receptors. This hormone decreases food intake by inducing anorexigenic factors as cocaine-amphetamine-related transcript (CART) and increases energy consumption by suppressing orexigenic neuropeptides such as neuropeptide Y (NPY). The biological activity of leptin is mediated by specific receptors (Ob-R), which belong to the class 1 cytokine receptor superfamily and are encoded by the gene diabetes (db). Alternative splicing of the db gene produces multiple isoforms, but only the long isoform Ob-Rb appears to be capable of transducing the leptin signal.Leptin is a hormone with pleiotropic actions. In fact, in addition to regulation of food intake, it also affects a variety of other physiological functions, including fertility, bone metabolism, inflammation, infection, and immune responses.In the last years, important advancements have been added to clarify the involvement of leptin in promoting autoimmune and rheumatic pathologies, particularly rheumatoid arthritis, osteoarthritis, and systemic lupus erythematosus (SLE).
## 2.2. Leptin and Osteoarthritis
It is increasingly evident that this hormone plays a key role in the OA pathophysiology. Leptin expression is much higher in osteoarthritic human cartilage than in normal cartilage, and there exists a strong correlation of synovial fluid leptin levels with body mass index (BMI) in people with severe osteoarthritis [4]. The first findings have suggested that high circulating leptin levels in obese individuals may protect cartilage from osteoarthritic degeneration. Actually, Dumond et al. have demonstrated that the intra-articular injection of leptin can strongly stimulate the synthesis of insulin-like growth factor-1 (IGF-1) and transforming growth factor-β (TGF-β) at both the messenger RNA (mRNA) and protein levels which can exert anabolic activities in cartilage metabolism [4].By contrast, leptin has been demonstrated to act as a proinflammatory agent in osteoarthritis. Otero et al. showed that, in cultured human and murine chondrocytes, type 2 nitric oxide synthase (NOS2) is activated by the combination of leptin plus IFNγ, and NOS2 activation by IL1 is increased by leptin via a mechanism involving JAK2, PI3K, MEK1, and p38 [5–7]. The costimulation of leptin plus IFNγ induces nitric oxide, a well-known proinflammatory mediator on joint cartilage, where it triggers chondrocyte phenotype loss, apoptosis, and metalloproteinases (MMPs) activation.Leptin, per se, is able to induce also the expression of MMPs involved in OA cartilage damage, such as MMP-9 and MMP-13 [8]. Recently, Koskinen et al. have suggested that leptin alone or in combination with IL-1β upregulates MMP-1 and MMP-3 production in human OA cartilage through the transcription factor NF-κB, protein kinase C, and MAP kinase pathways, and its levels correlate positively with MMP-1 and MMP-3 in synovial fluid (SF) from OA patients [9].Noteworthily, very recently, Gómez et al. have showed that in human chondrocytes leptin increased IL-8 production, which is one of the major mediators of the inflammatory response [10].Moreover, in articular cartilage of rats, gene expression of ADAMTS-4 and ADAMTS-5 (a disintegrin and metalloproteinase with thrombospondin motifs) was markedly increased after treatment with leptin inducing also a depletion of proteoglycans [11].Leptin could also contribute to abnormal osteoblast function in OA. Indeed, the elevated production of leptin in OA abnormal subchondral osteoblast is correlated with the increased levels of ALP (alkaline phosphatase), OC (osteocalcin), collagen type I, and TGF-β1, inducing a dysregulation of osteoblast function [12]. Very recently, Griffin et al. showed that the incidence of OA was not higher in ob/ob and db/db female obese mice than in control background strain (C57BL/6J) [13]. Nevertheless, in this study, no standard was set for the incidence of OA in obese control mice (without leptin mutation) [12].This recent finding suggests that obesity, as dysregulated body fat accumulation, per se, is not a risk factor for joint degeneration since adiposity in the absence of leptin signaling is insufficient to induce systemic inflammation and knee osteoarthritis in female mice.
## 2.3. Leptin and Rheumatoid Arthritis
Together with other neuroendocrine signals, leptin seems to play a role in autoimmune diseases such as RA, but whether leptin can harm or protect joint structures in RA is still unclear. In patients with RA, circulating leptin levels have been described as either higher or unmodified in comparison to healthy controls [8, 14]. In RA patients, a fasting-induced fall in circulating leptin is associated with CD4+ lymphocyte hyporeactivity and increased IL-4 secretion [15]. Experimental antigen-induced arthritis is less severe in leptin-deficient ob/ob mice than in wild-type mice, whereas leptin-deficient mice and leptin-receptor-deficient mice exhibited a delayed resolution of the inflammatory process in zymosan-induced experimental arthritis. Notably, leptin decreased the severity of septic arthritis in wild type mice. So, in the light of the present results it seems difficult to make an unambiguous conclusion about a potential role of leptin in RA [16]. Several authors have also demonstrated that there may exist a close dependence between the risk of aggressive course of RA and leptin levels [17, 18]. In addition, a correlation between serum leptin and synovial fluid/serum leptin ratio and disease duration and parameters of RA activity has been reported [19].The action of leptin in RA is not only targeted to articular tissue, but this adipokine also exerts direct modulatory effects on activation, proliferation, maturation, and production of inflammatory mediators in a variety of immune cells, including lymphocytes, natural killer cells, monocytes/macrophages, dentritic cells, neutrophils, and eosinophils [20].In particular, it is known that leptin is able to modulate T regulatory cells that are potent suppressors of autoimmunity. The group of Matarese has recently demonstrated that leptin secreted by adipocytes sustains Th1 immunity by promoting effector T cell proliferation and by constraining TReg cells expansion. Weight loss, with concomitant reduction in leptin levels, induces a reduction in effector T cells proliferation and an increased expansion of TReg cells leading to a downregulation of Th1 immunity and cell-mediated autoimmune diseases associated with increased susceptibility to infections. On the contrary, an increase in adipocyte mass leads to high leptin secretion, which results in expansion of effector T cells and reduction of TReg cells. This fact determines an overall enhancement of the proinflammatory immunity and of T-cell-mediated autoimmune disorders. Though, leptin can be considered as a link among immune tolerance, metabolic function, and autoimmunity and future strategies aimed at interfering with leptin signaling may represent innovative therapeutic tools for autoimmune disorders.Very recently it has been demonstrated that leptin can activate mammalian target of rapamycin (mTOR) and regulate the proliferative capacity of regulatory T (TReg) cells. This study suggests that the leptin-mTOR signalling pathway is an important link between host energy status and TReg cell activity. Authors conclude that oscillating mTOR activity is necessary for TReg cell activation and suggest that this might explain why TReg cells are unresponsive to TCR stimulation in vitro when high levels of leptin and nutrients may sustain mTOR activation [21, 22]. To note, both direct and indirect effects of leptin on the immune system have been described to account for the immune defects observed in leptin- and leptin-receptor-deficient rodents. Actually, Palmer et al. have also showed an indirect effect of leptin on the immune system, demonstrating that leptin receptor deficiency affects the immune system indirectly via changes in the systemic environment [23].
## 2.4. Leptin and Systemic Lupus Erythematosus (SLE)
Leptin has been suggested to have a role also in other rheumatic diseases such as systemic lupus erythematosus (SLE), in particular modulating the cardiovascular risk of SLE patients. Recently, the group of La Cava demonstrated that leptin and high-fat diet are able to induce proinflammatory high-density lipoproteins and atherosclerosis in BWF1 lupus-prone mice. These data suggest that environmental factors associated with obesity and metabolic syndrome can accelerate atherosclerosis and disease in a lupus-prone background [24].A relationship between leptin and lupus-disease-related factors is also found. In fact, patients with SLE have increased concentrations of leptin and these concentrations are associated with insulin resistance, BMI (body mass index), and CRP (C-reactive protein) in these patients [25].
## 3. ADIPONECTIN
### 3.1. Adiponectin: A Short Overview
Adiponectin, also known as GBP28, apM1, Acrp30, or AdipoQ, is a 244-residue protein that is produced mainly by WAT. Adiponectin has structural homology with collagens VIII and X and complement factor C1q, and it circulates in the blood in relatively large amounts in different molecular forms (trimers, hexamers, and also 12-18-mer forms) [26, 27]. It increases fatty acid oxidation and reduces the synthesis of glucose in the liver. Ablation of the adiponectin gene has no dramatic effect in knockout mice on a normal diet, but when placed on a high-fat/sucrose diet they develop severe insulin resistance and exhibit lipid accumulation in muscles [28]. Circulating adiponectin levels tend to be low in morbidly obese patients and increase with weight loss and with the use of thiazolidinediones, which enhance sensitivity to insulin [26, 29].Adiponectin acts via two receptors, one (AdipoR1) found predominantly in skeletal muscle and the other (AdipoR2) in liver. Transduction of the adiponectin signal by AdipoR1 and AdipoR2 involves the activation of AMPK, PPAR-α, PPAR-γ, and other signalling molecules [26]. To note, targeted disruption of AdipoR1 and AdipoR2 causes abrogation of adiponectin binding and all its metabolic actions [30].Actually, some evidences, indicates that adiponectin has a wide range of effects in pathologies with inflammatory component, such as cardiovascular disease, endothelial dysfunction, type 2 diabetes, metabolic syndrome, OA, and RA [31]. Adiponectin acts as a potent modulator of both B and T cells; moreover, it modulates the activity of immune innate response by inducing relevant anti-inflammatory factors such as IL-1 receptor antagonist and IL-10 [26].
### 3.2. Adiponectin and RA
The potential role of adiponectin in rheumatic diseases has been actively investigated. In general, low adiponectin levels have been associated with obesity, type 2 diabetes, atherosclerosis, and vessel inflammation, and in metabolic syndrome the role of adiponectin is clearly anti-inflammatory. On the other side, multiple studies described high adiponectin levels in patients with RA, and these levels correlate with severity of RA [14, 32]. Giles et al. identified a robust cross-sectional association between serum adiponectin levels and radiographic damage in patients with RA [33], suggesting that this adipokines may be a mediator of the paradoxical relationship between increasing adiposity and protection from radiographic damage in RA, due to adiponectin circulating levels decrease as adiposity increase. Indeed, considering that adiponectin may have negative effects on joint, this adipokine could be a relevant mediator to the inverse relationship between increasing adiposity and radiographic damage observed in RA studies.In contrast to its “protective” role against obesity and vascular diseases, at joint levels adiponectin might be proinflammatory and involved in matrix degradation. In synovial fibroblasts, adiponectin induces IL-6 production and metalloproteinase-1, two of the main mediators of RA via the p38 MAPK pathway [34]. Similarly, IL-8 is induced by adiponectin through an intracellular pathway involving NF-κB [10, 35].Recent studies showed that adiponectin might also contribute to synovitis and joint destruction in RA by stimulating matrix metalloproteinase-1, matrix metalloproteinase-13, and vascular endothelial growth factor expression in synovial cells, surprisingly, more than conventional proinflammatory mediators (i.e, IL-1 beta) [36]. In addition adiponectin increases both cyclooxygenase-2 (COX-2) and membrane-associated PGE synthase-1 (mPGES-1) mRNA and protein expression, in RA synovial fibroblasts (RASFs) in a time- and concentration-dependent manner [37]. This increase was inhibited by siRNA against adiponectin receptor (AdipoR1 and AdipoR2) or using inhibitors of specific proteins involved in adiponectin signal transduction [37].Recently, Frommer et al. have confirmed the proinflammatory role of adiponectin in RA by demonstrating that this adipokine promotes inflammation through cytokine synthesis, attraction of inflammatory cells to the synovium, and recruitment of prodestructive cells via chemokines, thus promoting matrix destruction at sites of cartilage invasion [38].
### 3.3. Adiponectin and OA
It is possible that adiponectin is also implicated in OA pathogenesis. Adiponectin has emerged as a regulator of immune responses and inflammatory arthritis. However, its role in OA and cartilage degradation is controversial and, under many aspects, poorly known. Nevertheless, in chondrocytes this adipokine induces proinflammatory mediators such as nitric oxide, IL-6, MCP-1, MMP-3 and MMP-9 as well as IL-8 [10, 39, 40].Recent studies show a potential source of adipokines at articular level: the infrapatellar fat pad (IFP). Actually, recent evidence indicates an inflammatory phenotype of this adipose compartment in patients with OA showing that IFP could contribute to the pathophysiological changes in the OA joint via the local production of cytokines and adipokines [41–43]. In addition, the implication of adiponectin in OA pathogenesis is supported also by clinical observations. Lauberg et al. have reported that plasma adiponectin levels were significantly higher in OA patients than in healthy controls [44], and they also observed higher plasma adiponectin levels in female patients with erosive hand OA than those with nonerosive OA [45].It is noteworthy that adiponectin-leptin ratio has been proposed as predictor of pain in OA patients [46]; in fact this adipokine has been detected in the OA synovial fluids correlating with osteoarthritis severity [47] and aggrecan degradation [48].
### 3.4. Adiponectin and SLE
The role of adiponectin in the SLE pathophysiology is not clear. High levels of adiponectin have been found in patients with systemic lupus erythematosus (SLE) in comparison with healthy controls [49]; intriguingly, among the SLE patients, patients with insulin resistance (IR) showed significantly lower adiponectin levels than patients without IR [50].Rovin et al. have reported that plasma adiponectin levels are increased in patients with renal SLE compared to healthy controls and patients with nonrenal SLE. During renal but not nonrenal SLE flare, urine adiponectin levels increase significantly. For this reason, urine adiponectin may be a biomarker of renal SLE flare [51]. Intriguingly, the group of Aprahamian has suggested that PPAR-gamma agonists may be useful agents for the treatment of SLE and also demonstrated that induction of adiponectin is the major mechanism underlying the immunomodulatory effects of PPAR-gamma agonists [52]. However, these authors obtained their data by using a murine model of lupus so that the reality regarding the potential therapeutic effect of PPAR gamma agonists in human SLE may be completely different.In addition, the study of Vadacca et al. reported no difference of adiponectin levels in SLE patients in comparison to healthy subjects [53].In addition, very recently, McMahon and colleagues have demonstrated that leptin levels confer increased risk of atherosclerosis in women with systemic lupus erythematosus and that there is no significant association between adiponectin and atherosclerotic plaques in SLE [24].
## 3.1. Adiponectin: A Short Overview
Adiponectin, also known as GBP28, apM1, Acrp30, or AdipoQ, is a 244-residue protein that is produced mainly by WAT. Adiponectin has structural homology with collagens VIII and X and complement factor C1q, and it circulates in the blood in relatively large amounts in different molecular forms (trimers, hexamers, and also 12-18-mer forms) [26, 27]. It increases fatty acid oxidation and reduces the synthesis of glucose in the liver. Ablation of the adiponectin gene has no dramatic effect in knockout mice on a normal diet, but when placed on a high-fat/sucrose diet they develop severe insulin resistance and exhibit lipid accumulation in muscles [28]. Circulating adiponectin levels tend to be low in morbidly obese patients and increase with weight loss and with the use of thiazolidinediones, which enhance sensitivity to insulin [26, 29].Adiponectin acts via two receptors, one (AdipoR1) found predominantly in skeletal muscle and the other (AdipoR2) in liver. Transduction of the adiponectin signal by AdipoR1 and AdipoR2 involves the activation of AMPK, PPAR-α, PPAR-γ, and other signalling molecules [26]. To note, targeted disruption of AdipoR1 and AdipoR2 causes abrogation of adiponectin binding and all its metabolic actions [30].Actually, some evidences, indicates that adiponectin has a wide range of effects in pathologies with inflammatory component, such as cardiovascular disease, endothelial dysfunction, type 2 diabetes, metabolic syndrome, OA, and RA [31]. Adiponectin acts as a potent modulator of both B and T cells; moreover, it modulates the activity of immune innate response by inducing relevant anti-inflammatory factors such as IL-1 receptor antagonist and IL-10 [26].
## 3.2. Adiponectin and RA
The potential role of adiponectin in rheumatic diseases has been actively investigated. In general, low adiponectin levels have been associated with obesity, type 2 diabetes, atherosclerosis, and vessel inflammation, and in metabolic syndrome the role of adiponectin is clearly anti-inflammatory. On the other side, multiple studies described high adiponectin levels in patients with RA, and these levels correlate with severity of RA [14, 32]. Giles et al. identified a robust cross-sectional association between serum adiponectin levels and radiographic damage in patients with RA [33], suggesting that this adipokines may be a mediator of the paradoxical relationship between increasing adiposity and protection from radiographic damage in RA, due to adiponectin circulating levels decrease as adiposity increase. Indeed, considering that adiponectin may have negative effects on joint, this adipokine could be a relevant mediator to the inverse relationship between increasing adiposity and radiographic damage observed in RA studies.In contrast to its “protective” role against obesity and vascular diseases, at joint levels adiponectin might be proinflammatory and involved in matrix degradation. In synovial fibroblasts, adiponectin induces IL-6 production and metalloproteinase-1, two of the main mediators of RA via the p38 MAPK pathway [34]. Similarly, IL-8 is induced by adiponectin through an intracellular pathway involving NF-κB [10, 35].Recent studies showed that adiponectin might also contribute to synovitis and joint destruction in RA by stimulating matrix metalloproteinase-1, matrix metalloproteinase-13, and vascular endothelial growth factor expression in synovial cells, surprisingly, more than conventional proinflammatory mediators (i.e, IL-1 beta) [36]. In addition adiponectin increases both cyclooxygenase-2 (COX-2) and membrane-associated PGE synthase-1 (mPGES-1) mRNA and protein expression, in RA synovial fibroblasts (RASFs) in a time- and concentration-dependent manner [37]. This increase was inhibited by siRNA against adiponectin receptor (AdipoR1 and AdipoR2) or using inhibitors of specific proteins involved in adiponectin signal transduction [37].Recently, Frommer et al. have confirmed the proinflammatory role of adiponectin in RA by demonstrating that this adipokine promotes inflammation through cytokine synthesis, attraction of inflammatory cells to the synovium, and recruitment of prodestructive cells via chemokines, thus promoting matrix destruction at sites of cartilage invasion [38].
## 3.3. Adiponectin and OA
It is possible that adiponectin is also implicated in OA pathogenesis. Adiponectin has emerged as a regulator of immune responses and inflammatory arthritis. However, its role in OA and cartilage degradation is controversial and, under many aspects, poorly known. Nevertheless, in chondrocytes this adipokine induces proinflammatory mediators such as nitric oxide, IL-6, MCP-1, MMP-3 and MMP-9 as well as IL-8 [10, 39, 40].Recent studies show a potential source of adipokines at articular level: the infrapatellar fat pad (IFP). Actually, recent evidence indicates an inflammatory phenotype of this adipose compartment in patients with OA showing that IFP could contribute to the pathophysiological changes in the OA joint via the local production of cytokines and adipokines [41–43]. In addition, the implication of adiponectin in OA pathogenesis is supported also by clinical observations. Lauberg et al. have reported that plasma adiponectin levels were significantly higher in OA patients than in healthy controls [44], and they also observed higher plasma adiponectin levels in female patients with erosive hand OA than those with nonerosive OA [45].It is noteworthy that adiponectin-leptin ratio has been proposed as predictor of pain in OA patients [46]; in fact this adipokine has been detected in the OA synovial fluids correlating with osteoarthritis severity [47] and aggrecan degradation [48].
## 3.4. Adiponectin and SLE
The role of adiponectin in the SLE pathophysiology is not clear. High levels of adiponectin have been found in patients with systemic lupus erythematosus (SLE) in comparison with healthy controls [49]; intriguingly, among the SLE patients, patients with insulin resistance (IR) showed significantly lower adiponectin levels than patients without IR [50].Rovin et al. have reported that plasma adiponectin levels are increased in patients with renal SLE compared to healthy controls and patients with nonrenal SLE. During renal but not nonrenal SLE flare, urine adiponectin levels increase significantly. For this reason, urine adiponectin may be a biomarker of renal SLE flare [51]. Intriguingly, the group of Aprahamian has suggested that PPAR-gamma agonists may be useful agents for the treatment of SLE and also demonstrated that induction of adiponectin is the major mechanism underlying the immunomodulatory effects of PPAR-gamma agonists [52]. However, these authors obtained their data by using a murine model of lupus so that the reality regarding the potential therapeutic effect of PPAR gamma agonists in human SLE may be completely different.In addition, the study of Vadacca et al. reported no difference of adiponectin levels in SLE patients in comparison to healthy subjects [53].In addition, very recently, McMahon and colleagues have demonstrated that leptin levels confer increased risk of atherosclerosis in women with systemic lupus erythematosus and that there is no significant association between adiponectin and atherosclerotic plaques in SLE [24].
## 4. RESISTIN
### 4.1. Resistin: A Short Overview
Resistin, known as adipocyte-secreted factor (ADSF) or found in inflammatory zone 3 (FIZZ3), was discovered in 2001 and was proposed as potential link between obesity and diabetes [54]. It was secreted by adipose tissue but has been found also in macrophages, neutrophils, and other cell types. Serum resistin levels increase with obesity in mice, rats, and humans [55, 56]. Increasing evidence indicates its important regulatory role in various biological processes, including several inflammatory diseases.
### 4.2. Resistin and RA
There are demonstrations that resistin may be involved in the pathogenesis of RA. Increased levels of this adipokine in synovial fluid from patients of rheumatoid arthritis (RA) compared to patients with noninflammatory rheumatic disorders have previously been observed [57].Actually, resistin has been found in the plasma and synovial fluid of RA patients, and injection of this adipokine into mice joints induce an arthritis-like condition, with leukocyte infiltration of synovial tissues, hypertrophy of the synovial layer, and pannus formation [58, 59]. Bokarewa et al. have showed also that resistin induces and is induced by several proinflammatory cytokines, such as TNF-α or IL-6, in peripheral blood mononuclear cells, via NF-κB pathway, indicating that resistin can increase its own activity by a positive feedback mechanism [58] Increased serum resistin in patients with rheumatoid arthritis correlated with both C-reactive protein (CRP) and DAS28, suggesting a role of this adipokine in the pathogenesis of rheumatoid arthritis [59]. Gonzalez-Gay et al. have confirmed this association between laboratory markers of inflammation, particularly CRP and resistin levels and have showed that anti-TNF-alpha therapy results in a rapid reduction of serum resistin levels in patients with RA [60].There is also an association between resistin and increased inflammation, joint destruction and levels of interleukin 1 receptor antagonist (IL-1RA) in rheumatoid arthritis female patients [61].
### 4.3. Resistin and OA
The proinflammatory profile of resistin, together with its association with obesity suggest that this adipokine might be another potential mediator that links OA with inflammation and obesity. It was demonstrated that this adipokine is elevated in both serum and SF after traumatic joint injuries. Recombinant resistin stimulated proteoglycan degradation in mouse femoral head cultures and the induction of inflammatory cytokines and PGE2 production. Moreover, it inhibited proteoglycan synthesis in human cartilage explants [62]. However, Berry et al. have not identified any association between baseline serum levels of resistin and cartilage volume loss [63].Recently, Zhang and colleagues demonstrated that resistin has diverse effects on gene expression in human chondrocytes, affecting chemokines, cytokines, and matrix gene expression. Messenger RNA stabilization and transcriptional upregulation are also involved in resistin-induced gene expression in human chondrocytes [64].
### 4.4. Resistin and SLE
In addition, resistin has a role as a marker of inflammation in other rheumatic diseases, such as systemic lupus erythematous (SLE). In fact, Almehed et al. have demonstrated a positive correlation between serum resistin levels, inflammation, bone mineral density, and renal functions in patients with SLE [65].
## 4.1. Resistin: A Short Overview
Resistin, known as adipocyte-secreted factor (ADSF) or found in inflammatory zone 3 (FIZZ3), was discovered in 2001 and was proposed as potential link between obesity and diabetes [54]. It was secreted by adipose tissue but has been found also in macrophages, neutrophils, and other cell types. Serum resistin levels increase with obesity in mice, rats, and humans [55, 56]. Increasing evidence indicates its important regulatory role in various biological processes, including several inflammatory diseases.
## 4.2. Resistin and RA
There are demonstrations that resistin may be involved in the pathogenesis of RA. Increased levels of this adipokine in synovial fluid from patients of rheumatoid arthritis (RA) compared to patients with noninflammatory rheumatic disorders have previously been observed [57].Actually, resistin has been found in the plasma and synovial fluid of RA patients, and injection of this adipokine into mice joints induce an arthritis-like condition, with leukocyte infiltration of synovial tissues, hypertrophy of the synovial layer, and pannus formation [58, 59]. Bokarewa et al. have showed also that resistin induces and is induced by several proinflammatory cytokines, such as TNF-α or IL-6, in peripheral blood mononuclear cells, via NF-κB pathway, indicating that resistin can increase its own activity by a positive feedback mechanism [58] Increased serum resistin in patients with rheumatoid arthritis correlated with both C-reactive protein (CRP) and DAS28, suggesting a role of this adipokine in the pathogenesis of rheumatoid arthritis [59]. Gonzalez-Gay et al. have confirmed this association between laboratory markers of inflammation, particularly CRP and resistin levels and have showed that anti-TNF-alpha therapy results in a rapid reduction of serum resistin levels in patients with RA [60].There is also an association between resistin and increased inflammation, joint destruction and levels of interleukin 1 receptor antagonist (IL-1RA) in rheumatoid arthritis female patients [61].
## 4.3. Resistin and OA
The proinflammatory profile of resistin, together with its association with obesity suggest that this adipokine might be another potential mediator that links OA with inflammation and obesity. It was demonstrated that this adipokine is elevated in both serum and SF after traumatic joint injuries. Recombinant resistin stimulated proteoglycan degradation in mouse femoral head cultures and the induction of inflammatory cytokines and PGE2 production. Moreover, it inhibited proteoglycan synthesis in human cartilage explants [62]. However, Berry et al. have not identified any association between baseline serum levels of resistin and cartilage volume loss [63].Recently, Zhang and colleagues demonstrated that resistin has diverse effects on gene expression in human chondrocytes, affecting chemokines, cytokines, and matrix gene expression. Messenger RNA stabilization and transcriptional upregulation are also involved in resistin-induced gene expression in human chondrocytes [64].
## 4.4. Resistin and SLE
In addition, resistin has a role as a marker of inflammation in other rheumatic diseases, such as systemic lupus erythematous (SLE). In fact, Almehed et al. have demonstrated a positive correlation between serum resistin levels, inflammation, bone mineral density, and renal functions in patients with SLE [65].
## 5. VISFATIN
### 5.1. Visfatin: A Short Overview
Visfatin, also named pre-B-cell colony-enhancing factor (PBEF) and nicotinamide phosphoribosyltransferase (Nampt), was originally discovered in liver, skeletal muscle, and bone marrow as a growth factor for B-lymphocyte precursors; however, it is also secreted by visceral fat [66, 67]. It is supposed that visfatin had insulin mimetic properties, but the role of this adipokine in the modulation of glucose metabolism, as well as its binding to insulin receptors, is still amatter of debate [67, 68].It has been reported that visfatin is increased in obesity. Moreover, leucocytes from obese patients produce higher amounts of visfatin compared with lean subjects, and, specifically, granulocytes and monocytes are the major visfatin-producing cells [69, 70]. However, leucocytes are not the only nonfat cell type that synthesizes visfatin. Actually, macrophages have been described as a source for visfatin production [71], and, interestingly, this adipokine promoted macrophage survival by reducing apoptosis [72].
### 5.2. Visfatin and RA
Visfatin may be considered another potential therapeutic target for RA with important proinflammatory and catabolic roles in RA pathogenesis. Our group demonstrated that circulating visfatin is higher in patients with RA than in healthy controls [14]. These data were also further confirmed by other authors [73]. To note, enhanced visfatin levels are associated with augmented joint damage [73]. Brentano and colleagues reported that visfatin was localized in the site of invasion of synovial tissue in joints of RA patients. Moreover, it is able to induce IL-6, MMP-1, and MMP-3 in RA synovial fibroblasts, as well as IL-6 and TNF-α in monocytes [74]. To note, PBEF knockdown in RASFs significantly inhibited basal and TLR ligand-induced production of IL-6, IL-8, MMP-1, and MMP-3 [74].Very recently, Busso et al. have showed that visfatin is a key mediator in inflammatory arthritis.The administration of a visfatin inhibitor to mice with collagen-induced arthritis reduced arthritis severity with similar effect to that produced by TNF-α inhibitor [75]. Moreover, pharmacological inhibition of visfatin led to reduced levels of intracellular NAD in inflammatory cells and decreased the production of TNF-α and IL-6 in affected joints [75]. However, the mechanisms by which visfatin exerts its catabolic effect in arthritic joints are still incompletely understood.
### 5.3. Visfatin and OA
At cartilage level, OA chondrocytes are able to produce visfatin and its expression is increased after IL-1β treatment [76]. Visfatin administration, like IL-1β, enhances PGE2 release. In line with this, visfatin also increases MMP-3 and MMP-13 synthesis and release and ADAMTS-4 and ADAMTS-5 expression in mouse articular chondrocytes [76]. Probably due to this augment in the expression of matrix degradative enzymes, visfatin decreases aggrecan expression [76].In addition, we showed that serum visfatin concentrations were higher in patients with OA compared to healthy controls [11]. Very recently, Duan et al. have reported that SF visfatin was positively correlated with degradation biomarker of collagen II, helix-II, and C-telopeptide of type II collagen (CTX-II) and degradation biomarker of aggrecan, aggrecanase-1 (AGG1), and aggrecanase-2 (AGG2), suggesting an involvement of adiponectin in cartilage matrix degradation [77].Taken together, these data suggest that visfatin has a catabolic function in cartilage and may have an important role in the pathophysiology of osteoarthritis.
### 5.4. Visfatin and SLE
Recent findings report also an implication of visfatin in SLE pathophysiology. It was showed that, in SLE patients, visfatin levels were higher compared to healthy controls [49, 73]. However, further studies are needed for more precise elucidation of the role that this adipokine plays in the SLE.
## 5.1. Visfatin: A Short Overview
Visfatin, also named pre-B-cell colony-enhancing factor (PBEF) and nicotinamide phosphoribosyltransferase (Nampt), was originally discovered in liver, skeletal muscle, and bone marrow as a growth factor for B-lymphocyte precursors; however, it is also secreted by visceral fat [66, 67]. It is supposed that visfatin had insulin mimetic properties, but the role of this adipokine in the modulation of glucose metabolism, as well as its binding to insulin receptors, is still amatter of debate [67, 68].It has been reported that visfatin is increased in obesity. Moreover, leucocytes from obese patients produce higher amounts of visfatin compared with lean subjects, and, specifically, granulocytes and monocytes are the major visfatin-producing cells [69, 70]. However, leucocytes are not the only nonfat cell type that synthesizes visfatin. Actually, macrophages have been described as a source for visfatin production [71], and, interestingly, this adipokine promoted macrophage survival by reducing apoptosis [72].
## 5.2. Visfatin and RA
Visfatin may be considered another potential therapeutic target for RA with important proinflammatory and catabolic roles in RA pathogenesis. Our group demonstrated that circulating visfatin is higher in patients with RA than in healthy controls [14]. These data were also further confirmed by other authors [73]. To note, enhanced visfatin levels are associated with augmented joint damage [73]. Brentano and colleagues reported that visfatin was localized in the site of invasion of synovial tissue in joints of RA patients. Moreover, it is able to induce IL-6, MMP-1, and MMP-3 in RA synovial fibroblasts, as well as IL-6 and TNF-α in monocytes [74]. To note, PBEF knockdown in RASFs significantly inhibited basal and TLR ligand-induced production of IL-6, IL-8, MMP-1, and MMP-3 [74].Very recently, Busso et al. have showed that visfatin is a key mediator in inflammatory arthritis.The administration of a visfatin inhibitor to mice with collagen-induced arthritis reduced arthritis severity with similar effect to that produced by TNF-α inhibitor [75]. Moreover, pharmacological inhibition of visfatin led to reduced levels of intracellular NAD in inflammatory cells and decreased the production of TNF-α and IL-6 in affected joints [75]. However, the mechanisms by which visfatin exerts its catabolic effect in arthritic joints are still incompletely understood.
## 5.3. Visfatin and OA
At cartilage level, OA chondrocytes are able to produce visfatin and its expression is increased after IL-1β treatment [76]. Visfatin administration, like IL-1β, enhances PGE2 release. In line with this, visfatin also increases MMP-3 and MMP-13 synthesis and release and ADAMTS-4 and ADAMTS-5 expression in mouse articular chondrocytes [76]. Probably due to this augment in the expression of matrix degradative enzymes, visfatin decreases aggrecan expression [76].In addition, we showed that serum visfatin concentrations were higher in patients with OA compared to healthy controls [11]. Very recently, Duan et al. have reported that SF visfatin was positively correlated with degradation biomarker of collagen II, helix-II, and C-telopeptide of type II collagen (CTX-II) and degradation biomarker of aggrecan, aggrecanase-1 (AGG1), and aggrecanase-2 (AGG2), suggesting an involvement of adiponectin in cartilage matrix degradation [77].Taken together, these data suggest that visfatin has a catabolic function in cartilage and may have an important role in the pathophysiology of osteoarthritis.
## 5.4. Visfatin and SLE
Recent findings report also an implication of visfatin in SLE pathophysiology. It was showed that, in SLE patients, visfatin levels were higher compared to healthy controls [49, 73]. However, further studies are needed for more precise elucidation of the role that this adipokine plays in the SLE.
## 6. CHEMERIN
Chemerin, also known as tazarotene-induced gene 2 and retinoic acid receptor responder 2 (RARRES2), is a novel identified chemoattractant adipokine [78]. It is secreted as an 18 kDa inactive proprotein and activated by posttranslational C-terminal cleavage [79]. Chemerin acts via the G-coupled receptor chemokine-like receptor 1 (CMKLR1 or ChemR23) [78]. Chemerin and its receptor are mainly expressed, but not exclusively, in adipose tissue [80], for instance, dendritic cells, and macrophages express chemerin receptor [81]. ChemR23 is also expressed by endothelial cells, and it is upregulated by proinflammatory cytokines such as TNF-α, IL-1β, and IL-6 [82]. Moreover, chemerin exogenous challenge promotes in vitro angiogenesis by inducing cell proliferation, endothelial migration, and capillary tube formation, critical steps in the development of angiogenesis [82].Interestingly, chondrocytes express chemerin and its receptor [83–85], and IL-1β is able to increase chemerin expression [84]. In the same way, Berg et al. have demonstrated that recombinant chemerin enhances the production of several proinflammatory cytokines (TNF-α, IL-1β, IL-6, and IL-8), as well as different MMPs (MMP-1, MMP-2, MMP-3, MMP 8, and MMP-13) in human articular chondrocytes [83]. These factors play a role in the degradation of the extracellular matrix, by causing a breakdown of the collagen and aggrecan framework, and result in the irreversible destruction of the cartilage in OA and RA. Moreover, these authors reported that the intracellular signalling after ChemR23 activation occurs through p42/44 MAPK and Akt phosphorylation.Chemerin and ChemR23 expression was found in SLE skin biopsies [85]. In vitro experiments showed that chemerin acts as a chemotactic factor for plasmacytoid DCs. The tissue distribution of this adipokine, located at the luminal side of inflamed blood vessels, suggests that chemerin is involved in the migration of plasmacytoid DCs and the accumulation of these cells in inflamed tissues in SLE patients [85]. Moreover, De Palma et al. found chemerin expression in renal tubular epithelial cells from SLE patients with nephritis [86]. These authors, using a transendothelial chemotaxis assay, demonstrated that the recruitment of plasmacytoid DCs by TNF-α was mediated by chemerin/ChemR23 interaction, which may be due to the induction of the cleavage of prochemerin by TNF-α through the local production of serine proteases in proximal tubular epithelial cells [79, 86–88].
## 7. LIPOCALIN 2
Lipocalin 2 (LCN2), also termed siderocalin, 24p3, uterocalin, and neutrophil gelatinase-associated lipocalin (NGAL), is a 25 kDa glycoprotein isolated from neutrophil granules although white adipose tissue (WAT) is thought to be the main source [89]. The LCN2 protein has been isolated as a 25 kDa monomer, as a 46 kDa homodimer, and in a covalent complex with MMP-9, and its cellular receptor, megalin (GP330), was recently described [90]. LCN2 is involved in apoptosis of haematopoietic cells [90], transport of fatty acids and iron [91], modulation of inflammation [92], among other processes.LCN2 has recently been identified in chondrocytes [93]. In these cells IL-1β, leptin, adiponectin, LPS, and dexamethasone act as potent modulators of LCN2 expression [84]. Lipocalin 2 is likely to be involved in matrix degradation since it forms molecular complexes with MMP-9 [94].Recently, the group of Katano confirmed that the level of NGAL in SF was significantly higher in patients with RA than in those with osteoarthritis. Through proteome analysis Katano et al. have showed that GM-CSF may contribute to the pathogenesis of RA by the upregulation of LCN2 in neutrophils, followed by induction of Cathepsin D, transitional endoplasmic reticulum ATPase (TERA), and transglutaminase 2 (tg2) in synoviocytes [35]. These enzymes may contribute to the proliferation of synovial cells and infiltration of inflammatory cells inside the synovia [35].Finally, LCN2 is also a candidate biomarker for the early detection of LN (lupus nephritis) that is an inflammation of the kidney caused by systemic lupus erythematosus (SLE), which is very common in childhood-onset SLE (cSLE). Hinze et al. have demonstrated that urinary and plasma NGAL (U-NGAL and P-NGAL) are excellent candidates for predictive biomarkers for worsening of cSLE renal and global disease activity, respectively [95].
## 8. SERUM AMYLOID A3
Serum amyloid A3 (SAA3) protein is an adipokine that belongs to the family of acute-phase serum amyloid A proteins (A-SAA) secreted in the acute phase of inflammation. In mice, all A-SAA proteins are actively transcribed [96–98] whereas, in humans, SAA3 is encoded by a pseudogene and its functional protein is unknown [99, 100]. In contrast to that, in other species, murine SAA3 expression is not confined to the liver but found in several cell types [101–103]. Murine SAA3 is involved in immune, metabolic, and cardiovascular homeostasis [103–105]. Certain factors (e.g., IL-1β, TNF, dexamethasone, IL-6, and bacterial LPS) and conditions such as obesity modulate SAA3 expression [101–103, 106]. SAA3 is induced by IL-1β in primary rabbit chondrocytes and can induce transcription of MMP-13 [107].
## 9. OTHER ADIPOKINES WITH A POTENTIAL ROLE IN RHEUMATIC DISEASES
### 9.1. Apelin, Vaspin, and Omentin
#### 9.1.1. Apelin
Apelin is a bioactive peptide that was originally identified as the endogenous ligand of the orphan G protein-coupled receptor APJ [108]. TNF increases both apelin productions in adipose tissue and blood plasma apelin levels when administered to mice [109]. Intriguingly, in mice with diet-induced obesity, macrophage counts and the levels of proinflammatory agents such as TNF rise progressively in adipose tissue [110]. Thus, one can envisage that overproduction of apelin in the obese might be an adaptive response that attempts to forestall the onset of obesity-related disorders such as mild chronic inflammation.Very recently, Hu et al. have suggested that apelin may play a catabolic role in cartilage metabolism and that it can be a risk factor in the pathophysiology of osteoarthritis. Apelin stimulates the proliferation of chondrocytes and significantly increases mRNA levels of MMP-1, MMP-3, MMP-9, and IL-1βin vitro. Intra-articular injection with apelin in vivo upregulates the expression of MMP-3, MMP-9, and IL-1β decreases the level of collagen II. In addition, after treatment with apelin, mRNA levels of ADAMTS-4 and ADAMTS-5 markedly increased and depletion of proteoglycan in articular cartilage was found [11].
#### 9.1.2. Vaspin
Vaspin is a serpin (serine protease inhibitor) that was produced in the visceral adipose tissue [111]. Interestingly, administration of vaspin to obese mice improved glucose tolerance and insulin sensitivity and reversed altered expression of genes that might promote insulin resistance. The induction of vaspin by adipose tissue might constitute a compensatory mechanism in response to obesity and its inflammatory complications.
#### 9.1.3. Omentin
is a protein of 40 kDa secreted by omental adipose tissue and highly abundant in human plasma that had previously been identified as intelectin, a new type of Ca2+-dependent lectin with affinity to galactofuranosyl residues (the last are constituents of pathogens and dominant immunogens) [112]. So, it was suggested that a biological function of omentin/intelectin was the specific recognition of pathogens and bacterial components, playing an important role in the innate immune response to parasite infection [113]. Moreover, several studies have shown that omentin gene expression is altered by inflammatory states and obesity [114]. Indeed, Kuperman et al. have found increased gene expression of omentin in airway epithelial cells of patients with asthma [115]. Intriguingly, a differential expression of omentin mRNA occurs in omental adipose tissue of patients with Crohn’s disease, suggesting that omentin could be a new candidate factor potentially involved in chronic inflammatory diseases in humans [112].Recently, Senolt et al. have found increased levels of vaspin and reduced levels ofomentin in the synovial fluid of patients with RA compared with those with OA [116]. This finding suggests that these two adipokines are likely involved in OA pathophysiology.
## 9.1. Apelin, Vaspin, and Omentin
### 9.1.1. Apelin
Apelin is a bioactive peptide that was originally identified as the endogenous ligand of the orphan G protein-coupled receptor APJ [108]. TNF increases both apelin productions in adipose tissue and blood plasma apelin levels when administered to mice [109]. Intriguingly, in mice with diet-induced obesity, macrophage counts and the levels of proinflammatory agents such as TNF rise progressively in adipose tissue [110]. Thus, one can envisage that overproduction of apelin in the obese might be an adaptive response that attempts to forestall the onset of obesity-related disorders such as mild chronic inflammation.Very recently, Hu et al. have suggested that apelin may play a catabolic role in cartilage metabolism and that it can be a risk factor in the pathophysiology of osteoarthritis. Apelin stimulates the proliferation of chondrocytes and significantly increases mRNA levels of MMP-1, MMP-3, MMP-9, and IL-1βin vitro. Intra-articular injection with apelin in vivo upregulates the expression of MMP-3, MMP-9, and IL-1β decreases the level of collagen II. In addition, after treatment with apelin, mRNA levels of ADAMTS-4 and ADAMTS-5 markedly increased and depletion of proteoglycan in articular cartilage was found [11].
### 9.1.2. Vaspin
Vaspin is a serpin (serine protease inhibitor) that was produced in the visceral adipose tissue [111]. Interestingly, administration of vaspin to obese mice improved glucose tolerance and insulin sensitivity and reversed altered expression of genes that might promote insulin resistance. The induction of vaspin by adipose tissue might constitute a compensatory mechanism in response to obesity and its inflammatory complications.
### 9.1.3. Omentin
is a protein of 40 kDa secreted by omental adipose tissue and highly abundant in human plasma that had previously been identified as intelectin, a new type of Ca2+-dependent lectin with affinity to galactofuranosyl residues (the last are constituents of pathogens and dominant immunogens) [112]. So, it was suggested that a biological function of omentin/intelectin was the specific recognition of pathogens and bacterial components, playing an important role in the innate immune response to parasite infection [113]. Moreover, several studies have shown that omentin gene expression is altered by inflammatory states and obesity [114]. Indeed, Kuperman et al. have found increased gene expression of omentin in airway epithelial cells of patients with asthma [115]. Intriguingly, a differential expression of omentin mRNA occurs in omental adipose tissue of patients with Crohn’s disease, suggesting that omentin could be a new candidate factor potentially involved in chronic inflammatory diseases in humans [112].Recently, Senolt et al. have found increased levels of vaspin and reduced levels ofomentin in the synovial fluid of patients with RA compared with those with OA [116]. This finding suggests that these two adipokines are likely involved in OA pathophysiology.
## 9.1.1. Apelin
Apelin is a bioactive peptide that was originally identified as the endogenous ligand of the orphan G protein-coupled receptor APJ [108]. TNF increases both apelin productions in adipose tissue and blood plasma apelin levels when administered to mice [109]. Intriguingly, in mice with diet-induced obesity, macrophage counts and the levels of proinflammatory agents such as TNF rise progressively in adipose tissue [110]. Thus, one can envisage that overproduction of apelin in the obese might be an adaptive response that attempts to forestall the onset of obesity-related disorders such as mild chronic inflammation.Very recently, Hu et al. have suggested that apelin may play a catabolic role in cartilage metabolism and that it can be a risk factor in the pathophysiology of osteoarthritis. Apelin stimulates the proliferation of chondrocytes and significantly increases mRNA levels of MMP-1, MMP-3, MMP-9, and IL-1βin vitro. Intra-articular injection with apelin in vivo upregulates the expression of MMP-3, MMP-9, and IL-1β decreases the level of collagen II. In addition, after treatment with apelin, mRNA levels of ADAMTS-4 and ADAMTS-5 markedly increased and depletion of proteoglycan in articular cartilage was found [11].
## 9.1.2. Vaspin
Vaspin is a serpin (serine protease inhibitor) that was produced in the visceral adipose tissue [111]. Interestingly, administration of vaspin to obese mice improved glucose tolerance and insulin sensitivity and reversed altered expression of genes that might promote insulin resistance. The induction of vaspin by adipose tissue might constitute a compensatory mechanism in response to obesity and its inflammatory complications.
## 9.1.3. Omentin
is a protein of 40 kDa secreted by omental adipose tissue and highly abundant in human plasma that had previously been identified as intelectin, a new type of Ca2+-dependent lectin with affinity to galactofuranosyl residues (the last are constituents of pathogens and dominant immunogens) [112]. So, it was suggested that a biological function of omentin/intelectin was the specific recognition of pathogens and bacterial components, playing an important role in the innate immune response to parasite infection [113]. Moreover, several studies have shown that omentin gene expression is altered by inflammatory states and obesity [114]. Indeed, Kuperman et al. have found increased gene expression of omentin in airway epithelial cells of patients with asthma [115]. Intriguingly, a differential expression of omentin mRNA occurs in omental adipose tissue of patients with Crohn’s disease, suggesting that omentin could be a new candidate factor potentially involved in chronic inflammatory diseases in humans [112].Recently, Senolt et al. have found increased levels of vaspin and reduced levels ofomentin in the synovial fluid of patients with RA compared with those with OA [116]. This finding suggests that these two adipokines are likely involved in OA pathophysiology.
## 10. CONCLUSIONS
The physiological role of adipokines is becoming much more clear and several clinical and experimental lines of evidence showed their contributions to inflammatory and rheumatic disorders. The complexity of the adipokine network in the pathogenesis and progression of rheumatic diseases raises, since the beginning, one important question of whether it may be possible to target the mechanism(s) by which adipokines contribute to disease selectively without suppressing their physiological actions. The data presented in this paper suggest that adipokines and their signalling pathways may represent innovative therapeutic strategies for autoimmune and rheumatic disorders (See Supplementary Tables S1 and S2). (See Supplementary Materials available at doi:10.1100/2011/290142).Although, these data are almost incomplete to allow translation of these approaches to clinical practice, several potential approaches are likely feasible. For instance, the control of leptin levels by using antibodies in a similar way to anti-TNF therapy might be an interesting strategy. Only further insights that clarify the mechanisms by which adipokines are regulated and which are the concrete roles of them in the rheumatic pathology could propose new pharmacological approaches for this disease.
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*Source: 290142-2011-10-25.xml* | 290142-2011-10-25_290142-2011-10-25.md | 67,208 | Beyond Fat Mass: Exploring the Role of Adipokines in Rheumatic Diseases | Morena Scotece; Javier Conde; Rodolfo Gómez; Veronica López; Francisca Lago; Juan Jesus Gómez-Reino; Oreste Gualillo | TheScientificWorldJOURNAL
(2011) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1100/2011/290142 | 290142-2011-10-25.xml | **Keywords:** white adipose tissue (WAT); adipokines; cytokines; rheumatic diseases; immune response; immune tolerance; metabolism; energetic homeostasis
---
## Abstract
The cloning of leptin in 1994 by Zhang et al. introduced a novel concept about white adipose tissue (WAT) as a very dynamic organ that releases a plethora of immune and inflammatory mediators, such as adipokines and cytokines, which are involved in multiple diseases. Actually, adipokines exert potent modulatory actions on target tissues involved in rheumatic diseases including cartilage, synovial, bone and immune cells. The goal of this paper is to elucidate the recent findings concerning the involvement of adipokines in rheumatic diseases, such as rheumatoid arthritis (RA), osteoarthritis (OA), and systemic lupus erythematosus (SLE).
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## Body
## 1. INTRODUCTION
In addition to the central role of lipid storage, white adipose tissue (WAT) is now recognized to be a multifactorial organ. It has a major endocrine function secreting several hormones, most notably leptin and adiponectin, together with a diverse range of other protein signals and factors. These adipose-derived peptides have been termed collectively “adipokines.” It is important to underline that these factors might be also synthesized in other tissues, rather than WAT, and participate in other relevant functions correlated with energy homeostasis and metabolism [1].Adipokines include a variety of proinflammatory peptides. These proinflammatory adipokines are increased in obesity and appear to contribute to the so-called “low-grade inflammatory state” of obese subjects creating a cluster of metabolic aberrations including cardiovascular complications and autoimmune inflammatory diseases.Initially restricted to metabolic activities, adipokines represent a new family of compounds that can be currently considered as key players of the complex network of soluble mediators involved in the pathophysiology of rheumatic diseases. For instance, obesity has long been considered as a risk factor for osteoarthritis (OA). It has been reported that obesity increases the incidence of OA, particularly in weight-bearing joints such as knees, and weight reduction is correlated with decreased progression of OA. A prevailing hypothesis is that obesity increases mechanical loading across the articular cartilage that leads to its degeneration. However, obesity is also associated with OA in non-weight-bearing joints such as finger joints and wrists, which suggest that these metabolic factors contribute to the high prevalence of OA in obese subjects [2].This paper addresses current data concerning the involvement of adipokines in the rheumatic diseases, focussing on the role of adipokines played in the pathophysiology of OA, rheumatoid arthritis (RA), and systemic lupus erythematosus (SLE).
## 2. LEPTIN AND ADIPONECTIN: A TALE OF TWO GIANTS
### 2.1. Leptin: A Short Overview
Leptin is the protein product of theobgene, the murine homologue of the human gene LEP, cloned in 1994 [3]. White adipose tissue cells mainly produce this adipokine, and its plasma concentration is directly correlated with the body-fat stores. It has a central role in fat metabolism; in fact leptin is considered a major regulator of body weight by suppressing appetite and stimulating energy expenditure via hypothalamic receptors. This hormone decreases food intake by inducing anorexigenic factors as cocaine-amphetamine-related transcript (CART) and increases energy consumption by suppressing orexigenic neuropeptides such as neuropeptide Y (NPY). The biological activity of leptin is mediated by specific receptors (Ob-R), which belong to the class 1 cytokine receptor superfamily and are encoded by the gene diabetes (db). Alternative splicing of the db gene produces multiple isoforms, but only the long isoform Ob-Rb appears to be capable of transducing the leptin signal.Leptin is a hormone with pleiotropic actions. In fact, in addition to regulation of food intake, it also affects a variety of other physiological functions, including fertility, bone metabolism, inflammation, infection, and immune responses.In the last years, important advancements have been added to clarify the involvement of leptin in promoting autoimmune and rheumatic pathologies, particularly rheumatoid arthritis, osteoarthritis, and systemic lupus erythematosus (SLE).
### 2.2. Leptin and Osteoarthritis
It is increasingly evident that this hormone plays a key role in the OA pathophysiology. Leptin expression is much higher in osteoarthritic human cartilage than in normal cartilage, and there exists a strong correlation of synovial fluid leptin levels with body mass index (BMI) in people with severe osteoarthritis [4]. The first findings have suggested that high circulating leptin levels in obese individuals may protect cartilage from osteoarthritic degeneration. Actually, Dumond et al. have demonstrated that the intra-articular injection of leptin can strongly stimulate the synthesis of insulin-like growth factor-1 (IGF-1) and transforming growth factor-β (TGF-β) at both the messenger RNA (mRNA) and protein levels which can exert anabolic activities in cartilage metabolism [4].By contrast, leptin has been demonstrated to act as a proinflammatory agent in osteoarthritis. Otero et al. showed that, in cultured human and murine chondrocytes, type 2 nitric oxide synthase (NOS2) is activated by the combination of leptin plus IFNγ, and NOS2 activation by IL1 is increased by leptin via a mechanism involving JAK2, PI3K, MEK1, and p38 [5–7]. The costimulation of leptin plus IFNγ induces nitric oxide, a well-known proinflammatory mediator on joint cartilage, where it triggers chondrocyte phenotype loss, apoptosis, and metalloproteinases (MMPs) activation.Leptin, per se, is able to induce also the expression of MMPs involved in OA cartilage damage, such as MMP-9 and MMP-13 [8]. Recently, Koskinen et al. have suggested that leptin alone or in combination with IL-1β upregulates MMP-1 and MMP-3 production in human OA cartilage through the transcription factor NF-κB, protein kinase C, and MAP kinase pathways, and its levels correlate positively with MMP-1 and MMP-3 in synovial fluid (SF) from OA patients [9].Noteworthily, very recently, Gómez et al. have showed that in human chondrocytes leptin increased IL-8 production, which is one of the major mediators of the inflammatory response [10].Moreover, in articular cartilage of rats, gene expression of ADAMTS-4 and ADAMTS-5 (a disintegrin and metalloproteinase with thrombospondin motifs) was markedly increased after treatment with leptin inducing also a depletion of proteoglycans [11].Leptin could also contribute to abnormal osteoblast function in OA. Indeed, the elevated production of leptin in OA abnormal subchondral osteoblast is correlated with the increased levels of ALP (alkaline phosphatase), OC (osteocalcin), collagen type I, and TGF-β1, inducing a dysregulation of osteoblast function [12]. Very recently, Griffin et al. showed that the incidence of OA was not higher in ob/ob and db/db female obese mice than in control background strain (C57BL/6J) [13]. Nevertheless, in this study, no standard was set for the incidence of OA in obese control mice (without leptin mutation) [12].This recent finding suggests that obesity, as dysregulated body fat accumulation, per se, is not a risk factor for joint degeneration since adiposity in the absence of leptin signaling is insufficient to induce systemic inflammation and knee osteoarthritis in female mice.
### 2.3. Leptin and Rheumatoid Arthritis
Together with other neuroendocrine signals, leptin seems to play a role in autoimmune diseases such as RA, but whether leptin can harm or protect joint structures in RA is still unclear. In patients with RA, circulating leptin levels have been described as either higher or unmodified in comparison to healthy controls [8, 14]. In RA patients, a fasting-induced fall in circulating leptin is associated with CD4+ lymphocyte hyporeactivity and increased IL-4 secretion [15]. Experimental antigen-induced arthritis is less severe in leptin-deficient ob/ob mice than in wild-type mice, whereas leptin-deficient mice and leptin-receptor-deficient mice exhibited a delayed resolution of the inflammatory process in zymosan-induced experimental arthritis. Notably, leptin decreased the severity of septic arthritis in wild type mice. So, in the light of the present results it seems difficult to make an unambiguous conclusion about a potential role of leptin in RA [16]. Several authors have also demonstrated that there may exist a close dependence between the risk of aggressive course of RA and leptin levels [17, 18]. In addition, a correlation between serum leptin and synovial fluid/serum leptin ratio and disease duration and parameters of RA activity has been reported [19].The action of leptin in RA is not only targeted to articular tissue, but this adipokine also exerts direct modulatory effects on activation, proliferation, maturation, and production of inflammatory mediators in a variety of immune cells, including lymphocytes, natural killer cells, monocytes/macrophages, dentritic cells, neutrophils, and eosinophils [20].In particular, it is known that leptin is able to modulate T regulatory cells that are potent suppressors of autoimmunity. The group of Matarese has recently demonstrated that leptin secreted by adipocytes sustains Th1 immunity by promoting effector T cell proliferation and by constraining TReg cells expansion. Weight loss, with concomitant reduction in leptin levels, induces a reduction in effector T cells proliferation and an increased expansion of TReg cells leading to a downregulation of Th1 immunity and cell-mediated autoimmune diseases associated with increased susceptibility to infections. On the contrary, an increase in adipocyte mass leads to high leptin secretion, which results in expansion of effector T cells and reduction of TReg cells. This fact determines an overall enhancement of the proinflammatory immunity and of T-cell-mediated autoimmune disorders. Though, leptin can be considered as a link among immune tolerance, metabolic function, and autoimmunity and future strategies aimed at interfering with leptin signaling may represent innovative therapeutic tools for autoimmune disorders.Very recently it has been demonstrated that leptin can activate mammalian target of rapamycin (mTOR) and regulate the proliferative capacity of regulatory T (TReg) cells. This study suggests that the leptin-mTOR signalling pathway is an important link between host energy status and TReg cell activity. Authors conclude that oscillating mTOR activity is necessary for TReg cell activation and suggest that this might explain why TReg cells are unresponsive to TCR stimulation in vitro when high levels of leptin and nutrients may sustain mTOR activation [21, 22]. To note, both direct and indirect effects of leptin on the immune system have been described to account for the immune defects observed in leptin- and leptin-receptor-deficient rodents. Actually, Palmer et al. have also showed an indirect effect of leptin on the immune system, demonstrating that leptin receptor deficiency affects the immune system indirectly via changes in the systemic environment [23].
### 2.4. Leptin and Systemic Lupus Erythematosus (SLE)
Leptin has been suggested to have a role also in other rheumatic diseases such as systemic lupus erythematosus (SLE), in particular modulating the cardiovascular risk of SLE patients. Recently, the group of La Cava demonstrated that leptin and high-fat diet are able to induce proinflammatory high-density lipoproteins and atherosclerosis in BWF1 lupus-prone mice. These data suggest that environmental factors associated with obesity and metabolic syndrome can accelerate atherosclerosis and disease in a lupus-prone background [24].A relationship between leptin and lupus-disease-related factors is also found. In fact, patients with SLE have increased concentrations of leptin and these concentrations are associated with insulin resistance, BMI (body mass index), and CRP (C-reactive protein) in these patients [25].
## 2.1. Leptin: A Short Overview
Leptin is the protein product of theobgene, the murine homologue of the human gene LEP, cloned in 1994 [3]. White adipose tissue cells mainly produce this adipokine, and its plasma concentration is directly correlated with the body-fat stores. It has a central role in fat metabolism; in fact leptin is considered a major regulator of body weight by suppressing appetite and stimulating energy expenditure via hypothalamic receptors. This hormone decreases food intake by inducing anorexigenic factors as cocaine-amphetamine-related transcript (CART) and increases energy consumption by suppressing orexigenic neuropeptides such as neuropeptide Y (NPY). The biological activity of leptin is mediated by specific receptors (Ob-R), which belong to the class 1 cytokine receptor superfamily and are encoded by the gene diabetes (db). Alternative splicing of the db gene produces multiple isoforms, but only the long isoform Ob-Rb appears to be capable of transducing the leptin signal.Leptin is a hormone with pleiotropic actions. In fact, in addition to regulation of food intake, it also affects a variety of other physiological functions, including fertility, bone metabolism, inflammation, infection, and immune responses.In the last years, important advancements have been added to clarify the involvement of leptin in promoting autoimmune and rheumatic pathologies, particularly rheumatoid arthritis, osteoarthritis, and systemic lupus erythematosus (SLE).
## 2.2. Leptin and Osteoarthritis
It is increasingly evident that this hormone plays a key role in the OA pathophysiology. Leptin expression is much higher in osteoarthritic human cartilage than in normal cartilage, and there exists a strong correlation of synovial fluid leptin levels with body mass index (BMI) in people with severe osteoarthritis [4]. The first findings have suggested that high circulating leptin levels in obese individuals may protect cartilage from osteoarthritic degeneration. Actually, Dumond et al. have demonstrated that the intra-articular injection of leptin can strongly stimulate the synthesis of insulin-like growth factor-1 (IGF-1) and transforming growth factor-β (TGF-β) at both the messenger RNA (mRNA) and protein levels which can exert anabolic activities in cartilage metabolism [4].By contrast, leptin has been demonstrated to act as a proinflammatory agent in osteoarthritis. Otero et al. showed that, in cultured human and murine chondrocytes, type 2 nitric oxide synthase (NOS2) is activated by the combination of leptin plus IFNγ, and NOS2 activation by IL1 is increased by leptin via a mechanism involving JAK2, PI3K, MEK1, and p38 [5–7]. The costimulation of leptin plus IFNγ induces nitric oxide, a well-known proinflammatory mediator on joint cartilage, where it triggers chondrocyte phenotype loss, apoptosis, and metalloproteinases (MMPs) activation.Leptin, per se, is able to induce also the expression of MMPs involved in OA cartilage damage, such as MMP-9 and MMP-13 [8]. Recently, Koskinen et al. have suggested that leptin alone or in combination with IL-1β upregulates MMP-1 and MMP-3 production in human OA cartilage through the transcription factor NF-κB, protein kinase C, and MAP kinase pathways, and its levels correlate positively with MMP-1 and MMP-3 in synovial fluid (SF) from OA patients [9].Noteworthily, very recently, Gómez et al. have showed that in human chondrocytes leptin increased IL-8 production, which is one of the major mediators of the inflammatory response [10].Moreover, in articular cartilage of rats, gene expression of ADAMTS-4 and ADAMTS-5 (a disintegrin and metalloproteinase with thrombospondin motifs) was markedly increased after treatment with leptin inducing also a depletion of proteoglycans [11].Leptin could also contribute to abnormal osteoblast function in OA. Indeed, the elevated production of leptin in OA abnormal subchondral osteoblast is correlated with the increased levels of ALP (alkaline phosphatase), OC (osteocalcin), collagen type I, and TGF-β1, inducing a dysregulation of osteoblast function [12]. Very recently, Griffin et al. showed that the incidence of OA was not higher in ob/ob and db/db female obese mice than in control background strain (C57BL/6J) [13]. Nevertheless, in this study, no standard was set for the incidence of OA in obese control mice (without leptin mutation) [12].This recent finding suggests that obesity, as dysregulated body fat accumulation, per se, is not a risk factor for joint degeneration since adiposity in the absence of leptin signaling is insufficient to induce systemic inflammation and knee osteoarthritis in female mice.
## 2.3. Leptin and Rheumatoid Arthritis
Together with other neuroendocrine signals, leptin seems to play a role in autoimmune diseases such as RA, but whether leptin can harm or protect joint structures in RA is still unclear. In patients with RA, circulating leptin levels have been described as either higher or unmodified in comparison to healthy controls [8, 14]. In RA patients, a fasting-induced fall in circulating leptin is associated with CD4+ lymphocyte hyporeactivity and increased IL-4 secretion [15]. Experimental antigen-induced arthritis is less severe in leptin-deficient ob/ob mice than in wild-type mice, whereas leptin-deficient mice and leptin-receptor-deficient mice exhibited a delayed resolution of the inflammatory process in zymosan-induced experimental arthritis. Notably, leptin decreased the severity of septic arthritis in wild type mice. So, in the light of the present results it seems difficult to make an unambiguous conclusion about a potential role of leptin in RA [16]. Several authors have also demonstrated that there may exist a close dependence between the risk of aggressive course of RA and leptin levels [17, 18]. In addition, a correlation between serum leptin and synovial fluid/serum leptin ratio and disease duration and parameters of RA activity has been reported [19].The action of leptin in RA is not only targeted to articular tissue, but this adipokine also exerts direct modulatory effects on activation, proliferation, maturation, and production of inflammatory mediators in a variety of immune cells, including lymphocytes, natural killer cells, monocytes/macrophages, dentritic cells, neutrophils, and eosinophils [20].In particular, it is known that leptin is able to modulate T regulatory cells that are potent suppressors of autoimmunity. The group of Matarese has recently demonstrated that leptin secreted by adipocytes sustains Th1 immunity by promoting effector T cell proliferation and by constraining TReg cells expansion. Weight loss, with concomitant reduction in leptin levels, induces a reduction in effector T cells proliferation and an increased expansion of TReg cells leading to a downregulation of Th1 immunity and cell-mediated autoimmune diseases associated with increased susceptibility to infections. On the contrary, an increase in adipocyte mass leads to high leptin secretion, which results in expansion of effector T cells and reduction of TReg cells. This fact determines an overall enhancement of the proinflammatory immunity and of T-cell-mediated autoimmune disorders. Though, leptin can be considered as a link among immune tolerance, metabolic function, and autoimmunity and future strategies aimed at interfering with leptin signaling may represent innovative therapeutic tools for autoimmune disorders.Very recently it has been demonstrated that leptin can activate mammalian target of rapamycin (mTOR) and regulate the proliferative capacity of regulatory T (TReg) cells. This study suggests that the leptin-mTOR signalling pathway is an important link between host energy status and TReg cell activity. Authors conclude that oscillating mTOR activity is necessary for TReg cell activation and suggest that this might explain why TReg cells are unresponsive to TCR stimulation in vitro when high levels of leptin and nutrients may sustain mTOR activation [21, 22]. To note, both direct and indirect effects of leptin on the immune system have been described to account for the immune defects observed in leptin- and leptin-receptor-deficient rodents. Actually, Palmer et al. have also showed an indirect effect of leptin on the immune system, demonstrating that leptin receptor deficiency affects the immune system indirectly via changes in the systemic environment [23].
## 2.4. Leptin and Systemic Lupus Erythematosus (SLE)
Leptin has been suggested to have a role also in other rheumatic diseases such as systemic lupus erythematosus (SLE), in particular modulating the cardiovascular risk of SLE patients. Recently, the group of La Cava demonstrated that leptin and high-fat diet are able to induce proinflammatory high-density lipoproteins and atherosclerosis in BWF1 lupus-prone mice. These data suggest that environmental factors associated with obesity and metabolic syndrome can accelerate atherosclerosis and disease in a lupus-prone background [24].A relationship between leptin and lupus-disease-related factors is also found. In fact, patients with SLE have increased concentrations of leptin and these concentrations are associated with insulin resistance, BMI (body mass index), and CRP (C-reactive protein) in these patients [25].
## 3. ADIPONECTIN
### 3.1. Adiponectin: A Short Overview
Adiponectin, also known as GBP28, apM1, Acrp30, or AdipoQ, is a 244-residue protein that is produced mainly by WAT. Adiponectin has structural homology with collagens VIII and X and complement factor C1q, and it circulates in the blood in relatively large amounts in different molecular forms (trimers, hexamers, and also 12-18-mer forms) [26, 27]. It increases fatty acid oxidation and reduces the synthesis of glucose in the liver. Ablation of the adiponectin gene has no dramatic effect in knockout mice on a normal diet, but when placed on a high-fat/sucrose diet they develop severe insulin resistance and exhibit lipid accumulation in muscles [28]. Circulating adiponectin levels tend to be low in morbidly obese patients and increase with weight loss and with the use of thiazolidinediones, which enhance sensitivity to insulin [26, 29].Adiponectin acts via two receptors, one (AdipoR1) found predominantly in skeletal muscle and the other (AdipoR2) in liver. Transduction of the adiponectin signal by AdipoR1 and AdipoR2 involves the activation of AMPK, PPAR-α, PPAR-γ, and other signalling molecules [26]. To note, targeted disruption of AdipoR1 and AdipoR2 causes abrogation of adiponectin binding and all its metabolic actions [30].Actually, some evidences, indicates that adiponectin has a wide range of effects in pathologies with inflammatory component, such as cardiovascular disease, endothelial dysfunction, type 2 diabetes, metabolic syndrome, OA, and RA [31]. Adiponectin acts as a potent modulator of both B and T cells; moreover, it modulates the activity of immune innate response by inducing relevant anti-inflammatory factors such as IL-1 receptor antagonist and IL-10 [26].
### 3.2. Adiponectin and RA
The potential role of adiponectin in rheumatic diseases has been actively investigated. In general, low adiponectin levels have been associated with obesity, type 2 diabetes, atherosclerosis, and vessel inflammation, and in metabolic syndrome the role of adiponectin is clearly anti-inflammatory. On the other side, multiple studies described high adiponectin levels in patients with RA, and these levels correlate with severity of RA [14, 32]. Giles et al. identified a robust cross-sectional association between serum adiponectin levels and radiographic damage in patients with RA [33], suggesting that this adipokines may be a mediator of the paradoxical relationship between increasing adiposity and protection from radiographic damage in RA, due to adiponectin circulating levels decrease as adiposity increase. Indeed, considering that adiponectin may have negative effects on joint, this adipokine could be a relevant mediator to the inverse relationship between increasing adiposity and radiographic damage observed in RA studies.In contrast to its “protective” role against obesity and vascular diseases, at joint levels adiponectin might be proinflammatory and involved in matrix degradation. In synovial fibroblasts, adiponectin induces IL-6 production and metalloproteinase-1, two of the main mediators of RA via the p38 MAPK pathway [34]. Similarly, IL-8 is induced by adiponectin through an intracellular pathway involving NF-κB [10, 35].Recent studies showed that adiponectin might also contribute to synovitis and joint destruction in RA by stimulating matrix metalloproteinase-1, matrix metalloproteinase-13, and vascular endothelial growth factor expression in synovial cells, surprisingly, more than conventional proinflammatory mediators (i.e, IL-1 beta) [36]. In addition adiponectin increases both cyclooxygenase-2 (COX-2) and membrane-associated PGE synthase-1 (mPGES-1) mRNA and protein expression, in RA synovial fibroblasts (RASFs) in a time- and concentration-dependent manner [37]. This increase was inhibited by siRNA against adiponectin receptor (AdipoR1 and AdipoR2) or using inhibitors of specific proteins involved in adiponectin signal transduction [37].Recently, Frommer et al. have confirmed the proinflammatory role of adiponectin in RA by demonstrating that this adipokine promotes inflammation through cytokine synthesis, attraction of inflammatory cells to the synovium, and recruitment of prodestructive cells via chemokines, thus promoting matrix destruction at sites of cartilage invasion [38].
### 3.3. Adiponectin and OA
It is possible that adiponectin is also implicated in OA pathogenesis. Adiponectin has emerged as a regulator of immune responses and inflammatory arthritis. However, its role in OA and cartilage degradation is controversial and, under many aspects, poorly known. Nevertheless, in chondrocytes this adipokine induces proinflammatory mediators such as nitric oxide, IL-6, MCP-1, MMP-3 and MMP-9 as well as IL-8 [10, 39, 40].Recent studies show a potential source of adipokines at articular level: the infrapatellar fat pad (IFP). Actually, recent evidence indicates an inflammatory phenotype of this adipose compartment in patients with OA showing that IFP could contribute to the pathophysiological changes in the OA joint via the local production of cytokines and adipokines [41–43]. In addition, the implication of adiponectin in OA pathogenesis is supported also by clinical observations. Lauberg et al. have reported that plasma adiponectin levels were significantly higher in OA patients than in healthy controls [44], and they also observed higher plasma adiponectin levels in female patients with erosive hand OA than those with nonerosive OA [45].It is noteworthy that adiponectin-leptin ratio has been proposed as predictor of pain in OA patients [46]; in fact this adipokine has been detected in the OA synovial fluids correlating with osteoarthritis severity [47] and aggrecan degradation [48].
### 3.4. Adiponectin and SLE
The role of adiponectin in the SLE pathophysiology is not clear. High levels of adiponectin have been found in patients with systemic lupus erythematosus (SLE) in comparison with healthy controls [49]; intriguingly, among the SLE patients, patients with insulin resistance (IR) showed significantly lower adiponectin levels than patients without IR [50].Rovin et al. have reported that plasma adiponectin levels are increased in patients with renal SLE compared to healthy controls and patients with nonrenal SLE. During renal but not nonrenal SLE flare, urine adiponectin levels increase significantly. For this reason, urine adiponectin may be a biomarker of renal SLE flare [51]. Intriguingly, the group of Aprahamian has suggested that PPAR-gamma agonists may be useful agents for the treatment of SLE and also demonstrated that induction of adiponectin is the major mechanism underlying the immunomodulatory effects of PPAR-gamma agonists [52]. However, these authors obtained their data by using a murine model of lupus so that the reality regarding the potential therapeutic effect of PPAR gamma agonists in human SLE may be completely different.In addition, the study of Vadacca et al. reported no difference of adiponectin levels in SLE patients in comparison to healthy subjects [53].In addition, very recently, McMahon and colleagues have demonstrated that leptin levels confer increased risk of atherosclerosis in women with systemic lupus erythematosus and that there is no significant association between adiponectin and atherosclerotic plaques in SLE [24].
## 3.1. Adiponectin: A Short Overview
Adiponectin, also known as GBP28, apM1, Acrp30, or AdipoQ, is a 244-residue protein that is produced mainly by WAT. Adiponectin has structural homology with collagens VIII and X and complement factor C1q, and it circulates in the blood in relatively large amounts in different molecular forms (trimers, hexamers, and also 12-18-mer forms) [26, 27]. It increases fatty acid oxidation and reduces the synthesis of glucose in the liver. Ablation of the adiponectin gene has no dramatic effect in knockout mice on a normal diet, but when placed on a high-fat/sucrose diet they develop severe insulin resistance and exhibit lipid accumulation in muscles [28]. Circulating adiponectin levels tend to be low in morbidly obese patients and increase with weight loss and with the use of thiazolidinediones, which enhance sensitivity to insulin [26, 29].Adiponectin acts via two receptors, one (AdipoR1) found predominantly in skeletal muscle and the other (AdipoR2) in liver. Transduction of the adiponectin signal by AdipoR1 and AdipoR2 involves the activation of AMPK, PPAR-α, PPAR-γ, and other signalling molecules [26]. To note, targeted disruption of AdipoR1 and AdipoR2 causes abrogation of adiponectin binding and all its metabolic actions [30].Actually, some evidences, indicates that adiponectin has a wide range of effects in pathologies with inflammatory component, such as cardiovascular disease, endothelial dysfunction, type 2 diabetes, metabolic syndrome, OA, and RA [31]. Adiponectin acts as a potent modulator of both B and T cells; moreover, it modulates the activity of immune innate response by inducing relevant anti-inflammatory factors such as IL-1 receptor antagonist and IL-10 [26].
## 3.2. Adiponectin and RA
The potential role of adiponectin in rheumatic diseases has been actively investigated. In general, low adiponectin levels have been associated with obesity, type 2 diabetes, atherosclerosis, and vessel inflammation, and in metabolic syndrome the role of adiponectin is clearly anti-inflammatory. On the other side, multiple studies described high adiponectin levels in patients with RA, and these levels correlate with severity of RA [14, 32]. Giles et al. identified a robust cross-sectional association between serum adiponectin levels and radiographic damage in patients with RA [33], suggesting that this adipokines may be a mediator of the paradoxical relationship between increasing adiposity and protection from radiographic damage in RA, due to adiponectin circulating levels decrease as adiposity increase. Indeed, considering that adiponectin may have negative effects on joint, this adipokine could be a relevant mediator to the inverse relationship between increasing adiposity and radiographic damage observed in RA studies.In contrast to its “protective” role against obesity and vascular diseases, at joint levels adiponectin might be proinflammatory and involved in matrix degradation. In synovial fibroblasts, adiponectin induces IL-6 production and metalloproteinase-1, two of the main mediators of RA via the p38 MAPK pathway [34]. Similarly, IL-8 is induced by adiponectin through an intracellular pathway involving NF-κB [10, 35].Recent studies showed that adiponectin might also contribute to synovitis and joint destruction in RA by stimulating matrix metalloproteinase-1, matrix metalloproteinase-13, and vascular endothelial growth factor expression in synovial cells, surprisingly, more than conventional proinflammatory mediators (i.e, IL-1 beta) [36]. In addition adiponectin increases both cyclooxygenase-2 (COX-2) and membrane-associated PGE synthase-1 (mPGES-1) mRNA and protein expression, in RA synovial fibroblasts (RASFs) in a time- and concentration-dependent manner [37]. This increase was inhibited by siRNA against adiponectin receptor (AdipoR1 and AdipoR2) or using inhibitors of specific proteins involved in adiponectin signal transduction [37].Recently, Frommer et al. have confirmed the proinflammatory role of adiponectin in RA by demonstrating that this adipokine promotes inflammation through cytokine synthesis, attraction of inflammatory cells to the synovium, and recruitment of prodestructive cells via chemokines, thus promoting matrix destruction at sites of cartilage invasion [38].
## 3.3. Adiponectin and OA
It is possible that adiponectin is also implicated in OA pathogenesis. Adiponectin has emerged as a regulator of immune responses and inflammatory arthritis. However, its role in OA and cartilage degradation is controversial and, under many aspects, poorly known. Nevertheless, in chondrocytes this adipokine induces proinflammatory mediators such as nitric oxide, IL-6, MCP-1, MMP-3 and MMP-9 as well as IL-8 [10, 39, 40].Recent studies show a potential source of adipokines at articular level: the infrapatellar fat pad (IFP). Actually, recent evidence indicates an inflammatory phenotype of this adipose compartment in patients with OA showing that IFP could contribute to the pathophysiological changes in the OA joint via the local production of cytokines and adipokines [41–43]. In addition, the implication of adiponectin in OA pathogenesis is supported also by clinical observations. Lauberg et al. have reported that plasma adiponectin levels were significantly higher in OA patients than in healthy controls [44], and they also observed higher plasma adiponectin levels in female patients with erosive hand OA than those with nonerosive OA [45].It is noteworthy that adiponectin-leptin ratio has been proposed as predictor of pain in OA patients [46]; in fact this adipokine has been detected in the OA synovial fluids correlating with osteoarthritis severity [47] and aggrecan degradation [48].
## 3.4. Adiponectin and SLE
The role of adiponectin in the SLE pathophysiology is not clear. High levels of adiponectin have been found in patients with systemic lupus erythematosus (SLE) in comparison with healthy controls [49]; intriguingly, among the SLE patients, patients with insulin resistance (IR) showed significantly lower adiponectin levels than patients without IR [50].Rovin et al. have reported that plasma adiponectin levels are increased in patients with renal SLE compared to healthy controls and patients with nonrenal SLE. During renal but not nonrenal SLE flare, urine adiponectin levels increase significantly. For this reason, urine adiponectin may be a biomarker of renal SLE flare [51]. Intriguingly, the group of Aprahamian has suggested that PPAR-gamma agonists may be useful agents for the treatment of SLE and also demonstrated that induction of adiponectin is the major mechanism underlying the immunomodulatory effects of PPAR-gamma agonists [52]. However, these authors obtained their data by using a murine model of lupus so that the reality regarding the potential therapeutic effect of PPAR gamma agonists in human SLE may be completely different.In addition, the study of Vadacca et al. reported no difference of adiponectin levels in SLE patients in comparison to healthy subjects [53].In addition, very recently, McMahon and colleagues have demonstrated that leptin levels confer increased risk of atherosclerosis in women with systemic lupus erythematosus and that there is no significant association between adiponectin and atherosclerotic plaques in SLE [24].
## 4. RESISTIN
### 4.1. Resistin: A Short Overview
Resistin, known as adipocyte-secreted factor (ADSF) or found in inflammatory zone 3 (FIZZ3), was discovered in 2001 and was proposed as potential link between obesity and diabetes [54]. It was secreted by adipose tissue but has been found also in macrophages, neutrophils, and other cell types. Serum resistin levels increase with obesity in mice, rats, and humans [55, 56]. Increasing evidence indicates its important regulatory role in various biological processes, including several inflammatory diseases.
### 4.2. Resistin and RA
There are demonstrations that resistin may be involved in the pathogenesis of RA. Increased levels of this adipokine in synovial fluid from patients of rheumatoid arthritis (RA) compared to patients with noninflammatory rheumatic disorders have previously been observed [57].Actually, resistin has been found in the plasma and synovial fluid of RA patients, and injection of this adipokine into mice joints induce an arthritis-like condition, with leukocyte infiltration of synovial tissues, hypertrophy of the synovial layer, and pannus formation [58, 59]. Bokarewa et al. have showed also that resistin induces and is induced by several proinflammatory cytokines, such as TNF-α or IL-6, in peripheral blood mononuclear cells, via NF-κB pathway, indicating that resistin can increase its own activity by a positive feedback mechanism [58] Increased serum resistin in patients with rheumatoid arthritis correlated with both C-reactive protein (CRP) and DAS28, suggesting a role of this adipokine in the pathogenesis of rheumatoid arthritis [59]. Gonzalez-Gay et al. have confirmed this association between laboratory markers of inflammation, particularly CRP and resistin levels and have showed that anti-TNF-alpha therapy results in a rapid reduction of serum resistin levels in patients with RA [60].There is also an association between resistin and increased inflammation, joint destruction and levels of interleukin 1 receptor antagonist (IL-1RA) in rheumatoid arthritis female patients [61].
### 4.3. Resistin and OA
The proinflammatory profile of resistin, together with its association with obesity suggest that this adipokine might be another potential mediator that links OA with inflammation and obesity. It was demonstrated that this adipokine is elevated in both serum and SF after traumatic joint injuries. Recombinant resistin stimulated proteoglycan degradation in mouse femoral head cultures and the induction of inflammatory cytokines and PGE2 production. Moreover, it inhibited proteoglycan synthesis in human cartilage explants [62]. However, Berry et al. have not identified any association between baseline serum levels of resistin and cartilage volume loss [63].Recently, Zhang and colleagues demonstrated that resistin has diverse effects on gene expression in human chondrocytes, affecting chemokines, cytokines, and matrix gene expression. Messenger RNA stabilization and transcriptional upregulation are also involved in resistin-induced gene expression in human chondrocytes [64].
### 4.4. Resistin and SLE
In addition, resistin has a role as a marker of inflammation in other rheumatic diseases, such as systemic lupus erythematous (SLE). In fact, Almehed et al. have demonstrated a positive correlation between serum resistin levels, inflammation, bone mineral density, and renal functions in patients with SLE [65].
## 4.1. Resistin: A Short Overview
Resistin, known as adipocyte-secreted factor (ADSF) or found in inflammatory zone 3 (FIZZ3), was discovered in 2001 and was proposed as potential link between obesity and diabetes [54]. It was secreted by adipose tissue but has been found also in macrophages, neutrophils, and other cell types. Serum resistin levels increase with obesity in mice, rats, and humans [55, 56]. Increasing evidence indicates its important regulatory role in various biological processes, including several inflammatory diseases.
## 4.2. Resistin and RA
There are demonstrations that resistin may be involved in the pathogenesis of RA. Increased levels of this adipokine in synovial fluid from patients of rheumatoid arthritis (RA) compared to patients with noninflammatory rheumatic disorders have previously been observed [57].Actually, resistin has been found in the plasma and synovial fluid of RA patients, and injection of this adipokine into mice joints induce an arthritis-like condition, with leukocyte infiltration of synovial tissues, hypertrophy of the synovial layer, and pannus formation [58, 59]. Bokarewa et al. have showed also that resistin induces and is induced by several proinflammatory cytokines, such as TNF-α or IL-6, in peripheral blood mononuclear cells, via NF-κB pathway, indicating that resistin can increase its own activity by a positive feedback mechanism [58] Increased serum resistin in patients with rheumatoid arthritis correlated with both C-reactive protein (CRP) and DAS28, suggesting a role of this adipokine in the pathogenesis of rheumatoid arthritis [59]. Gonzalez-Gay et al. have confirmed this association between laboratory markers of inflammation, particularly CRP and resistin levels and have showed that anti-TNF-alpha therapy results in a rapid reduction of serum resistin levels in patients with RA [60].There is also an association between resistin and increased inflammation, joint destruction and levels of interleukin 1 receptor antagonist (IL-1RA) in rheumatoid arthritis female patients [61].
## 4.3. Resistin and OA
The proinflammatory profile of resistin, together with its association with obesity suggest that this adipokine might be another potential mediator that links OA with inflammation and obesity. It was demonstrated that this adipokine is elevated in both serum and SF after traumatic joint injuries. Recombinant resistin stimulated proteoglycan degradation in mouse femoral head cultures and the induction of inflammatory cytokines and PGE2 production. Moreover, it inhibited proteoglycan synthesis in human cartilage explants [62]. However, Berry et al. have not identified any association between baseline serum levels of resistin and cartilage volume loss [63].Recently, Zhang and colleagues demonstrated that resistin has diverse effects on gene expression in human chondrocytes, affecting chemokines, cytokines, and matrix gene expression. Messenger RNA stabilization and transcriptional upregulation are also involved in resistin-induced gene expression in human chondrocytes [64].
## 4.4. Resistin and SLE
In addition, resistin has a role as a marker of inflammation in other rheumatic diseases, such as systemic lupus erythematous (SLE). In fact, Almehed et al. have demonstrated a positive correlation between serum resistin levels, inflammation, bone mineral density, and renal functions in patients with SLE [65].
## 5. VISFATIN
### 5.1. Visfatin: A Short Overview
Visfatin, also named pre-B-cell colony-enhancing factor (PBEF) and nicotinamide phosphoribosyltransferase (Nampt), was originally discovered in liver, skeletal muscle, and bone marrow as a growth factor for B-lymphocyte precursors; however, it is also secreted by visceral fat [66, 67]. It is supposed that visfatin had insulin mimetic properties, but the role of this adipokine in the modulation of glucose metabolism, as well as its binding to insulin receptors, is still amatter of debate [67, 68].It has been reported that visfatin is increased in obesity. Moreover, leucocytes from obese patients produce higher amounts of visfatin compared with lean subjects, and, specifically, granulocytes and monocytes are the major visfatin-producing cells [69, 70]. However, leucocytes are not the only nonfat cell type that synthesizes visfatin. Actually, macrophages have been described as a source for visfatin production [71], and, interestingly, this adipokine promoted macrophage survival by reducing apoptosis [72].
### 5.2. Visfatin and RA
Visfatin may be considered another potential therapeutic target for RA with important proinflammatory and catabolic roles in RA pathogenesis. Our group demonstrated that circulating visfatin is higher in patients with RA than in healthy controls [14]. These data were also further confirmed by other authors [73]. To note, enhanced visfatin levels are associated with augmented joint damage [73]. Brentano and colleagues reported that visfatin was localized in the site of invasion of synovial tissue in joints of RA patients. Moreover, it is able to induce IL-6, MMP-1, and MMP-3 in RA synovial fibroblasts, as well as IL-6 and TNF-α in monocytes [74]. To note, PBEF knockdown in RASFs significantly inhibited basal and TLR ligand-induced production of IL-6, IL-8, MMP-1, and MMP-3 [74].Very recently, Busso et al. have showed that visfatin is a key mediator in inflammatory arthritis.The administration of a visfatin inhibitor to mice with collagen-induced arthritis reduced arthritis severity with similar effect to that produced by TNF-α inhibitor [75]. Moreover, pharmacological inhibition of visfatin led to reduced levels of intracellular NAD in inflammatory cells and decreased the production of TNF-α and IL-6 in affected joints [75]. However, the mechanisms by which visfatin exerts its catabolic effect in arthritic joints are still incompletely understood.
### 5.3. Visfatin and OA
At cartilage level, OA chondrocytes are able to produce visfatin and its expression is increased after IL-1β treatment [76]. Visfatin administration, like IL-1β, enhances PGE2 release. In line with this, visfatin also increases MMP-3 and MMP-13 synthesis and release and ADAMTS-4 and ADAMTS-5 expression in mouse articular chondrocytes [76]. Probably due to this augment in the expression of matrix degradative enzymes, visfatin decreases aggrecan expression [76].In addition, we showed that serum visfatin concentrations were higher in patients with OA compared to healthy controls [11]. Very recently, Duan et al. have reported that SF visfatin was positively correlated with degradation biomarker of collagen II, helix-II, and C-telopeptide of type II collagen (CTX-II) and degradation biomarker of aggrecan, aggrecanase-1 (AGG1), and aggrecanase-2 (AGG2), suggesting an involvement of adiponectin in cartilage matrix degradation [77].Taken together, these data suggest that visfatin has a catabolic function in cartilage and may have an important role in the pathophysiology of osteoarthritis.
### 5.4. Visfatin and SLE
Recent findings report also an implication of visfatin in SLE pathophysiology. It was showed that, in SLE patients, visfatin levels were higher compared to healthy controls [49, 73]. However, further studies are needed for more precise elucidation of the role that this adipokine plays in the SLE.
## 5.1. Visfatin: A Short Overview
Visfatin, also named pre-B-cell colony-enhancing factor (PBEF) and nicotinamide phosphoribosyltransferase (Nampt), was originally discovered in liver, skeletal muscle, and bone marrow as a growth factor for B-lymphocyte precursors; however, it is also secreted by visceral fat [66, 67]. It is supposed that visfatin had insulin mimetic properties, but the role of this adipokine in the modulation of glucose metabolism, as well as its binding to insulin receptors, is still amatter of debate [67, 68].It has been reported that visfatin is increased in obesity. Moreover, leucocytes from obese patients produce higher amounts of visfatin compared with lean subjects, and, specifically, granulocytes and monocytes are the major visfatin-producing cells [69, 70]. However, leucocytes are not the only nonfat cell type that synthesizes visfatin. Actually, macrophages have been described as a source for visfatin production [71], and, interestingly, this adipokine promoted macrophage survival by reducing apoptosis [72].
## 5.2. Visfatin and RA
Visfatin may be considered another potential therapeutic target for RA with important proinflammatory and catabolic roles in RA pathogenesis. Our group demonstrated that circulating visfatin is higher in patients with RA than in healthy controls [14]. These data were also further confirmed by other authors [73]. To note, enhanced visfatin levels are associated with augmented joint damage [73]. Brentano and colleagues reported that visfatin was localized in the site of invasion of synovial tissue in joints of RA patients. Moreover, it is able to induce IL-6, MMP-1, and MMP-3 in RA synovial fibroblasts, as well as IL-6 and TNF-α in monocytes [74]. To note, PBEF knockdown in RASFs significantly inhibited basal and TLR ligand-induced production of IL-6, IL-8, MMP-1, and MMP-3 [74].Very recently, Busso et al. have showed that visfatin is a key mediator in inflammatory arthritis.The administration of a visfatin inhibitor to mice with collagen-induced arthritis reduced arthritis severity with similar effect to that produced by TNF-α inhibitor [75]. Moreover, pharmacological inhibition of visfatin led to reduced levels of intracellular NAD in inflammatory cells and decreased the production of TNF-α and IL-6 in affected joints [75]. However, the mechanisms by which visfatin exerts its catabolic effect in arthritic joints are still incompletely understood.
## 5.3. Visfatin and OA
At cartilage level, OA chondrocytes are able to produce visfatin and its expression is increased after IL-1β treatment [76]. Visfatin administration, like IL-1β, enhances PGE2 release. In line with this, visfatin also increases MMP-3 and MMP-13 synthesis and release and ADAMTS-4 and ADAMTS-5 expression in mouse articular chondrocytes [76]. Probably due to this augment in the expression of matrix degradative enzymes, visfatin decreases aggrecan expression [76].In addition, we showed that serum visfatin concentrations were higher in patients with OA compared to healthy controls [11]. Very recently, Duan et al. have reported that SF visfatin was positively correlated with degradation biomarker of collagen II, helix-II, and C-telopeptide of type II collagen (CTX-II) and degradation biomarker of aggrecan, aggrecanase-1 (AGG1), and aggrecanase-2 (AGG2), suggesting an involvement of adiponectin in cartilage matrix degradation [77].Taken together, these data suggest that visfatin has a catabolic function in cartilage and may have an important role in the pathophysiology of osteoarthritis.
## 5.4. Visfatin and SLE
Recent findings report also an implication of visfatin in SLE pathophysiology. It was showed that, in SLE patients, visfatin levels were higher compared to healthy controls [49, 73]. However, further studies are needed for more precise elucidation of the role that this adipokine plays in the SLE.
## 6. CHEMERIN
Chemerin, also known as tazarotene-induced gene 2 and retinoic acid receptor responder 2 (RARRES2), is a novel identified chemoattractant adipokine [78]. It is secreted as an 18 kDa inactive proprotein and activated by posttranslational C-terminal cleavage [79]. Chemerin acts via the G-coupled receptor chemokine-like receptor 1 (CMKLR1 or ChemR23) [78]. Chemerin and its receptor are mainly expressed, but not exclusively, in adipose tissue [80], for instance, dendritic cells, and macrophages express chemerin receptor [81]. ChemR23 is also expressed by endothelial cells, and it is upregulated by proinflammatory cytokines such as TNF-α, IL-1β, and IL-6 [82]. Moreover, chemerin exogenous challenge promotes in vitro angiogenesis by inducing cell proliferation, endothelial migration, and capillary tube formation, critical steps in the development of angiogenesis [82].Interestingly, chondrocytes express chemerin and its receptor [83–85], and IL-1β is able to increase chemerin expression [84]. In the same way, Berg et al. have demonstrated that recombinant chemerin enhances the production of several proinflammatory cytokines (TNF-α, IL-1β, IL-6, and IL-8), as well as different MMPs (MMP-1, MMP-2, MMP-3, MMP 8, and MMP-13) in human articular chondrocytes [83]. These factors play a role in the degradation of the extracellular matrix, by causing a breakdown of the collagen and aggrecan framework, and result in the irreversible destruction of the cartilage in OA and RA. Moreover, these authors reported that the intracellular signalling after ChemR23 activation occurs through p42/44 MAPK and Akt phosphorylation.Chemerin and ChemR23 expression was found in SLE skin biopsies [85]. In vitro experiments showed that chemerin acts as a chemotactic factor for plasmacytoid DCs. The tissue distribution of this adipokine, located at the luminal side of inflamed blood vessels, suggests that chemerin is involved in the migration of plasmacytoid DCs and the accumulation of these cells in inflamed tissues in SLE patients [85]. Moreover, De Palma et al. found chemerin expression in renal tubular epithelial cells from SLE patients with nephritis [86]. These authors, using a transendothelial chemotaxis assay, demonstrated that the recruitment of plasmacytoid DCs by TNF-α was mediated by chemerin/ChemR23 interaction, which may be due to the induction of the cleavage of prochemerin by TNF-α through the local production of serine proteases in proximal tubular epithelial cells [79, 86–88].
## 7. LIPOCALIN 2
Lipocalin 2 (LCN2), also termed siderocalin, 24p3, uterocalin, and neutrophil gelatinase-associated lipocalin (NGAL), is a 25 kDa glycoprotein isolated from neutrophil granules although white adipose tissue (WAT) is thought to be the main source [89]. The LCN2 protein has been isolated as a 25 kDa monomer, as a 46 kDa homodimer, and in a covalent complex with MMP-9, and its cellular receptor, megalin (GP330), was recently described [90]. LCN2 is involved in apoptosis of haematopoietic cells [90], transport of fatty acids and iron [91], modulation of inflammation [92], among other processes.LCN2 has recently been identified in chondrocytes [93]. In these cells IL-1β, leptin, adiponectin, LPS, and dexamethasone act as potent modulators of LCN2 expression [84]. Lipocalin 2 is likely to be involved in matrix degradation since it forms molecular complexes with MMP-9 [94].Recently, the group of Katano confirmed that the level of NGAL in SF was significantly higher in patients with RA than in those with osteoarthritis. Through proteome analysis Katano et al. have showed that GM-CSF may contribute to the pathogenesis of RA by the upregulation of LCN2 in neutrophils, followed by induction of Cathepsin D, transitional endoplasmic reticulum ATPase (TERA), and transglutaminase 2 (tg2) in synoviocytes [35]. These enzymes may contribute to the proliferation of synovial cells and infiltration of inflammatory cells inside the synovia [35].Finally, LCN2 is also a candidate biomarker for the early detection of LN (lupus nephritis) that is an inflammation of the kidney caused by systemic lupus erythematosus (SLE), which is very common in childhood-onset SLE (cSLE). Hinze et al. have demonstrated that urinary and plasma NGAL (U-NGAL and P-NGAL) are excellent candidates for predictive biomarkers for worsening of cSLE renal and global disease activity, respectively [95].
## 8. SERUM AMYLOID A3
Serum amyloid A3 (SAA3) protein is an adipokine that belongs to the family of acute-phase serum amyloid A proteins (A-SAA) secreted in the acute phase of inflammation. In mice, all A-SAA proteins are actively transcribed [96–98] whereas, in humans, SAA3 is encoded by a pseudogene and its functional protein is unknown [99, 100]. In contrast to that, in other species, murine SAA3 expression is not confined to the liver but found in several cell types [101–103]. Murine SAA3 is involved in immune, metabolic, and cardiovascular homeostasis [103–105]. Certain factors (e.g., IL-1β, TNF, dexamethasone, IL-6, and bacterial LPS) and conditions such as obesity modulate SAA3 expression [101–103, 106]. SAA3 is induced by IL-1β in primary rabbit chondrocytes and can induce transcription of MMP-13 [107].
## 9. OTHER ADIPOKINES WITH A POTENTIAL ROLE IN RHEUMATIC DISEASES
### 9.1. Apelin, Vaspin, and Omentin
#### 9.1.1. Apelin
Apelin is a bioactive peptide that was originally identified as the endogenous ligand of the orphan G protein-coupled receptor APJ [108]. TNF increases both apelin productions in adipose tissue and blood plasma apelin levels when administered to mice [109]. Intriguingly, in mice with diet-induced obesity, macrophage counts and the levels of proinflammatory agents such as TNF rise progressively in adipose tissue [110]. Thus, one can envisage that overproduction of apelin in the obese might be an adaptive response that attempts to forestall the onset of obesity-related disorders such as mild chronic inflammation.Very recently, Hu et al. have suggested that apelin may play a catabolic role in cartilage metabolism and that it can be a risk factor in the pathophysiology of osteoarthritis. Apelin stimulates the proliferation of chondrocytes and significantly increases mRNA levels of MMP-1, MMP-3, MMP-9, and IL-1βin vitro. Intra-articular injection with apelin in vivo upregulates the expression of MMP-3, MMP-9, and IL-1β decreases the level of collagen II. In addition, after treatment with apelin, mRNA levels of ADAMTS-4 and ADAMTS-5 markedly increased and depletion of proteoglycan in articular cartilage was found [11].
#### 9.1.2. Vaspin
Vaspin is a serpin (serine protease inhibitor) that was produced in the visceral adipose tissue [111]. Interestingly, administration of vaspin to obese mice improved glucose tolerance and insulin sensitivity and reversed altered expression of genes that might promote insulin resistance. The induction of vaspin by adipose tissue might constitute a compensatory mechanism in response to obesity and its inflammatory complications.
#### 9.1.3. Omentin
is a protein of 40 kDa secreted by omental adipose tissue and highly abundant in human plasma that had previously been identified as intelectin, a new type of Ca2+-dependent lectin with affinity to galactofuranosyl residues (the last are constituents of pathogens and dominant immunogens) [112]. So, it was suggested that a biological function of omentin/intelectin was the specific recognition of pathogens and bacterial components, playing an important role in the innate immune response to parasite infection [113]. Moreover, several studies have shown that omentin gene expression is altered by inflammatory states and obesity [114]. Indeed, Kuperman et al. have found increased gene expression of omentin in airway epithelial cells of patients with asthma [115]. Intriguingly, a differential expression of omentin mRNA occurs in omental adipose tissue of patients with Crohn’s disease, suggesting that omentin could be a new candidate factor potentially involved in chronic inflammatory diseases in humans [112].Recently, Senolt et al. have found increased levels of vaspin and reduced levels ofomentin in the synovial fluid of patients with RA compared with those with OA [116]. This finding suggests that these two adipokines are likely involved in OA pathophysiology.
## 9.1. Apelin, Vaspin, and Omentin
### 9.1.1. Apelin
Apelin is a bioactive peptide that was originally identified as the endogenous ligand of the orphan G protein-coupled receptor APJ [108]. TNF increases both apelin productions in adipose tissue and blood plasma apelin levels when administered to mice [109]. Intriguingly, in mice with diet-induced obesity, macrophage counts and the levels of proinflammatory agents such as TNF rise progressively in adipose tissue [110]. Thus, one can envisage that overproduction of apelin in the obese might be an adaptive response that attempts to forestall the onset of obesity-related disorders such as mild chronic inflammation.Very recently, Hu et al. have suggested that apelin may play a catabolic role in cartilage metabolism and that it can be a risk factor in the pathophysiology of osteoarthritis. Apelin stimulates the proliferation of chondrocytes and significantly increases mRNA levels of MMP-1, MMP-3, MMP-9, and IL-1βin vitro. Intra-articular injection with apelin in vivo upregulates the expression of MMP-3, MMP-9, and IL-1β decreases the level of collagen II. In addition, after treatment with apelin, mRNA levels of ADAMTS-4 and ADAMTS-5 markedly increased and depletion of proteoglycan in articular cartilage was found [11].
### 9.1.2. Vaspin
Vaspin is a serpin (serine protease inhibitor) that was produced in the visceral adipose tissue [111]. Interestingly, administration of vaspin to obese mice improved glucose tolerance and insulin sensitivity and reversed altered expression of genes that might promote insulin resistance. The induction of vaspin by adipose tissue might constitute a compensatory mechanism in response to obesity and its inflammatory complications.
### 9.1.3. Omentin
is a protein of 40 kDa secreted by omental adipose tissue and highly abundant in human plasma that had previously been identified as intelectin, a new type of Ca2+-dependent lectin with affinity to galactofuranosyl residues (the last are constituents of pathogens and dominant immunogens) [112]. So, it was suggested that a biological function of omentin/intelectin was the specific recognition of pathogens and bacterial components, playing an important role in the innate immune response to parasite infection [113]. Moreover, several studies have shown that omentin gene expression is altered by inflammatory states and obesity [114]. Indeed, Kuperman et al. have found increased gene expression of omentin in airway epithelial cells of patients with asthma [115]. Intriguingly, a differential expression of omentin mRNA occurs in omental adipose tissue of patients with Crohn’s disease, suggesting that omentin could be a new candidate factor potentially involved in chronic inflammatory diseases in humans [112].Recently, Senolt et al. have found increased levels of vaspin and reduced levels ofomentin in the synovial fluid of patients with RA compared with those with OA [116]. This finding suggests that these two adipokines are likely involved in OA pathophysiology.
## 9.1.1. Apelin
Apelin is a bioactive peptide that was originally identified as the endogenous ligand of the orphan G protein-coupled receptor APJ [108]. TNF increases both apelin productions in adipose tissue and blood plasma apelin levels when administered to mice [109]. Intriguingly, in mice with diet-induced obesity, macrophage counts and the levels of proinflammatory agents such as TNF rise progressively in adipose tissue [110]. Thus, one can envisage that overproduction of apelin in the obese might be an adaptive response that attempts to forestall the onset of obesity-related disorders such as mild chronic inflammation.Very recently, Hu et al. have suggested that apelin may play a catabolic role in cartilage metabolism and that it can be a risk factor in the pathophysiology of osteoarthritis. Apelin stimulates the proliferation of chondrocytes and significantly increases mRNA levels of MMP-1, MMP-3, MMP-9, and IL-1βin vitro. Intra-articular injection with apelin in vivo upregulates the expression of MMP-3, MMP-9, and IL-1β decreases the level of collagen II. In addition, after treatment with apelin, mRNA levels of ADAMTS-4 and ADAMTS-5 markedly increased and depletion of proteoglycan in articular cartilage was found [11].
## 9.1.2. Vaspin
Vaspin is a serpin (serine protease inhibitor) that was produced in the visceral adipose tissue [111]. Interestingly, administration of vaspin to obese mice improved glucose tolerance and insulin sensitivity and reversed altered expression of genes that might promote insulin resistance. The induction of vaspin by adipose tissue might constitute a compensatory mechanism in response to obesity and its inflammatory complications.
## 9.1.3. Omentin
is a protein of 40 kDa secreted by omental adipose tissue and highly abundant in human plasma that had previously been identified as intelectin, a new type of Ca2+-dependent lectin with affinity to galactofuranosyl residues (the last are constituents of pathogens and dominant immunogens) [112]. So, it was suggested that a biological function of omentin/intelectin was the specific recognition of pathogens and bacterial components, playing an important role in the innate immune response to parasite infection [113]. Moreover, several studies have shown that omentin gene expression is altered by inflammatory states and obesity [114]. Indeed, Kuperman et al. have found increased gene expression of omentin in airway epithelial cells of patients with asthma [115]. Intriguingly, a differential expression of omentin mRNA occurs in omental adipose tissue of patients with Crohn’s disease, suggesting that omentin could be a new candidate factor potentially involved in chronic inflammatory diseases in humans [112].Recently, Senolt et al. have found increased levels of vaspin and reduced levels ofomentin in the synovial fluid of patients with RA compared with those with OA [116]. This finding suggests that these two adipokines are likely involved in OA pathophysiology.
## 10. CONCLUSIONS
The physiological role of adipokines is becoming much more clear and several clinical and experimental lines of evidence showed their contributions to inflammatory and rheumatic disorders. The complexity of the adipokine network in the pathogenesis and progression of rheumatic diseases raises, since the beginning, one important question of whether it may be possible to target the mechanism(s) by which adipokines contribute to disease selectively without suppressing their physiological actions. The data presented in this paper suggest that adipokines and their signalling pathways may represent innovative therapeutic strategies for autoimmune and rheumatic disorders (See Supplementary Tables S1 and S2). (See Supplementary Materials available at doi:10.1100/2011/290142).Although, these data are almost incomplete to allow translation of these approaches to clinical practice, several potential approaches are likely feasible. For instance, the control of leptin levels by using antibodies in a similar way to anti-TNF therapy might be an interesting strategy. Only further insights that clarify the mechanisms by which adipokines are regulated and which are the concrete roles of them in the rheumatic pathology could propose new pharmacological approaches for this disease.
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*Source: 290142-2011-10-25.xml* | 2011 |
# Dynamic and Static Nature of Br4σ(4c–6e) and Se2Br5σ(7c–10e) in the Selenanthrene System and Related Species Elucidated by QTAIM Dual Functional Analysis with QC Calculations
**Authors:** Satoko Hayashi; Taro Nishide; Waro Nakanishi
**Journal:** Bioinorganic Chemistry and Applications
(2020)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2020/2901439
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## Abstract
The nature of Br4σ(4c–6e) of the BBr-∗-ABr-∗-ABr-∗-BBr form is elucidated for SeC12H8(Br)SeBr---Br-Br---BrSe(Br)C12H8Se, the selenanthrene system, and the models with QTAIM dual functional analysis (QTAIM-DFA). Asterisks (∗) are employed to emphasize the existence of bond critical points on the interactions in question. Data from the fully optimized structure correspond to the static nature of interactions. In our treatment, data from the perturbed structures, around the fully optimized structure, are employed for the analysis, in addition to those from the fully optimized one, which represent the dynamic nature of interactions. The ABr-∗-ABr and ABr-∗-BBr interactions are predicted to have the CT-TBP (trigonal bipyramidal adduct formation through charge transfer) nature and the typical hydrogen bond nature, respectively. The nature of Se2Br5σ(7c–10e) is also clarified typically, employing an anionic model of [Br-Se(C4H4Se)-Br---Br---Br-Se(C4H4Se)-Br]−, the 1,4-diselenin system, rather than (BrSeC12H8)Br---Se---Br-Br---Br-Se(C12H8Se)-Br, the selenanthrene system.
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## Body
## 1. Introduction
We have been much interested in the behavior of the linear interactions of theσ-type, higher than σ(3c–4e: three center-four electron interactions) [1–6], constructed by the atoms of heavier main group elements. We proposed to call such linear interactions the extended hypervalent interactions, σ(mc–ne: 4 ≤ m; m < n < 2m), after the hypervalent σ(3c–4e). The linear alignments of four chalcogen atoms were first demonstrated in the naphthalene system, bis[8-(phenylchalcogenyl)naphthyl]-1,1′-dichalcogenides [I: 1-(8-PhBEC10H6)AE-AE(C10H6BEPh-8′)-1′ (AE, BE = S and Se)] [7–12]. It was achieved through the preparation and the structural determination by the X-ray crystallographic analysis. The linear BE---AE-AE---BE interactions in I are proposed to be analysed as the EA2EB2σ(4c–6e) model not by the double AEBE2σ(3c–4e) model. EA2EB2σ(4c–6e) in I is characterized by the CT interaction of the np(BE) ⟶ σ∗(AE–AE)←np(BE) form [8, 10–12], where np(BE) stands for the p-type nonbonding orbitals of BE and σ∗(AE-AE) are the σ∗ orbitals of AE-AE. The novel reactivity of EA2EB2σ(4c–6e) in I was also clarified [8].σ(4c–6e) is the first member of σ(mc–ne: 4 ≤ m; m < n < 2m) [7–13]. The σ(4c–6e) interactions are strongly suggested to play an important role in the development of high functionalities in materials and in the key processes of biological and pharmaceutical activities, recently. The bonding is applied to a wide variety of fields, such as crystal engineering, supramolecular soft matters, and nanosciences [4, 14–23]. The nature of BE---AE and AE-AE in BE---AE-AE---BE of EA2EB2σ(4c–6e) has been elucidated [24–27] using the quantum theory of atoms in molecules (QTAIM) approach, introduced by Bader [28–37]. The linear interactions of the σ(4c–6e) type will form if BE in EA2EB2 is replaced by X, giving E2X2σ(4c–6e). The nature of E2X2σ(4c–6e) in the naphthalene system of 1-(8-XC10H6)E-E(C10H6X-8′)-1′ [II (E, X) = (S, Cl), (S, Br), (Se, Cl), and (Se, Br)] was similarly clarified very recently [38].Theσ(4c–6e) interaction will also be produced even if both BE and AE in EA2EB2 are replaced by X. X4σ(4c–6e) should also be stabilized through CT of the np(X) ⟶ σ∗(X-X) ← np(X) form. The energy lowering of the system through the CT interaction must be the driving force for the formation of X4σ(4c–6e). X4σ(4c–6e) is the typical kind of halogen bonds, together with E2X2σ(4c–6e), which are of current and continuous interest [39]. Br4σ(4c–6e) has been clearly established in the selenanthrene system, SeC12H8(Br)SeBr---Br-Br---BrSe(Br)C12H8Se (1), through the preparation and the structural determination by the X-ray crystallographic analysis [39]. The atoms taking part in the linear interaction in question are shown in bold. The structure of (BrSeC12H8)Br---Se---Br-Br---Br-Se(C12H8Se)-Br (2) was also reported, in addition to 1, which is suggested to contain Se2Br5σ(7c–10e) since the seven atoms of Se2Br5 align almost linearly in crystals. Figure 1 shows the structures of 1 and 2 determined by the X-ray analysis and the approximate MO model for σ(4c–6e) and σ(7c–10e).Figure 1
Structure of1 determined by the X-ray crystallographic analysis (a) and the approximate MO model for σ(4c–6e) (b); structure of 2 (c) and the approximate MO model for σ(7c–10e) (d).
(a)(b)(c)(d)It is challenging to elucidate the nature of Br4σ(4c–6e) of the np(Br) ⟶ σ∗(Br-Br)←np(Br) form in 1 and Se2Br5σ(7c–10e) in 2, together with the related species. Figure 2 illustrates the process assumed for the formation of 1 and 2 from selenanthrene (S: SeC12H8Se). In this process, (SeC12H8)Br-Se-Br (3) should be formed first in the reaction of S with Br2, and then 3 reacts with Br2 to yield Br[Se(Br) (C12H8)]Se---Br-Br (4). The almost linear alignment of Br---Se---Br-Br in 4 could be analysed by the SeBr3σ(4c–6e) model, where the Br and Se atoms in 4 are placed in close proximity in space. While 1 containing Br4σ(4c–6e) forms in the reaction of (3 + Br2 + 3), the reaction of 3 + 4 yields 2, consisting Se2Br5σ(7c–10e). Both 1 and 2 are recognized as the Br2-included species. While XC4H4(Br)SeBr---Br-Br---BrSe(Br)C4H4X (5 (X = Se) and 6 (X = S)), models of 1, also consisted of Br4σ(4c–6e), Se2Br5σ(7c–10e) will appear typically in the anionic species, [Br-Se(Me2)-Br---Br---Br-Se(Me2)-Br]− (7) and [Br-Se(SeC4H4)-Br---Br---Br-Se(C4H4Se)-Br]− (8), models of 2. Species, 5, 6, 7, and 8, are shown in Figure 2, where 5, 6, and 8 belong to the 1,4-diselenin system.Figure 2
Process assumed for the formation of Br4σ(4c–6e) in 1 from Se(C12H8)Se (S) via3 and Se2Br5σ(7c–10e) in 2via3 and 4. 5 and 6 with Br4σ(4c–6e), models of 1, and 7 and 8 with Se2Br5σ(7c–10e), models of 2, are also shown. Atoms taking part in the linear interactions are shown by red.What are the differences and similarities between X4σ(4c–6e), E4σ(4c–6e), and E2X2σ(4c–6e)? The nature of X4σ(4c–6e) in 1 (X = Br) is to be elucidated together with the models. Models, other than 5 and 6, are also devised to examine the stabilization sequence of Br4σ(4c–6e). H2Br4 (C2h) and Me2Br4 (C2h) have the form of R-Br---Br-Br---Br-R (RBr4R: R = H and Me), which are called the model group A (G(A)). The electronic efficiency to stabilize Br4σ(4c–6e) seems small for R in G(A). Br6 (C2h) is detected as the partial structure in the crystals of Br2 [40]. Br6 (C2h) in the crystals is denoted by Br6 (C2h)obsd. The optimized structure of Br6 (C2h) has one imaginary frequency, which belongs to G(A), together with Br6 (C2h)obsd. The optimized structure of Br6 retains the C2 symmetry, (Br6 (C2)), which also belongs to G(A). The CT interaction of the np(BBr) ⟶ σ∗(ABr-ABr) ⟵ np(BBr) form in Br4σ(4c–6e) will be much stabilized if the large negative charge is developed at the BBr atoms in Br-(R2)Se-BBr---ABr-ABr---BBr-Se(R2)-Br, where the ∠SeBBrABr is around 90°. The highly negatively charged BBr in Br-Se(R2)-BBr (R = H and Me) of σ(3c–4e) is employed to stabilize Br4σ(4c–6e), in this case. The models form G(B). The nature of Br4σ(4c–6e) in 5 and 6 is similarly analysed, which belongs to G(B). Br42− (D∞h) also belongs to G(B) although one imaginary frequency was predicted for Br42−, if optimized at the MP2 level. Figure 3 illustrates the story for the stabilization of Br4σ(4c–6e) in the sequence of the species, starting from G(A) to 1, via G(B). Figure 3 also shows the ABr-ABr and ABr---BBr distances (r(ABr-ABr) and r(ABr-BBr), respectively), together with the charge developed at BBr in the original species of R-BBr (Qn (BBr)), which construct R-BBr---ABr-ABr---BBr-R.Figure 3
Sequence in the stabilization of Br4σ(4c–6e), starting from those in G(A) to 1 via those of G(B).A chemical bond or interaction between atoms A and B is denoted by A-B, which corresponds to a bond path (BP) in the quantum theory of atoms in molecules (QTAIM) approach, introduced by Bader [28–37]. We will use A-∗-B for BP, where the asterisk emphasizes the existence of a bond critical point (BCP, ∗) in A-B [28, 29]. (Dots are usually employed to show BCPs in molecular graphs. Therefore, A-•-B would be more suitable to describe the BP with a BCP. Nevertheless, A-∗-B is employed to emphasize the existence of a BCP on the BP in question in our case. BCP is a point along BP at the interatomic surface, where ρ(r) (charge density) reaches a minimum along the interatomic (bond) path, while it is a maximum on the interatomic surface separating the atomic basins). The chemical bonds and interactions are usually classified by the signs of Laplacian rho (∇2ρb(rc)) and Hb(rc) at BCPs, where ρb(rc) and Hb(rc) are the charge densities and total electron energy densities at BCPs, respectively (see Scheme S1 in Supplementary File). The relations between Hb(rc), ∇2ρb(rc), Gb(rc) (the kinetic energy densities), and Vb(rc) (the potential energy densities) are represented in equations (1) and (2):(1)Hbrc=Gbrc+Vbrc,(2)ℏ28m∇2ρbrc=Hbrc−Vbrc2=Gbrc+Vbrc2.How can the nature of Br4σ(4c–6e) and Se2Br5σ(7c–10e) be clarified? For the characterization of interactions in more detail, we recently proposed QTAIM dual functional analysis (QTAIM-DFA) [42–47] for experimental chemists to analyze their own chemical bonds and interaction results based on their own expectations, according to the QTAIM approach [28–37]. Hb(rc) is plotted versus Hb(rc) − Vb(rc)/2 (= (ћ2/8m)∇2ρb(rc)) at BCPs in QTAIM-DFA. The classification of interactions by the signs of ∇2ρb(rc) and Hb(rc) is incorporated in QTAIM-DFA. Data from the fully optimized structures correspond to the static natures of the interactions, which are analysed using the polar coordinate (R, θ), representation [42, 44–46]. Each interaction plot, containing data from both the perturbed structures and the fully optimized one include a specific curve that provides important information about the interaction. This plot is expressed by (θp, κp), where θp corresponds to the tangent line of the plot and κp is the curvature. The concept of the dynamic nature of interactions has been proposed based on (θp, κp) [42, 44]. θ and θp are measured from the y-axis and the y-direction, respectively. We call (R, θ) and (θp, κp) QTAIM-DFA parameters, which are drawn in Figure 4, exemplified by Br42− (D∞h). While (R, θ) classifies the interactions, (θp, κp) characterizes them.Figure 4
QTAIM-DFA plots ofHb(rc) versus Hb(rc) − Vb(rc)/2 for ABr-∗-ABr (a) and ABr-∗-BBr (b) in Br4σ(4c–6e) of the species in Table 1, together with those of the perturbed structures generated with CIV. Marks and colours for the species are shown in the figure.
(a)(b)We proposed a highly reliable method to generate the perturbed structures for QTAIM-DFA very recently [48]. The method is called CIV, which employs the coordinates derived from the compliance force constants Cij for the internal vibrations. Compliance force constants Cij are defined as the partial second derivatives of the potential energy due to an external force, as shown in equation (3), where i and j refer to the internal coordinates and the force constants fi and fj correspond to i and j, respectively. The Cij values and the coordinates corresponding to the values can be calculated using the compliance 3.0.2 program, released by Brandhorst and Grunenberg [49–52]. The dynamic nature of interactions based on the perturbed structures with CIV is described as the “intrinsic dynamic nature of interactions” since the coordinates are invariant to the choice of the coordinate system:(3)Cij=∂2E∂fi∂fj.QTAIM-DFA has excellent potential for evaluating, classifying, characterizing, and understanding weak to strong interactions according to a unified form. The superiority of QTAIM-DFA to elucidate the nature of interactions, employing the perturbed structures generated with CIV, is explained in the previous papers [48, 53] (see also Figure S2 and Table S2 in Supplementary File). QTAIM-DFA is applied to standard interactions and rough criteria that distinguish the interaction in question from others which are obtained. QTAIM-DFA and the criteria are explained in Supplementary File using Schemes S1–S3, Figures S1 and S2, Table S1, and equations (S1)–(S7). The basic concept of the QTAIM approach is also explained.We consider QTAIM-DFA, employing the perturbed structures generated with CIV, to be well suited to elucidate the nature of Br4σ(4c–6e) in 1, Se2Br5σ(7c–10e) in 2, and the models derived from 1 and 2, together with the related linear interactions. The interactions in Br4σ(4c–6e) are denoted by BBr-∗-ABr-∗-ABr-∗-BBr, where the asterisk emphasizes the existence of a BCP in the interactions, so are those in Se2Br5σ(7c–10e). Herein, we present the results of the investigations on the extended hypervalent interactions in the species, together with the structural feature. Each interaction is classified and characterized, employing the criteria as a reference.
## 2. Methodological Details in Calculations
Calculations were performed employing the Gaussian 09 programs package [54]. The basis sets employed for the calculations were obtained, as implemented from Sapporo Basis Set Factory [55]. The basis sets of the (621/31/2), (6321/621/3), (74321/7421/72), and (743211/74111/721/2+1s1p) forms were employed for C, S, Se, and Br, respectively, with the (31/3) form for H. The basis set system is called BSS-A. All species were calculated employing BSS-A, and the Møller–Plesset second-order energy correlation (MP2) level [56–58] was applied for the optimizations. Optimized structures were confirmed by the frequency analysis. The results of the frequency analysis were used to calculate the Cij values and the coordinates (Ci) corresponding to the values. The DFT level of CAM-B3LYP [59] was also applied when necessary. The QTAIM functions were analysed with the AIM2000 [60] and AIMAll [61] programs.The method to generate perturbed structures with CIV is the same as that explained in the previous papers [48, 53]. As shown in equation (4), the i-th perturbed structure in question (Siw) is generated by the addition of the i-th coordinates (Ci), derived from Cij, to the standard orientation of a fully optimized structure (So) in the matrix representation. The coefficient fiw in equation (4) controls the structural difference between Siw and So: fiw is determined to satisfy equation (5) for r, where r and ro stand for the interaction distances in question in the perturbed and fully optimized structures, respectively, with ao = 0.52918 Å (Bohr radius). The Ci values of five digits are used to predict Siw:(4)Siw=So+fiw⋅Ci,(5)r=ro+wao,w=0,±0.05,and±0.1;ao=0.52918Å,(6)y=co+c1x+c2x2+c3x3,Rc2:square of correlation coefficient.In QTAIM-DFA,Hb(rc) is plotted versus Hb(rc) − Vb(rc)/2 for data of w = 0, ±0.05, and ±0.10 in equation (5). Each plot is analysed using a regression curve of the cubic function, as shown in equation (6), where (x, y) = (Hb(rc) − Vb(rc)/2 and Hb(rc)) (Rc2 (square of correlation coefficient) > 0.99999 in usual) [46].
## 3. Results and Discussion
### 3.1. Structural Optimizations
The structures of1 (Ci) and 2 (C1) determined by the X-ray analysis are denoted by 1 (Ci)obsd and 2 (C1)obsd, respectively [39]. The structural parameters are shown in Tables S2 and S3 in Supplementary File, respectively. Figure 3 contains the selected structural parameters for 1 (Ci)obsd. The structures are optimized for G(A) of H2Br4 (C2h), Me2Br4 (C2h), Br6 (C2h), and Br6 (C2) and G(B) of H4Se2Br6 (Ci), Me4Se2Br6 (Ci), 5 (Ci), and 6 (Ci), together with 3 (Cs), 4 (Cs), 7 (C2h), 8 (C2h), and Br2 (D∞h). The optimized structural parameters are also collected in Tables S2 and S3 in Supplementary File. The frequency analysis was successful for the optimized structures, except for 1 (Ci)obsd and Br6 (C2h). All positive frequencies were obtained for 1 (Ci), if calculated with CAM-B3LYP/BSS-A, which confirms the structure. The Br---Br distances of Br4σ(4c–6e) in 1 (Ci) are somewhat longer if optimized at the CAM-B3LYP level, relative to 1 (Ci)obsd. While one imaginary frequency is detected in Br6 (C2h), Br6 (C2) has all positive frequencies. The optimized structures are not shown in figures, instead, some of them can be found in Figures 3 and 5, where the molecular graphs are drawn on the optimized structures. Figure 3 contains the optimized r(ABr-ABr) and r(ABr-BBr) distances for the models and the charge developed at BBr in the original R-BBr and Br-(R2)Se-BBr (Qn (BBr)), which give the models of G(A) and G(B), respectively. The r(ABr-BBr) values become shorter in the order shown in equation (7), if evaluated with MP2/BSS-A:(7)rBAr−BBr:H2Br4C2h>1CiCAM>Br6C2andC2h>Br6C2hobsd40>Me2Br4C2h>Br42−D∞h>1Ciobsd≥Me4Se2Br6Ci≥H4Se2Br6Ci>5Ci≥6Ci.Figure 5
Molecular graphs of5 (Ci) (a), 6 (Ci) (b), 7 (C2h) (c), and 8 (C2h) (d) drawn on the structures optimized at the MP2 level, together with 1 (Ci)obsd (e) and 2 (C1)obsd (f). Contour plots of ρ(r) are also drawn on the planes containing the linear interactions. BCPs are denoted by red dots, RCPs (ring critical points) by yellow dots, and CCPs (cage critical points) by green dots. BPs (bond paths) are drawn as pink lines and the secondary ones as pink dots. They are associated with the BCPs. Carbon and hydrogen atoms are shown in black and gray, respectively. The contours (eao−3) are at 2l (l = ±8, ±7, …, and 0).
(a)(b)(c)(d)(e)(f)One imaginary frequency was also predicted forBr42− (D∞h) if optimized with MP2/BSS-A. Br42− (D∞h) seems to collapse to Br3− and Br−, according to the imaginary frequency. The double negative charges in Br42− (D∞h) would be responsible for the results. The electrostatic repulsion between the double negative charges will operate to collapse it.
### 3.2. Energies for Formation of Br4σ(4c–6e) and NBO Analysis
Energies for the formation of R′Br4R′ from the components (2R′Br + Br2) (ΔE) are defined by equation (8). The ΔE values evaluated on the energy surface are denoted by ΔEES, while those corrected with the zero-point energies are by ΔEZP. The ΔEES and ΔEZP values for the optimized structures are given in Table S2 in Supplementary File. ΔEZP are excellently correlated to ΔEES (ΔEZP = 0.99ΔEES + 1.93: Rc2 = 0.9998, see Figure S3 in Supplementary File):(8)ΔER2′Br4=ER2′Br4−2ER′Br+EBr2,(9)E2=qi×Fi,j2εj−εi.NBO analysis [62] was applied to ABr---BBr of the species to evaluate the contributions from CT to stabilize R′-BBr---ABr-ABr---BBr-R′. For each donor NBO (i) and acceptor NBO (j), the stabilization energy E(2) is calculated based on the second-order perturbation theory in NBO, according to equation (9), where qi is the donor orbital occupancy, εi and εj are diagonal elements (orbital energies), and F(i, j) is the off-diagonal NBO Fock matrix element. The results are collected in Table S4 in Supplementary File. The ΔEES values are very well correlated to E(2) for the optimized structures, except for Br42− (D∞h). (ΔEES = –0.71(2E(2)) + 7.17: Rc2 = 0.959, see Figure S4 in Supplementary File). Br42− (D∞h) is predicted to be less stable than the components.Before application of QTAIM-DFA to Br4σ(4c–6e) and Se2Br5σ(7c–10e), molecular graphs were examined, as shown in the next section.
### 3.3. Molecular Graphs with Contour Plots for the Species Containing Br4σ(4c–6e), Se2Br5σ(7c–10e), and Related Linear Interactions
Figure5 illustrates the molecular graphs of 5 (Ci), 6 (Ci), 7 (C2h), and 8 (C2h), drawn on the optimized structures, together with 1 (Ci)obsd and 2 (C1)obsd. Figure 5 also shows the contour plots of ρ(r) drawn on the suitable plane in the molecular graphs. BCPs are well demonstrated to locate on the (three-dimensional) saddle points of ρ(r). Molecular graphs of Me2Br4 (C2h), Br6 (C2), Br42− (D∞h), and Br(Me2)SeBr4Se(Me2)Br (Ci) are shown in Figure 3, which are drawn on the optimized structures.
### 3.4. Survey of Br4σ(4c–6e) and Se2Br5σ(7c–10e)
BPs in Br4σ(4c–6e) and Se2Br6σ(7c–10e) seem straight, as shown in Figures 3 and 5. To show the linearity more clearly, the lengths of BPs (rBP) for Br4σ(4c–6e) are calculated. The values are collected in Table S5 in Supplementary File, together with the corresponding straight-line distances (RSL). The table contains the values for Se2Br6σ(7c–10e) in 7 (C2h) and 8 (C2h). The differences between them (ΔrBP = rBP–RSL) are less than 0.003 Å. The rBP values are plotted versus RSL, which are shown in Figure S5 in Supplementary File. The correlations are excellent, as shown in the figure. Therefore, Br4σ(4c–6e) and Se2Br6σ(7c–10e) in the species can be approximated by the straight lines.Table 1
QTAIM functions and QTAIM-DFA parameters forBBr-∗-ABr-∗-A′Br-∗-B′Br at BCPs in Br4σ(4c–6e), together with ABr-∗-ABr in Br2, evaluated with MP2/BSS-Aa).
Species (symmetry)Interaction X-∗-Yρb(rc) (eao−3)c∇2ρb(rc)b) (au)Hb(rc) (au)kb(rc)c)Rd) (au)θe) (°)Cij (Å mdyn−1)θp:CIVf) (°)κp:CIVg) (au−1)Predicted natureBr2 (D∞h)h)Br-∗-Br0.1130−0.0001−0.0497−2.0050.0497180.10.4191.81.8SS/Cov-wi)Br42− (D∞h)j)ABr-∗-ABr0.09220.0052−0.0313−1.7510.0317170.60.8190.63.6r-CS/CT-TBPk)ABr-∗-BBr0.01980.00580.0001−0.9950.005889.5−19.6118.2146p-CS/t-HBncl)Br6 (C2)ABr-∗-ABr0.10990.0010−0.0466−1.9600.0467178.80.4191.32.3r-CS/CT-TBPk)ABr-∗-BBr0.01310.00490.0009−0.8990.005079.614.397.8105p-CS/t-HBncl)Br6 (C2h)m)ABr-∗-ABr0.10990.0010−0.0466−1.9610.0467178.80.4191.71.7r-CS/CT-TBPk)ABr-∗-BBr0.01310.00490.0009−0.8990.005079.614.397.697p-CS/t-HBncl)Br6 (C2h)obsdn)ABr-∗-ABr0.07650.0053−0.0200−1.6540.0207165.2r-CSABr-∗-BBr0.01560.00550.0007−0.9290.005582.5p-CSH2Br4 (C2h)ABr-∗-ABr0.11010.0008−0.0468−1.9660.0468179.00.4191.72.0r-CS/CT-TBPk)ABr-∗-BBr0.01180.00450.0010−0.8810.004678.015.594.7100p-CS/t-HBncl)Me2Br4ABr-∗-ABr0.10760.0016−0.0444−1.9320.0445177.90.4191.41.8r-CS/CT-TBPk)ABr-∗-BBr0.01640.00570.0006−0.9450.005784.110.5105.1100p-CS/t-HBncl)H4Se2Br6 (Ci)ABr-∗-ABr0.10280.0031-0.0400−1.8660.0401175.60.5191.52.5r-CS/CT-TBPk)ABr-∗-BBr0.02200.0068−0.0002−1.0160.006891.99.9117.475r-CS/t-HBwco)Me4Se2Br6 (Ci)ABr-∗-ABr0.10280.0032−0.0400−1.8620.0402175.40.5191.43.7r-CS/CT-TBPk)ABr-∗-BBr0.02120.0067−0.0001−1.0080.006790.99.9116.4101r-CS/t-HBwco)5 (Ci)p)ABr-∗-ABr0.10160.0036−0.0389−1.8440.0391174.70.5191.54.4r-CS/CT-TBPk)ABr-∗-BBr0.02260.0070−0.0003−1.0230.007092.76.8118.0557r-CS/t-HBwco)ABr-∗-BBrq)0.02260.0070−0.0003−1.0230.007092.76.8118.0551r-CS/t-HBwco)5 (Ci)r)ABr-∗-ABr0.10470.0020−0.0383−1.9050.0384177.00.5191.32.5r-CS/CT-TBPk)ABr-∗-BBr0.01450.00480.0008−0.9040.004880.115.997.4102p-CS/t-HBnco)6 (Ci)ABr-∗-ABr0.10140.0037−0.0388−1.8410.0389174.60.5191.536r-CS/CT-TBPk)ABr-∗-ABrq)0.10140.0037−0.0388−1.8410.0389174.60.5191.636r-CS/CT-TBPk)ABr-∗-BBrq)0.02270.0070−0.0004−1.0240.007192.842.1122.52474r-CS/t-HBwco)6 (Ci)r)ABr-∗-ABr0.10440.0021−0.0380−1.9010.0381176.90.5191.32.6r-CS/CT-TBPk)ABr-∗-BBr0.01470.00480.0008−0.9070.004980.316.697.8103p-CS/t-HBnco)1 (Ci)r)ABr-∗-ABr0.10630.0013−0.0398−1.9390.0398178.10.5191.72.3r-CS/CT-TBPk)ABr-∗-BBr0.01230.00430.0010−0.8680.004476.918.391.8100p-CS/t-HBncl)1 (Ci)obsds)ABr-∗-ABr0.10190.0032−0.0393−1.8600.0394175.3r-CSABr-∗-BBr0.02000.00660.0003−0.9790.006687.7p-CSa)See the text for BSS. b)c∇2ρb(rc) = Hb(rc) − Vb(rc)/2, where c = ћ2/8m. c)kb(rc) = Vb(rc)/Gb(rc). d)R = (x2 + y2)1/2, where (x, y) = (Hb(rc) − Vb(rc)/2, Hb(rc)). e)θ = 90° − tan−1 (y/x).f)θp = 90°– tan−1(dy/dx). g)κp = |d2y/dx2|/[1 + (dy/dx)2]3/2. h)The Br-Br distance in Br2 was optimized to be 2.2756 Å with MP2/BSS-A, which was very close to the observed distance in the gas phase (2.287 Å) [63]. However, the values are shorter than those determined by the X-ray crystallographic analysis (2.491 Å) [40] by 0.210 Å. The noncovalent Br---Br distance is 3.251 Å in crystal, which is shorter than the sum of the van der Waals radii [64] by 0.45 Å. i)The SS interaction of the weak covalent nature. j)With one imaginary frequency for the vibration mode of the SGU symmetry. k)The regular-CS interaction of the CT-TBP nature. l)The pure-CS interaction of the HB nature with no covalency. m)With one imaginary frequency for the rotational mode around the linear Br4 interaction. n)See ref. [40] o)The regular-CS interaction of the HB nature with covalency. p)With one imaginary frequency for the vibration mode of the AU symmetry. q)w = (0), ±0.025, and ±0.05. r)At the CAM-B3LYP level. s)See ref. [39].QTAIM functions are calculated for Br4σ(4c–6e) at BCPs. Table 1 collects the values for the interactions. Hb(rc) is plotted versus Hb(rc) − Vb(rc)/2 for the data shown in Table 1, together with those from the perturbed structures generated with CIV. Figure 4 shows the plots for the ABr-∗-ABr and ABr-∗-BBr interactions in Br4σ(4c–6e) of the bromine species. The plots for ABr-∗-ABr appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) < 0, for all species, except for the original Br2 (D∞h), of which the plot appears in the region of Hb(rc) − Vb(rc)/2 < 0 and Hb(rc) < 0. Therefore, the interactions are all classified by the regular-CS (closed shell) interactions, except for Br2 (D∞h), which is classified by the SS (shard shell) interaction. On the contrary, data of ABr-∗-BBr appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) > 0 for all species, except for those in H4Se2Br6 (Ci), Me4Se2Br6 (Ci), 5 (Ci), and 6 (Ci), which appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) < 0. As a result, ABr-∗-BBr is classified by the pure-CS interactions (p-CS) for all, except for the four species, of which ABr-∗-BBr is classified by the regular-CS interactions (r-CS). The ABr-∗-BBr interaction in Br42− (D∞h) is very close to the borderline between p-CS and r-CS since Hb(rc) = 0.0001 au for Br42− (D∞h), which is very close to zero. QTAIM-DFA parameters of (R, θ) and (θp, κp) are obtained by analysing the plots of Hb(rc) versus Hb(rc) − Vb(rc)/2 in Figure 4, according to equations (S3)–(S6). Table 1 collects the QTAIM-DFA parameters for Br4σ(4c–6e). The classification of interactions will also be discussed based on the (R, θ) values.QTAIM functions are similarly calculated for Se2Br6σ(7c–10e) at BCPs, together with the related interactions. Hb(rc) is similarly plotted versus Hb(rc) − Vb(rc)/2 although not shown in the figures. Then, QTAIM-DFA parameters of (R, θ) and (θp, κp) are obtained by analysing the plots, according to equations (S3)–(S6). Table 2 collects the QTAIM-DFA parameters of (R, θ) and (θp, κp) for Br4σ(4c–6e).Table 2
QTAIM functions and QTAIM-DFA parameters forABr-∗-ASe-∗-BBr-∗-CBr-∗-DBr-∗-BSe-∗-EBr at BCPs in 7 (C2h), 8 (C2h), and 2 (C1)obsd, together with ABr-∗-ASe-∗-BBr in 3 (Cs) and ABr-∗-ASe-∗-BBr-∗-CBr-∗-DBr in 4 (Cs), evaluated with MP2 BSS‐Aa).
Species (symmetry)Interaction X-∗-Yρb(rc) (eao−3)c∇2ρb(rc)b) (au)Hb(rc) (au)kb(rc)c)Rd) (au)θe) (°)Cij (Å mdyn−1)θp:CIVf) (°)κp:CIVg) (au−1)Predicted nature7 (C2h)ASe-∗-ABrh)0.04230.0080−0.0056−1.2580.0098124.86.3169.955r-CS/CT-MCi)ASe-∗-BBrj)0.08250.0043−0.0264−1.7530.0267170.71.2192.22.2r-CS/CT-TBPk)BBr-∗-CBrl)0.03350.0086−0.0022−1.1150.0088104.69.4145.5102r-CS/t-HBwcm)8 (C2h)ASe-∗-ABrh)0.04920.0085−0.0079−1.3180.0116133.02.3172.753r-CS/CT-MCi)ASe-∗-BBrj)0.06620.0075−0.0158−1.5130.0175154.62.2187.717r-CS/CT-TBPk)BBr-∗-CBrl)0.03980.0092−0.0038−1.1710.0100112.54.2151.554r-CS/t-HBwcm)2 (C1)obsdn)ABr-∗-ASe0.02190.0065−0.0005−1.0390.006594.6r-CSASe-∗-BBr0.05760.0102−0.0113−1.3560.0152137.8r-CSBBr-∗-CBr0.09520.0068−0.0337−1.7130.0343168.6r-CSCBr-∗-DBr0.01830.00620.0005−0.9610.006285.7p-CSDBr-∗-BSe0.08180.0063−0.0271−1.6820.0278166.9r-CSBSe-∗-EBr0.07530.0072−0.0220−1.6040.0231161.9r-CS3 (Cs)ABr-∗-ASe0.07370.0061−0.0214−1.6360.0223164.00.8185.88.4r-CS/CT-TBPk)ASe-∗-BBr0.06780.0069−0.0177−1.5620.0189158.71.0183.018r-CS/CT-TBPk)4 (Cs)ABr-∗-ASe0.01310.00420.0004−0.9450.004284.06.4105.184p-CS/t-HBnco)ASe-∗-BBr0.04250.0088−0.0052−1.2290.0103120.64.6163.263r-CS/CT-MCi)BBr-∗-CBr0.09330.0059−0.0321−1.7320.0326169.60.9192.15.6r-CS/CT-TBPk)a)See the text for BSS. b)c∇2ρb(rc) = Hb(rc) − Vb(rc)/2, where c = ћ2/8m. c)kb(rc) = Vb(rc)/Gb(rc). d)R = (x2 + y2)1/2, where (x, y) = (Hb(rc) − Vb(rc)/2, Hb(rc)). e)θ = 90° − tan−1 (y/x). f)θp = 90° − tan−1 (dy/dx). g)κp = |d2y/dx2|/[1 + (dy/dx)2]3/2. h)Because it has Ci symmetry, it is the same as BSe-∗-EBr. i)The regular-CS interaction of the CT-MC nature. j)The same as BSe-∗-DBr. k)The regular-CS interaction of the CT-TBP nature. l)The same as CBr-∗-DBr. m) The pure-CS interaction of the HB nature with no covalency. n)See ref. [39]. o)The regular-CS interaction of the HB nature with no covalency.
### 3.5. Nature of Br4σ(4c–6e)
Interactions are characterized by (R, θ), which correspond to the data from the fully optimized structures. On the contrary, they are characterized employing (θp, κp) derived from the data of the perturbed structures around the fully optimized structures and the fully optimized ones. In this case, the nature of interactions is substantially determined based of the (R, θ, θp) values, while the κp values are used only additionally. It is instructive to survey the criteria before detail discussion. The criteria tell us that 180° < θ (Hb(rc) − Vb(rc)/2 < 0) for the SS interactions, 90° < θ < 180° (Hb(rc) < 0) for the r-CS interactions, and 45° < θ < 90° (Hb(rc) > 0) for p-CS interactions. The θp value characterizes the interactions. In the p-CS region of 45° < θ < 90°, the character of interactions will be the vdW type for 45° < θp < 90°, whereas it will be the typical HB type without covalency (t-HBnc) for 90° < θp < 125°, where θp = 125° is tentatively given for θ = 90°. The CT interaction will appear in the r-CS region of 90° < θ < 180°. The t-HB type with covalency (t-HBwc) appears in the region of 125° < θp < 150° (90° < θ < 115°), where (θ, θp) = (115°, 150°) is tentatively given as the borderline between t-HBwc and the CT-MC nature. The borderline for the interactions between CT-MC and CT-TBP types is defined by θp = 180°. θ = 150° is tentatively given for θp = 180°. Classical chemical bonds of SS (180° < θ) will be strong (Cov-s) when R > 0.15 au, whereas they will be weak (Cov-w) for R < 0.15 au. The classification and characterization of interactions are summarized in Table S1 and Scheme S3 in Supplementary File.TheABr-∗-ABr and ABr-∗-BBr interactions of Br4σ(4c–6e) will be classified and characterized based on the (R, θ, θp) values, employing the standard values as a reference (see Scheme S2 in Supplementary File). R < 0.15 au for all interactions in Table 1; therefore, no Cov-s were detected in this work. The (θ, θp) values are (180.1°, 191.8°) for the original Br2 (D∞h) if evaluated with MP2/BSS-A. Therefore, the nature of Br-∗-Br in Br2 (D∞h) is classified by the SS interactions and characterized as the Cov-w nature, which is denoted by SS/Cov-w. The (θ, θp) values are (170.6–179.0°, 190.6–191.7°) for ABr-∗-ABr of Br4σ(4c–6e) in the optimized structures in Table 1, of which nature is r-CS/CT-TBP. The (θ, θp) values are (78.0–84.1°, 94.7–105.1°) for ABr-∗-BBr in the optimized structures of Br6 (C2), Br6 (C2h), and R2Br4 (C2h) (R = H and Me); therefore, the nature is predicted to be r-CS/t-HBwc. The nature of ABr-∗-BBr in R4Se2Br6 (Ci) (R = H and Me), 5 (Ci) and 6 (Ci), is r-CS/t-HBwc, judging from the (θ, θp) values of (90.9–92.8°, 116.4–122.5°). The calculated (θ, θp) values of ABr-∗-ABr and ABr-∗-BBr for the optimized structure of Br42− (D∞h) are (170.6°, 190.6°) and (89.5°, 118.2°), respectively. In this case, ABr-∗-ABr and ABr-∗-BBr are predicted to have the nature of r-CS/CT-TBP and p-CS/t-HBnc, respectively. However, ABr-∗-BBr is just the borderline region to the r-CS interactions with θ = 89.5°. The characteristic nature of the BE---AE-AE---BE interactions in Br42− (D∞h) would be controlled by the double negative charges in the species.The results in Table1 show that the ABr-∗-ABr interaction in Br4σ(4c–6e) becomes weaker, as the strength of the corresponding ABr-∗-BBr increases. The strength of ABr-∗-ABr becomes weaker in the order shown in equation (10), if evaluated by θ, while that of ABr-∗-BBr increases in the order shown in equation (11), if measured by θ. Very similar results were obtained by θp:(10)θforABr−∗−ABr:Br2D∞h>H2Br4C2h≥Br6C2andC2h>Me2Br4C2h>H4Se2Br6Ci≥Me4Se2Br6Ci≥1Ciobsd>5Ci>6Ci>Br6C2hobsd,(11)θforABr−∗−BBr:H2Br4C2h>Br6C2handC2≥Br6C2hobsd>Me2Br4C2h<1Ciobsd<Me4Se2Br6Ci<H4Se2Br6Ci<5Ci≈6Ci.The orders shown in equations (10) and (11) seem to reasonably explain the characteristic behavior of Br4σ(4c–6e). The results must be the reflection of the np(BBr) ⟶ σ∗(ABr-ABr) ← np(BBr) form of Br4σ(4c–6e), where ABr-∗-ABr and ABr-∗-BBr become weaker and stronger, respectively, as the CT interaction increases. Br4σ(4c–6e) will be stabilized more effectively, if the negative charge is developed more at BBr. However, the two Br− ligands in Br42− (D∞h) seem not so effective than that expected. This would come from the electrostatic repulsive factor between the double negative charges in Br42− (D∞h), as mentioned above.Theθ values for (ABr-∗-ABr and ABr-∗-BBr) in Br6 (C2h)obsd and 1 (Ci)obsd are (165.2°, 82.5°) and (175.3°, 87.7°), respectively. Therefore, ABr-∗-ABr and ABr-∗-BBr are classified by r-CS and p-CS, respectively. Both ABr-∗-ABr and ABr-∗-BBr in Br6 (C2h)obsd are predicted to be weaker than those in 1 (Ci)obsd, respectively. The results would be curious at the first glance, since ABr-∗-ABr will be weaker, if ABr-∗-BBr in BBr-∗-ABr-∗-ABr-∗-BBr becomes stronger, as mentioned above. They would be affected from the surrounding, such as the crystal packing effect. A Br2 molecule interacts with four bromine atoms adjacent to the Br2 molecule on the bc-plane in crystals, equivalently with 3.251 Å [40].Similar investigations were carried out for I4σ(4c–6e), which will be discussed elsewhere (it is demonstrated that Br4σ(4c–6e) is predicted to be somewhat stronger than I4σ(4c–6e)).
### 3.6. Nature of Se2Br5σ(7c–10e)
The nature of Se2Br5σ(7c–10e) in 7 (C2h) and 8 (C2h) is elucidated, together with SeBr2σ(3c–4e) in 3 and SeBr4σ(4c–6e) in 4. The results are collected in Table 2. Figure 6 shows symmetric ψ184 (HOMO) and antisymmetric ψ185 (LUMO) of 8 (C2h), which correspond to ψ5 and ψ6 in σ(7c–10e), illustrated in Figure 1 although the Se atoms are contained in the linear Se2Br5σ(7c–10e) in 8 (C2h). The linear seven atomic orbitals on Se2Br5 are shown to construct ψ184 (HOMO) and ψ185 (LUMO) of 8 (C2h), which can be analysed as the Se2Br5σ(7c–10e) [39], so can the linear interaction in 7 (C2h), although not shown. The pseudolinear interaction of the seven atoms of 1 (C1)obsd could also be explained by the Se2Br5σ(7c–10e) model.Figure 6
Molecular orbitals forσ(7c–10e). ψ184 (HOMO) and ψ185 (LUMO) of 8 (C2h).The results demonstrate that Se2Br5σ(7c–10e) stabilize well 7 (C2h) and 8 (C2h) although 1 (C1)obsd seems not so effective. The negative charge developed at the Br atom in 3 would not be sufficient to stabilize Se2Br5σ(7c–10e) in 1 (C1)obsd, relative to the case of the Br− anion in 7 (C2h) and 8 (C2h), irrespective of the highly negatively charged Br atoms in SeBr2σ(3c–4e) of 3.
## 3.1. Structural Optimizations
The structures of1 (Ci) and 2 (C1) determined by the X-ray analysis are denoted by 1 (Ci)obsd and 2 (C1)obsd, respectively [39]. The structural parameters are shown in Tables S2 and S3 in Supplementary File, respectively. Figure 3 contains the selected structural parameters for 1 (Ci)obsd. The structures are optimized for G(A) of H2Br4 (C2h), Me2Br4 (C2h), Br6 (C2h), and Br6 (C2) and G(B) of H4Se2Br6 (Ci), Me4Se2Br6 (Ci), 5 (Ci), and 6 (Ci), together with 3 (Cs), 4 (Cs), 7 (C2h), 8 (C2h), and Br2 (D∞h). The optimized structural parameters are also collected in Tables S2 and S3 in Supplementary File. The frequency analysis was successful for the optimized structures, except for 1 (Ci)obsd and Br6 (C2h). All positive frequencies were obtained for 1 (Ci), if calculated with CAM-B3LYP/BSS-A, which confirms the structure. The Br---Br distances of Br4σ(4c–6e) in 1 (Ci) are somewhat longer if optimized at the CAM-B3LYP level, relative to 1 (Ci)obsd. While one imaginary frequency is detected in Br6 (C2h), Br6 (C2) has all positive frequencies. The optimized structures are not shown in figures, instead, some of them can be found in Figures 3 and 5, where the molecular graphs are drawn on the optimized structures. Figure 3 contains the optimized r(ABr-ABr) and r(ABr-BBr) distances for the models and the charge developed at BBr in the original R-BBr and Br-(R2)Se-BBr (Qn (BBr)), which give the models of G(A) and G(B), respectively. The r(ABr-BBr) values become shorter in the order shown in equation (7), if evaluated with MP2/BSS-A:(7)rBAr−BBr:H2Br4C2h>1CiCAM>Br6C2andC2h>Br6C2hobsd40>Me2Br4C2h>Br42−D∞h>1Ciobsd≥Me4Se2Br6Ci≥H4Se2Br6Ci>5Ci≥6Ci.Figure 5
Molecular graphs of5 (Ci) (a), 6 (Ci) (b), 7 (C2h) (c), and 8 (C2h) (d) drawn on the structures optimized at the MP2 level, together with 1 (Ci)obsd (e) and 2 (C1)obsd (f). Contour plots of ρ(r) are also drawn on the planes containing the linear interactions. BCPs are denoted by red dots, RCPs (ring critical points) by yellow dots, and CCPs (cage critical points) by green dots. BPs (bond paths) are drawn as pink lines and the secondary ones as pink dots. They are associated with the BCPs. Carbon and hydrogen atoms are shown in black and gray, respectively. The contours (eao−3) are at 2l (l = ±8, ±7, …, and 0).
(a)(b)(c)(d)(e)(f)One imaginary frequency was also predicted forBr42− (D∞h) if optimized with MP2/BSS-A. Br42− (D∞h) seems to collapse to Br3− and Br−, according to the imaginary frequency. The double negative charges in Br42− (D∞h) would be responsible for the results. The electrostatic repulsion between the double negative charges will operate to collapse it.
## 3.2. Energies for Formation of Br4σ(4c–6e) and NBO Analysis
Energies for the formation of R′Br4R′ from the components (2R′Br + Br2) (ΔE) are defined by equation (8). The ΔE values evaluated on the energy surface are denoted by ΔEES, while those corrected with the zero-point energies are by ΔEZP. The ΔEES and ΔEZP values for the optimized structures are given in Table S2 in Supplementary File. ΔEZP are excellently correlated to ΔEES (ΔEZP = 0.99ΔEES + 1.93: Rc2 = 0.9998, see Figure S3 in Supplementary File):(8)ΔER2′Br4=ER2′Br4−2ER′Br+EBr2,(9)E2=qi×Fi,j2εj−εi.NBO analysis [62] was applied to ABr---BBr of the species to evaluate the contributions from CT to stabilize R′-BBr---ABr-ABr---BBr-R′. For each donor NBO (i) and acceptor NBO (j), the stabilization energy E(2) is calculated based on the second-order perturbation theory in NBO, according to equation (9), where qi is the donor orbital occupancy, εi and εj are diagonal elements (orbital energies), and F(i, j) is the off-diagonal NBO Fock matrix element. The results are collected in Table S4 in Supplementary File. The ΔEES values are very well correlated to E(2) for the optimized structures, except for Br42− (D∞h). (ΔEES = –0.71(2E(2)) + 7.17: Rc2 = 0.959, see Figure S4 in Supplementary File). Br42− (D∞h) is predicted to be less stable than the components.Before application of QTAIM-DFA to Br4σ(4c–6e) and Se2Br5σ(7c–10e), molecular graphs were examined, as shown in the next section.
## 3.3. Molecular Graphs with Contour Plots for the Species Containing Br4σ(4c–6e), Se2Br5σ(7c–10e), and Related Linear Interactions
Figure5 illustrates the molecular graphs of 5 (Ci), 6 (Ci), 7 (C2h), and 8 (C2h), drawn on the optimized structures, together with 1 (Ci)obsd and 2 (C1)obsd. Figure 5 also shows the contour plots of ρ(r) drawn on the suitable plane in the molecular graphs. BCPs are well demonstrated to locate on the (three-dimensional) saddle points of ρ(r). Molecular graphs of Me2Br4 (C2h), Br6 (C2), Br42− (D∞h), and Br(Me2)SeBr4Se(Me2)Br (Ci) are shown in Figure 3, which are drawn on the optimized structures.
## 3.4. Survey of Br4σ(4c–6e) and Se2Br5σ(7c–10e)
BPs in Br4σ(4c–6e) and Se2Br6σ(7c–10e) seem straight, as shown in Figures 3 and 5. To show the linearity more clearly, the lengths of BPs (rBP) for Br4σ(4c–6e) are calculated. The values are collected in Table S5 in Supplementary File, together with the corresponding straight-line distances (RSL). The table contains the values for Se2Br6σ(7c–10e) in 7 (C2h) and 8 (C2h). The differences between them (ΔrBP = rBP–RSL) are less than 0.003 Å. The rBP values are plotted versus RSL, which are shown in Figure S5 in Supplementary File. The correlations are excellent, as shown in the figure. Therefore, Br4σ(4c–6e) and Se2Br6σ(7c–10e) in the species can be approximated by the straight lines.Table 1
QTAIM functions and QTAIM-DFA parameters forBBr-∗-ABr-∗-A′Br-∗-B′Br at BCPs in Br4σ(4c–6e), together with ABr-∗-ABr in Br2, evaluated with MP2/BSS-Aa).
Species (symmetry)Interaction X-∗-Yρb(rc) (eao−3)c∇2ρb(rc)b) (au)Hb(rc) (au)kb(rc)c)Rd) (au)θe) (°)Cij (Å mdyn−1)θp:CIVf) (°)κp:CIVg) (au−1)Predicted natureBr2 (D∞h)h)Br-∗-Br0.1130−0.0001−0.0497−2.0050.0497180.10.4191.81.8SS/Cov-wi)Br42− (D∞h)j)ABr-∗-ABr0.09220.0052−0.0313−1.7510.0317170.60.8190.63.6r-CS/CT-TBPk)ABr-∗-BBr0.01980.00580.0001−0.9950.005889.5−19.6118.2146p-CS/t-HBncl)Br6 (C2)ABr-∗-ABr0.10990.0010−0.0466−1.9600.0467178.80.4191.32.3r-CS/CT-TBPk)ABr-∗-BBr0.01310.00490.0009−0.8990.005079.614.397.8105p-CS/t-HBncl)Br6 (C2h)m)ABr-∗-ABr0.10990.0010−0.0466−1.9610.0467178.80.4191.71.7r-CS/CT-TBPk)ABr-∗-BBr0.01310.00490.0009−0.8990.005079.614.397.697p-CS/t-HBncl)Br6 (C2h)obsdn)ABr-∗-ABr0.07650.0053−0.0200−1.6540.0207165.2r-CSABr-∗-BBr0.01560.00550.0007−0.9290.005582.5p-CSH2Br4 (C2h)ABr-∗-ABr0.11010.0008−0.0468−1.9660.0468179.00.4191.72.0r-CS/CT-TBPk)ABr-∗-BBr0.01180.00450.0010−0.8810.004678.015.594.7100p-CS/t-HBncl)Me2Br4ABr-∗-ABr0.10760.0016−0.0444−1.9320.0445177.90.4191.41.8r-CS/CT-TBPk)ABr-∗-BBr0.01640.00570.0006−0.9450.005784.110.5105.1100p-CS/t-HBncl)H4Se2Br6 (Ci)ABr-∗-ABr0.10280.0031-0.0400−1.8660.0401175.60.5191.52.5r-CS/CT-TBPk)ABr-∗-BBr0.02200.0068−0.0002−1.0160.006891.99.9117.475r-CS/t-HBwco)Me4Se2Br6 (Ci)ABr-∗-ABr0.10280.0032−0.0400−1.8620.0402175.40.5191.43.7r-CS/CT-TBPk)ABr-∗-BBr0.02120.0067−0.0001−1.0080.006790.99.9116.4101r-CS/t-HBwco)5 (Ci)p)ABr-∗-ABr0.10160.0036−0.0389−1.8440.0391174.70.5191.54.4r-CS/CT-TBPk)ABr-∗-BBr0.02260.0070−0.0003−1.0230.007092.76.8118.0557r-CS/t-HBwco)ABr-∗-BBrq)0.02260.0070−0.0003−1.0230.007092.76.8118.0551r-CS/t-HBwco)5 (Ci)r)ABr-∗-ABr0.10470.0020−0.0383−1.9050.0384177.00.5191.32.5r-CS/CT-TBPk)ABr-∗-BBr0.01450.00480.0008−0.9040.004880.115.997.4102p-CS/t-HBnco)6 (Ci)ABr-∗-ABr0.10140.0037−0.0388−1.8410.0389174.60.5191.536r-CS/CT-TBPk)ABr-∗-ABrq)0.10140.0037−0.0388−1.8410.0389174.60.5191.636r-CS/CT-TBPk)ABr-∗-BBrq)0.02270.0070−0.0004−1.0240.007192.842.1122.52474r-CS/t-HBwco)6 (Ci)r)ABr-∗-ABr0.10440.0021−0.0380−1.9010.0381176.90.5191.32.6r-CS/CT-TBPk)ABr-∗-BBr0.01470.00480.0008−0.9070.004980.316.697.8103p-CS/t-HBnco)1 (Ci)r)ABr-∗-ABr0.10630.0013−0.0398−1.9390.0398178.10.5191.72.3r-CS/CT-TBPk)ABr-∗-BBr0.01230.00430.0010−0.8680.004476.918.391.8100p-CS/t-HBncl)1 (Ci)obsds)ABr-∗-ABr0.10190.0032−0.0393−1.8600.0394175.3r-CSABr-∗-BBr0.02000.00660.0003−0.9790.006687.7p-CSa)See the text for BSS. b)c∇2ρb(rc) = Hb(rc) − Vb(rc)/2, where c = ћ2/8m. c)kb(rc) = Vb(rc)/Gb(rc). d)R = (x2 + y2)1/2, where (x, y) = (Hb(rc) − Vb(rc)/2, Hb(rc)). e)θ = 90° − tan−1 (y/x).f)θp = 90°– tan−1(dy/dx). g)κp = |d2y/dx2|/[1 + (dy/dx)2]3/2. h)The Br-Br distance in Br2 was optimized to be 2.2756 Å with MP2/BSS-A, which was very close to the observed distance in the gas phase (2.287 Å) [63]. However, the values are shorter than those determined by the X-ray crystallographic analysis (2.491 Å) [40] by 0.210 Å. The noncovalent Br---Br distance is 3.251 Å in crystal, which is shorter than the sum of the van der Waals radii [64] by 0.45 Å. i)The SS interaction of the weak covalent nature. j)With one imaginary frequency for the vibration mode of the SGU symmetry. k)The regular-CS interaction of the CT-TBP nature. l)The pure-CS interaction of the HB nature with no covalency. m)With one imaginary frequency for the rotational mode around the linear Br4 interaction. n)See ref. [40] o)The regular-CS interaction of the HB nature with covalency. p)With one imaginary frequency for the vibration mode of the AU symmetry. q)w = (0), ±0.025, and ±0.05. r)At the CAM-B3LYP level. s)See ref. [39].QTAIM functions are calculated for Br4σ(4c–6e) at BCPs. Table 1 collects the values for the interactions. Hb(rc) is plotted versus Hb(rc) − Vb(rc)/2 for the data shown in Table 1, together with those from the perturbed structures generated with CIV. Figure 4 shows the plots for the ABr-∗-ABr and ABr-∗-BBr interactions in Br4σ(4c–6e) of the bromine species. The plots for ABr-∗-ABr appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) < 0, for all species, except for the original Br2 (D∞h), of which the plot appears in the region of Hb(rc) − Vb(rc)/2 < 0 and Hb(rc) < 0. Therefore, the interactions are all classified by the regular-CS (closed shell) interactions, except for Br2 (D∞h), which is classified by the SS (shard shell) interaction. On the contrary, data of ABr-∗-BBr appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) > 0 for all species, except for those in H4Se2Br6 (Ci), Me4Se2Br6 (Ci), 5 (Ci), and 6 (Ci), which appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) < 0. As a result, ABr-∗-BBr is classified by the pure-CS interactions (p-CS) for all, except for the four species, of which ABr-∗-BBr is classified by the regular-CS interactions (r-CS). The ABr-∗-BBr interaction in Br42− (D∞h) is very close to the borderline between p-CS and r-CS since Hb(rc) = 0.0001 au for Br42− (D∞h), which is very close to zero. QTAIM-DFA parameters of (R, θ) and (θp, κp) are obtained by analysing the plots of Hb(rc) versus Hb(rc) − Vb(rc)/2 in Figure 4, according to equations (S3)–(S6). Table 1 collects the QTAIM-DFA parameters for Br4σ(4c–6e). The classification of interactions will also be discussed based on the (R, θ) values.QTAIM functions are similarly calculated for Se2Br6σ(7c–10e) at BCPs, together with the related interactions. Hb(rc) is similarly plotted versus Hb(rc) − Vb(rc)/2 although not shown in the figures. Then, QTAIM-DFA parameters of (R, θ) and (θp, κp) are obtained by analysing the plots, according to equations (S3)–(S6). Table 2 collects the QTAIM-DFA parameters of (R, θ) and (θp, κp) for Br4σ(4c–6e).Table 2
QTAIM functions and QTAIM-DFA parameters forABr-∗-ASe-∗-BBr-∗-CBr-∗-DBr-∗-BSe-∗-EBr at BCPs in 7 (C2h), 8 (C2h), and 2 (C1)obsd, together with ABr-∗-ASe-∗-BBr in 3 (Cs) and ABr-∗-ASe-∗-BBr-∗-CBr-∗-DBr in 4 (Cs), evaluated with MP2 BSS‐Aa).
Species (symmetry)Interaction X-∗-Yρb(rc) (eao−3)c∇2ρb(rc)b) (au)Hb(rc) (au)kb(rc)c)Rd) (au)θe) (°)Cij (Å mdyn−1)θp:CIVf) (°)κp:CIVg) (au−1)Predicted nature7 (C2h)ASe-∗-ABrh)0.04230.0080−0.0056−1.2580.0098124.86.3169.955r-CS/CT-MCi)ASe-∗-BBrj)0.08250.0043−0.0264−1.7530.0267170.71.2192.22.2r-CS/CT-TBPk)BBr-∗-CBrl)0.03350.0086−0.0022−1.1150.0088104.69.4145.5102r-CS/t-HBwcm)8 (C2h)ASe-∗-ABrh)0.04920.0085−0.0079−1.3180.0116133.02.3172.753r-CS/CT-MCi)ASe-∗-BBrj)0.06620.0075−0.0158−1.5130.0175154.62.2187.717r-CS/CT-TBPk)BBr-∗-CBrl)0.03980.0092−0.0038−1.1710.0100112.54.2151.554r-CS/t-HBwcm)2 (C1)obsdn)ABr-∗-ASe0.02190.0065−0.0005−1.0390.006594.6r-CSASe-∗-BBr0.05760.0102−0.0113−1.3560.0152137.8r-CSBBr-∗-CBr0.09520.0068−0.0337−1.7130.0343168.6r-CSCBr-∗-DBr0.01830.00620.0005−0.9610.006285.7p-CSDBr-∗-BSe0.08180.0063−0.0271−1.6820.0278166.9r-CSBSe-∗-EBr0.07530.0072−0.0220−1.6040.0231161.9r-CS3 (Cs)ABr-∗-ASe0.07370.0061−0.0214−1.6360.0223164.00.8185.88.4r-CS/CT-TBPk)ASe-∗-BBr0.06780.0069−0.0177−1.5620.0189158.71.0183.018r-CS/CT-TBPk)4 (Cs)ABr-∗-ASe0.01310.00420.0004−0.9450.004284.06.4105.184p-CS/t-HBnco)ASe-∗-BBr0.04250.0088−0.0052−1.2290.0103120.64.6163.263r-CS/CT-MCi)BBr-∗-CBr0.09330.0059−0.0321−1.7320.0326169.60.9192.15.6r-CS/CT-TBPk)a)See the text for BSS. b)c∇2ρb(rc) = Hb(rc) − Vb(rc)/2, where c = ћ2/8m. c)kb(rc) = Vb(rc)/Gb(rc). d)R = (x2 + y2)1/2, where (x, y) = (Hb(rc) − Vb(rc)/2, Hb(rc)). e)θ = 90° − tan−1 (y/x). f)θp = 90° − tan−1 (dy/dx). g)κp = |d2y/dx2|/[1 + (dy/dx)2]3/2. h)Because it has Ci symmetry, it is the same as BSe-∗-EBr. i)The regular-CS interaction of the CT-MC nature. j)The same as BSe-∗-DBr. k)The regular-CS interaction of the CT-TBP nature. l)The same as CBr-∗-DBr. m) The pure-CS interaction of the HB nature with no covalency. n)See ref. [39]. o)The regular-CS interaction of the HB nature with no covalency.
## 3.5. Nature of Br4σ(4c–6e)
Interactions are characterized by (R, θ), which correspond to the data from the fully optimized structures. On the contrary, they are characterized employing (θp, κp) derived from the data of the perturbed structures around the fully optimized structures and the fully optimized ones. In this case, the nature of interactions is substantially determined based of the (R, θ, θp) values, while the κp values are used only additionally. It is instructive to survey the criteria before detail discussion. The criteria tell us that 180° < θ (Hb(rc) − Vb(rc)/2 < 0) for the SS interactions, 90° < θ < 180° (Hb(rc) < 0) for the r-CS interactions, and 45° < θ < 90° (Hb(rc) > 0) for p-CS interactions. The θp value characterizes the interactions. In the p-CS region of 45° < θ < 90°, the character of interactions will be the vdW type for 45° < θp < 90°, whereas it will be the typical HB type without covalency (t-HBnc) for 90° < θp < 125°, where θp = 125° is tentatively given for θ = 90°. The CT interaction will appear in the r-CS region of 90° < θ < 180°. The t-HB type with covalency (t-HBwc) appears in the region of 125° < θp < 150° (90° < θ < 115°), where (θ, θp) = (115°, 150°) is tentatively given as the borderline between t-HBwc and the CT-MC nature. The borderline for the interactions between CT-MC and CT-TBP types is defined by θp = 180°. θ = 150° is tentatively given for θp = 180°. Classical chemical bonds of SS (180° < θ) will be strong (Cov-s) when R > 0.15 au, whereas they will be weak (Cov-w) for R < 0.15 au. The classification and characterization of interactions are summarized in Table S1 and Scheme S3 in Supplementary File.TheABr-∗-ABr and ABr-∗-BBr interactions of Br4σ(4c–6e) will be classified and characterized based on the (R, θ, θp) values, employing the standard values as a reference (see Scheme S2 in Supplementary File). R < 0.15 au for all interactions in Table 1; therefore, no Cov-s were detected in this work. The (θ, θp) values are (180.1°, 191.8°) for the original Br2 (D∞h) if evaluated with MP2/BSS-A. Therefore, the nature of Br-∗-Br in Br2 (D∞h) is classified by the SS interactions and characterized as the Cov-w nature, which is denoted by SS/Cov-w. The (θ, θp) values are (170.6–179.0°, 190.6–191.7°) for ABr-∗-ABr of Br4σ(4c–6e) in the optimized structures in Table 1, of which nature is r-CS/CT-TBP. The (θ, θp) values are (78.0–84.1°, 94.7–105.1°) for ABr-∗-BBr in the optimized structures of Br6 (C2), Br6 (C2h), and R2Br4 (C2h) (R = H and Me); therefore, the nature is predicted to be r-CS/t-HBwc. The nature of ABr-∗-BBr in R4Se2Br6 (Ci) (R = H and Me), 5 (Ci) and 6 (Ci), is r-CS/t-HBwc, judging from the (θ, θp) values of (90.9–92.8°, 116.4–122.5°). The calculated (θ, θp) values of ABr-∗-ABr and ABr-∗-BBr for the optimized structure of Br42− (D∞h) are (170.6°, 190.6°) and (89.5°, 118.2°), respectively. In this case, ABr-∗-ABr and ABr-∗-BBr are predicted to have the nature of r-CS/CT-TBP and p-CS/t-HBnc, respectively. However, ABr-∗-BBr is just the borderline region to the r-CS interactions with θ = 89.5°. The characteristic nature of the BE---AE-AE---BE interactions in Br42− (D∞h) would be controlled by the double negative charges in the species.The results in Table1 show that the ABr-∗-ABr interaction in Br4σ(4c–6e) becomes weaker, as the strength of the corresponding ABr-∗-BBr increases. The strength of ABr-∗-ABr becomes weaker in the order shown in equation (10), if evaluated by θ, while that of ABr-∗-BBr increases in the order shown in equation (11), if measured by θ. Very similar results were obtained by θp:(10)θforABr−∗−ABr:Br2D∞h>H2Br4C2h≥Br6C2andC2h>Me2Br4C2h>H4Se2Br6Ci≥Me4Se2Br6Ci≥1Ciobsd>5Ci>6Ci>Br6C2hobsd,(11)θforABr−∗−BBr:H2Br4C2h>Br6C2handC2≥Br6C2hobsd>Me2Br4C2h<1Ciobsd<Me4Se2Br6Ci<H4Se2Br6Ci<5Ci≈6Ci.The orders shown in equations (10) and (11) seem to reasonably explain the characteristic behavior of Br4σ(4c–6e). The results must be the reflection of the np(BBr) ⟶ σ∗(ABr-ABr) ← np(BBr) form of Br4σ(4c–6e), where ABr-∗-ABr and ABr-∗-BBr become weaker and stronger, respectively, as the CT interaction increases. Br4σ(4c–6e) will be stabilized more effectively, if the negative charge is developed more at BBr. However, the two Br− ligands in Br42− (D∞h) seem not so effective than that expected. This would come from the electrostatic repulsive factor between the double negative charges in Br42− (D∞h), as mentioned above.Theθ values for (ABr-∗-ABr and ABr-∗-BBr) in Br6 (C2h)obsd and 1 (Ci)obsd are (165.2°, 82.5°) and (175.3°, 87.7°), respectively. Therefore, ABr-∗-ABr and ABr-∗-BBr are classified by r-CS and p-CS, respectively. Both ABr-∗-ABr and ABr-∗-BBr in Br6 (C2h)obsd are predicted to be weaker than those in 1 (Ci)obsd, respectively. The results would be curious at the first glance, since ABr-∗-ABr will be weaker, if ABr-∗-BBr in BBr-∗-ABr-∗-ABr-∗-BBr becomes stronger, as mentioned above. They would be affected from the surrounding, such as the crystal packing effect. A Br2 molecule interacts with four bromine atoms adjacent to the Br2 molecule on the bc-plane in crystals, equivalently with 3.251 Å [40].Similar investigations were carried out for I4σ(4c–6e), which will be discussed elsewhere (it is demonstrated that Br4σ(4c–6e) is predicted to be somewhat stronger than I4σ(4c–6e)).
## 3.6. Nature of Se2Br5σ(7c–10e)
The nature of Se2Br5σ(7c–10e) in 7 (C2h) and 8 (C2h) is elucidated, together with SeBr2σ(3c–4e) in 3 and SeBr4σ(4c–6e) in 4. The results are collected in Table 2. Figure 6 shows symmetric ψ184 (HOMO) and antisymmetric ψ185 (LUMO) of 8 (C2h), which correspond to ψ5 and ψ6 in σ(7c–10e), illustrated in Figure 1 although the Se atoms are contained in the linear Se2Br5σ(7c–10e) in 8 (C2h). The linear seven atomic orbitals on Se2Br5 are shown to construct ψ184 (HOMO) and ψ185 (LUMO) of 8 (C2h), which can be analysed as the Se2Br5σ(7c–10e) [39], so can the linear interaction in 7 (C2h), although not shown. The pseudolinear interaction of the seven atoms of 1 (C1)obsd could also be explained by the Se2Br5σ(7c–10e) model.Figure 6
Molecular orbitals forσ(7c–10e). ψ184 (HOMO) and ψ185 (LUMO) of 8 (C2h).The results demonstrate that Se2Br5σ(7c–10e) stabilize well 7 (C2h) and 8 (C2h) although 1 (C1)obsd seems not so effective. The negative charge developed at the Br atom in 3 would not be sufficient to stabilize Se2Br5σ(7c–10e) in 1 (C1)obsd, relative to the case of the Br− anion in 7 (C2h) and 8 (C2h), irrespective of the highly negatively charged Br atoms in SeBr2σ(3c–4e) of 3.
## 4. Conclusion
The intrinsic dynamic and static nature of Br4σ(4c–6e) is elucidated for 1 (Ci)obsd and the related species with QTAIM-DFA, employing the perturbed structures generated with CIV. The ABr-ABr interactions in BBr-∗-ABr-∗-ABr-∗-BBr of Br4σ(4c–6e) are weaker than Br-∗-Br in the optimized structure of Br2 (D∞h), which is predicted to have the SS/Cov-w nature. The ABr-ABr interactions in Br4σ(4c–6e) of the models are predicted to have the r-CS/CT-TBP nature, if optimized with MP2/BSS-A. The ABr-ABr interaction in 1 (Ci)obsd also appears in the r-CS region. On the contrary, the ABr-BBr interactions in Br6 (C2), Br6 (C2h), H2Br4 (C2h), and Me2Br4 (C2h) are predicted to have the p-CS/t-HBnc nature, whereas those in H4Se2Br4 (Ci), Me4Se2Br4 (Ci), 5 (Ci), and 6 (Ci) have the r-CS/t-HBwc nature, if evaluated with MP2/BSS-A. The ABr-∗-BBr interactions become stronger in the order of H2Br4 (C2h) < Br6 (C2h) ≤ Br6 (C2) < Me2Br4 (C2h) << Me4Se2Br6 (Ci) ≤ H4Se2Br6 (Ci) ≤ 5 (Ci) < 6 (Ci), which is the inverse order for ABr-∗-ABr, as a whole. The results are in accordance with the CT interaction of the np(BBr) ⟶ σ∗(ABr-ABr) ← np(BBr) form derived from Br4σ(4c–6e). The decreased binding force of ABr-∗-ABr must be transferred to ABr-∗-BBr in Br4σ(4c–6e). Namely, it is demonstrated that Br4σ(4c–6e) is stabilized as the strength of ABr-∗-BBr in Br4σ(4c–6e) increases, while ABr-∗-ABr becomes weakened relative to that in the original Br2 (D∞h). In this process, Br4σ(4c–6e) is totally stabilized. The ABr-∗-ABr and ABr-∗-BBr interactions in Br6 (C2h)obsd and 1 (Ci)obsd are classified by the r-CS and p-CS interactions, respectively, where the interactions in Br6 (C2h)obsd seem somewhat weaker than those in 1 (Ci)obsd. The Se2Br5σ(7c–10e) interactions are similarly elucidated for 2 (C1)obsd and the anionic models of 7 (C2h) and 8 (C2h). The Se2Br5σ(7c–10e) nature is clearly established for the optimized structures of 7 (C2h) and 8 (C2h), rather than 2 (C1)obsd. Extended hypervalent interactions of the σ(mc–ne: 4 ≤ m; m < n < 2m) type are shown to be well analysed and evaluated with QTAIM-DFA, employing the perturbed structures generated with CIV, exemplified by Br4σ(4c–6e) and Se2Br5σ(7c–10e).
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*Source: 2901439-2020-07-24.xml* | 2901439-2020-07-24_2901439-2020-07-24.md | 60,611 | Dynamic and Static Nature of Br4σ(4c–6e) and Se2Br5σ(7c–10e) in the Selenanthrene System and Related Species Elucidated by QTAIM Dual Functional Analysis with QC Calculations | Satoko Hayashi; Taro Nishide; Waro Nakanishi | Bioinorganic Chemistry and Applications
(2020) | Chemistry and Chemical Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2020/2901439 | 2901439-2020-07-24.xml | ---
## Abstract
The nature of Br4σ(4c–6e) of the BBr-∗-ABr-∗-ABr-∗-BBr form is elucidated for SeC12H8(Br)SeBr---Br-Br---BrSe(Br)C12H8Se, the selenanthrene system, and the models with QTAIM dual functional analysis (QTAIM-DFA). Asterisks (∗) are employed to emphasize the existence of bond critical points on the interactions in question. Data from the fully optimized structure correspond to the static nature of interactions. In our treatment, data from the perturbed structures, around the fully optimized structure, are employed for the analysis, in addition to those from the fully optimized one, which represent the dynamic nature of interactions. The ABr-∗-ABr and ABr-∗-BBr interactions are predicted to have the CT-TBP (trigonal bipyramidal adduct formation through charge transfer) nature and the typical hydrogen bond nature, respectively. The nature of Se2Br5σ(7c–10e) is also clarified typically, employing an anionic model of [Br-Se(C4H4Se)-Br---Br---Br-Se(C4H4Se)-Br]−, the 1,4-diselenin system, rather than (BrSeC12H8)Br---Se---Br-Br---Br-Se(C12H8Se)-Br, the selenanthrene system.
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## Body
## 1. Introduction
We have been much interested in the behavior of the linear interactions of theσ-type, higher than σ(3c–4e: three center-four electron interactions) [1–6], constructed by the atoms of heavier main group elements. We proposed to call such linear interactions the extended hypervalent interactions, σ(mc–ne: 4 ≤ m; m < n < 2m), after the hypervalent σ(3c–4e). The linear alignments of four chalcogen atoms were first demonstrated in the naphthalene system, bis[8-(phenylchalcogenyl)naphthyl]-1,1′-dichalcogenides [I: 1-(8-PhBEC10H6)AE-AE(C10H6BEPh-8′)-1′ (AE, BE = S and Se)] [7–12]. It was achieved through the preparation and the structural determination by the X-ray crystallographic analysis. The linear BE---AE-AE---BE interactions in I are proposed to be analysed as the EA2EB2σ(4c–6e) model not by the double AEBE2σ(3c–4e) model. EA2EB2σ(4c–6e) in I is characterized by the CT interaction of the np(BE) ⟶ σ∗(AE–AE)←np(BE) form [8, 10–12], where np(BE) stands for the p-type nonbonding orbitals of BE and σ∗(AE-AE) are the σ∗ orbitals of AE-AE. The novel reactivity of EA2EB2σ(4c–6e) in I was also clarified [8].σ(4c–6e) is the first member of σ(mc–ne: 4 ≤ m; m < n < 2m) [7–13]. The σ(4c–6e) interactions are strongly suggested to play an important role in the development of high functionalities in materials and in the key processes of biological and pharmaceutical activities, recently. The bonding is applied to a wide variety of fields, such as crystal engineering, supramolecular soft matters, and nanosciences [4, 14–23]. The nature of BE---AE and AE-AE in BE---AE-AE---BE of EA2EB2σ(4c–6e) has been elucidated [24–27] using the quantum theory of atoms in molecules (QTAIM) approach, introduced by Bader [28–37]. The linear interactions of the σ(4c–6e) type will form if BE in EA2EB2 is replaced by X, giving E2X2σ(4c–6e). The nature of E2X2σ(4c–6e) in the naphthalene system of 1-(8-XC10H6)E-E(C10H6X-8′)-1′ [II (E, X) = (S, Cl), (S, Br), (Se, Cl), and (Se, Br)] was similarly clarified very recently [38].Theσ(4c–6e) interaction will also be produced even if both BE and AE in EA2EB2 are replaced by X. X4σ(4c–6e) should also be stabilized through CT of the np(X) ⟶ σ∗(X-X) ← np(X) form. The energy lowering of the system through the CT interaction must be the driving force for the formation of X4σ(4c–6e). X4σ(4c–6e) is the typical kind of halogen bonds, together with E2X2σ(4c–6e), which are of current and continuous interest [39]. Br4σ(4c–6e) has been clearly established in the selenanthrene system, SeC12H8(Br)SeBr---Br-Br---BrSe(Br)C12H8Se (1), through the preparation and the structural determination by the X-ray crystallographic analysis [39]. The atoms taking part in the linear interaction in question are shown in bold. The structure of (BrSeC12H8)Br---Se---Br-Br---Br-Se(C12H8Se)-Br (2) was also reported, in addition to 1, which is suggested to contain Se2Br5σ(7c–10e) since the seven atoms of Se2Br5 align almost linearly in crystals. Figure 1 shows the structures of 1 and 2 determined by the X-ray analysis and the approximate MO model for σ(4c–6e) and σ(7c–10e).Figure 1
Structure of1 determined by the X-ray crystallographic analysis (a) and the approximate MO model for σ(4c–6e) (b); structure of 2 (c) and the approximate MO model for σ(7c–10e) (d).
(a)(b)(c)(d)It is challenging to elucidate the nature of Br4σ(4c–6e) of the np(Br) ⟶ σ∗(Br-Br)←np(Br) form in 1 and Se2Br5σ(7c–10e) in 2, together with the related species. Figure 2 illustrates the process assumed for the formation of 1 and 2 from selenanthrene (S: SeC12H8Se). In this process, (SeC12H8)Br-Se-Br (3) should be formed first in the reaction of S with Br2, and then 3 reacts with Br2 to yield Br[Se(Br) (C12H8)]Se---Br-Br (4). The almost linear alignment of Br---Se---Br-Br in 4 could be analysed by the SeBr3σ(4c–6e) model, where the Br and Se atoms in 4 are placed in close proximity in space. While 1 containing Br4σ(4c–6e) forms in the reaction of (3 + Br2 + 3), the reaction of 3 + 4 yields 2, consisting Se2Br5σ(7c–10e). Both 1 and 2 are recognized as the Br2-included species. While XC4H4(Br)SeBr---Br-Br---BrSe(Br)C4H4X (5 (X = Se) and 6 (X = S)), models of 1, also consisted of Br4σ(4c–6e), Se2Br5σ(7c–10e) will appear typically in the anionic species, [Br-Se(Me2)-Br---Br---Br-Se(Me2)-Br]− (7) and [Br-Se(SeC4H4)-Br---Br---Br-Se(C4H4Se)-Br]− (8), models of 2. Species, 5, 6, 7, and 8, are shown in Figure 2, where 5, 6, and 8 belong to the 1,4-diselenin system.Figure 2
Process assumed for the formation of Br4σ(4c–6e) in 1 from Se(C12H8)Se (S) via3 and Se2Br5σ(7c–10e) in 2via3 and 4. 5 and 6 with Br4σ(4c–6e), models of 1, and 7 and 8 with Se2Br5σ(7c–10e), models of 2, are also shown. Atoms taking part in the linear interactions are shown by red.What are the differences and similarities between X4σ(4c–6e), E4σ(4c–6e), and E2X2σ(4c–6e)? The nature of X4σ(4c–6e) in 1 (X = Br) is to be elucidated together with the models. Models, other than 5 and 6, are also devised to examine the stabilization sequence of Br4σ(4c–6e). H2Br4 (C2h) and Me2Br4 (C2h) have the form of R-Br---Br-Br---Br-R (RBr4R: R = H and Me), which are called the model group A (G(A)). The electronic efficiency to stabilize Br4σ(4c–6e) seems small for R in G(A). Br6 (C2h) is detected as the partial structure in the crystals of Br2 [40]. Br6 (C2h) in the crystals is denoted by Br6 (C2h)obsd. The optimized structure of Br6 (C2h) has one imaginary frequency, which belongs to G(A), together with Br6 (C2h)obsd. The optimized structure of Br6 retains the C2 symmetry, (Br6 (C2)), which also belongs to G(A). The CT interaction of the np(BBr) ⟶ σ∗(ABr-ABr) ⟵ np(BBr) form in Br4σ(4c–6e) will be much stabilized if the large negative charge is developed at the BBr atoms in Br-(R2)Se-BBr---ABr-ABr---BBr-Se(R2)-Br, where the ∠SeBBrABr is around 90°. The highly negatively charged BBr in Br-Se(R2)-BBr (R = H and Me) of σ(3c–4e) is employed to stabilize Br4σ(4c–6e), in this case. The models form G(B). The nature of Br4σ(4c–6e) in 5 and 6 is similarly analysed, which belongs to G(B). Br42− (D∞h) also belongs to G(B) although one imaginary frequency was predicted for Br42−, if optimized at the MP2 level. Figure 3 illustrates the story for the stabilization of Br4σ(4c–6e) in the sequence of the species, starting from G(A) to 1, via G(B). Figure 3 also shows the ABr-ABr and ABr---BBr distances (r(ABr-ABr) and r(ABr-BBr), respectively), together with the charge developed at BBr in the original species of R-BBr (Qn (BBr)), which construct R-BBr---ABr-ABr---BBr-R.Figure 3
Sequence in the stabilization of Br4σ(4c–6e), starting from those in G(A) to 1 via those of G(B).A chemical bond or interaction between atoms A and B is denoted by A-B, which corresponds to a bond path (BP) in the quantum theory of atoms in molecules (QTAIM) approach, introduced by Bader [28–37]. We will use A-∗-B for BP, where the asterisk emphasizes the existence of a bond critical point (BCP, ∗) in A-B [28, 29]. (Dots are usually employed to show BCPs in molecular graphs. Therefore, A-•-B would be more suitable to describe the BP with a BCP. Nevertheless, A-∗-B is employed to emphasize the existence of a BCP on the BP in question in our case. BCP is a point along BP at the interatomic surface, where ρ(r) (charge density) reaches a minimum along the interatomic (bond) path, while it is a maximum on the interatomic surface separating the atomic basins). The chemical bonds and interactions are usually classified by the signs of Laplacian rho (∇2ρb(rc)) and Hb(rc) at BCPs, where ρb(rc) and Hb(rc) are the charge densities and total electron energy densities at BCPs, respectively (see Scheme S1 in Supplementary File). The relations between Hb(rc), ∇2ρb(rc), Gb(rc) (the kinetic energy densities), and Vb(rc) (the potential energy densities) are represented in equations (1) and (2):(1)Hbrc=Gbrc+Vbrc,(2)ℏ28m∇2ρbrc=Hbrc−Vbrc2=Gbrc+Vbrc2.How can the nature of Br4σ(4c–6e) and Se2Br5σ(7c–10e) be clarified? For the characterization of interactions in more detail, we recently proposed QTAIM dual functional analysis (QTAIM-DFA) [42–47] for experimental chemists to analyze their own chemical bonds and interaction results based on their own expectations, according to the QTAIM approach [28–37]. Hb(rc) is plotted versus Hb(rc) − Vb(rc)/2 (= (ћ2/8m)∇2ρb(rc)) at BCPs in QTAIM-DFA. The classification of interactions by the signs of ∇2ρb(rc) and Hb(rc) is incorporated in QTAIM-DFA. Data from the fully optimized structures correspond to the static natures of the interactions, which are analysed using the polar coordinate (R, θ), representation [42, 44–46]. Each interaction plot, containing data from both the perturbed structures and the fully optimized one include a specific curve that provides important information about the interaction. This plot is expressed by (θp, κp), where θp corresponds to the tangent line of the plot and κp is the curvature. The concept of the dynamic nature of interactions has been proposed based on (θp, κp) [42, 44]. θ and θp are measured from the y-axis and the y-direction, respectively. We call (R, θ) and (θp, κp) QTAIM-DFA parameters, which are drawn in Figure 4, exemplified by Br42− (D∞h). While (R, θ) classifies the interactions, (θp, κp) characterizes them.Figure 4
QTAIM-DFA plots ofHb(rc) versus Hb(rc) − Vb(rc)/2 for ABr-∗-ABr (a) and ABr-∗-BBr (b) in Br4σ(4c–6e) of the species in Table 1, together with those of the perturbed structures generated with CIV. Marks and colours for the species are shown in the figure.
(a)(b)We proposed a highly reliable method to generate the perturbed structures for QTAIM-DFA very recently [48]. The method is called CIV, which employs the coordinates derived from the compliance force constants Cij for the internal vibrations. Compliance force constants Cij are defined as the partial second derivatives of the potential energy due to an external force, as shown in equation (3), where i and j refer to the internal coordinates and the force constants fi and fj correspond to i and j, respectively. The Cij values and the coordinates corresponding to the values can be calculated using the compliance 3.0.2 program, released by Brandhorst and Grunenberg [49–52]. The dynamic nature of interactions based on the perturbed structures with CIV is described as the “intrinsic dynamic nature of interactions” since the coordinates are invariant to the choice of the coordinate system:(3)Cij=∂2E∂fi∂fj.QTAIM-DFA has excellent potential for evaluating, classifying, characterizing, and understanding weak to strong interactions according to a unified form. The superiority of QTAIM-DFA to elucidate the nature of interactions, employing the perturbed structures generated with CIV, is explained in the previous papers [48, 53] (see also Figure S2 and Table S2 in Supplementary File). QTAIM-DFA is applied to standard interactions and rough criteria that distinguish the interaction in question from others which are obtained. QTAIM-DFA and the criteria are explained in Supplementary File using Schemes S1–S3, Figures S1 and S2, Table S1, and equations (S1)–(S7). The basic concept of the QTAIM approach is also explained.We consider QTAIM-DFA, employing the perturbed structures generated with CIV, to be well suited to elucidate the nature of Br4σ(4c–6e) in 1, Se2Br5σ(7c–10e) in 2, and the models derived from 1 and 2, together with the related linear interactions. The interactions in Br4σ(4c–6e) are denoted by BBr-∗-ABr-∗-ABr-∗-BBr, where the asterisk emphasizes the existence of a BCP in the interactions, so are those in Se2Br5σ(7c–10e). Herein, we present the results of the investigations on the extended hypervalent interactions in the species, together with the structural feature. Each interaction is classified and characterized, employing the criteria as a reference.
## 2. Methodological Details in Calculations
Calculations were performed employing the Gaussian 09 programs package [54]. The basis sets employed for the calculations were obtained, as implemented from Sapporo Basis Set Factory [55]. The basis sets of the (621/31/2), (6321/621/3), (74321/7421/72), and (743211/74111/721/2+1s1p) forms were employed for C, S, Se, and Br, respectively, with the (31/3) form for H. The basis set system is called BSS-A. All species were calculated employing BSS-A, and the Møller–Plesset second-order energy correlation (MP2) level [56–58] was applied for the optimizations. Optimized structures were confirmed by the frequency analysis. The results of the frequency analysis were used to calculate the Cij values and the coordinates (Ci) corresponding to the values. The DFT level of CAM-B3LYP [59] was also applied when necessary. The QTAIM functions were analysed with the AIM2000 [60] and AIMAll [61] programs.The method to generate perturbed structures with CIV is the same as that explained in the previous papers [48, 53]. As shown in equation (4), the i-th perturbed structure in question (Siw) is generated by the addition of the i-th coordinates (Ci), derived from Cij, to the standard orientation of a fully optimized structure (So) in the matrix representation. The coefficient fiw in equation (4) controls the structural difference between Siw and So: fiw is determined to satisfy equation (5) for r, where r and ro stand for the interaction distances in question in the perturbed and fully optimized structures, respectively, with ao = 0.52918 Å (Bohr radius). The Ci values of five digits are used to predict Siw:(4)Siw=So+fiw⋅Ci,(5)r=ro+wao,w=0,±0.05,and±0.1;ao=0.52918Å,(6)y=co+c1x+c2x2+c3x3,Rc2:square of correlation coefficient.In QTAIM-DFA,Hb(rc) is plotted versus Hb(rc) − Vb(rc)/2 for data of w = 0, ±0.05, and ±0.10 in equation (5). Each plot is analysed using a regression curve of the cubic function, as shown in equation (6), where (x, y) = (Hb(rc) − Vb(rc)/2 and Hb(rc)) (Rc2 (square of correlation coefficient) > 0.99999 in usual) [46].
## 3. Results and Discussion
### 3.1. Structural Optimizations
The structures of1 (Ci) and 2 (C1) determined by the X-ray analysis are denoted by 1 (Ci)obsd and 2 (C1)obsd, respectively [39]. The structural parameters are shown in Tables S2 and S3 in Supplementary File, respectively. Figure 3 contains the selected structural parameters for 1 (Ci)obsd. The structures are optimized for G(A) of H2Br4 (C2h), Me2Br4 (C2h), Br6 (C2h), and Br6 (C2) and G(B) of H4Se2Br6 (Ci), Me4Se2Br6 (Ci), 5 (Ci), and 6 (Ci), together with 3 (Cs), 4 (Cs), 7 (C2h), 8 (C2h), and Br2 (D∞h). The optimized structural parameters are also collected in Tables S2 and S3 in Supplementary File. The frequency analysis was successful for the optimized structures, except for 1 (Ci)obsd and Br6 (C2h). All positive frequencies were obtained for 1 (Ci), if calculated with CAM-B3LYP/BSS-A, which confirms the structure. The Br---Br distances of Br4σ(4c–6e) in 1 (Ci) are somewhat longer if optimized at the CAM-B3LYP level, relative to 1 (Ci)obsd. While one imaginary frequency is detected in Br6 (C2h), Br6 (C2) has all positive frequencies. The optimized structures are not shown in figures, instead, some of them can be found in Figures 3 and 5, where the molecular graphs are drawn on the optimized structures. Figure 3 contains the optimized r(ABr-ABr) and r(ABr-BBr) distances for the models and the charge developed at BBr in the original R-BBr and Br-(R2)Se-BBr (Qn (BBr)), which give the models of G(A) and G(B), respectively. The r(ABr-BBr) values become shorter in the order shown in equation (7), if evaluated with MP2/BSS-A:(7)rBAr−BBr:H2Br4C2h>1CiCAM>Br6C2andC2h>Br6C2hobsd40>Me2Br4C2h>Br42−D∞h>1Ciobsd≥Me4Se2Br6Ci≥H4Se2Br6Ci>5Ci≥6Ci.Figure 5
Molecular graphs of5 (Ci) (a), 6 (Ci) (b), 7 (C2h) (c), and 8 (C2h) (d) drawn on the structures optimized at the MP2 level, together with 1 (Ci)obsd (e) and 2 (C1)obsd (f). Contour plots of ρ(r) are also drawn on the planes containing the linear interactions. BCPs are denoted by red dots, RCPs (ring critical points) by yellow dots, and CCPs (cage critical points) by green dots. BPs (bond paths) are drawn as pink lines and the secondary ones as pink dots. They are associated with the BCPs. Carbon and hydrogen atoms are shown in black and gray, respectively. The contours (eao−3) are at 2l (l = ±8, ±7, …, and 0).
(a)(b)(c)(d)(e)(f)One imaginary frequency was also predicted forBr42− (D∞h) if optimized with MP2/BSS-A. Br42− (D∞h) seems to collapse to Br3− and Br−, according to the imaginary frequency. The double negative charges in Br42− (D∞h) would be responsible for the results. The electrostatic repulsion between the double negative charges will operate to collapse it.
### 3.2. Energies for Formation of Br4σ(4c–6e) and NBO Analysis
Energies for the formation of R′Br4R′ from the components (2R′Br + Br2) (ΔE) are defined by equation (8). The ΔE values evaluated on the energy surface are denoted by ΔEES, while those corrected with the zero-point energies are by ΔEZP. The ΔEES and ΔEZP values for the optimized structures are given in Table S2 in Supplementary File. ΔEZP are excellently correlated to ΔEES (ΔEZP = 0.99ΔEES + 1.93: Rc2 = 0.9998, see Figure S3 in Supplementary File):(8)ΔER2′Br4=ER2′Br4−2ER′Br+EBr2,(9)E2=qi×Fi,j2εj−εi.NBO analysis [62] was applied to ABr---BBr of the species to evaluate the contributions from CT to stabilize R′-BBr---ABr-ABr---BBr-R′. For each donor NBO (i) and acceptor NBO (j), the stabilization energy E(2) is calculated based on the second-order perturbation theory in NBO, according to equation (9), where qi is the donor orbital occupancy, εi and εj are diagonal elements (orbital energies), and F(i, j) is the off-diagonal NBO Fock matrix element. The results are collected in Table S4 in Supplementary File. The ΔEES values are very well correlated to E(2) for the optimized structures, except for Br42− (D∞h). (ΔEES = –0.71(2E(2)) + 7.17: Rc2 = 0.959, see Figure S4 in Supplementary File). Br42− (D∞h) is predicted to be less stable than the components.Before application of QTAIM-DFA to Br4σ(4c–6e) and Se2Br5σ(7c–10e), molecular graphs were examined, as shown in the next section.
### 3.3. Molecular Graphs with Contour Plots for the Species Containing Br4σ(4c–6e), Se2Br5σ(7c–10e), and Related Linear Interactions
Figure5 illustrates the molecular graphs of 5 (Ci), 6 (Ci), 7 (C2h), and 8 (C2h), drawn on the optimized structures, together with 1 (Ci)obsd and 2 (C1)obsd. Figure 5 also shows the contour plots of ρ(r) drawn on the suitable plane in the molecular graphs. BCPs are well demonstrated to locate on the (three-dimensional) saddle points of ρ(r). Molecular graphs of Me2Br4 (C2h), Br6 (C2), Br42− (D∞h), and Br(Me2)SeBr4Se(Me2)Br (Ci) are shown in Figure 3, which are drawn on the optimized structures.
### 3.4. Survey of Br4σ(4c–6e) and Se2Br5σ(7c–10e)
BPs in Br4σ(4c–6e) and Se2Br6σ(7c–10e) seem straight, as shown in Figures 3 and 5. To show the linearity more clearly, the lengths of BPs (rBP) for Br4σ(4c–6e) are calculated. The values are collected in Table S5 in Supplementary File, together with the corresponding straight-line distances (RSL). The table contains the values for Se2Br6σ(7c–10e) in 7 (C2h) and 8 (C2h). The differences between them (ΔrBP = rBP–RSL) are less than 0.003 Å. The rBP values are plotted versus RSL, which are shown in Figure S5 in Supplementary File. The correlations are excellent, as shown in the figure. Therefore, Br4σ(4c–6e) and Se2Br6σ(7c–10e) in the species can be approximated by the straight lines.Table 1
QTAIM functions and QTAIM-DFA parameters forBBr-∗-ABr-∗-A′Br-∗-B′Br at BCPs in Br4σ(4c–6e), together with ABr-∗-ABr in Br2, evaluated with MP2/BSS-Aa).
Species (symmetry)Interaction X-∗-Yρb(rc) (eao−3)c∇2ρb(rc)b) (au)Hb(rc) (au)kb(rc)c)Rd) (au)θe) (°)Cij (Å mdyn−1)θp:CIVf) (°)κp:CIVg) (au−1)Predicted natureBr2 (D∞h)h)Br-∗-Br0.1130−0.0001−0.0497−2.0050.0497180.10.4191.81.8SS/Cov-wi)Br42− (D∞h)j)ABr-∗-ABr0.09220.0052−0.0313−1.7510.0317170.60.8190.63.6r-CS/CT-TBPk)ABr-∗-BBr0.01980.00580.0001−0.9950.005889.5−19.6118.2146p-CS/t-HBncl)Br6 (C2)ABr-∗-ABr0.10990.0010−0.0466−1.9600.0467178.80.4191.32.3r-CS/CT-TBPk)ABr-∗-BBr0.01310.00490.0009−0.8990.005079.614.397.8105p-CS/t-HBncl)Br6 (C2h)m)ABr-∗-ABr0.10990.0010−0.0466−1.9610.0467178.80.4191.71.7r-CS/CT-TBPk)ABr-∗-BBr0.01310.00490.0009−0.8990.005079.614.397.697p-CS/t-HBncl)Br6 (C2h)obsdn)ABr-∗-ABr0.07650.0053−0.0200−1.6540.0207165.2r-CSABr-∗-BBr0.01560.00550.0007−0.9290.005582.5p-CSH2Br4 (C2h)ABr-∗-ABr0.11010.0008−0.0468−1.9660.0468179.00.4191.72.0r-CS/CT-TBPk)ABr-∗-BBr0.01180.00450.0010−0.8810.004678.015.594.7100p-CS/t-HBncl)Me2Br4ABr-∗-ABr0.10760.0016−0.0444−1.9320.0445177.90.4191.41.8r-CS/CT-TBPk)ABr-∗-BBr0.01640.00570.0006−0.9450.005784.110.5105.1100p-CS/t-HBncl)H4Se2Br6 (Ci)ABr-∗-ABr0.10280.0031-0.0400−1.8660.0401175.60.5191.52.5r-CS/CT-TBPk)ABr-∗-BBr0.02200.0068−0.0002−1.0160.006891.99.9117.475r-CS/t-HBwco)Me4Se2Br6 (Ci)ABr-∗-ABr0.10280.0032−0.0400−1.8620.0402175.40.5191.43.7r-CS/CT-TBPk)ABr-∗-BBr0.02120.0067−0.0001−1.0080.006790.99.9116.4101r-CS/t-HBwco)5 (Ci)p)ABr-∗-ABr0.10160.0036−0.0389−1.8440.0391174.70.5191.54.4r-CS/CT-TBPk)ABr-∗-BBr0.02260.0070−0.0003−1.0230.007092.76.8118.0557r-CS/t-HBwco)ABr-∗-BBrq)0.02260.0070−0.0003−1.0230.007092.76.8118.0551r-CS/t-HBwco)5 (Ci)r)ABr-∗-ABr0.10470.0020−0.0383−1.9050.0384177.00.5191.32.5r-CS/CT-TBPk)ABr-∗-BBr0.01450.00480.0008−0.9040.004880.115.997.4102p-CS/t-HBnco)6 (Ci)ABr-∗-ABr0.10140.0037−0.0388−1.8410.0389174.60.5191.536r-CS/CT-TBPk)ABr-∗-ABrq)0.10140.0037−0.0388−1.8410.0389174.60.5191.636r-CS/CT-TBPk)ABr-∗-BBrq)0.02270.0070−0.0004−1.0240.007192.842.1122.52474r-CS/t-HBwco)6 (Ci)r)ABr-∗-ABr0.10440.0021−0.0380−1.9010.0381176.90.5191.32.6r-CS/CT-TBPk)ABr-∗-BBr0.01470.00480.0008−0.9070.004980.316.697.8103p-CS/t-HBnco)1 (Ci)r)ABr-∗-ABr0.10630.0013−0.0398−1.9390.0398178.10.5191.72.3r-CS/CT-TBPk)ABr-∗-BBr0.01230.00430.0010−0.8680.004476.918.391.8100p-CS/t-HBncl)1 (Ci)obsds)ABr-∗-ABr0.10190.0032−0.0393−1.8600.0394175.3r-CSABr-∗-BBr0.02000.00660.0003−0.9790.006687.7p-CSa)See the text for BSS. b)c∇2ρb(rc) = Hb(rc) − Vb(rc)/2, where c = ћ2/8m. c)kb(rc) = Vb(rc)/Gb(rc). d)R = (x2 + y2)1/2, where (x, y) = (Hb(rc) − Vb(rc)/2, Hb(rc)). e)θ = 90° − tan−1 (y/x).f)θp = 90°– tan−1(dy/dx). g)κp = |d2y/dx2|/[1 + (dy/dx)2]3/2. h)The Br-Br distance in Br2 was optimized to be 2.2756 Å with MP2/BSS-A, which was very close to the observed distance in the gas phase (2.287 Å) [63]. However, the values are shorter than those determined by the X-ray crystallographic analysis (2.491 Å) [40] by 0.210 Å. The noncovalent Br---Br distance is 3.251 Å in crystal, which is shorter than the sum of the van der Waals radii [64] by 0.45 Å. i)The SS interaction of the weak covalent nature. j)With one imaginary frequency for the vibration mode of the SGU symmetry. k)The regular-CS interaction of the CT-TBP nature. l)The pure-CS interaction of the HB nature with no covalency. m)With one imaginary frequency for the rotational mode around the linear Br4 interaction. n)See ref. [40] o)The regular-CS interaction of the HB nature with covalency. p)With one imaginary frequency for the vibration mode of the AU symmetry. q)w = (0), ±0.025, and ±0.05. r)At the CAM-B3LYP level. s)See ref. [39].QTAIM functions are calculated for Br4σ(4c–6e) at BCPs. Table 1 collects the values for the interactions. Hb(rc) is plotted versus Hb(rc) − Vb(rc)/2 for the data shown in Table 1, together with those from the perturbed structures generated with CIV. Figure 4 shows the plots for the ABr-∗-ABr and ABr-∗-BBr interactions in Br4σ(4c–6e) of the bromine species. The plots for ABr-∗-ABr appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) < 0, for all species, except for the original Br2 (D∞h), of which the plot appears in the region of Hb(rc) − Vb(rc)/2 < 0 and Hb(rc) < 0. Therefore, the interactions are all classified by the regular-CS (closed shell) interactions, except for Br2 (D∞h), which is classified by the SS (shard shell) interaction. On the contrary, data of ABr-∗-BBr appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) > 0 for all species, except for those in H4Se2Br6 (Ci), Me4Se2Br6 (Ci), 5 (Ci), and 6 (Ci), which appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) < 0. As a result, ABr-∗-BBr is classified by the pure-CS interactions (p-CS) for all, except for the four species, of which ABr-∗-BBr is classified by the regular-CS interactions (r-CS). The ABr-∗-BBr interaction in Br42− (D∞h) is very close to the borderline between p-CS and r-CS since Hb(rc) = 0.0001 au for Br42− (D∞h), which is very close to zero. QTAIM-DFA parameters of (R, θ) and (θp, κp) are obtained by analysing the plots of Hb(rc) versus Hb(rc) − Vb(rc)/2 in Figure 4, according to equations (S3)–(S6). Table 1 collects the QTAIM-DFA parameters for Br4σ(4c–6e). The classification of interactions will also be discussed based on the (R, θ) values.QTAIM functions are similarly calculated for Se2Br6σ(7c–10e) at BCPs, together with the related interactions. Hb(rc) is similarly plotted versus Hb(rc) − Vb(rc)/2 although not shown in the figures. Then, QTAIM-DFA parameters of (R, θ) and (θp, κp) are obtained by analysing the plots, according to equations (S3)–(S6). Table 2 collects the QTAIM-DFA parameters of (R, θ) and (θp, κp) for Br4σ(4c–6e).Table 2
QTAIM functions and QTAIM-DFA parameters forABr-∗-ASe-∗-BBr-∗-CBr-∗-DBr-∗-BSe-∗-EBr at BCPs in 7 (C2h), 8 (C2h), and 2 (C1)obsd, together with ABr-∗-ASe-∗-BBr in 3 (Cs) and ABr-∗-ASe-∗-BBr-∗-CBr-∗-DBr in 4 (Cs), evaluated with MP2 BSS‐Aa).
Species (symmetry)Interaction X-∗-Yρb(rc) (eao−3)c∇2ρb(rc)b) (au)Hb(rc) (au)kb(rc)c)Rd) (au)θe) (°)Cij (Å mdyn−1)θp:CIVf) (°)κp:CIVg) (au−1)Predicted nature7 (C2h)ASe-∗-ABrh)0.04230.0080−0.0056−1.2580.0098124.86.3169.955r-CS/CT-MCi)ASe-∗-BBrj)0.08250.0043−0.0264−1.7530.0267170.71.2192.22.2r-CS/CT-TBPk)BBr-∗-CBrl)0.03350.0086−0.0022−1.1150.0088104.69.4145.5102r-CS/t-HBwcm)8 (C2h)ASe-∗-ABrh)0.04920.0085−0.0079−1.3180.0116133.02.3172.753r-CS/CT-MCi)ASe-∗-BBrj)0.06620.0075−0.0158−1.5130.0175154.62.2187.717r-CS/CT-TBPk)BBr-∗-CBrl)0.03980.0092−0.0038−1.1710.0100112.54.2151.554r-CS/t-HBwcm)2 (C1)obsdn)ABr-∗-ASe0.02190.0065−0.0005−1.0390.006594.6r-CSASe-∗-BBr0.05760.0102−0.0113−1.3560.0152137.8r-CSBBr-∗-CBr0.09520.0068−0.0337−1.7130.0343168.6r-CSCBr-∗-DBr0.01830.00620.0005−0.9610.006285.7p-CSDBr-∗-BSe0.08180.0063−0.0271−1.6820.0278166.9r-CSBSe-∗-EBr0.07530.0072−0.0220−1.6040.0231161.9r-CS3 (Cs)ABr-∗-ASe0.07370.0061−0.0214−1.6360.0223164.00.8185.88.4r-CS/CT-TBPk)ASe-∗-BBr0.06780.0069−0.0177−1.5620.0189158.71.0183.018r-CS/CT-TBPk)4 (Cs)ABr-∗-ASe0.01310.00420.0004−0.9450.004284.06.4105.184p-CS/t-HBnco)ASe-∗-BBr0.04250.0088−0.0052−1.2290.0103120.64.6163.263r-CS/CT-MCi)BBr-∗-CBr0.09330.0059−0.0321−1.7320.0326169.60.9192.15.6r-CS/CT-TBPk)a)See the text for BSS. b)c∇2ρb(rc) = Hb(rc) − Vb(rc)/2, where c = ћ2/8m. c)kb(rc) = Vb(rc)/Gb(rc). d)R = (x2 + y2)1/2, where (x, y) = (Hb(rc) − Vb(rc)/2, Hb(rc)). e)θ = 90° − tan−1 (y/x). f)θp = 90° − tan−1 (dy/dx). g)κp = |d2y/dx2|/[1 + (dy/dx)2]3/2. h)Because it has Ci symmetry, it is the same as BSe-∗-EBr. i)The regular-CS interaction of the CT-MC nature. j)The same as BSe-∗-DBr. k)The regular-CS interaction of the CT-TBP nature. l)The same as CBr-∗-DBr. m) The pure-CS interaction of the HB nature with no covalency. n)See ref. [39]. o)The regular-CS interaction of the HB nature with no covalency.
### 3.5. Nature of Br4σ(4c–6e)
Interactions are characterized by (R, θ), which correspond to the data from the fully optimized structures. On the contrary, they are characterized employing (θp, κp) derived from the data of the perturbed structures around the fully optimized structures and the fully optimized ones. In this case, the nature of interactions is substantially determined based of the (R, θ, θp) values, while the κp values are used only additionally. It is instructive to survey the criteria before detail discussion. The criteria tell us that 180° < θ (Hb(rc) − Vb(rc)/2 < 0) for the SS interactions, 90° < θ < 180° (Hb(rc) < 0) for the r-CS interactions, and 45° < θ < 90° (Hb(rc) > 0) for p-CS interactions. The θp value characterizes the interactions. In the p-CS region of 45° < θ < 90°, the character of interactions will be the vdW type for 45° < θp < 90°, whereas it will be the typical HB type without covalency (t-HBnc) for 90° < θp < 125°, where θp = 125° is tentatively given for θ = 90°. The CT interaction will appear in the r-CS region of 90° < θ < 180°. The t-HB type with covalency (t-HBwc) appears in the region of 125° < θp < 150° (90° < θ < 115°), where (θ, θp) = (115°, 150°) is tentatively given as the borderline between t-HBwc and the CT-MC nature. The borderline for the interactions between CT-MC and CT-TBP types is defined by θp = 180°. θ = 150° is tentatively given for θp = 180°. Classical chemical bonds of SS (180° < θ) will be strong (Cov-s) when R > 0.15 au, whereas they will be weak (Cov-w) for R < 0.15 au. The classification and characterization of interactions are summarized in Table S1 and Scheme S3 in Supplementary File.TheABr-∗-ABr and ABr-∗-BBr interactions of Br4σ(4c–6e) will be classified and characterized based on the (R, θ, θp) values, employing the standard values as a reference (see Scheme S2 in Supplementary File). R < 0.15 au for all interactions in Table 1; therefore, no Cov-s were detected in this work. The (θ, θp) values are (180.1°, 191.8°) for the original Br2 (D∞h) if evaluated with MP2/BSS-A. Therefore, the nature of Br-∗-Br in Br2 (D∞h) is classified by the SS interactions and characterized as the Cov-w nature, which is denoted by SS/Cov-w. The (θ, θp) values are (170.6–179.0°, 190.6–191.7°) for ABr-∗-ABr of Br4σ(4c–6e) in the optimized structures in Table 1, of which nature is r-CS/CT-TBP. The (θ, θp) values are (78.0–84.1°, 94.7–105.1°) for ABr-∗-BBr in the optimized structures of Br6 (C2), Br6 (C2h), and R2Br4 (C2h) (R = H and Me); therefore, the nature is predicted to be r-CS/t-HBwc. The nature of ABr-∗-BBr in R4Se2Br6 (Ci) (R = H and Me), 5 (Ci) and 6 (Ci), is r-CS/t-HBwc, judging from the (θ, θp) values of (90.9–92.8°, 116.4–122.5°). The calculated (θ, θp) values of ABr-∗-ABr and ABr-∗-BBr for the optimized structure of Br42− (D∞h) are (170.6°, 190.6°) and (89.5°, 118.2°), respectively. In this case, ABr-∗-ABr and ABr-∗-BBr are predicted to have the nature of r-CS/CT-TBP and p-CS/t-HBnc, respectively. However, ABr-∗-BBr is just the borderline region to the r-CS interactions with θ = 89.5°. The characteristic nature of the BE---AE-AE---BE interactions in Br42− (D∞h) would be controlled by the double negative charges in the species.The results in Table1 show that the ABr-∗-ABr interaction in Br4σ(4c–6e) becomes weaker, as the strength of the corresponding ABr-∗-BBr increases. The strength of ABr-∗-ABr becomes weaker in the order shown in equation (10), if evaluated by θ, while that of ABr-∗-BBr increases in the order shown in equation (11), if measured by θ. Very similar results were obtained by θp:(10)θforABr−∗−ABr:Br2D∞h>H2Br4C2h≥Br6C2andC2h>Me2Br4C2h>H4Se2Br6Ci≥Me4Se2Br6Ci≥1Ciobsd>5Ci>6Ci>Br6C2hobsd,(11)θforABr−∗−BBr:H2Br4C2h>Br6C2handC2≥Br6C2hobsd>Me2Br4C2h<1Ciobsd<Me4Se2Br6Ci<H4Se2Br6Ci<5Ci≈6Ci.The orders shown in equations (10) and (11) seem to reasonably explain the characteristic behavior of Br4σ(4c–6e). The results must be the reflection of the np(BBr) ⟶ σ∗(ABr-ABr) ← np(BBr) form of Br4σ(4c–6e), where ABr-∗-ABr and ABr-∗-BBr become weaker and stronger, respectively, as the CT interaction increases. Br4σ(4c–6e) will be stabilized more effectively, if the negative charge is developed more at BBr. However, the two Br− ligands in Br42− (D∞h) seem not so effective than that expected. This would come from the electrostatic repulsive factor between the double negative charges in Br42− (D∞h), as mentioned above.Theθ values for (ABr-∗-ABr and ABr-∗-BBr) in Br6 (C2h)obsd and 1 (Ci)obsd are (165.2°, 82.5°) and (175.3°, 87.7°), respectively. Therefore, ABr-∗-ABr and ABr-∗-BBr are classified by r-CS and p-CS, respectively. Both ABr-∗-ABr and ABr-∗-BBr in Br6 (C2h)obsd are predicted to be weaker than those in 1 (Ci)obsd, respectively. The results would be curious at the first glance, since ABr-∗-ABr will be weaker, if ABr-∗-BBr in BBr-∗-ABr-∗-ABr-∗-BBr becomes stronger, as mentioned above. They would be affected from the surrounding, such as the crystal packing effect. A Br2 molecule interacts with four bromine atoms adjacent to the Br2 molecule on the bc-plane in crystals, equivalently with 3.251 Å [40].Similar investigations were carried out for I4σ(4c–6e), which will be discussed elsewhere (it is demonstrated that Br4σ(4c–6e) is predicted to be somewhat stronger than I4σ(4c–6e)).
### 3.6. Nature of Se2Br5σ(7c–10e)
The nature of Se2Br5σ(7c–10e) in 7 (C2h) and 8 (C2h) is elucidated, together with SeBr2σ(3c–4e) in 3 and SeBr4σ(4c–6e) in 4. The results are collected in Table 2. Figure 6 shows symmetric ψ184 (HOMO) and antisymmetric ψ185 (LUMO) of 8 (C2h), which correspond to ψ5 and ψ6 in σ(7c–10e), illustrated in Figure 1 although the Se atoms are contained in the linear Se2Br5σ(7c–10e) in 8 (C2h). The linear seven atomic orbitals on Se2Br5 are shown to construct ψ184 (HOMO) and ψ185 (LUMO) of 8 (C2h), which can be analysed as the Se2Br5σ(7c–10e) [39], so can the linear interaction in 7 (C2h), although not shown. The pseudolinear interaction of the seven atoms of 1 (C1)obsd could also be explained by the Se2Br5σ(7c–10e) model.Figure 6
Molecular orbitals forσ(7c–10e). ψ184 (HOMO) and ψ185 (LUMO) of 8 (C2h).The results demonstrate that Se2Br5σ(7c–10e) stabilize well 7 (C2h) and 8 (C2h) although 1 (C1)obsd seems not so effective. The negative charge developed at the Br atom in 3 would not be sufficient to stabilize Se2Br5σ(7c–10e) in 1 (C1)obsd, relative to the case of the Br− anion in 7 (C2h) and 8 (C2h), irrespective of the highly negatively charged Br atoms in SeBr2σ(3c–4e) of 3.
## 3.1. Structural Optimizations
The structures of1 (Ci) and 2 (C1) determined by the X-ray analysis are denoted by 1 (Ci)obsd and 2 (C1)obsd, respectively [39]. The structural parameters are shown in Tables S2 and S3 in Supplementary File, respectively. Figure 3 contains the selected structural parameters for 1 (Ci)obsd. The structures are optimized for G(A) of H2Br4 (C2h), Me2Br4 (C2h), Br6 (C2h), and Br6 (C2) and G(B) of H4Se2Br6 (Ci), Me4Se2Br6 (Ci), 5 (Ci), and 6 (Ci), together with 3 (Cs), 4 (Cs), 7 (C2h), 8 (C2h), and Br2 (D∞h). The optimized structural parameters are also collected in Tables S2 and S3 in Supplementary File. The frequency analysis was successful for the optimized structures, except for 1 (Ci)obsd and Br6 (C2h). All positive frequencies were obtained for 1 (Ci), if calculated with CAM-B3LYP/BSS-A, which confirms the structure. The Br---Br distances of Br4σ(4c–6e) in 1 (Ci) are somewhat longer if optimized at the CAM-B3LYP level, relative to 1 (Ci)obsd. While one imaginary frequency is detected in Br6 (C2h), Br6 (C2) has all positive frequencies. The optimized structures are not shown in figures, instead, some of them can be found in Figures 3 and 5, where the molecular graphs are drawn on the optimized structures. Figure 3 contains the optimized r(ABr-ABr) and r(ABr-BBr) distances for the models and the charge developed at BBr in the original R-BBr and Br-(R2)Se-BBr (Qn (BBr)), which give the models of G(A) and G(B), respectively. The r(ABr-BBr) values become shorter in the order shown in equation (7), if evaluated with MP2/BSS-A:(7)rBAr−BBr:H2Br4C2h>1CiCAM>Br6C2andC2h>Br6C2hobsd40>Me2Br4C2h>Br42−D∞h>1Ciobsd≥Me4Se2Br6Ci≥H4Se2Br6Ci>5Ci≥6Ci.Figure 5
Molecular graphs of5 (Ci) (a), 6 (Ci) (b), 7 (C2h) (c), and 8 (C2h) (d) drawn on the structures optimized at the MP2 level, together with 1 (Ci)obsd (e) and 2 (C1)obsd (f). Contour plots of ρ(r) are also drawn on the planes containing the linear interactions. BCPs are denoted by red dots, RCPs (ring critical points) by yellow dots, and CCPs (cage critical points) by green dots. BPs (bond paths) are drawn as pink lines and the secondary ones as pink dots. They are associated with the BCPs. Carbon and hydrogen atoms are shown in black and gray, respectively. The contours (eao−3) are at 2l (l = ±8, ±7, …, and 0).
(a)(b)(c)(d)(e)(f)One imaginary frequency was also predicted forBr42− (D∞h) if optimized with MP2/BSS-A. Br42− (D∞h) seems to collapse to Br3− and Br−, according to the imaginary frequency. The double negative charges in Br42− (D∞h) would be responsible for the results. The electrostatic repulsion between the double negative charges will operate to collapse it.
## 3.2. Energies for Formation of Br4σ(4c–6e) and NBO Analysis
Energies for the formation of R′Br4R′ from the components (2R′Br + Br2) (ΔE) are defined by equation (8). The ΔE values evaluated on the energy surface are denoted by ΔEES, while those corrected with the zero-point energies are by ΔEZP. The ΔEES and ΔEZP values for the optimized structures are given in Table S2 in Supplementary File. ΔEZP are excellently correlated to ΔEES (ΔEZP = 0.99ΔEES + 1.93: Rc2 = 0.9998, see Figure S3 in Supplementary File):(8)ΔER2′Br4=ER2′Br4−2ER′Br+EBr2,(9)E2=qi×Fi,j2εj−εi.NBO analysis [62] was applied to ABr---BBr of the species to evaluate the contributions from CT to stabilize R′-BBr---ABr-ABr---BBr-R′. For each donor NBO (i) and acceptor NBO (j), the stabilization energy E(2) is calculated based on the second-order perturbation theory in NBO, according to equation (9), where qi is the donor orbital occupancy, εi and εj are diagonal elements (orbital energies), and F(i, j) is the off-diagonal NBO Fock matrix element. The results are collected in Table S4 in Supplementary File. The ΔEES values are very well correlated to E(2) for the optimized structures, except for Br42− (D∞h). (ΔEES = –0.71(2E(2)) + 7.17: Rc2 = 0.959, see Figure S4 in Supplementary File). Br42− (D∞h) is predicted to be less stable than the components.Before application of QTAIM-DFA to Br4σ(4c–6e) and Se2Br5σ(7c–10e), molecular graphs were examined, as shown in the next section.
## 3.3. Molecular Graphs with Contour Plots for the Species Containing Br4σ(4c–6e), Se2Br5σ(7c–10e), and Related Linear Interactions
Figure5 illustrates the molecular graphs of 5 (Ci), 6 (Ci), 7 (C2h), and 8 (C2h), drawn on the optimized structures, together with 1 (Ci)obsd and 2 (C1)obsd. Figure 5 also shows the contour plots of ρ(r) drawn on the suitable plane in the molecular graphs. BCPs are well demonstrated to locate on the (three-dimensional) saddle points of ρ(r). Molecular graphs of Me2Br4 (C2h), Br6 (C2), Br42− (D∞h), and Br(Me2)SeBr4Se(Me2)Br (Ci) are shown in Figure 3, which are drawn on the optimized structures.
## 3.4. Survey of Br4σ(4c–6e) and Se2Br5σ(7c–10e)
BPs in Br4σ(4c–6e) and Se2Br6σ(7c–10e) seem straight, as shown in Figures 3 and 5. To show the linearity more clearly, the lengths of BPs (rBP) for Br4σ(4c–6e) are calculated. The values are collected in Table S5 in Supplementary File, together with the corresponding straight-line distances (RSL). The table contains the values for Se2Br6σ(7c–10e) in 7 (C2h) and 8 (C2h). The differences between them (ΔrBP = rBP–RSL) are less than 0.003 Å. The rBP values are plotted versus RSL, which are shown in Figure S5 in Supplementary File. The correlations are excellent, as shown in the figure. Therefore, Br4σ(4c–6e) and Se2Br6σ(7c–10e) in the species can be approximated by the straight lines.Table 1
QTAIM functions and QTAIM-DFA parameters forBBr-∗-ABr-∗-A′Br-∗-B′Br at BCPs in Br4σ(4c–6e), together with ABr-∗-ABr in Br2, evaluated with MP2/BSS-Aa).
Species (symmetry)Interaction X-∗-Yρb(rc) (eao−3)c∇2ρb(rc)b) (au)Hb(rc) (au)kb(rc)c)Rd) (au)θe) (°)Cij (Å mdyn−1)θp:CIVf) (°)κp:CIVg) (au−1)Predicted natureBr2 (D∞h)h)Br-∗-Br0.1130−0.0001−0.0497−2.0050.0497180.10.4191.81.8SS/Cov-wi)Br42− (D∞h)j)ABr-∗-ABr0.09220.0052−0.0313−1.7510.0317170.60.8190.63.6r-CS/CT-TBPk)ABr-∗-BBr0.01980.00580.0001−0.9950.005889.5−19.6118.2146p-CS/t-HBncl)Br6 (C2)ABr-∗-ABr0.10990.0010−0.0466−1.9600.0467178.80.4191.32.3r-CS/CT-TBPk)ABr-∗-BBr0.01310.00490.0009−0.8990.005079.614.397.8105p-CS/t-HBncl)Br6 (C2h)m)ABr-∗-ABr0.10990.0010−0.0466−1.9610.0467178.80.4191.71.7r-CS/CT-TBPk)ABr-∗-BBr0.01310.00490.0009−0.8990.005079.614.397.697p-CS/t-HBncl)Br6 (C2h)obsdn)ABr-∗-ABr0.07650.0053−0.0200−1.6540.0207165.2r-CSABr-∗-BBr0.01560.00550.0007−0.9290.005582.5p-CSH2Br4 (C2h)ABr-∗-ABr0.11010.0008−0.0468−1.9660.0468179.00.4191.72.0r-CS/CT-TBPk)ABr-∗-BBr0.01180.00450.0010−0.8810.004678.015.594.7100p-CS/t-HBncl)Me2Br4ABr-∗-ABr0.10760.0016−0.0444−1.9320.0445177.90.4191.41.8r-CS/CT-TBPk)ABr-∗-BBr0.01640.00570.0006−0.9450.005784.110.5105.1100p-CS/t-HBncl)H4Se2Br6 (Ci)ABr-∗-ABr0.10280.0031-0.0400−1.8660.0401175.60.5191.52.5r-CS/CT-TBPk)ABr-∗-BBr0.02200.0068−0.0002−1.0160.006891.99.9117.475r-CS/t-HBwco)Me4Se2Br6 (Ci)ABr-∗-ABr0.10280.0032−0.0400−1.8620.0402175.40.5191.43.7r-CS/CT-TBPk)ABr-∗-BBr0.02120.0067−0.0001−1.0080.006790.99.9116.4101r-CS/t-HBwco)5 (Ci)p)ABr-∗-ABr0.10160.0036−0.0389−1.8440.0391174.70.5191.54.4r-CS/CT-TBPk)ABr-∗-BBr0.02260.0070−0.0003−1.0230.007092.76.8118.0557r-CS/t-HBwco)ABr-∗-BBrq)0.02260.0070−0.0003−1.0230.007092.76.8118.0551r-CS/t-HBwco)5 (Ci)r)ABr-∗-ABr0.10470.0020−0.0383−1.9050.0384177.00.5191.32.5r-CS/CT-TBPk)ABr-∗-BBr0.01450.00480.0008−0.9040.004880.115.997.4102p-CS/t-HBnco)6 (Ci)ABr-∗-ABr0.10140.0037−0.0388−1.8410.0389174.60.5191.536r-CS/CT-TBPk)ABr-∗-ABrq)0.10140.0037−0.0388−1.8410.0389174.60.5191.636r-CS/CT-TBPk)ABr-∗-BBrq)0.02270.0070−0.0004−1.0240.007192.842.1122.52474r-CS/t-HBwco)6 (Ci)r)ABr-∗-ABr0.10440.0021−0.0380−1.9010.0381176.90.5191.32.6r-CS/CT-TBPk)ABr-∗-BBr0.01470.00480.0008−0.9070.004980.316.697.8103p-CS/t-HBnco)1 (Ci)r)ABr-∗-ABr0.10630.0013−0.0398−1.9390.0398178.10.5191.72.3r-CS/CT-TBPk)ABr-∗-BBr0.01230.00430.0010−0.8680.004476.918.391.8100p-CS/t-HBncl)1 (Ci)obsds)ABr-∗-ABr0.10190.0032−0.0393−1.8600.0394175.3r-CSABr-∗-BBr0.02000.00660.0003−0.9790.006687.7p-CSa)See the text for BSS. b)c∇2ρb(rc) = Hb(rc) − Vb(rc)/2, where c = ћ2/8m. c)kb(rc) = Vb(rc)/Gb(rc). d)R = (x2 + y2)1/2, where (x, y) = (Hb(rc) − Vb(rc)/2, Hb(rc)). e)θ = 90° − tan−1 (y/x).f)θp = 90°– tan−1(dy/dx). g)κp = |d2y/dx2|/[1 + (dy/dx)2]3/2. h)The Br-Br distance in Br2 was optimized to be 2.2756 Å with MP2/BSS-A, which was very close to the observed distance in the gas phase (2.287 Å) [63]. However, the values are shorter than those determined by the X-ray crystallographic analysis (2.491 Å) [40] by 0.210 Å. The noncovalent Br---Br distance is 3.251 Å in crystal, which is shorter than the sum of the van der Waals radii [64] by 0.45 Å. i)The SS interaction of the weak covalent nature. j)With one imaginary frequency for the vibration mode of the SGU symmetry. k)The regular-CS interaction of the CT-TBP nature. l)The pure-CS interaction of the HB nature with no covalency. m)With one imaginary frequency for the rotational mode around the linear Br4 interaction. n)See ref. [40] o)The regular-CS interaction of the HB nature with covalency. p)With one imaginary frequency for the vibration mode of the AU symmetry. q)w = (0), ±0.025, and ±0.05. r)At the CAM-B3LYP level. s)See ref. [39].QTAIM functions are calculated for Br4σ(4c–6e) at BCPs. Table 1 collects the values for the interactions. Hb(rc) is plotted versus Hb(rc) − Vb(rc)/2 for the data shown in Table 1, together with those from the perturbed structures generated with CIV. Figure 4 shows the plots for the ABr-∗-ABr and ABr-∗-BBr interactions in Br4σ(4c–6e) of the bromine species. The plots for ABr-∗-ABr appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) < 0, for all species, except for the original Br2 (D∞h), of which the plot appears in the region of Hb(rc) − Vb(rc)/2 < 0 and Hb(rc) < 0. Therefore, the interactions are all classified by the regular-CS (closed shell) interactions, except for Br2 (D∞h), which is classified by the SS (shard shell) interaction. On the contrary, data of ABr-∗-BBr appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) > 0 for all species, except for those in H4Se2Br6 (Ci), Me4Se2Br6 (Ci), 5 (Ci), and 6 (Ci), which appear in the region of Hb(rc) − Vb(rc)/2 > 0 and Hb(rc) < 0. As a result, ABr-∗-BBr is classified by the pure-CS interactions (p-CS) for all, except for the four species, of which ABr-∗-BBr is classified by the regular-CS interactions (r-CS). The ABr-∗-BBr interaction in Br42− (D∞h) is very close to the borderline between p-CS and r-CS since Hb(rc) = 0.0001 au for Br42− (D∞h), which is very close to zero. QTAIM-DFA parameters of (R, θ) and (θp, κp) are obtained by analysing the plots of Hb(rc) versus Hb(rc) − Vb(rc)/2 in Figure 4, according to equations (S3)–(S6). Table 1 collects the QTAIM-DFA parameters for Br4σ(4c–6e). The classification of interactions will also be discussed based on the (R, θ) values.QTAIM functions are similarly calculated for Se2Br6σ(7c–10e) at BCPs, together with the related interactions. Hb(rc) is similarly plotted versus Hb(rc) − Vb(rc)/2 although not shown in the figures. Then, QTAIM-DFA parameters of (R, θ) and (θp, κp) are obtained by analysing the plots, according to equations (S3)–(S6). Table 2 collects the QTAIM-DFA parameters of (R, θ) and (θp, κp) for Br4σ(4c–6e).Table 2
QTAIM functions and QTAIM-DFA parameters forABr-∗-ASe-∗-BBr-∗-CBr-∗-DBr-∗-BSe-∗-EBr at BCPs in 7 (C2h), 8 (C2h), and 2 (C1)obsd, together with ABr-∗-ASe-∗-BBr in 3 (Cs) and ABr-∗-ASe-∗-BBr-∗-CBr-∗-DBr in 4 (Cs), evaluated with MP2 BSS‐Aa).
Species (symmetry)Interaction X-∗-Yρb(rc) (eao−3)c∇2ρb(rc)b) (au)Hb(rc) (au)kb(rc)c)Rd) (au)θe) (°)Cij (Å mdyn−1)θp:CIVf) (°)κp:CIVg) (au−1)Predicted nature7 (C2h)ASe-∗-ABrh)0.04230.0080−0.0056−1.2580.0098124.86.3169.955r-CS/CT-MCi)ASe-∗-BBrj)0.08250.0043−0.0264−1.7530.0267170.71.2192.22.2r-CS/CT-TBPk)BBr-∗-CBrl)0.03350.0086−0.0022−1.1150.0088104.69.4145.5102r-CS/t-HBwcm)8 (C2h)ASe-∗-ABrh)0.04920.0085−0.0079−1.3180.0116133.02.3172.753r-CS/CT-MCi)ASe-∗-BBrj)0.06620.0075−0.0158−1.5130.0175154.62.2187.717r-CS/CT-TBPk)BBr-∗-CBrl)0.03980.0092−0.0038−1.1710.0100112.54.2151.554r-CS/t-HBwcm)2 (C1)obsdn)ABr-∗-ASe0.02190.0065−0.0005−1.0390.006594.6r-CSASe-∗-BBr0.05760.0102−0.0113−1.3560.0152137.8r-CSBBr-∗-CBr0.09520.0068−0.0337−1.7130.0343168.6r-CSCBr-∗-DBr0.01830.00620.0005−0.9610.006285.7p-CSDBr-∗-BSe0.08180.0063−0.0271−1.6820.0278166.9r-CSBSe-∗-EBr0.07530.0072−0.0220−1.6040.0231161.9r-CS3 (Cs)ABr-∗-ASe0.07370.0061−0.0214−1.6360.0223164.00.8185.88.4r-CS/CT-TBPk)ASe-∗-BBr0.06780.0069−0.0177−1.5620.0189158.71.0183.018r-CS/CT-TBPk)4 (Cs)ABr-∗-ASe0.01310.00420.0004−0.9450.004284.06.4105.184p-CS/t-HBnco)ASe-∗-BBr0.04250.0088−0.0052−1.2290.0103120.64.6163.263r-CS/CT-MCi)BBr-∗-CBr0.09330.0059−0.0321−1.7320.0326169.60.9192.15.6r-CS/CT-TBPk)a)See the text for BSS. b)c∇2ρb(rc) = Hb(rc) − Vb(rc)/2, where c = ћ2/8m. c)kb(rc) = Vb(rc)/Gb(rc). d)R = (x2 + y2)1/2, where (x, y) = (Hb(rc) − Vb(rc)/2, Hb(rc)). e)θ = 90° − tan−1 (y/x). f)θp = 90° − tan−1 (dy/dx). g)κp = |d2y/dx2|/[1 + (dy/dx)2]3/2. h)Because it has Ci symmetry, it is the same as BSe-∗-EBr. i)The regular-CS interaction of the CT-MC nature. j)The same as BSe-∗-DBr. k)The regular-CS interaction of the CT-TBP nature. l)The same as CBr-∗-DBr. m) The pure-CS interaction of the HB nature with no covalency. n)See ref. [39]. o)The regular-CS interaction of the HB nature with no covalency.
## 3.5. Nature of Br4σ(4c–6e)
Interactions are characterized by (R, θ), which correspond to the data from the fully optimized structures. On the contrary, they are characterized employing (θp, κp) derived from the data of the perturbed structures around the fully optimized structures and the fully optimized ones. In this case, the nature of interactions is substantially determined based of the (R, θ, θp) values, while the κp values are used only additionally. It is instructive to survey the criteria before detail discussion. The criteria tell us that 180° < θ (Hb(rc) − Vb(rc)/2 < 0) for the SS interactions, 90° < θ < 180° (Hb(rc) < 0) for the r-CS interactions, and 45° < θ < 90° (Hb(rc) > 0) for p-CS interactions. The θp value characterizes the interactions. In the p-CS region of 45° < θ < 90°, the character of interactions will be the vdW type for 45° < θp < 90°, whereas it will be the typical HB type without covalency (t-HBnc) for 90° < θp < 125°, where θp = 125° is tentatively given for θ = 90°. The CT interaction will appear in the r-CS region of 90° < θ < 180°. The t-HB type with covalency (t-HBwc) appears in the region of 125° < θp < 150° (90° < θ < 115°), where (θ, θp) = (115°, 150°) is tentatively given as the borderline between t-HBwc and the CT-MC nature. The borderline for the interactions between CT-MC and CT-TBP types is defined by θp = 180°. θ = 150° is tentatively given for θp = 180°. Classical chemical bonds of SS (180° < θ) will be strong (Cov-s) when R > 0.15 au, whereas they will be weak (Cov-w) for R < 0.15 au. The classification and characterization of interactions are summarized in Table S1 and Scheme S3 in Supplementary File.TheABr-∗-ABr and ABr-∗-BBr interactions of Br4σ(4c–6e) will be classified and characterized based on the (R, θ, θp) values, employing the standard values as a reference (see Scheme S2 in Supplementary File). R < 0.15 au for all interactions in Table 1; therefore, no Cov-s were detected in this work. The (θ, θp) values are (180.1°, 191.8°) for the original Br2 (D∞h) if evaluated with MP2/BSS-A. Therefore, the nature of Br-∗-Br in Br2 (D∞h) is classified by the SS interactions and characterized as the Cov-w nature, which is denoted by SS/Cov-w. The (θ, θp) values are (170.6–179.0°, 190.6–191.7°) for ABr-∗-ABr of Br4σ(4c–6e) in the optimized structures in Table 1, of which nature is r-CS/CT-TBP. The (θ, θp) values are (78.0–84.1°, 94.7–105.1°) for ABr-∗-BBr in the optimized structures of Br6 (C2), Br6 (C2h), and R2Br4 (C2h) (R = H and Me); therefore, the nature is predicted to be r-CS/t-HBwc. The nature of ABr-∗-BBr in R4Se2Br6 (Ci) (R = H and Me), 5 (Ci) and 6 (Ci), is r-CS/t-HBwc, judging from the (θ, θp) values of (90.9–92.8°, 116.4–122.5°). The calculated (θ, θp) values of ABr-∗-ABr and ABr-∗-BBr for the optimized structure of Br42− (D∞h) are (170.6°, 190.6°) and (89.5°, 118.2°), respectively. In this case, ABr-∗-ABr and ABr-∗-BBr are predicted to have the nature of r-CS/CT-TBP and p-CS/t-HBnc, respectively. However, ABr-∗-BBr is just the borderline region to the r-CS interactions with θ = 89.5°. The characteristic nature of the BE---AE-AE---BE interactions in Br42− (D∞h) would be controlled by the double negative charges in the species.The results in Table1 show that the ABr-∗-ABr interaction in Br4σ(4c–6e) becomes weaker, as the strength of the corresponding ABr-∗-BBr increases. The strength of ABr-∗-ABr becomes weaker in the order shown in equation (10), if evaluated by θ, while that of ABr-∗-BBr increases in the order shown in equation (11), if measured by θ. Very similar results were obtained by θp:(10)θforABr−∗−ABr:Br2D∞h>H2Br4C2h≥Br6C2andC2h>Me2Br4C2h>H4Se2Br6Ci≥Me4Se2Br6Ci≥1Ciobsd>5Ci>6Ci>Br6C2hobsd,(11)θforABr−∗−BBr:H2Br4C2h>Br6C2handC2≥Br6C2hobsd>Me2Br4C2h<1Ciobsd<Me4Se2Br6Ci<H4Se2Br6Ci<5Ci≈6Ci.The orders shown in equations (10) and (11) seem to reasonably explain the characteristic behavior of Br4σ(4c–6e). The results must be the reflection of the np(BBr) ⟶ σ∗(ABr-ABr) ← np(BBr) form of Br4σ(4c–6e), where ABr-∗-ABr and ABr-∗-BBr become weaker and stronger, respectively, as the CT interaction increases. Br4σ(4c–6e) will be stabilized more effectively, if the negative charge is developed more at BBr. However, the two Br− ligands in Br42− (D∞h) seem not so effective than that expected. This would come from the electrostatic repulsive factor between the double negative charges in Br42− (D∞h), as mentioned above.Theθ values for (ABr-∗-ABr and ABr-∗-BBr) in Br6 (C2h)obsd and 1 (Ci)obsd are (165.2°, 82.5°) and (175.3°, 87.7°), respectively. Therefore, ABr-∗-ABr and ABr-∗-BBr are classified by r-CS and p-CS, respectively. Both ABr-∗-ABr and ABr-∗-BBr in Br6 (C2h)obsd are predicted to be weaker than those in 1 (Ci)obsd, respectively. The results would be curious at the first glance, since ABr-∗-ABr will be weaker, if ABr-∗-BBr in BBr-∗-ABr-∗-ABr-∗-BBr becomes stronger, as mentioned above. They would be affected from the surrounding, such as the crystal packing effect. A Br2 molecule interacts with four bromine atoms adjacent to the Br2 molecule on the bc-plane in crystals, equivalently with 3.251 Å [40].Similar investigations were carried out for I4σ(4c–6e), which will be discussed elsewhere (it is demonstrated that Br4σ(4c–6e) is predicted to be somewhat stronger than I4σ(4c–6e)).
## 3.6. Nature of Se2Br5σ(7c–10e)
The nature of Se2Br5σ(7c–10e) in 7 (C2h) and 8 (C2h) is elucidated, together with SeBr2σ(3c–4e) in 3 and SeBr4σ(4c–6e) in 4. The results are collected in Table 2. Figure 6 shows symmetric ψ184 (HOMO) and antisymmetric ψ185 (LUMO) of 8 (C2h), which correspond to ψ5 and ψ6 in σ(7c–10e), illustrated in Figure 1 although the Se atoms are contained in the linear Se2Br5σ(7c–10e) in 8 (C2h). The linear seven atomic orbitals on Se2Br5 are shown to construct ψ184 (HOMO) and ψ185 (LUMO) of 8 (C2h), which can be analysed as the Se2Br5σ(7c–10e) [39], so can the linear interaction in 7 (C2h), although not shown. The pseudolinear interaction of the seven atoms of 1 (C1)obsd could also be explained by the Se2Br5σ(7c–10e) model.Figure 6
Molecular orbitals forσ(7c–10e). ψ184 (HOMO) and ψ185 (LUMO) of 8 (C2h).The results demonstrate that Se2Br5σ(7c–10e) stabilize well 7 (C2h) and 8 (C2h) although 1 (C1)obsd seems not so effective. The negative charge developed at the Br atom in 3 would not be sufficient to stabilize Se2Br5σ(7c–10e) in 1 (C1)obsd, relative to the case of the Br− anion in 7 (C2h) and 8 (C2h), irrespective of the highly negatively charged Br atoms in SeBr2σ(3c–4e) of 3.
## 4. Conclusion
The intrinsic dynamic and static nature of Br4σ(4c–6e) is elucidated for 1 (Ci)obsd and the related species with QTAIM-DFA, employing the perturbed structures generated with CIV. The ABr-ABr interactions in BBr-∗-ABr-∗-ABr-∗-BBr of Br4σ(4c–6e) are weaker than Br-∗-Br in the optimized structure of Br2 (D∞h), which is predicted to have the SS/Cov-w nature. The ABr-ABr interactions in Br4σ(4c–6e) of the models are predicted to have the r-CS/CT-TBP nature, if optimized with MP2/BSS-A. The ABr-ABr interaction in 1 (Ci)obsd also appears in the r-CS region. On the contrary, the ABr-BBr interactions in Br6 (C2), Br6 (C2h), H2Br4 (C2h), and Me2Br4 (C2h) are predicted to have the p-CS/t-HBnc nature, whereas those in H4Se2Br4 (Ci), Me4Se2Br4 (Ci), 5 (Ci), and 6 (Ci) have the r-CS/t-HBwc nature, if evaluated with MP2/BSS-A. The ABr-∗-BBr interactions become stronger in the order of H2Br4 (C2h) < Br6 (C2h) ≤ Br6 (C2) < Me2Br4 (C2h) << Me4Se2Br6 (Ci) ≤ H4Se2Br6 (Ci) ≤ 5 (Ci) < 6 (Ci), which is the inverse order for ABr-∗-ABr, as a whole. The results are in accordance with the CT interaction of the np(BBr) ⟶ σ∗(ABr-ABr) ← np(BBr) form derived from Br4σ(4c–6e). The decreased binding force of ABr-∗-ABr must be transferred to ABr-∗-BBr in Br4σ(4c–6e). Namely, it is demonstrated that Br4σ(4c–6e) is stabilized as the strength of ABr-∗-BBr in Br4σ(4c–6e) increases, while ABr-∗-ABr becomes weakened relative to that in the original Br2 (D∞h). In this process, Br4σ(4c–6e) is totally stabilized. The ABr-∗-ABr and ABr-∗-BBr interactions in Br6 (C2h)obsd and 1 (Ci)obsd are classified by the r-CS and p-CS interactions, respectively, where the interactions in Br6 (C2h)obsd seem somewhat weaker than those in 1 (Ci)obsd. The Se2Br5σ(7c–10e) interactions are similarly elucidated for 2 (C1)obsd and the anionic models of 7 (C2h) and 8 (C2h). The Se2Br5σ(7c–10e) nature is clearly established for the optimized structures of 7 (C2h) and 8 (C2h), rather than 2 (C1)obsd. Extended hypervalent interactions of the σ(mc–ne: 4 ≤ m; m < n < 2m) type are shown to be well analysed and evaluated with QTAIM-DFA, employing the perturbed structures generated with CIV, exemplified by Br4σ(4c–6e) and Se2Br5σ(7c–10e).
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*Source: 2901439-2020-07-24.xml* | 2020 |
# Estimation and Statistical Analysis of Human Voice Parameters to Investigate the Influence of Psychological Stress and to Determine the Vocal Tract Transfer Function of an Individual
**Authors:** Puneet Kumar Mongia; R. K. Sharma
**Journal:** Journal of Computer Networks and Communications
(2014)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2014/290147
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## Abstract
In this study the principal focus is to examine the influence of psychological stress (both positive and negative stress) on the human articulation and to determine the vocal tract transfer function of an individual using inverse filtering technique. Both of these analyses are carried out by estimating various voice parameters. The outcomes of the analysis of psychological stress indicate that all the voice parameters are affected due to the influence of stress on humans. About 35 out of 51 parameters follow a unique course of variation from normal to positive and negative stress in 32% of the total analyzed signals. The upshot of the analysis is to determine the vocal tract transfer function for each vowel for an individual. The analysis indicates that it can be computed by estimating the mean of the pole zero plots of that individual’s vocal tract estimated for the whole day. Besides this, an analysis is presented to find the relationship between the LPC coefficients of the vocal tract and the vocal tract cavities. The results of the analysis indicate that all the LPC coefficients of the vocal tract are affected due to change in the position of any cavity.
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## Body
## 1. Introduction
### 1.1. Voice Production Process
The process of voice production involves a sequence of complex biological activities. It originates from the production of airflow in the lungs, which is modulated by the vocal folds (for voice sounds). Spectral shaping of the modulated airflow is done by the vocal tract cavities which transfer the airflow to the lips to radiate the sound in the outside world. This process of voice production is very well discussed in [1–3]. A simplified view of speech production is shown in Figure 1. Here the speech organs are divided into three main parts: lungs, larynx, and vocal tract. Lungs are acting as a power supply which supplies air pressure signals to the larynx stage. The larynx modulates the airflow as is given by the lungs. It consists of two vocal folds or vocal cords. These folds are made up of masses of flesh, ligament, and muscles [2]. The basic functionality of these folds is to stretch between the front and back parts of the larynx. The glottis is a slit like space between the two folds. The vocal folds are open during breathing. But they can either be in open or vibrating condition depending upon the speaking state. In case of voice sources like vowels, the vocal folds are in a vibrating state. This means vocal folds are opening and closing rapidly. For other sources, the vocal folds are not vibrating rapidly [1]. After the larynx stage the signal passes through the vocal tract which consists of three cavities; pharynx cavity, oral cavity, and nasal cavity. These organs are helpful in shaping the modulated airflow spectrally and also in adjusting the quality of speech [2]. The vibration of the vocal folds in case of voice sources can be estimated in the form of a pulse called glottal pulse. A glottal pulse is shown in Figure 2. As we can see, initially the folds are in closed position (air flow is zero above vocal folds); then they are opening slowly (air flow is increasing); then they are fully open (air flow is maximized), and after that they are closing at a faster rate as shown in the figure. From this we can determine the time duration of one glottal cycle, which is known as pitch period and the reciprocal of pitch period is known as fundamental frequency [1]. The value of the fundamental frequency is influenced by many factors like vocal fold muscle tension, vocal fold mass, and the air pressure behind the vocal folds. The average pitch range is roughly 80 Hz to 400 Hz in males and 120 Hz to 800 Hz in females [2].Figure 1
Simplified view of speech production [1].Figure 2
Periodic glottal airflow waveform [1].As the glottal pulse or the excitation signal moves upward on its way through the mouth and nose, it encounters certain obstructions. First the wall of the throat (in the pharyngeal cavity) creates impedance in its path. This impedance causes certain resonance frequencies in the signal. The same effect is caused by the walls of the mouth surrounding the oral cavity and by the walls of the nose surrounding the nasal cavity. The sizes and conformations of these cavities are purely speaker dependent. The resonances of these three cavities (pharyngeal, oral, and nasal) are frequently called formants: the first formant, the second formant, and the third formant, respectively. These frequencies depend upon the shape and dimension of the vocal tract [4]. Because of the motion of organs like tongue, and teeth, higher formant values are likewise possible. As these formant values are immediately linked to the vocal tract cavities so these parameters are also very important and must be measured. After travelling through the vocal tract, the signal is radiated outwards in the form of speech through the lips or nose (in case of nasal voice signals).The parameters of these organs play a significant role in determining the speaker’s characteristics. Getting a true appraisal of these parameters helps us to see the operation of the human speech production mechanism in a more skillful way [5]. These parameters can be beneficial for many speech processing applications such as speaker recognition and speech synthesis [6]. Similarly in biomedical applications or clinical research for the analysis of psychological stress or alcohol intoxication, these parameters play an important role [7, 8]. There is some change in the values of these parameters for normal to diseased or stressed state [9]. So there is a need to effectively estimate these parameters from the voice signal.
### 1.2. Introduction to Stress
For a number of years the researchers in the field of Speech science and Laryngological studies, are constantly working on the acoustic characteristics of normal and pathological voice. Various methods have been modernized in this subject area for providing the quantitative data [10]. The major reason of growing research in this area is because of the importance of voice signal in determining the effect of clinical disorders like psychological stress. Stress or emphasis is mostly specified as a psychological state that is a reaction to a perceived threat or task demand and is normally accompanied by some specific emotions (e.g., fear, anger, or disgust) [11]. The long term occurrence of stress has serious health consequences [12]. The obvious question that comes to mind is how do we measure stress? The most accurate estimations of a person’s stress level can be found by measuring various psychological parameters, such as ECG, EEG or other biological signals, or some biochemical methods [9]. But all these methods require costly and large setup. However, it is very easy to analyze the voice or speech signal; hence this type of analysis is easy and inexpensive. In daily life we often use the term stress to identify negative emotions. However, stress can be classified in two parts, eustress which is a term for positive stress or emotion (like happiness) and distress, which refers to the negative stress or emotions (like anger, fear, or disgust). The positive stress motivates, focuses energy, feels exciting, and improves performance. In contrast, negative stress causes anxiety, feels unpleasant, and decreases performance [9].
### 1.3. Glottal Pulse Extraction
As discussed in the first section, the glottal airflow is filtered by the vocal tract to provide the air flow at the lip. This airflow is then converted to a pressure waveform at the lips and propagated as a sound signal. So, to get an estimate of the glottal airflow or glottal pulse, one needs to remove the effects of estimated vocal tract filter and lip radiation from the original speech signal. This technique is termed as inverse filtering, since in this process the estimated vocal tract filter and lip radiation effects are inversed to get the glottal flow estimate. MATLAB environment can be used to implement this technique [13–15].To receive such type of inverse filtering automatically, iterative adaptive inverse filtering (IAIF) algorithm has been used [16–18]. The block diagram of IAIF algorithm used is presented in Figure 3 [7]. Before estimation, the input speech signal is first high pass filtered using a linear-phase finite impulse response (FIR) filter with a cut-off frequency of 60 Hz to eliminate low frequency fluctuations and DC bias. The high pass filtered signal is used as the input to the next stages. The speech signal is divided into frames before filtering. In block 1, the LPC coefficient fit of order 1 is used to calculate the contribution of the glottal pulse to the speech signal. In the next block 2, this LPC coefficient of order 1 which symbolizes the force of the glottal pulse in the signal is used to design an inverse filter (all zero FIR filters) which is applied to get rid of the glottal effect of the original speech signal. So the input to block 3 represents the speech signal with the glottal flow component filtered out. Next in block 3, LPC fit of order 12 is used to capture the vocal tract filter effect in terms of filter coefficients. Here order 12 is chosen in accordance with the number of formant frequencies which is more than the double number of formants considered for the analysis [19, 20]. So in block 4, the vocal tract filter effect is removed from the original speech signal by inverse filtering. Signal out of this block consists of the effect of glottal flow and lip radiation effect. So to scrub out the radiation issue, a leaky integrator (with coefficient value more than 0.9 and less than 1) is used in block 5, which removes the lip radiation effect from the flow obtained after block 4. The output of block 5 is the first estimate of the glottal pulse. The second repetition runs analogously [7, 15]. The output of block 10 is the glottal pulse estimate of the original speech signal.Figure 3
Block diagram of IAIF.
### 1.4. Glottal Pulse and Its Derivative Parameters
The parameters of the glottal pulse can provide the quantitative information to examine their importance in the biomedical applications. There are three categories of glottal pulse parameters: time and amplitude domain, frequency domain, and glottal pulse derivative (LF) parameters. The time and amplitude domain parameters involve the extraction of certain time and amplitude instants from the glottal pulse. By counting on these timing instants, several time and amplitude based parameters can be calculated. These time instants can be specified using the glottal pulse and its derivative pulse as shown in Figure4.(i)
The fundamental time periodT is calculated using the fundamental frequency (f
o) of the signal frame.
(ii)
t
max
is that time instant when the amplitude of the glottal pulse is maximum or when the two vocal folds are completely open. t
min
can be defined similarly [21].
(iii)
A
a
c is the peak to peak amplitude level of the glottal pulse which is the difference between the maximum amplitude to the minimum amplitude of the glottal pulse [21].
(iv)
t
c is known as closure time instant which is the time instant when the two vocal folds are just about to close. This time instant is equal to that instant when the glottal pulse derivative pulse crosses to the positive amplitude after t
d
min
. Here t
d
min
is the time instant when the glottal pulse derivative pulse is at its minimum value [21].
(v)
t
o
1 and t
o
2 are the two opening time instants. To calculate t
o
1 first consider the time sequence which is having 10% amplitude of t
max
on the left side of it. Now go left from that time instant up to when the derivative pulse has approached the positive value of its amplitude. This time instant is the first opening time instant. For estimating t
o
2, first mark the time instant which is 5% more than t
o
1; then after this time instant look for the maximum positive value of the amplitude of the second derivative pulse of glottal waveform. That time instant is t
o
2. The importance of considering two opening instants is due to the more gradual opening of the glottal pulse than closing [21].
(vi)
t
q
c and t
q
o are the time instants where the amplitude of the glottal pulse is 50% of the peak to peak amplitude A
a
c [21].
(vii)
All the time based parameters are calculated with respect to the time instantt
max
[21].Time and amplitude instants in glottal pulse (a) and its derivative pulse (b) [15].
(a)
(b)From these timing instants, several time and amplitude based parameters can be calculated which are as follows.(i)
OQ (open quotient) measures the relative portion of the open phase compared to cycle duration. Two open quotients can be counted, namely, OQ1 and OQ2 [22].
(ii)
SQ (speed quotient) measures the ratio of the duration of opening phase to the duration of the closing phase. Possible speed quotients are SQ1 and SQ2 [22].
(iii)
CIQ (closing quotient) is the ratio of the duration of closing phase to the period lengthT [23].
(iv)
AQ (amplitude quotient) is the ratio of peak to peak amplitude level of glottal pulse and minimum amplitude of glottal pulse derivative [24, 25].
(v)
NAQ (normalized AQ) is the normalized value of AQ which is worked out by dividing AQ with the period lengthT [24, 25].
(vi)
QOQ (quasiopen quotient) is same as OQ except that it measures the relative portion of the quasitime instants, that is,t
q
c and t
q
o, compared to the cycle duration [26].
(vii)
OQ
a is the amplitude counterpart of OQ.Mathematically, these parameters can be developed as follows:(1)
OQ
1
=
t
c
-
t
o
1
T
,
OQ
2
=
t
c
-
t
o
2
T
,
OQ
a
=
A
a
c
Π
2
A
d
max
+
1
A
d
min
f
o
,
QOQ
=
t
q
c
-
t
q
o
T
,
SQ
1
=
t
max
-
t
o
1
t
c
-
t
max
,
SQ
2
=
t
max
-
t
o
2
t
c
-
t
max
,
CIQ
=
t
c
-
t
max
T
,
AQ
=
A
a
c
A
d
min
,
NAQ
=
AQ
T
.To estimate frequency domain parameters, the frequency or the power spectrum of the glottal pulse is considered as shown in Figure5 [15]. There are three main frequency domain parameters of the glottal pulse.Figure 5
Flow spectrum of a glottal pulse [15].First isH
1-H
2 or d
H
12 which is the difference of the first and second harmonics of the glottal frequency spectrum waveform in decibel [27]. Another similar parameter is harmonic richness factor (HRF), which is defined as the ratio between the sums of the amplitudes of harmonics above the fundamental frequency and the magnitude of the fundamental frequency or the first harmonic in decibels [28]. It is shown by the mathematical formula given below:
(2)
HRF
=
∑
r
≥
2
H
r
H
1
.HereH
r represents the magnitude of the rth harmonic. If H
1 increases, then H
1-H
2 will increase and HRF will decrease [15]. In [29], the author introduced another similar parameter, parabolic spectral parameter (PSP), which is the second order polynomial to the flow spectrum on a logarithmic scale, computed over a single glottal period [15].The final type of glottal pulse parameters is the glottal pulse derivative parameters. These parameters are termed as model based parameters because these parameters take on some mathematical expression on the glottal derivative pulse that generates an artificial derivative pulse. With the aid of the artificial pulse the model parameters are estimated. The most used mathematical model is Liljencrants-Fant (LF) model [7, 30]. It is a four parameter mathematical formulation of glottal flow derivative pulse [15]. It accepts applications in both voice analysis and speech synthesis [8, 31–35]. The spectral properties of glottal pulse parameters can also be considered with the aid of this model [36]. The LF approximated glottal derivative pulse is shown in Figure 6 [8].Figure 6
A typical approximation of glottal pulse (upper) and its derivative (lower) [8].Following are the timing instants and parameters of LF model.(i)
T
o
p is same as the opening time instant t
o
1 as we have talked about above.
(ii)
T
e is that time instant when the derivative pulse is having its minimum amplitude value [37].
(iii)
Time instantT
a is the timing instant of the tangent line drawn from the timing instant T
e to the right side of derivative pulse [37].
(iv)
Another timing instantT
p, is the instant when the derivative pulse crosses to zero amplitude level for the first time [38].
(v)
T
c is same as the glottal pulse closure time instant t
c.
(vi)
The parameterE
e is the magnitude of the slope of the negative going glottal pulse [38].From these timing instants a number of parameters can be obtained:(i)
(3)
R
a
=
T
a
′
f
o
,
whereT
a
′ time interval is equal to the difference between T
a and T
e and f
o is the fundamental frequency of the glottal pulse [32].
(ii)
(4)
R
g
=
1
2
T
p
′
f
o
,
whereT
p
′ time interval is equal to the difference between T
p and T
o
p [32].
(iii)
(5)
R
K
=
T
e
′
-
T
p
′
T
p
′
,
whereT
e
′ time interval is the difference between T
e and T
o
p [32].
(iv)
(6)
R
d
=
0.5
+
1.2
R
K
R
K
/
4
R
g
+
R
a
0.11
.
OQ (return) is the open quotient for return (closing) phase, which is calculated using the LF model. Consider(7)
OQ
=
T
e
′
f
o
=
1
+
R
K
2
R
g
.
### 1.5. Time, Frequency, and Energy Domain Parameters of Voice
To estimate the glottal parameters one has to apply several steps and algorithms for each frame of data. So if one does not want to look in depth of glottal based parameters, then, he can study the parameters that are directly estimated from the speech signal itself. Here in this section we will discuss time domain, frequency domain, and energy parameters of speech signal.(i)
Autocorrelation function is a time domain parameter of voice. It serves to see the similarity between a speech signal with itself after a little span of time. Let us consider a speech signals
(
n
) with a frame length of N samples. Let number of frames be m. Then the autocorrelation function of the speech signal for mth frame is defined as
(8)
r
m
=
1
2
N
+
1
∑
n
=
-
N
N
s
n
s
n
+
m
.
Whenm
=
0 then r
(
0
) represents the short term energy of the signal [39]. The value of the autocorrelation function varies between 0 and 1. It yields the value 1 if the speech signal is perfectly coupled with the signal frame just next to it.
(ii)
Harmonic to noise ratio (HNR) is the difference between the energies of the speech signal in periodic part and the energies of the signal in the noise in decibels. If HNR = 0 dB, then it implies that the energy in the harmonic part is equal to the energy in the noisy part. A large value of HNR is desirable in speech signals.
(iii)
Noise to harmonic ratio (NHR) is the average ratio of the energy of the noise components to the energy of the harmonic components present in the frequency range of speech signal. It evaluates noise present in the speech signal. Variations in amplitude, turbulence noise, subharmonic components, voice breaks, and so forth are considered in NHR. Low value of NHR is desirable in speech signals.
(iv)
Short time energy (STE) is defined as the energy of the short segment or frame of speech signal [40]. It can be applied as an effective parameter to differentiate between the voiced and unvoiced segments [41]. The short time energy can be expressed by the following mathematical expression:
(9)
STE
n
=
∑
n
s
n
w
n
-
m
2
.
Heres
(
n
) is the speech signal and w
(
n
) is the window function applied to the speech signal and m varies from 0 to n in a step of the frame size N, which means m
=
0
,
N
,
2
N
,
3
N
⋯
n
.
(v)
Energy entropy (EE) is a measure of the abrupt changes in energy. This is applied to observe silence and voiced region of speech segments. To calculate EE, first of all each frame is divided intoK subframes and energy of each sub frame is computed. Let e
i be the energy of a subframe, then EE of each frame is calculated using the formula [40]:
(10)
EE
=
-
∑
i
=
0
K
-
1
e
i
2
lo
g
2
e
i
2
.
(vi)
Zero crossing rate (ZCR) is a time domain parameter of speech signal. The number of times per second that the speech signal crosses the zero axis in a frame gives the ZCR in that frame [40]. Overall ZCR of the speech signal is computed by assuming the average value of all the individual ZCRs.
(vii)
Spectral centroid (SC) is used to characterize the center of mass of the speech spectrum. It is the weighted mean frequency for a given frame of the speech signal. Weights are the normalized energy of each frequency component in that frame. It can be helpful in detecting frequency peaks in the frame which can either correspond to the location of formants or pitch frequencies [42]. It is given by the formula below:
(11)
SC
=
∑
n
=
0
N
-
1
f
(
n
)
x
(
n
)
∑
n
=
0
N
-
1
x
(
n
)
.
Herex
(
n
) represents the weighted frequency value for the frame number n and f
(
n
) represents the center frequency value at that frame [40].
(viii)
Spectral flux (SF) is a measure which calculates how quickly the power spectrum of the signal is changing. It is the mean fluctuation of the power spectrum from one frame to the other frame. It is given by the formula below [40]:
(12)
SF
=
1
(
N
-
1
)
(
K
-
1
)
×
∑
n
=
1
N
-
1
∑
k
=
1
K
-
1
log
F
n
,
k
-
log
F
n
-
1
,
k
2
.
HereF
(
n
,
k
) is the FFT of the nth frame of the input speech signal, N is the total number of frames and K is the order of the FFT [40].
(ix)
Spectral roll off (SR) is a criterion of the spectral shape of sound like SC. It is that value of frequency for which 85% of the energy of the signal is less than that of frequency [40].
(x)
Jitter is a measure of period to period fluctuations in the fundamental frequency or pitch of the speech signal [43].Jitter in the signal is mainly affected due to the lack of control in the vibrations of the two vocal folds [44].Jitter can be assessed in many ways given below [43, 44]:
(a)
Jitter(absolute) is expressed as
(13)
J
i
t
t
e
r
abs
=
1
N
-
1
∑
k
=
1
N
-
1
T
k
-
T
k
+
1
.
HereN is the number of periods or frames of the signal and T
k is the pitch periods for the frame number k.
(b)
Jitter (relative) can be expressed equally:
(14)
J
i
t
t
e
r
relative
=
1
/
N
-
1
∑
k
=
1
N
-
1
T
k
-
T
k
+
1
1
/
N
∑
k
=
1
N
T
k
.
(c)
Jitter(rap) is the jitter calculated using relative average perturbation:
(15)
J
i
t
t
e
r
(
rap
)
=
1
/
N
-
2
∑
k
=
2
N
-
1
T
k
-
T
k
+
T
k
+
1
+
T
k
+
2
/
3
1
/
N
∑
k
=
1
N
T
k
.
(d)
Jitter(ppq5) is the five point period perturbation quotient jitter. It is computed as the average absolute difference between a period and the average of it and its four closest neighbors divided by the average period.
(xi)
Shimmer is a measure of period to period variation in the amplitudes of the speech signal [43]. It is affected mainly due to the reduction in the tension of the vocal folds [44].Shimmer can also be assessed in many ways listed below [43, 44]:
(a)
Shimmer (absolute) is the variation in the peak to peak amplitudes of the speech signal for consecutive periods taken in decibels. It can be expressed as
(16)
S
h
i
m
m
e
r
absolute
=
1
N
-
1
∑
k
=
1
N
-
1
20
log
A
k
+
1
A
k
.
HereA
k is the peak to peak amplitude for the current frame k and N is the number of frames.
(b)
Shimmer (relative) is the average absolute difference between the amplitudes of consecutive periods, divided by the average amplitude. It can be expressed as
(17)
S
h
i
m
m
e
r
relative
=
1
/
N
-
1
∑
k
=
1
N
-
1
A
k
-
A
k
+
1
1
/
N
∑
k
=
1
N
A
k
.
(c)
Shimmer(apq3) is the three point amplitude perturbation quotient which can be computed by considering the mean absolute deviation between the amplitude of a period and average of the amplitudes of its neighbors divided by the mean amplitude of the period. It can be expressed as
(18)
S
h
i
m
m
e
r
apq
3
=
1
/
N
-
2
∑
k
=
2
N
-
1
A
k
-
A
k
+
A
k
-
1
+
A
k
+
1
/
3
1
/
N
∑
k
=
1
N
-
1
A
k
.
(d)
SimilarlyShimmer(apq5) andShimmer(apq11) can be determined.It is said thatjitter(absolute) andshimmer(absolute) are useful in speaker recognition [44].(i)
Intensity or vocal intensity of the speech signal refers to the loudness effect of speech signal. Vocal intensity is related to the subglottis pressure of the airflow, which depends on the tension and the vibrations of the vocal folds [44]. A small number of vibrations in the vocal folds make quieter voice as compared to the large number of vibrations of the folds [45]. Mathematically vocal intensity can be expressed as sound intensity level (SIL) or sound pressure level (SPL) [46]. SIL or SPL is measured in dBs. SIL basically tells how much louder a given sound is as compared to the standard (soft) reference vocal intensity, of 10–12 watt/m2. This can be determined by [46]
(19)
SIL
=
10
log
I
I
0
dB
,
whereI
0 is the standard intensity value and sound intensity can also be expressed in terms of SPL also. Consider
(20)
SPL
=
10
log
P
P
0
dB
.
HereP
0 is the standard pressure level and is having the value of 0.00002 Pascal. SIL and SPL describe the same point of acoustic energy and can be used interchangeably [46].The formant frequencies can be estimated by taking the frequency response of the vocal tract filter. The peaks of the response are the formant frequencies. The amplitude and bandwidth values at those peaks are also very important parameters and must be considered.
## 1.1. Voice Production Process
The process of voice production involves a sequence of complex biological activities. It originates from the production of airflow in the lungs, which is modulated by the vocal folds (for voice sounds). Spectral shaping of the modulated airflow is done by the vocal tract cavities which transfer the airflow to the lips to radiate the sound in the outside world. This process of voice production is very well discussed in [1–3]. A simplified view of speech production is shown in Figure 1. Here the speech organs are divided into three main parts: lungs, larynx, and vocal tract. Lungs are acting as a power supply which supplies air pressure signals to the larynx stage. The larynx modulates the airflow as is given by the lungs. It consists of two vocal folds or vocal cords. These folds are made up of masses of flesh, ligament, and muscles [2]. The basic functionality of these folds is to stretch between the front and back parts of the larynx. The glottis is a slit like space between the two folds. The vocal folds are open during breathing. But they can either be in open or vibrating condition depending upon the speaking state. In case of voice sources like vowels, the vocal folds are in a vibrating state. This means vocal folds are opening and closing rapidly. For other sources, the vocal folds are not vibrating rapidly [1]. After the larynx stage the signal passes through the vocal tract which consists of three cavities; pharynx cavity, oral cavity, and nasal cavity. These organs are helpful in shaping the modulated airflow spectrally and also in adjusting the quality of speech [2]. The vibration of the vocal folds in case of voice sources can be estimated in the form of a pulse called glottal pulse. A glottal pulse is shown in Figure 2. As we can see, initially the folds are in closed position (air flow is zero above vocal folds); then they are opening slowly (air flow is increasing); then they are fully open (air flow is maximized), and after that they are closing at a faster rate as shown in the figure. From this we can determine the time duration of one glottal cycle, which is known as pitch period and the reciprocal of pitch period is known as fundamental frequency [1]. The value of the fundamental frequency is influenced by many factors like vocal fold muscle tension, vocal fold mass, and the air pressure behind the vocal folds. The average pitch range is roughly 80 Hz to 400 Hz in males and 120 Hz to 800 Hz in females [2].Figure 1
Simplified view of speech production [1].Figure 2
Periodic glottal airflow waveform [1].As the glottal pulse or the excitation signal moves upward on its way through the mouth and nose, it encounters certain obstructions. First the wall of the throat (in the pharyngeal cavity) creates impedance in its path. This impedance causes certain resonance frequencies in the signal. The same effect is caused by the walls of the mouth surrounding the oral cavity and by the walls of the nose surrounding the nasal cavity. The sizes and conformations of these cavities are purely speaker dependent. The resonances of these three cavities (pharyngeal, oral, and nasal) are frequently called formants: the first formant, the second formant, and the third formant, respectively. These frequencies depend upon the shape and dimension of the vocal tract [4]. Because of the motion of organs like tongue, and teeth, higher formant values are likewise possible. As these formant values are immediately linked to the vocal tract cavities so these parameters are also very important and must be measured. After travelling through the vocal tract, the signal is radiated outwards in the form of speech through the lips or nose (in case of nasal voice signals).The parameters of these organs play a significant role in determining the speaker’s characteristics. Getting a true appraisal of these parameters helps us to see the operation of the human speech production mechanism in a more skillful way [5]. These parameters can be beneficial for many speech processing applications such as speaker recognition and speech synthesis [6]. Similarly in biomedical applications or clinical research for the analysis of psychological stress or alcohol intoxication, these parameters play an important role [7, 8]. There is some change in the values of these parameters for normal to diseased or stressed state [9]. So there is a need to effectively estimate these parameters from the voice signal.
## 1.2. Introduction to Stress
For a number of years the researchers in the field of Speech science and Laryngological studies, are constantly working on the acoustic characteristics of normal and pathological voice. Various methods have been modernized in this subject area for providing the quantitative data [10]. The major reason of growing research in this area is because of the importance of voice signal in determining the effect of clinical disorders like psychological stress. Stress or emphasis is mostly specified as a psychological state that is a reaction to a perceived threat or task demand and is normally accompanied by some specific emotions (e.g., fear, anger, or disgust) [11]. The long term occurrence of stress has serious health consequences [12]. The obvious question that comes to mind is how do we measure stress? The most accurate estimations of a person’s stress level can be found by measuring various psychological parameters, such as ECG, EEG or other biological signals, or some biochemical methods [9]. But all these methods require costly and large setup. However, it is very easy to analyze the voice or speech signal; hence this type of analysis is easy and inexpensive. In daily life we often use the term stress to identify negative emotions. However, stress can be classified in two parts, eustress which is a term for positive stress or emotion (like happiness) and distress, which refers to the negative stress or emotions (like anger, fear, or disgust). The positive stress motivates, focuses energy, feels exciting, and improves performance. In contrast, negative stress causes anxiety, feels unpleasant, and decreases performance [9].
## 1.3. Glottal Pulse Extraction
As discussed in the first section, the glottal airflow is filtered by the vocal tract to provide the air flow at the lip. This airflow is then converted to a pressure waveform at the lips and propagated as a sound signal. So, to get an estimate of the glottal airflow or glottal pulse, one needs to remove the effects of estimated vocal tract filter and lip radiation from the original speech signal. This technique is termed as inverse filtering, since in this process the estimated vocal tract filter and lip radiation effects are inversed to get the glottal flow estimate. MATLAB environment can be used to implement this technique [13–15].To receive such type of inverse filtering automatically, iterative adaptive inverse filtering (IAIF) algorithm has been used [16–18]. The block diagram of IAIF algorithm used is presented in Figure 3 [7]. Before estimation, the input speech signal is first high pass filtered using a linear-phase finite impulse response (FIR) filter with a cut-off frequency of 60 Hz to eliminate low frequency fluctuations and DC bias. The high pass filtered signal is used as the input to the next stages. The speech signal is divided into frames before filtering. In block 1, the LPC coefficient fit of order 1 is used to calculate the contribution of the glottal pulse to the speech signal. In the next block 2, this LPC coefficient of order 1 which symbolizes the force of the glottal pulse in the signal is used to design an inverse filter (all zero FIR filters) which is applied to get rid of the glottal effect of the original speech signal. So the input to block 3 represents the speech signal with the glottal flow component filtered out. Next in block 3, LPC fit of order 12 is used to capture the vocal tract filter effect in terms of filter coefficients. Here order 12 is chosen in accordance with the number of formant frequencies which is more than the double number of formants considered for the analysis [19, 20]. So in block 4, the vocal tract filter effect is removed from the original speech signal by inverse filtering. Signal out of this block consists of the effect of glottal flow and lip radiation effect. So to scrub out the radiation issue, a leaky integrator (with coefficient value more than 0.9 and less than 1) is used in block 5, which removes the lip radiation effect from the flow obtained after block 4. The output of block 5 is the first estimate of the glottal pulse. The second repetition runs analogously [7, 15]. The output of block 10 is the glottal pulse estimate of the original speech signal.Figure 3
Block diagram of IAIF.
## 1.4. Glottal Pulse and Its Derivative Parameters
The parameters of the glottal pulse can provide the quantitative information to examine their importance in the biomedical applications. There are three categories of glottal pulse parameters: time and amplitude domain, frequency domain, and glottal pulse derivative (LF) parameters. The time and amplitude domain parameters involve the extraction of certain time and amplitude instants from the glottal pulse. By counting on these timing instants, several time and amplitude based parameters can be calculated. These time instants can be specified using the glottal pulse and its derivative pulse as shown in Figure4.(i)
The fundamental time periodT is calculated using the fundamental frequency (f
o) of the signal frame.
(ii)
t
max
is that time instant when the amplitude of the glottal pulse is maximum or when the two vocal folds are completely open. t
min
can be defined similarly [21].
(iii)
A
a
c is the peak to peak amplitude level of the glottal pulse which is the difference between the maximum amplitude to the minimum amplitude of the glottal pulse [21].
(iv)
t
c is known as closure time instant which is the time instant when the two vocal folds are just about to close. This time instant is equal to that instant when the glottal pulse derivative pulse crosses to the positive amplitude after t
d
min
. Here t
d
min
is the time instant when the glottal pulse derivative pulse is at its minimum value [21].
(v)
t
o
1 and t
o
2 are the two opening time instants. To calculate t
o
1 first consider the time sequence which is having 10% amplitude of t
max
on the left side of it. Now go left from that time instant up to when the derivative pulse has approached the positive value of its amplitude. This time instant is the first opening time instant. For estimating t
o
2, first mark the time instant which is 5% more than t
o
1; then after this time instant look for the maximum positive value of the amplitude of the second derivative pulse of glottal waveform. That time instant is t
o
2. The importance of considering two opening instants is due to the more gradual opening of the glottal pulse than closing [21].
(vi)
t
q
c and t
q
o are the time instants where the amplitude of the glottal pulse is 50% of the peak to peak amplitude A
a
c [21].
(vii)
All the time based parameters are calculated with respect to the time instantt
max
[21].Time and amplitude instants in glottal pulse (a) and its derivative pulse (b) [15].
(a)
(b)From these timing instants, several time and amplitude based parameters can be calculated which are as follows.(i)
OQ (open quotient) measures the relative portion of the open phase compared to cycle duration. Two open quotients can be counted, namely, OQ1 and OQ2 [22].
(ii)
SQ (speed quotient) measures the ratio of the duration of opening phase to the duration of the closing phase. Possible speed quotients are SQ1 and SQ2 [22].
(iii)
CIQ (closing quotient) is the ratio of the duration of closing phase to the period lengthT [23].
(iv)
AQ (amplitude quotient) is the ratio of peak to peak amplitude level of glottal pulse and minimum amplitude of glottal pulse derivative [24, 25].
(v)
NAQ (normalized AQ) is the normalized value of AQ which is worked out by dividing AQ with the period lengthT [24, 25].
(vi)
QOQ (quasiopen quotient) is same as OQ except that it measures the relative portion of the quasitime instants, that is,t
q
c and t
q
o, compared to the cycle duration [26].
(vii)
OQ
a is the amplitude counterpart of OQ.Mathematically, these parameters can be developed as follows:(1)
OQ
1
=
t
c
-
t
o
1
T
,
OQ
2
=
t
c
-
t
o
2
T
,
OQ
a
=
A
a
c
Π
2
A
d
max
+
1
A
d
min
f
o
,
QOQ
=
t
q
c
-
t
q
o
T
,
SQ
1
=
t
max
-
t
o
1
t
c
-
t
max
,
SQ
2
=
t
max
-
t
o
2
t
c
-
t
max
,
CIQ
=
t
c
-
t
max
T
,
AQ
=
A
a
c
A
d
min
,
NAQ
=
AQ
T
.To estimate frequency domain parameters, the frequency or the power spectrum of the glottal pulse is considered as shown in Figure5 [15]. There are three main frequency domain parameters of the glottal pulse.Figure 5
Flow spectrum of a glottal pulse [15].First isH
1-H
2 or d
H
12 which is the difference of the first and second harmonics of the glottal frequency spectrum waveform in decibel [27]. Another similar parameter is harmonic richness factor (HRF), which is defined as the ratio between the sums of the amplitudes of harmonics above the fundamental frequency and the magnitude of the fundamental frequency or the first harmonic in decibels [28]. It is shown by the mathematical formula given below:
(2)
HRF
=
∑
r
≥
2
H
r
H
1
.HereH
r represents the magnitude of the rth harmonic. If H
1 increases, then H
1-H
2 will increase and HRF will decrease [15]. In [29], the author introduced another similar parameter, parabolic spectral parameter (PSP), which is the second order polynomial to the flow spectrum on a logarithmic scale, computed over a single glottal period [15].The final type of glottal pulse parameters is the glottal pulse derivative parameters. These parameters are termed as model based parameters because these parameters take on some mathematical expression on the glottal derivative pulse that generates an artificial derivative pulse. With the aid of the artificial pulse the model parameters are estimated. The most used mathematical model is Liljencrants-Fant (LF) model [7, 30]. It is a four parameter mathematical formulation of glottal flow derivative pulse [15]. It accepts applications in both voice analysis and speech synthesis [8, 31–35]. The spectral properties of glottal pulse parameters can also be considered with the aid of this model [36]. The LF approximated glottal derivative pulse is shown in Figure 6 [8].Figure 6
A typical approximation of glottal pulse (upper) and its derivative (lower) [8].Following are the timing instants and parameters of LF model.(i)
T
o
p is same as the opening time instant t
o
1 as we have talked about above.
(ii)
T
e is that time instant when the derivative pulse is having its minimum amplitude value [37].
(iii)
Time instantT
a is the timing instant of the tangent line drawn from the timing instant T
e to the right side of derivative pulse [37].
(iv)
Another timing instantT
p, is the instant when the derivative pulse crosses to zero amplitude level for the first time [38].
(v)
T
c is same as the glottal pulse closure time instant t
c.
(vi)
The parameterE
e is the magnitude of the slope of the negative going glottal pulse [38].From these timing instants a number of parameters can be obtained:(i)
(3)
R
a
=
T
a
′
f
o
,
whereT
a
′ time interval is equal to the difference between T
a and T
e and f
o is the fundamental frequency of the glottal pulse [32].
(ii)
(4)
R
g
=
1
2
T
p
′
f
o
,
whereT
p
′ time interval is equal to the difference between T
p and T
o
p [32].
(iii)
(5)
R
K
=
T
e
′
-
T
p
′
T
p
′
,
whereT
e
′ time interval is the difference between T
e and T
o
p [32].
(iv)
(6)
R
d
=
0.5
+
1.2
R
K
R
K
/
4
R
g
+
R
a
0.11
.
OQ (return) is the open quotient for return (closing) phase, which is calculated using the LF model. Consider(7)
OQ
=
T
e
′
f
o
=
1
+
R
K
2
R
g
.
## 1.5. Time, Frequency, and Energy Domain Parameters of Voice
To estimate the glottal parameters one has to apply several steps and algorithms for each frame of data. So if one does not want to look in depth of glottal based parameters, then, he can study the parameters that are directly estimated from the speech signal itself. Here in this section we will discuss time domain, frequency domain, and energy parameters of speech signal.(i)
Autocorrelation function is a time domain parameter of voice. It serves to see the similarity between a speech signal with itself after a little span of time. Let us consider a speech signals
(
n
) with a frame length of N samples. Let number of frames be m. Then the autocorrelation function of the speech signal for mth frame is defined as
(8)
r
m
=
1
2
N
+
1
∑
n
=
-
N
N
s
n
s
n
+
m
.
Whenm
=
0 then r
(
0
) represents the short term energy of the signal [39]. The value of the autocorrelation function varies between 0 and 1. It yields the value 1 if the speech signal is perfectly coupled with the signal frame just next to it.
(ii)
Harmonic to noise ratio (HNR) is the difference between the energies of the speech signal in periodic part and the energies of the signal in the noise in decibels. If HNR = 0 dB, then it implies that the energy in the harmonic part is equal to the energy in the noisy part. A large value of HNR is desirable in speech signals.
(iii)
Noise to harmonic ratio (NHR) is the average ratio of the energy of the noise components to the energy of the harmonic components present in the frequency range of speech signal. It evaluates noise present in the speech signal. Variations in amplitude, turbulence noise, subharmonic components, voice breaks, and so forth are considered in NHR. Low value of NHR is desirable in speech signals.
(iv)
Short time energy (STE) is defined as the energy of the short segment or frame of speech signal [40]. It can be applied as an effective parameter to differentiate between the voiced and unvoiced segments [41]. The short time energy can be expressed by the following mathematical expression:
(9)
STE
n
=
∑
n
s
n
w
n
-
m
2
.
Heres
(
n
) is the speech signal and w
(
n
) is the window function applied to the speech signal and m varies from 0 to n in a step of the frame size N, which means m
=
0
,
N
,
2
N
,
3
N
⋯
n
.
(v)
Energy entropy (EE) is a measure of the abrupt changes in energy. This is applied to observe silence and voiced region of speech segments. To calculate EE, first of all each frame is divided intoK subframes and energy of each sub frame is computed. Let e
i be the energy of a subframe, then EE of each frame is calculated using the formula [40]:
(10)
EE
=
-
∑
i
=
0
K
-
1
e
i
2
lo
g
2
e
i
2
.
(vi)
Zero crossing rate (ZCR) is a time domain parameter of speech signal. The number of times per second that the speech signal crosses the zero axis in a frame gives the ZCR in that frame [40]. Overall ZCR of the speech signal is computed by assuming the average value of all the individual ZCRs.
(vii)
Spectral centroid (SC) is used to characterize the center of mass of the speech spectrum. It is the weighted mean frequency for a given frame of the speech signal. Weights are the normalized energy of each frequency component in that frame. It can be helpful in detecting frequency peaks in the frame which can either correspond to the location of formants or pitch frequencies [42]. It is given by the formula below:
(11)
SC
=
∑
n
=
0
N
-
1
f
(
n
)
x
(
n
)
∑
n
=
0
N
-
1
x
(
n
)
.
Herex
(
n
) represents the weighted frequency value for the frame number n and f
(
n
) represents the center frequency value at that frame [40].
(viii)
Spectral flux (SF) is a measure which calculates how quickly the power spectrum of the signal is changing. It is the mean fluctuation of the power spectrum from one frame to the other frame. It is given by the formula below [40]:
(12)
SF
=
1
(
N
-
1
)
(
K
-
1
)
×
∑
n
=
1
N
-
1
∑
k
=
1
K
-
1
log
F
n
,
k
-
log
F
n
-
1
,
k
2
.
HereF
(
n
,
k
) is the FFT of the nth frame of the input speech signal, N is the total number of frames and K is the order of the FFT [40].
(ix)
Spectral roll off (SR) is a criterion of the spectral shape of sound like SC. It is that value of frequency for which 85% of the energy of the signal is less than that of frequency [40].
(x)
Jitter is a measure of period to period fluctuations in the fundamental frequency or pitch of the speech signal [43].Jitter in the signal is mainly affected due to the lack of control in the vibrations of the two vocal folds [44].Jitter can be assessed in many ways given below [43, 44]:
(a)
Jitter(absolute) is expressed as
(13)
J
i
t
t
e
r
abs
=
1
N
-
1
∑
k
=
1
N
-
1
T
k
-
T
k
+
1
.
HereN is the number of periods or frames of the signal and T
k is the pitch periods for the frame number k.
(b)
Jitter (relative) can be expressed equally:
(14)
J
i
t
t
e
r
relative
=
1
/
N
-
1
∑
k
=
1
N
-
1
T
k
-
T
k
+
1
1
/
N
∑
k
=
1
N
T
k
.
(c)
Jitter(rap) is the jitter calculated using relative average perturbation:
(15)
J
i
t
t
e
r
(
rap
)
=
1
/
N
-
2
∑
k
=
2
N
-
1
T
k
-
T
k
+
T
k
+
1
+
T
k
+
2
/
3
1
/
N
∑
k
=
1
N
T
k
.
(d)
Jitter(ppq5) is the five point period perturbation quotient jitter. It is computed as the average absolute difference between a period and the average of it and its four closest neighbors divided by the average period.
(xi)
Shimmer is a measure of period to period variation in the amplitudes of the speech signal [43]. It is affected mainly due to the reduction in the tension of the vocal folds [44].Shimmer can also be assessed in many ways listed below [43, 44]:
(a)
Shimmer (absolute) is the variation in the peak to peak amplitudes of the speech signal for consecutive periods taken in decibels. It can be expressed as
(16)
S
h
i
m
m
e
r
absolute
=
1
N
-
1
∑
k
=
1
N
-
1
20
log
A
k
+
1
A
k
.
HereA
k is the peak to peak amplitude for the current frame k and N is the number of frames.
(b)
Shimmer (relative) is the average absolute difference between the amplitudes of consecutive periods, divided by the average amplitude. It can be expressed as
(17)
S
h
i
m
m
e
r
relative
=
1
/
N
-
1
∑
k
=
1
N
-
1
A
k
-
A
k
+
1
1
/
N
∑
k
=
1
N
A
k
.
(c)
Shimmer(apq3) is the three point amplitude perturbation quotient which can be computed by considering the mean absolute deviation between the amplitude of a period and average of the amplitudes of its neighbors divided by the mean amplitude of the period. It can be expressed as
(18)
S
h
i
m
m
e
r
apq
3
=
1
/
N
-
2
∑
k
=
2
N
-
1
A
k
-
A
k
+
A
k
-
1
+
A
k
+
1
/
3
1
/
N
∑
k
=
1
N
-
1
A
k
.
(d)
SimilarlyShimmer(apq5) andShimmer(apq11) can be determined.It is said thatjitter(absolute) andshimmer(absolute) are useful in speaker recognition [44].(i)
Intensity or vocal intensity of the speech signal refers to the loudness effect of speech signal. Vocal intensity is related to the subglottis pressure of the airflow, which depends on the tension and the vibrations of the vocal folds [44]. A small number of vibrations in the vocal folds make quieter voice as compared to the large number of vibrations of the folds [45]. Mathematically vocal intensity can be expressed as sound intensity level (SIL) or sound pressure level (SPL) [46]. SIL or SPL is measured in dBs. SIL basically tells how much louder a given sound is as compared to the standard (soft) reference vocal intensity, of 10–12 watt/m2. This can be determined by [46]
(19)
SIL
=
10
log
I
I
0
dB
,
whereI
0 is the standard intensity value and sound intensity can also be expressed in terms of SPL also. Consider
(20)
SPL
=
10
log
P
P
0
dB
.
HereP
0 is the standard pressure level and is having the value of 0.00002 Pascal. SIL and SPL describe the same point of acoustic energy and can be used interchangeably [46].The formant frequencies can be estimated by taking the frequency response of the vocal tract filter. The peaks of the response are the formant frequencies. The amplitude and bandwidth values at those peaks are also very important parameters and must be considered.
## 2. Results and Discussion
This section describes the experiments performed and results produced by those experiments. The experimental methodology is first outlined and then followed by the results of the experiment. Let us discuss various experiments performed on the voice parameters.
### 2.1. Estimation of Glottal Flow
The goal of this experiment was to estimate the glottal flow or glottal pulses from the voice signal of vowels using IAIF algorithm described in the above section by using MATLAB as well as SIMULINK [16–18]. The foremost prerequisite of this algorithm is to obtain the predictor coefficients from the speech signal. For this, lpc function in MATLAB or lpc model of SIMULINK can be used [13, 14]. The speech signal recordings were available in wav format. The speech signals were converted into data samples by taking the sampling frequency of 10 KHz using MATLAB. The workspace block was used to take those samples in SIMULINK. Digital filter design blocks were used for FIR high pass and inverse filtering. The Autocorrelation LPC blocks were employed to get the predictor coefficients. The digital Integrator block was used for integration. The SIMULINK model of the IAIF algorithm is shown in Figure 7.Figure 7
SIMULINK model of IAIF algorithm.The input speech waveform and output glottal waveform for vowel /a/ are shown in Figure8.Input speech waveform and Output glottal waveform of IAIF algorithm for vowel /a/.
(a)
(b)Using the MATLAB code of IAIF algorithm, glottal pulses of five vowels /a/, /e/, /i/, /o/, /u/ obtained are shown in Figure9.Glottal pulses for five vowels /a/, /e/, /i/, /o/, and /u/, respectively.
(a)
(b)
(c)
(d)
(e)
### 2.2. Comparison of Computed Formant Frequencies
Using the inverse filtering technique the formant parameters can be computed by using two methods. One of them is to find out the peaks of the frequency response of the vocal tract filter and other is to find out the roots of the polynomial equation formed using LPC coefficients of vocal tract filter as explained in [9]. This experimentation was performed to compare the computed formant frequencies by those two methods with the values obtained using phonetic software PRAAT [47].A total of 15 speech signals were analyzed and four formant frequencies were computed for each case. The speech signals used consist of five vowel segments each for male, female, and child and are available in [48]. In 12 of them (80% of the total), formant values obtained using the two methods above were rather near to the values computed using PRAAT software. In case of LPC polynomial root method, some false formants were also noted. So this idea is not so precise and should be used rarely. By applying these methods, we can also compute the 3 dB bandwidth values and amplitude values for each formant [9].Tables1 and 2 are shown for male vowel /i/ and child vowel /a/.Table 1
Comparison of computed formant frequencies for male vowel /i/.
Formant number
By roots
By response
By PRAAT
1
241.3
244.1
233.5
2
2263.6
2270.5
2246.1
3
3194.5
3203.1
3148.6
4
3832.6
3837.9
3828.7Table 2
A comparison of computed formant frequencies for child vowel /a/.
Formant number
By roots
By response
By PRAAT
1
532.5
546.9
549.5
2
1194.1
1196.3
1259.4
3
1807.9
1801.8
1872.6
4
3903.8
3911.1
3893.7
### 2.3. LPC Coefficients versus Vocal Tract Cavities
As we have discussed in the first section that inverse filtering and LPC coefficients approach can be used to model the human vocal tract and is helpful in determining the formant frequencies, so there can be some relationship between the LPC coefficients of the vocal tract and vocal tract cavities. This relationship can be helpful in determining which LPC coefficient of the vocal tract corresponds to which cavity of the vocal tract. It was talked about in the beginning section that each cavity of the vocal tract corresponds to a formant frequency and in the last experiment, we have computed formant frequencies using LPC coefficients of the vocal tract calculated during the final stage of IAIF algorithm. So a relationship can be derived between LPC coefficients and formant frequencies. To derive a relationship 5 speech signals (different persons) were taken. In each signal, each LPC coefficient of the vocal tract was changed (increased and decreased) from 5 to 50%. Corresponding to each change all the formant parameters (frequencies, amplitudes, and bandwidths) were estimated. So for a single signal a total of 24 sets of parameters (both increased and decreased) were tabulated. So for five signals a total of 120(
24
*
5
) sets of parameters were tabulated. A single set of the table for the first signal for a change up to 20% is shown in Table 3. This table determines the change in the formant parameters when the 1st LPC coefficient of the vocal tract is increased. Here bold values determine that the corresponding value is more than its original value when no parameter was changed. The original values of the parameters are depicted in Table 4.Table 3
Change in the formant parameters when a single coefficient value is changed from 5 to 20%.
Parameters/change
5%
10%
15%
20%
F
1 (Hz)
551.0
542.0
532.0
512.7
A
1 (dB)
31.2
29.7
20.7
16.4
B
1 (Hz)
37.4
47.6
138.0
225.0
F
2 (Hz)
913.0
883.8
849
825.2
A
2 (dB)
22.1
19.4
16.9
14.6
B
2 (Hz)
98.7
144.3
196.0
245.2
F
3 (Hz)
1967.0
1958.0
1953.0
1948.2
A
3 (dB)
3.3
2.8
2.4
1.9
B
3 (Hz)
312.0
323.9
335.0
348.1
F
4 (Hz)
3291.0
3281.2
3276.0
3271.5
A
4 (dB)
8.6
7.4
6.4
5.4
B
4 (Hz)
228.0
253.4
277.0
310.4
F
5 (Hz)
3842.0
3847.7
3857.0
3867.2
A
5 (dB)
11.9
11.0
10.2
9.4
B
5 (Hz)
84.6
89.0
93.5
98.2Table 4
Original values.
F
1 (Hz)
556.6
A
1 (dB)
21.1
B
1 (Hz)
109.7
F
2 (Hz)
947.3
A
2 (dB)
24.7
B
2 (Hz)
66.3
F
3 (Hz)
1977.5
A
3 (dB)
3.7
B
3 (Hz)
300.2
F
4 (Hz)
3300.8
A
4 (dB)
9.9
B
4 (Hz)
80.4
F
5 (Hz)
3833.0
A
5 (dB)
12.8
B
5 (Hz)
201.9After analyzing all the data, the following conclusions were derived.(i)
All the formant parameters were altered due to change in a single coefficient. This signifies that all the portions of the vocal tract are associated to each coefficient.
(ii)
Obtained results indicate that these variations follow an individual trend rather than any global trend. So this type of analysis is purely speaker dependent.
(iii)
Yet a similar trend can be imaged in the change of the value of formant frequencies of all the signals.
(iv)
FormantF1 changes (either increase or decrease) the most, if any individual coefficient is changed.
(v)
After that formantF2 andF4 come in 2nd and 3rd place in the list.
(vi)
In 4 out of 5 signals,F3 comes afterF4, and in 1 signalF5 comes afterF4.
(vii)
No such character of pattern was obtained for amplitudes and bandwidths.
(viii)
Nevertheless, in some cases an opposite tendency was seen in bandwidth and amplitude, meaning that if bandwidth was increasing, the amplitude was also decreasing for the whole change.Figure 10 shows diagrammatically the change in formant values along with bandwidths and amplitudes for a sample.Figure 10
Variations in the formant parameters due to change in LPC coefficients for a signal.
### 2.4. Estimation of Vocal Tract Transfer Function for an Individual
According to source-filter theory of speech production, to model the speech production mechanism digitally, we need to consider separate elements of speech production. The speech production system can be modelled with three separate elements: the source, the vocal tract filter, and the radiation effects [17]. The steady state system function of the digital filter is given by the expression:
(21)
H
z
=
S
z
U
z
=
G
1
-
∑
k
=
1
p
a
k
z
-
k
.The primary purpose of this experimentation was to somehow count for a method to forecast or predict the transfer function of vocal tract for an individual. The methodology used was first to calculate the vocal tract predictor coefficients for a signal from the final stage of IAIF algorithm and the gain factorG using lpc function in MATLAB, then by the use of (21) pole zero plot was plotted. As we have discussed before that the LPC order for the vocal tract filter taken is 12 so there will be 12 poles in the transfer function of the vocal tract (Section 1.3).The experimentation was done on two male persons of ages 24 and 26, respectively, by recording their voice samples using Sony IC Recorder (ICD-UX513F) device. Vowels /a/, /e/, and /o/ were taken for the analysis. Each person was asked to pronounce the vowels for at least 3 seconds. Both the persons were asked not to change their day to day activities during the analysis. Total 16 speech samples of each vowel were taken in a single day starting from 7:00 in the morning to 10:00 at night with each sample taken after each hour for each person. So for two persons a total of 96 voice signals of individual vowels were analyzed during two consecutive days. Each vowel signal was pulled out in frames with the help of phonetic software PRAAT [47]. The middle frame was taken for the analysis considering the fact that the speech signal is stationary for a small window of 30–50 msec and has the highest energy at its middle portion [15].For each signal, parameters like pitch, LPC coefficients of the vocal tract, formant frequencies, pole zero plot, and transfer function were estimated. LPC coefficients were estimated using IAIF algorithm. Formants were estimated using the frequency response method of LPC coefficients of the vocal tract. The pitch was estimated using PRAAT. MATLAB was used for pole zero plot for each signal.The following are the observations of this experiment.It was expected that the transfer function for a particular vowel must be unique for a person if calculated at any time of the day. But the experiment showed that the individual shapes of pole zero plots at any time in the day were different from the shapes of pole zero plots calculated at other times. Figure11 shows pole zero plots for first person at four sampling times.Pole zero plots of the vocal tract for vowel /a/ at times 7:00 AM day 1 (upper left side) 10:00 PM day 2 (upper right side), 3:00 PM day 1 (lower left side), and 9:00 PM day 2 (upper right side).
(a)
(b)
(c)
(d)When the mean value of all the coefficients for each individual vowel for each day was taken and pole-zero plot was plotted for those coefficients, then it was observed that the overall shapes of pole-zero plot for each day were approximately the same. Figure12 shows overall pole zero plot for person 2 for vowel /o/ for both days and Figure 13 shows overall pole zero plot for vowel /a/ for person 1 for both days. So it can be said that the average behaviour of the vocal tract throughout the day is the same which corresponds to its resonance or unique behaviour.Mean Pole zero plots for vowel /o/ for person 2 for day 1 (left side) and day 2 (right side).
(a)
(b)Mean Pole zero plots for vowel /e/ for person 1 for day 1 (left side) and day 2 (right side).
(a)
(b)The average pitch value and formant frequencies for person 1 are shown in Table5.Table 5
Average formant frequencies and pitch for person 1 for both days.
F
1 (Hz)
F
2 (Hz)
F
3 (Hz)
F
4 (Hz)
F
5 (Hz)
Pitch (Hz)
/a/
Day 1
405.58
1777.6
2413.9
3463.1
4312.0
109.60
Day 2
398.87
1753.2
2427.6
3355.6
4327.0
106.24
/e/
Day 1
304.56
1982.2
2395.8
3498.2
4101.6
110.12
Day 2
300.60
2062.7
2207.3
3564.1
4207.1
106.18
/o/
Day 1
389.40
811.16
2430.1
2770.5
4260.8
108.58
Day 2
403.07
862.75
2329.2
3185.8
4207.7
104.85The following observations can be concluded with this experiment.(i)
This experiment shows that the human vocal tract system tends to change its shape differently in different times of the day.
(ii)
This variation in the shape of the vocal tract can be due to day to day activities of that person and can be due to intake of food in the body through the throat or due to lack of energy in the body as the day goes on.
(iii)
But in spite of the fluctuations of the vocal tract, the overall shape follows clear uniqueness as we have found out from the pole zero curves.
(iv)
The pole-zero plot obtained after taking the mean values corresponds to the vocal tract transfer function for that individual for some specific vowel.
(v)
This uniqueness in the pole zero plot can act as a unique signature of that person because the shapes of the pole zero plot were different for same vowels in those two persons.
(vi)
So there exists a possibility to find out the biological signature of a person utilizing the vocal system in man.
(vii)
This type of analysis can be helpful in studying the vocal tract system behavior in terms of poles.
### 2.5. Statistical Investigation of Psychological Stress on Human Voice Spectrum
The following work deals with the analysis of speech signal under psychological stress for both positive and negative states of stress. To investigate the influence of stress on speech, acoustic parameters of speech signal were considered. For this type of estimation a suitable database or corpus is required. The most frequently used database among the researchers is the SUSAS (Speech under Simulated and Actual Stress) database of American English which is distributed by Linguistic Data Consortium at the University of Pennsylvania [49]. A German language database called emoDB is also very popular among researchers [50]. A list of existing emotional database is provided in [51, 52]. The database utilized in our analysis was Surrey Audio-Visual Expressed Emotion (SAVEE) database [53, 54]. The database consists of four persons (DC, JE, JK, and KL) of ages 27 to 31 depicting the six basic emotions (anger, disgust, fear, happiness, sadness, and surprise) and the neutral state. The recordings consist of 15 phonetically balanced sentences per emotion (with 15 additional sentences for neutral state) resulting in a corpus of 480 British English utterances. This database is an open source database which can be obtained from the university website on request [55].The database consists of 15 sentences for each speaker and represents all emotions. Out of these 15, 3 sentences are common and rests are emotion specific. These 3 sentences are considered for the evaluation.The three sentences were the following.(i)
She had your dark suit in greasy wash water all year.
(ii)
Do not ask me to carry an oily rag like that.
(iii)
Will you tell me why?There were three sentences for each speaker and each emotion so a total of 84 signals were considered. 11 vowel segments of 40–60 milliseconds duration were extracted from the individual words of these 3 sentences for each speaker and each emotion using phonetic software PRAAT.These segments consist of phonemes /aa/ (resemble vowel /a/ sound, e.g., hate), /la/ (resemble long vowel /a/, e.g., had), /u/ (resemble vowel sound /u/, e.g., book), /o/ (resemble vowel sound /o/, e.g., boat) and /aj/ (resemble vowel /i/ sound, e.g., hide). For each speaker and each emotion, a total of 11 segments were extracted so a total of 308 segments were analyzed.In the analysis the psychological stress is categorized into three major classes. First is neutral state, the second is positive stress, which was taken as a combination of happiness and surprise emotion, and third is negative stress, which was taken as a combination of anger, disgust, fear, and sadness emotions.A number of parameters (about 51 parameters) were judged in the depth psychologies which are grouped under the categories as follows.(i)
Group 1 = pitch and intensity (evaluated for all the sentences).
(ii)
Group 2 =Jitter,Shimmer, andAutocorrelation (evaluated for all the sentences).
(iii)
Group 3 = HNR (harmonic to noise ratio) and NHR (noise to harmonic ratio) (evaluated for all the sentences).
(iv)
Group 4 = energy, time, and frequency parameters (energy entropy (EE), short time energy (STE), zero crossing rate (ZCR), spectral roll off (SR), spectral centroid (SC), spectral flux (SF), (evaluated for all the sentences).
(v)
Group 5 = formant parameters (frequencies (F1, F2,andF3), amplitudes (A1, A2,andA3), and bandwidths (B1, B2,andB3) (evaluated vowels segment wise).
(vi)
Group 6 = glottal pulse timing parameters (NAQ, AQ (milli), CIQ, OQ1, OQ2, Oqa, QOQ, SQ1, and SQ2) (evaluated vowel segment wise).
(vii)
Group 7 = glottal pulse frequency parameters (dH12,PSP,and HRF) (evaluated vowel segment wise).
(viii)
Group 8 = glottal pulse derivative parameters (Ra, Rg, Rk, Rd,andOq) (fvaluated vowel segment wise).
(ix)
Group 9 = first 12 mfcc feature coefficients (evaluated vowel segments wise).Groups 1, 2, and 3 parameters were evaluated using PRAAT software. Groups 4, 5, 9, and 10 were assessed by writing their MATLAB codes. Groups 6, 7, and 8 were evaluated using TKK APARAT software [15].For each signal, all the parameters were evaluated and tabulated emotion wise. After evaluation, they were categorized in terms of positive, negative, and neutral states by combining the appropriate emotion (taking mean values).The outcomes of the analysis were analyzed by two methods. The foremost objective was to appear for the individual pattern in the decreasing order of values of the parameters in case of all the three states and second aim was to work out the most effective parameters among different groups.To count on the most effective parameters under each group, DR (discrimination ratio) criteria was used. Consider(22)
DR
i
=
m
N
i
-
m
S
i
2
d
N
i
2
+
d
S
i
2
,
where m
N is the mean value of that parameter under neutral state and m
S is the mean value of that parameter under stressed state. d
N and d
S are standard deviations for those parameters.DR was calculated for positive, negative, and overall stress (by taking averages of DR of both positive and negative). Higher the DR factor more effective is the parameter.Let us consider the DR calculation for first formantF1 for vowel /aa/ for speaker DC. By taking the mean values of first formantF1 for all frames following data was obtained:
(23)
m
N
F
1
=
656.74
Hz
,
m
P
F
1
=
650.64
Hz
,
m
Neg
(
F
1
)
=
639.65
Hz
,
d
N
(
F
1
)
=
37.979
Hz
,
d
P
F
1
=
18.989
Hz
,
d
Neg
F
1
=
13.81
Hz
.Using the above data DR for formantF1 for positive and negative stressed states can be calculated using (22):
(24)
DR
(
F
1
)
(
Positive
)
=
656.74
-
650.64
2
37.97
9
2
+
18.98
9
2
=
0.0206
.
Similarly,
(25)
DR
F
1
Negative
=
656.74
-
639.65
2
37.97
9
2
+
13.8
1
2
=
0.1787
.Overall DR can be calculated by taking the mean values of DR (positive) and DR (negative).Tables6 and 7 show the DR evaluation table for some parameters of vowels /aa/ for speaker JE for positive stress and for vowel /la/ for speaker JK for negative stress, respectively.Table 6
DR evaluation table for vowel /aa/ for speaker JE.
Parameter
Mean (N)
Deviation (N)
Mean (P)
Deviation (P)
DR (Pos)
F
1
615.24
41.43
610.35
34.52
0.01
F
2
1154.79
58.70
1182.86
44.89
0.14
F
3
2700.20
75.96
2967.53
84.59
5.53
A
1
32.26
1.09
22.43
3.05
9.24
A
2
13.81
1.80
16.67
3.15
0.62
A
3
10.63
0.70
7.65
0.65
9.65
B
1
71.70
8.72
173.04
136.03
0.55
B
2
290.47
10.67
183.69
44.65
5.41
B
3
105.75
32.67
143.75
30.42
0.72
NAQ
0.09
0.05
0.13
0.03
0.53
AQ (milli)
0.87
0.14
0.56
0.07
4.20
CIQ
0.16
0.10
0.27
0.09
0.73
OQ1
0.44
0.29
0.59
0.11
0.25
OQ2
0.39
0.29
0.49
0.13
0.11Table 7
DR evaluation table for vowel /la/ for speaker JK.
Parameter
Mean (N)
Deviation (N)
Mean (Neg)
Deviation (Neg)
DR (Neg)
F
1
755.21
25.06
802.82
54.16
0.64
F
2
1453.45
28.61
1515.30
76.87
0.57
F
3
2651.37
119.70
2606.61
173.18
0.05
A
1
20.15
2.18
19.09
6.11
0.03
A
2
14.79
4.04
15.59
4.27
0.02
A
3
15.74
2.52
10.62
2.76
1.88
B
1
136.33
30.70
208.07
125.56
0.31
B
2
209.80
107.89
185.96
84.99
0.03
B
3
141.36
39.45
216.01
85.44
0.63
NAQ
0.08
0.01
0.08
0.04
0.01
AQ (milli)
0.64
0.03
0.52
0.20
0.33
CIQ
0.12
0.02
0.14
0.08
0.06
OQ1
0.55
0.08
0.48
0.11
0.30
OQ2
0.28
0.06
0.35
0.10
0.31The results from the pattern in the order of stress state of the parameters are as follows.(i)
8 parameters out of 13 parameters (61.5%), which were evaluated for all the sentences, show a unique rule for all the speakers so they can be helpful in stress detection. Parameters such as pitch, intensity, shimmer, jitter, EE, ZC, SR, and SC show these results. For pitch and intensity, distribution functions were plotted. Figure14 shows the distribution function of pitch values in case of speaker DC. In 6 out of those 8 parameters, positive stressed signal shows the highest value, followed by negative stress and neutral case.
(ii)
27 out of 38 parameters (71%), which were evaluated for vowel segments, show unique patterns of the values for all the stress states in 3 out of 4 speakers. These 27 parameters were showing results for 37% of the total vowel signals that were analyzed. Out of these parameters, parameterR
a was showing positive results for all the analyzed vowels with positive stressed data having the highest value, followed by negative and neutral data.
(iii)
In nut shell, 35 parameters out of 51 parameters are affected due to stress and are showing a singular practice of values in the stressed state for 32% of the examined data.Figure 14
Distribution function for Pitch values for speaker DC.Results according to the DR criteria were evaluated group wise and are shown in Tables8 and 9.Table 8
Highest DR values for group numbers 1 to 4.
Group number
Positive effective
Negative effective
Overall
1
Pitch
Pitch
Pitch
2
—
Autocorrelation
—
3
HNR
HNR
—
4
—
—
SCTable 9
Highest DR values for group numbers 5 To 9. (P: positive; N: negative; O: overall).
(a)
Group name
/aa/
/la/
P
N
O
P
N
O
Formant freq.
F
3
F
3
F
3
—
—
—
Formant amp.
—
—
—
A
3
—
A
3
Formant BWs
—
—
—
B
3
B
3
B
3
Group 6
AQ
—
AQ
—
—
—
Group 7
—
—
—
—
—
—
Group 8
Ra
—
Ra
Ra
—
Ra
Group 9
—
—
—
—
—
—
(b)
Group name
/u/
/o/
P
N
O
P
N
O
Formant freq.
—
—
F
1
F
2
—
—
Formant amp.
A
1
—
A
1
—
—
—
Formant BWs
—
—
—
—
—
—
Group 6
—
—
—
—
—
—
Group 7
—
—
—
dH
dH
dH
Group 8
Ra
Ra
Ra
Ra
Ra
Ra
Group 9
—
—
—
—
—
—
#### 2.5.1. Final Results
(i)
For phoneme /aa/,F3,AQ, andRa are the most effective parameters for positive stress as well as overall stress detection.F3 is also the most effective parameter for negative stress detection.
(ii)
For phoneme /la/,A3,B3, andRa are the most effective parameters for positive as well as overall stress detection.B3 is also the most effective parameter for negative stress detection in this case.
(iii)
For phoneme /u/,A1 andRa are the most effective parameters for positive stress detection;Ra is also the most effective parameter for negative stress detection.F1,A1, andRa are the effective parameters for overall stress detection.
(iv)
For phoneme /o/,dH12 andRa are the most effective parameters for positive, negative and overall stress detection.F2 is also the effective parameters for positive stress detection.
(v)
For vowel independent parameters, pitch and HNR are the most effective parameters for positive stress detection; pitch, autocorrelation, and HNR are helpful in negative stress detection. Pitch and SC are helpful in overall stress detection.
(vi)
On the basis of pattern of values of parameters, phoneme /aa/ affects 7 parameters, phoneme /la/ affects 11 parameters, phoneme /u/ affects 5 parameters and phoneme /o/ affects 15 parameters.
(vii)
So we can say vowel /o/ should be used for stress detection as it is affecting the most number of parameters.
## 2.1. Estimation of Glottal Flow
The goal of this experiment was to estimate the glottal flow or glottal pulses from the voice signal of vowels using IAIF algorithm described in the above section by using MATLAB as well as SIMULINK [16–18]. The foremost prerequisite of this algorithm is to obtain the predictor coefficients from the speech signal. For this, lpc function in MATLAB or lpc model of SIMULINK can be used [13, 14]. The speech signal recordings were available in wav format. The speech signals were converted into data samples by taking the sampling frequency of 10 KHz using MATLAB. The workspace block was used to take those samples in SIMULINK. Digital filter design blocks were used for FIR high pass and inverse filtering. The Autocorrelation LPC blocks were employed to get the predictor coefficients. The digital Integrator block was used for integration. The SIMULINK model of the IAIF algorithm is shown in Figure 7.Figure 7
SIMULINK model of IAIF algorithm.The input speech waveform and output glottal waveform for vowel /a/ are shown in Figure8.Input speech waveform and Output glottal waveform of IAIF algorithm for vowel /a/.
(a)
(b)Using the MATLAB code of IAIF algorithm, glottal pulses of five vowels /a/, /e/, /i/, /o/, /u/ obtained are shown in Figure9.Glottal pulses for five vowels /a/, /e/, /i/, /o/, and /u/, respectively.
(a)
(b)
(c)
(d)
(e)
## 2.2. Comparison of Computed Formant Frequencies
Using the inverse filtering technique the formant parameters can be computed by using two methods. One of them is to find out the peaks of the frequency response of the vocal tract filter and other is to find out the roots of the polynomial equation formed using LPC coefficients of vocal tract filter as explained in [9]. This experimentation was performed to compare the computed formant frequencies by those two methods with the values obtained using phonetic software PRAAT [47].A total of 15 speech signals were analyzed and four formant frequencies were computed for each case. The speech signals used consist of five vowel segments each for male, female, and child and are available in [48]. In 12 of them (80% of the total), formant values obtained using the two methods above were rather near to the values computed using PRAAT software. In case of LPC polynomial root method, some false formants were also noted. So this idea is not so precise and should be used rarely. By applying these methods, we can also compute the 3 dB bandwidth values and amplitude values for each formant [9].Tables1 and 2 are shown for male vowel /i/ and child vowel /a/.Table 1
Comparison of computed formant frequencies for male vowel /i/.
Formant number
By roots
By response
By PRAAT
1
241.3
244.1
233.5
2
2263.6
2270.5
2246.1
3
3194.5
3203.1
3148.6
4
3832.6
3837.9
3828.7Table 2
A comparison of computed formant frequencies for child vowel /a/.
Formant number
By roots
By response
By PRAAT
1
532.5
546.9
549.5
2
1194.1
1196.3
1259.4
3
1807.9
1801.8
1872.6
4
3903.8
3911.1
3893.7
## 2.3. LPC Coefficients versus Vocal Tract Cavities
As we have discussed in the first section that inverse filtering and LPC coefficients approach can be used to model the human vocal tract and is helpful in determining the formant frequencies, so there can be some relationship between the LPC coefficients of the vocal tract and vocal tract cavities. This relationship can be helpful in determining which LPC coefficient of the vocal tract corresponds to which cavity of the vocal tract. It was talked about in the beginning section that each cavity of the vocal tract corresponds to a formant frequency and in the last experiment, we have computed formant frequencies using LPC coefficients of the vocal tract calculated during the final stage of IAIF algorithm. So a relationship can be derived between LPC coefficients and formant frequencies. To derive a relationship 5 speech signals (different persons) were taken. In each signal, each LPC coefficient of the vocal tract was changed (increased and decreased) from 5 to 50%. Corresponding to each change all the formant parameters (frequencies, amplitudes, and bandwidths) were estimated. So for a single signal a total of 24 sets of parameters (both increased and decreased) were tabulated. So for five signals a total of 120(
24
*
5
) sets of parameters were tabulated. A single set of the table for the first signal for a change up to 20% is shown in Table 3. This table determines the change in the formant parameters when the 1st LPC coefficient of the vocal tract is increased. Here bold values determine that the corresponding value is more than its original value when no parameter was changed. The original values of the parameters are depicted in Table 4.Table 3
Change in the formant parameters when a single coefficient value is changed from 5 to 20%.
Parameters/change
5%
10%
15%
20%
F
1 (Hz)
551.0
542.0
532.0
512.7
A
1 (dB)
31.2
29.7
20.7
16.4
B
1 (Hz)
37.4
47.6
138.0
225.0
F
2 (Hz)
913.0
883.8
849
825.2
A
2 (dB)
22.1
19.4
16.9
14.6
B
2 (Hz)
98.7
144.3
196.0
245.2
F
3 (Hz)
1967.0
1958.0
1953.0
1948.2
A
3 (dB)
3.3
2.8
2.4
1.9
B
3 (Hz)
312.0
323.9
335.0
348.1
F
4 (Hz)
3291.0
3281.2
3276.0
3271.5
A
4 (dB)
8.6
7.4
6.4
5.4
B
4 (Hz)
228.0
253.4
277.0
310.4
F
5 (Hz)
3842.0
3847.7
3857.0
3867.2
A
5 (dB)
11.9
11.0
10.2
9.4
B
5 (Hz)
84.6
89.0
93.5
98.2Table 4
Original values.
F
1 (Hz)
556.6
A
1 (dB)
21.1
B
1 (Hz)
109.7
F
2 (Hz)
947.3
A
2 (dB)
24.7
B
2 (Hz)
66.3
F
3 (Hz)
1977.5
A
3 (dB)
3.7
B
3 (Hz)
300.2
F
4 (Hz)
3300.8
A
4 (dB)
9.9
B
4 (Hz)
80.4
F
5 (Hz)
3833.0
A
5 (dB)
12.8
B
5 (Hz)
201.9After analyzing all the data, the following conclusions were derived.(i)
All the formant parameters were altered due to change in a single coefficient. This signifies that all the portions of the vocal tract are associated to each coefficient.
(ii)
Obtained results indicate that these variations follow an individual trend rather than any global trend. So this type of analysis is purely speaker dependent.
(iii)
Yet a similar trend can be imaged in the change of the value of formant frequencies of all the signals.
(iv)
FormantF1 changes (either increase or decrease) the most, if any individual coefficient is changed.
(v)
After that formantF2 andF4 come in 2nd and 3rd place in the list.
(vi)
In 4 out of 5 signals,F3 comes afterF4, and in 1 signalF5 comes afterF4.
(vii)
No such character of pattern was obtained for amplitudes and bandwidths.
(viii)
Nevertheless, in some cases an opposite tendency was seen in bandwidth and amplitude, meaning that if bandwidth was increasing, the amplitude was also decreasing for the whole change.Figure 10 shows diagrammatically the change in formant values along with bandwidths and amplitudes for a sample.Figure 10
Variations in the formant parameters due to change in LPC coefficients for a signal.
## 2.4. Estimation of Vocal Tract Transfer Function for an Individual
According to source-filter theory of speech production, to model the speech production mechanism digitally, we need to consider separate elements of speech production. The speech production system can be modelled with three separate elements: the source, the vocal tract filter, and the radiation effects [17]. The steady state system function of the digital filter is given by the expression:
(21)
H
z
=
S
z
U
z
=
G
1
-
∑
k
=
1
p
a
k
z
-
k
.The primary purpose of this experimentation was to somehow count for a method to forecast or predict the transfer function of vocal tract for an individual. The methodology used was first to calculate the vocal tract predictor coefficients for a signal from the final stage of IAIF algorithm and the gain factorG using lpc function in MATLAB, then by the use of (21) pole zero plot was plotted. As we have discussed before that the LPC order for the vocal tract filter taken is 12 so there will be 12 poles in the transfer function of the vocal tract (Section 1.3).The experimentation was done on two male persons of ages 24 and 26, respectively, by recording their voice samples using Sony IC Recorder (ICD-UX513F) device. Vowels /a/, /e/, and /o/ were taken for the analysis. Each person was asked to pronounce the vowels for at least 3 seconds. Both the persons were asked not to change their day to day activities during the analysis. Total 16 speech samples of each vowel were taken in a single day starting from 7:00 in the morning to 10:00 at night with each sample taken after each hour for each person. So for two persons a total of 96 voice signals of individual vowels were analyzed during two consecutive days. Each vowel signal was pulled out in frames with the help of phonetic software PRAAT [47]. The middle frame was taken for the analysis considering the fact that the speech signal is stationary for a small window of 30–50 msec and has the highest energy at its middle portion [15].For each signal, parameters like pitch, LPC coefficients of the vocal tract, formant frequencies, pole zero plot, and transfer function were estimated. LPC coefficients were estimated using IAIF algorithm. Formants were estimated using the frequency response method of LPC coefficients of the vocal tract. The pitch was estimated using PRAAT. MATLAB was used for pole zero plot for each signal.The following are the observations of this experiment.It was expected that the transfer function for a particular vowel must be unique for a person if calculated at any time of the day. But the experiment showed that the individual shapes of pole zero plots at any time in the day were different from the shapes of pole zero plots calculated at other times. Figure11 shows pole zero plots for first person at four sampling times.Pole zero plots of the vocal tract for vowel /a/ at times 7:00 AM day 1 (upper left side) 10:00 PM day 2 (upper right side), 3:00 PM day 1 (lower left side), and 9:00 PM day 2 (upper right side).
(a)
(b)
(c)
(d)When the mean value of all the coefficients for each individual vowel for each day was taken and pole-zero plot was plotted for those coefficients, then it was observed that the overall shapes of pole-zero plot for each day were approximately the same. Figure12 shows overall pole zero plot for person 2 for vowel /o/ for both days and Figure 13 shows overall pole zero plot for vowel /a/ for person 1 for both days. So it can be said that the average behaviour of the vocal tract throughout the day is the same which corresponds to its resonance or unique behaviour.Mean Pole zero plots for vowel /o/ for person 2 for day 1 (left side) and day 2 (right side).
(a)
(b)Mean Pole zero plots for vowel /e/ for person 1 for day 1 (left side) and day 2 (right side).
(a)
(b)The average pitch value and formant frequencies for person 1 are shown in Table5.Table 5
Average formant frequencies and pitch for person 1 for both days.
F
1 (Hz)
F
2 (Hz)
F
3 (Hz)
F
4 (Hz)
F
5 (Hz)
Pitch (Hz)
/a/
Day 1
405.58
1777.6
2413.9
3463.1
4312.0
109.60
Day 2
398.87
1753.2
2427.6
3355.6
4327.0
106.24
/e/
Day 1
304.56
1982.2
2395.8
3498.2
4101.6
110.12
Day 2
300.60
2062.7
2207.3
3564.1
4207.1
106.18
/o/
Day 1
389.40
811.16
2430.1
2770.5
4260.8
108.58
Day 2
403.07
862.75
2329.2
3185.8
4207.7
104.85The following observations can be concluded with this experiment.(i)
This experiment shows that the human vocal tract system tends to change its shape differently in different times of the day.
(ii)
This variation in the shape of the vocal tract can be due to day to day activities of that person and can be due to intake of food in the body through the throat or due to lack of energy in the body as the day goes on.
(iii)
But in spite of the fluctuations of the vocal tract, the overall shape follows clear uniqueness as we have found out from the pole zero curves.
(iv)
The pole-zero plot obtained after taking the mean values corresponds to the vocal tract transfer function for that individual for some specific vowel.
(v)
This uniqueness in the pole zero plot can act as a unique signature of that person because the shapes of the pole zero plot were different for same vowels in those two persons.
(vi)
So there exists a possibility to find out the biological signature of a person utilizing the vocal system in man.
(vii)
This type of analysis can be helpful in studying the vocal tract system behavior in terms of poles.
## 2.5. Statistical Investigation of Psychological Stress on Human Voice Spectrum
The following work deals with the analysis of speech signal under psychological stress for both positive and negative states of stress. To investigate the influence of stress on speech, acoustic parameters of speech signal were considered. For this type of estimation a suitable database or corpus is required. The most frequently used database among the researchers is the SUSAS (Speech under Simulated and Actual Stress) database of American English which is distributed by Linguistic Data Consortium at the University of Pennsylvania [49]. A German language database called emoDB is also very popular among researchers [50]. A list of existing emotional database is provided in [51, 52]. The database utilized in our analysis was Surrey Audio-Visual Expressed Emotion (SAVEE) database [53, 54]. The database consists of four persons (DC, JE, JK, and KL) of ages 27 to 31 depicting the six basic emotions (anger, disgust, fear, happiness, sadness, and surprise) and the neutral state. The recordings consist of 15 phonetically balanced sentences per emotion (with 15 additional sentences for neutral state) resulting in a corpus of 480 British English utterances. This database is an open source database which can be obtained from the university website on request [55].The database consists of 15 sentences for each speaker and represents all emotions. Out of these 15, 3 sentences are common and rests are emotion specific. These 3 sentences are considered for the evaluation.The three sentences were the following.(i)
She had your dark suit in greasy wash water all year.
(ii)
Do not ask me to carry an oily rag like that.
(iii)
Will you tell me why?There were three sentences for each speaker and each emotion so a total of 84 signals were considered. 11 vowel segments of 40–60 milliseconds duration were extracted from the individual words of these 3 sentences for each speaker and each emotion using phonetic software PRAAT.These segments consist of phonemes /aa/ (resemble vowel /a/ sound, e.g., hate), /la/ (resemble long vowel /a/, e.g., had), /u/ (resemble vowel sound /u/, e.g., book), /o/ (resemble vowel sound /o/, e.g., boat) and /aj/ (resemble vowel /i/ sound, e.g., hide). For each speaker and each emotion, a total of 11 segments were extracted so a total of 308 segments were analyzed.In the analysis the psychological stress is categorized into three major classes. First is neutral state, the second is positive stress, which was taken as a combination of happiness and surprise emotion, and third is negative stress, which was taken as a combination of anger, disgust, fear, and sadness emotions.A number of parameters (about 51 parameters) were judged in the depth psychologies which are grouped under the categories as follows.(i)
Group 1 = pitch and intensity (evaluated for all the sentences).
(ii)
Group 2 =Jitter,Shimmer, andAutocorrelation (evaluated for all the sentences).
(iii)
Group 3 = HNR (harmonic to noise ratio) and NHR (noise to harmonic ratio) (evaluated for all the sentences).
(iv)
Group 4 = energy, time, and frequency parameters (energy entropy (EE), short time energy (STE), zero crossing rate (ZCR), spectral roll off (SR), spectral centroid (SC), spectral flux (SF), (evaluated for all the sentences).
(v)
Group 5 = formant parameters (frequencies (F1, F2,andF3), amplitudes (A1, A2,andA3), and bandwidths (B1, B2,andB3) (evaluated vowels segment wise).
(vi)
Group 6 = glottal pulse timing parameters (NAQ, AQ (milli), CIQ, OQ1, OQ2, Oqa, QOQ, SQ1, and SQ2) (evaluated vowel segment wise).
(vii)
Group 7 = glottal pulse frequency parameters (dH12,PSP,and HRF) (evaluated vowel segment wise).
(viii)
Group 8 = glottal pulse derivative parameters (Ra, Rg, Rk, Rd,andOq) (fvaluated vowel segment wise).
(ix)
Group 9 = first 12 mfcc feature coefficients (evaluated vowel segments wise).Groups 1, 2, and 3 parameters were evaluated using PRAAT software. Groups 4, 5, 9, and 10 were assessed by writing their MATLAB codes. Groups 6, 7, and 8 were evaluated using TKK APARAT software [15].For each signal, all the parameters were evaluated and tabulated emotion wise. After evaluation, they were categorized in terms of positive, negative, and neutral states by combining the appropriate emotion (taking mean values).The outcomes of the analysis were analyzed by two methods. The foremost objective was to appear for the individual pattern in the decreasing order of values of the parameters in case of all the three states and second aim was to work out the most effective parameters among different groups.To count on the most effective parameters under each group, DR (discrimination ratio) criteria was used. Consider(22)
DR
i
=
m
N
i
-
m
S
i
2
d
N
i
2
+
d
S
i
2
,
where m
N is the mean value of that parameter under neutral state and m
S is the mean value of that parameter under stressed state. d
N and d
S are standard deviations for those parameters.DR was calculated for positive, negative, and overall stress (by taking averages of DR of both positive and negative). Higher the DR factor more effective is the parameter.Let us consider the DR calculation for first formantF1 for vowel /aa/ for speaker DC. By taking the mean values of first formantF1 for all frames following data was obtained:
(23)
m
N
F
1
=
656.74
Hz
,
m
P
F
1
=
650.64
Hz
,
m
Neg
(
F
1
)
=
639.65
Hz
,
d
N
(
F
1
)
=
37.979
Hz
,
d
P
F
1
=
18.989
Hz
,
d
Neg
F
1
=
13.81
Hz
.Using the above data DR for formantF1 for positive and negative stressed states can be calculated using (22):
(24)
DR
(
F
1
)
(
Positive
)
=
656.74
-
650.64
2
37.97
9
2
+
18.98
9
2
=
0.0206
.
Similarly,
(25)
DR
F
1
Negative
=
656.74
-
639.65
2
37.97
9
2
+
13.8
1
2
=
0.1787
.Overall DR can be calculated by taking the mean values of DR (positive) and DR (negative).Tables6 and 7 show the DR evaluation table for some parameters of vowels /aa/ for speaker JE for positive stress and for vowel /la/ for speaker JK for negative stress, respectively.Table 6
DR evaluation table for vowel /aa/ for speaker JE.
Parameter
Mean (N)
Deviation (N)
Mean (P)
Deviation (P)
DR (Pos)
F
1
615.24
41.43
610.35
34.52
0.01
F
2
1154.79
58.70
1182.86
44.89
0.14
F
3
2700.20
75.96
2967.53
84.59
5.53
A
1
32.26
1.09
22.43
3.05
9.24
A
2
13.81
1.80
16.67
3.15
0.62
A
3
10.63
0.70
7.65
0.65
9.65
B
1
71.70
8.72
173.04
136.03
0.55
B
2
290.47
10.67
183.69
44.65
5.41
B
3
105.75
32.67
143.75
30.42
0.72
NAQ
0.09
0.05
0.13
0.03
0.53
AQ (milli)
0.87
0.14
0.56
0.07
4.20
CIQ
0.16
0.10
0.27
0.09
0.73
OQ1
0.44
0.29
0.59
0.11
0.25
OQ2
0.39
0.29
0.49
0.13
0.11Table 7
DR evaluation table for vowel /la/ for speaker JK.
Parameter
Mean (N)
Deviation (N)
Mean (Neg)
Deviation (Neg)
DR (Neg)
F
1
755.21
25.06
802.82
54.16
0.64
F
2
1453.45
28.61
1515.30
76.87
0.57
F
3
2651.37
119.70
2606.61
173.18
0.05
A
1
20.15
2.18
19.09
6.11
0.03
A
2
14.79
4.04
15.59
4.27
0.02
A
3
15.74
2.52
10.62
2.76
1.88
B
1
136.33
30.70
208.07
125.56
0.31
B
2
209.80
107.89
185.96
84.99
0.03
B
3
141.36
39.45
216.01
85.44
0.63
NAQ
0.08
0.01
0.08
0.04
0.01
AQ (milli)
0.64
0.03
0.52
0.20
0.33
CIQ
0.12
0.02
0.14
0.08
0.06
OQ1
0.55
0.08
0.48
0.11
0.30
OQ2
0.28
0.06
0.35
0.10
0.31The results from the pattern in the order of stress state of the parameters are as follows.(i)
8 parameters out of 13 parameters (61.5%), which were evaluated for all the sentences, show a unique rule for all the speakers so they can be helpful in stress detection. Parameters such as pitch, intensity, shimmer, jitter, EE, ZC, SR, and SC show these results. For pitch and intensity, distribution functions were plotted. Figure14 shows the distribution function of pitch values in case of speaker DC. In 6 out of those 8 parameters, positive stressed signal shows the highest value, followed by negative stress and neutral case.
(ii)
27 out of 38 parameters (71%), which were evaluated for vowel segments, show unique patterns of the values for all the stress states in 3 out of 4 speakers. These 27 parameters were showing results for 37% of the total vowel signals that were analyzed. Out of these parameters, parameterR
a was showing positive results for all the analyzed vowels with positive stressed data having the highest value, followed by negative and neutral data.
(iii)
In nut shell, 35 parameters out of 51 parameters are affected due to stress and are showing a singular practice of values in the stressed state for 32% of the examined data.Figure 14
Distribution function for Pitch values for speaker DC.Results according to the DR criteria were evaluated group wise and are shown in Tables8 and 9.Table 8
Highest DR values for group numbers 1 to 4.
Group number
Positive effective
Negative effective
Overall
1
Pitch
Pitch
Pitch
2
—
Autocorrelation
—
3
HNR
HNR
—
4
—
—
SCTable 9
Highest DR values for group numbers 5 To 9. (P: positive; N: negative; O: overall).
(a)
Group name
/aa/
/la/
P
N
O
P
N
O
Formant freq.
F
3
F
3
F
3
—
—
—
Formant amp.
—
—
—
A
3
—
A
3
Formant BWs
—
—
—
B
3
B
3
B
3
Group 6
AQ
—
AQ
—
—
—
Group 7
—
—
—
—
—
—
Group 8
Ra
—
Ra
Ra
—
Ra
Group 9
—
—
—
—
—
—
(b)
Group name
/u/
/o/
P
N
O
P
N
O
Formant freq.
—
—
F
1
F
2
—
—
Formant amp.
A
1
—
A
1
—
—
—
Formant BWs
—
—
—
—
—
—
Group 6
—
—
—
—
—
—
Group 7
—
—
—
dH
dH
dH
Group 8
Ra
Ra
Ra
Ra
Ra
Ra
Group 9
—
—
—
—
—
—
### 2.5.1. Final Results
(i)
For phoneme /aa/,F3,AQ, andRa are the most effective parameters for positive stress as well as overall stress detection.F3 is also the most effective parameter for negative stress detection.
(ii)
For phoneme /la/,A3,B3, andRa are the most effective parameters for positive as well as overall stress detection.B3 is also the most effective parameter for negative stress detection in this case.
(iii)
For phoneme /u/,A1 andRa are the most effective parameters for positive stress detection;Ra is also the most effective parameter for negative stress detection.F1,A1, andRa are the effective parameters for overall stress detection.
(iv)
For phoneme /o/,dH12 andRa are the most effective parameters for positive, negative and overall stress detection.F2 is also the effective parameters for positive stress detection.
(v)
For vowel independent parameters, pitch and HNR are the most effective parameters for positive stress detection; pitch, autocorrelation, and HNR are helpful in negative stress detection. Pitch and SC are helpful in overall stress detection.
(vi)
On the basis of pattern of values of parameters, phoneme /aa/ affects 7 parameters, phoneme /la/ affects 11 parameters, phoneme /u/ affects 5 parameters and phoneme /o/ affects 15 parameters.
(vii)
So we can say vowel /o/ should be used for stress detection as it is affecting the most number of parameters.
## 2.5.1. Final Results
(i)
For phoneme /aa/,F3,AQ, andRa are the most effective parameters for positive stress as well as overall stress detection.F3 is also the most effective parameter for negative stress detection.
(ii)
For phoneme /la/,A3,B3, andRa are the most effective parameters for positive as well as overall stress detection.B3 is also the most effective parameter for negative stress detection in this case.
(iii)
For phoneme /u/,A1 andRa are the most effective parameters for positive stress detection;Ra is also the most effective parameter for negative stress detection.F1,A1, andRa are the effective parameters for overall stress detection.
(iv)
For phoneme /o/,dH12 andRa are the most effective parameters for positive, negative and overall stress detection.F2 is also the effective parameters for positive stress detection.
(v)
For vowel independent parameters, pitch and HNR are the most effective parameters for positive stress detection; pitch, autocorrelation, and HNR are helpful in negative stress detection. Pitch and SC are helpful in overall stress detection.
(vi)
On the basis of pattern of values of parameters, phoneme /aa/ affects 7 parameters, phoneme /la/ affects 11 parameters, phoneme /u/ affects 5 parameters and phoneme /o/ affects 15 parameters.
(vii)
So we can say vowel /o/ should be used for stress detection as it is affecting the most number of parameters.
## 3. Conclusions
In this paper, we have presented the speech signal analysis using inverse filtering and LPC coefficient approach to estimate some of the important speech parameters like glottal pulse estimation, glottal pulse timing and amplitude parameters, glottal pulse derivative parameters, voice parameters based on time, frequency and energy, MFC coefficients for feature extraction, pitch, intensity, and pole zero plot. The algorithms and methods used for the estimation were studied and discussed in the paper. The formant parameters were compared with the same parameters obtained using phonetic software PRAAT. An analysis was also performed to find out the relationship between the coefficients of the vocal tract and cavities of the vocal tract. Obtained results show that all the coefficients are related to the human vocal tract and no direct correspondence could be held. However, the amount of change in the formant frequencies follow a trend ofF
1 > F
2 > F
4 > F
3 > F
5 in most of the cases. Besides this a pole zero evaluation of vocal tract system was discussed to determine the vocal tract transfer function for individuals which shows that the human vocal tract system tends to change its shape in different times of the day for same vowel pronunciations. But the average pole zero plot evaluated follow a unique pattern. This indicates that the ordinary behaviour of human vocal tract system exhibits unique frequency response or resonance. This work can be helpful in simplification of voice related problems in terms of poles and zeros which can be extended further for studying unique voice features in every individual. At last, a speech signal analysis for stress detection was done using SAVEE database. A total of 51 parameters were evaluated and compared for positive stress, negative stress, and neutral state. The features summarized in Tables 8 and 9 have been proven to be the most effective parameters for stress detection among all speakers.In future, we plan to create our own database, adding other types of stress emotions. We aim to compare the speech features for same emotion for different languages to check whether the emotional content in speech is language dependent or not. Our goal is to detect similar effects with speech with other biological signals like ECG and EEG to identify the correlation among them, which can be helpful in early detection or prevention of many diseases.
---
*Source: 290147-2014-11-18.xml* | 290147-2014-11-18_290147-2014-11-18.md | 100,342 | Estimation and Statistical Analysis of Human Voice Parameters to Investigate the Influence of Psychological Stress and to Determine the Vocal Tract Transfer Function of an Individual | Puneet Kumar Mongia; R. K. Sharma | Journal of Computer Networks and Communications
(2014) | Engineering & Technology | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2014/290147 | 290147-2014-11-18.xml | ---
## Abstract
In this study the principal focus is to examine the influence of psychological stress (both positive and negative stress) on the human articulation and to determine the vocal tract transfer function of an individual using inverse filtering technique. Both of these analyses are carried out by estimating various voice parameters. The outcomes of the analysis of psychological stress indicate that all the voice parameters are affected due to the influence of stress on humans. About 35 out of 51 parameters follow a unique course of variation from normal to positive and negative stress in 32% of the total analyzed signals. The upshot of the analysis is to determine the vocal tract transfer function for each vowel for an individual. The analysis indicates that it can be computed by estimating the mean of the pole zero plots of that individual’s vocal tract estimated for the whole day. Besides this, an analysis is presented to find the relationship between the LPC coefficients of the vocal tract and the vocal tract cavities. The results of the analysis indicate that all the LPC coefficients of the vocal tract are affected due to change in the position of any cavity.
---
## Body
## 1. Introduction
### 1.1. Voice Production Process
The process of voice production involves a sequence of complex biological activities. It originates from the production of airflow in the lungs, which is modulated by the vocal folds (for voice sounds). Spectral shaping of the modulated airflow is done by the vocal tract cavities which transfer the airflow to the lips to radiate the sound in the outside world. This process of voice production is very well discussed in [1–3]. A simplified view of speech production is shown in Figure 1. Here the speech organs are divided into three main parts: lungs, larynx, and vocal tract. Lungs are acting as a power supply which supplies air pressure signals to the larynx stage. The larynx modulates the airflow as is given by the lungs. It consists of two vocal folds or vocal cords. These folds are made up of masses of flesh, ligament, and muscles [2]. The basic functionality of these folds is to stretch between the front and back parts of the larynx. The glottis is a slit like space between the two folds. The vocal folds are open during breathing. But they can either be in open or vibrating condition depending upon the speaking state. In case of voice sources like vowels, the vocal folds are in a vibrating state. This means vocal folds are opening and closing rapidly. For other sources, the vocal folds are not vibrating rapidly [1]. After the larynx stage the signal passes through the vocal tract which consists of three cavities; pharynx cavity, oral cavity, and nasal cavity. These organs are helpful in shaping the modulated airflow spectrally and also in adjusting the quality of speech [2]. The vibration of the vocal folds in case of voice sources can be estimated in the form of a pulse called glottal pulse. A glottal pulse is shown in Figure 2. As we can see, initially the folds are in closed position (air flow is zero above vocal folds); then they are opening slowly (air flow is increasing); then they are fully open (air flow is maximized), and after that they are closing at a faster rate as shown in the figure. From this we can determine the time duration of one glottal cycle, which is known as pitch period and the reciprocal of pitch period is known as fundamental frequency [1]. The value of the fundamental frequency is influenced by many factors like vocal fold muscle tension, vocal fold mass, and the air pressure behind the vocal folds. The average pitch range is roughly 80 Hz to 400 Hz in males and 120 Hz to 800 Hz in females [2].Figure 1
Simplified view of speech production [1].Figure 2
Periodic glottal airflow waveform [1].As the glottal pulse or the excitation signal moves upward on its way through the mouth and nose, it encounters certain obstructions. First the wall of the throat (in the pharyngeal cavity) creates impedance in its path. This impedance causes certain resonance frequencies in the signal. The same effect is caused by the walls of the mouth surrounding the oral cavity and by the walls of the nose surrounding the nasal cavity. The sizes and conformations of these cavities are purely speaker dependent. The resonances of these three cavities (pharyngeal, oral, and nasal) are frequently called formants: the first formant, the second formant, and the third formant, respectively. These frequencies depend upon the shape and dimension of the vocal tract [4]. Because of the motion of organs like tongue, and teeth, higher formant values are likewise possible. As these formant values are immediately linked to the vocal tract cavities so these parameters are also very important and must be measured. After travelling through the vocal tract, the signal is radiated outwards in the form of speech through the lips or nose (in case of nasal voice signals).The parameters of these organs play a significant role in determining the speaker’s characteristics. Getting a true appraisal of these parameters helps us to see the operation of the human speech production mechanism in a more skillful way [5]. These parameters can be beneficial for many speech processing applications such as speaker recognition and speech synthesis [6]. Similarly in biomedical applications or clinical research for the analysis of psychological stress or alcohol intoxication, these parameters play an important role [7, 8]. There is some change in the values of these parameters for normal to diseased or stressed state [9]. So there is a need to effectively estimate these parameters from the voice signal.
### 1.2. Introduction to Stress
For a number of years the researchers in the field of Speech science and Laryngological studies, are constantly working on the acoustic characteristics of normal and pathological voice. Various methods have been modernized in this subject area for providing the quantitative data [10]. The major reason of growing research in this area is because of the importance of voice signal in determining the effect of clinical disorders like psychological stress. Stress or emphasis is mostly specified as a psychological state that is a reaction to a perceived threat or task demand and is normally accompanied by some specific emotions (e.g., fear, anger, or disgust) [11]. The long term occurrence of stress has serious health consequences [12]. The obvious question that comes to mind is how do we measure stress? The most accurate estimations of a person’s stress level can be found by measuring various psychological parameters, such as ECG, EEG or other biological signals, or some biochemical methods [9]. But all these methods require costly and large setup. However, it is very easy to analyze the voice or speech signal; hence this type of analysis is easy and inexpensive. In daily life we often use the term stress to identify negative emotions. However, stress can be classified in two parts, eustress which is a term for positive stress or emotion (like happiness) and distress, which refers to the negative stress or emotions (like anger, fear, or disgust). The positive stress motivates, focuses energy, feels exciting, and improves performance. In contrast, negative stress causes anxiety, feels unpleasant, and decreases performance [9].
### 1.3. Glottal Pulse Extraction
As discussed in the first section, the glottal airflow is filtered by the vocal tract to provide the air flow at the lip. This airflow is then converted to a pressure waveform at the lips and propagated as a sound signal. So, to get an estimate of the glottal airflow or glottal pulse, one needs to remove the effects of estimated vocal tract filter and lip radiation from the original speech signal. This technique is termed as inverse filtering, since in this process the estimated vocal tract filter and lip radiation effects are inversed to get the glottal flow estimate. MATLAB environment can be used to implement this technique [13–15].To receive such type of inverse filtering automatically, iterative adaptive inverse filtering (IAIF) algorithm has been used [16–18]. The block diagram of IAIF algorithm used is presented in Figure 3 [7]. Before estimation, the input speech signal is first high pass filtered using a linear-phase finite impulse response (FIR) filter with a cut-off frequency of 60 Hz to eliminate low frequency fluctuations and DC bias. The high pass filtered signal is used as the input to the next stages. The speech signal is divided into frames before filtering. In block 1, the LPC coefficient fit of order 1 is used to calculate the contribution of the glottal pulse to the speech signal. In the next block 2, this LPC coefficient of order 1 which symbolizes the force of the glottal pulse in the signal is used to design an inverse filter (all zero FIR filters) which is applied to get rid of the glottal effect of the original speech signal. So the input to block 3 represents the speech signal with the glottal flow component filtered out. Next in block 3, LPC fit of order 12 is used to capture the vocal tract filter effect in terms of filter coefficients. Here order 12 is chosen in accordance with the number of formant frequencies which is more than the double number of formants considered for the analysis [19, 20]. So in block 4, the vocal tract filter effect is removed from the original speech signal by inverse filtering. Signal out of this block consists of the effect of glottal flow and lip radiation effect. So to scrub out the radiation issue, a leaky integrator (with coefficient value more than 0.9 and less than 1) is used in block 5, which removes the lip radiation effect from the flow obtained after block 4. The output of block 5 is the first estimate of the glottal pulse. The second repetition runs analogously [7, 15]. The output of block 10 is the glottal pulse estimate of the original speech signal.Figure 3
Block diagram of IAIF.
### 1.4. Glottal Pulse and Its Derivative Parameters
The parameters of the glottal pulse can provide the quantitative information to examine their importance in the biomedical applications. There are three categories of glottal pulse parameters: time and amplitude domain, frequency domain, and glottal pulse derivative (LF) parameters. The time and amplitude domain parameters involve the extraction of certain time and amplitude instants from the glottal pulse. By counting on these timing instants, several time and amplitude based parameters can be calculated. These time instants can be specified using the glottal pulse and its derivative pulse as shown in Figure4.(i)
The fundamental time periodT is calculated using the fundamental frequency (f
o) of the signal frame.
(ii)
t
max
is that time instant when the amplitude of the glottal pulse is maximum or when the two vocal folds are completely open. t
min
can be defined similarly [21].
(iii)
A
a
c is the peak to peak amplitude level of the glottal pulse which is the difference between the maximum amplitude to the minimum amplitude of the glottal pulse [21].
(iv)
t
c is known as closure time instant which is the time instant when the two vocal folds are just about to close. This time instant is equal to that instant when the glottal pulse derivative pulse crosses to the positive amplitude after t
d
min
. Here t
d
min
is the time instant when the glottal pulse derivative pulse is at its minimum value [21].
(v)
t
o
1 and t
o
2 are the two opening time instants. To calculate t
o
1 first consider the time sequence which is having 10% amplitude of t
max
on the left side of it. Now go left from that time instant up to when the derivative pulse has approached the positive value of its amplitude. This time instant is the first opening time instant. For estimating t
o
2, first mark the time instant which is 5% more than t
o
1; then after this time instant look for the maximum positive value of the amplitude of the second derivative pulse of glottal waveform. That time instant is t
o
2. The importance of considering two opening instants is due to the more gradual opening of the glottal pulse than closing [21].
(vi)
t
q
c and t
q
o are the time instants where the amplitude of the glottal pulse is 50% of the peak to peak amplitude A
a
c [21].
(vii)
All the time based parameters are calculated with respect to the time instantt
max
[21].Time and amplitude instants in glottal pulse (a) and its derivative pulse (b) [15].
(a)
(b)From these timing instants, several time and amplitude based parameters can be calculated which are as follows.(i)
OQ (open quotient) measures the relative portion of the open phase compared to cycle duration. Two open quotients can be counted, namely, OQ1 and OQ2 [22].
(ii)
SQ (speed quotient) measures the ratio of the duration of opening phase to the duration of the closing phase. Possible speed quotients are SQ1 and SQ2 [22].
(iii)
CIQ (closing quotient) is the ratio of the duration of closing phase to the period lengthT [23].
(iv)
AQ (amplitude quotient) is the ratio of peak to peak amplitude level of glottal pulse and minimum amplitude of glottal pulse derivative [24, 25].
(v)
NAQ (normalized AQ) is the normalized value of AQ which is worked out by dividing AQ with the period lengthT [24, 25].
(vi)
QOQ (quasiopen quotient) is same as OQ except that it measures the relative portion of the quasitime instants, that is,t
q
c and t
q
o, compared to the cycle duration [26].
(vii)
OQ
a is the amplitude counterpart of OQ.Mathematically, these parameters can be developed as follows:(1)
OQ
1
=
t
c
-
t
o
1
T
,
OQ
2
=
t
c
-
t
o
2
T
,
OQ
a
=
A
a
c
Π
2
A
d
max
+
1
A
d
min
f
o
,
QOQ
=
t
q
c
-
t
q
o
T
,
SQ
1
=
t
max
-
t
o
1
t
c
-
t
max
,
SQ
2
=
t
max
-
t
o
2
t
c
-
t
max
,
CIQ
=
t
c
-
t
max
T
,
AQ
=
A
a
c
A
d
min
,
NAQ
=
AQ
T
.To estimate frequency domain parameters, the frequency or the power spectrum of the glottal pulse is considered as shown in Figure5 [15]. There are three main frequency domain parameters of the glottal pulse.Figure 5
Flow spectrum of a glottal pulse [15].First isH
1-H
2 or d
H
12 which is the difference of the first and second harmonics of the glottal frequency spectrum waveform in decibel [27]. Another similar parameter is harmonic richness factor (HRF), which is defined as the ratio between the sums of the amplitudes of harmonics above the fundamental frequency and the magnitude of the fundamental frequency or the first harmonic in decibels [28]. It is shown by the mathematical formula given below:
(2)
HRF
=
∑
r
≥
2
H
r
H
1
.HereH
r represents the magnitude of the rth harmonic. If H
1 increases, then H
1-H
2 will increase and HRF will decrease [15]. In [29], the author introduced another similar parameter, parabolic spectral parameter (PSP), which is the second order polynomial to the flow spectrum on a logarithmic scale, computed over a single glottal period [15].The final type of glottal pulse parameters is the glottal pulse derivative parameters. These parameters are termed as model based parameters because these parameters take on some mathematical expression on the glottal derivative pulse that generates an artificial derivative pulse. With the aid of the artificial pulse the model parameters are estimated. The most used mathematical model is Liljencrants-Fant (LF) model [7, 30]. It is a four parameter mathematical formulation of glottal flow derivative pulse [15]. It accepts applications in both voice analysis and speech synthesis [8, 31–35]. The spectral properties of glottal pulse parameters can also be considered with the aid of this model [36]. The LF approximated glottal derivative pulse is shown in Figure 6 [8].Figure 6
A typical approximation of glottal pulse (upper) and its derivative (lower) [8].Following are the timing instants and parameters of LF model.(i)
T
o
p is same as the opening time instant t
o
1 as we have talked about above.
(ii)
T
e is that time instant when the derivative pulse is having its minimum amplitude value [37].
(iii)
Time instantT
a is the timing instant of the tangent line drawn from the timing instant T
e to the right side of derivative pulse [37].
(iv)
Another timing instantT
p, is the instant when the derivative pulse crosses to zero amplitude level for the first time [38].
(v)
T
c is same as the glottal pulse closure time instant t
c.
(vi)
The parameterE
e is the magnitude of the slope of the negative going glottal pulse [38].From these timing instants a number of parameters can be obtained:(i)
(3)
R
a
=
T
a
′
f
o
,
whereT
a
′ time interval is equal to the difference between T
a and T
e and f
o is the fundamental frequency of the glottal pulse [32].
(ii)
(4)
R
g
=
1
2
T
p
′
f
o
,
whereT
p
′ time interval is equal to the difference between T
p and T
o
p [32].
(iii)
(5)
R
K
=
T
e
′
-
T
p
′
T
p
′
,
whereT
e
′ time interval is the difference between T
e and T
o
p [32].
(iv)
(6)
R
d
=
0.5
+
1.2
R
K
R
K
/
4
R
g
+
R
a
0.11
.
OQ (return) is the open quotient for return (closing) phase, which is calculated using the LF model. Consider(7)
OQ
=
T
e
′
f
o
=
1
+
R
K
2
R
g
.
### 1.5. Time, Frequency, and Energy Domain Parameters of Voice
To estimate the glottal parameters one has to apply several steps and algorithms for each frame of data. So if one does not want to look in depth of glottal based parameters, then, he can study the parameters that are directly estimated from the speech signal itself. Here in this section we will discuss time domain, frequency domain, and energy parameters of speech signal.(i)
Autocorrelation function is a time domain parameter of voice. It serves to see the similarity between a speech signal with itself after a little span of time. Let us consider a speech signals
(
n
) with a frame length of N samples. Let number of frames be m. Then the autocorrelation function of the speech signal for mth frame is defined as
(8)
r
m
=
1
2
N
+
1
∑
n
=
-
N
N
s
n
s
n
+
m
.
Whenm
=
0 then r
(
0
) represents the short term energy of the signal [39]. The value of the autocorrelation function varies between 0 and 1. It yields the value 1 if the speech signal is perfectly coupled with the signal frame just next to it.
(ii)
Harmonic to noise ratio (HNR) is the difference between the energies of the speech signal in periodic part and the energies of the signal in the noise in decibels. If HNR = 0 dB, then it implies that the energy in the harmonic part is equal to the energy in the noisy part. A large value of HNR is desirable in speech signals.
(iii)
Noise to harmonic ratio (NHR) is the average ratio of the energy of the noise components to the energy of the harmonic components present in the frequency range of speech signal. It evaluates noise present in the speech signal. Variations in amplitude, turbulence noise, subharmonic components, voice breaks, and so forth are considered in NHR. Low value of NHR is desirable in speech signals.
(iv)
Short time energy (STE) is defined as the energy of the short segment or frame of speech signal [40]. It can be applied as an effective parameter to differentiate between the voiced and unvoiced segments [41]. The short time energy can be expressed by the following mathematical expression:
(9)
STE
n
=
∑
n
s
n
w
n
-
m
2
.
Heres
(
n
) is the speech signal and w
(
n
) is the window function applied to the speech signal and m varies from 0 to n in a step of the frame size N, which means m
=
0
,
N
,
2
N
,
3
N
⋯
n
.
(v)
Energy entropy (EE) is a measure of the abrupt changes in energy. This is applied to observe silence and voiced region of speech segments. To calculate EE, first of all each frame is divided intoK subframes and energy of each sub frame is computed. Let e
i be the energy of a subframe, then EE of each frame is calculated using the formula [40]:
(10)
EE
=
-
∑
i
=
0
K
-
1
e
i
2
lo
g
2
e
i
2
.
(vi)
Zero crossing rate (ZCR) is a time domain parameter of speech signal. The number of times per second that the speech signal crosses the zero axis in a frame gives the ZCR in that frame [40]. Overall ZCR of the speech signal is computed by assuming the average value of all the individual ZCRs.
(vii)
Spectral centroid (SC) is used to characterize the center of mass of the speech spectrum. It is the weighted mean frequency for a given frame of the speech signal. Weights are the normalized energy of each frequency component in that frame. It can be helpful in detecting frequency peaks in the frame which can either correspond to the location of formants or pitch frequencies [42]. It is given by the formula below:
(11)
SC
=
∑
n
=
0
N
-
1
f
(
n
)
x
(
n
)
∑
n
=
0
N
-
1
x
(
n
)
.
Herex
(
n
) represents the weighted frequency value for the frame number n and f
(
n
) represents the center frequency value at that frame [40].
(viii)
Spectral flux (SF) is a measure which calculates how quickly the power spectrum of the signal is changing. It is the mean fluctuation of the power spectrum from one frame to the other frame. It is given by the formula below [40]:
(12)
SF
=
1
(
N
-
1
)
(
K
-
1
)
×
∑
n
=
1
N
-
1
∑
k
=
1
K
-
1
log
F
n
,
k
-
log
F
n
-
1
,
k
2
.
HereF
(
n
,
k
) is the FFT of the nth frame of the input speech signal, N is the total number of frames and K is the order of the FFT [40].
(ix)
Spectral roll off (SR) is a criterion of the spectral shape of sound like SC. It is that value of frequency for which 85% of the energy of the signal is less than that of frequency [40].
(x)
Jitter is a measure of period to period fluctuations in the fundamental frequency or pitch of the speech signal [43].Jitter in the signal is mainly affected due to the lack of control in the vibrations of the two vocal folds [44].Jitter can be assessed in many ways given below [43, 44]:
(a)
Jitter(absolute) is expressed as
(13)
J
i
t
t
e
r
abs
=
1
N
-
1
∑
k
=
1
N
-
1
T
k
-
T
k
+
1
.
HereN is the number of periods or frames of the signal and T
k is the pitch periods for the frame number k.
(b)
Jitter (relative) can be expressed equally:
(14)
J
i
t
t
e
r
relative
=
1
/
N
-
1
∑
k
=
1
N
-
1
T
k
-
T
k
+
1
1
/
N
∑
k
=
1
N
T
k
.
(c)
Jitter(rap) is the jitter calculated using relative average perturbation:
(15)
J
i
t
t
e
r
(
rap
)
=
1
/
N
-
2
∑
k
=
2
N
-
1
T
k
-
T
k
+
T
k
+
1
+
T
k
+
2
/
3
1
/
N
∑
k
=
1
N
T
k
.
(d)
Jitter(ppq5) is the five point period perturbation quotient jitter. It is computed as the average absolute difference between a period and the average of it and its four closest neighbors divided by the average period.
(xi)
Shimmer is a measure of period to period variation in the amplitudes of the speech signal [43]. It is affected mainly due to the reduction in the tension of the vocal folds [44].Shimmer can also be assessed in many ways listed below [43, 44]:
(a)
Shimmer (absolute) is the variation in the peak to peak amplitudes of the speech signal for consecutive periods taken in decibels. It can be expressed as
(16)
S
h
i
m
m
e
r
absolute
=
1
N
-
1
∑
k
=
1
N
-
1
20
log
A
k
+
1
A
k
.
HereA
k is the peak to peak amplitude for the current frame k and N is the number of frames.
(b)
Shimmer (relative) is the average absolute difference between the amplitudes of consecutive periods, divided by the average amplitude. It can be expressed as
(17)
S
h
i
m
m
e
r
relative
=
1
/
N
-
1
∑
k
=
1
N
-
1
A
k
-
A
k
+
1
1
/
N
∑
k
=
1
N
A
k
.
(c)
Shimmer(apq3) is the three point amplitude perturbation quotient which can be computed by considering the mean absolute deviation between the amplitude of a period and average of the amplitudes of its neighbors divided by the mean amplitude of the period. It can be expressed as
(18)
S
h
i
m
m
e
r
apq
3
=
1
/
N
-
2
∑
k
=
2
N
-
1
A
k
-
A
k
+
A
k
-
1
+
A
k
+
1
/
3
1
/
N
∑
k
=
1
N
-
1
A
k
.
(d)
SimilarlyShimmer(apq5) andShimmer(apq11) can be determined.It is said thatjitter(absolute) andshimmer(absolute) are useful in speaker recognition [44].(i)
Intensity or vocal intensity of the speech signal refers to the loudness effect of speech signal. Vocal intensity is related to the subglottis pressure of the airflow, which depends on the tension and the vibrations of the vocal folds [44]. A small number of vibrations in the vocal folds make quieter voice as compared to the large number of vibrations of the folds [45]. Mathematically vocal intensity can be expressed as sound intensity level (SIL) or sound pressure level (SPL) [46]. SIL or SPL is measured in dBs. SIL basically tells how much louder a given sound is as compared to the standard (soft) reference vocal intensity, of 10–12 watt/m2. This can be determined by [46]
(19)
SIL
=
10
log
I
I
0
dB
,
whereI
0 is the standard intensity value and sound intensity can also be expressed in terms of SPL also. Consider
(20)
SPL
=
10
log
P
P
0
dB
.
HereP
0 is the standard pressure level and is having the value of 0.00002 Pascal. SIL and SPL describe the same point of acoustic energy and can be used interchangeably [46].The formant frequencies can be estimated by taking the frequency response of the vocal tract filter. The peaks of the response are the formant frequencies. The amplitude and bandwidth values at those peaks are also very important parameters and must be considered.
## 1.1. Voice Production Process
The process of voice production involves a sequence of complex biological activities. It originates from the production of airflow in the lungs, which is modulated by the vocal folds (for voice sounds). Spectral shaping of the modulated airflow is done by the vocal tract cavities which transfer the airflow to the lips to radiate the sound in the outside world. This process of voice production is very well discussed in [1–3]. A simplified view of speech production is shown in Figure 1. Here the speech organs are divided into three main parts: lungs, larynx, and vocal tract. Lungs are acting as a power supply which supplies air pressure signals to the larynx stage. The larynx modulates the airflow as is given by the lungs. It consists of two vocal folds or vocal cords. These folds are made up of masses of flesh, ligament, and muscles [2]. The basic functionality of these folds is to stretch between the front and back parts of the larynx. The glottis is a slit like space between the two folds. The vocal folds are open during breathing. But they can either be in open or vibrating condition depending upon the speaking state. In case of voice sources like vowels, the vocal folds are in a vibrating state. This means vocal folds are opening and closing rapidly. For other sources, the vocal folds are not vibrating rapidly [1]. After the larynx stage the signal passes through the vocal tract which consists of three cavities; pharynx cavity, oral cavity, and nasal cavity. These organs are helpful in shaping the modulated airflow spectrally and also in adjusting the quality of speech [2]. The vibration of the vocal folds in case of voice sources can be estimated in the form of a pulse called glottal pulse. A glottal pulse is shown in Figure 2. As we can see, initially the folds are in closed position (air flow is zero above vocal folds); then they are opening slowly (air flow is increasing); then they are fully open (air flow is maximized), and after that they are closing at a faster rate as shown in the figure. From this we can determine the time duration of one glottal cycle, which is known as pitch period and the reciprocal of pitch period is known as fundamental frequency [1]. The value of the fundamental frequency is influenced by many factors like vocal fold muscle tension, vocal fold mass, and the air pressure behind the vocal folds. The average pitch range is roughly 80 Hz to 400 Hz in males and 120 Hz to 800 Hz in females [2].Figure 1
Simplified view of speech production [1].Figure 2
Periodic glottal airflow waveform [1].As the glottal pulse or the excitation signal moves upward on its way through the mouth and nose, it encounters certain obstructions. First the wall of the throat (in the pharyngeal cavity) creates impedance in its path. This impedance causes certain resonance frequencies in the signal. The same effect is caused by the walls of the mouth surrounding the oral cavity and by the walls of the nose surrounding the nasal cavity. The sizes and conformations of these cavities are purely speaker dependent. The resonances of these three cavities (pharyngeal, oral, and nasal) are frequently called formants: the first formant, the second formant, and the third formant, respectively. These frequencies depend upon the shape and dimension of the vocal tract [4]. Because of the motion of organs like tongue, and teeth, higher formant values are likewise possible. As these formant values are immediately linked to the vocal tract cavities so these parameters are also very important and must be measured. After travelling through the vocal tract, the signal is radiated outwards in the form of speech through the lips or nose (in case of nasal voice signals).The parameters of these organs play a significant role in determining the speaker’s characteristics. Getting a true appraisal of these parameters helps us to see the operation of the human speech production mechanism in a more skillful way [5]. These parameters can be beneficial for many speech processing applications such as speaker recognition and speech synthesis [6]. Similarly in biomedical applications or clinical research for the analysis of psychological stress or alcohol intoxication, these parameters play an important role [7, 8]. There is some change in the values of these parameters for normal to diseased or stressed state [9]. So there is a need to effectively estimate these parameters from the voice signal.
## 1.2. Introduction to Stress
For a number of years the researchers in the field of Speech science and Laryngological studies, are constantly working on the acoustic characteristics of normal and pathological voice. Various methods have been modernized in this subject area for providing the quantitative data [10]. The major reason of growing research in this area is because of the importance of voice signal in determining the effect of clinical disorders like psychological stress. Stress or emphasis is mostly specified as a psychological state that is a reaction to a perceived threat or task demand and is normally accompanied by some specific emotions (e.g., fear, anger, or disgust) [11]. The long term occurrence of stress has serious health consequences [12]. The obvious question that comes to mind is how do we measure stress? The most accurate estimations of a person’s stress level can be found by measuring various psychological parameters, such as ECG, EEG or other biological signals, or some biochemical methods [9]. But all these methods require costly and large setup. However, it is very easy to analyze the voice or speech signal; hence this type of analysis is easy and inexpensive. In daily life we often use the term stress to identify negative emotions. However, stress can be classified in two parts, eustress which is a term for positive stress or emotion (like happiness) and distress, which refers to the negative stress or emotions (like anger, fear, or disgust). The positive stress motivates, focuses energy, feels exciting, and improves performance. In contrast, negative stress causes anxiety, feels unpleasant, and decreases performance [9].
## 1.3. Glottal Pulse Extraction
As discussed in the first section, the glottal airflow is filtered by the vocal tract to provide the air flow at the lip. This airflow is then converted to a pressure waveform at the lips and propagated as a sound signal. So, to get an estimate of the glottal airflow or glottal pulse, one needs to remove the effects of estimated vocal tract filter and lip radiation from the original speech signal. This technique is termed as inverse filtering, since in this process the estimated vocal tract filter and lip radiation effects are inversed to get the glottal flow estimate. MATLAB environment can be used to implement this technique [13–15].To receive such type of inverse filtering automatically, iterative adaptive inverse filtering (IAIF) algorithm has been used [16–18]. The block diagram of IAIF algorithm used is presented in Figure 3 [7]. Before estimation, the input speech signal is first high pass filtered using a linear-phase finite impulse response (FIR) filter with a cut-off frequency of 60 Hz to eliminate low frequency fluctuations and DC bias. The high pass filtered signal is used as the input to the next stages. The speech signal is divided into frames before filtering. In block 1, the LPC coefficient fit of order 1 is used to calculate the contribution of the glottal pulse to the speech signal. In the next block 2, this LPC coefficient of order 1 which symbolizes the force of the glottal pulse in the signal is used to design an inverse filter (all zero FIR filters) which is applied to get rid of the glottal effect of the original speech signal. So the input to block 3 represents the speech signal with the glottal flow component filtered out. Next in block 3, LPC fit of order 12 is used to capture the vocal tract filter effect in terms of filter coefficients. Here order 12 is chosen in accordance with the number of formant frequencies which is more than the double number of formants considered for the analysis [19, 20]. So in block 4, the vocal tract filter effect is removed from the original speech signal by inverse filtering. Signal out of this block consists of the effect of glottal flow and lip radiation effect. So to scrub out the radiation issue, a leaky integrator (with coefficient value more than 0.9 and less than 1) is used in block 5, which removes the lip radiation effect from the flow obtained after block 4. The output of block 5 is the first estimate of the glottal pulse. The second repetition runs analogously [7, 15]. The output of block 10 is the glottal pulse estimate of the original speech signal.Figure 3
Block diagram of IAIF.
## 1.4. Glottal Pulse and Its Derivative Parameters
The parameters of the glottal pulse can provide the quantitative information to examine their importance in the biomedical applications. There are three categories of glottal pulse parameters: time and amplitude domain, frequency domain, and glottal pulse derivative (LF) parameters. The time and amplitude domain parameters involve the extraction of certain time and amplitude instants from the glottal pulse. By counting on these timing instants, several time and amplitude based parameters can be calculated. These time instants can be specified using the glottal pulse and its derivative pulse as shown in Figure4.(i)
The fundamental time periodT is calculated using the fundamental frequency (f
o) of the signal frame.
(ii)
t
max
is that time instant when the amplitude of the glottal pulse is maximum or when the two vocal folds are completely open. t
min
can be defined similarly [21].
(iii)
A
a
c is the peak to peak amplitude level of the glottal pulse which is the difference between the maximum amplitude to the minimum amplitude of the glottal pulse [21].
(iv)
t
c is known as closure time instant which is the time instant when the two vocal folds are just about to close. This time instant is equal to that instant when the glottal pulse derivative pulse crosses to the positive amplitude after t
d
min
. Here t
d
min
is the time instant when the glottal pulse derivative pulse is at its minimum value [21].
(v)
t
o
1 and t
o
2 are the two opening time instants. To calculate t
o
1 first consider the time sequence which is having 10% amplitude of t
max
on the left side of it. Now go left from that time instant up to when the derivative pulse has approached the positive value of its amplitude. This time instant is the first opening time instant. For estimating t
o
2, first mark the time instant which is 5% more than t
o
1; then after this time instant look for the maximum positive value of the amplitude of the second derivative pulse of glottal waveform. That time instant is t
o
2. The importance of considering two opening instants is due to the more gradual opening of the glottal pulse than closing [21].
(vi)
t
q
c and t
q
o are the time instants where the amplitude of the glottal pulse is 50% of the peak to peak amplitude A
a
c [21].
(vii)
All the time based parameters are calculated with respect to the time instantt
max
[21].Time and amplitude instants in glottal pulse (a) and its derivative pulse (b) [15].
(a)
(b)From these timing instants, several time and amplitude based parameters can be calculated which are as follows.(i)
OQ (open quotient) measures the relative portion of the open phase compared to cycle duration. Two open quotients can be counted, namely, OQ1 and OQ2 [22].
(ii)
SQ (speed quotient) measures the ratio of the duration of opening phase to the duration of the closing phase. Possible speed quotients are SQ1 and SQ2 [22].
(iii)
CIQ (closing quotient) is the ratio of the duration of closing phase to the period lengthT [23].
(iv)
AQ (amplitude quotient) is the ratio of peak to peak amplitude level of glottal pulse and minimum amplitude of glottal pulse derivative [24, 25].
(v)
NAQ (normalized AQ) is the normalized value of AQ which is worked out by dividing AQ with the period lengthT [24, 25].
(vi)
QOQ (quasiopen quotient) is same as OQ except that it measures the relative portion of the quasitime instants, that is,t
q
c and t
q
o, compared to the cycle duration [26].
(vii)
OQ
a is the amplitude counterpart of OQ.Mathematically, these parameters can be developed as follows:(1)
OQ
1
=
t
c
-
t
o
1
T
,
OQ
2
=
t
c
-
t
o
2
T
,
OQ
a
=
A
a
c
Π
2
A
d
max
+
1
A
d
min
f
o
,
QOQ
=
t
q
c
-
t
q
o
T
,
SQ
1
=
t
max
-
t
o
1
t
c
-
t
max
,
SQ
2
=
t
max
-
t
o
2
t
c
-
t
max
,
CIQ
=
t
c
-
t
max
T
,
AQ
=
A
a
c
A
d
min
,
NAQ
=
AQ
T
.To estimate frequency domain parameters, the frequency or the power spectrum of the glottal pulse is considered as shown in Figure5 [15]. There are three main frequency domain parameters of the glottal pulse.Figure 5
Flow spectrum of a glottal pulse [15].First isH
1-H
2 or d
H
12 which is the difference of the first and second harmonics of the glottal frequency spectrum waveform in decibel [27]. Another similar parameter is harmonic richness factor (HRF), which is defined as the ratio between the sums of the amplitudes of harmonics above the fundamental frequency and the magnitude of the fundamental frequency or the first harmonic in decibels [28]. It is shown by the mathematical formula given below:
(2)
HRF
=
∑
r
≥
2
H
r
H
1
.HereH
r represents the magnitude of the rth harmonic. If H
1 increases, then H
1-H
2 will increase and HRF will decrease [15]. In [29], the author introduced another similar parameter, parabolic spectral parameter (PSP), which is the second order polynomial to the flow spectrum on a logarithmic scale, computed over a single glottal period [15].The final type of glottal pulse parameters is the glottal pulse derivative parameters. These parameters are termed as model based parameters because these parameters take on some mathematical expression on the glottal derivative pulse that generates an artificial derivative pulse. With the aid of the artificial pulse the model parameters are estimated. The most used mathematical model is Liljencrants-Fant (LF) model [7, 30]. It is a four parameter mathematical formulation of glottal flow derivative pulse [15]. It accepts applications in both voice analysis and speech synthesis [8, 31–35]. The spectral properties of glottal pulse parameters can also be considered with the aid of this model [36]. The LF approximated glottal derivative pulse is shown in Figure 6 [8].Figure 6
A typical approximation of glottal pulse (upper) and its derivative (lower) [8].Following are the timing instants and parameters of LF model.(i)
T
o
p is same as the opening time instant t
o
1 as we have talked about above.
(ii)
T
e is that time instant when the derivative pulse is having its minimum amplitude value [37].
(iii)
Time instantT
a is the timing instant of the tangent line drawn from the timing instant T
e to the right side of derivative pulse [37].
(iv)
Another timing instantT
p, is the instant when the derivative pulse crosses to zero amplitude level for the first time [38].
(v)
T
c is same as the glottal pulse closure time instant t
c.
(vi)
The parameterE
e is the magnitude of the slope of the negative going glottal pulse [38].From these timing instants a number of parameters can be obtained:(i)
(3)
R
a
=
T
a
′
f
o
,
whereT
a
′ time interval is equal to the difference between T
a and T
e and f
o is the fundamental frequency of the glottal pulse [32].
(ii)
(4)
R
g
=
1
2
T
p
′
f
o
,
whereT
p
′ time interval is equal to the difference between T
p and T
o
p [32].
(iii)
(5)
R
K
=
T
e
′
-
T
p
′
T
p
′
,
whereT
e
′ time interval is the difference between T
e and T
o
p [32].
(iv)
(6)
R
d
=
0.5
+
1.2
R
K
R
K
/
4
R
g
+
R
a
0.11
.
OQ (return) is the open quotient for return (closing) phase, which is calculated using the LF model. Consider(7)
OQ
=
T
e
′
f
o
=
1
+
R
K
2
R
g
.
## 1.5. Time, Frequency, and Energy Domain Parameters of Voice
To estimate the glottal parameters one has to apply several steps and algorithms for each frame of data. So if one does not want to look in depth of glottal based parameters, then, he can study the parameters that are directly estimated from the speech signal itself. Here in this section we will discuss time domain, frequency domain, and energy parameters of speech signal.(i)
Autocorrelation function is a time domain parameter of voice. It serves to see the similarity between a speech signal with itself after a little span of time. Let us consider a speech signals
(
n
) with a frame length of N samples. Let number of frames be m. Then the autocorrelation function of the speech signal for mth frame is defined as
(8)
r
m
=
1
2
N
+
1
∑
n
=
-
N
N
s
n
s
n
+
m
.
Whenm
=
0 then r
(
0
) represents the short term energy of the signal [39]. The value of the autocorrelation function varies between 0 and 1. It yields the value 1 if the speech signal is perfectly coupled with the signal frame just next to it.
(ii)
Harmonic to noise ratio (HNR) is the difference between the energies of the speech signal in periodic part and the energies of the signal in the noise in decibels. If HNR = 0 dB, then it implies that the energy in the harmonic part is equal to the energy in the noisy part. A large value of HNR is desirable in speech signals.
(iii)
Noise to harmonic ratio (NHR) is the average ratio of the energy of the noise components to the energy of the harmonic components present in the frequency range of speech signal. It evaluates noise present in the speech signal. Variations in amplitude, turbulence noise, subharmonic components, voice breaks, and so forth are considered in NHR. Low value of NHR is desirable in speech signals.
(iv)
Short time energy (STE) is defined as the energy of the short segment or frame of speech signal [40]. It can be applied as an effective parameter to differentiate between the voiced and unvoiced segments [41]. The short time energy can be expressed by the following mathematical expression:
(9)
STE
n
=
∑
n
s
n
w
n
-
m
2
.
Heres
(
n
) is the speech signal and w
(
n
) is the window function applied to the speech signal and m varies from 0 to n in a step of the frame size N, which means m
=
0
,
N
,
2
N
,
3
N
⋯
n
.
(v)
Energy entropy (EE) is a measure of the abrupt changes in energy. This is applied to observe silence and voiced region of speech segments. To calculate EE, first of all each frame is divided intoK subframes and energy of each sub frame is computed. Let e
i be the energy of a subframe, then EE of each frame is calculated using the formula [40]:
(10)
EE
=
-
∑
i
=
0
K
-
1
e
i
2
lo
g
2
e
i
2
.
(vi)
Zero crossing rate (ZCR) is a time domain parameter of speech signal. The number of times per second that the speech signal crosses the zero axis in a frame gives the ZCR in that frame [40]. Overall ZCR of the speech signal is computed by assuming the average value of all the individual ZCRs.
(vii)
Spectral centroid (SC) is used to characterize the center of mass of the speech spectrum. It is the weighted mean frequency for a given frame of the speech signal. Weights are the normalized energy of each frequency component in that frame. It can be helpful in detecting frequency peaks in the frame which can either correspond to the location of formants or pitch frequencies [42]. It is given by the formula below:
(11)
SC
=
∑
n
=
0
N
-
1
f
(
n
)
x
(
n
)
∑
n
=
0
N
-
1
x
(
n
)
.
Herex
(
n
) represents the weighted frequency value for the frame number n and f
(
n
) represents the center frequency value at that frame [40].
(viii)
Spectral flux (SF) is a measure which calculates how quickly the power spectrum of the signal is changing. It is the mean fluctuation of the power spectrum from one frame to the other frame. It is given by the formula below [40]:
(12)
SF
=
1
(
N
-
1
)
(
K
-
1
)
×
∑
n
=
1
N
-
1
∑
k
=
1
K
-
1
log
F
n
,
k
-
log
F
n
-
1
,
k
2
.
HereF
(
n
,
k
) is the FFT of the nth frame of the input speech signal, N is the total number of frames and K is the order of the FFT [40].
(ix)
Spectral roll off (SR) is a criterion of the spectral shape of sound like SC. It is that value of frequency for which 85% of the energy of the signal is less than that of frequency [40].
(x)
Jitter is a measure of period to period fluctuations in the fundamental frequency or pitch of the speech signal [43].Jitter in the signal is mainly affected due to the lack of control in the vibrations of the two vocal folds [44].Jitter can be assessed in many ways given below [43, 44]:
(a)
Jitter(absolute) is expressed as
(13)
J
i
t
t
e
r
abs
=
1
N
-
1
∑
k
=
1
N
-
1
T
k
-
T
k
+
1
.
HereN is the number of periods or frames of the signal and T
k is the pitch periods for the frame number k.
(b)
Jitter (relative) can be expressed equally:
(14)
J
i
t
t
e
r
relative
=
1
/
N
-
1
∑
k
=
1
N
-
1
T
k
-
T
k
+
1
1
/
N
∑
k
=
1
N
T
k
.
(c)
Jitter(rap) is the jitter calculated using relative average perturbation:
(15)
J
i
t
t
e
r
(
rap
)
=
1
/
N
-
2
∑
k
=
2
N
-
1
T
k
-
T
k
+
T
k
+
1
+
T
k
+
2
/
3
1
/
N
∑
k
=
1
N
T
k
.
(d)
Jitter(ppq5) is the five point period perturbation quotient jitter. It is computed as the average absolute difference between a period and the average of it and its four closest neighbors divided by the average period.
(xi)
Shimmer is a measure of period to period variation in the amplitudes of the speech signal [43]. It is affected mainly due to the reduction in the tension of the vocal folds [44].Shimmer can also be assessed in many ways listed below [43, 44]:
(a)
Shimmer (absolute) is the variation in the peak to peak amplitudes of the speech signal for consecutive periods taken in decibels. It can be expressed as
(16)
S
h
i
m
m
e
r
absolute
=
1
N
-
1
∑
k
=
1
N
-
1
20
log
A
k
+
1
A
k
.
HereA
k is the peak to peak amplitude for the current frame k and N is the number of frames.
(b)
Shimmer (relative) is the average absolute difference between the amplitudes of consecutive periods, divided by the average amplitude. It can be expressed as
(17)
S
h
i
m
m
e
r
relative
=
1
/
N
-
1
∑
k
=
1
N
-
1
A
k
-
A
k
+
1
1
/
N
∑
k
=
1
N
A
k
.
(c)
Shimmer(apq3) is the three point amplitude perturbation quotient which can be computed by considering the mean absolute deviation between the amplitude of a period and average of the amplitudes of its neighbors divided by the mean amplitude of the period. It can be expressed as
(18)
S
h
i
m
m
e
r
apq
3
=
1
/
N
-
2
∑
k
=
2
N
-
1
A
k
-
A
k
+
A
k
-
1
+
A
k
+
1
/
3
1
/
N
∑
k
=
1
N
-
1
A
k
.
(d)
SimilarlyShimmer(apq5) andShimmer(apq11) can be determined.It is said thatjitter(absolute) andshimmer(absolute) are useful in speaker recognition [44].(i)
Intensity or vocal intensity of the speech signal refers to the loudness effect of speech signal. Vocal intensity is related to the subglottis pressure of the airflow, which depends on the tension and the vibrations of the vocal folds [44]. A small number of vibrations in the vocal folds make quieter voice as compared to the large number of vibrations of the folds [45]. Mathematically vocal intensity can be expressed as sound intensity level (SIL) or sound pressure level (SPL) [46]. SIL or SPL is measured in dBs. SIL basically tells how much louder a given sound is as compared to the standard (soft) reference vocal intensity, of 10–12 watt/m2. This can be determined by [46]
(19)
SIL
=
10
log
I
I
0
dB
,
whereI
0 is the standard intensity value and sound intensity can also be expressed in terms of SPL also. Consider
(20)
SPL
=
10
log
P
P
0
dB
.
HereP
0 is the standard pressure level and is having the value of 0.00002 Pascal. SIL and SPL describe the same point of acoustic energy and can be used interchangeably [46].The formant frequencies can be estimated by taking the frequency response of the vocal tract filter. The peaks of the response are the formant frequencies. The amplitude and bandwidth values at those peaks are also very important parameters and must be considered.
## 2. Results and Discussion
This section describes the experiments performed and results produced by those experiments. The experimental methodology is first outlined and then followed by the results of the experiment. Let us discuss various experiments performed on the voice parameters.
### 2.1. Estimation of Glottal Flow
The goal of this experiment was to estimate the glottal flow or glottal pulses from the voice signal of vowels using IAIF algorithm described in the above section by using MATLAB as well as SIMULINK [16–18]. The foremost prerequisite of this algorithm is to obtain the predictor coefficients from the speech signal. For this, lpc function in MATLAB or lpc model of SIMULINK can be used [13, 14]. The speech signal recordings were available in wav format. The speech signals were converted into data samples by taking the sampling frequency of 10 KHz using MATLAB. The workspace block was used to take those samples in SIMULINK. Digital filter design blocks were used for FIR high pass and inverse filtering. The Autocorrelation LPC blocks were employed to get the predictor coefficients. The digital Integrator block was used for integration. The SIMULINK model of the IAIF algorithm is shown in Figure 7.Figure 7
SIMULINK model of IAIF algorithm.The input speech waveform and output glottal waveform for vowel /a/ are shown in Figure8.Input speech waveform and Output glottal waveform of IAIF algorithm for vowel /a/.
(a)
(b)Using the MATLAB code of IAIF algorithm, glottal pulses of five vowels /a/, /e/, /i/, /o/, /u/ obtained are shown in Figure9.Glottal pulses for five vowels /a/, /e/, /i/, /o/, and /u/, respectively.
(a)
(b)
(c)
(d)
(e)
### 2.2. Comparison of Computed Formant Frequencies
Using the inverse filtering technique the formant parameters can be computed by using two methods. One of them is to find out the peaks of the frequency response of the vocal tract filter and other is to find out the roots of the polynomial equation formed using LPC coefficients of vocal tract filter as explained in [9]. This experimentation was performed to compare the computed formant frequencies by those two methods with the values obtained using phonetic software PRAAT [47].A total of 15 speech signals were analyzed and four formant frequencies were computed for each case. The speech signals used consist of five vowel segments each for male, female, and child and are available in [48]. In 12 of them (80% of the total), formant values obtained using the two methods above were rather near to the values computed using PRAAT software. In case of LPC polynomial root method, some false formants were also noted. So this idea is not so precise and should be used rarely. By applying these methods, we can also compute the 3 dB bandwidth values and amplitude values for each formant [9].Tables1 and 2 are shown for male vowel /i/ and child vowel /a/.Table 1
Comparison of computed formant frequencies for male vowel /i/.
Formant number
By roots
By response
By PRAAT
1
241.3
244.1
233.5
2
2263.6
2270.5
2246.1
3
3194.5
3203.1
3148.6
4
3832.6
3837.9
3828.7Table 2
A comparison of computed formant frequencies for child vowel /a/.
Formant number
By roots
By response
By PRAAT
1
532.5
546.9
549.5
2
1194.1
1196.3
1259.4
3
1807.9
1801.8
1872.6
4
3903.8
3911.1
3893.7
### 2.3. LPC Coefficients versus Vocal Tract Cavities
As we have discussed in the first section that inverse filtering and LPC coefficients approach can be used to model the human vocal tract and is helpful in determining the formant frequencies, so there can be some relationship between the LPC coefficients of the vocal tract and vocal tract cavities. This relationship can be helpful in determining which LPC coefficient of the vocal tract corresponds to which cavity of the vocal tract. It was talked about in the beginning section that each cavity of the vocal tract corresponds to a formant frequency and in the last experiment, we have computed formant frequencies using LPC coefficients of the vocal tract calculated during the final stage of IAIF algorithm. So a relationship can be derived between LPC coefficients and formant frequencies. To derive a relationship 5 speech signals (different persons) were taken. In each signal, each LPC coefficient of the vocal tract was changed (increased and decreased) from 5 to 50%. Corresponding to each change all the formant parameters (frequencies, amplitudes, and bandwidths) were estimated. So for a single signal a total of 24 sets of parameters (both increased and decreased) were tabulated. So for five signals a total of 120(
24
*
5
) sets of parameters were tabulated. A single set of the table for the first signal for a change up to 20% is shown in Table 3. This table determines the change in the formant parameters when the 1st LPC coefficient of the vocal tract is increased. Here bold values determine that the corresponding value is more than its original value when no parameter was changed. The original values of the parameters are depicted in Table 4.Table 3
Change in the formant parameters when a single coefficient value is changed from 5 to 20%.
Parameters/change
5%
10%
15%
20%
F
1 (Hz)
551.0
542.0
532.0
512.7
A
1 (dB)
31.2
29.7
20.7
16.4
B
1 (Hz)
37.4
47.6
138.0
225.0
F
2 (Hz)
913.0
883.8
849
825.2
A
2 (dB)
22.1
19.4
16.9
14.6
B
2 (Hz)
98.7
144.3
196.0
245.2
F
3 (Hz)
1967.0
1958.0
1953.0
1948.2
A
3 (dB)
3.3
2.8
2.4
1.9
B
3 (Hz)
312.0
323.9
335.0
348.1
F
4 (Hz)
3291.0
3281.2
3276.0
3271.5
A
4 (dB)
8.6
7.4
6.4
5.4
B
4 (Hz)
228.0
253.4
277.0
310.4
F
5 (Hz)
3842.0
3847.7
3857.0
3867.2
A
5 (dB)
11.9
11.0
10.2
9.4
B
5 (Hz)
84.6
89.0
93.5
98.2Table 4
Original values.
F
1 (Hz)
556.6
A
1 (dB)
21.1
B
1 (Hz)
109.7
F
2 (Hz)
947.3
A
2 (dB)
24.7
B
2 (Hz)
66.3
F
3 (Hz)
1977.5
A
3 (dB)
3.7
B
3 (Hz)
300.2
F
4 (Hz)
3300.8
A
4 (dB)
9.9
B
4 (Hz)
80.4
F
5 (Hz)
3833.0
A
5 (dB)
12.8
B
5 (Hz)
201.9After analyzing all the data, the following conclusions were derived.(i)
All the formant parameters were altered due to change in a single coefficient. This signifies that all the portions of the vocal tract are associated to each coefficient.
(ii)
Obtained results indicate that these variations follow an individual trend rather than any global trend. So this type of analysis is purely speaker dependent.
(iii)
Yet a similar trend can be imaged in the change of the value of formant frequencies of all the signals.
(iv)
FormantF1 changes (either increase or decrease) the most, if any individual coefficient is changed.
(v)
After that formantF2 andF4 come in 2nd and 3rd place in the list.
(vi)
In 4 out of 5 signals,F3 comes afterF4, and in 1 signalF5 comes afterF4.
(vii)
No such character of pattern was obtained for amplitudes and bandwidths.
(viii)
Nevertheless, in some cases an opposite tendency was seen in bandwidth and amplitude, meaning that if bandwidth was increasing, the amplitude was also decreasing for the whole change.Figure 10 shows diagrammatically the change in formant values along with bandwidths and amplitudes for a sample.Figure 10
Variations in the formant parameters due to change in LPC coefficients for a signal.
### 2.4. Estimation of Vocal Tract Transfer Function for an Individual
According to source-filter theory of speech production, to model the speech production mechanism digitally, we need to consider separate elements of speech production. The speech production system can be modelled with three separate elements: the source, the vocal tract filter, and the radiation effects [17]. The steady state system function of the digital filter is given by the expression:
(21)
H
z
=
S
z
U
z
=
G
1
-
∑
k
=
1
p
a
k
z
-
k
.The primary purpose of this experimentation was to somehow count for a method to forecast or predict the transfer function of vocal tract for an individual. The methodology used was first to calculate the vocal tract predictor coefficients for a signal from the final stage of IAIF algorithm and the gain factorG using lpc function in MATLAB, then by the use of (21) pole zero plot was plotted. As we have discussed before that the LPC order for the vocal tract filter taken is 12 so there will be 12 poles in the transfer function of the vocal tract (Section 1.3).The experimentation was done on two male persons of ages 24 and 26, respectively, by recording their voice samples using Sony IC Recorder (ICD-UX513F) device. Vowels /a/, /e/, and /o/ were taken for the analysis. Each person was asked to pronounce the vowels for at least 3 seconds. Both the persons were asked not to change their day to day activities during the analysis. Total 16 speech samples of each vowel were taken in a single day starting from 7:00 in the morning to 10:00 at night with each sample taken after each hour for each person. So for two persons a total of 96 voice signals of individual vowels were analyzed during two consecutive days. Each vowel signal was pulled out in frames with the help of phonetic software PRAAT [47]. The middle frame was taken for the analysis considering the fact that the speech signal is stationary for a small window of 30–50 msec and has the highest energy at its middle portion [15].For each signal, parameters like pitch, LPC coefficients of the vocal tract, formant frequencies, pole zero plot, and transfer function were estimated. LPC coefficients were estimated using IAIF algorithm. Formants were estimated using the frequency response method of LPC coefficients of the vocal tract. The pitch was estimated using PRAAT. MATLAB was used for pole zero plot for each signal.The following are the observations of this experiment.It was expected that the transfer function for a particular vowel must be unique for a person if calculated at any time of the day. But the experiment showed that the individual shapes of pole zero plots at any time in the day were different from the shapes of pole zero plots calculated at other times. Figure11 shows pole zero plots for first person at four sampling times.Pole zero plots of the vocal tract for vowel /a/ at times 7:00 AM day 1 (upper left side) 10:00 PM day 2 (upper right side), 3:00 PM day 1 (lower left side), and 9:00 PM day 2 (upper right side).
(a)
(b)
(c)
(d)When the mean value of all the coefficients for each individual vowel for each day was taken and pole-zero plot was plotted for those coefficients, then it was observed that the overall shapes of pole-zero plot for each day were approximately the same. Figure12 shows overall pole zero plot for person 2 for vowel /o/ for both days and Figure 13 shows overall pole zero plot for vowel /a/ for person 1 for both days. So it can be said that the average behaviour of the vocal tract throughout the day is the same which corresponds to its resonance or unique behaviour.Mean Pole zero plots for vowel /o/ for person 2 for day 1 (left side) and day 2 (right side).
(a)
(b)Mean Pole zero plots for vowel /e/ for person 1 for day 1 (left side) and day 2 (right side).
(a)
(b)The average pitch value and formant frequencies for person 1 are shown in Table5.Table 5
Average formant frequencies and pitch for person 1 for both days.
F
1 (Hz)
F
2 (Hz)
F
3 (Hz)
F
4 (Hz)
F
5 (Hz)
Pitch (Hz)
/a/
Day 1
405.58
1777.6
2413.9
3463.1
4312.0
109.60
Day 2
398.87
1753.2
2427.6
3355.6
4327.0
106.24
/e/
Day 1
304.56
1982.2
2395.8
3498.2
4101.6
110.12
Day 2
300.60
2062.7
2207.3
3564.1
4207.1
106.18
/o/
Day 1
389.40
811.16
2430.1
2770.5
4260.8
108.58
Day 2
403.07
862.75
2329.2
3185.8
4207.7
104.85The following observations can be concluded with this experiment.(i)
This experiment shows that the human vocal tract system tends to change its shape differently in different times of the day.
(ii)
This variation in the shape of the vocal tract can be due to day to day activities of that person and can be due to intake of food in the body through the throat or due to lack of energy in the body as the day goes on.
(iii)
But in spite of the fluctuations of the vocal tract, the overall shape follows clear uniqueness as we have found out from the pole zero curves.
(iv)
The pole-zero plot obtained after taking the mean values corresponds to the vocal tract transfer function for that individual for some specific vowel.
(v)
This uniqueness in the pole zero plot can act as a unique signature of that person because the shapes of the pole zero plot were different for same vowels in those two persons.
(vi)
So there exists a possibility to find out the biological signature of a person utilizing the vocal system in man.
(vii)
This type of analysis can be helpful in studying the vocal tract system behavior in terms of poles.
### 2.5. Statistical Investigation of Psychological Stress on Human Voice Spectrum
The following work deals with the analysis of speech signal under psychological stress for both positive and negative states of stress. To investigate the influence of stress on speech, acoustic parameters of speech signal were considered. For this type of estimation a suitable database or corpus is required. The most frequently used database among the researchers is the SUSAS (Speech under Simulated and Actual Stress) database of American English which is distributed by Linguistic Data Consortium at the University of Pennsylvania [49]. A German language database called emoDB is also very popular among researchers [50]. A list of existing emotional database is provided in [51, 52]. The database utilized in our analysis was Surrey Audio-Visual Expressed Emotion (SAVEE) database [53, 54]. The database consists of four persons (DC, JE, JK, and KL) of ages 27 to 31 depicting the six basic emotions (anger, disgust, fear, happiness, sadness, and surprise) and the neutral state. The recordings consist of 15 phonetically balanced sentences per emotion (with 15 additional sentences for neutral state) resulting in a corpus of 480 British English utterances. This database is an open source database which can be obtained from the university website on request [55].The database consists of 15 sentences for each speaker and represents all emotions. Out of these 15, 3 sentences are common and rests are emotion specific. These 3 sentences are considered for the evaluation.The three sentences were the following.(i)
She had your dark suit in greasy wash water all year.
(ii)
Do not ask me to carry an oily rag like that.
(iii)
Will you tell me why?There were three sentences for each speaker and each emotion so a total of 84 signals were considered. 11 vowel segments of 40–60 milliseconds duration were extracted from the individual words of these 3 sentences for each speaker and each emotion using phonetic software PRAAT.These segments consist of phonemes /aa/ (resemble vowel /a/ sound, e.g., hate), /la/ (resemble long vowel /a/, e.g., had), /u/ (resemble vowel sound /u/, e.g., book), /o/ (resemble vowel sound /o/, e.g., boat) and /aj/ (resemble vowel /i/ sound, e.g., hide). For each speaker and each emotion, a total of 11 segments were extracted so a total of 308 segments were analyzed.In the analysis the psychological stress is categorized into three major classes. First is neutral state, the second is positive stress, which was taken as a combination of happiness and surprise emotion, and third is negative stress, which was taken as a combination of anger, disgust, fear, and sadness emotions.A number of parameters (about 51 parameters) were judged in the depth psychologies which are grouped under the categories as follows.(i)
Group 1 = pitch and intensity (evaluated for all the sentences).
(ii)
Group 2 =Jitter,Shimmer, andAutocorrelation (evaluated for all the sentences).
(iii)
Group 3 = HNR (harmonic to noise ratio) and NHR (noise to harmonic ratio) (evaluated for all the sentences).
(iv)
Group 4 = energy, time, and frequency parameters (energy entropy (EE), short time energy (STE), zero crossing rate (ZCR), spectral roll off (SR), spectral centroid (SC), spectral flux (SF), (evaluated for all the sentences).
(v)
Group 5 = formant parameters (frequencies (F1, F2,andF3), amplitudes (A1, A2,andA3), and bandwidths (B1, B2,andB3) (evaluated vowels segment wise).
(vi)
Group 6 = glottal pulse timing parameters (NAQ, AQ (milli), CIQ, OQ1, OQ2, Oqa, QOQ, SQ1, and SQ2) (evaluated vowel segment wise).
(vii)
Group 7 = glottal pulse frequency parameters (dH12,PSP,and HRF) (evaluated vowel segment wise).
(viii)
Group 8 = glottal pulse derivative parameters (Ra, Rg, Rk, Rd,andOq) (fvaluated vowel segment wise).
(ix)
Group 9 = first 12 mfcc feature coefficients (evaluated vowel segments wise).Groups 1, 2, and 3 parameters were evaluated using PRAAT software. Groups 4, 5, 9, and 10 were assessed by writing their MATLAB codes. Groups 6, 7, and 8 were evaluated using TKK APARAT software [15].For each signal, all the parameters were evaluated and tabulated emotion wise. After evaluation, they were categorized in terms of positive, negative, and neutral states by combining the appropriate emotion (taking mean values).The outcomes of the analysis were analyzed by two methods. The foremost objective was to appear for the individual pattern in the decreasing order of values of the parameters in case of all the three states and second aim was to work out the most effective parameters among different groups.To count on the most effective parameters under each group, DR (discrimination ratio) criteria was used. Consider(22)
DR
i
=
m
N
i
-
m
S
i
2
d
N
i
2
+
d
S
i
2
,
where m
N is the mean value of that parameter under neutral state and m
S is the mean value of that parameter under stressed state. d
N and d
S are standard deviations for those parameters.DR was calculated for positive, negative, and overall stress (by taking averages of DR of both positive and negative). Higher the DR factor more effective is the parameter.Let us consider the DR calculation for first formantF1 for vowel /aa/ for speaker DC. By taking the mean values of first formantF1 for all frames following data was obtained:
(23)
m
N
F
1
=
656.74
Hz
,
m
P
F
1
=
650.64
Hz
,
m
Neg
(
F
1
)
=
639.65
Hz
,
d
N
(
F
1
)
=
37.979
Hz
,
d
P
F
1
=
18.989
Hz
,
d
Neg
F
1
=
13.81
Hz
.Using the above data DR for formantF1 for positive and negative stressed states can be calculated using (22):
(24)
DR
(
F
1
)
(
Positive
)
=
656.74
-
650.64
2
37.97
9
2
+
18.98
9
2
=
0.0206
.
Similarly,
(25)
DR
F
1
Negative
=
656.74
-
639.65
2
37.97
9
2
+
13.8
1
2
=
0.1787
.Overall DR can be calculated by taking the mean values of DR (positive) and DR (negative).Tables6 and 7 show the DR evaluation table for some parameters of vowels /aa/ for speaker JE for positive stress and for vowel /la/ for speaker JK for negative stress, respectively.Table 6
DR evaluation table for vowel /aa/ for speaker JE.
Parameter
Mean (N)
Deviation (N)
Mean (P)
Deviation (P)
DR (Pos)
F
1
615.24
41.43
610.35
34.52
0.01
F
2
1154.79
58.70
1182.86
44.89
0.14
F
3
2700.20
75.96
2967.53
84.59
5.53
A
1
32.26
1.09
22.43
3.05
9.24
A
2
13.81
1.80
16.67
3.15
0.62
A
3
10.63
0.70
7.65
0.65
9.65
B
1
71.70
8.72
173.04
136.03
0.55
B
2
290.47
10.67
183.69
44.65
5.41
B
3
105.75
32.67
143.75
30.42
0.72
NAQ
0.09
0.05
0.13
0.03
0.53
AQ (milli)
0.87
0.14
0.56
0.07
4.20
CIQ
0.16
0.10
0.27
0.09
0.73
OQ1
0.44
0.29
0.59
0.11
0.25
OQ2
0.39
0.29
0.49
0.13
0.11Table 7
DR evaluation table for vowel /la/ for speaker JK.
Parameter
Mean (N)
Deviation (N)
Mean (Neg)
Deviation (Neg)
DR (Neg)
F
1
755.21
25.06
802.82
54.16
0.64
F
2
1453.45
28.61
1515.30
76.87
0.57
F
3
2651.37
119.70
2606.61
173.18
0.05
A
1
20.15
2.18
19.09
6.11
0.03
A
2
14.79
4.04
15.59
4.27
0.02
A
3
15.74
2.52
10.62
2.76
1.88
B
1
136.33
30.70
208.07
125.56
0.31
B
2
209.80
107.89
185.96
84.99
0.03
B
3
141.36
39.45
216.01
85.44
0.63
NAQ
0.08
0.01
0.08
0.04
0.01
AQ (milli)
0.64
0.03
0.52
0.20
0.33
CIQ
0.12
0.02
0.14
0.08
0.06
OQ1
0.55
0.08
0.48
0.11
0.30
OQ2
0.28
0.06
0.35
0.10
0.31The results from the pattern in the order of stress state of the parameters are as follows.(i)
8 parameters out of 13 parameters (61.5%), which were evaluated for all the sentences, show a unique rule for all the speakers so they can be helpful in stress detection. Parameters such as pitch, intensity, shimmer, jitter, EE, ZC, SR, and SC show these results. For pitch and intensity, distribution functions were plotted. Figure14 shows the distribution function of pitch values in case of speaker DC. In 6 out of those 8 parameters, positive stressed signal shows the highest value, followed by negative stress and neutral case.
(ii)
27 out of 38 parameters (71%), which were evaluated for vowel segments, show unique patterns of the values for all the stress states in 3 out of 4 speakers. These 27 parameters were showing results for 37% of the total vowel signals that were analyzed. Out of these parameters, parameterR
a was showing positive results for all the analyzed vowels with positive stressed data having the highest value, followed by negative and neutral data.
(iii)
In nut shell, 35 parameters out of 51 parameters are affected due to stress and are showing a singular practice of values in the stressed state for 32% of the examined data.Figure 14
Distribution function for Pitch values for speaker DC.Results according to the DR criteria were evaluated group wise and are shown in Tables8 and 9.Table 8
Highest DR values for group numbers 1 to 4.
Group number
Positive effective
Negative effective
Overall
1
Pitch
Pitch
Pitch
2
—
Autocorrelation
—
3
HNR
HNR
—
4
—
—
SCTable 9
Highest DR values for group numbers 5 To 9. (P: positive; N: negative; O: overall).
(a)
Group name
/aa/
/la/
P
N
O
P
N
O
Formant freq.
F
3
F
3
F
3
—
—
—
Formant amp.
—
—
—
A
3
—
A
3
Formant BWs
—
—
—
B
3
B
3
B
3
Group 6
AQ
—
AQ
—
—
—
Group 7
—
—
—
—
—
—
Group 8
Ra
—
Ra
Ra
—
Ra
Group 9
—
—
—
—
—
—
(b)
Group name
/u/
/o/
P
N
O
P
N
O
Formant freq.
—
—
F
1
F
2
—
—
Formant amp.
A
1
—
A
1
—
—
—
Formant BWs
—
—
—
—
—
—
Group 6
—
—
—
—
—
—
Group 7
—
—
—
dH
dH
dH
Group 8
Ra
Ra
Ra
Ra
Ra
Ra
Group 9
—
—
—
—
—
—
#### 2.5.1. Final Results
(i)
For phoneme /aa/,F3,AQ, andRa are the most effective parameters for positive stress as well as overall stress detection.F3 is also the most effective parameter for negative stress detection.
(ii)
For phoneme /la/,A3,B3, andRa are the most effective parameters for positive as well as overall stress detection.B3 is also the most effective parameter for negative stress detection in this case.
(iii)
For phoneme /u/,A1 andRa are the most effective parameters for positive stress detection;Ra is also the most effective parameter for negative stress detection.F1,A1, andRa are the effective parameters for overall stress detection.
(iv)
For phoneme /o/,dH12 andRa are the most effective parameters for positive, negative and overall stress detection.F2 is also the effective parameters for positive stress detection.
(v)
For vowel independent parameters, pitch and HNR are the most effective parameters for positive stress detection; pitch, autocorrelation, and HNR are helpful in negative stress detection. Pitch and SC are helpful in overall stress detection.
(vi)
On the basis of pattern of values of parameters, phoneme /aa/ affects 7 parameters, phoneme /la/ affects 11 parameters, phoneme /u/ affects 5 parameters and phoneme /o/ affects 15 parameters.
(vii)
So we can say vowel /o/ should be used for stress detection as it is affecting the most number of parameters.
## 2.1. Estimation of Glottal Flow
The goal of this experiment was to estimate the glottal flow or glottal pulses from the voice signal of vowels using IAIF algorithm described in the above section by using MATLAB as well as SIMULINK [16–18]. The foremost prerequisite of this algorithm is to obtain the predictor coefficients from the speech signal. For this, lpc function in MATLAB or lpc model of SIMULINK can be used [13, 14]. The speech signal recordings were available in wav format. The speech signals were converted into data samples by taking the sampling frequency of 10 KHz using MATLAB. The workspace block was used to take those samples in SIMULINK. Digital filter design blocks were used for FIR high pass and inverse filtering. The Autocorrelation LPC blocks were employed to get the predictor coefficients. The digital Integrator block was used for integration. The SIMULINK model of the IAIF algorithm is shown in Figure 7.Figure 7
SIMULINK model of IAIF algorithm.The input speech waveform and output glottal waveform for vowel /a/ are shown in Figure8.Input speech waveform and Output glottal waveform of IAIF algorithm for vowel /a/.
(a)
(b)Using the MATLAB code of IAIF algorithm, glottal pulses of five vowels /a/, /e/, /i/, /o/, /u/ obtained are shown in Figure9.Glottal pulses for five vowels /a/, /e/, /i/, /o/, and /u/, respectively.
(a)
(b)
(c)
(d)
(e)
## 2.2. Comparison of Computed Formant Frequencies
Using the inverse filtering technique the formant parameters can be computed by using two methods. One of them is to find out the peaks of the frequency response of the vocal tract filter and other is to find out the roots of the polynomial equation formed using LPC coefficients of vocal tract filter as explained in [9]. This experimentation was performed to compare the computed formant frequencies by those two methods with the values obtained using phonetic software PRAAT [47].A total of 15 speech signals were analyzed and four formant frequencies were computed for each case. The speech signals used consist of five vowel segments each for male, female, and child and are available in [48]. In 12 of them (80% of the total), formant values obtained using the two methods above were rather near to the values computed using PRAAT software. In case of LPC polynomial root method, some false formants were also noted. So this idea is not so precise and should be used rarely. By applying these methods, we can also compute the 3 dB bandwidth values and amplitude values for each formant [9].Tables1 and 2 are shown for male vowel /i/ and child vowel /a/.Table 1
Comparison of computed formant frequencies for male vowel /i/.
Formant number
By roots
By response
By PRAAT
1
241.3
244.1
233.5
2
2263.6
2270.5
2246.1
3
3194.5
3203.1
3148.6
4
3832.6
3837.9
3828.7Table 2
A comparison of computed formant frequencies for child vowel /a/.
Formant number
By roots
By response
By PRAAT
1
532.5
546.9
549.5
2
1194.1
1196.3
1259.4
3
1807.9
1801.8
1872.6
4
3903.8
3911.1
3893.7
## 2.3. LPC Coefficients versus Vocal Tract Cavities
As we have discussed in the first section that inverse filtering and LPC coefficients approach can be used to model the human vocal tract and is helpful in determining the formant frequencies, so there can be some relationship between the LPC coefficients of the vocal tract and vocal tract cavities. This relationship can be helpful in determining which LPC coefficient of the vocal tract corresponds to which cavity of the vocal tract. It was talked about in the beginning section that each cavity of the vocal tract corresponds to a formant frequency and in the last experiment, we have computed formant frequencies using LPC coefficients of the vocal tract calculated during the final stage of IAIF algorithm. So a relationship can be derived between LPC coefficients and formant frequencies. To derive a relationship 5 speech signals (different persons) were taken. In each signal, each LPC coefficient of the vocal tract was changed (increased and decreased) from 5 to 50%. Corresponding to each change all the formant parameters (frequencies, amplitudes, and bandwidths) were estimated. So for a single signal a total of 24 sets of parameters (both increased and decreased) were tabulated. So for five signals a total of 120(
24
*
5
) sets of parameters were tabulated. A single set of the table for the first signal for a change up to 20% is shown in Table 3. This table determines the change in the formant parameters when the 1st LPC coefficient of the vocal tract is increased. Here bold values determine that the corresponding value is more than its original value when no parameter was changed. The original values of the parameters are depicted in Table 4.Table 3
Change in the formant parameters when a single coefficient value is changed from 5 to 20%.
Parameters/change
5%
10%
15%
20%
F
1 (Hz)
551.0
542.0
532.0
512.7
A
1 (dB)
31.2
29.7
20.7
16.4
B
1 (Hz)
37.4
47.6
138.0
225.0
F
2 (Hz)
913.0
883.8
849
825.2
A
2 (dB)
22.1
19.4
16.9
14.6
B
2 (Hz)
98.7
144.3
196.0
245.2
F
3 (Hz)
1967.0
1958.0
1953.0
1948.2
A
3 (dB)
3.3
2.8
2.4
1.9
B
3 (Hz)
312.0
323.9
335.0
348.1
F
4 (Hz)
3291.0
3281.2
3276.0
3271.5
A
4 (dB)
8.6
7.4
6.4
5.4
B
4 (Hz)
228.0
253.4
277.0
310.4
F
5 (Hz)
3842.0
3847.7
3857.0
3867.2
A
5 (dB)
11.9
11.0
10.2
9.4
B
5 (Hz)
84.6
89.0
93.5
98.2Table 4
Original values.
F
1 (Hz)
556.6
A
1 (dB)
21.1
B
1 (Hz)
109.7
F
2 (Hz)
947.3
A
2 (dB)
24.7
B
2 (Hz)
66.3
F
3 (Hz)
1977.5
A
3 (dB)
3.7
B
3 (Hz)
300.2
F
4 (Hz)
3300.8
A
4 (dB)
9.9
B
4 (Hz)
80.4
F
5 (Hz)
3833.0
A
5 (dB)
12.8
B
5 (Hz)
201.9After analyzing all the data, the following conclusions were derived.(i)
All the formant parameters were altered due to change in a single coefficient. This signifies that all the portions of the vocal tract are associated to each coefficient.
(ii)
Obtained results indicate that these variations follow an individual trend rather than any global trend. So this type of analysis is purely speaker dependent.
(iii)
Yet a similar trend can be imaged in the change of the value of formant frequencies of all the signals.
(iv)
FormantF1 changes (either increase or decrease) the most, if any individual coefficient is changed.
(v)
After that formantF2 andF4 come in 2nd and 3rd place in the list.
(vi)
In 4 out of 5 signals,F3 comes afterF4, and in 1 signalF5 comes afterF4.
(vii)
No such character of pattern was obtained for amplitudes and bandwidths.
(viii)
Nevertheless, in some cases an opposite tendency was seen in bandwidth and amplitude, meaning that if bandwidth was increasing, the amplitude was also decreasing for the whole change.Figure 10 shows diagrammatically the change in formant values along with bandwidths and amplitudes for a sample.Figure 10
Variations in the formant parameters due to change in LPC coefficients for a signal.
## 2.4. Estimation of Vocal Tract Transfer Function for an Individual
According to source-filter theory of speech production, to model the speech production mechanism digitally, we need to consider separate elements of speech production. The speech production system can be modelled with three separate elements: the source, the vocal tract filter, and the radiation effects [17]. The steady state system function of the digital filter is given by the expression:
(21)
H
z
=
S
z
U
z
=
G
1
-
∑
k
=
1
p
a
k
z
-
k
.The primary purpose of this experimentation was to somehow count for a method to forecast or predict the transfer function of vocal tract for an individual. The methodology used was first to calculate the vocal tract predictor coefficients for a signal from the final stage of IAIF algorithm and the gain factorG using lpc function in MATLAB, then by the use of (21) pole zero plot was plotted. As we have discussed before that the LPC order for the vocal tract filter taken is 12 so there will be 12 poles in the transfer function of the vocal tract (Section 1.3).The experimentation was done on two male persons of ages 24 and 26, respectively, by recording their voice samples using Sony IC Recorder (ICD-UX513F) device. Vowels /a/, /e/, and /o/ were taken for the analysis. Each person was asked to pronounce the vowels for at least 3 seconds. Both the persons were asked not to change their day to day activities during the analysis. Total 16 speech samples of each vowel were taken in a single day starting from 7:00 in the morning to 10:00 at night with each sample taken after each hour for each person. So for two persons a total of 96 voice signals of individual vowels were analyzed during two consecutive days. Each vowel signal was pulled out in frames with the help of phonetic software PRAAT [47]. The middle frame was taken for the analysis considering the fact that the speech signal is stationary for a small window of 30–50 msec and has the highest energy at its middle portion [15].For each signal, parameters like pitch, LPC coefficients of the vocal tract, formant frequencies, pole zero plot, and transfer function were estimated. LPC coefficients were estimated using IAIF algorithm. Formants were estimated using the frequency response method of LPC coefficients of the vocal tract. The pitch was estimated using PRAAT. MATLAB was used for pole zero plot for each signal.The following are the observations of this experiment.It was expected that the transfer function for a particular vowel must be unique for a person if calculated at any time of the day. But the experiment showed that the individual shapes of pole zero plots at any time in the day were different from the shapes of pole zero plots calculated at other times. Figure11 shows pole zero plots for first person at four sampling times.Pole zero plots of the vocal tract for vowel /a/ at times 7:00 AM day 1 (upper left side) 10:00 PM day 2 (upper right side), 3:00 PM day 1 (lower left side), and 9:00 PM day 2 (upper right side).
(a)
(b)
(c)
(d)When the mean value of all the coefficients for each individual vowel for each day was taken and pole-zero plot was plotted for those coefficients, then it was observed that the overall shapes of pole-zero plot for each day were approximately the same. Figure12 shows overall pole zero plot for person 2 for vowel /o/ for both days and Figure 13 shows overall pole zero plot for vowel /a/ for person 1 for both days. So it can be said that the average behaviour of the vocal tract throughout the day is the same which corresponds to its resonance or unique behaviour.Mean Pole zero plots for vowel /o/ for person 2 for day 1 (left side) and day 2 (right side).
(a)
(b)Mean Pole zero plots for vowel /e/ for person 1 for day 1 (left side) and day 2 (right side).
(a)
(b)The average pitch value and formant frequencies for person 1 are shown in Table5.Table 5
Average formant frequencies and pitch for person 1 for both days.
F
1 (Hz)
F
2 (Hz)
F
3 (Hz)
F
4 (Hz)
F
5 (Hz)
Pitch (Hz)
/a/
Day 1
405.58
1777.6
2413.9
3463.1
4312.0
109.60
Day 2
398.87
1753.2
2427.6
3355.6
4327.0
106.24
/e/
Day 1
304.56
1982.2
2395.8
3498.2
4101.6
110.12
Day 2
300.60
2062.7
2207.3
3564.1
4207.1
106.18
/o/
Day 1
389.40
811.16
2430.1
2770.5
4260.8
108.58
Day 2
403.07
862.75
2329.2
3185.8
4207.7
104.85The following observations can be concluded with this experiment.(i)
This experiment shows that the human vocal tract system tends to change its shape differently in different times of the day.
(ii)
This variation in the shape of the vocal tract can be due to day to day activities of that person and can be due to intake of food in the body through the throat or due to lack of energy in the body as the day goes on.
(iii)
But in spite of the fluctuations of the vocal tract, the overall shape follows clear uniqueness as we have found out from the pole zero curves.
(iv)
The pole-zero plot obtained after taking the mean values corresponds to the vocal tract transfer function for that individual for some specific vowel.
(v)
This uniqueness in the pole zero plot can act as a unique signature of that person because the shapes of the pole zero plot were different for same vowels in those two persons.
(vi)
So there exists a possibility to find out the biological signature of a person utilizing the vocal system in man.
(vii)
This type of analysis can be helpful in studying the vocal tract system behavior in terms of poles.
## 2.5. Statistical Investigation of Psychological Stress on Human Voice Spectrum
The following work deals with the analysis of speech signal under psychological stress for both positive and negative states of stress. To investigate the influence of stress on speech, acoustic parameters of speech signal were considered. For this type of estimation a suitable database or corpus is required. The most frequently used database among the researchers is the SUSAS (Speech under Simulated and Actual Stress) database of American English which is distributed by Linguistic Data Consortium at the University of Pennsylvania [49]. A German language database called emoDB is also very popular among researchers [50]. A list of existing emotional database is provided in [51, 52]. The database utilized in our analysis was Surrey Audio-Visual Expressed Emotion (SAVEE) database [53, 54]. The database consists of four persons (DC, JE, JK, and KL) of ages 27 to 31 depicting the six basic emotions (anger, disgust, fear, happiness, sadness, and surprise) and the neutral state. The recordings consist of 15 phonetically balanced sentences per emotion (with 15 additional sentences for neutral state) resulting in a corpus of 480 British English utterances. This database is an open source database which can be obtained from the university website on request [55].The database consists of 15 sentences for each speaker and represents all emotions. Out of these 15, 3 sentences are common and rests are emotion specific. These 3 sentences are considered for the evaluation.The three sentences were the following.(i)
She had your dark suit in greasy wash water all year.
(ii)
Do not ask me to carry an oily rag like that.
(iii)
Will you tell me why?There were three sentences for each speaker and each emotion so a total of 84 signals were considered. 11 vowel segments of 40–60 milliseconds duration were extracted from the individual words of these 3 sentences for each speaker and each emotion using phonetic software PRAAT.These segments consist of phonemes /aa/ (resemble vowel /a/ sound, e.g., hate), /la/ (resemble long vowel /a/, e.g., had), /u/ (resemble vowel sound /u/, e.g., book), /o/ (resemble vowel sound /o/, e.g., boat) and /aj/ (resemble vowel /i/ sound, e.g., hide). For each speaker and each emotion, a total of 11 segments were extracted so a total of 308 segments were analyzed.In the analysis the psychological stress is categorized into three major classes. First is neutral state, the second is positive stress, which was taken as a combination of happiness and surprise emotion, and third is negative stress, which was taken as a combination of anger, disgust, fear, and sadness emotions.A number of parameters (about 51 parameters) were judged in the depth psychologies which are grouped under the categories as follows.(i)
Group 1 = pitch and intensity (evaluated for all the sentences).
(ii)
Group 2 =Jitter,Shimmer, andAutocorrelation (evaluated for all the sentences).
(iii)
Group 3 = HNR (harmonic to noise ratio) and NHR (noise to harmonic ratio) (evaluated for all the sentences).
(iv)
Group 4 = energy, time, and frequency parameters (energy entropy (EE), short time energy (STE), zero crossing rate (ZCR), spectral roll off (SR), spectral centroid (SC), spectral flux (SF), (evaluated for all the sentences).
(v)
Group 5 = formant parameters (frequencies (F1, F2,andF3), amplitudes (A1, A2,andA3), and bandwidths (B1, B2,andB3) (evaluated vowels segment wise).
(vi)
Group 6 = glottal pulse timing parameters (NAQ, AQ (milli), CIQ, OQ1, OQ2, Oqa, QOQ, SQ1, and SQ2) (evaluated vowel segment wise).
(vii)
Group 7 = glottal pulse frequency parameters (dH12,PSP,and HRF) (evaluated vowel segment wise).
(viii)
Group 8 = glottal pulse derivative parameters (Ra, Rg, Rk, Rd,andOq) (fvaluated vowel segment wise).
(ix)
Group 9 = first 12 mfcc feature coefficients (evaluated vowel segments wise).Groups 1, 2, and 3 parameters were evaluated using PRAAT software. Groups 4, 5, 9, and 10 were assessed by writing their MATLAB codes. Groups 6, 7, and 8 were evaluated using TKK APARAT software [15].For each signal, all the parameters were evaluated and tabulated emotion wise. After evaluation, they were categorized in terms of positive, negative, and neutral states by combining the appropriate emotion (taking mean values).The outcomes of the analysis were analyzed by two methods. The foremost objective was to appear for the individual pattern in the decreasing order of values of the parameters in case of all the three states and second aim was to work out the most effective parameters among different groups.To count on the most effective parameters under each group, DR (discrimination ratio) criteria was used. Consider(22)
DR
i
=
m
N
i
-
m
S
i
2
d
N
i
2
+
d
S
i
2
,
where m
N is the mean value of that parameter under neutral state and m
S is the mean value of that parameter under stressed state. d
N and d
S are standard deviations for those parameters.DR was calculated for positive, negative, and overall stress (by taking averages of DR of both positive and negative). Higher the DR factor more effective is the parameter.Let us consider the DR calculation for first formantF1 for vowel /aa/ for speaker DC. By taking the mean values of first formantF1 for all frames following data was obtained:
(23)
m
N
F
1
=
656.74
Hz
,
m
P
F
1
=
650.64
Hz
,
m
Neg
(
F
1
)
=
639.65
Hz
,
d
N
(
F
1
)
=
37.979
Hz
,
d
P
F
1
=
18.989
Hz
,
d
Neg
F
1
=
13.81
Hz
.Using the above data DR for formantF1 for positive and negative stressed states can be calculated using (22):
(24)
DR
(
F
1
)
(
Positive
)
=
656.74
-
650.64
2
37.97
9
2
+
18.98
9
2
=
0.0206
.
Similarly,
(25)
DR
F
1
Negative
=
656.74
-
639.65
2
37.97
9
2
+
13.8
1
2
=
0.1787
.Overall DR can be calculated by taking the mean values of DR (positive) and DR (negative).Tables6 and 7 show the DR evaluation table for some parameters of vowels /aa/ for speaker JE for positive stress and for vowel /la/ for speaker JK for negative stress, respectively.Table 6
DR evaluation table for vowel /aa/ for speaker JE.
Parameter
Mean (N)
Deviation (N)
Mean (P)
Deviation (P)
DR (Pos)
F
1
615.24
41.43
610.35
34.52
0.01
F
2
1154.79
58.70
1182.86
44.89
0.14
F
3
2700.20
75.96
2967.53
84.59
5.53
A
1
32.26
1.09
22.43
3.05
9.24
A
2
13.81
1.80
16.67
3.15
0.62
A
3
10.63
0.70
7.65
0.65
9.65
B
1
71.70
8.72
173.04
136.03
0.55
B
2
290.47
10.67
183.69
44.65
5.41
B
3
105.75
32.67
143.75
30.42
0.72
NAQ
0.09
0.05
0.13
0.03
0.53
AQ (milli)
0.87
0.14
0.56
0.07
4.20
CIQ
0.16
0.10
0.27
0.09
0.73
OQ1
0.44
0.29
0.59
0.11
0.25
OQ2
0.39
0.29
0.49
0.13
0.11Table 7
DR evaluation table for vowel /la/ for speaker JK.
Parameter
Mean (N)
Deviation (N)
Mean (Neg)
Deviation (Neg)
DR (Neg)
F
1
755.21
25.06
802.82
54.16
0.64
F
2
1453.45
28.61
1515.30
76.87
0.57
F
3
2651.37
119.70
2606.61
173.18
0.05
A
1
20.15
2.18
19.09
6.11
0.03
A
2
14.79
4.04
15.59
4.27
0.02
A
3
15.74
2.52
10.62
2.76
1.88
B
1
136.33
30.70
208.07
125.56
0.31
B
2
209.80
107.89
185.96
84.99
0.03
B
3
141.36
39.45
216.01
85.44
0.63
NAQ
0.08
0.01
0.08
0.04
0.01
AQ (milli)
0.64
0.03
0.52
0.20
0.33
CIQ
0.12
0.02
0.14
0.08
0.06
OQ1
0.55
0.08
0.48
0.11
0.30
OQ2
0.28
0.06
0.35
0.10
0.31The results from the pattern in the order of stress state of the parameters are as follows.(i)
8 parameters out of 13 parameters (61.5%), which were evaluated for all the sentences, show a unique rule for all the speakers so they can be helpful in stress detection. Parameters such as pitch, intensity, shimmer, jitter, EE, ZC, SR, and SC show these results. For pitch and intensity, distribution functions were plotted. Figure14 shows the distribution function of pitch values in case of speaker DC. In 6 out of those 8 parameters, positive stressed signal shows the highest value, followed by negative stress and neutral case.
(ii)
27 out of 38 parameters (71%), which were evaluated for vowel segments, show unique patterns of the values for all the stress states in 3 out of 4 speakers. These 27 parameters were showing results for 37% of the total vowel signals that were analyzed. Out of these parameters, parameterR
a was showing positive results for all the analyzed vowels with positive stressed data having the highest value, followed by negative and neutral data.
(iii)
In nut shell, 35 parameters out of 51 parameters are affected due to stress and are showing a singular practice of values in the stressed state for 32% of the examined data.Figure 14
Distribution function for Pitch values for speaker DC.Results according to the DR criteria were evaluated group wise and are shown in Tables8 and 9.Table 8
Highest DR values for group numbers 1 to 4.
Group number
Positive effective
Negative effective
Overall
1
Pitch
Pitch
Pitch
2
—
Autocorrelation
—
3
HNR
HNR
—
4
—
—
SCTable 9
Highest DR values for group numbers 5 To 9. (P: positive; N: negative; O: overall).
(a)
Group name
/aa/
/la/
P
N
O
P
N
O
Formant freq.
F
3
F
3
F
3
—
—
—
Formant amp.
—
—
—
A
3
—
A
3
Formant BWs
—
—
—
B
3
B
3
B
3
Group 6
AQ
—
AQ
—
—
—
Group 7
—
—
—
—
—
—
Group 8
Ra
—
Ra
Ra
—
Ra
Group 9
—
—
—
—
—
—
(b)
Group name
/u/
/o/
P
N
O
P
N
O
Formant freq.
—
—
F
1
F
2
—
—
Formant amp.
A
1
—
A
1
—
—
—
Formant BWs
—
—
—
—
—
—
Group 6
—
—
—
—
—
—
Group 7
—
—
—
dH
dH
dH
Group 8
Ra
Ra
Ra
Ra
Ra
Ra
Group 9
—
—
—
—
—
—
### 2.5.1. Final Results
(i)
For phoneme /aa/,F3,AQ, andRa are the most effective parameters for positive stress as well as overall stress detection.F3 is also the most effective parameter for negative stress detection.
(ii)
For phoneme /la/,A3,B3, andRa are the most effective parameters for positive as well as overall stress detection.B3 is also the most effective parameter for negative stress detection in this case.
(iii)
For phoneme /u/,A1 andRa are the most effective parameters for positive stress detection;Ra is also the most effective parameter for negative stress detection.F1,A1, andRa are the effective parameters for overall stress detection.
(iv)
For phoneme /o/,dH12 andRa are the most effective parameters for positive, negative and overall stress detection.F2 is also the effective parameters for positive stress detection.
(v)
For vowel independent parameters, pitch and HNR are the most effective parameters for positive stress detection; pitch, autocorrelation, and HNR are helpful in negative stress detection. Pitch and SC are helpful in overall stress detection.
(vi)
On the basis of pattern of values of parameters, phoneme /aa/ affects 7 parameters, phoneme /la/ affects 11 parameters, phoneme /u/ affects 5 parameters and phoneme /o/ affects 15 parameters.
(vii)
So we can say vowel /o/ should be used for stress detection as it is affecting the most number of parameters.
## 2.5.1. Final Results
(i)
For phoneme /aa/,F3,AQ, andRa are the most effective parameters for positive stress as well as overall stress detection.F3 is also the most effective parameter for negative stress detection.
(ii)
For phoneme /la/,A3,B3, andRa are the most effective parameters for positive as well as overall stress detection.B3 is also the most effective parameter for negative stress detection in this case.
(iii)
For phoneme /u/,A1 andRa are the most effective parameters for positive stress detection;Ra is also the most effective parameter for negative stress detection.F1,A1, andRa are the effective parameters for overall stress detection.
(iv)
For phoneme /o/,dH12 andRa are the most effective parameters for positive, negative and overall stress detection.F2 is also the effective parameters for positive stress detection.
(v)
For vowel independent parameters, pitch and HNR are the most effective parameters for positive stress detection; pitch, autocorrelation, and HNR are helpful in negative stress detection. Pitch and SC are helpful in overall stress detection.
(vi)
On the basis of pattern of values of parameters, phoneme /aa/ affects 7 parameters, phoneme /la/ affects 11 parameters, phoneme /u/ affects 5 parameters and phoneme /o/ affects 15 parameters.
(vii)
So we can say vowel /o/ should be used for stress detection as it is affecting the most number of parameters.
## 3. Conclusions
In this paper, we have presented the speech signal analysis using inverse filtering and LPC coefficient approach to estimate some of the important speech parameters like glottal pulse estimation, glottal pulse timing and amplitude parameters, glottal pulse derivative parameters, voice parameters based on time, frequency and energy, MFC coefficients for feature extraction, pitch, intensity, and pole zero plot. The algorithms and methods used for the estimation were studied and discussed in the paper. The formant parameters were compared with the same parameters obtained using phonetic software PRAAT. An analysis was also performed to find out the relationship between the coefficients of the vocal tract and cavities of the vocal tract. Obtained results show that all the coefficients are related to the human vocal tract and no direct correspondence could be held. However, the amount of change in the formant frequencies follow a trend ofF
1 > F
2 > F
4 > F
3 > F
5 in most of the cases. Besides this a pole zero evaluation of vocal tract system was discussed to determine the vocal tract transfer function for individuals which shows that the human vocal tract system tends to change its shape in different times of the day for same vowel pronunciations. But the average pole zero plot evaluated follow a unique pattern. This indicates that the ordinary behaviour of human vocal tract system exhibits unique frequency response or resonance. This work can be helpful in simplification of voice related problems in terms of poles and zeros which can be extended further for studying unique voice features in every individual. At last, a speech signal analysis for stress detection was done using SAVEE database. A total of 51 parameters were evaluated and compared for positive stress, negative stress, and neutral state. The features summarized in Tables 8 and 9 have been proven to be the most effective parameters for stress detection among all speakers.In future, we plan to create our own database, adding other types of stress emotions. We aim to compare the speech features for same emotion for different languages to check whether the emotional content in speech is language dependent or not. Our goal is to detect similar effects with speech with other biological signals like ECG and EEG to identify the correlation among them, which can be helpful in early detection or prevention of many diseases.
---
*Source: 290147-2014-11-18.xml* | 2014 |
# Research on Radiation Characteristic of Plasma Antenna through FDTD Method
**Authors:** Jianming Zhou; Jingjing Fang; Qiuyuan Lu; Fan Liu
**Journal:** The Scientific World Journal
(2014)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2014/290148
---
## Abstract
The radiation characteristic of plasma antenna is investigated by using the finite-difference time-domain (FDTD) approach in this paper. Through using FDTD method, we study the propagation of electromagnetic wave in free space in stretched coordinate. And the iterative equations of Maxwell equation are derived. In order to validate the correctness of this method, we simulate the process of electromagnetic wave propagating in free space. Results show that electromagnetic wave spreads out around the signal source and can be absorbed by the perfectly matched layer (PML). Otherwise, we study the propagation of electromagnetic wave in plasma by using the Boltzmann-Maxwell theory. In order to verify this theory, the whole process of electromagnetic wave propagating in plasma under one-dimension case is simulated. Results show that Boltzmann-Maxwell theory can be used to explain the phenomenon of electromagnetic wave propagating in plasma. Finally, the two-dimensional simulation model of plasma antenna is established under the cylindrical coordinate. And the near-field and far-field radiation pattern of plasma antenna are obtained. The experiments show that the variation of electron density can introduce the change of radiation characteristic.
---
## Body
## 1. Introduction
Plasma antenna usually adopts the partially or fully ionized gas as conducting medium instead of metallic materials. Compared with conventional metallic antenna, plasma antenna has many peculiar properties. For instance, it can be rapidly switched on or off; this characteristic makes plasma antenna suitable for stealth applications for military communication fields. Also, if this kind of antenna is used as the antenna array, the coupling between the elements of antenna array is small. In particular, radiation pattern of plasma antenna can be reconfigured through changing the frequency and intensity of pump signal, gas pressure, vessel dimensions, and so on. Because of the advantages above, many researchers and scientific utilities show great interests in it.At present, studies concerning plasma antenna may have three aspects: experimental investigation, theory derivation, and numerical calculation. Theodore Anderson together with Igor Alexeff [1] designed a smart plasma antenna and implemented a wide range of plasma antenna experiments. Their studies had proved that plasma antenna has reconfigurable characteristics. Kumar and Bora [2] designed a 30 cm plasma antenna and proved that the frequency and radiation pattern can be altered with the frequency and power of the pump signal. Yang et al. [3] and Zhao [4] obtained the dispersion relationships of the surface wave along the plasma column by using theoretical derivation approach. Wu et al. [5] and Xia and Yin [6] studied the radiation characteristic of plasma antenna through theoretical derivation. Dai et al. [7] calculated the coefficients of reflection and transmission of electromagnetic wave in plasma by using FDTD numerical method. Liang [8] simulated the radiation characteristic of cylindrical monopolar antenna by using FDTD method. Russo et al. [9–13] established one-dimensional and two-dimensional self-consistent model of plasma antenna and validated the correctness of the model through using FDTD method.From the investigations and research mentioned above, we can draw a conclusion that plasma is so complicated that one cannot find the real issues of the problem only through experimental approach. It is necessary to establish a rigorous mathematical model to investigate the radiation characteristic of plasma antenna. The numerical calculation approach applied in this paper is to study the radiation characteristic of plasma antenna.
## 2. Propagation of Electromagnetic Wave in Free Space and Plasma
There are two key issues to deal with in this research: one is the propagation of electromagnetic wave in free space and the other one is the propagation of electromagnetic wave in the plasma. Only these two problems are solved; then the investigation of radiation characteristic of plasma antenna can be further conducted.
### 2.1. Propagation of Electromagnetic Wave in Free Space
In order to apply FDTD method to simulate the propagation of electromagnetic wave in free space in cylindrical coordinate, the stretched coordinate is selected. So, the modified Maxwell equations can be expressed as below:(1)∇s×H=jωεE,(2)∇s×E=-jωμH,
where E represents electric field strength vector in volts per meter. H represents magnetic field strength vector in amperes per meter. ε denotes the permittivity in farad per meter. μ denotes the permeability in henry per meter. ω represents the angular frequency of incidence signal in radian per second.In stretched coordinate [14], we define
(3)sr=1+σrjωε0,sz=1+σzjωε0,
where sr and sz are coordinate stretched factor
(4)R⟶∫0rsr(r′)dr′={r,r′<r0r+1jωε0∫r0rσr(r′)dr′,r′<r0,(5)Z⟶∫0zsz(z′)dz′={z,z′<z0z+1jωε0∫z0zσz(z′)dz′,z′<z0,
where r0 and z0 represent the distance between the signal source and inner boundary of PML along r direction and z direction, respectively.Maxwell curl equation (1), then, can be represented by these three scale equations in cylindrical coordinate system as (6a)–(6c):(6a)jωε0Er=1R∂Hz∂φ-∂Hφ∂Z,(6b)jωε0Eφ=∂Hr∂Z-∂Hz∂R,(6c)jωε0Ez=1R∂(RHφ)∂R-1R∂Hr∂φ.From (4) and (5), (7) can be obtained as follows:
(7)∂∂R=1sr∂∂r,∂∂Z=1sz∂∂z.
Substituting (7) into (6a)–(6c) yields(8a)jωε0Er=1R∂Hz∂φ-1sz∂Hφ∂z,(8b)jωε0Eφ=1sz∂Hr∂z-1sr∂Hz∂r,(8c)jωε0Ez=1R1sr∂(RHφ)∂r-1R∂Hr∂φ.After multiplying sz·R/r, sz·sr, sr·R/r, respectively, (8a), (8b), and (8c) can be expressed as below:(9a)jωε0szRrEr=1r∂(szHz)∂φ-Rr∂Hφ∂z,(9b)jωε0szsrEφ=∂(srHr)∂z-∂(szHz)∂r,(9c)jωε0srRrEz=1r∂(RHφ)∂r-1r∂(srHr)∂φ.Substituting szHz=Hz′, srHr=Hr′, RHφ/r=Hφ′, REφ/r=Eφ′, szEz=Ez′, and srEr=Er′ into (9a)–(9c), (9a)–(9c) can be written as(10a)jωε0szsrRrEr′=1r∂Hz′∂φ-∂Hφ′∂z,(10b)jωε0szsrrREφ′=∂(Hr′)∂z-∂(Hz′)∂r,(10c)jωε0srRszrEz′=1r∂(rHφ′)∂r-1r∂(Hr′)∂φ.Namely,
(11)[1r∂Hz′∂φ-∂Hφ′∂z∂(Hr′)∂z-∂(Hz′)∂r1r∂(rHφ′)∂r-1r∂(Hr′)∂φ]=jωε0εrε-[Er′Eφ′Ez′].
Equation (11) can be shortly expressed as
(12)∇×H=jωε0εrε-E.According to the duality theorem, Maxwell curl equation (2) can be represented by equation
(13)[1r∂Ez′∂φ-∂Eφ′∂z∂(Er′)∂z-∂(Ez′)∂r1r∂(rEφ′)∂r-1r∂(Er′)∂φ]=-jωμ0μrμ-[Hr′Hφ′Hz′].
Equation (13) can be expressed as
(14)∇×E=-jωμ0μrμ-H,
where
(15)ε-=μ-=[szRsrr000szsrrR000srRszr].AS the plasma antenna is rotationally symmetric. Thus, it is suitable to study this problem in cylindrical coordinate. The TM modes are excited. Maxwell equations involve three components:Er, Ez, and Hφ. Thus, the Maxwell equation of electromagnetic wave propagating in free space will be reduced as(16a)-jωμ0szsrrRHφ′=∂(Er′)∂z-∂(Ez′)∂r,(16b)jωε0szsrRrEr′=-∂Hφ′∂z,(16c)jωε0srRszrEz′=1r∂(rHφ′)∂r.Applying the auxiliary differential equation method (ADE) [15], the iterative equations [16] of (16a)–(16c) are derived as follows:(17a)Bφ∣i,jn+1=(2ε0-dtσr2ε0+dtσr)Bφ∣i,jn+(2ε0dt2ε0+dtσr)[Ez∣i+1/2,jn+1/2-Ez∣i-1/2,jn+1/2dr-Er∣i,j+1/2n+1/2-Er∣i,j-1/2n+1/2dz],(17b)Hφ∣i,jn+1=(2ε0-σzdt2ε0+σzdt)Hφ∣i,jn+1+2ε0R(2ε0+σzdt)μ0μrr(Bφ∣i,jn+1-Bφ|i,jn),(18a)Dr∣i+1/2,j,kn+1=(2ε0-σzdt2ε0+σzdt)Dr∣i+1/2,j,kn+(2ε0dt2ε0+σzdt)×{1ri+1/2Hz∣i+1/2,j+1/2,kn+1/2-Hz∣i+1/2,j-1/2.kn+1/2dφ-Hφ∣i+1/2,j,k+1/2n+1/2-Hφ∣i+1/2,j·k-1/2n+1/2dz},(18b)Er∣i+1/2,j,kn+1=Er∣i+1/2,j,kn+rε0εrR(2ε0+dtσr2ε0Dr∣i+1/2,j,kn+1-2ε0-dtσr2ε0Dr∣i+1/2,j,kn),(19a)Dz∣i,j,k+1/2n+1=(2ε0-σrdt2ε0+σrdt)Dz∣i,j,k+1/2n+(2ε0dt2ε0+σrdt)×{(12r+1dr)Hφ∣i+1/2,j,k+1/2n+1/2+(12r-1dr)Hφ∣i-1/2,j,k+1/2n+1/2,},(19b)Ez∣i,j,k+1/2n+1=Ez∣i,j,k+1/2n+rε0εrR(2ε0+dtσz2ε0Dz∣i,j,k+1/2n+1-2ε0-dtσz2ε0Dz∣i,j,k+1/2n).By using these six iterative equations, we can calculate the value of electromagnetic field in PML. Also, we can use these iterative equations to calculate the value of electromagnetic field in free space by setting the electric conductivity atσz=0, σr=0, and εr=1.In order to validate the correctness of the theory above, we apply this approach in the propagation of electromagnetic field in free space. The two-dimensional FDTD computational space is shown as in Figure1.Figure 1
Two-dimensional FDTD computational space.Figure1 shows that half of the free space is simulated. The computational space is composed of 50 × 100 Yee sells. The signal source is sinusoidal signal with the frequency of 20 GHz. The spatial step is Δr=Δz=0.003m. The temporal step is Δt=2.123×10-12 s. The total number of time steps is 500. The number of PML cells is 9. The propagating process of electric field Er in free space is shown as in Figure 2.Figure 2
Propagating the electric fieldEr in free space.In Figure2, it is shown that the electric field Er spreads out around the signal source. When the electric field arrives at the interface between PML and free space, it can be absorbed by the PML. So, the theory put forward above is correct.
## 2.1. Propagation of Electromagnetic Wave in Free Space
In order to apply FDTD method to simulate the propagation of electromagnetic wave in free space in cylindrical coordinate, the stretched coordinate is selected. So, the modified Maxwell equations can be expressed as below:(1)∇s×H=jωεE,(2)∇s×E=-jωμH,
where E represents electric field strength vector in volts per meter. H represents magnetic field strength vector in amperes per meter. ε denotes the permittivity in farad per meter. μ denotes the permeability in henry per meter. ω represents the angular frequency of incidence signal in radian per second.In stretched coordinate [14], we define
(3)sr=1+σrjωε0,sz=1+σzjωε0,
where sr and sz are coordinate stretched factor
(4)R⟶∫0rsr(r′)dr′={r,r′<r0r+1jωε0∫r0rσr(r′)dr′,r′<r0,(5)Z⟶∫0zsz(z′)dz′={z,z′<z0z+1jωε0∫z0zσz(z′)dz′,z′<z0,
where r0 and z0 represent the distance between the signal source and inner boundary of PML along r direction and z direction, respectively.Maxwell curl equation (1), then, can be represented by these three scale equations in cylindrical coordinate system as (6a)–(6c):(6a)jωε0Er=1R∂Hz∂φ-∂Hφ∂Z,(6b)jωε0Eφ=∂Hr∂Z-∂Hz∂R,(6c)jωε0Ez=1R∂(RHφ)∂R-1R∂Hr∂φ.From (4) and (5), (7) can be obtained as follows:
(7)∂∂R=1sr∂∂r,∂∂Z=1sz∂∂z.
Substituting (7) into (6a)–(6c) yields(8a)jωε0Er=1R∂Hz∂φ-1sz∂Hφ∂z,(8b)jωε0Eφ=1sz∂Hr∂z-1sr∂Hz∂r,(8c)jωε0Ez=1R1sr∂(RHφ)∂r-1R∂Hr∂φ.After multiplying sz·R/r, sz·sr, sr·R/r, respectively, (8a), (8b), and (8c) can be expressed as below:(9a)jωε0szRrEr=1r∂(szHz)∂φ-Rr∂Hφ∂z,(9b)jωε0szsrEφ=∂(srHr)∂z-∂(szHz)∂r,(9c)jωε0srRrEz=1r∂(RHφ)∂r-1r∂(srHr)∂φ.Substituting szHz=Hz′, srHr=Hr′, RHφ/r=Hφ′, REφ/r=Eφ′, szEz=Ez′, and srEr=Er′ into (9a)–(9c), (9a)–(9c) can be written as(10a)jωε0szsrRrEr′=1r∂Hz′∂φ-∂Hφ′∂z,(10b)jωε0szsrrREφ′=∂(Hr′)∂z-∂(Hz′)∂r,(10c)jωε0srRszrEz′=1r∂(rHφ′)∂r-1r∂(Hr′)∂φ.Namely,
(11)[1r∂Hz′∂φ-∂Hφ′∂z∂(Hr′)∂z-∂(Hz′)∂r1r∂(rHφ′)∂r-1r∂(Hr′)∂φ]=jωε0εrε-[Er′Eφ′Ez′].
Equation (11) can be shortly expressed as
(12)∇×H=jωε0εrε-E.According to the duality theorem, Maxwell curl equation (2) can be represented by equation
(13)[1r∂Ez′∂φ-∂Eφ′∂z∂(Er′)∂z-∂(Ez′)∂r1r∂(rEφ′)∂r-1r∂(Er′)∂φ]=-jωμ0μrμ-[Hr′Hφ′Hz′].
Equation (13) can be expressed as
(14)∇×E=-jωμ0μrμ-H,
where
(15)ε-=μ-=[szRsrr000szsrrR000srRszr].AS the plasma antenna is rotationally symmetric. Thus, it is suitable to study this problem in cylindrical coordinate. The TM modes are excited. Maxwell equations involve three components:Er, Ez, and Hφ. Thus, the Maxwell equation of electromagnetic wave propagating in free space will be reduced as(16a)-jωμ0szsrrRHφ′=∂(Er′)∂z-∂(Ez′)∂r,(16b)jωε0szsrRrEr′=-∂Hφ′∂z,(16c)jωε0srRszrEz′=1r∂(rHφ′)∂r.Applying the auxiliary differential equation method (ADE) [15], the iterative equations [16] of (16a)–(16c) are derived as follows:(17a)Bφ∣i,jn+1=(2ε0-dtσr2ε0+dtσr)Bφ∣i,jn+(2ε0dt2ε0+dtσr)[Ez∣i+1/2,jn+1/2-Ez∣i-1/2,jn+1/2dr-Er∣i,j+1/2n+1/2-Er∣i,j-1/2n+1/2dz],(17b)Hφ∣i,jn+1=(2ε0-σzdt2ε0+σzdt)Hφ∣i,jn+1+2ε0R(2ε0+σzdt)μ0μrr(Bφ∣i,jn+1-Bφ|i,jn),(18a)Dr∣i+1/2,j,kn+1=(2ε0-σzdt2ε0+σzdt)Dr∣i+1/2,j,kn+(2ε0dt2ε0+σzdt)×{1ri+1/2Hz∣i+1/2,j+1/2,kn+1/2-Hz∣i+1/2,j-1/2.kn+1/2dφ-Hφ∣i+1/2,j,k+1/2n+1/2-Hφ∣i+1/2,j·k-1/2n+1/2dz},(18b)Er∣i+1/2,j,kn+1=Er∣i+1/2,j,kn+rε0εrR(2ε0+dtσr2ε0Dr∣i+1/2,j,kn+1-2ε0-dtσr2ε0Dr∣i+1/2,j,kn),(19a)Dz∣i,j,k+1/2n+1=(2ε0-σrdt2ε0+σrdt)Dz∣i,j,k+1/2n+(2ε0dt2ε0+σrdt)×{(12r+1dr)Hφ∣i+1/2,j,k+1/2n+1/2+(12r-1dr)Hφ∣i-1/2,j,k+1/2n+1/2,},(19b)Ez∣i,j,k+1/2n+1=Ez∣i,j,k+1/2n+rε0εrR(2ε0+dtσz2ε0Dz∣i,j,k+1/2n+1-2ε0-dtσz2ε0Dz∣i,j,k+1/2n).By using these six iterative equations, we can calculate the value of electromagnetic field in PML. Also, we can use these iterative equations to calculate the value of electromagnetic field in free space by setting the electric conductivity atσz=0, σr=0, and εr=1.In order to validate the correctness of the theory above, we apply this approach in the propagation of electromagnetic field in free space. The two-dimensional FDTD computational space is shown as in Figure1.Figure 1
Two-dimensional FDTD computational space.Figure1 shows that half of the free space is simulated. The computational space is composed of 50 × 100 Yee sells. The signal source is sinusoidal signal with the frequency of 20 GHz. The spatial step is Δr=Δz=0.003m. The temporal step is Δt=2.123×10-12 s. The total number of time steps is 500. The number of PML cells is 9. The propagating process of electric field Er in free space is shown as in Figure 2.Figure 2
Propagating the electric fieldEr in free space.In Figure2, it is shown that the electric field Er spreads out around the signal source. When the electric field arrives at the interface between PML and free space, it can be absorbed by the PML. So, the theory put forward above is correct.
## 3. Radiation Characteristic of Plasma Antenna
In this part, the radiation characteristic of plasma antenna under two-dimensional case is investigated. The geometry [17, 18] of plasma antenna is shown in Figure 3.Figure 3
Two-dimension geometry of plasma antenna.As Figure3 illustrated, V represents free space around the plasma antenna. The plasma antenna is fed by coaxial cable. The parameters a and b are inner and outer radius of coaxial cable with the ratio of b/a=2.3 to ensure that the characteristic impedance is 50 Ω. l represents the length of plasma antenna tube. By using the FDTD approach together with the theory in Section 2, we study the near-field and far-field radiation pattern of plasma antenna.
### 3.1. Near-Field Radiation Pattern
If we want to obtain the unique solution to Maxwell equation withinV, we must initialize the electromagnetic fields E and H within V at time t=0. Furthermore, the values n×E and n×H must be initialized also on the boundary surface for all time 0<t<t0. The gauss pulse voltage source is imposed on the cross section A-A′ as shown in Figure 3. The expression of Er is as follows:(20)Eri(t)=Vi(t)ln(b/a)rr^.This is the only electric field at the cross section if we choose2lA>ct0, because the field reflected from the end of the line will not reach the cross section during the observation time. The outer conductor of coaxial cable connects with ground. The inner conductor, outer conductor, and ground are considered as perfect electric conductor (PEC). So the value of n×E is zero on the surface of the coaxial cable and ground during the observation process.The gauss pulse voltage source is initialized with the parametersτa=h/c,τp/τa=8×10-2. The parameters describing the plasma antenna are as follows: the length l=50 cm and the radius of the conductors of the coaxial line a=1 cm and b=2.3 cm. The spatial step is Δr=Δz=(b-a)/4. The temporal step can be calculated according to the expression Δt=1/c*1/dr2+1/dz2. Usually, the time step is chosen to be 20% smaller than the courant stability limit. The parameters of plasma are initialized: electron density is ne=1×1017m-3 and collision frequency is νc=1.5×108Hz. From the equation ωp=e2ne/mε0, the angular frequency of plasma can be obtained as ωp=1.7815×1010 rad/s. Through FDTD method, the near-field of plasma antenna corresponding to the iterative numbers is 500, 1000, and 1500. The corresponding results are shown in Figures 4, 5, and 6.Figure 4
Near-field of plasma antenna with iterative number 500.Figure 5
Near-field of plasma antenna with iterative number 1000.Figure 6
Near-field of plasma antenna with iterative number 1500.Figure4 ~ Figure 4 are the near-field of plasma antenna with different iterative number. Figure 6 shows the part of the power radiated to the free space and part of power reflected back to the coaxial cable when electromagnetic wave propagates from the bottom to the joint of coaxial cable and plasma antenna. Figure 5 shows that when the iterative number is 1000, the electromagnetic wave continues to spread out and has not reached the top of the plasma antenna. At the same time, the reverse electric field in coaxial cable will continue to propagate in signal source direction. When the iterative number comes to 1500, the electromagnetic wave will arrive at the top of the plasma antenna. Figure 6 shows that reflection has happened and the second radiation is formed.
### 3.2. Far-Field Radiation Pattern
The finite-difference time-domain (FDTD) method [19, 20] is used to compute electric and magnetic field within a finite space around an electromagnetic object. Namely, only the value of near magnetic field can be obtained. Otherwise, we also care about the far-zone electromagnetic field of plasma antenna. The far-zone electromagnetic field can be computed from the near-field FDTD data through a near-field to far-field (NF-FF) transformation technique.The far-field value is calculated in cylindrical coordinate. The schematic map of NF-FF is shown as in Figure7.Figure 7
Schematic map of NF-FF transformation.The vectorr denotes the position of the observation point (r,θ); the vector r′ denotes the position of source. The value of the source can be calculated through FDTD method.Through using the Green function under two-dimension conditions, the expressions of far-zone electromagnetic field in cylindrical coordinate are(21)Ez=exp(-jkr)22jπkr(jk)(-Zfz+fmφ),Hz=exp(-jkr)22jπkr(-jk)(fφ+1Zfmz),
where fζ(φ), fmζ(φ)(ζ=z,φ) are current moment and magnetic moment, respectively:
(22)fζ(φ)=∫lJ(r′)exp(jk·r′)dl′,fmζ(φ)=∫lJm(r′)exp(jk·r′)dl′.
Mapping from spherical coordinate to cylindrical coordinate, we have
(23)k·r′=ksin(θ)·r′+kcos(θ)·z.
Substituting (23) into (22), (22) can be rewritten as
(24)fζ(φ)=∫lJζ(r′)exp(j(ksin(θ)·r′dsadsadsadsssffk+kcos(θ)·zr′))dl′,fmζ(φ)=∫lJmζ(r′)exp(j(ksin(θ)·r′dasdsadasdssssfdsf+kcos(θ)·zksin(θ)·r′))dl′.
Substituting (24) into (21), the far-field electromagnetic field can be obtained.Through the NF-FF method, the affection of electron density to the radiation characteristic of plasma antenna is studied. We initialize the typical parameters of plasma as below.Collision frequency isνc=1.5×108Hz, and the electron density is set as ne=1×1016m-3, ne=1×1017m-3, and ne=1×1018m-3, respectively. And the far-field of plasma antenna under different electron density is shown as in Figure 8.Figure 8
Far-field of plasma antenna under different electron density.In Figure8, it is shown that, with the variation of electron density of plasma antenna, the profile of far-field radiation pattern will change. The reason is that when the electromagnetic wave arrives at the plasma region, the interaction between electromagnetic wave and plasma changes the surface current distribution of plasma antenna, as it is known that the radiation pattern is determined by the surface current distribution of antenna. Thus, the far-field radiation pattern of plasma antenna will be changed.
## 3.1. Near-Field Radiation Pattern
If we want to obtain the unique solution to Maxwell equation withinV, we must initialize the electromagnetic fields E and H within V at time t=0. Furthermore, the values n×E and n×H must be initialized also on the boundary surface for all time 0<t<t0. The gauss pulse voltage source is imposed on the cross section A-A′ as shown in Figure 3. The expression of Er is as follows:(20)Eri(t)=Vi(t)ln(b/a)rr^.This is the only electric field at the cross section if we choose2lA>ct0, because the field reflected from the end of the line will not reach the cross section during the observation time. The outer conductor of coaxial cable connects with ground. The inner conductor, outer conductor, and ground are considered as perfect electric conductor (PEC). So the value of n×E is zero on the surface of the coaxial cable and ground during the observation process.The gauss pulse voltage source is initialized with the parametersτa=h/c,τp/τa=8×10-2. The parameters describing the plasma antenna are as follows: the length l=50 cm and the radius of the conductors of the coaxial line a=1 cm and b=2.3 cm. The spatial step is Δr=Δz=(b-a)/4. The temporal step can be calculated according to the expression Δt=1/c*1/dr2+1/dz2. Usually, the time step is chosen to be 20% smaller than the courant stability limit. The parameters of plasma are initialized: electron density is ne=1×1017m-3 and collision frequency is νc=1.5×108Hz. From the equation ωp=e2ne/mε0, the angular frequency of plasma can be obtained as ωp=1.7815×1010 rad/s. Through FDTD method, the near-field of plasma antenna corresponding to the iterative numbers is 500, 1000, and 1500. The corresponding results are shown in Figures 4, 5, and 6.Figure 4
Near-field of plasma antenna with iterative number 500.Figure 5
Near-field of plasma antenna with iterative number 1000.Figure 6
Near-field of plasma antenna with iterative number 1500.Figure4 ~ Figure 4 are the near-field of plasma antenna with different iterative number. Figure 6 shows the part of the power radiated to the free space and part of power reflected back to the coaxial cable when electromagnetic wave propagates from the bottom to the joint of coaxial cable and plasma antenna. Figure 5 shows that when the iterative number is 1000, the electromagnetic wave continues to spread out and has not reached the top of the plasma antenna. At the same time, the reverse electric field in coaxial cable will continue to propagate in signal source direction. When the iterative number comes to 1500, the electromagnetic wave will arrive at the top of the plasma antenna. Figure 6 shows that reflection has happened and the second radiation is formed.
## 3.2. Far-Field Radiation Pattern
The finite-difference time-domain (FDTD) method [19, 20] is used to compute electric and magnetic field within a finite space around an electromagnetic object. Namely, only the value of near magnetic field can be obtained. Otherwise, we also care about the far-zone electromagnetic field of plasma antenna. The far-zone electromagnetic field can be computed from the near-field FDTD data through a near-field to far-field (NF-FF) transformation technique.The far-field value is calculated in cylindrical coordinate. The schematic map of NF-FF is shown as in Figure7.Figure 7
Schematic map of NF-FF transformation.The vectorr denotes the position of the observation point (r,θ); the vector r′ denotes the position of source. The value of the source can be calculated through FDTD method.Through using the Green function under two-dimension conditions, the expressions of far-zone electromagnetic field in cylindrical coordinate are(21)Ez=exp(-jkr)22jπkr(jk)(-Zfz+fmφ),Hz=exp(-jkr)22jπkr(-jk)(fφ+1Zfmz),
where fζ(φ), fmζ(φ)(ζ=z,φ) are current moment and magnetic moment, respectively:
(22)fζ(φ)=∫lJ(r′)exp(jk·r′)dl′,fmζ(φ)=∫lJm(r′)exp(jk·r′)dl′.
Mapping from spherical coordinate to cylindrical coordinate, we have
(23)k·r′=ksin(θ)·r′+kcos(θ)·z.
Substituting (23) into (22), (22) can be rewritten as
(24)fζ(φ)=∫lJζ(r′)exp(j(ksin(θ)·r′dsadsadsadsssffk+kcos(θ)·zr′))dl′,fmζ(φ)=∫lJmζ(r′)exp(j(ksin(θ)·r′dasdsadasdssssfdsf+kcos(θ)·zksin(θ)·r′))dl′.
Substituting (24) into (21), the far-field electromagnetic field can be obtained.Through the NF-FF method, the affection of electron density to the radiation characteristic of plasma antenna is studied. We initialize the typical parameters of plasma as below.Collision frequency isνc=1.5×108Hz, and the electron density is set as ne=1×1016m-3, ne=1×1017m-3, and ne=1×1018m-3, respectively. And the far-field of plasma antenna under different electron density is shown as in Figure 8.Figure 8
Far-field of plasma antenna under different electron density.In Figure8, it is shown that, with the variation of electron density of plasma antenna, the profile of far-field radiation pattern will change. The reason is that when the electromagnetic wave arrives at the plasma region, the interaction between electromagnetic wave and plasma changes the surface current distribution of plasma antenna, as it is known that the radiation pattern is determined by the surface current distribution of antenna. Thus, the far-field radiation pattern of plasma antenna will be changed.
## 4. Conclusion
The radiation characteristic of plasma antenna is investigated in this paper. Before studying this problem, two key issues are investigated. Firstly, we study the propagation of electromagnetic wave in free space by using FDTD method. The updating equations of Maxwell equation in stretched coordinate are derived. In order to validate the correctness of the theory, the propagation of electromagnetic wave in free space is calculated. Results show that the theory is correct and can be used in cylindrical coordinate. Secondly, the radiation characteristic of plasma antenna under two-dimension case and the near-field radiation pattern are obtained. Through the NF-FF transformation, we obtain the far-field radiation pattern. From the results, we can conclude that the electron density can influence the radiation characteristic of plasma antenna.
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*Source: 290148-2014-07-09.xml* | 290148-2014-07-09_290148-2014-07-09.md | 27,445 | Research on Radiation Characteristic of Plasma Antenna through FDTD Method | Jianming Zhou; Jingjing Fang; Qiuyuan Lu; Fan Liu | The Scientific World Journal
(2014) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2014/290148 | 290148-2014-07-09.xml | ---
## Abstract
The radiation characteristic of plasma antenna is investigated by using the finite-difference time-domain (FDTD) approach in this paper. Through using FDTD method, we study the propagation of electromagnetic wave in free space in stretched coordinate. And the iterative equations of Maxwell equation are derived. In order to validate the correctness of this method, we simulate the process of electromagnetic wave propagating in free space. Results show that electromagnetic wave spreads out around the signal source and can be absorbed by the perfectly matched layer (PML). Otherwise, we study the propagation of electromagnetic wave in plasma by using the Boltzmann-Maxwell theory. In order to verify this theory, the whole process of electromagnetic wave propagating in plasma under one-dimension case is simulated. Results show that Boltzmann-Maxwell theory can be used to explain the phenomenon of electromagnetic wave propagating in plasma. Finally, the two-dimensional simulation model of plasma antenna is established under the cylindrical coordinate. And the near-field and far-field radiation pattern of plasma antenna are obtained. The experiments show that the variation of electron density can introduce the change of radiation characteristic.
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## Body
## 1. Introduction
Plasma antenna usually adopts the partially or fully ionized gas as conducting medium instead of metallic materials. Compared with conventional metallic antenna, plasma antenna has many peculiar properties. For instance, it can be rapidly switched on or off; this characteristic makes plasma antenna suitable for stealth applications for military communication fields. Also, if this kind of antenna is used as the antenna array, the coupling between the elements of antenna array is small. In particular, radiation pattern of plasma antenna can be reconfigured through changing the frequency and intensity of pump signal, gas pressure, vessel dimensions, and so on. Because of the advantages above, many researchers and scientific utilities show great interests in it.At present, studies concerning plasma antenna may have three aspects: experimental investigation, theory derivation, and numerical calculation. Theodore Anderson together with Igor Alexeff [1] designed a smart plasma antenna and implemented a wide range of plasma antenna experiments. Their studies had proved that plasma antenna has reconfigurable characteristics. Kumar and Bora [2] designed a 30 cm plasma antenna and proved that the frequency and radiation pattern can be altered with the frequency and power of the pump signal. Yang et al. [3] and Zhao [4] obtained the dispersion relationships of the surface wave along the plasma column by using theoretical derivation approach. Wu et al. [5] and Xia and Yin [6] studied the radiation characteristic of plasma antenna through theoretical derivation. Dai et al. [7] calculated the coefficients of reflection and transmission of electromagnetic wave in plasma by using FDTD numerical method. Liang [8] simulated the radiation characteristic of cylindrical monopolar antenna by using FDTD method. Russo et al. [9–13] established one-dimensional and two-dimensional self-consistent model of plasma antenna and validated the correctness of the model through using FDTD method.From the investigations and research mentioned above, we can draw a conclusion that plasma is so complicated that one cannot find the real issues of the problem only through experimental approach. It is necessary to establish a rigorous mathematical model to investigate the radiation characteristic of plasma antenna. The numerical calculation approach applied in this paper is to study the radiation characteristic of plasma antenna.
## 2. Propagation of Electromagnetic Wave in Free Space and Plasma
There are two key issues to deal with in this research: one is the propagation of electromagnetic wave in free space and the other one is the propagation of electromagnetic wave in the plasma. Only these two problems are solved; then the investigation of radiation characteristic of plasma antenna can be further conducted.
### 2.1. Propagation of Electromagnetic Wave in Free Space
In order to apply FDTD method to simulate the propagation of electromagnetic wave in free space in cylindrical coordinate, the stretched coordinate is selected. So, the modified Maxwell equations can be expressed as below:(1)∇s×H=jωεE,(2)∇s×E=-jωμH,
where E represents electric field strength vector in volts per meter. H represents magnetic field strength vector in amperes per meter. ε denotes the permittivity in farad per meter. μ denotes the permeability in henry per meter. ω represents the angular frequency of incidence signal in radian per second.In stretched coordinate [14], we define
(3)sr=1+σrjωε0,sz=1+σzjωε0,
where sr and sz are coordinate stretched factor
(4)R⟶∫0rsr(r′)dr′={r,r′<r0r+1jωε0∫r0rσr(r′)dr′,r′<r0,(5)Z⟶∫0zsz(z′)dz′={z,z′<z0z+1jωε0∫z0zσz(z′)dz′,z′<z0,
where r0 and z0 represent the distance between the signal source and inner boundary of PML along r direction and z direction, respectively.Maxwell curl equation (1), then, can be represented by these three scale equations in cylindrical coordinate system as (6a)–(6c):(6a)jωε0Er=1R∂Hz∂φ-∂Hφ∂Z,(6b)jωε0Eφ=∂Hr∂Z-∂Hz∂R,(6c)jωε0Ez=1R∂(RHφ)∂R-1R∂Hr∂φ.From (4) and (5), (7) can be obtained as follows:
(7)∂∂R=1sr∂∂r,∂∂Z=1sz∂∂z.
Substituting (7) into (6a)–(6c) yields(8a)jωε0Er=1R∂Hz∂φ-1sz∂Hφ∂z,(8b)jωε0Eφ=1sz∂Hr∂z-1sr∂Hz∂r,(8c)jωε0Ez=1R1sr∂(RHφ)∂r-1R∂Hr∂φ.After multiplying sz·R/r, sz·sr, sr·R/r, respectively, (8a), (8b), and (8c) can be expressed as below:(9a)jωε0szRrEr=1r∂(szHz)∂φ-Rr∂Hφ∂z,(9b)jωε0szsrEφ=∂(srHr)∂z-∂(szHz)∂r,(9c)jωε0srRrEz=1r∂(RHφ)∂r-1r∂(srHr)∂φ.Substituting szHz=Hz′, srHr=Hr′, RHφ/r=Hφ′, REφ/r=Eφ′, szEz=Ez′, and srEr=Er′ into (9a)–(9c), (9a)–(9c) can be written as(10a)jωε0szsrRrEr′=1r∂Hz′∂φ-∂Hφ′∂z,(10b)jωε0szsrrREφ′=∂(Hr′)∂z-∂(Hz′)∂r,(10c)jωε0srRszrEz′=1r∂(rHφ′)∂r-1r∂(Hr′)∂φ.Namely,
(11)[1r∂Hz′∂φ-∂Hφ′∂z∂(Hr′)∂z-∂(Hz′)∂r1r∂(rHφ′)∂r-1r∂(Hr′)∂φ]=jωε0εrε-[Er′Eφ′Ez′].
Equation (11) can be shortly expressed as
(12)∇×H=jωε0εrε-E.According to the duality theorem, Maxwell curl equation (2) can be represented by equation
(13)[1r∂Ez′∂φ-∂Eφ′∂z∂(Er′)∂z-∂(Ez′)∂r1r∂(rEφ′)∂r-1r∂(Er′)∂φ]=-jωμ0μrμ-[Hr′Hφ′Hz′].
Equation (13) can be expressed as
(14)∇×E=-jωμ0μrμ-H,
where
(15)ε-=μ-=[szRsrr000szsrrR000srRszr].AS the plasma antenna is rotationally symmetric. Thus, it is suitable to study this problem in cylindrical coordinate. The TM modes are excited. Maxwell equations involve three components:Er, Ez, and Hφ. Thus, the Maxwell equation of electromagnetic wave propagating in free space will be reduced as(16a)-jωμ0szsrrRHφ′=∂(Er′)∂z-∂(Ez′)∂r,(16b)jωε0szsrRrEr′=-∂Hφ′∂z,(16c)jωε0srRszrEz′=1r∂(rHφ′)∂r.Applying the auxiliary differential equation method (ADE) [15], the iterative equations [16] of (16a)–(16c) are derived as follows:(17a)Bφ∣i,jn+1=(2ε0-dtσr2ε0+dtσr)Bφ∣i,jn+(2ε0dt2ε0+dtσr)[Ez∣i+1/2,jn+1/2-Ez∣i-1/2,jn+1/2dr-Er∣i,j+1/2n+1/2-Er∣i,j-1/2n+1/2dz],(17b)Hφ∣i,jn+1=(2ε0-σzdt2ε0+σzdt)Hφ∣i,jn+1+2ε0R(2ε0+σzdt)μ0μrr(Bφ∣i,jn+1-Bφ|i,jn),(18a)Dr∣i+1/2,j,kn+1=(2ε0-σzdt2ε0+σzdt)Dr∣i+1/2,j,kn+(2ε0dt2ε0+σzdt)×{1ri+1/2Hz∣i+1/2,j+1/2,kn+1/2-Hz∣i+1/2,j-1/2.kn+1/2dφ-Hφ∣i+1/2,j,k+1/2n+1/2-Hφ∣i+1/2,j·k-1/2n+1/2dz},(18b)Er∣i+1/2,j,kn+1=Er∣i+1/2,j,kn+rε0εrR(2ε0+dtσr2ε0Dr∣i+1/2,j,kn+1-2ε0-dtσr2ε0Dr∣i+1/2,j,kn),(19a)Dz∣i,j,k+1/2n+1=(2ε0-σrdt2ε0+σrdt)Dz∣i,j,k+1/2n+(2ε0dt2ε0+σrdt)×{(12r+1dr)Hφ∣i+1/2,j,k+1/2n+1/2+(12r-1dr)Hφ∣i-1/2,j,k+1/2n+1/2,},(19b)Ez∣i,j,k+1/2n+1=Ez∣i,j,k+1/2n+rε0εrR(2ε0+dtσz2ε0Dz∣i,j,k+1/2n+1-2ε0-dtσz2ε0Dz∣i,j,k+1/2n).By using these six iterative equations, we can calculate the value of electromagnetic field in PML. Also, we can use these iterative equations to calculate the value of electromagnetic field in free space by setting the electric conductivity atσz=0, σr=0, and εr=1.In order to validate the correctness of the theory above, we apply this approach in the propagation of electromagnetic field in free space. The two-dimensional FDTD computational space is shown as in Figure1.Figure 1
Two-dimensional FDTD computational space.Figure1 shows that half of the free space is simulated. The computational space is composed of 50 × 100 Yee sells. The signal source is sinusoidal signal with the frequency of 20 GHz. The spatial step is Δr=Δz=0.003m. The temporal step is Δt=2.123×10-12 s. The total number of time steps is 500. The number of PML cells is 9. The propagating process of electric field Er in free space is shown as in Figure 2.Figure 2
Propagating the electric fieldEr in free space.In Figure2, it is shown that the electric field Er spreads out around the signal source. When the electric field arrives at the interface between PML and free space, it can be absorbed by the PML. So, the theory put forward above is correct.
## 2.1. Propagation of Electromagnetic Wave in Free Space
In order to apply FDTD method to simulate the propagation of electromagnetic wave in free space in cylindrical coordinate, the stretched coordinate is selected. So, the modified Maxwell equations can be expressed as below:(1)∇s×H=jωεE,(2)∇s×E=-jωμH,
where E represents electric field strength vector in volts per meter. H represents magnetic field strength vector in amperes per meter. ε denotes the permittivity in farad per meter. μ denotes the permeability in henry per meter. ω represents the angular frequency of incidence signal in radian per second.In stretched coordinate [14], we define
(3)sr=1+σrjωε0,sz=1+σzjωε0,
where sr and sz are coordinate stretched factor
(4)R⟶∫0rsr(r′)dr′={r,r′<r0r+1jωε0∫r0rσr(r′)dr′,r′<r0,(5)Z⟶∫0zsz(z′)dz′={z,z′<z0z+1jωε0∫z0zσz(z′)dz′,z′<z0,
where r0 and z0 represent the distance between the signal source and inner boundary of PML along r direction and z direction, respectively.Maxwell curl equation (1), then, can be represented by these three scale equations in cylindrical coordinate system as (6a)–(6c):(6a)jωε0Er=1R∂Hz∂φ-∂Hφ∂Z,(6b)jωε0Eφ=∂Hr∂Z-∂Hz∂R,(6c)jωε0Ez=1R∂(RHφ)∂R-1R∂Hr∂φ.From (4) and (5), (7) can be obtained as follows:
(7)∂∂R=1sr∂∂r,∂∂Z=1sz∂∂z.
Substituting (7) into (6a)–(6c) yields(8a)jωε0Er=1R∂Hz∂φ-1sz∂Hφ∂z,(8b)jωε0Eφ=1sz∂Hr∂z-1sr∂Hz∂r,(8c)jωε0Ez=1R1sr∂(RHφ)∂r-1R∂Hr∂φ.After multiplying sz·R/r, sz·sr, sr·R/r, respectively, (8a), (8b), and (8c) can be expressed as below:(9a)jωε0szRrEr=1r∂(szHz)∂φ-Rr∂Hφ∂z,(9b)jωε0szsrEφ=∂(srHr)∂z-∂(szHz)∂r,(9c)jωε0srRrEz=1r∂(RHφ)∂r-1r∂(srHr)∂φ.Substituting szHz=Hz′, srHr=Hr′, RHφ/r=Hφ′, REφ/r=Eφ′, szEz=Ez′, and srEr=Er′ into (9a)–(9c), (9a)–(9c) can be written as(10a)jωε0szsrRrEr′=1r∂Hz′∂φ-∂Hφ′∂z,(10b)jωε0szsrrREφ′=∂(Hr′)∂z-∂(Hz′)∂r,(10c)jωε0srRszrEz′=1r∂(rHφ′)∂r-1r∂(Hr′)∂φ.Namely,
(11)[1r∂Hz′∂φ-∂Hφ′∂z∂(Hr′)∂z-∂(Hz′)∂r1r∂(rHφ′)∂r-1r∂(Hr′)∂φ]=jωε0εrε-[Er′Eφ′Ez′].
Equation (11) can be shortly expressed as
(12)∇×H=jωε0εrε-E.According to the duality theorem, Maxwell curl equation (2) can be represented by equation
(13)[1r∂Ez′∂φ-∂Eφ′∂z∂(Er′)∂z-∂(Ez′)∂r1r∂(rEφ′)∂r-1r∂(Er′)∂φ]=-jωμ0μrμ-[Hr′Hφ′Hz′].
Equation (13) can be expressed as
(14)∇×E=-jωμ0μrμ-H,
where
(15)ε-=μ-=[szRsrr000szsrrR000srRszr].AS the plasma antenna is rotationally symmetric. Thus, it is suitable to study this problem in cylindrical coordinate. The TM modes are excited. Maxwell equations involve three components:Er, Ez, and Hφ. Thus, the Maxwell equation of electromagnetic wave propagating in free space will be reduced as(16a)-jωμ0szsrrRHφ′=∂(Er′)∂z-∂(Ez′)∂r,(16b)jωε0szsrRrEr′=-∂Hφ′∂z,(16c)jωε0srRszrEz′=1r∂(rHφ′)∂r.Applying the auxiliary differential equation method (ADE) [15], the iterative equations [16] of (16a)–(16c) are derived as follows:(17a)Bφ∣i,jn+1=(2ε0-dtσr2ε0+dtσr)Bφ∣i,jn+(2ε0dt2ε0+dtσr)[Ez∣i+1/2,jn+1/2-Ez∣i-1/2,jn+1/2dr-Er∣i,j+1/2n+1/2-Er∣i,j-1/2n+1/2dz],(17b)Hφ∣i,jn+1=(2ε0-σzdt2ε0+σzdt)Hφ∣i,jn+1+2ε0R(2ε0+σzdt)μ0μrr(Bφ∣i,jn+1-Bφ|i,jn),(18a)Dr∣i+1/2,j,kn+1=(2ε0-σzdt2ε0+σzdt)Dr∣i+1/2,j,kn+(2ε0dt2ε0+σzdt)×{1ri+1/2Hz∣i+1/2,j+1/2,kn+1/2-Hz∣i+1/2,j-1/2.kn+1/2dφ-Hφ∣i+1/2,j,k+1/2n+1/2-Hφ∣i+1/2,j·k-1/2n+1/2dz},(18b)Er∣i+1/2,j,kn+1=Er∣i+1/2,j,kn+rε0εrR(2ε0+dtσr2ε0Dr∣i+1/2,j,kn+1-2ε0-dtσr2ε0Dr∣i+1/2,j,kn),(19a)Dz∣i,j,k+1/2n+1=(2ε0-σrdt2ε0+σrdt)Dz∣i,j,k+1/2n+(2ε0dt2ε0+σrdt)×{(12r+1dr)Hφ∣i+1/2,j,k+1/2n+1/2+(12r-1dr)Hφ∣i-1/2,j,k+1/2n+1/2,},(19b)Ez∣i,j,k+1/2n+1=Ez∣i,j,k+1/2n+rε0εrR(2ε0+dtσz2ε0Dz∣i,j,k+1/2n+1-2ε0-dtσz2ε0Dz∣i,j,k+1/2n).By using these six iterative equations, we can calculate the value of electromagnetic field in PML. Also, we can use these iterative equations to calculate the value of electromagnetic field in free space by setting the electric conductivity atσz=0, σr=0, and εr=1.In order to validate the correctness of the theory above, we apply this approach in the propagation of electromagnetic field in free space. The two-dimensional FDTD computational space is shown as in Figure1.Figure 1
Two-dimensional FDTD computational space.Figure1 shows that half of the free space is simulated. The computational space is composed of 50 × 100 Yee sells. The signal source is sinusoidal signal with the frequency of 20 GHz. The spatial step is Δr=Δz=0.003m. The temporal step is Δt=2.123×10-12 s. The total number of time steps is 500. The number of PML cells is 9. The propagating process of electric field Er in free space is shown as in Figure 2.Figure 2
Propagating the electric fieldEr in free space.In Figure2, it is shown that the electric field Er spreads out around the signal source. When the electric field arrives at the interface between PML and free space, it can be absorbed by the PML. So, the theory put forward above is correct.
## 3. Radiation Characteristic of Plasma Antenna
In this part, the radiation characteristic of plasma antenna under two-dimensional case is investigated. The geometry [17, 18] of plasma antenna is shown in Figure 3.Figure 3
Two-dimension geometry of plasma antenna.As Figure3 illustrated, V represents free space around the plasma antenna. The plasma antenna is fed by coaxial cable. The parameters a and b are inner and outer radius of coaxial cable with the ratio of b/a=2.3 to ensure that the characteristic impedance is 50 Ω. l represents the length of plasma antenna tube. By using the FDTD approach together with the theory in Section 2, we study the near-field and far-field radiation pattern of plasma antenna.
### 3.1. Near-Field Radiation Pattern
If we want to obtain the unique solution to Maxwell equation withinV, we must initialize the electromagnetic fields E and H within V at time t=0. Furthermore, the values n×E and n×H must be initialized also on the boundary surface for all time 0<t<t0. The gauss pulse voltage source is imposed on the cross section A-A′ as shown in Figure 3. The expression of Er is as follows:(20)Eri(t)=Vi(t)ln(b/a)rr^.This is the only electric field at the cross section if we choose2lA>ct0, because the field reflected from the end of the line will not reach the cross section during the observation time. The outer conductor of coaxial cable connects with ground. The inner conductor, outer conductor, and ground are considered as perfect electric conductor (PEC). So the value of n×E is zero on the surface of the coaxial cable and ground during the observation process.The gauss pulse voltage source is initialized with the parametersτa=h/c,τp/τa=8×10-2. The parameters describing the plasma antenna are as follows: the length l=50 cm and the radius of the conductors of the coaxial line a=1 cm and b=2.3 cm. The spatial step is Δr=Δz=(b-a)/4. The temporal step can be calculated according to the expression Δt=1/c*1/dr2+1/dz2. Usually, the time step is chosen to be 20% smaller than the courant stability limit. The parameters of plasma are initialized: electron density is ne=1×1017m-3 and collision frequency is νc=1.5×108Hz. From the equation ωp=e2ne/mε0, the angular frequency of plasma can be obtained as ωp=1.7815×1010 rad/s. Through FDTD method, the near-field of plasma antenna corresponding to the iterative numbers is 500, 1000, and 1500. The corresponding results are shown in Figures 4, 5, and 6.Figure 4
Near-field of plasma antenna with iterative number 500.Figure 5
Near-field of plasma antenna with iterative number 1000.Figure 6
Near-field of plasma antenna with iterative number 1500.Figure4 ~ Figure 4 are the near-field of plasma antenna with different iterative number. Figure 6 shows the part of the power radiated to the free space and part of power reflected back to the coaxial cable when electromagnetic wave propagates from the bottom to the joint of coaxial cable and plasma antenna. Figure 5 shows that when the iterative number is 1000, the electromagnetic wave continues to spread out and has not reached the top of the plasma antenna. At the same time, the reverse electric field in coaxial cable will continue to propagate in signal source direction. When the iterative number comes to 1500, the electromagnetic wave will arrive at the top of the plasma antenna. Figure 6 shows that reflection has happened and the second radiation is formed.
### 3.2. Far-Field Radiation Pattern
The finite-difference time-domain (FDTD) method [19, 20] is used to compute electric and magnetic field within a finite space around an electromagnetic object. Namely, only the value of near magnetic field can be obtained. Otherwise, we also care about the far-zone electromagnetic field of plasma antenna. The far-zone electromagnetic field can be computed from the near-field FDTD data through a near-field to far-field (NF-FF) transformation technique.The far-field value is calculated in cylindrical coordinate. The schematic map of NF-FF is shown as in Figure7.Figure 7
Schematic map of NF-FF transformation.The vectorr denotes the position of the observation point (r,θ); the vector r′ denotes the position of source. The value of the source can be calculated through FDTD method.Through using the Green function under two-dimension conditions, the expressions of far-zone electromagnetic field in cylindrical coordinate are(21)Ez=exp(-jkr)22jπkr(jk)(-Zfz+fmφ),Hz=exp(-jkr)22jπkr(-jk)(fφ+1Zfmz),
where fζ(φ), fmζ(φ)(ζ=z,φ) are current moment and magnetic moment, respectively:
(22)fζ(φ)=∫lJ(r′)exp(jk·r′)dl′,fmζ(φ)=∫lJm(r′)exp(jk·r′)dl′.
Mapping from spherical coordinate to cylindrical coordinate, we have
(23)k·r′=ksin(θ)·r′+kcos(θ)·z.
Substituting (23) into (22), (22) can be rewritten as
(24)fζ(φ)=∫lJζ(r′)exp(j(ksin(θ)·r′dsadsadsadsssffk+kcos(θ)·zr′))dl′,fmζ(φ)=∫lJmζ(r′)exp(j(ksin(θ)·r′dasdsadasdssssfdsf+kcos(θ)·zksin(θ)·r′))dl′.
Substituting (24) into (21), the far-field electromagnetic field can be obtained.Through the NF-FF method, the affection of electron density to the radiation characteristic of plasma antenna is studied. We initialize the typical parameters of plasma as below.Collision frequency isνc=1.5×108Hz, and the electron density is set as ne=1×1016m-3, ne=1×1017m-3, and ne=1×1018m-3, respectively. And the far-field of plasma antenna under different electron density is shown as in Figure 8.Figure 8
Far-field of plasma antenna under different electron density.In Figure8, it is shown that, with the variation of electron density of plasma antenna, the profile of far-field radiation pattern will change. The reason is that when the electromagnetic wave arrives at the plasma region, the interaction between electromagnetic wave and plasma changes the surface current distribution of plasma antenna, as it is known that the radiation pattern is determined by the surface current distribution of antenna. Thus, the far-field radiation pattern of plasma antenna will be changed.
## 3.1. Near-Field Radiation Pattern
If we want to obtain the unique solution to Maxwell equation withinV, we must initialize the electromagnetic fields E and H within V at time t=0. Furthermore, the values n×E and n×H must be initialized also on the boundary surface for all time 0<t<t0. The gauss pulse voltage source is imposed on the cross section A-A′ as shown in Figure 3. The expression of Er is as follows:(20)Eri(t)=Vi(t)ln(b/a)rr^.This is the only electric field at the cross section if we choose2lA>ct0, because the field reflected from the end of the line will not reach the cross section during the observation time. The outer conductor of coaxial cable connects with ground. The inner conductor, outer conductor, and ground are considered as perfect electric conductor (PEC). So the value of n×E is zero on the surface of the coaxial cable and ground during the observation process.The gauss pulse voltage source is initialized with the parametersτa=h/c,τp/τa=8×10-2. The parameters describing the plasma antenna are as follows: the length l=50 cm and the radius of the conductors of the coaxial line a=1 cm and b=2.3 cm. The spatial step is Δr=Δz=(b-a)/4. The temporal step can be calculated according to the expression Δt=1/c*1/dr2+1/dz2. Usually, the time step is chosen to be 20% smaller than the courant stability limit. The parameters of plasma are initialized: electron density is ne=1×1017m-3 and collision frequency is νc=1.5×108Hz. From the equation ωp=e2ne/mε0, the angular frequency of plasma can be obtained as ωp=1.7815×1010 rad/s. Through FDTD method, the near-field of plasma antenna corresponding to the iterative numbers is 500, 1000, and 1500. The corresponding results are shown in Figures 4, 5, and 6.Figure 4
Near-field of plasma antenna with iterative number 500.Figure 5
Near-field of plasma antenna with iterative number 1000.Figure 6
Near-field of plasma antenna with iterative number 1500.Figure4 ~ Figure 4 are the near-field of plasma antenna with different iterative number. Figure 6 shows the part of the power radiated to the free space and part of power reflected back to the coaxial cable when electromagnetic wave propagates from the bottom to the joint of coaxial cable and plasma antenna. Figure 5 shows that when the iterative number is 1000, the electromagnetic wave continues to spread out and has not reached the top of the plasma antenna. At the same time, the reverse electric field in coaxial cable will continue to propagate in signal source direction. When the iterative number comes to 1500, the electromagnetic wave will arrive at the top of the plasma antenna. Figure 6 shows that reflection has happened and the second radiation is formed.
## 3.2. Far-Field Radiation Pattern
The finite-difference time-domain (FDTD) method [19, 20] is used to compute electric and magnetic field within a finite space around an electromagnetic object. Namely, only the value of near magnetic field can be obtained. Otherwise, we also care about the far-zone electromagnetic field of plasma antenna. The far-zone electromagnetic field can be computed from the near-field FDTD data through a near-field to far-field (NF-FF) transformation technique.The far-field value is calculated in cylindrical coordinate. The schematic map of NF-FF is shown as in Figure7.Figure 7
Schematic map of NF-FF transformation.The vectorr denotes the position of the observation point (r,θ); the vector r′ denotes the position of source. The value of the source can be calculated through FDTD method.Through using the Green function under two-dimension conditions, the expressions of far-zone electromagnetic field in cylindrical coordinate are(21)Ez=exp(-jkr)22jπkr(jk)(-Zfz+fmφ),Hz=exp(-jkr)22jπkr(-jk)(fφ+1Zfmz),
where fζ(φ), fmζ(φ)(ζ=z,φ) are current moment and magnetic moment, respectively:
(22)fζ(φ)=∫lJ(r′)exp(jk·r′)dl′,fmζ(φ)=∫lJm(r′)exp(jk·r′)dl′.
Mapping from spherical coordinate to cylindrical coordinate, we have
(23)k·r′=ksin(θ)·r′+kcos(θ)·z.
Substituting (23) into (22), (22) can be rewritten as
(24)fζ(φ)=∫lJζ(r′)exp(j(ksin(θ)·r′dsadsadsadsssffk+kcos(θ)·zr′))dl′,fmζ(φ)=∫lJmζ(r′)exp(j(ksin(θ)·r′dasdsadasdssssfdsf+kcos(θ)·zksin(θ)·r′))dl′.
Substituting (24) into (21), the far-field electromagnetic field can be obtained.Through the NF-FF method, the affection of electron density to the radiation characteristic of plasma antenna is studied. We initialize the typical parameters of plasma as below.Collision frequency isνc=1.5×108Hz, and the electron density is set as ne=1×1016m-3, ne=1×1017m-3, and ne=1×1018m-3, respectively. And the far-field of plasma antenna under different electron density is shown as in Figure 8.Figure 8
Far-field of plasma antenna under different electron density.In Figure8, it is shown that, with the variation of electron density of plasma antenna, the profile of far-field radiation pattern will change. The reason is that when the electromagnetic wave arrives at the plasma region, the interaction between electromagnetic wave and plasma changes the surface current distribution of plasma antenna, as it is known that the radiation pattern is determined by the surface current distribution of antenna. Thus, the far-field radiation pattern of plasma antenna will be changed.
## 4. Conclusion
The radiation characteristic of plasma antenna is investigated in this paper. Before studying this problem, two key issues are investigated. Firstly, we study the propagation of electromagnetic wave in free space by using FDTD method. The updating equations of Maxwell equation in stretched coordinate are derived. In order to validate the correctness of the theory, the propagation of electromagnetic wave in free space is calculated. Results show that the theory is correct and can be used in cylindrical coordinate. Secondly, the radiation characteristic of plasma antenna under two-dimension case and the near-field radiation pattern are obtained. Through the NF-FF transformation, we obtain the far-field radiation pattern. From the results, we can conclude that the electron density can influence the radiation characteristic of plasma antenna.
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*Source: 290148-2014-07-09.xml* | 2014 |
# N-TiO2-x Nanocatalysts: PLAL Synthesis and Photocatalytic Activity
**Authors:** Enza Fazio; Angela Maria Mezzasalma; Luisa D’Urso; Salvatore Spadaro; Francesco Barreca; Giovanni Gallo; Fortunato Neri; Giuseppe Compagnini
**Journal:** Journal of Nanomaterials
(2020)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2020/2901516
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## Abstract
N-TiO2-x nanocatalysts are developed by the pulsed laser ablation in liquid (PLAL) technique, a simple and surfactant-free preparation method. The PLAL approach allows synthesizing chemical-morphological fine-tuning water TiO2-based nanomaterials, starting from targets of different nature (powders and commercial high purity targets). The catalytic activity was investigated using methylene blue (cationic dye) and methyl orange (azo dye). A different photocatalytic response was found for the various kinds of N-TiO2-x. In the first 20 min, under UV and visible light, about 50% and 10% of the methyl orange were removed using the N-TiO2-x and TiO2 colloids, respectively. In addition, we observe that the response towards the methylene blue is comparable in all the synthesized samples under UV irradiation while differing by about 30% under a visible lamp. The enhanced photocatalytic response of the N-TiO2-x nanocatalysts with respect to the TiO2 one is dependent on the content of the nitrogen dopant, surface area, and nitrogen-oxygen bonding configurations.
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## Body
## 1. Introduction
TiO2 is extensively studied in view of photocatalytic applications thanks to its low cost, high photogenerated hole oxidizing power, and long lifetime of electron/hole pairs when irradiated with light. Such photoinduced electron-hole pairs have been utilized to generate electricity in solar cells, to split water into hydrogen and oxygen, and to oxidize and degrade inorganic/organic/biological compounds in environments as well as to create superhydrophilicity [1].The first reliable paper on photocatalytic activity of TiO2 was published in 1938. It has been shown that UV absorption produced active oxygen species on TiO2 surfaces, causing photobleaching of dyes [2]. Subsequent works to this have shown the oxidation of organic solvents and the formation of H2O2 under an UV irradiation of a mercury lamp under ambient conditions while the water photolysis was demonstrated for the first time in 1969 on TiO2 semiconductors [3]. Fundamental processes of TiO2 photoelectrochemistry have been studied intensively, mainly analyzing the behavior of TiO2 nanomaterials, interesting for their high surface-volume ratio. TiO2 nanostructures provide increased surface area at which photoinduced reactions may occur, enhancing the light absorption rate, increasing the surface photoinduced carrier density, enhancing the photoreduction rate, and resulting in higher surface photoactivity. At the same time, the high surface-volume ratio of the nanoparticles enhances the surface absorption of OH− and H2O, increasing the photocatalytic reaction rate [4, 5]. Based on the basic research results, industrial applications of photocatalytic TiO2 have been achieved since the end of the 1990s and will develop further in the 21st century. Among them are photocatalytic water splitting [6], purification of pollutants [7], photocatalytic self-cleaning [8], photocatalytic antibacteria, and photoinduced super hydrophilicity [9], as well as photovoltaics and photosynthesis [10] (see Figure 1).Figure 1
Dependence graph of photo-activated TiO2 materials applications. The flow goes from the top to the bottom direction.However, the large bandgap of TiO2 (3.2 eV for anatase and 3 eV for rutile) limits its light absorption only to the UV region [11]. Thus, pure TiO2 works as a photocatalytic material under UV light (4-5% of solar light), but it has very low photocatalytic activity in visible light (45% of solar spectrum). Some efforts have been made to overcome this limitation. Some aspects have been identified as essential to resolve the issue such as to tailor TiO2 bulk/surface electronic structures and the interfaces in order to tune surface band-bending, surface state distribution, and charge separation, which could significantly influence TiO2 photocatalysis response in the visible spectral range. The main requirements are (1) a high surface/volume ratio and a controlled anatase-rutile ratio to provide a large number of active sites for the degradation reaction and (2) shifting the absorption limit of the material in the visible range, searching for an increase in reaction rate of photocatalysis and hydrogen production.Doping appears as a good alternative for changing the activity of TiO2 catalysts through the optoelectrical modification of this material by the introduction of dopants with different energy levels between the conduction and valence bands. The applied dopants can be (1) noble metals (such as Ag, Au, Pd, and Pt), which absorb the visible light due to the surface plasmon resonance, but the high cost associated with these materials should be considered a disadvantage [12]; (2) transition metals cheaper than noble metals, but their leaching behavior leads to the fast deactivation of the catalyst and constitutes a second source of pollution [13]; and (3) nonmetals (N, B, S, F, and C) able to extend optical absorption of TiO2 to the visible light region and then to improve visible-light-driven photocatalytic processes [14, 15]. Among the above-mentioned nonmetals, the most suitable and commonly used is nitrogen.Nitrogen, as sulfur and fluorine species, is an anionic dopant which confers greater stability to the catalyst with respect to the conventional transition-metal dopants and also determines a significant red shift of the band gap into the visible range. According to theoretical modelling [16], the p-orbitals of the nitrogen dopant extensively overlapped, favouring the transfer of photogenerated charge carriers to the TiO2 surface, in turn increasing its photocatalytic activity [17]. It was proven that both in the anatase and rutile phases of TiO2, the N2p states were located just above the top of the O2p valence band, which means a red shift of the absorption band edge to the visible region [18].Despite the potential, data about the main changes provided by nitrogen doping in TiO2 is not well established. Moreover, for large scale usage of TiO2-xNx nanomaterials in all the solar radiation ranges, none of the results actually reached are satisfactory due to their low nitrogen/oxygen content, low chemical-physical stability, and increased carrier trapping.There are multiple and assorted methods to prepare N-TiO2 catalysts. Physical vapor deposition (PVD), reactive sputtering, cathodic arc deposition, plasma-gas reaction, and Chemical Vapor Deposition (CVD) are the common methods used to deposit N-doped titania films. However, all these techniques allow the deposition of low level N-doped titania with micron-sized structures only at high vacuum conditions (10-8-10-9 Pa) and at high temperature (1200-1500°C) to avoid sample reoxidation. The methods based on plasma-gas phase reactions with the use of TiN powders seem to be a good and low cost alternative to obtain films with a small particle size (about 10 nm). However, these samples show a high oxygen content (ca. 15–20 at.%) [19]. Recently TiO2, loading a different percentage of nitrogen, was prepared by nitridation of a nano-TiO2 powder in a mixed ammonia/argon atmosphere at a range of temperatures from 400 to 1100°C [17]. According to the results obtained by Zhang et al. [20], the samples prepared at 700°C are oxygen deficient, which may be partly responsible for the shifting band gap and for the significant photocatalytic activity. On the other hand, nanocolloid production generally involves the use of surfactants and derivatives which cause secondary pollution to the environment.For all these reasons, further studies will be useful mainly to (1) clarify whether oxygen deficiency has a bigger effect on photocatalytic activity than N-doping at low levels, (2) give a systematic and complete characterization of the chemical-morphological and optical properties of the synthesized N-TiO2-x nanomaterials, and (3) identify green methods and define a synthesis protocol in order to produce nanocolloids. This latter should be usable directly in the liquid phase in an innovative photocatalytic device, with a high degradation time (even in extreme conditions).In this work, we presented and discussed the results obtained using the potentiality of the pulsed laser ablation in liquid (PLAL) technique to prepare N-TiO2-x nanocolloids. The syntheses were carried out in water to favour the formation of (Ti-O-N), (−NH2), NO2−, N2, NHx, and (−OH) species, inducing their incorporation into the TiO2 lattice as nitride through dehydration. To this aim, the optimal PLAL deposition parameters (i.e., laser fluence and irradiation time) were found as well as the optimal composition of the targets (TiO2 mixed to TiN powders or TiN rod purchased from Matek Srl). PLAL processes were performed in ambient condition (room temperature) using the water as solvent, with the advantage to obtain nanocolloids, without by-products, suitable for mechanical deposition on photoanode materials or to be incorporated in integrated solar water-splitting devices.All the synthesized colloids were characterized by scanning transmission electron microscopy (STEM), X-ray photoelectron (XPS), and conventional optical spectroscopies, providing complementary information which allows drawing a picture of the compositional, morphological, and optical properties of the nanocomposites, constituting the starting point for their successive photocatalysis applications which require moderate operating temperatures and limited energy consumptions.
## 2. Experimental Section
TiO2-xNx powders, pressed into a disk at room temperature, were prepared starting from powders of TiN and TiO2 (P25), mixed at the TiN/TiO2 mass ratios of 75/25, 50/50, and 25/75. Then, the compacts were maintained in a furnace at around 250°C for 1 hour. Pulsed laser ablation in liquid (PLAL) processes of the pressed powders as well as of commercial TiN and TiO2 rod targets (synthesized by Matek Srl at 1200°C) were carried out in deionized water (H2O). The targets were irradiated at the laser fluence of 0.5 J/cm2 for an irradiation time of 15 min (samples labelled TION3-5 and TION1P-5P-17P-12P) and of 1.5 J/cm2 for 30 min (TION4), by the 532 nm radiation coming from a Nd:YAG laser source, operating at the repetition rate of 10 Hz and at the pulse width of 6 ns. The scheme of the PLAL setup and an overview of the sample set are shown in Figure 2.Figure 2
Scheme of PLAL setup and synthesis parameters for each adopted target.Scanning transmission electron microscopy (STEM) images were acquired using a Zeiss electronic microscope which operates at an accelerating voltage of 30 kV. Samples for the STEM analysis were prepared by dropping a suspension of the sonicated colloids on a 400 mesh holey-carbon support sputter-coated with chromium.A PerkinElmer (Lambda 750) spectrometer, working in the 300-900 nm range, was used to collect optical absorbance spectra.The crystalline phase of the oxide was also investigated by analyzing Raman scattering data. Raman spectra have been excited with the 532 and 638 nm diode laser lines mounted in the XploRA spectrometer coupled with an Olympus microscope. Spectra have been collected with a 50x objective (spot size of about 2μm) and a Charged Coupled Device (CCD) used as a sensor. An acquisition time of 80 s granted a sufficient S/N ratio.The chemical bonding states and the relative atomic content in the nanocomposites were investigated by X-ray Photoelectron Spectroscopy (XPS), using the Thermo Scientific K-Alpha system equipped with a monochromatic Al-Kα source (1486.6 eV) and operating with a pass energy of 50 eV in the CAE mode.Some aqueous solutions of methyl orange (MO) and methylene blue (MB) (Sigma-Aldrich) were prepared by dissolving the analytical grade dyes in the synthesized colloids at a1.5·10−5M concentration.MO and MB were used as probe molecules for a first evaluation of the photocatalytic activities of N-TiO2 nanostructures. The reaction was conducted in 3 ml of aqueous solution containing the dye, previously maintained in a beaker for 30 min at a temperature of about 10°C. The photocatalytic reaction was carried out under stirring. 0.5 mg of catalyst was dispersed in 3 ml of dye aqueous solution placed in an ice bath; in this way, the temperature of aqueous dispersion was maintained at around 14±2°C.A 40 W Hg lamp (for UV irradiation) and a 450 W xenon lamp (as a visible light source blocking UV radiation by a 400 nm glass filter) were used as light sources placed at a distance of about 15 cm. Prior to irradiation, the dye catalyst suspensions were kept in the dark for 30 min to ensure an adsorption/desorption equilibrium. Then, the photodecolourization of MO and MB was studied.Analytical samples were filtered through a 0.2μm Millipore® filter to remove the solid, at well-defined time intervals during the irradiation, and placed into a 0.35 ml microquartz cuvette. Then, the residual dye concentrations in the filtrates were analyzed by UV-visible spectrophotometer (PerkinElmer 750) at maximum absorption wavelengths (λmax) of 464 and 664 nm for MO and MB, respectively. Direct photolysis decolourization of the respective dye was estimated by performing blank experiments.
## 3. Results and Discussion
### 3.1. Sample Characterization
In Figure3 are shown representative STEM images of the samples obtained ablating in water targets of different nature. Specifically, the colloids, obtained ablating the (25/75) TiN/TiO2 powder targets, show a porous morphology with some spherical nanostructures with a mean diameter of about 50 nm (Figure 3(a)). It is to be noted that the observation of perfectly rounded submicrometer particles, probably associated with TiO2 species, is in agreement with what was observed by Felice et al. [21]. On the other hand, a high density of nanoparticles with a spherical shape and size mainly below 30 nm characterizes the colloids prepared ablating the high purity (99.99%) commercial TiN rod target (Figure 3(c)). An analogous morphology is shown by the colloids prepared ablating the TiN powder target (Figure 3(b)). More details can be observed from images d–h collected for the samples obtained ablating the (25/75) TiN/TiO2 powder targets and the TiN rod and powder targets.Figure 3
STEM images of the samples obtained ablating the (25/75) TiN/TiO2 powder targets (a, d, e), the TiN powder target (b, f), and the high purity (99.99%) commercial TiN rod target (c, g, h).
(a)(b)(c)(d)(e)(f)(g)(h)The sample obtained from the (25/75) mixed TiN/TiO2 powders show Raman features typical of the anatase-rich TiO2 material [6]. It is important to highlight that first-order Raman features of TiN (at 225 cm-1 (TA), 310 cm-1 (LA), and 540 cm-1(TO)) are almost absent, suggesting that nitrogen could be incorporated as a defect in the crystalline TiO2 lattice. Samples, obtained from TiN powder (red line) and rod (blue line) targets, showed very similar Raman spectra; in this case, TiN vibrational features are well observable (see Figure 4(a)) as indicated by the pronounced peak at about 550 cm-1 related to the TiN-TO mode [22]. Moreover, we observe that the Eg (associated to the anatase phase) signal below 200 cm-1 is totally absent and that the intensity ratio between the observed peaks at 200 and 290 cm-1 is very similar to that of a possible formation of a rutile TiO2 phase. Unfortunately, TiN and rutile features overlapped in this region, so a correct attribution for the rutile is not possible exclusively from Raman analyses. All this evidence indicates a tendency towards an anatase-rutile conversion and/or an oxygen replacement by nitrogen with the formation of Ti-N bonds [22]. Interstitial nitrogen species are expected as a result of the ablation of a TiN target in water.Figure 4
(a) Raman and (b) optical absorbance spectra of the synthesized samples.
(a)(b)In Figure4(b) are shown the optical absorbance spectra of the synthesized nanocolloids. We observe that (1) the colloid obtained by a TiN rod target is transparent (over 90%) in the visible range with a sharp absorption edge at about 350 nm, (2) a broad band at around 420 nm characterizes the sample prepared from the TiO2 powder target, and (3) a slight blue shift is evident in the colloids prepared using the pressed and sintered target with a (75/25) TiN/TiO2 mass ratio; for these samples, the 420 nm band is totally absent, while a significant visible light absorption contribution up to 600 nm is evident, probably due to the electronic transition from the localized N doping level to the conduction band of TiO2 (see also the scheme reported in Figure 5).Figure 5
Schematic diagram showing the valence and conduction bands of N-doped TiO2.The incorporation of nitrogen into the TiO2 lattice leads to the formation of a new midgap energy state, i.e., the N2p band above the O2p valence band. So, upon a visible light irradiation, the electrons can migrate from the valence band to the conduction band (Figure 5) and from here the expected visible light activity of N-dopedTiO2 or TiO2-xNx materials (see Catalytic Activities). Nitrogen can replace one or more oxygen atoms (“substitutional doping”), or nitrogen can be positioned in interstitial TiO2 sites (“interstitial doping”). In both cases, as shown in Figure 5, N doping leads to a change in the electronic behavior of the nanoparticle due to a change in the electronic band structures and/or a decrease of electron-hole recombination [23].XPS analysis allows investigating the surface chemical composition and bonding configurations of our samples, in which it is known that the surface chemical coordination greatly influences the catalytic response [24]. In Figures 6(a)–6(c) are shown representative Ti2p and N1s deconvoluted profiles, while the chemical atomic percentage of the detected species and the relative surface bonding configurations are reported in Table 1. Two different Ti2p profiles characterize our samples: those obtained starting from the TiN rod target (Figure 6(a)) show a broad band whose features are ascribed to the titanium nitride, the titanium dioxide (TiO2), and the intermediate phase of titanium oxynitride [25, 26]. Otherwise, in the samples obtained by the TiN powder (Figure 6(b)), narrower profiles are obtained and the binding energy of the Ti2p3/2 peak is brought closer to 458.5 eV (typical of TiO2 compound), while the binding energies of the other phases still fall within the possible ranges. Interestingly, no resolved N1s signal was collected from the powder targets while the N1s profile is well structured and defined for samples obtained from the rod targets (Figure 6(c)). The main components are located at around 396 and in the 397-400 eV range. These features are ascribed to the titanium oxynitride phase and to the nitrogen in substitutional and interstitial positions [26–31]. The NHx, NO/NO2, and NO3− contributions are generally reported at a binding energy higher than 400 eV [29–31] but, in our case, are less pronounced (see Figures 6(c) and 6(d)).Figure 6
Ti2p (a, b) deconvoluted profiles of the samples obtained from the TiN rod and TiN powder targets, respectively. We outline that all the samples obtained from the mixed powders show Ti2p line shapes similar to those of the sample starting from the TiN powder. The N1s deconvoluted profile of the sample obtained starting from the TiN rod target (c) and a scheme of the potential nitrogen allocation into the TiO2 structure (d).Table 1
Atomic surface chemical composition and bonding fraction estimated by the deconvoluted XPS spectra.
SampleChemical composition (%)Bonding configurations (%)Ti2pN1sN (%)Ti (%)O (%)Ti-NTi-O-NTi-O2N-Ti-ONsubst.Nint.NO/NO2TION1p1.128.870.10.86.492.8——100—TION5p0.728.471.00.53.596.0——100—TION12p5.923.870.30.93.495.7——100—TION17p4.619.875.60.03.796.3——100—TION312.228.859.115.526.058.567.418.59.54.6TION417.824.158.117.829.153.159.726.610.72.9TION514.825.759.617.430.152.665.522.09.92.7
### 3.2. Catalytic Activities
All the photocatalytic reactions were undertaken in air as the photobleaching of MB is irreversible in an oxygen-saturated aqueous solution such as ours, and in an ice bath to avoid degradation effects due to light irradiation-induced heating. The photodegradation was monitored by recording UV-visible extinction spectra as a function of light irradiation exposure time. The percentage of MB decolourization under ultraviolet and visible radiation for the synthesized and TiO2 reference samples is shown in Figure 7. Under UV and visible irradiation, all the produced nanostructures show a photocatalytic activity towards the degradation of methylene blue (MB) dye molecule. However, the response is comparable in all the samples under UV irradiation while, under the visible lamp, the estimated percentages differ by about 30%. In fact, for the samples obtained by ablating TiN powder and TiN/TiO2-mixed powder in 75/25 ratio, MB decolourization is about 45% but increases in the samples obtained from the TiN rod or from the TiN/TiO2-mixed powders at the 25/75 ratio. Photocatalytic decolourization behavior of MB dye (during visible irradiation, over the 1 h time frame of the experiment) seems to be influenced by the amount of N, Ti, and O and their bonding coordination and by the increasing absorption in the visible light region [32].Figure 7
Photocatalytic activity towards the methylene blue (MB) dye molecule under UV and visible irradiation (60 min exposure time).In Figure8 is shown the percentage of MO decolourization under UV and visible lamp for the synthesized and reference samples. MO is an azo dye characterized by a N=N linkage, which is anionic in aqueous media and absorbs light in the visible region (450–550 nm) with an absorption maxima at 464 nm [33]. The samples obtained by TiN rod or TiN powder targets as well as those in which the TiN fraction is higher than the TiO2 one (75/25 ratio) are the most active nanocomposites, both under UV and visible irradiation. For the colloids going from the TiN rod, we observe that, in the first 20 min, 50% and 60% of the dye were removed under UV and visible light, respectively, while only about 10% of the dye is removed for the TiO2 colloid. Moreover, 70% of MO decolourization occurs within 80 min under visible irradiation while the other samples, for which Ti-O chemical bonds dominate in comparison to TiN/Ti-O-N ones, show significantly less efficiency in the same range of time.Figure 8
Photocatalytic activity towards the methyl orange (MO) dye molecule under UV and visible irradiation (60 min exposure time).
(a)(b)In order to have a quantitative estimation of the photocatalytic activity, we carried out a simple fitting procedure already adopted to test photodegradation efficiency of MB using zinc oxide nanocolloids, prepared by picosecond pulsed laser ablation, as catalysts [34]. If a semilogarithm scale of the relative absorbance as function of irradiation time is employed, it is possible to obtain a pseudoorder constant rate for all analyzed samples (see Table 2). In detail, by following the equation
(1)lnAA0=−kct,with A0 and At as the starting absorbance and the absorbance at the time t, respectively, a linear fitting procedure, limited to the first 30 minutes of irradiation, is evidence that both dyes degrade faster under the visible source and that the highest kc value is obtained with nanocatalysts from the TiN rod target.Table 2
Photodegradation rate constants of MB and MO with different catalysts usinglnA/A0=−kct as the fitting equation model.
Samplekc (min-1)MBMOUV lampVisible lampUV lampVisible lampTION5 (TiN rod target)-0.0118-0.0211-0.0333-0.0426TION1P (TiN powder target)-0.0129-0.0126-0.0300-0.0326TION5P (TiN/TiO2 (25/75) target)-0.0103-0.0242-0.0043-0.0176TION12P (TiN/TiO2 (75/25) target)-0.0139-0.0113-0.0153-0.0158TiO2 target-0.0091-0.0211-0.0026-0.0046Hence, on the basis of the obtained results, we suggest that the sample obtained from TiN characterized by the higher N content could be photosensitized by the “N-doping.” In this case, oxygen vacancies promoted the charge recombination, resulting in weak reduction power. Otherwise, the high activity of the sample synthesized from the TiN/TiO2 mixed powder in 25/75 ratio was attributed to the abundance of hydroxy groups in its porous structure (see STEM image), which provided more active sites for the degradation reaction as well as to the high available surface/volume ratio of the catalyst, since this sample shows a porous structure (Figure 3(a)). Nevertheless, no clear correlation between the MB or MO photocatalytic activity and the chemical-structural properties of the synthesized nanocolloids is found, since dye decolourization is also affected by the ionic nature, structure and stability, adsorption, and orientation of the dye molecules on the surface of the catalyst [35, 36]. The synthesized N-TiO2 nanocatalysts should be further investigated in depth to improve their catalytic response in the visible spectral region by a more rational and environment-friendly PLAL approach.
## 3.1. Sample Characterization
In Figure3 are shown representative STEM images of the samples obtained ablating in water targets of different nature. Specifically, the colloids, obtained ablating the (25/75) TiN/TiO2 powder targets, show a porous morphology with some spherical nanostructures with a mean diameter of about 50 nm (Figure 3(a)). It is to be noted that the observation of perfectly rounded submicrometer particles, probably associated with TiO2 species, is in agreement with what was observed by Felice et al. [21]. On the other hand, a high density of nanoparticles with a spherical shape and size mainly below 30 nm characterizes the colloids prepared ablating the high purity (99.99%) commercial TiN rod target (Figure 3(c)). An analogous morphology is shown by the colloids prepared ablating the TiN powder target (Figure 3(b)). More details can be observed from images d–h collected for the samples obtained ablating the (25/75) TiN/TiO2 powder targets and the TiN rod and powder targets.Figure 3
STEM images of the samples obtained ablating the (25/75) TiN/TiO2 powder targets (a, d, e), the TiN powder target (b, f), and the high purity (99.99%) commercial TiN rod target (c, g, h).
(a)(b)(c)(d)(e)(f)(g)(h)The sample obtained from the (25/75) mixed TiN/TiO2 powders show Raman features typical of the anatase-rich TiO2 material [6]. It is important to highlight that first-order Raman features of TiN (at 225 cm-1 (TA), 310 cm-1 (LA), and 540 cm-1(TO)) are almost absent, suggesting that nitrogen could be incorporated as a defect in the crystalline TiO2 lattice. Samples, obtained from TiN powder (red line) and rod (blue line) targets, showed very similar Raman spectra; in this case, TiN vibrational features are well observable (see Figure 4(a)) as indicated by the pronounced peak at about 550 cm-1 related to the TiN-TO mode [22]. Moreover, we observe that the Eg (associated to the anatase phase) signal below 200 cm-1 is totally absent and that the intensity ratio between the observed peaks at 200 and 290 cm-1 is very similar to that of a possible formation of a rutile TiO2 phase. Unfortunately, TiN and rutile features overlapped in this region, so a correct attribution for the rutile is not possible exclusively from Raman analyses. All this evidence indicates a tendency towards an anatase-rutile conversion and/or an oxygen replacement by nitrogen with the formation of Ti-N bonds [22]. Interstitial nitrogen species are expected as a result of the ablation of a TiN target in water.Figure 4
(a) Raman and (b) optical absorbance spectra of the synthesized samples.
(a)(b)In Figure4(b) are shown the optical absorbance spectra of the synthesized nanocolloids. We observe that (1) the colloid obtained by a TiN rod target is transparent (over 90%) in the visible range with a sharp absorption edge at about 350 nm, (2) a broad band at around 420 nm characterizes the sample prepared from the TiO2 powder target, and (3) a slight blue shift is evident in the colloids prepared using the pressed and sintered target with a (75/25) TiN/TiO2 mass ratio; for these samples, the 420 nm band is totally absent, while a significant visible light absorption contribution up to 600 nm is evident, probably due to the electronic transition from the localized N doping level to the conduction band of TiO2 (see also the scheme reported in Figure 5).Figure 5
Schematic diagram showing the valence and conduction bands of N-doped TiO2.The incorporation of nitrogen into the TiO2 lattice leads to the formation of a new midgap energy state, i.e., the N2p band above the O2p valence band. So, upon a visible light irradiation, the electrons can migrate from the valence band to the conduction band (Figure 5) and from here the expected visible light activity of N-dopedTiO2 or TiO2-xNx materials (see Catalytic Activities). Nitrogen can replace one or more oxygen atoms (“substitutional doping”), or nitrogen can be positioned in interstitial TiO2 sites (“interstitial doping”). In both cases, as shown in Figure 5, N doping leads to a change in the electronic behavior of the nanoparticle due to a change in the electronic band structures and/or a decrease of electron-hole recombination [23].XPS analysis allows investigating the surface chemical composition and bonding configurations of our samples, in which it is known that the surface chemical coordination greatly influences the catalytic response [24]. In Figures 6(a)–6(c) are shown representative Ti2p and N1s deconvoluted profiles, while the chemical atomic percentage of the detected species and the relative surface bonding configurations are reported in Table 1. Two different Ti2p profiles characterize our samples: those obtained starting from the TiN rod target (Figure 6(a)) show a broad band whose features are ascribed to the titanium nitride, the titanium dioxide (TiO2), and the intermediate phase of titanium oxynitride [25, 26]. Otherwise, in the samples obtained by the TiN powder (Figure 6(b)), narrower profiles are obtained and the binding energy of the Ti2p3/2 peak is brought closer to 458.5 eV (typical of TiO2 compound), while the binding energies of the other phases still fall within the possible ranges. Interestingly, no resolved N1s signal was collected from the powder targets while the N1s profile is well structured and defined for samples obtained from the rod targets (Figure 6(c)). The main components are located at around 396 and in the 397-400 eV range. These features are ascribed to the titanium oxynitride phase and to the nitrogen in substitutional and interstitial positions [26–31]. The NHx, NO/NO2, and NO3− contributions are generally reported at a binding energy higher than 400 eV [29–31] but, in our case, are less pronounced (see Figures 6(c) and 6(d)).Figure 6
Ti2p (a, b) deconvoluted profiles of the samples obtained from the TiN rod and TiN powder targets, respectively. We outline that all the samples obtained from the mixed powders show Ti2p line shapes similar to those of the sample starting from the TiN powder. The N1s deconvoluted profile of the sample obtained starting from the TiN rod target (c) and a scheme of the potential nitrogen allocation into the TiO2 structure (d).Table 1
Atomic surface chemical composition and bonding fraction estimated by the deconvoluted XPS spectra.
SampleChemical composition (%)Bonding configurations (%)Ti2pN1sN (%)Ti (%)O (%)Ti-NTi-O-NTi-O2N-Ti-ONsubst.Nint.NO/NO2TION1p1.128.870.10.86.492.8——100—TION5p0.728.471.00.53.596.0——100—TION12p5.923.870.30.93.495.7——100—TION17p4.619.875.60.03.796.3——100—TION312.228.859.115.526.058.567.418.59.54.6TION417.824.158.117.829.153.159.726.610.72.9TION514.825.759.617.430.152.665.522.09.92.7
## 3.2. Catalytic Activities
All the photocatalytic reactions were undertaken in air as the photobleaching of MB is irreversible in an oxygen-saturated aqueous solution such as ours, and in an ice bath to avoid degradation effects due to light irradiation-induced heating. The photodegradation was monitored by recording UV-visible extinction spectra as a function of light irradiation exposure time. The percentage of MB decolourization under ultraviolet and visible radiation for the synthesized and TiO2 reference samples is shown in Figure 7. Under UV and visible irradiation, all the produced nanostructures show a photocatalytic activity towards the degradation of methylene blue (MB) dye molecule. However, the response is comparable in all the samples under UV irradiation while, under the visible lamp, the estimated percentages differ by about 30%. In fact, for the samples obtained by ablating TiN powder and TiN/TiO2-mixed powder in 75/25 ratio, MB decolourization is about 45% but increases in the samples obtained from the TiN rod or from the TiN/TiO2-mixed powders at the 25/75 ratio. Photocatalytic decolourization behavior of MB dye (during visible irradiation, over the 1 h time frame of the experiment) seems to be influenced by the amount of N, Ti, and O and their bonding coordination and by the increasing absorption in the visible light region [32].Figure 7
Photocatalytic activity towards the methylene blue (MB) dye molecule under UV and visible irradiation (60 min exposure time).In Figure8 is shown the percentage of MO decolourization under UV and visible lamp for the synthesized and reference samples. MO is an azo dye characterized by a N=N linkage, which is anionic in aqueous media and absorbs light in the visible region (450–550 nm) with an absorption maxima at 464 nm [33]. The samples obtained by TiN rod or TiN powder targets as well as those in which the TiN fraction is higher than the TiO2 one (75/25 ratio) are the most active nanocomposites, both under UV and visible irradiation. For the colloids going from the TiN rod, we observe that, in the first 20 min, 50% and 60% of the dye were removed under UV and visible light, respectively, while only about 10% of the dye is removed for the TiO2 colloid. Moreover, 70% of MO decolourization occurs within 80 min under visible irradiation while the other samples, for which Ti-O chemical bonds dominate in comparison to TiN/Ti-O-N ones, show significantly less efficiency in the same range of time.Figure 8
Photocatalytic activity towards the methyl orange (MO) dye molecule under UV and visible irradiation (60 min exposure time).
(a)(b)In order to have a quantitative estimation of the photocatalytic activity, we carried out a simple fitting procedure already adopted to test photodegradation efficiency of MB using zinc oxide nanocolloids, prepared by picosecond pulsed laser ablation, as catalysts [34]. If a semilogarithm scale of the relative absorbance as function of irradiation time is employed, it is possible to obtain a pseudoorder constant rate for all analyzed samples (see Table 2). In detail, by following the equation
(1)lnAA0=−kct,with A0 and At as the starting absorbance and the absorbance at the time t, respectively, a linear fitting procedure, limited to the first 30 minutes of irradiation, is evidence that both dyes degrade faster under the visible source and that the highest kc value is obtained with nanocatalysts from the TiN rod target.Table 2
Photodegradation rate constants of MB and MO with different catalysts usinglnA/A0=−kct as the fitting equation model.
Samplekc (min-1)MBMOUV lampVisible lampUV lampVisible lampTION5 (TiN rod target)-0.0118-0.0211-0.0333-0.0426TION1P (TiN powder target)-0.0129-0.0126-0.0300-0.0326TION5P (TiN/TiO2 (25/75) target)-0.0103-0.0242-0.0043-0.0176TION12P (TiN/TiO2 (75/25) target)-0.0139-0.0113-0.0153-0.0158TiO2 target-0.0091-0.0211-0.0026-0.0046Hence, on the basis of the obtained results, we suggest that the sample obtained from TiN characterized by the higher N content could be photosensitized by the “N-doping.” In this case, oxygen vacancies promoted the charge recombination, resulting in weak reduction power. Otherwise, the high activity of the sample synthesized from the TiN/TiO2 mixed powder in 25/75 ratio was attributed to the abundance of hydroxy groups in its porous structure (see STEM image), which provided more active sites for the degradation reaction as well as to the high available surface/volume ratio of the catalyst, since this sample shows a porous structure (Figure 3(a)). Nevertheless, no clear correlation between the MB or MO photocatalytic activity and the chemical-structural properties of the synthesized nanocolloids is found, since dye decolourization is also affected by the ionic nature, structure and stability, adsorption, and orientation of the dye molecules on the surface of the catalyst [35, 36]. The synthesized N-TiO2 nanocatalysts should be further investigated in depth to improve their catalytic response in the visible spectral region by a more rational and environment-friendly PLAL approach.
## 4. Conclusions
In this work, the potentiality of the pulsed laser ablation in liquid (PLAL) technique to prepare N-TiO2-x nanocolloids, suitable for mechanical deposition on photoanode materials by conventional spraying technique, or to be incorporated in integrated solar water-splitting devices was reported. Synthesis processes were carried out in water, using targets with different nature and composition, to favour the formation of (Ti-O-N), (−NH2), NO2−, N2, NHx, and (−OH) species, and the nitrogen incorporation into the TiO2 lattice as nitride through dehydration. PLAL processes were performed in ambient condition (room temperature) using the water as solvent, without the need to provide high temperature (T) and pressures (P), thus preparing nanocolloids, ready to use without by-products. The observed photoactivity response of the synthesized nanocatalysts is explained in terms of their surface composition and bonding configurations and optical and morphological properties, which has been tuned changing the incorporation of nitrogen into the TiO2 lattice, beneficial for potentially separating the photogenerated carriers in space.
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*Source: 2901516-2020-06-11.xml* | 2901516-2020-06-11_2901516-2020-06-11.md | 38,745 | N-TiO2-x Nanocatalysts: PLAL Synthesis and Photocatalytic Activity | Enza Fazio; Angela Maria Mezzasalma; Luisa D’Urso; Salvatore Spadaro; Francesco Barreca; Giovanni Gallo; Fortunato Neri; Giuseppe Compagnini | Journal of Nanomaterials
(2020) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2020/2901516 | 2901516-2020-06-11.xml | ---
## Abstract
N-TiO2-x nanocatalysts are developed by the pulsed laser ablation in liquid (PLAL) technique, a simple and surfactant-free preparation method. The PLAL approach allows synthesizing chemical-morphological fine-tuning water TiO2-based nanomaterials, starting from targets of different nature (powders and commercial high purity targets). The catalytic activity was investigated using methylene blue (cationic dye) and methyl orange (azo dye). A different photocatalytic response was found for the various kinds of N-TiO2-x. In the first 20 min, under UV and visible light, about 50% and 10% of the methyl orange were removed using the N-TiO2-x and TiO2 colloids, respectively. In addition, we observe that the response towards the methylene blue is comparable in all the synthesized samples under UV irradiation while differing by about 30% under a visible lamp. The enhanced photocatalytic response of the N-TiO2-x nanocatalysts with respect to the TiO2 one is dependent on the content of the nitrogen dopant, surface area, and nitrogen-oxygen bonding configurations.
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## Body
## 1. Introduction
TiO2 is extensively studied in view of photocatalytic applications thanks to its low cost, high photogenerated hole oxidizing power, and long lifetime of electron/hole pairs when irradiated with light. Such photoinduced electron-hole pairs have been utilized to generate electricity in solar cells, to split water into hydrogen and oxygen, and to oxidize and degrade inorganic/organic/biological compounds in environments as well as to create superhydrophilicity [1].The first reliable paper on photocatalytic activity of TiO2 was published in 1938. It has been shown that UV absorption produced active oxygen species on TiO2 surfaces, causing photobleaching of dyes [2]. Subsequent works to this have shown the oxidation of organic solvents and the formation of H2O2 under an UV irradiation of a mercury lamp under ambient conditions while the water photolysis was demonstrated for the first time in 1969 on TiO2 semiconductors [3]. Fundamental processes of TiO2 photoelectrochemistry have been studied intensively, mainly analyzing the behavior of TiO2 nanomaterials, interesting for their high surface-volume ratio. TiO2 nanostructures provide increased surface area at which photoinduced reactions may occur, enhancing the light absorption rate, increasing the surface photoinduced carrier density, enhancing the photoreduction rate, and resulting in higher surface photoactivity. At the same time, the high surface-volume ratio of the nanoparticles enhances the surface absorption of OH− and H2O, increasing the photocatalytic reaction rate [4, 5]. Based on the basic research results, industrial applications of photocatalytic TiO2 have been achieved since the end of the 1990s and will develop further in the 21st century. Among them are photocatalytic water splitting [6], purification of pollutants [7], photocatalytic self-cleaning [8], photocatalytic antibacteria, and photoinduced super hydrophilicity [9], as well as photovoltaics and photosynthesis [10] (see Figure 1).Figure 1
Dependence graph of photo-activated TiO2 materials applications. The flow goes from the top to the bottom direction.However, the large bandgap of TiO2 (3.2 eV for anatase and 3 eV for rutile) limits its light absorption only to the UV region [11]. Thus, pure TiO2 works as a photocatalytic material under UV light (4-5% of solar light), but it has very low photocatalytic activity in visible light (45% of solar spectrum). Some efforts have been made to overcome this limitation. Some aspects have been identified as essential to resolve the issue such as to tailor TiO2 bulk/surface electronic structures and the interfaces in order to tune surface band-bending, surface state distribution, and charge separation, which could significantly influence TiO2 photocatalysis response in the visible spectral range. The main requirements are (1) a high surface/volume ratio and a controlled anatase-rutile ratio to provide a large number of active sites for the degradation reaction and (2) shifting the absorption limit of the material in the visible range, searching for an increase in reaction rate of photocatalysis and hydrogen production.Doping appears as a good alternative for changing the activity of TiO2 catalysts through the optoelectrical modification of this material by the introduction of dopants with different energy levels between the conduction and valence bands. The applied dopants can be (1) noble metals (such as Ag, Au, Pd, and Pt), which absorb the visible light due to the surface plasmon resonance, but the high cost associated with these materials should be considered a disadvantage [12]; (2) transition metals cheaper than noble metals, but their leaching behavior leads to the fast deactivation of the catalyst and constitutes a second source of pollution [13]; and (3) nonmetals (N, B, S, F, and C) able to extend optical absorption of TiO2 to the visible light region and then to improve visible-light-driven photocatalytic processes [14, 15]. Among the above-mentioned nonmetals, the most suitable and commonly used is nitrogen.Nitrogen, as sulfur and fluorine species, is an anionic dopant which confers greater stability to the catalyst with respect to the conventional transition-metal dopants and also determines a significant red shift of the band gap into the visible range. According to theoretical modelling [16], the p-orbitals of the nitrogen dopant extensively overlapped, favouring the transfer of photogenerated charge carriers to the TiO2 surface, in turn increasing its photocatalytic activity [17]. It was proven that both in the anatase and rutile phases of TiO2, the N2p states were located just above the top of the O2p valence band, which means a red shift of the absorption band edge to the visible region [18].Despite the potential, data about the main changes provided by nitrogen doping in TiO2 is not well established. Moreover, for large scale usage of TiO2-xNx nanomaterials in all the solar radiation ranges, none of the results actually reached are satisfactory due to their low nitrogen/oxygen content, low chemical-physical stability, and increased carrier trapping.There are multiple and assorted methods to prepare N-TiO2 catalysts. Physical vapor deposition (PVD), reactive sputtering, cathodic arc deposition, plasma-gas reaction, and Chemical Vapor Deposition (CVD) are the common methods used to deposit N-doped titania films. However, all these techniques allow the deposition of low level N-doped titania with micron-sized structures only at high vacuum conditions (10-8-10-9 Pa) and at high temperature (1200-1500°C) to avoid sample reoxidation. The methods based on plasma-gas phase reactions with the use of TiN powders seem to be a good and low cost alternative to obtain films with a small particle size (about 10 nm). However, these samples show a high oxygen content (ca. 15–20 at.%) [19]. Recently TiO2, loading a different percentage of nitrogen, was prepared by nitridation of a nano-TiO2 powder in a mixed ammonia/argon atmosphere at a range of temperatures from 400 to 1100°C [17]. According to the results obtained by Zhang et al. [20], the samples prepared at 700°C are oxygen deficient, which may be partly responsible for the shifting band gap and for the significant photocatalytic activity. On the other hand, nanocolloid production generally involves the use of surfactants and derivatives which cause secondary pollution to the environment.For all these reasons, further studies will be useful mainly to (1) clarify whether oxygen deficiency has a bigger effect on photocatalytic activity than N-doping at low levels, (2) give a systematic and complete characterization of the chemical-morphological and optical properties of the synthesized N-TiO2-x nanomaterials, and (3) identify green methods and define a synthesis protocol in order to produce nanocolloids. This latter should be usable directly in the liquid phase in an innovative photocatalytic device, with a high degradation time (even in extreme conditions).In this work, we presented and discussed the results obtained using the potentiality of the pulsed laser ablation in liquid (PLAL) technique to prepare N-TiO2-x nanocolloids. The syntheses were carried out in water to favour the formation of (Ti-O-N), (−NH2), NO2−, N2, NHx, and (−OH) species, inducing their incorporation into the TiO2 lattice as nitride through dehydration. To this aim, the optimal PLAL deposition parameters (i.e., laser fluence and irradiation time) were found as well as the optimal composition of the targets (TiO2 mixed to TiN powders or TiN rod purchased from Matek Srl). PLAL processes were performed in ambient condition (room temperature) using the water as solvent, with the advantage to obtain nanocolloids, without by-products, suitable for mechanical deposition on photoanode materials or to be incorporated in integrated solar water-splitting devices.All the synthesized colloids were characterized by scanning transmission electron microscopy (STEM), X-ray photoelectron (XPS), and conventional optical spectroscopies, providing complementary information which allows drawing a picture of the compositional, morphological, and optical properties of the nanocomposites, constituting the starting point for their successive photocatalysis applications which require moderate operating temperatures and limited energy consumptions.
## 2. Experimental Section
TiO2-xNx powders, pressed into a disk at room temperature, were prepared starting from powders of TiN and TiO2 (P25), mixed at the TiN/TiO2 mass ratios of 75/25, 50/50, and 25/75. Then, the compacts were maintained in a furnace at around 250°C for 1 hour. Pulsed laser ablation in liquid (PLAL) processes of the pressed powders as well as of commercial TiN and TiO2 rod targets (synthesized by Matek Srl at 1200°C) were carried out in deionized water (H2O). The targets were irradiated at the laser fluence of 0.5 J/cm2 for an irradiation time of 15 min (samples labelled TION3-5 and TION1P-5P-17P-12P) and of 1.5 J/cm2 for 30 min (TION4), by the 532 nm radiation coming from a Nd:YAG laser source, operating at the repetition rate of 10 Hz and at the pulse width of 6 ns. The scheme of the PLAL setup and an overview of the sample set are shown in Figure 2.Figure 2
Scheme of PLAL setup and synthesis parameters for each adopted target.Scanning transmission electron microscopy (STEM) images were acquired using a Zeiss electronic microscope which operates at an accelerating voltage of 30 kV. Samples for the STEM analysis were prepared by dropping a suspension of the sonicated colloids on a 400 mesh holey-carbon support sputter-coated with chromium.A PerkinElmer (Lambda 750) spectrometer, working in the 300-900 nm range, was used to collect optical absorbance spectra.The crystalline phase of the oxide was also investigated by analyzing Raman scattering data. Raman spectra have been excited with the 532 and 638 nm diode laser lines mounted in the XploRA spectrometer coupled with an Olympus microscope. Spectra have been collected with a 50x objective (spot size of about 2μm) and a Charged Coupled Device (CCD) used as a sensor. An acquisition time of 80 s granted a sufficient S/N ratio.The chemical bonding states and the relative atomic content in the nanocomposites were investigated by X-ray Photoelectron Spectroscopy (XPS), using the Thermo Scientific K-Alpha system equipped with a monochromatic Al-Kα source (1486.6 eV) and operating with a pass energy of 50 eV in the CAE mode.Some aqueous solutions of methyl orange (MO) and methylene blue (MB) (Sigma-Aldrich) were prepared by dissolving the analytical grade dyes in the synthesized colloids at a1.5·10−5M concentration.MO and MB were used as probe molecules for a first evaluation of the photocatalytic activities of N-TiO2 nanostructures. The reaction was conducted in 3 ml of aqueous solution containing the dye, previously maintained in a beaker for 30 min at a temperature of about 10°C. The photocatalytic reaction was carried out under stirring. 0.5 mg of catalyst was dispersed in 3 ml of dye aqueous solution placed in an ice bath; in this way, the temperature of aqueous dispersion was maintained at around 14±2°C.A 40 W Hg lamp (for UV irradiation) and a 450 W xenon lamp (as a visible light source blocking UV radiation by a 400 nm glass filter) were used as light sources placed at a distance of about 15 cm. Prior to irradiation, the dye catalyst suspensions were kept in the dark for 30 min to ensure an adsorption/desorption equilibrium. Then, the photodecolourization of MO and MB was studied.Analytical samples were filtered through a 0.2μm Millipore® filter to remove the solid, at well-defined time intervals during the irradiation, and placed into a 0.35 ml microquartz cuvette. Then, the residual dye concentrations in the filtrates were analyzed by UV-visible spectrophotometer (PerkinElmer 750) at maximum absorption wavelengths (λmax) of 464 and 664 nm for MO and MB, respectively. Direct photolysis decolourization of the respective dye was estimated by performing blank experiments.
## 3. Results and Discussion
### 3.1. Sample Characterization
In Figure3 are shown representative STEM images of the samples obtained ablating in water targets of different nature. Specifically, the colloids, obtained ablating the (25/75) TiN/TiO2 powder targets, show a porous morphology with some spherical nanostructures with a mean diameter of about 50 nm (Figure 3(a)). It is to be noted that the observation of perfectly rounded submicrometer particles, probably associated with TiO2 species, is in agreement with what was observed by Felice et al. [21]. On the other hand, a high density of nanoparticles with a spherical shape and size mainly below 30 nm characterizes the colloids prepared ablating the high purity (99.99%) commercial TiN rod target (Figure 3(c)). An analogous morphology is shown by the colloids prepared ablating the TiN powder target (Figure 3(b)). More details can be observed from images d–h collected for the samples obtained ablating the (25/75) TiN/TiO2 powder targets and the TiN rod and powder targets.Figure 3
STEM images of the samples obtained ablating the (25/75) TiN/TiO2 powder targets (a, d, e), the TiN powder target (b, f), and the high purity (99.99%) commercial TiN rod target (c, g, h).
(a)(b)(c)(d)(e)(f)(g)(h)The sample obtained from the (25/75) mixed TiN/TiO2 powders show Raman features typical of the anatase-rich TiO2 material [6]. It is important to highlight that first-order Raman features of TiN (at 225 cm-1 (TA), 310 cm-1 (LA), and 540 cm-1(TO)) are almost absent, suggesting that nitrogen could be incorporated as a defect in the crystalline TiO2 lattice. Samples, obtained from TiN powder (red line) and rod (blue line) targets, showed very similar Raman spectra; in this case, TiN vibrational features are well observable (see Figure 4(a)) as indicated by the pronounced peak at about 550 cm-1 related to the TiN-TO mode [22]. Moreover, we observe that the Eg (associated to the anatase phase) signal below 200 cm-1 is totally absent and that the intensity ratio between the observed peaks at 200 and 290 cm-1 is very similar to that of a possible formation of a rutile TiO2 phase. Unfortunately, TiN and rutile features overlapped in this region, so a correct attribution for the rutile is not possible exclusively from Raman analyses. All this evidence indicates a tendency towards an anatase-rutile conversion and/or an oxygen replacement by nitrogen with the formation of Ti-N bonds [22]. Interstitial nitrogen species are expected as a result of the ablation of a TiN target in water.Figure 4
(a) Raman and (b) optical absorbance spectra of the synthesized samples.
(a)(b)In Figure4(b) are shown the optical absorbance spectra of the synthesized nanocolloids. We observe that (1) the colloid obtained by a TiN rod target is transparent (over 90%) in the visible range with a sharp absorption edge at about 350 nm, (2) a broad band at around 420 nm characterizes the sample prepared from the TiO2 powder target, and (3) a slight blue shift is evident in the colloids prepared using the pressed and sintered target with a (75/25) TiN/TiO2 mass ratio; for these samples, the 420 nm band is totally absent, while a significant visible light absorption contribution up to 600 nm is evident, probably due to the electronic transition from the localized N doping level to the conduction band of TiO2 (see also the scheme reported in Figure 5).Figure 5
Schematic diagram showing the valence and conduction bands of N-doped TiO2.The incorporation of nitrogen into the TiO2 lattice leads to the formation of a new midgap energy state, i.e., the N2p band above the O2p valence band. So, upon a visible light irradiation, the electrons can migrate from the valence band to the conduction band (Figure 5) and from here the expected visible light activity of N-dopedTiO2 or TiO2-xNx materials (see Catalytic Activities). Nitrogen can replace one or more oxygen atoms (“substitutional doping”), or nitrogen can be positioned in interstitial TiO2 sites (“interstitial doping”). In both cases, as shown in Figure 5, N doping leads to a change in the electronic behavior of the nanoparticle due to a change in the electronic band structures and/or a decrease of electron-hole recombination [23].XPS analysis allows investigating the surface chemical composition and bonding configurations of our samples, in which it is known that the surface chemical coordination greatly influences the catalytic response [24]. In Figures 6(a)–6(c) are shown representative Ti2p and N1s deconvoluted profiles, while the chemical atomic percentage of the detected species and the relative surface bonding configurations are reported in Table 1. Two different Ti2p profiles characterize our samples: those obtained starting from the TiN rod target (Figure 6(a)) show a broad band whose features are ascribed to the titanium nitride, the titanium dioxide (TiO2), and the intermediate phase of titanium oxynitride [25, 26]. Otherwise, in the samples obtained by the TiN powder (Figure 6(b)), narrower profiles are obtained and the binding energy of the Ti2p3/2 peak is brought closer to 458.5 eV (typical of TiO2 compound), while the binding energies of the other phases still fall within the possible ranges. Interestingly, no resolved N1s signal was collected from the powder targets while the N1s profile is well structured and defined for samples obtained from the rod targets (Figure 6(c)). The main components are located at around 396 and in the 397-400 eV range. These features are ascribed to the titanium oxynitride phase and to the nitrogen in substitutional and interstitial positions [26–31]. The NHx, NO/NO2, and NO3− contributions are generally reported at a binding energy higher than 400 eV [29–31] but, in our case, are less pronounced (see Figures 6(c) and 6(d)).Figure 6
Ti2p (a, b) deconvoluted profiles of the samples obtained from the TiN rod and TiN powder targets, respectively. We outline that all the samples obtained from the mixed powders show Ti2p line shapes similar to those of the sample starting from the TiN powder. The N1s deconvoluted profile of the sample obtained starting from the TiN rod target (c) and a scheme of the potential nitrogen allocation into the TiO2 structure (d).Table 1
Atomic surface chemical composition and bonding fraction estimated by the deconvoluted XPS spectra.
SampleChemical composition (%)Bonding configurations (%)Ti2pN1sN (%)Ti (%)O (%)Ti-NTi-O-NTi-O2N-Ti-ONsubst.Nint.NO/NO2TION1p1.128.870.10.86.492.8——100—TION5p0.728.471.00.53.596.0——100—TION12p5.923.870.30.93.495.7——100—TION17p4.619.875.60.03.796.3——100—TION312.228.859.115.526.058.567.418.59.54.6TION417.824.158.117.829.153.159.726.610.72.9TION514.825.759.617.430.152.665.522.09.92.7
### 3.2. Catalytic Activities
All the photocatalytic reactions were undertaken in air as the photobleaching of MB is irreversible in an oxygen-saturated aqueous solution such as ours, and in an ice bath to avoid degradation effects due to light irradiation-induced heating. The photodegradation was monitored by recording UV-visible extinction spectra as a function of light irradiation exposure time. The percentage of MB decolourization under ultraviolet and visible radiation for the synthesized and TiO2 reference samples is shown in Figure 7. Under UV and visible irradiation, all the produced nanostructures show a photocatalytic activity towards the degradation of methylene blue (MB) dye molecule. However, the response is comparable in all the samples under UV irradiation while, under the visible lamp, the estimated percentages differ by about 30%. In fact, for the samples obtained by ablating TiN powder and TiN/TiO2-mixed powder in 75/25 ratio, MB decolourization is about 45% but increases in the samples obtained from the TiN rod or from the TiN/TiO2-mixed powders at the 25/75 ratio. Photocatalytic decolourization behavior of MB dye (during visible irradiation, over the 1 h time frame of the experiment) seems to be influenced by the amount of N, Ti, and O and their bonding coordination and by the increasing absorption in the visible light region [32].Figure 7
Photocatalytic activity towards the methylene blue (MB) dye molecule under UV and visible irradiation (60 min exposure time).In Figure8 is shown the percentage of MO decolourization under UV and visible lamp for the synthesized and reference samples. MO is an azo dye characterized by a N=N linkage, which is anionic in aqueous media and absorbs light in the visible region (450–550 nm) with an absorption maxima at 464 nm [33]. The samples obtained by TiN rod or TiN powder targets as well as those in which the TiN fraction is higher than the TiO2 one (75/25 ratio) are the most active nanocomposites, both under UV and visible irradiation. For the colloids going from the TiN rod, we observe that, in the first 20 min, 50% and 60% of the dye were removed under UV and visible light, respectively, while only about 10% of the dye is removed for the TiO2 colloid. Moreover, 70% of MO decolourization occurs within 80 min under visible irradiation while the other samples, for which Ti-O chemical bonds dominate in comparison to TiN/Ti-O-N ones, show significantly less efficiency in the same range of time.Figure 8
Photocatalytic activity towards the methyl orange (MO) dye molecule under UV and visible irradiation (60 min exposure time).
(a)(b)In order to have a quantitative estimation of the photocatalytic activity, we carried out a simple fitting procedure already adopted to test photodegradation efficiency of MB using zinc oxide nanocolloids, prepared by picosecond pulsed laser ablation, as catalysts [34]. If a semilogarithm scale of the relative absorbance as function of irradiation time is employed, it is possible to obtain a pseudoorder constant rate for all analyzed samples (see Table 2). In detail, by following the equation
(1)lnAA0=−kct,with A0 and At as the starting absorbance and the absorbance at the time t, respectively, a linear fitting procedure, limited to the first 30 minutes of irradiation, is evidence that both dyes degrade faster under the visible source and that the highest kc value is obtained with nanocatalysts from the TiN rod target.Table 2
Photodegradation rate constants of MB and MO with different catalysts usinglnA/A0=−kct as the fitting equation model.
Samplekc (min-1)MBMOUV lampVisible lampUV lampVisible lampTION5 (TiN rod target)-0.0118-0.0211-0.0333-0.0426TION1P (TiN powder target)-0.0129-0.0126-0.0300-0.0326TION5P (TiN/TiO2 (25/75) target)-0.0103-0.0242-0.0043-0.0176TION12P (TiN/TiO2 (75/25) target)-0.0139-0.0113-0.0153-0.0158TiO2 target-0.0091-0.0211-0.0026-0.0046Hence, on the basis of the obtained results, we suggest that the sample obtained from TiN characterized by the higher N content could be photosensitized by the “N-doping.” In this case, oxygen vacancies promoted the charge recombination, resulting in weak reduction power. Otherwise, the high activity of the sample synthesized from the TiN/TiO2 mixed powder in 25/75 ratio was attributed to the abundance of hydroxy groups in its porous structure (see STEM image), which provided more active sites for the degradation reaction as well as to the high available surface/volume ratio of the catalyst, since this sample shows a porous structure (Figure 3(a)). Nevertheless, no clear correlation between the MB or MO photocatalytic activity and the chemical-structural properties of the synthesized nanocolloids is found, since dye decolourization is also affected by the ionic nature, structure and stability, adsorption, and orientation of the dye molecules on the surface of the catalyst [35, 36]. The synthesized N-TiO2 nanocatalysts should be further investigated in depth to improve their catalytic response in the visible spectral region by a more rational and environment-friendly PLAL approach.
## 3.1. Sample Characterization
In Figure3 are shown representative STEM images of the samples obtained ablating in water targets of different nature. Specifically, the colloids, obtained ablating the (25/75) TiN/TiO2 powder targets, show a porous morphology with some spherical nanostructures with a mean diameter of about 50 nm (Figure 3(a)). It is to be noted that the observation of perfectly rounded submicrometer particles, probably associated with TiO2 species, is in agreement with what was observed by Felice et al. [21]. On the other hand, a high density of nanoparticles with a spherical shape and size mainly below 30 nm characterizes the colloids prepared ablating the high purity (99.99%) commercial TiN rod target (Figure 3(c)). An analogous morphology is shown by the colloids prepared ablating the TiN powder target (Figure 3(b)). More details can be observed from images d–h collected for the samples obtained ablating the (25/75) TiN/TiO2 powder targets and the TiN rod and powder targets.Figure 3
STEM images of the samples obtained ablating the (25/75) TiN/TiO2 powder targets (a, d, e), the TiN powder target (b, f), and the high purity (99.99%) commercial TiN rod target (c, g, h).
(a)(b)(c)(d)(e)(f)(g)(h)The sample obtained from the (25/75) mixed TiN/TiO2 powders show Raman features typical of the anatase-rich TiO2 material [6]. It is important to highlight that first-order Raman features of TiN (at 225 cm-1 (TA), 310 cm-1 (LA), and 540 cm-1(TO)) are almost absent, suggesting that nitrogen could be incorporated as a defect in the crystalline TiO2 lattice. Samples, obtained from TiN powder (red line) and rod (blue line) targets, showed very similar Raman spectra; in this case, TiN vibrational features are well observable (see Figure 4(a)) as indicated by the pronounced peak at about 550 cm-1 related to the TiN-TO mode [22]. Moreover, we observe that the Eg (associated to the anatase phase) signal below 200 cm-1 is totally absent and that the intensity ratio between the observed peaks at 200 and 290 cm-1 is very similar to that of a possible formation of a rutile TiO2 phase. Unfortunately, TiN and rutile features overlapped in this region, so a correct attribution for the rutile is not possible exclusively from Raman analyses. All this evidence indicates a tendency towards an anatase-rutile conversion and/or an oxygen replacement by nitrogen with the formation of Ti-N bonds [22]. Interstitial nitrogen species are expected as a result of the ablation of a TiN target in water.Figure 4
(a) Raman and (b) optical absorbance spectra of the synthesized samples.
(a)(b)In Figure4(b) are shown the optical absorbance spectra of the synthesized nanocolloids. We observe that (1) the colloid obtained by a TiN rod target is transparent (over 90%) in the visible range with a sharp absorption edge at about 350 nm, (2) a broad band at around 420 nm characterizes the sample prepared from the TiO2 powder target, and (3) a slight blue shift is evident in the colloids prepared using the pressed and sintered target with a (75/25) TiN/TiO2 mass ratio; for these samples, the 420 nm band is totally absent, while a significant visible light absorption contribution up to 600 nm is evident, probably due to the electronic transition from the localized N doping level to the conduction band of TiO2 (see also the scheme reported in Figure 5).Figure 5
Schematic diagram showing the valence and conduction bands of N-doped TiO2.The incorporation of nitrogen into the TiO2 lattice leads to the formation of a new midgap energy state, i.e., the N2p band above the O2p valence band. So, upon a visible light irradiation, the electrons can migrate from the valence band to the conduction band (Figure 5) and from here the expected visible light activity of N-dopedTiO2 or TiO2-xNx materials (see Catalytic Activities). Nitrogen can replace one or more oxygen atoms (“substitutional doping”), or nitrogen can be positioned in interstitial TiO2 sites (“interstitial doping”). In both cases, as shown in Figure 5, N doping leads to a change in the electronic behavior of the nanoparticle due to a change in the electronic band structures and/or a decrease of electron-hole recombination [23].XPS analysis allows investigating the surface chemical composition and bonding configurations of our samples, in which it is known that the surface chemical coordination greatly influences the catalytic response [24]. In Figures 6(a)–6(c) are shown representative Ti2p and N1s deconvoluted profiles, while the chemical atomic percentage of the detected species and the relative surface bonding configurations are reported in Table 1. Two different Ti2p profiles characterize our samples: those obtained starting from the TiN rod target (Figure 6(a)) show a broad band whose features are ascribed to the titanium nitride, the titanium dioxide (TiO2), and the intermediate phase of titanium oxynitride [25, 26]. Otherwise, in the samples obtained by the TiN powder (Figure 6(b)), narrower profiles are obtained and the binding energy of the Ti2p3/2 peak is brought closer to 458.5 eV (typical of TiO2 compound), while the binding energies of the other phases still fall within the possible ranges. Interestingly, no resolved N1s signal was collected from the powder targets while the N1s profile is well structured and defined for samples obtained from the rod targets (Figure 6(c)). The main components are located at around 396 and in the 397-400 eV range. These features are ascribed to the titanium oxynitride phase and to the nitrogen in substitutional and interstitial positions [26–31]. The NHx, NO/NO2, and NO3− contributions are generally reported at a binding energy higher than 400 eV [29–31] but, in our case, are less pronounced (see Figures 6(c) and 6(d)).Figure 6
Ti2p (a, b) deconvoluted profiles of the samples obtained from the TiN rod and TiN powder targets, respectively. We outline that all the samples obtained from the mixed powders show Ti2p line shapes similar to those of the sample starting from the TiN powder. The N1s deconvoluted profile of the sample obtained starting from the TiN rod target (c) and a scheme of the potential nitrogen allocation into the TiO2 structure (d).Table 1
Atomic surface chemical composition and bonding fraction estimated by the deconvoluted XPS spectra.
SampleChemical composition (%)Bonding configurations (%)Ti2pN1sN (%)Ti (%)O (%)Ti-NTi-O-NTi-O2N-Ti-ONsubst.Nint.NO/NO2TION1p1.128.870.10.86.492.8——100—TION5p0.728.471.00.53.596.0——100—TION12p5.923.870.30.93.495.7——100—TION17p4.619.875.60.03.796.3——100—TION312.228.859.115.526.058.567.418.59.54.6TION417.824.158.117.829.153.159.726.610.72.9TION514.825.759.617.430.152.665.522.09.92.7
## 3.2. Catalytic Activities
All the photocatalytic reactions were undertaken in air as the photobleaching of MB is irreversible in an oxygen-saturated aqueous solution such as ours, and in an ice bath to avoid degradation effects due to light irradiation-induced heating. The photodegradation was monitored by recording UV-visible extinction spectra as a function of light irradiation exposure time. The percentage of MB decolourization under ultraviolet and visible radiation for the synthesized and TiO2 reference samples is shown in Figure 7. Under UV and visible irradiation, all the produced nanostructures show a photocatalytic activity towards the degradation of methylene blue (MB) dye molecule. However, the response is comparable in all the samples under UV irradiation while, under the visible lamp, the estimated percentages differ by about 30%. In fact, for the samples obtained by ablating TiN powder and TiN/TiO2-mixed powder in 75/25 ratio, MB decolourization is about 45% but increases in the samples obtained from the TiN rod or from the TiN/TiO2-mixed powders at the 25/75 ratio. Photocatalytic decolourization behavior of MB dye (during visible irradiation, over the 1 h time frame of the experiment) seems to be influenced by the amount of N, Ti, and O and their bonding coordination and by the increasing absorption in the visible light region [32].Figure 7
Photocatalytic activity towards the methylene blue (MB) dye molecule under UV and visible irradiation (60 min exposure time).In Figure8 is shown the percentage of MO decolourization under UV and visible lamp for the synthesized and reference samples. MO is an azo dye characterized by a N=N linkage, which is anionic in aqueous media and absorbs light in the visible region (450–550 nm) with an absorption maxima at 464 nm [33]. The samples obtained by TiN rod or TiN powder targets as well as those in which the TiN fraction is higher than the TiO2 one (75/25 ratio) are the most active nanocomposites, both under UV and visible irradiation. For the colloids going from the TiN rod, we observe that, in the first 20 min, 50% and 60% of the dye were removed under UV and visible light, respectively, while only about 10% of the dye is removed for the TiO2 colloid. Moreover, 70% of MO decolourization occurs within 80 min under visible irradiation while the other samples, for which Ti-O chemical bonds dominate in comparison to TiN/Ti-O-N ones, show significantly less efficiency in the same range of time.Figure 8
Photocatalytic activity towards the methyl orange (MO) dye molecule under UV and visible irradiation (60 min exposure time).
(a)(b)In order to have a quantitative estimation of the photocatalytic activity, we carried out a simple fitting procedure already adopted to test photodegradation efficiency of MB using zinc oxide nanocolloids, prepared by picosecond pulsed laser ablation, as catalysts [34]. If a semilogarithm scale of the relative absorbance as function of irradiation time is employed, it is possible to obtain a pseudoorder constant rate for all analyzed samples (see Table 2). In detail, by following the equation
(1)lnAA0=−kct,with A0 and At as the starting absorbance and the absorbance at the time t, respectively, a linear fitting procedure, limited to the first 30 minutes of irradiation, is evidence that both dyes degrade faster under the visible source and that the highest kc value is obtained with nanocatalysts from the TiN rod target.Table 2
Photodegradation rate constants of MB and MO with different catalysts usinglnA/A0=−kct as the fitting equation model.
Samplekc (min-1)MBMOUV lampVisible lampUV lampVisible lampTION5 (TiN rod target)-0.0118-0.0211-0.0333-0.0426TION1P (TiN powder target)-0.0129-0.0126-0.0300-0.0326TION5P (TiN/TiO2 (25/75) target)-0.0103-0.0242-0.0043-0.0176TION12P (TiN/TiO2 (75/25) target)-0.0139-0.0113-0.0153-0.0158TiO2 target-0.0091-0.0211-0.0026-0.0046Hence, on the basis of the obtained results, we suggest that the sample obtained from TiN characterized by the higher N content could be photosensitized by the “N-doping.” In this case, oxygen vacancies promoted the charge recombination, resulting in weak reduction power. Otherwise, the high activity of the sample synthesized from the TiN/TiO2 mixed powder in 25/75 ratio was attributed to the abundance of hydroxy groups in its porous structure (see STEM image), which provided more active sites for the degradation reaction as well as to the high available surface/volume ratio of the catalyst, since this sample shows a porous structure (Figure 3(a)). Nevertheless, no clear correlation between the MB or MO photocatalytic activity and the chemical-structural properties of the synthesized nanocolloids is found, since dye decolourization is also affected by the ionic nature, structure and stability, adsorption, and orientation of the dye molecules on the surface of the catalyst [35, 36]. The synthesized N-TiO2 nanocatalysts should be further investigated in depth to improve their catalytic response in the visible spectral region by a more rational and environment-friendly PLAL approach.
## 4. Conclusions
In this work, the potentiality of the pulsed laser ablation in liquid (PLAL) technique to prepare N-TiO2-x nanocolloids, suitable for mechanical deposition on photoanode materials by conventional spraying technique, or to be incorporated in integrated solar water-splitting devices was reported. Synthesis processes were carried out in water, using targets with different nature and composition, to favour the formation of (Ti-O-N), (−NH2), NO2−, N2, NHx, and (−OH) species, and the nitrogen incorporation into the TiO2 lattice as nitride through dehydration. PLAL processes were performed in ambient condition (room temperature) using the water as solvent, without the need to provide high temperature (T) and pressures (P), thus preparing nanocolloids, ready to use without by-products. The observed photoactivity response of the synthesized nanocatalysts is explained in terms of their surface composition and bonding configurations and optical and morphological properties, which has been tuned changing the incorporation of nitrogen into the TiO2 lattice, beneficial for potentially separating the photogenerated carriers in space.
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*Source: 2901516-2020-06-11.xml* | 2020 |
# Corrigendum to “Indicators of Quality of Clinical Care for Type 2 Diabetes Patients in Primary Health Care Centers in Qatar: A Retrospective Analysis”
**Authors:** Saleh Attal; Mohamed H. Mahmoud; Muna Taher Aseel; Ady Candra; Paul Amuna; Mohamed Elnagmy; Mostafa Abdallah; Nahed Ismail; Ahmed Hanfy; Dia Albaw; Abdulsalam Albashir; Hisham Elmahdi
**Journal:** International Journal of Endocrinology
(2020)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2020/2901538
---
## Body
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*Source: 2901538-2020-10-31.xml* | 2901538-2020-10-31_2901538-2020-10-31.md | 584 | Corrigendum to “Indicators of Quality of Clinical Care for Type 2 Diabetes Patients in Primary Health Care Centers in Qatar: A Retrospective Analysis” | Saleh Attal; Mohamed H. Mahmoud; Muna Taher Aseel; Ady Candra; Paul Amuna; Mohamed Elnagmy; Mostafa Abdallah; Nahed Ismail; Ahmed Hanfy; Dia Albaw; Abdulsalam Albashir; Hisham Elmahdi | International Journal of Endocrinology
(2020) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2020/2901538 | 2901538-2020-10-31.xml | ---
## Body
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*Source: 2901538-2020-10-31.xml* | 2020 |
# Investigating Peer Instruction: How the Initial Voting Session Affects Students' Experiences of Group Discussion
**Authors:** Kjetil L. Nielsen; Gabrielle Hansen-Nygård; John B. Stav
**Journal:** ISRN Education
(2012)
**Publisher:** International Scholarly Research Network
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.5402/2012/290157
---
## Abstract
Peer Instruction is a popular method of implementation when using Student Response Systems (SRS) in classroom teaching. The students engage in peer discussion to solve conceptual multiple choice problems. Before discussion, students are given time to think and give individual responses with a voting device. In this paper, we investigate how this initial voting session affects students’ experiences of the following discussion. The data is based on student interviews which were analyzed using analytical tools from grounded theory. The students emphasize the individual thinking period as crucial for constructing explanations, argumentation, and participation during discussions, and hence for facilitating learning. However, displaying the results from the initial vote can be devastating for the quality of the discussions, especially when there is a clear majority for a specific alternative. These findings are discussed in light of recent quantitative studies on Peer Instruction.
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## Body
## 1. Introduction
The traditional one-way teacher style of lecturing can be effective when delivering factual content, but it is not as effective for facilitating cognitive skills [1, 2]. Engaging students in active-learning activities can be an important factor for mastering skills such as critical thinking and problem solving [1, 3], skills that are often lacking in novice science students [4]. Although such skills are vital to evaluate scientific evidence and theories, students also have to be able to generate and present explanations and arguments for their evaluations, that is, to be fluent in the scientific language [5]. Novice students also suffer in that they are often unable to put into words, or at least scientific words, how they approach the use of theories to solve problems. Engaging students in peer discussions can challenge them to generate explanations and convincing arguments for their solution and in this way also facilitate deeper understanding of the scientific phenomena [5].One way of engaging students in active-learning activities is to use a Student Response System (SRS). Such systems are often used during the lecture to present students with multiple choice questions, which they will discuss with their peers in small groups before answering with a voting device [6–10]. The result from the voting session is displayed in the form of a histogram which can give the teacher an indication of the level of understanding among the students and if they are able to follow the lecture [10, 11]. SRS use in classroom teaching has been shown to increase learning [12–15] including increased conceptual understanding in physics courses [12, 16, 17].Although SRS can be an outstanding tool for facilitating peer discussion, different choices of implementation can have a high impact on the quality of the discussions. For instance, giving credits for SRS participation has been shown to increase the overall participation in the class [18]. However, in a study by James [19], the researcher found that if each individual student was “punished” for voting incorrectly, that is, that he/she was not given as much credit as voting correctly, the group discussions tended to be dominated by students with greater knowledge while other students remained passive. If the students were only credited for participation, they would be more inclined to participate and explore different explanations and ideas.One popular methodological implementation of SRS is with the Peer Instruction technique [17]. During the lecture students are presented with a problem, often where conceptual ideas are in focus, to challenge their knowledge about the subject as opposed to simply looking up the answer in the textbook. Students are given time to think on their own for about 2-3 minutes and answer individually before they are encouraged to engage in discussion with nearby students. The discussions are concluded with a revote and an explanation by the teacher. Dufresne et al. [11] describe a similar method, but where the initial voting session is omitted. Instead, students start discussing immediately after the question is presented and the group discussions are concluded with a class-wide discussion instead of teacher explanation.In a comparative study between Peer Instruction and the method described by Dufresne et al. [11], students felt that without the initial voting session they would be more inclined to be passive in group discussions and that the discussions would be more likely to be dominated by confident and/or “stronger” students [20]. Students reported that they used the initial voting session to formulate their own answer, which they in turn could use in the following discussion, and that they therefore would be more likely to engage in dialogue and defend their views. The researchers argued that the lack of an individual thinking period before discussion would result in less cognitive conflict at the start of discussion and thus students would be more inclined to accept dominant explanations.There have been several recent quantitative studies on different aspects of Peer Instruction [21–24]. Previous studies have shown that the amount of correct votes increases after the discussion [16, 25]. One interpretation of these results could be that students choose the same as stronger students and not that they change their answer as a result of learning. In a study by Smith et al. [23], the researchers found evidence that the increase of correct votes is indeed a result of increased learning and not primarily due to the influence of other students. Even in groups where no students initially had the right answer, they observed an increase in learning. Smith et al. [24] showed that both the peer discussion and teacher explanation are important for facilitating learning with Peer Instruction. Excluding either the discussion or teacher explanation showed less learning than the combination of both.A common practice when using Peer Instruction is to show students the results from the initial voting session prior to the group discussion [26]. Perez et al. [22] found that the probability of students switching to the alternative with the majority of votes increased by 30% if the results were displayed to the students. The researchers provided several interpretations for these findings. A clear majority could function as a stimulus for focused discussions and students might discover flaws in their original reasoning by trying to identify why most students chose one particular alternative. Another interpretation was that students simply switched to this alternative based on the consensus of nearby students. Confidence in their own choice has been shown to be significantly higher if students can see that they initially voted for an alternative in the majority [21]. This was persistent whether the alternative was correct or not.The study in this paper was a part of EU-cofounded projects (EduMecca, Do-it, Done-it and Global-SRS) at Sør-Trøndelag University College in Trondheim, Norway. One goal of these projects was to develop an online SRS designed for effective classroom teaching, where students can use their own mobile device, such as smart-phones, as a voting device as compared to the traditional “clickers”. As well as evaluating the system from a technical point of view, we also investigated different methodological implementations. More information about these projects can be found at our web page (http://www.histproject.no/).The inspiration for this study was the findings of Nicol and Boyle [20]. We wanted to go deeper into, and try to examine, the effects of the initial voting session (and thinking period) with Peer Instruction. To do so, we divided the study into two parts: a quantitative part based on survey data and video of students engaged in peer discussion during class and a pure qualitative part based on in-depth analysis of student interviews. In this paper we focus on the interviews and investigate students’ experiences regarding use of Peer Instruction and the effect of the initial voting session. The analysis of the video material is ongoing and will be presented at a later date. The paper starts with a description of study design and analysis methods followed by a presentation of the results. We conclude with a discussion of our findings; in particular, we discuss the results in light of the recent quantitative studies on Peer Instruction.
## 2. Method
The study was conducted in an introductory physics course for preparatory engineering students. The lectures usually consisted of 2 × 45 min. sessions generally constructed so that the first 45 min. dealt with new theory while the second focused on practical work, mainly problem solving. Four parallel classes with of a total of seven teachers (three classes used two different teachers) used SRS for eight weeks. One of the authors (K. L. Nielsen) was the teacher of the class with a single teacher. The second author (G. Hansen-Nygård) was present in lectures where SRS was used to function as an observer. Each class consisted of 50–70 students, the majority being male students. The theoretical part of the lectures was traditional teacher-style lectures (using digital blackboards) except that the teacher would present the students with 1–4 quizzes consisting of conceptual multiple choice questions. Each student borrowed an Apple iPod Touch which was used as a voting device. When SRS was used, the iPods were handed out at the beginning of the lecture and collected at the end. SRS was used in two of a total of three lectures each week due to some lectures running parallel timetables. To minimize the amount of variables in our data, all classes used the same set of multiple choice questions. We prepared around 50 concept questions which the teachers used in the course of the study.In order to investigate the effects of the initial thinking period with Peer Instruction, we also used another method which we called “Classic” as the reference. This method was similar to Peer Instruction apart from the initial voting session (and thinking period) being omitted; students started discussing immediately after the question was presented. In both methods, the discussions were concluded with a vote and a teacher explanation. During this project, two classes started with Peer Instruction while the other two started with Classic. After four weeks, we switched the methods in all classes.In order to get as reliable feedback from the students as possible, we did not emphasize that we were going to compare different methods. The teacher would just give different instructions based on the method used; for instance, to think individually without speaking to their fellow students in the case of the initial voting session of Peer Instruction. In both methods, students were encouraged to discuss the presented question in small groups for 2–4 minutes. The initial thinking period with Peer Instruction usually lasted about 1-2 minutes.The students were interviewed twice, once after Peer Instruction and once after Classic. One exception was one class which already had experience with SRS and the Classic method. That particular class had already been interviewed about SRS, and therefore was only interviewed once at the end of the 8-week testing period. The interviews were conducted by one of the authors (GHN). The first interview was about three hours and consisted of questions regarding students’ experiences with SRS in general. The second interview was shorter (around 60 minutes) and focused directly on the differences between the two methods. Many of the topics and questions in the second interview were created based on student feedback in the first interviews. The student interviews were conducted as focused (semistructured) group interviews, which is recognized as a reliable method of revealing informants’ perspectives [27]. There were four groups (one from each class) with four students per group consisting of both male and female students.The interviews were analyzed using analytical tools from grounded theory. We want to emphasize that we have not conducted a true grounded theory analysis, that is, with theory sampling to achieve theoretical saturation, but rather we have borrowed the analytical tools. These include a three-step coding scheme (line-by-line coding, focused coding, and categorization) adapted from Charmaz [28, 29]. This method is an appropriate direction for analysis of topics such as personal experiences, opinions, feelings, and attitudes [28]. The first step is to examine each line of data material and code it to define events that appear or are represented [28, 29]. We relied heavily on “in vivo” codes, that is, using the interviewers own words in the early stages of coding. This was to avoid misinterpretations of students’ utterances and assure that we maintained a close relationship between the codes and what expressed by the students. The next phase is to focus on several lines or paragraphs of the interviews (focused coding) where the most significant line-by-line codes are identified. Thus, we are left with a smaller number of codes that give a more accurate description of the data. In the last step, categorization, focused codes are treated more analytical and conceptual [28]. Each focused code is described in detail: its properties, its consequences, how they relate to other focused codes, and conditions under which they arise, is maintained, and changes [29]. This process often led to several focused codes being merged when very close relationships were discovered. In the end we have a small number of categories that describe students’ most significant experiences, in this case their experiences of the two SRS-sequences, Peer Instruction, and Classic.
## 3. Results
The analysis of the interviews resulted in three categories: (1)Argumentation and explanation, (2)Peer Instruction: Opportunity for individual thinking, and (3) Seeing the results: Authority of the majority. The first category deals with the students’ experiences of generating explanations and presenting arguments in group discussions, and how they perceive explanations and arguments from fellow students (and to some extent the teacher). It is not about the content of the arguments and explanations per se, but rather about the students’ own experiences of the process of generating and presenting them and how this relates to their learning. The second category is about thinking without the influence of others and how Peer Instruction gives an opportunity to reflect more deeply upon the questions and forming one’s own opinion, resulting in increased participation and confidence during discussion. The last category focuses on seeing the results from the initial vote in Peer Instruction and how a clear majority can influence students’ decision-making and the group discussion.Category 1: Argumentation and Explanation
Learning physics is more than just memorizing formulas. Although memorization is an important part of their learning process, students also emphasize the importance of being able to reflect upon and solve problems, preferably without the help or influence of others (Category 2). However, according to the students, the best confirmation that they have learned physics is when they are able to explain the solution to other students. Then they have to challenge themselves to explore other ways of thinking in order to generate explanations and arguments that will make the solution both convincing and understandable. In addition, explanations from their peers are often easier to understand because students have the same foundation and speak “the same language.” Students feel that the teacher is on a “higher level” and often uses complex words and phrases which can make his/her explanation hard to follow.You have to sort of re-learn it when you are going to explain it to others.—It becomes other words then [when peers explain], because it is like-minded people who repeat what the teacher said in a different way.According to the students, good group discussions with SRS start with an uncertainty or disagreement about the answer and all students collaborate towards a consensus. Different students remember different things, making it important that everyone participates. Also, if a student does not object or ask questions, it can be interpreted as agreement and that he/she understands the arguments being presented. In other words, being passive can result in students not being given enough explanation to understand the solution, and selecting the correct answer does not benefit learning if they have not understood why it is correct. I think it is important that everyone participates so that they can follow and understand why it is not like this and why it is like this.—If I do not say what I think, then maybe they just expect me to agree with them. And then no-one cares to explain it. So even if I vote the same as them and get the right answer, it does not help if I do not understand it.When students feel that they understand the question and have a good argument, they are more likely to be active during the discussion and try to convince their fellow students. Being convinced or proven wrong is an important part of their learning. As one student puts it: I think you remember it better for later if you are proven wrong.On the other hand, if the students are uncertain about the question or the solution, they are more inclined to be passive and withdraw from the discussion. Another factor that can increase passivity is sitting with students they do not know well. They are afraid of making a fool of themselves when they do not know how their fellow students will react to their arguments. Passivity in group discussions is also prominent if a student in the group is regarded as being skillful or “strong.” The arguments and explanations of stronger students are valued higher than those with equal or lesser skills. Students are then more likely to only listen to these explanations rather than try to find out the solution for themselves, often accepting the others’ conclusions without fully understanding them. You are more passive when you are uncertain, because then you listen to what the others say. And it might be the case that you did not understand the question and the alternatives the way you should have, and when the guy next to me says that it is like this and this: “OK, then maybe it is like this then”. And then you look at it and “OK, I think this also”, so without being certain of the answer I will vote the same.—When we sit and discuss there are certain people in the class you know are very skillful. So if someone in this group talks very loud or a person you know is very skillful says “No, it is B because…”, and then they start to talk, then everyone else in the group will just shut up and listen to what that person has to say. Then it becomes like “Yeah, OK. So maybe it is like this”, if you are uncertain. Then it is easy that you just listen to the others in the group rather than try and find the answer for yourself.The results from the voting session can thus give the teacher a “false” image of the level of understanding among the students. Even though the majority of students have voted for the correct answer, it does not mean that the majority have understood why it is correct. Students therefore emphasize the importance of the explanation given by the teacher after group discussions. The teacher should explain thoroughly both the correct and incorrect alternatives. Learning is not only gained by understanding why an alternative is correct. Understanding why an alternative is incorrect can be just as fruitful and often crucial, especially for students who have voted for the incorrect alternative. Even if the majority has voted correctly, I still think a short explanation is needed. Because the situation can be so that you just voted what the guy next to you thinks is correct and you just follow him. So it is good that we still get a short explanation.—There was one question we sat and discussed which we were absolutely sure was the correct answer. Then it turned out that it was actually wrong, and then I think that it is good that they [the teachers] explain. That they do not just say that “This is correct” and just explain this alternative, but that they go through all the alternatives and explain why they are wrong or show us with illustrations. Because then it is much clearer: “Yes, of course it is like this”.Category 2: Peer Instruction: Opportunity for Individual Thinking
The SRS gives students an opportunity to engage in solving problems in group discussions during lectures. If this is to really benefit their learning, however, students emphasize that it is important that they are able to reflect more deeply upon the problem at hand and struggle with it. Students feel that Peer Instruction, with its initial thinking period, gives them an opportunity to actually involve themselves in the question before discussions. This will not only enhance learning during discussion, it will also make it easier to remember the solution and explanation given by the teacher after the discussion.Yes, we have enough time to involve ourselves in the question [with Peer Instruction], and that is what’s important. That you have thought deeply about it. Because it’s first then you really have a benefit of the answer.—If you first have pondered over something, and maybe you did not find the solution, and then you get the explanation, then it is much easier to remember it [the solution]. When you first had the opportunity to struggle with something, and then you get the explanation, then you remember much better.For students to get involved in the questions, they feel that it is very important that they are able to form their own opinion without the influence of others. This can be difficult to achieve when using the Classic method because they go straight into group discussion after the question is presented. They are not given the opportunity to think individually without being “colored” by other students. I think it was much better [with Peer Instruction], because you are allowed to think for yourself and not having objections from everybody else.—You get a chance to make up your own mind before you get colored by what everybody else thinks.—You do not have time to think before you are influenced by the others’ opinions [with Classic].Students use the initial thinking period with Peer Instruction to construct their own mental image of the problem and an explanation which they can use in the following discussion (Category 1). When using the Classic method, explanations have to be generated during the discussion period (or when the teacher is reading the question), but often students experience that they barely have time to think before someone takes control and starts talking. When these students start to “think out loud”, other students will have a difficult time thinking and working out logical arguments (unless they step in and actively participate by uttering their own thoughts). They can quickly be drawn towards the arguments and conclusions of the students taking control and vote the same alternative without having been able to think for themselves and understand the answer. I think that it blocks your own thoughts if you first have to listen to other people’s ideas without having thought about it yourself; that you in a way forget to think for yourself.With an explanation ready, students feel they have much more to contribute to the discussions. Everyone in the group is more likely to be heard because they can present more convincing arguments for their opinions (Category 1). The group consists of stronger individuals who are more inclined to defend their views when they are given time to think for themselves. This way, both stronger and weaker students can benefit more from the Peer Instruction method since weaker students have greater opportunities to construct and present arguments, while stronger students have a higher probability of having their arguments challenged. After we have thought by ourselves, we have so much more to say, rather than when we went straight into discussion.—The initial thinking time you have, I think that is great! Then you are able to reflect over what you think so that you have a better basis for participating in the discussion in your group.—I feel that there will always be someone who dominates more, but now everyone had something to bring to the table, and everyone was heard because you had a better explanation for your opinions.With Peer Instruction the students find using SRS more serious and orderly. When using Classic it can be hard to know, according to the students, when to stop thinking for themselves and start discussing. With Peer Instruction, however, they know that the discussion starts immediately after the initial voting session. It thus becomes easier to focus on what they should do, when they should think for themselves and when they should discuss. There is more time to come to a consensus and find a shared solution that everyone is comfortable with. Since they are likely to have formulated an explanation during the initial voting session, more of the discussion time is used for actual discussion. The latter was the absolute best, yes, really [Peer Instruction]. It was a little more serious from the start really, because you had to work alone and had thought by yourself first. You put a little more into it than if you went directly to the group discussion, at least I think so. Also you got started at once, you got a better focus.—We also noticed that it was difficult to reach a good explanation [with Classic] that we agreed and where we felt that “Yeah, it must be right.” It was not always we were quite there yet, no, because there was such a short time. It was better when we had thought about it beforehand, and we had an explanation ready. So when we started to discuss there was more time to agree, and feel that we had the answer.Category 3: Seeing the Results: Authority of the Majority
Students clearly prefer Peer Instruction and experience it as the best method with regard to their own learning. However, the method is not without its weaknesses. After the initial vote the results are shown on a histogram. This last category is about how seeing these results can affect the quality of the discussions and how this in turn affects the students’ decision making. If there is a clear majority that has chosen a specific alternative, the discussion can often be guided towards this alternative. It is very likely the students just assume that this alternative is correct and try to work outwhy it is correct, rather than go through all alternatives to work out what is correct and what is not. With the Classic method they do not see any results before discussion and so every alternative is considered equal when they enter discussion. You become guided, or misguided, and lose focus of what you are supposed to discuss because so many in the class have voted “B”.—If you just see that “B” has gotten most of the votes, then you might just end up with trying to explain why “B” is correct rather than trying to find out what is the right answer.—Because if 80% have voted for one of the alternatives, then there is a high probability that it is correct, right? So then the discussion is focused on finding out why it is correct. And if we hadn’t chosen this [alternative], it would have been better if we did not know about it.Several students point out that it is not necessarily the majority that has chosen the correct alternative. Despite this, students feel that they still would be very likely to choose the same as the majority no matter what arguments are presented in the discussion, and without necessarily understanding why it is “correct”. If most have voted “B” and you answered “A”, you’re very inclined to answer “B” however the others argue for or against it.When students feel very uncertain they simply go for the alternative they perceive as most likely, which in most cases will be equal to the alternative which has got a clear majority of the votes (if any). If they have chosen an alternative with the majority of votes in the initial voting session, students become more confident in their choice, lowering their threshold for presenting arguments (Category 1). Even though they may not have the best arguments for this alternative, the students feel they are likely to be more certain of its correctness and defend their choice. The picture is reversed if their initial vote is in the minority. According to the students, they have to be very confident in their arguments to defend such an alternative.Interviewer: So the 20% of students who have voted for alternative “C” might not fight as hard to defend alternative “C” because 80% have voted alternative “B”?Everyone: Yes.Student: It’s not even certain that people will admit that they have answered “C”. It is likely that you will just ask the group “OK, why is it B?” That you just assume that it is “B” because the majority has voted “B”. So then you will just try to explain why this is correct, even though it might not be the correct answer. It might be the case that the majority voted incorrectly.Seeing a clear majority displayed in the results from the initial vote might have most effect on the group discussion when everyone in the group has answered the same as the majority. The students agree among themselves in the group and the majority of the class agrees with them. Then they are likely to lose interest in the question and talk about something else. It just wasn’t interesting to talk about it then [when they saw the results from the initial vote].Therefore students feel that it would be much better to not see the results of the initial vote until after the re vote. They find it interesting to see if the class have changed their mind during discussion, so several students point out that the best method would be to use Peer Instruction, but to wait to show the results of the initial vote until after the discussion to minimize “damage” to the discussion. As one student puts it: If you remove it [the results from the initial vote] there would have been better discussion per person in the class.
## 4. Discussion and Conclusion
We have studied students’ experiences of Peer Instruction with and without the initial voting session using focus group interviews and a grounded theory-based analysis. Students value the initial voting session as a means of delving more deeply into the question, generating a mental image of the problem and constructing an explanation with convincing arguments to use in the following discussion. This is consistent with findings of Nicol and Boyle [20]. In order to generate good explanations, students need time to clarify their thoughts and reflect more deeply upon the problem at hand [5]. Without the initial voting session such a process becomes very difficult because they will only be “allowed” to think and reflect until the first student starts to speak or “think aloud.” The consequence is often less participation and higher probability of accepting explanations presented by “stronger” students.Although the students emphasize the need to construct convincing arguments in order to defend their views, they do not necessarily feel this merely to “win” the discussions. A simplistic view of argumentation is to view it as a battle where one tries to defeat one’s opponent. Duschl and Osborne [5] argue that argumentation is also an exploration to find and fill out holes in one’s knowledge. This view is supported by the students. They want to be convinced of the arguments presented, and to be proven wrong can function as a high facilitator of learning as it can challenge their thinking and reveal flaws in their understanding. The initial voting session results in more arguments and ideas being presented during discussion and the students are more likely to come to a consensus.Another consequence of a greater number of ideas presented at the start of discussion is an increase in the probability of disagreement. Difference is an important part of learning, as Duschl and Osborne [5] stated fittingly: “without difference, there can be no argument, and without argument, there can be no explanation” (p. 53). This is not to say that initial conflict necessarily translates to increased learning. It is also important that the students actively engage in either trying to convince their neighbor or to be convinced, that is, that they state their thoughts and (dis)agreement. Passive compliance and/or insufficient verbalization during group discussion can have a detrimental effect on the learning outcome of discussions [2].Our research is consistent with the findings of Perez et al. [22] and Brooks and Koretsky [21] that displaying the results of the initial voting session can affect students’ decision making and confidence during discussion. As predicted by Perez et al. [22], the students in our research experience that an alternative with a clear majority of the votes becomes a center of focus for the group discussion, although not in a positive sense. Students point out that they will not necessarily try to find out the reason why the majority has chosen one specific alternative; they will automatically assume that it is correct. The histogram becomes an argument in itself, an argument much stronger than those presented in the discussion or through individual reasoning. The focus becomes on finding out why the alternative is correct and not if it is correct.The bias from seeing the results from the initial voting session was also shown to be stronger for more difficult questions [22]. Although our students do not specify this connection in particular, they do emphasize a stronger influence when they feel uncertain, and it is likely there is a high correlation between the difficulty of the question and the level of uncertainty among the students. By not showing the results prior to discussion, every alternative is initially considered equal. Rather than trying to “force” a solution upon an alternative with a clear majority, students are more likely to evaluate each alternative more thoroughly.Without a total evaluation of all alternatives, students will be more dependent on the teacher in order to accept the correctness of the alternative, rather than having it come through their own argumentation [5]. This is a prominent feature in novice students [25], and it is therefore not surprising that the students in our research emphasize the importance of the teacher explanations following the discussions. Our students stress the importance of the teacher carefully explaining the correct alternative and why it is correct in order to be convinced of the solution. This is consistent with the findings of Nicol and Boyle [20]. In addition, our students also emphasize the importance of the teacher explaining why the incorrect alternatives are incorrect. If they do not choose the correct alternative, or are not sure of its correctness, they need an explanation to be convinced and fully understand the solution.Smith et al. [24] argued that there is a synergy effect between peer discussion and the teacher explanation, making the combination facilitate more learning than either on its own. A majority of the students in their study also agreed that the peer discussion made them more prepared for the following explanation. The students’ experiences in our study are consistent with these findings in that the students feel that reflecting and struggling with a question makes it easier to remember the following explanation from the teacher. The initial voting session is crucial for this to happen as deeper reflection is difficult to achieve during peer discussion if they do not have time to formulate their thoughts without the influence of others.In the study by Smith et al. [24], many students even reported frustration when the teacher explanation was excluded when using Peer Instruction. An explanation for this can be that the teacher explanation functions as a closure for the SRS session and also removes any last doubts. Our students feel that they are very seldom 100% sure about the correctness of the answer, and therefore they need the feedback that they have not only chosen the correct answer, but have also understood the solution correctly. Not receiving this feedback is likely to cause frustration.In summary, the students in our research experience Peer Instruction as more beneficial to learning when the initial voting session is included, but where the voting results are not shown until after the revote. Our study has shed more light on recent findings on Peer Instruction from the students’ point of view. Nevertheless, more research is required to obtain a more complete picture of the effect of the initial voting session; for instance, to verify students’ claims of more fruitful discussions, where more arguments are presented. Our ongoing video analysis of students engaged in peer discussion, both with and without the initial voting session, should be able to give more insight to their experiences.
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*Source: 290157-2012-04-26.xml* | 290157-2012-04-26_290157-2012-04-26.md | 38,068 | Investigating Peer Instruction: How the Initial Voting Session Affects Students' Experiences of Group Discussion | Kjetil L. Nielsen; Gabrielle Hansen-Nygård; John B. Stav | ISRN Education
(2012) | Social Sciences & Business | International Scholarly Research Network | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.5402/2012/290157 | 290157-2012-04-26.xml | ---
## Abstract
Peer Instruction is a popular method of implementation when using Student Response Systems (SRS) in classroom teaching. The students engage in peer discussion to solve conceptual multiple choice problems. Before discussion, students are given time to think and give individual responses with a voting device. In this paper, we investigate how this initial voting session affects students’ experiences of the following discussion. The data is based on student interviews which were analyzed using analytical tools from grounded theory. The students emphasize the individual thinking period as crucial for constructing explanations, argumentation, and participation during discussions, and hence for facilitating learning. However, displaying the results from the initial vote can be devastating for the quality of the discussions, especially when there is a clear majority for a specific alternative. These findings are discussed in light of recent quantitative studies on Peer Instruction.
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## Body
## 1. Introduction
The traditional one-way teacher style of lecturing can be effective when delivering factual content, but it is not as effective for facilitating cognitive skills [1, 2]. Engaging students in active-learning activities can be an important factor for mastering skills such as critical thinking and problem solving [1, 3], skills that are often lacking in novice science students [4]. Although such skills are vital to evaluate scientific evidence and theories, students also have to be able to generate and present explanations and arguments for their evaluations, that is, to be fluent in the scientific language [5]. Novice students also suffer in that they are often unable to put into words, or at least scientific words, how they approach the use of theories to solve problems. Engaging students in peer discussions can challenge them to generate explanations and convincing arguments for their solution and in this way also facilitate deeper understanding of the scientific phenomena [5].One way of engaging students in active-learning activities is to use a Student Response System (SRS). Such systems are often used during the lecture to present students with multiple choice questions, which they will discuss with their peers in small groups before answering with a voting device [6–10]. The result from the voting session is displayed in the form of a histogram which can give the teacher an indication of the level of understanding among the students and if they are able to follow the lecture [10, 11]. SRS use in classroom teaching has been shown to increase learning [12–15] including increased conceptual understanding in physics courses [12, 16, 17].Although SRS can be an outstanding tool for facilitating peer discussion, different choices of implementation can have a high impact on the quality of the discussions. For instance, giving credits for SRS participation has been shown to increase the overall participation in the class [18]. However, in a study by James [19], the researcher found that if each individual student was “punished” for voting incorrectly, that is, that he/she was not given as much credit as voting correctly, the group discussions tended to be dominated by students with greater knowledge while other students remained passive. If the students were only credited for participation, they would be more inclined to participate and explore different explanations and ideas.One popular methodological implementation of SRS is with the Peer Instruction technique [17]. During the lecture students are presented with a problem, often where conceptual ideas are in focus, to challenge their knowledge about the subject as opposed to simply looking up the answer in the textbook. Students are given time to think on their own for about 2-3 minutes and answer individually before they are encouraged to engage in discussion with nearby students. The discussions are concluded with a revote and an explanation by the teacher. Dufresne et al. [11] describe a similar method, but where the initial voting session is omitted. Instead, students start discussing immediately after the question is presented and the group discussions are concluded with a class-wide discussion instead of teacher explanation.In a comparative study between Peer Instruction and the method described by Dufresne et al. [11], students felt that without the initial voting session they would be more inclined to be passive in group discussions and that the discussions would be more likely to be dominated by confident and/or “stronger” students [20]. Students reported that they used the initial voting session to formulate their own answer, which they in turn could use in the following discussion, and that they therefore would be more likely to engage in dialogue and defend their views. The researchers argued that the lack of an individual thinking period before discussion would result in less cognitive conflict at the start of discussion and thus students would be more inclined to accept dominant explanations.There have been several recent quantitative studies on different aspects of Peer Instruction [21–24]. Previous studies have shown that the amount of correct votes increases after the discussion [16, 25]. One interpretation of these results could be that students choose the same as stronger students and not that they change their answer as a result of learning. In a study by Smith et al. [23], the researchers found evidence that the increase of correct votes is indeed a result of increased learning and not primarily due to the influence of other students. Even in groups where no students initially had the right answer, they observed an increase in learning. Smith et al. [24] showed that both the peer discussion and teacher explanation are important for facilitating learning with Peer Instruction. Excluding either the discussion or teacher explanation showed less learning than the combination of both.A common practice when using Peer Instruction is to show students the results from the initial voting session prior to the group discussion [26]. Perez et al. [22] found that the probability of students switching to the alternative with the majority of votes increased by 30% if the results were displayed to the students. The researchers provided several interpretations for these findings. A clear majority could function as a stimulus for focused discussions and students might discover flaws in their original reasoning by trying to identify why most students chose one particular alternative. Another interpretation was that students simply switched to this alternative based on the consensus of nearby students. Confidence in their own choice has been shown to be significantly higher if students can see that they initially voted for an alternative in the majority [21]. This was persistent whether the alternative was correct or not.The study in this paper was a part of EU-cofounded projects (EduMecca, Do-it, Done-it and Global-SRS) at Sør-Trøndelag University College in Trondheim, Norway. One goal of these projects was to develop an online SRS designed for effective classroom teaching, where students can use their own mobile device, such as smart-phones, as a voting device as compared to the traditional “clickers”. As well as evaluating the system from a technical point of view, we also investigated different methodological implementations. More information about these projects can be found at our web page (http://www.histproject.no/).The inspiration for this study was the findings of Nicol and Boyle [20]. We wanted to go deeper into, and try to examine, the effects of the initial voting session (and thinking period) with Peer Instruction. To do so, we divided the study into two parts: a quantitative part based on survey data and video of students engaged in peer discussion during class and a pure qualitative part based on in-depth analysis of student interviews. In this paper we focus on the interviews and investigate students’ experiences regarding use of Peer Instruction and the effect of the initial voting session. The analysis of the video material is ongoing and will be presented at a later date. The paper starts with a description of study design and analysis methods followed by a presentation of the results. We conclude with a discussion of our findings; in particular, we discuss the results in light of the recent quantitative studies on Peer Instruction.
## 2. Method
The study was conducted in an introductory physics course for preparatory engineering students. The lectures usually consisted of 2 × 45 min. sessions generally constructed so that the first 45 min. dealt with new theory while the second focused on practical work, mainly problem solving. Four parallel classes with of a total of seven teachers (three classes used two different teachers) used SRS for eight weeks. One of the authors (K. L. Nielsen) was the teacher of the class with a single teacher. The second author (G. Hansen-Nygård) was present in lectures where SRS was used to function as an observer. Each class consisted of 50–70 students, the majority being male students. The theoretical part of the lectures was traditional teacher-style lectures (using digital blackboards) except that the teacher would present the students with 1–4 quizzes consisting of conceptual multiple choice questions. Each student borrowed an Apple iPod Touch which was used as a voting device. When SRS was used, the iPods were handed out at the beginning of the lecture and collected at the end. SRS was used in two of a total of three lectures each week due to some lectures running parallel timetables. To minimize the amount of variables in our data, all classes used the same set of multiple choice questions. We prepared around 50 concept questions which the teachers used in the course of the study.In order to investigate the effects of the initial thinking period with Peer Instruction, we also used another method which we called “Classic” as the reference. This method was similar to Peer Instruction apart from the initial voting session (and thinking period) being omitted; students started discussing immediately after the question was presented. In both methods, the discussions were concluded with a vote and a teacher explanation. During this project, two classes started with Peer Instruction while the other two started with Classic. After four weeks, we switched the methods in all classes.In order to get as reliable feedback from the students as possible, we did not emphasize that we were going to compare different methods. The teacher would just give different instructions based on the method used; for instance, to think individually without speaking to their fellow students in the case of the initial voting session of Peer Instruction. In both methods, students were encouraged to discuss the presented question in small groups for 2–4 minutes. The initial thinking period with Peer Instruction usually lasted about 1-2 minutes.The students were interviewed twice, once after Peer Instruction and once after Classic. One exception was one class which already had experience with SRS and the Classic method. That particular class had already been interviewed about SRS, and therefore was only interviewed once at the end of the 8-week testing period. The interviews were conducted by one of the authors (GHN). The first interview was about three hours and consisted of questions regarding students’ experiences with SRS in general. The second interview was shorter (around 60 minutes) and focused directly on the differences between the two methods. Many of the topics and questions in the second interview were created based on student feedback in the first interviews. The student interviews were conducted as focused (semistructured) group interviews, which is recognized as a reliable method of revealing informants’ perspectives [27]. There were four groups (one from each class) with four students per group consisting of both male and female students.The interviews were analyzed using analytical tools from grounded theory. We want to emphasize that we have not conducted a true grounded theory analysis, that is, with theory sampling to achieve theoretical saturation, but rather we have borrowed the analytical tools. These include a three-step coding scheme (line-by-line coding, focused coding, and categorization) adapted from Charmaz [28, 29]. This method is an appropriate direction for analysis of topics such as personal experiences, opinions, feelings, and attitudes [28]. The first step is to examine each line of data material and code it to define events that appear or are represented [28, 29]. We relied heavily on “in vivo” codes, that is, using the interviewers own words in the early stages of coding. This was to avoid misinterpretations of students’ utterances and assure that we maintained a close relationship between the codes and what expressed by the students. The next phase is to focus on several lines or paragraphs of the interviews (focused coding) where the most significant line-by-line codes are identified. Thus, we are left with a smaller number of codes that give a more accurate description of the data. In the last step, categorization, focused codes are treated more analytical and conceptual [28]. Each focused code is described in detail: its properties, its consequences, how they relate to other focused codes, and conditions under which they arise, is maintained, and changes [29]. This process often led to several focused codes being merged when very close relationships were discovered. In the end we have a small number of categories that describe students’ most significant experiences, in this case their experiences of the two SRS-sequences, Peer Instruction, and Classic.
## 3. Results
The analysis of the interviews resulted in three categories: (1)Argumentation and explanation, (2)Peer Instruction: Opportunity for individual thinking, and (3) Seeing the results: Authority of the majority. The first category deals with the students’ experiences of generating explanations and presenting arguments in group discussions, and how they perceive explanations and arguments from fellow students (and to some extent the teacher). It is not about the content of the arguments and explanations per se, but rather about the students’ own experiences of the process of generating and presenting them and how this relates to their learning. The second category is about thinking without the influence of others and how Peer Instruction gives an opportunity to reflect more deeply upon the questions and forming one’s own opinion, resulting in increased participation and confidence during discussion. The last category focuses on seeing the results from the initial vote in Peer Instruction and how a clear majority can influence students’ decision-making and the group discussion.Category 1: Argumentation and Explanation
Learning physics is more than just memorizing formulas. Although memorization is an important part of their learning process, students also emphasize the importance of being able to reflect upon and solve problems, preferably without the help or influence of others (Category 2). However, according to the students, the best confirmation that they have learned physics is when they are able to explain the solution to other students. Then they have to challenge themselves to explore other ways of thinking in order to generate explanations and arguments that will make the solution both convincing and understandable. In addition, explanations from their peers are often easier to understand because students have the same foundation and speak “the same language.” Students feel that the teacher is on a “higher level” and often uses complex words and phrases which can make his/her explanation hard to follow.You have to sort of re-learn it when you are going to explain it to others.—It becomes other words then [when peers explain], because it is like-minded people who repeat what the teacher said in a different way.According to the students, good group discussions with SRS start with an uncertainty or disagreement about the answer and all students collaborate towards a consensus. Different students remember different things, making it important that everyone participates. Also, if a student does not object or ask questions, it can be interpreted as agreement and that he/she understands the arguments being presented. In other words, being passive can result in students not being given enough explanation to understand the solution, and selecting the correct answer does not benefit learning if they have not understood why it is correct. I think it is important that everyone participates so that they can follow and understand why it is not like this and why it is like this.—If I do not say what I think, then maybe they just expect me to agree with them. And then no-one cares to explain it. So even if I vote the same as them and get the right answer, it does not help if I do not understand it.When students feel that they understand the question and have a good argument, they are more likely to be active during the discussion and try to convince their fellow students. Being convinced or proven wrong is an important part of their learning. As one student puts it: I think you remember it better for later if you are proven wrong.On the other hand, if the students are uncertain about the question or the solution, they are more inclined to be passive and withdraw from the discussion. Another factor that can increase passivity is sitting with students they do not know well. They are afraid of making a fool of themselves when they do not know how their fellow students will react to their arguments. Passivity in group discussions is also prominent if a student in the group is regarded as being skillful or “strong.” The arguments and explanations of stronger students are valued higher than those with equal or lesser skills. Students are then more likely to only listen to these explanations rather than try to find out the solution for themselves, often accepting the others’ conclusions without fully understanding them. You are more passive when you are uncertain, because then you listen to what the others say. And it might be the case that you did not understand the question and the alternatives the way you should have, and when the guy next to me says that it is like this and this: “OK, then maybe it is like this then”. And then you look at it and “OK, I think this also”, so without being certain of the answer I will vote the same.—When we sit and discuss there are certain people in the class you know are very skillful. So if someone in this group talks very loud or a person you know is very skillful says “No, it is B because…”, and then they start to talk, then everyone else in the group will just shut up and listen to what that person has to say. Then it becomes like “Yeah, OK. So maybe it is like this”, if you are uncertain. Then it is easy that you just listen to the others in the group rather than try and find the answer for yourself.The results from the voting session can thus give the teacher a “false” image of the level of understanding among the students. Even though the majority of students have voted for the correct answer, it does not mean that the majority have understood why it is correct. Students therefore emphasize the importance of the explanation given by the teacher after group discussions. The teacher should explain thoroughly both the correct and incorrect alternatives. Learning is not only gained by understanding why an alternative is correct. Understanding why an alternative is incorrect can be just as fruitful and often crucial, especially for students who have voted for the incorrect alternative. Even if the majority has voted correctly, I still think a short explanation is needed. Because the situation can be so that you just voted what the guy next to you thinks is correct and you just follow him. So it is good that we still get a short explanation.—There was one question we sat and discussed which we were absolutely sure was the correct answer. Then it turned out that it was actually wrong, and then I think that it is good that they [the teachers] explain. That they do not just say that “This is correct” and just explain this alternative, but that they go through all the alternatives and explain why they are wrong or show us with illustrations. Because then it is much clearer: “Yes, of course it is like this”.Category 2: Peer Instruction: Opportunity for Individual Thinking
The SRS gives students an opportunity to engage in solving problems in group discussions during lectures. If this is to really benefit their learning, however, students emphasize that it is important that they are able to reflect more deeply upon the problem at hand and struggle with it. Students feel that Peer Instruction, with its initial thinking period, gives them an opportunity to actually involve themselves in the question before discussions. This will not only enhance learning during discussion, it will also make it easier to remember the solution and explanation given by the teacher after the discussion.Yes, we have enough time to involve ourselves in the question [with Peer Instruction], and that is what’s important. That you have thought deeply about it. Because it’s first then you really have a benefit of the answer.—If you first have pondered over something, and maybe you did not find the solution, and then you get the explanation, then it is much easier to remember it [the solution]. When you first had the opportunity to struggle with something, and then you get the explanation, then you remember much better.For students to get involved in the questions, they feel that it is very important that they are able to form their own opinion without the influence of others. This can be difficult to achieve when using the Classic method because they go straight into group discussion after the question is presented. They are not given the opportunity to think individually without being “colored” by other students. I think it was much better [with Peer Instruction], because you are allowed to think for yourself and not having objections from everybody else.—You get a chance to make up your own mind before you get colored by what everybody else thinks.—You do not have time to think before you are influenced by the others’ opinions [with Classic].Students use the initial thinking period with Peer Instruction to construct their own mental image of the problem and an explanation which they can use in the following discussion (Category 1). When using the Classic method, explanations have to be generated during the discussion period (or when the teacher is reading the question), but often students experience that they barely have time to think before someone takes control and starts talking. When these students start to “think out loud”, other students will have a difficult time thinking and working out logical arguments (unless they step in and actively participate by uttering their own thoughts). They can quickly be drawn towards the arguments and conclusions of the students taking control and vote the same alternative without having been able to think for themselves and understand the answer. I think that it blocks your own thoughts if you first have to listen to other people’s ideas without having thought about it yourself; that you in a way forget to think for yourself.With an explanation ready, students feel they have much more to contribute to the discussions. Everyone in the group is more likely to be heard because they can present more convincing arguments for their opinions (Category 1). The group consists of stronger individuals who are more inclined to defend their views when they are given time to think for themselves. This way, both stronger and weaker students can benefit more from the Peer Instruction method since weaker students have greater opportunities to construct and present arguments, while stronger students have a higher probability of having their arguments challenged. After we have thought by ourselves, we have so much more to say, rather than when we went straight into discussion.—The initial thinking time you have, I think that is great! Then you are able to reflect over what you think so that you have a better basis for participating in the discussion in your group.—I feel that there will always be someone who dominates more, but now everyone had something to bring to the table, and everyone was heard because you had a better explanation for your opinions.With Peer Instruction the students find using SRS more serious and orderly. When using Classic it can be hard to know, according to the students, when to stop thinking for themselves and start discussing. With Peer Instruction, however, they know that the discussion starts immediately after the initial voting session. It thus becomes easier to focus on what they should do, when they should think for themselves and when they should discuss. There is more time to come to a consensus and find a shared solution that everyone is comfortable with. Since they are likely to have formulated an explanation during the initial voting session, more of the discussion time is used for actual discussion. The latter was the absolute best, yes, really [Peer Instruction]. It was a little more serious from the start really, because you had to work alone and had thought by yourself first. You put a little more into it than if you went directly to the group discussion, at least I think so. Also you got started at once, you got a better focus.—We also noticed that it was difficult to reach a good explanation [with Classic] that we agreed and where we felt that “Yeah, it must be right.” It was not always we were quite there yet, no, because there was such a short time. It was better when we had thought about it beforehand, and we had an explanation ready. So when we started to discuss there was more time to agree, and feel that we had the answer.Category 3: Seeing the Results: Authority of the Majority
Students clearly prefer Peer Instruction and experience it as the best method with regard to their own learning. However, the method is not without its weaknesses. After the initial vote the results are shown on a histogram. This last category is about how seeing these results can affect the quality of the discussions and how this in turn affects the students’ decision making. If there is a clear majority that has chosen a specific alternative, the discussion can often be guided towards this alternative. It is very likely the students just assume that this alternative is correct and try to work outwhy it is correct, rather than go through all alternatives to work out what is correct and what is not. With the Classic method they do not see any results before discussion and so every alternative is considered equal when they enter discussion. You become guided, or misguided, and lose focus of what you are supposed to discuss because so many in the class have voted “B”.—If you just see that “B” has gotten most of the votes, then you might just end up with trying to explain why “B” is correct rather than trying to find out what is the right answer.—Because if 80% have voted for one of the alternatives, then there is a high probability that it is correct, right? So then the discussion is focused on finding out why it is correct. And if we hadn’t chosen this [alternative], it would have been better if we did not know about it.Several students point out that it is not necessarily the majority that has chosen the correct alternative. Despite this, students feel that they still would be very likely to choose the same as the majority no matter what arguments are presented in the discussion, and without necessarily understanding why it is “correct”. If most have voted “B” and you answered “A”, you’re very inclined to answer “B” however the others argue for or against it.When students feel very uncertain they simply go for the alternative they perceive as most likely, which in most cases will be equal to the alternative which has got a clear majority of the votes (if any). If they have chosen an alternative with the majority of votes in the initial voting session, students become more confident in their choice, lowering their threshold for presenting arguments (Category 1). Even though they may not have the best arguments for this alternative, the students feel they are likely to be more certain of its correctness and defend their choice. The picture is reversed if their initial vote is in the minority. According to the students, they have to be very confident in their arguments to defend such an alternative.Interviewer: So the 20% of students who have voted for alternative “C” might not fight as hard to defend alternative “C” because 80% have voted alternative “B”?Everyone: Yes.Student: It’s not even certain that people will admit that they have answered “C”. It is likely that you will just ask the group “OK, why is it B?” That you just assume that it is “B” because the majority has voted “B”. So then you will just try to explain why this is correct, even though it might not be the correct answer. It might be the case that the majority voted incorrectly.Seeing a clear majority displayed in the results from the initial vote might have most effect on the group discussion when everyone in the group has answered the same as the majority. The students agree among themselves in the group and the majority of the class agrees with them. Then they are likely to lose interest in the question and talk about something else. It just wasn’t interesting to talk about it then [when they saw the results from the initial vote].Therefore students feel that it would be much better to not see the results of the initial vote until after the re vote. They find it interesting to see if the class have changed their mind during discussion, so several students point out that the best method would be to use Peer Instruction, but to wait to show the results of the initial vote until after the discussion to minimize “damage” to the discussion. As one student puts it: If you remove it [the results from the initial vote] there would have been better discussion per person in the class.
## 4. Discussion and Conclusion
We have studied students’ experiences of Peer Instruction with and without the initial voting session using focus group interviews and a grounded theory-based analysis. Students value the initial voting session as a means of delving more deeply into the question, generating a mental image of the problem and constructing an explanation with convincing arguments to use in the following discussion. This is consistent with findings of Nicol and Boyle [20]. In order to generate good explanations, students need time to clarify their thoughts and reflect more deeply upon the problem at hand [5]. Without the initial voting session such a process becomes very difficult because they will only be “allowed” to think and reflect until the first student starts to speak or “think aloud.” The consequence is often less participation and higher probability of accepting explanations presented by “stronger” students.Although the students emphasize the need to construct convincing arguments in order to defend their views, they do not necessarily feel this merely to “win” the discussions. A simplistic view of argumentation is to view it as a battle where one tries to defeat one’s opponent. Duschl and Osborne [5] argue that argumentation is also an exploration to find and fill out holes in one’s knowledge. This view is supported by the students. They want to be convinced of the arguments presented, and to be proven wrong can function as a high facilitator of learning as it can challenge their thinking and reveal flaws in their understanding. The initial voting session results in more arguments and ideas being presented during discussion and the students are more likely to come to a consensus.Another consequence of a greater number of ideas presented at the start of discussion is an increase in the probability of disagreement. Difference is an important part of learning, as Duschl and Osborne [5] stated fittingly: “without difference, there can be no argument, and without argument, there can be no explanation” (p. 53). This is not to say that initial conflict necessarily translates to increased learning. It is also important that the students actively engage in either trying to convince their neighbor or to be convinced, that is, that they state their thoughts and (dis)agreement. Passive compliance and/or insufficient verbalization during group discussion can have a detrimental effect on the learning outcome of discussions [2].Our research is consistent with the findings of Perez et al. [22] and Brooks and Koretsky [21] that displaying the results of the initial voting session can affect students’ decision making and confidence during discussion. As predicted by Perez et al. [22], the students in our research experience that an alternative with a clear majority of the votes becomes a center of focus for the group discussion, although not in a positive sense. Students point out that they will not necessarily try to find out the reason why the majority has chosen one specific alternative; they will automatically assume that it is correct. The histogram becomes an argument in itself, an argument much stronger than those presented in the discussion or through individual reasoning. The focus becomes on finding out why the alternative is correct and not if it is correct.The bias from seeing the results from the initial voting session was also shown to be stronger for more difficult questions [22]. Although our students do not specify this connection in particular, they do emphasize a stronger influence when they feel uncertain, and it is likely there is a high correlation between the difficulty of the question and the level of uncertainty among the students. By not showing the results prior to discussion, every alternative is initially considered equal. Rather than trying to “force” a solution upon an alternative with a clear majority, students are more likely to evaluate each alternative more thoroughly.Without a total evaluation of all alternatives, students will be more dependent on the teacher in order to accept the correctness of the alternative, rather than having it come through their own argumentation [5]. This is a prominent feature in novice students [25], and it is therefore not surprising that the students in our research emphasize the importance of the teacher explanations following the discussions. Our students stress the importance of the teacher carefully explaining the correct alternative and why it is correct in order to be convinced of the solution. This is consistent with the findings of Nicol and Boyle [20]. In addition, our students also emphasize the importance of the teacher explaining why the incorrect alternatives are incorrect. If they do not choose the correct alternative, or are not sure of its correctness, they need an explanation to be convinced and fully understand the solution.Smith et al. [24] argued that there is a synergy effect between peer discussion and the teacher explanation, making the combination facilitate more learning than either on its own. A majority of the students in their study also agreed that the peer discussion made them more prepared for the following explanation. The students’ experiences in our study are consistent with these findings in that the students feel that reflecting and struggling with a question makes it easier to remember the following explanation from the teacher. The initial voting session is crucial for this to happen as deeper reflection is difficult to achieve during peer discussion if they do not have time to formulate their thoughts without the influence of others.In the study by Smith et al. [24], many students even reported frustration when the teacher explanation was excluded when using Peer Instruction. An explanation for this can be that the teacher explanation functions as a closure for the SRS session and also removes any last doubts. Our students feel that they are very seldom 100% sure about the correctness of the answer, and therefore they need the feedback that they have not only chosen the correct answer, but have also understood the solution correctly. Not receiving this feedback is likely to cause frustration.In summary, the students in our research experience Peer Instruction as more beneficial to learning when the initial voting session is included, but where the voting results are not shown until after the revote. Our study has shed more light on recent findings on Peer Instruction from the students’ point of view. Nevertheless, more research is required to obtain a more complete picture of the effect of the initial voting session; for instance, to verify students’ claims of more fruitful discussions, where more arguments are presented. Our ongoing video analysis of students engaged in peer discussion, both with and without the initial voting session, should be able to give more insight to their experiences.
---
*Source: 290157-2012-04-26.xml* | 2012 |
# Comparative Performance of Creatinine-Based Estimated Glomerular Filtration Rate Equations in the Malays: A Pilot Study in Tertiary Hospital in Malaysia
**Authors:** Maisarah Jalalonmuhali; Ng Kok Peng; Lim Soo Kun
**Journal:** International Journal of Nephrology
(2017)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2017/2901581
---
## Abstract
Aim. To validate the accuracy of estimated glomerular filtration rate (eGFR) equations in Malay population attending our hospital in comparison with radiolabeled measured GFR.Methods. A cross-sectional study recruiting volunteered patients in the outpatient setting. Chromium EDTA (51Cr-EDTA) was used as measured GFR. The predictive capabilities of Cockcroft-Gault equation corrected for body surface area (CGBSA), four-variable Modification of Diet in Renal Disease (4-MDRD), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations were calculated.Results. A total of 51 subjects were recruited with mean measured GFR 42.04 (17.70–111.10) ml/min/1.73 m2. Estimated GFR based on CGBSA, 4-MDRD, and CKD-EPI were 40.47 (16.52–115.52), 35.90 (14.00–98.00), and 37.24 (14.00–121.00), respectively. Higher accuracy was noted in 4-MDRD equations throughout all GFR groups except for subgroup of GFR ≥ 60 ml/min/1.73 m2 where CGBSA was better.Conclusions. The 4-MDRD equation seems to perform better in estimating GFR in Malay CKD patients generally and specifically in the subgroup of GFR < 60 ml/min/1.73 m2 and both BMI subgroups.
---
## Body
## 1. Introduction
According to the 21st Malaysian Dialysis and Transplant Registry report, in the year 2013, a total of 31,637 patients received dialysis, an increase from a mere 11,842 in 2004. A staggering 61% of end-stage renal disease (ESRD) in Malaysia was reported to be caused by diabetes mellitus [1]. Chronic kidney disease (CKD) can lead to various complications and is well known to be an independent risk factor for cardiovascular disease [2]. A reduced glomerular filtration rate (GFR) to <60 ml/min/1.73 m2 alone is sufficient to diagnose CKD [3]. Direct assessment of GFR is measured from urinary or plasma clearance of an ideal filtration marker such as inulin or other alternative exogenous markers such as iothalamate, chromium 51 ethylenediaminetetraacetic acid (51Cr-EDTA), technetium-99 m diethylenetriaminepentaacetic acid (TC99m-DTPA), and iohexol. 51Cr-EDTA and TC99m-DTPA are radioactive tracers that were reported in radiological studies used to obtain accurate measurement of GFR [4, 5]. However, measuring clearance with exogenous markers is complex, expensive, and difficult to do in routine clinical practice. Therefore, an accurate, convenient, and precise method to estimate GFR is important to overcome this problem.Traditionally, serum creatinine has been used as a marker to assess kidney function. It is now an established fact that serum creatinine alone is not an accurate marker of GFR as it is dependent on muscle mass [6]. Apart from that, serum creatinine usually does not increase until GFR has decreased by 50% or more and thus many patients with normal serum creatinine may have lower GFR [7]. Therefore, a calculated GFR from creatinine-based method is recommended. In Malaysia, Cockcroft-Gault (CG) formula for estimating kidney function is still widely used. Unfortunately it has been reported to overestimate true GFR. The Modification of Diet in Renal Disease (MDRD) formula derived from MDRD study was proposed to overcome this limitation [8]. Based on the study, four-variable MDRD (4-MDRD) that consists of serum creatinine, gender, age, and ethnicity was derived and became commonly used in clinical practice and research. The 4-MDRD formula provides good GFR estimation particularly in the group of GFR <60 mL/min/1.73 m2 White Americans [9]. This subsequently leads to the new equation proposed for Caucasian and African-American CKD populations, known as Chronic Kidney Disease Epidemiological Collaboration (CKD-EPI) equation [10]. The development of this equation is mainly to overcome some of the limitations from MDRD equation, particularly in estimating GFR of >60 ml/min/1.73 m2.Among Asian population, namely, in Chinese, Japanese, and Thais, racial coefficient has been identified and incorporated in eGFR formulas [11–14]. To date, studies comparing different methods of kidney function assessment in our unique multiethnic population are very scarce. Evaluation of these methods in the Malays as the dominant ethnic group of this country is very interesting. A good eGFR formula needs to have lower bias and limits of agreement, in addition to excellent precision and accuracy. The objective of this study is to evaluate the accuracy of creatinine-based eGFR formulas compared to the measured GFR in Malay population.
## 2. Materials and Methods
This is a cross-sectional study conducted in University Malaya Medical Centre (UMMC), Kuala Lumpur, Malaysia, and approved by UMMC ethic committee. We used power and sample size software version 3 to calculate sample size. Single mean formula was used. Under a significance level of 0.05 and power of 0.90, the estimated sample size is46±10% patients. Our study cohort involved patients presented to UMMC nephrology clinic for their regular follow-up. Volunteered participants were recruited in continuous manner. All patients older than 18 years old with stable renal function for at least 3 months prior to recruitment were eligible to participate. Patients with acute deterioration of renal function, bedridden patients, patients with malnutrition, limb amputees, patients who are less than 18 years old, and pregnant women were excluded.
### 2.1.51Cr-EDTA Measurement
Measured GFR is determined by collecting blood sample from different arm 2, 2.5, 3, and 4 hours later following51Cr-EDTA single injection technique. Plasma clearance of 51Cr-EDTA from 4 samples was obtained based on the interval above. Patient’s height and weight were measured for body surface area (BSA) calculation. GFR was calculated using the slope-intercept method and normalized to BSA, which was calculated using du Bois formula. The result was then corrected using Brochner-Mortensen equation.Volume distribution (Vd) is calculated by(1)Vd=Standard activity (cpm)×weight of dose×100mlPo (cpm)×weight of standard.(i)
Standard activity is calculated using computer generated chromium result.(ii)
Weight of dose is calculated from weight of syringe and dose before injection − after injection.(iii)
Po (zero time plasma activity) is corrected by extrapolating the curve to zero time.Slope clearance (C-slope) is calculated by(2)C-slopeslope intercept=0.693T1/2×Vd.Normalized GFR is calculated by(3)NormalizedGFR=C-slopePatient’s BSA×1.73.
### 2.2. Calibration for the Serum Creatinine Assay
Serum creatinine was measured on a Dimension Vista system clinical chemistry analyzer (Siemens) with an assay using a modification of the kinetic Jaffe reaction (alkaline picrate reaction). This modified technique was reported to be less susceptible than conventional methods to interference from noncreatinine Jaffe positive compounds [15]. The creatinine assay was adjusted for calibration with the isotope dilution mass spectrometry (IDMS).
### 2.3. Estimated GFR Calculations
The eGFR values were calculated by using CG, 4-MDRD, and CKD-EPI equations. 4-MDRD and CKD-EPI derived eGFR are expressed as ml/min/1.73 m2. Meanwhile CG equation was converted from ml/min to ml/min/1.73 m2 by multiplying the calculated values by 1.73 and dividing by BSA (Table 1).Table 1
Different eGFR formula according to gender.
eGFR methods
Gender
Equations
Cockcroft-Gault
Male
140
-
A
g
e
×
m
a
s
s
(
k
g
)
×
1.23
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
(
u
m
o
l
/
L
)
Female
140
-
A
g
e
×
m
a
s
s
(
k
g
)
×
1.04
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
(
u
m
o
l
/
L
)
4-MDRD
Male
32788
×
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
-
1.154
×
A
g
e
-
0.203
×
{
1.212
i
f
B
l
a
c
k
}
Female
32788
×
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
-
1.154
×
A
g
e
-
0.203
×
{
1.212
if Black
}
×
0.742
(Serum creatinine in umol/L)
CKD-EPI
Male
141
×
min
(
SCr
/
0.9,1
)
-
0.411
×
max
(
SCr
/
0.9,1
)
-
1.209
×
0.993
A
g
e
×
{
1.159
if Black
}
Female
141
×
min
(
SCr
/
0.7,1
)
-
0.329
×
max
(
SCr
/
0.7,1
)
-
1.209
×
0.993
A
g
e
×
{
1.159
if Black
}
×
1.018
Cockcroft-Gault BSA
Calculated Cockcroft-Gault
×
1.73
BSA
### 2.4. Statistical Analysis
SPSS version 20.0 was used to calculate baseline characteristics frequency, mean, median, range, and standard deviation. Mean GFR were given with a 95% confidence interval (CI) unless indicated otherwise.p values < 0.05 were considered significant. Pearson’s correlation coefficients (r) were calculated between 51Cr-EDTA clearance and estimated GFR by a linear correlation analysis. Pairwise comparison of the mean was performed using paired t-test.Bias, precision, and accuracy within 10% and 30% of the measured GFR were determined. Bias is defined as mean difference between estimated GFR and the measured GFR (51Cr-EDTA). The precision of the estimates was determined as SD of the mean difference between measured GFR and eGFR. Accuracy was determined by integrating precision and bias and was calculated as the percentage of GFR estimates within 10 and 30% of the measured GFR. Moreover, a graphical analysis was carried out according to Bland and Altman plots. This was used to assess the limits of agreement between the eGFR and the measured GFR.In our study, accuracy is the most important determinants for a good estimated GFR and it is best if further supported by lower bias, greater precision, and lower limits of agreement. However, as we understand that bias, precision and limits of agreement may be affected by the overall means and outliers; therefore the individual parameter may not reflect the best estimated GFR.
## 2.1.51Cr-EDTA Measurement
Measured GFR is determined by collecting blood sample from different arm 2, 2.5, 3, and 4 hours later following51Cr-EDTA single injection technique. Plasma clearance of 51Cr-EDTA from 4 samples was obtained based on the interval above. Patient’s height and weight were measured for body surface area (BSA) calculation. GFR was calculated using the slope-intercept method and normalized to BSA, which was calculated using du Bois formula. The result was then corrected using Brochner-Mortensen equation.Volume distribution (Vd) is calculated by(1)Vd=Standard activity (cpm)×weight of dose×100mlPo (cpm)×weight of standard.(i)
Standard activity is calculated using computer generated chromium result.(ii)
Weight of dose is calculated from weight of syringe and dose before injection − after injection.(iii)
Po (zero time plasma activity) is corrected by extrapolating the curve to zero time.Slope clearance (C-slope) is calculated by(2)C-slopeslope intercept=0.693T1/2×Vd.Normalized GFR is calculated by(3)NormalizedGFR=C-slopePatient’s BSA×1.73.
## 2.2. Calibration for the Serum Creatinine Assay
Serum creatinine was measured on a Dimension Vista system clinical chemistry analyzer (Siemens) with an assay using a modification of the kinetic Jaffe reaction (alkaline picrate reaction). This modified technique was reported to be less susceptible than conventional methods to interference from noncreatinine Jaffe positive compounds [15]. The creatinine assay was adjusted for calibration with the isotope dilution mass spectrometry (IDMS).
## 2.3. Estimated GFR Calculations
The eGFR values were calculated by using CG, 4-MDRD, and CKD-EPI equations. 4-MDRD and CKD-EPI derived eGFR are expressed as ml/min/1.73 m2. Meanwhile CG equation was converted from ml/min to ml/min/1.73 m2 by multiplying the calculated values by 1.73 and dividing by BSA (Table 1).Table 1
Different eGFR formula according to gender.
eGFR methods
Gender
Equations
Cockcroft-Gault
Male
140
-
A
g
e
×
m
a
s
s
(
k
g
)
×
1.23
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
(
u
m
o
l
/
L
)
Female
140
-
A
g
e
×
m
a
s
s
(
k
g
)
×
1.04
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
(
u
m
o
l
/
L
)
4-MDRD
Male
32788
×
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
-
1.154
×
A
g
e
-
0.203
×
{
1.212
i
f
B
l
a
c
k
}
Female
32788
×
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
-
1.154
×
A
g
e
-
0.203
×
{
1.212
if Black
}
×
0.742
(Serum creatinine in umol/L)
CKD-EPI
Male
141
×
min
(
SCr
/
0.9,1
)
-
0.411
×
max
(
SCr
/
0.9,1
)
-
1.209
×
0.993
A
g
e
×
{
1.159
if Black
}
Female
141
×
min
(
SCr
/
0.7,1
)
-
0.329
×
max
(
SCr
/
0.7,1
)
-
1.209
×
0.993
A
g
e
×
{
1.159
if Black
}
×
1.018
Cockcroft-Gault BSA
Calculated Cockcroft-Gault
×
1.73
BSA
## 2.4. Statistical Analysis
SPSS version 20.0 was used to calculate baseline characteristics frequency, mean, median, range, and standard deviation. Mean GFR were given with a 95% confidence interval (CI) unless indicated otherwise.p values < 0.05 were considered significant. Pearson’s correlation coefficients (r) were calculated between 51Cr-EDTA clearance and estimated GFR by a linear correlation analysis. Pairwise comparison of the mean was performed using paired t-test.Bias, precision, and accuracy within 10% and 30% of the measured GFR were determined. Bias is defined as mean difference between estimated GFR and the measured GFR (51Cr-EDTA). The precision of the estimates was determined as SD of the mean difference between measured GFR and eGFR. Accuracy was determined by integrating precision and bias and was calculated as the percentage of GFR estimates within 10 and 30% of the measured GFR. Moreover, a graphical analysis was carried out according to Bland and Altman plots. This was used to assess the limits of agreement between the eGFR and the measured GFR.In our study, accuracy is the most important determinants for a good estimated GFR and it is best if further supported by lower bias, greater precision, and lower limits of agreement. However, as we understand that bias, precision and limits of agreement may be affected by the overall means and outliers; therefore the individual parameter may not reflect the best estimated GFR.
## 3. Results
A total of 51 patients were recruited with mean age of 58.7 years, where the youngest was 26 years old and the eldest was 78 years old. Majority of our patients are males representing 90.2%. The mean height and weight in our patient were 164.5 cm and 71.9 kg, respectively, with mean BMI of 26.5 kg/m2. Vast majority of our study patients had diabetic nephropathy (35.3%) and hypertension (19.6%) as the main cause of their CKD. Summary of patient’s baseline characteristics is tabulated in Table 2.Table 2
Baseline characteristics of patients.
Characteristic(n=51)
Mean ± SD (median) orn (%)
Male
46 (90.2)
Age (year)
58.7 ± 12.6 (61.0)
BMI (kg/m2)
26.5 ± 4.6 (25.5)
Plasma creatinine (umol/l)
192.5 ± 66.7 (190.0)
Plasma urea nitrogen (mmol/l)
9.8 ± 3.5 (9.4)
Plasma albumin (g/l)
37.9 ± 3.0 (38.0)
Measured GFR (ml/min/1.73m2)
42.04 ± 22.5 (35.1)
Causes of CKD
Diabetic nephropathy
18 (35.3)
Hypertension
10 (19.6)
Nondiabetic glomerulopathy
4 (7.8)
Renal calculi/nephrocalcinosis
4 (7.8)
Other causes
10 (19.7)
Unknown
5 (9.8)
CKD stages
1
2 (3.9)
2
8 (15.7)
3
26 (51.0)
4
15 (29.4)
Medical history
Diabetes mellitus
33 (64.7)
Hypertension
46 (90.2)
Medications
Diuretics
14 (27.5)
Antihypertensive
48 (94.1)
OHA/insulin
32 (62.7)
Statin
41 (80.4)
Smoking status
Current smoker
6 (11.8)
Ex-smoker
21 (41.2)
Nonsmoker
24 (47.1)From our cohort, mean measured GFR was 42.04 (17.70–111.10) ml/min/1.73 m2, while the estimated GFR based on CGBSA, 4-MDRD, and CKD-EPI formula were 40.47 (16.52–115.52), 35.90 (14.00–98.00), and 37.24 (14.00–121.00), respectively. The calculated GFR of the 4-MDRD and CKD-EPI differed significantly from measured GFR with p value = 0.001 and 0.005. The correlation between estimated and measured GFR is illustrated in Table 3.Table 3
Correlation coefficient (r), mean, bias, precision, and accuracy for CGBSA, 4-MDRD, and CKD-EPI formula.
Correlation coefficient (r)
Mean GFR
Range (IQR)
p value
Mean difference (bias)
SD of mean bias (precision)
Accuracy within
Lower
Upper
10%
30%
Measured GFR
42.039
17.70
111.10
CGBSA
0.877∗
40.467
16.52
115.52
0.303
−1.573
10.802
9.8
47.1
4-MDRD
0.848∗
35.902
14.00
98.00
0.001
−6.137
12.058
13.7
54.9
CKD-EPI
0.854∗
37.235
14.00
121.00
0.005
−4.804
11.697
13.7
49.0
∗Significantly correlating with p<0.001.
(Bias: mean difference of estimated GFR and measured GFR; accuracy:n percentage of GFR estimates within n% of measured GFR; IQR: interquartile range).Bias of CGBSA (1.573 ml/min/1.73 m2) was smaller than 4-MDRD (6.137 ml/min/1.73 m2) and CKD-EPI (4.804 ml/min/1.73 m2), while the precisions of the estimated GFR showed that CGBSA is more precise followed by CKD-EPI and 4-MDRD formula. However, from our cohort we found that 4-MDRD is the most accurate formula with the accuracy of 13.7 and 54.9% within 10 and 30% of measured GFR, respectively. Nevertheless, we noted that 4-MDRD formula underestimated GFR by 6.137 ml/min/1.73 m2; this was likely because of the outliers in this study cohort.The differences between estimated and measured GFR were illustrated using a graphical technique according to Bland and Altman plot (Figures1(a)–1(c)). These figures display the span between +2SD and −2SD of the mean difference (limits of agreement between 2 methods), which represent 95% CI. From the chart below it showed that smaller limits of agreement were found for the CGBSA (43.21 ml/min/1.73 m2), followed by CKD-EPI (46.78 ml/min/1.73 m2) and 4-MDRD (48.23 ml/min/1.73 m2) formula. Even though limits of agreement in 4-MDRD formula are wider, Figure 1(b) illustrated that each patient distribution is closer from one another and these wider limits of agreement can be explained by the extreme outliers (underestimated by almost 60 mls/min/1.73 m2) that present in this group. Thus, this make 4-MDRD formula the most accurate estimated GFR in comparison with 51Cr-EDTA throughout all ranges of GFR in our study cohort.Figure 1
(a–c) Bland and Altman analysis of GFR estimates. In this analysis, the differences between estimated and measured GFR are plotted against the average of the estimated and measured GFR for each individual patient.
(a)
Cockcroft-Gault BSA equation and measured GFR
(b)
4-MDRD equation and measured GFR
(c)
CKD-EPI equation and measured GFRPatients were further divided into two groups according to the measured GFR: GFR < 60 ml/min/1.73 m2 or GFR ≥ 60 ml/min/1.73 m2. In subgroup GFR < 60 ml/min/1.73 m2, lower bias was found for CGBSA formula (0.34 ml/min/1.73 m2) followed by CKD-EPI (2.24 ml/min/1.73 m2) and 4-MDRD (2.95 ml/min/1.73 m2). However, better accuracy within 10% of measured GFR was found in 4-MDRD and CKD-EPI formula. In subgroup GFR ≥ 60 ml/min/1.73 m2, a different pattern of bias and accuracy was noted. In this subgroup, CGBSA formula was found to be better in terms of bias (9.40 ml/min/1.73 m2) and accuracy within 10% of measured GFR (40%), while 4-MDRD and CKD-EPI formula were noted to have higher bias, 19.22 and 15.32 ml/min/1.73 m2, respectively, and lower accuracy within 10% of measured GFR. Precisions of all the equations were significantly lower in the patients with GFR <60 ml/min/1.73 m2 (Table 4).Table 4
Mean, bias, precision, and accuracy of GFR estimates within two GFR subgroups.
Variable
GFR < 60 ml/min/1.73 m2 (n=41)
GFR ≥ 60 ml/min/1.73 m2 (n=10)
GFR(ml/min/1.73 m2)
Measured
33.19 ± 10.39
78.32 ± 22.61
CGBSA
33.53 ± 10.79∗
68.92 ± 21.10∗∗
4-MDRD
30.24 ± 10.27∗
59.10 ± 21.35∗∗
CKD-EPI
30.95 ± 11.14∗
63.00 ± 23.49∗∗
Median bias
CGBSA
−0.99 (−9.6, 19.81)
−9.80 (−33.00, 27.35)
4-MDRD
−2.60 (−17.10, 10.20)
−19.70 (−55.80, 23.60)
CKD-EPI
−1.80 (−15.10, 13.20)
−14.70 (−48.80, 32.60)
Mean difference
CGBSA
0.34 ± 7.04
−9.40 ± 18.53
4-MDRD
−2.95 ± 6.13
19.22 ± 20.11
CKD-EPI
−2.24 ± 6.22
−15.32 ± 20.86
Accuracy within 10
%
CGBSA
24.4
40.0
4-MDRD
31.7
20.0
CKD-EPI
31.7
10.0
Accuracy within 30
%
CGBSA
63.4
70.0
4-MDRD
65.9
80.0
CKD-EPI
65.9
80.0
∗Mean CGBSA GFR versus measured GFR p=0.761, mean 4-MDRD GFR versus measured GFR p=0.004, and mean CKD-EPI GFR versus measured GFR p=0.026.
∗
∗Mean CGBSA GFR versus measured GFR p=0.143, mean 4-MDRD GFR versus measured GFR p=0.014, and mean CKD-EPI GFR versus measured GFR p=0.045.Assessment of eGFR formula in patients with BMI < 23 kg/m2 and BMI ≥ 23 kg/m2 was performed. In both subgroups, better accuracy within 10 and 30% of measured GFR was found in 4-MDRD formula, which was 14.3 and 50% in BMI < 23 kg/m2 while in subgroup BMI ≥ 23 kg/m2 was 16.2 and 54.0% (Table 5).Table 5
Mean, bias, precision, and accuracy of GFR estimates within two BMI subgroups.
Variable
BMI < 23 kg/m2 (n=14)
BMI ≥ 23 kg/m2 (n=37)
GFR(ml/min/1.73 m2)
Measured
43.19 ± 19.44
41.61 ± 23.78
CGBSA
41.80 ± 23.96∗
39.94 ± 17.67∗∗
4-MDRD
43.14 ± 23.28∗
33.16 ± 13.90∗∗
CKD-EPI
44.57 ± 25.73∗
34.46 ± 15.40∗∗
Median bias
CGBSA
−1.34 (−23.8, 27.35)
−1.66 (−33.07, 19.81)
4-MDRD
0.04 (−22.8, 23.6)
−8.44 (−55.80, 6.10)
CKD-EPI
1.39 (−19.8, 32.6)
−7.15 (−48.80, 7.10)
Mean difference
CGBSA
−1.34 ± 11.54
−1.66 ± 10.68
4-MDRD
−0.04 ± 11.06
8.44 ± 11.74
CKD-EPI
1.39 ± 12.31
−7.15 ± 10.71
Accuracy within 10
%
CGBSA
7.0
8.1
4-MDRD
14.3
16.2
CKD-EPI
14.3
10.8
Accuracy within 30
%
CGBSA
50.0
48.6
4-MDRD
50.0
54
CKD-EPI
42.9
54.1
∗Mean CGBSA GFR versus measured GFR p=0.672, mean 4-MDRD GFR versus measured GFR p=0.989, and mean CKD-EPI GFR versus measured GFR p=0.680.
∗
∗Mean CGBSA GFR versus measured GFR p=0.350, mean 4-MDRD GFR versus measured GFR p<0.001, and mean CKD-EPI GFR versus measured GFR p<0.001.
## 4. Discussions
This study investigated the performance of different creatinine-based eGFR formula in Malay population in a tertiary hospital in Malaysia. An accurate eGFR measurement is extremely important as a tool for CKD diagnosis, drug dosage preparations, and procedural preparation and subsequently to determine the efficacy of novel treatments to delay CKD progression in clinical practice. Performing labor-intensive radio-labelled GFR measurement is not practical and economical particularly in developing country like Malaysia.It is known that racial coefficient is an important factor to determine accurate GFR [11–14, 16, 17]. In our cohort, the eGFR obtained from each formula showed significant correlation with measured GFR (51Cr-EDTA). However, the eGFR by 4-MDRD formula in general was found to be more accurate than the other eGFR equations in estimating GFR in our small cohort.In the subgroup analysis of measured GFR < 60 mls/min/1.73 m2, our data showed that CKD-EPI and 4-MDRD formulas showed better performance pertaining to the accuracy in comparison with other estimates GFR. The results corresponded with MDRD study that was performed in White American patients, which revealed that MDRD equation showed a reliable performance in estimating GFR in CKD patients with GFR < 60 mls/min/1.73 m2. However, in Singaporean multiethnic study, it revealed that CKD-EPI was more accurate than the 4-MDRD in GFR < 60 ml/min/1.73 m2 and overestimated reference GFR when the reference GFR was ≥ 60 ml/min/1.73 m2 [18].Estimating GFR in overweight and obese populations is another interesting factor to look into as weight and body size may influence the level of creatinine. In subgroup analysis of BMI ≥ 23 kg/m2, greater accuracy was noted in 4-MDRD formula. Similar result was noted in another local study done by National University of Malaysia (UKM) that revealed MDRD equation showed greater accuracy and precision in obese individuals [19]. Interestingly, in BMI < 23 kg/m2, 4-MDRD fared better as well unlike in lean population in African that showed that CG was better than MDRD and CKD-EPI formula with regard to the narrow limits of agreement [16].
## 5. Limitations of the Study
This is a small single-centre cohort of CKD patients, who are predominantly male and mainly consisted of CKD stages 3 and 4. Due to the continuous sampling method used in this study, we are unable to ensure equal distribution of patients in different arms of subgroup analysis. Thus, to further validate the more recent CKD-EPI formula, more inclusion of other stages of CKD is needed. Although this study has the above-mentioned limitations, this is the first study to be conducted in Malaysia using51Cr-EDTA as reference GFR.
## 6. Conclusion
We found that 4-MDRD equation seems to be more accurate in estimating GFR in our small cohort of Malay CKD patients except in subgroup of GFR ≥ 60 mls/min/m2, where CGBSA was found to be better. We would like to propose further studies to look into the need for racial correction factor to improve the performance of the original 4-MDRD formula in Malay population.
---
*Source: 2901581-2017-06-18.xml* | 2901581-2017-06-18_2901581-2017-06-18.md | 25,320 | Comparative Performance of Creatinine-Based Estimated Glomerular Filtration Rate Equations in the Malays: A Pilot Study in Tertiary Hospital in Malaysia | Maisarah Jalalonmuhali; Ng Kok Peng; Lim Soo Kun | International Journal of Nephrology
(2017) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2017/2901581 | 2901581-2017-06-18.xml | ---
## Abstract
Aim. To validate the accuracy of estimated glomerular filtration rate (eGFR) equations in Malay population attending our hospital in comparison with radiolabeled measured GFR.Methods. A cross-sectional study recruiting volunteered patients in the outpatient setting. Chromium EDTA (51Cr-EDTA) was used as measured GFR. The predictive capabilities of Cockcroft-Gault equation corrected for body surface area (CGBSA), four-variable Modification of Diet in Renal Disease (4-MDRD), and Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equations were calculated.Results. A total of 51 subjects were recruited with mean measured GFR 42.04 (17.70–111.10) ml/min/1.73 m2. Estimated GFR based on CGBSA, 4-MDRD, and CKD-EPI were 40.47 (16.52–115.52), 35.90 (14.00–98.00), and 37.24 (14.00–121.00), respectively. Higher accuracy was noted in 4-MDRD equations throughout all GFR groups except for subgroup of GFR ≥ 60 ml/min/1.73 m2 where CGBSA was better.Conclusions. The 4-MDRD equation seems to perform better in estimating GFR in Malay CKD patients generally and specifically in the subgroup of GFR < 60 ml/min/1.73 m2 and both BMI subgroups.
---
## Body
## 1. Introduction
According to the 21st Malaysian Dialysis and Transplant Registry report, in the year 2013, a total of 31,637 patients received dialysis, an increase from a mere 11,842 in 2004. A staggering 61% of end-stage renal disease (ESRD) in Malaysia was reported to be caused by diabetes mellitus [1]. Chronic kidney disease (CKD) can lead to various complications and is well known to be an independent risk factor for cardiovascular disease [2]. A reduced glomerular filtration rate (GFR) to <60 ml/min/1.73 m2 alone is sufficient to diagnose CKD [3]. Direct assessment of GFR is measured from urinary or plasma clearance of an ideal filtration marker such as inulin or other alternative exogenous markers such as iothalamate, chromium 51 ethylenediaminetetraacetic acid (51Cr-EDTA), technetium-99 m diethylenetriaminepentaacetic acid (TC99m-DTPA), and iohexol. 51Cr-EDTA and TC99m-DTPA are radioactive tracers that were reported in radiological studies used to obtain accurate measurement of GFR [4, 5]. However, measuring clearance with exogenous markers is complex, expensive, and difficult to do in routine clinical practice. Therefore, an accurate, convenient, and precise method to estimate GFR is important to overcome this problem.Traditionally, serum creatinine has been used as a marker to assess kidney function. It is now an established fact that serum creatinine alone is not an accurate marker of GFR as it is dependent on muscle mass [6]. Apart from that, serum creatinine usually does not increase until GFR has decreased by 50% or more and thus many patients with normal serum creatinine may have lower GFR [7]. Therefore, a calculated GFR from creatinine-based method is recommended. In Malaysia, Cockcroft-Gault (CG) formula for estimating kidney function is still widely used. Unfortunately it has been reported to overestimate true GFR. The Modification of Diet in Renal Disease (MDRD) formula derived from MDRD study was proposed to overcome this limitation [8]. Based on the study, four-variable MDRD (4-MDRD) that consists of serum creatinine, gender, age, and ethnicity was derived and became commonly used in clinical practice and research. The 4-MDRD formula provides good GFR estimation particularly in the group of GFR <60 mL/min/1.73 m2 White Americans [9]. This subsequently leads to the new equation proposed for Caucasian and African-American CKD populations, known as Chronic Kidney Disease Epidemiological Collaboration (CKD-EPI) equation [10]. The development of this equation is mainly to overcome some of the limitations from MDRD equation, particularly in estimating GFR of >60 ml/min/1.73 m2.Among Asian population, namely, in Chinese, Japanese, and Thais, racial coefficient has been identified and incorporated in eGFR formulas [11–14]. To date, studies comparing different methods of kidney function assessment in our unique multiethnic population are very scarce. Evaluation of these methods in the Malays as the dominant ethnic group of this country is very interesting. A good eGFR formula needs to have lower bias and limits of agreement, in addition to excellent precision and accuracy. The objective of this study is to evaluate the accuracy of creatinine-based eGFR formulas compared to the measured GFR in Malay population.
## 2. Materials and Methods
This is a cross-sectional study conducted in University Malaya Medical Centre (UMMC), Kuala Lumpur, Malaysia, and approved by UMMC ethic committee. We used power and sample size software version 3 to calculate sample size. Single mean formula was used. Under a significance level of 0.05 and power of 0.90, the estimated sample size is46±10% patients. Our study cohort involved patients presented to UMMC nephrology clinic for their regular follow-up. Volunteered participants were recruited in continuous manner. All patients older than 18 years old with stable renal function for at least 3 months prior to recruitment were eligible to participate. Patients with acute deterioration of renal function, bedridden patients, patients with malnutrition, limb amputees, patients who are less than 18 years old, and pregnant women were excluded.
### 2.1.51Cr-EDTA Measurement
Measured GFR is determined by collecting blood sample from different arm 2, 2.5, 3, and 4 hours later following51Cr-EDTA single injection technique. Plasma clearance of 51Cr-EDTA from 4 samples was obtained based on the interval above. Patient’s height and weight were measured for body surface area (BSA) calculation. GFR was calculated using the slope-intercept method and normalized to BSA, which was calculated using du Bois formula. The result was then corrected using Brochner-Mortensen equation.Volume distribution (Vd) is calculated by(1)Vd=Standard activity (cpm)×weight of dose×100mlPo (cpm)×weight of standard.(i)
Standard activity is calculated using computer generated chromium result.(ii)
Weight of dose is calculated from weight of syringe and dose before injection − after injection.(iii)
Po (zero time plasma activity) is corrected by extrapolating the curve to zero time.Slope clearance (C-slope) is calculated by(2)C-slopeslope intercept=0.693T1/2×Vd.Normalized GFR is calculated by(3)NormalizedGFR=C-slopePatient’s BSA×1.73.
### 2.2. Calibration for the Serum Creatinine Assay
Serum creatinine was measured on a Dimension Vista system clinical chemistry analyzer (Siemens) with an assay using a modification of the kinetic Jaffe reaction (alkaline picrate reaction). This modified technique was reported to be less susceptible than conventional methods to interference from noncreatinine Jaffe positive compounds [15]. The creatinine assay was adjusted for calibration with the isotope dilution mass spectrometry (IDMS).
### 2.3. Estimated GFR Calculations
The eGFR values were calculated by using CG, 4-MDRD, and CKD-EPI equations. 4-MDRD and CKD-EPI derived eGFR are expressed as ml/min/1.73 m2. Meanwhile CG equation was converted from ml/min to ml/min/1.73 m2 by multiplying the calculated values by 1.73 and dividing by BSA (Table 1).Table 1
Different eGFR formula according to gender.
eGFR methods
Gender
Equations
Cockcroft-Gault
Male
140
-
A
g
e
×
m
a
s
s
(
k
g
)
×
1.23
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
(
u
m
o
l
/
L
)
Female
140
-
A
g
e
×
m
a
s
s
(
k
g
)
×
1.04
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
(
u
m
o
l
/
L
)
4-MDRD
Male
32788
×
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
-
1.154
×
A
g
e
-
0.203
×
{
1.212
i
f
B
l
a
c
k
}
Female
32788
×
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
-
1.154
×
A
g
e
-
0.203
×
{
1.212
if Black
}
×
0.742
(Serum creatinine in umol/L)
CKD-EPI
Male
141
×
min
(
SCr
/
0.9,1
)
-
0.411
×
max
(
SCr
/
0.9,1
)
-
1.209
×
0.993
A
g
e
×
{
1.159
if Black
}
Female
141
×
min
(
SCr
/
0.7,1
)
-
0.329
×
max
(
SCr
/
0.7,1
)
-
1.209
×
0.993
A
g
e
×
{
1.159
if Black
}
×
1.018
Cockcroft-Gault BSA
Calculated Cockcroft-Gault
×
1.73
BSA
### 2.4. Statistical Analysis
SPSS version 20.0 was used to calculate baseline characteristics frequency, mean, median, range, and standard deviation. Mean GFR were given with a 95% confidence interval (CI) unless indicated otherwise.p values < 0.05 were considered significant. Pearson’s correlation coefficients (r) were calculated between 51Cr-EDTA clearance and estimated GFR by a linear correlation analysis. Pairwise comparison of the mean was performed using paired t-test.Bias, precision, and accuracy within 10% and 30% of the measured GFR were determined. Bias is defined as mean difference between estimated GFR and the measured GFR (51Cr-EDTA). The precision of the estimates was determined as SD of the mean difference between measured GFR and eGFR. Accuracy was determined by integrating precision and bias and was calculated as the percentage of GFR estimates within 10 and 30% of the measured GFR. Moreover, a graphical analysis was carried out according to Bland and Altman plots. This was used to assess the limits of agreement between the eGFR and the measured GFR.In our study, accuracy is the most important determinants for a good estimated GFR and it is best if further supported by lower bias, greater precision, and lower limits of agreement. However, as we understand that bias, precision and limits of agreement may be affected by the overall means and outliers; therefore the individual parameter may not reflect the best estimated GFR.
## 2.1.51Cr-EDTA Measurement
Measured GFR is determined by collecting blood sample from different arm 2, 2.5, 3, and 4 hours later following51Cr-EDTA single injection technique. Plasma clearance of 51Cr-EDTA from 4 samples was obtained based on the interval above. Patient’s height and weight were measured for body surface area (BSA) calculation. GFR was calculated using the slope-intercept method and normalized to BSA, which was calculated using du Bois formula. The result was then corrected using Brochner-Mortensen equation.Volume distribution (Vd) is calculated by(1)Vd=Standard activity (cpm)×weight of dose×100mlPo (cpm)×weight of standard.(i)
Standard activity is calculated using computer generated chromium result.(ii)
Weight of dose is calculated from weight of syringe and dose before injection − after injection.(iii)
Po (zero time plasma activity) is corrected by extrapolating the curve to zero time.Slope clearance (C-slope) is calculated by(2)C-slopeslope intercept=0.693T1/2×Vd.Normalized GFR is calculated by(3)NormalizedGFR=C-slopePatient’s BSA×1.73.
## 2.2. Calibration for the Serum Creatinine Assay
Serum creatinine was measured on a Dimension Vista system clinical chemistry analyzer (Siemens) with an assay using a modification of the kinetic Jaffe reaction (alkaline picrate reaction). This modified technique was reported to be less susceptible than conventional methods to interference from noncreatinine Jaffe positive compounds [15]. The creatinine assay was adjusted for calibration with the isotope dilution mass spectrometry (IDMS).
## 2.3. Estimated GFR Calculations
The eGFR values were calculated by using CG, 4-MDRD, and CKD-EPI equations. 4-MDRD and CKD-EPI derived eGFR are expressed as ml/min/1.73 m2. Meanwhile CG equation was converted from ml/min to ml/min/1.73 m2 by multiplying the calculated values by 1.73 and dividing by BSA (Table 1).Table 1
Different eGFR formula according to gender.
eGFR methods
Gender
Equations
Cockcroft-Gault
Male
140
-
A
g
e
×
m
a
s
s
(
k
g
)
×
1.23
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
(
u
m
o
l
/
L
)
Female
140
-
A
g
e
×
m
a
s
s
(
k
g
)
×
1.04
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
(
u
m
o
l
/
L
)
4-MDRD
Male
32788
×
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
-
1.154
×
A
g
e
-
0.203
×
{
1.212
i
f
B
l
a
c
k
}
Female
32788
×
S
e
r
u
m
C
r
e
a
t
i
n
i
n
e
-
1.154
×
A
g
e
-
0.203
×
{
1.212
if Black
}
×
0.742
(Serum creatinine in umol/L)
CKD-EPI
Male
141
×
min
(
SCr
/
0.9,1
)
-
0.411
×
max
(
SCr
/
0.9,1
)
-
1.209
×
0.993
A
g
e
×
{
1.159
if Black
}
Female
141
×
min
(
SCr
/
0.7,1
)
-
0.329
×
max
(
SCr
/
0.7,1
)
-
1.209
×
0.993
A
g
e
×
{
1.159
if Black
}
×
1.018
Cockcroft-Gault BSA
Calculated Cockcroft-Gault
×
1.73
BSA
## 2.4. Statistical Analysis
SPSS version 20.0 was used to calculate baseline characteristics frequency, mean, median, range, and standard deviation. Mean GFR were given with a 95% confidence interval (CI) unless indicated otherwise.p values < 0.05 were considered significant. Pearson’s correlation coefficients (r) were calculated between 51Cr-EDTA clearance and estimated GFR by a linear correlation analysis. Pairwise comparison of the mean was performed using paired t-test.Bias, precision, and accuracy within 10% and 30% of the measured GFR were determined. Bias is defined as mean difference between estimated GFR and the measured GFR (51Cr-EDTA). The precision of the estimates was determined as SD of the mean difference between measured GFR and eGFR. Accuracy was determined by integrating precision and bias and was calculated as the percentage of GFR estimates within 10 and 30% of the measured GFR. Moreover, a graphical analysis was carried out according to Bland and Altman plots. This was used to assess the limits of agreement between the eGFR and the measured GFR.In our study, accuracy is the most important determinants for a good estimated GFR and it is best if further supported by lower bias, greater precision, and lower limits of agreement. However, as we understand that bias, precision and limits of agreement may be affected by the overall means and outliers; therefore the individual parameter may not reflect the best estimated GFR.
## 3. Results
A total of 51 patients were recruited with mean age of 58.7 years, where the youngest was 26 years old and the eldest was 78 years old. Majority of our patients are males representing 90.2%. The mean height and weight in our patient were 164.5 cm and 71.9 kg, respectively, with mean BMI of 26.5 kg/m2. Vast majority of our study patients had diabetic nephropathy (35.3%) and hypertension (19.6%) as the main cause of their CKD. Summary of patient’s baseline characteristics is tabulated in Table 2.Table 2
Baseline characteristics of patients.
Characteristic(n=51)
Mean ± SD (median) orn (%)
Male
46 (90.2)
Age (year)
58.7 ± 12.6 (61.0)
BMI (kg/m2)
26.5 ± 4.6 (25.5)
Plasma creatinine (umol/l)
192.5 ± 66.7 (190.0)
Plasma urea nitrogen (mmol/l)
9.8 ± 3.5 (9.4)
Plasma albumin (g/l)
37.9 ± 3.0 (38.0)
Measured GFR (ml/min/1.73m2)
42.04 ± 22.5 (35.1)
Causes of CKD
Diabetic nephropathy
18 (35.3)
Hypertension
10 (19.6)
Nondiabetic glomerulopathy
4 (7.8)
Renal calculi/nephrocalcinosis
4 (7.8)
Other causes
10 (19.7)
Unknown
5 (9.8)
CKD stages
1
2 (3.9)
2
8 (15.7)
3
26 (51.0)
4
15 (29.4)
Medical history
Diabetes mellitus
33 (64.7)
Hypertension
46 (90.2)
Medications
Diuretics
14 (27.5)
Antihypertensive
48 (94.1)
OHA/insulin
32 (62.7)
Statin
41 (80.4)
Smoking status
Current smoker
6 (11.8)
Ex-smoker
21 (41.2)
Nonsmoker
24 (47.1)From our cohort, mean measured GFR was 42.04 (17.70–111.10) ml/min/1.73 m2, while the estimated GFR based on CGBSA, 4-MDRD, and CKD-EPI formula were 40.47 (16.52–115.52), 35.90 (14.00–98.00), and 37.24 (14.00–121.00), respectively. The calculated GFR of the 4-MDRD and CKD-EPI differed significantly from measured GFR with p value = 0.001 and 0.005. The correlation between estimated and measured GFR is illustrated in Table 3.Table 3
Correlation coefficient (r), mean, bias, precision, and accuracy for CGBSA, 4-MDRD, and CKD-EPI formula.
Correlation coefficient (r)
Mean GFR
Range (IQR)
p value
Mean difference (bias)
SD of mean bias (precision)
Accuracy within
Lower
Upper
10%
30%
Measured GFR
42.039
17.70
111.10
CGBSA
0.877∗
40.467
16.52
115.52
0.303
−1.573
10.802
9.8
47.1
4-MDRD
0.848∗
35.902
14.00
98.00
0.001
−6.137
12.058
13.7
54.9
CKD-EPI
0.854∗
37.235
14.00
121.00
0.005
−4.804
11.697
13.7
49.0
∗Significantly correlating with p<0.001.
(Bias: mean difference of estimated GFR and measured GFR; accuracy:n percentage of GFR estimates within n% of measured GFR; IQR: interquartile range).Bias of CGBSA (1.573 ml/min/1.73 m2) was smaller than 4-MDRD (6.137 ml/min/1.73 m2) and CKD-EPI (4.804 ml/min/1.73 m2), while the precisions of the estimated GFR showed that CGBSA is more precise followed by CKD-EPI and 4-MDRD formula. However, from our cohort we found that 4-MDRD is the most accurate formula with the accuracy of 13.7 and 54.9% within 10 and 30% of measured GFR, respectively. Nevertheless, we noted that 4-MDRD formula underestimated GFR by 6.137 ml/min/1.73 m2; this was likely because of the outliers in this study cohort.The differences between estimated and measured GFR were illustrated using a graphical technique according to Bland and Altman plot (Figures1(a)–1(c)). These figures display the span between +2SD and −2SD of the mean difference (limits of agreement between 2 methods), which represent 95% CI. From the chart below it showed that smaller limits of agreement were found for the CGBSA (43.21 ml/min/1.73 m2), followed by CKD-EPI (46.78 ml/min/1.73 m2) and 4-MDRD (48.23 ml/min/1.73 m2) formula. Even though limits of agreement in 4-MDRD formula are wider, Figure 1(b) illustrated that each patient distribution is closer from one another and these wider limits of agreement can be explained by the extreme outliers (underestimated by almost 60 mls/min/1.73 m2) that present in this group. Thus, this make 4-MDRD formula the most accurate estimated GFR in comparison with 51Cr-EDTA throughout all ranges of GFR in our study cohort.Figure 1
(a–c) Bland and Altman analysis of GFR estimates. In this analysis, the differences between estimated and measured GFR are plotted against the average of the estimated and measured GFR for each individual patient.
(a)
Cockcroft-Gault BSA equation and measured GFR
(b)
4-MDRD equation and measured GFR
(c)
CKD-EPI equation and measured GFRPatients were further divided into two groups according to the measured GFR: GFR < 60 ml/min/1.73 m2 or GFR ≥ 60 ml/min/1.73 m2. In subgroup GFR < 60 ml/min/1.73 m2, lower bias was found for CGBSA formula (0.34 ml/min/1.73 m2) followed by CKD-EPI (2.24 ml/min/1.73 m2) and 4-MDRD (2.95 ml/min/1.73 m2). However, better accuracy within 10% of measured GFR was found in 4-MDRD and CKD-EPI formula. In subgroup GFR ≥ 60 ml/min/1.73 m2, a different pattern of bias and accuracy was noted. In this subgroup, CGBSA formula was found to be better in terms of bias (9.40 ml/min/1.73 m2) and accuracy within 10% of measured GFR (40%), while 4-MDRD and CKD-EPI formula were noted to have higher bias, 19.22 and 15.32 ml/min/1.73 m2, respectively, and lower accuracy within 10% of measured GFR. Precisions of all the equations were significantly lower in the patients with GFR <60 ml/min/1.73 m2 (Table 4).Table 4
Mean, bias, precision, and accuracy of GFR estimates within two GFR subgroups.
Variable
GFR < 60 ml/min/1.73 m2 (n=41)
GFR ≥ 60 ml/min/1.73 m2 (n=10)
GFR(ml/min/1.73 m2)
Measured
33.19 ± 10.39
78.32 ± 22.61
CGBSA
33.53 ± 10.79∗
68.92 ± 21.10∗∗
4-MDRD
30.24 ± 10.27∗
59.10 ± 21.35∗∗
CKD-EPI
30.95 ± 11.14∗
63.00 ± 23.49∗∗
Median bias
CGBSA
−0.99 (−9.6, 19.81)
−9.80 (−33.00, 27.35)
4-MDRD
−2.60 (−17.10, 10.20)
−19.70 (−55.80, 23.60)
CKD-EPI
−1.80 (−15.10, 13.20)
−14.70 (−48.80, 32.60)
Mean difference
CGBSA
0.34 ± 7.04
−9.40 ± 18.53
4-MDRD
−2.95 ± 6.13
19.22 ± 20.11
CKD-EPI
−2.24 ± 6.22
−15.32 ± 20.86
Accuracy within 10
%
CGBSA
24.4
40.0
4-MDRD
31.7
20.0
CKD-EPI
31.7
10.0
Accuracy within 30
%
CGBSA
63.4
70.0
4-MDRD
65.9
80.0
CKD-EPI
65.9
80.0
∗Mean CGBSA GFR versus measured GFR p=0.761, mean 4-MDRD GFR versus measured GFR p=0.004, and mean CKD-EPI GFR versus measured GFR p=0.026.
∗
∗Mean CGBSA GFR versus measured GFR p=0.143, mean 4-MDRD GFR versus measured GFR p=0.014, and mean CKD-EPI GFR versus measured GFR p=0.045.Assessment of eGFR formula in patients with BMI < 23 kg/m2 and BMI ≥ 23 kg/m2 was performed. In both subgroups, better accuracy within 10 and 30% of measured GFR was found in 4-MDRD formula, which was 14.3 and 50% in BMI < 23 kg/m2 while in subgroup BMI ≥ 23 kg/m2 was 16.2 and 54.0% (Table 5).Table 5
Mean, bias, precision, and accuracy of GFR estimates within two BMI subgroups.
Variable
BMI < 23 kg/m2 (n=14)
BMI ≥ 23 kg/m2 (n=37)
GFR(ml/min/1.73 m2)
Measured
43.19 ± 19.44
41.61 ± 23.78
CGBSA
41.80 ± 23.96∗
39.94 ± 17.67∗∗
4-MDRD
43.14 ± 23.28∗
33.16 ± 13.90∗∗
CKD-EPI
44.57 ± 25.73∗
34.46 ± 15.40∗∗
Median bias
CGBSA
−1.34 (−23.8, 27.35)
−1.66 (−33.07, 19.81)
4-MDRD
0.04 (−22.8, 23.6)
−8.44 (−55.80, 6.10)
CKD-EPI
1.39 (−19.8, 32.6)
−7.15 (−48.80, 7.10)
Mean difference
CGBSA
−1.34 ± 11.54
−1.66 ± 10.68
4-MDRD
−0.04 ± 11.06
8.44 ± 11.74
CKD-EPI
1.39 ± 12.31
−7.15 ± 10.71
Accuracy within 10
%
CGBSA
7.0
8.1
4-MDRD
14.3
16.2
CKD-EPI
14.3
10.8
Accuracy within 30
%
CGBSA
50.0
48.6
4-MDRD
50.0
54
CKD-EPI
42.9
54.1
∗Mean CGBSA GFR versus measured GFR p=0.672, mean 4-MDRD GFR versus measured GFR p=0.989, and mean CKD-EPI GFR versus measured GFR p=0.680.
∗
∗Mean CGBSA GFR versus measured GFR p=0.350, mean 4-MDRD GFR versus measured GFR p<0.001, and mean CKD-EPI GFR versus measured GFR p<0.001.
## 4. Discussions
This study investigated the performance of different creatinine-based eGFR formula in Malay population in a tertiary hospital in Malaysia. An accurate eGFR measurement is extremely important as a tool for CKD diagnosis, drug dosage preparations, and procedural preparation and subsequently to determine the efficacy of novel treatments to delay CKD progression in clinical practice. Performing labor-intensive radio-labelled GFR measurement is not practical and economical particularly in developing country like Malaysia.It is known that racial coefficient is an important factor to determine accurate GFR [11–14, 16, 17]. In our cohort, the eGFR obtained from each formula showed significant correlation with measured GFR (51Cr-EDTA). However, the eGFR by 4-MDRD formula in general was found to be more accurate than the other eGFR equations in estimating GFR in our small cohort.In the subgroup analysis of measured GFR < 60 mls/min/1.73 m2, our data showed that CKD-EPI and 4-MDRD formulas showed better performance pertaining to the accuracy in comparison with other estimates GFR. The results corresponded with MDRD study that was performed in White American patients, which revealed that MDRD equation showed a reliable performance in estimating GFR in CKD patients with GFR < 60 mls/min/1.73 m2. However, in Singaporean multiethnic study, it revealed that CKD-EPI was more accurate than the 4-MDRD in GFR < 60 ml/min/1.73 m2 and overestimated reference GFR when the reference GFR was ≥ 60 ml/min/1.73 m2 [18].Estimating GFR in overweight and obese populations is another interesting factor to look into as weight and body size may influence the level of creatinine. In subgroup analysis of BMI ≥ 23 kg/m2, greater accuracy was noted in 4-MDRD formula. Similar result was noted in another local study done by National University of Malaysia (UKM) that revealed MDRD equation showed greater accuracy and precision in obese individuals [19]. Interestingly, in BMI < 23 kg/m2, 4-MDRD fared better as well unlike in lean population in African that showed that CG was better than MDRD and CKD-EPI formula with regard to the narrow limits of agreement [16].
## 5. Limitations of the Study
This is a small single-centre cohort of CKD patients, who are predominantly male and mainly consisted of CKD stages 3 and 4. Due to the continuous sampling method used in this study, we are unable to ensure equal distribution of patients in different arms of subgroup analysis. Thus, to further validate the more recent CKD-EPI formula, more inclusion of other stages of CKD is needed. Although this study has the above-mentioned limitations, this is the first study to be conducted in Malaysia using51Cr-EDTA as reference GFR.
## 6. Conclusion
We found that 4-MDRD equation seems to be more accurate in estimating GFR in our small cohort of Malay CKD patients except in subgroup of GFR ≥ 60 mls/min/m2, where CGBSA was found to be better. We would like to propose further studies to look into the need for racial correction factor to improve the performance of the original 4-MDRD formula in Malay population.
---
*Source: 2901581-2017-06-18.xml* | 2017 |
# Long Noncoding RNA SOX2-OT: Regulations, Functions, and Roles on Mental Illnesses, Cancers, and Diabetic Complications
**Authors:** Pu-Yu Li; Ping Wang; She-Gan Gao; Dao-Yin Dong
**Journal:** BioMed Research International
(2020)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2020/2901589
---
## Abstract
SRY-box transcription factor 2 (SOX2) overlapping transcript (SOX2-OT) is an evolutionarily conserved long noncoding RNA. Its intronic region contains the SOX2 gene, the major regulator of the pluripotency of embryonic stem cells. The human SOX2-OT gene comprises multiple exons and has multiple transcription start sites and generates hundreds of transcripts. Transcription factors (IRF4, AR, and SOX3), transcriptional inhibitors (NSPc1, MTA3, and YY1), and miRNAs (miR-211 and miR-375) have been demonstrated to control certain SOX2-OT transcript level at the transcriptional or posttranscriptional levels. Accumulated evidence indicates its crucial roles in the regulation of the SOX2 gene, miRNAs, and transcriptional process. Restricted expression of SOX2-OT transcripts in the brain results in the association between SOX2-OT single nucleotide polymorphisms and mental illnesses such as schizophrenia and anorexia nervosa. SOX2-OT is notably elevated in tumor tissues, and a high level of SOX2-OT is well correlated with poor clinical outcomes in cancer patients, leading to the establishment of its role as an oncogene and a prognostic or diagnostic biomarker for cancers. The emerging evidence supports that SOX2-OT mediates diabetic complications. In summary, SOX2-OT has diversified functions and could be a therapeutic target for various diseases.
---
## Body
## 1. Introductions
SRY-box transcription factor 2 (SOX2) overlapping transcript (official symbol SOX2-OT according to the HUGO Gene Nomenclature Committee) is an evolutionarily conserved long noncoding RNA (lncRNA). The SOX2-OT gene is mapped to human chromosomal locus 3q26.33 and is located in a highly conserved region of more than 750 kb in humans and other vertebrates [1]. The SOX2-OT gene contains the key regulator of embryonic stem cell pluripotency, i.e., the SOX2 gene, within its intronic region, and both SOX2-OT and SOX2 are transcribed in the same orientation [2]. The human SOX2-OT gene comprises multiple exons and has multiple transcription start sites with complicated transcriptional features [1, 2]. Initially, Amaral et al. identified several variants of the SOX2-OT gene in mice and humans, including transcripts with multiple transcription start sites [2]. This group also identified SOX2-OT variants in chickens, frogs, and zebrafishes, and some transcripts appear to be species-specific [2]. As deep DNA sequencing technology has advanced, researchers have found that the SOX2-OT gene is expressed as 104 mRNA-like transcripts, the longest of which is approximately 4.3 kb in humans (according to the Ensembl genome database project) [3]. The comprehensive noncoding RNA sequence database RNA Central, which is maintained by the European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), includes information for 161 transcripts of the human SOX2-OT gene [4]. In mice, the SOX2 overlapping transcript (official symbol Sox2ot according to Mouse Genome Informatics) is mapped to chromosome 3qA3, and the transcript length is shorter than that of the human homolog. The Ensembl genome database includes 18 information for transcripts of the mouse Sox2ot gene [5].We searched studies regarding the SOX2-OT gene on PubMed and found that the SOX2-OT gene has received unprecedented attention within the last five years. The PubMed records indicated that only 17 articles exploring the functions of the SOX2-OT gene were published before 2015, whereas nearly 80 articles investigating the SOX2-OT gene were published from 2015 to date (May 2020). The earliest study regarding the SOX2-OT gene was published in 2003 [6]. In this study, the SOX2 gene was discovered by genomic analysis to be located in an intron of another gene, which they named SOX2-OT [6]. The researchers demonstrated that SOX2-OT contains at least five exons (current studies have shown that it contains dozens of exons) and produces a mRNA-like transcript from the same strand that SOX2 is located on [6]. This transcript is evolutionarily conserved; the human SOX2-OT transcript and available mouse expressed sequence tags share 80% nucleotide identity [6]. In addition, the genomic region (approximately 40 kb) encompassing the SOX2-OT transcription unit is highly conserved across vertebrates [6]. Subsequently, accumulating evidence has indicated that the SOX2-OT gene is associated with mental illnesses, cancers, and diabetic complications. SOX2-OT expression is upregulated during the central nervous system development and is restricted to the brain in adult humans and other vertebrates [2, 7]. Therefore, single-nucleotide polymorphisms (SNPs) in the SOX2-OT gene are associated with mental illnesses [8, 9]. Moreover, an increased expression of SOX2-OT is observed in tissues from various cancers; SOX2-OT typically functions as an oncogene to influence cancer progression and can serve as a prognostic or diagnostic biomarker for cancers [10]. In addition, studies have demonstrated that the SOX2-OT gene is involved in diabetic complications and other diseases [11–13]. In this review, we comprehensively summarize the most recent research progress in the regulation and function of SOX2-OT and the association of this lncRNA with various diseases. Moreover, we discuss the potential opportunities and challenges revealed by these findings.
## 2. SOX2-OT Regulates SOX2 Expression
The SOX2 gene is a key regulator of stem cell pluripotency and is embedded in an intron of SOX2-OT [1, 2]. lncRNAs can regulate the expression of adjacent overlapping genes via specific mechanisms [14]. Various studies have investigated the regulatory relationship between SOX2-OT and SOX2 (Table 1). Almost all cancer studies involving SOX2-OT and SOX2 have indicated that upregulation of SOX2-OT promotes SOX2 expression in cancer cells (Table 1); however, one study showed that SOX2-OT overexpression did not affect SOX2 expression [15]. Studies on septic cardiomyopathy demonstrated that the level of SOX2-OT is inversely correlated with that of SOX2 [16]. Furthermore, the levels of SOX2-OT and SOX2 are negatively correlated during neural differentiation of mouse embryonic stem cells [7] (Figure 1).Table 1
SOX2-OT regulates SOX2 expression.
RegulationIntermediatorCell modelCellular functionReferenceIncreasemiR-200cBladder cancerMetastasis and stemnessZhan et al. [17]IncreaseUnknownEsophageal squamous cell carcinomaMetastasis and stemnessDu et al. [56]DecreaseUnknownSeptic cardiomyopathyMitochondrial dysfunctionChen et al. [16]No effectUnknownEsophageal squamous cell carcinomaCell proliferationWu et al. [15]IncreaseUnknownCholangiocarcinomaProliferation and metastasisWei et al. [57]DecreasePromoter-enhancer loopEmbryonic developmentNeural differentiationMessemaker et al. [7]IncreasemiR-200 familyPancreatic ductal adenocarcinomaEMT, stemness, invasion, and metastasisLi et al. [18]DecreaseYY1Embryonic developmentRepresses neural progenitor proliferation and promotes neuronal differentiationKnauss et al. [20]IncreaseUnknownPancreatic ductal adenocarcinomaProliferation and tumor growthZhang et al. [19]IncreaseUnknownLung cancerProliferation, migration, invasion, and stemnessWang et al. [38]IncreaseUnknownBreast cancerProliferationAskarian-Amiri et al. [58]Note: EMT: epithelial-mesenchymal transition; YY1: Yin Yang-1.Figure 1
Long noncoding RNA SOX2-OT’s regulations, functions, and roles on mental illnesses, cancers, and diabetic complications. Transcription activators ((A) SOX2, IRF4, AR, and SOX3) can upregulate SOX2-OT expression, but transcription inhibitors ((B) NSPc1, MTA3, and YY1) and miRNAs ((C) miR-211 and miR-375) downregulate SOX2-OT expression. D. SOX2-OT upregulates SOX2 expression in cancer cells. (E) SOX2-OT downregulates SOX2 expression in neural stem cells. SOX2-OT can control miRNA levels via serving as a miRNA sponge (F) and affect transcription via serving as a bridge between epigenetic factors and DNA (G). (H) SOX2-OT SNPs are associated with mental illnesses. (I) SOX2-OT is a biomarker for cancers.Mechanistic investigations have revealed that SOX2-OT upregulates or downregulates the SOX2 expression through diverse pathways. Two studies demonstrated that SOX2-OT upregulates the SOX2 expression via the miR-200 family members in cancer cells [17, 18]. SOX2-OT acts as a miRNA sponge that competitively binds to miR-200 family members in order to upregulate the expression of SOX2 in cancer cells [17, 18]. One study revealed that the luciferase activity of the SOX2 promoter is significantly increased when SOX2-OT is overexpressed in pancreatic ductal adenocarcinoma cells, suggesting that SOX2-OT is a transcriptional activator of the SOX2 gene [19]. However, a study on central nervous system development showed that SOX2-OT physically interacts with the multifunctional transcriptional regulator YY1, which binds to several CpG islands in the SOX2 locus in a SOX2-OT-dependent manner and downregulates SOX2 expression in neural stem cells [20]. Another study showed that SOX2-OT impairs the formation of the chromatin promoter-enhancer loop upstream of the SOX2 gene and disrupts SOX2 transcription in neural stem cells [7]. Although few studies have investigated the mechanism by which SOX2-OT regulates the SOX2 expression in cancer cells or neural stem cells (Table 1), the regulation of the SOX2 expression by SOX2-OT in tumor cells follows a pattern opposite to that in neural stem cells (Table 1).
## 3. SOX2-OT Is a miRNA Sponge and a Regulator of Transcription
Research has suggested that some lncRNAs are involved in the competitive binding of miRNAs [21]. The members of this major subset of lncRNAs are called competing endogenous RNAs (ceRNAs), or miRNA sponges, and they form a regulatory network that controls the expression of protein-coding genes [22]. In this network, lncRNAs positively regulate the expression of protein-coding genes by competitively binding to their miRNAs [22]. SOX2-OT has been identified as an important ceRNA that affects cancer progression (Table 2, Figure 2(a)). An omics study revealed that SOX2-OT interacted with 6 differentially expressed miRNAs (hsa-mir-192-5p, hsa-mir-215-5p, hsa-mir-204-5p, hsa-mir-205-5p, hsa-mir-338-3p, hsa-mir-375) among 96 esophageal squamous cell carcinoma samples and 13 normal tissue samples [23]. In addition, numerous studies have demonstrated that SOX2-OT can bind to unique miRNAs in various cancers, and almost no overlapping miRNAs have been identified among those cancers (Table 2). miR-200c is the only exception, as SOX2-OT can target miR-200c in both bladder cancer and pancreatic ductal adenocarcinoma [17, 18]. Although SOX2-OT can target various miRNAs, it regulates similar cellular functions and behaviors, such as cancer cell proliferation, migration, invasion, metastasis, epithelial-mesenchymal transition (EMT), and stemness maintenance (Table 2).Table 2
SOX2-OT is a miRNA sponge.
miRNACancerTargetCellular functionReferencehsa-mir-192-5p, hsa-mir-215-5p, hsa-mir-204-5p, hsa-mir-205-5p, hsa-mir-338-3p, hsa-mir-375Esophageal squamous cell carcinomaUnknownUnknownTian et al. [23]miR-200cBladder cancerSOX2Increases bladder cancer cell stemness and metastasisZhan et al. [17]miR-146b-5pNasopharyngeal carcinomaHNRNPA2B1Increases proliferation and metastasis; decreases apoptosisZhang and Li [59]miR-369-3pProstate cancerCFL2Increases proliferation and migrationWo et al. [60]miR-363Ewing’s sarcomaFOXP4Increases proliferation and invasion; decreases apoptosisMa et al. [61]miR-132Non-small-cell lung cancerZEB2Increases proliferation, migration, invasion, and EMTZhang et al. [62]miR-211PheochromocytomaMCL-1 isoform 2Increases cell viability, migration, and invasion; decreases apoptosis and autophagyYin et al. [49]miR-194-5pGastric cancerAKT2Promotes proliferation, metastasis, invasion, migration, and EMTWei et al. [63], Qu et al. [64]miR-200 familyPancreatic ductal adenocarcinomaSOX2Promotes EMT and stem cell-like propertiesLi et al. [18]miR-194-5p, miR-122GliomaSOX3Increases proliferation, migration, and invasion; decreases apoptosisSu et al. [65]Note: EMT: epithelial-mesenchymal transition; Sox2: SRY-box transcription factor 2; HNRNPA2B1: heterogeneous nuclear ribonucleoprotein A2/B1; CFL2: cofilin 2; FOXP4: forkhead box P4; ZEB2: zinc finger E-box binding homeobox 2; MCL1 Isoform 2: myeloid cell leukemia sequence 1 isoform 2; AKT2: AKT serine/threonine kinase 2; SOX3: SRY-box transcription factor 3.Figure 2
SOX2-OT is a miRNA sponge and a regulator of transcription. (a) SOX2-OT is a miRNA sponge. (b) SOX2-OT acts as a bridge between epigenetic factors and DNA to affect gene expression. (c) SOX2-OT acts as a destabilizer of transcription factors to control gene expression. PRC: polycomb repressive complex; EZH2: enhancer of zeste 2; FUS: FUS RNA binding protein.
(a)(b)(c)In addition to acting as a miRNA sponge, SOX2-OT acts as a regulator of transcription by serving as a bridge between epigenetic factors and DNA to affect gene expression (Figure2(b)). A recent study revealed that SOX2-OT interacts with EZH2, recruits EZH2 to DNA to form the polycomb repressive complex 2 (PRC2), induces H3K27me3, and epigenetically inhibits PTEN expression in laryngeal squamous cell carcinoma cells [24]. Studies have demonstrated that SOX2-OT binds to nervous system polycomb 1 (NSPc1), a key component of polycomb repressive complex 1 (PRC1), in H4 glioma cells [25] and U87 glioma cells [26], and regulates cancer cell proliferation and apoptosis. SOX2-OT can also act as a destabilizer of transcription factors to control gene expression (Figure 2(c)). A study suggested that SOX2-OT directly binds to the transcription factor FUS and that FUS protein stability is altered by this binding [27]. Thus, SOX2-OT acts as a tumor promoter in pancreatic ductal adenocarcinoma by physically binding to FUS to regulate its downstream cell cycle-associated factors CCND1 and p27 [27] (Figure 1).
## 4. SOX2-OT Is Regulated at the Transcriptional and Posttranscriptional Levels
Most relevant studies have shown that SOX2-OT levels are increased in various cancers and have described the SOX2-OT gene as an oncogene [10]. An increasing number of studies have investigated the mechanism underlying SOX2-OT upregulation in cancer cells (Table 3). These studies have focused on transcriptional and posttranscriptional regulation. Four transcription factors (SOX2, IRF4, AR, and SOX3) were identified to be able to bind directly to the SOX2-OT promoter and promote its transcription (Table 3). Other studies identified three transcriptional inhibitors (NSPc1, MTA3, and YY1) that recruit the repressive complex to the SOX2-OT promoter to repress its expression (Table 3). Interestingly, Shafiee et al. revealed that two miRNAs (miR-211 and miR-375) are responsible for SOX2-OT downregulation in a model of Helicobacter pylori-induced carcinogenesis (Table 3, Figure 1).Table 3
SOX2-OT is regulated at the transcriptional and posttranscriptional levels.
FactorRegulatory effectCell modelReferenceNSPc1Represses transcriptionGlioma cellsLiang et al. [26]MTA3Represses transcriptionEsophageal squamous cell carcinoma cellsDu et al. [56]SOX2Promotes transcriptionEsophageal squamous cell carcinoma cellsWu et al. [15]IRF4Promotes transcriptionCholangiocarcinoma cellsWei et al. [57]YY1Represses transcriptionPancreatic ductal adenocarcinoma cellsZhang et al. [19]ARPromotes transcriptionEmbryonic neural stem cellsTosetti et al. [66]SOX3Promotes transcriptionGlioblastoma stem cellsSu et al. [65]miR-211Downregulates expression by directly binding to SOX2-OTEmbryonal carcinoma stem cells (NT-2)Shafiee et al. [67]miR-375Downregulates expression by directly binding to SOX2-OTEmbryonal carcinoma stem cells (NT-2)Shafiee et al. [68]Note: NSPc1: nervous system polycomb 1; MTA3: metastasis-associated protein 3; IRF4: interferon regulatory factor 4; YY1L Yin Yang-1; ARL androgen receptor; Sox3: SRY-box transcription factor 3.
## 5. SOX2-OT Is Upregulated during Central Nervous System Development, and Its Expression Is Restricted to the Brain
Studies have reported that a striking 40% of lncRNAs are expressed specifically in the brain, indicating the importance of lncRNAs in central nervous system development [28]. Numerous lncRNAs have been identified as regulators of the central nervous system development. Early studies showed that SOX2-OT is highly expressed in mouse embryonic stem cells and is downregulated during the differentiation of embryoid bodies into mesoderm [2]. However, Messemaker et al. demonstrated strong upregulation of SOX2-OT upon the differentiation of embryoid bodies into neuroectoderm, and upregulation of SOX2-OT was found to coincide with neural progenitor/stem cell formation as assessed via the induction of the SOX1 expression, which is a very early and specific marker of the neuroectodermal lineage [7]. Furthermore, SOX2-OT expressed sequence tags have been found in differentiated mouse neural stem cells, and its expression is confirmed in mouse primary neuronal cells [2]. RNA whole-mount in situ hybridization showed that in mice, SOX2-OT expression is limited to the developing brain, the ventral part of the neural tube, and the optic vesicle in mice [7]. Another study indicated that SOX2-OT is expressed in the developing cerebral cortex of mice, where it represses neural progenitor cell proliferation and promotes neuronal differentiation [20].To investigate the possible involvement of SOX2-OT in neural differentiation processes, Amaral et al. examined the dynamic change in the SOX2-OT expression via a neurosphere assay, an in vitro model of neurogenesis with cultures of neurospheres originating from neural stem cells and undifferentiated precursors in the subventricular zone of adult mice [2]. The differentiated population of neurons and glial cells from neurospheres cultured for 7 days in differentiation medium exhibited increased expression of SOX2-OT [2].Similar results have also been found in developing zebrafish embryos [7]. Studies have revealed that SOX2-OT is expressed in neuroectodermal tissue in zebrafish embryos at the tailbud stage [2]. Subsequently, SOX2-OT is highly expressed throughout the developing brain and eyes and is expressed at lower levels in the posterior neural tube at 28 hours postfertilization (hpf). In situ hybridization indicated specific expression of SOX2-OT in the retina and central nervous system in 48 hpf embryos, and this expression was maintained in the brain throughout the embryonic development until at least 6 days postfertilization (dpf) [2].Importantly, data from the Genotype-Tissue Expression (GTEx) project show that in adult humans, the SOX2-OT expression is almost completely restricted to the brain, including regions such as the cortex, hippocampus, hypothalamus, cerebellum, and spinal cord [29]. Single-cell RNA-seq data in the Human Cell Landscape (HCL) project indicate that SOX2-OT expression is concentrated in oligodendrocytes and FGF13+ or CXCL14+ neurons in adult humans [30].In summary, SOX2-OT is upregulated during central nervous system development (neurogenesis), and its expression is ultimately restricted to the brain in adult vertebrates.
## 6. SOX2-OT SNPs Are Associated with Mental Illnesses
Because SOX2-OT expression is restricted to the brain in adult humans, SOX2-OT SNPs are correlated with various mental illnesses, as identified by various studies. Genome-wide association studies (GWAS) indicate that the SNPs mapped to the SOX2-OT gene are associated with mental illnesses such as schizophrenia, general cognitive disorders, insomnia, eating disorders, night sleep phenotypes, and anorexia nervosa (Table4). More than 50% of SOX2-OT-associated diseases are mental illnesses (Table 4). Interestingly, almost all SOX2-OT SNPs are located in the intronic region of the SOX2-OT gene, possibly because the SOX2-OT gene encompasses a genomic region of more than 750 kb. However, one mutation (rs75380963) is located in the exonic region of the SOX2-OT gene (Table 4). Some of the mutations, for example, rs2567646 (general cognitive disorders), rs2216428 (general cognitive disorders), rs4854912 (eating disorders in patients with bipolar disorder), and rs13086738 (eating disorders in patients with bipolar disorder), are strongly correlated with mental illnesses, with odds ratios (ORs) of greater than 1.5 (Table 4, Figure 1).Table 4
The SNPs of SOX2-OT are associated with various diseases.
SNPMapped geneContextDisease/abnormalityPubMed IDrs13096176SOX2-OTintron_variantSchizophrenia31740837 [69]rs4855019SOX2-OTintron_variantSchizophrenia31740837 [69]rs9841616SOX2-OTintron_variantSchizophrenia31740837 [69]rs35788479SOX2-OTintron_variantGeneral risk tolerance30643258 [70]rs114600294SOX2-OTintron_variantGeneral risk tolerance30643258 [70]rs833268SOX2-OTintron_variantMale-pattern baldness30573740 [71]rs12632136SOX2-OTintron_variantReaction time29844566 [72]rs2216428SOX2-OTintron_variantGeneral cognitive disorder29844566 [72]rs1345417SOX2-OTintron_variantExcessive hairiness29895819 [73]rs60733335SOX2-OTintron_variantHair color30595370 [74]rs2216427SOX2-OTintron_variantInsomnia30804565 [75]rs12485391SOX2-OTintron_variantSmoking status30595370 [74]rs2567646SOX2-OTintron_variantGeneral cognitive disorder29844566 [72]rs9841616SOX2-OTintron_variantSchizophrenia25056061 [72]rs1345417SOX2-OTintron_variantEyebrow thickness30248107 [76]rs9841616SOX2-OTintron_variantSchizophrenia28991256 [77]rs9859557SOX2-OTintron_variantSchizophrenia28991256 [77]rs833270SOX2-OTintron_variantBalding type 130595370 [74]rs77025239SOX2-OTintron_variantEducational attainment30595370 [74]rs1805207SOX2-OTintron_variantBody mass index30595370 [74]rs9841616SOX2-OTintron_variantSchizophrenia26198764 [78]rs1805203SOX2-OTintron_variantSchizophrenia26198764 [78]rs1878874SOX2-OTintron_variantSchizophrenia26198764 [78]rs13086738SOX2-OTintron_variantEating disorder in individuals with bipolar disorder26433762 [79]rs4854912SOX2-OTintron_variantBipolar disorder and eating disorder26433762 [79]rs1345417SOX2-OTintron_variantMonobrow27182965 [80]rs2718791SOX2-OTintron_variantSmoking initiation30643251 [81]rs9859557SOX2-OTintron_variantSchizophrenia30285260 [82]rs9859557SOX2-OTintron_variantSchizophrenia30285260 [82]rs9841616SOX2-OTintron_variantSchizophrenia30285260 [82]rs9841616SOX2-OTintron_variantSchizophrenia30285260 [82]rs75380963SOX2-OTexon_variantCorneal astigmatism30306274 [83]rs77025239SOX2-OTintron_variantEducational attainment30038396 [84]rs2718791SOX2-OTintron_variantEducational attainment30038396 [84]rs77025239SOX2-OTintron_variantEducational attainment30038396 [84]rs9841382SOX2-OTintron_variantSelf-reported risk-taking behavior30271922 [85]rs9841382SOX2-OTintron_variantSelf-reported risk-taking behavior30181555 [86]rs9841382SOX2-OTintron_variantSelf-reported risk-taking behavior30181555 [86]rs4133078SOX2-OTintron_variantHeight30595370 [74]rs7631379SOX2-OTintron_variantSmoking initiation30643251 [81]rs34308817SOX2-OTintron_variantAnkle injury28957384 [87]rs6443750SOX2-OTintron_variantBody mass index30595370 [74]rs6443750SOX2-OTintron_variantBody mass index30239722 [88]rs186834402SOX2-OTintron_variantInterferon gamma levels27989323 [89]rs10937060SOX2-OTintron_variantNight sleep phenotypes27126917 [90]rs9839776SOX2-OTintron_variantAnorexia nervosa24514567 [8]rs4510419SOX2-OTintron_variantSmoking initiation30643251 [81]rs9839776SOX2-OTintron_variantBreast cancer28240100 [31]rs9839776SOX2-OTintron_variantRecurrent miscarriage31827385 [48]Note: SNPs: single-nucleotide polymorphisms; OR: odds ratio.In contrast to the evidence supporting the relationship between SOX2-OT and mental illnesses, evidence for the association between SOX2-OT SNPs and cancers is scarce. We found no data regarding the association between SOX2-OT SNPs and cancers in the Catalogue of Somatic Mutations in Cancer (COSMIC) or The Cancer Genome Atlas (TCGA) Program database. However, one study demonstrated that a SOX2-OT SNP (rs9839776) is strongly associated with increased expression of SOX2-OT in breast cancer tissues and that this SNP increases the risk of breast cancer in Chinese women (OR: 1.42; 95% CI: 1.06-1.90;p=0.018) [31]. In addition, another study revealed that copy number alteration (CNA) in the SOX2-OT locus is associated with esophageal squamous cell carcinoma [32].
## 7. SOX2-OT Is an Oncogene and a Biomarker for Cancers
lncRNAs have been demonstrated to be upregulated or downregulated during tumorigenesis and to function as oncogenes, suppressors, clinically useful diagnostic/prognostic biomarkers, or therapeutic targets in cancers because of their high sensitivity and specificity [33]. Accumulating evidence indicates that SOX2-OT is a key regulator of cancer stem cells and participates in cancer progression [10]. SOX2-OT is notably upregulated in numerous tumor tissues and cells (Table 5) and plays a vital role as an oncogene to promote the proliferation, invasion, migration, and growth of cancer cells and to suppress their apoptosis [10]. Depletion of SOX2-OT inhibits tumor cell proliferation, migration, invasion, and EMT [10]. However, a study showed that SOX2-OT is downregulated in gastric cancer, which contradicts the findings of the other four studies (Table 4). This contradictory result may have occurred because SOX2-OT has multiple splice variants. Indeed, Wang et al. thoroughly summarized recent studies regarding SOX2-OT expression, function, regulatory mechanisms, and clinical utility in human cancers [10].Table 5
Expression status of SOX2-OT in various cancers.
Expression statusCancerReferenceIncreasedLung cancerHou et al. [34], Zhang et al. [62], Jazi et al. [91]DecreasedGastric cancerFarhangian et al. [92]IncreasedGastric cancerZou et al. [37], Zhang et al. [36], Wei et al. [63], Qu et al. [64]IncreasedEsophageal cancerAliereza et al. [93], Tian et al. [23], Wu et al. [15]IncreasedBreast cancerIranpour et al. [94], Tang et al. [31]IncreasedHepatocellular carcinomaSun et al. [42], Shi et al. [35]IncreasedOvarian cancerHan et al. [95]IncreasedPancreatic ductal adenocarcinomaLi et al. [18], Zhang et al. [19]IncreasedCholangiocarcinomaLi et al. [40], Wei et al. [57]IncreasedOsteosarcomaWang et al. [38]IncreasedLaryngeal squamous cell carcinomaTai et al. [24], Feng et al. [96]IncreasedNasopharyngeal carcinomaZhang et al. [59]IncreasedGlioblastomaWang et al. [25]IncreasedBladder cancerZhan et al. [17]IncreasedProstate cancerWo et al. [60]IncreasedEwing’s sarcomaMa et al. [61]IncreasedColorectal cancerLiu et al. [97]SOX2-OT has been identified as a novel lncRNA that can serve as a prognostic biomarker for cancers. A high level of SOX2-OT correlates well with poor clinical outcomes in cancers [34–45]. Li et al. performed a meta-analysis of 13 selected studies by a comprehensive search of PubMed, EMBASE, Cochrane Library, and TCGA and found that the elevated SOX2-OT expression is significantly related to shorter overall and disease-free survival times in cancer patients [45]. Cancer patients with high SOX2-OT expression are more likely to have an advanced clinical stage, earlier lymphatic metastasis, earlier distant metastasis, a larger tumor size, and more extreme tumor invasion than those with low SOX2-OT expression [45]. In addition, two other meta-analyses consistently demonstrated that high SOX2-OT expression is significantly associated with worse overall survival, advanced clinical stage, worse tumor differentiation, earlier distant metastasis, and earlier lymph node metastasis in various cancers [39, 41, 46]. SOX2-OT expression could thus be a promising prognostic biomarker for poor survival in a variety of cancers.In addition to its prognostic value, circulating or exosome-derived SOX2-OT exhibits diagnostic value in non-small-cell lung cancer and lung squamous cell carcinoma [43, 44, 47]. Kamel et al. demonstrated that circulating SOX2-OT can distinguish non-small-cell lung cancer patients from control individuals, with an area under the curve of 0.73 (76.3% sensitivity and 78.6% specificity) [44]. Moreover, the combination of GAS5 expression and SOX2-OT expression can differentiate non-small-cell lung cancer patients from control individuals with increased sensitivity (83.8) and specificity (81.4) compared with those of SOX2-OT expression alone [44]. Teng et al. analyzed the level of exosomal SOX2-OT in plasma and concluded that the level of exosomal SOX2-OT is significantly increased in lung squamous cell carcinoma patients compared to normal control individuals, indicating the strong power of exosomal SOX2-OT for detecting lung squamous cell carcinoma. In that analysis, the area under the curve was 0.815, and the sensitivity and specificity were 76% and 73.17%, respectively [47]. Thus, SOX2-OT may serve as a promising noninvasive plasma-based diagnostic biomarker for cancers (Figure 1).
## 8. SOX2-OT Mediates Diabetic Complications
A few studies have investigated the possible association of SOX2-OT with diabetic complications, including diabetic nephropathy [12, 13] and diabetic retinopathy [11]. Microarray and bioinformatics analyses indicated that SOX2-OT is significantly downregulated in mice with diabetic nephropathy compared to control mice, and this result was confirmed in cultured human podocytes and mesangial cells [12]. SOX2-OT overexpression significantly alleviates high glucose-induced injury to human podocytes via autophagy induction through the miR-9/SIRT1 axis [13]. Conversely, although the SOX2-OT expression is significantly downregulated in the retinas of mice with streptozocin-induced diabetes, SOX2-OT knockdown protects retinal ganglion cells against high glucose-induced injury in vitro [11].
## 9. SOX2-OT and Other Diseases
In addition to the evidence supporting its involvement in cancers, mental illnesses, and diabetic complications, emerging evidence indicates the association of SOX2-OT with other diseases and events, such as miscarriage [48], septic cardiomyopathy [16], spinal cord injury [49], multiple sclerosis [50], and myopia [51]. An SNP (rs9839776 C>T) in the intronic region of the SOX2-OT gene is associated with increased risk for recurrent miscarriage (CT vs. CC: adjustedOR=1.357, 95%CI=1.065−1.728, p=0.0134) [48]. In addition, Chen et al. found that SOX2-OT was overexpressed and mitochondrial dysfunction occurred in a mouse model of lipopolysaccharide-induced septic cardiomyopathy; moreover, cardiac-specific knockdown of SOX2-OT via adeno-associated virus 9 (AAV9) harboring SOX2-OT siRNA ameliorated mitochondrial dysfunction in septic cardiomyopathy [16]. A lncRNA PCR array containing 90 common lncRNAs in peripheral blood mononuclear cells from patients with multiple sclerosis revealed a group of dysregulated lncRNAs in multiple sclerosis patients, and SOX2-OT was one of the most strongly downregulated lncRNAs with p<0.001 [50]. However, the SOX2-OT level is not associated with clinical variables such as the disease duration and expanded disability status scale score [50].
## 10. Conclusions and Future Directions
SOX2-OT is upregulated in many cancers and plays an oncogenic role in most tumors. In addition, SOX2-OT is upregulated during central nervous system development and is ultimately restricted to the brain in adult vertebrates. Emerging evidence indicates that multiple factors, including transcriptional activators (SOX2, IRF4, AR, and SOX3) and transcriptional inhibitors (NSPc1, MTA3, and YY1), as well as miRNAs (miR-211 and miR-375), can control the SOX2-OT expression transcriptionally or posttranscriptionally. However, rigorous investigations of the cause and effect mechanism underlying its upregulation in cancers and the central nervous system remain limited.The downstream targets of SOX2-OT have been elucidated. SOX2-OT performs various molecular and cellular functions via regulation of SOX2 (direct or indirect interactions), regulation of miRNAs (acting as a miRNA sponge), or regulation of transcriptional process (acting as a bridge between epigenetic factors and DNA). However, the precise role of the SOX2-OT gene in neurogenesis, cancers, mental illnesses, and diabetic complications must be systematically investigated and confirmed in a knockout animal model. Currently, no SOX2-OT knockout model is available to demonstrate the essential role of the SOX2-OT gene in neurogenesis and various diseases, because genetic depletion of a lncRNA—especially a lncRNA with multiple exons and transcription start sites, such as SOX2-OT—is difficult. Fortunately, strategies have been applied to generate lncRNA knockout mice, i.e., transcription start site disruption through the insertion of a transcription termination signal and deletion of important gene segments/exons via CRISPR/Cas9 genome editing [52, 53].Due to the complexity of transcriptional characteristics, including multiple transcription start sites and numerous transcripts in humans and other vertebrates, each transcript may play a unique role in different tissues, embryonic developmental stages, and disease conditions. There is an urgent demand to develop a method to systemically study each transcript under specific conditions. The most recently developed pooled CRISPR screening platform may constitute a good approach for studying the function of each SOX2-OT transcript [54, 55].SOX2-OT SNPs are associated with mental illnesses, but the precise functions of these SNPs are still obscure. We may need to investigate whether these SNPs alter SOX2-OT expression. In addition, the upregulation of SOX2-OT is correlated with poor outcomes in cancer patients, suggesting its potential function as a diagnostic and prognostic marker in tumors. However, the expression and chemical stability of SOX2-OT in body fluids remain unclear.The SOX2-OT gene has been widely studied in the past five years, and many important accomplishments have been achieved. However, studies on the SOX2-OT gene are still rare; less than one hundred papers on the SOX2-OT gene have been to date, despite an increasing trend. We still face many challenges, and many aspects of the SOX2-OT gene need to be investigated to provide a foundation for understanding its functions.
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*Source: 2901589-2020-11-27.xml* | 2901589-2020-11-27_2901589-2020-11-27.md | 34,705 | Long Noncoding RNA SOX2-OT: Regulations, Functions, and Roles on Mental Illnesses, Cancers, and Diabetic Complications | Pu-Yu Li; Ping Wang; She-Gan Gao; Dao-Yin Dong | BioMed Research International
(2020) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2020/2901589 | 2901589-2020-11-27.xml | ---
## Abstract
SRY-box transcription factor 2 (SOX2) overlapping transcript (SOX2-OT) is an evolutionarily conserved long noncoding RNA. Its intronic region contains the SOX2 gene, the major regulator of the pluripotency of embryonic stem cells. The human SOX2-OT gene comprises multiple exons and has multiple transcription start sites and generates hundreds of transcripts. Transcription factors (IRF4, AR, and SOX3), transcriptional inhibitors (NSPc1, MTA3, and YY1), and miRNAs (miR-211 and miR-375) have been demonstrated to control certain SOX2-OT transcript level at the transcriptional or posttranscriptional levels. Accumulated evidence indicates its crucial roles in the regulation of the SOX2 gene, miRNAs, and transcriptional process. Restricted expression of SOX2-OT transcripts in the brain results in the association between SOX2-OT single nucleotide polymorphisms and mental illnesses such as schizophrenia and anorexia nervosa. SOX2-OT is notably elevated in tumor tissues, and a high level of SOX2-OT is well correlated with poor clinical outcomes in cancer patients, leading to the establishment of its role as an oncogene and a prognostic or diagnostic biomarker for cancers. The emerging evidence supports that SOX2-OT mediates diabetic complications. In summary, SOX2-OT has diversified functions and could be a therapeutic target for various diseases.
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## Body
## 1. Introductions
SRY-box transcription factor 2 (SOX2) overlapping transcript (official symbol SOX2-OT according to the HUGO Gene Nomenclature Committee) is an evolutionarily conserved long noncoding RNA (lncRNA). The SOX2-OT gene is mapped to human chromosomal locus 3q26.33 and is located in a highly conserved region of more than 750 kb in humans and other vertebrates [1]. The SOX2-OT gene contains the key regulator of embryonic stem cell pluripotency, i.e., the SOX2 gene, within its intronic region, and both SOX2-OT and SOX2 are transcribed in the same orientation [2]. The human SOX2-OT gene comprises multiple exons and has multiple transcription start sites with complicated transcriptional features [1, 2]. Initially, Amaral et al. identified several variants of the SOX2-OT gene in mice and humans, including transcripts with multiple transcription start sites [2]. This group also identified SOX2-OT variants in chickens, frogs, and zebrafishes, and some transcripts appear to be species-specific [2]. As deep DNA sequencing technology has advanced, researchers have found that the SOX2-OT gene is expressed as 104 mRNA-like transcripts, the longest of which is approximately 4.3 kb in humans (according to the Ensembl genome database project) [3]. The comprehensive noncoding RNA sequence database RNA Central, which is maintained by the European Molecular Biology Laboratory-European Bioinformatics Institute (EMBL-EBI), includes information for 161 transcripts of the human SOX2-OT gene [4]. In mice, the SOX2 overlapping transcript (official symbol Sox2ot according to Mouse Genome Informatics) is mapped to chromosome 3qA3, and the transcript length is shorter than that of the human homolog. The Ensembl genome database includes 18 information for transcripts of the mouse Sox2ot gene [5].We searched studies regarding the SOX2-OT gene on PubMed and found that the SOX2-OT gene has received unprecedented attention within the last five years. The PubMed records indicated that only 17 articles exploring the functions of the SOX2-OT gene were published before 2015, whereas nearly 80 articles investigating the SOX2-OT gene were published from 2015 to date (May 2020). The earliest study regarding the SOX2-OT gene was published in 2003 [6]. In this study, the SOX2 gene was discovered by genomic analysis to be located in an intron of another gene, which they named SOX2-OT [6]. The researchers demonstrated that SOX2-OT contains at least five exons (current studies have shown that it contains dozens of exons) and produces a mRNA-like transcript from the same strand that SOX2 is located on [6]. This transcript is evolutionarily conserved; the human SOX2-OT transcript and available mouse expressed sequence tags share 80% nucleotide identity [6]. In addition, the genomic region (approximately 40 kb) encompassing the SOX2-OT transcription unit is highly conserved across vertebrates [6]. Subsequently, accumulating evidence has indicated that the SOX2-OT gene is associated with mental illnesses, cancers, and diabetic complications. SOX2-OT expression is upregulated during the central nervous system development and is restricted to the brain in adult humans and other vertebrates [2, 7]. Therefore, single-nucleotide polymorphisms (SNPs) in the SOX2-OT gene are associated with mental illnesses [8, 9]. Moreover, an increased expression of SOX2-OT is observed in tissues from various cancers; SOX2-OT typically functions as an oncogene to influence cancer progression and can serve as a prognostic or diagnostic biomarker for cancers [10]. In addition, studies have demonstrated that the SOX2-OT gene is involved in diabetic complications and other diseases [11–13]. In this review, we comprehensively summarize the most recent research progress in the regulation and function of SOX2-OT and the association of this lncRNA with various diseases. Moreover, we discuss the potential opportunities and challenges revealed by these findings.
## 2. SOX2-OT Regulates SOX2 Expression
The SOX2 gene is a key regulator of stem cell pluripotency and is embedded in an intron of SOX2-OT [1, 2]. lncRNAs can regulate the expression of adjacent overlapping genes via specific mechanisms [14]. Various studies have investigated the regulatory relationship between SOX2-OT and SOX2 (Table 1). Almost all cancer studies involving SOX2-OT and SOX2 have indicated that upregulation of SOX2-OT promotes SOX2 expression in cancer cells (Table 1); however, one study showed that SOX2-OT overexpression did not affect SOX2 expression [15]. Studies on septic cardiomyopathy demonstrated that the level of SOX2-OT is inversely correlated with that of SOX2 [16]. Furthermore, the levels of SOX2-OT and SOX2 are negatively correlated during neural differentiation of mouse embryonic stem cells [7] (Figure 1).Table 1
SOX2-OT regulates SOX2 expression.
RegulationIntermediatorCell modelCellular functionReferenceIncreasemiR-200cBladder cancerMetastasis and stemnessZhan et al. [17]IncreaseUnknownEsophageal squamous cell carcinomaMetastasis and stemnessDu et al. [56]DecreaseUnknownSeptic cardiomyopathyMitochondrial dysfunctionChen et al. [16]No effectUnknownEsophageal squamous cell carcinomaCell proliferationWu et al. [15]IncreaseUnknownCholangiocarcinomaProliferation and metastasisWei et al. [57]DecreasePromoter-enhancer loopEmbryonic developmentNeural differentiationMessemaker et al. [7]IncreasemiR-200 familyPancreatic ductal adenocarcinomaEMT, stemness, invasion, and metastasisLi et al. [18]DecreaseYY1Embryonic developmentRepresses neural progenitor proliferation and promotes neuronal differentiationKnauss et al. [20]IncreaseUnknownPancreatic ductal adenocarcinomaProliferation and tumor growthZhang et al. [19]IncreaseUnknownLung cancerProliferation, migration, invasion, and stemnessWang et al. [38]IncreaseUnknownBreast cancerProliferationAskarian-Amiri et al. [58]Note: EMT: epithelial-mesenchymal transition; YY1: Yin Yang-1.Figure 1
Long noncoding RNA SOX2-OT’s regulations, functions, and roles on mental illnesses, cancers, and diabetic complications. Transcription activators ((A) SOX2, IRF4, AR, and SOX3) can upregulate SOX2-OT expression, but transcription inhibitors ((B) NSPc1, MTA3, and YY1) and miRNAs ((C) miR-211 and miR-375) downregulate SOX2-OT expression. D. SOX2-OT upregulates SOX2 expression in cancer cells. (E) SOX2-OT downregulates SOX2 expression in neural stem cells. SOX2-OT can control miRNA levels via serving as a miRNA sponge (F) and affect transcription via serving as a bridge between epigenetic factors and DNA (G). (H) SOX2-OT SNPs are associated with mental illnesses. (I) SOX2-OT is a biomarker for cancers.Mechanistic investigations have revealed that SOX2-OT upregulates or downregulates the SOX2 expression through diverse pathways. Two studies demonstrated that SOX2-OT upregulates the SOX2 expression via the miR-200 family members in cancer cells [17, 18]. SOX2-OT acts as a miRNA sponge that competitively binds to miR-200 family members in order to upregulate the expression of SOX2 in cancer cells [17, 18]. One study revealed that the luciferase activity of the SOX2 promoter is significantly increased when SOX2-OT is overexpressed in pancreatic ductal adenocarcinoma cells, suggesting that SOX2-OT is a transcriptional activator of the SOX2 gene [19]. However, a study on central nervous system development showed that SOX2-OT physically interacts with the multifunctional transcriptional regulator YY1, which binds to several CpG islands in the SOX2 locus in a SOX2-OT-dependent manner and downregulates SOX2 expression in neural stem cells [20]. Another study showed that SOX2-OT impairs the formation of the chromatin promoter-enhancer loop upstream of the SOX2 gene and disrupts SOX2 transcription in neural stem cells [7]. Although few studies have investigated the mechanism by which SOX2-OT regulates the SOX2 expression in cancer cells or neural stem cells (Table 1), the regulation of the SOX2 expression by SOX2-OT in tumor cells follows a pattern opposite to that in neural stem cells (Table 1).
## 3. SOX2-OT Is a miRNA Sponge and a Regulator of Transcription
Research has suggested that some lncRNAs are involved in the competitive binding of miRNAs [21]. The members of this major subset of lncRNAs are called competing endogenous RNAs (ceRNAs), or miRNA sponges, and they form a regulatory network that controls the expression of protein-coding genes [22]. In this network, lncRNAs positively regulate the expression of protein-coding genes by competitively binding to their miRNAs [22]. SOX2-OT has been identified as an important ceRNA that affects cancer progression (Table 2, Figure 2(a)). An omics study revealed that SOX2-OT interacted with 6 differentially expressed miRNAs (hsa-mir-192-5p, hsa-mir-215-5p, hsa-mir-204-5p, hsa-mir-205-5p, hsa-mir-338-3p, hsa-mir-375) among 96 esophageal squamous cell carcinoma samples and 13 normal tissue samples [23]. In addition, numerous studies have demonstrated that SOX2-OT can bind to unique miRNAs in various cancers, and almost no overlapping miRNAs have been identified among those cancers (Table 2). miR-200c is the only exception, as SOX2-OT can target miR-200c in both bladder cancer and pancreatic ductal adenocarcinoma [17, 18]. Although SOX2-OT can target various miRNAs, it regulates similar cellular functions and behaviors, such as cancer cell proliferation, migration, invasion, metastasis, epithelial-mesenchymal transition (EMT), and stemness maintenance (Table 2).Table 2
SOX2-OT is a miRNA sponge.
miRNACancerTargetCellular functionReferencehsa-mir-192-5p, hsa-mir-215-5p, hsa-mir-204-5p, hsa-mir-205-5p, hsa-mir-338-3p, hsa-mir-375Esophageal squamous cell carcinomaUnknownUnknownTian et al. [23]miR-200cBladder cancerSOX2Increases bladder cancer cell stemness and metastasisZhan et al. [17]miR-146b-5pNasopharyngeal carcinomaHNRNPA2B1Increases proliferation and metastasis; decreases apoptosisZhang and Li [59]miR-369-3pProstate cancerCFL2Increases proliferation and migrationWo et al. [60]miR-363Ewing’s sarcomaFOXP4Increases proliferation and invasion; decreases apoptosisMa et al. [61]miR-132Non-small-cell lung cancerZEB2Increases proliferation, migration, invasion, and EMTZhang et al. [62]miR-211PheochromocytomaMCL-1 isoform 2Increases cell viability, migration, and invasion; decreases apoptosis and autophagyYin et al. [49]miR-194-5pGastric cancerAKT2Promotes proliferation, metastasis, invasion, migration, and EMTWei et al. [63], Qu et al. [64]miR-200 familyPancreatic ductal adenocarcinomaSOX2Promotes EMT and stem cell-like propertiesLi et al. [18]miR-194-5p, miR-122GliomaSOX3Increases proliferation, migration, and invasion; decreases apoptosisSu et al. [65]Note: EMT: epithelial-mesenchymal transition; Sox2: SRY-box transcription factor 2; HNRNPA2B1: heterogeneous nuclear ribonucleoprotein A2/B1; CFL2: cofilin 2; FOXP4: forkhead box P4; ZEB2: zinc finger E-box binding homeobox 2; MCL1 Isoform 2: myeloid cell leukemia sequence 1 isoform 2; AKT2: AKT serine/threonine kinase 2; SOX3: SRY-box transcription factor 3.Figure 2
SOX2-OT is a miRNA sponge and a regulator of transcription. (a) SOX2-OT is a miRNA sponge. (b) SOX2-OT acts as a bridge between epigenetic factors and DNA to affect gene expression. (c) SOX2-OT acts as a destabilizer of transcription factors to control gene expression. PRC: polycomb repressive complex; EZH2: enhancer of zeste 2; FUS: FUS RNA binding protein.
(a)(b)(c)In addition to acting as a miRNA sponge, SOX2-OT acts as a regulator of transcription by serving as a bridge between epigenetic factors and DNA to affect gene expression (Figure2(b)). A recent study revealed that SOX2-OT interacts with EZH2, recruits EZH2 to DNA to form the polycomb repressive complex 2 (PRC2), induces H3K27me3, and epigenetically inhibits PTEN expression in laryngeal squamous cell carcinoma cells [24]. Studies have demonstrated that SOX2-OT binds to nervous system polycomb 1 (NSPc1), a key component of polycomb repressive complex 1 (PRC1), in H4 glioma cells [25] and U87 glioma cells [26], and regulates cancer cell proliferation and apoptosis. SOX2-OT can also act as a destabilizer of transcription factors to control gene expression (Figure 2(c)). A study suggested that SOX2-OT directly binds to the transcription factor FUS and that FUS protein stability is altered by this binding [27]. Thus, SOX2-OT acts as a tumor promoter in pancreatic ductal adenocarcinoma by physically binding to FUS to regulate its downstream cell cycle-associated factors CCND1 and p27 [27] (Figure 1).
## 4. SOX2-OT Is Regulated at the Transcriptional and Posttranscriptional Levels
Most relevant studies have shown that SOX2-OT levels are increased in various cancers and have described the SOX2-OT gene as an oncogene [10]. An increasing number of studies have investigated the mechanism underlying SOX2-OT upregulation in cancer cells (Table 3). These studies have focused on transcriptional and posttranscriptional regulation. Four transcription factors (SOX2, IRF4, AR, and SOX3) were identified to be able to bind directly to the SOX2-OT promoter and promote its transcription (Table 3). Other studies identified three transcriptional inhibitors (NSPc1, MTA3, and YY1) that recruit the repressive complex to the SOX2-OT promoter to repress its expression (Table 3). Interestingly, Shafiee et al. revealed that two miRNAs (miR-211 and miR-375) are responsible for SOX2-OT downregulation in a model of Helicobacter pylori-induced carcinogenesis (Table 3, Figure 1).Table 3
SOX2-OT is regulated at the transcriptional and posttranscriptional levels.
FactorRegulatory effectCell modelReferenceNSPc1Represses transcriptionGlioma cellsLiang et al. [26]MTA3Represses transcriptionEsophageal squamous cell carcinoma cellsDu et al. [56]SOX2Promotes transcriptionEsophageal squamous cell carcinoma cellsWu et al. [15]IRF4Promotes transcriptionCholangiocarcinoma cellsWei et al. [57]YY1Represses transcriptionPancreatic ductal adenocarcinoma cellsZhang et al. [19]ARPromotes transcriptionEmbryonic neural stem cellsTosetti et al. [66]SOX3Promotes transcriptionGlioblastoma stem cellsSu et al. [65]miR-211Downregulates expression by directly binding to SOX2-OTEmbryonal carcinoma stem cells (NT-2)Shafiee et al. [67]miR-375Downregulates expression by directly binding to SOX2-OTEmbryonal carcinoma stem cells (NT-2)Shafiee et al. [68]Note: NSPc1: nervous system polycomb 1; MTA3: metastasis-associated protein 3; IRF4: interferon regulatory factor 4; YY1L Yin Yang-1; ARL androgen receptor; Sox3: SRY-box transcription factor 3.
## 5. SOX2-OT Is Upregulated during Central Nervous System Development, and Its Expression Is Restricted to the Brain
Studies have reported that a striking 40% of lncRNAs are expressed specifically in the brain, indicating the importance of lncRNAs in central nervous system development [28]. Numerous lncRNAs have been identified as regulators of the central nervous system development. Early studies showed that SOX2-OT is highly expressed in mouse embryonic stem cells and is downregulated during the differentiation of embryoid bodies into mesoderm [2]. However, Messemaker et al. demonstrated strong upregulation of SOX2-OT upon the differentiation of embryoid bodies into neuroectoderm, and upregulation of SOX2-OT was found to coincide with neural progenitor/stem cell formation as assessed via the induction of the SOX1 expression, which is a very early and specific marker of the neuroectodermal lineage [7]. Furthermore, SOX2-OT expressed sequence tags have been found in differentiated mouse neural stem cells, and its expression is confirmed in mouse primary neuronal cells [2]. RNA whole-mount in situ hybridization showed that in mice, SOX2-OT expression is limited to the developing brain, the ventral part of the neural tube, and the optic vesicle in mice [7]. Another study indicated that SOX2-OT is expressed in the developing cerebral cortex of mice, where it represses neural progenitor cell proliferation and promotes neuronal differentiation [20].To investigate the possible involvement of SOX2-OT in neural differentiation processes, Amaral et al. examined the dynamic change in the SOX2-OT expression via a neurosphere assay, an in vitro model of neurogenesis with cultures of neurospheres originating from neural stem cells and undifferentiated precursors in the subventricular zone of adult mice [2]. The differentiated population of neurons and glial cells from neurospheres cultured for 7 days in differentiation medium exhibited increased expression of SOX2-OT [2].Similar results have also been found in developing zebrafish embryos [7]. Studies have revealed that SOX2-OT is expressed in neuroectodermal tissue in zebrafish embryos at the tailbud stage [2]. Subsequently, SOX2-OT is highly expressed throughout the developing brain and eyes and is expressed at lower levels in the posterior neural tube at 28 hours postfertilization (hpf). In situ hybridization indicated specific expression of SOX2-OT in the retina and central nervous system in 48 hpf embryos, and this expression was maintained in the brain throughout the embryonic development until at least 6 days postfertilization (dpf) [2].Importantly, data from the Genotype-Tissue Expression (GTEx) project show that in adult humans, the SOX2-OT expression is almost completely restricted to the brain, including regions such as the cortex, hippocampus, hypothalamus, cerebellum, and spinal cord [29]. Single-cell RNA-seq data in the Human Cell Landscape (HCL) project indicate that SOX2-OT expression is concentrated in oligodendrocytes and FGF13+ or CXCL14+ neurons in adult humans [30].In summary, SOX2-OT is upregulated during central nervous system development (neurogenesis), and its expression is ultimately restricted to the brain in adult vertebrates.
## 6. SOX2-OT SNPs Are Associated with Mental Illnesses
Because SOX2-OT expression is restricted to the brain in adult humans, SOX2-OT SNPs are correlated with various mental illnesses, as identified by various studies. Genome-wide association studies (GWAS) indicate that the SNPs mapped to the SOX2-OT gene are associated with mental illnesses such as schizophrenia, general cognitive disorders, insomnia, eating disorders, night sleep phenotypes, and anorexia nervosa (Table4). More than 50% of SOX2-OT-associated diseases are mental illnesses (Table 4). Interestingly, almost all SOX2-OT SNPs are located in the intronic region of the SOX2-OT gene, possibly because the SOX2-OT gene encompasses a genomic region of more than 750 kb. However, one mutation (rs75380963) is located in the exonic region of the SOX2-OT gene (Table 4). Some of the mutations, for example, rs2567646 (general cognitive disorders), rs2216428 (general cognitive disorders), rs4854912 (eating disorders in patients with bipolar disorder), and rs13086738 (eating disorders in patients with bipolar disorder), are strongly correlated with mental illnesses, with odds ratios (ORs) of greater than 1.5 (Table 4, Figure 1).Table 4
The SNPs of SOX2-OT are associated with various diseases.
SNPMapped geneContextDisease/abnormalityPubMed IDrs13096176SOX2-OTintron_variantSchizophrenia31740837 [69]rs4855019SOX2-OTintron_variantSchizophrenia31740837 [69]rs9841616SOX2-OTintron_variantSchizophrenia31740837 [69]rs35788479SOX2-OTintron_variantGeneral risk tolerance30643258 [70]rs114600294SOX2-OTintron_variantGeneral risk tolerance30643258 [70]rs833268SOX2-OTintron_variantMale-pattern baldness30573740 [71]rs12632136SOX2-OTintron_variantReaction time29844566 [72]rs2216428SOX2-OTintron_variantGeneral cognitive disorder29844566 [72]rs1345417SOX2-OTintron_variantExcessive hairiness29895819 [73]rs60733335SOX2-OTintron_variantHair color30595370 [74]rs2216427SOX2-OTintron_variantInsomnia30804565 [75]rs12485391SOX2-OTintron_variantSmoking status30595370 [74]rs2567646SOX2-OTintron_variantGeneral cognitive disorder29844566 [72]rs9841616SOX2-OTintron_variantSchizophrenia25056061 [72]rs1345417SOX2-OTintron_variantEyebrow thickness30248107 [76]rs9841616SOX2-OTintron_variantSchizophrenia28991256 [77]rs9859557SOX2-OTintron_variantSchizophrenia28991256 [77]rs833270SOX2-OTintron_variantBalding type 130595370 [74]rs77025239SOX2-OTintron_variantEducational attainment30595370 [74]rs1805207SOX2-OTintron_variantBody mass index30595370 [74]rs9841616SOX2-OTintron_variantSchizophrenia26198764 [78]rs1805203SOX2-OTintron_variantSchizophrenia26198764 [78]rs1878874SOX2-OTintron_variantSchizophrenia26198764 [78]rs13086738SOX2-OTintron_variantEating disorder in individuals with bipolar disorder26433762 [79]rs4854912SOX2-OTintron_variantBipolar disorder and eating disorder26433762 [79]rs1345417SOX2-OTintron_variantMonobrow27182965 [80]rs2718791SOX2-OTintron_variantSmoking initiation30643251 [81]rs9859557SOX2-OTintron_variantSchizophrenia30285260 [82]rs9859557SOX2-OTintron_variantSchizophrenia30285260 [82]rs9841616SOX2-OTintron_variantSchizophrenia30285260 [82]rs9841616SOX2-OTintron_variantSchizophrenia30285260 [82]rs75380963SOX2-OTexon_variantCorneal astigmatism30306274 [83]rs77025239SOX2-OTintron_variantEducational attainment30038396 [84]rs2718791SOX2-OTintron_variantEducational attainment30038396 [84]rs77025239SOX2-OTintron_variantEducational attainment30038396 [84]rs9841382SOX2-OTintron_variantSelf-reported risk-taking behavior30271922 [85]rs9841382SOX2-OTintron_variantSelf-reported risk-taking behavior30181555 [86]rs9841382SOX2-OTintron_variantSelf-reported risk-taking behavior30181555 [86]rs4133078SOX2-OTintron_variantHeight30595370 [74]rs7631379SOX2-OTintron_variantSmoking initiation30643251 [81]rs34308817SOX2-OTintron_variantAnkle injury28957384 [87]rs6443750SOX2-OTintron_variantBody mass index30595370 [74]rs6443750SOX2-OTintron_variantBody mass index30239722 [88]rs186834402SOX2-OTintron_variantInterferon gamma levels27989323 [89]rs10937060SOX2-OTintron_variantNight sleep phenotypes27126917 [90]rs9839776SOX2-OTintron_variantAnorexia nervosa24514567 [8]rs4510419SOX2-OTintron_variantSmoking initiation30643251 [81]rs9839776SOX2-OTintron_variantBreast cancer28240100 [31]rs9839776SOX2-OTintron_variantRecurrent miscarriage31827385 [48]Note: SNPs: single-nucleotide polymorphisms; OR: odds ratio.In contrast to the evidence supporting the relationship between SOX2-OT and mental illnesses, evidence for the association between SOX2-OT SNPs and cancers is scarce. We found no data regarding the association between SOX2-OT SNPs and cancers in the Catalogue of Somatic Mutations in Cancer (COSMIC) or The Cancer Genome Atlas (TCGA) Program database. However, one study demonstrated that a SOX2-OT SNP (rs9839776) is strongly associated with increased expression of SOX2-OT in breast cancer tissues and that this SNP increases the risk of breast cancer in Chinese women (OR: 1.42; 95% CI: 1.06-1.90;p=0.018) [31]. In addition, another study revealed that copy number alteration (CNA) in the SOX2-OT locus is associated with esophageal squamous cell carcinoma [32].
## 7. SOX2-OT Is an Oncogene and a Biomarker for Cancers
lncRNAs have been demonstrated to be upregulated or downregulated during tumorigenesis and to function as oncogenes, suppressors, clinically useful diagnostic/prognostic biomarkers, or therapeutic targets in cancers because of their high sensitivity and specificity [33]. Accumulating evidence indicates that SOX2-OT is a key regulator of cancer stem cells and participates in cancer progression [10]. SOX2-OT is notably upregulated in numerous tumor tissues and cells (Table 5) and plays a vital role as an oncogene to promote the proliferation, invasion, migration, and growth of cancer cells and to suppress their apoptosis [10]. Depletion of SOX2-OT inhibits tumor cell proliferation, migration, invasion, and EMT [10]. However, a study showed that SOX2-OT is downregulated in gastric cancer, which contradicts the findings of the other four studies (Table 4). This contradictory result may have occurred because SOX2-OT has multiple splice variants. Indeed, Wang et al. thoroughly summarized recent studies regarding SOX2-OT expression, function, regulatory mechanisms, and clinical utility in human cancers [10].Table 5
Expression status of SOX2-OT in various cancers.
Expression statusCancerReferenceIncreasedLung cancerHou et al. [34], Zhang et al. [62], Jazi et al. [91]DecreasedGastric cancerFarhangian et al. [92]IncreasedGastric cancerZou et al. [37], Zhang et al. [36], Wei et al. [63], Qu et al. [64]IncreasedEsophageal cancerAliereza et al. [93], Tian et al. [23], Wu et al. [15]IncreasedBreast cancerIranpour et al. [94], Tang et al. [31]IncreasedHepatocellular carcinomaSun et al. [42], Shi et al. [35]IncreasedOvarian cancerHan et al. [95]IncreasedPancreatic ductal adenocarcinomaLi et al. [18], Zhang et al. [19]IncreasedCholangiocarcinomaLi et al. [40], Wei et al. [57]IncreasedOsteosarcomaWang et al. [38]IncreasedLaryngeal squamous cell carcinomaTai et al. [24], Feng et al. [96]IncreasedNasopharyngeal carcinomaZhang et al. [59]IncreasedGlioblastomaWang et al. [25]IncreasedBladder cancerZhan et al. [17]IncreasedProstate cancerWo et al. [60]IncreasedEwing’s sarcomaMa et al. [61]IncreasedColorectal cancerLiu et al. [97]SOX2-OT has been identified as a novel lncRNA that can serve as a prognostic biomarker for cancers. A high level of SOX2-OT correlates well with poor clinical outcomes in cancers [34–45]. Li et al. performed a meta-analysis of 13 selected studies by a comprehensive search of PubMed, EMBASE, Cochrane Library, and TCGA and found that the elevated SOX2-OT expression is significantly related to shorter overall and disease-free survival times in cancer patients [45]. Cancer patients with high SOX2-OT expression are more likely to have an advanced clinical stage, earlier lymphatic metastasis, earlier distant metastasis, a larger tumor size, and more extreme tumor invasion than those with low SOX2-OT expression [45]. In addition, two other meta-analyses consistently demonstrated that high SOX2-OT expression is significantly associated with worse overall survival, advanced clinical stage, worse tumor differentiation, earlier distant metastasis, and earlier lymph node metastasis in various cancers [39, 41, 46]. SOX2-OT expression could thus be a promising prognostic biomarker for poor survival in a variety of cancers.In addition to its prognostic value, circulating or exosome-derived SOX2-OT exhibits diagnostic value in non-small-cell lung cancer and lung squamous cell carcinoma [43, 44, 47]. Kamel et al. demonstrated that circulating SOX2-OT can distinguish non-small-cell lung cancer patients from control individuals, with an area under the curve of 0.73 (76.3% sensitivity and 78.6% specificity) [44]. Moreover, the combination of GAS5 expression and SOX2-OT expression can differentiate non-small-cell lung cancer patients from control individuals with increased sensitivity (83.8) and specificity (81.4) compared with those of SOX2-OT expression alone [44]. Teng et al. analyzed the level of exosomal SOX2-OT in plasma and concluded that the level of exosomal SOX2-OT is significantly increased in lung squamous cell carcinoma patients compared to normal control individuals, indicating the strong power of exosomal SOX2-OT for detecting lung squamous cell carcinoma. In that analysis, the area under the curve was 0.815, and the sensitivity and specificity were 76% and 73.17%, respectively [47]. Thus, SOX2-OT may serve as a promising noninvasive plasma-based diagnostic biomarker for cancers (Figure 1).
## 8. SOX2-OT Mediates Diabetic Complications
A few studies have investigated the possible association of SOX2-OT with diabetic complications, including diabetic nephropathy [12, 13] and diabetic retinopathy [11]. Microarray and bioinformatics analyses indicated that SOX2-OT is significantly downregulated in mice with diabetic nephropathy compared to control mice, and this result was confirmed in cultured human podocytes and mesangial cells [12]. SOX2-OT overexpression significantly alleviates high glucose-induced injury to human podocytes via autophagy induction through the miR-9/SIRT1 axis [13]. Conversely, although the SOX2-OT expression is significantly downregulated in the retinas of mice with streptozocin-induced diabetes, SOX2-OT knockdown protects retinal ganglion cells against high glucose-induced injury in vitro [11].
## 9. SOX2-OT and Other Diseases
In addition to the evidence supporting its involvement in cancers, mental illnesses, and diabetic complications, emerging evidence indicates the association of SOX2-OT with other diseases and events, such as miscarriage [48], septic cardiomyopathy [16], spinal cord injury [49], multiple sclerosis [50], and myopia [51]. An SNP (rs9839776 C>T) in the intronic region of the SOX2-OT gene is associated with increased risk for recurrent miscarriage (CT vs. CC: adjustedOR=1.357, 95%CI=1.065−1.728, p=0.0134) [48]. In addition, Chen et al. found that SOX2-OT was overexpressed and mitochondrial dysfunction occurred in a mouse model of lipopolysaccharide-induced septic cardiomyopathy; moreover, cardiac-specific knockdown of SOX2-OT via adeno-associated virus 9 (AAV9) harboring SOX2-OT siRNA ameliorated mitochondrial dysfunction in septic cardiomyopathy [16]. A lncRNA PCR array containing 90 common lncRNAs in peripheral blood mononuclear cells from patients with multiple sclerosis revealed a group of dysregulated lncRNAs in multiple sclerosis patients, and SOX2-OT was one of the most strongly downregulated lncRNAs with p<0.001 [50]. However, the SOX2-OT level is not associated with clinical variables such as the disease duration and expanded disability status scale score [50].
## 10. Conclusions and Future Directions
SOX2-OT is upregulated in many cancers and plays an oncogenic role in most tumors. In addition, SOX2-OT is upregulated during central nervous system development and is ultimately restricted to the brain in adult vertebrates. Emerging evidence indicates that multiple factors, including transcriptional activators (SOX2, IRF4, AR, and SOX3) and transcriptional inhibitors (NSPc1, MTA3, and YY1), as well as miRNAs (miR-211 and miR-375), can control the SOX2-OT expression transcriptionally or posttranscriptionally. However, rigorous investigations of the cause and effect mechanism underlying its upregulation in cancers and the central nervous system remain limited.The downstream targets of SOX2-OT have been elucidated. SOX2-OT performs various molecular and cellular functions via regulation of SOX2 (direct or indirect interactions), regulation of miRNAs (acting as a miRNA sponge), or regulation of transcriptional process (acting as a bridge between epigenetic factors and DNA). However, the precise role of the SOX2-OT gene in neurogenesis, cancers, mental illnesses, and diabetic complications must be systematically investigated and confirmed in a knockout animal model. Currently, no SOX2-OT knockout model is available to demonstrate the essential role of the SOX2-OT gene in neurogenesis and various diseases, because genetic depletion of a lncRNA—especially a lncRNA with multiple exons and transcription start sites, such as SOX2-OT—is difficult. Fortunately, strategies have been applied to generate lncRNA knockout mice, i.e., transcription start site disruption through the insertion of a transcription termination signal and deletion of important gene segments/exons via CRISPR/Cas9 genome editing [52, 53].Due to the complexity of transcriptional characteristics, including multiple transcription start sites and numerous transcripts in humans and other vertebrates, each transcript may play a unique role in different tissues, embryonic developmental stages, and disease conditions. There is an urgent demand to develop a method to systemically study each transcript under specific conditions. The most recently developed pooled CRISPR screening platform may constitute a good approach for studying the function of each SOX2-OT transcript [54, 55].SOX2-OT SNPs are associated with mental illnesses, but the precise functions of these SNPs are still obscure. We may need to investigate whether these SNPs alter SOX2-OT expression. In addition, the upregulation of SOX2-OT is correlated with poor outcomes in cancer patients, suggesting its potential function as a diagnostic and prognostic marker in tumors. However, the expression and chemical stability of SOX2-OT in body fluids remain unclear.The SOX2-OT gene has been widely studied in the past five years, and many important accomplishments have been achieved. However, studies on the SOX2-OT gene are still rare; less than one hundred papers on the SOX2-OT gene have been to date, despite an increasing trend. We still face many challenges, and many aspects of the SOX2-OT gene need to be investigated to provide a foundation for understanding its functions.
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*Source: 2901589-2020-11-27.xml* | 2020 |
# Using Molecular Markers to Help Predict Who Will Fail after Radical Prostatectomy
**Authors:** Gregory P. Swanson; David Quinn
**Journal:** Prostate Cancer
(2011)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2011/290160
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## Abstract
Recent phase III trial data clearly demonstrate that adjuvant therapy can reduce recurrence and increase survival after prostatectomy for prostate cancer. There is great interest in being able to accurately predict who is at risk of failure to avoid treating those who may not benefit. The standard markers consisting of prostate specific antigen (PSA), Gleason score, and pathological stage are not very specific, so there is an unmet need for other markers to aid in prognostic stratification. Numerous studies have been conducted with various markers and more recently gene signatures, but it is unclear whether any of them are really useful. We conducted a comprehensive review of the literature to determine the current status of molecular markers in predicting outcome after radical prostatectomy.
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## Body
## 1. Introduction
Prostate specific antigen (PSA), stage (either clinical or pathological), and Gleason score are firmly established as prognostic indicators in prostate cancer. Individually and collectively, they predict for failure after radiation and surgery. The predictive value has been increased with more detailed information such as the addition of the detailed pathological findings of extraprostatic extension (EPE), positive margins, seminal vesicle involvement, and lymph node involvement. Various combinations of factors have been combined into tables, formulas, neural networks, and nomograms. While they are important tools in trying to predict failure, they are limited by the predictive ability of the factors themselves. For example, from a nomogram, a patient with a Gleason 7 (3 + 4) cancer with extraprostatic extension and positive margins, negative lymph nodes, negative seminal vesicles, and preoperative PSA of 8.2 ng/mL is predicted to have a 10-year recurrence rate of 20% [1]. Telling a patient that he has a 1 out of 5 chance of failing may or may not be reassuring. The absolute precision would be able to tell a patient whether he will fail (100%) or not (0%). The ultimate goal is to try to determine who will fail, not who may fail. The only way to try to approach that goal is with more precise markers than we currently have. One area of major promise in this regard is the greater individual cancer data that can be obtained from molecular markers.We already have seen an example of the benefit of a marker in prostate cancer. The addition of the biological marker PSA offers more precise information over stage and Gleason score alone. In breast cancer, the marker Her 2-neu has been shown to be not only an important prognostic marker, but also a target of therapy [2]. The identification of the protein associated with bcr-abl (break point cluster region-Abelson proto-oncogene fusion) led to a major treatment breakthrough in chronic myelogenous leukemia (CML) [3]. Given these successes, interest has been generated in discovering molecular markers that would help with prostate cancer. Numerous markers have been evaluated, but usually in small numbers and in diverse patient populations. Also, they rarely are evaluated as to whether they enhance the predictive ability of the standard markers. The real test of a new maker (and the key to its success) will be whether it enhances the predictive ability of the prognostic triad of PSA, Gleason score, and stage (with all of its various subclassifications). The purpose of this evaluation is to determine whether any of these are truly helpful in determining who will fail after radical prostatectomy and whether we should consider adding them to our standard armatorium for evaluation.
## 2. Materials and Methods
A comprehensive Medline search was undertaken to identify studies of molecular markers in prostate cancer. In each of those studies, references were evaluated to try to capture all the studies that evaluated markers in patients undergoing radical prostatectomy.Most studies had too few patients to have enough statistical power to make meaningful prognostic statements. Also, most studies were not specific for patients that underwent surgery for their prostate cancer, but rather a mixture of different treatment modalities. While we reviewed all the studies, we focused on those with radical prostatectomy patients that were treated with curative intent. We also focused on studies with more than 50 patients, with the premise that lesser numbers were unlikely to have statistical relevance. In addition, we hoped to focus on studies that evaluated the investigated markers in conjunction with at least one of the accepted predictive factors (PSA, Gleason score, and stage). As it turned out, direct correlation with the known predictive factors was not very commonly performed.We searched for studies that show the possibility of increasing the predictive ability and discuss whether any appear to be able to help us better predict failure. We were not so much interested in determining the mechanistic underpinnings of cancer development and the effect on stage, rather whether markers could help predict the clinical behavior of prostate cancer and help determine appropriate intervention to try to cure more patients.
## 3. Results and Discussion
The literature was quite diverse, which makes interpretation of results difficult and direct comparisons impossible. As per all retrospective studies, there is inherent variation in the selection of patients. In addition, even for the same markers, the determination of positive and negative often varied greatly. Many of them were determined by semiquantitative immunohistochemical (IHC) staining with large methodological and intraobserver variability. Some investigators acknowledged that the staining level to determine what was “positive” had to be manipulated to have significant results [4]. Many studies included patients that received neoadjuvant androgen ablation or adjuvant androgen ablation and/or radiation therapy. While excluding those patients eliminates some of the perceived higher-risk patients, including patients that have additional treatments known to alter failure is also problematic. Also, most of the studies have very short followup, which makes any conclusions about failure tenuous at best. Many expressed markers show a close association with known prognostic factors and while they may be positive on univariate analysis, they fall out on multivariate analysis. These issues are inherent to retrospective studies, but they should be kept in mind.
### 3.1. Ki-67
Ki-67 is one of the earliest markers and is named for the original mouse antibody researched in Kiel Germany, reacting in well number 67 [5]. It serves as a proliferation marker that occurs only in dividing cells (not G0). The original antibody required fresh tissue, but the MIB-1 antibody can be used in formalin fixed tissue. The assessment of Ki-67 gives an estimate (index) of the portion of cells actively proliferating.Some studies report that Ki-67 is prognostic for failure (Table1). In a study of 70 radical prostatectomy patients, 50 were selected for further analysis [6]. With a median followup of 63 months, 18% failed (PSA > 0.2 ng/mL). The specimens were evaluated for Ki-67 via IHC staining. On univariate analysis of PSA, PSA doubling time, Ki-67%, tumor volume, and Gleason score, only Ki-67% and PSA were significant prognostic factors. In another study [7], 137 patients underwent radical prostatectomy with a mean followup of 5.4 years. The cohort included 25% lymph node positive and 36% received adjuvant therapy with radiation and/or androgen ablation. Ki-67 was scored as the per cent of staining >5% (78 or 57% if the patients) or <5% (59 or 43% of the patients); the mean was 7.5%. From the graph, for patients below the mean staining, 5-year recurrence free survival was approximately 78% compared to 65% if above the mean. Ki-67 was a significant factor on multiparameter analysis. The largest study evaluating Ki-67 was of 528 prostatectomy patients after exclusion of those that received neoadjuvant and adjuvant androgen ablation and radiation therapy [8]. With a median followup of 46 months, 101 (19%) failed for a 5-year disease-free (PSA < 0.2 ng/mL) rate of 78%. The tissue was evaluated using IHC staining for Ki-67 and chromogranin A (CGA). On multivariate analysis, Gleason score > 4 + 3, CGA positive, lymph node positive, PSA > 20 ng/mL, and Ki-67 were prognostic, while pathologic stage T3 and margin positivity were not. For the 300 Ki-67 ≥ 5% patients, 5-year biochemical recurrence-free survival (from graph) was 70%, while for the 228 with <5% staining, it was 88%. In another large study, Miyake et al. [9] studied 193 prostatectomy patients that did not receive adjuvant treatment. With a median followup of 63 months, 21% failed for a 5-year disease-free survival rate of 79%. They evaluated twelve markers with IHC. On univariate analysis, they found the following factors to be prognostic: PSA, Gleason score, lymph node positivity, tumor volume, seminal vesicle involvement, margin positive, and on immunohistochemical staining: Ki-67, p53, AR, MMP-2, MMP-9, and HSP27. On multivariate analysis, only Ki-67, seminal vesicle involvement, and margin positivity remained significant. In consideration of those three positive factors, if the patient was positive for 2 or 3 of them, the recurrence rate was 79%, if positive for one, 20%, and if negative for all 3, 4%. Ki-67 was also prognostic in a smaller study of 91 prostatectomy only patients [10]. With a median followup of 46.5 months, 29 (32%) progressed (PSA ≥ 0.2 ng/mL). For the 60% of patients with <5% PSA staining, 5-year disease-free survival was 84%, compared to 42% for those with ≥5% staining (from graph). On multivariate analysis, Ki-67 and Gleason score were prognostic. The final positive study was a multifactorial study [11] of 336 RRP patients, of which 249 had tissue. Lymph node positive patients were included. Failure was defined as PSA > 0.5 ng/mL. Five-year DFS was 63%, and 10-year was 41% with a median followup of 66 months. They utilized immunohistochemical staining for Ki-67, enhancer of zeste homolog 2 (EZH2), (discussed below) and minichromosome maintenance protein 7 (MMC7) (discussed below). They also used fluorescence in situ hybridization (FISH) for EIF3S3, a chromosome abnormality they had explored previously. On multivariate analysis considering EZH2, Ki-67, MCM7, Gleason score, pathologic stage, and PSA, the factors of pathologic stage, Ki-67 and MCM7 were significant predictive factors. From the graphs, for staining 0-1%, 10-year disease-free survival was 65%, for 2–15% was 38%, and for >15% was 27%. Demonstrative as to how other factors can have an effect of prognostic ability, in patients that were lymph node negative with an undetectable postsurgery PSA, Ki-67 dropped out and EZH2, MCM7, and PSA were prognostic. In Gleason, less than 7 patients, Ki-67 was the only significant factor; the 15 patients with Ki-67 staining of >1% had a 5- and 10-year disease-free survival of 70% and 45%, respectively (from the graph), compared to 100% for Ki-67 of 0-1%. No details of interaction with pathologic variables were given.Table 1
Ki-67 and outcomes after radical prostatectomy. The table indicates whether Ki-67 was positive on univariate or multivariate analysis for predicting failure. The failure of the entire cohort is given and then the outcomes for patients where Ki-67 was elevated versus not elevated.
Study#ptsMed (mean) months f/uInclude LN+ (#)Include Adj RX (#)Definition of failure@Univariate positiveMultivariate positiveGroup overall failureMarker elevated outcomeMarker not elevated outcomeKhatami et al. [6]50(63)NoNRPSA > 0.2 × 2YesNR18%NRNRBubendorf et al. [7]137(64)Yes (34)Yes (60)PSA, PAP, or ALP elevated*YesYes29%65% 5-yr dfs78% 5-yr dfsMay et al. [8]52846 (49)Yes (38)NoPSA > 0.2YesYes19% 5-yr dfs 78%70% 5-yr dfs88% 5-yr dfsMiyake et al. [9]19363Yes (13)NoPSA > 0.2YesYes21% 5-yr dfs 79%A: 79% recurB: 20% recurC: 4% recurRubio et al. [10]9146.5NRNoPSA ≥0.2YesYes32%42% 5-yr dfs84% 5-yr dfsLaitinen et al. [11]22966 (62)Yes (NR)Yes (4)PSA ≥ 0.5 × 2YesYes63% 5-yr dfs10-yr 41%5/10-yr dfs 2–15% : 62%/38% 16+% : 42%/27%5/10-yr dfs0-1% : 92%/65%Moul et al. [4]162(54)Yes (1)NRPSA > 0.2 × 2YesNo38%31% 6-yr dfs72% 6-yr dfsBettencort et al. [12] (same patients as [4] above)180(53)Yes (1)NRPSA > 0.2 × 2YesNo60% 5-yr dfs5-yr dfs1+ 69% 2–4+ 44%5-yr dfs83%Vis et al. [15]112113Yes (6)NoClinical only@Yes for clinical recurrenceNoClinical dfs 5-yr 52% 10-yr 42%Clinical dfs5-yr 75%10-yr 75%NR: not reported.@Most studies include biopsy-proven local recurrence and radiographic distant metastasis as failure in addition to PSA.*Three factors: Ki-67, SV+, margin+; A = 2-3 factors, B = one factor, C = all 3 negative.Even though those studies showed on multivariate analysis Ki-67 was able to predict failure, other than the correlation shown in the Miyake et al. study [9], none of the studies evaluated as to how Ki-67 improved the predictive ability of the standard prognostic factors. Therefore, its utility remains uncertain, which is further compounded by the studies that show that Ki-67 is not predictive for failure. In that regard, in a study of 162 patients undergoing RRP (median followup 4.5 years, PSA failure > 0.2 ng/mL at least twice), Ki-67 staining was measured <2 in 62% of the tumors and 2–4 in 38% [4]. On multivariate analysis including pathology stage, race, Gleason score, age, p53, bcl2, and Ki-67 (MIB-1) levels, p53 and bcl-2 were prognostic, but not Ki-67. The findings were confirmed in another study of the same patients [12]. From the cohort of 335 patients, this time 180 had available tissue. With a mean followup 4.4 years, and failure defined as PSA > 0.2 ng/mL twice, the overall 5-yr biochemical failure-free survival (BFFS) was 60%. Ninety per cent had measurable Ki-67 (MIB-1) staining. In 18 patients with negative or rare Ki-67 staining, 3 (5%) progressed for an 83% 5-year biochemical-free survival (BFFS); of 90 that stained 1+, 23 (37%) progressed for a 69% 5-year BFFS; and in 72 that were 2–4+, 36 (58%) progressed with a 5-yr BFFS of 44%. On multivariate analysis, stage and Gleason score were significant prognostic factors and Ki-67 was only marginal. In a subgroup analysis, Ki-67 appeared to differentiate failure in Gleason 2–6 patients, but not in higher grade. A third paper including at least some of the same patients (132) [13] showed Ki-67 positive patients had a higher recurrence rate but again the findings were not significant on multivariate analysis. In a different approach [14], 41 prostatectomy patients who failed within two years (PSA > 0.2 ng/mL) were matched for pathologic stage, PSA, and Gleason score with 41 patients who did not have a rising PSA by three years. They found no difference in Ki-67, p53, and bcl-2 between the two groups. Finally, in an evaluation of 112 prostatectomy patients [15], for patients with low MIB-1 staining, the 5- and 10-year clinical disease-free survival was 75% for both, and for high staining patients was 52 and 42%, respectively. In spite of this difference, MIB-1 was not predictive of recurrence or death on multivariate analysis.
### 3.2. Apoptosis-Related Markers (p53, bcl-2, and MDM2)
Cellular stress triggers (upregulates) p53, which accumulates in cells and leads to either cell cycle pause and repair or apoptosis. Loss of p53 function potentially can allow a cell that would normally undergo apoptosis to survive an otherwise lethal event. Bcl-2 is antiapoptotic and elevated levels can also conceptually allow cells to survive an otherwise lethal event. Mouse double minute-2 (MDM2) has an antiapoptotic effect by binding to p53 and inactivating it. Wild-type or normal p53 is cleared rapidly from cells, so measurable p53 is usually dysfunctional. Therefore, counter-intuitively, an elevated p53 actually represents decreased p53 function.As with Ki-67, there are several positive and negative studies (Table2). In 71 patients operated on before 1984 [16] with a median followup of 10.6 years, 15-year cause-specific survival for p53 positive patients was 38% and for p53 negative patients was 87%. They also found that the 15-year cause-specific survival for retinoblastoma protein (Rb) positive patients was 66% and Rb negative was 92%. On multivariate analysis, the combination of p53 and Rb was the strongest predictor of failure. There was no analysis with the common prognostic factors (stage, PSA, or Gleason score). A later study in 76 RRP patients with a median followup of 50 months found that 27% of the patients with <40% positive p53 staining recurred versus 6/10 (60%) with more than 40% staining [17]. On univariate analysis, nuclear grade, pathologic stage, and p53 were significant, but on multivariate analysis, only p53 was significant. In another prostatectomy study, 263 patients had a mean followup of 55 months and 39% failed [18]. Seventy-eight received adjuvant treatment. They found clustering of p53 positive cells (>12 cells) to be more predictive than percentage of positive cells. On multivariate analysis, both clustering and percentage p53 positive, along with PSA, path stage, Gleason score, and lymph node positivity were predictive for failure.Table 2
p53, bcl-2, and outcomes after radical prostatectomy. The table indicates whether p53 and bcl-2 was positive on univariate or multivariate analysis for predicting failure. The failure of the entire cohort is given and then the outcomes for patients where the marker was elevated versus not elevated.
Study#ptsMed (mean) months f/uInclude LN+ (n)Include Adj RX (n)Definition of failure@Univariate positiveMultivariate positiveGroup overall failureMarker elevated outcomeMarker not elevated outcomeP53Theodorescu et al. [16]71127Yes (1)NoClinical,PSA > 0.2YesYes51% failed15-yr cause-specific 38%15-yr cause-specific 87%Kuczyk et al. [17]7650Yes (6)NoClinicalYesYes32% failed20% died ca33% died ca16% died caQuinn et al. [18]263(56)Yes (5)Yes (99)PSA ≥ 0.4 × 2YesYes39% failed32% 5-yr dfs83% 5-yr dfsMoul et al. [4]162(54)Yes (1)NRPSA > 0.2 × 2YesYes38%39% 6-yr dfs76% 6-yr dfsBauer et al. [19] same patients as [4]175(55)Yes (1)NRPSA > 0.2 × 2YesYes38%45% failed5-yr dfs 49%23% failed5-yr dfs 78%Brewster et al. [20]76(38)NRNoPSA ≥ 0.2 × 2YesYes30%41% failed21% failedGoto et al. [21]11940NRNoPSA > 0.2NoNo13% failed40% failed10% failedMiyake et al. [9]19363Yes (13)NoPSA > 0.2YesNo21% failed5-yr dfs 79%NRNRWu et al. [23]7036.5NRNRPSA > 0.2 × 2NoNo30%44% failed26% failedOsman et al. [24]8665NRYes (33)3 × PSA increaseNRYesNR0 5-yr dfs68% 5-yr dfsBCL-2Bauer et al. [19]175(55)Yes (1)NRPSA > 0.2 × 2YesYes38% failed57% failed5-yr dfs 33%31% failed5-yr dfs 69%38% failedBCL2+ P53+5-yr dfs 25%BCL2− P53−5-yr dfs 80%Brewster et al. [20]76(38)NRNoPSA> 0.2 × 2YesYes30%53% failed24% failedGoto et al. [21]11940NRNoPSA > 0.2NoNo13% failed21% failed10% failedBubendorf et al. [22]137(64)Yes (34)Yes (60)PSA, PAP, ALKPNRNo19% failed5 yr dfs 78%10-yr dfs 18%10-yr dfs 52%Miyake et al. [9]19363Yes (13)NoPSA > 0.2NoNo21% failedNRNRWu et al. [23]7036.5NRNRPSA > 0.2 × 2YesYes30%67% failed28% failedNR: not reported.Most studies include clinical failure: biopsy-proven local recurrence and/or radiographic distant metastasis in addition to PSA.Several studies have considered p53 in conjunction with other factors such as bcl-2, and Ki-67. In one study consisting of 162 patients undergoing RRP (median followup 4.5 years, PSA failure > 0.2 ng/mL at least twice) p53 was measured negative in 31% of the tumors and positive (1–4+) in 69%. Bcl-2 was measured negative in 73% of the tumors and positive (1–4+) in 27% [4]. On multivariate analysis including pathology stage, race, Gleason score, age, p53, bcl-2, and Ki-67 (MIB-1) levels, p53 and bcl-2 were prognostic. There was no correlation as to what the markers added to the common prognostic markers. In another study from the same patient cohort, 175 patients underwent radical prostatectomy [19]. With a mean followup of 4.6 years, p53 staining was positive in 65% and the 5-year failure rate was 51%, compared to 22% for the patients that stained negative. Bcl-2 staining was positive in 27% and the 5-year failure rate was 67%, compared to 31% for the patients that stained negative. For patients that were both p53 and bcl-2 positive, the five-year failure rate was 75% compared to 20% for those that were negative for both. On multivariate analysis, stage, race, bcl-2, and p53 were all prognostic. Again, there was no indication of whether they enhanced the standard markers. Interestingly, in yet another analysis of some of the same patient cohort (132 patients) with median followup of 3.9 years, p53 positive patients had a higher recurrence rate but it was not significant on multivariate analysis [12]. Another study of p53 and bcl-2 looked at 76 prostatectomy patients with a mean followup of 38 months, 23 (30%) of whom failed [20]. Fifty-seven percent were p53 positive on prostatectomy tissue and 41% failed compared to 21% with normal p53. Twenty percent were bcl-2 aberrant on prostatectomy tissue and 53% failed compared to 24% of those with normal bcl-2. In an additional study of 119 radical prostatectomy patients receiving no neoadjuvant treatment and with a median followup of 3.3 years, 16 (13%) failed [21]. On multivariate analysis, bcl-2, p53, Ki-67, PSA, Gleason score, Capsular penetration, age, and margin positivity were not predictive, but SV involvement and caveolin-1 (see below) were.In an older cohort of patients (22% of the failures predated PSA), 30 received adjuvant treatment (mostly radiation) [22]. With a mean followup of 5.2 years, bcl-2 positivity was predictive of recurrence, but only stage pT3 and Ki-67 were predictive of failure (not p53). From the graph, for elevated bcl-2, 10-year disease-free survival was 18% and for nonelevated bcl-2 was 52%. Only 8% overexpressed p53. Like p53, it is also not uncommon for bcl-2 staining to be too low (<5%) to be meaningful [10].Miyake et al. evaluated 193 prostatectomy patients with twelve markers on IHC, including p53 [9]. While it was predictive on univariate analysis, it was not on multivariate. Bcl-2 was not predictive for either. In a study of 70 pathological T2 patients [23] with a median followup of 36.5 months, 30% suffered biochemical relapse (PSA > 0.2 ng/mL times two), sixteen patients were p53 positive, and 44% suffered PSA relapse which was not significantly different than the p53 negative patients (26% relapse). Only 3 (4%) patients were bcl-2 positive, but 2 (67%) relapsed, which was significantly higher than the bcl-2 negative patients (28% failure). Finally, in a study [24] of 86 patients (median followup 65 months) with an undetectable PSA after radical prostatectomy (38% received neoadjuvant treatment), 20% overexpressed p53 and had a higher risk of relapse. The 33% that overexpressed MDM2 also had a higher risk of relapse. No details were given, but on multivariate analysis, both p53 and p21 were predictive. Stage and MDM2 were not. Interestingly, there was no association with p53 overexpression and p21 or MDM2. As with all the studies discussed, there was no real analysis for correlation with standard predictive factors, so the real predictive power of these markers remains elusive.
### 3.3. E-Cadherin and Other Adhesion Molecules
Calcium-dependent adhesion molecules (cadherins) are transmembrane proteins that play a role in cell adhesion. E-cadherin is a subtype found in epithelial tissue with extracellular, transmembrane, and intracellular domains. The intracellular domain binds to beta catenin. In cancer, E-cadherin downregulation theoretically reduces cell adhesion resulting in increased cell motility and dissemination.In a study of 70 pathological T2 patients [23] with a median followup of 36.5 months, 30% suffered biochemical relapse (PSA > 0.2 ng/mL times two). Thirty-nine patients (56%) had aberrant E-cadherin staining, with a 44% PSA relapse rate, which was significantly worse than those with normal E-cadherin staining (13% recurrence). In 104 prostatectomy patients [25] (7 lymph node positive), low E-cadherin, Gleason score, and pathologic stage were predictive of biochemical failure (PSA > 0.5 ng/mL) on multivariate analysis. For clinical failure, pathological stage dropped out and elevated N-cadherin was significant. For patients with low E-cadherin, the 10-year biochemical failure-free survival was 14%, versus 33% for those with elevated levels. For N-cadherin, low levels resulted in 33% biochemical failure-free survival and high levels 14%. They found that the E-cadherin to N-cadherin ratio was more powerful than either alone, but did not provide specifics nor any details on the modification of the predictive power of standard factors. In a study of 67 radical prostatectomy patients [26] with a median followup of 54 months, 27 (40%) recurred clinically, 7 locally, and 20 systemically. When evaluated with IHC for E-cadherin, a cut point of 40% staining was chosen. For the 13 that stained less than 40%, 2 (15%) died of cancer and for the 54 that stained >40%, 14 (26%) died of cancer, but the difference was nonsignificant. E-cadherin was not predictive on univariate or multivariate analysis for either recurrence or survival. In 128 radical prostatectomy patients [27] without adjuvant treatment, tissue microarrays were made and stained with IHC staining. Normal was considered >70% staining. For nonmetastatic prostate cancer, 18% had aberrant staining. With a median followup of 23 months, 38% of the failures and 20% of the nonfailures had aberrant staining, a nonsignificant difference. Similarly, in a microarray study (discussed below), Rhodes et al. [28] found that a decreased E-cadherin to EZH2 ratio resulted in an increased rate of biochemical failure after radical prostatectomy.Brewster et al. [20] studied 76 prostatectomy patients; 49% were E-cadherin aberrant on prostatectomy tissue and 37% failed compared to 22% with normal E-cadherin. On multivariate analysis, it was not predictive when considered with p53, bcl-2, Gleason score, and margins. They also evaluated another apparent adhesion molecule in the form of the cell surface glycoprotein CD44. Sixty-four percent were CD44 minimal or absent on prostatectomy tissue. Of those with normal staining, 8% failed compared to 43% with aberrant staining. On multivariate analysis, it was not predictive when considered with p53, bcl-2, Gleason score, and margins. Two other studies evaluated CD44. In 97 radical prostatectomy patients [29] with median followup of 84 months, utilizing PSA of >1.0 as failure, most (86%) patients were positive for CD44, so risk was determined by graded intensity of the staining. Decreased expression increased the risk of failure. On univariate analysis, loss of CD44 and cd4v6 were predictive of clinical failure, but only CD44 was predictive for biochemical failure. In the other study, 99 patients had mean followup of 40 months and 26% suffered a biochemical recurrence [30]. CD44 was evaluated via an intensity and percent staining score, and 47% were downregulated. The 3-year recurrence-free survival was 77% for the nondown-regulated patients versus 48% for those with CD44 downregulation. It was not a significant predictor on multivariate analysis, when considered with p34.In none of these studies was there an assessment of how it modified the predictive ability of the standard prognostic factors.
### 3.4. EZH2
The Enhancer of Zeste 2 (EZH2) gene codes for polycomb group proteins that effect chromatin and silence genes. When overexpressed, it appears to be associated with tumorigenesis. In a study involving multiple cancers [31], 104 radical prostatectomy patients with a median followup of 104 months were evaluated with staining for EZH2. For low EZH2 staining, the 5- and 10-year cause-specific survival was 99% and 93%, respectively. For the high staining group, it was 89% and 53%, respectively. On univariate analysis, upper quartile EZH2 staining was predictive for clinical recurrence and on multivariate analysis was predictive for distant metastasis and death. In another study of 64 patients [32], tissue was stained for EZH2 and if the intensity was ≥3, 10/32 (31%) failed versus 3/32 (9%) if the staining was <3. It was a significant factor on multivariate analysis along with margin status, tumor size, Gleason score, and PSA. Finally, in a study (see Ki-67 above) [11] of 249 prostatectomy patients, five- and 10-year disease-free survival was 63% and 41%, respectively. On multivariate analysis, pathologic stage, Ki-67 and MCM7 were significant predictive factors (EZH2 was not). In patients that were lymph node negative with an undetectable postsurgery EZH2, MCM7 and PSA were prognostic. In Gleason less than 7 patients, Ki-67 was the only significant factor. There was no evaluation of whether this added to the predictive ability of standard factors.
### 3.5. Cyclin-Dependent Kinases (and Their Effectors)
Cyclin dependent kinases (CDKs) are protein kinases involved in the regulation of the cell’s progression though the cell cycle. As most cancers have dysfunctional cell cycle control, the kinases are implicated as part of the aberrancy. Cyclin D1 is specific for transition through G1/S. It has its effect by binding with cyclin dependent kinases 4 and 6 forming a complex that phosphorylates and inactivates the retinoblastoma protein (Rb). Overexpression of cyclin D1 has been associated with the malignant phenotype and its progression. There are several known inhibitors of cyclin dependent kinases. For example, p16INK4a (cyclin-dependent kinase inhibitor 2A) inactivates Cdk4 and CdK6 and thereby acts as a tumor suppressor (by blocking the phosphorylation of the Rb gene, which prevents transit through G1). Loss of p16 enables abnormal progression through the cell cycle, increasing the malignant potential. P21-waf1 encodes a cyclin dependent kinase inhibitor (p21 or cyclin dependent kinase inhibitor 1A), inhibiting CDKs 2 and 4, which leads to arrest at G1. It is induced by p53 (thus elevated p53 can lead to arrest at G1 through this route). P27Kip1 (cyclin dependent kinase inhibitor 1B) is also involved in G1 arrest by inhibiting cyclin dependent Cdk2 complexes E and A and D-Cdk4. Therefore, a decrease in p27 should result in increased proliferation. Lastly, p34cdc2 (cell division control protein 2) is a component that forms a kinase by binding with cyclin B1 (forming maturation-promoting factor (MPF)) that regulates G2/M transition and promotes mitosis).In a study [24] of 86 patients with an undetectable PSA after radical prostatectomy (38% received neoadjuvant treatment), 33% overexpressed p21Cip, and this was associated with a higher risk of relapse. No details were given, but on multivariate analysis, both p53 and p21 were predictive of relapse whereas stage and MDM2 were not.In one study, where the primary goal was to assess the association between pathological features and biomarker expression [33], p27Kip expression was evaluated in 113 prostatectomy specimens (median followup 4.6 years, 21% neoadjuvant androgen ablation), and correlated with outcome. Low p27 nuclear staining was a poor prognostic sign. On multivariate analysis, p27, seminal vesicle status and margin status were all predictive for recurrence, but no details were given. In a second study of 96 stage C lymph node negative patients undergoing radical prostatectomy with a median followup of 9.5 years [34], p27 Kip1 staining correlated with Gleason score (higher grades had decreased levels). The 9-year recurrence-free survival for levels ≤10% was 17%, for levels 11–50% was 47%, and for >50% was 67%. There was no correlation with the standard factors. In a third p27 study [35] of 86 patients (after excluding those that received adjuvant treatment), multivariate analysis demonstrated only pathologic stage and p27 to be predictive at a median followup of 40 months. High Gleason score was associated with low p27 staining. Thirty percent was the breakpoint between high and low staining. Fifty percent of patients with low staining failed (PSA > 0.4) and 78% with high staining failed. In another study with 95 patients [36], loss of p27 (<10%) on multivariate analysis was significant for recurrence, but not for survival. With a median followup of 49 months, 33% of the p27 negative patients failed versus 23% for the p27 positive patients (median followup 59 months). Another study was of 161 prostatectomy patients [37], which were divided into organ confined (n=76, median followup 42 months) and nonorgan confined (n=85, median followup 38 months) patients. p27 staining was performed on the biopsy, but not the final pathology specimen, and patients were not evaluated for the specific impact of positive margins, seminal vesicle involvement, or lymph node involvement. For the organ-confined patients, the 5-year recurrence rate was 26%, but 9% for those with high p27 staining and 37% with low (<45%) staining. In this subgroup, p27 was predictive for failure. In the nonorgan confined patients, the recurrence rate was 44%, but p27 was not predictive of failure in these more advanced patients and the actual effect on failure was not stated. In an evaluation [15] of 112 prostatectomy patients, 92 had adequate p27 staining. Thirty-five (38%) stained less than 50% and were classified as low staining. Based on clinical parameters, their 5- and 10-year disease-free survival were 37% and 26%, respectively. For the high staining patients, it was 79% and 77%, respectively. p27 predicted for clinical recurrence and cause-specific survival.Finally, in a study of 104 radical prostatectomy patients with a median followup of 56 months [38], p27 was determined by the per cent of nuclei staining, with the median of 64% used as the breakpoint between high and low. On multivariate analysis, pathologic stage and PSA were significant predictors of recurrence, but not p27.p16 has been evaluated in several studies. In 206 radical prostatectomy patients (18% with neoadjuvant androgen ablation) with a median followup of 72 months, one group [39] found positive p16INK4a staining to be associated with recurrence. On multivariate analysis, p16, PSA, Gleason score, and margin status were all predictive, but no actual outcome data was given. In another study [40], 88 prostatectomy patients (39% neoadjuvant treatment) with a median followup of 65 months stained for P16. Unlike Henshall et al. [39] (which called low <1%), their breakpoint was 5% positive nuclear staining. For the 38 patients that overexpressed, 21 (55%) failed versus 26% of the 50 under expressing patients. p16 was associated with PSA levels and was not an independent prognostic factor on multivariate analysis. They also did not report specifics on outcome. In a third study of 104 radical prostatectomy patients with a median followup of 56 months [41] the multivariate analysis for survival was positive for p16, age, grade, capsular penetration, and seminal vesicle involvement. They scored p16 by a fluorescence index. The low group had a 5-year survival of 78% versus 43% for the intermediate group (P=.005) and 42% for the high index group. There was no outcome data accounting for the standard factors. Ploidy or S phase was not predictive.In analysis of cyclin D1 and p34cdc2, 140 patients [42] with a median followup of 42 months were evaluated. Failure was defined as a PSA > 0.4. In patients that were p34cdc2 negative, 10% failed versus 26% that were positive. For Gleason 7 or greater, the failure rate was 26% for p34cdc2 negative and 38% for positive. On multivariate analysis, only p34cdc2 and Gleason score were predictive and cyclin D1 and ploidy were not. p34 was also evaluated in a study of 99 patients. With a mean followup of 40 months, 26% suffered a biochemical recurrence [30]. p34 was evaluated via an intensity and percent staining score and 61% were determined to have overexpressed p34. The 4-year recurrence-free survival (from the curves) was 98% for the nonover expressed patients versus 47% for those over expressing p34. It was a significant predictor on multivariate analysis, but there was no evaluation of whether it enhanced the predictive ability of standard factors.
### 3.6. Cathepsin-D
Cathepsins are proteases (i.e., involved in protein degradation) usually housed in lysosomes that proteolyse proteins that regulate cell growth. In a study [43], 105 radical prostatectomy patients were evaluated for cathepsin D. It was not prognostic on either univariate or multivariate analysis, but probably because the expression rate was extremely high at 98%.
### 3.7. Chondroitin Sulfate
Chondroitin sulfate is a structural glycosaminoglycan of the extracellular matrix that helps regulate cell activity. Ricciardelli et al. [44] studied 157 prostatectomy patients after exclusion of adjuvant and neoadjuvant treatment; failure was defined as a PSA > 0.2 and median followup was 47 months. They used an antibody to chondroitin sulfate and read the slides via an image capture technique with automated analysis. There was a twofold difference between this study and previous studies for the absolute value of the mean due to calibration differences, which demonstrates the lack of uniformity in these studies. The median was chosen as the cut point, although the most robust point was slightly above that. On multivariate analysis, chondroitin sulfate, Gleason score, preoperative PSA, and pathological stage were all predictive. For patients with low staining, 23% failed for a 5-year PSA failure rate of 33% versus 51% with high staining failing for a 5-year failure rate of 51%. There was some correlative analysis between chondroitin staining and other predictive factors. For patients with a preoperative PSA less than 10, 9% with low chondroitin sulfate staining failed versus 48% with high levels. In a more specific analysis, the five-year failure rate for Gleason 5–7 patients with low chondroitin levels and low PSA was 11% compared to 44% for low chondroitin staining patients with a high PSA. Further, Gleason 5–7 patients with high chondroitin sulfate staining and low PSA had a five-year failure rate of 56% versus 72% for high staining and high PSA. There was no evaluation done with the integration of pathology findings.
### 3.8. Hepsin and PIM1
Hepsin is a transmembrane serine protease whose exact function is unknown, but when upregulated appears to express a malignant phenotype. PIM1 encodes a protein kinase that promotes G1/S transition by upregulation of CDK2, facilitating cell proliferation and survival. One study [45] utilized human specimens and cell lines for comparison of malignant and benign tissue. Out of several hundred candidate genes, hepsin and PIM1 expression proteins were selected for further analysis. Hepsin was increased in malignant prostate tissue versus benign, but staining was greatest in PIN. In radical prostatectomy patients, low or absent hepsin increased failure. On multivariate analysis, both hepsin and Gleason score were predictive of failure. They also tested for PIM1. It was upregulated in prostate cancer and decreased levels were associated with increased PSA level in 135 patients with localized prostate cancer. It was significant on multivariate along with Gleason score 4-5 and PSA. They concluded that lower PIM1 levels were strongly associated with an increased risk of relapse. There was no outcome correlation with standard factors with either marker.
### 3.9. Cox-2
In a study of 91 prostatectomy patients [10], with a median followup of 46.5 months, 29 (32%) progressed (PSA > 0.2 ng/mL). A score was developed for percent and intensity of staining for Cox-2. For no staining, the failure rate was 26% versus 60% for 1–4, but then dropped back to 15% for 5–12. While it was a predictive marker on univariate analysis, it was not on multivariate.
### 3.10. Laminin Receptor (Ribosomal Protein SA)
Laminins are glycoproteins located in the basement membrane (basal lamina) that affect cell adhesion and migration as well as differentiation and survival. Laminin receptor (LR) is detected via the MLuC5 antibody. In an initial evaluation [46] in 140 patients, it appears that laminin receptor positivity might be associated with recurrence. Overall, the 3-year biochemical failure-free survival was 68%, but for LR positive patients the failure was 45% and for negative patients it was 7%. There was no correlation with PSA and Gleason score. The followup was only 20 months, and a later paper [47] showed that LR measurement of the biopsy tissue was not significantly predictive for biochemical progression, probably due to a lack of concordance between the measurements in biopsy tissue versus the larger tumor specimen.
### 3.11. Chromogranin A (CGA)
In a study of 528 prostatectomy patients [8] excluding neoadjuvant and adjuvant androgen ablation and radiation therapy, with a median followup of 46 months, 101 (19%) failed for a 5-year disease-free (PSA < 0.2 ng/mL) rate of 78%. The tissue was evaluated using IHC staining for Ki-67 and chromogranin A (CGA). On multivariate analysis, Gleason score > 4 + 3, CGA positive, lymph node positive, PSA >20 ng/mL, and Ki-67 were prognostic, while pathologic stage T3 and margin positivity were not. For the 32 CGA positive patients, the 5-year biochemical recurrence-free survival was 48% and for the 496 CGA negative it was 80%. Because of the small number of CGA positive patients, the only specific information was given on whether there was modification of prognosis of the standard factors was for Gleason <7 patients, where for the 304 CGA negative patients, 8% failed and for the 12 CGA positive, 25%.
### 3.12. Minichromosomal Maintenance Protein 7 (MCM7)
Minichromosome maintenance protein 7 (MCM7) appears to be a facilitator of DNA replication, so upregulation would be expected to increase proliferation. It has been found on microarray analyses that MCM7 is frequently amplified in prostate cancer. In an evaluation of prostatectomy patients [48], 52/68 (77%) with MCM7 amplification relapsed versus 7/57 (12%) without amplification. In a study discussed above (see Ki-67) [11], pathologic stage, Ki-67, and MCM7 were significant predictive factors. In evaluation of patients that were lymph node negative with an undetectable postsurgery, EZH2, MCM7, and PSA were prognostic. In both studies, there was no clinical correlation, so these interesting findings are of uncertain significance.
### 3.13. Histones
Histones are intranuclear proteins in chromatin around which DNA is “wound”, the modification of which influences their interaction with the DNA and affects some processes such as mitosis and gene regulation. In 183 radical prostatectomy patients, those that received androgen ablation were excluded. The median followup was 60 months and failure was defined as PSA > 0.2 ng/mL [49]. In order to evaluate sites on histones H3 and H4 with acetylation and dimethylation staining, 5 different sites were identified by using a clustering algorithm. While not independently predictive, when combined with Gleason score, the findings yielded prognostic information. From the graph, Gleason < 7 patients that were histone “favorable” had an 84% disease-free survival, while those unfavorable had a 58% disease-free survival. For Gleason 7–10, the favorable group had a disease-free survival of 46% versus 20% for the unfavorable.
### 3.14. TMPRSS2 : ERG Fusion
TMPRSS2 (transmembrane protease, serine 2) is an androgen-regulated gene found on chromosome 21 that encodes a transmembrane protease. In prostate cancer, it can be fused with genes for the ETS transcription factors, such as ERG (resulting in TMPRSS2 : ERG). This indirectly places ERG under androgen transcriptional control. There are multiple variants of this fusion. This can be detected through either RT-PCR or fluorescence in situ hybridization (FISH). In 165 prostatectomy patients with available frozen tissue [50] with a median followup of 20 months, tissue was evaluated for TMPRSS2 : ERG fusion gene and 49% was positive. For the fusion gene positive patients, 46% failed compared to 7% in fusion negative patients. On multivariate analysis, the fusion gene was the most predictive factor, followed by grade. Evaluation was made for different Gleason and pathologic findings. For Gleason 5-6 patients, 33% of the gene positive patients failed, versus 5% for the gene negative. For Gleason 7 and Gleason 8–10, it was 48% versus 7% and 75% versus 14%, respectively. For organ-confined patients, gene positive patients had a recurrence rate of 34% versus 10% for gene negative. For extraprostatic extension and seminal vesicle positive patients, it was 53% versus 3% and 67% versus 34%, respectively. For both Gleason score and pathological findings, all the differences were statistically significant, except for the seminal vesicle involved patients. Another study, started with 248 radical prostatectomy patients [51], but only 150 were ultimately evaluable by FISH. Of those, 50 (33%) were found to have TMPRSS2 : ERG rearrangement. With a median followup of 66 months and failure defined as two rises of PSA > 0.5 ng/mL, on multivariate analysis, Ki-67, pathologic stage, and TMPRSS2 : ERG fusion were significant, not Gleason score or PSA [52]. Yoshimoto et al. evaluated specimens from 125 radical prostatectomy patients, 122 of which had clinical followup and with a median followup, 49% had failed (PSA > 0.2 ng/mL). Neoadjuvant androgen ablation was allowed, and 2 patients were lymph node positive. FISH was used to evaluate for TMPRSS2 : ERG, and 48% were found to have rearrangements resulting in a 5-year biochemical failure-free survival (BFFS) of 46%. For those that were negative, 5-yr BFFS was 62% (P=.0523). Expanding on their previous work, they also evaluated for PTEN deletion by FISH. Only 82 of the 125 patients could be evaluated. There was no difference in 5-yr BFFS between those that were deletion negative and positive, but if they divided the deleted patients into hemizygous and homozygous deletions, they found that all the homozygous patients had failed by 5 years. If patients had both the PTEN deletion and the TMPRSS2 : ERG fusion, 5-yr BFFS was 30% versus 59% if they had neither (P=.001). They did not test to see whether these markers augmented the predictive ability of the three standard factors (Stage, Gleason score, or PSA), although on multivariate analysis only Gleason score, the TMPRSS2 : ERG/PTEN combination and homozygous PTEN deletion were prognostically significant. A study [53] using microarray to compare genes between benign and malignant cells found that ERG was the most commonly over expressed. Then utilizing QRT-PCR, they analyzed 114 prostate cancer patients and found ERG1 over expressed in 62%. Ninety-five patients had detectable levels and for a >100 over expression, the 5-year biochemical failure free-survival (from the graph) was 88%, for 2–100 fold 80% and for <2 fold 36%. On multivariate analysis, ERG1 (>100 versus <2) and Gleason (8–10) were significant, but not race, PSA, pathologic stage, margin positive, or seminal vesicle positivity.Not all studies found TMPRSS2 : ERG to be prognostic. In one study [54], two subgroups were taken from larger prospective studies and ultimate outcome collected from SEER data. This yielded no failure data and only crude followup of cancer-specific survival. Of the subgroups, only 57% could be scored for the fusion. They reported no association between the occurrence of TMPRSS2 : ERG (positive in 36% of the patients) and cancer specific survival. Researchers in a study [55] of 521 radical prostatectomy patients with 95 month median followup utilized FISH and found 42% had TMPRSS2 : ERG abnormalities. It was not associated with recurrence, metastasis or death. Finally, in a study of 54 patients [56], 35 (65%) had gene rearrangement, which was present in 60% of the nonfailing patients and 65% of the failing patients. In the evaluation of 28 benign prostate tissues, there were no rearrangements.
### 3.15. PTEN
The phosphatase and tensin homologue (PTEN) gene modulates the phosphotidylinositol 3-kinase (PI3K) pathway, a regulator of the Akt pathway. Lack of PTEN allows for upregulation of Akt and other cell cycle factors, increasing cell survival. As noted above [52] in the TMPRSS2 : ERG discussion, on multivariate analysis, homozygous PTEN deletion and the TMPRSS2 : ERG fusion were prognostically significant. In an earlier study specifically evaluating PTEN, the same authors [57] utilized fluorescence in situ hybridization (FISH) to PTEN in 107 prostatectomy patients. Tissue was scored as showing no deletions (56%), hemizygous deletions (39%), or homozygous deletions (5%). On Cox proportion hazard analysis, for univariate analysis, perineural invasion, seminal vesicle positive (SV+), extraprostatic extension (EPE), Gleason score, PSA, lymph node positivity, and PTEN deletion were all predictive. On multivariate analysis, only EPE, SV+, and PTEN were predictive. For PTEN, from the graph, 5-year PSA (>0.2 ng/mL) failure-free survival was 0 for the 5 homozygous patients, 48% for the 42 hemizygous patients, and 60% for the 60 patients without deletion. There was no discussion as to how PTEN modified the predictive ability of standard factors. In a separate study of 104 radical prostatectomy patients with a median followup of 56 months [38], PTEN was scored as an index based on percent staining and intensity. On multivariate analysis, pathologic stage and PSA were significant predictors of recurrence, but not PTEN.
### 3.16. Epidermal Growth Factor Receptors (EGFR)
Epidermal growth factors are extracellular ligands controlled by the cell surface epidermal growth factor receptors, which are tyrosine kinase receptors. When activated, they initiate a cascade of signal transduction (i.e., though the Akt pathway) that results in cell proliferation. If the receptor is mutated in the “on” position (i.e., over expression), the result could be uncontrolled proliferation. Her-2/neu (c-erb B2) encodes a tyrosine kinase growth factor receptor similar to the epidermal growth factor receptors and has been linked with advanced disease. In one study, [43] 105 radical prostatectomy patients were evaluated for epidermal growth factor receptor (EGFR). The expression rate was 48%, but it was not prognostic on either univariate or multivariate analysis. In 113 prostatectomy patients with a mean followup of 42 months [58], utilizing IHC, membranous and cytoplasmic staining was given a composite score so that ≥3 was considered positive. With that parameter, 29% of the tissue over expressed and there was no correlation with failure on univariate analysis. Utilizing FISH, it was found that 41% were amplified for Her2, but there was poor correlation with IHC staining (P=.25). While FISH analysis was significant for failure on univariate analysis, it was not a significant predictor of failure on multivariate analysis. In 99 patients with a mean followup of 40 months, 26% suffered a biochemical recurrence [30]. Her 2-neu was evaluated via FISH and 42% were found to be amplified. The 5-year recurrence-free survival was 75% for the nonamplified patients versus 47% for those with Her 2-neu amplification. It was not a significant predictor on multivariate analysis, when considered with p34.
### 3.17. VEGF
In a study of 193 prostatectomy patients [9], twelve markers were evaluated on IHC, including VEGF, but it was not predictive on univariate analysis.
### 3.18. Caveolins
Caveolins are cell membrane proteins involved in endocytosis resulting in invagination of the plasma membrane (caveolae). They appear to be involved in signal transduction with a role in homeostasis and tumorigenesis. Caveolins have been found to be both increased and decreased in cancer so their role is variable and uncertain. In radical prostatectomy patients selected for failing or not failing, 162 lymph node negative patients were identified. With immunohistochemical staining for caveolin 1, 22% were positive and five-year progression-free survival was 43% versus 68% for those that were negative. On multivariate analysis, caveolin 1, Gleason score, extracapsular extension, seminal vesicle involvement, and margin involvement were all predictive [59]. The same group later studied serum levels of caveolin 1. As noted above, in a study [21] of 119 radical prostatectomy patients on multivariate analysis only caveolin 1 staining and SV involvement were predictive on multivariate analysis, but bcl-2, p53, Ki-67, PSA, Gleason score, Capsular penetration, age, and margin positivity were not. For caveolin 1 positive patients, 9/32 (28%) failed versus 7/87 (8%) that were negative. In 232 prostatectomy patients that included lymph node positive and those that received salvage radiation therapy [60], with a median followup of 70 months, the 5-year biochemical-free survival rate was 80%. On multivariate analysis, only Gleason sum (not Caveolin 1 staining) was a significant predictor of failure. When limited to lower risk patients (n=177) with exclusion of lymph node positive, seminal vesicle positive, Gleason > 7, and extracapsular extension/margin positive, caveolin 1 was still not a significant predictor on multivariate analysis. They did find that in evaluating only the recurring patients, those that had caveolin 1 over expression did worse. In a similar study [61], 30% of 152 radical prostatectomy patients (including lymph node positive) stained positive for caveolin 1. It was not predictive on multivariate analysis (only seminal vesicle positivity, margin positivity, and PSA were), but when restricted to patients with organ-confined disease, it was the lone predictive factor. This is somewhat in contradistinction to the low risk patients noted in the study above.
### 3.19. Zinc-Alpha2-Glycoprotein (AZGP1)
Zinc-alpha2-glycoprotein (AZGP1) encodes for a protein historically thought to be involved in lipolysis and thought to have a role in the cachexia of cancer. From a series of 732 radical prostatectomy patients [62], 228 were analyzed. Forty-three percent failed with a PSA rise of ≥0.2 ng/mL. On IHC, tissue was scored as absent or weak versus strong AZGP1 staining. Twenty-nine percent stained weak. Although there were few events, it appears to be predictive of clinical recurrence and distant metastasis, but there was no evaluation as to modification of common prognostic factors. In a gene array study [63] discussed below, AZGP1 was predictive for nonrecurrence.
### 3.20. Alpha Methylacyl CoA Racemase (AMACR)
Alpha methylacyl CoA racemase (AMACR) is a catalytic enzyme (of fatty acids) that is frequently over expressed in prostate cancer, but levels are decreased in advanced cancers as compared to localized. In 204 radical prostatectomy patients [64], IHC was performed for AMACR expression proteins and regression analysis was used to correlate staining with PSA failure (>0.2 ng/mL). With visual scoring on a scale of 1–4, there was no correlation with failure, but with quantitative expression analysis, patients in the lower tertile were more likely to recur. For patients more than 1.11 standard deviations below the cut point, 37.5% failed versus 14.5% if they were above. This was significant on multivariate analysis along with PSA, Gleason score, and margin status, but there was no evaluation as to the actual effect on the prognostic ability of those factors.
### 3.21. Gene Arrays and Panels
With the use of gene expression micro arrays, the hope is that by screening a large number of genes, genes highly predictive of cancer recurrence could be identified. When using probe arrays, multiple genes can be identified that may predict for relapse. Several groups have evaluated this approach in predicting failure postprostatectomy. In a gene expression profile of 225 tumors with a median followup of 8 years [63], it was found that MUC1 was predictive of recurrence and AZGP1 was predictive of nonrecurrence. Both of these genes were predictive on multivariate analysis along with Gleason score, stage, and PSA. There were no actual outcome results given. A similar study [28] of 259 RRP patients with a median followup of 57 months searched also for markers using microarray assay. They found that the combination of EZH2 increased and ECAD decreased was most predictive of 5-year recurrence (38% versus 15% for those without that combination). On multivariate analysis, this ratio was significant along with PSA, margin status, and pathological stage, but not Gleason score. For organ-confined patients that were margin negative, those that were EZH2/ECAD elevated had a 27% recurrence rate, versus 10% for those that had a decreased ratio. They did not report on higher-risk patients. In a different study of 100 lymph node negative prostatectomy patients [65], with a median followup of 70 months an expression analysis of 12,625 transcripts identified 218 genes that were either up- or down regulated. Recurrence was defined as three rising PSA levels. The combination that predicted recurrence was deemed “poor markers”. For Gleason 6-7 cancers, the 5-year disease-free survival was 69%, but was 77% in the good marker group and 47% in the poor marker group. In Gleason 8-9 cancers, the 5-year disease-free survival rate was 26%, but was 67% with good markers and 0 with poor markers. On multivariate analysis, Gleason score and the gene expression markers were predictive of recurrence, but PSA and age were not. Using a postoperative nomogram [66] they identified poor risk patients by nomogram (undefined) who had a 28% 5-year disease-free survival, increasing 50% with good gene markers, but 19% with poor markers. In the nomogram predicted favorable group, 5-year disease-free survival was 81%, which was 87% with good markers and 59% with poor markers. The major limitation of the study is that there were only 21 patients in the training set and 79 patients in the validation set.Another approach is to pool multiple genes in order to try to produce a more powerful predictive model. This has been successful in breast cancer [67, 68]. With that approach [69], using a 70 gene set in it was possible to predict 27/29 “aggressive” and 27/32 “nonaggressive” cancers and predicted 16 of the 18 failures. Unfortunately, it appears only 61 patients were evaluated; there was no indication of how the findings related to standard prognostic factors. In a more comprehensive study [70] of 639 patients selected for systemic recurrence, biochemical (PSA) recurrence and nonrecurrence at 7 years, the groups were evaluated for genes that differed between them. Patients with adjuvant treatment were not excluded and failure was with a PSA > 0.2 and rising. The patients were divided into training and a validation set. Ultimately, a 17-gene panel was determined to be predictive. Clinical models based on Gleason score, and pathological stage (PSA and age were not informative) demonstrated a correlation (area under the curve) of 0.76 (0.74–0.78), while the probe set was 0.85 and the combination of the two was 0.87. They reported that the AUC for the validation set was lower. They compared their results to those of other gene array studies and found that all the other models performed better than the clinical model alone (0.74, ranging from 0.76–0.86), with their 17 gene probe being the highest. All the validation sets were lower than the training sets for these genes. In an exploratory study [71] of 72 prostatectomy patients with a median followup of 28 months, 24% relapsed. After scanning for 59,619 probe sets, over 200 genes could be identified that are associated either positively with relapse. In another exploratory study [72], tissue from 37 failing patients and 42 nonfailing patients was tested with a 22,283-gene probe microarray. The first goal was to see if the identified genes (ultimately 5–8 were used) could correctly identify the failing versus the nonfailing patients, which it did 75% of the time. When combined into a nomogram, the predictive rate increased to 89%. Given that nomograms are the most robust incorporation of the standard prognostic factors; this would represent an example of how molecular data can increase the ultimate ability to predict who will fail. Unfortunately, the number of patients evaluated was very small, so any conclusions are tentative at best. One last study took a different approach. Rather than do a blind probe for over- or under expressed genes, they [73] evaluated a pre-existing class of predictive genes like those successful in breast cancer [74]. Although the actual genes are variable, most of the predictive breast cancer genes fall under the general classification of cell cycle progression genes. In evaluation of that class of genes in a large prostatectomy cohort [73] (442 with tissue, median followup 9.5 years), a panel of 31 was tested for their ability to predict recurrence. Overall, 10-year progression-free survival was 64%. When evaluated for the standard findings of PSA, Gleason score, and pathologic findings, the patients could be divided into two groups based on these clinical factors. The low-risk group were patients with Gleason < 7, organ-confined disease, and PSA < 10 ng/mL (actually, PSA up to 30 ng/mL did not change the risk). Their 10-year risk of biochemical failure (PSA > 0.1 ng/mL) was 17%, but for those with a low CCP score, it was 4% and for a high CCP score it was 24%. For clinical high-risk patients (Gleason ≥ 7 and/or nonorgan confined and/or PSA > 30), 10-year biochemical failure was 61%, which was 51% for low CCP score, and 64% for high score. On multivariate analysis, they the CCP score was predictive of recurrence.It is interesting to note, as pointed out previously [71], using multigene predictive models, there is little overlap in the genes that are found to be significant in each of the models. This is postulated to be a factor of a large number of genes and a high signal-to-noise ratio associated with the prediction of biochemical recurrence. The challenge then is to determine which of these are true prognostic markers and which are otherwise just testing anomalies. It will take large comprehensive studies to determine this.
## 3.1. Ki-67
Ki-67 is one of the earliest markers and is named for the original mouse antibody researched in Kiel Germany, reacting in well number 67 [5]. It serves as a proliferation marker that occurs only in dividing cells (not G0). The original antibody required fresh tissue, but the MIB-1 antibody can be used in formalin fixed tissue. The assessment of Ki-67 gives an estimate (index) of the portion of cells actively proliferating.Some studies report that Ki-67 is prognostic for failure (Table1). In a study of 70 radical prostatectomy patients, 50 were selected for further analysis [6]. With a median followup of 63 months, 18% failed (PSA > 0.2 ng/mL). The specimens were evaluated for Ki-67 via IHC staining. On univariate analysis of PSA, PSA doubling time, Ki-67%, tumor volume, and Gleason score, only Ki-67% and PSA were significant prognostic factors. In another study [7], 137 patients underwent radical prostatectomy with a mean followup of 5.4 years. The cohort included 25% lymph node positive and 36% received adjuvant therapy with radiation and/or androgen ablation. Ki-67 was scored as the per cent of staining >5% (78 or 57% if the patients) or <5% (59 or 43% of the patients); the mean was 7.5%. From the graph, for patients below the mean staining, 5-year recurrence free survival was approximately 78% compared to 65% if above the mean. Ki-67 was a significant factor on multiparameter analysis. The largest study evaluating Ki-67 was of 528 prostatectomy patients after exclusion of those that received neoadjuvant and adjuvant androgen ablation and radiation therapy [8]. With a median followup of 46 months, 101 (19%) failed for a 5-year disease-free (PSA < 0.2 ng/mL) rate of 78%. The tissue was evaluated using IHC staining for Ki-67 and chromogranin A (CGA). On multivariate analysis, Gleason score > 4 + 3, CGA positive, lymph node positive, PSA > 20 ng/mL, and Ki-67 were prognostic, while pathologic stage T3 and margin positivity were not. For the 300 Ki-67 ≥ 5% patients, 5-year biochemical recurrence-free survival (from graph) was 70%, while for the 228 with <5% staining, it was 88%. In another large study, Miyake et al. [9] studied 193 prostatectomy patients that did not receive adjuvant treatment. With a median followup of 63 months, 21% failed for a 5-year disease-free survival rate of 79%. They evaluated twelve markers with IHC. On univariate analysis, they found the following factors to be prognostic: PSA, Gleason score, lymph node positivity, tumor volume, seminal vesicle involvement, margin positive, and on immunohistochemical staining: Ki-67, p53, AR, MMP-2, MMP-9, and HSP27. On multivariate analysis, only Ki-67, seminal vesicle involvement, and margin positivity remained significant. In consideration of those three positive factors, if the patient was positive for 2 or 3 of them, the recurrence rate was 79%, if positive for one, 20%, and if negative for all 3, 4%. Ki-67 was also prognostic in a smaller study of 91 prostatectomy only patients [10]. With a median followup of 46.5 months, 29 (32%) progressed (PSA ≥ 0.2 ng/mL). For the 60% of patients with <5% PSA staining, 5-year disease-free survival was 84%, compared to 42% for those with ≥5% staining (from graph). On multivariate analysis, Ki-67 and Gleason score were prognostic. The final positive study was a multifactorial study [11] of 336 RRP patients, of which 249 had tissue. Lymph node positive patients were included. Failure was defined as PSA > 0.5 ng/mL. Five-year DFS was 63%, and 10-year was 41% with a median followup of 66 months. They utilized immunohistochemical staining for Ki-67, enhancer of zeste homolog 2 (EZH2), (discussed below) and minichromosome maintenance protein 7 (MMC7) (discussed below). They also used fluorescence in situ hybridization (FISH) for EIF3S3, a chromosome abnormality they had explored previously. On multivariate analysis considering EZH2, Ki-67, MCM7, Gleason score, pathologic stage, and PSA, the factors of pathologic stage, Ki-67 and MCM7 were significant predictive factors. From the graphs, for staining 0-1%, 10-year disease-free survival was 65%, for 2–15% was 38%, and for >15% was 27%. Demonstrative as to how other factors can have an effect of prognostic ability, in patients that were lymph node negative with an undetectable postsurgery PSA, Ki-67 dropped out and EZH2, MCM7, and PSA were prognostic. In Gleason, less than 7 patients, Ki-67 was the only significant factor; the 15 patients with Ki-67 staining of >1% had a 5- and 10-year disease-free survival of 70% and 45%, respectively (from the graph), compared to 100% for Ki-67 of 0-1%. No details of interaction with pathologic variables were given.Table 1
Ki-67 and outcomes after radical prostatectomy. The table indicates whether Ki-67 was positive on univariate or multivariate analysis for predicting failure. The failure of the entire cohort is given and then the outcomes for patients where Ki-67 was elevated versus not elevated.
Study#ptsMed (mean) months f/uInclude LN+ (#)Include Adj RX (#)Definition of failure@Univariate positiveMultivariate positiveGroup overall failureMarker elevated outcomeMarker not elevated outcomeKhatami et al. [6]50(63)NoNRPSA > 0.2 × 2YesNR18%NRNRBubendorf et al. [7]137(64)Yes (34)Yes (60)PSA, PAP, or ALP elevated*YesYes29%65% 5-yr dfs78% 5-yr dfsMay et al. [8]52846 (49)Yes (38)NoPSA > 0.2YesYes19% 5-yr dfs 78%70% 5-yr dfs88% 5-yr dfsMiyake et al. [9]19363Yes (13)NoPSA > 0.2YesYes21% 5-yr dfs 79%A: 79% recurB: 20% recurC: 4% recurRubio et al. [10]9146.5NRNoPSA ≥0.2YesYes32%42% 5-yr dfs84% 5-yr dfsLaitinen et al. [11]22966 (62)Yes (NR)Yes (4)PSA ≥ 0.5 × 2YesYes63% 5-yr dfs10-yr 41%5/10-yr dfs 2–15% : 62%/38% 16+% : 42%/27%5/10-yr dfs0-1% : 92%/65%Moul et al. [4]162(54)Yes (1)NRPSA > 0.2 × 2YesNo38%31% 6-yr dfs72% 6-yr dfsBettencort et al. [12] (same patients as [4] above)180(53)Yes (1)NRPSA > 0.2 × 2YesNo60% 5-yr dfs5-yr dfs1+ 69% 2–4+ 44%5-yr dfs83%Vis et al. [15]112113Yes (6)NoClinical only@Yes for clinical recurrenceNoClinical dfs 5-yr 52% 10-yr 42%Clinical dfs5-yr 75%10-yr 75%NR: not reported.@Most studies include biopsy-proven local recurrence and radiographic distant metastasis as failure in addition to PSA.*Three factors: Ki-67, SV+, margin+; A = 2-3 factors, B = one factor, C = all 3 negative.Even though those studies showed on multivariate analysis Ki-67 was able to predict failure, other than the correlation shown in the Miyake et al. study [9], none of the studies evaluated as to how Ki-67 improved the predictive ability of the standard prognostic factors. Therefore, its utility remains uncertain, which is further compounded by the studies that show that Ki-67 is not predictive for failure. In that regard, in a study of 162 patients undergoing RRP (median followup 4.5 years, PSA failure > 0.2 ng/mL at least twice), Ki-67 staining was measured <2 in 62% of the tumors and 2–4 in 38% [4]. On multivariate analysis including pathology stage, race, Gleason score, age, p53, bcl2, and Ki-67 (MIB-1) levels, p53 and bcl-2 were prognostic, but not Ki-67. The findings were confirmed in another study of the same patients [12]. From the cohort of 335 patients, this time 180 had available tissue. With a mean followup 4.4 years, and failure defined as PSA > 0.2 ng/mL twice, the overall 5-yr biochemical failure-free survival (BFFS) was 60%. Ninety per cent had measurable Ki-67 (MIB-1) staining. In 18 patients with negative or rare Ki-67 staining, 3 (5%) progressed for an 83% 5-year biochemical-free survival (BFFS); of 90 that stained 1+, 23 (37%) progressed for a 69% 5-year BFFS; and in 72 that were 2–4+, 36 (58%) progressed with a 5-yr BFFS of 44%. On multivariate analysis, stage and Gleason score were significant prognostic factors and Ki-67 was only marginal. In a subgroup analysis, Ki-67 appeared to differentiate failure in Gleason 2–6 patients, but not in higher grade. A third paper including at least some of the same patients (132) [13] showed Ki-67 positive patients had a higher recurrence rate but again the findings were not significant on multivariate analysis. In a different approach [14], 41 prostatectomy patients who failed within two years (PSA > 0.2 ng/mL) were matched for pathologic stage, PSA, and Gleason score with 41 patients who did not have a rising PSA by three years. They found no difference in Ki-67, p53, and bcl-2 between the two groups. Finally, in an evaluation of 112 prostatectomy patients [15], for patients with low MIB-1 staining, the 5- and 10-year clinical disease-free survival was 75% for both, and for high staining patients was 52 and 42%, respectively. In spite of this difference, MIB-1 was not predictive of recurrence or death on multivariate analysis.
## 3.2. Apoptosis-Related Markers (p53, bcl-2, and MDM2)
Cellular stress triggers (upregulates) p53, which accumulates in cells and leads to either cell cycle pause and repair or apoptosis. Loss of p53 function potentially can allow a cell that would normally undergo apoptosis to survive an otherwise lethal event. Bcl-2 is antiapoptotic and elevated levels can also conceptually allow cells to survive an otherwise lethal event. Mouse double minute-2 (MDM2) has an antiapoptotic effect by binding to p53 and inactivating it. Wild-type or normal p53 is cleared rapidly from cells, so measurable p53 is usually dysfunctional. Therefore, counter-intuitively, an elevated p53 actually represents decreased p53 function.As with Ki-67, there are several positive and negative studies (Table2). In 71 patients operated on before 1984 [16] with a median followup of 10.6 years, 15-year cause-specific survival for p53 positive patients was 38% and for p53 negative patients was 87%. They also found that the 15-year cause-specific survival for retinoblastoma protein (Rb) positive patients was 66% and Rb negative was 92%. On multivariate analysis, the combination of p53 and Rb was the strongest predictor of failure. There was no analysis with the common prognostic factors (stage, PSA, or Gleason score). A later study in 76 RRP patients with a median followup of 50 months found that 27% of the patients with <40% positive p53 staining recurred versus 6/10 (60%) with more than 40% staining [17]. On univariate analysis, nuclear grade, pathologic stage, and p53 were significant, but on multivariate analysis, only p53 was significant. In another prostatectomy study, 263 patients had a mean followup of 55 months and 39% failed [18]. Seventy-eight received adjuvant treatment. They found clustering of p53 positive cells (>12 cells) to be more predictive than percentage of positive cells. On multivariate analysis, both clustering and percentage p53 positive, along with PSA, path stage, Gleason score, and lymph node positivity were predictive for failure.Table 2
p53, bcl-2, and outcomes after radical prostatectomy. The table indicates whether p53 and bcl-2 was positive on univariate or multivariate analysis for predicting failure. The failure of the entire cohort is given and then the outcomes for patients where the marker was elevated versus not elevated.
Study#ptsMed (mean) months f/uInclude LN+ (n)Include Adj RX (n)Definition of failure@Univariate positiveMultivariate positiveGroup overall failureMarker elevated outcomeMarker not elevated outcomeP53Theodorescu et al. [16]71127Yes (1)NoClinical,PSA > 0.2YesYes51% failed15-yr cause-specific 38%15-yr cause-specific 87%Kuczyk et al. [17]7650Yes (6)NoClinicalYesYes32% failed20% died ca33% died ca16% died caQuinn et al. [18]263(56)Yes (5)Yes (99)PSA ≥ 0.4 × 2YesYes39% failed32% 5-yr dfs83% 5-yr dfsMoul et al. [4]162(54)Yes (1)NRPSA > 0.2 × 2YesYes38%39% 6-yr dfs76% 6-yr dfsBauer et al. [19] same patients as [4]175(55)Yes (1)NRPSA > 0.2 × 2YesYes38%45% failed5-yr dfs 49%23% failed5-yr dfs 78%Brewster et al. [20]76(38)NRNoPSA ≥ 0.2 × 2YesYes30%41% failed21% failedGoto et al. [21]11940NRNoPSA > 0.2NoNo13% failed40% failed10% failedMiyake et al. [9]19363Yes (13)NoPSA > 0.2YesNo21% failed5-yr dfs 79%NRNRWu et al. [23]7036.5NRNRPSA > 0.2 × 2NoNo30%44% failed26% failedOsman et al. [24]8665NRYes (33)3 × PSA increaseNRYesNR0 5-yr dfs68% 5-yr dfsBCL-2Bauer et al. [19]175(55)Yes (1)NRPSA > 0.2 × 2YesYes38% failed57% failed5-yr dfs 33%31% failed5-yr dfs 69%38% failedBCL2+ P53+5-yr dfs 25%BCL2− P53−5-yr dfs 80%Brewster et al. [20]76(38)NRNoPSA> 0.2 × 2YesYes30%53% failed24% failedGoto et al. [21]11940NRNoPSA > 0.2NoNo13% failed21% failed10% failedBubendorf et al. [22]137(64)Yes (34)Yes (60)PSA, PAP, ALKPNRNo19% failed5 yr dfs 78%10-yr dfs 18%10-yr dfs 52%Miyake et al. [9]19363Yes (13)NoPSA > 0.2NoNo21% failedNRNRWu et al. [23]7036.5NRNRPSA > 0.2 × 2YesYes30%67% failed28% failedNR: not reported.Most studies include clinical failure: biopsy-proven local recurrence and/or radiographic distant metastasis in addition to PSA.Several studies have considered p53 in conjunction with other factors such as bcl-2, and Ki-67. In one study consisting of 162 patients undergoing RRP (median followup 4.5 years, PSA failure > 0.2 ng/mL at least twice) p53 was measured negative in 31% of the tumors and positive (1–4+) in 69%. Bcl-2 was measured negative in 73% of the tumors and positive (1–4+) in 27% [4]. On multivariate analysis including pathology stage, race, Gleason score, age, p53, bcl-2, and Ki-67 (MIB-1) levels, p53 and bcl-2 were prognostic. There was no correlation as to what the markers added to the common prognostic markers. In another study from the same patient cohort, 175 patients underwent radical prostatectomy [19]. With a mean followup of 4.6 years, p53 staining was positive in 65% and the 5-year failure rate was 51%, compared to 22% for the patients that stained negative. Bcl-2 staining was positive in 27% and the 5-year failure rate was 67%, compared to 31% for the patients that stained negative. For patients that were both p53 and bcl-2 positive, the five-year failure rate was 75% compared to 20% for those that were negative for both. On multivariate analysis, stage, race, bcl-2, and p53 were all prognostic. Again, there was no indication of whether they enhanced the standard markers. Interestingly, in yet another analysis of some of the same patient cohort (132 patients) with median followup of 3.9 years, p53 positive patients had a higher recurrence rate but it was not significant on multivariate analysis [12]. Another study of p53 and bcl-2 looked at 76 prostatectomy patients with a mean followup of 38 months, 23 (30%) of whom failed [20]. Fifty-seven percent were p53 positive on prostatectomy tissue and 41% failed compared to 21% with normal p53. Twenty percent were bcl-2 aberrant on prostatectomy tissue and 53% failed compared to 24% of those with normal bcl-2. In an additional study of 119 radical prostatectomy patients receiving no neoadjuvant treatment and with a median followup of 3.3 years, 16 (13%) failed [21]. On multivariate analysis, bcl-2, p53, Ki-67, PSA, Gleason score, Capsular penetration, age, and margin positivity were not predictive, but SV involvement and caveolin-1 (see below) were.In an older cohort of patients (22% of the failures predated PSA), 30 received adjuvant treatment (mostly radiation) [22]. With a mean followup of 5.2 years, bcl-2 positivity was predictive of recurrence, but only stage pT3 and Ki-67 were predictive of failure (not p53). From the graph, for elevated bcl-2, 10-year disease-free survival was 18% and for nonelevated bcl-2 was 52%. Only 8% overexpressed p53. Like p53, it is also not uncommon for bcl-2 staining to be too low (<5%) to be meaningful [10].Miyake et al. evaluated 193 prostatectomy patients with twelve markers on IHC, including p53 [9]. While it was predictive on univariate analysis, it was not on multivariate. Bcl-2 was not predictive for either. In a study of 70 pathological T2 patients [23] with a median followup of 36.5 months, 30% suffered biochemical relapse (PSA > 0.2 ng/mL times two), sixteen patients were p53 positive, and 44% suffered PSA relapse which was not significantly different than the p53 negative patients (26% relapse). Only 3 (4%) patients were bcl-2 positive, but 2 (67%) relapsed, which was significantly higher than the bcl-2 negative patients (28% failure). Finally, in a study [24] of 86 patients (median followup 65 months) with an undetectable PSA after radical prostatectomy (38% received neoadjuvant treatment), 20% overexpressed p53 and had a higher risk of relapse. The 33% that overexpressed MDM2 also had a higher risk of relapse. No details were given, but on multivariate analysis, both p53 and p21 were predictive. Stage and MDM2 were not. Interestingly, there was no association with p53 overexpression and p21 or MDM2. As with all the studies discussed, there was no real analysis for correlation with standard predictive factors, so the real predictive power of these markers remains elusive.
## 3.3. E-Cadherin and Other Adhesion Molecules
Calcium-dependent adhesion molecules (cadherins) are transmembrane proteins that play a role in cell adhesion. E-cadherin is a subtype found in epithelial tissue with extracellular, transmembrane, and intracellular domains. The intracellular domain binds to beta catenin. In cancer, E-cadherin downregulation theoretically reduces cell adhesion resulting in increased cell motility and dissemination.In a study of 70 pathological T2 patients [23] with a median followup of 36.5 months, 30% suffered biochemical relapse (PSA > 0.2 ng/mL times two). Thirty-nine patients (56%) had aberrant E-cadherin staining, with a 44% PSA relapse rate, which was significantly worse than those with normal E-cadherin staining (13% recurrence). In 104 prostatectomy patients [25] (7 lymph node positive), low E-cadherin, Gleason score, and pathologic stage were predictive of biochemical failure (PSA > 0.5 ng/mL) on multivariate analysis. For clinical failure, pathological stage dropped out and elevated N-cadherin was significant. For patients with low E-cadherin, the 10-year biochemical failure-free survival was 14%, versus 33% for those with elevated levels. For N-cadherin, low levels resulted in 33% biochemical failure-free survival and high levels 14%. They found that the E-cadherin to N-cadherin ratio was more powerful than either alone, but did not provide specifics nor any details on the modification of the predictive power of standard factors. In a study of 67 radical prostatectomy patients [26] with a median followup of 54 months, 27 (40%) recurred clinically, 7 locally, and 20 systemically. When evaluated with IHC for E-cadherin, a cut point of 40% staining was chosen. For the 13 that stained less than 40%, 2 (15%) died of cancer and for the 54 that stained >40%, 14 (26%) died of cancer, but the difference was nonsignificant. E-cadherin was not predictive on univariate or multivariate analysis for either recurrence or survival. In 128 radical prostatectomy patients [27] without adjuvant treatment, tissue microarrays were made and stained with IHC staining. Normal was considered >70% staining. For nonmetastatic prostate cancer, 18% had aberrant staining. With a median followup of 23 months, 38% of the failures and 20% of the nonfailures had aberrant staining, a nonsignificant difference. Similarly, in a microarray study (discussed below), Rhodes et al. [28] found that a decreased E-cadherin to EZH2 ratio resulted in an increased rate of biochemical failure after radical prostatectomy.Brewster et al. [20] studied 76 prostatectomy patients; 49% were E-cadherin aberrant on prostatectomy tissue and 37% failed compared to 22% with normal E-cadherin. On multivariate analysis, it was not predictive when considered with p53, bcl-2, Gleason score, and margins. They also evaluated another apparent adhesion molecule in the form of the cell surface glycoprotein CD44. Sixty-four percent were CD44 minimal or absent on prostatectomy tissue. Of those with normal staining, 8% failed compared to 43% with aberrant staining. On multivariate analysis, it was not predictive when considered with p53, bcl-2, Gleason score, and margins. Two other studies evaluated CD44. In 97 radical prostatectomy patients [29] with median followup of 84 months, utilizing PSA of >1.0 as failure, most (86%) patients were positive for CD44, so risk was determined by graded intensity of the staining. Decreased expression increased the risk of failure. On univariate analysis, loss of CD44 and cd4v6 were predictive of clinical failure, but only CD44 was predictive for biochemical failure. In the other study, 99 patients had mean followup of 40 months and 26% suffered a biochemical recurrence [30]. CD44 was evaluated via an intensity and percent staining score, and 47% were downregulated. The 3-year recurrence-free survival was 77% for the nondown-regulated patients versus 48% for those with CD44 downregulation. It was not a significant predictor on multivariate analysis, when considered with p34.In none of these studies was there an assessment of how it modified the predictive ability of the standard prognostic factors.
## 3.4. EZH2
The Enhancer of Zeste 2 (EZH2) gene codes for polycomb group proteins that effect chromatin and silence genes. When overexpressed, it appears to be associated with tumorigenesis. In a study involving multiple cancers [31], 104 radical prostatectomy patients with a median followup of 104 months were evaluated with staining for EZH2. For low EZH2 staining, the 5- and 10-year cause-specific survival was 99% and 93%, respectively. For the high staining group, it was 89% and 53%, respectively. On univariate analysis, upper quartile EZH2 staining was predictive for clinical recurrence and on multivariate analysis was predictive for distant metastasis and death. In another study of 64 patients [32], tissue was stained for EZH2 and if the intensity was ≥3, 10/32 (31%) failed versus 3/32 (9%) if the staining was <3. It was a significant factor on multivariate analysis along with margin status, tumor size, Gleason score, and PSA. Finally, in a study (see Ki-67 above) [11] of 249 prostatectomy patients, five- and 10-year disease-free survival was 63% and 41%, respectively. On multivariate analysis, pathologic stage, Ki-67 and MCM7 were significant predictive factors (EZH2 was not). In patients that were lymph node negative with an undetectable postsurgery EZH2, MCM7 and PSA were prognostic. In Gleason less than 7 patients, Ki-67 was the only significant factor. There was no evaluation of whether this added to the predictive ability of standard factors.
## 3.5. Cyclin-Dependent Kinases (and Their Effectors)
Cyclin dependent kinases (CDKs) are protein kinases involved in the regulation of the cell’s progression though the cell cycle. As most cancers have dysfunctional cell cycle control, the kinases are implicated as part of the aberrancy. Cyclin D1 is specific for transition through G1/S. It has its effect by binding with cyclin dependent kinases 4 and 6 forming a complex that phosphorylates and inactivates the retinoblastoma protein (Rb). Overexpression of cyclin D1 has been associated with the malignant phenotype and its progression. There are several known inhibitors of cyclin dependent kinases. For example, p16INK4a (cyclin-dependent kinase inhibitor 2A) inactivates Cdk4 and CdK6 and thereby acts as a tumor suppressor (by blocking the phosphorylation of the Rb gene, which prevents transit through G1). Loss of p16 enables abnormal progression through the cell cycle, increasing the malignant potential. P21-waf1 encodes a cyclin dependent kinase inhibitor (p21 or cyclin dependent kinase inhibitor 1A), inhibiting CDKs 2 and 4, which leads to arrest at G1. It is induced by p53 (thus elevated p53 can lead to arrest at G1 through this route). P27Kip1 (cyclin dependent kinase inhibitor 1B) is also involved in G1 arrest by inhibiting cyclin dependent Cdk2 complexes E and A and D-Cdk4. Therefore, a decrease in p27 should result in increased proliferation. Lastly, p34cdc2 (cell division control protein 2) is a component that forms a kinase by binding with cyclin B1 (forming maturation-promoting factor (MPF)) that regulates G2/M transition and promotes mitosis).In a study [24] of 86 patients with an undetectable PSA after radical prostatectomy (38% received neoadjuvant treatment), 33% overexpressed p21Cip, and this was associated with a higher risk of relapse. No details were given, but on multivariate analysis, both p53 and p21 were predictive of relapse whereas stage and MDM2 were not.In one study, where the primary goal was to assess the association between pathological features and biomarker expression [33], p27Kip expression was evaluated in 113 prostatectomy specimens (median followup 4.6 years, 21% neoadjuvant androgen ablation), and correlated with outcome. Low p27 nuclear staining was a poor prognostic sign. On multivariate analysis, p27, seminal vesicle status and margin status were all predictive for recurrence, but no details were given. In a second study of 96 stage C lymph node negative patients undergoing radical prostatectomy with a median followup of 9.5 years [34], p27 Kip1 staining correlated with Gleason score (higher grades had decreased levels). The 9-year recurrence-free survival for levels ≤10% was 17%, for levels 11–50% was 47%, and for >50% was 67%. There was no correlation with the standard factors. In a third p27 study [35] of 86 patients (after excluding those that received adjuvant treatment), multivariate analysis demonstrated only pathologic stage and p27 to be predictive at a median followup of 40 months. High Gleason score was associated with low p27 staining. Thirty percent was the breakpoint between high and low staining. Fifty percent of patients with low staining failed (PSA > 0.4) and 78% with high staining failed. In another study with 95 patients [36], loss of p27 (<10%) on multivariate analysis was significant for recurrence, but not for survival. With a median followup of 49 months, 33% of the p27 negative patients failed versus 23% for the p27 positive patients (median followup 59 months). Another study was of 161 prostatectomy patients [37], which were divided into organ confined (n=76, median followup 42 months) and nonorgan confined (n=85, median followup 38 months) patients. p27 staining was performed on the biopsy, but not the final pathology specimen, and patients were not evaluated for the specific impact of positive margins, seminal vesicle involvement, or lymph node involvement. For the organ-confined patients, the 5-year recurrence rate was 26%, but 9% for those with high p27 staining and 37% with low (<45%) staining. In this subgroup, p27 was predictive for failure. In the nonorgan confined patients, the recurrence rate was 44%, but p27 was not predictive of failure in these more advanced patients and the actual effect on failure was not stated. In an evaluation [15] of 112 prostatectomy patients, 92 had adequate p27 staining. Thirty-five (38%) stained less than 50% and were classified as low staining. Based on clinical parameters, their 5- and 10-year disease-free survival were 37% and 26%, respectively. For the high staining patients, it was 79% and 77%, respectively. p27 predicted for clinical recurrence and cause-specific survival.Finally, in a study of 104 radical prostatectomy patients with a median followup of 56 months [38], p27 was determined by the per cent of nuclei staining, with the median of 64% used as the breakpoint between high and low. On multivariate analysis, pathologic stage and PSA were significant predictors of recurrence, but not p27.p16 has been evaluated in several studies. In 206 radical prostatectomy patients (18% with neoadjuvant androgen ablation) with a median followup of 72 months, one group [39] found positive p16INK4a staining to be associated with recurrence. On multivariate analysis, p16, PSA, Gleason score, and margin status were all predictive, but no actual outcome data was given. In another study [40], 88 prostatectomy patients (39% neoadjuvant treatment) with a median followup of 65 months stained for P16. Unlike Henshall et al. [39] (which called low <1%), their breakpoint was 5% positive nuclear staining. For the 38 patients that overexpressed, 21 (55%) failed versus 26% of the 50 under expressing patients. p16 was associated with PSA levels and was not an independent prognostic factor on multivariate analysis. They also did not report specifics on outcome. In a third study of 104 radical prostatectomy patients with a median followup of 56 months [41] the multivariate analysis for survival was positive for p16, age, grade, capsular penetration, and seminal vesicle involvement. They scored p16 by a fluorescence index. The low group had a 5-year survival of 78% versus 43% for the intermediate group (P=.005) and 42% for the high index group. There was no outcome data accounting for the standard factors. Ploidy or S phase was not predictive.In analysis of cyclin D1 and p34cdc2, 140 patients [42] with a median followup of 42 months were evaluated. Failure was defined as a PSA > 0.4. In patients that were p34cdc2 negative, 10% failed versus 26% that were positive. For Gleason 7 or greater, the failure rate was 26% for p34cdc2 negative and 38% for positive. On multivariate analysis, only p34cdc2 and Gleason score were predictive and cyclin D1 and ploidy were not. p34 was also evaluated in a study of 99 patients. With a mean followup of 40 months, 26% suffered a biochemical recurrence [30]. p34 was evaluated via an intensity and percent staining score and 61% were determined to have overexpressed p34. The 4-year recurrence-free survival (from the curves) was 98% for the nonover expressed patients versus 47% for those over expressing p34. It was a significant predictor on multivariate analysis, but there was no evaluation of whether it enhanced the predictive ability of standard factors.
## 3.6. Cathepsin-D
Cathepsins are proteases (i.e., involved in protein degradation) usually housed in lysosomes that proteolyse proteins that regulate cell growth. In a study [43], 105 radical prostatectomy patients were evaluated for cathepsin D. It was not prognostic on either univariate or multivariate analysis, but probably because the expression rate was extremely high at 98%.
## 3.7. Chondroitin Sulfate
Chondroitin sulfate is a structural glycosaminoglycan of the extracellular matrix that helps regulate cell activity. Ricciardelli et al. [44] studied 157 prostatectomy patients after exclusion of adjuvant and neoadjuvant treatment; failure was defined as a PSA > 0.2 and median followup was 47 months. They used an antibody to chondroitin sulfate and read the slides via an image capture technique with automated analysis. There was a twofold difference between this study and previous studies for the absolute value of the mean due to calibration differences, which demonstrates the lack of uniformity in these studies. The median was chosen as the cut point, although the most robust point was slightly above that. On multivariate analysis, chondroitin sulfate, Gleason score, preoperative PSA, and pathological stage were all predictive. For patients with low staining, 23% failed for a 5-year PSA failure rate of 33% versus 51% with high staining failing for a 5-year failure rate of 51%. There was some correlative analysis between chondroitin staining and other predictive factors. For patients with a preoperative PSA less than 10, 9% with low chondroitin sulfate staining failed versus 48% with high levels. In a more specific analysis, the five-year failure rate for Gleason 5–7 patients with low chondroitin levels and low PSA was 11% compared to 44% for low chondroitin staining patients with a high PSA. Further, Gleason 5–7 patients with high chondroitin sulfate staining and low PSA had a five-year failure rate of 56% versus 72% for high staining and high PSA. There was no evaluation done with the integration of pathology findings.
## 3.8. Hepsin and PIM1
Hepsin is a transmembrane serine protease whose exact function is unknown, but when upregulated appears to express a malignant phenotype. PIM1 encodes a protein kinase that promotes G1/S transition by upregulation of CDK2, facilitating cell proliferation and survival. One study [45] utilized human specimens and cell lines for comparison of malignant and benign tissue. Out of several hundred candidate genes, hepsin and PIM1 expression proteins were selected for further analysis. Hepsin was increased in malignant prostate tissue versus benign, but staining was greatest in PIN. In radical prostatectomy patients, low or absent hepsin increased failure. On multivariate analysis, both hepsin and Gleason score were predictive of failure. They also tested for PIM1. It was upregulated in prostate cancer and decreased levels were associated with increased PSA level in 135 patients with localized prostate cancer. It was significant on multivariate along with Gleason score 4-5 and PSA. They concluded that lower PIM1 levels were strongly associated with an increased risk of relapse. There was no outcome correlation with standard factors with either marker.
## 3.9. Cox-2
In a study of 91 prostatectomy patients [10], with a median followup of 46.5 months, 29 (32%) progressed (PSA > 0.2 ng/mL). A score was developed for percent and intensity of staining for Cox-2. For no staining, the failure rate was 26% versus 60% for 1–4, but then dropped back to 15% for 5–12. While it was a predictive marker on univariate analysis, it was not on multivariate.
## 3.10. Laminin Receptor (Ribosomal Protein SA)
Laminins are glycoproteins located in the basement membrane (basal lamina) that affect cell adhesion and migration as well as differentiation and survival. Laminin receptor (LR) is detected via the MLuC5 antibody. In an initial evaluation [46] in 140 patients, it appears that laminin receptor positivity might be associated with recurrence. Overall, the 3-year biochemical failure-free survival was 68%, but for LR positive patients the failure was 45% and for negative patients it was 7%. There was no correlation with PSA and Gleason score. The followup was only 20 months, and a later paper [47] showed that LR measurement of the biopsy tissue was not significantly predictive for biochemical progression, probably due to a lack of concordance between the measurements in biopsy tissue versus the larger tumor specimen.
## 3.11. Chromogranin A (CGA)
In a study of 528 prostatectomy patients [8] excluding neoadjuvant and adjuvant androgen ablation and radiation therapy, with a median followup of 46 months, 101 (19%) failed for a 5-year disease-free (PSA < 0.2 ng/mL) rate of 78%. The tissue was evaluated using IHC staining for Ki-67 and chromogranin A (CGA). On multivariate analysis, Gleason score > 4 + 3, CGA positive, lymph node positive, PSA >20 ng/mL, and Ki-67 were prognostic, while pathologic stage T3 and margin positivity were not. For the 32 CGA positive patients, the 5-year biochemical recurrence-free survival was 48% and for the 496 CGA negative it was 80%. Because of the small number of CGA positive patients, the only specific information was given on whether there was modification of prognosis of the standard factors was for Gleason <7 patients, where for the 304 CGA negative patients, 8% failed and for the 12 CGA positive, 25%.
## 3.12. Minichromosomal Maintenance Protein 7 (MCM7)
Minichromosome maintenance protein 7 (MCM7) appears to be a facilitator of DNA replication, so upregulation would be expected to increase proliferation. It has been found on microarray analyses that MCM7 is frequently amplified in prostate cancer. In an evaluation of prostatectomy patients [48], 52/68 (77%) with MCM7 amplification relapsed versus 7/57 (12%) without amplification. In a study discussed above (see Ki-67) [11], pathologic stage, Ki-67, and MCM7 were significant predictive factors. In evaluation of patients that were lymph node negative with an undetectable postsurgery, EZH2, MCM7, and PSA were prognostic. In both studies, there was no clinical correlation, so these interesting findings are of uncertain significance.
## 3.13. Histones
Histones are intranuclear proteins in chromatin around which DNA is “wound”, the modification of which influences their interaction with the DNA and affects some processes such as mitosis and gene regulation. In 183 radical prostatectomy patients, those that received androgen ablation were excluded. The median followup was 60 months and failure was defined as PSA > 0.2 ng/mL [49]. In order to evaluate sites on histones H3 and H4 with acetylation and dimethylation staining, 5 different sites were identified by using a clustering algorithm. While not independently predictive, when combined with Gleason score, the findings yielded prognostic information. From the graph, Gleason < 7 patients that were histone “favorable” had an 84% disease-free survival, while those unfavorable had a 58% disease-free survival. For Gleason 7–10, the favorable group had a disease-free survival of 46% versus 20% for the unfavorable.
## 3.14. TMPRSS2 : ERG Fusion
TMPRSS2 (transmembrane protease, serine 2) is an androgen-regulated gene found on chromosome 21 that encodes a transmembrane protease. In prostate cancer, it can be fused with genes for the ETS transcription factors, such as ERG (resulting in TMPRSS2 : ERG). This indirectly places ERG under androgen transcriptional control. There are multiple variants of this fusion. This can be detected through either RT-PCR or fluorescence in situ hybridization (FISH). In 165 prostatectomy patients with available frozen tissue [50] with a median followup of 20 months, tissue was evaluated for TMPRSS2 : ERG fusion gene and 49% was positive. For the fusion gene positive patients, 46% failed compared to 7% in fusion negative patients. On multivariate analysis, the fusion gene was the most predictive factor, followed by grade. Evaluation was made for different Gleason and pathologic findings. For Gleason 5-6 patients, 33% of the gene positive patients failed, versus 5% for the gene negative. For Gleason 7 and Gleason 8–10, it was 48% versus 7% and 75% versus 14%, respectively. For organ-confined patients, gene positive patients had a recurrence rate of 34% versus 10% for gene negative. For extraprostatic extension and seminal vesicle positive patients, it was 53% versus 3% and 67% versus 34%, respectively. For both Gleason score and pathological findings, all the differences were statistically significant, except for the seminal vesicle involved patients. Another study, started with 248 radical prostatectomy patients [51], but only 150 were ultimately evaluable by FISH. Of those, 50 (33%) were found to have TMPRSS2 : ERG rearrangement. With a median followup of 66 months and failure defined as two rises of PSA > 0.5 ng/mL, on multivariate analysis, Ki-67, pathologic stage, and TMPRSS2 : ERG fusion were significant, not Gleason score or PSA [52]. Yoshimoto et al. evaluated specimens from 125 radical prostatectomy patients, 122 of which had clinical followup and with a median followup, 49% had failed (PSA > 0.2 ng/mL). Neoadjuvant androgen ablation was allowed, and 2 patients were lymph node positive. FISH was used to evaluate for TMPRSS2 : ERG, and 48% were found to have rearrangements resulting in a 5-year biochemical failure-free survival (BFFS) of 46%. For those that were negative, 5-yr BFFS was 62% (P=.0523). Expanding on their previous work, they also evaluated for PTEN deletion by FISH. Only 82 of the 125 patients could be evaluated. There was no difference in 5-yr BFFS between those that were deletion negative and positive, but if they divided the deleted patients into hemizygous and homozygous deletions, they found that all the homozygous patients had failed by 5 years. If patients had both the PTEN deletion and the TMPRSS2 : ERG fusion, 5-yr BFFS was 30% versus 59% if they had neither (P=.001). They did not test to see whether these markers augmented the predictive ability of the three standard factors (Stage, Gleason score, or PSA), although on multivariate analysis only Gleason score, the TMPRSS2 : ERG/PTEN combination and homozygous PTEN deletion were prognostically significant. A study [53] using microarray to compare genes between benign and malignant cells found that ERG was the most commonly over expressed. Then utilizing QRT-PCR, they analyzed 114 prostate cancer patients and found ERG1 over expressed in 62%. Ninety-five patients had detectable levels and for a >100 over expression, the 5-year biochemical failure free-survival (from the graph) was 88%, for 2–100 fold 80% and for <2 fold 36%. On multivariate analysis, ERG1 (>100 versus <2) and Gleason (8–10) were significant, but not race, PSA, pathologic stage, margin positive, or seminal vesicle positivity.Not all studies found TMPRSS2 : ERG to be prognostic. In one study [54], two subgroups were taken from larger prospective studies and ultimate outcome collected from SEER data. This yielded no failure data and only crude followup of cancer-specific survival. Of the subgroups, only 57% could be scored for the fusion. They reported no association between the occurrence of TMPRSS2 : ERG (positive in 36% of the patients) and cancer specific survival. Researchers in a study [55] of 521 radical prostatectomy patients with 95 month median followup utilized FISH and found 42% had TMPRSS2 : ERG abnormalities. It was not associated with recurrence, metastasis or death. Finally, in a study of 54 patients [56], 35 (65%) had gene rearrangement, which was present in 60% of the nonfailing patients and 65% of the failing patients. In the evaluation of 28 benign prostate tissues, there were no rearrangements.
## 3.15. PTEN
The phosphatase and tensin homologue (PTEN) gene modulates the phosphotidylinositol 3-kinase (PI3K) pathway, a regulator of the Akt pathway. Lack of PTEN allows for upregulation of Akt and other cell cycle factors, increasing cell survival. As noted above [52] in the TMPRSS2 : ERG discussion, on multivariate analysis, homozygous PTEN deletion and the TMPRSS2 : ERG fusion were prognostically significant. In an earlier study specifically evaluating PTEN, the same authors [57] utilized fluorescence in situ hybridization (FISH) to PTEN in 107 prostatectomy patients. Tissue was scored as showing no deletions (56%), hemizygous deletions (39%), or homozygous deletions (5%). On Cox proportion hazard analysis, for univariate analysis, perineural invasion, seminal vesicle positive (SV+), extraprostatic extension (EPE), Gleason score, PSA, lymph node positivity, and PTEN deletion were all predictive. On multivariate analysis, only EPE, SV+, and PTEN were predictive. For PTEN, from the graph, 5-year PSA (>0.2 ng/mL) failure-free survival was 0 for the 5 homozygous patients, 48% for the 42 hemizygous patients, and 60% for the 60 patients without deletion. There was no discussion as to how PTEN modified the predictive ability of standard factors. In a separate study of 104 radical prostatectomy patients with a median followup of 56 months [38], PTEN was scored as an index based on percent staining and intensity. On multivariate analysis, pathologic stage and PSA were significant predictors of recurrence, but not PTEN.
## 3.16. Epidermal Growth Factor Receptors (EGFR)
Epidermal growth factors are extracellular ligands controlled by the cell surface epidermal growth factor receptors, which are tyrosine kinase receptors. When activated, they initiate a cascade of signal transduction (i.e., though the Akt pathway) that results in cell proliferation. If the receptor is mutated in the “on” position (i.e., over expression), the result could be uncontrolled proliferation. Her-2/neu (c-erb B2) encodes a tyrosine kinase growth factor receptor similar to the epidermal growth factor receptors and has been linked with advanced disease. In one study, [43] 105 radical prostatectomy patients were evaluated for epidermal growth factor receptor (EGFR). The expression rate was 48%, but it was not prognostic on either univariate or multivariate analysis. In 113 prostatectomy patients with a mean followup of 42 months [58], utilizing IHC, membranous and cytoplasmic staining was given a composite score so that ≥3 was considered positive. With that parameter, 29% of the tissue over expressed and there was no correlation with failure on univariate analysis. Utilizing FISH, it was found that 41% were amplified for Her2, but there was poor correlation with IHC staining (P=.25). While FISH analysis was significant for failure on univariate analysis, it was not a significant predictor of failure on multivariate analysis. In 99 patients with a mean followup of 40 months, 26% suffered a biochemical recurrence [30]. Her 2-neu was evaluated via FISH and 42% were found to be amplified. The 5-year recurrence-free survival was 75% for the nonamplified patients versus 47% for those with Her 2-neu amplification. It was not a significant predictor on multivariate analysis, when considered with p34.
## 3.17. VEGF
In a study of 193 prostatectomy patients [9], twelve markers were evaluated on IHC, including VEGF, but it was not predictive on univariate analysis.
## 3.18. Caveolins
Caveolins are cell membrane proteins involved in endocytosis resulting in invagination of the plasma membrane (caveolae). They appear to be involved in signal transduction with a role in homeostasis and tumorigenesis. Caveolins have been found to be both increased and decreased in cancer so their role is variable and uncertain. In radical prostatectomy patients selected for failing or not failing, 162 lymph node negative patients were identified. With immunohistochemical staining for caveolin 1, 22% were positive and five-year progression-free survival was 43% versus 68% for those that were negative. On multivariate analysis, caveolin 1, Gleason score, extracapsular extension, seminal vesicle involvement, and margin involvement were all predictive [59]. The same group later studied serum levels of caveolin 1. As noted above, in a study [21] of 119 radical prostatectomy patients on multivariate analysis only caveolin 1 staining and SV involvement were predictive on multivariate analysis, but bcl-2, p53, Ki-67, PSA, Gleason score, Capsular penetration, age, and margin positivity were not. For caveolin 1 positive patients, 9/32 (28%) failed versus 7/87 (8%) that were negative. In 232 prostatectomy patients that included lymph node positive and those that received salvage radiation therapy [60], with a median followup of 70 months, the 5-year biochemical-free survival rate was 80%. On multivariate analysis, only Gleason sum (not Caveolin 1 staining) was a significant predictor of failure. When limited to lower risk patients (n=177) with exclusion of lymph node positive, seminal vesicle positive, Gleason > 7, and extracapsular extension/margin positive, caveolin 1 was still not a significant predictor on multivariate analysis. They did find that in evaluating only the recurring patients, those that had caveolin 1 over expression did worse. In a similar study [61], 30% of 152 radical prostatectomy patients (including lymph node positive) stained positive for caveolin 1. It was not predictive on multivariate analysis (only seminal vesicle positivity, margin positivity, and PSA were), but when restricted to patients with organ-confined disease, it was the lone predictive factor. This is somewhat in contradistinction to the low risk patients noted in the study above.
## 3.19. Zinc-Alpha2-Glycoprotein (AZGP1)
Zinc-alpha2-glycoprotein (AZGP1) encodes for a protein historically thought to be involved in lipolysis and thought to have a role in the cachexia of cancer. From a series of 732 radical prostatectomy patients [62], 228 were analyzed. Forty-three percent failed with a PSA rise of ≥0.2 ng/mL. On IHC, tissue was scored as absent or weak versus strong AZGP1 staining. Twenty-nine percent stained weak. Although there were few events, it appears to be predictive of clinical recurrence and distant metastasis, but there was no evaluation as to modification of common prognostic factors. In a gene array study [63] discussed below, AZGP1 was predictive for nonrecurrence.
## 3.20. Alpha Methylacyl CoA Racemase (AMACR)
Alpha methylacyl CoA racemase (AMACR) is a catalytic enzyme (of fatty acids) that is frequently over expressed in prostate cancer, but levels are decreased in advanced cancers as compared to localized. In 204 radical prostatectomy patients [64], IHC was performed for AMACR expression proteins and regression analysis was used to correlate staining with PSA failure (>0.2 ng/mL). With visual scoring on a scale of 1–4, there was no correlation with failure, but with quantitative expression analysis, patients in the lower tertile were more likely to recur. For patients more than 1.11 standard deviations below the cut point, 37.5% failed versus 14.5% if they were above. This was significant on multivariate analysis along with PSA, Gleason score, and margin status, but there was no evaluation as to the actual effect on the prognostic ability of those factors.
## 3.21. Gene Arrays and Panels
With the use of gene expression micro arrays, the hope is that by screening a large number of genes, genes highly predictive of cancer recurrence could be identified. When using probe arrays, multiple genes can be identified that may predict for relapse. Several groups have evaluated this approach in predicting failure postprostatectomy. In a gene expression profile of 225 tumors with a median followup of 8 years [63], it was found that MUC1 was predictive of recurrence and AZGP1 was predictive of nonrecurrence. Both of these genes were predictive on multivariate analysis along with Gleason score, stage, and PSA. There were no actual outcome results given. A similar study [28] of 259 RRP patients with a median followup of 57 months searched also for markers using microarray assay. They found that the combination of EZH2 increased and ECAD decreased was most predictive of 5-year recurrence (38% versus 15% for those without that combination). On multivariate analysis, this ratio was significant along with PSA, margin status, and pathological stage, but not Gleason score. For organ-confined patients that were margin negative, those that were EZH2/ECAD elevated had a 27% recurrence rate, versus 10% for those that had a decreased ratio. They did not report on higher-risk patients. In a different study of 100 lymph node negative prostatectomy patients [65], with a median followup of 70 months an expression analysis of 12,625 transcripts identified 218 genes that were either up- or down regulated. Recurrence was defined as three rising PSA levels. The combination that predicted recurrence was deemed “poor markers”. For Gleason 6-7 cancers, the 5-year disease-free survival was 69%, but was 77% in the good marker group and 47% in the poor marker group. In Gleason 8-9 cancers, the 5-year disease-free survival rate was 26%, but was 67% with good markers and 0 with poor markers. On multivariate analysis, Gleason score and the gene expression markers were predictive of recurrence, but PSA and age were not. Using a postoperative nomogram [66] they identified poor risk patients by nomogram (undefined) who had a 28% 5-year disease-free survival, increasing 50% with good gene markers, but 19% with poor markers. In the nomogram predicted favorable group, 5-year disease-free survival was 81%, which was 87% with good markers and 59% with poor markers. The major limitation of the study is that there were only 21 patients in the training set and 79 patients in the validation set.Another approach is to pool multiple genes in order to try to produce a more powerful predictive model. This has been successful in breast cancer [67, 68]. With that approach [69], using a 70 gene set in it was possible to predict 27/29 “aggressive” and 27/32 “nonaggressive” cancers and predicted 16 of the 18 failures. Unfortunately, it appears only 61 patients were evaluated; there was no indication of how the findings related to standard prognostic factors. In a more comprehensive study [70] of 639 patients selected for systemic recurrence, biochemical (PSA) recurrence and nonrecurrence at 7 years, the groups were evaluated for genes that differed between them. Patients with adjuvant treatment were not excluded and failure was with a PSA > 0.2 and rising. The patients were divided into training and a validation set. Ultimately, a 17-gene panel was determined to be predictive. Clinical models based on Gleason score, and pathological stage (PSA and age were not informative) demonstrated a correlation (area under the curve) of 0.76 (0.74–0.78), while the probe set was 0.85 and the combination of the two was 0.87. They reported that the AUC for the validation set was lower. They compared their results to those of other gene array studies and found that all the other models performed better than the clinical model alone (0.74, ranging from 0.76–0.86), with their 17 gene probe being the highest. All the validation sets were lower than the training sets for these genes. In an exploratory study [71] of 72 prostatectomy patients with a median followup of 28 months, 24% relapsed. After scanning for 59,619 probe sets, over 200 genes could be identified that are associated either positively with relapse. In another exploratory study [72], tissue from 37 failing patients and 42 nonfailing patients was tested with a 22,283-gene probe microarray. The first goal was to see if the identified genes (ultimately 5–8 were used) could correctly identify the failing versus the nonfailing patients, which it did 75% of the time. When combined into a nomogram, the predictive rate increased to 89%. Given that nomograms are the most robust incorporation of the standard prognostic factors; this would represent an example of how molecular data can increase the ultimate ability to predict who will fail. Unfortunately, the number of patients evaluated was very small, so any conclusions are tentative at best. One last study took a different approach. Rather than do a blind probe for over- or under expressed genes, they [73] evaluated a pre-existing class of predictive genes like those successful in breast cancer [74]. Although the actual genes are variable, most of the predictive breast cancer genes fall under the general classification of cell cycle progression genes. In evaluation of that class of genes in a large prostatectomy cohort [73] (442 with tissue, median followup 9.5 years), a panel of 31 was tested for their ability to predict recurrence. Overall, 10-year progression-free survival was 64%. When evaluated for the standard findings of PSA, Gleason score, and pathologic findings, the patients could be divided into two groups based on these clinical factors. The low-risk group were patients with Gleason < 7, organ-confined disease, and PSA < 10 ng/mL (actually, PSA up to 30 ng/mL did not change the risk). Their 10-year risk of biochemical failure (PSA > 0.1 ng/mL) was 17%, but for those with a low CCP score, it was 4% and for a high CCP score it was 24%. For clinical high-risk patients (Gleason ≥ 7 and/or nonorgan confined and/or PSA > 30), 10-year biochemical failure was 61%, which was 51% for low CCP score, and 64% for high score. On multivariate analysis, they the CCP score was predictive of recurrence.It is interesting to note, as pointed out previously [71], using multigene predictive models, there is little overlap in the genes that are found to be significant in each of the models. This is postulated to be a factor of a large number of genes and a high signal-to-noise ratio associated with the prediction of biochemical recurrence. The challenge then is to determine which of these are true prognostic markers and which are otherwise just testing anomalies. It will take large comprehensive studies to determine this.
## 4. Conclusion
This paper covered those tissue markers that have been evaluated as prognostic factors in radical prostatectomy patients. These markers and multiple others have also been evaluated in patients with noncurative treatment and metastatic disease, as well as numerous tissue culture systems. There are undoubtedly many useful makers that will be identified, especially with the high volume analyses possible with the microarrays. At this time, none of them have been overwhelming in their prognostic ability nor do they have a value that mandates clinical use.The reason for the failure of molecular markers in consistently predicting outcome may partially be due to the variability between studies due to their methodological differences. Unfortunately, most studies are too small to comprehensively evaluate their ability to improve on the prognostic ability of the standard factors of PSA, Gleason score, and stage. Until that occurs, they will remain research curiosities.In terms of the pathway forward for a useful marker or signature in prostate cancer, we have many challenges. Our current classification of prostate cancer even at the very rudimentary molecular level is lacking. The estrogen, progesterone, and Her 2-neu receptor status of breast cancer has allowed stratification of a complex disease for clinical trials and as a paradigm for molecular signature generation. To date, this has not been possible in prostate cancer, although recent work suggests the imprinting of the TMPRSS2-ERG, PTEN, and androgen receptor configurational status may be suitable. Similarly, basic molecular predictors of outcome in the adjuvant, hormone-naïve, and castrate-resistant settings have been slow to develop in a disease that in its most aggressive form evolves over a decade. Finally, predictors of response to standard therapies have been difficult to characterize in the absence of a single dominant gene or the ability to subsegment the disease. To move forward, markers or gene signatures will need to have strong biological base, be linked to a therapeutic intervention and have enough strength to add to the formidable triad of stage, Gleason score, and serum PSA in prostate cancer.
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*Source: 290160-2011-04-14.xml* | 290160-2011-04-14_290160-2011-04-14.md | 121,793 | Using Molecular Markers to Help Predict Who Will Fail after Radical Prostatectomy | Gregory P. Swanson; David Quinn | Prostate Cancer
(2011) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2011/290160 | 290160-2011-04-14.xml | ---
## Abstract
Recent phase III trial data clearly demonstrate that adjuvant therapy can reduce recurrence and increase survival after prostatectomy for prostate cancer. There is great interest in being able to accurately predict who is at risk of failure to avoid treating those who may not benefit. The standard markers consisting of prostate specific antigen (PSA), Gleason score, and pathological stage are not very specific, so there is an unmet need for other markers to aid in prognostic stratification. Numerous studies have been conducted with various markers and more recently gene signatures, but it is unclear whether any of them are really useful. We conducted a comprehensive review of the literature to determine the current status of molecular markers in predicting outcome after radical prostatectomy.
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## Body
## 1. Introduction
Prostate specific antigen (PSA), stage (either clinical or pathological), and Gleason score are firmly established as prognostic indicators in prostate cancer. Individually and collectively, they predict for failure after radiation and surgery. The predictive value has been increased with more detailed information such as the addition of the detailed pathological findings of extraprostatic extension (EPE), positive margins, seminal vesicle involvement, and lymph node involvement. Various combinations of factors have been combined into tables, formulas, neural networks, and nomograms. While they are important tools in trying to predict failure, they are limited by the predictive ability of the factors themselves. For example, from a nomogram, a patient with a Gleason 7 (3 + 4) cancer with extraprostatic extension and positive margins, negative lymph nodes, negative seminal vesicles, and preoperative PSA of 8.2 ng/mL is predicted to have a 10-year recurrence rate of 20% [1]. Telling a patient that he has a 1 out of 5 chance of failing may or may not be reassuring. The absolute precision would be able to tell a patient whether he will fail (100%) or not (0%). The ultimate goal is to try to determine who will fail, not who may fail. The only way to try to approach that goal is with more precise markers than we currently have. One area of major promise in this regard is the greater individual cancer data that can be obtained from molecular markers.We already have seen an example of the benefit of a marker in prostate cancer. The addition of the biological marker PSA offers more precise information over stage and Gleason score alone. In breast cancer, the marker Her 2-neu has been shown to be not only an important prognostic marker, but also a target of therapy [2]. The identification of the protein associated with bcr-abl (break point cluster region-Abelson proto-oncogene fusion) led to a major treatment breakthrough in chronic myelogenous leukemia (CML) [3]. Given these successes, interest has been generated in discovering molecular markers that would help with prostate cancer. Numerous markers have been evaluated, but usually in small numbers and in diverse patient populations. Also, they rarely are evaluated as to whether they enhance the predictive ability of the standard markers. The real test of a new maker (and the key to its success) will be whether it enhances the predictive ability of the prognostic triad of PSA, Gleason score, and stage (with all of its various subclassifications). The purpose of this evaluation is to determine whether any of these are truly helpful in determining who will fail after radical prostatectomy and whether we should consider adding them to our standard armatorium for evaluation.
## 2. Materials and Methods
A comprehensive Medline search was undertaken to identify studies of molecular markers in prostate cancer. In each of those studies, references were evaluated to try to capture all the studies that evaluated markers in patients undergoing radical prostatectomy.Most studies had too few patients to have enough statistical power to make meaningful prognostic statements. Also, most studies were not specific for patients that underwent surgery for their prostate cancer, but rather a mixture of different treatment modalities. While we reviewed all the studies, we focused on those with radical prostatectomy patients that were treated with curative intent. We also focused on studies with more than 50 patients, with the premise that lesser numbers were unlikely to have statistical relevance. In addition, we hoped to focus on studies that evaluated the investigated markers in conjunction with at least one of the accepted predictive factors (PSA, Gleason score, and stage). As it turned out, direct correlation with the known predictive factors was not very commonly performed.We searched for studies that show the possibility of increasing the predictive ability and discuss whether any appear to be able to help us better predict failure. We were not so much interested in determining the mechanistic underpinnings of cancer development and the effect on stage, rather whether markers could help predict the clinical behavior of prostate cancer and help determine appropriate intervention to try to cure more patients.
## 3. Results and Discussion
The literature was quite diverse, which makes interpretation of results difficult and direct comparisons impossible. As per all retrospective studies, there is inherent variation in the selection of patients. In addition, even for the same markers, the determination of positive and negative often varied greatly. Many of them were determined by semiquantitative immunohistochemical (IHC) staining with large methodological and intraobserver variability. Some investigators acknowledged that the staining level to determine what was “positive” had to be manipulated to have significant results [4]. Many studies included patients that received neoadjuvant androgen ablation or adjuvant androgen ablation and/or radiation therapy. While excluding those patients eliminates some of the perceived higher-risk patients, including patients that have additional treatments known to alter failure is also problematic. Also, most of the studies have very short followup, which makes any conclusions about failure tenuous at best. Many expressed markers show a close association with known prognostic factors and while they may be positive on univariate analysis, they fall out on multivariate analysis. These issues are inherent to retrospective studies, but they should be kept in mind.
### 3.1. Ki-67
Ki-67 is one of the earliest markers and is named for the original mouse antibody researched in Kiel Germany, reacting in well number 67 [5]. It serves as a proliferation marker that occurs only in dividing cells (not G0). The original antibody required fresh tissue, but the MIB-1 antibody can be used in formalin fixed tissue. The assessment of Ki-67 gives an estimate (index) of the portion of cells actively proliferating.Some studies report that Ki-67 is prognostic for failure (Table1). In a study of 70 radical prostatectomy patients, 50 were selected for further analysis [6]. With a median followup of 63 months, 18% failed (PSA > 0.2 ng/mL). The specimens were evaluated for Ki-67 via IHC staining. On univariate analysis of PSA, PSA doubling time, Ki-67%, tumor volume, and Gleason score, only Ki-67% and PSA were significant prognostic factors. In another study [7], 137 patients underwent radical prostatectomy with a mean followup of 5.4 years. The cohort included 25% lymph node positive and 36% received adjuvant therapy with radiation and/or androgen ablation. Ki-67 was scored as the per cent of staining >5% (78 or 57% if the patients) or <5% (59 or 43% of the patients); the mean was 7.5%. From the graph, for patients below the mean staining, 5-year recurrence free survival was approximately 78% compared to 65% if above the mean. Ki-67 was a significant factor on multiparameter analysis. The largest study evaluating Ki-67 was of 528 prostatectomy patients after exclusion of those that received neoadjuvant and adjuvant androgen ablation and radiation therapy [8]. With a median followup of 46 months, 101 (19%) failed for a 5-year disease-free (PSA < 0.2 ng/mL) rate of 78%. The tissue was evaluated using IHC staining for Ki-67 and chromogranin A (CGA). On multivariate analysis, Gleason score > 4 + 3, CGA positive, lymph node positive, PSA > 20 ng/mL, and Ki-67 were prognostic, while pathologic stage T3 and margin positivity were not. For the 300 Ki-67 ≥ 5% patients, 5-year biochemical recurrence-free survival (from graph) was 70%, while for the 228 with <5% staining, it was 88%. In another large study, Miyake et al. [9] studied 193 prostatectomy patients that did not receive adjuvant treatment. With a median followup of 63 months, 21% failed for a 5-year disease-free survival rate of 79%. They evaluated twelve markers with IHC. On univariate analysis, they found the following factors to be prognostic: PSA, Gleason score, lymph node positivity, tumor volume, seminal vesicle involvement, margin positive, and on immunohistochemical staining: Ki-67, p53, AR, MMP-2, MMP-9, and HSP27. On multivariate analysis, only Ki-67, seminal vesicle involvement, and margin positivity remained significant. In consideration of those three positive factors, if the patient was positive for 2 or 3 of them, the recurrence rate was 79%, if positive for one, 20%, and if negative for all 3, 4%. Ki-67 was also prognostic in a smaller study of 91 prostatectomy only patients [10]. With a median followup of 46.5 months, 29 (32%) progressed (PSA ≥ 0.2 ng/mL). For the 60% of patients with <5% PSA staining, 5-year disease-free survival was 84%, compared to 42% for those with ≥5% staining (from graph). On multivariate analysis, Ki-67 and Gleason score were prognostic. The final positive study was a multifactorial study [11] of 336 RRP patients, of which 249 had tissue. Lymph node positive patients were included. Failure was defined as PSA > 0.5 ng/mL. Five-year DFS was 63%, and 10-year was 41% with a median followup of 66 months. They utilized immunohistochemical staining for Ki-67, enhancer of zeste homolog 2 (EZH2), (discussed below) and minichromosome maintenance protein 7 (MMC7) (discussed below). They also used fluorescence in situ hybridization (FISH) for EIF3S3, a chromosome abnormality they had explored previously. On multivariate analysis considering EZH2, Ki-67, MCM7, Gleason score, pathologic stage, and PSA, the factors of pathologic stage, Ki-67 and MCM7 were significant predictive factors. From the graphs, for staining 0-1%, 10-year disease-free survival was 65%, for 2–15% was 38%, and for >15% was 27%. Demonstrative as to how other factors can have an effect of prognostic ability, in patients that were lymph node negative with an undetectable postsurgery PSA, Ki-67 dropped out and EZH2, MCM7, and PSA were prognostic. In Gleason, less than 7 patients, Ki-67 was the only significant factor; the 15 patients with Ki-67 staining of >1% had a 5- and 10-year disease-free survival of 70% and 45%, respectively (from the graph), compared to 100% for Ki-67 of 0-1%. No details of interaction with pathologic variables were given.Table 1
Ki-67 and outcomes after radical prostatectomy. The table indicates whether Ki-67 was positive on univariate or multivariate analysis for predicting failure. The failure of the entire cohort is given and then the outcomes for patients where Ki-67 was elevated versus not elevated.
Study#ptsMed (mean) months f/uInclude LN+ (#)Include Adj RX (#)Definition of failure@Univariate positiveMultivariate positiveGroup overall failureMarker elevated outcomeMarker not elevated outcomeKhatami et al. [6]50(63)NoNRPSA > 0.2 × 2YesNR18%NRNRBubendorf et al. [7]137(64)Yes (34)Yes (60)PSA, PAP, or ALP elevated*YesYes29%65% 5-yr dfs78% 5-yr dfsMay et al. [8]52846 (49)Yes (38)NoPSA > 0.2YesYes19% 5-yr dfs 78%70% 5-yr dfs88% 5-yr dfsMiyake et al. [9]19363Yes (13)NoPSA > 0.2YesYes21% 5-yr dfs 79%A: 79% recurB: 20% recurC: 4% recurRubio et al. [10]9146.5NRNoPSA ≥0.2YesYes32%42% 5-yr dfs84% 5-yr dfsLaitinen et al. [11]22966 (62)Yes (NR)Yes (4)PSA ≥ 0.5 × 2YesYes63% 5-yr dfs10-yr 41%5/10-yr dfs 2–15% : 62%/38% 16+% : 42%/27%5/10-yr dfs0-1% : 92%/65%Moul et al. [4]162(54)Yes (1)NRPSA > 0.2 × 2YesNo38%31% 6-yr dfs72% 6-yr dfsBettencort et al. [12] (same patients as [4] above)180(53)Yes (1)NRPSA > 0.2 × 2YesNo60% 5-yr dfs5-yr dfs1+ 69% 2–4+ 44%5-yr dfs83%Vis et al. [15]112113Yes (6)NoClinical only@Yes for clinical recurrenceNoClinical dfs 5-yr 52% 10-yr 42%Clinical dfs5-yr 75%10-yr 75%NR: not reported.@Most studies include biopsy-proven local recurrence and radiographic distant metastasis as failure in addition to PSA.*Three factors: Ki-67, SV+, margin+; A = 2-3 factors, B = one factor, C = all 3 negative.Even though those studies showed on multivariate analysis Ki-67 was able to predict failure, other than the correlation shown in the Miyake et al. study [9], none of the studies evaluated as to how Ki-67 improved the predictive ability of the standard prognostic factors. Therefore, its utility remains uncertain, which is further compounded by the studies that show that Ki-67 is not predictive for failure. In that regard, in a study of 162 patients undergoing RRP (median followup 4.5 years, PSA failure > 0.2 ng/mL at least twice), Ki-67 staining was measured <2 in 62% of the tumors and 2–4 in 38% [4]. On multivariate analysis including pathology stage, race, Gleason score, age, p53, bcl2, and Ki-67 (MIB-1) levels, p53 and bcl-2 were prognostic, but not Ki-67. The findings were confirmed in another study of the same patients [12]. From the cohort of 335 patients, this time 180 had available tissue. With a mean followup 4.4 years, and failure defined as PSA > 0.2 ng/mL twice, the overall 5-yr biochemical failure-free survival (BFFS) was 60%. Ninety per cent had measurable Ki-67 (MIB-1) staining. In 18 patients with negative or rare Ki-67 staining, 3 (5%) progressed for an 83% 5-year biochemical-free survival (BFFS); of 90 that stained 1+, 23 (37%) progressed for a 69% 5-year BFFS; and in 72 that were 2–4+, 36 (58%) progressed with a 5-yr BFFS of 44%. On multivariate analysis, stage and Gleason score were significant prognostic factors and Ki-67 was only marginal. In a subgroup analysis, Ki-67 appeared to differentiate failure in Gleason 2–6 patients, but not in higher grade. A third paper including at least some of the same patients (132) [13] showed Ki-67 positive patients had a higher recurrence rate but again the findings were not significant on multivariate analysis. In a different approach [14], 41 prostatectomy patients who failed within two years (PSA > 0.2 ng/mL) were matched for pathologic stage, PSA, and Gleason score with 41 patients who did not have a rising PSA by three years. They found no difference in Ki-67, p53, and bcl-2 between the two groups. Finally, in an evaluation of 112 prostatectomy patients [15], for patients with low MIB-1 staining, the 5- and 10-year clinical disease-free survival was 75% for both, and for high staining patients was 52 and 42%, respectively. In spite of this difference, MIB-1 was not predictive of recurrence or death on multivariate analysis.
### 3.2. Apoptosis-Related Markers (p53, bcl-2, and MDM2)
Cellular stress triggers (upregulates) p53, which accumulates in cells and leads to either cell cycle pause and repair or apoptosis. Loss of p53 function potentially can allow a cell that would normally undergo apoptosis to survive an otherwise lethal event. Bcl-2 is antiapoptotic and elevated levels can also conceptually allow cells to survive an otherwise lethal event. Mouse double minute-2 (MDM2) has an antiapoptotic effect by binding to p53 and inactivating it. Wild-type or normal p53 is cleared rapidly from cells, so measurable p53 is usually dysfunctional. Therefore, counter-intuitively, an elevated p53 actually represents decreased p53 function.As with Ki-67, there are several positive and negative studies (Table2). In 71 patients operated on before 1984 [16] with a median followup of 10.6 years, 15-year cause-specific survival for p53 positive patients was 38% and for p53 negative patients was 87%. They also found that the 15-year cause-specific survival for retinoblastoma protein (Rb) positive patients was 66% and Rb negative was 92%. On multivariate analysis, the combination of p53 and Rb was the strongest predictor of failure. There was no analysis with the common prognostic factors (stage, PSA, or Gleason score). A later study in 76 RRP patients with a median followup of 50 months found that 27% of the patients with <40% positive p53 staining recurred versus 6/10 (60%) with more than 40% staining [17]. On univariate analysis, nuclear grade, pathologic stage, and p53 were significant, but on multivariate analysis, only p53 was significant. In another prostatectomy study, 263 patients had a mean followup of 55 months and 39% failed [18]. Seventy-eight received adjuvant treatment. They found clustering of p53 positive cells (>12 cells) to be more predictive than percentage of positive cells. On multivariate analysis, both clustering and percentage p53 positive, along with PSA, path stage, Gleason score, and lymph node positivity were predictive for failure.Table 2
p53, bcl-2, and outcomes after radical prostatectomy. The table indicates whether p53 and bcl-2 was positive on univariate or multivariate analysis for predicting failure. The failure of the entire cohort is given and then the outcomes for patients where the marker was elevated versus not elevated.
Study#ptsMed (mean) months f/uInclude LN+ (n)Include Adj RX (n)Definition of failure@Univariate positiveMultivariate positiveGroup overall failureMarker elevated outcomeMarker not elevated outcomeP53Theodorescu et al. [16]71127Yes (1)NoClinical,PSA > 0.2YesYes51% failed15-yr cause-specific 38%15-yr cause-specific 87%Kuczyk et al. [17]7650Yes (6)NoClinicalYesYes32% failed20% died ca33% died ca16% died caQuinn et al. [18]263(56)Yes (5)Yes (99)PSA ≥ 0.4 × 2YesYes39% failed32% 5-yr dfs83% 5-yr dfsMoul et al. [4]162(54)Yes (1)NRPSA > 0.2 × 2YesYes38%39% 6-yr dfs76% 6-yr dfsBauer et al. [19] same patients as [4]175(55)Yes (1)NRPSA > 0.2 × 2YesYes38%45% failed5-yr dfs 49%23% failed5-yr dfs 78%Brewster et al. [20]76(38)NRNoPSA ≥ 0.2 × 2YesYes30%41% failed21% failedGoto et al. [21]11940NRNoPSA > 0.2NoNo13% failed40% failed10% failedMiyake et al. [9]19363Yes (13)NoPSA > 0.2YesNo21% failed5-yr dfs 79%NRNRWu et al. [23]7036.5NRNRPSA > 0.2 × 2NoNo30%44% failed26% failedOsman et al. [24]8665NRYes (33)3 × PSA increaseNRYesNR0 5-yr dfs68% 5-yr dfsBCL-2Bauer et al. [19]175(55)Yes (1)NRPSA > 0.2 × 2YesYes38% failed57% failed5-yr dfs 33%31% failed5-yr dfs 69%38% failedBCL2+ P53+5-yr dfs 25%BCL2− P53−5-yr dfs 80%Brewster et al. [20]76(38)NRNoPSA> 0.2 × 2YesYes30%53% failed24% failedGoto et al. [21]11940NRNoPSA > 0.2NoNo13% failed21% failed10% failedBubendorf et al. [22]137(64)Yes (34)Yes (60)PSA, PAP, ALKPNRNo19% failed5 yr dfs 78%10-yr dfs 18%10-yr dfs 52%Miyake et al. [9]19363Yes (13)NoPSA > 0.2NoNo21% failedNRNRWu et al. [23]7036.5NRNRPSA > 0.2 × 2YesYes30%67% failed28% failedNR: not reported.Most studies include clinical failure: biopsy-proven local recurrence and/or radiographic distant metastasis in addition to PSA.Several studies have considered p53 in conjunction with other factors such as bcl-2, and Ki-67. In one study consisting of 162 patients undergoing RRP (median followup 4.5 years, PSA failure > 0.2 ng/mL at least twice) p53 was measured negative in 31% of the tumors and positive (1–4+) in 69%. Bcl-2 was measured negative in 73% of the tumors and positive (1–4+) in 27% [4]. On multivariate analysis including pathology stage, race, Gleason score, age, p53, bcl-2, and Ki-67 (MIB-1) levels, p53 and bcl-2 were prognostic. There was no correlation as to what the markers added to the common prognostic markers. In another study from the same patient cohort, 175 patients underwent radical prostatectomy [19]. With a mean followup of 4.6 years, p53 staining was positive in 65% and the 5-year failure rate was 51%, compared to 22% for the patients that stained negative. Bcl-2 staining was positive in 27% and the 5-year failure rate was 67%, compared to 31% for the patients that stained negative. For patients that were both p53 and bcl-2 positive, the five-year failure rate was 75% compared to 20% for those that were negative for both. On multivariate analysis, stage, race, bcl-2, and p53 were all prognostic. Again, there was no indication of whether they enhanced the standard markers. Interestingly, in yet another analysis of some of the same patient cohort (132 patients) with median followup of 3.9 years, p53 positive patients had a higher recurrence rate but it was not significant on multivariate analysis [12]. Another study of p53 and bcl-2 looked at 76 prostatectomy patients with a mean followup of 38 months, 23 (30%) of whom failed [20]. Fifty-seven percent were p53 positive on prostatectomy tissue and 41% failed compared to 21% with normal p53. Twenty percent were bcl-2 aberrant on prostatectomy tissue and 53% failed compared to 24% of those with normal bcl-2. In an additional study of 119 radical prostatectomy patients receiving no neoadjuvant treatment and with a median followup of 3.3 years, 16 (13%) failed [21]. On multivariate analysis, bcl-2, p53, Ki-67, PSA, Gleason score, Capsular penetration, age, and margin positivity were not predictive, but SV involvement and caveolin-1 (see below) were.In an older cohort of patients (22% of the failures predated PSA), 30 received adjuvant treatment (mostly radiation) [22]. With a mean followup of 5.2 years, bcl-2 positivity was predictive of recurrence, but only stage pT3 and Ki-67 were predictive of failure (not p53). From the graph, for elevated bcl-2, 10-year disease-free survival was 18% and for nonelevated bcl-2 was 52%. Only 8% overexpressed p53. Like p53, it is also not uncommon for bcl-2 staining to be too low (<5%) to be meaningful [10].Miyake et al. evaluated 193 prostatectomy patients with twelve markers on IHC, including p53 [9]. While it was predictive on univariate analysis, it was not on multivariate. Bcl-2 was not predictive for either. In a study of 70 pathological T2 patients [23] with a median followup of 36.5 months, 30% suffered biochemical relapse (PSA > 0.2 ng/mL times two), sixteen patients were p53 positive, and 44% suffered PSA relapse which was not significantly different than the p53 negative patients (26% relapse). Only 3 (4%) patients were bcl-2 positive, but 2 (67%) relapsed, which was significantly higher than the bcl-2 negative patients (28% failure). Finally, in a study [24] of 86 patients (median followup 65 months) with an undetectable PSA after radical prostatectomy (38% received neoadjuvant treatment), 20% overexpressed p53 and had a higher risk of relapse. The 33% that overexpressed MDM2 also had a higher risk of relapse. No details were given, but on multivariate analysis, both p53 and p21 were predictive. Stage and MDM2 were not. Interestingly, there was no association with p53 overexpression and p21 or MDM2. As with all the studies discussed, there was no real analysis for correlation with standard predictive factors, so the real predictive power of these markers remains elusive.
### 3.3. E-Cadherin and Other Adhesion Molecules
Calcium-dependent adhesion molecules (cadherins) are transmembrane proteins that play a role in cell adhesion. E-cadherin is a subtype found in epithelial tissue with extracellular, transmembrane, and intracellular domains. The intracellular domain binds to beta catenin. In cancer, E-cadherin downregulation theoretically reduces cell adhesion resulting in increased cell motility and dissemination.In a study of 70 pathological T2 patients [23] with a median followup of 36.5 months, 30% suffered biochemical relapse (PSA > 0.2 ng/mL times two). Thirty-nine patients (56%) had aberrant E-cadherin staining, with a 44% PSA relapse rate, which was significantly worse than those with normal E-cadherin staining (13% recurrence). In 104 prostatectomy patients [25] (7 lymph node positive), low E-cadherin, Gleason score, and pathologic stage were predictive of biochemical failure (PSA > 0.5 ng/mL) on multivariate analysis. For clinical failure, pathological stage dropped out and elevated N-cadherin was significant. For patients with low E-cadherin, the 10-year biochemical failure-free survival was 14%, versus 33% for those with elevated levels. For N-cadherin, low levels resulted in 33% biochemical failure-free survival and high levels 14%. They found that the E-cadherin to N-cadherin ratio was more powerful than either alone, but did not provide specifics nor any details on the modification of the predictive power of standard factors. In a study of 67 radical prostatectomy patients [26] with a median followup of 54 months, 27 (40%) recurred clinically, 7 locally, and 20 systemically. When evaluated with IHC for E-cadherin, a cut point of 40% staining was chosen. For the 13 that stained less than 40%, 2 (15%) died of cancer and for the 54 that stained >40%, 14 (26%) died of cancer, but the difference was nonsignificant. E-cadherin was not predictive on univariate or multivariate analysis for either recurrence or survival. In 128 radical prostatectomy patients [27] without adjuvant treatment, tissue microarrays were made and stained with IHC staining. Normal was considered >70% staining. For nonmetastatic prostate cancer, 18% had aberrant staining. With a median followup of 23 months, 38% of the failures and 20% of the nonfailures had aberrant staining, a nonsignificant difference. Similarly, in a microarray study (discussed below), Rhodes et al. [28] found that a decreased E-cadherin to EZH2 ratio resulted in an increased rate of biochemical failure after radical prostatectomy.Brewster et al. [20] studied 76 prostatectomy patients; 49% were E-cadherin aberrant on prostatectomy tissue and 37% failed compared to 22% with normal E-cadherin. On multivariate analysis, it was not predictive when considered with p53, bcl-2, Gleason score, and margins. They also evaluated another apparent adhesion molecule in the form of the cell surface glycoprotein CD44. Sixty-four percent were CD44 minimal or absent on prostatectomy tissue. Of those with normal staining, 8% failed compared to 43% with aberrant staining. On multivariate analysis, it was not predictive when considered with p53, bcl-2, Gleason score, and margins. Two other studies evaluated CD44. In 97 radical prostatectomy patients [29] with median followup of 84 months, utilizing PSA of >1.0 as failure, most (86%) patients were positive for CD44, so risk was determined by graded intensity of the staining. Decreased expression increased the risk of failure. On univariate analysis, loss of CD44 and cd4v6 were predictive of clinical failure, but only CD44 was predictive for biochemical failure. In the other study, 99 patients had mean followup of 40 months and 26% suffered a biochemical recurrence [30]. CD44 was evaluated via an intensity and percent staining score, and 47% were downregulated. The 3-year recurrence-free survival was 77% for the nondown-regulated patients versus 48% for those with CD44 downregulation. It was not a significant predictor on multivariate analysis, when considered with p34.In none of these studies was there an assessment of how it modified the predictive ability of the standard prognostic factors.
### 3.4. EZH2
The Enhancer of Zeste 2 (EZH2) gene codes for polycomb group proteins that effect chromatin and silence genes. When overexpressed, it appears to be associated with tumorigenesis. In a study involving multiple cancers [31], 104 radical prostatectomy patients with a median followup of 104 months were evaluated with staining for EZH2. For low EZH2 staining, the 5- and 10-year cause-specific survival was 99% and 93%, respectively. For the high staining group, it was 89% and 53%, respectively. On univariate analysis, upper quartile EZH2 staining was predictive for clinical recurrence and on multivariate analysis was predictive for distant metastasis and death. In another study of 64 patients [32], tissue was stained for EZH2 and if the intensity was ≥3, 10/32 (31%) failed versus 3/32 (9%) if the staining was <3. It was a significant factor on multivariate analysis along with margin status, tumor size, Gleason score, and PSA. Finally, in a study (see Ki-67 above) [11] of 249 prostatectomy patients, five- and 10-year disease-free survival was 63% and 41%, respectively. On multivariate analysis, pathologic stage, Ki-67 and MCM7 were significant predictive factors (EZH2 was not). In patients that were lymph node negative with an undetectable postsurgery EZH2, MCM7 and PSA were prognostic. In Gleason less than 7 patients, Ki-67 was the only significant factor. There was no evaluation of whether this added to the predictive ability of standard factors.
### 3.5. Cyclin-Dependent Kinases (and Their Effectors)
Cyclin dependent kinases (CDKs) are protein kinases involved in the regulation of the cell’s progression though the cell cycle. As most cancers have dysfunctional cell cycle control, the kinases are implicated as part of the aberrancy. Cyclin D1 is specific for transition through G1/S. It has its effect by binding with cyclin dependent kinases 4 and 6 forming a complex that phosphorylates and inactivates the retinoblastoma protein (Rb). Overexpression of cyclin D1 has been associated with the malignant phenotype and its progression. There are several known inhibitors of cyclin dependent kinases. For example, p16INK4a (cyclin-dependent kinase inhibitor 2A) inactivates Cdk4 and CdK6 and thereby acts as a tumor suppressor (by blocking the phosphorylation of the Rb gene, which prevents transit through G1). Loss of p16 enables abnormal progression through the cell cycle, increasing the malignant potential. P21-waf1 encodes a cyclin dependent kinase inhibitor (p21 or cyclin dependent kinase inhibitor 1A), inhibiting CDKs 2 and 4, which leads to arrest at G1. It is induced by p53 (thus elevated p53 can lead to arrest at G1 through this route). P27Kip1 (cyclin dependent kinase inhibitor 1B) is also involved in G1 arrest by inhibiting cyclin dependent Cdk2 complexes E and A and D-Cdk4. Therefore, a decrease in p27 should result in increased proliferation. Lastly, p34cdc2 (cell division control protein 2) is a component that forms a kinase by binding with cyclin B1 (forming maturation-promoting factor (MPF)) that regulates G2/M transition and promotes mitosis).In a study [24] of 86 patients with an undetectable PSA after radical prostatectomy (38% received neoadjuvant treatment), 33% overexpressed p21Cip, and this was associated with a higher risk of relapse. No details were given, but on multivariate analysis, both p53 and p21 were predictive of relapse whereas stage and MDM2 were not.In one study, where the primary goal was to assess the association between pathological features and biomarker expression [33], p27Kip expression was evaluated in 113 prostatectomy specimens (median followup 4.6 years, 21% neoadjuvant androgen ablation), and correlated with outcome. Low p27 nuclear staining was a poor prognostic sign. On multivariate analysis, p27, seminal vesicle status and margin status were all predictive for recurrence, but no details were given. In a second study of 96 stage C lymph node negative patients undergoing radical prostatectomy with a median followup of 9.5 years [34], p27 Kip1 staining correlated with Gleason score (higher grades had decreased levels). The 9-year recurrence-free survival for levels ≤10% was 17%, for levels 11–50% was 47%, and for >50% was 67%. There was no correlation with the standard factors. In a third p27 study [35] of 86 patients (after excluding those that received adjuvant treatment), multivariate analysis demonstrated only pathologic stage and p27 to be predictive at a median followup of 40 months. High Gleason score was associated with low p27 staining. Thirty percent was the breakpoint between high and low staining. Fifty percent of patients with low staining failed (PSA > 0.4) and 78% with high staining failed. In another study with 95 patients [36], loss of p27 (<10%) on multivariate analysis was significant for recurrence, but not for survival. With a median followup of 49 months, 33% of the p27 negative patients failed versus 23% for the p27 positive patients (median followup 59 months). Another study was of 161 prostatectomy patients [37], which were divided into organ confined (n=76, median followup 42 months) and nonorgan confined (n=85, median followup 38 months) patients. p27 staining was performed on the biopsy, but not the final pathology specimen, and patients were not evaluated for the specific impact of positive margins, seminal vesicle involvement, or lymph node involvement. For the organ-confined patients, the 5-year recurrence rate was 26%, but 9% for those with high p27 staining and 37% with low (<45%) staining. In this subgroup, p27 was predictive for failure. In the nonorgan confined patients, the recurrence rate was 44%, but p27 was not predictive of failure in these more advanced patients and the actual effect on failure was not stated. In an evaluation [15] of 112 prostatectomy patients, 92 had adequate p27 staining. Thirty-five (38%) stained less than 50% and were classified as low staining. Based on clinical parameters, their 5- and 10-year disease-free survival were 37% and 26%, respectively. For the high staining patients, it was 79% and 77%, respectively. p27 predicted for clinical recurrence and cause-specific survival.Finally, in a study of 104 radical prostatectomy patients with a median followup of 56 months [38], p27 was determined by the per cent of nuclei staining, with the median of 64% used as the breakpoint between high and low. On multivariate analysis, pathologic stage and PSA were significant predictors of recurrence, but not p27.p16 has been evaluated in several studies. In 206 radical prostatectomy patients (18% with neoadjuvant androgen ablation) with a median followup of 72 months, one group [39] found positive p16INK4a staining to be associated with recurrence. On multivariate analysis, p16, PSA, Gleason score, and margin status were all predictive, but no actual outcome data was given. In another study [40], 88 prostatectomy patients (39% neoadjuvant treatment) with a median followup of 65 months stained for P16. Unlike Henshall et al. [39] (which called low <1%), their breakpoint was 5% positive nuclear staining. For the 38 patients that overexpressed, 21 (55%) failed versus 26% of the 50 under expressing patients. p16 was associated with PSA levels and was not an independent prognostic factor on multivariate analysis. They also did not report specifics on outcome. In a third study of 104 radical prostatectomy patients with a median followup of 56 months [41] the multivariate analysis for survival was positive for p16, age, grade, capsular penetration, and seminal vesicle involvement. They scored p16 by a fluorescence index. The low group had a 5-year survival of 78% versus 43% for the intermediate group (P=.005) and 42% for the high index group. There was no outcome data accounting for the standard factors. Ploidy or S phase was not predictive.In analysis of cyclin D1 and p34cdc2, 140 patients [42] with a median followup of 42 months were evaluated. Failure was defined as a PSA > 0.4. In patients that were p34cdc2 negative, 10% failed versus 26% that were positive. For Gleason 7 or greater, the failure rate was 26% for p34cdc2 negative and 38% for positive. On multivariate analysis, only p34cdc2 and Gleason score were predictive and cyclin D1 and ploidy were not. p34 was also evaluated in a study of 99 patients. With a mean followup of 40 months, 26% suffered a biochemical recurrence [30]. p34 was evaluated via an intensity and percent staining score and 61% were determined to have overexpressed p34. The 4-year recurrence-free survival (from the curves) was 98% for the nonover expressed patients versus 47% for those over expressing p34. It was a significant predictor on multivariate analysis, but there was no evaluation of whether it enhanced the predictive ability of standard factors.
### 3.6. Cathepsin-D
Cathepsins are proteases (i.e., involved in protein degradation) usually housed in lysosomes that proteolyse proteins that regulate cell growth. In a study [43], 105 radical prostatectomy patients were evaluated for cathepsin D. It was not prognostic on either univariate or multivariate analysis, but probably because the expression rate was extremely high at 98%.
### 3.7. Chondroitin Sulfate
Chondroitin sulfate is a structural glycosaminoglycan of the extracellular matrix that helps regulate cell activity. Ricciardelli et al. [44] studied 157 prostatectomy patients after exclusion of adjuvant and neoadjuvant treatment; failure was defined as a PSA > 0.2 and median followup was 47 months. They used an antibody to chondroitin sulfate and read the slides via an image capture technique with automated analysis. There was a twofold difference between this study and previous studies for the absolute value of the mean due to calibration differences, which demonstrates the lack of uniformity in these studies. The median was chosen as the cut point, although the most robust point was slightly above that. On multivariate analysis, chondroitin sulfate, Gleason score, preoperative PSA, and pathological stage were all predictive. For patients with low staining, 23% failed for a 5-year PSA failure rate of 33% versus 51% with high staining failing for a 5-year failure rate of 51%. There was some correlative analysis between chondroitin staining and other predictive factors. For patients with a preoperative PSA less than 10, 9% with low chondroitin sulfate staining failed versus 48% with high levels. In a more specific analysis, the five-year failure rate for Gleason 5–7 patients with low chondroitin levels and low PSA was 11% compared to 44% for low chondroitin staining patients with a high PSA. Further, Gleason 5–7 patients with high chondroitin sulfate staining and low PSA had a five-year failure rate of 56% versus 72% for high staining and high PSA. There was no evaluation done with the integration of pathology findings.
### 3.8. Hepsin and PIM1
Hepsin is a transmembrane serine protease whose exact function is unknown, but when upregulated appears to express a malignant phenotype. PIM1 encodes a protein kinase that promotes G1/S transition by upregulation of CDK2, facilitating cell proliferation and survival. One study [45] utilized human specimens and cell lines for comparison of malignant and benign tissue. Out of several hundred candidate genes, hepsin and PIM1 expression proteins were selected for further analysis. Hepsin was increased in malignant prostate tissue versus benign, but staining was greatest in PIN. In radical prostatectomy patients, low or absent hepsin increased failure. On multivariate analysis, both hepsin and Gleason score were predictive of failure. They also tested for PIM1. It was upregulated in prostate cancer and decreased levels were associated with increased PSA level in 135 patients with localized prostate cancer. It was significant on multivariate along with Gleason score 4-5 and PSA. They concluded that lower PIM1 levels were strongly associated with an increased risk of relapse. There was no outcome correlation with standard factors with either marker.
### 3.9. Cox-2
In a study of 91 prostatectomy patients [10], with a median followup of 46.5 months, 29 (32%) progressed (PSA > 0.2 ng/mL). A score was developed for percent and intensity of staining for Cox-2. For no staining, the failure rate was 26% versus 60% for 1–4, but then dropped back to 15% for 5–12. While it was a predictive marker on univariate analysis, it was not on multivariate.
### 3.10. Laminin Receptor (Ribosomal Protein SA)
Laminins are glycoproteins located in the basement membrane (basal lamina) that affect cell adhesion and migration as well as differentiation and survival. Laminin receptor (LR) is detected via the MLuC5 antibody. In an initial evaluation [46] in 140 patients, it appears that laminin receptor positivity might be associated with recurrence. Overall, the 3-year biochemical failure-free survival was 68%, but for LR positive patients the failure was 45% and for negative patients it was 7%. There was no correlation with PSA and Gleason score. The followup was only 20 months, and a later paper [47] showed that LR measurement of the biopsy tissue was not significantly predictive for biochemical progression, probably due to a lack of concordance between the measurements in biopsy tissue versus the larger tumor specimen.
### 3.11. Chromogranin A (CGA)
In a study of 528 prostatectomy patients [8] excluding neoadjuvant and adjuvant androgen ablation and radiation therapy, with a median followup of 46 months, 101 (19%) failed for a 5-year disease-free (PSA < 0.2 ng/mL) rate of 78%. The tissue was evaluated using IHC staining for Ki-67 and chromogranin A (CGA). On multivariate analysis, Gleason score > 4 + 3, CGA positive, lymph node positive, PSA >20 ng/mL, and Ki-67 were prognostic, while pathologic stage T3 and margin positivity were not. For the 32 CGA positive patients, the 5-year biochemical recurrence-free survival was 48% and for the 496 CGA negative it was 80%. Because of the small number of CGA positive patients, the only specific information was given on whether there was modification of prognosis of the standard factors was for Gleason <7 patients, where for the 304 CGA negative patients, 8% failed and for the 12 CGA positive, 25%.
### 3.12. Minichromosomal Maintenance Protein 7 (MCM7)
Minichromosome maintenance protein 7 (MCM7) appears to be a facilitator of DNA replication, so upregulation would be expected to increase proliferation. It has been found on microarray analyses that MCM7 is frequently amplified in prostate cancer. In an evaluation of prostatectomy patients [48], 52/68 (77%) with MCM7 amplification relapsed versus 7/57 (12%) without amplification. In a study discussed above (see Ki-67) [11], pathologic stage, Ki-67, and MCM7 were significant predictive factors. In evaluation of patients that were lymph node negative with an undetectable postsurgery, EZH2, MCM7, and PSA were prognostic. In both studies, there was no clinical correlation, so these interesting findings are of uncertain significance.
### 3.13. Histones
Histones are intranuclear proteins in chromatin around which DNA is “wound”, the modification of which influences their interaction with the DNA and affects some processes such as mitosis and gene regulation. In 183 radical prostatectomy patients, those that received androgen ablation were excluded. The median followup was 60 months and failure was defined as PSA > 0.2 ng/mL [49]. In order to evaluate sites on histones H3 and H4 with acetylation and dimethylation staining, 5 different sites were identified by using a clustering algorithm. While not independently predictive, when combined with Gleason score, the findings yielded prognostic information. From the graph, Gleason < 7 patients that were histone “favorable” had an 84% disease-free survival, while those unfavorable had a 58% disease-free survival. For Gleason 7–10, the favorable group had a disease-free survival of 46% versus 20% for the unfavorable.
### 3.14. TMPRSS2 : ERG Fusion
TMPRSS2 (transmembrane protease, serine 2) is an androgen-regulated gene found on chromosome 21 that encodes a transmembrane protease. In prostate cancer, it can be fused with genes for the ETS transcription factors, such as ERG (resulting in TMPRSS2 : ERG). This indirectly places ERG under androgen transcriptional control. There are multiple variants of this fusion. This can be detected through either RT-PCR or fluorescence in situ hybridization (FISH). In 165 prostatectomy patients with available frozen tissue [50] with a median followup of 20 months, tissue was evaluated for TMPRSS2 : ERG fusion gene and 49% was positive. For the fusion gene positive patients, 46% failed compared to 7% in fusion negative patients. On multivariate analysis, the fusion gene was the most predictive factor, followed by grade. Evaluation was made for different Gleason and pathologic findings. For Gleason 5-6 patients, 33% of the gene positive patients failed, versus 5% for the gene negative. For Gleason 7 and Gleason 8–10, it was 48% versus 7% and 75% versus 14%, respectively. For organ-confined patients, gene positive patients had a recurrence rate of 34% versus 10% for gene negative. For extraprostatic extension and seminal vesicle positive patients, it was 53% versus 3% and 67% versus 34%, respectively. For both Gleason score and pathological findings, all the differences were statistically significant, except for the seminal vesicle involved patients. Another study, started with 248 radical prostatectomy patients [51], but only 150 were ultimately evaluable by FISH. Of those, 50 (33%) were found to have TMPRSS2 : ERG rearrangement. With a median followup of 66 months and failure defined as two rises of PSA > 0.5 ng/mL, on multivariate analysis, Ki-67, pathologic stage, and TMPRSS2 : ERG fusion were significant, not Gleason score or PSA [52]. Yoshimoto et al. evaluated specimens from 125 radical prostatectomy patients, 122 of which had clinical followup and with a median followup, 49% had failed (PSA > 0.2 ng/mL). Neoadjuvant androgen ablation was allowed, and 2 patients were lymph node positive. FISH was used to evaluate for TMPRSS2 : ERG, and 48% were found to have rearrangements resulting in a 5-year biochemical failure-free survival (BFFS) of 46%. For those that were negative, 5-yr BFFS was 62% (P=.0523). Expanding on their previous work, they also evaluated for PTEN deletion by FISH. Only 82 of the 125 patients could be evaluated. There was no difference in 5-yr BFFS between those that were deletion negative and positive, but if they divided the deleted patients into hemizygous and homozygous deletions, they found that all the homozygous patients had failed by 5 years. If patients had both the PTEN deletion and the TMPRSS2 : ERG fusion, 5-yr BFFS was 30% versus 59% if they had neither (P=.001). They did not test to see whether these markers augmented the predictive ability of the three standard factors (Stage, Gleason score, or PSA), although on multivariate analysis only Gleason score, the TMPRSS2 : ERG/PTEN combination and homozygous PTEN deletion were prognostically significant. A study [53] using microarray to compare genes between benign and malignant cells found that ERG was the most commonly over expressed. Then utilizing QRT-PCR, they analyzed 114 prostate cancer patients and found ERG1 over expressed in 62%. Ninety-five patients had detectable levels and for a >100 over expression, the 5-year biochemical failure free-survival (from the graph) was 88%, for 2–100 fold 80% and for <2 fold 36%. On multivariate analysis, ERG1 (>100 versus <2) and Gleason (8–10) were significant, but not race, PSA, pathologic stage, margin positive, or seminal vesicle positivity.Not all studies found TMPRSS2 : ERG to be prognostic. In one study [54], two subgroups were taken from larger prospective studies and ultimate outcome collected from SEER data. This yielded no failure data and only crude followup of cancer-specific survival. Of the subgroups, only 57% could be scored for the fusion. They reported no association between the occurrence of TMPRSS2 : ERG (positive in 36% of the patients) and cancer specific survival. Researchers in a study [55] of 521 radical prostatectomy patients with 95 month median followup utilized FISH and found 42% had TMPRSS2 : ERG abnormalities. It was not associated with recurrence, metastasis or death. Finally, in a study of 54 patients [56], 35 (65%) had gene rearrangement, which was present in 60% of the nonfailing patients and 65% of the failing patients. In the evaluation of 28 benign prostate tissues, there were no rearrangements.
### 3.15. PTEN
The phosphatase and tensin homologue (PTEN) gene modulates the phosphotidylinositol 3-kinase (PI3K) pathway, a regulator of the Akt pathway. Lack of PTEN allows for upregulation of Akt and other cell cycle factors, increasing cell survival. As noted above [52] in the TMPRSS2 : ERG discussion, on multivariate analysis, homozygous PTEN deletion and the TMPRSS2 : ERG fusion were prognostically significant. In an earlier study specifically evaluating PTEN, the same authors [57] utilized fluorescence in situ hybridization (FISH) to PTEN in 107 prostatectomy patients. Tissue was scored as showing no deletions (56%), hemizygous deletions (39%), or homozygous deletions (5%). On Cox proportion hazard analysis, for univariate analysis, perineural invasion, seminal vesicle positive (SV+), extraprostatic extension (EPE), Gleason score, PSA, lymph node positivity, and PTEN deletion were all predictive. On multivariate analysis, only EPE, SV+, and PTEN were predictive. For PTEN, from the graph, 5-year PSA (>0.2 ng/mL) failure-free survival was 0 for the 5 homozygous patients, 48% for the 42 hemizygous patients, and 60% for the 60 patients without deletion. There was no discussion as to how PTEN modified the predictive ability of standard factors. In a separate study of 104 radical prostatectomy patients with a median followup of 56 months [38], PTEN was scored as an index based on percent staining and intensity. On multivariate analysis, pathologic stage and PSA were significant predictors of recurrence, but not PTEN.
### 3.16. Epidermal Growth Factor Receptors (EGFR)
Epidermal growth factors are extracellular ligands controlled by the cell surface epidermal growth factor receptors, which are tyrosine kinase receptors. When activated, they initiate a cascade of signal transduction (i.e., though the Akt pathway) that results in cell proliferation. If the receptor is mutated in the “on” position (i.e., over expression), the result could be uncontrolled proliferation. Her-2/neu (c-erb B2) encodes a tyrosine kinase growth factor receptor similar to the epidermal growth factor receptors and has been linked with advanced disease. In one study, [43] 105 radical prostatectomy patients were evaluated for epidermal growth factor receptor (EGFR). The expression rate was 48%, but it was not prognostic on either univariate or multivariate analysis. In 113 prostatectomy patients with a mean followup of 42 months [58], utilizing IHC, membranous and cytoplasmic staining was given a composite score so that ≥3 was considered positive. With that parameter, 29% of the tissue over expressed and there was no correlation with failure on univariate analysis. Utilizing FISH, it was found that 41% were amplified for Her2, but there was poor correlation with IHC staining (P=.25). While FISH analysis was significant for failure on univariate analysis, it was not a significant predictor of failure on multivariate analysis. In 99 patients with a mean followup of 40 months, 26% suffered a biochemical recurrence [30]. Her 2-neu was evaluated via FISH and 42% were found to be amplified. The 5-year recurrence-free survival was 75% for the nonamplified patients versus 47% for those with Her 2-neu amplification. It was not a significant predictor on multivariate analysis, when considered with p34.
### 3.17. VEGF
In a study of 193 prostatectomy patients [9], twelve markers were evaluated on IHC, including VEGF, but it was not predictive on univariate analysis.
### 3.18. Caveolins
Caveolins are cell membrane proteins involved in endocytosis resulting in invagination of the plasma membrane (caveolae). They appear to be involved in signal transduction with a role in homeostasis and tumorigenesis. Caveolins have been found to be both increased and decreased in cancer so their role is variable and uncertain. In radical prostatectomy patients selected for failing or not failing, 162 lymph node negative patients were identified. With immunohistochemical staining for caveolin 1, 22% were positive and five-year progression-free survival was 43% versus 68% for those that were negative. On multivariate analysis, caveolin 1, Gleason score, extracapsular extension, seminal vesicle involvement, and margin involvement were all predictive [59]. The same group later studied serum levels of caveolin 1. As noted above, in a study [21] of 119 radical prostatectomy patients on multivariate analysis only caveolin 1 staining and SV involvement were predictive on multivariate analysis, but bcl-2, p53, Ki-67, PSA, Gleason score, Capsular penetration, age, and margin positivity were not. For caveolin 1 positive patients, 9/32 (28%) failed versus 7/87 (8%) that were negative. In 232 prostatectomy patients that included lymph node positive and those that received salvage radiation therapy [60], with a median followup of 70 months, the 5-year biochemical-free survival rate was 80%. On multivariate analysis, only Gleason sum (not Caveolin 1 staining) was a significant predictor of failure. When limited to lower risk patients (n=177) with exclusion of lymph node positive, seminal vesicle positive, Gleason > 7, and extracapsular extension/margin positive, caveolin 1 was still not a significant predictor on multivariate analysis. They did find that in evaluating only the recurring patients, those that had caveolin 1 over expression did worse. In a similar study [61], 30% of 152 radical prostatectomy patients (including lymph node positive) stained positive for caveolin 1. It was not predictive on multivariate analysis (only seminal vesicle positivity, margin positivity, and PSA were), but when restricted to patients with organ-confined disease, it was the lone predictive factor. This is somewhat in contradistinction to the low risk patients noted in the study above.
### 3.19. Zinc-Alpha2-Glycoprotein (AZGP1)
Zinc-alpha2-glycoprotein (AZGP1) encodes for a protein historically thought to be involved in lipolysis and thought to have a role in the cachexia of cancer. From a series of 732 radical prostatectomy patients [62], 228 were analyzed. Forty-three percent failed with a PSA rise of ≥0.2 ng/mL. On IHC, tissue was scored as absent or weak versus strong AZGP1 staining. Twenty-nine percent stained weak. Although there were few events, it appears to be predictive of clinical recurrence and distant metastasis, but there was no evaluation as to modification of common prognostic factors. In a gene array study [63] discussed below, AZGP1 was predictive for nonrecurrence.
### 3.20. Alpha Methylacyl CoA Racemase (AMACR)
Alpha methylacyl CoA racemase (AMACR) is a catalytic enzyme (of fatty acids) that is frequently over expressed in prostate cancer, but levels are decreased in advanced cancers as compared to localized. In 204 radical prostatectomy patients [64], IHC was performed for AMACR expression proteins and regression analysis was used to correlate staining with PSA failure (>0.2 ng/mL). With visual scoring on a scale of 1–4, there was no correlation with failure, but with quantitative expression analysis, patients in the lower tertile were more likely to recur. For patients more than 1.11 standard deviations below the cut point, 37.5% failed versus 14.5% if they were above. This was significant on multivariate analysis along with PSA, Gleason score, and margin status, but there was no evaluation as to the actual effect on the prognostic ability of those factors.
### 3.21. Gene Arrays and Panels
With the use of gene expression micro arrays, the hope is that by screening a large number of genes, genes highly predictive of cancer recurrence could be identified. When using probe arrays, multiple genes can be identified that may predict for relapse. Several groups have evaluated this approach in predicting failure postprostatectomy. In a gene expression profile of 225 tumors with a median followup of 8 years [63], it was found that MUC1 was predictive of recurrence and AZGP1 was predictive of nonrecurrence. Both of these genes were predictive on multivariate analysis along with Gleason score, stage, and PSA. There were no actual outcome results given. A similar study [28] of 259 RRP patients with a median followup of 57 months searched also for markers using microarray assay. They found that the combination of EZH2 increased and ECAD decreased was most predictive of 5-year recurrence (38% versus 15% for those without that combination). On multivariate analysis, this ratio was significant along with PSA, margin status, and pathological stage, but not Gleason score. For organ-confined patients that were margin negative, those that were EZH2/ECAD elevated had a 27% recurrence rate, versus 10% for those that had a decreased ratio. They did not report on higher-risk patients. In a different study of 100 lymph node negative prostatectomy patients [65], with a median followup of 70 months an expression analysis of 12,625 transcripts identified 218 genes that were either up- or down regulated. Recurrence was defined as three rising PSA levels. The combination that predicted recurrence was deemed “poor markers”. For Gleason 6-7 cancers, the 5-year disease-free survival was 69%, but was 77% in the good marker group and 47% in the poor marker group. In Gleason 8-9 cancers, the 5-year disease-free survival rate was 26%, but was 67% with good markers and 0 with poor markers. On multivariate analysis, Gleason score and the gene expression markers were predictive of recurrence, but PSA and age were not. Using a postoperative nomogram [66] they identified poor risk patients by nomogram (undefined) who had a 28% 5-year disease-free survival, increasing 50% with good gene markers, but 19% with poor markers. In the nomogram predicted favorable group, 5-year disease-free survival was 81%, which was 87% with good markers and 59% with poor markers. The major limitation of the study is that there were only 21 patients in the training set and 79 patients in the validation set.Another approach is to pool multiple genes in order to try to produce a more powerful predictive model. This has been successful in breast cancer [67, 68]. With that approach [69], using a 70 gene set in it was possible to predict 27/29 “aggressive” and 27/32 “nonaggressive” cancers and predicted 16 of the 18 failures. Unfortunately, it appears only 61 patients were evaluated; there was no indication of how the findings related to standard prognostic factors. In a more comprehensive study [70] of 639 patients selected for systemic recurrence, biochemical (PSA) recurrence and nonrecurrence at 7 years, the groups were evaluated for genes that differed between them. Patients with adjuvant treatment were not excluded and failure was with a PSA > 0.2 and rising. The patients were divided into training and a validation set. Ultimately, a 17-gene panel was determined to be predictive. Clinical models based on Gleason score, and pathological stage (PSA and age were not informative) demonstrated a correlation (area under the curve) of 0.76 (0.74–0.78), while the probe set was 0.85 and the combination of the two was 0.87. They reported that the AUC for the validation set was lower. They compared their results to those of other gene array studies and found that all the other models performed better than the clinical model alone (0.74, ranging from 0.76–0.86), with their 17 gene probe being the highest. All the validation sets were lower than the training sets for these genes. In an exploratory study [71] of 72 prostatectomy patients with a median followup of 28 months, 24% relapsed. After scanning for 59,619 probe sets, over 200 genes could be identified that are associated either positively with relapse. In another exploratory study [72], tissue from 37 failing patients and 42 nonfailing patients was tested with a 22,283-gene probe microarray. The first goal was to see if the identified genes (ultimately 5–8 were used) could correctly identify the failing versus the nonfailing patients, which it did 75% of the time. When combined into a nomogram, the predictive rate increased to 89%. Given that nomograms are the most robust incorporation of the standard prognostic factors; this would represent an example of how molecular data can increase the ultimate ability to predict who will fail. Unfortunately, the number of patients evaluated was very small, so any conclusions are tentative at best. One last study took a different approach. Rather than do a blind probe for over- or under expressed genes, they [73] evaluated a pre-existing class of predictive genes like those successful in breast cancer [74]. Although the actual genes are variable, most of the predictive breast cancer genes fall under the general classification of cell cycle progression genes. In evaluation of that class of genes in a large prostatectomy cohort [73] (442 with tissue, median followup 9.5 years), a panel of 31 was tested for their ability to predict recurrence. Overall, 10-year progression-free survival was 64%. When evaluated for the standard findings of PSA, Gleason score, and pathologic findings, the patients could be divided into two groups based on these clinical factors. The low-risk group were patients with Gleason < 7, organ-confined disease, and PSA < 10 ng/mL (actually, PSA up to 30 ng/mL did not change the risk). Their 10-year risk of biochemical failure (PSA > 0.1 ng/mL) was 17%, but for those with a low CCP score, it was 4% and for a high CCP score it was 24%. For clinical high-risk patients (Gleason ≥ 7 and/or nonorgan confined and/or PSA > 30), 10-year biochemical failure was 61%, which was 51% for low CCP score, and 64% for high score. On multivariate analysis, they the CCP score was predictive of recurrence.It is interesting to note, as pointed out previously [71], using multigene predictive models, there is little overlap in the genes that are found to be significant in each of the models. This is postulated to be a factor of a large number of genes and a high signal-to-noise ratio associated with the prediction of biochemical recurrence. The challenge then is to determine which of these are true prognostic markers and which are otherwise just testing anomalies. It will take large comprehensive studies to determine this.
## 3.1. Ki-67
Ki-67 is one of the earliest markers and is named for the original mouse antibody researched in Kiel Germany, reacting in well number 67 [5]. It serves as a proliferation marker that occurs only in dividing cells (not G0). The original antibody required fresh tissue, but the MIB-1 antibody can be used in formalin fixed tissue. The assessment of Ki-67 gives an estimate (index) of the portion of cells actively proliferating.Some studies report that Ki-67 is prognostic for failure (Table1). In a study of 70 radical prostatectomy patients, 50 were selected for further analysis [6]. With a median followup of 63 months, 18% failed (PSA > 0.2 ng/mL). The specimens were evaluated for Ki-67 via IHC staining. On univariate analysis of PSA, PSA doubling time, Ki-67%, tumor volume, and Gleason score, only Ki-67% and PSA were significant prognostic factors. In another study [7], 137 patients underwent radical prostatectomy with a mean followup of 5.4 years. The cohort included 25% lymph node positive and 36% received adjuvant therapy with radiation and/or androgen ablation. Ki-67 was scored as the per cent of staining >5% (78 or 57% if the patients) or <5% (59 or 43% of the patients); the mean was 7.5%. From the graph, for patients below the mean staining, 5-year recurrence free survival was approximately 78% compared to 65% if above the mean. Ki-67 was a significant factor on multiparameter analysis. The largest study evaluating Ki-67 was of 528 prostatectomy patients after exclusion of those that received neoadjuvant and adjuvant androgen ablation and radiation therapy [8]. With a median followup of 46 months, 101 (19%) failed for a 5-year disease-free (PSA < 0.2 ng/mL) rate of 78%. The tissue was evaluated using IHC staining for Ki-67 and chromogranin A (CGA). On multivariate analysis, Gleason score > 4 + 3, CGA positive, lymph node positive, PSA > 20 ng/mL, and Ki-67 were prognostic, while pathologic stage T3 and margin positivity were not. For the 300 Ki-67 ≥ 5% patients, 5-year biochemical recurrence-free survival (from graph) was 70%, while for the 228 with <5% staining, it was 88%. In another large study, Miyake et al. [9] studied 193 prostatectomy patients that did not receive adjuvant treatment. With a median followup of 63 months, 21% failed for a 5-year disease-free survival rate of 79%. They evaluated twelve markers with IHC. On univariate analysis, they found the following factors to be prognostic: PSA, Gleason score, lymph node positivity, tumor volume, seminal vesicle involvement, margin positive, and on immunohistochemical staining: Ki-67, p53, AR, MMP-2, MMP-9, and HSP27. On multivariate analysis, only Ki-67, seminal vesicle involvement, and margin positivity remained significant. In consideration of those three positive factors, if the patient was positive for 2 or 3 of them, the recurrence rate was 79%, if positive for one, 20%, and if negative for all 3, 4%. Ki-67 was also prognostic in a smaller study of 91 prostatectomy only patients [10]. With a median followup of 46.5 months, 29 (32%) progressed (PSA ≥ 0.2 ng/mL). For the 60% of patients with <5% PSA staining, 5-year disease-free survival was 84%, compared to 42% for those with ≥5% staining (from graph). On multivariate analysis, Ki-67 and Gleason score were prognostic. The final positive study was a multifactorial study [11] of 336 RRP patients, of which 249 had tissue. Lymph node positive patients were included. Failure was defined as PSA > 0.5 ng/mL. Five-year DFS was 63%, and 10-year was 41% with a median followup of 66 months. They utilized immunohistochemical staining for Ki-67, enhancer of zeste homolog 2 (EZH2), (discussed below) and minichromosome maintenance protein 7 (MMC7) (discussed below). They also used fluorescence in situ hybridization (FISH) for EIF3S3, a chromosome abnormality they had explored previously. On multivariate analysis considering EZH2, Ki-67, MCM7, Gleason score, pathologic stage, and PSA, the factors of pathologic stage, Ki-67 and MCM7 were significant predictive factors. From the graphs, for staining 0-1%, 10-year disease-free survival was 65%, for 2–15% was 38%, and for >15% was 27%. Demonstrative as to how other factors can have an effect of prognostic ability, in patients that were lymph node negative with an undetectable postsurgery PSA, Ki-67 dropped out and EZH2, MCM7, and PSA were prognostic. In Gleason, less than 7 patients, Ki-67 was the only significant factor; the 15 patients with Ki-67 staining of >1% had a 5- and 10-year disease-free survival of 70% and 45%, respectively (from the graph), compared to 100% for Ki-67 of 0-1%. No details of interaction with pathologic variables were given.Table 1
Ki-67 and outcomes after radical prostatectomy. The table indicates whether Ki-67 was positive on univariate or multivariate analysis for predicting failure. The failure of the entire cohort is given and then the outcomes for patients where Ki-67 was elevated versus not elevated.
Study#ptsMed (mean) months f/uInclude LN+ (#)Include Adj RX (#)Definition of failure@Univariate positiveMultivariate positiveGroup overall failureMarker elevated outcomeMarker not elevated outcomeKhatami et al. [6]50(63)NoNRPSA > 0.2 × 2YesNR18%NRNRBubendorf et al. [7]137(64)Yes (34)Yes (60)PSA, PAP, or ALP elevated*YesYes29%65% 5-yr dfs78% 5-yr dfsMay et al. [8]52846 (49)Yes (38)NoPSA > 0.2YesYes19% 5-yr dfs 78%70% 5-yr dfs88% 5-yr dfsMiyake et al. [9]19363Yes (13)NoPSA > 0.2YesYes21% 5-yr dfs 79%A: 79% recurB: 20% recurC: 4% recurRubio et al. [10]9146.5NRNoPSA ≥0.2YesYes32%42% 5-yr dfs84% 5-yr dfsLaitinen et al. [11]22966 (62)Yes (NR)Yes (4)PSA ≥ 0.5 × 2YesYes63% 5-yr dfs10-yr 41%5/10-yr dfs 2–15% : 62%/38% 16+% : 42%/27%5/10-yr dfs0-1% : 92%/65%Moul et al. [4]162(54)Yes (1)NRPSA > 0.2 × 2YesNo38%31% 6-yr dfs72% 6-yr dfsBettencort et al. [12] (same patients as [4] above)180(53)Yes (1)NRPSA > 0.2 × 2YesNo60% 5-yr dfs5-yr dfs1+ 69% 2–4+ 44%5-yr dfs83%Vis et al. [15]112113Yes (6)NoClinical only@Yes for clinical recurrenceNoClinical dfs 5-yr 52% 10-yr 42%Clinical dfs5-yr 75%10-yr 75%NR: not reported.@Most studies include biopsy-proven local recurrence and radiographic distant metastasis as failure in addition to PSA.*Three factors: Ki-67, SV+, margin+; A = 2-3 factors, B = one factor, C = all 3 negative.Even though those studies showed on multivariate analysis Ki-67 was able to predict failure, other than the correlation shown in the Miyake et al. study [9], none of the studies evaluated as to how Ki-67 improved the predictive ability of the standard prognostic factors. Therefore, its utility remains uncertain, which is further compounded by the studies that show that Ki-67 is not predictive for failure. In that regard, in a study of 162 patients undergoing RRP (median followup 4.5 years, PSA failure > 0.2 ng/mL at least twice), Ki-67 staining was measured <2 in 62% of the tumors and 2–4 in 38% [4]. On multivariate analysis including pathology stage, race, Gleason score, age, p53, bcl2, and Ki-67 (MIB-1) levels, p53 and bcl-2 were prognostic, but not Ki-67. The findings were confirmed in another study of the same patients [12]. From the cohort of 335 patients, this time 180 had available tissue. With a mean followup 4.4 years, and failure defined as PSA > 0.2 ng/mL twice, the overall 5-yr biochemical failure-free survival (BFFS) was 60%. Ninety per cent had measurable Ki-67 (MIB-1) staining. In 18 patients with negative or rare Ki-67 staining, 3 (5%) progressed for an 83% 5-year biochemical-free survival (BFFS); of 90 that stained 1+, 23 (37%) progressed for a 69% 5-year BFFS; and in 72 that were 2–4+, 36 (58%) progressed with a 5-yr BFFS of 44%. On multivariate analysis, stage and Gleason score were significant prognostic factors and Ki-67 was only marginal. In a subgroup analysis, Ki-67 appeared to differentiate failure in Gleason 2–6 patients, but not in higher grade. A third paper including at least some of the same patients (132) [13] showed Ki-67 positive patients had a higher recurrence rate but again the findings were not significant on multivariate analysis. In a different approach [14], 41 prostatectomy patients who failed within two years (PSA > 0.2 ng/mL) were matched for pathologic stage, PSA, and Gleason score with 41 patients who did not have a rising PSA by three years. They found no difference in Ki-67, p53, and bcl-2 between the two groups. Finally, in an evaluation of 112 prostatectomy patients [15], for patients with low MIB-1 staining, the 5- and 10-year clinical disease-free survival was 75% for both, and for high staining patients was 52 and 42%, respectively. In spite of this difference, MIB-1 was not predictive of recurrence or death on multivariate analysis.
## 3.2. Apoptosis-Related Markers (p53, bcl-2, and MDM2)
Cellular stress triggers (upregulates) p53, which accumulates in cells and leads to either cell cycle pause and repair or apoptosis. Loss of p53 function potentially can allow a cell that would normally undergo apoptosis to survive an otherwise lethal event. Bcl-2 is antiapoptotic and elevated levels can also conceptually allow cells to survive an otherwise lethal event. Mouse double minute-2 (MDM2) has an antiapoptotic effect by binding to p53 and inactivating it. Wild-type or normal p53 is cleared rapidly from cells, so measurable p53 is usually dysfunctional. Therefore, counter-intuitively, an elevated p53 actually represents decreased p53 function.As with Ki-67, there are several positive and negative studies (Table2). In 71 patients operated on before 1984 [16] with a median followup of 10.6 years, 15-year cause-specific survival for p53 positive patients was 38% and for p53 negative patients was 87%. They also found that the 15-year cause-specific survival for retinoblastoma protein (Rb) positive patients was 66% and Rb negative was 92%. On multivariate analysis, the combination of p53 and Rb was the strongest predictor of failure. There was no analysis with the common prognostic factors (stage, PSA, or Gleason score). A later study in 76 RRP patients with a median followup of 50 months found that 27% of the patients with <40% positive p53 staining recurred versus 6/10 (60%) with more than 40% staining [17]. On univariate analysis, nuclear grade, pathologic stage, and p53 were significant, but on multivariate analysis, only p53 was significant. In another prostatectomy study, 263 patients had a mean followup of 55 months and 39% failed [18]. Seventy-eight received adjuvant treatment. They found clustering of p53 positive cells (>12 cells) to be more predictive than percentage of positive cells. On multivariate analysis, both clustering and percentage p53 positive, along with PSA, path stage, Gleason score, and lymph node positivity were predictive for failure.Table 2
p53, bcl-2, and outcomes after radical prostatectomy. The table indicates whether p53 and bcl-2 was positive on univariate or multivariate analysis for predicting failure. The failure of the entire cohort is given and then the outcomes for patients where the marker was elevated versus not elevated.
Study#ptsMed (mean) months f/uInclude LN+ (n)Include Adj RX (n)Definition of failure@Univariate positiveMultivariate positiveGroup overall failureMarker elevated outcomeMarker not elevated outcomeP53Theodorescu et al. [16]71127Yes (1)NoClinical,PSA > 0.2YesYes51% failed15-yr cause-specific 38%15-yr cause-specific 87%Kuczyk et al. [17]7650Yes (6)NoClinicalYesYes32% failed20% died ca33% died ca16% died caQuinn et al. [18]263(56)Yes (5)Yes (99)PSA ≥ 0.4 × 2YesYes39% failed32% 5-yr dfs83% 5-yr dfsMoul et al. [4]162(54)Yes (1)NRPSA > 0.2 × 2YesYes38%39% 6-yr dfs76% 6-yr dfsBauer et al. [19] same patients as [4]175(55)Yes (1)NRPSA > 0.2 × 2YesYes38%45% failed5-yr dfs 49%23% failed5-yr dfs 78%Brewster et al. [20]76(38)NRNoPSA ≥ 0.2 × 2YesYes30%41% failed21% failedGoto et al. [21]11940NRNoPSA > 0.2NoNo13% failed40% failed10% failedMiyake et al. [9]19363Yes (13)NoPSA > 0.2YesNo21% failed5-yr dfs 79%NRNRWu et al. [23]7036.5NRNRPSA > 0.2 × 2NoNo30%44% failed26% failedOsman et al. [24]8665NRYes (33)3 × PSA increaseNRYesNR0 5-yr dfs68% 5-yr dfsBCL-2Bauer et al. [19]175(55)Yes (1)NRPSA > 0.2 × 2YesYes38% failed57% failed5-yr dfs 33%31% failed5-yr dfs 69%38% failedBCL2+ P53+5-yr dfs 25%BCL2− P53−5-yr dfs 80%Brewster et al. [20]76(38)NRNoPSA> 0.2 × 2YesYes30%53% failed24% failedGoto et al. [21]11940NRNoPSA > 0.2NoNo13% failed21% failed10% failedBubendorf et al. [22]137(64)Yes (34)Yes (60)PSA, PAP, ALKPNRNo19% failed5 yr dfs 78%10-yr dfs 18%10-yr dfs 52%Miyake et al. [9]19363Yes (13)NoPSA > 0.2NoNo21% failedNRNRWu et al. [23]7036.5NRNRPSA > 0.2 × 2YesYes30%67% failed28% failedNR: not reported.Most studies include clinical failure: biopsy-proven local recurrence and/or radiographic distant metastasis in addition to PSA.Several studies have considered p53 in conjunction with other factors such as bcl-2, and Ki-67. In one study consisting of 162 patients undergoing RRP (median followup 4.5 years, PSA failure > 0.2 ng/mL at least twice) p53 was measured negative in 31% of the tumors and positive (1–4+) in 69%. Bcl-2 was measured negative in 73% of the tumors and positive (1–4+) in 27% [4]. On multivariate analysis including pathology stage, race, Gleason score, age, p53, bcl-2, and Ki-67 (MIB-1) levels, p53 and bcl-2 were prognostic. There was no correlation as to what the markers added to the common prognostic markers. In another study from the same patient cohort, 175 patients underwent radical prostatectomy [19]. With a mean followup of 4.6 years, p53 staining was positive in 65% and the 5-year failure rate was 51%, compared to 22% for the patients that stained negative. Bcl-2 staining was positive in 27% and the 5-year failure rate was 67%, compared to 31% for the patients that stained negative. For patients that were both p53 and bcl-2 positive, the five-year failure rate was 75% compared to 20% for those that were negative for both. On multivariate analysis, stage, race, bcl-2, and p53 were all prognostic. Again, there was no indication of whether they enhanced the standard markers. Interestingly, in yet another analysis of some of the same patient cohort (132 patients) with median followup of 3.9 years, p53 positive patients had a higher recurrence rate but it was not significant on multivariate analysis [12]. Another study of p53 and bcl-2 looked at 76 prostatectomy patients with a mean followup of 38 months, 23 (30%) of whom failed [20]. Fifty-seven percent were p53 positive on prostatectomy tissue and 41% failed compared to 21% with normal p53. Twenty percent were bcl-2 aberrant on prostatectomy tissue and 53% failed compared to 24% of those with normal bcl-2. In an additional study of 119 radical prostatectomy patients receiving no neoadjuvant treatment and with a median followup of 3.3 years, 16 (13%) failed [21]. On multivariate analysis, bcl-2, p53, Ki-67, PSA, Gleason score, Capsular penetration, age, and margin positivity were not predictive, but SV involvement and caveolin-1 (see below) were.In an older cohort of patients (22% of the failures predated PSA), 30 received adjuvant treatment (mostly radiation) [22]. With a mean followup of 5.2 years, bcl-2 positivity was predictive of recurrence, but only stage pT3 and Ki-67 were predictive of failure (not p53). From the graph, for elevated bcl-2, 10-year disease-free survival was 18% and for nonelevated bcl-2 was 52%. Only 8% overexpressed p53. Like p53, it is also not uncommon for bcl-2 staining to be too low (<5%) to be meaningful [10].Miyake et al. evaluated 193 prostatectomy patients with twelve markers on IHC, including p53 [9]. While it was predictive on univariate analysis, it was not on multivariate. Bcl-2 was not predictive for either. In a study of 70 pathological T2 patients [23] with a median followup of 36.5 months, 30% suffered biochemical relapse (PSA > 0.2 ng/mL times two), sixteen patients were p53 positive, and 44% suffered PSA relapse which was not significantly different than the p53 negative patients (26% relapse). Only 3 (4%) patients were bcl-2 positive, but 2 (67%) relapsed, which was significantly higher than the bcl-2 negative patients (28% failure). Finally, in a study [24] of 86 patients (median followup 65 months) with an undetectable PSA after radical prostatectomy (38% received neoadjuvant treatment), 20% overexpressed p53 and had a higher risk of relapse. The 33% that overexpressed MDM2 also had a higher risk of relapse. No details were given, but on multivariate analysis, both p53 and p21 were predictive. Stage and MDM2 were not. Interestingly, there was no association with p53 overexpression and p21 or MDM2. As with all the studies discussed, there was no real analysis for correlation with standard predictive factors, so the real predictive power of these markers remains elusive.
## 3.3. E-Cadherin and Other Adhesion Molecules
Calcium-dependent adhesion molecules (cadherins) are transmembrane proteins that play a role in cell adhesion. E-cadherin is a subtype found in epithelial tissue with extracellular, transmembrane, and intracellular domains. The intracellular domain binds to beta catenin. In cancer, E-cadherin downregulation theoretically reduces cell adhesion resulting in increased cell motility and dissemination.In a study of 70 pathological T2 patients [23] with a median followup of 36.5 months, 30% suffered biochemical relapse (PSA > 0.2 ng/mL times two). Thirty-nine patients (56%) had aberrant E-cadherin staining, with a 44% PSA relapse rate, which was significantly worse than those with normal E-cadherin staining (13% recurrence). In 104 prostatectomy patients [25] (7 lymph node positive), low E-cadherin, Gleason score, and pathologic stage were predictive of biochemical failure (PSA > 0.5 ng/mL) on multivariate analysis. For clinical failure, pathological stage dropped out and elevated N-cadherin was significant. For patients with low E-cadherin, the 10-year biochemical failure-free survival was 14%, versus 33% for those with elevated levels. For N-cadherin, low levels resulted in 33% biochemical failure-free survival and high levels 14%. They found that the E-cadherin to N-cadherin ratio was more powerful than either alone, but did not provide specifics nor any details on the modification of the predictive power of standard factors. In a study of 67 radical prostatectomy patients [26] with a median followup of 54 months, 27 (40%) recurred clinically, 7 locally, and 20 systemically. When evaluated with IHC for E-cadherin, a cut point of 40% staining was chosen. For the 13 that stained less than 40%, 2 (15%) died of cancer and for the 54 that stained >40%, 14 (26%) died of cancer, but the difference was nonsignificant. E-cadherin was not predictive on univariate or multivariate analysis for either recurrence or survival. In 128 radical prostatectomy patients [27] without adjuvant treatment, tissue microarrays were made and stained with IHC staining. Normal was considered >70% staining. For nonmetastatic prostate cancer, 18% had aberrant staining. With a median followup of 23 months, 38% of the failures and 20% of the nonfailures had aberrant staining, a nonsignificant difference. Similarly, in a microarray study (discussed below), Rhodes et al. [28] found that a decreased E-cadherin to EZH2 ratio resulted in an increased rate of biochemical failure after radical prostatectomy.Brewster et al. [20] studied 76 prostatectomy patients; 49% were E-cadherin aberrant on prostatectomy tissue and 37% failed compared to 22% with normal E-cadherin. On multivariate analysis, it was not predictive when considered with p53, bcl-2, Gleason score, and margins. They also evaluated another apparent adhesion molecule in the form of the cell surface glycoprotein CD44. Sixty-four percent were CD44 minimal or absent on prostatectomy tissue. Of those with normal staining, 8% failed compared to 43% with aberrant staining. On multivariate analysis, it was not predictive when considered with p53, bcl-2, Gleason score, and margins. Two other studies evaluated CD44. In 97 radical prostatectomy patients [29] with median followup of 84 months, utilizing PSA of >1.0 as failure, most (86%) patients were positive for CD44, so risk was determined by graded intensity of the staining. Decreased expression increased the risk of failure. On univariate analysis, loss of CD44 and cd4v6 were predictive of clinical failure, but only CD44 was predictive for biochemical failure. In the other study, 99 patients had mean followup of 40 months and 26% suffered a biochemical recurrence [30]. CD44 was evaluated via an intensity and percent staining score, and 47% were downregulated. The 3-year recurrence-free survival was 77% for the nondown-regulated patients versus 48% for those with CD44 downregulation. It was not a significant predictor on multivariate analysis, when considered with p34.In none of these studies was there an assessment of how it modified the predictive ability of the standard prognostic factors.
## 3.4. EZH2
The Enhancer of Zeste 2 (EZH2) gene codes for polycomb group proteins that effect chromatin and silence genes. When overexpressed, it appears to be associated with tumorigenesis. In a study involving multiple cancers [31], 104 radical prostatectomy patients with a median followup of 104 months were evaluated with staining for EZH2. For low EZH2 staining, the 5- and 10-year cause-specific survival was 99% and 93%, respectively. For the high staining group, it was 89% and 53%, respectively. On univariate analysis, upper quartile EZH2 staining was predictive for clinical recurrence and on multivariate analysis was predictive for distant metastasis and death. In another study of 64 patients [32], tissue was stained for EZH2 and if the intensity was ≥3, 10/32 (31%) failed versus 3/32 (9%) if the staining was <3. It was a significant factor on multivariate analysis along with margin status, tumor size, Gleason score, and PSA. Finally, in a study (see Ki-67 above) [11] of 249 prostatectomy patients, five- and 10-year disease-free survival was 63% and 41%, respectively. On multivariate analysis, pathologic stage, Ki-67 and MCM7 were significant predictive factors (EZH2 was not). In patients that were lymph node negative with an undetectable postsurgery EZH2, MCM7 and PSA were prognostic. In Gleason less than 7 patients, Ki-67 was the only significant factor. There was no evaluation of whether this added to the predictive ability of standard factors.
## 3.5. Cyclin-Dependent Kinases (and Their Effectors)
Cyclin dependent kinases (CDKs) are protein kinases involved in the regulation of the cell’s progression though the cell cycle. As most cancers have dysfunctional cell cycle control, the kinases are implicated as part of the aberrancy. Cyclin D1 is specific for transition through G1/S. It has its effect by binding with cyclin dependent kinases 4 and 6 forming a complex that phosphorylates and inactivates the retinoblastoma protein (Rb). Overexpression of cyclin D1 has been associated with the malignant phenotype and its progression. There are several known inhibitors of cyclin dependent kinases. For example, p16INK4a (cyclin-dependent kinase inhibitor 2A) inactivates Cdk4 and CdK6 and thereby acts as a tumor suppressor (by blocking the phosphorylation of the Rb gene, which prevents transit through G1). Loss of p16 enables abnormal progression through the cell cycle, increasing the malignant potential. P21-waf1 encodes a cyclin dependent kinase inhibitor (p21 or cyclin dependent kinase inhibitor 1A), inhibiting CDKs 2 and 4, which leads to arrest at G1. It is induced by p53 (thus elevated p53 can lead to arrest at G1 through this route). P27Kip1 (cyclin dependent kinase inhibitor 1B) is also involved in G1 arrest by inhibiting cyclin dependent Cdk2 complexes E and A and D-Cdk4. Therefore, a decrease in p27 should result in increased proliferation. Lastly, p34cdc2 (cell division control protein 2) is a component that forms a kinase by binding with cyclin B1 (forming maturation-promoting factor (MPF)) that regulates G2/M transition and promotes mitosis).In a study [24] of 86 patients with an undetectable PSA after radical prostatectomy (38% received neoadjuvant treatment), 33% overexpressed p21Cip, and this was associated with a higher risk of relapse. No details were given, but on multivariate analysis, both p53 and p21 were predictive of relapse whereas stage and MDM2 were not.In one study, where the primary goal was to assess the association between pathological features and biomarker expression [33], p27Kip expression was evaluated in 113 prostatectomy specimens (median followup 4.6 years, 21% neoadjuvant androgen ablation), and correlated with outcome. Low p27 nuclear staining was a poor prognostic sign. On multivariate analysis, p27, seminal vesicle status and margin status were all predictive for recurrence, but no details were given. In a second study of 96 stage C lymph node negative patients undergoing radical prostatectomy with a median followup of 9.5 years [34], p27 Kip1 staining correlated with Gleason score (higher grades had decreased levels). The 9-year recurrence-free survival for levels ≤10% was 17%, for levels 11–50% was 47%, and for >50% was 67%. There was no correlation with the standard factors. In a third p27 study [35] of 86 patients (after excluding those that received adjuvant treatment), multivariate analysis demonstrated only pathologic stage and p27 to be predictive at a median followup of 40 months. High Gleason score was associated with low p27 staining. Thirty percent was the breakpoint between high and low staining. Fifty percent of patients with low staining failed (PSA > 0.4) and 78% with high staining failed. In another study with 95 patients [36], loss of p27 (<10%) on multivariate analysis was significant for recurrence, but not for survival. With a median followup of 49 months, 33% of the p27 negative patients failed versus 23% for the p27 positive patients (median followup 59 months). Another study was of 161 prostatectomy patients [37], which were divided into organ confined (n=76, median followup 42 months) and nonorgan confined (n=85, median followup 38 months) patients. p27 staining was performed on the biopsy, but not the final pathology specimen, and patients were not evaluated for the specific impact of positive margins, seminal vesicle involvement, or lymph node involvement. For the organ-confined patients, the 5-year recurrence rate was 26%, but 9% for those with high p27 staining and 37% with low (<45%) staining. In this subgroup, p27 was predictive for failure. In the nonorgan confined patients, the recurrence rate was 44%, but p27 was not predictive of failure in these more advanced patients and the actual effect on failure was not stated. In an evaluation [15] of 112 prostatectomy patients, 92 had adequate p27 staining. Thirty-five (38%) stained less than 50% and were classified as low staining. Based on clinical parameters, their 5- and 10-year disease-free survival were 37% and 26%, respectively. For the high staining patients, it was 79% and 77%, respectively. p27 predicted for clinical recurrence and cause-specific survival.Finally, in a study of 104 radical prostatectomy patients with a median followup of 56 months [38], p27 was determined by the per cent of nuclei staining, with the median of 64% used as the breakpoint between high and low. On multivariate analysis, pathologic stage and PSA were significant predictors of recurrence, but not p27.p16 has been evaluated in several studies. In 206 radical prostatectomy patients (18% with neoadjuvant androgen ablation) with a median followup of 72 months, one group [39] found positive p16INK4a staining to be associated with recurrence. On multivariate analysis, p16, PSA, Gleason score, and margin status were all predictive, but no actual outcome data was given. In another study [40], 88 prostatectomy patients (39% neoadjuvant treatment) with a median followup of 65 months stained for P16. Unlike Henshall et al. [39] (which called low <1%), their breakpoint was 5% positive nuclear staining. For the 38 patients that overexpressed, 21 (55%) failed versus 26% of the 50 under expressing patients. p16 was associated with PSA levels and was not an independent prognostic factor on multivariate analysis. They also did not report specifics on outcome. In a third study of 104 radical prostatectomy patients with a median followup of 56 months [41] the multivariate analysis for survival was positive for p16, age, grade, capsular penetration, and seminal vesicle involvement. They scored p16 by a fluorescence index. The low group had a 5-year survival of 78% versus 43% for the intermediate group (P=.005) and 42% for the high index group. There was no outcome data accounting for the standard factors. Ploidy or S phase was not predictive.In analysis of cyclin D1 and p34cdc2, 140 patients [42] with a median followup of 42 months were evaluated. Failure was defined as a PSA > 0.4. In patients that were p34cdc2 negative, 10% failed versus 26% that were positive. For Gleason 7 or greater, the failure rate was 26% for p34cdc2 negative and 38% for positive. On multivariate analysis, only p34cdc2 and Gleason score were predictive and cyclin D1 and ploidy were not. p34 was also evaluated in a study of 99 patients. With a mean followup of 40 months, 26% suffered a biochemical recurrence [30]. p34 was evaluated via an intensity and percent staining score and 61% were determined to have overexpressed p34. The 4-year recurrence-free survival (from the curves) was 98% for the nonover expressed patients versus 47% for those over expressing p34. It was a significant predictor on multivariate analysis, but there was no evaluation of whether it enhanced the predictive ability of standard factors.
## 3.6. Cathepsin-D
Cathepsins are proteases (i.e., involved in protein degradation) usually housed in lysosomes that proteolyse proteins that regulate cell growth. In a study [43], 105 radical prostatectomy patients were evaluated for cathepsin D. It was not prognostic on either univariate or multivariate analysis, but probably because the expression rate was extremely high at 98%.
## 3.7. Chondroitin Sulfate
Chondroitin sulfate is a structural glycosaminoglycan of the extracellular matrix that helps regulate cell activity. Ricciardelli et al. [44] studied 157 prostatectomy patients after exclusion of adjuvant and neoadjuvant treatment; failure was defined as a PSA > 0.2 and median followup was 47 months. They used an antibody to chondroitin sulfate and read the slides via an image capture technique with automated analysis. There was a twofold difference between this study and previous studies for the absolute value of the mean due to calibration differences, which demonstrates the lack of uniformity in these studies. The median was chosen as the cut point, although the most robust point was slightly above that. On multivariate analysis, chondroitin sulfate, Gleason score, preoperative PSA, and pathological stage were all predictive. For patients with low staining, 23% failed for a 5-year PSA failure rate of 33% versus 51% with high staining failing for a 5-year failure rate of 51%. There was some correlative analysis between chondroitin staining and other predictive factors. For patients with a preoperative PSA less than 10, 9% with low chondroitin sulfate staining failed versus 48% with high levels. In a more specific analysis, the five-year failure rate for Gleason 5–7 patients with low chondroitin levels and low PSA was 11% compared to 44% for low chondroitin staining patients with a high PSA. Further, Gleason 5–7 patients with high chondroitin sulfate staining and low PSA had a five-year failure rate of 56% versus 72% for high staining and high PSA. There was no evaluation done with the integration of pathology findings.
## 3.8. Hepsin and PIM1
Hepsin is a transmembrane serine protease whose exact function is unknown, but when upregulated appears to express a malignant phenotype. PIM1 encodes a protein kinase that promotes G1/S transition by upregulation of CDK2, facilitating cell proliferation and survival. One study [45] utilized human specimens and cell lines for comparison of malignant and benign tissue. Out of several hundred candidate genes, hepsin and PIM1 expression proteins were selected for further analysis. Hepsin was increased in malignant prostate tissue versus benign, but staining was greatest in PIN. In radical prostatectomy patients, low or absent hepsin increased failure. On multivariate analysis, both hepsin and Gleason score were predictive of failure. They also tested for PIM1. It was upregulated in prostate cancer and decreased levels were associated with increased PSA level in 135 patients with localized prostate cancer. It was significant on multivariate along with Gleason score 4-5 and PSA. They concluded that lower PIM1 levels were strongly associated with an increased risk of relapse. There was no outcome correlation with standard factors with either marker.
## 3.9. Cox-2
In a study of 91 prostatectomy patients [10], with a median followup of 46.5 months, 29 (32%) progressed (PSA > 0.2 ng/mL). A score was developed for percent and intensity of staining for Cox-2. For no staining, the failure rate was 26% versus 60% for 1–4, but then dropped back to 15% for 5–12. While it was a predictive marker on univariate analysis, it was not on multivariate.
## 3.10. Laminin Receptor (Ribosomal Protein SA)
Laminins are glycoproteins located in the basement membrane (basal lamina) that affect cell adhesion and migration as well as differentiation and survival. Laminin receptor (LR) is detected via the MLuC5 antibody. In an initial evaluation [46] in 140 patients, it appears that laminin receptor positivity might be associated with recurrence. Overall, the 3-year biochemical failure-free survival was 68%, but for LR positive patients the failure was 45% and for negative patients it was 7%. There was no correlation with PSA and Gleason score. The followup was only 20 months, and a later paper [47] showed that LR measurement of the biopsy tissue was not significantly predictive for biochemical progression, probably due to a lack of concordance between the measurements in biopsy tissue versus the larger tumor specimen.
## 3.11. Chromogranin A (CGA)
In a study of 528 prostatectomy patients [8] excluding neoadjuvant and adjuvant androgen ablation and radiation therapy, with a median followup of 46 months, 101 (19%) failed for a 5-year disease-free (PSA < 0.2 ng/mL) rate of 78%. The tissue was evaluated using IHC staining for Ki-67 and chromogranin A (CGA). On multivariate analysis, Gleason score > 4 + 3, CGA positive, lymph node positive, PSA >20 ng/mL, and Ki-67 were prognostic, while pathologic stage T3 and margin positivity were not. For the 32 CGA positive patients, the 5-year biochemical recurrence-free survival was 48% and for the 496 CGA negative it was 80%. Because of the small number of CGA positive patients, the only specific information was given on whether there was modification of prognosis of the standard factors was for Gleason <7 patients, where for the 304 CGA negative patients, 8% failed and for the 12 CGA positive, 25%.
## 3.12. Minichromosomal Maintenance Protein 7 (MCM7)
Minichromosome maintenance protein 7 (MCM7) appears to be a facilitator of DNA replication, so upregulation would be expected to increase proliferation. It has been found on microarray analyses that MCM7 is frequently amplified in prostate cancer. In an evaluation of prostatectomy patients [48], 52/68 (77%) with MCM7 amplification relapsed versus 7/57 (12%) without amplification. In a study discussed above (see Ki-67) [11], pathologic stage, Ki-67, and MCM7 were significant predictive factors. In evaluation of patients that were lymph node negative with an undetectable postsurgery, EZH2, MCM7, and PSA were prognostic. In both studies, there was no clinical correlation, so these interesting findings are of uncertain significance.
## 3.13. Histones
Histones are intranuclear proteins in chromatin around which DNA is “wound”, the modification of which influences their interaction with the DNA and affects some processes such as mitosis and gene regulation. In 183 radical prostatectomy patients, those that received androgen ablation were excluded. The median followup was 60 months and failure was defined as PSA > 0.2 ng/mL [49]. In order to evaluate sites on histones H3 and H4 with acetylation and dimethylation staining, 5 different sites were identified by using a clustering algorithm. While not independently predictive, when combined with Gleason score, the findings yielded prognostic information. From the graph, Gleason < 7 patients that were histone “favorable” had an 84% disease-free survival, while those unfavorable had a 58% disease-free survival. For Gleason 7–10, the favorable group had a disease-free survival of 46% versus 20% for the unfavorable.
## 3.14. TMPRSS2 : ERG Fusion
TMPRSS2 (transmembrane protease, serine 2) is an androgen-regulated gene found on chromosome 21 that encodes a transmembrane protease. In prostate cancer, it can be fused with genes for the ETS transcription factors, such as ERG (resulting in TMPRSS2 : ERG). This indirectly places ERG under androgen transcriptional control. There are multiple variants of this fusion. This can be detected through either RT-PCR or fluorescence in situ hybridization (FISH). In 165 prostatectomy patients with available frozen tissue [50] with a median followup of 20 months, tissue was evaluated for TMPRSS2 : ERG fusion gene and 49% was positive. For the fusion gene positive patients, 46% failed compared to 7% in fusion negative patients. On multivariate analysis, the fusion gene was the most predictive factor, followed by grade. Evaluation was made for different Gleason and pathologic findings. For Gleason 5-6 patients, 33% of the gene positive patients failed, versus 5% for the gene negative. For Gleason 7 and Gleason 8–10, it was 48% versus 7% and 75% versus 14%, respectively. For organ-confined patients, gene positive patients had a recurrence rate of 34% versus 10% for gene negative. For extraprostatic extension and seminal vesicle positive patients, it was 53% versus 3% and 67% versus 34%, respectively. For both Gleason score and pathological findings, all the differences were statistically significant, except for the seminal vesicle involved patients. Another study, started with 248 radical prostatectomy patients [51], but only 150 were ultimately evaluable by FISH. Of those, 50 (33%) were found to have TMPRSS2 : ERG rearrangement. With a median followup of 66 months and failure defined as two rises of PSA > 0.5 ng/mL, on multivariate analysis, Ki-67, pathologic stage, and TMPRSS2 : ERG fusion were significant, not Gleason score or PSA [52]. Yoshimoto et al. evaluated specimens from 125 radical prostatectomy patients, 122 of which had clinical followup and with a median followup, 49% had failed (PSA > 0.2 ng/mL). Neoadjuvant androgen ablation was allowed, and 2 patients were lymph node positive. FISH was used to evaluate for TMPRSS2 : ERG, and 48% were found to have rearrangements resulting in a 5-year biochemical failure-free survival (BFFS) of 46%. For those that were negative, 5-yr BFFS was 62% (P=.0523). Expanding on their previous work, they also evaluated for PTEN deletion by FISH. Only 82 of the 125 patients could be evaluated. There was no difference in 5-yr BFFS between those that were deletion negative and positive, but if they divided the deleted patients into hemizygous and homozygous deletions, they found that all the homozygous patients had failed by 5 years. If patients had both the PTEN deletion and the TMPRSS2 : ERG fusion, 5-yr BFFS was 30% versus 59% if they had neither (P=.001). They did not test to see whether these markers augmented the predictive ability of the three standard factors (Stage, Gleason score, or PSA), although on multivariate analysis only Gleason score, the TMPRSS2 : ERG/PTEN combination and homozygous PTEN deletion were prognostically significant. A study [53] using microarray to compare genes between benign and malignant cells found that ERG was the most commonly over expressed. Then utilizing QRT-PCR, they analyzed 114 prostate cancer patients and found ERG1 over expressed in 62%. Ninety-five patients had detectable levels and for a >100 over expression, the 5-year biochemical failure free-survival (from the graph) was 88%, for 2–100 fold 80% and for <2 fold 36%. On multivariate analysis, ERG1 (>100 versus <2) and Gleason (8–10) were significant, but not race, PSA, pathologic stage, margin positive, or seminal vesicle positivity.Not all studies found TMPRSS2 : ERG to be prognostic. In one study [54], two subgroups were taken from larger prospective studies and ultimate outcome collected from SEER data. This yielded no failure data and only crude followup of cancer-specific survival. Of the subgroups, only 57% could be scored for the fusion. They reported no association between the occurrence of TMPRSS2 : ERG (positive in 36% of the patients) and cancer specific survival. Researchers in a study [55] of 521 radical prostatectomy patients with 95 month median followup utilized FISH and found 42% had TMPRSS2 : ERG abnormalities. It was not associated with recurrence, metastasis or death. Finally, in a study of 54 patients [56], 35 (65%) had gene rearrangement, which was present in 60% of the nonfailing patients and 65% of the failing patients. In the evaluation of 28 benign prostate tissues, there were no rearrangements.
## 3.15. PTEN
The phosphatase and tensin homologue (PTEN) gene modulates the phosphotidylinositol 3-kinase (PI3K) pathway, a regulator of the Akt pathway. Lack of PTEN allows for upregulation of Akt and other cell cycle factors, increasing cell survival. As noted above [52] in the TMPRSS2 : ERG discussion, on multivariate analysis, homozygous PTEN deletion and the TMPRSS2 : ERG fusion were prognostically significant. In an earlier study specifically evaluating PTEN, the same authors [57] utilized fluorescence in situ hybridization (FISH) to PTEN in 107 prostatectomy patients. Tissue was scored as showing no deletions (56%), hemizygous deletions (39%), or homozygous deletions (5%). On Cox proportion hazard analysis, for univariate analysis, perineural invasion, seminal vesicle positive (SV+), extraprostatic extension (EPE), Gleason score, PSA, lymph node positivity, and PTEN deletion were all predictive. On multivariate analysis, only EPE, SV+, and PTEN were predictive. For PTEN, from the graph, 5-year PSA (>0.2 ng/mL) failure-free survival was 0 for the 5 homozygous patients, 48% for the 42 hemizygous patients, and 60% for the 60 patients without deletion. There was no discussion as to how PTEN modified the predictive ability of standard factors. In a separate study of 104 radical prostatectomy patients with a median followup of 56 months [38], PTEN was scored as an index based on percent staining and intensity. On multivariate analysis, pathologic stage and PSA were significant predictors of recurrence, but not PTEN.
## 3.16. Epidermal Growth Factor Receptors (EGFR)
Epidermal growth factors are extracellular ligands controlled by the cell surface epidermal growth factor receptors, which are tyrosine kinase receptors. When activated, they initiate a cascade of signal transduction (i.e., though the Akt pathway) that results in cell proliferation. If the receptor is mutated in the “on” position (i.e., over expression), the result could be uncontrolled proliferation. Her-2/neu (c-erb B2) encodes a tyrosine kinase growth factor receptor similar to the epidermal growth factor receptors and has been linked with advanced disease. In one study, [43] 105 radical prostatectomy patients were evaluated for epidermal growth factor receptor (EGFR). The expression rate was 48%, but it was not prognostic on either univariate or multivariate analysis. In 113 prostatectomy patients with a mean followup of 42 months [58], utilizing IHC, membranous and cytoplasmic staining was given a composite score so that ≥3 was considered positive. With that parameter, 29% of the tissue over expressed and there was no correlation with failure on univariate analysis. Utilizing FISH, it was found that 41% were amplified for Her2, but there was poor correlation with IHC staining (P=.25). While FISH analysis was significant for failure on univariate analysis, it was not a significant predictor of failure on multivariate analysis. In 99 patients with a mean followup of 40 months, 26% suffered a biochemical recurrence [30]. Her 2-neu was evaluated via FISH and 42% were found to be amplified. The 5-year recurrence-free survival was 75% for the nonamplified patients versus 47% for those with Her 2-neu amplification. It was not a significant predictor on multivariate analysis, when considered with p34.
## 3.17. VEGF
In a study of 193 prostatectomy patients [9], twelve markers were evaluated on IHC, including VEGF, but it was not predictive on univariate analysis.
## 3.18. Caveolins
Caveolins are cell membrane proteins involved in endocytosis resulting in invagination of the plasma membrane (caveolae). They appear to be involved in signal transduction with a role in homeostasis and tumorigenesis. Caveolins have been found to be both increased and decreased in cancer so their role is variable and uncertain. In radical prostatectomy patients selected for failing or not failing, 162 lymph node negative patients were identified. With immunohistochemical staining for caveolin 1, 22% were positive and five-year progression-free survival was 43% versus 68% for those that were negative. On multivariate analysis, caveolin 1, Gleason score, extracapsular extension, seminal vesicle involvement, and margin involvement were all predictive [59]. The same group later studied serum levels of caveolin 1. As noted above, in a study [21] of 119 radical prostatectomy patients on multivariate analysis only caveolin 1 staining and SV involvement were predictive on multivariate analysis, but bcl-2, p53, Ki-67, PSA, Gleason score, Capsular penetration, age, and margin positivity were not. For caveolin 1 positive patients, 9/32 (28%) failed versus 7/87 (8%) that were negative. In 232 prostatectomy patients that included lymph node positive and those that received salvage radiation therapy [60], with a median followup of 70 months, the 5-year biochemical-free survival rate was 80%. On multivariate analysis, only Gleason sum (not Caveolin 1 staining) was a significant predictor of failure. When limited to lower risk patients (n=177) with exclusion of lymph node positive, seminal vesicle positive, Gleason > 7, and extracapsular extension/margin positive, caveolin 1 was still not a significant predictor on multivariate analysis. They did find that in evaluating only the recurring patients, those that had caveolin 1 over expression did worse. In a similar study [61], 30% of 152 radical prostatectomy patients (including lymph node positive) stained positive for caveolin 1. It was not predictive on multivariate analysis (only seminal vesicle positivity, margin positivity, and PSA were), but when restricted to patients with organ-confined disease, it was the lone predictive factor. This is somewhat in contradistinction to the low risk patients noted in the study above.
## 3.19. Zinc-Alpha2-Glycoprotein (AZGP1)
Zinc-alpha2-glycoprotein (AZGP1) encodes for a protein historically thought to be involved in lipolysis and thought to have a role in the cachexia of cancer. From a series of 732 radical prostatectomy patients [62], 228 were analyzed. Forty-three percent failed with a PSA rise of ≥0.2 ng/mL. On IHC, tissue was scored as absent or weak versus strong AZGP1 staining. Twenty-nine percent stained weak. Although there were few events, it appears to be predictive of clinical recurrence and distant metastasis, but there was no evaluation as to modification of common prognostic factors. In a gene array study [63] discussed below, AZGP1 was predictive for nonrecurrence.
## 3.20. Alpha Methylacyl CoA Racemase (AMACR)
Alpha methylacyl CoA racemase (AMACR) is a catalytic enzyme (of fatty acids) that is frequently over expressed in prostate cancer, but levels are decreased in advanced cancers as compared to localized. In 204 radical prostatectomy patients [64], IHC was performed for AMACR expression proteins and regression analysis was used to correlate staining with PSA failure (>0.2 ng/mL). With visual scoring on a scale of 1–4, there was no correlation with failure, but with quantitative expression analysis, patients in the lower tertile were more likely to recur. For patients more than 1.11 standard deviations below the cut point, 37.5% failed versus 14.5% if they were above. This was significant on multivariate analysis along with PSA, Gleason score, and margin status, but there was no evaluation as to the actual effect on the prognostic ability of those factors.
## 3.21. Gene Arrays and Panels
With the use of gene expression micro arrays, the hope is that by screening a large number of genes, genes highly predictive of cancer recurrence could be identified. When using probe arrays, multiple genes can be identified that may predict for relapse. Several groups have evaluated this approach in predicting failure postprostatectomy. In a gene expression profile of 225 tumors with a median followup of 8 years [63], it was found that MUC1 was predictive of recurrence and AZGP1 was predictive of nonrecurrence. Both of these genes were predictive on multivariate analysis along with Gleason score, stage, and PSA. There were no actual outcome results given. A similar study [28] of 259 RRP patients with a median followup of 57 months searched also for markers using microarray assay. They found that the combination of EZH2 increased and ECAD decreased was most predictive of 5-year recurrence (38% versus 15% for those without that combination). On multivariate analysis, this ratio was significant along with PSA, margin status, and pathological stage, but not Gleason score. For organ-confined patients that were margin negative, those that were EZH2/ECAD elevated had a 27% recurrence rate, versus 10% for those that had a decreased ratio. They did not report on higher-risk patients. In a different study of 100 lymph node negative prostatectomy patients [65], with a median followup of 70 months an expression analysis of 12,625 transcripts identified 218 genes that were either up- or down regulated. Recurrence was defined as three rising PSA levels. The combination that predicted recurrence was deemed “poor markers”. For Gleason 6-7 cancers, the 5-year disease-free survival was 69%, but was 77% in the good marker group and 47% in the poor marker group. In Gleason 8-9 cancers, the 5-year disease-free survival rate was 26%, but was 67% with good markers and 0 with poor markers. On multivariate analysis, Gleason score and the gene expression markers were predictive of recurrence, but PSA and age were not. Using a postoperative nomogram [66] they identified poor risk patients by nomogram (undefined) who had a 28% 5-year disease-free survival, increasing 50% with good gene markers, but 19% with poor markers. In the nomogram predicted favorable group, 5-year disease-free survival was 81%, which was 87% with good markers and 59% with poor markers. The major limitation of the study is that there were only 21 patients in the training set and 79 patients in the validation set.Another approach is to pool multiple genes in order to try to produce a more powerful predictive model. This has been successful in breast cancer [67, 68]. With that approach [69], using a 70 gene set in it was possible to predict 27/29 “aggressive” and 27/32 “nonaggressive” cancers and predicted 16 of the 18 failures. Unfortunately, it appears only 61 patients were evaluated; there was no indication of how the findings related to standard prognostic factors. In a more comprehensive study [70] of 639 patients selected for systemic recurrence, biochemical (PSA) recurrence and nonrecurrence at 7 years, the groups were evaluated for genes that differed between them. Patients with adjuvant treatment were not excluded and failure was with a PSA > 0.2 and rising. The patients were divided into training and a validation set. Ultimately, a 17-gene panel was determined to be predictive. Clinical models based on Gleason score, and pathological stage (PSA and age were not informative) demonstrated a correlation (area under the curve) of 0.76 (0.74–0.78), while the probe set was 0.85 and the combination of the two was 0.87. They reported that the AUC for the validation set was lower. They compared their results to those of other gene array studies and found that all the other models performed better than the clinical model alone (0.74, ranging from 0.76–0.86), with their 17 gene probe being the highest. All the validation sets were lower than the training sets for these genes. In an exploratory study [71] of 72 prostatectomy patients with a median followup of 28 months, 24% relapsed. After scanning for 59,619 probe sets, over 200 genes could be identified that are associated either positively with relapse. In another exploratory study [72], tissue from 37 failing patients and 42 nonfailing patients was tested with a 22,283-gene probe microarray. The first goal was to see if the identified genes (ultimately 5–8 were used) could correctly identify the failing versus the nonfailing patients, which it did 75% of the time. When combined into a nomogram, the predictive rate increased to 89%. Given that nomograms are the most robust incorporation of the standard prognostic factors; this would represent an example of how molecular data can increase the ultimate ability to predict who will fail. Unfortunately, the number of patients evaluated was very small, so any conclusions are tentative at best. One last study took a different approach. Rather than do a blind probe for over- or under expressed genes, they [73] evaluated a pre-existing class of predictive genes like those successful in breast cancer [74]. Although the actual genes are variable, most of the predictive breast cancer genes fall under the general classification of cell cycle progression genes. In evaluation of that class of genes in a large prostatectomy cohort [73] (442 with tissue, median followup 9.5 years), a panel of 31 was tested for their ability to predict recurrence. Overall, 10-year progression-free survival was 64%. When evaluated for the standard findings of PSA, Gleason score, and pathologic findings, the patients could be divided into two groups based on these clinical factors. The low-risk group were patients with Gleason < 7, organ-confined disease, and PSA < 10 ng/mL (actually, PSA up to 30 ng/mL did not change the risk). Their 10-year risk of biochemical failure (PSA > 0.1 ng/mL) was 17%, but for those with a low CCP score, it was 4% and for a high CCP score it was 24%. For clinical high-risk patients (Gleason ≥ 7 and/or nonorgan confined and/or PSA > 30), 10-year biochemical failure was 61%, which was 51% for low CCP score, and 64% for high score. On multivariate analysis, they the CCP score was predictive of recurrence.It is interesting to note, as pointed out previously [71], using multigene predictive models, there is little overlap in the genes that are found to be significant in each of the models. This is postulated to be a factor of a large number of genes and a high signal-to-noise ratio associated with the prediction of biochemical recurrence. The challenge then is to determine which of these are true prognostic markers and which are otherwise just testing anomalies. It will take large comprehensive studies to determine this.
## 4. Conclusion
This paper covered those tissue markers that have been evaluated as prognostic factors in radical prostatectomy patients. These markers and multiple others have also been evaluated in patients with noncurative treatment and metastatic disease, as well as numerous tissue culture systems. There are undoubtedly many useful makers that will be identified, especially with the high volume analyses possible with the microarrays. At this time, none of them have been overwhelming in their prognostic ability nor do they have a value that mandates clinical use.The reason for the failure of molecular markers in consistently predicting outcome may partially be due to the variability between studies due to their methodological differences. Unfortunately, most studies are too small to comprehensively evaluate their ability to improve on the prognostic ability of the standard factors of PSA, Gleason score, and stage. Until that occurs, they will remain research curiosities.In terms of the pathway forward for a useful marker or signature in prostate cancer, we have many challenges. Our current classification of prostate cancer even at the very rudimentary molecular level is lacking. The estrogen, progesterone, and Her 2-neu receptor status of breast cancer has allowed stratification of a complex disease for clinical trials and as a paradigm for molecular signature generation. To date, this has not been possible in prostate cancer, although recent work suggests the imprinting of the TMPRSS2-ERG, PTEN, and androgen receptor configurational status may be suitable. Similarly, basic molecular predictors of outcome in the adjuvant, hormone-naïve, and castrate-resistant settings have been slow to develop in a disease that in its most aggressive form evolves over a decade. Finally, predictors of response to standard therapies have been difficult to characterize in the absence of a single dominant gene or the ability to subsegment the disease. To move forward, markers or gene signatures will need to have strong biological base, be linked to a therapeutic intervention and have enough strength to add to the formidable triad of stage, Gleason score, and serum PSA in prostate cancer.
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*Source: 290160-2011-04-14.xml* | 2011 |
# Proteases of Wood Rot Fungi with Emphasis on the GenusPleurotus
**Authors:** Fabíola Dorneles Inácio; Roselene Oliveira Ferreira; Caroline Aparecida Vaz de Araujo; Tatiane Brugnari; Rafael Castoldi; Rosane Marina Peralta; Cristina Giatti Marques de Souza
**Journal:** BioMed Research International
(2015)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2015/290161
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## Abstract
Proteases are present in all living organisms and they play an important role in physiological conditions. Cell growth and death, blood clotting, and immune defense are all examples of the importance of proteases in maintaining homeostasis. There is growing interest in proteases due to their use for industrial purposes. The search for proteases with specific characteristics is designed to reduce production costs and to find suitable properties for certain industrial sectors, as well as good producing organisms. Ninety percent of commercialized proteases are obtained from microbial sources and proteases from macromycetes have recently gained prominence in the search for new enzymes with specific characteristics. The production of proteases from saprophytic basidiomycetes has led to the identification of various classes of proteases. The genusPleurotus has been extensively studied because of its ligninolytic enzymes. The characteristics of this genus are easy cultivation techniques, high yield, low nutrient requirements, and excellent adaptation. There are few studies in the literature about proteases of Pleurotus spp. This review gathers together information about proteases, especially those derived from basidiomycetes, and aims at stimulating further research about fungal proteases because of their physiological importance and their application in various industries such as biotechnology and medicine.
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## Body
## 1. Introduction
Enzymes are increasingly required in the commercial and industrial fields. For this reason, there is an intense search for new enzymes with particular properties that are desirable for certain commercial applications [1]. There are a limited number of known enzymes that are used commercially and consequently, the enzymes that are available are not used in large quantities. Approximately 75% of industrial enzymes are hydrolases, and the enzymes which degrade proteins account for 65% of the enzymes that are marketed worldwide [2].Proteases catalyze hydrolytic reactions, in which protein molecules are degraded into peptides and amino acids. Their properties are very diverse because the group is large and complex [3]. The study of proteases is of note in enzymology because of its biotechnological relevance. Proteases are a special group of enzymes because of their importance in the metabolism of organisms, their biochemical functions in metabolic pathways and cellular signaling, the importance of protease inhibitors, and their use in fine chemicals and the pharmaceutical industry [4].Most of the proteases used industrially are microbial and especially bacterial origin and these are preferred for their desired characteristics in biotechnology and their lower cost. Proteases which are of plant and animal origin, except for some specific uses, do not meet industrial demand. The industrial production of microbial proteases is favored due to the fact that they have a short generation time, because of the ease of genetically manipulating microorganisms, and because of the diversity of species available in nature, many of which are still unexplored [2, 3].Because of their potential therapeutic use, genes from protease bacteria, fungi, and viruses have been cloned and sequenced in order to increase the production of enzymes by recombinant DNA technology, to study the role of enzymes in pathogenicity and to cause changes in the properties of proteases to improve their commercial usage. In industries, proteases contribute to the development of processes and products with high added value. As biological catalysts, they offer advantages in relation to the use of chemical catalysts for numerous reasons, such as high catalytic activity, high specificity, and their availability in economically viable quantities [5]. However, the cost of production of proteases is the greatest barrier to their industrial application. Consequently, researches have been conducted to find low cost proteases useful in commercial and industrial sectors [6].Bacteria produce the majority of proteases of microbial origin. The genusBacillus produces proteases which are mainly neutral and alkaline [7]. However, the proteases of fungal origin,Aspergillus [8] andPenicillium [5], as well as being widely studied, appear in greater variety. A species can produce neutral, acidic, or alkaline proteases, as is the case ofAspergillus oryzae [7]. Proteases from basidiomycetes have unique properties and deserve further study. Although scientific research regarding the structural and functional characteristics of proteases from basidiomycetes started more than 30 years ago, the diversity and complexity of action of these enzymes has resulted in recent studies of xylotrophic basidiomycetes as a new source of proteases [9].ThePleurotus species are highly appreciated in cooking for their refined flavour and they have also been investigated because they contain bioactive, antitumor, anti-inflammatory, hypocholesterolemic, antiviral, antibiotic, antioxidant, antidiabetic, immunomodulatory, antitumor, antihyperlipidemic, and hepatoprotective compounds, among others [3, 10–12].The genusPleurotus is also known for its ability to degrade lignin through the production of ligninolytic enzymes, particularly laccase [11, 13]. Several studies have been performed with laccase ofPleurotus spp. [14, 15], linking the metabolism of ligninolytic enzymes with the presence of proteases [16]. Besides laccase, the production of numerous hydrolytic enzymes by such organisms has also been reported [17], and interesting studies of the proteases produced byPleurotus spp. have been described, resulting in the need for further research on these properties of this genus. The aim of this review was to gather information on proteolytic enzymes, including their most relevant and current industrial applications, as well as to gather the characteristics of proteases obtained from basidiomycetes, especially from the genusPleurotus.
## 2. Uses and Applications of Proteases
### 2.1. In the Detergent Industry
The use of proteases as a detergent dates back to 1914, when the “Burnus” brand of detergent was produced, which contained sodium carbonate and pancreatic extract [7]. Proteases can be separated into two major groups according to their ability to cleave N- or C-terminal peptide bonds (exopeptidases) or internal peptide bonds (endopeptidases), the latter being those which are most important industrially. They are also classified according to their optimum pH for activity (acid, neutral, or alkaline) and substrate specificity (collagenase, elastase, keratinase, etc.). Based on their mechanism of action and the functional groups in the active site, proteases can be classified into four main groups: serine, cysteine, aspartate, and metalloprotease [9].There are several industries that benefit from the catalytic properties of proteases, such as pharmaceutical, chemical, food processing, detergents, leather processing, and others. Their use in bioremediation processes has also been explored. Their properties, such as substrate specificity, optimum temperature and pH for activity, stability, and catalytic mechanism, differ greatly because this group is quite diverse [9, 18].The proteases used in detergents need to have stability in wide ranges of pH and at high temperatures, as well as compatibility with oxidizing agents. Interest in proteases that are active in a wide temperature range has been increasing because garments made from synthetic fibers are sensitive to high temperatures [19]. However, although bacterial proteases are commonly used in detergents, the high cost of the cell separation process, that is, obtaining cell-free enzyme preparations, limits their use. In this context, enzymes of fungal origin have advantages because they are mainly extracellular. Furthermore, the use of proteases as a basis for detergents is preferable to conventional synthetic products because they have greater cleaning capacity, improved performance at low wash temperatures, and reduce pollution because they are natural. Thus, there is always a demand for enzymes with improved efficiency that can improve the performance of detergents containing enzymes [7].
### 2.2. In the Pharmaceutical and Food Industries
Many proteases are related to the processes of infection caused by viruses, bacteria, and fungi, which are central to the interaction with the host cell. Proteolytic reactions are finely regulated and the variety of mechanisms involve high substrate specificity, ATP-directed protein degradation, restricted access to the active site, activation cascade, and selective and highly specific protein modification, as can be seen in the activation of zymogenic forms of enzymes by limited proteolysis [18, 20].The involvement of proteases in the mechanisms that cause diseases has caused them to become a target for developing therapeutic agents against diseases such as AIDS, cancer, Chagas disease, hepatitis, malaria and candidiasis, as well as inflammatory, immune, respiratory, cardiovascular, and neurodegenerative disorders [7, 18].Natural inhibitors play a role in the regulation of the proteolytic activity in cells; hence knowledge about the interaction of proteases with their substrates and their specificity is an essential tool for the development of synthetic inhibitors that can be used to control diseases in which proteases are involved [21]. There is an emerging market for enzyme inhibitors in countries like India, China, Japan, South Korea, Taiwan, Canada, Australia, and New Zealand [22]. Studies of the protein structure of peptidases through X-ray diffraction have made the development of proteolytic inhibitors possible by molecular modeling [21]. The first successful examples of protease inhibitors were the inhibitors of the aspartic protease of HIV-1, which were developed by the modeling technique. The peptidase of HIV cleaves the polyproteins of the virus into structural proteins, which are essential for the production of mature, infectious viral particles [23].The accumulation of fibrin in the blood can lead to thrombosis, which can cause heart attacks and other cardiovascular diseases [24]. Many products currently used in thrombolytic clinical therapy have undesirable side effects, such as intestinal bleeding in oral treatments, low specificity to fibrin, and relatively high costs [25–27]. Consequently, the growing interest in obtaining fibrinolytic proteases at a reduced cost and with the appropriate medical characteristics has led researchers to intensify their studies and, in recent decades, a number of fibrinolytic enzymes were isolated and characterized. Enzymes with fibrinolytic capacity have been obtained from snake venom, insects, marine animals, algae, fermented products, and microorganisms that are safe for humans and animals (food grade) [28–39].Recently, the fibrinolytic activity of proteases produced by microorganisms has attracted greater medical and commercial interest. Microorganisms are important sources of thrombolytic agents, though few of them have GRAS status (“generally recognized as safe”, i.e., totally safe for humans and animals, and the products obtained from them). Some species ofBacillus produce enzymes with thrombolytic activity, such as nattokinase (NK) fromBacillus natto, subtilisin DFE, and subtilisin DFE DJ-4 fromBacillus amyloliquefaciens [39]. Likewise,Streptococcus hemolyticus produces a streptokinase with thrombolytic action [26, 40]. In recent years, the search has intensified for microorganisms producing proteases with fibrinolytic activity and which are “food grade,” with the potential for exploiting them as functional additives in food and drugs to prevent or treat thrombosis and other related organic disorders [39].Other therapeutic agents include proteases that are used in the correction of deficient digestive enzymes. Elastase is used in the treatment of wounds, burns and abscesses [41, 42]. Proteases also play important roles in the production of animal feed, cleaning contact lenses, silver recovery from photographic films and X-ray and in the treatment of domestic and industrial sewage [19, 43].One of the most important industries in which proteases play an essential role is the food industry. They act as agents for modifying the functional properties of proteins, particularly in the processing of cheese (milk clotting, by the hydrolysis of a specific binding in casein), in obtaining protein hydrolyzates, improving the flavor of some foods and also in baking [19]. Proteases fromAspergillus oryzae are used to modify the gluten of wheat flour by facilitating handling and increasing the volume of bread dough. Proteases have been used since ancient times to prepare sauce and other derivatives from soy because this grain has high, good quality protein content. The proteolytic modification of soy proteins helps to improve their functional properties. These enzymes are also used in the synthesis of the artificial sweetener aspartame (through synthesis reactions produced by the thermolysin ofB. thermoprotyolyticus) and in the maturation (softening) of meat, particularly beef, through the alkaline elastase action ofBacillus. The microorganisms most commonly used for the production of proteases in the food industry are from the genusBacillus [7, 18, 26, 40].The requirements for proteases to act as industrial catalysts vary considerably. The enzymes to be used in the production of detergents and in the food industries need be produced in large quantities and should be efficient without further processing (in natura). The proteases already used in the pharmaceutical industries (such as medicines) are produced in small amounts but require extensive purification procedures [18].
## 2.1. In the Detergent Industry
The use of proteases as a detergent dates back to 1914, when the “Burnus” brand of detergent was produced, which contained sodium carbonate and pancreatic extract [7]. Proteases can be separated into two major groups according to their ability to cleave N- or C-terminal peptide bonds (exopeptidases) or internal peptide bonds (endopeptidases), the latter being those which are most important industrially. They are also classified according to their optimum pH for activity (acid, neutral, or alkaline) and substrate specificity (collagenase, elastase, keratinase, etc.). Based on their mechanism of action and the functional groups in the active site, proteases can be classified into four main groups: serine, cysteine, aspartate, and metalloprotease [9].There are several industries that benefit from the catalytic properties of proteases, such as pharmaceutical, chemical, food processing, detergents, leather processing, and others. Their use in bioremediation processes has also been explored. Their properties, such as substrate specificity, optimum temperature and pH for activity, stability, and catalytic mechanism, differ greatly because this group is quite diverse [9, 18].The proteases used in detergents need to have stability in wide ranges of pH and at high temperatures, as well as compatibility with oxidizing agents. Interest in proteases that are active in a wide temperature range has been increasing because garments made from synthetic fibers are sensitive to high temperatures [19]. However, although bacterial proteases are commonly used in detergents, the high cost of the cell separation process, that is, obtaining cell-free enzyme preparations, limits their use. In this context, enzymes of fungal origin have advantages because they are mainly extracellular. Furthermore, the use of proteases as a basis for detergents is preferable to conventional synthetic products because they have greater cleaning capacity, improved performance at low wash temperatures, and reduce pollution because they are natural. Thus, there is always a demand for enzymes with improved efficiency that can improve the performance of detergents containing enzymes [7].
## 2.2. In the Pharmaceutical and Food Industries
Many proteases are related to the processes of infection caused by viruses, bacteria, and fungi, which are central to the interaction with the host cell. Proteolytic reactions are finely regulated and the variety of mechanisms involve high substrate specificity, ATP-directed protein degradation, restricted access to the active site, activation cascade, and selective and highly specific protein modification, as can be seen in the activation of zymogenic forms of enzymes by limited proteolysis [18, 20].The involvement of proteases in the mechanisms that cause diseases has caused them to become a target for developing therapeutic agents against diseases such as AIDS, cancer, Chagas disease, hepatitis, malaria and candidiasis, as well as inflammatory, immune, respiratory, cardiovascular, and neurodegenerative disorders [7, 18].Natural inhibitors play a role in the regulation of the proteolytic activity in cells; hence knowledge about the interaction of proteases with their substrates and their specificity is an essential tool for the development of synthetic inhibitors that can be used to control diseases in which proteases are involved [21]. There is an emerging market for enzyme inhibitors in countries like India, China, Japan, South Korea, Taiwan, Canada, Australia, and New Zealand [22]. Studies of the protein structure of peptidases through X-ray diffraction have made the development of proteolytic inhibitors possible by molecular modeling [21]. The first successful examples of protease inhibitors were the inhibitors of the aspartic protease of HIV-1, which were developed by the modeling technique. The peptidase of HIV cleaves the polyproteins of the virus into structural proteins, which are essential for the production of mature, infectious viral particles [23].The accumulation of fibrin in the blood can lead to thrombosis, which can cause heart attacks and other cardiovascular diseases [24]. Many products currently used in thrombolytic clinical therapy have undesirable side effects, such as intestinal bleeding in oral treatments, low specificity to fibrin, and relatively high costs [25–27]. Consequently, the growing interest in obtaining fibrinolytic proteases at a reduced cost and with the appropriate medical characteristics has led researchers to intensify their studies and, in recent decades, a number of fibrinolytic enzymes were isolated and characterized. Enzymes with fibrinolytic capacity have been obtained from snake venom, insects, marine animals, algae, fermented products, and microorganisms that are safe for humans and animals (food grade) [28–39].Recently, the fibrinolytic activity of proteases produced by microorganisms has attracted greater medical and commercial interest. Microorganisms are important sources of thrombolytic agents, though few of them have GRAS status (“generally recognized as safe”, i.e., totally safe for humans and animals, and the products obtained from them). Some species ofBacillus produce enzymes with thrombolytic activity, such as nattokinase (NK) fromBacillus natto, subtilisin DFE, and subtilisin DFE DJ-4 fromBacillus amyloliquefaciens [39]. Likewise,Streptococcus hemolyticus produces a streptokinase with thrombolytic action [26, 40]. In recent years, the search has intensified for microorganisms producing proteases with fibrinolytic activity and which are “food grade,” with the potential for exploiting them as functional additives in food and drugs to prevent or treat thrombosis and other related organic disorders [39].Other therapeutic agents include proteases that are used in the correction of deficient digestive enzymes. Elastase is used in the treatment of wounds, burns and abscesses [41, 42]. Proteases also play important roles in the production of animal feed, cleaning contact lenses, silver recovery from photographic films and X-ray and in the treatment of domestic and industrial sewage [19, 43].One of the most important industries in which proteases play an essential role is the food industry. They act as agents for modifying the functional properties of proteins, particularly in the processing of cheese (milk clotting, by the hydrolysis of a specific binding in casein), in obtaining protein hydrolyzates, improving the flavor of some foods and also in baking [19]. Proteases fromAspergillus oryzae are used to modify the gluten of wheat flour by facilitating handling and increasing the volume of bread dough. Proteases have been used since ancient times to prepare sauce and other derivatives from soy because this grain has high, good quality protein content. The proteolytic modification of soy proteins helps to improve their functional properties. These enzymes are also used in the synthesis of the artificial sweetener aspartame (through synthesis reactions produced by the thermolysin ofB. thermoprotyolyticus) and in the maturation (softening) of meat, particularly beef, through the alkaline elastase action ofBacillus. The microorganisms most commonly used for the production of proteases in the food industry are from the genusBacillus [7, 18, 26, 40].The requirements for proteases to act as industrial catalysts vary considerably. The enzymes to be used in the production of detergents and in the food industries need be produced in large quantities and should be efficient without further processing (in natura). The proteases already used in the pharmaceutical industries (such as medicines) are produced in small amounts but require extensive purification procedures [18].
## 3. Proteases of Fungal Origin
The cost of production of proteases is the biggest obstacle to their industrial application. Consequently, the development of new processes to increase the yield of proteases with respect to industrial production, concomitantly with reduced production costs, is highly advantageous from the commercial point of view. Increased productivity has been achieved by selecting hyper-productive strains or by improving the culture media [7]. The global market for industrial enzymes reached about US $4.5 billion in 2012, with a projection of US $7.1 billion for 2018. Research on enzymes has revealed their use in different sectors and their catalytic properties have stimulated their use in industrial production and processes. Market growth has been positively influenced by new products and their advantages over traditional industrial methods [22, 44].Although the species of microorganisms that are used for industrial production are few in number, 90% of commercialized proteases are obtained from microbial sources. These are preferred to proteases from plants and animals due to their various characteristics, which are more suitable for biotechnological applications, such as activity within a broad range of temperature and pH, thermal stability, and high catalytic activity [18, 41, 45].Biodiversity is an invaluable resource for biotechnological innovation and it promotes the search for new strains of microorganisms to be used for specific industrial purposes. Because the use of proteases, especially those of the alkaline variety, is expected to rise over the coming decades, the production of microbial proteases represents a good alternative for the development of new methods in order to improve the production of these enzymes, as well as decreasing their price [7, 19]. The increased demand for proteases with specific properties has led biotechnologists to explore new sources of proteases.Most fungal proteases have neutral to slightly acidic characteristics [19]. Xerophilic fungi often contain proteases of low molecular weight (26 to 50 kDa) [24]. The study of fungal proteases has increased in recent decades, but knowledge about proteases from basidiomycetes is still limited [9]. In 2009, approximately 60% of the enzymes commercialized originated from fungi and only five originate macrofungi (three laccases, one peroxidase, and one phytase) [11].A few years ago, the proteases produced from micromycetes were predominant in studies regarding the search for new bioactives with economic and medicinal benefits [24].Aspergillus is considered to be the best producer of proteases [8]. In the food industryA. oryzae andA. sojae are noteworthy for their ability to eliminate bitterness [19].PenicilliumandRhizopus are also considered to produce proteases [5, 46] and the proteases from macromycetes recently gained prominence in the search for new enzymes with specific characteristics. Proteases produced from basidiomycetes such asAgaricus bisporus,Armillariella mellea,Flammulina velutipes,Grifola frondosa,Pleurotus ostreatus,Pleurotus eryngii,Phanerochaete chrysosporium,Schizophyllum commune, and others have been reported [47–50].There are vast majority of microorganisms that exist in nature have not yet been studied. Thus, the search for new natural molecules with interesting physiological effects, and the need to understand the mechanisms of production and regulation of expression of these bioactives, has resulted in the fact that the cultivation conditions that have already been defined and used successfully for ascomycetes such asAspergillus sp. andPenicillium sp. have now been extended to include basidiomycetes in the search for secondary bioactives and metabolites such as enzymes, antibiotics, and organic acids [46].
## 4. Proteases from Basidiomycetes
Basidiomycetes are fungi important for biological communities because they are excellent at degrading wood. Some genera have been used as food for centuries and they have enormous commercial importance. They are also producers of a group of commonly studied extracellular enzymes (xylanases, cellulases, and ligninolytic enzymes) [51]. Proteases play important roles in the physiology of fungi, acting in processes such as germination and sporulation. These enzymes seem to have a close relationship with the lifestyle of saprophytic fungi, as observed inPleurotus citrinopileatus [43].It has been found thatP. pulmonarius, which usually grows on dead timber, secretes subtilisin but does not produce trypsin.P. ostreatus, which grows in living hosts, secretes extracellular trypsin throughout its development. The presence of living tissues as hosts may be related to the expression of trypsin-type proteases [24]. Because most of the nitrogen in timber is in the form of proteins, proteases play a very important role in the metabolism of the proteins in the fungi of white rot in wood and it has been observed that depletion of nitrogen in the medium stimulates the secretion of proteases by fungi [3, 24, 52–57].The mycelial secretion of proteases by saprophytic basidiomycetes has led to the identification of various classes of proteases: subtilases were found inPleurotus ostreatus [58],Phanerochaete chrysosporium [59],Serpula lacrymans [52],Schizophyllum commune [47], andCoprinussp. [60]. Metalloproteinase was reported by Mchenry et al. [61] inChondrostereum purpureum and inHypsizygus marmoreus [62]. The mycelial secretion of aspartate proteases was reported inP. chrysosporium [49, 59],Amanita muscaria [63], andIrpex lacteus [64].Although they are recognized for their nutritional value and the extraction of bioactive compounds of basidiome and mycelia, mushrooms still possess much unexplored information in relation to some of the enzymes that they produce, such as proteases [6]. Proteases extracted from mushrooms have been purified and characterized [48]. The role of proteases in the regulation of the formation of basidiome inHypsizygus marmoreus was described by Terashita et al. [62] and their regulatory role regarding ligninolytic activity inP. chrysosporium andP. ostreatus, under nutritional limitation, was highlighted by Dass et al. [59] and Palmieri et al. [16], respectively.Phanerochaete chrysosporium has produced an acid protease in solid medium with wood, under ligninolytic conditions. This enzyme showed an isoelectric point that was higher than that of most acid proteases (5.6) and it has been characterized as a glycoprotein aspartate protease [49].From a selection of 27 strains of basidiomycetes that produce proteases [3],Lentinula edodes stood out with the largest halo of proteolytic activity using the method of selection on plates containing casein. In this study, the genusPleurotus ranked second in the production of protease. The authors attributed this proteolytic activity to ability of the fungus to grow on substrates with low nitrogen availability [47]. However, Zorn et al. [65] consider that the existence of nitrogen seems to stimulate the production of proteases by fungi. Media containing soybean, casein, gelatin, corn, and yeast are commonly used to produce protease. Other sources, such as starch, lactose, and barley are also used, but it is known that high concentrations of carbohydrates inhibit the production of enzymes [19]. The purification of a fibrinolytic protease fromCordyceps militaris showed characteristics of a 52 kDa subtilisin, which was higher than other fungal proteases. The enzyme rapidly degraded the α and γ chains, but it took longer to degrade the β chains of the fibrin, which was a pattern quite different from the action of proteases derived from snake venom [27]. The fibrinolytic protease activity of basidiomycetes has been recently demonstrated by several authors. Kim et al. [66] purified and characterized a metalloprotease from the mycelium ofPerenniporia fraxinea with fibrinolytic activity. The cloning, purification, and characterization of proteases fromPleurotus ostreatus with similar characteristics were performed by Yin et al. [2], Shen et al. [67], and Joh et al. [68].Although several studies have performed the purification and characterization of proteases from mycelium, basidiome, or culture filtrate, many aspects of the production of these enzymes have yet to be explored. The process of producing basidiome is laborious and time-consuming; it requires large volumes of substrate, space, and qualified labor and these factors hinder research in the laboratory. Cultivations which are performed in the vegetative phase are more viable for research because they can be kept in the laboratory, performed on a small and medium scale, and important parameters such as temperature, humidity, and agitation can be controlled [18].Microbial proteases can be produced in various ways and studies have shown that, depending on the culture conditions, different forms of the same protease can be expressed [19]. Most of the enzymes produced in industry are produced by submerged fermentation [8]. The use of liquid cultures facilitates the purification of bioactives such as enzymes and polysaccharides [3]. The submerged culture ofP. ostreatus in wheat gluten resulted in the secretion of proteases that noticeably increased the overall solubility of the medium [13].Submerged media with complex sources provide higher yields of protease compared to simple media, such as casein or gelatin [19]. However, using submerged culture requires greater resources, specific strains, and very controlled conditions, which does not occur in solid state fermentation, which therefore offers advantages in terms of environmental and economic aspects [8]. The solid cultivation of mushrooms and mycelium in order to obtain bioactives and enzymes remains a very viable alternative; waste from agriculture, forestry, or municipal waste are used for the production of enzymes of industrial interest. The combination of different solid substrates sometimes appears to increase the production of protease by fungi [19].Due to the similarity of the natural habitat of basidiomycetes, these organisms have excelled in the production of enzymes in solid cultures. Solid state fermentation in tomato pulp yielded good colonization and protease production on a large scale usingP. ostreatus [8]. Furthermore, proteases have been obtained by the solid state fermentation of soybean and wheat bran fibers [69]. The literature includes standardized techniques for the high yield recovery of proteases, as well as immobilization methods and different protocols for proteolytic assays and the purification of proteases [19].
## 5. Proteases fromPleurotus spp.
The genusPleurotus is the second main group of cultivated edible mushrooms in the world, comprising more than 40 species [51]. In descending order of worldwide production, the seven most produced edible mushrooms areAgaricus bisporus,Pleurotus spp.,Lentinula edodes,Auriculariaspp.,Volvariella volvacea,Flammulina velutipes, andTremella fuciformis [11]. However, species of the genusPleurotus present advantages when compared with others mushrooms. For example, they can be cultivated in different substrates and temperatures. They are also rich in essential amino acids and vitamins [70].Pleurotus can be grown artificially without major problems and it grows in a disorderly manner in tropical and subtropical regions [51]. This genus is a part of ligninolytic organisms and several studies have reported the ligninolytic capacity of its species [65]. Several bioactive compounds have been extracted from crude extracts, mycelia, and basidiome ofPleurotus spp. for study, such as polysaccharides, hemicelluloses, peptides, glycoproteins, lipids, hydrolytic enzymes, and others [12].Extracts of the basidiome and mycelia ofPleurotus spp. have been used as medicines and as nutritional supplements for human health. Several studies have reported its nutritional, immunomodulatory, antioxidant, antitumor, and hypoglycemic properties, among others.P. ostreatus has been effective in alleviating the effects of hepatotoxicity in rats and it protects the liver, heart, and brain against oxidative stress [51].In recent years, examples of the main genera of cultured basidiomycetes have been studied for their positive therapeutic effects. Hepatoprotective effect was observed forP. pulmonarius,P. ferulae, andP. tuber-regium, which were also active against human cancer cells [71]. Moreover, species of the genus have been used in the processes of bioremediation, delignification, and disinfection of effluent [17].Different strains ofPleurotus spp. (Figure 1) exhibit specific behaviors, which vary depending on the conditions where they are cultivated, including environmental factors such as types of substrates and supplementation. A study of three strains ofP. eryngii using sawdust and rice straw as a substrate for cultivation showed significant differences between the strains regarding growth rates, number of days for the first harvest, biological efficiency, and other parameters [72].P. eryngii is considered as one of the best species of the genus due to its consistency and because it has a longer lifetime than all the other species ofPleurotus. While most of the fungi in the Agaricales order show steady growth in tree trunks,P. eryngii grows well in subtropical pastures and grows excellently during cold periods [72].Figure 1
Pleurotus pulmonarius.The artificial cultivation ofP. eryngii on farms using automatic devices and sawdust has been performed successfully in Korea. The species has also been effective in lowering the levels of blood glucose, the inhibition of tumor cells, and antioxidant activity [73].P. citrinopileatus contains polysaccharides that have antihyperglycemic and antitumor effects [43]. Medicinal properties have also been observed inP. tuber-regium, which is also edible and grows well in tropical and subtropical regions. Several of its bioactive substances have been identified, such as glycoproteins, polysaccharides, and phytochemicals with pharmacological action [74].Basidiome ofP. pulmonarius has shown antitumor, antioxidant, and anti-inflammatory properties, suggesting the therapeutic effects of its metabolites in the treatment against some diseases, such as cancer [75].P. sajor-caju andP. ostreatus have also been investigated for their antioxidant capacity and both species share a similar amino acid profile. However, despite similarities with the properties ofPleurotusspp., there are many studies ofP. ostreatus at the expense of other species of the genus [51]. As stated, there is still little knowledge about the proteases derived from mushrooms, mainly thePleurotus genus [11].Studies of theP. ostreatus,P. eryngii,P. citrinopileatus, andP. chrysosporium species have showed that thePleurotus genus is a producer of proteases that seem to participate in the complex ligninolytic mechanism, degrading the laccase enzyme at certain stages of fungal growth [16, 43, 50, 59, 73].P. pulmonarius has important antimicrobial, anti-inflammatory, antioxidant, and antitumor properties; however, there is still little material in the literature regarding its production of proteases and their characterization. Nevertheless, it is known that the proteases secreted by this species do not appear to participate in the regulation of peroxidases, as has been reported forP. ostreatus proteases [16, 24, 75, 76]. In addition, no degradation of ligninolytic enzymes was observed when they came into contact with proteases fromPhanerochaete chrysosporium [49].In a comparison of six species of basidiomycetes,P. eryngii excelled in the production of protease. Pleurerin, the protease extracted from fruiting bodies ofP. eryngii with anti-HIV-1 action, has presented the characteristics of an aspartic protease due to its N-terminal sequence, which is different from other aspartic fungal proteases [50]. Most proteases of the genusPleurotus feature the characteristics of alkaline subtilases. There are six families of serine proteases, which are based on their amino acid sequence [58]. A study of proteases from 43 species of basidiomycetes showed a predominance of serine protease [9]. An alkaline protease was found in the basidiome ofP. citrinopileatus and it showed a similarity in amino acid sequence withAgaricus bisporus,Epichloë typhina, andPenicillium oxalicum fungi [43].Aspartic proteases are divided into 16 groups and are rarer inPleurotus [2].The fibrinolytic proteases ofPleurotus spp. have received attention in recent years because those searching for new proteases with fibrinolytic capacity are interested in nontoxic and edible fungi [77]. A monomeric protease with fibrinolytic activity was purified 29.3-fold from the basidiome ofP. eryngii produced in corn cob. The protease in question showed a high capacity for degrading fibrin and demonstrated a possible application as a thrombolytic agent. The hydrolysis of α and β chains of fibrinogen occurred in less than 10 min. The enzyme showed characteristics of a serine protease similar to subtilisin, as has been reported for most proteases from the genus [73].In a study by Liu et al. [77] the fibrinolytic and fibrinogenolytic enzyme fromP. pulmonarius grown in submerged state were efficient in degrading the α (3 min) and β (45 min) chains of fibrinogen, followed by γ after 10 h incubation. The enzyme was purified 147-fold and presented good stability at human body temperature, which enables it to be used as an alternative in thrombolytic treatments, including oral applications, because it is an edible fungus. Apart from fibrin degradation, the enzyme was also able to act as a plasminogen activator, which is not common in the literature. A fibrinolytic metalloproteinase purified from mycelia ofP. ostreatus showed a high similarity with the fibrinolytic proteases from the basidiome of the same fungus, which suggests the need for studies related to therapeutic treatments for thrombosis from the mycelium, which can be obtained more quickly and easily than the fruiting bodies [67].Hemolytic proteases have been reported less frequently in the genusPleurotus. The hemolysin of the basidiome ofP. nebrodensis showed apoptosis-inducing activity and antiproliferative cancer cells and also anti-HIV-1 activity, interfering in some way in the permeability of the cell membranes and preventing virus infection [78]. Activity against cancer cells has also been verified for proteases ofP. ostreatus. Hemolysin extracted fromP. eryngii was effective against leukemia cells [79] and showed antimicrobial effect forBacillus sp. [80]. However, these enzymes are not stable at temperatures higher than 40°C, which hinders their possible application as a medicament in the form of food because they would be made inactive by cooking or when passing through the intestinal tract [80, 81].Keratinases are a class of proteases that have received attention in the past. They consist of proteases that are capable of degrading substrates that are rich in insoluble keratins, such as wool, hair, and nail. Because of this, keratinases are used in environmental and technological processes [82]. However, regarding proteases in general, there is little existing research on keratinases of basidiomycetes and there are few reports about keratinases produced by the genusPleurotus spp.The secretome ofP. sapidus has shown protease production and ligninolytic enzymes, but some points remained unidentified, indicating that new enzymes with potential biotechnological applications should be studied and identified in the species [65]. The secretome ofP. ostreatus has shown the presence of proteases with a potential role in the regulation of other extracellular enzymes [13]. Metalloproteases are enzymes that are finely associated with physiological processes and they have been explored in studies of bacteria and mammals; however, there have been very few studies of the metalloproteases of basidiomycetes [68].Pleurotus spp. has been greatly cultivated for research related to medicine and also for the consumption of its fruiting bodies, which have agreeable flavors [24].Although the process of the emergence of the fruiting body of basidiomycetes is still not fully known, the expression of a metalloprotease in the early stages of the formation of a basidiome ofP. ostreatus has been verified, although the enzyme was not expressed in the mycelial stage or in the formation of spores [68]. The increase of proteases in mature hyphae has also been noted in mycelia ofP. pulmonarius, linking the time of the formation of the basidiome with the presence of such enzymes [70]. Furthermore, the addition of inhibitors of metalloproteinases has prevented the normal process of the formation of fruiting bodies ofHypsizygus marmoreus [62]. Vanillic acid has been reported as a good inducer of proteases ofPleurotus ostreatus [58]. In just four days of cultivation in solid state fermentation in residues in tomato,P. ostreatus produced high levels of protease, surpassing fungi which are considered to be the best producers of this enzyme, such asAspergillus [8].The most studied species of the genus isP. ostreatus. Proteases ofP. ostreatus with the capacity to coagulate of milk have been purified [83] and despite the classical techniques of production of proteases, recombinant enzymes have been produced in order to find better yields and new specialties [2, 19, 67, 68].Recent studies of DNA sequence and proteins have come together with the aim of studying enzymatic structures and mechanisms. As already mentioned, due to the vast diversity of proteases, further knowledge of molecular structures in 3D, active sites and mechanisms of catalysis, and enzyme inhibition are increasingly necessary [18]. Based on the N-terminal sequences of proteases ofP. ostreatus, a primer was developed in order to clone and amplify a DNA sequence that showed homologous regions with a hypothetical protease ofNeurospora crassa and another ofPhanerochaete chrysosporium—the first basidiomycete with a completely sequenced genome [58].A recent study compared the genomes of 33 basidiomycetes and resulted in the idea that the division of fungi into white rot fungi and brown rot fungi in wood cannot be sustained because of the existence of DNA sequences shared between the two groups of fungi that attributes complexity to the mechanisms of degradation of cellulose, hemicellulose, and lignin by basidiomycetes [89]. The three-dimensional structures of proteases and their inhibitors provide rich information about the mechanisms involved in catalysis, and they suggest processes for enzyme inhibition that are still unknown. Using X-ray diffraction, the three-dimensional structure of a serine protease inhibitor ofP. ostreatus complexed with subtilisin is shown in Figure 2 [84]. Table 1 shows some characteristics of proteasesPleurotus spp.Table 1
Characteristics of proteasesPleurotus spp.
Species
Molecular weight (kDa)
Optimum pH
Optimum temperature
Kind of protease
References
P. ostreatus
43
[2]
P. ostreatusvar.florida
38.7
7.5
37°C
Serine proteinase
[13]
P. citrinopileatus
28
10
50°C
Serine proteinase
[43]
P. eryngii
11.5
5
45°C
Aspartic protease
[50]
P. ostreatus
32
6.5
35°C
Metalloprotease
[67]
P. eryngii
14
5
30–40°C
Serine proteinase
[73]
P. ostreatus
18.2
7.4
40°C
Metalloprotease
[77]
P. nebrodensis
27
[78]
P. eryngii
17
37°C
[80]
P. ostreatus
Serine proteinase/metalloprotease
[83]
P. ostreatus
22
6.7
[84]
P. ostreatus
75
7.8
Serine protease
[85]
P. ostreatus
30/19/42.5
7.4/5.6
Serine protease/metalloprotease
[86]
P. sajor-caju
14.5/86
Metalloprotease
[87]
P. ostreatus
97/48.5
5.5–6.5
Cysteine protease
[88]Figure 2
Ribbon model of subtilisin BPN (blue) fromBacillus amyloliquefaciens in complex with serine protease inhibitor POIA1 (red) and calcium ion (grey sphere). Figure from pdbid: 1V5I.
## 6. Conclusions
There is still much progress to be made in the study of proteases ofPleurotus spp. and there is still much to be discovered regarding the genome, proteome, and metabolome of the genus. Several proteases ofPleurotus spp. have shown unique characteristics, which require further research.Pleurotus ostreatus is one of the few edible mushrooms produced on an industrial scale. Most of the research to be found in the literature concerns artificially cultivated basidiomycetes. It is known that there is a high demand in industry for proteolytic enzymes with appropriate specificity and stability to temperature, pH, metal ions, and so forth. However, it is common to find that studies of proteases of basidiomycetes recommend that further, more detailed, studies are required to reveal the mechanisms and physiological effects of proteases. Thus, studies of new proteases of the genusPleurotus, especially wild species, are an area of biotechnology that needs to be explored.
---
*Source: 290161-2015-06-09.xml* | 290161-2015-06-09_290161-2015-06-09.md | 47,080 | Proteases of Wood Rot Fungi with Emphasis on the GenusPleurotus | Fabíola Dorneles Inácio; Roselene Oliveira Ferreira; Caroline Aparecida Vaz de Araujo; Tatiane Brugnari; Rafael Castoldi; Rosane Marina Peralta; Cristina Giatti Marques de Souza | BioMed Research International
(2015) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2015/290161 | 290161-2015-06-09.xml | ---
## Abstract
Proteases are present in all living organisms and they play an important role in physiological conditions. Cell growth and death, blood clotting, and immune defense are all examples of the importance of proteases in maintaining homeostasis. There is growing interest in proteases due to their use for industrial purposes. The search for proteases with specific characteristics is designed to reduce production costs and to find suitable properties for certain industrial sectors, as well as good producing organisms. Ninety percent of commercialized proteases are obtained from microbial sources and proteases from macromycetes have recently gained prominence in the search for new enzymes with specific characteristics. The production of proteases from saprophytic basidiomycetes has led to the identification of various classes of proteases. The genusPleurotus has been extensively studied because of its ligninolytic enzymes. The characteristics of this genus are easy cultivation techniques, high yield, low nutrient requirements, and excellent adaptation. There are few studies in the literature about proteases of Pleurotus spp. This review gathers together information about proteases, especially those derived from basidiomycetes, and aims at stimulating further research about fungal proteases because of their physiological importance and their application in various industries such as biotechnology and medicine.
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## Body
## 1. Introduction
Enzymes are increasingly required in the commercial and industrial fields. For this reason, there is an intense search for new enzymes with particular properties that are desirable for certain commercial applications [1]. There are a limited number of known enzymes that are used commercially and consequently, the enzymes that are available are not used in large quantities. Approximately 75% of industrial enzymes are hydrolases, and the enzymes which degrade proteins account for 65% of the enzymes that are marketed worldwide [2].Proteases catalyze hydrolytic reactions, in which protein molecules are degraded into peptides and amino acids. Their properties are very diverse because the group is large and complex [3]. The study of proteases is of note in enzymology because of its biotechnological relevance. Proteases are a special group of enzymes because of their importance in the metabolism of organisms, their biochemical functions in metabolic pathways and cellular signaling, the importance of protease inhibitors, and their use in fine chemicals and the pharmaceutical industry [4].Most of the proteases used industrially are microbial and especially bacterial origin and these are preferred for their desired characteristics in biotechnology and their lower cost. Proteases which are of plant and animal origin, except for some specific uses, do not meet industrial demand. The industrial production of microbial proteases is favored due to the fact that they have a short generation time, because of the ease of genetically manipulating microorganisms, and because of the diversity of species available in nature, many of which are still unexplored [2, 3].Because of their potential therapeutic use, genes from protease bacteria, fungi, and viruses have been cloned and sequenced in order to increase the production of enzymes by recombinant DNA technology, to study the role of enzymes in pathogenicity and to cause changes in the properties of proteases to improve their commercial usage. In industries, proteases contribute to the development of processes and products with high added value. As biological catalysts, they offer advantages in relation to the use of chemical catalysts for numerous reasons, such as high catalytic activity, high specificity, and their availability in economically viable quantities [5]. However, the cost of production of proteases is the greatest barrier to their industrial application. Consequently, researches have been conducted to find low cost proteases useful in commercial and industrial sectors [6].Bacteria produce the majority of proteases of microbial origin. The genusBacillus produces proteases which are mainly neutral and alkaline [7]. However, the proteases of fungal origin,Aspergillus [8] andPenicillium [5], as well as being widely studied, appear in greater variety. A species can produce neutral, acidic, or alkaline proteases, as is the case ofAspergillus oryzae [7]. Proteases from basidiomycetes have unique properties and deserve further study. Although scientific research regarding the structural and functional characteristics of proteases from basidiomycetes started more than 30 years ago, the diversity and complexity of action of these enzymes has resulted in recent studies of xylotrophic basidiomycetes as a new source of proteases [9].ThePleurotus species are highly appreciated in cooking for their refined flavour and they have also been investigated because they contain bioactive, antitumor, anti-inflammatory, hypocholesterolemic, antiviral, antibiotic, antioxidant, antidiabetic, immunomodulatory, antitumor, antihyperlipidemic, and hepatoprotective compounds, among others [3, 10–12].The genusPleurotus is also known for its ability to degrade lignin through the production of ligninolytic enzymes, particularly laccase [11, 13]. Several studies have been performed with laccase ofPleurotus spp. [14, 15], linking the metabolism of ligninolytic enzymes with the presence of proteases [16]. Besides laccase, the production of numerous hydrolytic enzymes by such organisms has also been reported [17], and interesting studies of the proteases produced byPleurotus spp. have been described, resulting in the need for further research on these properties of this genus. The aim of this review was to gather information on proteolytic enzymes, including their most relevant and current industrial applications, as well as to gather the characteristics of proteases obtained from basidiomycetes, especially from the genusPleurotus.
## 2. Uses and Applications of Proteases
### 2.1. In the Detergent Industry
The use of proteases as a detergent dates back to 1914, when the “Burnus” brand of detergent was produced, which contained sodium carbonate and pancreatic extract [7]. Proteases can be separated into two major groups according to their ability to cleave N- or C-terminal peptide bonds (exopeptidases) or internal peptide bonds (endopeptidases), the latter being those which are most important industrially. They are also classified according to their optimum pH for activity (acid, neutral, or alkaline) and substrate specificity (collagenase, elastase, keratinase, etc.). Based on their mechanism of action and the functional groups in the active site, proteases can be classified into four main groups: serine, cysteine, aspartate, and metalloprotease [9].There are several industries that benefit from the catalytic properties of proteases, such as pharmaceutical, chemical, food processing, detergents, leather processing, and others. Their use in bioremediation processes has also been explored. Their properties, such as substrate specificity, optimum temperature and pH for activity, stability, and catalytic mechanism, differ greatly because this group is quite diverse [9, 18].The proteases used in detergents need to have stability in wide ranges of pH and at high temperatures, as well as compatibility with oxidizing agents. Interest in proteases that are active in a wide temperature range has been increasing because garments made from synthetic fibers are sensitive to high temperatures [19]. However, although bacterial proteases are commonly used in detergents, the high cost of the cell separation process, that is, obtaining cell-free enzyme preparations, limits their use. In this context, enzymes of fungal origin have advantages because they are mainly extracellular. Furthermore, the use of proteases as a basis for detergents is preferable to conventional synthetic products because they have greater cleaning capacity, improved performance at low wash temperatures, and reduce pollution because they are natural. Thus, there is always a demand for enzymes with improved efficiency that can improve the performance of detergents containing enzymes [7].
### 2.2. In the Pharmaceutical and Food Industries
Many proteases are related to the processes of infection caused by viruses, bacteria, and fungi, which are central to the interaction with the host cell. Proteolytic reactions are finely regulated and the variety of mechanisms involve high substrate specificity, ATP-directed protein degradation, restricted access to the active site, activation cascade, and selective and highly specific protein modification, as can be seen in the activation of zymogenic forms of enzymes by limited proteolysis [18, 20].The involvement of proteases in the mechanisms that cause diseases has caused them to become a target for developing therapeutic agents against diseases such as AIDS, cancer, Chagas disease, hepatitis, malaria and candidiasis, as well as inflammatory, immune, respiratory, cardiovascular, and neurodegenerative disorders [7, 18].Natural inhibitors play a role in the regulation of the proteolytic activity in cells; hence knowledge about the interaction of proteases with their substrates and their specificity is an essential tool for the development of synthetic inhibitors that can be used to control diseases in which proteases are involved [21]. There is an emerging market for enzyme inhibitors in countries like India, China, Japan, South Korea, Taiwan, Canada, Australia, and New Zealand [22]. Studies of the protein structure of peptidases through X-ray diffraction have made the development of proteolytic inhibitors possible by molecular modeling [21]. The first successful examples of protease inhibitors were the inhibitors of the aspartic protease of HIV-1, which were developed by the modeling technique. The peptidase of HIV cleaves the polyproteins of the virus into structural proteins, which are essential for the production of mature, infectious viral particles [23].The accumulation of fibrin in the blood can lead to thrombosis, which can cause heart attacks and other cardiovascular diseases [24]. Many products currently used in thrombolytic clinical therapy have undesirable side effects, such as intestinal bleeding in oral treatments, low specificity to fibrin, and relatively high costs [25–27]. Consequently, the growing interest in obtaining fibrinolytic proteases at a reduced cost and with the appropriate medical characteristics has led researchers to intensify their studies and, in recent decades, a number of fibrinolytic enzymes were isolated and characterized. Enzymes with fibrinolytic capacity have been obtained from snake venom, insects, marine animals, algae, fermented products, and microorganisms that are safe for humans and animals (food grade) [28–39].Recently, the fibrinolytic activity of proteases produced by microorganisms has attracted greater medical and commercial interest. Microorganisms are important sources of thrombolytic agents, though few of them have GRAS status (“generally recognized as safe”, i.e., totally safe for humans and animals, and the products obtained from them). Some species ofBacillus produce enzymes with thrombolytic activity, such as nattokinase (NK) fromBacillus natto, subtilisin DFE, and subtilisin DFE DJ-4 fromBacillus amyloliquefaciens [39]. Likewise,Streptococcus hemolyticus produces a streptokinase with thrombolytic action [26, 40]. In recent years, the search has intensified for microorganisms producing proteases with fibrinolytic activity and which are “food grade,” with the potential for exploiting them as functional additives in food and drugs to prevent or treat thrombosis and other related organic disorders [39].Other therapeutic agents include proteases that are used in the correction of deficient digestive enzymes. Elastase is used in the treatment of wounds, burns and abscesses [41, 42]. Proteases also play important roles in the production of animal feed, cleaning contact lenses, silver recovery from photographic films and X-ray and in the treatment of domestic and industrial sewage [19, 43].One of the most important industries in which proteases play an essential role is the food industry. They act as agents for modifying the functional properties of proteins, particularly in the processing of cheese (milk clotting, by the hydrolysis of a specific binding in casein), in obtaining protein hydrolyzates, improving the flavor of some foods and also in baking [19]. Proteases fromAspergillus oryzae are used to modify the gluten of wheat flour by facilitating handling and increasing the volume of bread dough. Proteases have been used since ancient times to prepare sauce and other derivatives from soy because this grain has high, good quality protein content. The proteolytic modification of soy proteins helps to improve their functional properties. These enzymes are also used in the synthesis of the artificial sweetener aspartame (through synthesis reactions produced by the thermolysin ofB. thermoprotyolyticus) and in the maturation (softening) of meat, particularly beef, through the alkaline elastase action ofBacillus. The microorganisms most commonly used for the production of proteases in the food industry are from the genusBacillus [7, 18, 26, 40].The requirements for proteases to act as industrial catalysts vary considerably. The enzymes to be used in the production of detergents and in the food industries need be produced in large quantities and should be efficient without further processing (in natura). The proteases already used in the pharmaceutical industries (such as medicines) are produced in small amounts but require extensive purification procedures [18].
## 2.1. In the Detergent Industry
The use of proteases as a detergent dates back to 1914, when the “Burnus” brand of detergent was produced, which contained sodium carbonate and pancreatic extract [7]. Proteases can be separated into two major groups according to their ability to cleave N- or C-terminal peptide bonds (exopeptidases) or internal peptide bonds (endopeptidases), the latter being those which are most important industrially. They are also classified according to their optimum pH for activity (acid, neutral, or alkaline) and substrate specificity (collagenase, elastase, keratinase, etc.). Based on their mechanism of action and the functional groups in the active site, proteases can be classified into four main groups: serine, cysteine, aspartate, and metalloprotease [9].There are several industries that benefit from the catalytic properties of proteases, such as pharmaceutical, chemical, food processing, detergents, leather processing, and others. Their use in bioremediation processes has also been explored. Their properties, such as substrate specificity, optimum temperature and pH for activity, stability, and catalytic mechanism, differ greatly because this group is quite diverse [9, 18].The proteases used in detergents need to have stability in wide ranges of pH and at high temperatures, as well as compatibility with oxidizing agents. Interest in proteases that are active in a wide temperature range has been increasing because garments made from synthetic fibers are sensitive to high temperatures [19]. However, although bacterial proteases are commonly used in detergents, the high cost of the cell separation process, that is, obtaining cell-free enzyme preparations, limits their use. In this context, enzymes of fungal origin have advantages because they are mainly extracellular. Furthermore, the use of proteases as a basis for detergents is preferable to conventional synthetic products because they have greater cleaning capacity, improved performance at low wash temperatures, and reduce pollution because they are natural. Thus, there is always a demand for enzymes with improved efficiency that can improve the performance of detergents containing enzymes [7].
## 2.2. In the Pharmaceutical and Food Industries
Many proteases are related to the processes of infection caused by viruses, bacteria, and fungi, which are central to the interaction with the host cell. Proteolytic reactions are finely regulated and the variety of mechanisms involve high substrate specificity, ATP-directed protein degradation, restricted access to the active site, activation cascade, and selective and highly specific protein modification, as can be seen in the activation of zymogenic forms of enzymes by limited proteolysis [18, 20].The involvement of proteases in the mechanisms that cause diseases has caused them to become a target for developing therapeutic agents against diseases such as AIDS, cancer, Chagas disease, hepatitis, malaria and candidiasis, as well as inflammatory, immune, respiratory, cardiovascular, and neurodegenerative disorders [7, 18].Natural inhibitors play a role in the regulation of the proteolytic activity in cells; hence knowledge about the interaction of proteases with their substrates and their specificity is an essential tool for the development of synthetic inhibitors that can be used to control diseases in which proteases are involved [21]. There is an emerging market for enzyme inhibitors in countries like India, China, Japan, South Korea, Taiwan, Canada, Australia, and New Zealand [22]. Studies of the protein structure of peptidases through X-ray diffraction have made the development of proteolytic inhibitors possible by molecular modeling [21]. The first successful examples of protease inhibitors were the inhibitors of the aspartic protease of HIV-1, which were developed by the modeling technique. The peptidase of HIV cleaves the polyproteins of the virus into structural proteins, which are essential for the production of mature, infectious viral particles [23].The accumulation of fibrin in the blood can lead to thrombosis, which can cause heart attacks and other cardiovascular diseases [24]. Many products currently used in thrombolytic clinical therapy have undesirable side effects, such as intestinal bleeding in oral treatments, low specificity to fibrin, and relatively high costs [25–27]. Consequently, the growing interest in obtaining fibrinolytic proteases at a reduced cost and with the appropriate medical characteristics has led researchers to intensify their studies and, in recent decades, a number of fibrinolytic enzymes were isolated and characterized. Enzymes with fibrinolytic capacity have been obtained from snake venom, insects, marine animals, algae, fermented products, and microorganisms that are safe for humans and animals (food grade) [28–39].Recently, the fibrinolytic activity of proteases produced by microorganisms has attracted greater medical and commercial interest. Microorganisms are important sources of thrombolytic agents, though few of them have GRAS status (“generally recognized as safe”, i.e., totally safe for humans and animals, and the products obtained from them). Some species ofBacillus produce enzymes with thrombolytic activity, such as nattokinase (NK) fromBacillus natto, subtilisin DFE, and subtilisin DFE DJ-4 fromBacillus amyloliquefaciens [39]. Likewise,Streptococcus hemolyticus produces a streptokinase with thrombolytic action [26, 40]. In recent years, the search has intensified for microorganisms producing proteases with fibrinolytic activity and which are “food grade,” with the potential for exploiting them as functional additives in food and drugs to prevent or treat thrombosis and other related organic disorders [39].Other therapeutic agents include proteases that are used in the correction of deficient digestive enzymes. Elastase is used in the treatment of wounds, burns and abscesses [41, 42]. Proteases also play important roles in the production of animal feed, cleaning contact lenses, silver recovery from photographic films and X-ray and in the treatment of domestic and industrial sewage [19, 43].One of the most important industries in which proteases play an essential role is the food industry. They act as agents for modifying the functional properties of proteins, particularly in the processing of cheese (milk clotting, by the hydrolysis of a specific binding in casein), in obtaining protein hydrolyzates, improving the flavor of some foods and also in baking [19]. Proteases fromAspergillus oryzae are used to modify the gluten of wheat flour by facilitating handling and increasing the volume of bread dough. Proteases have been used since ancient times to prepare sauce and other derivatives from soy because this grain has high, good quality protein content. The proteolytic modification of soy proteins helps to improve their functional properties. These enzymes are also used in the synthesis of the artificial sweetener aspartame (through synthesis reactions produced by the thermolysin ofB. thermoprotyolyticus) and in the maturation (softening) of meat, particularly beef, through the alkaline elastase action ofBacillus. The microorganisms most commonly used for the production of proteases in the food industry are from the genusBacillus [7, 18, 26, 40].The requirements for proteases to act as industrial catalysts vary considerably. The enzymes to be used in the production of detergents and in the food industries need be produced in large quantities and should be efficient without further processing (in natura). The proteases already used in the pharmaceutical industries (such as medicines) are produced in small amounts but require extensive purification procedures [18].
## 3. Proteases of Fungal Origin
The cost of production of proteases is the biggest obstacle to their industrial application. Consequently, the development of new processes to increase the yield of proteases with respect to industrial production, concomitantly with reduced production costs, is highly advantageous from the commercial point of view. Increased productivity has been achieved by selecting hyper-productive strains or by improving the culture media [7]. The global market for industrial enzymes reached about US $4.5 billion in 2012, with a projection of US $7.1 billion for 2018. Research on enzymes has revealed their use in different sectors and their catalytic properties have stimulated their use in industrial production and processes. Market growth has been positively influenced by new products and their advantages over traditional industrial methods [22, 44].Although the species of microorganisms that are used for industrial production are few in number, 90% of commercialized proteases are obtained from microbial sources. These are preferred to proteases from plants and animals due to their various characteristics, which are more suitable for biotechnological applications, such as activity within a broad range of temperature and pH, thermal stability, and high catalytic activity [18, 41, 45].Biodiversity is an invaluable resource for biotechnological innovation and it promotes the search for new strains of microorganisms to be used for specific industrial purposes. Because the use of proteases, especially those of the alkaline variety, is expected to rise over the coming decades, the production of microbial proteases represents a good alternative for the development of new methods in order to improve the production of these enzymes, as well as decreasing their price [7, 19]. The increased demand for proteases with specific properties has led biotechnologists to explore new sources of proteases.Most fungal proteases have neutral to slightly acidic characteristics [19]. Xerophilic fungi often contain proteases of low molecular weight (26 to 50 kDa) [24]. The study of fungal proteases has increased in recent decades, but knowledge about proteases from basidiomycetes is still limited [9]. In 2009, approximately 60% of the enzymes commercialized originated from fungi and only five originate macrofungi (three laccases, one peroxidase, and one phytase) [11].A few years ago, the proteases produced from micromycetes were predominant in studies regarding the search for new bioactives with economic and medicinal benefits [24].Aspergillus is considered to be the best producer of proteases [8]. In the food industryA. oryzae andA. sojae are noteworthy for their ability to eliminate bitterness [19].PenicilliumandRhizopus are also considered to produce proteases [5, 46] and the proteases from macromycetes recently gained prominence in the search for new enzymes with specific characteristics. Proteases produced from basidiomycetes such asAgaricus bisporus,Armillariella mellea,Flammulina velutipes,Grifola frondosa,Pleurotus ostreatus,Pleurotus eryngii,Phanerochaete chrysosporium,Schizophyllum commune, and others have been reported [47–50].There are vast majority of microorganisms that exist in nature have not yet been studied. Thus, the search for new natural molecules with interesting physiological effects, and the need to understand the mechanisms of production and regulation of expression of these bioactives, has resulted in the fact that the cultivation conditions that have already been defined and used successfully for ascomycetes such asAspergillus sp. andPenicillium sp. have now been extended to include basidiomycetes in the search for secondary bioactives and metabolites such as enzymes, antibiotics, and organic acids [46].
## 4. Proteases from Basidiomycetes
Basidiomycetes are fungi important for biological communities because they are excellent at degrading wood. Some genera have been used as food for centuries and they have enormous commercial importance. They are also producers of a group of commonly studied extracellular enzymes (xylanases, cellulases, and ligninolytic enzymes) [51]. Proteases play important roles in the physiology of fungi, acting in processes such as germination and sporulation. These enzymes seem to have a close relationship with the lifestyle of saprophytic fungi, as observed inPleurotus citrinopileatus [43].It has been found thatP. pulmonarius, which usually grows on dead timber, secretes subtilisin but does not produce trypsin.P. ostreatus, which grows in living hosts, secretes extracellular trypsin throughout its development. The presence of living tissues as hosts may be related to the expression of trypsin-type proteases [24]. Because most of the nitrogen in timber is in the form of proteins, proteases play a very important role in the metabolism of the proteins in the fungi of white rot in wood and it has been observed that depletion of nitrogen in the medium stimulates the secretion of proteases by fungi [3, 24, 52–57].The mycelial secretion of proteases by saprophytic basidiomycetes has led to the identification of various classes of proteases: subtilases were found inPleurotus ostreatus [58],Phanerochaete chrysosporium [59],Serpula lacrymans [52],Schizophyllum commune [47], andCoprinussp. [60]. Metalloproteinase was reported by Mchenry et al. [61] inChondrostereum purpureum and inHypsizygus marmoreus [62]. The mycelial secretion of aspartate proteases was reported inP. chrysosporium [49, 59],Amanita muscaria [63], andIrpex lacteus [64].Although they are recognized for their nutritional value and the extraction of bioactive compounds of basidiome and mycelia, mushrooms still possess much unexplored information in relation to some of the enzymes that they produce, such as proteases [6]. Proteases extracted from mushrooms have been purified and characterized [48]. The role of proteases in the regulation of the formation of basidiome inHypsizygus marmoreus was described by Terashita et al. [62] and their regulatory role regarding ligninolytic activity inP. chrysosporium andP. ostreatus, under nutritional limitation, was highlighted by Dass et al. [59] and Palmieri et al. [16], respectively.Phanerochaete chrysosporium has produced an acid protease in solid medium with wood, under ligninolytic conditions. This enzyme showed an isoelectric point that was higher than that of most acid proteases (5.6) and it has been characterized as a glycoprotein aspartate protease [49].From a selection of 27 strains of basidiomycetes that produce proteases [3],Lentinula edodes stood out with the largest halo of proteolytic activity using the method of selection on plates containing casein. In this study, the genusPleurotus ranked second in the production of protease. The authors attributed this proteolytic activity to ability of the fungus to grow on substrates with low nitrogen availability [47]. However, Zorn et al. [65] consider that the existence of nitrogen seems to stimulate the production of proteases by fungi. Media containing soybean, casein, gelatin, corn, and yeast are commonly used to produce protease. Other sources, such as starch, lactose, and barley are also used, but it is known that high concentrations of carbohydrates inhibit the production of enzymes [19]. The purification of a fibrinolytic protease fromCordyceps militaris showed characteristics of a 52 kDa subtilisin, which was higher than other fungal proteases. The enzyme rapidly degraded the α and γ chains, but it took longer to degrade the β chains of the fibrin, which was a pattern quite different from the action of proteases derived from snake venom [27]. The fibrinolytic protease activity of basidiomycetes has been recently demonstrated by several authors. Kim et al. [66] purified and characterized a metalloprotease from the mycelium ofPerenniporia fraxinea with fibrinolytic activity. The cloning, purification, and characterization of proteases fromPleurotus ostreatus with similar characteristics were performed by Yin et al. [2], Shen et al. [67], and Joh et al. [68].Although several studies have performed the purification and characterization of proteases from mycelium, basidiome, or culture filtrate, many aspects of the production of these enzymes have yet to be explored. The process of producing basidiome is laborious and time-consuming; it requires large volumes of substrate, space, and qualified labor and these factors hinder research in the laboratory. Cultivations which are performed in the vegetative phase are more viable for research because they can be kept in the laboratory, performed on a small and medium scale, and important parameters such as temperature, humidity, and agitation can be controlled [18].Microbial proteases can be produced in various ways and studies have shown that, depending on the culture conditions, different forms of the same protease can be expressed [19]. Most of the enzymes produced in industry are produced by submerged fermentation [8]. The use of liquid cultures facilitates the purification of bioactives such as enzymes and polysaccharides [3]. The submerged culture ofP. ostreatus in wheat gluten resulted in the secretion of proteases that noticeably increased the overall solubility of the medium [13].Submerged media with complex sources provide higher yields of protease compared to simple media, such as casein or gelatin [19]. However, using submerged culture requires greater resources, specific strains, and very controlled conditions, which does not occur in solid state fermentation, which therefore offers advantages in terms of environmental and economic aspects [8]. The solid cultivation of mushrooms and mycelium in order to obtain bioactives and enzymes remains a very viable alternative; waste from agriculture, forestry, or municipal waste are used for the production of enzymes of industrial interest. The combination of different solid substrates sometimes appears to increase the production of protease by fungi [19].Due to the similarity of the natural habitat of basidiomycetes, these organisms have excelled in the production of enzymes in solid cultures. Solid state fermentation in tomato pulp yielded good colonization and protease production on a large scale usingP. ostreatus [8]. Furthermore, proteases have been obtained by the solid state fermentation of soybean and wheat bran fibers [69]. The literature includes standardized techniques for the high yield recovery of proteases, as well as immobilization methods and different protocols for proteolytic assays and the purification of proteases [19].
## 5. Proteases fromPleurotus spp.
The genusPleurotus is the second main group of cultivated edible mushrooms in the world, comprising more than 40 species [51]. In descending order of worldwide production, the seven most produced edible mushrooms areAgaricus bisporus,Pleurotus spp.,Lentinula edodes,Auriculariaspp.,Volvariella volvacea,Flammulina velutipes, andTremella fuciformis [11]. However, species of the genusPleurotus present advantages when compared with others mushrooms. For example, they can be cultivated in different substrates and temperatures. They are also rich in essential amino acids and vitamins [70].Pleurotus can be grown artificially without major problems and it grows in a disorderly manner in tropical and subtropical regions [51]. This genus is a part of ligninolytic organisms and several studies have reported the ligninolytic capacity of its species [65]. Several bioactive compounds have been extracted from crude extracts, mycelia, and basidiome ofPleurotus spp. for study, such as polysaccharides, hemicelluloses, peptides, glycoproteins, lipids, hydrolytic enzymes, and others [12].Extracts of the basidiome and mycelia ofPleurotus spp. have been used as medicines and as nutritional supplements for human health. Several studies have reported its nutritional, immunomodulatory, antioxidant, antitumor, and hypoglycemic properties, among others.P. ostreatus has been effective in alleviating the effects of hepatotoxicity in rats and it protects the liver, heart, and brain against oxidative stress [51].In recent years, examples of the main genera of cultured basidiomycetes have been studied for their positive therapeutic effects. Hepatoprotective effect was observed forP. pulmonarius,P. ferulae, andP. tuber-regium, which were also active against human cancer cells [71]. Moreover, species of the genus have been used in the processes of bioremediation, delignification, and disinfection of effluent [17].Different strains ofPleurotus spp. (Figure 1) exhibit specific behaviors, which vary depending on the conditions where they are cultivated, including environmental factors such as types of substrates and supplementation. A study of three strains ofP. eryngii using sawdust and rice straw as a substrate for cultivation showed significant differences between the strains regarding growth rates, number of days for the first harvest, biological efficiency, and other parameters [72].P. eryngii is considered as one of the best species of the genus due to its consistency and because it has a longer lifetime than all the other species ofPleurotus. While most of the fungi in the Agaricales order show steady growth in tree trunks,P. eryngii grows well in subtropical pastures and grows excellently during cold periods [72].Figure 1
Pleurotus pulmonarius.The artificial cultivation ofP. eryngii on farms using automatic devices and sawdust has been performed successfully in Korea. The species has also been effective in lowering the levels of blood glucose, the inhibition of tumor cells, and antioxidant activity [73].P. citrinopileatus contains polysaccharides that have antihyperglycemic and antitumor effects [43]. Medicinal properties have also been observed inP. tuber-regium, which is also edible and grows well in tropical and subtropical regions. Several of its bioactive substances have been identified, such as glycoproteins, polysaccharides, and phytochemicals with pharmacological action [74].Basidiome ofP. pulmonarius has shown antitumor, antioxidant, and anti-inflammatory properties, suggesting the therapeutic effects of its metabolites in the treatment against some diseases, such as cancer [75].P. sajor-caju andP. ostreatus have also been investigated for their antioxidant capacity and both species share a similar amino acid profile. However, despite similarities with the properties ofPleurotusspp., there are many studies ofP. ostreatus at the expense of other species of the genus [51]. As stated, there is still little knowledge about the proteases derived from mushrooms, mainly thePleurotus genus [11].Studies of theP. ostreatus,P. eryngii,P. citrinopileatus, andP. chrysosporium species have showed that thePleurotus genus is a producer of proteases that seem to participate in the complex ligninolytic mechanism, degrading the laccase enzyme at certain stages of fungal growth [16, 43, 50, 59, 73].P. pulmonarius has important antimicrobial, anti-inflammatory, antioxidant, and antitumor properties; however, there is still little material in the literature regarding its production of proteases and their characterization. Nevertheless, it is known that the proteases secreted by this species do not appear to participate in the regulation of peroxidases, as has been reported forP. ostreatus proteases [16, 24, 75, 76]. In addition, no degradation of ligninolytic enzymes was observed when they came into contact with proteases fromPhanerochaete chrysosporium [49].In a comparison of six species of basidiomycetes,P. eryngii excelled in the production of protease. Pleurerin, the protease extracted from fruiting bodies ofP. eryngii with anti-HIV-1 action, has presented the characteristics of an aspartic protease due to its N-terminal sequence, which is different from other aspartic fungal proteases [50]. Most proteases of the genusPleurotus feature the characteristics of alkaline subtilases. There are six families of serine proteases, which are based on their amino acid sequence [58]. A study of proteases from 43 species of basidiomycetes showed a predominance of serine protease [9]. An alkaline protease was found in the basidiome ofP. citrinopileatus and it showed a similarity in amino acid sequence withAgaricus bisporus,Epichloë typhina, andPenicillium oxalicum fungi [43].Aspartic proteases are divided into 16 groups and are rarer inPleurotus [2].The fibrinolytic proteases ofPleurotus spp. have received attention in recent years because those searching for new proteases with fibrinolytic capacity are interested in nontoxic and edible fungi [77]. A monomeric protease with fibrinolytic activity was purified 29.3-fold from the basidiome ofP. eryngii produced in corn cob. The protease in question showed a high capacity for degrading fibrin and demonstrated a possible application as a thrombolytic agent. The hydrolysis of α and β chains of fibrinogen occurred in less than 10 min. The enzyme showed characteristics of a serine protease similar to subtilisin, as has been reported for most proteases from the genus [73].In a study by Liu et al. [77] the fibrinolytic and fibrinogenolytic enzyme fromP. pulmonarius grown in submerged state were efficient in degrading the α (3 min) and β (45 min) chains of fibrinogen, followed by γ after 10 h incubation. The enzyme was purified 147-fold and presented good stability at human body temperature, which enables it to be used as an alternative in thrombolytic treatments, including oral applications, because it is an edible fungus. Apart from fibrin degradation, the enzyme was also able to act as a plasminogen activator, which is not common in the literature. A fibrinolytic metalloproteinase purified from mycelia ofP. ostreatus showed a high similarity with the fibrinolytic proteases from the basidiome of the same fungus, which suggests the need for studies related to therapeutic treatments for thrombosis from the mycelium, which can be obtained more quickly and easily than the fruiting bodies [67].Hemolytic proteases have been reported less frequently in the genusPleurotus. The hemolysin of the basidiome ofP. nebrodensis showed apoptosis-inducing activity and antiproliferative cancer cells and also anti-HIV-1 activity, interfering in some way in the permeability of the cell membranes and preventing virus infection [78]. Activity against cancer cells has also been verified for proteases ofP. ostreatus. Hemolysin extracted fromP. eryngii was effective against leukemia cells [79] and showed antimicrobial effect forBacillus sp. [80]. However, these enzymes are not stable at temperatures higher than 40°C, which hinders their possible application as a medicament in the form of food because they would be made inactive by cooking or when passing through the intestinal tract [80, 81].Keratinases are a class of proteases that have received attention in the past. They consist of proteases that are capable of degrading substrates that are rich in insoluble keratins, such as wool, hair, and nail. Because of this, keratinases are used in environmental and technological processes [82]. However, regarding proteases in general, there is little existing research on keratinases of basidiomycetes and there are few reports about keratinases produced by the genusPleurotus spp.The secretome ofP. sapidus has shown protease production and ligninolytic enzymes, but some points remained unidentified, indicating that new enzymes with potential biotechnological applications should be studied and identified in the species [65]. The secretome ofP. ostreatus has shown the presence of proteases with a potential role in the regulation of other extracellular enzymes [13]. Metalloproteases are enzymes that are finely associated with physiological processes and they have been explored in studies of bacteria and mammals; however, there have been very few studies of the metalloproteases of basidiomycetes [68].Pleurotus spp. has been greatly cultivated for research related to medicine and also for the consumption of its fruiting bodies, which have agreeable flavors [24].Although the process of the emergence of the fruiting body of basidiomycetes is still not fully known, the expression of a metalloprotease in the early stages of the formation of a basidiome ofP. ostreatus has been verified, although the enzyme was not expressed in the mycelial stage or in the formation of spores [68]. The increase of proteases in mature hyphae has also been noted in mycelia ofP. pulmonarius, linking the time of the formation of the basidiome with the presence of such enzymes [70]. Furthermore, the addition of inhibitors of metalloproteinases has prevented the normal process of the formation of fruiting bodies ofHypsizygus marmoreus [62]. Vanillic acid has been reported as a good inducer of proteases ofPleurotus ostreatus [58]. In just four days of cultivation in solid state fermentation in residues in tomato,P. ostreatus produced high levels of protease, surpassing fungi which are considered to be the best producers of this enzyme, such asAspergillus [8].The most studied species of the genus isP. ostreatus. Proteases ofP. ostreatus with the capacity to coagulate of milk have been purified [83] and despite the classical techniques of production of proteases, recombinant enzymes have been produced in order to find better yields and new specialties [2, 19, 67, 68].Recent studies of DNA sequence and proteins have come together with the aim of studying enzymatic structures and mechanisms. As already mentioned, due to the vast diversity of proteases, further knowledge of molecular structures in 3D, active sites and mechanisms of catalysis, and enzyme inhibition are increasingly necessary [18]. Based on the N-terminal sequences of proteases ofP. ostreatus, a primer was developed in order to clone and amplify a DNA sequence that showed homologous regions with a hypothetical protease ofNeurospora crassa and another ofPhanerochaete chrysosporium—the first basidiomycete with a completely sequenced genome [58].A recent study compared the genomes of 33 basidiomycetes and resulted in the idea that the division of fungi into white rot fungi and brown rot fungi in wood cannot be sustained because of the existence of DNA sequences shared between the two groups of fungi that attributes complexity to the mechanisms of degradation of cellulose, hemicellulose, and lignin by basidiomycetes [89]. The three-dimensional structures of proteases and their inhibitors provide rich information about the mechanisms involved in catalysis, and they suggest processes for enzyme inhibition that are still unknown. Using X-ray diffraction, the three-dimensional structure of a serine protease inhibitor ofP. ostreatus complexed with subtilisin is shown in Figure 2 [84]. Table 1 shows some characteristics of proteasesPleurotus spp.Table 1
Characteristics of proteasesPleurotus spp.
Species
Molecular weight (kDa)
Optimum pH
Optimum temperature
Kind of protease
References
P. ostreatus
43
[2]
P. ostreatusvar.florida
38.7
7.5
37°C
Serine proteinase
[13]
P. citrinopileatus
28
10
50°C
Serine proteinase
[43]
P. eryngii
11.5
5
45°C
Aspartic protease
[50]
P. ostreatus
32
6.5
35°C
Metalloprotease
[67]
P. eryngii
14
5
30–40°C
Serine proteinase
[73]
P. ostreatus
18.2
7.4
40°C
Metalloprotease
[77]
P. nebrodensis
27
[78]
P. eryngii
17
37°C
[80]
P. ostreatus
Serine proteinase/metalloprotease
[83]
P. ostreatus
22
6.7
[84]
P. ostreatus
75
7.8
Serine protease
[85]
P. ostreatus
30/19/42.5
7.4/5.6
Serine protease/metalloprotease
[86]
P. sajor-caju
14.5/86
Metalloprotease
[87]
P. ostreatus
97/48.5
5.5–6.5
Cysteine protease
[88]Figure 2
Ribbon model of subtilisin BPN (blue) fromBacillus amyloliquefaciens in complex with serine protease inhibitor POIA1 (red) and calcium ion (grey sphere). Figure from pdbid: 1V5I.
## 6. Conclusions
There is still much progress to be made in the study of proteases ofPleurotus spp. and there is still much to be discovered regarding the genome, proteome, and metabolome of the genus. Several proteases ofPleurotus spp. have shown unique characteristics, which require further research.Pleurotus ostreatus is one of the few edible mushrooms produced on an industrial scale. Most of the research to be found in the literature concerns artificially cultivated basidiomycetes. It is known that there is a high demand in industry for proteolytic enzymes with appropriate specificity and stability to temperature, pH, metal ions, and so forth. However, it is common to find that studies of proteases of basidiomycetes recommend that further, more detailed, studies are required to reveal the mechanisms and physiological effects of proteases. Thus, studies of new proteases of the genusPleurotus, especially wild species, are an area of biotechnology that needs to be explored.
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*Source: 290161-2015-06-09.xml* | 2015 |
# Optimized Design of Mechanical Chain Drive Based on a Wireless Sensor Network Data Algorithm
**Authors:** Min Zhuang; Ge Li; Kexin Ding; Guansheng Xu
**Journal:** Journal of Sensors
(2021)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2021/2901624
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## Abstract
In this paper, we use a wireless sensor network data algorithm to optimize the design of mechanical chain drive by conducting an in-depth study of the mechanical chain drive optimization. We utilize the crowdsourcing feature of the swarm-wise sensing network for assisted wireless sensor networking to achieve crowdsourcing-assisted localization. We consider a framework for crowdsourcing-assisted GPS localization of wireless sensor networks and propose two recruitment participant optimization objectives, namely, minimum participants and time efficiency, respectively. A model and theoretical basis are provided for the subsequent trusted data-driven participant selection problem in swarm-wise sensing networks. The sprocket-chain engagement frequency has the greatest influence on the horizontal bending-vertical bending composite in different terrain conditions. The dynamic characteristics under working conditions are most influenced, while the scraping of the scraper and the central groove significantly influenced horizontal bending and vertical bending. Under load conditions, the amplitude of the scraper and central groove scraping increases significantly, which harm the dynamics of the scraper conveyor. By monitoring the speed difference between the head and tail sprockets and the overhang of the scraper, the tensioning status of the scraper conveyor chain can be effectively monitored to avoid chain jamming and chain breakage caused by the loose chain, thus improving the reliability and stability of the scraper conveyor.
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## Body
## 1. Introduction
The development of wireless sensor networks and group intelligence-aware networks has been carried out relatively independently, and no research has been conducted to converge the two. Network convergence originally means that with the development of technology, the telephone network and data network gradually merge into one; that is, voice signal transmission through data networks has become a reality and continues to spread. The merging of telephone and data networks will greatly reduce the operating costs of communication networks and simplify the management of the network for users; the biggest benefit is the cost savings. The meaning behind this is that the emergence of new technologies can enhance the original technology, which is often very mature, and preapplication has built a huge system with huge investment [1]. In wireless sensor network monitoring applications that require high reliability of data collection, the ability of the nodes to collect complete data from the monitoring area and transmit them to the user center in a reliable and timely manner is directly related to the effectiveness of the network application [2]. For example, in wireless sensor network data collection based on applications such as soil site monitoring, to accurately predict and identify risk factors, it is not only required that the sensor network can collect data reflecting the complete status of the monitoring area but also required that these data are reliably transmitted to the user within a specified delay [3]. However, random deployment of nodes or coverage voids created during network operation degrades the network coverage quality of service, resulting in the network not being able to collect complete data from the monitoring area.There are also a variety of factors that affect reliable data collection during the data transmission phase; for example, sensor nodes are battery-powered; once the nodes die due to energy exhaustion, data transmission will be interrupted and cannot continue, affecting the continuous data collection; data collection delays caused by factors such as congestion waiting, dormant scheduling, and unreliable links are too large to meet the data of delay-sensitive wireless sensor network application collection performance requirements; data overflow generated by insufficient node storage space and packet loss due to unreliable links degrade data collection rate performance [4]. From the working principle of the scraper conveyor, the scraper chain is the key component of the scraper conveyor, which is the traction mechanism of the scraper conveyor and is the component that transmits traction force and directly scrapes and transports materials. The chain operates under sliding friction conditions and is not only subjected to large static and dynamic loads but also eroded by mine water, so it usually has a high failure rate. Often, the original technology is already very mature and the early application has established a huge system, with huge investment. The original system does not completely lose its value but can also be used by advanced new technologies. Therefore, a fusion mechanism is needed to enable the new technology and the original technology to be combined into one and function together. Typical failure forms of scraper chains include chain jamming, chain skipping, chain breaking, etc. Some studies show that the reliability of the scraper conveyor decreases exponentially as the working time increases [5]. Although this method can effectively detect the occurrence of faults, it has a certain lag; i.e., it cannot predict and avoid faults in advance.Wireless sensor networks inevitably face the problems of incomplete data collection in the monitoring area due to coverage voids: the problem of data collection rate degradation due to unreliable link packet loss, the problem of mobile sink data collection techniques not meeting the low latency collection of event monitoring data, and the problem of sink not reliably collecting complete data in the monitoring area due to limited node resources. Unlike the existing message detection-based hole detection algorithm, the hole detection algorithm in this paper can rely on the information of incomplete coverage intersection for concurrent detection of multiple connected holes, which reduces the energy consumption and time of hole detection. In addition, the hole repair algorithm in this paper reduces the number of mobile nodes required for hole repair by optimizing the hole repair drive nodes and can achieve low redundancy and complete repair of covered holes. Considering the dynamic change of node energy and data collection, the minimum dwell time and maximum waiting time of the mobile device are predicted based on the Markov model to avoid its large-span movement in the monitoring area. Compared with existing methods, PPAGS can largely increase the data collection rate with a small number of mobile devices while reducing the data collection delay.
## 2. Current Status of Research
Considering the operating characteristics of the scraper conveyor, based on the existing advanced sensing technologies, relevant experts and scholars have overcome the problems in assessing the operating condition of the scraper conveyor, and a certain research base has been established, but it is still limited to the system platform design, wireless sensing technology development, and data processing algorithm optimization [6]. The current research mostly uses sensors and measurement devices to measure different parameters of the chain drive system, and the main measurement tools include tension sensors, angle sensors, electromagnetic sensors, Hall elements, and electromagnetic detection devices [7]. In turn, a wireless sensor network is designed for data transmission, and data analysis of different parameters is used to assess the operating status of the equipment for condition monitoring and fault determination of the scraper conveyor [8]. To improve data transmission efficiency, in wireless sensing technology development, Cunningham designed a remote monitoring system for a scraper conveyor combining an RFID wireless sensor network, CAN bus, and industrial Ethernet [9]. Sadeeq and Zeebaree designed a wireless detection system for scraper conveyor drive based on RFID technology [10]. Amutha et al. developed a remote monitoring system based on industrial Ethernet and a wireless mesh switching network-based remote monitoring communication platform to realize remote on-board monitoring of the scraper conveyor [11]. However, although the efficiency of data acquisition was improved to some extent through the design of the network structure, it still failed to apply the measured data to the monitoring of the operation status of the equipment.When random coverage is performed, there will be several uncovered areas, often called coverage holes, despite the dense network as a guarantee of coverage. For this reason, mobile nodes are added to the sensor network and allowed to move after random deployment to compensate for the uncovered areas. This is an important class of research problems, which is called the coverage problem of mobile wireless sensor networks. In this paper, we will study this type of problem with the main goal of obtainingK-recoveries at minimal movement cost [12]. The coverage problem for mobile sensors is the initial version of mobile swarm intelligence sensing, where sensors can only be controlled centrally or are given very limited control strategies. The study of how mobile swarm intelligence perception can provide location information for the mobile sensor coverage problem is one of the research areas in this paper [13]. The BikeNet system uses various sensors and smartphones equipped on cyclists’ bikes to sense and share the air quality and road conditions around the cycling path so that cyclists have real-time knowledge of the environment for path selection and optimal cycling experience [14]. The CrowdAtlas system addresses the current problem of untimely and costly updates of electronic maps by using sensory data from GPS sensors of cell phones and cars of many users in the city to build a real-time updated map of urban roads. The monitoring system includes an electromagnetic sound emitter and an electromagnetic sound sensor [15]. The electromagnetic sound emitted by the electromagnetic sound emitter is reflected when it meets the scraper chain of the scraper conveyor. The electromagnetic sound sensor determines the degree of surface damage to the scraper chain by analyzing the reflected electromagnetic sound. This monitoring system predicts scraper chain failure by directly monitoring the physical form of the scraper chain. The disadvantage is that the working environment of the scraper conveyor is harsh and the scraper chain will be covered by coal and other materials during normal operation, which makes monitoring inaccurate or even completely impossible.The actual working environment of the scraper conveyor is usually harsher, manifested by strong vibration and strong electromagnetic interference. It is also required that these data be reliably transmitted to the user within a specified delay. However, random deployment of nodes or coverage holes generated during network operation reduces the quality of network coverage services, resulting in the inability of the network to collect complete data in the monitoring area. For some coal mines with high water seepage, it is also necessary to pay attention to the fact that mine water may flood the return scraper located below the middle plate. Therefore, the tension monitoring system for the scraper conveyor needs to face the problems of waterproof, antivibration, antielectromagnetic interference, electromagnetic magnetic shielding, etc. For the problems of mine water and strong vibration, it is necessary to improve the stability of the hardware design of the monitoring system, as well as to design the protection scheme. On the other hand, for the mine water and electromagnetic environment can affect the communication and other functions of the tension monitoring system, there is also a need to conduct in-depth research on wireless communication under the mine. In addition, wireless sensor network data collection technology performance indicators include network throughput, robustness, security, and confidentiality. In addition to energy efficiency, which is the primary performance indicator for all wireless sensor network applications, other network performance indicators vary from one application scenario to another. The application of wireless sensor networks in the military field needs to ensure the security and confidentiality of data collection.
## 3. Optimized Design Analysis of Mechanical Chain Drive with the Wireless Sensor Network Data Algorithm
### 3.1. Wireless Sensor Network Data Algorithm Design
Wireless link quality affects the performance of network routing protocols. Wireless links are unreliable due to the external environment and cochannel signals. Evaluating the link quality helps to improve the packet forwarding rate and helps to reduce the energy consumption of the network nodes. Identifying credible real data from group-wise perception, participant perception with noise or even conflicting data is a challenging problem. A part of the research focuses on authentic discovery algorithms, and these studies focus on estimating the data quality of participants and discovering potentially authentic data synchronously by quality-based data fusion. They describe the reliability of participants as the variance of a normal distribution, and the estimated true values are usually computed as a weighted average sum or found using a Bayesian approach through EM algorithms or parameterization [16]. As mentioned in Section 3 for moving sensors to achieve specific coverage requirements, collecting the GPS locations of randomly placed sensors in the network is the first step in computing and planning sensor movements, so it is important to assist mobile wireless sensor networks for GPS localization. It makes sense to set the application scenario within urban centers (urban fields) where many people with smart devices are active. This provides a greater opportunity to provide mobile wireless sensor network GPS information. Of course, recruiting participants for the swarm intelligence sensing task needs to be considered at a certain cost. Firstly, recruiting as few participants as possible is one of the goals, and secondly, those suitable participants need to be selected for the recruitment process.The wireless sensor network is abstractly represented asG=V,E,Q,W, where V represents the set of network nodes; E represents the set of wireless links of network nodes; Q represents the set of network link quality, and the link i,j quality is denoted as i,pj, assuming that the link quality between all nodes is known; and W represents the set of work schedules of network nodes, and the work schedule wi of any node i is represented by a string consisting of 0 and 1 sequences. A work cycle of the network is denoted as T, and a time slot is denoted as π. There are T time slots in a work cycle, and each time slot π completes one data transmission. The state of each time slot is divided into a sleep state and active state, which are represented by 1 and 0, respectively. In period T, the time slot position of the active state of node i is calculated according to
(1)Xi,n=iIDmodTπ,Xi,n−1=Xi,n−CiIDmodTπ.The next-hop forwarding node selection considers the residual energy of the nodes as well as the link quality, which balances the energy consumption of the network nodes and increases the network lifetime. The link metric of nodei with neighbor node j is defined as
(2)SLQEi,j=βpi,j+1−βEj1+βW,∑i,j=1Mxijyij≤1.Due to other reasons such as load changes, the chain tension of the scraper conveyor will change constantly during the actual coal mining work, making the whole section or local tension of the chain exceed the design value. Too much or too little chain tension will affect the normal operation of the scraper conveyor. If the chain is too loose, the chain will easily break away from the sprocket at the separation point of the head sprocket or the tail sprocket and the chain, causing impact and vibration of the sprocket and causing accidents such as chain breakage and chain jamming in serious cases [17]. Data overflow caused by insufficient node storage space and data packet loss caused by unreliable links reduce the performance of the data collection rate. If the chain is too tight, it will increase the friction between the chain and the sprocket and the middle groove, increase the running resistance, make the power consumption of the scraper conveyor increase, and accelerate the wear of the related equipment. The scraper conveyor is not only used as coal transportation equipment in the coal mining working face but also used as a track for the coal mining machine to run. The coal mining machine moves on the scraper conveyor slide and cuts the coal wall, and the coal falls on the scraper conveyor and is pushed to the head by the scraper and scraper chain. Although this method can effectively detect the occurrence of faults, it has a certain hysteresis; that is, it cannot predict and avoid faults in advance. Wireless sensor networks inevitably face the problem of incomplete collection of data in the monitoring area caused by coverage holes and the problem of reduced data collection rate due to packet loss on unreliable links. The function of the scraper conveyor determines that the body of the scraper conveyor is very low, and during operation, there is a large amount of ore impact accompanied by electromagnetic interference from the high-power motor. For some coal mines, large amounts of mine water can seep out of the comprehensive mining face and its presence will also affect the monitoring system, as shown in Figure 1. This principle ensures that the mobile node introduced by the selected cavity driving node has the maximum area for the repair of the cavity region at the cavity repair location. The covered voids consist of boundary arcs of multiple void boundary nodes, and each node has at most two incomplete coverage intersections in the void area.Figure 1
Wireless sensor network framework.If each introduced mobile node can only eliminate one void boundary node, the mobile node transforms into a void boundary node and adds a void boundary node in the case of incomplete repair of the coverage void, which is slower in void repair, and when the mobile node introduced by a certain driver node can eliminate more incomplete coverage intersections, it can eliminate more void boundary nodes, which will speed up the void repair. This will speed up the hole repair and help reduce the number of mobile nodes required for hole repair. When the mobile nodes introduced at one time have eliminated all the incomplete coverage intersections, it means that the current hole is repaired.(3)pA=mintij.Based on the introduction of mobile node undivided holes, the nonparallel dichotomous repair strategy ensures that the coverage holes are completely repaired because at least 2 incomplete coverage intersections are eliminated per mobile node introduction during the nonparallel repair of the holes based on the drive node selection principles 1 and 3. Each introduced mobile node produces a maximum of 2 incomplete coverage intersections. The trajectory formed by the blade edge line rotating around the rotary axis is a single-leaf hyperboloid, which can be studied by using the properties of the single-leaf hyperboloid, as shown in Figure2, which can be regarded as the edge line AB rotating around the rotary axis OZ.Figure 2
Network data algorithm framework.The contact force between scraper chains is the main cause of chain fatigue and failure. Or use the Bayesian method to find the true value through the EM algorithm or parameterized method. Under the framework of crowdsourcing, assist the mobile wireless sensor network for GPS positioning. The study of the force characteristics of the chain drive system is essentially a study of the change of contact force between scraper chains at different positions. In the transmission process of the scraper conveyor chain drive system, the scraper chain, as the main traction component, includes two types of horizontal circular chain (horizontal chain) and vertical circular chain (vertical chain). The driving chain wheel teeth are circular arc tooth profiles, and there are chain nest grooves and vertical chain grooves distributed between any adjacent teeth. In the process of the chain drive system, the horizontal chain lies flat in the chain nest groove, and the vertical chain is connected with the horizontal chain and distributed in the vertical chain groove. The tooth profile of the driving sprocket is not only the main part of the scraper chain and teeth engagement and disengagement but also the main area of the sprocket bearing force, so the parametric modeling is of great significance to the structure development and optimization design of the sprocket.(4)D0=psin60/N2−dcos60/N2,W=2H+dcos90N+Asin90N−d.The link metric is between nodei and neighbor node j. The Creo2.0 software development platform enables the virtual assembly of different mechanical systems and can be used for the rapid construction of 3D models of scraper conveyor chain drive systems. Among them, the “bottom-up” design method is the most conventional modeling method for virtual assembly, which models each component separately and then assembles each part into a whole in a step-by-step manner from the bottom up according to a certain installation order, constraint relationship, and hierarchy, which requires constant assembly and interference analysis to coordinate the design process to avoid interference errors. The “top-down” assembly design method is adopted for the 3D model of the chain drive system, which can achieve a high degree of coordination between the parametric design of key components and the virtual assembly process. The main principle is as follows: set the overall framework of the assembly or structural assembly scheme, which is used as the installation directory tree of the whole product, and in the assembly process, based on the directory tree, the subordinate assembly relationship and assembly order of different parts can be established from the top-level down to the bottom-level components and parts for assembly.
(5)ddt∂T∂qT+∂T∂qT−φqTp−θqTμ=Q,where the complete constraint equation of the system satisfies(6)φq,t=1.The incomplete constraint equations of the system satisfy(7)θq,q1,t=1.Its basic idea comes from a collective intelligence that includes the contributions of thousands of individuals. And smart devices, such as mobile smartphones, offer a surprisingly diverse range of uses. This flexibility is mainly because these smart devices are often embedded with highly accurate GPS positioning systems. People can easily take these smart devices with them and use them anytime and anywhere, which greatly enhances the mobility of these smart devices. The GPS positioning of mobile wireless sensor networks is assisted in the framework of crowdsourcing. As mentioned in Section3 for moving sensors to achieve specific coverage requirements, collecting GPS locations of randomly placed sensors in the network is the first step in computing and planning sensor movements, so it is important to assist mobile wireless sensor networks for GPS localization. A virtual prototype model of a double-chain traction chain transmission system considering the movement constraints and force relationships between different components and the dynamic characteristics of the chain transmission system under normal operating conditions, stuck-chain fault conditions, and broken-chain fault conditions is studied. It makes sense to set the application scenario within the urban fields (urban centers), where many people with smart devices are active. This provides a greater opportunity to provide GPS information from mobile wireless sensor networks. Of course, recruiting participants for the swarm intelligence sensing task needs to be considered at a certain cost: firstly recruiting as few participants as possible is one of the goals, and secondly, those suitable participants need to be selected for the recruitment process.
(8)Fq,u,μ,λ,t=1,Gu,q=u+q,ϕq,t=1.To study the dynamics of the chain drive system, it is necessary to study the complex contact problem between different rigid body surfaces while considering its multibody dynamic characteristics. The contact between different rigid bodies of the chain drive system is a complex nonlinear problem, and the contact collision can be regarded as a time-varying dynamic process, and the most used algorithms to deal with the boundaries of the contact problem are the implicit Lagrange algorithm and the display penalty function method [18]. In this section, the research and analysis of the contact problem between different rigid bodies of the chain drive system mainly involve contact collision detection and contact force solution. The polygonal contact model satisfies the following two characteristics: the surfaces of any rigid bodies in contact with each other can be described by polygons, and the commonly used methods for constructing polygonal surfaces include Bessel curves and NURBS methods; the contact force between any two contacting bodies of the system can be determined based on the elastic base model.
### 3.2. Experimental Optimization Design of Mechanical Chain Drive
Since the tension acquisition device needs to follow the movement of the scraper to collect the tension of the scraper chain in real time, the tension acquisition device cannot obtain a stable energy source by wired means. The energy source of the tension acquisition device is set as a battery because it relies on the power generation principle such as piezoelectric vibration capturing energy, which leads to the unstable supply voltage. The capacity of the battery and the power consumption of the tension collection device determine the service time of the tension collection device [19]. The capacity of the battery is limited by the size of the battery, and the tension collection device and the battery are encapsulated together in the cavity of the lower pressure plate of the scraper, so there is a great limitation on the size and quantity of the battery. Therefore, to maximize the service time of the tension acquisition device, an energy-saving strategy is designed to reduce the power consumption of the tension acquisition device. The energy-saving strategy requires a proximity switch on the hardware and a dormant program on the software to form in conjunction. As mentioned above, the wireless communication distance is very short, and the data sent by the tension acquisition device can only be received by the data receiving device when the device moves with the squeegee to a position close to the data receiving device installed in the middle plate. Therefore, a proximity switch needs to be designed to notify the tension acquisition device when to start sending data. When the data transmission ends or is no longer within the communication range, the tension acquisition device can turn off the wireless transmitting function and enter the low-power sleep mode to save energy.The theoretical calculation of the dimensions of each component of the microstrip antenna was carried out above, and to further optimize the performance of the theoretically calculated natures, the length of the radiating patch of the microstrip antenna and the width of the 1/4 wavelength impedance converter were scanned by the simulation software HFSS to seek the dimensions that satisfy the best performance of the antenna. During the actual operation of the chain drive system, there are obvious contact relations between the components such as scraper chain, sprocket, and central groove, and contact pairs are formed between two rigid bodies in arbitrary contact, which play an important role in analyzing the interaction relations of the contacting rigid bodies. By analyzing the geometric position of different rigid body polygon contact planes, the contact collision can be detected. The following analysis of the contact between the driving sprocket and scraper chain and the contact relationship between adjacent scraper chains provides an effective basis for studying the contact collision relationship of different rigid bodies of the chain drive system, as shown in Figure3.Figure 3
Contact relationship between the chain wheel and scraper chain.In the actual operation of the chain drive system, there are obvious contact relations between the components such as scraper chain, sprocket, and central groove, and contact pairs are formed between two rigid bodies in arbitrary contact, which play an important role in the analysis of the interaction relations of contacting rigid bodies. By analyzing the geometric position of different rigid body polygon contact planes, the contact collision can be detected. The following analysis of the contact between the driving sprocket and scraper chain and the contact relationship between adjacent scraper chains provides an effective basis for studying the contact collision relationship of different rigid bodies in the chain drive system. By optimizing the driving node, the mobile node for cavity repair and the optimal repair location are determined to ensure that the area of the cavity to be repaired each time reaches the maximum. The experimental results show that compared with the existing methods, CHDARPI has reduced the average detection time and detection energy consumption by 15.2% and 16.7%, respectively.In actual operation, chain jamming and chain breakage failures are the most common forms of failure in the chain drive system of the scraper conveyor. In this paper, based on the simulation analysis of the virtual prototype model of the chain drive system under normal operating conditions, the dynamics of the chain drive system when the chain jamming fault and chain breakage fault occur are studied by setting the fault conditions. When the chain jamming fault occurs, it shows the jamming and tensing of the scraper chain; when the chain breakage fault occurs, it shows the sudden breakage of a scraper chain, and the scraper chains at the fault location are separated from each other [20]. These two protocols can effectively reduce the average energy consumption of network nodes, and the data collection rate of both exceeds 88%. To simulate the chain jamming fault condition, the sudden tensioning of the chain drive system can be realized by setting the sudden increase in the stiffness coefficient of the contact pair between the horizontal chain and the vertical chain, and the scraper chains forming the contact pair can be separated by releasing the contact pair between the horizontal chain and the vertical chain, thus simulating the chain breakage fault of the chain drive system [21]. Figure 4 depicts the study process of the dynamic characteristics of the chain drive system under the fault condition. The virtual prototype model of the chain drive system under the fault condition can be established quickly by setting the contact stiffness surge and releasing the contact constraints, and the simulation solution can be realized.Figure 4
Chain failure simulation analysis flow.To research the monitoring and diagnosis method of the heavy-duty scraper conveyor chain drive system, the dynamic characteristics of the chain drive system need to be fully considered. At present, the study of dynamic characteristics of chain drive systems based on the experimental method is costly and difficult to operate, so most of the research mostly focuses on model simplification and theoretical analysis of the single-chain system, and the reliability of the research method is low [22]. Considering the complexity of the structural composition of the scraper conveyor and the difficulty of the study of the dynamic characteristics, this section establishes a virtual prototype model of the double-chain traction chain drive system based on the multibody dynamic theory and contact collision theory, which integrates the motion constraints and force relationships between different components and studies the dynamic characteristics of the chain drive system under the conditions of normal operation, chain jamming fault operation, and chain breakage fault operation.
## 3.1. Wireless Sensor Network Data Algorithm Design
Wireless link quality affects the performance of network routing protocols. Wireless links are unreliable due to the external environment and cochannel signals. Evaluating the link quality helps to improve the packet forwarding rate and helps to reduce the energy consumption of the network nodes. Identifying credible real data from group-wise perception, participant perception with noise or even conflicting data is a challenging problem. A part of the research focuses on authentic discovery algorithms, and these studies focus on estimating the data quality of participants and discovering potentially authentic data synchronously by quality-based data fusion. They describe the reliability of participants as the variance of a normal distribution, and the estimated true values are usually computed as a weighted average sum or found using a Bayesian approach through EM algorithms or parameterization [16]. As mentioned in Section 3 for moving sensors to achieve specific coverage requirements, collecting the GPS locations of randomly placed sensors in the network is the first step in computing and planning sensor movements, so it is important to assist mobile wireless sensor networks for GPS localization. It makes sense to set the application scenario within urban centers (urban fields) where many people with smart devices are active. This provides a greater opportunity to provide mobile wireless sensor network GPS information. Of course, recruiting participants for the swarm intelligence sensing task needs to be considered at a certain cost. Firstly, recruiting as few participants as possible is one of the goals, and secondly, those suitable participants need to be selected for the recruitment process.The wireless sensor network is abstractly represented asG=V,E,Q,W, where V represents the set of network nodes; E represents the set of wireless links of network nodes; Q represents the set of network link quality, and the link i,j quality is denoted as i,pj, assuming that the link quality between all nodes is known; and W represents the set of work schedules of network nodes, and the work schedule wi of any node i is represented by a string consisting of 0 and 1 sequences. A work cycle of the network is denoted as T, and a time slot is denoted as π. There are T time slots in a work cycle, and each time slot π completes one data transmission. The state of each time slot is divided into a sleep state and active state, which are represented by 1 and 0, respectively. In period T, the time slot position of the active state of node i is calculated according to
(1)Xi,n=iIDmodTπ,Xi,n−1=Xi,n−CiIDmodTπ.The next-hop forwarding node selection considers the residual energy of the nodes as well as the link quality, which balances the energy consumption of the network nodes and increases the network lifetime. The link metric of nodei with neighbor node j is defined as
(2)SLQEi,j=βpi,j+1−βEj1+βW,∑i,j=1Mxijyij≤1.Due to other reasons such as load changes, the chain tension of the scraper conveyor will change constantly during the actual coal mining work, making the whole section or local tension of the chain exceed the design value. Too much or too little chain tension will affect the normal operation of the scraper conveyor. If the chain is too loose, the chain will easily break away from the sprocket at the separation point of the head sprocket or the tail sprocket and the chain, causing impact and vibration of the sprocket and causing accidents such as chain breakage and chain jamming in serious cases [17]. Data overflow caused by insufficient node storage space and data packet loss caused by unreliable links reduce the performance of the data collection rate. If the chain is too tight, it will increase the friction between the chain and the sprocket and the middle groove, increase the running resistance, make the power consumption of the scraper conveyor increase, and accelerate the wear of the related equipment. The scraper conveyor is not only used as coal transportation equipment in the coal mining working face but also used as a track for the coal mining machine to run. The coal mining machine moves on the scraper conveyor slide and cuts the coal wall, and the coal falls on the scraper conveyor and is pushed to the head by the scraper and scraper chain. Although this method can effectively detect the occurrence of faults, it has a certain hysteresis; that is, it cannot predict and avoid faults in advance. Wireless sensor networks inevitably face the problem of incomplete collection of data in the monitoring area caused by coverage holes and the problem of reduced data collection rate due to packet loss on unreliable links. The function of the scraper conveyor determines that the body of the scraper conveyor is very low, and during operation, there is a large amount of ore impact accompanied by electromagnetic interference from the high-power motor. For some coal mines, large amounts of mine water can seep out of the comprehensive mining face and its presence will also affect the monitoring system, as shown in Figure 1. This principle ensures that the mobile node introduced by the selected cavity driving node has the maximum area for the repair of the cavity region at the cavity repair location. The covered voids consist of boundary arcs of multiple void boundary nodes, and each node has at most two incomplete coverage intersections in the void area.Figure 1
Wireless sensor network framework.If each introduced mobile node can only eliminate one void boundary node, the mobile node transforms into a void boundary node and adds a void boundary node in the case of incomplete repair of the coverage void, which is slower in void repair, and when the mobile node introduced by a certain driver node can eliminate more incomplete coverage intersections, it can eliminate more void boundary nodes, which will speed up the void repair. This will speed up the hole repair and help reduce the number of mobile nodes required for hole repair. When the mobile nodes introduced at one time have eliminated all the incomplete coverage intersections, it means that the current hole is repaired.(3)pA=mintij.Based on the introduction of mobile node undivided holes, the nonparallel dichotomous repair strategy ensures that the coverage holes are completely repaired because at least 2 incomplete coverage intersections are eliminated per mobile node introduction during the nonparallel repair of the holes based on the drive node selection principles 1 and 3. Each introduced mobile node produces a maximum of 2 incomplete coverage intersections. The trajectory formed by the blade edge line rotating around the rotary axis is a single-leaf hyperboloid, which can be studied by using the properties of the single-leaf hyperboloid, as shown in Figure2, which can be regarded as the edge line AB rotating around the rotary axis OZ.Figure 2
Network data algorithm framework.The contact force between scraper chains is the main cause of chain fatigue and failure. Or use the Bayesian method to find the true value through the EM algorithm or parameterized method. Under the framework of crowdsourcing, assist the mobile wireless sensor network for GPS positioning. The study of the force characteristics of the chain drive system is essentially a study of the change of contact force between scraper chains at different positions. In the transmission process of the scraper conveyor chain drive system, the scraper chain, as the main traction component, includes two types of horizontal circular chain (horizontal chain) and vertical circular chain (vertical chain). The driving chain wheel teeth are circular arc tooth profiles, and there are chain nest grooves and vertical chain grooves distributed between any adjacent teeth. In the process of the chain drive system, the horizontal chain lies flat in the chain nest groove, and the vertical chain is connected with the horizontal chain and distributed in the vertical chain groove. The tooth profile of the driving sprocket is not only the main part of the scraper chain and teeth engagement and disengagement but also the main area of the sprocket bearing force, so the parametric modeling is of great significance to the structure development and optimization design of the sprocket.(4)D0=psin60/N2−dcos60/N2,W=2H+dcos90N+Asin90N−d.The link metric is between nodei and neighbor node j. The Creo2.0 software development platform enables the virtual assembly of different mechanical systems and can be used for the rapid construction of 3D models of scraper conveyor chain drive systems. Among them, the “bottom-up” design method is the most conventional modeling method for virtual assembly, which models each component separately and then assembles each part into a whole in a step-by-step manner from the bottom up according to a certain installation order, constraint relationship, and hierarchy, which requires constant assembly and interference analysis to coordinate the design process to avoid interference errors. The “top-down” assembly design method is adopted for the 3D model of the chain drive system, which can achieve a high degree of coordination between the parametric design of key components and the virtual assembly process. The main principle is as follows: set the overall framework of the assembly or structural assembly scheme, which is used as the installation directory tree of the whole product, and in the assembly process, based on the directory tree, the subordinate assembly relationship and assembly order of different parts can be established from the top-level down to the bottom-level components and parts for assembly.
(5)ddt∂T∂qT+∂T∂qT−φqTp−θqTμ=Q,where the complete constraint equation of the system satisfies(6)φq,t=1.The incomplete constraint equations of the system satisfy(7)θq,q1,t=1.Its basic idea comes from a collective intelligence that includes the contributions of thousands of individuals. And smart devices, such as mobile smartphones, offer a surprisingly diverse range of uses. This flexibility is mainly because these smart devices are often embedded with highly accurate GPS positioning systems. People can easily take these smart devices with them and use them anytime and anywhere, which greatly enhances the mobility of these smart devices. The GPS positioning of mobile wireless sensor networks is assisted in the framework of crowdsourcing. As mentioned in Section3 for moving sensors to achieve specific coverage requirements, collecting GPS locations of randomly placed sensors in the network is the first step in computing and planning sensor movements, so it is important to assist mobile wireless sensor networks for GPS localization. A virtual prototype model of a double-chain traction chain transmission system considering the movement constraints and force relationships between different components and the dynamic characteristics of the chain transmission system under normal operating conditions, stuck-chain fault conditions, and broken-chain fault conditions is studied. It makes sense to set the application scenario within the urban fields (urban centers), where many people with smart devices are active. This provides a greater opportunity to provide GPS information from mobile wireless sensor networks. Of course, recruiting participants for the swarm intelligence sensing task needs to be considered at a certain cost: firstly recruiting as few participants as possible is one of the goals, and secondly, those suitable participants need to be selected for the recruitment process.
(8)Fq,u,μ,λ,t=1,Gu,q=u+q,ϕq,t=1.To study the dynamics of the chain drive system, it is necessary to study the complex contact problem between different rigid body surfaces while considering its multibody dynamic characteristics. The contact between different rigid bodies of the chain drive system is a complex nonlinear problem, and the contact collision can be regarded as a time-varying dynamic process, and the most used algorithms to deal with the boundaries of the contact problem are the implicit Lagrange algorithm and the display penalty function method [18]. In this section, the research and analysis of the contact problem between different rigid bodies of the chain drive system mainly involve contact collision detection and contact force solution. The polygonal contact model satisfies the following two characteristics: the surfaces of any rigid bodies in contact with each other can be described by polygons, and the commonly used methods for constructing polygonal surfaces include Bessel curves and NURBS methods; the contact force between any two contacting bodies of the system can be determined based on the elastic base model.
## 3.2. Experimental Optimization Design of Mechanical Chain Drive
Since the tension acquisition device needs to follow the movement of the scraper to collect the tension of the scraper chain in real time, the tension acquisition device cannot obtain a stable energy source by wired means. The energy source of the tension acquisition device is set as a battery because it relies on the power generation principle such as piezoelectric vibration capturing energy, which leads to the unstable supply voltage. The capacity of the battery and the power consumption of the tension collection device determine the service time of the tension collection device [19]. The capacity of the battery is limited by the size of the battery, and the tension collection device and the battery are encapsulated together in the cavity of the lower pressure plate of the scraper, so there is a great limitation on the size and quantity of the battery. Therefore, to maximize the service time of the tension acquisition device, an energy-saving strategy is designed to reduce the power consumption of the tension acquisition device. The energy-saving strategy requires a proximity switch on the hardware and a dormant program on the software to form in conjunction. As mentioned above, the wireless communication distance is very short, and the data sent by the tension acquisition device can only be received by the data receiving device when the device moves with the squeegee to a position close to the data receiving device installed in the middle plate. Therefore, a proximity switch needs to be designed to notify the tension acquisition device when to start sending data. When the data transmission ends or is no longer within the communication range, the tension acquisition device can turn off the wireless transmitting function and enter the low-power sleep mode to save energy.The theoretical calculation of the dimensions of each component of the microstrip antenna was carried out above, and to further optimize the performance of the theoretically calculated natures, the length of the radiating patch of the microstrip antenna and the width of the 1/4 wavelength impedance converter were scanned by the simulation software HFSS to seek the dimensions that satisfy the best performance of the antenna. During the actual operation of the chain drive system, there are obvious contact relations between the components such as scraper chain, sprocket, and central groove, and contact pairs are formed between two rigid bodies in arbitrary contact, which play an important role in analyzing the interaction relations of the contacting rigid bodies. By analyzing the geometric position of different rigid body polygon contact planes, the contact collision can be detected. The following analysis of the contact between the driving sprocket and scraper chain and the contact relationship between adjacent scraper chains provides an effective basis for studying the contact collision relationship of different rigid bodies of the chain drive system, as shown in Figure3.Figure 3
Contact relationship between the chain wheel and scraper chain.In the actual operation of the chain drive system, there are obvious contact relations between the components such as scraper chain, sprocket, and central groove, and contact pairs are formed between two rigid bodies in arbitrary contact, which play an important role in the analysis of the interaction relations of contacting rigid bodies. By analyzing the geometric position of different rigid body polygon contact planes, the contact collision can be detected. The following analysis of the contact between the driving sprocket and scraper chain and the contact relationship between adjacent scraper chains provides an effective basis for studying the contact collision relationship of different rigid bodies in the chain drive system. By optimizing the driving node, the mobile node for cavity repair and the optimal repair location are determined to ensure that the area of the cavity to be repaired each time reaches the maximum. The experimental results show that compared with the existing methods, CHDARPI has reduced the average detection time and detection energy consumption by 15.2% and 16.7%, respectively.In actual operation, chain jamming and chain breakage failures are the most common forms of failure in the chain drive system of the scraper conveyor. In this paper, based on the simulation analysis of the virtual prototype model of the chain drive system under normal operating conditions, the dynamics of the chain drive system when the chain jamming fault and chain breakage fault occur are studied by setting the fault conditions. When the chain jamming fault occurs, it shows the jamming and tensing of the scraper chain; when the chain breakage fault occurs, it shows the sudden breakage of a scraper chain, and the scraper chains at the fault location are separated from each other [20]. These two protocols can effectively reduce the average energy consumption of network nodes, and the data collection rate of both exceeds 88%. To simulate the chain jamming fault condition, the sudden tensioning of the chain drive system can be realized by setting the sudden increase in the stiffness coefficient of the contact pair between the horizontal chain and the vertical chain, and the scraper chains forming the contact pair can be separated by releasing the contact pair between the horizontal chain and the vertical chain, thus simulating the chain breakage fault of the chain drive system [21]. Figure 4 depicts the study process of the dynamic characteristics of the chain drive system under the fault condition. The virtual prototype model of the chain drive system under the fault condition can be established quickly by setting the contact stiffness surge and releasing the contact constraints, and the simulation solution can be realized.Figure 4
Chain failure simulation analysis flow.To research the monitoring and diagnosis method of the heavy-duty scraper conveyor chain drive system, the dynamic characteristics of the chain drive system need to be fully considered. At present, the study of dynamic characteristics of chain drive systems based on the experimental method is costly and difficult to operate, so most of the research mostly focuses on model simplification and theoretical analysis of the single-chain system, and the reliability of the research method is low [22]. Considering the complexity of the structural composition of the scraper conveyor and the difficulty of the study of the dynamic characteristics, this section establishes a virtual prototype model of the double-chain traction chain drive system based on the multibody dynamic theory and contact collision theory, which integrates the motion constraints and force relationships between different components and studies the dynamic characteristics of the chain drive system under the conditions of normal operation, chain jamming fault operation, and chain breakage fault operation.
## 4. Analysis of Results
### 4.1. Wireless Sensor Network Data Algorithm Results
Figure5 shows the number of anchor points in the monitoring area for the four algorithms with different MCD charging radii. It can be found that the number of anchor points corresponding to all four algorithms decreases as the charging radius of MCD increases, which is because the charging radius of MCD determines the size of each access cell area, and the larger the charging radius, the fewer anchor points in the monitoring area. To address the problems of high detection energy consumption and long detection time of the existing coverage hole detection algorithm based on boundary node message detection, a coverage hole detection algorithm CHDARPI based on the relative position information of link intersection is proposed, and a hole detection message forwarding mechanism based on node orientation angle adaption is designed to achieve the detection of multiple types of coverage holes based on the relative position information of link intersection in the hole detection message.Figure 5
Radius and number of anchor points.To achieve low redundancy and complete repair of coverage voids, a dichotomous-based distributed coverage void repair algorithm CHRAND is then proposed to determine the mobile node and the optimal repair location for void repair by optimizing the drive node, which ensures the maximum area of each repaired void. The experimental results show that CHDARPI decreases 15.2% and 16.7% in the average detection time and detection energy consumption, respectively, compared with the existing methods. When the number of mobile nodes in the network is sufficient, the void repair rate of GRAND can reach 100%, and the repair redundancy does not exceed 0.354, as shown in Figure6.Figure 6
Radius and MCD travel distance.To address the problem of data collection rate degradation due to unreliable links, an energy-efficient routing protocol for wireless sensor networks is studied, and a dynamic hierarchical routing protocol EEDRP combined with a dormancy scheduling mechanism is proposed to minimize node energy consumption by making each node in a low-energy operating mode through the dormancy scheduling mechanism. It further combines node residual energy and link quality to determine the next-hop node forwarding set and reduces data transmission delay while improving data transmission reliability through ak-packet retransmission mechanism based on active time slot prediction. Specifically, the relationship between unreliable links and the “energy hole” of the clustering protocol is analyzed, and the fuzzy logic idea is used to decide the network clustering radius. The experimental results show that EEDRP and UCPFLUL protocols can effectively reduce the average energy consumption of network nodes, and the data collection rate of both protocols exceeds 88%.In the application of mobile sink banded wireless sensor network based on event monitoring, a mobile sink data collection algorithm DCAFAN based on agent node forwarding is proposed to meet the low latency performance requirement of event monitoring data collection, while the existing data collection technique of building to the sink path can solve the above latency problem but has the problem of unreliable data transmission. Specifically, DCAFAN constructs a queue of agent nodes that identify the moving trajectory of sink and a sequence of line nodes that store tracking agent nodes, and data nodes transmit data to sink by acquiring tracking agent nodes. The sequence of line nodes and the queue of agent nodes are updated with tracking agent nodes to avoid their death due to energy exhaustion. In addition, a wake-up time-lag difference-based routing method is proposed to assist DCAFAN in solving the problem of excessive node data transmission delay under low duty cycle networks. Experimental results show that DCAFAN has good data collection delay performance while balancing network node energy consumption as well as data collection rate performance.
### 4.2. Mechanical Chain Drive Optimization Results
Figure7 depicts the Simulink solution module for scraper chain tension estimation. The solution module takes the drive sprocket torque as the system input, provides the known parameters from the state space equations, and uses the state observer constructed in this study as a tool to estimate the scraper chain tension variation for each discrete unit body from the known state parameters. The results of tension estimation at different contact points of the chain drive system during the 1~3 s stable operation phase are described. Combined with equations (7) and (8), the three-dimensional surface plots of the tension variation at different contact position points estimated by the state observer when taking different values are depicted in the figure. The analysis shows that the tension distribution law of the chain drive system is closely related to the spatial location of the contact points.Figure 7
Tension distribution of the scraper chain at different contact positions.At the same moment, along the scraper chain running direction, the tension at different contact points of the upper side chain of the chain drive system increases continuously, and the tension at different contact points of the lower side chain also shows an increasing trend, which is consistent with the theoretical analysis of the scraper chain tension distribution mentioned above. When taking different values, the tension changes at different contact points of the upper and lower side chains also meet the above variation law. For the upper side chain, the minimum and maximum values of tension occur at contact points 1 and 73, respectively, and the minimum and maximum values of tension for the lower side chain occur at contact points 74 and 146, which are consistent with the theoretical analysis of the tension distribution of the scraper chain. For the upper side chain and the lower side chain, the tension of the scraper chain is the smallest at the point where the sprocket engages and separates from the scraper chain, and the tension of the scraper chain is the largest when the sprocket engages and meets the scraper chain; when different values are taken, the location distribution of the maximum and minimum points of the contact force of the upper side chain and the lower side chain also meets the above variation law. Therefore, the scraper chain strains at different locations of the single-chain system measured by the scraper chain strain test experiment and the tensions at different contact locations estimated by the state observer have the same variation characteristics, which further verifies the reliability of the proposed tension estimation method.The chain drive system is prone to chain jamming failure and chain breakage failure so that the working performance of the whole chain drive system is reduced and the safe production of the scraper conveyor is affected, so it is necessary to provide early warning of the occurrence of scraper chain failure in time to avoid malignant accidents. Based on the research of the scraper chain tension distribution law monitoring method, this section proposes a scraper chain fault diagnosis method based on tension estimation. From Figure8, it can be obtained that the maximum tension values at different contact points of the upper side chain system are significantly higher than those of the lower side chain system, so the upper side chain system is more prone to damage due to stress concentration. Then, the tension distribution state of the chain drive system is analyzed; at the same time, combined with the theoretical calculation results and the virtual prototype simulation results, the error analysis of the estimated results of the tension change of the scraper chain is carried out, and the strain test experiment of the scraper chain is carried out. Experimental verification is performed. In addition, in the actual production environment, the upper side chain system is more likely to be influenced by external factors and scraper chain failure occurs. Therefore, the contact point of the upper side chain system is taken as the research object to start the research of scraper chain fault diagnosis.Figure 8
Estimation error of the upper side chain system.In this section, the tension variation of the scraper chain is estimated based on the state observer, and then, the diagnosis of the chain jamming fault and chain breakage fault of the scraper chain is made. The diagnosis effect is not affected by the fault location and the change of the stiffness coefficient, and it can accurately determine whether the scraper chain is faulty and distinguish the fault type. Combined with the aforementioned study on the characteristics of the scraper chain tension change under fault conditions based on the virtual prototype simulation technology and the analysis of the experimental data of the scraper conveyor chain drive system fault test, it can be seen that in the fault stabilization stage, when the chain jamming fault occurs, the contact force between the monitored scraper chains and the strain of the measured scraper chains increases significantly compared with the normal conditions, and when the chain breakage fault occurs, the strain between the monitored scraper chains increases significantly compared with the normal conditions. In the case of chain breakage, the contact force between the monitored scraper chains and the measured strain of the scraper chains decreases compared to the normal condition. The predicted tension variation patterns of the scraper chain at the fault-prone locations under the chain jamming and chain breakage conditions are consistent with the simulation results of the virtual prototype and the experimental analysis results, which verify the effectiveness of the scraper chain fault diagnosis strategy described in this section.The state-space equations of the discretized model are established, and the design method of the state observer is studied; the matrix dimensionality reduction algorithm is proposed, and the tension distribution monitoring method of the chain drive system based on the state observer is studied, and the scraper chain tension changes at different position points of the whole chain drive system are estimated by the scraper chain tension at finite known position points, and then the tension distribution state of the chain drive system is analyzed; meanwhile, the error analysis of the scraper chain tension changes is carried out based on the theoretical calculation results and the virtual prototype simulation results. Meanwhile, the error analysis of the estimation results of the scraper chain tension variation is combined with the theoretical calculation results and the simulation results of the virtual prototype, and the experimental verification is carried out based on the scraper chain strain test experiment. The error analysis and experimental verification show that the proposed tension distribution monitoring method can effectively predict the tension change of the scraper chain with high estimation accuracy and reliability and can realize comprehensive monitoring and analysis of tension change at different position points of the chain drive system with the premise of reducing the number of sensors used.
## 4.1. Wireless Sensor Network Data Algorithm Results
Figure5 shows the number of anchor points in the monitoring area for the four algorithms with different MCD charging radii. It can be found that the number of anchor points corresponding to all four algorithms decreases as the charging radius of MCD increases, which is because the charging radius of MCD determines the size of each access cell area, and the larger the charging radius, the fewer anchor points in the monitoring area. To address the problems of high detection energy consumption and long detection time of the existing coverage hole detection algorithm based on boundary node message detection, a coverage hole detection algorithm CHDARPI based on the relative position information of link intersection is proposed, and a hole detection message forwarding mechanism based on node orientation angle adaption is designed to achieve the detection of multiple types of coverage holes based on the relative position information of link intersection in the hole detection message.Figure 5
Radius and number of anchor points.To achieve low redundancy and complete repair of coverage voids, a dichotomous-based distributed coverage void repair algorithm CHRAND is then proposed to determine the mobile node and the optimal repair location for void repair by optimizing the drive node, which ensures the maximum area of each repaired void. The experimental results show that CHDARPI decreases 15.2% and 16.7% in the average detection time and detection energy consumption, respectively, compared with the existing methods. When the number of mobile nodes in the network is sufficient, the void repair rate of GRAND can reach 100%, and the repair redundancy does not exceed 0.354, as shown in Figure6.Figure 6
Radius and MCD travel distance.To address the problem of data collection rate degradation due to unreliable links, an energy-efficient routing protocol for wireless sensor networks is studied, and a dynamic hierarchical routing protocol EEDRP combined with a dormancy scheduling mechanism is proposed to minimize node energy consumption by making each node in a low-energy operating mode through the dormancy scheduling mechanism. It further combines node residual energy and link quality to determine the next-hop node forwarding set and reduces data transmission delay while improving data transmission reliability through ak-packet retransmission mechanism based on active time slot prediction. Specifically, the relationship between unreliable links and the “energy hole” of the clustering protocol is analyzed, and the fuzzy logic idea is used to decide the network clustering radius. The experimental results show that EEDRP and UCPFLUL protocols can effectively reduce the average energy consumption of network nodes, and the data collection rate of both protocols exceeds 88%.In the application of mobile sink banded wireless sensor network based on event monitoring, a mobile sink data collection algorithm DCAFAN based on agent node forwarding is proposed to meet the low latency performance requirement of event monitoring data collection, while the existing data collection technique of building to the sink path can solve the above latency problem but has the problem of unreliable data transmission. Specifically, DCAFAN constructs a queue of agent nodes that identify the moving trajectory of sink and a sequence of line nodes that store tracking agent nodes, and data nodes transmit data to sink by acquiring tracking agent nodes. The sequence of line nodes and the queue of agent nodes are updated with tracking agent nodes to avoid their death due to energy exhaustion. In addition, a wake-up time-lag difference-based routing method is proposed to assist DCAFAN in solving the problem of excessive node data transmission delay under low duty cycle networks. Experimental results show that DCAFAN has good data collection delay performance while balancing network node energy consumption as well as data collection rate performance.
## 4.2. Mechanical Chain Drive Optimization Results
Figure7 depicts the Simulink solution module for scraper chain tension estimation. The solution module takes the drive sprocket torque as the system input, provides the known parameters from the state space equations, and uses the state observer constructed in this study as a tool to estimate the scraper chain tension variation for each discrete unit body from the known state parameters. The results of tension estimation at different contact points of the chain drive system during the 1~3 s stable operation phase are described. Combined with equations (7) and (8), the three-dimensional surface plots of the tension variation at different contact position points estimated by the state observer when taking different values are depicted in the figure. The analysis shows that the tension distribution law of the chain drive system is closely related to the spatial location of the contact points.Figure 7
Tension distribution of the scraper chain at different contact positions.At the same moment, along the scraper chain running direction, the tension at different contact points of the upper side chain of the chain drive system increases continuously, and the tension at different contact points of the lower side chain also shows an increasing trend, which is consistent with the theoretical analysis of the scraper chain tension distribution mentioned above. When taking different values, the tension changes at different contact points of the upper and lower side chains also meet the above variation law. For the upper side chain, the minimum and maximum values of tension occur at contact points 1 and 73, respectively, and the minimum and maximum values of tension for the lower side chain occur at contact points 74 and 146, which are consistent with the theoretical analysis of the tension distribution of the scraper chain. For the upper side chain and the lower side chain, the tension of the scraper chain is the smallest at the point where the sprocket engages and separates from the scraper chain, and the tension of the scraper chain is the largest when the sprocket engages and meets the scraper chain; when different values are taken, the location distribution of the maximum and minimum points of the contact force of the upper side chain and the lower side chain also meets the above variation law. Therefore, the scraper chain strains at different locations of the single-chain system measured by the scraper chain strain test experiment and the tensions at different contact locations estimated by the state observer have the same variation characteristics, which further verifies the reliability of the proposed tension estimation method.The chain drive system is prone to chain jamming failure and chain breakage failure so that the working performance of the whole chain drive system is reduced and the safe production of the scraper conveyor is affected, so it is necessary to provide early warning of the occurrence of scraper chain failure in time to avoid malignant accidents. Based on the research of the scraper chain tension distribution law monitoring method, this section proposes a scraper chain fault diagnosis method based on tension estimation. From Figure8, it can be obtained that the maximum tension values at different contact points of the upper side chain system are significantly higher than those of the lower side chain system, so the upper side chain system is more prone to damage due to stress concentration. Then, the tension distribution state of the chain drive system is analyzed; at the same time, combined with the theoretical calculation results and the virtual prototype simulation results, the error analysis of the estimated results of the tension change of the scraper chain is carried out, and the strain test experiment of the scraper chain is carried out. Experimental verification is performed. In addition, in the actual production environment, the upper side chain system is more likely to be influenced by external factors and scraper chain failure occurs. Therefore, the contact point of the upper side chain system is taken as the research object to start the research of scraper chain fault diagnosis.Figure 8
Estimation error of the upper side chain system.In this section, the tension variation of the scraper chain is estimated based on the state observer, and then, the diagnosis of the chain jamming fault and chain breakage fault of the scraper chain is made. The diagnosis effect is not affected by the fault location and the change of the stiffness coefficient, and it can accurately determine whether the scraper chain is faulty and distinguish the fault type. Combined with the aforementioned study on the characteristics of the scraper chain tension change under fault conditions based on the virtual prototype simulation technology and the analysis of the experimental data of the scraper conveyor chain drive system fault test, it can be seen that in the fault stabilization stage, when the chain jamming fault occurs, the contact force between the monitored scraper chains and the strain of the measured scraper chains increases significantly compared with the normal conditions, and when the chain breakage fault occurs, the strain between the monitored scraper chains increases significantly compared with the normal conditions. In the case of chain breakage, the contact force between the monitored scraper chains and the measured strain of the scraper chains decreases compared to the normal condition. The predicted tension variation patterns of the scraper chain at the fault-prone locations under the chain jamming and chain breakage conditions are consistent with the simulation results of the virtual prototype and the experimental analysis results, which verify the effectiveness of the scraper chain fault diagnosis strategy described in this section.The state-space equations of the discretized model are established, and the design method of the state observer is studied; the matrix dimensionality reduction algorithm is proposed, and the tension distribution monitoring method of the chain drive system based on the state observer is studied, and the scraper chain tension changes at different position points of the whole chain drive system are estimated by the scraper chain tension at finite known position points, and then the tension distribution state of the chain drive system is analyzed; meanwhile, the error analysis of the scraper chain tension changes is carried out based on the theoretical calculation results and the virtual prototype simulation results. Meanwhile, the error analysis of the estimation results of the scraper chain tension variation is combined with the theoretical calculation results and the simulation results of the virtual prototype, and the experimental verification is carried out based on the scraper chain strain test experiment. The error analysis and experimental verification show that the proposed tension distribution monitoring method can effectively predict the tension change of the scraper chain with high estimation accuracy and reliability and can realize comprehensive monitoring and analysis of tension change at different position points of the chain drive system with the premise of reducing the number of sensors used.
## 5. Conclusion
A lot of results have been achieved in various aspects of research on coverage voids and data collection techniques for wireless sensor networks, but as the application scope of wireless sensor networks continues to extend, there are still many critical issues to be addressed to meet the ever-changing application requirements. In this paper, we address the impact of node resource constraints, unreliable links, and coverage voids on data collection performance and study data collection techniques in various application scenarios with the goals of low-energy consumption, low latency, and high collection rate. To address the impact of limited node resources on the data collection performance of wireless sensor networks, the existing mobile device path planning algorithm with combined mobile data collection and wireless charging functions cannot simultaneously solve the problems of low data collection rate and high data collection delay under the continuous operation requirements of the network; this paper proposes a greedy policy-based mobile device path planning algorithm PPAGS. The minimum dwell time and maximum wait time of mobile devices in each access unit are predicted using the Markov model for the dynamic change of parameters such as node energy and data collection, which avoids the mobile devices from moving across a large span in the monitoring area. In addition, the PPAGS algorithm has the advantages of low complexity, and there is no need to obtain the actual location information of nodes and anchors during the operation. The experimental results show that the average data collection delay of PPAGS decreases by 25.9%, the average data collection rate increases by 7% to 98.91%, and the average node failure rate does not exceed 3.1% compared with existing methods.
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*Source: 2901624-2021-09-14.xml* | 2901624-2021-09-14_2901624-2021-09-14.md | 77,164 | Optimized Design of Mechanical Chain Drive Based on a Wireless Sensor Network Data Algorithm | Min Zhuang; Ge Li; Kexin Ding; Guansheng Xu | Journal of Sensors
(2021) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2021/2901624 | 2901624-2021-09-14.xml | ---
## Abstract
In this paper, we use a wireless sensor network data algorithm to optimize the design of mechanical chain drive by conducting an in-depth study of the mechanical chain drive optimization. We utilize the crowdsourcing feature of the swarm-wise sensing network for assisted wireless sensor networking to achieve crowdsourcing-assisted localization. We consider a framework for crowdsourcing-assisted GPS localization of wireless sensor networks and propose two recruitment participant optimization objectives, namely, minimum participants and time efficiency, respectively. A model and theoretical basis are provided for the subsequent trusted data-driven participant selection problem in swarm-wise sensing networks. The sprocket-chain engagement frequency has the greatest influence on the horizontal bending-vertical bending composite in different terrain conditions. The dynamic characteristics under working conditions are most influenced, while the scraping of the scraper and the central groove significantly influenced horizontal bending and vertical bending. Under load conditions, the amplitude of the scraper and central groove scraping increases significantly, which harm the dynamics of the scraper conveyor. By monitoring the speed difference between the head and tail sprockets and the overhang of the scraper, the tensioning status of the scraper conveyor chain can be effectively monitored to avoid chain jamming and chain breakage caused by the loose chain, thus improving the reliability and stability of the scraper conveyor.
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## Body
## 1. Introduction
The development of wireless sensor networks and group intelligence-aware networks has been carried out relatively independently, and no research has been conducted to converge the two. Network convergence originally means that with the development of technology, the telephone network and data network gradually merge into one; that is, voice signal transmission through data networks has become a reality and continues to spread. The merging of telephone and data networks will greatly reduce the operating costs of communication networks and simplify the management of the network for users; the biggest benefit is the cost savings. The meaning behind this is that the emergence of new technologies can enhance the original technology, which is often very mature, and preapplication has built a huge system with huge investment [1]. In wireless sensor network monitoring applications that require high reliability of data collection, the ability of the nodes to collect complete data from the monitoring area and transmit them to the user center in a reliable and timely manner is directly related to the effectiveness of the network application [2]. For example, in wireless sensor network data collection based on applications such as soil site monitoring, to accurately predict and identify risk factors, it is not only required that the sensor network can collect data reflecting the complete status of the monitoring area but also required that these data are reliably transmitted to the user within a specified delay [3]. However, random deployment of nodes or coverage voids created during network operation degrades the network coverage quality of service, resulting in the network not being able to collect complete data from the monitoring area.There are also a variety of factors that affect reliable data collection during the data transmission phase; for example, sensor nodes are battery-powered; once the nodes die due to energy exhaustion, data transmission will be interrupted and cannot continue, affecting the continuous data collection; data collection delays caused by factors such as congestion waiting, dormant scheduling, and unreliable links are too large to meet the data of delay-sensitive wireless sensor network application collection performance requirements; data overflow generated by insufficient node storage space and packet loss due to unreliable links degrade data collection rate performance [4]. From the working principle of the scraper conveyor, the scraper chain is the key component of the scraper conveyor, which is the traction mechanism of the scraper conveyor and is the component that transmits traction force and directly scrapes and transports materials. The chain operates under sliding friction conditions and is not only subjected to large static and dynamic loads but also eroded by mine water, so it usually has a high failure rate. Often, the original technology is already very mature and the early application has established a huge system, with huge investment. The original system does not completely lose its value but can also be used by advanced new technologies. Therefore, a fusion mechanism is needed to enable the new technology and the original technology to be combined into one and function together. Typical failure forms of scraper chains include chain jamming, chain skipping, chain breaking, etc. Some studies show that the reliability of the scraper conveyor decreases exponentially as the working time increases [5]. Although this method can effectively detect the occurrence of faults, it has a certain lag; i.e., it cannot predict and avoid faults in advance.Wireless sensor networks inevitably face the problems of incomplete data collection in the monitoring area due to coverage voids: the problem of data collection rate degradation due to unreliable link packet loss, the problem of mobile sink data collection techniques not meeting the low latency collection of event monitoring data, and the problem of sink not reliably collecting complete data in the monitoring area due to limited node resources. Unlike the existing message detection-based hole detection algorithm, the hole detection algorithm in this paper can rely on the information of incomplete coverage intersection for concurrent detection of multiple connected holes, which reduces the energy consumption and time of hole detection. In addition, the hole repair algorithm in this paper reduces the number of mobile nodes required for hole repair by optimizing the hole repair drive nodes and can achieve low redundancy and complete repair of covered holes. Considering the dynamic change of node energy and data collection, the minimum dwell time and maximum waiting time of the mobile device are predicted based on the Markov model to avoid its large-span movement in the monitoring area. Compared with existing methods, PPAGS can largely increase the data collection rate with a small number of mobile devices while reducing the data collection delay.
## 2. Current Status of Research
Considering the operating characteristics of the scraper conveyor, based on the existing advanced sensing technologies, relevant experts and scholars have overcome the problems in assessing the operating condition of the scraper conveyor, and a certain research base has been established, but it is still limited to the system platform design, wireless sensing technology development, and data processing algorithm optimization [6]. The current research mostly uses sensors and measurement devices to measure different parameters of the chain drive system, and the main measurement tools include tension sensors, angle sensors, electromagnetic sensors, Hall elements, and electromagnetic detection devices [7]. In turn, a wireless sensor network is designed for data transmission, and data analysis of different parameters is used to assess the operating status of the equipment for condition monitoring and fault determination of the scraper conveyor [8]. To improve data transmission efficiency, in wireless sensing technology development, Cunningham designed a remote monitoring system for a scraper conveyor combining an RFID wireless sensor network, CAN bus, and industrial Ethernet [9]. Sadeeq and Zeebaree designed a wireless detection system for scraper conveyor drive based on RFID technology [10]. Amutha et al. developed a remote monitoring system based on industrial Ethernet and a wireless mesh switching network-based remote monitoring communication platform to realize remote on-board monitoring of the scraper conveyor [11]. However, although the efficiency of data acquisition was improved to some extent through the design of the network structure, it still failed to apply the measured data to the monitoring of the operation status of the equipment.When random coverage is performed, there will be several uncovered areas, often called coverage holes, despite the dense network as a guarantee of coverage. For this reason, mobile nodes are added to the sensor network and allowed to move after random deployment to compensate for the uncovered areas. This is an important class of research problems, which is called the coverage problem of mobile wireless sensor networks. In this paper, we will study this type of problem with the main goal of obtainingK-recoveries at minimal movement cost [12]. The coverage problem for mobile sensors is the initial version of mobile swarm intelligence sensing, where sensors can only be controlled centrally or are given very limited control strategies. The study of how mobile swarm intelligence perception can provide location information for the mobile sensor coverage problem is one of the research areas in this paper [13]. The BikeNet system uses various sensors and smartphones equipped on cyclists’ bikes to sense and share the air quality and road conditions around the cycling path so that cyclists have real-time knowledge of the environment for path selection and optimal cycling experience [14]. The CrowdAtlas system addresses the current problem of untimely and costly updates of electronic maps by using sensory data from GPS sensors of cell phones and cars of many users in the city to build a real-time updated map of urban roads. The monitoring system includes an electromagnetic sound emitter and an electromagnetic sound sensor [15]. The electromagnetic sound emitted by the electromagnetic sound emitter is reflected when it meets the scraper chain of the scraper conveyor. The electromagnetic sound sensor determines the degree of surface damage to the scraper chain by analyzing the reflected electromagnetic sound. This monitoring system predicts scraper chain failure by directly monitoring the physical form of the scraper chain. The disadvantage is that the working environment of the scraper conveyor is harsh and the scraper chain will be covered by coal and other materials during normal operation, which makes monitoring inaccurate or even completely impossible.The actual working environment of the scraper conveyor is usually harsher, manifested by strong vibration and strong electromagnetic interference. It is also required that these data be reliably transmitted to the user within a specified delay. However, random deployment of nodes or coverage holes generated during network operation reduces the quality of network coverage services, resulting in the inability of the network to collect complete data in the monitoring area. For some coal mines with high water seepage, it is also necessary to pay attention to the fact that mine water may flood the return scraper located below the middle plate. Therefore, the tension monitoring system for the scraper conveyor needs to face the problems of waterproof, antivibration, antielectromagnetic interference, electromagnetic magnetic shielding, etc. For the problems of mine water and strong vibration, it is necessary to improve the stability of the hardware design of the monitoring system, as well as to design the protection scheme. On the other hand, for the mine water and electromagnetic environment can affect the communication and other functions of the tension monitoring system, there is also a need to conduct in-depth research on wireless communication under the mine. In addition, wireless sensor network data collection technology performance indicators include network throughput, robustness, security, and confidentiality. In addition to energy efficiency, which is the primary performance indicator for all wireless sensor network applications, other network performance indicators vary from one application scenario to another. The application of wireless sensor networks in the military field needs to ensure the security and confidentiality of data collection.
## 3. Optimized Design Analysis of Mechanical Chain Drive with the Wireless Sensor Network Data Algorithm
### 3.1. Wireless Sensor Network Data Algorithm Design
Wireless link quality affects the performance of network routing protocols. Wireless links are unreliable due to the external environment and cochannel signals. Evaluating the link quality helps to improve the packet forwarding rate and helps to reduce the energy consumption of the network nodes. Identifying credible real data from group-wise perception, participant perception with noise or even conflicting data is a challenging problem. A part of the research focuses on authentic discovery algorithms, and these studies focus on estimating the data quality of participants and discovering potentially authentic data synchronously by quality-based data fusion. They describe the reliability of participants as the variance of a normal distribution, and the estimated true values are usually computed as a weighted average sum or found using a Bayesian approach through EM algorithms or parameterization [16]. As mentioned in Section 3 for moving sensors to achieve specific coverage requirements, collecting the GPS locations of randomly placed sensors in the network is the first step in computing and planning sensor movements, so it is important to assist mobile wireless sensor networks for GPS localization. It makes sense to set the application scenario within urban centers (urban fields) where many people with smart devices are active. This provides a greater opportunity to provide mobile wireless sensor network GPS information. Of course, recruiting participants for the swarm intelligence sensing task needs to be considered at a certain cost. Firstly, recruiting as few participants as possible is one of the goals, and secondly, those suitable participants need to be selected for the recruitment process.The wireless sensor network is abstractly represented asG=V,E,Q,W, where V represents the set of network nodes; E represents the set of wireless links of network nodes; Q represents the set of network link quality, and the link i,j quality is denoted as i,pj, assuming that the link quality between all nodes is known; and W represents the set of work schedules of network nodes, and the work schedule wi of any node i is represented by a string consisting of 0 and 1 sequences. A work cycle of the network is denoted as T, and a time slot is denoted as π. There are T time slots in a work cycle, and each time slot π completes one data transmission. The state of each time slot is divided into a sleep state and active state, which are represented by 1 and 0, respectively. In period T, the time slot position of the active state of node i is calculated according to
(1)Xi,n=iIDmodTπ,Xi,n−1=Xi,n−CiIDmodTπ.The next-hop forwarding node selection considers the residual energy of the nodes as well as the link quality, which balances the energy consumption of the network nodes and increases the network lifetime. The link metric of nodei with neighbor node j is defined as
(2)SLQEi,j=βpi,j+1−βEj1+βW,∑i,j=1Mxijyij≤1.Due to other reasons such as load changes, the chain tension of the scraper conveyor will change constantly during the actual coal mining work, making the whole section or local tension of the chain exceed the design value. Too much or too little chain tension will affect the normal operation of the scraper conveyor. If the chain is too loose, the chain will easily break away from the sprocket at the separation point of the head sprocket or the tail sprocket and the chain, causing impact and vibration of the sprocket and causing accidents such as chain breakage and chain jamming in serious cases [17]. Data overflow caused by insufficient node storage space and data packet loss caused by unreliable links reduce the performance of the data collection rate. If the chain is too tight, it will increase the friction between the chain and the sprocket and the middle groove, increase the running resistance, make the power consumption of the scraper conveyor increase, and accelerate the wear of the related equipment. The scraper conveyor is not only used as coal transportation equipment in the coal mining working face but also used as a track for the coal mining machine to run. The coal mining machine moves on the scraper conveyor slide and cuts the coal wall, and the coal falls on the scraper conveyor and is pushed to the head by the scraper and scraper chain. Although this method can effectively detect the occurrence of faults, it has a certain hysteresis; that is, it cannot predict and avoid faults in advance. Wireless sensor networks inevitably face the problem of incomplete collection of data in the monitoring area caused by coverage holes and the problem of reduced data collection rate due to packet loss on unreliable links. The function of the scraper conveyor determines that the body of the scraper conveyor is very low, and during operation, there is a large amount of ore impact accompanied by electromagnetic interference from the high-power motor. For some coal mines, large amounts of mine water can seep out of the comprehensive mining face and its presence will also affect the monitoring system, as shown in Figure 1. This principle ensures that the mobile node introduced by the selected cavity driving node has the maximum area for the repair of the cavity region at the cavity repair location. The covered voids consist of boundary arcs of multiple void boundary nodes, and each node has at most two incomplete coverage intersections in the void area.Figure 1
Wireless sensor network framework.If each introduced mobile node can only eliminate one void boundary node, the mobile node transforms into a void boundary node and adds a void boundary node in the case of incomplete repair of the coverage void, which is slower in void repair, and when the mobile node introduced by a certain driver node can eliminate more incomplete coverage intersections, it can eliminate more void boundary nodes, which will speed up the void repair. This will speed up the hole repair and help reduce the number of mobile nodes required for hole repair. When the mobile nodes introduced at one time have eliminated all the incomplete coverage intersections, it means that the current hole is repaired.(3)pA=mintij.Based on the introduction of mobile node undivided holes, the nonparallel dichotomous repair strategy ensures that the coverage holes are completely repaired because at least 2 incomplete coverage intersections are eliminated per mobile node introduction during the nonparallel repair of the holes based on the drive node selection principles 1 and 3. Each introduced mobile node produces a maximum of 2 incomplete coverage intersections. The trajectory formed by the blade edge line rotating around the rotary axis is a single-leaf hyperboloid, which can be studied by using the properties of the single-leaf hyperboloid, as shown in Figure2, which can be regarded as the edge line AB rotating around the rotary axis OZ.Figure 2
Network data algorithm framework.The contact force between scraper chains is the main cause of chain fatigue and failure. Or use the Bayesian method to find the true value through the EM algorithm or parameterized method. Under the framework of crowdsourcing, assist the mobile wireless sensor network for GPS positioning. The study of the force characteristics of the chain drive system is essentially a study of the change of contact force between scraper chains at different positions. In the transmission process of the scraper conveyor chain drive system, the scraper chain, as the main traction component, includes two types of horizontal circular chain (horizontal chain) and vertical circular chain (vertical chain). The driving chain wheel teeth are circular arc tooth profiles, and there are chain nest grooves and vertical chain grooves distributed between any adjacent teeth. In the process of the chain drive system, the horizontal chain lies flat in the chain nest groove, and the vertical chain is connected with the horizontal chain and distributed in the vertical chain groove. The tooth profile of the driving sprocket is not only the main part of the scraper chain and teeth engagement and disengagement but also the main area of the sprocket bearing force, so the parametric modeling is of great significance to the structure development and optimization design of the sprocket.(4)D0=psin60/N2−dcos60/N2,W=2H+dcos90N+Asin90N−d.The link metric is between nodei and neighbor node j. The Creo2.0 software development platform enables the virtual assembly of different mechanical systems and can be used for the rapid construction of 3D models of scraper conveyor chain drive systems. Among them, the “bottom-up” design method is the most conventional modeling method for virtual assembly, which models each component separately and then assembles each part into a whole in a step-by-step manner from the bottom up according to a certain installation order, constraint relationship, and hierarchy, which requires constant assembly and interference analysis to coordinate the design process to avoid interference errors. The “top-down” assembly design method is adopted for the 3D model of the chain drive system, which can achieve a high degree of coordination between the parametric design of key components and the virtual assembly process. The main principle is as follows: set the overall framework of the assembly or structural assembly scheme, which is used as the installation directory tree of the whole product, and in the assembly process, based on the directory tree, the subordinate assembly relationship and assembly order of different parts can be established from the top-level down to the bottom-level components and parts for assembly.
(5)ddt∂T∂qT+∂T∂qT−φqTp−θqTμ=Q,where the complete constraint equation of the system satisfies(6)φq,t=1.The incomplete constraint equations of the system satisfy(7)θq,q1,t=1.Its basic idea comes from a collective intelligence that includes the contributions of thousands of individuals. And smart devices, such as mobile smartphones, offer a surprisingly diverse range of uses. This flexibility is mainly because these smart devices are often embedded with highly accurate GPS positioning systems. People can easily take these smart devices with them and use them anytime and anywhere, which greatly enhances the mobility of these smart devices. The GPS positioning of mobile wireless sensor networks is assisted in the framework of crowdsourcing. As mentioned in Section3 for moving sensors to achieve specific coverage requirements, collecting GPS locations of randomly placed sensors in the network is the first step in computing and planning sensor movements, so it is important to assist mobile wireless sensor networks for GPS localization. A virtual prototype model of a double-chain traction chain transmission system considering the movement constraints and force relationships between different components and the dynamic characteristics of the chain transmission system under normal operating conditions, stuck-chain fault conditions, and broken-chain fault conditions is studied. It makes sense to set the application scenario within the urban fields (urban centers), where many people with smart devices are active. This provides a greater opportunity to provide GPS information from mobile wireless sensor networks. Of course, recruiting participants for the swarm intelligence sensing task needs to be considered at a certain cost: firstly recruiting as few participants as possible is one of the goals, and secondly, those suitable participants need to be selected for the recruitment process.
(8)Fq,u,μ,λ,t=1,Gu,q=u+q,ϕq,t=1.To study the dynamics of the chain drive system, it is necessary to study the complex contact problem between different rigid body surfaces while considering its multibody dynamic characteristics. The contact between different rigid bodies of the chain drive system is a complex nonlinear problem, and the contact collision can be regarded as a time-varying dynamic process, and the most used algorithms to deal with the boundaries of the contact problem are the implicit Lagrange algorithm and the display penalty function method [18]. In this section, the research and analysis of the contact problem between different rigid bodies of the chain drive system mainly involve contact collision detection and contact force solution. The polygonal contact model satisfies the following two characteristics: the surfaces of any rigid bodies in contact with each other can be described by polygons, and the commonly used methods for constructing polygonal surfaces include Bessel curves and NURBS methods; the contact force between any two contacting bodies of the system can be determined based on the elastic base model.
### 3.2. Experimental Optimization Design of Mechanical Chain Drive
Since the tension acquisition device needs to follow the movement of the scraper to collect the tension of the scraper chain in real time, the tension acquisition device cannot obtain a stable energy source by wired means. The energy source of the tension acquisition device is set as a battery because it relies on the power generation principle such as piezoelectric vibration capturing energy, which leads to the unstable supply voltage. The capacity of the battery and the power consumption of the tension collection device determine the service time of the tension collection device [19]. The capacity of the battery is limited by the size of the battery, and the tension collection device and the battery are encapsulated together in the cavity of the lower pressure plate of the scraper, so there is a great limitation on the size and quantity of the battery. Therefore, to maximize the service time of the tension acquisition device, an energy-saving strategy is designed to reduce the power consumption of the tension acquisition device. The energy-saving strategy requires a proximity switch on the hardware and a dormant program on the software to form in conjunction. As mentioned above, the wireless communication distance is very short, and the data sent by the tension acquisition device can only be received by the data receiving device when the device moves with the squeegee to a position close to the data receiving device installed in the middle plate. Therefore, a proximity switch needs to be designed to notify the tension acquisition device when to start sending data. When the data transmission ends or is no longer within the communication range, the tension acquisition device can turn off the wireless transmitting function and enter the low-power sleep mode to save energy.The theoretical calculation of the dimensions of each component of the microstrip antenna was carried out above, and to further optimize the performance of the theoretically calculated natures, the length of the radiating patch of the microstrip antenna and the width of the 1/4 wavelength impedance converter were scanned by the simulation software HFSS to seek the dimensions that satisfy the best performance of the antenna. During the actual operation of the chain drive system, there are obvious contact relations between the components such as scraper chain, sprocket, and central groove, and contact pairs are formed between two rigid bodies in arbitrary contact, which play an important role in analyzing the interaction relations of the contacting rigid bodies. By analyzing the geometric position of different rigid body polygon contact planes, the contact collision can be detected. The following analysis of the contact between the driving sprocket and scraper chain and the contact relationship between adjacent scraper chains provides an effective basis for studying the contact collision relationship of different rigid bodies of the chain drive system, as shown in Figure3.Figure 3
Contact relationship between the chain wheel and scraper chain.In the actual operation of the chain drive system, there are obvious contact relations between the components such as scraper chain, sprocket, and central groove, and contact pairs are formed between two rigid bodies in arbitrary contact, which play an important role in the analysis of the interaction relations of contacting rigid bodies. By analyzing the geometric position of different rigid body polygon contact planes, the contact collision can be detected. The following analysis of the contact between the driving sprocket and scraper chain and the contact relationship between adjacent scraper chains provides an effective basis for studying the contact collision relationship of different rigid bodies in the chain drive system. By optimizing the driving node, the mobile node for cavity repair and the optimal repair location are determined to ensure that the area of the cavity to be repaired each time reaches the maximum. The experimental results show that compared with the existing methods, CHDARPI has reduced the average detection time and detection energy consumption by 15.2% and 16.7%, respectively.In actual operation, chain jamming and chain breakage failures are the most common forms of failure in the chain drive system of the scraper conveyor. In this paper, based on the simulation analysis of the virtual prototype model of the chain drive system under normal operating conditions, the dynamics of the chain drive system when the chain jamming fault and chain breakage fault occur are studied by setting the fault conditions. When the chain jamming fault occurs, it shows the jamming and tensing of the scraper chain; when the chain breakage fault occurs, it shows the sudden breakage of a scraper chain, and the scraper chains at the fault location are separated from each other [20]. These two protocols can effectively reduce the average energy consumption of network nodes, and the data collection rate of both exceeds 88%. To simulate the chain jamming fault condition, the sudden tensioning of the chain drive system can be realized by setting the sudden increase in the stiffness coefficient of the contact pair between the horizontal chain and the vertical chain, and the scraper chains forming the contact pair can be separated by releasing the contact pair between the horizontal chain and the vertical chain, thus simulating the chain breakage fault of the chain drive system [21]. Figure 4 depicts the study process of the dynamic characteristics of the chain drive system under the fault condition. The virtual prototype model of the chain drive system under the fault condition can be established quickly by setting the contact stiffness surge and releasing the contact constraints, and the simulation solution can be realized.Figure 4
Chain failure simulation analysis flow.To research the monitoring and diagnosis method of the heavy-duty scraper conveyor chain drive system, the dynamic characteristics of the chain drive system need to be fully considered. At present, the study of dynamic characteristics of chain drive systems based on the experimental method is costly and difficult to operate, so most of the research mostly focuses on model simplification and theoretical analysis of the single-chain system, and the reliability of the research method is low [22]. Considering the complexity of the structural composition of the scraper conveyor and the difficulty of the study of the dynamic characteristics, this section establishes a virtual prototype model of the double-chain traction chain drive system based on the multibody dynamic theory and contact collision theory, which integrates the motion constraints and force relationships between different components and studies the dynamic characteristics of the chain drive system under the conditions of normal operation, chain jamming fault operation, and chain breakage fault operation.
## 3.1. Wireless Sensor Network Data Algorithm Design
Wireless link quality affects the performance of network routing protocols. Wireless links are unreliable due to the external environment and cochannel signals. Evaluating the link quality helps to improve the packet forwarding rate and helps to reduce the energy consumption of the network nodes. Identifying credible real data from group-wise perception, participant perception with noise or even conflicting data is a challenging problem. A part of the research focuses on authentic discovery algorithms, and these studies focus on estimating the data quality of participants and discovering potentially authentic data synchronously by quality-based data fusion. They describe the reliability of participants as the variance of a normal distribution, and the estimated true values are usually computed as a weighted average sum or found using a Bayesian approach through EM algorithms or parameterization [16]. As mentioned in Section 3 for moving sensors to achieve specific coverage requirements, collecting the GPS locations of randomly placed sensors in the network is the first step in computing and planning sensor movements, so it is important to assist mobile wireless sensor networks for GPS localization. It makes sense to set the application scenario within urban centers (urban fields) where many people with smart devices are active. This provides a greater opportunity to provide mobile wireless sensor network GPS information. Of course, recruiting participants for the swarm intelligence sensing task needs to be considered at a certain cost. Firstly, recruiting as few participants as possible is one of the goals, and secondly, those suitable participants need to be selected for the recruitment process.The wireless sensor network is abstractly represented asG=V,E,Q,W, where V represents the set of network nodes; E represents the set of wireless links of network nodes; Q represents the set of network link quality, and the link i,j quality is denoted as i,pj, assuming that the link quality between all nodes is known; and W represents the set of work schedules of network nodes, and the work schedule wi of any node i is represented by a string consisting of 0 and 1 sequences. A work cycle of the network is denoted as T, and a time slot is denoted as π. There are T time slots in a work cycle, and each time slot π completes one data transmission. The state of each time slot is divided into a sleep state and active state, which are represented by 1 and 0, respectively. In period T, the time slot position of the active state of node i is calculated according to
(1)Xi,n=iIDmodTπ,Xi,n−1=Xi,n−CiIDmodTπ.The next-hop forwarding node selection considers the residual energy of the nodes as well as the link quality, which balances the energy consumption of the network nodes and increases the network lifetime. The link metric of nodei with neighbor node j is defined as
(2)SLQEi,j=βpi,j+1−βEj1+βW,∑i,j=1Mxijyij≤1.Due to other reasons such as load changes, the chain tension of the scraper conveyor will change constantly during the actual coal mining work, making the whole section or local tension of the chain exceed the design value. Too much or too little chain tension will affect the normal operation of the scraper conveyor. If the chain is too loose, the chain will easily break away from the sprocket at the separation point of the head sprocket or the tail sprocket and the chain, causing impact and vibration of the sprocket and causing accidents such as chain breakage and chain jamming in serious cases [17]. Data overflow caused by insufficient node storage space and data packet loss caused by unreliable links reduce the performance of the data collection rate. If the chain is too tight, it will increase the friction between the chain and the sprocket and the middle groove, increase the running resistance, make the power consumption of the scraper conveyor increase, and accelerate the wear of the related equipment. The scraper conveyor is not only used as coal transportation equipment in the coal mining working face but also used as a track for the coal mining machine to run. The coal mining machine moves on the scraper conveyor slide and cuts the coal wall, and the coal falls on the scraper conveyor and is pushed to the head by the scraper and scraper chain. Although this method can effectively detect the occurrence of faults, it has a certain hysteresis; that is, it cannot predict and avoid faults in advance. Wireless sensor networks inevitably face the problem of incomplete collection of data in the monitoring area caused by coverage holes and the problem of reduced data collection rate due to packet loss on unreliable links. The function of the scraper conveyor determines that the body of the scraper conveyor is very low, and during operation, there is a large amount of ore impact accompanied by electromagnetic interference from the high-power motor. For some coal mines, large amounts of mine water can seep out of the comprehensive mining face and its presence will also affect the monitoring system, as shown in Figure 1. This principle ensures that the mobile node introduced by the selected cavity driving node has the maximum area for the repair of the cavity region at the cavity repair location. The covered voids consist of boundary arcs of multiple void boundary nodes, and each node has at most two incomplete coverage intersections in the void area.Figure 1
Wireless sensor network framework.If each introduced mobile node can only eliminate one void boundary node, the mobile node transforms into a void boundary node and adds a void boundary node in the case of incomplete repair of the coverage void, which is slower in void repair, and when the mobile node introduced by a certain driver node can eliminate more incomplete coverage intersections, it can eliminate more void boundary nodes, which will speed up the void repair. This will speed up the hole repair and help reduce the number of mobile nodes required for hole repair. When the mobile nodes introduced at one time have eliminated all the incomplete coverage intersections, it means that the current hole is repaired.(3)pA=mintij.Based on the introduction of mobile node undivided holes, the nonparallel dichotomous repair strategy ensures that the coverage holes are completely repaired because at least 2 incomplete coverage intersections are eliminated per mobile node introduction during the nonparallel repair of the holes based on the drive node selection principles 1 and 3. Each introduced mobile node produces a maximum of 2 incomplete coverage intersections. The trajectory formed by the blade edge line rotating around the rotary axis is a single-leaf hyperboloid, which can be studied by using the properties of the single-leaf hyperboloid, as shown in Figure2, which can be regarded as the edge line AB rotating around the rotary axis OZ.Figure 2
Network data algorithm framework.The contact force between scraper chains is the main cause of chain fatigue and failure. Or use the Bayesian method to find the true value through the EM algorithm or parameterized method. Under the framework of crowdsourcing, assist the mobile wireless sensor network for GPS positioning. The study of the force characteristics of the chain drive system is essentially a study of the change of contact force between scraper chains at different positions. In the transmission process of the scraper conveyor chain drive system, the scraper chain, as the main traction component, includes two types of horizontal circular chain (horizontal chain) and vertical circular chain (vertical chain). The driving chain wheel teeth are circular arc tooth profiles, and there are chain nest grooves and vertical chain grooves distributed between any adjacent teeth. In the process of the chain drive system, the horizontal chain lies flat in the chain nest groove, and the vertical chain is connected with the horizontal chain and distributed in the vertical chain groove. The tooth profile of the driving sprocket is not only the main part of the scraper chain and teeth engagement and disengagement but also the main area of the sprocket bearing force, so the parametric modeling is of great significance to the structure development and optimization design of the sprocket.(4)D0=psin60/N2−dcos60/N2,W=2H+dcos90N+Asin90N−d.The link metric is between nodei and neighbor node j. The Creo2.0 software development platform enables the virtual assembly of different mechanical systems and can be used for the rapid construction of 3D models of scraper conveyor chain drive systems. Among them, the “bottom-up” design method is the most conventional modeling method for virtual assembly, which models each component separately and then assembles each part into a whole in a step-by-step manner from the bottom up according to a certain installation order, constraint relationship, and hierarchy, which requires constant assembly and interference analysis to coordinate the design process to avoid interference errors. The “top-down” assembly design method is adopted for the 3D model of the chain drive system, which can achieve a high degree of coordination between the parametric design of key components and the virtual assembly process. The main principle is as follows: set the overall framework of the assembly or structural assembly scheme, which is used as the installation directory tree of the whole product, and in the assembly process, based on the directory tree, the subordinate assembly relationship and assembly order of different parts can be established from the top-level down to the bottom-level components and parts for assembly.
(5)ddt∂T∂qT+∂T∂qT−φqTp−θqTμ=Q,where the complete constraint equation of the system satisfies(6)φq,t=1.The incomplete constraint equations of the system satisfy(7)θq,q1,t=1.Its basic idea comes from a collective intelligence that includes the contributions of thousands of individuals. And smart devices, such as mobile smartphones, offer a surprisingly diverse range of uses. This flexibility is mainly because these smart devices are often embedded with highly accurate GPS positioning systems. People can easily take these smart devices with them and use them anytime and anywhere, which greatly enhances the mobility of these smart devices. The GPS positioning of mobile wireless sensor networks is assisted in the framework of crowdsourcing. As mentioned in Section3 for moving sensors to achieve specific coverage requirements, collecting GPS locations of randomly placed sensors in the network is the first step in computing and planning sensor movements, so it is important to assist mobile wireless sensor networks for GPS localization. A virtual prototype model of a double-chain traction chain transmission system considering the movement constraints and force relationships between different components and the dynamic characteristics of the chain transmission system under normal operating conditions, stuck-chain fault conditions, and broken-chain fault conditions is studied. It makes sense to set the application scenario within the urban fields (urban centers), where many people with smart devices are active. This provides a greater opportunity to provide GPS information from mobile wireless sensor networks. Of course, recruiting participants for the swarm intelligence sensing task needs to be considered at a certain cost: firstly recruiting as few participants as possible is one of the goals, and secondly, those suitable participants need to be selected for the recruitment process.
(8)Fq,u,μ,λ,t=1,Gu,q=u+q,ϕq,t=1.To study the dynamics of the chain drive system, it is necessary to study the complex contact problem between different rigid body surfaces while considering its multibody dynamic characteristics. The contact between different rigid bodies of the chain drive system is a complex nonlinear problem, and the contact collision can be regarded as a time-varying dynamic process, and the most used algorithms to deal with the boundaries of the contact problem are the implicit Lagrange algorithm and the display penalty function method [18]. In this section, the research and analysis of the contact problem between different rigid bodies of the chain drive system mainly involve contact collision detection and contact force solution. The polygonal contact model satisfies the following two characteristics: the surfaces of any rigid bodies in contact with each other can be described by polygons, and the commonly used methods for constructing polygonal surfaces include Bessel curves and NURBS methods; the contact force between any two contacting bodies of the system can be determined based on the elastic base model.
## 3.2. Experimental Optimization Design of Mechanical Chain Drive
Since the tension acquisition device needs to follow the movement of the scraper to collect the tension of the scraper chain in real time, the tension acquisition device cannot obtain a stable energy source by wired means. The energy source of the tension acquisition device is set as a battery because it relies on the power generation principle such as piezoelectric vibration capturing energy, which leads to the unstable supply voltage. The capacity of the battery and the power consumption of the tension collection device determine the service time of the tension collection device [19]. The capacity of the battery is limited by the size of the battery, and the tension collection device and the battery are encapsulated together in the cavity of the lower pressure plate of the scraper, so there is a great limitation on the size and quantity of the battery. Therefore, to maximize the service time of the tension acquisition device, an energy-saving strategy is designed to reduce the power consumption of the tension acquisition device. The energy-saving strategy requires a proximity switch on the hardware and a dormant program on the software to form in conjunction. As mentioned above, the wireless communication distance is very short, and the data sent by the tension acquisition device can only be received by the data receiving device when the device moves with the squeegee to a position close to the data receiving device installed in the middle plate. Therefore, a proximity switch needs to be designed to notify the tension acquisition device when to start sending data. When the data transmission ends or is no longer within the communication range, the tension acquisition device can turn off the wireless transmitting function and enter the low-power sleep mode to save energy.The theoretical calculation of the dimensions of each component of the microstrip antenna was carried out above, and to further optimize the performance of the theoretically calculated natures, the length of the radiating patch of the microstrip antenna and the width of the 1/4 wavelength impedance converter were scanned by the simulation software HFSS to seek the dimensions that satisfy the best performance of the antenna. During the actual operation of the chain drive system, there are obvious contact relations between the components such as scraper chain, sprocket, and central groove, and contact pairs are formed between two rigid bodies in arbitrary contact, which play an important role in analyzing the interaction relations of the contacting rigid bodies. By analyzing the geometric position of different rigid body polygon contact planes, the contact collision can be detected. The following analysis of the contact between the driving sprocket and scraper chain and the contact relationship between adjacent scraper chains provides an effective basis for studying the contact collision relationship of different rigid bodies of the chain drive system, as shown in Figure3.Figure 3
Contact relationship between the chain wheel and scraper chain.In the actual operation of the chain drive system, there are obvious contact relations between the components such as scraper chain, sprocket, and central groove, and contact pairs are formed between two rigid bodies in arbitrary contact, which play an important role in the analysis of the interaction relations of contacting rigid bodies. By analyzing the geometric position of different rigid body polygon contact planes, the contact collision can be detected. The following analysis of the contact between the driving sprocket and scraper chain and the contact relationship between adjacent scraper chains provides an effective basis for studying the contact collision relationship of different rigid bodies in the chain drive system. By optimizing the driving node, the mobile node for cavity repair and the optimal repair location are determined to ensure that the area of the cavity to be repaired each time reaches the maximum. The experimental results show that compared with the existing methods, CHDARPI has reduced the average detection time and detection energy consumption by 15.2% and 16.7%, respectively.In actual operation, chain jamming and chain breakage failures are the most common forms of failure in the chain drive system of the scraper conveyor. In this paper, based on the simulation analysis of the virtual prototype model of the chain drive system under normal operating conditions, the dynamics of the chain drive system when the chain jamming fault and chain breakage fault occur are studied by setting the fault conditions. When the chain jamming fault occurs, it shows the jamming and tensing of the scraper chain; when the chain breakage fault occurs, it shows the sudden breakage of a scraper chain, and the scraper chains at the fault location are separated from each other [20]. These two protocols can effectively reduce the average energy consumption of network nodes, and the data collection rate of both exceeds 88%. To simulate the chain jamming fault condition, the sudden tensioning of the chain drive system can be realized by setting the sudden increase in the stiffness coefficient of the contact pair between the horizontal chain and the vertical chain, and the scraper chains forming the contact pair can be separated by releasing the contact pair between the horizontal chain and the vertical chain, thus simulating the chain breakage fault of the chain drive system [21]. Figure 4 depicts the study process of the dynamic characteristics of the chain drive system under the fault condition. The virtual prototype model of the chain drive system under the fault condition can be established quickly by setting the contact stiffness surge and releasing the contact constraints, and the simulation solution can be realized.Figure 4
Chain failure simulation analysis flow.To research the monitoring and diagnosis method of the heavy-duty scraper conveyor chain drive system, the dynamic characteristics of the chain drive system need to be fully considered. At present, the study of dynamic characteristics of chain drive systems based on the experimental method is costly and difficult to operate, so most of the research mostly focuses on model simplification and theoretical analysis of the single-chain system, and the reliability of the research method is low [22]. Considering the complexity of the structural composition of the scraper conveyor and the difficulty of the study of the dynamic characteristics, this section establishes a virtual prototype model of the double-chain traction chain drive system based on the multibody dynamic theory and contact collision theory, which integrates the motion constraints and force relationships between different components and studies the dynamic characteristics of the chain drive system under the conditions of normal operation, chain jamming fault operation, and chain breakage fault operation.
## 4. Analysis of Results
### 4.1. Wireless Sensor Network Data Algorithm Results
Figure5 shows the number of anchor points in the monitoring area for the four algorithms with different MCD charging radii. It can be found that the number of anchor points corresponding to all four algorithms decreases as the charging radius of MCD increases, which is because the charging radius of MCD determines the size of each access cell area, and the larger the charging radius, the fewer anchor points in the monitoring area. To address the problems of high detection energy consumption and long detection time of the existing coverage hole detection algorithm based on boundary node message detection, a coverage hole detection algorithm CHDARPI based on the relative position information of link intersection is proposed, and a hole detection message forwarding mechanism based on node orientation angle adaption is designed to achieve the detection of multiple types of coverage holes based on the relative position information of link intersection in the hole detection message.Figure 5
Radius and number of anchor points.To achieve low redundancy and complete repair of coverage voids, a dichotomous-based distributed coverage void repair algorithm CHRAND is then proposed to determine the mobile node and the optimal repair location for void repair by optimizing the drive node, which ensures the maximum area of each repaired void. The experimental results show that CHDARPI decreases 15.2% and 16.7% in the average detection time and detection energy consumption, respectively, compared with the existing methods. When the number of mobile nodes in the network is sufficient, the void repair rate of GRAND can reach 100%, and the repair redundancy does not exceed 0.354, as shown in Figure6.Figure 6
Radius and MCD travel distance.To address the problem of data collection rate degradation due to unreliable links, an energy-efficient routing protocol for wireless sensor networks is studied, and a dynamic hierarchical routing protocol EEDRP combined with a dormancy scheduling mechanism is proposed to minimize node energy consumption by making each node in a low-energy operating mode through the dormancy scheduling mechanism. It further combines node residual energy and link quality to determine the next-hop node forwarding set and reduces data transmission delay while improving data transmission reliability through ak-packet retransmission mechanism based on active time slot prediction. Specifically, the relationship between unreliable links and the “energy hole” of the clustering protocol is analyzed, and the fuzzy logic idea is used to decide the network clustering radius. The experimental results show that EEDRP and UCPFLUL protocols can effectively reduce the average energy consumption of network nodes, and the data collection rate of both protocols exceeds 88%.In the application of mobile sink banded wireless sensor network based on event monitoring, a mobile sink data collection algorithm DCAFAN based on agent node forwarding is proposed to meet the low latency performance requirement of event monitoring data collection, while the existing data collection technique of building to the sink path can solve the above latency problem but has the problem of unreliable data transmission. Specifically, DCAFAN constructs a queue of agent nodes that identify the moving trajectory of sink and a sequence of line nodes that store tracking agent nodes, and data nodes transmit data to sink by acquiring tracking agent nodes. The sequence of line nodes and the queue of agent nodes are updated with tracking agent nodes to avoid their death due to energy exhaustion. In addition, a wake-up time-lag difference-based routing method is proposed to assist DCAFAN in solving the problem of excessive node data transmission delay under low duty cycle networks. Experimental results show that DCAFAN has good data collection delay performance while balancing network node energy consumption as well as data collection rate performance.
### 4.2. Mechanical Chain Drive Optimization Results
Figure7 depicts the Simulink solution module for scraper chain tension estimation. The solution module takes the drive sprocket torque as the system input, provides the known parameters from the state space equations, and uses the state observer constructed in this study as a tool to estimate the scraper chain tension variation for each discrete unit body from the known state parameters. The results of tension estimation at different contact points of the chain drive system during the 1~3 s stable operation phase are described. Combined with equations (7) and (8), the three-dimensional surface plots of the tension variation at different contact position points estimated by the state observer when taking different values are depicted in the figure. The analysis shows that the tension distribution law of the chain drive system is closely related to the spatial location of the contact points.Figure 7
Tension distribution of the scraper chain at different contact positions.At the same moment, along the scraper chain running direction, the tension at different contact points of the upper side chain of the chain drive system increases continuously, and the tension at different contact points of the lower side chain also shows an increasing trend, which is consistent with the theoretical analysis of the scraper chain tension distribution mentioned above. When taking different values, the tension changes at different contact points of the upper and lower side chains also meet the above variation law. For the upper side chain, the minimum and maximum values of tension occur at contact points 1 and 73, respectively, and the minimum and maximum values of tension for the lower side chain occur at contact points 74 and 146, which are consistent with the theoretical analysis of the tension distribution of the scraper chain. For the upper side chain and the lower side chain, the tension of the scraper chain is the smallest at the point where the sprocket engages and separates from the scraper chain, and the tension of the scraper chain is the largest when the sprocket engages and meets the scraper chain; when different values are taken, the location distribution of the maximum and minimum points of the contact force of the upper side chain and the lower side chain also meets the above variation law. Therefore, the scraper chain strains at different locations of the single-chain system measured by the scraper chain strain test experiment and the tensions at different contact locations estimated by the state observer have the same variation characteristics, which further verifies the reliability of the proposed tension estimation method.The chain drive system is prone to chain jamming failure and chain breakage failure so that the working performance of the whole chain drive system is reduced and the safe production of the scraper conveyor is affected, so it is necessary to provide early warning of the occurrence of scraper chain failure in time to avoid malignant accidents. Based on the research of the scraper chain tension distribution law monitoring method, this section proposes a scraper chain fault diagnosis method based on tension estimation. From Figure8, it can be obtained that the maximum tension values at different contact points of the upper side chain system are significantly higher than those of the lower side chain system, so the upper side chain system is more prone to damage due to stress concentration. Then, the tension distribution state of the chain drive system is analyzed; at the same time, combined with the theoretical calculation results and the virtual prototype simulation results, the error analysis of the estimated results of the tension change of the scraper chain is carried out, and the strain test experiment of the scraper chain is carried out. Experimental verification is performed. In addition, in the actual production environment, the upper side chain system is more likely to be influenced by external factors and scraper chain failure occurs. Therefore, the contact point of the upper side chain system is taken as the research object to start the research of scraper chain fault diagnosis.Figure 8
Estimation error of the upper side chain system.In this section, the tension variation of the scraper chain is estimated based on the state observer, and then, the diagnosis of the chain jamming fault and chain breakage fault of the scraper chain is made. The diagnosis effect is not affected by the fault location and the change of the stiffness coefficient, and it can accurately determine whether the scraper chain is faulty and distinguish the fault type. Combined with the aforementioned study on the characteristics of the scraper chain tension change under fault conditions based on the virtual prototype simulation technology and the analysis of the experimental data of the scraper conveyor chain drive system fault test, it can be seen that in the fault stabilization stage, when the chain jamming fault occurs, the contact force between the monitored scraper chains and the strain of the measured scraper chains increases significantly compared with the normal conditions, and when the chain breakage fault occurs, the strain between the monitored scraper chains increases significantly compared with the normal conditions. In the case of chain breakage, the contact force between the monitored scraper chains and the measured strain of the scraper chains decreases compared to the normal condition. The predicted tension variation patterns of the scraper chain at the fault-prone locations under the chain jamming and chain breakage conditions are consistent with the simulation results of the virtual prototype and the experimental analysis results, which verify the effectiveness of the scraper chain fault diagnosis strategy described in this section.The state-space equations of the discretized model are established, and the design method of the state observer is studied; the matrix dimensionality reduction algorithm is proposed, and the tension distribution monitoring method of the chain drive system based on the state observer is studied, and the scraper chain tension changes at different position points of the whole chain drive system are estimated by the scraper chain tension at finite known position points, and then the tension distribution state of the chain drive system is analyzed; meanwhile, the error analysis of the scraper chain tension changes is carried out based on the theoretical calculation results and the virtual prototype simulation results. Meanwhile, the error analysis of the estimation results of the scraper chain tension variation is combined with the theoretical calculation results and the simulation results of the virtual prototype, and the experimental verification is carried out based on the scraper chain strain test experiment. The error analysis and experimental verification show that the proposed tension distribution monitoring method can effectively predict the tension change of the scraper chain with high estimation accuracy and reliability and can realize comprehensive monitoring and analysis of tension change at different position points of the chain drive system with the premise of reducing the number of sensors used.
## 4.1. Wireless Sensor Network Data Algorithm Results
Figure5 shows the number of anchor points in the monitoring area for the four algorithms with different MCD charging radii. It can be found that the number of anchor points corresponding to all four algorithms decreases as the charging radius of MCD increases, which is because the charging radius of MCD determines the size of each access cell area, and the larger the charging radius, the fewer anchor points in the monitoring area. To address the problems of high detection energy consumption and long detection time of the existing coverage hole detection algorithm based on boundary node message detection, a coverage hole detection algorithm CHDARPI based on the relative position information of link intersection is proposed, and a hole detection message forwarding mechanism based on node orientation angle adaption is designed to achieve the detection of multiple types of coverage holes based on the relative position information of link intersection in the hole detection message.Figure 5
Radius and number of anchor points.To achieve low redundancy and complete repair of coverage voids, a dichotomous-based distributed coverage void repair algorithm CHRAND is then proposed to determine the mobile node and the optimal repair location for void repair by optimizing the drive node, which ensures the maximum area of each repaired void. The experimental results show that CHDARPI decreases 15.2% and 16.7% in the average detection time and detection energy consumption, respectively, compared with the existing methods. When the number of mobile nodes in the network is sufficient, the void repair rate of GRAND can reach 100%, and the repair redundancy does not exceed 0.354, as shown in Figure6.Figure 6
Radius and MCD travel distance.To address the problem of data collection rate degradation due to unreliable links, an energy-efficient routing protocol for wireless sensor networks is studied, and a dynamic hierarchical routing protocol EEDRP combined with a dormancy scheduling mechanism is proposed to minimize node energy consumption by making each node in a low-energy operating mode through the dormancy scheduling mechanism. It further combines node residual energy and link quality to determine the next-hop node forwarding set and reduces data transmission delay while improving data transmission reliability through ak-packet retransmission mechanism based on active time slot prediction. Specifically, the relationship between unreliable links and the “energy hole” of the clustering protocol is analyzed, and the fuzzy logic idea is used to decide the network clustering radius. The experimental results show that EEDRP and UCPFLUL protocols can effectively reduce the average energy consumption of network nodes, and the data collection rate of both protocols exceeds 88%.In the application of mobile sink banded wireless sensor network based on event monitoring, a mobile sink data collection algorithm DCAFAN based on agent node forwarding is proposed to meet the low latency performance requirement of event monitoring data collection, while the existing data collection technique of building to the sink path can solve the above latency problem but has the problem of unreliable data transmission. Specifically, DCAFAN constructs a queue of agent nodes that identify the moving trajectory of sink and a sequence of line nodes that store tracking agent nodes, and data nodes transmit data to sink by acquiring tracking agent nodes. The sequence of line nodes and the queue of agent nodes are updated with tracking agent nodes to avoid their death due to energy exhaustion. In addition, a wake-up time-lag difference-based routing method is proposed to assist DCAFAN in solving the problem of excessive node data transmission delay under low duty cycle networks. Experimental results show that DCAFAN has good data collection delay performance while balancing network node energy consumption as well as data collection rate performance.
## 4.2. Mechanical Chain Drive Optimization Results
Figure7 depicts the Simulink solution module for scraper chain tension estimation. The solution module takes the drive sprocket torque as the system input, provides the known parameters from the state space equations, and uses the state observer constructed in this study as a tool to estimate the scraper chain tension variation for each discrete unit body from the known state parameters. The results of tension estimation at different contact points of the chain drive system during the 1~3 s stable operation phase are described. Combined with equations (7) and (8), the three-dimensional surface plots of the tension variation at different contact position points estimated by the state observer when taking different values are depicted in the figure. The analysis shows that the tension distribution law of the chain drive system is closely related to the spatial location of the contact points.Figure 7
Tension distribution of the scraper chain at different contact positions.At the same moment, along the scraper chain running direction, the tension at different contact points of the upper side chain of the chain drive system increases continuously, and the tension at different contact points of the lower side chain also shows an increasing trend, which is consistent with the theoretical analysis of the scraper chain tension distribution mentioned above. When taking different values, the tension changes at different contact points of the upper and lower side chains also meet the above variation law. For the upper side chain, the minimum and maximum values of tension occur at contact points 1 and 73, respectively, and the minimum and maximum values of tension for the lower side chain occur at contact points 74 and 146, which are consistent with the theoretical analysis of the tension distribution of the scraper chain. For the upper side chain and the lower side chain, the tension of the scraper chain is the smallest at the point where the sprocket engages and separates from the scraper chain, and the tension of the scraper chain is the largest when the sprocket engages and meets the scraper chain; when different values are taken, the location distribution of the maximum and minimum points of the contact force of the upper side chain and the lower side chain also meets the above variation law. Therefore, the scraper chain strains at different locations of the single-chain system measured by the scraper chain strain test experiment and the tensions at different contact locations estimated by the state observer have the same variation characteristics, which further verifies the reliability of the proposed tension estimation method.The chain drive system is prone to chain jamming failure and chain breakage failure so that the working performance of the whole chain drive system is reduced and the safe production of the scraper conveyor is affected, so it is necessary to provide early warning of the occurrence of scraper chain failure in time to avoid malignant accidents. Based on the research of the scraper chain tension distribution law monitoring method, this section proposes a scraper chain fault diagnosis method based on tension estimation. From Figure8, it can be obtained that the maximum tension values at different contact points of the upper side chain system are significantly higher than those of the lower side chain system, so the upper side chain system is more prone to damage due to stress concentration. Then, the tension distribution state of the chain drive system is analyzed; at the same time, combined with the theoretical calculation results and the virtual prototype simulation results, the error analysis of the estimated results of the tension change of the scraper chain is carried out, and the strain test experiment of the scraper chain is carried out. Experimental verification is performed. In addition, in the actual production environment, the upper side chain system is more likely to be influenced by external factors and scraper chain failure occurs. Therefore, the contact point of the upper side chain system is taken as the research object to start the research of scraper chain fault diagnosis.Figure 8
Estimation error of the upper side chain system.In this section, the tension variation of the scraper chain is estimated based on the state observer, and then, the diagnosis of the chain jamming fault and chain breakage fault of the scraper chain is made. The diagnosis effect is not affected by the fault location and the change of the stiffness coefficient, and it can accurately determine whether the scraper chain is faulty and distinguish the fault type. Combined with the aforementioned study on the characteristics of the scraper chain tension change under fault conditions based on the virtual prototype simulation technology and the analysis of the experimental data of the scraper conveyor chain drive system fault test, it can be seen that in the fault stabilization stage, when the chain jamming fault occurs, the contact force between the monitored scraper chains and the strain of the measured scraper chains increases significantly compared with the normal conditions, and when the chain breakage fault occurs, the strain between the monitored scraper chains increases significantly compared with the normal conditions. In the case of chain breakage, the contact force between the monitored scraper chains and the measured strain of the scraper chains decreases compared to the normal condition. The predicted tension variation patterns of the scraper chain at the fault-prone locations under the chain jamming and chain breakage conditions are consistent with the simulation results of the virtual prototype and the experimental analysis results, which verify the effectiveness of the scraper chain fault diagnosis strategy described in this section.The state-space equations of the discretized model are established, and the design method of the state observer is studied; the matrix dimensionality reduction algorithm is proposed, and the tension distribution monitoring method of the chain drive system based on the state observer is studied, and the scraper chain tension changes at different position points of the whole chain drive system are estimated by the scraper chain tension at finite known position points, and then the tension distribution state of the chain drive system is analyzed; meanwhile, the error analysis of the scraper chain tension changes is carried out based on the theoretical calculation results and the virtual prototype simulation results. Meanwhile, the error analysis of the estimation results of the scraper chain tension variation is combined with the theoretical calculation results and the simulation results of the virtual prototype, and the experimental verification is carried out based on the scraper chain strain test experiment. The error analysis and experimental verification show that the proposed tension distribution monitoring method can effectively predict the tension change of the scraper chain with high estimation accuracy and reliability and can realize comprehensive monitoring and analysis of tension change at different position points of the chain drive system with the premise of reducing the number of sensors used.
## 5. Conclusion
A lot of results have been achieved in various aspects of research on coverage voids and data collection techniques for wireless sensor networks, but as the application scope of wireless sensor networks continues to extend, there are still many critical issues to be addressed to meet the ever-changing application requirements. In this paper, we address the impact of node resource constraints, unreliable links, and coverage voids on data collection performance and study data collection techniques in various application scenarios with the goals of low-energy consumption, low latency, and high collection rate. To address the impact of limited node resources on the data collection performance of wireless sensor networks, the existing mobile device path planning algorithm with combined mobile data collection and wireless charging functions cannot simultaneously solve the problems of low data collection rate and high data collection delay under the continuous operation requirements of the network; this paper proposes a greedy policy-based mobile device path planning algorithm PPAGS. The minimum dwell time and maximum wait time of mobile devices in each access unit are predicted using the Markov model for the dynamic change of parameters such as node energy and data collection, which avoids the mobile devices from moving across a large span in the monitoring area. In addition, the PPAGS algorithm has the advantages of low complexity, and there is no need to obtain the actual location information of nodes and anchors during the operation. The experimental results show that the average data collection delay of PPAGS decreases by 25.9%, the average data collection rate increases by 7% to 98.91%, and the average node failure rate does not exceed 3.1% compared with existing methods.
---
*Source: 2901624-2021-09-14.xml* | 2021 |
# Analysis of Vibrations Generated by the Presence of Corrugation in a Modeled Tram Track
**Authors:** Julia I. Real Herráiz; Silvia Morales-Ivorra; Clara Zamorano Martín; Vicente Soler Basauri
**Journal:** Mathematical Problems in Engineering
(2015)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2015/290164
---
## Abstract
In recent years, there has been a significant increase in the development of the railway system. Despite the huge benefits of railways, one of the main drawbacks of this mode of transport is vibrations caused by vehicles in service, especially in the case of trams circulating in urban areas. Moreover, this undesirable phenomenon may be exacerbated by the presence of irregularities in the rail-wheel contact. Thus, an analytical model able to reproduce the vibrational behavior of a real stretch of tram track was implemented. Besides, a simulation of different types of corrugation was carried out by calculating in an auxiliary model the dynamic overloads generated by corrugation. These dynamic overloads fed the main model to obtain the vibrations generated and then transmitted to the track.
---
## Body
## 1. Introduction
The development of new railway networks as well as the improvement of the already existing tracks has become a worldwide priority. At the same time, externalities derived from railway operations have been identified as a major drawback for this mode of transport, with vibrations being one of the externalities which must be highlighted. Vibrations, caused by vehicles in service, are propagated from the railway superstructure, and they may affect people or structures in the surrounding areas. Thus, major efforts have been focused in minimizing the potential effect of vibratory waves on elements placed outside of the transport system, being necessary to study their nature and mechanisms of generation, transmission, and propagation.Railway vibrations are originated by the rail-wheel contact, so contact surfaces of both elements have a huge influence on the wave features of generated vibration, as stated by [1]. Tough different rail irregularities are able to modify the running surface and, therefore, cause specific vibrations; this study has been focused on the vibrational effects caused by corrugation.Corrugation is a widespread pathology which can be found in all types of railroads. Reference [2] established that given a particular rail profile, corrugation can be considered, in one hand, both as a wavelength-fixing mechanism which depends on the dynamic features of the railroad and as a damage mechanism induced by dynamic loads. This finally results in a change in the rail profile determining new wavelengths as far as new damage, thus constituting a cyclic and progressive process. Besides, these authors classified the structural pathologies depending on the wavelength-fixing mechanism and on the damage mechanisms and proposed some treatments to reduce them. Reference [3] extended the research of causes of corrugation and suggested new treatments to prevent its progress.More recently, [4, 5] after studying the development of corrugation by finite element models (FEM) in different types of railroads, we concluded that curves with small radii favor the appearance of wear, with the damage placed under those wheels circulating in the inner side of the curve.Furthermore, at high speeds, the performance against corrugation is better in slab tracks than in ballasted tracks. A different point of view was contributed by [6], who analyzed the influence of pad stiffness when corrugation appeared in the low rail of a curve in Bilbao’s underground. Those authors considered a multibody model for the vehicle and, applying [7] proposals, predicted frequencies at which corrugation is more likely to occur. Besides, they demonstrated that elastic pads reduce corrugation by suppressing some wavelengths that otherwise will be developed.Different prediction models for corrugation have been described until now, acquiring special relevance to know how imperfections in rails surface affect the vibrations induced to the track. Dynamic overloads originated by corrugation were calculated by [8] and then implemented in a discrete FEM to assess the vibrations derived from it. They concluded that frequencies associated with those continuous defects can be determined by the quotient between train speed and the wavelength associated with this imperfection.By using a three-dimensional model of wheel-rail interaction, [9] predicted the evolution of wear as well as its effect on the dynamic behavior of the track. According to this study, being the speed of the vehicle and the wavelength associated with corrugation constants, the larger the amplitude, the higher the dynamic overloads and wear derived from corrugation. Moreover, with the rest of parameters being constant, the greater the corrugation wavelength, the lower dynamic overloads and wear. In addition, the vertical stiffness of the different elements of the track was noted as a determining factor on the corrugation properties (i.e., amplitude and wavelength).Reference [10], by using a FEM in a moving reference system, analyzed the vehicle-track interaction. On the surface of a rail, a sinusoidal corrugation was simulated, concluding that all the dynamic responses (displacement, loads, and acceleration) induced by this irregularity keep this sinusoidal shape. It was also found that the greater the severity of the defect, the higher the dynamic overloads generated. As for the speed, its influence on the dynamic response of the track was demonstrated. When forces in the wheel-rail contact were measured, it was found that both displacements and accelerations grew with speed.In the present paper, an analytical model based on that used by [11] was implemented to reproduce the vibratory behavior of a tram track. Vibration data obtained in a campaign of measurements were used to calibrate the model.Once proved the ability of the model to reproduce the vibratory phenomenon from the real track, corrugation will be introduced in the model and its effect on the vibrations transmitted to the ground will be analyzed. This will require the use of an auxiliary model, as that presented by [12] is able to calculate those dynamic overloads generated by corrugation and transmitted to the track. Thus, once the dynamic overloads are obtained, they will be introduced in the main model to calculate the vibrations generated by this irregularity. Furthermore, a sensibility analysis of the different parameters involved in the generation of dynamic overloads will be carried out to unravel those who are relevant in the vibration phenomenon and thus act on them.This model may be useful to predict vibrations generated by the track corrugation and after establishing acceptable vibratory levels, it may allow determining the optimum moment to carry out the maintenance operations. Furthermore, the present analytical model can also be employed to calculate those track overloads due to corrugation which generate not only an aggravation of the rail irregularities but also premature deterioration of the rest of the track, as stated by [3].
## 2. Analytical Modelization of the Track
The aim of this section is to describe the modelization process of the stretch of the tramway track studied, as well as its analytical resolution. In addition, the data, obtained in a measurement campaign and used to calibrate the model, will be presented. Thus, a model able to reproduce accurately the vibratory behavior of the studied track has been obtained and then discussed.
### 2.1. Description of the Tramway Track Stretch
The cross-section of the track studied is constituted by a Ph37N rail embedded in elastomeric material, which are housed in a 15.5 cm thick surface layer made of concrete blocks. The surface layer is on a reinforced concrete slab of 22 cm thickness, which rests on a 25 cm thick layer of lean concrete as shown in Figure1.Figure 1The tram in service on this stretch of track is a Vossloh 4100 series as shown in Figure2. Its service speed is 35 km/h—with 100 km/h being its maximum speed—and transmits an axle load of 100 kN. The vehicle is composed of two motorized passenger cars at both extremes and another placed in the middle of them. The distance between axles of a same bogie is 2 m, and the distances between bogies are in turn 12.54 m, 4.70 m, and 12.54 m.Figure 2
### 2.2. Description of the Track Model
A bidimensional model able to calculate stresses and displacements is considered following [11, 13].A system integrated by three layers representing the different materials that compose the track is developed. As stated in the previous section, a Phoenix rail and the elastomeric material are placed in the first layer and composed of concrete blocks. The second layer represents the concrete slab and the third one the lean concrete. Note that an indefinite depth for ground located under the last of these three layers (Boussinesq half space) is assumed.The rail has been represented as a Timoshenko beam following [14], with its movement equations being those described by [3]
(1)
ρ
A
∂
2
w
∂
t
2
=
∂
∂
x
A
k
G
∂
w
∂
x
-
θ
+
q
x
,
t
,
ρ
I
∂
2
θ
∂
t
2
=
∂
∂
x
E
I
∂
θ
∂
x
+
A
k
G
∂
w
∂
x
-
θ
,
where A is the cross-sectional area, A
k is the shear cross-sectional area, E corresponds to Young modulus, I is the inertia in y-axis direction, ρ is the rail mass density, w is the vertical rail displacement, θ is the angular displacement, and q
(
x
,
t
) is the applied load depending on position and time.Otherwise, the features of materials composing the layers are shown in Table1.Table 1
E (Pa)
ν
ρ (kg/m3)
Paving blocks
2.25 ∗ 10∧9
0.25
2400
Reinforced concrete
2.73 ∗ 10∧10
0.25
2400
Lean concrete
2.25 ∗ 10∧10
0.2
2300By assuming a low viscosity between layers and following the research made by [15] the displacements can be expressed by means of the following vectorial equation:
(2)
λ
^
+
μ
^
∇
x
,
z
∇
x
,
z
d
+
μ
^
∇
x
,
z
2
d
=
ρ
∂
2
d
∂
t
2
,
while d
=
u
x
,
z
,
t
,
0
,
v
x
,
z
,
t represents the displacement of each layer, with ρ being the mass density for each layer. Meanwhile, λ
^ and μ
^ are the parameters employed to describe the viscoelastic behavior of each layer, as stated by [15]. Those parameters will be calibrated by using experimental data.
### 2.3. Load Modeling
When modeling loads, two different situations must be distinguished. On one hand, the quasistatic loads, which are due to the weight of the train traveling at a speedV-, must be taken into account. On the other hand, the dynamic overloads, which are the result of irregularities in the rail-wheel contact, will be discussed. These irregularities may be caused by defects in rails or wheels, joints between rails, or corrugation.The introduction of the harmonic loads which represent the dynamic overloads in the model is made following [16]. These harmonic loads can be written as P
j
t
=
P
0
j
cos
(
ϖ
j
t
), where P
0
j and ϖ
j represent, respectively, the magnitude and the characteristic angular frequency for each load.The effect of quasistatic loads can be introduced as a dynamic overload with a null characteristic angular frequency, as stated by [13] or following the Zimmermann formulation, as described by [17]. Because of computational time reasons, in this paper the second procedure will be followed.According to the Zimmermann method described by [17], the displacement of the rail due to a quasistatic load can be expressed as
(3)
d
4
z
d
x
4
+
k
E
I
z
=
0
.
Imposing the appropriate boundary conditions (point load, symmetry of the deformed shape of the rail, and disappearance of loading effect with distance) leads to the following expression for the vertical displacement developed by [17]
(4)
z
=
Q
2
b
C
b
C
4
E
I
4
e
-
x
/
L
v
cos
x
L
v
+
sin
x
L
v
,
where Q is the transmitted load, b is the gauge, C is an equivalent ballast coefficient, and L
v is an elastic length defined as
(5)
L
v
=
b
C
4
E
I
4
.
Once rail vertical displacements have been calculated, by renaming x
=
V
·
t, where V is the tram speed and t is time, they are differentiated twice with respect to time to obtain the desired accelerations.
### 2.4. Analytical Solution
Following [16], in order to solve the high complexity that often implies integration of movement equations, the Lamé potentials and Fourier Transform will be used. Thus, the movement of the beam representing the rail can be written as
(6)
A
K
G
k
2
1
+
A
K
G
I
ρ
ω
2
-
A
K
G
-
E
I
k
2
-
ρ
A
ω
2
w
~
~
k
,
ω
=
q
~
~
k
,
ω
-
a
σ
~
~
Z
Z
1
k
,
0
,
ω
.
And the expressions for layers motion expressed in terms of Lamé potentials are
(7)
d
2
φ
~
~
d
z
2
-
R
L
2
φ
~
~
=
0
,
d
2
ψ
~
~
d
z
2
-
R
T
2
ψ
~
~
=
0
,
where φ
~
~ and ψ
~
~ are the Lamé potentials expressed in the frequency-wave number domain. The R
L
2 and R
T
2 functions represent the longitudinal and shear wave transmission speed, respectively, with their expressions being as follows:
(8)
R
L
2
=
k
2
-
ω
2
c
L
2
-
i
ω
λ
*
+
2
μ
*
/
ρ
,
R
T
2
=
k
2
-
ω
2
c
T
2
-
i
ω
μ
*
/
ρ
,
where λ
* and μ
* are the parameters which define the damping of the track and c
L and c
T represent the velocities of the longitudinal and shear waves in the layer.Then, the expressions for the displacements (9) and (10) and stresses (11) and (12) can be written as
(9)
u
~
~
k
,
z
,
ω
=
i
k
φ
~
~
-
d
ψ
~
~
d
z
,
(10)
v
~
~
k
,
z
,
ω
=
d
φ
~
~
d
z
+
i
k
ψ
~
~
,
(11)
σ
~
~
z
z
k
,
z
,
ω
=
λ
^
~
d
2
φ
~
~
d
z
2
-
k
2
φ
~
~
+
2
μ
^
~
d
2
φ
~
~
d
z
2
-
i
k
d
ψ
~
~
d
z
,
(12)
σ
~
~
z
x
k
,
z
,
ω
=
μ
^
~
2
i
k
d
φ
~
~
d
z
+
d
2
ψ
~
~
d
z
2
+
k
2
ψ
~
~
.
Solving the system (7) and replacing φ
~
~ and ψ
~
~ in (9)–(12):
(13)
u
~
~
j
k
,
z
,
ω
=
i
k
A
1
j
k
,
ω
e
R
L
j
z
+
A
2
j
k
,
ω
e
-
R
L
j
z
+
R
T
j
A
3
j
k
,
ω
e
R
T
j
z
-
A
4
j
k
,
ω
e
-
R
T
j
z
v
~
~
j
k
,
z
,
ω
=
R
L
j
A
1
j
k
,
ω
e
R
L
j
z
-
A
2
j
k
,
ω
e
-
R
L
j
z
-
i
k
A
3
j
k
,
ω
e
R
T
j
z
+
A
4
j
k
,
ω
e
-
R
T
j
z
σ
~
~
Z
Z
j
k
,
z
,
ω
=
C
1
j
A
1
j
k
,
ω
e
R
L
j
z
+
A
2
j
k
,
ω
e
-
R
L
j
z
+
C
2
j
A
3
j
k
,
ω
e
R
T
j
z
-
A
4
j
k
,
ω
e
-
R
T
j
z
σ
~
~
Z
x
j
k
,
z
,
ω
=
D
1
j
A
1
j
k
,
ω
e
R
L
j
z
-
A
2
j
k
,
ω
e
-
R
L
j
z
+
D
2
j
A
3
j
k
,
ω
e
R
T
j
z
+
A
4
j
k
,
ω
e
-
R
T
j
z
,
where
(14)
C
1
j
=
λ
^
~
j
+
2
μ
^
~
j
R
L
2
j
-
λ
^
~
j
k
,
C
2
j
=
-
2
i
k
μ
^
~
j
R
T
j
,
D
1
j
=
2
i
k
μ
^
~
j
R
L
j
,
D
2
j
=
μ
^
~
j
k
2
+
R
T
j
2
.
Boundary conditions are set so that the displacements between adjacent layers are equal and stresses between them are balanced. Furthermore, no horizontal rail movement and the vanishing of radiated vibrations as the soil depth increases are assumed.Therefore, replacing the boundary condition of each layer in (13) follows the expression M
·
A
=
q, where M is a coefficient matrix, A is the vector of coefficients to be calculated, and q is the vector of loads acting on the system.Following [15], once the motion and stresses expressions have been obtained in terms of deepness and in frequency-wave number domain, they are returned to the space-time domain by using the inverse Fourier transform. In order to optimize this process the displacements are written in terms of the wave number domain and then the expression of the inverse Fourier transform is converted into an addition following [14].The accelerations in each layer are obtained by differentiating twice, with respect to time, the displacement expressions from the inverse Fourier transform.Total accelerations generated and transmitted to the surrounding ground are obtained through superposition of quasistatic and dynamic overloads.In order to provide reliability to the model, a measurement camping was carried out as aforementioned. Data, obtained by triaxial accelerometers FastTracer Sequoia, have been processed and compared with those calculated in the model. After calibrating the damping parameters of the layers, the result of comparison between model and real data is shown in Figure3.Figure 3Figure3 shows the ability of the model to represent the peaks of vibrations and clearly reproduce the effect of passing passenger cars and their bogies through the stretch of the track. However, as shown in Figure 3, measured data (green) is much noisier than the modeled one (red). These noisier accelerogram recordings may be due to the numerous factors intervening in the real vibratory phenomenon such as rails and wheels imperfections. In contrast, only few harmonic loads have been considered in the model to simulate these irregularities. Amplitudes and angular frequencies of these harmonic loads have been obtained after analyzing the Fourier spectrum of the registered data, taking their more significant values. To more accurate results, a larger number of harmonics might be considered, with the drawback of an increased computational time.It must be highlighted that, due to the typology of track studied, it was not possible to set the accelerometers in the rail, so they were placed next to the elastomeric material where the rail was housed. Then, the data registered with the accelerometers were influenced by the presence of this elastomeric material.
## 2.1. Description of the Tramway Track Stretch
The cross-section of the track studied is constituted by a Ph37N rail embedded in elastomeric material, which are housed in a 15.5 cm thick surface layer made of concrete blocks. The surface layer is on a reinforced concrete slab of 22 cm thickness, which rests on a 25 cm thick layer of lean concrete as shown in Figure1.Figure 1The tram in service on this stretch of track is a Vossloh 4100 series as shown in Figure2. Its service speed is 35 km/h—with 100 km/h being its maximum speed—and transmits an axle load of 100 kN. The vehicle is composed of two motorized passenger cars at both extremes and another placed in the middle of them. The distance between axles of a same bogie is 2 m, and the distances between bogies are in turn 12.54 m, 4.70 m, and 12.54 m.Figure 2
## 2.2. Description of the Track Model
A bidimensional model able to calculate stresses and displacements is considered following [11, 13].A system integrated by three layers representing the different materials that compose the track is developed. As stated in the previous section, a Phoenix rail and the elastomeric material are placed in the first layer and composed of concrete blocks. The second layer represents the concrete slab and the third one the lean concrete. Note that an indefinite depth for ground located under the last of these three layers (Boussinesq half space) is assumed.The rail has been represented as a Timoshenko beam following [14], with its movement equations being those described by [3]
(1)
ρ
A
∂
2
w
∂
t
2
=
∂
∂
x
A
k
G
∂
w
∂
x
-
θ
+
q
x
,
t
,
ρ
I
∂
2
θ
∂
t
2
=
∂
∂
x
E
I
∂
θ
∂
x
+
A
k
G
∂
w
∂
x
-
θ
,
where A is the cross-sectional area, A
k is the shear cross-sectional area, E corresponds to Young modulus, I is the inertia in y-axis direction, ρ is the rail mass density, w is the vertical rail displacement, θ is the angular displacement, and q
(
x
,
t
) is the applied load depending on position and time.Otherwise, the features of materials composing the layers are shown in Table1.Table 1
E (Pa)
ν
ρ (kg/m3)
Paving blocks
2.25 ∗ 10∧9
0.25
2400
Reinforced concrete
2.73 ∗ 10∧10
0.25
2400
Lean concrete
2.25 ∗ 10∧10
0.2
2300By assuming a low viscosity between layers and following the research made by [15] the displacements can be expressed by means of the following vectorial equation:
(2)
λ
^
+
μ
^
∇
x
,
z
∇
x
,
z
d
+
μ
^
∇
x
,
z
2
d
=
ρ
∂
2
d
∂
t
2
,
while d
=
u
x
,
z
,
t
,
0
,
v
x
,
z
,
t represents the displacement of each layer, with ρ being the mass density for each layer. Meanwhile, λ
^ and μ
^ are the parameters employed to describe the viscoelastic behavior of each layer, as stated by [15]. Those parameters will be calibrated by using experimental data.
## 2.3. Load Modeling
When modeling loads, two different situations must be distinguished. On one hand, the quasistatic loads, which are due to the weight of the train traveling at a speedV-, must be taken into account. On the other hand, the dynamic overloads, which are the result of irregularities in the rail-wheel contact, will be discussed. These irregularities may be caused by defects in rails or wheels, joints between rails, or corrugation.The introduction of the harmonic loads which represent the dynamic overloads in the model is made following [16]. These harmonic loads can be written as P
j
t
=
P
0
j
cos
(
ϖ
j
t
), where P
0
j and ϖ
j represent, respectively, the magnitude and the characteristic angular frequency for each load.The effect of quasistatic loads can be introduced as a dynamic overload with a null characteristic angular frequency, as stated by [13] or following the Zimmermann formulation, as described by [17]. Because of computational time reasons, in this paper the second procedure will be followed.According to the Zimmermann method described by [17], the displacement of the rail due to a quasistatic load can be expressed as
(3)
d
4
z
d
x
4
+
k
E
I
z
=
0
.
Imposing the appropriate boundary conditions (point load, symmetry of the deformed shape of the rail, and disappearance of loading effect with distance) leads to the following expression for the vertical displacement developed by [17]
(4)
z
=
Q
2
b
C
b
C
4
E
I
4
e
-
x
/
L
v
cos
x
L
v
+
sin
x
L
v
,
where Q is the transmitted load, b is the gauge, C is an equivalent ballast coefficient, and L
v is an elastic length defined as
(5)
L
v
=
b
C
4
E
I
4
.
Once rail vertical displacements have been calculated, by renaming x
=
V
·
t, where V is the tram speed and t is time, they are differentiated twice with respect to time to obtain the desired accelerations.
## 2.4. Analytical Solution
Following [16], in order to solve the high complexity that often implies integration of movement equations, the Lamé potentials and Fourier Transform will be used. Thus, the movement of the beam representing the rail can be written as
(6)
A
K
G
k
2
1
+
A
K
G
I
ρ
ω
2
-
A
K
G
-
E
I
k
2
-
ρ
A
ω
2
w
~
~
k
,
ω
=
q
~
~
k
,
ω
-
a
σ
~
~
Z
Z
1
k
,
0
,
ω
.
And the expressions for layers motion expressed in terms of Lamé potentials are
(7)
d
2
φ
~
~
d
z
2
-
R
L
2
φ
~
~
=
0
,
d
2
ψ
~
~
d
z
2
-
R
T
2
ψ
~
~
=
0
,
where φ
~
~ and ψ
~
~ are the Lamé potentials expressed in the frequency-wave number domain. The R
L
2 and R
T
2 functions represent the longitudinal and shear wave transmission speed, respectively, with their expressions being as follows:
(8)
R
L
2
=
k
2
-
ω
2
c
L
2
-
i
ω
λ
*
+
2
μ
*
/
ρ
,
R
T
2
=
k
2
-
ω
2
c
T
2
-
i
ω
μ
*
/
ρ
,
where λ
* and μ
* are the parameters which define the damping of the track and c
L and c
T represent the velocities of the longitudinal and shear waves in the layer.Then, the expressions for the displacements (9) and (10) and stresses (11) and (12) can be written as
(9)
u
~
~
k
,
z
,
ω
=
i
k
φ
~
~
-
d
ψ
~
~
d
z
,
(10)
v
~
~
k
,
z
,
ω
=
d
φ
~
~
d
z
+
i
k
ψ
~
~
,
(11)
σ
~
~
z
z
k
,
z
,
ω
=
λ
^
~
d
2
φ
~
~
d
z
2
-
k
2
φ
~
~
+
2
μ
^
~
d
2
φ
~
~
d
z
2
-
i
k
d
ψ
~
~
d
z
,
(12)
σ
~
~
z
x
k
,
z
,
ω
=
μ
^
~
2
i
k
d
φ
~
~
d
z
+
d
2
ψ
~
~
d
z
2
+
k
2
ψ
~
~
.
Solving the system (7) and replacing φ
~
~ and ψ
~
~ in (9)–(12):
(13)
u
~
~
j
k
,
z
,
ω
=
i
k
A
1
j
k
,
ω
e
R
L
j
z
+
A
2
j
k
,
ω
e
-
R
L
j
z
+
R
T
j
A
3
j
k
,
ω
e
R
T
j
z
-
A
4
j
k
,
ω
e
-
R
T
j
z
v
~
~
j
k
,
z
,
ω
=
R
L
j
A
1
j
k
,
ω
e
R
L
j
z
-
A
2
j
k
,
ω
e
-
R
L
j
z
-
i
k
A
3
j
k
,
ω
e
R
T
j
z
+
A
4
j
k
,
ω
e
-
R
T
j
z
σ
~
~
Z
Z
j
k
,
z
,
ω
=
C
1
j
A
1
j
k
,
ω
e
R
L
j
z
+
A
2
j
k
,
ω
e
-
R
L
j
z
+
C
2
j
A
3
j
k
,
ω
e
R
T
j
z
-
A
4
j
k
,
ω
e
-
R
T
j
z
σ
~
~
Z
x
j
k
,
z
,
ω
=
D
1
j
A
1
j
k
,
ω
e
R
L
j
z
-
A
2
j
k
,
ω
e
-
R
L
j
z
+
D
2
j
A
3
j
k
,
ω
e
R
T
j
z
+
A
4
j
k
,
ω
e
-
R
T
j
z
,
where
(14)
C
1
j
=
λ
^
~
j
+
2
μ
^
~
j
R
L
2
j
-
λ
^
~
j
k
,
C
2
j
=
-
2
i
k
μ
^
~
j
R
T
j
,
D
1
j
=
2
i
k
μ
^
~
j
R
L
j
,
D
2
j
=
μ
^
~
j
k
2
+
R
T
j
2
.
Boundary conditions are set so that the displacements between adjacent layers are equal and stresses between them are balanced. Furthermore, no horizontal rail movement and the vanishing of radiated vibrations as the soil depth increases are assumed.Therefore, replacing the boundary condition of each layer in (13) follows the expression M
·
A
=
q, where M is a coefficient matrix, A is the vector of coefficients to be calculated, and q is the vector of loads acting on the system.Following [15], once the motion and stresses expressions have been obtained in terms of deepness and in frequency-wave number domain, they are returned to the space-time domain by using the inverse Fourier transform. In order to optimize this process the displacements are written in terms of the wave number domain and then the expression of the inverse Fourier transform is converted into an addition following [14].The accelerations in each layer are obtained by differentiating twice, with respect to time, the displacement expressions from the inverse Fourier transform.Total accelerations generated and transmitted to the surrounding ground are obtained through superposition of quasistatic and dynamic overloads.In order to provide reliability to the model, a measurement camping was carried out as aforementioned. Data, obtained by triaxial accelerometers FastTracer Sequoia, have been processed and compared with those calculated in the model. After calibrating the damping parameters of the layers, the result of comparison between model and real data is shown in Figure3.Figure 3Figure3 shows the ability of the model to represent the peaks of vibrations and clearly reproduce the effect of passing passenger cars and their bogies through the stretch of the track. However, as shown in Figure 3, measured data (green) is much noisier than the modeled one (red). These noisier accelerogram recordings may be due to the numerous factors intervening in the real vibratory phenomenon such as rails and wheels imperfections. In contrast, only few harmonic loads have been considered in the model to simulate these irregularities. Amplitudes and angular frequencies of these harmonic loads have been obtained after analyzing the Fourier spectrum of the registered data, taking their more significant values. To more accurate results, a larger number of harmonics might be considered, with the drawback of an increased computational time.It must be highlighted that, due to the typology of track studied, it was not possible to set the accelerometers in the rail, so they were placed next to the elastomeric material where the rail was housed. Then, the data registered with the accelerometers were influenced by the presence of this elastomeric material.
## 3. Analysis of Corrugation
Simulation and analysis of the effect of corrugation in the model presented in the previous section will be addressed. The procedure will be as follows: dynamic overloads caused by the presence of corrugation on the rail will be calculated by using an auxiliary quarter car model and then the influence in dynamic overloads of parameters which define rail irregularities will be discussed.Dynamic overloads generate an increase of vibrations and wear, with the first one being the objective of this research. Thus, overloads will feed the model described in Section2 as harmonic forces in order to obtain the accelerations generated by rail irregularities.
### 3.1. Quarter Car Model
The vehicle can be modeled in different ways depending on the number of degrees of freedom given to the system: it can range from hundreds of degrees of freedom allowed by commercial multibody systems (MBS) to systems with a single degree of freedom constituted by a mass attached to the track by a spring.Between both extreme cases, the following can be found: (i) the quarter car model, which will be presented below; (ii) the half car system, it takes into account the sprung masses, the semisprung masses, and the unsprung masses; and (iii) the full car models, these allow us to take into account not only the displacements of masses but also their rotation with respect to each axis.Nevertheless, from the point of view of the main model and the fact that the loads introduced only have a vertical component, using a full bogie model would be an unnecessary computational expense. Moreover, [18] experimentally demonstrated that the influence on the dynamic stresses of the sprung and semisprung masses is negligible compared to the unsprung masses.Therefore, to calculate the dynamic overloads generated by corrugation, a quarter car system will be implemented using MATLAB software. In this model, the masses of the vehicle are discomposed in sprung and unsprung masses. The compatibility of strengths and displacements between both masses are solved by a spring and a damping element. Meanwhile, the strength transmission between the unsprung masses and the rail is performed by an equivalent spring, which takes into account not only the stiffness of the rail-wheel Hertzian contact but also the stiffness of the underlying track.The expressions governing the behavior of the quarter car model are as follows:(15)
m
2
x
2
′′
+
k
2
(
x
2
-
x
1
)
+
c
2
(
x
2
′
-
x
1
′
)
=
0
,
m
1
x
1
′′
-
c
2
x
2
′
+
c
2
x
1
′
-
k
2
x
2
+
k
2
+
k
1
x
1
-
k
1
z
=
0
,
where: m
1: unsprung mass per wheel, k
1: contact stiffness, m
2: sprung mass per wheel, k
2: primary stiffness, c
2: primary damping, x
i: displacement of the ith mass, x
i
′: velocity of the ith mass, and x
i
′′: acceleration of the ith mass.In Figure4, a quarter car model sketch can be seen.Figure 4In Table2 the values for the mass, stiffness, and damping are shown.Table 2
Quarter car model values
m
1 (kg)
500
k
1 (N/m)
32,000,000
m
2 (kg)
4,000
k
2 (N/m)
501,745
c
2 (N⋅s/m)
875Problem resolution is performed by the Laplace transference function and, once the accelerations of both masses have been obtained, dynamic overloads are calculated as follows:(16)
F
dyn
=
m
1
x
1
′′
+
m
2
x
2
′′
.
### 3.2. Sensitivity Analysis
Real rail profiles may be compared to a sum of sinusoids of different amplitudes and wavelengths. Therefore, in order to analyze the effect of a particular corrugation phenomenon, the profile of the affected track is modeled as a sinusoidal function, which is defined by wear amplitude and wavelength. Furthermore, the speed of the train in service is needed to be taken into account due to the dynamic performance of the analysis. When studying the influence of these parameters on the dynamic overloads, an amplitudeA = 0.25 mm, a wavelength λ = 0.5 m, and a speed V = 50 km/h are set. Then, with two of these parameters being fixed, the third one will be modified in order to analyze its influence on dynamic overloads.It must be highlighted that overload values given for each amplitude, speed, and wavelength correspond to the maximum absolute value of the stationary part of the overload function. The reason for this choice is to consider the most unfavorable case from the point of view of track design, maintenance, and security.Figure5 shows the influence of the speed of the tram on dynamic overloads, being the amplitude and wavelength of corrugation: A = 0.25 mm and λ = 0.5 m. From this analysis, it can be affirmed that dynamic overloads grow when increasing the speed of the vehicle.Figure 5On the other hand, the influence of wavelength on dynamic overloads, beingA = 0.25 mm and V = 50 km/h, is shown in Figure 6. In this graph, the peak obtained when the wavelength is about 0.1 m must be highlighted. Following [19], natural frequencies of the system are calculated as the root of the eigenvalues of
(17)
k
1
+
k
2
m
1
-
k
2
m
1
-
k
2
m
2
k
2
m
2
.
Then, the natural frequencies are 894.9302 rad/s and 9.4815 rad/s, the wavelength being associated with first natural frequency: λ = 0.0975 m, which corresponds to the wavelength estimated from Figure 6. Then, it can be said that for this wavelength—being the speed of the vehicle and train and track features constants—a resonance phenomenon will appear.Figure 6From Figure7, it can be noticed that, far from those wavelengths affected by the resonance phenomenon, dynamic overloads decrease when the wavelength of the irregularity increases. That is, the farther the distance between two consecutive irregularities, the lower the forces transmitted to the track.Figure 7Figure8 shows the influence of wear amplitude on dynamic overloads, being λ = 0.5 m and V = 50 km/h. This leads us to affirm that the higher the amplitude, the greater the overload. Furthermore, it must be noticed that overloads and corrugation amplitude are linearly related.Figure 8Taking into account the strong nonlinear behavior of the vehicle-track system, the linear behavior of the amplitude of corrugation must be explained. In order to assess the validity of the results obtained with the quarter car model, a multibody model has been implemented with the VAMPIRE commercial software and the influence of the amplitude has been studied. The results are exposed in Figure9.Figure 9From Figure9, two different behaviours of the relation amplitude-dynamic overloads are shown. On one hand, when the amplitude of corrugation is lower than 1 mm, the overloads generated by this pathology show a quasilinear behaviour for both models. On the other hand, when the amplitude exceeds this value a nonlinear behaviour can be appreciated for the multibody model but its behaviour remains quasilinear when dynamic overloads are calculated with the quarter car model.Thus, it can be concluded that the quarter car model described in this paper only is able to be used when the amplitude of the defect considered is lower than 1 mm.In conclusion, since it is not feasible that amplitudes higher than 1 mm appear in a tram track as the one proposed in this study and the quarter car model presents the advantage of its simplicity when comparing with the multibody model, the use of this model has been justified. Nevertheless, before using this model for other types of railroads where higher amplitudes may be reached a preliminary study must be carried out.
### 3.3. Definition of Different Scenarios
Below, a simulation of different scenarios will be performed. Irregularities simulated by the model will be added to the imperfections already present in the calibrated track. The values used in these simulations are shown in Table3.Table 3
V (km/h)
35
50
80
A (mm)
0.1
0.25
0.5
λ (m)
0.3
0.5
1Note that in the model a punctual contact between wheels and rails is assumed. Therefore, when simulating wear of a very short wavelength and high amplitude it would be necessary to check the veracity of this hypothesis. Thus, it is established that the curvature of the sinusoid representing the rail must be greater than wheel curvature.Wheel curvature is1
/
R
w.The curvature of the sinusoid representing the rail can be expressed asy
=
-
A
sin
(
k
x
) so: y
=
-
A
·
sin
(
2
π
x
/
λ
). By differentiating twice with respect to the position:
(18)
y
′′
=
4
π
2
λ
2
·
A
·
sin
2
π
x
λ
.
So the maximum curvature of the rail is (
4
π
2
/
λ
2
)
A m−1.Relating both curvatures,(19)
1
R
w
≤
4
π
2
λ
2
A
.
Then, the wavelength of the irregularity considered must satisfy
(20)
λ
≥
2
π
A
R
w
.
After verifying that all of them satisfy (20), the scenarios are discussed in Table 4.Table 4
Scenario
V (km/h)
A (mm)
λ (m)
F
din
max
(N)
a
max
(m/s2)
Case 1
35
0.25
0.5
1.7783
e
+
04
2.44511
Case 2
50
0.25
0.5
3.8228
e
+
04
4.77442
Case 3
80
0.25
0.5
1.0621
e
+
05
12.3465
Case 4
50
0.1
0.5
1.5291
e
+
04
4.62642
Case 5
50
0.5
0.5
7.6456
e
+
04
4.92609
Case 6
50
0.25
0.3
1.1547
e
+
05
5.69606
Case 7
50
0.25
1
8.4703
e
+
03
4.01358From the results for the dynamic overloads, the behavior predicted by earlier Figures5–8 is confirmed: high speed, high wavelengths, and low amplitudes generate higher values for dynamic overloads.Furthermore, in general, the higher the dynamic overload generated by corrugation, the greater the maximum accelerations generated and transmitted to the track. However, this affirmation is not satisfied in all cases (see cases 1 and 7). As discussed in Section2, this is due to the fact that the whole behavior of the system is determined by not only dynamic overloads, but also the quasistatic ones, which depend on speed. Thus, although in case 7 lower dynamic overloads have been obtained compared to case 1, the influence of the vehicle speed causes the greater accelerations generated in case 7.
## 3.1. Quarter Car Model
The vehicle can be modeled in different ways depending on the number of degrees of freedom given to the system: it can range from hundreds of degrees of freedom allowed by commercial multibody systems (MBS) to systems with a single degree of freedom constituted by a mass attached to the track by a spring.Between both extreme cases, the following can be found: (i) the quarter car model, which will be presented below; (ii) the half car system, it takes into account the sprung masses, the semisprung masses, and the unsprung masses; and (iii) the full car models, these allow us to take into account not only the displacements of masses but also their rotation with respect to each axis.Nevertheless, from the point of view of the main model and the fact that the loads introduced only have a vertical component, using a full bogie model would be an unnecessary computational expense. Moreover, [18] experimentally demonstrated that the influence on the dynamic stresses of the sprung and semisprung masses is negligible compared to the unsprung masses.Therefore, to calculate the dynamic overloads generated by corrugation, a quarter car system will be implemented using MATLAB software. In this model, the masses of the vehicle are discomposed in sprung and unsprung masses. The compatibility of strengths and displacements between both masses are solved by a spring and a damping element. Meanwhile, the strength transmission between the unsprung masses and the rail is performed by an equivalent spring, which takes into account not only the stiffness of the rail-wheel Hertzian contact but also the stiffness of the underlying track.The expressions governing the behavior of the quarter car model are as follows:(15)
m
2
x
2
′′
+
k
2
(
x
2
-
x
1
)
+
c
2
(
x
2
′
-
x
1
′
)
=
0
,
m
1
x
1
′′
-
c
2
x
2
′
+
c
2
x
1
′
-
k
2
x
2
+
k
2
+
k
1
x
1
-
k
1
z
=
0
,
where: m
1: unsprung mass per wheel, k
1: contact stiffness, m
2: sprung mass per wheel, k
2: primary stiffness, c
2: primary damping, x
i: displacement of the ith mass, x
i
′: velocity of the ith mass, and x
i
′′: acceleration of the ith mass.In Figure4, a quarter car model sketch can be seen.Figure 4In Table2 the values for the mass, stiffness, and damping are shown.Table 2
Quarter car model values
m
1 (kg)
500
k
1 (N/m)
32,000,000
m
2 (kg)
4,000
k
2 (N/m)
501,745
c
2 (N⋅s/m)
875Problem resolution is performed by the Laplace transference function and, once the accelerations of both masses have been obtained, dynamic overloads are calculated as follows:(16)
F
dyn
=
m
1
x
1
′′
+
m
2
x
2
′′
.
## 3.2. Sensitivity Analysis
Real rail profiles may be compared to a sum of sinusoids of different amplitudes and wavelengths. Therefore, in order to analyze the effect of a particular corrugation phenomenon, the profile of the affected track is modeled as a sinusoidal function, which is defined by wear amplitude and wavelength. Furthermore, the speed of the train in service is needed to be taken into account due to the dynamic performance of the analysis. When studying the influence of these parameters on the dynamic overloads, an amplitudeA = 0.25 mm, a wavelength λ = 0.5 m, and a speed V = 50 km/h are set. Then, with two of these parameters being fixed, the third one will be modified in order to analyze its influence on dynamic overloads.It must be highlighted that overload values given for each amplitude, speed, and wavelength correspond to the maximum absolute value of the stationary part of the overload function. The reason for this choice is to consider the most unfavorable case from the point of view of track design, maintenance, and security.Figure5 shows the influence of the speed of the tram on dynamic overloads, being the amplitude and wavelength of corrugation: A = 0.25 mm and λ = 0.5 m. From this analysis, it can be affirmed that dynamic overloads grow when increasing the speed of the vehicle.Figure 5On the other hand, the influence of wavelength on dynamic overloads, beingA = 0.25 mm and V = 50 km/h, is shown in Figure 6. In this graph, the peak obtained when the wavelength is about 0.1 m must be highlighted. Following [19], natural frequencies of the system are calculated as the root of the eigenvalues of
(17)
k
1
+
k
2
m
1
-
k
2
m
1
-
k
2
m
2
k
2
m
2
.
Then, the natural frequencies are 894.9302 rad/s and 9.4815 rad/s, the wavelength being associated with first natural frequency: λ = 0.0975 m, which corresponds to the wavelength estimated from Figure 6. Then, it can be said that for this wavelength—being the speed of the vehicle and train and track features constants—a resonance phenomenon will appear.Figure 6From Figure7, it can be noticed that, far from those wavelengths affected by the resonance phenomenon, dynamic overloads decrease when the wavelength of the irregularity increases. That is, the farther the distance between two consecutive irregularities, the lower the forces transmitted to the track.Figure 7Figure8 shows the influence of wear amplitude on dynamic overloads, being λ = 0.5 m and V = 50 km/h. This leads us to affirm that the higher the amplitude, the greater the overload. Furthermore, it must be noticed that overloads and corrugation amplitude are linearly related.Figure 8Taking into account the strong nonlinear behavior of the vehicle-track system, the linear behavior of the amplitude of corrugation must be explained. In order to assess the validity of the results obtained with the quarter car model, a multibody model has been implemented with the VAMPIRE commercial software and the influence of the amplitude has been studied. The results are exposed in Figure9.Figure 9From Figure9, two different behaviours of the relation amplitude-dynamic overloads are shown. On one hand, when the amplitude of corrugation is lower than 1 mm, the overloads generated by this pathology show a quasilinear behaviour for both models. On the other hand, when the amplitude exceeds this value a nonlinear behaviour can be appreciated for the multibody model but its behaviour remains quasilinear when dynamic overloads are calculated with the quarter car model.Thus, it can be concluded that the quarter car model described in this paper only is able to be used when the amplitude of the defect considered is lower than 1 mm.In conclusion, since it is not feasible that amplitudes higher than 1 mm appear in a tram track as the one proposed in this study and the quarter car model presents the advantage of its simplicity when comparing with the multibody model, the use of this model has been justified. Nevertheless, before using this model for other types of railroads where higher amplitudes may be reached a preliminary study must be carried out.
## 3.3. Definition of Different Scenarios
Below, a simulation of different scenarios will be performed. Irregularities simulated by the model will be added to the imperfections already present in the calibrated track. The values used in these simulations are shown in Table3.Table 3
V (km/h)
35
50
80
A (mm)
0.1
0.25
0.5
λ (m)
0.3
0.5
1Note that in the model a punctual contact between wheels and rails is assumed. Therefore, when simulating wear of a very short wavelength and high amplitude it would be necessary to check the veracity of this hypothesis. Thus, it is established that the curvature of the sinusoid representing the rail must be greater than wheel curvature.Wheel curvature is1
/
R
w.The curvature of the sinusoid representing the rail can be expressed asy
=
-
A
sin
(
k
x
) so: y
=
-
A
·
sin
(
2
π
x
/
λ
). By differentiating twice with respect to the position:
(18)
y
′′
=
4
π
2
λ
2
·
A
·
sin
2
π
x
λ
.
So the maximum curvature of the rail is (
4
π
2
/
λ
2
)
A m−1.Relating both curvatures,(19)
1
R
w
≤
4
π
2
λ
2
A
.
Then, the wavelength of the irregularity considered must satisfy
(20)
λ
≥
2
π
A
R
w
.
After verifying that all of them satisfy (20), the scenarios are discussed in Table 4.Table 4
Scenario
V (km/h)
A (mm)
λ (m)
F
din
max
(N)
a
max
(m/s2)
Case 1
35
0.25
0.5
1.7783
e
+
04
2.44511
Case 2
50
0.25
0.5
3.8228
e
+
04
4.77442
Case 3
80
0.25
0.5
1.0621
e
+
05
12.3465
Case 4
50
0.1
0.5
1.5291
e
+
04
4.62642
Case 5
50
0.5
0.5
7.6456
e
+
04
4.92609
Case 6
50
0.25
0.3
1.1547
e
+
05
5.69606
Case 7
50
0.25
1
8.4703
e
+
03
4.01358From the results for the dynamic overloads, the behavior predicted by earlier Figures5–8 is confirmed: high speed, high wavelengths, and low amplitudes generate higher values for dynamic overloads.Furthermore, in general, the higher the dynamic overload generated by corrugation, the greater the maximum accelerations generated and transmitted to the track. However, this affirmation is not satisfied in all cases (see cases 1 and 7). As discussed in Section2, this is due to the fact that the whole behavior of the system is determined by not only dynamic overloads, but also the quasistatic ones, which depend on speed. Thus, although in case 7 lower dynamic overloads have been obtained compared to case 1, the influence of the vehicle speed causes the greater accelerations generated in case 7.
## 4. Conclusions
The aim of this paper was to implement a model able to reproduce the vibratory behavior of a tram railroad, where a measurement campaign was conducted. Then, after confirming its correct behavior, a simulation of corrugation in that track was performed.For this purpose, an analytical model has been implemented in the Mathematica software based on that developed by [16]. Subsequently, a morphological calibration was carried out.An auxiliary quarter car model was implemented to evaluate the dynamic overloads generated by corrugation, and the following conclusions were obtained: the greater the speed of the vehicle and the amplitude of the defect, the greater the dynamic overloads transmitted to the track. On the other hand, the higher corrugation wavelength, the lower overloads generated.Dynamic overloads obtained as stated before feed the main model to obtain the vibrations generated by rail corrugation. From this analysis, it may be concluded that the overloads transmitted to the track due to corrugation are highly influential in the maximum acceleration generated by the vehicle, but also the effect of vehicle speed is very significant.The model described in this paper may be used as an aid to maintenance of railway infrastructure. Overall, for a given stretch of track, tram vehicles usually travel at the same speed. Moreover, according to [2] given the main features of a stretch of track and of those vehicles traveling through it, wavelength of rail corrugation may be predicted. Then, being the maximum allowable values for vibrations fixed for a particular stretch of track, model can predict from which corrugation amplitude maintenance operations are needed.
---
*Source: 290164-2015-02-04.xml* | 290164-2015-02-04_290164-2015-02-04.md | 48,095 | Analysis of Vibrations Generated by the Presence of Corrugation in a Modeled Tram Track | Julia I. Real Herráiz; Silvia Morales-Ivorra; Clara Zamorano Martín; Vicente Soler Basauri | Mathematical Problems in Engineering
(2015) | Engineering & Technology | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2015/290164 | 290164-2015-02-04.xml | ---
## Abstract
In recent years, there has been a significant increase in the development of the railway system. Despite the huge benefits of railways, one of the main drawbacks of this mode of transport is vibrations caused by vehicles in service, especially in the case of trams circulating in urban areas. Moreover, this undesirable phenomenon may be exacerbated by the presence of irregularities in the rail-wheel contact. Thus, an analytical model able to reproduce the vibrational behavior of a real stretch of tram track was implemented. Besides, a simulation of different types of corrugation was carried out by calculating in an auxiliary model the dynamic overloads generated by corrugation. These dynamic overloads fed the main model to obtain the vibrations generated and then transmitted to the track.
---
## Body
## 1. Introduction
The development of new railway networks as well as the improvement of the already existing tracks has become a worldwide priority. At the same time, externalities derived from railway operations have been identified as a major drawback for this mode of transport, with vibrations being one of the externalities which must be highlighted. Vibrations, caused by vehicles in service, are propagated from the railway superstructure, and they may affect people or structures in the surrounding areas. Thus, major efforts have been focused in minimizing the potential effect of vibratory waves on elements placed outside of the transport system, being necessary to study their nature and mechanisms of generation, transmission, and propagation.Railway vibrations are originated by the rail-wheel contact, so contact surfaces of both elements have a huge influence on the wave features of generated vibration, as stated by [1]. Tough different rail irregularities are able to modify the running surface and, therefore, cause specific vibrations; this study has been focused on the vibrational effects caused by corrugation.Corrugation is a widespread pathology which can be found in all types of railroads. Reference [2] established that given a particular rail profile, corrugation can be considered, in one hand, both as a wavelength-fixing mechanism which depends on the dynamic features of the railroad and as a damage mechanism induced by dynamic loads. This finally results in a change in the rail profile determining new wavelengths as far as new damage, thus constituting a cyclic and progressive process. Besides, these authors classified the structural pathologies depending on the wavelength-fixing mechanism and on the damage mechanisms and proposed some treatments to reduce them. Reference [3] extended the research of causes of corrugation and suggested new treatments to prevent its progress.More recently, [4, 5] after studying the development of corrugation by finite element models (FEM) in different types of railroads, we concluded that curves with small radii favor the appearance of wear, with the damage placed under those wheels circulating in the inner side of the curve.Furthermore, at high speeds, the performance against corrugation is better in slab tracks than in ballasted tracks. A different point of view was contributed by [6], who analyzed the influence of pad stiffness when corrugation appeared in the low rail of a curve in Bilbao’s underground. Those authors considered a multibody model for the vehicle and, applying [7] proposals, predicted frequencies at which corrugation is more likely to occur. Besides, they demonstrated that elastic pads reduce corrugation by suppressing some wavelengths that otherwise will be developed.Different prediction models for corrugation have been described until now, acquiring special relevance to know how imperfections in rails surface affect the vibrations induced to the track. Dynamic overloads originated by corrugation were calculated by [8] and then implemented in a discrete FEM to assess the vibrations derived from it. They concluded that frequencies associated with those continuous defects can be determined by the quotient between train speed and the wavelength associated with this imperfection.By using a three-dimensional model of wheel-rail interaction, [9] predicted the evolution of wear as well as its effect on the dynamic behavior of the track. According to this study, being the speed of the vehicle and the wavelength associated with corrugation constants, the larger the amplitude, the higher the dynamic overloads and wear derived from corrugation. Moreover, with the rest of parameters being constant, the greater the corrugation wavelength, the lower dynamic overloads and wear. In addition, the vertical stiffness of the different elements of the track was noted as a determining factor on the corrugation properties (i.e., amplitude and wavelength).Reference [10], by using a FEM in a moving reference system, analyzed the vehicle-track interaction. On the surface of a rail, a sinusoidal corrugation was simulated, concluding that all the dynamic responses (displacement, loads, and acceleration) induced by this irregularity keep this sinusoidal shape. It was also found that the greater the severity of the defect, the higher the dynamic overloads generated. As for the speed, its influence on the dynamic response of the track was demonstrated. When forces in the wheel-rail contact were measured, it was found that both displacements and accelerations grew with speed.In the present paper, an analytical model based on that used by [11] was implemented to reproduce the vibratory behavior of a tram track. Vibration data obtained in a campaign of measurements were used to calibrate the model.Once proved the ability of the model to reproduce the vibratory phenomenon from the real track, corrugation will be introduced in the model and its effect on the vibrations transmitted to the ground will be analyzed. This will require the use of an auxiliary model, as that presented by [12] is able to calculate those dynamic overloads generated by corrugation and transmitted to the track. Thus, once the dynamic overloads are obtained, they will be introduced in the main model to calculate the vibrations generated by this irregularity. Furthermore, a sensibility analysis of the different parameters involved in the generation of dynamic overloads will be carried out to unravel those who are relevant in the vibration phenomenon and thus act on them.This model may be useful to predict vibrations generated by the track corrugation and after establishing acceptable vibratory levels, it may allow determining the optimum moment to carry out the maintenance operations. Furthermore, the present analytical model can also be employed to calculate those track overloads due to corrugation which generate not only an aggravation of the rail irregularities but also premature deterioration of the rest of the track, as stated by [3].
## 2. Analytical Modelization of the Track
The aim of this section is to describe the modelization process of the stretch of the tramway track studied, as well as its analytical resolution. In addition, the data, obtained in a measurement campaign and used to calibrate the model, will be presented. Thus, a model able to reproduce accurately the vibratory behavior of the studied track has been obtained and then discussed.
### 2.1. Description of the Tramway Track Stretch
The cross-section of the track studied is constituted by a Ph37N rail embedded in elastomeric material, which are housed in a 15.5 cm thick surface layer made of concrete blocks. The surface layer is on a reinforced concrete slab of 22 cm thickness, which rests on a 25 cm thick layer of lean concrete as shown in Figure1.Figure 1The tram in service on this stretch of track is a Vossloh 4100 series as shown in Figure2. Its service speed is 35 km/h—with 100 km/h being its maximum speed—and transmits an axle load of 100 kN. The vehicle is composed of two motorized passenger cars at both extremes and another placed in the middle of them. The distance between axles of a same bogie is 2 m, and the distances between bogies are in turn 12.54 m, 4.70 m, and 12.54 m.Figure 2
### 2.2. Description of the Track Model
A bidimensional model able to calculate stresses and displacements is considered following [11, 13].A system integrated by three layers representing the different materials that compose the track is developed. As stated in the previous section, a Phoenix rail and the elastomeric material are placed in the first layer and composed of concrete blocks. The second layer represents the concrete slab and the third one the lean concrete. Note that an indefinite depth for ground located under the last of these three layers (Boussinesq half space) is assumed.The rail has been represented as a Timoshenko beam following [14], with its movement equations being those described by [3]
(1)
ρ
A
∂
2
w
∂
t
2
=
∂
∂
x
A
k
G
∂
w
∂
x
-
θ
+
q
x
,
t
,
ρ
I
∂
2
θ
∂
t
2
=
∂
∂
x
E
I
∂
θ
∂
x
+
A
k
G
∂
w
∂
x
-
θ
,
where A is the cross-sectional area, A
k is the shear cross-sectional area, E corresponds to Young modulus, I is the inertia in y-axis direction, ρ is the rail mass density, w is the vertical rail displacement, θ is the angular displacement, and q
(
x
,
t
) is the applied load depending on position and time.Otherwise, the features of materials composing the layers are shown in Table1.Table 1
E (Pa)
ν
ρ (kg/m3)
Paving blocks
2.25 ∗ 10∧9
0.25
2400
Reinforced concrete
2.73 ∗ 10∧10
0.25
2400
Lean concrete
2.25 ∗ 10∧10
0.2
2300By assuming a low viscosity between layers and following the research made by [15] the displacements can be expressed by means of the following vectorial equation:
(2)
λ
^
+
μ
^
∇
x
,
z
∇
x
,
z
d
+
μ
^
∇
x
,
z
2
d
=
ρ
∂
2
d
∂
t
2
,
while d
=
u
x
,
z
,
t
,
0
,
v
x
,
z
,
t represents the displacement of each layer, with ρ being the mass density for each layer. Meanwhile, λ
^ and μ
^ are the parameters employed to describe the viscoelastic behavior of each layer, as stated by [15]. Those parameters will be calibrated by using experimental data.
### 2.3. Load Modeling
When modeling loads, two different situations must be distinguished. On one hand, the quasistatic loads, which are due to the weight of the train traveling at a speedV-, must be taken into account. On the other hand, the dynamic overloads, which are the result of irregularities in the rail-wheel contact, will be discussed. These irregularities may be caused by defects in rails or wheels, joints between rails, or corrugation.The introduction of the harmonic loads which represent the dynamic overloads in the model is made following [16]. These harmonic loads can be written as P
j
t
=
P
0
j
cos
(
ϖ
j
t
), where P
0
j and ϖ
j represent, respectively, the magnitude and the characteristic angular frequency for each load.The effect of quasistatic loads can be introduced as a dynamic overload with a null characteristic angular frequency, as stated by [13] or following the Zimmermann formulation, as described by [17]. Because of computational time reasons, in this paper the second procedure will be followed.According to the Zimmermann method described by [17], the displacement of the rail due to a quasistatic load can be expressed as
(3)
d
4
z
d
x
4
+
k
E
I
z
=
0
.
Imposing the appropriate boundary conditions (point load, symmetry of the deformed shape of the rail, and disappearance of loading effect with distance) leads to the following expression for the vertical displacement developed by [17]
(4)
z
=
Q
2
b
C
b
C
4
E
I
4
e
-
x
/
L
v
cos
x
L
v
+
sin
x
L
v
,
where Q is the transmitted load, b is the gauge, C is an equivalent ballast coefficient, and L
v is an elastic length defined as
(5)
L
v
=
b
C
4
E
I
4
.
Once rail vertical displacements have been calculated, by renaming x
=
V
·
t, where V is the tram speed and t is time, they are differentiated twice with respect to time to obtain the desired accelerations.
### 2.4. Analytical Solution
Following [16], in order to solve the high complexity that often implies integration of movement equations, the Lamé potentials and Fourier Transform will be used. Thus, the movement of the beam representing the rail can be written as
(6)
A
K
G
k
2
1
+
A
K
G
I
ρ
ω
2
-
A
K
G
-
E
I
k
2
-
ρ
A
ω
2
w
~
~
k
,
ω
=
q
~
~
k
,
ω
-
a
σ
~
~
Z
Z
1
k
,
0
,
ω
.
And the expressions for layers motion expressed in terms of Lamé potentials are
(7)
d
2
φ
~
~
d
z
2
-
R
L
2
φ
~
~
=
0
,
d
2
ψ
~
~
d
z
2
-
R
T
2
ψ
~
~
=
0
,
where φ
~
~ and ψ
~
~ are the Lamé potentials expressed in the frequency-wave number domain. The R
L
2 and R
T
2 functions represent the longitudinal and shear wave transmission speed, respectively, with their expressions being as follows:
(8)
R
L
2
=
k
2
-
ω
2
c
L
2
-
i
ω
λ
*
+
2
μ
*
/
ρ
,
R
T
2
=
k
2
-
ω
2
c
T
2
-
i
ω
μ
*
/
ρ
,
where λ
* and μ
* are the parameters which define the damping of the track and c
L and c
T represent the velocities of the longitudinal and shear waves in the layer.Then, the expressions for the displacements (9) and (10) and stresses (11) and (12) can be written as
(9)
u
~
~
k
,
z
,
ω
=
i
k
φ
~
~
-
d
ψ
~
~
d
z
,
(10)
v
~
~
k
,
z
,
ω
=
d
φ
~
~
d
z
+
i
k
ψ
~
~
,
(11)
σ
~
~
z
z
k
,
z
,
ω
=
λ
^
~
d
2
φ
~
~
d
z
2
-
k
2
φ
~
~
+
2
μ
^
~
d
2
φ
~
~
d
z
2
-
i
k
d
ψ
~
~
d
z
,
(12)
σ
~
~
z
x
k
,
z
,
ω
=
μ
^
~
2
i
k
d
φ
~
~
d
z
+
d
2
ψ
~
~
d
z
2
+
k
2
ψ
~
~
.
Solving the system (7) and replacing φ
~
~ and ψ
~
~ in (9)–(12):
(13)
u
~
~
j
k
,
z
,
ω
=
i
k
A
1
j
k
,
ω
e
R
L
j
z
+
A
2
j
k
,
ω
e
-
R
L
j
z
+
R
T
j
A
3
j
k
,
ω
e
R
T
j
z
-
A
4
j
k
,
ω
e
-
R
T
j
z
v
~
~
j
k
,
z
,
ω
=
R
L
j
A
1
j
k
,
ω
e
R
L
j
z
-
A
2
j
k
,
ω
e
-
R
L
j
z
-
i
k
A
3
j
k
,
ω
e
R
T
j
z
+
A
4
j
k
,
ω
e
-
R
T
j
z
σ
~
~
Z
Z
j
k
,
z
,
ω
=
C
1
j
A
1
j
k
,
ω
e
R
L
j
z
+
A
2
j
k
,
ω
e
-
R
L
j
z
+
C
2
j
A
3
j
k
,
ω
e
R
T
j
z
-
A
4
j
k
,
ω
e
-
R
T
j
z
σ
~
~
Z
x
j
k
,
z
,
ω
=
D
1
j
A
1
j
k
,
ω
e
R
L
j
z
-
A
2
j
k
,
ω
e
-
R
L
j
z
+
D
2
j
A
3
j
k
,
ω
e
R
T
j
z
+
A
4
j
k
,
ω
e
-
R
T
j
z
,
where
(14)
C
1
j
=
λ
^
~
j
+
2
μ
^
~
j
R
L
2
j
-
λ
^
~
j
k
,
C
2
j
=
-
2
i
k
μ
^
~
j
R
T
j
,
D
1
j
=
2
i
k
μ
^
~
j
R
L
j
,
D
2
j
=
μ
^
~
j
k
2
+
R
T
j
2
.
Boundary conditions are set so that the displacements between adjacent layers are equal and stresses between them are balanced. Furthermore, no horizontal rail movement and the vanishing of radiated vibrations as the soil depth increases are assumed.Therefore, replacing the boundary condition of each layer in (13) follows the expression M
·
A
=
q, where M is a coefficient matrix, A is the vector of coefficients to be calculated, and q is the vector of loads acting on the system.Following [15], once the motion and stresses expressions have been obtained in terms of deepness and in frequency-wave number domain, they are returned to the space-time domain by using the inverse Fourier transform. In order to optimize this process the displacements are written in terms of the wave number domain and then the expression of the inverse Fourier transform is converted into an addition following [14].The accelerations in each layer are obtained by differentiating twice, with respect to time, the displacement expressions from the inverse Fourier transform.Total accelerations generated and transmitted to the surrounding ground are obtained through superposition of quasistatic and dynamic overloads.In order to provide reliability to the model, a measurement camping was carried out as aforementioned. Data, obtained by triaxial accelerometers FastTracer Sequoia, have been processed and compared with those calculated in the model. After calibrating the damping parameters of the layers, the result of comparison between model and real data is shown in Figure3.Figure 3Figure3 shows the ability of the model to represent the peaks of vibrations and clearly reproduce the effect of passing passenger cars and their bogies through the stretch of the track. However, as shown in Figure 3, measured data (green) is much noisier than the modeled one (red). These noisier accelerogram recordings may be due to the numerous factors intervening in the real vibratory phenomenon such as rails and wheels imperfections. In contrast, only few harmonic loads have been considered in the model to simulate these irregularities. Amplitudes and angular frequencies of these harmonic loads have been obtained after analyzing the Fourier spectrum of the registered data, taking their more significant values. To more accurate results, a larger number of harmonics might be considered, with the drawback of an increased computational time.It must be highlighted that, due to the typology of track studied, it was not possible to set the accelerometers in the rail, so they were placed next to the elastomeric material where the rail was housed. Then, the data registered with the accelerometers were influenced by the presence of this elastomeric material.
## 2.1. Description of the Tramway Track Stretch
The cross-section of the track studied is constituted by a Ph37N rail embedded in elastomeric material, which are housed in a 15.5 cm thick surface layer made of concrete blocks. The surface layer is on a reinforced concrete slab of 22 cm thickness, which rests on a 25 cm thick layer of lean concrete as shown in Figure1.Figure 1The tram in service on this stretch of track is a Vossloh 4100 series as shown in Figure2. Its service speed is 35 km/h—with 100 km/h being its maximum speed—and transmits an axle load of 100 kN. The vehicle is composed of two motorized passenger cars at both extremes and another placed in the middle of them. The distance between axles of a same bogie is 2 m, and the distances between bogies are in turn 12.54 m, 4.70 m, and 12.54 m.Figure 2
## 2.2. Description of the Track Model
A bidimensional model able to calculate stresses and displacements is considered following [11, 13].A system integrated by three layers representing the different materials that compose the track is developed. As stated in the previous section, a Phoenix rail and the elastomeric material are placed in the first layer and composed of concrete blocks. The second layer represents the concrete slab and the third one the lean concrete. Note that an indefinite depth for ground located under the last of these three layers (Boussinesq half space) is assumed.The rail has been represented as a Timoshenko beam following [14], with its movement equations being those described by [3]
(1)
ρ
A
∂
2
w
∂
t
2
=
∂
∂
x
A
k
G
∂
w
∂
x
-
θ
+
q
x
,
t
,
ρ
I
∂
2
θ
∂
t
2
=
∂
∂
x
E
I
∂
θ
∂
x
+
A
k
G
∂
w
∂
x
-
θ
,
where A is the cross-sectional area, A
k is the shear cross-sectional area, E corresponds to Young modulus, I is the inertia in y-axis direction, ρ is the rail mass density, w is the vertical rail displacement, θ is the angular displacement, and q
(
x
,
t
) is the applied load depending on position and time.Otherwise, the features of materials composing the layers are shown in Table1.Table 1
E (Pa)
ν
ρ (kg/m3)
Paving blocks
2.25 ∗ 10∧9
0.25
2400
Reinforced concrete
2.73 ∗ 10∧10
0.25
2400
Lean concrete
2.25 ∗ 10∧10
0.2
2300By assuming a low viscosity between layers and following the research made by [15] the displacements can be expressed by means of the following vectorial equation:
(2)
λ
^
+
μ
^
∇
x
,
z
∇
x
,
z
d
+
μ
^
∇
x
,
z
2
d
=
ρ
∂
2
d
∂
t
2
,
while d
=
u
x
,
z
,
t
,
0
,
v
x
,
z
,
t represents the displacement of each layer, with ρ being the mass density for each layer. Meanwhile, λ
^ and μ
^ are the parameters employed to describe the viscoelastic behavior of each layer, as stated by [15]. Those parameters will be calibrated by using experimental data.
## 2.3. Load Modeling
When modeling loads, two different situations must be distinguished. On one hand, the quasistatic loads, which are due to the weight of the train traveling at a speedV-, must be taken into account. On the other hand, the dynamic overloads, which are the result of irregularities in the rail-wheel contact, will be discussed. These irregularities may be caused by defects in rails or wheels, joints between rails, or corrugation.The introduction of the harmonic loads which represent the dynamic overloads in the model is made following [16]. These harmonic loads can be written as P
j
t
=
P
0
j
cos
(
ϖ
j
t
), where P
0
j and ϖ
j represent, respectively, the magnitude and the characteristic angular frequency for each load.The effect of quasistatic loads can be introduced as a dynamic overload with a null characteristic angular frequency, as stated by [13] or following the Zimmermann formulation, as described by [17]. Because of computational time reasons, in this paper the second procedure will be followed.According to the Zimmermann method described by [17], the displacement of the rail due to a quasistatic load can be expressed as
(3)
d
4
z
d
x
4
+
k
E
I
z
=
0
.
Imposing the appropriate boundary conditions (point load, symmetry of the deformed shape of the rail, and disappearance of loading effect with distance) leads to the following expression for the vertical displacement developed by [17]
(4)
z
=
Q
2
b
C
b
C
4
E
I
4
e
-
x
/
L
v
cos
x
L
v
+
sin
x
L
v
,
where Q is the transmitted load, b is the gauge, C is an equivalent ballast coefficient, and L
v is an elastic length defined as
(5)
L
v
=
b
C
4
E
I
4
.
Once rail vertical displacements have been calculated, by renaming x
=
V
·
t, where V is the tram speed and t is time, they are differentiated twice with respect to time to obtain the desired accelerations.
## 2.4. Analytical Solution
Following [16], in order to solve the high complexity that often implies integration of movement equations, the Lamé potentials and Fourier Transform will be used. Thus, the movement of the beam representing the rail can be written as
(6)
A
K
G
k
2
1
+
A
K
G
I
ρ
ω
2
-
A
K
G
-
E
I
k
2
-
ρ
A
ω
2
w
~
~
k
,
ω
=
q
~
~
k
,
ω
-
a
σ
~
~
Z
Z
1
k
,
0
,
ω
.
And the expressions for layers motion expressed in terms of Lamé potentials are
(7)
d
2
φ
~
~
d
z
2
-
R
L
2
φ
~
~
=
0
,
d
2
ψ
~
~
d
z
2
-
R
T
2
ψ
~
~
=
0
,
where φ
~
~ and ψ
~
~ are the Lamé potentials expressed in the frequency-wave number domain. The R
L
2 and R
T
2 functions represent the longitudinal and shear wave transmission speed, respectively, with their expressions being as follows:
(8)
R
L
2
=
k
2
-
ω
2
c
L
2
-
i
ω
λ
*
+
2
μ
*
/
ρ
,
R
T
2
=
k
2
-
ω
2
c
T
2
-
i
ω
μ
*
/
ρ
,
where λ
* and μ
* are the parameters which define the damping of the track and c
L and c
T represent the velocities of the longitudinal and shear waves in the layer.Then, the expressions for the displacements (9) and (10) and stresses (11) and (12) can be written as
(9)
u
~
~
k
,
z
,
ω
=
i
k
φ
~
~
-
d
ψ
~
~
d
z
,
(10)
v
~
~
k
,
z
,
ω
=
d
φ
~
~
d
z
+
i
k
ψ
~
~
,
(11)
σ
~
~
z
z
k
,
z
,
ω
=
λ
^
~
d
2
φ
~
~
d
z
2
-
k
2
φ
~
~
+
2
μ
^
~
d
2
φ
~
~
d
z
2
-
i
k
d
ψ
~
~
d
z
,
(12)
σ
~
~
z
x
k
,
z
,
ω
=
μ
^
~
2
i
k
d
φ
~
~
d
z
+
d
2
ψ
~
~
d
z
2
+
k
2
ψ
~
~
.
Solving the system (7) and replacing φ
~
~ and ψ
~
~ in (9)–(12):
(13)
u
~
~
j
k
,
z
,
ω
=
i
k
A
1
j
k
,
ω
e
R
L
j
z
+
A
2
j
k
,
ω
e
-
R
L
j
z
+
R
T
j
A
3
j
k
,
ω
e
R
T
j
z
-
A
4
j
k
,
ω
e
-
R
T
j
z
v
~
~
j
k
,
z
,
ω
=
R
L
j
A
1
j
k
,
ω
e
R
L
j
z
-
A
2
j
k
,
ω
e
-
R
L
j
z
-
i
k
A
3
j
k
,
ω
e
R
T
j
z
+
A
4
j
k
,
ω
e
-
R
T
j
z
σ
~
~
Z
Z
j
k
,
z
,
ω
=
C
1
j
A
1
j
k
,
ω
e
R
L
j
z
+
A
2
j
k
,
ω
e
-
R
L
j
z
+
C
2
j
A
3
j
k
,
ω
e
R
T
j
z
-
A
4
j
k
,
ω
e
-
R
T
j
z
σ
~
~
Z
x
j
k
,
z
,
ω
=
D
1
j
A
1
j
k
,
ω
e
R
L
j
z
-
A
2
j
k
,
ω
e
-
R
L
j
z
+
D
2
j
A
3
j
k
,
ω
e
R
T
j
z
+
A
4
j
k
,
ω
e
-
R
T
j
z
,
where
(14)
C
1
j
=
λ
^
~
j
+
2
μ
^
~
j
R
L
2
j
-
λ
^
~
j
k
,
C
2
j
=
-
2
i
k
μ
^
~
j
R
T
j
,
D
1
j
=
2
i
k
μ
^
~
j
R
L
j
,
D
2
j
=
μ
^
~
j
k
2
+
R
T
j
2
.
Boundary conditions are set so that the displacements between adjacent layers are equal and stresses between them are balanced. Furthermore, no horizontal rail movement and the vanishing of radiated vibrations as the soil depth increases are assumed.Therefore, replacing the boundary condition of each layer in (13) follows the expression M
·
A
=
q, where M is a coefficient matrix, A is the vector of coefficients to be calculated, and q is the vector of loads acting on the system.Following [15], once the motion and stresses expressions have been obtained in terms of deepness and in frequency-wave number domain, they are returned to the space-time domain by using the inverse Fourier transform. In order to optimize this process the displacements are written in terms of the wave number domain and then the expression of the inverse Fourier transform is converted into an addition following [14].The accelerations in each layer are obtained by differentiating twice, with respect to time, the displacement expressions from the inverse Fourier transform.Total accelerations generated and transmitted to the surrounding ground are obtained through superposition of quasistatic and dynamic overloads.In order to provide reliability to the model, a measurement camping was carried out as aforementioned. Data, obtained by triaxial accelerometers FastTracer Sequoia, have been processed and compared with those calculated in the model. After calibrating the damping parameters of the layers, the result of comparison between model and real data is shown in Figure3.Figure 3Figure3 shows the ability of the model to represent the peaks of vibrations and clearly reproduce the effect of passing passenger cars and their bogies through the stretch of the track. However, as shown in Figure 3, measured data (green) is much noisier than the modeled one (red). These noisier accelerogram recordings may be due to the numerous factors intervening in the real vibratory phenomenon such as rails and wheels imperfections. In contrast, only few harmonic loads have been considered in the model to simulate these irregularities. Amplitudes and angular frequencies of these harmonic loads have been obtained after analyzing the Fourier spectrum of the registered data, taking their more significant values. To more accurate results, a larger number of harmonics might be considered, with the drawback of an increased computational time.It must be highlighted that, due to the typology of track studied, it was not possible to set the accelerometers in the rail, so they were placed next to the elastomeric material where the rail was housed. Then, the data registered with the accelerometers were influenced by the presence of this elastomeric material.
## 3. Analysis of Corrugation
Simulation and analysis of the effect of corrugation in the model presented in the previous section will be addressed. The procedure will be as follows: dynamic overloads caused by the presence of corrugation on the rail will be calculated by using an auxiliary quarter car model and then the influence in dynamic overloads of parameters which define rail irregularities will be discussed.Dynamic overloads generate an increase of vibrations and wear, with the first one being the objective of this research. Thus, overloads will feed the model described in Section2 as harmonic forces in order to obtain the accelerations generated by rail irregularities.
### 3.1. Quarter Car Model
The vehicle can be modeled in different ways depending on the number of degrees of freedom given to the system: it can range from hundreds of degrees of freedom allowed by commercial multibody systems (MBS) to systems with a single degree of freedom constituted by a mass attached to the track by a spring.Between both extreme cases, the following can be found: (i) the quarter car model, which will be presented below; (ii) the half car system, it takes into account the sprung masses, the semisprung masses, and the unsprung masses; and (iii) the full car models, these allow us to take into account not only the displacements of masses but also their rotation with respect to each axis.Nevertheless, from the point of view of the main model and the fact that the loads introduced only have a vertical component, using a full bogie model would be an unnecessary computational expense. Moreover, [18] experimentally demonstrated that the influence on the dynamic stresses of the sprung and semisprung masses is negligible compared to the unsprung masses.Therefore, to calculate the dynamic overloads generated by corrugation, a quarter car system will be implemented using MATLAB software. In this model, the masses of the vehicle are discomposed in sprung and unsprung masses. The compatibility of strengths and displacements between both masses are solved by a spring and a damping element. Meanwhile, the strength transmission between the unsprung masses and the rail is performed by an equivalent spring, which takes into account not only the stiffness of the rail-wheel Hertzian contact but also the stiffness of the underlying track.The expressions governing the behavior of the quarter car model are as follows:(15)
m
2
x
2
′′
+
k
2
(
x
2
-
x
1
)
+
c
2
(
x
2
′
-
x
1
′
)
=
0
,
m
1
x
1
′′
-
c
2
x
2
′
+
c
2
x
1
′
-
k
2
x
2
+
k
2
+
k
1
x
1
-
k
1
z
=
0
,
where: m
1: unsprung mass per wheel, k
1: contact stiffness, m
2: sprung mass per wheel, k
2: primary stiffness, c
2: primary damping, x
i: displacement of the ith mass, x
i
′: velocity of the ith mass, and x
i
′′: acceleration of the ith mass.In Figure4, a quarter car model sketch can be seen.Figure 4In Table2 the values for the mass, stiffness, and damping are shown.Table 2
Quarter car model values
m
1 (kg)
500
k
1 (N/m)
32,000,000
m
2 (kg)
4,000
k
2 (N/m)
501,745
c
2 (N⋅s/m)
875Problem resolution is performed by the Laplace transference function and, once the accelerations of both masses have been obtained, dynamic overloads are calculated as follows:(16)
F
dyn
=
m
1
x
1
′′
+
m
2
x
2
′′
.
### 3.2. Sensitivity Analysis
Real rail profiles may be compared to a sum of sinusoids of different amplitudes and wavelengths. Therefore, in order to analyze the effect of a particular corrugation phenomenon, the profile of the affected track is modeled as a sinusoidal function, which is defined by wear amplitude and wavelength. Furthermore, the speed of the train in service is needed to be taken into account due to the dynamic performance of the analysis. When studying the influence of these parameters on the dynamic overloads, an amplitudeA = 0.25 mm, a wavelength λ = 0.5 m, and a speed V = 50 km/h are set. Then, with two of these parameters being fixed, the third one will be modified in order to analyze its influence on dynamic overloads.It must be highlighted that overload values given for each amplitude, speed, and wavelength correspond to the maximum absolute value of the stationary part of the overload function. The reason for this choice is to consider the most unfavorable case from the point of view of track design, maintenance, and security.Figure5 shows the influence of the speed of the tram on dynamic overloads, being the amplitude and wavelength of corrugation: A = 0.25 mm and λ = 0.5 m. From this analysis, it can be affirmed that dynamic overloads grow when increasing the speed of the vehicle.Figure 5On the other hand, the influence of wavelength on dynamic overloads, beingA = 0.25 mm and V = 50 km/h, is shown in Figure 6. In this graph, the peak obtained when the wavelength is about 0.1 m must be highlighted. Following [19], natural frequencies of the system are calculated as the root of the eigenvalues of
(17)
k
1
+
k
2
m
1
-
k
2
m
1
-
k
2
m
2
k
2
m
2
.
Then, the natural frequencies are 894.9302 rad/s and 9.4815 rad/s, the wavelength being associated with first natural frequency: λ = 0.0975 m, which corresponds to the wavelength estimated from Figure 6. Then, it can be said that for this wavelength—being the speed of the vehicle and train and track features constants—a resonance phenomenon will appear.Figure 6From Figure7, it can be noticed that, far from those wavelengths affected by the resonance phenomenon, dynamic overloads decrease when the wavelength of the irregularity increases. That is, the farther the distance between two consecutive irregularities, the lower the forces transmitted to the track.Figure 7Figure8 shows the influence of wear amplitude on dynamic overloads, being λ = 0.5 m and V = 50 km/h. This leads us to affirm that the higher the amplitude, the greater the overload. Furthermore, it must be noticed that overloads and corrugation amplitude are linearly related.Figure 8Taking into account the strong nonlinear behavior of the vehicle-track system, the linear behavior of the amplitude of corrugation must be explained. In order to assess the validity of the results obtained with the quarter car model, a multibody model has been implemented with the VAMPIRE commercial software and the influence of the amplitude has been studied. The results are exposed in Figure9.Figure 9From Figure9, two different behaviours of the relation amplitude-dynamic overloads are shown. On one hand, when the amplitude of corrugation is lower than 1 mm, the overloads generated by this pathology show a quasilinear behaviour for both models. On the other hand, when the amplitude exceeds this value a nonlinear behaviour can be appreciated for the multibody model but its behaviour remains quasilinear when dynamic overloads are calculated with the quarter car model.Thus, it can be concluded that the quarter car model described in this paper only is able to be used when the amplitude of the defect considered is lower than 1 mm.In conclusion, since it is not feasible that amplitudes higher than 1 mm appear in a tram track as the one proposed in this study and the quarter car model presents the advantage of its simplicity when comparing with the multibody model, the use of this model has been justified. Nevertheless, before using this model for other types of railroads where higher amplitudes may be reached a preliminary study must be carried out.
### 3.3. Definition of Different Scenarios
Below, a simulation of different scenarios will be performed. Irregularities simulated by the model will be added to the imperfections already present in the calibrated track. The values used in these simulations are shown in Table3.Table 3
V (km/h)
35
50
80
A (mm)
0.1
0.25
0.5
λ (m)
0.3
0.5
1Note that in the model a punctual contact between wheels and rails is assumed. Therefore, when simulating wear of a very short wavelength and high amplitude it would be necessary to check the veracity of this hypothesis. Thus, it is established that the curvature of the sinusoid representing the rail must be greater than wheel curvature.Wheel curvature is1
/
R
w.The curvature of the sinusoid representing the rail can be expressed asy
=
-
A
sin
(
k
x
) so: y
=
-
A
·
sin
(
2
π
x
/
λ
). By differentiating twice with respect to the position:
(18)
y
′′
=
4
π
2
λ
2
·
A
·
sin
2
π
x
λ
.
So the maximum curvature of the rail is (
4
π
2
/
λ
2
)
A m−1.Relating both curvatures,(19)
1
R
w
≤
4
π
2
λ
2
A
.
Then, the wavelength of the irregularity considered must satisfy
(20)
λ
≥
2
π
A
R
w
.
After verifying that all of them satisfy (20), the scenarios are discussed in Table 4.Table 4
Scenario
V (km/h)
A (mm)
λ (m)
F
din
max
(N)
a
max
(m/s2)
Case 1
35
0.25
0.5
1.7783
e
+
04
2.44511
Case 2
50
0.25
0.5
3.8228
e
+
04
4.77442
Case 3
80
0.25
0.5
1.0621
e
+
05
12.3465
Case 4
50
0.1
0.5
1.5291
e
+
04
4.62642
Case 5
50
0.5
0.5
7.6456
e
+
04
4.92609
Case 6
50
0.25
0.3
1.1547
e
+
05
5.69606
Case 7
50
0.25
1
8.4703
e
+
03
4.01358From the results for the dynamic overloads, the behavior predicted by earlier Figures5–8 is confirmed: high speed, high wavelengths, and low amplitudes generate higher values for dynamic overloads.Furthermore, in general, the higher the dynamic overload generated by corrugation, the greater the maximum accelerations generated and transmitted to the track. However, this affirmation is not satisfied in all cases (see cases 1 and 7). As discussed in Section2, this is due to the fact that the whole behavior of the system is determined by not only dynamic overloads, but also the quasistatic ones, which depend on speed. Thus, although in case 7 lower dynamic overloads have been obtained compared to case 1, the influence of the vehicle speed causes the greater accelerations generated in case 7.
## 3.1. Quarter Car Model
The vehicle can be modeled in different ways depending on the number of degrees of freedom given to the system: it can range from hundreds of degrees of freedom allowed by commercial multibody systems (MBS) to systems with a single degree of freedom constituted by a mass attached to the track by a spring.Between both extreme cases, the following can be found: (i) the quarter car model, which will be presented below; (ii) the half car system, it takes into account the sprung masses, the semisprung masses, and the unsprung masses; and (iii) the full car models, these allow us to take into account not only the displacements of masses but also their rotation with respect to each axis.Nevertheless, from the point of view of the main model and the fact that the loads introduced only have a vertical component, using a full bogie model would be an unnecessary computational expense. Moreover, [18] experimentally demonstrated that the influence on the dynamic stresses of the sprung and semisprung masses is negligible compared to the unsprung masses.Therefore, to calculate the dynamic overloads generated by corrugation, a quarter car system will be implemented using MATLAB software. In this model, the masses of the vehicle are discomposed in sprung and unsprung masses. The compatibility of strengths and displacements between both masses are solved by a spring and a damping element. Meanwhile, the strength transmission between the unsprung masses and the rail is performed by an equivalent spring, which takes into account not only the stiffness of the rail-wheel Hertzian contact but also the stiffness of the underlying track.The expressions governing the behavior of the quarter car model are as follows:(15)
m
2
x
2
′′
+
k
2
(
x
2
-
x
1
)
+
c
2
(
x
2
′
-
x
1
′
)
=
0
,
m
1
x
1
′′
-
c
2
x
2
′
+
c
2
x
1
′
-
k
2
x
2
+
k
2
+
k
1
x
1
-
k
1
z
=
0
,
where: m
1: unsprung mass per wheel, k
1: contact stiffness, m
2: sprung mass per wheel, k
2: primary stiffness, c
2: primary damping, x
i: displacement of the ith mass, x
i
′: velocity of the ith mass, and x
i
′′: acceleration of the ith mass.In Figure4, a quarter car model sketch can be seen.Figure 4In Table2 the values for the mass, stiffness, and damping are shown.Table 2
Quarter car model values
m
1 (kg)
500
k
1 (N/m)
32,000,000
m
2 (kg)
4,000
k
2 (N/m)
501,745
c
2 (N⋅s/m)
875Problem resolution is performed by the Laplace transference function and, once the accelerations of both masses have been obtained, dynamic overloads are calculated as follows:(16)
F
dyn
=
m
1
x
1
′′
+
m
2
x
2
′′
.
## 3.2. Sensitivity Analysis
Real rail profiles may be compared to a sum of sinusoids of different amplitudes and wavelengths. Therefore, in order to analyze the effect of a particular corrugation phenomenon, the profile of the affected track is modeled as a sinusoidal function, which is defined by wear amplitude and wavelength. Furthermore, the speed of the train in service is needed to be taken into account due to the dynamic performance of the analysis. When studying the influence of these parameters on the dynamic overloads, an amplitudeA = 0.25 mm, a wavelength λ = 0.5 m, and a speed V = 50 km/h are set. Then, with two of these parameters being fixed, the third one will be modified in order to analyze its influence on dynamic overloads.It must be highlighted that overload values given for each amplitude, speed, and wavelength correspond to the maximum absolute value of the stationary part of the overload function. The reason for this choice is to consider the most unfavorable case from the point of view of track design, maintenance, and security.Figure5 shows the influence of the speed of the tram on dynamic overloads, being the amplitude and wavelength of corrugation: A = 0.25 mm and λ = 0.5 m. From this analysis, it can be affirmed that dynamic overloads grow when increasing the speed of the vehicle.Figure 5On the other hand, the influence of wavelength on dynamic overloads, beingA = 0.25 mm and V = 50 km/h, is shown in Figure 6. In this graph, the peak obtained when the wavelength is about 0.1 m must be highlighted. Following [19], natural frequencies of the system are calculated as the root of the eigenvalues of
(17)
k
1
+
k
2
m
1
-
k
2
m
1
-
k
2
m
2
k
2
m
2
.
Then, the natural frequencies are 894.9302 rad/s and 9.4815 rad/s, the wavelength being associated with first natural frequency: λ = 0.0975 m, which corresponds to the wavelength estimated from Figure 6. Then, it can be said that for this wavelength—being the speed of the vehicle and train and track features constants—a resonance phenomenon will appear.Figure 6From Figure7, it can be noticed that, far from those wavelengths affected by the resonance phenomenon, dynamic overloads decrease when the wavelength of the irregularity increases. That is, the farther the distance between two consecutive irregularities, the lower the forces transmitted to the track.Figure 7Figure8 shows the influence of wear amplitude on dynamic overloads, being λ = 0.5 m and V = 50 km/h. This leads us to affirm that the higher the amplitude, the greater the overload. Furthermore, it must be noticed that overloads and corrugation amplitude are linearly related.Figure 8Taking into account the strong nonlinear behavior of the vehicle-track system, the linear behavior of the amplitude of corrugation must be explained. In order to assess the validity of the results obtained with the quarter car model, a multibody model has been implemented with the VAMPIRE commercial software and the influence of the amplitude has been studied. The results are exposed in Figure9.Figure 9From Figure9, two different behaviours of the relation amplitude-dynamic overloads are shown. On one hand, when the amplitude of corrugation is lower than 1 mm, the overloads generated by this pathology show a quasilinear behaviour for both models. On the other hand, when the amplitude exceeds this value a nonlinear behaviour can be appreciated for the multibody model but its behaviour remains quasilinear when dynamic overloads are calculated with the quarter car model.Thus, it can be concluded that the quarter car model described in this paper only is able to be used when the amplitude of the defect considered is lower than 1 mm.In conclusion, since it is not feasible that amplitudes higher than 1 mm appear in a tram track as the one proposed in this study and the quarter car model presents the advantage of its simplicity when comparing with the multibody model, the use of this model has been justified. Nevertheless, before using this model for other types of railroads where higher amplitudes may be reached a preliminary study must be carried out.
## 3.3. Definition of Different Scenarios
Below, a simulation of different scenarios will be performed. Irregularities simulated by the model will be added to the imperfections already present in the calibrated track. The values used in these simulations are shown in Table3.Table 3
V (km/h)
35
50
80
A (mm)
0.1
0.25
0.5
λ (m)
0.3
0.5
1Note that in the model a punctual contact between wheels and rails is assumed. Therefore, when simulating wear of a very short wavelength and high amplitude it would be necessary to check the veracity of this hypothesis. Thus, it is established that the curvature of the sinusoid representing the rail must be greater than wheel curvature.Wheel curvature is1
/
R
w.The curvature of the sinusoid representing the rail can be expressed asy
=
-
A
sin
(
k
x
) so: y
=
-
A
·
sin
(
2
π
x
/
λ
). By differentiating twice with respect to the position:
(18)
y
′′
=
4
π
2
λ
2
·
A
·
sin
2
π
x
λ
.
So the maximum curvature of the rail is (
4
π
2
/
λ
2
)
A m−1.Relating both curvatures,(19)
1
R
w
≤
4
π
2
λ
2
A
.
Then, the wavelength of the irregularity considered must satisfy
(20)
λ
≥
2
π
A
R
w
.
After verifying that all of them satisfy (20), the scenarios are discussed in Table 4.Table 4
Scenario
V (km/h)
A (mm)
λ (m)
F
din
max
(N)
a
max
(m/s2)
Case 1
35
0.25
0.5
1.7783
e
+
04
2.44511
Case 2
50
0.25
0.5
3.8228
e
+
04
4.77442
Case 3
80
0.25
0.5
1.0621
e
+
05
12.3465
Case 4
50
0.1
0.5
1.5291
e
+
04
4.62642
Case 5
50
0.5
0.5
7.6456
e
+
04
4.92609
Case 6
50
0.25
0.3
1.1547
e
+
05
5.69606
Case 7
50
0.25
1
8.4703
e
+
03
4.01358From the results for the dynamic overloads, the behavior predicted by earlier Figures5–8 is confirmed: high speed, high wavelengths, and low amplitudes generate higher values for dynamic overloads.Furthermore, in general, the higher the dynamic overload generated by corrugation, the greater the maximum accelerations generated and transmitted to the track. However, this affirmation is not satisfied in all cases (see cases 1 and 7). As discussed in Section2, this is due to the fact that the whole behavior of the system is determined by not only dynamic overloads, but also the quasistatic ones, which depend on speed. Thus, although in case 7 lower dynamic overloads have been obtained compared to case 1, the influence of the vehicle speed causes the greater accelerations generated in case 7.
## 4. Conclusions
The aim of this paper was to implement a model able to reproduce the vibratory behavior of a tram railroad, where a measurement campaign was conducted. Then, after confirming its correct behavior, a simulation of corrugation in that track was performed.For this purpose, an analytical model has been implemented in the Mathematica software based on that developed by [16]. Subsequently, a morphological calibration was carried out.An auxiliary quarter car model was implemented to evaluate the dynamic overloads generated by corrugation, and the following conclusions were obtained: the greater the speed of the vehicle and the amplitude of the defect, the greater the dynamic overloads transmitted to the track. On the other hand, the higher corrugation wavelength, the lower overloads generated.Dynamic overloads obtained as stated before feed the main model to obtain the vibrations generated by rail corrugation. From this analysis, it may be concluded that the overloads transmitted to the track due to corrugation are highly influential in the maximum acceleration generated by the vehicle, but also the effect of vehicle speed is very significant.The model described in this paper may be used as an aid to maintenance of railway infrastructure. Overall, for a given stretch of track, tram vehicles usually travel at the same speed. Moreover, according to [2] given the main features of a stretch of track and of those vehicles traveling through it, wavelength of rail corrugation may be predicted. Then, being the maximum allowable values for vibrations fixed for a particular stretch of track, model can predict from which corrugation amplitude maintenance operations are needed.
---
*Source: 290164-2015-02-04.xml* | 2015 |
# Preparation of Bioactive Titanium Surfaces via Fluoride and Fibronectin Retention
**Authors:** Carlos Nelson Elias; Patricia Abdo Gravina; Costa e Silva Filho; Pedro Augusto de Paula Nascente
**Journal:** International Journal of Biomaterials
(2012)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2012/290179
---
## Abstract
Statement of Problem. The chemical or topographic modification of the dental implant surface can affect bone healing, promote accelerated osteogenesis, and increase bone-implant contact and bonding strength. Objective. In this work, the effects of dental implant surface treatment and fibronectin adsorption on the adhesion of osteoblasts were analyzed. Materials and Methods. Two titanium dental implants (Porous-acid etching and PorousNano-acid etching followed by fluoride ion modification) were characterized by high-resolution scanning electron microscopy, atomic force microscopy, and X-ray diffraction before and after the incorporation of human plasma fibronectin (FN). The objective was to investigate the biofunctionalization of these surfaces and examine their effects on the interaction with osteoblastic cells. Results. The evaluation techniques used showed that the Porous and PorousNano implants have similar microstructural characteristics. Spectrophotometry demonstrated similar levels of fibronectin adsorption on both surfaces (80%). The association indexes of osteoblastic cells in FN-treated samples were significantly higher than those in samples without FN. The radioactivity values associated with the same samples, expressed as counts per minute (cpm), suggested that FN incorporation is an important determinant of the in vitro cytocompatibility of the surfaces. Conclusion. The preparation of bioactive titanium surfaces via fluoride and FN retention proved to be a useful treatment to optimize and to accelerate the osseointegration process for dental implants.
---
## Body
## 1. Introduction
The phenomenon of endosseous implant osseointegration, conceptualized by Branemark as the “direct, structural and functional link between the living and orderly bone and the surface of an implant subjected to functional loads” [1], is fundamental to the success of dental implant applications. Commercially pure titanium (cp Ti) is the main material used for this purpose because it has good biocompatibility and adequate mechanical strength. Ti exposed to oxidizing agents spontaneously forms a 10-100 Å thick titanium oxide layer. This layer is stable in most media, especially under physiological conditions, and, surgically, it shows no change in thickness or corrosion. This ensures implant-bone tissue interaction and osseointegration [2]. The reactions of the tissue host with the biomaterial are determined by the surface properties of the biomaterial. The dental implant surface treatment should induce the differentiation of the desired cells [3]. Surface treatments of available implants promote changes in the mechanical, microstructural, and physical properties, as well as the wettability, energy, chemical composition, and density of chemical groups or molecules on the surface [2, 4].This paper shows that the bone-implant interface strength is greater in dental implants with rough surfaces than in those with smooth surfaces [5, 6]. Treatments to increase the surface area for fibrin adhesion encourages implant adhesion. The presence of these surfaces also increases platelet activation, which produces large gradients of cytokines and growth factors through which leukocytes and osteogenic cells can penetrate the healing site [7]. Titanium surfaces coated with proteins can influence host reactions and thus enhance tissue integration [4]. Fibronectin is a major adhesion protein in the extracellular membrane, and it is important for cell adhesion, migration, proliferation, differentiation, and survival because it facilitates focal contacts with the receptors.Appropriate changes in dental implant surface roughness can produce better anchoring strength and mechanical locking in the early stages of osseointegration [2, 6]. Moreover, surfaces with different microtopographies provide a larger area for fibrin adhesion, potentiate platelet activation, and favorably affect local angiogenesis and cellular functions including migration, alignment, orientation, attachment, and differentiation [5, 6].Johansson et al. [8] observed that surfaces treated with fluoride are smoother than sandblasted surfaces but that fluoride-treated surfaces showed higher calcium-phosphorus binding capacity, which could indicate an increased ability of the surface to react with calcified tissues and promote integration between bone and implant. According to Ellingsen and Lyngstadaas [9], in vitro tests have shown that titanium fluoride treatments have a greater capacity for the nucleation of phosphate crystals than sandblasted Ti implants. In vivo fluoride ion-modified implants have generally proven superior to sandblasted surfaces in terms of osseointegration, ultimately increasing the removal torques.Fibronectin is a major extracellular matrix protein that is known to promote cell attachment and spreading, differentiation, and phagocytosis. It is a dimeric glycoprotein found in all vertebrates in two basic forms: soluble (plasma and other fluids) and insoluble (extracellular matrix of various tissues). It has a molecular weight between 440 and 500 kDa. Disulfide bridges link one subunit to another via sites near the carboxy termini of each subunit. The fibronectin protein has folds that lead to structural remodeling and various conformations according to the medium [10–12].Fibronectin (FN) functions in cell adhesion, migration, survival, proliferation, and differentiation as well as tissue organization. The FN molecule can interact with other biomolecules, such as collagen, proteoglycan, heparin, hyaluronic acid, fibrin/fibrinogen, plasmin, gangliosides, complement components, and also integral proteins of cell plasma membrane-integrins, as well as with itself [13].Menezes [10] conducted a study to assess the interaction of human osteoblasts with films of human plasma fibronectin prepared under different pH conditions. The results showed no quantitative differences in the interaction of human osteoblastic cells (HOB) to different coatings, but qualitative differences were observed; osteoblasts adhered to each of the substrates in very different ways. The largest areas of cells adhesion were observed for substrates preincubated at 4.5 pH.Petrie et al. [14] conducted a clinical study to evaluate the effects of specific bioactive coatings on the healing of bone tissue and the osseointegration of titanium dental implants. The author showed that surfaces containing a FN fragment for the integrin α5β1 (FNIII7–10) increase osteoblastic differentiation and optimize tissue formation and functional integration compared with untreated surfaces or surfaces containing only the RGD sequence.The purpose of this study was to evaluate the effect of the fluoride treatment of cp titanium samples on the adhesion and proliferation of osteoblastic cells on surfaces with and without fibronectin coating.
## 2. Materials and Methods
### 2.1. Samples
Implants and discs of grade 4 machined cp Ti were provided by Conexão Sistemas de Prótese (Arujá, SP, Brazil). Samples were submitted to surface treatment and divided into four groups:Porous: samples treated in acidic solutions containing HNO3, H2SO4, and HCl (surface treatment similar to Porous implants available from Conexão Sistemas de Prótese);PorousNano: treatment similar to Group 1 followed by fluoride ion modification by immersion for one hour in a solution containing fluorine ions;Porous-FN: treatment similar to Group 1 with FN incorporation;PorousNano-FN: treatment similar to Group 2 with FN incorporation.After treatments, samples from the Porous and PorousNano groups were washed with distilled water and absolute alcohol, dried in oven at 70°C for two hours, and packed and sterilized by gamma irradiation (25 kGy).
### 2.2. Surface Characterization
To characterize the surface morphology and identify differences in samples submitted to treatments with acids and/or fluorides, the samples were characterized by a high-resolution scanning electron microscopy (FEG/EDS, Philips XL30FEG). The results were complemented by analysis with an MFP-3D atomic force microscope (Asylum Research, CA, USA) operating in contact at room temperature mode. The cantilevers used were V shaped, NP-S model (Veeco Probes, CA, USA) with an 0.08 N/m spring constant, and calibrated using the thermal noise method. To reduce damage to samples and reduce noise, images were acquired using low-frequency scanning (1.0 Hz) with256×256 pixel resolution. Image processing was performed in the program IGOR PRO (WaveMetrics, Portland, OR, USA) using a MFP-3D platform developed by Asylum Research.
### 2.3. Identification of Crystalline Phases
An X-ray diffractometer was used to identify crystalline phases on discs. X-ray diffraction for the analysis of thin films (grazing incidence technique) was conducted at 40 kV and 30 mA. A copper anode was used (Cu-Kα=1,542Å) with an RU 200B model Rigaku generator and 0.02° step/minute.
### 2.4. Fibronectin Incorporation
Human serum fibronectin (Sigma-Aldrich Co., São Paulo, Brazil)) was diluted to 10 g/mL, pH 4.5 in previously filtered 20 mM sodium acetate (Reagen Laboratory Products, Paraná, Brazil) buffer solution. NaCl was added to the solution to maintain the medium’s ionic strength between 0.145 and 0.150 mol·dm−3.Samples from the Porous and PorousNano groups were coated with fibronectin at room temperature for 2 hours. Substrates with FN were washed with PBS (phosphate [0.01 M] buffered saline [0.15 M], pH 7.2) to remove nonadsorbed molecules. Then, the adsorbed molecules were detached using 0.1% trypsin and PBS. One to two minutes later, the excess was removed, and the resulting solution was collected and analyzed with a Spectrum 22PC spectrophotometer to quantify the adsorbed molecules. Spectrophotometry was also used to determine the FN’s absorbance on both surfaces (protein concentration in solutions that absorb radiation). Negative (PBS) and positive (FN suspension 100μg/mL) controls were performed. The wavelength used was 550 nm (protein reading).
### 2.5. Culture of Osteoblasts
Cells were maintained in polystyrene bottles containing DMEM (Dulbecco’s Modified Eagle Medium) culture medium with low glucose, 10% fetal bovine serum (Soromed Industry, São Paulo, Brazil), and 1% essential amino acids solution (Minimum Essential amino acid solution 100x, Sigma-Aldrich) ascorbic acid (0.15 gL−1, Sigma-Aldrich) buffered with 10 mM HEPES (Sigma-Aldrich) and 14.3 mM NaHCO3 (Reagen). The pH of the medium was adjusted to 7.2. Cultures were incubated at 37°C in 5% CO2 atmosphere. The enzymatic cell detachment technique was used to transpose cells from the stock culture flask to substrates for the adhesion assay. Confluent cultures were treated with 0.2% trypsin (Difco Microbiology Co., USA) and 0.02% EDTA (Sigma-Aldrich) in saline solution (0.8% NaCl [Reagan], 0.01% KCl [Sigma-Aldrich]; 0.29% NaHPO4·7H2O [Reagan], and 0.02% KH2PO4 [Sigma-Aldrich] in H2O) for 5 minutes at 37°C. Then, the detached cells were collected, and the proteolytic action of trypsin was inhibited by adding fetal calf serum to the solution. The suspension was then centrifuged at 1500 rpm at 22°C, and the pelleted cells were resuspended in culture medium without fetal calf serum. The cell concentration/density of the suspension was estimated by counting in a hematimetric Neubauer chamber.
### 2.6. Interaction of Cells with Samples
After the cell concentration of the suspension was measured in a hematimetric chamber, 106 cells/mL were taken and allowed to interact with the samples with and without FN coating, which totaled four groups. After an hour of interaction, the supernatants were discarded, and the cells that were attached (adsorbed and adhered) to surfaces were washed with PBS and fixed using glutaraldehyde (2.5% in PBS). Glutaraldehyde was used as fixative to avoid damaging cell integrity (glutaraldehyde contains two functional groups that link two proteins). This procedure was adopted because the use of formaldehyde (which has only one functional group) as a fixative profoundly deformed the cells. After fixation, cells were trypsinized and counted in a hematimetric Neubauer chamber.
### 2.7. Surface Radioactivity
Human osteoblastic cells (HOBs) were cultivated to evaluate cell adhesion and proliferation by liquid scintillation counting. Cells from confluent HOB cultures were detached with trypsin, washed, and counted in a hematimetric chamber. Then, the culture was resuspended in DMEM containing serum and [3H]-thymidine (1143 cpm). After allowing incorporation for a period of 12 hours, the confluent cells were again detached and washed in DMEM without serum, and a liquid scintillator (Beckman, Rack III) was used to evaluate the radioactivity associated with cells. The resulting values were expressed as counts per minute (cpm). These cells, incorporating [3H]-thymidine, were associated with different surfaces (Porous, Porous-FN, PorousNano, and PorousNano-FN) for a period of 3 hours, and counts were carried out after 1, 2, and 3 hours. This cell behavior evaluation method allows accurate reproduction, favoring the future applicability of FN incorporation onto surfaces of dental implants.
## 2.1. Samples
Implants and discs of grade 4 machined cp Ti were provided by Conexão Sistemas de Prótese (Arujá, SP, Brazil). Samples were submitted to surface treatment and divided into four groups:Porous: samples treated in acidic solutions containing HNO3, H2SO4, and HCl (surface treatment similar to Porous implants available from Conexão Sistemas de Prótese);PorousNano: treatment similar to Group 1 followed by fluoride ion modification by immersion for one hour in a solution containing fluorine ions;Porous-FN: treatment similar to Group 1 with FN incorporation;PorousNano-FN: treatment similar to Group 2 with FN incorporation.After treatments, samples from the Porous and PorousNano groups were washed with distilled water and absolute alcohol, dried in oven at 70°C for two hours, and packed and sterilized by gamma irradiation (25 kGy).
## 2.2. Surface Characterization
To characterize the surface morphology and identify differences in samples submitted to treatments with acids and/or fluorides, the samples were characterized by a high-resolution scanning electron microscopy (FEG/EDS, Philips XL30FEG). The results were complemented by analysis with an MFP-3D atomic force microscope (Asylum Research, CA, USA) operating in contact at room temperature mode. The cantilevers used were V shaped, NP-S model (Veeco Probes, CA, USA) with an 0.08 N/m spring constant, and calibrated using the thermal noise method. To reduce damage to samples and reduce noise, images were acquired using low-frequency scanning (1.0 Hz) with256×256 pixel resolution. Image processing was performed in the program IGOR PRO (WaveMetrics, Portland, OR, USA) using a MFP-3D platform developed by Asylum Research.
## 2.3. Identification of Crystalline Phases
An X-ray diffractometer was used to identify crystalline phases on discs. X-ray diffraction for the analysis of thin films (grazing incidence technique) was conducted at 40 kV and 30 mA. A copper anode was used (Cu-Kα=1,542Å) with an RU 200B model Rigaku generator and 0.02° step/minute.
## 2.4. Fibronectin Incorporation
Human serum fibronectin (Sigma-Aldrich Co., São Paulo, Brazil)) was diluted to 10 g/mL, pH 4.5 in previously filtered 20 mM sodium acetate (Reagen Laboratory Products, Paraná, Brazil) buffer solution. NaCl was added to the solution to maintain the medium’s ionic strength between 0.145 and 0.150 mol·dm−3.Samples from the Porous and PorousNano groups were coated with fibronectin at room temperature for 2 hours. Substrates with FN were washed with PBS (phosphate [0.01 M] buffered saline [0.15 M], pH 7.2) to remove nonadsorbed molecules. Then, the adsorbed molecules were detached using 0.1% trypsin and PBS. One to two minutes later, the excess was removed, and the resulting solution was collected and analyzed with a Spectrum 22PC spectrophotometer to quantify the adsorbed molecules. Spectrophotometry was also used to determine the FN’s absorbance on both surfaces (protein concentration in solutions that absorb radiation). Negative (PBS) and positive (FN suspension 100μg/mL) controls were performed. The wavelength used was 550 nm (protein reading).
## 2.5. Culture of Osteoblasts
Cells were maintained in polystyrene bottles containing DMEM (Dulbecco’s Modified Eagle Medium) culture medium with low glucose, 10% fetal bovine serum (Soromed Industry, São Paulo, Brazil), and 1% essential amino acids solution (Minimum Essential amino acid solution 100x, Sigma-Aldrich) ascorbic acid (0.15 gL−1, Sigma-Aldrich) buffered with 10 mM HEPES (Sigma-Aldrich) and 14.3 mM NaHCO3 (Reagen). The pH of the medium was adjusted to 7.2. Cultures were incubated at 37°C in 5% CO2 atmosphere. The enzymatic cell detachment technique was used to transpose cells from the stock culture flask to substrates for the adhesion assay. Confluent cultures were treated with 0.2% trypsin (Difco Microbiology Co., USA) and 0.02% EDTA (Sigma-Aldrich) in saline solution (0.8% NaCl [Reagan], 0.01% KCl [Sigma-Aldrich]; 0.29% NaHPO4·7H2O [Reagan], and 0.02% KH2PO4 [Sigma-Aldrich] in H2O) for 5 minutes at 37°C. Then, the detached cells were collected, and the proteolytic action of trypsin was inhibited by adding fetal calf serum to the solution. The suspension was then centrifuged at 1500 rpm at 22°C, and the pelleted cells were resuspended in culture medium without fetal calf serum. The cell concentration/density of the suspension was estimated by counting in a hematimetric Neubauer chamber.
## 2.6. Interaction of Cells with Samples
After the cell concentration of the suspension was measured in a hematimetric chamber, 106 cells/mL were taken and allowed to interact with the samples with and without FN coating, which totaled four groups. After an hour of interaction, the supernatants were discarded, and the cells that were attached (adsorbed and adhered) to surfaces were washed with PBS and fixed using glutaraldehyde (2.5% in PBS). Glutaraldehyde was used as fixative to avoid damaging cell integrity (glutaraldehyde contains two functional groups that link two proteins). This procedure was adopted because the use of formaldehyde (which has only one functional group) as a fixative profoundly deformed the cells. After fixation, cells were trypsinized and counted in a hematimetric Neubauer chamber.
## 2.7. Surface Radioactivity
Human osteoblastic cells (HOBs) were cultivated to evaluate cell adhesion and proliferation by liquid scintillation counting. Cells from confluent HOB cultures were detached with trypsin, washed, and counted in a hematimetric chamber. Then, the culture was resuspended in DMEM containing serum and [3H]-thymidine (1143 cpm). After allowing incorporation for a period of 12 hours, the confluent cells were again detached and washed in DMEM without serum, and a liquid scintillator (Beckman, Rack III) was used to evaluate the radioactivity associated with cells. The resulting values were expressed as counts per minute (cpm). These cells, incorporating [3H]-thymidine, were associated with different surfaces (Porous, Porous-FN, PorousNano, and PorousNano-FN) for a period of 3 hours, and counts were carried out after 1, 2, and 3 hours. This cell behavior evaluation method allows accurate reproduction, favoring the future applicability of FN incorporation onto surfaces of dental implants.
## 3. Results
### 3.1. Surface Morphology
Figure1 shows Porous and PorousNano titanium surfaces before coating with fibronectin. These surfaces exhibited microcavities with different sizes and sharp edges. Immersion into a solution containing fluoride ions (PorousNano) did not change the microcavity morphology, and the sharp edges persisted. A minor modification caused by immersion is shown in Figure 1(c); some white regions are observed when compared with Figure 1(b). At high magnification (Figure 1(d)), the PorousNano group showed evidence of particle clusters at the surface due to immersion in the solution containing fluoride ions. This is the major ultrastructural characteristic of the PorousNano sample.SEM images of the samples before coating with fibronectin. (a) and (b) Porous samples (acid treatment). (c) and (d) PorousNano samples (acid treatment followed by fluoride ion modification).
(a)
(b)
(c)
(d)Figure2 shows images obtained by atomic force microscopy. In Figure 2(a), the microcavity edges are more flattened but maintain the sharp features that seem to assist or facilitate the adsorption of fibronectin and cells. Figure 2(b) shows the PorousNano sample surface at high magnification, demonstrating that the roughness pattern at the microcavity edges is flattened by immersion treatment in a solution containing fluoride ions.AFM images: (a) Porous and (b) PorousNano.
(a)
(b)The surface roughness of the Porous sample (Figure2(a)) was 1759.7 nm (±204.4 nm), whereas the roughness of the PorousNano surface sample (Figure 2(b)) was 1406.5 nm (±226.9 nm).
### 3.2. Identification of Crystalline Phases
Figure3 shows the X-ray diffraction spectra of the Porous and PorousNano surfaces. Both contain only titanium as the crystalline phase.Figure 3
X-ray diffraction spectra of Porous and PorousNano surfaces.
### 3.3. Incorporation of Fibronectin
Porous and PorousNano titanium surfaces were treated with crystal violet (1% in PBS), and the stain associated with the surfaces was eluted with methanol. Negative (buffer solution) and positive (FN suspension) controls were assessed by spectrophotometry. The absorbance was proportional to the amount of the cells such that more the cells on the surface corresponded to larger absorbance values. Cells treated with PBS measured at 0.326 absorbance units (AU) at 550 nm (reading for proteins). The FN suspension (100μg/mL) measured at 2.992 units. After the FN incorporation in Porous, and PorousNano tablets, both spectrophotometric measurements were 2.473 absorbance units (82.6%) at 550 nm, indicating that the two surfaces exhibit similar behavior with respect to fibronectin incorporation.
### 3.4. Interaction of Cells with Surfaces
A total of 106 human osteoblastic cells/mL were delivered to Porous and PorousNano surfaces, and, after a 1.0 hour interaction, 7.9×104 cells/mL and 2.3×105 cells/mL were associated with the Porous and PorousNano (no protein coating) surfaces, respectively. The combination of cells to both surfaces, with and without the fibronectin incorporation, resulted in different association indices. For comparison, association index values were considered null for samples without FN. After one hour, the association indices values of cells with samples with FN showed increase of 44.7% (±0.8%) and 57.4% (±0.3%) for Porous-FN and PorousNano-FN surfaces, respectively, compared to the same surfaces without FN.The cell-surface interaction index of the PorousNano-FN was approximately 28% higher than that of the Porous-FN.
### 3.5. Surface Radioactivity
After the incorporation of [3H]-thymidine for 12 hours, the radioactivity associated with osteoblast cells was evaluated. Subsequently, 1.8×106 cells/mL, corresponding to 1,100 cpm, were delivered to Porous, Porous-FN, PorousNano, and PorousNano-FN surfaces. The results are shown in Figure 4.Figure 4
Radioactivity associated with osteoblasts on Porous, Porous-FN, PorousNano, and PorousNano-FN surfaces. The resulting values were expressed as counts per minute (cpm).After one hour of interaction, 70% of cells (0.751 cpm) were associated with the PorousNano surface. This number is most likely low because some cells died or were not associated with the sample at the beginning of the process. The number of associated cells increased with interaction time, reaching 0.864 cpm after three hours; that is, there was a 15% increase in the amount of associated cells due to proliferation and cell division.Only 64% of the cells interacting with the Porous surface (0.687 cpm) remained associated after one hour, but this number increased approximately 32% after 3 hours of interaction, reaching 0.905 cpm.On the Porous-FN surface, 90% of cells (0.976 cpm) were associated after 1 hour of interaction. The number of attached cells increased 9% after three hours, reaching 1.064 cpm. For the PorousNano-FN surface, 92% of cells (0.986 cpm) were associated after one hour of interaction, and this number increased by 11.5% over three hours, reaching 1.100 cpm.
## 3.1. Surface Morphology
Figure1 shows Porous and PorousNano titanium surfaces before coating with fibronectin. These surfaces exhibited microcavities with different sizes and sharp edges. Immersion into a solution containing fluoride ions (PorousNano) did not change the microcavity morphology, and the sharp edges persisted. A minor modification caused by immersion is shown in Figure 1(c); some white regions are observed when compared with Figure 1(b). At high magnification (Figure 1(d)), the PorousNano group showed evidence of particle clusters at the surface due to immersion in the solution containing fluoride ions. This is the major ultrastructural characteristic of the PorousNano sample.SEM images of the samples before coating with fibronectin. (a) and (b) Porous samples (acid treatment). (c) and (d) PorousNano samples (acid treatment followed by fluoride ion modification).
(a)
(b)
(c)
(d)Figure2 shows images obtained by atomic force microscopy. In Figure 2(a), the microcavity edges are more flattened but maintain the sharp features that seem to assist or facilitate the adsorption of fibronectin and cells. Figure 2(b) shows the PorousNano sample surface at high magnification, demonstrating that the roughness pattern at the microcavity edges is flattened by immersion treatment in a solution containing fluoride ions.AFM images: (a) Porous and (b) PorousNano.
(a)
(b)The surface roughness of the Porous sample (Figure2(a)) was 1759.7 nm (±204.4 nm), whereas the roughness of the PorousNano surface sample (Figure 2(b)) was 1406.5 nm (±226.9 nm).
## 3.2. Identification of Crystalline Phases
Figure3 shows the X-ray diffraction spectra of the Porous and PorousNano surfaces. Both contain only titanium as the crystalline phase.Figure 3
X-ray diffraction spectra of Porous and PorousNano surfaces.
## 3.3. Incorporation of Fibronectin
Porous and PorousNano titanium surfaces were treated with crystal violet (1% in PBS), and the stain associated with the surfaces was eluted with methanol. Negative (buffer solution) and positive (FN suspension) controls were assessed by spectrophotometry. The absorbance was proportional to the amount of the cells such that more the cells on the surface corresponded to larger absorbance values. Cells treated with PBS measured at 0.326 absorbance units (AU) at 550 nm (reading for proteins). The FN suspension (100μg/mL) measured at 2.992 units. After the FN incorporation in Porous, and PorousNano tablets, both spectrophotometric measurements were 2.473 absorbance units (82.6%) at 550 nm, indicating that the two surfaces exhibit similar behavior with respect to fibronectin incorporation.
## 3.4. Interaction of Cells with Surfaces
A total of 106 human osteoblastic cells/mL were delivered to Porous and PorousNano surfaces, and, after a 1.0 hour interaction, 7.9×104 cells/mL and 2.3×105 cells/mL were associated with the Porous and PorousNano (no protein coating) surfaces, respectively. The combination of cells to both surfaces, with and without the fibronectin incorporation, resulted in different association indices. For comparison, association index values were considered null for samples without FN. After one hour, the association indices values of cells with samples with FN showed increase of 44.7% (±0.8%) and 57.4% (±0.3%) for Porous-FN and PorousNano-FN surfaces, respectively, compared to the same surfaces without FN.The cell-surface interaction index of the PorousNano-FN was approximately 28% higher than that of the Porous-FN.
## 3.5. Surface Radioactivity
After the incorporation of [3H]-thymidine for 12 hours, the radioactivity associated with osteoblast cells was evaluated. Subsequently, 1.8×106 cells/mL, corresponding to 1,100 cpm, were delivered to Porous, Porous-FN, PorousNano, and PorousNano-FN surfaces. The results are shown in Figure 4.Figure 4
Radioactivity associated with osteoblasts on Porous, Porous-FN, PorousNano, and PorousNano-FN surfaces. The resulting values were expressed as counts per minute (cpm).After one hour of interaction, 70% of cells (0.751 cpm) were associated with the PorousNano surface. This number is most likely low because some cells died or were not associated with the sample at the beginning of the process. The number of associated cells increased with interaction time, reaching 0.864 cpm after three hours; that is, there was a 15% increase in the amount of associated cells due to proliferation and cell division.Only 64% of the cells interacting with the Porous surface (0.687 cpm) remained associated after one hour, but this number increased approximately 32% after 3 hours of interaction, reaching 0.905 cpm.On the Porous-FN surface, 90% of cells (0.976 cpm) were associated after 1 hour of interaction. The number of attached cells increased 9% after three hours, reaching 1.064 cpm. For the PorousNano-FN surface, 92% of cells (0.986 cpm) were associated after one hour of interaction, and this number increased by 11.5% over three hours, reaching 1.100 cpm.
## 4. Discussion
Figure1(a) shows the surface morphology of a Porous sample obtained by immersion treatment in acid solution. The acid etching produces a homogeneous surface characterized by microcavities surrounded by tapered summits. This pattern of roughness produces a homogeneous surface without preferential roughness orientation.Figure1(c) shows that the immersion of the Porous surface in a solution containing fluoride ions did not change the microcavity morphology, and the sharp edges persisted. At higher magnification, the presence of flatter areas and smaller micropeaks may be noted although these surfaces remain tapered. This change may be associated with the high reactivity of fluorine ions and the chemical susceptibility of titanium oxide to these ions, which may produce a coalescence of peaks. These results are consistent with those of Ellingsen and Lyngstadaas [9] and Johansson et al. [8], which showed that titanium surfaces treated with fluoride present smoother microtopographies and lower Ra values than acid-treated surfaces without fluoride. Figure 1(d) demonstrates the presence of microcavities, summits, and conglomerates on their edges, most likely due to the corrosion process and consequent decrease in surface roughness for the surface subjected to immersion in solution containing fluoride.Images obtained by atomic force microscopy (Figure2) show that both the Porous and PorousNano surfaces exhibit microcavities surrounded by summits. Like the high-resolution SEM images, the AFM images indicate that summits and microcavities of the PorousNano sample surface have smoother edges although they remain tapered. These sharp edges seem to assist or facilitate the adsorption of FN and cells.As measured based on the images obtained through AFM, the roughness of the PorousNano surface sample was lower than that of the Porous surface, demonstrating that treatment with fluoride reduced the summit height, most likely due to the reaction of titanium oxide with fluoride ions. This ultrastructural aspect of the summits contributes to the more homogeneous roughness pattern of the PorousNano surface, in addition to the presence of smoother areas and larger microcavities.The presence of only one crystalline phase of titanium was revealed by X-ray diffraction of the Porous and PorousNano samples. It is likely that the immersion in a solution containing fluoride ions adds only a small amount of this element to the titanium surface and that this trace amount of fluoride cannot be detected by the XRD technique for the analysis of thin films (grazing incidence technique).Approximately 80% of the FN allowed to interact with Porous and PorousNano surfaces was adsorbed (2.473 AU). This result demonstrates that the chemical treatment with acids (Porous) and chemical treatment with acids followed by immersion in solution containing fluoride ions (PorousNano) did not affect the incorporation of biomolecule; that is, the presence of the fluoride ion did not influence the protein adsorption. Dos Santos et al. [15] observed that FN adsorption to anodized titanium samples was 68%. It can be concluded that titanium surfaces have an affinity for fibronectin and that differences in the percentage of incorporation in different studies most likely are due to the conditions under which the FN was reacted with the surfaces (pH used, for example) and/or the various treatments performed on them.Cell counting in a hematimetric chamber is a sensitive and accurate technique for the evaluation of cell adhesion to titanium surfaces. In this study, the PorousNano surface showed a stronger association with osteoblastic cells (2,3×105 cells/mL) than the Porous surface (7,9×104 cells/mL) after one hour of interaction. Because 106 cells/mL were taken to interact with surfaces, approximately 8% adhered to the Porous sample, while 23% were associated with the PorousNano sample. These indices suggest that the surface subjected to chemical treatment followed by immersion in a solution containing fluoride ions favors the adhesion of most cells during the initial interaction period. As mentioned earlier, the association indices of the Porous and PorousNano surfaces without fibronectin were considered null for evaluations of the influence of protein on cell behavior. Thus, the number of cells associated with the PorousNano with FN surface increased 57.4% compared with the same surface without the biological variable. For the Porous with FN surface, the increase in cell adhesion was 44.7% compared to the same area without the protein. These indices show that the protein variable is responsible for the significant increase in the number of cells attached to the surfaces, confirming the results of Ku et al. [16], who also reported an increase in the adhesion rate of cells to surfaces treated with recombinant fibronectin. They showed that, for TiO2, cell adhesion was initiated after 3 hours and had significantly lower cell numbers for all measurement points compared with FN. The present work showed the same results.The cell-surface interaction index of PorousNano with FN was approximately 28% higher than that of the Porous with FN surface. This study demonstrates that, among the four types of surfaces examined, the PorousNano with fibronectin coating most favors the adsorption and adhesion of osteoblastic cells during the tested interaction period. In addition, the study provides strong evidence that FN incorporation into titanium surfaces is much more relevant for biocompatibility and the consequent acceleration of the osseointegration process than surface treatment with acid and/or immersion in solution containing fluoride ions.A total of1.8×106 cells/mL (1.100 cpm) were allowed to interact with Porous, Porous-FN, PorousNano, and PorousNano-FN titanium surfaces for three hours. After one hour of interaction, 92% of the cells were associated with the PorousNano-FN surface, and 90% of cells were associated with the Porous-FN surface, while 70% and 64% of cells were associated with the PorousNano and Porous surfaces (without FN), respectively. These results confirm that the protein coating accelerated the adsorption of cells during the initial interaction period (adaptation period). This can be explained by the fact that when fibronectin is allowed to interact with titanium samples under ideal conditions of pH such that its cryptic sites are exposed, the fibronectin signals to osteoblasts to activate the cell cycle and initiate the secretion of ECM proteins.The Porous-FN and PorousNano-FN surfaces showed similar behavior during the three-hour interaction, both during the initial adherence of cells (approximately 90% for both surfaces) and in their proliferation. The cell number increased by 14% for the sample PorousNano-FN and 12% for Porous-FN in the first 3 hours of interaction (Figure4). Ku et al. [16] also demonstrated that the biomimetization of titanium surfaces with fibronectin increased the adhesion, proliferation, and differentiation rates of cells.In samples without FN, this study showed that within one-to-three hours of interaction, the number of cells attached to the PorousNano surface increased by 32%, while the number of cells attached to the Porous surface increased by 15%. This difference shows that the surface that received acid treatment followed by immersion in a solution containing fluoride ions (Nano) showed accelerated cell division and proliferation compared to the Porous surface. Figure4 shows that the PorousNano surface without fibronectin coating exhibited the greatest increase in cpm as a function of time over 3 hours. Ellingsen and Lyngstadaas [9] and Johansson et al. [8] showed that fluoride-treated surfaces have a greater capacity to react with biological tissues and nuclear phosphate crystals in vitro, in addition to offering greater osseointegration resistance in vivo. Although previous studies have used different methodologies for fluoride treatment, their results also suggest that the presence of fluoride ions on titanium surfaces facilitates various osseointegration processes. Analysis of the experimental cell adhesion and proliferation data presented in Figure 4 showed that the cell behavior was similar in all samples containing fibronectin. The results of this study show that the FN is critical to the biocompatibility of surfaces of titanium implants, but when this protein is not present, treatment with acids and fluorides seems to favor more tissue integration than treatment with acid only (i.e., no fluoride).
## 5. Conclusions
Based on the experimental results, it can be concluded that(a)
the surfaces of titanium samples treated with fluoride ions (PorousNano) retained the basic microstructural characteristics of surfaces not treated with fluoride (Porous),(b)
the Porous and PorousNano surfaces incorporated similar levels of FN (approximately 80%) over the time tested (3 hours), demonstrating that the presence of fluoride ions did not influence protein adsorption,(c)
the association indices of HOB cells to the four tested surfaces suggest that FN incorporation is critical for thein vitro cytocompatibility of surfaces,(d)
FN-treated samples showed significantly higher percentages of associated cells during the initial period of one hour, confirming that FN (the biological variable) had a greater effect on the adhesion and proliferation of cells than the fluoride treatment of titanium surfaces used in this study.
---
*Source: 290179-2012-11-08.xml* | 290179-2012-11-08_290179-2012-11-08.md | 39,783 | Preparation of Bioactive Titanium Surfaces via Fluoride and Fibronectin Retention | Carlos Nelson Elias; Patricia Abdo Gravina; Costa e Silva Filho; Pedro Augusto de Paula Nascente | International Journal of Biomaterials
(2012) | Engineering & Technology | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2012/290179 | 290179-2012-11-08.xml | ---
## Abstract
Statement of Problem. The chemical or topographic modification of the dental implant surface can affect bone healing, promote accelerated osteogenesis, and increase bone-implant contact and bonding strength. Objective. In this work, the effects of dental implant surface treatment and fibronectin adsorption on the adhesion of osteoblasts were analyzed. Materials and Methods. Two titanium dental implants (Porous-acid etching and PorousNano-acid etching followed by fluoride ion modification) were characterized by high-resolution scanning electron microscopy, atomic force microscopy, and X-ray diffraction before and after the incorporation of human plasma fibronectin (FN). The objective was to investigate the biofunctionalization of these surfaces and examine their effects on the interaction with osteoblastic cells. Results. The evaluation techniques used showed that the Porous and PorousNano implants have similar microstructural characteristics. Spectrophotometry demonstrated similar levels of fibronectin adsorption on both surfaces (80%). The association indexes of osteoblastic cells in FN-treated samples were significantly higher than those in samples without FN. The radioactivity values associated with the same samples, expressed as counts per minute (cpm), suggested that FN incorporation is an important determinant of the in vitro cytocompatibility of the surfaces. Conclusion. The preparation of bioactive titanium surfaces via fluoride and FN retention proved to be a useful treatment to optimize and to accelerate the osseointegration process for dental implants.
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## Body
## 1. Introduction
The phenomenon of endosseous implant osseointegration, conceptualized by Branemark as the “direct, structural and functional link between the living and orderly bone and the surface of an implant subjected to functional loads” [1], is fundamental to the success of dental implant applications. Commercially pure titanium (cp Ti) is the main material used for this purpose because it has good biocompatibility and adequate mechanical strength. Ti exposed to oxidizing agents spontaneously forms a 10-100 Å thick titanium oxide layer. This layer is stable in most media, especially under physiological conditions, and, surgically, it shows no change in thickness or corrosion. This ensures implant-bone tissue interaction and osseointegration [2]. The reactions of the tissue host with the biomaterial are determined by the surface properties of the biomaterial. The dental implant surface treatment should induce the differentiation of the desired cells [3]. Surface treatments of available implants promote changes in the mechanical, microstructural, and physical properties, as well as the wettability, energy, chemical composition, and density of chemical groups or molecules on the surface [2, 4].This paper shows that the bone-implant interface strength is greater in dental implants with rough surfaces than in those with smooth surfaces [5, 6]. Treatments to increase the surface area for fibrin adhesion encourages implant adhesion. The presence of these surfaces also increases platelet activation, which produces large gradients of cytokines and growth factors through which leukocytes and osteogenic cells can penetrate the healing site [7]. Titanium surfaces coated with proteins can influence host reactions and thus enhance tissue integration [4]. Fibronectin is a major adhesion protein in the extracellular membrane, and it is important for cell adhesion, migration, proliferation, differentiation, and survival because it facilitates focal contacts with the receptors.Appropriate changes in dental implant surface roughness can produce better anchoring strength and mechanical locking in the early stages of osseointegration [2, 6]. Moreover, surfaces with different microtopographies provide a larger area for fibrin adhesion, potentiate platelet activation, and favorably affect local angiogenesis and cellular functions including migration, alignment, orientation, attachment, and differentiation [5, 6].Johansson et al. [8] observed that surfaces treated with fluoride are smoother than sandblasted surfaces but that fluoride-treated surfaces showed higher calcium-phosphorus binding capacity, which could indicate an increased ability of the surface to react with calcified tissues and promote integration between bone and implant. According to Ellingsen and Lyngstadaas [9], in vitro tests have shown that titanium fluoride treatments have a greater capacity for the nucleation of phosphate crystals than sandblasted Ti implants. In vivo fluoride ion-modified implants have generally proven superior to sandblasted surfaces in terms of osseointegration, ultimately increasing the removal torques.Fibronectin is a major extracellular matrix protein that is known to promote cell attachment and spreading, differentiation, and phagocytosis. It is a dimeric glycoprotein found in all vertebrates in two basic forms: soluble (plasma and other fluids) and insoluble (extracellular matrix of various tissues). It has a molecular weight between 440 and 500 kDa. Disulfide bridges link one subunit to another via sites near the carboxy termini of each subunit. The fibronectin protein has folds that lead to structural remodeling and various conformations according to the medium [10–12].Fibronectin (FN) functions in cell adhesion, migration, survival, proliferation, and differentiation as well as tissue organization. The FN molecule can interact with other biomolecules, such as collagen, proteoglycan, heparin, hyaluronic acid, fibrin/fibrinogen, plasmin, gangliosides, complement components, and also integral proteins of cell plasma membrane-integrins, as well as with itself [13].Menezes [10] conducted a study to assess the interaction of human osteoblasts with films of human plasma fibronectin prepared under different pH conditions. The results showed no quantitative differences in the interaction of human osteoblastic cells (HOB) to different coatings, but qualitative differences were observed; osteoblasts adhered to each of the substrates in very different ways. The largest areas of cells adhesion were observed for substrates preincubated at 4.5 pH.Petrie et al. [14] conducted a clinical study to evaluate the effects of specific bioactive coatings on the healing of bone tissue and the osseointegration of titanium dental implants. The author showed that surfaces containing a FN fragment for the integrin α5β1 (FNIII7–10) increase osteoblastic differentiation and optimize tissue formation and functional integration compared with untreated surfaces or surfaces containing only the RGD sequence.The purpose of this study was to evaluate the effect of the fluoride treatment of cp titanium samples on the adhesion and proliferation of osteoblastic cells on surfaces with and without fibronectin coating.
## 2. Materials and Methods
### 2.1. Samples
Implants and discs of grade 4 machined cp Ti were provided by Conexão Sistemas de Prótese (Arujá, SP, Brazil). Samples were submitted to surface treatment and divided into four groups:Porous: samples treated in acidic solutions containing HNO3, H2SO4, and HCl (surface treatment similar to Porous implants available from Conexão Sistemas de Prótese);PorousNano: treatment similar to Group 1 followed by fluoride ion modification by immersion for one hour in a solution containing fluorine ions;Porous-FN: treatment similar to Group 1 with FN incorporation;PorousNano-FN: treatment similar to Group 2 with FN incorporation.After treatments, samples from the Porous and PorousNano groups were washed with distilled water and absolute alcohol, dried in oven at 70°C for two hours, and packed and sterilized by gamma irradiation (25 kGy).
### 2.2. Surface Characterization
To characterize the surface morphology and identify differences in samples submitted to treatments with acids and/or fluorides, the samples were characterized by a high-resolution scanning electron microscopy (FEG/EDS, Philips XL30FEG). The results were complemented by analysis with an MFP-3D atomic force microscope (Asylum Research, CA, USA) operating in contact at room temperature mode. The cantilevers used were V shaped, NP-S model (Veeco Probes, CA, USA) with an 0.08 N/m spring constant, and calibrated using the thermal noise method. To reduce damage to samples and reduce noise, images were acquired using low-frequency scanning (1.0 Hz) with256×256 pixel resolution. Image processing was performed in the program IGOR PRO (WaveMetrics, Portland, OR, USA) using a MFP-3D platform developed by Asylum Research.
### 2.3. Identification of Crystalline Phases
An X-ray diffractometer was used to identify crystalline phases on discs. X-ray diffraction for the analysis of thin films (grazing incidence technique) was conducted at 40 kV and 30 mA. A copper anode was used (Cu-Kα=1,542Å) with an RU 200B model Rigaku generator and 0.02° step/minute.
### 2.4. Fibronectin Incorporation
Human serum fibronectin (Sigma-Aldrich Co., São Paulo, Brazil)) was diluted to 10 g/mL, pH 4.5 in previously filtered 20 mM sodium acetate (Reagen Laboratory Products, Paraná, Brazil) buffer solution. NaCl was added to the solution to maintain the medium’s ionic strength between 0.145 and 0.150 mol·dm−3.Samples from the Porous and PorousNano groups were coated with fibronectin at room temperature for 2 hours. Substrates with FN were washed with PBS (phosphate [0.01 M] buffered saline [0.15 M], pH 7.2) to remove nonadsorbed molecules. Then, the adsorbed molecules were detached using 0.1% trypsin and PBS. One to two minutes later, the excess was removed, and the resulting solution was collected and analyzed with a Spectrum 22PC spectrophotometer to quantify the adsorbed molecules. Spectrophotometry was also used to determine the FN’s absorbance on both surfaces (protein concentration in solutions that absorb radiation). Negative (PBS) and positive (FN suspension 100μg/mL) controls were performed. The wavelength used was 550 nm (protein reading).
### 2.5. Culture of Osteoblasts
Cells were maintained in polystyrene bottles containing DMEM (Dulbecco’s Modified Eagle Medium) culture medium with low glucose, 10% fetal bovine serum (Soromed Industry, São Paulo, Brazil), and 1% essential amino acids solution (Minimum Essential amino acid solution 100x, Sigma-Aldrich) ascorbic acid (0.15 gL−1, Sigma-Aldrich) buffered with 10 mM HEPES (Sigma-Aldrich) and 14.3 mM NaHCO3 (Reagen). The pH of the medium was adjusted to 7.2. Cultures were incubated at 37°C in 5% CO2 atmosphere. The enzymatic cell detachment technique was used to transpose cells from the stock culture flask to substrates for the adhesion assay. Confluent cultures were treated with 0.2% trypsin (Difco Microbiology Co., USA) and 0.02% EDTA (Sigma-Aldrich) in saline solution (0.8% NaCl [Reagan], 0.01% KCl [Sigma-Aldrich]; 0.29% NaHPO4·7H2O [Reagan], and 0.02% KH2PO4 [Sigma-Aldrich] in H2O) for 5 minutes at 37°C. Then, the detached cells were collected, and the proteolytic action of trypsin was inhibited by adding fetal calf serum to the solution. The suspension was then centrifuged at 1500 rpm at 22°C, and the pelleted cells were resuspended in culture medium without fetal calf serum. The cell concentration/density of the suspension was estimated by counting in a hematimetric Neubauer chamber.
### 2.6. Interaction of Cells with Samples
After the cell concentration of the suspension was measured in a hematimetric chamber, 106 cells/mL were taken and allowed to interact with the samples with and without FN coating, which totaled four groups. After an hour of interaction, the supernatants were discarded, and the cells that were attached (adsorbed and adhered) to surfaces were washed with PBS and fixed using glutaraldehyde (2.5% in PBS). Glutaraldehyde was used as fixative to avoid damaging cell integrity (glutaraldehyde contains two functional groups that link two proteins). This procedure was adopted because the use of formaldehyde (which has only one functional group) as a fixative profoundly deformed the cells. After fixation, cells were trypsinized and counted in a hematimetric Neubauer chamber.
### 2.7. Surface Radioactivity
Human osteoblastic cells (HOBs) were cultivated to evaluate cell adhesion and proliferation by liquid scintillation counting. Cells from confluent HOB cultures were detached with trypsin, washed, and counted in a hematimetric chamber. Then, the culture was resuspended in DMEM containing serum and [3H]-thymidine (1143 cpm). After allowing incorporation for a period of 12 hours, the confluent cells were again detached and washed in DMEM without serum, and a liquid scintillator (Beckman, Rack III) was used to evaluate the radioactivity associated with cells. The resulting values were expressed as counts per minute (cpm). These cells, incorporating [3H]-thymidine, were associated with different surfaces (Porous, Porous-FN, PorousNano, and PorousNano-FN) for a period of 3 hours, and counts were carried out after 1, 2, and 3 hours. This cell behavior evaluation method allows accurate reproduction, favoring the future applicability of FN incorporation onto surfaces of dental implants.
## 2.1. Samples
Implants and discs of grade 4 machined cp Ti were provided by Conexão Sistemas de Prótese (Arujá, SP, Brazil). Samples were submitted to surface treatment and divided into four groups:Porous: samples treated in acidic solutions containing HNO3, H2SO4, and HCl (surface treatment similar to Porous implants available from Conexão Sistemas de Prótese);PorousNano: treatment similar to Group 1 followed by fluoride ion modification by immersion for one hour in a solution containing fluorine ions;Porous-FN: treatment similar to Group 1 with FN incorporation;PorousNano-FN: treatment similar to Group 2 with FN incorporation.After treatments, samples from the Porous and PorousNano groups were washed with distilled water and absolute alcohol, dried in oven at 70°C for two hours, and packed and sterilized by gamma irradiation (25 kGy).
## 2.2. Surface Characterization
To characterize the surface morphology and identify differences in samples submitted to treatments with acids and/or fluorides, the samples were characterized by a high-resolution scanning electron microscopy (FEG/EDS, Philips XL30FEG). The results were complemented by analysis with an MFP-3D atomic force microscope (Asylum Research, CA, USA) operating in contact at room temperature mode. The cantilevers used were V shaped, NP-S model (Veeco Probes, CA, USA) with an 0.08 N/m spring constant, and calibrated using the thermal noise method. To reduce damage to samples and reduce noise, images were acquired using low-frequency scanning (1.0 Hz) with256×256 pixel resolution. Image processing was performed in the program IGOR PRO (WaveMetrics, Portland, OR, USA) using a MFP-3D platform developed by Asylum Research.
## 2.3. Identification of Crystalline Phases
An X-ray diffractometer was used to identify crystalline phases on discs. X-ray diffraction for the analysis of thin films (grazing incidence technique) was conducted at 40 kV and 30 mA. A copper anode was used (Cu-Kα=1,542Å) with an RU 200B model Rigaku generator and 0.02° step/minute.
## 2.4. Fibronectin Incorporation
Human serum fibronectin (Sigma-Aldrich Co., São Paulo, Brazil)) was diluted to 10 g/mL, pH 4.5 in previously filtered 20 mM sodium acetate (Reagen Laboratory Products, Paraná, Brazil) buffer solution. NaCl was added to the solution to maintain the medium’s ionic strength between 0.145 and 0.150 mol·dm−3.Samples from the Porous and PorousNano groups were coated with fibronectin at room temperature for 2 hours. Substrates with FN were washed with PBS (phosphate [0.01 M] buffered saline [0.15 M], pH 7.2) to remove nonadsorbed molecules. Then, the adsorbed molecules were detached using 0.1% trypsin and PBS. One to two minutes later, the excess was removed, and the resulting solution was collected and analyzed with a Spectrum 22PC spectrophotometer to quantify the adsorbed molecules. Spectrophotometry was also used to determine the FN’s absorbance on both surfaces (protein concentration in solutions that absorb radiation). Negative (PBS) and positive (FN suspension 100μg/mL) controls were performed. The wavelength used was 550 nm (protein reading).
## 2.5. Culture of Osteoblasts
Cells were maintained in polystyrene bottles containing DMEM (Dulbecco’s Modified Eagle Medium) culture medium with low glucose, 10% fetal bovine serum (Soromed Industry, São Paulo, Brazil), and 1% essential amino acids solution (Minimum Essential amino acid solution 100x, Sigma-Aldrich) ascorbic acid (0.15 gL−1, Sigma-Aldrich) buffered with 10 mM HEPES (Sigma-Aldrich) and 14.3 mM NaHCO3 (Reagen). The pH of the medium was adjusted to 7.2. Cultures were incubated at 37°C in 5% CO2 atmosphere. The enzymatic cell detachment technique was used to transpose cells from the stock culture flask to substrates for the adhesion assay. Confluent cultures were treated with 0.2% trypsin (Difco Microbiology Co., USA) and 0.02% EDTA (Sigma-Aldrich) in saline solution (0.8% NaCl [Reagan], 0.01% KCl [Sigma-Aldrich]; 0.29% NaHPO4·7H2O [Reagan], and 0.02% KH2PO4 [Sigma-Aldrich] in H2O) for 5 minutes at 37°C. Then, the detached cells were collected, and the proteolytic action of trypsin was inhibited by adding fetal calf serum to the solution. The suspension was then centrifuged at 1500 rpm at 22°C, and the pelleted cells were resuspended in culture medium without fetal calf serum. The cell concentration/density of the suspension was estimated by counting in a hematimetric Neubauer chamber.
## 2.6. Interaction of Cells with Samples
After the cell concentration of the suspension was measured in a hematimetric chamber, 106 cells/mL were taken and allowed to interact with the samples with and without FN coating, which totaled four groups. After an hour of interaction, the supernatants were discarded, and the cells that were attached (adsorbed and adhered) to surfaces were washed with PBS and fixed using glutaraldehyde (2.5% in PBS). Glutaraldehyde was used as fixative to avoid damaging cell integrity (glutaraldehyde contains two functional groups that link two proteins). This procedure was adopted because the use of formaldehyde (which has only one functional group) as a fixative profoundly deformed the cells. After fixation, cells were trypsinized and counted in a hematimetric Neubauer chamber.
## 2.7. Surface Radioactivity
Human osteoblastic cells (HOBs) were cultivated to evaluate cell adhesion and proliferation by liquid scintillation counting. Cells from confluent HOB cultures were detached with trypsin, washed, and counted in a hematimetric chamber. Then, the culture was resuspended in DMEM containing serum and [3H]-thymidine (1143 cpm). After allowing incorporation for a period of 12 hours, the confluent cells were again detached and washed in DMEM without serum, and a liquid scintillator (Beckman, Rack III) was used to evaluate the radioactivity associated with cells. The resulting values were expressed as counts per minute (cpm). These cells, incorporating [3H]-thymidine, were associated with different surfaces (Porous, Porous-FN, PorousNano, and PorousNano-FN) for a period of 3 hours, and counts were carried out after 1, 2, and 3 hours. This cell behavior evaluation method allows accurate reproduction, favoring the future applicability of FN incorporation onto surfaces of dental implants.
## 3. Results
### 3.1. Surface Morphology
Figure1 shows Porous and PorousNano titanium surfaces before coating with fibronectin. These surfaces exhibited microcavities with different sizes and sharp edges. Immersion into a solution containing fluoride ions (PorousNano) did not change the microcavity morphology, and the sharp edges persisted. A minor modification caused by immersion is shown in Figure 1(c); some white regions are observed when compared with Figure 1(b). At high magnification (Figure 1(d)), the PorousNano group showed evidence of particle clusters at the surface due to immersion in the solution containing fluoride ions. This is the major ultrastructural characteristic of the PorousNano sample.SEM images of the samples before coating with fibronectin. (a) and (b) Porous samples (acid treatment). (c) and (d) PorousNano samples (acid treatment followed by fluoride ion modification).
(a)
(b)
(c)
(d)Figure2 shows images obtained by atomic force microscopy. In Figure 2(a), the microcavity edges are more flattened but maintain the sharp features that seem to assist or facilitate the adsorption of fibronectin and cells. Figure 2(b) shows the PorousNano sample surface at high magnification, demonstrating that the roughness pattern at the microcavity edges is flattened by immersion treatment in a solution containing fluoride ions.AFM images: (a) Porous and (b) PorousNano.
(a)
(b)The surface roughness of the Porous sample (Figure2(a)) was 1759.7 nm (±204.4 nm), whereas the roughness of the PorousNano surface sample (Figure 2(b)) was 1406.5 nm (±226.9 nm).
### 3.2. Identification of Crystalline Phases
Figure3 shows the X-ray diffraction spectra of the Porous and PorousNano surfaces. Both contain only titanium as the crystalline phase.Figure 3
X-ray diffraction spectra of Porous and PorousNano surfaces.
### 3.3. Incorporation of Fibronectin
Porous and PorousNano titanium surfaces were treated with crystal violet (1% in PBS), and the stain associated with the surfaces was eluted with methanol. Negative (buffer solution) and positive (FN suspension) controls were assessed by spectrophotometry. The absorbance was proportional to the amount of the cells such that more the cells on the surface corresponded to larger absorbance values. Cells treated with PBS measured at 0.326 absorbance units (AU) at 550 nm (reading for proteins). The FN suspension (100μg/mL) measured at 2.992 units. After the FN incorporation in Porous, and PorousNano tablets, both spectrophotometric measurements were 2.473 absorbance units (82.6%) at 550 nm, indicating that the two surfaces exhibit similar behavior with respect to fibronectin incorporation.
### 3.4. Interaction of Cells with Surfaces
A total of 106 human osteoblastic cells/mL were delivered to Porous and PorousNano surfaces, and, after a 1.0 hour interaction, 7.9×104 cells/mL and 2.3×105 cells/mL were associated with the Porous and PorousNano (no protein coating) surfaces, respectively. The combination of cells to both surfaces, with and without the fibronectin incorporation, resulted in different association indices. For comparison, association index values were considered null for samples without FN. After one hour, the association indices values of cells with samples with FN showed increase of 44.7% (±0.8%) and 57.4% (±0.3%) for Porous-FN and PorousNano-FN surfaces, respectively, compared to the same surfaces without FN.The cell-surface interaction index of the PorousNano-FN was approximately 28% higher than that of the Porous-FN.
### 3.5. Surface Radioactivity
After the incorporation of [3H]-thymidine for 12 hours, the radioactivity associated with osteoblast cells was evaluated. Subsequently, 1.8×106 cells/mL, corresponding to 1,100 cpm, were delivered to Porous, Porous-FN, PorousNano, and PorousNano-FN surfaces. The results are shown in Figure 4.Figure 4
Radioactivity associated with osteoblasts on Porous, Porous-FN, PorousNano, and PorousNano-FN surfaces. The resulting values were expressed as counts per minute (cpm).After one hour of interaction, 70% of cells (0.751 cpm) were associated with the PorousNano surface. This number is most likely low because some cells died or were not associated with the sample at the beginning of the process. The number of associated cells increased with interaction time, reaching 0.864 cpm after three hours; that is, there was a 15% increase in the amount of associated cells due to proliferation and cell division.Only 64% of the cells interacting with the Porous surface (0.687 cpm) remained associated after one hour, but this number increased approximately 32% after 3 hours of interaction, reaching 0.905 cpm.On the Porous-FN surface, 90% of cells (0.976 cpm) were associated after 1 hour of interaction. The number of attached cells increased 9% after three hours, reaching 1.064 cpm. For the PorousNano-FN surface, 92% of cells (0.986 cpm) were associated after one hour of interaction, and this number increased by 11.5% over three hours, reaching 1.100 cpm.
## 3.1. Surface Morphology
Figure1 shows Porous and PorousNano titanium surfaces before coating with fibronectin. These surfaces exhibited microcavities with different sizes and sharp edges. Immersion into a solution containing fluoride ions (PorousNano) did not change the microcavity morphology, and the sharp edges persisted. A minor modification caused by immersion is shown in Figure 1(c); some white regions are observed when compared with Figure 1(b). At high magnification (Figure 1(d)), the PorousNano group showed evidence of particle clusters at the surface due to immersion in the solution containing fluoride ions. This is the major ultrastructural characteristic of the PorousNano sample.SEM images of the samples before coating with fibronectin. (a) and (b) Porous samples (acid treatment). (c) and (d) PorousNano samples (acid treatment followed by fluoride ion modification).
(a)
(b)
(c)
(d)Figure2 shows images obtained by atomic force microscopy. In Figure 2(a), the microcavity edges are more flattened but maintain the sharp features that seem to assist or facilitate the adsorption of fibronectin and cells. Figure 2(b) shows the PorousNano sample surface at high magnification, demonstrating that the roughness pattern at the microcavity edges is flattened by immersion treatment in a solution containing fluoride ions.AFM images: (a) Porous and (b) PorousNano.
(a)
(b)The surface roughness of the Porous sample (Figure2(a)) was 1759.7 nm (±204.4 nm), whereas the roughness of the PorousNano surface sample (Figure 2(b)) was 1406.5 nm (±226.9 nm).
## 3.2. Identification of Crystalline Phases
Figure3 shows the X-ray diffraction spectra of the Porous and PorousNano surfaces. Both contain only titanium as the crystalline phase.Figure 3
X-ray diffraction spectra of Porous and PorousNano surfaces.
## 3.3. Incorporation of Fibronectin
Porous and PorousNano titanium surfaces were treated with crystal violet (1% in PBS), and the stain associated with the surfaces was eluted with methanol. Negative (buffer solution) and positive (FN suspension) controls were assessed by spectrophotometry. The absorbance was proportional to the amount of the cells such that more the cells on the surface corresponded to larger absorbance values. Cells treated with PBS measured at 0.326 absorbance units (AU) at 550 nm (reading for proteins). The FN suspension (100μg/mL) measured at 2.992 units. After the FN incorporation in Porous, and PorousNano tablets, both spectrophotometric measurements were 2.473 absorbance units (82.6%) at 550 nm, indicating that the two surfaces exhibit similar behavior with respect to fibronectin incorporation.
## 3.4. Interaction of Cells with Surfaces
A total of 106 human osteoblastic cells/mL were delivered to Porous and PorousNano surfaces, and, after a 1.0 hour interaction, 7.9×104 cells/mL and 2.3×105 cells/mL were associated with the Porous and PorousNano (no protein coating) surfaces, respectively. The combination of cells to both surfaces, with and without the fibronectin incorporation, resulted in different association indices. For comparison, association index values were considered null for samples without FN. After one hour, the association indices values of cells with samples with FN showed increase of 44.7% (±0.8%) and 57.4% (±0.3%) for Porous-FN and PorousNano-FN surfaces, respectively, compared to the same surfaces without FN.The cell-surface interaction index of the PorousNano-FN was approximately 28% higher than that of the Porous-FN.
## 3.5. Surface Radioactivity
After the incorporation of [3H]-thymidine for 12 hours, the radioactivity associated with osteoblast cells was evaluated. Subsequently, 1.8×106 cells/mL, corresponding to 1,100 cpm, were delivered to Porous, Porous-FN, PorousNano, and PorousNano-FN surfaces. The results are shown in Figure 4.Figure 4
Radioactivity associated with osteoblasts on Porous, Porous-FN, PorousNano, and PorousNano-FN surfaces. The resulting values were expressed as counts per minute (cpm).After one hour of interaction, 70% of cells (0.751 cpm) were associated with the PorousNano surface. This number is most likely low because some cells died or were not associated with the sample at the beginning of the process. The number of associated cells increased with interaction time, reaching 0.864 cpm after three hours; that is, there was a 15% increase in the amount of associated cells due to proliferation and cell division.Only 64% of the cells interacting with the Porous surface (0.687 cpm) remained associated after one hour, but this number increased approximately 32% after 3 hours of interaction, reaching 0.905 cpm.On the Porous-FN surface, 90% of cells (0.976 cpm) were associated after 1 hour of interaction. The number of attached cells increased 9% after three hours, reaching 1.064 cpm. For the PorousNano-FN surface, 92% of cells (0.986 cpm) were associated after one hour of interaction, and this number increased by 11.5% over three hours, reaching 1.100 cpm.
## 4. Discussion
Figure1(a) shows the surface morphology of a Porous sample obtained by immersion treatment in acid solution. The acid etching produces a homogeneous surface characterized by microcavities surrounded by tapered summits. This pattern of roughness produces a homogeneous surface without preferential roughness orientation.Figure1(c) shows that the immersion of the Porous surface in a solution containing fluoride ions did not change the microcavity morphology, and the sharp edges persisted. At higher magnification, the presence of flatter areas and smaller micropeaks may be noted although these surfaces remain tapered. This change may be associated with the high reactivity of fluorine ions and the chemical susceptibility of titanium oxide to these ions, which may produce a coalescence of peaks. These results are consistent with those of Ellingsen and Lyngstadaas [9] and Johansson et al. [8], which showed that titanium surfaces treated with fluoride present smoother microtopographies and lower Ra values than acid-treated surfaces without fluoride. Figure 1(d) demonstrates the presence of microcavities, summits, and conglomerates on their edges, most likely due to the corrosion process and consequent decrease in surface roughness for the surface subjected to immersion in solution containing fluoride.Images obtained by atomic force microscopy (Figure2) show that both the Porous and PorousNano surfaces exhibit microcavities surrounded by summits. Like the high-resolution SEM images, the AFM images indicate that summits and microcavities of the PorousNano sample surface have smoother edges although they remain tapered. These sharp edges seem to assist or facilitate the adsorption of FN and cells.As measured based on the images obtained through AFM, the roughness of the PorousNano surface sample was lower than that of the Porous surface, demonstrating that treatment with fluoride reduced the summit height, most likely due to the reaction of titanium oxide with fluoride ions. This ultrastructural aspect of the summits contributes to the more homogeneous roughness pattern of the PorousNano surface, in addition to the presence of smoother areas and larger microcavities.The presence of only one crystalline phase of titanium was revealed by X-ray diffraction of the Porous and PorousNano samples. It is likely that the immersion in a solution containing fluoride ions adds only a small amount of this element to the titanium surface and that this trace amount of fluoride cannot be detected by the XRD technique for the analysis of thin films (grazing incidence technique).Approximately 80% of the FN allowed to interact with Porous and PorousNano surfaces was adsorbed (2.473 AU). This result demonstrates that the chemical treatment with acids (Porous) and chemical treatment with acids followed by immersion in solution containing fluoride ions (PorousNano) did not affect the incorporation of biomolecule; that is, the presence of the fluoride ion did not influence the protein adsorption. Dos Santos et al. [15] observed that FN adsorption to anodized titanium samples was 68%. It can be concluded that titanium surfaces have an affinity for fibronectin and that differences in the percentage of incorporation in different studies most likely are due to the conditions under which the FN was reacted with the surfaces (pH used, for example) and/or the various treatments performed on them.Cell counting in a hematimetric chamber is a sensitive and accurate technique for the evaluation of cell adhesion to titanium surfaces. In this study, the PorousNano surface showed a stronger association with osteoblastic cells (2,3×105 cells/mL) than the Porous surface (7,9×104 cells/mL) after one hour of interaction. Because 106 cells/mL were taken to interact with surfaces, approximately 8% adhered to the Porous sample, while 23% were associated with the PorousNano sample. These indices suggest that the surface subjected to chemical treatment followed by immersion in a solution containing fluoride ions favors the adhesion of most cells during the initial interaction period. As mentioned earlier, the association indices of the Porous and PorousNano surfaces without fibronectin were considered null for evaluations of the influence of protein on cell behavior. Thus, the number of cells associated with the PorousNano with FN surface increased 57.4% compared with the same surface without the biological variable. For the Porous with FN surface, the increase in cell adhesion was 44.7% compared to the same area without the protein. These indices show that the protein variable is responsible for the significant increase in the number of cells attached to the surfaces, confirming the results of Ku et al. [16], who also reported an increase in the adhesion rate of cells to surfaces treated with recombinant fibronectin. They showed that, for TiO2, cell adhesion was initiated after 3 hours and had significantly lower cell numbers for all measurement points compared with FN. The present work showed the same results.The cell-surface interaction index of PorousNano with FN was approximately 28% higher than that of the Porous with FN surface. This study demonstrates that, among the four types of surfaces examined, the PorousNano with fibronectin coating most favors the adsorption and adhesion of osteoblastic cells during the tested interaction period. In addition, the study provides strong evidence that FN incorporation into titanium surfaces is much more relevant for biocompatibility and the consequent acceleration of the osseointegration process than surface treatment with acid and/or immersion in solution containing fluoride ions.A total of1.8×106 cells/mL (1.100 cpm) were allowed to interact with Porous, Porous-FN, PorousNano, and PorousNano-FN titanium surfaces for three hours. After one hour of interaction, 92% of the cells were associated with the PorousNano-FN surface, and 90% of cells were associated with the Porous-FN surface, while 70% and 64% of cells were associated with the PorousNano and Porous surfaces (without FN), respectively. These results confirm that the protein coating accelerated the adsorption of cells during the initial interaction period (adaptation period). This can be explained by the fact that when fibronectin is allowed to interact with titanium samples under ideal conditions of pH such that its cryptic sites are exposed, the fibronectin signals to osteoblasts to activate the cell cycle and initiate the secretion of ECM proteins.The Porous-FN and PorousNano-FN surfaces showed similar behavior during the three-hour interaction, both during the initial adherence of cells (approximately 90% for both surfaces) and in their proliferation. The cell number increased by 14% for the sample PorousNano-FN and 12% for Porous-FN in the first 3 hours of interaction (Figure4). Ku et al. [16] also demonstrated that the biomimetization of titanium surfaces with fibronectin increased the adhesion, proliferation, and differentiation rates of cells.In samples without FN, this study showed that within one-to-three hours of interaction, the number of cells attached to the PorousNano surface increased by 32%, while the number of cells attached to the Porous surface increased by 15%. This difference shows that the surface that received acid treatment followed by immersion in a solution containing fluoride ions (Nano) showed accelerated cell division and proliferation compared to the Porous surface. Figure4 shows that the PorousNano surface without fibronectin coating exhibited the greatest increase in cpm as a function of time over 3 hours. Ellingsen and Lyngstadaas [9] and Johansson et al. [8] showed that fluoride-treated surfaces have a greater capacity to react with biological tissues and nuclear phosphate crystals in vitro, in addition to offering greater osseointegration resistance in vivo. Although previous studies have used different methodologies for fluoride treatment, their results also suggest that the presence of fluoride ions on titanium surfaces facilitates various osseointegration processes. Analysis of the experimental cell adhesion and proliferation data presented in Figure 4 showed that the cell behavior was similar in all samples containing fibronectin. The results of this study show that the FN is critical to the biocompatibility of surfaces of titanium implants, but when this protein is not present, treatment with acids and fluorides seems to favor more tissue integration than treatment with acid only (i.e., no fluoride).
## 5. Conclusions
Based on the experimental results, it can be concluded that(a)
the surfaces of titanium samples treated with fluoride ions (PorousNano) retained the basic microstructural characteristics of surfaces not treated with fluoride (Porous),(b)
the Porous and PorousNano surfaces incorporated similar levels of FN (approximately 80%) over the time tested (3 hours), demonstrating that the presence of fluoride ions did not influence protein adsorption,(c)
the association indices of HOB cells to the four tested surfaces suggest that FN incorporation is critical for thein vitro cytocompatibility of surfaces,(d)
FN-treated samples showed significantly higher percentages of associated cells during the initial period of one hour, confirming that FN (the biological variable) had a greater effect on the adhesion and proliferation of cells than the fluoride treatment of titanium surfaces used in this study.
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*Source: 290179-2012-11-08.xml* | 2012 |
# A Human Motion Function Rehabilitation Monitoring System Based on Data Mining
**Authors:** Xiaojing Chen
**Journal:** Scientific Programming
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2901812
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## Abstract
Human motion interaction technologies have evolved to a new level with the development of traditional reality technology as science and technology have developed. Fully interactive and human motion interaction technologies are becoming more common in fields such as medical rehabilitation and military simulations. Human motion is at the heart of all activity, and motion analysis and human motion are critical theoretical disciplines. Identification is based on behavior and motion in human motion, with attributes such as effectiveness, intelligence, potent interaction, and rich expression data. When studying human movement, many researchers now prefer this method. However, this study was conducted with insufficient suggestions for real-time human motion function assessment, rehabilitation, and improvement. The development of an information monitoring system for human motion function rehabilitation can be used to evaluate the efficacy of patient rehabilitation training. A human motion function rehabilitation monitoring system is created using an effective and thorough design methodology. The system is made up of the rehabilitation monitoring terminal, the human motion function monitoring module, and the medical center monitoring system. Therefore, the motion-based data mining technique is better for the human motion function rehabilitation monitoring system. The normalized proportion of motion features will assist in the creation of a database for human motion mining. The nonlinear classification function is used in this paper to scientifically categorize human motion features to implement data mining techniques for monitoring human motion function rehabilitation. The effectiveness of patient rehabilitation is significantly increased by the use of a human motion-based rehabilitation monitoring system.
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## Body
## 1. Introduction
A patient may be required to complete a comprehensive and important physical rehabilitation program to regain their prior strength, flexibility, and fitness after some kind of illness, injury, or surgery. The primary goal is to evaluate and optimize the patients' lifetime capabilities and motion qualities, and it is standard procedure in this environment to continuously monitor the patients' movements. In rehabilitation facilities, traditional physiotherapy-based treatments are frequently used; these treatments indicate the need for qualified professionals and their invaluable competence [1]. The standardized, objective data necessary to fairly assess patients' accomplishments might not be present in these treatments. Since the 1980s, there has been an increase in patients with motor function problems, which has made human motion tracking for rehabilitation a popular research topic. Humans must move their bodies in order to survive, and healthy people move their bodies frequently, while sick people move their bodies much less frequently. Stroke, one of the leading causes of disability in the world, frequently results in a limb or limbs losing all or some of their performance as a result of motor dysfunction [2]. In recent years, neurorehabilitation medicine research has advanced gradually, and the general public has assumed that damaged human motor function could be partially restored. Using scientific rehabilitation techniques could result in complete paralysis, low stamina, loss of motor control, or muscle weakness. On the other hand, looking for an effective rehabilitation treatment method to assist the patient in regaining human motor function will be counterproductive. It not only helps to improve the standard of living for patients but also reduces the burden on their families and society [3]. The overarching functional design scheme of the human motor function rehabilitation monitoring system clarifies the particular design plan of the subsystem. The monitoring terminal for rehabilitation, the human motor function monitoring module, and the monitoring system for the medical facility are also included in the composition.Through trials, information on plantar pressure under different motion modes and details on the current gait were acquired. Li et al. are now using fuzzy mathematics theory to characterize human behavior. The significant gait events, such as the contact of the leg and foot, were identified using dynamic baseline monitoring. The screening windows are used to filter the repeated individual monitoring over a specified period for the error monitoring of vital gait events, significantly improving identification accuracy and supplying essential gait data for the categorization of movement patterns. The viability and effectiveness of the fuzzy theory application for human motion identification are established by performing similarities comparisons on each pattern, the relevant levels of motion extraction features, and the relevant levels of motion pattern recognition. Artificial intelligence is expected to provide processing approaches and research projects to meet future demand [4]. Villanueva et al. describe a wearable multisensor system for monitoring human movement in stroke rehabilitation. It is composed of several teeny-tiny modules that can wirelessly connect and transmit motion-related data to an acquisition device. It is beneficial for human motion collecting and monitoring, which is required for activities such as activity detection, measuring physical and athletic performance, and rehabilitation, and according to the results of a series of experiments, we evaluated its performance in real-world environments [5]. Banaee et al. investigated the most cutting-edge methods and algorithms for interpreting data from smart technology used for physiologic monitoring of vital signs in healthcare services in a recent publication. The paper provides an overview of the more popular data mining applications, such as intrusion detection systems, prediction, and decision making, with an emphasis on continuous time-series observations. The study also discusses the suitability of specific data mining and machine learning algorithms used to evaluate the physiological data and provides an overview of the features of the data sets used in experimental verification. Several key challenges for data mining approaches in health monitoring systems have been identified based on this literature review [6].Rehabilitation training is a method of brain plasticity rehabilitation treatment, and the findings of modern neurorehabilitation medicine and associated studies show that. For human motor dysfunction caused by problems such as stroke, adopting scientific rehabilitation training treatment modalities can effectively recover the damaged human motor function to a corresponding extent. Rehabilitation physicians must conduct a real-time objective evaluation of the effect of rehabilitation training on patients during the rehabilitation training process. Accurately assess motor recovery ability as well as training participation, and effectively adjust the feedback scheme of rehabilitation training based on the evaluation results. The efficiency of rehabilitation training is improved, and the effect of rehabilitation is maximized. The process of analyzing and extracting information from large datasets is called data mining. It is important to use a data mining method to monitor the rehabilitation training process for patients with human motor dysfunction and deep understanding. The effect of rehabilitation training under objective data is significant in terms of improving the effectiveness of rehabilitation treatment for patients. The overall functional design scheme of the human motor function rehabilitation monitoring system clarifies the subsystem’s specific design scheme. The rehabilitation monitoring terminal, the human motor function monitoring module, and the medical center monitoring system are all part of this system.The innovation of this paper is as follows:(i)
Firstly, the data mining method based on motor features was applied to the human motor function rehabilitation monitoring system, and human motor function rehabilitation monitoring data mining was realized(ii)
Secondly, in comparison with the traditional monitoring system of human motor function rehabilitation, the data mining-based monitoring system of human motor function rehabilitation is presented(iii)
Finally, overall performance improved both the real-time performance of the human motor function rehabilitation monitoring system and the effect of patient rehabilitation trainingThe remainder of the paper is structured logically as follows: Section2 shows related work; Section 3 represents the human motion function rehabilitation monitoring system based on data mining; Section 4 demonstrates the human motion function rehabilitation monitoring method based on motion characteristics, and Section 5 shows the experimental results and analysis. Finally, Section 6 concluded this work.
## 2. Related Work
In the early years, relevant researchers at home and abroad began to conduct in-depth research on human physiological parameters and rehabilitation monitoring, and they achieved some research results through their efforts. Li et al. proposed a monitoring system for human remote rehabilitation training, which provides a remote rehabilitation training monitoring platform for patients in rehabilitation. The terminal-controlled module processor is a 32-bit STMicroelectronics (STM32) integrated circuit that controls data acquisition, processing, and transmission. Complete the communication between the acquisition device and the cloud server during the rehabilitation process using the Message Queuing Telemetry Transport (MQTT) protocol. Analyze the time-frequency domain of electromyography (EMG) signal to calculate the specific situation of muscle strength and muscle fatigue and calculate the activity of human joints from the signal of attitude sensor for rehabilitation evaluation of rehabilitation training. To complete the interaction between the browser and the cloud server, use the Tomcat server to display the patient’s rehabilitation data on the web page. However, remote rehabilitation training monitoring, uploading, and the mointoring system need help to discharge stroke patients for rehabilitation treatment and early recurrence warnings. A multifunctional human motor function rehabilitation monitoring system was created, which included human physiological signals, treatment, and data analysis. The therapeutic device uses transcranial direct current stimulation technology to accurately output constant and direct current. The patient’s heart rate and other pertinent data are then routinely monitored by the intelligent bracelet, which is created as an adjunct rehabilitation monitoring device. Send the rehabilitation data to the mobile phone via Bluetooth, and then use the mobile phone to summarize the treatment records and vital signs data before uploading the summarized data to the cloud for in-depth analysis. It is specifically used to adjust the rehabilitation treatment plan or for early warning of stroke recurrence. The development results show that the monitoring system can not only meet the needs of human motor function rehabilitation treatment but also realize the interconnection between cloud and equipment. The system can provide effective solutions for personalized treatment of stroke, recurrence early warning, and database, but the system has the problem of high cost [7]. Yang et al. describe a human rehabilitation monitoring system based on an embedded controller designed to meet the needs of human postoperative recovery training. A multifunction human rehabilitation training mode, movement posture, EMG signal acquisition, and safety protection are realized. The training process is identified and analyzed by using the random forest machine learning method and linear regression method. The results show that the designed human rehabilitation control and monitoring system can use Android for portable control. To complete the intelligent analysis of the rehabilitation training process, use the monitoring signals in the training process. The random forest method has advantages over the linear regression method in human motion recognition, but the rehabilitation effect of this method is poor [8]. Guan et al. propose a human rehabilitation movement monitoring method based on human posture information to control rehabilitation training for patients with human motor dysfunction after surgery. It is a data collection system for human motion data that is customized to the structural characteristics and functional requirements of rehabilitated patients. The kinematic model of human rehabilitation is built, and a behavior information collection system for human posture is established on the rehabilitation platform. The software evaluates the expected follow-up speed of rehabilitation based on the behavior change information representing human posture obtained from the displacement analysis sensor. To reduce the error generated, the tracking controller is designed using the fuzzy control method and a simulation experiment. However, this method has the problem of poor real-time performance in the process of patients’ real-time tracking movement and realization of the following effect of rehabilitation on patients’ motion posture [9].
## 3. Human Motion Function Rehabilitation Monitoring System Based on Data Mining
Figure1 depicts the overall framework of the human motor function rehabilitation monitoring system. The data mining-based human motion function rehabilitation monitoring system is primarily composed of a large number of collection nodes for physiological parameters worn by patients. A self-organized wireless network is established between the nodes, and the physiological parameter signals are transmitted to the convergence node of the wireless network through the Zonal Intercommunication Global (ZigBee) protocol. ZigBee is a low-power, low-data-rate M2M (machine-to-machine) wireless network and Internet-of-Things (IoT). The ZigBee protocol is based on IEEE 802.15.4. A ZigBee network is made up of several full-function devices (FFD) that gather data from nearby reduced-function devices (RFD).Figure 1
Overall frame diagram of the rehabilitation monitoring system.The local monitoring system consists of embedded portable devices connected to a wireless network, with a sink node collecting physiological data. The main purpose of the medical center’s monitoring system is to create a database of multiple physiological parameters of patients and extract them. Identify patients’ physiological and psychological states and evaluate patients’ rehabilitation effects in real time [10, 11].
### 3.1. Design of Rehabilitation Monitoring Terminal System
Figure2 shows the composition of the rehabilitation monitoring terminal system. The physiological parameter acquisition module and the data transmission module are included in the design of the rehabilitation monitoring terminal system. The physiological parameter acquisition module is a multiparameter physiological module that measures and monitors heart rate, noninvasive blood pressure, respiration, oxygen saturation, temperature, and Enteric Coated (EC). The acquisition module of physiological parameters must install the node in the appropriate position of the patient’s body to collect the patient’s human physiological signals. The selection of physiological signals is mainly divided into collecting electromyography (EMG), electrocardiography (ECG), pulse, and triaxial acceleration. In the node design of hardware, medical sensors and methods for specific physiological signals and signal conditioning circuits such as filtering are composed [12, 13].Figure 2
Rehabilitation monitoring terminal system composition diagram.The rehabilitation data transmission module in the hardware platform makes use of data communication between network nodes and the iris node. The integrated processing chip of the node is the controller and the radiofrequency (RF) chip is the wireless transceiver. The tiny operating system and network cable network routing protocol design are used in the software implementation. The designed networking application is added to the control chip of each node, which can realize the rehabilitation data transmission between wireless nodes, as well as some characteristics such as low-power consumption, load balancing, and robustness.
### 3.2. Human Motor Function Rehabilitation Monitoring Module
Figure3 shows the composition of human motor function rehabilitation monitoring. The unit hardware of the monitoring module is an embedded operating system using the processor core board of the Advanced RISC Machine (ARM9). The software realizes the terminal node data collection, processing, and storage of rehabilitation data and provides the user interface for images for patients. It uploads the collected rehabilitation training data to the medical monitoring center. The local monitoring system module specifically includes embedded transplantation and multiple modules such as data acquisition, data storage, display unit, and network communication [14, 15].Figure 3
Local monitoring system composition diagram.The rehabilitation training data acquisition module serves as the interface between the network node and the ARM processor, and it must analyze various physiological data types. The node collects data using the serial communication protocol, and data processing is the core module in the local monitoring system. It must process and store various physiological signals collected from patients, as well as various control instructions received from the display unit, which is a designed monitoring interface. In the development environment, a graphical interface primarily displays the collected human physiological signals of patients in the form of a real-time dynamic curve. The network communication module is a bridge connecting the local monitoring system and the monitoring system of the medical center. The module adopts Transmission Control Protocol (TCP) and realizes the sending and receiving of rehabilitation data through the socket communication model design.
### 3.3. Medical Center Monitoring System
Figure4 shows the composition of the monitoring system of the medical center. The medical center’s monitoring system is built on the Client/Server framework, which consists of monitoring software for both the server and the client. The server realizes the communication with the local monitoring system and client monitoring software, as well as the storage and processing of rehabilitation data. It specifically includes multiple modules such as network communication, user information management, and ecological parameter monitoring [16, 17].Figure 4
Composition of the medical center monitoring system.The communication server is built based on the TCP, connected with a socket, receives the link from the online local monitoring system and the analysis data packet of the communication protocol, and stores it in the database. The data processing module includes data analysis, preliminary diagnosis, data storage, and so on. The physiological parameters are mined by a data mining algorithm, and the physiological features are extracted and preliminarily diagnosed. The processed data is stored in the database for query and call by the monitoring software of the client. User information management mainly saves the patient’s personal information and physiological data. The monitoring module of physiological parameters uses the call database to obtain the physiological data of patients and displays electrocardiogram (ECG), muscle point, pulse, and other signals in the form of a waveform curve. It is also capable of monitoring physiological parameters. It will provide an early warning if a patient’s physiological parameters exceed the set threshold [18, 19].
### 3.4. Data Frame
The data frame defines the format of the data packet when transmitting rehabilitation data, including the destination node, source node, and the length of the data packet. The specific format of the data frame is shown in Table1.Table 1
Data frame format of the terminal node.
The field namesLength (bytes)Tiny OS Header6Xmesh Header8Xsensor Header5Data Payload17CRC2
## 3.1. Design of Rehabilitation Monitoring Terminal System
Figure2 shows the composition of the rehabilitation monitoring terminal system. The physiological parameter acquisition module and the data transmission module are included in the design of the rehabilitation monitoring terminal system. The physiological parameter acquisition module is a multiparameter physiological module that measures and monitors heart rate, noninvasive blood pressure, respiration, oxygen saturation, temperature, and Enteric Coated (EC). The acquisition module of physiological parameters must install the node in the appropriate position of the patient’s body to collect the patient’s human physiological signals. The selection of physiological signals is mainly divided into collecting electromyography (EMG), electrocardiography (ECG), pulse, and triaxial acceleration. In the node design of hardware, medical sensors and methods for specific physiological signals and signal conditioning circuits such as filtering are composed [12, 13].Figure 2
Rehabilitation monitoring terminal system composition diagram.The rehabilitation data transmission module in the hardware platform makes use of data communication between network nodes and the iris node. The integrated processing chip of the node is the controller and the radiofrequency (RF) chip is the wireless transceiver. The tiny operating system and network cable network routing protocol design are used in the software implementation. The designed networking application is added to the control chip of each node, which can realize the rehabilitation data transmission between wireless nodes, as well as some characteristics such as low-power consumption, load balancing, and robustness.
## 3.2. Human Motor Function Rehabilitation Monitoring Module
Figure3 shows the composition of human motor function rehabilitation monitoring. The unit hardware of the monitoring module is an embedded operating system using the processor core board of the Advanced RISC Machine (ARM9). The software realizes the terminal node data collection, processing, and storage of rehabilitation data and provides the user interface for images for patients. It uploads the collected rehabilitation training data to the medical monitoring center. The local monitoring system module specifically includes embedded transplantation and multiple modules such as data acquisition, data storage, display unit, and network communication [14, 15].Figure 3
Local monitoring system composition diagram.The rehabilitation training data acquisition module serves as the interface between the network node and the ARM processor, and it must analyze various physiological data types. The node collects data using the serial communication protocol, and data processing is the core module in the local monitoring system. It must process and store various physiological signals collected from patients, as well as various control instructions received from the display unit, which is a designed monitoring interface. In the development environment, a graphical interface primarily displays the collected human physiological signals of patients in the form of a real-time dynamic curve. The network communication module is a bridge connecting the local monitoring system and the monitoring system of the medical center. The module adopts Transmission Control Protocol (TCP) and realizes the sending and receiving of rehabilitation data through the socket communication model design.
## 3.3. Medical Center Monitoring System
Figure4 shows the composition of the monitoring system of the medical center. The medical center’s monitoring system is built on the Client/Server framework, which consists of monitoring software for both the server and the client. The server realizes the communication with the local monitoring system and client monitoring software, as well as the storage and processing of rehabilitation data. It specifically includes multiple modules such as network communication, user information management, and ecological parameter monitoring [16, 17].Figure 4
Composition of the medical center monitoring system.The communication server is built based on the TCP, connected with a socket, receives the link from the online local monitoring system and the analysis data packet of the communication protocol, and stores it in the database. The data processing module includes data analysis, preliminary diagnosis, data storage, and so on. The physiological parameters are mined by a data mining algorithm, and the physiological features are extracted and preliminarily diagnosed. The processed data is stored in the database for query and call by the monitoring software of the client. User information management mainly saves the patient’s personal information and physiological data. The monitoring module of physiological parameters uses the call database to obtain the physiological data of patients and displays electrocardiogram (ECG), muscle point, pulse, and other signals in the form of a waveform curve. It is also capable of monitoring physiological parameters. It will provide an early warning if a patient’s physiological parameters exceed the set threshold [18, 19].
## 3.4. Data Frame
The data frame defines the format of the data packet when transmitting rehabilitation data, including the destination node, source node, and the length of the data packet. The specific format of the data frame is shown in Table1.Table 1
Data frame format of the terminal node.
The field namesLength (bytes)Tiny OS Header6Xmesh Header8Xsensor Header5Data Payload17CRC2
## 4. Human Motion Function Rehabilitation Monitoring Method Based on Motion Characteristics
There is a close relationship between human motion characteristics and human actions. It is necessary to analyze the importance of human motion characteristics from the direction of human motion. We will talk about the characteristic threshold of patients’ human motion.
### 4.1. Motion Feature Extraction
Some of the patient’s human motion features are deleted based on the threshold to obtain the real motion behavior-related features. In general, the motion feature weight coefficient of the patient must be calculated using parameters such as intensity and amplitude. The patient’s human behavior movements are described to convey the significance of the patient’s human motion feature. SupposeMj is the intensity parameter of the patient’s human motion characteristics, M0 is the motion amplitude parameter of human motion characteristics, and Q is the number of human motion characteristics. Calculate the threshold change parameter: (1)SMDS=M1+M2QT.In the process of patients’ rehabilitation training, the importance of motor function intensity parameters is higher than that of motion amplitude parameters. Therefore, they must be given different weight coefficients [20, 21]. By setting the weight coefficient proportion in the golden section mode, formula (1) can be transformed to obtain(2)SMDS=20.618Mj+0.382M0Mj+M0.In formula (2), SMDS represents the parameter of threshold change, which can map the patient rehabilitation data to the range of 0,1. The mapping formula is represented by(3)x=1−expSMDS.In formula (3), χ represents the influence of the threshold change parameters on the threshold. Assuming that the duration of the patient’s human motion is Ue and the total duration of human motion is Us, the characteristics of the motion time are smoothed to eliminate the error, and the threshold can be expressed by(4)ε=βUe+Us1+χ.If the characteristic parameter of human motion in the process of rehabilitation is greater than the threshold, it can be judged that the feature is the real motion feature of the human body.
### 4.2. Optimizing the Data Mining Process of Human Motor Function Rehabilitation
Through the nonlinear classification function, the data mining of human motion function rehabilitation monitoring can be realized based on extracting the human motion characteristics of patients. Let the set composed of human motion characteristics of patients be described byyj,zj,zj∈1,−1, and the classification function be expressed by(5)gy=x•y+c.If the classification interval of patient rehabilitation monitoring data is the maximum, the requirements of the following formula must be met:(6)zjx•y+c−1≥0,j=1,2,…,p.The solution of the optimal classification function can be expressed by(7)γx=12x=12x•x.The Lagrange factor is introduced into the classification function of patients’ human motor function rehabilitation monitoring, and the function represented by the following formula can be obtained:(8)Mx,c,b=12x•x−∑j=1pbjzjx•y+c−1.It is concluded that the classification function of human motion characteristics in the process of patient rehabilitation monitoring can be expressed as(9)gy=sgn∑j=1pbj∗zjyj•y+c∗.According to the above classification function of patients’ human motion features, patients’ human motion features can be divided into different categories of motion feature sets [22, 23]. According to these characteristics, the motor function data mining process in the process of patient rehabilitation monitoring can be described by(10)gy=sgn∑j=1pbj∗expy−yj2ε2+c∗.In the process of human motion mining of patients’ human motion function rehabilitation monitoring data, the most important problem is how to select scientific parameters. If the parameters are not scientific, it will have a great impact on the accuracy of human motion mining results [24, 25]. Therefore, we must optimize the penalty coefficient and the width of the kernel function through the radial basis kernel function. According to the optimized results, the optimal rehabilitation effect of human motor function is obtained, and the research on human motor function rehabilitation monitoring system based on data mining is completed.
## 4.1. Motion Feature Extraction
Some of the patient’s human motion features are deleted based on the threshold to obtain the real motion behavior-related features. In general, the motion feature weight coefficient of the patient must be calculated using parameters such as intensity and amplitude. The patient’s human behavior movements are described to convey the significance of the patient’s human motion feature. SupposeMj is the intensity parameter of the patient’s human motion characteristics, M0 is the motion amplitude parameter of human motion characteristics, and Q is the number of human motion characteristics. Calculate the threshold change parameter: (1)SMDS=M1+M2QT.In the process of patients’ rehabilitation training, the importance of motor function intensity parameters is higher than that of motion amplitude parameters. Therefore, they must be given different weight coefficients [20, 21]. By setting the weight coefficient proportion in the golden section mode, formula (1) can be transformed to obtain(2)SMDS=20.618Mj+0.382M0Mj+M0.In formula (2), SMDS represents the parameter of threshold change, which can map the patient rehabilitation data to the range of 0,1. The mapping formula is represented by(3)x=1−expSMDS.In formula (3), χ represents the influence of the threshold change parameters on the threshold. Assuming that the duration of the patient’s human motion is Ue and the total duration of human motion is Us, the characteristics of the motion time are smoothed to eliminate the error, and the threshold can be expressed by(4)ε=βUe+Us1+χ.If the characteristic parameter of human motion in the process of rehabilitation is greater than the threshold, it can be judged that the feature is the real motion feature of the human body.
## 4.2. Optimizing the Data Mining Process of Human Motor Function Rehabilitation
Through the nonlinear classification function, the data mining of human motion function rehabilitation monitoring can be realized based on extracting the human motion characteristics of patients. Let the set composed of human motion characteristics of patients be described byyj,zj,zj∈1,−1, and the classification function be expressed by(5)gy=x•y+c.If the classification interval of patient rehabilitation monitoring data is the maximum, the requirements of the following formula must be met:(6)zjx•y+c−1≥0,j=1,2,…,p.The solution of the optimal classification function can be expressed by(7)γx=12x=12x•x.The Lagrange factor is introduced into the classification function of patients’ human motor function rehabilitation monitoring, and the function represented by the following formula can be obtained:(8)Mx,c,b=12x•x−∑j=1pbjzjx•y+c−1.It is concluded that the classification function of human motion characteristics in the process of patient rehabilitation monitoring can be expressed as(9)gy=sgn∑j=1pbj∗zjyj•y+c∗.According to the above classification function of patients’ human motion features, patients’ human motion features can be divided into different categories of motion feature sets [22, 23]. According to these characteristics, the motor function data mining process in the process of patient rehabilitation monitoring can be described by(10)gy=sgn∑j=1pbj∗expy−yj2ε2+c∗.In the process of human motion mining of patients’ human motion function rehabilitation monitoring data, the most important problem is how to select scientific parameters. If the parameters are not scientific, it will have a great impact on the accuracy of human motion mining results [24, 25]. Therefore, we must optimize the penalty coefficient and the width of the kernel function through the radial basis kernel function. According to the optimized results, the optimal rehabilitation effect of human motor function is obtained, and the research on human motor function rehabilitation monitoring system based on data mining is completed.
## 5. Experimental Result and Analysis
Experiment verification is used to demonstrate the performance of the human motion function rehabilitation monitoring system based on data mining. Table2 shows the experimental environment of the rehabilitation monitoring system.Table 2
Experimental environment of the rehabilitation monitoring system.
TypeExperimental environmentThe operating systemWindows 7 (64 bits)Development platformUnity3D, Visual Studio (2017)Development of languageC++Memory4 GB (gigabyte)Figure5 shows the mining error comparison between the human motion function rehabilitation monitoring method based on motion feature data mining proposed in this paper and the human motion function rehabilitation monitoring method based on traditional data mining.Figure 5
Comparison of mining errors of different mining methods.Figure5 shows that at the start of the experiment, the mining error of the traditional data mining human motion function rehabilitation monitoring method was 29%. However, as the amount of data increases, the mining error gradually increases, reaching 42% before beginning to decline. Traditional data mining has a high overall error rate, resulting in poor data mining accuracy. At the start of the experiment, the mining error of the human motion function rehabilitation monitoring method based on motion features proposed in this paper was low. Although data increases slightly, the overall increase does not exceed 10%. This shows that the mining accuracy of the method proposed in this paper is high enough to effectively mine important patient information. They assist doctors in understanding the rehabilitation situations of patients so they can adjust the rehabilitation scheme for patients and improve the rehabilitation effect of patients during the rehabilitation monitoring process. The mining times of the motion feature data mining-based human motion function rehabilitation monitoring method and the traditional data mining-based human motion function rehabilitation monitoring method are compared in Table 3.Table 3
Comparison of mining time of different mining methods.
Different methodsMining time (s)Proposed methods15Traditional method47It can be seen from Table3 that the time of traditional data mining methods in mining human motor function rehabilitation data is 47 s while the time required to mine human motor function rehabilitation data using the action feature data mining method proposed in this paper is 15 s. This shows how using the method outlined in this paper can effectively increase the effectiveness of data mining and assist medical professionals in quickly analyzing patient rehabilitation monitoring data. The human motion function rehabilitation monitoring system of the method suggested in this paper and the human motion function rehabilitation monitoring system are compared in real time in Figure 6.Figure 6
Comparison of the real-time performance of rehabilitation monitoring systems under different methods.The analysis of Figure6 shows that the real-time performance of the human motor function rehabilitation monitoring system of the method proposed in the document is not high as a whole [3]. The real-time performance gradually increases with the increase of data at the beginning of the experiment. The real-time performance of the proposed human motion function rehabilitation monitoring system in the document gradually improves, but then declines when the experimental data reaches 1000 [4]. Throughout the experiment, the real-time performance of the human motion function rehabilitation monitoring system proposed in this paper was excellent. This is because this system uses data mining to monitor the rehabilitation training process for patients with human motion dysfunction. To understand the effect of rehabilitation training on patients in real time, we must first master the effect of rehabilitation training under objective data. The human motion function rehabilitation monitoring system of the method suggested in this paper and the human motion function rehabilitation monitoring system are compared in terms of overall performance in Figure 7.Figure 7
Overall performance comparison of rehabilitation monitoring systems under different methods.Figure7 shows that the overall performance of the human motor function rehabilitation monitoring system was better at the start of the experiment, but began to deteriorate as the data volume increased. At the start of the experiment, the overall performance of the human motor function rehabilitation monitoring system was slightly lower. This paper presented the overall performance that improved gradually as experimental data increased, but system performance was slightly significantly underrepresented in comparison with the rehabilitation monitoring system. The more stable overall performance of the data mining-based monitoring system for human motor function rehabilitation presented in this paper is because the data mining method presented in this paper classifies human motor features through a nonlinear classification function, which enables the mining of human motor function rehabilitation monitoring.
## 6. Conclusions
Human motion recognition research is expected to show that motion recognition is improved by human motion recognition. Human motion recognition science is progressing, and new technologies to improve our daily lives are emerging. This paper presented the design of a data-mining monitoring system for the restoration of human motor function. As the number of people suffering from human motor dysfunction as a result of illnesses such as stroke rises, this can be used in rehabilitation therapy. Relevant studies have shown that the use of scientific rehabilitation training can restore the damaged human motor function of patients to a great extent. In the process of rehabilitation training, rehabilitation doctors should monitor the physiological information of patients in real time. This paper uses data mining techniques to design and implement a human motion function rehabilitation monitoring system to meet this demand. This system enables timely evaluation of the training effect of patients’ rehabilitation as well as timely modification of the rehabilitation plan. The system processes and analyzes the physiological information of patients to improve the effectiveness of rehabilitation training. The results of the experiments show that the human motion function rehabilitation monitoring system suggested in this research has good overall performance. This significantly improves the system’s real-time performance and patient rehabilitation effectiveness. Although the system works well, it will be improved to increase battery life, reduce sensor size and weight, and improve the temporal synchronization of various sensor signals. The proposed system will be a component of a networked rehabilitation system that will also include sensors and rehabilitation robotics [26].
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*Source: 2901812-2022-08-04.xml* | 2901812-2022-08-04_2901812-2022-08-04.md | 41,593 | A Human Motion Function Rehabilitation Monitoring System Based on Data Mining | Xiaojing Chen | Scientific Programming
(2022) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2901812 | 2901812-2022-08-04.xml | ---
## Abstract
Human motion interaction technologies have evolved to a new level with the development of traditional reality technology as science and technology have developed. Fully interactive and human motion interaction technologies are becoming more common in fields such as medical rehabilitation and military simulations. Human motion is at the heart of all activity, and motion analysis and human motion are critical theoretical disciplines. Identification is based on behavior and motion in human motion, with attributes such as effectiveness, intelligence, potent interaction, and rich expression data. When studying human movement, many researchers now prefer this method. However, this study was conducted with insufficient suggestions for real-time human motion function assessment, rehabilitation, and improvement. The development of an information monitoring system for human motion function rehabilitation can be used to evaluate the efficacy of patient rehabilitation training. A human motion function rehabilitation monitoring system is created using an effective and thorough design methodology. The system is made up of the rehabilitation monitoring terminal, the human motion function monitoring module, and the medical center monitoring system. Therefore, the motion-based data mining technique is better for the human motion function rehabilitation monitoring system. The normalized proportion of motion features will assist in the creation of a database for human motion mining. The nonlinear classification function is used in this paper to scientifically categorize human motion features to implement data mining techniques for monitoring human motion function rehabilitation. The effectiveness of patient rehabilitation is significantly increased by the use of a human motion-based rehabilitation monitoring system.
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## Body
## 1. Introduction
A patient may be required to complete a comprehensive and important physical rehabilitation program to regain their prior strength, flexibility, and fitness after some kind of illness, injury, or surgery. The primary goal is to evaluate and optimize the patients' lifetime capabilities and motion qualities, and it is standard procedure in this environment to continuously monitor the patients' movements. In rehabilitation facilities, traditional physiotherapy-based treatments are frequently used; these treatments indicate the need for qualified professionals and their invaluable competence [1]. The standardized, objective data necessary to fairly assess patients' accomplishments might not be present in these treatments. Since the 1980s, there has been an increase in patients with motor function problems, which has made human motion tracking for rehabilitation a popular research topic. Humans must move their bodies in order to survive, and healthy people move their bodies frequently, while sick people move their bodies much less frequently. Stroke, one of the leading causes of disability in the world, frequently results in a limb or limbs losing all or some of their performance as a result of motor dysfunction [2]. In recent years, neurorehabilitation medicine research has advanced gradually, and the general public has assumed that damaged human motor function could be partially restored. Using scientific rehabilitation techniques could result in complete paralysis, low stamina, loss of motor control, or muscle weakness. On the other hand, looking for an effective rehabilitation treatment method to assist the patient in regaining human motor function will be counterproductive. It not only helps to improve the standard of living for patients but also reduces the burden on their families and society [3]. The overarching functional design scheme of the human motor function rehabilitation monitoring system clarifies the particular design plan of the subsystem. The monitoring terminal for rehabilitation, the human motor function monitoring module, and the monitoring system for the medical facility are also included in the composition.Through trials, information on plantar pressure under different motion modes and details on the current gait were acquired. Li et al. are now using fuzzy mathematics theory to characterize human behavior. The significant gait events, such as the contact of the leg and foot, were identified using dynamic baseline monitoring. The screening windows are used to filter the repeated individual monitoring over a specified period for the error monitoring of vital gait events, significantly improving identification accuracy and supplying essential gait data for the categorization of movement patterns. The viability and effectiveness of the fuzzy theory application for human motion identification are established by performing similarities comparisons on each pattern, the relevant levels of motion extraction features, and the relevant levels of motion pattern recognition. Artificial intelligence is expected to provide processing approaches and research projects to meet future demand [4]. Villanueva et al. describe a wearable multisensor system for monitoring human movement in stroke rehabilitation. It is composed of several teeny-tiny modules that can wirelessly connect and transmit motion-related data to an acquisition device. It is beneficial for human motion collecting and monitoring, which is required for activities such as activity detection, measuring physical and athletic performance, and rehabilitation, and according to the results of a series of experiments, we evaluated its performance in real-world environments [5]. Banaee et al. investigated the most cutting-edge methods and algorithms for interpreting data from smart technology used for physiologic monitoring of vital signs in healthcare services in a recent publication. The paper provides an overview of the more popular data mining applications, such as intrusion detection systems, prediction, and decision making, with an emphasis on continuous time-series observations. The study also discusses the suitability of specific data mining and machine learning algorithms used to evaluate the physiological data and provides an overview of the features of the data sets used in experimental verification. Several key challenges for data mining approaches in health monitoring systems have been identified based on this literature review [6].Rehabilitation training is a method of brain plasticity rehabilitation treatment, and the findings of modern neurorehabilitation medicine and associated studies show that. For human motor dysfunction caused by problems such as stroke, adopting scientific rehabilitation training treatment modalities can effectively recover the damaged human motor function to a corresponding extent. Rehabilitation physicians must conduct a real-time objective evaluation of the effect of rehabilitation training on patients during the rehabilitation training process. Accurately assess motor recovery ability as well as training participation, and effectively adjust the feedback scheme of rehabilitation training based on the evaluation results. The efficiency of rehabilitation training is improved, and the effect of rehabilitation is maximized. The process of analyzing and extracting information from large datasets is called data mining. It is important to use a data mining method to monitor the rehabilitation training process for patients with human motor dysfunction and deep understanding. The effect of rehabilitation training under objective data is significant in terms of improving the effectiveness of rehabilitation treatment for patients. The overall functional design scheme of the human motor function rehabilitation monitoring system clarifies the subsystem’s specific design scheme. The rehabilitation monitoring terminal, the human motor function monitoring module, and the medical center monitoring system are all part of this system.The innovation of this paper is as follows:(i)
Firstly, the data mining method based on motor features was applied to the human motor function rehabilitation monitoring system, and human motor function rehabilitation monitoring data mining was realized(ii)
Secondly, in comparison with the traditional monitoring system of human motor function rehabilitation, the data mining-based monitoring system of human motor function rehabilitation is presented(iii)
Finally, overall performance improved both the real-time performance of the human motor function rehabilitation monitoring system and the effect of patient rehabilitation trainingThe remainder of the paper is structured logically as follows: Section2 shows related work; Section 3 represents the human motion function rehabilitation monitoring system based on data mining; Section 4 demonstrates the human motion function rehabilitation monitoring method based on motion characteristics, and Section 5 shows the experimental results and analysis. Finally, Section 6 concluded this work.
## 2. Related Work
In the early years, relevant researchers at home and abroad began to conduct in-depth research on human physiological parameters and rehabilitation monitoring, and they achieved some research results through their efforts. Li et al. proposed a monitoring system for human remote rehabilitation training, which provides a remote rehabilitation training monitoring platform for patients in rehabilitation. The terminal-controlled module processor is a 32-bit STMicroelectronics (STM32) integrated circuit that controls data acquisition, processing, and transmission. Complete the communication between the acquisition device and the cloud server during the rehabilitation process using the Message Queuing Telemetry Transport (MQTT) protocol. Analyze the time-frequency domain of electromyography (EMG) signal to calculate the specific situation of muscle strength and muscle fatigue and calculate the activity of human joints from the signal of attitude sensor for rehabilitation evaluation of rehabilitation training. To complete the interaction between the browser and the cloud server, use the Tomcat server to display the patient’s rehabilitation data on the web page. However, remote rehabilitation training monitoring, uploading, and the mointoring system need help to discharge stroke patients for rehabilitation treatment and early recurrence warnings. A multifunctional human motor function rehabilitation monitoring system was created, which included human physiological signals, treatment, and data analysis. The therapeutic device uses transcranial direct current stimulation technology to accurately output constant and direct current. The patient’s heart rate and other pertinent data are then routinely monitored by the intelligent bracelet, which is created as an adjunct rehabilitation monitoring device. Send the rehabilitation data to the mobile phone via Bluetooth, and then use the mobile phone to summarize the treatment records and vital signs data before uploading the summarized data to the cloud for in-depth analysis. It is specifically used to adjust the rehabilitation treatment plan or for early warning of stroke recurrence. The development results show that the monitoring system can not only meet the needs of human motor function rehabilitation treatment but also realize the interconnection between cloud and equipment. The system can provide effective solutions for personalized treatment of stroke, recurrence early warning, and database, but the system has the problem of high cost [7]. Yang et al. describe a human rehabilitation monitoring system based on an embedded controller designed to meet the needs of human postoperative recovery training. A multifunction human rehabilitation training mode, movement posture, EMG signal acquisition, and safety protection are realized. The training process is identified and analyzed by using the random forest machine learning method and linear regression method. The results show that the designed human rehabilitation control and monitoring system can use Android for portable control. To complete the intelligent analysis of the rehabilitation training process, use the monitoring signals in the training process. The random forest method has advantages over the linear regression method in human motion recognition, but the rehabilitation effect of this method is poor [8]. Guan et al. propose a human rehabilitation movement monitoring method based on human posture information to control rehabilitation training for patients with human motor dysfunction after surgery. It is a data collection system for human motion data that is customized to the structural characteristics and functional requirements of rehabilitated patients. The kinematic model of human rehabilitation is built, and a behavior information collection system for human posture is established on the rehabilitation platform. The software evaluates the expected follow-up speed of rehabilitation based on the behavior change information representing human posture obtained from the displacement analysis sensor. To reduce the error generated, the tracking controller is designed using the fuzzy control method and a simulation experiment. However, this method has the problem of poor real-time performance in the process of patients’ real-time tracking movement and realization of the following effect of rehabilitation on patients’ motion posture [9].
## 3. Human Motion Function Rehabilitation Monitoring System Based on Data Mining
Figure1 depicts the overall framework of the human motor function rehabilitation monitoring system. The data mining-based human motion function rehabilitation monitoring system is primarily composed of a large number of collection nodes for physiological parameters worn by patients. A self-organized wireless network is established between the nodes, and the physiological parameter signals are transmitted to the convergence node of the wireless network through the Zonal Intercommunication Global (ZigBee) protocol. ZigBee is a low-power, low-data-rate M2M (machine-to-machine) wireless network and Internet-of-Things (IoT). The ZigBee protocol is based on IEEE 802.15.4. A ZigBee network is made up of several full-function devices (FFD) that gather data from nearby reduced-function devices (RFD).Figure 1
Overall frame diagram of the rehabilitation monitoring system.The local monitoring system consists of embedded portable devices connected to a wireless network, with a sink node collecting physiological data. The main purpose of the medical center’s monitoring system is to create a database of multiple physiological parameters of patients and extract them. Identify patients’ physiological and psychological states and evaluate patients’ rehabilitation effects in real time [10, 11].
### 3.1. Design of Rehabilitation Monitoring Terminal System
Figure2 shows the composition of the rehabilitation monitoring terminal system. The physiological parameter acquisition module and the data transmission module are included in the design of the rehabilitation monitoring terminal system. The physiological parameter acquisition module is a multiparameter physiological module that measures and monitors heart rate, noninvasive blood pressure, respiration, oxygen saturation, temperature, and Enteric Coated (EC). The acquisition module of physiological parameters must install the node in the appropriate position of the patient’s body to collect the patient’s human physiological signals. The selection of physiological signals is mainly divided into collecting electromyography (EMG), electrocardiography (ECG), pulse, and triaxial acceleration. In the node design of hardware, medical sensors and methods for specific physiological signals and signal conditioning circuits such as filtering are composed [12, 13].Figure 2
Rehabilitation monitoring terminal system composition diagram.The rehabilitation data transmission module in the hardware platform makes use of data communication between network nodes and the iris node. The integrated processing chip of the node is the controller and the radiofrequency (RF) chip is the wireless transceiver. The tiny operating system and network cable network routing protocol design are used in the software implementation. The designed networking application is added to the control chip of each node, which can realize the rehabilitation data transmission between wireless nodes, as well as some characteristics such as low-power consumption, load balancing, and robustness.
### 3.2. Human Motor Function Rehabilitation Monitoring Module
Figure3 shows the composition of human motor function rehabilitation monitoring. The unit hardware of the monitoring module is an embedded operating system using the processor core board of the Advanced RISC Machine (ARM9). The software realizes the terminal node data collection, processing, and storage of rehabilitation data and provides the user interface for images for patients. It uploads the collected rehabilitation training data to the medical monitoring center. The local monitoring system module specifically includes embedded transplantation and multiple modules such as data acquisition, data storage, display unit, and network communication [14, 15].Figure 3
Local monitoring system composition diagram.The rehabilitation training data acquisition module serves as the interface between the network node and the ARM processor, and it must analyze various physiological data types. The node collects data using the serial communication protocol, and data processing is the core module in the local monitoring system. It must process and store various physiological signals collected from patients, as well as various control instructions received from the display unit, which is a designed monitoring interface. In the development environment, a graphical interface primarily displays the collected human physiological signals of patients in the form of a real-time dynamic curve. The network communication module is a bridge connecting the local monitoring system and the monitoring system of the medical center. The module adopts Transmission Control Protocol (TCP) and realizes the sending and receiving of rehabilitation data through the socket communication model design.
### 3.3. Medical Center Monitoring System
Figure4 shows the composition of the monitoring system of the medical center. The medical center’s monitoring system is built on the Client/Server framework, which consists of monitoring software for both the server and the client. The server realizes the communication with the local monitoring system and client monitoring software, as well as the storage and processing of rehabilitation data. It specifically includes multiple modules such as network communication, user information management, and ecological parameter monitoring [16, 17].Figure 4
Composition of the medical center monitoring system.The communication server is built based on the TCP, connected with a socket, receives the link from the online local monitoring system and the analysis data packet of the communication protocol, and stores it in the database. The data processing module includes data analysis, preliminary diagnosis, data storage, and so on. The physiological parameters are mined by a data mining algorithm, and the physiological features are extracted and preliminarily diagnosed. The processed data is stored in the database for query and call by the monitoring software of the client. User information management mainly saves the patient’s personal information and physiological data. The monitoring module of physiological parameters uses the call database to obtain the physiological data of patients and displays electrocardiogram (ECG), muscle point, pulse, and other signals in the form of a waveform curve. It is also capable of monitoring physiological parameters. It will provide an early warning if a patient’s physiological parameters exceed the set threshold [18, 19].
### 3.4. Data Frame
The data frame defines the format of the data packet when transmitting rehabilitation data, including the destination node, source node, and the length of the data packet. The specific format of the data frame is shown in Table1.Table 1
Data frame format of the terminal node.
The field namesLength (bytes)Tiny OS Header6Xmesh Header8Xsensor Header5Data Payload17CRC2
## 3.1. Design of Rehabilitation Monitoring Terminal System
Figure2 shows the composition of the rehabilitation monitoring terminal system. The physiological parameter acquisition module and the data transmission module are included in the design of the rehabilitation monitoring terminal system. The physiological parameter acquisition module is a multiparameter physiological module that measures and monitors heart rate, noninvasive blood pressure, respiration, oxygen saturation, temperature, and Enteric Coated (EC). The acquisition module of physiological parameters must install the node in the appropriate position of the patient’s body to collect the patient’s human physiological signals. The selection of physiological signals is mainly divided into collecting electromyography (EMG), electrocardiography (ECG), pulse, and triaxial acceleration. In the node design of hardware, medical sensors and methods for specific physiological signals and signal conditioning circuits such as filtering are composed [12, 13].Figure 2
Rehabilitation monitoring terminal system composition diagram.The rehabilitation data transmission module in the hardware platform makes use of data communication between network nodes and the iris node. The integrated processing chip of the node is the controller and the radiofrequency (RF) chip is the wireless transceiver. The tiny operating system and network cable network routing protocol design are used in the software implementation. The designed networking application is added to the control chip of each node, which can realize the rehabilitation data transmission between wireless nodes, as well as some characteristics such as low-power consumption, load balancing, and robustness.
## 3.2. Human Motor Function Rehabilitation Monitoring Module
Figure3 shows the composition of human motor function rehabilitation monitoring. The unit hardware of the monitoring module is an embedded operating system using the processor core board of the Advanced RISC Machine (ARM9). The software realizes the terminal node data collection, processing, and storage of rehabilitation data and provides the user interface for images for patients. It uploads the collected rehabilitation training data to the medical monitoring center. The local monitoring system module specifically includes embedded transplantation and multiple modules such as data acquisition, data storage, display unit, and network communication [14, 15].Figure 3
Local monitoring system composition diagram.The rehabilitation training data acquisition module serves as the interface between the network node and the ARM processor, and it must analyze various physiological data types. The node collects data using the serial communication protocol, and data processing is the core module in the local monitoring system. It must process and store various physiological signals collected from patients, as well as various control instructions received from the display unit, which is a designed monitoring interface. In the development environment, a graphical interface primarily displays the collected human physiological signals of patients in the form of a real-time dynamic curve. The network communication module is a bridge connecting the local monitoring system and the monitoring system of the medical center. The module adopts Transmission Control Protocol (TCP) and realizes the sending and receiving of rehabilitation data through the socket communication model design.
## 3.3. Medical Center Monitoring System
Figure4 shows the composition of the monitoring system of the medical center. The medical center’s monitoring system is built on the Client/Server framework, which consists of monitoring software for both the server and the client. The server realizes the communication with the local monitoring system and client monitoring software, as well as the storage and processing of rehabilitation data. It specifically includes multiple modules such as network communication, user information management, and ecological parameter monitoring [16, 17].Figure 4
Composition of the medical center monitoring system.The communication server is built based on the TCP, connected with a socket, receives the link from the online local monitoring system and the analysis data packet of the communication protocol, and stores it in the database. The data processing module includes data analysis, preliminary diagnosis, data storage, and so on. The physiological parameters are mined by a data mining algorithm, and the physiological features are extracted and preliminarily diagnosed. The processed data is stored in the database for query and call by the monitoring software of the client. User information management mainly saves the patient’s personal information and physiological data. The monitoring module of physiological parameters uses the call database to obtain the physiological data of patients and displays electrocardiogram (ECG), muscle point, pulse, and other signals in the form of a waveform curve. It is also capable of monitoring physiological parameters. It will provide an early warning if a patient’s physiological parameters exceed the set threshold [18, 19].
## 3.4. Data Frame
The data frame defines the format of the data packet when transmitting rehabilitation data, including the destination node, source node, and the length of the data packet. The specific format of the data frame is shown in Table1.Table 1
Data frame format of the terminal node.
The field namesLength (bytes)Tiny OS Header6Xmesh Header8Xsensor Header5Data Payload17CRC2
## 4. Human Motion Function Rehabilitation Monitoring Method Based on Motion Characteristics
There is a close relationship between human motion characteristics and human actions. It is necessary to analyze the importance of human motion characteristics from the direction of human motion. We will talk about the characteristic threshold of patients’ human motion.
### 4.1. Motion Feature Extraction
Some of the patient’s human motion features are deleted based on the threshold to obtain the real motion behavior-related features. In general, the motion feature weight coefficient of the patient must be calculated using parameters such as intensity and amplitude. The patient’s human behavior movements are described to convey the significance of the patient’s human motion feature. SupposeMj is the intensity parameter of the patient’s human motion characteristics, M0 is the motion amplitude parameter of human motion characteristics, and Q is the number of human motion characteristics. Calculate the threshold change parameter: (1)SMDS=M1+M2QT.In the process of patients’ rehabilitation training, the importance of motor function intensity parameters is higher than that of motion amplitude parameters. Therefore, they must be given different weight coefficients [20, 21]. By setting the weight coefficient proportion in the golden section mode, formula (1) can be transformed to obtain(2)SMDS=20.618Mj+0.382M0Mj+M0.In formula (2), SMDS represents the parameter of threshold change, which can map the patient rehabilitation data to the range of 0,1. The mapping formula is represented by(3)x=1−expSMDS.In formula (3), χ represents the influence of the threshold change parameters on the threshold. Assuming that the duration of the patient’s human motion is Ue and the total duration of human motion is Us, the characteristics of the motion time are smoothed to eliminate the error, and the threshold can be expressed by(4)ε=βUe+Us1+χ.If the characteristic parameter of human motion in the process of rehabilitation is greater than the threshold, it can be judged that the feature is the real motion feature of the human body.
### 4.2. Optimizing the Data Mining Process of Human Motor Function Rehabilitation
Through the nonlinear classification function, the data mining of human motion function rehabilitation monitoring can be realized based on extracting the human motion characteristics of patients. Let the set composed of human motion characteristics of patients be described byyj,zj,zj∈1,−1, and the classification function be expressed by(5)gy=x•y+c.If the classification interval of patient rehabilitation monitoring data is the maximum, the requirements of the following formula must be met:(6)zjx•y+c−1≥0,j=1,2,…,p.The solution of the optimal classification function can be expressed by(7)γx=12x=12x•x.The Lagrange factor is introduced into the classification function of patients’ human motor function rehabilitation monitoring, and the function represented by the following formula can be obtained:(8)Mx,c,b=12x•x−∑j=1pbjzjx•y+c−1.It is concluded that the classification function of human motion characteristics in the process of patient rehabilitation monitoring can be expressed as(9)gy=sgn∑j=1pbj∗zjyj•y+c∗.According to the above classification function of patients’ human motion features, patients’ human motion features can be divided into different categories of motion feature sets [22, 23]. According to these characteristics, the motor function data mining process in the process of patient rehabilitation monitoring can be described by(10)gy=sgn∑j=1pbj∗expy−yj2ε2+c∗.In the process of human motion mining of patients’ human motion function rehabilitation monitoring data, the most important problem is how to select scientific parameters. If the parameters are not scientific, it will have a great impact on the accuracy of human motion mining results [24, 25]. Therefore, we must optimize the penalty coefficient and the width of the kernel function through the radial basis kernel function. According to the optimized results, the optimal rehabilitation effect of human motor function is obtained, and the research on human motor function rehabilitation monitoring system based on data mining is completed.
## 4.1. Motion Feature Extraction
Some of the patient’s human motion features are deleted based on the threshold to obtain the real motion behavior-related features. In general, the motion feature weight coefficient of the patient must be calculated using parameters such as intensity and amplitude. The patient’s human behavior movements are described to convey the significance of the patient’s human motion feature. SupposeMj is the intensity parameter of the patient’s human motion characteristics, M0 is the motion amplitude parameter of human motion characteristics, and Q is the number of human motion characteristics. Calculate the threshold change parameter: (1)SMDS=M1+M2QT.In the process of patients’ rehabilitation training, the importance of motor function intensity parameters is higher than that of motion amplitude parameters. Therefore, they must be given different weight coefficients [20, 21]. By setting the weight coefficient proportion in the golden section mode, formula (1) can be transformed to obtain(2)SMDS=20.618Mj+0.382M0Mj+M0.In formula (2), SMDS represents the parameter of threshold change, which can map the patient rehabilitation data to the range of 0,1. The mapping formula is represented by(3)x=1−expSMDS.In formula (3), χ represents the influence of the threshold change parameters on the threshold. Assuming that the duration of the patient’s human motion is Ue and the total duration of human motion is Us, the characteristics of the motion time are smoothed to eliminate the error, and the threshold can be expressed by(4)ε=βUe+Us1+χ.If the characteristic parameter of human motion in the process of rehabilitation is greater than the threshold, it can be judged that the feature is the real motion feature of the human body.
## 4.2. Optimizing the Data Mining Process of Human Motor Function Rehabilitation
Through the nonlinear classification function, the data mining of human motion function rehabilitation monitoring can be realized based on extracting the human motion characteristics of patients. Let the set composed of human motion characteristics of patients be described byyj,zj,zj∈1,−1, and the classification function be expressed by(5)gy=x•y+c.If the classification interval of patient rehabilitation monitoring data is the maximum, the requirements of the following formula must be met:(6)zjx•y+c−1≥0,j=1,2,…,p.The solution of the optimal classification function can be expressed by(7)γx=12x=12x•x.The Lagrange factor is introduced into the classification function of patients’ human motor function rehabilitation monitoring, and the function represented by the following formula can be obtained:(8)Mx,c,b=12x•x−∑j=1pbjzjx•y+c−1.It is concluded that the classification function of human motion characteristics in the process of patient rehabilitation monitoring can be expressed as(9)gy=sgn∑j=1pbj∗zjyj•y+c∗.According to the above classification function of patients’ human motion features, patients’ human motion features can be divided into different categories of motion feature sets [22, 23]. According to these characteristics, the motor function data mining process in the process of patient rehabilitation monitoring can be described by(10)gy=sgn∑j=1pbj∗expy−yj2ε2+c∗.In the process of human motion mining of patients’ human motion function rehabilitation monitoring data, the most important problem is how to select scientific parameters. If the parameters are not scientific, it will have a great impact on the accuracy of human motion mining results [24, 25]. Therefore, we must optimize the penalty coefficient and the width of the kernel function through the radial basis kernel function. According to the optimized results, the optimal rehabilitation effect of human motor function is obtained, and the research on human motor function rehabilitation monitoring system based on data mining is completed.
## 5. Experimental Result and Analysis
Experiment verification is used to demonstrate the performance of the human motion function rehabilitation monitoring system based on data mining. Table2 shows the experimental environment of the rehabilitation monitoring system.Table 2
Experimental environment of the rehabilitation monitoring system.
TypeExperimental environmentThe operating systemWindows 7 (64 bits)Development platformUnity3D, Visual Studio (2017)Development of languageC++Memory4 GB (gigabyte)Figure5 shows the mining error comparison between the human motion function rehabilitation monitoring method based on motion feature data mining proposed in this paper and the human motion function rehabilitation monitoring method based on traditional data mining.Figure 5
Comparison of mining errors of different mining methods.Figure5 shows that at the start of the experiment, the mining error of the traditional data mining human motion function rehabilitation monitoring method was 29%. However, as the amount of data increases, the mining error gradually increases, reaching 42% before beginning to decline. Traditional data mining has a high overall error rate, resulting in poor data mining accuracy. At the start of the experiment, the mining error of the human motion function rehabilitation monitoring method based on motion features proposed in this paper was low. Although data increases slightly, the overall increase does not exceed 10%. This shows that the mining accuracy of the method proposed in this paper is high enough to effectively mine important patient information. They assist doctors in understanding the rehabilitation situations of patients so they can adjust the rehabilitation scheme for patients and improve the rehabilitation effect of patients during the rehabilitation monitoring process. The mining times of the motion feature data mining-based human motion function rehabilitation monitoring method and the traditional data mining-based human motion function rehabilitation monitoring method are compared in Table 3.Table 3
Comparison of mining time of different mining methods.
Different methodsMining time (s)Proposed methods15Traditional method47It can be seen from Table3 that the time of traditional data mining methods in mining human motor function rehabilitation data is 47 s while the time required to mine human motor function rehabilitation data using the action feature data mining method proposed in this paper is 15 s. This shows how using the method outlined in this paper can effectively increase the effectiveness of data mining and assist medical professionals in quickly analyzing patient rehabilitation monitoring data. The human motion function rehabilitation monitoring system of the method suggested in this paper and the human motion function rehabilitation monitoring system are compared in real time in Figure 6.Figure 6
Comparison of the real-time performance of rehabilitation monitoring systems under different methods.The analysis of Figure6 shows that the real-time performance of the human motor function rehabilitation monitoring system of the method proposed in the document is not high as a whole [3]. The real-time performance gradually increases with the increase of data at the beginning of the experiment. The real-time performance of the proposed human motion function rehabilitation monitoring system in the document gradually improves, but then declines when the experimental data reaches 1000 [4]. Throughout the experiment, the real-time performance of the human motion function rehabilitation monitoring system proposed in this paper was excellent. This is because this system uses data mining to monitor the rehabilitation training process for patients with human motion dysfunction. To understand the effect of rehabilitation training on patients in real time, we must first master the effect of rehabilitation training under objective data. The human motion function rehabilitation monitoring system of the method suggested in this paper and the human motion function rehabilitation monitoring system are compared in terms of overall performance in Figure 7.Figure 7
Overall performance comparison of rehabilitation monitoring systems under different methods.Figure7 shows that the overall performance of the human motor function rehabilitation monitoring system was better at the start of the experiment, but began to deteriorate as the data volume increased. At the start of the experiment, the overall performance of the human motor function rehabilitation monitoring system was slightly lower. This paper presented the overall performance that improved gradually as experimental data increased, but system performance was slightly significantly underrepresented in comparison with the rehabilitation monitoring system. The more stable overall performance of the data mining-based monitoring system for human motor function rehabilitation presented in this paper is because the data mining method presented in this paper classifies human motor features through a nonlinear classification function, which enables the mining of human motor function rehabilitation monitoring.
## 6. Conclusions
Human motion recognition research is expected to show that motion recognition is improved by human motion recognition. Human motion recognition science is progressing, and new technologies to improve our daily lives are emerging. This paper presented the design of a data-mining monitoring system for the restoration of human motor function. As the number of people suffering from human motor dysfunction as a result of illnesses such as stroke rises, this can be used in rehabilitation therapy. Relevant studies have shown that the use of scientific rehabilitation training can restore the damaged human motor function of patients to a great extent. In the process of rehabilitation training, rehabilitation doctors should monitor the physiological information of patients in real time. This paper uses data mining techniques to design and implement a human motion function rehabilitation monitoring system to meet this demand. This system enables timely evaluation of the training effect of patients’ rehabilitation as well as timely modification of the rehabilitation plan. The system processes and analyzes the physiological information of patients to improve the effectiveness of rehabilitation training. The results of the experiments show that the human motion function rehabilitation monitoring system suggested in this research has good overall performance. This significantly improves the system’s real-time performance and patient rehabilitation effectiveness. Although the system works well, it will be improved to increase battery life, reduce sensor size and weight, and improve the temporal synchronization of various sensor signals. The proposed system will be a component of a networked rehabilitation system that will also include sensors and rehabilitation robotics [26].
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*Source: 2901812-2022-08-04.xml* | 2022 |
# Digital Art Design Effectiveness Model System Based on K-Medoids Algorithm
**Authors:** Xin Luo
**Journal:** Advances in Multimedia
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2901815
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## Abstract
With the development of the times, figurative expressions no longer meet the creative needs of artists and the aesthetic demands of the people. In order to express art in a more profound way, the perfect use of abstract graphics plays a crucial role in the success of the work. In recent years, there has been a surge in the creation of digital art, but there is relatively little theoretical literature on the combination of abstract graphics as a visual language and digital art. In addition, research on the theoretical aspects of digital art design is also relatively weak, so it is essential to analyse the formal aesthetics and innovative applications. In fact, digital art design has a very important role to play in promoting the development of creative cultural industries. In other words, the healthy development of digital art design can influence the future prospects of a country’s creative and cultural industries. Digital art design is an integrated and complex production process and labour outcome. In addition to its human, aesthetic, and social value, digital art also has an economic value. Digital art is a new art form that combines digital technology and artistic aesthetics. As such, digital art is characterised by high technology, diverse forms, popularised art, and the advantages of high communication, interactivity, and influence, which can provide more assistance for the innovation and application of abstract graphics. Digital art is multifaceted and has an artistic expression that cannot be matched by other forms of technology. Abstract graphics, driven by digital art, are full of novelty and interest and can greatly enrich people’s emotions and senses. Abstract graphics bring the experience of digital art to its fullest potential. The combination of digital art and abstract graphics offers more innovation and possibilities for the development of art and will bring great prosperity to art communication. With the widespread use of computer and network technology, the Internet has developed rapidly. In this context, digital art, as art created in a digital way and concept, has gained widespread attention. As a result, how to integrate existing computer resources in the new environment to build a model of digital art design effectiveness will cause a direct influence on the quality of digital art design with digital content innovation as the core. At the same time, as digital art becomes more and more popular, the demand for digital talents becomes very urgent. As a result, the cultivation of high-quality digital talents has become a major concern for society. Therefore, in order to explore the success of digital art design and the cultivation of digital art talents, and to better serve the innovation of digital art, this paper proposes a digital art effectiveness model based on the K-medoids algorithm. This model can provide a deeper and more comprehensive understanding of digital art and abstract graphics and provide theoretical support for professional design creation.
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## Body
## 1. Introduction
Digital art design belongs to a new field that has emerged from a high degree of integration between science technology and art [1]. According to its characteristics, digital art design can be divided into two different levels: computer graphics technology [2] and art design [3]. Digital art in a broad sense is digital art. Digital art in a narrow sense generally refers to the use of computers to process or produce art-related designs, animations, audio-visuals, or other works of art [4]. In the early twentieth century, with the development of modern information technology and the rapid spread of computers, society entered a fully digital age. The use of various algorithms and mathematical models, such as machine learning [5, 6], text recognition [7, 8], and total life cycle assessment [9, 10], can accelerate the development of computer technology. In this context, the rapid development of scientific and industrial technology is increasingly contributing to artistic expression. This has led to the formation of modern art, video art, and design art [11]. The interpenetration of these three separate art forms has led to the formation of a new aesthetic ideology in the form of postmodernism, which has given rise to digital art.Digital art is a comprehensive field that encompasses several disciplines. To be specific, digital art is an integrated form of artistic communication that encompasses art, sociology, technology, and aesthetics as well as popular culture [12]. As a result, digital art is a disciplinary synthesis of natural, social, technological, and humanistic disciplines and is a new type of discipline in which digital technology and art intersect. Considering the mass art, reproducible and commercial nature of digital art has accelerated the spread of digital art and has led to a trend towards the visualisation and graphicisation of art and culture in the direction of popularisation [13]. The wide application of computers, driven by digital technology, has expanded the means of creating works of art [14]. At the same time, the constant development of digital technology has also led to changes in the development of abstract graphics. Many disciplines between art and science, such as graphic design, costume design, and environmental design, have been broadened by the influence of modern digital information technology [15]. Correspondingly, the field of design has also undergone a quantitative to qualitative change, rising to a whole new level. Art is constantly evolving towards science, and science is gradually being transformed into art [16]. As a result, with the development of the times, figurative expressions are no longer sufficient to meet the creative needs of artists and the aesthetic demands of people. The combination of digital art and abstract graphics has created a different visual and aesthetic experience than before [17, 18]. The use of abstract graphics in digital art has played a crucial role in the development of the arts. People’s interest and enthusiasm for digital art are expanding, and it is becoming an integral part of life today, making it the most favourable time to develop digital art [19].As shown in Figure1, digital art design is a cross-cutting field and is a unique industry that is a composite of at least three industries. Firstly, it is an industry supported by the information technology industry [20]. Secondly, it is an industry with its roots in cultural industries [21]. Finally, it is an industry driven by creative industries [22]. The information industry is a collective term for industries engaged in the production of information technology, information services, information equipment, and products in the context of socioeconomic activities [23]. The cultural industries are those activities that deal mainly with activities based on symbolic goods, the economic value of which is derived from their cultural value. Creative industries are those industries that have the potential to generate wealth and employment through the generation and development of intellectual property, derived from the creativity, skills, and talents of individuals [24]. An industry that is a combination of these three industries is a creative cultural industry. To be specific, it refers to the industry that can create and enhance cultural resources with the help of high technology and can generate high value-added products through the development and application of intellectual property rights [25, 26]. As a result, digital art design is the core component of the entrepreneurial cultural industry, and its quantity and quality are directly related to the competitiveness of the creative cultural industry.Figure 1
Component of digital art design industry.The main characteristics of digital art design are the following. Firstly, digital art design has a strong commodity character [27]. Commodity means that digital art design is a labour product and a labour product for exchange. This is a characteristic common to all cultural products that are produced in large batches by large machines [28]. The result of digital art design can therefore be considered as a means of earning a living for the designer, a commodity ready for exchange. As a result, it is quite reasonable to consider the result of the designer’s labour for exchange to be a commodity. It is the commodity nature of digital art design that has led to a further exploration of its value components on this basis [29]. In addition to this, digital art design is extremely easy to reproduce. The ease of reproduction of digital art design means that it can be reproduced quickly using advanced technology. The ease of reproduction is a function of the difficulty of conceptualising and creating the work in advance. The more advanced the technology is, the easier and cheaper it becomes to reproduce [30]. The history of mankind has gone through a period of manual reproduction, a period of mechanical reproduction, and a period of digital reproduction. Digital reproduction has both advantages and disadvantages. Specifically, it can provide the creative industries with a timely, rapid, and inexpensive means of distribution, allowing creative cultural products based on digital art and design to be sold worldwide, regardless of geography.Graphics emerged as human society developed. As early as primitive society, graphics were used as a way to record information about life in a figurative way [31]. As societies became more social, people began to use graphics as a way to record and transmit information more easily, eventually evolving into writing. However, the changes in social production and the great wealth of material culture have led to a significant change in the aesthetics of graphic art [32]. Concrete representations were no longer sufficient to meet people’s aesthetic needs, so abstract graphics, which are highly refined and simplified summaries of real things, were created. The term abstraction was first used to refer to the philosophical idea of the ability to integrate concepts by discarding concrete details in thought. The original meaning of abstraction is to extract the most critical and representative elements of a real thing and to simplify them to form a conceptual symbol without detracting from the essence of the thing. Abstract shapes are generally formed by combining geometric forms such as points, lines, and surfaces, reconstructing and abstracting figurative objects to create a simple and powerful graphic representation [33]. The essence of abstract graphics is the simplification and generalisation of figurative objects, and the simplicity of expression is the mode of thinking and expression that abstract graphics have always followed. Abstract graphics were born out of the desire to use symbolic metaphors to broaden the viewer’s imagination [17]. To a certain extent, the abstract form of representation can be free from the constraints of the abstracted object. To be specific, the artist can add his subjective imagination to the abstraction, combining the points, lines, and surfaces of the abstraction in an orderly or disorderly manner, thus enriching the meaning and connotation of the work itself. At the same time, abstract graphic design has the advantage and characteristic of being rich in form, free, and independent. It has a strong visual symbolism. By using abstract geometric structures and line elements to represent figurative objects, the form can be highly summarised and the viewer can easily associate it with the meaning it conveys.This study focuses on the development and application of the digital art and design effectiveness model based on the standard development methodology of the K-medoids algorithm. In order to develop the model, it is necessary to implement a data centre platform, a portal platform, a unified authentication subsystem, and an application integration platform in the digital management information system. As a result, the development and application of this system can greatly enhance the management of digital art and design and provide a basis for innovation.
## 2. Cluster Analysis
As a typical unsupervised division-based clustering algorithm, K-medoids has the advantages of simple clustering idea, high feasibility of clustering process, and near-linear time complexity of clustering. At the same time, the K-medoids algorithm can also show good technical support for complex data mining, so it has been developed rapidly in many industries. In the field of digital art design, the K-medoids algorithm has also been widely applied. In addition, the K-medoids algorithm is a common data mining method. It is an unsupervised algorithm that classifies data points with the same class and common attributes into the same class. In the same class, the similarity of the clustered objects is high. Conversely, in different classes, the similarity of the clustered objects is very low. With this classification method, more accurate classes can be obtained than with the K-means method.
### 2.1. K-Means Algorithm
Cluster analysis techniques are widely used in various fields and have been improved for different applications. At the same time, cluster analysis techniques allow for the development of corresponding algorithms and models. Broadly speaking, these methods can be classified as lattices, hierarchies, densities, and delineation methods. In the era of big data, structured and semistructured data resources are growing rapidly and users are searching for information in a wider and wider range. The introduction of cluster analysis technology can effectively improve the classification of similar information, so that individuals in the same class have a high degree of homogeneity. This technique allows for a high degree of heterogeneity between individuals in different categories, thus effectively increasing the accuracy of the user’s information.One of the traditional clustering algorithms is the K-means algorithm. The detailed process of the K-means algorithm can be seen in Figure2. The division-based clustering starts by specifying the number of clusters k. Assuming that the sample contains m data objects, k<m. Then k initial centroids are selected from the data sample and iterated until the initial threshold is met.Figure 2
Detailed process of the K-means algorithm.The corresponding target value function is shown in(1)T=∑i=1k∑d∈xid−μi22.where the existing data set is D=d1,d2,...,dm, the class cluster result after conducting the K-means algorithm is X=x1,x2,…,xk, and μi refers to the mean value.There are two types of hierarchical clustering: cohesive hierarchical clustering and split hierarchical clustering. The former starts at the bottom, where each data sample is initially in one class and then continues to merge the least distant clusters to form new clusters. The algorithm ends when all the data belong to a single cluster or when a certain end condition is reached. The latter takes a cluster that includes all the data as a starting point and splits it into a number of subclusters. Each subcluster continues to split downwards until eventually each cluster contains only one data element, as illustrated in Figure3.Figure 3
Process of hierarchical clustering.
### 2.2. K-Medoids Algorithm
The K-medoids clustering algorithm is a division-based clustering method. Compared to K-means, the K-medoids algorithm is easier to implement and has better convergence and time complexity. As a result, the K-medoids algorithm can give better results when searching globally.The K-medoids algorithm divides them data objects into k classes as reference centres for clustering. The data objects that are not classified into classes are then classified into neighbouring clusters according to the distance priority principle. The K-medoids clustering algorithm is based on the principle of optimality of the clustering criterion function, using the object closest to the cluster centre as the class centre. As a result, this algorithm can significantly enhance robustness and is relatively effective for small data sets.Among thek clusters that are eligible in the output, the effect of clustering is usually measured using an absolute error standard function, defined by(2)A=∑i=1k∑z∈ciz−ci2,where z refers to the object of the cluster ci.Thus, the detailed process of the K-medoids algorithm can be seen in Figure4.Figure 4
Detailed process of the K-medoids algorithm.The K-medoids clustering algorithm is able to obtain more desirable classification results by repeatedly calculating and updating the mean value of the objects around the cluster centroids in the clustering process. In the design process of digital art, this approach is utilised to produce initial classes by categorising different art resources in aggregate through categories and other means. The K-medoids clustering algorithm is then used to cluster and analyse the feature codes of knowledge until the classes converge.In the feature extraction phase, the knowledge information that has not yet been determined by the classification during the training process is expressed according to the feature vector of knowledge information as follows:(3)I=b1,b2,⋯,bnT,where bn refers to the nth information in the digital art design process.After that, the classification of the knowledge information to be classified and the training set is calculated according to the vector angle cosine formula, as shown in(4)simI,Ii=∑k=1nzkzik∑k=1nzk2∑k=1nzik2.Also, the principle of using the vector angle cosine can be seen in Figure5.Figure 5
Principle of using the vector angle cosine.The K-medoids algorithm takes the centroid that makes the total difference function negative as the new class centre each time a new centroid is selected, based on calculating the difference between the sum of the squares of the distances from all data points in the original class to the class centre and the sum of the squares of the distances from all data points to the new centroid after replacement. This approach can effectively avoid the influence of the algorithm on outliers and is highly robust. At the same time, the clustering results are independent of the order in which the data object points are entered, so the clustering method also has the advantages of data object translation and orthogonal transformation invariance.
### 2.3. Experimental Analysis
In order to ensure the effectiveness of the experiments, the content of digital art design is analysed in order to reduce the dimensionality of the calculations. The experiments are carried out using the method proposed in this paper. The data set is derived from a database of digital art and design provided by a company, with 10 categories. Four of these categories are selected for this study: painting, clothing, sketching, and music. The experimental data are shown in Table1.Table 1
Experimental data of digital art design.
CategoryPaintingClothingSketchingMusicTraining set287305214563Testing set194143176324Total number481448390887After applying the K-medoids algorithm, the classification result can be seen in Table2.Table 2
Classification result.
ValueP valueR-valueFI-value876.477.273.51279.778.174.21584.282.180.51975.173.471.92176.275.874.6From Table2, it can be seen that when the value is 15, P value, R-value, and FI-value reach their maximum value, suggesting that the clustering effect is optimal at this point.
## 2.1. K-Means Algorithm
Cluster analysis techniques are widely used in various fields and have been improved for different applications. At the same time, cluster analysis techniques allow for the development of corresponding algorithms and models. Broadly speaking, these methods can be classified as lattices, hierarchies, densities, and delineation methods. In the era of big data, structured and semistructured data resources are growing rapidly and users are searching for information in a wider and wider range. The introduction of cluster analysis technology can effectively improve the classification of similar information, so that individuals in the same class have a high degree of homogeneity. This technique allows for a high degree of heterogeneity between individuals in different categories, thus effectively increasing the accuracy of the user’s information.One of the traditional clustering algorithms is the K-means algorithm. The detailed process of the K-means algorithm can be seen in Figure2. The division-based clustering starts by specifying the number of clusters k. Assuming that the sample contains m data objects, k<m. Then k initial centroids are selected from the data sample and iterated until the initial threshold is met.Figure 2
Detailed process of the K-means algorithm.The corresponding target value function is shown in(1)T=∑i=1k∑d∈xid−μi22.where the existing data set is D=d1,d2,...,dm, the class cluster result after conducting the K-means algorithm is X=x1,x2,…,xk, and μi refers to the mean value.There are two types of hierarchical clustering: cohesive hierarchical clustering and split hierarchical clustering. The former starts at the bottom, where each data sample is initially in one class and then continues to merge the least distant clusters to form new clusters. The algorithm ends when all the data belong to a single cluster or when a certain end condition is reached. The latter takes a cluster that includes all the data as a starting point and splits it into a number of subclusters. Each subcluster continues to split downwards until eventually each cluster contains only one data element, as illustrated in Figure3.Figure 3
Process of hierarchical clustering.
## 2.2. K-Medoids Algorithm
The K-medoids clustering algorithm is a division-based clustering method. Compared to K-means, the K-medoids algorithm is easier to implement and has better convergence and time complexity. As a result, the K-medoids algorithm can give better results when searching globally.The K-medoids algorithm divides them data objects into k classes as reference centres for clustering. The data objects that are not classified into classes are then classified into neighbouring clusters according to the distance priority principle. The K-medoids clustering algorithm is based on the principle of optimality of the clustering criterion function, using the object closest to the cluster centre as the class centre. As a result, this algorithm can significantly enhance robustness and is relatively effective for small data sets.Among thek clusters that are eligible in the output, the effect of clustering is usually measured using an absolute error standard function, defined by(2)A=∑i=1k∑z∈ciz−ci2,where z refers to the object of the cluster ci.Thus, the detailed process of the K-medoids algorithm can be seen in Figure4.Figure 4
Detailed process of the K-medoids algorithm.The K-medoids clustering algorithm is able to obtain more desirable classification results by repeatedly calculating and updating the mean value of the objects around the cluster centroids in the clustering process. In the design process of digital art, this approach is utilised to produce initial classes by categorising different art resources in aggregate through categories and other means. The K-medoids clustering algorithm is then used to cluster and analyse the feature codes of knowledge until the classes converge.In the feature extraction phase, the knowledge information that has not yet been determined by the classification during the training process is expressed according to the feature vector of knowledge information as follows:(3)I=b1,b2,⋯,bnT,where bn refers to the nth information in the digital art design process.After that, the classification of the knowledge information to be classified and the training set is calculated according to the vector angle cosine formula, as shown in(4)simI,Ii=∑k=1nzkzik∑k=1nzk2∑k=1nzik2.Also, the principle of using the vector angle cosine can be seen in Figure5.Figure 5
Principle of using the vector angle cosine.The K-medoids algorithm takes the centroid that makes the total difference function negative as the new class centre each time a new centroid is selected, based on calculating the difference between the sum of the squares of the distances from all data points in the original class to the class centre and the sum of the squares of the distances from all data points to the new centroid after replacement. This approach can effectively avoid the influence of the algorithm on outliers and is highly robust. At the same time, the clustering results are independent of the order in which the data object points are entered, so the clustering method also has the advantages of data object translation and orthogonal transformation invariance.
## 2.3. Experimental Analysis
In order to ensure the effectiveness of the experiments, the content of digital art design is analysed in order to reduce the dimensionality of the calculations. The experiments are carried out using the method proposed in this paper. The data set is derived from a database of digital art and design provided by a company, with 10 categories. Four of these categories are selected for this study: painting, clothing, sketching, and music. The experimental data are shown in Table1.Table 1
Experimental data of digital art design.
CategoryPaintingClothingSketchingMusicTraining set287305214563Testing set194143176324Total number481448390887After applying the K-medoids algorithm, the classification result can be seen in Table2.Table 2
Classification result.
ValueP valueR-valueFI-value876.477.273.51279.778.174.21584.282.180.51975.173.471.92176.275.874.6From Table2, it can be seen that when the value is 15, P value, R-value, and FI-value reach their maximum value, suggesting that the clustering effect is optimal at this point.
## 3. Digital Art Design Effectiveness Model
### 3.1. Demand Analysis
The main difference between digital art and design and other fields is that there is no single model. In other words, it is a complex systemic project that integrates creativity, research, and development. It includes not only design foundations, design concepts, and design skills, but also the development of practical skills such as hands-on production. This is why the user should be given priority when designing effective models for digital art and design. Figure6 summarizes the four main role objects in the digital art design effectiveness model.Figure 6
Four main role objects in the digital art design effectiveness model.
### 3.2. Analysis of Model Operating Environment
The model runs on a standard server, which needs to be set up as a web server and database server. When a certain number of users access the system at the same time, the server is able to keep the system running and provide the services required by each user. In addition, users need to access the server via the network. Therefore, only the user side and the server side are connected to the LAN and the server is accessed via the LAN, which ensures both speed and network security.Combining the advantages and disadvantages of C/S and B/S, this model uses a combination of C/S and B/S architecture. For example, for the database, a B/S web application environment is used for the data query service. The C/S web application environment is used to run on the campus network. As a result, the overall structure of the digital art design effectiveness model is shown in Figure7.Figure 7
Structure of the digital art design effectiveness model.C/S mode applications can be developed with client-side applications according to the actual situation. If the client has a high processing power, more tasks can be implemented on the client side. If the network communication conditions are good and the server computing performance is high, then more computing operations can be implemented on the server side. For example, some management information systems based on the C/S model even integrate all functions on the server side, where most of the processing tasks such as data access, logical operations, data storage, and control of the system’s business processes are realised. This leads to a surge in network access, which needs to be supported by good network conditions. With the server as the focus of the entire system, the server is slow to respond and may even become “jammed” when a large number of users access the server at the same time. Due to the difficulties of synchronising data in a C/S structure, the use of a C/S structure for the entire digital art and design effectiveness model will result in inefficient operation. However, the C/S structure can share some of the transaction processing requirements and can handle more complex business processes. Therefore, the digital art and design effectiveness model proposed in this study adopts a C/S architecture for the implementation of some core modules that need to handle complex business.
### 3.3. Principle of Digital Art Design Effectiveness Model
In the formal digital art and design environment, learning tasks are set in accordance with the content or requirements of the model and are required to be completed by the designer. The designer is a passive participant, whereas the activity is something that the designer needs to actively engage in to complete. As a result, the designer can develop their own creative style and form at the right time when working with digital art design. In addition to this, the designer’s role, access to tools and resources, and the resultant outcomes should be given appropriate internal links when creating digital art.It is also important to note that, with the creation of digital art, creating online has become a focus of research. What is unique about online creation compared to traditional design models is that it has to reflect both the centrality of the designer and the special aspects of the online environment in the design of the activity. When designing online, special attention is paid to the following aspects. For example, the design of a designer-centred online platform, the provision of design tools, resources and technical support, and the creation of learning contexts in which designers can flexibly apply their knowledge.
## 3.1. Demand Analysis
The main difference between digital art and design and other fields is that there is no single model. In other words, it is a complex systemic project that integrates creativity, research, and development. It includes not only design foundations, design concepts, and design skills, but also the development of practical skills such as hands-on production. This is why the user should be given priority when designing effective models for digital art and design. Figure6 summarizes the four main role objects in the digital art design effectiveness model.Figure 6
Four main role objects in the digital art design effectiveness model.
## 3.2. Analysis of Model Operating Environment
The model runs on a standard server, which needs to be set up as a web server and database server. When a certain number of users access the system at the same time, the server is able to keep the system running and provide the services required by each user. In addition, users need to access the server via the network. Therefore, only the user side and the server side are connected to the LAN and the server is accessed via the LAN, which ensures both speed and network security.Combining the advantages and disadvantages of C/S and B/S, this model uses a combination of C/S and B/S architecture. For example, for the database, a B/S web application environment is used for the data query service. The C/S web application environment is used to run on the campus network. As a result, the overall structure of the digital art design effectiveness model is shown in Figure7.Figure 7
Structure of the digital art design effectiveness model.C/S mode applications can be developed with client-side applications according to the actual situation. If the client has a high processing power, more tasks can be implemented on the client side. If the network communication conditions are good and the server computing performance is high, then more computing operations can be implemented on the server side. For example, some management information systems based on the C/S model even integrate all functions on the server side, where most of the processing tasks such as data access, logical operations, data storage, and control of the system’s business processes are realised. This leads to a surge in network access, which needs to be supported by good network conditions. With the server as the focus of the entire system, the server is slow to respond and may even become “jammed” when a large number of users access the server at the same time. Due to the difficulties of synchronising data in a C/S structure, the use of a C/S structure for the entire digital art and design effectiveness model will result in inefficient operation. However, the C/S structure can share some of the transaction processing requirements and can handle more complex business processes. Therefore, the digital art and design effectiveness model proposed in this study adopts a C/S architecture for the implementation of some core modules that need to handle complex business.
## 3.3. Principle of Digital Art Design Effectiveness Model
In the formal digital art and design environment, learning tasks are set in accordance with the content or requirements of the model and are required to be completed by the designer. The designer is a passive participant, whereas the activity is something that the designer needs to actively engage in to complete. As a result, the designer can develop their own creative style and form at the right time when working with digital art design. In addition to this, the designer’s role, access to tools and resources, and the resultant outcomes should be given appropriate internal links when creating digital art.It is also important to note that, with the creation of digital art, creating online has become a focus of research. What is unique about online creation compared to traditional design models is that it has to reflect both the centrality of the designer and the special aspects of the online environment in the design of the activity. When designing online, special attention is paid to the following aspects. For example, the design of a designer-centred online platform, the provision of design tools, resources and technical support, and the creation of learning contexts in which designers can flexibly apply their knowledge.
## 4. Conclusion
The application of computers in digital technology has expanded the channels of artistic expression, and the change in artistic thinking in the context of digital technology has led to changes in the development of abstract graphics. Digital art is a combination of natural and social disciplines, technology, and the humanities and is a new discipline that combines digital technology and art. The combination of abstract graphics and digital technology allows for the creation of works full of novelty and interest. In the context of digital art, the fusion of information and big data has begun to visualise abstract graphic information. Combined with augmented reality technology, the senses interact with virtual reality in real time. The combination of abstract graphics as a visual language for digital art expression and digital technology is highly integrated and has significantly changed the traditional use of graphics production, design thinking, and aesthetic thinking. Digital art, as a different form of art from the traditional ones, has the characteristics and advantages of being high-tech, high-impact, and highly interactive. As a result, digital art can be used to express a wide range of subjects in a multitude of ways. The multifaceted use of digital art reflects the emotional resonance, digital information, and humanistic concepts in a modern context. The concept of abstract graphics in digital art is transformed from an objective to a more subjective expression of the subject matter, with design thinking becoming more experimental and beginning to explore the future and the unknown in greater depth.The digital art design effectiveness model designed for this study has a relatively good overall plan. And the model can be well combined with the K-medoids algorithm so that the data shared between modules can be clustered and analysed. However, the specific implementation of each module’s functionality is relatively straightforward, with the implementation focusing on the more commonly used functions. However, the development of this model is essentially a prototype development approach, but one that is different from the prototype development approach. The requirements and planning for the model were completed prior to development and only some of the functionality was not code-specifically implemented. The model will be refined and improved as it is used.
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*Source: 2901815-2022-07-06.xml* | 2901815-2022-07-06_2901815-2022-07-06.md | 37,567 | Digital Art Design Effectiveness Model System Based on K-Medoids Algorithm | Xin Luo | Advances in Multimedia
(2022) | Computer Science | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2901815 | 2901815-2022-07-06.xml | ---
## Abstract
With the development of the times, figurative expressions no longer meet the creative needs of artists and the aesthetic demands of the people. In order to express art in a more profound way, the perfect use of abstract graphics plays a crucial role in the success of the work. In recent years, there has been a surge in the creation of digital art, but there is relatively little theoretical literature on the combination of abstract graphics as a visual language and digital art. In addition, research on the theoretical aspects of digital art design is also relatively weak, so it is essential to analyse the formal aesthetics and innovative applications. In fact, digital art design has a very important role to play in promoting the development of creative cultural industries. In other words, the healthy development of digital art design can influence the future prospects of a country’s creative and cultural industries. Digital art design is an integrated and complex production process and labour outcome. In addition to its human, aesthetic, and social value, digital art also has an economic value. Digital art is a new art form that combines digital technology and artistic aesthetics. As such, digital art is characterised by high technology, diverse forms, popularised art, and the advantages of high communication, interactivity, and influence, which can provide more assistance for the innovation and application of abstract graphics. Digital art is multifaceted and has an artistic expression that cannot be matched by other forms of technology. Abstract graphics, driven by digital art, are full of novelty and interest and can greatly enrich people’s emotions and senses. Abstract graphics bring the experience of digital art to its fullest potential. The combination of digital art and abstract graphics offers more innovation and possibilities for the development of art and will bring great prosperity to art communication. With the widespread use of computer and network technology, the Internet has developed rapidly. In this context, digital art, as art created in a digital way and concept, has gained widespread attention. As a result, how to integrate existing computer resources in the new environment to build a model of digital art design effectiveness will cause a direct influence on the quality of digital art design with digital content innovation as the core. At the same time, as digital art becomes more and more popular, the demand for digital talents becomes very urgent. As a result, the cultivation of high-quality digital talents has become a major concern for society. Therefore, in order to explore the success of digital art design and the cultivation of digital art talents, and to better serve the innovation of digital art, this paper proposes a digital art effectiveness model based on the K-medoids algorithm. This model can provide a deeper and more comprehensive understanding of digital art and abstract graphics and provide theoretical support for professional design creation.
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## Body
## 1. Introduction
Digital art design belongs to a new field that has emerged from a high degree of integration between science technology and art [1]. According to its characteristics, digital art design can be divided into two different levels: computer graphics technology [2] and art design [3]. Digital art in a broad sense is digital art. Digital art in a narrow sense generally refers to the use of computers to process or produce art-related designs, animations, audio-visuals, or other works of art [4]. In the early twentieth century, with the development of modern information technology and the rapid spread of computers, society entered a fully digital age. The use of various algorithms and mathematical models, such as machine learning [5, 6], text recognition [7, 8], and total life cycle assessment [9, 10], can accelerate the development of computer technology. In this context, the rapid development of scientific and industrial technology is increasingly contributing to artistic expression. This has led to the formation of modern art, video art, and design art [11]. The interpenetration of these three separate art forms has led to the formation of a new aesthetic ideology in the form of postmodernism, which has given rise to digital art.Digital art is a comprehensive field that encompasses several disciplines. To be specific, digital art is an integrated form of artistic communication that encompasses art, sociology, technology, and aesthetics as well as popular culture [12]. As a result, digital art is a disciplinary synthesis of natural, social, technological, and humanistic disciplines and is a new type of discipline in which digital technology and art intersect. Considering the mass art, reproducible and commercial nature of digital art has accelerated the spread of digital art and has led to a trend towards the visualisation and graphicisation of art and culture in the direction of popularisation [13]. The wide application of computers, driven by digital technology, has expanded the means of creating works of art [14]. At the same time, the constant development of digital technology has also led to changes in the development of abstract graphics. Many disciplines between art and science, such as graphic design, costume design, and environmental design, have been broadened by the influence of modern digital information technology [15]. Correspondingly, the field of design has also undergone a quantitative to qualitative change, rising to a whole new level. Art is constantly evolving towards science, and science is gradually being transformed into art [16]. As a result, with the development of the times, figurative expressions are no longer sufficient to meet the creative needs of artists and the aesthetic demands of people. The combination of digital art and abstract graphics has created a different visual and aesthetic experience than before [17, 18]. The use of abstract graphics in digital art has played a crucial role in the development of the arts. People’s interest and enthusiasm for digital art are expanding, and it is becoming an integral part of life today, making it the most favourable time to develop digital art [19].As shown in Figure1, digital art design is a cross-cutting field and is a unique industry that is a composite of at least three industries. Firstly, it is an industry supported by the information technology industry [20]. Secondly, it is an industry with its roots in cultural industries [21]. Finally, it is an industry driven by creative industries [22]. The information industry is a collective term for industries engaged in the production of information technology, information services, information equipment, and products in the context of socioeconomic activities [23]. The cultural industries are those activities that deal mainly with activities based on symbolic goods, the economic value of which is derived from their cultural value. Creative industries are those industries that have the potential to generate wealth and employment through the generation and development of intellectual property, derived from the creativity, skills, and talents of individuals [24]. An industry that is a combination of these three industries is a creative cultural industry. To be specific, it refers to the industry that can create and enhance cultural resources with the help of high technology and can generate high value-added products through the development and application of intellectual property rights [25, 26]. As a result, digital art design is the core component of the entrepreneurial cultural industry, and its quantity and quality are directly related to the competitiveness of the creative cultural industry.Figure 1
Component of digital art design industry.The main characteristics of digital art design are the following. Firstly, digital art design has a strong commodity character [27]. Commodity means that digital art design is a labour product and a labour product for exchange. This is a characteristic common to all cultural products that are produced in large batches by large machines [28]. The result of digital art design can therefore be considered as a means of earning a living for the designer, a commodity ready for exchange. As a result, it is quite reasonable to consider the result of the designer’s labour for exchange to be a commodity. It is the commodity nature of digital art design that has led to a further exploration of its value components on this basis [29]. In addition to this, digital art design is extremely easy to reproduce. The ease of reproduction of digital art design means that it can be reproduced quickly using advanced technology. The ease of reproduction is a function of the difficulty of conceptualising and creating the work in advance. The more advanced the technology is, the easier and cheaper it becomes to reproduce [30]. The history of mankind has gone through a period of manual reproduction, a period of mechanical reproduction, and a period of digital reproduction. Digital reproduction has both advantages and disadvantages. Specifically, it can provide the creative industries with a timely, rapid, and inexpensive means of distribution, allowing creative cultural products based on digital art and design to be sold worldwide, regardless of geography.Graphics emerged as human society developed. As early as primitive society, graphics were used as a way to record information about life in a figurative way [31]. As societies became more social, people began to use graphics as a way to record and transmit information more easily, eventually evolving into writing. However, the changes in social production and the great wealth of material culture have led to a significant change in the aesthetics of graphic art [32]. Concrete representations were no longer sufficient to meet people’s aesthetic needs, so abstract graphics, which are highly refined and simplified summaries of real things, were created. The term abstraction was first used to refer to the philosophical idea of the ability to integrate concepts by discarding concrete details in thought. The original meaning of abstraction is to extract the most critical and representative elements of a real thing and to simplify them to form a conceptual symbol without detracting from the essence of the thing. Abstract shapes are generally formed by combining geometric forms such as points, lines, and surfaces, reconstructing and abstracting figurative objects to create a simple and powerful graphic representation [33]. The essence of abstract graphics is the simplification and generalisation of figurative objects, and the simplicity of expression is the mode of thinking and expression that abstract graphics have always followed. Abstract graphics were born out of the desire to use symbolic metaphors to broaden the viewer’s imagination [17]. To a certain extent, the abstract form of representation can be free from the constraints of the abstracted object. To be specific, the artist can add his subjective imagination to the abstraction, combining the points, lines, and surfaces of the abstraction in an orderly or disorderly manner, thus enriching the meaning and connotation of the work itself. At the same time, abstract graphic design has the advantage and characteristic of being rich in form, free, and independent. It has a strong visual symbolism. By using abstract geometric structures and line elements to represent figurative objects, the form can be highly summarised and the viewer can easily associate it with the meaning it conveys.This study focuses on the development and application of the digital art and design effectiveness model based on the standard development methodology of the K-medoids algorithm. In order to develop the model, it is necessary to implement a data centre platform, a portal platform, a unified authentication subsystem, and an application integration platform in the digital management information system. As a result, the development and application of this system can greatly enhance the management of digital art and design and provide a basis for innovation.
## 2. Cluster Analysis
As a typical unsupervised division-based clustering algorithm, K-medoids has the advantages of simple clustering idea, high feasibility of clustering process, and near-linear time complexity of clustering. At the same time, the K-medoids algorithm can also show good technical support for complex data mining, so it has been developed rapidly in many industries. In the field of digital art design, the K-medoids algorithm has also been widely applied. In addition, the K-medoids algorithm is a common data mining method. It is an unsupervised algorithm that classifies data points with the same class and common attributes into the same class. In the same class, the similarity of the clustered objects is high. Conversely, in different classes, the similarity of the clustered objects is very low. With this classification method, more accurate classes can be obtained than with the K-means method.
### 2.1. K-Means Algorithm
Cluster analysis techniques are widely used in various fields and have been improved for different applications. At the same time, cluster analysis techniques allow for the development of corresponding algorithms and models. Broadly speaking, these methods can be classified as lattices, hierarchies, densities, and delineation methods. In the era of big data, structured and semistructured data resources are growing rapidly and users are searching for information in a wider and wider range. The introduction of cluster analysis technology can effectively improve the classification of similar information, so that individuals in the same class have a high degree of homogeneity. This technique allows for a high degree of heterogeneity between individuals in different categories, thus effectively increasing the accuracy of the user’s information.One of the traditional clustering algorithms is the K-means algorithm. The detailed process of the K-means algorithm can be seen in Figure2. The division-based clustering starts by specifying the number of clusters k. Assuming that the sample contains m data objects, k<m. Then k initial centroids are selected from the data sample and iterated until the initial threshold is met.Figure 2
Detailed process of the K-means algorithm.The corresponding target value function is shown in(1)T=∑i=1k∑d∈xid−μi22.where the existing data set is D=d1,d2,...,dm, the class cluster result after conducting the K-means algorithm is X=x1,x2,…,xk, and μi refers to the mean value.There are two types of hierarchical clustering: cohesive hierarchical clustering and split hierarchical clustering. The former starts at the bottom, where each data sample is initially in one class and then continues to merge the least distant clusters to form new clusters. The algorithm ends when all the data belong to a single cluster or when a certain end condition is reached. The latter takes a cluster that includes all the data as a starting point and splits it into a number of subclusters. Each subcluster continues to split downwards until eventually each cluster contains only one data element, as illustrated in Figure3.Figure 3
Process of hierarchical clustering.
### 2.2. K-Medoids Algorithm
The K-medoids clustering algorithm is a division-based clustering method. Compared to K-means, the K-medoids algorithm is easier to implement and has better convergence and time complexity. As a result, the K-medoids algorithm can give better results when searching globally.The K-medoids algorithm divides them data objects into k classes as reference centres for clustering. The data objects that are not classified into classes are then classified into neighbouring clusters according to the distance priority principle. The K-medoids clustering algorithm is based on the principle of optimality of the clustering criterion function, using the object closest to the cluster centre as the class centre. As a result, this algorithm can significantly enhance robustness and is relatively effective for small data sets.Among thek clusters that are eligible in the output, the effect of clustering is usually measured using an absolute error standard function, defined by(2)A=∑i=1k∑z∈ciz−ci2,where z refers to the object of the cluster ci.Thus, the detailed process of the K-medoids algorithm can be seen in Figure4.Figure 4
Detailed process of the K-medoids algorithm.The K-medoids clustering algorithm is able to obtain more desirable classification results by repeatedly calculating and updating the mean value of the objects around the cluster centroids in the clustering process. In the design process of digital art, this approach is utilised to produce initial classes by categorising different art resources in aggregate through categories and other means. The K-medoids clustering algorithm is then used to cluster and analyse the feature codes of knowledge until the classes converge.In the feature extraction phase, the knowledge information that has not yet been determined by the classification during the training process is expressed according to the feature vector of knowledge information as follows:(3)I=b1,b2,⋯,bnT,where bn refers to the nth information in the digital art design process.After that, the classification of the knowledge information to be classified and the training set is calculated according to the vector angle cosine formula, as shown in(4)simI,Ii=∑k=1nzkzik∑k=1nzk2∑k=1nzik2.Also, the principle of using the vector angle cosine can be seen in Figure5.Figure 5
Principle of using the vector angle cosine.The K-medoids algorithm takes the centroid that makes the total difference function negative as the new class centre each time a new centroid is selected, based on calculating the difference between the sum of the squares of the distances from all data points in the original class to the class centre and the sum of the squares of the distances from all data points to the new centroid after replacement. This approach can effectively avoid the influence of the algorithm on outliers and is highly robust. At the same time, the clustering results are independent of the order in which the data object points are entered, so the clustering method also has the advantages of data object translation and orthogonal transformation invariance.
### 2.3. Experimental Analysis
In order to ensure the effectiveness of the experiments, the content of digital art design is analysed in order to reduce the dimensionality of the calculations. The experiments are carried out using the method proposed in this paper. The data set is derived from a database of digital art and design provided by a company, with 10 categories. Four of these categories are selected for this study: painting, clothing, sketching, and music. The experimental data are shown in Table1.Table 1
Experimental data of digital art design.
CategoryPaintingClothingSketchingMusicTraining set287305214563Testing set194143176324Total number481448390887After applying the K-medoids algorithm, the classification result can be seen in Table2.Table 2
Classification result.
ValueP valueR-valueFI-value876.477.273.51279.778.174.21584.282.180.51975.173.471.92176.275.874.6From Table2, it can be seen that when the value is 15, P value, R-value, and FI-value reach their maximum value, suggesting that the clustering effect is optimal at this point.
## 2.1. K-Means Algorithm
Cluster analysis techniques are widely used in various fields and have been improved for different applications. At the same time, cluster analysis techniques allow for the development of corresponding algorithms and models. Broadly speaking, these methods can be classified as lattices, hierarchies, densities, and delineation methods. In the era of big data, structured and semistructured data resources are growing rapidly and users are searching for information in a wider and wider range. The introduction of cluster analysis technology can effectively improve the classification of similar information, so that individuals in the same class have a high degree of homogeneity. This technique allows for a high degree of heterogeneity between individuals in different categories, thus effectively increasing the accuracy of the user’s information.One of the traditional clustering algorithms is the K-means algorithm. The detailed process of the K-means algorithm can be seen in Figure2. The division-based clustering starts by specifying the number of clusters k. Assuming that the sample contains m data objects, k<m. Then k initial centroids are selected from the data sample and iterated until the initial threshold is met.Figure 2
Detailed process of the K-means algorithm.The corresponding target value function is shown in(1)T=∑i=1k∑d∈xid−μi22.where the existing data set is D=d1,d2,...,dm, the class cluster result after conducting the K-means algorithm is X=x1,x2,…,xk, and μi refers to the mean value.There are two types of hierarchical clustering: cohesive hierarchical clustering and split hierarchical clustering. The former starts at the bottom, where each data sample is initially in one class and then continues to merge the least distant clusters to form new clusters. The algorithm ends when all the data belong to a single cluster or when a certain end condition is reached. The latter takes a cluster that includes all the data as a starting point and splits it into a number of subclusters. Each subcluster continues to split downwards until eventually each cluster contains only one data element, as illustrated in Figure3.Figure 3
Process of hierarchical clustering.
## 2.2. K-Medoids Algorithm
The K-medoids clustering algorithm is a division-based clustering method. Compared to K-means, the K-medoids algorithm is easier to implement and has better convergence and time complexity. As a result, the K-medoids algorithm can give better results when searching globally.The K-medoids algorithm divides them data objects into k classes as reference centres for clustering. The data objects that are not classified into classes are then classified into neighbouring clusters according to the distance priority principle. The K-medoids clustering algorithm is based on the principle of optimality of the clustering criterion function, using the object closest to the cluster centre as the class centre. As a result, this algorithm can significantly enhance robustness and is relatively effective for small data sets.Among thek clusters that are eligible in the output, the effect of clustering is usually measured using an absolute error standard function, defined by(2)A=∑i=1k∑z∈ciz−ci2,where z refers to the object of the cluster ci.Thus, the detailed process of the K-medoids algorithm can be seen in Figure4.Figure 4
Detailed process of the K-medoids algorithm.The K-medoids clustering algorithm is able to obtain more desirable classification results by repeatedly calculating and updating the mean value of the objects around the cluster centroids in the clustering process. In the design process of digital art, this approach is utilised to produce initial classes by categorising different art resources in aggregate through categories and other means. The K-medoids clustering algorithm is then used to cluster and analyse the feature codes of knowledge until the classes converge.In the feature extraction phase, the knowledge information that has not yet been determined by the classification during the training process is expressed according to the feature vector of knowledge information as follows:(3)I=b1,b2,⋯,bnT,where bn refers to the nth information in the digital art design process.After that, the classification of the knowledge information to be classified and the training set is calculated according to the vector angle cosine formula, as shown in(4)simI,Ii=∑k=1nzkzik∑k=1nzk2∑k=1nzik2.Also, the principle of using the vector angle cosine can be seen in Figure5.Figure 5
Principle of using the vector angle cosine.The K-medoids algorithm takes the centroid that makes the total difference function negative as the new class centre each time a new centroid is selected, based on calculating the difference between the sum of the squares of the distances from all data points in the original class to the class centre and the sum of the squares of the distances from all data points to the new centroid after replacement. This approach can effectively avoid the influence of the algorithm on outliers and is highly robust. At the same time, the clustering results are independent of the order in which the data object points are entered, so the clustering method also has the advantages of data object translation and orthogonal transformation invariance.
## 2.3. Experimental Analysis
In order to ensure the effectiveness of the experiments, the content of digital art design is analysed in order to reduce the dimensionality of the calculations. The experiments are carried out using the method proposed in this paper. The data set is derived from a database of digital art and design provided by a company, with 10 categories. Four of these categories are selected for this study: painting, clothing, sketching, and music. The experimental data are shown in Table1.Table 1
Experimental data of digital art design.
CategoryPaintingClothingSketchingMusicTraining set287305214563Testing set194143176324Total number481448390887After applying the K-medoids algorithm, the classification result can be seen in Table2.Table 2
Classification result.
ValueP valueR-valueFI-value876.477.273.51279.778.174.21584.282.180.51975.173.471.92176.275.874.6From Table2, it can be seen that when the value is 15, P value, R-value, and FI-value reach their maximum value, suggesting that the clustering effect is optimal at this point.
## 3. Digital Art Design Effectiveness Model
### 3.1. Demand Analysis
The main difference between digital art and design and other fields is that there is no single model. In other words, it is a complex systemic project that integrates creativity, research, and development. It includes not only design foundations, design concepts, and design skills, but also the development of practical skills such as hands-on production. This is why the user should be given priority when designing effective models for digital art and design. Figure6 summarizes the four main role objects in the digital art design effectiveness model.Figure 6
Four main role objects in the digital art design effectiveness model.
### 3.2. Analysis of Model Operating Environment
The model runs on a standard server, which needs to be set up as a web server and database server. When a certain number of users access the system at the same time, the server is able to keep the system running and provide the services required by each user. In addition, users need to access the server via the network. Therefore, only the user side and the server side are connected to the LAN and the server is accessed via the LAN, which ensures both speed and network security.Combining the advantages and disadvantages of C/S and B/S, this model uses a combination of C/S and B/S architecture. For example, for the database, a B/S web application environment is used for the data query service. The C/S web application environment is used to run on the campus network. As a result, the overall structure of the digital art design effectiveness model is shown in Figure7.Figure 7
Structure of the digital art design effectiveness model.C/S mode applications can be developed with client-side applications according to the actual situation. If the client has a high processing power, more tasks can be implemented on the client side. If the network communication conditions are good and the server computing performance is high, then more computing operations can be implemented on the server side. For example, some management information systems based on the C/S model even integrate all functions on the server side, where most of the processing tasks such as data access, logical operations, data storage, and control of the system’s business processes are realised. This leads to a surge in network access, which needs to be supported by good network conditions. With the server as the focus of the entire system, the server is slow to respond and may even become “jammed” when a large number of users access the server at the same time. Due to the difficulties of synchronising data in a C/S structure, the use of a C/S structure for the entire digital art and design effectiveness model will result in inefficient operation. However, the C/S structure can share some of the transaction processing requirements and can handle more complex business processes. Therefore, the digital art and design effectiveness model proposed in this study adopts a C/S architecture for the implementation of some core modules that need to handle complex business.
### 3.3. Principle of Digital Art Design Effectiveness Model
In the formal digital art and design environment, learning tasks are set in accordance with the content or requirements of the model and are required to be completed by the designer. The designer is a passive participant, whereas the activity is something that the designer needs to actively engage in to complete. As a result, the designer can develop their own creative style and form at the right time when working with digital art design. In addition to this, the designer’s role, access to tools and resources, and the resultant outcomes should be given appropriate internal links when creating digital art.It is also important to note that, with the creation of digital art, creating online has become a focus of research. What is unique about online creation compared to traditional design models is that it has to reflect both the centrality of the designer and the special aspects of the online environment in the design of the activity. When designing online, special attention is paid to the following aspects. For example, the design of a designer-centred online platform, the provision of design tools, resources and technical support, and the creation of learning contexts in which designers can flexibly apply their knowledge.
## 3.1. Demand Analysis
The main difference between digital art and design and other fields is that there is no single model. In other words, it is a complex systemic project that integrates creativity, research, and development. It includes not only design foundations, design concepts, and design skills, but also the development of practical skills such as hands-on production. This is why the user should be given priority when designing effective models for digital art and design. Figure6 summarizes the four main role objects in the digital art design effectiveness model.Figure 6
Four main role objects in the digital art design effectiveness model.
## 3.2. Analysis of Model Operating Environment
The model runs on a standard server, which needs to be set up as a web server and database server. When a certain number of users access the system at the same time, the server is able to keep the system running and provide the services required by each user. In addition, users need to access the server via the network. Therefore, only the user side and the server side are connected to the LAN and the server is accessed via the LAN, which ensures both speed and network security.Combining the advantages and disadvantages of C/S and B/S, this model uses a combination of C/S and B/S architecture. For example, for the database, a B/S web application environment is used for the data query service. The C/S web application environment is used to run on the campus network. As a result, the overall structure of the digital art design effectiveness model is shown in Figure7.Figure 7
Structure of the digital art design effectiveness model.C/S mode applications can be developed with client-side applications according to the actual situation. If the client has a high processing power, more tasks can be implemented on the client side. If the network communication conditions are good and the server computing performance is high, then more computing operations can be implemented on the server side. For example, some management information systems based on the C/S model even integrate all functions on the server side, where most of the processing tasks such as data access, logical operations, data storage, and control of the system’s business processes are realised. This leads to a surge in network access, which needs to be supported by good network conditions. With the server as the focus of the entire system, the server is slow to respond and may even become “jammed” when a large number of users access the server at the same time. Due to the difficulties of synchronising data in a C/S structure, the use of a C/S structure for the entire digital art and design effectiveness model will result in inefficient operation. However, the C/S structure can share some of the transaction processing requirements and can handle more complex business processes. Therefore, the digital art and design effectiveness model proposed in this study adopts a C/S architecture for the implementation of some core modules that need to handle complex business.
## 3.3. Principle of Digital Art Design Effectiveness Model
In the formal digital art and design environment, learning tasks are set in accordance with the content or requirements of the model and are required to be completed by the designer. The designer is a passive participant, whereas the activity is something that the designer needs to actively engage in to complete. As a result, the designer can develop their own creative style and form at the right time when working with digital art design. In addition to this, the designer’s role, access to tools and resources, and the resultant outcomes should be given appropriate internal links when creating digital art.It is also important to note that, with the creation of digital art, creating online has become a focus of research. What is unique about online creation compared to traditional design models is that it has to reflect both the centrality of the designer and the special aspects of the online environment in the design of the activity. When designing online, special attention is paid to the following aspects. For example, the design of a designer-centred online platform, the provision of design tools, resources and technical support, and the creation of learning contexts in which designers can flexibly apply their knowledge.
## 4. Conclusion
The application of computers in digital technology has expanded the channels of artistic expression, and the change in artistic thinking in the context of digital technology has led to changes in the development of abstract graphics. Digital art is a combination of natural and social disciplines, technology, and the humanities and is a new discipline that combines digital technology and art. The combination of abstract graphics and digital technology allows for the creation of works full of novelty and interest. In the context of digital art, the fusion of information and big data has begun to visualise abstract graphic information. Combined with augmented reality technology, the senses interact with virtual reality in real time. The combination of abstract graphics as a visual language for digital art expression and digital technology is highly integrated and has significantly changed the traditional use of graphics production, design thinking, and aesthetic thinking. Digital art, as a different form of art from the traditional ones, has the characteristics and advantages of being high-tech, high-impact, and highly interactive. As a result, digital art can be used to express a wide range of subjects in a multitude of ways. The multifaceted use of digital art reflects the emotional resonance, digital information, and humanistic concepts in a modern context. The concept of abstract graphics in digital art is transformed from an objective to a more subjective expression of the subject matter, with design thinking becoming more experimental and beginning to explore the future and the unknown in greater depth.The digital art design effectiveness model designed for this study has a relatively good overall plan. And the model can be well combined with the K-medoids algorithm so that the data shared between modules can be clustered and analysed. However, the specific implementation of each module’s functionality is relatively straightforward, with the implementation focusing on the more commonly used functions. However, the development of this model is essentially a prototype development approach, but one that is different from the prototype development approach. The requirements and planning for the model were completed prior to development and only some of the functionality was not code-specifically implemented. The model will be refined and improved as it is used.
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*Source: 2901815-2022-07-06.xml* | 2022 |
# Necroptosis Mediates TNF-Induced Toxicity of Hippocampal Neurons
**Authors:** Shan Liu; Xing Wang; Yun Li; Lei Xu; Xiaoliang Yu; Lin Ge; Jun Li; Yongjin Zhu; Sudan He
**Journal:** BioMed Research International
(2014)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2014/290182
---
## Abstract
Tumor necrosis factor-α (TNF-α) is a critical proinflammatory cytokine regulating neuroinflammation. Elevated levels of TNF-α have been associated with various neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. However, the signaling events that lead to TNF-α-initiated neurotoxicity are still unclear. Here, we report that RIP3-mediated necroptosis, a form of regulated necrosis, is activated in the mouse hippocampus after intracerebroventricular injection of TNF-α. RIP3 deficiency attenuates TNF-α-initiated loss of hippocampal neurons. Furthermore, we characterized the molecular mechanism of TNF-α-induced neurotoxicity in HT-22 hippocampal neuronal cells. HT-22 cells are sensitive to TNF-α only upon caspase blockage and subsequently undergo necrosis. The cell death is suppressed by knockdown of CYLD or RIP1 or RIP3 or MLKL, suggesting that this necrosis is necroptosis and mediated by CYLD-RIP1-RIP3-MLKL signaling pathway. TNF-α-induced necroptosis of HT-22 cells is largely independent of both ROS accumulation and calcium influx although these events have been shown to be critical for necroptosis in certain cell lines. Taken together, these data not only provide the first in vivo evidence for a role of RIP3 in TNF-α-induced toxicity of hippocampal neurons, but also demonstrate that TNF-α promotes CYLD-RIP1-RIP3-MLKL-mediated necroptosis of hippocampal neurons largely bypassing ROS accumulation and calcium influx.
---
## Body
## 1. Introduction
Massive loss of a particular subset of neurons is a pathological hallmark of neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS). Cytokine-driven neuroinflammation and neurotoxicity have been implicated in the initiation and progression of these devastating diseases [1]. Ample evidence suggests that tumor necrosis factor-α (TNF-α) is a key proinflammatory cytokine regulating neuroinflammation and plays roles in both homeostasis and disease pathophysiology in the central nervous system (CNS) [2]. TNF-α is commonly elevated in the clinic and animal models of neurodegenerative diseases. For example, increased level of TNF-α is detected in the brain and plasma in AD patients and mouse models of AD. In CNS, TNF-α is mainly produced by activated microglia and astrocytes in response to various stimuli including infection and injury. Genetic deletion of TNFR1 has been shown to attenuate the production of the amyloid-β (Aβ) and to improve impairments in mice with AD [3, 4]. Moreover, deficiency of TNF-α or TNF receptor protects against dopaminergic neurotoxicity [5, 6]. Therefore, overproduction of TNF-α is strongly linked with neuronal damage, and blockage of TNF-α-mediated neurotoxic pathway emerges as an attractive strategy for the treatment of degenerative diseases such as AD and PD. Although TNF-α has been shown to be neurotoxic to cultured neurons by promoting glutamate production [7], the signaling events that lead to TNF-α-initiated neurotoxicity are not yet understood.As a pleiotropic factor, TNF-α is involved in diverse cellular responses including apoptosis and necrosis. TNF family of cytokines, such as TNF-α, TRAIL, and FasL, triggers apoptosis by recruiting and activating caspase-8 through the adaptor protein FADD. In some cell types, suppression of caspase-8 or FADD sensitizes cells to programmed necrosis (termed necroptosis) in response to these cytokines as well as ligands of Toll-like receptors (TLRs) [8, 9]. Necroptosis depends on the formation of a necrosome complex, which contains receptor-interacting kinase-1 (RIP1) [10], receptor-interacting kinase-3 (RIP3) [11–13], and mixed lineage kinase domain-like protein (MLKL) [14, 15]. In TNF-α-induced necroptosis, deubiquitination of RIP1 by cylindromatosis (CYLD) is a critical process for necrosome formation and activation [16, 17]. Although downstream mechanisms mediating execution of necroptosis remain to be elucidated, reactive oxygen species (ROS) accumulation [13, 18] and calcium influx [19] have been shown to be critical for necroptosis in certain cell lines.The connection between necroptosis and neuronal damage has been suggested by studies demonstrating a protective effect of necroptosis inhibitor on brain injury in experimental stroke and trauma models [20, 21]. We therefore hypothesize that necroptosis is activated during neuroinflammation and further drives neurotoxicity. To this end, we used RIP3-deficient mice to determine the regulation of necroptosis in TNF-α-induced neurotoxicityin vivo. Here, we demonstrated that deficiency of RIP3 alleviates the loss of hippocampal neurons in the mouse hippocampus after intracerebroventricular injection of TNF-α. Using anin vitro hippocampal neuronal model, we provided a detailed molecular characterization of TNF-α-induced death of hippocampal neurons.
## 2. Materials and Methods
### 2.1. Animal Models
RIP3 knockout mice were generated as described previously [11] and crossed to C57BL/6 mice for ten generations. Female wild-type and RIP3 knockout mice at 6–8 weeks of age received intracerebroventricular injection of TNF-α. In brief, 2.5 μg or 5 μg TNF-α was dissolved in PBS to make a total volume of 20 μL and then injected into each lateral ventricle. The control group mice received 20 μL PBS. After 3 days, mice were scarified and the proteins were extracted from hippocampus and subjected to western blot analysis. Morphology of hippocampal neurons was analyzed by Nissl staining of brain sections. All animal experiments were performed in accordance with protocols by the Institutional Animal Care and Use Committee at Soochow University.
### 2.2. Reagents
Dulbecco’s modified Eagle’s medium (DMEM) was from Thermo. Penicillin/streptomycin, L-Glutamine, and fetal bovine serum (FBS) were from GIBCO. BHA, NAC, phosphate buffered saline (PBS), and Lanthanum(III) chloride heptahydrate (LaCl3·7H2O) were from Sigma. Recombinant TNF-α was purified as described previously [11]. z-VAD was from Bachem. Necrostatin-1 was from Alexis Biochemicals. Propidium Iodide was from Biouniquer. The following antibodies were used for western blotting: mouse RIP3 (Prosci, 2283), RIP1 (BD Biosciences, 610459), mouse CYLD (Cell Signaling, 437700), caspase-3 (Cell Signaling, 9662), and β-actin (Sigma).
### 2.3. Cell Culture
Mouse hippocampal neuron (HT-22) cells were a gift from the Lab of Dr. Zhenghong Qin (Soochow University). Mouse embryonic fibroblasts (MEFs) were isolated from day 14.5–15.5 embryos. These cells were grown in DMEM supplemented with 10% fetal bovine serum.
### 2.4. Plasmids and Oligos
Lentiviral expression construct containing mouse RIP3 was amplified from RIP3 plasmid with primers containing an N-terminal Flag epitope and then cloned into pCAG-MCS-IRES vector that was a gift from the Lab of Dr. Yun Zhao (Soochow University). Lentiviral expression construct containing RIP3-RHIM domain mutant (RIP3-RHIM-Mut) or RIP3 kinase mutant (RIP3 K51A) was generated by QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies). Mouse RIP3, RIP1, MLKL, and CYLD siRNAs were synthesized by GenePharma: RIP3-1 (cccgacgaugucuucugucaa), RIP3-2 (cuccuuaaagucaauaaacau), RIP1-1 (ccacuagucugacugauga), RIP1-2 (ucaccaauguugcaggaua), CYLD-1 (uccauugaggauguaaauaaa), CYLD-2 (aaggguugaaccauuguuaaa), MLKL-1 (gagauccaguucaacgaua), and MLKL-2 (uaccaucaaaguauucaacaa).
### 2.5. Nissl Staining
The mice were sacrificed 72 h after intracerebroventricular injection of TNFα. Brains were dissected out of the skull and put in 4% paraformaldehyde to fix the tissue for 24 hours at room temperature and then stored in 30% sucrose phosphate buffer overnight until the tissue sank to the bottom of the solution. 20 μm sections were cut in the coronal plane using a freezing microtome (Leica CM19500) and mounted on gelatin coated slides. The sections were further stained in 0.1% cresyl violet solution (Sigma-Aldrich) at 37°C for several minutes. Rinse quickly in distilled water followed by differentiation in 95% ethyl alcohol and check microscopically for best result. Dehydrate in 100% alcohol and clear in xylene. Finally, the sections were mounted using a neutral balsam and photos were taken under microscope.
### 2.6. Western Blot Analysis
Cell pellets were lysed in lysis buffer containing 20 mM Tris-Hcl (pH 8.0), 150 mM NaCl, 1% Triton X-100, 1% Glycerol, 0.5 mM DTT, 1 mM Na3VO4, 25 mMβ-glycerol-phosphate, and 1 mM PMSF supplemented with protease inhibitor cocktail (Roche). The mouse tissue was grinded and resuspended in lysis buffer with 0.1% SDS. The resuspended cell pellet or tissue was vortexed for 10 seconds, then incubated on ice for 20 min, and then centrifuged at 20,000 g for 20 min. Protein concentration was determined by Quick Start Bradford 1x Dye Reagent (Bio-Rad). The protein samples were prepared for western blot analysis.
### 2.7. Generation of Stable Cell Lines
293T cells werecotransfected with lentiviral expression construct and packaging plasmids mix, and viral particles were collected after 48 hours and 72 hours. HT-22 cells were infected with lentivirus containing RIP3, RIP3K51A, and RIP3-RHIM-Mut, respectively. 72 hours later cells were selected with GFP by fluorescence-activated cell sorting.
### 2.8. Transfection and Cell Viability Assay
HT-22 cells were transfected with siRNAs by Lipofectamine RNAiMAX Reagent (Invitrogen) for 60 h and then treated with the indicated drug for about 20 h. Cell survival was determined by Cell Titer-Glo Luminescent Cell Viability Assay kit (Promega).
## 2.1. Animal Models
RIP3 knockout mice were generated as described previously [11] and crossed to C57BL/6 mice for ten generations. Female wild-type and RIP3 knockout mice at 6–8 weeks of age received intracerebroventricular injection of TNF-α. In brief, 2.5 μg or 5 μg TNF-α was dissolved in PBS to make a total volume of 20 μL and then injected into each lateral ventricle. The control group mice received 20 μL PBS. After 3 days, mice were scarified and the proteins were extracted from hippocampus and subjected to western blot analysis. Morphology of hippocampal neurons was analyzed by Nissl staining of brain sections. All animal experiments were performed in accordance with protocols by the Institutional Animal Care and Use Committee at Soochow University.
## 2.2. Reagents
Dulbecco’s modified Eagle’s medium (DMEM) was from Thermo. Penicillin/streptomycin, L-Glutamine, and fetal bovine serum (FBS) were from GIBCO. BHA, NAC, phosphate buffered saline (PBS), and Lanthanum(III) chloride heptahydrate (LaCl3·7H2O) were from Sigma. Recombinant TNF-α was purified as described previously [11]. z-VAD was from Bachem. Necrostatin-1 was from Alexis Biochemicals. Propidium Iodide was from Biouniquer. The following antibodies were used for western blotting: mouse RIP3 (Prosci, 2283), RIP1 (BD Biosciences, 610459), mouse CYLD (Cell Signaling, 437700), caspase-3 (Cell Signaling, 9662), and β-actin (Sigma).
## 2.3. Cell Culture
Mouse hippocampal neuron (HT-22) cells were a gift from the Lab of Dr. Zhenghong Qin (Soochow University). Mouse embryonic fibroblasts (MEFs) were isolated from day 14.5–15.5 embryos. These cells were grown in DMEM supplemented with 10% fetal bovine serum.
## 2.4. Plasmids and Oligos
Lentiviral expression construct containing mouse RIP3 was amplified from RIP3 plasmid with primers containing an N-terminal Flag epitope and then cloned into pCAG-MCS-IRES vector that was a gift from the Lab of Dr. Yun Zhao (Soochow University). Lentiviral expression construct containing RIP3-RHIM domain mutant (RIP3-RHIM-Mut) or RIP3 kinase mutant (RIP3 K51A) was generated by QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies). Mouse RIP3, RIP1, MLKL, and CYLD siRNAs were synthesized by GenePharma: RIP3-1 (cccgacgaugucuucugucaa), RIP3-2 (cuccuuaaagucaauaaacau), RIP1-1 (ccacuagucugacugauga), RIP1-2 (ucaccaauguugcaggaua), CYLD-1 (uccauugaggauguaaauaaa), CYLD-2 (aaggguugaaccauuguuaaa), MLKL-1 (gagauccaguucaacgaua), and MLKL-2 (uaccaucaaaguauucaacaa).
## 2.5. Nissl Staining
The mice were sacrificed 72 h after intracerebroventricular injection of TNFα. Brains were dissected out of the skull and put in 4% paraformaldehyde to fix the tissue for 24 hours at room temperature and then stored in 30% sucrose phosphate buffer overnight until the tissue sank to the bottom of the solution. 20 μm sections were cut in the coronal plane using a freezing microtome (Leica CM19500) and mounted on gelatin coated slides. The sections were further stained in 0.1% cresyl violet solution (Sigma-Aldrich) at 37°C for several minutes. Rinse quickly in distilled water followed by differentiation in 95% ethyl alcohol and check microscopically for best result. Dehydrate in 100% alcohol and clear in xylene. Finally, the sections were mounted using a neutral balsam and photos were taken under microscope.
## 2.6. Western Blot Analysis
Cell pellets were lysed in lysis buffer containing 20 mM Tris-Hcl (pH 8.0), 150 mM NaCl, 1% Triton X-100, 1% Glycerol, 0.5 mM DTT, 1 mM Na3VO4, 25 mMβ-glycerol-phosphate, and 1 mM PMSF supplemented with protease inhibitor cocktail (Roche). The mouse tissue was grinded and resuspended in lysis buffer with 0.1% SDS. The resuspended cell pellet or tissue was vortexed for 10 seconds, then incubated on ice for 20 min, and then centrifuged at 20,000 g for 20 min. Protein concentration was determined by Quick Start Bradford 1x Dye Reagent (Bio-Rad). The protein samples were prepared for western blot analysis.
## 2.7. Generation of Stable Cell Lines
293T cells werecotransfected with lentiviral expression construct and packaging plasmids mix, and viral particles were collected after 48 hours and 72 hours. HT-22 cells were infected with lentivirus containing RIP3, RIP3K51A, and RIP3-RHIM-Mut, respectively. 72 hours later cells were selected with GFP by fluorescence-activated cell sorting.
## 2.8. Transfection and Cell Viability Assay
HT-22 cells were transfected with siRNAs by Lipofectamine RNAiMAX Reagent (Invitrogen) for 60 h and then treated with the indicated drug for about 20 h. Cell survival was determined by Cell Titer-Glo Luminescent Cell Viability Assay kit (Promega).
## 3. Results
### 3.1. The Regulation of RIP3 in TNF-α-Induced Toxicity of Hippocampal NeuronsIn Vivo
RIP3 is a key molecule regulating necroptosis induced by TNF family cytokines and ligands of TLR3/4. Elevated expression of RIP3 protein is observed in the damage tissues and correlates with active necroptosis during the pathogenesis of diseases such as acute pancreatitis, retinal detachment, and liver injury [11, 22, 23]. To assess the role of necroptosis in TNF-α-induced neurotoxicity, we challenged wild-type and RIP3-deficient mice with intracerebroventricular injection of TNF-α. Histological analysis with Nissl staining of neurons was performed to evaluate TNF-α-induced damage of neurons. We observed that administration of TNF-α to wild-type mice caused a reduction in neuronal density in the hippocampus especially CA3 region in a dose-dependent manner as compared with control-treated mice (Figure 1(a)). Notably, no obvious loss of hippocampal neurons was observed in RIP3-deficient mice after treatment of TNF-α (Figure 1(a)). Moreover, we noticed that the expression levels of RIP1 and RIP3 were increased in the hippocampus after TNF-α treatment (Figure 1(b)), while there is no detectable activation of caspase-3 which is an executioner caspase activated via proteolytic cleavage during apoptosis (Figure 1(c)), indicating that necroptosis but not apoptosis is activated by the injection of TNF-α. These results indicate that necroptosis is activated in CNS and contributes to the toxicity of hippocampal neurons in response to TNF-α.The regulation of RIP3 in TNF-α-induced toxicity of hippocampal neuronsin vivo. (a) Nissl staining of hippocampal neurons 72 h after treatment. Wild-type (WT) and RIP3 knockout (KO) mice received intracerebroventricular injection of PBS or the indicated dose of TNF-α. The neurons of brain sections from WT and KO mice were analyzed by Nissl staining (n=7) and morphology of hippocampal CA3 region was shown. Arrows indicate the loss of hippocampal neurons. (b) and (c) Expressions of RIP1, RIP3, and caspase-3 in the hippocampus after TNF-α treatment. Proteins extracted from hippocampus in the wild-type mice treated with PBS or TNF-α were analyzed by western blot using indicated antibodies. PC: MEF cells were treated with staurosporine at 150 nM for 15 hours. The results shown here are representative of five mice.
(a)
(b)
(c)
### 3.2. HT-22 Hippocampal Neurons Are Committed to Necrosis rather than Apoptosis in Response to TNF-α
Having observed RIP3-mediated necroptosis in TNF-α-induced toxicity of hippocampal neuronsin vivo, we sought to clarify the molecule mechanism underling TNF-α-induced neurotoxicity in HT-22 hippocampal neuronal cell line, which is often employed as anin vitro model of hippocampal neuron. We observed that HT-22 cells were resistant to TNF-α, even in the presence of Smac mimetic, a compound which can mimic the function of proapoptotic protein Smac/Diablo and induces apoptosis as a single agent or in combination with TNF-α [24, 25] (Figure 2(a)). Notably, addition of caspase inhibitor, z-VAD, sensitized HT-22 cells to death in response to TNF-α in a dose-dependent manner (Figure 2(a)). Propidium iodide (PI) positive cells were detected in TNF/z-VAD treated HT-22 cells (Figure 2(b)), suggesting that these cells lost membrane permeability and underwent necrosis. Taken together, these data demonstrate that HT-22 hippocampal neuronal cells are committed to TNF-α-induced necrosis rather than apoptosis.HT-22 hippocampal neurons are committed to necrosis rather than apoptosis in response to TNF-α. (a) HT-22 hippocampal neuronal cells were treated as indicated for 20 h. Cell viability was determined by measuring ATP levels. Data are represented as mean ± standard deviation of duplicates. T: TNF-α; S: Smac mimetic (100 nM); and Z: z-VAD (20μM). (b) HT-22 hippocampal neurons were treated with DMSO or TNF-α (300 ng/mL)/z-VAD for 20 h and then analyzed for PI staining by flow cytometry. Identical concentrations were used in later experiments. Data are represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus control. All experiments were repeated three times with similar results.
(a)
(b)
### 3.3. TNF-α-Induced Necrosis of HT-22 Cells Is Mediated by CYLD-RIP1-RIP3-MLKL Signaling Pathway
RIP3 kinase is a key determinant for necroptosis. RIP3 protein contains an N-terminal serine/threonine kinase domain and a C-terminal RIP homotypic interaction motif (RHIM). The kinase activity and RHIM domain of RIP3 are critical for its function in mediating necroptosis [11]. We examined the role of RIP3 in TNF-α-induced necrosis in HT-22 cells by RNAi approach. Knockdown of endogenous RIP3 greatly blocked TNF-α-induced necrosis (Figures 3(a) and 3(b)), which was restored by stable expression of a shRNA-resistant wild-type RIP3, but not a shRNA-resistant kinase dead form or RHIM mutant form of RIP3 (Figures 3(c) and 3(d)), indicating that both kinase activity and RHIM domain of RIP3 are crucial for TNF-α-induced necrosis of HT-22 cells.TNF-α-induced necrosis of HT-22 cells depends on RIP3 and its kinase activity. (a) HT-22 cells were transfected with the negative control (NC) or RIP3 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of RIP3 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP3 and β-actin levels. (c) HT-22 cells stably expressing a siRNA-resistant WT-RIP3 or RIP3-K51A or RIP3-RHIM-Mut were transfected with the control or RIP3 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. WT-RIP3: HT-22 cells stably expressing a siRNA-resistant wild-type form of RIP3; RIP3-K51A: HT-22 cells stably expressing a siRNA-resistant RIP3 kinase dead mutant. RIP3-RHIM Mut: HT-22 cells stably expressing a siRNA-resistant RHIM domain mutant form of RIP3. (d) The knockdown efficiency of RIP3 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP3 and β-actin levels. All experiments were repeated three times with similar results.
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(d)RHIM domain of RIP3 is known to be critical for its interaction with RIP1 during necroptosis [26]. We further tested whether RIP1 is required for TNF-α-induced necrosis of HT-22 cells. As shown in Figures 4(a) and 4(b), reducing endogenous RIP1 suppressed TNF-α-induced necrosis. In addition, knockdown of CYLD, a deubiquitinase of RIP1, blocked TNF-α-induced necrosis of HT-22 cells (Figures 4(c) and 4(d)).RIP1 and its deubiquitinase CYLD are required for TNF-α-induced necrosis of HT-22 cells. (a) HT-22 cells were transfected with the negative control or RIP1 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of RIP1 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP1 and β-actin levels. (c) HT-22 cells were transfected with the negative control or CYLD siRNAs. Forty-eight hours after transfection, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (d) The knockdown efficiency of CYLD RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of CYLD and β-actin levels. All experiments were repeated three times with similar results.
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(d)MLKL is a kinase-like protein and functions as a substrate of RIP3. To assess the requirement of MLKL in TNF-α-induced necrosis of HT-22 cells, we performed MLKL RNAi in the cells and found knockdown of MLKL efficiently reduced the cell death (Figures 5(a) and 5(b)).MLKL is essential for TNF-α-induced necrosis of HT-22 cells. (a) HT-22 cells were transfected with the negative control or MLKL siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of MLKL RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of MLKL and β-actin levels. All experiments were repeated three times with similar results.
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### 3.4. TNF-α-Induced Necroptosis of HT-22 Cells Is Largely Independent of ROS Accumulation and Calcium Influx
We and others have shown that ROS accumulation is required for RIP3-mediated necrosis in certain cell lines such as mouse embryonic fibroblast (MEF) [13, 18], so we evaluated the role of ROS in TNF-α-induced necroptosis of HT-22 cells by using two widely used ROS scavengers, butylated hydroxyanisole (BHA) and N-acetylcysteine (NAC). MEF cells are known to undergo necroptosis in response to TNF-α, Smac mimetic and z-VAD. In the presence of BHA at 100 μM, the survival rate of HT-22 cells was increased by 13% and around 30% cells still underwent necrosis in response to TNF-α plus z-VAD, while TNF-α-induced necrosis in MEF cells was entirely prevented by BHA (Figures 6(a) and 6(b)). NAC had no inhibitory effect on TNF-α-induced necrosis of HT-22 cells, whereas the survival rate of MEF cells treated with necroptotic stimuli was increased by 40% after the addition of NAC at 10 mM (Figures 6(a) and 6(b)). Recently, calcium influx has been reported to be essential for necroptosis. We tested whether calcium influx is involved in TNF-α-induced necroptosis of HT-22. As shown in Figure 6(c), inhibition of calcium influx by the addition of LaCl3, a non-voltage-sensitive channel blocker, increased the survival rate of HT-22 by around 14%. Notably, TNF-α-induced necroptosis of HT-22 cells largely proceeded even in the presence of both LaCl3 and NAC (Figure 6(c)). These results demonstrated that TNF-α-initiated necroptosis in HT-22 cells is largely independent of ROS accumulation and calcium influx.TNF-α-induced necrosis of HT-22 cells is largely independent of ROS accumulation and calcium. (a) HT-22 cells were treated with control or BHA or NAC at the indicated concentration 3 h before the treatment of control or TNF-α/z-VAD for 20 h; cell viability was determined by measuring ATP levels. *P<0.01, **P<0.001 versus control-T+Z. (b) MEF cells were treated with control or BMS NAC at the indicated concentration 3 h before the treatment of control or TNF-α/Smac mimetic/z-VAD for 20 h; cell viability was determined by measuring ATP levels. *P<0.01, **P<0.001 versus control-T+S+Z. (c) HT-22 cells were treated with control or LaCl3 or NAC at the indicated concentration 3 h before the treatment of control or TNF-α/z-VAD for 20 h; cell viability was determined by measuring ATP levels. Data are represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus control-T+Z. All experiments were repeated three times with similar results.
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## 3.1. The Regulation of RIP3 in TNF-α-Induced Toxicity of Hippocampal NeuronsIn Vivo
RIP3 is a key molecule regulating necroptosis induced by TNF family cytokines and ligands of TLR3/4. Elevated expression of RIP3 protein is observed in the damage tissues and correlates with active necroptosis during the pathogenesis of diseases such as acute pancreatitis, retinal detachment, and liver injury [11, 22, 23]. To assess the role of necroptosis in TNF-α-induced neurotoxicity, we challenged wild-type and RIP3-deficient mice with intracerebroventricular injection of TNF-α. Histological analysis with Nissl staining of neurons was performed to evaluate TNF-α-induced damage of neurons. We observed that administration of TNF-α to wild-type mice caused a reduction in neuronal density in the hippocampus especially CA3 region in a dose-dependent manner as compared with control-treated mice (Figure 1(a)). Notably, no obvious loss of hippocampal neurons was observed in RIP3-deficient mice after treatment of TNF-α (Figure 1(a)). Moreover, we noticed that the expression levels of RIP1 and RIP3 were increased in the hippocampus after TNF-α treatment (Figure 1(b)), while there is no detectable activation of caspase-3 which is an executioner caspase activated via proteolytic cleavage during apoptosis (Figure 1(c)), indicating that necroptosis but not apoptosis is activated by the injection of TNF-α. These results indicate that necroptosis is activated in CNS and contributes to the toxicity of hippocampal neurons in response to TNF-α.The regulation of RIP3 in TNF-α-induced toxicity of hippocampal neuronsin vivo. (a) Nissl staining of hippocampal neurons 72 h after treatment. Wild-type (WT) and RIP3 knockout (KO) mice received intracerebroventricular injection of PBS or the indicated dose of TNF-α. The neurons of brain sections from WT and KO mice were analyzed by Nissl staining (n=7) and morphology of hippocampal CA3 region was shown. Arrows indicate the loss of hippocampal neurons. (b) and (c) Expressions of RIP1, RIP3, and caspase-3 in the hippocampus after TNF-α treatment. Proteins extracted from hippocampus in the wild-type mice treated with PBS or TNF-α were analyzed by western blot using indicated antibodies. PC: MEF cells were treated with staurosporine at 150 nM for 15 hours. The results shown here are representative of five mice.
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## 3.2. HT-22 Hippocampal Neurons Are Committed to Necrosis rather than Apoptosis in Response to TNF-α
Having observed RIP3-mediated necroptosis in TNF-α-induced toxicity of hippocampal neuronsin vivo, we sought to clarify the molecule mechanism underling TNF-α-induced neurotoxicity in HT-22 hippocampal neuronal cell line, which is often employed as anin vitro model of hippocampal neuron. We observed that HT-22 cells were resistant to TNF-α, even in the presence of Smac mimetic, a compound which can mimic the function of proapoptotic protein Smac/Diablo and induces apoptosis as a single agent or in combination with TNF-α [24, 25] (Figure 2(a)). Notably, addition of caspase inhibitor, z-VAD, sensitized HT-22 cells to death in response to TNF-α in a dose-dependent manner (Figure 2(a)). Propidium iodide (PI) positive cells were detected in TNF/z-VAD treated HT-22 cells (Figure 2(b)), suggesting that these cells lost membrane permeability and underwent necrosis. Taken together, these data demonstrate that HT-22 hippocampal neuronal cells are committed to TNF-α-induced necrosis rather than apoptosis.HT-22 hippocampal neurons are committed to necrosis rather than apoptosis in response to TNF-α. (a) HT-22 hippocampal neuronal cells were treated as indicated for 20 h. Cell viability was determined by measuring ATP levels. Data are represented as mean ± standard deviation of duplicates. T: TNF-α; S: Smac mimetic (100 nM); and Z: z-VAD (20μM). (b) HT-22 hippocampal neurons were treated with DMSO or TNF-α (300 ng/mL)/z-VAD for 20 h and then analyzed for PI staining by flow cytometry. Identical concentrations were used in later experiments. Data are represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus control. All experiments were repeated three times with similar results.
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## 3.3. TNF-α-Induced Necrosis of HT-22 Cells Is Mediated by CYLD-RIP1-RIP3-MLKL Signaling Pathway
RIP3 kinase is a key determinant for necroptosis. RIP3 protein contains an N-terminal serine/threonine kinase domain and a C-terminal RIP homotypic interaction motif (RHIM). The kinase activity and RHIM domain of RIP3 are critical for its function in mediating necroptosis [11]. We examined the role of RIP3 in TNF-α-induced necrosis in HT-22 cells by RNAi approach. Knockdown of endogenous RIP3 greatly blocked TNF-α-induced necrosis (Figures 3(a) and 3(b)), which was restored by stable expression of a shRNA-resistant wild-type RIP3, but not a shRNA-resistant kinase dead form or RHIM mutant form of RIP3 (Figures 3(c) and 3(d)), indicating that both kinase activity and RHIM domain of RIP3 are crucial for TNF-α-induced necrosis of HT-22 cells.TNF-α-induced necrosis of HT-22 cells depends on RIP3 and its kinase activity. (a) HT-22 cells were transfected with the negative control (NC) or RIP3 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of RIP3 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP3 and β-actin levels. (c) HT-22 cells stably expressing a siRNA-resistant WT-RIP3 or RIP3-K51A or RIP3-RHIM-Mut were transfected with the control or RIP3 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. WT-RIP3: HT-22 cells stably expressing a siRNA-resistant wild-type form of RIP3; RIP3-K51A: HT-22 cells stably expressing a siRNA-resistant RIP3 kinase dead mutant. RIP3-RHIM Mut: HT-22 cells stably expressing a siRNA-resistant RHIM domain mutant form of RIP3. (d) The knockdown efficiency of RIP3 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP3 and β-actin levels. All experiments were repeated three times with similar results.
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(d)RHIM domain of RIP3 is known to be critical for its interaction with RIP1 during necroptosis [26]. We further tested whether RIP1 is required for TNF-α-induced necrosis of HT-22 cells. As shown in Figures 4(a) and 4(b), reducing endogenous RIP1 suppressed TNF-α-induced necrosis. In addition, knockdown of CYLD, a deubiquitinase of RIP1, blocked TNF-α-induced necrosis of HT-22 cells (Figures 4(c) and 4(d)).RIP1 and its deubiquitinase CYLD are required for TNF-α-induced necrosis of HT-22 cells. (a) HT-22 cells were transfected with the negative control or RIP1 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of RIP1 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP1 and β-actin levels. (c) HT-22 cells were transfected with the negative control or CYLD siRNAs. Forty-eight hours after transfection, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (d) The knockdown efficiency of CYLD RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of CYLD and β-actin levels. All experiments were repeated three times with similar results.
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(d)MLKL is a kinase-like protein and functions as a substrate of RIP3. To assess the requirement of MLKL in TNF-α-induced necrosis of HT-22 cells, we performed MLKL RNAi in the cells and found knockdown of MLKL efficiently reduced the cell death (Figures 5(a) and 5(b)).MLKL is essential for TNF-α-induced necrosis of HT-22 cells. (a) HT-22 cells were transfected with the negative control or MLKL siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of MLKL RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of MLKL and β-actin levels. All experiments were repeated three times with similar results.
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## 3.4. TNF-α-Induced Necroptosis of HT-22 Cells Is Largely Independent of ROS Accumulation and Calcium Influx
We and others have shown that ROS accumulation is required for RIP3-mediated necrosis in certain cell lines such as mouse embryonic fibroblast (MEF) [13, 18], so we evaluated the role of ROS in TNF-α-induced necroptosis of HT-22 cells by using two widely used ROS scavengers, butylated hydroxyanisole (BHA) and N-acetylcysteine (NAC). MEF cells are known to undergo necroptosis in response to TNF-α, Smac mimetic and z-VAD. In the presence of BHA at 100 μM, the survival rate of HT-22 cells was increased by 13% and around 30% cells still underwent necrosis in response to TNF-α plus z-VAD, while TNF-α-induced necrosis in MEF cells was entirely prevented by BHA (Figures 6(a) and 6(b)). NAC had no inhibitory effect on TNF-α-induced necrosis of HT-22 cells, whereas the survival rate of MEF cells treated with necroptotic stimuli was increased by 40% after the addition of NAC at 10 mM (Figures 6(a) and 6(b)). Recently, calcium influx has been reported to be essential for necroptosis. We tested whether calcium influx is involved in TNF-α-induced necroptosis of HT-22. As shown in Figure 6(c), inhibition of calcium influx by the addition of LaCl3, a non-voltage-sensitive channel blocker, increased the survival rate of HT-22 by around 14%. Notably, TNF-α-induced necroptosis of HT-22 cells largely proceeded even in the presence of both LaCl3 and NAC (Figure 6(c)). These results demonstrated that TNF-α-initiated necroptosis in HT-22 cells is largely independent of ROS accumulation and calcium influx.TNF-α-induced necrosis of HT-22 cells is largely independent of ROS accumulation and calcium. (a) HT-22 cells were treated with control or BHA or NAC at the indicated concentration 3 h before the treatment of control or TNF-α/z-VAD for 20 h; cell viability was determined by measuring ATP levels. *P<0.01, **P<0.001 versus control-T+Z. (b) MEF cells were treated with control or BMS NAC at the indicated concentration 3 h before the treatment of control or TNF-α/Smac mimetic/z-VAD for 20 h; cell viability was determined by measuring ATP levels. *P<0.01, **P<0.001 versus control-T+S+Z. (c) HT-22 cells were treated with control or LaCl3 or NAC at the indicated concentration 3 h before the treatment of control or TNF-α/z-VAD for 20 h; cell viability was determined by measuring ATP levels. Data are represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus control-T+Z. All experiments were repeated three times with similar results.
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## 4. Discussion
TNF-α is a key mediator of neuroinflammation. Elevated levels of TNF-α are associated with various neurodegenerative conditions and contribute to neurotoxicity. The mechanisms underlying TNF-α-initiated neurotoxicity are largely unknown. Our present work revealed an important role of necroptosis in TNF-α-induced toxicity of hippocampal neurons.Necroptosis is a form of programmed necrosis which is regulated by RIP1 and RIP3 kinases. Apoptosis is known to negatively regulate necroptosis via active caspase-8, which is able to cleave necrosis regulators including RIP1, RIP3, and CYLD [8]. A recent work has shown that mutating the caspase-8 cleavage site at Asp 215 of CYLD is sufficient to promote necroptosis even in the absence of caspase inhibitor, indicating that caspase-8 prevents necroptosis through processing CYLD [27]. CYLD was originally thought to deubiquitinate RIP1 at the membrane receptor complex and promote the recruitment of RIP1 into the necrosome. Recently, it was shown to control the deubiquitination of RIP1 and it facilitates kinase activation in the necrosome [17]. Among the components of necrosome, MLKL is a functional substrate of RIP3. Upon the phosphorylation of MLKL by RIP3, MLKL forms oligomers and locates to the cell plasma membrane [19, 28, 29]. Although mechanisms of necroptosis are extensively studied, there is little known about the machinery of necroptosis in neuronal cells. In this study, we found that HT-22 hippocampal neurons are committed to necroptosis rather than apoptosis in response to TNF-α. Using RNAi approach, we demonstrated that TNF-α-induced neuronal necrosis is mediated by CYLD-RIP1-RIP3-MLKL signaling pathway. Our present study suggests that the core components of necrosome have conserved roles in neuronal necrosis initiated by TNF-α.Necroptotic cell death is characterized by disrupted plasma membrane; however, the downstream events of necrosome leading to collapse of membrane are largely unknown. ROS production has been shown to be required for necroptosis in several mouse cell lines including L929, MEF, NIH3T3, and macrophages, whereas it is not involved in necroptosis in HT-29 human colon cancer cells [30]. NADPH oxidase NOX1 and metabolic enzymes have been implicated in the control of ROS production during necroptosis [13, 31]. We have shown that TNF-α-induced necroptosis of HT-22 cells mouse hippocampal neurons is largely independent of ROS accumulation. Recently, TRPM7 has been identified to mediate calcium influx through acting downstream of MLKL membrane localization in TNF-α-induced necroptosis [28]. In our study, we showed that TNF-α-induced necroptosis of HT-22 cells largely proceeds even in the presence of calcium channel inhibitor and ROS scavenger. The data indicate that TNF-α-induced necroptosis of HT-22 cells largely bypasses ROS accumulation and calcium influx. Therefore, it is tempting to speculate that different downstream responses activated by necrosome depend on cell type. Future studies are required to clarify crucial downstream events for the execution of necroptosis in hippocampal neurons.Necroptosis is emerging as an important process involved in various pathological conditions including ischemic injury, acute pancreatitis, inflammatory bowel disease, and neuronal damage. Recent studies have demonstrated that increased level of RIP3 expression in the damage tissue correlates with the induction of necroptosis in the mouse models of acute pancreatitis and inflammatory bowel disease (IBD) [30] and patients with IBD [32]. Interestingly, we observed elevated expressions of RIP3 and RIP1 proteins and neuronal cell death in the hippocampus after intracerebroventricular injection of TNF-α. Importantly, genetic deletion of RIP3 reduced the loss of hippocampal neurons after intracerebroventricular injection of TNF-α. To our knowledge, the data represent the firstin vivo evidence for a role of RIP3 in TNF-α-induced neurotoxicity of hippocampal neurons. Blockage of necroptosis by necrostatin-1, a chemical inhibitor targeting RIP1 kinase, has provided protective effects on neuronal damage in animal models of brain injury [20], stroke [18], and amyotrophic lateral sclerosis [33]. Our study has demonstrated that necroptosis mediates TNF-α-initiated damage of hippocampal neurons. Given the elevated levels of TNF-α in the brains during various neurodegenerative diseases, neuronal cells may be susceptible to necroptosis upon stimulation of TNF-α, therefore contributing to the pathogenesis of neurodegenerative diseases. Targeted prevention of neuronal necroptosis may provide a novel therapeutic approach for the treatment of the related neurodegenerative diseases.
## 5. Conclusions
Taken together, our study revealed an important role of necroptosis in TNF-α-induced neurotoxicity. Necroptosis can be activated in the mouse hippocampus after intracerebroventricular injection of TNF-α. RIP3 deficiency attenuates TNF-α-initiated loss of hippocampal neurons. HT-22 hippocampal cells are sensitive to TNF-α only upon caspase blockage and subsequently undergo necrosis. A detailed molecular characterization demonstrates that TNF-α-induced necrosis in HT-22 cells is mediated by CYLD-RIP1-RIP3-MLKL necroptotic signaling pathway and largely independent of both ROS accumulation and calcium influx.
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*Source: 290182-2014-07-01.xml* | 290182-2014-07-01_290182-2014-07-01.md | 43,549 | Necroptosis Mediates TNF-Induced Toxicity of Hippocampal Neurons | Shan Liu; Xing Wang; Yun Li; Lei Xu; Xiaoliang Yu; Lin Ge; Jun Li; Yongjin Zhu; Sudan He | BioMed Research International
(2014) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2014/290182 | 290182-2014-07-01.xml | ---
## Abstract
Tumor necrosis factor-α (TNF-α) is a critical proinflammatory cytokine regulating neuroinflammation. Elevated levels of TNF-α have been associated with various neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease. However, the signaling events that lead to TNF-α-initiated neurotoxicity are still unclear. Here, we report that RIP3-mediated necroptosis, a form of regulated necrosis, is activated in the mouse hippocampus after intracerebroventricular injection of TNF-α. RIP3 deficiency attenuates TNF-α-initiated loss of hippocampal neurons. Furthermore, we characterized the molecular mechanism of TNF-α-induced neurotoxicity in HT-22 hippocampal neuronal cells. HT-22 cells are sensitive to TNF-α only upon caspase blockage and subsequently undergo necrosis. The cell death is suppressed by knockdown of CYLD or RIP1 or RIP3 or MLKL, suggesting that this necrosis is necroptosis and mediated by CYLD-RIP1-RIP3-MLKL signaling pathway. TNF-α-induced necroptosis of HT-22 cells is largely independent of both ROS accumulation and calcium influx although these events have been shown to be critical for necroptosis in certain cell lines. Taken together, these data not only provide the first in vivo evidence for a role of RIP3 in TNF-α-induced toxicity of hippocampal neurons, but also demonstrate that TNF-α promotes CYLD-RIP1-RIP3-MLKL-mediated necroptosis of hippocampal neurons largely bypassing ROS accumulation and calcium influx.
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## Body
## 1. Introduction
Massive loss of a particular subset of neurons is a pathological hallmark of neurodegenerative diseases such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and multiple sclerosis (MS). Cytokine-driven neuroinflammation and neurotoxicity have been implicated in the initiation and progression of these devastating diseases [1]. Ample evidence suggests that tumor necrosis factor-α (TNF-α) is a key proinflammatory cytokine regulating neuroinflammation and plays roles in both homeostasis and disease pathophysiology in the central nervous system (CNS) [2]. TNF-α is commonly elevated in the clinic and animal models of neurodegenerative diseases. For example, increased level of TNF-α is detected in the brain and plasma in AD patients and mouse models of AD. In CNS, TNF-α is mainly produced by activated microglia and astrocytes in response to various stimuli including infection and injury. Genetic deletion of TNFR1 has been shown to attenuate the production of the amyloid-β (Aβ) and to improve impairments in mice with AD [3, 4]. Moreover, deficiency of TNF-α or TNF receptor protects against dopaminergic neurotoxicity [5, 6]. Therefore, overproduction of TNF-α is strongly linked with neuronal damage, and blockage of TNF-α-mediated neurotoxic pathway emerges as an attractive strategy for the treatment of degenerative diseases such as AD and PD. Although TNF-α has been shown to be neurotoxic to cultured neurons by promoting glutamate production [7], the signaling events that lead to TNF-α-initiated neurotoxicity are not yet understood.As a pleiotropic factor, TNF-α is involved in diverse cellular responses including apoptosis and necrosis. TNF family of cytokines, such as TNF-α, TRAIL, and FasL, triggers apoptosis by recruiting and activating caspase-8 through the adaptor protein FADD. In some cell types, suppression of caspase-8 or FADD sensitizes cells to programmed necrosis (termed necroptosis) in response to these cytokines as well as ligands of Toll-like receptors (TLRs) [8, 9]. Necroptosis depends on the formation of a necrosome complex, which contains receptor-interacting kinase-1 (RIP1) [10], receptor-interacting kinase-3 (RIP3) [11–13], and mixed lineage kinase domain-like protein (MLKL) [14, 15]. In TNF-α-induced necroptosis, deubiquitination of RIP1 by cylindromatosis (CYLD) is a critical process for necrosome formation and activation [16, 17]. Although downstream mechanisms mediating execution of necroptosis remain to be elucidated, reactive oxygen species (ROS) accumulation [13, 18] and calcium influx [19] have been shown to be critical for necroptosis in certain cell lines.The connection between necroptosis and neuronal damage has been suggested by studies demonstrating a protective effect of necroptosis inhibitor on brain injury in experimental stroke and trauma models [20, 21]. We therefore hypothesize that necroptosis is activated during neuroinflammation and further drives neurotoxicity. To this end, we used RIP3-deficient mice to determine the regulation of necroptosis in TNF-α-induced neurotoxicityin vivo. Here, we demonstrated that deficiency of RIP3 alleviates the loss of hippocampal neurons in the mouse hippocampus after intracerebroventricular injection of TNF-α. Using anin vitro hippocampal neuronal model, we provided a detailed molecular characterization of TNF-α-induced death of hippocampal neurons.
## 2. Materials and Methods
### 2.1. Animal Models
RIP3 knockout mice were generated as described previously [11] and crossed to C57BL/6 mice for ten generations. Female wild-type and RIP3 knockout mice at 6–8 weeks of age received intracerebroventricular injection of TNF-α. In brief, 2.5 μg or 5 μg TNF-α was dissolved in PBS to make a total volume of 20 μL and then injected into each lateral ventricle. The control group mice received 20 μL PBS. After 3 days, mice were scarified and the proteins were extracted from hippocampus and subjected to western blot analysis. Morphology of hippocampal neurons was analyzed by Nissl staining of brain sections. All animal experiments were performed in accordance with protocols by the Institutional Animal Care and Use Committee at Soochow University.
### 2.2. Reagents
Dulbecco’s modified Eagle’s medium (DMEM) was from Thermo. Penicillin/streptomycin, L-Glutamine, and fetal bovine serum (FBS) were from GIBCO. BHA, NAC, phosphate buffered saline (PBS), and Lanthanum(III) chloride heptahydrate (LaCl3·7H2O) were from Sigma. Recombinant TNF-α was purified as described previously [11]. z-VAD was from Bachem. Necrostatin-1 was from Alexis Biochemicals. Propidium Iodide was from Biouniquer. The following antibodies were used for western blotting: mouse RIP3 (Prosci, 2283), RIP1 (BD Biosciences, 610459), mouse CYLD (Cell Signaling, 437700), caspase-3 (Cell Signaling, 9662), and β-actin (Sigma).
### 2.3. Cell Culture
Mouse hippocampal neuron (HT-22) cells were a gift from the Lab of Dr. Zhenghong Qin (Soochow University). Mouse embryonic fibroblasts (MEFs) were isolated from day 14.5–15.5 embryos. These cells were grown in DMEM supplemented with 10% fetal bovine serum.
### 2.4. Plasmids and Oligos
Lentiviral expression construct containing mouse RIP3 was amplified from RIP3 plasmid with primers containing an N-terminal Flag epitope and then cloned into pCAG-MCS-IRES vector that was a gift from the Lab of Dr. Yun Zhao (Soochow University). Lentiviral expression construct containing RIP3-RHIM domain mutant (RIP3-RHIM-Mut) or RIP3 kinase mutant (RIP3 K51A) was generated by QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies). Mouse RIP3, RIP1, MLKL, and CYLD siRNAs were synthesized by GenePharma: RIP3-1 (cccgacgaugucuucugucaa), RIP3-2 (cuccuuaaagucaauaaacau), RIP1-1 (ccacuagucugacugauga), RIP1-2 (ucaccaauguugcaggaua), CYLD-1 (uccauugaggauguaaauaaa), CYLD-2 (aaggguugaaccauuguuaaa), MLKL-1 (gagauccaguucaacgaua), and MLKL-2 (uaccaucaaaguauucaacaa).
### 2.5. Nissl Staining
The mice were sacrificed 72 h after intracerebroventricular injection of TNFα. Brains were dissected out of the skull and put in 4% paraformaldehyde to fix the tissue for 24 hours at room temperature and then stored in 30% sucrose phosphate buffer overnight until the tissue sank to the bottom of the solution. 20 μm sections were cut in the coronal plane using a freezing microtome (Leica CM19500) and mounted on gelatin coated slides. The sections were further stained in 0.1% cresyl violet solution (Sigma-Aldrich) at 37°C for several minutes. Rinse quickly in distilled water followed by differentiation in 95% ethyl alcohol and check microscopically for best result. Dehydrate in 100% alcohol and clear in xylene. Finally, the sections were mounted using a neutral balsam and photos were taken under microscope.
### 2.6. Western Blot Analysis
Cell pellets were lysed in lysis buffer containing 20 mM Tris-Hcl (pH 8.0), 150 mM NaCl, 1% Triton X-100, 1% Glycerol, 0.5 mM DTT, 1 mM Na3VO4, 25 mMβ-glycerol-phosphate, and 1 mM PMSF supplemented with protease inhibitor cocktail (Roche). The mouse tissue was grinded and resuspended in lysis buffer with 0.1% SDS. The resuspended cell pellet or tissue was vortexed for 10 seconds, then incubated on ice for 20 min, and then centrifuged at 20,000 g for 20 min. Protein concentration was determined by Quick Start Bradford 1x Dye Reagent (Bio-Rad). The protein samples were prepared for western blot analysis.
### 2.7. Generation of Stable Cell Lines
293T cells werecotransfected with lentiviral expression construct and packaging plasmids mix, and viral particles were collected after 48 hours and 72 hours. HT-22 cells were infected with lentivirus containing RIP3, RIP3K51A, and RIP3-RHIM-Mut, respectively. 72 hours later cells were selected with GFP by fluorescence-activated cell sorting.
### 2.8. Transfection and Cell Viability Assay
HT-22 cells were transfected with siRNAs by Lipofectamine RNAiMAX Reagent (Invitrogen) for 60 h and then treated with the indicated drug for about 20 h. Cell survival was determined by Cell Titer-Glo Luminescent Cell Viability Assay kit (Promega).
## 2.1. Animal Models
RIP3 knockout mice were generated as described previously [11] and crossed to C57BL/6 mice for ten generations. Female wild-type and RIP3 knockout mice at 6–8 weeks of age received intracerebroventricular injection of TNF-α. In brief, 2.5 μg or 5 μg TNF-α was dissolved in PBS to make a total volume of 20 μL and then injected into each lateral ventricle. The control group mice received 20 μL PBS. After 3 days, mice were scarified and the proteins were extracted from hippocampus and subjected to western blot analysis. Morphology of hippocampal neurons was analyzed by Nissl staining of brain sections. All animal experiments were performed in accordance with protocols by the Institutional Animal Care and Use Committee at Soochow University.
## 2.2. Reagents
Dulbecco’s modified Eagle’s medium (DMEM) was from Thermo. Penicillin/streptomycin, L-Glutamine, and fetal bovine serum (FBS) were from GIBCO. BHA, NAC, phosphate buffered saline (PBS), and Lanthanum(III) chloride heptahydrate (LaCl3·7H2O) were from Sigma. Recombinant TNF-α was purified as described previously [11]. z-VAD was from Bachem. Necrostatin-1 was from Alexis Biochemicals. Propidium Iodide was from Biouniquer. The following antibodies were used for western blotting: mouse RIP3 (Prosci, 2283), RIP1 (BD Biosciences, 610459), mouse CYLD (Cell Signaling, 437700), caspase-3 (Cell Signaling, 9662), and β-actin (Sigma).
## 2.3. Cell Culture
Mouse hippocampal neuron (HT-22) cells were a gift from the Lab of Dr. Zhenghong Qin (Soochow University). Mouse embryonic fibroblasts (MEFs) were isolated from day 14.5–15.5 embryos. These cells were grown in DMEM supplemented with 10% fetal bovine serum.
## 2.4. Plasmids and Oligos
Lentiviral expression construct containing mouse RIP3 was amplified from RIP3 plasmid with primers containing an N-terminal Flag epitope and then cloned into pCAG-MCS-IRES vector that was a gift from the Lab of Dr. Yun Zhao (Soochow University). Lentiviral expression construct containing RIP3-RHIM domain mutant (RIP3-RHIM-Mut) or RIP3 kinase mutant (RIP3 K51A) was generated by QuikChange Lightning Site-Directed Mutagenesis Kit (Agilent Technologies). Mouse RIP3, RIP1, MLKL, and CYLD siRNAs were synthesized by GenePharma: RIP3-1 (cccgacgaugucuucugucaa), RIP3-2 (cuccuuaaagucaauaaacau), RIP1-1 (ccacuagucugacugauga), RIP1-2 (ucaccaauguugcaggaua), CYLD-1 (uccauugaggauguaaauaaa), CYLD-2 (aaggguugaaccauuguuaaa), MLKL-1 (gagauccaguucaacgaua), and MLKL-2 (uaccaucaaaguauucaacaa).
## 2.5. Nissl Staining
The mice were sacrificed 72 h after intracerebroventricular injection of TNFα. Brains were dissected out of the skull and put in 4% paraformaldehyde to fix the tissue for 24 hours at room temperature and then stored in 30% sucrose phosphate buffer overnight until the tissue sank to the bottom of the solution. 20 μm sections were cut in the coronal plane using a freezing microtome (Leica CM19500) and mounted on gelatin coated slides. The sections were further stained in 0.1% cresyl violet solution (Sigma-Aldrich) at 37°C for several minutes. Rinse quickly in distilled water followed by differentiation in 95% ethyl alcohol and check microscopically for best result. Dehydrate in 100% alcohol and clear in xylene. Finally, the sections were mounted using a neutral balsam and photos were taken under microscope.
## 2.6. Western Blot Analysis
Cell pellets were lysed in lysis buffer containing 20 mM Tris-Hcl (pH 8.0), 150 mM NaCl, 1% Triton X-100, 1% Glycerol, 0.5 mM DTT, 1 mM Na3VO4, 25 mMβ-glycerol-phosphate, and 1 mM PMSF supplemented with protease inhibitor cocktail (Roche). The mouse tissue was grinded and resuspended in lysis buffer with 0.1% SDS. The resuspended cell pellet or tissue was vortexed for 10 seconds, then incubated on ice for 20 min, and then centrifuged at 20,000 g for 20 min. Protein concentration was determined by Quick Start Bradford 1x Dye Reagent (Bio-Rad). The protein samples were prepared for western blot analysis.
## 2.7. Generation of Stable Cell Lines
293T cells werecotransfected with lentiviral expression construct and packaging plasmids mix, and viral particles were collected after 48 hours and 72 hours. HT-22 cells were infected with lentivirus containing RIP3, RIP3K51A, and RIP3-RHIM-Mut, respectively. 72 hours later cells were selected with GFP by fluorescence-activated cell sorting.
## 2.8. Transfection and Cell Viability Assay
HT-22 cells were transfected with siRNAs by Lipofectamine RNAiMAX Reagent (Invitrogen) for 60 h and then treated with the indicated drug for about 20 h. Cell survival was determined by Cell Titer-Glo Luminescent Cell Viability Assay kit (Promega).
## 3. Results
### 3.1. The Regulation of RIP3 in TNF-α-Induced Toxicity of Hippocampal NeuronsIn Vivo
RIP3 is a key molecule regulating necroptosis induced by TNF family cytokines and ligands of TLR3/4. Elevated expression of RIP3 protein is observed in the damage tissues and correlates with active necroptosis during the pathogenesis of diseases such as acute pancreatitis, retinal detachment, and liver injury [11, 22, 23]. To assess the role of necroptosis in TNF-α-induced neurotoxicity, we challenged wild-type and RIP3-deficient mice with intracerebroventricular injection of TNF-α. Histological analysis with Nissl staining of neurons was performed to evaluate TNF-α-induced damage of neurons. We observed that administration of TNF-α to wild-type mice caused a reduction in neuronal density in the hippocampus especially CA3 region in a dose-dependent manner as compared with control-treated mice (Figure 1(a)). Notably, no obvious loss of hippocampal neurons was observed in RIP3-deficient mice after treatment of TNF-α (Figure 1(a)). Moreover, we noticed that the expression levels of RIP1 and RIP3 were increased in the hippocampus after TNF-α treatment (Figure 1(b)), while there is no detectable activation of caspase-3 which is an executioner caspase activated via proteolytic cleavage during apoptosis (Figure 1(c)), indicating that necroptosis but not apoptosis is activated by the injection of TNF-α. These results indicate that necroptosis is activated in CNS and contributes to the toxicity of hippocampal neurons in response to TNF-α.The regulation of RIP3 in TNF-α-induced toxicity of hippocampal neuronsin vivo. (a) Nissl staining of hippocampal neurons 72 h after treatment. Wild-type (WT) and RIP3 knockout (KO) mice received intracerebroventricular injection of PBS or the indicated dose of TNF-α. The neurons of brain sections from WT and KO mice were analyzed by Nissl staining (n=7) and morphology of hippocampal CA3 region was shown. Arrows indicate the loss of hippocampal neurons. (b) and (c) Expressions of RIP1, RIP3, and caspase-3 in the hippocampus after TNF-α treatment. Proteins extracted from hippocampus in the wild-type mice treated with PBS or TNF-α were analyzed by western blot using indicated antibodies. PC: MEF cells were treated with staurosporine at 150 nM for 15 hours. The results shown here are representative of five mice.
(a)
(b)
(c)
### 3.2. HT-22 Hippocampal Neurons Are Committed to Necrosis rather than Apoptosis in Response to TNF-α
Having observed RIP3-mediated necroptosis in TNF-α-induced toxicity of hippocampal neuronsin vivo, we sought to clarify the molecule mechanism underling TNF-α-induced neurotoxicity in HT-22 hippocampal neuronal cell line, which is often employed as anin vitro model of hippocampal neuron. We observed that HT-22 cells were resistant to TNF-α, even in the presence of Smac mimetic, a compound which can mimic the function of proapoptotic protein Smac/Diablo and induces apoptosis as a single agent or in combination with TNF-α [24, 25] (Figure 2(a)). Notably, addition of caspase inhibitor, z-VAD, sensitized HT-22 cells to death in response to TNF-α in a dose-dependent manner (Figure 2(a)). Propidium iodide (PI) positive cells were detected in TNF/z-VAD treated HT-22 cells (Figure 2(b)), suggesting that these cells lost membrane permeability and underwent necrosis. Taken together, these data demonstrate that HT-22 hippocampal neuronal cells are committed to TNF-α-induced necrosis rather than apoptosis.HT-22 hippocampal neurons are committed to necrosis rather than apoptosis in response to TNF-α. (a) HT-22 hippocampal neuronal cells were treated as indicated for 20 h. Cell viability was determined by measuring ATP levels. Data are represented as mean ± standard deviation of duplicates. T: TNF-α; S: Smac mimetic (100 nM); and Z: z-VAD (20μM). (b) HT-22 hippocampal neurons were treated with DMSO or TNF-α (300 ng/mL)/z-VAD for 20 h and then analyzed for PI staining by flow cytometry. Identical concentrations were used in later experiments. Data are represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus control. All experiments were repeated three times with similar results.
(a)
(b)
### 3.3. TNF-α-Induced Necrosis of HT-22 Cells Is Mediated by CYLD-RIP1-RIP3-MLKL Signaling Pathway
RIP3 kinase is a key determinant for necroptosis. RIP3 protein contains an N-terminal serine/threonine kinase domain and a C-terminal RIP homotypic interaction motif (RHIM). The kinase activity and RHIM domain of RIP3 are critical for its function in mediating necroptosis [11]. We examined the role of RIP3 in TNF-α-induced necrosis in HT-22 cells by RNAi approach. Knockdown of endogenous RIP3 greatly blocked TNF-α-induced necrosis (Figures 3(a) and 3(b)), which was restored by stable expression of a shRNA-resistant wild-type RIP3, but not a shRNA-resistant kinase dead form or RHIM mutant form of RIP3 (Figures 3(c) and 3(d)), indicating that both kinase activity and RHIM domain of RIP3 are crucial for TNF-α-induced necrosis of HT-22 cells.TNF-α-induced necrosis of HT-22 cells depends on RIP3 and its kinase activity. (a) HT-22 cells were transfected with the negative control (NC) or RIP3 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of RIP3 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP3 and β-actin levels. (c) HT-22 cells stably expressing a siRNA-resistant WT-RIP3 or RIP3-K51A or RIP3-RHIM-Mut were transfected with the control or RIP3 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. WT-RIP3: HT-22 cells stably expressing a siRNA-resistant wild-type form of RIP3; RIP3-K51A: HT-22 cells stably expressing a siRNA-resistant RIP3 kinase dead mutant. RIP3-RHIM Mut: HT-22 cells stably expressing a siRNA-resistant RHIM domain mutant form of RIP3. (d) The knockdown efficiency of RIP3 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP3 and β-actin levels. All experiments were repeated three times with similar results.
(a)
(b)
(c)
(d)RHIM domain of RIP3 is known to be critical for its interaction with RIP1 during necroptosis [26]. We further tested whether RIP1 is required for TNF-α-induced necrosis of HT-22 cells. As shown in Figures 4(a) and 4(b), reducing endogenous RIP1 suppressed TNF-α-induced necrosis. In addition, knockdown of CYLD, a deubiquitinase of RIP1, blocked TNF-α-induced necrosis of HT-22 cells (Figures 4(c) and 4(d)).RIP1 and its deubiquitinase CYLD are required for TNF-α-induced necrosis of HT-22 cells. (a) HT-22 cells were transfected with the negative control or RIP1 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of RIP1 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP1 and β-actin levels. (c) HT-22 cells were transfected with the negative control or CYLD siRNAs. Forty-eight hours after transfection, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (d) The knockdown efficiency of CYLD RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of CYLD and β-actin levels. All experiments were repeated three times with similar results.
(a)
(b)
(c)
(d)MLKL is a kinase-like protein and functions as a substrate of RIP3. To assess the requirement of MLKL in TNF-α-induced necrosis of HT-22 cells, we performed MLKL RNAi in the cells and found knockdown of MLKL efficiently reduced the cell death (Figures 5(a) and 5(b)).MLKL is essential for TNF-α-induced necrosis of HT-22 cells. (a) HT-22 cells were transfected with the negative control or MLKL siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of MLKL RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of MLKL and β-actin levels. All experiments were repeated three times with similar results.
(a)
(b)
### 3.4. TNF-α-Induced Necroptosis of HT-22 Cells Is Largely Independent of ROS Accumulation and Calcium Influx
We and others have shown that ROS accumulation is required for RIP3-mediated necrosis in certain cell lines such as mouse embryonic fibroblast (MEF) [13, 18], so we evaluated the role of ROS in TNF-α-induced necroptosis of HT-22 cells by using two widely used ROS scavengers, butylated hydroxyanisole (BHA) and N-acetylcysteine (NAC). MEF cells are known to undergo necroptosis in response to TNF-α, Smac mimetic and z-VAD. In the presence of BHA at 100 μM, the survival rate of HT-22 cells was increased by 13% and around 30% cells still underwent necrosis in response to TNF-α plus z-VAD, while TNF-α-induced necrosis in MEF cells was entirely prevented by BHA (Figures 6(a) and 6(b)). NAC had no inhibitory effect on TNF-α-induced necrosis of HT-22 cells, whereas the survival rate of MEF cells treated with necroptotic stimuli was increased by 40% after the addition of NAC at 10 mM (Figures 6(a) and 6(b)). Recently, calcium influx has been reported to be essential for necroptosis. We tested whether calcium influx is involved in TNF-α-induced necroptosis of HT-22. As shown in Figure 6(c), inhibition of calcium influx by the addition of LaCl3, a non-voltage-sensitive channel blocker, increased the survival rate of HT-22 by around 14%. Notably, TNF-α-induced necroptosis of HT-22 cells largely proceeded even in the presence of both LaCl3 and NAC (Figure 6(c)). These results demonstrated that TNF-α-initiated necroptosis in HT-22 cells is largely independent of ROS accumulation and calcium influx.TNF-α-induced necrosis of HT-22 cells is largely independent of ROS accumulation and calcium. (a) HT-22 cells were treated with control or BHA or NAC at the indicated concentration 3 h before the treatment of control or TNF-α/z-VAD for 20 h; cell viability was determined by measuring ATP levels. *P<0.01, **P<0.001 versus control-T+Z. (b) MEF cells were treated with control or BMS NAC at the indicated concentration 3 h before the treatment of control or TNF-α/Smac mimetic/z-VAD for 20 h; cell viability was determined by measuring ATP levels. *P<0.01, **P<0.001 versus control-T+S+Z. (c) HT-22 cells were treated with control or LaCl3 or NAC at the indicated concentration 3 h before the treatment of control or TNF-α/z-VAD for 20 h; cell viability was determined by measuring ATP levels. Data are represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus control-T+Z. All experiments were repeated three times with similar results.
(a)
(b)
(c)
## 3.1. The Regulation of RIP3 in TNF-α-Induced Toxicity of Hippocampal NeuronsIn Vivo
RIP3 is a key molecule regulating necroptosis induced by TNF family cytokines and ligands of TLR3/4. Elevated expression of RIP3 protein is observed in the damage tissues and correlates with active necroptosis during the pathogenesis of diseases such as acute pancreatitis, retinal detachment, and liver injury [11, 22, 23]. To assess the role of necroptosis in TNF-α-induced neurotoxicity, we challenged wild-type and RIP3-deficient mice with intracerebroventricular injection of TNF-α. Histological analysis with Nissl staining of neurons was performed to evaluate TNF-α-induced damage of neurons. We observed that administration of TNF-α to wild-type mice caused a reduction in neuronal density in the hippocampus especially CA3 region in a dose-dependent manner as compared with control-treated mice (Figure 1(a)). Notably, no obvious loss of hippocampal neurons was observed in RIP3-deficient mice after treatment of TNF-α (Figure 1(a)). Moreover, we noticed that the expression levels of RIP1 and RIP3 were increased in the hippocampus after TNF-α treatment (Figure 1(b)), while there is no detectable activation of caspase-3 which is an executioner caspase activated via proteolytic cleavage during apoptosis (Figure 1(c)), indicating that necroptosis but not apoptosis is activated by the injection of TNF-α. These results indicate that necroptosis is activated in CNS and contributes to the toxicity of hippocampal neurons in response to TNF-α.The regulation of RIP3 in TNF-α-induced toxicity of hippocampal neuronsin vivo. (a) Nissl staining of hippocampal neurons 72 h after treatment. Wild-type (WT) and RIP3 knockout (KO) mice received intracerebroventricular injection of PBS or the indicated dose of TNF-α. The neurons of brain sections from WT and KO mice were analyzed by Nissl staining (n=7) and morphology of hippocampal CA3 region was shown. Arrows indicate the loss of hippocampal neurons. (b) and (c) Expressions of RIP1, RIP3, and caspase-3 in the hippocampus after TNF-α treatment. Proteins extracted from hippocampus in the wild-type mice treated with PBS or TNF-α were analyzed by western blot using indicated antibodies. PC: MEF cells were treated with staurosporine at 150 nM for 15 hours. The results shown here are representative of five mice.
(a)
(b)
(c)
## 3.2. HT-22 Hippocampal Neurons Are Committed to Necrosis rather than Apoptosis in Response to TNF-α
Having observed RIP3-mediated necroptosis in TNF-α-induced toxicity of hippocampal neuronsin vivo, we sought to clarify the molecule mechanism underling TNF-α-induced neurotoxicity in HT-22 hippocampal neuronal cell line, which is often employed as anin vitro model of hippocampal neuron. We observed that HT-22 cells were resistant to TNF-α, even in the presence of Smac mimetic, a compound which can mimic the function of proapoptotic protein Smac/Diablo and induces apoptosis as a single agent or in combination with TNF-α [24, 25] (Figure 2(a)). Notably, addition of caspase inhibitor, z-VAD, sensitized HT-22 cells to death in response to TNF-α in a dose-dependent manner (Figure 2(a)). Propidium iodide (PI) positive cells were detected in TNF/z-VAD treated HT-22 cells (Figure 2(b)), suggesting that these cells lost membrane permeability and underwent necrosis. Taken together, these data demonstrate that HT-22 hippocampal neuronal cells are committed to TNF-α-induced necrosis rather than apoptosis.HT-22 hippocampal neurons are committed to necrosis rather than apoptosis in response to TNF-α. (a) HT-22 hippocampal neuronal cells were treated as indicated for 20 h. Cell viability was determined by measuring ATP levels. Data are represented as mean ± standard deviation of duplicates. T: TNF-α; S: Smac mimetic (100 nM); and Z: z-VAD (20μM). (b) HT-22 hippocampal neurons were treated with DMSO or TNF-α (300 ng/mL)/z-VAD for 20 h and then analyzed for PI staining by flow cytometry. Identical concentrations were used in later experiments. Data are represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus control. All experiments were repeated three times with similar results.
(a)
(b)
## 3.3. TNF-α-Induced Necrosis of HT-22 Cells Is Mediated by CYLD-RIP1-RIP3-MLKL Signaling Pathway
RIP3 kinase is a key determinant for necroptosis. RIP3 protein contains an N-terminal serine/threonine kinase domain and a C-terminal RIP homotypic interaction motif (RHIM). The kinase activity and RHIM domain of RIP3 are critical for its function in mediating necroptosis [11]. We examined the role of RIP3 in TNF-α-induced necrosis in HT-22 cells by RNAi approach. Knockdown of endogenous RIP3 greatly blocked TNF-α-induced necrosis (Figures 3(a) and 3(b)), which was restored by stable expression of a shRNA-resistant wild-type RIP3, but not a shRNA-resistant kinase dead form or RHIM mutant form of RIP3 (Figures 3(c) and 3(d)), indicating that both kinase activity and RHIM domain of RIP3 are crucial for TNF-α-induced necrosis of HT-22 cells.TNF-α-induced necrosis of HT-22 cells depends on RIP3 and its kinase activity. (a) HT-22 cells were transfected with the negative control (NC) or RIP3 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of RIP3 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP3 and β-actin levels. (c) HT-22 cells stably expressing a siRNA-resistant WT-RIP3 or RIP3-K51A or RIP3-RHIM-Mut were transfected with the control or RIP3 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. WT-RIP3: HT-22 cells stably expressing a siRNA-resistant wild-type form of RIP3; RIP3-K51A: HT-22 cells stably expressing a siRNA-resistant RIP3 kinase dead mutant. RIP3-RHIM Mut: HT-22 cells stably expressing a siRNA-resistant RHIM domain mutant form of RIP3. (d) The knockdown efficiency of RIP3 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP3 and β-actin levels. All experiments were repeated three times with similar results.
(a)
(b)
(c)
(d)RHIM domain of RIP3 is known to be critical for its interaction with RIP1 during necroptosis [26]. We further tested whether RIP1 is required for TNF-α-induced necrosis of HT-22 cells. As shown in Figures 4(a) and 4(b), reducing endogenous RIP1 suppressed TNF-α-induced necrosis. In addition, knockdown of CYLD, a deubiquitinase of RIP1, blocked TNF-α-induced necrosis of HT-22 cells (Figures 4(c) and 4(d)).RIP1 and its deubiquitinase CYLD are required for TNF-α-induced necrosis of HT-22 cells. (a) HT-22 cells were transfected with the negative control or RIP1 siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of RIP1 RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of RIP1 and β-actin levels. (c) HT-22 cells were transfected with the negative control or CYLD siRNAs. Forty-eight hours after transfection, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (d) The knockdown efficiency of CYLD RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of CYLD and β-actin levels. All experiments were repeated three times with similar results.
(a)
(b)
(c)
(d)MLKL is a kinase-like protein and functions as a substrate of RIP3. To assess the requirement of MLKL in TNF-α-induced necrosis of HT-22 cells, we performed MLKL RNAi in the cells and found knockdown of MLKL efficiently reduced the cell death (Figures 5(a) and 5(b)).MLKL is essential for TNF-α-induced necrosis of HT-22 cells. (a) HT-22 cells were transfected with the negative control or MLKL siRNAs. After 60 h, cells were treated with control or TNF-α/z-VAD for another 20 h and then cell viability was determined by measuring ATP levels. Data were represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus NC-T+Z. (b) The knockdown efficiency of MLKL RNAi. Cell lysates were collected 60 h after transfection and subjected to western blot analysis of MLKL and β-actin levels. All experiments were repeated three times with similar results.
(a)
(b)
## 3.4. TNF-α-Induced Necroptosis of HT-22 Cells Is Largely Independent of ROS Accumulation and Calcium Influx
We and others have shown that ROS accumulation is required for RIP3-mediated necrosis in certain cell lines such as mouse embryonic fibroblast (MEF) [13, 18], so we evaluated the role of ROS in TNF-α-induced necroptosis of HT-22 cells by using two widely used ROS scavengers, butylated hydroxyanisole (BHA) and N-acetylcysteine (NAC). MEF cells are known to undergo necroptosis in response to TNF-α, Smac mimetic and z-VAD. In the presence of BHA at 100 μM, the survival rate of HT-22 cells was increased by 13% and around 30% cells still underwent necrosis in response to TNF-α plus z-VAD, while TNF-α-induced necrosis in MEF cells was entirely prevented by BHA (Figures 6(a) and 6(b)). NAC had no inhibitory effect on TNF-α-induced necrosis of HT-22 cells, whereas the survival rate of MEF cells treated with necroptotic stimuli was increased by 40% after the addition of NAC at 10 mM (Figures 6(a) and 6(b)). Recently, calcium influx has been reported to be essential for necroptosis. We tested whether calcium influx is involved in TNF-α-induced necroptosis of HT-22. As shown in Figure 6(c), inhibition of calcium influx by the addition of LaCl3, a non-voltage-sensitive channel blocker, increased the survival rate of HT-22 by around 14%. Notably, TNF-α-induced necroptosis of HT-22 cells largely proceeded even in the presence of both LaCl3 and NAC (Figure 6(c)). These results demonstrated that TNF-α-initiated necroptosis in HT-22 cells is largely independent of ROS accumulation and calcium influx.TNF-α-induced necrosis of HT-22 cells is largely independent of ROS accumulation and calcium. (a) HT-22 cells were treated with control or BHA or NAC at the indicated concentration 3 h before the treatment of control or TNF-α/z-VAD for 20 h; cell viability was determined by measuring ATP levels. *P<0.01, **P<0.001 versus control-T+Z. (b) MEF cells were treated with control or BMS NAC at the indicated concentration 3 h before the treatment of control or TNF-α/Smac mimetic/z-VAD for 20 h; cell viability was determined by measuring ATP levels. *P<0.01, **P<0.001 versus control-T+S+Z. (c) HT-22 cells were treated with control or LaCl3 or NAC at the indicated concentration 3 h before the treatment of control or TNF-α/z-VAD for 20 h; cell viability was determined by measuring ATP levels. Data are represented as mean ± standard deviation of duplicates. *P<0.01, **P<0.001 versus control-T+Z. All experiments were repeated three times with similar results.
(a)
(b)
(c)
## 4. Discussion
TNF-α is a key mediator of neuroinflammation. Elevated levels of TNF-α are associated with various neurodegenerative conditions and contribute to neurotoxicity. The mechanisms underlying TNF-α-initiated neurotoxicity are largely unknown. Our present work revealed an important role of necroptosis in TNF-α-induced toxicity of hippocampal neurons.Necroptosis is a form of programmed necrosis which is regulated by RIP1 and RIP3 kinases. Apoptosis is known to negatively regulate necroptosis via active caspase-8, which is able to cleave necrosis regulators including RIP1, RIP3, and CYLD [8]. A recent work has shown that mutating the caspase-8 cleavage site at Asp 215 of CYLD is sufficient to promote necroptosis even in the absence of caspase inhibitor, indicating that caspase-8 prevents necroptosis through processing CYLD [27]. CYLD was originally thought to deubiquitinate RIP1 at the membrane receptor complex and promote the recruitment of RIP1 into the necrosome. Recently, it was shown to control the deubiquitination of RIP1 and it facilitates kinase activation in the necrosome [17]. Among the components of necrosome, MLKL is a functional substrate of RIP3. Upon the phosphorylation of MLKL by RIP3, MLKL forms oligomers and locates to the cell plasma membrane [19, 28, 29]. Although mechanisms of necroptosis are extensively studied, there is little known about the machinery of necroptosis in neuronal cells. In this study, we found that HT-22 hippocampal neurons are committed to necroptosis rather than apoptosis in response to TNF-α. Using RNAi approach, we demonstrated that TNF-α-induced neuronal necrosis is mediated by CYLD-RIP1-RIP3-MLKL signaling pathway. Our present study suggests that the core components of necrosome have conserved roles in neuronal necrosis initiated by TNF-α.Necroptotic cell death is characterized by disrupted plasma membrane; however, the downstream events of necrosome leading to collapse of membrane are largely unknown. ROS production has been shown to be required for necroptosis in several mouse cell lines including L929, MEF, NIH3T3, and macrophages, whereas it is not involved in necroptosis in HT-29 human colon cancer cells [30]. NADPH oxidase NOX1 and metabolic enzymes have been implicated in the control of ROS production during necroptosis [13, 31]. We have shown that TNF-α-induced necroptosis of HT-22 cells mouse hippocampal neurons is largely independent of ROS accumulation. Recently, TRPM7 has been identified to mediate calcium influx through acting downstream of MLKL membrane localization in TNF-α-induced necroptosis [28]. In our study, we showed that TNF-α-induced necroptosis of HT-22 cells largely proceeds even in the presence of calcium channel inhibitor and ROS scavenger. The data indicate that TNF-α-induced necroptosis of HT-22 cells largely bypasses ROS accumulation and calcium influx. Therefore, it is tempting to speculate that different downstream responses activated by necrosome depend on cell type. Future studies are required to clarify crucial downstream events for the execution of necroptosis in hippocampal neurons.Necroptosis is emerging as an important process involved in various pathological conditions including ischemic injury, acute pancreatitis, inflammatory bowel disease, and neuronal damage. Recent studies have demonstrated that increased level of RIP3 expression in the damage tissue correlates with the induction of necroptosis in the mouse models of acute pancreatitis and inflammatory bowel disease (IBD) [30] and patients with IBD [32]. Interestingly, we observed elevated expressions of RIP3 and RIP1 proteins and neuronal cell death in the hippocampus after intracerebroventricular injection of TNF-α. Importantly, genetic deletion of RIP3 reduced the loss of hippocampal neurons after intracerebroventricular injection of TNF-α. To our knowledge, the data represent the firstin vivo evidence for a role of RIP3 in TNF-α-induced neurotoxicity of hippocampal neurons. Blockage of necroptosis by necrostatin-1, a chemical inhibitor targeting RIP1 kinase, has provided protective effects on neuronal damage in animal models of brain injury [20], stroke [18], and amyotrophic lateral sclerosis [33]. Our study has demonstrated that necroptosis mediates TNF-α-initiated damage of hippocampal neurons. Given the elevated levels of TNF-α in the brains during various neurodegenerative diseases, neuronal cells may be susceptible to necroptosis upon stimulation of TNF-α, therefore contributing to the pathogenesis of neurodegenerative diseases. Targeted prevention of neuronal necroptosis may provide a novel therapeutic approach for the treatment of the related neurodegenerative diseases.
## 5. Conclusions
Taken together, our study revealed an important role of necroptosis in TNF-α-induced neurotoxicity. Necroptosis can be activated in the mouse hippocampus after intracerebroventricular injection of TNF-α. RIP3 deficiency attenuates TNF-α-initiated loss of hippocampal neurons. HT-22 hippocampal cells are sensitive to TNF-α only upon caspase blockage and subsequently undergo necrosis. A detailed molecular characterization demonstrates that TNF-α-induced necrosis in HT-22 cells is mediated by CYLD-RIP1-RIP3-MLKL necroptotic signaling pathway and largely independent of both ROS accumulation and calcium influx.
---
*Source: 290182-2014-07-01.xml* | 2014 |
# Advanced Information Technology Convergence
**Authors:** Jucheng Yang; Hui Cheng; Sook Yoon; Anthony T. S. Ho; Weiming Zeng
**Journal:** Journal of Electrical and Computer Engineering
(2016)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2016/2901835
---
## Body
---
*Source: 2901835-2016-06-29.xml* | 2901835-2016-06-29_2901835-2016-06-29.md | 387 | Advanced Information Technology Convergence | Jucheng Yang; Hui Cheng; Sook Yoon; Anthony T. S. Ho; Weiming Zeng | Journal of Electrical and Computer Engineering
(2016) | Engineering & Technology | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2016/2901835 | 2901835-2016-06-29.xml | ---
## Body
---
*Source: 2901835-2016-06-29.xml* | 2016 |
# Activity of Antioxidant Enzymes in the Tumor and Adjacent Noncancerous Tissues of Non-Small-Cell Lung Cancer
**Authors:** Marzena Zalewska-Ziob; Brygida Adamek; Janusz Kasperczyk; Ewa Romuk; Edyta Hudziec; Ewa Chwalińska; Katarzyna Dobija-Kubica; Paweł Rogoziński; Krzysztof Bruliński
**Journal:** Oxidative Medicine and Cellular Longevity
(2019)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2019/2901840
---
## Abstract
Lung tissue is directly exposed to high oxygen pressure, as well as increased endogenous and exogenous oxidative stress. Reactive oxygen species (ROS) generated in these conditions play an important role in the initiation and promotion of neoplastic growth. In response to oxidative stress, the antioxidant activity increases and minimizes ROS-induced injury in experimental systems. The aim of the present study was to evaluate the activity of antioxidant enzymes, such as superoxide dismutase (SOD; isoforms: Cu/ZnSOD and MnSOD), catalase (CAT), glutathione peroxidase (GPx), glutathione reductase (GR), and glutathione S-transferase (GST), along with the concentration of malondialdehyde (MDA) in tumor and adjacent noncancerous tissues of two histological types of NSCLC, i.e., adenocarcinoma and squamous cell carcinoma, collected from 53 individuals with surgically resectable NSCLC. MDA concentration was similar in tumors compared with adjacent noncancerous tissues. Tumor cells had low MnSOD activity, usually low Cu/ZnSOD activity, and almost always low catalase activity compared with those of the corresponding tumor-free lung tissues. Activities of GSH-related enzymes were significantly higher in tumor tissues, irrespective of the histological type of cancer. This pattern of antioxidant enzymes activity could possibly be the way by which tumor cells protect themselves against increased oxidative stress.
---
## Body
## 1. Introduction
During the last ten decades, lung cancer has become one of the most frequently occurring cancers and it is the leading cause of cancer-related death worldwide [1, 2]. Lung cancer usually originates from the basal epithelial cells and is classified into two types, namely, non-small-cell lung cancer (NSCLC), accounting for approximately 85% of all the cases, and small-cell lung cancer (SCLC), accounting for the remaining 15% of the cases with NSCLC. Based on the histological features, NSCLCs are classified into adenocarcinoma, squamous cell carcinoma, and large cell carcinoma, accounting for 40%, 20%, and 3% of the total lung cancer cases, respectively [3, 4].The lung is directly exposed to high oxygen pressure, environmental irritants, and pollutants including oxidants, such as oxidant gases, ultrafine particulate materials, nanoparticles from industrial pollution, and car exhaust fumes, and smoking, all of which generate free radicals. This results in oxidative stress in the lungs and other organs of the body. The inflammatory response mediated by the inhalation of microbes, mainly viruses and bacteria, is also known to be an additional endogenous source of oxidative stress [5, 6].Reactive oxygen species (ROS) are an integral part of the cell’s oxygen metabolism which play an important role in several cellular processes at physiological concentrations by activating signaling pathways necessary for cell growth and proliferation. However, an excessive production of ROS damages important macromolecules, such as DNA, proteins, and lipids [7–9]. Malondialdehyde (MDA), one of the end-products of lipid peroxidation, is a highly toxic compound, which oxidatively modifies the macromolecules within the cells by reacting with imino (=NH) and sulphydryl (-SH) groups of proteins and DNA. MDA is considered to be a biomarker of lipid oxidative damage, especially those incorporated into the cell membranes [10, 11].The lungs are protected against these oxidants by a variety of mechanisms which include a complex system of antioxidant enzymes, namely superoxide dismutase (SOD), glutathione peroxidase (GPx), glutathione reductase (GR), catalase (CAT), and nonenzymatic antioxidants (e.g., glutathione (GSH); vitamins A, C, D, and E; andβ-carotene) [5]. The destructive chain of reactions initiated by ROS can be prevented by antioxidant enzymes; however, the inability of antioxidant enzymes to counteract the intracellular ROS levels leads to metabolic disturbances and cell death.The first line of defense against ROS is SOD, which catalyzes the dismutation of superoxide anion (O2•−) into O2 and hydrogen peroxide (H2O2). Three isoforms of SOD exist in mammals: the cytoplasmic Cu/ZnSOD (SOD1), the mitochondrial MnSOD (SOD2), and the extracellular SOD (ECSOD, SOD3), all of which require catalytic metal (Cu or Mn) for activation and have been detected in human lung tissues. H2O2 generated as a result of the dismutation of O2•− by SOD is further reduced to H2O by CAT or GPx [5, 12–14].GSH, a thiol-group containing tripeptide, is synthesized from three amino acids, namely glycine, cysteine, and glutamate. GSH confers protection against oxidative stress by reducing hydroperoxides, quenching free radicals, and detoxifying xenobiotics [15]. The liver is the primary site of total body GSH turnover and accounts for over 90% of the GSH inflow into the systemic circulation. However, the concentration of GSH in the epithelial lining of human lungs is ~140 times higher than that in the circulation [5, 16]. The GSH-dependent antioxidant system consists of GSH and GSH-related enzymes which include glutathione S-transferase (GST), GPx, and GR [17]. GST catalyzes the conjugation of GSH with a variety of toxic compounds, including oxidative intermediates (such as lipids and DNA hydroperoxides and aldehydes), thereby, rendering them less toxic and facilitating their removal from the cells [18, 19]. GPx catalyzes the reduction of hydroperoxides, including lipid hydroperoxides, to water and the corresponding stable alcohols by using GSH as a substrate. This results in the oxidation of GSH yielding glutathione disulfide (GSSG), which is converted back by GR to its reduced form (GSH) [8, 17]. The shifting of the GSH/GSSG ratio towards the oxidized state in response to various intra- and extracellular environmental conditions in turn activates several signaling pathways (including protein kinase B, protein phosphatases 1 and 2A, calcineurin, nuclear factor κB, c-Jun N-terminal kinase, apoptosis signal-regulated kinase 1, and mitogen-activated protein kinase), which reduces cell proliferation and increases apoptosis [8, 20].Although oxidative stress has been implicated in several diseases including cancer, the mechanisms responsible for the induction of ROS in cancerous cells have not been fully understood. It is known that inflammation, oncogenic signals, DNA mutations, and dysfunction in the respiratory chain play an important role in inducing oxidative stress [8, 9]. The present study aims at evaluating the activity of antioxidant enzymes, such as SOD (Cu/ZnSOD, and MnSOD), CAT, GPx, GR, and GST along with the concentration of MDA in tumor and adjacent noncancerous tissues of two histological types of NSCLC.
## 2. Material and Methods
### 2.1. Patients and Samples
Our study group consisted of 53 patients (13 females and 40 males) aged between 47 to 75 years (average age:63.4±7.69years) who were diagnosed with primary NSCLC and had undergone surgery in the Thoracic Surgery Ward of the Specialist Hospital of Lung Diseases and Tuberculosis in Bystra Slaska, Poland, between 2009 and 2010. Sociodemographic characteristics, such as age, sex, and smoking status (nonsmokers and active smokers), were collected using a standard questionnaire. Tumor and adjacent noncancerous tissues after excision were evaluated for clinical parameters, such as histopathological type (adenocarcinoma/squamous cell carcinoma), pathological staging of the tumor (pTNM), and the grade of differentiation (G), independently by two pathomorphologists.
### 2.2. Preparation of Tissues
Tumor and adjacent noncancerous lung parenchymatous tissues (taken at a distance of not less than 5 cm from the visible edge of the tumor) were obtained at the time of surgical resection. Each sample was placed in a separate tube, stored at -20 °C, and transported to Department of Medical and Molecular Biology in Zabrze, Poland for determining the concentration of MDA and activity of SOD, Cu/ZnSOD, MnSOD, CAT, GPx, GR, and GST. Tissue samples were cut into small pieces, homogenized in 0.9% NaCl on ice (0.3 g of tissue in 2.7 ml NaCl) in short cycles of a few seconds, and sonicated to disintegrate the cell membranes using a UP50H ultrasonic processor (Hielscher Ultrasonics GmbH, Germany). Tissue homogenates were centrifuged at 13,000 rpm for 10 minutes at 4 °C, and the supernatants were frozen at -80 °C until biochemical parameters were analyzed. The study protocol was approved by The Ethical Committee of the Medical University of Silesia in Katowice, Poland (KNW/0022/KB1/119/I/09). All the subjects were enrolled voluntarily after being informed about the scope and goal of this trial.
### 2.3. Biochemical Analyses
#### 2.3.1. Determination of MDA Concentration
MDA concentration was measured fluorometrically using thiobarbituric acid (TBA) according to the method of Ohkawa et al. [21]. The method was slightly modified by adding sodium sulfate and 3,5-diisobutyl-4-hydroxytoluene to increase the specificity of the reaction. Fluorescence was read at the excitation and emission wavelengths of 515 and 552 nm, respectively, on an LS 45 fluorescence spectrometer (PerkinElmer, USA). Concentration of MDA was calculated by using a standard curve prepared from 1,1,3,3-tetraethoxypropane. Data was expressed as μmoles MDA per 1 g of total protein (μmol/g).
#### 2.3.2. Determination of SOD Activity
The activity of SOD (EC.1.15.1.1) in tissue homogenates was determined by following the method of Oyanagui [22]. A superoxide anion radical (O2−), produced in the reaction catalysed by xanthine oxidase, reacts with hydroxylamine to form nitric ion. Nitric ion combines with naphthalene diamine and sulfaniline acid producing a colored product. The concentration of this colored product is proportional to the activity of SOD in the samples. The absorbance was read at 560 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzymatic activity was expressed as nitrite units (NU) per 1 mg of protein in tissue. One NU is defined as 50% inhibition of nitrite ion formation under the method’s condition. KCN was used as the inhibitor of the Cu/ZnSOD isoenzyme. Cu/ZnSOD activity was calculated as the difference between total SOD activity and MnSOD activity.
#### 2.3.3. Determination of CAT Activity
CAT (EC.1.11.1.9) activity was measured in the supernatant of the lung homogenates by following the kinetic method of Aebi [23]. Briefly, 50 mM Tris/HCl buffer, pH 7.4, and perhydrol were mixed with 50 μl of homogenate. After 10 seconds, the absorbance was read at 240 nm every 30 seconds for 2 minutes using a Shimadzu UV-1700 PharmaSpec UV-Vis Spectrophotometer (Kyoto, Japan). Enzymatic activity was expressed as International Unit (IU) per 1 g of total protein (IU/g of total protein).
#### 2.3.4. Determination of GPx Activity
GPx (E.C.1.11.1.9) activity was measured by following the method of Paglia and Valentine by using GSH andtert-butyl peroxide as substrates [24]. The kinetics of changes in absorbance were read at 355 nm on a PerkinElmer Victor X3 (PerkinElmer, USA). The activity of GPx was expressed as the quantity of μmoles of a reduced form of nicotinamide adenine dinucleotide phosphate (NADPH+H+) required to recover GSH in 1 minute, and expressed as IU/g of total protein.
#### 2.3.5. Determination of GST Activity
The activity of GST (EC 2.5.1.18) was measured according to the kinetic method described by Habig and Jakoby [25]. In this method, GST reacts with 1-chloro-2,3-dinitrobenzene producing a thioether. The change in absorbance at 355 nm was monitored using a PerkinElmer Victor X3 reader. One unit of GST was defined as micromoles of thioether produced in 1 minute. The results were expressed as IU/g protein.
#### 2.3.6. Determination of GR Activity
The activity of GR (E.C.1.6.4.2) was measured in the supernatant of tissue homogenates by following Richterich’s kinetic method [26], where oxidized glutathione (GSSG) was used as a substrate. Changes in absorbance were read at 355 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzyme activity was determined as μmoles of NADPH+H+ required to replenish the concentration of GSH in 1 minute, and expressed as IU/g protein.
#### 2.3.7. Protein Concentration
Protein concentration in the samples was determined by Lowry’s method using bovine serum albumin as a standard [27].
### 2.4. Statistical Analysis
All statistical analyses were performed using Statistica 13.1 (StatSoft, USA). The normality of the result distribution was verified. Data is presented asmeanvalue±standarddeviation (SD). To determine the statistical significance of differences among various experimental groups, t-test or Mann-Whitney’s test was performed. The correlation between different variables was calculated using Pearson’s linear correlation coefficient. Statistical significance was set at a p value ≤ 0.5. The lack of statistical significance is presented as NS (nonsignificant).
## 2.1. Patients and Samples
Our study group consisted of 53 patients (13 females and 40 males) aged between 47 to 75 years (average age:63.4±7.69years) who were diagnosed with primary NSCLC and had undergone surgery in the Thoracic Surgery Ward of the Specialist Hospital of Lung Diseases and Tuberculosis in Bystra Slaska, Poland, between 2009 and 2010. Sociodemographic characteristics, such as age, sex, and smoking status (nonsmokers and active smokers), were collected using a standard questionnaire. Tumor and adjacent noncancerous tissues after excision were evaluated for clinical parameters, such as histopathological type (adenocarcinoma/squamous cell carcinoma), pathological staging of the tumor (pTNM), and the grade of differentiation (G), independently by two pathomorphologists.
## 2.2. Preparation of Tissues
Tumor and adjacent noncancerous lung parenchymatous tissues (taken at a distance of not less than 5 cm from the visible edge of the tumor) were obtained at the time of surgical resection. Each sample was placed in a separate tube, stored at -20 °C, and transported to Department of Medical and Molecular Biology in Zabrze, Poland for determining the concentration of MDA and activity of SOD, Cu/ZnSOD, MnSOD, CAT, GPx, GR, and GST. Tissue samples were cut into small pieces, homogenized in 0.9% NaCl on ice (0.3 g of tissue in 2.7 ml NaCl) in short cycles of a few seconds, and sonicated to disintegrate the cell membranes using a UP50H ultrasonic processor (Hielscher Ultrasonics GmbH, Germany). Tissue homogenates were centrifuged at 13,000 rpm for 10 minutes at 4 °C, and the supernatants were frozen at -80 °C until biochemical parameters were analyzed. The study protocol was approved by The Ethical Committee of the Medical University of Silesia in Katowice, Poland (KNW/0022/KB1/119/I/09). All the subjects were enrolled voluntarily after being informed about the scope and goal of this trial.
## 2.3. Biochemical Analyses
### 2.3.1. Determination of MDA Concentration
MDA concentration was measured fluorometrically using thiobarbituric acid (TBA) according to the method of Ohkawa et al. [21]. The method was slightly modified by adding sodium sulfate and 3,5-diisobutyl-4-hydroxytoluene to increase the specificity of the reaction. Fluorescence was read at the excitation and emission wavelengths of 515 and 552 nm, respectively, on an LS 45 fluorescence spectrometer (PerkinElmer, USA). Concentration of MDA was calculated by using a standard curve prepared from 1,1,3,3-tetraethoxypropane. Data was expressed as μmoles MDA per 1 g of total protein (μmol/g).
### 2.3.2. Determination of SOD Activity
The activity of SOD (EC.1.15.1.1) in tissue homogenates was determined by following the method of Oyanagui [22]. A superoxide anion radical (O2−), produced in the reaction catalysed by xanthine oxidase, reacts with hydroxylamine to form nitric ion. Nitric ion combines with naphthalene diamine and sulfaniline acid producing a colored product. The concentration of this colored product is proportional to the activity of SOD in the samples. The absorbance was read at 560 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzymatic activity was expressed as nitrite units (NU) per 1 mg of protein in tissue. One NU is defined as 50% inhibition of nitrite ion formation under the method’s condition. KCN was used as the inhibitor of the Cu/ZnSOD isoenzyme. Cu/ZnSOD activity was calculated as the difference between total SOD activity and MnSOD activity.
### 2.3.3. Determination of CAT Activity
CAT (EC.1.11.1.9) activity was measured in the supernatant of the lung homogenates by following the kinetic method of Aebi [23]. Briefly, 50 mM Tris/HCl buffer, pH 7.4, and perhydrol were mixed with 50 μl of homogenate. After 10 seconds, the absorbance was read at 240 nm every 30 seconds for 2 minutes using a Shimadzu UV-1700 PharmaSpec UV-Vis Spectrophotometer (Kyoto, Japan). Enzymatic activity was expressed as International Unit (IU) per 1 g of total protein (IU/g of total protein).
### 2.3.4. Determination of GPx Activity
GPx (E.C.1.11.1.9) activity was measured by following the method of Paglia and Valentine by using GSH andtert-butyl peroxide as substrates [24]. The kinetics of changes in absorbance were read at 355 nm on a PerkinElmer Victor X3 (PerkinElmer, USA). The activity of GPx was expressed as the quantity of μmoles of a reduced form of nicotinamide adenine dinucleotide phosphate (NADPH+H+) required to recover GSH in 1 minute, and expressed as IU/g of total protein.
### 2.3.5. Determination of GST Activity
The activity of GST (EC 2.5.1.18) was measured according to the kinetic method described by Habig and Jakoby [25]. In this method, GST reacts with 1-chloro-2,3-dinitrobenzene producing a thioether. The change in absorbance at 355 nm was monitored using a PerkinElmer Victor X3 reader. One unit of GST was defined as micromoles of thioether produced in 1 minute. The results were expressed as IU/g protein.
### 2.3.6. Determination of GR Activity
The activity of GR (E.C.1.6.4.2) was measured in the supernatant of tissue homogenates by following Richterich’s kinetic method [26], where oxidized glutathione (GSSG) was used as a substrate. Changes in absorbance were read at 355 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzyme activity was determined as μmoles of NADPH+H+ required to replenish the concentration of GSH in 1 minute, and expressed as IU/g protein.
### 2.3.7. Protein Concentration
Protein concentration in the samples was determined by Lowry’s method using bovine serum albumin as a standard [27].
## 2.3.1. Determination of MDA Concentration
MDA concentration was measured fluorometrically using thiobarbituric acid (TBA) according to the method of Ohkawa et al. [21]. The method was slightly modified by adding sodium sulfate and 3,5-diisobutyl-4-hydroxytoluene to increase the specificity of the reaction. Fluorescence was read at the excitation and emission wavelengths of 515 and 552 nm, respectively, on an LS 45 fluorescence spectrometer (PerkinElmer, USA). Concentration of MDA was calculated by using a standard curve prepared from 1,1,3,3-tetraethoxypropane. Data was expressed as μmoles MDA per 1 g of total protein (μmol/g).
## 2.3.2. Determination of SOD Activity
The activity of SOD (EC.1.15.1.1) in tissue homogenates was determined by following the method of Oyanagui [22]. A superoxide anion radical (O2−), produced in the reaction catalysed by xanthine oxidase, reacts with hydroxylamine to form nitric ion. Nitric ion combines with naphthalene diamine and sulfaniline acid producing a colored product. The concentration of this colored product is proportional to the activity of SOD in the samples. The absorbance was read at 560 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzymatic activity was expressed as nitrite units (NU) per 1 mg of protein in tissue. One NU is defined as 50% inhibition of nitrite ion formation under the method’s condition. KCN was used as the inhibitor of the Cu/ZnSOD isoenzyme. Cu/ZnSOD activity was calculated as the difference between total SOD activity and MnSOD activity.
## 2.3.3. Determination of CAT Activity
CAT (EC.1.11.1.9) activity was measured in the supernatant of the lung homogenates by following the kinetic method of Aebi [23]. Briefly, 50 mM Tris/HCl buffer, pH 7.4, and perhydrol were mixed with 50 μl of homogenate. After 10 seconds, the absorbance was read at 240 nm every 30 seconds for 2 minutes using a Shimadzu UV-1700 PharmaSpec UV-Vis Spectrophotometer (Kyoto, Japan). Enzymatic activity was expressed as International Unit (IU) per 1 g of total protein (IU/g of total protein).
## 2.3.4. Determination of GPx Activity
GPx (E.C.1.11.1.9) activity was measured by following the method of Paglia and Valentine by using GSH andtert-butyl peroxide as substrates [24]. The kinetics of changes in absorbance were read at 355 nm on a PerkinElmer Victor X3 (PerkinElmer, USA). The activity of GPx was expressed as the quantity of μmoles of a reduced form of nicotinamide adenine dinucleotide phosphate (NADPH+H+) required to recover GSH in 1 minute, and expressed as IU/g of total protein.
## 2.3.5. Determination of GST Activity
The activity of GST (EC 2.5.1.18) was measured according to the kinetic method described by Habig and Jakoby [25]. In this method, GST reacts with 1-chloro-2,3-dinitrobenzene producing a thioether. The change in absorbance at 355 nm was monitored using a PerkinElmer Victor X3 reader. One unit of GST was defined as micromoles of thioether produced in 1 minute. The results were expressed as IU/g protein.
## 2.3.6. Determination of GR Activity
The activity of GR (E.C.1.6.4.2) was measured in the supernatant of tissue homogenates by following Richterich’s kinetic method [26], where oxidized glutathione (GSSG) was used as a substrate. Changes in absorbance were read at 355 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzyme activity was determined as μmoles of NADPH+H+ required to replenish the concentration of GSH in 1 minute, and expressed as IU/g protein.
## 2.3.7. Protein Concentration
Protein concentration in the samples was determined by Lowry’s method using bovine serum albumin as a standard [27].
## 2.4. Statistical Analysis
All statistical analyses were performed using Statistica 13.1 (StatSoft, USA). The normality of the result distribution was verified. Data is presented asmeanvalue±standarddeviation (SD). To determine the statistical significance of differences among various experimental groups, t-test or Mann-Whitney’s test was performed. The correlation between different variables was calculated using Pearson’s linear correlation coefficient. Statistical significance was set at a p value ≤ 0.5. The lack of statistical significance is presented as NS (nonsignificant).
## 3. Results
The sociodemographic characteristics and clinical and pathological features of the study participants are presented in Table1.Table 1
The clinical and pathological features of NSCLC patients.
Variables
Number of patients (%)53 (100)
Sex
F
13 (24.53)
M
40 (75.47)
Age
≤65 years
31 (58.49)
>65 years
22 (41.51)
Histology
Squamous cell carcinoma
36 (67.93)
Adenocarcinoma
17 (32.07)
Differentiation grade
G1
0 (0)
G2
21 (39.62)
G3
32 (60.38)
T factor
T1
12 (22.64
T2
34 (64.15)
T3
7 (13.21)
N factor
N0
27 (50.94)
N1
18 (33.96)
N2
8 (15.10)
COPD
Yes
22 (41.51)
No
31 (58.49)
Smoking status
Smokers
39 (73.58)
Nonsmokers
13 (24.53)
No data
1 (1.89)
Abbreviations: G—histopathological cancer grading (G1: well differentiated; G2: moderately differentiated; G3: poorly differentiated; G4: undifferentiated); T—tumor size (T1:size≤3cm; T2: size>3cm to ≤5 cm; T3: size>5cm to 7 cm); N—metastatic lymph nodes (N0: no regional lymph node metastasis; N1: metastasis in ipsilateral peribronchial and/or hilar lymph node and intrapulmonary node; N2: metastasis in ipsilateral mediastinal and/or subcarinal lymph nodes); COPD—chronic obstructive pulmonary disease [28].The concentrations of MDA and the activities of antioxidant enzymes in the tumor and adjacent noncancerous tissues from patients with NSCLC were compared. No significant differences were observed in the concentrations of MDA and activities of MnSOD and Cu/ZnSOD, while the activities of CAT, GPx, GR, and GST were found to be significantly altered in tumor tissues compared with those in the adjacent noncancerous tissues. The activities of SOD and CAT were significantly higher in the adjacent noncancerous tissues than those in tumor tissues, while the activities of GSH-related enzymes were significantly higher in tumor tissues than in the adjacent noncancerous tissues (Table2).Table 2
Concentrations of MDA and activities of antioxidant enzymes in the tumor and adjacent noncancerous tissues of patients with NSCLC.
Parameters
Tumor tissue
Adjacent noncancerous tissue
p value
MDA (μmol/g)
0.69±0.78
0.47±0.14
NS
SOD (NU/mg)
16.26±3.96
18.53±4.51
0.016
MnSOD (NU/mg)
9.91±4.55
11.28±3.85
NS
Cu/ZnSOD (NU/mg)
6.37±4.26
7.25±2.07
NS
CAT (IU/g)
49.79±36.99
130±49.97
0.00001
GPx (IU/g)
8.61±6.34
5.58±2.66
0.004
GST (IU/g)
3.82±3.46
1.61±1.09
0.00024
GR (IU/g)
27.27±22.85
9.86±5.21
<0.001
NS—not significant.The abovementioned parameters were then compared based on the histological types of tumor. We found that the activity of GSH-related enzymes was significantly higher in cancer tissues of both adenocarcinoma and squamous cell carcinoma than in the noncancerous tissues, while the activity of CAT was significantly higher in the adjacent noncancerous tissues than in the tumor tissues. The activities of SOD and MnSOD were found to be significantly high only in noncancerous tissues of patients with squamous cell carcinoma, while their activities did not change significantly in patients diagnosed with adenocarcinoma (Table3).Table 3
Concentrations of MDA and activities of antioxidant enzymes in the cancerous and noncancerous tissues of patients with adenocarcinoma and squamous cell carcinoma.
Parameters
Adenocarcinoma
Squamous cell carcinoma
Tumor
Adjacent noncancerous tissue
p value
Tumor
Adjacent noncancerous tissue
p value
MDA (μmol/g)
0.57±0.44
0.47±0.18
NS
0.74±0.93
0.47±0.13
NS
SOD (NU/mg)
16.88±3.77
17.28±5.31
NS
15.98±4.08
19.15±4.02
0.008
MnSOD (NU/mg)
11.2±4.0
10.4±4.31
NS
9.34±4.53
11.7±3.61
0.04
Cu/ZnSOD (NU/mg)
5.76±4.29
6.86±2.6
NS
6.69±4.28
7.44±1.78
NS
CAT (IU/g)
45.4±24.93
130.64±50.2
<0.001
51.85±41.84
130.42±50.7
<0.001
GPx (IU/g)
10.75±7.54
5.95±2.47
0.04
7.58±5.52
5.4±2.73
0.05
GST (IU/g)
3.14±2.16
1.5±1.3
0.04
4.14±3.91
1.60±0.95
0.002
GR (IU/g)
28.43±16.36
8.94±3.39
<0.001
26.88±25.51
10.31±5.89
0.002
NS—not significant.No significant difference in the activity of antioxidant enzymes and concentration of MDA was observed between tumor and adjacent noncancerous tissues of patients with adenocarcinoma and squamous cell carcinoma (Table4).Table 4
Concentration of MDA and activity of antioxidant enzymes in tumor and adjacent noncancerous tissues of patients with adenocarcinoma and squamous cell carcinoma.
Parameters
Tumor
Adjacent noncancerous tissue
Adenocarcinoma
Squamous cell carcinoma
p value
Adenocarcinoma
Squamous cell carcinoma
p value
MDA (μmol/g)
0.91±1.30
0.94±1.27
NS
0.47±0.18
0.48±0.11
NS
SOD (NU/mg)
16.14±4.24
16.45±4.04
NS
17.28±5.31
19.15±4.02
NS
MnSOD (NU/mg)
10.74±4.25
10.25±5.00
NS
10.40±4.31
11.70±3.60
NS
Cu/ZnSOD (NU/mg)
5.45±3.94
6.20±4.15
NS
6.86±2.60
7.44±1.80
NS
CAT IU/g)
61.51±62.22
48.78±39.90
NS
130.64±50.30
130.42±50.71
NS
GPx (IU/g)
10.31±7.02
7.03±5.93
NS
5.94±2.47
5.40±2.73
NS
GST (IU/g)
2.90±2.11
4.15±3.74
NS
1.60±1.30
1.60±0.95
NS
GR (IU/g)
26.65±16.46
28.22±25.00
NS
8.94±3.39
10.31±5.89
NS
NS—not significant.Similarly, no significant difference was observed in the concentrations of MDA and activities of antioxidant enzymes between the tumor and adjacent noncancerous tissues of patients with different differentiation grades of tumor (G1, G2, and G3), tumor size (T1, T2, and T3), and metastatic lymph nodes (N0, N1, and N2) (data not shown).Furthermore, the correlation between the activity of antioxidant enzymes and age, and the sex of the patients was also examined. The results are presented in Table5. The activity of GST was found to be significantly higher in tumor tissues of patients who were more than 65 years old than in the group of younger patients (p=0.02). The activities of other antioxidant enzymes did not change significantly between the two groups.Table 5
Effect of age and sex of patients on the activity of antioxidant enzymes and concentration of MDA in tumor tissues.
Parameters
Age
Sex
≤65 years
>65 years
p value
Female
Male
p value
MDA (μmol/g)
0.81±1.27
1.14±1.27
NS
0.59±0.28
1.04±1.45
NS
SOD (NU/mg)
16.08±4.6
16.76±3.22
NS
16.52±4.05
16.30±4.10
NS
MnSOD (NU/mg)
10.91±4.65
9.71±4.87
NS
11.62±3.87
10.01±4.97
NS
Cu/ZnSOD (NU/mg)
5.19±3.49
7.04±4.61
NS
5.01±4.38
6.28±3.96
NS
CAT (IU/g)
59.71±51.32
43.23±41.98
NS
48.72±31.97
54.21±52.39
NS
GPx (IU/g)
7.93±6.33
8.31±6.67
NS
12.02±6.16
6.81±6.02
0.009
GST (IU/g)
2.85±2.46
5.01±3.99
0.02
3.00±1.82
4.00±3.68
NS
GR (IU/g)
23.45±15.52
33.71±29.00
NS
24.72±17.77
28.69±23.92
NS
NS—not significant.We did not find any change in the activity of antioxidant enzymes between males and females, except for the activity of GPx, which was significantly higher in women than in men (p=0.009).We also analyzed the relationship between the activity of antioxidant enzymes in tumor tissues and factors associated with carcinogenicity, such as smoking, and COPD; however, no significant relationship was observed between these parameters (data not shown).
## 4. Discussion
In patients with lung cancer, only a 16% 5-year survival rate is noted worldwide. The number of deaths due to lung cancer is expected to rise to 10 million deaths per year by 2030 [1, 2, 29]. The factors that cause lung cancer are complex and not yet fully understood. In recent years, the levels of ROS have aroused interest as signal molecules required for regulating various biological processes. It has been shown that cancer cells have increased ROS levels in comparison to their normal counterparts. This is due to an altered metabolism and mitochondrial dysfunction in cancer cells [30, 31]. ROS play a dual role as both deleterious and beneficial molecules. The “two-faced” character of ROS results from the fact that ROS within cells act as secondary messengers in intracellular signaling cascades, which induce and maintain the oncogenic phenotype of cancer cells. However, ROS can also induce cellular senescence and apoptosis and can therefore function as an antitumorigenic factor [32].
### 4.1. MDA
MDA, formed under oxidative stress conditions, is an end-product generated by the decomposition of arachidonic acid and larger polyunsaturated fatty acids, and has the ability to react with biomolecules, such as proteins or DNA [33, 34]. It has been widely used as a biomarker for lipid peroxidation, and it is known to be associated with different pathological conditions; however, its biological activity has not been studied in a dose-dependent manner [11, 35]. Moreover, several studies have evaluated the concentration of MDA in serum or urine samples of patients; however, that does not reflect the extent of oxidative damage caused by ROS in a given tissue or organ. In this study, MDA concentrations were not found to be significantly different between tumor and adjacent normal tissues of patients with NSCLC (Table 2), irrespective of the difference in histological types of NSCLC (Tables 3 and 4) or the age and sex of the patients (Table 5). Gegotek et al. reported significantly high levels of reactive aldehydes in tumor tissues of patients with NSCLC than in noncancerous tissues [36]. In a group of Algerian lung cancer patients, concentrations of MDA, determined by using the TBA method similar to our study, were significantly high in tumor tissues than in the peritumoral stroma [37]. They were also several times higher than those measured in our study. However, the TBA reacting substances (TBARs) test is known for its nonspecificity, which has led to substantial controversy over its use for the quantification of MDA levels [11]. An adequate method for the determination of MDA levels in appropriate biological samples remains to be determined.Antioxidant enzymes constitute the main defense mechanism of lung tissues against ROS-mediated injury, and their activity increases in response to oxidative stress. This has been shown to minimize ROS-mediated injury in experimental systems indicating that antioxidant levels might help in determining the role of ROS in the initiation of lung carcinogenesis [38]. In this study, we aim to evaluate the activity of antioxidant enzymes in the tumor and adjacent noncancerous tissues.
### 4.2. SOD
The first line of protection against ROS includes three isoforms of SOD, namely cytosolic Cu/ZnSOD, mitochondrial MnSOD, and extracellular SOD, which are present in the epithelial lining of blood vessels [38]. They play a major role in protecting the lungs against free radicals produced as a part of normal metabolism and also prevent the progression of oxidative stress-related lung diseases. In the present study, the activity of Cu/ZnSOD, MnSOD, and SOD was found to be higher in the adjacent noncancerous tissues than in the tumor tissues; however, this effect was significant only for SOD activity (p=0.016). The results of this study are in contrast with those of Chung-man Ho et al. who demonstrated that the activity of SOD was significantly higher in the tumor tissues than in the adjacent tumor-free lung tissues in patients with NSCLC (p=0.035) [38]. When the activities of antioxidant enzymes were compared according to the histological types of NSCLC, we observed that the activities of SOD and MnSOD in the adjacent noncancerous tissues were significantly higher in patients with squamous cell carcinoma (Table 3) than in patients with adenocarcinoma. The results obtained by Svensk et al. suggested that the activity of MnSOD increased in lung carcinoma, and this increase was more prominent in patients with squamous cell carcinoma than in patients with the other types of lung carcinomas [14]. Interestingly, no significant difference was observed in the activity of different isoforms of SOD between the adjacent nonmalignant tissues of adenocarcinoma and squamous cell carcinoma (Table 4). As rightly discussed by Kinnula and Crapo [5], it is difficult to compare the activities of the three different isoforms of SOD in the lung because they are located in compartments of different sizes and have been evaluated by several investigators using different assays, each having different sensitivities and specificities.The association of aging with oxidative stress is undisputable. Aging, resulting from the accumulation of molecular damages in DNA, proteins, and lipids, is characterized by an increase in the intracellular levels of oxidative stress. Therefore, in this study, we compared the activity of antioxidant enzymes in tumor tissues of patients with NSCLC by categorizing them in two age groups—below and above 65 years of age [39]. The activity of the three different isoforms of SOD did not change significantly between the tumor and noncancerous tissues of patients above or below 65 years of age. Similarly, no significant difference was observed in the activity of SOD between females and males (Table 5).
### 4.3. CAT
CAT, located mainly in peroxisomes, decomposes H2O2, a by-product of fatty acid oxidation, to oxygen and water. Thus, CAT confers protection against the toxic effects of H2O2 without generating intermediate free radicals, and the resulting oxygen is utilized for other metabolic processes [40]. A significant reduction in the activity of CAT has been observed in many types of cancer: head and neck, lungs, gastrointestinal tract, breasts, kidney, or leukemia [41]. In this study, CAT activity in NSCLC patients was significantly high (p=0.00001) in the adjacent noncancerous tissues (Table 2), irrespective of the different histological types of lung cancer (Table 3). Similar results were also obtained by Otsmane et al. [37]. Ho et al. [38] proposed that inflammation in the lungs may contribute to the decreased activity of catalase, resulting in an increased concentration of intracellular H2O2 and the promotion of cancer.
### 4.4. GSH-Related Enzymes
The levels of GSH and enzymes required for maintaining its levels in turn have been suggested to constitute one of the basic antioxidant defense mechanisms of the human lungs [17].Previous studies suggested that the antioxidant activity is impaired in lung cancers, and the expression of GSH-related antioxidant enzymes creates an interindividual risk factor for lung cancer [42]. In the present study, the activity of GSH-related antioxidant enzymes, namely, GPx, GST, and GR, were significantly higher in the tumor tissues than in the adjacent noncancerous lung tissues (Table 2) in patients with adenocarcinoma and squamous cell carcinoma (Table 3). However, the activity of these enzymes was not found to be significantly different between the two histological types of NSCLC (Table 4). Since GSH is essential for mounting successful immune response by activating T-lymphocytes and polymorphonuclear leukocytes for producing cytokines [43], there could be a link between the activity of GSH-related enzymes and tumor biology. Cancer tissue might be superior to adjacent noncancerous tissue in terms of its ability to decrease oxidative stress, thereby, facilitating tumor growth. The mediators and cellular effectors of inflammation are important constituents of the local environment of tumor tissue. Thus, cancer cells are able to protect themselves by increasing the intracellular concentrations of GSH. Inflammation in the tumor microenvironment aids in the proliferation and survival of malignant cells; promotes angiogenesis and metastasis; and alters immune response, response to hormones, and chemotherapeutic agents [44, 45]. Contrary to previously analyzed enzymes determined in our study, only GSH-related molecules have shown differences according to age: surprisingly GST activity was higher in the tumor tissue of patients above 65 years of age (p=0.02, Table 5). Interestingly, females with NSCLC exhibited a significantly higher activity of GPx in tumor tissues relative to men.The link between inflammation and cancer has also been confirmed by anti-inflammatory therapies that have proven to be effective in the prevention and treatment of cancer [46]. Therefore, the relationship between the activity of antioxidant enzymes and COPD was examined. Damage to the lungs in COPD is caused by oxidative stress (both exogenous resulting from smoking and endogenous), release of inflammatory cytokines, protease activity (due to the imbalance in protease : antiprotease ratio), and expression of autoantibodies [47]. This in turn can lead to airway destruction, air trapping, and lung hyperinflation [48]. Smoking is believed to be the primary cause of lung cancer. The adverse action of cigarette smoke is due to the presence of a large variety of compounds like nicotine, benzo(a)pyrene, oxidants, and free radicals that initiate, promote, and/or amplify oxidative damage [49]. Several studies have reported that cigarette smoking is associated with an increase in the incidence and severity of various diseases, such as lung cancer and COPD [6, 50]. COPD and lung cancer are caused by cigarette smoking, and there is increasing evidence linking the two diseases beyond just a common etiology. COPD is an independent risk factor for lung carcinoma, particularly for squamous cell carcinoma, and lung cancer is up to five times more likely to occur in smokers with airflow obstruction than those with normal lung function [51]. Villeneuve et al. reported that the lifetime risk of developing lung cancer is 17.2% and 11.6% for males and females, respectively, among smokers, when compared with 1.3% for males and 1.4% for females among nonsmokers [52]. In this study, we evaluated the activity of antioxidant enzymes in the tumor and adjacent noncancerous tissues obtained from patients with NSCLC. We did not find any significant difference in the activity of antioxidant enzymes between smokers and nonsmokers, and patients with or without COPD. It is possible that smoking or other inflammatory lung diseases do not have a pivotal impact on oxidative stress nascency in the initial stage of cancer development.The incidence rate of lung cancer is declining in men and plateauing in women after increasing for several decades. This lag in the temporal trend of lung cancer incidence rates in women compared with that in men is reflected in historical differences in cigarette smoking habits between men and women; cigarette smoking in women peaked about 20 years later than in men [1]. Our results suggested that the age and sex of the patients do not have any effect on the activity of antioxidant enzymes in the tumor tissues of NSCLC patients, except for the activity of GPx and GST as mentioned in Table 5. The activity of antioxidant enzymes was not found to be correlated with differentiation grade, tumor size, and metastatic lymph nodes (data not shown).In majority of the studies, the activity of antioxidant enzymes has been determined in the peripheral blood erythrocytes of patients with neoplastic diseases and not in the cancerous tissues. In this study, we evaluated the activities of antioxidant enzymes in the homogenates of lung tissue, and therefore, our results cannot always be directly compared with those reported by others. Moreover, the percentage of adeno- and squamous cell carcinomas in patients recruited in this study was different from the statistics available for general lung cancer: 32% and 67% of the cases of adenocarcinoma and squamous cell carcinoma, respectively, in this study versus 40% and 30% of the cases according to available statistics. Therefore, we have discussed our results only for NSCLC, in general, and compared the activity of antioxidant enzymes between the two histological types of lung cancer. Further studies with a large cohort of patients with NSCLC are warranted to conclusively prove our observations.
## 4.1. MDA
MDA, formed under oxidative stress conditions, is an end-product generated by the decomposition of arachidonic acid and larger polyunsaturated fatty acids, and has the ability to react with biomolecules, such as proteins or DNA [33, 34]. It has been widely used as a biomarker for lipid peroxidation, and it is known to be associated with different pathological conditions; however, its biological activity has not been studied in a dose-dependent manner [11, 35]. Moreover, several studies have evaluated the concentration of MDA in serum or urine samples of patients; however, that does not reflect the extent of oxidative damage caused by ROS in a given tissue or organ. In this study, MDA concentrations were not found to be significantly different between tumor and adjacent normal tissues of patients with NSCLC (Table 2), irrespective of the difference in histological types of NSCLC (Tables 3 and 4) or the age and sex of the patients (Table 5). Gegotek et al. reported significantly high levels of reactive aldehydes in tumor tissues of patients with NSCLC than in noncancerous tissues [36]. In a group of Algerian lung cancer patients, concentrations of MDA, determined by using the TBA method similar to our study, were significantly high in tumor tissues than in the peritumoral stroma [37]. They were also several times higher than those measured in our study. However, the TBA reacting substances (TBARs) test is known for its nonspecificity, which has led to substantial controversy over its use for the quantification of MDA levels [11]. An adequate method for the determination of MDA levels in appropriate biological samples remains to be determined.Antioxidant enzymes constitute the main defense mechanism of lung tissues against ROS-mediated injury, and their activity increases in response to oxidative stress. This has been shown to minimize ROS-mediated injury in experimental systems indicating that antioxidant levels might help in determining the role of ROS in the initiation of lung carcinogenesis [38]. In this study, we aim to evaluate the activity of antioxidant enzymes in the tumor and adjacent noncancerous tissues.
## 4.2. SOD
The first line of protection against ROS includes three isoforms of SOD, namely cytosolic Cu/ZnSOD, mitochondrial MnSOD, and extracellular SOD, which are present in the epithelial lining of blood vessels [38]. They play a major role in protecting the lungs against free radicals produced as a part of normal metabolism and also prevent the progression of oxidative stress-related lung diseases. In the present study, the activity of Cu/ZnSOD, MnSOD, and SOD was found to be higher in the adjacent noncancerous tissues than in the tumor tissues; however, this effect was significant only for SOD activity (p=0.016). The results of this study are in contrast with those of Chung-man Ho et al. who demonstrated that the activity of SOD was significantly higher in the tumor tissues than in the adjacent tumor-free lung tissues in patients with NSCLC (p=0.035) [38]. When the activities of antioxidant enzymes were compared according to the histological types of NSCLC, we observed that the activities of SOD and MnSOD in the adjacent noncancerous tissues were significantly higher in patients with squamous cell carcinoma (Table 3) than in patients with adenocarcinoma. The results obtained by Svensk et al. suggested that the activity of MnSOD increased in lung carcinoma, and this increase was more prominent in patients with squamous cell carcinoma than in patients with the other types of lung carcinomas [14]. Interestingly, no significant difference was observed in the activity of different isoforms of SOD between the adjacent nonmalignant tissues of adenocarcinoma and squamous cell carcinoma (Table 4). As rightly discussed by Kinnula and Crapo [5], it is difficult to compare the activities of the three different isoforms of SOD in the lung because they are located in compartments of different sizes and have been evaluated by several investigators using different assays, each having different sensitivities and specificities.The association of aging with oxidative stress is undisputable. Aging, resulting from the accumulation of molecular damages in DNA, proteins, and lipids, is characterized by an increase in the intracellular levels of oxidative stress. Therefore, in this study, we compared the activity of antioxidant enzymes in tumor tissues of patients with NSCLC by categorizing them in two age groups—below and above 65 years of age [39]. The activity of the three different isoforms of SOD did not change significantly between the tumor and noncancerous tissues of patients above or below 65 years of age. Similarly, no significant difference was observed in the activity of SOD between females and males (Table 5).
## 4.3. CAT
CAT, located mainly in peroxisomes, decomposes H2O2, a by-product of fatty acid oxidation, to oxygen and water. Thus, CAT confers protection against the toxic effects of H2O2 without generating intermediate free radicals, and the resulting oxygen is utilized for other metabolic processes [40]. A significant reduction in the activity of CAT has been observed in many types of cancer: head and neck, lungs, gastrointestinal tract, breasts, kidney, or leukemia [41]. In this study, CAT activity in NSCLC patients was significantly high (p=0.00001) in the adjacent noncancerous tissues (Table 2), irrespective of the different histological types of lung cancer (Table 3). Similar results were also obtained by Otsmane et al. [37]. Ho et al. [38] proposed that inflammation in the lungs may contribute to the decreased activity of catalase, resulting in an increased concentration of intracellular H2O2 and the promotion of cancer.
## 4.4. GSH-Related Enzymes
The levels of GSH and enzymes required for maintaining its levels in turn have been suggested to constitute one of the basic antioxidant defense mechanisms of the human lungs [17].Previous studies suggested that the antioxidant activity is impaired in lung cancers, and the expression of GSH-related antioxidant enzymes creates an interindividual risk factor for lung cancer [42]. In the present study, the activity of GSH-related antioxidant enzymes, namely, GPx, GST, and GR, were significantly higher in the tumor tissues than in the adjacent noncancerous lung tissues (Table 2) in patients with adenocarcinoma and squamous cell carcinoma (Table 3). However, the activity of these enzymes was not found to be significantly different between the two histological types of NSCLC (Table 4). Since GSH is essential for mounting successful immune response by activating T-lymphocytes and polymorphonuclear leukocytes for producing cytokines [43], there could be a link between the activity of GSH-related enzymes and tumor biology. Cancer tissue might be superior to adjacent noncancerous tissue in terms of its ability to decrease oxidative stress, thereby, facilitating tumor growth. The mediators and cellular effectors of inflammation are important constituents of the local environment of tumor tissue. Thus, cancer cells are able to protect themselves by increasing the intracellular concentrations of GSH. Inflammation in the tumor microenvironment aids in the proliferation and survival of malignant cells; promotes angiogenesis and metastasis; and alters immune response, response to hormones, and chemotherapeutic agents [44, 45]. Contrary to previously analyzed enzymes determined in our study, only GSH-related molecules have shown differences according to age: surprisingly GST activity was higher in the tumor tissue of patients above 65 years of age (p=0.02, Table 5). Interestingly, females with NSCLC exhibited a significantly higher activity of GPx in tumor tissues relative to men.The link between inflammation and cancer has also been confirmed by anti-inflammatory therapies that have proven to be effective in the prevention and treatment of cancer [46]. Therefore, the relationship between the activity of antioxidant enzymes and COPD was examined. Damage to the lungs in COPD is caused by oxidative stress (both exogenous resulting from smoking and endogenous), release of inflammatory cytokines, protease activity (due to the imbalance in protease : antiprotease ratio), and expression of autoantibodies [47]. This in turn can lead to airway destruction, air trapping, and lung hyperinflation [48]. Smoking is believed to be the primary cause of lung cancer. The adverse action of cigarette smoke is due to the presence of a large variety of compounds like nicotine, benzo(a)pyrene, oxidants, and free radicals that initiate, promote, and/or amplify oxidative damage [49]. Several studies have reported that cigarette smoking is associated with an increase in the incidence and severity of various diseases, such as lung cancer and COPD [6, 50]. COPD and lung cancer are caused by cigarette smoking, and there is increasing evidence linking the two diseases beyond just a common etiology. COPD is an independent risk factor for lung carcinoma, particularly for squamous cell carcinoma, and lung cancer is up to five times more likely to occur in smokers with airflow obstruction than those with normal lung function [51]. Villeneuve et al. reported that the lifetime risk of developing lung cancer is 17.2% and 11.6% for males and females, respectively, among smokers, when compared with 1.3% for males and 1.4% for females among nonsmokers [52]. In this study, we evaluated the activity of antioxidant enzymes in the tumor and adjacent noncancerous tissues obtained from patients with NSCLC. We did not find any significant difference in the activity of antioxidant enzymes between smokers and nonsmokers, and patients with or without COPD. It is possible that smoking or other inflammatory lung diseases do not have a pivotal impact on oxidative stress nascency in the initial stage of cancer development.The incidence rate of lung cancer is declining in men and plateauing in women after increasing for several decades. This lag in the temporal trend of lung cancer incidence rates in women compared with that in men is reflected in historical differences in cigarette smoking habits between men and women; cigarette smoking in women peaked about 20 years later than in men [1]. Our results suggested that the age and sex of the patients do not have any effect on the activity of antioxidant enzymes in the tumor tissues of NSCLC patients, except for the activity of GPx and GST as mentioned in Table 5. The activity of antioxidant enzymes was not found to be correlated with differentiation grade, tumor size, and metastatic lymph nodes (data not shown).In majority of the studies, the activity of antioxidant enzymes has been determined in the peripheral blood erythrocytes of patients with neoplastic diseases and not in the cancerous tissues. In this study, we evaluated the activities of antioxidant enzymes in the homogenates of lung tissue, and therefore, our results cannot always be directly compared with those reported by others. Moreover, the percentage of adeno- and squamous cell carcinomas in patients recruited in this study was different from the statistics available for general lung cancer: 32% and 67% of the cases of adenocarcinoma and squamous cell carcinoma, respectively, in this study versus 40% and 30% of the cases according to available statistics. Therefore, we have discussed our results only for NSCLC, in general, and compared the activity of antioxidant enzymes between the two histological types of lung cancer. Further studies with a large cohort of patients with NSCLC are warranted to conclusively prove our observations.
## 5. Conclusion
A significant change in the activity of antioxidant enzymes was observed during the process of carcinogenesis. Tumor cells always had low MnSOD activity, usually low Cu/ZnSOD activity, and almost always low catalase activity compared with those of the corresponding normal tissues. Activities of GSH-related enzymes were significantly high in lung cancer tissues, irrespective of the histological type of lung cancer, which could possibly be the way by which tumor cells protect themselves against increased oxidative stress.
---
*Source: 2901840-2019-10-31.xml* | 2901840-2019-10-31_2901840-2019-10-31.md | 55,470 | Activity of Antioxidant Enzymes in the Tumor and Adjacent Noncancerous Tissues of Non-Small-Cell Lung Cancer | Marzena Zalewska-Ziob; Brygida Adamek; Janusz Kasperczyk; Ewa Romuk; Edyta Hudziec; Ewa Chwalińska; Katarzyna Dobija-Kubica; Paweł Rogoziński; Krzysztof Bruliński | Oxidative Medicine and Cellular Longevity
(2019) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2019/2901840 | 2901840-2019-10-31.xml | ---
## Abstract
Lung tissue is directly exposed to high oxygen pressure, as well as increased endogenous and exogenous oxidative stress. Reactive oxygen species (ROS) generated in these conditions play an important role in the initiation and promotion of neoplastic growth. In response to oxidative stress, the antioxidant activity increases and minimizes ROS-induced injury in experimental systems. The aim of the present study was to evaluate the activity of antioxidant enzymes, such as superoxide dismutase (SOD; isoforms: Cu/ZnSOD and MnSOD), catalase (CAT), glutathione peroxidase (GPx), glutathione reductase (GR), and glutathione S-transferase (GST), along with the concentration of malondialdehyde (MDA) in tumor and adjacent noncancerous tissues of two histological types of NSCLC, i.e., adenocarcinoma and squamous cell carcinoma, collected from 53 individuals with surgically resectable NSCLC. MDA concentration was similar in tumors compared with adjacent noncancerous tissues. Tumor cells had low MnSOD activity, usually low Cu/ZnSOD activity, and almost always low catalase activity compared with those of the corresponding tumor-free lung tissues. Activities of GSH-related enzymes were significantly higher in tumor tissues, irrespective of the histological type of cancer. This pattern of antioxidant enzymes activity could possibly be the way by which tumor cells protect themselves against increased oxidative stress.
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## Body
## 1. Introduction
During the last ten decades, lung cancer has become one of the most frequently occurring cancers and it is the leading cause of cancer-related death worldwide [1, 2]. Lung cancer usually originates from the basal epithelial cells and is classified into two types, namely, non-small-cell lung cancer (NSCLC), accounting for approximately 85% of all the cases, and small-cell lung cancer (SCLC), accounting for the remaining 15% of the cases with NSCLC. Based on the histological features, NSCLCs are classified into adenocarcinoma, squamous cell carcinoma, and large cell carcinoma, accounting for 40%, 20%, and 3% of the total lung cancer cases, respectively [3, 4].The lung is directly exposed to high oxygen pressure, environmental irritants, and pollutants including oxidants, such as oxidant gases, ultrafine particulate materials, nanoparticles from industrial pollution, and car exhaust fumes, and smoking, all of which generate free radicals. This results in oxidative stress in the lungs and other organs of the body. The inflammatory response mediated by the inhalation of microbes, mainly viruses and bacteria, is also known to be an additional endogenous source of oxidative stress [5, 6].Reactive oxygen species (ROS) are an integral part of the cell’s oxygen metabolism which play an important role in several cellular processes at physiological concentrations by activating signaling pathways necessary for cell growth and proliferation. However, an excessive production of ROS damages important macromolecules, such as DNA, proteins, and lipids [7–9]. Malondialdehyde (MDA), one of the end-products of lipid peroxidation, is a highly toxic compound, which oxidatively modifies the macromolecules within the cells by reacting with imino (=NH) and sulphydryl (-SH) groups of proteins and DNA. MDA is considered to be a biomarker of lipid oxidative damage, especially those incorporated into the cell membranes [10, 11].The lungs are protected against these oxidants by a variety of mechanisms which include a complex system of antioxidant enzymes, namely superoxide dismutase (SOD), glutathione peroxidase (GPx), glutathione reductase (GR), catalase (CAT), and nonenzymatic antioxidants (e.g., glutathione (GSH); vitamins A, C, D, and E; andβ-carotene) [5]. The destructive chain of reactions initiated by ROS can be prevented by antioxidant enzymes; however, the inability of antioxidant enzymes to counteract the intracellular ROS levels leads to metabolic disturbances and cell death.The first line of defense against ROS is SOD, which catalyzes the dismutation of superoxide anion (O2•−) into O2 and hydrogen peroxide (H2O2). Three isoforms of SOD exist in mammals: the cytoplasmic Cu/ZnSOD (SOD1), the mitochondrial MnSOD (SOD2), and the extracellular SOD (ECSOD, SOD3), all of which require catalytic metal (Cu or Mn) for activation and have been detected in human lung tissues. H2O2 generated as a result of the dismutation of O2•− by SOD is further reduced to H2O by CAT or GPx [5, 12–14].GSH, a thiol-group containing tripeptide, is synthesized from three amino acids, namely glycine, cysteine, and glutamate. GSH confers protection against oxidative stress by reducing hydroperoxides, quenching free radicals, and detoxifying xenobiotics [15]. The liver is the primary site of total body GSH turnover and accounts for over 90% of the GSH inflow into the systemic circulation. However, the concentration of GSH in the epithelial lining of human lungs is ~140 times higher than that in the circulation [5, 16]. The GSH-dependent antioxidant system consists of GSH and GSH-related enzymes which include glutathione S-transferase (GST), GPx, and GR [17]. GST catalyzes the conjugation of GSH with a variety of toxic compounds, including oxidative intermediates (such as lipids and DNA hydroperoxides and aldehydes), thereby, rendering them less toxic and facilitating their removal from the cells [18, 19]. GPx catalyzes the reduction of hydroperoxides, including lipid hydroperoxides, to water and the corresponding stable alcohols by using GSH as a substrate. This results in the oxidation of GSH yielding glutathione disulfide (GSSG), which is converted back by GR to its reduced form (GSH) [8, 17]. The shifting of the GSH/GSSG ratio towards the oxidized state in response to various intra- and extracellular environmental conditions in turn activates several signaling pathways (including protein kinase B, protein phosphatases 1 and 2A, calcineurin, nuclear factor κB, c-Jun N-terminal kinase, apoptosis signal-regulated kinase 1, and mitogen-activated protein kinase), which reduces cell proliferation and increases apoptosis [8, 20].Although oxidative stress has been implicated in several diseases including cancer, the mechanisms responsible for the induction of ROS in cancerous cells have not been fully understood. It is known that inflammation, oncogenic signals, DNA mutations, and dysfunction in the respiratory chain play an important role in inducing oxidative stress [8, 9]. The present study aims at evaluating the activity of antioxidant enzymes, such as SOD (Cu/ZnSOD, and MnSOD), CAT, GPx, GR, and GST along with the concentration of MDA in tumor and adjacent noncancerous tissues of two histological types of NSCLC.
## 2. Material and Methods
### 2.1. Patients and Samples
Our study group consisted of 53 patients (13 females and 40 males) aged between 47 to 75 years (average age:63.4±7.69years) who were diagnosed with primary NSCLC and had undergone surgery in the Thoracic Surgery Ward of the Specialist Hospital of Lung Diseases and Tuberculosis in Bystra Slaska, Poland, between 2009 and 2010. Sociodemographic characteristics, such as age, sex, and smoking status (nonsmokers and active smokers), were collected using a standard questionnaire. Tumor and adjacent noncancerous tissues after excision were evaluated for clinical parameters, such as histopathological type (adenocarcinoma/squamous cell carcinoma), pathological staging of the tumor (pTNM), and the grade of differentiation (G), independently by two pathomorphologists.
### 2.2. Preparation of Tissues
Tumor and adjacent noncancerous lung parenchymatous tissues (taken at a distance of not less than 5 cm from the visible edge of the tumor) were obtained at the time of surgical resection. Each sample was placed in a separate tube, stored at -20 °C, and transported to Department of Medical and Molecular Biology in Zabrze, Poland for determining the concentration of MDA and activity of SOD, Cu/ZnSOD, MnSOD, CAT, GPx, GR, and GST. Tissue samples were cut into small pieces, homogenized in 0.9% NaCl on ice (0.3 g of tissue in 2.7 ml NaCl) in short cycles of a few seconds, and sonicated to disintegrate the cell membranes using a UP50H ultrasonic processor (Hielscher Ultrasonics GmbH, Germany). Tissue homogenates were centrifuged at 13,000 rpm for 10 minutes at 4 °C, and the supernatants were frozen at -80 °C until biochemical parameters were analyzed. The study protocol was approved by The Ethical Committee of the Medical University of Silesia in Katowice, Poland (KNW/0022/KB1/119/I/09). All the subjects were enrolled voluntarily after being informed about the scope and goal of this trial.
### 2.3. Biochemical Analyses
#### 2.3.1. Determination of MDA Concentration
MDA concentration was measured fluorometrically using thiobarbituric acid (TBA) according to the method of Ohkawa et al. [21]. The method was slightly modified by adding sodium sulfate and 3,5-diisobutyl-4-hydroxytoluene to increase the specificity of the reaction. Fluorescence was read at the excitation and emission wavelengths of 515 and 552 nm, respectively, on an LS 45 fluorescence spectrometer (PerkinElmer, USA). Concentration of MDA was calculated by using a standard curve prepared from 1,1,3,3-tetraethoxypropane. Data was expressed as μmoles MDA per 1 g of total protein (μmol/g).
#### 2.3.2. Determination of SOD Activity
The activity of SOD (EC.1.15.1.1) in tissue homogenates was determined by following the method of Oyanagui [22]. A superoxide anion radical (O2−), produced in the reaction catalysed by xanthine oxidase, reacts with hydroxylamine to form nitric ion. Nitric ion combines with naphthalene diamine and sulfaniline acid producing a colored product. The concentration of this colored product is proportional to the activity of SOD in the samples. The absorbance was read at 560 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzymatic activity was expressed as nitrite units (NU) per 1 mg of protein in tissue. One NU is defined as 50% inhibition of nitrite ion formation under the method’s condition. KCN was used as the inhibitor of the Cu/ZnSOD isoenzyme. Cu/ZnSOD activity was calculated as the difference between total SOD activity and MnSOD activity.
#### 2.3.3. Determination of CAT Activity
CAT (EC.1.11.1.9) activity was measured in the supernatant of the lung homogenates by following the kinetic method of Aebi [23]. Briefly, 50 mM Tris/HCl buffer, pH 7.4, and perhydrol were mixed with 50 μl of homogenate. After 10 seconds, the absorbance was read at 240 nm every 30 seconds for 2 minutes using a Shimadzu UV-1700 PharmaSpec UV-Vis Spectrophotometer (Kyoto, Japan). Enzymatic activity was expressed as International Unit (IU) per 1 g of total protein (IU/g of total protein).
#### 2.3.4. Determination of GPx Activity
GPx (E.C.1.11.1.9) activity was measured by following the method of Paglia and Valentine by using GSH andtert-butyl peroxide as substrates [24]. The kinetics of changes in absorbance were read at 355 nm on a PerkinElmer Victor X3 (PerkinElmer, USA). The activity of GPx was expressed as the quantity of μmoles of a reduced form of nicotinamide adenine dinucleotide phosphate (NADPH+H+) required to recover GSH in 1 minute, and expressed as IU/g of total protein.
#### 2.3.5. Determination of GST Activity
The activity of GST (EC 2.5.1.18) was measured according to the kinetic method described by Habig and Jakoby [25]. In this method, GST reacts with 1-chloro-2,3-dinitrobenzene producing a thioether. The change in absorbance at 355 nm was monitored using a PerkinElmer Victor X3 reader. One unit of GST was defined as micromoles of thioether produced in 1 minute. The results were expressed as IU/g protein.
#### 2.3.6. Determination of GR Activity
The activity of GR (E.C.1.6.4.2) was measured in the supernatant of tissue homogenates by following Richterich’s kinetic method [26], where oxidized glutathione (GSSG) was used as a substrate. Changes in absorbance were read at 355 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzyme activity was determined as μmoles of NADPH+H+ required to replenish the concentration of GSH in 1 minute, and expressed as IU/g protein.
#### 2.3.7. Protein Concentration
Protein concentration in the samples was determined by Lowry’s method using bovine serum albumin as a standard [27].
### 2.4. Statistical Analysis
All statistical analyses were performed using Statistica 13.1 (StatSoft, USA). The normality of the result distribution was verified. Data is presented asmeanvalue±standarddeviation (SD). To determine the statistical significance of differences among various experimental groups, t-test or Mann-Whitney’s test was performed. The correlation between different variables was calculated using Pearson’s linear correlation coefficient. Statistical significance was set at a p value ≤ 0.5. The lack of statistical significance is presented as NS (nonsignificant).
## 2.1. Patients and Samples
Our study group consisted of 53 patients (13 females and 40 males) aged between 47 to 75 years (average age:63.4±7.69years) who were diagnosed with primary NSCLC and had undergone surgery in the Thoracic Surgery Ward of the Specialist Hospital of Lung Diseases and Tuberculosis in Bystra Slaska, Poland, between 2009 and 2010. Sociodemographic characteristics, such as age, sex, and smoking status (nonsmokers and active smokers), were collected using a standard questionnaire. Tumor and adjacent noncancerous tissues after excision were evaluated for clinical parameters, such as histopathological type (adenocarcinoma/squamous cell carcinoma), pathological staging of the tumor (pTNM), and the grade of differentiation (G), independently by two pathomorphologists.
## 2.2. Preparation of Tissues
Tumor and adjacent noncancerous lung parenchymatous tissues (taken at a distance of not less than 5 cm from the visible edge of the tumor) were obtained at the time of surgical resection. Each sample was placed in a separate tube, stored at -20 °C, and transported to Department of Medical and Molecular Biology in Zabrze, Poland for determining the concentration of MDA and activity of SOD, Cu/ZnSOD, MnSOD, CAT, GPx, GR, and GST. Tissue samples were cut into small pieces, homogenized in 0.9% NaCl on ice (0.3 g of tissue in 2.7 ml NaCl) in short cycles of a few seconds, and sonicated to disintegrate the cell membranes using a UP50H ultrasonic processor (Hielscher Ultrasonics GmbH, Germany). Tissue homogenates were centrifuged at 13,000 rpm for 10 minutes at 4 °C, and the supernatants were frozen at -80 °C until biochemical parameters were analyzed. The study protocol was approved by The Ethical Committee of the Medical University of Silesia in Katowice, Poland (KNW/0022/KB1/119/I/09). All the subjects were enrolled voluntarily after being informed about the scope and goal of this trial.
## 2.3. Biochemical Analyses
### 2.3.1. Determination of MDA Concentration
MDA concentration was measured fluorometrically using thiobarbituric acid (TBA) according to the method of Ohkawa et al. [21]. The method was slightly modified by adding sodium sulfate and 3,5-diisobutyl-4-hydroxytoluene to increase the specificity of the reaction. Fluorescence was read at the excitation and emission wavelengths of 515 and 552 nm, respectively, on an LS 45 fluorescence spectrometer (PerkinElmer, USA). Concentration of MDA was calculated by using a standard curve prepared from 1,1,3,3-tetraethoxypropane. Data was expressed as μmoles MDA per 1 g of total protein (μmol/g).
### 2.3.2. Determination of SOD Activity
The activity of SOD (EC.1.15.1.1) in tissue homogenates was determined by following the method of Oyanagui [22]. A superoxide anion radical (O2−), produced in the reaction catalysed by xanthine oxidase, reacts with hydroxylamine to form nitric ion. Nitric ion combines with naphthalene diamine and sulfaniline acid producing a colored product. The concentration of this colored product is proportional to the activity of SOD in the samples. The absorbance was read at 560 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzymatic activity was expressed as nitrite units (NU) per 1 mg of protein in tissue. One NU is defined as 50% inhibition of nitrite ion formation under the method’s condition. KCN was used as the inhibitor of the Cu/ZnSOD isoenzyme. Cu/ZnSOD activity was calculated as the difference between total SOD activity and MnSOD activity.
### 2.3.3. Determination of CAT Activity
CAT (EC.1.11.1.9) activity was measured in the supernatant of the lung homogenates by following the kinetic method of Aebi [23]. Briefly, 50 mM Tris/HCl buffer, pH 7.4, and perhydrol were mixed with 50 μl of homogenate. After 10 seconds, the absorbance was read at 240 nm every 30 seconds for 2 minutes using a Shimadzu UV-1700 PharmaSpec UV-Vis Spectrophotometer (Kyoto, Japan). Enzymatic activity was expressed as International Unit (IU) per 1 g of total protein (IU/g of total protein).
### 2.3.4. Determination of GPx Activity
GPx (E.C.1.11.1.9) activity was measured by following the method of Paglia and Valentine by using GSH andtert-butyl peroxide as substrates [24]. The kinetics of changes in absorbance were read at 355 nm on a PerkinElmer Victor X3 (PerkinElmer, USA). The activity of GPx was expressed as the quantity of μmoles of a reduced form of nicotinamide adenine dinucleotide phosphate (NADPH+H+) required to recover GSH in 1 minute, and expressed as IU/g of total protein.
### 2.3.5. Determination of GST Activity
The activity of GST (EC 2.5.1.18) was measured according to the kinetic method described by Habig and Jakoby [25]. In this method, GST reacts with 1-chloro-2,3-dinitrobenzene producing a thioether. The change in absorbance at 355 nm was monitored using a PerkinElmer Victor X3 reader. One unit of GST was defined as micromoles of thioether produced in 1 minute. The results were expressed as IU/g protein.
### 2.3.6. Determination of GR Activity
The activity of GR (E.C.1.6.4.2) was measured in the supernatant of tissue homogenates by following Richterich’s kinetic method [26], where oxidized glutathione (GSSG) was used as a substrate. Changes in absorbance were read at 355 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzyme activity was determined as μmoles of NADPH+H+ required to replenish the concentration of GSH in 1 minute, and expressed as IU/g protein.
### 2.3.7. Protein Concentration
Protein concentration in the samples was determined by Lowry’s method using bovine serum albumin as a standard [27].
## 2.3.1. Determination of MDA Concentration
MDA concentration was measured fluorometrically using thiobarbituric acid (TBA) according to the method of Ohkawa et al. [21]. The method was slightly modified by adding sodium sulfate and 3,5-diisobutyl-4-hydroxytoluene to increase the specificity of the reaction. Fluorescence was read at the excitation and emission wavelengths of 515 and 552 nm, respectively, on an LS 45 fluorescence spectrometer (PerkinElmer, USA). Concentration of MDA was calculated by using a standard curve prepared from 1,1,3,3-tetraethoxypropane. Data was expressed as μmoles MDA per 1 g of total protein (μmol/g).
## 2.3.2. Determination of SOD Activity
The activity of SOD (EC.1.15.1.1) in tissue homogenates was determined by following the method of Oyanagui [22]. A superoxide anion radical (O2−), produced in the reaction catalysed by xanthine oxidase, reacts with hydroxylamine to form nitric ion. Nitric ion combines with naphthalene diamine and sulfaniline acid producing a colored product. The concentration of this colored product is proportional to the activity of SOD in the samples. The absorbance was read at 560 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzymatic activity was expressed as nitrite units (NU) per 1 mg of protein in tissue. One NU is defined as 50% inhibition of nitrite ion formation under the method’s condition. KCN was used as the inhibitor of the Cu/ZnSOD isoenzyme. Cu/ZnSOD activity was calculated as the difference between total SOD activity and MnSOD activity.
## 2.3.3. Determination of CAT Activity
CAT (EC.1.11.1.9) activity was measured in the supernatant of the lung homogenates by following the kinetic method of Aebi [23]. Briefly, 50 mM Tris/HCl buffer, pH 7.4, and perhydrol were mixed with 50 μl of homogenate. After 10 seconds, the absorbance was read at 240 nm every 30 seconds for 2 minutes using a Shimadzu UV-1700 PharmaSpec UV-Vis Spectrophotometer (Kyoto, Japan). Enzymatic activity was expressed as International Unit (IU) per 1 g of total protein (IU/g of total protein).
## 2.3.4. Determination of GPx Activity
GPx (E.C.1.11.1.9) activity was measured by following the method of Paglia and Valentine by using GSH andtert-butyl peroxide as substrates [24]. The kinetics of changes in absorbance were read at 355 nm on a PerkinElmer Victor X3 (PerkinElmer, USA). The activity of GPx was expressed as the quantity of μmoles of a reduced form of nicotinamide adenine dinucleotide phosphate (NADPH+H+) required to recover GSH in 1 minute, and expressed as IU/g of total protein.
## 2.3.5. Determination of GST Activity
The activity of GST (EC 2.5.1.18) was measured according to the kinetic method described by Habig and Jakoby [25]. In this method, GST reacts with 1-chloro-2,3-dinitrobenzene producing a thioether. The change in absorbance at 355 nm was monitored using a PerkinElmer Victor X3 reader. One unit of GST was defined as micromoles of thioether produced in 1 minute. The results were expressed as IU/g protein.
## 2.3.6. Determination of GR Activity
The activity of GR (E.C.1.6.4.2) was measured in the supernatant of tissue homogenates by following Richterich’s kinetic method [26], where oxidized glutathione (GSSG) was used as a substrate. Changes in absorbance were read at 355 nm on a Victor X3 Light Plate Reader (PerkinElmer, USA). Enzyme activity was determined as μmoles of NADPH+H+ required to replenish the concentration of GSH in 1 minute, and expressed as IU/g protein.
## 2.3.7. Protein Concentration
Protein concentration in the samples was determined by Lowry’s method using bovine serum albumin as a standard [27].
## 2.4. Statistical Analysis
All statistical analyses were performed using Statistica 13.1 (StatSoft, USA). The normality of the result distribution was verified. Data is presented asmeanvalue±standarddeviation (SD). To determine the statistical significance of differences among various experimental groups, t-test or Mann-Whitney’s test was performed. The correlation between different variables was calculated using Pearson’s linear correlation coefficient. Statistical significance was set at a p value ≤ 0.5. The lack of statistical significance is presented as NS (nonsignificant).
## 3. Results
The sociodemographic characteristics and clinical and pathological features of the study participants are presented in Table1.Table 1
The clinical and pathological features of NSCLC patients.
Variables
Number of patients (%)53 (100)
Sex
F
13 (24.53)
M
40 (75.47)
Age
≤65 years
31 (58.49)
>65 years
22 (41.51)
Histology
Squamous cell carcinoma
36 (67.93)
Adenocarcinoma
17 (32.07)
Differentiation grade
G1
0 (0)
G2
21 (39.62)
G3
32 (60.38)
T factor
T1
12 (22.64
T2
34 (64.15)
T3
7 (13.21)
N factor
N0
27 (50.94)
N1
18 (33.96)
N2
8 (15.10)
COPD
Yes
22 (41.51)
No
31 (58.49)
Smoking status
Smokers
39 (73.58)
Nonsmokers
13 (24.53)
No data
1 (1.89)
Abbreviations: G—histopathological cancer grading (G1: well differentiated; G2: moderately differentiated; G3: poorly differentiated; G4: undifferentiated); T—tumor size (T1:size≤3cm; T2: size>3cm to ≤5 cm; T3: size>5cm to 7 cm); N—metastatic lymph nodes (N0: no regional lymph node metastasis; N1: metastasis in ipsilateral peribronchial and/or hilar lymph node and intrapulmonary node; N2: metastasis in ipsilateral mediastinal and/or subcarinal lymph nodes); COPD—chronic obstructive pulmonary disease [28].The concentrations of MDA and the activities of antioxidant enzymes in the tumor and adjacent noncancerous tissues from patients with NSCLC were compared. No significant differences were observed in the concentrations of MDA and activities of MnSOD and Cu/ZnSOD, while the activities of CAT, GPx, GR, and GST were found to be significantly altered in tumor tissues compared with those in the adjacent noncancerous tissues. The activities of SOD and CAT were significantly higher in the adjacent noncancerous tissues than those in tumor tissues, while the activities of GSH-related enzymes were significantly higher in tumor tissues than in the adjacent noncancerous tissues (Table2).Table 2
Concentrations of MDA and activities of antioxidant enzymes in the tumor and adjacent noncancerous tissues of patients with NSCLC.
Parameters
Tumor tissue
Adjacent noncancerous tissue
p value
MDA (μmol/g)
0.69±0.78
0.47±0.14
NS
SOD (NU/mg)
16.26±3.96
18.53±4.51
0.016
MnSOD (NU/mg)
9.91±4.55
11.28±3.85
NS
Cu/ZnSOD (NU/mg)
6.37±4.26
7.25±2.07
NS
CAT (IU/g)
49.79±36.99
130±49.97
0.00001
GPx (IU/g)
8.61±6.34
5.58±2.66
0.004
GST (IU/g)
3.82±3.46
1.61±1.09
0.00024
GR (IU/g)
27.27±22.85
9.86±5.21
<0.001
NS—not significant.The abovementioned parameters were then compared based on the histological types of tumor. We found that the activity of GSH-related enzymes was significantly higher in cancer tissues of both adenocarcinoma and squamous cell carcinoma than in the noncancerous tissues, while the activity of CAT was significantly higher in the adjacent noncancerous tissues than in the tumor tissues. The activities of SOD and MnSOD were found to be significantly high only in noncancerous tissues of patients with squamous cell carcinoma, while their activities did not change significantly in patients diagnosed with adenocarcinoma (Table3).Table 3
Concentrations of MDA and activities of antioxidant enzymes in the cancerous and noncancerous tissues of patients with adenocarcinoma and squamous cell carcinoma.
Parameters
Adenocarcinoma
Squamous cell carcinoma
Tumor
Adjacent noncancerous tissue
p value
Tumor
Adjacent noncancerous tissue
p value
MDA (μmol/g)
0.57±0.44
0.47±0.18
NS
0.74±0.93
0.47±0.13
NS
SOD (NU/mg)
16.88±3.77
17.28±5.31
NS
15.98±4.08
19.15±4.02
0.008
MnSOD (NU/mg)
11.2±4.0
10.4±4.31
NS
9.34±4.53
11.7±3.61
0.04
Cu/ZnSOD (NU/mg)
5.76±4.29
6.86±2.6
NS
6.69±4.28
7.44±1.78
NS
CAT (IU/g)
45.4±24.93
130.64±50.2
<0.001
51.85±41.84
130.42±50.7
<0.001
GPx (IU/g)
10.75±7.54
5.95±2.47
0.04
7.58±5.52
5.4±2.73
0.05
GST (IU/g)
3.14±2.16
1.5±1.3
0.04
4.14±3.91
1.60±0.95
0.002
GR (IU/g)
28.43±16.36
8.94±3.39
<0.001
26.88±25.51
10.31±5.89
0.002
NS—not significant.No significant difference in the activity of antioxidant enzymes and concentration of MDA was observed between tumor and adjacent noncancerous tissues of patients with adenocarcinoma and squamous cell carcinoma (Table4).Table 4
Concentration of MDA and activity of antioxidant enzymes in tumor and adjacent noncancerous tissues of patients with adenocarcinoma and squamous cell carcinoma.
Parameters
Tumor
Adjacent noncancerous tissue
Adenocarcinoma
Squamous cell carcinoma
p value
Adenocarcinoma
Squamous cell carcinoma
p value
MDA (μmol/g)
0.91±1.30
0.94±1.27
NS
0.47±0.18
0.48±0.11
NS
SOD (NU/mg)
16.14±4.24
16.45±4.04
NS
17.28±5.31
19.15±4.02
NS
MnSOD (NU/mg)
10.74±4.25
10.25±5.00
NS
10.40±4.31
11.70±3.60
NS
Cu/ZnSOD (NU/mg)
5.45±3.94
6.20±4.15
NS
6.86±2.60
7.44±1.80
NS
CAT IU/g)
61.51±62.22
48.78±39.90
NS
130.64±50.30
130.42±50.71
NS
GPx (IU/g)
10.31±7.02
7.03±5.93
NS
5.94±2.47
5.40±2.73
NS
GST (IU/g)
2.90±2.11
4.15±3.74
NS
1.60±1.30
1.60±0.95
NS
GR (IU/g)
26.65±16.46
28.22±25.00
NS
8.94±3.39
10.31±5.89
NS
NS—not significant.Similarly, no significant difference was observed in the concentrations of MDA and activities of antioxidant enzymes between the tumor and adjacent noncancerous tissues of patients with different differentiation grades of tumor (G1, G2, and G3), tumor size (T1, T2, and T3), and metastatic lymph nodes (N0, N1, and N2) (data not shown).Furthermore, the correlation between the activity of antioxidant enzymes and age, and the sex of the patients was also examined. The results are presented in Table5. The activity of GST was found to be significantly higher in tumor tissues of patients who were more than 65 years old than in the group of younger patients (p=0.02). The activities of other antioxidant enzymes did not change significantly between the two groups.Table 5
Effect of age and sex of patients on the activity of antioxidant enzymes and concentration of MDA in tumor tissues.
Parameters
Age
Sex
≤65 years
>65 years
p value
Female
Male
p value
MDA (μmol/g)
0.81±1.27
1.14±1.27
NS
0.59±0.28
1.04±1.45
NS
SOD (NU/mg)
16.08±4.6
16.76±3.22
NS
16.52±4.05
16.30±4.10
NS
MnSOD (NU/mg)
10.91±4.65
9.71±4.87
NS
11.62±3.87
10.01±4.97
NS
Cu/ZnSOD (NU/mg)
5.19±3.49
7.04±4.61
NS
5.01±4.38
6.28±3.96
NS
CAT (IU/g)
59.71±51.32
43.23±41.98
NS
48.72±31.97
54.21±52.39
NS
GPx (IU/g)
7.93±6.33
8.31±6.67
NS
12.02±6.16
6.81±6.02
0.009
GST (IU/g)
2.85±2.46
5.01±3.99
0.02
3.00±1.82
4.00±3.68
NS
GR (IU/g)
23.45±15.52
33.71±29.00
NS
24.72±17.77
28.69±23.92
NS
NS—not significant.We did not find any change in the activity of antioxidant enzymes between males and females, except for the activity of GPx, which was significantly higher in women than in men (p=0.009).We also analyzed the relationship between the activity of antioxidant enzymes in tumor tissues and factors associated with carcinogenicity, such as smoking, and COPD; however, no significant relationship was observed between these parameters (data not shown).
## 4. Discussion
In patients with lung cancer, only a 16% 5-year survival rate is noted worldwide. The number of deaths due to lung cancer is expected to rise to 10 million deaths per year by 2030 [1, 2, 29]. The factors that cause lung cancer are complex and not yet fully understood. In recent years, the levels of ROS have aroused interest as signal molecules required for regulating various biological processes. It has been shown that cancer cells have increased ROS levels in comparison to their normal counterparts. This is due to an altered metabolism and mitochondrial dysfunction in cancer cells [30, 31]. ROS play a dual role as both deleterious and beneficial molecules. The “two-faced” character of ROS results from the fact that ROS within cells act as secondary messengers in intracellular signaling cascades, which induce and maintain the oncogenic phenotype of cancer cells. However, ROS can also induce cellular senescence and apoptosis and can therefore function as an antitumorigenic factor [32].
### 4.1. MDA
MDA, formed under oxidative stress conditions, is an end-product generated by the decomposition of arachidonic acid and larger polyunsaturated fatty acids, and has the ability to react with biomolecules, such as proteins or DNA [33, 34]. It has been widely used as a biomarker for lipid peroxidation, and it is known to be associated with different pathological conditions; however, its biological activity has not been studied in a dose-dependent manner [11, 35]. Moreover, several studies have evaluated the concentration of MDA in serum or urine samples of patients; however, that does not reflect the extent of oxidative damage caused by ROS in a given tissue or organ. In this study, MDA concentrations were not found to be significantly different between tumor and adjacent normal tissues of patients with NSCLC (Table 2), irrespective of the difference in histological types of NSCLC (Tables 3 and 4) or the age and sex of the patients (Table 5). Gegotek et al. reported significantly high levels of reactive aldehydes in tumor tissues of patients with NSCLC than in noncancerous tissues [36]. In a group of Algerian lung cancer patients, concentrations of MDA, determined by using the TBA method similar to our study, were significantly high in tumor tissues than in the peritumoral stroma [37]. They were also several times higher than those measured in our study. However, the TBA reacting substances (TBARs) test is known for its nonspecificity, which has led to substantial controversy over its use for the quantification of MDA levels [11]. An adequate method for the determination of MDA levels in appropriate biological samples remains to be determined.Antioxidant enzymes constitute the main defense mechanism of lung tissues against ROS-mediated injury, and their activity increases in response to oxidative stress. This has been shown to minimize ROS-mediated injury in experimental systems indicating that antioxidant levels might help in determining the role of ROS in the initiation of lung carcinogenesis [38]. In this study, we aim to evaluate the activity of antioxidant enzymes in the tumor and adjacent noncancerous tissues.
### 4.2. SOD
The first line of protection against ROS includes three isoforms of SOD, namely cytosolic Cu/ZnSOD, mitochondrial MnSOD, and extracellular SOD, which are present in the epithelial lining of blood vessels [38]. They play a major role in protecting the lungs against free radicals produced as a part of normal metabolism and also prevent the progression of oxidative stress-related lung diseases. In the present study, the activity of Cu/ZnSOD, MnSOD, and SOD was found to be higher in the adjacent noncancerous tissues than in the tumor tissues; however, this effect was significant only for SOD activity (p=0.016). The results of this study are in contrast with those of Chung-man Ho et al. who demonstrated that the activity of SOD was significantly higher in the tumor tissues than in the adjacent tumor-free lung tissues in patients with NSCLC (p=0.035) [38]. When the activities of antioxidant enzymes were compared according to the histological types of NSCLC, we observed that the activities of SOD and MnSOD in the adjacent noncancerous tissues were significantly higher in patients with squamous cell carcinoma (Table 3) than in patients with adenocarcinoma. The results obtained by Svensk et al. suggested that the activity of MnSOD increased in lung carcinoma, and this increase was more prominent in patients with squamous cell carcinoma than in patients with the other types of lung carcinomas [14]. Interestingly, no significant difference was observed in the activity of different isoforms of SOD between the adjacent nonmalignant tissues of adenocarcinoma and squamous cell carcinoma (Table 4). As rightly discussed by Kinnula and Crapo [5], it is difficult to compare the activities of the three different isoforms of SOD in the lung because they are located in compartments of different sizes and have been evaluated by several investigators using different assays, each having different sensitivities and specificities.The association of aging with oxidative stress is undisputable. Aging, resulting from the accumulation of molecular damages in DNA, proteins, and lipids, is characterized by an increase in the intracellular levels of oxidative stress. Therefore, in this study, we compared the activity of antioxidant enzymes in tumor tissues of patients with NSCLC by categorizing them in two age groups—below and above 65 years of age [39]. The activity of the three different isoforms of SOD did not change significantly between the tumor and noncancerous tissues of patients above or below 65 years of age. Similarly, no significant difference was observed in the activity of SOD between females and males (Table 5).
### 4.3. CAT
CAT, located mainly in peroxisomes, decomposes H2O2, a by-product of fatty acid oxidation, to oxygen and water. Thus, CAT confers protection against the toxic effects of H2O2 without generating intermediate free radicals, and the resulting oxygen is utilized for other metabolic processes [40]. A significant reduction in the activity of CAT has been observed in many types of cancer: head and neck, lungs, gastrointestinal tract, breasts, kidney, or leukemia [41]. In this study, CAT activity in NSCLC patients was significantly high (p=0.00001) in the adjacent noncancerous tissues (Table 2), irrespective of the different histological types of lung cancer (Table 3). Similar results were also obtained by Otsmane et al. [37]. Ho et al. [38] proposed that inflammation in the lungs may contribute to the decreased activity of catalase, resulting in an increased concentration of intracellular H2O2 and the promotion of cancer.
### 4.4. GSH-Related Enzymes
The levels of GSH and enzymes required for maintaining its levels in turn have been suggested to constitute one of the basic antioxidant defense mechanisms of the human lungs [17].Previous studies suggested that the antioxidant activity is impaired in lung cancers, and the expression of GSH-related antioxidant enzymes creates an interindividual risk factor for lung cancer [42]. In the present study, the activity of GSH-related antioxidant enzymes, namely, GPx, GST, and GR, were significantly higher in the tumor tissues than in the adjacent noncancerous lung tissues (Table 2) in patients with adenocarcinoma and squamous cell carcinoma (Table 3). However, the activity of these enzymes was not found to be significantly different between the two histological types of NSCLC (Table 4). Since GSH is essential for mounting successful immune response by activating T-lymphocytes and polymorphonuclear leukocytes for producing cytokines [43], there could be a link between the activity of GSH-related enzymes and tumor biology. Cancer tissue might be superior to adjacent noncancerous tissue in terms of its ability to decrease oxidative stress, thereby, facilitating tumor growth. The mediators and cellular effectors of inflammation are important constituents of the local environment of tumor tissue. Thus, cancer cells are able to protect themselves by increasing the intracellular concentrations of GSH. Inflammation in the tumor microenvironment aids in the proliferation and survival of malignant cells; promotes angiogenesis and metastasis; and alters immune response, response to hormones, and chemotherapeutic agents [44, 45]. Contrary to previously analyzed enzymes determined in our study, only GSH-related molecules have shown differences according to age: surprisingly GST activity was higher in the tumor tissue of patients above 65 years of age (p=0.02, Table 5). Interestingly, females with NSCLC exhibited a significantly higher activity of GPx in tumor tissues relative to men.The link between inflammation and cancer has also been confirmed by anti-inflammatory therapies that have proven to be effective in the prevention and treatment of cancer [46]. Therefore, the relationship between the activity of antioxidant enzymes and COPD was examined. Damage to the lungs in COPD is caused by oxidative stress (both exogenous resulting from smoking and endogenous), release of inflammatory cytokines, protease activity (due to the imbalance in protease : antiprotease ratio), and expression of autoantibodies [47]. This in turn can lead to airway destruction, air trapping, and lung hyperinflation [48]. Smoking is believed to be the primary cause of lung cancer. The adverse action of cigarette smoke is due to the presence of a large variety of compounds like nicotine, benzo(a)pyrene, oxidants, and free radicals that initiate, promote, and/or amplify oxidative damage [49]. Several studies have reported that cigarette smoking is associated with an increase in the incidence and severity of various diseases, such as lung cancer and COPD [6, 50]. COPD and lung cancer are caused by cigarette smoking, and there is increasing evidence linking the two diseases beyond just a common etiology. COPD is an independent risk factor for lung carcinoma, particularly for squamous cell carcinoma, and lung cancer is up to five times more likely to occur in smokers with airflow obstruction than those with normal lung function [51]. Villeneuve et al. reported that the lifetime risk of developing lung cancer is 17.2% and 11.6% for males and females, respectively, among smokers, when compared with 1.3% for males and 1.4% for females among nonsmokers [52]. In this study, we evaluated the activity of antioxidant enzymes in the tumor and adjacent noncancerous tissues obtained from patients with NSCLC. We did not find any significant difference in the activity of antioxidant enzymes between smokers and nonsmokers, and patients with or without COPD. It is possible that smoking or other inflammatory lung diseases do not have a pivotal impact on oxidative stress nascency in the initial stage of cancer development.The incidence rate of lung cancer is declining in men and plateauing in women after increasing for several decades. This lag in the temporal trend of lung cancer incidence rates in women compared with that in men is reflected in historical differences in cigarette smoking habits between men and women; cigarette smoking in women peaked about 20 years later than in men [1]. Our results suggested that the age and sex of the patients do not have any effect on the activity of antioxidant enzymes in the tumor tissues of NSCLC patients, except for the activity of GPx and GST as mentioned in Table 5. The activity of antioxidant enzymes was not found to be correlated with differentiation grade, tumor size, and metastatic lymph nodes (data not shown).In majority of the studies, the activity of antioxidant enzymes has been determined in the peripheral blood erythrocytes of patients with neoplastic diseases and not in the cancerous tissues. In this study, we evaluated the activities of antioxidant enzymes in the homogenates of lung tissue, and therefore, our results cannot always be directly compared with those reported by others. Moreover, the percentage of adeno- and squamous cell carcinomas in patients recruited in this study was different from the statistics available for general lung cancer: 32% and 67% of the cases of adenocarcinoma and squamous cell carcinoma, respectively, in this study versus 40% and 30% of the cases according to available statistics. Therefore, we have discussed our results only for NSCLC, in general, and compared the activity of antioxidant enzymes between the two histological types of lung cancer. Further studies with a large cohort of patients with NSCLC are warranted to conclusively prove our observations.
## 4.1. MDA
MDA, formed under oxidative stress conditions, is an end-product generated by the decomposition of arachidonic acid and larger polyunsaturated fatty acids, and has the ability to react with biomolecules, such as proteins or DNA [33, 34]. It has been widely used as a biomarker for lipid peroxidation, and it is known to be associated with different pathological conditions; however, its biological activity has not been studied in a dose-dependent manner [11, 35]. Moreover, several studies have evaluated the concentration of MDA in serum or urine samples of patients; however, that does not reflect the extent of oxidative damage caused by ROS in a given tissue or organ. In this study, MDA concentrations were not found to be significantly different between tumor and adjacent normal tissues of patients with NSCLC (Table 2), irrespective of the difference in histological types of NSCLC (Tables 3 and 4) or the age and sex of the patients (Table 5). Gegotek et al. reported significantly high levels of reactive aldehydes in tumor tissues of patients with NSCLC than in noncancerous tissues [36]. In a group of Algerian lung cancer patients, concentrations of MDA, determined by using the TBA method similar to our study, were significantly high in tumor tissues than in the peritumoral stroma [37]. They were also several times higher than those measured in our study. However, the TBA reacting substances (TBARs) test is known for its nonspecificity, which has led to substantial controversy over its use for the quantification of MDA levels [11]. An adequate method for the determination of MDA levels in appropriate biological samples remains to be determined.Antioxidant enzymes constitute the main defense mechanism of lung tissues against ROS-mediated injury, and their activity increases in response to oxidative stress. This has been shown to minimize ROS-mediated injury in experimental systems indicating that antioxidant levels might help in determining the role of ROS in the initiation of lung carcinogenesis [38]. In this study, we aim to evaluate the activity of antioxidant enzymes in the tumor and adjacent noncancerous tissues.
## 4.2. SOD
The first line of protection against ROS includes three isoforms of SOD, namely cytosolic Cu/ZnSOD, mitochondrial MnSOD, and extracellular SOD, which are present in the epithelial lining of blood vessels [38]. They play a major role in protecting the lungs against free radicals produced as a part of normal metabolism and also prevent the progression of oxidative stress-related lung diseases. In the present study, the activity of Cu/ZnSOD, MnSOD, and SOD was found to be higher in the adjacent noncancerous tissues than in the tumor tissues; however, this effect was significant only for SOD activity (p=0.016). The results of this study are in contrast with those of Chung-man Ho et al. who demonstrated that the activity of SOD was significantly higher in the tumor tissues than in the adjacent tumor-free lung tissues in patients with NSCLC (p=0.035) [38]. When the activities of antioxidant enzymes were compared according to the histological types of NSCLC, we observed that the activities of SOD and MnSOD in the adjacent noncancerous tissues were significantly higher in patients with squamous cell carcinoma (Table 3) than in patients with adenocarcinoma. The results obtained by Svensk et al. suggested that the activity of MnSOD increased in lung carcinoma, and this increase was more prominent in patients with squamous cell carcinoma than in patients with the other types of lung carcinomas [14]. Interestingly, no significant difference was observed in the activity of different isoforms of SOD between the adjacent nonmalignant tissues of adenocarcinoma and squamous cell carcinoma (Table 4). As rightly discussed by Kinnula and Crapo [5], it is difficult to compare the activities of the three different isoforms of SOD in the lung because they are located in compartments of different sizes and have been evaluated by several investigators using different assays, each having different sensitivities and specificities.The association of aging with oxidative stress is undisputable. Aging, resulting from the accumulation of molecular damages in DNA, proteins, and lipids, is characterized by an increase in the intracellular levels of oxidative stress. Therefore, in this study, we compared the activity of antioxidant enzymes in tumor tissues of patients with NSCLC by categorizing them in two age groups—below and above 65 years of age [39]. The activity of the three different isoforms of SOD did not change significantly between the tumor and noncancerous tissues of patients above or below 65 years of age. Similarly, no significant difference was observed in the activity of SOD between females and males (Table 5).
## 4.3. CAT
CAT, located mainly in peroxisomes, decomposes H2O2, a by-product of fatty acid oxidation, to oxygen and water. Thus, CAT confers protection against the toxic effects of H2O2 without generating intermediate free radicals, and the resulting oxygen is utilized for other metabolic processes [40]. A significant reduction in the activity of CAT has been observed in many types of cancer: head and neck, lungs, gastrointestinal tract, breasts, kidney, or leukemia [41]. In this study, CAT activity in NSCLC patients was significantly high (p=0.00001) in the adjacent noncancerous tissues (Table 2), irrespective of the different histological types of lung cancer (Table 3). Similar results were also obtained by Otsmane et al. [37]. Ho et al. [38] proposed that inflammation in the lungs may contribute to the decreased activity of catalase, resulting in an increased concentration of intracellular H2O2 and the promotion of cancer.
## 4.4. GSH-Related Enzymes
The levels of GSH and enzymes required for maintaining its levels in turn have been suggested to constitute one of the basic antioxidant defense mechanisms of the human lungs [17].Previous studies suggested that the antioxidant activity is impaired in lung cancers, and the expression of GSH-related antioxidant enzymes creates an interindividual risk factor for lung cancer [42]. In the present study, the activity of GSH-related antioxidant enzymes, namely, GPx, GST, and GR, were significantly higher in the tumor tissues than in the adjacent noncancerous lung tissues (Table 2) in patients with adenocarcinoma and squamous cell carcinoma (Table 3). However, the activity of these enzymes was not found to be significantly different between the two histological types of NSCLC (Table 4). Since GSH is essential for mounting successful immune response by activating T-lymphocytes and polymorphonuclear leukocytes for producing cytokines [43], there could be a link between the activity of GSH-related enzymes and tumor biology. Cancer tissue might be superior to adjacent noncancerous tissue in terms of its ability to decrease oxidative stress, thereby, facilitating tumor growth. The mediators and cellular effectors of inflammation are important constituents of the local environment of tumor tissue. Thus, cancer cells are able to protect themselves by increasing the intracellular concentrations of GSH. Inflammation in the tumor microenvironment aids in the proliferation and survival of malignant cells; promotes angiogenesis and metastasis; and alters immune response, response to hormones, and chemotherapeutic agents [44, 45]. Contrary to previously analyzed enzymes determined in our study, only GSH-related molecules have shown differences according to age: surprisingly GST activity was higher in the tumor tissue of patients above 65 years of age (p=0.02, Table 5). Interestingly, females with NSCLC exhibited a significantly higher activity of GPx in tumor tissues relative to men.The link between inflammation and cancer has also been confirmed by anti-inflammatory therapies that have proven to be effective in the prevention and treatment of cancer [46]. Therefore, the relationship between the activity of antioxidant enzymes and COPD was examined. Damage to the lungs in COPD is caused by oxidative stress (both exogenous resulting from smoking and endogenous), release of inflammatory cytokines, protease activity (due to the imbalance in protease : antiprotease ratio), and expression of autoantibodies [47]. This in turn can lead to airway destruction, air trapping, and lung hyperinflation [48]. Smoking is believed to be the primary cause of lung cancer. The adverse action of cigarette smoke is due to the presence of a large variety of compounds like nicotine, benzo(a)pyrene, oxidants, and free radicals that initiate, promote, and/or amplify oxidative damage [49]. Several studies have reported that cigarette smoking is associated with an increase in the incidence and severity of various diseases, such as lung cancer and COPD [6, 50]. COPD and lung cancer are caused by cigarette smoking, and there is increasing evidence linking the two diseases beyond just a common etiology. COPD is an independent risk factor for lung carcinoma, particularly for squamous cell carcinoma, and lung cancer is up to five times more likely to occur in smokers with airflow obstruction than those with normal lung function [51]. Villeneuve et al. reported that the lifetime risk of developing lung cancer is 17.2% and 11.6% for males and females, respectively, among smokers, when compared with 1.3% for males and 1.4% for females among nonsmokers [52]. In this study, we evaluated the activity of antioxidant enzymes in the tumor and adjacent noncancerous tissues obtained from patients with NSCLC. We did not find any significant difference in the activity of antioxidant enzymes between smokers and nonsmokers, and patients with or without COPD. It is possible that smoking or other inflammatory lung diseases do not have a pivotal impact on oxidative stress nascency in the initial stage of cancer development.The incidence rate of lung cancer is declining in men and plateauing in women after increasing for several decades. This lag in the temporal trend of lung cancer incidence rates in women compared with that in men is reflected in historical differences in cigarette smoking habits between men and women; cigarette smoking in women peaked about 20 years later than in men [1]. Our results suggested that the age and sex of the patients do not have any effect on the activity of antioxidant enzymes in the tumor tissues of NSCLC patients, except for the activity of GPx and GST as mentioned in Table 5. The activity of antioxidant enzymes was not found to be correlated with differentiation grade, tumor size, and metastatic lymph nodes (data not shown).In majority of the studies, the activity of antioxidant enzymes has been determined in the peripheral blood erythrocytes of patients with neoplastic diseases and not in the cancerous tissues. In this study, we evaluated the activities of antioxidant enzymes in the homogenates of lung tissue, and therefore, our results cannot always be directly compared with those reported by others. Moreover, the percentage of adeno- and squamous cell carcinomas in patients recruited in this study was different from the statistics available for general lung cancer: 32% and 67% of the cases of adenocarcinoma and squamous cell carcinoma, respectively, in this study versus 40% and 30% of the cases according to available statistics. Therefore, we have discussed our results only for NSCLC, in general, and compared the activity of antioxidant enzymes between the two histological types of lung cancer. Further studies with a large cohort of patients with NSCLC are warranted to conclusively prove our observations.
## 5. Conclusion
A significant change in the activity of antioxidant enzymes was observed during the process of carcinogenesis. Tumor cells always had low MnSOD activity, usually low Cu/ZnSOD activity, and almost always low catalase activity compared with those of the corresponding normal tissues. Activities of GSH-related enzymes were significantly high in lung cancer tissues, irrespective of the histological type of lung cancer, which could possibly be the way by which tumor cells protect themselves against increased oxidative stress.
---
*Source: 2901840-2019-10-31.xml* | 2019 |
# Probabilistic Solution of Rational Difference Equations System with Random Parameters
**Authors:** Seifedine Kadry
**Journal:** ISRN Applied Mathematics
(2012)
**Publisher:** International Scholarly Research Network
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.5402/2012/290186
---
## Abstract
We study the periodicity of the solutions of the rational difference equations system of typexn=a/yn−p, yn=b/xn+p−2 (p≥1), and then we propose new exact procedure to find the probability density function of the solution, where a, b, x0=N and y0=M are independent random variables.
---
## Body
## 1. Introduction
Stochastic systems of difference equations usually appear in the investigation of systems with discrete time or in the numerical solution of systems with continuous time. A lot of difference systems have variable structures subject to stochastic abrupt changes, which may result from abrupt phenomena such as stochastic failures and repairs of the components, changes in the interconnections of subsystems, and sudden environment changes. Recently, there has been great interest in studying difference equation systems. One of the reasons for this is the necessity for some techniques that can be used in investigating equations arising in mathematical models describing real-life situations in population biology, economics, probability theory, genetics, psychology, and so forth. There are many papers related to the difference equations system; for example, Çinar [1] studied the solutions of the system of difference equations:(1.1)xn+1=1yn,yn+1=ynxn-1yn-1.
Papaschinopoulos and Schinas [2] studied the oscillatory behavior, the boundedness of the solutions, and the global asymptotic stability of the positive equilibrium of the system of nonlinear difference equations:(1.2)xn+1=A+ynxn-p,yn+1=A+xnyn-q,n=0,1,…,p,q.
Özban [3] studied the positive solutions of the system of rational difference equations:(1.3)xn=ayn-3,yn=byn-3xn-qyn-q.
Clark and Kulenović [4] investigated the global asymptotic stability:(1.4)xn+1=xna+cyn,yn+1=ynb+dxn.
Yang and Xu [5] propose a method to deal with the mean square exponential stability of impulsive stochastic difference equations.In this paper, we investigate the analytic solution of the stochastic difference equations system:(1.5)xn=ayn-p,yn=bxn+p-2,
where a, b, x0=N and y0=M are independent random variables.
## 2. Periodicity of the Solutions
In this section, we study the periodicity of the solutions of system (1.5).Theorem 2.1.
All solutions of (1.5) are periodic with period 2.Proof.
One has the following:(2.1)xn+2=ayn-p+2=ab/xn=abxn,yn+2=bxn+p=ba/yn=bayn.
Therefore, the proof was completed.Theorem 2.2.
Forp=1, all solutions of (1.5) are
(2.2)x2n+1=an+1bnM,y2n+1=bn+1anN,x2n+2=an+1Nbn+1,y2n+2=bn+1Man+1.Proof.
By induction, suppose the result holds forn-1:
(2.3)x2n-1=anbn-1M,y2n-1=bnan-1N,x2n=anNbn,y2n=bnMan.
For n,
(2.4)x2n+1=ay2n=an+1bnM,y2n+1=bx2n=bn+1anN,x2n+2=ay2n+1=an+1Nbn+1,y2n+2=bx2n+1=bn+1Man+1.
Hence, the proof is completed by induction.
## 3. Analytic Stochastic Solutions
In this section, we develop an analytic technique to find the stochastic solutions of (cf. Theorem2.2)(3.1)x2n+1=an+1bnM,y2n+1=bn+1anN,x2n+2=an+1Nbn+1,y2n+2=bn+1Man+1.
The solution of a stochastic system of difference equations is obtained when evaluating the statistical characteristic of the solution process like the mean, standard deviation, high-order moments, and the most important characteristic, “the probability density function” (pdf). Our proposed technique is based on the transformation of random variables to get the pdf of xn and yn.
## 4. Transformation of Random Variables Technique (TRVT)
Definition 4.1.
LetX be a continuous random variable with generic probability density function f(x) defined over the support c1<x<c2. And, let Y=u(X) be an invertible function of X with inverse function X=v(Y). Then, using the transformation of random variable technique (TRVT) defined by Kadry and Younes [6], Kadry [7], El-Tawil et al. [8], and Kadry and Smaili [9], the probability density function of Y is
(4.1)pdf(y)=pdf(v(y))⋅|v′(y)|
defined over the support u(c1)<y<u(c2).To simplify our technique, let us consider the following stochastic equation:(4.2)z=yβxα(α,β∈Z),
where x and y are two independent random variables. To find the pdf of z, firstly we linearize the denominator, and then we find the pdf of the product of two random variables:we supposeδ=1/xα, and then we apply the TRVT technique to get the pdf of δ,(4.3)fδ(δ)=-1δ2αδ-1+ααfx(x).
Once the linearization step has been done, it is required to find the pdf of the product of two random variables. To do that, we developed the following theorem.Theorem 4.2.
LetX be a continuous random variable with distribution function f(X) which is defined on the interval [a,b], where 0<a<b<∞. Similarly, let Y be a random variable of the continuous type with distribution function g(Y) which is defined on the interval [c,d], where 0<c<d<∞. The pdf of z=XY,h(z) is obtained as follows.Case 1 (ad<bc).
One has(4.4)h(z)={∫az/cg(zX)f(X)1Xdx,ac<z<ad,∫z/dz/cg(zX)f(X)1Xdx,ad<z<bc,∫z/dbg(zX)f(X)1Xdx.bc<z<bd.Case 2 (ad=bc).
One has(4.5)h(z)={∫az/cg(zX)f(X)1Xdx,ac<z<ad,∫z/dbg(zX)f(X)1Xdx,ad<z<bd.Case 3 (ad>bc).
One has(4.6)h(z)={∫az/cg(zX)f(X)1Xdx,ac<z<bc,∫abg(zX)f(X)1Xdx,bc<z<ad,∫z/dbg(zX)f(X)1Xdx,ad<z<bd.Proof.
Only the case ofad<bc is considered. The other cases are proven analogously. Using [kadry], the transformation w=X and z=XY is bijective. The Jacobian of this transformation becomes
(4.7)J=|10-zw21w|=1w.
The joint pdf of w and z is
(4.8)fW,Z(w,z)=f(w)f(zw)1|w|.
Integrating with respect to w over the appropriate intervals and replacing w with X in the final result yields the marginal pdf of z:
(4.9)h(z)={∫az/cg(zX)f(X)1Xdx,ac<z<ad,∫z/dz/cg(zX)f(X)1Xdx,ad<z<bc,∫z/dbg(zX)f(X)1Xdx,bc<z<bd.
---
*Source: 290186-2012-05-16.xml* | 290186-2012-05-16_290186-2012-05-16.md | 5,970 | Probabilistic Solution of Rational Difference Equations System with Random Parameters | Seifedine Kadry | ISRN Applied Mathematics
(2012) | Mathematical Sciences | International Scholarly Research Network | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.5402/2012/290186 | 290186-2012-05-16.xml | ---
## Abstract
We study the periodicity of the solutions of the rational difference equations system of typexn=a/yn−p, yn=b/xn+p−2 (p≥1), and then we propose new exact procedure to find the probability density function of the solution, where a, b, x0=N and y0=M are independent random variables.
---
## Body
## 1. Introduction
Stochastic systems of difference equations usually appear in the investigation of systems with discrete time or in the numerical solution of systems with continuous time. A lot of difference systems have variable structures subject to stochastic abrupt changes, which may result from abrupt phenomena such as stochastic failures and repairs of the components, changes in the interconnections of subsystems, and sudden environment changes. Recently, there has been great interest in studying difference equation systems. One of the reasons for this is the necessity for some techniques that can be used in investigating equations arising in mathematical models describing real-life situations in population biology, economics, probability theory, genetics, psychology, and so forth. There are many papers related to the difference equations system; for example, Çinar [1] studied the solutions of the system of difference equations:(1.1)xn+1=1yn,yn+1=ynxn-1yn-1.
Papaschinopoulos and Schinas [2] studied the oscillatory behavior, the boundedness of the solutions, and the global asymptotic stability of the positive equilibrium of the system of nonlinear difference equations:(1.2)xn+1=A+ynxn-p,yn+1=A+xnyn-q,n=0,1,…,p,q.
Özban [3] studied the positive solutions of the system of rational difference equations:(1.3)xn=ayn-3,yn=byn-3xn-qyn-q.
Clark and Kulenović [4] investigated the global asymptotic stability:(1.4)xn+1=xna+cyn,yn+1=ynb+dxn.
Yang and Xu [5] propose a method to deal with the mean square exponential stability of impulsive stochastic difference equations.In this paper, we investigate the analytic solution of the stochastic difference equations system:(1.5)xn=ayn-p,yn=bxn+p-2,
where a, b, x0=N and y0=M are independent random variables.
## 2. Periodicity of the Solutions
In this section, we study the periodicity of the solutions of system (1.5).Theorem 2.1.
All solutions of (1.5) are periodic with period 2.Proof.
One has the following:(2.1)xn+2=ayn-p+2=ab/xn=abxn,yn+2=bxn+p=ba/yn=bayn.
Therefore, the proof was completed.Theorem 2.2.
Forp=1, all solutions of (1.5) are
(2.2)x2n+1=an+1bnM,y2n+1=bn+1anN,x2n+2=an+1Nbn+1,y2n+2=bn+1Man+1.Proof.
By induction, suppose the result holds forn-1:
(2.3)x2n-1=anbn-1M,y2n-1=bnan-1N,x2n=anNbn,y2n=bnMan.
For n,
(2.4)x2n+1=ay2n=an+1bnM,y2n+1=bx2n=bn+1anN,x2n+2=ay2n+1=an+1Nbn+1,y2n+2=bx2n+1=bn+1Man+1.
Hence, the proof is completed by induction.
## 3. Analytic Stochastic Solutions
In this section, we develop an analytic technique to find the stochastic solutions of (cf. Theorem2.2)(3.1)x2n+1=an+1bnM,y2n+1=bn+1anN,x2n+2=an+1Nbn+1,y2n+2=bn+1Man+1.
The solution of a stochastic system of difference equations is obtained when evaluating the statistical characteristic of the solution process like the mean, standard deviation, high-order moments, and the most important characteristic, “the probability density function” (pdf). Our proposed technique is based on the transformation of random variables to get the pdf of xn and yn.
## 4. Transformation of Random Variables Technique (TRVT)
Definition 4.1.
LetX be a continuous random variable with generic probability density function f(x) defined over the support c1<x<c2. And, let Y=u(X) be an invertible function of X with inverse function X=v(Y). Then, using the transformation of random variable technique (TRVT) defined by Kadry and Younes [6], Kadry [7], El-Tawil et al. [8], and Kadry and Smaili [9], the probability density function of Y is
(4.1)pdf(y)=pdf(v(y))⋅|v′(y)|
defined over the support u(c1)<y<u(c2).To simplify our technique, let us consider the following stochastic equation:(4.2)z=yβxα(α,β∈Z),
where x and y are two independent random variables. To find the pdf of z, firstly we linearize the denominator, and then we find the pdf of the product of two random variables:we supposeδ=1/xα, and then we apply the TRVT technique to get the pdf of δ,(4.3)fδ(δ)=-1δ2αδ-1+ααfx(x).
Once the linearization step has been done, it is required to find the pdf of the product of two random variables. To do that, we developed the following theorem.Theorem 4.2.
LetX be a continuous random variable with distribution function f(X) which is defined on the interval [a,b], where 0<a<b<∞. Similarly, let Y be a random variable of the continuous type with distribution function g(Y) which is defined on the interval [c,d], where 0<c<d<∞. The pdf of z=XY,h(z) is obtained as follows.Case 1 (ad<bc).
One has(4.4)h(z)={∫az/cg(zX)f(X)1Xdx,ac<z<ad,∫z/dz/cg(zX)f(X)1Xdx,ad<z<bc,∫z/dbg(zX)f(X)1Xdx.bc<z<bd.Case 2 (ad=bc).
One has(4.5)h(z)={∫az/cg(zX)f(X)1Xdx,ac<z<ad,∫z/dbg(zX)f(X)1Xdx,ad<z<bd.Case 3 (ad>bc).
One has(4.6)h(z)={∫az/cg(zX)f(X)1Xdx,ac<z<bc,∫abg(zX)f(X)1Xdx,bc<z<ad,∫z/dbg(zX)f(X)1Xdx,ad<z<bd.Proof.
Only the case ofad<bc is considered. The other cases are proven analogously. Using [kadry], the transformation w=X and z=XY is bijective. The Jacobian of this transformation becomes
(4.7)J=|10-zw21w|=1w.
The joint pdf of w and z is
(4.8)fW,Z(w,z)=f(w)f(zw)1|w|.
Integrating with respect to w over the appropriate intervals and replacing w with X in the final result yields the marginal pdf of z:
(4.9)h(z)={∫az/cg(zX)f(X)1Xdx,ac<z<ad,∫z/dz/cg(zX)f(X)1Xdx,ad<z<bc,∫z/dbg(zX)f(X)1Xdx,bc<z<bd.
---
*Source: 290186-2012-05-16.xml* | 2012 |
# Chronic Unpredictable Mild Stress Aggravates Mood Disorder, Cognitive Impairment, and Brain Insulin Resistance in Diabetic Rat
**Authors:** Hui Yang; Wei Li; Pan Meng; Zhuo Liu; Jian Liu; Yuhong Wang
**Journal:** Evidence-Based Complementary and Alternative Medicine
(2018)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2018/2901863
---
## Abstract
Diabetes-induced brain insulin resistance is associated with many mental diseases, including depression. Epidemiological evidences demonstrate the pathophysiologic link between stress, depression, and diabetes. This study was designed to determine whether chronic unpredictable mild stress- (CUMS-) induced changes in brain insulin resistance could contribute to deterioration in mood and cognitive functions in diabetic rats. Male SD rats were randomly assigned to three groups, including standard control group, the diabetes group, and the diabetes with CUMS group. After 7 weeks, emotional behaviors and memory performances as well as metabolic phenotypes were measured. In addition, we examined the changes in protein expression related to brain insulin signaling. Our results show that rats in diabetes with CUMS group displayed a decreased locomotor behavior in open-field test, an increased immobility time in forced swim test, and tail suspension test, and an impaired learning and memory in the Morris water maze when compared to animals in diabetes group. Further, diabetes with CUMS exhibited a significant decrease in phosphorylation of insulin receptor and an increase phosphorylation of IRS-1 in brain. These results suggest that the depression-like behaviors and cognitive function impairments in diabetic rats with CUMS were related to the changes of brain insulin signaling.
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## Body
## 1. Introduction
More than 382 million patients worldwide suffered from diabetes mellitus in 2013, and this number will reach 592 million in 2035 [1]. The prevalence of depression in people with diabetes may run up to 38.75%. Among these people, 48.38% were found suffering from moderately depressed [2]. A cross-sectional study [3] described that 35.1% patients with diabetes were diagnosed depression symptoms. Statistically, Bhattacharya and his colleagues found that “total healthcare expenditures were reduced by treatment with antidepressants (16% reduction), psychotherapy (22%), and both therapy types in combination (28%) compared to no depression treatment” [4]. However, the government did not pay attention to the increase prevalence of depression and diabetes and its health services. Moreover, the treatments to patients with related diseases were insufficient [5]. The potential biopsychosocial risk factors of diabetes and depression were the influences on marital status, occupation, and social support [6]. The researches associated with pathophysiological mechanisms of depression in patients with diabetes were insufficient. The association between depression and insulin resistance (IR) can explain the biological link between depression and type 2 diabetes [7]. Understanding the disordered systemic IR and defective brain insulin signaling in comorbidity of diabetes and depression has become a topic of concern and public health challenge.Comorbidity between diabetes and depression was related to biological, psychological, and social factors, according to Tesfa Dejenie Habtewold [6]. An average depression symptoms score of patients with diabetes was usually affected by external factors including income, educational status, physical activity, and fearing diabetes-related complication and death [6, 8]. However, it is difficult to analyze the external factors in animal trials. Although db/db mice and streptozotocin- (STZ-) diabetic rat were utilized to study this comorbidity [9, 10], the outside influential factors were not considered in most of studies. Chronic unpredictable mild stress (CUMS) procedure has been widely utilized in the study with encouraging results [11]. CUMS model of depression has good predictive validity, face validity, and construct validity [11]. Thus, it is worthwhile to optimize the experimental model in this comorbidity by combining CUMS with diabetes. And it is meaningful to explore the association between depression and diabetes mellitus based on this animal model.Insulin regulates glucose uptake and storage in peripheral tissues, and it has been shown to alter brain function and metabolism [12–14]. Pancreas is the only organ to produce insulin and the insulin crosses the blood-brain barrier (BBB) by using a saturable transporter, and acts on the brain function through glucose utilization [15].Previous reports demonstrate that IR leads to memory impairment and it is a risk factor for diabetic encephalopathy in recent years [16, 17]. There are many theories to explain the connection between diabetes and psychiatric disorders, including abnormal glucose metabolism, impaired brain insulin signaling, neurogenesis, and alterations in glucocorticoid levels [18]. Nevertheless, the pathologic role of brain insulin in hippocampus in diabetes-related depression is not fully explained.A combination of high-fat diet (HFD) and tail meridians injection of streptozotocin (STZ) is a well-established approach to inducing diabetes mellitus [19]. And CUMS provides the diabetic rats with appropriate stress stimulation. However, the possible effect of CUMS on depression-like alterations in rats with diabetes characterized by brain insulin resistance has not yet been investigated. This study is aimed to study the changes of emotional behaviors and memory performances, glucose metabolism, and brain insulin signaling in rats with diabetes subjected to CUMS.
## 2. Material and Methods
### 2.1. Animals
Adult male Sprague-Dawley rats (weight, 200-220g; license No. SCXK 2009-0004) were provided by Hunan Slac Jingda Laboratory Animal Co., Ltd. (Changsha, China). They were housed with access to food and water, and maintained on a 12h light/dark cycle (lights on at 7:00 a.m.), at 22°C with low humidity. All animal experiments were carried out in accordance with the National Institute of Health Guide for the Care and Use of Laboratory Animals (NIH publication 8023, revised 1996) and with the approval of the Animal Ethics Welfare Committee of the First Affiliated Hospital of Hunan University of Chinese Medicine.
### 2.2. Chemicals and Reagents
Streptozotocin (STZ) was purchased from Sigma-Aldrich (St. Louis, MO, USA). The high-fat diet (HFD) consisted of 58% fat, 25% protein, and 17% carbohydrate, as a percentage of the total kilocalories. Antibodies against pIR(Y1158) and pIRS1(S307) were purchased from Abcam (Cambridge, UK).
### 2.3. Instruments
The high-speed refrigerated centrifuge was from Sigma-Aldrich (SIGMA 3K15, Sigma Laborzentrifugen GmbH, Osterode am Harz, Germany), a microplate reader was obtained from Thermo Fisher Scientific Inc. (Waltham, MA, USA; MK3), and open boxes and the Morris water were obtained from Panlab(SMART3.0, Panlab, Spanish).
### 2.4. Model of Diabetes and the Procedure of CUMS
The experimental model of diabetes mellitus (DM) was induced with a combination of low-dose STZ and a HFD. Following the onset of the experiment, the rats were fed libitum with a HFD for two weeks and then received 38 mg/kg STZ freshly dissolved in citrate buffer (pH 4.5) intraperitoneally after fasting overnight [20]. The rats with nonfasting plasma glucose levels of ≥300 mg/dl were considered diabetic and selected for further study. The CUMS model was established according to the methods of Willner with modifications [21]. The stress procedure contained a range of stressors, which consisted of 24 h water deprivation, a 1 min tail pinch, 5 min thermal stimulation in a 45°C oven, 5 min cold swimming at 4°C, a 24 h reversed light/dark cycle, 48 h food deprivation, electric shock to the foot (10 mA current; administered every other minute and lasting 10 sec per time for 30 times), shaking (once per second; lasting for 15 min), noise (85 dB), and strange smell. During a period of 28 days, one of the stimuli was selected randomly and applied to the rats so that the rats were not able to expect the stimulus. Every stimulus used 2 or 3 times in total for each rat within 28 days. So, SD rats were divided into 3 groups, including control group, diabetic group, and diabetes with CUMS group. Body weights were assessed weekly starting from the seventeenth day.
### 2.5. Glucose Metabolism Measurements
#### 2.5.1. Oral Glucose Tolerance Test (OGTT)
Following the final behavioral test, overnight-fasted rat was given a glucose solution orally (2.0 g/kg). And then blood sample was collected from the tail tip of conscious rat before and after glucose load at 0, 30, 60, 90, and 120 minutes for measurements of serum glucose using a single touch glucometer.
#### 2.5.2. Blood Glucose, HbA1C, Insulin, and Leptin
After the oral glucose tolerance test, a single touch glucometer (OneTouch Ultra2; LifeScan, High Wycombe, UK) was used to determine the glucose levels in plasma collected from the tail vein of the rats. Subsequently, the rats were anesthetized, and blood samples were collected by the abdominal aortic method in tubes containing EDTA and centrifuged at 2,500xg for 15min at 4°C. The serum was stored at -70°C until analysis. The serum levels of fasting insulin (FINS, Nanjing Jiancheng, Nanjing, China), glycosylated hemoglobin (HbA1c, Nanjing Jiancheng, Nanjing, China), and leptin (LEP, ELISA LAB, Wuhan, China) were detected using enzymatic kits (Nanjing Jiancheng, Nanjing, China). The homeostasis model assessment of insulin resistance was calculated as followed: (HOMA-IR) = (FPG×FINS) /22.5. All serum samples were measured with a RT-1904C Semi-Auto Chemistry Analyzer (Rayto Life and Analytical Sciences Co., Ltd., Shenzhen, China).
### 2.6. Behavioral Measurements
#### 2.6.1. Open-Field Test (OF)
An 80cm×80cm×40cm open-field was utilized in this experiment. The bottom of the box was divided into 25 equilateral squares. The rats were placed in the central of the open-field, after that the horizontal movement (four feet within a square counted as one score) and vertical movement were counted by scoring within 3min after 1min adaptation.
#### 2.6.2. Tail Suspension Test (TST)
The tail suspension apparatus consisted of an iron shelf supporting a stainless steel bar approximately 30 cm from the ground. About 4 cm tail tip of rats was fixed to that steel bar. Then each rat could adapt to this new condition for 1 minute. Depression-like behavior was inferred from increased duration of immobility in 3 minutes. In addition, all rats could not interfere with each other in the test.
#### 2.6.3. Forced Swim Test (FST)
This test needs a circular fiberglass pool containing warm water (25±1°C). And in this experiment, all the rats were given 1 minute to adjust and 3 minutes to swim. Immobility time was determined by the time a rat stopped struggling. Moreover, moved slowly to remain floating in the water was seen as immobility.
#### 2.6.4. Morris Water Maze Test (MWM)
The Morris water maze consisted of a circular fiberglass pool (200cm in diameter) filled with water (25±1°C) and made opaque with black nontoxic paint. The trials were conducted once a day for five days. The time for rats to locate the platform was recorded. Each trial lasted either until the rat located the platform for 60 sec, which was recorded as the escape latency (EL) time, and the mean EL time of the last four days as the outcome of learning. The platform was removed for a 60-sec probe trial on the final day, and the time spent swimming in the platform quadrant was recorded as the space exploration time (SET).
### 2.7. Western Blot Analysis
The hippocampus was homogenized in lysis buffer (Sigma, St. Louis, MO, USA)]. After that, the protein was electrophoretically resolved on 10% SDS-polyacrylamide gels and transferred to nitrocellulose membranes. The blots were blocked with skimmed milk and incubated in anti-p-IR (1:1000; Cell Signaling Technology, USA) and anti-p-IRS-1 (1:1000; Cell Signaling Technology, USA) for 4°C overnight respectively. And then secondary HRP antibody was added. Finally, the signals were visualized by use of Enhanced Chemioluminescence kit (ECL, Amersham).
### 2.8. Statistical Analysis
All the data were based on SPSS16.0 and analyzed by one-way analysis of variance (ANOVA). Covariance analysis was utilized in evasive latency in water maze test. A level ofp<0.05 was set as statistically significant.
## 2.1. Animals
Adult male Sprague-Dawley rats (weight, 200-220g; license No. SCXK 2009-0004) were provided by Hunan Slac Jingda Laboratory Animal Co., Ltd. (Changsha, China). They were housed with access to food and water, and maintained on a 12h light/dark cycle (lights on at 7:00 a.m.), at 22°C with low humidity. All animal experiments were carried out in accordance with the National Institute of Health Guide for the Care and Use of Laboratory Animals (NIH publication 8023, revised 1996) and with the approval of the Animal Ethics Welfare Committee of the First Affiliated Hospital of Hunan University of Chinese Medicine.
## 2.2. Chemicals and Reagents
Streptozotocin (STZ) was purchased from Sigma-Aldrich (St. Louis, MO, USA). The high-fat diet (HFD) consisted of 58% fat, 25% protein, and 17% carbohydrate, as a percentage of the total kilocalories. Antibodies against pIR(Y1158) and pIRS1(S307) were purchased from Abcam (Cambridge, UK).
## 2.3. Instruments
The high-speed refrigerated centrifuge was from Sigma-Aldrich (SIGMA 3K15, Sigma Laborzentrifugen GmbH, Osterode am Harz, Germany), a microplate reader was obtained from Thermo Fisher Scientific Inc. (Waltham, MA, USA; MK3), and open boxes and the Morris water were obtained from Panlab(SMART3.0, Panlab, Spanish).
## 2.4. Model of Diabetes and the Procedure of CUMS
The experimental model of diabetes mellitus (DM) was induced with a combination of low-dose STZ and a HFD. Following the onset of the experiment, the rats were fed libitum with a HFD for two weeks and then received 38 mg/kg STZ freshly dissolved in citrate buffer (pH 4.5) intraperitoneally after fasting overnight [20]. The rats with nonfasting plasma glucose levels of ≥300 mg/dl were considered diabetic and selected for further study. The CUMS model was established according to the methods of Willner with modifications [21]. The stress procedure contained a range of stressors, which consisted of 24 h water deprivation, a 1 min tail pinch, 5 min thermal stimulation in a 45°C oven, 5 min cold swimming at 4°C, a 24 h reversed light/dark cycle, 48 h food deprivation, electric shock to the foot (10 mA current; administered every other minute and lasting 10 sec per time for 30 times), shaking (once per second; lasting for 15 min), noise (85 dB), and strange smell. During a period of 28 days, one of the stimuli was selected randomly and applied to the rats so that the rats were not able to expect the stimulus. Every stimulus used 2 or 3 times in total for each rat within 28 days. So, SD rats were divided into 3 groups, including control group, diabetic group, and diabetes with CUMS group. Body weights were assessed weekly starting from the seventeenth day.
## 2.5. Glucose Metabolism Measurements
### 2.5.1. Oral Glucose Tolerance Test (OGTT)
Following the final behavioral test, overnight-fasted rat was given a glucose solution orally (2.0 g/kg). And then blood sample was collected from the tail tip of conscious rat before and after glucose load at 0, 30, 60, 90, and 120 minutes for measurements of serum glucose using a single touch glucometer.
### 2.5.2. Blood Glucose, HbA1C, Insulin, and Leptin
After the oral glucose tolerance test, a single touch glucometer (OneTouch Ultra2; LifeScan, High Wycombe, UK) was used to determine the glucose levels in plasma collected from the tail vein of the rats. Subsequently, the rats were anesthetized, and blood samples were collected by the abdominal aortic method in tubes containing EDTA and centrifuged at 2,500xg for 15min at 4°C. The serum was stored at -70°C until analysis. The serum levels of fasting insulin (FINS, Nanjing Jiancheng, Nanjing, China), glycosylated hemoglobin (HbA1c, Nanjing Jiancheng, Nanjing, China), and leptin (LEP, ELISA LAB, Wuhan, China) were detected using enzymatic kits (Nanjing Jiancheng, Nanjing, China). The homeostasis model assessment of insulin resistance was calculated as followed: (HOMA-IR) = (FPG×FINS) /22.5. All serum samples were measured with a RT-1904C Semi-Auto Chemistry Analyzer (Rayto Life and Analytical Sciences Co., Ltd., Shenzhen, China).
## 2.5.1. Oral Glucose Tolerance Test (OGTT)
Following the final behavioral test, overnight-fasted rat was given a glucose solution orally (2.0 g/kg). And then blood sample was collected from the tail tip of conscious rat before and after glucose load at 0, 30, 60, 90, and 120 minutes for measurements of serum glucose using a single touch glucometer.
## 2.5.2. Blood Glucose, HbA1C, Insulin, and Leptin
After the oral glucose tolerance test, a single touch glucometer (OneTouch Ultra2; LifeScan, High Wycombe, UK) was used to determine the glucose levels in plasma collected from the tail vein of the rats. Subsequently, the rats were anesthetized, and blood samples were collected by the abdominal aortic method in tubes containing EDTA and centrifuged at 2,500xg for 15min at 4°C. The serum was stored at -70°C until analysis. The serum levels of fasting insulin (FINS, Nanjing Jiancheng, Nanjing, China), glycosylated hemoglobin (HbA1c, Nanjing Jiancheng, Nanjing, China), and leptin (LEP, ELISA LAB, Wuhan, China) were detected using enzymatic kits (Nanjing Jiancheng, Nanjing, China). The homeostasis model assessment of insulin resistance was calculated as followed: (HOMA-IR) = (FPG×FINS) /22.5. All serum samples were measured with a RT-1904C Semi-Auto Chemistry Analyzer (Rayto Life and Analytical Sciences Co., Ltd., Shenzhen, China).
## 2.6. Behavioral Measurements
### 2.6.1. Open-Field Test (OF)
An 80cm×80cm×40cm open-field was utilized in this experiment. The bottom of the box was divided into 25 equilateral squares. The rats were placed in the central of the open-field, after that the horizontal movement (four feet within a square counted as one score) and vertical movement were counted by scoring within 3min after 1min adaptation.
### 2.6.2. Tail Suspension Test (TST)
The tail suspension apparatus consisted of an iron shelf supporting a stainless steel bar approximately 30 cm from the ground. About 4 cm tail tip of rats was fixed to that steel bar. Then each rat could adapt to this new condition for 1 minute. Depression-like behavior was inferred from increased duration of immobility in 3 minutes. In addition, all rats could not interfere with each other in the test.
### 2.6.3. Forced Swim Test (FST)
This test needs a circular fiberglass pool containing warm water (25±1°C). And in this experiment, all the rats were given 1 minute to adjust and 3 minutes to swim. Immobility time was determined by the time a rat stopped struggling. Moreover, moved slowly to remain floating in the water was seen as immobility.
### 2.6.4. Morris Water Maze Test (MWM)
The Morris water maze consisted of a circular fiberglass pool (200cm in diameter) filled with water (25±1°C) and made opaque with black nontoxic paint. The trials were conducted once a day for five days. The time for rats to locate the platform was recorded. Each trial lasted either until the rat located the platform for 60 sec, which was recorded as the escape latency (EL) time, and the mean EL time of the last four days as the outcome of learning. The platform was removed for a 60-sec probe trial on the final day, and the time spent swimming in the platform quadrant was recorded as the space exploration time (SET).
## 2.6.1. Open-Field Test (OF)
An 80cm×80cm×40cm open-field was utilized in this experiment. The bottom of the box was divided into 25 equilateral squares. The rats were placed in the central of the open-field, after that the horizontal movement (four feet within a square counted as one score) and vertical movement were counted by scoring within 3min after 1min adaptation.
## 2.6.2. Tail Suspension Test (TST)
The tail suspension apparatus consisted of an iron shelf supporting a stainless steel bar approximately 30 cm from the ground. About 4 cm tail tip of rats was fixed to that steel bar. Then each rat could adapt to this new condition for 1 minute. Depression-like behavior was inferred from increased duration of immobility in 3 minutes. In addition, all rats could not interfere with each other in the test.
## 2.6.3. Forced Swim Test (FST)
This test needs a circular fiberglass pool containing warm water (25±1°C). And in this experiment, all the rats were given 1 minute to adjust and 3 minutes to swim. Immobility time was determined by the time a rat stopped struggling. Moreover, moved slowly to remain floating in the water was seen as immobility.
## 2.6.4. Morris Water Maze Test (MWM)
The Morris water maze consisted of a circular fiberglass pool (200cm in diameter) filled with water (25±1°C) and made opaque with black nontoxic paint. The trials were conducted once a day for five days. The time for rats to locate the platform was recorded. Each trial lasted either until the rat located the platform for 60 sec, which was recorded as the escape latency (EL) time, and the mean EL time of the last four days as the outcome of learning. The platform was removed for a 60-sec probe trial on the final day, and the time spent swimming in the platform quadrant was recorded as the space exploration time (SET).
## 2.7. Western Blot Analysis
The hippocampus was homogenized in lysis buffer (Sigma, St. Louis, MO, USA)]. After that, the protein was electrophoretically resolved on 10% SDS-polyacrylamide gels and transferred to nitrocellulose membranes. The blots were blocked with skimmed milk and incubated in anti-p-IR (1:1000; Cell Signaling Technology, USA) and anti-p-IRS-1 (1:1000; Cell Signaling Technology, USA) for 4°C overnight respectively. And then secondary HRP antibody was added. Finally, the signals were visualized by use of Enhanced Chemioluminescence kit (ECL, Amersham).
## 2.8. Statistical Analysis
All the data were based on SPSS16.0 and analyzed by one-way analysis of variance (ANOVA). Covariance analysis was utilized in evasive latency in water maze test. A level ofp<0.05 was set as statistically significant.
## 3. Result
### 3.1. CUMS Accelerate Weight Loss in Rat with Diabetes
Rats in normal group kept a healthy weight gain during the whole experiment, while diabetic rats put on a little weight at first 2 weeks and lost weight at last 2 weeks. However, when CUMS was started, the weight loss was the most serious. Starting from 31 days, significant weight loss was observed in both diabetic groups compared with the control group (Figure1,p<0.01). Meanwhile, a serious weight loss was found in diabetes with CUMS rather than diabetic rats (Figure 1,p<0.05 andp<0.01).Figure 1
Body weight. Body weight significantly decreased in both diabetic rats. And there was a significant difference between diabetic rat with CUMS and without CUMS.∗∗p<0.01, control versus diabetic. #p<0.05, diabetic versus diabetic +CUMS. ##p<0.01, diabetic versus diabetic +CUMS.
### 3.2. Disorders of Blood Glucose and Relative Indexes in Diabetic Rats with CUMS
High-fat diet and streptozotocin injection resulted in a diabetic syndrome verified by the presence of hyperglycemia, high levels of hemoglobin A1c concentrations (HbA1c), and peripheral insulin resistance. The concentrations of fasting blood glucose, HbA1c, insulin, and leptin in both of the diabetic groups were significantly higher than the control group (Figures2(c), 2(d), 2(e), and 2(g),p<0.01 orp<0.05). Moreover, glucose tolerance and insulin resistance were impaired in diabetic groups than control group (Figures 2(b) and 2(f),p<0.01). However, there were no significant differences of blood glucose and relative indexes between diabetic group and diabetic + CUMS group except for leptin.Figure 2
Characterization of diabetic rats with CUMS. High-fat diet and streptozotocin injection induces changes in fasting blood glucose levels, HbA1c levels, insulin resistance index, and oral glucose tolerance test. After receiving CUMS, there were no obvious changes in the above indexes of the diabetic rats. (a) Oral glucose tolerance test. (b) Area under curve of the glucose level in oral glucose tolerance test. (c) The level of HbA1c. (d) Fasting blood glucose concentration. (e) Fasting insulin concentration. (f) Insulin resistance index. (g) The level of leptin.∗∗p<0.01, control versus diabetic.
(a) (b) (c) (d) (e) (f) (g)
### 3.3. CUMS Decrease the Performance Status in Diabetic Rat
Depression-like behaviors were assessed in the open-field (OF), forced swim test (FST), and tail suspension test (TST). In the OF, the horizontal activity and vertical activity were observed to evaluate the motion activity and curiosity in an open-field. The result indicates that there was a down-regulation in both diabetic groups when compared with control group. However, the total activity scores of horizon activities and vertical activities were significantly reduced in diabetic + CUMS group instead of diabetic group when compared with control group (Figure3(a),p<0.01). Further, the diabetic rats with CUMS had fewer activity scores when compared with the diabetic group (Figure 3(a),p<0.01). Moreover, in FST, the duration of immobility was obviously increased in diabetic group and diabetic + CUMS group when contrast to control group (Figure 3(b),p<0.01 andp<0.05). And there was a dramatic difference between diabetes group and diabetes + CUMS group (Figure 3(b),p<0.01). Similarly, in TST, the time of immobility was obvious longer in diabetic + CUMS group than it was in control group, and it was much longer than diabetes group as well (Figure 3(b),p<0.01). Nevertheless, in this test, there were no significant differences between diabetic group and control group. Thus, the results demonstrate that depression-like behaviors in diabetic + CUMS group were more obvious than other groups.Figure 3
CUMS induces changes in depressive-like behaviors of diabetic rats. (a) The locomotion in OF. (b) The time of immobility in TST and FST.∗∗p<0.01, control versus diabetic. ##p<0.01, diabetic versus diabetic +CUMS.
(a) (b)
### 3.4. CUMS Leads to a Declined Capability of Learning and Memory in Diabetic Rat
The purpose of Morris water maze is to test the capability of learning and memory by place navigation and space exploration. The evasive latency (EL) was recorded in place navigation. There was a negative relationship between EL and the duration of the training days in all three groups according to regression analysis (Figure4(a)). It appears to be a linear relationship (R2 value 0.9307, 0.9702, and 0.9742) in control group, diabetic group, and diabetic + CUMS group, respectively. EL went down significantly over time when the animals had high learning capacity. Thus, we use the slope of the regression curve to demonstrate the capability of learning. And we found that there is a significant difference between diabetic + CUMS group and control group in learning slope curve according to covariance analysis (p=0.046).Figure 4
CUMS induces declines in cognitive function of diabetic rats. (a) The time of escape latency. (b) The time of space exploration.∗∗p<0.01, control versus diabetic. ##p<0.01, #p<0.05, diabetic versus diabetic +CUMS.
(a) (b)On the 5th day of the test, place exploration was performed. The duration for rats to spend in target area and locate the site (platform) was recorded as space exploration time (SET). The result demonstrates that SET in target area was significantly lower in both diabetic groups when compared with control group (Figure4(b),p<0.01). These data suggest that the capability of learning and memory in diabetic rat were significantly affected by CUMS.
### 3.5. The Abnormal Brain Insulin Signaling Pathway in the Hippocampus of Diabetic Rats with CUMS
The levels of the phosphorylation of IR and Ser phosphorylation of IRS-1 protein were analyzed by a quantitative Western blot procedure in hippocampus (Figure5(a)). The intensities of β-actin bands were taken as an equal load controls and the ratios p-IR: IR and p-IRS-1: IRS-1 were calculated for each lane and the results are expressed as a percentage of p-IR and p-IRS-1 proteins (Figure 5(b),p<0.05). It has been found that both of diabetic rats had lower hippocampal p-IR and higher p-IRS-1 concentration when compared with control group. Diabetic rats subjected to CUMS increased in p-IR and decreased in p-IRS-1 levels in hippocampus compared with diabetic rats.Figure 5
CUMS led to impairment of insulin signaling pathway in hippocampus of diabetic rats. (a) Representative Western blots of IR and IRS-1 proteins. (b) Densitometry measurements.∗p<0.05, control versus diabetic. #p<0.05, diabetic versus diabetic +CUMS.
(a) (b)
## 3.1. CUMS Accelerate Weight Loss in Rat with Diabetes
Rats in normal group kept a healthy weight gain during the whole experiment, while diabetic rats put on a little weight at first 2 weeks and lost weight at last 2 weeks. However, when CUMS was started, the weight loss was the most serious. Starting from 31 days, significant weight loss was observed in both diabetic groups compared with the control group (Figure1,p<0.01). Meanwhile, a serious weight loss was found in diabetes with CUMS rather than diabetic rats (Figure 1,p<0.05 andp<0.01).Figure 1
Body weight. Body weight significantly decreased in both diabetic rats. And there was a significant difference between diabetic rat with CUMS and without CUMS.∗∗p<0.01, control versus diabetic. #p<0.05, diabetic versus diabetic +CUMS. ##p<0.01, diabetic versus diabetic +CUMS.
## 3.2. Disorders of Blood Glucose and Relative Indexes in Diabetic Rats with CUMS
High-fat diet and streptozotocin injection resulted in a diabetic syndrome verified by the presence of hyperglycemia, high levels of hemoglobin A1c concentrations (HbA1c), and peripheral insulin resistance. The concentrations of fasting blood glucose, HbA1c, insulin, and leptin in both of the diabetic groups were significantly higher than the control group (Figures2(c), 2(d), 2(e), and 2(g),p<0.01 orp<0.05). Moreover, glucose tolerance and insulin resistance were impaired in diabetic groups than control group (Figures 2(b) and 2(f),p<0.01). However, there were no significant differences of blood glucose and relative indexes between diabetic group and diabetic + CUMS group except for leptin.Figure 2
Characterization of diabetic rats with CUMS. High-fat diet and streptozotocin injection induces changes in fasting blood glucose levels, HbA1c levels, insulin resistance index, and oral glucose tolerance test. After receiving CUMS, there were no obvious changes in the above indexes of the diabetic rats. (a) Oral glucose tolerance test. (b) Area under curve of the glucose level in oral glucose tolerance test. (c) The level of HbA1c. (d) Fasting blood glucose concentration. (e) Fasting insulin concentration. (f) Insulin resistance index. (g) The level of leptin.∗∗p<0.01, control versus diabetic.
(a) (b) (c) (d) (e) (f) (g)
## 3.3. CUMS Decrease the Performance Status in Diabetic Rat
Depression-like behaviors were assessed in the open-field (OF), forced swim test (FST), and tail suspension test (TST). In the OF, the horizontal activity and vertical activity were observed to evaluate the motion activity and curiosity in an open-field. The result indicates that there was a down-regulation in both diabetic groups when compared with control group. However, the total activity scores of horizon activities and vertical activities were significantly reduced in diabetic + CUMS group instead of diabetic group when compared with control group (Figure3(a),p<0.01). Further, the diabetic rats with CUMS had fewer activity scores when compared with the diabetic group (Figure 3(a),p<0.01). Moreover, in FST, the duration of immobility was obviously increased in diabetic group and diabetic + CUMS group when contrast to control group (Figure 3(b),p<0.01 andp<0.05). And there was a dramatic difference between diabetes group and diabetes + CUMS group (Figure 3(b),p<0.01). Similarly, in TST, the time of immobility was obvious longer in diabetic + CUMS group than it was in control group, and it was much longer than diabetes group as well (Figure 3(b),p<0.01). Nevertheless, in this test, there were no significant differences between diabetic group and control group. Thus, the results demonstrate that depression-like behaviors in diabetic + CUMS group were more obvious than other groups.Figure 3
CUMS induces changes in depressive-like behaviors of diabetic rats. (a) The locomotion in OF. (b) The time of immobility in TST and FST.∗∗p<0.01, control versus diabetic. ##p<0.01, diabetic versus diabetic +CUMS.
(a) (b)
## 3.4. CUMS Leads to a Declined Capability of Learning and Memory in Diabetic Rat
The purpose of Morris water maze is to test the capability of learning and memory by place navigation and space exploration. The evasive latency (EL) was recorded in place navigation. There was a negative relationship between EL and the duration of the training days in all three groups according to regression analysis (Figure4(a)). It appears to be a linear relationship (R2 value 0.9307, 0.9702, and 0.9742) in control group, diabetic group, and diabetic + CUMS group, respectively. EL went down significantly over time when the animals had high learning capacity. Thus, we use the slope of the regression curve to demonstrate the capability of learning. And we found that there is a significant difference between diabetic + CUMS group and control group in learning slope curve according to covariance analysis (p=0.046).Figure 4
CUMS induces declines in cognitive function of diabetic rats. (a) The time of escape latency. (b) The time of space exploration.∗∗p<0.01, control versus diabetic. ##p<0.01, #p<0.05, diabetic versus diabetic +CUMS.
(a) (b)On the 5th day of the test, place exploration was performed. The duration for rats to spend in target area and locate the site (platform) was recorded as space exploration time (SET). The result demonstrates that SET in target area was significantly lower in both diabetic groups when compared with control group (Figure4(b),p<0.01). These data suggest that the capability of learning and memory in diabetic rat were significantly affected by CUMS.
## 3.5. The Abnormal Brain Insulin Signaling Pathway in the Hippocampus of Diabetic Rats with CUMS
The levels of the phosphorylation of IR and Ser phosphorylation of IRS-1 protein were analyzed by a quantitative Western blot procedure in hippocampus (Figure5(a)). The intensities of β-actin bands were taken as an equal load controls and the ratios p-IR: IR and p-IRS-1: IRS-1 were calculated for each lane and the results are expressed as a percentage of p-IR and p-IRS-1 proteins (Figure 5(b),p<0.05). It has been found that both of diabetic rats had lower hippocampal p-IR and higher p-IRS-1 concentration when compared with control group. Diabetic rats subjected to CUMS increased in p-IR and decreased in p-IRS-1 levels in hippocampus compared with diabetic rats.Figure 5
CUMS led to impairment of insulin signaling pathway in hippocampus of diabetic rats. (a) Representative Western blots of IR and IRS-1 proteins. (b) Densitometry measurements.∗p<0.05, control versus diabetic. #p<0.05, diabetic versus diabetic +CUMS.
(a) (b)
## 4. Discussion
Diabetes usually causes a number of complications involving brain function which related to cognitive decline and depression [22]. The effects of diabetes on central nervous system (CNS) were related to the negative impact of behavioral and emotional functions, with pathological mechanism [9, 10, 23]. The behavioral despair performed an increased immobility time in forced swim test in adult db/db mice [23]. However, Dinel and his colleagues reported that an impaired spatial recognition memory was found in db/db mice, rather than depressive-like behaviors [10]. Moreover, Can et al. found that diabetes mellitus (DM) causes depression deterioration, and spontaneous locomotor activities were decreased accompanied with learning parameters impairment [9]. Thus, the results of mood disturbances (depression) in diabetic rats are inconsistent, as well as it was in this study (Figure 3). Clinical evidences suggest that lots of external factors, such as inactivity, poor sleep, diet, and early life stress are associated with both diabetes and depression [24]. Therefore, we can surmise that the above competing results in animal experiments were related to the reason that external factors were not considered. CUMS is a classic method for building an animal model with a core symptom of depression [11]. This approach can provide a chronic mild stress and simulate the stress that patients suffered from. Thus, in this study, the influence of CUMS on the changes of emotional behaviors and memory performances in diabetic rats was investigated, as well as central insulin signaling.Prior to the above problems, it is better for us to understand that whether CUMS could affect the body weight, glucose level, and systemic insulin resistance in diabetic rats. There was a statistically significant weight loss in both of diabetic groups (Figure1). And the increased glucose, HbA1c level, and leptin concentration were found in both of diabetic rat (Figures 2(b), 2(c), and 2(g)), which exhibited impaired glucose tolerance (Figures 2(a) and 2(c)). These results indicate systemic IR with the high HOMA-IR index in two diabetic groups (Figure 2(d)). Leptin is an adipocyte hormone regarded as the afferent signal in a negative feedback loop regulating insulin biosynthesis and secretion [25]. The increased results of the insulin and leptin suggest that the leptin resistant occurred in increased leptin and it caused hyperinsulinemia. And stress could deteriorate the leptin resistant of diabetic rat. Furthermore, there are no significant differences between diabetic and diabetic + CUMS group on the aspect of fasting blood glucose, glucose tolerance, HbA1c, and peripheral insulin resistance (Figure 2). Although previous study shows that an oral glucose tolerance and serum insulin levels in normal control animals were damaged after CUMS was performed [26], we found that there are no remarkable changes in metabolic phenotypes after CUMS performed on diabetic rats in this study. Thus, it is concluded that the effect of outside interfere becomes inconspicuous after the occurrence of diseases such as obesity diabetes with which already accompany disordered endocrine function.It has been previously studied that diabetes mellitus (DM) have negative impacts on the central nervous system [27–30]. Many literatures suggested that the cognitive impairment was closely related to diabetes [31, 32]. We also observed that there are significant changes in learning and memory performance in diabetic rats with CUMS when compared to control group (Figure 4). However, whether depression-like behaviors are associated with diabetes mellitus is not clear. Liu and his coworkers found that db/db mice performed increased anxiety-like behaviors instead of depression-like behaviors [10]. On the contrary, another research group suggests that diabetes mellitus exacerbate the depression levels [9]. Thus, this study reported the depression behaviors and locomotor deficits in diabetic rats and CUMS with diabetes. Our results reveal that diabetes rats exhibited depressive-like behaviors as assessed by immobility time in the forced swim rather than depression in the open-field and tail suspension tests (Figure 3). Based on this study, it suggests that depressive moods and cognitive deficits do not occur at the same time in diabetes. S. Sasaki-Hamada and his colleagues found that synaptic plasticity of hippocampus was affected by the length of diabetes [33]. In addition, neuroplasticity is thought to be closely related to mood disorders [34]. Consistence to the above results, we found that there is a link between the depression-like behaviors and the length of diabetes in diabetic rats. Furthermore, cognitive impairment, especially memory damage, may occur earlier than mood disorder in diabetic rats. More importantly, CUMS could aggravate the emotional and cognitive impairment in diabetic rats, whereas, as stated before, the imbalanced glucose metabolism is hardly deteriorated after CUMS performed in diabetic rats. It concluded that the effect of interfere stress on behavior and cognition is greater than that of blood glucose on behavior and cognition when diabetes was existed. Thus, ignoring the psychological counseling of diabetic patients may accelerate the occurrence of diabetes-related depression.Insulin signaling in brain plays an important role in the development and progression of diabetes mellitus [35], as well as diabetic encephalopathy [16]. This system of the brain is involved in the regulation of neuronal growth and synaptic plasticity and controls metabolic process in the CNS and periphery [36]. Depression symptoms and cognitive functions including spatial memory are associated with brain insulin resistance in type 2 diabetes [37, 38]. Furthermore, the recent researches indicate that chronic stress mediated behavioral dysfunction in normal mice are associated with impaired hippocampal insulin signaling [39]. To further investigate the underlying molecular in diabetes, depression, and stress, CUMS performed on diabetes was utilized to induce IR in peripheral and central organs. Our study researched the activation of insulin signaling in the hippocampus, a key brain area for the control of emotional and cognitive behaviors. Insulin receptor and its major downstream targets, insulin receptor substrate 1 (IRS-1), and IRS-2 are regarded as the core in insulin signaling [40]. The different phosphorylated subtypes of IRS family of protein could activate the different downstream signaling cascade, thereby inducing the physiological function and pathological change. For example, phosphorylation of IRS could activate phosphatidylinositol 3-kinase (PI3K) and phosphoinositide-dependent protein kinase-1 (PDK1) activation, thereby activating the downstream signaling cascade involving Akt [41]. Activation of Akt leads to the phosphorylation of GSK3β, and the Akt/GSK3β pathways are important regulators of depression [42]. In addition, phosphorylated IRS can also regulate the activation of JNK, CHOP (stress), and NF-κB (inflammatory pathways) [43]. Our data demonstrated that phosphorylation of IR was decreased, while serine phosphorylation of IRS-1 was increased in hippocampus in diabetic rats (Figure 5). When CUMS is applied to diabetic animals, the increased p-IPS-1 level and decreased p-IR level were getting severer.In summary, it is difficult to explain the relationship between diabetes and depression. Recent reports demonstrate that shared clinical and pathophysiologic traits between diabetes and depression raise the possibility that stress and pressure play an important role in the pathophysiology of cognitive decline. Data in this study reveal the effects of CUMS aggravated mood disorder, cognitive impairment in diabetic rats. These results are in accordance with the previous studies that people whom lived in a bad situation would be more prone to depression. Moreover, animals with diabetes are more prone to pose negative effects on brain insulin signaling under CUMS condition.
---
*Source: 2901863-2018-12-03.xml* | 2901863-2018-12-03_2901863-2018-12-03.md | 44,049 | Chronic Unpredictable Mild Stress Aggravates Mood Disorder, Cognitive Impairment, and Brain Insulin Resistance in Diabetic Rat | Hui Yang; Wei Li; Pan Meng; Zhuo Liu; Jian Liu; Yuhong Wang | Evidence-Based Complementary and Alternative Medicine
(2018) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2018/2901863 | 2901863-2018-12-03.xml | ---
## Abstract
Diabetes-induced brain insulin resistance is associated with many mental diseases, including depression. Epidemiological evidences demonstrate the pathophysiologic link between stress, depression, and diabetes. This study was designed to determine whether chronic unpredictable mild stress- (CUMS-) induced changes in brain insulin resistance could contribute to deterioration in mood and cognitive functions in diabetic rats. Male SD rats were randomly assigned to three groups, including standard control group, the diabetes group, and the diabetes with CUMS group. After 7 weeks, emotional behaviors and memory performances as well as metabolic phenotypes were measured. In addition, we examined the changes in protein expression related to brain insulin signaling. Our results show that rats in diabetes with CUMS group displayed a decreased locomotor behavior in open-field test, an increased immobility time in forced swim test, and tail suspension test, and an impaired learning and memory in the Morris water maze when compared to animals in diabetes group. Further, diabetes with CUMS exhibited a significant decrease in phosphorylation of insulin receptor and an increase phosphorylation of IRS-1 in brain. These results suggest that the depression-like behaviors and cognitive function impairments in diabetic rats with CUMS were related to the changes of brain insulin signaling.
---
## Body
## 1. Introduction
More than 382 million patients worldwide suffered from diabetes mellitus in 2013, and this number will reach 592 million in 2035 [1]. The prevalence of depression in people with diabetes may run up to 38.75%. Among these people, 48.38% were found suffering from moderately depressed [2]. A cross-sectional study [3] described that 35.1% patients with diabetes were diagnosed depression symptoms. Statistically, Bhattacharya and his colleagues found that “total healthcare expenditures were reduced by treatment with antidepressants (16% reduction), psychotherapy (22%), and both therapy types in combination (28%) compared to no depression treatment” [4]. However, the government did not pay attention to the increase prevalence of depression and diabetes and its health services. Moreover, the treatments to patients with related diseases were insufficient [5]. The potential biopsychosocial risk factors of diabetes and depression were the influences on marital status, occupation, and social support [6]. The researches associated with pathophysiological mechanisms of depression in patients with diabetes were insufficient. The association between depression and insulin resistance (IR) can explain the biological link between depression and type 2 diabetes [7]. Understanding the disordered systemic IR and defective brain insulin signaling in comorbidity of diabetes and depression has become a topic of concern and public health challenge.Comorbidity between diabetes and depression was related to biological, psychological, and social factors, according to Tesfa Dejenie Habtewold [6]. An average depression symptoms score of patients with diabetes was usually affected by external factors including income, educational status, physical activity, and fearing diabetes-related complication and death [6, 8]. However, it is difficult to analyze the external factors in animal trials. Although db/db mice and streptozotocin- (STZ-) diabetic rat were utilized to study this comorbidity [9, 10], the outside influential factors were not considered in most of studies. Chronic unpredictable mild stress (CUMS) procedure has been widely utilized in the study with encouraging results [11]. CUMS model of depression has good predictive validity, face validity, and construct validity [11]. Thus, it is worthwhile to optimize the experimental model in this comorbidity by combining CUMS with diabetes. And it is meaningful to explore the association between depression and diabetes mellitus based on this animal model.Insulin regulates glucose uptake and storage in peripheral tissues, and it has been shown to alter brain function and metabolism [12–14]. Pancreas is the only organ to produce insulin and the insulin crosses the blood-brain barrier (BBB) by using a saturable transporter, and acts on the brain function through glucose utilization [15].Previous reports demonstrate that IR leads to memory impairment and it is a risk factor for diabetic encephalopathy in recent years [16, 17]. There are many theories to explain the connection between diabetes and psychiatric disorders, including abnormal glucose metabolism, impaired brain insulin signaling, neurogenesis, and alterations in glucocorticoid levels [18]. Nevertheless, the pathologic role of brain insulin in hippocampus in diabetes-related depression is not fully explained.A combination of high-fat diet (HFD) and tail meridians injection of streptozotocin (STZ) is a well-established approach to inducing diabetes mellitus [19]. And CUMS provides the diabetic rats with appropriate stress stimulation. However, the possible effect of CUMS on depression-like alterations in rats with diabetes characterized by brain insulin resistance has not yet been investigated. This study is aimed to study the changes of emotional behaviors and memory performances, glucose metabolism, and brain insulin signaling in rats with diabetes subjected to CUMS.
## 2. Material and Methods
### 2.1. Animals
Adult male Sprague-Dawley rats (weight, 200-220g; license No. SCXK 2009-0004) were provided by Hunan Slac Jingda Laboratory Animal Co., Ltd. (Changsha, China). They were housed with access to food and water, and maintained on a 12h light/dark cycle (lights on at 7:00 a.m.), at 22°C with low humidity. All animal experiments were carried out in accordance with the National Institute of Health Guide for the Care and Use of Laboratory Animals (NIH publication 8023, revised 1996) and with the approval of the Animal Ethics Welfare Committee of the First Affiliated Hospital of Hunan University of Chinese Medicine.
### 2.2. Chemicals and Reagents
Streptozotocin (STZ) was purchased from Sigma-Aldrich (St. Louis, MO, USA). The high-fat diet (HFD) consisted of 58% fat, 25% protein, and 17% carbohydrate, as a percentage of the total kilocalories. Antibodies against pIR(Y1158) and pIRS1(S307) were purchased from Abcam (Cambridge, UK).
### 2.3. Instruments
The high-speed refrigerated centrifuge was from Sigma-Aldrich (SIGMA 3K15, Sigma Laborzentrifugen GmbH, Osterode am Harz, Germany), a microplate reader was obtained from Thermo Fisher Scientific Inc. (Waltham, MA, USA; MK3), and open boxes and the Morris water were obtained from Panlab(SMART3.0, Panlab, Spanish).
### 2.4. Model of Diabetes and the Procedure of CUMS
The experimental model of diabetes mellitus (DM) was induced with a combination of low-dose STZ and a HFD. Following the onset of the experiment, the rats were fed libitum with a HFD for two weeks and then received 38 mg/kg STZ freshly dissolved in citrate buffer (pH 4.5) intraperitoneally after fasting overnight [20]. The rats with nonfasting plasma glucose levels of ≥300 mg/dl were considered diabetic and selected for further study. The CUMS model was established according to the methods of Willner with modifications [21]. The stress procedure contained a range of stressors, which consisted of 24 h water deprivation, a 1 min tail pinch, 5 min thermal stimulation in a 45°C oven, 5 min cold swimming at 4°C, a 24 h reversed light/dark cycle, 48 h food deprivation, electric shock to the foot (10 mA current; administered every other minute and lasting 10 sec per time for 30 times), shaking (once per second; lasting for 15 min), noise (85 dB), and strange smell. During a period of 28 days, one of the stimuli was selected randomly and applied to the rats so that the rats were not able to expect the stimulus. Every stimulus used 2 or 3 times in total for each rat within 28 days. So, SD rats were divided into 3 groups, including control group, diabetic group, and diabetes with CUMS group. Body weights were assessed weekly starting from the seventeenth day.
### 2.5. Glucose Metabolism Measurements
#### 2.5.1. Oral Glucose Tolerance Test (OGTT)
Following the final behavioral test, overnight-fasted rat was given a glucose solution orally (2.0 g/kg). And then blood sample was collected from the tail tip of conscious rat before and after glucose load at 0, 30, 60, 90, and 120 minutes for measurements of serum glucose using a single touch glucometer.
#### 2.5.2. Blood Glucose, HbA1C, Insulin, and Leptin
After the oral glucose tolerance test, a single touch glucometer (OneTouch Ultra2; LifeScan, High Wycombe, UK) was used to determine the glucose levels in plasma collected from the tail vein of the rats. Subsequently, the rats were anesthetized, and blood samples were collected by the abdominal aortic method in tubes containing EDTA and centrifuged at 2,500xg for 15min at 4°C. The serum was stored at -70°C until analysis. The serum levels of fasting insulin (FINS, Nanjing Jiancheng, Nanjing, China), glycosylated hemoglobin (HbA1c, Nanjing Jiancheng, Nanjing, China), and leptin (LEP, ELISA LAB, Wuhan, China) were detected using enzymatic kits (Nanjing Jiancheng, Nanjing, China). The homeostasis model assessment of insulin resistance was calculated as followed: (HOMA-IR) = (FPG×FINS) /22.5. All serum samples were measured with a RT-1904C Semi-Auto Chemistry Analyzer (Rayto Life and Analytical Sciences Co., Ltd., Shenzhen, China).
### 2.6. Behavioral Measurements
#### 2.6.1. Open-Field Test (OF)
An 80cm×80cm×40cm open-field was utilized in this experiment. The bottom of the box was divided into 25 equilateral squares. The rats were placed in the central of the open-field, after that the horizontal movement (four feet within a square counted as one score) and vertical movement were counted by scoring within 3min after 1min adaptation.
#### 2.6.2. Tail Suspension Test (TST)
The tail suspension apparatus consisted of an iron shelf supporting a stainless steel bar approximately 30 cm from the ground. About 4 cm tail tip of rats was fixed to that steel bar. Then each rat could adapt to this new condition for 1 minute. Depression-like behavior was inferred from increased duration of immobility in 3 minutes. In addition, all rats could not interfere with each other in the test.
#### 2.6.3. Forced Swim Test (FST)
This test needs a circular fiberglass pool containing warm water (25±1°C). And in this experiment, all the rats were given 1 minute to adjust and 3 minutes to swim. Immobility time was determined by the time a rat stopped struggling. Moreover, moved slowly to remain floating in the water was seen as immobility.
#### 2.6.4. Morris Water Maze Test (MWM)
The Morris water maze consisted of a circular fiberglass pool (200cm in diameter) filled with water (25±1°C) and made opaque with black nontoxic paint. The trials were conducted once a day for five days. The time for rats to locate the platform was recorded. Each trial lasted either until the rat located the platform for 60 sec, which was recorded as the escape latency (EL) time, and the mean EL time of the last four days as the outcome of learning. The platform was removed for a 60-sec probe trial on the final day, and the time spent swimming in the platform quadrant was recorded as the space exploration time (SET).
### 2.7. Western Blot Analysis
The hippocampus was homogenized in lysis buffer (Sigma, St. Louis, MO, USA)]. After that, the protein was electrophoretically resolved on 10% SDS-polyacrylamide gels and transferred to nitrocellulose membranes. The blots were blocked with skimmed milk and incubated in anti-p-IR (1:1000; Cell Signaling Technology, USA) and anti-p-IRS-1 (1:1000; Cell Signaling Technology, USA) for 4°C overnight respectively. And then secondary HRP antibody was added. Finally, the signals were visualized by use of Enhanced Chemioluminescence kit (ECL, Amersham).
### 2.8. Statistical Analysis
All the data were based on SPSS16.0 and analyzed by one-way analysis of variance (ANOVA). Covariance analysis was utilized in evasive latency in water maze test. A level ofp<0.05 was set as statistically significant.
## 2.1. Animals
Adult male Sprague-Dawley rats (weight, 200-220g; license No. SCXK 2009-0004) were provided by Hunan Slac Jingda Laboratory Animal Co., Ltd. (Changsha, China). They were housed with access to food and water, and maintained on a 12h light/dark cycle (lights on at 7:00 a.m.), at 22°C with low humidity. All animal experiments were carried out in accordance with the National Institute of Health Guide for the Care and Use of Laboratory Animals (NIH publication 8023, revised 1996) and with the approval of the Animal Ethics Welfare Committee of the First Affiliated Hospital of Hunan University of Chinese Medicine.
## 2.2. Chemicals and Reagents
Streptozotocin (STZ) was purchased from Sigma-Aldrich (St. Louis, MO, USA). The high-fat diet (HFD) consisted of 58% fat, 25% protein, and 17% carbohydrate, as a percentage of the total kilocalories. Antibodies against pIR(Y1158) and pIRS1(S307) were purchased from Abcam (Cambridge, UK).
## 2.3. Instruments
The high-speed refrigerated centrifuge was from Sigma-Aldrich (SIGMA 3K15, Sigma Laborzentrifugen GmbH, Osterode am Harz, Germany), a microplate reader was obtained from Thermo Fisher Scientific Inc. (Waltham, MA, USA; MK3), and open boxes and the Morris water were obtained from Panlab(SMART3.0, Panlab, Spanish).
## 2.4. Model of Diabetes and the Procedure of CUMS
The experimental model of diabetes mellitus (DM) was induced with a combination of low-dose STZ and a HFD. Following the onset of the experiment, the rats were fed libitum with a HFD for two weeks and then received 38 mg/kg STZ freshly dissolved in citrate buffer (pH 4.5) intraperitoneally after fasting overnight [20]. The rats with nonfasting plasma glucose levels of ≥300 mg/dl were considered diabetic and selected for further study. The CUMS model was established according to the methods of Willner with modifications [21]. The stress procedure contained a range of stressors, which consisted of 24 h water deprivation, a 1 min tail pinch, 5 min thermal stimulation in a 45°C oven, 5 min cold swimming at 4°C, a 24 h reversed light/dark cycle, 48 h food deprivation, electric shock to the foot (10 mA current; administered every other minute and lasting 10 sec per time for 30 times), shaking (once per second; lasting for 15 min), noise (85 dB), and strange smell. During a period of 28 days, one of the stimuli was selected randomly and applied to the rats so that the rats were not able to expect the stimulus. Every stimulus used 2 or 3 times in total for each rat within 28 days. So, SD rats were divided into 3 groups, including control group, diabetic group, and diabetes with CUMS group. Body weights were assessed weekly starting from the seventeenth day.
## 2.5. Glucose Metabolism Measurements
### 2.5.1. Oral Glucose Tolerance Test (OGTT)
Following the final behavioral test, overnight-fasted rat was given a glucose solution orally (2.0 g/kg). And then blood sample was collected from the tail tip of conscious rat before and after glucose load at 0, 30, 60, 90, and 120 minutes for measurements of serum glucose using a single touch glucometer.
### 2.5.2. Blood Glucose, HbA1C, Insulin, and Leptin
After the oral glucose tolerance test, a single touch glucometer (OneTouch Ultra2; LifeScan, High Wycombe, UK) was used to determine the glucose levels in plasma collected from the tail vein of the rats. Subsequently, the rats were anesthetized, and blood samples were collected by the abdominal aortic method in tubes containing EDTA and centrifuged at 2,500xg for 15min at 4°C. The serum was stored at -70°C until analysis. The serum levels of fasting insulin (FINS, Nanjing Jiancheng, Nanjing, China), glycosylated hemoglobin (HbA1c, Nanjing Jiancheng, Nanjing, China), and leptin (LEP, ELISA LAB, Wuhan, China) were detected using enzymatic kits (Nanjing Jiancheng, Nanjing, China). The homeostasis model assessment of insulin resistance was calculated as followed: (HOMA-IR) = (FPG×FINS) /22.5. All serum samples were measured with a RT-1904C Semi-Auto Chemistry Analyzer (Rayto Life and Analytical Sciences Co., Ltd., Shenzhen, China).
## 2.5.1. Oral Glucose Tolerance Test (OGTT)
Following the final behavioral test, overnight-fasted rat was given a glucose solution orally (2.0 g/kg). And then blood sample was collected from the tail tip of conscious rat before and after glucose load at 0, 30, 60, 90, and 120 minutes for measurements of serum glucose using a single touch glucometer.
## 2.5.2. Blood Glucose, HbA1C, Insulin, and Leptin
After the oral glucose tolerance test, a single touch glucometer (OneTouch Ultra2; LifeScan, High Wycombe, UK) was used to determine the glucose levels in plasma collected from the tail vein of the rats. Subsequently, the rats were anesthetized, and blood samples were collected by the abdominal aortic method in tubes containing EDTA and centrifuged at 2,500xg for 15min at 4°C. The serum was stored at -70°C until analysis. The serum levels of fasting insulin (FINS, Nanjing Jiancheng, Nanjing, China), glycosylated hemoglobin (HbA1c, Nanjing Jiancheng, Nanjing, China), and leptin (LEP, ELISA LAB, Wuhan, China) were detected using enzymatic kits (Nanjing Jiancheng, Nanjing, China). The homeostasis model assessment of insulin resistance was calculated as followed: (HOMA-IR) = (FPG×FINS) /22.5. All serum samples were measured with a RT-1904C Semi-Auto Chemistry Analyzer (Rayto Life and Analytical Sciences Co., Ltd., Shenzhen, China).
## 2.6. Behavioral Measurements
### 2.6.1. Open-Field Test (OF)
An 80cm×80cm×40cm open-field was utilized in this experiment. The bottom of the box was divided into 25 equilateral squares. The rats were placed in the central of the open-field, after that the horizontal movement (four feet within a square counted as one score) and vertical movement were counted by scoring within 3min after 1min adaptation.
### 2.6.2. Tail Suspension Test (TST)
The tail suspension apparatus consisted of an iron shelf supporting a stainless steel bar approximately 30 cm from the ground. About 4 cm tail tip of rats was fixed to that steel bar. Then each rat could adapt to this new condition for 1 minute. Depression-like behavior was inferred from increased duration of immobility in 3 minutes. In addition, all rats could not interfere with each other in the test.
### 2.6.3. Forced Swim Test (FST)
This test needs a circular fiberglass pool containing warm water (25±1°C). And in this experiment, all the rats were given 1 minute to adjust and 3 minutes to swim. Immobility time was determined by the time a rat stopped struggling. Moreover, moved slowly to remain floating in the water was seen as immobility.
### 2.6.4. Morris Water Maze Test (MWM)
The Morris water maze consisted of a circular fiberglass pool (200cm in diameter) filled with water (25±1°C) and made opaque with black nontoxic paint. The trials were conducted once a day for five days. The time for rats to locate the platform was recorded. Each trial lasted either until the rat located the platform for 60 sec, which was recorded as the escape latency (EL) time, and the mean EL time of the last four days as the outcome of learning. The platform was removed for a 60-sec probe trial on the final day, and the time spent swimming in the platform quadrant was recorded as the space exploration time (SET).
## 2.6.1. Open-Field Test (OF)
An 80cm×80cm×40cm open-field was utilized in this experiment. The bottom of the box was divided into 25 equilateral squares. The rats were placed in the central of the open-field, after that the horizontal movement (four feet within a square counted as one score) and vertical movement were counted by scoring within 3min after 1min adaptation.
## 2.6.2. Tail Suspension Test (TST)
The tail suspension apparatus consisted of an iron shelf supporting a stainless steel bar approximately 30 cm from the ground. About 4 cm tail tip of rats was fixed to that steel bar. Then each rat could adapt to this new condition for 1 minute. Depression-like behavior was inferred from increased duration of immobility in 3 minutes. In addition, all rats could not interfere with each other in the test.
## 2.6.3. Forced Swim Test (FST)
This test needs a circular fiberglass pool containing warm water (25±1°C). And in this experiment, all the rats were given 1 minute to adjust and 3 minutes to swim. Immobility time was determined by the time a rat stopped struggling. Moreover, moved slowly to remain floating in the water was seen as immobility.
## 2.6.4. Morris Water Maze Test (MWM)
The Morris water maze consisted of a circular fiberglass pool (200cm in diameter) filled with water (25±1°C) and made opaque with black nontoxic paint. The trials were conducted once a day for five days. The time for rats to locate the platform was recorded. Each trial lasted either until the rat located the platform for 60 sec, which was recorded as the escape latency (EL) time, and the mean EL time of the last four days as the outcome of learning. The platform was removed for a 60-sec probe trial on the final day, and the time spent swimming in the platform quadrant was recorded as the space exploration time (SET).
## 2.7. Western Blot Analysis
The hippocampus was homogenized in lysis buffer (Sigma, St. Louis, MO, USA)]. After that, the protein was electrophoretically resolved on 10% SDS-polyacrylamide gels and transferred to nitrocellulose membranes. The blots were blocked with skimmed milk and incubated in anti-p-IR (1:1000; Cell Signaling Technology, USA) and anti-p-IRS-1 (1:1000; Cell Signaling Technology, USA) for 4°C overnight respectively. And then secondary HRP antibody was added. Finally, the signals were visualized by use of Enhanced Chemioluminescence kit (ECL, Amersham).
## 2.8. Statistical Analysis
All the data were based on SPSS16.0 and analyzed by one-way analysis of variance (ANOVA). Covariance analysis was utilized in evasive latency in water maze test. A level ofp<0.05 was set as statistically significant.
## 3. Result
### 3.1. CUMS Accelerate Weight Loss in Rat with Diabetes
Rats in normal group kept a healthy weight gain during the whole experiment, while diabetic rats put on a little weight at first 2 weeks and lost weight at last 2 weeks. However, when CUMS was started, the weight loss was the most serious. Starting from 31 days, significant weight loss was observed in both diabetic groups compared with the control group (Figure1,p<0.01). Meanwhile, a serious weight loss was found in diabetes with CUMS rather than diabetic rats (Figure 1,p<0.05 andp<0.01).Figure 1
Body weight. Body weight significantly decreased in both diabetic rats. And there was a significant difference between diabetic rat with CUMS and without CUMS.∗∗p<0.01, control versus diabetic. #p<0.05, diabetic versus diabetic +CUMS. ##p<0.01, diabetic versus diabetic +CUMS.
### 3.2. Disorders of Blood Glucose and Relative Indexes in Diabetic Rats with CUMS
High-fat diet and streptozotocin injection resulted in a diabetic syndrome verified by the presence of hyperglycemia, high levels of hemoglobin A1c concentrations (HbA1c), and peripheral insulin resistance. The concentrations of fasting blood glucose, HbA1c, insulin, and leptin in both of the diabetic groups were significantly higher than the control group (Figures2(c), 2(d), 2(e), and 2(g),p<0.01 orp<0.05). Moreover, glucose tolerance and insulin resistance were impaired in diabetic groups than control group (Figures 2(b) and 2(f),p<0.01). However, there were no significant differences of blood glucose and relative indexes between diabetic group and diabetic + CUMS group except for leptin.Figure 2
Characterization of diabetic rats with CUMS. High-fat diet and streptozotocin injection induces changes in fasting blood glucose levels, HbA1c levels, insulin resistance index, and oral glucose tolerance test. After receiving CUMS, there were no obvious changes in the above indexes of the diabetic rats. (a) Oral glucose tolerance test. (b) Area under curve of the glucose level in oral glucose tolerance test. (c) The level of HbA1c. (d) Fasting blood glucose concentration. (e) Fasting insulin concentration. (f) Insulin resistance index. (g) The level of leptin.∗∗p<0.01, control versus diabetic.
(a) (b) (c) (d) (e) (f) (g)
### 3.3. CUMS Decrease the Performance Status in Diabetic Rat
Depression-like behaviors were assessed in the open-field (OF), forced swim test (FST), and tail suspension test (TST). In the OF, the horizontal activity and vertical activity were observed to evaluate the motion activity and curiosity in an open-field. The result indicates that there was a down-regulation in both diabetic groups when compared with control group. However, the total activity scores of horizon activities and vertical activities were significantly reduced in diabetic + CUMS group instead of diabetic group when compared with control group (Figure3(a),p<0.01). Further, the diabetic rats with CUMS had fewer activity scores when compared with the diabetic group (Figure 3(a),p<0.01). Moreover, in FST, the duration of immobility was obviously increased in diabetic group and diabetic + CUMS group when contrast to control group (Figure 3(b),p<0.01 andp<0.05). And there was a dramatic difference between diabetes group and diabetes + CUMS group (Figure 3(b),p<0.01). Similarly, in TST, the time of immobility was obvious longer in diabetic + CUMS group than it was in control group, and it was much longer than diabetes group as well (Figure 3(b),p<0.01). Nevertheless, in this test, there were no significant differences between diabetic group and control group. Thus, the results demonstrate that depression-like behaviors in diabetic + CUMS group were more obvious than other groups.Figure 3
CUMS induces changes in depressive-like behaviors of diabetic rats. (a) The locomotion in OF. (b) The time of immobility in TST and FST.∗∗p<0.01, control versus diabetic. ##p<0.01, diabetic versus diabetic +CUMS.
(a) (b)
### 3.4. CUMS Leads to a Declined Capability of Learning and Memory in Diabetic Rat
The purpose of Morris water maze is to test the capability of learning and memory by place navigation and space exploration. The evasive latency (EL) was recorded in place navigation. There was a negative relationship between EL and the duration of the training days in all three groups according to regression analysis (Figure4(a)). It appears to be a linear relationship (R2 value 0.9307, 0.9702, and 0.9742) in control group, diabetic group, and diabetic + CUMS group, respectively. EL went down significantly over time when the animals had high learning capacity. Thus, we use the slope of the regression curve to demonstrate the capability of learning. And we found that there is a significant difference between diabetic + CUMS group and control group in learning slope curve according to covariance analysis (p=0.046).Figure 4
CUMS induces declines in cognitive function of diabetic rats. (a) The time of escape latency. (b) The time of space exploration.∗∗p<0.01, control versus diabetic. ##p<0.01, #p<0.05, diabetic versus diabetic +CUMS.
(a) (b)On the 5th day of the test, place exploration was performed. The duration for rats to spend in target area and locate the site (platform) was recorded as space exploration time (SET). The result demonstrates that SET in target area was significantly lower in both diabetic groups when compared with control group (Figure4(b),p<0.01). These data suggest that the capability of learning and memory in diabetic rat were significantly affected by CUMS.
### 3.5. The Abnormal Brain Insulin Signaling Pathway in the Hippocampus of Diabetic Rats with CUMS
The levels of the phosphorylation of IR and Ser phosphorylation of IRS-1 protein were analyzed by a quantitative Western blot procedure in hippocampus (Figure5(a)). The intensities of β-actin bands were taken as an equal load controls and the ratios p-IR: IR and p-IRS-1: IRS-1 were calculated for each lane and the results are expressed as a percentage of p-IR and p-IRS-1 proteins (Figure 5(b),p<0.05). It has been found that both of diabetic rats had lower hippocampal p-IR and higher p-IRS-1 concentration when compared with control group. Diabetic rats subjected to CUMS increased in p-IR and decreased in p-IRS-1 levels in hippocampus compared with diabetic rats.Figure 5
CUMS led to impairment of insulin signaling pathway in hippocampus of diabetic rats. (a) Representative Western blots of IR and IRS-1 proteins. (b) Densitometry measurements.∗p<0.05, control versus diabetic. #p<0.05, diabetic versus diabetic +CUMS.
(a) (b)
## 3.1. CUMS Accelerate Weight Loss in Rat with Diabetes
Rats in normal group kept a healthy weight gain during the whole experiment, while diabetic rats put on a little weight at first 2 weeks and lost weight at last 2 weeks. However, when CUMS was started, the weight loss was the most serious. Starting from 31 days, significant weight loss was observed in both diabetic groups compared with the control group (Figure1,p<0.01). Meanwhile, a serious weight loss was found in diabetes with CUMS rather than diabetic rats (Figure 1,p<0.05 andp<0.01).Figure 1
Body weight. Body weight significantly decreased in both diabetic rats. And there was a significant difference between diabetic rat with CUMS and without CUMS.∗∗p<0.01, control versus diabetic. #p<0.05, diabetic versus diabetic +CUMS. ##p<0.01, diabetic versus diabetic +CUMS.
## 3.2. Disorders of Blood Glucose and Relative Indexes in Diabetic Rats with CUMS
High-fat diet and streptozotocin injection resulted in a diabetic syndrome verified by the presence of hyperglycemia, high levels of hemoglobin A1c concentrations (HbA1c), and peripheral insulin resistance. The concentrations of fasting blood glucose, HbA1c, insulin, and leptin in both of the diabetic groups were significantly higher than the control group (Figures2(c), 2(d), 2(e), and 2(g),p<0.01 orp<0.05). Moreover, glucose tolerance and insulin resistance were impaired in diabetic groups than control group (Figures 2(b) and 2(f),p<0.01). However, there were no significant differences of blood glucose and relative indexes between diabetic group and diabetic + CUMS group except for leptin.Figure 2
Characterization of diabetic rats with CUMS. High-fat diet and streptozotocin injection induces changes in fasting blood glucose levels, HbA1c levels, insulin resistance index, and oral glucose tolerance test. After receiving CUMS, there were no obvious changes in the above indexes of the diabetic rats. (a) Oral glucose tolerance test. (b) Area under curve of the glucose level in oral glucose tolerance test. (c) The level of HbA1c. (d) Fasting blood glucose concentration. (e) Fasting insulin concentration. (f) Insulin resistance index. (g) The level of leptin.∗∗p<0.01, control versus diabetic.
(a) (b) (c) (d) (e) (f) (g)
## 3.3. CUMS Decrease the Performance Status in Diabetic Rat
Depression-like behaviors were assessed in the open-field (OF), forced swim test (FST), and tail suspension test (TST). In the OF, the horizontal activity and vertical activity were observed to evaluate the motion activity and curiosity in an open-field. The result indicates that there was a down-regulation in both diabetic groups when compared with control group. However, the total activity scores of horizon activities and vertical activities were significantly reduced in diabetic + CUMS group instead of diabetic group when compared with control group (Figure3(a),p<0.01). Further, the diabetic rats with CUMS had fewer activity scores when compared with the diabetic group (Figure 3(a),p<0.01). Moreover, in FST, the duration of immobility was obviously increased in diabetic group and diabetic + CUMS group when contrast to control group (Figure 3(b),p<0.01 andp<0.05). And there was a dramatic difference between diabetes group and diabetes + CUMS group (Figure 3(b),p<0.01). Similarly, in TST, the time of immobility was obvious longer in diabetic + CUMS group than it was in control group, and it was much longer than diabetes group as well (Figure 3(b),p<0.01). Nevertheless, in this test, there were no significant differences between diabetic group and control group. Thus, the results demonstrate that depression-like behaviors in diabetic + CUMS group were more obvious than other groups.Figure 3
CUMS induces changes in depressive-like behaviors of diabetic rats. (a) The locomotion in OF. (b) The time of immobility in TST and FST.∗∗p<0.01, control versus diabetic. ##p<0.01, diabetic versus diabetic +CUMS.
(a) (b)
## 3.4. CUMS Leads to a Declined Capability of Learning and Memory in Diabetic Rat
The purpose of Morris water maze is to test the capability of learning and memory by place navigation and space exploration. The evasive latency (EL) was recorded in place navigation. There was a negative relationship between EL and the duration of the training days in all three groups according to regression analysis (Figure4(a)). It appears to be a linear relationship (R2 value 0.9307, 0.9702, and 0.9742) in control group, diabetic group, and diabetic + CUMS group, respectively. EL went down significantly over time when the animals had high learning capacity. Thus, we use the slope of the regression curve to demonstrate the capability of learning. And we found that there is a significant difference between diabetic + CUMS group and control group in learning slope curve according to covariance analysis (p=0.046).Figure 4
CUMS induces declines in cognitive function of diabetic rats. (a) The time of escape latency. (b) The time of space exploration.∗∗p<0.01, control versus diabetic. ##p<0.01, #p<0.05, diabetic versus diabetic +CUMS.
(a) (b)On the 5th day of the test, place exploration was performed. The duration for rats to spend in target area and locate the site (platform) was recorded as space exploration time (SET). The result demonstrates that SET in target area was significantly lower in both diabetic groups when compared with control group (Figure4(b),p<0.01). These data suggest that the capability of learning and memory in diabetic rat were significantly affected by CUMS.
## 3.5. The Abnormal Brain Insulin Signaling Pathway in the Hippocampus of Diabetic Rats with CUMS
The levels of the phosphorylation of IR and Ser phosphorylation of IRS-1 protein were analyzed by a quantitative Western blot procedure in hippocampus (Figure5(a)). The intensities of β-actin bands were taken as an equal load controls and the ratios p-IR: IR and p-IRS-1: IRS-1 were calculated for each lane and the results are expressed as a percentage of p-IR and p-IRS-1 proteins (Figure 5(b),p<0.05). It has been found that both of diabetic rats had lower hippocampal p-IR and higher p-IRS-1 concentration when compared with control group. Diabetic rats subjected to CUMS increased in p-IR and decreased in p-IRS-1 levels in hippocampus compared with diabetic rats.Figure 5
CUMS led to impairment of insulin signaling pathway in hippocampus of diabetic rats. (a) Representative Western blots of IR and IRS-1 proteins. (b) Densitometry measurements.∗p<0.05, control versus diabetic. #p<0.05, diabetic versus diabetic +CUMS.
(a) (b)
## 4. Discussion
Diabetes usually causes a number of complications involving brain function which related to cognitive decline and depression [22]. The effects of diabetes on central nervous system (CNS) were related to the negative impact of behavioral and emotional functions, with pathological mechanism [9, 10, 23]. The behavioral despair performed an increased immobility time in forced swim test in adult db/db mice [23]. However, Dinel and his colleagues reported that an impaired spatial recognition memory was found in db/db mice, rather than depressive-like behaviors [10]. Moreover, Can et al. found that diabetes mellitus (DM) causes depression deterioration, and spontaneous locomotor activities were decreased accompanied with learning parameters impairment [9]. Thus, the results of mood disturbances (depression) in diabetic rats are inconsistent, as well as it was in this study (Figure 3). Clinical evidences suggest that lots of external factors, such as inactivity, poor sleep, diet, and early life stress are associated with both diabetes and depression [24]. Therefore, we can surmise that the above competing results in animal experiments were related to the reason that external factors were not considered. CUMS is a classic method for building an animal model with a core symptom of depression [11]. This approach can provide a chronic mild stress and simulate the stress that patients suffered from. Thus, in this study, the influence of CUMS on the changes of emotional behaviors and memory performances in diabetic rats was investigated, as well as central insulin signaling.Prior to the above problems, it is better for us to understand that whether CUMS could affect the body weight, glucose level, and systemic insulin resistance in diabetic rats. There was a statistically significant weight loss in both of diabetic groups (Figure1). And the increased glucose, HbA1c level, and leptin concentration were found in both of diabetic rat (Figures 2(b), 2(c), and 2(g)), which exhibited impaired glucose tolerance (Figures 2(a) and 2(c)). These results indicate systemic IR with the high HOMA-IR index in two diabetic groups (Figure 2(d)). Leptin is an adipocyte hormone regarded as the afferent signal in a negative feedback loop regulating insulin biosynthesis and secretion [25]. The increased results of the insulin and leptin suggest that the leptin resistant occurred in increased leptin and it caused hyperinsulinemia. And stress could deteriorate the leptin resistant of diabetic rat. Furthermore, there are no significant differences between diabetic and diabetic + CUMS group on the aspect of fasting blood glucose, glucose tolerance, HbA1c, and peripheral insulin resistance (Figure 2). Although previous study shows that an oral glucose tolerance and serum insulin levels in normal control animals were damaged after CUMS was performed [26], we found that there are no remarkable changes in metabolic phenotypes after CUMS performed on diabetic rats in this study. Thus, it is concluded that the effect of outside interfere becomes inconspicuous after the occurrence of diseases such as obesity diabetes with which already accompany disordered endocrine function.It has been previously studied that diabetes mellitus (DM) have negative impacts on the central nervous system [27–30]. Many literatures suggested that the cognitive impairment was closely related to diabetes [31, 32]. We also observed that there are significant changes in learning and memory performance in diabetic rats with CUMS when compared to control group (Figure 4). However, whether depression-like behaviors are associated with diabetes mellitus is not clear. Liu and his coworkers found that db/db mice performed increased anxiety-like behaviors instead of depression-like behaviors [10]. On the contrary, another research group suggests that diabetes mellitus exacerbate the depression levels [9]. Thus, this study reported the depression behaviors and locomotor deficits in diabetic rats and CUMS with diabetes. Our results reveal that diabetes rats exhibited depressive-like behaviors as assessed by immobility time in the forced swim rather than depression in the open-field and tail suspension tests (Figure 3). Based on this study, it suggests that depressive moods and cognitive deficits do not occur at the same time in diabetes. S. Sasaki-Hamada and his colleagues found that synaptic plasticity of hippocampus was affected by the length of diabetes [33]. In addition, neuroplasticity is thought to be closely related to mood disorders [34]. Consistence to the above results, we found that there is a link between the depression-like behaviors and the length of diabetes in diabetic rats. Furthermore, cognitive impairment, especially memory damage, may occur earlier than mood disorder in diabetic rats. More importantly, CUMS could aggravate the emotional and cognitive impairment in diabetic rats, whereas, as stated before, the imbalanced glucose metabolism is hardly deteriorated after CUMS performed in diabetic rats. It concluded that the effect of interfere stress on behavior and cognition is greater than that of blood glucose on behavior and cognition when diabetes was existed. Thus, ignoring the psychological counseling of diabetic patients may accelerate the occurrence of diabetes-related depression.Insulin signaling in brain plays an important role in the development and progression of diabetes mellitus [35], as well as diabetic encephalopathy [16]. This system of the brain is involved in the regulation of neuronal growth and synaptic plasticity and controls metabolic process in the CNS and periphery [36]. Depression symptoms and cognitive functions including spatial memory are associated with brain insulin resistance in type 2 diabetes [37, 38]. Furthermore, the recent researches indicate that chronic stress mediated behavioral dysfunction in normal mice are associated with impaired hippocampal insulin signaling [39]. To further investigate the underlying molecular in diabetes, depression, and stress, CUMS performed on diabetes was utilized to induce IR in peripheral and central organs. Our study researched the activation of insulin signaling in the hippocampus, a key brain area for the control of emotional and cognitive behaviors. Insulin receptor and its major downstream targets, insulin receptor substrate 1 (IRS-1), and IRS-2 are regarded as the core in insulin signaling [40]. The different phosphorylated subtypes of IRS family of protein could activate the different downstream signaling cascade, thereby inducing the physiological function and pathological change. For example, phosphorylation of IRS could activate phosphatidylinositol 3-kinase (PI3K) and phosphoinositide-dependent protein kinase-1 (PDK1) activation, thereby activating the downstream signaling cascade involving Akt [41]. Activation of Akt leads to the phosphorylation of GSK3β, and the Akt/GSK3β pathways are important regulators of depression [42]. In addition, phosphorylated IRS can also regulate the activation of JNK, CHOP (stress), and NF-κB (inflammatory pathways) [43]. Our data demonstrated that phosphorylation of IR was decreased, while serine phosphorylation of IRS-1 was increased in hippocampus in diabetic rats (Figure 5). When CUMS is applied to diabetic animals, the increased p-IPS-1 level and decreased p-IR level were getting severer.In summary, it is difficult to explain the relationship between diabetes and depression. Recent reports demonstrate that shared clinical and pathophysiologic traits between diabetes and depression raise the possibility that stress and pressure play an important role in the pathophysiology of cognitive decline. Data in this study reveal the effects of CUMS aggravated mood disorder, cognitive impairment in diabetic rats. These results are in accordance with the previous studies that people whom lived in a bad situation would be more prone to depression. Moreover, animals with diabetes are more prone to pose negative effects on brain insulin signaling under CUMS condition.
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*Source: 2901863-2018-12-03.xml* | 2018 |
# Recognizing Amino Acid Chirality with Surface-Imprinted Polymers Prepared in W/O Emulsions
**Authors:** Min Jae Shin; Young Jae Shin; Seung Won Hwang; Jae Sup Shin
**Journal:** International Journal of Polymer Science
(2013)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2013/290187
---
## Abstract
A molecularly imprinted polymer was prepared by a surface molecular imprinting technique in water-in-oil (W/O) emulsion. In this technique, the solid polymer, which is molecularly imprinted at the internal cavity surface, is prepared by polymerizing W/O emulsions consisting of a water-soluble imprinted molecule, a functional host molecule, an emulsion stabilizer, and a crosslinking agent. Dioleoyl phosphate was used as an emulsion stabilizer, and this compound also acted as a monomer and a host functional group in the imprinted cavity. Divinylbenzene was used as a crosslinker. Tryptophan methyl ester and phenylalanine methyl ester were used as the target template materials. These imprinted polymers exhibited enantiomeric selectivity in absorption experiments, and the maximum separation factor was 1.58. The enantiomeric selectivity with tryptophan methyl ester was higher than that with phenylalanine methyl ester.
---
## Body
## 1. Introduction
Recently, significant attention has been paid to the development of a molecular imprinting technique that enables polymers to mimic biological receptors. This technique is a very useful approach for the fabrication of a matrix with molecular recognition sites, which are formed by the addition of template molecules during the matrix formation process and the removal of the template molecule after the matrix formation [1–5]. Polymers that were prepared by the molecular imprinting technique have attracted much attention as interesting separation tools, especially for high performance liquid chromatography (HPLC). The imprinting technique is conceptually easy to apply to a wide variety of target molecules. Important applications are optical resolutions of amino acids or amino acid derivatives [6–12], direct enantiomeric separation of drugs [13, 14], and separation of sugar or sugar derivatives [4, 15, 16].The “surface molecular imprinting technique” was proposed to overcome the inapplicability to water-soluble substances, which are important in the biological or biomedical field [17–20]. In this technique, the solid polymer, which is molecularly imprinted at the internal cavity surface, is prepared by polymerizing water-in-oil (W/O) emulsions consisting of a water-soluble imprint molecule, a functional host molecule, an emulsion stabilizer, and a crosslinking agent. The organic-aqueous interface in W/O emulsions is utilized as the recognition field for a target molecule. The target molecule forms a complex with the functional host molecule, while the orientation of the functional host molecule itself is fixed at the oil-water interface. After polymerization, preparation provides the recognition sites at the inner cavity surface of the imprinted bulk polymer. The complex between the functional host molecule and the target material should not be too hydrophobic or hydrophilic, because otherwise the complex would not be located at the oil-water interface. Thus, a functional host molecule should be amphiphilic, just like a surfactant molecule, in order to yield a high template effect for the target molecule. The crosslinking agent crosslinks the organic phase and stabilizes the water pool or the imprinted water cavity after polymerization. The bulk polymer that is obtained is ground to small particles in order to interact with the target molecules in the solution.In this study, we tried to have a host molecule with a crosslinker participate in the polymerization. So dioleoyl phosphoric acid was selected as a host molecule, and the polymerization was conducted with a large amount of benzoyl peroxide at a high temperature to polymerize both the host molecule and divinylbenzene.
## 2. Experimental
### 2.1. Reagents and Instruments
L-Tryptophan methyl ester (L-TRPM), D-tryptophan methyl ester (D-TRPM), divinylbenzene (DVB), L-phenylalanine methyl ester (L-PHEM), D-phenylalanine methyl ester (D-PHEM), benzoyl peroxide (BPO), L-glutamic acid, oleyl alcohol, D-gluconic acidδ-lactone, phosphorus oxychloride, styrene, and xylenes were obtained from Aldrich. Dioleyl phosphoric acid (DOPA) and L-glutamic acid dioleylester ribitol (L-GADR) were synthesized using already reported methods [17, 21–23]. Divinylbenzene was used after treatment with silica gel to remove an inhibitor. Figure 1 shows the chemical structures of TRPM, PHEM, DOPA, and L-GADR.Molecular structures of (a) TRPM, (b) PHEM, (c) DOPA, and (d) L-GADR.
(a)
TRPM
(b)
PHEM
(c)
DOPA
(d)
L-GADRInfrared spectroscopy (IR) was performed using an FT-IR 680 (Jasco International). Sonication was performed using a Cole-Parmer 4710250W sonicator. Scanning electron microscopy (SEM) was performed using both a Hitachi S-2500C and a Hitachi S-5200V scanning electron microscope.
### 2.2. Preparation of L- or D-TRPM-Imprinted Polymers
40.0 g (0.307 mol) of DVB and 1.50 g (2.50 mmol) of DOPA were dissolved in 20 mL of xylenes. Another solution was prepared by dissolving 0.102 g (0.40 mmol) of L- or D-TRPM·HCl in 20 mL of water which contained 0.10 M phosphate buffer solution adjusted to pH 7.0. This buffer solution was added to the xylenes solution. The mixture was sonicated for 5 min to obtain the stable W/O emulsion. Then, 1.60 g (6.61 mmol) of BPO initiator was added to this solution, and then, this solution was sonicated again for 2 min. This mixture was polymerized at 60°C for 30 min, and then, temperature was gradually raised to 140°C, and the reaction was continued at 140°C for 24 h under a flow of nitrogen. The obtained bulk polymer was dried under a vacuum at 50°C for 48 h and ground into particles. The particles were washed with 0.50 M HCl to remove the imprinted L- or D-TRPM and then filtered off. This procedure was repeated several times until the imprinted molecule in the filtrate could not be detected by a UV spectrometer. Finally, the polymer was dried under a vacuum at 50°C for 48 h.
### 2.3. Preparation of L- or D-PHEM-Imprinted Polymers
These imprinted polymers were prepared by the same method as the preparation for the L- or D-TRPM-imprinted polymers using L- or D-PHEM instead of L- or D-TRPM.
### 2.4. Adsorption Experiments Using the Imprinted Polymers
The batchwise adsorption experiments of L,D-TRPM and L,D-PHEM were conducted for the L- or D-TRPM-imprinted polymers and L- or D-TRPM-imprinted polymers, respectively. 0.050 g of the imprinted polymer was added to 5.0 mL of aqueous solution containing 0.50 mM of L- or D-TRPM and placed in a sealed 10 mL tube. The pH was adjusted to a desired value between 3.0 and 8.0 with 0.10 M KH2PO4 or K2HPO4 and 0.10 M HNO3 or 0.10 M NaOH. The mixture was shaken in a thermostated water bath at 30°C for 24 h. The polymers were then filtered off through a polyethylene membrane. The amount of each amino acid derivative adsorbed to the polymers was calculated from their residual amount in the filtrate. The concentration of amino acid derivatives was analyzed by an HPLC system. The adsorption tests were conducted at least 3 times, and the data was analyzed and compared with average values. The experimental errors were less than 6%.
### 2.5. Binding Constant of the Substrate for Imprinted Polymer
Binding constants of the substrate for the imprinted polymer were evaluated with the batchwise method. 0.050 g of the imprinted polymer sample was immersed in a sealed 10 mL tube. Then, a 5 mL of the aqueous solution was added, which was buffered with 0.10 M KH2PO4 or K2HPO4 and 0.10 M HNO3 or 0.10 M NaOH containing a substrate that was adjusted to a desired concentration of between 0.050 M and 1.0 M. The mixture was shaken at 30°C for 24 h. The polymers were then filtered off through the polyethylene membrane. The concentration of the substrate in the filtrate was analyzed by means of the HPLC system. The binding constants were calculated by a modified Scatchard equation [24, 25].
## 2.1. Reagents and Instruments
L-Tryptophan methyl ester (L-TRPM), D-tryptophan methyl ester (D-TRPM), divinylbenzene (DVB), L-phenylalanine methyl ester (L-PHEM), D-phenylalanine methyl ester (D-PHEM), benzoyl peroxide (BPO), L-glutamic acid, oleyl alcohol, D-gluconic acidδ-lactone, phosphorus oxychloride, styrene, and xylenes were obtained from Aldrich. Dioleyl phosphoric acid (DOPA) and L-glutamic acid dioleylester ribitol (L-GADR) were synthesized using already reported methods [17, 21–23]. Divinylbenzene was used after treatment with silica gel to remove an inhibitor. Figure 1 shows the chemical structures of TRPM, PHEM, DOPA, and L-GADR.Molecular structures of (a) TRPM, (b) PHEM, (c) DOPA, and (d) L-GADR.
(a)
TRPM
(b)
PHEM
(c)
DOPA
(d)
L-GADRInfrared spectroscopy (IR) was performed using an FT-IR 680 (Jasco International). Sonication was performed using a Cole-Parmer 4710250W sonicator. Scanning electron microscopy (SEM) was performed using both a Hitachi S-2500C and a Hitachi S-5200V scanning electron microscope.
## 2.2. Preparation of L- or D-TRPM-Imprinted Polymers
40.0 g (0.307 mol) of DVB and 1.50 g (2.50 mmol) of DOPA were dissolved in 20 mL of xylenes. Another solution was prepared by dissolving 0.102 g (0.40 mmol) of L- or D-TRPM·HCl in 20 mL of water which contained 0.10 M phosphate buffer solution adjusted to pH 7.0. This buffer solution was added to the xylenes solution. The mixture was sonicated for 5 min to obtain the stable W/O emulsion. Then, 1.60 g (6.61 mmol) of BPO initiator was added to this solution, and then, this solution was sonicated again for 2 min. This mixture was polymerized at 60°C for 30 min, and then, temperature was gradually raised to 140°C, and the reaction was continued at 140°C for 24 h under a flow of nitrogen. The obtained bulk polymer was dried under a vacuum at 50°C for 48 h and ground into particles. The particles were washed with 0.50 M HCl to remove the imprinted L- or D-TRPM and then filtered off. This procedure was repeated several times until the imprinted molecule in the filtrate could not be detected by a UV spectrometer. Finally, the polymer was dried under a vacuum at 50°C for 48 h.
## 2.3. Preparation of L- or D-PHEM-Imprinted Polymers
These imprinted polymers were prepared by the same method as the preparation for the L- or D-TRPM-imprinted polymers using L- or D-PHEM instead of L- or D-TRPM.
## 2.4. Adsorption Experiments Using the Imprinted Polymers
The batchwise adsorption experiments of L,D-TRPM and L,D-PHEM were conducted for the L- or D-TRPM-imprinted polymers and L- or D-TRPM-imprinted polymers, respectively. 0.050 g of the imprinted polymer was added to 5.0 mL of aqueous solution containing 0.50 mM of L- or D-TRPM and placed in a sealed 10 mL tube. The pH was adjusted to a desired value between 3.0 and 8.0 with 0.10 M KH2PO4 or K2HPO4 and 0.10 M HNO3 or 0.10 M NaOH. The mixture was shaken in a thermostated water bath at 30°C for 24 h. The polymers were then filtered off through a polyethylene membrane. The amount of each amino acid derivative adsorbed to the polymers was calculated from their residual amount in the filtrate. The concentration of amino acid derivatives was analyzed by an HPLC system. The adsorption tests were conducted at least 3 times, and the data was analyzed and compared with average values. The experimental errors were less than 6%.
## 2.5. Binding Constant of the Substrate for Imprinted Polymer
Binding constants of the substrate for the imprinted polymer were evaluated with the batchwise method. 0.050 g of the imprinted polymer sample was immersed in a sealed 10 mL tube. Then, a 5 mL of the aqueous solution was added, which was buffered with 0.10 M KH2PO4 or K2HPO4 and 0.10 M HNO3 or 0.10 M NaOH containing a substrate that was adjusted to a desired concentration of between 0.050 M and 1.0 M. The mixture was shaken at 30°C for 24 h. The polymers were then filtered off through the polyethylene membrane. The concentration of the substrate in the filtrate was analyzed by means of the HPLC system. The binding constants were calculated by a modified Scatchard equation [24, 25].
## 3. Results and Discussion
### 3.1. The Preparation of the Imprinted Polymer
The imprinted polymers were prepared by the surface molecular imprinting technique with W/O emulsions. L- or D-TRPM and L- or D-PHEM were used as the target imprinted molecules, and DOPA was used as both a functional monomer and an emulsion stabilizer. DVB was used as a crosslinker, xylenes were used as a diluent, and BPO was used as an initiator. In order to determine the polymerization conditions, we referred to the result of the radical polymerization for triglyceride oils. Many researchers attempted the radical polymerization of the triglyceride oils with styrene or DVB [26, 27]. Therefore, we used a larger amount of initiator compared to the general polymerization. BPO was used at 2.2 mol % versus the amount of DVB, and this amount is 2.6 times larger than the amount of DOPA. The polymerization was conducted at first at 60°C for 30 min to prevent bumping, and after that the temperature was raised to 140°C gradually, and the polymerization was continued for 24 h under a flow of nitrogen at 140°C. In order to conduct the experiment at 140°C, the xylenes (bp 137–140°C) were used as a diluent.In order to estimate the exact amount of DOPA which participated in the polymerization, we conducted the preliminary experiment for the polymerization of DOPA with styrene or DVB. 31.9 g (0.307 mol) of styrene and 1.50 g (2.50 mmol) of DOPA were dissolved in 20 mL of xylenes, and the polymerization was conducted with 1.60 g (6.61 mmol) of BPO initiator at 140°C for 24 h under a flow of nitrogen. After finishing the polymerization, the remaining unpolymerized amount of DOPA was estimated using HPLC. The result showed that 56% of DOPA remained in the filtrate. This means that 44% of the DOPA was participated in the polymerization. We also tried another preliminary experiment with DVB. Instead of styrene, 40.0 g (0.307 mol) of DVB was used and the same experiment was conducted, and the remaining amount of DOPA was estimated using HPLC. The results showed that 9% of the DOPA remained in the filtrate. This means that 91% of DOPA stayed in the crosslinked polymer. We did not think that all 91% of the DOPA was polymerized with DVB. The IR spectrum of this polymer showed that some amount of double bonds still remained in the polymer. Because only 44% of the DOPA participated in the polymerization with styrene, we presumed that more than 44% of the DOPA participated in the polymerization with DVB. Therefore, we also presumed that some small part of the DOPAs were possible to anchor onto the highly crosslinked polymer.After polymerization, the obtained polymer was dried under vacuum, and this polymer was grounded into small particles. After that, the imprinted molecules in the polymer were extracted with 0.50 M HCl solution. The obtained polymer particles were dried under vacuum. The average size of the particles was about 50 um.Figure2 shows the SEM of the particle surface. Figure 2 shows that a lot of round shape rooms were formed by the W/O emulsions. At the surface of these round shape rooms, numerous imprinted cavities were positioned.Figure 2
SEM photograph of L-TRPM-imprinted polymer.
### 3.2. Adsorption Behavior of the Imprinted Polymers
The adsorption experiment was conducted using the L-TRPM-imprinted polymer. The enantiomeric selectivity of this imprinted polymer was estimated using L-TRPM and D-TRPM as substrates. We conducted the adsorption experiment at pH 3.0, pH 5.0, pH 7.0, and pH 8.0. We quantitatively characterized the template effect in the L- and D-imprinted polymers by evaluating the binding constants. The binding constant (K) can be evaluated on the basis of the slope and intercepted by the modified Scatchard plot. The binding constant becomes an indicator to express an adsorption affinity of recognition sites for the target amino acid derivative. To discuss the enantioselectivity quantitatively, we defined the separation factor as follows: α=KL/KD or α=KD/KL.Table1 shows the results for the adsorption of L-TRPM and D-TRPM on the L-TRPM-imprinted polymer. The results showed that the binding constant increased as the pH increased. The separation factor was 1.02 at pH 3.0. This means that there was not much difference in the binding constant of the L-TRPM with that of the D-TRPM, but the separation factor was 1.58 at pH 7.0. This means that this imprinted polymer had a high enantiomeric selectivity at pH 7.0. At pH 8.0, the separation factor decreased relative to the data at pH 7.0. This result indicates that the interaction of the functional group in the imprinted cavity with the functional group of the substrate became maximized at pH 7.0.Table 1
The adsorption of L-TRPM and D-TRPM on the L-TRPM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-TRPM
1.29× 102
1.02
D-TRPM
1.27× 102
5.0
L-TRPM
1.02 × 103
1.12
D-TRPM
0.91 × 103
7.0
L-TRPM
3.05 × 103
1.58
D-TRPM
1.93 × 103
8.0
L-TRPM
3.48 × 103
1.39
D-TRPM
2.50 × 103Using the D-TRPM-imprinted polymer, almost similar results were obtained compared to the data from the L-TRPM-imprinted polymer. Table2 shows the results for the adsorption of L-TRPM and D-TRPM on the D-TRPM-imprinted polymer. The separation factor was a little lower, but the difference value is within the error range.Table 2
The adsorption of L-TRPM and D-TRPM on the D-TRPM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-TRPM
1.32× 102
1.04
D-TRPM
1.37 × 102
5.0
L-TRPM
0.94 × 103
1.11
D-TRPM
1.04 × 103
7.0
L-TRPM
2.02 × 103
1.49
D-TRPM
3.01 × 103
8.0
L-TRPM
2.55 × 103
1.32
D-TRPM
3.36 × 103The adsorption experiment was conducted using the L-PHEM-imprinted polymer. The enantiomeric selectivity of this imprinted polymer was estimated using L-PHEM and D-PHEM as the substrates. Table3 shows the results for the adsorption of L-PHEM and D-PHEM on the L-PHEM-imprinted polymer, and Table 4 shows the results for the adsorption of L-PHEM and D-PHEM on the D-PHEM-imprinted polymer. The results showed that the trend of the data was almost similar with that of the TRPM-imprinted polymer, but the separation factor was much lower in value compared with that of the TRPM-imprinted polymer. The separation factor of the L-TRPM-imprinted polymer was 1.58 at pH 7.0 but the separation factor of the L-PHEM-imprinted polymer was 1.35. We think that the nitrogen in the tryptophan ring of TRPM participates in an important interaction between the functional group in the imprinted cavity and the functional group in the substrate that is needed for increasing enantiomeric selectivity.Table 3
The adsorption of L-PHEM and D-PHEM on the L-PHEM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-PHEM
1.48× 102
1.04
D-PHEM
1.42 × 102
5.0
L-PHEM
1.72 × 103
1.06
D-PHEM
1.62 × 103
7.0
L-PHEM
3.45 × 103
1.35
D-PHEM
2.56 × 103
8.0
L-PHEM
4.17 × 103
1.18
D-PHEM
3.53 × 103Table 4
The adsorption of L-PHEM and D-PHEM on the D-PHEM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-PHEM
1.39× 102
1.04
D-PHEM
1.45 × 102
5.0
L-PHEM
1.52 × 103
1.08
D-PHEM
1.64 × 103
7.0
L-PHEM
2.64 × 103
1.33
D-PHEM
3.51 × 103
8.0
L-PHEM
3.50 × 103
1.16
D-PHEM
4.06 × 103
### 3.3. Effect of the Chiral Emulsion Stabilizer
The Goto group introduced the surface molecular imprinting technique. They used L-GADR as an emulsion stabilizer [28]. So, we tried to use this chiral compound in our system. 0.207 g (0.251 mmol) of L-GADR was added during the preparation of the imprinted polymer with L-TRPM as a template molecule. The results showed that the separation factor was 1.60 at pH 7.0. We tried the same experiment 3 times. All of the results ((1) 1.63, (2) 1.58, and (3) 1.59) showed that the separation factor was more than 1.58. This means that L-GADR was effective in achieving enantiomeric selectivity, but compared to the result without L-GADR, the separation factor was bigger by a small amount. We also tried to conduct the experiment using 2 times the amount of L-GADR (0.414 g, 0.502 mmol). The results showed that the separation factor was average 1.61 ((1) 1.58, (2) 1.63, and (3) 1.62). This result value shows a little increase, but the value is within the experimental error. So, we concluded that this chiral compound is not very effective for achieving enantiomeric selectivity.
## 3.1. The Preparation of the Imprinted Polymer
The imprinted polymers were prepared by the surface molecular imprinting technique with W/O emulsions. L- or D-TRPM and L- or D-PHEM were used as the target imprinted molecules, and DOPA was used as both a functional monomer and an emulsion stabilizer. DVB was used as a crosslinker, xylenes were used as a diluent, and BPO was used as an initiator. In order to determine the polymerization conditions, we referred to the result of the radical polymerization for triglyceride oils. Many researchers attempted the radical polymerization of the triglyceride oils with styrene or DVB [26, 27]. Therefore, we used a larger amount of initiator compared to the general polymerization. BPO was used at 2.2 mol % versus the amount of DVB, and this amount is 2.6 times larger than the amount of DOPA. The polymerization was conducted at first at 60°C for 30 min to prevent bumping, and after that the temperature was raised to 140°C gradually, and the polymerization was continued for 24 h under a flow of nitrogen at 140°C. In order to conduct the experiment at 140°C, the xylenes (bp 137–140°C) were used as a diluent.In order to estimate the exact amount of DOPA which participated in the polymerization, we conducted the preliminary experiment for the polymerization of DOPA with styrene or DVB. 31.9 g (0.307 mol) of styrene and 1.50 g (2.50 mmol) of DOPA were dissolved in 20 mL of xylenes, and the polymerization was conducted with 1.60 g (6.61 mmol) of BPO initiator at 140°C for 24 h under a flow of nitrogen. After finishing the polymerization, the remaining unpolymerized amount of DOPA was estimated using HPLC. The result showed that 56% of DOPA remained in the filtrate. This means that 44% of the DOPA was participated in the polymerization. We also tried another preliminary experiment with DVB. Instead of styrene, 40.0 g (0.307 mol) of DVB was used and the same experiment was conducted, and the remaining amount of DOPA was estimated using HPLC. The results showed that 9% of the DOPA remained in the filtrate. This means that 91% of DOPA stayed in the crosslinked polymer. We did not think that all 91% of the DOPA was polymerized with DVB. The IR spectrum of this polymer showed that some amount of double bonds still remained in the polymer. Because only 44% of the DOPA participated in the polymerization with styrene, we presumed that more than 44% of the DOPA participated in the polymerization with DVB. Therefore, we also presumed that some small part of the DOPAs were possible to anchor onto the highly crosslinked polymer.After polymerization, the obtained polymer was dried under vacuum, and this polymer was grounded into small particles. After that, the imprinted molecules in the polymer were extracted with 0.50 M HCl solution. The obtained polymer particles were dried under vacuum. The average size of the particles was about 50 um.Figure2 shows the SEM of the particle surface. Figure 2 shows that a lot of round shape rooms were formed by the W/O emulsions. At the surface of these round shape rooms, numerous imprinted cavities were positioned.Figure 2
SEM photograph of L-TRPM-imprinted polymer.
## 3.2. Adsorption Behavior of the Imprinted Polymers
The adsorption experiment was conducted using the L-TRPM-imprinted polymer. The enantiomeric selectivity of this imprinted polymer was estimated using L-TRPM and D-TRPM as substrates. We conducted the adsorption experiment at pH 3.0, pH 5.0, pH 7.0, and pH 8.0. We quantitatively characterized the template effect in the L- and D-imprinted polymers by evaluating the binding constants. The binding constant (K) can be evaluated on the basis of the slope and intercepted by the modified Scatchard plot. The binding constant becomes an indicator to express an adsorption affinity of recognition sites for the target amino acid derivative. To discuss the enantioselectivity quantitatively, we defined the separation factor as follows: α=KL/KD or α=KD/KL.Table1 shows the results for the adsorption of L-TRPM and D-TRPM on the L-TRPM-imprinted polymer. The results showed that the binding constant increased as the pH increased. The separation factor was 1.02 at pH 3.0. This means that there was not much difference in the binding constant of the L-TRPM with that of the D-TRPM, but the separation factor was 1.58 at pH 7.0. This means that this imprinted polymer had a high enantiomeric selectivity at pH 7.0. At pH 8.0, the separation factor decreased relative to the data at pH 7.0. This result indicates that the interaction of the functional group in the imprinted cavity with the functional group of the substrate became maximized at pH 7.0.Table 1
The adsorption of L-TRPM and D-TRPM on the L-TRPM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-TRPM
1.29× 102
1.02
D-TRPM
1.27× 102
5.0
L-TRPM
1.02 × 103
1.12
D-TRPM
0.91 × 103
7.0
L-TRPM
3.05 × 103
1.58
D-TRPM
1.93 × 103
8.0
L-TRPM
3.48 × 103
1.39
D-TRPM
2.50 × 103Using the D-TRPM-imprinted polymer, almost similar results were obtained compared to the data from the L-TRPM-imprinted polymer. Table2 shows the results for the adsorption of L-TRPM and D-TRPM on the D-TRPM-imprinted polymer. The separation factor was a little lower, but the difference value is within the error range.Table 2
The adsorption of L-TRPM and D-TRPM on the D-TRPM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-TRPM
1.32× 102
1.04
D-TRPM
1.37 × 102
5.0
L-TRPM
0.94 × 103
1.11
D-TRPM
1.04 × 103
7.0
L-TRPM
2.02 × 103
1.49
D-TRPM
3.01 × 103
8.0
L-TRPM
2.55 × 103
1.32
D-TRPM
3.36 × 103The adsorption experiment was conducted using the L-PHEM-imprinted polymer. The enantiomeric selectivity of this imprinted polymer was estimated using L-PHEM and D-PHEM as the substrates. Table3 shows the results for the adsorption of L-PHEM and D-PHEM on the L-PHEM-imprinted polymer, and Table 4 shows the results for the adsorption of L-PHEM and D-PHEM on the D-PHEM-imprinted polymer. The results showed that the trend of the data was almost similar with that of the TRPM-imprinted polymer, but the separation factor was much lower in value compared with that of the TRPM-imprinted polymer. The separation factor of the L-TRPM-imprinted polymer was 1.58 at pH 7.0 but the separation factor of the L-PHEM-imprinted polymer was 1.35. We think that the nitrogen in the tryptophan ring of TRPM participates in an important interaction between the functional group in the imprinted cavity and the functional group in the substrate that is needed for increasing enantiomeric selectivity.Table 3
The adsorption of L-PHEM and D-PHEM on the L-PHEM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-PHEM
1.48× 102
1.04
D-PHEM
1.42 × 102
5.0
L-PHEM
1.72 × 103
1.06
D-PHEM
1.62 × 103
7.0
L-PHEM
3.45 × 103
1.35
D-PHEM
2.56 × 103
8.0
L-PHEM
4.17 × 103
1.18
D-PHEM
3.53 × 103Table 4
The adsorption of L-PHEM and D-PHEM on the D-PHEM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-PHEM
1.39× 102
1.04
D-PHEM
1.45 × 102
5.0
L-PHEM
1.52 × 103
1.08
D-PHEM
1.64 × 103
7.0
L-PHEM
2.64 × 103
1.33
D-PHEM
3.51 × 103
8.0
L-PHEM
3.50 × 103
1.16
D-PHEM
4.06 × 103
## 3.3. Effect of the Chiral Emulsion Stabilizer
The Goto group introduced the surface molecular imprinting technique. They used L-GADR as an emulsion stabilizer [28]. So, we tried to use this chiral compound in our system. 0.207 g (0.251 mmol) of L-GADR was added during the preparation of the imprinted polymer with L-TRPM as a template molecule. The results showed that the separation factor was 1.60 at pH 7.0. We tried the same experiment 3 times. All of the results ((1) 1.63, (2) 1.58, and (3) 1.59) showed that the separation factor was more than 1.58. This means that L-GADR was effective in achieving enantiomeric selectivity, but compared to the result without L-GADR, the separation factor was bigger by a small amount. We also tried to conduct the experiment using 2 times the amount of L-GADR (0.414 g, 0.502 mmol). The results showed that the separation factor was average 1.61 ((1) 1.58, (2) 1.63, and (3) 1.62). This result value shows a little increase, but the value is within the experimental error. So, we concluded that this chiral compound is not very effective for achieving enantiomeric selectivity.
## 4. Conclusion
Amino acid-imprinted polymers were prepared by a surface imprinting technique in a W/O emulsion. DOPA was used as the emulsion stabilizer and the material for the host functional group in the imprinted cavity. DVB was used as a crosslinker. TRPM and PHEM were used as the imprinted materials and the substrate materials. The absorption experiments were conducted using these imprinted polymers with enantiomeric substrate materials. These polymers exhibited high enantiomeric selectivity for TRPM and PHEM. The separation factor of the TRPM-imprinted polymer was much higher than that of the PHEM-imprinted polymer.
---
*Source: 290187-2013-05-22.xml* | 290187-2013-05-22_290187-2013-05-22.md | 30,192 | Recognizing Amino Acid Chirality with Surface-Imprinted Polymers Prepared in W/O Emulsions | Min Jae Shin; Young Jae Shin; Seung Won Hwang; Jae Sup Shin | International Journal of Polymer Science
(2013) | Chemistry and Chemical Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2013/290187 | 290187-2013-05-22.xml | ---
## Abstract
A molecularly imprinted polymer was prepared by a surface molecular imprinting technique in water-in-oil (W/O) emulsion. In this technique, the solid polymer, which is molecularly imprinted at the internal cavity surface, is prepared by polymerizing W/O emulsions consisting of a water-soluble imprinted molecule, a functional host molecule, an emulsion stabilizer, and a crosslinking agent. Dioleoyl phosphate was used as an emulsion stabilizer, and this compound also acted as a monomer and a host functional group in the imprinted cavity. Divinylbenzene was used as a crosslinker. Tryptophan methyl ester and phenylalanine methyl ester were used as the target template materials. These imprinted polymers exhibited enantiomeric selectivity in absorption experiments, and the maximum separation factor was 1.58. The enantiomeric selectivity with tryptophan methyl ester was higher than that with phenylalanine methyl ester.
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## Body
## 1. Introduction
Recently, significant attention has been paid to the development of a molecular imprinting technique that enables polymers to mimic biological receptors. This technique is a very useful approach for the fabrication of a matrix with molecular recognition sites, which are formed by the addition of template molecules during the matrix formation process and the removal of the template molecule after the matrix formation [1–5]. Polymers that were prepared by the molecular imprinting technique have attracted much attention as interesting separation tools, especially for high performance liquid chromatography (HPLC). The imprinting technique is conceptually easy to apply to a wide variety of target molecules. Important applications are optical resolutions of amino acids or amino acid derivatives [6–12], direct enantiomeric separation of drugs [13, 14], and separation of sugar or sugar derivatives [4, 15, 16].The “surface molecular imprinting technique” was proposed to overcome the inapplicability to water-soluble substances, which are important in the biological or biomedical field [17–20]. In this technique, the solid polymer, which is molecularly imprinted at the internal cavity surface, is prepared by polymerizing water-in-oil (W/O) emulsions consisting of a water-soluble imprint molecule, a functional host molecule, an emulsion stabilizer, and a crosslinking agent. The organic-aqueous interface in W/O emulsions is utilized as the recognition field for a target molecule. The target molecule forms a complex with the functional host molecule, while the orientation of the functional host molecule itself is fixed at the oil-water interface. After polymerization, preparation provides the recognition sites at the inner cavity surface of the imprinted bulk polymer. The complex between the functional host molecule and the target material should not be too hydrophobic or hydrophilic, because otherwise the complex would not be located at the oil-water interface. Thus, a functional host molecule should be amphiphilic, just like a surfactant molecule, in order to yield a high template effect for the target molecule. The crosslinking agent crosslinks the organic phase and stabilizes the water pool or the imprinted water cavity after polymerization. The bulk polymer that is obtained is ground to small particles in order to interact with the target molecules in the solution.In this study, we tried to have a host molecule with a crosslinker participate in the polymerization. So dioleoyl phosphoric acid was selected as a host molecule, and the polymerization was conducted with a large amount of benzoyl peroxide at a high temperature to polymerize both the host molecule and divinylbenzene.
## 2. Experimental
### 2.1. Reagents and Instruments
L-Tryptophan methyl ester (L-TRPM), D-tryptophan methyl ester (D-TRPM), divinylbenzene (DVB), L-phenylalanine methyl ester (L-PHEM), D-phenylalanine methyl ester (D-PHEM), benzoyl peroxide (BPO), L-glutamic acid, oleyl alcohol, D-gluconic acidδ-lactone, phosphorus oxychloride, styrene, and xylenes were obtained from Aldrich. Dioleyl phosphoric acid (DOPA) and L-glutamic acid dioleylester ribitol (L-GADR) were synthesized using already reported methods [17, 21–23]. Divinylbenzene was used after treatment with silica gel to remove an inhibitor. Figure 1 shows the chemical structures of TRPM, PHEM, DOPA, and L-GADR.Molecular structures of (a) TRPM, (b) PHEM, (c) DOPA, and (d) L-GADR.
(a)
TRPM
(b)
PHEM
(c)
DOPA
(d)
L-GADRInfrared spectroscopy (IR) was performed using an FT-IR 680 (Jasco International). Sonication was performed using a Cole-Parmer 4710250W sonicator. Scanning electron microscopy (SEM) was performed using both a Hitachi S-2500C and a Hitachi S-5200V scanning electron microscope.
### 2.2. Preparation of L- or D-TRPM-Imprinted Polymers
40.0 g (0.307 mol) of DVB and 1.50 g (2.50 mmol) of DOPA were dissolved in 20 mL of xylenes. Another solution was prepared by dissolving 0.102 g (0.40 mmol) of L- or D-TRPM·HCl in 20 mL of water which contained 0.10 M phosphate buffer solution adjusted to pH 7.0. This buffer solution was added to the xylenes solution. The mixture was sonicated for 5 min to obtain the stable W/O emulsion. Then, 1.60 g (6.61 mmol) of BPO initiator was added to this solution, and then, this solution was sonicated again for 2 min. This mixture was polymerized at 60°C for 30 min, and then, temperature was gradually raised to 140°C, and the reaction was continued at 140°C for 24 h under a flow of nitrogen. The obtained bulk polymer was dried under a vacuum at 50°C for 48 h and ground into particles. The particles were washed with 0.50 M HCl to remove the imprinted L- or D-TRPM and then filtered off. This procedure was repeated several times until the imprinted molecule in the filtrate could not be detected by a UV spectrometer. Finally, the polymer was dried under a vacuum at 50°C for 48 h.
### 2.3. Preparation of L- or D-PHEM-Imprinted Polymers
These imprinted polymers were prepared by the same method as the preparation for the L- or D-TRPM-imprinted polymers using L- or D-PHEM instead of L- or D-TRPM.
### 2.4. Adsorption Experiments Using the Imprinted Polymers
The batchwise adsorption experiments of L,D-TRPM and L,D-PHEM were conducted for the L- or D-TRPM-imprinted polymers and L- or D-TRPM-imprinted polymers, respectively. 0.050 g of the imprinted polymer was added to 5.0 mL of aqueous solution containing 0.50 mM of L- or D-TRPM and placed in a sealed 10 mL tube. The pH was adjusted to a desired value between 3.0 and 8.0 with 0.10 M KH2PO4 or K2HPO4 and 0.10 M HNO3 or 0.10 M NaOH. The mixture was shaken in a thermostated water bath at 30°C for 24 h. The polymers were then filtered off through a polyethylene membrane. The amount of each amino acid derivative adsorbed to the polymers was calculated from their residual amount in the filtrate. The concentration of amino acid derivatives was analyzed by an HPLC system. The adsorption tests were conducted at least 3 times, and the data was analyzed and compared with average values. The experimental errors were less than 6%.
### 2.5. Binding Constant of the Substrate for Imprinted Polymer
Binding constants of the substrate for the imprinted polymer were evaluated with the batchwise method. 0.050 g of the imprinted polymer sample was immersed in a sealed 10 mL tube. Then, a 5 mL of the aqueous solution was added, which was buffered with 0.10 M KH2PO4 or K2HPO4 and 0.10 M HNO3 or 0.10 M NaOH containing a substrate that was adjusted to a desired concentration of between 0.050 M and 1.0 M. The mixture was shaken at 30°C for 24 h. The polymers were then filtered off through the polyethylene membrane. The concentration of the substrate in the filtrate was analyzed by means of the HPLC system. The binding constants were calculated by a modified Scatchard equation [24, 25].
## 2.1. Reagents and Instruments
L-Tryptophan methyl ester (L-TRPM), D-tryptophan methyl ester (D-TRPM), divinylbenzene (DVB), L-phenylalanine methyl ester (L-PHEM), D-phenylalanine methyl ester (D-PHEM), benzoyl peroxide (BPO), L-glutamic acid, oleyl alcohol, D-gluconic acidδ-lactone, phosphorus oxychloride, styrene, and xylenes were obtained from Aldrich. Dioleyl phosphoric acid (DOPA) and L-glutamic acid dioleylester ribitol (L-GADR) were synthesized using already reported methods [17, 21–23]. Divinylbenzene was used after treatment with silica gel to remove an inhibitor. Figure 1 shows the chemical structures of TRPM, PHEM, DOPA, and L-GADR.Molecular structures of (a) TRPM, (b) PHEM, (c) DOPA, and (d) L-GADR.
(a)
TRPM
(b)
PHEM
(c)
DOPA
(d)
L-GADRInfrared spectroscopy (IR) was performed using an FT-IR 680 (Jasco International). Sonication was performed using a Cole-Parmer 4710250W sonicator. Scanning electron microscopy (SEM) was performed using both a Hitachi S-2500C and a Hitachi S-5200V scanning electron microscope.
## 2.2. Preparation of L- or D-TRPM-Imprinted Polymers
40.0 g (0.307 mol) of DVB and 1.50 g (2.50 mmol) of DOPA were dissolved in 20 mL of xylenes. Another solution was prepared by dissolving 0.102 g (0.40 mmol) of L- or D-TRPM·HCl in 20 mL of water which contained 0.10 M phosphate buffer solution adjusted to pH 7.0. This buffer solution was added to the xylenes solution. The mixture was sonicated for 5 min to obtain the stable W/O emulsion. Then, 1.60 g (6.61 mmol) of BPO initiator was added to this solution, and then, this solution was sonicated again for 2 min. This mixture was polymerized at 60°C for 30 min, and then, temperature was gradually raised to 140°C, and the reaction was continued at 140°C for 24 h under a flow of nitrogen. The obtained bulk polymer was dried under a vacuum at 50°C for 48 h and ground into particles. The particles were washed with 0.50 M HCl to remove the imprinted L- or D-TRPM and then filtered off. This procedure was repeated several times until the imprinted molecule in the filtrate could not be detected by a UV spectrometer. Finally, the polymer was dried under a vacuum at 50°C for 48 h.
## 2.3. Preparation of L- or D-PHEM-Imprinted Polymers
These imprinted polymers were prepared by the same method as the preparation for the L- or D-TRPM-imprinted polymers using L- or D-PHEM instead of L- or D-TRPM.
## 2.4. Adsorption Experiments Using the Imprinted Polymers
The batchwise adsorption experiments of L,D-TRPM and L,D-PHEM were conducted for the L- or D-TRPM-imprinted polymers and L- or D-TRPM-imprinted polymers, respectively. 0.050 g of the imprinted polymer was added to 5.0 mL of aqueous solution containing 0.50 mM of L- or D-TRPM and placed in a sealed 10 mL tube. The pH was adjusted to a desired value between 3.0 and 8.0 with 0.10 M KH2PO4 or K2HPO4 and 0.10 M HNO3 or 0.10 M NaOH. The mixture was shaken in a thermostated water bath at 30°C for 24 h. The polymers were then filtered off through a polyethylene membrane. The amount of each amino acid derivative adsorbed to the polymers was calculated from their residual amount in the filtrate. The concentration of amino acid derivatives was analyzed by an HPLC system. The adsorption tests were conducted at least 3 times, and the data was analyzed and compared with average values. The experimental errors were less than 6%.
## 2.5. Binding Constant of the Substrate for Imprinted Polymer
Binding constants of the substrate for the imprinted polymer were evaluated with the batchwise method. 0.050 g of the imprinted polymer sample was immersed in a sealed 10 mL tube. Then, a 5 mL of the aqueous solution was added, which was buffered with 0.10 M KH2PO4 or K2HPO4 and 0.10 M HNO3 or 0.10 M NaOH containing a substrate that was adjusted to a desired concentration of between 0.050 M and 1.0 M. The mixture was shaken at 30°C for 24 h. The polymers were then filtered off through the polyethylene membrane. The concentration of the substrate in the filtrate was analyzed by means of the HPLC system. The binding constants were calculated by a modified Scatchard equation [24, 25].
## 3. Results and Discussion
### 3.1. The Preparation of the Imprinted Polymer
The imprinted polymers were prepared by the surface molecular imprinting technique with W/O emulsions. L- or D-TRPM and L- or D-PHEM were used as the target imprinted molecules, and DOPA was used as both a functional monomer and an emulsion stabilizer. DVB was used as a crosslinker, xylenes were used as a diluent, and BPO was used as an initiator. In order to determine the polymerization conditions, we referred to the result of the radical polymerization for triglyceride oils. Many researchers attempted the radical polymerization of the triglyceride oils with styrene or DVB [26, 27]. Therefore, we used a larger amount of initiator compared to the general polymerization. BPO was used at 2.2 mol % versus the amount of DVB, and this amount is 2.6 times larger than the amount of DOPA. The polymerization was conducted at first at 60°C for 30 min to prevent bumping, and after that the temperature was raised to 140°C gradually, and the polymerization was continued for 24 h under a flow of nitrogen at 140°C. In order to conduct the experiment at 140°C, the xylenes (bp 137–140°C) were used as a diluent.In order to estimate the exact amount of DOPA which participated in the polymerization, we conducted the preliminary experiment for the polymerization of DOPA with styrene or DVB. 31.9 g (0.307 mol) of styrene and 1.50 g (2.50 mmol) of DOPA were dissolved in 20 mL of xylenes, and the polymerization was conducted with 1.60 g (6.61 mmol) of BPO initiator at 140°C for 24 h under a flow of nitrogen. After finishing the polymerization, the remaining unpolymerized amount of DOPA was estimated using HPLC. The result showed that 56% of DOPA remained in the filtrate. This means that 44% of the DOPA was participated in the polymerization. We also tried another preliminary experiment with DVB. Instead of styrene, 40.0 g (0.307 mol) of DVB was used and the same experiment was conducted, and the remaining amount of DOPA was estimated using HPLC. The results showed that 9% of the DOPA remained in the filtrate. This means that 91% of DOPA stayed in the crosslinked polymer. We did not think that all 91% of the DOPA was polymerized with DVB. The IR spectrum of this polymer showed that some amount of double bonds still remained in the polymer. Because only 44% of the DOPA participated in the polymerization with styrene, we presumed that more than 44% of the DOPA participated in the polymerization with DVB. Therefore, we also presumed that some small part of the DOPAs were possible to anchor onto the highly crosslinked polymer.After polymerization, the obtained polymer was dried under vacuum, and this polymer was grounded into small particles. After that, the imprinted molecules in the polymer were extracted with 0.50 M HCl solution. The obtained polymer particles were dried under vacuum. The average size of the particles was about 50 um.Figure2 shows the SEM of the particle surface. Figure 2 shows that a lot of round shape rooms were formed by the W/O emulsions. At the surface of these round shape rooms, numerous imprinted cavities were positioned.Figure 2
SEM photograph of L-TRPM-imprinted polymer.
### 3.2. Adsorption Behavior of the Imprinted Polymers
The adsorption experiment was conducted using the L-TRPM-imprinted polymer. The enantiomeric selectivity of this imprinted polymer was estimated using L-TRPM and D-TRPM as substrates. We conducted the adsorption experiment at pH 3.0, pH 5.0, pH 7.0, and pH 8.0. We quantitatively characterized the template effect in the L- and D-imprinted polymers by evaluating the binding constants. The binding constant (K) can be evaluated on the basis of the slope and intercepted by the modified Scatchard plot. The binding constant becomes an indicator to express an adsorption affinity of recognition sites for the target amino acid derivative. To discuss the enantioselectivity quantitatively, we defined the separation factor as follows: α=KL/KD or α=KD/KL.Table1 shows the results for the adsorption of L-TRPM and D-TRPM on the L-TRPM-imprinted polymer. The results showed that the binding constant increased as the pH increased. The separation factor was 1.02 at pH 3.0. This means that there was not much difference in the binding constant of the L-TRPM with that of the D-TRPM, but the separation factor was 1.58 at pH 7.0. This means that this imprinted polymer had a high enantiomeric selectivity at pH 7.0. At pH 8.0, the separation factor decreased relative to the data at pH 7.0. This result indicates that the interaction of the functional group in the imprinted cavity with the functional group of the substrate became maximized at pH 7.0.Table 1
The adsorption of L-TRPM and D-TRPM on the L-TRPM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-TRPM
1.29× 102
1.02
D-TRPM
1.27× 102
5.0
L-TRPM
1.02 × 103
1.12
D-TRPM
0.91 × 103
7.0
L-TRPM
3.05 × 103
1.58
D-TRPM
1.93 × 103
8.0
L-TRPM
3.48 × 103
1.39
D-TRPM
2.50 × 103Using the D-TRPM-imprinted polymer, almost similar results were obtained compared to the data from the L-TRPM-imprinted polymer. Table2 shows the results for the adsorption of L-TRPM and D-TRPM on the D-TRPM-imprinted polymer. The separation factor was a little lower, but the difference value is within the error range.Table 2
The adsorption of L-TRPM and D-TRPM on the D-TRPM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-TRPM
1.32× 102
1.04
D-TRPM
1.37 × 102
5.0
L-TRPM
0.94 × 103
1.11
D-TRPM
1.04 × 103
7.0
L-TRPM
2.02 × 103
1.49
D-TRPM
3.01 × 103
8.0
L-TRPM
2.55 × 103
1.32
D-TRPM
3.36 × 103The adsorption experiment was conducted using the L-PHEM-imprinted polymer. The enantiomeric selectivity of this imprinted polymer was estimated using L-PHEM and D-PHEM as the substrates. Table3 shows the results for the adsorption of L-PHEM and D-PHEM on the L-PHEM-imprinted polymer, and Table 4 shows the results for the adsorption of L-PHEM and D-PHEM on the D-PHEM-imprinted polymer. The results showed that the trend of the data was almost similar with that of the TRPM-imprinted polymer, but the separation factor was much lower in value compared with that of the TRPM-imprinted polymer. The separation factor of the L-TRPM-imprinted polymer was 1.58 at pH 7.0 but the separation factor of the L-PHEM-imprinted polymer was 1.35. We think that the nitrogen in the tryptophan ring of TRPM participates in an important interaction between the functional group in the imprinted cavity and the functional group in the substrate that is needed for increasing enantiomeric selectivity.Table 3
The adsorption of L-PHEM and D-PHEM on the L-PHEM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-PHEM
1.48× 102
1.04
D-PHEM
1.42 × 102
5.0
L-PHEM
1.72 × 103
1.06
D-PHEM
1.62 × 103
7.0
L-PHEM
3.45 × 103
1.35
D-PHEM
2.56 × 103
8.0
L-PHEM
4.17 × 103
1.18
D-PHEM
3.53 × 103Table 4
The adsorption of L-PHEM and D-PHEM on the D-PHEM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-PHEM
1.39× 102
1.04
D-PHEM
1.45 × 102
5.0
L-PHEM
1.52 × 103
1.08
D-PHEM
1.64 × 103
7.0
L-PHEM
2.64 × 103
1.33
D-PHEM
3.51 × 103
8.0
L-PHEM
3.50 × 103
1.16
D-PHEM
4.06 × 103
### 3.3. Effect of the Chiral Emulsion Stabilizer
The Goto group introduced the surface molecular imprinting technique. They used L-GADR as an emulsion stabilizer [28]. So, we tried to use this chiral compound in our system. 0.207 g (0.251 mmol) of L-GADR was added during the preparation of the imprinted polymer with L-TRPM as a template molecule. The results showed that the separation factor was 1.60 at pH 7.0. We tried the same experiment 3 times. All of the results ((1) 1.63, (2) 1.58, and (3) 1.59) showed that the separation factor was more than 1.58. This means that L-GADR was effective in achieving enantiomeric selectivity, but compared to the result without L-GADR, the separation factor was bigger by a small amount. We also tried to conduct the experiment using 2 times the amount of L-GADR (0.414 g, 0.502 mmol). The results showed that the separation factor was average 1.61 ((1) 1.58, (2) 1.63, and (3) 1.62). This result value shows a little increase, but the value is within the experimental error. So, we concluded that this chiral compound is not very effective for achieving enantiomeric selectivity.
## 3.1. The Preparation of the Imprinted Polymer
The imprinted polymers were prepared by the surface molecular imprinting technique with W/O emulsions. L- or D-TRPM and L- or D-PHEM were used as the target imprinted molecules, and DOPA was used as both a functional monomer and an emulsion stabilizer. DVB was used as a crosslinker, xylenes were used as a diluent, and BPO was used as an initiator. In order to determine the polymerization conditions, we referred to the result of the radical polymerization for triglyceride oils. Many researchers attempted the radical polymerization of the triglyceride oils with styrene or DVB [26, 27]. Therefore, we used a larger amount of initiator compared to the general polymerization. BPO was used at 2.2 mol % versus the amount of DVB, and this amount is 2.6 times larger than the amount of DOPA. The polymerization was conducted at first at 60°C for 30 min to prevent bumping, and after that the temperature was raised to 140°C gradually, and the polymerization was continued for 24 h under a flow of nitrogen at 140°C. In order to conduct the experiment at 140°C, the xylenes (bp 137–140°C) were used as a diluent.In order to estimate the exact amount of DOPA which participated in the polymerization, we conducted the preliminary experiment for the polymerization of DOPA with styrene or DVB. 31.9 g (0.307 mol) of styrene and 1.50 g (2.50 mmol) of DOPA were dissolved in 20 mL of xylenes, and the polymerization was conducted with 1.60 g (6.61 mmol) of BPO initiator at 140°C for 24 h under a flow of nitrogen. After finishing the polymerization, the remaining unpolymerized amount of DOPA was estimated using HPLC. The result showed that 56% of DOPA remained in the filtrate. This means that 44% of the DOPA was participated in the polymerization. We also tried another preliminary experiment with DVB. Instead of styrene, 40.0 g (0.307 mol) of DVB was used and the same experiment was conducted, and the remaining amount of DOPA was estimated using HPLC. The results showed that 9% of the DOPA remained in the filtrate. This means that 91% of DOPA stayed in the crosslinked polymer. We did not think that all 91% of the DOPA was polymerized with DVB. The IR spectrum of this polymer showed that some amount of double bonds still remained in the polymer. Because only 44% of the DOPA participated in the polymerization with styrene, we presumed that more than 44% of the DOPA participated in the polymerization with DVB. Therefore, we also presumed that some small part of the DOPAs were possible to anchor onto the highly crosslinked polymer.After polymerization, the obtained polymer was dried under vacuum, and this polymer was grounded into small particles. After that, the imprinted molecules in the polymer were extracted with 0.50 M HCl solution. The obtained polymer particles were dried under vacuum. The average size of the particles was about 50 um.Figure2 shows the SEM of the particle surface. Figure 2 shows that a lot of round shape rooms were formed by the W/O emulsions. At the surface of these round shape rooms, numerous imprinted cavities were positioned.Figure 2
SEM photograph of L-TRPM-imprinted polymer.
## 3.2. Adsorption Behavior of the Imprinted Polymers
The adsorption experiment was conducted using the L-TRPM-imprinted polymer. The enantiomeric selectivity of this imprinted polymer was estimated using L-TRPM and D-TRPM as substrates. We conducted the adsorption experiment at pH 3.0, pH 5.0, pH 7.0, and pH 8.0. We quantitatively characterized the template effect in the L- and D-imprinted polymers by evaluating the binding constants. The binding constant (K) can be evaluated on the basis of the slope and intercepted by the modified Scatchard plot. The binding constant becomes an indicator to express an adsorption affinity of recognition sites for the target amino acid derivative. To discuss the enantioselectivity quantitatively, we defined the separation factor as follows: α=KL/KD or α=KD/KL.Table1 shows the results for the adsorption of L-TRPM and D-TRPM on the L-TRPM-imprinted polymer. The results showed that the binding constant increased as the pH increased. The separation factor was 1.02 at pH 3.0. This means that there was not much difference in the binding constant of the L-TRPM with that of the D-TRPM, but the separation factor was 1.58 at pH 7.0. This means that this imprinted polymer had a high enantiomeric selectivity at pH 7.0. At pH 8.0, the separation factor decreased relative to the data at pH 7.0. This result indicates that the interaction of the functional group in the imprinted cavity with the functional group of the substrate became maximized at pH 7.0.Table 1
The adsorption of L-TRPM and D-TRPM on the L-TRPM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-TRPM
1.29× 102
1.02
D-TRPM
1.27× 102
5.0
L-TRPM
1.02 × 103
1.12
D-TRPM
0.91 × 103
7.0
L-TRPM
3.05 × 103
1.58
D-TRPM
1.93 × 103
8.0
L-TRPM
3.48 × 103
1.39
D-TRPM
2.50 × 103Using the D-TRPM-imprinted polymer, almost similar results were obtained compared to the data from the L-TRPM-imprinted polymer. Table2 shows the results for the adsorption of L-TRPM and D-TRPM on the D-TRPM-imprinted polymer. The separation factor was a little lower, but the difference value is within the error range.Table 2
The adsorption of L-TRPM and D-TRPM on the D-TRPM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-TRPM
1.32× 102
1.04
D-TRPM
1.37 × 102
5.0
L-TRPM
0.94 × 103
1.11
D-TRPM
1.04 × 103
7.0
L-TRPM
2.02 × 103
1.49
D-TRPM
3.01 × 103
8.0
L-TRPM
2.55 × 103
1.32
D-TRPM
3.36 × 103The adsorption experiment was conducted using the L-PHEM-imprinted polymer. The enantiomeric selectivity of this imprinted polymer was estimated using L-PHEM and D-PHEM as the substrates. Table3 shows the results for the adsorption of L-PHEM and D-PHEM on the L-PHEM-imprinted polymer, and Table 4 shows the results for the adsorption of L-PHEM and D-PHEM on the D-PHEM-imprinted polymer. The results showed that the trend of the data was almost similar with that of the TRPM-imprinted polymer, but the separation factor was much lower in value compared with that of the TRPM-imprinted polymer. The separation factor of the L-TRPM-imprinted polymer was 1.58 at pH 7.0 but the separation factor of the L-PHEM-imprinted polymer was 1.35. We think that the nitrogen in the tryptophan ring of TRPM participates in an important interaction between the functional group in the imprinted cavity and the functional group in the substrate that is needed for increasing enantiomeric selectivity.Table 3
The adsorption of L-PHEM and D-PHEM on the L-PHEM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-PHEM
1.48× 102
1.04
D-PHEM
1.42 × 102
5.0
L-PHEM
1.72 × 103
1.06
D-PHEM
1.62 × 103
7.0
L-PHEM
3.45 × 103
1.35
D-PHEM
2.56 × 103
8.0
L-PHEM
4.17 × 103
1.18
D-PHEM
3.53 × 103Table 4
The adsorption of L-PHEM and D-PHEM on the D-PHEM-imprinted polymer.
pH
Substrate
Binding constant,K (M−1)
Separation factor,α
3.0
L-PHEM
1.39× 102
1.04
D-PHEM
1.45 × 102
5.0
L-PHEM
1.52 × 103
1.08
D-PHEM
1.64 × 103
7.0
L-PHEM
2.64 × 103
1.33
D-PHEM
3.51 × 103
8.0
L-PHEM
3.50 × 103
1.16
D-PHEM
4.06 × 103
## 3.3. Effect of the Chiral Emulsion Stabilizer
The Goto group introduced the surface molecular imprinting technique. They used L-GADR as an emulsion stabilizer [28]. So, we tried to use this chiral compound in our system. 0.207 g (0.251 mmol) of L-GADR was added during the preparation of the imprinted polymer with L-TRPM as a template molecule. The results showed that the separation factor was 1.60 at pH 7.0. We tried the same experiment 3 times. All of the results ((1) 1.63, (2) 1.58, and (3) 1.59) showed that the separation factor was more than 1.58. This means that L-GADR was effective in achieving enantiomeric selectivity, but compared to the result without L-GADR, the separation factor was bigger by a small amount. We also tried to conduct the experiment using 2 times the amount of L-GADR (0.414 g, 0.502 mmol). The results showed that the separation factor was average 1.61 ((1) 1.58, (2) 1.63, and (3) 1.62). This result value shows a little increase, but the value is within the experimental error. So, we concluded that this chiral compound is not very effective for achieving enantiomeric selectivity.
## 4. Conclusion
Amino acid-imprinted polymers were prepared by a surface imprinting technique in a W/O emulsion. DOPA was used as the emulsion stabilizer and the material for the host functional group in the imprinted cavity. DVB was used as a crosslinker. TRPM and PHEM were used as the imprinted materials and the substrate materials. The absorption experiments were conducted using these imprinted polymers with enantiomeric substrate materials. These polymers exhibited high enantiomeric selectivity for TRPM and PHEM. The separation factor of the TRPM-imprinted polymer was much higher than that of the PHEM-imprinted polymer.
---
*Source: 290187-2013-05-22.xml* | 2013 |
# NLRP3 Inflammasome Formation and Activation in Nonalcoholic Steatohepatitis: Therapeutic Target for Antimetabolic Syndrome Remedy FTZ
**Authors:** Yu Chen; Xingxiang He; Xinxu Yuan; Jinni Hong; Owais Bhat; Guangbi Li; Pin-Lan Li; Jiao Guo
**Journal:** Oxidative Medicine and Cellular Longevity
(2018)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2018/2901871
---
## Abstract
The Nod-like receptor protein 3 (NLRP3) inflammasome activation not only serves as an intracellular machinery triggering inflammation but also produces uncanonical effects beyond inflammation such as changing cell metabolism and increasing cell membrane permeability. The present study was designed to test whether this NLRP3 inflammasome activation contributes to the “two-hit” injury during nonalcoholic steatohepatitis (NASH) and whether it can be a therapeutic target for the action of Fufang Zhenzhu Tiaozhi (FTZ), a widely used herbal remedy for hyperlipidemia and metabolic syndrome in China. We first demonstrated that NLRP3 inflammasome formation and activation as well as lipid deposition occurred in the liver of mice on the high-fat diet (HFD), as shown by increased NLRP3 aggregation, enhanced production of IL-1β and high mobility group box 1 (HMGB1), and remarkable lipid deposition in liver cells. FTZ extracts not only significantly reduced the NLRP3 inflammasome formation and activation but also attenuated the liver steatosis and fibrogenic phenotype changed. In in vitro studies, palmitic acid (PA) was found to increase colocalization of NLRP3 components and enhanced caspase-1 activity in hepatic stellate cells (HSCs), indicating enhanced formation and activation of NLRP3 inflammasomes by PA. PA also increased lipid deposition. Nlrp3 siRNA can reverse this effect by silencing the NLRP3 inflammasome and both with FTZ. In FTZ-treated cells, not only inflammasome formation and activation was substantially attenuated but also lipid deposition in HSCs was blocked. This inhibition of FTZ on lipid deposition was similar to the effects of glycyrrhizin, an HMGB1 inhibitor. Mechanistically, stimulated membrane raft redox signaling platform formation and increased O2•− production by PA to activate NLRP3 inflammasomes in HSCs was blocked by FTZ treatment. It is concluded that FTZ extracts inhibit NASH by its action on both inflammatory response and liver lipid metabolism associated with NLRP3 inflammasome formation and activation.
---
## Body
## 1. Introduction
Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease throughout the world. NAFLD may either be present as a simple steatosis (nonalcoholic fatty liver) or evolves towards its inflammatory complication (10–20%), namely, nonalcoholic steatohepatitis (NASH), which can further progress towards liver cirrhosis and hepatocellular carcinoma, a complication that occurs increasingly in the noncirrhotic NAFLD population [1]. It is generally accepted that the pathogenesis of NASH is involved in a two-step process, which is referred to as a “two-hit” model. The first “hit” is associated with excessive triglyceride or other lipid accumulation in the liver, and the second “hit” leads to the development of liver inflammation and fibrosis, which is attributed to several important pathogenic factors that can eventually induce liver damage such as inflammatory cytokines, oxidative stress, mitochondrial dysfunction, and/or endoplasmic reticulum stress. Recent studies have indicated that the Nod-like receptor protein 3 (NLRP3) inflammasome activation may play a fundamental role in the development of NASH [2, 3]. Since NLRP3 inflammasome has been reported to not only activate the inflammatory response but also possess noncanonical or noninflammatory action that may contribute to the progression of some chronic degenerative or fibrotic diseases [4–7], it is possible that the activation of NLRP3 inflammasome mediates NASH development via the “two-hit” mechanism. We hypothesized that not only hepatitis and consequent fibrosis but also liver steatosis in the progression of NASH may be triggered or modulated by NLRP3 inflammasome activation. In this regard, recent studies indeed demonstrated that in addition to classical inflammatory cytokines such as IL-1β and IL-18, HMGB1 released during NLRP3 inflammasome activation is also importantly implicated in both liver steatosis and subsequent hepatitis or fibrosis [8–10]. These inflammatory and uncanonical or noninflammatory effects of NLRP3 inflammasomes on the development of NASH has been the main theme in the present study.The noncanonical effects during NLRP3 inflammasome activation may answer a long-lasting question of why classic anti-inflammatory medicines, such as commonly used indole and arylpropionic acid derivatives, are not very efficient in the prevention or treatment of many degenerative diseases including NASH, where chronic inflammation are its hallmarks. It may be promising to target the NLRP3 inflammasome and thereby block the “two-hit” mechanisms during NASH. In this regard, a candidate may be Fufang Zhenzhu Tiaozhi (FTZ), a widely used herbal remedy for hyperlipidemia and metabolic syndrome in China, which showed its cocktail therapeutic efficiency. FTZ that has been patented in both the USA and China is a mixture extracted from the Chinese herbal prescription, consisting ofRhizoma coptidis, Fructus Ligustri Lucidi, Herba cirsii japonici, Radix Salvia miltiorrhiza, Radix Notoginseng, Cortex Eucommiae, Fructus Citri Sarcodactylis, and Radix Atractylodes macrocephala. FTZ has been prescribed over the last 15 years for treatment of hyperlipidemia and metabolic syndrome and related complications such as atherosclerosis and NASH [11, 12]. In a recent study, some components of FTZ were found to prevent the development of fatty liver in rats [13]. However, the mechanism mediating its action remains unknown. In the present study, after characterization of roles in which NLRP3 inflammasomes play in NASH, we also examined whether FTZ prevents NASH development by targeting the effects of NLRP3 inflammasome activation on both inflammatory response and steatosis in the liver.
## 2. Material and Methods
### 2.1. Animals
C57BL/6J mice (8 weeks of age, male or female) were fed a normal diet (ND) or a high-fat diet (HFD, number D12492, Research Diets, NJ, USA) for 4 weeks, and then FTZ extracts (100 mg/kg/day) were fed by gavage for the last 4 weeks both with HFD. The preparation of FTZ extracts for mice was consistent with the protocol described previously [14]. All mice were randomly distributed to different experimental groups. At the endpoint of the experimental period, blood samples were collected and these mice were then sacrificed for harvest of the liver tissues, which were used for oil red O staining, immunofluorescence staining, and biochemical analysis. All protocols were approved by the Institutional Animal Care and Use Committee of the Virginia Commonwealth University.
### 2.2. Cell Culture and Treatments
Mouse hepatic stellate cells (HSCs) were prepared by the discontinuous density gradient centrifugation technique as previously described, and some minor modifications were made to increase success rate as we described previously [4]. The collected cells were cultured in DMEM (Gibco, Carlsbad, CA, USA) containing 10% FBS (Gibco) in humidified 95% air and 5% CO2 mixture at 37°C. The cell viability, as measured by a Trypan Blue exclusion assay, was approximately 90%. HSCs were treated with palmitic acid (PA, 200 μM/ml) for indicated hours. HSCs were characterized and confirmed as previously described [15]. We chose to work on HSCs, because they are a major cell type responsible for the progression of liver fibrosis. Our previous studies have shown that NLRP3 inflammasome activation is mainly responsible for the development of liver fibrosis [3, 4]. Our preliminary experiments demonstrated that the optimum response of inflammasome activation occurred over 24-hour PA treatment in HSC cultures, and therefore all experiments in our cell study protocols used the same duration of PA before and after treatments of FTZ extracts (50 μg/ml, prepared by DMSO and diluted with medium in 1 : 1000) or administration of inflammasome inhibitors or blockers such as ROS scavenger N-acetyl-L-cysteine (NAC, 10 μM, Sigma, St. Louis, MO, USA).
### 2.3. Oil Red O Staining
For oil red O staining, the liver tissue slides and HSCs grown on a chamber with coverslips were used as described previously [16] with minor modifications. HSCs (104 cells/well) cultured in a chamber with glass coverslips were treated as indicated and loaded with PA for 24 hours. Frozen liver tissue slides and the HSC coverslips were then stained with oil red O (0.1% in isopropanol) for determination of lipid accumulation. The oil red O staining was examined by light microscopy, and images were obtained by MetaMorph 6.0. The data was represented by the area percentage of each cell positive for oil red O stain, which was calculated in Image Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD, USA). For each sample, at least 200 cells were analyzed and summarized oil red O positive cell counts were used for statistical analysis.
### 2.4. Confocal Microscopic Analysis
For confocal analysis of inflammasome molecule colocalization or aggregation, the liver tissue slides and HSCs grown on a chamber with coverslips were used. They were first fixed in 4% paraformaldehyde in phosphate-buffered saline (PFA/PBS) for 15 min. After being permeabilized with 0.1% Triton X-100/PBS and rinsed with PBS, the slides were incubated overnight at 4°C with anti-NLRP3 (1 : 200, Abcam, MA, USA) and anti-ASC (1 : 50, Enzo, PA, USA) or anti-caspase-1 (1 : 100, Abcam). After washing, these slides incubated with primary antibodies were then incubated with Alexa-488- or Alexa-555-labeled secondary antibodies for 1 h at room temperature. The slides were mounted and subjected to examinations using a confocal laser scanning microscope (Fluoview FV1000, Olympus, Japan) with photos being taken and the colocalization of NLRP3 with ASC or caspase-1 analyzed by the Image-Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD, USA). The summarized data of molecular colocalization efficiency was expressed as correlation coefficient as we described previously [17–19].FLICA Staining. During the last hour of incubation, cells were labeled with FAM-YVAD-fmk caspase-1 FLICA™ kit (Immunochemistry, Bloomington, IN, USA) according to the manufacturer’s guidelines, which binds activated caspase-1. Stained cells were visualized by confocal microscopy for active caspase-1 oligomerization, which was colocalized with fibrotic markers vimentin (with antibody staining at 1 : 200) and α-smooth muscle actin (α-SMA, with antibody at 1 : 200).Immunofluorescent Microscopic Analysis of Membrane Raft (MR) Clusters. HSCs were grown on glass coverslips. After fixation with 4% PFA, cells were incubated with Alexa Fluor 488-conjugated cholera toxin B (Alexa488-CTXB, 2 μg/ml, 2 h, Molecular Probes, CA, USA), which binds with the MR-enriched ganglioside GM1. For dual-staining detection of the colocalization of MRs with gp91phox and p47phox, the cells were first incubated with Alexa488-CTXB and then with anti-gp91phox and p47phox (1: 200, BD Biosciences, CA, USA), respectively, which was followed by corresponding Alexa555-conjugated secondary antibodies (1: 500, Invitrogen, NY, USA). Then, the colocalization was visualized with confocal microscopy [20, 21].
### 2.5. Immunohistochemistry
Liver tissues were fixed in 4% (v/v) paraformaldehyde (PFA) in PBS and embedded with paraffin, which were then sliced into tissue sections (4 μM) and mounted on glass slides. These tissue slides were stained with goat anti-IL-1β antibody (1 : 100, R&D Systems) overnight at 4°C after a 20 min wash with 3% H2O2 and 30 min blocking with 10% serum and then probed with anti-goat Ig-G second antibody labeled with HRP according to the protocols described previously [18, 22]. Negative controls were prepared without the primary antibodies. The area percentage of the positive staining was calculated in Image Pro Plus 6.0 software.
### 2.6. Western Blot Analysis
Proteins from cell lysates were denatured with SDS buffer and boiled for 5 minutes. Samples were run on a SDS-PAGE gel, transferred onto polyvinylidene difluoride (PVDF) membrane, and blocked with 5% milk. Then, the membranes were probed with the following primary antibodies overnight at 4°C: rabbit anti-caspase-1 (1 : 500, Santa Cruz, CA, USA) and rabbit anti-β-actin (1 : 10000, Santa Cruz). They were incubated with goat anti-rabbit-HRP Ig-G (1 : 5000, Santa Cruz) for 1 hour at room temperature. Immunoreactive bands were detected by chemiluminescence techniques after washing three times and then visualized on Kodak Omat X-ray film. The intensity of the specific bands was calculated using ImageJ software version 1.44p.
### 2.7. Il-1β Elisa
After PA treatment with or without pretreatments of inhibitors, the cell supernatant was also collected to measure IL-1β production by a mouse IL-1β ELISA kit (Bender MedSystems, CA, USA) according to the protocol described by the manufacturer. The data was expressed as the fold change compared with control cells.
### 2.8. Electromagnetic Spin Resonance (ESR) Spectrometry
For detection of NADPH oxidase-dependent O2•− production, protein was gently isolated from 1 × 106 cells and resuspended with modified Krebs–4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid buffer containing deferoximine (100 μM, Sigma) and diethyldithiocarbamate (5 μM; Sigma). A spin trap, 1-hydroxy-3- methoxycarbonyl-2,2,5,5-tetramethylpyrrolidine (CMH, NOXygen, Elzach, Germany) (1 mM final concentration) was then added to the mixture in the presence or absence of manganese-dependent superoxide dismutase (SOD, 200 U/ml; Sigma). The mixtures were loaded into glass capillaries and immediately analyzed for O2•− formation kinetics for 10 min in a MiniScope MS200 ESR spectrometer (Magnettech, Berlin, Germany). The ESR spectrometer was set according to the following parameters: biofield, 3350; field sweep, 60 G; microwave frequency, 9.78 GHz; microwave power, 20 mW; modulation amplitude, 3 G; 4096 points of resolution; and receiver gain, 50. The ESR spectrometric signal was recorded in arbitrary units, and the final results were expressed as the fold changes of the treatment group compared to control as we described previously [23].
### 2.9. Statistics
Data are presented as means ± standard error mean. The significant differences between and within multiple groups were examined using one-way or two-way ANOVA, followed by Duncan’s multiple-range test.p<0.05 was considered statistically significant.
## 2.1. Animals
C57BL/6J mice (8 weeks of age, male or female) were fed a normal diet (ND) or a high-fat diet (HFD, number D12492, Research Diets, NJ, USA) for 4 weeks, and then FTZ extracts (100 mg/kg/day) were fed by gavage for the last 4 weeks both with HFD. The preparation of FTZ extracts for mice was consistent with the protocol described previously [14]. All mice were randomly distributed to different experimental groups. At the endpoint of the experimental period, blood samples were collected and these mice were then sacrificed for harvest of the liver tissues, which were used for oil red O staining, immunofluorescence staining, and biochemical analysis. All protocols were approved by the Institutional Animal Care and Use Committee of the Virginia Commonwealth University.
## 2.2. Cell Culture and Treatments
Mouse hepatic stellate cells (HSCs) were prepared by the discontinuous density gradient centrifugation technique as previously described, and some minor modifications were made to increase success rate as we described previously [4]. The collected cells were cultured in DMEM (Gibco, Carlsbad, CA, USA) containing 10% FBS (Gibco) in humidified 95% air and 5% CO2 mixture at 37°C. The cell viability, as measured by a Trypan Blue exclusion assay, was approximately 90%. HSCs were treated with palmitic acid (PA, 200 μM/ml) for indicated hours. HSCs were characterized and confirmed as previously described [15]. We chose to work on HSCs, because they are a major cell type responsible for the progression of liver fibrosis. Our previous studies have shown that NLRP3 inflammasome activation is mainly responsible for the development of liver fibrosis [3, 4]. Our preliminary experiments demonstrated that the optimum response of inflammasome activation occurred over 24-hour PA treatment in HSC cultures, and therefore all experiments in our cell study protocols used the same duration of PA before and after treatments of FTZ extracts (50 μg/ml, prepared by DMSO and diluted with medium in 1 : 1000) or administration of inflammasome inhibitors or blockers such as ROS scavenger N-acetyl-L-cysteine (NAC, 10 μM, Sigma, St. Louis, MO, USA).
## 2.3. Oil Red O Staining
For oil red O staining, the liver tissue slides and HSCs grown on a chamber with coverslips were used as described previously [16] with minor modifications. HSCs (104 cells/well) cultured in a chamber with glass coverslips were treated as indicated and loaded with PA for 24 hours. Frozen liver tissue slides and the HSC coverslips were then stained with oil red O (0.1% in isopropanol) for determination of lipid accumulation. The oil red O staining was examined by light microscopy, and images were obtained by MetaMorph 6.0. The data was represented by the area percentage of each cell positive for oil red O stain, which was calculated in Image Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD, USA). For each sample, at least 200 cells were analyzed and summarized oil red O positive cell counts were used for statistical analysis.
## 2.4. Confocal Microscopic Analysis
For confocal analysis of inflammasome molecule colocalization or aggregation, the liver tissue slides and HSCs grown on a chamber with coverslips were used. They were first fixed in 4% paraformaldehyde in phosphate-buffered saline (PFA/PBS) for 15 min. After being permeabilized with 0.1% Triton X-100/PBS and rinsed with PBS, the slides were incubated overnight at 4°C with anti-NLRP3 (1 : 200, Abcam, MA, USA) and anti-ASC (1 : 50, Enzo, PA, USA) or anti-caspase-1 (1 : 100, Abcam). After washing, these slides incubated with primary antibodies were then incubated with Alexa-488- or Alexa-555-labeled secondary antibodies for 1 h at room temperature. The slides were mounted and subjected to examinations using a confocal laser scanning microscope (Fluoview FV1000, Olympus, Japan) with photos being taken and the colocalization of NLRP3 with ASC or caspase-1 analyzed by the Image-Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD, USA). The summarized data of molecular colocalization efficiency was expressed as correlation coefficient as we described previously [17–19].FLICA Staining. During the last hour of incubation, cells were labeled with FAM-YVAD-fmk caspase-1 FLICA™ kit (Immunochemistry, Bloomington, IN, USA) according to the manufacturer’s guidelines, which binds activated caspase-1. Stained cells were visualized by confocal microscopy for active caspase-1 oligomerization, which was colocalized with fibrotic markers vimentin (with antibody staining at 1 : 200) and α-smooth muscle actin (α-SMA, with antibody at 1 : 200).Immunofluorescent Microscopic Analysis of Membrane Raft (MR) Clusters. HSCs were grown on glass coverslips. After fixation with 4% PFA, cells were incubated with Alexa Fluor 488-conjugated cholera toxin B (Alexa488-CTXB, 2 μg/ml, 2 h, Molecular Probes, CA, USA), which binds with the MR-enriched ganglioside GM1. For dual-staining detection of the colocalization of MRs with gp91phox and p47phox, the cells were first incubated with Alexa488-CTXB and then with anti-gp91phox and p47phox (1: 200, BD Biosciences, CA, USA), respectively, which was followed by corresponding Alexa555-conjugated secondary antibodies (1: 500, Invitrogen, NY, USA). Then, the colocalization was visualized with confocal microscopy [20, 21].
## 2.5. Immunohistochemistry
Liver tissues were fixed in 4% (v/v) paraformaldehyde (PFA) in PBS and embedded with paraffin, which were then sliced into tissue sections (4 μM) and mounted on glass slides. These tissue slides were stained with goat anti-IL-1β antibody (1 : 100, R&D Systems) overnight at 4°C after a 20 min wash with 3% H2O2 and 30 min blocking with 10% serum and then probed with anti-goat Ig-G second antibody labeled with HRP according to the protocols described previously [18, 22]. Negative controls were prepared without the primary antibodies. The area percentage of the positive staining was calculated in Image Pro Plus 6.0 software.
## 2.6. Western Blot Analysis
Proteins from cell lysates were denatured with SDS buffer and boiled for 5 minutes. Samples were run on a SDS-PAGE gel, transferred onto polyvinylidene difluoride (PVDF) membrane, and blocked with 5% milk. Then, the membranes were probed with the following primary antibodies overnight at 4°C: rabbit anti-caspase-1 (1 : 500, Santa Cruz, CA, USA) and rabbit anti-β-actin (1 : 10000, Santa Cruz). They were incubated with goat anti-rabbit-HRP Ig-G (1 : 5000, Santa Cruz) for 1 hour at room temperature. Immunoreactive bands were detected by chemiluminescence techniques after washing three times and then visualized on Kodak Omat X-ray film. The intensity of the specific bands was calculated using ImageJ software version 1.44p.
## 2.7. Il-1β Elisa
After PA treatment with or without pretreatments of inhibitors, the cell supernatant was also collected to measure IL-1β production by a mouse IL-1β ELISA kit (Bender MedSystems, CA, USA) according to the protocol described by the manufacturer. The data was expressed as the fold change compared with control cells.
## 2.8. Electromagnetic Spin Resonance (ESR) Spectrometry
For detection of NADPH oxidase-dependent O2•− production, protein was gently isolated from 1 × 106 cells and resuspended with modified Krebs–4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid buffer containing deferoximine (100 μM, Sigma) and diethyldithiocarbamate (5 μM; Sigma). A spin trap, 1-hydroxy-3- methoxycarbonyl-2,2,5,5-tetramethylpyrrolidine (CMH, NOXygen, Elzach, Germany) (1 mM final concentration) was then added to the mixture in the presence or absence of manganese-dependent superoxide dismutase (SOD, 200 U/ml; Sigma). The mixtures were loaded into glass capillaries and immediately analyzed for O2•− formation kinetics for 10 min in a MiniScope MS200 ESR spectrometer (Magnettech, Berlin, Germany). The ESR spectrometer was set according to the following parameters: biofield, 3350; field sweep, 60 G; microwave frequency, 9.78 GHz; microwave power, 20 mW; modulation amplitude, 3 G; 4096 points of resolution; and receiver gain, 50. The ESR spectrometric signal was recorded in arbitrary units, and the final results were expressed as the fold changes of the treatment group compared to control as we described previously [23].
## 2.9. Statistics
Data are presented as means ± standard error mean. The significant differences between and within multiple groups were examined using one-way or two-way ANOVA, followed by Duncan’s multiple-range test.p<0.05 was considered statistically significant.
## 3. Results
### 3.1. NLRP3 Inflammasome Formation and Activation in the Liver of Mice on the HFD with and without Treatment of FTZ
By confocal microscopy, we found that there was significantly elevated colocalization of NLRP3 with ASC or caspase-1 in the liver of mice on the HFD compared with mice on the ND, indicating enhanced formation of NLRP3 inflammasomes. In mice receiving FTZ, HFD-induced increases in colocalization of NLRP3 inflammasome components were substantially blocked (Figure1(a)). Quantitation of the NLRP3 colocalization by measurement of correlation coefficient is presented in Figure 1(b), showing that NLRP3 inflammasome formation was significantly enhanced in mice on the HFD diet compared to mice on the ND and this enhanced NLRP3 inflammasome formation in the liver of mice on the HFD was significantly attenuated by FTZ.Figure 1
NLRP3 inflammasome formation and activation in the liver from mice on the HFD with and without FTZ treatment. (a) Representative confocal fluorescence images show the colocalization of NLRP3 with caspase-1 or ASC. (b) Correlation coefficient showing a statistically significant increase in NLRP3 inflammasome formation in HFD for 8 weeks with and without FTZ treatment (100 mg/kg/day) by gavage for 4 weeks (n=5 mice per group). (c) Representative immunohistochemical images show positive stain of IL-1β and IL-18 in the liver. (d) Positive staining area of IL-1β and IL-18 showing a statistically significant increase after NLRP3 inflammasome formation in the liver of mice on the HFD, which was suppressed by FTZ (n=4 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group.
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(d)Immunohistochemical analysis showed that both IL-1β and IL-18 (Figure 1(c)) levels significantly increased around fatty hepatocytes in the liver of mice on the HFD, suggesting activation of the inflammasome in these cells. FTZ treatment remarkably reduced this HFD-induced increase in hepatic IL-1β and IL-18. As shown in Figure 1(d), the positive staining areas of hepatic IL-1β and IL-18 were significantly increased in mice on the HFD without treatment of FTZ. In mice receiving FTZ, the increased IL-1β and IL-18 staining in the liver of mice on the HFD was significantly suppressed. It is clear that FTZ can inhibit the activation of NLRP3 inflammasomes in the liver.
### 3.2. Steatosis and NASH in the Liver of Mice on the HFD with and without FTZ Treatment
Steatosis as an important pathological change of NASH was analyzed in mice on the HFD. By oil red O staining, it was found that HFD caused a significant increase in lipid deposition in the liver of mice without treatment of FTZ. This enhanced oil red O staining in the liver was markedly reduced when mice were treated with FTZ (Figure2(a)). The quantitation of tissue areas stained by oil red O showed that more than 40% of the liver in mice on the HFD were with lipid deposition. Treatment of mice with FTZ significantly attenuated this HFD-induced lipid deposition in the liver (Figure 2(b)). It is clear that FTZ significantly prevented steatosis in mice fed with HFD.Figure 2
Steatosis and hepatitis in the liver from mice on the HFD with and without FTZ treatment. (a) Representative oil red O staining shows positive staining of lipid deposition in the liver. (b) Positive staining area of lipid deposition showing statistically significant increases after HFD, which was suppressed by FTZ (n=5 mice per group). (c) Representative H&E staining images showing inflammatory infiltration and fatty bulbs in liver cells after HFD which was attenuated by FTZ. (d) NAFLD activity score showing statistically significant increases after HFD for 8 weeks with and without FTZ treatment (n=5 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group
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(d)By H&E staining, we also examined the morphological changes in the liver of mice from different experimental groups. As shown in Figure2(c), besides lipid deposition the liver from mice on the HFD exhibited obvious inflammatory cell infiltration and increases in protein leakage into interstitial space. However, the liver from mice receiving FTZ almost lacked these inflammatory changes. Figure 2(d) depicts the results from the analysis of NAFLD activity score, showing that the increase in NAFLD activity score was highly significant in the liver of mice fed the HFD and that FTZ treatment significantly inhibited such increase in NAFLD activity score.
### 3.3. Fibrotic Changes Associated with NLRP3 Inflammasome Activation in the Liver of Mice on the HFD with and without FTZ Treatment
In addition to steatosis and inflammatory response detected, we also examined whether there is fibrogenic pathology in the liver from different experimental groups of mice. It was found that in the hepatic interstitium, in particular, in tissues around liver sinuses, there were increased levels ofα-SMA and vimentin, as shown by immunohistochemical staining (Figure 3(a)). It is well known that increased α-SMA and vimentin indicate phenotype changes of cells from quiescent to activated status, which occurred more remarkably in HSCs. These results were semiquantitated by measurement of α-SMA and vimentin staining areas in the liver. It was shown that α-SMA and vimentin levels in the liver were significantly elevated in mice on the HFD, and this HFD-induced fibrotic change in the liver was significantly blocked by FTZ treatment (Figure 3(b)).Figure 3
Fibrogenic phenotypes in the liver from mice on the HFD with and without FTZ treatment. (a) Representative immunohistochemical images showing enhancedα-SMA and vimentin staining, which are the markers of phenotype changed from quiescent to activated in HSCs. FTZ reduced HFD-induced increase in α-SMA and vimentin staining. (b) Summarized data depicting a significant increase in α-SMA and vimentin level in the liver of mice on the HFD with and without FTZ treatment (n=4 mice per group). (c, d) Representative images and PPC showing FLICA, active caspase-1 colocalization with α-SMA or vimentin staining in the liver of mice on the HFD, which was reduced by FTZ (n=4 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group.
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(d)Since previous studies have shown that the formation and activation of NLRP3 inflammasomes in fibroblasts including HSCs may trigger the development of liver fibrosis [4], we determined whether these inflammasome-triggered fibrogenetic effects occur in NAFLD. By confocal microscopy, FLICA that indicates activated caspase-1 (green) was found to colocalize with increased α-SMA or vimentin (red) around liver sinuses and portal venules of the liver from mice on the HFD as shown by yellow spots (Figure 3(c)). In the liver from mice treated with FTZ, this enhanced colocalization of FLICA with α-SMA or vimentin was substantially reduced. By quantitative analysis of this colocalization of FLICA with α-SMA or vimentin, we found that the areas or cells with inflammasome activation had much higher level of α-SMA or vimentin, indicating the fibrogenesis during this model of NAFLD. FTZ significantly blocked this HFD-induced fibrogenic effect (Figure 3(d)).
### 3.4. PA-Induced NLRP3 Inflammasomes Formation and Increased Caspase-1 Activity in HSCs
To explore the mechanisms of NLRP3 inflammasome formation and activation in HSCs, we used palmitic acid (PA), one of the major components of saturated fatty acid, to induce lipid deposition to examine the role of NLRP3 inflammasome activation and related NASH-like changes in these cells. Confocal microscopic analysis found that the colocalization of NLRP3 with caspase-1 or ASC increased in HSCs upon PA stimulation, which indicates the aggregation or assembly of these inflammasome molecules indeed occurs in response to PA stimulation. In HSCs pretreated with FTZ extracts, there was no colocalization of NLRP3 with caspase-1 or ASC in HSCs stimulated by PA (Figure4(a)). The correlation coefficient of NLRP3 with ASC or caspase-1 showed that the colocalization of NLRP3 molecules increased significantly in HSCs stimulated by PA, which was completely blocked by FTZ, suggesting that FTZ is able to block NLRP3 inflammasome formation induced by PA in HSCs (Figure 4(b)).Figure 4
NLRP3 inflammasome formation and activation in HSCs after PA-induced steatosis with and without FTZ treatment. (a) Representative confocal fluorescence images show the colocalization of NLRP3 with caspase-1 or ASC in HSCs. (b) Correlation coefficient (PCC) showing a statistically significant increase in NLRP3 inflammasomes formation in PA-treated (200 mM/ml, 24 hours) HSCs, which was almost completely blocked by FTZ (50μg/ml, 24 hours) (n=5 batches of cells). (c) Representative Western blot gel documents showing cleaved caspase-1 increased in HSCs treated with PA but blocked by FTZ. (d) Densitometric quantitation of immunoreactive bands showing a statistically significant increase in cleaved caspase-1 after PA-treated cells (n=6 batches of cells). (e) ELISA of IL-1β levels from cell media showing a statistically significant increase induced by PA and decreased by FTZ (n=5 batches of cells). ∗p<0.05 versus Vehl-Ctrl group; #p<0.05 versus PA-Vehl group.
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(e)We also determined NLRP3 inflammasome activation by analysis of active caspase-1 and IL-1β production in HSCs with and without pretreatment with FTZ. As shown in Figures 4(c) and 4(d), PA significantly increased the level of cleaved or active caspase-1 (15 kDa) and FTZ completely blocked this PA-induced increase in active caspase-1 level. Correspondingly, biochemical analysis showed that PA induced a significant increase in IL-1β production from HSCs, which was also completely blocked by FTZ treatment. The inhibition of PA-induced IL-1β production by FTZ was similar to the effects of NAC, an often used antioxidant for suppression of NLRP3 inflammasome activation (Figure 4(e)).
### 3.5. Effects of Mouse Nlrp3 Gene Silencing on PA-Induced NLRP3 Inflammasome Activation with and without FTZ
Knockdown of mouse Nlrp3 mRNA level by Nlrp3 siRNA in HSCs remarkably inhibited PA-induced colocalization of ASC with caspase-1 (Figures5(a) and 5(b)) and attenuated PA-increased level of cleaved caspase-1 (Figure 5(c)) and both blocked by FTZ. Consistent with these findings, Nlrp3 gene silencing with or without FTZ blocked IL-1β production in HSCs (Figures 6(a) and 6(b)) and PA-induced steatosis (Figure 6(c)). These results from NLRP3 gene silencing further support that it is the NLRP3 inflammasome that contributes to inflammatory response during NASH of this model and that the effective treatment of FTZ may be due to inhibition of the NLRP3 inflammasome activation.Figure 5
Nlrp3 gene silencing inhibited PA-induced NLRP3 inflammasomes formation and activation in HSCs with and without FTZ treatment. (a) Representative fluorescence confocal microscopic images showing the colocalization of ASC with caspase-1. (b) Correction coefficient (PCC) showing a statistically significant increase in colocalization of ASC with caspase-1 in PA-treated HSCs, which was suppressed by Nlrp3 siRNA and FTZ. (c) Representative Western blot gel documents showing cleaved caspase-1 increased in HSCs treated with PA but blocked by Nlrp3 siRNA and FTZ. (d) Densitometric quantitation of immunoreactive bands showing a statistically significant decrease in cleaved caspase-1 by using Nlrp3 siRNA and FTZ (n=3 batches of cells). ∗p<0.05 versus Ctrl-scram group; #p<0.05 versus PA-scram group.
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(d)Figure 6
Nlrp3 gene silencing inhibited PA-induced NLRP3 inflammasome production and steatosis in HSCs with and without FTZ treatment. (a) Representative oil red O images showing positive staining of lipid deposition in PA-treated HSCs, which was suppressed by Nlrp3 siRNA and FTZ. (b) Staining area of lipid deposition showing a statistically significant increase induced by PA, which was reduced by Nlrp3 siRNA and FTZ. (c) ELISA of IL-1β levels from cell media showing a statistically significant decreased by Nlrp3 siRNA and with FTZ (n=3 batches of cells). ∗p<0.05 versus Ctrl-scram group; #p<0.05 versus PA-scram group.
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### 3.6. Involvement of Redox Signaling in PA-Induced NLRP3 Inflammasome Activation in HSCs and the Effect of FTZ
Since previous studies showed that the MR redox signaling platforms and redox signaling are involved in inflammasome activation [24–26], we determined whether PA-induced NLRP3 inflammasome activation is associated with this redox regulatory pathway. As measured by ESR, O2•− production significantly increased when HSCs were stimulated by PA, which was shown in largely enhanced reactive signals in ESR chromatography. FTZ had no effects on basal O2•− production but inhibited PA-induced increases in ESR signal (Figure 7(a)). By calculation and nomination to SOD-sensitive components in ESR signals, PA-induced O2•− production in HSCs was found to be completely blocked by FTZ. This FTZ-mediated inhibitory effects on PA-induced O2•− production were similar to NAC (Figure 7(b)).Figure 7
Superoxide production and NADPH oxidase-membrane raft (MR) clustering in HSCs induced by PA with and without FTZ. (a) Representative ESR traces of superoxide (O2•−) trapped by CMH using NADPH as substrate upon PA stimulation in HSCs. (b) The bar graph summarizing ESR data, showing that PA enhanced O2•− production in HSCs, which was attenuated by FTZ and NAC (n=5 batches of cells). (c) Representative fluorescence confocal microscopic images showing the colocalization of MR component labeled by CTXB with NADPH oxidase subunit gp91 or p47. (d) Correction coefficient (PCC) showing a statistically significant increase in colocalization of CTXB with gp91 or p47 in PA-treated HSCs, which was suppressed by FTZ or NAC treatment (n=5 batches of cells). ∗p<0.05 versus Ctrl-Vehl group; #p<0.05 versus PA-Vehl group.
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(d)We next used Alexa Fluor 488-labeled CTXB (a MR marker) and anti-gp91 or anti-p47 antibody (NADPH oxidase (NOX) subunits) to measure clustering of MRs with both NOX subunits, which indicates MR redox signaling platform formation to produce O2•−. PA stimulation was found to significantly increase MR clustering with gp91 or p47 NOX subunits, as shown by the yellow patches on the HSC membrane (Figure 7(c)). It is well known that this MR redox platform formation led to the activation of NOX and subsequent generation of O2•−. These results were summarized in Figure 7(d), clearly showing that PA stimulated MR redox signaling platform formation in HSC membrane and FTZ blocked this PA effect.
### 3.7. Contribution of HMGB1 from NLRP3 Inflammasome Activation to PA-Induced Lipid Deposition and to the Beneficial Effects of FTZ
As described above, our animal studies found that NLRP3 inflammasome activation not only participated in HFD-induced hepatitis and liver fibrosis but also caused steatosis in the liver. FTZ could block the development of both steatosis and sterile hepatitis in the liver. It seems that NLRP3 inflammasome activation also has uncanonical effects in NASH development which is beyond inflammation. To test this hypothesis, we addressed the role of HMGB1, an NLRP3 inflammasome product, which has been reported to increase lipid deposition [8]. As shown in Figure 8(a), the representative oil red O staining showed that PA resulted in strong staining of lipids in HSCs, which was blocked by FTZ pretreatment. The effects of PA can be mimicked by HMGB1 but inhibited by HMGB1 inhibitor, glycyrrhizin (GLY). The quantitative measurement of oil red O staining areas was summarized in Figure 8(b), showing that PA increased lipid deposition, which was blocked by FTZ. The PA-induced lipid deposition was significantly enhanced by the addition of HMGB1 but blocked by GLY, even in the presence of HMGB1.Figure 8
Involvement of HMGB1 in lipid deposition in HSCs treated with PA with and without FTZ treatment. (a) Representative oil red O images showing positive staining of lipid deposition in PA-treated HSCs, which was enhanced by HMGB1 but suppressed by FTZ and GLY, an inhibitor of HMGB1. (b) Staining area of lipid deposition showing a statistically significant increase induced by PA, which was enhanced by HMGB1, but reduced by FTZ and HMGB1 inhibitor, GLY (n=5 batches of cells). ∗p<0.05 versus PA-Vehl group; #p<0.05 versus PA-HMGB1-Vehl group.
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## 3.1. NLRP3 Inflammasome Formation and Activation in the Liver of Mice on the HFD with and without Treatment of FTZ
By confocal microscopy, we found that there was significantly elevated colocalization of NLRP3 with ASC or caspase-1 in the liver of mice on the HFD compared with mice on the ND, indicating enhanced formation of NLRP3 inflammasomes. In mice receiving FTZ, HFD-induced increases in colocalization of NLRP3 inflammasome components were substantially blocked (Figure1(a)). Quantitation of the NLRP3 colocalization by measurement of correlation coefficient is presented in Figure 1(b), showing that NLRP3 inflammasome formation was significantly enhanced in mice on the HFD diet compared to mice on the ND and this enhanced NLRP3 inflammasome formation in the liver of mice on the HFD was significantly attenuated by FTZ.Figure 1
NLRP3 inflammasome formation and activation in the liver from mice on the HFD with and without FTZ treatment. (a) Representative confocal fluorescence images show the colocalization of NLRP3 with caspase-1 or ASC. (b) Correlation coefficient showing a statistically significant increase in NLRP3 inflammasome formation in HFD for 8 weeks with and without FTZ treatment (100 mg/kg/day) by gavage for 4 weeks (n=5 mice per group). (c) Representative immunohistochemical images show positive stain of IL-1β and IL-18 in the liver. (d) Positive staining area of IL-1β and IL-18 showing a statistically significant increase after NLRP3 inflammasome formation in the liver of mice on the HFD, which was suppressed by FTZ (n=4 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group.
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(d)Immunohistochemical analysis showed that both IL-1β and IL-18 (Figure 1(c)) levels significantly increased around fatty hepatocytes in the liver of mice on the HFD, suggesting activation of the inflammasome in these cells. FTZ treatment remarkably reduced this HFD-induced increase in hepatic IL-1β and IL-18. As shown in Figure 1(d), the positive staining areas of hepatic IL-1β and IL-18 were significantly increased in mice on the HFD without treatment of FTZ. In mice receiving FTZ, the increased IL-1β and IL-18 staining in the liver of mice on the HFD was significantly suppressed. It is clear that FTZ can inhibit the activation of NLRP3 inflammasomes in the liver.
## 3.2. Steatosis and NASH in the Liver of Mice on the HFD with and without FTZ Treatment
Steatosis as an important pathological change of NASH was analyzed in mice on the HFD. By oil red O staining, it was found that HFD caused a significant increase in lipid deposition in the liver of mice without treatment of FTZ. This enhanced oil red O staining in the liver was markedly reduced when mice were treated with FTZ (Figure2(a)). The quantitation of tissue areas stained by oil red O showed that more than 40% of the liver in mice on the HFD were with lipid deposition. Treatment of mice with FTZ significantly attenuated this HFD-induced lipid deposition in the liver (Figure 2(b)). It is clear that FTZ significantly prevented steatosis in mice fed with HFD.Figure 2
Steatosis and hepatitis in the liver from mice on the HFD with and without FTZ treatment. (a) Representative oil red O staining shows positive staining of lipid deposition in the liver. (b) Positive staining area of lipid deposition showing statistically significant increases after HFD, which was suppressed by FTZ (n=5 mice per group). (c) Representative H&E staining images showing inflammatory infiltration and fatty bulbs in liver cells after HFD which was attenuated by FTZ. (d) NAFLD activity score showing statistically significant increases after HFD for 8 weeks with and without FTZ treatment (n=5 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group
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(d)By H&E staining, we also examined the morphological changes in the liver of mice from different experimental groups. As shown in Figure2(c), besides lipid deposition the liver from mice on the HFD exhibited obvious inflammatory cell infiltration and increases in protein leakage into interstitial space. However, the liver from mice receiving FTZ almost lacked these inflammatory changes. Figure 2(d) depicts the results from the analysis of NAFLD activity score, showing that the increase in NAFLD activity score was highly significant in the liver of mice fed the HFD and that FTZ treatment significantly inhibited such increase in NAFLD activity score.
## 3.3. Fibrotic Changes Associated with NLRP3 Inflammasome Activation in the Liver of Mice on the HFD with and without FTZ Treatment
In addition to steatosis and inflammatory response detected, we also examined whether there is fibrogenic pathology in the liver from different experimental groups of mice. It was found that in the hepatic interstitium, in particular, in tissues around liver sinuses, there were increased levels ofα-SMA and vimentin, as shown by immunohistochemical staining (Figure 3(a)). It is well known that increased α-SMA and vimentin indicate phenotype changes of cells from quiescent to activated status, which occurred more remarkably in HSCs. These results were semiquantitated by measurement of α-SMA and vimentin staining areas in the liver. It was shown that α-SMA and vimentin levels in the liver were significantly elevated in mice on the HFD, and this HFD-induced fibrotic change in the liver was significantly blocked by FTZ treatment (Figure 3(b)).Figure 3
Fibrogenic phenotypes in the liver from mice on the HFD with and without FTZ treatment. (a) Representative immunohistochemical images showing enhancedα-SMA and vimentin staining, which are the markers of phenotype changed from quiescent to activated in HSCs. FTZ reduced HFD-induced increase in α-SMA and vimentin staining. (b) Summarized data depicting a significant increase in α-SMA and vimentin level in the liver of mice on the HFD with and without FTZ treatment (n=4 mice per group). (c, d) Representative images and PPC showing FLICA, active caspase-1 colocalization with α-SMA or vimentin staining in the liver of mice on the HFD, which was reduced by FTZ (n=4 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group.
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(d)Since previous studies have shown that the formation and activation of NLRP3 inflammasomes in fibroblasts including HSCs may trigger the development of liver fibrosis [4], we determined whether these inflammasome-triggered fibrogenetic effects occur in NAFLD. By confocal microscopy, FLICA that indicates activated caspase-1 (green) was found to colocalize with increased α-SMA or vimentin (red) around liver sinuses and portal venules of the liver from mice on the HFD as shown by yellow spots (Figure 3(c)). In the liver from mice treated with FTZ, this enhanced colocalization of FLICA with α-SMA or vimentin was substantially reduced. By quantitative analysis of this colocalization of FLICA with α-SMA or vimentin, we found that the areas or cells with inflammasome activation had much higher level of α-SMA or vimentin, indicating the fibrogenesis during this model of NAFLD. FTZ significantly blocked this HFD-induced fibrogenic effect (Figure 3(d)).
## 3.4. PA-Induced NLRP3 Inflammasomes Formation and Increased Caspase-1 Activity in HSCs
To explore the mechanisms of NLRP3 inflammasome formation and activation in HSCs, we used palmitic acid (PA), one of the major components of saturated fatty acid, to induce lipid deposition to examine the role of NLRP3 inflammasome activation and related NASH-like changes in these cells. Confocal microscopic analysis found that the colocalization of NLRP3 with caspase-1 or ASC increased in HSCs upon PA stimulation, which indicates the aggregation or assembly of these inflammasome molecules indeed occurs in response to PA stimulation. In HSCs pretreated with FTZ extracts, there was no colocalization of NLRP3 with caspase-1 or ASC in HSCs stimulated by PA (Figure4(a)). The correlation coefficient of NLRP3 with ASC or caspase-1 showed that the colocalization of NLRP3 molecules increased significantly in HSCs stimulated by PA, which was completely blocked by FTZ, suggesting that FTZ is able to block NLRP3 inflammasome formation induced by PA in HSCs (Figure 4(b)).Figure 4
NLRP3 inflammasome formation and activation in HSCs after PA-induced steatosis with and without FTZ treatment. (a) Representative confocal fluorescence images show the colocalization of NLRP3 with caspase-1 or ASC in HSCs. (b) Correlation coefficient (PCC) showing a statistically significant increase in NLRP3 inflammasomes formation in PA-treated (200 mM/ml, 24 hours) HSCs, which was almost completely blocked by FTZ (50μg/ml, 24 hours) (n=5 batches of cells). (c) Representative Western blot gel documents showing cleaved caspase-1 increased in HSCs treated with PA but blocked by FTZ. (d) Densitometric quantitation of immunoreactive bands showing a statistically significant increase in cleaved caspase-1 after PA-treated cells (n=6 batches of cells). (e) ELISA of IL-1β levels from cell media showing a statistically significant increase induced by PA and decreased by FTZ (n=5 batches of cells). ∗p<0.05 versus Vehl-Ctrl group; #p<0.05 versus PA-Vehl group.
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(e)We also determined NLRP3 inflammasome activation by analysis of active caspase-1 and IL-1β production in HSCs with and without pretreatment with FTZ. As shown in Figures 4(c) and 4(d), PA significantly increased the level of cleaved or active caspase-1 (15 kDa) and FTZ completely blocked this PA-induced increase in active caspase-1 level. Correspondingly, biochemical analysis showed that PA induced a significant increase in IL-1β production from HSCs, which was also completely blocked by FTZ treatment. The inhibition of PA-induced IL-1β production by FTZ was similar to the effects of NAC, an often used antioxidant for suppression of NLRP3 inflammasome activation (Figure 4(e)).
## 3.5. Effects of Mouse Nlrp3 Gene Silencing on PA-Induced NLRP3 Inflammasome Activation with and without FTZ
Knockdown of mouse Nlrp3 mRNA level by Nlrp3 siRNA in HSCs remarkably inhibited PA-induced colocalization of ASC with caspase-1 (Figures5(a) and 5(b)) and attenuated PA-increased level of cleaved caspase-1 (Figure 5(c)) and both blocked by FTZ. Consistent with these findings, Nlrp3 gene silencing with or without FTZ blocked IL-1β production in HSCs (Figures 6(a) and 6(b)) and PA-induced steatosis (Figure 6(c)). These results from NLRP3 gene silencing further support that it is the NLRP3 inflammasome that contributes to inflammatory response during NASH of this model and that the effective treatment of FTZ may be due to inhibition of the NLRP3 inflammasome activation.Figure 5
Nlrp3 gene silencing inhibited PA-induced NLRP3 inflammasomes formation and activation in HSCs with and without FTZ treatment. (a) Representative fluorescence confocal microscopic images showing the colocalization of ASC with caspase-1. (b) Correction coefficient (PCC) showing a statistically significant increase in colocalization of ASC with caspase-1 in PA-treated HSCs, which was suppressed by Nlrp3 siRNA and FTZ. (c) Representative Western blot gel documents showing cleaved caspase-1 increased in HSCs treated with PA but blocked by Nlrp3 siRNA and FTZ. (d) Densitometric quantitation of immunoreactive bands showing a statistically significant decrease in cleaved caspase-1 by using Nlrp3 siRNA and FTZ (n=3 batches of cells). ∗p<0.05 versus Ctrl-scram group; #p<0.05 versus PA-scram group.
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(d)Figure 6
Nlrp3 gene silencing inhibited PA-induced NLRP3 inflammasome production and steatosis in HSCs with and without FTZ treatment. (a) Representative oil red O images showing positive staining of lipid deposition in PA-treated HSCs, which was suppressed by Nlrp3 siRNA and FTZ. (b) Staining area of lipid deposition showing a statistically significant increase induced by PA, which was reduced by Nlrp3 siRNA and FTZ. (c) ELISA of IL-1β levels from cell media showing a statistically significant decreased by Nlrp3 siRNA and with FTZ (n=3 batches of cells). ∗p<0.05 versus Ctrl-scram group; #p<0.05 versus PA-scram group.
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## 3.6. Involvement of Redox Signaling in PA-Induced NLRP3 Inflammasome Activation in HSCs and the Effect of FTZ
Since previous studies showed that the MR redox signaling platforms and redox signaling are involved in inflammasome activation [24–26], we determined whether PA-induced NLRP3 inflammasome activation is associated with this redox regulatory pathway. As measured by ESR, O2•− production significantly increased when HSCs were stimulated by PA, which was shown in largely enhanced reactive signals in ESR chromatography. FTZ had no effects on basal O2•− production but inhibited PA-induced increases in ESR signal (Figure 7(a)). By calculation and nomination to SOD-sensitive components in ESR signals, PA-induced O2•− production in HSCs was found to be completely blocked by FTZ. This FTZ-mediated inhibitory effects on PA-induced O2•− production were similar to NAC (Figure 7(b)).Figure 7
Superoxide production and NADPH oxidase-membrane raft (MR) clustering in HSCs induced by PA with and without FTZ. (a) Representative ESR traces of superoxide (O2•−) trapped by CMH using NADPH as substrate upon PA stimulation in HSCs. (b) The bar graph summarizing ESR data, showing that PA enhanced O2•− production in HSCs, which was attenuated by FTZ and NAC (n=5 batches of cells). (c) Representative fluorescence confocal microscopic images showing the colocalization of MR component labeled by CTXB with NADPH oxidase subunit gp91 or p47. (d) Correction coefficient (PCC) showing a statistically significant increase in colocalization of CTXB with gp91 or p47 in PA-treated HSCs, which was suppressed by FTZ or NAC treatment (n=5 batches of cells). ∗p<0.05 versus Ctrl-Vehl group; #p<0.05 versus PA-Vehl group.
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(d)We next used Alexa Fluor 488-labeled CTXB (a MR marker) and anti-gp91 or anti-p47 antibody (NADPH oxidase (NOX) subunits) to measure clustering of MRs with both NOX subunits, which indicates MR redox signaling platform formation to produce O2•−. PA stimulation was found to significantly increase MR clustering with gp91 or p47 NOX subunits, as shown by the yellow patches on the HSC membrane (Figure 7(c)). It is well known that this MR redox platform formation led to the activation of NOX and subsequent generation of O2•−. These results were summarized in Figure 7(d), clearly showing that PA stimulated MR redox signaling platform formation in HSC membrane and FTZ blocked this PA effect.
## 3.7. Contribution of HMGB1 from NLRP3 Inflammasome Activation to PA-Induced Lipid Deposition and to the Beneficial Effects of FTZ
As described above, our animal studies found that NLRP3 inflammasome activation not only participated in HFD-induced hepatitis and liver fibrosis but also caused steatosis in the liver. FTZ could block the development of both steatosis and sterile hepatitis in the liver. It seems that NLRP3 inflammasome activation also has uncanonical effects in NASH development which is beyond inflammation. To test this hypothesis, we addressed the role of HMGB1, an NLRP3 inflammasome product, which has been reported to increase lipid deposition [8]. As shown in Figure 8(a), the representative oil red O staining showed that PA resulted in strong staining of lipids in HSCs, which was blocked by FTZ pretreatment. The effects of PA can be mimicked by HMGB1 but inhibited by HMGB1 inhibitor, glycyrrhizin (GLY). The quantitative measurement of oil red O staining areas was summarized in Figure 8(b), showing that PA increased lipid deposition, which was blocked by FTZ. The PA-induced lipid deposition was significantly enhanced by the addition of HMGB1 but blocked by GLY, even in the presence of HMGB1.Figure 8
Involvement of HMGB1 in lipid deposition in HSCs treated with PA with and without FTZ treatment. (a) Representative oil red O images showing positive staining of lipid deposition in PA-treated HSCs, which was enhanced by HMGB1 but suppressed by FTZ and GLY, an inhibitor of HMGB1. (b) Staining area of lipid deposition showing a statistically significant increase induced by PA, which was enhanced by HMGB1, but reduced by FTZ and HMGB1 inhibitor, GLY (n=5 batches of cells). ∗p<0.05 versus PA-Vehl group; #p<0.05 versus PA-HMGB1-Vehl group.
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## 4. Discussion
The current study provides several important findings. First, it demonstrated that NLRP3 formation and activation was enhanced during the development of NASH, which was confirmed in bothin vivo animal and in vitro cell studies. Secondly, we verified the FTZ effect on NLRP3 inflammasome by using siRNA knocking down Nlrp3 gene. Thirdly, it was found that the NLRP3 inflammasome activation was inhibited by FTZ, which was accompanied by a reduction of liver lipid deposition and fibrogenic phenotype changed. It is indicated that FTZ exerts its beneficial action to not only prevent the inflammatory response but also suppress steatosis during HFD. Lastly, it showed that MR redox signaling platform formation and associated NADPH oxidase activation were involved in NLRP3 inflammasome activation and thereby contributed to the development of NASH. This MR redox signaling mechanism is responsible for liver inflammasome activation and NASH participated in the beneficial effects of FTZ against lipid deposition, inflammation, and fibrosis in the liver. The results suggest that NLRP3 inflammasome formation and activation via MR raft redox signaling platforms play a critical role in the initiation and progression of NASH and that FTZ exerts its beneficial action through inhibition of NLRP3 inflammasome activation in the liver.We first determined whether NLRP3 inflammasome formation and activation occurred during the development of NASH using a mouse model of steatosis induced by HFD. NAFLD activity scores in the 8-week HFD group are among 3 to 4, which considered borderline or positive for NASH which also considered as the early stage of NASH. It was found that this inflammasome was formed and activated in the liver, which was companied by sterile inflammation and fibrogenesis, indicating the typical pathological changes of NASH. In isolated and cultured HSCs, we further showed that PA significantly enhanced NLRP3 inflammasome formation and activation, which were also with lipid deposition and fibrogenic phenotype changed in HSCs. These results tell us that NLRP3 inflammasome activation in the liver or in HSCs may be an important early pathogenic mechanism to turn on the inflammatory response and thereby instigate liver fibrosis during NASH. This is consistent with some previous reports indicating that NLRP3 inflammasome activation plays a fundamental role in the development of NASH [3]. In other liver fibrotic animal models such as alcoholic steatosis and cirrhosis [2], viral hepatitis-induced cirrhosis [27] and hepatic fibrosis during Schistosoma J infection [4], NLRP3 inflammasome activation has also been reported to either trigger or modulate hepatic inflammation leading to fibrosis [28]. The Sirius red staining in histological liver sections showed no significant liver fibrosis and cirrhosis after 8 weeks of HFD in this mouse model. However, some staining could be seen in sinus area with more HSCs. It is possible that some HSCs become fibrotic even at weeks of HFD when NLRP3 inflammasomes are activated (Supplementary Figure 3). Taken together, it is clear that NLRP3 inflammasome as intracellular inflammatory machinery is essential for the development of NASH and other liver fibrotic diseases.Although chronic inflammation is a hallmark of NASH, the classic anti-inflammatory medicines, such as commonly used indole and arylpropionic acid derivatives are not very efficient in the prevention or treatment of NASH [29]. This may be mainly because these classical anti-inflammatory strategies may not target the noninflammatory or noncanonical effects during NLRP3 inflammasome activation in the development of NASH [6], and therefore they may only have a limited therapeutic effect. This led us to think that the NLRP3 inflammasome and its regulatory pathways may be an ideal target for treatment of chronic degenerative diseases like NASH with multiple pathological processes. Given our long-lasting interest in FTZ, a widely used herbal remedy for metabolic syndrome and hyperlipidemia and related complications in China, we tested whether FTZ exerts its action through inhibition of NLRP3 inflammasome formation and activation. In our studies with an animal model of NASH induced by HFD and with cultured HSCs stimulated by PA, we demonstrated that FTZ remarkably inhibited the formation and activation of NLRP3 inflammasomes. This inhibitory effects of FTZ on NLRP3 inflammasome activation reduced both hepatic inflammation and steatosis. Furthermore, this NLRP3 inhibition was also found to abrogate fibrotic process in the liver during NASH. It appears that FTZ indeed exerts its beneficial action in preventing NASH through suppression of NLRP3 inflammasome activation in the liver. To our knowledge, the findings from the present study for the first time link the therapeutic effect of FTZ to NLRP3 inflammasome activation, which serves as a molecular mechanism of the FTZ action.FTZ has been prescribed over the last 15 years for treatment of hyperlipidemia and metabolic syndrome and related complications such as atherosclerosis and NASH [11, 12]. Previous studies have demonstrated that FTZ attenuated metabolic syndrome- (MS-) associated symptoms and pathological changes in tissues or cells, which was attributed to the decreases in the plasma levels of glucose and lipids [30]. In addition, some studies have shown that FTZ attenuated the downregulation of PI3K p85 mRNA and IRS1 protein in both insulin-resistant HepG2 cells and MS rats [30]. In a recent study, some components of FTZ were found to prevent the development of fatty liver in rats [13]. However, these studies did not elucidate the precise mechanisms how FTZ works to inhibit liver inflammation and to change fibrogenic phenotype. In the present study, we not only demonstrated that the suppression of NLRP3 inflammasome as an intracellular inflammatory machinery during NASH is an underlying mechanism responsible for the anti-inflammatory action of FTZ but also interestingly confirmed that FTZ inhibits lipid deposition in liver cells by the blockade of NLRP3 inflammasome-mediated HMGB1 production. It is believed that through inhibition of NLRP3 inflammasome activation FTZ may work to interfere with the early lipid deposition process and the late induction of hepatic inflammation and fibrosis during the progression of NASH. In previous studies, cholesterol, free fatty acids, and triglycerides were found to store in HSCs, which may activate these cells to become fibrogenic initiating or promoting liver fibrosis. Activated HSCs could sensitize the cell injury to further enhance lipid accumulation when there is increased intake of cholesterol, which may lead a vicious cycle in NASH, namely, accumulated lipids activating HSCs and the latter resulting in more accumulation of lipids in these cells [31]. The results from the present study provide the first experimental evidence that HMGB1 release derived from NLRP3 inflammasome-dependent caspase-1 activity may be involved in this lipid deposition process as shown in some other studies [5, 32, 33]. This action of HMGB1 can be blocked by FTZ treatment.We also explored the mechanisms by which FTZ inhibits NLRP3 inflammasome formation and activation and thereby prevent NASH development. It was demonstrated that FTZ inhibited MR redox signaling platform formation to produce O2•−. This action further blocked NLRP3 inflammasome formation and activation in HFD-induced NASH in mice or in PA-stimulated HSCs. Although there are reports that in chronic liver disease oxidative stress has a clear role in HSC activation triggering fibrotic process [34], the results from the present study are the first to clarify that local oxidative stress may induce HSC activation and liver fibrosis through NLRP3 inflammasomes. FTZ may target this very early event of NASH to prevent the degenerative outcome of this liver disease. All these roles of NLRP3 inflammasomes in NASH and the beneficial effects of FTZ are diagrammatically summarized in Figure 9.Figure 9
A schematic illustration of plausible mechanisms by which FTZ inhibits the NLRP3 inflammasome formation and activation and thus ameliorates steatohepatitis or NASH.In summary, the present study demonstrated that increased NLRP3 inflammasome formation and activation are an important pathogenic mechanism initiating and promoting the development of NASH. FTZ suppressed this NLRP3 inflammasome activation to prevent steatosis, hepatic inflammation, and fibrogenic phenotype changed. This beneficial action of FTZ through the inhibition of NLRP3 inflammasome activation was not only associated with suppression of liver inflammation and HSCs activation leading to fibrogenesis but also with the early event of lipid deposition triggering steatosis. Furthermore, we showed that the inhibitory effect of FTZ on the NLRP3 inflammasome activation was due to blockade of MR redox signaling platform formation and subsequent O2•− production.
## 5. Conclusion
The present study demonstrates that FTZ extracts inhibit NASH by its action on both inflammatory response and lipid metabolism associated with NLRP3 inflammasome activation in the liver. Targeting NLRP3 inflammasome to reduce steatosis, sterile liver inflammation, and consequent fibrosis may be an underlying mechanism for the therapeutic action of FTZ on NASH and possibly on other end-organ damage induced by metabolic syndrome.
---
*Source: 2901871-2018-07-22.xml* | 2901871-2018-07-22_2901871-2018-07-22.md | 66,212 | NLRP3 Inflammasome Formation and Activation in Nonalcoholic Steatohepatitis: Therapeutic Target for Antimetabolic Syndrome Remedy FTZ | Yu Chen; Xingxiang He; Xinxu Yuan; Jinni Hong; Owais Bhat; Guangbi Li; Pin-Lan Li; Jiao Guo | Oxidative Medicine and Cellular Longevity
(2018) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2018/2901871 | 2901871-2018-07-22.xml | ---
## Abstract
The Nod-like receptor protein 3 (NLRP3) inflammasome activation not only serves as an intracellular machinery triggering inflammation but also produces uncanonical effects beyond inflammation such as changing cell metabolism and increasing cell membrane permeability. The present study was designed to test whether this NLRP3 inflammasome activation contributes to the “two-hit” injury during nonalcoholic steatohepatitis (NASH) and whether it can be a therapeutic target for the action of Fufang Zhenzhu Tiaozhi (FTZ), a widely used herbal remedy for hyperlipidemia and metabolic syndrome in China. We first demonstrated that NLRP3 inflammasome formation and activation as well as lipid deposition occurred in the liver of mice on the high-fat diet (HFD), as shown by increased NLRP3 aggregation, enhanced production of IL-1β and high mobility group box 1 (HMGB1), and remarkable lipid deposition in liver cells. FTZ extracts not only significantly reduced the NLRP3 inflammasome formation and activation but also attenuated the liver steatosis and fibrogenic phenotype changed. In in vitro studies, palmitic acid (PA) was found to increase colocalization of NLRP3 components and enhanced caspase-1 activity in hepatic stellate cells (HSCs), indicating enhanced formation and activation of NLRP3 inflammasomes by PA. PA also increased lipid deposition. Nlrp3 siRNA can reverse this effect by silencing the NLRP3 inflammasome and both with FTZ. In FTZ-treated cells, not only inflammasome formation and activation was substantially attenuated but also lipid deposition in HSCs was blocked. This inhibition of FTZ on lipid deposition was similar to the effects of glycyrrhizin, an HMGB1 inhibitor. Mechanistically, stimulated membrane raft redox signaling platform formation and increased O2•− production by PA to activate NLRP3 inflammasomes in HSCs was blocked by FTZ treatment. It is concluded that FTZ extracts inhibit NASH by its action on both inflammatory response and liver lipid metabolism associated with NLRP3 inflammasome formation and activation.
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## Body
## 1. Introduction
Nonalcoholic fatty liver disease (NAFLD) is the most common liver disease throughout the world. NAFLD may either be present as a simple steatosis (nonalcoholic fatty liver) or evolves towards its inflammatory complication (10–20%), namely, nonalcoholic steatohepatitis (NASH), which can further progress towards liver cirrhosis and hepatocellular carcinoma, a complication that occurs increasingly in the noncirrhotic NAFLD population [1]. It is generally accepted that the pathogenesis of NASH is involved in a two-step process, which is referred to as a “two-hit” model. The first “hit” is associated with excessive triglyceride or other lipid accumulation in the liver, and the second “hit” leads to the development of liver inflammation and fibrosis, which is attributed to several important pathogenic factors that can eventually induce liver damage such as inflammatory cytokines, oxidative stress, mitochondrial dysfunction, and/or endoplasmic reticulum stress. Recent studies have indicated that the Nod-like receptor protein 3 (NLRP3) inflammasome activation may play a fundamental role in the development of NASH [2, 3]. Since NLRP3 inflammasome has been reported to not only activate the inflammatory response but also possess noncanonical or noninflammatory action that may contribute to the progression of some chronic degenerative or fibrotic diseases [4–7], it is possible that the activation of NLRP3 inflammasome mediates NASH development via the “two-hit” mechanism. We hypothesized that not only hepatitis and consequent fibrosis but also liver steatosis in the progression of NASH may be triggered or modulated by NLRP3 inflammasome activation. In this regard, recent studies indeed demonstrated that in addition to classical inflammatory cytokines such as IL-1β and IL-18, HMGB1 released during NLRP3 inflammasome activation is also importantly implicated in both liver steatosis and subsequent hepatitis or fibrosis [8–10]. These inflammatory and uncanonical or noninflammatory effects of NLRP3 inflammasomes on the development of NASH has been the main theme in the present study.The noncanonical effects during NLRP3 inflammasome activation may answer a long-lasting question of why classic anti-inflammatory medicines, such as commonly used indole and arylpropionic acid derivatives, are not very efficient in the prevention or treatment of many degenerative diseases including NASH, where chronic inflammation are its hallmarks. It may be promising to target the NLRP3 inflammasome and thereby block the “two-hit” mechanisms during NASH. In this regard, a candidate may be Fufang Zhenzhu Tiaozhi (FTZ), a widely used herbal remedy for hyperlipidemia and metabolic syndrome in China, which showed its cocktail therapeutic efficiency. FTZ that has been patented in both the USA and China is a mixture extracted from the Chinese herbal prescription, consisting ofRhizoma coptidis, Fructus Ligustri Lucidi, Herba cirsii japonici, Radix Salvia miltiorrhiza, Radix Notoginseng, Cortex Eucommiae, Fructus Citri Sarcodactylis, and Radix Atractylodes macrocephala. FTZ has been prescribed over the last 15 years for treatment of hyperlipidemia and metabolic syndrome and related complications such as atherosclerosis and NASH [11, 12]. In a recent study, some components of FTZ were found to prevent the development of fatty liver in rats [13]. However, the mechanism mediating its action remains unknown. In the present study, after characterization of roles in which NLRP3 inflammasomes play in NASH, we also examined whether FTZ prevents NASH development by targeting the effects of NLRP3 inflammasome activation on both inflammatory response and steatosis in the liver.
## 2. Material and Methods
### 2.1. Animals
C57BL/6J mice (8 weeks of age, male or female) were fed a normal diet (ND) or a high-fat diet (HFD, number D12492, Research Diets, NJ, USA) for 4 weeks, and then FTZ extracts (100 mg/kg/day) were fed by gavage for the last 4 weeks both with HFD. The preparation of FTZ extracts for mice was consistent with the protocol described previously [14]. All mice were randomly distributed to different experimental groups. At the endpoint of the experimental period, blood samples were collected and these mice were then sacrificed for harvest of the liver tissues, which were used for oil red O staining, immunofluorescence staining, and biochemical analysis. All protocols were approved by the Institutional Animal Care and Use Committee of the Virginia Commonwealth University.
### 2.2. Cell Culture and Treatments
Mouse hepatic stellate cells (HSCs) were prepared by the discontinuous density gradient centrifugation technique as previously described, and some minor modifications were made to increase success rate as we described previously [4]. The collected cells were cultured in DMEM (Gibco, Carlsbad, CA, USA) containing 10% FBS (Gibco) in humidified 95% air and 5% CO2 mixture at 37°C. The cell viability, as measured by a Trypan Blue exclusion assay, was approximately 90%. HSCs were treated with palmitic acid (PA, 200 μM/ml) for indicated hours. HSCs were characterized and confirmed as previously described [15]. We chose to work on HSCs, because they are a major cell type responsible for the progression of liver fibrosis. Our previous studies have shown that NLRP3 inflammasome activation is mainly responsible for the development of liver fibrosis [3, 4]. Our preliminary experiments demonstrated that the optimum response of inflammasome activation occurred over 24-hour PA treatment in HSC cultures, and therefore all experiments in our cell study protocols used the same duration of PA before and after treatments of FTZ extracts (50 μg/ml, prepared by DMSO and diluted with medium in 1 : 1000) or administration of inflammasome inhibitors or blockers such as ROS scavenger N-acetyl-L-cysteine (NAC, 10 μM, Sigma, St. Louis, MO, USA).
### 2.3. Oil Red O Staining
For oil red O staining, the liver tissue slides and HSCs grown on a chamber with coverslips were used as described previously [16] with minor modifications. HSCs (104 cells/well) cultured in a chamber with glass coverslips were treated as indicated and loaded with PA for 24 hours. Frozen liver tissue slides and the HSC coverslips were then stained with oil red O (0.1% in isopropanol) for determination of lipid accumulation. The oil red O staining was examined by light microscopy, and images were obtained by MetaMorph 6.0. The data was represented by the area percentage of each cell positive for oil red O stain, which was calculated in Image Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD, USA). For each sample, at least 200 cells were analyzed and summarized oil red O positive cell counts were used for statistical analysis.
### 2.4. Confocal Microscopic Analysis
For confocal analysis of inflammasome molecule colocalization or aggregation, the liver tissue slides and HSCs grown on a chamber with coverslips were used. They were first fixed in 4% paraformaldehyde in phosphate-buffered saline (PFA/PBS) for 15 min. After being permeabilized with 0.1% Triton X-100/PBS and rinsed with PBS, the slides were incubated overnight at 4°C with anti-NLRP3 (1 : 200, Abcam, MA, USA) and anti-ASC (1 : 50, Enzo, PA, USA) or anti-caspase-1 (1 : 100, Abcam). After washing, these slides incubated with primary antibodies were then incubated with Alexa-488- or Alexa-555-labeled secondary antibodies for 1 h at room temperature. The slides were mounted and subjected to examinations using a confocal laser scanning microscope (Fluoview FV1000, Olympus, Japan) with photos being taken and the colocalization of NLRP3 with ASC or caspase-1 analyzed by the Image-Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD, USA). The summarized data of molecular colocalization efficiency was expressed as correlation coefficient as we described previously [17–19].FLICA Staining. During the last hour of incubation, cells were labeled with FAM-YVAD-fmk caspase-1 FLICA™ kit (Immunochemistry, Bloomington, IN, USA) according to the manufacturer’s guidelines, which binds activated caspase-1. Stained cells were visualized by confocal microscopy for active caspase-1 oligomerization, which was colocalized with fibrotic markers vimentin (with antibody staining at 1 : 200) and α-smooth muscle actin (α-SMA, with antibody at 1 : 200).Immunofluorescent Microscopic Analysis of Membrane Raft (MR) Clusters. HSCs were grown on glass coverslips. After fixation with 4% PFA, cells were incubated with Alexa Fluor 488-conjugated cholera toxin B (Alexa488-CTXB, 2 μg/ml, 2 h, Molecular Probes, CA, USA), which binds with the MR-enriched ganglioside GM1. For dual-staining detection of the colocalization of MRs with gp91phox and p47phox, the cells were first incubated with Alexa488-CTXB and then with anti-gp91phox and p47phox (1: 200, BD Biosciences, CA, USA), respectively, which was followed by corresponding Alexa555-conjugated secondary antibodies (1: 500, Invitrogen, NY, USA). Then, the colocalization was visualized with confocal microscopy [20, 21].
### 2.5. Immunohistochemistry
Liver tissues were fixed in 4% (v/v) paraformaldehyde (PFA) in PBS and embedded with paraffin, which were then sliced into tissue sections (4 μM) and mounted on glass slides. These tissue slides were stained with goat anti-IL-1β antibody (1 : 100, R&D Systems) overnight at 4°C after a 20 min wash with 3% H2O2 and 30 min blocking with 10% serum and then probed with anti-goat Ig-G second antibody labeled with HRP according to the protocols described previously [18, 22]. Negative controls were prepared without the primary antibodies. The area percentage of the positive staining was calculated in Image Pro Plus 6.0 software.
### 2.6. Western Blot Analysis
Proteins from cell lysates were denatured with SDS buffer and boiled for 5 minutes. Samples were run on a SDS-PAGE gel, transferred onto polyvinylidene difluoride (PVDF) membrane, and blocked with 5% milk. Then, the membranes were probed with the following primary antibodies overnight at 4°C: rabbit anti-caspase-1 (1 : 500, Santa Cruz, CA, USA) and rabbit anti-β-actin (1 : 10000, Santa Cruz). They were incubated with goat anti-rabbit-HRP Ig-G (1 : 5000, Santa Cruz) for 1 hour at room temperature. Immunoreactive bands were detected by chemiluminescence techniques after washing three times and then visualized on Kodak Omat X-ray film. The intensity of the specific bands was calculated using ImageJ software version 1.44p.
### 2.7. Il-1β Elisa
After PA treatment with or without pretreatments of inhibitors, the cell supernatant was also collected to measure IL-1β production by a mouse IL-1β ELISA kit (Bender MedSystems, CA, USA) according to the protocol described by the manufacturer. The data was expressed as the fold change compared with control cells.
### 2.8. Electromagnetic Spin Resonance (ESR) Spectrometry
For detection of NADPH oxidase-dependent O2•− production, protein was gently isolated from 1 × 106 cells and resuspended with modified Krebs–4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid buffer containing deferoximine (100 μM, Sigma) and diethyldithiocarbamate (5 μM; Sigma). A spin trap, 1-hydroxy-3- methoxycarbonyl-2,2,5,5-tetramethylpyrrolidine (CMH, NOXygen, Elzach, Germany) (1 mM final concentration) was then added to the mixture in the presence or absence of manganese-dependent superoxide dismutase (SOD, 200 U/ml; Sigma). The mixtures were loaded into glass capillaries and immediately analyzed for O2•− formation kinetics for 10 min in a MiniScope MS200 ESR spectrometer (Magnettech, Berlin, Germany). The ESR spectrometer was set according to the following parameters: biofield, 3350; field sweep, 60 G; microwave frequency, 9.78 GHz; microwave power, 20 mW; modulation amplitude, 3 G; 4096 points of resolution; and receiver gain, 50. The ESR spectrometric signal was recorded in arbitrary units, and the final results were expressed as the fold changes of the treatment group compared to control as we described previously [23].
### 2.9. Statistics
Data are presented as means ± standard error mean. The significant differences between and within multiple groups were examined using one-way or two-way ANOVA, followed by Duncan’s multiple-range test.p<0.05 was considered statistically significant.
## 2.1. Animals
C57BL/6J mice (8 weeks of age, male or female) were fed a normal diet (ND) or a high-fat diet (HFD, number D12492, Research Diets, NJ, USA) for 4 weeks, and then FTZ extracts (100 mg/kg/day) were fed by gavage for the last 4 weeks both with HFD. The preparation of FTZ extracts for mice was consistent with the protocol described previously [14]. All mice were randomly distributed to different experimental groups. At the endpoint of the experimental period, blood samples were collected and these mice were then sacrificed for harvest of the liver tissues, which were used for oil red O staining, immunofluorescence staining, and biochemical analysis. All protocols were approved by the Institutional Animal Care and Use Committee of the Virginia Commonwealth University.
## 2.2. Cell Culture and Treatments
Mouse hepatic stellate cells (HSCs) were prepared by the discontinuous density gradient centrifugation technique as previously described, and some minor modifications were made to increase success rate as we described previously [4]. The collected cells were cultured in DMEM (Gibco, Carlsbad, CA, USA) containing 10% FBS (Gibco) in humidified 95% air and 5% CO2 mixture at 37°C. The cell viability, as measured by a Trypan Blue exclusion assay, was approximately 90%. HSCs were treated with palmitic acid (PA, 200 μM/ml) for indicated hours. HSCs were characterized and confirmed as previously described [15]. We chose to work on HSCs, because they are a major cell type responsible for the progression of liver fibrosis. Our previous studies have shown that NLRP3 inflammasome activation is mainly responsible for the development of liver fibrosis [3, 4]. Our preliminary experiments demonstrated that the optimum response of inflammasome activation occurred over 24-hour PA treatment in HSC cultures, and therefore all experiments in our cell study protocols used the same duration of PA before and after treatments of FTZ extracts (50 μg/ml, prepared by DMSO and diluted with medium in 1 : 1000) or administration of inflammasome inhibitors or blockers such as ROS scavenger N-acetyl-L-cysteine (NAC, 10 μM, Sigma, St. Louis, MO, USA).
## 2.3. Oil Red O Staining
For oil red O staining, the liver tissue slides and HSCs grown on a chamber with coverslips were used as described previously [16] with minor modifications. HSCs (104 cells/well) cultured in a chamber with glass coverslips were treated as indicated and loaded with PA for 24 hours. Frozen liver tissue slides and the HSC coverslips were then stained with oil red O (0.1% in isopropanol) for determination of lipid accumulation. The oil red O staining was examined by light microscopy, and images were obtained by MetaMorph 6.0. The data was represented by the area percentage of each cell positive for oil red O stain, which was calculated in Image Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD, USA). For each sample, at least 200 cells were analyzed and summarized oil red O positive cell counts were used for statistical analysis.
## 2.4. Confocal Microscopic Analysis
For confocal analysis of inflammasome molecule colocalization or aggregation, the liver tissue slides and HSCs grown on a chamber with coverslips were used. They were first fixed in 4% paraformaldehyde in phosphate-buffered saline (PFA/PBS) for 15 min. After being permeabilized with 0.1% Triton X-100/PBS and rinsed with PBS, the slides were incubated overnight at 4°C with anti-NLRP3 (1 : 200, Abcam, MA, USA) and anti-ASC (1 : 50, Enzo, PA, USA) or anti-caspase-1 (1 : 100, Abcam). After washing, these slides incubated with primary antibodies were then incubated with Alexa-488- or Alexa-555-labeled secondary antibodies for 1 h at room temperature. The slides were mounted and subjected to examinations using a confocal laser scanning microscope (Fluoview FV1000, Olympus, Japan) with photos being taken and the colocalization of NLRP3 with ASC or caspase-1 analyzed by the Image-Pro Plus 6.0 software (Media Cybernetics, Bethesda, MD, USA). The summarized data of molecular colocalization efficiency was expressed as correlation coefficient as we described previously [17–19].FLICA Staining. During the last hour of incubation, cells were labeled with FAM-YVAD-fmk caspase-1 FLICA™ kit (Immunochemistry, Bloomington, IN, USA) according to the manufacturer’s guidelines, which binds activated caspase-1. Stained cells were visualized by confocal microscopy for active caspase-1 oligomerization, which was colocalized with fibrotic markers vimentin (with antibody staining at 1 : 200) and α-smooth muscle actin (α-SMA, with antibody at 1 : 200).Immunofluorescent Microscopic Analysis of Membrane Raft (MR) Clusters. HSCs were grown on glass coverslips. After fixation with 4% PFA, cells were incubated with Alexa Fluor 488-conjugated cholera toxin B (Alexa488-CTXB, 2 μg/ml, 2 h, Molecular Probes, CA, USA), which binds with the MR-enriched ganglioside GM1. For dual-staining detection of the colocalization of MRs with gp91phox and p47phox, the cells were first incubated with Alexa488-CTXB and then with anti-gp91phox and p47phox (1: 200, BD Biosciences, CA, USA), respectively, which was followed by corresponding Alexa555-conjugated secondary antibodies (1: 500, Invitrogen, NY, USA). Then, the colocalization was visualized with confocal microscopy [20, 21].
## 2.5. Immunohistochemistry
Liver tissues were fixed in 4% (v/v) paraformaldehyde (PFA) in PBS and embedded with paraffin, which were then sliced into tissue sections (4 μM) and mounted on glass slides. These tissue slides were stained with goat anti-IL-1β antibody (1 : 100, R&D Systems) overnight at 4°C after a 20 min wash with 3% H2O2 and 30 min blocking with 10% serum and then probed with anti-goat Ig-G second antibody labeled with HRP according to the protocols described previously [18, 22]. Negative controls were prepared without the primary antibodies. The area percentage of the positive staining was calculated in Image Pro Plus 6.0 software.
## 2.6. Western Blot Analysis
Proteins from cell lysates were denatured with SDS buffer and boiled for 5 minutes. Samples were run on a SDS-PAGE gel, transferred onto polyvinylidene difluoride (PVDF) membrane, and blocked with 5% milk. Then, the membranes were probed with the following primary antibodies overnight at 4°C: rabbit anti-caspase-1 (1 : 500, Santa Cruz, CA, USA) and rabbit anti-β-actin (1 : 10000, Santa Cruz). They were incubated with goat anti-rabbit-HRP Ig-G (1 : 5000, Santa Cruz) for 1 hour at room temperature. Immunoreactive bands were detected by chemiluminescence techniques after washing three times and then visualized on Kodak Omat X-ray film. The intensity of the specific bands was calculated using ImageJ software version 1.44p.
## 2.7. Il-1β Elisa
After PA treatment with or without pretreatments of inhibitors, the cell supernatant was also collected to measure IL-1β production by a mouse IL-1β ELISA kit (Bender MedSystems, CA, USA) according to the protocol described by the manufacturer. The data was expressed as the fold change compared with control cells.
## 2.8. Electromagnetic Spin Resonance (ESR) Spectrometry
For detection of NADPH oxidase-dependent O2•− production, protein was gently isolated from 1 × 106 cells and resuspended with modified Krebs–4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid buffer containing deferoximine (100 μM, Sigma) and diethyldithiocarbamate (5 μM; Sigma). A spin trap, 1-hydroxy-3- methoxycarbonyl-2,2,5,5-tetramethylpyrrolidine (CMH, NOXygen, Elzach, Germany) (1 mM final concentration) was then added to the mixture in the presence or absence of manganese-dependent superoxide dismutase (SOD, 200 U/ml; Sigma). The mixtures were loaded into glass capillaries and immediately analyzed for O2•− formation kinetics for 10 min in a MiniScope MS200 ESR spectrometer (Magnettech, Berlin, Germany). The ESR spectrometer was set according to the following parameters: biofield, 3350; field sweep, 60 G; microwave frequency, 9.78 GHz; microwave power, 20 mW; modulation amplitude, 3 G; 4096 points of resolution; and receiver gain, 50. The ESR spectrometric signal was recorded in arbitrary units, and the final results were expressed as the fold changes of the treatment group compared to control as we described previously [23].
## 2.9. Statistics
Data are presented as means ± standard error mean. The significant differences between and within multiple groups were examined using one-way or two-way ANOVA, followed by Duncan’s multiple-range test.p<0.05 was considered statistically significant.
## 3. Results
### 3.1. NLRP3 Inflammasome Formation and Activation in the Liver of Mice on the HFD with and without Treatment of FTZ
By confocal microscopy, we found that there was significantly elevated colocalization of NLRP3 with ASC or caspase-1 in the liver of mice on the HFD compared with mice on the ND, indicating enhanced formation of NLRP3 inflammasomes. In mice receiving FTZ, HFD-induced increases in colocalization of NLRP3 inflammasome components were substantially blocked (Figure1(a)). Quantitation of the NLRP3 colocalization by measurement of correlation coefficient is presented in Figure 1(b), showing that NLRP3 inflammasome formation was significantly enhanced in mice on the HFD diet compared to mice on the ND and this enhanced NLRP3 inflammasome formation in the liver of mice on the HFD was significantly attenuated by FTZ.Figure 1
NLRP3 inflammasome formation and activation in the liver from mice on the HFD with and without FTZ treatment. (a) Representative confocal fluorescence images show the colocalization of NLRP3 with caspase-1 or ASC. (b) Correlation coefficient showing a statistically significant increase in NLRP3 inflammasome formation in HFD for 8 weeks with and without FTZ treatment (100 mg/kg/day) by gavage for 4 weeks (n=5 mice per group). (c) Representative immunohistochemical images show positive stain of IL-1β and IL-18 in the liver. (d) Positive staining area of IL-1β and IL-18 showing a statistically significant increase after NLRP3 inflammasome formation in the liver of mice on the HFD, which was suppressed by FTZ (n=4 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group.
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(d)Immunohistochemical analysis showed that both IL-1β and IL-18 (Figure 1(c)) levels significantly increased around fatty hepatocytes in the liver of mice on the HFD, suggesting activation of the inflammasome in these cells. FTZ treatment remarkably reduced this HFD-induced increase in hepatic IL-1β and IL-18. As shown in Figure 1(d), the positive staining areas of hepatic IL-1β and IL-18 were significantly increased in mice on the HFD without treatment of FTZ. In mice receiving FTZ, the increased IL-1β and IL-18 staining in the liver of mice on the HFD was significantly suppressed. It is clear that FTZ can inhibit the activation of NLRP3 inflammasomes in the liver.
### 3.2. Steatosis and NASH in the Liver of Mice on the HFD with and without FTZ Treatment
Steatosis as an important pathological change of NASH was analyzed in mice on the HFD. By oil red O staining, it was found that HFD caused a significant increase in lipid deposition in the liver of mice without treatment of FTZ. This enhanced oil red O staining in the liver was markedly reduced when mice were treated with FTZ (Figure2(a)). The quantitation of tissue areas stained by oil red O showed that more than 40% of the liver in mice on the HFD were with lipid deposition. Treatment of mice with FTZ significantly attenuated this HFD-induced lipid deposition in the liver (Figure 2(b)). It is clear that FTZ significantly prevented steatosis in mice fed with HFD.Figure 2
Steatosis and hepatitis in the liver from mice on the HFD with and without FTZ treatment. (a) Representative oil red O staining shows positive staining of lipid deposition in the liver. (b) Positive staining area of lipid deposition showing statistically significant increases after HFD, which was suppressed by FTZ (n=5 mice per group). (c) Representative H&E staining images showing inflammatory infiltration and fatty bulbs in liver cells after HFD which was attenuated by FTZ. (d) NAFLD activity score showing statistically significant increases after HFD for 8 weeks with and without FTZ treatment (n=5 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group
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(d)By H&E staining, we also examined the morphological changes in the liver of mice from different experimental groups. As shown in Figure2(c), besides lipid deposition the liver from mice on the HFD exhibited obvious inflammatory cell infiltration and increases in protein leakage into interstitial space. However, the liver from mice receiving FTZ almost lacked these inflammatory changes. Figure 2(d) depicts the results from the analysis of NAFLD activity score, showing that the increase in NAFLD activity score was highly significant in the liver of mice fed the HFD and that FTZ treatment significantly inhibited such increase in NAFLD activity score.
### 3.3. Fibrotic Changes Associated with NLRP3 Inflammasome Activation in the Liver of Mice on the HFD with and without FTZ Treatment
In addition to steatosis and inflammatory response detected, we also examined whether there is fibrogenic pathology in the liver from different experimental groups of mice. It was found that in the hepatic interstitium, in particular, in tissues around liver sinuses, there were increased levels ofα-SMA and vimentin, as shown by immunohistochemical staining (Figure 3(a)). It is well known that increased α-SMA and vimentin indicate phenotype changes of cells from quiescent to activated status, which occurred more remarkably in HSCs. These results were semiquantitated by measurement of α-SMA and vimentin staining areas in the liver. It was shown that α-SMA and vimentin levels in the liver were significantly elevated in mice on the HFD, and this HFD-induced fibrotic change in the liver was significantly blocked by FTZ treatment (Figure 3(b)).Figure 3
Fibrogenic phenotypes in the liver from mice on the HFD with and without FTZ treatment. (a) Representative immunohistochemical images showing enhancedα-SMA and vimentin staining, which are the markers of phenotype changed from quiescent to activated in HSCs. FTZ reduced HFD-induced increase in α-SMA and vimentin staining. (b) Summarized data depicting a significant increase in α-SMA and vimentin level in the liver of mice on the HFD with and without FTZ treatment (n=4 mice per group). (c, d) Representative images and PPC showing FLICA, active caspase-1 colocalization with α-SMA or vimentin staining in the liver of mice on the HFD, which was reduced by FTZ (n=4 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group.
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(d)Since previous studies have shown that the formation and activation of NLRP3 inflammasomes in fibroblasts including HSCs may trigger the development of liver fibrosis [4], we determined whether these inflammasome-triggered fibrogenetic effects occur in NAFLD. By confocal microscopy, FLICA that indicates activated caspase-1 (green) was found to colocalize with increased α-SMA or vimentin (red) around liver sinuses and portal venules of the liver from mice on the HFD as shown by yellow spots (Figure 3(c)). In the liver from mice treated with FTZ, this enhanced colocalization of FLICA with α-SMA or vimentin was substantially reduced. By quantitative analysis of this colocalization of FLICA with α-SMA or vimentin, we found that the areas or cells with inflammasome activation had much higher level of α-SMA or vimentin, indicating the fibrogenesis during this model of NAFLD. FTZ significantly blocked this HFD-induced fibrogenic effect (Figure 3(d)).
### 3.4. PA-Induced NLRP3 Inflammasomes Formation and Increased Caspase-1 Activity in HSCs
To explore the mechanisms of NLRP3 inflammasome formation and activation in HSCs, we used palmitic acid (PA), one of the major components of saturated fatty acid, to induce lipid deposition to examine the role of NLRP3 inflammasome activation and related NASH-like changes in these cells. Confocal microscopic analysis found that the colocalization of NLRP3 with caspase-1 or ASC increased in HSCs upon PA stimulation, which indicates the aggregation or assembly of these inflammasome molecules indeed occurs in response to PA stimulation. In HSCs pretreated with FTZ extracts, there was no colocalization of NLRP3 with caspase-1 or ASC in HSCs stimulated by PA (Figure4(a)). The correlation coefficient of NLRP3 with ASC or caspase-1 showed that the colocalization of NLRP3 molecules increased significantly in HSCs stimulated by PA, which was completely blocked by FTZ, suggesting that FTZ is able to block NLRP3 inflammasome formation induced by PA in HSCs (Figure 4(b)).Figure 4
NLRP3 inflammasome formation and activation in HSCs after PA-induced steatosis with and without FTZ treatment. (a) Representative confocal fluorescence images show the colocalization of NLRP3 with caspase-1 or ASC in HSCs. (b) Correlation coefficient (PCC) showing a statistically significant increase in NLRP3 inflammasomes formation in PA-treated (200 mM/ml, 24 hours) HSCs, which was almost completely blocked by FTZ (50μg/ml, 24 hours) (n=5 batches of cells). (c) Representative Western blot gel documents showing cleaved caspase-1 increased in HSCs treated with PA but blocked by FTZ. (d) Densitometric quantitation of immunoreactive bands showing a statistically significant increase in cleaved caspase-1 after PA-treated cells (n=6 batches of cells). (e) ELISA of IL-1β levels from cell media showing a statistically significant increase induced by PA and decreased by FTZ (n=5 batches of cells). ∗p<0.05 versus Vehl-Ctrl group; #p<0.05 versus PA-Vehl group.
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(e)We also determined NLRP3 inflammasome activation by analysis of active caspase-1 and IL-1β production in HSCs with and without pretreatment with FTZ. As shown in Figures 4(c) and 4(d), PA significantly increased the level of cleaved or active caspase-1 (15 kDa) and FTZ completely blocked this PA-induced increase in active caspase-1 level. Correspondingly, biochemical analysis showed that PA induced a significant increase in IL-1β production from HSCs, which was also completely blocked by FTZ treatment. The inhibition of PA-induced IL-1β production by FTZ was similar to the effects of NAC, an often used antioxidant for suppression of NLRP3 inflammasome activation (Figure 4(e)).
### 3.5. Effects of Mouse Nlrp3 Gene Silencing on PA-Induced NLRP3 Inflammasome Activation with and without FTZ
Knockdown of mouse Nlrp3 mRNA level by Nlrp3 siRNA in HSCs remarkably inhibited PA-induced colocalization of ASC with caspase-1 (Figures5(a) and 5(b)) and attenuated PA-increased level of cleaved caspase-1 (Figure 5(c)) and both blocked by FTZ. Consistent with these findings, Nlrp3 gene silencing with or without FTZ blocked IL-1β production in HSCs (Figures 6(a) and 6(b)) and PA-induced steatosis (Figure 6(c)). These results from NLRP3 gene silencing further support that it is the NLRP3 inflammasome that contributes to inflammatory response during NASH of this model and that the effective treatment of FTZ may be due to inhibition of the NLRP3 inflammasome activation.Figure 5
Nlrp3 gene silencing inhibited PA-induced NLRP3 inflammasomes formation and activation in HSCs with and without FTZ treatment. (a) Representative fluorescence confocal microscopic images showing the colocalization of ASC with caspase-1. (b) Correction coefficient (PCC) showing a statistically significant increase in colocalization of ASC with caspase-1 in PA-treated HSCs, which was suppressed by Nlrp3 siRNA and FTZ. (c) Representative Western blot gel documents showing cleaved caspase-1 increased in HSCs treated with PA but blocked by Nlrp3 siRNA and FTZ. (d) Densitometric quantitation of immunoreactive bands showing a statistically significant decrease in cleaved caspase-1 by using Nlrp3 siRNA and FTZ (n=3 batches of cells). ∗p<0.05 versus Ctrl-scram group; #p<0.05 versus PA-scram group.
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(d)Figure 6
Nlrp3 gene silencing inhibited PA-induced NLRP3 inflammasome production and steatosis in HSCs with and without FTZ treatment. (a) Representative oil red O images showing positive staining of lipid deposition in PA-treated HSCs, which was suppressed by Nlrp3 siRNA and FTZ. (b) Staining area of lipid deposition showing a statistically significant increase induced by PA, which was reduced by Nlrp3 siRNA and FTZ. (c) ELISA of IL-1β levels from cell media showing a statistically significant decreased by Nlrp3 siRNA and with FTZ (n=3 batches of cells). ∗p<0.05 versus Ctrl-scram group; #p<0.05 versus PA-scram group.
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### 3.6. Involvement of Redox Signaling in PA-Induced NLRP3 Inflammasome Activation in HSCs and the Effect of FTZ
Since previous studies showed that the MR redox signaling platforms and redox signaling are involved in inflammasome activation [24–26], we determined whether PA-induced NLRP3 inflammasome activation is associated with this redox regulatory pathway. As measured by ESR, O2•− production significantly increased when HSCs were stimulated by PA, which was shown in largely enhanced reactive signals in ESR chromatography. FTZ had no effects on basal O2•− production but inhibited PA-induced increases in ESR signal (Figure 7(a)). By calculation and nomination to SOD-sensitive components in ESR signals, PA-induced O2•− production in HSCs was found to be completely blocked by FTZ. This FTZ-mediated inhibitory effects on PA-induced O2•− production were similar to NAC (Figure 7(b)).Figure 7
Superoxide production and NADPH oxidase-membrane raft (MR) clustering in HSCs induced by PA with and without FTZ. (a) Representative ESR traces of superoxide (O2•−) trapped by CMH using NADPH as substrate upon PA stimulation in HSCs. (b) The bar graph summarizing ESR data, showing that PA enhanced O2•− production in HSCs, which was attenuated by FTZ and NAC (n=5 batches of cells). (c) Representative fluorescence confocal microscopic images showing the colocalization of MR component labeled by CTXB with NADPH oxidase subunit gp91 or p47. (d) Correction coefficient (PCC) showing a statistically significant increase in colocalization of CTXB with gp91 or p47 in PA-treated HSCs, which was suppressed by FTZ or NAC treatment (n=5 batches of cells). ∗p<0.05 versus Ctrl-Vehl group; #p<0.05 versus PA-Vehl group.
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(d)We next used Alexa Fluor 488-labeled CTXB (a MR marker) and anti-gp91 or anti-p47 antibody (NADPH oxidase (NOX) subunits) to measure clustering of MRs with both NOX subunits, which indicates MR redox signaling platform formation to produce O2•−. PA stimulation was found to significantly increase MR clustering with gp91 or p47 NOX subunits, as shown by the yellow patches on the HSC membrane (Figure 7(c)). It is well known that this MR redox platform formation led to the activation of NOX and subsequent generation of O2•−. These results were summarized in Figure 7(d), clearly showing that PA stimulated MR redox signaling platform formation in HSC membrane and FTZ blocked this PA effect.
### 3.7. Contribution of HMGB1 from NLRP3 Inflammasome Activation to PA-Induced Lipid Deposition and to the Beneficial Effects of FTZ
As described above, our animal studies found that NLRP3 inflammasome activation not only participated in HFD-induced hepatitis and liver fibrosis but also caused steatosis in the liver. FTZ could block the development of both steatosis and sterile hepatitis in the liver. It seems that NLRP3 inflammasome activation also has uncanonical effects in NASH development which is beyond inflammation. To test this hypothesis, we addressed the role of HMGB1, an NLRP3 inflammasome product, which has been reported to increase lipid deposition [8]. As shown in Figure 8(a), the representative oil red O staining showed that PA resulted in strong staining of lipids in HSCs, which was blocked by FTZ pretreatment. The effects of PA can be mimicked by HMGB1 but inhibited by HMGB1 inhibitor, glycyrrhizin (GLY). The quantitative measurement of oil red O staining areas was summarized in Figure 8(b), showing that PA increased lipid deposition, which was blocked by FTZ. The PA-induced lipid deposition was significantly enhanced by the addition of HMGB1 but blocked by GLY, even in the presence of HMGB1.Figure 8
Involvement of HMGB1 in lipid deposition in HSCs treated with PA with and without FTZ treatment. (a) Representative oil red O images showing positive staining of lipid deposition in PA-treated HSCs, which was enhanced by HMGB1 but suppressed by FTZ and GLY, an inhibitor of HMGB1. (b) Staining area of lipid deposition showing a statistically significant increase induced by PA, which was enhanced by HMGB1, but reduced by FTZ and HMGB1 inhibitor, GLY (n=5 batches of cells). ∗p<0.05 versus PA-Vehl group; #p<0.05 versus PA-HMGB1-Vehl group.
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## 3.1. NLRP3 Inflammasome Formation and Activation in the Liver of Mice on the HFD with and without Treatment of FTZ
By confocal microscopy, we found that there was significantly elevated colocalization of NLRP3 with ASC or caspase-1 in the liver of mice on the HFD compared with mice on the ND, indicating enhanced formation of NLRP3 inflammasomes. In mice receiving FTZ, HFD-induced increases in colocalization of NLRP3 inflammasome components were substantially blocked (Figure1(a)). Quantitation of the NLRP3 colocalization by measurement of correlation coefficient is presented in Figure 1(b), showing that NLRP3 inflammasome formation was significantly enhanced in mice on the HFD diet compared to mice on the ND and this enhanced NLRP3 inflammasome formation in the liver of mice on the HFD was significantly attenuated by FTZ.Figure 1
NLRP3 inflammasome formation and activation in the liver from mice on the HFD with and without FTZ treatment. (a) Representative confocal fluorescence images show the colocalization of NLRP3 with caspase-1 or ASC. (b) Correlation coefficient showing a statistically significant increase in NLRP3 inflammasome formation in HFD for 8 weeks with and without FTZ treatment (100 mg/kg/day) by gavage for 4 weeks (n=5 mice per group). (c) Representative immunohistochemical images show positive stain of IL-1β and IL-18 in the liver. (d) Positive staining area of IL-1β and IL-18 showing a statistically significant increase after NLRP3 inflammasome formation in the liver of mice on the HFD, which was suppressed by FTZ (n=4 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group.
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(d)Immunohistochemical analysis showed that both IL-1β and IL-18 (Figure 1(c)) levels significantly increased around fatty hepatocytes in the liver of mice on the HFD, suggesting activation of the inflammasome in these cells. FTZ treatment remarkably reduced this HFD-induced increase in hepatic IL-1β and IL-18. As shown in Figure 1(d), the positive staining areas of hepatic IL-1β and IL-18 were significantly increased in mice on the HFD without treatment of FTZ. In mice receiving FTZ, the increased IL-1β and IL-18 staining in the liver of mice on the HFD was significantly suppressed. It is clear that FTZ can inhibit the activation of NLRP3 inflammasomes in the liver.
## 3.2. Steatosis and NASH in the Liver of Mice on the HFD with and without FTZ Treatment
Steatosis as an important pathological change of NASH was analyzed in mice on the HFD. By oil red O staining, it was found that HFD caused a significant increase in lipid deposition in the liver of mice without treatment of FTZ. This enhanced oil red O staining in the liver was markedly reduced when mice were treated with FTZ (Figure2(a)). The quantitation of tissue areas stained by oil red O showed that more than 40% of the liver in mice on the HFD were with lipid deposition. Treatment of mice with FTZ significantly attenuated this HFD-induced lipid deposition in the liver (Figure 2(b)). It is clear that FTZ significantly prevented steatosis in mice fed with HFD.Figure 2
Steatosis and hepatitis in the liver from mice on the HFD with and without FTZ treatment. (a) Representative oil red O staining shows positive staining of lipid deposition in the liver. (b) Positive staining area of lipid deposition showing statistically significant increases after HFD, which was suppressed by FTZ (n=5 mice per group). (c) Representative H&E staining images showing inflammatory infiltration and fatty bulbs in liver cells after HFD which was attenuated by FTZ. (d) NAFLD activity score showing statistically significant increases after HFD for 8 weeks with and without FTZ treatment (n=5 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group
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(d)By H&E staining, we also examined the morphological changes in the liver of mice from different experimental groups. As shown in Figure2(c), besides lipid deposition the liver from mice on the HFD exhibited obvious inflammatory cell infiltration and increases in protein leakage into interstitial space. However, the liver from mice receiving FTZ almost lacked these inflammatory changes. Figure 2(d) depicts the results from the analysis of NAFLD activity score, showing that the increase in NAFLD activity score was highly significant in the liver of mice fed the HFD and that FTZ treatment significantly inhibited such increase in NAFLD activity score.
## 3.3. Fibrotic Changes Associated with NLRP3 Inflammasome Activation in the Liver of Mice on the HFD with and without FTZ Treatment
In addition to steatosis and inflammatory response detected, we also examined whether there is fibrogenic pathology in the liver from different experimental groups of mice. It was found that in the hepatic interstitium, in particular, in tissues around liver sinuses, there were increased levels ofα-SMA and vimentin, as shown by immunohistochemical staining (Figure 3(a)). It is well known that increased α-SMA and vimentin indicate phenotype changes of cells from quiescent to activated status, which occurred more remarkably in HSCs. These results were semiquantitated by measurement of α-SMA and vimentin staining areas in the liver. It was shown that α-SMA and vimentin levels in the liver were significantly elevated in mice on the HFD, and this HFD-induced fibrotic change in the liver was significantly blocked by FTZ treatment (Figure 3(b)).Figure 3
Fibrogenic phenotypes in the liver from mice on the HFD with and without FTZ treatment. (a) Representative immunohistochemical images showing enhancedα-SMA and vimentin staining, which are the markers of phenotype changed from quiescent to activated in HSCs. FTZ reduced HFD-induced increase in α-SMA and vimentin staining. (b) Summarized data depicting a significant increase in α-SMA and vimentin level in the liver of mice on the HFD with and without FTZ treatment (n=4 mice per group). (c, d) Representative images and PPC showing FLICA, active caspase-1 colocalization with α-SMA or vimentin staining in the liver of mice on the HFD, which was reduced by FTZ (n=4 mice per group). ∗p<0.05 versus ND-Vehl group; #p<0.05 versus HFD-Vehl group.
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(d)Since previous studies have shown that the formation and activation of NLRP3 inflammasomes in fibroblasts including HSCs may trigger the development of liver fibrosis [4], we determined whether these inflammasome-triggered fibrogenetic effects occur in NAFLD. By confocal microscopy, FLICA that indicates activated caspase-1 (green) was found to colocalize with increased α-SMA or vimentin (red) around liver sinuses and portal venules of the liver from mice on the HFD as shown by yellow spots (Figure 3(c)). In the liver from mice treated with FTZ, this enhanced colocalization of FLICA with α-SMA or vimentin was substantially reduced. By quantitative analysis of this colocalization of FLICA with α-SMA or vimentin, we found that the areas or cells with inflammasome activation had much higher level of α-SMA or vimentin, indicating the fibrogenesis during this model of NAFLD. FTZ significantly blocked this HFD-induced fibrogenic effect (Figure 3(d)).
## 3.4. PA-Induced NLRP3 Inflammasomes Formation and Increased Caspase-1 Activity in HSCs
To explore the mechanisms of NLRP3 inflammasome formation and activation in HSCs, we used palmitic acid (PA), one of the major components of saturated fatty acid, to induce lipid deposition to examine the role of NLRP3 inflammasome activation and related NASH-like changes in these cells. Confocal microscopic analysis found that the colocalization of NLRP3 with caspase-1 or ASC increased in HSCs upon PA stimulation, which indicates the aggregation or assembly of these inflammasome molecules indeed occurs in response to PA stimulation. In HSCs pretreated with FTZ extracts, there was no colocalization of NLRP3 with caspase-1 or ASC in HSCs stimulated by PA (Figure4(a)). The correlation coefficient of NLRP3 with ASC or caspase-1 showed that the colocalization of NLRP3 molecules increased significantly in HSCs stimulated by PA, which was completely blocked by FTZ, suggesting that FTZ is able to block NLRP3 inflammasome formation induced by PA in HSCs (Figure 4(b)).Figure 4
NLRP3 inflammasome formation and activation in HSCs after PA-induced steatosis with and without FTZ treatment. (a) Representative confocal fluorescence images show the colocalization of NLRP3 with caspase-1 or ASC in HSCs. (b) Correlation coefficient (PCC) showing a statistically significant increase in NLRP3 inflammasomes formation in PA-treated (200 mM/ml, 24 hours) HSCs, which was almost completely blocked by FTZ (50μg/ml, 24 hours) (n=5 batches of cells). (c) Representative Western blot gel documents showing cleaved caspase-1 increased in HSCs treated with PA but blocked by FTZ. (d) Densitometric quantitation of immunoreactive bands showing a statistically significant increase in cleaved caspase-1 after PA-treated cells (n=6 batches of cells). (e) ELISA of IL-1β levels from cell media showing a statistically significant increase induced by PA and decreased by FTZ (n=5 batches of cells). ∗p<0.05 versus Vehl-Ctrl group; #p<0.05 versus PA-Vehl group.
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(c)
(d)
(e)We also determined NLRP3 inflammasome activation by analysis of active caspase-1 and IL-1β production in HSCs with and without pretreatment with FTZ. As shown in Figures 4(c) and 4(d), PA significantly increased the level of cleaved or active caspase-1 (15 kDa) and FTZ completely blocked this PA-induced increase in active caspase-1 level. Correspondingly, biochemical analysis showed that PA induced a significant increase in IL-1β production from HSCs, which was also completely blocked by FTZ treatment. The inhibition of PA-induced IL-1β production by FTZ was similar to the effects of NAC, an often used antioxidant for suppression of NLRP3 inflammasome activation (Figure 4(e)).
## 3.5. Effects of Mouse Nlrp3 Gene Silencing on PA-Induced NLRP3 Inflammasome Activation with and without FTZ
Knockdown of mouse Nlrp3 mRNA level by Nlrp3 siRNA in HSCs remarkably inhibited PA-induced colocalization of ASC with caspase-1 (Figures5(a) and 5(b)) and attenuated PA-increased level of cleaved caspase-1 (Figure 5(c)) and both blocked by FTZ. Consistent with these findings, Nlrp3 gene silencing with or without FTZ blocked IL-1β production in HSCs (Figures 6(a) and 6(b)) and PA-induced steatosis (Figure 6(c)). These results from NLRP3 gene silencing further support that it is the NLRP3 inflammasome that contributes to inflammatory response during NASH of this model and that the effective treatment of FTZ may be due to inhibition of the NLRP3 inflammasome activation.Figure 5
Nlrp3 gene silencing inhibited PA-induced NLRP3 inflammasomes formation and activation in HSCs with and without FTZ treatment. (a) Representative fluorescence confocal microscopic images showing the colocalization of ASC with caspase-1. (b) Correction coefficient (PCC) showing a statistically significant increase in colocalization of ASC with caspase-1 in PA-treated HSCs, which was suppressed by Nlrp3 siRNA and FTZ. (c) Representative Western blot gel documents showing cleaved caspase-1 increased in HSCs treated with PA but blocked by Nlrp3 siRNA and FTZ. (d) Densitometric quantitation of immunoreactive bands showing a statistically significant decrease in cleaved caspase-1 by using Nlrp3 siRNA and FTZ (n=3 batches of cells). ∗p<0.05 versus Ctrl-scram group; #p<0.05 versus PA-scram group.
(a)
(b)
(c)
(d)Figure 6
Nlrp3 gene silencing inhibited PA-induced NLRP3 inflammasome production and steatosis in HSCs with and without FTZ treatment. (a) Representative oil red O images showing positive staining of lipid deposition in PA-treated HSCs, which was suppressed by Nlrp3 siRNA and FTZ. (b) Staining area of lipid deposition showing a statistically significant increase induced by PA, which was reduced by Nlrp3 siRNA and FTZ. (c) ELISA of IL-1β levels from cell media showing a statistically significant decreased by Nlrp3 siRNA and with FTZ (n=3 batches of cells). ∗p<0.05 versus Ctrl-scram group; #p<0.05 versus PA-scram group.
(a)
(b)
(c)
## 3.6. Involvement of Redox Signaling in PA-Induced NLRP3 Inflammasome Activation in HSCs and the Effect of FTZ
Since previous studies showed that the MR redox signaling platforms and redox signaling are involved in inflammasome activation [24–26], we determined whether PA-induced NLRP3 inflammasome activation is associated with this redox regulatory pathway. As measured by ESR, O2•− production significantly increased when HSCs were stimulated by PA, which was shown in largely enhanced reactive signals in ESR chromatography. FTZ had no effects on basal O2•− production but inhibited PA-induced increases in ESR signal (Figure 7(a)). By calculation and nomination to SOD-sensitive components in ESR signals, PA-induced O2•− production in HSCs was found to be completely blocked by FTZ. This FTZ-mediated inhibitory effects on PA-induced O2•− production were similar to NAC (Figure 7(b)).Figure 7
Superoxide production and NADPH oxidase-membrane raft (MR) clustering in HSCs induced by PA with and without FTZ. (a) Representative ESR traces of superoxide (O2•−) trapped by CMH using NADPH as substrate upon PA stimulation in HSCs. (b) The bar graph summarizing ESR data, showing that PA enhanced O2•− production in HSCs, which was attenuated by FTZ and NAC (n=5 batches of cells). (c) Representative fluorescence confocal microscopic images showing the colocalization of MR component labeled by CTXB with NADPH oxidase subunit gp91 or p47. (d) Correction coefficient (PCC) showing a statistically significant increase in colocalization of CTXB with gp91 or p47 in PA-treated HSCs, which was suppressed by FTZ or NAC treatment (n=5 batches of cells). ∗p<0.05 versus Ctrl-Vehl group; #p<0.05 versus PA-Vehl group.
(a)
(b)
(c)
(d)We next used Alexa Fluor 488-labeled CTXB (a MR marker) and anti-gp91 or anti-p47 antibody (NADPH oxidase (NOX) subunits) to measure clustering of MRs with both NOX subunits, which indicates MR redox signaling platform formation to produce O2•−. PA stimulation was found to significantly increase MR clustering with gp91 or p47 NOX subunits, as shown by the yellow patches on the HSC membrane (Figure 7(c)). It is well known that this MR redox platform formation led to the activation of NOX and subsequent generation of O2•−. These results were summarized in Figure 7(d), clearly showing that PA stimulated MR redox signaling platform formation in HSC membrane and FTZ blocked this PA effect.
## 3.7. Contribution of HMGB1 from NLRP3 Inflammasome Activation to PA-Induced Lipid Deposition and to the Beneficial Effects of FTZ
As described above, our animal studies found that NLRP3 inflammasome activation not only participated in HFD-induced hepatitis and liver fibrosis but also caused steatosis in the liver. FTZ could block the development of both steatosis and sterile hepatitis in the liver. It seems that NLRP3 inflammasome activation also has uncanonical effects in NASH development which is beyond inflammation. To test this hypothesis, we addressed the role of HMGB1, an NLRP3 inflammasome product, which has been reported to increase lipid deposition [8]. As shown in Figure 8(a), the representative oil red O staining showed that PA resulted in strong staining of lipids in HSCs, which was blocked by FTZ pretreatment. The effects of PA can be mimicked by HMGB1 but inhibited by HMGB1 inhibitor, glycyrrhizin (GLY). The quantitative measurement of oil red O staining areas was summarized in Figure 8(b), showing that PA increased lipid deposition, which was blocked by FTZ. The PA-induced lipid deposition was significantly enhanced by the addition of HMGB1 but blocked by GLY, even in the presence of HMGB1.Figure 8
Involvement of HMGB1 in lipid deposition in HSCs treated with PA with and without FTZ treatment. (a) Representative oil red O images showing positive staining of lipid deposition in PA-treated HSCs, which was enhanced by HMGB1 but suppressed by FTZ and GLY, an inhibitor of HMGB1. (b) Staining area of lipid deposition showing a statistically significant increase induced by PA, which was enhanced by HMGB1, but reduced by FTZ and HMGB1 inhibitor, GLY (n=5 batches of cells). ∗p<0.05 versus PA-Vehl group; #p<0.05 versus PA-HMGB1-Vehl group.
(a)
(b)
## 4. Discussion
The current study provides several important findings. First, it demonstrated that NLRP3 formation and activation was enhanced during the development of NASH, which was confirmed in bothin vivo animal and in vitro cell studies. Secondly, we verified the FTZ effect on NLRP3 inflammasome by using siRNA knocking down Nlrp3 gene. Thirdly, it was found that the NLRP3 inflammasome activation was inhibited by FTZ, which was accompanied by a reduction of liver lipid deposition and fibrogenic phenotype changed. It is indicated that FTZ exerts its beneficial action to not only prevent the inflammatory response but also suppress steatosis during HFD. Lastly, it showed that MR redox signaling platform formation and associated NADPH oxidase activation were involved in NLRP3 inflammasome activation and thereby contributed to the development of NASH. This MR redox signaling mechanism is responsible for liver inflammasome activation and NASH participated in the beneficial effects of FTZ against lipid deposition, inflammation, and fibrosis in the liver. The results suggest that NLRP3 inflammasome formation and activation via MR raft redox signaling platforms play a critical role in the initiation and progression of NASH and that FTZ exerts its beneficial action through inhibition of NLRP3 inflammasome activation in the liver.We first determined whether NLRP3 inflammasome formation and activation occurred during the development of NASH using a mouse model of steatosis induced by HFD. NAFLD activity scores in the 8-week HFD group are among 3 to 4, which considered borderline or positive for NASH which also considered as the early stage of NASH. It was found that this inflammasome was formed and activated in the liver, which was companied by sterile inflammation and fibrogenesis, indicating the typical pathological changes of NASH. In isolated and cultured HSCs, we further showed that PA significantly enhanced NLRP3 inflammasome formation and activation, which were also with lipid deposition and fibrogenic phenotype changed in HSCs. These results tell us that NLRP3 inflammasome activation in the liver or in HSCs may be an important early pathogenic mechanism to turn on the inflammatory response and thereby instigate liver fibrosis during NASH. This is consistent with some previous reports indicating that NLRP3 inflammasome activation plays a fundamental role in the development of NASH [3]. In other liver fibrotic animal models such as alcoholic steatosis and cirrhosis [2], viral hepatitis-induced cirrhosis [27] and hepatic fibrosis during Schistosoma J infection [4], NLRP3 inflammasome activation has also been reported to either trigger or modulate hepatic inflammation leading to fibrosis [28]. The Sirius red staining in histological liver sections showed no significant liver fibrosis and cirrhosis after 8 weeks of HFD in this mouse model. However, some staining could be seen in sinus area with more HSCs. It is possible that some HSCs become fibrotic even at weeks of HFD when NLRP3 inflammasomes are activated (Supplementary Figure 3). Taken together, it is clear that NLRP3 inflammasome as intracellular inflammatory machinery is essential for the development of NASH and other liver fibrotic diseases.Although chronic inflammation is a hallmark of NASH, the classic anti-inflammatory medicines, such as commonly used indole and arylpropionic acid derivatives are not very efficient in the prevention or treatment of NASH [29]. This may be mainly because these classical anti-inflammatory strategies may not target the noninflammatory or noncanonical effects during NLRP3 inflammasome activation in the development of NASH [6], and therefore they may only have a limited therapeutic effect. This led us to think that the NLRP3 inflammasome and its regulatory pathways may be an ideal target for treatment of chronic degenerative diseases like NASH with multiple pathological processes. Given our long-lasting interest in FTZ, a widely used herbal remedy for metabolic syndrome and hyperlipidemia and related complications in China, we tested whether FTZ exerts its action through inhibition of NLRP3 inflammasome formation and activation. In our studies with an animal model of NASH induced by HFD and with cultured HSCs stimulated by PA, we demonstrated that FTZ remarkably inhibited the formation and activation of NLRP3 inflammasomes. This inhibitory effects of FTZ on NLRP3 inflammasome activation reduced both hepatic inflammation and steatosis. Furthermore, this NLRP3 inhibition was also found to abrogate fibrotic process in the liver during NASH. It appears that FTZ indeed exerts its beneficial action in preventing NASH through suppression of NLRP3 inflammasome activation in the liver. To our knowledge, the findings from the present study for the first time link the therapeutic effect of FTZ to NLRP3 inflammasome activation, which serves as a molecular mechanism of the FTZ action.FTZ has been prescribed over the last 15 years for treatment of hyperlipidemia and metabolic syndrome and related complications such as atherosclerosis and NASH [11, 12]. Previous studies have demonstrated that FTZ attenuated metabolic syndrome- (MS-) associated symptoms and pathological changes in tissues or cells, which was attributed to the decreases in the plasma levels of glucose and lipids [30]. In addition, some studies have shown that FTZ attenuated the downregulation of PI3K p85 mRNA and IRS1 protein in both insulin-resistant HepG2 cells and MS rats [30]. In a recent study, some components of FTZ were found to prevent the development of fatty liver in rats [13]. However, these studies did not elucidate the precise mechanisms how FTZ works to inhibit liver inflammation and to change fibrogenic phenotype. In the present study, we not only demonstrated that the suppression of NLRP3 inflammasome as an intracellular inflammatory machinery during NASH is an underlying mechanism responsible for the anti-inflammatory action of FTZ but also interestingly confirmed that FTZ inhibits lipid deposition in liver cells by the blockade of NLRP3 inflammasome-mediated HMGB1 production. It is believed that through inhibition of NLRP3 inflammasome activation FTZ may work to interfere with the early lipid deposition process and the late induction of hepatic inflammation and fibrosis during the progression of NASH. In previous studies, cholesterol, free fatty acids, and triglycerides were found to store in HSCs, which may activate these cells to become fibrogenic initiating or promoting liver fibrosis. Activated HSCs could sensitize the cell injury to further enhance lipid accumulation when there is increased intake of cholesterol, which may lead a vicious cycle in NASH, namely, accumulated lipids activating HSCs and the latter resulting in more accumulation of lipids in these cells [31]. The results from the present study provide the first experimental evidence that HMGB1 release derived from NLRP3 inflammasome-dependent caspase-1 activity may be involved in this lipid deposition process as shown in some other studies [5, 32, 33]. This action of HMGB1 can be blocked by FTZ treatment.We also explored the mechanisms by which FTZ inhibits NLRP3 inflammasome formation and activation and thereby prevent NASH development. It was demonstrated that FTZ inhibited MR redox signaling platform formation to produce O2•−. This action further blocked NLRP3 inflammasome formation and activation in HFD-induced NASH in mice or in PA-stimulated HSCs. Although there are reports that in chronic liver disease oxidative stress has a clear role in HSC activation triggering fibrotic process [34], the results from the present study are the first to clarify that local oxidative stress may induce HSC activation and liver fibrosis through NLRP3 inflammasomes. FTZ may target this very early event of NASH to prevent the degenerative outcome of this liver disease. All these roles of NLRP3 inflammasomes in NASH and the beneficial effects of FTZ are diagrammatically summarized in Figure 9.Figure 9
A schematic illustration of plausible mechanisms by which FTZ inhibits the NLRP3 inflammasome formation and activation and thus ameliorates steatohepatitis or NASH.In summary, the present study demonstrated that increased NLRP3 inflammasome formation and activation are an important pathogenic mechanism initiating and promoting the development of NASH. FTZ suppressed this NLRP3 inflammasome activation to prevent steatosis, hepatic inflammation, and fibrogenic phenotype changed. This beneficial action of FTZ through the inhibition of NLRP3 inflammasome activation was not only associated with suppression of liver inflammation and HSCs activation leading to fibrogenesis but also with the early event of lipid deposition triggering steatosis. Furthermore, we showed that the inhibitory effect of FTZ on the NLRP3 inflammasome activation was due to blockade of MR redox signaling platform formation and subsequent O2•− production.
## 5. Conclusion
The present study demonstrates that FTZ extracts inhibit NASH by its action on both inflammatory response and lipid metabolism associated with NLRP3 inflammasome activation in the liver. Targeting NLRP3 inflammasome to reduce steatosis, sterile liver inflammation, and consequent fibrosis may be an underlying mechanism for the therapeutic action of FTZ on NASH and possibly on other end-organ damage induced by metabolic syndrome.
---
*Source: 2901871-2018-07-22.xml* | 2018 |
# Oxidant Antioxidants and Adaptive Responses to Exercise
**Authors:** Paola Venditti; Mari Carmen Gomez-Cabrera; Yong Zhang; Zsolt Radak
**Journal:** Oxidative Medicine and Cellular Longevity
(2015)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2015/290190
---
## Body
---
*Source: 290190-2015-03-24.xml* | 290190-2015-03-24_290190-2015-03-24.md | 392 | Oxidant Antioxidants and Adaptive Responses to Exercise | Paola Venditti; Mari Carmen Gomez-Cabrera; Yong Zhang; Zsolt Radak | Oxidative Medicine and Cellular Longevity
(2015) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2015/290190 | 290190-2015-03-24.xml | ---
## Body
---
*Source: 290190-2015-03-24.xml* | 2015 |
# Optimized Collection Protocol for Plasma MicroRNA Measurement in Patients with Cardiovascular Disease
**Authors:** Chi-Sheng Wu; Fen-Chiung Lin; Shu-Jen Chen; Yung-Lung Chen; Wen-Jung Chung; Cheng-I Cheng
**Journal:** BioMed Research International
(2016)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2016/2901938
---
## Abstract
Background. Various microRNAs (miRNAs) are used as markers of acute coronary syndrome, in which heparinization is considered mandatory therapy. Nevertheless, a standard method of handling plasma samples has not been proposed, and the effects of heparin treatment on miRNA detection are rarely discussed.Materials and Method. This study used quantitative polymerase chain reaction (qPCR) analysis to investigate how storage temperature, standby time, hemolysis, and heparin treatment affect miRNA measurement in plasma samples from 25 patients undergoing cardiac catheterization.Results. For most miRNAs, the qPCR results remained consistent during the first 2 hours. The miRNA signals did not significantly differ between samples stored at 4°C before processing and samples stored at room temperature (RT) before processing. miR-451a/miR-23a ratio < 60 indicated < 0.12% hemolysis with 100% sensitivity and 100% specificity. Pretreatment with 0.25 U heparinase I recovered qPCR signals that were reduced byin vivo heparinization.Conclusions. For miRNA measurement, blood samples stored at RT should be processed into plasma within 2 hours after withdrawal and should be pretreated with 0.25 U heparinase I to overcome heparin-attenuated miRNA signals. The miR-451a/miR-23a ratio is a reliable indicator of significant hemolysis.
---
## Body
## 1. Introduction
Cardiovascular disease (CVD) includes coronary heart disease, cardiomyopathy, hypertensive heart disease, and heart failure. Risk factors for CVD include advanced age, male gender, high blood pressure, smoking, family history of CVD, and family history [1–7]. Although the incidence and mortality rate of CVD are both declining in high-income countries [1], coronary artery disease remains a leading cause of death worldwide [8]. Additionally, CVD may present as acute coronary syndrome (ACS), which has a high mortality rate. Pathologic processes involved in ACS include vascular inflammation, rupture of coronary artery plaques, platelet activation, and subsequent myocardial necrosis. Therefore, many studies have attempted to identify novel biomarkers for identifying patients at high risk of CVD. One proposed biomarker is microRNA (miRNA) [9, 10].MicroRNA is a noncoding small RNA that is 21–23 nucleotides in length. In plants, animals, and some viruses, small RNA functions as RNA silencer by modifying posttranscriptional regulation [11]. Diseases known to be regulated by miRNA include cancer [12–16], obesity [17, 18], and various other diseases of the nervous system [19], the immune system [20], and the heart [21]. MicroRNA can be sampled from body fluids such as serum, plasma, saliva, and urine. Since miRNA can be collected and detected extracellularly, a major benefit of using miRNA detection for disease diagnosis is its noninvasiveness. Specifically, recent studies indicate that circulating miRNA is a useful biomarker of various diseases [22], including ACS [23, 24].Cell matrix will be released after erythrocytes rupture due to either physical stress, or red blood cell- (RBC-) specific or RBC-abundant miRNAs are present in hemolyzed blood samples. Hemolysis can potentially affect the accuracy of miRNA quantification in a blood sample. Although studies have shown that expressions of miR-451a and miR-16 in RBCs are detectable in hemolyzed blood samples [25, 26], no studies have thoroughly investigated the potential use of miRNA as an indicator of hemolysis.In ACS patients, miRNA detection is routinely performed because altered miRNA is associated with ACS risk and outcome [27–32]. However, none of the pioneering studies in the use of miRNA detection have comprehensively discussed sample preparation. For example, reported standby times and storage temperatures of plasma samples during transport from the emergency department to the laboratory vary widely. No information regarding differential patterns of miRNA within the uncertain collection time is available. According to established guidelines, heparin treatment is essential for ACS patients [33], and heparin is known to affect accuracy in detecting miRNA signals [34–37]. Although a previous study showed that heparinase can improve quantitative real-time polymerase chain reaction (qPCR) signals [37], the optimal heparinase dose for qPCR has not been determined.Therefore, this study developed a multiplex qPCR system for simultaneously screening 18 miRNA targets and determined the optimal miR-451a/miR-23a ratio for predicting hemolysis in plasma samples. A literature review shows that this study is the first report of a standardized procedure for clinical measurement of miRNA in plasma samples from CVD patients and the first to determine the optimal heparinase dose for qPCR.
## 2. Materials and Methods
### 2.1. Clinical Sample Collection
This study was approved by the Institutional Review Board of Kaohsiung Chang Gung Memorial Hospital (102-1790A3). The recruitment criteria were age of 30–70 years, clinical indications for elective cardiac catheterization for ischemic heart disease or heart failure, and written informed consent. Exclusion criteria were hemoglobin less than 12 g/dL, pregnancy, peritoneal dialysis or hemodialysis for end stage renal disease, acute myocardial infarction, contraindications for heparinization, and unstable hemodynamic condition. Clinical data collection included clinical indication for cardiac catheterization and demography.During cardiac catheterization, the radial artery was cannulated with a 6 Fr artery sheath, and 36 mL of unheparinized blood was withdrawn from the sheath. Five minutes after administration of heparin 100 U/Kg through the artery sheath, another 36 mL of heparinized blood was withdrawn. For the coronary angiogram, a cardiac catheter was inserted to ensure an even distribution of heparin in the circulatory system. Next, 6 mL of heparinized or unheparinized blood was dispensed into a 10-mL EDTA K2 tube (BD Vacutainer, Ref. 367525) and kept still at either room temperature (RT) or at 4°C for the time intervals shown in Figure1. The tube containing the blood sample was centrifuged at 2,000 ×g for 10 minutes. The plasma was then aspirated to another 10 mL centrifuge tube and centrifuged at 2,500 ×g for 15 minutes. Finally, 300 μL of clear plasma was pipetted into a 1.5 mL eppendorf containing 6 μL of protease inhibiter (Roche, Cat. number 11836145001) and stored at −80°C.Figure 1
Flowchart of plasma sample collection procedure. Plasma samples were collected at the catheterization laboratory as described in Materials and Methods.
### 2.2. Generation of Hemolyzed Plasma Samples
Next, 1 mL unheparinized whole blood derived from some patients was aspirated from the EDTA K2 tube into an eppendorf tube. Varying degrees of hemolysis were induced by vigorous manual shaking until the color of the sample could be matched to the hemolysis color card (see Supplementary Fig. 1A in Supplementary Material available online athttp://dx.doi.org/10.1155/2016/2901938). The hemolyzed samples (Supplementary Fig. 1B) were then processed into plasma samples as described above and stored at −80°C.
### 2.3. RNA Preparation and Reverse Transcription
Total RNA from 300μL of plasma samples was subjected to miRNA extraction with miRNeasy minikit (QIAGEN, GmbH, Hilden, Germany). Briefly, 700 μL of QUIzol reagent was added to the plasma sample, and the sample was allowed to stand at RT for 5 minutes. Next, 1 nM of synthetic cel-miR-39 RNA (5′-CGAUGGGCAGCUAUAUUCACCUUG-3′) was added into the mixture as the spike-in control to monitor the RNA extraction and qPCR processing. Then, 140 μL of chloroform (Merck & Co., Inc.) was added into the sample, mixed well for 15 seconds, and left standing for 3 minutes at RT. The upper layer of 550 μL aqueous solution was aspirated by centrifugation at 15,000 ×g at 4°C for 15 minutes and then thoroughly mixed with 825 μL of ethanol. The samples were further eluted through the microcolumn and washed with RWP and RPE buffer. Finally, total RNA was dissolved in 30 μL of RNase-free water. To convert the detected miRNA into its corresponding cDNA, 5.4 μL of total RNA, 75 nM of 20 miRNA primers mix, 0.5 mM dNTP, 2 U RNaseout, and 120 U Superscript III (Invitrogen, CA) were used for reverse transcription reaction in a total reaction mixture of 12 μL. The processing program was 16°C for 30 minutes; 49 cycles of 20°C for 30 seconds, 42°C for 30 seconds, and 50°C for 1 second; and 72°C for 10 minutes. Reverse transcription products were stored at −20°C.
### 2.4. qPCR Assay
In qPCR assay of 8μL miRNA, 0.5 μL of a 5-fold dilution of RT product was used as a template. The template was mixed with 4 μL 2x Master Mix (Applied Biosystems, Foster City, CA), 0.25 M universal reverse primer, 0.2 M gene-specific primers, and 0.125 mM TaqMan probe (Applied Biosystems, Foster City, CA). The qPCR conditions (QuantStudio™ 12K Flex Real-time PCR System, Applied Biosystems, Foster City, CA) were 95°C for 10 minutes; 45 cycles of 95°C for 15 seconds and 60°C for 30 seconds; and a dissociation stage.
### 2.5. miRNA Data Analysis
The cycle threshold (Ct) value was calculated by determining the cycle number at which the change in fluorescence intensity crossed the threshold of 0.05. For each sample, the delta Ct was calculated by subtracting the Ct of the sample from the Ct of cel-miR-238. The normalized delta Ct was converted to the miRNA copy number as the copies per uL of plasma.
### 2.6. Heparinase I Usage
To evaluate whether heparinase reverses heparin-related effects on miRNA measurement, heparinase I (H2519, SIGMA-ALDRICH, USA) doses of 0.5 U, 0.25 U, 0.025 U, and 0.0025 U were added into reverse transcription reaction mixes. Briefly, 5.4μL of the RNA samples derived from heparinized blood was incubated with different doses of heparinase I, 2 U of RNase out, and 1.25 mM MgCl2 at 25°C for 1 hour. The RT reaction procedure described above was then performed.
### 2.7. Statistical Analysis
In the storage condition validation group, the variation between 0 h and 2 h was analyzed in each patient by Mann–Whitney test. AP value of <0.05 was considered statistically significant. In each patient, the effects of various heparinase dosages administered at RT and at 4°C were compared by ANOVA.
## 2.1. Clinical Sample Collection
This study was approved by the Institutional Review Board of Kaohsiung Chang Gung Memorial Hospital (102-1790A3). The recruitment criteria were age of 30–70 years, clinical indications for elective cardiac catheterization for ischemic heart disease or heart failure, and written informed consent. Exclusion criteria were hemoglobin less than 12 g/dL, pregnancy, peritoneal dialysis or hemodialysis for end stage renal disease, acute myocardial infarction, contraindications for heparinization, and unstable hemodynamic condition. Clinical data collection included clinical indication for cardiac catheterization and demography.During cardiac catheterization, the radial artery was cannulated with a 6 Fr artery sheath, and 36 mL of unheparinized blood was withdrawn from the sheath. Five minutes after administration of heparin 100 U/Kg through the artery sheath, another 36 mL of heparinized blood was withdrawn. For the coronary angiogram, a cardiac catheter was inserted to ensure an even distribution of heparin in the circulatory system. Next, 6 mL of heparinized or unheparinized blood was dispensed into a 10-mL EDTA K2 tube (BD Vacutainer, Ref. 367525) and kept still at either room temperature (RT) or at 4°C for the time intervals shown in Figure1. The tube containing the blood sample was centrifuged at 2,000 ×g for 10 minutes. The plasma was then aspirated to another 10 mL centrifuge tube and centrifuged at 2,500 ×g for 15 minutes. Finally, 300 μL of clear plasma was pipetted into a 1.5 mL eppendorf containing 6 μL of protease inhibiter (Roche, Cat. number 11836145001) and stored at −80°C.Figure 1
Flowchart of plasma sample collection procedure. Plasma samples were collected at the catheterization laboratory as described in Materials and Methods.
## 2.2. Generation of Hemolyzed Plasma Samples
Next, 1 mL unheparinized whole blood derived from some patients was aspirated from the EDTA K2 tube into an eppendorf tube. Varying degrees of hemolysis were induced by vigorous manual shaking until the color of the sample could be matched to the hemolysis color card (see Supplementary Fig. 1A in Supplementary Material available online athttp://dx.doi.org/10.1155/2016/2901938). The hemolyzed samples (Supplementary Fig. 1B) were then processed into plasma samples as described above and stored at −80°C.
## 2.3. RNA Preparation and Reverse Transcription
Total RNA from 300μL of plasma samples was subjected to miRNA extraction with miRNeasy minikit (QIAGEN, GmbH, Hilden, Germany). Briefly, 700 μL of QUIzol reagent was added to the plasma sample, and the sample was allowed to stand at RT for 5 minutes. Next, 1 nM of synthetic cel-miR-39 RNA (5′-CGAUGGGCAGCUAUAUUCACCUUG-3′) was added into the mixture as the spike-in control to monitor the RNA extraction and qPCR processing. Then, 140 μL of chloroform (Merck & Co., Inc.) was added into the sample, mixed well for 15 seconds, and left standing for 3 minutes at RT. The upper layer of 550 μL aqueous solution was aspirated by centrifugation at 15,000 ×g at 4°C for 15 minutes and then thoroughly mixed with 825 μL of ethanol. The samples were further eluted through the microcolumn and washed with RWP and RPE buffer. Finally, total RNA was dissolved in 30 μL of RNase-free water. To convert the detected miRNA into its corresponding cDNA, 5.4 μL of total RNA, 75 nM of 20 miRNA primers mix, 0.5 mM dNTP, 2 U RNaseout, and 120 U Superscript III (Invitrogen, CA) were used for reverse transcription reaction in a total reaction mixture of 12 μL. The processing program was 16°C for 30 minutes; 49 cycles of 20°C for 30 seconds, 42°C for 30 seconds, and 50°C for 1 second; and 72°C for 10 minutes. Reverse transcription products were stored at −20°C.
## 2.4. qPCR Assay
In qPCR assay of 8μL miRNA, 0.5 μL of a 5-fold dilution of RT product was used as a template. The template was mixed with 4 μL 2x Master Mix (Applied Biosystems, Foster City, CA), 0.25 M universal reverse primer, 0.2 M gene-specific primers, and 0.125 mM TaqMan probe (Applied Biosystems, Foster City, CA). The qPCR conditions (QuantStudio™ 12K Flex Real-time PCR System, Applied Biosystems, Foster City, CA) were 95°C for 10 minutes; 45 cycles of 95°C for 15 seconds and 60°C for 30 seconds; and a dissociation stage.
## 2.5. miRNA Data Analysis
The cycle threshold (Ct) value was calculated by determining the cycle number at which the change in fluorescence intensity crossed the threshold of 0.05. For each sample, the delta Ct was calculated by subtracting the Ct of the sample from the Ct of cel-miR-238. The normalized delta Ct was converted to the miRNA copy number as the copies per uL of plasma.
## 2.6. Heparinase I Usage
To evaluate whether heparinase reverses heparin-related effects on miRNA measurement, heparinase I (H2519, SIGMA-ALDRICH, USA) doses of 0.5 U, 0.25 U, 0.025 U, and 0.0025 U were added into reverse transcription reaction mixes. Briefly, 5.4μL of the RNA samples derived from heparinized blood was incubated with different doses of heparinase I, 2 U of RNase out, and 1.25 mM MgCl2 at 25°C for 1 hour. The RT reaction procedure described above was then performed.
## 2.7. Statistical Analysis
In the storage condition validation group, the variation between 0 h and 2 h was analyzed in each patient by Mann–Whitney test. AP value of <0.05 was considered statistically significant. In each patient, the effects of various heparinase dosages administered at RT and at 4°C were compared by ANOVA.
## 3. Results
### 3.1. Patient Characteristics
Table1 lists the demographic characteristics of the cohort of 25 patients enrolled in this study. The patients had a mean age of 62.0
±
6.6 years, and 76% (19) of the patients were male. One patient underwent cardiac catheterization to evaluate the etiology of heart failure, and 24 patients underwent cardiac catheterization to evaluate the severity of coronary artery disease.Table 1
Patient demographics.
Clinical characteristics
Patient number (%)
Age (years)
62.0 ± 6.6
Male
19 (76%)
Hypertension
20 (80%)
Diabetes
10 (40%)
Atrial fibrillation
4 (16%)
Heart failure
6 (24%)
Stroke
5 (20%)
Coronary artery disease
5 (20%)
Chronic kidney disease
5 (20%)
Indications for cardiac catheterization
Evaluation of coronary artery disease
24 (96%)
Evaluation of heart failure
1 (4%)
### 3.2. Specificity of Primer and Probe for Candidate miRNA
Since both nonspecific and background signals can interfere with qPCR, the TaqMan probe specificity with its correlated synthetic cDNA was tested in each of the 18 candidate miRNA targets in this study (Supplementary Fig. 2) to determine the miRNA signal with the best specificity. Cel-miR-238 was used as the spike-in control for monitoring RNA extraction and qPCR detection in plasma samples during the experiment. The primers were designed specifically for the 18 candidate miRNA targets, which were selected because they are known to be associated with CVD. After qPCR assay, the quantification cycle (Ct) value was converted to the copy number (106 copies of each cDNA used as template for qPCR). Supplementary Fig. 2 shows the PCR results, which indicated that each probe had high specificity and high affinity with its own cDNA template. The PCR results indicated that all gene-specific primers and probes were suitable for detecting all candidate miRNAs in our clinical samples.
### 3.3. Hemolysis Test
Hemolysis of RBC in clinical samples interferes with the Ct value of qPCR. Additionally, miR-451a expression is associated with hemolysis whereas miR-23a is constant in hemolyzed blood samples [25, 38]. Therefore, this study investigated whether the miR-451a/miR-23a ratio is a good marker of significant hemolysis. First, an artificial mechanical method was used to generate eight different hemolysis grades (grades 0 to 7) from blood samples from four subjects. Supplementary Fig. 1B shows the plasma samples prepared from hemolyzed blood samples. Expressions of miR-451a and miR-23a in these plasma samples were then measured by qPCR. Figures 2(a) and 2(b) show that expressions of miR-451a and miR-23a, respectively, remained stable in unhemolyzed blood samples kept at RT or at 4°C for varying durations. Figure 2(c) shows that, in further comparisons with other plasma samples of varying hemolysis grades kept at RT for 0 h or 2 h in the same study subjects, a high miR-451a/miR-23a ratio correlated with a high grade of hemolysis. Since hemoglobin 1 g/L [5, 39] is considered mild hemolysis, this study defined significant hemolysis as a hemolysis grade of >0.12%. A receiver operating characteristics curve analysis showed that the miR-451a/miR-23a ratio had an area under the curve value of 1.0 (P
<
0.001), which indicated that this ratio is a good hemolysis marker. When the cut-off point for the miR-451a/miR-23a ratio was set to 60, both the sensitivity and the specificity were 100% (Supplementary Table 1).Figure 2
Expressions of miR-425a and miR-23a represent the hemolysis status of clinical samples. The qPCR analysis revealed that expressions of miR-451a and miR-23a stored at (a) RT or (b) at 4°C were stable from 0 h to 8 h. The Ct values shown in the tables indicate the qPCR results for five individuals at different time points. TheP value indicates the significance of each time point compared with time 0 h. (c) Manual hemolysis test was performed in 32 differential hemolytic plasma samples (see Materials and Methods). Hemolytic grade was defined by hemolysis card (Supplementary Fig. 1A). The miR-425a/miR-23a ratio increased as hemolysis grade increased.
(a)
(b)
(c)
### 3.4. Sample Storage at RT Is Better Than Storage at 4°C
To determine the optimal storage condition for plasma samples used for qPCR detection, plasma samples from five patients (P03, P04, P08, P10, and P11) were used as the training group for qPCR. In each sample, the delta Ct value and average of the 18 miRNA targets were normalized to each Ct value at time 0 at RT (Figure3(a)) and at 4°C (Figure 3(b)). The results showed that storage time significantly affected the qPCR Ct value under both the RT and 4°C conditions (P
<
0.0001 and P
=
0.0368, resp.). These results indicate the need to consider plasma storage conditions when performing qPCR data analysis. To determine the best storage condition, the delta Ct value relative to time 0 of each miRNA was calculated for samples P03, P04, P08, P10, and P11. Figure 3(c) shows that the RT and 4°C conditions significantly differed (P
<
0.0001) at 0.5 h, 1 h, and 2 h but not at 4 h. The delta Ct value adjusted to time 0 revealed that the change was smaller at RT than at 4°C before 4 h. These results showed that, for plasma samples processed within 2 h, those stored at RT yield more reliable qPCR results compared to those stored at 4°C.Figure 3
Plasma storage condition test. The miRNA expressin patterns at time 0 h, 0,5 h, 1 h, 2 h, and 4 h for storage at (a) RT and (b) at 4°C. (c) Average change in Ct value in five clinical samples of plasma stored for varying durations ranging from 0.5 h to 4 h at RT and at 4°C. From 0.5 h to 2 h, the delta Ct was more stable at RT than at 4°C. The scale indicates the delta Ct value of the qPCR result in comparison with time 0.
(a)
(b)
(c)
### 3.5. Expression of miRNA Stored at RT for 2 h
This study further evaluated whether samples stored at RT for 2 h were suitable for miRNA detection. Plasma samples derived from nine patients were used as a test cohort to verify the changes in qPCR signals between 0 h and 2 h. Figure4 shows that the qPCR signals of 18 miRNA samples between 0 h and 2 h did not significantly differ as a whole in each patient as a whole. However, the statistical data in Table 2 show a significant reduction in the expressions of two miRNA targets (miR-15b-5p and miR-30e-5p) from 0 h to 2 h whereas the largest difference in delta Ct in the three miRNA targets was less than 1.4. These data indicate that although some miRNA targets degraded after storage at RT for 2 h, most targets remained stable.Table 2
Expression of miRNA (ct value) at 0 h and 2 h.
miRNA
0 h
2 h
P
∗
Median ± SD
Median ± SD
hsa-miR-15b-5p
30.55 ± 0.98
29.75 ± 1.07
0.0315†
hsa-miR-17-5p
29 ± 1.08
29.43 ± 1.19
0.3401
hsa-miR-19a-3p
29.85 ± 0.96
31.39 ± 1.25
0.3865
hsa-miR-20a-5p
32.98 ± 1.05
32.09 ± 1.08
0.1135
hsa-miR-21-5p
32.29 ± 0.87
32.43 ± 0.97
0.7962
hsa-miR-24-3p
28.37 ± 1.17
28.06 ± 1.26
0.8633
hsa-miR-27a-3p
30.04 ± 0.96
29.7 ± 1
0.2581
hsa-miR-27b-3p
30.35 ± 0.99
30.59 ± 1.01
1
hsa-miR-30c-5p
33.07 ± 0.98
32.78 ± 0.88
0.7962
hsa-miR-30e-5p
34.25 ± 1.11
32.84 ± 1.06
0.0315†
hsa-miR-145-5p
32.01 ± 0.8
31.31 ± 1.12
0.2581
hsa-miR-150-5p
29.84 ± 0.86
30.31 ± 0.61
0.2973
hsa-miR-199a-3p
31.51 ± 1.51
30.78 ± 1.95
0.7304
hsa-miR-210
33.6 ± 1.19
33.5 ± 1.15
0.3401
hsa-miR-221-3p
29.06 ± 1.25
29.82 ± 1.43
0.6665
hsa-miR-222-3p
31.12 ± 0.89
30.65 ± 0.92
0.1615
hsa-miR-320a
28.26 ± 0.86
28.85 ± 0.8
0.2224
hsa-miR-423-5p
28.81 ± 1.11
28.52 ± 1.07
0.4363
∗Mann–Whitney U test.
†Statistically significant.Figure 4
Comparison of samples stored at RT for 0 h and at RT for 2 h. The qPCR results at time 0 and at 2 h were compared in nine individual plasma samples.
### 3.6. Heparinase I Improves qPCR Efficiency in Plasma Samples
Heparin is commonly used to avoid blood clotting in cardiac catheterization. However, since heparin reportedly reduces qPCR signals, this study investigated whether heparinase I treatment can restore miRNA expression in RNA samples before qPCR. First, the control cel-miR-39 was used as a test indicator for comparing qPCR results. Figure5(a) shows that, regardless of whether samples were kept at RT or at 4°C and regardless of whether samples were kept for 0.5 h or for 8 h, treatment with 0.25 U and 0.5 U heparinase I significantly increased heparin-reduced delta Ct by 1.5 and 2.8, respectively. Similar results were observed for miR-15b-5p, miR-17-5p, and miR-18e-5p in plasma samples derived from patients P03 and P04 (Figure 5(b)). Next, this study investigated the dose-dependent effects of heparinase I on plasma samples afterin vivo heparinization. Figure 5(d) shows that heparinase I improved the qPCR signals of cel-miR-39 and miR-15b-5p at both RT and 4°C. However, 0.25 U heparinase I obtained a significantly larger delta Ct compared to 0.025 U and 0.0025 U heparinase I. In Figure 5(e), a comparison of the Ct values for all miRNA candidates in the multiplex detection panel shows that the total increase in miRNA was ~2 Ct after treatment with 0.25 U at RT and at 4°C. These results indicate that treatment with 0.25 U of heparinase I obtained a Ct value similar to that in untreated samples.Figure 5
Heparinase I treatment improved Ct values of qPCR signals of clinical samples. (a) The qPCR signal was enhanced by treatment with 0.5 U and 0.25 U of heparinase I in spike-in control cel-miR-39 in four individual plasma samples stored for 0.5 h (top) or at 8 h (bottom) at RT or at 4°C. (b) Two individual plasma samples (P03 ad P04) treated with 0.5 U and 0.25 U heparinase I showed similar qPCR detection results for four independent miRNA targets. (c) Heparinase I treatment improved the qPCR signal. For cel-miR-39 (top), a dose-dependent effect of heparinase I was obsercved in samples stored for 2 h or 4 h at RT or at 4°C. Similar results were observed in four individual samples of human miR-15b-5p. (d) A heparinase I dose of 0.25 U significantly improved the qPCR signal in samples stored for 2 h or 4 h at RT or at 4°C in one-way ANOVA.P
∗
∗
∗
<
0.001; P
∗
∗
<
0.01; P
∗
<
0.05.
(a)
(b)
(d)
(e)Expressions of 18 miRNA in individuals treated with 0.25 U heparinase were similar. Figure6(a) shows that, in four individuals, expression of miRNA did not differ at RT or at 4°C after 2 h or 4 h. To simulate the common clinical scenario of delayed sample processing, correlation coefficients between 2 h and 4 h were calculated for 0.25 U heparinase I at both RT and 4°C. Figure 6(b) shows that the correlation coefficients were 0.84–0.93 between different standby times and temperatures (P
<
0.05). The experimental results show that that treatment with 0.25 U heparinase I improves the Ct value of plasma samples stored for 2 h or for 4 h at RT or at 4°C.Figure 6
Conservative correlation of miRNA expression induced by heparinase I treatment. (a) In four individuals, treatment with 0.25 U heparinase I induced similar miRNA expression levels in samples stored for 2 h at RT or at 4°C (top). Similar results were observed in samples stored for 4 h (bottom). (b) One-way ANOVA showed that miRNA expression induced by 0.25 U heparinase I treatment significantly correlated with storage time and storage temperature.
(a)
(b)
## 3.1. Patient Characteristics
Table1 lists the demographic characteristics of the cohort of 25 patients enrolled in this study. The patients had a mean age of 62.0
±
6.6 years, and 76% (19) of the patients were male. One patient underwent cardiac catheterization to evaluate the etiology of heart failure, and 24 patients underwent cardiac catheterization to evaluate the severity of coronary artery disease.Table 1
Patient demographics.
Clinical characteristics
Patient number (%)
Age (years)
62.0 ± 6.6
Male
19 (76%)
Hypertension
20 (80%)
Diabetes
10 (40%)
Atrial fibrillation
4 (16%)
Heart failure
6 (24%)
Stroke
5 (20%)
Coronary artery disease
5 (20%)
Chronic kidney disease
5 (20%)
Indications for cardiac catheterization
Evaluation of coronary artery disease
24 (96%)
Evaluation of heart failure
1 (4%)
## 3.2. Specificity of Primer and Probe for Candidate miRNA
Since both nonspecific and background signals can interfere with qPCR, the TaqMan probe specificity with its correlated synthetic cDNA was tested in each of the 18 candidate miRNA targets in this study (Supplementary Fig. 2) to determine the miRNA signal with the best specificity. Cel-miR-238 was used as the spike-in control for monitoring RNA extraction and qPCR detection in plasma samples during the experiment. The primers were designed specifically for the 18 candidate miRNA targets, which were selected because they are known to be associated with CVD. After qPCR assay, the quantification cycle (Ct) value was converted to the copy number (106 copies of each cDNA used as template for qPCR). Supplementary Fig. 2 shows the PCR results, which indicated that each probe had high specificity and high affinity with its own cDNA template. The PCR results indicated that all gene-specific primers and probes were suitable for detecting all candidate miRNAs in our clinical samples.
## 3.3. Hemolysis Test
Hemolysis of RBC in clinical samples interferes with the Ct value of qPCR. Additionally, miR-451a expression is associated with hemolysis whereas miR-23a is constant in hemolyzed blood samples [25, 38]. Therefore, this study investigated whether the miR-451a/miR-23a ratio is a good marker of significant hemolysis. First, an artificial mechanical method was used to generate eight different hemolysis grades (grades 0 to 7) from blood samples from four subjects. Supplementary Fig. 1B shows the plasma samples prepared from hemolyzed blood samples. Expressions of miR-451a and miR-23a in these plasma samples were then measured by qPCR. Figures 2(a) and 2(b) show that expressions of miR-451a and miR-23a, respectively, remained stable in unhemolyzed blood samples kept at RT or at 4°C for varying durations. Figure 2(c) shows that, in further comparisons with other plasma samples of varying hemolysis grades kept at RT for 0 h or 2 h in the same study subjects, a high miR-451a/miR-23a ratio correlated with a high grade of hemolysis. Since hemoglobin 1 g/L [5, 39] is considered mild hemolysis, this study defined significant hemolysis as a hemolysis grade of >0.12%. A receiver operating characteristics curve analysis showed that the miR-451a/miR-23a ratio had an area under the curve value of 1.0 (P
<
0.001), which indicated that this ratio is a good hemolysis marker. When the cut-off point for the miR-451a/miR-23a ratio was set to 60, both the sensitivity and the specificity were 100% (Supplementary Table 1).Figure 2
Expressions of miR-425a and miR-23a represent the hemolysis status of clinical samples. The qPCR analysis revealed that expressions of miR-451a and miR-23a stored at (a) RT or (b) at 4°C were stable from 0 h to 8 h. The Ct values shown in the tables indicate the qPCR results for five individuals at different time points. TheP value indicates the significance of each time point compared with time 0 h. (c) Manual hemolysis test was performed in 32 differential hemolytic plasma samples (see Materials and Methods). Hemolytic grade was defined by hemolysis card (Supplementary Fig. 1A). The miR-425a/miR-23a ratio increased as hemolysis grade increased.
(a)
(b)
(c)
## 3.4. Sample Storage at RT Is Better Than Storage at 4°C
To determine the optimal storage condition for plasma samples used for qPCR detection, plasma samples from five patients (P03, P04, P08, P10, and P11) were used as the training group for qPCR. In each sample, the delta Ct value and average of the 18 miRNA targets were normalized to each Ct value at time 0 at RT (Figure3(a)) and at 4°C (Figure 3(b)). The results showed that storage time significantly affected the qPCR Ct value under both the RT and 4°C conditions (P
<
0.0001 and P
=
0.0368, resp.). These results indicate the need to consider plasma storage conditions when performing qPCR data analysis. To determine the best storage condition, the delta Ct value relative to time 0 of each miRNA was calculated for samples P03, P04, P08, P10, and P11. Figure 3(c) shows that the RT and 4°C conditions significantly differed (P
<
0.0001) at 0.5 h, 1 h, and 2 h but not at 4 h. The delta Ct value adjusted to time 0 revealed that the change was smaller at RT than at 4°C before 4 h. These results showed that, for plasma samples processed within 2 h, those stored at RT yield more reliable qPCR results compared to those stored at 4°C.Figure 3
Plasma storage condition test. The miRNA expressin patterns at time 0 h, 0,5 h, 1 h, 2 h, and 4 h for storage at (a) RT and (b) at 4°C. (c) Average change in Ct value in five clinical samples of plasma stored for varying durations ranging from 0.5 h to 4 h at RT and at 4°C. From 0.5 h to 2 h, the delta Ct was more stable at RT than at 4°C. The scale indicates the delta Ct value of the qPCR result in comparison with time 0.
(a)
(b)
(c)
## 3.5. Expression of miRNA Stored at RT for 2 h
This study further evaluated whether samples stored at RT for 2 h were suitable for miRNA detection. Plasma samples derived from nine patients were used as a test cohort to verify the changes in qPCR signals between 0 h and 2 h. Figure4 shows that the qPCR signals of 18 miRNA samples between 0 h and 2 h did not significantly differ as a whole in each patient as a whole. However, the statistical data in Table 2 show a significant reduction in the expressions of two miRNA targets (miR-15b-5p and miR-30e-5p) from 0 h to 2 h whereas the largest difference in delta Ct in the three miRNA targets was less than 1.4. These data indicate that although some miRNA targets degraded after storage at RT for 2 h, most targets remained stable.Table 2
Expression of miRNA (ct value) at 0 h and 2 h.
miRNA
0 h
2 h
P
∗
Median ± SD
Median ± SD
hsa-miR-15b-5p
30.55 ± 0.98
29.75 ± 1.07
0.0315†
hsa-miR-17-5p
29 ± 1.08
29.43 ± 1.19
0.3401
hsa-miR-19a-3p
29.85 ± 0.96
31.39 ± 1.25
0.3865
hsa-miR-20a-5p
32.98 ± 1.05
32.09 ± 1.08
0.1135
hsa-miR-21-5p
32.29 ± 0.87
32.43 ± 0.97
0.7962
hsa-miR-24-3p
28.37 ± 1.17
28.06 ± 1.26
0.8633
hsa-miR-27a-3p
30.04 ± 0.96
29.7 ± 1
0.2581
hsa-miR-27b-3p
30.35 ± 0.99
30.59 ± 1.01
1
hsa-miR-30c-5p
33.07 ± 0.98
32.78 ± 0.88
0.7962
hsa-miR-30e-5p
34.25 ± 1.11
32.84 ± 1.06
0.0315†
hsa-miR-145-5p
32.01 ± 0.8
31.31 ± 1.12
0.2581
hsa-miR-150-5p
29.84 ± 0.86
30.31 ± 0.61
0.2973
hsa-miR-199a-3p
31.51 ± 1.51
30.78 ± 1.95
0.7304
hsa-miR-210
33.6 ± 1.19
33.5 ± 1.15
0.3401
hsa-miR-221-3p
29.06 ± 1.25
29.82 ± 1.43
0.6665
hsa-miR-222-3p
31.12 ± 0.89
30.65 ± 0.92
0.1615
hsa-miR-320a
28.26 ± 0.86
28.85 ± 0.8
0.2224
hsa-miR-423-5p
28.81 ± 1.11
28.52 ± 1.07
0.4363
∗Mann–Whitney U test.
†Statistically significant.Figure 4
Comparison of samples stored at RT for 0 h and at RT for 2 h. The qPCR results at time 0 and at 2 h were compared in nine individual plasma samples.
## 3.6. Heparinase I Improves qPCR Efficiency in Plasma Samples
Heparin is commonly used to avoid blood clotting in cardiac catheterization. However, since heparin reportedly reduces qPCR signals, this study investigated whether heparinase I treatment can restore miRNA expression in RNA samples before qPCR. First, the control cel-miR-39 was used as a test indicator for comparing qPCR results. Figure5(a) shows that, regardless of whether samples were kept at RT or at 4°C and regardless of whether samples were kept for 0.5 h or for 8 h, treatment with 0.25 U and 0.5 U heparinase I significantly increased heparin-reduced delta Ct by 1.5 and 2.8, respectively. Similar results were observed for miR-15b-5p, miR-17-5p, and miR-18e-5p in plasma samples derived from patients P03 and P04 (Figure 5(b)). Next, this study investigated the dose-dependent effects of heparinase I on plasma samples afterin vivo heparinization. Figure 5(d) shows that heparinase I improved the qPCR signals of cel-miR-39 and miR-15b-5p at both RT and 4°C. However, 0.25 U heparinase I obtained a significantly larger delta Ct compared to 0.025 U and 0.0025 U heparinase I. In Figure 5(e), a comparison of the Ct values for all miRNA candidates in the multiplex detection panel shows that the total increase in miRNA was ~2 Ct after treatment with 0.25 U at RT and at 4°C. These results indicate that treatment with 0.25 U of heparinase I obtained a Ct value similar to that in untreated samples.Figure 5
Heparinase I treatment improved Ct values of qPCR signals of clinical samples. (a) The qPCR signal was enhanced by treatment with 0.5 U and 0.25 U of heparinase I in spike-in control cel-miR-39 in four individual plasma samples stored for 0.5 h (top) or at 8 h (bottom) at RT or at 4°C. (b) Two individual plasma samples (P03 ad P04) treated with 0.5 U and 0.25 U heparinase I showed similar qPCR detection results for four independent miRNA targets. (c) Heparinase I treatment improved the qPCR signal. For cel-miR-39 (top), a dose-dependent effect of heparinase I was obsercved in samples stored for 2 h or 4 h at RT or at 4°C. Similar results were observed in four individual samples of human miR-15b-5p. (d) A heparinase I dose of 0.25 U significantly improved the qPCR signal in samples stored for 2 h or 4 h at RT or at 4°C in one-way ANOVA.P
∗
∗
∗
<
0.001; P
∗
∗
<
0.01; P
∗
<
0.05.
(a)
(b)
(d)
(e)Expressions of 18 miRNA in individuals treated with 0.25 U heparinase were similar. Figure6(a) shows that, in four individuals, expression of miRNA did not differ at RT or at 4°C after 2 h or 4 h. To simulate the common clinical scenario of delayed sample processing, correlation coefficients between 2 h and 4 h were calculated for 0.25 U heparinase I at both RT and 4°C. Figure 6(b) shows that the correlation coefficients were 0.84–0.93 between different standby times and temperatures (P
<
0.05). The experimental results show that that treatment with 0.25 U heparinase I improves the Ct value of plasma samples stored for 2 h or for 4 h at RT or at 4°C.Figure 6
Conservative correlation of miRNA expression induced by heparinase I treatment. (a) In four individuals, treatment with 0.25 U heparinase I induced similar miRNA expression levels in samples stored for 2 h at RT or at 4°C (top). Similar results were observed in samples stored for 4 h (bottom). (b) One-way ANOVA showed that miRNA expression induced by 0.25 U heparinase I treatment significantly correlated with storage time and storage temperature.
(a)
(b)
## 4. Discussion
Because both plasma samples and serum samples are easily obtained, circulating miRNA is now considered emerging biomarkers for many diseases [25]. Many factors, for example, anticoagulant treatment, can affect the signal obtained in miRNA measurement [36]. Therefore, the plasma processing procedure is an important issue because procedural differences can obtain very different test results. Procedural differences may also explain the wide diversity of biomarkers used for the same disease in previous publications. Blood samples extracted must be processed into plasma or serum before miRNA measurement. However, miRNA in whole blood samples or processed plasma stored at RT or even refrigerated may start to degrade [40]. Another problem is that blood samples may not be adequately protected in emergency wards and in some clinical scenarios. Hence, the objective of this study was to develop and validate a standard procedure for processing heparinase I. Experiments showed that miRNA stored at RT remains stable for 2 h after the sample is taken and that 0.25 U heparinase I can recover the qPCR signal of miRNA when the signal is attenuated by heparin treatment.
### 4.1. Optimized Clinical Procedure for Sample Collection and Processing
In clinical practice, plasma sampling and RNA extraction are performed using diverse methods [25, 26]. Additionally, the time needed for withdrawing and processing blood samples may vary widely in different clinical settings. These confounding factors may then affect miRNA measurements. Our experiments compared qPCR signals at different time points and under different temperature conditions. The experiments showed that most target miRNAs stored at RT remained stable for 2 h, and their qPCR results were comparable to those stored at 4°C for 2 h. These data indicate that blood samples extracted from patients in an emergency department can be stably stored at RT for 2 hours. However, miR-15b-5p and miR-30e-5p measurements significantly differed between 0 h and 2 h. Notably, since only nine clinical samples were analyzed, significant differences may have resulted from individual variability. Therefore, these data should be interpreted cautiously until the degradation kinetics of specific miRNAs are clarified in further experiments.
### 4.2. Effect of Heparinase on Recovery of Heparin-I Induced Attenuation of qPCR Signals
Heparin is a widely used medication for treating CVD (including ACS) and for preventing blood clotting in some clinical procedures such as percutaneous coronary intervention and cardiac surgery. Plasma derived from CVD patients contains coagulation cascade, which is a clotting factor. Anticoagulants can cause inaccurate miRNA measurements through mechanisms that are poorly understood. Therefore, thein vivo experiments in this study investigated the effects of heparin treatment on miRNA expression. The Ct values of miRNA targets derived from plasma samples treated with or withoutFlavobacterium heparinase I were compared. The signals significantly improved in the control, cel-miR-39, and target miRNAs, and the Ct was observed almost 5 cycles earlier in samples treated with 0.25 U or with 0.5 U heparinase I and stored at RT or at 4°C after treatment. The qPCR results were superior to those reported in a previous study [41]. The effects were also consistent after different standby times and after storage at different temperatures before sample processing. Notably, the qPCR signal can be improved with aFlavobacterium heparinase I dose as low as 0.25 U. This dose is much smaller than the requiredBacteroides heparinase dose reported in a previous work [42] but obtains a similar magnitude of recovery. The experimental results show thatFlavobacterium heparinase I treatment improves qPCR signals attenuated by heparinization.
### 4.3. Clinical Implications
This study showed that, for miRNA quantification, whole blood samples should be processed into plasma within 2 hours after withdrawal and should be stored at RT rather than at 4°C. Additionally,in vitro experiments should be performed to investigate the degrading kinetics of a specific miRNA before clinical application. Finally, plasma samples should be treated with 0.25 U of heparinase I to recoverin vivo heparin-related delay of Ct in the qPCR, and the ratio of miR-451a/miR-23a should be assessed at regular intervals to evaluate hemolysis.
## 4.1. Optimized Clinical Procedure for Sample Collection and Processing
In clinical practice, plasma sampling and RNA extraction are performed using diverse methods [25, 26]. Additionally, the time needed for withdrawing and processing blood samples may vary widely in different clinical settings. These confounding factors may then affect miRNA measurements. Our experiments compared qPCR signals at different time points and under different temperature conditions. The experiments showed that most target miRNAs stored at RT remained stable for 2 h, and their qPCR results were comparable to those stored at 4°C for 2 h. These data indicate that blood samples extracted from patients in an emergency department can be stably stored at RT for 2 hours. However, miR-15b-5p and miR-30e-5p measurements significantly differed between 0 h and 2 h. Notably, since only nine clinical samples were analyzed, significant differences may have resulted from individual variability. Therefore, these data should be interpreted cautiously until the degradation kinetics of specific miRNAs are clarified in further experiments.
## 4.2. Effect of Heparinase on Recovery of Heparin-I Induced Attenuation of qPCR Signals
Heparin is a widely used medication for treating CVD (including ACS) and for preventing blood clotting in some clinical procedures such as percutaneous coronary intervention and cardiac surgery. Plasma derived from CVD patients contains coagulation cascade, which is a clotting factor. Anticoagulants can cause inaccurate miRNA measurements through mechanisms that are poorly understood. Therefore, thein vivo experiments in this study investigated the effects of heparin treatment on miRNA expression. The Ct values of miRNA targets derived from plasma samples treated with or withoutFlavobacterium heparinase I were compared. The signals significantly improved in the control, cel-miR-39, and target miRNAs, and the Ct was observed almost 5 cycles earlier in samples treated with 0.25 U or with 0.5 U heparinase I and stored at RT or at 4°C after treatment. The qPCR results were superior to those reported in a previous study [41]. The effects were also consistent after different standby times and after storage at different temperatures before sample processing. Notably, the qPCR signal can be improved with aFlavobacterium heparinase I dose as low as 0.25 U. This dose is much smaller than the requiredBacteroides heparinase dose reported in a previous work [42] but obtains a similar magnitude of recovery. The experimental results show thatFlavobacterium heparinase I treatment improves qPCR signals attenuated by heparinization.
## 4.3. Clinical Implications
This study showed that, for miRNA quantification, whole blood samples should be processed into plasma within 2 hours after withdrawal and should be stored at RT rather than at 4°C. Additionally,in vitro experiments should be performed to investigate the degrading kinetics of a specific miRNA before clinical application. Finally, plasma samples should be treated with 0.25 U of heparinase I to recoverin vivo heparin-related delay of Ct in the qPCR, and the ratio of miR-451a/miR-23a should be assessed at regular intervals to evaluate hemolysis.
## 5. Conclusions
Before processing into plasma for miRNA measurement, whole blood samples should be stored at RT for no longer than 2 h after withdrawal. Pretreating samples with 0.25 U heparinase I can recover miRNA signals attenuated by heparin. A reliable indicator of severe hemolysis is miR-451a/miR-23a > 60.
---
*Source: 2901938-2016-09-20.xml* | 2901938-2016-09-20_2901938-2016-09-20.md | 47,496 | Optimized Collection Protocol for Plasma MicroRNA Measurement in Patients with Cardiovascular Disease | Chi-Sheng Wu; Fen-Chiung Lin; Shu-Jen Chen; Yung-Lung Chen; Wen-Jung Chung; Cheng-I Cheng | BioMed Research International
(2016) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2016/2901938 | 2901938-2016-09-20.xml | ---
## Abstract
Background. Various microRNAs (miRNAs) are used as markers of acute coronary syndrome, in which heparinization is considered mandatory therapy. Nevertheless, a standard method of handling plasma samples has not been proposed, and the effects of heparin treatment on miRNA detection are rarely discussed.Materials and Method. This study used quantitative polymerase chain reaction (qPCR) analysis to investigate how storage temperature, standby time, hemolysis, and heparin treatment affect miRNA measurement in plasma samples from 25 patients undergoing cardiac catheterization.Results. For most miRNAs, the qPCR results remained consistent during the first 2 hours. The miRNA signals did not significantly differ between samples stored at 4°C before processing and samples stored at room temperature (RT) before processing. miR-451a/miR-23a ratio < 60 indicated < 0.12% hemolysis with 100% sensitivity and 100% specificity. Pretreatment with 0.25 U heparinase I recovered qPCR signals that were reduced byin vivo heparinization.Conclusions. For miRNA measurement, blood samples stored at RT should be processed into plasma within 2 hours after withdrawal and should be pretreated with 0.25 U heparinase I to overcome heparin-attenuated miRNA signals. The miR-451a/miR-23a ratio is a reliable indicator of significant hemolysis.
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## Body
## 1. Introduction
Cardiovascular disease (CVD) includes coronary heart disease, cardiomyopathy, hypertensive heart disease, and heart failure. Risk factors for CVD include advanced age, male gender, high blood pressure, smoking, family history of CVD, and family history [1–7]. Although the incidence and mortality rate of CVD are both declining in high-income countries [1], coronary artery disease remains a leading cause of death worldwide [8]. Additionally, CVD may present as acute coronary syndrome (ACS), which has a high mortality rate. Pathologic processes involved in ACS include vascular inflammation, rupture of coronary artery plaques, platelet activation, and subsequent myocardial necrosis. Therefore, many studies have attempted to identify novel biomarkers for identifying patients at high risk of CVD. One proposed biomarker is microRNA (miRNA) [9, 10].MicroRNA is a noncoding small RNA that is 21–23 nucleotides in length. In plants, animals, and some viruses, small RNA functions as RNA silencer by modifying posttranscriptional regulation [11]. Diseases known to be regulated by miRNA include cancer [12–16], obesity [17, 18], and various other diseases of the nervous system [19], the immune system [20], and the heart [21]. MicroRNA can be sampled from body fluids such as serum, plasma, saliva, and urine. Since miRNA can be collected and detected extracellularly, a major benefit of using miRNA detection for disease diagnosis is its noninvasiveness. Specifically, recent studies indicate that circulating miRNA is a useful biomarker of various diseases [22], including ACS [23, 24].Cell matrix will be released after erythrocytes rupture due to either physical stress, or red blood cell- (RBC-) specific or RBC-abundant miRNAs are present in hemolyzed blood samples. Hemolysis can potentially affect the accuracy of miRNA quantification in a blood sample. Although studies have shown that expressions of miR-451a and miR-16 in RBCs are detectable in hemolyzed blood samples [25, 26], no studies have thoroughly investigated the potential use of miRNA as an indicator of hemolysis.In ACS patients, miRNA detection is routinely performed because altered miRNA is associated with ACS risk and outcome [27–32]. However, none of the pioneering studies in the use of miRNA detection have comprehensively discussed sample preparation. For example, reported standby times and storage temperatures of plasma samples during transport from the emergency department to the laboratory vary widely. No information regarding differential patterns of miRNA within the uncertain collection time is available. According to established guidelines, heparin treatment is essential for ACS patients [33], and heparin is known to affect accuracy in detecting miRNA signals [34–37]. Although a previous study showed that heparinase can improve quantitative real-time polymerase chain reaction (qPCR) signals [37], the optimal heparinase dose for qPCR has not been determined.Therefore, this study developed a multiplex qPCR system for simultaneously screening 18 miRNA targets and determined the optimal miR-451a/miR-23a ratio for predicting hemolysis in plasma samples. A literature review shows that this study is the first report of a standardized procedure for clinical measurement of miRNA in plasma samples from CVD patients and the first to determine the optimal heparinase dose for qPCR.
## 2. Materials and Methods
### 2.1. Clinical Sample Collection
This study was approved by the Institutional Review Board of Kaohsiung Chang Gung Memorial Hospital (102-1790A3). The recruitment criteria were age of 30–70 years, clinical indications for elective cardiac catheterization for ischemic heart disease or heart failure, and written informed consent. Exclusion criteria were hemoglobin less than 12 g/dL, pregnancy, peritoneal dialysis or hemodialysis for end stage renal disease, acute myocardial infarction, contraindications for heparinization, and unstable hemodynamic condition. Clinical data collection included clinical indication for cardiac catheterization and demography.During cardiac catheterization, the radial artery was cannulated with a 6 Fr artery sheath, and 36 mL of unheparinized blood was withdrawn from the sheath. Five minutes after administration of heparin 100 U/Kg through the artery sheath, another 36 mL of heparinized blood was withdrawn. For the coronary angiogram, a cardiac catheter was inserted to ensure an even distribution of heparin in the circulatory system. Next, 6 mL of heparinized or unheparinized blood was dispensed into a 10-mL EDTA K2 tube (BD Vacutainer, Ref. 367525) and kept still at either room temperature (RT) or at 4°C for the time intervals shown in Figure1. The tube containing the blood sample was centrifuged at 2,000 ×g for 10 minutes. The plasma was then aspirated to another 10 mL centrifuge tube and centrifuged at 2,500 ×g for 15 minutes. Finally, 300 μL of clear plasma was pipetted into a 1.5 mL eppendorf containing 6 μL of protease inhibiter (Roche, Cat. number 11836145001) and stored at −80°C.Figure 1
Flowchart of plasma sample collection procedure. Plasma samples were collected at the catheterization laboratory as described in Materials and Methods.
### 2.2. Generation of Hemolyzed Plasma Samples
Next, 1 mL unheparinized whole blood derived from some patients was aspirated from the EDTA K2 tube into an eppendorf tube. Varying degrees of hemolysis were induced by vigorous manual shaking until the color of the sample could be matched to the hemolysis color card (see Supplementary Fig. 1A in Supplementary Material available online athttp://dx.doi.org/10.1155/2016/2901938). The hemolyzed samples (Supplementary Fig. 1B) were then processed into plasma samples as described above and stored at −80°C.
### 2.3. RNA Preparation and Reverse Transcription
Total RNA from 300μL of plasma samples was subjected to miRNA extraction with miRNeasy minikit (QIAGEN, GmbH, Hilden, Germany). Briefly, 700 μL of QUIzol reagent was added to the plasma sample, and the sample was allowed to stand at RT for 5 minutes. Next, 1 nM of synthetic cel-miR-39 RNA (5′-CGAUGGGCAGCUAUAUUCACCUUG-3′) was added into the mixture as the spike-in control to monitor the RNA extraction and qPCR processing. Then, 140 μL of chloroform (Merck & Co., Inc.) was added into the sample, mixed well for 15 seconds, and left standing for 3 minutes at RT. The upper layer of 550 μL aqueous solution was aspirated by centrifugation at 15,000 ×g at 4°C for 15 minutes and then thoroughly mixed with 825 μL of ethanol. The samples were further eluted through the microcolumn and washed with RWP and RPE buffer. Finally, total RNA was dissolved in 30 μL of RNase-free water. To convert the detected miRNA into its corresponding cDNA, 5.4 μL of total RNA, 75 nM of 20 miRNA primers mix, 0.5 mM dNTP, 2 U RNaseout, and 120 U Superscript III (Invitrogen, CA) were used for reverse transcription reaction in a total reaction mixture of 12 μL. The processing program was 16°C for 30 minutes; 49 cycles of 20°C for 30 seconds, 42°C for 30 seconds, and 50°C for 1 second; and 72°C for 10 minutes. Reverse transcription products were stored at −20°C.
### 2.4. qPCR Assay
In qPCR assay of 8μL miRNA, 0.5 μL of a 5-fold dilution of RT product was used as a template. The template was mixed with 4 μL 2x Master Mix (Applied Biosystems, Foster City, CA), 0.25 M universal reverse primer, 0.2 M gene-specific primers, and 0.125 mM TaqMan probe (Applied Biosystems, Foster City, CA). The qPCR conditions (QuantStudio™ 12K Flex Real-time PCR System, Applied Biosystems, Foster City, CA) were 95°C for 10 minutes; 45 cycles of 95°C for 15 seconds and 60°C for 30 seconds; and a dissociation stage.
### 2.5. miRNA Data Analysis
The cycle threshold (Ct) value was calculated by determining the cycle number at which the change in fluorescence intensity crossed the threshold of 0.05. For each sample, the delta Ct was calculated by subtracting the Ct of the sample from the Ct of cel-miR-238. The normalized delta Ct was converted to the miRNA copy number as the copies per uL of plasma.
### 2.6. Heparinase I Usage
To evaluate whether heparinase reverses heparin-related effects on miRNA measurement, heparinase I (H2519, SIGMA-ALDRICH, USA) doses of 0.5 U, 0.25 U, 0.025 U, and 0.0025 U were added into reverse transcription reaction mixes. Briefly, 5.4μL of the RNA samples derived from heparinized blood was incubated with different doses of heparinase I, 2 U of RNase out, and 1.25 mM MgCl2 at 25°C for 1 hour. The RT reaction procedure described above was then performed.
### 2.7. Statistical Analysis
In the storage condition validation group, the variation between 0 h and 2 h was analyzed in each patient by Mann–Whitney test. AP value of <0.05 was considered statistically significant. In each patient, the effects of various heparinase dosages administered at RT and at 4°C were compared by ANOVA.
## 2.1. Clinical Sample Collection
This study was approved by the Institutional Review Board of Kaohsiung Chang Gung Memorial Hospital (102-1790A3). The recruitment criteria were age of 30–70 years, clinical indications for elective cardiac catheterization for ischemic heart disease or heart failure, and written informed consent. Exclusion criteria were hemoglobin less than 12 g/dL, pregnancy, peritoneal dialysis or hemodialysis for end stage renal disease, acute myocardial infarction, contraindications for heparinization, and unstable hemodynamic condition. Clinical data collection included clinical indication for cardiac catheterization and demography.During cardiac catheterization, the radial artery was cannulated with a 6 Fr artery sheath, and 36 mL of unheparinized blood was withdrawn from the sheath. Five minutes after administration of heparin 100 U/Kg through the artery sheath, another 36 mL of heparinized blood was withdrawn. For the coronary angiogram, a cardiac catheter was inserted to ensure an even distribution of heparin in the circulatory system. Next, 6 mL of heparinized or unheparinized blood was dispensed into a 10-mL EDTA K2 tube (BD Vacutainer, Ref. 367525) and kept still at either room temperature (RT) or at 4°C for the time intervals shown in Figure1. The tube containing the blood sample was centrifuged at 2,000 ×g for 10 minutes. The plasma was then aspirated to another 10 mL centrifuge tube and centrifuged at 2,500 ×g for 15 minutes. Finally, 300 μL of clear plasma was pipetted into a 1.5 mL eppendorf containing 6 μL of protease inhibiter (Roche, Cat. number 11836145001) and stored at −80°C.Figure 1
Flowchart of plasma sample collection procedure. Plasma samples were collected at the catheterization laboratory as described in Materials and Methods.
## 2.2. Generation of Hemolyzed Plasma Samples
Next, 1 mL unheparinized whole blood derived from some patients was aspirated from the EDTA K2 tube into an eppendorf tube. Varying degrees of hemolysis were induced by vigorous manual shaking until the color of the sample could be matched to the hemolysis color card (see Supplementary Fig. 1A in Supplementary Material available online athttp://dx.doi.org/10.1155/2016/2901938). The hemolyzed samples (Supplementary Fig. 1B) were then processed into plasma samples as described above and stored at −80°C.
## 2.3. RNA Preparation and Reverse Transcription
Total RNA from 300μL of plasma samples was subjected to miRNA extraction with miRNeasy minikit (QIAGEN, GmbH, Hilden, Germany). Briefly, 700 μL of QUIzol reagent was added to the plasma sample, and the sample was allowed to stand at RT for 5 minutes. Next, 1 nM of synthetic cel-miR-39 RNA (5′-CGAUGGGCAGCUAUAUUCACCUUG-3′) was added into the mixture as the spike-in control to monitor the RNA extraction and qPCR processing. Then, 140 μL of chloroform (Merck & Co., Inc.) was added into the sample, mixed well for 15 seconds, and left standing for 3 minutes at RT. The upper layer of 550 μL aqueous solution was aspirated by centrifugation at 15,000 ×g at 4°C for 15 minutes and then thoroughly mixed with 825 μL of ethanol. The samples were further eluted through the microcolumn and washed with RWP and RPE buffer. Finally, total RNA was dissolved in 30 μL of RNase-free water. To convert the detected miRNA into its corresponding cDNA, 5.4 μL of total RNA, 75 nM of 20 miRNA primers mix, 0.5 mM dNTP, 2 U RNaseout, and 120 U Superscript III (Invitrogen, CA) were used for reverse transcription reaction in a total reaction mixture of 12 μL. The processing program was 16°C for 30 minutes; 49 cycles of 20°C for 30 seconds, 42°C for 30 seconds, and 50°C for 1 second; and 72°C for 10 minutes. Reverse transcription products were stored at −20°C.
## 2.4. qPCR Assay
In qPCR assay of 8μL miRNA, 0.5 μL of a 5-fold dilution of RT product was used as a template. The template was mixed with 4 μL 2x Master Mix (Applied Biosystems, Foster City, CA), 0.25 M universal reverse primer, 0.2 M gene-specific primers, and 0.125 mM TaqMan probe (Applied Biosystems, Foster City, CA). The qPCR conditions (QuantStudio™ 12K Flex Real-time PCR System, Applied Biosystems, Foster City, CA) were 95°C for 10 minutes; 45 cycles of 95°C for 15 seconds and 60°C for 30 seconds; and a dissociation stage.
## 2.5. miRNA Data Analysis
The cycle threshold (Ct) value was calculated by determining the cycle number at which the change in fluorescence intensity crossed the threshold of 0.05. For each sample, the delta Ct was calculated by subtracting the Ct of the sample from the Ct of cel-miR-238. The normalized delta Ct was converted to the miRNA copy number as the copies per uL of plasma.
## 2.6. Heparinase I Usage
To evaluate whether heparinase reverses heparin-related effects on miRNA measurement, heparinase I (H2519, SIGMA-ALDRICH, USA) doses of 0.5 U, 0.25 U, 0.025 U, and 0.0025 U were added into reverse transcription reaction mixes. Briefly, 5.4μL of the RNA samples derived from heparinized blood was incubated with different doses of heparinase I, 2 U of RNase out, and 1.25 mM MgCl2 at 25°C for 1 hour. The RT reaction procedure described above was then performed.
## 2.7. Statistical Analysis
In the storage condition validation group, the variation between 0 h and 2 h was analyzed in each patient by Mann–Whitney test. AP value of <0.05 was considered statistically significant. In each patient, the effects of various heparinase dosages administered at RT and at 4°C were compared by ANOVA.
## 3. Results
### 3.1. Patient Characteristics
Table1 lists the demographic characteristics of the cohort of 25 patients enrolled in this study. The patients had a mean age of 62.0
±
6.6 years, and 76% (19) of the patients were male. One patient underwent cardiac catheterization to evaluate the etiology of heart failure, and 24 patients underwent cardiac catheterization to evaluate the severity of coronary artery disease.Table 1
Patient demographics.
Clinical characteristics
Patient number (%)
Age (years)
62.0 ± 6.6
Male
19 (76%)
Hypertension
20 (80%)
Diabetes
10 (40%)
Atrial fibrillation
4 (16%)
Heart failure
6 (24%)
Stroke
5 (20%)
Coronary artery disease
5 (20%)
Chronic kidney disease
5 (20%)
Indications for cardiac catheterization
Evaluation of coronary artery disease
24 (96%)
Evaluation of heart failure
1 (4%)
### 3.2. Specificity of Primer and Probe for Candidate miRNA
Since both nonspecific and background signals can interfere with qPCR, the TaqMan probe specificity with its correlated synthetic cDNA was tested in each of the 18 candidate miRNA targets in this study (Supplementary Fig. 2) to determine the miRNA signal with the best specificity. Cel-miR-238 was used as the spike-in control for monitoring RNA extraction and qPCR detection in plasma samples during the experiment. The primers were designed specifically for the 18 candidate miRNA targets, which were selected because they are known to be associated with CVD. After qPCR assay, the quantification cycle (Ct) value was converted to the copy number (106 copies of each cDNA used as template for qPCR). Supplementary Fig. 2 shows the PCR results, which indicated that each probe had high specificity and high affinity with its own cDNA template. The PCR results indicated that all gene-specific primers and probes were suitable for detecting all candidate miRNAs in our clinical samples.
### 3.3. Hemolysis Test
Hemolysis of RBC in clinical samples interferes with the Ct value of qPCR. Additionally, miR-451a expression is associated with hemolysis whereas miR-23a is constant in hemolyzed blood samples [25, 38]. Therefore, this study investigated whether the miR-451a/miR-23a ratio is a good marker of significant hemolysis. First, an artificial mechanical method was used to generate eight different hemolysis grades (grades 0 to 7) from blood samples from four subjects. Supplementary Fig. 1B shows the plasma samples prepared from hemolyzed blood samples. Expressions of miR-451a and miR-23a in these plasma samples were then measured by qPCR. Figures 2(a) and 2(b) show that expressions of miR-451a and miR-23a, respectively, remained stable in unhemolyzed blood samples kept at RT or at 4°C for varying durations. Figure 2(c) shows that, in further comparisons with other plasma samples of varying hemolysis grades kept at RT for 0 h or 2 h in the same study subjects, a high miR-451a/miR-23a ratio correlated with a high grade of hemolysis. Since hemoglobin 1 g/L [5, 39] is considered mild hemolysis, this study defined significant hemolysis as a hemolysis grade of >0.12%. A receiver operating characteristics curve analysis showed that the miR-451a/miR-23a ratio had an area under the curve value of 1.0 (P
<
0.001), which indicated that this ratio is a good hemolysis marker. When the cut-off point for the miR-451a/miR-23a ratio was set to 60, both the sensitivity and the specificity were 100% (Supplementary Table 1).Figure 2
Expressions of miR-425a and miR-23a represent the hemolysis status of clinical samples. The qPCR analysis revealed that expressions of miR-451a and miR-23a stored at (a) RT or (b) at 4°C were stable from 0 h to 8 h. The Ct values shown in the tables indicate the qPCR results for five individuals at different time points. TheP value indicates the significance of each time point compared with time 0 h. (c) Manual hemolysis test was performed in 32 differential hemolytic plasma samples (see Materials and Methods). Hemolytic grade was defined by hemolysis card (Supplementary Fig. 1A). The miR-425a/miR-23a ratio increased as hemolysis grade increased.
(a)
(b)
(c)
### 3.4. Sample Storage at RT Is Better Than Storage at 4°C
To determine the optimal storage condition for plasma samples used for qPCR detection, plasma samples from five patients (P03, P04, P08, P10, and P11) were used as the training group for qPCR. In each sample, the delta Ct value and average of the 18 miRNA targets were normalized to each Ct value at time 0 at RT (Figure3(a)) and at 4°C (Figure 3(b)). The results showed that storage time significantly affected the qPCR Ct value under both the RT and 4°C conditions (P
<
0.0001 and P
=
0.0368, resp.). These results indicate the need to consider plasma storage conditions when performing qPCR data analysis. To determine the best storage condition, the delta Ct value relative to time 0 of each miRNA was calculated for samples P03, P04, P08, P10, and P11. Figure 3(c) shows that the RT and 4°C conditions significantly differed (P
<
0.0001) at 0.5 h, 1 h, and 2 h but not at 4 h. The delta Ct value adjusted to time 0 revealed that the change was smaller at RT than at 4°C before 4 h. These results showed that, for plasma samples processed within 2 h, those stored at RT yield more reliable qPCR results compared to those stored at 4°C.Figure 3
Plasma storage condition test. The miRNA expressin patterns at time 0 h, 0,5 h, 1 h, 2 h, and 4 h for storage at (a) RT and (b) at 4°C. (c) Average change in Ct value in five clinical samples of plasma stored for varying durations ranging from 0.5 h to 4 h at RT and at 4°C. From 0.5 h to 2 h, the delta Ct was more stable at RT than at 4°C. The scale indicates the delta Ct value of the qPCR result in comparison with time 0.
(a)
(b)
(c)
### 3.5. Expression of miRNA Stored at RT for 2 h
This study further evaluated whether samples stored at RT for 2 h were suitable for miRNA detection. Plasma samples derived from nine patients were used as a test cohort to verify the changes in qPCR signals between 0 h and 2 h. Figure4 shows that the qPCR signals of 18 miRNA samples between 0 h and 2 h did not significantly differ as a whole in each patient as a whole. However, the statistical data in Table 2 show a significant reduction in the expressions of two miRNA targets (miR-15b-5p and miR-30e-5p) from 0 h to 2 h whereas the largest difference in delta Ct in the three miRNA targets was less than 1.4. These data indicate that although some miRNA targets degraded after storage at RT for 2 h, most targets remained stable.Table 2
Expression of miRNA (ct value) at 0 h and 2 h.
miRNA
0 h
2 h
P
∗
Median ± SD
Median ± SD
hsa-miR-15b-5p
30.55 ± 0.98
29.75 ± 1.07
0.0315†
hsa-miR-17-5p
29 ± 1.08
29.43 ± 1.19
0.3401
hsa-miR-19a-3p
29.85 ± 0.96
31.39 ± 1.25
0.3865
hsa-miR-20a-5p
32.98 ± 1.05
32.09 ± 1.08
0.1135
hsa-miR-21-5p
32.29 ± 0.87
32.43 ± 0.97
0.7962
hsa-miR-24-3p
28.37 ± 1.17
28.06 ± 1.26
0.8633
hsa-miR-27a-3p
30.04 ± 0.96
29.7 ± 1
0.2581
hsa-miR-27b-3p
30.35 ± 0.99
30.59 ± 1.01
1
hsa-miR-30c-5p
33.07 ± 0.98
32.78 ± 0.88
0.7962
hsa-miR-30e-5p
34.25 ± 1.11
32.84 ± 1.06
0.0315†
hsa-miR-145-5p
32.01 ± 0.8
31.31 ± 1.12
0.2581
hsa-miR-150-5p
29.84 ± 0.86
30.31 ± 0.61
0.2973
hsa-miR-199a-3p
31.51 ± 1.51
30.78 ± 1.95
0.7304
hsa-miR-210
33.6 ± 1.19
33.5 ± 1.15
0.3401
hsa-miR-221-3p
29.06 ± 1.25
29.82 ± 1.43
0.6665
hsa-miR-222-3p
31.12 ± 0.89
30.65 ± 0.92
0.1615
hsa-miR-320a
28.26 ± 0.86
28.85 ± 0.8
0.2224
hsa-miR-423-5p
28.81 ± 1.11
28.52 ± 1.07
0.4363
∗Mann–Whitney U test.
†Statistically significant.Figure 4
Comparison of samples stored at RT for 0 h and at RT for 2 h. The qPCR results at time 0 and at 2 h were compared in nine individual plasma samples.
### 3.6. Heparinase I Improves qPCR Efficiency in Plasma Samples
Heparin is commonly used to avoid blood clotting in cardiac catheterization. However, since heparin reportedly reduces qPCR signals, this study investigated whether heparinase I treatment can restore miRNA expression in RNA samples before qPCR. First, the control cel-miR-39 was used as a test indicator for comparing qPCR results. Figure5(a) shows that, regardless of whether samples were kept at RT or at 4°C and regardless of whether samples were kept for 0.5 h or for 8 h, treatment with 0.25 U and 0.5 U heparinase I significantly increased heparin-reduced delta Ct by 1.5 and 2.8, respectively. Similar results were observed for miR-15b-5p, miR-17-5p, and miR-18e-5p in plasma samples derived from patients P03 and P04 (Figure 5(b)). Next, this study investigated the dose-dependent effects of heparinase I on plasma samples afterin vivo heparinization. Figure 5(d) shows that heparinase I improved the qPCR signals of cel-miR-39 and miR-15b-5p at both RT and 4°C. However, 0.25 U heparinase I obtained a significantly larger delta Ct compared to 0.025 U and 0.0025 U heparinase I. In Figure 5(e), a comparison of the Ct values for all miRNA candidates in the multiplex detection panel shows that the total increase in miRNA was ~2 Ct after treatment with 0.25 U at RT and at 4°C. These results indicate that treatment with 0.25 U of heparinase I obtained a Ct value similar to that in untreated samples.Figure 5
Heparinase I treatment improved Ct values of qPCR signals of clinical samples. (a) The qPCR signal was enhanced by treatment with 0.5 U and 0.25 U of heparinase I in spike-in control cel-miR-39 in four individual plasma samples stored for 0.5 h (top) or at 8 h (bottom) at RT or at 4°C. (b) Two individual plasma samples (P03 ad P04) treated with 0.5 U and 0.25 U heparinase I showed similar qPCR detection results for four independent miRNA targets. (c) Heparinase I treatment improved the qPCR signal. For cel-miR-39 (top), a dose-dependent effect of heparinase I was obsercved in samples stored for 2 h or 4 h at RT or at 4°C. Similar results were observed in four individual samples of human miR-15b-5p. (d) A heparinase I dose of 0.25 U significantly improved the qPCR signal in samples stored for 2 h or 4 h at RT or at 4°C in one-way ANOVA.P
∗
∗
∗
<
0.001; P
∗
∗
<
0.01; P
∗
<
0.05.
(a)
(b)
(d)
(e)Expressions of 18 miRNA in individuals treated with 0.25 U heparinase were similar. Figure6(a) shows that, in four individuals, expression of miRNA did not differ at RT or at 4°C after 2 h or 4 h. To simulate the common clinical scenario of delayed sample processing, correlation coefficients between 2 h and 4 h were calculated for 0.25 U heparinase I at both RT and 4°C. Figure 6(b) shows that the correlation coefficients were 0.84–0.93 between different standby times and temperatures (P
<
0.05). The experimental results show that that treatment with 0.25 U heparinase I improves the Ct value of plasma samples stored for 2 h or for 4 h at RT or at 4°C.Figure 6
Conservative correlation of miRNA expression induced by heparinase I treatment. (a) In four individuals, treatment with 0.25 U heparinase I induced similar miRNA expression levels in samples stored for 2 h at RT or at 4°C (top). Similar results were observed in samples stored for 4 h (bottom). (b) One-way ANOVA showed that miRNA expression induced by 0.25 U heparinase I treatment significantly correlated with storage time and storage temperature.
(a)
(b)
## 3.1. Patient Characteristics
Table1 lists the demographic characteristics of the cohort of 25 patients enrolled in this study. The patients had a mean age of 62.0
±
6.6 years, and 76% (19) of the patients were male. One patient underwent cardiac catheterization to evaluate the etiology of heart failure, and 24 patients underwent cardiac catheterization to evaluate the severity of coronary artery disease.Table 1
Patient demographics.
Clinical characteristics
Patient number (%)
Age (years)
62.0 ± 6.6
Male
19 (76%)
Hypertension
20 (80%)
Diabetes
10 (40%)
Atrial fibrillation
4 (16%)
Heart failure
6 (24%)
Stroke
5 (20%)
Coronary artery disease
5 (20%)
Chronic kidney disease
5 (20%)
Indications for cardiac catheterization
Evaluation of coronary artery disease
24 (96%)
Evaluation of heart failure
1 (4%)
## 3.2. Specificity of Primer and Probe for Candidate miRNA
Since both nonspecific and background signals can interfere with qPCR, the TaqMan probe specificity with its correlated synthetic cDNA was tested in each of the 18 candidate miRNA targets in this study (Supplementary Fig. 2) to determine the miRNA signal with the best specificity. Cel-miR-238 was used as the spike-in control for monitoring RNA extraction and qPCR detection in plasma samples during the experiment. The primers were designed specifically for the 18 candidate miRNA targets, which were selected because they are known to be associated with CVD. After qPCR assay, the quantification cycle (Ct) value was converted to the copy number (106 copies of each cDNA used as template for qPCR). Supplementary Fig. 2 shows the PCR results, which indicated that each probe had high specificity and high affinity with its own cDNA template. The PCR results indicated that all gene-specific primers and probes were suitable for detecting all candidate miRNAs in our clinical samples.
## 3.3. Hemolysis Test
Hemolysis of RBC in clinical samples interferes with the Ct value of qPCR. Additionally, miR-451a expression is associated with hemolysis whereas miR-23a is constant in hemolyzed blood samples [25, 38]. Therefore, this study investigated whether the miR-451a/miR-23a ratio is a good marker of significant hemolysis. First, an artificial mechanical method was used to generate eight different hemolysis grades (grades 0 to 7) from blood samples from four subjects. Supplementary Fig. 1B shows the plasma samples prepared from hemolyzed blood samples. Expressions of miR-451a and miR-23a in these plasma samples were then measured by qPCR. Figures 2(a) and 2(b) show that expressions of miR-451a and miR-23a, respectively, remained stable in unhemolyzed blood samples kept at RT or at 4°C for varying durations. Figure 2(c) shows that, in further comparisons with other plasma samples of varying hemolysis grades kept at RT for 0 h or 2 h in the same study subjects, a high miR-451a/miR-23a ratio correlated with a high grade of hemolysis. Since hemoglobin 1 g/L [5, 39] is considered mild hemolysis, this study defined significant hemolysis as a hemolysis grade of >0.12%. A receiver operating characteristics curve analysis showed that the miR-451a/miR-23a ratio had an area under the curve value of 1.0 (P
<
0.001), which indicated that this ratio is a good hemolysis marker. When the cut-off point for the miR-451a/miR-23a ratio was set to 60, both the sensitivity and the specificity were 100% (Supplementary Table 1).Figure 2
Expressions of miR-425a and miR-23a represent the hemolysis status of clinical samples. The qPCR analysis revealed that expressions of miR-451a and miR-23a stored at (a) RT or (b) at 4°C were stable from 0 h to 8 h. The Ct values shown in the tables indicate the qPCR results for five individuals at different time points. TheP value indicates the significance of each time point compared with time 0 h. (c) Manual hemolysis test was performed in 32 differential hemolytic plasma samples (see Materials and Methods). Hemolytic grade was defined by hemolysis card (Supplementary Fig. 1A). The miR-425a/miR-23a ratio increased as hemolysis grade increased.
(a)
(b)
(c)
## 3.4. Sample Storage at RT Is Better Than Storage at 4°C
To determine the optimal storage condition for plasma samples used for qPCR detection, plasma samples from five patients (P03, P04, P08, P10, and P11) were used as the training group for qPCR. In each sample, the delta Ct value and average of the 18 miRNA targets were normalized to each Ct value at time 0 at RT (Figure3(a)) and at 4°C (Figure 3(b)). The results showed that storage time significantly affected the qPCR Ct value under both the RT and 4°C conditions (P
<
0.0001 and P
=
0.0368, resp.). These results indicate the need to consider plasma storage conditions when performing qPCR data analysis. To determine the best storage condition, the delta Ct value relative to time 0 of each miRNA was calculated for samples P03, P04, P08, P10, and P11. Figure 3(c) shows that the RT and 4°C conditions significantly differed (P
<
0.0001) at 0.5 h, 1 h, and 2 h but not at 4 h. The delta Ct value adjusted to time 0 revealed that the change was smaller at RT than at 4°C before 4 h. These results showed that, for plasma samples processed within 2 h, those stored at RT yield more reliable qPCR results compared to those stored at 4°C.Figure 3
Plasma storage condition test. The miRNA expressin patterns at time 0 h, 0,5 h, 1 h, 2 h, and 4 h for storage at (a) RT and (b) at 4°C. (c) Average change in Ct value in five clinical samples of plasma stored for varying durations ranging from 0.5 h to 4 h at RT and at 4°C. From 0.5 h to 2 h, the delta Ct was more stable at RT than at 4°C. The scale indicates the delta Ct value of the qPCR result in comparison with time 0.
(a)
(b)
(c)
## 3.5. Expression of miRNA Stored at RT for 2 h
This study further evaluated whether samples stored at RT for 2 h were suitable for miRNA detection. Plasma samples derived from nine patients were used as a test cohort to verify the changes in qPCR signals between 0 h and 2 h. Figure4 shows that the qPCR signals of 18 miRNA samples between 0 h and 2 h did not significantly differ as a whole in each patient as a whole. However, the statistical data in Table 2 show a significant reduction in the expressions of two miRNA targets (miR-15b-5p and miR-30e-5p) from 0 h to 2 h whereas the largest difference in delta Ct in the three miRNA targets was less than 1.4. These data indicate that although some miRNA targets degraded after storage at RT for 2 h, most targets remained stable.Table 2
Expression of miRNA (ct value) at 0 h and 2 h.
miRNA
0 h
2 h
P
∗
Median ± SD
Median ± SD
hsa-miR-15b-5p
30.55 ± 0.98
29.75 ± 1.07
0.0315†
hsa-miR-17-5p
29 ± 1.08
29.43 ± 1.19
0.3401
hsa-miR-19a-3p
29.85 ± 0.96
31.39 ± 1.25
0.3865
hsa-miR-20a-5p
32.98 ± 1.05
32.09 ± 1.08
0.1135
hsa-miR-21-5p
32.29 ± 0.87
32.43 ± 0.97
0.7962
hsa-miR-24-3p
28.37 ± 1.17
28.06 ± 1.26
0.8633
hsa-miR-27a-3p
30.04 ± 0.96
29.7 ± 1
0.2581
hsa-miR-27b-3p
30.35 ± 0.99
30.59 ± 1.01
1
hsa-miR-30c-5p
33.07 ± 0.98
32.78 ± 0.88
0.7962
hsa-miR-30e-5p
34.25 ± 1.11
32.84 ± 1.06
0.0315†
hsa-miR-145-5p
32.01 ± 0.8
31.31 ± 1.12
0.2581
hsa-miR-150-5p
29.84 ± 0.86
30.31 ± 0.61
0.2973
hsa-miR-199a-3p
31.51 ± 1.51
30.78 ± 1.95
0.7304
hsa-miR-210
33.6 ± 1.19
33.5 ± 1.15
0.3401
hsa-miR-221-3p
29.06 ± 1.25
29.82 ± 1.43
0.6665
hsa-miR-222-3p
31.12 ± 0.89
30.65 ± 0.92
0.1615
hsa-miR-320a
28.26 ± 0.86
28.85 ± 0.8
0.2224
hsa-miR-423-5p
28.81 ± 1.11
28.52 ± 1.07
0.4363
∗Mann–Whitney U test.
†Statistically significant.Figure 4
Comparison of samples stored at RT for 0 h and at RT for 2 h. The qPCR results at time 0 and at 2 h were compared in nine individual plasma samples.
## 3.6. Heparinase I Improves qPCR Efficiency in Plasma Samples
Heparin is commonly used to avoid blood clotting in cardiac catheterization. However, since heparin reportedly reduces qPCR signals, this study investigated whether heparinase I treatment can restore miRNA expression in RNA samples before qPCR. First, the control cel-miR-39 was used as a test indicator for comparing qPCR results. Figure5(a) shows that, regardless of whether samples were kept at RT or at 4°C and regardless of whether samples were kept for 0.5 h or for 8 h, treatment with 0.25 U and 0.5 U heparinase I significantly increased heparin-reduced delta Ct by 1.5 and 2.8, respectively. Similar results were observed for miR-15b-5p, miR-17-5p, and miR-18e-5p in plasma samples derived from patients P03 and P04 (Figure 5(b)). Next, this study investigated the dose-dependent effects of heparinase I on plasma samples afterin vivo heparinization. Figure 5(d) shows that heparinase I improved the qPCR signals of cel-miR-39 and miR-15b-5p at both RT and 4°C. However, 0.25 U heparinase I obtained a significantly larger delta Ct compared to 0.025 U and 0.0025 U heparinase I. In Figure 5(e), a comparison of the Ct values for all miRNA candidates in the multiplex detection panel shows that the total increase in miRNA was ~2 Ct after treatment with 0.25 U at RT and at 4°C. These results indicate that treatment with 0.25 U of heparinase I obtained a Ct value similar to that in untreated samples.Figure 5
Heparinase I treatment improved Ct values of qPCR signals of clinical samples. (a) The qPCR signal was enhanced by treatment with 0.5 U and 0.25 U of heparinase I in spike-in control cel-miR-39 in four individual plasma samples stored for 0.5 h (top) or at 8 h (bottom) at RT or at 4°C. (b) Two individual plasma samples (P03 ad P04) treated with 0.5 U and 0.25 U heparinase I showed similar qPCR detection results for four independent miRNA targets. (c) Heparinase I treatment improved the qPCR signal. For cel-miR-39 (top), a dose-dependent effect of heparinase I was obsercved in samples stored for 2 h or 4 h at RT or at 4°C. Similar results were observed in four individual samples of human miR-15b-5p. (d) A heparinase I dose of 0.25 U significantly improved the qPCR signal in samples stored for 2 h or 4 h at RT or at 4°C in one-way ANOVA.P
∗
∗
∗
<
0.001; P
∗
∗
<
0.01; P
∗
<
0.05.
(a)
(b)
(d)
(e)Expressions of 18 miRNA in individuals treated with 0.25 U heparinase were similar. Figure6(a) shows that, in four individuals, expression of miRNA did not differ at RT or at 4°C after 2 h or 4 h. To simulate the common clinical scenario of delayed sample processing, correlation coefficients between 2 h and 4 h were calculated for 0.25 U heparinase I at both RT and 4°C. Figure 6(b) shows that the correlation coefficients were 0.84–0.93 between different standby times and temperatures (P
<
0.05). The experimental results show that that treatment with 0.25 U heparinase I improves the Ct value of plasma samples stored for 2 h or for 4 h at RT or at 4°C.Figure 6
Conservative correlation of miRNA expression induced by heparinase I treatment. (a) In four individuals, treatment with 0.25 U heparinase I induced similar miRNA expression levels in samples stored for 2 h at RT or at 4°C (top). Similar results were observed in samples stored for 4 h (bottom). (b) One-way ANOVA showed that miRNA expression induced by 0.25 U heparinase I treatment significantly correlated with storage time and storage temperature.
(a)
(b)
## 4. Discussion
Because both plasma samples and serum samples are easily obtained, circulating miRNA is now considered emerging biomarkers for many diseases [25]. Many factors, for example, anticoagulant treatment, can affect the signal obtained in miRNA measurement [36]. Therefore, the plasma processing procedure is an important issue because procedural differences can obtain very different test results. Procedural differences may also explain the wide diversity of biomarkers used for the same disease in previous publications. Blood samples extracted must be processed into plasma or serum before miRNA measurement. However, miRNA in whole blood samples or processed plasma stored at RT or even refrigerated may start to degrade [40]. Another problem is that blood samples may not be adequately protected in emergency wards and in some clinical scenarios. Hence, the objective of this study was to develop and validate a standard procedure for processing heparinase I. Experiments showed that miRNA stored at RT remains stable for 2 h after the sample is taken and that 0.25 U heparinase I can recover the qPCR signal of miRNA when the signal is attenuated by heparin treatment.
### 4.1. Optimized Clinical Procedure for Sample Collection and Processing
In clinical practice, plasma sampling and RNA extraction are performed using diverse methods [25, 26]. Additionally, the time needed for withdrawing and processing blood samples may vary widely in different clinical settings. These confounding factors may then affect miRNA measurements. Our experiments compared qPCR signals at different time points and under different temperature conditions. The experiments showed that most target miRNAs stored at RT remained stable for 2 h, and their qPCR results were comparable to those stored at 4°C for 2 h. These data indicate that blood samples extracted from patients in an emergency department can be stably stored at RT for 2 hours. However, miR-15b-5p and miR-30e-5p measurements significantly differed between 0 h and 2 h. Notably, since only nine clinical samples were analyzed, significant differences may have resulted from individual variability. Therefore, these data should be interpreted cautiously until the degradation kinetics of specific miRNAs are clarified in further experiments.
### 4.2. Effect of Heparinase on Recovery of Heparin-I Induced Attenuation of qPCR Signals
Heparin is a widely used medication for treating CVD (including ACS) and for preventing blood clotting in some clinical procedures such as percutaneous coronary intervention and cardiac surgery. Plasma derived from CVD patients contains coagulation cascade, which is a clotting factor. Anticoagulants can cause inaccurate miRNA measurements through mechanisms that are poorly understood. Therefore, thein vivo experiments in this study investigated the effects of heparin treatment on miRNA expression. The Ct values of miRNA targets derived from plasma samples treated with or withoutFlavobacterium heparinase I were compared. The signals significantly improved in the control, cel-miR-39, and target miRNAs, and the Ct was observed almost 5 cycles earlier in samples treated with 0.25 U or with 0.5 U heparinase I and stored at RT or at 4°C after treatment. The qPCR results were superior to those reported in a previous study [41]. The effects were also consistent after different standby times and after storage at different temperatures before sample processing. Notably, the qPCR signal can be improved with aFlavobacterium heparinase I dose as low as 0.25 U. This dose is much smaller than the requiredBacteroides heparinase dose reported in a previous work [42] but obtains a similar magnitude of recovery. The experimental results show thatFlavobacterium heparinase I treatment improves qPCR signals attenuated by heparinization.
### 4.3. Clinical Implications
This study showed that, for miRNA quantification, whole blood samples should be processed into plasma within 2 hours after withdrawal and should be stored at RT rather than at 4°C. Additionally,in vitro experiments should be performed to investigate the degrading kinetics of a specific miRNA before clinical application. Finally, plasma samples should be treated with 0.25 U of heparinase I to recoverin vivo heparin-related delay of Ct in the qPCR, and the ratio of miR-451a/miR-23a should be assessed at regular intervals to evaluate hemolysis.
## 4.1. Optimized Clinical Procedure for Sample Collection and Processing
In clinical practice, plasma sampling and RNA extraction are performed using diverse methods [25, 26]. Additionally, the time needed for withdrawing and processing blood samples may vary widely in different clinical settings. These confounding factors may then affect miRNA measurements. Our experiments compared qPCR signals at different time points and under different temperature conditions. The experiments showed that most target miRNAs stored at RT remained stable for 2 h, and their qPCR results were comparable to those stored at 4°C for 2 h. These data indicate that blood samples extracted from patients in an emergency department can be stably stored at RT for 2 hours. However, miR-15b-5p and miR-30e-5p measurements significantly differed between 0 h and 2 h. Notably, since only nine clinical samples were analyzed, significant differences may have resulted from individual variability. Therefore, these data should be interpreted cautiously until the degradation kinetics of specific miRNAs are clarified in further experiments.
## 4.2. Effect of Heparinase on Recovery of Heparin-I Induced Attenuation of qPCR Signals
Heparin is a widely used medication for treating CVD (including ACS) and for preventing blood clotting in some clinical procedures such as percutaneous coronary intervention and cardiac surgery. Plasma derived from CVD patients contains coagulation cascade, which is a clotting factor. Anticoagulants can cause inaccurate miRNA measurements through mechanisms that are poorly understood. Therefore, thein vivo experiments in this study investigated the effects of heparin treatment on miRNA expression. The Ct values of miRNA targets derived from plasma samples treated with or withoutFlavobacterium heparinase I were compared. The signals significantly improved in the control, cel-miR-39, and target miRNAs, and the Ct was observed almost 5 cycles earlier in samples treated with 0.25 U or with 0.5 U heparinase I and stored at RT or at 4°C after treatment. The qPCR results were superior to those reported in a previous study [41]. The effects were also consistent after different standby times and after storage at different temperatures before sample processing. Notably, the qPCR signal can be improved with aFlavobacterium heparinase I dose as low as 0.25 U. This dose is much smaller than the requiredBacteroides heparinase dose reported in a previous work [42] but obtains a similar magnitude of recovery. The experimental results show thatFlavobacterium heparinase I treatment improves qPCR signals attenuated by heparinization.
## 4.3. Clinical Implications
This study showed that, for miRNA quantification, whole blood samples should be processed into plasma within 2 hours after withdrawal and should be stored at RT rather than at 4°C. Additionally,in vitro experiments should be performed to investigate the degrading kinetics of a specific miRNA before clinical application. Finally, plasma samples should be treated with 0.25 U of heparinase I to recoverin vivo heparin-related delay of Ct in the qPCR, and the ratio of miR-451a/miR-23a should be assessed at regular intervals to evaluate hemolysis.
## 5. Conclusions
Before processing into plasma for miRNA measurement, whole blood samples should be stored at RT for no longer than 2 h after withdrawal. Pretreating samples with 0.25 U heparinase I can recover miRNA signals attenuated by heparin. A reliable indicator of severe hemolysis is miR-451a/miR-23a > 60.
---
*Source: 2901938-2016-09-20.xml* | 2016 |
# The Frequency of Nonmotor Symptoms among Advanced Parkinson Patients May Depend on Instrument Used for Assessment
**Authors:** Nelson Hwynn; Ihtsham U. Haq; Irene A. Malaty; Andrew S. Resnick; Michael S. Okun; Danica S. Carew; Genko Oyama; Yunfeng Dai; Samuel S. Wu; Ramon L. Rodriguez; Charles E. Jacobson; Hubert H. Fernandez
**Journal:** Parkinson's Disease
(2011)
**Publisher:** SAGE-Hindawi Access to Research
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.4061/2011/290195
---
## Abstract
Background. Nonmotor symptoms (NMS) of Parkinson's disease (PD) may be more debilitating than motor symptoms. The purpose of this study was to determine the frequency and corecognition of NMS among our advanced PD cohort (patients considered for deep brain stimulation (DBS)) and caregivers.
Methods. NMS-Questionnaire (NMS-Q), a self-administered screening questionnaire, and NMS Assessment-Scale (NMS-S), a clinician-administered scale, were administered to PD patients and caregivers. Results. We enrolled 33 PD patients (23 males, 10 females) and caregivers. The most frequent NMS among patients using NMS-Q were gastrointestinal (87.9%), sleep (84.9%), and urinary (72.7%), while the most frequent symptoms using NMS-S were sleep (90.9%), gastrointestinal (75.8%), and mood (75.8%). Patient/caregiver scoring correlations for NMS-Q and NMS-S were 0.670 (P<0.0001) and 0.527 (P=0.0016), respectively. Conclusion The frequency of NMS among advanced PD patients and correlation between patients and caregivers varied with the instrument used. The overall correlation between patient and caregiver was greater with NMS-Q than NMS-S.
---
## Body
## 1. Introduction
It is becoming increasingly recognized that PD is a multidimensional disease and that nonmotor symptoms (NMS) can potentially affect quality of life as much or more than motor dysfunction [1]. NMS may be underrecognized by physicians and include such important features as cognitive impairment, depression, and apathy. A recent paper by Carter and colleagues found that NMS may contribute more to caregiver strain and depression than motor symptoms [2]. The NMS Questionnaire (NMS-Q) was devised to screen patients and was recently validated [3]. Subsequently, an NMS Assessment Scale for Parkinson’s disease (NMS-S) has been created to assess the frequency and severity of NMS in PD [4].In a large, recent multicenter study by Barone and colleagues, 98.6% of PD patients had at least one NMS [5]. However, studies surveying NMS specifically in advanced PD patients have been limited. We suspected that, in this subset of PD patients, NMS may play even greater role and may be more prevalent.We chose a population with relatively advanced PD, and we aimed in this study to determine the frequency of NMS in PD patients and to evaluate the correlation between PD patient and caregiver perceptions of NMS.
## 2. Methods
Consecutive advanced PD patients with severe motor fluctuations who were candidates undergoing evaluation for either unilateral STN or GPI stimulation were included. All patients signed informed consents to have their data stored in a database in accordance with the Declaration of Helsinki. All subjects were between the ages of 18 to 85, had diagnosis of idiopathic PD confirmed by a movement disorders specialist (UK Brain Bank criteria), and also had a documented greater than 30% improvement in motor performance following levodopa administration (as measured by the Unified Parkinson’s Disease Rating Scale Part III). Subjects were excluded from DBS implantation and consequently from this study if they had significant and active psychiatric disease after a structured clinical interview (SCID) or if demented (DRS score of <130 or demented based on neuropsychological profile).The NMS-S and NMS-Q were separately administered to each subject and caregiver. The NMS-S (clinically driven questionnaire) was administered by a trained member of the movement disorders team just prior to DBS surgery. Patients were separated from their caregivers during scale and questionnaire administration.The NMS-Q form lists NMS symptoms with a “yes” or “no” format. “Yes” answers are assigned one point; “no” answers are assigned 0 points. The subsets were divided in an attempt to better match comparison to the NMS-S as follows: questions 1, 3, and 4–7 were grouped under thegastrointestinal symptoms subset; questions 8-9 were grouped under the urinary symptoms subset; questions 2, 10-11, and 27-28 were grouped under the miscellaneous symptoms subset; questions 12-13 and 15 were grouped under the cognition symptoms subset; questions 16-17 were grouped under the mood symptoms subset; questions 18-19 were grouped under the sexual dysfunctionsymptoms subset; questions 20-21 were grouped under the cardiovascular/falls symptoms subset; questions 22–26 were grouped under the sleep symptoms subset; questions 14, 29-30 were grouped under perceptual symptoms subset.The NMS-S not only assesses if NMS are present, but the frequency (range of 0–4) and severity (range of 0–3) are also rated. If the product of frequency x severity is 1 or greater, then 1 point is assigned. The NMS-S was designed for patients to assess their symptoms and not specifically for caregiver assessment. Using the NMS-S form, the subsets were divided as follows: questions 1-2 were grouped under thecardiovascular/falls symptom subset; questions 3–7 were grouped under the sleep/fatigue symptoms subset; questions 8–14 were grouped under the mood symptoms subset; questions 15–17 were grouped under the perceptual symptoms subset; questions 18–20 were grouped under the cognition symptoms subset; questions 21–23 were grouped under the gastrointestinal symptoms subset; questions 24–26 were grouped under the urinary symptoms subset; questions 27-28 were grouped under the sexual dysfunction symptoms subset; questions 29–32 were grouped under the miscellaneous symptoms subset.Percent prevalence was calculated by form (NMS-Q or NMS-S) and by scorer (patient or caregiver). For each domain and the total score of NMS-Q and NMS-S, Spearman's rank correlation coefficient was evaluated between patient and caregiver scoring and tested whether the correlation was significantly different from zero.
## 3. Results
Thirty-three PD patients and their caregivers were included in the study. Twenty-six patients eventually underwent STN implantation at our institution. The remaining seven patients subsequently underwent GPi implantation. The average age of PD patients who participated was 61.3 years ± 8.1. Twenty three patients were men, and 10 patients were women. The average off-medication UPDRS motor score at baseline was 40.3 points ± 11.9.
### 3.1. NMS-Q
Table1 summarizes the prevalence and correlation of NMS by patients and caregivers. According to patients, the most common NMS-Q items were GI (87.9%), sleep (84.9%), and urinary (72.7%) symptoms. The least prevalent NMS identified by PD patients were perceptual (which included diplopia and delusional thoughts) (18.2%), mood (48.5%), cardiovascular/falls (54.6%) and sexual (54.6%) symptoms.Table 1
Frequency of nonmotor symptoms. In the NMS-Q, at least 1 question in the category is “yes.” In the NMS-S, Severity “Frequency” is greater than 0 in at least 1 item in the subgroups.
NMS-QPatient evaluationCaregiver evaluationCorrelationP valuePercent prevalencePercent prevalenceGastrointestinal87.9%81.8%0.530.002Sleep84.9%90.9%0.620.0001Urinary72.7%63.6%0.620.0001Miscellaneous*69.7%69.7%0.540.001Cognition63.6%66.7%0.460.007Sexual54.6%57.1%0.420.03Cardiovascular/falls54.6%42.4%0.360.04Mood48.5%54.6%0.650<.0001Perceptual**18.2%15.2%0.460.007NMS-SPatient evaluationCaregiver evaluationCorrelationP valuePercent prevalencePercent prevalenceSleep/Fatigue90.9%93.9%0.460.01Gastrointestinal75.8%72.7%0.480.005Mood75.8%72.7%0.550.0009Miscellaneous***72.7%66.7%0.380.03Cognition60.6%69.7%0.620.0001Urinary57.6%48.5%0.470.01Sexual45.5%53.6%0.500.01Cardiovascular/falls45.5%33.3%0.390.02Perceptual****18.2%15.2%0.400.02*Refers to miscellaneous subset in NMS-Q that includes questions about change in smell, unexplained pain, unexplained weight change, swelling of legs, and excessive sweating.**Refers to perceptual subset in NMS-Q that includes questions about diplopia and delusional thoughts.***Refers to miscellaneous subset in NMS-S that includes questions about unexplained pain, change in smell, unexplained weight change, and excessive sweating.****Refers to perceptual subset in NMS-S that includes questions about hallucinations, delusional beliefs, and diplopia.According to caregivers using the NMS-Q, the most prevalent NMS symptoms were sleep (90.9%), GI (81.8%), and miscellaneous (which included unexplained pain, anosmia, weight loss, and excessive sweating) (69.7%) items. The least prevalent NMS caregivers identified were perceptual (15.2%), cardiovascular (42.4%), and mood (54.6%) symptoms.
### 3.2. NMS-S
Table1 summarizes the prevalence and correlation of NMS by patients and caregivers. According to patients, the most common NMS using the NMS-S were sleep (90.9%), GI (75.8%), and mood (75.8%) symptoms. The least prevalent NMS in PD patients were perceptual (18.2%), cardiovascular (45.5%), and sexual (45.5%) symptoms.Using the NMS-S, caregivers identified sleep (93.9%), GI (72.7%), and mood (72.7%) and cognition (69.7%) symptoms most commonly. The least prevalent NMS that their caregivers identified was perceptual (15.2%), cardiovascular (33.3%), and urinary (48.5%) symptoms.
### 3.3. Patient and Caregiver Correlations
The highest correlation of identified NMS symptoms using NMS-Q between patients and their caregivers was with mood (0.65), sleep (0.62), urinary (0.62), and miscellaneous (0.54) symptoms. The lowest correlation of identified NMS symptoms using NMS-Q between patients and their caregivers was with cardiovascular (0.36), sexual (0.42), perceptual (0.46), and gastrointestinal (0.53) symptoms (Table1).The highest correlation of identified NMS symptoms using NMS-S between patients and their caregivers was with cognition (0.62), mood (0.55), and sexual symptoms (0.50). The lowest correlation of identified NMS symptoms using NMS-S between patients and their caregivers was with miscellaneous (0.38), cardiovascular (0.39), and perceptual subsets (0.40) (Table1).Spearman’s correlation coefficient of NMS-Q scores between patient and caregiver was 0.670 (Pvalue<0.0001). Spearman’s correlation coefficient of NMS-S was 0.527 (Pvalue=0.0016).
## 3.1. NMS-Q
Table1 summarizes the prevalence and correlation of NMS by patients and caregivers. According to patients, the most common NMS-Q items were GI (87.9%), sleep (84.9%), and urinary (72.7%) symptoms. The least prevalent NMS identified by PD patients were perceptual (which included diplopia and delusional thoughts) (18.2%), mood (48.5%), cardiovascular/falls (54.6%) and sexual (54.6%) symptoms.Table 1
Frequency of nonmotor symptoms. In the NMS-Q, at least 1 question in the category is “yes.” In the NMS-S, Severity “Frequency” is greater than 0 in at least 1 item in the subgroups.
NMS-QPatient evaluationCaregiver evaluationCorrelationP valuePercent prevalencePercent prevalenceGastrointestinal87.9%81.8%0.530.002Sleep84.9%90.9%0.620.0001Urinary72.7%63.6%0.620.0001Miscellaneous*69.7%69.7%0.540.001Cognition63.6%66.7%0.460.007Sexual54.6%57.1%0.420.03Cardiovascular/falls54.6%42.4%0.360.04Mood48.5%54.6%0.650<.0001Perceptual**18.2%15.2%0.460.007NMS-SPatient evaluationCaregiver evaluationCorrelationP valuePercent prevalencePercent prevalenceSleep/Fatigue90.9%93.9%0.460.01Gastrointestinal75.8%72.7%0.480.005Mood75.8%72.7%0.550.0009Miscellaneous***72.7%66.7%0.380.03Cognition60.6%69.7%0.620.0001Urinary57.6%48.5%0.470.01Sexual45.5%53.6%0.500.01Cardiovascular/falls45.5%33.3%0.390.02Perceptual****18.2%15.2%0.400.02*Refers to miscellaneous subset in NMS-Q that includes questions about change in smell, unexplained pain, unexplained weight change, swelling of legs, and excessive sweating.**Refers to perceptual subset in NMS-Q that includes questions about diplopia and delusional thoughts.***Refers to miscellaneous subset in NMS-S that includes questions about unexplained pain, change in smell, unexplained weight change, and excessive sweating.****Refers to perceptual subset in NMS-S that includes questions about hallucinations, delusional beliefs, and diplopia.According to caregivers using the NMS-Q, the most prevalent NMS symptoms were sleep (90.9%), GI (81.8%), and miscellaneous (which included unexplained pain, anosmia, weight loss, and excessive sweating) (69.7%) items. The least prevalent NMS caregivers identified were perceptual (15.2%), cardiovascular (42.4%), and mood (54.6%) symptoms.
## 3.2. NMS-S
Table1 summarizes the prevalence and correlation of NMS by patients and caregivers. According to patients, the most common NMS using the NMS-S were sleep (90.9%), GI (75.8%), and mood (75.8%) symptoms. The least prevalent NMS in PD patients were perceptual (18.2%), cardiovascular (45.5%), and sexual (45.5%) symptoms.Using the NMS-S, caregivers identified sleep (93.9%), GI (72.7%), and mood (72.7%) and cognition (69.7%) symptoms most commonly. The least prevalent NMS that their caregivers identified was perceptual (15.2%), cardiovascular (33.3%), and urinary (48.5%) symptoms.
## 3.3. Patient and Caregiver Correlations
The highest correlation of identified NMS symptoms using NMS-Q between patients and their caregivers was with mood (0.65), sleep (0.62), urinary (0.62), and miscellaneous (0.54) symptoms. The lowest correlation of identified NMS symptoms using NMS-Q between patients and their caregivers was with cardiovascular (0.36), sexual (0.42), perceptual (0.46), and gastrointestinal (0.53) symptoms (Table1).The highest correlation of identified NMS symptoms using NMS-S between patients and their caregivers was with cognition (0.62), mood (0.55), and sexual symptoms (0.50). The lowest correlation of identified NMS symptoms using NMS-S between patients and their caregivers was with miscellaneous (0.38), cardiovascular (0.39), and perceptual subsets (0.40) (Table1).Spearman’s correlation coefficient of NMS-Q scores between patient and caregiver was 0.670 (Pvalue<0.0001). Spearman’s correlation coefficient of NMS-S was 0.527 (Pvalue=0.0016).
## 4. Discussion
The most frequent NMS in Chaudhuri’s tested cohort of PD patients using the NMS-Q included nocturia (66.7%), urinary urgency (61%), constipation (46.7%), memory (43.9%), and sadness (44.7%) [3]. Further, in the Chaudhuri and Martinez-Martin cohort, the most prevalent symptoms using the NMS-S included nocturia (59.5%), urinary urgency (53.6%), constipation (50.2%), depression (48.2%), insomnia (44.3%), and concentration (44%) [4]. A comparison to our cohort of advanced (presurgical) PD patients reveals similar findings but different rank order. When using the NMS-Q, patients in our study reported gastrointestinal, sleep, and urinary symptoms, and when using the NMS-S, PD patients reported sleep, gastrointestinal, and mood symptoms most frequently. The reasons for the differences include different cohorts, different disease severities, and a different demographic population. Also this advanced PD patient population was screened for cognitive findings and excluded for severe mood disorders prior to DBS surgery, and this may have also accounted for some of the differences.The frequency of NMS among advanced PD patients varied in our study depending on the type of instrument utilized. For example, the frequency of mood symptoms was among the top 3 in the NMS-S, but in the bottom 3 in the NMS-Q. This could be a reflection of the difference of emphasis between the scales. In the NMS-Q, there were 2 questions that made up the mood subset, while, in the NMS-S there were 7. Devoting more questions to a particular symptom may increase sensitivity of the instrument for identifying milder manifestations of difficulty. In another example, in the NMS-Q scale, the gastrointestinal subset was composed of 9 questions, while in the NMS-S scale, the gastrointestinal subset was composed of only 3 questions. Finally, another important difference is that NMS-Q is patient driven while the NMS-S is clinician driven. In the mood example, clinician interpretation of a patient’s answer may impact reporting differently than self-reported information. Self-report for items such as sexual difficulties may be more likely to capture full disclosure than face-to-face reporting, within a clinician-administered scale. For these reasons, the NMS frequencies differ and are instrument driven if they are compared head to head as a screening tool. This methodology of this study simplifies the results of the NMS-S, which is designed to assess impact of the NMS rather than simply screening for its presence as in the NMS-Q.The correlation of NMS between patients and caregivers was also variable depending on the instrument and the symptom subset. In general, there was higher overall correlation in identifying NMS between PD patients and caregivers using the NMS-Q than with NMS-S. The NMS-Q had 5 subsets where the correlation between patient and caregiver responses was greater than 0.50, while the NMS-S had only 3 reaching this level. The 3 subsets with the highest patient/caregiver correlation using NMS-Q were mood, sleep, and urinary symptoms, and this differed from the 3 subsets with the highest patient/caregiver correlation using NMS-S where cognition, mood, and sexual items emerged. Of these most correlated NMS, only mood was within the highest correlated symptoms when using both instruments. The lack of correlation using the other symptom subsets between the patients and their caregivers may have been due to the caregiver’s ability to recognize but not accurately rank the severity of symptoms close to how patients would report them. The NMS-Q is useful to screen for the presence of nonmotor symptoms in Parkinson’s patients but does not reveal the extent that these symptoms affect quality of life. The NMS-S on the other hand takes into consideration the factors of duration and severity of symptoms that are present and extent that it affects the quality of life, but the instrument is more complicated and correct completion may require a trained member of the clinic/research team and not by patients themselves. The NMS-S was not designed to be administered to caregivers, as they are less apt than patients to more fully understand both the severity and duration of NMS that patients experience, which explains why there is lower correlation between patient and caregiver scores using the NMS-S than NMS-Q.There were several limitations to our study. The small sample size was the greatest limitation. Furthermore, the prevalence of mood symptoms in this cohort may not have been truly representative of the general advanced PD state since unstable psychiatric illness and neuropsychological issues were screened out as part of establishing DBS candidacy. The data do speak to how commonly NMS occurs and that there may be issues with clinicians recognizing these features especially when focusing on motor issues and, interestingly, may be variably identified depending on which scale or questionnaire they use. Clinicians providing care and especially those providing DBS should be aware of the instrument-dependent nature of their recognition of these issues. The NMS-Q had better correlation between patients’ and caregivers’ reported symptoms, while the NMS-S offers the additional dimension of addressing severity of symptoms that are identified.In summary, while these 2 instruments have their weaknesses and differences in instrument properties, they have been used in previous epidemiological studies as a basis for determining frequencies. We realize that while our N is small and the population is indeed biased to the “surgical patient.” this may prevent us from determining the true prevalence of NMS in advanced PD and explains the difference in results between our cohort and prior results reported by Chaudhuri. Our emphasis was not as much on the accurate accounting of each NMS, but more that, when converting these scale responses to a simple “symptom is present” versus “symptom is absent,” the responses indeed varied even if the two instruments were administered by the same individuals (patient and caregivers); literally, one instrument right after the other.
---
*Source: 290195-2011-07-26.xml* | 290195-2011-07-26_290195-2011-07-26.md | 20,637 | The Frequency of Nonmotor Symptoms among Advanced Parkinson Patients May Depend on Instrument Used for Assessment | Nelson Hwynn; Ihtsham U. Haq; Irene A. Malaty; Andrew S. Resnick; Michael S. Okun; Danica S. Carew; Genko Oyama; Yunfeng Dai; Samuel S. Wu; Ramon L. Rodriguez; Charles E. Jacobson; Hubert H. Fernandez | Parkinson's Disease
(2011) | Medical & Health Sciences | SAGE-Hindawi Access to Research | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.4061/2011/290195 | 290195-2011-07-26.xml | ---
## Abstract
Background. Nonmotor symptoms (NMS) of Parkinson's disease (PD) may be more debilitating than motor symptoms. The purpose of this study was to determine the frequency and corecognition of NMS among our advanced PD cohort (patients considered for deep brain stimulation (DBS)) and caregivers.
Methods. NMS-Questionnaire (NMS-Q), a self-administered screening questionnaire, and NMS Assessment-Scale (NMS-S), a clinician-administered scale, were administered to PD patients and caregivers. Results. We enrolled 33 PD patients (23 males, 10 females) and caregivers. The most frequent NMS among patients using NMS-Q were gastrointestinal (87.9%), sleep (84.9%), and urinary (72.7%), while the most frequent symptoms using NMS-S were sleep (90.9%), gastrointestinal (75.8%), and mood (75.8%). Patient/caregiver scoring correlations for NMS-Q and NMS-S were 0.670 (P<0.0001) and 0.527 (P=0.0016), respectively. Conclusion The frequency of NMS among advanced PD patients and correlation between patients and caregivers varied with the instrument used. The overall correlation between patient and caregiver was greater with NMS-Q than NMS-S.
---
## Body
## 1. Introduction
It is becoming increasingly recognized that PD is a multidimensional disease and that nonmotor symptoms (NMS) can potentially affect quality of life as much or more than motor dysfunction [1]. NMS may be underrecognized by physicians and include such important features as cognitive impairment, depression, and apathy. A recent paper by Carter and colleagues found that NMS may contribute more to caregiver strain and depression than motor symptoms [2]. The NMS Questionnaire (NMS-Q) was devised to screen patients and was recently validated [3]. Subsequently, an NMS Assessment Scale for Parkinson’s disease (NMS-S) has been created to assess the frequency and severity of NMS in PD [4].In a large, recent multicenter study by Barone and colleagues, 98.6% of PD patients had at least one NMS [5]. However, studies surveying NMS specifically in advanced PD patients have been limited. We suspected that, in this subset of PD patients, NMS may play even greater role and may be more prevalent.We chose a population with relatively advanced PD, and we aimed in this study to determine the frequency of NMS in PD patients and to evaluate the correlation between PD patient and caregiver perceptions of NMS.
## 2. Methods
Consecutive advanced PD patients with severe motor fluctuations who were candidates undergoing evaluation for either unilateral STN or GPI stimulation were included. All patients signed informed consents to have their data stored in a database in accordance with the Declaration of Helsinki. All subjects were between the ages of 18 to 85, had diagnosis of idiopathic PD confirmed by a movement disorders specialist (UK Brain Bank criteria), and also had a documented greater than 30% improvement in motor performance following levodopa administration (as measured by the Unified Parkinson’s Disease Rating Scale Part III). Subjects were excluded from DBS implantation and consequently from this study if they had significant and active psychiatric disease after a structured clinical interview (SCID) or if demented (DRS score of <130 or demented based on neuropsychological profile).The NMS-S and NMS-Q were separately administered to each subject and caregiver. The NMS-S (clinically driven questionnaire) was administered by a trained member of the movement disorders team just prior to DBS surgery. Patients were separated from their caregivers during scale and questionnaire administration.The NMS-Q form lists NMS symptoms with a “yes” or “no” format. “Yes” answers are assigned one point; “no” answers are assigned 0 points. The subsets were divided in an attempt to better match comparison to the NMS-S as follows: questions 1, 3, and 4–7 were grouped under thegastrointestinal symptoms subset; questions 8-9 were grouped under the urinary symptoms subset; questions 2, 10-11, and 27-28 were grouped under the miscellaneous symptoms subset; questions 12-13 and 15 were grouped under the cognition symptoms subset; questions 16-17 were grouped under the mood symptoms subset; questions 18-19 were grouped under the sexual dysfunctionsymptoms subset; questions 20-21 were grouped under the cardiovascular/falls symptoms subset; questions 22–26 were grouped under the sleep symptoms subset; questions 14, 29-30 were grouped under perceptual symptoms subset.The NMS-S not only assesses if NMS are present, but the frequency (range of 0–4) and severity (range of 0–3) are also rated. If the product of frequency x severity is 1 or greater, then 1 point is assigned. The NMS-S was designed for patients to assess their symptoms and not specifically for caregiver assessment. Using the NMS-S form, the subsets were divided as follows: questions 1-2 were grouped under thecardiovascular/falls symptom subset; questions 3–7 were grouped under the sleep/fatigue symptoms subset; questions 8–14 were grouped under the mood symptoms subset; questions 15–17 were grouped under the perceptual symptoms subset; questions 18–20 were grouped under the cognition symptoms subset; questions 21–23 were grouped under the gastrointestinal symptoms subset; questions 24–26 were grouped under the urinary symptoms subset; questions 27-28 were grouped under the sexual dysfunction symptoms subset; questions 29–32 were grouped under the miscellaneous symptoms subset.Percent prevalence was calculated by form (NMS-Q or NMS-S) and by scorer (patient or caregiver). For each domain and the total score of NMS-Q and NMS-S, Spearman's rank correlation coefficient was evaluated between patient and caregiver scoring and tested whether the correlation was significantly different from zero.
## 3. Results
Thirty-three PD patients and their caregivers were included in the study. Twenty-six patients eventually underwent STN implantation at our institution. The remaining seven patients subsequently underwent GPi implantation. The average age of PD patients who participated was 61.3 years ± 8.1. Twenty three patients were men, and 10 patients were women. The average off-medication UPDRS motor score at baseline was 40.3 points ± 11.9.
### 3.1. NMS-Q
Table1 summarizes the prevalence and correlation of NMS by patients and caregivers. According to patients, the most common NMS-Q items were GI (87.9%), sleep (84.9%), and urinary (72.7%) symptoms. The least prevalent NMS identified by PD patients were perceptual (which included diplopia and delusional thoughts) (18.2%), mood (48.5%), cardiovascular/falls (54.6%) and sexual (54.6%) symptoms.Table 1
Frequency of nonmotor symptoms. In the NMS-Q, at least 1 question in the category is “yes.” In the NMS-S, Severity “Frequency” is greater than 0 in at least 1 item in the subgroups.
NMS-QPatient evaluationCaregiver evaluationCorrelationP valuePercent prevalencePercent prevalenceGastrointestinal87.9%81.8%0.530.002Sleep84.9%90.9%0.620.0001Urinary72.7%63.6%0.620.0001Miscellaneous*69.7%69.7%0.540.001Cognition63.6%66.7%0.460.007Sexual54.6%57.1%0.420.03Cardiovascular/falls54.6%42.4%0.360.04Mood48.5%54.6%0.650<.0001Perceptual**18.2%15.2%0.460.007NMS-SPatient evaluationCaregiver evaluationCorrelationP valuePercent prevalencePercent prevalenceSleep/Fatigue90.9%93.9%0.460.01Gastrointestinal75.8%72.7%0.480.005Mood75.8%72.7%0.550.0009Miscellaneous***72.7%66.7%0.380.03Cognition60.6%69.7%0.620.0001Urinary57.6%48.5%0.470.01Sexual45.5%53.6%0.500.01Cardiovascular/falls45.5%33.3%0.390.02Perceptual****18.2%15.2%0.400.02*Refers to miscellaneous subset in NMS-Q that includes questions about change in smell, unexplained pain, unexplained weight change, swelling of legs, and excessive sweating.**Refers to perceptual subset in NMS-Q that includes questions about diplopia and delusional thoughts.***Refers to miscellaneous subset in NMS-S that includes questions about unexplained pain, change in smell, unexplained weight change, and excessive sweating.****Refers to perceptual subset in NMS-S that includes questions about hallucinations, delusional beliefs, and diplopia.According to caregivers using the NMS-Q, the most prevalent NMS symptoms were sleep (90.9%), GI (81.8%), and miscellaneous (which included unexplained pain, anosmia, weight loss, and excessive sweating) (69.7%) items. The least prevalent NMS caregivers identified were perceptual (15.2%), cardiovascular (42.4%), and mood (54.6%) symptoms.
### 3.2. NMS-S
Table1 summarizes the prevalence and correlation of NMS by patients and caregivers. According to patients, the most common NMS using the NMS-S were sleep (90.9%), GI (75.8%), and mood (75.8%) symptoms. The least prevalent NMS in PD patients were perceptual (18.2%), cardiovascular (45.5%), and sexual (45.5%) symptoms.Using the NMS-S, caregivers identified sleep (93.9%), GI (72.7%), and mood (72.7%) and cognition (69.7%) symptoms most commonly. The least prevalent NMS that their caregivers identified was perceptual (15.2%), cardiovascular (33.3%), and urinary (48.5%) symptoms.
### 3.3. Patient and Caregiver Correlations
The highest correlation of identified NMS symptoms using NMS-Q between patients and their caregivers was with mood (0.65), sleep (0.62), urinary (0.62), and miscellaneous (0.54) symptoms. The lowest correlation of identified NMS symptoms using NMS-Q between patients and their caregivers was with cardiovascular (0.36), sexual (0.42), perceptual (0.46), and gastrointestinal (0.53) symptoms (Table1).The highest correlation of identified NMS symptoms using NMS-S between patients and their caregivers was with cognition (0.62), mood (0.55), and sexual symptoms (0.50). The lowest correlation of identified NMS symptoms using NMS-S between patients and their caregivers was with miscellaneous (0.38), cardiovascular (0.39), and perceptual subsets (0.40) (Table1).Spearman’s correlation coefficient of NMS-Q scores between patient and caregiver was 0.670 (Pvalue<0.0001). Spearman’s correlation coefficient of NMS-S was 0.527 (Pvalue=0.0016).
## 3.1. NMS-Q
Table1 summarizes the prevalence and correlation of NMS by patients and caregivers. According to patients, the most common NMS-Q items were GI (87.9%), sleep (84.9%), and urinary (72.7%) symptoms. The least prevalent NMS identified by PD patients were perceptual (which included diplopia and delusional thoughts) (18.2%), mood (48.5%), cardiovascular/falls (54.6%) and sexual (54.6%) symptoms.Table 1
Frequency of nonmotor symptoms. In the NMS-Q, at least 1 question in the category is “yes.” In the NMS-S, Severity “Frequency” is greater than 0 in at least 1 item in the subgroups.
NMS-QPatient evaluationCaregiver evaluationCorrelationP valuePercent prevalencePercent prevalenceGastrointestinal87.9%81.8%0.530.002Sleep84.9%90.9%0.620.0001Urinary72.7%63.6%0.620.0001Miscellaneous*69.7%69.7%0.540.001Cognition63.6%66.7%0.460.007Sexual54.6%57.1%0.420.03Cardiovascular/falls54.6%42.4%0.360.04Mood48.5%54.6%0.650<.0001Perceptual**18.2%15.2%0.460.007NMS-SPatient evaluationCaregiver evaluationCorrelationP valuePercent prevalencePercent prevalenceSleep/Fatigue90.9%93.9%0.460.01Gastrointestinal75.8%72.7%0.480.005Mood75.8%72.7%0.550.0009Miscellaneous***72.7%66.7%0.380.03Cognition60.6%69.7%0.620.0001Urinary57.6%48.5%0.470.01Sexual45.5%53.6%0.500.01Cardiovascular/falls45.5%33.3%0.390.02Perceptual****18.2%15.2%0.400.02*Refers to miscellaneous subset in NMS-Q that includes questions about change in smell, unexplained pain, unexplained weight change, swelling of legs, and excessive sweating.**Refers to perceptual subset in NMS-Q that includes questions about diplopia and delusional thoughts.***Refers to miscellaneous subset in NMS-S that includes questions about unexplained pain, change in smell, unexplained weight change, and excessive sweating.****Refers to perceptual subset in NMS-S that includes questions about hallucinations, delusional beliefs, and diplopia.According to caregivers using the NMS-Q, the most prevalent NMS symptoms were sleep (90.9%), GI (81.8%), and miscellaneous (which included unexplained pain, anosmia, weight loss, and excessive sweating) (69.7%) items. The least prevalent NMS caregivers identified were perceptual (15.2%), cardiovascular (42.4%), and mood (54.6%) symptoms.
## 3.2. NMS-S
Table1 summarizes the prevalence and correlation of NMS by patients and caregivers. According to patients, the most common NMS using the NMS-S were sleep (90.9%), GI (75.8%), and mood (75.8%) symptoms. The least prevalent NMS in PD patients were perceptual (18.2%), cardiovascular (45.5%), and sexual (45.5%) symptoms.Using the NMS-S, caregivers identified sleep (93.9%), GI (72.7%), and mood (72.7%) and cognition (69.7%) symptoms most commonly. The least prevalent NMS that their caregivers identified was perceptual (15.2%), cardiovascular (33.3%), and urinary (48.5%) symptoms.
## 3.3. Patient and Caregiver Correlations
The highest correlation of identified NMS symptoms using NMS-Q between patients and their caregivers was with mood (0.65), sleep (0.62), urinary (0.62), and miscellaneous (0.54) symptoms. The lowest correlation of identified NMS symptoms using NMS-Q between patients and their caregivers was with cardiovascular (0.36), sexual (0.42), perceptual (0.46), and gastrointestinal (0.53) symptoms (Table1).The highest correlation of identified NMS symptoms using NMS-S between patients and their caregivers was with cognition (0.62), mood (0.55), and sexual symptoms (0.50). The lowest correlation of identified NMS symptoms using NMS-S between patients and their caregivers was with miscellaneous (0.38), cardiovascular (0.39), and perceptual subsets (0.40) (Table1).Spearman’s correlation coefficient of NMS-Q scores between patient and caregiver was 0.670 (Pvalue<0.0001). Spearman’s correlation coefficient of NMS-S was 0.527 (Pvalue=0.0016).
## 4. Discussion
The most frequent NMS in Chaudhuri’s tested cohort of PD patients using the NMS-Q included nocturia (66.7%), urinary urgency (61%), constipation (46.7%), memory (43.9%), and sadness (44.7%) [3]. Further, in the Chaudhuri and Martinez-Martin cohort, the most prevalent symptoms using the NMS-S included nocturia (59.5%), urinary urgency (53.6%), constipation (50.2%), depression (48.2%), insomnia (44.3%), and concentration (44%) [4]. A comparison to our cohort of advanced (presurgical) PD patients reveals similar findings but different rank order. When using the NMS-Q, patients in our study reported gastrointestinal, sleep, and urinary symptoms, and when using the NMS-S, PD patients reported sleep, gastrointestinal, and mood symptoms most frequently. The reasons for the differences include different cohorts, different disease severities, and a different demographic population. Also this advanced PD patient population was screened for cognitive findings and excluded for severe mood disorders prior to DBS surgery, and this may have also accounted for some of the differences.The frequency of NMS among advanced PD patients varied in our study depending on the type of instrument utilized. For example, the frequency of mood symptoms was among the top 3 in the NMS-S, but in the bottom 3 in the NMS-Q. This could be a reflection of the difference of emphasis between the scales. In the NMS-Q, there were 2 questions that made up the mood subset, while, in the NMS-S there were 7. Devoting more questions to a particular symptom may increase sensitivity of the instrument for identifying milder manifestations of difficulty. In another example, in the NMS-Q scale, the gastrointestinal subset was composed of 9 questions, while in the NMS-S scale, the gastrointestinal subset was composed of only 3 questions. Finally, another important difference is that NMS-Q is patient driven while the NMS-S is clinician driven. In the mood example, clinician interpretation of a patient’s answer may impact reporting differently than self-reported information. Self-report for items such as sexual difficulties may be more likely to capture full disclosure than face-to-face reporting, within a clinician-administered scale. For these reasons, the NMS frequencies differ and are instrument driven if they are compared head to head as a screening tool. This methodology of this study simplifies the results of the NMS-S, which is designed to assess impact of the NMS rather than simply screening for its presence as in the NMS-Q.The correlation of NMS between patients and caregivers was also variable depending on the instrument and the symptom subset. In general, there was higher overall correlation in identifying NMS between PD patients and caregivers using the NMS-Q than with NMS-S. The NMS-Q had 5 subsets where the correlation between patient and caregiver responses was greater than 0.50, while the NMS-S had only 3 reaching this level. The 3 subsets with the highest patient/caregiver correlation using NMS-Q were mood, sleep, and urinary symptoms, and this differed from the 3 subsets with the highest patient/caregiver correlation using NMS-S where cognition, mood, and sexual items emerged. Of these most correlated NMS, only mood was within the highest correlated symptoms when using both instruments. The lack of correlation using the other symptom subsets between the patients and their caregivers may have been due to the caregiver’s ability to recognize but not accurately rank the severity of symptoms close to how patients would report them. The NMS-Q is useful to screen for the presence of nonmotor symptoms in Parkinson’s patients but does not reveal the extent that these symptoms affect quality of life. The NMS-S on the other hand takes into consideration the factors of duration and severity of symptoms that are present and extent that it affects the quality of life, but the instrument is more complicated and correct completion may require a trained member of the clinic/research team and not by patients themselves. The NMS-S was not designed to be administered to caregivers, as they are less apt than patients to more fully understand both the severity and duration of NMS that patients experience, which explains why there is lower correlation between patient and caregiver scores using the NMS-S than NMS-Q.There were several limitations to our study. The small sample size was the greatest limitation. Furthermore, the prevalence of mood symptoms in this cohort may not have been truly representative of the general advanced PD state since unstable psychiatric illness and neuropsychological issues were screened out as part of establishing DBS candidacy. The data do speak to how commonly NMS occurs and that there may be issues with clinicians recognizing these features especially when focusing on motor issues and, interestingly, may be variably identified depending on which scale or questionnaire they use. Clinicians providing care and especially those providing DBS should be aware of the instrument-dependent nature of their recognition of these issues. The NMS-Q had better correlation between patients’ and caregivers’ reported symptoms, while the NMS-S offers the additional dimension of addressing severity of symptoms that are identified.In summary, while these 2 instruments have their weaknesses and differences in instrument properties, they have been used in previous epidemiological studies as a basis for determining frequencies. We realize that while our N is small and the population is indeed biased to the “surgical patient.” this may prevent us from determining the true prevalence of NMS in advanced PD and explains the difference in results between our cohort and prior results reported by Chaudhuri. Our emphasis was not as much on the accurate accounting of each NMS, but more that, when converting these scale responses to a simple “symptom is present” versus “symptom is absent,” the responses indeed varied even if the two instruments were administered by the same individuals (patient and caregivers); literally, one instrument right after the other.
---
*Source: 290195-2011-07-26.xml* | 2011 |
# The Analysis of the Effect of Blood Transfusion on Changes of Blood Platelet Parameters in Patients with Leukemia Treated with Chemotherapy
**Authors:** Yangxin He; Shanshan Liang; Yali Xu; Chunjing Wan; Feng Ma; Baoyan Wang
**Journal:** Evidence-Based Complementary and Alternative Medicine
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2901993
---
## Abstract
Objective. To study and analyze the effect of blood transfusion on the change of blood platelet parameters in patients with leukemia treated with chemotherapy. Methods. Ninety-eight patients with leukemia treated with chemotherapy in the First Affiliated Hospital of Xi’an Jiaotong University from January 2021 to January 2022 were selected to observe the changes of platelet parameters before and after blood transfusion. Results. There was significant difference between pre-transfusion and post-transfusion indexes (platelet count, mean platelet volume, and hematocrit) (P<0.05). After binary logistic regression analysis, the use of antibiotics (OR = 2.235), blood transfusion history (OR = 3.086), abnormal white blood cell count (OR = 1.134), and frozen plasma transfusion (OR = 3.121) were the main factors of blood platelet parameters after transfusion in leukemia patients (P<0.05). Conclusion. Blood transfusion is beneficial to improve blood platelet parameters and prevent bleeding in patients with leukemia treated with chemotherapy. Attention should be paid to patients with risk factors for poor response to blood platelet transfusion and early intervention.
---
## Body
## 1. Introduction
Acute leukemia is a malignant clonal disease of hematopoietic stem cells. Abnormal proliferation of primitive and immature cells inhibits normal hematopoiesis of bone marrow and can also infiltrate extramedullary organs such as the liver, spleen, and lymph nodes. It is mainly divided into two types: acute lymphoblastic leukemia and acute myeloid leukemia [1], and the mortality is high in malignancies [2]. To prevent thrombocytopenia or bleeding, blood transfusion therapy is one of the supportive care measures for leukemia patients following cytotoxic chemotherapy [3, 4]. However, during blood transfusion therapy, the body is stimulated to produce anti-platelet-associated antibodies due to the immune effect of leukocytes in blood products, affecting the effect of platelet transfusion, resulting in no significant increase in platelet count, bleeding symptoms are not significantly controlled, fever, allergy, and other adverse reactions may also occur, and intracranial hemorrhage may also be caused in severe cases [5, 6]. At present, there is no unified theory about the changes of platelet coefficient and related influencing factors after blood transfusion treatment, and there are few related studies. Therefore, it is of great significance to identify the effect of blood transfusion on blood platelet parameters in leukemia patients treated with chemotherapy as early as possible and take effective intervention in a timely manner.
## 2. Study Subjects and Methods
A total of 98 leukemia patients who were treated with chemotherapy in the department of hematology from January 2021 to January 2022 in the First Affiliated Hospital of Xi’an Jiaotong University were selected by convenience sampling. All patients were diagnosed by bone marrow examination and met the Criteria for the Diagnosis and Efficacy of Hematological Diseases. Chemotherapy regimen is in line with the National Comprehensive Cancer Network (NCCN) guidelines for adult leukemia treatment. All patients received adjuvant treatment with traditional Chinese medicine. Compound ingredients: Angelica sinensis, Astragalus membranaceus, Ligustrum lucidum, Atractylodes macrocephala, Radix Pseudostellariae, Radix Scutellariae, Radix Polygoni Multiflori, wolfberry, dodder seed, Fructus Psoraleae, Morinda officinalis. The patient took the prescription orally once in the morning and once in the evening. This study was approved by the medical ethics committee of the First Affiliated Hospital of Xi’an Jiaotong University (no. xjt122), which is in line with the Declaration of Helsinki. All patients signed informed consent.
### 2.1. Inclusion Criteria
Inclusion criteria were as follows: (1) patients who signed the informed consent form of blood transfusion products and (2) patients having clear consciousness.
### 2.2. Exclusion Criteria
Exclusion criteria were as follows: (1) combined with other diseases that can lead to thrombocytopenia such as malignant tumors, rheumatism, and immune system diseases; (2) combined with important organ dysfunction; (3) patients with mental disorders who cannot cooperate with this study; and (4) breastfeeding or pregnant women.
### 2.3. Methods of Blood Transfusion
Whole blood and blood components were all included. According to the specific implementation of conventional chemotherapy regimen, when the patient developed clinical abnormalities after chemotherapy, multiple transfusions of whole blood were required, each transfusion volume was 300 ml, blood was transfused every other day for 3 consecutive transfusions, and another 10 U therapeutic dose of blood platelets was transfused.
### 2.4. Outcome Measures
Baseline data such as gender, age, disease type, antibiotic use, history of blood transfusion, and platelet type (frozen platelets and fresh platelets) were collected. Within 24 hours after the end of chemotherapy, 2 ml of fasting peripheral venous blood was extracted with EDTA anticoagulation tube. Platelet count (PLT), mean platelet volume (MPV), platelet volume distribution width (PDW), and platelet volume (PCT) were measured by automatic blood cell analyzer within 24 hours. The corrected count of increment (CCI) was calculated. CCI = (post-transfusion platelet count transfusion-pre-platelet count) (109/L) × body surface area (m2))/(total number of platelets transfused (1011/L)). If the CCI value at 24 hours after transfusion was less than 4.5 × 109/L, it indicated that the platelet transfusion was ineffective.
### 2.5. Data Analysis
Data analysis was performed using the software SPSS 24.0, expressed as mean ± standard deviation, qualitative data were described as percentages, and quantitative data were tested by normality. The platelet correlation coefficient of patients before and after blood transfusion was compared by paired samplet-test. Binary logistic regression analysis was used to analyze the influencing factors of platelet transfusion efficacy. P<0.05 indicated a statistically significant difference.
## 2.1. Inclusion Criteria
Inclusion criteria were as follows: (1) patients who signed the informed consent form of blood transfusion products and (2) patients having clear consciousness.
## 2.2. Exclusion Criteria
Exclusion criteria were as follows: (1) combined with other diseases that can lead to thrombocytopenia such as malignant tumors, rheumatism, and immune system diseases; (2) combined with important organ dysfunction; (3) patients with mental disorders who cannot cooperate with this study; and (4) breastfeeding or pregnant women.
## 2.3. Methods of Blood Transfusion
Whole blood and blood components were all included. According to the specific implementation of conventional chemotherapy regimen, when the patient developed clinical abnormalities after chemotherapy, multiple transfusions of whole blood were required, each transfusion volume was 300 ml, blood was transfused every other day for 3 consecutive transfusions, and another 10 U therapeutic dose of blood platelets was transfused.
## 2.4. Outcome Measures
Baseline data such as gender, age, disease type, antibiotic use, history of blood transfusion, and platelet type (frozen platelets and fresh platelets) were collected. Within 24 hours after the end of chemotherapy, 2 ml of fasting peripheral venous blood was extracted with EDTA anticoagulation tube. Platelet count (PLT), mean platelet volume (MPV), platelet volume distribution width (PDW), and platelet volume (PCT) were measured by automatic blood cell analyzer within 24 hours. The corrected count of increment (CCI) was calculated. CCI = (post-transfusion platelet count transfusion-pre-platelet count) (109/L) × body surface area (m2))/(total number of platelets transfused (1011/L)). If the CCI value at 24 hours after transfusion was less than 4.5 × 109/L, it indicated that the platelet transfusion was ineffective.
## 2.5. Data Analysis
Data analysis was performed using the software SPSS 24.0, expressed as mean ± standard deviation, qualitative data were described as percentages, and quantitative data were tested by normality. The platelet correlation coefficient of patients before and after blood transfusion was compared by paired samplet-test. Binary logistic regression analysis was used to analyze the influencing factors of platelet transfusion efficacy. P<0.05 indicated a statistically significant difference.
## 3. Results
### 3.1. Baseline Characteristics
This study included 52 cases of acute lymphoblastic leukemia (ALL), 22 cases of acute myeloid leukemia (AML), and 24 cases of acute promyelocytic leukemia (APL). The mean age of patients was 42.13 ± 1.02 years old (range 34 to 69 years old), males accounted for 44.9% (44/98), antibiotics were used in 38.8% (38/98), frozen plasma was transfused in 20.4% (20/98), and white blood cell count was abnormal in 24.5% (24/98). Patients who had a blood transfusion history before this transfusion accounted for 42.9%, 32 patients developed clinically abnormal changes during the chemotherapy period, and 66 patients developed clinically abnormal changes during the interval between chemotherapies (within 2 weeks after the end of the chemotherapy course), and 15 patients did not respond to platelet transfusion.
### 3.2. Changes in Blood Platelet Parameters before and after Transfusion
Comparative analysis of blood platelet parameters before and after transfusion showed that MPV, PCT, and PLT were significantly improved in patients after transfusion, as shown in Table1.Table 1
Changes in blood platelet parameters before and after transfusion.
MPV (fL)PDW (%)PCT (%)PLT (×109/L)Pre-infusion10.39 ± 0.6816.17 ± 0.030.024 ± 0.00555.90 ± 0.1624 hours after infusion10.23 ± 0.7916.23 ± 0.050.053 ± 0.00460.08 ± 0.92T−5.397−2.359−15.158−9.469P0.0060.078<0.0010.001
### 3.3. Influencing Factors of Blood Platelet Parameter Changes after Transfusion
The CCI value at 24 hours after transfusion was bounded by 4.5 × 109/L to determine whether this blood platelet transfusion was effective or ineffective, and the CCI value at 24 hours was used as the outcome measure. Among all the patients, 15 patients who failed to respond to transfusion were selected, and 15 patients were randomly selected in a ratio of 1 : 1 among 83 patients who responded to transfusion for secondary analysis. Binary logistic regression analysis showed that the use of antibiotics, history of blood transfusion, abnormal white blood cell count, and frozen plasma transfusion were the main factors affecting the changes of blood platelet parameters after transfusion in leukemia patients (P<0.05), as shown in Table 2.Table 2
Influencing factors of blood platelet parameter changes after transfusion.
B valueStandard errorWald valueOR95% CIP valueGender0.7310.6712.5374.1052.147–8.0920.347Age0.2570.83317.2467.1364.099–10.7650.134Antibiotic use0.8040.6451.5522.2350.631–7.9180.213History of transfusion2.6740.74611.4123.0862.766–5.9080.007Abnormal white blood cell count3.7050.84219.6731.1340.91–2.4190.001Platelet species1.7880.56410.3353.1212.034–8.1320.03
## 3.1. Baseline Characteristics
This study included 52 cases of acute lymphoblastic leukemia (ALL), 22 cases of acute myeloid leukemia (AML), and 24 cases of acute promyelocytic leukemia (APL). The mean age of patients was 42.13 ± 1.02 years old (range 34 to 69 years old), males accounted for 44.9% (44/98), antibiotics were used in 38.8% (38/98), frozen plasma was transfused in 20.4% (20/98), and white blood cell count was abnormal in 24.5% (24/98). Patients who had a blood transfusion history before this transfusion accounted for 42.9%, 32 patients developed clinically abnormal changes during the chemotherapy period, and 66 patients developed clinically abnormal changes during the interval between chemotherapies (within 2 weeks after the end of the chemotherapy course), and 15 patients did not respond to platelet transfusion.
## 3.2. Changes in Blood Platelet Parameters before and after Transfusion
Comparative analysis of blood platelet parameters before and after transfusion showed that MPV, PCT, and PLT were significantly improved in patients after transfusion, as shown in Table1.Table 1
Changes in blood platelet parameters before and after transfusion.
MPV (fL)PDW (%)PCT (%)PLT (×109/L)Pre-infusion10.39 ± 0.6816.17 ± 0.030.024 ± 0.00555.90 ± 0.1624 hours after infusion10.23 ± 0.7916.23 ± 0.050.053 ± 0.00460.08 ± 0.92T−5.397−2.359−15.158−9.469P0.0060.078<0.0010.001
## 3.3. Influencing Factors of Blood Platelet Parameter Changes after Transfusion
The CCI value at 24 hours after transfusion was bounded by 4.5 × 109/L to determine whether this blood platelet transfusion was effective or ineffective, and the CCI value at 24 hours was used as the outcome measure. Among all the patients, 15 patients who failed to respond to transfusion were selected, and 15 patients were randomly selected in a ratio of 1 : 1 among 83 patients who responded to transfusion for secondary analysis. Binary logistic regression analysis showed that the use of antibiotics, history of blood transfusion, abnormal white blood cell count, and frozen plasma transfusion were the main factors affecting the changes of blood platelet parameters after transfusion in leukemia patients (P<0.05), as shown in Table 2.Table 2
Influencing factors of blood platelet parameter changes after transfusion.
B valueStandard errorWald valueOR95% CIP valueGender0.7310.6712.5374.1052.147–8.0920.347Age0.2570.83317.2467.1364.099–10.7650.134Antibiotic use0.8040.6451.5522.2350.631–7.9180.213History of transfusion2.6740.74611.4123.0862.766–5.9080.007Abnormal white blood cell count3.7050.84219.6731.1340.91–2.4190.001Platelet species1.7880.56410.3353.1212.034–8.1320.03
## 4. Discussion
Leukemia is a clonal malignant disease with abnormal hematopoietic stem cells, which has a great impact on the life safety of patients. Clinical manifestations of patients were anemia, infection, severe bleeding symptoms, and death in severe cases. At present, chemotherapy is mainly used to improve the clinical symptoms of patients in clinical practice, mainly to change blood platelet parameters, and specific treatment is carried out [7]. Different degrees of bleeding caused by thrombocytopenia in patients with leukemia after chemotherapy are the main factors leading to death. Blood transfusion is currently one of the common methods to treat and prevent bleeding in patients with acute leukemia. However, in repeated blood transfusion, bone marrow megakaryocytes divide and proliferate, significantly reducing the effect of blood transfusion [8]. Adverse reactions of blood transfusion may occur, which can seriously interfere the therapeutic effect and lead to various serious consequences such as blood transfusion lung injury and pulmonary microvascular embolism, increasing the risk of death [9]. Exploring the changes of blood platelet parameters and influencing factors in patients with leukemia treated with after blood transfusion and giving targeted suggestions are the key to guide the planning of treatment options and improve the therapeutic effect.In this study, patients with leukemia treated with chemotherapy received blood transfusion treatment, including whole blood transfusion and blood components. The main purpose was to prevent bleeding and regulate platelet-related parameters. MPV, PCT, and PLT were significantly different before and after transfusion, which indicated that blood transfusion could improve blood platelet parameters and prevent bleeding in patients with leukemia received chemotherapy. This finding is partially in contrast to the findings of Comont et al.’s study [10], which showed that in multiple transfusions, patients developed platelet antibodies, PCT and PLT gradually decreased, and MPV gradually increased. Although transfusion of whole blood and component blood can bring obvious therapeutic effect, it affects the therapeutic effect due to the complex components of blood products [11].At present, the effect of blood transfusion on blood platelet parameters in patients with leukemia who received chemotherapy is influenced by multiple factors, but the results of various studies are not uniform [12, 13]. In this study, the results of binary logistic regression analysis showed that the use of antibiotics, history of blood transfusion, abnormal white blood cell count, and frozen plasma transfusion were the main influencing factors of ineffective platelet transfusion after blood transfusion in leukemia patients. However, there was no significant difference regardless of age or gender. Leukemia patients can be affected by a variety of factors, causing fever, infection, and other complications, requiring the use of antibiotics, resulting in a large number of platelet consumption. Inflammatory reactions can produce a variety of antibodies, resulting in rapid reduction of platelet counts and affecting platelet transfusion [14]. Frozen blood platelets increase the risk of exposure to phosphatidylserine moieties during freezing, prompting platelet activation, which in turn accelerates the rate at which blood platelets damage the mononuclear phagocytic system after entering the body, resulting in insignificant improvement in blood platelet counts and poor response to transfusions after treatment with blood platelet transfusions [15]. The study by Tantanate et al. [16] indicated that multiple blood platelet transfusions resulted in decreased platelet counts and increased risk of bleeding, similar to the finding that a blood transfusions history was a risk factor for platelet transfusion efficacy in this study. Research [17] showed that when patients receive platelet infusion, leukocytes in the body can secrete a large number of histamines, leukotrienes, and other components, which promote the body to have allergic reactions, increase the risk of hemolysis and allergy, and then affect the effect of infusion treatment, which is similar to the result that abnormal leukocytes increase the risk of ineffective infusion in this study. The sample size of this study is less, which may affect the authenticity of the results. The research is still limited, and large-sample research is needed to explore and analyze.
## 5. Conclusion
Blood transfusion is beneficial to improve blood platelet parameters and prevent bleeding in patients with leukemia treated with chemotherapy.
---
*Source: 2901993-2022-08-29.xml* | 2901993-2022-08-29_2901993-2022-08-29.md | 19,324 | The Analysis of the Effect of Blood Transfusion on Changes of Blood Platelet Parameters in Patients with Leukemia Treated with Chemotherapy | Yangxin He; Shanshan Liang; Yali Xu; Chunjing Wan; Feng Ma; Baoyan Wang | Evidence-Based Complementary and Alternative Medicine
(2022) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2901993 | 2901993-2022-08-29.xml | ---
## Abstract
Objective. To study and analyze the effect of blood transfusion on the change of blood platelet parameters in patients with leukemia treated with chemotherapy. Methods. Ninety-eight patients with leukemia treated with chemotherapy in the First Affiliated Hospital of Xi’an Jiaotong University from January 2021 to January 2022 were selected to observe the changes of platelet parameters before and after blood transfusion. Results. There was significant difference between pre-transfusion and post-transfusion indexes (platelet count, mean platelet volume, and hematocrit) (P<0.05). After binary logistic regression analysis, the use of antibiotics (OR = 2.235), blood transfusion history (OR = 3.086), abnormal white blood cell count (OR = 1.134), and frozen plasma transfusion (OR = 3.121) were the main factors of blood platelet parameters after transfusion in leukemia patients (P<0.05). Conclusion. Blood transfusion is beneficial to improve blood platelet parameters and prevent bleeding in patients with leukemia treated with chemotherapy. Attention should be paid to patients with risk factors for poor response to blood platelet transfusion and early intervention.
---
## Body
## 1. Introduction
Acute leukemia is a malignant clonal disease of hematopoietic stem cells. Abnormal proliferation of primitive and immature cells inhibits normal hematopoiesis of bone marrow and can also infiltrate extramedullary organs such as the liver, spleen, and lymph nodes. It is mainly divided into two types: acute lymphoblastic leukemia and acute myeloid leukemia [1], and the mortality is high in malignancies [2]. To prevent thrombocytopenia or bleeding, blood transfusion therapy is one of the supportive care measures for leukemia patients following cytotoxic chemotherapy [3, 4]. However, during blood transfusion therapy, the body is stimulated to produce anti-platelet-associated antibodies due to the immune effect of leukocytes in blood products, affecting the effect of platelet transfusion, resulting in no significant increase in platelet count, bleeding symptoms are not significantly controlled, fever, allergy, and other adverse reactions may also occur, and intracranial hemorrhage may also be caused in severe cases [5, 6]. At present, there is no unified theory about the changes of platelet coefficient and related influencing factors after blood transfusion treatment, and there are few related studies. Therefore, it is of great significance to identify the effect of blood transfusion on blood platelet parameters in leukemia patients treated with chemotherapy as early as possible and take effective intervention in a timely manner.
## 2. Study Subjects and Methods
A total of 98 leukemia patients who were treated with chemotherapy in the department of hematology from January 2021 to January 2022 in the First Affiliated Hospital of Xi’an Jiaotong University were selected by convenience sampling. All patients were diagnosed by bone marrow examination and met the Criteria for the Diagnosis and Efficacy of Hematological Diseases. Chemotherapy regimen is in line with the National Comprehensive Cancer Network (NCCN) guidelines for adult leukemia treatment. All patients received adjuvant treatment with traditional Chinese medicine. Compound ingredients: Angelica sinensis, Astragalus membranaceus, Ligustrum lucidum, Atractylodes macrocephala, Radix Pseudostellariae, Radix Scutellariae, Radix Polygoni Multiflori, wolfberry, dodder seed, Fructus Psoraleae, Morinda officinalis. The patient took the prescription orally once in the morning and once in the evening. This study was approved by the medical ethics committee of the First Affiliated Hospital of Xi’an Jiaotong University (no. xjt122), which is in line with the Declaration of Helsinki. All patients signed informed consent.
### 2.1. Inclusion Criteria
Inclusion criteria were as follows: (1) patients who signed the informed consent form of blood transfusion products and (2) patients having clear consciousness.
### 2.2. Exclusion Criteria
Exclusion criteria were as follows: (1) combined with other diseases that can lead to thrombocytopenia such as malignant tumors, rheumatism, and immune system diseases; (2) combined with important organ dysfunction; (3) patients with mental disorders who cannot cooperate with this study; and (4) breastfeeding or pregnant women.
### 2.3. Methods of Blood Transfusion
Whole blood and blood components were all included. According to the specific implementation of conventional chemotherapy regimen, when the patient developed clinical abnormalities after chemotherapy, multiple transfusions of whole blood were required, each transfusion volume was 300 ml, blood was transfused every other day for 3 consecutive transfusions, and another 10 U therapeutic dose of blood platelets was transfused.
### 2.4. Outcome Measures
Baseline data such as gender, age, disease type, antibiotic use, history of blood transfusion, and platelet type (frozen platelets and fresh platelets) were collected. Within 24 hours after the end of chemotherapy, 2 ml of fasting peripheral venous blood was extracted with EDTA anticoagulation tube. Platelet count (PLT), mean platelet volume (MPV), platelet volume distribution width (PDW), and platelet volume (PCT) were measured by automatic blood cell analyzer within 24 hours. The corrected count of increment (CCI) was calculated. CCI = (post-transfusion platelet count transfusion-pre-platelet count) (109/L) × body surface area (m2))/(total number of platelets transfused (1011/L)). If the CCI value at 24 hours after transfusion was less than 4.5 × 109/L, it indicated that the platelet transfusion was ineffective.
### 2.5. Data Analysis
Data analysis was performed using the software SPSS 24.0, expressed as mean ± standard deviation, qualitative data were described as percentages, and quantitative data were tested by normality. The platelet correlation coefficient of patients before and after blood transfusion was compared by paired samplet-test. Binary logistic regression analysis was used to analyze the influencing factors of platelet transfusion efficacy. P<0.05 indicated a statistically significant difference.
## 2.1. Inclusion Criteria
Inclusion criteria were as follows: (1) patients who signed the informed consent form of blood transfusion products and (2) patients having clear consciousness.
## 2.2. Exclusion Criteria
Exclusion criteria were as follows: (1) combined with other diseases that can lead to thrombocytopenia such as malignant tumors, rheumatism, and immune system diseases; (2) combined with important organ dysfunction; (3) patients with mental disorders who cannot cooperate with this study; and (4) breastfeeding or pregnant women.
## 2.3. Methods of Blood Transfusion
Whole blood and blood components were all included. According to the specific implementation of conventional chemotherapy regimen, when the patient developed clinical abnormalities after chemotherapy, multiple transfusions of whole blood were required, each transfusion volume was 300 ml, blood was transfused every other day for 3 consecutive transfusions, and another 10 U therapeutic dose of blood platelets was transfused.
## 2.4. Outcome Measures
Baseline data such as gender, age, disease type, antibiotic use, history of blood transfusion, and platelet type (frozen platelets and fresh platelets) were collected. Within 24 hours after the end of chemotherapy, 2 ml of fasting peripheral venous blood was extracted with EDTA anticoagulation tube. Platelet count (PLT), mean platelet volume (MPV), platelet volume distribution width (PDW), and platelet volume (PCT) were measured by automatic blood cell analyzer within 24 hours. The corrected count of increment (CCI) was calculated. CCI = (post-transfusion platelet count transfusion-pre-platelet count) (109/L) × body surface area (m2))/(total number of platelets transfused (1011/L)). If the CCI value at 24 hours after transfusion was less than 4.5 × 109/L, it indicated that the platelet transfusion was ineffective.
## 2.5. Data Analysis
Data analysis was performed using the software SPSS 24.0, expressed as mean ± standard deviation, qualitative data were described as percentages, and quantitative data were tested by normality. The platelet correlation coefficient of patients before and after blood transfusion was compared by paired samplet-test. Binary logistic regression analysis was used to analyze the influencing factors of platelet transfusion efficacy. P<0.05 indicated a statistically significant difference.
## 3. Results
### 3.1. Baseline Characteristics
This study included 52 cases of acute lymphoblastic leukemia (ALL), 22 cases of acute myeloid leukemia (AML), and 24 cases of acute promyelocytic leukemia (APL). The mean age of patients was 42.13 ± 1.02 years old (range 34 to 69 years old), males accounted for 44.9% (44/98), antibiotics were used in 38.8% (38/98), frozen plasma was transfused in 20.4% (20/98), and white blood cell count was abnormal in 24.5% (24/98). Patients who had a blood transfusion history before this transfusion accounted for 42.9%, 32 patients developed clinically abnormal changes during the chemotherapy period, and 66 patients developed clinically abnormal changes during the interval between chemotherapies (within 2 weeks after the end of the chemotherapy course), and 15 patients did not respond to platelet transfusion.
### 3.2. Changes in Blood Platelet Parameters before and after Transfusion
Comparative analysis of blood platelet parameters before and after transfusion showed that MPV, PCT, and PLT were significantly improved in patients after transfusion, as shown in Table1.Table 1
Changes in blood platelet parameters before and after transfusion.
MPV (fL)PDW (%)PCT (%)PLT (×109/L)Pre-infusion10.39 ± 0.6816.17 ± 0.030.024 ± 0.00555.90 ± 0.1624 hours after infusion10.23 ± 0.7916.23 ± 0.050.053 ± 0.00460.08 ± 0.92T−5.397−2.359−15.158−9.469P0.0060.078<0.0010.001
### 3.3. Influencing Factors of Blood Platelet Parameter Changes after Transfusion
The CCI value at 24 hours after transfusion was bounded by 4.5 × 109/L to determine whether this blood platelet transfusion was effective or ineffective, and the CCI value at 24 hours was used as the outcome measure. Among all the patients, 15 patients who failed to respond to transfusion were selected, and 15 patients were randomly selected in a ratio of 1 : 1 among 83 patients who responded to transfusion for secondary analysis. Binary logistic regression analysis showed that the use of antibiotics, history of blood transfusion, abnormal white blood cell count, and frozen plasma transfusion were the main factors affecting the changes of blood platelet parameters after transfusion in leukemia patients (P<0.05), as shown in Table 2.Table 2
Influencing factors of blood platelet parameter changes after transfusion.
B valueStandard errorWald valueOR95% CIP valueGender0.7310.6712.5374.1052.147–8.0920.347Age0.2570.83317.2467.1364.099–10.7650.134Antibiotic use0.8040.6451.5522.2350.631–7.9180.213History of transfusion2.6740.74611.4123.0862.766–5.9080.007Abnormal white blood cell count3.7050.84219.6731.1340.91–2.4190.001Platelet species1.7880.56410.3353.1212.034–8.1320.03
## 3.1. Baseline Characteristics
This study included 52 cases of acute lymphoblastic leukemia (ALL), 22 cases of acute myeloid leukemia (AML), and 24 cases of acute promyelocytic leukemia (APL). The mean age of patients was 42.13 ± 1.02 years old (range 34 to 69 years old), males accounted for 44.9% (44/98), antibiotics were used in 38.8% (38/98), frozen plasma was transfused in 20.4% (20/98), and white blood cell count was abnormal in 24.5% (24/98). Patients who had a blood transfusion history before this transfusion accounted for 42.9%, 32 patients developed clinically abnormal changes during the chemotherapy period, and 66 patients developed clinically abnormal changes during the interval between chemotherapies (within 2 weeks after the end of the chemotherapy course), and 15 patients did not respond to platelet transfusion.
## 3.2. Changes in Blood Platelet Parameters before and after Transfusion
Comparative analysis of blood platelet parameters before and after transfusion showed that MPV, PCT, and PLT were significantly improved in patients after transfusion, as shown in Table1.Table 1
Changes in blood platelet parameters before and after transfusion.
MPV (fL)PDW (%)PCT (%)PLT (×109/L)Pre-infusion10.39 ± 0.6816.17 ± 0.030.024 ± 0.00555.90 ± 0.1624 hours after infusion10.23 ± 0.7916.23 ± 0.050.053 ± 0.00460.08 ± 0.92T−5.397−2.359−15.158−9.469P0.0060.078<0.0010.001
## 3.3. Influencing Factors of Blood Platelet Parameter Changes after Transfusion
The CCI value at 24 hours after transfusion was bounded by 4.5 × 109/L to determine whether this blood platelet transfusion was effective or ineffective, and the CCI value at 24 hours was used as the outcome measure. Among all the patients, 15 patients who failed to respond to transfusion were selected, and 15 patients were randomly selected in a ratio of 1 : 1 among 83 patients who responded to transfusion for secondary analysis. Binary logistic regression analysis showed that the use of antibiotics, history of blood transfusion, abnormal white blood cell count, and frozen plasma transfusion were the main factors affecting the changes of blood platelet parameters after transfusion in leukemia patients (P<0.05), as shown in Table 2.Table 2
Influencing factors of blood platelet parameter changes after transfusion.
B valueStandard errorWald valueOR95% CIP valueGender0.7310.6712.5374.1052.147–8.0920.347Age0.2570.83317.2467.1364.099–10.7650.134Antibiotic use0.8040.6451.5522.2350.631–7.9180.213History of transfusion2.6740.74611.4123.0862.766–5.9080.007Abnormal white blood cell count3.7050.84219.6731.1340.91–2.4190.001Platelet species1.7880.56410.3353.1212.034–8.1320.03
## 4. Discussion
Leukemia is a clonal malignant disease with abnormal hematopoietic stem cells, which has a great impact on the life safety of patients. Clinical manifestations of patients were anemia, infection, severe bleeding symptoms, and death in severe cases. At present, chemotherapy is mainly used to improve the clinical symptoms of patients in clinical practice, mainly to change blood platelet parameters, and specific treatment is carried out [7]. Different degrees of bleeding caused by thrombocytopenia in patients with leukemia after chemotherapy are the main factors leading to death. Blood transfusion is currently one of the common methods to treat and prevent bleeding in patients with acute leukemia. However, in repeated blood transfusion, bone marrow megakaryocytes divide and proliferate, significantly reducing the effect of blood transfusion [8]. Adverse reactions of blood transfusion may occur, which can seriously interfere the therapeutic effect and lead to various serious consequences such as blood transfusion lung injury and pulmonary microvascular embolism, increasing the risk of death [9]. Exploring the changes of blood platelet parameters and influencing factors in patients with leukemia treated with after blood transfusion and giving targeted suggestions are the key to guide the planning of treatment options and improve the therapeutic effect.In this study, patients with leukemia treated with chemotherapy received blood transfusion treatment, including whole blood transfusion and blood components. The main purpose was to prevent bleeding and regulate platelet-related parameters. MPV, PCT, and PLT were significantly different before and after transfusion, which indicated that blood transfusion could improve blood platelet parameters and prevent bleeding in patients with leukemia received chemotherapy. This finding is partially in contrast to the findings of Comont et al.’s study [10], which showed that in multiple transfusions, patients developed platelet antibodies, PCT and PLT gradually decreased, and MPV gradually increased. Although transfusion of whole blood and component blood can bring obvious therapeutic effect, it affects the therapeutic effect due to the complex components of blood products [11].At present, the effect of blood transfusion on blood platelet parameters in patients with leukemia who received chemotherapy is influenced by multiple factors, but the results of various studies are not uniform [12, 13]. In this study, the results of binary logistic regression analysis showed that the use of antibiotics, history of blood transfusion, abnormal white blood cell count, and frozen plasma transfusion were the main influencing factors of ineffective platelet transfusion after blood transfusion in leukemia patients. However, there was no significant difference regardless of age or gender. Leukemia patients can be affected by a variety of factors, causing fever, infection, and other complications, requiring the use of antibiotics, resulting in a large number of platelet consumption. Inflammatory reactions can produce a variety of antibodies, resulting in rapid reduction of platelet counts and affecting platelet transfusion [14]. Frozen blood platelets increase the risk of exposure to phosphatidylserine moieties during freezing, prompting platelet activation, which in turn accelerates the rate at which blood platelets damage the mononuclear phagocytic system after entering the body, resulting in insignificant improvement in blood platelet counts and poor response to transfusions after treatment with blood platelet transfusions [15]. The study by Tantanate et al. [16] indicated that multiple blood platelet transfusions resulted in decreased platelet counts and increased risk of bleeding, similar to the finding that a blood transfusions history was a risk factor for platelet transfusion efficacy in this study. Research [17] showed that when patients receive platelet infusion, leukocytes in the body can secrete a large number of histamines, leukotrienes, and other components, which promote the body to have allergic reactions, increase the risk of hemolysis and allergy, and then affect the effect of infusion treatment, which is similar to the result that abnormal leukocytes increase the risk of ineffective infusion in this study. The sample size of this study is less, which may affect the authenticity of the results. The research is still limited, and large-sample research is needed to explore and analyze.
## 5. Conclusion
Blood transfusion is beneficial to improve blood platelet parameters and prevent bleeding in patients with leukemia treated with chemotherapy.
---
*Source: 2901993-2022-08-29.xml* | 2022 |
# An Improved Asymptotic on the Representations of Integers as Sums of Products
**Authors:** Wenjia Zhao
**Journal:** Journal of Mathematics
(2021)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2021/2902015
---
## Abstract
In this paper, we improve the error terms of Chace’s results in the study by Chace (1994) on the number of ways of writing an integerN as a sum of k products of l factors, valid for k≥3 and l=2, 3. More precisely, for l=2, 3, we improve the upper bound Nk−1−2k−2/k−1l+1+ε, k≥3 for the error term, to N2−2/2l+1+ε when k=3 and Nk−1−4k−2/l+1k+l−2+ε when k≥4.
---
## Body
## 1. Introduction
In this paper, we study the number of representations of a natural numberN as a sum of k terms, each being a product of l factors. Let νN;k,l denote this number. This problem was studied by Estermann [1, 2] in the case k=2 or 3 and l=2 by using some properties of Dirichlet L-function. His method is not easy to be generalized. Later, Chace [3] generalized Estermann’s result to k≥3 and l≥2. For such k and l, he got(1)νN;k,l=μN;k,l+EN;k,l,where(2)μN;k,l≍Nk−1logkl−1N,and(3)EN;k,l≪εNk−1−2k−2/k−1l+1+ε,ifk=3orl=2,l=3,Nk−1−3k−2/k−1l+2+ε,ifkandl≥4.Here,μN;k,l is defined in (72). The way he studied the problem is different from Estermann. The main tools he used are the Hardy–Littlewood method and some results from the divisor problem in arithmetic progressions. He got the main term μN;k,l which is a sum of terms of the form Sℐ, where S are the “singular series” and ℐ are the “singular integrals.” They occur in the applications of the Hardy–Littlewood method. In this paper, we improve Chace’s result in the cases k≥3 and l=2,3. We get the following result.Theorem 1.
Supposek≥3 and l=2,3. Then,(4)νN;k,l=μN;k,l+EN;k,l,where μN;k,l defined by (72) satisfies (2) and the error term satisfies(5)EN;k,l≪εN2−2/2l+1+ε,ifk=3,Nk−1−4k−2/l+1k+l−2+ε,ifk≥4.We can compare the exponents in (3) with our results (5). For l=2,3, we see that 2−2/2l+1<k−1−2k−2/k−1l+1=2−1/l+1 when k=3 and k−1−4k−2/l+1k+l−2<k−1−3k−2/k−1l+2 when k≥4. Our error terms are better than Chace’s.The proof of the theorem is an application of the Hardy–Littlewood method (cf, Chapter 3 of [4]), the Voronoi summation formula, and some results from the Kloosterman sums. The estimates on the minor arc were studied by Chace, and his result is sufficient for us. Hence, we will not focus on the minor arc in this paper. The main difficulty arises in treating the error term of the major arcs. In Section 2, we make some preparations for our proof. We state the Voronoi summation formula and give some lemmas related to the Kloosterman sums in this section. In Sections 3.1 and 3.2, we obtain a bound for the contribution from the minor arcs. In §3.3, we prove our theorem.
## 2. Applications of the Voronoi Summation Formula
LetX>0. Suppose that fx is a smooth function compactly supported in X−Xδ,2X+Xδ with 0<δ<1, satisfying fx=1 in X,2X and(6)fjx≪X−δj,j≥0,(7)∫fjxdx≪X−δj−1,j≥1.Let(8)Fs=∫0∞fxxs−1dx,be the Mellin transformation of fx. To state Voronoi’s summation formula, we introduce the notations below. For ℜs>1, let(9)Els,hq=∑n=1∞dlnenh/qns,where(10)dln=∑n1⋯nl=n1.We define(11)Al±n,aq=12∑n1⋯nl=nIn1,…,nl,a;q±In1,…,nl,a;q,(12)Ul±x=12πi∫ℜs=σγl±sdsxs,where(13)In1,…,nl,a;q=∑x1,…,xlmodqen1x1+⋯+nlxl+ax1⋯xlq,(14)γl±s=Γls/2+1±−1/4Γl1−s/2+1±−1/4,for x>0 and 0<ℜs<1/2−1/l. From Theorem 2 in [5], we know the following lemma.Lemma 1 (Voronoi’s summation formula).
With the above notations, we have, forl≥2,(15)∑n=1∞fndlnenhq=Ress=1FsEls,hq+πl/2ql∑n=1∞Al+n,hq∫0∞fxUl+πlnxqldx+i3lπl/2ql∑n=1∞Al−n,hq∫0∞fxUl−πlnxqldx.
To simplify the integrals in (15), we define(16)Gl±x=12πi∫ℜs=1−σFsγl±sxsds,where σ>0. By (12), it is clear that(17)∫0∞fxUl±xydx=12πi∫0∞∫ℜs=σfxγl±sdsxys,=−12πi∫ℜs=1−σ∫0∞fxxs−1dxγl±1−sys−1ds,=−12πi∫ℜs=1−σFsγl±sys−1ds,=−1yGl±y.
To use Lemma1 in practice, we need to estimate the residue in (15), Gl±x and Al±n,h/q. We first compute the residue. For 0≤j≤l−1, we define(18)Ajq=∑b=1qeabqcj+1b,q,where a>0 is an integer, and the coefficients cjb,q are sums of terms of the form(19)∑b1b2≡bmodqfb1,for some function f. The coefficients cjb,q are given explicitly in equation (2.13) in [6]. It has been shown in [6] that for a,q=1, Ajq is independent of a.Lemma 2.
Suppose1≤a≤q, a,q=1. We have(20)Ress=1FsEls,aq=∑n=0l−1Anq∫0∞fxlognxn!dx.Proof.
By (9), we can rewrite Els,a/q as(21)Els,aq=∑hmodqeahqZs;h,q,where(22)Zs;h,q=∑n≥1n=hmodqdlnns,for ℜs>1. Therefore,(23)Ress=1FsEls,aq=∑h=1qeahq∫0∞fxdRess=1Zs;h,qxss.
Chace (Theorem1 and (2.1) in [6]) gave that(24)Ress=1Zs;h,qxss=∑n=0l−1cn+1h,qLnx,where(25)Lnx=x∑j=0n−1n−jlogjxj!.
Substituting this into (23), we have(26)Ress=1FsEls,aq=∑n=0l−1Anq∫0∞fslognxn!dx.
The proof of the lemma is complete.
Our next lemma, proved by Jiang and Lü (Lemma 2.7 in [7]), is to evaluate the integrals in (15).Lemma 3.
LetGl±x be defined as in (16). Then, we have, for l≥2,(27)Gl±x≪X−A,ifx>Xl1−δ−1+ε,xXl−1/2l,ifX−1≪x≤Xl1−δ−1+ε,xX1/2X1−δε,ifx≪X−1.Proof.
This can be proved by takingJ=X1−δ with 0<δ<1 in Lemma 2.7 of [7].
The following two lemmas give estimates forAl±n,a/q. This two lemmas play an important role in our proof. We use some results for the Kloosterman sum to obtain the power saving in the q aspect.Lemma 4.
Suppose1≤a≤q, a,q=1, and let Al±n,a/q be defined as in (11). We have(28)∑amodqa,q=1Al±n,aqe−aNq≪εql+1/2+εnε.Proof.
By (13), we obtain(29)∑amodqa,q=1Im1,…,ml,a;qe−aNq=∑x1,…,xlmodqem1x1+⋯mlxlq∑amodqa,q=1eax1⋯xl−aNq,=∑d|qdμqd∑x1,…,xlmodqx1⋯xl=Nmoddem1x1+⋯mlxlq,=∑d|qq/d|mdμqdqdlSldqm;N,d,where(30)Slm;N,d≔∑x1,…,xlmoddx1⋯xl=Nmoddem1x1+⋯+mlxld,for m=m1,…,ml∈ℤl. Here, the notation d|m means that d divides each component of m. Then, we obtain that the left hand side of the desired equation in our lemma equals to(31)12∑m1⋯ml=n∑d|qq/d|mdqdlμqdSlmq/d;N,d+Slmq/d;−N,d=12∑d|qdqdlμqd∑m1⋯ml=nd/qlSlm;N,d+Slm;−N,d.
Now, we define(32)Kl−1m;w=∑x1,…,xl−1modwxj,w=1,1≤j≤l−1em1x1+⋯+ml−1xl−1+mlx1⋯xl−1¯w,for m=m1,…,ml∈ℤl and w∈ℤ. Here, x¯ denotes the multiplicative inverse of x modulo w. In Section 6 in [8], Smith gave that(33)∑m1⋯ml=nSlm;N,d=∑b|dbl|nbl−1dln/blKl−1eNn/bl;d/b.,where et=1,…,1,t∈ℤl for all t∈ℤ. Therefore, (31) can be written as(34)12∑q=q1d1bbl|n/q1ld1q1lblμq1dlnq1lblKl−1eNnq1lbl;d1+Kl−1e−Nnq1lbl;d1.
Taking the change of variables thatm=q1b, we get(35)∑amodqa,q=1Al±n,aqe−aNq=q2dlnKl−1eNn;q±Kl−1e−Nn;q.
From Theorem 6 in [9], we know that(36)Kl−1et;q≤ql−1/2dlq.
The lemma follows immediately.Lemma 5.
Suppose1≤a≤q, a,q=1, and l=2,3. Let Al±n,a/q be defined as before. Then, we have(37)Al±n,aq≪εql/2+εnεn,q1/2.Proof.
By (13), for l=2, we have(38)In1,n2,a;q=∑x1,x2modqen1x1+n2x2+ax1x2q=∑x1modqen1x1q∑x2modqen2+ax1x2q=q∑x1modqax1=−n2modqen1x1q≪q.
Forl=3, one has(39)In1,n2,n3,a;q=q∑d|n2,n3,qdSn1,−n2n3a¯d;qd.
Now, if we use Weil’s classical bound(40)Sm,n;c≤m,n,c1/2d2cc1/2,then it follows from (39) that(41)In1,n2,n3,a;q≪εq3/2+ε∑d|n2,n3,qn1d,n2n3a¯,q1/2.
Ford|n2,n3,q and a,q=1, noting that n=n1n2n3 by (11), we have n1d,n2n3a¯,q≤n1n2n3a¯,q=n,q. Therefore,(42)In1,n2,n3,a;q≪εq3/2+εn,q1/2.
Hence, we have(43)Al±n,aq≪εql/2+εn,q1/2∑n1n2n3=n1≪εql/2+εnεn,q1/2,for l=2,3. The proof of the lemma is complete.
## 3. Proof of Theorem1
In this section, we prove Theorem1. The main difficulty arises in treating the major arcs. The results from Kloosterman’s sums will play a role in our proof. Throughout this section, 1≤X≤N/2. We choose a smooth function f compactly supported in X−Xδ,2X+Xδ with 0<δ<1, satisfying fx=1 in X,2X and (6) and (7). To apply the circle method, we choose the parameters P and Q such that(44)PQ=N,P≤N1/l.By Dirichlet’s lemma on rational approximations, eachα∈I≔1/Q,1+1/Q may be written in the form as follows:(45)α=aq+β,β<1qQ,for some integers a and q with 1≤a≤q≤Q and a,q=1. We denote by Mq,a the set of α satisfying (45) and define the major arc by(46)M=∪1≤q≤P∪1≤a≤qa,q=1Ma,q.It follows fromP≤N1/l<Q/2 that the major arcs Mq,a are disjoint. The union m of minor arcs is just the complement of M in I. We denote(47)Slα=∑n≤Ndlnenα.Then, we have(48)νN;k,l=∫ISlkαe−Nαdα,=∫MSlkαe−Nαdα+∫mSlkαe−Nαdα.The upper bound of the integral ofSlkα on m is given by Chace [3].Lemma 6.
Supposek≥3 and l≥2 are integers. Then,(49)∫mSlkαe−Nαdα≪εNk−1+εP−k+2.This estimate on the minor arc is sufficient for us. It remains to consider the integral ofSlα on the major arc. Let(50)Slα,X=∑X<n≤2Xdlnenα.Now, forα=a/q+β∈M, we have(51)Slα,X=∑n=1∞fβndlneanq+R1,lα,X,where fβx≔fxexβ and(52)R1,lα,X=−∑X−Xδ<n≤X+∑2X<n<2X+Xδfndlnenα≪εXδ+ε.It is clear thatfβx is a smooth function compactly supported in X−Xδ,2X+Xδ. Moreover, it satisfies(53)fβvx≪βX+X1−δXv,for any v≥0, and(54)∫fβvxdx≪∑0≤j≤vβv−j∫fjxdx,≪βvX+βv−1∑1≤j≤vX1−δβXj−1,≪βvX+βv−1+X−δv−1,≪1+βXβX+X1−δXv−1,for any v≥1. Now, by Lemma 1, we get(55)∑n=1∞fβndlneanq=Ress=1FβsElaq+R2,laq+β,X,where(56)Fβs=∫0∞fβxxs−1dx,is the Mellin transformation of fβx and(57)R2,laq+β,X≔πl/2ql∑n=1∞Al+n,aq∫0∞fxUl+πlnxqldx+i3lπl/2ql∑n=1∞Al−n,aq∫0∞fxUl−πlnxqldx.It follows from Lemma2 that(58)Ress=1FβsElaq=∑n=0l−1Anq∫0∞fβslognxn!dβ.From Equation (4.8) in [3], we know that(59)Ajq≪εq−1+ε.Then, we have(60)Ress=1FβsEls,aq=∑n=0l−1Anq∫X2Xeβxlognxn!dx+R3,lα,X,where(61)R3,lα,X≪εq−1+εXδ+ε.Now, forα=a/q+β∈M, by (51), (55), and (60), we write(62)Slα,X=Tlα,X+Rlα,X,where(63)Tlaq+β,X=∑n=0l−1Anq∫X2Xeβxlognxn!dx,(64)Rlα,X=R1,lα,X+R2,lα,X+R3,lα,X.Hence, by dyadic analysis, forα=a/q+β∈M, formally, we write(65)Slα=Tlα+Rlα,where(66)Rlα=∑j=1log2N−1∑t=13Rt,lα,N/2+O1,(67)Tlaq+β=∑n=0l−1AnqInβ,with(68)Inβ=∫1Neβxlognxn!dx,for n=0,1,…,l−1. Therefore, we have(69)∫MSlkαe−Nαdα=∑j=0kkjMj,lN,where(70)Mj,lN=∫MTlk−jαRljαe−Nαdα.It has been proved by Chace (Section 5 in [3]) that(71)M0,lN=μN;k,l+OεNk−1+εP−k+2,where(72)μN;k,l=∑q=1∞CqN∫−∞∞∑n=0l−1AnqInβke−Nβdβ,satisfying(73)μN;k,l≍Nk−1logkl−1N.In the following subsections, we will estimateMj,lN for 1≤j≤k.
### 3.1. The Estimate ofM1,lN
In this section, we give the upper bound ofM1,lN.Lemma 7.
Letl=2or3. We have(74)M1,lN≪εN1+1−δl−1/2+εPl−1/2+N1+δ+ε,ifk=3,Nk−2+1−δl−1/2+ε+Nk−2+δ+ε,ifk≥4.Proof.
By our definition of major arc (46), we have(75)M1,lN=∑q≤P∑amodqa,q=1∫β<1qQTlk−1aq+βRlaq+βe−Nαdα.
Because forα=a/q+β∈M, Tlα,N is independent of a, and we can interchange the order of summation over a and the integral and then take the summation of Rlα,Ne−Na/q over a first. Therefore,(76)M1,lN≪∑q≤P∫β<1qQTlaq+βk−1∑amodqa,q=1Rlaq+βe−aNqdα.
By (59) and (68), it is clear that(77)Tlaq+β≪εq−1+εNεminN,β−1.
By the definition ofRlα in (66), we have(78)∑amodqa,q=1Rt,laq+βe−aNq≪∑t=13max1≤X≤N/2∑amodqa,q=1Rlaq+β,Xe−aNq+q.
We deduce that(79)∑amodqa,q=1R1,laq+β,Xe−aNq=∑X−Xδ≤n≤Xor2X≤n≤2X+Xδdlnn∑amodqa,q=1ean−Nqenβ=−∑d|qdμqd∑X−Xδ≤n≤Xor2X≤n≤2X+Xδ,n≡Nmodddlnfnenβ≪εXδ+ε.
It is obvious from (61) that(80)∑amodqa,q=1R3,laq+β,Xe−aNq=≪εXδ+ε.
It remains to consider the summation ofR2,l. We write Gl,β± be Gl± with F replaced by Fβ in (16). Similar to the assertions of Lemma 3, we have(81)Gl,β±x≪X−Aifx>βX+X1−δl+εX−1,1+βXxXl−1/2lifX−1≪x≤βX+X1−δl+εX−1,1+βXxX1/2βX+X1−δεifx≪X−1.
Notice that(82)∫0∞fβxUl±xydx=−1yGβ,l±y.
Then, by Lemma4, we have(83)q−l∑n=1∞∑amodqa,q=1Al±n,aqe−aNq∫0∞fβxUl±πlnxqldx≪εq−l−1/2+ε∑n=1∞nεqlnGl,β±πlnql≪εq−l−1/2+ε∑n≤βX+X1−δl+εqlX−1nε1+βXqlnnXqll−1/2l+∑n≪qlX−1nεqln1+βXnXql1/2βX+X1−δε≪εql+1/2+εβX+X1−δl−1/2+ε1+βX.
Therefore, we get(84)∑amodqa,q=1R2,laq+β,Xe−aNq≪εql+1/2+εβX+X1−δl−1/2+ε1+βX.
Hence, by (79), (80), and (84), for l=2,3, one has(85)∑amodqa,q=1Rlaq+βe−aNq≪∑t=13max1≤X≤N/2∑amodqa,q=1Rt,laq+β,Xe−aNq≪εql+1/2+εβN+N1−δl−1/2+ε1+βN+Nδ+ε.
Substituting this and (77) into (76), we obtain(86)M1,lN≪∑q≤P∫β<1qQTlaq+βk−1∑amodqa,q=1Rlaq+βe−aNqdα≪∑q≤Pq−k+1+l+1/2+εNε∫β<1qQminN,β−1k−1βN+N1−δl−1/2+ε1+βXdβ+∑q≤Pq−k+1+ε∫β<1qQminN,β−1k−1Nδ+εdβ.
By some elementary calculations, we get the desired result.
### 3.2. Integral ofMj,lN, 2≤j≤k, on the Major Arcs
The way we treat forMj,lN for j≥2 is different from that of M1,lN. We get the following lemma.Lemma 8.
LetMj,lN and 2≤j≤k be defined as before. We have, for l=2,3,(87)∑j=2kkjMj,lN≪εPl+1N1−δl−1+ε+Pl+2Nε+PN2δ+ε,ifk=3,Nk−3+εPlN1−δl−1+Pl+1+Nk−3+2δ+ε,ifk≥4.Proof.
The strategy is similar to that of Section 5 in [3]. Note that(88)∑j=2kTlk−jαRljα≪Rlα2Slαk−2+Tlαk−2.
We obtain(89)∑j=2kkjMj,lN≪∫M∑j=2kTlk−jαRljαdα≪maxα∈MRlα2∫MSlαk−2+Tlαk−2dα.
Similar to (83), by (81) and Lemma 5, we have, for l=2,3 and α=a/q+β∈M,(90)R2,lα,X≪εql/2+εβX+Jl−1/2+ε1+βX.
Hence, by (52), (61), (64), (90), and (66), we have(91)maxα∈MRlα≪maxα∈Mmax1≤X≤N/2∑t=13Rt,lα,X+1≪εmaxa/q+β∈Mql/2+ε1+βNβN+N1−δl−1/2+ε+Nδ+ε≪εPl/2N1−δl−1/2+ε+Pl+1/2+ε+Nδ+ε.
Now, fork=3, by Cauchy’s inequality, the definition of major arc (46), and Parseval’s identity, we obtain(92)∫MSlαdα≪M1/2∫01Slα2dα1/2≪εPNε.
Fork≥4, we have(93)∫MSlαk−2dα≪maxα∈MSlαk−4∫01Slα2dα≪εNk−3+ε,by the fact that Slα≪εN1+ε. One then shows that(94)∫MTlαk−2dα≪εPNε,ifk=3,Nk−3+ε,ifk≥4,by using the definition of the major arc and (77). Combining these results, we complete the proof of the lemma.
### 3.3. Proof of Theorem1
By Lemma6 and (69)–(73), we have, for k≥3, l=2,3,(95)νN;k,l=μN;k,l+kM1,lN+∑j=2kkjMj,lN+OεNk−1+εP−k+2,where(96)μN;k,l=∑q=1∞CqN∫−∞∞∑n=0l−1AnqInβke−Nβdβ,satisfying(97)μN;k,l≍Nk−1logkl−1N.Now, by Lemmas7 and 8, taking(98)δ=2l−12l+1,ifk=3,l−1l+1,ifk≥4,andP=N2/2l+1,ifk=3,N4/l+1k+l−2,ifk≥4,we have, for l=2,3,(99)νN;k,l=μN;3,l+OεN2−2/2l+1+ε,ifk=3,μN;k,l+OεNk−1−4k−2/l+1k+l−2+ε,ifk≥4.We complete the proof of Theorem1.
## 3.1. The Estimate ofM1,lN
In this section, we give the upper bound ofM1,lN.Lemma 7.
Letl=2or3. We have(74)M1,lN≪εN1+1−δl−1/2+εPl−1/2+N1+δ+ε,ifk=3,Nk−2+1−δl−1/2+ε+Nk−2+δ+ε,ifk≥4.Proof.
By our definition of major arc (46), we have(75)M1,lN=∑q≤P∑amodqa,q=1∫β<1qQTlk−1aq+βRlaq+βe−Nαdα.
Because forα=a/q+β∈M, Tlα,N is independent of a, and we can interchange the order of summation over a and the integral and then take the summation of Rlα,Ne−Na/q over a first. Therefore,(76)M1,lN≪∑q≤P∫β<1qQTlaq+βk−1∑amodqa,q=1Rlaq+βe−aNqdα.
By (59) and (68), it is clear that(77)Tlaq+β≪εq−1+εNεminN,β−1.
By the definition ofRlα in (66), we have(78)∑amodqa,q=1Rt,laq+βe−aNq≪∑t=13max1≤X≤N/2∑amodqa,q=1Rlaq+β,Xe−aNq+q.
We deduce that(79)∑amodqa,q=1R1,laq+β,Xe−aNq=∑X−Xδ≤n≤Xor2X≤n≤2X+Xδdlnn∑amodqa,q=1ean−Nqenβ=−∑d|qdμqd∑X−Xδ≤n≤Xor2X≤n≤2X+Xδ,n≡Nmodddlnfnenβ≪εXδ+ε.
It is obvious from (61) that(80)∑amodqa,q=1R3,laq+β,Xe−aNq=≪εXδ+ε.
It remains to consider the summation ofR2,l. We write Gl,β± be Gl± with F replaced by Fβ in (16). Similar to the assertions of Lemma 3, we have(81)Gl,β±x≪X−Aifx>βX+X1−δl+εX−1,1+βXxXl−1/2lifX−1≪x≤βX+X1−δl+εX−1,1+βXxX1/2βX+X1−δεifx≪X−1.
Notice that(82)∫0∞fβxUl±xydx=−1yGβ,l±y.
Then, by Lemma4, we have(83)q−l∑n=1∞∑amodqa,q=1Al±n,aqe−aNq∫0∞fβxUl±πlnxqldx≪εq−l−1/2+ε∑n=1∞nεqlnGl,β±πlnql≪εq−l−1/2+ε∑n≤βX+X1−δl+εqlX−1nε1+βXqlnnXqll−1/2l+∑n≪qlX−1nεqln1+βXnXql1/2βX+X1−δε≪εql+1/2+εβX+X1−δl−1/2+ε1+βX.
Therefore, we get(84)∑amodqa,q=1R2,laq+β,Xe−aNq≪εql+1/2+εβX+X1−δl−1/2+ε1+βX.
Hence, by (79), (80), and (84), for l=2,3, one has(85)∑amodqa,q=1Rlaq+βe−aNq≪∑t=13max1≤X≤N/2∑amodqa,q=1Rt,laq+β,Xe−aNq≪εql+1/2+εβN+N1−δl−1/2+ε1+βN+Nδ+ε.
Substituting this and (77) into (76), we obtain(86)M1,lN≪∑q≤P∫β<1qQTlaq+βk−1∑amodqa,q=1Rlaq+βe−aNqdα≪∑q≤Pq−k+1+l+1/2+εNε∫β<1qQminN,β−1k−1βN+N1−δl−1/2+ε1+βXdβ+∑q≤Pq−k+1+ε∫β<1qQminN,β−1k−1Nδ+εdβ.
By some elementary calculations, we get the desired result.
## 3.2. Integral ofMj,lN, 2≤j≤k, on the Major Arcs
The way we treat forMj,lN for j≥2 is different from that of M1,lN. We get the following lemma.Lemma 8.
LetMj,lN and 2≤j≤k be defined as before. We have, for l=2,3,(87)∑j=2kkjMj,lN≪εPl+1N1−δl−1+ε+Pl+2Nε+PN2δ+ε,ifk=3,Nk−3+εPlN1−δl−1+Pl+1+Nk−3+2δ+ε,ifk≥4.Proof.
The strategy is similar to that of Section 5 in [3]. Note that(88)∑j=2kTlk−jαRljα≪Rlα2Slαk−2+Tlαk−2.
We obtain(89)∑j=2kkjMj,lN≪∫M∑j=2kTlk−jαRljαdα≪maxα∈MRlα2∫MSlαk−2+Tlαk−2dα.
Similar to (83), by (81) and Lemma 5, we have, for l=2,3 and α=a/q+β∈M,(90)R2,lα,X≪εql/2+εβX+Jl−1/2+ε1+βX.
Hence, by (52), (61), (64), (90), and (66), we have(91)maxα∈MRlα≪maxα∈Mmax1≤X≤N/2∑t=13Rt,lα,X+1≪εmaxa/q+β∈Mql/2+ε1+βNβN+N1−δl−1/2+ε+Nδ+ε≪εPl/2N1−δl−1/2+ε+Pl+1/2+ε+Nδ+ε.
Now, fork=3, by Cauchy’s inequality, the definition of major arc (46), and Parseval’s identity, we obtain(92)∫MSlαdα≪M1/2∫01Slα2dα1/2≪εPNε.
Fork≥4, we have(93)∫MSlαk−2dα≪maxα∈MSlαk−4∫01Slα2dα≪εNk−3+ε,by the fact that Slα≪εN1+ε. One then shows that(94)∫MTlαk−2dα≪εPNε,ifk=3,Nk−3+ε,ifk≥4,by using the definition of the major arc and (77). Combining these results, we complete the proof of the lemma.
## 3.3. Proof of Theorem1
By Lemma6 and (69)–(73), we have, for k≥3, l=2,3,(95)νN;k,l=μN;k,l+kM1,lN+∑j=2kkjMj,lN+OεNk−1+εP−k+2,where(96)μN;k,l=∑q=1∞CqN∫−∞∞∑n=0l−1AnqInβke−Nβdβ,satisfying(97)μN;k,l≍Nk−1logkl−1N.Now, by Lemmas7 and 8, taking(98)δ=2l−12l+1,ifk=3,l−1l+1,ifk≥4,andP=N2/2l+1,ifk=3,N4/l+1k+l−2,ifk≥4,we have, for l=2,3,(99)νN;k,l=μN;3,l+OεN2−2/2l+1+ε,ifk=3,μN;k,l+OεNk−1−4k−2/l+1k+l−2+ε,ifk≥4.We complete the proof of Theorem1.
---
*Source: 2902015-2021-11-23.xml* | 2902015-2021-11-23_2902015-2021-11-23.md | 19,294 | An Improved Asymptotic on the Representations of Integers as Sums of Products | Wenjia Zhao | Journal of Mathematics
(2021) | Mathematical Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2021/2902015 | 2902015-2021-11-23.xml | ---
## Abstract
In this paper, we improve the error terms of Chace’s results in the study by Chace (1994) on the number of ways of writing an integerN as a sum of k products of l factors, valid for k≥3 and l=2, 3. More precisely, for l=2, 3, we improve the upper bound Nk−1−2k−2/k−1l+1+ε, k≥3 for the error term, to N2−2/2l+1+ε when k=3 and Nk−1−4k−2/l+1k+l−2+ε when k≥4.
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## Body
## 1. Introduction
In this paper, we study the number of representations of a natural numberN as a sum of k terms, each being a product of l factors. Let νN;k,l denote this number. This problem was studied by Estermann [1, 2] in the case k=2 or 3 and l=2 by using some properties of Dirichlet L-function. His method is not easy to be generalized. Later, Chace [3] generalized Estermann’s result to k≥3 and l≥2. For such k and l, he got(1)νN;k,l=μN;k,l+EN;k,l,where(2)μN;k,l≍Nk−1logkl−1N,and(3)EN;k,l≪εNk−1−2k−2/k−1l+1+ε,ifk=3orl=2,l=3,Nk−1−3k−2/k−1l+2+ε,ifkandl≥4.Here,μN;k,l is defined in (72). The way he studied the problem is different from Estermann. The main tools he used are the Hardy–Littlewood method and some results from the divisor problem in arithmetic progressions. He got the main term μN;k,l which is a sum of terms of the form Sℐ, where S are the “singular series” and ℐ are the “singular integrals.” They occur in the applications of the Hardy–Littlewood method. In this paper, we improve Chace’s result in the cases k≥3 and l=2,3. We get the following result.Theorem 1.
Supposek≥3 and l=2,3. Then,(4)νN;k,l=μN;k,l+EN;k,l,where μN;k,l defined by (72) satisfies (2) and the error term satisfies(5)EN;k,l≪εN2−2/2l+1+ε,ifk=3,Nk−1−4k−2/l+1k+l−2+ε,ifk≥4.We can compare the exponents in (3) with our results (5). For l=2,3, we see that 2−2/2l+1<k−1−2k−2/k−1l+1=2−1/l+1 when k=3 and k−1−4k−2/l+1k+l−2<k−1−3k−2/k−1l+2 when k≥4. Our error terms are better than Chace’s.The proof of the theorem is an application of the Hardy–Littlewood method (cf, Chapter 3 of [4]), the Voronoi summation formula, and some results from the Kloosterman sums. The estimates on the minor arc were studied by Chace, and his result is sufficient for us. Hence, we will not focus on the minor arc in this paper. The main difficulty arises in treating the error term of the major arcs. In Section 2, we make some preparations for our proof. We state the Voronoi summation formula and give some lemmas related to the Kloosterman sums in this section. In Sections 3.1 and 3.2, we obtain a bound for the contribution from the minor arcs. In §3.3, we prove our theorem.
## 2. Applications of the Voronoi Summation Formula
LetX>0. Suppose that fx is a smooth function compactly supported in X−Xδ,2X+Xδ with 0<δ<1, satisfying fx=1 in X,2X and(6)fjx≪X−δj,j≥0,(7)∫fjxdx≪X−δj−1,j≥1.Let(8)Fs=∫0∞fxxs−1dx,be the Mellin transformation of fx. To state Voronoi’s summation formula, we introduce the notations below. For ℜs>1, let(9)Els,hq=∑n=1∞dlnenh/qns,where(10)dln=∑n1⋯nl=n1.We define(11)Al±n,aq=12∑n1⋯nl=nIn1,…,nl,a;q±In1,…,nl,a;q,(12)Ul±x=12πi∫ℜs=σγl±sdsxs,where(13)In1,…,nl,a;q=∑x1,…,xlmodqen1x1+⋯+nlxl+ax1⋯xlq,(14)γl±s=Γls/2+1±−1/4Γl1−s/2+1±−1/4,for x>0 and 0<ℜs<1/2−1/l. From Theorem 2 in [5], we know the following lemma.Lemma 1 (Voronoi’s summation formula).
With the above notations, we have, forl≥2,(15)∑n=1∞fndlnenhq=Ress=1FsEls,hq+πl/2ql∑n=1∞Al+n,hq∫0∞fxUl+πlnxqldx+i3lπl/2ql∑n=1∞Al−n,hq∫0∞fxUl−πlnxqldx.
To simplify the integrals in (15), we define(16)Gl±x=12πi∫ℜs=1−σFsγl±sxsds,where σ>0. By (12), it is clear that(17)∫0∞fxUl±xydx=12πi∫0∞∫ℜs=σfxγl±sdsxys,=−12πi∫ℜs=1−σ∫0∞fxxs−1dxγl±1−sys−1ds,=−12πi∫ℜs=1−σFsγl±sys−1ds,=−1yGl±y.
To use Lemma1 in practice, we need to estimate the residue in (15), Gl±x and Al±n,h/q. We first compute the residue. For 0≤j≤l−1, we define(18)Ajq=∑b=1qeabqcj+1b,q,where a>0 is an integer, and the coefficients cjb,q are sums of terms of the form(19)∑b1b2≡bmodqfb1,for some function f. The coefficients cjb,q are given explicitly in equation (2.13) in [6]. It has been shown in [6] that for a,q=1, Ajq is independent of a.Lemma 2.
Suppose1≤a≤q, a,q=1. We have(20)Ress=1FsEls,aq=∑n=0l−1Anq∫0∞fxlognxn!dx.Proof.
By (9), we can rewrite Els,a/q as(21)Els,aq=∑hmodqeahqZs;h,q,where(22)Zs;h,q=∑n≥1n=hmodqdlnns,for ℜs>1. Therefore,(23)Ress=1FsEls,aq=∑h=1qeahq∫0∞fxdRess=1Zs;h,qxss.
Chace (Theorem1 and (2.1) in [6]) gave that(24)Ress=1Zs;h,qxss=∑n=0l−1cn+1h,qLnx,where(25)Lnx=x∑j=0n−1n−jlogjxj!.
Substituting this into (23), we have(26)Ress=1FsEls,aq=∑n=0l−1Anq∫0∞fslognxn!dx.
The proof of the lemma is complete.
Our next lemma, proved by Jiang and Lü (Lemma 2.7 in [7]), is to evaluate the integrals in (15).Lemma 3.
LetGl±x be defined as in (16). Then, we have, for l≥2,(27)Gl±x≪X−A,ifx>Xl1−δ−1+ε,xXl−1/2l,ifX−1≪x≤Xl1−δ−1+ε,xX1/2X1−δε,ifx≪X−1.Proof.
This can be proved by takingJ=X1−δ with 0<δ<1 in Lemma 2.7 of [7].
The following two lemmas give estimates forAl±n,a/q. This two lemmas play an important role in our proof. We use some results for the Kloosterman sum to obtain the power saving in the q aspect.Lemma 4.
Suppose1≤a≤q, a,q=1, and let Al±n,a/q be defined as in (11). We have(28)∑amodqa,q=1Al±n,aqe−aNq≪εql+1/2+εnε.Proof.
By (13), we obtain(29)∑amodqa,q=1Im1,…,ml,a;qe−aNq=∑x1,…,xlmodqem1x1+⋯mlxlq∑amodqa,q=1eax1⋯xl−aNq,=∑d|qdμqd∑x1,…,xlmodqx1⋯xl=Nmoddem1x1+⋯mlxlq,=∑d|qq/d|mdμqdqdlSldqm;N,d,where(30)Slm;N,d≔∑x1,…,xlmoddx1⋯xl=Nmoddem1x1+⋯+mlxld,for m=m1,…,ml∈ℤl. Here, the notation d|m means that d divides each component of m. Then, we obtain that the left hand side of the desired equation in our lemma equals to(31)12∑m1⋯ml=n∑d|qq/d|mdqdlμqdSlmq/d;N,d+Slmq/d;−N,d=12∑d|qdqdlμqd∑m1⋯ml=nd/qlSlm;N,d+Slm;−N,d.
Now, we define(32)Kl−1m;w=∑x1,…,xl−1modwxj,w=1,1≤j≤l−1em1x1+⋯+ml−1xl−1+mlx1⋯xl−1¯w,for m=m1,…,ml∈ℤl and w∈ℤ. Here, x¯ denotes the multiplicative inverse of x modulo w. In Section 6 in [8], Smith gave that(33)∑m1⋯ml=nSlm;N,d=∑b|dbl|nbl−1dln/blKl−1eNn/bl;d/b.,where et=1,…,1,t∈ℤl for all t∈ℤ. Therefore, (31) can be written as(34)12∑q=q1d1bbl|n/q1ld1q1lblμq1dlnq1lblKl−1eNnq1lbl;d1+Kl−1e−Nnq1lbl;d1.
Taking the change of variables thatm=q1b, we get(35)∑amodqa,q=1Al±n,aqe−aNq=q2dlnKl−1eNn;q±Kl−1e−Nn;q.
From Theorem 6 in [9], we know that(36)Kl−1et;q≤ql−1/2dlq.
The lemma follows immediately.Lemma 5.
Suppose1≤a≤q, a,q=1, and l=2,3. Let Al±n,a/q be defined as before. Then, we have(37)Al±n,aq≪εql/2+εnεn,q1/2.Proof.
By (13), for l=2, we have(38)In1,n2,a;q=∑x1,x2modqen1x1+n2x2+ax1x2q=∑x1modqen1x1q∑x2modqen2+ax1x2q=q∑x1modqax1=−n2modqen1x1q≪q.
Forl=3, one has(39)In1,n2,n3,a;q=q∑d|n2,n3,qdSn1,−n2n3a¯d;qd.
Now, if we use Weil’s classical bound(40)Sm,n;c≤m,n,c1/2d2cc1/2,then it follows from (39) that(41)In1,n2,n3,a;q≪εq3/2+ε∑d|n2,n3,qn1d,n2n3a¯,q1/2.
Ford|n2,n3,q and a,q=1, noting that n=n1n2n3 by (11), we have n1d,n2n3a¯,q≤n1n2n3a¯,q=n,q. Therefore,(42)In1,n2,n3,a;q≪εq3/2+εn,q1/2.
Hence, we have(43)Al±n,aq≪εql/2+εn,q1/2∑n1n2n3=n1≪εql/2+εnεn,q1/2,for l=2,3. The proof of the lemma is complete.
## 3. Proof of Theorem1
In this section, we prove Theorem1. The main difficulty arises in treating the major arcs. The results from Kloosterman’s sums will play a role in our proof. Throughout this section, 1≤X≤N/2. We choose a smooth function f compactly supported in X−Xδ,2X+Xδ with 0<δ<1, satisfying fx=1 in X,2X and (6) and (7). To apply the circle method, we choose the parameters P and Q such that(44)PQ=N,P≤N1/l.By Dirichlet’s lemma on rational approximations, eachα∈I≔1/Q,1+1/Q may be written in the form as follows:(45)α=aq+β,β<1qQ,for some integers a and q with 1≤a≤q≤Q and a,q=1. We denote by Mq,a the set of α satisfying (45) and define the major arc by(46)M=∪1≤q≤P∪1≤a≤qa,q=1Ma,q.It follows fromP≤N1/l<Q/2 that the major arcs Mq,a are disjoint. The union m of minor arcs is just the complement of M in I. We denote(47)Slα=∑n≤Ndlnenα.Then, we have(48)νN;k,l=∫ISlkαe−Nαdα,=∫MSlkαe−Nαdα+∫mSlkαe−Nαdα.The upper bound of the integral ofSlkα on m is given by Chace [3].Lemma 6.
Supposek≥3 and l≥2 are integers. Then,(49)∫mSlkαe−Nαdα≪εNk−1+εP−k+2.This estimate on the minor arc is sufficient for us. It remains to consider the integral ofSlα on the major arc. Let(50)Slα,X=∑X<n≤2Xdlnenα.Now, forα=a/q+β∈M, we have(51)Slα,X=∑n=1∞fβndlneanq+R1,lα,X,where fβx≔fxexβ and(52)R1,lα,X=−∑X−Xδ<n≤X+∑2X<n<2X+Xδfndlnenα≪εXδ+ε.It is clear thatfβx is a smooth function compactly supported in X−Xδ,2X+Xδ. Moreover, it satisfies(53)fβvx≪βX+X1−δXv,for any v≥0, and(54)∫fβvxdx≪∑0≤j≤vβv−j∫fjxdx,≪βvX+βv−1∑1≤j≤vX1−δβXj−1,≪βvX+βv−1+X−δv−1,≪1+βXβX+X1−δXv−1,for any v≥1. Now, by Lemma 1, we get(55)∑n=1∞fβndlneanq=Ress=1FβsElaq+R2,laq+β,X,where(56)Fβs=∫0∞fβxxs−1dx,is the Mellin transformation of fβx and(57)R2,laq+β,X≔πl/2ql∑n=1∞Al+n,aq∫0∞fxUl+πlnxqldx+i3lπl/2ql∑n=1∞Al−n,aq∫0∞fxUl−πlnxqldx.It follows from Lemma2 that(58)Ress=1FβsElaq=∑n=0l−1Anq∫0∞fβslognxn!dβ.From Equation (4.8) in [3], we know that(59)Ajq≪εq−1+ε.Then, we have(60)Ress=1FβsEls,aq=∑n=0l−1Anq∫X2Xeβxlognxn!dx+R3,lα,X,where(61)R3,lα,X≪εq−1+εXδ+ε.Now, forα=a/q+β∈M, by (51), (55), and (60), we write(62)Slα,X=Tlα,X+Rlα,X,where(63)Tlaq+β,X=∑n=0l−1Anq∫X2Xeβxlognxn!dx,(64)Rlα,X=R1,lα,X+R2,lα,X+R3,lα,X.Hence, by dyadic analysis, forα=a/q+β∈M, formally, we write(65)Slα=Tlα+Rlα,where(66)Rlα=∑j=1log2N−1∑t=13Rt,lα,N/2+O1,(67)Tlaq+β=∑n=0l−1AnqInβ,with(68)Inβ=∫1Neβxlognxn!dx,for n=0,1,…,l−1. Therefore, we have(69)∫MSlkαe−Nαdα=∑j=0kkjMj,lN,where(70)Mj,lN=∫MTlk−jαRljαe−Nαdα.It has been proved by Chace (Section 5 in [3]) that(71)M0,lN=μN;k,l+OεNk−1+εP−k+2,where(72)μN;k,l=∑q=1∞CqN∫−∞∞∑n=0l−1AnqInβke−Nβdβ,satisfying(73)μN;k,l≍Nk−1logkl−1N.In the following subsections, we will estimateMj,lN for 1≤j≤k.
### 3.1. The Estimate ofM1,lN
In this section, we give the upper bound ofM1,lN.Lemma 7.
Letl=2or3. We have(74)M1,lN≪εN1+1−δl−1/2+εPl−1/2+N1+δ+ε,ifk=3,Nk−2+1−δl−1/2+ε+Nk−2+δ+ε,ifk≥4.Proof.
By our definition of major arc (46), we have(75)M1,lN=∑q≤P∑amodqa,q=1∫β<1qQTlk−1aq+βRlaq+βe−Nαdα.
Because forα=a/q+β∈M, Tlα,N is independent of a, and we can interchange the order of summation over a and the integral and then take the summation of Rlα,Ne−Na/q over a first. Therefore,(76)M1,lN≪∑q≤P∫β<1qQTlaq+βk−1∑amodqa,q=1Rlaq+βe−aNqdα.
By (59) and (68), it is clear that(77)Tlaq+β≪εq−1+εNεminN,β−1.
By the definition ofRlα in (66), we have(78)∑amodqa,q=1Rt,laq+βe−aNq≪∑t=13max1≤X≤N/2∑amodqa,q=1Rlaq+β,Xe−aNq+q.
We deduce that(79)∑amodqa,q=1R1,laq+β,Xe−aNq=∑X−Xδ≤n≤Xor2X≤n≤2X+Xδdlnn∑amodqa,q=1ean−Nqenβ=−∑d|qdμqd∑X−Xδ≤n≤Xor2X≤n≤2X+Xδ,n≡Nmodddlnfnenβ≪εXδ+ε.
It is obvious from (61) that(80)∑amodqa,q=1R3,laq+β,Xe−aNq=≪εXδ+ε.
It remains to consider the summation ofR2,l. We write Gl,β± be Gl± with F replaced by Fβ in (16). Similar to the assertions of Lemma 3, we have(81)Gl,β±x≪X−Aifx>βX+X1−δl+εX−1,1+βXxXl−1/2lifX−1≪x≤βX+X1−δl+εX−1,1+βXxX1/2βX+X1−δεifx≪X−1.
Notice that(82)∫0∞fβxUl±xydx=−1yGβ,l±y.
Then, by Lemma4, we have(83)q−l∑n=1∞∑amodqa,q=1Al±n,aqe−aNq∫0∞fβxUl±πlnxqldx≪εq−l−1/2+ε∑n=1∞nεqlnGl,β±πlnql≪εq−l−1/2+ε∑n≤βX+X1−δl+εqlX−1nε1+βXqlnnXqll−1/2l+∑n≪qlX−1nεqln1+βXnXql1/2βX+X1−δε≪εql+1/2+εβX+X1−δl−1/2+ε1+βX.
Therefore, we get(84)∑amodqa,q=1R2,laq+β,Xe−aNq≪εql+1/2+εβX+X1−δl−1/2+ε1+βX.
Hence, by (79), (80), and (84), for l=2,3, one has(85)∑amodqa,q=1Rlaq+βe−aNq≪∑t=13max1≤X≤N/2∑amodqa,q=1Rt,laq+β,Xe−aNq≪εql+1/2+εβN+N1−δl−1/2+ε1+βN+Nδ+ε.
Substituting this and (77) into (76), we obtain(86)M1,lN≪∑q≤P∫β<1qQTlaq+βk−1∑amodqa,q=1Rlaq+βe−aNqdα≪∑q≤Pq−k+1+l+1/2+εNε∫β<1qQminN,β−1k−1βN+N1−δl−1/2+ε1+βXdβ+∑q≤Pq−k+1+ε∫β<1qQminN,β−1k−1Nδ+εdβ.
By some elementary calculations, we get the desired result.
### 3.2. Integral ofMj,lN, 2≤j≤k, on the Major Arcs
The way we treat forMj,lN for j≥2 is different from that of M1,lN. We get the following lemma.Lemma 8.
LetMj,lN and 2≤j≤k be defined as before. We have, for l=2,3,(87)∑j=2kkjMj,lN≪εPl+1N1−δl−1+ε+Pl+2Nε+PN2δ+ε,ifk=3,Nk−3+εPlN1−δl−1+Pl+1+Nk−3+2δ+ε,ifk≥4.Proof.
The strategy is similar to that of Section 5 in [3]. Note that(88)∑j=2kTlk−jαRljα≪Rlα2Slαk−2+Tlαk−2.
We obtain(89)∑j=2kkjMj,lN≪∫M∑j=2kTlk−jαRljαdα≪maxα∈MRlα2∫MSlαk−2+Tlαk−2dα.
Similar to (83), by (81) and Lemma 5, we have, for l=2,3 and α=a/q+β∈M,(90)R2,lα,X≪εql/2+εβX+Jl−1/2+ε1+βX.
Hence, by (52), (61), (64), (90), and (66), we have(91)maxα∈MRlα≪maxα∈Mmax1≤X≤N/2∑t=13Rt,lα,X+1≪εmaxa/q+β∈Mql/2+ε1+βNβN+N1−δl−1/2+ε+Nδ+ε≪εPl/2N1−δl−1/2+ε+Pl+1/2+ε+Nδ+ε.
Now, fork=3, by Cauchy’s inequality, the definition of major arc (46), and Parseval’s identity, we obtain(92)∫MSlαdα≪M1/2∫01Slα2dα1/2≪εPNε.
Fork≥4, we have(93)∫MSlαk−2dα≪maxα∈MSlαk−4∫01Slα2dα≪εNk−3+ε,by the fact that Slα≪εN1+ε. One then shows that(94)∫MTlαk−2dα≪εPNε,ifk=3,Nk−3+ε,ifk≥4,by using the definition of the major arc and (77). Combining these results, we complete the proof of the lemma.
### 3.3. Proof of Theorem1
By Lemma6 and (69)–(73), we have, for k≥3, l=2,3,(95)νN;k,l=μN;k,l+kM1,lN+∑j=2kkjMj,lN+OεNk−1+εP−k+2,where(96)μN;k,l=∑q=1∞CqN∫−∞∞∑n=0l−1AnqInβke−Nβdβ,satisfying(97)μN;k,l≍Nk−1logkl−1N.Now, by Lemmas7 and 8, taking(98)δ=2l−12l+1,ifk=3,l−1l+1,ifk≥4,andP=N2/2l+1,ifk=3,N4/l+1k+l−2,ifk≥4,we have, for l=2,3,(99)νN;k,l=μN;3,l+OεN2−2/2l+1+ε,ifk=3,μN;k,l+OεNk−1−4k−2/l+1k+l−2+ε,ifk≥4.We complete the proof of Theorem1.
## 3.1. The Estimate ofM1,lN
In this section, we give the upper bound ofM1,lN.Lemma 7.
Letl=2or3. We have(74)M1,lN≪εN1+1−δl−1/2+εPl−1/2+N1+δ+ε,ifk=3,Nk−2+1−δl−1/2+ε+Nk−2+δ+ε,ifk≥4.Proof.
By our definition of major arc (46), we have(75)M1,lN=∑q≤P∑amodqa,q=1∫β<1qQTlk−1aq+βRlaq+βe−Nαdα.
Because forα=a/q+β∈M, Tlα,N is independent of a, and we can interchange the order of summation over a and the integral and then take the summation of Rlα,Ne−Na/q over a first. Therefore,(76)M1,lN≪∑q≤P∫β<1qQTlaq+βk−1∑amodqa,q=1Rlaq+βe−aNqdα.
By (59) and (68), it is clear that(77)Tlaq+β≪εq−1+εNεminN,β−1.
By the definition ofRlα in (66), we have(78)∑amodqa,q=1Rt,laq+βe−aNq≪∑t=13max1≤X≤N/2∑amodqa,q=1Rlaq+β,Xe−aNq+q.
We deduce that(79)∑amodqa,q=1R1,laq+β,Xe−aNq=∑X−Xδ≤n≤Xor2X≤n≤2X+Xδdlnn∑amodqa,q=1ean−Nqenβ=−∑d|qdμqd∑X−Xδ≤n≤Xor2X≤n≤2X+Xδ,n≡Nmodddlnfnenβ≪εXδ+ε.
It is obvious from (61) that(80)∑amodqa,q=1R3,laq+β,Xe−aNq=≪εXδ+ε.
It remains to consider the summation ofR2,l. We write Gl,β± be Gl± with F replaced by Fβ in (16). Similar to the assertions of Lemma 3, we have(81)Gl,β±x≪X−Aifx>βX+X1−δl+εX−1,1+βXxXl−1/2lifX−1≪x≤βX+X1−δl+εX−1,1+βXxX1/2βX+X1−δεifx≪X−1.
Notice that(82)∫0∞fβxUl±xydx=−1yGβ,l±y.
Then, by Lemma4, we have(83)q−l∑n=1∞∑amodqa,q=1Al±n,aqe−aNq∫0∞fβxUl±πlnxqldx≪εq−l−1/2+ε∑n=1∞nεqlnGl,β±πlnql≪εq−l−1/2+ε∑n≤βX+X1−δl+εqlX−1nε1+βXqlnnXqll−1/2l+∑n≪qlX−1nεqln1+βXnXql1/2βX+X1−δε≪εql+1/2+εβX+X1−δl−1/2+ε1+βX.
Therefore, we get(84)∑amodqa,q=1R2,laq+β,Xe−aNq≪εql+1/2+εβX+X1−δl−1/2+ε1+βX.
Hence, by (79), (80), and (84), for l=2,3, one has(85)∑amodqa,q=1Rlaq+βe−aNq≪∑t=13max1≤X≤N/2∑amodqa,q=1Rt,laq+β,Xe−aNq≪εql+1/2+εβN+N1−δl−1/2+ε1+βN+Nδ+ε.
Substituting this and (77) into (76), we obtain(86)M1,lN≪∑q≤P∫β<1qQTlaq+βk−1∑amodqa,q=1Rlaq+βe−aNqdα≪∑q≤Pq−k+1+l+1/2+εNε∫β<1qQminN,β−1k−1βN+N1−δl−1/2+ε1+βXdβ+∑q≤Pq−k+1+ε∫β<1qQminN,β−1k−1Nδ+εdβ.
By some elementary calculations, we get the desired result.
## 3.2. Integral ofMj,lN, 2≤j≤k, on the Major Arcs
The way we treat forMj,lN for j≥2 is different from that of M1,lN. We get the following lemma.Lemma 8.
LetMj,lN and 2≤j≤k be defined as before. We have, for l=2,3,(87)∑j=2kkjMj,lN≪εPl+1N1−δl−1+ε+Pl+2Nε+PN2δ+ε,ifk=3,Nk−3+εPlN1−δl−1+Pl+1+Nk−3+2δ+ε,ifk≥4.Proof.
The strategy is similar to that of Section 5 in [3]. Note that(88)∑j=2kTlk−jαRljα≪Rlα2Slαk−2+Tlαk−2.
We obtain(89)∑j=2kkjMj,lN≪∫M∑j=2kTlk−jαRljαdα≪maxα∈MRlα2∫MSlαk−2+Tlαk−2dα.
Similar to (83), by (81) and Lemma 5, we have, for l=2,3 and α=a/q+β∈M,(90)R2,lα,X≪εql/2+εβX+Jl−1/2+ε1+βX.
Hence, by (52), (61), (64), (90), and (66), we have(91)maxα∈MRlα≪maxα∈Mmax1≤X≤N/2∑t=13Rt,lα,X+1≪εmaxa/q+β∈Mql/2+ε1+βNβN+N1−δl−1/2+ε+Nδ+ε≪εPl/2N1−δl−1/2+ε+Pl+1/2+ε+Nδ+ε.
Now, fork=3, by Cauchy’s inequality, the definition of major arc (46), and Parseval’s identity, we obtain(92)∫MSlαdα≪M1/2∫01Slα2dα1/2≪εPNε.
Fork≥4, we have(93)∫MSlαk−2dα≪maxα∈MSlαk−4∫01Slα2dα≪εNk−3+ε,by the fact that Slα≪εN1+ε. One then shows that(94)∫MTlαk−2dα≪εPNε,ifk=3,Nk−3+ε,ifk≥4,by using the definition of the major arc and (77). Combining these results, we complete the proof of the lemma.
## 3.3. Proof of Theorem1
By Lemma6 and (69)–(73), we have, for k≥3, l=2,3,(95)νN;k,l=μN;k,l+kM1,lN+∑j=2kkjMj,lN+OεNk−1+εP−k+2,where(96)μN;k,l=∑q=1∞CqN∫−∞∞∑n=0l−1AnqInβke−Nβdβ,satisfying(97)μN;k,l≍Nk−1logkl−1N.Now, by Lemmas7 and 8, taking(98)δ=2l−12l+1,ifk=3,l−1l+1,ifk≥4,andP=N2/2l+1,ifk=3,N4/l+1k+l−2,ifk≥4,we have, for l=2,3,(99)νN;k,l=μN;3,l+OεN2−2/2l+1+ε,ifk=3,μN;k,l+OεNk−1−4k−2/l+1k+l−2+ε,ifk≥4.We complete the proof of Theorem1.
---
*Source: 2902015-2021-11-23.xml* | 2021 |
# Critical State of Sand Matrix Soils
**Authors:** Aminaton Marto; Choy Soon Tan; Ahmad Mahir Makhtar; Tiong Kung Leong
**Journal:** The Scientific World Journal
(2014)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2014/290207
---
## Abstract
The Critical State Soil Mechanic (CSSM) is a globally recognised framework while the critical states for sand and clay are both well established. Nevertheless, the development of the critical state of sand matrix soils is lacking. This paper discusses the development of critical state lines and corresponding critical state parameters for the investigated material, sand matrix soils using sand-kaolin mixtures. The output of this paper can be used as an interpretation framework for the research on liquefaction susceptibility of sand matrix soils in the future. The strain controlled triaxial test apparatus was used to provide the monotonic loading onto the reconstituted soil specimens. All tested soils were subjected to isotropic consolidation and sheared under undrained condition until critical state was ascertain. Based on the results of 32 test specimens, the critical state lines for eight different sand matrix soils were developed together with the corresponding values of critical state parameters,M, λ, and Γ. The range of the value of M, λ, and Γ is 0.803–0.998, 0.144–0.248, and 1.727–2.279, respectively. These values are comparable to the critical state parameters of river sand and kaolin clay. However, the relationship between fines percentages and these critical state parameters is too scattered to be correlated.
---
## Body
## 1. Introduction
Recent field evidences of ground failure in sand with limiting percentages of fines during strong earthquakes have highlighted the need to better characterize the stress-strain behaviour of saturated soils in a broader range, from pure sand to sand matrix soils. Although the recent study trend focuses more on the investigation of sand with limiting percentages of fines, the situation is more worsening when there is still no clear conclusion that could be drawn at this moment to describe the roles of fines in liquefaction susceptibility of sand matrix soils. In the absence of a fundamental understanding of the seismic behaviour of sand matrix soils, the usability of the currently used liquefaction susceptibility assessment criteria, the Modified Chinese Criteria that solely relies on the interpretation of few earthquake events, is actually questionable [1–3].The shear strength and the deformation behaviour of soil are so depended to the combination of changes in volume and confining stress. But the research approach in geotechnical field is to lump together those related postreconnaissance data to formulate new empirical assessment criteria, without capturing their true characteristic through fundamental soil mechanics interpretation. Without implicitly considering the fundamental basis of soil mechanics, applicability of these empirical guidelines which is nonuniversally applicable is arguable. These empirical data only provide limited insight to existing state of art.The stress-strain behaviour of soils could be either stimulated through constitute models or interpreted within classical plasticity models such as Mohr-Coulomb. Among these models, Critical State Soil Mechanic (CSSM) developed by Schofield and Wroth [4] is the most robust framework to explain the fundamental behaviour of different soil materials. The fact that a loose soil is compressible while a dense soil is dilatants is in general agreement. Density well presented the soil behaviour especially for granular soils. Therefore, CSSM is a powerful tool able to explain the behaviour of soil at various density states. It is a globally recognised framework that the critical states for sand and clay are both well established. Nevertheless, the development of the critical state of sand matrix soils is lacking.Moreover, CSSM also rooted the basic theoretical framework of soil liquefaction, yet most available findings within the current literature were outside this critical state context. Table1 summarizes the overall developments of critical CSSM with respect to soil liquefaction study. This paper aims to discuss the development of the critical state line and corresponded critical state parameters for the investigated material, sand matrix soils using sand-kaolin mixtures. The output of this paper will be used as an interpretation framework for the research of liquefaction susceptibility of sand matrix soils in future.Table 1
Overall developments of CSSM with respect to soil liquefaction.
Year
Researchers
Developments
1940
Casagrande [11]
Introduced critical void ratio, the same void ratio where contracted loose soil and dilated dense soil approach after sheared to large strains
1956
Taylor [12]
Showed experimentally that dilatancy is stress dependent
1958
Roscoe et al. [13]
Defined critical state as the ultimate state at which a soil continues to deform at constant stress and constant void ratio
1968
Schofield and Wroth [4]
Brought together stress-dependent strength and dilatancy to introduce critical state soil mechanics with Cam-Clay model
1969
Castro [14]
Observed three different types of stress-strain behaviour (liquefaction, limited liquefaction, and dilation) in monotonic loading tests
1975
Casagrande [15]
Developed steady state line from both drained and undrained tests and noticed that dense sand can be liquefying under sufficient high load
1981
Poulos [16]
Formalised the concept of steady state of deformation (continually deformation under four constant conditions: volume, normal effective stress, shear stress, and velocity)
1985
Poulos et al. [17]
Recognised that steady-state line is useful for identifying the susceptibility of flow liquefaction
1985
Been and Jefferies [18]
Proposed state parameter, the void ratio difference between current state and critical state at same mean stress
1991
Been et al. [19]
Showed that critical state and steady state of sands are equivalent and independent of stress path, sample preparation method, and initial density
## 2. The Critical State of Sand
To date, quite a number of granular soils have been tested to establish for their critical state. Figure1 shows the undrained behaviour of loose sand under triaxial testing. The steady state is exactly representing the critical void ratio under CSSM interpretation. The critical state line (CSL) shows the unique relationship between the deviator stress (q), the mean normal effective stress (p
′), and the specific volume (ν). The relationship is as follows:
(1)
q
f
=
M
p
f
′
ν
f
=
Γ
-
λ
ln
p
f
′
in which the subscripts “f” denote the ultimate failure at the critical states; M denote the critical stress ratio; λ denote the gradient of the critical state line; Γ denote the intercept of the critical state line. The parameters of M
,
λ, and Γ are regarded as constants for a particular soil and the values for some typical soils are given in Table 2.Table 2
Critical state parameters of some soil types [20].
Soil Indexes
LL
PL
λ
Γ
N
M
ϕ
′
κ
/
λ
Fine-grained clay soils
London clay
75
30
0.16
2.45
2.68
0.89
23°
0.39
Kaolin clay
65
15
0.19
3.14
3.26
1.00
25°
0.26
Glacial till
35
17
0.09
1.81
1.98
1.18
29°
0.16
Coarse-grained soils
River sand
0.16
2.99
3.17
1.28
32°
0.09
Decomposed granite
0.09
2.04
2.17
1.59
39°
0.06
Carbonate sand
0.34
4.35
4.80
1.65
40°
0.01Figure 1
Idealised behaviour of loose particular soil in undrained triaxial shear [10].Jefferies and Been [5] had summarised some of the important results as shown in Table 3. In fact, the critical state line is not always in its linear relationship especially at stresses higher than 1000 kPa. However, the range of interest in engineering community is lower than 500 kPa; it is true to treat the critical state line in linear form.Table 3
Critical state properties of some soils (after Jefferies and Been [5]).
Soils
Fines (%)
e
max
e
min
Γ
λ
10
M
Castro sand B
0
0.840
0.500
0.791
0.041
1.22
Castro sand C
0
0.990
0.660
0.988
0.038
1.37
Monterey
0
0.820
0.540
0.878
0.029
1.29
Nevada
7.5
0.887
0.511
0.910
0.045
1.2
Ottawa
0
0.790
0.490
0.754
0.028
1.13
Toyoura
0
0.873
0.656
1.000
0.039
1.24
Erksak 330/0.7
0.7
0.747
0.521
0.816
0.031
1.27
Erksak 320/1
1
0.808
0.614
0.875
0.043
1.27
Erksak 355/3
3
0.963
0.525
0.848
0.054
1.18
Chek Lap Kok
0.5
0.682
0.411
0.905
0.13
—Several researchers try to correlate index properties of granular soils with critical state parameter including fines content [6], void ratio [7], and liquidity index [8]. However, findings show that these index properties on their own only give scatter relationship to be correlated with critical state parameters. These findings therefore are too irrelevant to be practically used. However the intrinsic properties of sand including grain size distribution do actually show their significance influence to the critical state line. Clean sand with rounded grains would have a lower value of λ (λ about 0.03) compared to silty sands with angular shape (λ about 0.2).
## 3. Experiment Testing
In order to establish the critical state line and the critical state parameters for the investigated material, monotonic triaxial compression tests have been performed. The discussion in this paper based on a total of 32 triaxial tests was carried out on sand-kaolin mixtures at several percentages by weight. The parent sand is uniformly graded medium sand (SP) with specific gravity of 2.63. It was obtained from a river in Johor Bahru, Malaysia. In order to obtain clean sand, it was first rinsed with water to remove impurities before proceeding with the sieve analysis. White kaolin with a specific gravity of 2.62, plastic limit of 38, and liquid limit of 25, manufactured by Kaolin (Malaysia) Sdn Bhd, were added to parent sand to create sand matrix soils with various fines percentages by weight. The index properties of the tested sand matrix soils are presented in Table4. The specific gravity of all sand matrix soils is therefore also as 2.63. Based on the criteria of coefficient of uniformity (Cu) and coefficient of curvature (Cc) in Unified Soil Classification System, all of the sand matrix soils are classified under uniformly graded soils (SP). Particle size distribution is shown in Figure 2.Table 4
Compositional characteristic of tested sand matrix soils.
Tested soils
Weight percentages (%)
Density (Mg m−3)
Void ratio
Grading
Sand
kaolin
Min
Max
Min
Max
Cu
Cc
SA1
100
0
1.37
1.59
0.920
0.649
4.1
1.5
SK1
95
5
1.39
1.66
0.894
0.582
4.8
1.7
SK2
90
10
1.41
1.70
0.867
0.550
5.0
1.2
SK3
85
15
1.43
1.76
0.841
0.491
5.4
1.2
SK4
80
20
1.45
1.80
0.815
0.462
5.7
0.8
SK5
75
25
1.47
1.87
0.788
0.409
5.7
0.4
SK6
70
30
1.39
1.76
0.894
0.491
5.4
0.3
SK7
60
40
1.28
1.63
1.051
0.615
4.6
0.3Figure 2
Particle size distribution of the tested soils.The testing conditions were set constantly to increase the precision. All tested specimens have an approximately 100 mm height by 50 mm diameter cylindrical size. Monotonic triaxial compression tests were carried out on strain controlled triaxial apparatus under undrained condition. The specimens were prepared under dry deposition methods to a relative density of 50%. The mould was gently tapped to densify the sand to the required void ratio. The specimens were saturated by being initially flushed with deaired water and followed by increasing the back pressure of 100 kPa. An effective stress of approximately 10 kPa was maintained on the specimen during back pressure saturation. To enhance the consistency of the testing condition, the test was terminated if the specimen could not reach aB value of at least 0.96 at this stage. The strain rate of the shearing process is 0.2 mm/min. The specimens were then isotropically consolidated at various effective confining stresses of 50 kPa, 100 kpa, 200 kPa, and 400 kPa. The moisture content was measured at the end of monotonic tests to enable the specific volume at particular mean normal effective stress to be backed calculated.
## 4. Results and Discussion
Figure3(a) shows the typical stress path of the tested soils performed in this study, particularly the clean sand specimen (SA1). The peak deviator stress is correspondingly increasing at higher effective confining stress as shown in Figure 3(b). It can be observed in Figure 3(c) that the dense specimens (at relative density of 50%) develop negative pore pressure and thus increase the final shear strength. In fact, most researchers prefer to use loose state specimen in establishing the critical state line because of the noticeable peak strength and residue state. However, the existence of quasi-steady state is so confusing and may lead to conservative conclusion. Hence, a dense specimen was considered in this study. Figure 3(d) shows the peak deviator stress of all 32 monotonic undrained triaxial testings. The hyperbolic curve and the noticeable drop at 25% of kaolin added in sand have been justified in companion paper [9]. The additional of fines will initially facilitate grain separation. At the point of threshold fines content where the fines already fully occupy the interstitial space between the sand grains, it forces a return of the sand matrix soils to far less compressible behaviour.(a) Stress path; (b) peak deviator stress; (c) pore pressure developments; (d) undrained shear strength of tested sand matrix soils.
(a)
(b)
(c)
(d)Based on the results of monotonic undrained triaxial testing, the critical state lines of 8 different sand matrix soils are plotted in two different spaces. These critical state lines are parallel to one another. In fact, the straight line through the origin in Figure4(a) (q-p
′ space) and the curved line in Figure 4(b) (v-p
′ space) are corresponded, when transforming the v-p
′ space into log form as in Figure 4(c); the values of Γ and λ could be obtained. Table 5 summarised the critical state parameters of the tested soils in this study. The range of the value of M, λ, and Γ is 0.803–0.998, 0.144–0.248, and 1.727–2.279, respectively. These values are comparable to the critical state parameters of river sand and kaolin clay as shown in Table 2. To compare these critical state parameters at different percentages of fines, for example, Figure 4(d) was plotted, particularly the value of M across fines percentages. However, there is not an apparent relationship that could be drawn between fines percentages and these critical state parameters. The relationship between fines percentages and these critical state parameters are too scattered to be correlated. In addition, other compositional characteristics including both coefficient of curvature and uniformity, limiting void ratio, and void ratio range are also able to uniquely describe the behaviour of sand matrix soils of different fines percentages. The general indexes that have been usually used to describe the compositional characteristics are not sufficient enough to give good correlations in quantifying the trends of critical state parameters across different percentages of fines added in parent sand. Loosely speaking, the plastic behaviour due to the presence of kaolin, as the plastic fines, is a very potential cause for such variation. The plasticity of higher percentages of kaolin existing within parent sand should have higher values compared to lower percentages. Although it is important to find out which intrinsic factor is actually corresponding to such changes, it is beyond the aims and scope of this paper. Therefore, more researches are warranted in future.Table 5
The critical state parameters.
Soils
M
Γ
λ
SA1
0.998
2.279
0.248
SK1
0.926
2.180
0.232
SK2
0.969
2.094
0.221
SK3
0.970
1.956
0.189
SK4
0.940
1.840
0.166
SK5
0.803
1.727
0.148
SK6
0.882
1.829
0.144
SK7
0.940
1.944
0.269Critical state line and critical state parameters of tested sand matrix soils.
(a)
Critical state line inq-p
′ space
(b)
Critical state line inv-p
′ space
(c)
Critical sate line in log form
(d)
Critical state parameters
## 5. Conclusion
An experimental study with undrained monotonic triaxial compression test has been conducted on sand-kaolin mixtures (sand matrix soils) and the results were used to establish the critical state of the soils together with corresponding critical state parameters. Based on the results, the following conclusions are achieved.(1)
The range of the value ofM, λ, and Γ is 0.803–0.998, 0.144–0.248, and 1.727–2.279, respectively.
(2)
Neither the fines percentages nor other corresponding compositional characteristics are adequate to be correlated with the critical state parameters of sand matrix soils.
(3)
More researches are warranted in future to find out which intrinsic factor significantly contributes to the changes to the critical state parameters of sand matrix soils across different fines percentages.
---
*Source: 290207-2014-03-16.xml* | 290207-2014-03-16_290207-2014-03-16.md | 17,098 | Critical State of Sand Matrix Soils | Aminaton Marto; Choy Soon Tan; Ahmad Mahir Makhtar; Tiong Kung Leong | The Scientific World Journal
(2014) | Medical & Health Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2014/290207 | 290207-2014-03-16.xml | ---
## Abstract
The Critical State Soil Mechanic (CSSM) is a globally recognised framework while the critical states for sand and clay are both well established. Nevertheless, the development of the critical state of sand matrix soils is lacking. This paper discusses the development of critical state lines and corresponding critical state parameters for the investigated material, sand matrix soils using sand-kaolin mixtures. The output of this paper can be used as an interpretation framework for the research on liquefaction susceptibility of sand matrix soils in the future. The strain controlled triaxial test apparatus was used to provide the monotonic loading onto the reconstituted soil specimens. All tested soils were subjected to isotropic consolidation and sheared under undrained condition until critical state was ascertain. Based on the results of 32 test specimens, the critical state lines for eight different sand matrix soils were developed together with the corresponding values of critical state parameters,M, λ, and Γ. The range of the value of M, λ, and Γ is 0.803–0.998, 0.144–0.248, and 1.727–2.279, respectively. These values are comparable to the critical state parameters of river sand and kaolin clay. However, the relationship between fines percentages and these critical state parameters is too scattered to be correlated.
---
## Body
## 1. Introduction
Recent field evidences of ground failure in sand with limiting percentages of fines during strong earthquakes have highlighted the need to better characterize the stress-strain behaviour of saturated soils in a broader range, from pure sand to sand matrix soils. Although the recent study trend focuses more on the investigation of sand with limiting percentages of fines, the situation is more worsening when there is still no clear conclusion that could be drawn at this moment to describe the roles of fines in liquefaction susceptibility of sand matrix soils. In the absence of a fundamental understanding of the seismic behaviour of sand matrix soils, the usability of the currently used liquefaction susceptibility assessment criteria, the Modified Chinese Criteria that solely relies on the interpretation of few earthquake events, is actually questionable [1–3].The shear strength and the deformation behaviour of soil are so depended to the combination of changes in volume and confining stress. But the research approach in geotechnical field is to lump together those related postreconnaissance data to formulate new empirical assessment criteria, without capturing their true characteristic through fundamental soil mechanics interpretation. Without implicitly considering the fundamental basis of soil mechanics, applicability of these empirical guidelines which is nonuniversally applicable is arguable. These empirical data only provide limited insight to existing state of art.The stress-strain behaviour of soils could be either stimulated through constitute models or interpreted within classical plasticity models such as Mohr-Coulomb. Among these models, Critical State Soil Mechanic (CSSM) developed by Schofield and Wroth [4] is the most robust framework to explain the fundamental behaviour of different soil materials. The fact that a loose soil is compressible while a dense soil is dilatants is in general agreement. Density well presented the soil behaviour especially for granular soils. Therefore, CSSM is a powerful tool able to explain the behaviour of soil at various density states. It is a globally recognised framework that the critical states for sand and clay are both well established. Nevertheless, the development of the critical state of sand matrix soils is lacking.Moreover, CSSM also rooted the basic theoretical framework of soil liquefaction, yet most available findings within the current literature were outside this critical state context. Table1 summarizes the overall developments of critical CSSM with respect to soil liquefaction study. This paper aims to discuss the development of the critical state line and corresponded critical state parameters for the investigated material, sand matrix soils using sand-kaolin mixtures. The output of this paper will be used as an interpretation framework for the research of liquefaction susceptibility of sand matrix soils in future.Table 1
Overall developments of CSSM with respect to soil liquefaction.
Year
Researchers
Developments
1940
Casagrande [11]
Introduced critical void ratio, the same void ratio where contracted loose soil and dilated dense soil approach after sheared to large strains
1956
Taylor [12]
Showed experimentally that dilatancy is stress dependent
1958
Roscoe et al. [13]
Defined critical state as the ultimate state at which a soil continues to deform at constant stress and constant void ratio
1968
Schofield and Wroth [4]
Brought together stress-dependent strength and dilatancy to introduce critical state soil mechanics with Cam-Clay model
1969
Castro [14]
Observed three different types of stress-strain behaviour (liquefaction, limited liquefaction, and dilation) in monotonic loading tests
1975
Casagrande [15]
Developed steady state line from both drained and undrained tests and noticed that dense sand can be liquefying under sufficient high load
1981
Poulos [16]
Formalised the concept of steady state of deformation (continually deformation under four constant conditions: volume, normal effective stress, shear stress, and velocity)
1985
Poulos et al. [17]
Recognised that steady-state line is useful for identifying the susceptibility of flow liquefaction
1985
Been and Jefferies [18]
Proposed state parameter, the void ratio difference between current state and critical state at same mean stress
1991
Been et al. [19]
Showed that critical state and steady state of sands are equivalent and independent of stress path, sample preparation method, and initial density
## 2. The Critical State of Sand
To date, quite a number of granular soils have been tested to establish for their critical state. Figure1 shows the undrained behaviour of loose sand under triaxial testing. The steady state is exactly representing the critical void ratio under CSSM interpretation. The critical state line (CSL) shows the unique relationship between the deviator stress (q), the mean normal effective stress (p
′), and the specific volume (ν). The relationship is as follows:
(1)
q
f
=
M
p
f
′
ν
f
=
Γ
-
λ
ln
p
f
′
in which the subscripts “f” denote the ultimate failure at the critical states; M denote the critical stress ratio; λ denote the gradient of the critical state line; Γ denote the intercept of the critical state line. The parameters of M
,
λ, and Γ are regarded as constants for a particular soil and the values for some typical soils are given in Table 2.Table 2
Critical state parameters of some soil types [20].
Soil Indexes
LL
PL
λ
Γ
N
M
ϕ
′
κ
/
λ
Fine-grained clay soils
London clay
75
30
0.16
2.45
2.68
0.89
23°
0.39
Kaolin clay
65
15
0.19
3.14
3.26
1.00
25°
0.26
Glacial till
35
17
0.09
1.81
1.98
1.18
29°
0.16
Coarse-grained soils
River sand
0.16
2.99
3.17
1.28
32°
0.09
Decomposed granite
0.09
2.04
2.17
1.59
39°
0.06
Carbonate sand
0.34
4.35
4.80
1.65
40°
0.01Figure 1
Idealised behaviour of loose particular soil in undrained triaxial shear [10].Jefferies and Been [5] had summarised some of the important results as shown in Table 3. In fact, the critical state line is not always in its linear relationship especially at stresses higher than 1000 kPa. However, the range of interest in engineering community is lower than 500 kPa; it is true to treat the critical state line in linear form.Table 3
Critical state properties of some soils (after Jefferies and Been [5]).
Soils
Fines (%)
e
max
e
min
Γ
λ
10
M
Castro sand B
0
0.840
0.500
0.791
0.041
1.22
Castro sand C
0
0.990
0.660
0.988
0.038
1.37
Monterey
0
0.820
0.540
0.878
0.029
1.29
Nevada
7.5
0.887
0.511
0.910
0.045
1.2
Ottawa
0
0.790
0.490
0.754
0.028
1.13
Toyoura
0
0.873
0.656
1.000
0.039
1.24
Erksak 330/0.7
0.7
0.747
0.521
0.816
0.031
1.27
Erksak 320/1
1
0.808
0.614
0.875
0.043
1.27
Erksak 355/3
3
0.963
0.525
0.848
0.054
1.18
Chek Lap Kok
0.5
0.682
0.411
0.905
0.13
—Several researchers try to correlate index properties of granular soils with critical state parameter including fines content [6], void ratio [7], and liquidity index [8]. However, findings show that these index properties on their own only give scatter relationship to be correlated with critical state parameters. These findings therefore are too irrelevant to be practically used. However the intrinsic properties of sand including grain size distribution do actually show their significance influence to the critical state line. Clean sand with rounded grains would have a lower value of λ (λ about 0.03) compared to silty sands with angular shape (λ about 0.2).
## 3. Experiment Testing
In order to establish the critical state line and the critical state parameters for the investigated material, monotonic triaxial compression tests have been performed. The discussion in this paper based on a total of 32 triaxial tests was carried out on sand-kaolin mixtures at several percentages by weight. The parent sand is uniformly graded medium sand (SP) with specific gravity of 2.63. It was obtained from a river in Johor Bahru, Malaysia. In order to obtain clean sand, it was first rinsed with water to remove impurities before proceeding with the sieve analysis. White kaolin with a specific gravity of 2.62, plastic limit of 38, and liquid limit of 25, manufactured by Kaolin (Malaysia) Sdn Bhd, were added to parent sand to create sand matrix soils with various fines percentages by weight. The index properties of the tested sand matrix soils are presented in Table4. The specific gravity of all sand matrix soils is therefore also as 2.63. Based on the criteria of coefficient of uniformity (Cu) and coefficient of curvature (Cc) in Unified Soil Classification System, all of the sand matrix soils are classified under uniformly graded soils (SP). Particle size distribution is shown in Figure 2.Table 4
Compositional characteristic of tested sand matrix soils.
Tested soils
Weight percentages (%)
Density (Mg m−3)
Void ratio
Grading
Sand
kaolin
Min
Max
Min
Max
Cu
Cc
SA1
100
0
1.37
1.59
0.920
0.649
4.1
1.5
SK1
95
5
1.39
1.66
0.894
0.582
4.8
1.7
SK2
90
10
1.41
1.70
0.867
0.550
5.0
1.2
SK3
85
15
1.43
1.76
0.841
0.491
5.4
1.2
SK4
80
20
1.45
1.80
0.815
0.462
5.7
0.8
SK5
75
25
1.47
1.87
0.788
0.409
5.7
0.4
SK6
70
30
1.39
1.76
0.894
0.491
5.4
0.3
SK7
60
40
1.28
1.63
1.051
0.615
4.6
0.3Figure 2
Particle size distribution of the tested soils.The testing conditions were set constantly to increase the precision. All tested specimens have an approximately 100 mm height by 50 mm diameter cylindrical size. Monotonic triaxial compression tests were carried out on strain controlled triaxial apparatus under undrained condition. The specimens were prepared under dry deposition methods to a relative density of 50%. The mould was gently tapped to densify the sand to the required void ratio. The specimens were saturated by being initially flushed with deaired water and followed by increasing the back pressure of 100 kPa. An effective stress of approximately 10 kPa was maintained on the specimen during back pressure saturation. To enhance the consistency of the testing condition, the test was terminated if the specimen could not reach aB value of at least 0.96 at this stage. The strain rate of the shearing process is 0.2 mm/min. The specimens were then isotropically consolidated at various effective confining stresses of 50 kPa, 100 kpa, 200 kPa, and 400 kPa. The moisture content was measured at the end of monotonic tests to enable the specific volume at particular mean normal effective stress to be backed calculated.
## 4. Results and Discussion
Figure3(a) shows the typical stress path of the tested soils performed in this study, particularly the clean sand specimen (SA1). The peak deviator stress is correspondingly increasing at higher effective confining stress as shown in Figure 3(b). It can be observed in Figure 3(c) that the dense specimens (at relative density of 50%) develop negative pore pressure and thus increase the final shear strength. In fact, most researchers prefer to use loose state specimen in establishing the critical state line because of the noticeable peak strength and residue state. However, the existence of quasi-steady state is so confusing and may lead to conservative conclusion. Hence, a dense specimen was considered in this study. Figure 3(d) shows the peak deviator stress of all 32 monotonic undrained triaxial testings. The hyperbolic curve and the noticeable drop at 25% of kaolin added in sand have been justified in companion paper [9]. The additional of fines will initially facilitate grain separation. At the point of threshold fines content where the fines already fully occupy the interstitial space between the sand grains, it forces a return of the sand matrix soils to far less compressible behaviour.(a) Stress path; (b) peak deviator stress; (c) pore pressure developments; (d) undrained shear strength of tested sand matrix soils.
(a)
(b)
(c)
(d)Based on the results of monotonic undrained triaxial testing, the critical state lines of 8 different sand matrix soils are plotted in two different spaces. These critical state lines are parallel to one another. In fact, the straight line through the origin in Figure4(a) (q-p
′ space) and the curved line in Figure 4(b) (v-p
′ space) are corresponded, when transforming the v-p
′ space into log form as in Figure 4(c); the values of Γ and λ could be obtained. Table 5 summarised the critical state parameters of the tested soils in this study. The range of the value of M, λ, and Γ is 0.803–0.998, 0.144–0.248, and 1.727–2.279, respectively. These values are comparable to the critical state parameters of river sand and kaolin clay as shown in Table 2. To compare these critical state parameters at different percentages of fines, for example, Figure 4(d) was plotted, particularly the value of M across fines percentages. However, there is not an apparent relationship that could be drawn between fines percentages and these critical state parameters. The relationship between fines percentages and these critical state parameters are too scattered to be correlated. In addition, other compositional characteristics including both coefficient of curvature and uniformity, limiting void ratio, and void ratio range are also able to uniquely describe the behaviour of sand matrix soils of different fines percentages. The general indexes that have been usually used to describe the compositional characteristics are not sufficient enough to give good correlations in quantifying the trends of critical state parameters across different percentages of fines added in parent sand. Loosely speaking, the plastic behaviour due to the presence of kaolin, as the plastic fines, is a very potential cause for such variation. The plasticity of higher percentages of kaolin existing within parent sand should have higher values compared to lower percentages. Although it is important to find out which intrinsic factor is actually corresponding to such changes, it is beyond the aims and scope of this paper. Therefore, more researches are warranted in future.Table 5
The critical state parameters.
Soils
M
Γ
λ
SA1
0.998
2.279
0.248
SK1
0.926
2.180
0.232
SK2
0.969
2.094
0.221
SK3
0.970
1.956
0.189
SK4
0.940
1.840
0.166
SK5
0.803
1.727
0.148
SK6
0.882
1.829
0.144
SK7
0.940
1.944
0.269Critical state line and critical state parameters of tested sand matrix soils.
(a)
Critical state line inq-p
′ space
(b)
Critical state line inv-p
′ space
(c)
Critical sate line in log form
(d)
Critical state parameters
## 5. Conclusion
An experimental study with undrained monotonic triaxial compression test has been conducted on sand-kaolin mixtures (sand matrix soils) and the results were used to establish the critical state of the soils together with corresponding critical state parameters. Based on the results, the following conclusions are achieved.(1)
The range of the value ofM, λ, and Γ is 0.803–0.998, 0.144–0.248, and 1.727–2.279, respectively.
(2)
Neither the fines percentages nor other corresponding compositional characteristics are adequate to be correlated with the critical state parameters of sand matrix soils.
(3)
More researches are warranted in future to find out which intrinsic factor significantly contributes to the changes to the critical state parameters of sand matrix soils across different fines percentages.
---
*Source: 290207-2014-03-16.xml* | 2014 |
# Correlation between Mitochondrial Dysfunction, Cardiovascular Diseases, and Traditional Chinese Medicine
**Authors:** Li Zhu; Zhigang Chen; Keli Han; Yilin Zhao; Yan Li; Dongxu Li; Xiulong Wang; Xuefang Li; Siyu Sun; Fei Lin; Guoan Zhao
**Journal:** Evidence-Based Complementary and Alternative Medicine
(2020)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2020/2902136
---
## Abstract
Cardiovascular disease (CVD) is the number one threat that seriously endangers human health. However, the mechanism of their occurrence is not completely clear. Increasing studies showed that mitochondrial dysfunction is closely related to CVD. Possible causes of mitochondrial dysfunction include oxidative stress, Ca2+ disorder, mitochondrial DNA mutations, and reduction of mitochondrial biosynthesis, all of which are closely related to the development of CVD. At present, traditional Chinese medicine (TCM) is widely used in the treatment of CVD. TCM has the therapeutic characteristics of multitargets and multipathways. Studies have shown that TCM can treat CVD by protecting mitochondrial function. Via systematic literature review, the results show that the specific mechanisms include antioxidant stress, regulation of calcium homeostasis, antiapoptosis, and regulation of mitochondrial biosynthesis. This article describes the relationship between mitochondrial dysfunction and CVD, summarizes the TCM commonly used for the treatment of CVD in recent years, and focuses on the regulatory effect of TCM on mitochondrial function.
---
## Body
## 1. Introduction
With the continuous progress in the treatment of infectious diseases and the extension of human life span, the battlefield between humans and diseases has shifted to chronic noncommunicable diseases. Among them, cardiovascular disease (CVD) has become the leading cause of death in China and worldwide as its incidence continues to increase, and it poses a serious threat to the safety and quality of life of patients [1, 2]. Atherosclerosis, hypertension, myocardial ischemia-reperfusion injury, and heart failure are common CVDs or pathological processes. However, the mechanism of their occurrence is not completely clear. An increasing number of studies has shown that mitochondrial dysfunction is closely related to CVD. The mechanisms mainly include oxidative stress disorder, calcium disorder, reduction of mitochondrial biosynthesis, transition of mitochondrial permeability, and accumulation of mitochondrial DNA mutation. At present, TCM, which has the characteristics of multitargets and multipathways, is widely used in the treatment of CVD [3]. Therefore, in this paper, we discuss the relationship between mitochondrial dysfunction and CVD, as well as the therapeutic mechanism of TCM in the treatment of CVD with respect to mitochondrial function.
## 2. Functional Properties of Mitochondria
Mitochondria are semiautonomous organelles with a unique genetic system that provide the chemical energy required for biosynthesis, respiration, secretion, and mechanical movement in organisms; they are also important organelles that generate intracellular free radicals and regulate apoptosis [4–6]. Mitochondria are known as “capacity factories,” “apoptosis switches,” and “enzyme bags.” They are also called “cellular energy-processing factories” because they oxidize three major nutrients to provide adenosine triphosphate (ATP), which is required for life activities [4]. In addition to being energy producers, mitochondria are also the main site of reactive oxygen species [6] (ROS) production. Furthermore, mitochondria also play an important role in the regulation of intracellular calcium homeostasis, calcium-sensitive enzyme activity, and signal transduction [7]. In conclusion, mitochondria are central mediators of energy production, signal transduction, oxidative stress, Ca2+ homeostasis, and apoptosis regulation. Therefore, the normal function of mitochondria is of great importance in life activities.
## 3. Mitochondria and Cardiomyocytes
Cardiomyocytes are highly dependent on aerobic oxidation to supply energy. They contain a considerable amount of mitochondria, up to 20–30% of cell capacity, which provide more than 90% of energy to the heart muscle [8, 9]. The sources of myocardial energy include fatty acids, glucose, and other carbohydrates. These substrates are metabolized in mitochondria, providing energy for cardiomyocytes through oxidative phosphorylation. In fact, 60% to 90% of the energy needed by myocardium originates from the ATP produced by aerobic oxidation of fatty acids. Only 10% to 40% of the energy is generated by glucose glycolysis and lactic acid oxidation. In addition, the production and utilization of ketone body, ornithine, heme, cardiolipin, and ubiquinone are all related to mitochondria [10].As a vital functional organelle in myocardial cells, the function of mitochondria is key to elucidating the physiological and pathological changes in CVD, and mitochondrial homeostasis is the core element for maintaining myocardial metabolism, function, and structure [11].
## 4. Mitochondrial Homeostasis
Mitochondrial homeostasis is the steady-state balance between mitochondrial biogenesis and degradation. It involves many aspects such as mitochondrial division and fusion [6, 12], mitochondrial crest remodeling [6, 8], mitochondrial biosynthesis [13, 14], mitochondrial autophagy [15, 16], and mitochondrial oxidative stress [9, 17]. Mitochondrial homeostasis refers to the healthy and stable state of mitochondrial content and metabolism for ensuring the stability of cell energy supply and material metabolism. To maintain the integrity of the mitochondrial structure, mitochondrial division and fusion and mitochondrial crest morphology are altered along with changes in intracellular energy supply [12]. Mitochondrial health is maintained through biosynthesis and autophagy degradation to respond to different energy requirements of cells [10, 15]. In addition, ROS in mitochondria can be used as signal molecules to activate redox signal molecules through redox reaction, thus participating in the regulation of intracellular signal transduction [18]. Disruption of mitochondrial homeostasis may cause imbalance of mitochondrial motility, lysis of mitochondrial cristae, disruption of mitochondrial biosynthesis, abnormal degradation of mitochondrial autophagy, and oxidative stress in mitochondria. Therefore, the stable state of mitochondrial structure and function has very important physiological significance for the growth, metabolism, and heredity of organisms [19].
## 5. Mitochondria Dysfunction and Cardiovascular Diseases
Mitochondria are the energy factories of cells, and their main function is to consume oxygen and metabolize three major nutrients (sugars, lipids, and amino acids) to produce CO2, water, and energy (ATP) [4]. Cells often need to manage their energy expenditure based on the availability of nutrients and their ability to produce ATP [10]. Disrupted mitochondrial homeostasis will lead to abnormal metabolism of these common substances in the body. Higher organisms need to consume larger amount of energy, and the ATP produced by anaerobic glycolysis is only approximately 1/16 of that produced by aerobic oxidation.Mitochondria are exposed to various physiological or stress signals, and they produce different signal molecules that affect oxidative stress, apoptosis, autophagy, and inflammation, which are closely related to the occurrence of CVD [11, 16, 20]. The pathophysiological processes of abnormal effects of mitochondria on CVD are reflected in the following aspects: (1) because cardiomyocytes rely on fatty acid-driven oxidative phosphorylation to produce ATP, a decline in the biological efficiency of the mitochondrial network may directly harm the contractility of cardiomyocytes; (2) because Ca2+ flow is the core of overall cardiac activity, incapability of the mitochondrial network to regulate Ca2+ homeostasis can alter cardiac function; (3) physiological inflammatory homeostasis has a certain protective effect not only on cardiac function but also on vascular filling, but the accumulation of damaged mitochondria in the cytoplasm of cardiomyocytes or endothelial cells can cause pathogenic inflammation; and (4) the integrity of the cardiovascular system is essential for cardiac contractile and circulatory functions. Severe mitochondrial dysfunction and accumulation of damaged mitochondria initiate a series of cell death that eventually leads to pathological damage.
## 6. Mitochondrial Dysfunction and Atherosclerosis
Atherosclerotic (AS) is the main cause of death due to cardiovascular disease. In patients with mitochondrial dysfunction, decreased activity of progressive respiratory chain enzymes, excessive production of ROS, and cumulative mitochondrial DNA (mtDNA) damage or mutations are closely related to the occurrence and development of atherosclerosis [21, 22]. Studies have shown that oxidized low-density lipoprotein (ox-LDL) plays an important role in the occurrence and development of atherosclerosis; ROS produced by mitochondria and its modified ox-LDL are involved in all pathological processes of atherosclerosis [23]. Ox-LDL can slow down the electron transport of mitochondrial respiratory chain by inhibiting the activity of mitochondrial respiratory enzymes and increasing the formation of ROS, thus forming a vicious circle and promoting endothelial injury and atherosclerosis [23]. It was found that when the activity of Mn-SOD (SOD2) decreased, mtDNA damage increased in apoE−/− rats, which preceded the formation of atherosclerotic plaques. As oxidative stress in mitochondria increased, atherosclerotic lesions were significantly aggravated [24]. In addition, studies in apoE−/−-SOD2+/− mice have shown that an increase in mitochondrial ROS not only promoted the formation of atherosclerotic plaques but also increased the susceptibility of the body to atherosclerotic risk factors [25]. Moreover, mtDNA damage caused by DNA repair dysfunction can directly accelerate atherosclerosis in apoE−/− rats and promote diabetic atherosclerotic complications. Furthermore, transient opening of mitochondrial permeability transition pore (mPTP) can depolarize mitochondrial membrane potential, whereas long-term opening of mPTP leads to matrix swelling, rupture of mitochondrial outer membrane, and apoptosis. Both of these changes can promote the occurrence and development of atherosclerosis [21, 22]. In an experiment using wild-type mice, it was found that aging led to increases in IL-6 level and mitochondrial dysfunction. Hyperlipidemia further decreased the mitochondrial function and increased the level of Parkin in the aorta of old mice (16 months of age). Importantly, oral spermidine can enhance the mitotic function of aged hyperlipidemic mice, prevent elevation of aortic IL-6 and Parkin levels, reduce mitochondrial dysfunction, and reduce atherosclerosis formation. Overall, new treatments that improve vascular mitochondrial bioenergetics or reduce inflammation before hyperlipidemia may reduce age-related atherosclerosis [26]. Overall, oxidative stress, inflammatory reaction, and mitochondrial dysfunction play a key role in the formation of atherosclerosis. Mitochondria-targeted antioxidant and anti-inflammatory therapies may have great prospects for the treatment of atherosclerosis [27].
## 7. Mitochondrial Dysfunction and Hypertension
Hypertension is a common CVD in modern society. Many studies have shown that mitochondrial dysfunction is closely related to hypertension [28]. The superoxide anions produced by mitochondria can oxidize the NO released by endothelial cells, decrease the endothelium-dependent vasodilation function, increase vascular force, and increase blood pressure. Uncoupling of mitochondrial oxidative phosphorylation caused by UCP2 gene polymorphism or altered expression is also associated with high blood pressure [29]. In addition, the lack of mitochondrial productivity, calcium overload, and mitochondrial DNA mutations are all involved in the pathological process of arterial hypertension and hypertensive heart disease. Angiotensin II (Ang II) plays an important role in the development of hypertension. Ang II can also inactivate the NO produced by endothelial cell by stimulating the production of mitochondrial ROS, resulting in vascular endothelial dysfunction [30]. Mitochondrial dysfunction is also related to dysfunction of blood pressure regulation center [31]. Related research has confirmed that mitochondrial dysfunction caused by maternally inherited mitochondrial transfer ribonucleic acid (tRNA) mutations is associated with the development of essential hypertension [32]. Otherwise, under the conditions of inflammation, Ang II stimulation, and metabolic syndrome, disturbances in mitochondrial biogenesis and mitochondrial bioenergetics in the brain will lead to the accumulation of ROS, which plays an active role in the pathophysiology of ROS-related neurogenic hypertension [33]. Overall, increased ROS production, decreased ATP production, and calcium overload play an important role in the occurrence and development of hypertension. Moreover, mitochondrial gene polymorphism and mitochondrial tRNA gene mutations are also associated with hypertension.
## 8. Mitochondrial Dysfunction and Myocardial Ischemia-Reperfusion Injury
Myocardial ischemia-reperfusion injury (IR injury) is common in reperfusion therapy after acute myocardial infarction, manifesting as arrhythmia, reduced cardiac systolic function, and other phenomena. Mitochondrial energy metabolism disorder is an important factor causing myocardial IR injury [34]. The main mechanisms include reduced mitochondrial ATP production and excessive ROS production, causing oxidative stress, Ca2+ overload, and sustained mPTP opening [18, 35]. Excessive ROS production during ischemic myocardial reperfusion is the main cause of myocardial IR injury, and mitochondria are an important source of ROS. On the one hand, increased ROS can damage the mitochondrial membrane system, which affects the mitochondrial membrane potential and disrupts mitochondrial ATP synthesis. On the other hand, mitochondria produce excessive ROS, which causes peroxidation of proteins and lipids and damage to the mitochondrial membrane, further decreasing the activity of the electron transport chain enzymes, which in turn form a vicious circle that eventually leads to cardiomyocyte apoptosis and necrosis [36]. In addition to excessive ROS, myocardial ischemia-reperfusion-induced cell Ca2+ overload is an important cause of myocardial IR injury [18, 35]. Persistent opening of mitochondrial mPTP with high permeability also plays an important role in IR injury. This causes the entrance of numerous small molecules to mitochondria, resulting in the swelling of mitochondria, rupture of the outer membrane, collapse of membrane potential, and release of various proapoptotic factors to induce cell apoptosis or death [35]. Taken together, improving mitochondrial function, reducing oxidative stress caused by excessive production of mitochondrial ROS, preventing intracellular calcium overload, and preventing the opening of mitochondrial mPTP are effective measures for the prevention and treatment of IR injury.
## 9. Mitochondrial Dysfunction and Heart Failure
Heart failure (HF) is the final stage of the development of various CVDs, such as myocardial infarction, hypertension, and cardiomyopathy. The relationship between mitochondrial dysfunction and HF is mainly reflected as follows: the disturbance of mitochondrial energy metabolism plays an important role in the occurrence and development of HF. During HF, mitochondrial ATP synthesis decreased, and ROS production increased, whereas the disturbance of energy metabolism in myocardial mitochondria aggravated the disruption of cardiac mechanical function and deterioration of cardiac function. ROS modified myofibrillar protein in the myocardium via oxidation, resulting in a progressive decrease in cardiac contractile function and irreversible cardiac injury [37, 38]. Studies in an experimental HF model have shown that the expression of myocardial mitochondrial biosynthesis factor is downregulated, whereas mtDNA content is reduced, which not only results in reduced mitochondrial biosynthesis but also causes mitochondrial oxidative phosphorylation and reduces the ability of mitochondria to oxidize fatty acids, which leads to deficiencies in myocardial energy production and HF development [39]. In patients with congenital heart disease, damage in mtDNA replication leads to the loss of right ventricular mtDNA, resulting in the progression of heart hypertrophy to HF [40, 41]. Therefore, to prevent mitochondrial damage and maintain the integrity of its function, reducing oxidative stress will be an important strategy in the treatment of HF [41].In summary, the maintenance of mitochondrial homeostasis is very important in life activities, and mitochondrial dysfunction is closely related to the occurrence and development of CVD. TCM is widely applied in the clinical treatment of CVD, and mitochondria are the intracellular targets of many kinds of drugs. Thus, we propose that TCM can treat CVD by affecting mitochondrial homeostasis.
## 10. Protective Effect of TCM on Myocardial Mitochondria
Mitochondria play a significant role in the regulation of physiological function and pathological process in the cardiovascular system [11]. TCM [42], including the chemical components, single herbs, and compound medicines, can treat CVD by regulating the function of mitochondria, which will be described below.
### 10.1. Chemical Components of TCM
The chemical components of TCM are the substance bases of its pharmacology. The composition of TCM is extremely complex, as each TCM contains many kinds of chemical components. Components that have biological activity and play a role in the prevention and treatment of diseases are known as effective components. Modern studies have shown that the effective components of TCM can protect cardiomyocyte mitochondria in many ways. Several common drugs are summarized in Tables1–4.Table 1
Regulatory effects of active components of TCM on mitochondria.
CategoryChemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferenceRestoratives for invigorating qiGinsenoside compound KRadix ginsengC36H62O8Inhibition of nuclear factor-Bκ, p38, and JNK MAPK pathwaysLu et al. [43]Astragaloside IVRadix AstragaliC41H68O14Regulation of NF-κB/PGC-1α signaling-mediated energy biosynthesisZhang et al. [44]Downregulation of miR-23a and miR-92a-activated PI3K/AKT and MAPK/ERK signaling pathwaysGong et al. [45]Stimulation of fatty acidß-oxidation and improvement of mitochondrial functionDong et al. [46]Astragalus polysaccharidesRadix AstragaliC10H7ClN2O2SInhibition of apoptosisLiu et al. [47]SalidrosideRhodiola crenulataC14H20O7Activation of a mitochondria-associated AMPK/PI3K/Akt/GSK3β pathwayZheng et al. [48]Restoratives for nourishing yinOphiopogonin DRadix OphiopogonisC44H70O16Antioxidant and antiapoptotic effectsHuang et al. [49]EcliptalEclipta alba—Activation of the Wnt-pathway and alteration of AKT signalingYang et al. [50]Restoratives for nourishing yangVelvet antlerCornu cervi pantotrichum—Regulation of the PI3K/Akt signaling pathway and mitochondrial membrane potentialXiao et al. [51]IcariinHerba EpimediiC33H40O15Activation of sirtuin-1/FOXO1 signaling and improvement of mitochondrial membrane homeostasisWu et al. [52]Table 2
Regulatory effects of the active components of traditional Chinese medicine on mitochondria for promoting blood circulation and removing blood stasis.
Chemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferencePanax notoginseng saponinsRadix NotoginsengC47H80O17Attenuation of oxidative stress and cardiomyocyte apoptosisZhang et al. [53]Zhou et al. [54]Notoginsenoside R1Radix NotoginsengC54H92O24Elevation of mitochondrial ATP synthased-subunitsHe et al. [55]Salvianolic acid ARadix Salviae MiltiorrhizaeC26H22O10Promotion of myocardial mitochondria biogenesisZhang et al. [56]Salvianolic acid BRadix Salviae Miltiorrhizae—Improvement of mitochondrial biogenesisPan et al. [57]Tanshinone IIARadix Salviae MiltiorrhizaeC19H18O3Upregulation of 14-3-3η, prevention of mPTP opening, and inhibition of apoptosisZhang et al. [58]DihydronortanshinoneRadix Salviae Miltiorrhizae—Anti-inflammatory effect via the NF-κB, mitochondrial ROS, and MAPK pathwaysWu et al. [59]CurcuminRhizoma Curcumae LongaeC21H20O6Antioxidant and anti-inflammatory activitiesLi et al. [60]Mitochondrial stress and substrate switching inhibitionTable 3
Regulatory effects of the active components of interior warming medicines on mitochondria.
Chemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferenceFlavonoid glycosidesFenugreek—Regulation of glycolipid metabolismLuan et al. [61]Rhizoma ZingiberC17H26O4Improvement of ectopic lipid accumulation, mitochondrial dysfunction, and insulin resistanceLiu et al. [62]Table 4
Regulatory effects of the active components of other traditional Chinese medicines on mitochondria.
Type of TCMMonomer sourceMolecular formulaMechanism of actionReferenceTriptolideTripterygium wilfordiiC21H28O6Regulation of mitochondrial membrane permeabilizationXi et al. [63]OxymatrineRadix Sophorae FlavescentisC16H26N2O2Inhibition of cardiac apoptosis and oxidative stressZhang et al. [64]Epigallocatechin gallateGreen teaC22H18O11Inhibition of deterioration of mitochondrial structure and function by OMA1Nan et al. [65]Cyclovirobuxine DBuxus microphylla SiebC26H46N2OAntioxidant effect and promotion of mitochondrial biogenesisGuo et al. [66]TetrandrineRadix Stephaniae TetrandraeC38H42N2O6Regulation of glycolysis and energy metabolismZhang et al. [67]
### 10.2. Single Herbs of TCM
Single herbs are a type of TCM. Different single herbs have different curative effects, but they may have the same drug action. A single herb can have many different effects. Previous studies have shown that some single-herb medicines can treat coronary heart disease (CHD) by affecting mitochondrial homeostasis. Several common drugs are summarized in Table5.Table 5
Regulatory effects of single-herb traditional Chinese medicines on mitochondria.
Type of TCMSingle herbMechanism of actionReferenceRestoratives for invigorating qiRadix AstragaliPromotion of mitochondrial bioenergeticsHuang et al. [68]Restoratives for invigorating qiRhodiola roseaPromotion of mitochondrial biogenesis and functionsZhuang et al. [69]Antioxidant and anti-inflammatory activitiesZhou et al. [70]Heat clearing Chinese medicinal herbsSilybum marianumMitigation of oxidative stress and attenuation of reactive fibrosis via TGFß1/TßRs/SMAD2/3 signalingVilahur et al. [71]Invigorating the blood and removing blood stasisSalviae Miltiorrhizae Radix et RhizomaActivation of the Nrf2-mediated antioxidant defense systemLi et al. [72]The interior warming Chinese medicinal herbsCortex CinnamomiUpregulation of mitochondrial biogenesisSong et al. [73]
### 10.3. Compound Prescriptions of TCM
Compound prescriptions are the main form of clinical TCM. After determining the treatment based on syndrome differentiation, a compound prescription is formulated by selecting the appropriate drug, determining the dosage, and combining two or more medicines according to the requirements of the basic structure of the prescription. The main objectives of these prescriptions are to enhance drug efficacy, produce synergistic drug effects, control the direction of multifunctional single herbs, expand the scope of treatment, improve drug adaptation to complex conditions, and control the toxic and side effects of drugs.Clinically, most of the drugs used to treat CHD are compound prescriptions. The regulation of CHD by compound prescriptions involve the whole body, including the heart, brain, liver, kidney, lung, large intestine, muscle, and other viscera, and they improve the structure and quantity of mitochondria in each tissue [39, 74]. In addition, compound prescriptions can treat CHD by protecting mitochondrial function, reducing antioxidant stress, improving mitochondrial lipid metabolism, and exerting anti-inflammatory effect. The compound prescriptions commonly used in TCM are listed in Table 6.Table 6
Regulatory effects of compound prescriptions on mitochondria.
Name of compound prescriptionComponents of compound prescriptionMechanism of actionReferenceShengmai formula (SM)Radix ginseng and Radix OphiopogonisProtection of cardiomyocytes against hypoxiaWang et al. [75], Yu et al. [76]Induction of mitophagy and modulation of mitochondrial dynamicsShenxian-Shengmai oral (SXSM)Red Radix ginseng, Herba Epimedii, Fructus Psoraleae (salted), Fructus Lycii, Herba Ephedrae, etc.Antioxidant effect, promotion of SOD activity, elevation of GSH content, and reduction of intracellular ROS levelsZhao et al. [77]YiXin-Shu (YXS)Ginseng, Radix Astragali, Salvia miltiorrhiza, Ophiopogon, Ligusticum, etc.Upregulation of endogenous nuclear receptors (LXRα, PPARα, PPARβ, and ERα) as well as suppression of apoptosis and oxidative stressZhao et al. [78]Shengmai San (SMS)Panax ginseng, Ophiopogon japonicus, and Schisandra chinensisImprovement of mitochondrial lipid metabolism, restoration of mitochondrial structure and function, and promotion of mitochondrial biogenesis via the Sirt1/PGC-1α pathwayTian et al. [79], Lu et al. [80], andLi et al. [81]QiShenYiQi Pills (QSYQ)Radix Astragali, Salvia miltiorrhiza, Panax notoginseng, etc.Regulation of energy metabolism and elevation of mitochondrial content and biogenesis via PGC-1α activationLin et al. [82], Yu et al. [83], and Lin et al. [84]Shexiang Baoxin Pill (SBP)Moschus, Radix Ginseng, Calculus Bovis, Styrax, Cortex Cinnamomi, Venenum Bufonis, and Borneolum SyntheticumAnti-inflammatory and antioxidant effects, improvement of lipid metabolism, protection of mitochondrial function, and upregulation of AMPK and PGC-1a expressionWei et al. [85]Qiang-Xin 1 formulaAstragalus, Poria, Schisandra, Salvia miltiorrhiza, etc.Prevention of sepsis-induced apoptosisXu et al. [86]Tongxinluo capsule (TXL)Radix ginseng, Hirudo, Scorpio, Radix Paeoniae Rubra, etc.Anti-inflammatory effect and improvement of lipid metabolismZhang et al. [74] Ma et al. [87]In summary, mitochondria are semiautonomous organelles that integrate the three basic life activities: material metabolism, energy metabolism, and genetic variation; they are also the place for intracellular respiration and energy conversion and participate in various important physiological and biochemical processes. Overall, TCM affects the processes of mitochondrial energy metabolism, apoptosis, and oxidative stress in multilevels via multitargets, and the same category of drugs has certain commonness and individuality. The mechanisms are summarized in Table7.Table 7
Action mechanisms of TCM on mitochondria.
Action mechanismChemical components of TCMSingle herbCompound prescriptionMitochondrial structureVelvet antler, icariin, tanshinone IIA, triptolide, and epigallocatechin gallate—Shengmai SanMitochondria biosynthesisEcliptal, salvianolic acid A, salvianolic acid B, and cyclovirobuxine DRadix Astragali, Rhodiola rosea, Cortex, CinnamomiQiShenYiQi pillsMitochondrial functionFlavonoid glycosides, 6-gingerol, and epigallocatechin gallateRhodiola roseaShengmai formula, Shengmai San, and Shexiang Baoxin pillAnti-inflammatory effectGinsenoside compound K, astragaloside IV, dihydronortanshinone, and curcuminRhodiola roseaTongxinluo capsule (TXL), Shexiang Baoxin pillInhibit apoptosisAstragalus polysaccharides, ophiopogonin D, and oxymatrine—YiXin-Shu, Qiang-Xin 1 formulaAntioxidationOphiopogonin D, panax notoginseng saponins, oxymatrine, cyclovirobuxine D, and curcuminRhodiola rosea, Silybum marianum, Salviae, Miltiorrhizae Radix et RhizomaShenxian-Shengmai oral, YiXin-Shu, and Shexiang Baoxin pillEnergy metabolismSalidroside, notoginsenoside R1, and tetrandrineRadix Astragali—
## 10.1. Chemical Components of TCM
The chemical components of TCM are the substance bases of its pharmacology. The composition of TCM is extremely complex, as each TCM contains many kinds of chemical components. Components that have biological activity and play a role in the prevention and treatment of diseases are known as effective components. Modern studies have shown that the effective components of TCM can protect cardiomyocyte mitochondria in many ways. Several common drugs are summarized in Tables1–4.Table 1
Regulatory effects of active components of TCM on mitochondria.
CategoryChemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferenceRestoratives for invigorating qiGinsenoside compound KRadix ginsengC36H62O8Inhibition of nuclear factor-Bκ, p38, and JNK MAPK pathwaysLu et al. [43]Astragaloside IVRadix AstragaliC41H68O14Regulation of NF-κB/PGC-1α signaling-mediated energy biosynthesisZhang et al. [44]Downregulation of miR-23a and miR-92a-activated PI3K/AKT and MAPK/ERK signaling pathwaysGong et al. [45]Stimulation of fatty acidß-oxidation and improvement of mitochondrial functionDong et al. [46]Astragalus polysaccharidesRadix AstragaliC10H7ClN2O2SInhibition of apoptosisLiu et al. [47]SalidrosideRhodiola crenulataC14H20O7Activation of a mitochondria-associated AMPK/PI3K/Akt/GSK3β pathwayZheng et al. [48]Restoratives for nourishing yinOphiopogonin DRadix OphiopogonisC44H70O16Antioxidant and antiapoptotic effectsHuang et al. [49]EcliptalEclipta alba—Activation of the Wnt-pathway and alteration of AKT signalingYang et al. [50]Restoratives for nourishing yangVelvet antlerCornu cervi pantotrichum—Regulation of the PI3K/Akt signaling pathway and mitochondrial membrane potentialXiao et al. [51]IcariinHerba EpimediiC33H40O15Activation of sirtuin-1/FOXO1 signaling and improvement of mitochondrial membrane homeostasisWu et al. [52]Table 2
Regulatory effects of the active components of traditional Chinese medicine on mitochondria for promoting blood circulation and removing blood stasis.
Chemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferencePanax notoginseng saponinsRadix NotoginsengC47H80O17Attenuation of oxidative stress and cardiomyocyte apoptosisZhang et al. [53]Zhou et al. [54]Notoginsenoside R1Radix NotoginsengC54H92O24Elevation of mitochondrial ATP synthased-subunitsHe et al. [55]Salvianolic acid ARadix Salviae MiltiorrhizaeC26H22O10Promotion of myocardial mitochondria biogenesisZhang et al. [56]Salvianolic acid BRadix Salviae Miltiorrhizae—Improvement of mitochondrial biogenesisPan et al. [57]Tanshinone IIARadix Salviae MiltiorrhizaeC19H18O3Upregulation of 14-3-3η, prevention of mPTP opening, and inhibition of apoptosisZhang et al. [58]DihydronortanshinoneRadix Salviae Miltiorrhizae—Anti-inflammatory effect via the NF-κB, mitochondrial ROS, and MAPK pathwaysWu et al. [59]CurcuminRhizoma Curcumae LongaeC21H20O6Antioxidant and anti-inflammatory activitiesLi et al. [60]Mitochondrial stress and substrate switching inhibitionTable 3
Regulatory effects of the active components of interior warming medicines on mitochondria.
Chemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferenceFlavonoid glycosidesFenugreek—Regulation of glycolipid metabolismLuan et al. [61]Rhizoma ZingiberC17H26O4Improvement of ectopic lipid accumulation, mitochondrial dysfunction, and insulin resistanceLiu et al. [62]Table 4
Regulatory effects of the active components of other traditional Chinese medicines on mitochondria.
Type of TCMMonomer sourceMolecular formulaMechanism of actionReferenceTriptolideTripterygium wilfordiiC21H28O6Regulation of mitochondrial membrane permeabilizationXi et al. [63]OxymatrineRadix Sophorae FlavescentisC16H26N2O2Inhibition of cardiac apoptosis and oxidative stressZhang et al. [64]Epigallocatechin gallateGreen teaC22H18O11Inhibition of deterioration of mitochondrial structure and function by OMA1Nan et al. [65]Cyclovirobuxine DBuxus microphylla SiebC26H46N2OAntioxidant effect and promotion of mitochondrial biogenesisGuo et al. [66]TetrandrineRadix Stephaniae TetrandraeC38H42N2O6Regulation of glycolysis and energy metabolismZhang et al. [67]
## 10.2. Single Herbs of TCM
Single herbs are a type of TCM. Different single herbs have different curative effects, but they may have the same drug action. A single herb can have many different effects. Previous studies have shown that some single-herb medicines can treat coronary heart disease (CHD) by affecting mitochondrial homeostasis. Several common drugs are summarized in Table5.Table 5
Regulatory effects of single-herb traditional Chinese medicines on mitochondria.
Type of TCMSingle herbMechanism of actionReferenceRestoratives for invigorating qiRadix AstragaliPromotion of mitochondrial bioenergeticsHuang et al. [68]Restoratives for invigorating qiRhodiola roseaPromotion of mitochondrial biogenesis and functionsZhuang et al. [69]Antioxidant and anti-inflammatory activitiesZhou et al. [70]Heat clearing Chinese medicinal herbsSilybum marianumMitigation of oxidative stress and attenuation of reactive fibrosis via TGFß1/TßRs/SMAD2/3 signalingVilahur et al. [71]Invigorating the blood and removing blood stasisSalviae Miltiorrhizae Radix et RhizomaActivation of the Nrf2-mediated antioxidant defense systemLi et al. [72]The interior warming Chinese medicinal herbsCortex CinnamomiUpregulation of mitochondrial biogenesisSong et al. [73]
## 10.3. Compound Prescriptions of TCM
Compound prescriptions are the main form of clinical TCM. After determining the treatment based on syndrome differentiation, a compound prescription is formulated by selecting the appropriate drug, determining the dosage, and combining two or more medicines according to the requirements of the basic structure of the prescription. The main objectives of these prescriptions are to enhance drug efficacy, produce synergistic drug effects, control the direction of multifunctional single herbs, expand the scope of treatment, improve drug adaptation to complex conditions, and control the toxic and side effects of drugs.Clinically, most of the drugs used to treat CHD are compound prescriptions. The regulation of CHD by compound prescriptions involve the whole body, including the heart, brain, liver, kidney, lung, large intestine, muscle, and other viscera, and they improve the structure and quantity of mitochondria in each tissue [39, 74]. In addition, compound prescriptions can treat CHD by protecting mitochondrial function, reducing antioxidant stress, improving mitochondrial lipid metabolism, and exerting anti-inflammatory effect. The compound prescriptions commonly used in TCM are listed in Table 6.Table 6
Regulatory effects of compound prescriptions on mitochondria.
Name of compound prescriptionComponents of compound prescriptionMechanism of actionReferenceShengmai formula (SM)Radix ginseng and Radix OphiopogonisProtection of cardiomyocytes against hypoxiaWang et al. [75], Yu et al. [76]Induction of mitophagy and modulation of mitochondrial dynamicsShenxian-Shengmai oral (SXSM)Red Radix ginseng, Herba Epimedii, Fructus Psoraleae (salted), Fructus Lycii, Herba Ephedrae, etc.Antioxidant effect, promotion of SOD activity, elevation of GSH content, and reduction of intracellular ROS levelsZhao et al. [77]YiXin-Shu (YXS)Ginseng, Radix Astragali, Salvia miltiorrhiza, Ophiopogon, Ligusticum, etc.Upregulation of endogenous nuclear receptors (LXRα, PPARα, PPARβ, and ERα) as well as suppression of apoptosis and oxidative stressZhao et al. [78]Shengmai San (SMS)Panax ginseng, Ophiopogon japonicus, and Schisandra chinensisImprovement of mitochondrial lipid metabolism, restoration of mitochondrial structure and function, and promotion of mitochondrial biogenesis via the Sirt1/PGC-1α pathwayTian et al. [79], Lu et al. [80], andLi et al. [81]QiShenYiQi Pills (QSYQ)Radix Astragali, Salvia miltiorrhiza, Panax notoginseng, etc.Regulation of energy metabolism and elevation of mitochondrial content and biogenesis via PGC-1α activationLin et al. [82], Yu et al. [83], and Lin et al. [84]Shexiang Baoxin Pill (SBP)Moschus, Radix Ginseng, Calculus Bovis, Styrax, Cortex Cinnamomi, Venenum Bufonis, and Borneolum SyntheticumAnti-inflammatory and antioxidant effects, improvement of lipid metabolism, protection of mitochondrial function, and upregulation of AMPK and PGC-1a expressionWei et al. [85]Qiang-Xin 1 formulaAstragalus, Poria, Schisandra, Salvia miltiorrhiza, etc.Prevention of sepsis-induced apoptosisXu et al. [86]Tongxinluo capsule (TXL)Radix ginseng, Hirudo, Scorpio, Radix Paeoniae Rubra, etc.Anti-inflammatory effect and improvement of lipid metabolismZhang et al. [74] Ma et al. [87]In summary, mitochondria are semiautonomous organelles that integrate the three basic life activities: material metabolism, energy metabolism, and genetic variation; they are also the place for intracellular respiration and energy conversion and participate in various important physiological and biochemical processes. Overall, TCM affects the processes of mitochondrial energy metabolism, apoptosis, and oxidative stress in multilevels via multitargets, and the same category of drugs has certain commonness and individuality. The mechanisms are summarized in Table7.Table 7
Action mechanisms of TCM on mitochondria.
Action mechanismChemical components of TCMSingle herbCompound prescriptionMitochondrial structureVelvet antler, icariin, tanshinone IIA, triptolide, and epigallocatechin gallate—Shengmai SanMitochondria biosynthesisEcliptal, salvianolic acid A, salvianolic acid B, and cyclovirobuxine DRadix Astragali, Rhodiola rosea, Cortex, CinnamomiQiShenYiQi pillsMitochondrial functionFlavonoid glycosides, 6-gingerol, and epigallocatechin gallateRhodiola roseaShengmai formula, Shengmai San, and Shexiang Baoxin pillAnti-inflammatory effectGinsenoside compound K, astragaloside IV, dihydronortanshinone, and curcuminRhodiola roseaTongxinluo capsule (TXL), Shexiang Baoxin pillInhibit apoptosisAstragalus polysaccharides, ophiopogonin D, and oxymatrine—YiXin-Shu, Qiang-Xin 1 formulaAntioxidationOphiopogonin D, panax notoginseng saponins, oxymatrine, cyclovirobuxine D, and curcuminRhodiola rosea, Silybum marianum, Salviae, Miltiorrhizae Radix et RhizomaShenxian-Shengmai oral, YiXin-Shu, and Shexiang Baoxin pillEnergy metabolismSalidroside, notoginsenoside R1, and tetrandrineRadix Astragali—
## 11. Conclusions and Perspectives
CVD is the leading cause of death in China [2]. CHD is a relatively common type of CVD. At present, CHD has become a major global public health problem; although antithrombosis, anti-ischemia, and lipid-regulating interventional therapies and secondary preventions have been used to improve CHD symptoms and reduce the mortality and HF after percutaneous coronary intervention(PCI), no reflow after revascularization, depression after CHD, CHD complications, and antithrombotic drug resistance still persist as clinical problems that need to be solved. At present, syndrome differentiation via a combination of modern medicine and TCM is the main method for treating CVD in China and abroad [88].Coronary atherosclerosis or vasospasm leads to decreased myocardial blood perfusion and increased ischemic damage of cells. During the ischemic period, hypoxia causes inhibition of mitochondrial ATP synthesis and oxidative phosphorylation, making it difficult for cells to maintain normal ATP content. At the same time, under the condition of ischemia and hypoxia, excessive metabolites, such as lactic acid, pyruvate, phosphate, and other acids, accumulate in the myocardium and produce symptoms such as angina pectoris or chest tiredness. An evidence showed that mitochondrial dysfunction occurs in the early stage of CHD and mitochondrial autophagy occurs in the late stage, which involves the steady-state dynamic balance of mitochondria [89].A growing number of studies showed that mitochondria play an important role in the cardiovascular system. Mitochondria can be used as targets for the treatment of CVDs [90]. Mutations in mtDNA affect CVD, leading to hypertension, atherosclerosis, and cardiomyopathy. However, TCM can regulate the structure and function of mitochondria by increasing electron transport and oxidative phosphorylation of mitochondria, thus regulating mitochondria-mediated apoptosis and reducing mitochondrial ROS to treat CVD.At present, there are multiple forms of TCM used in the treatment of CVD, including its active components, single herbs, and compound prescriptions [3, 42]. One review of 68 randomized controlled trials that included a total of 16171 patients revealed that, compared with blank control or placebo, TCM effectively reduces the severity of angina pectoris and MI; it also lowers blood pressure in patients with hypertension and improves cardiac function in patients with HF [91]. In most studies, the frequency of adverse effects was not higher for TCM than for controls or Western medicine [91]. However, the methodological quality of the majority of included studies was low; further studies using strictly designed randomized controlled trials are necessary to provide strong evidence [92]. Owing to the complexity of CVD pathogenesis, the action mechanism of TCM in the treatment of CVD is difficult to clarify. Moreover, mitochondria are the intracellular targets of many drugs, and there are extensive and complex interactions between mitochondria and related drugs [90].TCM has the advantages of multitarget and multipathways [42, 93]. A large number of clinical experiences and studies have shown that TCM plays an important role in the prevention, treatment, and prognosis of CVD [93]. Previous studies by our team have shown that circRNAs are closely related to the pathological process of acute coronary syndrome via a mechanism that may be related to the up- or downregulation of circRNAs and miRNAs and the coexpression of circRNA-miRNA [94]. In addition, through literature review, we consider that the circRNA-miRNA-mRNA network may be a new regulatory mechanism for TCM to effectively treat CVD [93]. Besides, TCM has been shown to improve the morphology and structure of mitochondria and participate in a series of metabolic processes, including regulation of energy metabolism, inhibition of apoptosis, and reduction of oxygen free radical production in mitochondria. There is a certain correlation between the intracellular targets of TCM and mitochondria.Furthermore, we should treat diseases according to syndrome differentiation and reasonably choose TCM based on the basic theory of TCM. Integrating TCM with Western medicine, an unprecedented task in today’s world, would provide a new medical model with unique advantages that can play an important role in the treatment of diseases [95]. Some experiments have confirmed the efficacy of combining TCM with Western medicine for the treatment of angina pectoris [96], and evidence for using TCM for the treatment of other CVDs is also increasing [3]. The combination of TCM and Western medicine is an attractive avenue for therapeutic intervention in CVD, and it may be the best scheme for CVD treatment. Thus, developing a strategy for integrating TCM with Western medicine will greatly contribute to human health care [95].
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*Source: 2902136-2020-10-08.xml* | 2902136-2020-10-08_2902136-2020-10-08.md | 43,697 | Correlation between Mitochondrial Dysfunction, Cardiovascular Diseases, and Traditional Chinese Medicine | Li Zhu; Zhigang Chen; Keli Han; Yilin Zhao; Yan Li; Dongxu Li; Xiulong Wang; Xuefang Li; Siyu Sun; Fei Lin; Guoan Zhao | Evidence-Based Complementary and Alternative Medicine
(2020) | Medical & Health Sciences | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2020/2902136 | 2902136-2020-10-08.xml | ---
## Abstract
Cardiovascular disease (CVD) is the number one threat that seriously endangers human health. However, the mechanism of their occurrence is not completely clear. Increasing studies showed that mitochondrial dysfunction is closely related to CVD. Possible causes of mitochondrial dysfunction include oxidative stress, Ca2+ disorder, mitochondrial DNA mutations, and reduction of mitochondrial biosynthesis, all of which are closely related to the development of CVD. At present, traditional Chinese medicine (TCM) is widely used in the treatment of CVD. TCM has the therapeutic characteristics of multitargets and multipathways. Studies have shown that TCM can treat CVD by protecting mitochondrial function. Via systematic literature review, the results show that the specific mechanisms include antioxidant stress, regulation of calcium homeostasis, antiapoptosis, and regulation of mitochondrial biosynthesis. This article describes the relationship between mitochondrial dysfunction and CVD, summarizes the TCM commonly used for the treatment of CVD in recent years, and focuses on the regulatory effect of TCM on mitochondrial function.
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## Body
## 1. Introduction
With the continuous progress in the treatment of infectious diseases and the extension of human life span, the battlefield between humans and diseases has shifted to chronic noncommunicable diseases. Among them, cardiovascular disease (CVD) has become the leading cause of death in China and worldwide as its incidence continues to increase, and it poses a serious threat to the safety and quality of life of patients [1, 2]. Atherosclerosis, hypertension, myocardial ischemia-reperfusion injury, and heart failure are common CVDs or pathological processes. However, the mechanism of their occurrence is not completely clear. An increasing number of studies has shown that mitochondrial dysfunction is closely related to CVD. The mechanisms mainly include oxidative stress disorder, calcium disorder, reduction of mitochondrial biosynthesis, transition of mitochondrial permeability, and accumulation of mitochondrial DNA mutation. At present, TCM, which has the characteristics of multitargets and multipathways, is widely used in the treatment of CVD [3]. Therefore, in this paper, we discuss the relationship between mitochondrial dysfunction and CVD, as well as the therapeutic mechanism of TCM in the treatment of CVD with respect to mitochondrial function.
## 2. Functional Properties of Mitochondria
Mitochondria are semiautonomous organelles with a unique genetic system that provide the chemical energy required for biosynthesis, respiration, secretion, and mechanical movement in organisms; they are also important organelles that generate intracellular free radicals and regulate apoptosis [4–6]. Mitochondria are known as “capacity factories,” “apoptosis switches,” and “enzyme bags.” They are also called “cellular energy-processing factories” because they oxidize three major nutrients to provide adenosine triphosphate (ATP), which is required for life activities [4]. In addition to being energy producers, mitochondria are also the main site of reactive oxygen species [6] (ROS) production. Furthermore, mitochondria also play an important role in the regulation of intracellular calcium homeostasis, calcium-sensitive enzyme activity, and signal transduction [7]. In conclusion, mitochondria are central mediators of energy production, signal transduction, oxidative stress, Ca2+ homeostasis, and apoptosis regulation. Therefore, the normal function of mitochondria is of great importance in life activities.
## 3. Mitochondria and Cardiomyocytes
Cardiomyocytes are highly dependent on aerobic oxidation to supply energy. They contain a considerable amount of mitochondria, up to 20–30% of cell capacity, which provide more than 90% of energy to the heart muscle [8, 9]. The sources of myocardial energy include fatty acids, glucose, and other carbohydrates. These substrates are metabolized in mitochondria, providing energy for cardiomyocytes through oxidative phosphorylation. In fact, 60% to 90% of the energy needed by myocardium originates from the ATP produced by aerobic oxidation of fatty acids. Only 10% to 40% of the energy is generated by glucose glycolysis and lactic acid oxidation. In addition, the production and utilization of ketone body, ornithine, heme, cardiolipin, and ubiquinone are all related to mitochondria [10].As a vital functional organelle in myocardial cells, the function of mitochondria is key to elucidating the physiological and pathological changes in CVD, and mitochondrial homeostasis is the core element for maintaining myocardial metabolism, function, and structure [11].
## 4. Mitochondrial Homeostasis
Mitochondrial homeostasis is the steady-state balance between mitochondrial biogenesis and degradation. It involves many aspects such as mitochondrial division and fusion [6, 12], mitochondrial crest remodeling [6, 8], mitochondrial biosynthesis [13, 14], mitochondrial autophagy [15, 16], and mitochondrial oxidative stress [9, 17]. Mitochondrial homeostasis refers to the healthy and stable state of mitochondrial content and metabolism for ensuring the stability of cell energy supply and material metabolism. To maintain the integrity of the mitochondrial structure, mitochondrial division and fusion and mitochondrial crest morphology are altered along with changes in intracellular energy supply [12]. Mitochondrial health is maintained through biosynthesis and autophagy degradation to respond to different energy requirements of cells [10, 15]. In addition, ROS in mitochondria can be used as signal molecules to activate redox signal molecules through redox reaction, thus participating in the regulation of intracellular signal transduction [18]. Disruption of mitochondrial homeostasis may cause imbalance of mitochondrial motility, lysis of mitochondrial cristae, disruption of mitochondrial biosynthesis, abnormal degradation of mitochondrial autophagy, and oxidative stress in mitochondria. Therefore, the stable state of mitochondrial structure and function has very important physiological significance for the growth, metabolism, and heredity of organisms [19].
## 5. Mitochondria Dysfunction and Cardiovascular Diseases
Mitochondria are the energy factories of cells, and their main function is to consume oxygen and metabolize three major nutrients (sugars, lipids, and amino acids) to produce CO2, water, and energy (ATP) [4]. Cells often need to manage their energy expenditure based on the availability of nutrients and their ability to produce ATP [10]. Disrupted mitochondrial homeostasis will lead to abnormal metabolism of these common substances in the body. Higher organisms need to consume larger amount of energy, and the ATP produced by anaerobic glycolysis is only approximately 1/16 of that produced by aerobic oxidation.Mitochondria are exposed to various physiological or stress signals, and they produce different signal molecules that affect oxidative stress, apoptosis, autophagy, and inflammation, which are closely related to the occurrence of CVD [11, 16, 20]. The pathophysiological processes of abnormal effects of mitochondria on CVD are reflected in the following aspects: (1) because cardiomyocytes rely on fatty acid-driven oxidative phosphorylation to produce ATP, a decline in the biological efficiency of the mitochondrial network may directly harm the contractility of cardiomyocytes; (2) because Ca2+ flow is the core of overall cardiac activity, incapability of the mitochondrial network to regulate Ca2+ homeostasis can alter cardiac function; (3) physiological inflammatory homeostasis has a certain protective effect not only on cardiac function but also on vascular filling, but the accumulation of damaged mitochondria in the cytoplasm of cardiomyocytes or endothelial cells can cause pathogenic inflammation; and (4) the integrity of the cardiovascular system is essential for cardiac contractile and circulatory functions. Severe mitochondrial dysfunction and accumulation of damaged mitochondria initiate a series of cell death that eventually leads to pathological damage.
## 6. Mitochondrial Dysfunction and Atherosclerosis
Atherosclerotic (AS) is the main cause of death due to cardiovascular disease. In patients with mitochondrial dysfunction, decreased activity of progressive respiratory chain enzymes, excessive production of ROS, and cumulative mitochondrial DNA (mtDNA) damage or mutations are closely related to the occurrence and development of atherosclerosis [21, 22]. Studies have shown that oxidized low-density lipoprotein (ox-LDL) plays an important role in the occurrence and development of atherosclerosis; ROS produced by mitochondria and its modified ox-LDL are involved in all pathological processes of atherosclerosis [23]. Ox-LDL can slow down the electron transport of mitochondrial respiratory chain by inhibiting the activity of mitochondrial respiratory enzymes and increasing the formation of ROS, thus forming a vicious circle and promoting endothelial injury and atherosclerosis [23]. It was found that when the activity of Mn-SOD (SOD2) decreased, mtDNA damage increased in apoE−/− rats, which preceded the formation of atherosclerotic plaques. As oxidative stress in mitochondria increased, atherosclerotic lesions were significantly aggravated [24]. In addition, studies in apoE−/−-SOD2+/− mice have shown that an increase in mitochondrial ROS not only promoted the formation of atherosclerotic plaques but also increased the susceptibility of the body to atherosclerotic risk factors [25]. Moreover, mtDNA damage caused by DNA repair dysfunction can directly accelerate atherosclerosis in apoE−/− rats and promote diabetic atherosclerotic complications. Furthermore, transient opening of mitochondrial permeability transition pore (mPTP) can depolarize mitochondrial membrane potential, whereas long-term opening of mPTP leads to matrix swelling, rupture of mitochondrial outer membrane, and apoptosis. Both of these changes can promote the occurrence and development of atherosclerosis [21, 22]. In an experiment using wild-type mice, it was found that aging led to increases in IL-6 level and mitochondrial dysfunction. Hyperlipidemia further decreased the mitochondrial function and increased the level of Parkin in the aorta of old mice (16 months of age). Importantly, oral spermidine can enhance the mitotic function of aged hyperlipidemic mice, prevent elevation of aortic IL-6 and Parkin levels, reduce mitochondrial dysfunction, and reduce atherosclerosis formation. Overall, new treatments that improve vascular mitochondrial bioenergetics or reduce inflammation before hyperlipidemia may reduce age-related atherosclerosis [26]. Overall, oxidative stress, inflammatory reaction, and mitochondrial dysfunction play a key role in the formation of atherosclerosis. Mitochondria-targeted antioxidant and anti-inflammatory therapies may have great prospects for the treatment of atherosclerosis [27].
## 7. Mitochondrial Dysfunction and Hypertension
Hypertension is a common CVD in modern society. Many studies have shown that mitochondrial dysfunction is closely related to hypertension [28]. The superoxide anions produced by mitochondria can oxidize the NO released by endothelial cells, decrease the endothelium-dependent vasodilation function, increase vascular force, and increase blood pressure. Uncoupling of mitochondrial oxidative phosphorylation caused by UCP2 gene polymorphism or altered expression is also associated with high blood pressure [29]. In addition, the lack of mitochondrial productivity, calcium overload, and mitochondrial DNA mutations are all involved in the pathological process of arterial hypertension and hypertensive heart disease. Angiotensin II (Ang II) plays an important role in the development of hypertension. Ang II can also inactivate the NO produced by endothelial cell by stimulating the production of mitochondrial ROS, resulting in vascular endothelial dysfunction [30]. Mitochondrial dysfunction is also related to dysfunction of blood pressure regulation center [31]. Related research has confirmed that mitochondrial dysfunction caused by maternally inherited mitochondrial transfer ribonucleic acid (tRNA) mutations is associated with the development of essential hypertension [32]. Otherwise, under the conditions of inflammation, Ang II stimulation, and metabolic syndrome, disturbances in mitochondrial biogenesis and mitochondrial bioenergetics in the brain will lead to the accumulation of ROS, which plays an active role in the pathophysiology of ROS-related neurogenic hypertension [33]. Overall, increased ROS production, decreased ATP production, and calcium overload play an important role in the occurrence and development of hypertension. Moreover, mitochondrial gene polymorphism and mitochondrial tRNA gene mutations are also associated with hypertension.
## 8. Mitochondrial Dysfunction and Myocardial Ischemia-Reperfusion Injury
Myocardial ischemia-reperfusion injury (IR injury) is common in reperfusion therapy after acute myocardial infarction, manifesting as arrhythmia, reduced cardiac systolic function, and other phenomena. Mitochondrial energy metabolism disorder is an important factor causing myocardial IR injury [34]. The main mechanisms include reduced mitochondrial ATP production and excessive ROS production, causing oxidative stress, Ca2+ overload, and sustained mPTP opening [18, 35]. Excessive ROS production during ischemic myocardial reperfusion is the main cause of myocardial IR injury, and mitochondria are an important source of ROS. On the one hand, increased ROS can damage the mitochondrial membrane system, which affects the mitochondrial membrane potential and disrupts mitochondrial ATP synthesis. On the other hand, mitochondria produce excessive ROS, which causes peroxidation of proteins and lipids and damage to the mitochondrial membrane, further decreasing the activity of the electron transport chain enzymes, which in turn form a vicious circle that eventually leads to cardiomyocyte apoptosis and necrosis [36]. In addition to excessive ROS, myocardial ischemia-reperfusion-induced cell Ca2+ overload is an important cause of myocardial IR injury [18, 35]. Persistent opening of mitochondrial mPTP with high permeability also plays an important role in IR injury. This causes the entrance of numerous small molecules to mitochondria, resulting in the swelling of mitochondria, rupture of the outer membrane, collapse of membrane potential, and release of various proapoptotic factors to induce cell apoptosis or death [35]. Taken together, improving mitochondrial function, reducing oxidative stress caused by excessive production of mitochondrial ROS, preventing intracellular calcium overload, and preventing the opening of mitochondrial mPTP are effective measures for the prevention and treatment of IR injury.
## 9. Mitochondrial Dysfunction and Heart Failure
Heart failure (HF) is the final stage of the development of various CVDs, such as myocardial infarction, hypertension, and cardiomyopathy. The relationship between mitochondrial dysfunction and HF is mainly reflected as follows: the disturbance of mitochondrial energy metabolism plays an important role in the occurrence and development of HF. During HF, mitochondrial ATP synthesis decreased, and ROS production increased, whereas the disturbance of energy metabolism in myocardial mitochondria aggravated the disruption of cardiac mechanical function and deterioration of cardiac function. ROS modified myofibrillar protein in the myocardium via oxidation, resulting in a progressive decrease in cardiac contractile function and irreversible cardiac injury [37, 38]. Studies in an experimental HF model have shown that the expression of myocardial mitochondrial biosynthesis factor is downregulated, whereas mtDNA content is reduced, which not only results in reduced mitochondrial biosynthesis but also causes mitochondrial oxidative phosphorylation and reduces the ability of mitochondria to oxidize fatty acids, which leads to deficiencies in myocardial energy production and HF development [39]. In patients with congenital heart disease, damage in mtDNA replication leads to the loss of right ventricular mtDNA, resulting in the progression of heart hypertrophy to HF [40, 41]. Therefore, to prevent mitochondrial damage and maintain the integrity of its function, reducing oxidative stress will be an important strategy in the treatment of HF [41].In summary, the maintenance of mitochondrial homeostasis is very important in life activities, and mitochondrial dysfunction is closely related to the occurrence and development of CVD. TCM is widely applied in the clinical treatment of CVD, and mitochondria are the intracellular targets of many kinds of drugs. Thus, we propose that TCM can treat CVD by affecting mitochondrial homeostasis.
## 10. Protective Effect of TCM on Myocardial Mitochondria
Mitochondria play a significant role in the regulation of physiological function and pathological process in the cardiovascular system [11]. TCM [42], including the chemical components, single herbs, and compound medicines, can treat CVD by regulating the function of mitochondria, which will be described below.
### 10.1. Chemical Components of TCM
The chemical components of TCM are the substance bases of its pharmacology. The composition of TCM is extremely complex, as each TCM contains many kinds of chemical components. Components that have biological activity and play a role in the prevention and treatment of diseases are known as effective components. Modern studies have shown that the effective components of TCM can protect cardiomyocyte mitochondria in many ways. Several common drugs are summarized in Tables1–4.Table 1
Regulatory effects of active components of TCM on mitochondria.
CategoryChemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferenceRestoratives for invigorating qiGinsenoside compound KRadix ginsengC36H62O8Inhibition of nuclear factor-Bκ, p38, and JNK MAPK pathwaysLu et al. [43]Astragaloside IVRadix AstragaliC41H68O14Regulation of NF-κB/PGC-1α signaling-mediated energy biosynthesisZhang et al. [44]Downregulation of miR-23a and miR-92a-activated PI3K/AKT and MAPK/ERK signaling pathwaysGong et al. [45]Stimulation of fatty acidß-oxidation and improvement of mitochondrial functionDong et al. [46]Astragalus polysaccharidesRadix AstragaliC10H7ClN2O2SInhibition of apoptosisLiu et al. [47]SalidrosideRhodiola crenulataC14H20O7Activation of a mitochondria-associated AMPK/PI3K/Akt/GSK3β pathwayZheng et al. [48]Restoratives for nourishing yinOphiopogonin DRadix OphiopogonisC44H70O16Antioxidant and antiapoptotic effectsHuang et al. [49]EcliptalEclipta alba—Activation of the Wnt-pathway and alteration of AKT signalingYang et al. [50]Restoratives for nourishing yangVelvet antlerCornu cervi pantotrichum—Regulation of the PI3K/Akt signaling pathway and mitochondrial membrane potentialXiao et al. [51]IcariinHerba EpimediiC33H40O15Activation of sirtuin-1/FOXO1 signaling and improvement of mitochondrial membrane homeostasisWu et al. [52]Table 2
Regulatory effects of the active components of traditional Chinese medicine on mitochondria for promoting blood circulation and removing blood stasis.
Chemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferencePanax notoginseng saponinsRadix NotoginsengC47H80O17Attenuation of oxidative stress and cardiomyocyte apoptosisZhang et al. [53]Zhou et al. [54]Notoginsenoside R1Radix NotoginsengC54H92O24Elevation of mitochondrial ATP synthased-subunitsHe et al. [55]Salvianolic acid ARadix Salviae MiltiorrhizaeC26H22O10Promotion of myocardial mitochondria biogenesisZhang et al. [56]Salvianolic acid BRadix Salviae Miltiorrhizae—Improvement of mitochondrial biogenesisPan et al. [57]Tanshinone IIARadix Salviae MiltiorrhizaeC19H18O3Upregulation of 14-3-3η, prevention of mPTP opening, and inhibition of apoptosisZhang et al. [58]DihydronortanshinoneRadix Salviae Miltiorrhizae—Anti-inflammatory effect via the NF-κB, mitochondrial ROS, and MAPK pathwaysWu et al. [59]CurcuminRhizoma Curcumae LongaeC21H20O6Antioxidant and anti-inflammatory activitiesLi et al. [60]Mitochondrial stress and substrate switching inhibitionTable 3
Regulatory effects of the active components of interior warming medicines on mitochondria.
Chemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferenceFlavonoid glycosidesFenugreek—Regulation of glycolipid metabolismLuan et al. [61]Rhizoma ZingiberC17H26O4Improvement of ectopic lipid accumulation, mitochondrial dysfunction, and insulin resistanceLiu et al. [62]Table 4
Regulatory effects of the active components of other traditional Chinese medicines on mitochondria.
Type of TCMMonomer sourceMolecular formulaMechanism of actionReferenceTriptolideTripterygium wilfordiiC21H28O6Regulation of mitochondrial membrane permeabilizationXi et al. [63]OxymatrineRadix Sophorae FlavescentisC16H26N2O2Inhibition of cardiac apoptosis and oxidative stressZhang et al. [64]Epigallocatechin gallateGreen teaC22H18O11Inhibition of deterioration of mitochondrial structure and function by OMA1Nan et al. [65]Cyclovirobuxine DBuxus microphylla SiebC26H46N2OAntioxidant effect and promotion of mitochondrial biogenesisGuo et al. [66]TetrandrineRadix Stephaniae TetrandraeC38H42N2O6Regulation of glycolysis and energy metabolismZhang et al. [67]
### 10.2. Single Herbs of TCM
Single herbs are a type of TCM. Different single herbs have different curative effects, but they may have the same drug action. A single herb can have many different effects. Previous studies have shown that some single-herb medicines can treat coronary heart disease (CHD) by affecting mitochondrial homeostasis. Several common drugs are summarized in Table5.Table 5
Regulatory effects of single-herb traditional Chinese medicines on mitochondria.
Type of TCMSingle herbMechanism of actionReferenceRestoratives for invigorating qiRadix AstragaliPromotion of mitochondrial bioenergeticsHuang et al. [68]Restoratives for invigorating qiRhodiola roseaPromotion of mitochondrial biogenesis and functionsZhuang et al. [69]Antioxidant and anti-inflammatory activitiesZhou et al. [70]Heat clearing Chinese medicinal herbsSilybum marianumMitigation of oxidative stress and attenuation of reactive fibrosis via TGFß1/TßRs/SMAD2/3 signalingVilahur et al. [71]Invigorating the blood and removing blood stasisSalviae Miltiorrhizae Radix et RhizomaActivation of the Nrf2-mediated antioxidant defense systemLi et al. [72]The interior warming Chinese medicinal herbsCortex CinnamomiUpregulation of mitochondrial biogenesisSong et al. [73]
### 10.3. Compound Prescriptions of TCM
Compound prescriptions are the main form of clinical TCM. After determining the treatment based on syndrome differentiation, a compound prescription is formulated by selecting the appropriate drug, determining the dosage, and combining two or more medicines according to the requirements of the basic structure of the prescription. The main objectives of these prescriptions are to enhance drug efficacy, produce synergistic drug effects, control the direction of multifunctional single herbs, expand the scope of treatment, improve drug adaptation to complex conditions, and control the toxic and side effects of drugs.Clinically, most of the drugs used to treat CHD are compound prescriptions. The regulation of CHD by compound prescriptions involve the whole body, including the heart, brain, liver, kidney, lung, large intestine, muscle, and other viscera, and they improve the structure and quantity of mitochondria in each tissue [39, 74]. In addition, compound prescriptions can treat CHD by protecting mitochondrial function, reducing antioxidant stress, improving mitochondrial lipid metabolism, and exerting anti-inflammatory effect. The compound prescriptions commonly used in TCM are listed in Table 6.Table 6
Regulatory effects of compound prescriptions on mitochondria.
Name of compound prescriptionComponents of compound prescriptionMechanism of actionReferenceShengmai formula (SM)Radix ginseng and Radix OphiopogonisProtection of cardiomyocytes against hypoxiaWang et al. [75], Yu et al. [76]Induction of mitophagy and modulation of mitochondrial dynamicsShenxian-Shengmai oral (SXSM)Red Radix ginseng, Herba Epimedii, Fructus Psoraleae (salted), Fructus Lycii, Herba Ephedrae, etc.Antioxidant effect, promotion of SOD activity, elevation of GSH content, and reduction of intracellular ROS levelsZhao et al. [77]YiXin-Shu (YXS)Ginseng, Radix Astragali, Salvia miltiorrhiza, Ophiopogon, Ligusticum, etc.Upregulation of endogenous nuclear receptors (LXRα, PPARα, PPARβ, and ERα) as well as suppression of apoptosis and oxidative stressZhao et al. [78]Shengmai San (SMS)Panax ginseng, Ophiopogon japonicus, and Schisandra chinensisImprovement of mitochondrial lipid metabolism, restoration of mitochondrial structure and function, and promotion of mitochondrial biogenesis via the Sirt1/PGC-1α pathwayTian et al. [79], Lu et al. [80], andLi et al. [81]QiShenYiQi Pills (QSYQ)Radix Astragali, Salvia miltiorrhiza, Panax notoginseng, etc.Regulation of energy metabolism and elevation of mitochondrial content and biogenesis via PGC-1α activationLin et al. [82], Yu et al. [83], and Lin et al. [84]Shexiang Baoxin Pill (SBP)Moschus, Radix Ginseng, Calculus Bovis, Styrax, Cortex Cinnamomi, Venenum Bufonis, and Borneolum SyntheticumAnti-inflammatory and antioxidant effects, improvement of lipid metabolism, protection of mitochondrial function, and upregulation of AMPK and PGC-1a expressionWei et al. [85]Qiang-Xin 1 formulaAstragalus, Poria, Schisandra, Salvia miltiorrhiza, etc.Prevention of sepsis-induced apoptosisXu et al. [86]Tongxinluo capsule (TXL)Radix ginseng, Hirudo, Scorpio, Radix Paeoniae Rubra, etc.Anti-inflammatory effect and improvement of lipid metabolismZhang et al. [74] Ma et al. [87]In summary, mitochondria are semiautonomous organelles that integrate the three basic life activities: material metabolism, energy metabolism, and genetic variation; they are also the place for intracellular respiration and energy conversion and participate in various important physiological and biochemical processes. Overall, TCM affects the processes of mitochondrial energy metabolism, apoptosis, and oxidative stress in multilevels via multitargets, and the same category of drugs has certain commonness and individuality. The mechanisms are summarized in Table7.Table 7
Action mechanisms of TCM on mitochondria.
Action mechanismChemical components of TCMSingle herbCompound prescriptionMitochondrial structureVelvet antler, icariin, tanshinone IIA, triptolide, and epigallocatechin gallate—Shengmai SanMitochondria biosynthesisEcliptal, salvianolic acid A, salvianolic acid B, and cyclovirobuxine DRadix Astragali, Rhodiola rosea, Cortex, CinnamomiQiShenYiQi pillsMitochondrial functionFlavonoid glycosides, 6-gingerol, and epigallocatechin gallateRhodiola roseaShengmai formula, Shengmai San, and Shexiang Baoxin pillAnti-inflammatory effectGinsenoside compound K, astragaloside IV, dihydronortanshinone, and curcuminRhodiola roseaTongxinluo capsule (TXL), Shexiang Baoxin pillInhibit apoptosisAstragalus polysaccharides, ophiopogonin D, and oxymatrine—YiXin-Shu, Qiang-Xin 1 formulaAntioxidationOphiopogonin D, panax notoginseng saponins, oxymatrine, cyclovirobuxine D, and curcuminRhodiola rosea, Silybum marianum, Salviae, Miltiorrhizae Radix et RhizomaShenxian-Shengmai oral, YiXin-Shu, and Shexiang Baoxin pillEnergy metabolismSalidroside, notoginsenoside R1, and tetrandrineRadix Astragali—
## 10.1. Chemical Components of TCM
The chemical components of TCM are the substance bases of its pharmacology. The composition of TCM is extremely complex, as each TCM contains many kinds of chemical components. Components that have biological activity and play a role in the prevention and treatment of diseases are known as effective components. Modern studies have shown that the effective components of TCM can protect cardiomyocyte mitochondria in many ways. Several common drugs are summarized in Tables1–4.Table 1
Regulatory effects of active components of TCM on mitochondria.
CategoryChemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferenceRestoratives for invigorating qiGinsenoside compound KRadix ginsengC36H62O8Inhibition of nuclear factor-Bκ, p38, and JNK MAPK pathwaysLu et al. [43]Astragaloside IVRadix AstragaliC41H68O14Regulation of NF-κB/PGC-1α signaling-mediated energy biosynthesisZhang et al. [44]Downregulation of miR-23a and miR-92a-activated PI3K/AKT and MAPK/ERK signaling pathwaysGong et al. [45]Stimulation of fatty acidß-oxidation and improvement of mitochondrial functionDong et al. [46]Astragalus polysaccharidesRadix AstragaliC10H7ClN2O2SInhibition of apoptosisLiu et al. [47]SalidrosideRhodiola crenulataC14H20O7Activation of a mitochondria-associated AMPK/PI3K/Akt/GSK3β pathwayZheng et al. [48]Restoratives for nourishing yinOphiopogonin DRadix OphiopogonisC44H70O16Antioxidant and antiapoptotic effectsHuang et al. [49]EcliptalEclipta alba—Activation of the Wnt-pathway and alteration of AKT signalingYang et al. [50]Restoratives for nourishing yangVelvet antlerCornu cervi pantotrichum—Regulation of the PI3K/Akt signaling pathway and mitochondrial membrane potentialXiao et al. [51]IcariinHerba EpimediiC33H40O15Activation of sirtuin-1/FOXO1 signaling and improvement of mitochondrial membrane homeostasisWu et al. [52]Table 2
Regulatory effects of the active components of traditional Chinese medicine on mitochondria for promoting blood circulation and removing blood stasis.
Chemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferencePanax notoginseng saponinsRadix NotoginsengC47H80O17Attenuation of oxidative stress and cardiomyocyte apoptosisZhang et al. [53]Zhou et al. [54]Notoginsenoside R1Radix NotoginsengC54H92O24Elevation of mitochondrial ATP synthased-subunitsHe et al. [55]Salvianolic acid ARadix Salviae MiltiorrhizaeC26H22O10Promotion of myocardial mitochondria biogenesisZhang et al. [56]Salvianolic acid BRadix Salviae Miltiorrhizae—Improvement of mitochondrial biogenesisPan et al. [57]Tanshinone IIARadix Salviae MiltiorrhizaeC19H18O3Upregulation of 14-3-3η, prevention of mPTP opening, and inhibition of apoptosisZhang et al. [58]DihydronortanshinoneRadix Salviae Miltiorrhizae—Anti-inflammatory effect via the NF-κB, mitochondrial ROS, and MAPK pathwaysWu et al. [59]CurcuminRhizoma Curcumae LongaeC21H20O6Antioxidant and anti-inflammatory activitiesLi et al. [60]Mitochondrial stress and substrate switching inhibitionTable 3
Regulatory effects of the active components of interior warming medicines on mitochondria.
Chemical components of TCMMonomer sourceMolecular formulaMechanism of actionReferenceFlavonoid glycosidesFenugreek—Regulation of glycolipid metabolismLuan et al. [61]Rhizoma ZingiberC17H26O4Improvement of ectopic lipid accumulation, mitochondrial dysfunction, and insulin resistanceLiu et al. [62]Table 4
Regulatory effects of the active components of other traditional Chinese medicines on mitochondria.
Type of TCMMonomer sourceMolecular formulaMechanism of actionReferenceTriptolideTripterygium wilfordiiC21H28O6Regulation of mitochondrial membrane permeabilizationXi et al. [63]OxymatrineRadix Sophorae FlavescentisC16H26N2O2Inhibition of cardiac apoptosis and oxidative stressZhang et al. [64]Epigallocatechin gallateGreen teaC22H18O11Inhibition of deterioration of mitochondrial structure and function by OMA1Nan et al. [65]Cyclovirobuxine DBuxus microphylla SiebC26H46N2OAntioxidant effect and promotion of mitochondrial biogenesisGuo et al. [66]TetrandrineRadix Stephaniae TetrandraeC38H42N2O6Regulation of glycolysis and energy metabolismZhang et al. [67]
## 10.2. Single Herbs of TCM
Single herbs are a type of TCM. Different single herbs have different curative effects, but they may have the same drug action. A single herb can have many different effects. Previous studies have shown that some single-herb medicines can treat coronary heart disease (CHD) by affecting mitochondrial homeostasis. Several common drugs are summarized in Table5.Table 5
Regulatory effects of single-herb traditional Chinese medicines on mitochondria.
Type of TCMSingle herbMechanism of actionReferenceRestoratives for invigorating qiRadix AstragaliPromotion of mitochondrial bioenergeticsHuang et al. [68]Restoratives for invigorating qiRhodiola roseaPromotion of mitochondrial biogenesis and functionsZhuang et al. [69]Antioxidant and anti-inflammatory activitiesZhou et al. [70]Heat clearing Chinese medicinal herbsSilybum marianumMitigation of oxidative stress and attenuation of reactive fibrosis via TGFß1/TßRs/SMAD2/3 signalingVilahur et al. [71]Invigorating the blood and removing blood stasisSalviae Miltiorrhizae Radix et RhizomaActivation of the Nrf2-mediated antioxidant defense systemLi et al. [72]The interior warming Chinese medicinal herbsCortex CinnamomiUpregulation of mitochondrial biogenesisSong et al. [73]
## 10.3. Compound Prescriptions of TCM
Compound prescriptions are the main form of clinical TCM. After determining the treatment based on syndrome differentiation, a compound prescription is formulated by selecting the appropriate drug, determining the dosage, and combining two or more medicines according to the requirements of the basic structure of the prescription. The main objectives of these prescriptions are to enhance drug efficacy, produce synergistic drug effects, control the direction of multifunctional single herbs, expand the scope of treatment, improve drug adaptation to complex conditions, and control the toxic and side effects of drugs.Clinically, most of the drugs used to treat CHD are compound prescriptions. The regulation of CHD by compound prescriptions involve the whole body, including the heart, brain, liver, kidney, lung, large intestine, muscle, and other viscera, and they improve the structure and quantity of mitochondria in each tissue [39, 74]. In addition, compound prescriptions can treat CHD by protecting mitochondrial function, reducing antioxidant stress, improving mitochondrial lipid metabolism, and exerting anti-inflammatory effect. The compound prescriptions commonly used in TCM are listed in Table 6.Table 6
Regulatory effects of compound prescriptions on mitochondria.
Name of compound prescriptionComponents of compound prescriptionMechanism of actionReferenceShengmai formula (SM)Radix ginseng and Radix OphiopogonisProtection of cardiomyocytes against hypoxiaWang et al. [75], Yu et al. [76]Induction of mitophagy and modulation of mitochondrial dynamicsShenxian-Shengmai oral (SXSM)Red Radix ginseng, Herba Epimedii, Fructus Psoraleae (salted), Fructus Lycii, Herba Ephedrae, etc.Antioxidant effect, promotion of SOD activity, elevation of GSH content, and reduction of intracellular ROS levelsZhao et al. [77]YiXin-Shu (YXS)Ginseng, Radix Astragali, Salvia miltiorrhiza, Ophiopogon, Ligusticum, etc.Upregulation of endogenous nuclear receptors (LXRα, PPARα, PPARβ, and ERα) as well as suppression of apoptosis and oxidative stressZhao et al. [78]Shengmai San (SMS)Panax ginseng, Ophiopogon japonicus, and Schisandra chinensisImprovement of mitochondrial lipid metabolism, restoration of mitochondrial structure and function, and promotion of mitochondrial biogenesis via the Sirt1/PGC-1α pathwayTian et al. [79], Lu et al. [80], andLi et al. [81]QiShenYiQi Pills (QSYQ)Radix Astragali, Salvia miltiorrhiza, Panax notoginseng, etc.Regulation of energy metabolism and elevation of mitochondrial content and biogenesis via PGC-1α activationLin et al. [82], Yu et al. [83], and Lin et al. [84]Shexiang Baoxin Pill (SBP)Moschus, Radix Ginseng, Calculus Bovis, Styrax, Cortex Cinnamomi, Venenum Bufonis, and Borneolum SyntheticumAnti-inflammatory and antioxidant effects, improvement of lipid metabolism, protection of mitochondrial function, and upregulation of AMPK and PGC-1a expressionWei et al. [85]Qiang-Xin 1 formulaAstragalus, Poria, Schisandra, Salvia miltiorrhiza, etc.Prevention of sepsis-induced apoptosisXu et al. [86]Tongxinluo capsule (TXL)Radix ginseng, Hirudo, Scorpio, Radix Paeoniae Rubra, etc.Anti-inflammatory effect and improvement of lipid metabolismZhang et al. [74] Ma et al. [87]In summary, mitochondria are semiautonomous organelles that integrate the three basic life activities: material metabolism, energy metabolism, and genetic variation; they are also the place for intracellular respiration and energy conversion and participate in various important physiological and biochemical processes. Overall, TCM affects the processes of mitochondrial energy metabolism, apoptosis, and oxidative stress in multilevels via multitargets, and the same category of drugs has certain commonness and individuality. The mechanisms are summarized in Table7.Table 7
Action mechanisms of TCM on mitochondria.
Action mechanismChemical components of TCMSingle herbCompound prescriptionMitochondrial structureVelvet antler, icariin, tanshinone IIA, triptolide, and epigallocatechin gallate—Shengmai SanMitochondria biosynthesisEcliptal, salvianolic acid A, salvianolic acid B, and cyclovirobuxine DRadix Astragali, Rhodiola rosea, Cortex, CinnamomiQiShenYiQi pillsMitochondrial functionFlavonoid glycosides, 6-gingerol, and epigallocatechin gallateRhodiola roseaShengmai formula, Shengmai San, and Shexiang Baoxin pillAnti-inflammatory effectGinsenoside compound K, astragaloside IV, dihydronortanshinone, and curcuminRhodiola roseaTongxinluo capsule (TXL), Shexiang Baoxin pillInhibit apoptosisAstragalus polysaccharides, ophiopogonin D, and oxymatrine—YiXin-Shu, Qiang-Xin 1 formulaAntioxidationOphiopogonin D, panax notoginseng saponins, oxymatrine, cyclovirobuxine D, and curcuminRhodiola rosea, Silybum marianum, Salviae, Miltiorrhizae Radix et RhizomaShenxian-Shengmai oral, YiXin-Shu, and Shexiang Baoxin pillEnergy metabolismSalidroside, notoginsenoside R1, and tetrandrineRadix Astragali—
## 11. Conclusions and Perspectives
CVD is the leading cause of death in China [2]. CHD is a relatively common type of CVD. At present, CHD has become a major global public health problem; although antithrombosis, anti-ischemia, and lipid-regulating interventional therapies and secondary preventions have been used to improve CHD symptoms and reduce the mortality and HF after percutaneous coronary intervention(PCI), no reflow after revascularization, depression after CHD, CHD complications, and antithrombotic drug resistance still persist as clinical problems that need to be solved. At present, syndrome differentiation via a combination of modern medicine and TCM is the main method for treating CVD in China and abroad [88].Coronary atherosclerosis or vasospasm leads to decreased myocardial blood perfusion and increased ischemic damage of cells. During the ischemic period, hypoxia causes inhibition of mitochondrial ATP synthesis and oxidative phosphorylation, making it difficult for cells to maintain normal ATP content. At the same time, under the condition of ischemia and hypoxia, excessive metabolites, such as lactic acid, pyruvate, phosphate, and other acids, accumulate in the myocardium and produce symptoms such as angina pectoris or chest tiredness. An evidence showed that mitochondrial dysfunction occurs in the early stage of CHD and mitochondrial autophagy occurs in the late stage, which involves the steady-state dynamic balance of mitochondria [89].A growing number of studies showed that mitochondria play an important role in the cardiovascular system. Mitochondria can be used as targets for the treatment of CVDs [90]. Mutations in mtDNA affect CVD, leading to hypertension, atherosclerosis, and cardiomyopathy. However, TCM can regulate the structure and function of mitochondria by increasing electron transport and oxidative phosphorylation of mitochondria, thus regulating mitochondria-mediated apoptosis and reducing mitochondrial ROS to treat CVD.At present, there are multiple forms of TCM used in the treatment of CVD, including its active components, single herbs, and compound prescriptions [3, 42]. One review of 68 randomized controlled trials that included a total of 16171 patients revealed that, compared with blank control or placebo, TCM effectively reduces the severity of angina pectoris and MI; it also lowers blood pressure in patients with hypertension and improves cardiac function in patients with HF [91]. In most studies, the frequency of adverse effects was not higher for TCM than for controls or Western medicine [91]. However, the methodological quality of the majority of included studies was low; further studies using strictly designed randomized controlled trials are necessary to provide strong evidence [92]. Owing to the complexity of CVD pathogenesis, the action mechanism of TCM in the treatment of CVD is difficult to clarify. Moreover, mitochondria are the intracellular targets of many drugs, and there are extensive and complex interactions between mitochondria and related drugs [90].TCM has the advantages of multitarget and multipathways [42, 93]. A large number of clinical experiences and studies have shown that TCM plays an important role in the prevention, treatment, and prognosis of CVD [93]. Previous studies by our team have shown that circRNAs are closely related to the pathological process of acute coronary syndrome via a mechanism that may be related to the up- or downregulation of circRNAs and miRNAs and the coexpression of circRNA-miRNA [94]. In addition, through literature review, we consider that the circRNA-miRNA-mRNA network may be a new regulatory mechanism for TCM to effectively treat CVD [93]. Besides, TCM has been shown to improve the morphology and structure of mitochondria and participate in a series of metabolic processes, including regulation of energy metabolism, inhibition of apoptosis, and reduction of oxygen free radical production in mitochondria. There is a certain correlation between the intracellular targets of TCM and mitochondria.Furthermore, we should treat diseases according to syndrome differentiation and reasonably choose TCM based on the basic theory of TCM. Integrating TCM with Western medicine, an unprecedented task in today’s world, would provide a new medical model with unique advantages that can play an important role in the treatment of diseases [95]. Some experiments have confirmed the efficacy of combining TCM with Western medicine for the treatment of angina pectoris [96], and evidence for using TCM for the treatment of other CVDs is also increasing [3]. The combination of TCM and Western medicine is an attractive avenue for therapeutic intervention in CVD, and it may be the best scheme for CVD treatment. Thus, developing a strategy for integrating TCM with Western medicine will greatly contribute to human health care [95].
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*Source: 2902136-2020-10-08.xml* | 2020 |
# Time Fractional Schrodinger Equation Revisited
**Authors:** B. N. Narahari Achar; Bradley T. Yale; John W. Hanneken
**Journal:** Advances in Mathematical Physics
(2013)
**Publisher:** Hindawi Publishing Corporation
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2013/290216
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## Abstract
The time fractional Schrodinger equation (TFSE) for a nonrelativistic particle is derived on the basis of the Feynman path integral method by extending it initially to the case of a “free particle” obeying fractional dynamics, obtained by replacing the integer order derivatives with respect to time by those of fractional order. The equations of motion contain quantities which have “fractional” dimensions, chosen such that the “energy” has the correct dimension[ML2/T2]. The action S is defined as a fractional time integral of the Lagrangian, and a “fractional Planck constant” is introduced. The TFSE corresponds to a “subdiffusion” equation with an imaginary fractional diffusion constant and reproduces the regular Schrodinger equation in the limit of integer order. The present work corrects a number of errors in Naber’s work. The correct continuity equation for the probability density is derived and a Green function solution for the case of a “free particle” is obtained. The total probability for a “free” particle is shown to go to zero in the limit of infinite time, in contrast with Naber’s result of a total probability greater than unity. A generalization to the case of a particle moving in a potential is also given.
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## Body
## 1. Introduction
There has been an explosive research output in recent years in the application of methods of fractional calculus [1–13] to the study of quantum phenomena [14–42]. The well-known Schrodinger equation with a first-order derivative in time and second-order derivatives in space coordinates was given by Schrodinger as an Ansatz. The Schrodinger equation has been generalized to (i) a space fractional Schrodinger equation involving noninteger order space derivatives but retaining first-order time derivative [14–18], (ii) a time fractional Schrodinger equation involving non-integer order time derivative but retaining the second-order space derivatives [19], or (iii) more general fractional Schrodinger equation where both time and space derivatives are of non-integer order [20–26]. The fractional Schrodinger equation has also been obtained by using a fractional generalization of the Laplacian operator [20] and by using a fractional variation principle and a fractional Klein-Gordon equation [36]. In all these cases the fractional derivatives employed have been the regular fractional derivatives of the Riemann-Liouville type or the Caputo type (generally used in physical applications with initial conditions) which are both nonlocal in nature. The fractional derivative which is nonlocal by definition can be made “local” by a limiting process as shown by Kolwankar and Gangal [41]. Highly irregular and nowhere differentiable functions can be analyzed locally using these local fractional derivatives. The Heisenberg principle in the fractional context has been investigated using local fractional Fourier analysis [42].The Schrodinger equation for a free particle has the appearance of a diffusion equation with an imaginary diffusion coefficient. This suggests a method of deriving the Schrodinger equation as has been done using the Feynman path integral technique [43–45] based on the Gaussian probability distribution in the space of all possible paths. In other words, the classical Brownian motion leads to the Schrodinger equation in quantum mechanics. As far as deriving the fractional Schrodinger equation is concerned, the path integral approach for the Brownian-like paths for the Levy stable processes which leads to the classical space fractional diffusion equation has been extended to the Levy-like quantum paths leading to the space fractional Schrodinger equation (SFSE) in the seminal papers of Laskin [14–18]. It may be noted that in this case, the time derivative is still the integer first-order derivative; only the space part is of fractional order. The SFSE still retains the Markovian character and other fundamental aspects such as the Hermiticity of the Hamilton operator. Parity conservation and the current density have been explored in the space fractional quantum mechanics in terms of the Riesz fractional derivative. Applications of SFSE cover the dynamics of a free particle, particle in an infinite potential well, fractional Bohr atom, and the quantum fractional oscillator. Thus the space fractional Schrodinger equation appears to have been well established [18]. This theory has been further generalized recently within the frame work of tempered ultradistributions [39]. Thus the theory of SFSE can be considered fully established from the point of view of the Feynman path integral technique.The fractional time derivative was introduced into the Schrodinger equation by Naber [19] by simply replacing the first-order time derivative by a derivative of non-integer order and retaining the second-order space derivatives intact. The resulting equation is referred to as the time fractional Schrodinger equation (TFSE). He did not derive the TFSE using the path integral or any other method. Naber carried out the time fractional modification to the Schrodinger equation in analogy with time fractional diffusion equation [19] but included the imaginary number i raised to a fractional power (the fractional degree being the same as the fractional order of the time derivative), implying a sort of the Wick rotation. In Naber’s opinion [19], the TFSE is equivalent to the usual Schrodinger equation, but with a time-dependent Hamiltonian. He obtained the solutions for a free particle and a particle in a potential well. A lot of subsequent work has been done on the TFSE, mostly based on Naber’s work [21–23, 28], including its generalization into space-time fractional quantum dynamics by including non-integer order derivatives in both time and space. Yet some basic questions have not been addressed. It has been observed that TFSE describes non-Markovian evolution and that the Green function in the form of the Mittag-Leffler function does not satisfy Stone’s theorem on one-parameter unitary groups and the semiclassical approximation in terms of the classical action is not defined [31]. There has been no derivation of TFSE on a basis similar to that of SFSE and it is the purpose of the present paper to rectify this lacuna. Since the path integral method of deriving the space fractional part of the Schrodinger equation is well established, the present paper concentrates only on deriving the time fractional Schrodinger equation from the Feynman path integral approach, leading to the time fractional Schrodinger equation as given by Naber. It may be pointed out that some results of Naber, such as the total probability being greater than unity, are difficult to understand physically. Moreover, several major errors in Naber’s paper have gone unnoticed and in fact have been repeated by workers who have followed his work. Furthermore, some of these authors have introduced errors of their own. Since many of the conclusions in Naber’s paper are based on derivations which include these errors, it calls for a reexamination of Naber’s generalization to the time fractional Schrodinger equation.The present paper derives the time fractional Schrodinger equation using the Feynman path integral technique. It concentrates on the time fractional part only and not on the space fractional part as the theory of the latter has been well established in the works of Laskin [14–18]. Furthermore, the paper considers only the Caputo-type nonlocal fractional derivatives and not the local fractional derivatives discussed earlier. The paper starts from a generalization of the classical dynamics into fractional dynamics of a free particle and then adapting the Feynman technique derives the correct equations for TFSE. It is demonstrated that Naber’s result of probability being greater than unity is spurious and is a result of the ad hoc raising of the imaginary number i to a fractional power. The correct continuity equation for the probability density is also derived. The paper concludes with some new results.
## 2. Feynman Path Integral Method
The starting point for the Feynman method [43–46] is the classical Lagrangian L=L(x,x˙,t) and the action S=∫L(x,x˙,t)dt constructed from it. However, in view of the generalization to fractional calculus methods to be carried out later, the equations of motion of a classical particle in one dimension in the usual notation are considered first:
(1)mdxdt=p,dpdt=F.
Integrating with respect to time yields
(2)x=x0+1m∫0tp(τ)dτ,(3)p=p0+∫0tF(τ)dτ.
In the usual notation the Lagrangian is given by
(4)L(x,x˙,t)=T-V
and the action is given by
(5)S=∫0tL(x,x˙,τ)dτ.
An outline of the Feynman path integral method is presented following very closely the account given by Feynman and Hibbs [43]. The essence of the Feynman path integral approach to quantum mechanics is in the probability amplitude (also known as the propagator or the Green function) K(xb,tb;xa,ta) for a particle starting from a position xa at time ta to reach a position xb at a later time tb, which arises from the contributions from all trajectories from xa to xb:
(6)K(xb,tb;xa,ta)=∑all pathsϕ[x(t)],
where the contribution from each of the paths has the form
(7)ϕ[x(t)]=const.exp[iSℏ].
Here S is the action defined in (5) and ℏ is Planck’s constant, the quantum of action. The time integral of the Lagrangian is to be taken along the path in question. Restricting to one dimension, the probability amplitude can be written as
(8)K(xb,tb;xa,ta)=∫abexp[iℏ∫tatbLdt]𝔇x(t).
The symbol 𝔇 indicates the fact that the operation of integration is carried over all paths from a to b.The wave functionψ(xb,tb) gives the total probability amplitude to arrive at xb at tb satisfying (9), where the integral is taken over all possible values of xa(9)ψ(xb,tb)=∫-∞∞K(xb,tb;xa,ta)ψ(xa,ta)dxa.
The kernel K can be computed by first carrying out a “time slicing” operation by dividing the time interval from ta to tb into N segments of duration
(10)ε=tb-taN,
where
(11)ta=t0<t1<t2<⋯<tN-1<tN=tb;(12)K(xb,tb;xa,ta)=limε→01A∭⋯∫exp[iS[b,a]ℏ]=limε→01A×dx1Adx2Adx3A⋯dxN-1A,
where
(13)S[b,a]=∫tatbL(x,x˙,t)dt
is a line integral taken over the trajectory passing through the point x(t). The constant A is a normalizing factor.The Schrodinger equation for a free particle in one dimension is derived by considering a special case of (9), which describes the evolution of the wave function from a time ta to a time tb, when tb differs from ta by an infinitesimal amount ε and applied to the case of a free particle. This step is based on the fact that the semiclassical approximation is valid not only in the limit of ℏ→0 but also in the limit of small time interval [45]. The Kernel is proportional to the exponential of (i/ℏ) times the classical action for the infinitesimal time interval ε=tb-ta. With an obvious change of notation xb=x, xa=x0, ta=t, tb=t+ε and using the fact that the particle is free, (2) yields
(14)p0=m(x-x0)ε
and (4) yields
(15)L=T=m(x-x0)22ε2
and (5) yields for the action
(16)S=εL=m(x-x0)22ε.
As a consequence, (9) becomes
(17)ψ(x,t+ε)=∫-∞∞1Aexp[im(x-x0)22ε]ψ(x0,t)dx0.
If x differs appreciably from x0, the exponential in (17) oscillates very rapidly and the integral over x0 contributes a very small value and only those paths which are very close to x give significant contributions. Changing the variable in the integral from x0 to η=x-x0 makes it ψ(x0,t)=ψ(x+η,t). Since both ε and η are small quantities, ψ(x,t+ε) may be expanded in Taylor’s series and only up to terms of order ε are retained. On the right-hand side, ψ(x+η,t) may be expanded in Taylor’s series in powers of η, retaining terms up to second order in η (the integral involving the first-order term vanishes). Then (17) becomes
(18)ψ(x,t)+ε∂ψ∂t=∫-∞∞1Aexp[-mη22iℏε]×(ψ(x,t)+η∂ψ∂x+η22∂2ψ∂x2)dη.
On the right-hand side the middle term vanishes on integration. It follows by equating the leading terms on both sides
(19)ψ(x,t)=∫-∞∞1Aexp[-mη22iℏε]ψ(x,t)dη
Hence(20a)A=∫-∞∞exp[-mη22iℏε]dη=2πiℏεm,(20b)∫-∞∞1Aexp[-mη22iℏε](η22∂2ψ∂x2)dη=εiℏ2m∂2ψ∂x2.Equating the remaining terms results in
(21)∂ψ∂t=iℏ2m∂2ψ∂x2.
This can be recognized as the diffusion equation with an imaginary diffusion coefficient or the Schrodinger equation for a free particle in quantum mechanics.These considerations can be easily extended to the case of a particle moving in a potential field by incorporating a potential termV(x,t) in the Lagrangian L=T-V in (15). This will necessitate [43] incorporating an additional factor {1-(iε/ℏ)V(x,t)} in (18), which becomes
(22)ψ(x,t)+ε∂ψ∂t=∫-∞∞1Aexp[-mη22iℏε]{1-iεℏV(x,t)}×(ψ(x,t)+η∂ψ∂x+η22∂2ψ∂x2)dη.
Then (21) becomes
(23)∂ψ∂t=iℏ2m∂2ψ∂x2-iℏVψ.
Multiplying both sides by -ℏ/i results in the standard Schrodinger equation of quantum mechanics:
(24)iℏ∂ψ∂t=-ℏ22m∂2ψ∂x2+Vψ.
It is to be noted that the imaginary number i on the left-hand side is not arbitrary; it arises from the coefficient of the potential term V in (23) but ultimately from the coefficient of S/ℏ in (7). This minor detail becomes important as will be discussed later in Section 8.These considerations will be generalized for a particle obeying fractional dynamics. It can then be extended to the case of a particle in a potential field by including the potential term and making appropriate changes as will be described later.
## 3. Fractional Dynamics of a Free Particle
The first step is to generalize the equations of motion, (1)–(3), by replacing the integrals and derivatives by appropriate fractional integrals and derivatives. For physical problems with well-definable initial conditions the accepted practice is to employ the Caputo fractional derivatives [5]. The Caputo derivative of order β is defined by [3]:
(25)0CDtβf(t)=1Γ(n-β)∫0tfn(τ)dτ(t-τ)β+1-n(n-1<β<n).
In the limit β→n, the Caputo derivative becomes the ordinary nth derivative of the function.The fractional integral of orderβ is defined by
(26)0Itβf(t)=1Γ(β)∫0tf(τ)(t-τ)β-1dτ.
In generalizing the equations of motion, the second-order time derivative in Newton’s law is replaced by a Caputo derivative of order α, and the first-order derivative is replaced by a Caputo derivative of order (α/2) [47]. Then (2) and (3) become
(27)x=x0+1mfΓ(α/2)∫0tpf(τ)(t-τ)α/2-1dτ,pf=pf0+1Γ(α/2)∫0tF(τ)(t-τ)α/2-1dτ,
where as usual x0, pf0 refer to the initial position and initial value of the “fractional momentum” pf, respectively. It is to be noted that the variables x, t are still the space and time variables and have the dimensions of length and time [L] and [T], respectively. However, the dynamical quantities obtained by the operation of fractional derivation have different dimensions; for example, “fractional velocity” with the notation 0CDtα/2x=x˙α/2 would have the units [L/Tα/2]. The dimension for the parameter “mf” in the fractional momentum, pf=mfx˙α/2, is no longer just [M] but has to be chosen [47] so that the fractional quantity pf2/2mf has the dimensions of energy [ML2/T2]. Thus the dimension of the parameter “mf” is [MT2-α] and the fractional momentum has the dimensions [ML/T2-α/2]. The Lagrangian in (4) when generalized has the dimensions of energy. Of course, all quantities regain the standard dimensions in the limit α→2.
## 4. Time Fractional Schrodinger Equation for a Free Particle
There are two possible generalizations of the action integral in (5) used in fractional dynamics [11]:
(28)SI=∫0tL(x,x˙α/2,t)dt,(29)SII=1Γ(α/2)∫0tL(x,x˙α/2,τ)(t-τ)α/2-1dτ.
Since the Lagrangian has the dimensions of energy, the dimensions of action defined in (28) and (29), SI and SII, are different.The dimensions ofSI are the same as that of the regular action, namely, [ML2/T], but that of SII is [ML2/T2-α/2]. In the Newtonian limit α→2, SII→ regular action. These dimensional considerations have to be kept in mind in generalizing the Feynman method. In particular, if the choice from (29) is made, then a “fractional Planck constant” ℏf with appropriate dimensions must be introduced in order to render the argument of the exponential in (7) dimensionless.For a “free particle” (27) yields
(30)x=x0+pf0tα/2mfΓ(1+α/2),(31)pf=pf0.
After carrying out the time slicing operation as in (11) and making the same approximation the evolution of the wave function in an infinitesimal interval of time ε can now be obtained. Equation (30) yields
(32)pf0=(x-x0)mfΓ(1+α/2)εα/2
and hence
(33)L=mfΓ(1+α/2)(x-x0)22εα.
But for action, there are two choices:
(34)SI=mfΓ2(1+α/2)(x-x0)22εα-1,(35)SII=mfΓ(1+α/2)(x-x0)22εα/2.Making the appropriate changes, the equations for the evolution of the wave function in the two cases are(36)ψI(x,t+ε)=∫-∞∞1AIexp[imfΓ2(1+α/2)(x-x0)22ℏεα-1]×ψI(x0,t)dx0,(37)ψII(x,t+ε)=∫-∞∞1AIIexp[imfΓ(1+α/2)(x-x0)22ℏfεα/2]×ψII(x0,t)dx0.
Changing the variable in the integrals from x0 to η=x-x0 as before and introducing two constants
(38)aI=mfΓ2(1+α/2)2iℏ,aII=mfΓ(1+α/2)2iℏf.
Equations (36) and (37) can be written as
(39)ψI(x,t+ε)=∫-∞∞1AIexp[-aIη2εα-1]ψI(x+η,t)dη,(40)ψII(x,t+ε)=∫-∞∞1AIIexp[-aIIη2εα/2]ψII(x+η,t)dη.
The left-hand sides of (39) and (40) can be expanded in fractional Taylor’s series [48] in time, with fractional derivative of order γ, and keeping only the lowest-order term in γ yields
(41)ψI,II(x,t+ε)=ψI,II(x,t)+0CDtγψI,II(x,t)εγΓ(γ+1)+⋯.
In the right-hand side a Taylor expansion with terms up to second order in η with respect to space can be carried out and the two cases will be considered separately. Thus, the equation for ψI(x,t) becomes
(42)ψI(x,t)+0CDtγψI(x,t)εγΓ(γ+1)=∫-∞∞1AIexp[-aIη2εα-1]×{ψI(x,t)+η∂ψI∂x+η22∂2ψI∂x2}dη.
On evaluating the integrals on the right-hand side of (42), the middle term with the first power of η vanishes. Equating the leading terms on both sides of (42) yieldsψ
I
(
x
,
t
)
=
(
1
/
A
I
)
π
ε
α
-
1
/
a
I
ψ
I
(
x
,
t
), requiring that AI=πεα-1/aI. Equation (42) reduces to
(43)ψI(x,t)+0CDtγψI(x,t)εγΓ(γ+1)={ψI(x,t)+14εα-1aI∂2ψI(x,t)∂x2}.
Equating the remaining terms requires that the powers of ε must be the same on both sides; that is, γ=α-1. Inserting the value of aI and simplifying (43) yield
(44)0CDtα-1ψI(x,t)=iℏ2mfΓ(α)Γ2(1+α/2)∂2ψI(x,t)∂x2.
Similarly, by expanding (40) the equation for ψII(x,t) becomes
(45)ψII(x,t)+0CDtγψII(x,t)εγΓ(γ+1)=∫-∞∞1AIIexp[-aIIη2εα/2]×{ψII(x,t)+η∂ψII∂x+η22∂2ψII∂x2}dη.
On evaluating the integrals on the right-hand side of (45) the middle term vanishes. Equating the leading terms on both sides of (45) as before yields for the normalizing factor AII=πεα/2/aII. Equation (45) reduces to
(46)ψII(x,t)+0CDtγψII(x,t)εγΓ(γ+1)={ψII(x,t)+14εα/2aII∂2ψII(x,t)∂x2}.
In the remaining terms, the powers of ε must be the same. This requires γ=α/2. Inserting the value of aII and simplifying (46) yield the equation for the wave function ψII(x,t):
(47)0CDtα/2ψII(x,t)=iℏf2mf∂2ψII(x,t)∂x2.
This completes the derivation based on the Feynman path integral method and (44) and (47) constitute the time fractional Schrodinger equations for a free particle corresponding to two ways of defining the action integral for a fractional dynamical system. In the limit α→2, the fractional dynamical system goes over to the regular Newtonian system and in this case both (44) and (47) reduce to
(48)∂ψ(x,t)∂t=iℏ2m∂2ψ(x,t)∂x2
given earlier, thus recovering the standard Schrodinger equation for a free quantum particle [49].It should be noted that sinceα≤2, with α=2 being the limiting case, the order of the time fractional derivative is ≤1 in both (44) and (47) and cannot exceed 1. This means the time fractional Schrodinger equation as derived from the path integral method always corresponds to the “subdiffusion” case in contrast to the case where the TFSE is obtained by a simple replacement of the first-order time derivative by a fractional order derivative [19]. Furthermore, the order α/2 of the fractional derivative corresponds to the first-order regular derivative as has been used above in Section 3. Thus it appears that the second method of defining the action leading to (47) is the natural way to generalize to TFSE. In appearance also it is as if the equation has been obtained by replacing all quantities in the Schrodinger equation by an equivalent fractional quantity, except the space derivative. Furthermore, (44) becomes a fractional order integro-differential equation when α<1 and no longer just a fractional order differential equation. Because of these reasons, it is considered the method of choice to use (47) as the TFSE derived from the path integral method and no further reference will be made to (44).The coefficient of the space derivative term in (47) has the dimension [L2/Tα/2], corresponding to the fractional diffusion coefficient. Thus (47) can be considered a time fractional diffusion equation with an imaginary fractional diffusion coefficient, just as (48), the regular Schrodinger equation, can be considered to be a diffusion equation with an imaginary diffusion coefficient. Thus all the mathematical machinery of time fractional diffusion theory [5, 50–59] can be imported advantageously.Although it is possible to introduce additional parameters and cast (47) in a dimensionless form, it has not been done here. However, for convenience, the subscript II is dropped from the wave function; a simplified notation for the Caputo derivative, ∂tβψ, with β=α/2 will be used. Naturally, 0<β≤1, and β→1 yields the regular first-order time derivative, denoted by ∂t. After incorporating these changes and defining a new constant Df=ℏf/2mf, (47) becomes
(49)∂tβψ(x,t)=iDf∂2ψ(x,t)∂x2(0<β≤1).Equation (49) can be solved by a combination of the Fourier and Laplace transform methods [52–54].
## 5. Probability Current and the Continuity Equation
The probability densityρ is defined by ρ=ψ*ψ=ψψ*. The complex conjugate wave function satisfies
(50)∂tβψ*(x,t)=-iDf∂2ψ*(x,t)∂x2.
There is an identity satisfied by the Caputo derivative [5]
(51)∂t1-β∂tβf(t)=∂tf(t),
where the right-hand side represents the regular first-order derivative. This identity can be used in studying the time derivative of the probability density, given by
(52)∂tρ=∂t(ψψ*)=(∂tψ)ψ*+ψ(∂tψ*).
Inserting from (51) gives
(53)∂tρ=(∂t1-β∂tβψ)ψ*+ψ(∂t1-β∂tβψ*).
Substituting from (49) and (50), (53) yields
(54)∂tρ=(∂t1-β(iDf∂2ψ(x,t)∂x2))ψ*+ψ(∂t1-β(-iDf∂2ψ*(x,t)∂x2)).
Equation (54) can be rewritten after factoring out the constant and interchanging the order of space and time derivatives as
(55)∂tρ=iDf{(∂2∂x2∂t1-βψ)ψ*-ψ(∂2∂x2∂t1-βψ*)}.
Introducing a new function ψ~=∂t1-βψ, (55) can be written as
(56)∂tρ=iDf{(∂2∂x2ψ~)ψ*-ψ(∂2∂x2ψ~*)}.
Defining a probability current density given by
(57)Jx=-iDf[ψ~*∂ψ∂x-ψ∂ψ~*∂x],
equation (56) can be written as
(58)∂tρ+∂Jx∂x=0.
This is the time fractional version of the continuity equation. In the limit β→1, ψ~→ψ ψ~*→ψ* and (58) reproduce the continuity equation of standard quantum mechanics [49]. It may be noted that (58) differs from Naber’s result ((24) in [19]) and will be discussed later.
## 6. Solution for TFSE for a Free Particle
The solution for the TFSE for a free particle under the conditionsψ
(
x
,
0
)
=
ψ
0
(
x
); ψ(x,t)→0, |x|→∞, t>0 is available in the literature but considered here for purposes of obtaining the Green function for the TFSE.By applying the combined Fourier and Laplace transforms defined by(59)ψ~^(k,s)=12π∫-∞∞e-ikx[∫0∞e-stψ(x,t)dt]dx
equation (49) reduces to
(60)sβψ~^(k,s)-sβ-1ψ~(k,0)=-iDfk2ψ~^(k,s)
resulting in
(61)ψ~^(k,s)=ψ~(k,0)sβ-1sβ+iDfk2.Applying the inverse Laplace transform, (61) yields
(62)ψ~(k,t)=ψ~(k,0)Eβ,1(-iDfk2tβ)
in terms of the Mittag-Leffler function defined by a series or by the inverse Lapalce transform [3]:
(63)Eα,β(z)=∑n=0∞znΓ(αn+β)=L-1{sα-βsα-z}.The Green function solution can be written as(64)ψ(x,t)=∫-∞∞ψ(x-ξ)Gβ(ξ,t)dξ,
where the Green function is given by the inverse Fourier transform of the Mittag-Leffler function
(65)Gβ(x,t)=12π∫-∞∞eikxEβ,1(-iDfk2tβ)dk,
where the Mittag-Leffler function has been defined [3] before in (63).The Fourier inversion in (65) can be carried out [52–54] using the property that the Mittag-Leffler function is related through the Laplace integral to another special function of the Wright type denoted by
(66)Mβ(z)=W(-z;-β,1-β)=∑n=0∞(-z)nn!Γ(-βn+1-β)0<β<1,
where the Wright function is defined by [54]
(67)W(z;λ,μ)=∑n=0∞znn!Γ(λn+μ)λ>-1,μ∈C.
The Green function in (65) is then given by
(68)Gβ(x,t)=121iDftβ/2Mβ/2(|x|iDftβ/2).
In the context of fractional diffusion, the function Mβ/2(z) belongs to the Wright type of probability densities characterized by the similarity variable z=|x|/Dftβ/2, where Df is the fractional diffusion coefficient, with ∫0∞Mβ/2(z)dz=1. Furthermore, the probability densities are non-Markovian and exhibit a variance consistent with slow anomalous diffusion [49–51], σβ2(t)=(2/Γ(β+1))Dftβ.In the limit ofβ→1, the probability density function goes over to the Gaussian
(69)M1/2(z)=1πe-z2/4
corresponding to regular diffusion. A plot of the reduced probability density function is given in Figure 1.Figure 1
Reduced probability density function.The Green function for regular diffusion describes a probability density, whereas the corresponding Green function for the Schrodinger equation is the propagator, which describes the probability amplitude for the particle to propagate fromxa at ta to xb at tb. In exactly the same way, the Green function for time fractional diffusion describes a probability density, whereas the Green function in (68) is the fractional propagator and gives the probability amplitude. Of particular interest is the Fourier component of the wave function in (62) in connection with the total probability as t→∞; the case discussed by Naber [19] and will be discussed in the next section.
## 7. Comments about Some Results in Naber’s Work [19]
This section draws attention to some errors in Naber’s paper which have gone unnoticed and have been reproduced repeatedly. Naber’s equations will be referred to by their number and a prefix N. Naber explicitly states that he uses the Caputo derivative, which has been defined earlier in (25) in this paper. Although Naber does not give the explicit definition of the Caputo fractional derivative in his paper [19], it can be inferred from (NA.3) given in the appendix to his paper.(a) However, Naber writes in (N16) for a Caputo derivative of order (1-ν), reproduced here for convenience in (70):
(70)Dt1-νψ(t,x)=1Γ(1-ν)×∫0tdψ(τ,x)dτdτ(t-τ)ν(0<ν<1).
This is incorrect, as can be checked easily by taking the limit ν→1. The left-hand side →ψ(t,x) as the derivative of zero order, but the right-hand side →0 because of the Γ function in the denominator. The correct form of equation is
(71)Dt1-νψ(t,x)=1Γ(ν)∫0tdψ(τ,x)dτdτ(t-τ)1-ν.
As a consequence, the weight factor in (N18) should be (t-τ)1-ν and not (t-τ)-ν, which Naber uses to give a physical significance to the entity he has introduced. The correct weight factor in (N18) would →1 in the limit ν→1.(b) In (N11), Naber gives an identity satisfied supposedly by fractional Caputo derivatives of order less than 1, reproduced here for convenience in (72).
(72)Dt1-νDtνy(t)=dydt-[Dtνy(t)]t=0t1-νΓ(ν).
This identity is not correct and cannot be found anywhere. The identity satisfied by the Caputo derivatives is given in [5] and reproduced later in the current notation for ν<1(73)Dt-νDtνy(t)=y(t)-y(0).
This yields Dt1-νDtνy(t)=dy/dt=∂ty(t) and has been used earlier in (52) in this paper.The incorrect identity has been used by Naber to derive an equation for the probability current, which is obviously incorrect. Unfortunately, the incorrect identity, as given by Naber, in (72) has been repeatedly used in the literature. The correct equation for the probability current has been given in this paper in (59), which reduces to the standard continuity equation for the probability current in regular quantum mechanics [49].(c) This point concerns the separation of the Mittag-Leffler function with an imaginary argument into an oscillatory part and a part which decays exponentially with time. There is nothing wrong with the derivation itself as given by Naber, and the function under discussion is the Fourier component of the free particle wave function, in his notation(74)Ψ=Ψ0Eν(ω(-it)ν),
where Eν(z) in Naber’s notation corresponds to the Mittag-Leffler function Eν,1(z) defined in (63).The Mittag-Leffler function with the complex argument has been separated into an oscillatory part and a part based on the evaluation of the inverse Laplace transform(75)A(t)=12πi∫γ-i∞γ+i∞estsν-1A0dssν-σiν
along a Hankel contour and considering the contribution from the residue of the pole s0=σ1/νi together with the contribution from the integral along the two strips on either side of the branch cut, which is a standard procedure. Naber finally gives the solution as
(76)Ψ=Ψ0{e-iω1/νtν-Fν(ω(-i)ν,t)}.
He argues that in the limit of t→∞ the total probability arises basically from the first term and is equal to 1/ν2, assuming that the wave function was initially normalized. Since ν<1, the total probability is >1, a result difficult to understand physically. However, it is shown later that the solution derived in this paper yields a probability that →0 in the limit t→∞.The solution corresponding to (74) is given by (62) in this paper. The separation into two parts corresponding to (76) can be carried out by considering the inverse Laplace transform of (61):
(77)ψ~(k,t)=12πi∫γ-i∞γ+i∞estsβ-1ψ~(k,0)dssβ+iDfk2.
As usual, the Bromwich contour is replaced by the Hankel contour. The two contributions arise from (i) the residue at the pole at s0=(Dfk2)1/β(-i)1/β and (ii) the integral along the two strips from 0 to -∞ introduced along the branch cut. The latter yields a contribution which decays in time just as the second term in Naber’s equation (76). The contribution from the residue is given by
(78)Residueψ~(k,0)=e(-i)1/β(Dfk2)1/βtβ
and corresponds to the first term on the right-hand side in (76). However,
(79)(-i)1/β=(e-iπ/2)1/β=(e-iπ/2β)=(cosπ2β-isinπ2β).
Therefore, (78) yields
(80)ψ~(k,t)ψ~(k,0)=Residueψ~(k,0)=et(Dfk2)1/βcos(π/2β)e-it(Dfk2)1/βsin(π/2β).
The right-hand side of (80) has an amplitude term and an oscillatory factor. Because β<1, cos(π/2β) is negative, the amplitude factor decays in time exponentially and →0 in the limit t→∞. Thus the contribution from the residue due to the pole also →0. Thus the entire wave function →0 in the limit of t→∞, so does the probability density. Hence the total probability also →0, in contrast to Naber’s result.The question naturally arises why there is this difference in the two results, both of which are concerned with the Mittag-Leffler functions with complex arguments. The reason appears to be that in Naber’s case, the pole occurs ats0=σ1/νi, whereas in the present paper, the pole occurs (using the same notation as Naber) at s0=σ1/ν(-i)1/ν. The simple i in Naber’s case leads to the purely oscillatory solution and hence to the result of the probability being greater than unity. In our paper the imaginary number raised to the fractional power leads to the exponentially decaying solution and hence leads to the correct limit when t→∞, namely, zero total probability. Naber’s result is a direct consequence of his choice to raise the power of the imaginary number i to the fractional power, so as to incorporate a Wick rotation. However, as had been indicated earlier, this imaginary number cannot be arbitrarily altered as it is connected with the phase factor iS/ℏ in the Feynman propagator. If it is necessary to include a Wick rotation, the power of i should be changed to ν+1 in Naber’s equation (N9) instead of just ν. If this is done, the total probability would properly →0 in the limit t→∞. If this is done, then the TFSE can be interpreted as the analytic continuation of the fractional diffusion equation, just as the regular Schrodinger equation can be considered as the analytic continuation of the regular diffusion equation.
## 8. TFSE for a Particle in a Potential Field
So far attention has been focused on a free particle. These considerations can be easily extended to the case of a particle moving in a potential field by incorporating a potential termV(x,t) in the Lagrangian L=T-V. This will necessitate incorporating an additional term -V(x,t)εα/2/Γ(1+α/2) in the right-hand side of (35) and an additional factor -(i/hf)(V(x,t)εα/2/Γ(1+α/2)) in the exponential in (37). This results in changing (45) into
(81)ψII(x,t)+0CDtβψII(x,t)εβΓ(β+1)=∫-∞∞1AIIexp[-aIIη2εα/2]{1-ihfV(x,t)εα/2Γ(1+α/2)}×{ψII(x,t)+η∂ψII∂x+η22∂2ψII∂x2}dη.Equation (47) then becomes
(82)0CDtα/2ψII(x,t)=iℏf2mf∂2ψII(x,t)∂x2-ihfV(x,t)ψ(x,t).
Multiplying both sides by -ℏf/i results in the FTSE for a particle in a potential field as
(83)iℏf∂tβψ(x,t)=-ℏf22mf∂2ψ(x,t)∂x2-V(x,t)ψ(x,t)
which reduces to the standard Schrodinger equation of quantum mechanics:
(84)iℏ∂ψ∂t=-ℏ22m∂2ψ∂x2+Vψ.
One final remark needs to be made concerning the use of the Planck units for casting the TFSE in terms of dimensionless quantities. After the derivation, the FTSE in (83) can be cast in dimensionless quantities; however, the appropriate fractional Planck units must be defined to take care of the fractional quantities involved in (83).
## 9. Discussion and Conclusions
The TFSE has been derived using the Feynman path integral technique for a nonrelativistic particle. As expected the TFSE looks like a time fractional diffusion equation with an imaginary fractional diffusion constant but pertains to the realm of subdiffusion only, in contrast to Naber’s generalization which includes superdiffusion as well. This is understandable because the case considered in this paper pertains to the nonrelativistic case. Relativistic considerations would have to be included for the superdiffusion case, which would lead to the Klein-Gordon equation in the integer order limit. In adapting the Feynman method, it is shown that it is preferable to introduce the actionS as a fractional time integral of the Lagrangian and that it is necessary to introduce a “fractional Planck constant.” In the limit of integer order, the regular action S, the regular Schrodinger equation, and the regular Planck constant are all recovered. It may be of interest to note that there is a fractional Planck constant implied in Naber’s work also, although it is not explicitly so stated. His equations are rendered nondimensional by using the Planck units of mass, length, and time and then generalized to fractional derivatives after including a Wick rotation. This implies a change of variable of time t→it so that the imaginary number is raised to the same power as the order of the fractional time derivative involved. However, the Planck units may not be the appropriate quantities as the equations involve quantities of fractional dimension and the equations must be made nondimensional after the generalization to fractional derivatives and not before. A fractional Planck constant does show up in Naber’s treatment as well, as the ratio of masses m/Mp [31, 32].A number of errors in Naber’s work have been corrected. The correct continuity equation for the probability current is derived and the Green function solution for a free particle is given. The Green function is given in terms of a special type of function, the M-Wright function, which is used extensively in studies of time fractional subdiffusion studies. In the context of time fractional diffusion, the M-Wright function is a probability density function in time, which is non-Markovian and goes over to the Gaussian in the nonfractional limiting case. In the context of TFSE, the M-Wright function gives the propagator, which is a probability amplitude. Probability considerations are accounted for by the usual process of squaring of the amplitude. In particular, it is shown that Naber’s result that the total probability is greater than unity in the long-time limit is a spurious result arising out of the operation of arbitrarily raising of the imaginary numberi to the power of the same degree as the fractional time derivative invoking a Wick rotation. It is shown that such arbitrary change of the imaginary number cannot be carried out as the imaginary number i is connected with the phase of the action S in the path integral contribution. However, if we desired to consider a Wick rotation, it should be included as an additional increase of the index of the power of the imaginary number. The TFSE for a particle moving in a potential field is also derived. Furthermore, it is suggested that even in studies of fractional classical mechanics, such as those using variational methods, the action integral be expressed as a time fractional integral of the Lagrangian. Further extensions including the solutions to particle subject to different potentials are underway.
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*Source: 290216-2013-07-28.xml* | 290216-2013-07-28_290216-2013-07-28.md | 38,456 | Time Fractional Schrodinger Equation Revisited | B. N. Narahari Achar; Bradley T. Yale; John W. Hanneken | Advances in Mathematical Physics
(2013) | Mathematical Sciences | Hindawi Publishing Corporation | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2013/290216 | 290216-2013-07-28.xml | ---
## Abstract
The time fractional Schrodinger equation (TFSE) for a nonrelativistic particle is derived on the basis of the Feynman path integral method by extending it initially to the case of a “free particle” obeying fractional dynamics, obtained by replacing the integer order derivatives with respect to time by those of fractional order. The equations of motion contain quantities which have “fractional” dimensions, chosen such that the “energy” has the correct dimension[ML2/T2]. The action S is defined as a fractional time integral of the Lagrangian, and a “fractional Planck constant” is introduced. The TFSE corresponds to a “subdiffusion” equation with an imaginary fractional diffusion constant and reproduces the regular Schrodinger equation in the limit of integer order. The present work corrects a number of errors in Naber’s work. The correct continuity equation for the probability density is derived and a Green function solution for the case of a “free particle” is obtained. The total probability for a “free” particle is shown to go to zero in the limit of infinite time, in contrast with Naber’s result of a total probability greater than unity. A generalization to the case of a particle moving in a potential is also given.
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## Body
## 1. Introduction
There has been an explosive research output in recent years in the application of methods of fractional calculus [1–13] to the study of quantum phenomena [14–42]. The well-known Schrodinger equation with a first-order derivative in time and second-order derivatives in space coordinates was given by Schrodinger as an Ansatz. The Schrodinger equation has been generalized to (i) a space fractional Schrodinger equation involving noninteger order space derivatives but retaining first-order time derivative [14–18], (ii) a time fractional Schrodinger equation involving non-integer order time derivative but retaining the second-order space derivatives [19], or (iii) more general fractional Schrodinger equation where both time and space derivatives are of non-integer order [20–26]. The fractional Schrodinger equation has also been obtained by using a fractional generalization of the Laplacian operator [20] and by using a fractional variation principle and a fractional Klein-Gordon equation [36]. In all these cases the fractional derivatives employed have been the regular fractional derivatives of the Riemann-Liouville type or the Caputo type (generally used in physical applications with initial conditions) which are both nonlocal in nature. The fractional derivative which is nonlocal by definition can be made “local” by a limiting process as shown by Kolwankar and Gangal [41]. Highly irregular and nowhere differentiable functions can be analyzed locally using these local fractional derivatives. The Heisenberg principle in the fractional context has been investigated using local fractional Fourier analysis [42].The Schrodinger equation for a free particle has the appearance of a diffusion equation with an imaginary diffusion coefficient. This suggests a method of deriving the Schrodinger equation as has been done using the Feynman path integral technique [43–45] based on the Gaussian probability distribution in the space of all possible paths. In other words, the classical Brownian motion leads to the Schrodinger equation in quantum mechanics. As far as deriving the fractional Schrodinger equation is concerned, the path integral approach for the Brownian-like paths for the Levy stable processes which leads to the classical space fractional diffusion equation has been extended to the Levy-like quantum paths leading to the space fractional Schrodinger equation (SFSE) in the seminal papers of Laskin [14–18]. It may be noted that in this case, the time derivative is still the integer first-order derivative; only the space part is of fractional order. The SFSE still retains the Markovian character and other fundamental aspects such as the Hermiticity of the Hamilton operator. Parity conservation and the current density have been explored in the space fractional quantum mechanics in terms of the Riesz fractional derivative. Applications of SFSE cover the dynamics of a free particle, particle in an infinite potential well, fractional Bohr atom, and the quantum fractional oscillator. Thus the space fractional Schrodinger equation appears to have been well established [18]. This theory has been further generalized recently within the frame work of tempered ultradistributions [39]. Thus the theory of SFSE can be considered fully established from the point of view of the Feynman path integral technique.The fractional time derivative was introduced into the Schrodinger equation by Naber [19] by simply replacing the first-order time derivative by a derivative of non-integer order and retaining the second-order space derivatives intact. The resulting equation is referred to as the time fractional Schrodinger equation (TFSE). He did not derive the TFSE using the path integral or any other method. Naber carried out the time fractional modification to the Schrodinger equation in analogy with time fractional diffusion equation [19] but included the imaginary number i raised to a fractional power (the fractional degree being the same as the fractional order of the time derivative), implying a sort of the Wick rotation. In Naber’s opinion [19], the TFSE is equivalent to the usual Schrodinger equation, but with a time-dependent Hamiltonian. He obtained the solutions for a free particle and a particle in a potential well. A lot of subsequent work has been done on the TFSE, mostly based on Naber’s work [21–23, 28], including its generalization into space-time fractional quantum dynamics by including non-integer order derivatives in both time and space. Yet some basic questions have not been addressed. It has been observed that TFSE describes non-Markovian evolution and that the Green function in the form of the Mittag-Leffler function does not satisfy Stone’s theorem on one-parameter unitary groups and the semiclassical approximation in terms of the classical action is not defined [31]. There has been no derivation of TFSE on a basis similar to that of SFSE and it is the purpose of the present paper to rectify this lacuna. Since the path integral method of deriving the space fractional part of the Schrodinger equation is well established, the present paper concentrates only on deriving the time fractional Schrodinger equation from the Feynman path integral approach, leading to the time fractional Schrodinger equation as given by Naber. It may be pointed out that some results of Naber, such as the total probability being greater than unity, are difficult to understand physically. Moreover, several major errors in Naber’s paper have gone unnoticed and in fact have been repeated by workers who have followed his work. Furthermore, some of these authors have introduced errors of their own. Since many of the conclusions in Naber’s paper are based on derivations which include these errors, it calls for a reexamination of Naber’s generalization to the time fractional Schrodinger equation.The present paper derives the time fractional Schrodinger equation using the Feynman path integral technique. It concentrates on the time fractional part only and not on the space fractional part as the theory of the latter has been well established in the works of Laskin [14–18]. Furthermore, the paper considers only the Caputo-type nonlocal fractional derivatives and not the local fractional derivatives discussed earlier. The paper starts from a generalization of the classical dynamics into fractional dynamics of a free particle and then adapting the Feynman technique derives the correct equations for TFSE. It is demonstrated that Naber’s result of probability being greater than unity is spurious and is a result of the ad hoc raising of the imaginary number i to a fractional power. The correct continuity equation for the probability density is also derived. The paper concludes with some new results.
## 2. Feynman Path Integral Method
The starting point for the Feynman method [43–46] is the classical Lagrangian L=L(x,x˙,t) and the action S=∫L(x,x˙,t)dt constructed from it. However, in view of the generalization to fractional calculus methods to be carried out later, the equations of motion of a classical particle in one dimension in the usual notation are considered first:
(1)mdxdt=p,dpdt=F.
Integrating with respect to time yields
(2)x=x0+1m∫0tp(τ)dτ,(3)p=p0+∫0tF(τ)dτ.
In the usual notation the Lagrangian is given by
(4)L(x,x˙,t)=T-V
and the action is given by
(5)S=∫0tL(x,x˙,τ)dτ.
An outline of the Feynman path integral method is presented following very closely the account given by Feynman and Hibbs [43]. The essence of the Feynman path integral approach to quantum mechanics is in the probability amplitude (also known as the propagator or the Green function) K(xb,tb;xa,ta) for a particle starting from a position xa at time ta to reach a position xb at a later time tb, which arises from the contributions from all trajectories from xa to xb:
(6)K(xb,tb;xa,ta)=∑all pathsϕ[x(t)],
where the contribution from each of the paths has the form
(7)ϕ[x(t)]=const.exp[iSℏ].
Here S is the action defined in (5) and ℏ is Planck’s constant, the quantum of action. The time integral of the Lagrangian is to be taken along the path in question. Restricting to one dimension, the probability amplitude can be written as
(8)K(xb,tb;xa,ta)=∫abexp[iℏ∫tatbLdt]𝔇x(t).
The symbol 𝔇 indicates the fact that the operation of integration is carried over all paths from a to b.The wave functionψ(xb,tb) gives the total probability amplitude to arrive at xb at tb satisfying (9), where the integral is taken over all possible values of xa(9)ψ(xb,tb)=∫-∞∞K(xb,tb;xa,ta)ψ(xa,ta)dxa.
The kernel K can be computed by first carrying out a “time slicing” operation by dividing the time interval from ta to tb into N segments of duration
(10)ε=tb-taN,
where
(11)ta=t0<t1<t2<⋯<tN-1<tN=tb;(12)K(xb,tb;xa,ta)=limε→01A∭⋯∫exp[iS[b,a]ℏ]=limε→01A×dx1Adx2Adx3A⋯dxN-1A,
where
(13)S[b,a]=∫tatbL(x,x˙,t)dt
is a line integral taken over the trajectory passing through the point x(t). The constant A is a normalizing factor.The Schrodinger equation for a free particle in one dimension is derived by considering a special case of (9), which describes the evolution of the wave function from a time ta to a time tb, when tb differs from ta by an infinitesimal amount ε and applied to the case of a free particle. This step is based on the fact that the semiclassical approximation is valid not only in the limit of ℏ→0 but also in the limit of small time interval [45]. The Kernel is proportional to the exponential of (i/ℏ) times the classical action for the infinitesimal time interval ε=tb-ta. With an obvious change of notation xb=x, xa=x0, ta=t, tb=t+ε and using the fact that the particle is free, (2) yields
(14)p0=m(x-x0)ε
and (4) yields
(15)L=T=m(x-x0)22ε2
and (5) yields for the action
(16)S=εL=m(x-x0)22ε.
As a consequence, (9) becomes
(17)ψ(x,t+ε)=∫-∞∞1Aexp[im(x-x0)22ε]ψ(x0,t)dx0.
If x differs appreciably from x0, the exponential in (17) oscillates very rapidly and the integral over x0 contributes a very small value and only those paths which are very close to x give significant contributions. Changing the variable in the integral from x0 to η=x-x0 makes it ψ(x0,t)=ψ(x+η,t). Since both ε and η are small quantities, ψ(x,t+ε) may be expanded in Taylor’s series and only up to terms of order ε are retained. On the right-hand side, ψ(x+η,t) may be expanded in Taylor’s series in powers of η, retaining terms up to second order in η (the integral involving the first-order term vanishes). Then (17) becomes
(18)ψ(x,t)+ε∂ψ∂t=∫-∞∞1Aexp[-mη22iℏε]×(ψ(x,t)+η∂ψ∂x+η22∂2ψ∂x2)dη.
On the right-hand side the middle term vanishes on integration. It follows by equating the leading terms on both sides
(19)ψ(x,t)=∫-∞∞1Aexp[-mη22iℏε]ψ(x,t)dη
Hence(20a)A=∫-∞∞exp[-mη22iℏε]dη=2πiℏεm,(20b)∫-∞∞1Aexp[-mη22iℏε](η22∂2ψ∂x2)dη=εiℏ2m∂2ψ∂x2.Equating the remaining terms results in
(21)∂ψ∂t=iℏ2m∂2ψ∂x2.
This can be recognized as the diffusion equation with an imaginary diffusion coefficient or the Schrodinger equation for a free particle in quantum mechanics.These considerations can be easily extended to the case of a particle moving in a potential field by incorporating a potential termV(x,t) in the Lagrangian L=T-V in (15). This will necessitate [43] incorporating an additional factor {1-(iε/ℏ)V(x,t)} in (18), which becomes
(22)ψ(x,t)+ε∂ψ∂t=∫-∞∞1Aexp[-mη22iℏε]{1-iεℏV(x,t)}×(ψ(x,t)+η∂ψ∂x+η22∂2ψ∂x2)dη.
Then (21) becomes
(23)∂ψ∂t=iℏ2m∂2ψ∂x2-iℏVψ.
Multiplying both sides by -ℏ/i results in the standard Schrodinger equation of quantum mechanics:
(24)iℏ∂ψ∂t=-ℏ22m∂2ψ∂x2+Vψ.
It is to be noted that the imaginary number i on the left-hand side is not arbitrary; it arises from the coefficient of the potential term V in (23) but ultimately from the coefficient of S/ℏ in (7). This minor detail becomes important as will be discussed later in Section 8.These considerations will be generalized for a particle obeying fractional dynamics. It can then be extended to the case of a particle in a potential field by including the potential term and making appropriate changes as will be described later.
## 3. Fractional Dynamics of a Free Particle
The first step is to generalize the equations of motion, (1)–(3), by replacing the integrals and derivatives by appropriate fractional integrals and derivatives. For physical problems with well-definable initial conditions the accepted practice is to employ the Caputo fractional derivatives [5]. The Caputo derivative of order β is defined by [3]:
(25)0CDtβf(t)=1Γ(n-β)∫0tfn(τ)dτ(t-τ)β+1-n(n-1<β<n).
In the limit β→n, the Caputo derivative becomes the ordinary nth derivative of the function.The fractional integral of orderβ is defined by
(26)0Itβf(t)=1Γ(β)∫0tf(τ)(t-τ)β-1dτ.
In generalizing the equations of motion, the second-order time derivative in Newton’s law is replaced by a Caputo derivative of order α, and the first-order derivative is replaced by a Caputo derivative of order (α/2) [47]. Then (2) and (3) become
(27)x=x0+1mfΓ(α/2)∫0tpf(τ)(t-τ)α/2-1dτ,pf=pf0+1Γ(α/2)∫0tF(τ)(t-τ)α/2-1dτ,
where as usual x0, pf0 refer to the initial position and initial value of the “fractional momentum” pf, respectively. It is to be noted that the variables x, t are still the space and time variables and have the dimensions of length and time [L] and [T], respectively. However, the dynamical quantities obtained by the operation of fractional derivation have different dimensions; for example, “fractional velocity” with the notation 0CDtα/2x=x˙α/2 would have the units [L/Tα/2]. The dimension for the parameter “mf” in the fractional momentum, pf=mfx˙α/2, is no longer just [M] but has to be chosen [47] so that the fractional quantity pf2/2mf has the dimensions of energy [ML2/T2]. Thus the dimension of the parameter “mf” is [MT2-α] and the fractional momentum has the dimensions [ML/T2-α/2]. The Lagrangian in (4) when generalized has the dimensions of energy. Of course, all quantities regain the standard dimensions in the limit α→2.
## 4. Time Fractional Schrodinger Equation for a Free Particle
There are two possible generalizations of the action integral in (5) used in fractional dynamics [11]:
(28)SI=∫0tL(x,x˙α/2,t)dt,(29)SII=1Γ(α/2)∫0tL(x,x˙α/2,τ)(t-τ)α/2-1dτ.
Since the Lagrangian has the dimensions of energy, the dimensions of action defined in (28) and (29), SI and SII, are different.The dimensions ofSI are the same as that of the regular action, namely, [ML2/T], but that of SII is [ML2/T2-α/2]. In the Newtonian limit α→2, SII→ regular action. These dimensional considerations have to be kept in mind in generalizing the Feynman method. In particular, if the choice from (29) is made, then a “fractional Planck constant” ℏf with appropriate dimensions must be introduced in order to render the argument of the exponential in (7) dimensionless.For a “free particle” (27) yields
(30)x=x0+pf0tα/2mfΓ(1+α/2),(31)pf=pf0.
After carrying out the time slicing operation as in (11) and making the same approximation the evolution of the wave function in an infinitesimal interval of time ε can now be obtained. Equation (30) yields
(32)pf0=(x-x0)mfΓ(1+α/2)εα/2
and hence
(33)L=mfΓ(1+α/2)(x-x0)22εα.
But for action, there are two choices:
(34)SI=mfΓ2(1+α/2)(x-x0)22εα-1,(35)SII=mfΓ(1+α/2)(x-x0)22εα/2.Making the appropriate changes, the equations for the evolution of the wave function in the two cases are(36)ψI(x,t+ε)=∫-∞∞1AIexp[imfΓ2(1+α/2)(x-x0)22ℏεα-1]×ψI(x0,t)dx0,(37)ψII(x,t+ε)=∫-∞∞1AIIexp[imfΓ(1+α/2)(x-x0)22ℏfεα/2]×ψII(x0,t)dx0.
Changing the variable in the integrals from x0 to η=x-x0 as before and introducing two constants
(38)aI=mfΓ2(1+α/2)2iℏ,aII=mfΓ(1+α/2)2iℏf.
Equations (36) and (37) can be written as
(39)ψI(x,t+ε)=∫-∞∞1AIexp[-aIη2εα-1]ψI(x+η,t)dη,(40)ψII(x,t+ε)=∫-∞∞1AIIexp[-aIIη2εα/2]ψII(x+η,t)dη.
The left-hand sides of (39) and (40) can be expanded in fractional Taylor’s series [48] in time, with fractional derivative of order γ, and keeping only the lowest-order term in γ yields
(41)ψI,II(x,t+ε)=ψI,II(x,t)+0CDtγψI,II(x,t)εγΓ(γ+1)+⋯.
In the right-hand side a Taylor expansion with terms up to second order in η with respect to space can be carried out and the two cases will be considered separately. Thus, the equation for ψI(x,t) becomes
(42)ψI(x,t)+0CDtγψI(x,t)εγΓ(γ+1)=∫-∞∞1AIexp[-aIη2εα-1]×{ψI(x,t)+η∂ψI∂x+η22∂2ψI∂x2}dη.
On evaluating the integrals on the right-hand side of (42), the middle term with the first power of η vanishes. Equating the leading terms on both sides of (42) yieldsψ
I
(
x
,
t
)
=
(
1
/
A
I
)
π
ε
α
-
1
/
a
I
ψ
I
(
x
,
t
), requiring that AI=πεα-1/aI. Equation (42) reduces to
(43)ψI(x,t)+0CDtγψI(x,t)εγΓ(γ+1)={ψI(x,t)+14εα-1aI∂2ψI(x,t)∂x2}.
Equating the remaining terms requires that the powers of ε must be the same on both sides; that is, γ=α-1. Inserting the value of aI and simplifying (43) yield
(44)0CDtα-1ψI(x,t)=iℏ2mfΓ(α)Γ2(1+α/2)∂2ψI(x,t)∂x2.
Similarly, by expanding (40) the equation for ψII(x,t) becomes
(45)ψII(x,t)+0CDtγψII(x,t)εγΓ(γ+1)=∫-∞∞1AIIexp[-aIIη2εα/2]×{ψII(x,t)+η∂ψII∂x+η22∂2ψII∂x2}dη.
On evaluating the integrals on the right-hand side of (45) the middle term vanishes. Equating the leading terms on both sides of (45) as before yields for the normalizing factor AII=πεα/2/aII. Equation (45) reduces to
(46)ψII(x,t)+0CDtγψII(x,t)εγΓ(γ+1)={ψII(x,t)+14εα/2aII∂2ψII(x,t)∂x2}.
In the remaining terms, the powers of ε must be the same. This requires γ=α/2. Inserting the value of aII and simplifying (46) yield the equation for the wave function ψII(x,t):
(47)0CDtα/2ψII(x,t)=iℏf2mf∂2ψII(x,t)∂x2.
This completes the derivation based on the Feynman path integral method and (44) and (47) constitute the time fractional Schrodinger equations for a free particle corresponding to two ways of defining the action integral for a fractional dynamical system. In the limit α→2, the fractional dynamical system goes over to the regular Newtonian system and in this case both (44) and (47) reduce to
(48)∂ψ(x,t)∂t=iℏ2m∂2ψ(x,t)∂x2
given earlier, thus recovering the standard Schrodinger equation for a free quantum particle [49].It should be noted that sinceα≤2, with α=2 being the limiting case, the order of the time fractional derivative is ≤1 in both (44) and (47) and cannot exceed 1. This means the time fractional Schrodinger equation as derived from the path integral method always corresponds to the “subdiffusion” case in contrast to the case where the TFSE is obtained by a simple replacement of the first-order time derivative by a fractional order derivative [19]. Furthermore, the order α/2 of the fractional derivative corresponds to the first-order regular derivative as has been used above in Section 3. Thus it appears that the second method of defining the action leading to (47) is the natural way to generalize to TFSE. In appearance also it is as if the equation has been obtained by replacing all quantities in the Schrodinger equation by an equivalent fractional quantity, except the space derivative. Furthermore, (44) becomes a fractional order integro-differential equation when α<1 and no longer just a fractional order differential equation. Because of these reasons, it is considered the method of choice to use (47) as the TFSE derived from the path integral method and no further reference will be made to (44).The coefficient of the space derivative term in (47) has the dimension [L2/Tα/2], corresponding to the fractional diffusion coefficient. Thus (47) can be considered a time fractional diffusion equation with an imaginary fractional diffusion coefficient, just as (48), the regular Schrodinger equation, can be considered to be a diffusion equation with an imaginary diffusion coefficient. Thus all the mathematical machinery of time fractional diffusion theory [5, 50–59] can be imported advantageously.Although it is possible to introduce additional parameters and cast (47) in a dimensionless form, it has not been done here. However, for convenience, the subscript II is dropped from the wave function; a simplified notation for the Caputo derivative, ∂tβψ, with β=α/2 will be used. Naturally, 0<β≤1, and β→1 yields the regular first-order time derivative, denoted by ∂t. After incorporating these changes and defining a new constant Df=ℏf/2mf, (47) becomes
(49)∂tβψ(x,t)=iDf∂2ψ(x,t)∂x2(0<β≤1).Equation (49) can be solved by a combination of the Fourier and Laplace transform methods [52–54].
## 5. Probability Current and the Continuity Equation
The probability densityρ is defined by ρ=ψ*ψ=ψψ*. The complex conjugate wave function satisfies
(50)∂tβψ*(x,t)=-iDf∂2ψ*(x,t)∂x2.
There is an identity satisfied by the Caputo derivative [5]
(51)∂t1-β∂tβf(t)=∂tf(t),
where the right-hand side represents the regular first-order derivative. This identity can be used in studying the time derivative of the probability density, given by
(52)∂tρ=∂t(ψψ*)=(∂tψ)ψ*+ψ(∂tψ*).
Inserting from (51) gives
(53)∂tρ=(∂t1-β∂tβψ)ψ*+ψ(∂t1-β∂tβψ*).
Substituting from (49) and (50), (53) yields
(54)∂tρ=(∂t1-β(iDf∂2ψ(x,t)∂x2))ψ*+ψ(∂t1-β(-iDf∂2ψ*(x,t)∂x2)).
Equation (54) can be rewritten after factoring out the constant and interchanging the order of space and time derivatives as
(55)∂tρ=iDf{(∂2∂x2∂t1-βψ)ψ*-ψ(∂2∂x2∂t1-βψ*)}.
Introducing a new function ψ~=∂t1-βψ, (55) can be written as
(56)∂tρ=iDf{(∂2∂x2ψ~)ψ*-ψ(∂2∂x2ψ~*)}.
Defining a probability current density given by
(57)Jx=-iDf[ψ~*∂ψ∂x-ψ∂ψ~*∂x],
equation (56) can be written as
(58)∂tρ+∂Jx∂x=0.
This is the time fractional version of the continuity equation. In the limit β→1, ψ~→ψ ψ~*→ψ* and (58) reproduce the continuity equation of standard quantum mechanics [49]. It may be noted that (58) differs from Naber’s result ((24) in [19]) and will be discussed later.
## 6. Solution for TFSE for a Free Particle
The solution for the TFSE for a free particle under the conditionsψ
(
x
,
0
)
=
ψ
0
(
x
); ψ(x,t)→0, |x|→∞, t>0 is available in the literature but considered here for purposes of obtaining the Green function for the TFSE.By applying the combined Fourier and Laplace transforms defined by(59)ψ~^(k,s)=12π∫-∞∞e-ikx[∫0∞e-stψ(x,t)dt]dx
equation (49) reduces to
(60)sβψ~^(k,s)-sβ-1ψ~(k,0)=-iDfk2ψ~^(k,s)
resulting in
(61)ψ~^(k,s)=ψ~(k,0)sβ-1sβ+iDfk2.Applying the inverse Laplace transform, (61) yields
(62)ψ~(k,t)=ψ~(k,0)Eβ,1(-iDfk2tβ)
in terms of the Mittag-Leffler function defined by a series or by the inverse Lapalce transform [3]:
(63)Eα,β(z)=∑n=0∞znΓ(αn+β)=L-1{sα-βsα-z}.The Green function solution can be written as(64)ψ(x,t)=∫-∞∞ψ(x-ξ)Gβ(ξ,t)dξ,
where the Green function is given by the inverse Fourier transform of the Mittag-Leffler function
(65)Gβ(x,t)=12π∫-∞∞eikxEβ,1(-iDfk2tβ)dk,
where the Mittag-Leffler function has been defined [3] before in (63).The Fourier inversion in (65) can be carried out [52–54] using the property that the Mittag-Leffler function is related through the Laplace integral to another special function of the Wright type denoted by
(66)Mβ(z)=W(-z;-β,1-β)=∑n=0∞(-z)nn!Γ(-βn+1-β)0<β<1,
where the Wright function is defined by [54]
(67)W(z;λ,μ)=∑n=0∞znn!Γ(λn+μ)λ>-1,μ∈C.
The Green function in (65) is then given by
(68)Gβ(x,t)=121iDftβ/2Mβ/2(|x|iDftβ/2).
In the context of fractional diffusion, the function Mβ/2(z) belongs to the Wright type of probability densities characterized by the similarity variable z=|x|/Dftβ/2, where Df is the fractional diffusion coefficient, with ∫0∞Mβ/2(z)dz=1. Furthermore, the probability densities are non-Markovian and exhibit a variance consistent with slow anomalous diffusion [49–51], σβ2(t)=(2/Γ(β+1))Dftβ.In the limit ofβ→1, the probability density function goes over to the Gaussian
(69)M1/2(z)=1πe-z2/4
corresponding to regular diffusion. A plot of the reduced probability density function is given in Figure 1.Figure 1
Reduced probability density function.The Green function for regular diffusion describes a probability density, whereas the corresponding Green function for the Schrodinger equation is the propagator, which describes the probability amplitude for the particle to propagate fromxa at ta to xb at tb. In exactly the same way, the Green function for time fractional diffusion describes a probability density, whereas the Green function in (68) is the fractional propagator and gives the probability amplitude. Of particular interest is the Fourier component of the wave function in (62) in connection with the total probability as t→∞; the case discussed by Naber [19] and will be discussed in the next section.
## 7. Comments about Some Results in Naber’s Work [19]
This section draws attention to some errors in Naber’s paper which have gone unnoticed and have been reproduced repeatedly. Naber’s equations will be referred to by their number and a prefix N. Naber explicitly states that he uses the Caputo derivative, which has been defined earlier in (25) in this paper. Although Naber does not give the explicit definition of the Caputo fractional derivative in his paper [19], it can be inferred from (NA.3) given in the appendix to his paper.(a) However, Naber writes in (N16) for a Caputo derivative of order (1-ν), reproduced here for convenience in (70):
(70)Dt1-νψ(t,x)=1Γ(1-ν)×∫0tdψ(τ,x)dτdτ(t-τ)ν(0<ν<1).
This is incorrect, as can be checked easily by taking the limit ν→1. The left-hand side →ψ(t,x) as the derivative of zero order, but the right-hand side →0 because of the Γ function in the denominator. The correct form of equation is
(71)Dt1-νψ(t,x)=1Γ(ν)∫0tdψ(τ,x)dτdτ(t-τ)1-ν.
As a consequence, the weight factor in (N18) should be (t-τ)1-ν and not (t-τ)-ν, which Naber uses to give a physical significance to the entity he has introduced. The correct weight factor in (N18) would →1 in the limit ν→1.(b) In (N11), Naber gives an identity satisfied supposedly by fractional Caputo derivatives of order less than 1, reproduced here for convenience in (72).
(72)Dt1-νDtνy(t)=dydt-[Dtνy(t)]t=0t1-νΓ(ν).
This identity is not correct and cannot be found anywhere. The identity satisfied by the Caputo derivatives is given in [5] and reproduced later in the current notation for ν<1(73)Dt-νDtνy(t)=y(t)-y(0).
This yields Dt1-νDtνy(t)=dy/dt=∂ty(t) and has been used earlier in (52) in this paper.The incorrect identity has been used by Naber to derive an equation for the probability current, which is obviously incorrect. Unfortunately, the incorrect identity, as given by Naber, in (72) has been repeatedly used in the literature. The correct equation for the probability current has been given in this paper in (59), which reduces to the standard continuity equation for the probability current in regular quantum mechanics [49].(c) This point concerns the separation of the Mittag-Leffler function with an imaginary argument into an oscillatory part and a part which decays exponentially with time. There is nothing wrong with the derivation itself as given by Naber, and the function under discussion is the Fourier component of the free particle wave function, in his notation(74)Ψ=Ψ0Eν(ω(-it)ν),
where Eν(z) in Naber’s notation corresponds to the Mittag-Leffler function Eν,1(z) defined in (63).The Mittag-Leffler function with the complex argument has been separated into an oscillatory part and a part based on the evaluation of the inverse Laplace transform(75)A(t)=12πi∫γ-i∞γ+i∞estsν-1A0dssν-σiν
along a Hankel contour and considering the contribution from the residue of the pole s0=σ1/νi together with the contribution from the integral along the two strips on either side of the branch cut, which is a standard procedure. Naber finally gives the solution as
(76)Ψ=Ψ0{e-iω1/νtν-Fν(ω(-i)ν,t)}.
He argues that in the limit of t→∞ the total probability arises basically from the first term and is equal to 1/ν2, assuming that the wave function was initially normalized. Since ν<1, the total probability is >1, a result difficult to understand physically. However, it is shown later that the solution derived in this paper yields a probability that →0 in the limit t→∞.The solution corresponding to (74) is given by (62) in this paper. The separation into two parts corresponding to (76) can be carried out by considering the inverse Laplace transform of (61):
(77)ψ~(k,t)=12πi∫γ-i∞γ+i∞estsβ-1ψ~(k,0)dssβ+iDfk2.
As usual, the Bromwich contour is replaced by the Hankel contour. The two contributions arise from (i) the residue at the pole at s0=(Dfk2)1/β(-i)1/β and (ii) the integral along the two strips from 0 to -∞ introduced along the branch cut. The latter yields a contribution which decays in time just as the second term in Naber’s equation (76). The contribution from the residue is given by
(78)Residueψ~(k,0)=e(-i)1/β(Dfk2)1/βtβ
and corresponds to the first term on the right-hand side in (76). However,
(79)(-i)1/β=(e-iπ/2)1/β=(e-iπ/2β)=(cosπ2β-isinπ2β).
Therefore, (78) yields
(80)ψ~(k,t)ψ~(k,0)=Residueψ~(k,0)=et(Dfk2)1/βcos(π/2β)e-it(Dfk2)1/βsin(π/2β).
The right-hand side of (80) has an amplitude term and an oscillatory factor. Because β<1, cos(π/2β) is negative, the amplitude factor decays in time exponentially and →0 in the limit t→∞. Thus the contribution from the residue due to the pole also →0. Thus the entire wave function →0 in the limit of t→∞, so does the probability density. Hence the total probability also →0, in contrast to Naber’s result.The question naturally arises why there is this difference in the two results, both of which are concerned with the Mittag-Leffler functions with complex arguments. The reason appears to be that in Naber’s case, the pole occurs ats0=σ1/νi, whereas in the present paper, the pole occurs (using the same notation as Naber) at s0=σ1/ν(-i)1/ν. The simple i in Naber’s case leads to the purely oscillatory solution and hence to the result of the probability being greater than unity. In our paper the imaginary number raised to the fractional power leads to the exponentially decaying solution and hence leads to the correct limit when t→∞, namely, zero total probability. Naber’s result is a direct consequence of his choice to raise the power of the imaginary number i to the fractional power, so as to incorporate a Wick rotation. However, as had been indicated earlier, this imaginary number cannot be arbitrarily altered as it is connected with the phase factor iS/ℏ in the Feynman propagator. If it is necessary to include a Wick rotation, the power of i should be changed to ν+1 in Naber’s equation (N9) instead of just ν. If this is done, the total probability would properly →0 in the limit t→∞. If this is done, then the TFSE can be interpreted as the analytic continuation of the fractional diffusion equation, just as the regular Schrodinger equation can be considered as the analytic continuation of the regular diffusion equation.
## 8. TFSE for a Particle in a Potential Field
So far attention has been focused on a free particle. These considerations can be easily extended to the case of a particle moving in a potential field by incorporating a potential termV(x,t) in the Lagrangian L=T-V. This will necessitate incorporating an additional term -V(x,t)εα/2/Γ(1+α/2) in the right-hand side of (35) and an additional factor -(i/hf)(V(x,t)εα/2/Γ(1+α/2)) in the exponential in (37). This results in changing (45) into
(81)ψII(x,t)+0CDtβψII(x,t)εβΓ(β+1)=∫-∞∞1AIIexp[-aIIη2εα/2]{1-ihfV(x,t)εα/2Γ(1+α/2)}×{ψII(x,t)+η∂ψII∂x+η22∂2ψII∂x2}dη.Equation (47) then becomes
(82)0CDtα/2ψII(x,t)=iℏf2mf∂2ψII(x,t)∂x2-ihfV(x,t)ψ(x,t).
Multiplying both sides by -ℏf/i results in the FTSE for a particle in a potential field as
(83)iℏf∂tβψ(x,t)=-ℏf22mf∂2ψ(x,t)∂x2-V(x,t)ψ(x,t)
which reduces to the standard Schrodinger equation of quantum mechanics:
(84)iℏ∂ψ∂t=-ℏ22m∂2ψ∂x2+Vψ.
One final remark needs to be made concerning the use of the Planck units for casting the TFSE in terms of dimensionless quantities. After the derivation, the FTSE in (83) can be cast in dimensionless quantities; however, the appropriate fractional Planck units must be defined to take care of the fractional quantities involved in (83).
## 9. Discussion and Conclusions
The TFSE has been derived using the Feynman path integral technique for a nonrelativistic particle. As expected the TFSE looks like a time fractional diffusion equation with an imaginary fractional diffusion constant but pertains to the realm of subdiffusion only, in contrast to Naber’s generalization which includes superdiffusion as well. This is understandable because the case considered in this paper pertains to the nonrelativistic case. Relativistic considerations would have to be included for the superdiffusion case, which would lead to the Klein-Gordon equation in the integer order limit. In adapting the Feynman method, it is shown that it is preferable to introduce the actionS as a fractional time integral of the Lagrangian and that it is necessary to introduce a “fractional Planck constant.” In the limit of integer order, the regular action S, the regular Schrodinger equation, and the regular Planck constant are all recovered. It may be of interest to note that there is a fractional Planck constant implied in Naber’s work also, although it is not explicitly so stated. His equations are rendered nondimensional by using the Planck units of mass, length, and time and then generalized to fractional derivatives after including a Wick rotation. This implies a change of variable of time t→it so that the imaginary number is raised to the same power as the order of the fractional time derivative involved. However, the Planck units may not be the appropriate quantities as the equations involve quantities of fractional dimension and the equations must be made nondimensional after the generalization to fractional derivatives and not before. A fractional Planck constant does show up in Naber’s treatment as well, as the ratio of masses m/Mp [31, 32].A number of errors in Naber’s work have been corrected. The correct continuity equation for the probability current is derived and the Green function solution for a free particle is given. The Green function is given in terms of a special type of function, the M-Wright function, which is used extensively in studies of time fractional subdiffusion studies. In the context of time fractional diffusion, the M-Wright function is a probability density function in time, which is non-Markovian and goes over to the Gaussian in the nonfractional limiting case. In the context of TFSE, the M-Wright function gives the propagator, which is a probability amplitude. Probability considerations are accounted for by the usual process of squaring of the amplitude. In particular, it is shown that Naber’s result that the total probability is greater than unity in the long-time limit is a spurious result arising out of the operation of arbitrarily raising of the imaginary numberi to the power of the same degree as the fractional time derivative invoking a Wick rotation. It is shown that such arbitrary change of the imaginary number cannot be carried out as the imaginary number i is connected with the phase of the action S in the path integral contribution. However, if we desired to consider a Wick rotation, it should be included as an additional increase of the index of the power of the imaginary number. The TFSE for a particle moving in a potential field is also derived. Furthermore, it is suggested that even in studies of fractional classical mechanics, such as those using variational methods, the action integral be expressed as a time fractional integral of the Lagrangian. Further extensions including the solutions to particle subject to different potentials are underway.
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*Source: 290216-2013-07-28.xml* | 2013 |
# Global Path Planning for Unmanned Surface Vehicle Based on Improved Quantum Ant Colony Algorithm
**Authors:** Guoqing Xia; Zhiwei Han; Bo Zhao; Caiyun Liu; Xinwei Wang
**Journal:** Mathematical Problems in Engineering
(2019)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2019/2902170
---
## Abstract
As a tool to monitor marine environments and to perform dangerous tasks instead of manned vessels, unmanned surface vehicles (USVs) have extensive applications. Because most path planning algorithms have difficulty meeting the mission requirements of USVs, the purpose of this study was to plan a global path with multiple objectives, such as path length, energy consumption, path smoothness, and path safety, for USV in marine environments. A global path planning algorithm based on an improved quantum ant colony algorithm (IQACA) is proposed. The improved quantum ant colony algorithm is an algorithm that benefits from the high efficiency of quantum computing and the optimization ability of the ant colony algorithm. The proposed algorithm can plan a path considering multiple objectives simultaneously. The simulation results show that the proposed algorithm’s obtained minimum was 2.1–6.5% lower than those of the quantum ant colony algorithm (QACA) and ant colony algorithm (ACA), and the number of iterations required to converge to the minimum was 11.2–24.5% lower than those of the QACA and ACA. In addition, the optimized path for the USV was obtained effectively and efficiently.
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## Body
## 1. Introduction
An unmanned surface vehicle (USV) is a kind of autonomous marine vehicle. Determining the path of a USV is an important problem associated with its safety and efficiency [1]. Depending on whether the environmental information is obtained from a digital map or sensors, path planning is divided into global and local stages [2]. In this paper, a USV global path planning study is presented. Global path planning is the process of planning a path to connect the starting and destination points under a given planning space from a digital map and constraints according to the mission requirements. The indices for evaluating a path can be path length, energy consumption, path smoothness, and path safety.Obtaining a short path from the starting point to the destination point is one of the main objectives of global path planning. Planning the shortest path is an NP-hard problem [3]. Existing methods take the path length as a single objective of the path planning, and neither energy consumption nor other indices are considered.The energy consumption during sailing determines the USV’s endurance and the duration of the mission. Since the environmental loads such as wind, waves, and ocean currents influence the performance of the USV, the calculation of the USV’s energy consumption is complex. Niu et al. [4] considered the effect of the ocean current on the energy consumption of USVs. Lee et al. [5] found a more economical path by considering the shallow water effect as well as tidal currents and wind for surface ship navigation. Most calculations of energy consumption have considered the effects of ocean currents on the USV without considering wind and waves.The smoothness of a path depends on the size and number of the turns that the USV makes while sailing along the planned path. The smoother path allows the USV to make fewer turns along the path, which reduces the mechanical wear on the steering actuators, such as rudders. Smooth paths can reduce unnecessary curvature discontinuities and possible stops. In a previous report [6], the smoothness of a path was evaluated by summing the angles of each turn on the path that the vehicle follows. Ma et al. [7] evaluated the turn angle set by adopting the maximum value of the turn angle set to assess the path smoothness for the USV.Obstacles such as islands and reefs affect the safety of the USV. Path safety means that the USV cannot collide with any obstacles while sailing. Ma et al. [7] used circles that just covered the obstacles to identify the safe area.Since USV global path planning involves optimization algorithms, environmental models, and marine craft hydrodynamics, existing path planning algorithms have difficulty meeting the mission requirements. Intelligent optimization algorithms are widely used in global path planning, such as the genetic algorithm [8], particle swarm algorithm [9], NSGA-II [10], and ant colony algorithm [11]. With the development of quantum technology, the idea of combining quantum computing with intelligent optimization algorithms has been developed. Narayanan and Moore combined quantum mechanics principles and evolutionary computing methods for the first time [12]. A quantum bit and superposition of states were proposed to solve the knapsack problem by a quantum-inspired evolutionary algorithm (QEA) [13]. Based on the QEA with a quantum rotation gate strategy, an adaptive evolution-based quantum-inspired evolutionary algorithm (AEQEA) introduces an adaptive evolution mechanism [14]. A new improved quantum evolution algorithm (IQEA) with a mixed local search procedure was proposed [15]. Li et al. [16] proposed a quantum ant colony algorithm (QACA) that combined quantum computing and the ant colony algorithm for continuous space optimization. You et al. [17] proposed a novel parallel ant colony optimization algorithm based on a quantum dynamics mechanism (PQACO). An improved quantum ant colony algorithm was proposed for the optimization of evacuation paths from dangerous areas to safe areas [18]. The quantum ant colony algorithm was used to determine campus path navigation [19].In this paper, a global path planning algorithm for USV based on the improved quantum ant colony algorithm (IQACA) is proposed. The main contributions of the proposed approach are as follows:(1)
At present, most USV global path planning algorithms only search for a feasible path for one objective [3–6]. In this paper, path planning was considered with multiple simultaneous objectives, which were path length, energy consumption, path smoothness, and path safety.(2)
The IQACA is a new optimization algorithm that combines quantum-inspired computing with the ant colony algorithm (ACA). The quantum bit (Q-bit) is used to encode the pheromone in the ACA to obtain the quantum pheromone, and the ant movement is determined based on the concentration of the quantum pheromone on the path. Compared to the existing QACA [16–19], the phase of the quantum ant colony is transformed by an adaptive quantum rotation gate, and the quantum pheromone is updated by local and global update rules in the IQACA.Simulation experiments in a complex environment with wind, waves, and ocean currents verified the effectiveness of the objective model, and we obtained a desired path based on the IQACA.The paper is organized as follows. In Section2, the USV path planning problem is established, and the USV kinetic model, environmental loads, and cost function of the path planning are described. In Section 3, the principles of the IQACA are provided, and we apply the IQACA to USV global path planning. In Section 4, the simulations for USV global path planning using the IQACA are presented. Conclusions are provided in Section 5.
## 2. Problem Statement
### 2.1. USV Kinetic Model
The kinetic model of a USV accounts for the forces, such as the control force and environmental loads, which cause USV motion. For the USV, the control force is mainly the thrust of each propeller. The environmental loads on the USV are generated by wind, waves, and ocean currents. The kinetic model of the USV, which was proposed previously [20], is as follows:(1)Mν˙+Cνν+Dνν=τenv+τthr(2)τenv=τwind+τwave+τcurrentwhere M is the system inertia matrix, C(ν) is the Coriolis-centripetal matrix, D(ν)∈R3×3 is damping matrix. τwind, τwave, and τcurrent are wind, wave, and ocean current forces acting on the USV, respectively, and τthr is the thrust generated by the USV propulsion system. The generalized velocity ν=[u,v,r]T is obtained by (1), where the first two components (u,v) are the linear velocities of the surge and sway, and r is the angular velocity of the yaw.
### 2.2. Models of Environmental Loads
When planning a global path for USVs, it is necessary to consider the environmental effects on the vehicles. Thus, we need to analyze the impacts of wind, waves, and ocean currents on the USV. The planned area is a confined sea with some static obstacles, and the mission execution time is short. Therefore, it can be assumed that the environmental loads are basically stable in limited time and space.
#### 2.2.1. Wind Forces
The wind acts directly on the superstructure of the hull. As reported previously [21], the wind forces are written as follows:(3)τwindX=12ρaAfVw2CwxαRτwindY=12ρaAsVw2CwyαRτwindN=12ρaAsVw2CwnαR·Lwhere ρa is the density of air, Af and As are the frontal and lateral projected areas, Cwx(αR), Cwy(αR), and Cwn(αR) are the empirical force coefficients, αR is the angle between the wind and the heading of the vessel, L is the length of the vessel, Vw is the relative wind speed, and τwindX, τwindY, and τwindN are the wind forces during the surge, sway, and yaw, respectively [22].
#### 2.2.2. Wave Forces
When a vehicle is sailing on the sea, the interference of wave forces is complicated. The wave forces acting on the hull are first- and second-order wave forces. The second-order wave forces, which impact the heading and path of the USV, are proportional to the square of the wave height [22]. The wave forces are simplified as follows:(4)τwaveX=Kw1ss2+2λ1ωe1s+ωe12w1+d1τwaveY=Kw2ss2+2λ2ωe2s+ωe22w2+d2τwaveN=Kw3ss2+2λ3ωe3s+ωe32w3+d3where wi(i=1,2,3) are Gaussian white noise processes, and τwaveX, τwaveY, and τwaveN are the wave forces during the surge, sway, and yaw, respectively. The amplitudes of τwaveX, τwaveY, and τwaveN are adjusted by choosing the constants Kwi(i=1,2,3), while the spectra are parameterized in terms of the pairs λi and ωei(i=1,2,3). The wave drift forces di(i=1,2,3) are usually modeled as slowly varying bias terms:(5)d˙1=w4d˙2=w5d˙3=w6where wi(i=4,5,6) are Gaussian white noise processes [22].
#### 2.2.3. Ocean Current Forces
The ocean currents cause vessels sailing on the sea to change their positions and postures. The ocean current forces are given as follows:(6)τcurrentX=12ρAfVc2CXβτcurrentY=12ρAsVc2CYβτcurrentN=12ρAsVc2CNβ·Lwhere ρ is the density of the seawater, Af and As are the frontal and lateral projected areas below the waterline, respectively, CX, CY, and CN are the empirical force coefficients, Vc is the relative current speed, β is the angle between the ocean current and the heading of the vessel, L is the length of the vessel, and τcurrentX, τcurrentY, and τcurrentN are the ocean current forces during surge, sway, and yaw, respectively [22].
### 2.3. Path Representation by Grids
The real task area is partitioned to reduce the modeling complexity. Visibility graphs [23], Voronoi diagrams [24], and grid maps [25] are the most commonly used path planning algorithms. The grid map-based path planning algorithm is powerful in that it generates a path with the shortest computation time [25]. To facilitate the calculation, the planned path is represented on grids. The area under consideration is discretized into grids. The information, such as the relative speed and direction of the wind, the amplitude and direction of the waves, the relative speed and direction of ocean current, and the position of the obstacles, is discretized in each grid. Stationary obstacles are encoded in a binary format on the grids. We assigned weights of 1 to all obstacle grids and weights of 0 to all free neighbor grids of them.
### 2.4. Objectives of USV Global Path Planning
Since USV global path planning is a multiobjective optimization problem, we should analyze the interrelated objectives and discuss the importance of each objective based on the requirements of the mission. A cost function can be constructed as a weighted sum of the objective functions. Finally, the cost function is used to evaluate the quality of the planned path.
#### 2.4.1. Path Length
Since the task area is modeled by grids, the planned path is represented on a rectangular grid. The path passes the centers of the grids. Thus, the distanceLi,i+1 between two adjacent waypoints pi=(xi,yi) and pi+1=(xi+1,yi+1) is equal to the Euclidean distance between the centers of the grids as follows:(7)Li,i+1=1,xi=xi+1oryi=yi+12,otherwiseThe positions ofpi and pi+1 are shown in Figure 1. If pi and pi+1 are adjacent in the horizontal or vertical direction, Li,i+1=1. If pi and pi+1 are adjacent in the diagonal direction, Li,i+1=2.Figure 1
The positions ofpi and pi+1.Therefore, the total length of the pathL is the sum of the distances between the adjacent waypoints:(8)L=∑i=1mLi,i+1where m is the number of path segments.
#### 2.4.2. Energy Consumption
In this paper, the energy consumption of the USV while sailing is derived from the propulsion system. Thus,E is the sum of the energy consumption of each segment along the entire path:(9)E=∑i=1mEi,i+1Supposing that the USV is sailing at a constant velocity betweenpi and pi+1, the energy consumption Ei,i+1 between pi and pi+1 equals the work done by the propulsion system to overcome the environmental loads, such that(10)Ei,i+1=τenv·v→usv·twhere t is the time for the USV to sail in Li,i+1.(11)t=Li,i+1v→outwhere v→usv is the magnitude of the velocity v→usv generated by the USV propulsion system, τenv is the resultant force of the environmental loads, and v→out is the magnitude of the velocity v→out of the USV moving in the horizontal plane. Since the headings of the USV in the grid are several fixed values, as shown in Figure 1, the angular velocity r caused by the yaw motion can be ignored when solving v→out. Hence, v→out is equal to(12)v→out=u2+v2where u and v are obtained by (1).It is known from (10) and (11) that the energy consumption is proportional to v→usv and 1/v→out, when the thrust τthr generated by the propulsion system is a fixed value. To reduce the energy consumption, it is necessary to adjust the USV’s heading to take advantage of the environmental loads to increase v→out.
#### 2.4.3. Path Smoothness
It is assumed that the current waypoint of the USV ispi=(xi,yi), the previous waypoint is pi-1=(xi-1,yi-1), and the next waypoint is pi+1=(xi+1,yi+1). Thus, the angle θi+1 of the vector pipi+1→ and the angle θi of the vector pi-1pi→ are(13)θi+1=arctanyi+1-yixi+1-xi(14)θi=arctanyi-yi-1xi-xi-1The differenceψi between θi+1 and θi is(15)ψi=absθi+1-θiθ i, θi+1, and ψi, are shown in Figure 2. Therefore, the cost function of the path smoothness Jsmooth is(16)Jsmooth=∑i=1Nψiwhere N is the number of differences ψi.Figure 2
The angles of the path segments.
#### 2.4.4. Path Safety
Using the safety cost of the nodes on the grids cannot accurately represent the threat impact of each path segment. First, three sampling points are selected on a path segment and the average Euclidean distance between the three sampling points and the center of the obstacle is calculated. The schematic diagram of the calculation of the path safety is shown in Figure3. lk is the length of the kth path segment between the waypoint pi and pi+1. For the kth path segment, three sampling points are taken at lk/6, lk/2, and 5lk/6, respectively. The average Euclidean distance between the three sampling points and the center of the obstacle is(17)DT,k=13dT,kjlk6+dT,kjlk2+dT,kj5lk6where dT,kj() is the Euclidean distance from the sampling point on the kth path segment to the center of the obstacle Tj.Figure 3
Schematic diagram of the calculation of the path safety.The path safety cost between waypointpi and pi+1 denoted as Jsafei,i+1 is(18)Jsafei,i+1=0,d>dsafe_max1DT,ki,i+1,dsafe_min≤d≤dsafe_max1,d<dsafe_minwhere d is the distance between the USV and the obstacle’s center, dsafe_max is the radius of the obstacle’s affected area, and dsafe_min is the radius of the no-sail zone. JT,ki,i+1 is obtained using (17).Thus, the entire path safety cost functionJsafe is(19)Jsafe=∑i=1NJsafei,i+1where N is the number of the waypoints of the planned path.
#### 2.4.5. Cost Function
In summary, the cost function of the USV global path planning was established as(20)minJ=w1·L+w2·E+w3·Jsmooth+w4·Jsafewhere L, E, Jsmooth, and Jsafe are obtained by (8), (9), (16), and (19), respectively. w1, w2, w3, and w4 represent the weights of the path length, energy consumption, path smoothness, and path safety in the cost function, respectively, subject to(21)L≤Lmax0≤v→out≤vmaxwhere Lmax is the maximum voyage distance of the USV and vmax is the maximum speed of the USV.
## 2.1. USV Kinetic Model
The kinetic model of a USV accounts for the forces, such as the control force and environmental loads, which cause USV motion. For the USV, the control force is mainly the thrust of each propeller. The environmental loads on the USV are generated by wind, waves, and ocean currents. The kinetic model of the USV, which was proposed previously [20], is as follows:(1)Mν˙+Cνν+Dνν=τenv+τthr(2)τenv=τwind+τwave+τcurrentwhere M is the system inertia matrix, C(ν) is the Coriolis-centripetal matrix, D(ν)∈R3×3 is damping matrix. τwind, τwave, and τcurrent are wind, wave, and ocean current forces acting on the USV, respectively, and τthr is the thrust generated by the USV propulsion system. The generalized velocity ν=[u,v,r]T is obtained by (1), where the first two components (u,v) are the linear velocities of the surge and sway, and r is the angular velocity of the yaw.
## 2.2. Models of Environmental Loads
When planning a global path for USVs, it is necessary to consider the environmental effects on the vehicles. Thus, we need to analyze the impacts of wind, waves, and ocean currents on the USV. The planned area is a confined sea with some static obstacles, and the mission execution time is short. Therefore, it can be assumed that the environmental loads are basically stable in limited time and space.
### 2.2.1. Wind Forces
The wind acts directly on the superstructure of the hull. As reported previously [21], the wind forces are written as follows:(3)τwindX=12ρaAfVw2CwxαRτwindY=12ρaAsVw2CwyαRτwindN=12ρaAsVw2CwnαR·Lwhere ρa is the density of air, Af and As are the frontal and lateral projected areas, Cwx(αR), Cwy(αR), and Cwn(αR) are the empirical force coefficients, αR is the angle between the wind and the heading of the vessel, L is the length of the vessel, Vw is the relative wind speed, and τwindX, τwindY, and τwindN are the wind forces during the surge, sway, and yaw, respectively [22].
### 2.2.2. Wave Forces
When a vehicle is sailing on the sea, the interference of wave forces is complicated. The wave forces acting on the hull are first- and second-order wave forces. The second-order wave forces, which impact the heading and path of the USV, are proportional to the square of the wave height [22]. The wave forces are simplified as follows:(4)τwaveX=Kw1ss2+2λ1ωe1s+ωe12w1+d1τwaveY=Kw2ss2+2λ2ωe2s+ωe22w2+d2τwaveN=Kw3ss2+2λ3ωe3s+ωe32w3+d3where wi(i=1,2,3) are Gaussian white noise processes, and τwaveX, τwaveY, and τwaveN are the wave forces during the surge, sway, and yaw, respectively. The amplitudes of τwaveX, τwaveY, and τwaveN are adjusted by choosing the constants Kwi(i=1,2,3), while the spectra are parameterized in terms of the pairs λi and ωei(i=1,2,3). The wave drift forces di(i=1,2,3) are usually modeled as slowly varying bias terms:(5)d˙1=w4d˙2=w5d˙3=w6where wi(i=4,5,6) are Gaussian white noise processes [22].
### 2.2.3. Ocean Current Forces
The ocean currents cause vessels sailing on the sea to change their positions and postures. The ocean current forces are given as follows:(6)τcurrentX=12ρAfVc2CXβτcurrentY=12ρAsVc2CYβτcurrentN=12ρAsVc2CNβ·Lwhere ρ is the density of the seawater, Af and As are the frontal and lateral projected areas below the waterline, respectively, CX, CY, and CN are the empirical force coefficients, Vc is the relative current speed, β is the angle between the ocean current and the heading of the vessel, L is the length of the vessel, and τcurrentX, τcurrentY, and τcurrentN are the ocean current forces during surge, sway, and yaw, respectively [22].
## 2.2.1. Wind Forces
The wind acts directly on the superstructure of the hull. As reported previously [21], the wind forces are written as follows:(3)τwindX=12ρaAfVw2CwxαRτwindY=12ρaAsVw2CwyαRτwindN=12ρaAsVw2CwnαR·Lwhere ρa is the density of air, Af and As are the frontal and lateral projected areas, Cwx(αR), Cwy(αR), and Cwn(αR) are the empirical force coefficients, αR is the angle between the wind and the heading of the vessel, L is the length of the vessel, Vw is the relative wind speed, and τwindX, τwindY, and τwindN are the wind forces during the surge, sway, and yaw, respectively [22].
## 2.2.2. Wave Forces
When a vehicle is sailing on the sea, the interference of wave forces is complicated. The wave forces acting on the hull are first- and second-order wave forces. The second-order wave forces, which impact the heading and path of the USV, are proportional to the square of the wave height [22]. The wave forces are simplified as follows:(4)τwaveX=Kw1ss2+2λ1ωe1s+ωe12w1+d1τwaveY=Kw2ss2+2λ2ωe2s+ωe22w2+d2τwaveN=Kw3ss2+2λ3ωe3s+ωe32w3+d3where wi(i=1,2,3) are Gaussian white noise processes, and τwaveX, τwaveY, and τwaveN are the wave forces during the surge, sway, and yaw, respectively. The amplitudes of τwaveX, τwaveY, and τwaveN are adjusted by choosing the constants Kwi(i=1,2,3), while the spectra are parameterized in terms of the pairs λi and ωei(i=1,2,3). The wave drift forces di(i=1,2,3) are usually modeled as slowly varying bias terms:(5)d˙1=w4d˙2=w5d˙3=w6where wi(i=4,5,6) are Gaussian white noise processes [22].
## 2.2.3. Ocean Current Forces
The ocean currents cause vessels sailing on the sea to change their positions and postures. The ocean current forces are given as follows:(6)τcurrentX=12ρAfVc2CXβτcurrentY=12ρAsVc2CYβτcurrentN=12ρAsVc2CNβ·Lwhere ρ is the density of the seawater, Af and As are the frontal and lateral projected areas below the waterline, respectively, CX, CY, and CN are the empirical force coefficients, Vc is the relative current speed, β is the angle between the ocean current and the heading of the vessel, L is the length of the vessel, and τcurrentX, τcurrentY, and τcurrentN are the ocean current forces during surge, sway, and yaw, respectively [22].
## 2.3. Path Representation by Grids
The real task area is partitioned to reduce the modeling complexity. Visibility graphs [23], Voronoi diagrams [24], and grid maps [25] are the most commonly used path planning algorithms. The grid map-based path planning algorithm is powerful in that it generates a path with the shortest computation time [25]. To facilitate the calculation, the planned path is represented on grids. The area under consideration is discretized into grids. The information, such as the relative speed and direction of the wind, the amplitude and direction of the waves, the relative speed and direction of ocean current, and the position of the obstacles, is discretized in each grid. Stationary obstacles are encoded in a binary format on the grids. We assigned weights of 1 to all obstacle grids and weights of 0 to all free neighbor grids of them.
## 2.4. Objectives of USV Global Path Planning
Since USV global path planning is a multiobjective optimization problem, we should analyze the interrelated objectives and discuss the importance of each objective based on the requirements of the mission. A cost function can be constructed as a weighted sum of the objective functions. Finally, the cost function is used to evaluate the quality of the planned path.
### 2.4.1. Path Length
Since the task area is modeled by grids, the planned path is represented on a rectangular grid. The path passes the centers of the grids. Thus, the distanceLi,i+1 between two adjacent waypoints pi=(xi,yi) and pi+1=(xi+1,yi+1) is equal to the Euclidean distance between the centers of the grids as follows:(7)Li,i+1=1,xi=xi+1oryi=yi+12,otherwiseThe positions ofpi and pi+1 are shown in Figure 1. If pi and pi+1 are adjacent in the horizontal or vertical direction, Li,i+1=1. If pi and pi+1 are adjacent in the diagonal direction, Li,i+1=2.Figure 1
The positions ofpi and pi+1.Therefore, the total length of the pathL is the sum of the distances between the adjacent waypoints:(8)L=∑i=1mLi,i+1where m is the number of path segments.
### 2.4.2. Energy Consumption
In this paper, the energy consumption of the USV while sailing is derived from the propulsion system. Thus,E is the sum of the energy consumption of each segment along the entire path:(9)E=∑i=1mEi,i+1Supposing that the USV is sailing at a constant velocity betweenpi and pi+1, the energy consumption Ei,i+1 between pi and pi+1 equals the work done by the propulsion system to overcome the environmental loads, such that(10)Ei,i+1=τenv·v→usv·twhere t is the time for the USV to sail in Li,i+1.(11)t=Li,i+1v→outwhere v→usv is the magnitude of the velocity v→usv generated by the USV propulsion system, τenv is the resultant force of the environmental loads, and v→out is the magnitude of the velocity v→out of the USV moving in the horizontal plane. Since the headings of the USV in the grid are several fixed values, as shown in Figure 1, the angular velocity r caused by the yaw motion can be ignored when solving v→out. Hence, v→out is equal to(12)v→out=u2+v2where u and v are obtained by (1).It is known from (10) and (11) that the energy consumption is proportional to v→usv and 1/v→out, when the thrust τthr generated by the propulsion system is a fixed value. To reduce the energy consumption, it is necessary to adjust the USV’s heading to take advantage of the environmental loads to increase v→out.
### 2.4.3. Path Smoothness
It is assumed that the current waypoint of the USV ispi=(xi,yi), the previous waypoint is pi-1=(xi-1,yi-1), and the next waypoint is pi+1=(xi+1,yi+1). Thus, the angle θi+1 of the vector pipi+1→ and the angle θi of the vector pi-1pi→ are(13)θi+1=arctanyi+1-yixi+1-xi(14)θi=arctanyi-yi-1xi-xi-1The differenceψi between θi+1 and θi is(15)ψi=absθi+1-θiθ i, θi+1, and ψi, are shown in Figure 2. Therefore, the cost function of the path smoothness Jsmooth is(16)Jsmooth=∑i=1Nψiwhere N is the number of differences ψi.Figure 2
The angles of the path segments.
### 2.4.4. Path Safety
Using the safety cost of the nodes on the grids cannot accurately represent the threat impact of each path segment. First, three sampling points are selected on a path segment and the average Euclidean distance between the three sampling points and the center of the obstacle is calculated. The schematic diagram of the calculation of the path safety is shown in Figure3. lk is the length of the kth path segment between the waypoint pi and pi+1. For the kth path segment, three sampling points are taken at lk/6, lk/2, and 5lk/6, respectively. The average Euclidean distance between the three sampling points and the center of the obstacle is(17)DT,k=13dT,kjlk6+dT,kjlk2+dT,kj5lk6where dT,kj() is the Euclidean distance from the sampling point on the kth path segment to the center of the obstacle Tj.Figure 3
Schematic diagram of the calculation of the path safety.The path safety cost between waypointpi and pi+1 denoted as Jsafei,i+1 is(18)Jsafei,i+1=0,d>dsafe_max1DT,ki,i+1,dsafe_min≤d≤dsafe_max1,d<dsafe_minwhere d is the distance between the USV and the obstacle’s center, dsafe_max is the radius of the obstacle’s affected area, and dsafe_min is the radius of the no-sail zone. JT,ki,i+1 is obtained using (17).Thus, the entire path safety cost functionJsafe is(19)Jsafe=∑i=1NJsafei,i+1where N is the number of the waypoints of the planned path.
### 2.4.5. Cost Function
In summary, the cost function of the USV global path planning was established as(20)minJ=w1·L+w2·E+w3·Jsmooth+w4·Jsafewhere L, E, Jsmooth, and Jsafe are obtained by (8), (9), (16), and (19), respectively. w1, w2, w3, and w4 represent the weights of the path length, energy consumption, path smoothness, and path safety in the cost function, respectively, subject to(21)L≤Lmax0≤v→out≤vmaxwhere Lmax is the maximum voyage distance of the USV and vmax is the maximum speed of the USV.
## 2.4.1. Path Length
Since the task area is modeled by grids, the planned path is represented on a rectangular grid. The path passes the centers of the grids. Thus, the distanceLi,i+1 between two adjacent waypoints pi=(xi,yi) and pi+1=(xi+1,yi+1) is equal to the Euclidean distance between the centers of the grids as follows:(7)Li,i+1=1,xi=xi+1oryi=yi+12,otherwiseThe positions ofpi and pi+1 are shown in Figure 1. If pi and pi+1 are adjacent in the horizontal or vertical direction, Li,i+1=1. If pi and pi+1 are adjacent in the diagonal direction, Li,i+1=2.Figure 1
The positions ofpi and pi+1.Therefore, the total length of the pathL is the sum of the distances between the adjacent waypoints:(8)L=∑i=1mLi,i+1where m is the number of path segments.
## 2.4.2. Energy Consumption
In this paper, the energy consumption of the USV while sailing is derived from the propulsion system. Thus,E is the sum of the energy consumption of each segment along the entire path:(9)E=∑i=1mEi,i+1Supposing that the USV is sailing at a constant velocity betweenpi and pi+1, the energy consumption Ei,i+1 between pi and pi+1 equals the work done by the propulsion system to overcome the environmental loads, such that(10)Ei,i+1=τenv·v→usv·twhere t is the time for the USV to sail in Li,i+1.(11)t=Li,i+1v→outwhere v→usv is the magnitude of the velocity v→usv generated by the USV propulsion system, τenv is the resultant force of the environmental loads, and v→out is the magnitude of the velocity v→out of the USV moving in the horizontal plane. Since the headings of the USV in the grid are several fixed values, as shown in Figure 1, the angular velocity r caused by the yaw motion can be ignored when solving v→out. Hence, v→out is equal to(12)v→out=u2+v2where u and v are obtained by (1).It is known from (10) and (11) that the energy consumption is proportional to v→usv and 1/v→out, when the thrust τthr generated by the propulsion system is a fixed value. To reduce the energy consumption, it is necessary to adjust the USV’s heading to take advantage of the environmental loads to increase v→out.
## 2.4.3. Path Smoothness
It is assumed that the current waypoint of the USV ispi=(xi,yi), the previous waypoint is pi-1=(xi-1,yi-1), and the next waypoint is pi+1=(xi+1,yi+1). Thus, the angle θi+1 of the vector pipi+1→ and the angle θi of the vector pi-1pi→ are(13)θi+1=arctanyi+1-yixi+1-xi(14)θi=arctanyi-yi-1xi-xi-1The differenceψi between θi+1 and θi is(15)ψi=absθi+1-θiθ i, θi+1, and ψi, are shown in Figure 2. Therefore, the cost function of the path smoothness Jsmooth is(16)Jsmooth=∑i=1Nψiwhere N is the number of differences ψi.Figure 2
The angles of the path segments.
## 2.4.4. Path Safety
Using the safety cost of the nodes on the grids cannot accurately represent the threat impact of each path segment. First, three sampling points are selected on a path segment and the average Euclidean distance between the three sampling points and the center of the obstacle is calculated. The schematic diagram of the calculation of the path safety is shown in Figure3. lk is the length of the kth path segment between the waypoint pi and pi+1. For the kth path segment, three sampling points are taken at lk/6, lk/2, and 5lk/6, respectively. The average Euclidean distance between the three sampling points and the center of the obstacle is(17)DT,k=13dT,kjlk6+dT,kjlk2+dT,kj5lk6where dT,kj() is the Euclidean distance from the sampling point on the kth path segment to the center of the obstacle Tj.Figure 3
Schematic diagram of the calculation of the path safety.The path safety cost between waypointpi and pi+1 denoted as Jsafei,i+1 is(18)Jsafei,i+1=0,d>dsafe_max1DT,ki,i+1,dsafe_min≤d≤dsafe_max1,d<dsafe_minwhere d is the distance between the USV and the obstacle’s center, dsafe_max is the radius of the obstacle’s affected area, and dsafe_min is the radius of the no-sail zone. JT,ki,i+1 is obtained using (17).Thus, the entire path safety cost functionJsafe is(19)Jsafe=∑i=1NJsafei,i+1where N is the number of the waypoints of the planned path.
## 2.4.5. Cost Function
In summary, the cost function of the USV global path planning was established as(20)minJ=w1·L+w2·E+w3·Jsmooth+w4·Jsafewhere L, E, Jsmooth, and Jsafe are obtained by (8), (9), (16), and (19), respectively. w1, w2, w3, and w4 represent the weights of the path length, energy consumption, path smoothness, and path safety in the cost function, respectively, subject to(21)L≤Lmax0≤v→out≤vmaxwhere Lmax is the maximum voyage distance of the USV and vmax is the maximum speed of the USV.
## 3. Optimization Algorithm
In this section, we will introduce the optimization algorithm for the USV global path planning—the IQACA. The IQACA is a new optimization algorithm that combines quantum-inspired computing with ant colony optimization algorithm. We will introduce quantum code and a quantum rotation gate from quantum-inspired computing. Some rules based on the ant colony optimization algorithm are presented.
### 3.1. Quantum Code
The quantum bit (Q-bit) is the basic unit in quantum computing. A Q-bit is a system that has two possible states0 and 1. The state of a Q-bit φ is expressed as(22)φ=α0+β1where α and β are the probability amplitudes, which satisfy α2+β2=1. α2 and β2 are the probabilities in states 0 and 1, respectively. Thus, the state of the Q-bit φ is an uncertain superposition state between 0 and 1. When the number of Q-bits of an individual Xi is n, Xi is expressed as(23)Xi=αi1αi2…αinβi1βi2…βinwhere Xic=(αi1,⋯,αin) and Xis=(βi1,⋯,βin) are the two sets of solutions for individual Xi. Therefore, after quantum coding, every individual has two sets of solutions and the search space is doubled.In the IQACA, the quantum pheromone is obtained by encoding the pheromone left by the ants on the path in the ACA by the Q-bits. The transfer direction of the ants is selected by the quantum pheromone concentration on the path. Thus, the quantum pheromone concentration valueτijt of the ith ant on the jth point in the tth iteration is expressed as(24)τijt=αijtβijt
### 3.2. Adaptive Quantum Rotation Gate
In the quantum optimization algorithm, a quantum rotation gate is used to update the Q-bits. The update rule of a Q-bit is as follows:(25)αijt+1βijt+1=Uθtαijtβijtwhere [αijt,βijt]T represents the probability amplitude of the Q-bits in the tth iteration. U(θt) is the quantum rotation gate in the tth iteration(26)Uθt=cosθt-sinθtsinθtcosθtwhere θt is the rotation angle in the tth iteration. In a previous paper [13], the rotation angle was obtained by looking it up in a table. In another paper [26], the local and global updates of the pheromone concentration increments in the ACA were added to the rotation angle step function. In the IQACA, an adaptive adjustment strategy for the rotation angle is obtained by comparing the current solution and the global optimal solution currently being searched. Thus, the rotation angle θt in the tth iteration is(27)θt=-sgnAi·Δθiwhere -sgnAi is the direction of the rotation angle and Δθi is the size of the rotation angle. Ai is(28)Ai=α0α1β0β1where α0 and β0 are the probability amplitudes of the quantum pheromone corresponding to the global optimal solution currently searched and α1 and β1 are the probability amplitudes of the quantum pheromone corresponding to the current solution. Δθi is(29)Δθi=Je-Je-JkNmax·twhere Jk is the cost value of ant k in the current solution, Je is the cost value of the global optimal solution currently searched, and Nmax is the maximum number of iterations.
### 3.3. Transfer Rule and Transition Probability
The ant colony optimization algorithm is a bionic intelligent algorithm inspired by the foraging behavior of ant colonies [27]. During the foraging, ants produce a substance called a pheromone. The concentration of the pheromone, which is related to the path length, will determine the movement of other ants. If the path is shorter, the concentration of the pheromone left on the path is larger.To achieve multiobjective path planning, multiple pieces of heuristic information are used to determine the ant’s transfer rules and transition probabilities. The transfer rule of antk from point i to point j is(30)s=argmaxs∈Sτijktαηijktβεijtγq≤q0s~q>q0where q is a random number in the range [0,1]. q0 is a constant within [0,1]. S is the set of points that ant k may reach by point i. s~ is the target waypoint selected by the following equation:(31)pijkt=τijktαηijktβμijktγ∑s∈allowediτijktαηijktβμijktγwhere τijk(t) is the pheromone on the path from point i to point j in the tth iteration and α(α>0) is the pheromone index. ηijk(t) is the multiple inspiration information on the path from point i to point j in the tth iteration, β(β>0) is the index of multiple inspiration information, μijk(t) is the quantum information strength on the path from point i to point j in the tth iteration, which is expressed as μijk(t)=1/αijk(t)2, and γ(γ>0) is the index of the quantum information strength.The multiple pieces of heuristic information include the path length heuristic informationϕijk(t), energy consumption heuristic information εijk(t), path smoothness heuristic information φijk(t), and path safety heuristic information ζijk(t).(32)ηijktβ=ϕijktaεijktbφijktcζijktd(33)ϕijt=1Lijεijt=1Eijφijt=1Jsmoothijζijt=1Jsafeijwhere Lij, Eij, Jsmoothij, and Jsafeij are obtained by (8), (9), (16), and (19), respectively. a, b, c, and d are the indices of the path length heuristic information, energy consumption heuristic information, path smoothness heuristic information, and path safety heuristic information, respectively.
### 3.4. Update Rules of Pheromone
After every ant completes a one-transfer, the pheromone on the path it passes is locally updated to avoid falling into a local optimum. When the current point of the ant ispi and the next point is pj, the pheromone local updating rule is(34)τpj=1-ρ1·τpi+ρ1·Δτijwhere τ(pi) is the pheromone of the current point, τ(pj) is the pheromone of the next point, ρ1(0<ρ1<1) is the pheromone local updating coefficient, and Δτij is the pheromone that every ant leaves on the path from pi to pj in this iteration, expressed as follows:(35)Δτij=∑k=1nΔτijk(36)Δτijk=QJk,thepathsegmentofthekthant0,elsewhere Q is a constant and Jk is the cost value of the kth ant’s path.After all the ants complete an iteration, the pheromone is globally updated to increase the pheromone concentration on the optimized path. The rules are as follows:(37)τpj=1-ρ2·τpj+ρ2·Δτbest,pj=s~1-ρ2·τpj,pj≠s~(38)Δτbest=QJe,ifi,jbelongstotheoptimalpathinthiscycle0,elsewhere Q is a constant, Je is the cost value of the optimal path in this iteration, ρ2(0<ρ2<1) is the pheromone global updating coefficient, and s~ is the global optimal solution currently being searched.
### 3.5. Global Path Planning Algorithm Based on IQACA
The flowchart of global path planning algorithm based on the IQACA is shown in Figure4.Figure 4
The flowchart of the global path planning algorithm based on the IQACA.The main steps are as follows:Step 1 (initialize the parameters).
The number of the ants in the colony isn. The maximum number of iterations is Nmax. The initial quantum pheromone concentration value of the ith ant on the jth waypoint is expressed as τijt=[αijt,βijt]T=[1/2,1/2]T, where t=0;Step 2.
The ants are placed at the starting point. The transfer rule of the ants is determined by (30), and the target waypoint is selected by (31).Step 3.
The phases of the Q-bits are updated by (25).Step 4.
The pheromone is locally updated by (34).Step 5.
After all the ants have passed by all the points in an iteration, the pheromone is globally updated by (37).Step 6.
The candidate solution selected by the ants is output and the path cost is calculated.Step 7.
If the iterationt>Nmax, the algorithm moves to Step 8; otherwise, it returns to Step 2.Step 8.
The waypoints of the optimized solution and the cost value of the path are output. The global optimized path is obtained by the waypoints of the optimized solution.Step 9.
The algorithm ends.
## 3.1. Quantum Code
The quantum bit (Q-bit) is the basic unit in quantum computing. A Q-bit is a system that has two possible states0 and 1. The state of a Q-bit φ is expressed as(22)φ=α0+β1where α and β are the probability amplitudes, which satisfy α2+β2=1. α2 and β2 are the probabilities in states 0 and 1, respectively. Thus, the state of the Q-bit φ is an uncertain superposition state between 0 and 1. When the number of Q-bits of an individual Xi is n, Xi is expressed as(23)Xi=αi1αi2…αinβi1βi2…βinwhere Xic=(αi1,⋯,αin) and Xis=(βi1,⋯,βin) are the two sets of solutions for individual Xi. Therefore, after quantum coding, every individual has two sets of solutions and the search space is doubled.In the IQACA, the quantum pheromone is obtained by encoding the pheromone left by the ants on the path in the ACA by the Q-bits. The transfer direction of the ants is selected by the quantum pheromone concentration on the path. Thus, the quantum pheromone concentration valueτijt of the ith ant on the jth point in the tth iteration is expressed as(24)τijt=αijtβijt
## 3.2. Adaptive Quantum Rotation Gate
In the quantum optimization algorithm, a quantum rotation gate is used to update the Q-bits. The update rule of a Q-bit is as follows:(25)αijt+1βijt+1=Uθtαijtβijtwhere [αijt,βijt]T represents the probability amplitude of the Q-bits in the tth iteration. U(θt) is the quantum rotation gate in the tth iteration(26)Uθt=cosθt-sinθtsinθtcosθtwhere θt is the rotation angle in the tth iteration. In a previous paper [13], the rotation angle was obtained by looking it up in a table. In another paper [26], the local and global updates of the pheromone concentration increments in the ACA were added to the rotation angle step function. In the IQACA, an adaptive adjustment strategy for the rotation angle is obtained by comparing the current solution and the global optimal solution currently being searched. Thus, the rotation angle θt in the tth iteration is(27)θt=-sgnAi·Δθiwhere -sgnAi is the direction of the rotation angle and Δθi is the size of the rotation angle. Ai is(28)Ai=α0α1β0β1where α0 and β0 are the probability amplitudes of the quantum pheromone corresponding to the global optimal solution currently searched and α1 and β1 are the probability amplitudes of the quantum pheromone corresponding to the current solution. Δθi is(29)Δθi=Je-Je-JkNmax·twhere Jk is the cost value of ant k in the current solution, Je is the cost value of the global optimal solution currently searched, and Nmax is the maximum number of iterations.
## 3.3. Transfer Rule and Transition Probability
The ant colony optimization algorithm is a bionic intelligent algorithm inspired by the foraging behavior of ant colonies [27]. During the foraging, ants produce a substance called a pheromone. The concentration of the pheromone, which is related to the path length, will determine the movement of other ants. If the path is shorter, the concentration of the pheromone left on the path is larger.To achieve multiobjective path planning, multiple pieces of heuristic information are used to determine the ant’s transfer rules and transition probabilities. The transfer rule of antk from point i to point j is(30)s=argmaxs∈Sτijktαηijktβεijtγq≤q0s~q>q0where q is a random number in the range [0,1]. q0 is a constant within [0,1]. S is the set of points that ant k may reach by point i. s~ is the target waypoint selected by the following equation:(31)pijkt=τijktαηijktβμijktγ∑s∈allowediτijktαηijktβμijktγwhere τijk(t) is the pheromone on the path from point i to point j in the tth iteration and α(α>0) is the pheromone index. ηijk(t) is the multiple inspiration information on the path from point i to point j in the tth iteration, β(β>0) is the index of multiple inspiration information, μijk(t) is the quantum information strength on the path from point i to point j in the tth iteration, which is expressed as μijk(t)=1/αijk(t)2, and γ(γ>0) is the index of the quantum information strength.The multiple pieces of heuristic information include the path length heuristic informationϕijk(t), energy consumption heuristic information εijk(t), path smoothness heuristic information φijk(t), and path safety heuristic information ζijk(t).(32)ηijktβ=ϕijktaεijktbφijktcζijktd(33)ϕijt=1Lijεijt=1Eijφijt=1Jsmoothijζijt=1Jsafeijwhere Lij, Eij, Jsmoothij, and Jsafeij are obtained by (8), (9), (16), and (19), respectively. a, b, c, and d are the indices of the path length heuristic information, energy consumption heuristic information, path smoothness heuristic information, and path safety heuristic information, respectively.
## 3.4. Update Rules of Pheromone
After every ant completes a one-transfer, the pheromone on the path it passes is locally updated to avoid falling into a local optimum. When the current point of the ant ispi and the next point is pj, the pheromone local updating rule is(34)τpj=1-ρ1·τpi+ρ1·Δτijwhere τ(pi) is the pheromone of the current point, τ(pj) is the pheromone of the next point, ρ1(0<ρ1<1) is the pheromone local updating coefficient, and Δτij is the pheromone that every ant leaves on the path from pi to pj in this iteration, expressed as follows:(35)Δτij=∑k=1nΔτijk(36)Δτijk=QJk,thepathsegmentofthekthant0,elsewhere Q is a constant and Jk is the cost value of the kth ant’s path.After all the ants complete an iteration, the pheromone is globally updated to increase the pheromone concentration on the optimized path. The rules are as follows:(37)τpj=1-ρ2·τpj+ρ2·Δτbest,pj=s~1-ρ2·τpj,pj≠s~(38)Δτbest=QJe,ifi,jbelongstotheoptimalpathinthiscycle0,elsewhere Q is a constant, Je is the cost value of the optimal path in this iteration, ρ2(0<ρ2<1) is the pheromone global updating coefficient, and s~ is the global optimal solution currently being searched.
## 3.5. Global Path Planning Algorithm Based on IQACA
The flowchart of global path planning algorithm based on the IQACA is shown in Figure4.Figure 4
The flowchart of the global path planning algorithm based on the IQACA.The main steps are as follows:Step 1 (initialize the parameters).
The number of the ants in the colony isn. The maximum number of iterations is Nmax. The initial quantum pheromone concentration value of the ith ant on the jth waypoint is expressed as τijt=[αijt,βijt]T=[1/2,1/2]T, where t=0;Step 2.
The ants are placed at the starting point. The transfer rule of the ants is determined by (30), and the target waypoint is selected by (31).Step 3.
The phases of the Q-bits are updated by (25).Step 4.
The pheromone is locally updated by (34).Step 5.
After all the ants have passed by all the points in an iteration, the pheromone is globally updated by (37).Step 6.
The candidate solution selected by the ants is output and the path cost is calculated.Step 7.
If the iterationt>Nmax, the algorithm moves to Step 8; otherwise, it returns to Step 2.Step 8.
The waypoints of the optimized solution and the cost value of the path are output. The global optimized path is obtained by the waypoints of the optimized solution.Step 9.
The algorithm ends.
## 4. Simulation Studies
In this section, the effectiveness and efficiency of the IQACA are validated. The section consists of two parts. The first subsection compares the performance of the ACA, QACA, and IQACA with the Traveling Salesman Problem (TSP). The second subsection deals with the USV global path planning based on the IQACA. To validate the proposed algorithm, simulations were conducted.
### 4.1. Performance Evaluation of IQACA
To validate the effectiveness of the IQACA presented in this paper, we compared the algorithm performance between ACA, QACA, and IQACA with the TSP. In this paper, RAND100 was selected from the TSPLIB standard library for the simulations. The maximum number of iterationsNmax=200, the number of the ants n=100, α=3, β=1, γ=2, and ρ1=ρ2=0.8. The obtained values are shown in Table 1, and the iterations are shown in Figure 5.Table 1
The obtained values from the simulations.
Algorithm Length Iteration ACA 8447 167 QACA 8062 142 IQACA 7891 126Figure 5
Convergence of the IQACA, QACA, and ACA.The known optimal value of RAND100 is 7891. From Table1, it was concluded that the path length of RAND100 obtained by the IQACA was 2.12% lower than that obtained by the QACA and 6.58% lower than that obtained by the ACA. The number of iterations required for the IQACA to converge to the minimum was 11.27% lower than the QACA and 24.55% lower than the ACA. The results show that the IQACA was superior to the QACA and the ACA in both the path length and iteration number. Since the algorithm uses the pheromone local and global updates, and the phases of the Q-bits are updated by the adaptive quantum rotation gate, the IQACA can avoid the local optimal solution. Because the pheromone is encoded by Q-bits, the search space is doubled, and the convergence speed is faster. Thus, the IQACA is an effective and efficient algorithm.
### 4.2. USV Global Path Planning Based on IQACA
In this subsection, we will show a simulation of USV global path planning based on the proposed algorithm. Obstacles are black-colored. The coordinates of the starting point are(0.5,24.5), and the coordinates of the destination point are (29.5,0.5). The length of the side of a grid is 1km. We assumed that the wind, waves, and ocean current act on the vessel from the same direction, since in most cases the ocean current is the most significant environmental disturbance on the vessel. In this simulation, the direction of the disturbances is assumed as 240° in the Northeast coordinate system. The relative wind speed was 7.5m/s. The wave height was 2.5m. The relative ocean current was 2.0m/s. The thrust of the USV propulsion system was 500kN. The coefficients of the USV in this simulation are shown in Table 2. The maximum number of iterations was 500, the number of the ants was 100, α=3, γ=2, and ρ1=ρ2=0.8. The safety boundary of the obstacle was represented by a dotted red circle whose radius was 1.3 times the distance between the vertex and the center of the obstacle. The optimal path is represented by a solid blue line. The objectives of the global path planning were determined based on their respective weights. We considered four scenarios in this simulation. In the first scenario, we highly weighted the path length, so that the weights [w1,w2,w3,w4] in the cost function (20) were [0.5,0.1,0.3,0.1]. In the other three scenario, we weighted the energy consumption, path smoothness, and path safety, respectively, such that the weights [w1,w2,w3,w4] were [0.1,0.5,0.1,0.3], [0.3,0.1,0.5,0.1], and [0.1,0.3,0.1,0.5], respectively.Table 2
Coefficients of USV.
Property Value Length overall (m) 80.8 Breadth (m) 18.2 Draught (m) 5.0 Area of frontal projection above the waterline (m2) 330.9 Area of lateral projection above the waterline (m2) 874.8 Area of frontal projection below the waterline (m2) 91.0 Area of lateral projection below the waterline (m2) 323.4Figures6–9 show the planned paths in the four scenarios. The path length, energy consumption, path smoothness, and path safety index for each planned path are listed in Table 3. The results indicate that the proposed algorithm can plan feasible paths for the USV considering different objectives simultaneously. Moreover, by adjusting the weights of different objectives, the proposed algorithm can generate paths for different purposes.Table 3
Path data for different objectives.
Objective Path length(km) Energy consumption(1×107kJ) Path smoothness(rad) Path safety index Path length 41.87 12.38 18.85 26.89 Energy consumption 48.31 10.81 28.27 27.12 Path smoothness 43.63 11.95 14.14 15.51 Path safety 46.80 11.96 28.27 7.61Figure 6
Planned path focusing on the path length.Figure 7
Planned path focusing on the energy consumption.Figure 8
Planned path focusing on the path smoothness.Figure 9
Planned path focusing on the path safety.
## 4.1. Performance Evaluation of IQACA
To validate the effectiveness of the IQACA presented in this paper, we compared the algorithm performance between ACA, QACA, and IQACA with the TSP. In this paper, RAND100 was selected from the TSPLIB standard library for the simulations. The maximum number of iterationsNmax=200, the number of the ants n=100, α=3, β=1, γ=2, and ρ1=ρ2=0.8. The obtained values are shown in Table 1, and the iterations are shown in Figure 5.Table 1
The obtained values from the simulations.
Algorithm Length Iteration ACA 8447 167 QACA 8062 142 IQACA 7891 126Figure 5
Convergence of the IQACA, QACA, and ACA.The known optimal value of RAND100 is 7891. From Table1, it was concluded that the path length of RAND100 obtained by the IQACA was 2.12% lower than that obtained by the QACA and 6.58% lower than that obtained by the ACA. The number of iterations required for the IQACA to converge to the minimum was 11.27% lower than the QACA and 24.55% lower than the ACA. The results show that the IQACA was superior to the QACA and the ACA in both the path length and iteration number. Since the algorithm uses the pheromone local and global updates, and the phases of the Q-bits are updated by the adaptive quantum rotation gate, the IQACA can avoid the local optimal solution. Because the pheromone is encoded by Q-bits, the search space is doubled, and the convergence speed is faster. Thus, the IQACA is an effective and efficient algorithm.
## 4.2. USV Global Path Planning Based on IQACA
In this subsection, we will show a simulation of USV global path planning based on the proposed algorithm. Obstacles are black-colored. The coordinates of the starting point are(0.5,24.5), and the coordinates of the destination point are (29.5,0.5). The length of the side of a grid is 1km. We assumed that the wind, waves, and ocean current act on the vessel from the same direction, since in most cases the ocean current is the most significant environmental disturbance on the vessel. In this simulation, the direction of the disturbances is assumed as 240° in the Northeast coordinate system. The relative wind speed was 7.5m/s. The wave height was 2.5m. The relative ocean current was 2.0m/s. The thrust of the USV propulsion system was 500kN. The coefficients of the USV in this simulation are shown in Table 2. The maximum number of iterations was 500, the number of the ants was 100, α=3, γ=2, and ρ1=ρ2=0.8. The safety boundary of the obstacle was represented by a dotted red circle whose radius was 1.3 times the distance between the vertex and the center of the obstacle. The optimal path is represented by a solid blue line. The objectives of the global path planning were determined based on their respective weights. We considered four scenarios in this simulation. In the first scenario, we highly weighted the path length, so that the weights [w1,w2,w3,w4] in the cost function (20) were [0.5,0.1,0.3,0.1]. In the other three scenario, we weighted the energy consumption, path smoothness, and path safety, respectively, such that the weights [w1,w2,w3,w4] were [0.1,0.5,0.1,0.3], [0.3,0.1,0.5,0.1], and [0.1,0.3,0.1,0.5], respectively.Table 2
Coefficients of USV.
Property Value Length overall (m) 80.8 Breadth (m) 18.2 Draught (m) 5.0 Area of frontal projection above the waterline (m2) 330.9 Area of lateral projection above the waterline (m2) 874.8 Area of frontal projection below the waterline (m2) 91.0 Area of lateral projection below the waterline (m2) 323.4Figures6–9 show the planned paths in the four scenarios. The path length, energy consumption, path smoothness, and path safety index for each planned path are listed in Table 3. The results indicate that the proposed algorithm can plan feasible paths for the USV considering different objectives simultaneously. Moreover, by adjusting the weights of different objectives, the proposed algorithm can generate paths for different purposes.Table 3
Path data for different objectives.
Objective Path length(km) Energy consumption(1×107kJ) Path smoothness(rad) Path safety index Path length 41.87 12.38 18.85 26.89 Energy consumption 48.31 10.81 28.27 27.12 Path smoothness 43.63 11.95 14.14 15.51 Path safety 46.80 11.96 28.27 7.61Figure 6
Planned path focusing on the path length.Figure 7
Planned path focusing on the energy consumption.Figure 8
Planned path focusing on the path smoothness.Figure 9
Planned path focusing on the path safety.
## 5. Conclusion
This paper proposed a global path planning algorithm for the USV based on an improved quantum ant colony algorithm (IQACA).The IQACA is an optimization algorithm that combines quantum computing with the ACA. In IQACA, using Q-bits to encode the pheromone of the ants, the search space is doubled when the number of the ants is the same. The simulation results show that the proposed algorithm’s obtained minimum was 2.1–6.5% lower than those of the quantum ant colony algorithm (QACA) and ant colony algorithm (ACA), and the number of iterations required to converge to the minimum was 11.2–24.5% lower than those of the QACA and ACA. Based on the model of the kinetics of the USV and the marine environment, we defined the objectives of the path planning: the path length, energy consumption, path smoothness, and path safety. The simulation results showed that the proposed algorithm can consider several optimization objectives and generate paths satisfying these requirements.In the future, the following studies should be conducted in depth. First, the correlation between the multiple objectives should be calculated to determine the weight of each objective in the cost function to meet the actual mission requirements. Moreover, the kinetic and kinematic constraints of the USV should be added to the cost function. Finally, more practical environmental loads should be applied to calculate their effects on the path energy consumption of the USV.
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*Source: 2902170-2019-04-24.xml* | 2902170-2019-04-24_2902170-2019-04-24.md | 59,441 | Global Path Planning for Unmanned Surface Vehicle Based on Improved Quantum Ant Colony Algorithm | Guoqing Xia; Zhiwei Han; Bo Zhao; Caiyun Liu; Xinwei Wang | Mathematical Problems in Engineering
(2019) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2019/2902170 | 2902170-2019-04-24.xml | ---
## Abstract
As a tool to monitor marine environments and to perform dangerous tasks instead of manned vessels, unmanned surface vehicles (USVs) have extensive applications. Because most path planning algorithms have difficulty meeting the mission requirements of USVs, the purpose of this study was to plan a global path with multiple objectives, such as path length, energy consumption, path smoothness, and path safety, for USV in marine environments. A global path planning algorithm based on an improved quantum ant colony algorithm (IQACA) is proposed. The improved quantum ant colony algorithm is an algorithm that benefits from the high efficiency of quantum computing and the optimization ability of the ant colony algorithm. The proposed algorithm can plan a path considering multiple objectives simultaneously. The simulation results show that the proposed algorithm’s obtained minimum was 2.1–6.5% lower than those of the quantum ant colony algorithm (QACA) and ant colony algorithm (ACA), and the number of iterations required to converge to the minimum was 11.2–24.5% lower than those of the QACA and ACA. In addition, the optimized path for the USV was obtained effectively and efficiently.
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## Body
## 1. Introduction
An unmanned surface vehicle (USV) is a kind of autonomous marine vehicle. Determining the path of a USV is an important problem associated with its safety and efficiency [1]. Depending on whether the environmental information is obtained from a digital map or sensors, path planning is divided into global and local stages [2]. In this paper, a USV global path planning study is presented. Global path planning is the process of planning a path to connect the starting and destination points under a given planning space from a digital map and constraints according to the mission requirements. The indices for evaluating a path can be path length, energy consumption, path smoothness, and path safety.Obtaining a short path from the starting point to the destination point is one of the main objectives of global path planning. Planning the shortest path is an NP-hard problem [3]. Existing methods take the path length as a single objective of the path planning, and neither energy consumption nor other indices are considered.The energy consumption during sailing determines the USV’s endurance and the duration of the mission. Since the environmental loads such as wind, waves, and ocean currents influence the performance of the USV, the calculation of the USV’s energy consumption is complex. Niu et al. [4] considered the effect of the ocean current on the energy consumption of USVs. Lee et al. [5] found a more economical path by considering the shallow water effect as well as tidal currents and wind for surface ship navigation. Most calculations of energy consumption have considered the effects of ocean currents on the USV without considering wind and waves.The smoothness of a path depends on the size and number of the turns that the USV makes while sailing along the planned path. The smoother path allows the USV to make fewer turns along the path, which reduces the mechanical wear on the steering actuators, such as rudders. Smooth paths can reduce unnecessary curvature discontinuities and possible stops. In a previous report [6], the smoothness of a path was evaluated by summing the angles of each turn on the path that the vehicle follows. Ma et al. [7] evaluated the turn angle set by adopting the maximum value of the turn angle set to assess the path smoothness for the USV.Obstacles such as islands and reefs affect the safety of the USV. Path safety means that the USV cannot collide with any obstacles while sailing. Ma et al. [7] used circles that just covered the obstacles to identify the safe area.Since USV global path planning involves optimization algorithms, environmental models, and marine craft hydrodynamics, existing path planning algorithms have difficulty meeting the mission requirements. Intelligent optimization algorithms are widely used in global path planning, such as the genetic algorithm [8], particle swarm algorithm [9], NSGA-II [10], and ant colony algorithm [11]. With the development of quantum technology, the idea of combining quantum computing with intelligent optimization algorithms has been developed. Narayanan and Moore combined quantum mechanics principles and evolutionary computing methods for the first time [12]. A quantum bit and superposition of states were proposed to solve the knapsack problem by a quantum-inspired evolutionary algorithm (QEA) [13]. Based on the QEA with a quantum rotation gate strategy, an adaptive evolution-based quantum-inspired evolutionary algorithm (AEQEA) introduces an adaptive evolution mechanism [14]. A new improved quantum evolution algorithm (IQEA) with a mixed local search procedure was proposed [15]. Li et al. [16] proposed a quantum ant colony algorithm (QACA) that combined quantum computing and the ant colony algorithm for continuous space optimization. You et al. [17] proposed a novel parallel ant colony optimization algorithm based on a quantum dynamics mechanism (PQACO). An improved quantum ant colony algorithm was proposed for the optimization of evacuation paths from dangerous areas to safe areas [18]. The quantum ant colony algorithm was used to determine campus path navigation [19].In this paper, a global path planning algorithm for USV based on the improved quantum ant colony algorithm (IQACA) is proposed. The main contributions of the proposed approach are as follows:(1)
At present, most USV global path planning algorithms only search for a feasible path for one objective [3–6]. In this paper, path planning was considered with multiple simultaneous objectives, which were path length, energy consumption, path smoothness, and path safety.(2)
The IQACA is a new optimization algorithm that combines quantum-inspired computing with the ant colony algorithm (ACA). The quantum bit (Q-bit) is used to encode the pheromone in the ACA to obtain the quantum pheromone, and the ant movement is determined based on the concentration of the quantum pheromone on the path. Compared to the existing QACA [16–19], the phase of the quantum ant colony is transformed by an adaptive quantum rotation gate, and the quantum pheromone is updated by local and global update rules in the IQACA.Simulation experiments in a complex environment with wind, waves, and ocean currents verified the effectiveness of the objective model, and we obtained a desired path based on the IQACA.The paper is organized as follows. In Section2, the USV path planning problem is established, and the USV kinetic model, environmental loads, and cost function of the path planning are described. In Section 3, the principles of the IQACA are provided, and we apply the IQACA to USV global path planning. In Section 4, the simulations for USV global path planning using the IQACA are presented. Conclusions are provided in Section 5.
## 2. Problem Statement
### 2.1. USV Kinetic Model
The kinetic model of a USV accounts for the forces, such as the control force and environmental loads, which cause USV motion. For the USV, the control force is mainly the thrust of each propeller. The environmental loads on the USV are generated by wind, waves, and ocean currents. The kinetic model of the USV, which was proposed previously [20], is as follows:(1)Mν˙+Cνν+Dνν=τenv+τthr(2)τenv=τwind+τwave+τcurrentwhere M is the system inertia matrix, C(ν) is the Coriolis-centripetal matrix, D(ν)∈R3×3 is damping matrix. τwind, τwave, and τcurrent are wind, wave, and ocean current forces acting on the USV, respectively, and τthr is the thrust generated by the USV propulsion system. The generalized velocity ν=[u,v,r]T is obtained by (1), where the first two components (u,v) are the linear velocities of the surge and sway, and r is the angular velocity of the yaw.
### 2.2. Models of Environmental Loads
When planning a global path for USVs, it is necessary to consider the environmental effects on the vehicles. Thus, we need to analyze the impacts of wind, waves, and ocean currents on the USV. The planned area is a confined sea with some static obstacles, and the mission execution time is short. Therefore, it can be assumed that the environmental loads are basically stable in limited time and space.
#### 2.2.1. Wind Forces
The wind acts directly on the superstructure of the hull. As reported previously [21], the wind forces are written as follows:(3)τwindX=12ρaAfVw2CwxαRτwindY=12ρaAsVw2CwyαRτwindN=12ρaAsVw2CwnαR·Lwhere ρa is the density of air, Af and As are the frontal and lateral projected areas, Cwx(αR), Cwy(αR), and Cwn(αR) are the empirical force coefficients, αR is the angle between the wind and the heading of the vessel, L is the length of the vessel, Vw is the relative wind speed, and τwindX, τwindY, and τwindN are the wind forces during the surge, sway, and yaw, respectively [22].
#### 2.2.2. Wave Forces
When a vehicle is sailing on the sea, the interference of wave forces is complicated. The wave forces acting on the hull are first- and second-order wave forces. The second-order wave forces, which impact the heading and path of the USV, are proportional to the square of the wave height [22]. The wave forces are simplified as follows:(4)τwaveX=Kw1ss2+2λ1ωe1s+ωe12w1+d1τwaveY=Kw2ss2+2λ2ωe2s+ωe22w2+d2τwaveN=Kw3ss2+2λ3ωe3s+ωe32w3+d3where wi(i=1,2,3) are Gaussian white noise processes, and τwaveX, τwaveY, and τwaveN are the wave forces during the surge, sway, and yaw, respectively. The amplitudes of τwaveX, τwaveY, and τwaveN are adjusted by choosing the constants Kwi(i=1,2,3), while the spectra are parameterized in terms of the pairs λi and ωei(i=1,2,3). The wave drift forces di(i=1,2,3) are usually modeled as slowly varying bias terms:(5)d˙1=w4d˙2=w5d˙3=w6where wi(i=4,5,6) are Gaussian white noise processes [22].
#### 2.2.3. Ocean Current Forces
The ocean currents cause vessels sailing on the sea to change their positions and postures. The ocean current forces are given as follows:(6)τcurrentX=12ρAfVc2CXβτcurrentY=12ρAsVc2CYβτcurrentN=12ρAsVc2CNβ·Lwhere ρ is the density of the seawater, Af and As are the frontal and lateral projected areas below the waterline, respectively, CX, CY, and CN are the empirical force coefficients, Vc is the relative current speed, β is the angle between the ocean current and the heading of the vessel, L is the length of the vessel, and τcurrentX, τcurrentY, and τcurrentN are the ocean current forces during surge, sway, and yaw, respectively [22].
### 2.3. Path Representation by Grids
The real task area is partitioned to reduce the modeling complexity. Visibility graphs [23], Voronoi diagrams [24], and grid maps [25] are the most commonly used path planning algorithms. The grid map-based path planning algorithm is powerful in that it generates a path with the shortest computation time [25]. To facilitate the calculation, the planned path is represented on grids. The area under consideration is discretized into grids. The information, such as the relative speed and direction of the wind, the amplitude and direction of the waves, the relative speed and direction of ocean current, and the position of the obstacles, is discretized in each grid. Stationary obstacles are encoded in a binary format on the grids. We assigned weights of 1 to all obstacle grids and weights of 0 to all free neighbor grids of them.
### 2.4. Objectives of USV Global Path Planning
Since USV global path planning is a multiobjective optimization problem, we should analyze the interrelated objectives and discuss the importance of each objective based on the requirements of the mission. A cost function can be constructed as a weighted sum of the objective functions. Finally, the cost function is used to evaluate the quality of the planned path.
#### 2.4.1. Path Length
Since the task area is modeled by grids, the planned path is represented on a rectangular grid. The path passes the centers of the grids. Thus, the distanceLi,i+1 between two adjacent waypoints pi=(xi,yi) and pi+1=(xi+1,yi+1) is equal to the Euclidean distance between the centers of the grids as follows:(7)Li,i+1=1,xi=xi+1oryi=yi+12,otherwiseThe positions ofpi and pi+1 are shown in Figure 1. If pi and pi+1 are adjacent in the horizontal or vertical direction, Li,i+1=1. If pi and pi+1 are adjacent in the diagonal direction, Li,i+1=2.Figure 1
The positions ofpi and pi+1.Therefore, the total length of the pathL is the sum of the distances between the adjacent waypoints:(8)L=∑i=1mLi,i+1where m is the number of path segments.
#### 2.4.2. Energy Consumption
In this paper, the energy consumption of the USV while sailing is derived from the propulsion system. Thus,E is the sum of the energy consumption of each segment along the entire path:(9)E=∑i=1mEi,i+1Supposing that the USV is sailing at a constant velocity betweenpi and pi+1, the energy consumption Ei,i+1 between pi and pi+1 equals the work done by the propulsion system to overcome the environmental loads, such that(10)Ei,i+1=τenv·v→usv·twhere t is the time for the USV to sail in Li,i+1.(11)t=Li,i+1v→outwhere v→usv is the magnitude of the velocity v→usv generated by the USV propulsion system, τenv is the resultant force of the environmental loads, and v→out is the magnitude of the velocity v→out of the USV moving in the horizontal plane. Since the headings of the USV in the grid are several fixed values, as shown in Figure 1, the angular velocity r caused by the yaw motion can be ignored when solving v→out. Hence, v→out is equal to(12)v→out=u2+v2where u and v are obtained by (1).It is known from (10) and (11) that the energy consumption is proportional to v→usv and 1/v→out, when the thrust τthr generated by the propulsion system is a fixed value. To reduce the energy consumption, it is necessary to adjust the USV’s heading to take advantage of the environmental loads to increase v→out.
#### 2.4.3. Path Smoothness
It is assumed that the current waypoint of the USV ispi=(xi,yi), the previous waypoint is pi-1=(xi-1,yi-1), and the next waypoint is pi+1=(xi+1,yi+1). Thus, the angle θi+1 of the vector pipi+1→ and the angle θi of the vector pi-1pi→ are(13)θi+1=arctanyi+1-yixi+1-xi(14)θi=arctanyi-yi-1xi-xi-1The differenceψi between θi+1 and θi is(15)ψi=absθi+1-θiθ i, θi+1, and ψi, are shown in Figure 2. Therefore, the cost function of the path smoothness Jsmooth is(16)Jsmooth=∑i=1Nψiwhere N is the number of differences ψi.Figure 2
The angles of the path segments.
#### 2.4.4. Path Safety
Using the safety cost of the nodes on the grids cannot accurately represent the threat impact of each path segment. First, three sampling points are selected on a path segment and the average Euclidean distance between the three sampling points and the center of the obstacle is calculated. The schematic diagram of the calculation of the path safety is shown in Figure3. lk is the length of the kth path segment between the waypoint pi and pi+1. For the kth path segment, three sampling points are taken at lk/6, lk/2, and 5lk/6, respectively. The average Euclidean distance between the three sampling points and the center of the obstacle is(17)DT,k=13dT,kjlk6+dT,kjlk2+dT,kj5lk6where dT,kj() is the Euclidean distance from the sampling point on the kth path segment to the center of the obstacle Tj.Figure 3
Schematic diagram of the calculation of the path safety.The path safety cost between waypointpi and pi+1 denoted as Jsafei,i+1 is(18)Jsafei,i+1=0,d>dsafe_max1DT,ki,i+1,dsafe_min≤d≤dsafe_max1,d<dsafe_minwhere d is the distance between the USV and the obstacle’s center, dsafe_max is the radius of the obstacle’s affected area, and dsafe_min is the radius of the no-sail zone. JT,ki,i+1 is obtained using (17).Thus, the entire path safety cost functionJsafe is(19)Jsafe=∑i=1NJsafei,i+1where N is the number of the waypoints of the planned path.
#### 2.4.5. Cost Function
In summary, the cost function of the USV global path planning was established as(20)minJ=w1·L+w2·E+w3·Jsmooth+w4·Jsafewhere L, E, Jsmooth, and Jsafe are obtained by (8), (9), (16), and (19), respectively. w1, w2, w3, and w4 represent the weights of the path length, energy consumption, path smoothness, and path safety in the cost function, respectively, subject to(21)L≤Lmax0≤v→out≤vmaxwhere Lmax is the maximum voyage distance of the USV and vmax is the maximum speed of the USV.
## 2.1. USV Kinetic Model
The kinetic model of a USV accounts for the forces, such as the control force and environmental loads, which cause USV motion. For the USV, the control force is mainly the thrust of each propeller. The environmental loads on the USV are generated by wind, waves, and ocean currents. The kinetic model of the USV, which was proposed previously [20], is as follows:(1)Mν˙+Cνν+Dνν=τenv+τthr(2)τenv=τwind+τwave+τcurrentwhere M is the system inertia matrix, C(ν) is the Coriolis-centripetal matrix, D(ν)∈R3×3 is damping matrix. τwind, τwave, and τcurrent are wind, wave, and ocean current forces acting on the USV, respectively, and τthr is the thrust generated by the USV propulsion system. The generalized velocity ν=[u,v,r]T is obtained by (1), where the first two components (u,v) are the linear velocities of the surge and sway, and r is the angular velocity of the yaw.
## 2.2. Models of Environmental Loads
When planning a global path for USVs, it is necessary to consider the environmental effects on the vehicles. Thus, we need to analyze the impacts of wind, waves, and ocean currents on the USV. The planned area is a confined sea with some static obstacles, and the mission execution time is short. Therefore, it can be assumed that the environmental loads are basically stable in limited time and space.
### 2.2.1. Wind Forces
The wind acts directly on the superstructure of the hull. As reported previously [21], the wind forces are written as follows:(3)τwindX=12ρaAfVw2CwxαRτwindY=12ρaAsVw2CwyαRτwindN=12ρaAsVw2CwnαR·Lwhere ρa is the density of air, Af and As are the frontal and lateral projected areas, Cwx(αR), Cwy(αR), and Cwn(αR) are the empirical force coefficients, αR is the angle between the wind and the heading of the vessel, L is the length of the vessel, Vw is the relative wind speed, and τwindX, τwindY, and τwindN are the wind forces during the surge, sway, and yaw, respectively [22].
### 2.2.2. Wave Forces
When a vehicle is sailing on the sea, the interference of wave forces is complicated. The wave forces acting on the hull are first- and second-order wave forces. The second-order wave forces, which impact the heading and path of the USV, are proportional to the square of the wave height [22]. The wave forces are simplified as follows:(4)τwaveX=Kw1ss2+2λ1ωe1s+ωe12w1+d1τwaveY=Kw2ss2+2λ2ωe2s+ωe22w2+d2τwaveN=Kw3ss2+2λ3ωe3s+ωe32w3+d3where wi(i=1,2,3) are Gaussian white noise processes, and τwaveX, τwaveY, and τwaveN are the wave forces during the surge, sway, and yaw, respectively. The amplitudes of τwaveX, τwaveY, and τwaveN are adjusted by choosing the constants Kwi(i=1,2,3), while the spectra are parameterized in terms of the pairs λi and ωei(i=1,2,3). The wave drift forces di(i=1,2,3) are usually modeled as slowly varying bias terms:(5)d˙1=w4d˙2=w5d˙3=w6where wi(i=4,5,6) are Gaussian white noise processes [22].
### 2.2.3. Ocean Current Forces
The ocean currents cause vessels sailing on the sea to change their positions and postures. The ocean current forces are given as follows:(6)τcurrentX=12ρAfVc2CXβτcurrentY=12ρAsVc2CYβτcurrentN=12ρAsVc2CNβ·Lwhere ρ is the density of the seawater, Af and As are the frontal and lateral projected areas below the waterline, respectively, CX, CY, and CN are the empirical force coefficients, Vc is the relative current speed, β is the angle between the ocean current and the heading of the vessel, L is the length of the vessel, and τcurrentX, τcurrentY, and τcurrentN are the ocean current forces during surge, sway, and yaw, respectively [22].
## 2.2.1. Wind Forces
The wind acts directly on the superstructure of the hull. As reported previously [21], the wind forces are written as follows:(3)τwindX=12ρaAfVw2CwxαRτwindY=12ρaAsVw2CwyαRτwindN=12ρaAsVw2CwnαR·Lwhere ρa is the density of air, Af and As are the frontal and lateral projected areas, Cwx(αR), Cwy(αR), and Cwn(αR) are the empirical force coefficients, αR is the angle between the wind and the heading of the vessel, L is the length of the vessel, Vw is the relative wind speed, and τwindX, τwindY, and τwindN are the wind forces during the surge, sway, and yaw, respectively [22].
## 2.2.2. Wave Forces
When a vehicle is sailing on the sea, the interference of wave forces is complicated. The wave forces acting on the hull are first- and second-order wave forces. The second-order wave forces, which impact the heading and path of the USV, are proportional to the square of the wave height [22]. The wave forces are simplified as follows:(4)τwaveX=Kw1ss2+2λ1ωe1s+ωe12w1+d1τwaveY=Kw2ss2+2λ2ωe2s+ωe22w2+d2τwaveN=Kw3ss2+2λ3ωe3s+ωe32w3+d3where wi(i=1,2,3) are Gaussian white noise processes, and τwaveX, τwaveY, and τwaveN are the wave forces during the surge, sway, and yaw, respectively. The amplitudes of τwaveX, τwaveY, and τwaveN are adjusted by choosing the constants Kwi(i=1,2,3), while the spectra are parameterized in terms of the pairs λi and ωei(i=1,2,3). The wave drift forces di(i=1,2,3) are usually modeled as slowly varying bias terms:(5)d˙1=w4d˙2=w5d˙3=w6where wi(i=4,5,6) are Gaussian white noise processes [22].
## 2.2.3. Ocean Current Forces
The ocean currents cause vessels sailing on the sea to change their positions and postures. The ocean current forces are given as follows:(6)τcurrentX=12ρAfVc2CXβτcurrentY=12ρAsVc2CYβτcurrentN=12ρAsVc2CNβ·Lwhere ρ is the density of the seawater, Af and As are the frontal and lateral projected areas below the waterline, respectively, CX, CY, and CN are the empirical force coefficients, Vc is the relative current speed, β is the angle between the ocean current and the heading of the vessel, L is the length of the vessel, and τcurrentX, τcurrentY, and τcurrentN are the ocean current forces during surge, sway, and yaw, respectively [22].
## 2.3. Path Representation by Grids
The real task area is partitioned to reduce the modeling complexity. Visibility graphs [23], Voronoi diagrams [24], and grid maps [25] are the most commonly used path planning algorithms. The grid map-based path planning algorithm is powerful in that it generates a path with the shortest computation time [25]. To facilitate the calculation, the planned path is represented on grids. The area under consideration is discretized into grids. The information, such as the relative speed and direction of the wind, the amplitude and direction of the waves, the relative speed and direction of ocean current, and the position of the obstacles, is discretized in each grid. Stationary obstacles are encoded in a binary format on the grids. We assigned weights of 1 to all obstacle grids and weights of 0 to all free neighbor grids of them.
## 2.4. Objectives of USV Global Path Planning
Since USV global path planning is a multiobjective optimization problem, we should analyze the interrelated objectives and discuss the importance of each objective based on the requirements of the mission. A cost function can be constructed as a weighted sum of the objective functions. Finally, the cost function is used to evaluate the quality of the planned path.
### 2.4.1. Path Length
Since the task area is modeled by grids, the planned path is represented on a rectangular grid. The path passes the centers of the grids. Thus, the distanceLi,i+1 between two adjacent waypoints pi=(xi,yi) and pi+1=(xi+1,yi+1) is equal to the Euclidean distance between the centers of the grids as follows:(7)Li,i+1=1,xi=xi+1oryi=yi+12,otherwiseThe positions ofpi and pi+1 are shown in Figure 1. If pi and pi+1 are adjacent in the horizontal or vertical direction, Li,i+1=1. If pi and pi+1 are adjacent in the diagonal direction, Li,i+1=2.Figure 1
The positions ofpi and pi+1.Therefore, the total length of the pathL is the sum of the distances between the adjacent waypoints:(8)L=∑i=1mLi,i+1where m is the number of path segments.
### 2.4.2. Energy Consumption
In this paper, the energy consumption of the USV while sailing is derived from the propulsion system. Thus,E is the sum of the energy consumption of each segment along the entire path:(9)E=∑i=1mEi,i+1Supposing that the USV is sailing at a constant velocity betweenpi and pi+1, the energy consumption Ei,i+1 between pi and pi+1 equals the work done by the propulsion system to overcome the environmental loads, such that(10)Ei,i+1=τenv·v→usv·twhere t is the time for the USV to sail in Li,i+1.(11)t=Li,i+1v→outwhere v→usv is the magnitude of the velocity v→usv generated by the USV propulsion system, τenv is the resultant force of the environmental loads, and v→out is the magnitude of the velocity v→out of the USV moving in the horizontal plane. Since the headings of the USV in the grid are several fixed values, as shown in Figure 1, the angular velocity r caused by the yaw motion can be ignored when solving v→out. Hence, v→out is equal to(12)v→out=u2+v2where u and v are obtained by (1).It is known from (10) and (11) that the energy consumption is proportional to v→usv and 1/v→out, when the thrust τthr generated by the propulsion system is a fixed value. To reduce the energy consumption, it is necessary to adjust the USV’s heading to take advantage of the environmental loads to increase v→out.
### 2.4.3. Path Smoothness
It is assumed that the current waypoint of the USV ispi=(xi,yi), the previous waypoint is pi-1=(xi-1,yi-1), and the next waypoint is pi+1=(xi+1,yi+1). Thus, the angle θi+1 of the vector pipi+1→ and the angle θi of the vector pi-1pi→ are(13)θi+1=arctanyi+1-yixi+1-xi(14)θi=arctanyi-yi-1xi-xi-1The differenceψi between θi+1 and θi is(15)ψi=absθi+1-θiθ i, θi+1, and ψi, are shown in Figure 2. Therefore, the cost function of the path smoothness Jsmooth is(16)Jsmooth=∑i=1Nψiwhere N is the number of differences ψi.Figure 2
The angles of the path segments.
### 2.4.4. Path Safety
Using the safety cost of the nodes on the grids cannot accurately represent the threat impact of each path segment. First, three sampling points are selected on a path segment and the average Euclidean distance between the three sampling points and the center of the obstacle is calculated. The schematic diagram of the calculation of the path safety is shown in Figure3. lk is the length of the kth path segment between the waypoint pi and pi+1. For the kth path segment, three sampling points are taken at lk/6, lk/2, and 5lk/6, respectively. The average Euclidean distance between the three sampling points and the center of the obstacle is(17)DT,k=13dT,kjlk6+dT,kjlk2+dT,kj5lk6where dT,kj() is the Euclidean distance from the sampling point on the kth path segment to the center of the obstacle Tj.Figure 3
Schematic diagram of the calculation of the path safety.The path safety cost between waypointpi and pi+1 denoted as Jsafei,i+1 is(18)Jsafei,i+1=0,d>dsafe_max1DT,ki,i+1,dsafe_min≤d≤dsafe_max1,d<dsafe_minwhere d is the distance between the USV and the obstacle’s center, dsafe_max is the radius of the obstacle’s affected area, and dsafe_min is the radius of the no-sail zone. JT,ki,i+1 is obtained using (17).Thus, the entire path safety cost functionJsafe is(19)Jsafe=∑i=1NJsafei,i+1where N is the number of the waypoints of the planned path.
### 2.4.5. Cost Function
In summary, the cost function of the USV global path planning was established as(20)minJ=w1·L+w2·E+w3·Jsmooth+w4·Jsafewhere L, E, Jsmooth, and Jsafe are obtained by (8), (9), (16), and (19), respectively. w1, w2, w3, and w4 represent the weights of the path length, energy consumption, path smoothness, and path safety in the cost function, respectively, subject to(21)L≤Lmax0≤v→out≤vmaxwhere Lmax is the maximum voyage distance of the USV and vmax is the maximum speed of the USV.
## 2.4.1. Path Length
Since the task area is modeled by grids, the planned path is represented on a rectangular grid. The path passes the centers of the grids. Thus, the distanceLi,i+1 between two adjacent waypoints pi=(xi,yi) and pi+1=(xi+1,yi+1) is equal to the Euclidean distance between the centers of the grids as follows:(7)Li,i+1=1,xi=xi+1oryi=yi+12,otherwiseThe positions ofpi and pi+1 are shown in Figure 1. If pi and pi+1 are adjacent in the horizontal or vertical direction, Li,i+1=1. If pi and pi+1 are adjacent in the diagonal direction, Li,i+1=2.Figure 1
The positions ofpi and pi+1.Therefore, the total length of the pathL is the sum of the distances between the adjacent waypoints:(8)L=∑i=1mLi,i+1where m is the number of path segments.
## 2.4.2. Energy Consumption
In this paper, the energy consumption of the USV while sailing is derived from the propulsion system. Thus,E is the sum of the energy consumption of each segment along the entire path:(9)E=∑i=1mEi,i+1Supposing that the USV is sailing at a constant velocity betweenpi and pi+1, the energy consumption Ei,i+1 between pi and pi+1 equals the work done by the propulsion system to overcome the environmental loads, such that(10)Ei,i+1=τenv·v→usv·twhere t is the time for the USV to sail in Li,i+1.(11)t=Li,i+1v→outwhere v→usv is the magnitude of the velocity v→usv generated by the USV propulsion system, τenv is the resultant force of the environmental loads, and v→out is the magnitude of the velocity v→out of the USV moving in the horizontal plane. Since the headings of the USV in the grid are several fixed values, as shown in Figure 1, the angular velocity r caused by the yaw motion can be ignored when solving v→out. Hence, v→out is equal to(12)v→out=u2+v2where u and v are obtained by (1).It is known from (10) and (11) that the energy consumption is proportional to v→usv and 1/v→out, when the thrust τthr generated by the propulsion system is a fixed value. To reduce the energy consumption, it is necessary to adjust the USV’s heading to take advantage of the environmental loads to increase v→out.
## 2.4.3. Path Smoothness
It is assumed that the current waypoint of the USV ispi=(xi,yi), the previous waypoint is pi-1=(xi-1,yi-1), and the next waypoint is pi+1=(xi+1,yi+1). Thus, the angle θi+1 of the vector pipi+1→ and the angle θi of the vector pi-1pi→ are(13)θi+1=arctanyi+1-yixi+1-xi(14)θi=arctanyi-yi-1xi-xi-1The differenceψi between θi+1 and θi is(15)ψi=absθi+1-θiθ i, θi+1, and ψi, are shown in Figure 2. Therefore, the cost function of the path smoothness Jsmooth is(16)Jsmooth=∑i=1Nψiwhere N is the number of differences ψi.Figure 2
The angles of the path segments.
## 2.4.4. Path Safety
Using the safety cost of the nodes on the grids cannot accurately represent the threat impact of each path segment. First, three sampling points are selected on a path segment and the average Euclidean distance between the three sampling points and the center of the obstacle is calculated. The schematic diagram of the calculation of the path safety is shown in Figure3. lk is the length of the kth path segment between the waypoint pi and pi+1. For the kth path segment, three sampling points are taken at lk/6, lk/2, and 5lk/6, respectively. The average Euclidean distance between the three sampling points and the center of the obstacle is(17)DT,k=13dT,kjlk6+dT,kjlk2+dT,kj5lk6where dT,kj() is the Euclidean distance from the sampling point on the kth path segment to the center of the obstacle Tj.Figure 3
Schematic diagram of the calculation of the path safety.The path safety cost between waypointpi and pi+1 denoted as Jsafei,i+1 is(18)Jsafei,i+1=0,d>dsafe_max1DT,ki,i+1,dsafe_min≤d≤dsafe_max1,d<dsafe_minwhere d is the distance between the USV and the obstacle’s center, dsafe_max is the radius of the obstacle’s affected area, and dsafe_min is the radius of the no-sail zone. JT,ki,i+1 is obtained using (17).Thus, the entire path safety cost functionJsafe is(19)Jsafe=∑i=1NJsafei,i+1where N is the number of the waypoints of the planned path.
## 2.4.5. Cost Function
In summary, the cost function of the USV global path planning was established as(20)minJ=w1·L+w2·E+w3·Jsmooth+w4·Jsafewhere L, E, Jsmooth, and Jsafe are obtained by (8), (9), (16), and (19), respectively. w1, w2, w3, and w4 represent the weights of the path length, energy consumption, path smoothness, and path safety in the cost function, respectively, subject to(21)L≤Lmax0≤v→out≤vmaxwhere Lmax is the maximum voyage distance of the USV and vmax is the maximum speed of the USV.
## 3. Optimization Algorithm
In this section, we will introduce the optimization algorithm for the USV global path planning—the IQACA. The IQACA is a new optimization algorithm that combines quantum-inspired computing with ant colony optimization algorithm. We will introduce quantum code and a quantum rotation gate from quantum-inspired computing. Some rules based on the ant colony optimization algorithm are presented.
### 3.1. Quantum Code
The quantum bit (Q-bit) is the basic unit in quantum computing. A Q-bit is a system that has two possible states0 and 1. The state of a Q-bit φ is expressed as(22)φ=α0+β1where α and β are the probability amplitudes, which satisfy α2+β2=1. α2 and β2 are the probabilities in states 0 and 1, respectively. Thus, the state of the Q-bit φ is an uncertain superposition state between 0 and 1. When the number of Q-bits of an individual Xi is n, Xi is expressed as(23)Xi=αi1αi2…αinβi1βi2…βinwhere Xic=(αi1,⋯,αin) and Xis=(βi1,⋯,βin) are the two sets of solutions for individual Xi. Therefore, after quantum coding, every individual has two sets of solutions and the search space is doubled.In the IQACA, the quantum pheromone is obtained by encoding the pheromone left by the ants on the path in the ACA by the Q-bits. The transfer direction of the ants is selected by the quantum pheromone concentration on the path. Thus, the quantum pheromone concentration valueτijt of the ith ant on the jth point in the tth iteration is expressed as(24)τijt=αijtβijt
### 3.2. Adaptive Quantum Rotation Gate
In the quantum optimization algorithm, a quantum rotation gate is used to update the Q-bits. The update rule of a Q-bit is as follows:(25)αijt+1βijt+1=Uθtαijtβijtwhere [αijt,βijt]T represents the probability amplitude of the Q-bits in the tth iteration. U(θt) is the quantum rotation gate in the tth iteration(26)Uθt=cosθt-sinθtsinθtcosθtwhere θt is the rotation angle in the tth iteration. In a previous paper [13], the rotation angle was obtained by looking it up in a table. In another paper [26], the local and global updates of the pheromone concentration increments in the ACA were added to the rotation angle step function. In the IQACA, an adaptive adjustment strategy for the rotation angle is obtained by comparing the current solution and the global optimal solution currently being searched. Thus, the rotation angle θt in the tth iteration is(27)θt=-sgnAi·Δθiwhere -sgnAi is the direction of the rotation angle and Δθi is the size of the rotation angle. Ai is(28)Ai=α0α1β0β1where α0 and β0 are the probability amplitudes of the quantum pheromone corresponding to the global optimal solution currently searched and α1 and β1 are the probability amplitudes of the quantum pheromone corresponding to the current solution. Δθi is(29)Δθi=Je-Je-JkNmax·twhere Jk is the cost value of ant k in the current solution, Je is the cost value of the global optimal solution currently searched, and Nmax is the maximum number of iterations.
### 3.3. Transfer Rule and Transition Probability
The ant colony optimization algorithm is a bionic intelligent algorithm inspired by the foraging behavior of ant colonies [27]. During the foraging, ants produce a substance called a pheromone. The concentration of the pheromone, which is related to the path length, will determine the movement of other ants. If the path is shorter, the concentration of the pheromone left on the path is larger.To achieve multiobjective path planning, multiple pieces of heuristic information are used to determine the ant’s transfer rules and transition probabilities. The transfer rule of antk from point i to point j is(30)s=argmaxs∈Sτijktαηijktβεijtγq≤q0s~q>q0where q is a random number in the range [0,1]. q0 is a constant within [0,1]. S is the set of points that ant k may reach by point i. s~ is the target waypoint selected by the following equation:(31)pijkt=τijktαηijktβμijktγ∑s∈allowediτijktαηijktβμijktγwhere τijk(t) is the pheromone on the path from point i to point j in the tth iteration and α(α>0) is the pheromone index. ηijk(t) is the multiple inspiration information on the path from point i to point j in the tth iteration, β(β>0) is the index of multiple inspiration information, μijk(t) is the quantum information strength on the path from point i to point j in the tth iteration, which is expressed as μijk(t)=1/αijk(t)2, and γ(γ>0) is the index of the quantum information strength.The multiple pieces of heuristic information include the path length heuristic informationϕijk(t), energy consumption heuristic information εijk(t), path smoothness heuristic information φijk(t), and path safety heuristic information ζijk(t).(32)ηijktβ=ϕijktaεijktbφijktcζijktd(33)ϕijt=1Lijεijt=1Eijφijt=1Jsmoothijζijt=1Jsafeijwhere Lij, Eij, Jsmoothij, and Jsafeij are obtained by (8), (9), (16), and (19), respectively. a, b, c, and d are the indices of the path length heuristic information, energy consumption heuristic information, path smoothness heuristic information, and path safety heuristic information, respectively.
### 3.4. Update Rules of Pheromone
After every ant completes a one-transfer, the pheromone on the path it passes is locally updated to avoid falling into a local optimum. When the current point of the ant ispi and the next point is pj, the pheromone local updating rule is(34)τpj=1-ρ1·τpi+ρ1·Δτijwhere τ(pi) is the pheromone of the current point, τ(pj) is the pheromone of the next point, ρ1(0<ρ1<1) is the pheromone local updating coefficient, and Δτij is the pheromone that every ant leaves on the path from pi to pj in this iteration, expressed as follows:(35)Δτij=∑k=1nΔτijk(36)Δτijk=QJk,thepathsegmentofthekthant0,elsewhere Q is a constant and Jk is the cost value of the kth ant’s path.After all the ants complete an iteration, the pheromone is globally updated to increase the pheromone concentration on the optimized path. The rules are as follows:(37)τpj=1-ρ2·τpj+ρ2·Δτbest,pj=s~1-ρ2·τpj,pj≠s~(38)Δτbest=QJe,ifi,jbelongstotheoptimalpathinthiscycle0,elsewhere Q is a constant, Je is the cost value of the optimal path in this iteration, ρ2(0<ρ2<1) is the pheromone global updating coefficient, and s~ is the global optimal solution currently being searched.
### 3.5. Global Path Planning Algorithm Based on IQACA
The flowchart of global path planning algorithm based on the IQACA is shown in Figure4.Figure 4
The flowchart of the global path planning algorithm based on the IQACA.The main steps are as follows:Step 1 (initialize the parameters).
The number of the ants in the colony isn. The maximum number of iterations is Nmax. The initial quantum pheromone concentration value of the ith ant on the jth waypoint is expressed as τijt=[αijt,βijt]T=[1/2,1/2]T, where t=0;Step 2.
The ants are placed at the starting point. The transfer rule of the ants is determined by (30), and the target waypoint is selected by (31).Step 3.
The phases of the Q-bits are updated by (25).Step 4.
The pheromone is locally updated by (34).Step 5.
After all the ants have passed by all the points in an iteration, the pheromone is globally updated by (37).Step 6.
The candidate solution selected by the ants is output and the path cost is calculated.Step 7.
If the iterationt>Nmax, the algorithm moves to Step 8; otherwise, it returns to Step 2.Step 8.
The waypoints of the optimized solution and the cost value of the path are output. The global optimized path is obtained by the waypoints of the optimized solution.Step 9.
The algorithm ends.
## 3.1. Quantum Code
The quantum bit (Q-bit) is the basic unit in quantum computing. A Q-bit is a system that has two possible states0 and 1. The state of a Q-bit φ is expressed as(22)φ=α0+β1where α and β are the probability amplitudes, which satisfy α2+β2=1. α2 and β2 are the probabilities in states 0 and 1, respectively. Thus, the state of the Q-bit φ is an uncertain superposition state between 0 and 1. When the number of Q-bits of an individual Xi is n, Xi is expressed as(23)Xi=αi1αi2…αinβi1βi2…βinwhere Xic=(αi1,⋯,αin) and Xis=(βi1,⋯,βin) are the two sets of solutions for individual Xi. Therefore, after quantum coding, every individual has two sets of solutions and the search space is doubled.In the IQACA, the quantum pheromone is obtained by encoding the pheromone left by the ants on the path in the ACA by the Q-bits. The transfer direction of the ants is selected by the quantum pheromone concentration on the path. Thus, the quantum pheromone concentration valueτijt of the ith ant on the jth point in the tth iteration is expressed as(24)τijt=αijtβijt
## 3.2. Adaptive Quantum Rotation Gate
In the quantum optimization algorithm, a quantum rotation gate is used to update the Q-bits. The update rule of a Q-bit is as follows:(25)αijt+1βijt+1=Uθtαijtβijtwhere [αijt,βijt]T represents the probability amplitude of the Q-bits in the tth iteration. U(θt) is the quantum rotation gate in the tth iteration(26)Uθt=cosθt-sinθtsinθtcosθtwhere θt is the rotation angle in the tth iteration. In a previous paper [13], the rotation angle was obtained by looking it up in a table. In another paper [26], the local and global updates of the pheromone concentration increments in the ACA were added to the rotation angle step function. In the IQACA, an adaptive adjustment strategy for the rotation angle is obtained by comparing the current solution and the global optimal solution currently being searched. Thus, the rotation angle θt in the tth iteration is(27)θt=-sgnAi·Δθiwhere -sgnAi is the direction of the rotation angle and Δθi is the size of the rotation angle. Ai is(28)Ai=α0α1β0β1where α0 and β0 are the probability amplitudes of the quantum pheromone corresponding to the global optimal solution currently searched and α1 and β1 are the probability amplitudes of the quantum pheromone corresponding to the current solution. Δθi is(29)Δθi=Je-Je-JkNmax·twhere Jk is the cost value of ant k in the current solution, Je is the cost value of the global optimal solution currently searched, and Nmax is the maximum number of iterations.
## 3.3. Transfer Rule and Transition Probability
The ant colony optimization algorithm is a bionic intelligent algorithm inspired by the foraging behavior of ant colonies [27]. During the foraging, ants produce a substance called a pheromone. The concentration of the pheromone, which is related to the path length, will determine the movement of other ants. If the path is shorter, the concentration of the pheromone left on the path is larger.To achieve multiobjective path planning, multiple pieces of heuristic information are used to determine the ant’s transfer rules and transition probabilities. The transfer rule of antk from point i to point j is(30)s=argmaxs∈Sτijktαηijktβεijtγq≤q0s~q>q0where q is a random number in the range [0,1]. q0 is a constant within [0,1]. S is the set of points that ant k may reach by point i. s~ is the target waypoint selected by the following equation:(31)pijkt=τijktαηijktβμijktγ∑s∈allowediτijktαηijktβμijktγwhere τijk(t) is the pheromone on the path from point i to point j in the tth iteration and α(α>0) is the pheromone index. ηijk(t) is the multiple inspiration information on the path from point i to point j in the tth iteration, β(β>0) is the index of multiple inspiration information, μijk(t) is the quantum information strength on the path from point i to point j in the tth iteration, which is expressed as μijk(t)=1/αijk(t)2, and γ(γ>0) is the index of the quantum information strength.The multiple pieces of heuristic information include the path length heuristic informationϕijk(t), energy consumption heuristic information εijk(t), path smoothness heuristic information φijk(t), and path safety heuristic information ζijk(t).(32)ηijktβ=ϕijktaεijktbφijktcζijktd(33)ϕijt=1Lijεijt=1Eijφijt=1Jsmoothijζijt=1Jsafeijwhere Lij, Eij, Jsmoothij, and Jsafeij are obtained by (8), (9), (16), and (19), respectively. a, b, c, and d are the indices of the path length heuristic information, energy consumption heuristic information, path smoothness heuristic information, and path safety heuristic information, respectively.
## 3.4. Update Rules of Pheromone
After every ant completes a one-transfer, the pheromone on the path it passes is locally updated to avoid falling into a local optimum. When the current point of the ant ispi and the next point is pj, the pheromone local updating rule is(34)τpj=1-ρ1·τpi+ρ1·Δτijwhere τ(pi) is the pheromone of the current point, τ(pj) is the pheromone of the next point, ρ1(0<ρ1<1) is the pheromone local updating coefficient, and Δτij is the pheromone that every ant leaves on the path from pi to pj in this iteration, expressed as follows:(35)Δτij=∑k=1nΔτijk(36)Δτijk=QJk,thepathsegmentofthekthant0,elsewhere Q is a constant and Jk is the cost value of the kth ant’s path.After all the ants complete an iteration, the pheromone is globally updated to increase the pheromone concentration on the optimized path. The rules are as follows:(37)τpj=1-ρ2·τpj+ρ2·Δτbest,pj=s~1-ρ2·τpj,pj≠s~(38)Δτbest=QJe,ifi,jbelongstotheoptimalpathinthiscycle0,elsewhere Q is a constant, Je is the cost value of the optimal path in this iteration, ρ2(0<ρ2<1) is the pheromone global updating coefficient, and s~ is the global optimal solution currently being searched.
## 3.5. Global Path Planning Algorithm Based on IQACA
The flowchart of global path planning algorithm based on the IQACA is shown in Figure4.Figure 4
The flowchart of the global path planning algorithm based on the IQACA.The main steps are as follows:Step 1 (initialize the parameters).
The number of the ants in the colony isn. The maximum number of iterations is Nmax. The initial quantum pheromone concentration value of the ith ant on the jth waypoint is expressed as τijt=[αijt,βijt]T=[1/2,1/2]T, where t=0;Step 2.
The ants are placed at the starting point. The transfer rule of the ants is determined by (30), and the target waypoint is selected by (31).Step 3.
The phases of the Q-bits are updated by (25).Step 4.
The pheromone is locally updated by (34).Step 5.
After all the ants have passed by all the points in an iteration, the pheromone is globally updated by (37).Step 6.
The candidate solution selected by the ants is output and the path cost is calculated.Step 7.
If the iterationt>Nmax, the algorithm moves to Step 8; otherwise, it returns to Step 2.Step 8.
The waypoints of the optimized solution and the cost value of the path are output. The global optimized path is obtained by the waypoints of the optimized solution.Step 9.
The algorithm ends.
## 4. Simulation Studies
In this section, the effectiveness and efficiency of the IQACA are validated. The section consists of two parts. The first subsection compares the performance of the ACA, QACA, and IQACA with the Traveling Salesman Problem (TSP). The second subsection deals with the USV global path planning based on the IQACA. To validate the proposed algorithm, simulations were conducted.
### 4.1. Performance Evaluation of IQACA
To validate the effectiveness of the IQACA presented in this paper, we compared the algorithm performance between ACA, QACA, and IQACA with the TSP. In this paper, RAND100 was selected from the TSPLIB standard library for the simulations. The maximum number of iterationsNmax=200, the number of the ants n=100, α=3, β=1, γ=2, and ρ1=ρ2=0.8. The obtained values are shown in Table 1, and the iterations are shown in Figure 5.Table 1
The obtained values from the simulations.
Algorithm Length Iteration ACA 8447 167 QACA 8062 142 IQACA 7891 126Figure 5
Convergence of the IQACA, QACA, and ACA.The known optimal value of RAND100 is 7891. From Table1, it was concluded that the path length of RAND100 obtained by the IQACA was 2.12% lower than that obtained by the QACA and 6.58% lower than that obtained by the ACA. The number of iterations required for the IQACA to converge to the minimum was 11.27% lower than the QACA and 24.55% lower than the ACA. The results show that the IQACA was superior to the QACA and the ACA in both the path length and iteration number. Since the algorithm uses the pheromone local and global updates, and the phases of the Q-bits are updated by the adaptive quantum rotation gate, the IQACA can avoid the local optimal solution. Because the pheromone is encoded by Q-bits, the search space is doubled, and the convergence speed is faster. Thus, the IQACA is an effective and efficient algorithm.
### 4.2. USV Global Path Planning Based on IQACA
In this subsection, we will show a simulation of USV global path planning based on the proposed algorithm. Obstacles are black-colored. The coordinates of the starting point are(0.5,24.5), and the coordinates of the destination point are (29.5,0.5). The length of the side of a grid is 1km. We assumed that the wind, waves, and ocean current act on the vessel from the same direction, since in most cases the ocean current is the most significant environmental disturbance on the vessel. In this simulation, the direction of the disturbances is assumed as 240° in the Northeast coordinate system. The relative wind speed was 7.5m/s. The wave height was 2.5m. The relative ocean current was 2.0m/s. The thrust of the USV propulsion system was 500kN. The coefficients of the USV in this simulation are shown in Table 2. The maximum number of iterations was 500, the number of the ants was 100, α=3, γ=2, and ρ1=ρ2=0.8. The safety boundary of the obstacle was represented by a dotted red circle whose radius was 1.3 times the distance between the vertex and the center of the obstacle. The optimal path is represented by a solid blue line. The objectives of the global path planning were determined based on their respective weights. We considered four scenarios in this simulation. In the first scenario, we highly weighted the path length, so that the weights [w1,w2,w3,w4] in the cost function (20) were [0.5,0.1,0.3,0.1]. In the other three scenario, we weighted the energy consumption, path smoothness, and path safety, respectively, such that the weights [w1,w2,w3,w4] were [0.1,0.5,0.1,0.3], [0.3,0.1,0.5,0.1], and [0.1,0.3,0.1,0.5], respectively.Table 2
Coefficients of USV.
Property Value Length overall (m) 80.8 Breadth (m) 18.2 Draught (m) 5.0 Area of frontal projection above the waterline (m2) 330.9 Area of lateral projection above the waterline (m2) 874.8 Area of frontal projection below the waterline (m2) 91.0 Area of lateral projection below the waterline (m2) 323.4Figures6–9 show the planned paths in the four scenarios. The path length, energy consumption, path smoothness, and path safety index for each planned path are listed in Table 3. The results indicate that the proposed algorithm can plan feasible paths for the USV considering different objectives simultaneously. Moreover, by adjusting the weights of different objectives, the proposed algorithm can generate paths for different purposes.Table 3
Path data for different objectives.
Objective Path length(km) Energy consumption(1×107kJ) Path smoothness(rad) Path safety index Path length 41.87 12.38 18.85 26.89 Energy consumption 48.31 10.81 28.27 27.12 Path smoothness 43.63 11.95 14.14 15.51 Path safety 46.80 11.96 28.27 7.61Figure 6
Planned path focusing on the path length.Figure 7
Planned path focusing on the energy consumption.Figure 8
Planned path focusing on the path smoothness.Figure 9
Planned path focusing on the path safety.
## 4.1. Performance Evaluation of IQACA
To validate the effectiveness of the IQACA presented in this paper, we compared the algorithm performance between ACA, QACA, and IQACA with the TSP. In this paper, RAND100 was selected from the TSPLIB standard library for the simulations. The maximum number of iterationsNmax=200, the number of the ants n=100, α=3, β=1, γ=2, and ρ1=ρ2=0.8. The obtained values are shown in Table 1, and the iterations are shown in Figure 5.Table 1
The obtained values from the simulations.
Algorithm Length Iteration ACA 8447 167 QACA 8062 142 IQACA 7891 126Figure 5
Convergence of the IQACA, QACA, and ACA.The known optimal value of RAND100 is 7891. From Table1, it was concluded that the path length of RAND100 obtained by the IQACA was 2.12% lower than that obtained by the QACA and 6.58% lower than that obtained by the ACA. The number of iterations required for the IQACA to converge to the minimum was 11.27% lower than the QACA and 24.55% lower than the ACA. The results show that the IQACA was superior to the QACA and the ACA in both the path length and iteration number. Since the algorithm uses the pheromone local and global updates, and the phases of the Q-bits are updated by the adaptive quantum rotation gate, the IQACA can avoid the local optimal solution. Because the pheromone is encoded by Q-bits, the search space is doubled, and the convergence speed is faster. Thus, the IQACA is an effective and efficient algorithm.
## 4.2. USV Global Path Planning Based on IQACA
In this subsection, we will show a simulation of USV global path planning based on the proposed algorithm. Obstacles are black-colored. The coordinates of the starting point are(0.5,24.5), and the coordinates of the destination point are (29.5,0.5). The length of the side of a grid is 1km. We assumed that the wind, waves, and ocean current act on the vessel from the same direction, since in most cases the ocean current is the most significant environmental disturbance on the vessel. In this simulation, the direction of the disturbances is assumed as 240° in the Northeast coordinate system. The relative wind speed was 7.5m/s. The wave height was 2.5m. The relative ocean current was 2.0m/s. The thrust of the USV propulsion system was 500kN. The coefficients of the USV in this simulation are shown in Table 2. The maximum number of iterations was 500, the number of the ants was 100, α=3, γ=2, and ρ1=ρ2=0.8. The safety boundary of the obstacle was represented by a dotted red circle whose radius was 1.3 times the distance between the vertex and the center of the obstacle. The optimal path is represented by a solid blue line. The objectives of the global path planning were determined based on their respective weights. We considered four scenarios in this simulation. In the first scenario, we highly weighted the path length, so that the weights [w1,w2,w3,w4] in the cost function (20) were [0.5,0.1,0.3,0.1]. In the other three scenario, we weighted the energy consumption, path smoothness, and path safety, respectively, such that the weights [w1,w2,w3,w4] were [0.1,0.5,0.1,0.3], [0.3,0.1,0.5,0.1], and [0.1,0.3,0.1,0.5], respectively.Table 2
Coefficients of USV.
Property Value Length overall (m) 80.8 Breadth (m) 18.2 Draught (m) 5.0 Area of frontal projection above the waterline (m2) 330.9 Area of lateral projection above the waterline (m2) 874.8 Area of frontal projection below the waterline (m2) 91.0 Area of lateral projection below the waterline (m2) 323.4Figures6–9 show the planned paths in the four scenarios. The path length, energy consumption, path smoothness, and path safety index for each planned path are listed in Table 3. The results indicate that the proposed algorithm can plan feasible paths for the USV considering different objectives simultaneously. Moreover, by adjusting the weights of different objectives, the proposed algorithm can generate paths for different purposes.Table 3
Path data for different objectives.
Objective Path length(km) Energy consumption(1×107kJ) Path smoothness(rad) Path safety index Path length 41.87 12.38 18.85 26.89 Energy consumption 48.31 10.81 28.27 27.12 Path smoothness 43.63 11.95 14.14 15.51 Path safety 46.80 11.96 28.27 7.61Figure 6
Planned path focusing on the path length.Figure 7
Planned path focusing on the energy consumption.Figure 8
Planned path focusing on the path smoothness.Figure 9
Planned path focusing on the path safety.
## 5. Conclusion
This paper proposed a global path planning algorithm for the USV based on an improved quantum ant colony algorithm (IQACA).The IQACA is an optimization algorithm that combines quantum computing with the ACA. In IQACA, using Q-bits to encode the pheromone of the ants, the search space is doubled when the number of the ants is the same. The simulation results show that the proposed algorithm’s obtained minimum was 2.1–6.5% lower than those of the quantum ant colony algorithm (QACA) and ant colony algorithm (ACA), and the number of iterations required to converge to the minimum was 11.2–24.5% lower than those of the QACA and ACA. Based on the model of the kinetics of the USV and the marine environment, we defined the objectives of the path planning: the path length, energy consumption, path smoothness, and path safety. The simulation results showed that the proposed algorithm can consider several optimization objectives and generate paths satisfying these requirements.In the future, the following studies should be conducted in depth. First, the correlation between the multiple objectives should be calculated to determine the weight of each objective in the cost function to meet the actual mission requirements. Moreover, the kinetic and kinematic constraints of the USV should be added to the cost function. Finally, more practical environmental loads should be applied to calculate their effects on the path energy consumption of the USV.
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*Source: 2902170-2019-04-24.xml* | 2019 |
# Simulation of Vehicular Network Use in Emergency Situations and Security Applications on a Pakistan Highway
**Authors:** Asaad T. Al-Douri; Noor Mohammed Kadhim; A. A. Hamad Mohamad; Melese Abeyie
**Journal:** Security and Communication Networks
(2022)
**Publisher:** Hindawi
**License:** http://creativecommons.org/licenses/by/4.0/
**DOI:** 10.1155/2022/2902263
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## Abstract
VANETs (vehicular ad hoc networks), which are revolutionary techniques to enhance road safety, can be used to broadcast information about dangerous traffic conditions or accidents. However, distributing important information for driver safety and well-being has strict time and reliability requirements. This is because messages must be received by all cars involved in a potentially dangerous scenario for proper precautions to be taken to avoid the problem from materializing or intensifying. Because of the deterioration in conventional wireless communication system performance, ensuring that such requirements are met is a serious concern. To validate the concept before the actual installation of such systems and their absorption into the vehicle sector, it is therefore critical to employ simulation methodologies that are both reliable and thorough. This piece consists of large-scale, realistic security simulation research of an emergency situation based on actual road traffic data acquired on a Pakistan route. The study’s findings are detailed in the following paragraphs. Aspects such as the incorporation of fixed communication units along a stretch of roadway and the performance of the vehicular network notifying all vehicles engaged in the various accident scenarios modeled on the same stretch of highway were evaluated. Both of these characteristics were designed to increase safety and security applications. After doing the investigation, it was observed that when fixed communication units are incorporated into the network infrastructure, there is a shorter delay in receiving the accident notification. This was the conclusion made after reviewing the findings. Drivers of vehicles located closer to the accident site will be able to respond in a timely and safe manner as a result of this improvement in network performance, and drivers security of vehicles located further away will have the option of exiting the highway to avoid potential congestion caused by increased road traffic.
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## Body
## 1. Introduction
Pakistan’s increasing urbanization at 3.3% per year and population growth of about 2% per year have contributed to the country’s 18.3% increase in the number of motor vehicles registered during the last two decades [1]. Even though the country’s road network has not increased significantly in recent years, there has been a significant increase in automotive collisions in Pakistan. In Pakistan, the accident death rate is 14.2 per 100,000 people [2], an unacceptably high figure. According to the Pakistan Bureau of Statistics [3], 48,828 individuals died due to traffic accidents in Pakistan. The authors assessed the performance of Het-Net, which combines Wi-Fi, DSRC, and LTE technologies for V2V and V2I communications, and found that using other wireless technology could reduce the need for expensive DSRC infrastructure by up to 55%. An application layer handoff method was created to enable Het-Net communication for two CVT applications: traffic data collection [4]. The nation’s network of highways and motorways carries most of the country’s high-speed traffic. Several researchers have focused on the relationship analysis of accidents and numerous contributory components during the accident study done on roads and highways. Most of Pakistan’s highways and other roadways are classified as either national highways or motorways [5].The development of new wireless network technologies and the existence of low-cost embedded systems with high computational capacities gave rise to the emergence of vehicular networks, both in terms of research and of the market. This type of network enables the communication between vehicles (vehicle-to-vehicle (V2V)) and between them and the road infrastructure (vehicle-to-infrastructure (V2I)) [6].The main interest in VANETs arises from using new road safety paradigms based on cooperation between the various entities involved in communication [7], which significantly improve road safety and promote sustainable mobility. However, given the criticality of this type of application, simulation studies are needed in large-scale environments and conditions as close as possible to reality. The potential advantages of the technology can be verified before starting its introduction in vehicles and infrastructures.This work intends to analyze the feasibility of using vehicular networks in highway scenarios to respond to accident situations. Three different aspects are intended to be evaluated:(i)
The impact of roadside units (RSUs) in the accident notification process is to assess the need to invest in their installation.(ii)
The ability to give timely warning to vehicles close to the accident zone to avoid chain collisions.(iii)
The ability to warn vehicles far from the affected region to ensure that they can choose an alternative route, minimizing traffic congestion.The study presented in the simulation is based on the real case of the Pakistan motorway AH1/M-2 (Islamabad to Lahore motorway), which connects the capital, Islamabad, to Lahore. AH1/M-2 is located in Pakistan; the Lahore-Islamabad Motorway is a highway that runs from north to south and connects Rawalpindi/Islamabad to Lahore. This motorway is one of the several motorways under the responsibility of Pakistan road safety [8].
## 2. Review of Literature
### 2.1. Security Applications
The development of vehicular networks enables the development of new types of road safety applications. These applications are based on cooperation and information sharing between vehicles and the surrounding environment and aim to alert the driver of situations that affect safety and mobility conditions throughout the journey.In [9], characterization of the different types of applications was carried out, and it was concluded that safety applications should be used essentially to support accident situations, provide information at intersections, and avoid traffic congestion. However, many options regarding the most appropriate protocol architecture and communication mechanisms are left open.The study presented in [10] further characterizes the types of road safety applications, defining applications for five different purposes:(i)
Alert for dangerous infrastructure features.(ii)
Alert for abnormal traffic conditions.(iii)
Warning of collision danger.(iv)
Warning of impending shock.(v)
Accident notification.According to the same study, this type of application requires the use of new communication mechanisms that allow sending information to an unspecified set of nodes: dissemination within a geographic area (Geocast) and periodic dissemination to adjacent nodes (Beaconing). Multi-hop communication and store-and-forward are also used to guarantee the reception of information by nodes that are outside the initial range and correlation to reduce data traffic, especially in situations of a high density of vehicles.A crucial aspect of the performance of these applications is related to the definition of the scope of the Geocast and the validity time of the security information. In [11], the authors stipulate 250 m as an acceptable value for a maximum range of a Geocast communication and 10 s as a time limit for the validity of the information. However, an experimental study carried out in the context of the European Cooperative Vehicle-Infrastructure Systems (CVIS) project with a set of safety applications developed by the consortium concluded that the warning time should not exceed 5 s [11].For applications aimed at alerting drivers to potential accidents, there are other determining factors for their success, such as the accuracy of the vehicle’s location and the prediction of its movement, which are directly related to the time period between beacons. Studies reported in [12] show that a frequency of 5 Hz guarantees an adequate performance for this type of application.Several authors have also carried out performance studies on applications to avoid accidents at intersections [12, 13]. However, these studies do not apply to a motorway scenario, given the scenario’s different mobility patterns and characteristics.
### 2.2. Safety Applications for Emergency Situations
A potentially dangerous situation can trigger the transmission of messages generated by various road safety applications, of which the most relevant for an accident scenario are(i)
Sudden braking warning (emergency electronic brake lights (EEBL)).(ii)
Post-crash warning (PCW).(iii)
Cooperative collision warning (CCW) alert.The EEBL application allows a vehicle to notify vehicles behind it when it suddenly brakes. It is especially useful in poor visibility conditions where vehicles may not be aware in time that the vehicle in front has braked/activated the brake lights. The PCW application notifies vehicles approaching an accident scene of the presence of an immobilized vehicle due to an accident or mechanical failure. Finally, the CCW application mitigates the occurrence of collisions by sending periodic information about the position, speed, acceleration, and direction of each vehicle.According to [14, 15], these applications can be characterized according to different parameters, as shown in Table 1.Table 1
Characterization of road safety applications.
EEBLPCWCCWCommunication modeGeo-broadcastGeo-broadcastGeo-broadcastCardinalityUnidirectionalUnidirectionalUnidirectionalType of communicationV2VV2I, V2VV2VTransmission modeBy eventBy eventPeriodicallyFreq. min. messages (Hz)∼10∼1∼10Maximum latency (s)0.10.50.1Reach (m)∼300∼300∼150
## 2.1. Security Applications
The development of vehicular networks enables the development of new types of road safety applications. These applications are based on cooperation and information sharing between vehicles and the surrounding environment and aim to alert the driver of situations that affect safety and mobility conditions throughout the journey.In [9], characterization of the different types of applications was carried out, and it was concluded that safety applications should be used essentially to support accident situations, provide information at intersections, and avoid traffic congestion. However, many options regarding the most appropriate protocol architecture and communication mechanisms are left open.The study presented in [10] further characterizes the types of road safety applications, defining applications for five different purposes:(i)
Alert for dangerous infrastructure features.(ii)
Alert for abnormal traffic conditions.(iii)
Warning of collision danger.(iv)
Warning of impending shock.(v)
Accident notification.According to the same study, this type of application requires the use of new communication mechanisms that allow sending information to an unspecified set of nodes: dissemination within a geographic area (Geocast) and periodic dissemination to adjacent nodes (Beaconing). Multi-hop communication and store-and-forward are also used to guarantee the reception of information by nodes that are outside the initial range and correlation to reduce data traffic, especially in situations of a high density of vehicles.A crucial aspect of the performance of these applications is related to the definition of the scope of the Geocast and the validity time of the security information. In [11], the authors stipulate 250 m as an acceptable value for a maximum range of a Geocast communication and 10 s as a time limit for the validity of the information. However, an experimental study carried out in the context of the European Cooperative Vehicle-Infrastructure Systems (CVIS) project with a set of safety applications developed by the consortium concluded that the warning time should not exceed 5 s [11].For applications aimed at alerting drivers to potential accidents, there are other determining factors for their success, such as the accuracy of the vehicle’s location and the prediction of its movement, which are directly related to the time period between beacons. Studies reported in [12] show that a frequency of 5 Hz guarantees an adequate performance for this type of application.Several authors have also carried out performance studies on applications to avoid accidents at intersections [12, 13]. However, these studies do not apply to a motorway scenario, given the scenario’s different mobility patterns and characteristics.
## 2.2. Safety Applications for Emergency Situations
A potentially dangerous situation can trigger the transmission of messages generated by various road safety applications, of which the most relevant for an accident scenario are(i)
Sudden braking warning (emergency electronic brake lights (EEBL)).(ii)
Post-crash warning (PCW).(iii)
Cooperative collision warning (CCW) alert.The EEBL application allows a vehicle to notify vehicles behind it when it suddenly brakes. It is especially useful in poor visibility conditions where vehicles may not be aware in time that the vehicle in front has braked/activated the brake lights. The PCW application notifies vehicles approaching an accident scene of the presence of an immobilized vehicle due to an accident or mechanical failure. Finally, the CCW application mitigates the occurrence of collisions by sending periodic information about the position, speed, acceleration, and direction of each vehicle.According to [14, 15], these applications can be characterized according to different parameters, as shown in Table 1.Table 1
Characterization of road safety applications.
EEBLPCWCCWCommunication modeGeo-broadcastGeo-broadcastGeo-broadcastCardinalityUnidirectionalUnidirectionalUnidirectionalType of communicationV2VV2I, V2VV2VTransmission modeBy eventBy eventPeriodicallyFreq. min. messages (Hz)∼10∼1∼10Maximum latency (s)0.10.50.1Reach (m)∼300∼300∼150
## 3. Characterization of the Scenario
### 3.1. General Information
The AH1/M-2 highway is considered one of the most congested highways in the country since it is one of the two main access routes to the city of Islamabad. The 25 kilometers between Islamabad and Lahore on the AH1/M-2 include 12 intersections with 60 access routes.In terms of technology, AH1/M-2 is a highway equipped with an advanced infrastructure, made up of a backbone, which interlinks a set of sensors, video surveillance cameras (CCTV), and variable message boards (PMVs). The CCTV poles are placed laterally in locations that offer good visibility, and the PMVs are placed on raised porches perpendicular to AH1/M-2. In any two cases, these systems are spread over the entire length of the highway, being placed at about 6 m height. There are sensors at the entrances and exits and sensors located along two different sections of the AH1/M-2. Currently, this infrastructure is used to collect traffic information, identify dangerous situations, detect accidents, and provide information to drivers about traffic conditions. All information is centralized at the operational coordination center—CCO, which manages all highways concessioned by the SKB Engineering group.The variety of sensorization equipment available enables the collection of data of a variety of types, including traffic intensity and density, class, the combined weight of two vehicles, and average speed, Het-Net might offer extra supplemental connectivity for safety applications to notify upstream vehicles to take preventative measures to avoid issue spots. This information is delivered and processed to central systems for statistical processing before being sent, in quasireal time, to PMVs to avoid problem locations.
### 3.2. Characterization of Traffic
A historical record of traffic information allows modeling the traffic in a macroscopic way [14]. This record indicates the average intensity of traffic in different locations, measured every 10 minutes. In addition, there is also a record of the origin-destination matrix for every two accesses of AH1/M-2. Based on the analysis of the registered information, it was possible to determine the intensity of traffic in different sections throughout the day. The values were obtained from the three most representative locations in different periods of the day: o period of less traffic (2:00-3:00 a.m.), o period of higher traffic (8:00-9:00 a.m.), and a period of medium traffic (13:00-14:00).
### 3.3. Characterization of the Accident Conditions
For the history of traffic, SKB Engineering also has information that allows for identifying the locations most prone to accidents and defining the most frequent causes. According to the data made available by SKB Engineering, there are five most critical areas [15].In the first zone, it occurs in the Islamabad to Lahore section, between departures 9 and 10. The main cause of accidents consists of strong winds and excessive speed, which results in the vehicle not being misled and, possibly, in an accident. The second area is located next to CREL, near exit 6, not in the Islamabad to Lahore direction. In this area, the accidents are caused mainly by the sudden variation in traffic density on the curve that immediately precedes a departure. Drivers who dislodge at excessive speed are not aware of the rapid formation of a queue next to the exit and are forced to reduce speed abruptly. The following two locations are located close to the departure point for the National Stadium: a sharp curve, combined with the excessive speed of two vehicles, is the main cause of accidents. The last area is located near Exit 5, not in the Islamabad to Lahore direction, in the direction of Islamabad to Lahore. More than once, the main cause of the accident was excessive speed [16]. Even though they occur often, road accidents are the worst thing that may happen to a road user. The most regrettable aspect is that we don't learn from our on-the-road errors. The majority of road users are generally relatively aware of the general norms and safety precautions when using the roads; it is only the road users' slack attitude due to overspeeding, drunk driving, driver distractions, red light jumping, and avoiding safety equipment such seat belts and helmets. . Still, in certain situations, accidents occur in high-traffic conditions, which can occur even when the traffic is heavy. Likewise, it is essential to model the occurrence of accidents in different traffic conditions.
## 3.1. General Information
The AH1/M-2 highway is considered one of the most congested highways in the country since it is one of the two main access routes to the city of Islamabad. The 25 kilometers between Islamabad and Lahore on the AH1/M-2 include 12 intersections with 60 access routes.In terms of technology, AH1/M-2 is a highway equipped with an advanced infrastructure, made up of a backbone, which interlinks a set of sensors, video surveillance cameras (CCTV), and variable message boards (PMVs). The CCTV poles are placed laterally in locations that offer good visibility, and the PMVs are placed on raised porches perpendicular to AH1/M-2. In any two cases, these systems are spread over the entire length of the highway, being placed at about 6 m height. There are sensors at the entrances and exits and sensors located along two different sections of the AH1/M-2. Currently, this infrastructure is used to collect traffic information, identify dangerous situations, detect accidents, and provide information to drivers about traffic conditions. All information is centralized at the operational coordination center—CCO, which manages all highways concessioned by the SKB Engineering group.The variety of sensorization equipment available enables the collection of data of a variety of types, including traffic intensity and density, class, the combined weight of two vehicles, and average speed, Het-Net might offer extra supplemental connectivity for safety applications to notify upstream vehicles to take preventative measures to avoid issue spots. This information is delivered and processed to central systems for statistical processing before being sent, in quasireal time, to PMVs to avoid problem locations.
## 3.2. Characterization of Traffic
A historical record of traffic information allows modeling the traffic in a macroscopic way [14]. This record indicates the average intensity of traffic in different locations, measured every 10 minutes. In addition, there is also a record of the origin-destination matrix for every two accesses of AH1/M-2. Based on the analysis of the registered information, it was possible to determine the intensity of traffic in different sections throughout the day. The values were obtained from the three most representative locations in different periods of the day: o period of less traffic (2:00-3:00 a.m.), o period of higher traffic (8:00-9:00 a.m.), and a period of medium traffic (13:00-14:00).
## 3.3. Characterization of the Accident Conditions
For the history of traffic, SKB Engineering also has information that allows for identifying the locations most prone to accidents and defining the most frequent causes. According to the data made available by SKB Engineering, there are five most critical areas [15].In the first zone, it occurs in the Islamabad to Lahore section, between departures 9 and 10. The main cause of accidents consists of strong winds and excessive speed, which results in the vehicle not being misled and, possibly, in an accident. The second area is located next to CREL, near exit 6, not in the Islamabad to Lahore direction. In this area, the accidents are caused mainly by the sudden variation in traffic density on the curve that immediately precedes a departure. Drivers who dislodge at excessive speed are not aware of the rapid formation of a queue next to the exit and are forced to reduce speed abruptly. The following two locations are located close to the departure point for the National Stadium: a sharp curve, combined with the excessive speed of two vehicles, is the main cause of accidents. The last area is located near Exit 5, not in the Islamabad to Lahore direction, in the direction of Islamabad to Lahore. More than once, the main cause of the accident was excessive speed [16]. Even though they occur often, road accidents are the worst thing that may happen to a road user. The most regrettable aspect is that we don't learn from our on-the-road errors. The majority of road users are generally relatively aware of the general norms and safety precautions when using the roads; it is only the road users' slack attitude due to overspeeding, drunk driving, driver distractions, red light jumping, and avoiding safety equipment such seat belts and helmets. . Still, in certain situations, accidents occur in high-traffic conditions, which can occur even when the traffic is heavy. Likewise, it is essential to model the occurrence of accidents in different traffic conditions.
## 4. Vehicle Support Network for Emergency Applications
### 4.1. Architecture of the Vehicular Network
Two fundamental aspects to be balanced do not design a vehicular network with the need to use fixed communication units (RSUs) properly positioned to increase the coverage of communication in order to ensure better connectivity.In the case of AH1/M-2, there is already a network infrastructure, so it is relatively easy to find suitable locations to place the aforementioned RSUs, namely, locations with better visibility, where the CCTV cameras or PMVs are currently located. Still, it is necessary to guarantee that there is a significant improvement in performance, which justifies the investment to carry out the RSUs. Likewise, two different scenarios will be considered:(i)
Vehicular network without RSUs that supports only vehicle-to-vehicle (V2V) communication.(ii)
Vehicle network with RSUSs that also supports vehicle-to-infrastructure (V2I/I2V) communication.Figure1 represents the complete case, with a network containing RSUs allowing V2V and V2I/I2V communication.Figure 1
Proposed VANET architecture.In a real situation, the vehicles and the RSUs may be equipped with antennas with different characteristics. V2I is used where an RSU is available, and V2V multihop communication is used where the RSU's communication range cannot reach, with the knowledge that the antennas of the RSUs have a greater range and that they are located above the height of two vehicles to prevent them from acting as an obstruction to the propagation of the signal, this method could be successful for roads and highways with sparsely distributed RSUs. As can be seen, the subject of this study is V2V multihop communication because it is crucial to EM broadcasting for accident prevention [17].
### 4.2. Architecture
Figure2 illustrates the architecture for all of us on the network, which must be similar for all of us and adaptable to various types of applications. Also, vehicles and RSUs support a set of road safety applications, with the information generated by these applications being disseminated within a given geographic area using an unreliable transport protocol and a geographic routing protocol or GPSR (Greedy Perimeter Stateless Routing) [18]. The geographic routing protocol was modified to support communication within a geographic area, limited or not, to a restricted set of us, the performance of vehicular networks on highways, taking into account aspects such as the feasibility of placing RSUs along with the infrastructure and its impact on this same performance. In terms of access to the medium and physical transmission of data, the protocols implemented in the IEEE 802.11p standard are used, on which the WAVE (wireless access in vehicular environment) systems are based [17].Figure 2
Architecture of a network node.
### 4.3. Emergency Applications
In the event of an accident, it is crucial to ensure that, firstly, the accident does not escalate and, secondly, to avoid the formation of long and lengthy traffic queues, whose tails can also imply sudden braking, leading to second accidents.It is considered that, immediately after the accident, the vehicle notifies those approaching from its rear if the damage caused by the accident does not make it impossible. Vehicles approaching the accident site may be at a point on the motorway that precedes an exit, so they can anticipate their departure from the motorway upon receiving the warning. Vehicles that are very close to the accident scene, to the point of having to drastically reduce their speed when they perceive a dangerous approach to the vehicle in front, must transmit sudden braking/risk of imminent collision in the rear warnings to the other vehicles.This modeling will allow analyzing the coexistence of several road safety applications and their impact on communication in an emergency scenario.From an application point of view, it is necessary to support the three applications, namely,(i)
PCW application—used to notify the occurrence of an accident. The crashed vehicle generates notifications for a short time. These notifications are resent by the vehicles that receive them in order to ensure that the information reaches quickly beyond the affected area. However, in order to avoid broadcast storm situations, such as those described in [19], these notifications are only resent the first time they are received through a simple correlation mechanism.(ii)
EEBL application—used to warn vehicles of sudden braking by the vehicle in front. The braking vehicle generates messages for a short time at a relatively high rate. These messages are not forwarded by the vehicles that receive them.(iii)
CCW application—used to detect potential collision situations based on the location information it periodically receives from its neighbors. The messages generated by each node have an exclusively local character, not being forwarded to nodes that are not adjacent to it.For an effective response to an emergency situation, it is essential to ensure that, despite the coexistence of road safety traffic from different applications, it is possible to fulfill the requirements previously stipulated for each of them, namely, in terms of the ability to notify vehicles of a situation of an accident.
## 4.1. Architecture of the Vehicular Network
Two fundamental aspects to be balanced do not design a vehicular network with the need to use fixed communication units (RSUs) properly positioned to increase the coverage of communication in order to ensure better connectivity.In the case of AH1/M-2, there is already a network infrastructure, so it is relatively easy to find suitable locations to place the aforementioned RSUs, namely, locations with better visibility, where the CCTV cameras or PMVs are currently located. Still, it is necessary to guarantee that there is a significant improvement in performance, which justifies the investment to carry out the RSUs. Likewise, two different scenarios will be considered:(i)
Vehicular network without RSUs that supports only vehicle-to-vehicle (V2V) communication.(ii)
Vehicle network with RSUSs that also supports vehicle-to-infrastructure (V2I/I2V) communication.Figure1 represents the complete case, with a network containing RSUs allowing V2V and V2I/I2V communication.Figure 1
Proposed VANET architecture.In a real situation, the vehicles and the RSUs may be equipped with antennas with different characteristics. V2I is used where an RSU is available, and V2V multihop communication is used where the RSU's communication range cannot reach, with the knowledge that the antennas of the RSUs have a greater range and that they are located above the height of two vehicles to prevent them from acting as an obstruction to the propagation of the signal, this method could be successful for roads and highways with sparsely distributed RSUs. As can be seen, the subject of this study is V2V multihop communication because it is crucial to EM broadcasting for accident prevention [17].
## 4.2. Architecture
Figure2 illustrates the architecture for all of us on the network, which must be similar for all of us and adaptable to various types of applications. Also, vehicles and RSUs support a set of road safety applications, with the information generated by these applications being disseminated within a given geographic area using an unreliable transport protocol and a geographic routing protocol or GPSR (Greedy Perimeter Stateless Routing) [18]. The geographic routing protocol was modified to support communication within a geographic area, limited or not, to a restricted set of us, the performance of vehicular networks on highways, taking into account aspects such as the feasibility of placing RSUs along with the infrastructure and its impact on this same performance. In terms of access to the medium and physical transmission of data, the protocols implemented in the IEEE 802.11p standard are used, on which the WAVE (wireless access in vehicular environment) systems are based [17].Figure 2
Architecture of a network node.
## 4.3. Emergency Applications
In the event of an accident, it is crucial to ensure that, firstly, the accident does not escalate and, secondly, to avoid the formation of long and lengthy traffic queues, whose tails can also imply sudden braking, leading to second accidents.It is considered that, immediately after the accident, the vehicle notifies those approaching from its rear if the damage caused by the accident does not make it impossible. Vehicles approaching the accident site may be at a point on the motorway that precedes an exit, so they can anticipate their departure from the motorway upon receiving the warning. Vehicles that are very close to the accident scene, to the point of having to drastically reduce their speed when they perceive a dangerous approach to the vehicle in front, must transmit sudden braking/risk of imminent collision in the rear warnings to the other vehicles.This modeling will allow analyzing the coexistence of several road safety applications and their impact on communication in an emergency scenario.From an application point of view, it is necessary to support the three applications, namely,(i)
PCW application—used to notify the occurrence of an accident. The crashed vehicle generates notifications for a short time. These notifications are resent by the vehicles that receive them in order to ensure that the information reaches quickly beyond the affected area. However, in order to avoid broadcast storm situations, such as those described in [19], these notifications are only resent the first time they are received through a simple correlation mechanism.(ii)
EEBL application—used to warn vehicles of sudden braking by the vehicle in front. The braking vehicle generates messages for a short time at a relatively high rate. These messages are not forwarded by the vehicles that receive them.(iii)
CCW application—used to detect potential collision situations based on the location information it periodically receives from its neighbors. The messages generated by each node have an exclusively local character, not being forwarded to nodes that are not adjacent to it.For an effective response to an emergency situation, it is essential to ensure that, despite the coexistence of road safety traffic from different applications, it is possible to fulfill the requirements previously stipulated for each of them, namely, in terms of the ability to notify vehicles of a situation of an accident.
## 5. Accident Scenario Modeling
### 5.1. Characterization of the Accident Scenario
In order to obtain reliable results, an attempt was made to reproduce an accident scenario in simulation. Among the various types of cases identified in Section 3.3, the first was chosen, as it was the one where the most accidents were reported. This location (Jhelum, Punjab, Pakistan, (32.675778, 72.755291), shown in Figure3, is located on the Islamabad to Lahore (direction: Islamabad), close to k22.1 km, and in an area where the motorway has three lanes where accidents often happen there. The distance between the exit immediately before the accident site (10th exit) is approximately 1.2 km (red spot marker in the figure). To take advantage of the existing infrastructure, the RSUs must be placed next to the CCTV poles or next to the PMVs (marked in the figure with blue markers). However, since the distance between them is only a few hundred meters, there will be no need to install RSUs in all locations. The vehicle moves at the maximum permitted speed (120 km/h), so the RSUs must be placed next. Therefore, it was decided to include in the scenario, modeling only MSWs with an average distance between them of about 1 km (MSW 1, 2, and 3) for to be safe and avoid a collision, and this is a relatively simple representation of reality since it does not consider the natural distribution of vehicle departure times and their movement.Figure 3
Islamabad to Lahore section of the AH1/M-2 motorway.As mentioned earlier, the most frequent cause of accidents is speeding. However, accidents can occur in situations of high-traffic intensity or even in situations of low intensity. Any of these scenarios can have a strong impact on the performance of the vehicular network, as the first can lead to an overload of data traffic, and the second can lead to a lack of connectivity in the network. In order to better assess the impact of these two extreme cases, it was decided to select the values recorded section for the period with the highest traffic. At this stage, if your resource does not show up in the Endpoint list and you created both your hosted zone and the resource to which you are directing traffic using the same AWS account, make sure the following: verify that the record type you selected is supported, specific to the resource you are routing traffic to, for instance, you must select A — IPv4 address for the record type if you want to direct traffic to an S3 bucket.
### 5.2. Mobility Model
The mobility simulator MOVE1 (Mobility Model Generator for Vehicular Networks) was used for the mobility simulation since it fits the scenario under study. This road traffic generator allows the modeling of scenarios with a high number of nodes, taking into account both aspects of macro and micro-mobility [2], and allows the interconnection to the used network simulator—the ns-32.Based on the scenario described above, a section was defined in MOVE’s Map Editor with the characteristics indicated in Tables2 and 3. It should be noted that MOVE does not allow the creation of complex profiles with curves and unevenness, so it is not possible to represent the geography of the section in question accurately.Table 2
Characterization of the highway section of the AH1/M-2.
Length of the section (m)3000 (22 km to 25 km)Direction of trafficIslamabad to LahoreNumber of ways02 to 03Speed limit (km/h)120Table 3
Location of the most relevant points.
Real position (km)Position MOVE (m)Local accident22.0752925First departure23.231770MSW 124.84160MSW 223.791210MSW 322.62400To model the mobility of the nodes, we used vehicle movement generator based on previously defined traffic intensity values. The RSUs were represented using fixed nodes located at the exact coordinates of the previously selected CCTV systems. The mobility model used by MOVE is the car-following model [20, 21], managing to model the acceleration, braking, or lane change following the approach of other vehicles and the constant speed that allows for maintaining the minimum safety distance from the front vehicle. However, it does not consider the drivers’ response to stimuli, which could be interesting for modeling accident situations. In the model used, at the initial instant, the vehicles are all at the starting point, corresponding to the entrance to the highway. The departure time of each vehicle is randomly defined, following a uniform distribution, with values between the initial time and the final time of the simulation (180 s). The vehicle starts moving at the maximum permitted speed (120 km/h). This is a relatively simple representation of reality since it does not consider the real distribution of vehicle departure times and their movement, thus being able to condition the traffic density that is obtained and, consequently, the network’s performance. However, the existing real data do not allow a more detailed characterization.The modeling of the accident scene was carried out considering two different situations: in the first situation, the vehicle victim of the accident is stopped, preventing circulation in one of the carriageways; in the second situation, the three lanes are blocked, one by the injured vehicle and the others, e.g., by assistance vehicles.
### 5.3. Vehicle Network Modeling
The simulation of the accident scenario was performed using the ns-3 network simulator. The choice of this simulator was due to the fact that it is a free-to-use tool widely used by the scientific community, which allows complex simulations to be carried out with a level of detail that allows the reproduction of real results in a very reliable way.The vehicular network architecture is implemented by importing the MOVE output file, which contains the position of each node at each instant of simulation time. In simulations involving V2I/I2V communication, RSUs are special nodes whose position coordinate is maintained throughout the simulation. Vehicle entry and movement are carried out according to the mobility model described above.The fact that ns-3 does not yet have all the modules necessary to simulate a node with the proposed architecture (Figure2) led to the need to make adaptations to the model proposed previously.The previously considered applications are modeled through CBR (constant bit rate) traffic generators, with different time configurations between message generation. For the sake of simplicity, all messages have the same size (480 bytes), which was defined in order to ensure that the security information is already included in the packet, following the indications defined in [17–19].As previously mentioned, information from the PCW application has to reach all nodes quickly, which is achieved by having the receiving nodes resend the information received for the first time, while the information from the other applications has a local character. This behavior was modeled by defining the time to live (TTL) field in the message, which allows controlling the number of times the message is retransmitted. Therefore, for the PCW application, a value was selected that allows the message to be retransmitted the number of times necessary to allow its reception by nodes that are before the exit at the moment of the accident. This value must be parameterized for the different scenarios that may be considered. In order to respect the functional principles defined above, the PCW and EEBL applications only start when an accident occurs. The values used are shown in Table4.Table 4
Parameterization of traffic generators.
PCWEEBLCCWSize of messages (B)480480480Frequency (Hz)882DestinyAllAllAllTTL6022Start time (s)TaccidentTaccident0End instant (s)TsimulationTsimulationTsimulationThe simulation model developed uses the UDP protocol as an unreliable transport protocol at the transport level. At the routing level, a module was used that implements the GPSR geographic routing protocol [20], with a location service similar to the one used by Karp and Kung in the specification of the protocol itself.At the MAC layer level, the biggest limitations arise since ns-3 does not yet support the 802.11p protocol [17]. Thus, it was necessary to resort to the module that implements 802.11 communication in ad hoc mode. With this solution, there is no support for quality of service and switching between channels, which are essential mechanisms for the coexistence of security applications with other types of applications. The fact that applications other than those related to emergency scenarios are not being considered strongly reduces the impact of this limitation. It may, however, happen that, due to the inability to differentiate the various applications in use, the performance of the most critical application—PCW—is affected.The physical layer already has support for the 802.11p standard, and this was the model used. In order to obtain simulation results that approximate the real conditions as closely as possible, special care was taken in the choice of propagation models. We chose to use a model that accounts for losses due to signal attenuation with distance (path loss) and another that accounts for losses due to the effects of signal dispersion (multi-path fading). Therefore, the two-ray ground reflection and Nakagami [22] models are used. The range of the different types of antennas was modeled using the configuration of transmission power and antenna gain. The values used are shown in Table 5.Table 5
Parameterization of propagation models and antennas.
VehicleRSUNakagami modelNakagamim-factorm01.5m10.75m20.5Two-ray ground modelHeight (m)1.76.3AntennasTransmission power (dBm)518Hook (dBi)29
## 5.1. Characterization of the Accident Scenario
In order to obtain reliable results, an attempt was made to reproduce an accident scenario in simulation. Among the various types of cases identified in Section 3.3, the first was chosen, as it was the one where the most accidents were reported. This location (Jhelum, Punjab, Pakistan, (32.675778, 72.755291), shown in Figure3, is located on the Islamabad to Lahore (direction: Islamabad), close to k22.1 km, and in an area where the motorway has three lanes where accidents often happen there. The distance between the exit immediately before the accident site (10th exit) is approximately 1.2 km (red spot marker in the figure). To take advantage of the existing infrastructure, the RSUs must be placed next to the CCTV poles or next to the PMVs (marked in the figure with blue markers). However, since the distance between them is only a few hundred meters, there will be no need to install RSUs in all locations. The vehicle moves at the maximum permitted speed (120 km/h), so the RSUs must be placed next. Therefore, it was decided to include in the scenario, modeling only MSWs with an average distance between them of about 1 km (MSW 1, 2, and 3) for to be safe and avoid a collision, and this is a relatively simple representation of reality since it does not consider the natural distribution of vehicle departure times and their movement.Figure 3
Islamabad to Lahore section of the AH1/M-2 motorway.As mentioned earlier, the most frequent cause of accidents is speeding. However, accidents can occur in situations of high-traffic intensity or even in situations of low intensity. Any of these scenarios can have a strong impact on the performance of the vehicular network, as the first can lead to an overload of data traffic, and the second can lead to a lack of connectivity in the network. In order to better assess the impact of these two extreme cases, it was decided to select the values recorded section for the period with the highest traffic. At this stage, if your resource does not show up in the Endpoint list and you created both your hosted zone and the resource to which you are directing traffic using the same AWS account, make sure the following: verify that the record type you selected is supported, specific to the resource you are routing traffic to, for instance, you must select A — IPv4 address for the record type if you want to direct traffic to an S3 bucket.
## 5.2. Mobility Model
The mobility simulator MOVE1 (Mobility Model Generator for Vehicular Networks) was used for the mobility simulation since it fits the scenario under study. This road traffic generator allows the modeling of scenarios with a high number of nodes, taking into account both aspects of macro and micro-mobility [2], and allows the interconnection to the used network simulator—the ns-32.Based on the scenario described above, a section was defined in MOVE’s Map Editor with the characteristics indicated in Tables2 and 3. It should be noted that MOVE does not allow the creation of complex profiles with curves and unevenness, so it is not possible to represent the geography of the section in question accurately.Table 2
Characterization of the highway section of the AH1/M-2.
Length of the section (m)3000 (22 km to 25 km)Direction of trafficIslamabad to LahoreNumber of ways02 to 03Speed limit (km/h)120Table 3
Location of the most relevant points.
Real position (km)Position MOVE (m)Local accident22.0752925First departure23.231770MSW 124.84160MSW 223.791210MSW 322.62400To model the mobility of the nodes, we used vehicle movement generator based on previously defined traffic intensity values. The RSUs were represented using fixed nodes located at the exact coordinates of the previously selected CCTV systems. The mobility model used by MOVE is the car-following model [20, 21], managing to model the acceleration, braking, or lane change following the approach of other vehicles and the constant speed that allows for maintaining the minimum safety distance from the front vehicle. However, it does not consider the drivers’ response to stimuli, which could be interesting for modeling accident situations. In the model used, at the initial instant, the vehicles are all at the starting point, corresponding to the entrance to the highway. The departure time of each vehicle is randomly defined, following a uniform distribution, with values between the initial time and the final time of the simulation (180 s). The vehicle starts moving at the maximum permitted speed (120 km/h). This is a relatively simple representation of reality since it does not consider the real distribution of vehicle departure times and their movement, thus being able to condition the traffic density that is obtained and, consequently, the network’s performance. However, the existing real data do not allow a more detailed characterization.The modeling of the accident scene was carried out considering two different situations: in the first situation, the vehicle victim of the accident is stopped, preventing circulation in one of the carriageways; in the second situation, the three lanes are blocked, one by the injured vehicle and the others, e.g., by assistance vehicles.
## 5.3. Vehicle Network Modeling
The simulation of the accident scenario was performed using the ns-3 network simulator. The choice of this simulator was due to the fact that it is a free-to-use tool widely used by the scientific community, which allows complex simulations to be carried out with a level of detail that allows the reproduction of real results in a very reliable way.The vehicular network architecture is implemented by importing the MOVE output file, which contains the position of each node at each instant of simulation time. In simulations involving V2I/I2V communication, RSUs are special nodes whose position coordinate is maintained throughout the simulation. Vehicle entry and movement are carried out according to the mobility model described above.The fact that ns-3 does not yet have all the modules necessary to simulate a node with the proposed architecture (Figure2) led to the need to make adaptations to the model proposed previously.The previously considered applications are modeled through CBR (constant bit rate) traffic generators, with different time configurations between message generation. For the sake of simplicity, all messages have the same size (480 bytes), which was defined in order to ensure that the security information is already included in the packet, following the indications defined in [17–19].As previously mentioned, information from the PCW application has to reach all nodes quickly, which is achieved by having the receiving nodes resend the information received for the first time, while the information from the other applications has a local character. This behavior was modeled by defining the time to live (TTL) field in the message, which allows controlling the number of times the message is retransmitted. Therefore, for the PCW application, a value was selected that allows the message to be retransmitted the number of times necessary to allow its reception by nodes that are before the exit at the moment of the accident. This value must be parameterized for the different scenarios that may be considered. In order to respect the functional principles defined above, the PCW and EEBL applications only start when an accident occurs. The values used are shown in Table4.Table 4
Parameterization of traffic generators.
PCWEEBLCCWSize of messages (B)480480480Frequency (Hz)882DestinyAllAllAllTTL6022Start time (s)TaccidentTaccident0End instant (s)TsimulationTsimulationTsimulationThe simulation model developed uses the UDP protocol as an unreliable transport protocol at the transport level. At the routing level, a module was used that implements the GPSR geographic routing protocol [20], with a location service similar to the one used by Karp and Kung in the specification of the protocol itself.At the MAC layer level, the biggest limitations arise since ns-3 does not yet support the 802.11p protocol [17]. Thus, it was necessary to resort to the module that implements 802.11 communication in ad hoc mode. With this solution, there is no support for quality of service and switching between channels, which are essential mechanisms for the coexistence of security applications with other types of applications. The fact that applications other than those related to emergency scenarios are not being considered strongly reduces the impact of this limitation. It may, however, happen that, due to the inability to differentiate the various applications in use, the performance of the most critical application—PCW—is affected.The physical layer already has support for the 802.11p standard, and this was the model used. In order to obtain simulation results that approximate the real conditions as closely as possible, special care was taken in the choice of propagation models. We chose to use a model that accounts for losses due to signal attenuation with distance (path loss) and another that accounts for losses due to the effects of signal dispersion (multi-path fading). Therefore, the two-ray ground reflection and Nakagami [22] models are used. The range of the different types of antennas was modeled using the configuration of transmission power and antenna gain. The values used are shown in Table 5.Table 5
Parameterization of propagation models and antennas.
VehicleRSUNakagami modelNakagamim-factorm01.5m10.75m20.5Two-ray ground modelHeight (m)1.76.3AntennasTransmission power (dBm)518Hook (dBi)29
## 6. Results and Discussion
### 6.1. Test Scenario
The tests carried out are intended to assess whether the most critical application (PCW) requirements can be guaranteed, taking into account that there is traffic coming from other security applications in circulation. This assessment was carried out in several different scenarios:(i)
Communication with and without MSW.(ii)
One-way or three-way blocking.(iii)
Traffic with low and high intensities.
### 6.2. Evaluation Metrics
To measure the performance of the PCW application, application-level and network-level metrics were stipulated. From an application point of view, the following metrics were defined:(i)
Warning rate: the percentage of vehicles in circulation that received an accident notification.(ii)
Useful warning rate: the percentage of vehicles in circulation that received the accident notification within the latency and range limit characteristic of the PCW application.(iii)
Notification latency: time that elapses from when the accident occurs until the vehicle is notified.(iv)
Notification position: position of the node when it receives the accident notification, measured about the input coordinate.At the network level, the metrics considered were(i)
Number of hops: number of nodes used to relay the message.
### 6.3. Results Obtained: General Case
The information of each vehicle at the moment of the accident notification is represented through a set ofXY-type graphs. The X coordinate describes the notification latency and the Y coordinate describes the notification position. Figures 4(a) and 4(b) illustrate the values obtained in the situation of low vehicular intensity, and Figure 5 illustrates the case where the intensity is high.Figure 4
(a) Low vehicle intensity: the notification latency is in the order of 100 ms. (b) High vehicle intensity: the notification latency is in the order of 100 ms.
(a)(b)Figure 5
Low vehicle intensity; V2V and V2I communication; 1 blocked way (a) and high vehicle intensity; V2V and V2I communication; 1 blocked way (b).
(a)(b)Except for vehicles that are further away from the accident, in a low traffic intensity with V2V communication, most vehicles receive the notification very quickly, with the notification latency in the order of 100 ms. However, more distant vehicles have higher latencies (about 500 ms), although they can be warned when they are still far from the accident site. As shown in Figure4(b), the existence of RSUs (dots illustrated in red) makes it possible to reduce the latency value for more distant vehicles. When the traffic intensity is high, there is a greater variation in the notification conditions, which translates into a greater dispersion of the notification position. Regarding the notification latency, although there are variations in value, the maximum observed latency is much lower (about 135 ms) since more vehicles are capable of retransmitting the notification. The existence of RSUs allows more nodes to receive the notification faster, which is visible by the higher concentration of points along the Y-axis. It is also verified that the number of distant nodes that receive the notification earlier increases. This situation is particularly evident in the case of MSW 2 (Y = ∼1210 m). The results presented in Figures 5(a) and 5(b) illustrate the number of hops used histogram and confirm the previous conclusions. The use of RSUs reduces the number of communication hops, which reduces the notification latency since the RSU has a greater range and allows the transmission of information to distant nodes more quickly.
### 6.4. Results Obtained: Post-Accident Conditions
Based on the information received, it is also possible to assess how the notification would allow drivers to react promptly to the accident situation. Two different situations must be considered:(i)
Drivers in the accident area must be warned quickly to react in time to avoid secondary accidents.(ii)
Drivers who are en route to the accident area but still have time to receive the alert so that they can deviate follow an alternative route, avoiding congestion.Based on these assumptions, the warning rate, the useful warning rate, and the notification latency were measured for the general case and for each of the situations identified above. Table6 presents the results obtained for each of these metrics. In this study, it was considered that, in the general case and in the case of nodes before the exit, the warning was only useful if it arrived before 500 ms. In contrast, the maximum acceptable value for nodes in the accident region was 105 ms (the latency value defined for the EEBL application with a margin of 5%).Table 6
Results for the different post-accident conditions.
Global statisticsTotalBefore you leaveAccident areaNotice fee100%100%100%Useful notice fee100%100%86%Minimum notification latency (ms)102.75102.75102.75Average notification latency (ms)107.14107.32104.22Maximum notification latency (ms)133.92133.92111.79
## 6.1. Test Scenario
The tests carried out are intended to assess whether the most critical application (PCW) requirements can be guaranteed, taking into account that there is traffic coming from other security applications in circulation. This assessment was carried out in several different scenarios:(i)
Communication with and without MSW.(ii)
One-way or three-way blocking.(iii)
Traffic with low and high intensities.
## 6.2. Evaluation Metrics
To measure the performance of the PCW application, application-level and network-level metrics were stipulated. From an application point of view, the following metrics were defined:(i)
Warning rate: the percentage of vehicles in circulation that received an accident notification.(ii)
Useful warning rate: the percentage of vehicles in circulation that received the accident notification within the latency and range limit characteristic of the PCW application.(iii)
Notification latency: time that elapses from when the accident occurs until the vehicle is notified.(iv)
Notification position: position of the node when it receives the accident notification, measured about the input coordinate.At the network level, the metrics considered were(i)
Number of hops: number of nodes used to relay the message.
## 6.3. Results Obtained: General Case
The information of each vehicle at the moment of the accident notification is represented through a set ofXY-type graphs. The X coordinate describes the notification latency and the Y coordinate describes the notification position. Figures 4(a) and 4(b) illustrate the values obtained in the situation of low vehicular intensity, and Figure 5 illustrates the case where the intensity is high.Figure 4
(a) Low vehicle intensity: the notification latency is in the order of 100 ms. (b) High vehicle intensity: the notification latency is in the order of 100 ms.
(a)(b)Figure 5
Low vehicle intensity; V2V and V2I communication; 1 blocked way (a) and high vehicle intensity; V2V and V2I communication; 1 blocked way (b).
(a)(b)Except for vehicles that are further away from the accident, in a low traffic intensity with V2V communication, most vehicles receive the notification very quickly, with the notification latency in the order of 100 ms. However, more distant vehicles have higher latencies (about 500 ms), although they can be warned when they are still far from the accident site. As shown in Figure4(b), the existence of RSUs (dots illustrated in red) makes it possible to reduce the latency value for more distant vehicles. When the traffic intensity is high, there is a greater variation in the notification conditions, which translates into a greater dispersion of the notification position. Regarding the notification latency, although there are variations in value, the maximum observed latency is much lower (about 135 ms) since more vehicles are capable of retransmitting the notification. The existence of RSUs allows more nodes to receive the notification faster, which is visible by the higher concentration of points along the Y-axis. It is also verified that the number of distant nodes that receive the notification earlier increases. This situation is particularly evident in the case of MSW 2 (Y = ∼1210 m). The results presented in Figures 5(a) and 5(b) illustrate the number of hops used histogram and confirm the previous conclusions. The use of RSUs reduces the number of communication hops, which reduces the notification latency since the RSU has a greater range and allows the transmission of information to distant nodes more quickly.
## 6.4. Results Obtained: Post-Accident Conditions
Based on the information received, it is also possible to assess how the notification would allow drivers to react promptly to the accident situation. Two different situations must be considered:(i)
Drivers in the accident area must be warned quickly to react in time to avoid secondary accidents.(ii)
Drivers who are en route to the accident area but still have time to receive the alert so that they can deviate follow an alternative route, avoiding congestion.Based on these assumptions, the warning rate, the useful warning rate, and the notification latency were measured for the general case and for each of the situations identified above. Table6 presents the results obtained for each of these metrics. In this study, it was considered that, in the general case and in the case of nodes before the exit, the warning was only useful if it arrived before 500 ms. In contrast, the maximum acceptable value for nodes in the accident region was 105 ms (the latency value defined for the EEBL application with a margin of 5%).Table 6
Results for the different post-accident conditions.
Global statisticsTotalBefore you leaveAccident areaNotice fee100%100%100%Useful notice fee100%100%86%Minimum notification latency (ms)102.75102.75102.75Average notification latency (ms)107.14107.32104.22Maximum notification latency (ms)133.92133.92111.79
## 7. Conclusions and Recommendations
In the present work, the performance of vehicular networks on highways was analyzed, taking into account aspects such as the feasibility of placing RSUs along with the infrastructure, its impact on this same performance, and the ability to enable the timely receipt of warnings regarding emergencies, to minimize second collisions and mitigate traffic congestion. Different aspects were analyzed using the modeling and simulation of mobility and communication between vehicles and, additionally, between vehicles and road infrastructure—the RSUs.The results obtained allow us to conclude that the use of RSUs improves the performance of road safety applications, as it reduces the latency in receiving information. From the analysis of the same data, it is still possible to conclude that it is not necessary to install the RSUs mentioned above in all locations where there are currently CCTV poles or PMVs, which will have significant cost advantages.From the results in a post-accident phase, referring to high-intensity conditions, with three blocked lanes and the inclusion of RSUs, it appears that vehicles far from the accident zone, at a point that precedes an exit, are all warned in time. If the alert appeared before 500ms, it was beneficial. In contrast, if the maximum acceptable value for nodes in the accident region was 105 ms, it would be not useful. All vehicles in the accident zone, i.e., within the maximum range of 300 m, received the notification. However, only about 86% of them received it within the latency limit, i.e., 105 ms. However, considering the 500 ms of the PCW application, all nodes under study received the notification successfully, with a latency below this value.In future work, we intend to evaluate this situation in a small-scale experimental prototype, which allows us to assess to what extent the results obtained by simulation are representative of the real situation. This study will make it possible to determine the importance of aspects that cannot be modeled in simulation, such as the presence of obstacles on the motorway and the actual geometry of the motorway itself (levels, bridges, and curves, among others).
---
*Source: 2902263-2022-07-20.xml* | 2902263-2022-07-20_2902263-2022-07-20.md | 65,468 | Simulation of Vehicular Network Use in Emergency Situations and Security Applications on a Pakistan Highway | Asaad T. Al-Douri; Noor Mohammed Kadhim; A. A. Hamad Mohamad; Melese Abeyie | Security and Communication Networks
(2022) | Engineering & Technology | Hindawi | CC BY 4.0 | http://creativecommons.org/licenses/by/4.0/ | 10.1155/2022/2902263 | 2902263-2022-07-20.xml | ---
## Abstract
VANETs (vehicular ad hoc networks), which are revolutionary techniques to enhance road safety, can be used to broadcast information about dangerous traffic conditions or accidents. However, distributing important information for driver safety and well-being has strict time and reliability requirements. This is because messages must be received by all cars involved in a potentially dangerous scenario for proper precautions to be taken to avoid the problem from materializing or intensifying. Because of the deterioration in conventional wireless communication system performance, ensuring that such requirements are met is a serious concern. To validate the concept before the actual installation of such systems and their absorption into the vehicle sector, it is therefore critical to employ simulation methodologies that are both reliable and thorough. This piece consists of large-scale, realistic security simulation research of an emergency situation based on actual road traffic data acquired on a Pakistan route. The study’s findings are detailed in the following paragraphs. Aspects such as the incorporation of fixed communication units along a stretch of roadway and the performance of the vehicular network notifying all vehicles engaged in the various accident scenarios modeled on the same stretch of highway were evaluated. Both of these characteristics were designed to increase safety and security applications. After doing the investigation, it was observed that when fixed communication units are incorporated into the network infrastructure, there is a shorter delay in receiving the accident notification. This was the conclusion made after reviewing the findings. Drivers of vehicles located closer to the accident site will be able to respond in a timely and safe manner as a result of this improvement in network performance, and drivers security of vehicles located further away will have the option of exiting the highway to avoid potential congestion caused by increased road traffic.
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## Body
## 1. Introduction
Pakistan’s increasing urbanization at 3.3% per year and population growth of about 2% per year have contributed to the country’s 18.3% increase in the number of motor vehicles registered during the last two decades [1]. Even though the country’s road network has not increased significantly in recent years, there has been a significant increase in automotive collisions in Pakistan. In Pakistan, the accident death rate is 14.2 per 100,000 people [2], an unacceptably high figure. According to the Pakistan Bureau of Statistics [3], 48,828 individuals died due to traffic accidents in Pakistan. The authors assessed the performance of Het-Net, which combines Wi-Fi, DSRC, and LTE technologies for V2V and V2I communications, and found that using other wireless technology could reduce the need for expensive DSRC infrastructure by up to 55%. An application layer handoff method was created to enable Het-Net communication for two CVT applications: traffic data collection [4]. The nation’s network of highways and motorways carries most of the country’s high-speed traffic. Several researchers have focused on the relationship analysis of accidents and numerous contributory components during the accident study done on roads and highways. Most of Pakistan’s highways and other roadways are classified as either national highways or motorways [5].The development of new wireless network technologies and the existence of low-cost embedded systems with high computational capacities gave rise to the emergence of vehicular networks, both in terms of research and of the market. This type of network enables the communication between vehicles (vehicle-to-vehicle (V2V)) and between them and the road infrastructure (vehicle-to-infrastructure (V2I)) [6].The main interest in VANETs arises from using new road safety paradigms based on cooperation between the various entities involved in communication [7], which significantly improve road safety and promote sustainable mobility. However, given the criticality of this type of application, simulation studies are needed in large-scale environments and conditions as close as possible to reality. The potential advantages of the technology can be verified before starting its introduction in vehicles and infrastructures.This work intends to analyze the feasibility of using vehicular networks in highway scenarios to respond to accident situations. Three different aspects are intended to be evaluated:(i)
The impact of roadside units (RSUs) in the accident notification process is to assess the need to invest in their installation.(ii)
The ability to give timely warning to vehicles close to the accident zone to avoid chain collisions.(iii)
The ability to warn vehicles far from the affected region to ensure that they can choose an alternative route, minimizing traffic congestion.The study presented in the simulation is based on the real case of the Pakistan motorway AH1/M-2 (Islamabad to Lahore motorway), which connects the capital, Islamabad, to Lahore. AH1/M-2 is located in Pakistan; the Lahore-Islamabad Motorway is a highway that runs from north to south and connects Rawalpindi/Islamabad to Lahore. This motorway is one of the several motorways under the responsibility of Pakistan road safety [8].
## 2. Review of Literature
### 2.1. Security Applications
The development of vehicular networks enables the development of new types of road safety applications. These applications are based on cooperation and information sharing between vehicles and the surrounding environment and aim to alert the driver of situations that affect safety and mobility conditions throughout the journey.In [9], characterization of the different types of applications was carried out, and it was concluded that safety applications should be used essentially to support accident situations, provide information at intersections, and avoid traffic congestion. However, many options regarding the most appropriate protocol architecture and communication mechanisms are left open.The study presented in [10] further characterizes the types of road safety applications, defining applications for five different purposes:(i)
Alert for dangerous infrastructure features.(ii)
Alert for abnormal traffic conditions.(iii)
Warning of collision danger.(iv)
Warning of impending shock.(v)
Accident notification.According to the same study, this type of application requires the use of new communication mechanisms that allow sending information to an unspecified set of nodes: dissemination within a geographic area (Geocast) and periodic dissemination to adjacent nodes (Beaconing). Multi-hop communication and store-and-forward are also used to guarantee the reception of information by nodes that are outside the initial range and correlation to reduce data traffic, especially in situations of a high density of vehicles.A crucial aspect of the performance of these applications is related to the definition of the scope of the Geocast and the validity time of the security information. In [11], the authors stipulate 250 m as an acceptable value for a maximum range of a Geocast communication and 10 s as a time limit for the validity of the information. However, an experimental study carried out in the context of the European Cooperative Vehicle-Infrastructure Systems (CVIS) project with a set of safety applications developed by the consortium concluded that the warning time should not exceed 5 s [11].For applications aimed at alerting drivers to potential accidents, there are other determining factors for their success, such as the accuracy of the vehicle’s location and the prediction of its movement, which are directly related to the time period between beacons. Studies reported in [12] show that a frequency of 5 Hz guarantees an adequate performance for this type of application.Several authors have also carried out performance studies on applications to avoid accidents at intersections [12, 13]. However, these studies do not apply to a motorway scenario, given the scenario’s different mobility patterns and characteristics.
### 2.2. Safety Applications for Emergency Situations
A potentially dangerous situation can trigger the transmission of messages generated by various road safety applications, of which the most relevant for an accident scenario are(i)
Sudden braking warning (emergency electronic brake lights (EEBL)).(ii)
Post-crash warning (PCW).(iii)
Cooperative collision warning (CCW) alert.The EEBL application allows a vehicle to notify vehicles behind it when it suddenly brakes. It is especially useful in poor visibility conditions where vehicles may not be aware in time that the vehicle in front has braked/activated the brake lights. The PCW application notifies vehicles approaching an accident scene of the presence of an immobilized vehicle due to an accident or mechanical failure. Finally, the CCW application mitigates the occurrence of collisions by sending periodic information about the position, speed, acceleration, and direction of each vehicle.According to [14, 15], these applications can be characterized according to different parameters, as shown in Table 1.Table 1
Characterization of road safety applications.
EEBLPCWCCWCommunication modeGeo-broadcastGeo-broadcastGeo-broadcastCardinalityUnidirectionalUnidirectionalUnidirectionalType of communicationV2VV2I, V2VV2VTransmission modeBy eventBy eventPeriodicallyFreq. min. messages (Hz)∼10∼1∼10Maximum latency (s)0.10.50.1Reach (m)∼300∼300∼150
## 2.1. Security Applications
The development of vehicular networks enables the development of new types of road safety applications. These applications are based on cooperation and information sharing between vehicles and the surrounding environment and aim to alert the driver of situations that affect safety and mobility conditions throughout the journey.In [9], characterization of the different types of applications was carried out, and it was concluded that safety applications should be used essentially to support accident situations, provide information at intersections, and avoid traffic congestion. However, many options regarding the most appropriate protocol architecture and communication mechanisms are left open.The study presented in [10] further characterizes the types of road safety applications, defining applications for five different purposes:(i)
Alert for dangerous infrastructure features.(ii)
Alert for abnormal traffic conditions.(iii)
Warning of collision danger.(iv)
Warning of impending shock.(v)
Accident notification.According to the same study, this type of application requires the use of new communication mechanisms that allow sending information to an unspecified set of nodes: dissemination within a geographic area (Geocast) and periodic dissemination to adjacent nodes (Beaconing). Multi-hop communication and store-and-forward are also used to guarantee the reception of information by nodes that are outside the initial range and correlation to reduce data traffic, especially in situations of a high density of vehicles.A crucial aspect of the performance of these applications is related to the definition of the scope of the Geocast and the validity time of the security information. In [11], the authors stipulate 250 m as an acceptable value for a maximum range of a Geocast communication and 10 s as a time limit for the validity of the information. However, an experimental study carried out in the context of the European Cooperative Vehicle-Infrastructure Systems (CVIS) project with a set of safety applications developed by the consortium concluded that the warning time should not exceed 5 s [11].For applications aimed at alerting drivers to potential accidents, there are other determining factors for their success, such as the accuracy of the vehicle’s location and the prediction of its movement, which are directly related to the time period between beacons. Studies reported in [12] show that a frequency of 5 Hz guarantees an adequate performance for this type of application.Several authors have also carried out performance studies on applications to avoid accidents at intersections [12, 13]. However, these studies do not apply to a motorway scenario, given the scenario’s different mobility patterns and characteristics.
## 2.2. Safety Applications for Emergency Situations
A potentially dangerous situation can trigger the transmission of messages generated by various road safety applications, of which the most relevant for an accident scenario are(i)
Sudden braking warning (emergency electronic brake lights (EEBL)).(ii)
Post-crash warning (PCW).(iii)
Cooperative collision warning (CCW) alert.The EEBL application allows a vehicle to notify vehicles behind it when it suddenly brakes. It is especially useful in poor visibility conditions where vehicles may not be aware in time that the vehicle in front has braked/activated the brake lights. The PCW application notifies vehicles approaching an accident scene of the presence of an immobilized vehicle due to an accident or mechanical failure. Finally, the CCW application mitigates the occurrence of collisions by sending periodic information about the position, speed, acceleration, and direction of each vehicle.According to [14, 15], these applications can be characterized according to different parameters, as shown in Table 1.Table 1
Characterization of road safety applications.
EEBLPCWCCWCommunication modeGeo-broadcastGeo-broadcastGeo-broadcastCardinalityUnidirectionalUnidirectionalUnidirectionalType of communicationV2VV2I, V2VV2VTransmission modeBy eventBy eventPeriodicallyFreq. min. messages (Hz)∼10∼1∼10Maximum latency (s)0.10.50.1Reach (m)∼300∼300∼150
## 3. Characterization of the Scenario
### 3.1. General Information
The AH1/M-2 highway is considered one of the most congested highways in the country since it is one of the two main access routes to the city of Islamabad. The 25 kilometers between Islamabad and Lahore on the AH1/M-2 include 12 intersections with 60 access routes.In terms of technology, AH1/M-2 is a highway equipped with an advanced infrastructure, made up of a backbone, which interlinks a set of sensors, video surveillance cameras (CCTV), and variable message boards (PMVs). The CCTV poles are placed laterally in locations that offer good visibility, and the PMVs are placed on raised porches perpendicular to AH1/M-2. In any two cases, these systems are spread over the entire length of the highway, being placed at about 6 m height. There are sensors at the entrances and exits and sensors located along two different sections of the AH1/M-2. Currently, this infrastructure is used to collect traffic information, identify dangerous situations, detect accidents, and provide information to drivers about traffic conditions. All information is centralized at the operational coordination center—CCO, which manages all highways concessioned by the SKB Engineering group.The variety of sensorization equipment available enables the collection of data of a variety of types, including traffic intensity and density, class, the combined weight of two vehicles, and average speed, Het-Net might offer extra supplemental connectivity for safety applications to notify upstream vehicles to take preventative measures to avoid issue spots. This information is delivered and processed to central systems for statistical processing before being sent, in quasireal time, to PMVs to avoid problem locations.
### 3.2. Characterization of Traffic
A historical record of traffic information allows modeling the traffic in a macroscopic way [14]. This record indicates the average intensity of traffic in different locations, measured every 10 minutes. In addition, there is also a record of the origin-destination matrix for every two accesses of AH1/M-2. Based on the analysis of the registered information, it was possible to determine the intensity of traffic in different sections throughout the day. The values were obtained from the three most representative locations in different periods of the day: o period of less traffic (2:00-3:00 a.m.), o period of higher traffic (8:00-9:00 a.m.), and a period of medium traffic (13:00-14:00).
### 3.3. Characterization of the Accident Conditions
For the history of traffic, SKB Engineering also has information that allows for identifying the locations most prone to accidents and defining the most frequent causes. According to the data made available by SKB Engineering, there are five most critical areas [15].In the first zone, it occurs in the Islamabad to Lahore section, between departures 9 and 10. The main cause of accidents consists of strong winds and excessive speed, which results in the vehicle not being misled and, possibly, in an accident. The second area is located next to CREL, near exit 6, not in the Islamabad to Lahore direction. In this area, the accidents are caused mainly by the sudden variation in traffic density on the curve that immediately precedes a departure. Drivers who dislodge at excessive speed are not aware of the rapid formation of a queue next to the exit and are forced to reduce speed abruptly. The following two locations are located close to the departure point for the National Stadium: a sharp curve, combined with the excessive speed of two vehicles, is the main cause of accidents. The last area is located near Exit 5, not in the Islamabad to Lahore direction, in the direction of Islamabad to Lahore. More than once, the main cause of the accident was excessive speed [16]. Even though they occur often, road accidents are the worst thing that may happen to a road user. The most regrettable aspect is that we don't learn from our on-the-road errors. The majority of road users are generally relatively aware of the general norms and safety precautions when using the roads; it is only the road users' slack attitude due to overspeeding, drunk driving, driver distractions, red light jumping, and avoiding safety equipment such seat belts and helmets. . Still, in certain situations, accidents occur in high-traffic conditions, which can occur even when the traffic is heavy. Likewise, it is essential to model the occurrence of accidents in different traffic conditions.
## 3.1. General Information
The AH1/M-2 highway is considered one of the most congested highways in the country since it is one of the two main access routes to the city of Islamabad. The 25 kilometers between Islamabad and Lahore on the AH1/M-2 include 12 intersections with 60 access routes.In terms of technology, AH1/M-2 is a highway equipped with an advanced infrastructure, made up of a backbone, which interlinks a set of sensors, video surveillance cameras (CCTV), and variable message boards (PMVs). The CCTV poles are placed laterally in locations that offer good visibility, and the PMVs are placed on raised porches perpendicular to AH1/M-2. In any two cases, these systems are spread over the entire length of the highway, being placed at about 6 m height. There are sensors at the entrances and exits and sensors located along two different sections of the AH1/M-2. Currently, this infrastructure is used to collect traffic information, identify dangerous situations, detect accidents, and provide information to drivers about traffic conditions. All information is centralized at the operational coordination center—CCO, which manages all highways concessioned by the SKB Engineering group.The variety of sensorization equipment available enables the collection of data of a variety of types, including traffic intensity and density, class, the combined weight of two vehicles, and average speed, Het-Net might offer extra supplemental connectivity for safety applications to notify upstream vehicles to take preventative measures to avoid issue spots. This information is delivered and processed to central systems for statistical processing before being sent, in quasireal time, to PMVs to avoid problem locations.
## 3.2. Characterization of Traffic
A historical record of traffic information allows modeling the traffic in a macroscopic way [14]. This record indicates the average intensity of traffic in different locations, measured every 10 minutes. In addition, there is also a record of the origin-destination matrix for every two accesses of AH1/M-2. Based on the analysis of the registered information, it was possible to determine the intensity of traffic in different sections throughout the day. The values were obtained from the three most representative locations in different periods of the day: o period of less traffic (2:00-3:00 a.m.), o period of higher traffic (8:00-9:00 a.m.), and a period of medium traffic (13:00-14:00).
## 3.3. Characterization of the Accident Conditions
For the history of traffic, SKB Engineering also has information that allows for identifying the locations most prone to accidents and defining the most frequent causes. According to the data made available by SKB Engineering, there are five most critical areas [15].In the first zone, it occurs in the Islamabad to Lahore section, between departures 9 and 10. The main cause of accidents consists of strong winds and excessive speed, which results in the vehicle not being misled and, possibly, in an accident. The second area is located next to CREL, near exit 6, not in the Islamabad to Lahore direction. In this area, the accidents are caused mainly by the sudden variation in traffic density on the curve that immediately precedes a departure. Drivers who dislodge at excessive speed are not aware of the rapid formation of a queue next to the exit and are forced to reduce speed abruptly. The following two locations are located close to the departure point for the National Stadium: a sharp curve, combined with the excessive speed of two vehicles, is the main cause of accidents. The last area is located near Exit 5, not in the Islamabad to Lahore direction, in the direction of Islamabad to Lahore. More than once, the main cause of the accident was excessive speed [16]. Even though they occur often, road accidents are the worst thing that may happen to a road user. The most regrettable aspect is that we don't learn from our on-the-road errors. The majority of road users are generally relatively aware of the general norms and safety precautions when using the roads; it is only the road users' slack attitude due to overspeeding, drunk driving, driver distractions, red light jumping, and avoiding safety equipment such seat belts and helmets. . Still, in certain situations, accidents occur in high-traffic conditions, which can occur even when the traffic is heavy. Likewise, it is essential to model the occurrence of accidents in different traffic conditions.
## 4. Vehicle Support Network for Emergency Applications
### 4.1. Architecture of the Vehicular Network
Two fundamental aspects to be balanced do not design a vehicular network with the need to use fixed communication units (RSUs) properly positioned to increase the coverage of communication in order to ensure better connectivity.In the case of AH1/M-2, there is already a network infrastructure, so it is relatively easy to find suitable locations to place the aforementioned RSUs, namely, locations with better visibility, where the CCTV cameras or PMVs are currently located. Still, it is necessary to guarantee that there is a significant improvement in performance, which justifies the investment to carry out the RSUs. Likewise, two different scenarios will be considered:(i)
Vehicular network without RSUs that supports only vehicle-to-vehicle (V2V) communication.(ii)
Vehicle network with RSUSs that also supports vehicle-to-infrastructure (V2I/I2V) communication.Figure1 represents the complete case, with a network containing RSUs allowing V2V and V2I/I2V communication.Figure 1
Proposed VANET architecture.In a real situation, the vehicles and the RSUs may be equipped with antennas with different characteristics. V2I is used where an RSU is available, and V2V multihop communication is used where the RSU's communication range cannot reach, with the knowledge that the antennas of the RSUs have a greater range and that they are located above the height of two vehicles to prevent them from acting as an obstruction to the propagation of the signal, this method could be successful for roads and highways with sparsely distributed RSUs. As can be seen, the subject of this study is V2V multihop communication because it is crucial to EM broadcasting for accident prevention [17].
### 4.2. Architecture
Figure2 illustrates the architecture for all of us on the network, which must be similar for all of us and adaptable to various types of applications. Also, vehicles and RSUs support a set of road safety applications, with the information generated by these applications being disseminated within a given geographic area using an unreliable transport protocol and a geographic routing protocol or GPSR (Greedy Perimeter Stateless Routing) [18]. The geographic routing protocol was modified to support communication within a geographic area, limited or not, to a restricted set of us, the performance of vehicular networks on highways, taking into account aspects such as the feasibility of placing RSUs along with the infrastructure and its impact on this same performance. In terms of access to the medium and physical transmission of data, the protocols implemented in the IEEE 802.11p standard are used, on which the WAVE (wireless access in vehicular environment) systems are based [17].Figure 2
Architecture of a network node.
### 4.3. Emergency Applications
In the event of an accident, it is crucial to ensure that, firstly, the accident does not escalate and, secondly, to avoid the formation of long and lengthy traffic queues, whose tails can also imply sudden braking, leading to second accidents.It is considered that, immediately after the accident, the vehicle notifies those approaching from its rear if the damage caused by the accident does not make it impossible. Vehicles approaching the accident site may be at a point on the motorway that precedes an exit, so they can anticipate their departure from the motorway upon receiving the warning. Vehicles that are very close to the accident scene, to the point of having to drastically reduce their speed when they perceive a dangerous approach to the vehicle in front, must transmit sudden braking/risk of imminent collision in the rear warnings to the other vehicles.This modeling will allow analyzing the coexistence of several road safety applications and their impact on communication in an emergency scenario.From an application point of view, it is necessary to support the three applications, namely,(i)
PCW application—used to notify the occurrence of an accident. The crashed vehicle generates notifications for a short time. These notifications are resent by the vehicles that receive them in order to ensure that the information reaches quickly beyond the affected area. However, in order to avoid broadcast storm situations, such as those described in [19], these notifications are only resent the first time they are received through a simple correlation mechanism.(ii)
EEBL application—used to warn vehicles of sudden braking by the vehicle in front. The braking vehicle generates messages for a short time at a relatively high rate. These messages are not forwarded by the vehicles that receive them.(iii)
CCW application—used to detect potential collision situations based on the location information it periodically receives from its neighbors. The messages generated by each node have an exclusively local character, not being forwarded to nodes that are not adjacent to it.For an effective response to an emergency situation, it is essential to ensure that, despite the coexistence of road safety traffic from different applications, it is possible to fulfill the requirements previously stipulated for each of them, namely, in terms of the ability to notify vehicles of a situation of an accident.
## 4.1. Architecture of the Vehicular Network
Two fundamental aspects to be balanced do not design a vehicular network with the need to use fixed communication units (RSUs) properly positioned to increase the coverage of communication in order to ensure better connectivity.In the case of AH1/M-2, there is already a network infrastructure, so it is relatively easy to find suitable locations to place the aforementioned RSUs, namely, locations with better visibility, where the CCTV cameras or PMVs are currently located. Still, it is necessary to guarantee that there is a significant improvement in performance, which justifies the investment to carry out the RSUs. Likewise, two different scenarios will be considered:(i)
Vehicular network without RSUs that supports only vehicle-to-vehicle (V2V) communication.(ii)
Vehicle network with RSUSs that also supports vehicle-to-infrastructure (V2I/I2V) communication.Figure1 represents the complete case, with a network containing RSUs allowing V2V and V2I/I2V communication.Figure 1
Proposed VANET architecture.In a real situation, the vehicles and the RSUs may be equipped with antennas with different characteristics. V2I is used where an RSU is available, and V2V multihop communication is used where the RSU's communication range cannot reach, with the knowledge that the antennas of the RSUs have a greater range and that they are located above the height of two vehicles to prevent them from acting as an obstruction to the propagation of the signal, this method could be successful for roads and highways with sparsely distributed RSUs. As can be seen, the subject of this study is V2V multihop communication because it is crucial to EM broadcasting for accident prevention [17].
## 4.2. Architecture
Figure2 illustrates the architecture for all of us on the network, which must be similar for all of us and adaptable to various types of applications. Also, vehicles and RSUs support a set of road safety applications, with the information generated by these applications being disseminated within a given geographic area using an unreliable transport protocol and a geographic routing protocol or GPSR (Greedy Perimeter Stateless Routing) [18]. The geographic routing protocol was modified to support communication within a geographic area, limited or not, to a restricted set of us, the performance of vehicular networks on highways, taking into account aspects such as the feasibility of placing RSUs along with the infrastructure and its impact on this same performance. In terms of access to the medium and physical transmission of data, the protocols implemented in the IEEE 802.11p standard are used, on which the WAVE (wireless access in vehicular environment) systems are based [17].Figure 2
Architecture of a network node.
## 4.3. Emergency Applications
In the event of an accident, it is crucial to ensure that, firstly, the accident does not escalate and, secondly, to avoid the formation of long and lengthy traffic queues, whose tails can also imply sudden braking, leading to second accidents.It is considered that, immediately after the accident, the vehicle notifies those approaching from its rear if the damage caused by the accident does not make it impossible. Vehicles approaching the accident site may be at a point on the motorway that precedes an exit, so they can anticipate their departure from the motorway upon receiving the warning. Vehicles that are very close to the accident scene, to the point of having to drastically reduce their speed when they perceive a dangerous approach to the vehicle in front, must transmit sudden braking/risk of imminent collision in the rear warnings to the other vehicles.This modeling will allow analyzing the coexistence of several road safety applications and their impact on communication in an emergency scenario.From an application point of view, it is necessary to support the three applications, namely,(i)
PCW application—used to notify the occurrence of an accident. The crashed vehicle generates notifications for a short time. These notifications are resent by the vehicles that receive them in order to ensure that the information reaches quickly beyond the affected area. However, in order to avoid broadcast storm situations, such as those described in [19], these notifications are only resent the first time they are received through a simple correlation mechanism.(ii)
EEBL application—used to warn vehicles of sudden braking by the vehicle in front. The braking vehicle generates messages for a short time at a relatively high rate. These messages are not forwarded by the vehicles that receive them.(iii)
CCW application—used to detect potential collision situations based on the location information it periodically receives from its neighbors. The messages generated by each node have an exclusively local character, not being forwarded to nodes that are not adjacent to it.For an effective response to an emergency situation, it is essential to ensure that, despite the coexistence of road safety traffic from different applications, it is possible to fulfill the requirements previously stipulated for each of them, namely, in terms of the ability to notify vehicles of a situation of an accident.
## 5. Accident Scenario Modeling
### 5.1. Characterization of the Accident Scenario
In order to obtain reliable results, an attempt was made to reproduce an accident scenario in simulation. Among the various types of cases identified in Section 3.3, the first was chosen, as it was the one where the most accidents were reported. This location (Jhelum, Punjab, Pakistan, (32.675778, 72.755291), shown in Figure3, is located on the Islamabad to Lahore (direction: Islamabad), close to k22.1 km, and in an area where the motorway has three lanes where accidents often happen there. The distance between the exit immediately before the accident site (10th exit) is approximately 1.2 km (red spot marker in the figure). To take advantage of the existing infrastructure, the RSUs must be placed next to the CCTV poles or next to the PMVs (marked in the figure with blue markers). However, since the distance between them is only a few hundred meters, there will be no need to install RSUs in all locations. The vehicle moves at the maximum permitted speed (120 km/h), so the RSUs must be placed next. Therefore, it was decided to include in the scenario, modeling only MSWs with an average distance between them of about 1 km (MSW 1, 2, and 3) for to be safe and avoid a collision, and this is a relatively simple representation of reality since it does not consider the natural distribution of vehicle departure times and their movement.Figure 3
Islamabad to Lahore section of the AH1/M-2 motorway.As mentioned earlier, the most frequent cause of accidents is speeding. However, accidents can occur in situations of high-traffic intensity or even in situations of low intensity. Any of these scenarios can have a strong impact on the performance of the vehicular network, as the first can lead to an overload of data traffic, and the second can lead to a lack of connectivity in the network. In order to better assess the impact of these two extreme cases, it was decided to select the values recorded section for the period with the highest traffic. At this stage, if your resource does not show up in the Endpoint list and you created both your hosted zone and the resource to which you are directing traffic using the same AWS account, make sure the following: verify that the record type you selected is supported, specific to the resource you are routing traffic to, for instance, you must select A — IPv4 address for the record type if you want to direct traffic to an S3 bucket.
### 5.2. Mobility Model
The mobility simulator MOVE1 (Mobility Model Generator for Vehicular Networks) was used for the mobility simulation since it fits the scenario under study. This road traffic generator allows the modeling of scenarios with a high number of nodes, taking into account both aspects of macro and micro-mobility [2], and allows the interconnection to the used network simulator—the ns-32.Based on the scenario described above, a section was defined in MOVE’s Map Editor with the characteristics indicated in Tables2 and 3. It should be noted that MOVE does not allow the creation of complex profiles with curves and unevenness, so it is not possible to represent the geography of the section in question accurately.Table 2
Characterization of the highway section of the AH1/M-2.
Length of the section (m)3000 (22 km to 25 km)Direction of trafficIslamabad to LahoreNumber of ways02 to 03Speed limit (km/h)120Table 3
Location of the most relevant points.
Real position (km)Position MOVE (m)Local accident22.0752925First departure23.231770MSW 124.84160MSW 223.791210MSW 322.62400To model the mobility of the nodes, we used vehicle movement generator based on previously defined traffic intensity values. The RSUs were represented using fixed nodes located at the exact coordinates of the previously selected CCTV systems. The mobility model used by MOVE is the car-following model [20, 21], managing to model the acceleration, braking, or lane change following the approach of other vehicles and the constant speed that allows for maintaining the minimum safety distance from the front vehicle. However, it does not consider the drivers’ response to stimuli, which could be interesting for modeling accident situations. In the model used, at the initial instant, the vehicles are all at the starting point, corresponding to the entrance to the highway. The departure time of each vehicle is randomly defined, following a uniform distribution, with values between the initial time and the final time of the simulation (180 s). The vehicle starts moving at the maximum permitted speed (120 km/h). This is a relatively simple representation of reality since it does not consider the real distribution of vehicle departure times and their movement, thus being able to condition the traffic density that is obtained and, consequently, the network’s performance. However, the existing real data do not allow a more detailed characterization.The modeling of the accident scene was carried out considering two different situations: in the first situation, the vehicle victim of the accident is stopped, preventing circulation in one of the carriageways; in the second situation, the three lanes are blocked, one by the injured vehicle and the others, e.g., by assistance vehicles.
### 5.3. Vehicle Network Modeling
The simulation of the accident scenario was performed using the ns-3 network simulator. The choice of this simulator was due to the fact that it is a free-to-use tool widely used by the scientific community, which allows complex simulations to be carried out with a level of detail that allows the reproduction of real results in a very reliable way.The vehicular network architecture is implemented by importing the MOVE output file, which contains the position of each node at each instant of simulation time. In simulations involving V2I/I2V communication, RSUs are special nodes whose position coordinate is maintained throughout the simulation. Vehicle entry and movement are carried out according to the mobility model described above.The fact that ns-3 does not yet have all the modules necessary to simulate a node with the proposed architecture (Figure2) led to the need to make adaptations to the model proposed previously.The previously considered applications are modeled through CBR (constant bit rate) traffic generators, with different time configurations between message generation. For the sake of simplicity, all messages have the same size (480 bytes), which was defined in order to ensure that the security information is already included in the packet, following the indications defined in [17–19].As previously mentioned, information from the PCW application has to reach all nodes quickly, which is achieved by having the receiving nodes resend the information received for the first time, while the information from the other applications has a local character. This behavior was modeled by defining the time to live (TTL) field in the message, which allows controlling the number of times the message is retransmitted. Therefore, for the PCW application, a value was selected that allows the message to be retransmitted the number of times necessary to allow its reception by nodes that are before the exit at the moment of the accident. This value must be parameterized for the different scenarios that may be considered. In order to respect the functional principles defined above, the PCW and EEBL applications only start when an accident occurs. The values used are shown in Table4.Table 4
Parameterization of traffic generators.
PCWEEBLCCWSize of messages (B)480480480Frequency (Hz)882DestinyAllAllAllTTL6022Start time (s)TaccidentTaccident0End instant (s)TsimulationTsimulationTsimulationThe simulation model developed uses the UDP protocol as an unreliable transport protocol at the transport level. At the routing level, a module was used that implements the GPSR geographic routing protocol [20], with a location service similar to the one used by Karp and Kung in the specification of the protocol itself.At the MAC layer level, the biggest limitations arise since ns-3 does not yet support the 802.11p protocol [17]. Thus, it was necessary to resort to the module that implements 802.11 communication in ad hoc mode. With this solution, there is no support for quality of service and switching between channels, which are essential mechanisms for the coexistence of security applications with other types of applications. The fact that applications other than those related to emergency scenarios are not being considered strongly reduces the impact of this limitation. It may, however, happen that, due to the inability to differentiate the various applications in use, the performance of the most critical application—PCW—is affected.The physical layer already has support for the 802.11p standard, and this was the model used. In order to obtain simulation results that approximate the real conditions as closely as possible, special care was taken in the choice of propagation models. We chose to use a model that accounts for losses due to signal attenuation with distance (path loss) and another that accounts for losses due to the effects of signal dispersion (multi-path fading). Therefore, the two-ray ground reflection and Nakagami [22] models are used. The range of the different types of antennas was modeled using the configuration of transmission power and antenna gain. The values used are shown in Table 5.Table 5
Parameterization of propagation models and antennas.
VehicleRSUNakagami modelNakagamim-factorm01.5m10.75m20.5Two-ray ground modelHeight (m)1.76.3AntennasTransmission power (dBm)518Hook (dBi)29
## 5.1. Characterization of the Accident Scenario
In order to obtain reliable results, an attempt was made to reproduce an accident scenario in simulation. Among the various types of cases identified in Section 3.3, the first was chosen, as it was the one where the most accidents were reported. This location (Jhelum, Punjab, Pakistan, (32.675778, 72.755291), shown in Figure3, is located on the Islamabad to Lahore (direction: Islamabad), close to k22.1 km, and in an area where the motorway has three lanes where accidents often happen there. The distance between the exit immediately before the accident site (10th exit) is approximately 1.2 km (red spot marker in the figure). To take advantage of the existing infrastructure, the RSUs must be placed next to the CCTV poles or next to the PMVs (marked in the figure with blue markers). However, since the distance between them is only a few hundred meters, there will be no need to install RSUs in all locations. The vehicle moves at the maximum permitted speed (120 km/h), so the RSUs must be placed next. Therefore, it was decided to include in the scenario, modeling only MSWs with an average distance between them of about 1 km (MSW 1, 2, and 3) for to be safe and avoid a collision, and this is a relatively simple representation of reality since it does not consider the natural distribution of vehicle departure times and their movement.Figure 3
Islamabad to Lahore section of the AH1/M-2 motorway.As mentioned earlier, the most frequent cause of accidents is speeding. However, accidents can occur in situations of high-traffic intensity or even in situations of low intensity. Any of these scenarios can have a strong impact on the performance of the vehicular network, as the first can lead to an overload of data traffic, and the second can lead to a lack of connectivity in the network. In order to better assess the impact of these two extreme cases, it was decided to select the values recorded section for the period with the highest traffic. At this stage, if your resource does not show up in the Endpoint list and you created both your hosted zone and the resource to which you are directing traffic using the same AWS account, make sure the following: verify that the record type you selected is supported, specific to the resource you are routing traffic to, for instance, you must select A — IPv4 address for the record type if you want to direct traffic to an S3 bucket.
## 5.2. Mobility Model
The mobility simulator MOVE1 (Mobility Model Generator for Vehicular Networks) was used for the mobility simulation since it fits the scenario under study. This road traffic generator allows the modeling of scenarios with a high number of nodes, taking into account both aspects of macro and micro-mobility [2], and allows the interconnection to the used network simulator—the ns-32.Based on the scenario described above, a section was defined in MOVE’s Map Editor with the characteristics indicated in Tables2 and 3. It should be noted that MOVE does not allow the creation of complex profiles with curves and unevenness, so it is not possible to represent the geography of the section in question accurately.Table 2
Characterization of the highway section of the AH1/M-2.
Length of the section (m)3000 (22 km to 25 km)Direction of trafficIslamabad to LahoreNumber of ways02 to 03Speed limit (km/h)120Table 3
Location of the most relevant points.
Real position (km)Position MOVE (m)Local accident22.0752925First departure23.231770MSW 124.84160MSW 223.791210MSW 322.62400To model the mobility of the nodes, we used vehicle movement generator based on previously defined traffic intensity values. The RSUs were represented using fixed nodes located at the exact coordinates of the previously selected CCTV systems. The mobility model used by MOVE is the car-following model [20, 21], managing to model the acceleration, braking, or lane change following the approach of other vehicles and the constant speed that allows for maintaining the minimum safety distance from the front vehicle. However, it does not consider the drivers’ response to stimuli, which could be interesting for modeling accident situations. In the model used, at the initial instant, the vehicles are all at the starting point, corresponding to the entrance to the highway. The departure time of each vehicle is randomly defined, following a uniform distribution, with values between the initial time and the final time of the simulation (180 s). The vehicle starts moving at the maximum permitted speed (120 km/h). This is a relatively simple representation of reality since it does not consider the real distribution of vehicle departure times and their movement, thus being able to condition the traffic density that is obtained and, consequently, the network’s performance. However, the existing real data do not allow a more detailed characterization.The modeling of the accident scene was carried out considering two different situations: in the first situation, the vehicle victim of the accident is stopped, preventing circulation in one of the carriageways; in the second situation, the three lanes are blocked, one by the injured vehicle and the others, e.g., by assistance vehicles.
## 5.3. Vehicle Network Modeling
The simulation of the accident scenario was performed using the ns-3 network simulator. The choice of this simulator was due to the fact that it is a free-to-use tool widely used by the scientific community, which allows complex simulations to be carried out with a level of detail that allows the reproduction of real results in a very reliable way.The vehicular network architecture is implemented by importing the MOVE output file, which contains the position of each node at each instant of simulation time. In simulations involving V2I/I2V communication, RSUs are special nodes whose position coordinate is maintained throughout the simulation. Vehicle entry and movement are carried out according to the mobility model described above.The fact that ns-3 does not yet have all the modules necessary to simulate a node with the proposed architecture (Figure2) led to the need to make adaptations to the model proposed previously.The previously considered applications are modeled through CBR (constant bit rate) traffic generators, with different time configurations between message generation. For the sake of simplicity, all messages have the same size (480 bytes), which was defined in order to ensure that the security information is already included in the packet, following the indications defined in [17–19].As previously mentioned, information from the PCW application has to reach all nodes quickly, which is achieved by having the receiving nodes resend the information received for the first time, while the information from the other applications has a local character. This behavior was modeled by defining the time to live (TTL) field in the message, which allows controlling the number of times the message is retransmitted. Therefore, for the PCW application, a value was selected that allows the message to be retransmitted the number of times necessary to allow its reception by nodes that are before the exit at the moment of the accident. This value must be parameterized for the different scenarios that may be considered. In order to respect the functional principles defined above, the PCW and EEBL applications only start when an accident occurs. The values used are shown in Table4.Table 4
Parameterization of traffic generators.
PCWEEBLCCWSize of messages (B)480480480Frequency (Hz)882DestinyAllAllAllTTL6022Start time (s)TaccidentTaccident0End instant (s)TsimulationTsimulationTsimulationThe simulation model developed uses the UDP protocol as an unreliable transport protocol at the transport level. At the routing level, a module was used that implements the GPSR geographic routing protocol [20], with a location service similar to the one used by Karp and Kung in the specification of the protocol itself.At the MAC layer level, the biggest limitations arise since ns-3 does not yet support the 802.11p protocol [17]. Thus, it was necessary to resort to the module that implements 802.11 communication in ad hoc mode. With this solution, there is no support for quality of service and switching between channels, which are essential mechanisms for the coexistence of security applications with other types of applications. The fact that applications other than those related to emergency scenarios are not being considered strongly reduces the impact of this limitation. It may, however, happen that, due to the inability to differentiate the various applications in use, the performance of the most critical application—PCW—is affected.The physical layer already has support for the 802.11p standard, and this was the model used. In order to obtain simulation results that approximate the real conditions as closely as possible, special care was taken in the choice of propagation models. We chose to use a model that accounts for losses due to signal attenuation with distance (path loss) and another that accounts for losses due to the effects of signal dispersion (multi-path fading). Therefore, the two-ray ground reflection and Nakagami [22] models are used. The range of the different types of antennas was modeled using the configuration of transmission power and antenna gain. The values used are shown in Table 5.Table 5
Parameterization of propagation models and antennas.
VehicleRSUNakagami modelNakagamim-factorm01.5m10.75m20.5Two-ray ground modelHeight (m)1.76.3AntennasTransmission power (dBm)518Hook (dBi)29
## 6. Results and Discussion
### 6.1. Test Scenario
The tests carried out are intended to assess whether the most critical application (PCW) requirements can be guaranteed, taking into account that there is traffic coming from other security applications in circulation. This assessment was carried out in several different scenarios:(i)
Communication with and without MSW.(ii)
One-way or three-way blocking.(iii)
Traffic with low and high intensities.
### 6.2. Evaluation Metrics
To measure the performance of the PCW application, application-level and network-level metrics were stipulated. From an application point of view, the following metrics were defined:(i)
Warning rate: the percentage of vehicles in circulation that received an accident notification.(ii)
Useful warning rate: the percentage of vehicles in circulation that received the accident notification within the latency and range limit characteristic of the PCW application.(iii)
Notification latency: time that elapses from when the accident occurs until the vehicle is notified.(iv)
Notification position: position of the node when it receives the accident notification, measured about the input coordinate.At the network level, the metrics considered were(i)
Number of hops: number of nodes used to relay the message.
### 6.3. Results Obtained: General Case
The information of each vehicle at the moment of the accident notification is represented through a set ofXY-type graphs. The X coordinate describes the notification latency and the Y coordinate describes the notification position. Figures 4(a) and 4(b) illustrate the values obtained in the situation of low vehicular intensity, and Figure 5 illustrates the case where the intensity is high.Figure 4
(a) Low vehicle intensity: the notification latency is in the order of 100 ms. (b) High vehicle intensity: the notification latency is in the order of 100 ms.
(a)(b)Figure 5
Low vehicle intensity; V2V and V2I communication; 1 blocked way (a) and high vehicle intensity; V2V and V2I communication; 1 blocked way (b).
(a)(b)Except for vehicles that are further away from the accident, in a low traffic intensity with V2V communication, most vehicles receive the notification very quickly, with the notification latency in the order of 100 ms. However, more distant vehicles have higher latencies (about 500 ms), although they can be warned when they are still far from the accident site. As shown in Figure4(b), the existence of RSUs (dots illustrated in red) makes it possible to reduce the latency value for more distant vehicles. When the traffic intensity is high, there is a greater variation in the notification conditions, which translates into a greater dispersion of the notification position. Regarding the notification latency, although there are variations in value, the maximum observed latency is much lower (about 135 ms) since more vehicles are capable of retransmitting the notification. The existence of RSUs allows more nodes to receive the notification faster, which is visible by the higher concentration of points along the Y-axis. It is also verified that the number of distant nodes that receive the notification earlier increases. This situation is particularly evident in the case of MSW 2 (Y = ∼1210 m). The results presented in Figures 5(a) and 5(b) illustrate the number of hops used histogram and confirm the previous conclusions. The use of RSUs reduces the number of communication hops, which reduces the notification latency since the RSU has a greater range and allows the transmission of information to distant nodes more quickly.
### 6.4. Results Obtained: Post-Accident Conditions
Based on the information received, it is also possible to assess how the notification would allow drivers to react promptly to the accident situation. Two different situations must be considered:(i)
Drivers in the accident area must be warned quickly to react in time to avoid secondary accidents.(ii)
Drivers who are en route to the accident area but still have time to receive the alert so that they can deviate follow an alternative route, avoiding congestion.Based on these assumptions, the warning rate, the useful warning rate, and the notification latency were measured for the general case and for each of the situations identified above. Table6 presents the results obtained for each of these metrics. In this study, it was considered that, in the general case and in the case of nodes before the exit, the warning was only useful if it arrived before 500 ms. In contrast, the maximum acceptable value for nodes in the accident region was 105 ms (the latency value defined for the EEBL application with a margin of 5%).Table 6
Results for the different post-accident conditions.
Global statisticsTotalBefore you leaveAccident areaNotice fee100%100%100%Useful notice fee100%100%86%Minimum notification latency (ms)102.75102.75102.75Average notification latency (ms)107.14107.32104.22Maximum notification latency (ms)133.92133.92111.79
## 6.1. Test Scenario
The tests carried out are intended to assess whether the most critical application (PCW) requirements can be guaranteed, taking into account that there is traffic coming from other security applications in circulation. This assessment was carried out in several different scenarios:(i)
Communication with and without MSW.(ii)
One-way or three-way blocking.(iii)
Traffic with low and high intensities.
## 6.2. Evaluation Metrics
To measure the performance of the PCW application, application-level and network-level metrics were stipulated. From an application point of view, the following metrics were defined:(i)
Warning rate: the percentage of vehicles in circulation that received an accident notification.(ii)
Useful warning rate: the percentage of vehicles in circulation that received the accident notification within the latency and range limit characteristic of the PCW application.(iii)
Notification latency: time that elapses from when the accident occurs until the vehicle is notified.(iv)
Notification position: position of the node when it receives the accident notification, measured about the input coordinate.At the network level, the metrics considered were(i)
Number of hops: number of nodes used to relay the message.
## 6.3. Results Obtained: General Case
The information of each vehicle at the moment of the accident notification is represented through a set ofXY-type graphs. The X coordinate describes the notification latency and the Y coordinate describes the notification position. Figures 4(a) and 4(b) illustrate the values obtained in the situation of low vehicular intensity, and Figure 5 illustrates the case where the intensity is high.Figure 4
(a) Low vehicle intensity: the notification latency is in the order of 100 ms. (b) High vehicle intensity: the notification latency is in the order of 100 ms.
(a)(b)Figure 5
Low vehicle intensity; V2V and V2I communication; 1 blocked way (a) and high vehicle intensity; V2V and V2I communication; 1 blocked way (b).
(a)(b)Except for vehicles that are further away from the accident, in a low traffic intensity with V2V communication, most vehicles receive the notification very quickly, with the notification latency in the order of 100 ms. However, more distant vehicles have higher latencies (about 500 ms), although they can be warned when they are still far from the accident site. As shown in Figure4(b), the existence of RSUs (dots illustrated in red) makes it possible to reduce the latency value for more distant vehicles. When the traffic intensity is high, there is a greater variation in the notification conditions, which translates into a greater dispersion of the notification position. Regarding the notification latency, although there are variations in value, the maximum observed latency is much lower (about 135 ms) since more vehicles are capable of retransmitting the notification. The existence of RSUs allows more nodes to receive the notification faster, which is visible by the higher concentration of points along the Y-axis. It is also verified that the number of distant nodes that receive the notification earlier increases. This situation is particularly evident in the case of MSW 2 (Y = ∼1210 m). The results presented in Figures 5(a) and 5(b) illustrate the number of hops used histogram and confirm the previous conclusions. The use of RSUs reduces the number of communication hops, which reduces the notification latency since the RSU has a greater range and allows the transmission of information to distant nodes more quickly.
## 6.4. Results Obtained: Post-Accident Conditions
Based on the information received, it is also possible to assess how the notification would allow drivers to react promptly to the accident situation. Two different situations must be considered:(i)
Drivers in the accident area must be warned quickly to react in time to avoid secondary accidents.(ii)
Drivers who are en route to the accident area but still have time to receive the alert so that they can deviate follow an alternative route, avoiding congestion.Based on these assumptions, the warning rate, the useful warning rate, and the notification latency were measured for the general case and for each of the situations identified above. Table6 presents the results obtained for each of these metrics. In this study, it was considered that, in the general case and in the case of nodes before the exit, the warning was only useful if it arrived before 500 ms. In contrast, the maximum acceptable value for nodes in the accident region was 105 ms (the latency value defined for the EEBL application with a margin of 5%).Table 6
Results for the different post-accident conditions.
Global statisticsTotalBefore you leaveAccident areaNotice fee100%100%100%Useful notice fee100%100%86%Minimum notification latency (ms)102.75102.75102.75Average notification latency (ms)107.14107.32104.22Maximum notification latency (ms)133.92133.92111.79
## 7. Conclusions and Recommendations
In the present work, the performance of vehicular networks on highways was analyzed, taking into account aspects such as the feasibility of placing RSUs along with the infrastructure, its impact on this same performance, and the ability to enable the timely receipt of warnings regarding emergencies, to minimize second collisions and mitigate traffic congestion. Different aspects were analyzed using the modeling and simulation of mobility and communication between vehicles and, additionally, between vehicles and road infrastructure—the RSUs.The results obtained allow us to conclude that the use of RSUs improves the performance of road safety applications, as it reduces the latency in receiving information. From the analysis of the same data, it is still possible to conclude that it is not necessary to install the RSUs mentioned above in all locations where there are currently CCTV poles or PMVs, which will have significant cost advantages.From the results in a post-accident phase, referring to high-intensity conditions, with three blocked lanes and the inclusion of RSUs, it appears that vehicles far from the accident zone, at a point that precedes an exit, are all warned in time. If the alert appeared before 500ms, it was beneficial. In contrast, if the maximum acceptable value for nodes in the accident region was 105 ms, it would be not useful. All vehicles in the accident zone, i.e., within the maximum range of 300 m, received the notification. However, only about 86% of them received it within the latency limit, i.e., 105 ms. However, considering the 500 ms of the PCW application, all nodes under study received the notification successfully, with a latency below this value.In future work, we intend to evaluate this situation in a small-scale experimental prototype, which allows us to assess to what extent the results obtained by simulation are representative of the real situation. This study will make it possible to determine the importance of aspects that cannot be modeled in simulation, such as the presence of obstacles on the motorway and the actual geometry of the motorway itself (levels, bridges, and curves, among others).
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*Source: 2902263-2022-07-20.xml* | 2022 |
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