Objective:Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic disorder can be reliably diagnosed utilizing combinations of multiple polygenic scores for psychiatric disorders and their intermediate phenotypes, compared with single polygenic score approaches, by applying specific machine learning techniques.Methods:Polygenic scores for 48 psychiatric disorders and intermediate phenotypes based on large-scale genome-wide association studies ( n = 7556–1,131,881) were calculated for people with panic disorder ( n = 718) and healthy controls ( n = 1717). Discrimination between people with panic disorder and healthy controls was based on the 48 polygenic scores using five methods for classification: logistic regression, neural networks, quadratic discriminant analysis, random forests and a support vector machine. Differences in discrimination accuracy (area under the curve) due to an increased number of polygenic score combinations and differences in the accuracy across five classifiers were investigated.Results:All five classifiers performed relatively well for distinguishing people with panic disorder from healthy controls by increasing the number of polygenic scores. Of the 48 polygenic scores, the polygenic score for anxiety UK Biobank was the most useful for discrimination by the classifiers. In combinations of two or three polygenic scores, the polygenic score for anxiety UK Biobank was included as one of polygenic scores in all classifiers. When all 48 polygenic scores were used in combination, the greatest areas under the curve significantly differed among the five classifiers. Support vector machine and logistic regression had higher accuracy than quadratic discriminant analysis and random forests. For each classifier, the greatest area under the curve was 0.600 ± 0.030 for logistic regression (polygenic score combinations N = 14), 0.591 ± 0.039 for neural networks ( N = 9), 0.603 ± 0.033 for quadratic discriminant analysis ( N = 10), 0.572 ± 0.039 for random forests ( N = 25) and 0.617 ± 0.041 for support vector machine ( N = 11). The greatest areas under the curve at the best polygenic score combination significantly differed among the five classifiers. Random forests had the lowest accuracy among classifiers. Support vector machine had higher accuracy than neural networks.Conclusions:These findings suggest that increasing the number of polygenic score combinations up to approximately 10 effectively improved the discrimination accuracy and that support vector machine exhibited greater accuracy among classifiers. However, the discrimination accuracy for panic disorder, when based solely on polygenic score combinations, was found to be modest.
{"title":"Discrimination between healthy participants and people with panic disorder based on polygenic scores for psychiatric disorders and for intermediate phenotypes using machine learning","authors":"Kazutaka Ohi, Yuta Tanaka, Takeshi Otowa, Mihoko Shimada, Hisanobu Kaiya, Fumichika Nishimura, Tsukasa Sasaki, Hisashi Tanii, Toshiki Shioiri, Takeshi Hara","doi":"10.1177/00048674241242936","DOIUrl":"https://doi.org/10.1177/00048674241242936","url":null,"abstract":"Objective:Panic disorder is a modestly heritable condition. Currently, diagnosis is based only on clinical symptoms; identifying objective biomarkers and a more reliable diagnostic procedure is desirable. We investigated whether people with panic disorder can be reliably diagnosed utilizing combinations of multiple polygenic scores for psychiatric disorders and their intermediate phenotypes, compared with single polygenic score approaches, by applying specific machine learning techniques.Methods:Polygenic scores for 48 psychiatric disorders and intermediate phenotypes based on large-scale genome-wide association studies ( n = 7556–1,131,881) were calculated for people with panic disorder ( n = 718) and healthy controls ( n = 1717). Discrimination between people with panic disorder and healthy controls was based on the 48 polygenic scores using five methods for classification: logistic regression, neural networks, quadratic discriminant analysis, random forests and a support vector machine. Differences in discrimination accuracy (area under the curve) due to an increased number of polygenic score combinations and differences in the accuracy across five classifiers were investigated.Results:All five classifiers performed relatively well for distinguishing people with panic disorder from healthy controls by increasing the number of polygenic scores. Of the 48 polygenic scores, the polygenic score for anxiety UK Biobank was the most useful for discrimination by the classifiers. In combinations of two or three polygenic scores, the polygenic score for anxiety UK Biobank was included as one of polygenic scores in all classifiers. When all 48 polygenic scores were used in combination, the greatest areas under the curve significantly differed among the five classifiers. Support vector machine and logistic regression had higher accuracy than quadratic discriminant analysis and random forests. For each classifier, the greatest area under the curve was 0.600 ± 0.030 for logistic regression (polygenic score combinations N = 14), 0.591 ± 0.039 for neural networks ( N = 9), 0.603 ± 0.033 for quadratic discriminant analysis ( N = 10), 0.572 ± 0.039 for random forests ( N = 25) and 0.617 ± 0.041 for support vector machine ( N = 11). The greatest areas under the curve at the best polygenic score combination significantly differed among the five classifiers. Random forests had the lowest accuracy among classifiers. Support vector machine had higher accuracy than neural networks.Conclusions:These findings suggest that increasing the number of polygenic score combinations up to approximately 10 effectively improved the discrimination accuracy and that support vector machine exhibited greater accuracy among classifiers. However, the discrimination accuracy for panic disorder, when based solely on polygenic score combinations, was found to be modest.","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140598296","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-04-06DOI: 10.1177/00048674241244601
Breanne Hobden, Jamie Bryant, Robert Davis, Todd Heard, Jenn Rumbel, Jamie Newman, Bron Rose, David Lambkin, Rob Sanson-Fisher, Megan Freund
Objectives:To determine the prevalence and demographic, social and health characteristics associated with co-occurring psychological distress symptoms, risky alcohol and/or substance use among a national sample of Aboriginal and Torres Strait Islander people aged 15 years or older.Methods:This study uses secondary cross-sectional data from the 2018-19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS). Data were collected via face-to-face interviews with those living in private dwellings across Australia. Participants were Aboriginal and Torres Strait Islander people ( n = 10,579) aged 15 years or older. Data pertaining to psychological distress, alcohol and substance use were obtained and weighted to represent the total population of Aboriginal and Torres Strait Islander people in Australia.Results:A total of 20.3% participants were found to have co-occurring psychological distress, risky alcohol use and/or substance use, and 4.0% reported co-occurrence of all three conditions. Female participants in a registered marriage and fully engaged in study or employment had lower rates of co-occurring conditions. Poorer self-rated health, one or more chronic conditions and increased experiences of unfair treatment and physical harm in the past 12 months were associated with increased rates of co-occurring conditions.Conclusion:A range of potential risk and protective factors were identified for co-occurring psychological distress, risky alcohol and/or substance use among Aboriginal and Torres Strait Islander people. This information is critical for planning effective holistic strategies to decrease the burden of suffering imposed upon the individual, family and community members impacted by co-occurring conditions.
{"title":"Co-occurring psychological distress and alcohol or other drug use among Indigenous Australians: Data from the National Aboriginal and Torres Strait Islander Health Survey","authors":"Breanne Hobden, Jamie Bryant, Robert Davis, Todd Heard, Jenn Rumbel, Jamie Newman, Bron Rose, David Lambkin, Rob Sanson-Fisher, Megan Freund","doi":"10.1177/00048674241244601","DOIUrl":"https://doi.org/10.1177/00048674241244601","url":null,"abstract":"Objectives:To determine the prevalence and demographic, social and health characteristics associated with co-occurring psychological distress symptoms, risky alcohol and/or substance use among a national sample of Aboriginal and Torres Strait Islander people aged 15 years or older.Methods:This study uses secondary cross-sectional data from the 2018-19 National Aboriginal and Torres Strait Islander Health Survey (NATSIHS). Data were collected via face-to-face interviews with those living in private dwellings across Australia. Participants were Aboriginal and Torres Strait Islander people ( n = 10,579) aged 15 years or older. Data pertaining to psychological distress, alcohol and substance use were obtained and weighted to represent the total population of Aboriginal and Torres Strait Islander people in Australia.Results:A total of 20.3% participants were found to have co-occurring psychological distress, risky alcohol use and/or substance use, and 4.0% reported co-occurrence of all three conditions. Female participants in a registered marriage and fully engaged in study or employment had lower rates of co-occurring conditions. Poorer self-rated health, one or more chronic conditions and increased experiences of unfair treatment and physical harm in the past 12 months were associated with increased rates of co-occurring conditions.Conclusion:A range of potential risk and protective factors were identified for co-occurring psychological distress, risky alcohol and/or substance use among Aboriginal and Torres Strait Islander people. This information is critical for planning effective holistic strategies to decrease the burden of suffering imposed upon the individual, family and community members impacted by co-occurring conditions.","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140598297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-03-04DOI: 10.1177/00048674241235587
Sean Halstead, Norman Sartorius, Susanna Every-Palmer, Najma Siddiqi, Giovanni de Girolamo, Dan Siskind, Nicola Warren
{"title":"Physical multimorbidity and mental illness: A global challenge","authors":"Sean Halstead, Norman Sartorius, Susanna Every-Palmer, Najma Siddiqi, Giovanni de Girolamo, Dan Siskind, Nicola Warren","doi":"10.1177/00048674241235587","DOIUrl":"https://doi.org/10.1177/00048674241235587","url":null,"abstract":"","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140034873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1177/00048674231169682
{"title":"RANZCP Abstracts","authors":"","doi":"10.1177/00048674231169682","DOIUrl":"https://doi.org/10.1177/00048674231169682","url":null,"abstract":"","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80866190","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-02-01DOI: 10.1177/00048674221150360
Owen P. O’Sullivan
{"title":"Book Review of “Psychopathology of Rare and Unusual Syndromes” by Femi Oyebode","authors":"Owen P. O’Sullivan","doi":"10.1177/00048674221150360","DOIUrl":"https://doi.org/10.1177/00048674221150360","url":null,"abstract":"","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80214911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-10-27DOI: 10.1007/978-3-540-68706-1_518
Paul B. Badcock
{"title":"Mania","authors":"Paul B. Badcock","doi":"10.1007/978-3-540-68706-1_518","DOIUrl":"https://doi.org/10.1007/978-3-540-68706-1_518","url":null,"abstract":"","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-10-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74799103","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-11DOI: 10.1177/00048674221104403
I. Berger
{"title":"Seeking mental health support as a psychiatrist","authors":"I. Berger","doi":"10.1177/00048674221104403","DOIUrl":"https://doi.org/10.1177/00048674221104403","url":null,"abstract":"","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82248978","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-10DOI: 10.1177/00048674221103478
G. Parker, Michael J. Spoelma, G. Tavella
Objectives: Judging that the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) criteria for defining mania/hypomania (and thus bipolar I/II disorders, respectively) would benefit from review, we formed an expert taskforce to derive modified criteria for consideration. The aim of this paper is to summarise the component stages and detail the final recommended criteria. Methods: We first sought taskforce members’ views on the Diagnostic and Statistical Manual of Mental Disorders criteria and how they might be modified. Next, members recruited patients with a bipolar I or II disorder, and who were asked to judge new definitional options and complete a symptom checklist to determine the most differentiating items. The latter task was also completed by a small comparison group of unipolar depressed patients to determine the mood state items that best differentiate unipolar from bipolar subjects. Subsequent reports overviewed analyses arguing for bipolar I and II as being categorically distinct and generated empirically derived diagnostic criteria. Results: Alternatives to all the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) criteria were generated. Modifications included recognising that impairment is not a necessary criterion, removing hospitalisation as automatically assigning bipolar I status, adding an irritable/angry symptom construct to the symptom list, deleting a mandatory duration period for manic/hypomanic episodes, and requiring a greater number of affirmed symptoms for a bipolar diagnosis to manage the risk of overdiagnosis. Granular symptom criteria were identified by analyses and constructed to assist clinician assessment. A potential bipolar screening measure was developed with analyses showing that it could clearly distinguish bipolar versus unipolar status, whether symptom items were assigned as having equal status or weighted by their quantified diagnostic contribution. Conclusion: While requiring further validation, we suggest that the revised criteria overcome several current Diagnostic and Statistical Manual of Mental Disorders (5th ed.) limitations to defining and differentiating the two bipolar sub-types, while still respecting and preserving the Diagnostic and Statistical Manual of Mental Disorders template. It will be necessary to determine whether the bipolar screening measure has superiority to currently accepted measures.
{"title":"The AREDOC project and its implications for the definition and measurement of the bipolar disorders: A summary report","authors":"G. Parker, Michael J. Spoelma, G. Tavella","doi":"10.1177/00048674221103478","DOIUrl":"https://doi.org/10.1177/00048674221103478","url":null,"abstract":"Objectives: Judging that the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) criteria for defining mania/hypomania (and thus bipolar I/II disorders, respectively) would benefit from review, we formed an expert taskforce to derive modified criteria for consideration. The aim of this paper is to summarise the component stages and detail the final recommended criteria. Methods: We first sought taskforce members’ views on the Diagnostic and Statistical Manual of Mental Disorders criteria and how they might be modified. Next, members recruited patients with a bipolar I or II disorder, and who were asked to judge new definitional options and complete a symptom checklist to determine the most differentiating items. The latter task was also completed by a small comparison group of unipolar depressed patients to determine the mood state items that best differentiate unipolar from bipolar subjects. Subsequent reports overviewed analyses arguing for bipolar I and II as being categorically distinct and generated empirically derived diagnostic criteria. Results: Alternatives to all the Diagnostic and Statistical Manual of Mental Disorders (5th ed.) criteria were generated. Modifications included recognising that impairment is not a necessary criterion, removing hospitalisation as automatically assigning bipolar I status, adding an irritable/angry symptom construct to the symptom list, deleting a mandatory duration period for manic/hypomanic episodes, and requiring a greater number of affirmed symptoms for a bipolar diagnosis to manage the risk of overdiagnosis. Granular symptom criteria were identified by analyses and constructed to assist clinician assessment. A potential bipolar screening measure was developed with analyses showing that it could clearly distinguish bipolar versus unipolar status, whether symptom items were assigned as having equal status or weighted by their quantified diagnostic contribution. Conclusion: While requiring further validation, we suggest that the revised criteria overcome several current Diagnostic and Statistical Manual of Mental Disorders (5th ed.) limitations to defining and differentiating the two bipolar sub-types, while still respecting and preserving the Diagnostic and Statistical Manual of Mental Disorders template. It will be necessary to determine whether the bipolar screening measure has superiority to currently accepted measures.","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80410230","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-10DOI: 10.1177/00048674221103491
G. Malhi, Erica Bell, Cornélia Kaufmann, V. Brakoulias
{"title":"The broader benefits of DBS for refractory OCD","authors":"G. Malhi, Erica Bell, Cornélia Kaufmann, V. Brakoulias","doi":"10.1177/00048674221103491","DOIUrl":"https://doi.org/10.1177/00048674221103491","url":null,"abstract":"","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75165767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-06-08DOI: 10.1177/00048674221106678
C. Foldi, M. James, RobynM . Brown, M. Piya, T. Steward
Australian & New Zealand Journal of Psychiatry, 56(7) Eating disorders are among the most complex psychiatric disorders encountered in clinical practice, with anorexia nervosa (AN), for example, having the highest mortality rate of any psychiatric illness. The aetiology of eating disorders remains elusive and the development of targeted pharmacological interventions for eating disorders has stalled. Moreover, a 2017 study found that government funding for eating disorder research in Australia equates to approximately AUD$1.10 per affected individual, in noticeable contrast to research funding for schizophrenia standing at AUD$67.36 per affected individual (Murray et al., 2017). At the 2022 Meeting of the Australia and New Zealand Academy of Eating Disorders (ANZAED), we held a Plenary session entitled ‘Translating eating disorders neuroscience research: Lessons from bench-to-bedside treatments’ to highlight potential avenues for the development of novel eating disorder treatments. This article presents a summary of the topics covered therewithin.
澳大利亚和新西兰精神病学杂志，56(7)饮食失调是临床实践中遇到的最复杂的精神障碍之一，例如神经性厌食症(AN)是所有精神疾病中死亡率最高的。饮食失调的病因仍然难以捉摸，针对饮食失调的药物干预的发展已经停滞。此外，2017年的一项研究发现，澳大利亚政府为饮食失调研究提供的资金相当于每个受影响个体约1.10澳元，与精神分裂症的研究资金形成鲜明对比，每个受影响个体的研究资金为67.36澳元(Murray et al.， 2017)。在澳大利亚和新西兰饮食失调学会(ANZAED) 2022年会议上，我们举行了题为“转化饮食失调神经科学研究:从实验到临床治疗的经验教训”的全体会议，以强调发展新型饮食失调治疗的潜在途径。本文概述了其中涉及的主题。
{"title":"Advancing translational neuroscience research for eating disorders","authors":"C. Foldi, M. James, RobynM . Brown, M. Piya, T. Steward","doi":"10.1177/00048674221106678","DOIUrl":"https://doi.org/10.1177/00048674221106678","url":null,"abstract":"Australian & New Zealand Journal of Psychiatry, 56(7) Eating disorders are among the most complex psychiatric disorders encountered in clinical practice, with anorexia nervosa (AN), for example, having the highest mortality rate of any psychiatric illness. The aetiology of eating disorders remains elusive and the development of targeted pharmacological interventions for eating disorders has stalled. Moreover, a 2017 study found that government funding for eating disorder research in Australia equates to approximately AUD$1.10 per affected individual, in noticeable contrast to research funding for schizophrenia standing at AUD$67.36 per affected individual (Murray et al., 2017). At the 2022 Meeting of the Australia and New Zealand Academy of Eating Disorders (ANZAED), we held a Plenary session entitled ‘Translating eating disorders neuroscience research: Lessons from bench-to-bedside treatments’ to highlight potential avenues for the development of novel eating disorder treatments. This article presents a summary of the topics covered therewithin.","PeriodicalId":8576,"journal":{"name":"Australian & New Zealand Journal of Psychiatry","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78272061","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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