Pub Date : 2021-01-01DOI: 10.35248/2153-0602.21.12.241
Azonbakin Simon, A. Bruno, Adovoekpe Diane, M. Gbedo, Goussanou Yannick, A. Agbanlinsou, A. Philippe, Gangbo Flore, Lalèyè Anatole
Couple infertility is one of the major public health problems nowadays. Genetic etiologies are rarely discussed in our country, because of the predominance of infectious causes. Here we report a case of translocation t (2; 5) (q37.3;14 q35.3) explaining infertility in a 50-year-old man with a spermogram showing astheno teratozoospermia and normal phenotypic examination.
{"title":"Translocation (2; 5) (q37.3, q14q35.3) in a Case of Male Infertility in Cotonou","authors":"Azonbakin Simon, A. Bruno, Adovoekpe Diane, M. Gbedo, Goussanou Yannick, A. Agbanlinsou, A. Philippe, Gangbo Flore, Lalèyè Anatole","doi":"10.35248/2153-0602.21.12.241","DOIUrl":"https://doi.org/10.35248/2153-0602.21.12.241","url":null,"abstract":"Couple infertility is one of the major public health problems nowadays. Genetic etiologies are rarely discussed in our country, because of the predominance of infectious causes. Here we report a case of translocation t (2; 5) (q37.3;14 q35.3) explaining infertility in a 50-year-old man with a spermogram showing astheno teratozoospermia and normal phenotypic examination.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"130 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73878132","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 : 2021-01-01DOI: 10.35248/2153-0602.21.12.E132
S. Martin
DNA sequencing is the way toward deciding the grouping of nucleotides inside a DNA particle. Each organic entity's DNA comprises of a remarkable grouping of nucleotides. Deciding the grouping can help researchers analyze DNA between organic entities, which can help show how the creatures are connected. This implies that by sequencing a stretch of DNA, it will be feasible to know the request in which the four nucleotide bases – adenine, guanine, cytosine, and thymine – happen inside that nucleic corrosive particle. The need of DNA sequencing was first made clear by Francis Crick's hypothesis that the succession of nucleotides inside a DNA atom straightforwardly affected the amino corrosive groupings of proteins. At that point, the conviction was that a totally sequenced genome would prompt a quantum jump in understanding the natural chemistry of cells and organic entities. Present day DNA sequencing comprises of high-throughput strategies which permit whole DNA arrangements to be found very quickly. This innovation has permitted numerous organizations to begin offering at-home DNA testing. Large numbers of the "results" found by these tests are just connections found between a hereditary variation and a specific condition. Notwithstanding, innovation has additionally permitted researchers to test the DNA of numerous organic entities to more readily comprehend developmental connections..
{"title":"Overview of DNA Sequencing methods","authors":"S. Martin","doi":"10.35248/2153-0602.21.12.E132","DOIUrl":"https://doi.org/10.35248/2153-0602.21.12.E132","url":null,"abstract":"DNA sequencing is the way toward deciding the grouping of nucleotides inside a DNA particle. Each organic entity's DNA comprises of a remarkable grouping of nucleotides. Deciding the grouping can help researchers analyze DNA between organic entities, which can help show how the creatures are connected. This implies that by sequencing a stretch of DNA, it will be feasible to know the request in which the four nucleotide bases – adenine, guanine, cytosine, and thymine – happen inside that nucleic corrosive particle. The need of DNA sequencing was first made clear by Francis Crick's hypothesis that the succession of nucleotides inside a DNA atom straightforwardly affected the amino corrosive groupings of proteins. At that point, the conviction was that a totally sequenced genome would prompt a quantum jump in understanding the natural chemistry of cells and organic entities. Present day DNA sequencing comprises of high-throughput strategies which permit whole DNA arrangements to be found very quickly. This innovation has permitted numerous organizations to begin offering at-home DNA testing. Large numbers of the \"results\" found by these tests are just connections found between a hereditary variation and a specific condition. Notwithstanding, innovation has additionally permitted researchers to test the DNA of numerous organic entities to more readily comprehend developmental connections..","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"21 1","pages":"1-1"},"PeriodicalIF":0.0,"publicationDate":"2021-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86284458","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 : 2020-01-01DOI: 10.35248/2153-0602.20.11.220
A. Musa, U. Aliyu
According to international agency for research on cancer, female breast cancer was the leading type of cancer worldwide in terms of the number of new cases (approximately 2.1 million) diagnosed in 2018. Predicting outcome of a disease is a challenging task. Data mining techniques tends to simplify the prediction segment. Automated tools have made it possible to collect large volumes of medical data, which are made available to the medical research groups. This study aimed to apply machine learning algorithms using decision three classifier and descriptive statistics to evaluate the performance of the model in predicting the probability of cancer metastasis in patients that present late. Materials and method: The breast cancer disease dataset has been taken from the department of Radiotherapy and Oncology of Usmanu Danfodiyo University Teaching Hospital, Sokoto state, Nigerian. Dataset has 259 instances and 10 attributes. The experimental results of this study used, decision three classifier in IMB SPSS (version 23) software environment. In the experiment, two classes were used and therefore a 2 × 2 confusion matrix was applied. Class 0=Not Metastasized, Class 1=Metastasized. We applied supervised machine learning approach in which dataset were divided into two classes that is training and testing using 10 fold cross validation. Results: Shows that 259 instance of breast cancer, 218(84.2%) cases were not metastasized while 41(15.8%) cases were metastasized to the other region of the body. The overall accuracy of the model was found to be 87%, with the sensitivity of 88%, specificity 75% and the precision of 98% Conclusion: Based on these findings, the machine learning algorism using decision three classifiers predicted that 87% of the tumor presented at stage IV, indicating that the tumour can spread to the other region of the body.
{"title":"Application of Machine Learning Techniques in Predicting of Breast Cancer Metastases Using Decision Tree Algorithm, in Sokoto Northwestern Nigeria","authors":"A. Musa, U. Aliyu","doi":"10.35248/2153-0602.20.11.220","DOIUrl":"https://doi.org/10.35248/2153-0602.20.11.220","url":null,"abstract":"According to international agency for research on cancer, female breast cancer was the leading type of cancer worldwide in terms of the number of new cases (approximately 2.1 million) diagnosed in 2018. Predicting outcome of a disease is a challenging task. Data mining techniques tends to simplify the prediction segment. Automated tools have made it possible to collect large volumes of medical data, which are made available to the medical research groups. This study aimed to apply machine learning algorithms using decision three classifier and descriptive statistics to evaluate the performance of the model in predicting the probability of cancer metastasis in patients that present late. Materials and method: The breast cancer disease dataset has been taken from the department of Radiotherapy and Oncology of Usmanu Danfodiyo University Teaching Hospital, Sokoto state, Nigerian. Dataset has 259 instances and 10 attributes. The experimental results of this study used, decision three classifier in IMB SPSS (version 23) software environment. In the experiment, two classes were used and therefore a 2 × 2 confusion matrix was applied. Class 0=Not Metastasized, Class 1=Metastasized. We applied supervised machine learning approach in which dataset were divided into two classes that is training and testing using 10 fold cross validation. Results: Shows that 259 instance of breast cancer, 218(84.2%) cases were not metastasized while 41(15.8%) cases were metastasized to the other region of the body. The overall accuracy of the model was found to be 87%, with the sensitivity of 88%, specificity 75% and the precision of 98% Conclusion: Based on these findings, the machine learning algorism using decision three classifiers predicted that 87% of the tumor presented at stage IV, indicating that the tumour can spread to the other region of the body.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"28 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79481763","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 : 2020-01-01DOI: 10.35248/2165-7556.20.11.223
R. Holmes
At least fifteen families of mammalian carbonic anhydrases (CA) (E.C. 4.2.1.2) catalyse the hydration of carbon dioxide and related functions. CA5A and CA5B genes encode distinct mitochondrial enzymes and perform essential biochemical roles, including ammonia detoxification and glucose metabolism. Bioinformatic methods were used to predict the amino acid sequences, secondary structures and gene locations for CA5A and CA5B genes and proteins using data from vertebrate genome projects. CA5A and CA5B genes usually contained 7 coding exons for each of the vertebrate genomes examined. Human CA5A and CA5B subunits contained 305 and 317 amino acids, respectively, with key amino acid residues including mitochondrial transit peptides; three Zinc binding sites (His130, His132, His155); and a Tyr164 active site. Phylogenetic analyses of vertebrate CA5 gene families suggested that it is an ancient gene in vertebrate evolution which had undergone a gene duplication event in a mammalian ancestral genome forming the CA5A and CA5B gene families in monotreme, marsupial and eutherian mammals. CA5A was predominantly expressed in liver whereas CA5B had a wide tissue distribution profile, was localized on the X-chromosome and was more highly conserved during mammalian evolution.
{"title":"Comparative Studies of Vertebrate Mitochondrial Carbonic Anhydrase (CA5) Genes and Proteins: Evidence for Gene Duplication in Mammals with CA5A Being Liver Specific and CA5B Broadly Expressed and Located on the X-Chromosome","authors":"R. Holmes","doi":"10.35248/2165-7556.20.11.223","DOIUrl":"https://doi.org/10.35248/2165-7556.20.11.223","url":null,"abstract":"At least fifteen families of mammalian carbonic anhydrases (CA) (E.C. 4.2.1.2) catalyse the hydration of carbon dioxide and related functions. CA5A and CA5B genes encode distinct mitochondrial enzymes and perform essential biochemical roles, including ammonia detoxification and glucose metabolism. Bioinformatic methods were used to predict the amino acid sequences, secondary structures and gene locations for CA5A and CA5B genes and proteins using data from vertebrate genome projects. CA5A and CA5B genes usually contained 7 coding exons for each of the vertebrate genomes examined. Human CA5A and CA5B subunits contained 305 and 317 amino acids, respectively, with key amino acid residues including mitochondrial transit peptides; three Zinc binding sites (His130, His132, His155); and a Tyr164 active site. Phylogenetic analyses of vertebrate CA5 gene families suggested that it is an ancient gene in vertebrate evolution which had undergone a gene duplication event in a mammalian ancestral genome forming the CA5A and CA5B gene families in monotreme, marsupial and eutherian mammals. CA5A was predominantly expressed in liver whereas CA5B had a wide tissue distribution profile, was localized on the X-chromosome and was more highly conserved during mammalian evolution.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"16 1","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73109229","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 : 2020-01-01DOI: 10.35248/2153-0602.20.11.221
Yosuke Kondo, S. Miyazaki
Genome-wide analysis has shown that there are non-protein-coding RNAs (ncRNAs) that are localized on intronic regions of protein-coding genes. The intronic ncRNAs are hosted in introns of protein-coding genes that are referred to as host genes. Our previous study reported genomic features of intronic ncRNA genes and host genes. However, transcriptomic features of host genes have not been investigated. Here we report gene expression level analysis of host genes and investigate biological functions of host genes. Our results showed that gene expression levels of host genes tend to be higher than those of non-host genes. Host genes orthologous between human and mouse have more conserved expression levels than non-host orthologous genes. And host genes with high expression levels involve nervous system, gene expression, protein modification and cytoskeleton whereas there were mostly no enriched biological functions in host genes with low expression levels. These results suggest that host genes have characteristic transcript quantification and biological functions. The characteristics may be useful for further analysis of regulatory ways of host gene expression.
{"title":"Gene Expression Level and Gene Set Enrichment Analysis of Host Genes","authors":"Yosuke Kondo, S. Miyazaki","doi":"10.35248/2153-0602.20.11.221","DOIUrl":"https://doi.org/10.35248/2153-0602.20.11.221","url":null,"abstract":"Genome-wide analysis has shown that there are non-protein-coding RNAs (ncRNAs) that are localized on intronic regions of protein-coding genes. The intronic ncRNAs are hosted in introns of protein-coding genes that are referred to as host genes. Our previous study reported genomic features of intronic ncRNA genes and host genes. However, transcriptomic features of host genes have not been investigated. Here we report gene expression level analysis of host genes and investigate biological functions of host genes. Our results showed that gene expression levels of host genes tend to be higher than those of non-host genes. Host genes orthologous between human and mouse have more conserved expression levels than non-host orthologous genes. And host genes with high expression levels involve nervous system, gene expression, protein modification and cytoskeleton whereas there were mostly no enriched biological functions in host genes with low expression levels. These results suggest that host genes have characteristic transcript quantification and biological functions. The characteristics may be useful for further analysis of regulatory ways of host gene expression.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"53 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86499454","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 : 2020-01-01DOI: 10.35248/2153-0602.20.11.222
Ishaku L. Haruna, Huitong Zhou, J. Hickford
The objective of this short commentary is to elaborate on some of the main themes identified in the previously published article entitled “Genetic variation and haplotypic diversity in the myostatin gene of New Zealand cattle breeds”. The absence of genetic variation in the coding sequences of myostatin gene in the New Zealand cattle breeds likely suggests one or more of the effects of selection pressure, cross-breeding and inbreeding and genetic drift.
{"title":"Short Commentary on: Absence of Genetic Variation in the Coding Sequence of Myostatin Gene (MSTN) in New Zealand Cattle Breeds","authors":"Ishaku L. Haruna, Huitong Zhou, J. Hickford","doi":"10.35248/2153-0602.20.11.222","DOIUrl":"https://doi.org/10.35248/2153-0602.20.11.222","url":null,"abstract":"The objective of this short commentary is to elaborate on some of the main themes identified in the previously published article entitled “Genetic variation and haplotypic diversity in the myostatin gene of New Zealand cattle breeds”. The absence of genetic variation in the coding sequences of myostatin gene in the New Zealand cattle breeds likely suggests one or more of the effects of selection pressure, cross-breeding and inbreeding and genetic drift.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"11 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81642511","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 : 2020-01-01DOI: 10.35248/2153-0602.20.11.E221
S. Daefler
Data mining refers to the processes of discovering large data sets which involves the methods of intersection of statistics, Data base systems and machine learning. Genomics refers to the study of structure, function, evolution, and mapping of genomes. Proteomics refers to study of proteins as proteins are the essential things for the growth of function and growth of living organisms. Data Mining in Genomics and proteomics correlates the interface of computer science along with the biological aspects which paves an easy and essential way for future biological researchers throughout the world.
{"title":"Data Mining in Genomics and Proteomics for a New Era of Computational Biology","authors":"S. Daefler","doi":"10.35248/2153-0602.20.11.E221","DOIUrl":"https://doi.org/10.35248/2153-0602.20.11.E221","url":null,"abstract":"Data mining refers to the processes of discovering large data sets which involves the methods of intersection of statistics, Data base systems and machine learning. Genomics refers to the study of structure, function, evolution, and mapping of genomes. Proteomics refers to study of proteins as proteins are the essential things for the growth of function and growth of living organisms. Data Mining in Genomics and proteomics correlates the interface of computer science along with the biological aspects which paves an easy and essential way for future biological researchers throughout the world.","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"3 1","pages":"1-1"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74665495","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 : 2020-01-01DOI: 10.35248/2153-0602.20.S6.004
Tianfu Wu
{"title":"Autoantibodies and Apoptosis in Lupus Nephritis by Genetic Association","authors":"Tianfu Wu","doi":"10.35248/2153-0602.20.S6.004","DOIUrl":"https://doi.org/10.35248/2153-0602.20.S6.004","url":null,"abstract":"","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"150 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77384248","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 : 2020-01-01DOI: 10.35248/2153-0602.20.S6.002
Tianfu Wu
{"title":"Lupus Nephritis Caused by an Auto Invulnerable Infection from Genomics","authors":"Tianfu Wu","doi":"10.35248/2153-0602.20.S6.002","DOIUrl":"https://doi.org/10.35248/2153-0602.20.S6.002","url":null,"abstract":"","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"75 1","pages":"1-2"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76524712","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 : 2020-01-01DOI: 10.35248/2153-0602.20.S6.003
Sasidharan Pk
The medical professionals became more hysterical than the public in behavior. Yes, the real problem was not the virus, but the issues behind the virus, the people who by encroaching into the nature and natural habitats of the animals to produce a new virus, and those who took the wrong decisions due to lack of genuine insight into social health or public health. Public health for most of the decision makers is just about availability of treatment facilities including vaccines and ventilators, which is in fact not. Public health in reality is an issue of empowering the people to live in environment that would enable them to practice good diet and lifestyle and avail all the social determinants of health, including safe drinking water, decent shelter, balanced diet, proper primary education and so on. The reality all over the world, even in Covid-19, is that the marginalized sections had suffered from all diseases and their consequences. Even lack of awareness about healthy living, leave alone the issue of empowerment, is a manifestation of marginalization. I am certain that this is true regarding all the countries, only difference being magnitude of marginalization, and the combination of items left out in the list of necessities would vary from place to place. In this scenario, the medical professionals are facing an unforeseen challenge to look after their patients, their own health, and their family, due to the pandemic. The suggestions and guidelines which are given below are for them and their patients
{"title":"Action Plans for Medical Professionals to Fight COVID-19","authors":"Sasidharan Pk","doi":"10.35248/2153-0602.20.S6.003","DOIUrl":"https://doi.org/10.35248/2153-0602.20.S6.003","url":null,"abstract":"The medical professionals became more hysterical than the public in behavior. Yes, the real problem was not the virus, but the issues behind the virus, the people who by encroaching into the nature and natural habitats of the animals to produce a new virus, and those who took the wrong decisions due to lack of genuine insight into social health or public health. Public health for most of the decision makers is just about availability of treatment facilities including vaccines and ventilators, which is in fact not. Public health in reality is an issue of empowering the people to live in environment that would enable them to practice good diet and lifestyle and avail all the social determinants of health, including safe drinking water, decent shelter, balanced diet, proper primary education and so on. The reality all over the world, even in Covid-19, is that the marginalized sections had suffered from all diseases and their consequences. Even lack of awareness about healthy living, leave alone the issue of empowerment, is a manifestation of marginalization. I am certain that this is true regarding all the countries, only difference being magnitude of marginalization, and the combination of items left out in the list of necessities would vary from place to place. In this scenario, the medical professionals are facing an unforeseen challenge to look after their patients, their own health, and their family, due to the pandemic. The suggestions and guidelines which are given below are for them and their patients","PeriodicalId":15630,"journal":{"name":"Journal of Data Mining in Genomics & Proteomics","volume":"15 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87135338","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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