Genome Medicine最新文献

{"title":"Identifying latent genetic interactions in genome-wide association studies using multiple traits","authors":"Andrew J. Bass, Shijia Bian, Aliza P. Wingo, Thomas S. Wingo, David J. Cutler, Michael P. Epstein","doi":"10.1186/s13073-024-01329-0","DOIUrl":"https://doi.org/10.1186/s13073-024-01329-0","url":null,"abstract":"The \"missing\" heritability of complex traits may be partly explained by genetic variants interacting with other genes or environments that are difficult to specify, observe, and detect. We propose a new kernel-based method called Latent Interaction Testing (LIT) to screen for genetic interactions that leverages pleiotropy from multiple related traits without requiring the interacting variable to be specified or observed. Using simulated data, we demonstrate that LIT increases power to detect latent genetic interactions compared to univariate methods. We then apply LIT to obesity-related traits in the UK Biobank and detect variants with interactive effects near known obesity-related genes (URL: https://CRAN.R-project.org/package=lit ).","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140804996","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance","authors":"João Dourado Santos, Daniel Sobral, Miguel Pinheiro, J. Isidro, Carlijn Bogaardt, Miguel Pinto, Rodrigo Eusébio, André Santos, Rafael Mamede, Daniel L. Horton, João Paulo Gomes, V. Borges","doi":"10.1186/s13073-024-01334-3","DOIUrl":"https://doi.org/10.1186/s13073-024-01334-3","url":null,"abstract":"","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140653660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single-cell transcriptomics reveal distinct immune-infiltrating phenotypes and macrophage–tumor interaction axes among different lineages of pituitary neuroendocrine tumors","authors":"Shaojian Lin, Yuting Dai, Changxi Han, Tianyi Han, Linfeng Zhao, Renyan Wu, Jianyue Liu, Bo Zhang, Ning Huang, Yanting Liu, Shujing Lai, Jintong Shi, Yu Wang, Meiqing Lou, Jing Xie, Yijun Cheng, Hao Tang, Hong Yao, Hai Fang, Yan Zhang, Xuefeng Wu, Lei Shen, Youqiong Ye, Li Xue, Zhe Bao Wu","doi":"10.1186/s13073-024-01325-4","DOIUrl":"https://doi.org/10.1186/s13073-024-01325-4","url":null,"abstract":"","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140661318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metabolic and inflammatory perturbation of diabetes associated gut dysbiosis in people living with and without HIV infection","authors":"Kai Luo, Brandilyn A. Peters, Jee-Young Moon, Xiaonan Xue, Zheng Wang, Mykhaylo Usyk, David B. Hanna, Alan L. Landay, Michael F. Schneider, Deborah Gustafson, Kathleen M. Weber, Audrey French, Anjali Sharma, Kathryn Anastos, Tao Wang, Todd Brown, Clary B. Clish, Robert C. Kaplan, Rob Knight, Robert D. Burk, Qibin Qi","doi":"10.1186/s13073-024-01336-1","DOIUrl":"https://doi.org/10.1186/s13073-024-01336-1","url":null,"abstract":"Gut dysbiosis has been linked with both HIV infection and diabetes, but its interplay with metabolic and inflammatory responses in diabetes, particularly in the context of HIV infection, remains unclear. We first conducted a cross-sectional association analysis to characterize the gut microbial, circulating metabolite, and immune/inflammatory protein features associated with diabetes in up to 493 women (~ 146 with prevalent diabetes with 69.9% HIV +) of the Women’s Interagency HIV Study. Prospective analyses were then conducted to determine associations of identified metabolites with incident diabetes over 12 years of follow-up in 694 participants (391 women from WIHS and 303 men from the Multicenter AIDS Cohort Study; 166 incident cases were recorded) with and without HIV infection. Mediation analyses were conducted to explore whether gut bacteria–diabetes associations are explained by altered metabolites and proteins. Seven gut bacterial genera were identified to be associated with diabetes (FDR-q < 0.1), with positive associations for Shigella, Escherichia, Megasphaera, and Lactobacillus, and inverse associations for Adlercreutzia, Ruminococcus, and Intestinibacter. Importantly, the associations of most species, especially Adlercreutzia and Ruminococcus, were largely independent of antidiabetic medications use. Meanwhile, 18 proteins and 76 metabolites, including 3 microbially derived metabolites (trimethylamine N-oxide, phenylacetylglutamine (PAGln), imidazolepropionic acid (IMP)), 50 lipids (e.g., diradylglycerols (DGs) and triradylglycerols (TGs)) and 23 non-lipid metabolites, were associated with diabetes (FDR-q < 0.1), with the majority showing positive associations and more than half of them (59/76) associated with incident diabetes. In mediation analyses, several proteins, especially interleukin-18 receptor 1 and osteoprotegerin, IMP and PAGln partially mediate the observed bacterial genera–diabetes associations, particularly for those of Adlercreutzia and Escherichia. Many diabetes-associated metabolites and proteins were altered in HIV, but no effect modification on their associations with diabetes was observed by HIV. Among individuals with and without HIV, multiple gut bacterial genera, blood metabolites, and proinflammatory proteins were associated with diabetes. The observed mediated effects by metabolites and proteins in genera–diabetes associations highlighted the potential involvement of inflammatory and metabolic perturbations in the link between gut dysbiosis and diabetes in the context of HIV infection.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140628873","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The emergence of highly resistant and hypervirulent Klebsiella pneumoniae CC14 clone in a tertiary hospital over 8 years","authors":"Sharif Hala, Mohammed Malaikah, Jiayi Huang, Wesam Bahitham, Omniya Fallatah, Samer Zakri, Chakkiath Paul Antony, Mohammed Alshehri, Raeece Naeem Ghazzali, Fathia Ben-Rached, Abdullah Alsahafi, Asim Alsaedi, Ghadeer AlAhmadi, Mai Kaaki, Meshari Alazmi, Baraa AlhajHussein, Muhammad Yaseen, Hosam M. Zowawi, Majed F. Alghoribi, Abdulhakeem O. Althaqafi, Abdulfattah Al-Amri, Danesh Moradigaravand, Arnab Pain","doi":"10.1186/s13073-024-01332-5","DOIUrl":"https://doi.org/10.1186/s13073-024-01332-5","url":null,"abstract":"Klebsiella pneumoniae is a major bacterial and opportunistic human pathogen, increasingly recognized as a healthcare burden globally. The convergence of resistance and virulence in K. pneumoniae strains has led to the formation of hypervirulent and multidrug-resistant strains with dual risk, limiting treatment options. K. pneumoniae clones are known to emerge locally and spread globally. Therefore, an understanding of the dynamics and evolution of the emerging strains in hospitals is warranted to prevent future outbreaks. In this study, we conducted an in-depth genomic analysis on a large-scale collection of 328 multidrug-resistant (MDR) K. pneumoniae strains recovered from 239 patients from a single major hospital in the western coastal city of Jeddah in Saudi Arabia from 2014 through 2022. We employed a broad range of phylogenetic and phylodynamic methods to understand the evolution of the predominant clones on epidemiological time scales, virulence and resistance determinants, and their dynamics. We also integrated the genomic data with detailed electronic health record (EHR) data for the patients to understand the clinical implications of the resistance and virulence of different strains. We discovered a diverse population underlying the infections, with most strains belonging to Clonal Complex 14 (CC14) exhibiting dominance. Specifically, we observed the emergence and continuous expansion of strains belonging to the dominant ST2096 in the CC14 clade across hospital wards in recent years. These strains acquired resistance mutations against colistin and extended spectrum β-lactamase (ESBL) and carbapenemase genes, namely blaOXA-48 and blaOXA-232, located on three distinct plasmids, on epidemiological time scales. Strains of ST2096 exhibited a high virulence level with the presence of the siderophore aerobactin (iuc) locus situated on the same mosaic plasmid as the ESBL gene. Integration of ST2096 with EHR data confirmed the significant link between colonization by ST2096 and the diagnosis of sepsis and elevated in-hospital mortality (p-value < 0.05). Overall, these results demonstrate the clinical significance of ST2096 clones and illustrate the rapid evolution of an emerging hypervirulent and MDR K. pneumoniae in a clinical setting.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140616916","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"National genomic epidemiology investigation revealed the spread of carbapenem-resistant Escherichia coli in healthy populations and the impact on public health","authors":"Yan Li, Yanyan Zhang, Xinran Sun, Yuchen Wu, Zelin Yan, Xiaoyang Ju, Yonglu Huang, Hongwei Zhou, Zhiqiang Wang, Shaolin Wang, Rong Zhang, Ruichao Li","doi":"10.1186/s13073-024-01310-x","DOIUrl":"https://doi.org/10.1186/s13073-024-01310-x","url":null,"abstract":"Carbapenem-resistant Escherichia coli (CREC) has been considered as WHO priority pathogens, causing a great public health concern globally. While CREC from patients has been thoroughly investigated, the prevalence and underlying risks of CREC in healthy populations have been overlooked. Systematic research on the prevalence of CREC in healthy individuals was conducted here. We aimed to characterize CREC collected from healthy populations in China between 2020 and 2022 and to compare the genomes of CREC isolates isolated from healthy individuals and clinical patients. We present a nationwide investigation of CREC isolates among healthy populations in China, employing robust molecular and genomic analyses. Antimicrobial susceptibility testing, whole-genome sequencing, and bioinformatics were utilized to analyze a cohort of CREC isolates (n = 113) obtained from fecal samples of 5 064 healthy individuals. Representative plasmids were extracted for third-generation nanopore sequencing. We previously collected 113 non-duplicate CREC isolates (59 in 2018, 54 in 2020) collected from ICU patients in 15 provinces and municipalities in China, and these clinical isolates were used to compare with the isolates in this study. Furthermore, we employ comparative genomics approaches to elucidate molecular variations and potential correlations between clinical and non-clinical CREC isolates. A total of 147 CREC isolates were identified from 5 064 samples collected across 11 provinces in China. These isolates were classified into 64 known sequence types (STs), but no dominant STs were observed. In total, seven carbapenemase genes were detected with blaNDM-5 (n = 116) being the most prevalent one. Genetic environments and plasmid backbones of blaNDM were conserved in CREC isolated from healthy individuals. Furthermore, we compared clinical and healthy human-originated CRECs, revealing noteworthy distinctions in 23 resistance genes, including blaNDM-1, blaNDM-5, and blaKPC (χ2 test, p < 0.05). Clinical isolates contained more virulence factors associated with iron uptake, adhesion, and invasion than those obtained from healthy individuals. Notably, CREC isolates generally found healthy people are detected in hospitalized patients. Our findings underscore the significance of healthy populations-derived CRECs as a crucial reservoir of antibiotic resistance genes (ARGs). This highlights the need for ongoing monitoring of CREC isolates in healthy populations to accurately assess the potential risks posed by clinical CREC isolates.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140576226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"PheSeq, a Bayesian deep learning model to enhance and interpret the gene-disease association studies","authors":"Xinzhi Yao, Sizhuo Ouyang, Yulong Lian, Qianqian Peng, Xionghui Zhou, Feier Huang, Xuehai Hu, Feng Shi, Jingbo Xia","doi":"10.1186/s13073-024-01330-7","DOIUrl":"https://doi.org/10.1186/s13073-024-01330-7","url":null,"abstract":"Despite the abundance of genotype-phenotype association studies, the resulting association outcomes often lack robustness and interpretations. To address these challenges, we introduce PheSeq, a Bayesian deep learning model that enhances and interprets association studies through the integration and perception of phenotype descriptions. By implementing the PheSeq model in three case studies on Alzheimer’s disease, breast cancer, and lung cancer, we identify 1024 priority genes for Alzheimer’s disease and 818 and 566 genes for breast cancer and lung cancer, respectively. Benefiting from data fusion, these findings represent moderate positive rates, high recall rates, and interpretation in gene-disease association studies.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575982","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Single cell lineage tracing reveals clonal dynamics of anti-EGFR therapy resistance in triple negative breast cancer","authors":"Simona Pellecchia, Melania Franchini, Gaetano Viscido, Riccardo Arnese, Gennaro Gambardella","doi":"10.1186/s13073-024-01327-2","DOIUrl":"https://doi.org/10.1186/s13073-024-01327-2","url":null,"abstract":"Most primary Triple Negative Breast Cancers (TNBCs) show amplification of the Epidermal Growth Factor Receptor (EGFR) gene, leading to increased protein expression. However, unlike other EGFR-driven cancers, targeting this receptor in TNBC yields inconsistent therapeutic responses. To elucidate the underlying mechanisms of this variability, we employ cellular barcoding and single-cell transcriptomics to reconstruct the subclonal dynamics of EGFR-amplified TNBC cells in response to afatinib, a tyrosine kinase inhibitor (TKI) that irreversibly inhibits EGFR. Integrated lineage tracing analysis revealed a rare pre-existing subpopulation of cells with distinct biological signature, including elevated expression levels of Insulin-Like Growth Factor Binding Protein 2 (IGFBP2). We show that IGFBP2 overexpression is sufficient to render TNBC cells tolerant to afatinib treatment by activating the compensatory insulin-like growth factor I receptor (IGF1-R) signalling pathway. Finally, based on reconstructed mechanisms of resistance, we employ deep learning techniques to predict the afatinib sensitivity of TNBC cells. Our strategy proved effective in reconstructing the complex signalling network driving EGFR-targeted therapy resistance, offering new insights for the development of individualized treatment strategies in TNBC.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140602596","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Burden of Mendelian disorders in a large Middle Eastern biobank","authors":"Waleed Aamer, Aljazi Al-Maraghi, Najeeb Syed, Geethanjali Devadoss Gandhi, Elbay Aliyev, Alya A. Al-Kurbi, Omayma Al-Saei, Muhammad Kohailan, Navaneethakrishnan Krishnamoorthy, Sasirekha Palaniswamy, Khulod Al-Malki, Saleha Abbasi, Nourhen Agrebi, Fatemeh Abbaszadeh, Ammira S. Al-Shabeeb Akil, Ramin Badii, Tawfeg Ben-Omran, Bernice Lo, Younes Mokrab, Khalid A. Fakhro","doi":"10.1186/s13073-024-01307-6","DOIUrl":"https://doi.org/10.1186/s13073-024-01307-6","url":null,"abstract":"Genome sequencing of large biobanks from under-represented ancestries provides a valuable resource for the interrogation of Mendelian disease burden at world population level, complementing small-scale familial studies. Here, we interrogate 6045 whole genomes from Qatar—a Middle Eastern population with high consanguinity and understudied mutational burden—enrolled at the national Biobank and phenotyped for 58 clinically-relevant quantitative traits. We examine a curated set of 2648 Mendelian genes from 20 panels, annotating known and novel pathogenic variants and assessing their penetrance and impact on the measured traits. We find that 62.5% of participants are carriers of at least 1 known pathogenic variant relating to recessive conditions, with homozygosity observed in 1 in 150 subjects (0.6%) for which Peninsular Arabs are particularly enriched versus other ancestries (5.8-fold). On average, 52.3 loss-of-function variants were found per genome, 6.5 of which affect a known Mendelian gene. Several variants annotated in ClinVar/HGMD as pathogenic appeared at intermediate frequencies in this cohort (1–3%), highlighting Arab founder effect, while others have exceedingly high frequencies (> 5%) prompting reconsideration as benign. Furthermore, cumulative gene burden analysis revealed 56 genes having gene carrier frequency > 1/50, including 5 ACMG Tier 3 panel genes which would be candidates for adding to newborn screening in the country. Additionally, leveraging 58 biobank traits, we systematically assess the impact of novel/rare variants on phenotypes and discover 39 candidate large-effect variants associating with extreme quantitative traits. Furthermore, through rare variant burden testing, we discover 13 genes with high mutational load, including 5 with impact on traits relevant to disease conditions, including metabolic disorder and type 2 diabetes, consistent with the high prevalence of these conditions in the region. This study on the first phase of the growing Qatar Genome Program cohort provides a comprehensive resource from a Middle Eastern population to understand the global mutational burden in Mendelian genes and their impact on traits in seemingly healthy individuals in high consanguinity settings.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575879","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Smoking-associated gene expression alterations in nasal epithelium reveal immune impairment linked to lung cancer risk","authors":"Maria Stella de Biase, Florian Massip, Tzu-Ting Wei, Federico M. Giorgi, Rory Stark, Amanda Stone, Amy Gladwell, Martin O’Reilly, Daniel Schütte, Ines de Santiago, Kerstin B. Meyer, Florian Markowetz, Bruce A. J. Ponder, Robert C. Rintoul, Roland F. Schwarz","doi":"10.1186/s13073-024-01317-4","DOIUrl":"https://doi.org/10.1186/s13073-024-01317-4","url":null,"abstract":" Lung cancer is the leading cause of cancer-related death in the world. In contrast to many other cancers, a direct connection to modifiable lifestyle risk in the form of tobacco smoke has long been established. More than 50% of all smoking-related lung cancers occur in former smokers, 40% of which occur more than 15 years after smoking cessation. Despite extensive research, the molecular processes for persistent lung cancer risk remain unclear. We thus set out to examine whether risk stratification in the clinic and in the general population can be improved upon by the addition of genetic data and to explore the mechanisms of the persisting risk in former smokers. We analysed transcriptomic data from accessible airway tissues of 487 subjects, including healthy volunteers and clinic patients of different smoking statuses. We developed a computational model to assess smoking-associated gene expression changes and their reversibility after smoking is stopped, comparing healthy subjects to clinic patients with and without lung cancer. We find persistent smoking-associated immune alterations to be a hallmark of the clinic patients. Integrating previous GWAS data using a transcriptional network approach, we demonstrate that the same immune- and interferon-related pathways are strongly enriched for genes linked to known genetic risk factors, demonstrating a causal relationship between immune alteration and lung cancer risk. Finally, we used accessible airway transcriptomic data to derive a non-invasive lung cancer risk classifier. Our results provide initial evidence for germline-mediated personalized smoke injury response and risk in the general population, with potential implications for managing long-term lung cancer incidence and mortality.","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":null,"pages":null},"PeriodicalIF":12.3,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140575726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}