HGG Advances最新文献

{"title":"A parametric bootstrap approach for computing confidence intervals for genetic correlations with application to genetically determined protein-protein networks.","authors":"Yi-Ting Tsai, Yana Hrytsenko, Michael Elgart, Usman A Tahir, Zsu-Zsu Chen, James G Wilson, Robert E Gerszten, Tamar Sofer","doi":"10.1016/j.xhgg.2024.100304","DOIUrl":"10.1016/j.xhgg.2024.100304","url":null,"abstract":"<p><p>Genetic correlation refers to the correlation between genetic determinants of a pair of traits. When using individual-level data, it is typically estimated based on a bivariate model specification where the correlation between the two variables is identifiable and can be estimated from a covariance model that incorporates the genetic relationship between individuals, e.g., using a pre-specified kinship matrix. Inference relying on asymptotic normality of the genetic correlation parameter estimates may be inaccurate when the sample size is low, when the genetic correlation is close to the boundary of the parameter space, and when the heritability of at least one of the traits is low. We address this problem by developing a parametric bootstrap procedure to construct confidence intervals for genetic correlation estimates. The procedure simulates paired traits under a range of heritability and genetic correlation parameters, and it uses the population structure encapsulated by the kinship matrix. Heritabilities and genetic correlations are estimated using the close-form, method of moment, Haseman-Elston regression estimators. The proposed parametric bootstrap procedure is especially useful when genetic correlations are computed on pairs of thousands of traits measured on the same exact set of individuals. We demonstrate the parametric bootstrap approach on a proteomics dataset from the Jackson Heart Study.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11140211/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140891839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DNA methylation analysis in patients with neurodevelopmental disorders improves variant interpretation and reveals complexity.","authors":"Slavica Trajkova, Jennifer Kerkhof, Matteo Rossi Sebastiano, Lisa Pavinato, Enza Ferrero, Chiara Giovenino, Diana Carli, Eleonora Di Gregorio, Roberta Marinoni, Giorgia Mandrile, Flavia Palermo, Silvia Carestiato, Simona Cardaropoli, Verdiana Pullano, Antonina Rinninella, Elisa Giorgio, Tommaso Pippucci, Paola Dimartino, Jessica Rzasa, Kathleen Rooney, Haley McConkey, Aleksandar Petlichkovski, Barbara Pasini, Elena Sukarova-Angelovska, Christopher M Campbell, Kay Metcalfe, Sarah Jenkinson, Siddharth Banka, Alessandro Mussa, Giovanni Battista Ferrero, Bekim Sadikovic, Alfredo Brusco","doi":"10.1016/j.xhgg.2024.100309","DOIUrl":"10.1016/j.xhgg.2024.100309","url":null,"abstract":"<p><p>Analysis of genomic DNA methylation by generating epigenetic signature profiles (episignatures) is increasingly being implemented in genetic diagnosis. Here we report our experience using episignature analysis to resolve both uncomplicated and complex cases of neurodevelopmental disorders (NDDs). We analyzed 97 NDDs divided into (1) a validation cohort of 59 patients with likely pathogenic/pathogenic variants characterized by a known episignature and (2) a test cohort of 38 patients harboring variants of unknown significance or unidentified variants. The expected episignature was obtained in most cases with likely pathogenic/pathogenic variants (53/59 [90%]), a revealing exception being the overlapping profile of two SMARCB1 pathogenic variants with ARID1A/B:c.6200, confirmed by the overlapping clinical features. In the test cohort, five cases showed the expected episignature, including (1) novel pathogenic variants in ARID1B and BRWD3; (2) a deletion in ATRX causing MRXFH1 X-linked mental retardation; and (3) confirmed the clinical diagnosis of Cornelia de Lange (CdL) syndrome in mutation-negative CdL patients. Episignatures analysis of the in BAF complex components revealed novel functional protein interactions and common episignatures affecting homologous residues in highly conserved paralogous proteins (SMARCA2 M856V and SMARCA4 M866V). Finally, we also found sex-dependent episignatures in X-linked disorders. Implementation of episignature profiling is still in its early days, but with increasing utilization comes increasing awareness of the capacity of this methodology to help resolve the complex challenges of genetic diagnoses.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11216013/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140946204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distinct positions of genetic and oral histories: Perspectives from India.","authors":"Arjun Biddanda, Esha Bandyopadhyay, Constanza de la Fuente Castro, David Witonsky, Jose A Urban Aragon, Nagarjuna Pasupuleti, Hannah M Moots, Renée Fonseca, Suzanne Freilich, Jovan Stanisavic, Tabitha Willis, Anoushka Menon, Mohammed S Mustak, Chinnappa Dilip Kodira, Anjaparavanda P Naren, Mithun Sikdar, Niraj Rai, Maanasa Raghavan","doi":"10.1016/j.xhgg.2024.100305","DOIUrl":"10.1016/j.xhgg.2024.100305","url":null,"abstract":"<p><p>Over the past decade, genomic data have contributed to several insights on global human population histories. These studies have been met both with interest and critically, particularly by populations with oral histories that are records of their past and often reference their origins. While several studies have reported concordance between oral and genetic histories, there is potential for tension that may stem from genetic histories being prioritized or used to confirm community-based knowledge and ethnography, especially if they differ. To investigate the interplay between oral and genetic histories, we focused on the southwestern region of India and analyzed whole-genome sequence data from 156 individuals identifying as Bunt, Kodava, Nair, and Kapla. We supplemented limited anthropological records on these populations with oral history accounts from community members and historical literature, focusing on references to non-local origins such as the ancient Scythians in the case of Bunt, Kodava, and Nair, members of Alexander the Great's army for the Kodava, and an African-related source for Kapla. We found these populations to be genetically most similar to other Indian populations, with the Kapla more similar to South Indian tribal populations that maximize a genetic ancestry related to Ancient Ancestral South Indians. We did not find evidence of additional genetic sources in the study populations than those known to have contributed to many other present-day South Asian populations. Our results demonstrate that oral and genetic histories may not always provide consistent accounts of population origins and motivate further community-engaged, multi-disciplinary investigations of non-local origin stories in these communities.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11153255/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140891880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Whole-genome sequences reveal zygotic composition in chimeric twins.","authors":"Christopher J Yoon, Chang Hyun Nam, Taewoo Kim, Jeong Seok Lee, Ryul Kim, Kijong Yi, June-Young Koh, Jiye Kim, Hyein Won, Ji Won Oh, Obi L Griffith, Malachi Griffith, Joohon Sung, Tae Yeul Kim, Duck Cho, Ji Seon Choi, Young Seok Ju","doi":"10.1016/j.xhgg.2024.100301","DOIUrl":"10.1016/j.xhgg.2024.100301","url":null,"abstract":"<p><p>While most dizygotic twins have a dichorionic placenta, rare cases of dizygotic twins with a monochorionic placenta have been reported. The monochorionic placenta in dizygotic twins allows in utero exchange of embryonic cells, resulting in chimerism in the twins. In practice, this chimerism is incidentally identified in mixed ABO blood types or in the presence of cells with a discordant sex chromosome. Here, we applied whole-genome sequencing to one triplet and one twin family to precisely understand their zygotic compositions, using millions of genomic variants as barcodes of zygotic origins. Peripheral blood showed asymmetrical contributions from two sister zygotes, where one of the zygotes was the major clone in both twins. Single-cell RNA sequencing of peripheral blood tissues further showed differential contributions from the two sister zygotes across blood cell types. In contrast, buccal tissues were pure in genetic composition, suggesting that in utero cellular exchanges were confined to the blood tissues. Our study illustrates the cellular history of twinning during human development, which is critical for managing the health of chimeric individuals in the era of genomic medicine.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11201346/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141076827","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identifying dysregulated regions in amyotrophic lateral sclerosis through chromatin accessibility outliers.","authors":"Muhammed Hasan Çelik, Julien Gagneur, Ryan G Lim, Jie Wu, Leslie M Thompson, Xiaohui Xie","doi":"10.1016/j.xhgg.2024.100318","DOIUrl":"10.1016/j.xhgg.2024.100318","url":null,"abstract":"<p><p>The high heritability of amyotrophic lateral sclerosis (ALS) contrasts with its low molecular diagnosis rate post-genetic testing, pointing to potential undiscovered genetic factors. To aid the exploration of these factors, we introduced EpiOut, an algorithm to identify chromatin accessibility outliers that are regions exhibiting divergent accessibility from the population baseline in a single or few samples. Annotation of accessible regions with histone chromatin immunoprecipitation sequencing and Hi-C indicates that outliers are concentrated in functional loci, especially among promoters interacting with active enhancers. Across different omics levels, outliers are robustly replicated, and chromatin accessibility outliers are reliable predictors of gene expression outliers and aberrant protein levels. When promoter accessibility does not align with gene expression, our results indicate that molecular aberrations are more likely to be linked to post-transcriptional regulation rather than transcriptional regulation. Our findings demonstrate that the outlier detection paradigm can uncover dysregulated regions in rare diseases. EpiOut is available at github.com/uci-cbcl/EpiOut.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11260578/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141318511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generalizability of PGS₃₁₃ for breast cancer risk in a Los Angeles biobank.","authors":"Helen Shang, Yi Ding, Vidhya Venkateswaran, Kristin Boulier, Nikhita Kathuria-Prakash, Parisa Boodaghi Malidarreh, Jacob M Luber, Bogdan Pasaniuc","doi":"10.1016/j.xhgg.2024.100302","DOIUrl":"10.1016/j.xhgg.2024.100302","url":null,"abstract":"<p><p>Polygenic scores (PGSs) summarize the combined effect of common risk variants and are associated with breast cancer risk in patients without identifiable monogenic risk factors. One of the most well-validated PGSs in breast cancer to date is PGS₃₁₃, which was developed from a Northern European biobank but has shown attenuated performance in non-European ancestries. We further investigate the generalizability of the PGS₃₁₃ for American women of European (EA), African (AFR), Asian (EAA), and Latinx (HL) ancestry within one institution with a singular electronic health record (EHR) system, genotyping platform, and quality control process. We found that the PGS₃₁₃ achieved overlapping areas under the receiver operator characteristic (ROC) curve (AUCs) in females of HL (AUC = 0.68, 95% confidence interval [CI] = 0.65-0.71) and EA ancestry (AUC = 0.70, 95% CI = 0.69-0.71) but lower AUCs for the AFR and EAA populations (AFR: AUC = 0.61, 95% CI = 0.56-0.65; EAA: AUC = 0.64, 95% CI = 0.60-0.680). While PGS₃₁₃ is associated with hormone-receptor-positive (HR+) disease in EA Americans (odds ratio [OR] = 1.42, 95% CI = 1.16-1.64), this association is lost in African, Latinx, and Asian Americans. In summary, we found that PGS₃₁₃ was significantly associated with breast cancer but with attenuated accuracy in women of AFR and EAA descent within a singular health system in Los Angeles. Our work further highlights the need for additional validation in diverse cohorts prior to the clinical implementation of PGSs.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11137525/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140867594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Transcriptome-wide association analysis identifies candidate susceptibility genes for prostate-specific antigen levels in men without prostate cancer.","authors":"Dorothy M Chen, Ruocheng Dong, Linda Kachuri, Thomas J Hoffmann, Yu Jiang, Sonja I Berndt, John P Shelley, Kerry R Schaffer, Mitchell J Machiela, Neal D Freedman, Wen-Yi Huang, Shengchao A Li, Hans Lilja, Amy C Justice, Ravi K Madduri, Alex A Rodriguez, Stephen K Van Den Eeden, Stephen J Chanock, Christopher A Haiman, David V Conti, Robert J Klein, Jonathan D Mosley, John S Witte, Rebecca E Graff","doi":"10.1016/j.xhgg.2024.100315","DOIUrl":"10.1016/j.xhgg.2024.100315","url":null,"abstract":"<p><p>Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility for prostate cancer (PCa) screening. Using genome-wide association study (GWAS) summary statistics from 95,768 PCa-free men, we conducted a transcriptome-wide association study (TWAS) to examine impacts of genetically predicted gene expression on PSA. Analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10 × 10^-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61 × 10^-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses identified 155 statistically significantly (p < 0.05/22,249 = 2.25 × 10^-6) genes. Out of 173 unique PSA-associated genes across analyses, we replicated 151 (87.3%) in a TWAS of 209,318 PCa-free individuals from the Million Veteran Program. Based on conditional analyses, we found 20 genes (11 single tissue, nine cross-tissue) that were associated with PSA levels in the discovery TWAS that were not attributable to a lead variant from a GWAS. Ten of these 20 genes replicated, and two of the replicated genes had colocalization probability of >0.5: CCNA2 and HIST1H2BN. Six of the 20 identified genes are not known to impact PCa risk. Fine-mapping based on whole blood and prostate tissue revealed five protein-coding genes with evidence of causal relationships with PSA levels. Of these five genes, four exhibited evidence of colocalization and one was conditionally independent of previous GWAS findings. These results yield hypotheses that should be further explored to improve understanding of genetic factors underlying PSA levels.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11262184/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141284896","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DeepFace: Deep-learning-based framework to contextualize orofacial-cleft-related variants during human embryonic craniofacial development.","authors":"Yulin Dai, Toshiyuki Itai, Guangsheng Pei, Fangfang Yan, Yan Chu, Xiaoqian Jiang, Seth M Weinberg, Nandita Mukhopadhyay, Mary L Marazita, Lukas M Simon, Peilin Jia, Zhongming Zhao","doi":"10.1016/j.xhgg.2024.100322","DOIUrl":"10.1016/j.xhgg.2024.100322","url":null,"abstract":"","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11262157/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141471226","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of novel driver risk genes in CNV loci associated with neurodevelopmental disorders.","authors":"Sara Azidane, Xavier Gallego, Lynn Durham, Mario Cáceres, Emre Guney, Laura Pérez-Cano","doi":"10.1016/j.xhgg.2024.100316","DOIUrl":"10.1016/j.xhgg.2024.100316","url":null,"abstract":"<p><p>Copy-number variants (CNVs) are genome-wide structural variations involving the duplication or deletion of large nucleotide sequences. While these types of variations can be commonly found in humans, large and rare CNVs are known to contribute to the development of various neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD). Nevertheless, given that these NDD-risk CNVs cover broad regions of the genome, it is particularly challenging to pinpoint the critical gene(s) responsible for the manifestation of the phenotype. In this study, we performed a meta-analysis of CNV data from 11,614 affected individuals with NDDs and 4,031 control individuals from SFARI database to identify 41 NDD-risk CNV loci, including 24 novel regions. We also found evidence for dosage-sensitive genes within these regions being significantly enriched for known NDD-risk genes and pathways. In addition, a significant proportion of these genes was found to (1) converge in protein-protein interaction networks, (2) be among most expressed genes in the brain across all developmental stages, and (3) be hit by deletions that are significantly over-transmitted to individuals with ASD within multiplex ASD families from the iHART cohort. Finally, we conducted a burden analysis using 4,281 NDD cases from Decipher and iHART cohorts, and 2,504 neurotypical control individuals from 1000 Genomes and iHART, which resulted in the validation of the association of 162 dosage-sensitive genes driving risk for NDDs, including 22 novel NDD-risk genes. Importantly, most NDD-risk CNV loci entail multiple NDD-risk genes in agreement with a polygenic model associated with the majority of NDD cases.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11264174/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141288712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic yield after next-generation sequencing in pediatric cardiovascular disease.","authors":"Anne M Slavotinek, Michelle L Thompson, Lisa J Martin, Bruce D Gelb","doi":"10.1016/j.xhgg.2024.100286","DOIUrl":"10.1016/j.xhgg.2024.100286","url":null,"abstract":"<p><p>Genetic testing with exome sequencing and genome sequencing is increasingly offered to infants and children with cardiovascular diseases. However, the rates of positive diagnoses after genetic testing within the different categories of cardiac disease and phenotypic subtypes of congenital heart disease (CHD) have been little studied. We report the diagnostic yield after next-generation sequencing in 500 patients with CHD from diverse population subgroups that were enrolled at three different sites in the Clinical Sequencing Evidence-Generating Research consortium. Patients were ascertained due to a primary cardiovascular issue comprising arrhythmia, cardiomyopathy, and/or CHD, and corresponding human phenotype ontology terms were selected to describe the cardiac and extracardiac findings. We examined the diagnostic yield for patients with arrhythmia, cardiomyopathy, and/or CHD and phenotypic subtypes of CHD comprising conotruncal defects, heterotaxy, left ventricular outflow tract obstruction, septal defects, and \"other\" heart defects. We found a significant increase in the frequency of positive findings for patients who underwent genome sequencing compared to exome sequencing and for syndromic cardiac defects compared to isolated cardiac defects. We also found significantly higher diagnostic rates for patients who presented with isolated cardiomyopathy compared to isolated CHD. For patients with syndromic presentations who underwent genome sequencing, there were significant differences in the numbers of positive diagnoses for phenotypic subcategories of CHD, ranging from 31.7% for septal defects to 60% for \"other\". Despite variation in the diagnostic yield at each site, our results support genetic testing in pediatric patients with syndromic and isolated cardiovascular issues and in all subtypes of CHD.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":null,"pages":null},"PeriodicalIF":3.3,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11024993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140194673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}