HGG Advances最新文献

{"title":"Gene-specific pathogenicity predictor for chromatin remodeling BAF complex-associated neurodevelopmental disorders.","authors":"Joshua Hack, Mohammad Nazim","doi":"10.1016/j.xhgg.2026.100583","DOIUrl":"10.1016/j.xhgg.2026.100583","url":null,"abstract":"<p><p>Advancements in whole-genome sequencing have increased the number of variants of uncertain significance (VUS) identified in human genomes. This has created a diagnostic bottleneck for genetic counselors tasked with sifting through these variants and determining those most likely to be causative for a patient's clinical presentation. Machine learning (ML) tools can aid in identifying pathogenic variants from VUS, but there is a need for gene-specific algorithms that predict pathogenic variants with high accuracy. To address this need, we present a workflow for developing gene-specific, ensemble-learning ML tools, that leverage outputs from other algorithms, locations of variants within the gene, and evolutionary conservation data to make a prediction of pathogenicity. Variants in SMARCA2 and SMARCA4 that are associated with rare neurodevelopmental diseases were used to screen 15 ML algorithms. A random forest learner was tuned to yield a final accuracy of 0.93 on holdout data. Generalizing this predictor to other BRG1/BRM-associated factor (BAF) complex proteins resulted in a sharp decline in performance. We trained a final predictor for all genes in the study to create a predictor that identifies pathogenic variants in these BAF subunits with an accuracy of 0.91 on holdout data. This predictor specific to BAF complex proteins performs with higher accuracy and area under the precision-recall curve than any other predictor. The decline in performance when generalized to other proteins emphasizes the need for the gene-specific calibration of predictors. Our workflow for the development of such models provides a quick, computationally inexpensive route for improving the ML tools available to genetic counselors.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100583"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13000492/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147322285","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":"Breaking barriers to completing genetic testing for inherited breast cancer among at-risk Black women using a community-based participatory research approach.","authors":"Sarah H Choi, Sanjana Ramesh, Shanequa Reed, Georgina Menyah, Pamela Ganschow, Vida Henderson, Henry M Dunnenberger","doi":"10.1016/j.xhgg.2026.100591","DOIUrl":"10.1016/j.xhgg.2026.100591","url":null,"abstract":"<p><p>National guidelines from the US Preventive Services Task Force and the National Comprehensive Cancer Network recommend the use of family-health-history (FHH)-based risk assessment tools to guide genetic testing (GT) among women with an increased risk of inherited cancer and inform personalized cancer risk management. Prior research has focused on attitudes toward and decisions about initial uptake of GT in Black patients but little is known about the factors that impact the subsequent completion of GT after they have already provided consent. Using a community-based participatory research (CBPR) approach, we aimed to identify barriers and actionable strategies to improve GT completion offered through the Breast Health Assessment (BHA), an FHH screening tool administered at routine mammography visits. We conducted semi-structured interviews with 12 Black women who screened high-risk for inherited breast cancer and consented to GT through the BHA, but did not complete saliva sample collection. Thematic analysis revealed that lack of dedicated support throughout the BHA workflow emerged as a key obstacle to sample collection, whereas medical mistrust, shame, and limited knowledge were largely regarded as cultural barriers that had no impact on GT completion. Low utilization among participants reflected logistical challenges highlighting the need to evaluate multi-level implementation processes to better understand and address inequities in GT completion. Participants suggested implementing early educational outreach, culturally relevant messaging, and interpersonal touchpoints to promote GT uptake. By applying a CBPR approach, we translated these findings into actionable, equity-focused strategies to improve GT completion within a population genetic screening program.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100591"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13071439/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147475560","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":"Variant selection to maximize variance explained in cis-Mendelian randomization.","authors":"Ang Zhou, Ville Karhunen, Haodong Tian, Janne Pott, Ashish Patel, Eric A W Slob, Stephen Burgess","doi":"10.1016/j.xhgg.2026.100573","DOIUrl":"10.1016/j.xhgg.2026.100573","url":null,"abstract":"<p><p>Optimal selection of instrumental variables (IVs) from a single gene region in cis-Mendelian randomization (MR) is challenging, as variants are highly correlated due to linkage disequilibrium (LD). Using only the lead variant is convenient but may not achieve full statistical power if multiple signals exist. We compared four selection methods that incorporate correlated non-lead variants, including LD-pruning, conditional and joint analysis (COJO), sum of single effects (SuSiE) regression, and principal component analysis (PCA), and evaluated their ability to increase instrument strength, measured by variance explained in the exposure (R²), relative to the lead-variant-only approach. We applied these methods to circulating haptoglobin (HP), to simulated traits with known variance explained, and to 15 additional gene regions where non-lead cis-protein quantitative trait loci (pQTLs) contributed varying proportions of cis-genetic variance. R² was estimated from variant-protein association estimates (Fenland study, n = 10,708) using LD from the UK Biobank (n = 356,557). In the HP region, the four methods produced a median proportional gain in R² of 145.1% compared with the lead variant alone (range: 69.6%-169.4%), with a median reduction in the MR standard error of 36.3% (range: -37.9% to -19.3%). In simulations, all methods were able to recover the expected genetic variance. Across the 15 gene regions, methods incorporating non-lead variants consistently outperformed the lead-variant-only approach. Variant selection methods incorporating correlated non-lead variants can reliably improve instrument strength in cis-MR analyses. We recommend using such methods but advise comparing their estimates with the lead-variant-only estimate to safeguard against numerical instability.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100573"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12887808/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145994600","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":"Evaluating genetic ancestry inference from single-cell transcriptomic datasets.","authors":"Jianing Yao, Steven Gazal","doi":"10.1016/j.xhgg.2026.100564","DOIUrl":"10.1016/j.xhgg.2026.100564","url":null,"abstract":"<p><p>Characterizing the ancestry of donors in single-cell transcriptomic studies is crucial to ensure genetic homogeneity, reduce biases in analyses, identify ancestry-specific regulatory mechanisms and their downstream roles in disease, and ensure that existing datasets are representative of human genetic diversity. While these datasets are now widely available, information on the ancestry of donors is often missing, hindering further analysis. Here, we propose a framework to evaluate methods for inferring genetic ancestry from genetic polymorphisms detected in single-cell sequencing reads. We demonstrate that widely used tools (e.g., ADMIXTURE) provide accurate inference of genetic ancestry and admixture proportions, despite the limited number of genetic polymorphisms identified and imperfect variant calling from sequencing reads. We infer genetic ancestry for 401 donors from 10 Human Cell Atlas datasets and report a high proportion of donors of European ancestry in this resource. For researchers generating single-cell transcriptomic datasets, we recommend reporting genetic ancestry inference for all donors and generating datasets that represent diverse ancestries.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100564"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12860357/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145935601","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":"Germline HLA heterozygosity is associated with decreased lung cancer risk.","authors":"Taotao Tan, Vikram R Shaw, Jinyoung Byun, Hyun-Sung Lee, Younghun Han, Yafang Li, Rayjean J Hung, David C Christiani, Xin-An Wang, Mattias Johansson, Xiangjun Xiao, David Zaridze, Stig Egil Bojesen, Sanjay Shete, Demetrios Albanes, Melinda C Aldrich, Adonina Tardon, Guillermo Fernandez-Tardon, Loïc Le Marchand, Gad Rennert, Heike Bickeböller, H-Erich Wichmann, Angela Risch, John K Field, Michael Davies, Penella Woll, Lambertus A Kiemeney, Aage Haugen, Shanbeh Zienolddiny, Stephen Lam, Mikael Johansson, Kjell Grankvist, Matthew B Schabath, Angeline Andrew, Philip Lazarus, Susanne M Arnold, Dakai Zhu, Maria Teresa Landi, James McKay, Christopher Amos, Chao Cheng","doi":"10.1016/j.xhgg.2026.100567","DOIUrl":"10.1016/j.xhgg.2026.100567","url":null,"abstract":"<p><p>Heterozygosity at human leukocyte antigen (HLA) loci may improve lung cancer immunosurveillance by increasing recognition of the tumor by the immune system. Previous studies utilizing data from population-level biobanks, such as the United Kingdom Biobank and FinnGen, have identified an association between germline HLA class II (HLA-II) heterozygosity and reduced lung cancer risk in smokers. In the present study, we evaluate the association between HLA heterozygosity and lung cancer in a large case-control study (15,302 cases and 14,580 controls) with imputed HLA allele-type information, comparing differences in HLA heterozygosity between smokers and non-smokers, among lung cancer subtypes, and at 2- and 4-digit HLA allele resolution. We identify a strong protective association of HLA-II heterozygosity in smokers compared to non-smokers, particularly at the HLA-DPB1 and HLA-DPA1 loci, and provide subtype-specific resolution. Finally, analysis of the additive effects of HLA allele heterozygosity in smokers identified significant associations with several 4-digit HLA alleles, including HLA-B∗08:01, HLA-A∗01:01, HLA-C∗07:01, HLA-DQA1∗05:01, HLA-DRB1∗03:01, and HLA-C∗03:04. Our study provides additional evidence, with added histologic subtype information, that germline HLA-II heterozygosity is inversely associated with lung cancer risk.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100567"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12860938/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145967049","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":"Recessive AARS1 variants perturb human and mouse development.","authors":"Jennifer L Watts, Nicole Costantino, Ammar Husami, Thamara Dayarathna, Logan Willeke, Loren D M Peña, Elizabeth Seiwert, Donald L Gilbert, Rolf W Stottmann","doi":"10.1016/j.xhgg.2026.100565","DOIUrl":"10.1016/j.xhgg.2026.100565","url":null,"abstract":"<p><p>Humans with pathogenic loss of function alanyl-tRNA synthetase 1 (AARS1) variants have a range of congenital brain phenotypes, including a high prevalence of microcephaly. The molecular mechanisms for this are unclear but zebrafish mutants in aars1 have reduced neurogenesis and increased apoptosis. Here, we report two individuals with compound heterozygous AARS1 variants. We created two mouse models to study the role of Aars1 in embryonic brain development. We provide evidence from these mouse models and in vitro splicing assays that both human AARS1 alleles are pathogenic. Mice homozygous for either a missense allele or an indel allele are both lethal very early in embryonic development. Aars1^G80S/WT heterozygous animals show reduced Purkinje cell immunoreactivity at 8 months of age but no gross morphological cerebellar phenotypes or impaired performance in a motor coordination assay. We conclude these are pathogenic alleles in AARS1 but lethality in mice preclude a detailed study of neural development.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100565"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12859473/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145935607","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":"Bi-allelic RNU6ATAC variants cause a minor spliceopathy characterized by transcriptome-wide minor intron retention and multisystem manifestations.","authors":"Rodrigo Mendez, Taylor M Arriaga, Jialan Ma, Devon E Bonner, Sara Emami, Rebecca J Levy, Afaf Alsagheir, Bader Alhaddad, Khadijah Bakur, Rachel A Ungar, Dena R Matalon, Alexander M Miller, Jonathan Nguyen, Kevin S Smith, Stuart A Scott, Linda Liao, Zena Ng, Shruti Marwaha, Alistair Ward, Danica Novacic, Fowzan S Alkuraya, Jonathan A Bernstein, Vijay S Ganesh, Anne O'Donnell-Luria, Stephen B Montgomery, Matthew T Wheeler","doi":"10.1016/j.xhgg.2026.100588","DOIUrl":"10.1016/j.xhgg.2026.100588","url":null,"abstract":"<p><p>We report three individuals with bi-allelic variants in RNU6ATAC, which encodes the U6atac minor spliceosomal small nuclear RNA (snRNA), causing a multisystem minor spliceopathy. Through RNA sequencing analysis, we identified a distinctive excess of minor intron retention (MIR) in two unrelated individuals, which guided the identification of bi-allelic RNU6ATAC variants. The discovery cohort presented with variable multisystem manifestations. One individual presented with refractory epilepsy, microcephaly, developmental delay, ataxia, bilateral toe syndactyly, hypereosinophilia, and short stature, whereas the other exhibited failure to thrive, short stature, primary hypothyroidism, combined variable immunodeficiency, eosinophilic colitis, ichthyosis vulgaris, scoliosis, and chronic inflammatory demyelinating polyneuropathy without neurodevelopmental involvement. Despite organ-specific variation, both individuals displayed impaired growth and eosinophil-driven inflammation. Recently, we identified a third affected individual from an independent cohort whose phenotype bridges these features, combining microcephaly, growth failure with severe immunodeficiency, and skeletal abnormalities. The distinctive excess of MIR outliers in the discovery cohort supports minor spliceosome dysfunction, mirroring the molecular signature of RNU4ATAC-opathy. These findings nominate RNU6ATAC as a disease-associated gene, defining an expanded clinical spectrum of minor spliceopathies. Our study supports the power of integrating genomic and transcriptomic approaches for diagnosing splicing disorders and highlights the critical role of spliceosomal snRNAs in human disease.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100588"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13049632/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147436239","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":"Accurate and scalable genome-wide ancestry estimation using haplotype clusters.","authors":"Jonas Meisner","doi":"10.1016/j.xhgg.2026.100561","DOIUrl":"10.1016/j.xhgg.2026.100561","url":null,"abstract":"<p><p>Unsupervised genome-wide ancestry estimation in unrelated individuals has been a staple in population and medical genetics for decades, and its importance continues to grow with the increasing number of large genetic cohorts of mixed ancestries. We propose an extension to the hapla framework that scales model-based ancestry estimation to unprecedented sample sizes by leveraging inferred haplotype clusters from phased genotype data. Our haplotype cluster-based approach is approximately 5× and 20× faster than the fastest model-free and model-based SNP-based approaches, respectively, for unsupervised genome-wide ancestry estimation on the harmonized Human Genome Diversity Project and 1000 Genomes Project dataset. Furthermore, we demonstrate that it is the most accurate method to date in an extensive simulation study, across a range of sample sizes from thousands to hundreds of thousands of individuals. Our accurate ancestry estimates can help reduce health disparities and accelerate precision medicine efforts in the growing number of biobanks globally.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100561"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12859494/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145946042","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":"Sex-stratified genetic regulators of cytokine production in the Dutch and Tanzanian populations.","authors":"Caroline Amour, Raul Cetatean, Isis Ricano Ponce, Nick Keur, Godfrey S Temba, Vesla I Kullaya, Blandina T Mmbaga, Reginald Kavishe, Leo A B Joosten, Mihai G Netea, Quirijn de Mast, Collins K Boahen, Vinod Kumar","doi":"10.1016/j.xhgg.2026.100593","DOIUrl":"10.1016/j.xhgg.2026.100593","url":null,"abstract":"<p><p>Differences in immune responses are observed between males and females, influenced by genetic, hormonal, and environmental factors. The sex-specific genetic effects on cytokine production, however, remain underexplored. This study aimed to identify sex-specific quantitative trait loci (QTLs) affecting cytokine production in response to diverse infectious antigens. We performed sex-stratified cytokine QTL (cQTLs) mapping in two population-based cohorts from Tanzania and the Netherlands. In the Tanzanian cohort, 12 genome-wide significant cytokine QTLs were identified, with 7 observed in males and 5 in females. In the Dutch cohort, 12 genome-wide significant cQTLs were identified, with 6 cQTLs each in males and females. Colocalization analysis confirmed that all 12 genome-wide cQTLs from the Tanzanian cohort are sex specific, while in the Dutch cohort 10 genome-wide cQTL variants are modulated in a sex-specific manner. Furthermore, pathway and phenotype enrichment analyses linked the identified cQTL variants to relevant immune functions and sex-biased traits. Our study highlights the importance of sex-stratified genetic analyses when investigating the genetic basis of cytokine production in humans. We show that sex-specific cQTLs may underlie observed phenotypic differences between males and females and that accounting for such effects can inform the development of personalized medical treatments for sex-biased diseases.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100593"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13071459/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147487252","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":"A reference panel for linkage disequilibrium and genotype imputation using whole-genome sequencing data from 2,680 participants across India.","authors":"Zheng Li, Wei Zhao, Xiang Zhou, Yuk Yee Leung, Gerard D Schellenberg, Li-San Wang, Sebastian Schönherr, Lukas Forer, Christian Fuchsberger, Sharmistha Dey, Jinkook Lee, Jennifer A Smith, Aparajit B Dey, Sharon L R Kardia","doi":"10.1016/j.xhgg.2026.100579","DOIUrl":"10.1016/j.xhgg.2026.100579","url":null,"abstract":"<p><p>India is the most populous country globally, yet genetic studies involving Indian individuals remain limited. The Indian population is composed of many founder groups and has a mixed genetic ancestry, including an ancestral component not observed anywhere outside of India. This presents a unique opportunity to uncover novel disease variants and develop tailored medical interventions. To facilitate genetic research in India, a crucial first step is to create a foundational resource that serves as a benchmark for future population studies and methods development. Thus, we constructed the largest and most nationally representative linkage disequilibrium (LD) and genotype imputation reference panels in India to date, using high-coverage whole-genome sequencing data of 2,680 participants from the Longitudinal Aging Study in India-Harmonized Diagnostic Assessment of Dementia (LASI-DAD). As an LD reference panel, LASI-DAD includes 69.5 million variants, representing 170% and 213% increases relative to the 1000 Genomes Project and TOP-LD South Asian panels, respectively. Besides serving as an LD lookup panel, LASI-DAD facilitates various statistical analyses relying on precise LD estimates. In polygenic risk score (PRS) analyses, LASI-DAD improved the PRS predictive performance by 2.1%-35.1% across traits and studies. As an imputation reference panel, LASI-DAD enhanced imputation accuracy, measured by the Pearson correlation between imputed and true genotypes, by 3%-101% (mean 38%) compared with the TOPMed panel and by 3%-73% (mean 27%) compared with the Genome Asia Pilot panel across different allele frequencies. The LASI-DAD reference panel is publicly available to benefit future studies.</p>","PeriodicalId":34530,"journal":{"name":"HGG Advances","volume":" ","pages":"100579"},"PeriodicalIF":3.1,"publicationDate":"2026-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12945573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146143881","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}