bioRxiv : the preprint server for biology最新文献

{"title":"Ambient Pollution Components and Sources Associated with Hippocampal Architecture and Memory in Pre-Adolescents.","authors":"Michael A Rosario, Kirthana Sukumaran, Katherine L Bottenhorn, Alethea de Jesus, Carlos Cadenas-Iniguez, Hedyeh Ahmadi, Rima Habre, Shermaine Abad, Jacob G Pine, Deanna M Barch, Joel Schwartz, Daniel A Hackman, Jiu-Chan Chen, Megan M Herting","doi":"10.1101/2025.06.05.658105","DOIUrl":"10.1101/2025.06.05.658105","url":null,"abstract":"<p><strong>Background: </strong>Ambient air pollution poses significant risks to brain health. Hippocampal structure and function are particularly vulnerable, yet the extent to which they are associated with air pollution in children remains unclear. We therefore conducted multi-pollutant mixture analyses to examine how air pollution influences hippocampal architecture and memory performance in late childhood.</p><p><strong>Methods: </strong>We used partial least squares correlation to explore cross-sectional associations between fifteen PM_2.5 components, six PM_2.5 source factors, NO₂, and ozone exposures, and measures of hippocampal microstructure and volume in children aged 9-11 years (n = 7,940) We adjusted for demographic, socioeconomic, and neuroimaging confounds. We also tested whether air pollutants were associated with hippocampal-dependent list-learning memory performance to examine functional implications of air pollution exposure. Shared variance refers to the proportion of total covariance between variable sets captured by each latent dimension in the multivariate relationship.</p><p><strong>Findings: </strong>In the first latent dimension, greater exposure to organic carbon and ozone was associated with differential hippocampal diffusion (72% of shared variance), whereas the second latent dimension linked elemental carbon and iron to hippocampal diffusion (24% of shared variance). Source-based analyses identified biomass burning and traffic pollution as key contributors (61% and 32% variance, respectively). Volumetric analyses revealed higher copper and zinc exposure correlated with smaller hippocampal subregion volumes (left head, right body, tail; 77% variance), whereas lower nickel levels correlated with smaller right head volume (12% variance). Higher industrial and traffic pollutants were also associated with smaller hippocampal volumes (75% variance). We found two latent dimensions (67% and 23% variance, respectively) showing poorer learning, immediate recall, and mnemonic interference performance linked to higher calcium, elemental carbon, and zinc, and organic carbon, alongside lower copper exposure. Finally, hippocampal diffusion (higher free water/lower hindered extracellular diffusion; 83% variance) and smaller tail volumes (96% variance) were linked to poorer RAVLT recall.</p><p><strong>Interpretation: </strong>These results underscore the complex relationship between air pollution exposure and hippocampal architecture and cautions that such structural changes may either presage or reflect subtle differences in neurocomputational mechanisms associated with learning and memory performance in children.</p><p><strong>Funding: </strong>U.S. National Institute of Environmental Health Sciences.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157601/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277394","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":"PLIERv2: bigger, better and faster.","authors":"Marc Subirana-Granés, Sutanu Nandi, Haoyu Zhang, Maria Chikina, Milton Pividori","doi":"10.1101/2025.06.05.658122","DOIUrl":"10.1101/2025.06.05.658122","url":null,"abstract":"<p><p>Gene expression analysis has long been fundamental for elucidating molecular pathways and gene-disease relationships, but traditional single-gene approaches cannot capture the coordinated regulatory networks underlying complex phenotypes; although unsupervised matrix factorization methods (e.g., PCA, NMF) reveal coexpression patterns, they lack the ability to incorporate prior biological knowledge and often struggle with interpretability and technical noise correction. Semi-supervised strategies such as PLIER have improved interpretability by integrating pathway annotations during latent variable extraction, yet the original PLIER implementation is prohibitively slow and memory-intensive, making it impractical for modern large-scale resources like ARCHS4 or recount3. Here, we introduce PLIERv2, which overcomes these constraints through a two-phase algorithmic design (an unsupervised \"PLIERbase\" initialization followed by a \"PLIERfull\" regression that incorporates priors via glmnet), rigorous internal cross-validation to tune regularization parameters for each latent variable, and efficient on-disk data handling using memory-mapped matrices from the bigstatsr package. Benchmarking on GTEx, recount2, and ARCHS4 demonstrates that PLIERv2 achieves 7×-41× speedups over PLIERv1, succeeds in modeling hundreds of thousands of samples that PLIERv1 cannot handle, and maintains or improves biological specificity of latent variables as shown by tissue-alignment and pathway enrichment analyses. By filling the gap in scalable, biologically informed latent variable extraction, PLIERv2 enables comprehensive analysis of modern transcriptomic compendia and paves the way for deeper insights into gene regulatory networks and downstream applications in translational genomics.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157376/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277786","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":"Robust self-supervised machine learning for single cell embeddings and annotations.","authors":"Christine Yiwen Yeh, Min Woo Sun, Dixian Zhu, Livnat Jerby","doi":"10.1101/2025.06.05.658097","DOIUrl":"10.1101/2025.06.05.658097","url":null,"abstract":"<p><p>Dimensionality reduction and clustering are critical steps in single-cell and spatial genomics studies. Here, we show that existing dimensionality reduction and clustering methods suffer from: (1) overfitting to the dominant patterns while missing unique ones, which impairs the detection and annotation of rare cell types and states, and (2) fitting to technical noise over biological signal. To address this, we developed DR-GEM, a self-supervised meta-algorithm that combines principles in distributionally robust optimization with balanced consensus machine learning. DR-GEM supervises itself by (1) using the reconstruction error to identify and reorient its attention to samples/cells that are otherwise poorly embedded, and (2) using balanced consensus learning as a mechanism to increase robustness and mitigate the impact of low-quality samples/cells. Applied to synthetic and real-world single cell 'omics data, single cell resolution spatial transcriptomics, and Perturb-seq datasets, DR-GEM markedly and consistently outperforms existing methods in obtaining reliable embeddings, recovering rare cell types, filtering noise, and uncovering the underlying biology. In summary, this study surfaces and addresses a gap in single cell genomics and brings self-supervision to the realm of dimensionality reduction and clustering to better support data-driven discoveries.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157554/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277818","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":"Allele Specific Expression Quality Control Fills Critical Gap in Transcriptome Assisted Rare Variant Interpretation.","authors":"Kaushik Ram Ganapathy, Eric Song, Daniel Munro, Ali Torkamani, Pejman Mohammadi","doi":"10.1101/2025.05.30.657086","DOIUrl":"10.1101/2025.05.30.657086","url":null,"abstract":"<p><p>Allele-specific expression (ASE) captures the functional impact of genetic variation on transcription, offering a high-resolution view of cis-regulatory effects, but its quality can be diminished by technical, biological, and analysis artifacts. We introduce aseQC, a statistical framework that quantifies sample-level ASE quality in terms of the overall expected extra-binomial variation to exclude uncharacteristically noisy samples in a cohort to improve robustness of downstream analyses. Applying aseQC to a dataset of rare mendelian muscular disorders, successfully identified previously annotated low-quality cases demonstrating clinical genomic utility. When applied to 15,253 samples in extensively quality controlled GTEx project data, aseQC uncovered 563 low-quality samples that exhibit excessive allelic imbalance. We identify these to be associated with specific processing dates but not otherwise described adequately by any other quality control measures and metadata available in GTEx data. We show that these low-quality samples lead to 23.6 and 31.6 -fold increased ASE, and splicing outliers, degrading the performance of transcriptome analysis for rare variant interpretation. In contrast, we did not observe any adverse effect associated with inclusion of these samples in common-variant analysis using quantitative traits loci mapping. By enabling quick and reliable assessment of sample quality, aseQC presents a critical step for identifying subtle quality issues that remain critical for a successful analysis of rare variant effects using transcriptome data.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157414/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277382","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":"Structural basis for antibody cross-neutralization of dengue and Zika viruses.","authors":"Nicholas K Hurlburt, Jay Lubow, Leslie Goo, Marie Pancera","doi":"10.1101/2025.06.05.658091","DOIUrl":"10.1101/2025.06.05.658091","url":null,"abstract":"<p><p>Safe and effective vaccines against co-circulating mosquito-borne orthoflaviviruses such as Zika virus (ZikV) and the four serotypes of dengue virus (DenV1-4) must elicit broadly neutralizing antibodies (bnAbs) to prevent the risk of enhancement of infection by non-neutralizing antibodies. We recently discovered new orthoflavivirus-directed bnAbs, including F25.S02, which neutralizes DenV1-4 and ZikV with comparable or superior potency to the previously characterized E dimer epitope (EDE) bnAbs. Mutagenesis studies of viral envelope proteins showed that the epitope specificity of F25.S02 is distinct from EDE1 bnAbs. Here, we used cryoEM and X-ray crystallography to understand the basis of cross-neutralization of F25.S02 at the molecular level. We obtained a ~4.2 Å cryoEM structure of F25.S02 Fab bound to a stabilized DenV3 soluble E protein dimer and a 2.3 Å crystal structure of F25.S02 Fab bound to ZikV soluble E protein dimer. Like previously described EDE1 bnAbs, the structural epitope of F25.S02 is at the E dimer interface, encompassing predominantly conserved regions in domain II, including the fusion loop. However, unlike EDE1 bnAbs, F25.S02 binding is almost entirely dependent on the heavy chain and is shifted slightly away from the dimer symmetry axis. Our findings emphasize the importance of this cross-neutralizing site of vulnerability for DenV and ZikV that can facilitate rational design of vaccines and therapeutics.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157686/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277887","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":"Ultrafast endocytosis in mouse cortical inhibitory synapses.","authors":"Chelsy R Eddings, Shigeki Watanabe","doi":"10.1101/2025.06.06.658279","DOIUrl":"10.1101/2025.06.06.658279","url":null,"abstract":"<p><p>Neural circuitry depends on excitatory and inhibitory regulation of activity to yield functional outputs. However, examinations of synaptic vesicle recycling have focused heavily on excitatory synapses, leaving many questions unanswered for inhibitory synapse dynamics. Here we show that both excitatory and inhibitory cortical synapses contain depots of a protein essential for ultrafast endocytosis, Dynamin 1xA, at a region immediately next to the active zone where ultrafast endocytosis takes place. Using zap-and-freeze time-resolved electron microscopy in mouse acute cortical slices, we observe uncoated pits reminiscent of ultrafast endocytic intermediates appearing post-stimulus at putative inhibitory synapses. These findings suggest that excitatory and inhibitory synapses may perform similar modes of endocytosis.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157488/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277944","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":"Youth-associated protein TIMP2 alters microglial state and function in the context of aging.","authors":"Brittany M Hemmer, Ana Catarina Ferreira, Sarah M Philippi, Samuele F Petridis, Annie Phan, Joseph M Castellano","doi":"10.1101/2025.05.20.655226","DOIUrl":"10.1101/2025.05.20.655226","url":null,"abstract":"<p><p>There is little understanding of how aging serves as the strongest risk factor for several neurogenerative diseases. Specific neural cell types, such as microglia, undergo age-related maladaptive changes, including increased inflammation, impaired debris clearance, and cellular senescence, yet specific mediators that regulate these processes remain unclear. The aged brain is rejuvenated by youth-associated plasma factors, including tissue inhibitor of metalloproteinases 2 (TIMP2), which we have shown acts on the extracellular matrix (ECM) to regulate synaptic plasticity. Given emerging roles for microglia in these processes, we examined the impact of TIMP2 on microglial function. We show that TIMP2 deletion exacerbates microglial phenotypes associated with aging, including transcriptomic changes in cell activation, increased microgliosis, and increased levels of stress and inflammatory proteins measured in the brain extracellular space by <i>in vivo</i> microdialysis. Deleting specific cellular pools of TIMP2 <i>in</i> vivo increased microglial activation and altered myelin phagocytosis. Treating aged mice with TIMP2 reversed several phenotypes observed in our deletion models, resulting in decreased microglial activation, reduced proportions of proinflammatory microglia, and enhanced phagocytosis of physiological substrates. Our results identify TIMP2 as a key modulator of age-associated microglia dysfunction. Harnessing its activity may mitigate detrimental effects of age-associated insults on microglia function.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12139801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144236709","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":"Single-cell transcriptomics showed that maternal PCB exposure dysregulated ER stress-mediated cell type-specific responses in the liver of female offspring.","authors":"Joe Lim, Youjun Suh, Xueshu Li, Rebecca Wilson, Hans-Joachim Lehmler, Pamela Lein, Julia Yue Cui","doi":"10.1101/2025.06.04.657944","DOIUrl":"10.1101/2025.06.04.657944","url":null,"abstract":"<p><p>Polychlorinated biphenyls (PCBs) are persistent environmental toxicants that bioaccumulate in the food chain and readily cross the placenta, raising concerns for developmental toxicity. While PCB exposure has been associated with metabolic and neurodevelopmental disorders, its cell type-specific effects on liver development remain poorly understood. This study aimed to investigate how maternal exposure to an environmentally relevant Fox River PCB mixture affects liver development in female offspring at single-cell resolution. We hypothesized that early-life PCB exposure disrupts hepatic metabolic and immune function in a cell type-specific manner. Using single-cell RNA sequencing (scRNA-seq) on liver tissue from postnatal day 28 female mice perinatally exposed to PCBs, we identified major hepatic and immune cell populations and assessed cell-specific transcriptional responses. PCB exposure significantly altered the proportions of endothelial cells and Kupffer cells and reduced neutrophil abundance. Transcriptomic analysis revealed that PCBs dysregulated key pathways in hepatocytes and non-parenchymal cells, including ER stress responses, drug metabolism, and glucose/insulin signaling. Notably, hepatocytes exhibited upregulation of phase-I drug-metabolizing enzymes and uptake transporters, but downregulation of phase-II enzymes and efflux transporters. Kupffer cells and endothelial cells had altered immune and metabolic gene expression, and intercellular communication analysis predicted disrupted fibronectin, collagen, and chemokine signaling due to PCB exposure. RT-qPCR validation confirmed increased hepatic ER stress marker expression. Together these findings demonstrate that perinatal PCB exposure induces persistent, cell type-specific transcriptomic reprogramming in the liver, impairing metabolic and immune functions. This study highlights the utility of single-cell transcriptomics for revealing toxicant effects with cellular precision during critical windows of development.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157533/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277748","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":"scMetaIntegrator: a meta-analysis approach to paired single-cell differential expression analysis.","authors":"Kalani Ratnasiri, Sara N Mach, Catherine A Blish, Purvesh Khatri","doi":"10.1101/2025.06.04.657898","DOIUrl":"10.1101/2025.06.04.657898","url":null,"abstract":"<p><p>Traditional differential gene expression methods are limited for analysis of single cell RNA-sequencing (scRNA-seq) studies that use paired repeated measures and matched cohort designs. Many existing approaches consider cells as independent samples, leading to high false positive rates while ignoring inherent sampling structures. Although pseudobulk methods address this, they ignore intra-sample expression variability and have higher false negatives rates. We propose a novel meta-analysis approach that accounts for biological replicates and cell variability in paired scRNA-seq data. Using both real and synthetic datasets, we show that our method, single-cell MetaIntegrator (https://github.com/Khatri-Lab/scMetaIntegrator), provides robust effect size estimates and reproducible p-values.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157664/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277835","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":"G1 and G2 ApolipoproteinL1 modulate macrophage inflammation and lipid accumulation through the polyamine pathway.","authors":"Esther Liu, Matthew Wright, Andrew O Kearney, Tiffany Caza, Johnson Y Yang, Valerie Garcia, Amal O Dadi, Shuta Ishibe, Navdeep S Chandel, Hanrui Zhang, Edward B Thorp, Jennie Lin","doi":"10.1101/2025.06.06.658371","DOIUrl":"10.1101/2025.06.06.658371","url":null,"abstract":"<p><p>The G1 and G2 variants of the gene encoding Apolipoprotein L1 (<i>APOL1</i>) increase risk for kidney disease and cardiometabolic traits. While previous studies have elucidated key mechanisms by which G1 and G2 <i>APOL1</i> cause cellular inflammation and cytotoxicity, it remains unclear whether these mechanisms drive inflammation in G1 and G2 macrophages. In this study, we used mouse bone-marrow-derived macrophages and human induced pluripotent stem cell-derived macrophages to identify altered immune signaling and inflammatory activation caused by G1 and G2 <i>APOL1</i>. We demonstrated that G1 and G2 APOL1 increased lipid accumulation, pro-inflammatory cytokine expression, and inflammasome signaling; this inflammatory response was sustained when treated with anti-inflammatory cytokines IL-4 and IL-10. Additionally, in G1 and G2 macrophages we observed increased mitochondrial size and elongation, oxidative phosphorylation, and glycolysis. Finally, we used unbiased metabolite analysis to identify an accumulation of polyamine spermidine and the enrichment of the spermidine synthesis pathway in G1 and G2 macrophages. When treated with polyamine inhibitor α-difluoromethylornithine (DFMO), lipid accumulation and inflammasome gene expression decreased in G1 and G2 macrophages. Together, these findings establish the pro-inflammatory effects of G1 and G2 <i>APOL1</i> in macrophages and identify a novel pathway which ameliorates G1 and G2 effects on cellular inflammation.</p>","PeriodicalId":519960,"journal":{"name":"bioRxiv : the preprint server for biology","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-06-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12157409/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144277573","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}