PLoS Computational Biology最新文献

{"title":"Computational deconvolution of drug sensitivity via single-cell-to-bulk transcriptome mapping.","authors":"Alexandre Coudray, Romain Forey, Benjamin Bejar Haro, Filipe Martins, Joana Carlevaro-Fita, Shaoline Sheppard, Sandra Eloise Offner, Gioele La Manno, Guillaume Obozinski, Didier Trono","doi":"10.1371/journal.pcbi.1014862","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014862","url":null,"abstract":"<p><p>Analyses routinely conducted in both fundamental research and biomedical studies often report aggregate signals derived from heterogeneous mixtures of cells. These mixtures reflect the intrinsic anatomical and functional complexity of the tissues and organs from which they are derived. Such bulk measurements obscure cell-specific signals, thereby hindering accurate interpretation of the underlying biological processes. Here, we introduce CLIMB and CLIFF, a two-step machine-learning framework that deconvolves bulk RNA-seq into cell-type composition and expression, and then resolves bulk drug sensitivity measurements into cell subtype- and single-cell-specific profiles. We first validate CLIMB using in-vitro mixtures of leukemic cell lines with experimentally known cell-type proportions, then extend this validation to large-scale, cross-dataset pseudo-bulk analyses built from independent scRNA-seq references across two disease contexts and five cancer types - mimicking the reference-to-target mismatches encountered in real applications - and show that CLIMB accurately infers the cellular composition of bulk samples, outperforming state-of-the-art bulk deconvolution methods. We emphasize CLIMB's effectiveness in acute myeloid leukemia, where it offers highly accurate estimation of leukemic stem cell fractions across three test datasets and three patient cohorts. We then validate CLIFF, our algorithm for estimating cell subtype- and single-cell-specific drug sensitivity, first on the same in-vitro cell line mixtures using experimentally measured drug responses, and then through in-depth, realistic-scale pseudo-bulk simulations. We applied our deconvolution strategy to the beatAML cohort dataset, currently the most extensive database of ex-vivo drug screening data. This analysis generated a cell subtype-resolved drug sensitivity landscape for 121 compounds, revealing multiple compounds putatively active against leukemic stem cells, including midostaurin, A-674563, SNS-032, and foretinib. Collectively, our work introduces a general computational framework for resolving bulk functional measurements at cell-type and single-cell resolution, providing an attractive new computational tool for drug development and precision medicine.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014862"},"PeriodicalIF":3.6,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Weak dispersal and landscape size inevitably promote local biodiversity in heterogeneous metacommunities of competing species.","authors":"Frederik De Laender, Andrew Gonzalez, Olivia Bleeckx, Dieter Ebert, György Barabás","doi":"10.1371/journal.pcbi.1014028","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014028","url":null,"abstract":"<p><p>We provide a general theoretical explanation for a longstanding result in spatial ecology: weak dispersal among habitat patches promotes local species richness. Using analytical approximations of spatial Lotka-Volterra competition models, we show that local species persistence in heterogeneous landscapes can be expressed as the balance between the total density across patches and the local exclusion rate. We further demonstrate that local multispecies coexistence is governed by the feasibility domain, linking spatial coexistence to a structural property of nonspatial competitive systems. Together, these results explain why weak dispersal increases local species richness and why this effect strengthens with the number of available patches, i.e., landscape size. We test these predictions using numerical simulations and find that the theory breaks down only when both dispersal and competitive interactions are very strong, in which case dispersal has a unimodal effect on coexistence. In contrast, landscape size retains a positive effect on coexistence whenever an effect is detectable. We then apply the theory to long-term data from a natural metacommunity of microcrustaceans. We detect strong competition among species and find no detectable effect of dispersal rate on local coexistence, whereas species co-occurrence increases with local landscape size, as predicted by theory. Together, our results identify how dispersal, interaction strength, and landscape size jointly regulate local species richness in competitive systems.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014028"},"PeriodicalIF":3.6,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ten simple rules for developing a reporting appraisal tool.","authors":"Kyle Morrison, Malgorzata Lagisz","doi":"10.1371/journal.pcbi.1014841","DOIUrl":"10.1371/journal.pcbi.1014841","url":null,"abstract":"<p><p>In an ideal world, authors would report clearly and transparently exactly what they conducted. In reality, reporting is often incomplete, and key elements of research conduct are frequently missing from manuscripts. Reporting guidelines were developed to address this problem by helping authors identify what should be reported. These guidelines have been highly valuable for authors, but they are not well suited for appraising reporting during peer review or editorial assessment despite common use. This is because authors and appraisers have different needs: authors require a comprehensive guide for writing, whereas appraisers need a tool that is concise, repeatable, and easy to use. We therefore propose the development of reporting appraisal tools: operationalised tools designed specifically to assess whether a paper has reported the minimum essential elements of a study. To support their development, we present 10 simple rules.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014841"},"PeriodicalIF":3.6,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13674756/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Computation-through-Dynamics Toolkit: Simulated datasets and quality metrics for dynamical models of neural activity.","authors":"Christopher Versteeg, Jonathan D McCart, Mitchell Ostrow, David M Zoltowski, Clayton B Washington, Laura Driscoll, Olivier Codol, Jonathan A Michaels, Scott W Linderman, David Sussillo, Chethan Pandarinath","doi":"10.1371/journal.pcbi.1014755","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014755","url":null,"abstract":"<p><p>A primary goal of systems neuroscience is to discover how ensembles of neurons transform inputs into goal-directed behavior, a process known as neural computation. A powerful framework for understanding neural computation uses neural dynamics - the rules that govern how neural activity evolves over time - to explain how goal-directed input-output transformations occur. As dynamical rules are not directly observable, we need computational models that can infer neural dynamics from recorded neural activity. We typically validate such models using synthetic datasets with known ground-truth dynamics, but unfortunately existing synthetic datasets don't reflect fundamental features of neural computation and may therefore be poor proxies for neural systems. Further, the field lacks validated metrics for quantifying the accuracy of the dynamics inferred by models. The Computation-through-Dynamics Toolkit (CtDToolkit) addresses these critical gaps by providing: 1) synthetic datasets that reflect computational properties of biological neural circuits, 2) interpretable metrics for quantifying model performance, and 3) a standardized pipeline for training and evaluating models with or without known external inputs. In this manuscript, we demonstrate how CtDToolkit can help guide the development, tuning, and troubleshooting of neural dynamics models. In summary, CtDToolkit provides a necessary framework for model developers to better understand and characterize neural computation through the lens of dynamics.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014755"},"PeriodicalIF":3.6,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149195863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"From prompts to genomes: A constraint-first framework for AI-driven sequence design across life and viruses.","authors":"Adhityo Wicaksono, Arli Aditya Parikesit","doi":"10.1371/journal.pcbi.1014865","DOIUrl":"10.1371/journal.pcbi.1014865","url":null,"abstract":"<p><p>A constraint-first framework for future 'prompt-to-genome' AI across Bacteria, Archaea, Eukaryota, and viruses is proposed. Genome-scale models can now generate long DNA sequences, and experimentally viable genome-scale designs have begun to appear, but sequence generation alone does not establish biological feasibility. Constraints should not require designs to remain within natural sequence space; rather, they should define testable boundaries for function, inheritance, lifecycle coherence and safe use, including new-to-nature designs. We propose a two-part system. First, a Constraint Compiler translates natural-language prompts into machine-checkable specifications defining scope, context, objectives, assumptions and governance requirements. Second, a modular Validator Stack (C1-C6) evaluates candidate designs for sequence integrity, gene and regulatory plausibility, genome completeness, comparative coherence, systems-level feasibility, and safety and governance. Extreme prompts serve as stress tests to expose hidden assumptions, conflicting objectives, and refusal points, complemented by adversarial testing and risk assessment. A phased roadmap and community benchmarks are proposed to measure specification accuracy, biological feasibility, robustness, and governance performance. The goal is to move prompt-to-genome systems from impressive generation toward reliable, auditable, and accountable biological design.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014865"},"PeriodicalIF":3.6,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13671503/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149195846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Leveraging spatial structure to design spatially-targeted malaria interventions at the community-scale.","authors":"Michelle V Evans, Benjamin Roche, Vincent Herbreteau, Christophe Révillion, Thibault Catry, Matthew H Bonds, Karen E Finnegan, Ezra Mitsinjoniala, Felana A Ihantamalala, Mauricianot Randriamihaja, Oméga Raobela, Andres Garchitorena","doi":"10.1371/journal.pcbi.1014857","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014857","url":null,"abstract":"<p><p>Progress in malaria control has stagnated since the early 21st century in many countries, requiring new approaches such as the use of spatially-targeted interventions. However, evidence on the effectiveness of spatially-targeted interventions is mixed, depending on both the setting and intervention. In addition, the potential role of community health programs in implementing spatial targeting is underexplored, with models focusing on coarser spatial scales than those needed to guide programmatic activities. We developed a two-age-class, spatially-explicit model of malaria at the community-scale for a district in southeastern Madagascar, accounting for environmental heterogeneity and spatial structure, to explore spatially-targeted community health interventions. The model was fit to field-based case notifications and malaria prevalence data and then used to simulate three interventions: indoor residual spraying (IRS), supplemental coverage of long-lasting insecticide-treated nets (LLIN), and active case detection (ACD). We compared five scenarios, one with no spatial targeting and others targeting communities (i) nearest to clinics, (ii) furthest from clinics, (iii) with highest incidence, and (iv) that are spatially central. The non-targeted intervention was generally the most effective, but the least resource efficient. The second most effective intervention was based on spatial centrality, which reached a larger population while using fewer transportation resources than the non-targeted intervention. No combination of interventions was able to eliminate malaria in the district, although detecting symptomatic cases through ACD could avert 100% of severe malaria cases at high detection rates. These results highlight the potential for targeted malaria interventions, especially in low-income settings, that take into account spatial structure in the human population and transport networks to reduce malaria burdens using fewer resources than conventional district-wide interventions. [A French language abstract is available as Text A in S1 Appendix].</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014857"},"PeriodicalIF":3.6,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149195844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ten simple rules to build genomics capacity for routine laboratory practice in the Global South.","authors":"Emilyn Costa Conceição, Abhinav Sharma, Davi Josué Marcon, Layana Rufino Ribeiro, Danna Karen Corrêa Dos Santos, Lilian Eduarda de Oliveira Freitas, Alex Brito Souza, Hendor Neves Ribeiro de Jesus, Maria Cristina da Silva Lourenço, Valnete das Graças Dantas Andrade, Marco Aurélio Almeida de Oliveira, Tatyana Costa Amorim Ramos, Ítalo José Mesquita Cavalcante, Arabela Leal E Silva de Melo, Nabila Ismail, Tulio de Oliveira, Robin Mark Warren, Adriana Ayden Ferreira, Theolis Costa Barbosa Bessa, Cristiane Cunha Frota, Philip Noel Suffys, Karla Valéria Batista Lima","doi":"10.1371/journal.pcbi.1014863","DOIUrl":"10.1371/journal.pcbi.1014863","url":null,"abstract":"<p><p>Developing sustainable genomics capacity in the Global South requires more than technology transfer; it depends on human-centered approaches based on the workflows and existing expertise of laboratory personnel, institutional collaboration, and long-term integration into health systems. Drawing on lessons learned from regional capacity-building initiatives, this article proposes ten simple rules for implementing and sustaining genomics capacity within public health and clinical laboratory settings. These rules emphasize local context, strategic planning, continuous learning, and equitable collaboration. Together, they provide a roadmap for laboratories aiming to transform genomic technologies from research tools for diagnosis, surveillance and decision-making, into routine instruments for public health in low- and middle-income countries.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014863"},"PeriodicalIF":3.6,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13671508/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149195822","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"How compartmentalization and proliferation shape the splenic T cell repertoire during an immune response to a complex antigen in mice.","authors":"Franka Buytenhuijs, Cornelia Tune, Thomas C Smits, Andrea Schampel, Lisa-Kristin Schierloh, René Pagel, Jürgen Westermann, Johannes Textor","doi":"10.1371/journal.pcbi.1014859","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014859","url":null,"abstract":"<p><p>The adaptive immune system recognizes billions of unique antigens using highly variable T cell receptors (TCRs). To what extent TCR features shape the spatial distribution of the TCR repertoire (TCR-R) within lymphoid organs remains unclear. Here, we compared the TCR-R composition in T cell zones (TCZ), B cell zones (BCZ), and germinal centers (GC) of the spleen by analyzing the complementarity-determining region 3 of the beta chain (CDR3β) in microdissected splenic compartments from naïve and immunized mice. While we found substantial differences in TCR-R composition between these compartments, these differences largely disappeared once the effects of compartment size and proliferation were accounted for: During steady state, the few T cells found in BCZs strongly resemble random subsets of those found in TCZs. After immunization, expanded clones started appearing in the TCZ at day 3 and later shifted to the BCZ. GCs harbored even further expanded clones that were grouped into clusters with high sequence similarity. TCR-R differences during the immune response were well explained by a Galton-Watson model of T cell proliferation, suggesting that this could be the central factor shaping the observed TCR-R differences. Similarly, while TCR length and closeness to germline initially showed more pronounced differences between the compartments, our models of random distribution and proliferation explained these differences almost entirely. Hence, our findings suggest that splenic TCR-Rs are shaped predominantly by compartment size and proliferation rates rather than TCR sequence features. This would imply that quantitative assessment of TCR-R dynamics across heterogeneous spatial compartments during an immune response is only possible when these effects are explicitly accounted for.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014859"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"MEGH-DDI: MolT5-driven edge-aware graph learning with Hop2Token representation for drug-drug interaction prediction.","authors":"Li Zhou, Yun Zuo, Wenying He, Zhaohong Deng","doi":"10.1371/journal.pcbi.1014393","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014393","url":null,"abstract":"<p><p>Drug-drug interactions (DDIs) are critical in pharmacology, as synergistic or antagonistic effects between co-administered drugs can enhance therapeutic outcomes or cause toxicity, posing major challenges for drug safety assessment and new drug development. Current molecular representation methods often fail to capture dynamic substructure relationships or semantic interactions among functional groups. To overcome these limitations, this study proposes MEGH-DDI, a multimodal framework that integrates complementary molecular representation learning with graph-structure dynamic perception. The framework employs a dual-channel semantic module that combines Mol2vec-based substructure representations with MolT5 chemical language embeddings, while SHAP-based dynamic feature selection reduces redundancy. For fine-grained structural modeling, we introduce an edge-aware GCNII equipped with bond-level attention to distinguish different types of chemical bonds. Furthermore, the Hop2Token module converts multi-hop neighborhoods into token sequences, enabling Transformer-based modeling of high-order substructure dependencies. Experimental results demonstrate that MEGH-DDI achieves competitive performance across both transductive and inductive settings. On the DrugBank dataset, MEGH-DDI attains an accuracy of 98.36% in the transductive task, outperforming earlier baselines and surpassing recent state-of-the-art methods, with both AUC and AP exceeding 99.7%. On the ChChMiner dataset, MEGH-DDI achieves an F1 score of 99.05%, improving over the best existing method by 2.74 percentage points. In the inductive settings, MEGH-DDI achieves competitive performance across most evaluation metrics on both datasets, showing advantages over competing methods on several key metrics. These results demonstrate the effectiveness of MEGH-DDI in predicting DDI involving previously unseen drugs and its potential to generalize to complex DDI prediction scenarios. To enhance interpretability, MEGH-DDI incorporates a three-level mechanism spanning atoms, chemical bonds, and topological paths, highlighting key atoms and bond contributions. Overall, MEGH-DDI provides an efficient, accurate, and interpretable solution for drug safety assessment and new drug discovery. Code and datasets are available at https://github.com/Lilyjoys/MEGH-DDI, and a free web platform is provided at http://www.edgh-ddi.com.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014393"},"PeriodicalIF":3.6,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184044","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distinct extracellular architectures shape mechanical persistence in GPVI and CLEC-2 receptor assemblies.","authors":"Yao Zhang, Yue Cheng, Han Ni Soe, Zhipeng Xu","doi":"10.1371/journal.pcbi.1014884","DOIUrl":"https://doi.org/10.1371/journal.pcbi.1014884","url":null,"abstract":"<p><p>Glycoprotein VI (GPVI) and C-type lectin-like receptor 2 (CLEC-2) are platelet-activating receptors whose extracellular organization contributes to receptor association and signaling during thrombus formation, yet how alternative receptor architectures influence mechanical persistence remains unclear. We used molecular dynamics to compare a GPVI dimer based on 2GI7, a domain-swapped GPVI assembly derived from 7NMU, and a crystallographic CLEC-2 contact using the same pulling protocol and constant-force conditions. During the first 5 nm of imposed separation, reconstructed GPVI required less force and mechanical work than CLEC-2 and domain-swapped GPVI. Under constant-force loading from 400 to 600 pN, reconstructed GPVI also reached the same extension endpoint markedly earlier than the domain-swapped assembly, with passage times differing by more than an order of magnitude under several conditions. Extended pulling to approximately 10 nm produced complete loss of interreceptor heavy-atom contacts in reconstructed GPVI while local peptide and disulfide connectivity remained intact. In contrast, the domain-swapped preparation retained resistance over a larger part of the separation pathway and showed substantially greater mechanical persistence. These results show that alternative extracellular arrangements of the same receptor are not mechanically equivalent and that uncertainty in GPVI architecture can translate into large differences in force transmission and persistence under load. Such architecture-dependent persistence may influence the stability of extracellular receptor associations during thrombus formation and thereby affect the mechanical lifetime of receptor clusters under load.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"22 10","pages":"e1014884"},"PeriodicalIF":3.6,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149184094","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}