PLoS Computational Biology最新文献

{"title":"Mouse and human striatal projection neurons compared - somatodendritic arbor, spines and in silico analyses.","authors":"Alexander Kozlov, Lidia Blazquez-Llorca, Ruth Benavides-Piccione, Asta Kastanauskaite, Ana I Rojo, Alberto Muñoz, Antonio Cuadrado, Javier DeFelipe, Sten Grillner","doi":"10.1371/journal.pcbi.1013569","DOIUrl":"10.1371/journal.pcbi.1013569","url":null,"abstract":"<p><p>Dysfunction of the basal ganglia is implicated in a wide range of neurological and psychiatric disorders. Our understanding of the operation of the basal ganglia is largely derived on data from studies conducted on mice, which are frequently used as model organisms for various clinical conditions. The striatum, the largest compartment of the basal ganglia, consists of 90-95% striatal projection neurons (SPNs). It is therefore crucial to establish if human and mouse SPNs have distinct or similar properties, as this has implications for the relevance of mouse models for understanding the human striatum. To address this, we compared the general organization of the somato-dendritic tree of SPNs, the dimensions of the dendrites, the density and size of spines (spine surface area), and ion channel subtypes in human and mouse SPNs. Our findings reveal that human SPNs are significantly larger, but otherwise the organisation of the dendritic tree (dendrogram) with an average of approximately 5 primary dendrites, is similar in both species. Additionally in both humans and mice, over 90% of the spines are located on the terminal branches of each dendrite. Human spines are somewhat larger (4.3 versus 3.1 μm2) and the terminal dendrites have a uniform diameter in both humans and mice, although somewhat broader in the latter (1.0 versus 0.6 μm). The composition of ion channels is also largely conserved. These data have been used to simulate human SPNs building on our previous detailed simulation of mouse SPNs. We conclude that the human SPNs essentially appear as enlarged versions of the mouse SPNs. This similarity suggests that both species process information in a comparable manner, supporting the relevance of mouse models for studying the human striatum.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1013569"},"PeriodicalIF":3.6,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12530558/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145259060","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":"Superspreading and the evolution of virulence.","authors":"Xander O'Neill, Andy White, Graham R Northrup, Chadi M Saad-Roy, P Signe White, Mike Boots","doi":"10.1371/journal.pcbi.1013517","DOIUrl":"10.1371/journal.pcbi.1013517","url":null,"abstract":"<p><p>Superspreading, where a small proportion of a population can cause a high proportion of infection transmission, is well known to be important to the epidemiology of a wide range of pathogens, including SARS-CoV-2. However, despite its ubiquity in important human and animal pathogens, the impact of superspreading on the evolution of pathogen virulence is not well understood. Using theory and both deterministic and stochastic simulations we examine the evolution of pathogen virulence under a range of different distributions of infection transmission for the host. Importantly, for many pathogens, superpreader events may be associated with increased tolerance to infection or asymptomatic infection and when we account for this superspreading selects for higher virulence. In contrast, in animal populations where highly connected individuals, that are linked to superspreader events, also have fitness benefits, superspreading may select for milder pathogens. In isolation, the transmission distribution of the host does not impact selection for pathogen virulence. However, superspreading reduces the rate of pathogen evolution and generates considerable variation in pathogen virulence. Therefore, the adaptation of an emerging infectious disease, that exhibits superspreading, is likely to be slowed and characterised by the maintenance of maladaptive variants. Taken as a whole, our results show that superspreading can have important impacts on the evolution of pathogens.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1013517"},"PeriodicalIF":3.6,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12510586/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145259025","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":"Environmental motion presented ahead of self-motion modulates heading direction estimation.","authors":"Liana Nafisa Saftari, Jongmin Moon, Oh-Sang Kwon","doi":"10.1371/journal.pcbi.1013571","DOIUrl":"10.1371/journal.pcbi.1013571","url":null,"abstract":"<p><p>The ability of a moving observer to accurately perceive their heading direction is essential for effective locomotion and balance control. While previous studies have shown that observers integrate visual and vestibular signals collected during movement, it remains unclear whether and how observers use visual signals collected before their movement to perceive heading direction. Here we investigate the effect of environmental motion that occurred ahead of self-motion on the perception of self-motion. Human observers sat on a motion platform, viewed visual motion stimuli, and then reported their perceived heading after the platform moved. The results reveal that environmental motion presented before the observers' movement significantly modulates their heading perception. We account for this effect using a normative computational model that takes into account the causal relationship between visual signals generated before and during the observers' movement. Overall, our study highlights the crucial role of environmental motion presented before self-motion in heading perception, broadening the current perspective on the computational mechanisms behind heading estimation.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1013571"},"PeriodicalIF":3.6,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12527208/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145258986","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":"Spatial distribution of cytoskeleton-mediated feedback controls cell polarization: A computational study.","authors":"Parijat Banerjee, Jonathan A Kuhn, Dhiman Sankar Pal, Yu Deng, Tatsat Banerjee, Peter N Devreotes, Pablo A Iglesias","doi":"10.1371/journal.pcbi.1013036","DOIUrl":"10.1371/journal.pcbi.1013036","url":null,"abstract":"<p><p>In the social amoeba Dictyostelium, cell motility is regulated through a signal transduction excitable network that interfaces with the cytoskeleton to control actin polymerization patterns. In turn, the cytoskeleton influences the signaling machinery via several feedback loops, but the nature and function of this feedback remain poorly understood. In this study, we use computational models to discern the essential role of complementary positive and negative feedback loops in polarizing cells. We contrast two potential mechanisms for the negative feedback: local inhibition and global inhibition. Our results indicate that both mechanisms can stabilize the leading edge and inhibit actin polymerization in other sites, preventing multipolarity. While some experimental perturbations align more closely with the local inhibition model, statistical analyses reveal its limited polarization potential within a wide excitability range. Conversely, global inhibition more effectively suppresses secondary and tertiary leading-edge formation, making it a more robust polarization mechanism. This raises an intriguing question: if local inhibition better replicates experimental observations but is less effective for polarization than local excitation and global inhibition, could there be a supplementary mechanism enhancing its polarization potential? To address this, we propose a novel mechanism involving the dynamic partitioning of back molecules which enhances communication between the front and back of the cell and can be leveraged by local feedback interactions between the cytoskeleton and signal transduction to improve polarization efficiency.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1013036"},"PeriodicalIF":3.6,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145259075","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":"Importance of localized dilatation and distensibility in identifying determinants of thoracic aortic aneurysm with neural operators.","authors":"David S Li, Somdatta Goswami, Qianying Cao, Vivek Oommen, Roland Assi, Jay D Humphrey, George E Karniadakis","doi":"10.1371/journal.pcbi.1013550","DOIUrl":"10.1371/journal.pcbi.1013550","url":null,"abstract":"<p><p>Thoracic aortic aneurysms (TAAs) stem from diverse mechanical and mechanobiological disruptions to the aortic wall that can also increase the risk of dissection or rupture. There is increasing evidence that dysfunctions along the aortic mechanotransduction axis, including reduced integrity of elastic fibers and loss of cell-matrix connections, are particularly capable of causing thoracic aortopathy. Because different insults can produce distinct mechanical vulnerabilities, there is a pressing need to identify interacting factors that drive progression. In this work, we employ a finite element framework to generate synthetic TAAs arising from hundreds of heterogeneous insults that span a range of compromised elastic fiber integrity and cellular mechanosensing. From these simulations, we construct localized dilatation and distensibility maps throughout the aortic domain to serve as training data for neural network models to predict the initiating combined insult. Several candidate architectures (Deep Operator Networks, UNets, and Laplace Neural Operators) and input data formats are compared to establish a standard for handling future subject-specific information. We further quantify the predictive capability when networks are trained on geometric (dilatation) information alone, which mimics current clinical guidelines, versus training on both geometric and mechanical (distensibility) information. We show that prediction errors based on dilatation data are significantly higher than those based on dilatation and distensibility across all networks considered, highlighting the benefit of obtaining local distensibility measures in TAA assessment. Additionally, we identify UNet as the best-performing architecture across all training data formats. These findings demonstrate the importance of obtaining full-field measurements of both dilatation and distensibility in the aneurysmal aorta to identify the mechanobiological insults that drive disease progression, which will advance personalized treatment strategies that target the underlying pathologic mechanisms.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1013550"},"PeriodicalIF":3.6,"publicationDate":"2025-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12520381/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145259062","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":"Dynamic modelling of cell cycle arrest through integrated single-cell and mathematical modelling approaches.","authors":"Javiera Cortés-Ríos, Maria Rodriguez-Fernandez, Peter Karl Sorger, Fabian Fröhlich","doi":"10.1371/journal.pcbi.1012890","DOIUrl":"10.1371/journal.pcbi.1012890","url":null,"abstract":"<p><p>Highly multiplexed imaging assays allow simultaneous quantification of multiple protein and phosphorylation markers, providing a static snapshots of cell types and states. Pseudo-time techniques can transform these static snapshots of unsynchronized cells into dynamic trajectories, enabling the study of dynamic processes such as development trajectories and the cell cycle. Such ordering also enables training of mathematical models on these data, but technical challenges have hitherto made it difficult to integrate multiple experimental conditions, limiting the predictive power and insights these models can generate. In this work, we propose data processing and model training approaches for integrating multiplexed, multi-condition immunofluorescence data with mathematical modelling. We devise training strategies for mathematical models that are applicable to datasets where cells exhibit oscillatory as well as arrested dynamics and use them to train a cell cycle model on a dataset of MCF-10A mammary epithelial cells exposed to cell-cycle arresting small molecules. We validate the model by investigating predicted growth factor sensitivities and responses to inhibitors of cells at different initial conditions. We anticipate that our framework will generalise to other highly multiplexed measurement techniques such as mass-cytometry, rendering larger bodies of data accessible to dynamic modelling and paving the way to deeper biological insights.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1012890"},"PeriodicalIF":3.6,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12520361/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244896","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":"The mechanism of dynamic steady states in lamellipodia.","authors":"June Hyung Kim, Taeyoon Kim","doi":"10.1371/journal.pcbi.1013572","DOIUrl":"10.1371/journal.pcbi.1013572","url":null,"abstract":"<p><p>Lamellipodia are quasi-two-dimensional actin projections formed on the leading edge of the cell, playing an important role in sensing surrounding mechanical environments by forming focal adhesions. A branched actin network in the lamellipodia exhibits a stable, yet dynamic steady state characterized by a retrograde flow, which is attributed to a balance between network assembly at the leading edge and disassembly at the rear. Although the molecular players and architecture of the lamellipodia have been investigated extensively during recent decades, it still remains elusive how the dynamic steady state with continuous retrograde flow is achieved and robustly maintained. Using an agent-based computational model, we probed how physical interactions between subcellular components in the lamellipodia mediate and sustain the dynamic steady state. We simulated the branched network found in the lamellipodia, consisting of F-actin, myosin motor, Arp2/3 complex, and actin cross-linking protein, on an elastic substrate. We reproduced a steady retrograde flow induced by myosin activity and balanced by the interplay between network assembly and disassembly, but hindered by resistances from adhesions formed on the underlying substrate. We found that F-actin severing is crucial for maintaining a continuous, uniform retrograde flow because it enhances the disassembly of actin bundle/arc formed due to network contraction at the rear. In addition, we demonstrated that different modes of dynamic steady states are possible, and that a network which failed to show the retrograde flow due to perturbations can be rescued by altering other factors. Our study provides insights into understanding how cells maintain the dynamic steady state of the lamellipodia in highly varying microenvironments.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1013572"},"PeriodicalIF":3.6,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12517506/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244916","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":"AI-driven discovery of novel extracellular matrix biomarkers in pelvic organ prolapse.","authors":"Yanlin Mi, Ben Cahill, Venkata V B Yallapragada, Reut Rotem, Barry A O'Reilly, Sabin Tabirca","doi":"10.1371/journal.pcbi.1013483","DOIUrl":"10.1371/journal.pcbi.1013483","url":null,"abstract":"<p><p>Deep learning for protein function prediction faces significant challenges in identifying disease-specific proteins. We present Extracellular Matrix Protein Predictor (EPOP), an advanced transfer learning framework leveraging protein language models to decode disease mechanisms. Focusing on pelvic organ prolapse (POP), which affects up to 50% of women worldwide, EPOP demonstrates AI's power to reveal novel therapeutic targets. We developed a sophisticated fine-tuning protocol for the ESM-2 model, optimized for ECM protein prediction. Our architecture integrates specialized attention mechanisms with interpretability modules, trained on expertly curated and balanced datasets totaling 80,000 proteins (40,000 ECM and 40,000 non-ECM). The framework employs a novel validation strategy using a 16,000-sample independent test set and clinical proteomics data. EPOP achieved unprecedented performance (99.40% accuracy) in ECM protein classification, significantly surpassing traditional deep learning architectures (10.81% improvement over Transformer models, 21.71% over Long Short-Term Memory). Applied to clinical samples, our model revealed a previously unknown pattern of ECM remodeling, identifying 24 novel disease-associated proteins. Model interpretability analysis uncovered specific sequence motifs and structural features critical for ECM protein function, providing mechanistic insights into disease progression. EPOP demonstrates how advanced AI bridges molecular analysis and clinical applications, uncovering novel therapeutic targets. Its success suggests broader applications across ECM-related disorders, potentially transforming approaches to diseases affecting connective tissue architecture.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1013483"},"PeriodicalIF":3.6,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12503291/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244945","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":"A digital DNA system favours the superiority of unidirectional inheritance over 'Lamarckian' inheritance.","authors":"Aswathi Shiju, Samantha D M Arras, Allen G Rodrigo, Anthony M Poole","doi":"10.1371/journal.pcbi.1012677","DOIUrl":"10.1371/journal.pcbi.1012677","url":null,"abstract":"<p><p>In biology, changes to a DNA sequence can impact protein sequence but changes to protein sequences (phenotype) do not flow back into DNA (genotype). A system with bidirectional information flow (i.e., both translation and 'reverse translation') remains a theoretical possibility for an independent origin of life or an artificial biosystem, but the recent development of digital data storage in DNA does just this: changes made to a digital file can be written back into DNA, meaning changes to 'phenotype' can be written back to 'genotype'. To explore the evolutionary properties of such a system, we created an artificial system where synthetic DNA serves as genotype and music as phenotype. Audio can be output from a DNA sequence, then recorded and written to DNA as 'codons', enabling bidirectional information flow (DNA→music and music→DNA). Our results show that the mutation rate in a bidirectional system is much higher than for unidirectional information flow, and that, under reverse translation there is no mechanism for preservation of codon choice across generations. This has the effect of eliminating the impact of spontaneous synonymous mutations, a key benefit of a redundant genetic code. As a result, non-synonymous mutations are the only DNA-level changes that are transmitted across generations, and, as non-synonymous mutations can emerge at both 'genotypic' and 'phenotypic' levels, these occur at a two-fold higher frequency than in a unidirectional system. Our system holds some practical insight. First, for DNA read/write systems, it may be wise to avoid designing systems with 'de novo reverse translation' because the opportunities for mutation are higher; tracking genotype information from the preceding generation to guide this process may reduce error. Second, our system helps clarify how a 'Lamarckian' biological system might operate. We conclude that, were a 'Lamarckian' system of inheritance a feature of early genetic systems, it would likely have been short lived as the high frequency of mutation would risk driving the system to extinction. A system based on unidirectional information flow thus appears superior as there are fewer opportunities for mutational error.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1012677"},"PeriodicalIF":3.6,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12517530/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244887","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":"OCIAD2 as a novel prognostic and therapeutic biomarker for pancreatic cancer: A study based on transcriptomic signature and bioinformatics analysis.","authors":"Zhongyuan Cui, Xia Lei, Yani Gou, Zhixian Wu, Xiaojun Huang","doi":"10.1371/journal.pcbi.1013566","DOIUrl":"10.1371/journal.pcbi.1013566","url":null,"abstract":"<p><strong>Background: </strong>It is urgent to explore the potential biomarkers for pancreatic cancer (PC) prognosis and treatment to improve patients' outcomes.</p><p><strong>Methods: </strong>Firstly, we performed an integrated bioinformatics analysis based on extensive transcriptome data from 615 PC tumors and 329 adjacent tissues, screening for genes with prognostic value. We then validated the prognostic value of OCIAD2, DCBLD2, and SAMD9 in different datasets and analyzed their expression levels in single-cell sequencing datasets of normal, paracancer, primary, and metastatic tissues. Next, we further explored the carcinogenic effect after knocking down the expression of OCIAD2 in PC cancer cell line. Finally, a drug sensitivity analysis was conducted.</p><p><strong>Results: </strong>Differentially expressed genes (DEGs) analysis identified 22 DEGs: ACSL5, ANTXR1, AP1S3, ATP2C2, B3GNT5, C15orf48, CAPG, CTSK, DAPP1, DCBLD2, GPX8, HEPH, IFI44, KRT23, NCF2, OCIAD2, SAMD9, SLC39A10, ST6GALNAC1, TBC1D2, TMSB10 and TSPAN5 with prognostic value in PC, though the related function and mechanism are still unclear. Single-cell sequencing results indicated that OCIAD2 was prominently expressed in ductal cells of primary and metastatic tumors. The expression levels of OCIAD2 mRNA and protein were the highest in pancreatic tumor tissues. Mechanism studies revealed that STAT1 and STAT2 in the JAK-STAT pathway and CCND1, CDK1, and CDK2 in the cell cycle pathway were significantly down-regulated after OCIAD2 knockdown. Drug sensitivity analysis identified 25 compounds significantly associated with OCIAD2.</p><p><strong>Conclusions: </strong>These results indicate that OCIAD2 is a potential prognostic biomarker and therapeutic target for PC patients.</p>","PeriodicalId":20241,"journal":{"name":"PLoS Computational Biology","volume":"21 10","pages":"e1013566"},"PeriodicalIF":3.6,"publicationDate":"2025-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12517509/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145244874","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}