Methods最新文献

{"title":"Circularization enhances RNA aptamer binding and Stability: Evidence from in-cell NMR","authors":"Omar Eladl","doi":"10.1016/j.ymeth.2025.07.006","DOIUrl":"10.1016/j.ymeth.2025.07.006","url":null,"abstract":"<div><div>RNA aptamers are emerging as promising molecular probes due to their high specificity and low immunogenicity. However, their clinical potential is often limited by instability under physiological conditions, primarily due to exonucleolytic degradation and structural flexibility. To address these challenges in a model system, we designed a circular RNA aptamer targeting the HIV-1 Tat protein.</div><div>Enzymatic circularization of the aptamer was performed using T4 RNA ligase, and circularization was confirmed by mobility shift assays and RNase R digestion. Binding affinity was assessed via filter dot blot assay, while structural stability was evaluated using 1D imino proton NMR and CLEANEX-PM experiments. Intracellular stability was monitored using in-cell NMR following transfection into HeLa cells.</div><div>In our study, the circular aptamer showed approximately tenfold higher binding affinity compared to its linear counterpart, as determined by filter binding assay. NMR analysis indicated improved structural rigidity, preservation of native base pairing, and reduced solvent exchange. Notably, in-cell NMR revealed that the circular aptamer remained detectable up to 18 h post-transfection, whereas the linear aptamer degraded within a few hours.</div><div>In this system, circularization substantially improved the binding performance and intracellular persistence of the RNA aptamer. These findings demonstrate the feasibility of applying RNA circularization to enhance aptamer functionality in living cells and lay the groundwork for future therapeutic exploration.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"242 ","pages":"Pages 72-79"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144655189","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A prognostic gene signature and subtype-specific drug sensitivity in TNBC revealed by single-cell and bulk RNA sequencing: Insights into stemness and tumor heterogeneity","authors":"Do Thi Minh Xuan ,&nbsp;Doan Phuong Quy Nguyen ,&nbsp;Van Thi Ngoc Tram ,&nbsp;Hoang Dang Khoa Ta","doi":"10.1016/j.ymeth.2025.06.007","DOIUrl":"10.1016/j.ymeth.2025.06.007","url":null,"abstract":"<div><div>Triple-negative breast cancer (TNBC) remains one of the most aggressive Triple-negative breast cancer (TNBC) remains one of the most aggressive and therapeutically challenging breast cancer subtypes, largely due to its lack of targetable receptors and its intrinsic chemoresistance. In this study, we applied an integrative multi-omics approach − combining single-cell RNA sequencing (scRNA-seq) with bulk transcriptomic, epigenomic, and mutational analyses, to investigate the cellular heterogeneity and underlying mechanisms of drug resistance in TNBC. Analysis of the scRNA-seq dataset (GSE176078) revealed a complex tumor microenvironment with a highly plastic cancer epithelial subpopulation (Cluster C4) exhibiting elevated multipotency and distinct intercellular communication patterns. Concurrently, unsupervised clustering of TCGA-BRCA data delineated three molecular subtypes (CS1, CS2, and CS3) with unique biological and metabolic profiles, where CS3 notably exhibited unique molecular features associated with chromatin remodeling and high proliferative activity, suggesting distinct therapeutic vulnerabilities. An overlap analysis between scRNA-seq and bulk RNA-seq data identified 220 common differentially expressed genes (DEGs), from which a four-gene prognostic signature (CTSF, GBP1, BCL2A1, and EMP1) was derived. This signature robustly stratified patients by overall survival across both internal and external cohorts. Overall, our findings provide critical insights into the molecular drivers of chemoresistance in TNBC and offer a foundation for personalized therapeutic strategies.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"242 ","pages":"Pages 24-37"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144320849","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Immunoinformatics-based multi-epitope vaccine design using transforming growth factor beta-2 proprotein (TGFB2) for glioblastoma multiforme (GBM): GVac","authors":"Deniz Tülümen ,&nbsp;Esra Aydemir ,&nbsp;Furkan Ayaz","doi":"10.1016/j.ymeth.2025.07.001","DOIUrl":"10.1016/j.ymeth.2025.07.001","url":null,"abstract":"<div><div>Glioblastoma multiforme (GBM), a malignant glioma, is a central nervous system tumor with a high mortality rate in the world. Despite its high mortality rate, there is no effective treatment yet. Classical treatment methods are usually applied to patients, but patients lose their lives in a short time. A strong vaccine or drug that will extend the life of patients has not yet emerged. In this study, various bioinformatic analyses were performed on the Transforming growth factor beta-2 proprotein (TGFB2) belonging to GBM, and a multi-epitope vaccine design was made. These analyses include allergenicity, antigenicity and toxicity tests, various epitope selections, molecular docking, molecular dynamics simulation and immune simulation analyses. As a result of all analyses, a vaccine candidate called GVac was revealed. Gvac is enhanced with an adjuvant called batroxicidin (BatxC), an antimicrobial peptide. While analyses of Gvac generally yield strong results, it offers the potential to be used in various clinical studies if carried forward. With developing technologies, it is now necessary to move away from classical treatment methods and apply to treatment methods that can provide faster and more effective results. This is also the aim of this study. Gvac may offer hope to GBM patients awaiting treatment around the world and the studies need to be carried forward.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"242 ","pages":"Pages 38-53"},"PeriodicalIF":4.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144569839","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A simple, accurate method for the measurement of lysosomal activity","authors":"Yoshito Iwai ,&nbsp;Yuriko Furuya ,&nbsp;Yuji Oguro ,&nbsp;Keiji Yamamoto","doi":"10.1016/j.ymeth.2025.07.008","DOIUrl":"10.1016/j.ymeth.2025.07.008","url":null,"abstract":"<div><div>Lysosomes are responsible for the degradation of intra- and extracellular components and are thus essential for the quality control of proteins and organelles. Lysosomal dysfunction leads to lysosomal storage diseases, and it is therefore important to identify which types of stress cause functional abnormalities. Lysosomal function is generally evaluated by measuring the enzyme activity of lysosomes with fluorescent dyes. However, fluorescence microscopy can lead to different outcomes due to variations in the field of view, the analysis software used, and the parameter settings. We therefore developed a method that uses only a microplate reader and DQ Green BSA, a dye that emits fluorescence upon lysosomal degradation, to ascertain lysosomal activity. HEK293 cells were treated with DQ Green BSA with or without bafilomycin A1 and lysates extracted using cell lysis buffer. Fluorescence intensities and protein concentrations in the cell lysates were then measured using a microplate reader and the bicinchoninic acid method, respectively, and the fluorescence intensity divided by the protein concentration. Results indicated a significant lysosome inhibitor-induced dose-dependent decrease in the lysosomal activity. The Z’-factor of 0.77 obtained using the proposed method is a significant improvement over the − 0.06 obtained using the conventional method. The versatility of the method was evaluated with different cell types, cell lysis buffers, inhibitors, and protease substrates. These results suggest that the method works regardless of the cells or reagents used, and indicates the relative simplicity and accuracy of the proposed method compared to the currently utilized method.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"242 ","pages":"Pages 143-147"},"PeriodicalIF":4.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144717210","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development of capillary electrophoresis method to measure albumin thiol oxidation in dystrophic humans and animal models of Duchenne muscular dystrophy.","authors":"Angelo Patrick R Bautista, Jessica R Terrill, Marisa N Duong, Gabriella Angelica, Irene Tsioutsias, Christopher P James, Aude Lafoux, Corinne Huchet, Peter G Arthur","doi":"10.1016/j.ymeth.2025.07.010","DOIUrl":"10.1016/j.ymeth.2025.07.010","url":null,"abstract":"<p><p>Inflammatory responses evident in many diseases involve the generation of oxidants which can cause oxidant-induced post-translational modifications to proteins. Albumin, the most abundant plasma protein, contains a free thiol group which is susceptible to oxidative modification. We propose that albumin thiol oxidation (AlbOx) could be a useful biomarker to monitor changes in inflammatory activity and oxidative stress. To measure AlbOx in humans and animal models, we developed a fast, sensitive, simple, and reproducible capillary electrophoresis method (CE-AlbOx). This method can analyse total, reversible, and irreversible oxidation of albumin. The method only requires a small volume of sample (<10 μL blood), has an intra/interday variation of <2 %, and has a total run time of 17 min. We validated the usefulness of AlbOx as a biomarker of chronic inflammation by analysing samples from patients with, and animal models of, Duchenne muscular dystrophy (DMD), a disease associated with chronic inflammation. The main findings in this study are (1) dystrophic humans and animals have higher oxidised albumin compared to healthy controls, (2) mouse albumin has two reactive cysteine groups, and (3) our method is the first to quantify the different oxidation states of mouse albumin. In conclusion, we have developed a new method to measure albumin oxidation in humans and animals using capillary electrophoresis. The simple methodology of the CE-AlbOx method makes it advantageous to current methods and can be readily used as a biomarker of inflammation and oxidative stress in both humans and animal models.</p>","PeriodicalId":390,"journal":{"name":"Methods","volume":" ","pages":"159-168"},"PeriodicalIF":4.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144768179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"3DCellComposer − A versatile pipeline utilizing 2D cell segmentation methods for 3D cell segmentation","authors":"Haoran Chen ,&nbsp;Ted Zhang,&nbsp;Matthew Ruffalo,&nbsp;Robert F. Murphy","doi":"10.1016/j.ymeth.2025.07.007","DOIUrl":"10.1016/j.ymeth.2025.07.007","url":null,"abstract":"<div><div>Cell segmentation is crucial in bioimage informatics, as its accuracy directly impacts conclusions drawn from cellular analyses. While many approaches to 2D cell segmentation have been described, 3D cell segmentation has received much less attention. 3D segmentation faces significant challenges, including limited training data availability due to the difficulty of the task for human annotators, and inherent three-dimensional complexity. As a result, existing 3D cell segmentation methods often lack broad applicability across different imaging modalities. To address this, we developed a generalizable approach for using 2D cell segmentation methods to produce accurate 3D cell segmentations. We implemented this approach in 3DCellComposer, a versatile, open-source package that allows users to choose any existing 2D segmentation model appropriate for their tissue or cell type(s) without requiring any additional training. Importantly, we have enhanced our open source CellSegmentationEvaluator quality evaluation tool to support 3D images. It provides metrics that allow selection of the best approach for a given imaging source and modality, without the need for human annotations to assess performance. Using these metrics, we demonstrated that our approach produced high-quality 3D segmentations of multichannel tissue images. 3DCellComposer, when paired with well-trained 2D segmentation models, provides an important alternative to acquiring human-annotated 3D images for new sample types or imaging modalities and then training 3D segmentation models using them. It is expected to be of significant value for large scale projects such as the Human BioMolecular Atlas Program.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"242 ","pages":"Pages 113-122"},"PeriodicalIF":4.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751950","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Interpretable multimodal learning for tumor protein-metal binding: Progress, challenges, and perspectives","authors":"Xiaokun Liu ,&nbsp;Sayedmohammadreza Rastegari ,&nbsp;Yijun Huang ,&nbsp;Sxe Chang Cheong ,&nbsp;Weikang Liu ,&nbsp;Wenjie Zhao ,&nbsp;Qihao Tian ,&nbsp;Hongming Wang ,&nbsp;Yingjie Guo ,&nbsp;Shuo Zhou ,&nbsp;Sina Tabakhi ,&nbsp;Xianyuan Liu ,&nbsp;Zheqing Zhu ,&nbsp;Wei Sang ,&nbsp;Haiping Lu","doi":"10.1016/j.ymeth.2025.07.004","DOIUrl":"10.1016/j.ymeth.2025.07.004","url":null,"abstract":"<div><div>In cancer therapeutics, protein-metal binding mechanisms critically govern the pharmacokinetics and targeting efficacy of drugs, thereby fundamentally shaping the rational design of anticancer metallodrugs. While conventional laboratory methods used to study such mechanisms are often costly, low throughput, and limited in capturing dynamic biological processes, machine learning (ML) has emerged as a promising alternative. Despite increasing efforts to develop protein-metal binding datasets and ML algorithms, the application of ML in tumor protein-metal binding remains limited. Key challenges include a shortage of high-quality, tumor-specific datasets, insufficient consideration of multiple data modalities, and the complexity of interpreting results due to the “black box” nature of complex ML models. This paper summarizes recent progress and ongoing challenges in using ML to predict tumor protein-metal binding, focusing on data, modeling, and interpretability. We present multimodal protein-metal binding datasets and outline strategies for acquiring, curating, and preprocessing them for training ML models. Moreover, we explore the complementary value provided by different data modalities and examine methods for their integration. We also review approaches for improving model interpretability to support more trustworthy decisions in cancer research. Finally, we offer our perspective on research opportunities and propose strategies to address the scarcity of tumor protein data and the limited number of predictive models for tumor protein-metal binding. We also highlight two promising directions for effective metal-based drug design: integrating protein-protein interaction data to provide structural insights into metal-binding events and predicting structural changes in tumor proteins after metal binding.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"242 ","pages":"Pages 97-112"},"PeriodicalIF":4.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144697285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DEF-DSVM: A deep ensemble feature learning and deepSVM approach for multifaceted analysis and diagnosis of Alzheimer's disease from EEG signals.","authors":"Shabnam Hesari, Hamidreza Ghaffari, Khosro Rezaee","doi":"10.1016/j.ymeth.2025.08.003","DOIUrl":"10.1016/j.ymeth.2025.08.003","url":null,"abstract":"<p><p>Early detection of Alzheimer's disease (AD) and its precursor, mild cognitive impairment (MCI), is paramount for timely intervention and effective disease management. This study introduces a novel computer-aided diagnostic model that leverages electroencephalogram (EEG) data to precisely identify and classify AD and MCI. A comprehensive preprocessing pipeline is employed, incorporating discrete wavelet transform (DWT) for EEG signal decomposition into relevant subbands and subsequent signal windowing to address non-stationarity. Spectrograms derived from these preprocessed signals serve as input for a deep ensemble feature learning and deep support vector machine (DEF-DSVM) architecture. The DEF-DSVM model significantly enhances the accuracy of diagnosing both MCI and AD, achieving an impressive 98.17% accuracy rate that surpasses contemporary state-of-the-art methods. Beyond diagnostic precision, the model effectively identifies specific EEG subbands-namely alpha, theta, and delta-instrumental in elucidating the pathophysiology of AD and MCI. The structure's generalizability and robustness are validated using the Figshare dataset, encompassing, AD, MCI, and control classes. To ensure a rigorous assessment of the model's performance, the Leave-One-Subject-Out (LOSO) cross-validation procedure is employed in lieu of the traditional K-fold approach, mitigating the risk of overoptimistic performance estimates and providing a more accurate reflection of the model's ability to generalize to novel, unseen subjects. Further evaluation of the method's generalizability through its application to an EEG dataset related to attention deficit hyperactivity disorder (ADHD) highlights its broader clinical utility across various neurodegenerative disorders. These findings establish the DEF-DSVM model as a reliable and potent tool for the early diagnosis and monitoring of AD and MCI, offering substantial accuracy gains and demonstrating its potential for widespread application across different neurological conditions.</p>","PeriodicalId":390,"journal":{"name":"Methods","volume":" ","pages":"169-186"},"PeriodicalIF":4.3,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144793172","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-filter based signed heterogeneous graph convolutional networks for predicting activating/inhibiting drug-target interactions","authors":"Ming Chen ,&nbsp;Haike Li ,&nbsp;Yunhan Pan ,&nbsp;Yinglong Dai ,&nbsp;Xiujuan Lei ,&nbsp;Yi Pan","doi":"10.1016/j.ymeth.2025.05.005","DOIUrl":"10.1016/j.ymeth.2025.05.005","url":null,"abstract":"<div><div>The prediction of mechanisms within drug-target interactions (DTIs) can boost the drug discovery process, which has traditionally relied on time-consuming and expensive laboratory experiments. Despite much more attention has been paid to predicting DTIs, but few studies focused on their activating/inhibiting mechanisms. In this work, we model DTIs on signed heterogeneous networks, through categorizing activating/inhibiting DTIs into signed links, and accordingly introducing the coherence/incoherence between drugs on a common target to construct signed drug-drug links. We propose a multi-filter based signed heterogeneous graph convolutional network (MFSHGCN) for drugs and targets embedding, via employing dual filters on both the signed drug-drug sub-graph and the signed DTI sub-graph to converge the spectral information from positive and negative edges. We further put forward an end-to-end framework to predict activation and inhibition within DTIs. The comparison results demonstrate the introduction of coherence/incoherence of drug pairs and the design of our multi-filter system can effectively improve the prediction metrics, even without relying on rich node information and interactions from drug pairs or target pairs. Case studies on breast cancer and lung cancer confirm the model's feasibility.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"241 ","pages":"Pages 51-58"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144092458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Quorum sensing: An essential factor in culturing the human promyelocytic leukemia cell line HL-60 and its neutrophil-related functions","authors":"Danfeng Li ,&nbsp;Tian Yang ,&nbsp;Siyuan Ma ,&nbsp;Xinwei Lyu ,&nbsp;Cheng Hu ,&nbsp;Jiayin Yan ,&nbsp;Lihong Guo ,&nbsp;Jiali Tan","doi":"10.1016/j.ymeth.2025.05.008","DOIUrl":"10.1016/j.ymeth.2025.05.008","url":null,"abstract":"<div><div>HL-60 cells are frequently employed as a standard <em>in vitro</em> model for neutrophil research and extensively utilized. However, the cultivation of HL-60 cells presents a recurring challenge. Historically, cell culture density has been ignored in the consistency of culture conditions. Here, we optimized the culture protocol and explored the impact of culture density on HL-60 cells. Additionally, we investigated the differentiated rate and antibacterial potential of differentiated HL-60 (dHL-60) neutrophils across varying cell density cultures. The findings revealed a positive correlation between cell proliferation activity and cell density, suggesting that increased density facilitates enhanced cell proliferation. Furthermore, as the density of the cell culture increased, there was a concomitant rise in the differentiation rate of HL-60 cells into neutrophils upon stimulation. Importantly, this elevated density also led to significantly higher levels of mitochondrial reactive oxygen species (ROS) production and bacterial phagocytosis. Further investigation revealed that small extracellular vesicles (sEVs) are crucial communicator in quorum sensing within HL-60 cells. Supplementation of HL60-derived sEVs (hEVs) in low-density cell populations resulted in a restoration of cell proliferation, in dose-dependent tendency. Conversely, the inhibition of EV-secretion in HL-60 cells restrains cell growth and proliferation. Overall, our study not only optimized the HL-60 cell culture protocol but also elucidated the critical role of culture density in enhancing HL-60 cell proliferation and antibacterial activity. This finding offers a noteworthy consideration for <em>in vitro</em> experiments of HL-60 cells and suggests the involvement of a quorum sensing mechanism within the neutrophil microenvironment.</div></div>","PeriodicalId":390,"journal":{"name":"Methods","volume":"241 ","pages":"Pages 94-102"},"PeriodicalIF":4.2,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126136","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}