Cytometry Part A最新文献

{"title":"Morphological Profiling of Imaging Flow Cytometry Data Uncovers Heterogeneity in Infected Gephyrocapsa huxleyi Cultures.","authors":"Maxim Lippeveld, Daniel Peralta, Assaf Vardi, Flora Vincent, Yvan Saeys","doi":"10.1002/cyto.a.24944","DOIUrl":"10.1002/cyto.a.24944","url":null,"abstract":"<p><p>Phytoplankton, such as the coccolitophore Gephyrocapsa huxleyi (G. huxleyi), has a major ecological impact through photosynthesis-the production of oxygen and organic material. A significant threat to G. huxleyi populations is viral infection with the specific Gephyrocapsa huxleyi virus (GhV). Previous research has provided important insight into the infection cycle of G. huxleyi. However, research including quantitative morphological information on infected cells is lacking, potentially masking heterogeneity in the infection cycle. In this study, we propose a machine learning (ML) pipeline to incorporate morphological profiling into the analysis of spatially resolved single-molecule mRNA fluorescence in situ hybridization (smFISH)-imaging flow cytometry (IFC) data acquired on infected G. huxleyi populations. First, we propose to simplify infection monitoring by using a classification model that does not rely on mRNA staining. Second, we propose an exploratory data analysis pipeline to disentangle two modes of cell death in infected cultures and a subpopulation of healthy cells that potentially will not die from infection, but from programmed cell death (PCD). Overall, we show that morphological profiling of smFISH-IFC data is highly suited for studying microbial interactions in phytoplankton populations.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"438-449"},"PeriodicalIF":2.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144301314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Imaging and Cytometric Techniques to Characterize Lipid Accumulation in Wolman Disease.","authors":"Marine Laurent, Jérémie Cosette, Giulia Pavani, Sarah Bayol, Christine Jenny, Rim Harb, Julie Oustelandt, Anais Brassier, Daniel Stockholm, Mario Amendola","doi":"10.1002/cyto.a.24949","DOIUrl":"10.1002/cyto.a.24949","url":null,"abstract":"<p><p>Wolman disease (WD) is a severe lysosomal storage disorder characterized by fatal lipid accumulation caused by the deficiency of a lipid metabolic enzyme, Lysosomal Acid Lipase (LAL), involved in the lysosomal hydrolysis of cholesterols and triglycerides. Due to the imbalance of lipid homeostasis, WD patients suffer from severe hepatosplenomegaly, hepatic failure, and adrenal calcification resulting in a premature infant death within the first year of age. In this work, we explored multiple imaging analyses to fully characterize the phenotype of LAL-deficient cells. In particular, we stained WD patients' fibroblasts for intracellular lipid droplets (LD) and lysosomes, and we analyzed staining intensity and granularity, as well as an increased number of LD and lysosomes using fluorescence wide-field microscopy, confocal microscopy, conventional, and image flow cytometry. Noteworthy, we showed that lipid homeostasis was restored upon delivery of a functional LAL transgene. Finally, since fibroblasts cannot be used as routine clinical tests as they are difficult to collect from WD patients, we confirmed our observations in LAL deficient human blood cell lines and in peripheral blood mononuclear cells (PBMC) from the LAL deficient (LAL-D) mouse model, as a proxy for easily accessible WD PBMC. Overall, we expect that this novel imaging analysis pipeline will help to diagnose WD, follow its progression, and evaluate the success of enzyme replacement therapy or gene correction strategies for WD as well as other lysosomal storage disorders.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"464-475"},"PeriodicalIF":2.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144559449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"GatingTree: Pathfinding Analysis of Group-Specific Effects in Cytometry Data.","authors":"Masahiro Ono","doi":"10.1002/cyto.a.24948","DOIUrl":"10.1002/cyto.a.24948","url":null,"abstract":"<p><p>Advancements in cytometry technologies have led to a remarkable increase in the number of markers that can be analyzed simultaneously, presenting significant challenges in data analysis. Traditional approaches, such as dimensional reduction techniques and computational clustering, although popular, often face reproducibility challenges due to their heavy reliance on inherent data structures. This reliance prevents the direct translation of their outputs into gating strategies for downstream experiments. Here, we propose the novel Gating Tree methodology, a pathfinding approach that investigates the multidimensional data landscape to unravel group-specific features without the use of dimensional reduction. This method employs novel measures, including enrichment scores and gating entropy, to effectively identify group-specific features within high-dimensional cytometric data sets. Our analysis, applied to both simulated and real cytometric data sets, demonstrates that the Gating Tree not only identifies group-specific features comprehensively but also produces outputs that are immediately usable as gating strategies for pinpointing key cell populations. Furthermore, by integrating machine learning methods, including Random Forest, we have benchmarked Gating Tree against existing methods, demonstrating its superior performance. A range of supervised and unsupervised methods implemented in Gating Tree thus provides effective visualization and output data, which can be immediately used as successive gating strategies for downstream study.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"476-496"},"PeriodicalIF":2.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144567258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Recommendations for Accurate Target Expression Evaluation by Quantitative Flow Cytometry.","authors":"Tamara Lekishvili, Maxime Moulard, Sarah Jetzer, Alisa Kirkin, Teresa Maria Frasconi, Gülsah Celik, Anne Goubier, Amelie Croset","doi":"10.1002/cyto.a.24943","DOIUrl":"10.1002/cyto.a.24943","url":null,"abstract":"<p><p>Among various cellular characteristics, flow cytometry can evaluate antigen expression through qualitative or quantitative approaches. For relative quantification, fluorescence intensity (FI) values are converted into quantitative measurements using appropriate reference materials. To quantitatively estimate antigen density or define ligand-binding sites per cell, antibody binding capacity (ABC) values serve as the preferred metric. Standardizing assays through the conversion of arbitrary FI units into quantitative data is essential for consistency. However, reported ABC values for well-characterized antigens vary across the literature. This study addresses the challenges in achieving robust and reproducible quantitative flow cytometry data, offering methodological recommendations for accurately assessing target expression. Our research includes a comprehensive investigation of multiple factors, such as conventional and full-spectrum instruments, antibodies, reagents, matrices, cell density/confluency, cellular autofluorescence, and quantitative kits, to identify the primary sources of variation in ABC calculations. By implementing a systematic and integrated approach, we aim to ensure the generation of reliable and reproducible ABC values. Longitudinal studies provide strong evidence of assay robustness, while the established protocol further supports biomarker evaluation across different matrices and various stages of drug development.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"423-437"},"PeriodicalIF":2.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144301315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Small U-Net for Fast and Reliable Segmentation in Imaging Flow Cytometry.","authors":"Sara Kaliman, Raghava Alajangi, Nadia Sbaa, Paul Müller, Nadine Ströhlein, Jeffrey Harmon, Martin Kräter, Jochen Guck, Shada Abuhattum","doi":"10.1002/cyto.a.24947","DOIUrl":"10.1002/cyto.a.24947","url":null,"abstract":"<p><p>Imaging flow cytometry requires rapid and accurate segmentation methods to ensure high-quality cellular morphology analysis and cell counting. In deformability cytometry (DC), a specific type of imaging flow cytometry, accurately detecting cell contours is critical for evaluating mechanical properties that serve as disease markers. Traditional thresholding methods, commonly used for their speed in high-throughput applications, often struggle with low-contrast images, leading to inaccuracies in detecting the object contour. Conversely, standard neural network approaches like U-Net, though effective in medical imaging, are less suitable for high-speed imaging applications due to long inference times. To address these issues, we present a solution that enables both fast and accurate segmentation, designed for imaging flow cytometry. Our method employs a small U-Net model trained on high-quality, curated, and annotated data. This optimized model outperforms traditional thresholding methods and other neural networks, delivering a 35× speed improvement on CPU over the standard U-Net. The enhanced performance is demonstrated by a significant reduction in systematic measurement errors in blood samples analyzed using DC. The tools developed in this study are adaptable for various imaging flow cytometry applications. This approach improves segmentation quality while maintaining the rapid processing necessary for high-throughput environments.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"450-463"},"PeriodicalIF":2.1,"publicationDate":"2025-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144526786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"CYTO-Connect: A New Era in Cytometry Conferences Begins in Perth, Australia","authors":"Matthew D. Linden,&nbsp;Henry Y. L. Hui","doi":"10.1002/cyto.a.24945","DOIUrl":"10.1002/cyto.a.24945","url":null,"abstract":"&lt;p&gt;The International Society for the Advancement of Cytometry (ISAC) and its regional partner in Oceania, The Australasian Cytometry Society (ACS), are collaborating to introduce CYTO-Connect, a groundbreaking new conference set to debut in Perth, Australia, from November 27th to 29th, 2025 (https://cytoconnectperth2025.com.au/).&lt;/p&gt;&lt;p&gt;It is more than 45 years since ISAC was first established (as the International Society for Analytical Cytology) and it remains the premier international scientific community for cytometry and the quantitative cell sciences. ISAC's annual scientific meeting, known as “CYTO” attracts scientists and exhibitors from all over the world. While CYTO is hosted by a different city each year, historically these have always been in North America or Europe, leaving much of the globe under-represented in cytometry education and networking.&lt;/p&gt;&lt;p&gt;The ACS is an ISAC-associated society and has a similar history. Only slightly younger than ISAC, ACS was established in 1979 as the Australasian Flow Cytometry Group. ACS holds an annual scientific meeting, typically hosted in Australia or New Zealand.&lt;/p&gt;&lt;p&gt;CYTO-Connect will not be the first time that ISAC and ACS have worked together to deliver a landmark conference in Oceania. As far back as 1999 [&lt;span&gt;1&lt;/span&gt;], ISAC partnered with ACS to host the second Sam Latt conference on Hamilton Island, Australia. Then, more recently, ACS and ISAC worked together with the Singaporean Society for Immunology to produce CYTO Asia. This groundbreaking meeting, chaired by Paul Hutchinson, was held in Singapore in 2017 and received international acclaim [&lt;span&gt;2&lt;/span&gt;]. CYTO-Connect seeks to build on the success of these previous collaborations to blend the best of ACS and CYTO.&lt;/p&gt;&lt;p&gt;Overlooking the Indian Ocean on Australia's West coast, Perth is the capital city of Western Australia. While Perth is a lengthy flight (or two!) from North America and Europe, Perth is only a short hop away and roughly equidistant from major Australian capitals, as well as major cities in Southeast Asia; Singapore, Jakarta, Kuala Lumpur, Ho Chi Minh, Bangkok. Perth shares its time zone with China, Hong Kong, Brunei, and Philippines. A perfect location to connect with cytometrists in this rapidly growing region. Perth's unique position makes it a natural hub for connecting cytometry communities across Oceania, Asia, and beyond—exactly the kind of global exchange CYTO-Connect aims to foster.&lt;/p&gt;&lt;p&gt;The Cytometry Society (India) has partnered with ACS to support CYTO Connect, and we are excited to welcome delegates and speakers from India to present in Perth. Dr. Vainav Patel is Vice President (Basic Research) of The Cytometry Society of India (TCS) and heads the Viral Immunopathogenesis Lab at ICMR-NIRRCH, Mumbai. Dr. Vainav also served as Nodal Officer of the Covid19 team of the institute. We are looking forward to his presentations at CYTO-Connect, including the topic of immune monitoring and vaccine development i","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"107 6","pages":"357-360"},"PeriodicalIF":2.5,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24945","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144495071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Increasing Cell Sorting Recovery Using the Simple “Three-Puddle Method”","authors":"María José Castro Pérez,&nbsp;Carl Henderson","doi":"10.1002/cyto.a.24942","DOIUrl":"10.1002/cyto.a.24942","url":null,"abstract":"<p>Recovery is a key performance parameter in cell sorters, a metric that assesses the match between the number of particles reported as sorted by the instrument and the actual number of particles gathered in the collection vessels. Sorting relies on the precise timing of the charging of a droplet containing the particle of interest in a critical measurement called drop delay (DD). DD timings are typically reliant on manufacturer recommended fluorescent bead reagents. Cuvette-based cell sorters in particular depend upon these fixed-sized QC beads for an automated approach to the DD calculation using an image-based camera system. Previous literature has highlighted the mismatch between these DD values and the settings best accommodating actual samples. Here, we present a new method for DD calculation—the Three-Puddle Method (3PM), based on procedures originally described for <i>jet-in-air</i> cell sorters; it optimizes DD values according to the target particle to be sorted, increasing sort recoveries for a range of cell sizes and particle types. With regard to recovery, 3PM-calculated DD values correlate with those achieved via optimum DD, defined using Rmax protocol, a robust metric for recovery. The advantages of the 3PM then are that it is a simple-to-implement protocol which has limited cell expenditure, essential in the handling of precious rare samples and the success of single cell and bulk sorting and the downstream applications relying on it.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"107 6","pages":"404-415"},"PeriodicalIF":2.5,"publicationDate":"2025-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24942","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144207957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nuclear-Free Zoning","authors":"Stephen Lockett,&nbsp;Andrew Weisman","doi":"10.1002/cyto.a.24939","DOIUrl":"10.1002/cyto.a.24939","url":null,"abstract":"&lt;p&gt;Spatial proteomics and transcriptomics are mainstream technologies that molecularly characterize individual cells or groups of cells at spatial locations throughout the tissue. As a result, these methods produce new understandings of organ and organism development and of disease progression, including elucidating the role of immune cells in carcinogenesis. The steps in the execution of such imaging-based technologies are to cut a thin tissue section (≈ 5 μm thickness), uniquely label the specific protein or RNA molecules of interest, acquire images of the labeled section, and analyze the images. In most cases, the labels are fluorescent, and some methods cyclically iterate between labeling and acquisition to build up a profile of scores of proteins or RNA transcripts across the tissue.&lt;/p&gt;&lt;p&gt;State of the art acquisition methods produce images of sufficient spatial resolution to facilitate localization of the labeled species in the individual cells. Consequently, the canonical image analysis methods first detect each cell by segmenting its counter-stained nucleus followed by quantifying each labeled species in the nucleus or in the surrounding cytoplasm of the nucleus. Such methods work well for cells that have small, ring-shaped cytoplasm surrounding their nuclei (e.g., T cells) and cells that adhere to each other into a cobble stone arrangement (e.g., epithelial cells). However, some cell types take on elongated morphology with their cytoplasm extending tens of microns from their nucleus (e.g., neurons, myocytes, and fibroblasts), and for these types, the nucleus is not representative of the overall cell extent and shape, leading to failed estimation of the cytoplasmic zone for these cells. Directly finding the borders of such cells by explicitly labeling the plasma membranes has shown promise, but universal plasma membrane markers have proven elusive. Moreover, some proteins of interest are inherently extracellular, such as matrix-metalloproteinases that can play a key role in tumor cell invasion.&lt;/p&gt;&lt;p&gt;Recently, several studies reported cell detection methods that circumvent nucleus segmentation and instead rely on certain molecular markers, or combinations thereof, being present in the cytoplasm of one cell with different levels of the markers in neighboring cells. In one early study [&lt;span&gt;1&lt;/span&gt;], cell type signatures were calculated by clustering from combinations of gene expression markers in osmFISH and MERFISH images. Examples of subsequent works were an approach that optimizes cell boundary locations by considering the joint likelihood of transcriptional expression along with cell morphology [&lt;span&gt;2&lt;/span&gt;]. In 2023, Liu et al. [&lt;span&gt;3&lt;/span&gt;] used unsupervised clustering of pixel-level features for capturing relevant objects, such as the extracellular matrix, outside of the cell, and in addition, clustering of pixels that lie within the cells improved cell segmentation over standard methods.&lt;/p&gt;&lt;p&gt;Methods to date to investigate","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"107 6","pages":"361-363"},"PeriodicalIF":2.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24939","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"OMIP-115: High-Dimensional Phenotypic Characterization of Human Natural Killer Cells for Therapeutic Use","authors":"Emil Birch Christensen,&nbsp;Moritz Schaefer,&nbsp;Mike Bogetofte Barnkob,&nbsp;Christian Nielsen,&nbsp;Torben Barington","doi":"10.1002/cyto.a.24941","DOIUrl":"10.1002/cyto.a.24941","url":null,"abstract":"<p>This 29-color flow cytometry panel was developed and optimized for in-depth characterization of human peripheral blood NK cells for preclinical development and monitoring of NK cell therapies. The panel includes markers associated with NK cell differentiation, cytotoxicity, tissue residency, as well as NK cell dysfunction. Panel optimization was performed on freshly isolated and ex vivo activated NK cells enriched from human peripheral blood mononuclear cells (PBMCs). Overall, this panel functions as a tool to extensively characterize human NK cells, paving the way for rapid and standardized approaches to evaluate the biological activity of therapeutic NK cell products.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"107 6","pages":"372-377"},"PeriodicalIF":2.5,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24941","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144198426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Standardization of Suspension and Imaging Mass Cytometry Single-Cell Readouts for Clinical Decision Making","authors":"Ruben Casanova,&nbsp;Shuhan Xu,&nbsp;Pierre Bost,&nbsp;Sujana Sivapatham,&nbsp;Andrea Jacobs,&nbsp;Stefanie Engler,&nbsp;Tumor Profiler Consortium,&nbsp;Mitchell P. Levesque,&nbsp;Reinhard Dummer,&nbsp;Bernd Bodenmiller,&nbsp;Stéphane Chevrier","doi":"10.1002/cyto.a.24940","DOIUrl":"10.1002/cyto.a.24940","url":null,"abstract":"<p>Suspension and imaging mass cytometry are single-cell, proteomic-based methods used to characterize tissue composition and structure. Data assessing the consistency of these methods over an extended period of time are still sparse and are needed if mass cytometry-based methods are to be used clinically. Here, we present experimental and computational pipelines developed within the Tumor Profiler clinical study, an observational clinical trial assessing the relevance of cutting-edge technologies in guiding treatment decisions for advanced cancer patients. By using aliquots of frozen antibody panels, batch effects between independent experiments performed within a time frame of 1 year were minimized. The inclusion of well-characterized reference samples allowed us to assess and correct for batch effects. A systematic evaluation of a test tumor sample analyzed in each run showed that our batch correction approach consistently reduced signal variations. We provide an exemplary analysis of a representative patient sample including an overview of data provided to clinicians and potential treatment suggestions. This study demonstrates that standardized suspension and imaging mass cytometry measurements generate robust data that meet clinical requirements for reproducibility and provide oncologists with valuable insights on the biology of patient tumors.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"107 6","pages":"390-403"},"PeriodicalIF":2.5,"publicationDate":"2025-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24940","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144126975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}