Cytometry Part A最新文献

{"title":"Human mesenchymal stem cells increase LLC metastasis and stimulate or decelerate tumor development depending on injection method and cell amount","authors":"Yurii V. Stepanov,&nbsp;Iuliia Golovynska,&nbsp;Galyna Ostrovska,&nbsp;Larysa Pylyp,&nbsp;Taisa Dovbynchuk,&nbsp;Liudmyla I. Stepanova,&nbsp;Oleksandr Gorbach,&nbsp;Volodymyr Shablii,&nbsp;Hao Xu,&nbsp;Liudmyla V. Garmanchuk,&nbsp;Tymish Y. Ohulchanskyy,&nbsp;Junle Qu,&nbsp;Galina I. Solyanik","doi":"10.1002/cyto.a.24814","DOIUrl":"10.1002/cyto.a.24814","url":null,"abstract":"<p>Mesenchymal stem cells (MSCs) being injected into the body can stimulate or decelerate carcinogenesis. Here, the direction of influence of human placenta-derived MSCs (P-MSCs) on the Lewis lung carcinoma (LLC) tumor development and metastatic potential is investigated in C57BL/6 mice depending on the injection method. After intramuscular co-inoculation of LLC and P-MSCs (LLC + P-MSCs), the growth of primary tumor and angiogenesis are slowed down compared to the control LLC on the 15th day. This is explained by the fact of a decrease in the secretion of proangiogenic factors during in vitro co-cultivation of an equal amount of LLC and P-MSCs. When P-MSCs are intravenously (i.v.) injected in the mice with developing LLC (LLC + P-MSCs(i.v.)), the tumor growth and angiogenesis are stimulated on the 15th day. A highly activated secretion of proangiogenic factors by P-MSCs in a similar in vitro model can explain this. In both the models compared to the control on the 23rd day, there is no significant difference in the tumor growth, while angiogenesis remains correspondingly decelerated or stimulated. However, in both the models, the total volume and number of lung metastases constantly increase compared to the control: it is mainly due to small-size metastases for LLC + P-MSCs(i.v.) and larger ones for LLC + P-MSCs. The increase in the rate of LLC cell dissemination after the injection of P-MSCs is explained by the disordered polyploidy and chromosomal instability, leading to an increase in migration and invasion of cancer cells. After LLC + P-MSCs co-inoculation, the tumor cell karyotype has the most complex and heterogeneous chromosomal structure. These findings indicate a bidirectional effect of P-MSCs on the growth of LLC in the early periods after injection, depending on the injection method, and, correspondingly, the number of contacting cells. However, regardless of the injection method, P-MSCs are shown to increase LLC aggressiveness related to cancer-associated angiogenesis and metastasis activation in the long term.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"105 4","pages":"252-265"},"PeriodicalIF":3.7,"publicationDate":"2023-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138458510","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":"Imaging flow cytometry of tumoroids: A new method for studying GPCR expression","authors":"V. Gratio,&nbsp;S. Dayot,&nbsp;S. Benadda,&nbsp;P. Nicole,&nbsp;L. Saveanu,&nbsp;T. Voisin,&nbsp;A. Couvineau","doi":"10.1002/cyto.a.24809","DOIUrl":"10.1002/cyto.a.24809","url":null,"abstract":"<p>Fluorescence confocal microscopy is commonly used to analyze the regulation membrane proteins expression such as G protein-coupled receptors (GPCRs). With this approach, the internal movement of GPCRs within the cell can be observed with a high degree of resolution. However, these microscopy techniques led to complex and time-consuming analysis and did not allow a large population of events to be sampled. A recent approach termed imaging flow cytometry (IFC), which combines flow cytometry and fluorescence microscopy, had two main advantages to study the regulation of GPCRs expression such as orexins receptors (OXRs): the ability (1) to analyze large numbers of cells and; (2) to visualize cell integrity and fluorescent markers localization. Here, we compare these two technologies using the orexin A (OxA) ligand coupled to rhodamine (OxA-rho) to investigate anti-tumoral OX1R expression in human digestive cancers. IFC has been adapted for cancer epithelial adherent cells and also to 3D cell culture tumoroids which partially mimic tumoral structures. In the absence of specific antibody, expression of OX1R is examined in the presence of OxA-rho. 2D-culture of colon cancer cells HT-29 exhibits a maximum level of OX1R internalization induced by OxA with 19% ± 3% colocalizing to early endosomes. In 3D-culture of HT-29 cells, internalization of OX1R/OxA-rho reached its maximum at 60 min, with 30.7% ± 6.4% of OX1R colocalizing with early endosomes. This is the first application of IFC to the analysis of the expression of a native GPCR, OX1R, in both 2D and 3D cultures of adherent cancer cells.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"105 4","pages":"276-287"},"PeriodicalIF":3.7,"publicationDate":"2023-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24809","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138451169","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":"A 19-color single-tube full spectrum flow cytometry assay for the detection of measurable residual disease in acute myeloid leukemia","authors":"Hendrik Fokken,&nbsp;Julian Waclawski,&nbsp;Nadine Kattre,&nbsp;Arnold Kloos,&nbsp;Sebastian Müller,&nbsp;Max Ettinger,&nbsp;Tim Kacprowski,&nbsp;Michael Heuser,&nbsp;Tobias Maetzig,&nbsp;Adrian Schwarzer","doi":"10.1002/cyto.a.24811","DOIUrl":"10.1002/cyto.a.24811","url":null,"abstract":"<p>Multiparameter flow cytometry (MFC) has emerged as a standard method for quantifying measurable residual disease (MRD) in acute myeloid leukemia. However, the limited number of available channels on conventional flow cytometers requires the division of a diagnostic sample into several tubes, restricting the number of cells and the complexity of immunophenotypes that can be analyzed. Full spectrum flow cytometers overcome this limitation by enabling the simultaneous use of up to 40 fluorescent markers. Here, we used this approach to develop a good laboratory practice-conform single-tube 19-color MRD detection assay that complies with recommendations of the European LeukemiaNet Flow-MRD Working Party. We based our assay on clinically-validated antibody clones and evaluated its performance on an IVD-certified full spectrum flow cytometer. We measured MRD and normal bone marrow samples and compared the MRD data to a widely used reference MRD-MFC panel generating highly concordant results. Using our newly developed single-tube panel, we established reference values in healthy bone marrow for 28 consensus leukemia-associated immunophenotypes and introduced a semi-automated dimensionality-reduction, clustering and cell type identification approach that aids the unbiased detection of aberrant cells. In summary, we provide a comprehensive full spectrum MRD-MFC workflow with the potential for rapid implementation for routine diagnostics due to reduced cell requirements and ease of data analysis with increased reproducibility in comparison to conventional FlowMRD routines.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"105 3","pages":"181-195"},"PeriodicalIF":3.7,"publicationDate":"2023-11-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24811","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138175868","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":"Assessment of inter-operator variability in peripheral monocyte subset gating strategy using flow cytometry in patients with suspected acute stroke","authors":"Evelyne Heng,&nbsp;Marie Neuwirth,&nbsp;Floriane Mas,&nbsp;Geneviève Contant,&nbsp;Mikaël Mazighi,&nbsp;Joffrey Feriel,&nbsp;Bertrand Montpellier,&nbsp;Caren Brumpt,&nbsp;Georges Jourdi,&nbsp;Emmanuel Curis,&nbsp;Virginie Siguret","doi":"10.1002/cyto.a.24810","DOIUrl":"10.1002/cyto.a.24810","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Background</h3>\u0000 \u0000 <p>Innovative tools to reliably identify patients with acute stroke are needed. Peripheral monocyte subsets, that is, classical-Mon1, intermediate-Mon2, and non-classical-Mon3, with their activation marker expression analyzed using flow-cytometry (FCM) could be interesting cell biomarker candidates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Aim</h3>\u0000 \u0000 <p>To assess the inter-operator variability in a new peripheral monocyte subset gating strategy using FCM in patients with suspected acute stroke.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>In BOOST-study (“Biomarkers-algOrithm-for-strOke-diagnoSis-and Treatment-resistance-prediction,” NCT04726839), patients ≥18 years with symptoms suggesting acute stroke within the last 24 h were included. Blood was collected upon admission to emergency unit. FCM analysis was performed using the FACS-CANTO-II® flow-cytometer and Flow-Jo™-software. Analyzed markers were CD45/CD91/CD14/CD16 (monocyte backbone) and CD62L/CD11b/HLA-DR/CD86/CCR2/ICAM-1/CX3CR1/TF (activation markers). Inter-operator agreement (starting from raw-data files) was quantified by the measure distribution and, for each patient, the coefficient of variation (CV).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Three operators analyzed 20 patient blood samples. Median inter-operator CVs were below the pre-specified tolerance limits (10% [for Mon1 counts], 20% [Mon2, Mon3 counts], 15% [activation marker median-fluorescence-intensities]). We observed a slight, but systematic, inter-operator effect. Overall, absolute inter-operator differences in fractions of monocyte subsets were &lt;0.03.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>Our gating strategy allowed monocyte subset gating with an acceptable inter-operator variability. Although low, the inter-operator effect should be considered in monocyte data analysis of BOOST-patients.</p>\u0000 </section>\u0000 </div>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"105 3","pages":"171-180"},"PeriodicalIF":3.7,"publicationDate":"2023-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24810","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136396790","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":"Guidelines for establishing a cytometry laboratory","authors":"Anna C. Belkina,&nbsp;Caroline E. Roe,&nbsp;Vera A. Tang,&nbsp;Jessica B. Back,&nbsp;Claudia Bispo,&nbsp;Alexis Conway,&nbsp;Uttara Chakraborty,&nbsp;Kathleen T. Daniels,&nbsp;Gelo de la Cruz,&nbsp;Laura Ferrer-Font,&nbsp;Andrew Filby,&nbsp;David M. Gravano,&nbsp;Michael D. Gregory,&nbsp;Christopher Hall,&nbsp;Christian Kukat,&nbsp;André Mozes,&nbsp;Diana Ordoñez-Rueda,&nbsp;Eva Orlowski-Oliver,&nbsp;Isabella Pesce,&nbsp;Ziv Porat,&nbsp;Nicole J. Poulton,&nbsp;Kristen M. Reifel,&nbsp;Aja M. Rieger,&nbsp;Rachael T. C. Sheridan,&nbsp;Gert Van Isterdael,&nbsp;Rachael V. Walker","doi":"10.1002/cyto.a.24807","DOIUrl":"10.1002/cyto.a.24807","url":null,"abstract":"<p>The purpose of this document is to provide guidance for establishing and maintaining growth and development of flow cytometry shared resource laboratories. While the best practices offered in this manuscript are not intended to be universal or exhaustive, they do outline key goals that should be prioritized to achieve operational excellence and meet the needs of the scientific community. Additionally, this document provides information on available technologies and software relevant to shared resource laboratories. This manuscript builds on the work of Barsky et al. 2016 published in <i>Cytometry Part A</i> and incorporates recent advancements in cytometric technology. A flow cytometer is a specialized piece of technology that require special care and consideration in its housing and operations. As with any scientific equipment, a thorough evaluation of the location, space requirements, auxiliary resources, and support is crucial for successful operation. This comprehensive resource has been written by past and present members of the International Society for Advancement of Cytometry (ISAC) Shared Resource Laboratory (SRL) Emerging Leaders Program https://isac-net.org/general/custom.asp?page=SRL-Emerging-Leaders with extensive expertise in managing flow cytometry SRLs from around the world in different settings including academia and industry. It is intended to assist in establishing a new flow cytometry SRL, re-purposing an existing space into such a facility, or adding a flow cytometer to an individual lab in academia or industry. This resource reviews the available cytometry technologies, the operational requirements, and best practices in SRL staffing and management.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"105 2","pages":"88-111"},"PeriodicalIF":3.7,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/cyto.a.24807","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71520782","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":"Novel phenotypical and functional sub-classification of liver macrophages highlights changes in population dynamics in experimental mouse models.","authors":"Hiroyuki Nakashima, Bradley M Kearney, Azusa Kato, Hiromi Miyazaki, Seigo Ito, Masahiro Nakashima, Manabu Kinoshita","doi":"10.1002/cyto.a.24783","DOIUrl":"10.1002/cyto.a.24783","url":null,"abstract":"<p><p>Liver macrophages are critical components of systemic immune system defense mechanisms. F4/80^high Kupffer cells (KCs) are the predominant liver-resident macrophages and the first immune cells to contact pathogens entering the liver. F4/80^low monocyte-derived macrophages (MoMφs) are essential macrophages that modulate liver immune functions. Here we report a novel method of identifying subpopulations of these two populations using traditional flow cytometry and examine each subpopulation for its putative roles in the pathogenesis of an experimental non-alcoholic steatohepatitis model. Using male C57BL/6 mice, we isolated and analyzed liver non-parenchymal cells by flow cytometry. We identified F4/80^high and F4/80^low macrophage populations and characterized subpopulations using uniform manifold approximation and projection. We identified three subpopulations in F4/80^high macrophages: CD163(+) KCs, CD163(-) KCs, and liver capsular macrophages. CD163(+) KCs had higher phagocytic and bactericidal activities and more complex cellular structures than CD163(-) KCs. We also identified four subpopulations of F4/80^low MoMφs based on Ly6C and MHC class II expression: infiltrating monocytes, pro-inflammatory MoMφs, Ly6C(-) monocytes, and conventional dendritic cells. CCR2 knock-out mice expressed lower levels of these monocyte-derived cells, and the count varied by subpopulation. In high-fat- and cholesterol-diet-fed mice, only one subpopulation, pro-inflammatory MoMφs, significantly increased in count. This indicates that changes to this subpopulation is the first step in the progression to non-alcoholic steatohepatitis. The community can use our novel subpopulation and gating strategy to better understand complex immunological mechanisms in various liver disorders through detailed analysis of these subpopulations.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"902-914"},"PeriodicalIF":3.7,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10414481","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":"flowSim: Near duplicate detection for flow cytometry data.","authors":"Sebastiano Montante, Yixuan Chen, Ryan R Brinkman","doi":"10.1002/cyto.a.24776","DOIUrl":"10.1002/cyto.a.24776","url":null,"abstract":"<p><p>The analysis of large amounts of data is important for the development of machine learning (ML) models. flowSim is the first algorithm designed to visualize, detect and remove highly redundant information in flow cytometry (FCM) training sets to decrease the computational time for training and increase the performance of ML algorithms by reducing overfitting. flowSim performs near duplicate image detection by combining community detection algorithms with the density analysis of the marker expression values. flowSim clustering compared to consensus manual clustering on a dataset composed of 160 images of bivariate FCM data had a mean Adjusted Rand Index of 0.90, demonstrating its efficiency in identifying similar patterns. flowSim selectively discarded near duplicate files in datasets constructed with known redundancy, and removed 92.6% of FCM images in a dataset of over 500,000 drawn from public repositories.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"889-901"},"PeriodicalIF":2.5,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10834853/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10102459","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":"Assessing the performance of the Cell Painting assay across different imaging systems.","authors":"Callum Tromans-Coia, Nasim Jamali, Hamdah Shafqat Abbasi, Kenneth A Giuliano, Mai Hagimoto, Kevin Jan, Erika Kaneko, Stefan Letzsch, Alexander Schreiner, Jonathan Z Sexton, Mahomi Suzuki, O Joseph Trask, Mitsunari Yamaguchi, Fumiki Yanagawa, Michael Yang, Anne E Carpenter, Beth A Cimini","doi":"10.1002/cyto.a.24786","DOIUrl":"10.1002/cyto.a.24786","url":null,"abstract":"<p><p>Quantitative microscopy is a powerful method for performing phenotypic screens from which image-based profiling can extract a wealth of information, termed profiles. These profiles can be used to elucidate the changes in cellular phenotypes across cell populations from different patient samples or following genetic or chemical perturbations. One such image-based profiling method is the Cell Painting assay, which provides morphological insight through the imaging of eight cellular compartments. Here, we examine the performance of the Cell Painting assay across multiple high-throughput microscope systems and find that all are compatible with this assay. Furthermore, we determine independently for each microscope system the best performing settings, providing those who wish to adopt this assay an ideal starting point for their own assays. We also explore the impact of microscopy setting changes in the Cell Painting assay and find that few dramatically reduce the quality of a Cell Painting profile, regardless of the microscope used.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"915-926"},"PeriodicalIF":2.5,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10841730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41103665","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-095: 40-Color spectral flow cytometry delineates all major leukocyte populations in murine lymphoid tissues.","authors":"Aris J Kare, Lisa Nichols, Ricardo Zermeno, Marina N Raie, Spencer K Tumbale, Katherine W Ferrara","doi":"10.1002/cyto.a.24788","DOIUrl":"10.1002/cyto.a.24788","url":null,"abstract":"<p><p>High-dimensional immunoprofiling is essential for studying host response to immunotherapy, infection, and disease in murine model systems. However, the difficulty of multiparameter panel design combined with a lack of existing murine tools has prevented the comprehensive study of all major leukocyte phenotypes in a single assay. Herein, we present a 40-color flow cytometry panel for deep immunophenotyping of murine lymphoid tissues, including the spleen, blood, Peyer's patches, inguinal lymph nodes, bone marrow, and thymus. This panel uses a robust set of surface markers capable of differentiating leukocyte subsets without the use of intracellular staining, thus allowing for the use of cells in downstream functional experiments or multiomic analyses. Our panel classifies T cells, B cells, natural killer cells, innate lymphoid cells, monocytes, macrophages, dendritic cells, basophils, neutrophils, eosinophils, progenitors, and their functional subsets by using a series of co-stimulatory, checkpoint, activation, migration, and maturation markers. This tool has a multitude of systems immunology applications ranging from serial monitoring of circulating blood signatures to complex endpoint analysis, especially in pre-clinical settings where treatments can modulate leukocyte abundance and/or function. Ultimately, this 40-color panel resolves a diverse array of immune cells on the axes of time, tissue, and treatment, filling the niche for a modern tool dedicated to murine immunophenotyping.</p>","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":" ","pages":"839-850"},"PeriodicalIF":2.5,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10843696/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41125768","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":"Issue Information ‐ Editorial Policy","authors":"","doi":"10.1002/cyto.a.24646","DOIUrl":"https://doi.org/10.1002/cyto.a.24646","url":null,"abstract":"","PeriodicalId":11068,"journal":{"name":"Cytometry Part A","volume":"14 1","pages":""},"PeriodicalIF":3.7,"publicationDate":"2023-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139300022","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}