用流式细胞术评估疑似急性卒中患者外周血单核细胞亚群门控策略的操作者间变异性。

IF 2.5 4区 生物学 Q3 BIOCHEMICAL RESEARCH METHODS Cytometry Part A Pub Date : 2023-11-16 DOI:10.1002/cyto.a.24810
Evelyne Heng, Marie Neuwirth, Floriane Mas, Geneviève Contant, Mikaël Mazighi, Joffrey Feriel, Bertrand Montpellier, Caren Brumpt, Georges Jourdi, Emmanuel Curis, Virginie Siguret
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引用次数: 0

摘要

背景:需要创新的工具来可靠地识别急性脑卒中患者。外周血单核细胞亚群,即经典- mon1、中间- mon2和非经典- mon3,利用流式细胞术(FCM)分析它们的激活标记表达可能是有趣的细胞生物标记候选者。方法:在boost研究(“脑卒中诊断和治疗抵抗预测的生物标志物算法”,NCT04726839)中,≥18岁且在过去24小时内出现急性脑卒中症状的患者被纳入研究对象。在进入急诊室时采集了血液。FCM分析使用FACS-CANTO-II®流式细胞仪和Flow-Jo™-软件进行。分析的标记为CD45/CD91/CD14/CD16(单核细胞骨干)和CD62L/CD11b/HLA-DR/CD86/CCR2/ICAM-1/CX3CR1/TF(激活标记)。操作者之间的一致性(从原始数据文件开始)通过测量分布和每个患者的变异系数(CV)来量化。结果:3名操作员分析了20例患者的血液样本。操作者间的中位数cv低于预先规定的耐受限度(10% [Mon1计数],20% [Mon2, Mon3计数],15%[激活标记中位荧光强度])。我们观察到一种轻微但系统的操作员间效应。结论:我们的门控策略允许单核细胞亚群门控具有可接受的操作员间可变性。虽然低,但在boost患者的单核细胞数据分析中应考虑操作者间效应。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Assessment of inter-operator variability in peripheral monocyte subset gating strategy using flow cytometry in patients with suspected acute stroke

Background

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.

Aim

To assess the inter-operator variability in a new peripheral monocyte subset gating strategy using FCM in patients with suspected acute stroke.

Methods

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).

Results

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 <0.03.

Conclusion

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.

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来源期刊
Cytometry Part A
Cytometry Part A 生物-生化研究方法
CiteScore
8.10
自引率
13.50%
发文量
183
审稿时长
4-8 weeks
期刊介绍: Cytometry Part A, the journal of quantitative single-cell analysis, features original research reports and reviews of innovative scientific studies employing quantitative single-cell measurement, separation, manipulation, and modeling techniques, as well as original articles on mechanisms of molecular and cellular functions obtained by cytometry techniques. The journal welcomes submissions from multiple research fields that fully embrace the study of the cytome: Biomedical Instrumentation Engineering Biophotonics Bioinformatics Cell Biology Computational Biology Data Science Immunology Parasitology Microbiology Neuroscience Cancer Stem Cells Tissue Regeneration.
期刊最新文献
Issue Information - TOC Volume 105A, Number 12, December 2024 Cover Image Autofluorescence lifetime flow cytometry rapidly flows from strength to strength. Flow cytometry-based method to detect and separate Mycoplasma hyorhinis in cell cultures. The consequence of mismatched buffers in purity checks when spectral cell sorting
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