分类
单元格排序
微流控
鉴定(生物学)
计算机视觉
人工智能
化学
细胞仪
计算机科学
生物医学工程
纳米技术
细胞
工程类
材料科学
生物
生物化学
植物
程序设计语言
作者
Yu Wang,Dong-Fei Wang,Huifeng Wang,Jianwei Wang,Jian‐Zhang Pan,Xiaogang Guo,Qun Fang
出处
期刊:Talanta
[Elsevier]
日期:2021-01-23
卷期号:226: 122136-122136
被引量:13
标识
DOI:10.1016/j.talanta.2021.122136
摘要
The identification, sorting and analysis of rare target single cells in human blood has always been a clinically meaningful medical challenge. Here, we developed a microfluidic robot platform for sorting specific rare cells from complex clinical blood samples based on machine vision-based image identification, liquid handling robot and droplet-based microfluidic techniques. The robot integrated a cell capture and droplet generation module, a laser-induced fluorescence imaging module, a target cell identification and data analysis module, and a system control module, which could automatically achieve the scanning imaging of cell array, cell identification, capturing, and droplet generation of rare target cells from blood samples containing large numbers of normal cells. Based on the robot platform, a novel “gold panning” multi-step sorting strategy was proposed to achieve the sorting of rare target cells in large-scale cell samples with high operation efficiency and high sorting purity (>90%). The robot platform and the multi-step sorting strategy were applied in the sorting of circulating endothelial progenitor cells (CEPCs) in human blood to demonstrate their feasibility and application potential in the sorting and analysis of rare specific cells. Approximately 1,000 CEPCs were automatically identified from 3,000,000 blood cells at a scanning speed of ca. 4,000 cells/s, and 20 25-nL droplets containing single CEPCs were generated.
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