基于图像的活细胞分选。
Image-Based Live Cell Sorting.
机构信息
Joint Department of Biomedical Engineering, University of North Carolina, Chapel Hill, NC, and North Carolina State University, Raleigh, NC, USA; Department of Bioengineering, University of Washington, Seattle, WA, USA.
Department of Bioengineering, University of Washington, Seattle, WA, USA.
出版信息
Trends Biotechnol. 2021 Jun;39(6):613-623. doi: 10.1016/j.tibtech.2020.10.006. Epub 2020 Nov 13.
Abstract
Technologies capable of cell separation based on cell images provide powerful tools enabling cell selection criteria that rely on spatially or temporally varying properties. Image-based cell sorting (IBCS) systems utilize microfluidic or microarray platforms, each having unique characteristics and applications. The advent of IBCS marks a new paradigm in which cell phenotype and behavior can be explored with high resolution and tied to cellular physiological and omics data, providing a deeper understanding of single-cell physiology and the creation of cell lines with unique properties. Cell sorting guided by high-content image information has far-reaching implications in biomedical research, clinical medicine, and pharmaceutical development.
摘要
基于细胞图像进行细胞分离的技术为基于随空间或时间变化的特性的细胞选择标准提供了强大的工具。基于图像的细胞分选（IBCS）系统利用微流控或微阵列平台，每个平台都具有独特的特点和应用。IBCS 的出现标志着一个新的范例，其中可以以高分辨率探索细胞表型和行为，并与细胞生理和组学数据相关联，从而更深入地了解单细胞生理学并创建具有独特特性的细胞系。基于高内涵图像信息的细胞分选在生物医学研究、临床医学和药物开发方面具有深远的意义。
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