Image-Based Live Cell Sorting.

Autor: LaBelle CA; 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., Massaro A; Department of Bioengineering, University of Washington, Seattle, WA, USA., Cortés-Llanos B; Department of Bioengineering, University of Washington, Seattle, WA, USA., Sims CE; Department of Bioengineering, University of Washington, Seattle, WA, USA; Department of Medicine, University of Washington, Seattle, WA, USA., Allbritton NL; Department of Bioengineering, University of Washington, Seattle, WA, USA. Electronic address: nlallbr@uw.edu.
Jazyk: angličtina
Zdroj: Trends in biotechnology [Trends Biotechnol] 2021 Jun; Vol. 39 (6), pp. 613-623. Date of Electronic Publication: 2020 Nov 13.
DOI: 10.1016/j.tibtech.2020.10.006
Abstrakt: 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.
(Copyright © 2020 Elsevier Ltd. All rights reserved.)
Databáze: MEDLINE
Externí odkaz: