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Raman image-activated cell sorting. | LitMetric

AI Article Synopsis

  • Recent advancements in imaging technologies, like image-activated cell sorting and imaging-based cell picking, have enhanced our understanding of biological systems over the past decade.
  • Traditional methods often depend on fluorescent labeling for identifying cellular characteristics, which can be limited and indirect.
  • The new approach demonstrated involves Raman image-activated cell sorting that uses ultrafast stimulated Raman scattering (SRS) microscopy to directly analyze single live cells without fluorescent labels, allowing for real-time sorting of various cell types at high speeds.

Article Abstract

The advent of image-activated cell sorting and imaging-based cell picking has advanced our knowledge and exploitation of biological systems in the last decade. Unfortunately, they generally rely on fluorescent labeling for cellular phenotyping, an indirect measure of the molecular landscape in the cell, which has critical limitations. Here we demonstrate Raman image-activated cell sorting by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping. Specifically, the technology enables real-time SRS-image-based sorting of single live cells with a throughput of up to ~100 events per second without the need for fluorescent labeling. To show the broad utility of the technology, we show its applicability to diverse cell types and sizes. The technology is highly versatile and holds promise for numerous applications that are previously difficult or undesirable with fluorescence-based technologies.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7351993PMC
http://dx.doi.org/10.1038/s41467-020-17285-3DOI Listing

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