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Label-free image-encoded microfluidic cell sorter with a scanning Bessel beam

The microfluidic-based, label-free image-guided cell sorter offers a low-cost, high information content, and disposable solution that overcomes many limitations in conventional cell sorters. However, flow confinement for most microfluidic devices is generally only one-dimensional using sheath flow....

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Detalles Bibliográficos
Autores principales: Chen, Xinyu, Waller, Lauren, Chen, Jiajie, Tang, Rui, Zhang, Zunming, Gagne, Ivan, Gutierrez, Bien, Cho, Sung Hwan, Tseng, Chi-Yang, Lian, Ian Y., Lo, Yu-Hwa
Formato: Online Artículo Texto
Lenguaje:English
Publicado: AIP Publishing LLC 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8259130/
https://www.ncbi.nlm.nih.gov/pubmed/34263031
http://dx.doi.org/10.1063/5.0051354
Descripción
Sumario:The microfluidic-based, label-free image-guided cell sorter offers a low-cost, high information content, and disposable solution that overcomes many limitations in conventional cell sorters. However, flow confinement for most microfluidic devices is generally only one-dimensional using sheath flow. As a result, the equilibrium distribution of cells spreads beyond the focal plane of commonly used Gaussian laser excitation beams, resulting in a large number of blurred images that hinder subsequent cell sorting based on cell image features. To address this issue, we present a Bessel–Gaussian beam image-guided cell sorter with an ultra-long depth of focus, enabling focused images of >85% of passing cells. This system features label-free sorting capabilities based on features extracted from the output temporal waveform of a photomultiplier tube (PMT) detector. For the sorting of polystyrene beads, SKNO1 leukemia cells, and Scenedesmus green algae, our results indicate a sorting purity of 97%, 97%, and 98%, respectively, showing that the temporal waveforms from the PMT outputs have strong correlations with cell image features. These correlations are also confirmed by off-line reconstructed cell images from a temporal–spatial transformation algorithm tailored to the scanning Bessel–Gaussian beam.