1. Label-free image-encoded microfluidic cell sorter with a scanning Bessel beam
- Author
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Yu-Hwa Lo, Ian Lian, Zunming Zhang, Bien Gutierrez, Chi-Yang Tseng, Rui Tang, Sung Hwan Cho, Lauren Waller, Ivan Gagne, Xinyu Chen, and Jiajie Chen
- Subjects
Depth of focus ,Photomultiplier ,Materials science ,Computer Networks and Communications ,business.industry ,Detector ,Sorting ,Articles ,Cell sorting ,Laser ,Atomic and Molecular Physics, and Optics ,law.invention ,TA1501-1820 ,Cardinal point ,Optics ,law ,Bessel beam ,Applied optics. Photonics ,business - Abstract
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.
- Published
- 2021