ArticleBiomedical optics express2016
Light-sheet-based 2D light scattering cytometry for label-free characterization of senescent cells.
Article in Biomedical optics express, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Dynamic light scattering microscopy sensing mitochondria dynamics for label-free detection of triple-negative breast cancer enhanced by deep learning.Biomedical optics express · 2023Article
- Online Monitoring of the Concentrations of Amorphous and Crystalline Mesoscopic Species Present in Solution.Crystal growth & design · 2022Article
- Investigation of different wavelengths for scattering-based light sheet microscopy.Biomedical optics express · 2022Article
- Scattering Inversion Study for Suspended Label-Free Lymphocytes with Complex Fine Structures.BME frontiers · 2022Article
- Label-free light-sheet microfluidic cytometry for the automatic identification of senescent cells.Biomedical optics express · 2018Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A light-sheet-based 2D light scattering cytometer is developed for label-free characterization of senescent cells. The light-sheet provides an illumination beam with controlled thickness for single cell excitation, and 2D light scattering patterns are obtained by using a defocused imaging method. The principle of this cytometer is validated by distinguishing microspheres with submicron resolution. Automatic classification of senescent and normal cells is achieved at single cell level by using the support vector machine (SVM) algorithm, where a sensitivity of 89.1% and a specificity of 96.4% are obtained. Our results suggest that the light-sheet-based 2D light scattering label-free cytometry has the capability to perform size differentiation of beads with submicron resolution and to classify different groups of cells without fluorescent labeling, showing the potential for clinical diagnosis of senescence-related diseases.
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