Broadband CARS Hyperspectral Classification of Single Immune Cells.

宽带CARS高光谱技术对单个免疫细胞进行分类

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作者:Muddiman Ryan, Harkin Sarah, Butler Marion, Hennelly Bryan
Broadband CARS is a coherent Raman scattering technique that provides access to the full biological vibrational spectrum within milliseconds, facilitating the recording of widefield hyperspectral Raman images. In this work, BCARS hyperspectral images of unstained cells from two different cell lines of immune lineage (T cell [Jurkat] and pDCs [CAL-1]) were recorded and analyzed using multivariate statistical algorithms in order to determine the spectral differences between the cells. A classifier was trained which could distinguish the known cells with a 97% out-of-bag accuracy. The classifier was then applied to unlabeled samples containing a mixture of the two cell types on the same coverslip. This work demonstrates single-cell analysis of pDCs (CAL-1) and T cells (Jurkat) using BCARS. This approach enables an initial validation of cellular classification. We further demonstrate the capability of BCARS cell classification using single spectra of 5 ms acquisition time.

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