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K-means clustering of coherent Raman spectra from extracellular vesicles visualized by label-free multiphoton imaging.
Optics Letters ( IF 3.1 ) Pub Date : 2020-06-26 , DOI: 10.1364/ol.395838
Yi Sun , Ethan W. Chen , Jalen Thomas , Yuan Liu , Haohua Tu , Stephen A. Boppart

Extracellular vesicles (EVs) have emerged as potential biomarkers in cancer research and for clinical diagnosis. Little is known, however, about their spatial distributions in tissue and the different subpopulations that may exist. Here we report the use of label-free nonlinear optical imaging techniques to provide spatially resolved chemical information of EVs within untreated tissues. A multimodal nonlinear optical imaging system incorporating multiphoton autofluorescence and hyperspectral coherent anti-Stokes Raman scattering (CARS) imaging was built to visualize the spatial tissue distribution and probe the spectra of EVs. K-means clustering is performed on the CARS spectra from EVs in rat mammary tissues and human breast tumor tissue to reveal both the spatial distribution of EV clusters and their different chemical signatures. Correlations are identified between EV clusters and metabolic information.

中文翻译:

通过无标记多光子成像可视化的细胞外囊泡相干拉曼光谱的 K 均值聚类。

细胞外囊泡(EV)已成为癌症研究和临床诊断中的潜在生物标志物。然而,人们对它们在组织中的空间分布以及可能存在的不同亚群知之甚少。在这里,我们报告使用无标记非线性光学成像技术来提供未处理组织内 EV 的空间分辨化学信息。建立了结合多光子自发荧光和高光谱相干反斯托克斯拉曼散射(CARS)成像的多模态非线性光学成像系统,以可视化空间组织分布并探测电动汽车的光谱。对大鼠乳腺组织和人类乳腺肿瘤组织中 EV 的 CARS 光谱进行 K 均值聚类,以揭示 EV 簇的空间分布及其不同的化学特征。确定了 EV 簇和代谢信息之间的相关性。
更新日期:2020-07-02
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