Label-Free, Noninvasive Bone Cell Classification by Hyperspectral Confocal Raman Microscopy.

ABSTRACT: Characterizing and identifying cells in multicellular in vitro models remain a substantial challenge. Here, we utilize hyperspectral confocal Raman microscopy and principal component analysis coupled with linear discriminant analysis to form a label-free, noninvasive approach for classifying bone cells and osteosarcoma cells. Through the development of a library of hyperspectral Raman images of the K7M2-wt osteosarcoma cell lines, 7F2 osteoblast cell lines, RAW 264.7 macrophage cell line, and osteoclasts induced from RAW 264.7 macrophages, we built a linear discriminant model capable of correctly identifying each of these cell types. The model was cross-validated using a k-fold cross validation scheme. The results show a minimum of 72% accuracy in predicting cell type. We also utili

SUBMITTER: Piontkowski ZT 

PROVIDER: S-EPMC10900511 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature