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Updated: Jan 23, 2026

Combining Raman Imaging and Multivariate Analysis to Visualize Lignin, Cellulose, and Hemicellulose in the Plant Cell Wall
Published on: June 10, 2017
Label-free Raman imaging of live osteosarcoma cells with multivariate analysis
Jie Li1,2, Jie Qin3, Xu Zhang1,2
1Institute of Photonics and Photon-Technology, Northwest University, #229 North Taibai Road, Xi'an, 710069, Shaanxi, China.
Abstract:
Confocal Raman microspectral imaging (CRMI) is an advanced cell-imaging method that maps endogenous molecular compositions with their unique spectral fingerprint indicators. The aim of this work was to provide a visualized understanding of subcellular features of live osteosarcoma cells using a 532-nm laser excitation without the use of dyes or molecular probes. Both malignant osteoblast and spindle osteosarcoma cells derived from the BALB/c mouse osteosarcoma cell line K7M2 were investigated in this work. After preprocessing the obtained spectral dataset, K-means cluster analysis (KCA) is employed to reconstruct Raman spectroscopic maps of single biological cells by identifying regions of the cellular membrane, cytoplasm, organelles, and nucleus with their corresponding mean spectra. Principal component analysis (PCA) was further employed to indicate variables of significant influence on the separation of the spectra of each cellular component. The biochemical components of the two cell types were then extracted by showing the spectral and distribution features attributed to proteins, lipids, and DNA. Using this standardized CRMI technique and multivariate analysis approaches, the results obtained could be a sound foundation for a typical Raman imaging protocol of live cellular biomedical analysis.
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