Department of Anatomy and Cell Biology, University of Illinois at Chicago, Chicago, IL, USA.
Department of Bioengineering, University of Colorado Denver, Aurora, CO, USA.
Methods Mol Biol. 2022;2413:193-209. doi: 10.1007/978-1-0716-1896-7_20.
Raman spectroscopy using feature selection schemes has considerable advantages over gas chromatography for the analysis of fatty acids' composition changes. Here, we introduce an educational methodology to demonstrate the potential of micro-Raman spectroscopy to determine with high accuracy the unsaturation or saturation degrees and composition changes of the fatty acids found in the lipid droplets of the LNCaP prostate cancer cells that were treated with various fatty acids. The methodology uses highly discriminatory wavenumbers among fatty acids present in the sample selected by using the Support Vector Machine algorithm.
拉曼光谱结合特征选择方案在分析脂肪酸组成变化方面比气相色谱法具有明显优势。在这里,我们介绍了一种教育方法,以展示微拉曼光谱在确定用不同脂肪酸处理的 LNCaP 前列腺癌细胞的脂滴中脂肪酸的不饱和或饱和程度以及组成变化方面具有高精度的潜力。该方法使用支持向量机算法选择的样品中存在的具有高度区分性的波数。