Abstract
Mast cell (MC) degranulation is an important step in the healing process. In this study, silver-nanoparticles-based surface-enhanced Raman spectroscopy (SERS) was used to investigate the spectral characteristics of degranulation of MCs activated by low-intensity laser. The significant spectral changes, such as Raman peak intensities, suggested the concentration variation of some degranulated substances. The Raman intensity ratio of 799-554 cm(-)(1) could be used as a potential internal indicator for the degranulation degree of MCs. Principal component analysis (PCA) was employed to reduce the high dimension of spectra into a few principal components (PCs) while retaining the most diagnostically significant information for sample differentiation. Using the diagnostically significant PC scores (P < 0.05), linear discriminate analysis (LDA) was applied to identify different cell degranulation groups with high sensitivity, specificity and accuracy. This exploratory work demonstrates that SERS technique combined with a PCA-LDA algorithm possesses great potential for developing a label-free, comprehensive, non-invasive and accurate method for measuring MC degranulation.