Featuring few essential Raman spectroscopic signatures between heterogeneous cells.

Abstract

Here we demonstrate it is instructive to quantify cell Raman spectroscopy by sparse regularization. To be able to extract the specific spectral differences in a heterogeneous cell system with great spectroscopic similarities derived from many common biomolecular components, the maximum information entropy probability was proposed and exemplified by identifying normal lymphocytes from leukemia cells. The essential spectroscopic features were observed to locate at three Raman peaks whose spectral signatures were commensurate. The applicability of the extracted features was acknowledged by that the predicted identification accuracy of up to 93% was still achieved when only two peaks were loaded into decision tree model, which may provide the possibility of a clinically rapid hematological malignancy detection.