Abstract

Primary pancreatic α, β, δ, and pancreatic polypeptide (PP) cells are reliable cell models for diabetes research. However, the separation and purification of these cells in living conditions remains an obstacle for researchers. The interaction of visible light with cellular molecules can produce Raman scattering, which can be analyzed to obtain cellular intrinsic molecular fingerprints. It has been speculated that primary pancreatic α, β, δ, and PP cells can be identified and separated from each other according to their spectral differences. To test this hypothesis, Raman spectra detection was performed on rat islet cells. Single islet cells identified by Raman scattering under living conditions were verified using immunohistochemistry. Thus, Raman data were acquired from a pure line of islet cells as a training sample and then used to establish the discriminant function. Then, using the principal component analysis–linear discriminate analysis (PCA-LDA) method, the four types of islet cells could be identified and discriminated by Raman spectroscopy. This study provides a label-free and noninvasive method for discriminating islet cell types in a randomly distributed mixed islet cell population via their physical properties rather than by using antibodies or fluorescence labeling.

© 2018 The Author(s)

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