Abstract
A home-made near-infrared laser tweezers Raman spectroscopy (LTRS) system was applied to detect hemoglobin variation in red blood cells (RBCs) from diabetes without exogenous labeling. Results showed significant spectral differences existed between the diabetic and normal RBCs, including the peaks dominated by protein components (e.g. 1003 cm-1) and heme groups (e.g. 753 cm-1) in RBCs, and accurate classification results for diabetes detection were obtained by linear discriminant analysis with 100% sensitivity (i.e. no false negatives in the study). This work indicated the great promise of LTRS as a label-free RBC analytical tool for improving the accurate detection of type II diabetes.
Highlights
Diabetes has become an important public health problem recently with an estimated 422 million adults living with it in the world [1]
HbA1c test is conducted by assay techniques, including immunoassay, boronated affinity chromatography (BAC), high performance liquid chromatography (HPLC) and so on [7, 8]
The principal component analysis and linear discriminant analysis (PCA-LDA) multivariate methods are utilized to analyze and discriminate the red blood cells (RBCs) spectra acquired from the two groups
Summary
Diabetes has become an important public health problem recently with an estimated 422 million adults living with it in the world [1]. HbA1c test is conducted by assay techniques, including immunoassay, boronated affinity chromatography (BAC), high performance liquid chromatography (HPLC) and so on [7, 8] These methods have certain inadequacies, such as the long time for the analysis, the complicated operation for cell lysis and antibody-based labeling, and the need for invasive exogenous reagent and big sample volume [8]. The principal component analysis and linear discriminant analysis (PCA-LDA) multivariate methods are utilized to analyze and discriminate the RBCs spectra acquired from the two groups This primary study may develop a reagent-free and reliable method for type II diabetes screening, which can be performed on micro-sample volume with the need for little or no sample preparation
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