Abstract
A statistical method based on Raman spectroscopy for the screening of immunoglobulin M (IgM) in dengue virus (DENV) infected human sera is presented. In total, 108 sera samples were collected and their antibody indexes (AI) for IgM were determined through enzyme-linked immunosorbent assay (ELISA). Raman spectra of these samples were acquired using a 785 nm wavelength excitation laser. Seventy-eight Raman spectra were selected randomly and unbiasedly for the development of a statistical model using partial least square (PLS) regression, while the remaining 30 were used for testing the developed model. An R-square (r2) value of 0.929 was determined using the leave-one-sample-out (LOO) cross validation method, showing the validity of this model. It considers all molecular changes related to IgM concentration, and describes their role in infection. A graphical user interface (GUI) platform has been developed to run a developed multivariate model for the prediction of AI of IgM for blindly tested samples, and an excellent agreement has been found between model predicted and clinically determined values. Parameters like sensitivity, specificity, accuracy, and area under receiver operator characteristic (ROC) curve for these tested samples are also reported to visualize model performance.
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