Abstract
Paracoccidioidomycosis (PCM) is a systemic mycosis caused by fungi of the genus Paracoccidioides. Serological tests are auxiliary in the diagnosis of PCM. However, the lack of standardization is a central problem in serodiagnosis and antibody titration. The objective of this study was to propose a methodology based on Fourier transform infrared spectroscopy (FTIR) for predicting antibody titers in patients with PCM. A total of 118 serum samples from patients with PCM were included, for which antibody titration using double immunodiffusion (DID) was previously performed. Serum samples were analyzed by attenuated total reflection (ATR)-FTIR and a supervised analysis with partial least squares regression (PLS) was used to predict the antibody titers. The PLS model with two latent variables and with the use of one orthogonal signal correction (OSC) showed a determination coefficient (R2) higher than 0.9999 for both the calibration and prediction set. The model was able to predict the antibody titers from patients with PCM with a minimal error. Therefore, modeling with FTIR/ATR and multivariate calibration proved to be a fast and highly accurate method for antibody titration, replacing the need for antigen production and performance of traditional serological tests.
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