Paracoccidioidomycosis (PCM) is a systemic mycosis that is diagnosed by visualizing the fungus in clinical samples or by other methods, like serological techniques. However, all PCM diagnostic methods have limitations. The aim of this study was to develop a diagnostic tool for PCM based on Fourier transform infrared (FTIR) spectroscopy. A total of 224 serum samples were included: 132 from PCM patients and 92 constituting the control group (50 from healthy blood donors and 42 from patients with other systemic mycoses). Samples were analyzed by attenuated total reflection (ATR) and a t-test was performed to find differences in the spectra of the two groups. The wavenumbers that had p < 0.05 had their diagnostic potential evaluated using receiver operating characteristic (ROC) curves. The spectral region with the lowest p value was used for variable selection through principal component analysis (PCA). The selected variables were used in a linear discriminant analysis (LDA). In univariate analysis, the ROC curves with the best performance were obtained in the region 1551–1095 cm⁻¹. The wavenumber that had the highest AUC value was 1264 cm⁻¹, achieving a sensitivity of 97.73%, specificity of 76.01%, and accuracy of 94.22%. The total separation of groups was obtained in the PCA performed with a spectral range of 1551–1095 cm⁻¹. LDA performed with the eight wavenumbers with the greatest weight from the group discrimination in the PCA obtained 100% accuracy. The methodology proposed here is simple, fast, and highly accurate, proving its potential to be applied in the diagnosis of PCM. The proposed method is more accurate than the currently known diagnostic methods, which is particularly relevant for a neglected tropical mycosis such as paracoccidioidomycosis.

Leprosy is an infectious disease caused by the Mycobacterium leprae complex. Although the diagnosis of this disease is clinical, additional tests are often needed. One of the most common tests is intradermal smear bacilloscopy, which detects the patient's bacillary load. However, bacilloscopy is an invasive test and its results are subjective. The aim of this study was to propose a methodology based on Fourier transform infrared (FTIR) spectroscopy to predict the bacilloscopic index in the saliva of leprosy patients. A total of 88 saliva samples were included, and the bacilloscopic index of the patients was previously defined by intradermal smear bacilloscopy. The saliva samples were analyzed by attenuated total reflection (ATR)-FTIR; a supervised analysis with partial least squares regression (PLS), after orthogonal signal correction (OSC), was used to predict the bacilloscopic index. The PLS model with three latent variables and one OSC component obtained a coefficient of determination greater than 0.9999 in both the calibration and prediction sets. The model was able to predict the bacilloscopic indexes with a minimum error, demonstrating its robustness. Thus, modeling with ATR/FTIR and multivariate calibration using one OSC component showed high accuracy and reproducibility, overcoming the limitations of intradermal smear bacilloscopy and proving to be a promising method in the clinical management of patients with leprosy.

Paracoccidioidomycosis (PCM), caused by fungi of the genus Paracoccidioides, is the main endemic mycosis in Brazil, with serious social and public-health impacts. Although the state of Rio Grande do Sul in southern Brazil is an area of high endemicity, data on PCM in this state are very sparse. Here, an exhaustive literature search was conducted for PCM cases reported in Rio Grande do Sul, in addition to the environmental occurrence of Paracoccidioides spp. in the state. From 1942 to 2023, 52 studies were found, encompassing a total of 1576 PCM cases. The male : female ratio was 15 : 1, and the most affected age group was 41–60 years. Lesions were reported at 11 different anatomical sites, with a predominance of the lungs and upper aerodigestive tract mucosa. Data such as treatment and mortality were rarely reported. Cases were recorded in 30% of the municipalities in the state, predominantly in the northern region. Regarding the environmental presence of Paracoccidioides spp., anti-P. brasiliensis and anti-P. lutzii antibodies have been identified in several animal species in addition to isolation of the fungi from soil samples. Although a literature search is useful for a basic knowledge of PCM occurrence, the need for epidemiological surveillance of the disease in Rio Grande do Sul is urgent, considering its high endemicity and occurrence in all regions of the state.

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.