Navegando por Autor "Bhattacharjee, Tanmoy"

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    Biochemical changes in Leishmania braziliensis after photodynamic therapy with methylene blue assessed by the Fourier transform infrared spectroscopy
    (Springer Nature Link) Sakane, Kumiko Koibuchi; Bhattacharjee, Tanmoy; Fagundes, Jaciara; Marcolino, Luciana Maria Cortez; Ferreira, Isabelle; Pinto, Juliana Guerra; Ferreira-Strixino, Juliana
    Photodynamic therapy (PDT) with photosensitizer methylene blue was applied to Leishmania braziliensis, and Fourier transform infrared (FTIR) spectroscopy was used to study biochemical changes in the parasite after PDT in comparison to untreated (C), only irradiation (I), and only photosensitizer (PS). Spectral analysis suggests increase in lipids, proteins, and protein secondary structures in PDT compared with C and decrease in nucleic acids and carbohydrates. Interestingly, these trends are different from PDT of Leishmania major species, wherein lipids decrease; there are minimal changes in secondary structures and increase in nucleic acids and carbohydrates. The study thus suggests possibility of different biomolecular players/pathways in PDT-induced death of L. braziliensis and L. major.
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    Saliva FTIR Spectra and Machine Learning for Autism Spectrum Disorder Diagnosis-Preliminary Study
    (IEEE) Pinto, Mayara Moniz Vieira; Arisawa, Emilia Angela Lo Schiavo; Raniero, Leandro José; Bhattacharjee, Tanmoy
    The diagnosis of Autism Spectrum Disorder (ASD) remains a challenge due to the lack of specific tests and biological markers. ASD is a neurodevelopmental disorder that affects in- dividuals throughout their lives, and its diagnosis allows access to treatments that improve their prognosis. Saliva analysis by Fourier Transform Infrared Spectroscopy (FTIR), which was not previ- ously reported, appears to be a promising diagnostic tool for ASD. This study acquired spectra from samples of 19 ASD and 19 control children. Spectral signatures suggest the dominance of protein secondary structures, β-pleated sheet and α-helix structures in ASD and control children, respectively. Support Vector Machine (SVM) gave the best diagnosis, with sensitivity, precision, and specificity being 92%, 94%, and 95%, respectively. Shapley values analysis to understand the impact of spectral features on the SVM classifier identified β-pleated and β-turn sheets as responsible for classification. Results indicate the potential of saliva-based FTIR for autism diagnosis, warranting a large-scale trial.