Navegando por Assunto "Diagnosis"

Agora exibindo 1 - 2 de 2
  • Imagem de Miniatura
    Item
    Plasmatic and salivary biomarkers for early diagnosis of Autism Spectrum Disorder: a systematic review
    (CDRR Editors) Pinto, Mayara Moniz Vieira; Arisawa, Emília Angela Lo Schiavo; Martins, Rodrigo Alvaro Brandão Lopes; Raniero, Leandro José
    Autistic Spectrum Disorder (ASD) is considered a neurological development disorder characterized by different degrees of deficit in communication, social interaction, and learning, accompanied by repetitive and stereotyped patterns of behavior. ASD diagnosis is extremely complex due to the still unknown etiopathology, the diversity of symptoms presented by the individuals, and it is carried out solely from clinical observations of the individual's behavior. This study aims to review the main plasma and salivary biomarkers currently studied for the early diagnosis of ASD. For this systematic literature review, we used the online data directory and database “Google Scholar” and “Publish Medliner” (PubMed), respectively, with the descriptors: “Autism”, “Biomarker”, “Diagnostic”, “Saliva”, and “Plasma”. We selected 564 studies in PubMed and 185 in Google Scholar, by screening the titles. After reading the abstracts, we excluded 647 studies, either due to irrelevance or because they were review articles, genetics studies or did not use plasma or saliva samples. The remaining 102 original studies were evaluated in full, and 83 were excluded. Thus, nineteen complete articles that met the inclusion criteria were included in the qualitative analysis. Results identified Cortisol, glutamate/GABA, glutathione, Lipid peroxidation, markers of oxidative stress, mitochondrial dysfunction, and pro-inflammatory cytokines, especially IL-6, as the main plasma and salivary biomarkers currently studied for the early diagnosis of ASD. However, considering that several results were controversial and inconclusive, further studies are needed to validate specific biomarkers as diagnostic tools. The current findings encourage studies that are controlled, multicentric, prospective, and of greater diagnostic precision.
  • Imagem de Miniatura
    Item
    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.