Salivary Detection of Zika Virus Infection Using ATR-FTIR Spectroscopy Coupled with Machine Learning Algorithms and Univariate Analysis: A Proof-of-Concept Animal Study

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Autor(es): dc.contributorUniversidade Federal de Uberlândia (UFU)-
Autor(es): dc.contributorUniversity Center of Triangle (UNITRI)-
Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.creatorOliveira, Stephanie Wutke-
Autor(es): dc.creatorCardoso-Sousa, Leia-
Autor(es): dc.creatorGeorjutti, Renata Pereira-
Autor(es): dc.creatorShimizu, Jacqueline Farinha-
Autor(es): dc.creatorSilva, Suely-
Autor(es): dc.creatorCaixeta, Douglas Carvalho-
Autor(es): dc.creatorGuevara-Vega, Marco-
Autor(es): dc.creatorCunha, Thúlio Marquez-
Autor(es): dc.creatorCarneiro, Murillo Guimarães-
Autor(es): dc.creatorGoulart, Luiz Ricardo-
Autor(es): dc.creatorJardim, Ana Carolina Gomes-
Autor(es): dc.creatorSabino-Silva, Robinson-
Data de aceite: dc.date.accessioned2025-08-21T21:33:50Z-
Data de disponibilização: dc.date.available2025-08-21T21:33:50Z-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-07-29-
Data de envio: dc.date.issued2023-04-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.3390/diagnostics13081443-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/247259-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/247259-
Descrição: dc.descriptionZika virus (ZIKV) diagnosis is currently performed through an invasive, painful, and costly procedure using molecular biology. Consequently, the search for a non-invasive, more cost-effective, reagent-free, and sustainable method for ZIKV diagnosis is of great relevance. It is critical to prepare a global strategy for the next ZIKV outbreak given its devastating consequences, particularly in pregnant women. Attenuated total reflection–Fourier transform infrared (ATR-FTIR) spectroscopy has been used to discriminate systemic diseases using saliva; however, the salivary diagnostic application in viral diseases is unknown. To test this hypothesis, we intradermally challenged interferon-gamma gene knockout C57/BL6 mice with ZIKV (50 µL,105 FFU, n = 7) or vehicle (50 µL, n = 8). Saliva samples were collected on day three (due to the peak of viremia) and the spleen was also harvested. Changes in the salivary spectral profile were analyzed by Student’s t test (p < 0.05), multivariate analysis, and the diagnostic capacity by ROC curve. ZIKV infection was confirmed by real-time PCR of the spleen sample. The infrared spectroscopy coupled with univariate analysis suggested the vibrational mode at 1547 cm−1 as a potential candidate to discriminate ZIKV and control salivary samples. Three PCs explained 93.2% of the cumulative variance in PCA analysis and the spectrochemical analysis with LDA achieved an accuracy of 93.3%, with a specificity of 87.5% and sensitivity of 100%. The LDA-SVM analysis showed 100% discrimination between both classes. Our results suggest that ATR-FTIR applied to saliva might have high accuracy in ZIKV diagnosis with potential as a non-invasive and cost-effective diagnostic tool.-
Descrição: dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)-
Descrição: dc.descriptionFundação de Amparo à Pesquisa do Estado de Minas Gerais (FAPEMIG)-
Descrição: dc.descriptionInnovation Center in Salivary Diagnostic and Nanobiotechnology Department of Physiology Institute of Biomedical Sciences Federal University of Uberlandia-
Descrição: dc.descriptionCollege of Dentistry University Center of Triangle (UNITRI)-
Descrição: dc.descriptionLaboratory of Antiviral Research Institute of Biomedical Science Federal University of Uberlandia-
Descrição: dc.descriptionInstitute of Biosciences Humanities and Exact Sciences São Paulo State University-
Descrição: dc.descriptionSchool of Medicine Federal University of Uberlandia (UFU)-
Descrição: dc.descriptionFaculty of Computing Federal University of Uberlandia (UFU)-
Descrição: dc.descriptionInstitute of Biotechnology Federal University of Uberlandia-
Descrição: dc.descriptionInstitute of Biosciences Humanities and Exact Sciences São Paulo State University-
Descrição: dc.descriptionCNPq: 409157/2022-8-
Descrição: dc.descriptionFAPEMIG: APQ-00476-20-
Descrição: dc.descriptionFAPEMIG: APQ-01487-22-
Descrição: dc.descriptionFAPEMIG: APQ-02148-21-
Descrição: dc.descriptionFAPEMIG: APQ-03613-17-
Descrição: dc.descriptionFAPEMIG: APQ-04686-22-
Idioma: dc.languageen-
Relação: dc.relationDiagnostics-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectATR-FTIR-
Palavras-chave: dc.subjectdiagnosis-
Palavras-chave: dc.subjectmice-
Palavras-chave: dc.subjectsaliva-
Palavras-chave: dc.subjectZika virus-
Título: dc.titleSalivary Detection of Zika Virus Infection Using ATR-FTIR Spectroscopy Coupled with Machine Learning Algorithms and Univariate Analysis: A Proof-of-Concept Animal Study-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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