Biochemical characterization of saliva of smoking and non-smoking patients by using Fourier-transform infrared spectroscopy

dc.contributorHUANG, ZHIWEI
dc.creatorFERREIRA, MARIA C. de M.S.C.
dc.creatorLEAL, LEONARDO B.
dc.creatorNOGUEIRA, MARCELO S.
dc.creatorCASTRO, PEDRO A.A.
dc.creatorPERALTA, FELIPE
dc.creatorZEZELL, DENISE M.
dc.creatorCARVALHO, LUIS F. das C. e S. de
dc.creatorSPIE PHOTONICS WEST; SPIE BIOS
dc.date2022-08-26T19:01:13Z
dc.date2022-08-26T19:01:13Z
dc.dateJanuary 22 - February 28, 2022
dc.date.accessioned2023-09-28T14:23:04Z
dc.date.available2023-09-28T14:23:04Z
dc.identifierhttp://repositorio.ipen.br/handle/123456789/33253
dc.identifier10.1117/12.2610565
dc.identifier0000-0001-7404-9606
dc.identifier.urihttps://repositorioslatinoamericanos.uchile.cl/handle/2250/9003472
dc.descriptionMore than 90% of oral malignant neoplasms consist of squamous cell carcinoma originated from extrinsic and/or intrinsic multifactorial etiology on the epithelium of the oral mucosa. This multifactorial etiology makes early-stage cancer detection challenging due to the lack of associated oral-tissue clinical features and absence of changes on conventional cellular-imaging, serological and histopathological exams. By using a molecular-sensitive optical technique such as Fourier-transform infrared (FT-IR) spectroscopy, disease-specific biochemical changes can be detected non-destructively, non-invasively and with small sample volumes. In this study, we have used FT-IR spectroscopy to analyze saliva samples of control, smoker, and occasional smoker groups and determine their intrinsic molecular changes as well as the performance of sample differentiation by using a neural network classifier. Saliva samples were collected by spitting, homogenized and stored at -20??C until analysis. Spectral data was collected in the fingerprint region (900cm-1 to 1800cm- 1) by using a Thermo Scientific Nicolet 6700 ATR FT-IR Spectrometer, in which 1-??l samples were placed on the crystal without additives and left to dry completely by an average time of 5 minutes. Data pre-processing and analysis was performed on the OriginPro8.5 and Orange software. Saliva-sample classification was performed with leave-one-out validation. Correctly classified instances were 72.7% for the control group, 65.5% for occasional smokers and 75% for smokers. Sample differences were observed in the peaks at 1076cm-1 (skeletal cis conformation of DNA and symmetric stretching of phosphate [PO2], 1403cm-1 symmetric CH3 modes of protein methyl groups and ??sCH3 of collagen, 1451cm- 1 asymmetrical CH3 bending modes of the protein methyl groups, 1547cm-1 of protein band, amide II, peptide and proteins amide II, and 1646cm-1 amide I, C5 methylated cytosine, C==O bond, C==C stretching uracil and NH2 guanine.
dc.descriptionFunda????o de Amparo ?? Pesquisa do Estado de S??o Paulo (FAPESP)
dc.descriptionFAPESP: 18/03636-7
dc.format119570E-1 - 119570E-12
dc.publisherSPIE
dc.relationProceedings SPIE 11957, Biomedical Vibrational Spectroscopy 2022: Advances in Research and Industry
dc.rightsclosedAccess
dc.subjectneoplasms
dc.subjectoral cavity
dc.subjecttobacco smokes
dc.subjectfourier transformation
dc.subjectinfrared spectra
dc.subjectspectroscopy
dc.subjectbiopsy
dc.subjectdiagnostic techniques
dc.subjecttobacco
dc.titleBiochemical characterization of saliva of smoking and non-smoking patients by using Fourier-transform infrared spectroscopy
dc.typeTexto completo de evento
dc.coverageI
dc.localBellingham, WA, USA


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