Ferreira Maria Clara Coelho, Magalhães Vitórya Carvalho Pádua de, Morais Thayná Melo de Lima, Peralta Felipe, Castro Pedro Arthur Augusto, Zezell Denise Maria, Nogueira Marcelo Saito, Carvalho Luis Felipe Cs
Departamento de Odontologia, Universidade de Taubaté, Taubaté, Brazil.
Departamento de Odontologia, UNISOCIESC, Centro Universitário Tupy, Joinville, Brazil.
Technol Cancer Res Treat. 2025 Jan-Dec;24:15330338251317304. doi: 10.1177/15330338251317304. Epub 2025 May 19.
According to the WHO, oral cancer is the thirteenth most common cancer worldwide, with tobacco use being one of the primary causes of oral cancer. This study aimed to characterize and differentiate the saliva and bound water using FTIR spectroscopy in smoking and non-smoking individuals. This prospective observational study analyzed dried saliva samples from control, smoking, and occasional smoking groups using an attenuated total reflectance Fourier Transform Infrared (ATR-FTIR) spectrometer. The high wavenumber spectral region of 2800-3600 cm-¹ was selected for analysis. The results indicate that standard variance normalization (SNV) reduced intragroup variability and highlighted differences in smokers' spectra within the 3250-3500 cm-¹ region, associated with the absorption of water bound to saliva molecules. Cubic SVM models using SNV spectra demonstrated higher classification accuracy between groups, achieving 15.6% greater sensitivity and 1.3% lower specificity compared to models based on the second-order derivative. RUSBoosted Trees addressed data imbalances, enhancing both sensitivity and specificity. The study suggests that spectral changes may reflect salivary biochemistry linked to smoking and potentially to oral cancer risk. We conclude that differentiation between normal individuals and smokers can be achieved using high wavenumber FTIR spectral analysis. Additionally, we demonstrate the relationship between bound water molecules and salivary biomolecules in control, smoking, and occasional smoking groups. This technique has potential applications in elucidating OH vibrations within biological systems.
根据世界卫生组织的数据,口腔癌是全球第十三大常见癌症,吸烟是口腔癌的主要病因之一。本研究旨在利用傅里叶变换红外光谱(FTIR)对吸烟和不吸烟个体的唾液及结合水进行表征和区分。这项前瞻性观察性研究使用衰减全反射傅里叶变换红外光谱仪(ATR-FTIR)分析了对照组、吸烟组和偶尔吸烟组的干燥唾液样本。选择2800-3600 cm-¹的高波数光谱区域进行分析。结果表明,标准方差归一化(SNV)降低了组内变异性,并突出了吸烟者在3250-3500 cm-¹区域光谱的差异,这与唾液分子结合水的吸收有关。使用SNV光谱的立方支持向量机(SVM)模型在组间显示出更高的分类准确率,与基于二阶导数的模型相比,灵敏度提高了15.6%,特异性降低了1.3%。随机欠采样提升树(RUSBoosted Trees)解决了数据不平衡问题,提高了灵敏度和特异性。该研究表明,光谱变化可能反映了与吸烟以及潜在的口腔癌风险相关的唾液生物化学特征。我们得出结论,使用高波数FTIR光谱分析可以实现正常个体与吸烟者之间的区分。此外,我们还展示了对照组、吸烟组和偶尔吸烟组中结合水分子与唾液生物分子之间的关系。这项技术在阐明生物系统中的OH振动方面具有潜在应用价值。