Respiratory Diseases, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy.
Respiratory Diseases, Department DiBrain, University of Bari, 70124 Bari, Italy.
Molecules. 2024 Sep 13;29(18):4358. doi: 10.3390/molecules29184358.
This study investigates volatile organic compound (VOC) profiles in the exhaled breath of normal subjects under different oxygenation conditions-normoxia (FiO2 21%), hypoxia (FiO2 11%), and hyperoxia (FiO2 35%)-using an electronic nose (e-nose). We aim to identify significant differences in VOC profiles among the three conditions utilizing principal component analysis (PCA) and canonical discriminant analysis (CDA). Our results indicate distinct VOC patterns corresponding to each oxygenation state, demonstrating the potential of e-nose technology in detecting physiological changes in breath composition (cross-validated accuracy values: FiO2 21% vs. FiO2 11% = 63%, FiO2 11% vs. FiO2 35% = 65%, FiO2 21% vs. FiO2 35% = 71%, and < 0.05 for all). This research underscores the viability of breathomics in the non-invasive monitoring and diagnostics of various respiratory and systemic conditions.
本研究使用电子鼻（e-nose）在不同氧合条件下（正常氧合[FiO2 21%]、缺氧[FiO2 11%]和高氧合[FiO2 35%]）调查正常受试者呼气中的挥发性有机化合物（VOC）谱。我们旨在使用主成分分析（PCA）和典型判别分析（CDA）确定三种条件下 VOC 谱之间的显著差异。我们的结果表明，每个氧合状态对应独特的 VOC 模式，证明了 e-nose 技术在检测呼吸成分生理变化方面的潜力（交叉验证准确性值：FiO2 21%与 FiO2 11%=63%，FiO2 11%与 FiO2 35%=65%，FiO2 21%与 FiO2 35%=71%，均<0.05）。这项研究强调了呼吸组学在各种呼吸和系统状况的非侵入性监测和诊断中的可行性。
