Electronic nose based analysis of exhaled volatile organic compounds spectrum reveals asthmatic shifts and consistency in controls post-exercise and spirometry.

IF 3.7 4区 医学 Q1 BIOCHEMICAL RESEARCH METHODS
Silvano Dragonieri, Marcin Di Marco, Madiha Ahroud, Vitaliano Nicola Quaranta, Andrea Portacci, Ilaria Iorillo, Francesca Montagnolo, Giovanna Elisiana Carpagnano
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引用次数: 0

Abstract

Analyzing exhaled volatile organic compounds (VOCs) with an electronic nose (e-nose) is emerging in medical diagnostics as a non-invasive, quick, and sensitive method for disease detection and monitoring. This study investigates if activities like spirometry or physical exercise affect exhaled VOCs measurements in asthmatics and healthy individuals, a crucial step for e-nose technology's validation for clinical use. The study analyzed exhaled VOCs using an e-nose in 27 healthy individuals and 27 patients with stable asthma, before and after performing spirometry and climbing five flights of stairs. Breath samples were collected using a validated technique and analyzed with a Cyranose 320 e-nose. In healthy controls, the exhaled VOCs spectrum remained unchanged after both lung function test and exercise. In asthmatics, principal component analysis and subsequent discriminant analysis revealed significant differences post-spirometry (vs. baseline 66.7% cross validated accuracy [CVA],p< 0.05) and exercise (vs. baseline 70.4% CVA,p< 0.05). E-nose measurements in healthy individuals are consistent, unaffected by spirometry or physical exercise. However, in asthma patients, significant changes in exhaled VOCs were detected post-activities, indicating airway responses likely due to constriction or inflammation, underscoring the e-nose's potential for respiratory condition diagnosis and monitoring.

基于电子鼻的呼出挥发性有机化合物频谱分析揭示了哮喘的转变以及运动后和肺活量测定对照组的一致性。
背景:使用电子鼻(e-nose)分析呼出的挥发性有机化合物(VOCs)作为一种无创、快速、灵敏的疾病检测和监控方法,正在医疗诊断领域崭露头角。本研究调查了肺活量测定或体育锻炼等活动是否会影响哮喘患者和健康人呼出的挥发性有机化合物测量值,这是电子鼻技术临床应用验证的关键一步:研究使用电子鼻分析了 27 名健康人和 27 名稳定期哮喘患者在进行肺活量测定和爬五层楼梯前后呼出的挥发性有机化合物。研究人员使用经过验证的技术收集呼气样本,并使用 Cyranose 320 电子鼻进行分析:在健康对照组中,肺功能测试和运动后呼出的挥发性有机化合物谱保持不变。在哮喘患者中,主成分分析和随后的判别分析显示出呼吸测定后的显著差异(与基线66.7%的交叉验证准确度[CVA]相比,P<0.05)。
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来源期刊
Journal of breath research
Journal of breath research BIOCHEMICAL RESEARCH METHODS-RESPIRATORY SYSTEM
CiteScore
7.60
自引率
21.10%
发文量
49
审稿时长
>12 weeks
期刊介绍: Journal of Breath Research is dedicated to all aspects of scientific breath research. The traditional focus is on analysis of volatile compounds and aerosols in exhaled breath for the investigation of exogenous exposures, metabolism, toxicology, health status and the diagnosis of disease and breath odours. The journal also welcomes other breath-related topics. Typical areas of interest include: Big laboratory instrumentation: describing new state-of-the-art analytical instrumentation capable of performing high-resolution discovery and targeted breath research; exploiting complex technologies drawn from other areas of biochemistry and genetics for breath research. Engineering solutions: developing new breath sampling technologies for condensate and aerosols, for chemical and optical sensors, for extraction and sample preparation methods, for automation and standardization, and for multiplex analyses to preserve the breath matrix and facilitating analytical throughput. Measure exhaled constituents (e.g. CO2, acetone, isoprene) as markers of human presence or mitigate such contaminants in enclosed environments. Human and animal in vivo studies: decoding the ''breath exposome'', implementing exposure and intervention studies, performing cross-sectional and case-control research, assaying immune and inflammatory response, and testing mammalian host response to infections and exogenous exposures to develop information directly applicable to systems biology. Studying inhalation toxicology; inhaled breath as a source of internal dose; resultant blood, breath and urinary biomarkers linked to inhalation pathway. Cellular and molecular level in vitro studies. Clinical, pharmacological and forensic applications. Mathematical, statistical and graphical data interpretation.
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