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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],< 0.05) and exercise (vs. baseline 70.4% CVA,< 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.
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http://dx.doi.org/10.1088/1752-7163/ad5864 | DOI Listing |
Clin Transl Gastroenterol
September 2025
Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, Sichuan Province, China.
Background: Although colorectal cancer (CRC) screening has been incorporated into organized programs in many countries, a universally accepted noninvasive and efficient screening method remains unavailable.
Objective: This study aimed to assess the diagnostic potential of volatile organic compounds (VOCs) in exhaled breath via electronic nose (eNose) for noninvasive CRC detection.
Methods: The Cyranose320 sensor device was used to collect and analyze breath samples.
Biosensors (Basel)
August 2025
School of Pharmaceutical Sciences and Institute of Materia Medica, Xinjiang University, Urumqi 830017, China.
Volatile organic compounds (VOCs) present in human exhaled breath have emerged as promising biomarkers for non-invasive disease diagnosis. However, traditional VOC detection technology that relies on large instruments is not widely used due to high costs and cumbersome testing processes. Machine learning-assisted gas sensor arrays offer a compelling alternative by enabling the accurate identification of complex VOC mixtures through collaborative multi-sensor detection and advanced algorithmic analysis.
View Article and Find Full Text PDFEnviron Sci Technol
August 2025
Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science & Engineering, Fudan University, Shanghai 200438, P. R. China.
Human exhaled volatile organic compounds (VOCs) exhibit diverse profiles influenced by environmental exposures, yet the physiological processes governing their inhalation retention and exhalation dynamics remain unclear. This study introduces the inhalation retention index (IRI), a metric for quantifying the uptake of ambient VOCs in humans. Using GC × GC-TOF MS/FID, we analyzed exhaled breath samples from 103 individuals alongside corresponding ambient air samples, identifying 107 common VOCs.
View Article and Find Full Text PDFResearch (Wash D C)
August 2025
Laboratory of Advanced Theranostic Materials and Technology, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
Volatile organic compounds (VOCs) serve as critical biomarkers in exhaled breath for early-stage cancer patients, and their rapid, trace-level detection holds marked implications for cancer screening. Surface-enhanced Raman scattering (SERS) technology demonstrates strong potential for trace VOC gas detection due to its ultra-high sensitivity and immunity to water interference. However, while surface plasmon resonance (SPR)-free semiconductor substrates offer superior spectral stability and selectivity, their sensitivity toward VOC detection remains suboptimal.
View Article and Find Full Text PDFFront Mol Biosci
August 2025
Department of Medicine, Medical School, Fu Jen Catholic University, New Taipei City, Taiwan.
Aims: Approximately 25%-30% of the global population is affected by non-alcoholic fatty liver disease (NAFLD). This study aimed to explore whether NAFLD could be effectively detected using 341 volatile organic compounds (VOCs) via 10 machine learning (Mach-L) algorithms in a cohort of 1,501 individuals.
Methods: Participants were selected from the Taiwan MJ cohort, which includes comprehensive demographic, biochemical, lifestyle, and VOCs data.