{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T03:14:54Z","timestamp":1788146094093,"version":"build-2803163510"},"reference-count":10,"publisher":"Walter de Gruyter GmbH","issue":"4","license":[{"start":{"date-parts":[[2026,7,6]],"date-time":"2026-07-06T00:00:00Z","timestamp":1783296000000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,24]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Traditional disease screening methods often rely on protein biomarkers or imaging, which are somewhat constrained by their sensitivity, invasiveness, and limitation in detecting diseases at earlier stages. To achieve both noninvasive and early warning of diseases or physiology change, monitoring gaseous biomarkers such as volatile organic compounds (VOCs) and nitric oxide (NO) in exhaled breath is a promising solution. It has been demonstrated that these biomarkers as a group change rapidly in response to alterations in human physiology, which allows\u00a0rapid noninvasive earlier screenings of asthma, lung cancer, coronavirus disease 2019 (COVID-19) and other diseases. Interestingly, this has also been demonstrated for real-time monitoring of air toxicity by resolving rats\u2019 breath-borne biomarkers. Here, we propose the use of artificial intelligence (AI) and breath-borne gaseous biomarkers to construct the \u201cfingerprint pattern\u201d of a specific disease or certain environmental hazards for early warning.<\/jats:p>","DOI":"10.1515\/mr-2026-0033","type":"journal-article","created":{"date-parts":[[2026,7,5]],"date-time":"2026-07-05T16:55:43Z","timestamp":1783270543000},"page":"351-353","source":"Crossref","is-referenced-by-count":0,"title":["Gaseous biomarkers speak medical conditions"],"prefix":"10.1515","volume":"6","author":[{"given":"Chenyu","family":"Zhu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Regional Environment and Sustainability, College of Environmental Sciences and Engineering , Peking University , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huaying","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Regional Environment and Sustainability, College of Environmental Sciences and Engineering , Peking University , Beijing , China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1442-8054","authenticated-orcid":false,"given":"Maosheng","family":"Yao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Regional Environment and Sustainability, College of Environmental Sciences and Engineering , Peking University , Beijing , China"},{"name":"Institute of Environment & Health, College of Chemistry and Environmental Science , Inner Mongolia Normal University , Hohhot , Inner Mongolia Autonomous Region , China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"374","published-online":{"date-parts":[[2026,7,6]]},"reference":[{"key":"2026083102570606019_j_mr-2026-0033_ref_001","doi-asserted-by":"crossref","unstructured":"Pauling, L, Robinson, AB, Teranishi, R, Cary, P. Quantitative analysis of urine vapor and breath by gas-liquid partition chromatography. Proc Natl Acad Sci USA 1971;68:2374\u20136. https:\/\/doi.org\/10.1073\/pnas.68.10.2374.","DOI":"10.1073\/pnas.68.10.2374"},{"key":"2026083102570606019_j_mr-2026-0033_ref_002","unstructured":"Asthma GIf. Global strategy for asthma management and prevention. Global Initiative for Asthma; 2025. https:\/\/ginasthma.org\/2025-gina-strategy-report\/ [Accessed 18 Jun 2026]."},{"key":"2026083102570606019_j_mr-2026-0033_ref_003","doi-asserted-by":"crossref","unstructured":"Haick, H, Broza, YY, Mochalski, P, Ruzsanyi, V, Amann, A. Assessment, origin, and implementation of breath volatile cancer markers. Chem Soc Rev 2014;43:1423\u201349. https:\/\/doi.org\/10.1039\/c3cs60329f.","DOI":"10.1039\/C3CS60329F"},{"key":"2026083102570606019_j_mr-2026-0033_ref_004","doi-asserted-by":"crossref","unstructured":"Das, S, Pal, M. Review\u2013non-invasive monitoring of human health by exhaled breath analysis: a comprehensive review. J\u00a0Electrochem Soc 2020;167:037562. https:\/\/doi.org\/10.1149\/1945-7111\/ab67a6.","DOI":"10.1149\/1945-7111\/ab67a6"},{"key":"2026083102570606019_j_mr-2026-0033_ref_005","doi-asserted-by":"crossref","unstructured":"Chen, H, Qi, X, Zhang, L, Li, X, Ma, J, Zhang, C, et al.. COVID-19 screening using breath-borne volatile organic compounds. J\u00a0Breath Res 2021;15:047104. https:\/\/doi.org\/10.1088\/1752-7163\/ac2e57.","DOI":"10.1088\/1752-7163\/ac2e57"},{"key":"2026083102570606019_j_mr-2026-0033_ref_006","unstructured":"U.S. food and drug administration (FDA), https:\/\/www.fda.gov\/news-events\/press-announcements\/coronavirus-covid-19-update-fda-authorizes-first-test-patient-home-sample-collection [Accessed 18 Jun 2026]."},{"key":"2026083102570606019_j_mr-2026-0033_ref_007","doi-asserted-by":"crossref","unstructured":"Jiao, B, Zhang, S, Bei, Y, Bu, G, Yuan, L, Zhu, Y, et al.. A detection model for cognitive dysfunction based on volatile organic compounds from a large Chinese community cohort. Alzheimer\u2019s Dement 2023;19:4852\u201362. https:\/\/doi.org\/10.1002\/alz.13053.","DOI":"10.1002\/alz.13053"},{"key":"2026083102570606019_j_mr-2026-0033_ref_008","doi-asserted-by":"crossref","unstructured":"Zhang, L, Li, X, Chen, H, Wu, Z, Hu, M, Yao, M. Haze air pollution health impacts of breath-borne VOCs. Environ Sci Technol 2022;56:8541\u201351. https:\/\/doi.org\/10.1021\/acs.est.2c01778.","DOI":"10.1021\/acs.est.2c01778"},{"key":"2026083102570606019_j_mr-2026-0033_ref_009","doi-asserted-by":"crossref","unstructured":"Chen, X, Liu, F, Niu, Z, Mao, S, Tang, H, Li, N, et al.. The association between short-term exposure to ambient air pollution and fractional exhaled nitric oxide level: a systematic review and meta-analysis of panel studies. Environ Pollut 2020;265:114833, https:\/\/doi.org\/10.1016\/j.envpol.2020.114833.","DOI":"10.1016\/j.envpol.2020.114833"},{"key":"2026083102570606019_j_mr-2026-0033_ref_010","doi-asserted-by":"crossref","unstructured":"Zhu, C, Xing, Q, Liu, H, Guo, Z, Wang, Z, Chen, Z, et al.. Air toxicity surveillance across thirteen cities using rats. Environ Sci Technol 2025;59:8461\u201374. https:\/\/doi.org\/10.1021\/acs.est.5c01250.","DOI":"10.1021\/acs.est.5c01250"}],"container-title":["Medical Review"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.degruyterbrill.com\/document\/doi\/10.1515\/mr-2026-0033\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyterbrill.com\/document\/doi\/10.1515\/mr-2026-0033\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,31]],"date-time":"2026-08-31T02:59:58Z","timestamp":1788145198000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyterbrill.com\/document\/doi\/10.1515\/mr-2026-0033\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7,6]]},"references-count":10,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2026,6,16]]},"published-print":{"date-parts":[[2026,8,24]]}},"alternative-id":["10.1515\/mr-2026-0033"],"URL":"https:\/\/doi.org\/10.1515\/mr-2026-0033","relation":{},"ISSN":["2749-9642"],"issn-type":[{"value":"2749-9642","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7,6]]}}}