Ultrasensitive multispecies spectroscopic breath analysis for real-time health monitoring and diagnostics
Breath analysis enables rapid, noninvasive diagnostics, as well as long-term monitoring of human health, through the identification and quantification of exhaled biomarkers. Here, we demonstrate the remarkable capabilities of mid-infrared (mid-IR) cavity-enhanced direct-frequency comb spectroscopy (...
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| Vydáno v: | Proceedings of the National Academy of Sciences - PNAS Ročník 118; číslo 40 |
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| Hlavní autoři: | , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
United States
05.10.2021
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| Témata: | |
| ISSN: | 1091-6490, 1091-6490 |
| On-line přístup: | Zjistit podrobnosti o přístupu |
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| Shrnutí: | Breath analysis enables rapid, noninvasive diagnostics, as well as long-term monitoring of human health, through the identification and quantification of exhaled biomarkers. Here, we demonstrate the remarkable capabilities of mid-infrared (mid-IR) cavity-enhanced direct-frequency comb spectroscopy (CE-DFCS) applied to breath analysis. We simultaneously detect and monitor as a function of time four breath biomarkers-[Formula: see text]OH, [Formula: see text], [Formula: see text]O, and HDO-as well as illustrate the feasibility of detecting at least six more ([Formula: see text]CO, [Formula: see text], OCS, [Formula: see text], [Formula: see text], and [Formula: see text]) without modifications to the experimental apparatus. We achieve ultrahigh detection sensitivity at the parts-per-trillion level. This is made possible by the combination of the broadband spectral coverage of a frequency comb, the high spectral resolution afforded by the individual comb teeth, and the sensitivity enhancement resulting from a high-finesse cavity. Exploiting recent advances in frequency comb, optical coating, and photodetector technologies, we can access a large variety of biomarkers with strong carbon-hydrogen-bond spectral signatures in the mid-IR. |
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| Bibliografie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| ISSN: | 1091-6490 1091-6490 |
| DOI: | 10.1073/pnas.2105063118 |