Validation of a sensor system for the measurement of breath ammonia using selected-ion flow-tube mass spectrometry.
| Autor: | Wagner M; BreathDX (UK) Ltd, Bristol, United Kingdom.; Centre for Biomedical Research, School of Applied Sciences, University of the West of England, Coldharbour Lane, Bristol BS16 1QY, United Kingdom., Saad S; Centre for Biomedical Research, School of Applied Sciences, University of the West of England, Coldharbour Lane, Bristol BS16 1QY, United Kingdom., Killard AJ; BreathDX (UK) Ltd, Bristol, United Kingdom.; Centre for Biomedical Research, School of Applied Sciences, University of the West of England, Coldharbour Lane, Bristol BS16 1QY, United Kingdom. |
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| Jazyk: | angličtina |
| Zdroj: | Journal of breath research [J Breath Res] 2024 Nov 14; Vol. 19 (1). Date of Electronic Publication: 2024 Nov 14. |
| DOI: | 10.1088/1752-7163/ad8e7d |
| Abstrakt: | The measurement of trace breath gases is of growing interest for its potential to provide non-invasive physiological information in health and disease. While instrumental techniques such as selected-ion flow-tube mass spectrometry (SIFT-MS) can achieve this, these are less suitable for clinical application. Sensitive sensor-based systems for breath ammonia could be more widely deployed, but have proven challenging to develop. This work demonstrates the sequential analytical validation of an electrochemical impedance-based sensor system for the measurement of ammonia in breath using SIFT-MS. Qualitative and relative responses between the two methods were comparable, although there were consistent differences in absolute concentration. When tested in artificial breath ammonia, sensors had a relative impedance sensitivity of 3.43 × 10 -5 ppbv -1 for each breath in the range of 249-1653 ppbv ( r 2 = 0.87, p < 0.05). When correlated with SIFT-MS using human breath ( n = 14), ammonia was detected in the range of 100-700 ppbv ( r = 0.78, p < 0.001), demonstrating acceptable sensitivity, reproducibility and dynamic range for clinical application. (© 2024 IOP Publishing Ltd. All rights, including for text and data mining, AI training, and similar technologies, are reserved.) |
| Databáze: | MEDLINE |
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