Monitoring Lipolysis by Sensing Breath Acetone down to Parts‐per‐Billion. Issue 4 (12th March 2021)

• Record Type: Journal Article
• Authors: Weber, Ines C.; Derron, Nina; Königstein, Karsten; Gerber, Philipp A.; Güntner, Andreas T.; Pratsinis, Sotiris E.
• Is Part Of: Small science. Volume 1:Issue 4(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-12
• Subjects: breath acetone sensors -- end‐tidal acetone -- mobile health -- monitoring lipolysis; Nanoscience -- Periodicals; Nanotechnology -- Periodicals; 620.5
• DOI: 10.1002/smsc.202100004
• Languages: English
• ISSNs: 2688-4046

Abstract

Abstract : Mobile health technologies can provide information routinely and on demand to manage metabolic diseases (e.g., diabetes and obesity) and optimize their treatment (e.g., exercise or dieting). Most promising is breath acetone monitoring to track lipolysis and complement standard glucose monitoring. Yet, accurate quantification of acetone down to parts‐per‐billion (ppb) is difficult with compact and mobile devices in the presence of interferants at comparable or higher concentrations. Herein, a low‐cost detector that quantifies end‐tidal acetone during exercise and rest is presented with excellent bias (25 ppb) and unprecedented precision (169 ppb) in 146 breath samples. It combines a flame‐made Pt/Al2 O3 catalyst with a chemoresistive Si/WO3 sensor. The detector is robust against orders of magnitude higher ethanol concentrations from disinfection and exercise‐driven endogenous breath isoprene ones, as validated by mass spectrometry. This detector accurately tracks the individual lipolysis dynamics in all volunteers, as confirmed by blood ketone measurements. It can be integrated readily into handheld devices for personalized metabolic assessment at home, in gyms, and clinics. Abstract : A compact and low‐cost acetone detector tracks lipolysis from exhaled breath during exercise and rest, in excellent agreement with mass spectrometry and blood ketone measurements. It exhibits high robustness to endogenous isoprene and background ethanol by screening a Si/WO3 sensor with a selective catalytic Pt/Al2 O3 filter. Hence, this detector is promising for personalized and non‐invasive metabolic assessment.