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« Previous AbstractNon-contact breath sampling for sensor-based breath analysis    Next AbstractIdentification of Key Volatile Organic Compounds Released by Gastric Tissues as Potential Non-Invasive Biomarkers for Gastric Cancer »

Molecules


Title:Modelling of Breath and Various Blood Volatilomic Profiles-Implications for Breath Volatile Analysis
Author(s):Mochalski P; King J; Mayhew CA; Unterkofler K;
Address:"Institute for Breath Research, Leopold-Franzens-Universitat, Innrain 66, A-6020 Innsbruck, Austria. Institute of Chemistry, Jan Kochanowski University, 25-369 Kielce, Poland. Tiroler Krebsforschungsinstitut (TKFI), Innrain 66, A-6020 Innsbruck, Austria. Research Center BI, University of Applied Sciences Vorarlberg, Hochschulstrasse 1, A-6850 Dornbirn, Austria"
Journal Title:Molecules
Year:2022
Volume:20220407
Issue:8
Page Number: -
DOI: 10.3390/molecules27082381
ISSN/ISBN:1420-3049 (Electronic) 1420-3049 (Linking)
Abstract:"Researchers looking for biomarkers from different sources, such as breath, urine, or blood, frequently search for specific patterns of volatile organic compounds (VOCs), often using pattern recognition or machine learning techniques. However, they are not generally aware that these patterns change depending on the source they use. Therefore, we have created a simple model to demonstrate that the distribution patterns of VOCs in fat, mixed venous blood, alveolar air, and end-tidal breath are different. Our approach follows well-established models for the description of dynamic real-time breath concentration profiles. We start with a uniform distribution of end-tidal concentrations of selected VOCs and calculate the corresponding target concentrations. For this, we only need partition coefficients, mass balance, and the assumption of an equilibrium state, which avoids the need to know the volatiles' metabolic rates and production rates within the different compartments"
Keywords:Biomarkers *Body Fluids/chemistry Breath Tests/methods *Volatile Organic Compounds/analysis VOCs blood breath end-tidal air fat modelling partition coefficients volatilome;
Notes:"MedlineMochalski, Pawel King, Julian Mayhew, Chris A Unterkofler, Karl eng 824986/European Union's Horizon~2020 research and innovation programme/ Switzerland 2022/04/24 Molecules. 2022 Apr 7; 27(8):2381. doi: 10.3390/molecules27082381"

 
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Citation: El-Sayed AM 2024. The Pherobase: Database of Pheromones and Semiochemicals. <http://www.pherobase.com>.
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