Back to Search Start Over

Metabolic monitoring via on-line analysis of 13 C-enriched carbon dioxide in exhaled mouse breath using substrate-integrated hollow waveguide infrared spectroscopy and luminescence sensing combined with Bayesian sampling.

Authors :
Seichter F
Vogt J
Tütüncü E
Hagemann LT
Wachter U
Gröger M
Kress S
Radermacher P
Mizaikoff B
Source :
Journal of breath research [J Breath Res] 2021 Feb 25; Vol. 15 (2), pp. 026013. Date of Electronic Publication: 2021 Feb 25.
Publication Year :
2021

Abstract

In studies that target specific functions or organs, the response is often overlaid by indirect effects of the intervention on global metabolism. The metabolic side of these interactions can be assessed based on total energy expenditure (TEE) and the contributions of the principal energy sources, carbohydrates, proteins and fat to whole body CO <subscript>2</subscript> production. These parameters can be identified from indirect calorimetry using respiratory oxygen intake and CO <subscript>2</subscript> dioxide production data that are combined with the response of the <superscript>13</superscript> CO <subscript>2</subscript> release in the expired air and the glucose tracer enrichment in plasma following a <superscript>13</superscript> C glucose stable isotope infusion. This concept is applied to a mouse protocol involving anesthesia, mechanical respiration, a disease model, like hemorrhage and therapeutic intervention. It faces challenges caused by a small sample size for both breath and plasma as well as changes in metabolic parameters caused by disease and intervention. Key parameters are derived from multiple measurements, all afflicted with errors that may accumulate leading to unrealistic values. To cope with these challenges, a sensitive on-line breath analysis system based on substrate-integrated hollow waveguide infrared spectroscopy and luminescence (iHWG-IR-LS) was used to monitor gas exchange values. A Bayesian statistical model is developed that uses established equations for indirect calorimetry to predict values for respiratory gas exchange and tracer data that are consistent with the corresponding measurements and also provides statistical error bands for these parameters. With this new methodology, it was possible to estimate important metabolic parameters (respiratory quotient (RQ), relative contribution of carbohydrate, protein and fat oxidation f <subscript>carb</subscript> , f <subscript>fat</subscript> and f <subscript>prot</subscript> , total energy expenditure TEE) in a resolution never available before for a minimal invasive protocol of mice under anesthesia.

Details

Language :
English
ISSN :
1752-7163
Volume :
15
Issue :
2
Database :
MEDLINE
Journal :
Journal of breath research
Publication Type :
Academic Journal
Accession number :
33630755
Full Text :
https://doi.org/10.1088/1752-7163/ab8dcd