Quantitative interpretation and modelling of continuous nonprotein respiratory quotients

The Respiratory Exchange Ratio (RER), which is the ratio of total carbon dioxide produced over total oxygen consumed, serves as a qualitative measure to determine the substrate usage of a particular organism on the whole-body level. Quantification of RER by its direct conversion into %Glucose (%Gox) and %Lipid oxidation (%Lox) at a given timepoint can be done by utilizing nonprotein respiratory quotient tables. These tables, however, are limited to specific increments, and intermediate RER values are not covered by these tables. RER data are mostly continuous, which requires faithful interpolation, which we aimed for here. We first determined, statistically and schematically, that linear interpolation would lead to incorrect values. Therefore, we constructed a new mathematical model as an interpolating strategy to translate continuous RER values into correct values of %Gox and %Lox. We validated our new mathematical model against the original table by Péronnet & Massicotte (1), against a linear interpolation of these data, as well as against a model based on an exponential approach using a dataset of a nutritional intervention study in mice. This showed that our model outperforms the other methods, providing more accurate data. We conclude that applying our mathematical model will lead to an increase in data quality and offer a very simple, straightforward approach to obtain best %Gox and %Lox levels from continuous RER values.