The Influence of Environmental Temperature on Metabolic Flexibility in Young Healthy Adults During Exercise
Bibliographic record
Abstract
Metabolic flexibility is the ability of an organism to match fuel oxidation to its availability. It tends to be compromised in individuals suffering from metabolic diseases, lipo- and glucotoxicity, and mitochondrial dysfunctions. Recent incremental maximal oxygen consumption exercise studies performed in cold environments have demonstrated an increase in lipid oxidation over a wide range of exercise intensities. Whether metabolic flexibility is compromised or altered by a drive in lipid utilization during exercise in the cold remains unclear. PURPOSE: The aim of the present study was to investigate whether metabolic flexibility is altered during incremental maximal exercise to volitional fatigue in a cold environment. METHODS: Ten healthy participants (22 ± 1 yrs, 68.1 ± 7.8 kg, 169.7 ± 4.9 cm, 21.1 ± 9.7 %BF) dressed in shorts and a t-shirt, performed four maximal incremental treadmill tests to volitional fatigue, in a fasted state. Tests were performed in a cold (0.89°C ± 1.8) (CO) or a thermoneutral (TN) environment (22.0°C ± 0.9), with and without a pre-exercise ingestion of a 75-g glucose solution. Paired t-tests were performed to compare the effects of temperature using the difference between glucose and non-glucose conditions. Differences in averaged respiratory exchange ratio ([INCREMENT]RER) during the entire exercise period, maximal fat oxidation ([INCREMENT]MFO), and where MFO occurred along the exercise intensity spectrum ([INCREMENT]Fatmax) were analysed via whole-body indirect calorimetry. RESULTS: No statistical differences in fat utilization during CO exercise when compared to TN as indicated by [INCREMENT]RER (0.05 ± 0.02 vs. 0.05 ± 0.02; p = 0.584), [INCREMENT]MFO (0.21 ± 0.18 vs. 0.16 ± 0.13 g•min-1; p = 0.133) and [INCREMENT]Fatmax (13.3 ± 19.0 vs. 0.6 ± 21.3 %V[Combining Dot Above]O2peak ; p = 0.266) in CO and TN, respectively. CONCLUSION: A cold environment increases lipid contribution as metabolic fuel during exercise, and may be considered in training and health-intervention strategies. In the present study, an acute glucose ingestion causing a shift in carbohydrate utilization, was similar in both the cold and thermoneutral environment, indicating that exercising in a cold environment does not compromise metabolic flexibility. Future exercise studies should investigate the metabolic influences of high-fat diets and acute lipid overload in cold and warm environments.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".