Increased Reliance on Carbohydrates for Aerobic Exercise in Highland Andean Leaf-Eared Mice, but Not in Highland Lima Leaf-Eared Mice
Bibliographic record
Abstract
Exercise is an important performance trait in mammals and variation in aerobic capacity and/or substrate allocation during submaximal exercise may be important for survival at high altitude. Comparisons between lowland and highland populations is a fruitful approach to understanding the mechanisms for altitude differences in exercise performance. However, it has only been applied in very few highland species. The leaf-eared mice (LEM, genus Phyllotis) of South America are a promising taxon to uncover the pervasiveness of hypoxia tolerance mechanisms. Here we use lowland and highland populations of Andean and Lima LEM (P. andium and P. limatus), acclimated to common laboratory conditions, to determine exercise-induced maximal oxygen consumption (V˙O2max), and submaximal exercise metabolism. Lowland and highland populations of both species showed no difference in V˙O2max running in either normoxia or hypoxia. When run at 75% of V˙O2max, highland Andean LEM had a greater reliance on carbohydrate oxidation to power exercise. In contrast, highland Lima LEM showed no difference in exercise fuel use compared to their lowland counterparts. The higher carbohydrate oxidation seen in highland Andean LEM was not explained by maximal activities of glycolytic enzymes in the gastrocnemius muscle, which were equivalent to lowlanders. This result is consistent with data on highland deer mouse populations and suggests changes in metabolic regulation may explain altitude differences in exercise performance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".