Exercise Recovery in High Altitude Deer Mice
Bibliographic record
Abstract
Animals who live in the high-altitude environment are faced with the harsh conditions of low oxygen availability. This can make it difficult to perform daily tasks that require aerobic metabolism. However, deer mice (Peromyscus maniculatus) have evolved physiological adaptions that allow populations to survive in the high-altitude environment. One activity important for survival is aerobic locomotion and the rapid recovery of muscle metabolism after a bout of exercise. Hypoxia acclimated high-altitude mice have a greater reliance on carbohydrates to power exercise than low altitude mice and show a significant depletion of muscle glycogen. However, it is unclear how quickly after exercise is finished that these mice can replenish muscle glycogen stores. The gastrocnemius muscle of high-altitude deer mice has a more aerobic phenotype and a greater capacity to oxidize lipids than in low altitude mice. This suggests that high altitude mice may recover more quickly from exercise than their lowland counterparts due to a greater capacity to power glycogen replenishment through aerobic metabolism using the lipids stored in muscle as intramuscular triglycerides (IMTG). Using low- and high-altitude native deer mice born and raised in common lab conditions and acclimated to chronic hypoxia, I determined changes in oxygen consumption (VO2) following aerobic exercise and sampled skeletal muscle at various time points during recovery to examine changes in key metabolites, including glycogen and IMTG. I found there was depletion in glycogen stores during exercise in lowlanders and glycogen did return to resting levels following 90 minutes of recovery. In contrast, IMTG’s did not significantly change with exercise or during the recovery period in either population. These data suggest that muscle recovery from aerobic exercise may be influenced by altitude ancestry in deer mice.
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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 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".