Metabolism of normothermic woodchucks during prolonged fasting
Bibliographic record
Abstract
The energy metabolism of hibernators has not been characterized for normothermic fasting, and our goal was to quantify oxidative fuel selection of non-hibernating woodchucks Marmota monax during prolonged food deprivation. Indirect calorimetry and nitrogen excretion measurements were used to assess changes in metabolic rate (VO2), fuel selection and composition of nitrogen wastes, as well as seasonal differences. For reference, matching experiments were also performed on rabbits. The results show that woodchucks have a higher metabolic rate in summer (271 micromol O2 kg(-1) min(-1)) than in spring (200 micromol O2 kg(-1) min(-1)) and that fasting-induced metabolic depression is only possible in summer (-25% in 14 days). The metabolic rate of rabbits is high at all times (383 micromol O2 kg(-1) min(-1)), but they show a more rapid depression in response to fasting (-32% in 7 days). Woodchucks have a naturally low reliance on proteins in the fed state (accounting for 8% VO2) in spring; 17% VO2 in summer; vs 28% VO2 in rabbits) and are able to decrease it even further during fasting (spring, 5% VO2); summer, 6% VO2; vs 20% VO2 in rabbits). This study shows that, apart from their notorious capacity for hibernation, woodchucks are particularly well adapted for normothermic fasting. Their ability to cope with prolonged food deprivation is based on a series of integrated responses eliciting deep metabolic depression and a rapid change in fuel selection to spare limited protein reserves. Information presently available on prolonged fasting suggests that such an ability for metabolic depression, possibly down to minimal levels still compatible with normothermic life, may be common among mammals. In contrast, the extreme protein sparing demonstrated in woodchucks is a unique metabolic feature of fasting champions.
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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 | 0.000 | 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".