Out Cold: Biochemical Regulation of Mammalian Hibernation – A Mini-Review
Bibliographic record
Abstract
Hibernating mammals offer an intriguing example of natural torpor and illustrate the regulatory mechanisms that control metabolic rate depression and the cell preservation strategies that support long-term viability in a hypometabolic state. These suggest applied strategies for improving the hypothermic preservation of human organs for transplant, and guidelines that could aid the development of torpor as an intervention strategy in human medicine. Recent advances in hibernation research have illustrated mechanisms that contribute to metabolic depression by orchestrating the global suppression of ATP-expensive transcription and translation including multiple forms of post-translational modification of proteins/enzymes (phosphorylation, acetylation, SUMOylation), mRNA storage mechanisms, and differential expression of microRNA species. DNA-screening technologies have also contributed new advances in understanding the range of cell functions that are impacted during torpor and point out some critical preservation strategies that aid long-term viability in a torpid state. These include antioxidant defenses, chaperones and the implementation of the unfolded protein response, and the enhancement of serpins (serine protease inhibitors) to control the actions of extracellular proteases in clotting and inflammation responses.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".