Out Cold: Biochemical Regulation of Mammalian Hibernation – A Mini-Review
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it