Regulation of AKT in Richardson’s ground squirrels during hibernation
Bibliographic record
Abstract
Hibernation is a winter survival strategy for many small mammals metabolic rate falls by >95%, core body temperature can approach 0°C, and all physiological functions are suppressed. Energy savings of ~90% are achieved compared with the costs of remaining euthermic (37°C) over the winter. The protein kinase Akt (or PKB) plays a central role in coordinating growth and survival responses in cells and we hypothesized that regulation of Akt would be critical in hibernation. Kinetic properties of muscle Akt were compared in euthermic vs hibernating states; total and phosphorylated Akt protein was also quantified by Western blotting. Total Akt protein did not change in hibernation but phospho‐Akt (the active form) and measured Akt activity decreased significantly by 40% and 60%, respectively, compared with euthermic controls. S0.5 values for Akt peptide fell by 28% during hibernation whereas S0.5 ATP increased by 330%. Low temperature assay (10°C) strongly affected S0.5 ATP of euthermic Akt (a 350% increase). Akt activation energy (Ea) and sensitivity to denaturation by urea did not change between euthermia and hibernation. DEAE Sephadex chromatography showed three peaks (isozymes) of Akt in euthermic muscle but only two peaks during hibernation. The results document differential regulation of Akt during hibernation and suggest a key role for Akt in cell survival during torpor. Funded by NSERC Canada.
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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".