Myostatin levels in skeletal muscle of hibernating ground squirrels
Bibliographic record
Abstract
Myostatin, a negative regulator of muscle mass, is elevated during disuse and starvation. Mammalian hibernation presents a unique scenario, where animals are hypocaloric and in torpor, but the extent of muscle protein loss is minimized. We hypothesized that myostatin expression, which is usually increased early in disuse and under hypocaloric conditions, could be suppressed in this unique model. Skeletal muscle was collected from thirteen-lined ground squirrels, Spermophilus tridecemlineatus, at six time points during hibernation: control euthermic (CON); entrance into hibernation (ENT), body temperature (T(b)) falling; early hibernation (EHib), stable T(b) in torpor for 24 h; late hibernation (LHib), stable T(b) in torpor for 3 days; early arousal (EAr), T(b) rising; and arousal (AR), T(b) restored to 34-37°C for about 18 h. There was no significant increase of myostatin during ENT, EHib or LHib. Unexpectedly, there were approximately sixfold increases in myostatin protein levels as squirrels arose from torpor. The elevation during EAr remained high in AR, which represented an interbout time period. Mechanisms that could release the suppression or promote increased levels of myostatin were assessed. SMAD2 and phosphorylated SMAD2 were increased during EHib, but only the phosphorylated SMAD2 during AR mirrored increases in myostatin. Follistatin, a negative regulator of myostatin, did not follow the same time course as myostatin or its signaling pathway, indicating more control of myostatin at the signaling level. However, SMAD7, an inhibitory SMAD, did not appear to play a significant role during deep hibernation. Hibernation is an excellent natural model to study factors involved in the endogenous intracellular mechanisms controlling myostatin.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".