Effect of short-term hindlimb immobilization on skeletal muscle atrophy and the transcriptome in a low compared with high responder to endurance training model
Bibliographic record
Abstract
Skeletal muscle atrophy is a physiological response to disuse, aging, and disease. We compared changes in muscle mass and the transcriptome profile after short-term immobilization in a divergent model of high and low responders to endurance training to identify biological processes associated with the early atrophy response. Female rats selectively bred for high response to endurance training (HRT) and low response to endurance training (LRT; n = 6/group; generation 19) underwent 3 day hindlimb cast immobilization to compare atrophy of plantaris and soleus muscles with line-matched controls (n = 6/group). RNA sequencing was utilized to identify Gene Ontology Biological Processes with differential gene set enrichment. Aerobic training performed prior to the intervention showed HRT improved running distance (+60.6 ± 29.6%), while LRT were unchanged (-0.3 ± 13.3%). Soleus atrophy was greater in LRT vs. HRT (-9.0 ±8.8 vs. 6.2 ±8.2%; P<0.05) and there was a similar trend in plantaris (-16.4 ±5.6% vs. -8.5 ±7.4%; P = 0.064). A total of 140 and 118 biological processes were differentially enriched in plantaris and soleus muscles, respectively. Soleus muscle exhibited divergent LRT and HRT responses in processes including autophagy and immune response. In plantaris, processes associated with protein ubiquitination, as well as the atrogenes (Trim63 and Fbxo32), were more positively enriched in LRT. Overall, LRT demonstrate exacerbated atrophy compared to HRT, associated with differential gene enrichments of biological processes. This indicates that genetic factors that result in divergent adaptations to endurance exercise, may also regulate biological processes associated with short-term muscle unloading.
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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 | 0.001 |
| 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".