Mammalian target of rapamycin pathway is up-regulated by both acute endurance exercise and chronic muscle contraction in rat skeletal muscle
Bibliographic record
Abstract
This study examined changes in the expression of translation initiation regulatory proteins and mRNA following both an acute bout of endurance exercise and chronic muscle contractile activity. Female Sprague Dawley rats ran for 2 h at 15 m·min(-1) followed by an increase in speed of 5 m·min(-1) every 5 min until volitional fatigue. The red gastrocnemius muscle was harvested from nonexercised animals (control; n = 6) and from animals that exercised either immediately after exercise (n = 6) or following 3 h of recovery from exercise (n = 6). Compared with control, ribosomal protein S6 (rpS6) mRNA was elevated (p < 0.05) at both 0 h (+32%) and 3 h (+47%). Both a catalytic subunit of eukaryotic initiation factor 2B (eIF2Bε) (+127%) and mammalian target of rapamycin (mTOR) mRNA (+44%) were increased at 3 h, compared with control. Phosphorylation of mTOR (+40%) and S6 kinase 1 (S6K1) (+266%) were increased immediately after exercise (p < 0.05). Female Sprague Dawley rats also underwent chronic stimulation of the peroneal nerve continuously for 7 days. The red gastrocnemius muscle was removed 24 h after cessation of the stimulation. Chronic muscle stimulation increased (p < 0.05) mTOR protein (+74%), rpS6 (+31%), and eukaryotic initiation factor 2α (+44%, p = 0.069), and this was accompanied by an increase in cytochrome c (+31%). Increased resting phosphorylation was observed for rpS6 (+51%) (p < 0.05) but not for mTOR or eukaryotic initiation factor 4E binding protein 1. These experiments demonstrate that both acute and chronic contractile activity up-regulate the mTOR pathway and mitochondrial content in murine skeletal muscle. This up-regulation of the mTOR pathway may increase translation efficiency and may also represent an important control point in exercise-mediated mitochondrial biogenesis.
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.
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".