Increases in skeletal muscle ATGL and its inhibitor G0S2 following 8 weeks of endurance training in metabolically different rat skeletal muscles
Bibliographic record
Abstract
Adipose triglyceride lipase (ATGL) catalyzes the rate-limiting removal of the first fatty acid from a triglyceride. ATGL is activated by comparative gene identification-58 and inhibited by G(0)/G(1) switch gene-2 protein (G0S2). Research in other tissues and cell culture indicates that inhibition is dependent on relative G0S2-to-ATGL protein content. G0S2 may also have several roles within mitochondria; however, this has yet to be observed in skeletal muscle. The purpose of this study was to determine if muscle G0S2 relative to ATGL content would decrease to facilitate intramuscular lipolysis following endurance training. Male Sprague-Dawley rats (n = 10; age 51-53 days old) were progressively treadmill trained at a 10% incline for 8 wk ending with 25 m/min for 1 h compared with control. Sciatic nerve stimulation for hind-limb muscle contraction (and lipolysis) was administered for 30 min to one leg, leaving the opposing leg as a resting control. Soleus (SOL), red gastrocnemius (RG), and white gastrocnemius were excised from both legs following stimulation or control. ATGL protein increased in all trained muscles. Unexpectedly, G0S2 protein was greater in the trained SOL and RG. In RG-isolated mitochondria, G0S2 also increased with training, yet mitochondrial G0S2 content was unaltered with acute contraction; therefore, any role of G0S2 in the mitochondria does not appear to be acutely mediated by content alone. In summary, G0S2 increased with training in oxidative muscles and mitochondria but not following acute contraction, suggesting that inhibition is not through relative G0S2-to-ATGL content but through more complicated intracellular mechanisms.
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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) | 0.001 | 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".