Abnormal protein turnover and anabolic resistance to exercise in sarcopenic obesity
Bibliographic record
Abstract
Obesity may impair protein synthesis rates and cause anabolic resistance to growth factors, hormones, and exercise, ultimately affecting skeletal muscle mass and function. To better understand muscle wasting and anabolic resistance with obesity, we assessed protein 24-h fractional synthesis rates (24-h FSRs) in selected hind-limb muscles of sedentary and resistance-exercised lean and obese Zucker rats. Despite atrophied hind-limb muscles (-28% vs. lean rats), 24-h FSRs of mixed proteins were significantly higher in quadriceps (+18%) and red or white gastrocnemius (+22 or +38%, respectively) of obese animals when compared to lean littermates. Basal synthesis rates of myofibrillar (+8%) and mitochondrial proteins (-1%) in quadriceps were not different between phenotypes, while manufacture of cytosolic proteins (+12%) was moderately elevated in obese cohorts. Western blot analyses revealed a robust activation of p70S6k (+178%) and a lower expression of the endogenous mTOR inhibitor DEPTOR (-28%) in obese rats, collectively suggesting that there is an obesity-induced increase in net protein turnover favoring degradation. Lastly, the protein synthetic response to exercise of mixed (-7%), myofibrillar (+6%), and cytosolic (+7%) quadriceps subfractions was blunted compared to the lean phenotype (+34, +40, and +17%, respectively), indicating a muscle- and subfraction-specific desensitization to the anabolic stimulus of exercise in obese animals.
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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 | 0.001 | 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".