<scp>l</scp>-Carnitine supplement reduces skeletal muscle atrophy induced by prolonged hindlimb suspension in rats
Bibliographic record
Abstract
l-Carnitine was recently found to downregulate the ubiquitin proteasome pathway (UPP) and increase insulin-like growth factor 1 concentrations in animal models. However, the effect of l-carnitine administration on disuse muscle atrophy induced by hindlimb suspension has not yet been studied. Thus, we hypothesized that l-carnitine may have a protective effect on muscle atrophy induced by hindlimb suspension via the Akt1/mTOR and/or UPP. Male Wistar rats were assigned to 3 groups: hindlimb suspension group, hindlimb suspension with l-carnitine administration (1250 mg·kg−1·day−1) group, and pair-fed group adjusted hindlimb suspension. l-Carnitine administration for 2 weeks of hindlimb suspension alleviated the decrease in weight and fiber size in the soleus muscle. In addition, l-carnitine suppressed atrogin-1 mRNA expression, which has been reported to play a pivotal role in muscle atrophy. The present study shows that l-carnitine has a protective effect against soleus muscle atrophy caused by hindlimb suspension and decreased E3 ligase messenger RNA expression, suggesting the possibility that l-carnitine protects against muscle atrophy, at least in part, through the inhibition of the UPP. These observations suggest that l-carnitine could serve as an effective supplement in the decrease of muscle atrophy caused by weightlessness in the fields of clinical and rehabilitative research.
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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) | 0.001 | 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 | 0.001 | 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".