Influence of ageing and essential amino acids on quantitative patterns of troponin T alternative splicing in human skeletal muscle
Bibliographic record
Abstract
Ageing is associated with a loss of skeletal muscle performance, a condition referred to as sarcopenia. In part, the age-related reduction in performance is due to a selective loss of muscle fiber mass, but mass-independent effects have also been demonstrated. An important mass-independent determinant of muscle performance is the pattern of expression of isoforms of proteins that participate in muscle contraction (e.g., the troponins). In the present study, we tested the hypothesis that ageing impairs alternative splicing of the pre-mRNA encoding fast skeletal muscle troponin T (TNNT3) in human vastus lateralis muscle. Furthermore, we hypothesized that resistance exercise alone or in combination with consumption of essential amino acids would attenuate age-associated effects on TNNT3 alternative splicing. Our results indicate that ageing negatively affects the pattern of TNNT3 alternative splicing in a manner that correlates quantitatively with age-associated reductions in muscle performance. Interestingly, whereas vastus lateralis TNNT3 alternative splicing was unaffected by a bout of resistance exercise 24 h prior to muscle biopsy, ingestion of a mixture of essential amino acids after resistance exercise resulted in a significant shift in the pattern of TNNT3 splice form expression in both age groups to one predicted to promote greater muscle performance. We conclude that essential amino acid supplementation after resistance exercise may provide a means to reduce impairments in skeletal muscle quality during ageing in humans.
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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 | 0.000 |
| 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".