Lower Integrated Muscle Protein Synthesis in Masters Compared with Younger Athletes
Bibliographic record
Abstract
PURPOSE: The objective of this study is to compare the integrated muscle protein synthesis (MPS) rates of masters and younger triathletes over three consecutive days of intense endurance training. Recovery of cycling performance, after muscle-damaging running, was also compared between groups. METHODS: Five masters (age, 53 ± 2 yr; V˙O2max, 55.7 ± 6.9 mL·kg·min) and six younger (age, 27 ± 2 yr; V˙O2max, 62.3 ± 1.5 mL·kg·min) trained triathletes volunteered for the study. Baseline skeletal muscle and saliva were initially sampled, after which a 150-mL bolus of deuterium oxide (70%) was consumed. Participants then completed a 30-min downhill run; three 20-km cycling time trials (TT) were completed 10, 24, and 48 h after the run. Saliva was collected each morning, and skeletal muscle was again sampled 72 h after the run; both were used for MPS analysis. Diet was controlled throughout the study. RESULTS: Over 3 d, masters triathletes showed a significantly lower myofibrillar fractional synthetic rate (1.49% ± 0.12%·d) compared with the younger (1.70% ± 0.09%·d) triathletes (P = 0.009, d = 1.98). There was also a trend for masters triathletes to produce a slower cycle TT (-3.0%, d = 0.46) than younger triathletes (-1.4%, d = 0.29) at 10 h postrun in comparison with the baseline performance. The between-group comparison of change was moderate (d = 0.51), suggesting slower acute recovery among masters triathletes. CONCLUSIONS: The present data show lower MPS rates in well-trained masters triathletes over 3 d of training, and this likely contributes to poorer muscle protein repair and remodeling. Furthermore, acute recovery of cycle TT performance tended to be poorer in the masters triathletes.
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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 | 0.001 | 0.001 |
| 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) | 0.004 | 0.001 |
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".