Age Differences in Recovery Rate Following an Aerobic-Based Exercise Protocol Inducing Muscle Damage Among Amateur, Male Athletes
Bibliographic record
Abstract
Purpose: Compare recovery rates between active young (Y) and middle-aged (MA) males up to 48H post aerobically based, exercise-induced muscle damage (EIMD) protocol. A secondary aim was to explore the relationships between changes in indices associated with EIMD and recovery throughout this timeframe. Methods: Twenty-eight Y (n = 14, 26.1 ± 2.9y, 74.5 ± 9.3 kg) and MA (n = 14, 43.6 ± 4.1y, 77.3 ± 12.9 kg) physically active males, completed a 60-min downhill running (DHR) on a treadmill at −10% incline and at 65% of maximal heart rate (HR). Biochemical, biomechanical, psychological, force production and muscle integrity (using MRI diffusion tensor imaging) markers were measured at baseline, immediately-post, and up to 48H post DHR. Results: During the DHR, HR was lower (p < 0.05) in MA compared to Y, but running pace and distance covered were comparable between groups. No statistical or meaningful differences were observed between groups for any of the outcomes. Yet, Significant (p < 0.05) time-effects within each group were observed: markers of muscle damage, cadence and perception of pain increased, while TNF-a, isometric and dynamic force production and stride-length decreased. Creatine-kinase at 24H-post and 48H-post were correlated (p < 0.05, r range = −0.57 to 0.55) with pain perception, stride-length, and cadence at 24H-post and 48H-post. Significant (p < 0.05) correlations were observed between isometric force production at all time-points and IL-6 at 48H-post DHR (r range = −0.62 to (−0.74). Conclusion: Y and MA active male amateur athletes recover in a comparable manner following an EIMD downhill protocol. These results indicate that similar recovery strategies can be used by trainees from both age groups following an aerobic-based EIMD protocol.
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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) | 0.002 | 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".