Cross-bridge Kinetics Impairment In Elite Octogenarian Masters Athletes
Bibliographic record
Abstract
The association between adult normal aging and impairments of the neuromuscular system as well as the application of exercise training to attenuate these problems have already been reported by several studies. However, it is still not clear whether intrinsic cross-bridge kinetics, especially of the ‘slow’ resilient fibre type, are affected in aging muscle, and if this kinetics would be better preserved in high functioning elderly athletes. PURPOSE: to compare cross-bridge kinetics in healthy non-athlete octogenarians to age-matched world class masters athletes, and young controls. METHODS: Skinned muscle fibres obtained from vastus lateralis biopsies of young (∼23y), old non-athlete (NA) adults (∼80y), and age-matched world class masters athletes (MA; ∼80y) were first isometrically activated to assess force per cross-sectional (Po), then submitted to slack test, and shortening-re-stretch protocol, by which unloaded shortening velocity (Vo), and the rate constant of force redevelopment (ktr) were respectively obtained. A post-hoc analysis was performed, and only the mechanical properties of ‘slow type’ fibres based on unloaded shortening velocity measurements were used (the level of significance was set at P<0.05). RESULTS: MA and NA produced ∼55% and 45% lower Po than young. Vo for both MA and NA old groups were ∼62% and 42% slower, respectively, compared with young. Both MA and NA adults had ∼2 times slower values for ktr compared with young. CONCLUSION: The lower ktr in both old groups relative to young suggests that impaired cross-bridge kinetics was, at least in part, responsible for impaired single fibre contractile properties, i.e Vo, Po, with aging. Apparently, masters athletes’ higher performance cannot be attributed to their intrinsic cross-bridge kinetics.
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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) | 0.002 | 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".