Recovery of Motoneuron Output Is Delayed in Old Men Following High-Intensity Fatigue
Bibliographic record
Abstract
Despite an age-related slowing in the contractile properties of the triceps surae, inherently low maximal motor unit firing rates (MUFRs) in the soleus are unchanged. Fatigue following high-intensity contractions is characterized by contractile slowing in conjunction with a reduction in MUFRs in young adults. Here we exploit the ageing model of the soleus to assess changes in neuromuscular function during fatigue and short-term recovery. We hypothesize that a high-intensity sustained contraction will cause minimal reductions in MUFRs in young and old subjects but that recovery of MUFRs will be delayed in aged subjects. We compared the effects of a high-intensity sustained task on the MUFRs of the soleus and triceps surae contractile properties in six young (approximately 24 yr) and six old (approximately 75 yr) men. Various measures of the contractile function of the triceps surae were tested during two to six sessions via maximal voluntary isometric contractions (MVCs) and tibial nerve stimulation. Populations of MUFR trains were recorded from the soleus during brief (approximately 7 s) MVCs, a high-intensity (75% MVC) sustained fatiguing task, and brief MVCs following task failure at 1, 2, 5, and 10 min. Old men had greater time to task failure than the young (approximately 138 and approximately 100 s, respectively). Voluntary activation was near maximal (>99%) for all subjects but at task failure, decreased to approximately 89% in both groups. Maximal MUFRs, for both groups, were reduced by approximately 44% and twitch contraction duration slowed by approximately 30% following task failure. Contraction duration recovered equally for both groups within 2 min, but maximal MUFRs did not recover until 5 min in the old compared with 1 min for the young. The surprising fatigue-induced reduction in MUFRs was similar for both groups, but despite a similar recovery of contractile properties for both, recovery of MUFRs was impaired in the old subjects.
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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 | 0.001 |
| 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".