Neuromuscular fatigue and aging: Central and peripheral factors
Bibliographic record
Abstract
A limited number of studies have investigated the effect of old age on neuromuscular fatigue, yet a variety of protocols have been used to compare the fatigability of old and young humans. These include voluntary isometric and isokinetic contraction protocols at maximal and submaximal intensities, and electrical stimulation protocols of continuous or intermittent stimulation at a variety of stimulation frequencies. The results of these studies are summarized in this review. Although it seems reasonable to suggest that age-related changes in muscle morphology and motor unit remodeling, as well as the associated loss of strength and slowed contractile properties, may improve the resistance to neuromuscular fatigue in old humans, the collective results suggest that it is not possible to make this generalization. In fact, it cannot be generalized that the muscles of old humans are either more or less fatigable than young adults because the extent of the difference in fatigability relies strongly on the fatigue task performed (task-dependency). Age-related changes that occur within the neuromuscular system may result in some candidate fatigue sites increasing or decreasing their susceptibility to failure under specific task conditions. These candidate fatigue sites include central drive, muscle membrane excitability, excitation-contraction coupling mechanisms, and metabolic capacities. The effect of old age on these various central and peripheral sites is discussed with respect to their relative contribution during different fatigue tasks. Moreover, the impact of the possible confounding effects of subject habituation, physical activity status, and sex on the fatigability comparison is addressed.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".