Innervation and neuromuscular control in ageing skeletal muscle
Bibliographic record
Abstract
Changes in the neuromuscular system affecting the ageing motor unit manifest structurally as a reduction in motor unit number secondary to motor neuron loss; fibre type grouping due to repeating cycles of denervation-reinnervation; and instability of the neuromuscular junction that may be due to either or both of a gradual perturbation in postsynaptic signalling mechanisms necessary for maintenance of the endplate acetylcholine receptor clusters or a sudden process involving motor neuron death or traumatic injury to the muscle fibre. Functionally, these changes manifest as a reduction in strength and coordination that precedes a loss in muscle mass and contributes to impairments in fatigue. Regular muscle activation in postural muscles or through habitual physical activity can attenuate some of these structural and functional changes up to a point along the ageing continuum. On the other hand, regular muscle activation in advanced age (>75 years) loses its efficacy, and at least in rodents may exacerbate age-related motor neuron death. Transgenic mouse studies aimed at identifying potential mechanisms of motor unit disruptions in ageing muscle are not conclusive due to many different mechanisms converging on similar motor unit alterations, many of which phenocopy ageing muscle. Longitudinal studies of ageing models and humans will help clarify the cause and effect relationships and thus, identify relevant therapeutic targets to better preserve muscle function across the lifespan.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".