Adaptive and maladaptive motor axonal sprouting in aging and motoneuron disease
Bibliographic record
Abstract
Motor unit (MU) enlargement by sprouting is an important compensatory mechanism for loss of functional MUs during normal aging and neuromuscular disease. Perisynaptic Schwann cells at neuromuscular junctions extend processes that bridge between denervated and reinnervated endplates, and guide axonal sprouts to reinnervate the denervated endplates. In a rat model of partial denervation, high levels of daily neuromuscular activity have been shown to inhibit the outgrowth of sprouts by preventing Schwann cell bridging. In this review, we consider (1) the relative roles of increasing levels of oxidative stress and neuromuscular activity to the destabilization of neuromuscular junctions with age and disease, and (2) how a progressive increase in the neuromuscular activity of declining numbers of functional MUs contributes to the progressive failure of adaptive sprouting and, in turn, to the progressive muscle weakness in the motoneuron diseases of post-polio syndrome and amyotrophic lateral sclerosis. We conclude that there is a time-related progression of MU loss, adaptive sprouting followed by maladaptive sprouting, and continuing recession of terminals during normal aging. The progression is accelerated in motoneuron disease, progressing more rapidly in the post-polio syndrome after prolonged denervation and extremely rapidly in ALS.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".