Sprouting capacity of lumbar motoneurons in normal and hemisected spinal cords of the rat
Bibliographic record
Abstract
Nerve sprouting to reinnervate partially denervated muscles is important in several disease and injury states. To examine the effectiveness of sprouting of active and inactive motor units (MUs) and the basis for a limit to sprouting, one of three rat lumbar spinal roots was cut under normal conditions and when the spinal cord was hemisected at T12. Muscle and MU isometric contractile forces were recorded and muscle fibres in glycogen-depleted single muscle units enumerated 23 to 380 days after surgery. Enlargement of intact MUs by sprouting was effective in compensating for up to 80% loss of innervation. For injuries that removed >70-80% of the intact MUs, muscle contractile force and weight dropped sharply. For partial denervation of <70%, all MUs increased contractile force by the same factor in both normally active muscles and muscles whose activity was reduced by T12 hemisection. Direct measurements of MU size by counting glycogen-depleted muscle fibres in physiologically and histochemically defined muscle units, provided direct evidence for a limit in MU size, whether or not the activity of the muscles was reduced by spinal cord hemisection. Analysis of spatial distribution of muscle fibres within the outer boundaries of the muscle unit demonstrated a progressive increase in fibres within the territory to the limit of sprouting when most of the muscle unit fibres were adjacent to each other. We conclude that the upper limit of MU enlargement may be explained by the reinnervation of denervated muscle fibres by axon sprouts within the spatial territory of the muscle unit, formerly distributed in a mosaic pattern.
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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) | 0.001 | 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".