Size of myelinated nerve fibres is not increased by expansion of the peripheral field in cats
Bibliographic record
Abstract
This study tests the hypothesis that target size regulates the size of myelinated sensory and motor fibres in peripheral nerves. Cat medial gastrocnemius (MG) muscles were partially denervated and the size of the remaining nerve fibres that sprouted was examined 6.4 +/- 0.9 months later to determine whether nerve fibre size increased with target size. Electrophysiological and morphometric analyses were used to quantify myelinated nerve fibre size. Charge measurements from dorsal and ventral roots were used to electrophysiologically quantify the relative number of cut nerve fibres and the average size of the remaining intact sensory and motor nerve fibres. Medial gastrocnemius muscle and motor unit forces provided indirect measurements of the increase in target size. Conduction velocities and amplitude of unitary action potentials of motor nerve fibres innervating single motor units were also measured after partial denervation. Electrophysiological measurements of nerve fibre size and morphometric measurements of outer fibre perimeters and fibre areas concurred and demonstrated that myelinated nerve fibres supplying partially denervated MG muscles did not increase in size in parallel with the increase in the target size. Thus, unlike non-myelinated nerve fibres, the size of myelinated nerve fibres does not increase as target size increases. Retrograde control of size in non-myelinated but not in myelinated nerve fibres demonstrates differences in plasticity of neurons in the somatic and autonomic nervous systems.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".