Chemical communication between regenerating motor axons and Schwann cells in the growth pathway
Bibliographic record
Abstract
There are receptors on denervated Schwann cells that may respond to the neurotransmitters that are released from growth cones of regenerating motor axons. In order to ascertain whether the interaction of the transmitters and their receptors plays a role during axon regeneration, we investigated whether pharmacological block of the interaction would reduce the number of motoneurons that regenerate their axons after nerve section and surgical repair. Peripheral nerves in the hindlimbs of rats and mice were cut and repaired, and various drugs were applied to the peripheral nerve stump either directly or via mini-osmotic pumps over a 2-4-week period to block the binding of acetylcholine to nicotinic and muscarinic acetylcholine receptors (AChRs: alpha-bungarotoxin, tubocurarine, atropine and, gallamine) and binding of ATP to P2Y receptors (suramin). In rats, the nicotinic AChR antagonistic drugs and suramin reduced the number of motoneurons that regenerated their axons through the distal nerve stump. In mice, suramin significantly reduced the upregulation of the carbohydrate HNK-1 on the Schwann cells in the distal nerve stump that normally occurs during motor axon regeneration. These data indicate that chemical communication between regenerating axons and Schwann cells during axon regeneration via released neurotransmitters and their receptors may play an important role in axon regeneration.
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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 | 0.000 | 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) | 0.002 | 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".