Bibliographic record
Abstract
Injured peripheral nerves but not central nerves have the capacity to regenerate and reinnervate their target organs. After the two most severe peripheral nerve injuries of six types, crush and transection injuries, nerve fibers distal to the injury site undergo Wallerian degeneration. The denervated Schwann cells (SCs) proliferate, elongate and line the endoneurial tubes to guide and support regenerating axons. The axons emerge from the stump of the viable nerve attached to the neuronal soma. The SCs downregulate myelin-associated genes and concurrently, upregulate growth-associated genes that include neurotrophic factors as do the injured neurons. However, the gene expression is transient and progressively fails to support axon regeneration within the SC-containing endoneurial tubes. Moreover, despite some preference of regenerating motor and sensory axons to "find" their appropriate pathways, the axons fail to enter their original endoneurial tubes and to reinnervate original target organs, obstacles to functional recovery that confront nerve surgeons. Several surgical manipulations in clinical use, including nerve and tendon transfers, the potential for brief low-frequency electrical stimulation proximal to nerve repair, and local FK506 application to accelerate axon outgrowth, are encouraging as is the continuing research to elucidate the molecular basis of nerve 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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.004 |
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".