Experimental strategies to promote functional recovery after peripheral nerve injuries
Bibliographic record
Abstract
The capacity of Schwann cells (SCs) in the peripheral nervous system to support axonal regeneration, in contrast to the oligodendrocytes in the central nervous system, has led to the misconception that peripheral nerve regeneration always restores function. Here, we consider how prolonged periods of time that injured neurons remain without targets during axonal regeneration (chronic axotomy) and that SCs in the distal nerve stumps remain chronically denervated (chronic denervation) progressively reduce the number of motoneurons that regenerate their axons. We demonstrate the effectiveness of low-dose, brain-derived neurotrophic and glial-derived neurotrophic factors to counteract the effects of chronic axotomy in promoting axonal regeneration. High-dose brain-derived neurotrophic factor (BDNF) on the other hand, acting through the p75 receptor, inhibits axonal regeneration and may be a factor in stopping regenerating axons from forming neuromuscular connections in skeletal muscle. The immunophilin, FK506, is also effective in promoting axonal regeneration after chronic axotomy. Chronic denervation of SCs (>1 month) severely deters axonal regeneration, although the few motor axons that do regenerate to reinnervate muscles become myelinated and form enlarged motor units in the reinnervated muscles. We found that in vitro incubation of chronically denervated SCs with transforming growth factor-beta re-established their growth-supportive phenotype in vivo, consistent with the idea that the interaction between invading macrophages and denervated SCs during Wallerian degeneration is essential to sustain axonal regeneration by promoting the growth-supportive SC phenotype. Finally, we consider the effectiveness of a brief period of 20 Hz electrical stimulation in promoting the regeneration of axons across the surgical gap after nerve repair.
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".