Regeneration into Protected and Chronically Denervated Peripheral Nerve Stumps
Bibliographic record
Abstract
OBJECTIVE: Delayed repair of peripheral nerve injuries often results in poor motor functional recovery. This may be a result of the deterioration or loss of endoneurial pathways in the distal nerve stump before motor axons can regenerate into the stump. METHODS: Using the rat femoral nerve, we protected distal endoneurial pathways of the saphenous nerve with either cross-suture of the quadriceps motor nerve (Group A) or resuture of the saphenous nerve (Group B) to compare later motor regeneration into the "protected" saphenous nerve pathway to chronic denervation and "unprotected" saphenous nerve (Group C). A total of 60 rats, 20 per group, were operated on. After this protection (or lack thereof) for 8 weeks, the motor branch of the femoral nerve was cut and sutured to the distal saphenous nerve to allow motor regeneration into protected and unprotected saphenous nerve stumps. The quantitative assessment of axonal regeneration was performed after 6 weeks by use of nerve sampling for axon counts and retrogradely labeled motor neuron counts. RESULTS: Significantly more myelinated axons innervated the motor (A) than the sensory (B) and no-protection (C) groups. There were significantly more retrogradely labeled femoral motor neurons in Group A than in the unprotected group (C). CONCLUSION: We conclude that even 2 months of denervation of the distal nerve pathway is deleterious to regeneration and that protection of the pathway improves subsequent reinnervation and regeneration. Moreover, if the desired regeneration is motor, protection of the distal nerve pathway by a motor nerve conditions is better than a sensory nerve.
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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".