Repair of the Sciatic Nerve Defect with a Direct Gradual Lengthening of Proximal and Distal Nerve Stumps in Rabbits
Bibliographic record
Abstract
BACKGROUND: The current clinical repair method used for the segmental peripheral nerve defect is autogenous nerve grafting. However, this method has several inherent disadvantages. Therefore, the authors have invented an alternative method for repairing the segmental peripheral nerve defect with a direct gradual lengthening of nerve stumps. In this study, for the clinical application, the authors developed a new external nerve-lengthening device for lengthening peripheral nerve stumps daily without anesthesia. METHODS: In this study, a nerve segment 20 mm in length was resected from the rabbit sciatic nerve. In the nerve-lengthening group, direct nerve lengthening was performed in the proximal and distal nerve stumps at a rate of 1 mm/day without anesthesia. After being lengthened for 22 days, both proximal and distal nerve stumps were evaluated by immunohistochemical analysis. When confirming that both nerve stumps were successfully lengthened, a direct end-to-end neurorrhaphy was performed. As a control, 20-mm-long autografting was performed immediately after nerve resection. Nerve regeneration was evaluated by electrophysiologic and histologic examination at 16 weeks after the first operation in both the nerve-lengthening and the control groups. RESULTS: The results of both electrophysiologic evaluation and histologic examination showed that the nerve-lengthening group performed significantly better than the autografting group. CONCLUSION: The gradual nerve-lengthening procedure can be used as an alternative therapeutic method for repairing segmental peripheral nerve defects, which proved to be advantageous over widely adopted autogenous nerve grafting.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".