Local Polyethylene Glycol in Combination with Chitosan Based Hybrid Nanofiber Conduit Accelerates Transected Peripheral Nerve Regeneration
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVE: The incapability to promptly improve behavioral function after discontinuation of peripheral nerves is a current problem in clinical practice. Effect of local polyethylene glycol in combination with chitosan-based hybrid nanofiber conduit was assessed. STUDY DESIGN: A 10-mm sciatic nerve defect was bridged using a chitosan-based hybrid nanofiber conduit (Chitosan) filled with phosphate-buffered saline. In authograft group (AUTO), a segment of sciatic nerve was transected and reimplanted reversely. In polyethylene glycol-treated group (CHIT/PEG), the conduit was filled with polyethylene glycol solution. The regenerated fibers were studied within 12 weeks after surgery. RESULTS: The behavioral and functional tests confirmed faster recovery of the regenerated axons in PEG-treated group compared to Chitosan group (p < .05). The mean ratios of gastrocnemius muscles weight were measured. There was statistically significant difference between the muscle weight ratios of CHIT/PEG and Chitosan groups (p < .05). Morphometric indices of regenerated fibers showed number and diameter of the myelinated fibers were significantly higher in CHIT/PEG than in Chitosan. In immuohistochemistry, the location of reactions to S-100 in CHIT/PEG was clearly more positive than Chitosan group. CONCLUSION: polyethylene glycol solution when loaded in a chitosan-based hybrid nanofiber conduit resulted in acceleration of functional recovery and quantitative morphometric indices of sciatic nerve.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it