Collagen Nerve Conduits Promote Enhanced Axonal Regeneration, Schwann Cell Association, and Neovascularization Compared to Silicone Conduits
Bibliographic record
Abstract
Peripheral nerve regeneration within guidance conduits involves a critical association between regenerating axons, Schwann cells (SCs), and neovascularization. However, it is currently unknown if there is a greater association between these factors in nonpermeable versus semipermeable nerve guide conduits. We therefore examined this collaboration in both silicone- and collagen-based nerve conduits in both 5- and 10-mm-injury gaps in rat sciatic nerves. Results indicate that collagen conduits promoted enhanced axonal and SC regeneration and association when compared to silicone conduits in the shorter 5-mm-gap model. In addition, collagen tubes displayed enhanced neovascularization over silicone conduits, suggesting that these three factors are intimately related in successful peripheral nerve regeneration. At later time points (1- and 2-month analysis) in a 10-mm-gap model, collagen tubes displayed enhanced axonal regeneration, myelination, and vascularization when compared to silicone-based conduits. Results from these studies suggest that regenerating cables within collagen-based conduits are revascularized earlier and more completely, which in turn enhances peripheral nerve regeneration through these nerve guides as compared to silicone conduits.
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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) | 0.001 | 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".