PEOT/PBT Guides Enhance Nerve Regeneration in Long Gap Defects
Bibliographic record
Abstract
Development of new nerve guides is required for replacing autologous nerve grafts for the repair of long gap defects after nerve injury. A nerve guide comprised only of electrospun fibers able to bridge a critical (15 mm) nerve gap in a rat animal model is reported for the first time. The nerve conduits are made of poly(ethylene oxide terephthalate) and poly(butylene terephthalate) (PEOT/PBT), a biocompatible copolymer composed of alternating amorphous, hydrophilic poly(ethylene oxide terephthalate), and crystalline, hydrophobic poly(butylene terephthalate) segments. These guides show suitable mechanical properties, high porosity, and fibers aligned in the longitudinal axis of the guide. In vitro studies show that both neurites and Schwann cells exhibit growth alignment with PA fibers. In vivo studies reveal that, after rat sciatic nerve transection and repair with PEOT/PBT guides, axons grow occupying a larger area compared to silicone tubes. Moreover, after repair of limiting (10 mm) and critical (15 mm) nerve gaps, PEOT/PBT guides significantly increase the percentage of regenerated nerves, the number of regenerated myelinated axons, and improve motor, sensory, and autonomic reinnervation in both gaps. This nerve conduit design combines the properties of PEOT/PBT with electrospun structure, demonstrating that nerve regeneration through long gaps can be achieved through the design of instructive biomaterial constructs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".