Effect of Platelet-rich Plasma and Brief Electrical Stimulation Following Facial Nerve Neurorrhaphy in a Rat Model
Bibliographic record
Abstract
Background: With ongoing investigations to improve facial nerve recovery after injury, brief electrical stimulation (BES) and platelet-rich plasma (PRP) application have become promising modalities. The usage of combined modalities has not yet been investigated. We aimed to evaluate differences in facial nerve regeneration between rats receiving BES (group 1) and rats receiving BES plus PRP (group 2) following transection and primary neurorrhaphy. Methods: This was a prospective randomized animal study of 2 groups of 6 rats that underwent facial nerve transection and repair at the main trunk of the nerve. Both groups received BES on postoperative day 0 for 1 hour using an implantable stimulation device, with group 2 additionally receiving concurrent PRP. The primary measure of whisker amplitude was recorded from 2 to 8 weeks postoperatively. Results: At week 2, the average whisker amplitude for groups 1 and 2 was 6.5 and 2.0 degrees, respectively. At week 4, group 1 remained unchanged at 6.1 degrees, whereas group 2 improved to 10.1 degrees. By 6 weeks, average amplitudes were 8.2 and 14.0 degrees, respectively. By week 8, measures were 9.8 and 16.7 degrees, respectively. All results were statistically significant (P < 0.05). Conclusions: Application of BES and PRP following neurorrhaphy in a rat model yields a greater effect than BES alone in expediting facial nerve recovery.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".