EFFECT OF BOTULINUM TOXIN ON SURGICAL WOUND HEALING AND SCAR FORMATION (AN EXPERIMENTAL STUDY)
Bibliographic record
Abstract
Introduction: The process of wound healing is complicated. Despite research, hypertrophic scars still occur and can pose functional and aesthetic issues. Improvement for hypertrophic scars has been attained using a variety of treatment modalities. The strain from the underlying muscles working on the wound edge throughout the healing process is a critical factor in shaping the scar's final appearance. Since botulinum toxin type A (BTA) causes total muscle paralysis, it was suggested as a possible treatment.Objectives: To evaluate the effect of BTA injection on the final appearance of the surgical scar.Materials and Methods: Thirty-six mature male New Zealand rabbits weighing 3.5–4 kg were studied experimentally (one year of age). They were divided into two groups: One received BTA injections into the cheek muscles surrounding a Y-shaped surgical incision. The other group received no further treatment after the incision. A follow-up was performed after 2, 4, and 6 weeks for the assessment of the scar parameters (wound width and Vancouver scar scale (VSS), along with clinical photographs). After each period, the sacrifice group of rabbits was done. Samples were prepared for histological and histomorphometric analysis by being dissected.Results: When compared to the control group, the BTA-treated group showed an improvement in the appearance of scars, VSS and a reduced increase in wound width. Histological and histomorphometric results indicate that the BTA group had a better layout and less collagen deposition than the control group.Conclusions: BTA injection effectively reduced collagen fibril production and improved hypertrophic scar appearance.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".