The Effect of Platelet‐Rich Plasma on Healing of Palatal Donor Site following Connective Tissue Harvesting: A Pilot Study in Dogs
Bibliographic record
Abstract
BACKGROUND: Peri-implant plastic surgery includes soft tissue enhancement by connective tissue grafting. The palatal donor site provides peri-implant keratinized mucosa and soft tissue height. Platelet-rich plasma (PRP) contains growth factors that may enhance early healing. PURPOSE: The present animal study investigated the effect of PRP on wound healing of palatal donor site after connective tissue harvesting. MATERIALS AND METHODS: In 12 mongrel dogs, bilateral palatal connective tissues of 10 × 15 mm were harvested. At test site, PRP was applied into the wound, and the contralateral site served as control. The healing was evaluated clinically and histologically at 1 week, 2 weeks, and 4 weeks after surgeries. Exact binomial probability and Wilcoxon signed-rank test were used to compare the clinical and histologic measurements. RESULTS: No statistically significant differences between PRP and control sites were measured with regard to clinical healing (p = 1.000) and histologic variables, including inflammatory cells (p = .750), collagen fibers (p = .375), and granulation tissue (p = .500) at any time interval. CONCLUSION: The addition of PRP to palatal mucosal wound sites did not accelerate wound healing.
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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 | 0.002 | 0.001 |
| 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) | 0.001 | 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".