Platelet Rich Fibrin (PRF) Enhances Scar Resolution of High-tension Wounds in Rats
Bibliographic record
Abstract
PURPOSE: Mechanical tension is a central determinant of the size, strength, and physiology of scars formed after cutaneous injury. (1) During post-traumatic proliferation and remodeling, supraphysiologic tension modulates cell signaling and differentiation as well as angiogenic and inflammatory mediators. (2,3) Platelet-rich fibrin (PRF) is an autologous, patient-derived biologic scaffold generated from the blood that maintains a locally high concentration of growth factors, previously demonstrated to enhance angiogenesis and mitigate inflammation. (4,5) Here, we sought to evaluate the possible therapeutic relationship between PRF and cutaneous wounds in a model of variable-tension murine injury. METHOD: 60 Wistar Hannover rats were stratified to receive either high, medium, or low tension injuries via controlled dorsal skin incision/excision. Each cohort received a) isotonic solution injection (sham) or b) PRF emplacement. Wounds were followed for 28 days andTracked visually utilizing the Vancouver Scar Scale (VSS). On the 28th-day scar, the width was measured by caliper, and skin samples were collected for mechanical testing and/or histologic evaluation via H&E and Type I collagen immunochemistry. RESULTS: Wound healing was appropriately delayed under high tension conditions with the formation of more proliferative scars as assessed by the VSS. Scar width increased in direct correlation to the magnitude of tension applied. Under conditions of PRF treatment, scar/wound scores were improved vs. controls at all levels of tensions assessed. Scar width was noticeably and statistically thinner vs. control in all groups. High-tension scars retained tensile characteristics consistent with lower-tension injuries in the presence of PRF but not control treatment. PRF-treated wounds additionally demonstrated more robust Type I Collagen expression in PRF-treated high-tension wounds. CONCLUSION: PRF-treatment improved scar and wound healing characteristics vs. control. This effect was amplified in the high-tension wound environment. REFERENCES: 1. Morin G, Rand CPTM, P.A. Burgess MAJL, Voussoughi J, M. Graeber COLG. Wound healing: relationship of wound closing tension to tensile strength in rats. The Laryngoscope. 1989;99(8). doi:10.1288/00005537-198908000-00003 2. Wilkinson HN, Hardman MJ. Wound healing: Cellular mechanisms and pathological outcomes. Open Biology. 2020;10(9):200223. doi:10.1098/rsob.200223 3. Shaw TJ, Martin P. Wound repair: A showcase for cell plasticity and Migration. Current Opinion in Cell Biology. 2016;42:29-37. doi:10.1016/j.ceb.2016.04.001 4. Strauss F-J, Nasirzade J, Kargarpoor Z, Stähli A, Gruber R. Effect of platelet-rich fibrin on cell proliferation, migration, differentiation, inflammation, and osteoclastogenesis: A systematic review of in vitro studies. Clinical Oral Investigations. 2019;24(2):569-584. doi:10.1007/s00784-019-03156-9 5. Dohle E, El Bagdadi K, Sader R, Choukroun J, James Kirkpatrick C, Ghanaati S. Platelet-rich fibrin-based matrices to improve angiogenesis in an in vitro co-culture model for Bone Tissue Engineering. Journal of Tissue Engineering and Regenerative Medicine. 2017;12(3):598-610. doi:10.1002/term.2475
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".