Comparing The Role of Mesenchymal Stem Cell Glue (MSCS) With Platelet Rich Fibrin (PRF) Gel in Treating Abrasions
Bibliographic record
Abstract
Abstract Introduction: Abrasions are minor injuries to the body's skin and inner linings that can be seen on any part of the body, but are most commonly found on the forehead, nose tip, cheek, and chin region. Though, facial abrasions are superficial injuries, but it can also lead to unacceptable scars and appearances. Hence, using the autologous medium as a dressing material over these abrasions can substantially reduce the tendency of scar and hyperpigmentation. A blood clot serves as the focal point for healing, with 95% red blood cells and 5% platelets making up a normal blood clot. PRF membranes prevent epithelial cells from migrating away from its surface, stimulate the development of micro vascularization, and protect open wounds. Natural stem cell therapy is the latest advancement in treatment of facial wounds and has shown to increase the level of collagen and elastin in skin and reduce scars. This study aims to compare and evaluate the outcomes of dressing materials over abrasive wounds and their role in soft tissue healing. Purpose: The study aims to evaluate the healing potential of mesenchymal stem cells and platelet rich fibrin in treating skin abrasions. Study Design: A total number of 32 patients requiring intervention in abrasive wounds were randomly divided into two groups: Group A-16 treated with PRF and Group B-16 treated with MSCs. Results: Our study found that both PRF and PRFM induces a dense fibrous matrix and stimulates angiogenesis and epithelialization, leading to the conversion of soluble fibrinogen into insoluble fibrin that polymerizes with thrombin. The PRF membrane consists of a fibrin 3D mesh polymerized structure, platelets, leukocytes, growth factors, and circulating stem cells. Post-operative pain, clinical appearance of wound bed, size of the wound along with H2O2 epithelial test and Vancouver scar scale showed no significant difference (p>0.05). Conclusion: PRF and MSCs have improved soft tissue healing, decreased discomfort, increased wound contraction and epithelization, and decreased scarring of healing wound sites. This is the first time that the efficacy of both dressing materials is compared, but additional clinical studies are needed to compare them. Future studies are needed to better understand the platelet concentrates' capacity for regeneration.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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".