Leucocyte‐ and platelet‐rich fibrin regulates expression of genes related to early wound healing in human gingival fibroblasts
Bibliographic record
Abstract
BACKGROUND: Leucocyte- and platelet-rich fibrin (L-PRF) is a blood-derived biomaterial rich in leucocytes and platelets embedded in a high-density fibrin network that can be compressed into a membrane and used in surgical applications to stimulate tissue regeneration and wound healing, especially in oral cavity. This study aimed to determine the combined effects of the growth factors and cells present in L-PRF on fibroblasts that directly face the L-PRF membranes placed during surgical procedures. METHODS: The effect of L-PRF from six donors on the expression of 84 key wound healing genes in normal human gingival fibroblasts was tested by RT-qPCR. RESULTS: L-PRF significantly regulated the expression of 33 fibroblast genes (39%), including interleukins, myofibroblast-, extracellular matrix- and angiogenesis-associated genes, and matrix metalloproteinase-1 and -3. L-PRF regulated fibroblast gene expression both time- and dose-dependently, and the effects were mediated by mitogen-activated protein kinases ERK1/2, JNK and p38. L-PRF also stimulated fibroblast wound closure and promoted the ability of fibroblasts to induce endothelial tube formation. L-PRF-induced gene expression changes in fibroblast were similar to those observed in early human and pig wounds. CONCLUSIONS: This study provides new insights into the biological mechanism by which L-PRF regulates key gingival fibroblast functions important in wound healing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".