Effect of Platelet Releasate on Bone Cell Migration and Recruitment In Vitro
Bibliographic record
Abstract
The use of platelets and platelet products has become increasingly popular clinically as a means of accelerating endosseous wound healing. It is likely that growth factors released by activated platelets at the site of injury play a role in bone regeneration by stimulating the migration and proliferation of bone cells. In this study, a novel in vitro assay was developed to study the effects of platelet releasate (PR) collected from activated platelet concentrate on rat bone marrow-derived cells. Cultures of primary rat bone marrow cells were overlaid with a fibrin matrix, and the number of cells migrating within the three-dimensional matrix and the leading front of migration were quantified. The addition of PR to the top of the fibrin gels at different time points caused a 25% increase in the leading front of migration and a 3.5-fold increase in the number of migrating cells. Platelet releasate was also shown to have a mitogenic effect on bone cells in proliferation studies. Comparison between migration and proliferation data indicated that PR stimulates the initial recruitment of bone marrow cells to migration. This assay further allowed the determination that rat bone marrow cells are capable of exerting contractile forces on fibrin matrices and that matrix contraction is directly related to the migratory activity of cells. The results provide a potential mechanism to explain why biologically active platelet-derived factors enhance endosseous 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".