Differences in platelet‐rich plasma composition influence bone healing
Bibliographic record
Abstract
Abstract Aim Platelet‐rich plasma (PRP) is an autologous blood‐derived material that has been used to enhance bone regeneration. Clinical studies, however, reported inconsistent outcomes. This study aimed to assess the effect of changes in leucocyte and PRP (L‐PRP) composition on bone defect healing. Materials and Methods L‐PRPs were prepared using different centrifugation methods and their regenerative potential was assessed in an in‐vivo rat model. Bilateral critical‐size tibial bone defects were created and filled with single‐spin L‐PRP, double‐spin L‐PRP, or filtered L‐PRP. Empty defects and defects treated with collagen scaffolds served as controls. Rats were euthanized after 2 weeks, and their tibias were collected and analysed using micro‐CT and histology. Results Double‐spin L‐PRP contained higher concentrations of platelets than single‐spin L‐PRP and filtered L‐PRP. Filtration of single‐spin L‐PRP resulted in lower concentrations of minerals and metabolites. In vivo, double‐spin L‐PRP improved bone healing by significantly reducing the size of bone defects (1.08 ± 0.2 mm 3 ) compared to single‐spin L‐PRP (1.42 ± 0.27 mm 3 ) or filtered L‐PRP (1.38 ± 0.28 mm 3 ). There were fewer mast cells, lymphocytes, and macrophages in defects treated with double‐spin L‐PRP than in those treated with single‐spin or filtered L‐PRP. Conclusion The preparation method of L‐PRP affects their composition and potential to regenerate bone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".