Assessing Bone Regeneration with T-PRF and L-PRF: Micro-CT Study
Bibliographic record
Abstract
The purpose of this study is to compare the efficacy of locally applied Titanium-Prepared Platelet-Rich Fibrin(T-PRF) and Leukocyte-Platelet Rich Fibrin (L-PRF) in bone defect healing through a micro-CT analysis and histopathological examination in rabbit models. Eight male New Zealand rabbits aged 4-6 months were subjected to surgery to create circular bicortical defects with a 6 mm diameter. The defects were treated with either T-PRF, L-PRF, or saline solution as a control. Micro-CT imaging with a Bruker Skyscan 1272 system was utilized to evaluate bone regeneration, followed by histological examination after sacrifice. Statistical analysis was performed to determine significant differences among the groups. Analysis of micro-CT data revealed significant differences among the experimental groups in terms of bone volume, trabecular thickness, trabecular number, connectivity, and connectivity density (p<0.05). Both T-PRF and L-PRF groups exhibited improved bone parameters compared to the control group, with the L-PRF group demonstrating even better outcomes. However, trabecular separation and bone surface area to volume ratio did not show significant differences among the groups (p>0.05). Histological examination indicated advanced healing stages in the L-PRF group, suggesting the efficacy of both T-PRF and L-PRF in bone regeneration, with L-PRF showing superior effects. Due to the surface modifications of titanium tubes used in the preparation protocol of T-PRF extracts, sterilization conditions, and environmental factors, they can influence the quality of the obtained extract. Considering the challenges in standardizing the factors in the preparation protocol of T-PRF, it is recommended to apply L-PRF for the healing of bone defects.
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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 | 0.000 |
| 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 | 0.001 | 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".