An Evaluation of Hydroxyapatite and Biphasic Calcium Phosphate in Combination With Pluronic F127 and BMP on Bone Repair
Bibliographic record
Abstract
Calcium phosphates like hydroxyapatite (HA), beta-tricalcium phosphate (beta-TCP), and their mixtures (biphasic calcium phosphates; BCP) are used clinically to repair bone defects. These materials can be difficult to handle and have no inherent biological activity. Handling properties of other bone substitute materials have been improved by combining them with an inert carrier such as Pluronic F-127 (Pluronic, BASF, Mt. Olive, NJ), while the addition of bone morphogenetic proteins (BMP) with such implants has also been shown to enhance bone repair. This study assessed the impact of adding Pluronic and BMPs to an HA (C-Graft) or a BCP (80/20 HA/beta-TCP ratio; Algisorb) implant's ability of promote bony repair in the rabbit calvarial defect model.Twenty-five New Zealand white rabbits were divided into 5 groups of 5 animals each. Bilateral calvarial defects were made in the parietal bones of each animal. HA or BCP alone or combined with Pluronic and/or BMP were implanted into the defect sites. Animals were euthanized at 6 weeks, postoperatively. Bone regeneration was evaluated quantitatively by histomorphometry. The amount of bone regeneration, which occurred in defects containing HA and BCP, was similar over the time period studied. Incorporating Pluronic increased handling and moldability without compromising osteoconductivity of either calcium phosphate. The addition of BMP significantly increased the amount of new bone formed with all calcium phosphates studied (P < 0.05). These results suggest that Pluronic can be added to calcium phosphates to enhance handling and moldability without any negative effects on their biocompatibility and that healing can be enhanced with the incorporation of BMPs.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 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".