Improved bone regeneration using bone anabolic drug conjugates (C3 and C6) with deproteinized bovine bone mineral as a carrier in rat mandibular defects
Bibliographic record
Abstract
BACKGROUND: Deproteinized bovine bone mineral (DBBM) has been extensively studied and used for bone regeneration in oral and maxillofacial surgery. However, it lacks an osteoinductive ability. We developed two novel bone anabolic conjugated drugs, known as C3 and C6, of an inactive bisphosphonate and a bone activating synthetic prostaglandin agonist. The aim was to investigate whether these drugs prebound to DBBM granules have the potential to achieve rapid and enhanced bone regeneration. METHODS: Bilateral defects (4.3 mm diameter circular through and through) were created in mandibular angles of 24 Sprague-Dawley rats were filled with DBBM Control, DBBM with C3 or DBBM with C6 (n = 8 defects per group/ each timepoint). After 2 and 4 weeks, postmortem samples were analyzed by microcomputed tomography followed by backscattering electron microscopy and histology. RESULTS: DBBM grafts containing the C3 and C6 conjugated drugs showed significantly more bone formation than DBBM control at 2 and 4 weeks. The C6 containing DBBM demonstrated the highest percentage of new bone formation at 4 weeks. There was no significant difference in the percentage of the remaining graft between the different groups at 2 or 4 weeks. CONCLUSIONS: DBBM granules containing conjugated drugs C3 and C6 induced greater new bone volume generated and increased the bone formation rate more than the DBBM controls. This is expected to allow the development of clinical treatments that provide more predictable and improved bone regeneration for bone defect repair in oral and maxillofacial surgery.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".