Osteoinductive potential of a novel biphasic calcium phosphate bone graft in comparison with autographs, xenografts, and <scp>DFDBA</scp>
Bibliographic record
Abstract
OBJECTIVES: Since the original description of osteoinduction in the early 20th century, the study and development of innovative biomaterials has emerged. Recently, novel synthetic bone grafts have been reported with potential to form ectopic bone in vivo. However, their full characterization in comparison with other leading bone grafts has not been investigated. The aim of this study was to determine the osteoinductive potential of bone grafts by comparing autogenous bone grafts, demineralized freeze-dried bone allografts (DFDBA), a commonly utilized natural bone mineral (NBM) from bovine origin (Bio-Oss), and a newly developed biphasic calcium phosphate (BCP). MATERIALS AND METHODS: Grafts were compared in vitro for their ability to stimulate bone marrow stromal cell (BMSC) migration, proliferation, and differentiation as assessed by quantitative real-time PCR for genes coding for bone markers including Runx2, collagen I, and osteocalcin. Furthermore, bone grafts were implanted in the calf muscle of 12 beagle dogs to determine their potential to form ectopic bone in vivo. RESULTS: The in vitro results demonstrate that both autografts and DFDBA show potential for cell recruitment, whereas only autografts and BCP demonstrated the ability to differentiate BMSCs toward the osteoblast lineage. The in vivo ectopic bone model demonstrated that while NBM particles were not osteoinductive and autogenous bone grafts were resorbed quickly in vivo, ectopic bone formation was reported in DFDBA and in synthetic BCP grafts. CONCLUSION: The modifications in nanotopography and chemical composition of the newly developed BCP bone grafts significantly promoted ectopic bone formation confirming their osteoinductive potential. In conclusion, the results from this study provide evidence that synthetic bone grafts not only serve as a three-dimensional scaffold but are also able to promote osteoinduction.
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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 | 0.001 | 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".