The Effect of Decortication for Periosteal Expansion Osteogenesis Using Shape Memory Alloy Mesh Device
Bibliographic record
Abstract
BACKGROUND: In conventional bone grafting technique, decortication procedure enhances the healing process and bone regeneration to reach the grafted site more readily. PURPOSE: This study evaluates to improve periosteal expansion osteogenesis (PEO) using a shape memory alloy mesh (SMA) device with decortication in a rabbit model. MATERIALS AND METHODS: The SMA device was inserted under the periosteum at the forehead and pushed, bent, and attached to the bone surface and fixed with a titanium screw. Twelve rabbits were divided into two groups: PEO without decortication (P group) and with decortication (D group). After 2 weeks, the screw was removed, and the mesh was activated by its own elasticity. Rabbits were sacrificed 5 (P1/D1) and 8 (P2/D2) weeks after operation and histologically and radiographically evaluated. RESULTS: The mean activation height was 2.9 ± 0.5 mm. The ratio of new bone volume in the elevated volume was 17.6% in P1, 59.8% in D1 33.4% in P2, and 65.1% in D2. D group had a statistically higher volume of new bone than P group during each period (p < .05). CONCLUSION: PEO with decortication appears to be a promising clinical alternative for bone augmentation and introduces the new concept of "dynamic graft and guided bone regeneration (GBR)."
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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".