Histologic and histomorphometric evaluation of the bone regeneration following cortical bone repositioning in a rabbit mandible
Bibliographic record
Abstract
BACKGROUND: Although bone graft (BG) is the gold standard for bone augmentation, its use is hampered by donor site morbidity and limited quantity. PURPOSE: To evaluate the capabilities of bone formation by cortical bone repositioning (CBR) as the healing response following grafting of autogenous bone block without filling biomaterial at the gap between gap and recipient. MATERIALS AND METHODS: Twelve Japanese White rabbits were divided into three groups (postoperative 2, 5, and 8 weeks). A cortical block was freed from the mandibular body, half of the block was positioned and fixed overlapped the original bone surface beside the defect and the other half remained only elevated above the defect. Three areas were decided for the evaluation; BG, CBR, and defect (D) area. Areas were evaluated by micro-CT, histology, and histomorphometric analysis. RESULTS: There is no statistical difference between BG and CBR by evaluating distance and area in histomorphometrical analysis (P < .05). D area showed statistical decrease compared with BG and CBR at week 2. Histologically, new bone was evident at week 2, mature bone was observed in all three areas at week 8, D area disappeared and fused completely with the elevated bone block. CONCLUSION: CBR has potential for bone augmentation as BG induced from its own regenerative ability of healing process.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".