Tooth as graft material: Histologic study
Bibliographic record
Abstract
BACKGROUND: An effective regenerative protocol is key to reestablish and maintain the hard and soft tissue dimensions over time. The choice of the graft material and its properties also could have an impact on the results. To prevent alveolar ridge dimensional changes, since numerous graft materials have been suggested and in the past years, a growing interest in teeth material has been observed as a valuable alternative to synthetic biomaterials. AIM: The aim of the study was to explore the histomorphometric outcomes of tooth derivative materials as used as bone substitute material in socket preservation procedure. METHODS: After alveolar socket preservation (ASP) procedures using autologous demineralized tooth as graft material prepared by means of an innovative device, was evaluated. A total of 101 histological samples, from 96 subjects, were analyzed by evaluating the total amount of bone (BV), residual tooth material (residual graft, TT), and vital bone (VB). The section from each sample was then split in nine subsections, resulting in 909 subsections, to allow statistical comparison between the different areas. RESULTS: It was not noticed a statistically significant difference between maxillary and mandibular sites, being the amount of VB in upper jaw sites 37.9 ± 21.9% and 38.0 ± 22.0% in lower jaw sites and the amount of TT was 7.7 ± 12.2% in maxilla and 7.0 ± 11.1% in mandibles. None of the other considered parameters, including defect type and section position, were statistically correlated to the results of the histomorphometric analysis. CONCLUSIONS: ASP procedure using demineralized autologous tooth-derived biomaterial may be a predictable procedure to produce new vital bone potentially capable to support dental implant rehabilitation.
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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) | 0.004 | 0.001 |
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".