Sinus Lift Using a Nanocrystalline Hydroxyapatite Silica Gel in Severely Resorbed Maxillae: Histological Preliminary Study
Bibliographic record
Abstract
PURPOSE: The aim of this preliminary study was to evaluate histologically a nanocrystalline hydroxyapatite silica gel in maxillary sinus floor grafting in severely resorbed maxillae. MATERIALS AND METHODS: A total of 16 consecutive patients scheduled for sinus lift were recruited during this study. Patients were randomly divided in two groups, eight patients each. In both groups, preoperative residual bone level ranged between 1 and 3 mm (mean value of 2.03 mm). No membrane was used to occlude the buccal window. Second surgery was carried out after a healing period of 3 months in Group 1 and 6 months in Group 2. Using a trephine bur, one bone specimen was harvested from each augmented sinus and underwent histological and histomorphometric analysis. RESULTS: Histological analysis showed significant new bone formation and remodeling of the grafted material. In the cores obtained at 6 months, regenerated bone, residual NanoBone, and bone marrow occupied respectively 48 +/- 4.63%, 28 +/- 5.33%, and 24 +/- 7.23% of the grafted volume. In the specimens taken 3 months after grafting, mean new bone was 8 +/- 3.34%, mean NanoBone was 45 +/- 5.10%, and mean bone marrow was 47 +/- 6.81% of the bioptical volume. CONCLUSIONS: Within the limits of this preliminary prospective study, it was concluded that grafting of maxillary sinus using nanostructured hydroxyapatite silica gel as only bone filler is a reliable procedure also in critical anatomic conditions and after early healing period.
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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".