Histomorphometric Evaluation of Bioceramic Molecular Impregnated and Dual Acid‐Etched Implant Surfaces in the Human Posterior Maxilla
Bibliographic record
Abstract
BACKGROUND: Physical and bioceramic incorporation surface treatments at the nanometer scale showed higher means of bone-to-implant contact (BIC) and torque values compared with surface topography at the micrometer scale; however, the literature concerning the effect of nanometer scale parameters is sparse. PURPOSE: The aim of this study was to evaluate the influence of two different implant surfaces on the percentage bone-to-implant contact (BIC%) and bone osteocyte density in the human posterior maxilla after 2 months of unloaded healing. MATERIALS AND METHODS: The implants utilized presented dual acid-etched (DAE) surface and a bioceramic molecular impregnated treatment (Ossean®, Intra-Lock International, Boca Raton, FL, USA) serving as control and test, respectively. Ten subjects (59 ± 9 years of age) received two implants (one of each surface) during conventional implant surgery in the posterior maxilla. After the non-loaded period of 2 months, the implants and the surrounding tissue were removed by means of a trephine and were non-decalcified processed for ground sectioning and analysis of BIC%, bone density in threaded area (BA%), and osteocyte index (Oi). RESULTS: Two DAE implants were found to be clinically unstable at time of retrieval. Histometric evaluation showed significantly higher BIC% and Oi for the test compared to the control surface (p < .05), and that BA% was not significantly different between groups. Wilcoxon matched pairs test was used to compare the differences of histomorphometric variables between implant surfaces. The significance test was conducted at a 5% level of significance. CONCLUSION: The histological data suggest that the bioceramic molecular impregnated surface-treated implants positively modulated bone healing at early implantation times compared to the DAE surface.
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 | 0.000 | 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) | 0.002 | 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".