Sequential Healing at Calcium‐ versus Calcium Phosphate‐Modified Titanium Implant Surfaces: An Experimental Study in Dogs
Bibliographic record
Abstract
PURPOSE: The aim of this paper was to study the sequential healing of bone tissues at implants with different configuration and different modified surfaces. MATERIALS AND METHODS: Twelve Beagle dogs were used. Extractions of all teeth from the second premolar to the first molar were performed in both sides of the mandible. After 3 months, full-thickness flaps were elevated and two implants of different systems and with different surfaces were randomly installed in the premolar region in one side of the mandible. One surface was acid etched and further modified with calcium ions (BTI unicCa®), the other was sandblasted and acid etched plus a nanometer calcium phosphate deposition (3i T3®). The flaps were sutured to allow a fully submerged healing. The surgery on the other side of the mandible and the sacrifices were planned in such a way to obtain biopsies representing the healing after 1, 2, 4, and 8 weeks (n = 6 per period). RESULTS: After 1 and 2 weeks of healing, the mean values of new bone apposition on the implant surfaces were 5.9 ± 3.3% and 29.8 ± 16.0% at BTI unicCa and 4.6 ± 3.3% and 12.4 ± 5.6% at 3i T3, respectively. After 4 and 8 weeks, the percentage increased, being 49.4 ± 8.1% and 63.6 ± 7.3% at BTI unicCa and 40.3 ± 10.0% and 47.3 ± 20.2 at 3i T3, respectively. Differences statistically significant between the two surfaces were found only at the 2- and 4-week observation periods. Concomitantly, the old bone was resorbed at both surfaces from about 15-17% after 1 week to about 4-6% after 8 weeks of healing. CONCLUSION: Moderately rough surfaces modified with calcium ions or discrete calcium phosphate nanocrystalline deposition showed similar patterns of sequential healing. Higher new bone percentages were found at BTI unicCa compared with the 3i T3 implants, the difference being statistically significant at 2 and 4 weeks observation.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".