Importance of Ca<sup>2+</sup> Modifications for Osseointegration of Smooth and Moderately Rough Anodized Titanium Implants – A Removal Torque and Histological Evaluation in Rabbit
Bibliographic record
Abstract
BACKGROUND: Incorporation of Ca(2+) into the titania of anodized titanium surfaces has been found to enhance osseointegration. It provides a stable surface when the ions are incorporated into the oxide layer during the anodizing process. The Ca(2+) may suggestively be prominent sites for mineral induction, attract proteins, and catalyze intracellular cascades. PURPOSE: The aim of the present study was to evaluate the osseointegration of smooth (S(a) < 0.5 µm) and moderately rough (S(a) 1.0-2.0 µm) commercially pure titanium implants, with and without Ca(2+) , in order to reflect on the importance of surface chemistry in relation to topography. MATERIALS AND METHODS: Anodized implants with (OxCa) or without Ca(2+) (Ox), blasted implants (Bl), and blasted anodized implants, with (BlOxCa) or without Ca(2+) (BlOx), were inserted in rabbit femur and tibia. The implant surfaces were characterized using interferometry, scanning electron microscopy, and X-ray photoelectron spectroscopy prior to implant installation. Removal torque (RTQ) measurements were executed on all implants after a healing period of 12 weeks. The implants were, thereafter, removed en bloc with surrounding tissues and prepared for histological evaluations. RESULTS: RTQ measurements of tibial implants revealed significantly higher values for BlOxCa implants (90.7 ± 23.3 Ncm) compared to OxCa (64.6 ± 18.2 Ncm) and BlOx implants (69.7 ± 17.5 Ncm) (p = 0.029). Ca(2+) modification of smooth implants placed in the femur did not reveal any differences. CONCLUSION: Ca(2+) modification of smooth implants resulted in similar interfacial shear strength as moderately rough implants and Ca(2+) modification of moderately rough implants demonstrated the significantly strongest interfacial shear strength when placed in rabbit tibia. This possibly demonstrated surface chemistry compensating for lesser roughness.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".