Biomechanical Measurements of Calcium‐Incorporated Oxidized Implants in Rabbit Bone: Effect of Calcium Surface Chemistry of a Novel Implant
Bibliographic record
Abstract
BACKGROUND: In oral implantology there has been a general trend away from machine-turned minimally rough and acid-etched and blasted implants toward intermediary roughened surfaces. Mechanical interlocking at micron resolution is claimed to be the dominant reason for the fixation of such implants in bone. However, clinical demands for stronger and faster bone bonding to the implant (eg, in immediately loaded and compromised bone cases) have motivated the development of novel surfaces capable of chemical bonding. PURPOSE: The purpose of the present study is to investigate bone tissue reactions to a newly developed calciumincorporated oxidized implant. The specific aim is to assess the effect of calcium surface chemistry on the bone response. MATERIALS AND METHODS: Calcium (Ca) ion-incorporated implants were prepared by micro arc oxidation methods. Surface oxide properties were characterized by using various surface analytic techniques involving scanning electron microscopy, x-ray diffractometry, x-ray photoelectron spectroscopy, and optical interferometry. Twenty screw-shaped commercially pure (CP) titanium implants (10 turned implants [controls] and 10 Ca-incorporated implants [tests]) were inserted in the femoral condyles of 10 New Zealand White rabbits. RESULTS: After a healing period of 6 weeks, resonance frequency analyses and removal torque measurements of the Ca-incorporated oxidized implants demonstrated statistically significant improvements of implant integration with bone in comparison to machine-turned control implants (p = 0.013 and p = 0.005, respectively). CONCLUSIONS: The Ca-reinforced surface chemistry of the oxidized implants significantly improved bone responses in a rabbit model. The present study suggests that biochemical bonding at the bone-implant interface, in combination with mechanical interlocking, may play a dominant role in the fixation of Ca-incorporated oxidized implants in bone. The observed rapid and strong integration of test Ca implants may have clinical implications for immediate or early loading and improved performance in compromised bone.
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) | 0.001 | 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".