Evaluations of Bone Tissue Integration to Pure and Alloyed Titanium Implants
Bibliographic record
Abstract
PURPOSE: This study was performed for comparisons of tissue integration to commercially pure (CP) and titanium-6-aluminum-4 vanadium (Ti-6-Al-4V) implants using various existing three-dimensional biomechanical and two-dimensional histomorphometrical techniques, and to monitor the loosening torque during in vivo removal torque (RTQ) test with a novel unit not used before in a pilot study in rabbits. MATERIALS AND METHODS: The implants were topographically characterized and inserted in femurs and tibiae of five rabbits (in total 40 implants, 20 per group). After 16 weeks, the implant integration was biomechanically evaluated by: (1) resonance frequency test, and (2) peak RTQ test and the graph from the monitoring curve. Biopsies of the implants in situ were processed to undecalcified cut and ground sections followed by light microscopical quantifications. Shear strength calculations were performed. RESULTS: Significantly higher mean value of RTQ (p = .01) and shear strength tests (p = .03) were observed for the CP titanium implants compared to Ti-6-Al-4V implants. The monitoring curve from the RTQ test demonstrated no differences in the shape or form that could provide further information about the differences in the implant-to-bone attachment. CONCLUSIONS: The CP titanium implants showed increased RTQ and shear strength values compared to the Ti-6-Al-4V implants. The new tool of monitoring the RTQ curve could not demonstrate differences between the two materials. The exact influence of the implant materials on the surrounding tissues needs to be further investigated.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".