Oxidized Titanium Implants Enhance Osseointegration via Mechanisms Involving<scp>RANK</scp>/<scp>RANKL</scp>/<scp>OPG</scp>Regulation
Bibliographic record
Abstract
BACKGROUND: The role of implant surface properties for bone formation and bone remodeling, that is, the major events during osseointegration, are incompletely understood. PURPOSE: This experimental study aimed to investigate the relation between molecular and morphological patterns at the bone interface for machined and oxidized implants. MATERIALS AND METHODS: Machined and anodically oxidized titanium implants were inserted in rat tibiae. The implants and surrounding tissue were retrieved at 1, 3, 6, 14, or 28 days for gene expression, histology, histomorphometry, backscatter scanning electron microscopy, and transmission electron microscopy. RESULTS: Compared with machined-surface implants, a higher degree of mineralized bone was found in contact with the oxidized-surface implants. After 3 days, cells adherent to the oxidized implants demonstrated a markedly higher expression of receptor activator of nuclear factor kappa-B (RANK), receptor activator of nuclear factor kappa-B ligand (RANKL), and osteoprotegerin (OPG). Whereas the OPG expression was higher at the machined implants at 6, 14, and 28 days, a higher RANKL/OPG ratio was detected at the oxidized implants. Between 3 and 14 days, both implants demonstrated a temporal increase in RANKL/OPG, corresponding to the remodeling phase at the bone-implant interface. For both implant types, the RANKL/OPG ratio sharply decreased to a low level after 28 days. CONCLUSIONS: The present results show that oxidized implants rapidly promote a high degree of mineralized bone apposition to the surface. As determined by the gene expression data, the mechanisms involve an early induction of osteoclastic differentiation and subsequently more intensive bone remodeling, which accelerates the maturation of the bone-implant interface. The present study suggests that the RANKL/OPG ratio is a sensitive indicator for monitoring the remodeling process during osseointegration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".