Treatment of a commercial, machined surface titanium implant with H<sub>2</sub>SO<sub>4</sub>/H<sub>2</sub>O<sub>2</sub> enhances contact osteogenesis
Bibliographic record
Abstract
BACKGROUND: It has recently been reported that controlled chemical oxidation of titanium (Ti) with sulfuric acid (H(2)SO(4))/hydrogen peroxide (H(2)O(2)) significantly influences the early stages of in vitro osteogenesis. The aim of this study was to evaluate whether this chemical treatment can also influence in vivo bone formation. MATERIAL AND METHODS: Ti implants (Mk III) were etched with H(2)SO(4)/H(2)O(2) for 4 h at room temperature. Mandibular premolars were extracted in eight dogs and, after 3 months, three treated and three untreated implants were placed in each animal. At 3 and 8 weeks postimplantation, the animals were sacrificed, and the implants with surrounding bone were harvested, fixed with formaldehyde, and processed for embedding in LR White. Sections of bone with the implants were prepared, stained with Stevenel's blue and Alizarin red, and analyzed histomorphometrically for percentage of bone-to-implant contact (BIC), percentage of mineralized bone area between threads (BABT), and percentage of mineralized bone area within the mirror area (BAMA). Data were analyzed statistically using two-way analysis of variance. RESULTS: Treated implants exhibited significantly more (P<0.05) BIC than control, untreated ones both at 3 (68.1% vs. 27.9%) and 8 weeks (73.5% vs. 14.7%) postimplantation. However, there was no difference in the BABT and BAMA. Histological analysis confirmed that, in most cases, new bone in contact with the implant formed in a direction away from it. CONCLUSIONS: These data indicate that a controlled chemical oxidation of Ti implants significantly enhances contact osteogenesis and suggest that this treatment may be beneficial for early loading of implants.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".