Acid and Alkaline Etching of Sandblasted Zirconia Implants: A Histomorphometric Study in Miniature Pigs
Bibliographic record
Abstract
BACKGROUND: Zirconia (ZrO2 ) has received interest as a dental material; however, little information is available on the impact of surface modifications on the osseointegration of zirconia implants. PURPOSE: The aim of the present study was to determine the effect of acid or alkaline etching of sandblasted ZrO2 implants on bone apposition in vivo. METHODS: Cylindrical ZrO2 implants with two circumferential grooves were placed in the maxilla of 12 miniature pigs. Biopsies were harvested after 1, 2, 4, and 8 weeks of healing. Undecalcified toluidine blue-stained ground sections were produced. The bone-to-implant contact, the bone area, and the presence of multinucleated giant cells were determined by histomorphometry. An uncorrected explorative statistical analysis was performed. RESULTS: Acid etching but not alkaline etching of sandblasted ZrO2 implants caused more bone-to-implant contact than sandblasted ZrO2 implants. The bone area was unaffected by the surface modifications. Acid and alkaline etching both increased the formation of multinucleated giant cells at the implant surface. CONCLUSIONS: This study provides a scientific basis to further investigate the impact of acid etching of sandblasted ZrO2 implants on osseointegration and the role of multinucleated giant cells in this process.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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; 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".