Deproteinized Bovine Bone Used as an Adjunct to Guided Bone Augmentation: An Experimental Study in the Rat
Bibliographic record
Abstract
BACKGROUND: Promising results have been reported following treatment of periodontal and peri-implant bone defects with deproteinized bovine bone grafts, but their influence on bone formation has not been clarified. PURPOSE: The goal of this study was to examine whether implantation of deproteinized bovine bone (Bio-Oss, Geistlich AG, Wolhusen, Switzerland) influences bone formation when used as an adjunct to guided bone augmentation (GBA). MATERIALS AND METHODS: A rigid, hemispherical, Teflon capsule was loosely packed with a standardized quantity of Bio-Oss and placed with its open part facing the lateral surface of the mandibular ramus (test) in 30 rats. At the contralateral side of the jaw, an empty capsule was placed (control). Groups of 10 animals were sacrificed after 1, 2, and 4 months. The volumes of the space created by the capsule and of the (1) newly formed bone, (2) remaining Bio-Oss particles, (3) soft connective tissue, and (4) acellular space in the capsule were estimated by a point-counting technique in three or four histologic sections, taken by uniformly random sampling. RESULTS: Bone formation at 1 month was limited in both tests and controls. After 2 months, the mean volume of the newly formed bone occupied 9.0% of the space created by the capsule in the test specimens compared with 23.8% in the control specimens (p < .01). After 4 months, the respective figures were 11.6% (tests) versus 38.7% (controls) (p < .01). CONCLUSION: It can be concluded that Bio-Oss, used as an adjunct to GBA, interferes with bone formation.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".