Biological performance of a novel bovine hydroxyapatite in a guided bone regeneration model: A preclinical study in a mandibular defect in dogs
Bibliographic record
Abstract
OBJECTIVES: This preclinical model study aims to evaluate the performance and safety of a novel hydroxyapatite biomaterial (Wishbone Hydroxyapatite, WHA) on guided bone regeneration compared to a commercially available deproteinized bovine bone mineral (Bio-Oss, BO). MATERIAL AND METHODS: Twenty-four beagle dogs were allocated to three timepoint cohorts (4, 12, and 26 weeks) of eight animals each. In all animals, four critical-sized, independent wall mandibular defects were created (32 defects/cohort). Each animal received all four treatments, allocated randomly to separated defects: WHA + collagen membrane (M), BO + M, no treatment (Sham, Sh), and Sh + M. At each timepoint, the specimens were harvested for histologic and histomorphometric analyses to determine the newly formed bone and osteoconductivity. RESULTS: At 4 weeks, bone regeneration was significantly higher for WHA + M (46.8%) when compared to BO + M (21.4%), Sh (15.1%), and Sh + M (23.1%) (p < 0.05); at 12 and 26 weeks, regeneration was similar for WHA and BO. Bone-to-material contact increased over time similarly for WHA + M and BO + M. From a safety point of view, inflammation attributed to WHA + M or BO + M was minimal; necrosis or fatty infiltrate was absent. CONCLUSIONS: WHA + M resulted in higher bone regeneration rate than BO + M at 4 weeks. Both BO + M and WHA + M were more efficient than both Sh groups at all timepoints. Safety and biocompatibility of WHA was favorable and comparable to that of BO.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".