Physico‐chemical and biological characterization of a new bovine bone mineral matrix available for human usage
Bibliographic record
Abstract
BACKGROUND: Anorganic bovine bone has been deeply studied for bone regeneration in the oral cavity. Different manufacturing processes can modify the final composition of the biomaterial and the responses that induce. AIM: To evaluate the physico-chemical characteristics of a bovine bone mineral matrix and the clinical, radiographical, histological, and mRNA results after using it for maxillary sinus floor augmentation in humans. MATERIALS AND METHODS: First, the physical-chemical characteristics of the biomaterial were evaluated by X-ray powder diffraction, X-ray fluorescence, and electron microscopy. A frequently used biomaterial with the same animal origin was used as comparator. Then, a clinical study was designed for evaluating clinical, radiographical, histological, and mRNA outcomes. Patients in need of two-stage maxillary sinus floor augmentation were included in the study. Six months after the grafting procedure, a bone biopsy was collected for evaluation. RESULTS: In terms of physico-chemical characteristics, no differences were found between both biomaterials. Clinically, 10 patients were included in the study. After 6 months, clinical and radiographical data showed adequate outcomes for allowing implant placement. Histological, immunohistochemical and mRNA analyses showed that the biomaterial in use provides biological support to induce responses similar to those of other commonly used biomaterials. CONCLUSION: Bovine bone mineral matrix (Creos™ Xenogain) used as a single material for maxillary sinus floor augmentation shows adequate biological, clinical, and radiological outcomes. In fact, the results from this study are similar to those reported in the literature for another bovine bone-derived biomaterial with whom it shares composition and micro- and nanoscale characteristics.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".