Host responses to a strontium releasing high boron glass using a rabbit bilateral femoral defect model
Bibliographic record
Abstract
Borate glasses have shown promising potential as bioactive materials. With recent research demonstrating that glass properties may be modulated by appropriate compositional design. This may provide for indication specific material characteristics and controlled release of therapeutic inorganic ions (i.e., strontium); controlling such release is critical in order to harness the therapeutic potential. Within this sub-chronic pilot study, a rabbit long-bone model was utilized to explore the safety and efficacy of a high borate glass (LB102: 70B2O3−20SrO-6Na2O-4La2O3) particulate (90 - 710 μm) for bone regeneration. Six bilateral full-thickness defects (Ø = 3.5 mm; L = 8 mm) were created in three white New Zealand rabbits. Longitudinal non-decalcified sections of each defect site were produced and stained with Goldner's Trichrome. Histopathological examination revealed that LB102 demonstrated osteoconductive and osseointegrative properties with greater new bone being formed within and surrounding LB102 particles, when compared to the sham control. The inflammatory cell infiltration was observed to be slightly higher in the control when compared to LB102 defect sites, while no significant difference in fibrosis and neovascularization was determined, indicating that healing was occurring in a normal fashion. These data further suggest the possible utility of high borate glasses with appropriate compositional design for medical applications, such as bone augmentation. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 105B: 1818–1827, 2017.
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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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".