An evaluation of the processing conditions, structure, and properties (biaxial flexural strength and antibacterial efficacy) of sintered strontium–zinc–silicate glass ceramics
Bibliographic record
Abstract
The use of artificial bone grafts has increased in order to satisfy a growing demand for bone replacement materials. Initial mechanical stability of synthetic bone grafts is very advantageous for certain clinical applications. Coupled with the advantage of mechanical strength, a material with inherent antibacterial properties would be very beneficial. A series of strontium-doped zinc silicate (Ca-Sr-Na-Zn-Si) glass ceramics have been characterized in terms of their crystalline structure, biaxial flexural strength and antibacterial efficacy based on the identification of optimum sintering conditions. All three glass ceramics, namely, BT110, BT111, and BT112 were found to be fully crystalline, with BT111 and BT112 comprising of biocompatible crystalline phases. The biaxial flexural strengths of the three glass ceramics ranged from 70 to 149 MPa and were shown to be superior to those of clinically established ceramics in dry conditions and following incubation in simulated physiological conditions. The bacteriostatic effect for each glass ceramic was also established, where BT112 showed an inhibitory effect against three of the most common bacteria found at implantation sites, namely, Enterococcus faecalis, methicillin-resistant Staphylococcus aureus (MRSA), and Pseudomonas aeruginosa. The results of the evaluation suggest that the materials studied offer advantages over current clinical materials and indicate the potential suitability of the glass ceramics as therapeutic bone grafts.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".