Titanium addition influences antibacterial activity of bioactive glass coatings on metallic implants
Bibliographic record
Abstract
In an attempt to combat the possibility of bacterial infection and insufficient bone growth around metallic, surgical implants, bioactive glasses may be employed as coatings. In this work, silica-based and borate-based glass series were synthesized for this purpose and subsequently characterized in terms of antibacterial behavior, solubility and cytotoxicity. Borate-based glasses were found to exhibit significantly superior antibacterial properties and increased solubility compared to their silica-based counterparts, with BRT0 and BRT3 (borate-based glasses with 0 and 15 mol% of titanium dioxide incorporated, respectively) outperforming the remainder of the glasses, both borate and silicate based, in these respects. Atomic Absorption Spectroscopy confirmed the release of zinc ions (Zn 2+ ), which has been linked to the antibacterial abilities of glasses SRT0, BRT0 and BRT3, with inhibition effectively achieved at concentrations lower than 0.7 ppm. In vitro cytotoxicity studies using MC3T3-E1 osteoblasts confirmed that cell proliferation was affected by all glasses in this study, with decreased proliferation attributed to a faster release of sodium ions over calcium ions in both glass series, factor known to slow cell proliferation in vitro .
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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) | 0.002 | 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".