Bioactive Glass Preloaded with Antibiotics for Delivery of Long-Term Localized Drug Release Exhibiting Inherent Antimicrobial Activity
Bibliographic record
Abstract
Bacterial infections caused by biofilms are often difficult to treat due to the resistant nature of the latter, which require high concentrations of antibiotics to be applied for prolonged periods to achieve complete eradication. This study aimed to design a new drug delivery system for long-term drug release for the treatment of bacterial infections. Specifically, bioactive glass preloaded with vancomycin (BG-V) and synthesized without any thermal treatment was designed to load higher percentages of the drug and release it slowly over time. In this study, BG-V was-synthesized using a solution containing vancomycin, with glass being formed around it by adding metal precursors to this solution. The BG-V was then left to dry at room temperature to form a white powder with vancomycin trapped in the structure. The successful synthesis of BG-V was confirmed by X-ray diffraction, Fourier-transform infrared spectroscopy, scanning emission microscopy, and nitrogen adsorption–desorption analysis. The results showed that BG-V was successfully developed using FTIR, showing vancomycin within the BG-V structure. After the drug release, BG-V showed great bioactivity, as indicated by the XRD and bacterial studies. The result shows that drug release is controlled by a combination of diffusion through the matrix and the gradual erosion of the delivery system.
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 | 0.000 | 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) | 0.000 | 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".