Incorporating gold into nanocrystalline silver dressings reduces grain boundary size and maintains suitable antimicrobial properties
Bibliographic record
Abstract
Nanocrystalline silver dressings are widely known to be potent antimicrobial and anti-inflammatory agents and have long been used to treat topical wounds. Gold is known to be a strong anti-inflammatory agent and has been used in the treatment of rheumatoid arthritis for >70 years. The purpose of this work was to study the effect of incorporating gold into nanocrystalline silver dressings from antimicrobial and anti-inflammatory perspectives. Gold and silver dressing alloys were created by direct current magnetron sputtering and compared with pure silver nanocrystalline dressings using conventional biological (log reduction and corrected zone of inhibition) and physical (X-ray diffraction, X-ray photoelectron spectroscopy, energy-dispersive X-ray spectroscopy, atomic absorption spectroscopy, atomic force microscopy and scanning electron microscopy) characterisation techniques. While the gold/silver dressings were slightly weaker antimicrobials than the pure silver nanocrystalline structures, the addition of gold to the nanostructure reduces the minimum crystallite size from 17 to 4 nm. This difference increases the number of grain boundary atoms from 12% to 40% which could augment the anti-inflammatory properties of the dressings. The formation of gold oxide (Au2O3) was thought to be responsible for the observed decrease in crystallite size.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 teacher head, 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".