Silver Oxynitrate, an Unexplored Silver Compound with Antimicrobial and Antibiofilm Activity
Bibliographic record
Abstract
Historically it has been accepted, and recent research has established, that silver (Ag) is an efficacious antimicrobial agent. A dwindling pipeline of new antibiotics, combined with an increase in the number of antibiotic-resistant infections, is bringing Ag to the fore as a therapeutic compound to treat infectious diseases. Currently, many formulations of Ag are being deployed for commercial and medical purposes, with various degrees of effectiveness at killing microbial cells. Here, we evaluated the antimicrobial and antibiofilm capacity of our lead compound, silver oxynitrate [Ag(Ag3O4)2NO3 or Ag7NO11], against other metal compounds with documented antimicrobial activity, including Ag2SO4, AgNO3, silver sulfadiazine (AgSD), AgO, Ag2O, and CuSO4. Our findings reveal that Ag7NO11 eradicates biofilm and planktonic populations of Pseudomonas aeruginosa, Escherichia coli, Staphylococcus aureus, uropathogenic Escherichia coli (UPEC), fluoroquinolone-resistant Pseudomonas aeruginosa (FQRP), and methicillin-resistant Staphylococcus aureus (MRSA) at lower concentrations than those of the other tested metal salts. Altogether, our results demonstrate that Ag7NO11 has an enhanced efficacy for the treatment of biofilm-forming pathogens.
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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) | 0.000 | 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".