Green synthesis of catalytic gold/bismuth oxyiodide nanocomposites with oxygen vacancies for treatment of bacterial infections
Why this work is in the frame
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Bibliographic record
Abstract
We have developed a simple and green solution for the synthesis of catalytic gold-doped bismuth oxyiodide (Au/BiOI) nanocomposites at room temperature from an aqueous mixture of gold ions, bismuth ions, and iodide ions. Au nanoparticles (NPs) were formed in situ and doped into BiOI nanosheets. The oxygen vacancies generated in BiOI give rise to its oxidase-like activity, and Au doping facilitated the reaction leading to a 4-fold higher oxidase-like activity of the Au/BiOI nanocomposite. The Au/BiOI nanocomposites showed wide spectrum antimicrobial activity not only against non-multidrug-resistant E. coli, K. pneumoniae, S. enteritidis, S. aureus, and B. subtilis bacteria, but also against multidrug-resistant bacteria, methicillin-resistant S. aureus (MRSA). The gold doping reduced the minimal inhibitory concentration value by ∼2000-fold for the Au/BiOI nanocomposite, in comparison with only BiOI nanoparticles. The bactericidal property of the Au/BiOI nanocomposite arose from the combined effect of the disruption of the bacterial membrane through a strong interaction of the nanocomposite with the bacteria and the generation of reactive oxygen species. Also, the Au/BiOI nanocomposite is highly biocompatible, which has been demonstrated in vitro by analysis of cytotoxicity and hemolysis, and in vivo by evaluating ocular tissue responses. Furthermore, intrastromal administration of Au/BiOI nanocomposites can effectively alleviate S. aureus-induced bacterial keratitis in rabbits, suggesting a significant disinfectant benefit in preclinical studies. The Au/BiOI nanocomposites show great potential for the inactivation of bacterial pathogens in an aqueous environment and treatment of bacterial infection-induced diseases.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 it