Highly Efficient Antimicrobial Activity of CuxFeyOz Nanoparticles against Important Human Pathogens
Bibliographic record
Abstract
The development of innovative antimicrobial materials is crucial in thwarting infectious diseases caused by microbes, as drug-resistant pathogens are increasing in both number and capacity to detoxify the antimicrobial drugs used today. An ideal antimicrobial material should inhibit a wide variety of bacteria in a short period of time, be less or not toxic to normal cells, and the fabrication or synthesis process should be cheap and easy. We report a one-step microwave-assisted hydrothermal synthesis of mixed composite CuxFeyOz (Fe2O3/Cu2O/CuO/CuFe2O) nanoparticles (NPs) as an excellent antimicrobial material. The 1 mg/mL CuxFeyOz NPs with the composition 36% CuFeO2, 28% Cu2O and 36% Fe2O3 have a general antimicrobial activity greater than 5 log reduction within 4 h against nine important human pathogenic bacteria (including drug-resistant bacteria as well as Gram-positive and Gram-negative strains). For example, they induced a >9 log reduction in Escherichia coli B viability after 15 min of incubation, and an ~8 log reduction in multidrug-resistant Klebsiella pneumoniae after 4 h incubation. Cytotoxicity tests against mouse fibroblast cells showed about 74% viability when exposed to 1 mg/mL CuxFeyOz NPs for 24 h, compared to the 20% viability for 1 mg/mL pure Cu2O NPs synthesized by the same method. These results show that the CuxFeyOz composite NPs are a highly efficient, low-toxicity and cheap antimicrobial material that has promising potential for applications in medical and food safety.
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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) | 0.001 | 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 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".