Development of Antimicrobial Paper Coatings Containing Bacteriophages and Silver Nanoparticles for Control of Foodborne Pathogens
Bibliographic record
Abstract
In this study, a novel antimicrobial formula that incorporates Listeria bacteriophage P100 and silver nanoparticles into an alginate matrix was successfully developed. Paper coated with the antimicrobial formula inhibited the growth of Listeria monocytogenes. The effects of alginate concentration on the formation of silver nanoparticles, silver concentration on the infectivity of phages, and of low alginate concentrations on the sustained release of silver and phages were explored. The highest antimicrobial activity of the alginate–silver coating was achieved with an alginate concentration of 1%. Adding phage P100 (109 PFU/mL) into the alginate–silver coating led to a synergic effect that resulted in a 5-log reduction in L. monocytogenes. A bioactive paper was then developed by coating a base paper with the antimicrobial formula at different coating weights, followed by infrared drying. The higher coating weight was a crucial factor for the maintenance of phage infectivity throughout the coating and drying processes. Phages incorporated into the alginate matrix remained functional even after high-temperature infrared drying. Taken together, an optimized coating matrix is critical in improving the antimicrobial performance of bioactive paper as well as maintaining phage infectivity during the paper manufacturing process.
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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 | 0.000 | 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 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".