Antimicrobial light-activated materials: towards application for food and environmental safety
Bibliographic record
Abstract
AIMS: To produce light-activated antimicrobial materials composed of the photodynamic dye phloxine B incorporated into paper or cellulose membranes and to investigate ability of these materials to decrease bacterial loads on their surfaces as well as on food surfaces that were in contact with these materials under illumination with regular white light. METHODS AND RESULTS: Antimicrobial cellulose-based materials with incorporated phloxine B were produced using a layer-by-layer deposition method. Antimicrobial properties of the materials were tested in model systems as well as for decontamination of food and food contact surfaces. Pseudomonas aeruginosa, Listeria monocytogenes and Bacillus anthracis were efficiently killed by exposure of the bacterial suspension to the dye-containing material under illumination with white light, but Salmonella Typhimurium and Escherichia coli O157:H7 were only partially affected. Application of the materials for decontamination of food surfaces artificially contaminated with L. monocytogenes was shown to be ineffective, while the self-decontamination of the material surface by exposure to white light resulted in eradication of L. monocytogenes cells from the material surface. CONCLUSIONS: The developed materials showed significant self-decontaminating ability when under illumination; however, decontamination of food surfaces in contact with the developed materials was not achieved. SIGNIFICANCE AND IMPACT OF THE STUDY: The study demonstrates the antibacterial activity of materials with incorporated photodynamic dyes when under illumination with regular-intensity white light. Possible uses of the light-activated antimicrobial materials for food processing, as food contact surfaces, and surfaces in public areas to prevent cross-contamination are discussed.
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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) | 0.001 | 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".