In vitro assessment of skin sensitization, irritability and toxicity of bacteriocins and reuterin for possible topical applications
Bibliographic record
Abstract
Abstract Bacteriocins and reuterin are promising antimicrobials for application in food, veterinary, and medical sectors. In the light of their high potential for application in hand sanitizer, we investigated the skin toxicity of reuterin, microcin J25, pediocin PA-1, bactofencin A, and nisin Z in vitro using neutral red and LDH release assays on NHEK cells. We determined their skin sensitization potential using the human cell line activation test (h-CLAT). Their skin irritation potential was measured on human epidermal model EpiDerm™. We showed that the viability and membrane integrity of NHEK cells remained unaltered after exposure to bacteriocins and reuterin at concentrations up to 400 µg/mL and 80 mg/mL, respectively. Furthermore, microcin J25 and reuterin showed no skin sensitization at concentrations up to 100 µg/mL and 40 mg/mL, respectively, while pediocin PA-1, bactofencin A, and nisin Z caused sensitization at concentrations higher than 100 µg/mL. Tissue viability was unaffected in presence of bacteriocins and reuterin at concentrations up to 200 µg/mL and 40 mg/mL, respectively, which was confirmed by measuring cytokine IL-1α and IL-8 levels and by histological analysis. In conclusion, the current study provides scientific evidence that some bacteriocins and reuterin, could be safely applied topically as sanitizers at recommended concentrations.
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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) | 0.001 | 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) | 0.001 | 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".