Bacteriocins as a new generation of antimicrobials: toxicity aspects and regulations
Bibliographic record
Abstract
In recent decades, bacteriocins have received substantial attention as antimicrobial compounds. Although bacteriocins have been predominantly exploited as food preservatives, they are now receiving increased attention as potential clinical antimicrobials and as possible immune-modulating agents. Infections caused by antibiotic-resistant bacteria have been declared as a global threat to public health. Bacteriocins represent a potential solution to this worldwide threat due to their broad- or narrow-spectrum activity against antibiotic-resistant bacteria. Notably, despite their role in food safety as natural alternatives to chemical preservatives, nisin remains the only bacteriocin legally approved by regulatory agencies as a food preservative. Moreover, insufficient data on the safety and toxicity of bacteriocins represent a barrier against the more widespread use of bacteriocins by the food and medical industry. Here, we focus on the most recent trends relating to the application of bacteriocins, their toxicity and impacts.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".