Prospects for using bacteriocins in aquaculture
Bibliographic record
Abstract
This paper provides an overview of the recent information on the use of bacteriocins in aquaculture. The development of the aquaculture sector in recent years brings the problem of antibiotic resistance in aquatic organisms to the foreground. Many countries are facing the challenge of replacing antibiotics with safer and more effective substances. Bacteriocins, nature-like antimicrobial peptides, are used as a solution to this problem. The structure of peptides is studied using metagenomic sequencing, which pinpoints the exact amino acid sequence. A literature search has revealed cases in Russia of microbial sludge from the biofloc system being used in aquaculture facilities not only for water purification but also to combat various diseases. Bacteriocins are more widely applied abroad, e.g. in China, Japan, Canada, or Norway, where strains of the genus Bacillus, Lactobacillus plantarum 42, Lactobacillus plantarum YRL45, Lactobacillus plantarum W3-2, Lactococcus spp., Pediocin PA-1 (Pediococcus acidilactici), Pediococcusa cidilactici DSM 10313 are used. The identified peptides help enhance fish growth and survival; improve water quality through decomposition of organic substances; are effective in suppressing pathogenic microflora, reduce the risk of diseases in aquaculture; are active against Enterococcus faecalis, Staphylococcus aureus, Listeria monocytogenes, Bacillus cereus and Clostridium botulinum. By adding bacteriocins to feeds, fish farmers can reduce dependence on traditional treatments. Thus, bacteriocins are an emerging group of antimicrobial drugs which can improve the quality of aquaculture produce, make it safer for consumers, and expand the drug market for aquaculture facilities.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".