Synergistic Effect between Colistin and Bacteriocins in Controlling Gram-Negative Pathogens and Their Potential To Reduce Antibiotic Toxicity in Mammalian Epithelial Cells
Bibliographic record
Abstract
Pathogens resistant to most conventional antibiotics are a harbinger of the need to discover novel antimicrobials and anti-infective agents and develop innovative strategies to combat them. The aim of this study was to assess the in vitro activity of colistin alone or in combination with two bacteriocins, nisin A and pediocin PA-1/AcH, against Salmonella choleraesuis ATCC 14028, Pseudomonas aeruginosa ATCC 27853, Yersinia enterocolitica ATCC 9610, and Escherichia coli ATCC 35150 (O157:H7). The strain most sensitive to colistin was enterohemorrhagic E. coli O157:H7, which was inhibited at a concentration of about 0.12 μg/ml. When nisin A (1.70 μg/ml) or pediocin PA-1/AcH (1.56 μg/ml) was combined with colistin, the concentrations required to inhibit E. coli O157:H7 were 0.01 and 0.03 μg/ml, respectively. The in vitro antigenotoxic effect of colistin was determined by using the comet assay method to measure the level of DNA damage in freshly isolated human peripheral blood leukocytes (PBLs) incubated with colistin for 1 h at 37°C. Changes in the tail extents of PBLs of about 69.29 ± 0.08 μm were observed at a final colistin concentration of about 550 ng/ml. Besides the synergistic effect, the combination of colistin (1 mg/ml) and nisin (2 mg/ml) permitted us to re-evaluate the toxic effect of colistin on Vero (monkey kidney epithelial) cells.
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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".