Growth and adhesion inhibition of pathogenic bacteria by live and heat-killed food-origin <i>Lactobacillus</i> strains or their supernatants
Bibliographic record
Abstract
The study aimed to evaluate qualitatively and quantitatively the antimicrobial capacity of 10 potential probiotic Lactobacillus strains against model enteropathogens and spoilage microorganisms. The probiotic strains (live and heat-killed forms) were also assessed for their ability to inhibit adhesion of selected pathogens to Caco-2 cells. The largest inhibition zones (the diffusion method) were connected with the usage of whole bacteria cultures (WBC), also high and moderate with cell-free supernatant (CFS) and the lowest with cell-free neutralized supernatant (CNS). The highest antagonistic activity of Lactobacillus strains was observed against L. monocytogenes strains, moderate activity against Salmonella, Shigella, Escherichia coli, Pseudomonas and, the lowest against S.aureus, Bacillus and Enterococcus. The inhibition of adhesion to Caco-2 cells was very high in the case of E. coli, Salmonella and L. monocytogenes, and moderate in the case of S.aureus. On average, the inhibition effect was higher when pathogenic bacteria were treated by WBC, than heat-killed Lactobacillus. Although, in most samples, the effect was not significantly different (P> 0.05). The strains Lb. brevis O24 and Lb. rhamnosus K3 showed the biggest overall antimicrobial properties, and were most effective in adherence inhibition of investigated indicator strains. These bacteria or their metabolites can be used for the production of various foods or pharmaceutical products.
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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".