Inactivation of Adhesion and Invasion of Food-Borne <i>Listeria monocytogenes</i> by Bacteriocin-Producing <i>Bifidobacterium</i> Strains of Human Origin
Bibliographic record
Abstract
Three bacteriocin-producing bifidobacterial isolates from newborns were identified as Bifidobacterium thermacidophilum (two strains) and B. thermophilum (one strain). This study was undertaken to evaluate the ability of these strains to compete with food-borne Listeria monocytogenes for adhesion and invasion sites on Caco-2 and HT-29 cells. The bifidobacteria adhered at levels ranging from 4% to 10% of the CFU added, but none of the bifidobacteria were able to invade cells. The abilities of Listeria to adhere to and to invade cells varied widely depending on the strain tested. Three groups of Listeria were identified based on invasiveness: weakly invasive, moderately invasive, and highly invasive strains. One strain from each group was tested in competition with bifidobacteria. B. thermacidophilum RBL70 was the most effective in blocking invasion of Listeria, and the decreases in invasion ranged from 38% to 90%. For all three bifidobacterial strains, contact between the cell monolayer and the bifidobacteria for 1 h before exposure to Listeria increased the degree of inhibition. Finally, visualization of competition for adhesion sites on cells by fluorescent in situ hybridization suggested that the two bacteria tended to adhere in close proximity.
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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) | 0.000 | 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 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".