<i>Bifidobacterium breve</i> IPLA20005 affects in vitro the expression of <i>hly</i> and <i>luxS</i> genes, related to the virulence of <i>Listeria monocytogenes</i> Lm23
Bibliographic record
Abstract
Mechanistic features that characterize the interaction and inhibition of the food-borne pathogen Listeria monocytogenes by members of the genus Bifidobacterium still remain unclear. In the present work, we tried to shed light on the influence that co-cultivation of L. monocytogenes with Bifidobacterium breve may exert on both microorganisms and on virulence of the pathogen. Production of acetate and lactate was measured by gas chromatography and high-performance liquid chromatography, respectively; bacterial counts were obtained by plate count; gene expression was determined by RT-qPCR; and haemolytic activity was analyzed against goat erythrocytes. We found slightly but significantly lower final counts of Listeria and Bifidobacterium (p < 0.05) and lower haemolytic efficiency in L. monocytogenes cells from cocultures than in those from monocultures. In contrast, the hly and luxS genes, which code for the cytolysin listeriolysin O and participate in biofilm formation, respectively, were overexpressed when L. monocytogenes was grown in coculture. This indicates that the presence of Bifidobacterium is able to modify the gene expression and haemolytic activity of L. monocytogenes when both microorganisms grow together.
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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) | 0.001 | 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".