Allicin inhibits <i>Pseudomonas aeruginosa</i> virulence by suppressing the <i>rhl</i> and <i>pqs</i> quorum-sensing systems
Bibliographic record
Abstract
Pseudomonas aeruginosa is a virulent bacterium that secretes a variety of virulence factors that aid in establishing infections in individuals. Allicin, derived from garlic, has been shown to inhibit virulence factor production and biofilm formation in P. aeruginosa. However, the mechanisms underlying the allicin-mediated regulation of P. aeruginosa virulence remain unclear. In this study, we investigated the possible mechanisms underlying allicin-mediated virulence regulation in P. aeruginosa. The results showed that allicin attenuates the production of P. aeruginosa virulence-associated factors, such as elastase, pyocyanin, pyoverdine, and rhamnolipids, by inhibiting the rhl and pqs quorum-sensing systems. Further analysis revealed that the rhl and pqs systems play different roles during the allicin-mediated regulation process. Taken together, these results support the potential use of allicin as a therapeutic agent in controlling P. aeruginosa infection and associated mechanisms.
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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".