Baicalin Represses Type Three Secretion System of Pseudomonas aeruginosa through PQS System
Bibliographic record
Abstract
Therapeutics that target the virulence of pathogens rather than their viability offer a promising alternative for treating infectious diseases and circumventing antibiotic resistance. In this study, we searched for anti-virulence compounds against Pseudomonas aeruginosa from Chinese herbs and investigated baicalin from Scutellariae radix as such an active anti-virulence compound. The effect of baicalin on a range of important virulence factors in P. aeruginosa was assessed using luxCDABE-based reporters and by phenotypical assays. The molecular mechanism of the virulence inhibition by baicalin was investigated using genetic approaches. The impact of baicalin on P. aeruginosa pathogenicity was evaluated by both in vitro assays and in vivo animal models. The results show that baicalin diminished a plenty of important virulence factors in P. aeruginosa, including the Type III secretion system (T3SS). Baicalin treatment reduced the cellular toxicity of P. aeruginosa on the mammalian cells and attenuated in vivo pathogenicity in a Drosophila melanogaster infection model. In a rat pulmonary infection model, baicalin significantly reduced the severity of lung pathology and accelerated lung bacterial clearance. The PqsR of the Pseudomonas quinolone signal (PQS) system was found to be required for baicalin’s impact on T3SS. These findings indicate that baicalin is a promising therapeutic candidate for treating P. aeruginosa infections.
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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".