Inhibition of<i> Pseudomonas aeruginosa</i> Biofilm Formation by Traditional Chinese Medicinal Herb<i> Herba patriniae</i>
Bibliographic record
Abstract
New antimicrobial agents are urgently needed to treat infections caused by drug-resistant pathogens and by pathogens capable of persisting in biofilms. The aim of this study was to identify traditional Chinese herbs that could inhibit biofilm formation of Pseudomonas aeruginosa , an important human pathogen that causes serious and difficult-to-treat infections in humans. A luxCDABE -based reporter system was constructed to monitor the expression of six key biofilm-associated genes in P. aeruginosa . The reporters were used to screen a library of 36 herb extracts for inhibitory properties against these genes. The results obtained indicated that the extract of Herba patriniae displayed significant inhibitory effect on almost all of these biofilm-associated genes. Quantitative analysis showed that H. patriniae extract was able to significantly reduce the biofilm formation and dramatically altered the structure of the mature biofilms of P. aeruginosa . Further studies showed H. patriniae extract decreased exopolysaccharide production by P. aeruginosa and promoted its swarming motility, two features disparately associated with biofilm formation. These results provided a potential mechanism for the use of H. patriniae to treat bacterial infections by traditional Chinese medicines and revealed a promising candidate for exploration of new drugs against P. aeruginosa biofilm-associated 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 | 0.001 | 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 | 0.001 |
| 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".