Efflux pump inhibitors (EPIs) as new antimicrobial agents against <i>Pseudomonas aeruginosa</i>
Bibliographic record
Abstract
Pseudomonas aeruginosa is an opportunistic human pathogen and one of the leading causes of nosocomial infections worldwide. The difficulty in treatment of pseudomonas infections arises from being multidrug resistant (MDR) and exhibits resistance to most antimicrobial agents due to the expression of different mechanisms overcoming their effects. Of these resistance mechanisms, the active efflux pumps in Pseudomonas aeruginosa that belong to the resistance nodulation division (RND) plays a very important role in extruding the antibiotics outside the bacterial cells providing a protective means against their antibacterial activity. Beside its role against the antimicrobial agents, these pumps can extrude biocides, detergents, and other metabolic inhibitors. It is clear that efflux pumps can be targets for new antimicrobial agents. Peptidomimetic compounds such as phenylalanine arginyl β-naphthylamide (PAβN) have been introduced as efflux pump inhibitors (EPIs); their mechanism of action is through competitive inhibition with antibiotics on the efflux pump resulting in increased intracellular concentration of antibiotic, hence, restoring its antibacterial activity. The advantage of EPIs is the difficulty to develop bacterial resistance against them, but the disadvantage is their toxic property hindering their clinical application. The structure activity relationship of these compounds showed other derivatives from PAβN that are higher in their activity with higher solubility in biological fluids and decreased toxicity level. This raises further questions on how can we compact Pseudomonas infections. Of particular importance, the recent resurgence in the use of older antibiotics such as polymyxins and probably applying stricter control measures in order to prevent their spread in clinical sittings.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".