Parallel evolution and local differentiation in quinolone resistance in Pseudomonas aeruginosa
Bibliographic record
Abstract
The emergence and spread of antibiotic resistance in pathogens is a major impediment to the control of microbial disease. Here, we review mechanisms of quinolone resistance in Pseudomonas aeruginosa, an important nosocomial pathogen and a major cause of morbidity in cystic fibrosis (CF) patients. In this quantitative literature review, we find that mutations in DNA gyrase A, the primary target of quinolones in Gram-negative bacteria, are the most common resistance mutations identified in clinical samples of all origins, in keeping with previous observations. However, the identities of non-gyrase resistance mutations vary systematically between samples isolated from CF patients and those isolated from acute infections. CF-derived strains tend to harbour mutations in the efflux pump regulator nfxB, while non-CF strains tend to bear mutations in the efflux regulator mexR or in parC, which encodes one of two subunits of DNA topoisomerase IV. We suggest that differences in resistance mechanisms between CF and non-CF strains result either from local adaptation to different sites of infection or from differences in mutational processes between different environments. We further discuss the therapeutic implications of local differentiation in resistance mechanisms to a common antibiotic.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".