Aminoglycoside resistance mechanisms in <i>Pseudomonas aeruginosa</i> isolates from non-cystic fibrosis patients in Thailand
Bibliographic record
Abstract
This study aimed to examine aminoglycosides (AMGs) resistance mechanisms, including the AMG-modifying enzyme genes, mexXY, rplY, nuoG, and galU, in the Pseudomonas aeruginosa non-cystic fibrosis (CF) isolates in Thailand. One hundred P. aeruginosa isolates from non-CF patients were examined for susceptibility to AMGs and for the presence of 10 AMG-modifying enzyme genes. Thirty randomly selected isolates were tested for transcription of mexXY and nuoG and mutations in rplY and galU. All the P. aeruginosa isolates exhibited simultaneous resistance to at least 4 AMGs. High resistance rates to amikacin (92%), gentamicin (95%), streptomycin (99%), and tobramycin (96%) were observed, and all isolates were resistant to kanamycin, neomycin, and spectinomycin. Nine AMG-modifying enzyme genes were detected, including aadA1 (84%), aadB (84%), aadA2 (67%), ant(2″)-Ia (72%), strA-strB (70%), aph(3')-IIb (57%), aac(3')-Ia (40%), and aac(6')-IIa (27%). None of the isolates harbored aac(6')-IIb. Of 30 isolates tested, all but 1 isolate expressed MexXY. Two isolates did not express nuoG. Six isolates carried an amino acid change in RplY, but none of the isolates harbored mutation in galU. The results indicated that the AMG-modifying enzyme genes were widespread among the P. aeruginosa non-CF isolates. The MexXY efflux pump and inactivation for rplY played a role in AMG resistance but disruption of nuoG or galU did not.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".