Molecular Antimicrobial Resistance of<i>Neisseria gonorrhoeae</i>in a Moroccan Area
Bibliographic record
Abstract
Objectives. To identify the prevalence and the types ofNeisseria gonorrhoeae(NG) resistance plasmids-mediated penicillin (PPNG) and tetracycline (TRNG), the ciprofloxacin resistance (CRNG), and related risk factors of each types of resistance.Methods. The beta-lactamase-producing plasmid types (Africa, Asia, and Toronto),tetMtetracycline resistance plasmid types (America and Dutch), and the determination of the Ser-91 mutation of GyrA were detected by specifics PCRs on 149 diagnosed NG positives samples followed byHinf1digestion fortetMandgyrAmutation.Results. 135 (90.1%) samples showed a profile of molecular resistance to at least one antibiotic with predominance of ciprofloxacin resistance. In fact, 36 (24.2%) and 69 (46.3%) cases harbored PPNG and TRNG, respectively, and 116 (77.9%) cases showed the mutation Ser-91 of GyrA (CRNG). From a total of 36 PPNG isolates, the Toronto, Asian, and Toronto/Asian types were detected in 13 (36.1%), 10 (27.8%), and 13 (36.1%) cases, respectively, whereas the African type was not detected. In addition, the American type of TRNG was detected in 92.8% (64/69) of cases, while the Dutch type was detected in 7.2% (5/69) of cases. The association of demographics and clinical variables with NG resistance to ciprofloxacin, penicillin, and tetracycline was studied and the risk factors have been determined.Conclusion. Resistance to penicillin, tetracycline, and ciprofloxacin among NG samples positives remained at high levels in Morocco as determined by molecular profile. So, the use of molecular tools for NG antimicrobial resistance detection can help in the management and spread limitation of this infection.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".