NG-STAR genotypes are associated with MDR in Neisseria gonorrhoeae isolates collected in 2017 in Shanghai
Bibliographic record
Abstract
OBJECTIVES: To determine the association of Neisseria gonorrhoeae antimicrobial resistance and genotypes using N. gonorrhoeae sequence typing for antimicrobial resistance (NG-STAR). METHODS: We characterized 124 N. gonorrhoeae isolates for their antimicrobial susceptibility profiles and NG-STAR ST characteristics using the guidelines of CLSI and EUCAST. The NG-STAR STs of seven loci were analysed. N. gonorrhoeae multiantigen sequence typing (NG-MAST) and MLST analysis was conducted in isolates with specific NG-STAR STs. RESULTS: NG-STAR differentiated 124 N. gonorrhoeae isolates into 84 STs, of which 66 STs were novel to the NG-STAR database. NG-STAR ST-199, ST-348, ST-428, ST-497 and ST-1138 were the predominant STs. Three N. gonorrhoeae isolates with ceftriaxone and cefixime MICs ≥1.0 mg/L were grouped as NG-STAR ST-233. NG-STAR ST-202 isolates (n=4) were associated with high azithromycin MICs and had an identical NG-MAST ST. The NG-STAR ST-348 group (n=5) comprised more isolates with reduced susceptibility to cefixime (n=4) than cefixime-susceptible isolates (n=1). CONCLUSIONS: NG-STAR analysis differentiated N. gonorrhoeae isolates in settings with a high prevalence of antimicrobial resistance. Specific NG-STAR STs are associated with reduced susceptibility to ceftriaxone or cefixime and resistance to azithromycin in N. gonorrhoeae.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".