Emerging epidemic of the Africa-type plasmid in penicillinase-producing <i>Neisseria gonorrhoeae</i> in Guangdong, China, 2013–2022
Bibliographic record
Abstract
The prevalence of penicillinase-producing Neisseria gonorrhoeae (PPNG) is a crucial public health concern because of its resistance to penicillin and cephalosporins. From 2013 to 2022, a total of 1,748 N. gonorrhoeae isolates from Guangdong, China, were examined for their antibiotic susceptibility and molecular epidemiological characteristics. PPNG prevalence increased markedly from 37.25% to 63.87%. This increase was accompanied by a shift in predominant plasmid types carried by PPNG isolates: the rate of PPNG isolates carrying the Africa-type plasmid increased from 18.42% to 91.55%, whereas the rate of isolates carrying the Asia-type plasmid decreased from 81.58% to 7.58%. The prevalence of blaTEM-135, which is linked to cephalosporin resistance, declined from 52.63% to 4.37%, whereas that of blaTEM-1 increased from 47.37% to 86.88%, and new blaTEM variants emerged (10.99% by 2022). Most blaTEM-1 (88.26%) and new blaTEM alleles (83.70%) were associated with the Africa-type plasmid, whereas 86.79% of blaTEM-135 alleles were linked to the Asia-type plasmid. Resistance to ceftriaxone was higher in the Asia-type group (11.67%) than in the Africa-type, Toronto/Rio-type and non-PPNG groups. Genotyping identified diverse sequence types (STs) among PPNGs, in which MLST ST7363, NG-STAR ST2477, NG-MAST ST17748, and NG STAR CC1124 were predominant. This study underscores the rising prevalence of PPNG in Guangdong driven by clonal expansion and changing plasmid dynamics, affecting cephalosporin resistance and highlighting the need for continued surveillance and research into effective treatment strategies.
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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".