Multiplex Real-Time PCR Assay for Simultaneous Identification of Neisseria gonorrhoeae and Its Ciprofloxacin Susceptibility Status
Bibliographic record
Abstract
ABSTRACT A real-time PCR (RT-PCR) assay was designed for the simultaneous identification of Neisseria gonorrhoeae and its ciprofloxacin susceptibility status. A SYBR green-based multiplex RT-PCR format was used; it comprised two different forward primers and a common reverse primer to detect single nucleotide polymorphisms (SNPs) in gyrA of N. gonorrhoeae . The primer pairs were evaluated for their sensitivity and specificity using genomic DNA from 254 N. gonorrhoeae isolates (82 were ciprofloxacin susceptible and 172 were ciprofloxacin resistant) and 23 non- N. gonorrhoeae species isolates. The performance of the primers was validated using genomic DNA from 100 different N. gonorrhoeae isolates (46 were ciprofloxacin susceptible and 54 were ciprofloxacin resistant) and 52 non- N. gonorrhoeae isolates. The latter panel was revalidated by testing 99 (46 isolates were ciprofloxacin susceptible and 53 isolates were ciprofloxacin resistant) of the N. gonorrhoeae isolates and 23 non- N. gonorrhoeae isolates. These primers detected N. gonorrhoeae and its ciprofloxacin susceptibility status with over 99% sensitivity and specificity for all panels tested. This assay has the potential to be an inexpensive and rapid test for the simultaneous identification of N. gonorrhoeae and its ciprofloxacin susceptibility status.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".