Evaluation of Amplification Targets for the Specific Detection of <i>Bordetella pertussis</i> Using Real‐Time Polymerase Chain Reaction
Bibliographic record
Abstract
BACKGROUND: Bordetella pertussis infections continue to be a major public health challenge in Canada. Polymerase chain reaction (PCR) assays to detect B pertussis are typically based on the multicopy insertion sequence IS481, which offers high sensitivity but lacks species specificity. METHODS: A novel B pertussis real-time PCR assay based on the porin gene was tested in parallel with several previously published assays that target genes such as IS481, ptx-promoter, pertactin and a putative thialase. The assays were evaluated using a reference panel of common respiratory bacteria including different Bordetella species and 107 clinical nasopharyngeal specimens. Discrepant results were confirmed by sequencing the PCR products. RESULTS: Analytical sensitivity was highest for the assay targeting the IS481 element; however, the assay lacked specificity for B pertussis in the reference panel and in the clinical samples. False-positive results were also observed with assays targeting the ptx-promoter and pertactin genes. A PCR assay based on the thialase gene was highly specific but failed to detect all reference strains of B pertussis. However, a novel assay targeting the porin gene demonstrated high specificity for B pertussis both in the reference panel and in clinical samples and, based on sequence-confirmed results, correctly predicted all B pertussis-positive cases in clinical samples. According to Probit regression analysis, the 95% detection limit of the new assay was 4 colony forming units/reaction. CONCLUSION: A novel porin assay for B pertussis demonstrated superior performance and may be useful for improved molecular detection of B pertussis in clinical specimens.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".