A Universal Influenza A and B Duplex Real‐time RT‐PCR Assay
Bibliographic record
Abstract
A high throughput universal influenza A and B duplex real-time RT-PCR was developed to meet effectively the heightened surveillance and diagnostic needs essential in managing influenza infections and outbreaks. Primers and probes, designed to target highly conserved regions of the matrix protein of influenza A and the nucleoprotein of influenza B, were optimized using the high-throughput LightCycler 480 II system. Analytical sensitivity and specificity were characterized using RNA transcripts diluted serially, archived non-influenza respiratory viruses, and proficiency test samples. Eighty-nine clinical samples were tested in parallel against existing influenza A and B monoplex assays. Once validated, the duplex assay was applied prospectively on 2,458 clinical specimens that were later subtyped. In April 2011, the emergence of an influenza B variant necessitated the inclusion of an additional modified probe for influenza B and revalidation of the revised protocol. The lower detection limits of the assay were 50 copies/PCR. There was no cross-reactivity against any non-influenza respiratory virus and all proficiency testing materials were identified correctly. The parallel testing revealed a 98.9% overall agreement. Routine application of the assay revealed high sensitivity and specificity for the detection of influenza A/H1N1/2009, A/H3N2 and influenza B. Assay C(q) values correlated well between the pre- and post-revision protocols for influenza A (r(2) = 0.998) and B (r(2) = 0.999). The revised protocol detected three additional novel influenza B variant cases in 200 specimens reported previously as influenza B negative. This in-house assay offers a highly sensitive and specific option for laboratories seeking to expand their influenza testing capacity.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.003 |
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".