Design and Validation of Real-Time Reverse Transcription-PCR Assays for Detection of Pandemic (H1N1) 2009 Virus
Bibliographic record
Abstract
Tracking novel influenza viruses which have the potential to cause pandemics, such as the pandemic (H1N1) 2009 virus, is a public health priority. Pandemic (H1N1) 2009 virus was first identified in Mexico in April 2009 and spread worldwide over a short period of time. Well-validated diagnostic tools that are rapid, sensitive, and specific for the detection and tracking of this virus are needed. Three real-time reverse transcription PCR (RT-PCR) assays for the amplification and detection of pandemic (H1N1) 2009 virus were developed, and their performance characteristics were compared with those of other published diagnostic assays. Thirty-nine samples confirmed to be positive for pandemic (H1N1) 2009 virus from Alberta, Canada, and six additional samples that were positive for influenza A virus but that were not typeable by using published seasonal influenza H1/H3 virus assays were available for this validation. Amplification and direct sequencing of the products was considered the "gold standard" for case identification. The new assays were sensitive and able to reproducibly detect virus in a 10(-6) dilution of 4 x 10(6) 50% tissue culture infective doses/ml when 5 microl was used as the template. They showed 100% specificity and did not cross-react with other respiratory viruses or seasonal influenza A virus subtypes. The coefficient of variation in crossing cycle threshold values for the detection of different template concentrations of pandemic (H1N1) 2009 virus was < or =3.13%, showing good reproducibility. The assays had a wide dynamic range for the detection of pandemic (H1N1) 2009 virus and utilized testing platforms appropriate for high diagnostic throughput with rapid turnaround times. We developed and validated these real-time PCR procedures with the goal that they will be useful for diagnosis and surveillance of pandemic (H1N1) 2009 virus. These findings will contribute to the informed management of this novel virus.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".