Neuraminidase Subtyping of Avian Influenza Viruses with PrimerHunter-Designed Primers and Quadruplicate Primer Pools
Bibliographic record
Abstract
We have previously developed a software package called PrimerHunter to design primers for PCR-based virus subtyping. In this study, 9 pairs of primers were designed with PrimerHunter and successfully used to differentiate the 9 neuraminidase (NA) genes of avian influenza viruses (AIVs) in multiple PCR-based assays. Furthermore, primer pools were designed and successfully used to decrease the number of reactions needed for NA subtyping from 9 to 4. The quadruplicate primer-pool method is cost-saving, and was shown to be suitable for the NA subtyping of both cultured AIVs and uncultured AIV swab samples. The primers selected for this study showed excellent sensitivity and specificity in NA subtyping by RT-PCR, SYBR green-based Real-time PCR and Real-time RT-PCR methods. AIV RNA of 2 to 200 copies (varied by NA subtypes) could be detected by these reactions. No unspecific amplification was displayed when detecting RNAs of other avian infectious viruses such as Infectious bronchitis virus, Infectious bursal disease virus and Newcastle disease virus. In summary, this study introduced several sensitive and specific PCR-based assays for NA subtyping of AIVs and also validated again the effectiveness of the PrimerHunter tool for the design of subtyping primers.
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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 | 0.008 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 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 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".