Nucleotide sequence analysis and development of consensus primers of RT‐PCR for detection of norwalk‐like viruses prevailing in Japan
Bibliographic record
Abstract
A total of 177 different nucleotide sequences of the RNA polymerase region of Norwalk-like viruses (NLVs) genomes, collected via a nation-wide survey project in Japan between 1989 and 1998, were examined by reverse transcription-polymerase chain reaction (RT-PCR) employing various primer pairs. The nucleotide sequences of different strains showed great diversity, with a range of 57 to 100% identities among strains. The strains could be classified into five clusters: Norwalk (NV), Snow Mountain agent/Bristol virus (SMA/BV), Toronto virus/Mexico virus (TV/MX), and Japan specific cluster 1 and 2 (JP-1 and JP-2). Within each cluster there is greater than 85% identity of amino acid sequence (more than 75% identity of nucleotide sequences), based on sequence homology analysis. We believe that two of the five clusters, JP-1and JP-2, define new specific clusters found in Japan according to phylogenetic and pair-wise comparison studies. An RT-PCR procedure was designed using new consensus primer pairs, P1/P2, P1/P3, and Y1/Y2 based on multiple alignment of collected nucleotide sequences, that are expected to detect nearly all NLVs prevailing in Japan. The usefulness of the primers was tested by ten different laboratories in Japan using a panel of ten fecal samples containing different virus strains. The identification of these primer pairs will facilitate routine diagnosis of NLV infection by RT-PCR and offers the potential for their direct detection in food and environmental samples.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".