Is a highly pathogenic avian influenza virus H5N1 fragment recombined in PB1 the key for the epidemic of the novel AIV H7N9 in China, 2013?
Bibliographic record
Abstract
BACKGROUND: A novel avian influenza A H7N9 virus that infects humans was identified in China in 2013. This study is the first to comprehensively investigate the characteristics of genomic recombination, rather than reassortment, which has been the subject of investigation in previously reported studies. METHODS: Novel avian influenza virus (AIV) H7N9 genome sequences were obtained from the NCBI Influenza Virus Sequence Database and the Global Initiative on Sharing Avian Influenza Database (GISAID) and a representative isolate was subjected to homogeneity analysis. A phylogenetic tree was constructed. Eight segments of the isolate were analyzed to identify segments with recombination events, the corresponding recombination fragments, and breakpoints. The evolutionary history of the recombined fragments was tracked by constructing phylogenetic trees of the recombination fragments. RESULTS: Among the eight segments of the novel AIV H7N9 analyzed, only the PB1 segment showed a marked recombination phenomenon, with 11 recombination events; these included five actual recombination events and six possible misalignment artifact recombination events. The most notable was the recombination of a 291-nucleotide (nt) fragment at the 490-780 nt site that was affiliated to a highly pathogenic avian influenza virus (HPAIV) H5N1 (A/tree sparrow/Thailand/VSMU-16-RBR/2005). The phylogenetic tree of the 291-nt recombination fragment on the PB1 segment showed that the novel AIV H7N9 had a close genetic relationship to H9N2 and H5N1. CONCLUSIONS: The novel AIV H7N9 might have reassorted its PB1 segment from H9N2 circulating in China, and this H9N2 PB1 might have been recombined into a highly pathogenic fragment from HPAIV H5N1, which could be the reason for the high fatality rate among patients with AIV H7N9 influenza.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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 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".