Phylogenetic analysis of HA and NA genes of influenza H1N1 viruses from 1918 to 2017
Bibliographic record
Abstract
The 1918 "Spanish" pandemic is the earliest known influenza H1N1 virus. Since then H1N1 viruses circulated between humans and animals continuously. With the increased amount of samples of H1N1 viruses and technology development, researchers have been studying how the viruses evolved. Here, we analyzed HA and NA genes of H1N1 viruses from three aspects: host distribution, geographical distribution and phylogenetic analysis. The data showed hosts were predominantly human, swine and poultry, and other hosts were mainly cat, ferret, wild bear, canine, cheetah and seal. In terms of geographical distribution, the North America and Eurasia were the main H1N1 influenza pandemic areas. Of them, the United States, China, Japan, Canada, the United Kingdom, India and Singapore were the most affected. The phylogenetic analysis of surface genes of influenza H1N1 viruses from 1918 to 2017 worldwide revealed the distribution of all avian influenza viruses (AIVs) showed a clear geographical difference, mainly concentrated in Eurasia and America. American and Eurasian swine viruses might be the ancestors of the 2009 pandemic virus' HA and NA genes. Swine influenza viruses played an important role in the spread of influenza viruses across species. To our knowledge, this is the first large-scale phylogenetic analysis of HA and NA genes of influenza H1N1 viruses worldwide until now. Our findings further emphasize the importance of surveillance of the genetic diversity of influenza H1N1 viruses in different hosts and raised more concerns about the long-time monitoring. Keywords: influenza H1N1 viruses; HA genes; NA genes; phylogenetic analysis; evolution.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".