Potential Pandemic of H7N9 Avian Influenza A Virus in Human
Bibliographic record
Abstract
Since 2013, the H7N9 avian influenza A virus (AIV) has caused human infections and to the extent of now surpassing H5N1. This raises an alarm about the potential of H7N9 to become a pandemic problem. Our compilation of the amino acid changes required for AIVs to cross the species-barrier discovers 58 that have very high proportions in both the human- and avian-isolated H7N9 viruses. These changes correspond with sporadic human infections that continue to occur in regions of avian infections. Among the six internal viral genes, amino acid changes do not differ significantly between H9N2 and H7N9, except for V100A in PA, and K526R, D627K, and D701N in PB2. H9N2 AIVs provide internal genes to H7N9. Most of the amino acid changes in H7N9 appear to come directly from H9N2. Seventeen amino acid substitutions appear to have fixed quickly by the 5th wave. Among these, six amino acid sites in HA1 are receptor binding sites, and PB2-A588V was shown to promote the adaptation of AIVs to mammals. The accelerated fixation of mutations may promote the adaptation of H7N9 to human, but need further functional evidence. Although H7N9 AIVs still cannot efficiently transmit between humans, they have the genetic makeup associated with human infections. These viruses must be controlled in poultry to remove the threat of it becoming a human pandemic event.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".