Potential for Low-Pathogenic Avian H7 Influenza A Viruses To Replicate and Cause Disease in a Mammalian Model
Bibliographic record
Abstract
H7 subtype influenza A viruses are widely distributed and have been responsible for human infections and numerous outbreaks in poultry with significant impact. Despite this, the disease-causing potential of the precursor low-pathogenic (LP) H7 viruses from the wild bird reservoir has not been investigated. Our objective was to assess the disease-causing potential of 30 LP H7 viruses isolated from wild avian species in the United States and Canada using the DBA/2J mouse model. Without prior mammalian adaptation, the majority of viruses, 27 (90%), caused mortality in mice. Of these, 17 (56.7%) caused 100% mortality and 24 were of pathogenicity similar to that of A/Anhui/1/2013 (H7N9), which is highly pathogenic in mice. Viruses of duck origin were more pathogenic than those of shorebird origin, as 13 of 18 (72.2%) duck origin viruses caused 100% mortality while 4 of 12 (33.3%) shorebird origin viruses caused 100% mortality, despite there being no difference in mean lung viral titers between the groups. Replication beyond the respiratory tract was also evident, particularly in the heart and brain. Of the 16 viruses studied for fecal shedding, 11 were detected in fecal samples. These viruses exhibited a strong preference for avian-type α2,3-linked sialic acids; however, binding to mammalian-type α2,6-linked sialic acids was also detected. These findings indicate that LP avian H7 influenza A viruses are able to infect and cause disease in mammals without prior adaptation and therefore pose a potential public health risk. IMPORTANCE: Low-pathogenic (LP) avian H7 influenza A viruses are widely distributed in the avian reservoir and are the precursors of numerous outbreaks of highly pathogenic avian influenza viruses in commercial poultry farms. However, unlike highly pathogenic H7 viruses, the disease-causing potential of LP H7 viruses from the wild bird reservoir has not been investigated. To address this, we studied 30 LP avian H7 viruses isolated from wild avian species in the United States and Canada using the DBA/2J mouse model. Surprisingly, the majority of these viruses, 90%, caused mortality in mice without prior mammalian adaptation, and 56.7% caused 100% mortality. There was also evidence of spread beyond the respiratory tract and fecal shedding. Therefore, the disease-causing potential of LP avian H7 influenza A viruses in mammals may be underestimated, and these viruses therefore pose a potential public health risk.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".