Pathogenic influenza B virus in the ferret model establishes lower respiratory tract infection
Bibliographic record
Abstract
Influenza B viruses have become increasingly more prominent during influenza seasons. Influenza B infection is typically considered a mild disease and receives less attention than influenza A, but has been causing 20 to 50 % of the total influenza incidence in several regions around the world. Although there is increasing evidence of mid to lower respiratory tract diseases such as bronchitis and pneumonia in influenza B patients, little is known about the pathogenesis of recent influenza B viruses. Here we investigated the clinical and pathological profiles of infection with strains representing the two current co-circulating B lineages (B/Yamagata and B/Victoria) in the ferret model. Specifically, we studied two B/Victoria (B/Brisbane/60/2008 and B/Bolivia/1526/2010) and two B/Yamagata (B/Florida/04/2006 and B/Wisconsin/01/2010) strain infections in ferrets and observed strain-specific but not lineage-specific pathogenicity. We found B/Brisbane/60/2008 caused the most severe clinical illness and B/Brisbane/60/2008 and the B/Yamagata strains instigated pathology in the middle to lower respiratory tract. Importantly, B/Brisbane/60/2008 established efficient lower respiratory tract infection with high viral burden. Our phylogenetic analyses demonstrate profound reassortment among recent influenza B viruses, which indicates the genetic make-up of B/Brisbane/60/2008 differs from the other strains. This may explain the pathogenicity difference post-infection in ferrets.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".