Comparative Analyses of Pandemic H1N1 and Seasonal H1N1, H3N2, and Influenza B Infections Depict Distinct Clinical Pictures in Ferrets
Bibliographic record
Abstract
Influenza A and B infections are a worldwide health concern to both humans and animals. High genetic evolution rates of the influenza virus allow the constant emergence of new strains and cause illness variation. Since human influenza infections are often complicated by secondary factors such as age and underlying medical conditions, strain or subtype specific clinical features are difficult to assess. Here we infected ferrets with 13 currently circulating influenza strains (including strains of pandemic 2009 H1N1 [H1N1pdm] and seasonal A/H1N1, A/H3N2, and B viruses). The clinical parameters were measured daily for 14 days in stable environmental conditions to compare clinical characteristics. We found that H1N1pdm strains had a more severe physiological impact than all season strains where pandemic A/California/07/2009 was the most clinically pathogenic pandemic strain. The most serious illness among seasonal A/H1N1 and A/H3N2 groups was caused by A/Solomon Islands/03/2006 and A/Perth/16/2009, respectively. Among the 13 studied strains, B/Hubei-Wujiagang/158/2009 presented the mildest clinical symptoms. We have also discovered that disease severity (by clinical illness and histopathology) correlated with influenza specific antibody response but not viral replication in the upper respiratory tract. H1N1pdm induced the highest and most rapid antibody response followed by seasonal A/H3N2, seasonal A/H1N1 and seasonal influenza B (with B/Hubei-Wujiagang/158/2009 inducing the weakest response). Our study is the first to compare the clinical features of multiple circulating influenza strains in ferrets. These findings will help to characterize the clinical pictures of specific influenza strains as well as give insights into the development and administration of appropriate influenza therapeutics.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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".