Tree shrew as a new animal model to study the pathogenesis of avian influenza (H9N2) virus infection
Bibliographic record
Abstract
Outbreaks of avian influenza virus continue to pose threats to human health. Animal models such as the mouse, ferret, and macaque are used to understand the pathogenesis of avian influenza virus infection in humans. We previously reported that the tree shrew (Tupaia belangeri, family Tupaiidae), which is regarded as a “low-level primate”, has α2,3- and α2,6-linked sialic acid receptor distributions similar to those of humans and is potentially a useful mammalian model for studying mild human influenza (H1N1) virus infection. In this study, we used the tree shrew experimental model to investigate the pathogenesis of avian influenza A (H9N2) virus infection and the effect of the E627K mutation in the PB2 gene, an adaptation to mammalian hosts. Evidence of disease, virus titers in the upper and lower respiratory tract, histopathology and induction of proinflammatory cytokines are described. We also established ex vivo culture models of tree shrew respiratory tissues to study the tropism and replication of the H9N2 virus. Our results demonstrated that the tree shrew is a viable new in vivo experimental model for avian influenza research that provides results comparable to those observed in ferrets. The disease spectrum and pathogenesis in tree shrews correlate well with what is observed in humans.
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".