Host gene expression profiles in ferrets infected with genetically distinct henipavirus strains
Bibliographic record
Abstract
Henipavirus infection causes severe respiratory and neurological disease in humans that can be fatal.To characterize the pathogenic mechanisms of henipavirus infection in vivo, we performed experimental infections in ferrets followed by genome-wide gene expression analysis of lung and brain tissues.The Hendra, Nipah-Bangladesh, and Nipah-Malaysia strains caused severe respiratory and neurological disease with animals succumbing around 7 days post infection.Despite the presence of abundant viral shedding, animal-toanimal transmission did not occur.The host gene expression profiles of the lung tissue showed early activation of interferon responses and subsequent expression of inflammation-related genes that coincided with the clinical deterioration.Additionally, the lung tissue showed unchanged levels of lymphocyte markers and progressive downregulation of cell cycle genes and extracellular matrix components.Infection in the brain resulted in a limited breadth of the host responses, which is in accordance with the immunoprivileged status of this organ.Finally, we propose a model of the pathogenic mechanisms of henipavirus infection that integrates multiple components of the host responses. Author summaryHenipavirus infection can cause severe and often lethal respiratory and neurological disease in humans.The mechanisms by which these viruses cause disease are unknown.To characterize the mechanisms of henipavirus disease in vivo, we performed experimental infections in ferrets followed by characterization of the host response in lung and brain
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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".