Interferon Response Factors 3 and 7 Protect against Chikungunya Virus Hemorrhagic Fever and Shock
Bibliographic record
Abstract
Chikungunya virus (CHIKV) infections can produce severe disease and mortality. Here we show that CHIKV infection of adult mice deficient in interferon response factors 3 and 7 (IRF3/7(-/-)) is lethal. Mortality was associated with undetectable levels of alpha/beta interferon (IFN-α/β) in serum, ∼50- and ∼10-fold increases in levels of IFN-γ and tumor necrosis factor (TNF), respectively, increased virus replication, edema, vasculitis, hemorrhage, fever followed by hypothermia, oliguria, thrombocytopenia, and raised hematocrits. These features are consistent with hemorrhagic shock and were also evident in infected IFN-α/β receptor-deficient mice. In situ hybridization suggested CHIKV infection of endothelium, fibroblasts, skeletal muscle, mononuclear cells, chondrocytes, and keratinocytes in IRF3/7(-/-) mice; all but the latter two stained positive in wild-type mice. Vaccination protected IRF3/7(-/-) mice, suggesting that defective antibody responses were not responsible for mortality. IPS-1- and TRIF-dependent pathways were primarily responsible for IFN-α/β induction, with IRF7 being upregulated >100-fold in infected wild-type mice. These studies suggest that inadequate IFN-α/β responses following virus infection can be sufficient to induce hemorrhagic fever and shock, a finding with implications for understanding severe CHIKV disease and dengue hemorrhagic fever/dengue shock syndrome.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".