Autoantibodies neutralizing type I IFNs underlie West Nile virus encephalitis in ∼40% of patients
Bibliographic record
Abstract
Mosquito-borne West Nile virus (WNV) infection is benign in most individuals but can cause encephalitis in <1% of infected individuals. We show that ∼35% of patients hospitalized for WNV disease (WNVD) in six independent cohorts from the EU and USA carry auto-Abs neutralizing IFN-α and/or -ω. The prevalence of these antibodies is highest in patients with encephalitis (∼40%), and that in individuals with silent WNV infection is as low as that in the general population. The odds ratios for WNVD in individuals with these auto-Abs relative to those without them in the general population range from 19.0 (95% CI 15.0-24.0, P value <10-15) for auto-Abs neutralizing only 100 pg/ml IFN-α and/or IFN-ω to 127.4 (CI 87.1-186.4, P value <10-15) for auto-Abs neutralizing both IFN-α and IFN-ω at a concentration of 10 ng/ml. These antibodies block the protective effect of IFN-α in Vero cells infected with WNV in vitro. Auto-Abs neutralizing IFN-α and/or IFN-ω underlie ∼40% of cases of WNV encephalitis.
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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 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".