Human Polyclonal Antibodies Prevent Lethal Zika Virus Infection in Mice
Bibliographic record
Abstract
Abstract Zika virus (ZIKV) is an emerging mosquito-borne flavivirus that represents a major threat to global health. ZIKV infections in adults are generally asymptomatic or present with mild symptoms. However, recent outbreaks of ZIKV have revealed that it can cause Congenital Zika Syndrome in neonates and Guillain-Barré syndrome in adults. Currently, no ZIKV-specific vaccines or antiviral treatments are available. In this study, we tested the efficacy of convalescent plasma IgG hyperimmune product (ZIKV-IG) isolated from individuals with high neutralizing anti-ZIKV titers as a therapeutic candidate against ZIKV infection using a model of ZIKV infection in Ifnar1−/− mice. ZIKV-IG successfully protected mice from lethal ZIKV challenge. In particular, ZIKV-IG treatment at 24 hours after lethal ZIKV infection improved survival by reducing weight loss and tissue viral burden and improving clinical score. Additionally, ZIKV-IG eliminated ZIKV-induced tissue damage and inflammation in the brain and liver. These results indicate that ZIKV-IG is efficacious against ZIKV, suggesting this human polyclonal antibody is a viable candidate for further development as a treatment against human ZIKV infection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".