Induction of Epitope-Specific Neutralizing Antibodies against West Nile Virus
Bibliographic record
Abstract
Previous studies have established that an epitope on the lateral ridge of domain III (DIII-lr) of West Nile virus (WNV) envelope (E) protein is recognized by strongly neutralizing type-specific antibodies. In contrast, an epitope against the fusion loop in domain II (DII-fl) is recognized by flavivirus cross-reactive antibodies with less neutralizing potential. Using gain- and loss-of-function E proteins and wild-type and variant WNV reporter virus particles, we evaluated the expression pattern and activity of antibodies against the DIII-lr and DII-fl epitopes in mouse and human serum after WNV infection. In mice, immunoglobulin M (IgM) antibodies to the DIII-lr epitope were detected at low levels at day 6 after infection. However, compared to IgG responses against other epitopes in DI and DII, which were readily detected at day 8, the development of IgG against DIII-lr epitope was delayed and did not appear consistently until day 15. This late time point is notable since almost all death after WNV infection in mice occurs by day 12. Nonetheless, at later time points, DIII-lr antibodies accumulated and comprised a significant fraction of the DIII-specific IgG response. In sera from infected humans, DIII-lr antibodies were detected at low levels and did not correlate with clinical outcome. In contrast, antibodies to the DII-fl were detected in all human serum samples and encompassed a significant percentage of the anti-E protein response. Our experiments suggest that the highly neutralizing DIII-lr IgG antibodies have little significant role in primary infection and that the antibody response of humans may be skewed toward the induction of cross-reactive, less-neutralizing antibodies.
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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) | 0.000 | 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) | 0.001 | 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".