The role of dengue virus nonstructural protein 1 (NS1) C‐terminal region in anti‐NS1‐mediated platelet dysfunction
Bibliographic record
Abstract
Dengue virus (DV) infection may develop into severe hemorrhage. Our previous studies showed that anti‐DV nonstructural protein 1 (NS1) cross‐reacted with human platelets and inhibited platelet aggregation. Based on the sequence homology alignment, the C‐terminal region of DV NS1 protein contained cross‐reactive epitopes which are shared between NS1 and self‐antigens. To investigate the pathological roles of cross‐reactive epitopes of NS1, we compared the effects of antibodies against full‐length DV NS1 and NS1 lacking the C‐terminal amino acids 271 to 352 (ΔC NS1). We found that anti‐ΔC NS1 showed lower platelet binding ability than that of anti‐full‐length NS1. Anti‐full‐length NS1 but not anti‐ΔC NS1 inhibited platelet aggregation. Studies on the mechanism of platelet aggregation inhibition indicated an effect of anti‐DV NS1 antibodies on integrin activation. Using a murine model to assess the bleeding tendency caused by anti‐DV NS1, we found that the bleeding time in full‐length NS1‐hyperimmunized mice was longer than that in the normal control. ΔC NS1‐hyperimmunized mice showed a bleeding time similar to that of normal control mice. Passive immunization with anti‐DV NS1 antibodies showed a decrease in antibody titers which was correlated with the binding of antibodies to platelets in mice. This finding was not observed in mice given anti‐ΔC NS1. In conclusion, we demonstrated that platelet dysfunction and bleeding tendency were induced by anti‐full‐length DV NS1 but not by anti‐ΔC NS1 antibodies. These findings may provide a strategy for dengue vaccine development.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".