Molecular mimicry between virus and host and its implications for dengue disease pathogenesis
Bibliographic record
Abstract
Numerous infectious agents may trigger autoimmunity or even result in autoimmune diseases. Several mechanisms have been proposed for pathogen-triggered autoimmunity including molecular mimicry, cryptic antigens, epitope spreading, bystander activation and polyclonal activation. In the case of dengue virus infection which causes serious public health problems, the mechanisms regarding the pathogenesis of dengue hemorrhagic syndrome are not fully resolved. Our previous studies suggest a mechanism of molecular mimicry in which antibodies directed against dengue virus non-structural protein 1 (NS1) cross-react with human platelets and endothelial cells and cause their damage and dysfunction, which may be related to the clinical features of dengue disease. Several cell surface proteins recognized by patient serum samples and anti-NS1 antibodies have been identified. Based on proteomic studies and sequence analysis, the C-terminal region of dengue virus NS1 shows sequence homology with target proteins. In addition, different regions of dengue virus proteins including core, prM, E and NS1 proteins show sequence homology with different coagulatory molecules. As an example, the amino acid sequence 101-106 of E protein (WGNGCG) shows sequence homology with factors XI, X, IX, VII, II (thrombin), plasminogen and tissue plasminogen activator. Furthermore, single chain variable region against NS1 can interfere with fibrin formation, which leads to prolonged thrombin time. We hypothesize that molecular mimicry between dengue virus proteins and coagulatory molecules may induce cross-reactive autoantibodies that can interfere with coagulation activation. A molecular mimicry pathogenesis for dengue disease which involves cross-reactivity of dengue virus with human endothelial cells, platelets and coagulatory molecules is proposed.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".