Dengue virus binding and replication by platelets
Bibliographic record
Abstract
Dengue virus (DENV) infection causes ∼200 million cases of severe flulike illness annually, escalating to life-threatening hemorrhagic fever or shock syndrome in ∼500,000. Although thrombocytopenia is typical of both mild and severe diseases, the mechanism triggering platelet reduction is incompletely understood. As a probable initiating event, direct purified DENV-platelet binding was followed in the current study by quantitative reverse transcription-polymerase chain reaction and confirmed antigenically. Approximately 800 viruses specifically bound per platelet at 37°C. Fewer sites were observed at 25°C, the blood bank storage temperature (∼350 sites), or 4°C, known to attenuate virus cell entry (∼200 sites). Dendritic cell-specific intercellular adhesion molecule-3-grabbing nonintegrin (DC-SIGN) and heparan sulfate proteoglycan were implicated as coreceptors because only the combination of anti-DC-SIGN and low-molecular-weight heparin prevented binding. Interestingly, at 37°C and 25°C, platelets replicated the positive sense single-stranded RNA genome of DENV by up to ∼4-fold over 7 days. Further time course experiments demonstrated production of viral NS1 protein, which is known to be highly antigenic in patient serum. The infectivity of DENV intrinsically decayed in vitro, which was moderated by platelet-mediated generation of viable progeny. This was shown using a transcription inhibitor and confirmed by freeze-denatured platelets being incapable of replicating the DENV genome. For the first time, these data demonstrate that platelets directly bind DENV saturably and produce infectious virus. Thus, expression of antigen encoded by DENV is a novel consideration in the pathogen-induced thrombocytopenia mechanism. These results furthermore draw attention to the possibility that platelets may produce permissive RNA viruses in addition to DENV.
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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) | 0.001 | 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".