Endothelial cell surface expression of protein disulfide isomerase activates β1 and β3 integrins and facilitates dengue virus infection
Bibliographic record
Abstract
Infection with dengue virus (DENV) causes diseases ranging from mild dengue fever to severe hemorrhage or shock syndrome. DENV infection of endothelial cells may cause cell apoptosis or vascular leakage and result in clinical illness of hemorrhage. However, the endothelial cell molecules involved in DENV infection and the mechanisms governing virus-cell interactions are still uncertain. Since protein disulfide isomerase (PDI) reducing function at the cell surface was shown to be required for entry of certain viruses and bacteria, we explored the role of PDI expressed on endothelial cell surface in DENV infection. Using siRNA to knock down PDI, DENV infection was reduced which could be reversed by treating cells with a reducing agent Tris(2-carboxyethyl)phosphine hydrochloride (TCEP). DENV-induced PDI surface expression was mediated through the Lys-Asp-Glu-Leu (KDEL) receptor-Src family kinase signal pathway. Furthermore, cell surface PDI colocalized with β1 and β3 integrins after DENV infection, and the activation of integrins was blocked by PDI inhibition. Finally, blockade of PDI inhibited DENV entry into endothelial cells. Our findings suggest a novel mechanism whereby surface PDI which causes integrin activation is involved in DENV entry, and DENV infection further increases PDI surface expression at later time points. These findings may have implications for anti-DENV drug design.
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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 | 0.000 |
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".