RNA Sensors Enable Human Mast Cell Anti-Viral Chemokine Production and IFN-Mediated Protection in Response to Antibody-Enhanced Dengue Virus Infection
Bibliographic record
Abstract
Dengue hemorrhagic fever and/or dengue shock syndrome represent the most serious pathophysiological manifestations of human dengue virus infection. Despite intensive research, the mechanisms and important cellular players that contribute to dengue disease are unclear. Mast cells are tissue-resident innate immune cells that play a sentinel cell role in host protection against infectious agents via pathogen-recognition receptors by producing potent mediators that modulate inflammation, cell recruitment and normal vascular homeostasis. Most importantly, mast cells are susceptible to antibody-enhanced dengue virus infection and respond with selective cytokine and chemokine responses. In order to obtain a global view of dengue virus-induced gene regulation in mast cells, primary human cord blood-derived mast cells (CBMCs) and the KU812 and HMC-1 mast cell lines were infected with dengue virus in the presence of dengue-immune sera and their responses were evaluated at the mRNA and protein levels. Mast cells responded to antibody-enhanced dengue virus infection or polyinosiniċpolycytidylic acid treatment with the production of type I interferons and the rapid and potent production of chemokines including CCL4, CCL5 and CXCL10. Multiple interferon-stimulated genes were also upregulated as well as mRNA and protein for the RNA sensors PKR, RIG-I and MDA5. Dengue virus-induced chemokine production by KU812 cells was significantly modulated by siRNA knockdown of RIG-I and PKR, in a negative and positive manner, respectively. Pretreatment of fresh KU812 cells with supernatants from dengue virus-infected mast cells provided protection from subsequent infection with dengue virus in a type I interferon-dependent manner. These findings support a role for tissue-resident mast cells in the early detection of antibody-enhanced dengue virus infection via RNA sensors, the protection of neighbouring cells through interferon production and the potential recruitment of leukocytes via chemokine production.
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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".