Establishment of a severe dengue disease murine model for preclinical CD8+ T cell targeting vaccine trials
Bibliographic record
Abstract
Dengue fever, a mosquito-borne disease, is responsible for approximately 390 million infections and 20,000 deaths worldwide each year. Since 2018, Aedes genus mosquitos, which transmit the dengue virus (DENV1-DENV4), have become locally established in Canada, increasing the risk for local dengue transmissions. A primary infection with one dengue strain does not provide long-term cross-protection against the other three strains, and a secondary infection with a different strain associates with an increased risk of severe dengue due to a phenomenon known as antibody-dependent enhancement (ADE). The goal of this project is to utilize genetically modified mice, in combination with the administration of anti-flavivirus antibodies as immunogens, to recapitulate key features of dengue fever. Establishing this murine model in the lab will provide a valuable platform for testing a novel CD8-targeting mRNA vaccine. We characterized the disease phenotype of type-I interferon alpha/beta receptor (IFNAR1) knockout mice following infection with a mouse-adapted dengue strain (D220). IFNAR1-/- mice that received anti-flavivirus antibodies prior to infection exhibited more severe clinical outcomes compared to both non-ADE and C57BL/6 resistant mice. Notably, vascular leakage, which is a symptom of severe dengue fever in human, was observed in IFNAR1-/- ADE mice during the acute phase of infection. Additionally, the viral load in IFNAR1-/- ADE mice was elevated compared to uninfected mice, with viral transcripts detected in organ samples. Furthermore, the infection elicited a robust CD8+ T cell response, including the shift of phenotype from naïve T cells to effector T cells and the secretion of IFNγ cytokines. Importantly, we have identified an indicator for dengue-experienced CD8+ T cells. These results suggest that severe dengue fever can be replicated in mice and highlight the crucial role of CD8+ T cells in host defense against DENV, providing a valuable resource for testing new preventive measures against severe dengue disease
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".