Dengue Immunopathogenesis: A Crosstalk between Host and Viral Factors Leading to Disease: Part I - Dengue Virus Tropism, Host Innate Immune Responses, and Subversion of Antiviral Responses
Bibliographic record
Abstract
Dengue is the most prevalent emerging mosquito-borne viral disease, affecting more than 40% of the human population worldwide. Many symptomatic dengue virus (DENV) infections result in a relatively benign disease course known as dengue fever (DF). However, a small proportion of patients develop severe clinical manifestations, englobed in two main categories known as dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS). Secondary infection with any of the four dengue virus serotypes (DENV1, -2, -3, and -4) is a risk factor to develop severe forms of dengue disease. DSS is primarily characterized by sudden and abrupt endothelial dysfunction, resulting in vascular leak and organ impairment, which may progress to hypovolemic shock and death. Severe DENV disease (DHF/DSS) is thought to follow a complex relationship between distinct immunopathogenic processes involving host and viral factors, such as the serotype cross-reactive antibody-dependent enhancement (ADE), the activation of T cells and complement pathways, the phenomenon of the cytokine storm, and the newly described viral toxin activity of the nonstructural protein 1 (NS1), which together play critical roles in inducing vascular leak and virus pathogenesis. In this chapter that is divided in two parts, we will outline the recent advances in our understanding of DENV pathogenesis, highlighting key viral-host interactions and discussing how these interactions may contribute to DENV immunopathology and the development of vascular leak, a hallmark of severe dengue. Part I will address the general features of the DENV complex, including the virus structure and genome, epidemiology, and clinical outcomes, followed by an updated review of the literature describing the host innate immune strategies as well as the viral mechanisms acting against and in favor of the DENV replication cycle and infection.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".