The Early Whole-Blood Transcriptional Signature of Dengue Virus and Features Associated with Progression to Dengue Shock Syndrome in Vietnamese Children and Young Adults
Bibliographic record
Abstract
Dengue is a pantropic public health problem. In children, dengue shock syndrome (DSS) is the most common life-threatening complication. The ability to predict which patients may develop DSS may improve triage and treatment. To this end, we conducted a nested case-control comparison of the early host transcriptional features in 24 DSS patients and 56 sex-, age-, and virus serotype-matched uncomplicated (UC) dengue patients. In the first instance, we defined the "early dengue" profile. The transcriptional signature in acute rather than convalescent samples (≤72 h post-illness onset) was defined by an overabundance of interferon-inducible transcripts (31% of the 551 overabundant transcripts) and canonical gene ontology terms that included the following: response to virus, immune response, innate immune response, and inflammatory response. Pathway and network analyses identified STAT1, STAT2, STAT3, IRF7, IRF9, IRF1, CEBPB, and SP1 as key transcriptional factors mediating the early response. Strikingly, the only difference in the transcriptional signatures of early DSS and UC dengue cases was the greater abundance of several neutrophil-associated transcripts in patients who progressed to DSS, a finding supported by higher plasma concentrations of several canonical proteins associated with neutrophil degranulation (bactericidal/permeability-increasing protein [BPI], elastase 2 [ELA2], and defensin 1 alpha [DEF1A]). Elevated levels of neutrophil-associated transcripts were independent of the neutrophil count and also of the genotype of the infecting virus, as genome-length sequences of dengue virus serotype 1 (DENV-1) (n = 15) and DENV-2 (n = 3) sampled from DSS patients were phylogenetically indistinguishable from those sampled from uncomplicated dengue patients (32 DENV-1 and 9 DENV-2 sequences). Collectively, these data suggest a hitherto unrecognized association between neutrophil activation, pathogenesis, and the development of DSS and point to future strategies for guiding prognosis.
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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".