Soluble triggering receptor expressed on myeloid cells 1 is associated with hemoconcentration and endothelial activation in children and young adults with dengue virus infection in the Philippines
Bibliographic record
Abstract
BACKGROUND: Triggering receptor expressed on myeloid cells 1 (TREM1) is a cell-surface receptor expressed on neutrophils that amplifies the inflammatory response. Dengue virus (DENV) infection is characterized by systemic inflammation, endothelial activation, and vascular leakage. METHODOLOGY/PRINCIPAL FINDINGS: We investigated circulating soluble TREM-1 (sTREM-1) levels in 244 children and young adults aged 1-26 years with dengue fever presenting to an outpatient clinic in the Philippines. Elevated sTREM-1 (≥130 pg/mL) was associated with hemoconcentration, a hallmark of vascular leakage (odds ratio (OR) 3.8, 95%CI 1.6-10, p = 0.0020). In turn, hemoconcentration was associated with hospitalization (OR 4.2, 95%CI 1.0-38, p = 0.0497) and higher volume of intravenous fluid required for resuscitation (p = 0.019). Elevated inflammation marker TNF (≥5 pg/mL) was associated with increased sTREM-1 levels (p = 0.0014). Endothelial activation markers angiopoietin-2 (Ang-2), soluble FMS-like tyrosine kinase-1 (sFlt-1), and soluble vascular cell adhesion molecule 1 (sVCAM-1) were correlated with sTREM-1 levels (p < 0.0001 for all three comparisons). CONCLUSIONS/SIGNIFICANCE: Our findings suggest that sTREM-1 may be a clinically informative marker of neutrophil activation, associated with hemoconcentration, systemic inflammation, and endothelial activation and in dengue fever.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".