Mercury increases IL-1β and IL-18 secretion and intensifies coronary arteritis in an animal model of Kawasaki disease
Bibliographic record
Abstract
Kawasaki disease (KD) is a multisystem vasculitis that predominantly targets the coronary arteries in young children. Epidemiological data suggest both environmental and genetic factors contribute to the susceptibility and severity of the disease. Mercury (Hg) is a known environmental pollutant and a Ca2+ signaling modulator. Ca2+ signaling regulates the activation of NLRP3 inflammasome. Using the Lactobacillus casei cell wall extract (LCWE) induced coronary arteritis mouse model of KD; we studied the effect of mercury on inflammasome activation and its impact on the immunopathogenesis of KD. Mercury enhances the expression of inflammasome activation resulting in caspase-1 mediated secretion of IL-1β and IL-18 cytokines. In vivo, the administration of mercury together with disease inducing LCWE exacerbates disease resulting in increased incidence and severity of coronary arteritis compared to LCWE alone. Mercury can act as a novel danger signal modulating Ca2+ signaling to increase IL-1β and IL-18 secretion and intensifies coronary arteritis in an animal model of KD.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".