Monocyte‐Derived Interleukin‐1β As the Driver of S100A12‐Induced Sterile Inflammatory Activation of Human Coronary Artery Endothelial Cells: Implications for the Pathogenesis of Kawasaki Disease
Bibliographic record
Abstract
OBJECTIVE: Kawasaki disease (KD) is an acute vasculitis of childhood, predominantly affecting the coronary arteries. S100A12, a granulocyte-derived agonist of both the receptor for advanced glycation end products (RAGE) and Toll-like receptor 4 (TLR-4), is strongly up-regulated in KD. This study was undertaken to investigate the potential contributions of S100A12 to the pathogenesis of KD. METHODS: Serum samples from patients with KD (n = 30) at different stages pre- and post-intravenous immunoglobulin (IVIG) treatment were analyzed for the expression of S100A12, cytokines, chemokines, and soluble markers of endothelial cell activation. Primary human coronary artery endothelial cells (HCAECs) were analyzed for responsiveness to direct stimulation with S100A12 or lipopolysaccharide (LPS), as assessed by real-time quantitative reverse transcription-polymerase chain reaction analysis of cytokine and endothelial cell adhesion molecule messenger RNA expression. Alternatively, HCAECs were cultured in conditioned medium obtained from primary human monocytes that were stimulated with LPS or S100A12 in the absence or presence of IVIG or cytokine antagonists. RESULTS: = -0.6, P = 0.0003). Yet, HCAECs were not responsive to direct S100A12 stimulation, despite the presence of appropriate receptors (RAGE, TLR-4). HCAECs did, however, respond to supernatants obtained from S100A12-stimulated primary human monocytes, as evidenced by the gene expression of inflammatory cytokines and adhesion molecules. This response was strictly dependent on interleukin-1β (IL-1β) signaling (P < 0.001). CONCLUSION: In its role as a highly expressed mediator of sterile inflammation in KD, S100A12 appears to activate HCAECs in an IL-1β-dependent manner. These data provide new mechanistic insights into the contributions of S100A12 and IL-1β to disease pathogenesis, and may therefore support current IL-1-targeting studies in the treatment of patients with KD.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".