Thymic stromal lymphopoietin induces platelet mitophagy and promotes thrombosis in Kawasaki disease
Bibliographic record
Abstract
Kawasaki disease (KD) is an acute systemic vasculitis primarily affecting infants and children. Activated platelets predispose patients to coronary artery structural lesions that may lead to thrombotic cardiovascular events. To discover potential proteins underlying platelet activation in KD, we conducted a protein chip assay of 34 cytokines and discovered thymic stromal lymphopoietin (TSLP) was aberrantly expressed, which remained elevated after intravenous immunoglobulin G (IVIG) treatment and during convalescence in KD patients in comparison to healthy controls. Enzyme-linked immunosorbent assay (ELISA) corroborated the upregulation of TSLP in KD patients, which was exacerbated in convalescent patients complicated with thrombosis. TSLP receptors on platelets were also significantly upregulated in KD patients complicated with thrombosis. Platelet activation, apoptosis, and mitochondrial autophagy (mitophagy) were increased in convalescence KD patients complicated with thrombosis. In vitro, TSLP induced platelet activation and platelet mitophagy in healthy blood donors, as observed in KD patients. TSLP, similar to mitophagy agonist carbonyl cyanide 3-chlorophenyl hydrazone (CCCP), promoted thrombosis, which was attenuated by the mitophagy inhibitor Mdivi-1. Co-immunoprecipitation in TSLP-treated platelets revealed TSLP receptor (TSLPR) bound to mitophagy regulators, Parkin and Voltage Dependent Anion Channel Protein 1 (VDAC1).Thus, our results demonstrated that TSLP induced platelet mitophagy via a novel TSLPR/Parkin/VDAC1 pathway that promoted thrombosis in KD. These results suggest TSLP as a novel therapeutic target against KD-associated thrombosis.
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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".