Inflammasome Signaling, Thromboinflammation, and Venous Thromboembolism
Bibliographic record
Abstract
Venous thromboembolism (VTE) remains a major health burden despite anticoagulation advances, suggesting incomplete management of pathogenic mechanisms. The NLRP3 (NACHT-, LRR- and pyrin domain-containing protein 3) inflammasome, interleukin (IL)-1, and pyroptosis are emerging contributors to the inflammatory pathogenesis of VTE. Inflammasome pathway activation occurs in patients with VTE. In preclinical models, inflammasome signaling blockade reduces venous thrombogenesis and vascular injury, suggesting that this therapeutic approach may potentially maximize anticoagulation benefits, protecting from VTE occurrence, recurrence, and ensuing post-thrombotic syndrome. The nonselective NLRP3 inhibitor colchicine and the anti-IL-1β agent canakinumab reduce atherothrombosis without increasing bleeding. Rosuvastatin reduces primary venous thrombotic events at least in part through lipid-lowering independent mechanisms, paving the way to targeted anti-inflammatory strategies in VTE. This review outlines recent preclinical and clinical evidence supporting a role for inflammasome pathway activation in venous thrombosis, and discusses the, yet unexplored, therapeutic potential of modulating inflammasome signaling to prevent and manage VTE.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".