Release of Neutrophil Extracellular Traps by Neutrophils Stimulated With Antiphospholipid Antibodies: A Newly Identified Mechanism of Thrombosis in the Antiphospholipid Syndrome
Bibliographic record
Abstract
OBJECTIVE: Antiphospholipid antibodies (aPL), especially those targeting β2 -glycoprotein I (β2 GPI), are well known to activate endothelial cells, monocytes, and platelets, with prothrombotic implications. In contrast, the interaction of aPL with neutrophils has not been extensively studied. Neutrophil extracellular traps (NETs) have recently been recognized as an important activator of the coagulation cascade, as well as an integral component of arterial and venous thrombi. This study was undertaken to determine whether aPL activate neutrophils to release NETs, thereby predisposing to the arterial and venous thrombosis inherent in the antiphospholipid syndrome (APS). METHODS: Neutrophils, sera, and plasma were prepared from patients with primary APS (n = 52) or from healthy volunteers and characterized. No patient had concomitant systemic lupus erythematosus. RESULTS: Sera and plasma from patients with primary APS had elevated levels of both cell-free DNA and NETs, as compared to healthy volunteers. Freshly isolated neutrophils from patients with APS were predisposed to high levels of spontaneous NET release. Further, APS patient sera, as well as IgG purified from APS patients, stimulated NET release from control neutrophils. Human aPL monoclonal antibodies, especially those targeting β2 GPI, also enhanced NET release. The induction of APS NETs was abrogated with inhibitors of reactive oxygen species formation and Toll-like receptor 4 signaling. Highlighting the potential clinical relevance of these findings, APS NETs promoted thrombin generation. CONCLUSION: Our findings indicate that NET release warrants further investigation as a novel therapeutic target in APS.
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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".