<b>Anti</b> phospholipid antibody-mediated effects in an arterial model of thrombosis are dependent on <b>Toll-like receptor 4</b>
Bibliographic record
Abstract
Patients with antiphospholipid syndrome (APS) produce antiphospholipid antibodies (aPL) and develop vascular thrombosis that may occur in large or small vessels in the arterial or venous beds. On the other hand, many individuals produce aPL and yet never develop thrombotic events. Toll-like receptor 4 (TLR4) appears to be necessary for aPL-mediated prothrombotic effects in venous and microvascular models of thrombosis, but its role in arterial thrombosis has not been studied. Here, we propose that aPL alone are insufficient to cause thrombotic events in an arterial model of APS, and that a concomitant trigger of innate immunity (e.g. TLR4 activation) is required. We show specifically that anti-β2-glycoprotein I (anti-β2GPI) antibodies, a subset of aPL, accelerated thrombus formation in C57BL/6 wild-type, but not TLR4-deficient, mice in a ferric chloride-induced carotid artery injury model. These aPL bound to arterial and venous endothelial cells, particularly in the presence of β2GPI, and to human TLR4 by enzyme-linked immunoassay. Arterial endothelium from aPL-treated mice had enhanced leukocyte adhesion, compared to control IgG-treated mice. In addition, aPL treatment of mice enhanced expression of tissue factor (TF) in leukocytes induced by the TLR4 ligand lipopolysaccharide (LPS). aPL also enhanced LPS-induced TF expression in human leukocytes in vitro. Our findings support a mechanism in which aPL enhance TF expression by leukocytes, as well as augment adhesion of leukocytes to the arterial endothelium. The activation of TLR4 in aPL-positive individuals may be required to trigger thrombotic events.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| 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 | 0.001 |
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".