Endothelial Microparticle Formation by Angiotensin II Is Mediated via Ang II Receptor Type I/NADPH Oxidase/ Rho Kinase Pathways Targeted to Lipid Rafts
Bibliographic record
Abstract
OBJECTIVE: Circulating microparticles are increased in cardiovascular disease and may themselves promote oxidative stress and inflammation. Molecular mechanisms underlying their formation and signaling are unclear. We investigated the role of reactive oxygen species (ROS), Rho kinase, and lipid rafts in microparticle formation and examined their functional significance in endothelial cells (ECs). METHODS AND RESULTS: Microparticle formation from angiotensin II (Ang II)-stimulated ECs and apolipoprotein E(-/-) mice was assessed by annexin V or by CD144 staining and electron microscopy. Ang II promoted microparticle formation and increased EC O(2)(-) generation and Rho kinase activity. Ang II-stimulated effects were inhibited by irbesartan (Ang II receptor type I blocker) and fasudil (Rho kinase inhibitor). Methyl-β-cyclodextrin and nystatin, which disrupt lipid rafts/caveolae, blocked microparticle release. Functional responses, assessed in microparticle-stimulated ECs, revealed increased O(2)(-) production, enhanced vascular cell adhesion molecule/platelet-EC adhesion molecule expression, and augmented macrophage adhesion. Inhibition of epidermal growth factor receptor blocked the prooxidative and proinflammatory effects of microparticles. In vitro observations were confirmed in apolipoprotein E(-/-) mice, which displayed vascular inflammation and high levels of circulating endothelial microparticles, effects that were reduced by apocynin. CONCLUSIONS: We demonstrated direct actions of Ang II on endothelial microparticle release, mediated through NADPH oxidase, ROS, and Rho kinase targeted to lipid rafts. Microparticles themselves stimulated endothelial ROS formation and inflammatory responses. Our findings suggest a feedforward system whereby Ang II promotes EC injury through its own endothelial-derived microparticles.
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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 | 0.001 |
| 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".