Characterization and Gene Expression Analysis of Serum-Derived Extracellular Vesicles in Primary Aldosteronism
Bibliographic record
Abstract
Patients affected by primary aldosteronism (PA) display an increased risk of cardiovascular events compared with essential hypertension (EH). Endothelial dysfunction favors initiation and progression of atherosclerosis and circulating extracellular vesicles (EVs), reflecting endothelial cell activity, could represent one of the mediators of endothelial dysfunction in these patients. The aim of this study was to characterize circulating EVs from patients diagnosed with PA and to explore their functional significance. Serum EVs were isolated from 12 patients with PA and 12 with EH, matched by sex, age, and blood pressure, and compared with 8 normotensive controls. At nanoparticle tracking analysis, EVs concentration was 2.2× higher in patients with PA ( P=0.033) compared with EH and a significant correlation between EV number and serum aldosterone and potassium levels was identified. Fluorescence-activated cell sorting analysis demonstrated that patients with PA presented a higher absolute number of endothelial-derived EVs compared with both patients with EH and normotensive controls. Through EV mRNA profiling, 15 up-regulated and 4 down-regulated genes in patients with PA compared with EH were identified; moreover, EDN1 was expressed only in patients with PA. Microarray platform was validated by quantative real-time polymerase chain reaction on 4 genes ( CASP1, EDN1, F2R, and HMOX1) involved in apoptosis, inflammation, and endothelial dysfunction. After unilateral adrenalectomy, EVs number and expression of CASP1 and EDN1 significantly decreased in patients with PA ( P<0.05). Additionally, the incubation with PA-derived EVs reduced angiogenesis and induced apoptosis in vitro. Circulating EVs might not only represent a marker of endothelial dysfunction but also contribute themselves to vascular dysfunction in patients with PA.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".