Mechanism of Vascular Dysfunction Due to Circulating Factors in Women With Preeclampsia [23O]
Bibliographic record
Abstract
INTRODUCTION: Circulating factors have been proposed to play a major role in the pathophysiology of endothelial dysfunction observed in preeclampsia (PE), defined as new-onset hypertension with proteinuria after 20 weeks of gestation. We hypothesized that circulating factors in PE plasma lead to endothelial dysfunction by increasing oxidative stress and reducing nitric oxide and prostaglandin bioavailability. METHODS: Pregnant rat uterine and mesenteric arteries were incubated overnight with 3% normotensive (NP) or PE plasma collected from pregnant women. Responses to methacholine were obtained using wire myography to assess endothelial function pathways. Vascular superoxide production was measured via dihydroethidium staining and nitric oxide synthase (NOS) expression via Western blots. RESULTS: PE plasma significantly increased superoxide production and impaired endothelial function in uterine arteries (Emax 79.9±5.6% vs 44.9±6.3%, P=.0004), which was restored in the presence of oxidant scavengers or prostaglandin synthesis inhibition. Uterine artery vasodilation was abolished in the presence of pan nitric oxide synthase inhibition in both NP- and PE-treated vessels, but inducible NOS (iNOS)-dependent vasodilation was present only in NP-treated arteries. Uterine arteries exposed to PE plasma exhibit an increased endothelial NOS expression and a decreased iNOS expression. PE plasma did not alter endothelial function in mesenteric arteries, suggesting the effect of circulating factors on endothelial function was vascular bed specific. CONCLUSION: We have shown that circulating factors contribute to endothelial dysfunction via altered oxidative stress and vasodilator pathways. This study contributes to understanding the pathophysiology and finding a potential target for intervention in PE.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".