Placenta-derived extracellular vesicles from preeclamptic and healthy pregnancies impair <i>ex vivo</i> vascular endothelial function
Bibliographic record
Abstract
Preeclampsia (PE) is a pregnancy syndrome characterized by new-onset hypertension and end-organ dysfunction. The pathophysiology of PE remains undetermined, but it is thought that maternal vascular dysfunction plays a central role, potentially due, in part, to the release of syncytiotrophoblast-derived extracellular vesicles (STBEVs) into the maternal circulation by a dysfunctional placenta. STBEVs from normal pregnancies (NP) impair vascular function, but the effect of PE STBEVs (known to differ in composition with elevated circulating levels) on vascular function are not known. We hypothesized that PE STBEVs have more detrimental effects on vascular function compared with NP STBEVs. STBEVs were collected by perfusion of placentas from women with NP or PE. Mesenteric arteries from pregnant rats were incubated overnight with NP or PE STBEVs, and vascular function was assessed by wire myography. NP and PE STBEVs impaired endothelial function, partially by reducing nitric oxide (NO) bioavailability. Incubation of human umbilical vein endothelial cells with NP and PE STBEVs increased nuclear factor κ-light-chain-enhancer of activated B cell (NF-κB) activation, reactive oxygen species, nitrotyrosine levels, and reduced NO levels. However, PE STBEVs increased NF-κB activation and nitrotyrosine levels to a lesser extent than NP STBEVs. Taken together, no greater impact of PE STBEVs compared with NP STBEVs on endothelial function was found. However, the impaired vascular function by PE STBEVs and increased levels of STBEVs in PE suggest PE STBEVs may contribute to maternal vascular dysfunction in PE. Our study further expands on the potential mechanisms that lead to adverse outcomes in PE and provides potential targets for future interventions.
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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".