Microvascular endothelial cells from preeclamptic women exhibit altered expression of angiogenic and vasopressor factors
Bibliographic record
Abstract
Preeclampsia (PE) is a severe complication of pregnancy associated with maternal and fetal morbidity and mortality. The underlying pathophysiology involves maternal systemic vascular and endothelial dysfunction associated with circulating antiangiogenic factors, although the specific etiology of the disease remains elusive. Our aim was to investigate the maternal endothelium in PE by exploring the expression of genes involved with endothelial function in a novel platform of maternal primary endothelial cells. Adipose tissue was sampled at the time of caesarean section from both normal and preeclamptic patients. Maternal microvascular endothelial cells were isolated by tissue digestion and CD31 magnetic Dynabeads. Cell purity was confirmed by immunofluorescence microscopy and flow cytometry. Western analyses revealed VEGF activation of VEGF receptor 2 (VEGFR2) and ERK in primary cells. Quantitative PCR analyses revealed significantly altered mRNA levels of various genes involved with angiogenesis and blood pressure control in preeclamptic cells, including soluble fms-like tyrosine kinase-1, endoglin, VEGFR2, angiotensin receptor 1, and endothelin compared with cells isolated from normal pregnancies. Overall, maternal endothelial cells from preeclamptic patients exhibit extensive alteration of expression of factors associated with antiangiogenic and vasoconstrictive phenotypes, shedding light on the underlying mechanisms associated with the vascular dysfunction characteristic of 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 | 0.000 |
| 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".