Angiogenic imbalance and plasma lipid alterations in women with preeclampsia from a developing country
Bibliographic record
Abstract
BACKGROUND: An imbalance between anti-angiogenic factors (e.g. soluble vascular endothelial growth factor receptor-1 (s-FLT1) and soluble endoglin (s-Eng)) and pro-angiogenic factors (e.g. placental growth factor (PlGF)) as well as increased oxidized low-density lipoprotein (ox-LDL) concentrations have been associated with preeclampsia (PE). Risk factors associated with the development of PE, however, are known to be different between developed and developing countries. The aim of the study was to determine the levels of s-FLT1, s-Eng, PIGF, and ox-LDL in women with PE from a developing country. METHODS: A multi-center case-control study was conducted. One hundred and forty three women with PE were matched by age and parity with 143 healthy pregnant women without cardiovascular or endocrine diseases. Before delivery, blood samples were taken and serum was stored until analysis. RESULTS: Women with PE had lower concentrations of PIGF (p<0.0001) and higher concentrations of s-Eng (p=0.001) than healthy pregnant women. There were no differences between the groups regarding ox-LDL or s-FLT1. Women with early onset PE had higher s-FLT1 concentrations (p=0.0004) and lower PIGF concentrations (p<0.0001) than their healthy pregnant controls. Women with late onset PE had higher concentrations of s-Eng (p=0.005). Women with severe PE had higher concentrations of s-Eng (p=0.0008) and ox-LDL (p=0.01), and lower concentrations of PIGF (p<0.0001). CONCLUSIONS: Women with PE from a developing country demonstrated an angiogenic imbalance and an increased rate of LDL oxidation. Findings from this study support the theory that PE is a multifactorial disease, and understanding differences in these subpopulations may provide a better target to approach future therapies.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".