The role of matrix metalloproteinases in vascular function: implications for normal pregnancy and pre‐eclampsia
Bibliographic record
Abstract
OBJECTIVES: (1) To investigate the effects of plasma from non-pregnant, normal pregnant and pre-eclamptic women on myogenic tone and endothelium-dependent relaxation; (2) To investigate the role of matrix metalloproteinases (MMPs) in these parameters of vascular function. DESIGN: Analysis of the effects of plasma from non-pregnant, normal pregnant and pre-eclamptic women on myogenic tone and endothelium-dependent relaxation, and the effects of MMP inhibition on these parameters. SETTING: University of Alberta, Edmonton, Alberta, Canada. SAMPLES: Pooled plasma from non-pregnant (n= 9), normal pregnant (n= 6) and pre-eclamptic women (n= 12). METHODS: Mesenteric arteries from virgin female C57BL/6J mice were exposed to pooled plasma from non-pregnant, normal pregnant and pre-eclamptic women in the absence and presence of GM6001 (5 microM; MMP inhibitor), and arterial function was assessed. MAIN OUTCOME MEASURES: Myogenic tone and endothelium-dependent relaxation. RESULTS: Plasma of women with pre-eclampsia, and interestingly, plasma of non-pregnant women, significantly enhanced myogenic tone at pressures > or =70 mmHg (P < 0.001) and blunted the maximum relaxation to methacholine (P < 0.001; P < 0.005) in isolated arteries. GM6001 altered response only in vessels exposed to the plasma of women with pre-eclampsia; however, contrary to our hypothesis, this further enhanced myogenic tone and further abrogated relaxation. CONCLUSIONS: The strikingly similar vascular function profiles of vessels incubated in the plasma of non-pregnant and pre-eclamptic women suggest that pre-eclampsia may be due, in part, to the lack of a necessary adaptation to pregnancy. Despite these similarities, however, there are differential effects of MMP inhibition, suggesting that MMPs play a greater role in the vasculature of women with pre-eclampsia compared with non-pregnant and normal pregnant women.
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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 | 0.001 |
| 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".