The influence of prenatal exercise and pre-eclampsia on maternal vascular function
Bibliographic record
Abstract
During healthy pregnancy, the cardiovascular system undergoes diverse adaptations to support adequate transfer of oxygen and nutrients from mother to fetus. In order to accommodate the large expansion of blood volume and associated cardiac output, the structure, mechanics, and function of the arteries are altered. Specifically, in healthy pregnancy there is a remodeling of arteries (increased angiogenesis and vasodilation), a generalized reduction in arterial stiffness (increased compliance), and an enhanced endothelial function. The development of pregnancy complications, specifically pre-eclampsia, is associated with poor placentation (decreased angiogenesis), increased arterial stiffness, and vascular dysfunction (reduced endothelial function). Many of the positive adaptations that occur in healthy pregnancy are enhanced in response to chronic exercise. Specifically, placental angiogenesis and endothelial function have been shown to improve to a greater extent in women who are active during their pregnancy compared with those who are not. Prenatal exercise may be important in helping to reduce the risk of vascular dysfunction in pregnancy. However, our knowledge of the vascular adaptations resulting from maternal exercise is limited. This review highlights maternal vascular adaptations occurring during healthy pregnancy, and contrasts the vascular maladaptation associated with pre-eclampsia. Finally, we discuss the role of prenatal exercise on vascular function in the potential prevention of vascular complications associated with pre-eclampsia.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".