Mechanisms of Uterine Artery Dysfunction in Pregnancy Complications
Bibliographic record
Abstract
Pregnancy is a unique condition, and the vascular processes that are required for this undertaking are both complex and extensive. In this review, we discuss the vascular adaptations which occur in the maternal uterine arterial bed to maintain blood supply to the fetal-placental unit. In complicated pregnancies, inadequate remodeling of the uterine arteries, hormonal imbalances, and pre-existing conditions such as obesity, hypertension, diabetes etc. may lead to maladaptations of the uterine vasculature that includes increased vasoconstriction and endothelial dysfunction. Ultimately, uterine artery dysfunction results in increased vascular resistance impeding blood flow to the fetal-placental unit and limiting fetal growth and development. A strong association exists between poor fetal development in utero and later life health issues, which can include obesity, poor neurological development, and enhanced susceptibility to cardiovascular disease. Therefore, the detrimental outcomes of a complicated pregnancy are far-reaching and significantly impact the health of the population as a whole. Many treatment options to improve maternal uterine artery function and ameliorate the impact on the fetus are being considered. A particular difficulty in treating complicated pregnancies is the presence of not 1 but (at least) 2 patients. Novel approaches are required to successfully improve pregnancy outcomes and minimize the impact on later life health.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".