The sympathetic nervous system in healthy and hypertensive pregnancies: physiology or pathology?
Bibliographic record
Abstract
NEW FINDINGS: What is the topic of this review? Sympathoexcitation in both healthy and hypertensive pregnancies, and concurrent adaptations along the neurovascular cascade. What advances does it highlight? Known and plausible adaptations along the neurovascular cascade which may offset elevated MSNA in normotensive pregnancy while also highlighting knowledge gaps regarding understudied pathways. ABSTRACT: The progression from conception through to the postpartum period represents an extraordinary period of physiological adaptation in the mother to support the growth and development of the fetus. Healthy, normotensive human pregnancies are associated with striking increases in both plasma volume and sympathetic nerve activity, yet normal or reduced blood pressure; it represents a unique period of apparent healthy sympathetic hyperactivity. However, how this normal blood pressure is achieved in the face of sympathoexcitation, and the mechanisms responsible for this increased activity are unclear. Importantly, sympathetic activation has been implicated in hypertensive pregnancy disorders - the leading causes of maternal-fetal morbidity and mortality in the developed world. An understudied link between pregnancy and the development of maternal hypertension may lie in the sympathetic nervous system regulation of blood pressure. This brief review presents the latest data on sympathoexcitation in both healthy and hypertensive pregnancies, and concurrent adaptations along the neurovascular cascade.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".