Effect of Pregnancy on Sympathetic and Peripheral Vascular Responses to the Cold Pressor Test
Bibliographic record
Abstract
Little is known regarding sympathetic neurovascular regulation during pregnancy. We hypothesized that, despite elevated muscle sympathetic nerve activity (MSNA; peroneal microneurography) in normotensive pregnant women (NP) versus non‐pregnant controls (CT), neurovascular transduction would be blunted in NP, resulting in similar mean arterial pressure (MAP) between groups. Integrated MSNA was obtained during 3 min of rest and 3 min of reflex sympathetic activation (cold pressor test; CPT). Total peripheral resistance (TPR; MAP/Q) and burst frequency (BF) were used to calculate neurovascular transduction (TPR/BF). CPT data were analyzed in 30s bins; the bin corresponding to the highest BF value was selected for analysis. Baseline MAP and TPR were not different between NP vs CT (90±16 vs 90±5 mmHg, P =0.9 and 12±2 vs 13±2 mmHg/L/min, P =0.5, respectively) whereas BF (36±7 vs 24±2, P <0.01) and total MSNA (BF x normalized burst amplitude; 1743±286 vs 1145±191, P <0.01) were higher and neurovascular transduction lower (0.3±0.1 vs 0.5±0.1, P =0.01) in NP. During CPT, BF and total MSNA were higher in NP vs CT (56±17 vs 34±10, P =0.03; 2677±650 vs 1529±515, P =0.01), while no differences in MAP or TPR were observed between NP vs CT (99±24 vs 101±7, P =0.8; 13±4 vs 13±3, P =0.7). Neurovascular transduction during CPT was lower in NP than CT (0.24±0.10 vs 0.40±0.07, P =0.01), indicating a vascular adaptation to pregnancy. Supported by WCHRI, NSERC & University of Alberta Human Performance Scholarship Fund.
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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 | 0.000 | 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 | 0.001 |
| 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".