Maternal vascular responses to hypoxia in a rat model of intrauterine growth restriction
Bibliographic record
Abstract
Intrauterine growth restriction (IUGR) is a common pregnancy complication and is a leading cause of fetal morbidity and mortality. Placental hypoxia contributes to adverse fetal consequences, such as IUGR. Exposing pregnant rats to hypoxia can lead to IUGR; however, assessment of maternal vascular function in a rat model of hypoxia, and the mechanisms that may contribute to adverse pregnancy outcomes, has not been extensively studied. We hypothesized that exposing pregnant rats to hypoxia will affect maternal systemic vascular function and increase the uterine artery resistance index (RI), which will be associated with IUGR. To test this hypothesis, pregnant rats were kept in normoxia (21% O2) or hypoxia (11% O2) from gestational day (GD) 6 to 20. Maternal blood pressure, uteroplacental resistance index (RI) (ultrasound biomicroscopy), and vascular function (wire myography) were assessed in uterine and mesenteric arteries. Fetal weight was significantly reduced ( P < 0.001), while maternal blood pressure was increased ( P < 0.05) in rats exposed to hypoxia. Maternal vascular function was also affected after exposure to hypoxia, including impaired endothelium-dependent vasodilation responses to methacholine in isolated uterine arteries (pEC50 normoxia: 6.55 ± 0.23 vs. hypoxia: 5.02 ± 0.35, P < 0.01) and a reduced uterine artery RI in vivo (normoxia: 0.63 ± 0.04 vs. hypoxia: 0.53 ± 0.01, P < 0.05); associated with an increase in umbilical vein RI (normoxia: 0.35 ± 0.02 vs. hypoxia: 0.45 ± 0.04, P < 0.05). These data demonstrate maternal and fetal alterations in vascular function due to prenatal exposure to hypoxia. Further, although there was a compensatory reduction in uterine artery RI in the hypoxia groups, this was not sufficient to prevent IUGR.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.002 |
| 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".