Site-Specific Increases in Utero- and Fetoplacental Arterial Vascular Resistance in eNOS-Deficient Mice Due to Impaired Arterial Enlargement1
Bibliographic record
Abstract
The sites of elevated vascular resistance that impede placental perfusion in pathological pregnancies are unknown. In the current study, we identified these sites in a knockout mouse model (eNOS(-/-)) with reduced uterine (-55%) and umbilical (-29%) artery blood flows caused by endothelial nitric oxide synthase deficiency. Uteroplacental and fetoplacental arterial vascular trees of pregnant mice near term were imaged using x-ray microcomputed tomography (n = 5-10 placentas from 3-5 dams/group). The resulting three-dimensional images were analyzed to assess vessel geometry and vascular resistance. In control and eNOS(-/-) trees, ∼90% of total uteroplacental vascular resistance was located in the radial arteries. Changes in eNOS(-/-) vessel geometry, including 30% reductions in uterine, radial, and spiral artery diameters, were calculated to increase arterial resistance downstream of the uterine artery by 2.3-fold, predicting a 57% decrease in uterine blood flow. Despite large reductions in eNOS(-/-) spiral arteries (-55% by volume) and maternal canals (-67% by volume), these vessels were relatively minor contributors to resistance. In the eNOS(-/-) fetoplacental tree, the number of arterioles (50-75 μm diameter) increased by 26%. Nevertheless, calculated resistance rose by 19%, predominantly because arteries near the periphery of the tree selectively exhibited a 7%-9% diameter reduction. We conclude that previously observed decreases in uterine and umbilical blood flows in eNOS(-/-) pregnancies are associated with markedly divergent structural changes in the uteroplacental versus fetoplacental circulations. Results showed the radial arteries were critical determinants of uteroplacental resistance in mice and therefore warrant greater attention in future studies in pathological human pregnancies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".