Uterine perivascular adipose tissue is a novel mediator of uterine artery blood flow and reactivity in rat pregnancy
Bibliographic record
Abstract
KEY POINTS: In vivo, uterine perivascular adipose tissue (PVAT) potentiates uterine artery blood flow in pregnant rats, although not in non-pregnant rats. In isolated preparations, uterine PVAT has pro-contractile and anti-dilatory effects on uterine arteries. Pregnancy induces changes in uterine arteries that makes them responsive to uterine PVAT signalling. ABSTRACT: An increase in uterine artery blood flow (UtBF) is a common and necessary feature of a healthy pregnancy. In the present study, we tested the hypothesis that adipose tissue surrounding uterine arteries (uterine perivascular adipose tissue; PVAT) is a novel local mediator of UtBF and uterine artery tone during pregnancy. In vivo experiments in anaesthetized Sprague-Dawley rats showed that pregnant animals (gestational day 16, term = 22--23 days) had a three-fold higher UtBF compared to non-pregnant animals. Surgical removal of uterine PVAT reduced UtBF only in pregnant rats. In a series of ex vivo bioassays, we demonstrated that uterine PVAT had pro-contractile and anti-dilatory effects on rat uterine arteries. In the presence of PVAT-conditioned media, isolated uterine arteries from both pregnant and non-pregnant rats had reduced vasodilatory responses. In non-pregnant rats, these responses were mediated at the level of uterine vascular smooth muscle, whereas, in pregnant rats, PVAT-media reduced endothelium-dependent relaxation. Pregnancy increased adipocyte size in ovarian adipose tissue but had no effect on uterine PVAT adipocyte morphology. In addition, pregnancy down-regulated the gene expression of metabolic adipokines in uterine but not in aortic PVAT. In conclusion, this is the first study to demonstrate that uterine PVAT plays a regulatory role in UtBF, at least in part, as a result of its actions on uterine artery tone. We propose that the interaction between the uterine vascular wall and its adjacent adipose tissue may provide new insights for interventions in pregnancies with adipose tissue dysfunction and abnormal UtBF.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".