A High Cholesterol Diet During Late Pregnancy Impairs Long-Term Maternal Vascular Function in Mice
Bibliographic record
Abstract
BACKGROUND: Gestational dyslipidemia is associated with pregnancy complications including preeclampsia. However, whether gestational dyslipidemia leads postpartum vascular dysfunction, which could increase the risk for cardiovascular complications later in life, is not known. Here, we aimed to determine whether a gestational dyslipidemia affects postpartum vascular health and induces early signs of atherosclerosis. METHODS: Pregnant C57BL/6 mice received a high cholesterol diet or control diet from gestational day 13.5 until term. After delivery, all mice received the control diet for ≈3 months postpartum (PP). Age-matched nulliparous females were on the same diets for equal periods. After 3 months, all mice were euthanized, serum was collected, and aortas were isolated to assess vascular function (wire myography) and markers of oxidative stress and early atherosclerosis. RESULTS: PP-high cholesterol diet females had increased circulating cholesterol levels compared with PP-control diet mice, without effect of the diet in nulliparous mice. Methacholine-induced vasodilation was impaired, and nitric oxide contribution reduced, by the high cholesterol diet in aortas of PP mice, but not in nulliparous mice. Exposure to oxidized low-density-protein cholesterol further impaired methylcholine-induced vasodilation in PP-high cholesterol diet aortas only. Compared with PP-control diet mice, aortic inducible nitric oxide synthase expression, reactive oxygen species and nitrotyrosine levels were increased in aortas from PP-high cholesterol diet mice. No differences in aortic lipid deposition and macrophage infiltration were found. CONCLUSIONS: Exposure to a high cholesterol diet in pregnancy impairs vascular function postpartum. Our results support the hypothesis that gestational dyslipidemia impacts maternal vascular function after pregnancy, which could potentially predispose these women to future cardiovascular complications.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".