Changes in cardiac structure in hypertension produced by placental ischemia in pregnant rats: effect of tumor necrosis factor blockade
Bibliographic record
Abstract
OBJECTIVES: Chronic reduction of uteroplacental perfusion pressure (RUPP) in pregnant rats leads to placental ischemia, maternal endothelial cell dysfunction, hypertension and elevated levels of tumor necrosis factor-alpha (TNF-α). In this study we investigated the hypothesis that placental ischemia in pregnant rat, a model of preeclampsia, stimulates cardiac hypertrophy and fibrosis via a TNF-α-dependent mechanism. METHODS: Normal pregnant Sprague-Dawley rats and RUPP rats were evaluated on day 19 of gestation. To test the role of TNF-α in mediating change in the RUPP rat heart, a TNF-α inhibitor, etanercept, was administered on day 18 of gestation at a dose of 0.8 mg/kg, s.c. RESULTS: In comparison to normal pregnant rats, RUPP animals display enlarged cardiomyocytes, microvascular rarefaction, fibrosis, apoptosis as well as increased expression of markers of heart hypertrophy and fibrosis. Etanercept (E) treatment prevented enlargement of cardiomyocytes, fibrosis and apoptosis and this was accompanied by significantly lowered blood pressure in RUPP rats. Etanercept treatment lowered expression of mRNA for brain natriuretic peptide, a marker of cardiac hypertrophy. It also heightened expression of endothelial nitric oxide synthase and its phosphorylation as well as oxytocin receptor identified in cardiac microvessels. TNF-α inhibition prevented microvascular rarefaction in the heart as indicated by augmented CD31, a marker of angiogenesis. CONCLUSIONS: These results suggest that RUPP leads to microvascular rarefaction in the heart, exaggerated cardiomyocyte size, apoptosis, fibrosis, and the alteration of cardiac gene expression that are modulated by the inflammatory cytokine TNFα.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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".