Vascular gene expression in mice overexpressing human endothelin-1 targeted to the endothelium
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Bibliographic record
Abstract
Endothelin (ET)-1 plays an important pathophysiological role in several vascular diseases including hypertension and atherosclerosis. Transgenic mice overexpressing human preproET-1 selectively in the endothelium (eET-1) exhibit vascular injury in the absence of blood pressure elevation. ET-1 overexpression may induce vascular injury by inducing changes in gene expression. To understand mechanisms whereby ET-1 induces vascular damage, vascular gene expression profiling was performed using DNA microarrays. RNA from mesenteric arteries of male and female young (6-7 wk) and mature (6-8 mo) eET-1 and wild-type (WT) mice was isolated, and changes in gene expression were determined by genome-wide expression profiling using Illumina microarray and FlexArray software. Data were analyzed using a relaxed and a stringent statistical approach. The gene lists were compared and analyzed as well with Ingenuity Pathway Analysis. The most common change was an increase in the expression of lipid metabolism genes. Four of these genes were validated by qPCR, cyp51, dgat2, and scd1 genes in young and elovl6 in both young and mature male mice, supporting a role of ET-1 in atherosclerosis. To test the hypothesis that ET-1 participates in mechanisms leading to atherosclerosis, we crossed eET-1 with atherosclerosis-prone apoE(-/-) mice to determine whether ET-1 overexpression exacerbates high-fat diet (HFD)-induced atherosclerosis using oil red O staining of descending thoracic aorta. HFD increased lipid plaques by 3-, 27-, and 86-fold in eET-1, apoE(-/-), and crossed mice, respectively, vs. WT. This suggests that increased endothelial ET-1 expression results in early changes in gene expression in the vascular wall that enhance lipid biosynthesis and accelerate progression of atherosclerosis.
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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) | 0.000 | 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) | 0.000 | 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 it