Endothelial expression of endoglin in normocholesterolemic and hypercholesterolemic C57BL/6J mice before and after atorvastatin treatment
Bibliographic record
Abstract
Endoglin (CD105) is a homodimeric transmembrane glycoprotein strongly related to transforming growth factor (TGF)-beta signaling and many pathological states. In this study, we wanted to evaluate whether endoglin is expressed in normocholesterolemic and hypercholesterolemic C57BL/6J mice as well as whether it is affected by atorvastatin treatment in these mice. C57BL/6J mice were fed with chow diet or an atherogenic diet for 12 weeks after weaning. In 2 atorvastatin-treated groups, mice were fed the same diets (chow or atherogenic) as described above except atorvastatin was added at the dosage of 10 mg x kg(-1) x day(-1) for the last 8 weeks before euthanasia. Biochemical analysis of blood samples revealed that administration of atherogenic diet significantly increased levels of total cholesterol, VLDL, LDL, and decreased levels of HDL. Atorvastatin treatment resulted in a significant decrease in total cholesterol and VLDL only in mice fed by atherogenic diet. Quantitative stereological analysis revealed that atorvastatin significantly decreased endothelial expression of endoglin in C57BL/6J mice fed the atherogenic diet. In conclusion, we demonstrated that endothelial expression of endoglin is upregulated by hypercholesterolemia and decreased by the hypolipidemic effect of atorvastatin in C57BL/6J mice, suggesting that endoglin expression could be involved in atherogenesis.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".