Vascular inflammation in absence of blood pressure elevation in transgenic murine model overexpressing endothelin-1 in endothelial cells
Bibliographic record
Abstract
OBJECTIVE: We previously showed that in transgenic mice with endothelium-targeted overexpression of human preproendothelin-1, mesenteric resistance arteries exhibited vascular remodeling, endothelial dysfunction and increased oxidative stress early in life in the absence of significant elevation of blood pressure. To further characterize this model, the role of vascular inflammation was investigated in young male transgenic and wild-type littermate mice. METHODS AND RESULTS: Systemic and local inflammatory markers in mesenteric arteries were assessed by Luminex-based enzyme-linked immunosorbent assay technique, confocal microscopy, electrophoretic mobility shift assay and western blotting in 10-week old male transgenic and wild-type mice. Although no differences were found for systemic inflammatory markers, vascular staining for monocyte chemoattractant protein-1 and macrophage infiltration were significantly increased (P < 0.05) in transgenic mice compared with wild-type littermates. Transgenic mice exhibited significant increase (P < 0.01) in the activation of transcription factors activator protein-1 and nuclear factor kappa B compared with wild-type littermates. Western blotting analysis showed significantly increased (P < 0.05) blood vessel wall expression of vascular cell adhesion molecule-1 in transgenic mice. CONCLUSION: These findings suggest that in this murine model of endothelial cell-restricted preproendothelin-1 overexpression, endothelin-1 induces vascular inflammation by multiple pathways in young animals in the absence of blood pressure elevation or systemic inflammation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.001 | 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".