Abstract 638: Urotensin II Promotes Calcification in Vascular Smooth Muscle Cells
Bibliographic record
Abstract
Introduction: Atherosclerosis is a leading cause of death in Western societies. Vasoactive peptide urotensin II (UII) is upregulated in atherosclerosis and several other cardiovascular diseases however further research is required to develop a complete understanding of UII’s role in the pathogenesis of atherosclerosis. Hypothesis: We hypothesized that UII stimulates calcification in vascular smooth muscle cells and that UII, urotensin II related peptide (URP) and UT receptor expression are upregulated in calcified aortic valves. Methods and Results: Human aortic smooth muscle cells (HASMC) were cultured in phosphate media (2.6mmol/L) for 13 days in the presence of varying concentrations of UII (0, 10, 50, 100nm) and the amount of calcium was measured with a calcium assay kit. Protein was extracted and measured with a protein assay kit. HASMC calcification was assessed as the ratio of calcium (μg)/protein (mg). HASMC calcification increased with increasing UII concentration and was significantly elevated in 100nm of UII (N=6, P<0.05) 13 days after incubation. We also examined UII, URP and UT protein expression in 90 carotid endarterectomies and 87 mitral, non-calcified and calcified aortic valves by immunohistochemistry. Multivariant Spearman correlation analyses in carotids revealed significant positive correlations between UII, URP and UT overall staining with calcification, remodeling and inflammation (P<0.05). In valves there was significant positive correlations between UII, URP and UT overall staining with calcification, fibrosis, remodeling, inflammation, lipid score and microvessels (P<0.05). Conclusion: The stimulatory effect of UII on vascular smooth muscle cell calcification as well as the upregulated expression of UII, URP and UT in calcified aortic valves suggests that the UT receptor system plays a key role in the pathogenesis of atherosclerosis and valve calcification.
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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) | 0.000 | 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) | 0.005 | 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".