Docosahexaenoic Acid Monoacylglyceride Decreases Endothelin-1 Induced Ca2+ Sensitivity and Proliferation in Human Pulmonary Arteries
Bibliographic record
Abstract
BACKGROUND: Pulmonary artery vasoconstriction and vascular remodeling contribute to a sustained elevation of pulmonary vascular resistance and pressure in patients with pulmonary arterial hypertension (PH), an often fatal hemodynamic disease. The effect of docosahexaenoic acid monoacylglyceride (MAG-DHA) and the role of the 17 kDa protein kinase C-potentiated inhibitor protein (CPI-17) were determined on vasoconstriction and smooth muscle cell proliferation of human pulmonary arteries (HPA). METHODS: HPA were obtained from 16 patients undergoing lung resection for carcinoma. The mechanical tension and Ca(2+) sensitivity were measured on arterial rings treated with endothelin-1 (ET-1) in the absence or presence of MAG-DHA. The effect of MAG-DHA on the level of proliferation of smooth muscle cells isolated from HPA was evaluated in order to determine the role of CPI-17 protein. RESULTS: MAG-DHA treatment decreased the reactivity and Ca(2+) sensitivity induced by ET-1 in HPA. MAG-DHA treatment also decreased the expression of vascular endothelial growth factor (VEGF) induced by ET-1. Moreover, both VEGF inhibitor and MAG-DHA treatments reduced Ca(2+) hypersensitivity induced by ET-1, which was associated to a reduction in CPI-17 and myosin-binding subunit of the myosin light chain phosphatase (MYPT-1) phosphorylation levels. Proliferation of ET-1-stimulated HPA smooth muscle cells (PASMc) was also decreased following CPI-17 small interfering RNA transfection and MAG-DHA treatments. Western blot analyses revealed that MAG-DHA treatment resulted in decreased phosphorylation levels of CPI-17 and extracellular signal-regulated kinases (ERK) in PASMc treated with ET-1. CONCLUSIONS: We have demonstrated that VEGF interacts with CPI-17 signaling pathway resulting in an increase in Ca(2+) sensitivity and proliferation of PASMc, whereas MAG-DHA treatment reversed these effects.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".