19,20-EpDPE, a bioactive CYP450 metabolite of DHA monoacyglyceride, decreases Ca<sup>2+</sup>sensitivity in human pulmonary arteries
Bibliographic record
Abstract
The aim of this study was to investigate the effect of docosahexaenoic acid monoacylglyceride (MAG-DHA) on human pulmonary arterial tone. Tension measurements on pulmonary arterial tissues demonstrated that MAG-DHA reduced U-46619-induced tone, which is highly sensitive to the H-1152 inhibitor. Results also showed that MAG-DHA treatments decreased RhoA activity levels, which in turn inactivated the Rho-kinase pathway, leading to a reduction in U-46619-induced Ca(2+) sensitivity of permeabilized pulmonary artery smooth muscle cells. According to the mechanical responses assessing U-46619-induced Ca(2+) sensitivity in the absence or presence of 3 μM MAG-DHA, MAG-DHA plus 1 μM N-methylsulfonyl-6-(2-propargyloxyphenyl) hexanamide (MS-PPOH, a cytochrome P-450 epoxygenase inhibitor) and 300 nM 19,20-epoxydocosapentaenoic acid (a cytochrome P-450 epoxygenase-dependent DHA metabolite), our data suggest that the MAG-DHA is metabolized in a bioactive epoxymetabolite. This epoxyeicosanoid in turn decreases active tone and Ca(2+) sensitivity of smooth muscles cells through an inhibition of the Rho-kinase pathway. Together, these data provide primary evidence regarding the mode of action of MAG-DHA in human pulmonary arteries and suggest that this compound may be of pharmacological interest in patients with pulmonary hypertension to generate intracellular bioactive metabolites.
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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 | 0.000 |
| 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".