Improved bioavailability of epoxyeicosatrienoic acids reduces TP-receptor agonist-induced tension in human bronchi
Bibliographic record
Abstract
Epoxyeicosatrienoic acid (EET) and thromboxane A(2) are arachidonic acid derivatives. The former has initially been defined as an epithelium-derived hyperpolarizing factor displaying broncho-relaxing and anti-inflammatory properties, as recently demonstrated, whereas thromboxane A(2) induces vaso- and bronchoconstriction upon binding to thromboxane-prostanoid (TP)-receptor. EETs, however, are quickly degraded by the soluble epoxide hydrolase (sEH) into inactive diol compounds. The aim of this study was to investigate the effects of 14,15-EET on TP-receptor activation in human bronchi. Tension measurements performed on native bronchi from various species, acutely treated with increasing 14,15-EET concentrations, revealed specific and concentration-dependent relationships as well as a decrease in the tension induced by 30 nM U-46619, used as a synthetic TP-receptor agonist. Interestingly, acute treatments with 3 μM N-(methylsulfonyl)-2-(2-propynyloxy)-benzenehexanamide, an epoxygenase inhibitor, which minimizes endogenous production of EET, resulted in an increased reactivity to U-46619. Furthermore, we demonstrated that chronic treatments with trans-4-[4-(3-adamantan-1-yl-ureido)-cyclohexyloxy]-benzoic acid (t-AUCB), a sEH inhibitor, reduced human bronchi reactivity to U-46619. During our tension measurements, we also observed that human bronchi generated small-amplitude contractions; these spontaneous activities were reduced upon acute 14,15-EET treatments in the presence of t-AUCB. Altogether, these data demonstrate that endogenous and exogenous 14,15-EET could interfere with the activation of TP-receptors as well as with spontaneous oscillations in human airway smooth muscle tissues.
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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) | 0.001 | 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".