Relationship between bradykinin-induced relaxation and endogenous epoxyeicosanoid synthesis in human bronchi
Bibliographic record
Abstract
Epoxyeicosanoids (EETs) are produced by cytochrome P-450 epoxygenase; however, it is not yet known what triggers their endogenous production in epithelial cells. The relaxing effects of bradykinin are known to be related to endogenous production of epithelial-derived hyperpolarizing factors (EpDHF). Because of their effects on membrane potential, EETs have been reported to be EpDHF candidates (Benoit C, Renaudon B, Salvail D, Rousseau E. Am J Physiol Lung Cell Mol Physiol 280: L965-L973, 2001.). Thus, we hypothesized that bradykinin (BK) may stimulate endogenous EET production in human bronchi. To test this hypothesis, the relaxing and hyperpolarizing effects of BK and 14,15-EET were quantified on human bronchi, as well as the effects of various enzymatic inhibitors on these actions. One micromolar BK or 1 μM 14,15-EET induced a 45% relaxation on the tension induced by 30 nM U-46619 [a thromboxane-prostanoid (TP)-receptor agonist]. These BK-relaxing effects were reduced by 42% upon addition of 10 nM iberiotoxin [a large-conductance Ca(2+)-sensitive K(+) (BK(Ca)) channel blocker], by 27% following addition of 3 μM 14,15-epoxyeicosa-5(Z)-enoic acid (an EET antagonist), and by 32% with 3 μM N-methanesulfonyl-6-(2-propargyloxyphenyl)hexanamide (MS-PPOH, an epoxygenase inhibitor). Hence, BK and 14,15-EET display net hyperpolarizing effects on airway smooth muscle cells that are related to the activation of BK(Ca) channels and ultimately yielding to relaxation. Data also indicate that 3 μM MS-PPOH reduced the hyperpolarizing effects of BK by 43%. Together, the present data support the current hypothesis suggesting a direct relationship between BK and the production of EET regioisomers. Because of its potent anti-inflammatory and relaxing properties, epoxyeicosanoid signaling may represent a promising target in asthma and chronic obstructive pulmonary disease.
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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) | 0.002 | 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".