Bradykinin stimulates ceramide production by activating specific BK-B<sub>1</sub>receptor in rat small artery
Bibliographic record
Abstract
Bradykinin (BK), a proinflammatory factor and vasodilator, causes functional change of the small artery. However, it is not clear whether any of these changes induced by BK are mediated by N-acetyl-D-sphingosine (ceramide). Therefore, we investigated whether BK affects the hydrolysis of sphingomyelin and generation of ceramide in the intact rat small artery. Our results suggest that BK induces sphingomyelin hydrolysis and increases ceramide production in a time- and dose-dependent manner. Relative to controls, BK causes a 50% decrease in sphingomyelin levels. Ceramide levels increase in response to BK with the highest level being obtained with 10(-8) M BK as well as similar amounts of ceramide are generated when exogenous sphingomyelinase (SMase) is added. We then determined which of the two BK receptors (BK-B(1) antagonist Lys-Des-Arg(9)-Leu(8)-BK or the BK-B(2) antagonist HOE-140) are implicated in the BK-induced generation of ceramide. The BK-B(2) antagonist did not alter the effect of BK on ceramide generation, whereas the BK-B(1) antagonist blocked the BK-induced production of ceramide. Although ceramide had no effect on KCl-induced constrictions, ceramide dilated preconstricted (phenylephrine) small pressurized rat mesenteric arteries by approximately 40%. These results suggest that the activation of the BK-B(1) receptor mediates the BK-induced activation of SMase and of the production of ceramide. In conclusion, BK-mediated effects on vascular tone may be due, at least in part, to the increased production of ceramide.
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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) | 0.001 | 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".