Differential participation of protein kinase C and Rho kinase in α<sub>1</sub>-adrenoceptor mediated contraction in rat arteries
Bibliographic record
Abstract
The major functional alpha1-adrenoceptor in the rat aorta is of the alpha1Dsubtype and that in the caudal artery is of the alpha1A subtype. In the present study, the participation of protein kinase C (PKC) and Rho kinase (RhoK) in contractile responses to stimulation of the alpha1-adrenoceptors in these two arteries was investigated. Both the PKC inhibitor Ro-318220 and the RhoK inhibitor Y-27632 significantly blocked contractile responses of the aorta to phenylephrine (PE) and the selective alpha1A-adrenoceptor agonist A61603. When used in combination, the inhibitors had an additive blocking effect. In the caudal artery, Y-27632 but not Ro-318220 inhibited contractile responses to PE and A61603, and, in combination, the antagonism produced was no greater than that by Y-27632 alone. Contractile responses to direct activation of PKC with phorbol 12,13-dibutyrate were much smaller and levels of CPI-17 (PKC-activated protein phosphatase inhibitor of 17 kDa) were much lower in the caudal artery than the aorta. The results suggest that both PKC and RhoK contribute independently to contractile responses to stimulation of alpha1D-adrenoceptors in the aorta. However, RhoK, but not PKC, participates in contractile responses to stimulation of alpha1A-adrenoceptors in the caudal artery. This difference may largely be due to differences between the two arteries in the extent to which PKC participates in contraction.
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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".