Calyculin A and Outward K+ Channel Currents in Rat Tail Artery Smooth Muscle Cells
Bibliographic record
Abstract
Protein dephosphorylation mediated by phosphatases represents an important mechanism for modulating the functions of the targeted proteins. Calyculin A has been extensively used as a specific inhibitor of protein phosphatases. However, the effect of calyculin A on K channel currents in vascular smooth muscle cells (SMCs) and the underlying mechanisms had been unknown. It was found in the current study that calyculin A inhibited the whole-cell outward K channel currents in rat tail artery SMCs in a concentration-dependent (median inhibitory concentration, 12.6 n ) and reversible fashion. The extracellular applied calyculin A induced a biphasic change in K current amplitude with an initial transient increase followed by a long-lasting inhibition (n = 6). The intracellularly applied calyculin A (100 nM ) caused a lesser inhibition (33 +/- 1%) of K channel currents than that caused by the extracellularly applied calyculin A (55.3 +/- 8% inhibition) and did not result in an initial increase in K channel currents. The inhibitory effect of the intracellularly applied calyculin A on K channel currents was reversed to a stimulatory effect after ATP was omitted from the intracellular solution. The K currents inhibited by calyculin A were conducted by the iberiotoxin-sensitive K channels in SMCs. Moreover, okadaic acid (0.03-3 microM ) did not cause any significant change in K(Ca) channel currents. In conclusion, calyculin A inhibited K(Ca) channel currents in vascular SMCs. This effect of calyculin A, however, was not mediated by the inhibition of protein phosphatases.
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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".