Nitric oxide/cGMP‐mediated regulation of a large conductance Ca‐activated K <sup>+</sup> (BK <sub>Ca</sub> ) channel via site‐specific phosphorylation
Bibliographic record
Abstract
Nitric oxide (NO) is a potent endogenous relaxing agent that decreases vascular smooth muscle tone. NO elevates cGMP, leading to activation of cGMP‐dependent protein kinase Iα (cGKIα) and phosphorylation of several targets, including the BK Ca channel. Phosphorylation of the BK Ca α subunit enhances channel opening, resulting in a greater membrane hyperpolarization, decreased calcium influx and smooth muscle relaxation. Mutagenesis studies have suggested possible sites of cGKIα‐dependent phosphorylation on the BK Ca α subunit, but these have yet to be directly confirmed biochemically. In order to independently identify sites of cGKIα‐induced phosphorylation, site‐specific BK Ca channel mutants were created and examined by in vitro phosphorylation. Antibodies raised against putative phosphorylation sites were produced and isolated to further characterize phosphorylation sites in situ . Results from cGKIα‐induced phosphorylation of site‐specific mutant BK Ca channels in vitro reveal two putative sites of phosphorylation within the cytosolic C‐terminus. Confirmation of these phosphorylation sites will help define the functional effects of phosphorylation on the channel, the overall vasorelaxation effect produced by NO and elucidate problems in vasorelaxation that may be observed in smooth muscle‐related disorders, such as hypertension, incontinence, and asthma. (Funded by CIHR)
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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 | 0.000 |
| 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".