Specific phosphorylation sites underlie the stimulation of a large conductance, Ca <sup>2+</sup> ‐activated K <sup>+</sup> channel by cGMP‐dependent protein kinase
Bibliographic record
Abstract
Smooth muscle contractility and neuronal excitability are regulated by large conductance, Ca(2+)-activated K(+) (BKCa) channels, the activity of which can be increased after modulation by type I cGMP-dependent protein kinase (cGKI) via nitric oxide (NO)/cGMP signaling. Our study focused on identifying key phosphorylation sites within the BKCa channel underlying functional enhancement of channel activity by cGKI. BKCa channel phosphorylation by cGKIα was characterized biochemically using radiolabeled ATP, and regulation of channel activity by NO/cGMP signaling was quantified in rat aortic A7r5 smooth muscle cells by cell-attached patch-clamp recording. Serine to alanine substitutions at 3 of 6 putative cGKI phosphorylation sites (Ser691, Ser873, and Ser1112) in the BKCa α subunit individually reduced direct channel phosphorylation by 25-60% and blocked BKCa activation by either an NO donor or a membrane-permeable cGMP by 80-100%. Acute inhibition of cGKI prevented stimulus-evoked enhancement of BKCa channel activity. Our data further suggest that augmentation of BKCa activity by NO/cGMP/cGKI signaling requires phosphorylation at all 3 sites and is independent of elevations in [Ca(2+)]i. Phosphorylation of 3 specific Ser residues within the murine BKCa α subunit by cGKIα accounts for the enhanced BKCa channel activity induced by elevated [cGMP]i in situ.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".