Protein kinases modulate store-operated channels in pulmonary artery smooth muscle cells
Bibliographic record
Abstract
BACKGROUND: This study investigates whether protein kinase G (PKG), protein kinase A (PKA) and protein kinase C (PKC) are involved in the regulatory mechanisms of store-operated channel (SOC) in pulmonary arteries. METHODS: Pulmonary artery smooth muscle cells (PASMCs) were enzymatically dissociated from rat intralobar pulmonary arteries. Whole cell, cell-attached and inside-out patch-clamp electrophysiology were used to monitor SOCs in isolated PASMCs. RESULTS: Initially the Ca2+-ATPase inhibitor cyclopiazonic acid (CPA, 10 μM) initiated a whole cell current that was reduced by the SOC blocker SKF-96365 (10 μM). Subsequent work using both cell-attached and whole cell configurations revealed that the PKG and PKA inhibitors, KT5823 (3 μM) and H-89 (10 μM), also stimulated SOC activity; this augmentation was attenuated by the SOC blockers SKF-96365 (10 μM) and Ni2+ (0.1 mM). Finally using the inside-out configuration, the PKC activator phorbol 12-myristate 13-acetate (PMA, 10 μM) was confirmed to modestly stimulate SOC activity although this augmentation appeared to be more substantial following the application of 10 μM inositol 1,4,5-triphosphate (Ins(1,4,5)P3). CONCLUSIONS: SOC activity in PASMCs was stimulated by the inhibition of PKG and PKA and the activation of PKC. Our findings suggest that the SOC could be a substrate of these protein kinases, which therefore would regulate the intracellular concentration of calcium and pulmonary arteriopathy via SOC.
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".