Syntaxin-1A Actions on Sulfonylurea Receptor 2A Can Block Acidic pH-induced Cardiac KATP Channel Activation
Bibliographic record
Abstract
During cardiac ischemia, ATP stores are depleted, and cardiomyocyte intracellular pH lowers to <7.0. The acidic pH acts on the Kir6.2 subunit of K(ATP) channels to reduce its sensitivity to ATP, causing channel opening. We recently reported that syntaxin-1A (Syn-1A) binds nucleotide binding folds (NBF)-1 and NBF2 of sulfonylurea receptor 2A (SUR2A) to inhibit channel activity (Kang, Y., Leung, Y. M., Manning-Fox, J. E., Xia, F., Xie, H., Sheu, L., Tsushima, R. G., Light, P. E., and Gaisano, H. Y. (2004) J. Biol. Chem. 279, 47125-47131). Here, we examined Syn-1A actions on SUR2A to influence the pH regulation of cardiac K(ATP) channels. K(ATP) channel currents from inside-out patches excised from Kir6.2/SUR2A expressing HEK293 cells and freshly isolated cardiac myocytes were increased by reducing intracellular pH from 7.4 to 6.8, which could be blocked by increasing concentrations of Syn-1A added to the cytoplasmic surface. Syn-1A had no effect on C-terminal truncated Kir6.2 (Kir6.2-deltaC26) channels expressed in TSA cells without the SUR subunit. In vitro binding and co-immunoprecipitation studies show that Syn-1A binding to SUR2A or its NBF-1 and NBF-2 domain proteins increased progressively as pH was reduced from 7.4 to 6.0. The enhancement of Syn-1A binding to SUR2A by acidic pH was further regulated by Mg2+ and ATP. Therefore, pH regulates Kir.6.2/SUR2A channels not only by its direct actions on the Kir6.2 subunit but also by modulation of Syn-1A binding to SUR2A. The increased Syn-1A binding to the SUR2A at acidic pH would assert some inhibition of the K(ATP) channels, which may serve as a "brake" to temper the fluctuation of low pH-induced K(ATP) channel opening that could induce fatal reentrant arrhythmias.
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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".