Kir6.2 Polymorphisms Sensitize β-Cell ATP-Sensitive Potassium Channels to Activation by Acyl CoAs
Bibliographic record
Abstract
The commonly occurring E23K and I337V Kir6.2 polymorphisms in the ATP-sensitive potassium (KATP) channel are more frequent in Caucasian type 2 diabetic populations. However, the underlying cellular mechanisms contributing to the pathogenesis of type 2 diabetes remain uncharacterized. Chronic elevation of plasma free fatty acids observed in obese and type 2 diabetic subjects leads to cytosolic accumulation of long-chain acyl CoAs (LC-CoAs) in pancreatic beta-cells. We postulated that the documented stimulatory effects of LC-CoAs on KATP channels might be enhanced in polymorphic KATP channels. Patch-clamp experiments were performed on inside-out patches containing recombinant KATP channels (Kir6.2/SUR1) to record macroscopic currents. KATP channels containing Kir6.2 (E23K/I337V) showed significantly increased activity in response to physiological palmitoyl-CoA concentrations (100-1,000 nmol/l) compared with wild-type KATP channels. At physiological intracellular ATP concentrations (mmol/l), E23K/I337V polymorphic KATP channels demonstrated significantly enhanced activity in response to palmitoyl-CoA. The observed increase in KATP channel activity may result in multiple defects in glucose homeostasis, including impaired insulin and glucagon-like peptide-1 secretion and increased glucagon release. In summary, these results suggest that the E23K/I337V polymorphism may have a diabetogenic effect via increased KATP channel activity in response to endogenous levels of LC-CoAs in tissues involved in the maintenance of glucose homeostasis.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".