ATP-sensitive potassium channels participate in glucose uptake in skeletal muscle and adipose tissue
Bibliographic record
Abstract
ATP-sensitive potassium (K(ATP)) channels are known to be critical in the control of both insulin and glucagon secretion, the major hormones in the maintenance of glucose homeostasis. The involvement of K(ATP) channels in glucose uptake in the target tissues of insulin, however, is not known. We show here that Kir6.2(-/-) mice lacking Kir6.2, the pore-forming subunit of these channels, have no K(ATP) channel activity in their skeletal muscles. A 2-deoxy-[(3)H]glucose uptake experiment in vivo showed that the basal and insulin-stimulated glucose uptake in skeletal muscles and adipose tissues of Kir6.2(-/-) mice is enhanced compared with that in wild-type (WT) mice. In addition, in vitro measurement of glucose uptake indicates that disruption of the channel increases the basal glucose uptake in Kir6.2(-/-) extensor digitorum longus and the insulin-stimulated glucose uptake in Kir6.2(-/-) soleus muscle. In contrast, glucose uptake in adipose tissue, measured in vitro, was similar in Kir6.2(-/-) and WT mice, suggesting that the increase in glucose uptake in Kir6.2(-/-) adipocytes is mediated by altered extracellular hormonal or neuronal signals altered by disruption of the K(ATP) channels.
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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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".