Identification and Pharmacological Characterization of Sarcolemmal ATP-Sensitive Potassium Channels in the Murine Atrial HL-1 Cell Line
Bibliographic record
Abstract
Activation of ATP-sensitive potassium (KATP) channels is known to have cardioprotective effects during periods of ischemia and reperfusion, making these channels important targets for clinical drug discovery. Using electrophysiological techniques we identify KATP channels in a mouse atrial cell line (HL-1). HL-1 KATP channels exhibited a concentration-dependent inhibition by ATP (IC50 = 23.3 +/- 3.2 microM), a unitary single-channel conductance of 55 pS, and sensitivity to the isoform-specific KATP channel opener P1075 and inhibitor HMR1098. Adenoviral infection of a dominant-negative Kir6.2 subunit significantly reduced the P1075-sensitive sarcKATP current. Taken together, the data indicate that HL-1 KATP channels are composed of sulfonylurea receptor isoform SUR2A coupled to the pore-forming Kir6.2 subunit--the molecular makeup of sarcKATP channels found in native cardiac myocytes. Pharmacological activation of HL-1 cell KATP channels also resulted in action potential shortening. Using the membrane potential-sensitive dye DiBac4(3), we demonstrated that the sarcKATP channel opener P1075 (20 microM) produced a concentration-dependent hyperpolarization of a monolayer of HL-1 cells that could be reversed by channel inhibition with HMR1098 (20 microM). We conclude that the HL-1 cells are an excellent cell line for studying cardiac sarcKATP channels, and these cells may also provide an important tool for the testing of novel pharmacological modulators of KATP channels in fluorescence-based assays.
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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 | 0.001 |
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".