Biophysical properties of slow potassium channels in human embryonic stem cell derived cardiomyocytes implicate subunit stoichiometry
Bibliographic record
Abstract
Human embryonic stem cells (hESCs) are an important cellular model for studying ion channel function in the context of a human cardiac cell and will provide a wealth of information about both heritable arrhythmias and acquired electrophysiological disorders. However, detailed electrophysiological characterization of the important cardiac ion channels has been so far overlooked. Because mutations in the gene for the I(Ks) α subunit, KCNQ1, constitute the majority of long QT syndrome (LQT-1) cases, we have carried out a detailed biophysical analysis of this channel expressed in hESCs to establish baseline I(Ks) channel biophysical properties in cardiac myocytes derived from hESCs (hESC-CMs). I(Ks) channels are heteromultimeric proteins consisting of four identical α-subunits (KCNQ1) assembled with auxiliary β-subunits (KCNE1). We found that the half-maximal I(Ks) activation voltage in hESC-CMs and in myocytes derived from human induced pluripotent stems cells (hiPSC-CMs) falls between that of KCNQ1 channels expressed alone and with full complement of KCNE1, the major KCNE subunit expressed in hESC-CMs as shown by qPCR analysis. Overexpression of KCNE1 by transfection of hESC-CMs markedly shifted and slowed native I(Ks) activation implying assembly of additional KCNE1 subunits with endogenous channels. Our results in hESC-CMs, which indicate an I(Ks) subunit stoichiometry that can be altered by variable KCNE1 expression, suggest the possibility for variable I(Ks) function in the developing heart, in different tissues in the heart, and in disease. This establishes a new baseline for I(Ks) channel properties in myocytes derived from pluripotent stem cells and will guide future studies in patient-specific hiPSCs.
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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 | 0.000 |
| 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".