Kv4.3-Encoded Fast Transient Outward Current Is Presented in Kv4.2 Knockout Mouse Cardiomyocytes
Bibliographic record
Abstract
Gradients of the fast transient outward K+ current (Ito,f) contribute to heterogeneity of ventricular repolarization in a number of species. Cardiac Ito,f levels and gradients change notably with heart disease. Human cardiac Ito,f appears to be encoded by the Kv4.3 pore-forming α-subunit plus the auxiliary KChIP2 β-subunit while mouse cardiac Ito,f requires Kv4.2 and Kv4.3 α-subunits plus KChIP2. Regional differences in cardiac Ito,f are associated with expression differences in Kv4.2 and KChIP2. Although Ito,f was reported to be absent in mouse ventricular cardiomyocytes lacking the Kv4.2 gene (Kv4.2-/-) when short depolarizing voltage pulses were used to activate voltage-gated K+ currents, in the present study, we showed that the use of long depolarization steps revealed a heteropodatoxin-sensitive Ito,f (at ~40% of the wild-type levels). Immunohistological studies further demonstrated membrane expression of Kv4.3 in Kv4.2-/- cardiomyocytes. Transmural Ito,f gradients across the left ventricular wall were reduced by ~3.5-fold in Kv4.2-/- heart, compared to wild-type. The Ito,f gradient in Kv4.2-/- hearts was associated with gradients in KChIP2 mRNA expression while in wild-type there was also a gradient in Kv4.2 expression. In conclusion, we found that Kv4.3-based Ito,f exists in the absence of Kv4.2, although with a reduced transmural gradient. Kv4.2-/- mice may be a useful animal model for studying Kv4.3-based Ito,f as observed in humans.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".