Dynamic of Ion Channel Expression at the Plasma Membrane of Cardiomyocytes
Bibliographic record
Abstract
Cardiac myocytes are characterized by distinct structural and functional entities involved in the generation and transmission of the action potential and the excitation-contraction coupling process. Key to their function is the specific organization of ion channels and transporters to and within distinct membrane domains, which supports the anisotropic propagation of the depolarization wave. This review addresses the current knowledge on the molecular actors regulating the distinct trafficking and targeting mechanisms of ion channels in the highly polarized cardiac myocyte. In addition to ubiquitous mechanisms shared by other excitable cells, cardiac myocytes show unique specialization, illustrated by the molecular organization of myocyte-myocyte contacts, e.g., the intercalated disc and the gap junction. Many factors contribute to the specialization of the cardiac sarcolemma and the functional expression of cardiac ion channels, including various anchoring proteins, motors, small GTPases, membrane lipids, and cholesterol. The discovery of genetic defects in some of these actors, leading to complex cardiac disorders, emphasizes the importance of trafficking and targeting of ion channels to cardiac function. A major challenge in the field is to understand how these and other actors work together in intact myocytes to fine-tune ion channel expression and control cardiac excitability.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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".