Mathematical Model of the Rapidly Activating Delayed Rectifier Potassium Current I<sub>Kr</sub> in Rabbit Sinoatrial Node
Bibliographic record
Abstract
INTRODUCTION: A rapidly activating delayed rectifier potassium current (I(Kr)) is known to have an important role in determining the properties of spontaneous pacing in enzymatically isolated rabbit sinoatrial node (SAN) cells. The functional characteristics of I(Kr) are conferred by its dependence on time, voltage, and external potassium. The aim of this study was to develop a rigorous mathematical representation for I(Kr) based on experimental findings and to investigate the role of I(Kr) in the automaticity and intercellular communication of SAN cells. METHODS AND RESULTS: A Markov model was developed using available experimental data for I(Kr) in rabbit SAN. The dependence of I(Kr) on external potassium, [K+]o, was incorporated using data from both in vitro preparations and results from heterologous expression experiments for this ether-a-go-go related gene product. Our simulation results show the following. (1) I(Kr) is the dominant repolarizing current in rabbit SAN cells. (2) Deactivation of I(Kr) contributes to the net current change during the early diastolic depolarization phase. (3) Inward rectification of I(Kr) results in a decrease in membrane resistance during repolarization relative to plateau. (4) The complex [K+]o dependence of I(Kr) confers [K+]o insensitivity on isolated cells, which may account for the sensitivity of pacing rate to elevated [K+]o at the tissue level. CONCLUSION: Model results show that I(Kr) mediates diastolic depolarization by the kinetics of its decay and by lowering resistance during late repolarization. In elevated [K+]o, increased chord conductance is balanced by the changes in kinetics and voltage dependence of I(Kr) so that the pacing rate of single cells may be more [K+]o insensitive than expected. In addition, elevated [K+]o increases I(Kr) magnitude during repolarization but lowers resistance, so current flow through gap junctions is less able to hyperpolarize pacing cells.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".