Recent human ventricular cell action potential models under varied ischaemic conditions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Investigating arrhythmic mechanisms during ischaemia is essential to improve clinical therapy. However, experimental data in human is scarce. Computational models are an essential tool for bridging this gap. Recent human ventricular cell action potential (AP) models have been built with data from healthy cells, thus their applicability to studies of ischaemia is mostly unknown. We have carried out a simulation study in single cell and tissue under normal and varied ischaemic conditions using 4 recent human models: ten Tusscher et al. 2006 (TP06), Grandi et al. 2010 (GPB), Carro et al. 2011 (CRLP), and O'hara et al. 2011 (ORd). We varied two parameters that play an important role in arrhythmogenesis during ischaemia: extracellular potassium concentration ([K+]o) and peak conductance of the ATP-sensitive inward-rectifying potassium current (IK(ATP)). To assess the applicability of these models to simulate ischaemia, we calculated AP duration (APD) and post-repolarisation refractoriness (PRR), biomarkers of arrhythmic risk. Results show that all models displayed the expected APD shortening due to IK(ATP) activation and hyperkalaemia. Furthermore, all models, apart from the ORd, reproduced an increase in PRR. The GPB did not show propagation of excitation for [K+]o=9mM. This study suggests that the CRLP and TP06 models are the most suitable for performing human-specific simulations of arrhythmogenesis during myocardial ischaemia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it