ArticleJournal of the Royal Society, Interface2017
Modelling variability in cardiac electrophysiology: a moment-matching approach.
Article in Journal of the Royal Society, Interface, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Cellular heterogeneity and repolarisation across the atria: an in silico study.Medical & biological engineering & computing · 2022Article
- Brain physiome: A concept bridgingBioactive materials · 2022Review
- Bayesian Calibration of Electrophysiology Models Using Restitution Curve Emulators.Frontiers in physiology · 2021Article
- Order Through Disorder: The Characteristic Variability of Systems.Frontiers in cell and developmental biology · 2020Review
- Mechanisms Underlying Interactions Between Low-Frequency Oscillations and Beat-to-Beat Variability of Celullar Ventricular Repolarization in Response to Sympathetic Stimulation: Implications for Arrhythmogenesis.Frontiers in physiology · 2019Article
- Unlocking data sets by calibrating populations of models to data density: A study in atrial electrophysiology.Science advances · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
The variability observed in action potential (AP) cardiomyocyte measurements is the consequence of many different sources of randomness. Often ignored, this variability may be studied to gain insight into the cell ionic properties. In this paper, we focus on the study of ionic channel conductances and describe a methodology to estimate their probability density function (PDF) from AP recordings. The method relies on the matching of observable statistical moments and on the maximum entropy principle. We present four case studies using synthetic and sets of experimental AP measurements from human and canine cardiomyocytes. In each case, the proposed methodology is applied to infer the PDF of key conductances from the exhibited variability. The estimated PDFs are discussed and, when possible, compared to the true distributions. We conclude that it is possible to extract relevant information from the variability in AP measurements and discuss the limitations and possible implications of the proposed approach.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.