Evidence map›Paper›PMID 35053355›Full record

ArticleCells2022

Ion Channel Modeling beyond State of the Art: A Comparison with a System Theory-Based Model of the Shaker-Related Voltage-Gated Potassium Channel Kv1.1.

Sonja Langthaler, Jasmina Lozanović Šajić, Theresa Rienmüller, Seth H Weinberg, Christian Baumgartner

Abstract readComparative Study
In one paragraph

Article in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Sonja LangthalerInstitute of Health Care Engineering with European Testing Center for Medical Devices, Graz University of Technology, A-8010 Graz, Austria.ORCID 0000-0001-5160-4910
Jasmina Lozanović ŠajićInstitute of Health Care Engineering with European Testing Center for Medical Devices, Graz University of Technology, A-8010 Graz, Austria.ORCID 0000-0002-5717-4269
Theresa RienmüllerInstitute of Health Care Engineering with European Testing Center for Medical Devices, Graz University of Technology, A-8010 Graz, Austria.ORCID 0000-0002-9623-106X
Seth H WeinbergDepartment of Biomedical Engineering, The Ohio State University, Columbus, OH 43210, USA.ORCID 0000-0003-1170-0419
Christian BaumgartnerInstitute of Health Care Engineering with European Testing Center for Medical Devices, Graz University of Technology, A-8010 Graz, Austria.ORCID 0000-0002-3763-5195

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mathematical modeling of ion channel kinetics is an important tool for studying the electrophysiological mechanisms of the nerves, heart, or cancer, from a single cell to an organ. Common approaches use either a Hodgkin-Huxley (HH) or a hidden Markov model (HMM) description, depending on the level of detail of the functionality and structural changes of the underlying channel gating, and taking into account the computational effort for model simulations. Here, we introduce for the first time a novel system theory-based approach for ion channel modeling based on the concept of transfer function characterization, without a priori knowledge of the biological system, using patch clamp measurements. Using the shaker-related voltage-gated potassium channel Kv1.1 (KCNA1) as an example, we compare the established approaches, HH and HMM, with the system theory-based concept in terms of model accuracy, computational effort, the degree of electrophysiological interpretability, and methodological limitations. This highly data-driven modeling concept offers a new opportunity for the phenomenological kinetic modeling of ion channels, exhibiting exceptional accuracy and computational efficiency compared to the conventional methods. The method has a high potential to further improve the quality and computational performance of complex cell and organ model simulations, and could provide a valuable new tool in the field of next-generation in silico electrophysiology.

Indexed as

Models, BiologicalAnimalsComputer SimulationIon Channel GatingKv1.1 Potassium ChannelMarkov ChainsProtein SubunitsRatsKv1.1 Potassium ChannelProtein Subunitscomputational modelelectrophysiologyhidden Markov modelHodgkin–Huxleyion channelssystem and control theory

Identifiers

PMID35053355
PMCPMC8773569

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Registered trials

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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.