Evidence map›Paper›PMID 39539954›Full record

ArticleFrontiers in physiology2024

CardioMEA: comprehensive data analysis platform for studying cardiac diseases and drug responses.

Jihyun Lee, Eliane Duperrex, Ibrahim El-Battrawy, Alyssa Hohn, Ardan M Saguner, Firat Duru, Vishalini Emmenegger, Lukas Cyganek, Andreas Hierlemann, Hasan Ulusan

Abstract read
In one paragraph

Article in Frontiers in physiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

10 authors.

Jihyun LeeDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Eliane DuperrexDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Ibrahim El-BattrawySt. Josef Hospital, Ruhr-University Bochum, Bochum, Germany.
Alyssa HohnGerman Center for Cardiovascular Research, Partner Site Heidelberg-Mannheim and Göttingen, Heidelberg, Germany.
Ardan M SagunerDepartment of Cardiology, Electrophysiology Division, University Heart Center Zurich, Zurich, Switzerland.
Firat DuruDepartment of Cardiology, Electrophysiology Division, University Heart Center Zurich, Zurich, Switzerland.
Vishalini EmmeneggerDepartment of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Lukas CyganekGerman Center for Cardiovascular Research, Partner Site Heidelberg-Mannheim and Göttingen, Heidelberg, Germany.
Andreas Hierlemann *Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
Hasan Ulusan *Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: In recent years, high-density microelectrode arrays (HD-MEAs) have emerged as a valuable tool in preclinical research for characterizing the electrophysiology of human induced pluripotent stem-cell-derived cardiomyocytes (iPSC-CMs). HD-MEAs enable the capturing of both extracellular and intracellular signals on a large scale, while minimizing potential damage to the cell. However, despite technological advancements of HD-MEAs, there is a lack of effective data-analysis platforms that are capable of processing and analyzing the data, particularly in the context of cardiac arrhythmias and drug testing. Methods: To address this need, we introduce CardioMEA, a comprehensive data-analysis platform designed specifically for HD-MEA data that have been obtained from iPSCCMs. CardioMEA features scalable data processing pipelines and an interactive web-based dashboard for advanced visualization and analysis. In addition to its core functionalities, CardioMEA incorporates modules designed to discern crucial electrophysiological features between diseased and healthy iPSC-CMs. Notably, CardioMEA has the unique capability to analyze both extracellular and intracellular signals, thereby facilitating customized analyses for specific research tasks. Results and discussion: We demonstrate the practical application of CardioMEA by analyzing electrophysiological signals from iPSC-CM cultures exposed to seven antiarrhythmic drugs. CardioMEA holds great potential as an intuitive, userfriendly platform for studying cardiac diseases and assessing drug effects.

Indexed as

antiarrhythmic drugcardiac arrhythmiainduced pluripotent stem cellmachine learningmicroelectrode array

Identifiers

PMID39539954
PMCPMC11557525

What OpenQuestion holds

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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.