Evidence map›Paper›PMID 27281718›Full record

ArticleComputers in biology and medicine2016

Automated detection and analysis of depolarization events in human cardiomyocytes using MaDEC.

Agnieszka F Szymanska, Christopher Heylman, Rupsa Datta, Enrico Gratton, Zoran Nenadic

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Computers in biology and medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.2field-weighted citation impact, top 45% of its field
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

0 citing papers in PubMed, 3 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 2 institutions in 1 country.

Agnieszka F SzymanskaDepartment of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA. Electronic address: aggie.szymanska@gmail.com.
Christopher HeylmanLaboratory for Fluorescence Dynamics, Department of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA.
Rupsa DattaLaboratory for Fluorescence Dynamics, Department of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA.
Enrico GrattonLaboratory for Fluorescence Dynamics, Department of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA.
Zoran NenadicDepartment of Biomedical Engineering, University of California Irvine, Irvine, CA 92697, USA.
University of California, Irvine · USFluor (United States) · US

Funding

Uncover Strategies Used By Biological SystemsP50GM076516 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI LANDER, ARTHUR D · 2007 to 2016
$25.1M
TRD4: Phasor analysisP41GM103540 · NIGMS · UNIVERSITY OF CALIFORNIA-IRVINE · PI GRATTON, ENRICO · 2012 to 2020
$12.5M
An integrated in vitro model of perfused tumor and cardiac tissueUH2TR000481 · NCATS · UNIVERSITY OF CALIFORNIA-IRVINE · PI GEORGE, STEVEN CARL · 2012 to 2013
$1.6M
NCATS NIH HHS UH2 TR000481NIGMS NIH HHS P41 GM103540NIGMS NIH HHS P50 GM076516
6 · The paper itself

Abstract

Optical imaging-based methods for assessing the membrane electrophysiology of in vitro human cardiac cells allow for non-invasive temporal assessment of the effect of drugs and other stimuli. Automated methods for detecting and analyzing the depolarization events (DEs) in image-based data allow quantitative assessment of these different treatments. In this study, we use 2-photon microscopy of fluorescent voltage-sensitive dyes (VSDs) to capture the membrane voltage of actively beating human induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs). We built a custom and freely available Matlab software, called MaDEC, to detect, quantify, and compare DEs of hiPS-CMs treated with the β-adrenergic drugs, propranolol and isoproterenol. The efficacy of our software is quantified by comparing detection results against manual DE detection by expert analysts, and comparing DE analysis results to known drug-induced electrophysiological effects. The software accurately detected DEs with true positive rates of 98-100% and false positive rates of 1-2%, at signal-to-noise ratios (SNRs) of 5 and above. The MaDEC software was also able to distinguish control DEs from drug-treated DEs both immediately as well as 10min after drug administration.

Indexed as

SoftwareElectronic Data ProcessingHumansInduced Pluripotent Stem CellsIsoproterenolMembrane PotentialsMyocytes, CardiacPropranololIsoproterenolPropranololClassificationhiPS derived cardiomyocytesMatched filterSignal detectionVoltage-sensitive dye imaging

Identifiers

PMID27281718
PMCPMC4938768
OpenAlexW2398598216

What OpenQuestion holds

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Registered trials

None linked

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.