Evidence map›Paper›PMID 27250776›Full record

ReviewStem cells (Dayton, Ohio)2016

Concise Review: Measuring Physiological Responses of Human Pluripotent Stem Cell Derived Cardiomyocytes to Drugs and Disease.

Berend J van Meer, Leon G J Tertoolen, Christine L Mummery

Abstract readReview
In one paragraph

Review in Stem cells (Dayton, Ohio), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers.

0numbers the graph read from it
0cells of the map it votes in
41citing 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

41 citing papers in PubMed.

  1. Machine Learning in Stem Cell Research: From Biological Data to Clinical Translation.Computational and structural biotechnology journal · 2026
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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

3 authors.

Berend J van MeerDepartment of Anatomy and Embryology, Leiden University Medical Center, Leiden, The Netherlands.
Leon G J TertoolenDepartment of Anatomy and Embryology, Leiden University Medical Center, Leiden, The Netherlands.
Christine L MummeryDepartment of Anatomy and Embryology, Leiden University Medical Center, Leiden, The Netherlands.

Funding

European Research Council 323182National Centre for the Replacement, Refinement and Reduction of Animals in Research NC/C013105/1National Centre for the Replacement, Refinement and Reduction of Animals in Research NC/C013202/1
6 · The paper itself

Abstract

Cardiomyocytes from human pluripotent stem cells (hPSC) are of growing interest as models to understand mechanisms underlying genetic disease, identify potential drug targets and for safety pharmacology as they may predict human relevant effects more accurately and inexpensively than animals or other cell models. Crucial to their optimal use are accurate methods to quantify cardiomyocyte phenotypes accurately and reproducibly. Here, we review current methods for determining biophysical parameters of hPSC-derived cardiomyocytes (hPSC-CMs) that recapitulate disease and drug responses. Even though hPSC-CMs as currently available are immature, various biophysical methods are nevertheless already providing useful insights into the biology of the human heart and its maladies. Advantages and limitations of assays currently available looking toward applications of hPSC-CMs are described with examples of how they have been used to date. This will help guide the choice of biophysical method to characterize healthy cardiomyocytes and their pathologies in vitro. Stem Cells 2016;34:2008-2015.

Indexed as

DiseaseBiophysical PhenomenaCalcium SignalingHumansMyocytes, CardiacPharmaceutical PreparationsPluripotent Stem CellsPharmaceutical PreparationsCardiac disease modellingCardiomyocyte maturationCardiomyocyte physiologyDrug testingHeartHumanPluripotent stem cells

Identifiers

PMID27250776
PMCPMC5113667

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.