Evidence map›Paper›PMID 32298635›Full record

ArticleBiophysical journal2020

All-Optical Electrophysiology Refines Populations of In Silico Human iPSC-CMs for Drug Evaluation.

Michelangelo Paci, Elisa Passini, Aleksandra Klimas, Stefano Severi, Jari Hyttinen, Blanca Rodriguez, Emilia Entcheva

Open access · hybridAbstract read
In one paragraph

Article in Biophysical journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 42 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
42citing papers in PubMed, 1 pooled it
6.6field-weighted citation impact, top 2% 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

42 citing papers in PubMed, 1 synthesis or guideline pooled it, 74 citations in OpenAlex.

  1. Pooled it
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  8. Sometimes extracellular recordings fail for good reasons.NPJ systems biology and applications · 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

7 authors at 5 institutions in 4 countries.

Michelangelo PaciBioMediTech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland. Electronic address: michelangelo.paci@tuni.fi.
Elisa PassiniDepartment of Computer Science, University of Oxford, Oxford, United Kingdom.
Aleksandra KlimasDepartment of Biological Sciences, Carnegie Mellon University, Pittsburgh, Pennsylvania.
Stefano SeveriDepartment of Electrical, Electronic and Information Engineering "Guglielmo Marconi," University of Bologna, Cesena, Italy.
Jari HyttinenBioMediTech, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland.
Blanca RodriguezDepartment of Computer Science, University of Oxford, Oxford, United Kingdom.
Emilia EntchevaDepartment of Biomedical Engineering, George Washington University, Washington, D.C.
Tampere University · FIUniversity of Oxford · GBCarnegie Mellon University · USGeorge Washington University · USMarconi University · IT

Funding

Scalable platform for optimizing human cardiac tissue engineering via optical pacing and on-demand oxygenationR01HL144157 · NHLBI · GEORGE WASHINGTON UNIVERSITY · PI ENTCHEVA, EMILIA, KAY, MATTHEW W. · 2019 to 2022
$2.8M
British Heart Foundation RE/08/004/23915British Heart Foundation RE/13/1/30181NHLBI NIH HHS R01 HL144157Wellcome TrustWellcome Trust 100246/Z/12/ZWellcome Trust 214290/Z/18/Z
6 · The paper itself

Abstract

High-throughput in vitro drug assays have been impacted by recent advances in human induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) technology and by contact-free all-optical systems simultaneously measuring action potentials (APs) and Ca

Indexed as

Induced Pluripotent Stem CellsAction PotentialsAdultComputer SimulationDrug EvaluationHumansMyocytes, Cardiac

Identifiers

PMID32298635
PMCPMC7231889
OpenAlexW3014696819

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.