Evidence map›Paper›PMID 25813860›Full record

ReviewTissue engineering. Part B, Reviews2015

Signaling Pathways and Gene Regulatory Networks in Cardiomyocyte Differentiation.

Abhirath Parikh, Jincheng Wu, Robert M Blanton, Emmanuel S Tzanakakis

Abstract readReview
In one paragraph

Review in Tissue engineering. Part B, Reviews, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

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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

4 authors.

Abhirath Parikh1 Lonza Walkersville, Inc. , Lonza Group, Walkersville, Maryland.
Jincheng Wu2 Department of Chemical and Biological Engineering, Tufts University , Medford, Massachusetts.
Robert M Blanton3 Division of Cardiology, Molecular Cardiology Research Institute , Tufts Medical Center, Tufts School of Medicine, Boston, Massachusetts.
Emmanuel S Tzanakakis2 Department of Chemical and Biological Engineering, Tufts University , Medford, Massachusetts.

Funding

Bioprocess for cardiac cell generation from human induced pluripotent stem cellsR01HL103709 · NHLBI · TUFTS UNIVERSITY MEDFORD · PI TZANAKAKIS, EMMANOUHL · 2011 to 2014
$1.5M
NHLBI NIH HHS R01 HL103709NHLBI NIH HHS R01HL103709
6 · The paper itself

Abstract

Strategies for harnessing stem cells as a source to treat cell loss in heart disease are the subject of intense research. Human pluripotent stem cells (hPSCs) can be expanded extensively in vitro and therefore can potentially provide sufficient quantities of patient-specific differentiated cardiomyocytes. Although multiple stimuli direct heart development, the differentiation process is driven in large part by signaling activity. The engineering of hPSCs to heart cell progeny has extensively relied on establishing proper combinations of soluble signals, which target genetic programs thereby inducing cardiomyocyte specification. Pertinent differentiation strategies have relied as a template on the development of embryonic heart in multiple model organisms. Here, information on the regulation of cardiomyocyte development from in vivo genetic and embryological studies is critically reviewed. A fresh interpretation is provided of in vivo and in vitro data on signaling pathways and gene regulatory networks (GRNs) underlying cardiopoiesis. The state-of-the-art understanding of signaling pathways and GRNs presented here can inform the design and optimization of methods for the engineering of tissues for heart therapies.

Indexed as

Gene Regulatory NetworksAnimalsCell DifferentiationHeartHumansMyocytes, CardiacPluripotent Stem CellsSignal Transduction

Identifiers

PMID25813860
PMCPMC4533091

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.