Evidence map›Paper›PMID 27551501›Full record

ArticleCell death discovery2016

Systematic selection of small molecules to promote differentiation of embryonic stem cells and experimental validation for generating cardiomyocytes.

Y KalantarMotamedi, M Peymani, H Baharvand, M H Nasr-Esfahani, A Bender

Abstract read
In one paragraph

Article in Cell death discovery, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
  5. Thymus Regeneration and Future Challenges.Stem cell reviews and reports · 2020
    Review
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
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.

Y KalantarMotamediCentre for Molecular Informatics, Department of Chemistry, University of Cambridge , Lensfield Road, Cambridge CB2 1EW, UK.
M PeymaniDepartment of Cell and Molecular Biology, Cell Science Research Centre, Royan Institute for Biotechnology, ACECR , Isfahan, Iran.
H BaharvandDepartment of Stem Cells and Developmental Biology, Cell Science Research Center, Royan Institute for Stem Cell Biology and Technology, ACECR , Tehran, Iran.
M H Nasr-EsfahaniDepartment of Cell and Molecular Biology, Cell Science Research Centre, Royan Institute for Biotechnology, ACECR , Isfahan, Iran.
A BenderCentre for Molecular Informatics, Department of Chemistry, University of Cambridge , Lensfield Road, Cambridge CB2 1EW, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small molecules are being increasingly used for inducing the targeted differentiation of stem cells to different cell types. However, until now no systematic method for selecting suitable small molecules for this purpose has been presented. In this work, we propose an integrated and general bioinformatics- and cheminformatics-based approach for selecting small molecules which direct cellular differentiation in the desired way. The approach was successfully experimentally validated for differentiating stem cells into cardiomyocytes. All predicted compounds enhanced expression of cardiac progenitor (Gata4, Nkx2-5 and Mef2c) and mature cardiac markers (Actc1, myh6) significantly during and post-cardiac progenitor formation. The best-performing compound, Famotidine, increased the percentage of Myh6-positive cells from 33 to 56%, and enhanced the expression of Nkx2.5 and Tnnt2 cardiac progenitor and cardiac markers in protein level. The approach employed in the study is applicable to all other stem cell differentiation settings where gene expression data are available.

Identifiers

PMID27551501
PMCPMC4979408

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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.