Evidence map›Paper›PMID 35099750›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2022

Differentiation and Characterization of Human Pluripotent Stem Cell-Derived Cardiac Endothelial Cells for In Vitro Applications.

Kavita Raniga, Nguyen T N Vo, Chris Denning

Abstract read
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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

3 authors.

Kavita RanigaDepartment of Stem Cell Biology, Biodiscovery Institute, University of Nottingham, Nottingham, UK.
Nguyen T N VoDepartment of Stem Cell Biology, Biodiscovery Institute, University of Nottingham, Nottingham, UK.
Chris DenningDepartment of Stem Cell Biology, Biodiscovery Institute, University of Nottingham, Nottingham, UK. Chris.denning@nottingham.ac.uk.

Funding

Medical Research Council MR/L012618/1National Centre for the Replacement, Refinement and Reduction of Animals in Research NC/C013202/1National Centre for the Replacement, Refinement and Reduction of Animals in Research NC/T2T0119
6 · The paper itself

Abstract

Various protocols have been developed to generate endothelial cells for disease modeling, angiogenesis, vascular regeneration, and drug screening. These protocols often require cell sorting, as most differentiation strategies result in a heterogenous population of endothelial cells (ECs). For any given model system, one important consideration is choosing the appropriate EC subtype, as different EC populations have unique molecular signatures.Herein, we describe a protocol for cardiac EC differentiation and a protocol for endothelial cell characterization. This protocol is aimed at investigating differentiation efficiency by measuring endothelial lineage markers, CD31, VE-Cadherin, and VEGFR2 by flow cytometry. Collectively, these protocols comprise the tools required to generate cardiac ECs efficiently and reproducibly from different hPSC lines without the need for cell sorting. Our protocol adds to the panel of hPSCs for cardiac EC differentiation and addresses reproducibility concerns of hPSC-based experiments. The approaches described are also applicable for complex model generation where multiple cardiovascular cell types are involved and may assist in optimizing differentiations for different cell lineages, including cardiomyocytes, cardiac endothelial cells, and cardiac fibroblasts.

Indexed as

Endothelial CellsPluripotent Stem CellsCell DifferentiationCell LineageHumansMyocytes, CardiacReproducibility of ResultsCardiac endothelial cellsCardiac mesodermFlow cytometryStem cell differentiationVEGF

Identifiers

What OpenQuestion holds

Textmetadata
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.