Evidence map›Paper›PMID 31653933›Full record

ArticleScientific reports2019

Seeding hESCs to achieve optimal colony clonality.

L E Wadkin, S Orozco-Fuentes, I Neganova, S Bojic, A Laude, M Lako, N G Parker, A Shukurov

Abstract read
In one paragraph

Article in Scientific reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Review
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

8 authors.

L E WadkinSchool of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, UK. l.e.wadkin@ncl.ac.uk.ORCID http://orcid.org/0000-0001-7355-2023
S Orozco-FuentesSchool of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, UK.ORCID http://orcid.org/0000-0002-6192-7710
I NeganovaInstitute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
S BojicInstitute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
A LaudeBio-Imaging Unit, Medical School, Newcastle University, Newcastle upon Tyne, UK.
M LakoInstitute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, UK.
N G ParkerSchool of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, UK.
A ShukurovSchool of Mathematics, Statistics and Physics, Newcastle University, Newcastle upon Tyne, UK.

Funding

Biotechnology and Biological Sciences Research Council BB/I020209/1Medical Research Council G0301182
6 · The paper itself

Abstract

Human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) have promising clinical applications which often rely on clonally-homogeneous cell populations. To achieve this, it is important to ensure that each colony originates from a single founding cell and to avoid subsequent merging of colonies during their growth. Clonal homogeneity can be obtained with low seeding densities; however, this leads to low yield and viability. It is therefore important to quantitatively assess how seeding density affects clonality loss so that experimental protocols can be optimised to meet the required standards. Here we develop a quantitative framework for modelling the growth of hESC colonies from a given seeding density based on stochastic exponential growth. This allows us to identify the timescales for colony merges and over which colony size no longer predicts the number of founding cells. We demonstrate the success of our model by applying it to our own experiments of hESC colony growth; while this is based on a particular experimental set-up, the model can be applied more generally to other cell lines and experimental conditions to predict these important timescales.

Indexed as

Cell DifferentiationCell ProliferationAlgorithmsCell Culture TechniquesCells, CulturedClone CellsHuman Embryonic Stem CellsHumansInduced Pluripotent Stem CellsModels, TheoreticalReproducibility of Results

Identifiers

PMID31653933
PMCPMC6814789

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.