Evidence map›Paper›PMID 29786561›Full record

ReviewPhilosophical transactions of the Royal Society of London. Series B, Biological sciences2018

Impedance-based cellular assays for regenerative medicine.

W Gamal, H Wu, I Underwood, J Jia, S Smith, P O Bagnaninchi

Abstract readReview
In one paragraph

Review in Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing 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

15 citing papers in PubMed.

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  15. Designer human tissue: coming to a lab near you.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2018
    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

6 authors.

W GamalSchool of Electronic Engineering, Bangor University, Bangor LL57 1UT, UK.
H WuSchool of Engineering, University of Edinburgh, Edinburgh EH9 3FB, UK.
I UnderwoodSchool of Engineering, University of Edinburgh, Edinburgh EH9 3FB, UK.
J JiaSchool of Engineering, University of Edinburgh, Edinburgh EH9 3FB, UK.
S SmithSchool of Engineering, University of Edinburgh, Edinburgh EH9 3FB, UK.
P O BagnaninchiMRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh EH16 4UU, UK pierre.bagnaninchi@ed.ac.uk.ORCID 0000-0001-5433-9630

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Therapies based on regenerative techniques have the potential to radically improve healthcare in the coming years. As a result, there is an emerging need for non-destructive and label-free technologies to assess the quality of engineered tissues and cell-based products prior to their use in the clinic. In parallel, the emerging regenerative medicine industry that aims to produce stem cells and their progeny on a large scale will benefit from moving away from existing destructive biochemical assays towards data-driven automation and control at the industrial scale. Impedance-based cellular assays (IBCA) have emerged as an alternative approach to study stem-cell properties and cumulative studies, reviewed here, have shown their potential to monitor stem-cell renewal, differentiation and maturation. They offer a novel method to non-destructively assess and quality-control stem-cell cultures. In addition, when combined with

Indexed as

Cell DifferentiationElectric ImpedanceCell Culture TechniquesDielectric SpectroscopyHumansRegenerative MedicineStem CellsTissue EngineeringTomographyelectrical impedance spectroscopyimpedance sensingimpedance spectroscopylabel-free assaysstem celltissue engineering

Identifiers

PMID29786561
PMCPMC5974449

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.