Evidence map›Paper›PMID 30667009›Full record

ArticleLab on a chip2019

Spatiotemporal quantification of acoustic cell patterning using Voronoï tessellation.

James P K Armstrong, Stephanie A Maynard, Isaac J Pence, Amanda C Franklin, Bruce W Drinkwater, Molly M Stevens

Open access · hybridAbstract read
In one paragraph

Article in Lab on a chip, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
2.3field-weighted citation impact, top 13% of its field
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

17 citing papers in PubMed, 36 citations in OpenAlex.

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  14. Acoustic Microfluidics.Annual review of analytical chemistry (Palo Alto, Calif.) · 2020
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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

6 authors at 2 institutions in 2 countries.

James P K ArmstrongDepartment of Materials, Department of Bioengineering, and Institute for Biomedical Engineering, Imperial College London, London, SW7 2AZ, UK. m.stevens@imperial.ac.uk.
Stephanie A Maynard
Isaac J Pence
Amanda C Franklin
Bruce W Drinkwater
Molly M Stevens
Institute for Biomedical Engineering · CHUniversity of Bristol · GB

Funding

European Research Council 616417Medical Research Council MR/K026666/1Medical Research Council MR/K026682/1Medical Research Council MR/R015651/1Medical Research Council MR/S00551X/1Versus Arthritis 21138Wellcome Trust 098411
6 · The paper itself

Abstract

Acoustic patterning using ultrasound standing waves has recently emerged as a potent biotechnology enabling the remote generation of ordered cell systems. This capability has opened up exciting opportunities, for example, in guiding the development of organoid cultures or the organization of complex tissues. The success of these studies is often contingent on the formation of tightly-packed and uniform cell arrays; however, a number of factors can act to disrupt or prevent acoustic patterning. Yet, to the best of our knowledge, there has been no comprehensive assessment of the quality of acoustically-patterned cell populations. In this report we use a mathematical approach, known as Voronoï tessellation, to generate a series of metrics that can be used to measure the effect of cell concentration, pressure amplitude, ultrasound frequency and biomaterial viscosity upon the quality of acoustically-patterned cell systems. Moreover, we extend this approach towards the characterization of spatiotemporal processes, namely, the acoustic patterning of cell suspensions and the migration of patterned, adherent cell clusters. This strategy is simple, unbiased and highly informative, and we anticipate that the methods described here will provide a systematic framework for all stages of acoustic patterning, including the robust quality control of devices, statistical comparison of patterning conditions, the quantitative exploration of parameter limits and the ability to track patterned tissue formation over time.

Indexed as

AcousticsAnimalsCell LineMiceUltrasonic Waves

Identifiers

PMID30667009
PMCPMC6386121
OpenAlexW2913201305

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.