Evidence map›Paper›PMID 35992772›Full record

ReviewInterface focus2022

Current strategies with implementation of three-dimensional cell culture: the challenge of quantification.

Jonathan Temple, Eirini Velliou, Mona Shehata, Raphaël Lévy

Erratum issuedAbstract readReview
In one paragraph

Review in Interface focus, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

  1. Review
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  6. Review
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  15. Review
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  17. Review
  18. Plant Cellulose as a Substrate for 3D Neural Stem Cell Culture.Bioengineering (Basel, Switzerland) · 2023
    Article
  19. Article
  20. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Jonathan TempleBioscience building, University of Liverpool, Liverpool L69 3BX, UK.ORCID 0000-0003-4460-1601
Eirini VelliouCentre for 3D Models of Health and Disease, University College London, London, UK.
Mona ShehataHutchison-MRC Research Centre, University of Cambridge, Cambridge CB2 1TN, UK.
Raphaël LévyBioscience building, University of Liverpool, Liverpool L69 3BX, UK.

Funding

Medical Research Council MR/R025762/1Medical Research Council MR/V028553/1
6 · The paper itself

Abstract

From growing cells in spheroids to arranging them on complex engineered scaffolds, three-dimensional cell culture protocols are rapidly expanding and diversifying. While these systems may often improve the physiological relevance of cell culture models, they come with technical challenges, as many of the analytical methods used to characterize traditional two-dimensional (2D) cells must be modified or replaced to be effective. Here we review the advantages and limitations of quantification methods based either on biochemical measurements or microscopy imaging. We focus on the most basic of parameters that one may want to measure, the number of cells. Precise determination of this number is essential for many analytical techniques where measured quantities are only meaningful when normalized to the number of cells (e.g. cytochrome p450 enzyme activity). Thus, accurate measurement of cell number is often a prerequisite to allowing comparisons across different conditions (culturing conditions or drug and treatment screening) or between cells in different spatial states. We note that this issue is often neglected in the literature with little or no information given regarding how normalization was performed, we highlight the pitfalls and complications of quantification and call for more accurate reporting to improve reproducibility.

Indexed as

cell culturehydrogelorganoidscaffoldspheroidthree-dimensional cell culture

Identifiers

PMID35992772
PMCPMC9372643

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.