Evidence map›Paper›PMID 26023328›Full record

ArticleBMC biophysics2015

The biophysical nature of cells: potential cell behaviours revealed by analytical and computational studies of cell surface mechanics.

Ramiro Magno, Verônica A Grieneisen, Athanasius Fm Marée

Open access · bronzeAbstract read
In one paragraph

Article in BMC biophysics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

31 citing papers in PubMed, 88 citations in OpenAlex.

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  4. Cell Simulation as Cell Segmentation.bioRxiv : the preprint server for biology · 2024
    Article
  5. Choice of friction coefficient deeply affects tissue behaviour in stochastic epithelial vertex models.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024
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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

3 authors at 2 institutions in 2 countries.

Ramiro MagnoTheoretical Biology/Bioinformatics, Dept. of Biology, Utrecht University, Padualaan 83584 CH, Utrecht, Netherlands ; Computational and Systems Biology, John Innes Centre,, Norwich Research Park, NR4 7UH, Norwich, UK.
Verônica A GrieneisenComputational and Systems Biology, John Innes Centre,, Norwich Research Park, NR4 7UH, Norwich, UK.
Athanasius Fm MaréeComputational and Systems Biology, John Innes Centre,, Norwich Research Park, NR4 7UH, Norwich, UK.
John Innes Centre · GBNorwich Research Park · GB

Funding

Biotechnology and Biological Sciences Research Council BBS/E/J/000C0645Biotechnology and Biological Sciences Research Council BBS/E/J/000C0646
6 · The paper itself

Abstract

backgroundThe biophysical characteristics of cells determine their shape in isolation and when packed within tissues. Cells can form regular or irregular epithelial structures, round up and form clusters, or deform and attach to substrates. The acquired shape of cells and tissues is a consequence of (i) internal cytoskeletal processes, such as actin polymerisation and cortical myosin contraction, (ii) adhesion molecules within the cell membrane that interact with substrates and neighbouring cells, and (iii) processes that regulate cell volume. Although these processes seem relatively simple, when combined they unleash a rich variety of cellular behaviour that is not readily understandable outside a theoretical framework.

methodsWe perform a mathematical analysis of a commonly used class of model formalisms that describe cell surface mechanics using an energy-based approach. Predictions are then confirmed through comparison with the computational outcomes of a Vertex model and 2D and 3D simulations of the Cellular Potts model.

resultsThe analytical study reveals the complete possible spectrum of single cell behaviour and tissue packing in both 2D and 3D, by taking the typical core elements of cell surface mechanics into account: adhesion, cortical tension and volume conservation. We show that from an energy-based description, forces and tensions can be derived, as well as the prediction of cell behaviour and tissue packing, providing an intuitive and biologically relevant mapping between modelling parameters and experiments.

conclusionsThe quantitative cellular behaviours and biological insights agree between the analytical study and the diverse computational model formalisms, including the Cellular Potts model. This illustrates the generality of energy-based approaches for cell surface mechanics and highlights how meaningful and quantitative comparisons between models can be established. Moreover, the mathematical analysis reveals direct links between known biophysical properties and specific parameter settings within the Cellular Potts model.

Indexed as

3D modellingAdhesionCell shapeCell sortingCell surface mechanicsCellular dynamicsCellular Potts modelCellular vertex-modelsCortical tensionGrid anisotropyMembrane tensionTissue packing

Identifiers

PMID26023328
PMCPMC4446964
OpenAlexW1719999885

What OpenQuestion holds

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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.