Evidence map›Paper›PMID 35877643›Full record

ArticleJournal of imaging2022

Force Estimation during Cell Migration Using Mathematical Modelling.

Fengwei Yang, Chandrasekhar Venkataraman, Sai Gu, Vanessa Styles, Anotida Madzvamuse

Open access · goldAbstract read
In one paragraph

Article in Journal of imaging, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.1field-weighted citation impact, top 59% 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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 3 institutions in 2 countries.

Fengwei YangDepartment of Engineering, University of Warwick, Coventry CV4 7AL, UK.ORCID 0000-0002-0619-0840
Chandrasekhar VenkataramanDepartment of Mathematics, School of Mathematical and Physical Sciences, University of Sussex, Brighton BN1 9QH, UK.ORCID 0000-0003-4039-2056
Sai GuDepartment of Engineering, University of Warwick, Coventry CV4 7AL, UK.
Vanessa StylesDepartment of Mathematics, School of Mathematical and Physical Sciences, University of Sussex, Brighton BN1 9QH, UK.ORCID 0000-0002-0387-4067
Anotida MadzvamuseDepartment of Mathematics, School of Mathematical and Physical Sciences, University of Sussex, Brighton BN1 9QH, UK.ORCID 0000-0002-9511-8903
University of Sussex · GBUniversity of Warwick · GBUniversity of British Columbia · CA

Funding

Engineering and Physical Sciences Research Council EP/R001588/1Engineering and Physical Sciences Research Council EP/T00410X/1European Union 642866Leverhulme Trust RPG-2014-14Wolfson Foundation G1949
6 · The paper itself

Abstract

Cell migration is essential for physiological, pathological and biomedical processes such as, in embryogenesis, wound healing, immune response, cancer metastasis, tumour invasion and inflammation. In light of this, quantifying mechanical properties during the process of cell migration is of great interest in experimental sciences, yet few theoretical approaches in this direction have been studied. In this work, we propose a theoretical and computational approach based on the optimal control of geometric partial differential equations to estimate cell membrane forces associated with cell polarisation during migration. Specifically, cell membrane forces are inferred or estimated by fitting a mathematical model to a sequence of images, allowing us to capture dynamics of the cell migration. Our approach offers a robust and accurate framework to compute geometric mechanical membrane forces associated with cell polarisation during migration and also yields geometric information of independent interest, we illustrate one such example that involves quantifying cell proliferation levels which are associated with cell division, cell fusion or cell death.

Indexed as

cell migrationcell polarisationgeometric partial differential equationsmechanical membrane forcesoptimal control

Identifiers

PMID35877643
PMCPMC9320649
OpenAlexW4285733589

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.