Evidence map›Paper›PMID 32370690›Full record

ArticleJournal of the Royal Society, Interface2020

A minimal mechanosensing model predicts keratocyte evolution on flexible substrates.

Zhiwen Zhang, Phoebus Rosakis, Thomas Y Hou, Guruswami Ravichandran

Open access · greenAbstract read
In one paragraph

Article in Journal of the Royal Society, Interface, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 40% 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

3 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
  2. Article
  3. Tools for computational analysis of moving boundary problems in cellular mechanobiology.Wiley interdisciplinary reviews. Systems biology and medicine · 2020
    Review
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

4 authors at 3 institutions in 3 countries.

Zhiwen ZhangDepartment of Mathematics, The University of Hong Kong, Pokfulam Road, Hong Kong SAR.
Phoebus RosakisDepartment of Mathematics and Applied Mathematics, University of Crete, Heraklion 70013 Crete, Greece.
Thomas Y HouComputing and Mathematical Sciences, California Institute of Technology, Pasadena, CA 91125, USA.
Guruswami RavichandranDivision of Engineering and Applied Science, California Institute of Technology, Pasadena, CA 91125, USA.
California Institute of Technology · USUniversity of Crete · GRUniversity of Hong Kong · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A mathematical model is proposed for shape evolution and locomotion of fish epidermal keratocytes on elastic substrates. The model is based on mechanosensing concepts: cells apply contractile forces onto the elastic substrate, while cell shape evolution depends locally on the substrate stress generated by themselves or external mechanical stimuli acting on the substrate. We use the level set method to study the behaviour of the model numerically, and predict a number of distinct phenomena observed in experiments, such as (i) symmetry breaking from the stationary centrosymmetric to the well-known steadily propagating crescent shape, (ii) asymmetric bipedal oscillations and travelling waves in the lamellipodium leading edge, (iii) response to remote mechanical stress externally applied to the substrate (tensotaxis) and (iv) changing direction of motion towards an interface with a rigid substrate (durotaxis).

Indexed as

LocomotionPseudopodiaAnimalsCell MovementCell ShapeModels, BiologicalStress, Mechanicalcellular locomotionkeratocyteslevel set methodmechanosensing

Identifiers

PMID32370690
PMCPMC7276546
OpenAlexW2795033709

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.