Evidence map›Paper›PMID 23139838›Full record

ArticlePloS one2012

Dynamic mechanisms of cell rigidity sensing: insights from a computational model of actomyosin networks.

Carlos Borau, Taeyoon Kim, Tamara Bidone, José Manuel García-Aznar, Roger D Kamm

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed
2.4field-weighted citation impact, top 12% 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

35 citing papers in PubMed, 64 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Mechanics of cell-cell junctions.Biophysical journal · 2023
    Article
  6. Article
  7. Review
  8. Article
  9. Tools for computational analysis of moving boundary problems in cellular mechanobiology.Wiley interdisciplinary reviews. Systems biology and medicine · 2020
    Review
  10. Self-organized cytoskeletal alignment duringPhilosophical transactions of the Royal Society of London. Series B, Biological sciences · 2020
    Article
  11. Article
  12. Modelling actin polymerization: the effect on confined cell migration.Biomechanics and modeling in mechanobiology · 2019
    Article
  13. Article
  14. Multiscale model of integrin adhesion assembly.PLoS computational biology · 2019
    Article
  15. Article
  16. Computational modeling of single-cell mechanics and cytoskeletal mechanobiology.Wiley interdisciplinary reviews. Systems biology and medicine · 2018
    Review
  17. Integration ofFrontiers in physiology · 2018
    Article
  18. Tension, contraction and tissue morphogenesis.Development (Cambridge, England) · 2017
    Review
  19. Article
  20. Article
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 4 institutions in 3 countries.

Carlos BorauAragón Institute of Engineering Research (I3A), Department of Mechanical Engineering, University of Zaragoza, Zaragoza, Spain.
Taeyoon Kim
Tamara Bidone
José Manuel García-Aznar
Roger D Kamm
Massachusetts Institute of Technology · USPolytechnic University of Turin · ITUniversidad de Zaragoza · ESUniversity of Chicago · US

Funding

Beagle: A Supercomputer for Computational Biology, Simulation, and Data AnalysisS10RR029030 · NCRR · UNIVERSITY OF CHICAGO · PI FOSTER, IAN · 2010 to 2010
$7.0M
NCRR NIH HHS S10 RR029030NCRR NIH HHS S10 RR029030-01
6 · The paper itself

Abstract

Cells modulate themselves in response to the surrounding environment like substrate elasticity, exhibiting structural reorganization driven by the contractility of cytoskeleton. The cytoskeleton is the scaffolding structure of eukaryotic cells, playing a central role in many mechanical and biological functions. It is composed of a network of actins, actin cross-linking proteins (ACPs), and molecular motors. The motors generate contractile forces by sliding couples of actin filaments in a polar fashion, and the contractile response of the cytoskeleton network is known to be modulated also by external stimuli, such as substrate stiffness. This implies an important role of actomyosin contractility in the cell mechano-sensing. However, how cells sense matrix stiffness via the contractility remains an open question. Here, we present a 3-D Brownian dynamics computational model of a cross-linked actin network including the dynamics of molecular motors and ACPs. The mechano-sensing properties of this active network are investigated by evaluating contraction and stress in response to different substrate stiffness. Results demonstrate two mechanisms that act to limit internal stress: (i) In stiff substrates, motors walk until they exert their maximum force, leading to a plateau stress that is independent of substrate stiffness, whereas (ii) in soft substrates, motors walk until they become blocked by other motors or ACPs, leading to submaximal stress levels. Therefore, this study provides new insights into the role of molecular motors in the contraction and rigidity sensing of cells.

Indexed as

Models, BiologicalActin CytoskeletonActinsActomyosinBiomechanical PhenomenaCellsMolecular Motor ProteinsMovementStress, PhysiologicalActinsActomyosinMolecular Motor Proteins

Identifiers

PMID23139838
PMCPMC3489786
OpenAlexW2002112707

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.