Evidence map›Paper›PMID 26019013›Full record

ReviewIntegrative biology : quantitative biosciences from nano to macro2015

Multiscale mechanobiology: computational models for integrating molecules to multicellular systems.

Michael Mak, Taeyoon Kim, Muhammad H Zaman, Roger D Kamm

Abstract readReview
In one paragraph

Review in Integrative biology : quantitative biosciences from nano to macro, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Article
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  9. Article
  10. Mechanobiology of the female reproductive system.Reproductive medicine and biology · 2021
    Review
  11. Article
  12. Article
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  19. In Vitro Modeling of Mechanics in Cancer Metastasis.ACS biomaterials science & engineering · 2018
    Review
  20. 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.

Michael MakDepartment of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. rdkamm@mit.edu.
Taeyoon Kim
Muhammad H Zaman
Roger D Kamm

Funding

Modeling bi-directional signaling and cytoskeletal dynamics in 3D cell migrationsU01CA177799 · NCI · BOSTON UNIVERSITY (CHARLES RIVER CAMPUS) · PI GERTLER, FRANK B, KAMM, ROGER D · 2013 to 2017
$3.0M
Multiscale Analysis of Cancer Cell MechanicsF32CA196149 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI MAK, MICHAEL · 2015 to 2016
$98k
NCI NIH HHS F32 CA196149NCI NIH HHS U01 CA177799
6 · The paper itself

Abstract

Mechanical signals exist throughout the biological landscape. Across all scales, these signals, in the form of force, stiffness, and deformations, are generated and processed, resulting in an active mechanobiological circuit that controls many fundamental aspects of life, from protein unfolding and cytoskeletal remodeling to collective cell motions. The multiple scales and complex feedback involved present a challenge for fully understanding the nature of this circuit, particularly in development and disease in which it has been implicated. Computational models that accurately predict and are based on experimental data enable a means to integrate basic principles and explore fine details of mechanosensing and mechanotransduction in and across all levels of biological systems. Here we review recent advances in these models along with supporting and emerging experimental findings.

Indexed as

BiophysicsModels, BiologicalActin CytoskeletonAnimalsBiomechanical PhenomenaCell CommunicationComputer SimulationExtracellular MatrixHumansMechanotransduction, CellularMolecular Dynamics SimulationMolecular Motor ProteinsSystems BiologyMolecular Motor Proteins

Identifiers

PMID26019013
PMCPMC4677065

What OpenQuestion holds

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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.