Evidence mapPaperPMID 40131342Full record

ArticleJournal of biomechanical engineering2025

Multiscale Kinematic Growth Coupled With Mechanosensitive Systems Biology in Open-Source Software.

Steven A LaBelle, Mohammadreza Soltany Sadrabadi, Seungik Baek, Mohammad R K Mofrad, Jeffrey A Weiss, Amirhossein Arzani

Abstract read
In one paragraph

Article in Journal of biomechanical engineering, 2025. 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
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

0 citing papers in PubMed.

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

6 authors.

Steven A LaBelle *Department of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112.
Mohammadreza Soltany Sadrabadi *Department of Mechanical Engineering, Northern Arizona University, Flagstaff, AZ 86011.
Seungik BaekDepartment of Mechanical Engineering, Michigan State University, East Lansing, MI 48824.
Mohammad R K MofradDepartment of Bioengineering and Mechanical Engineering, University of California, Berkeley, Berkeley, CA 94720.
Jeffrey A WeissDepartment of Biomedical Engineering, University of Utah, Salt Lake City, UT 84112; Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112.
Amirhossein ArzaniScientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT 84112; Department of Mechanical Engineering, University of Utah, Salt Lake City, UT 84112.

Funding

Finite Elements For Biomechanics And BiophysicsR01GM083925 · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2025 to 2025
$475k
Mechanical Stress and Lung Tumor ProgressionR01CA290182 · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2025 to 2025
$461k
National Science Foundation 2246911NCI NIH HHS R01 CA290182NIGMS NIH HHS R01 GM083925NIH HHS 5R01CA290182
6 · The paper itself

Abstract

Multiscale coupling between cell-scale biology and tissue-scale mechanics is a promising approach for modeling disease growth. In such models, tissue-level growth and remodeling (G&R) are driven by cell-level signaling pathways and systems biology models, where each model operates at different scales. Herein, we generate multiscale G&R models to capture the associated multiscale connections. At the cell-scale, we consider systems biology models in the form of systems of ordinary differential equations (ODEs) and partial differential equations (PDEs) representing the reactions between the biochemicals causing the growth based on mass-action or logic-based Hill-type kinetics. At the tissue-scale, we employ kinematic growth in continuum frameworks. Two illustrative test problems (a tissue graft and aneurysm growth) are examined with various chemical signaling networks, boundary conditions, and mechano-chemical coupling strategies. We extend two open-source software frameworks-febio and fenics-to disseminate examples of multiscale growth and remodeling simulations. One-way and two-way coupling between the systems biology and the growth models are compared and the effect of biochemical diffusivity and ODE versus PDE-based systems biology modeling on the G&R results are studied. The results show that growth patterns emerge from reactions between biochemicals, the choice between ODEs and PDEs systems biology modeling, and the coupling strategy. Cross-verification confirms that results for febio and fenics are nearly identical. We hope that these open-source tools will support reproducibility and education within the biomechanics community.

Indexed as

Mechanical PhenomenaMechanotransduction, CellularModels, BiologicalSoftwareSystems BiologyBiomechanical PhenomenaHumansaneurysmcell signalinggrowth and remodelingmultiscale modelingsystems mechanobiology

Identifiers

PMID40131342
PMCPMC12147932

What Socratic holds

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Registered trials

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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 Socratic graph.