Evidence map›Paper›PMID 31920691›Full record

ArticleFrontiers in physiology2019

Multiscale Coupling of an Agent-Based Model of Tissue Fibrosis and a Logic-Based Model of Intracellular Signaling.

S Michaela Rikard, Thomas L Athey, Anders R Nelson, Steven L M Christiansen, Jia-Jye Lee, Jeffrey W Holmes, Shayn M Peirce, Jeffrey J Saucerman

Open access · goldAbstract read
In one paragraph

Article in Frontiers in physiology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers.

0numbers the graph read from it
0cells of the map it votes in
38citing papers in PubMed
3.7field-weighted citation impact, top 6% 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

38 citing papers in PubMed, 47 citations in OpenAlex.

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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

8 authors at 2 institutions in 1 country.

S Michaela RikardDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States.
Thomas L AtheyDepartment of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, United States.
Anders R NelsonDepartment of Pharmacology, University of Virginia, Charlottesville, VA, United States.
Steven L M ChristiansenDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States.
Jia-Jye LeeDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States.
Jeffrey W HolmesDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States.
Shayn M PeirceDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States.
Jeffrey J SaucermanDepartment of Biomedical Engineering, University of Virginia, Charlottesville, VA, United States.
University of Virginia · USJohns Hopkins University · US

Funding

BASIC CARDIOVASCULAR RESEARCH TRAINING GRANTT32HL007284 · NHLBI · UNIVERSITY OF VIRGINIA CHARLOTTESVILLE · PI Brant E Isakson, Gary K Owens · 1985 to 2026
$19.6M
Defining SMC phenotypes critical in late stage atherosclerosis pathogenesisR01HL136314 · NHLBI · UNIVERSITY OF VIRGINIA · PI OWENS, GARY K · 2018 to 2021
$3.0M
Multiscale Modeling for Treatment Discovery in Duchenne Muscular DystrophyU01AR069393 · NIAMS · UNIVERSITY OF VIRGINIA · PI BLEMKER, SILVIA SALINAS, PEIRCE-COTTLER, SHAYN · 2016 to 2020
$2.5M
Systems Biology of Hypertrophic Heart Disease from Molecular Pathways to Organ SystemR01HL137100 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI MCCULLOCH, ANDREW D. · 2017 to 2020
$2.0M
Systems Pharmacology Model for Spatial Control of Cardiac FibrosisR01HL137755 · NHLBI · UNIVERSITY OF VIRGINIA · PI HOLMES, JEFFREY W, SAUCERMAN, JEFFREY J. · 2017 to 2020
$1.9M
Computational Modeling of Scar Formation After Myocardial InfarctionR01HL116449 · NHLBI · UNIVERSITY OF VIRGINIA · PI HOLMES, JEFFREY W · 2014 to 2018
$1.5M
NHLBI NIH HHS R01 HL116449NHLBI NIH HHS R01 HL136314NHLBI NIH HHS R01 HL137100NHLBI NIH HHS R01 HL137755NHLBI NIH HHS T32 HL007284NIAMS NIH HHS U01 AR069393
6 · The paper itself

Abstract

Wound healing and fibrosis following myocardial infarction (MI) is a dynamic process involving many cell types, extracellular matrix (ECM), and inflammatory cues. As both incidence and survival rates for MI increase, management of post-MI recovery and associated complications are an increasingly important focus. Complexity of the wound healing process and the need for improved therapeutics necessitate a better understanding of the biochemical cues that drive fibrosis. To study the progression of cardiac fibrosis across spatial and temporal scales, we developed a novel hybrid multiscale model that couples a logic-based differential equation (LDE) model of the fibroblast intracellular signaling network with an agent-based model (ABM) of multi-cellular tissue remodeling. The ABM computes information about cytokine and growth factor levels in the environment including TGFβ, TNFα, IL-1β, and IL-6, which are passed as inputs to the LDE model. The LDE model then computes the network signaling state of individual cardiac fibroblasts within the ABM. Based on the current network state, fibroblasts make decisions regarding cytokine secretion and deposition and degradation of collagen. Simulated fibroblasts respond dynamically to rapidly changing extracellular environments and contribute to spatial heterogeneity in model predicted fibrosis, which is governed by many parameters including cell density, cell migration speeds, and cytokine levels. Verification tests confirmed that predictions of the coupled model and network model alone were consistent in response to constant cytokine inputs and furthermore, a subset of coupled model predictions were validated with

Indexed as

agent-based modelcardiac fibroblastfibrosismultiscale modelingmyocardial infarctionnetwork modelsystems biology

Identifiers

PMID31920691
PMCPMC6928129
OpenAlexW2990186364

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.