Evidence map›Paper›PMID 37879587›Full record

ArticleActa biomaterialia2023

A data-driven computational model for engineered cardiac microtissues.

Javiera Jilberto, Samuel J DePalma, Jason Lo, Hiba Kobeissi, Lani Quach, Emma Lejeune, Brendon M Baker, David Nordsletten

Open access · hybridAbstract read
In one paragraph

Article in Acta biomaterialia, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
4.4field-weighted citation impact, top 5% 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

10 citing papers in PubMed, 14 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Estimation of Active Tension in Cardiac Microtissues by Solving a PDE-Constrained Optimization Problem.International journal for numerical methods in biomedical engineering · 2025
    Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. 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

8 authors at 3 institutions in 2 countries.

Javiera JilbertoDepartment of Biomedical Engineering, University of Michigan, MI, USA. Electronic address: jilberto@umich.edu.
Samuel J DePalmaDepartment of Biomedical Engineering, University of Michigan, MI, USA.
Jason LoDepartment of Biomedical Engineering, University of Michigan, MI, USA.
Hiba KobeissiDepartment of Mechanical Engineering, Boston University, MA, USA.
Lani QuachDepartment of Biomedical Engineering, University of Michigan, MI, USA.
Emma LejeuneDepartment of Mechanical Engineering, Boston University, MA, USA.
Brendon M BakerDepartment of Biomedical Engineering, University of Michigan, MI, USA.
David NordslettenDepartment of Biomedical Engineering, University of Michigan, MI, USA; Department of Cardiac Surgery, University of Michigan, MI, USA; Department of Biomedical Engineering, School of Imaging Sciences and Biomedical Engineering, King's College London, London, UK.
University of Michigan · USBoston University · USKing's College London · GB

Funding

Training Program in Translational Cardiovascular Research and EntrepreneurshipT32HL125242 · NHLBI · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI MICHELE, DANIEL E · 2015 to 2024
$1.9M
NHLBI NIH HHS T32 HL125242
6 · The paper itself

Abstract

Engineered heart tissues (EHTs) present a potential solution to some of the current challenges in the treatment of heart disease; however, the development of mature, adult-like cardiac tissues remains elusive. Mechanical stimuli have been observed to improve whole-tissue function and cardiomyocyte (CM) maturation, although our ability to fully utilize these mechanisms is hampered, in part, by our incomplete understanding of the mechanobiology of EHTs. In this work, we leverage experimental data, produced by a mechanically tunable experimental setup, to introduce a tissue-specific computational modeling pipeline of EHTs. Our new modeling pipeline generates simulated, image-based EHTs, capturing ECM and myofibrillar structure as well as functional parameters estimated directly from experimental data. This approach enables the unique estimation of EHT function by data-based estimation of CM active stresses. We use this experimental and modeling pipeline to study different mechanical environments, where we contrast the force output of the tissue with the computed active stress of CMs. We show that the significant differences in measured experimental forces can largely be explained by the levels of myofibril formation achieved by the CMs in the distinct mechanical environments, with active stress showing more muted variations across conditions. The presented model also enables us to dissect the relative contributions of myofibrils and extracellular matrix to tissue force output, a task difficult to address experimentally. These results highlight the importance of tissue-specific modeling to augment EHT experiments, providing deeper insights into the mechanobiology driving EHT function. STATEMENT OF SIGNIFICANCE: Engineered heart tissues (EHTs) have the potential to revolutionize the way heart disease is treated. However, developing mature cardiomyocytes (CM) in these tissues remains a challenge due, in part, to our incomplete understanding of the fundamental biomechanical mechanisms that drive EHT development. This work integrates the experimental data of an EHT platform developed to study the influence of mechanics in CM maturation with computational biomechanical models. This approach is used to augment conclusions obtained in-vitro - by measuring quantities such as cell stress and strain - and to dissect the relevance of each component in the whole tissue performance. Our results show how a combination of specialized in-silico and in-vitro approaches can help us better understand the mechanobiology of EHTs.

Indexed as

Heart DiseasesMyocytes, CardiacExtracellular MatrixHumansMyocardiumTissue EngineeringCardiac biomechanicsComputational modelingEngineered heart tissuesMechanobiology

Identifiers

PMID37879587
PMCPMC10938557
OpenAlexW4387873327

What Socratic holds

Textmetadata
LicenceTDM
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 Socratic graph.