ArticleActa biomaterialia2023
A data-driven computational model for engineered cardiac microtissues.
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.
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Who cites it
10 citing papers in PubMed, 14 citations in OpenAlex.
- Quantifying the spatiotemporal mechanical dynamics of engineered cardiac microbundles.PLoS computational biology · 2026Article
- Heart-On-a-Chip with Integrated Ultrasoft Mechanosensors for Continuous Measurement of Cell- and Tissue-Scale Contractile Stresses.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Biomimetic electrospun scaffolds for engineered heart tissue: from design parameters to drug testing platforms.Frontiers in bioengineering and biotechnology · 2026Review
- Quantifying HiPSC-CM structural organization at scale with deep learning-enhanced SarcGraph.PLoS computational biology · 2025Article
- Estimation of Active Tension in Cardiac Microtissues by Solving a PDE-Constrained Optimization Problem.International journal for numerical methods in biomedical engineering · 2025Article
- Biomechanical mechanism and clinical management progress of surgical wound tension.Frontiers in surgery · 2025Review
- Matrix Architecture and Mechanics Regulate Myofibril Organization, Costamere Assembly, and Contractility in Engineered Myocardial Microtissues.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Article
- MicroBundlePillarTrack: A Python package for automated segmentation, tracking, and analysis of pillar deflection in cardiac microbundles.microPublication biology · 2024Article
- MicroBundleCompute: Automated segmentation, tracking, and analysis of subdomain deformation in cardiac microbundles.PloS one · 2024Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
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.
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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.