2019
DOI: 10.1002/wsbm.1470
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Exploring cardiac form and function: A length‐scale computational biology approach

Abstract: The ability to adequately pump blood throughout the body is the result of tightly regulated feedback mechanisms that exist across many spatial scales in the heart. Diseases which impede the function at any one of the spatial scales can cause detrimental cardiac remodeling and eventual heart failure. An overarching goal of cardiac research is to use engineered heart tissue in vitro to study the physiology of diseased heart tissue, develop cell replacement therapies, and explore drug testing applications. A comm… Show more

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Cited by 5 publications
(4 citation statements)
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“…Understanding the details of cardiomyocyte differentiation and maturation is extremely important for the development of new therapeutic and diagnostic tools (Karbassi et al, 2020 ). To maximize the physiological relevance of such studies, it is important to be able to integrate data collected at different length scales, ranging from the molecular level, crossing the dimensions of individual cells, and reaching the scale of tissues and organs (Sherman & Grosberg, 2019 ). Here we aimed at implementing such approach by combining protein data generated by fluorescence microscopy and Western Blot with the characterization of mechanical properties of single cells, while also assessing the collective dynamic behavior of the corresponding cell monolayers.…”
Section: Discussionmentioning
confidence: 99%
“…Understanding the details of cardiomyocyte differentiation and maturation is extremely important for the development of new therapeutic and diagnostic tools (Karbassi et al, 2020 ). To maximize the physiological relevance of such studies, it is important to be able to integrate data collected at different length scales, ranging from the molecular level, crossing the dimensions of individual cells, and reaching the scale of tissues and organs (Sherman & Grosberg, 2019 ). Here we aimed at implementing such approach by combining protein data generated by fluorescence microscopy and Western Blot with the characterization of mechanical properties of single cells, while also assessing the collective dynamic behavior of the corresponding cell monolayers.…”
Section: Discussionmentioning
confidence: 99%
“…Some authors propose some guidelines for computing approaches [3,18], and promote graph theory as a good candidate for multi-scale reconstruction, though it has the potential for error propagation if there are errors in the graph structure. Indeed, the emphasis is on the initialization of links between variables, with a priori knowledge provided by experts in biology [3,19]. [20] shows that the most robust predictive models are created by coupling machine learning and multi-scale modelling.…”
Section: Introductionmentioning
confidence: 99%
“…In current multi-scale modelling methods, visualization is often used to represent biological knowledge as well as statistical findings from machine learning methods. However, it typically provides limited opportunities for biological experts to participate in the learning process, which hinders integrative biological research [3,19]. Indeed, the integration of human knowledge and expertise into machine learning is becoming increasingly popular across various domains and has proven to be effective [21].…”
Section: Introductionmentioning
confidence: 99%
“…To be useful in a clinical context, numerical simulation tools always have to strike a balance between high numerical accuracy and low computational effort ( 1 , 2 ). Especially modeling the human cardiac function in silico remains a challenging task: The multi-physics nature of the heart in combination with a multi-scale dimension in time and space claims high demands on computational cardiac modeling ( 3 , 4 ). As myocardial tension development and wall deformation drive the blood flow, the physical domains of cardiac continuum mechanics and fluid dynamics are of particular interest for the numerical reproduction of the pumping function of the human heart.…”
Section: Introductionmentioning
confidence: 99%