1
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Hilhorst PLJ, Quicken S, van de Vosse FN, Huberts W. Efficient sensitivity analysis for biomechanical models with correlated inputs. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2024; 40:e3797. [PMID: 38116742 DOI: 10.1002/cnm.3797] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 09/08/2023] [Accepted: 11/26/2023] [Indexed: 12/21/2023]
Abstract
In most variance-based sensitivity analysis (SA) approaches applied to biomechanical models, statistical independence of the model input is assumed. However, often the model inputs are correlated. This might alter the interpretation of the SA results, which may severely impact the guidance provided during model development and personalization. Potential reasons for the infrequent usage of SA techniques that account for input correlation are the associated high computational costs, especially for models with many parameters, and the fact that the input correlation structure is often unknown. The aim of this study was to propose an efficient correlated global sensitivity analysis method by applying a surrogate model-based approach. Furthermore, this article demonstrates how correlated SA should be interpreted and how the applied method can guide the modeler during model development and personalization, even when the correlation structure is not entirely known beforehand. The proposed methodology was applied to a typical example of a pulse wave propagation model and resulted in accurate SA results that could be obtained at a theoretically 27,000× lower computational cost compared to the correlated SA approach without employing a surrogate model. Furthermore, our results demonstrate that input correlations can significantly affect SA results, which emphasizes the need to thoroughly investigate the effect of input correlations during model development. We conclude that our proposed surrogate-based SA approach allows modelers to efficiently perform correlated SA to complex biomechanical models and allows modelers to focus on input prioritization, input fixing and model reduction, or assessing the dependency structure between parameters.
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Affiliation(s)
- Pjotr L J Hilhorst
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Sjeng Quicken
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Frans N van de Vosse
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Wouter Huberts
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
- CARIM School for Cardiovascular Diseases, Biomedical Engineering, Maastricht University, Maastricht, The Netherlands
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2
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Trayanova NA, Prakosa A. Up digital and personal: How heart digital twins can transform heart patient care. Heart Rhythm 2024; 21:89-99. [PMID: 37871809 PMCID: PMC10872898 DOI: 10.1016/j.hrthm.2023.10.019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Revised: 10/12/2023] [Accepted: 10/15/2023] [Indexed: 10/25/2023]
Abstract
Precision medicine is the vision of health care where therapy is tailored to each patient. As part of this vision, digital twinning technology promises to deliver a digital representation of organs or even patients by using tools capable of simulating personal health conditions and predicting patient or disease trajectories on the basis of relationships learned both from data and from biophysics knowledge. Such virtual replicas would update themselves with data from monitoring devices and medical tests and assessments, reflecting dynamically the changes in our health conditions and the responses to treatment. In precision cardiology, the concepts and initial applications of heart digital twins have slowly been gaining popularity and the trust of the clinical community. In this article, we review the advancement in heart digital twinning and its initial translation to the management of heart rhythm disorders.
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Affiliation(s)
- Natalia A Trayanova
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland.
| | - Adityo Prakosa
- Alliance for Cardiovascular Diagnostic and Treatment Innovation, Johns Hopkins University, Baltimore, Maryland
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3
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Liu MB, Ajijola OA. The promise of cardiac neuromodulation: can computational modelling bridge the gap? J Physiol 2023; 601:3693-3694. [PMID: 37535053 PMCID: PMC10529398 DOI: 10.1113/jp285309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 07/25/2023] [Indexed: 08/04/2023] Open
Affiliation(s)
- Michael B Liu
- Division of Cardiovascular Medicine, Stanford University, Palo Alto, CA, USA
| | - Olujimi A Ajijola
- UCLA Cardiac Arrhythmia Center, University of California, Los Angeles, CA, USA
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4
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Wang Y, Majumder R, Tian FB, Gao X. Editorial: Modeling of cardiovascular systems. Front Physiol 2022; 13:1094146. [DOI: 10.3389/fphys.2022.1094146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2022] [Accepted: 11/16/2022] [Indexed: 11/30/2022] Open
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5
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Aminian-Dehkordi J, Valiei A, Mofrad MRK. Emerging computational paradigms to address the complex role of gut microbial metabolism in cardiovascular diseases. Front Cardiovasc Med 2022; 9:987104. [PMID: 36299869 PMCID: PMC9589059 DOI: 10.3389/fcvm.2022.987104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
The human gut microbiota and its associated perturbations are implicated in a variety of cardiovascular diseases (CVDs). There is evidence that the structure and metabolic composition of the gut microbiome and some of its metabolites have mechanistic associations with several CVDs. Nevertheless, there is a need to unravel metabolic behavior and underlying mechanisms of microbiome-host interactions. This need is even more highlighted when considering that microbiome-secreted metabolites contributing to CVDs are the subject of intensive research to develop new prevention and therapeutic techniques. In addition to the application of high-throughput data used in microbiome-related studies, advanced computational tools enable us to integrate omics into different mathematical models, including constraint-based models, dynamic models, agent-based models, and machine learning tools, to build a holistic picture of metabolic pathological mechanisms. In this article, we aim to review and introduce state-of-the-art mathematical models and computational approaches addressing the link between the microbiome and CVDs.
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Affiliation(s)
| | | | - Mohammad R. K. Mofrad
- Department of Bioengineering and Mechanical Engineering, University of California, Berkeley, Berkeley, CA, United States
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6
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Linka K, Cavinato C, Humphrey JD, Cyron CJ. Predicting and understanding arterial elasticity from key microstructural features by bidirectional deep learning. Acta Biomater 2022; 147:63-72. [PMID: 35643194 DOI: 10.1016/j.actbio.2022.05.039] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Revised: 05/19/2022] [Accepted: 05/19/2022] [Indexed: 01/15/2023]
Abstract
Microstructural features and mechanical properties are closely related in all soft biological tissues. Both yet exhibit considerable inter-individual differences and are affected by factors such as aging and disease and its progression. Histological analysis, modern in situ imaging, and biomechanical testing have deepened our understanding of these complex interrelations, yet two key questions remain: (1) Given the specific microstructure, can one predict the macroscopic mechanical properties without mechanical testing? (2) Can one quantify individual contributions of the different microstructural features to the macroscopic mechanical properties in an automated, systematic and largely unbiased way? Here we propose a bidirectional deep learning architecture to address these two questions. Our architecture uses data from standard histological analyses, two-photon microscopy and biaxial biomechanical testing. Its capabilities are demonstrated by predicting with high accuracy (R2=0.92) the evolving mechanical properties of the murine aorta during maturation and aging. Moreover, our architecture reveals that the extracellular matrix composition and organization are the most prominent factors governing the macroscopic mechanical properties of the tissues studied herein. STATEMENT OF SIGNIFICANCE: .
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Affiliation(s)
- Kevin Linka
- Institute for Continuum and Material Mechanics, Hamburg University of Technology, Hamburg, Germany
| | - Cristina Cavinato
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA
| | - Jay D Humphrey
- Department of Biomedical Engineering, Yale University, New Haven, CT, USA; Vascular Biology and Therapeutics Program, Yale School of Medicine, New Haven, CT, USA
| | - Christian J Cyron
- Institute for Continuum and Material Mechanics, Hamburg University of Technology, Hamburg, Germany; Institute of Material Systems Modeling, Helmholtz-Zentrum Hereon, Geesthacht, Germany.
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7
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Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond. Ann Biomed Eng 2022; 50:615-627. [PMID: 35445297 DOI: 10.1007/s10439-022-02967-4] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Accepted: 04/07/2022] [Indexed: 12/13/2022]
Abstract
Recent progress in machine learning (ML), together with advanced computational power, have provided new research opportunities in cardiovascular modeling. While classifying patient outcomes and medical image segmentation with ML have already shown significant promising results, ML for the prediction of biomechanics such as blood flow or tissue dynamics is in its infancy. This perspective article discusses some of the challenges in using ML for replacing well-established physics-based models in cardiovascular biomechanics. Specifically, we discuss the large landscape of input features in 3D patient-specific modeling as well as the high-dimensional output space of field variables that vary in space and time. We argue that the end purpose of such ML models needs to be clearly defined and the tradeoff between the loss in accuracy and the gained speedup carefully interpreted in the context of translational modeling. We also discuss several exciting venues where ML could be strategically used to augment traditional physics-based modeling in cardiovascular biomechanics. In these applications, ML is not replacing physics-based modeling, but providing opportunities to solve ill-defined problems, improve measurement data quality, enable a solution to computationally expensive problems, and interpret complex spatiotemporal data by extracting hidden patterns. In summary, we suggest a strategic integration of ML in cardiovascular biomechanics modeling where the ML model is not the end goal but rather a tool to facilitate enhanced modeling.
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8
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Sarma H, Upadhyaya M, Gogoi B, Phukan M, Kashyap P, Das B, Devi R, Sharma HK. Cardiovascular Drugs: an Insight of In Silico Drug Design Tools. J Pharm Innov 2021. [DOI: 10.1007/s12247-021-09587-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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9
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Hallow KM, Van Brackle CH, Anjum S, Ermakov S. Cardiorenal Systems Modeling: Left Ventricular Hypertrophy and Differential Effects of Antihypertensive Therapies on Hypertrophy Regression. Front Physiol 2021; 12:679930. [PMID: 34220545 PMCID: PMC8242213 DOI: 10.3389/fphys.2021.679930] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Accepted: 05/25/2021] [Indexed: 12/11/2022] Open
Abstract
Cardiac and renal function are inextricably connected through both hemodynamic and neurohormonal mechanisms, and the interaction between these organ systems plays an important role in adaptive and pathophysiologic remodeling of the heart, as well as in the response to renally acting therapies. Insufficient understanding of the integrative function or dysfunction of these physiological systems has led to many examples of unexpected or incompletely understood clinical trial results. Mathematical models of heart and kidney physiology have long been used to better understand the function of these organs, but an integrated model of renal function and cardiac function and cardiac remodeling has not yet been published. Here we describe an integrated cardiorenal model that couples existing cardiac and renal models, and expands them to simulate cardiac remodeling in response to pressure and volume overload, as well as hypertrophy regression in response to angiotensin receptor blockers and beta-blockers. The model is able to reproduce different patterns of hypertrophy in response to pressure and volume overload. We show that increases in myocyte diameter are adaptive in pressure overload not only because it normalizes wall shear stress, as others have shown before, but also because it limits excess volume accumulation and further elevation of cardiac stresses by maintaining cardiac output and renal sodium and water balance. The model also reproduces the clinically observed larger LV mass reduction with angiotensin receptor blockers than with beta blockers. We further provide a mechanistic explanation for this difference by showing that heart rate lowering with beta blockers limits the reduction in peak systolic wall stress (a key signal for myocyte hypertrophy) relative to ARBs.
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Affiliation(s)
- K Melissa Hallow
- School of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, GA, United States
| | - Charles H Van Brackle
- School of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, GA, United States
| | - Sommer Anjum
- School of Chemical, Materials, and Biomedical Engineering, University of Georgia, Athens, GA, United States
| | - Sergey Ermakov
- Clinical Pharmacology, Modeling and Simulation, Amgen Inc., South San Francisco, CA, United States
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10
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Yin H, Arpino JM, Lee JJ, Pickering JG. Regenerated Microvascular Networks in Ischemic Skeletal Muscle. Front Physiol 2021; 12:662073. [PMID: 34177614 PMCID: PMC8231913 DOI: 10.3389/fphys.2021.662073] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2021] [Accepted: 05/10/2021] [Indexed: 12/24/2022] Open
Abstract
Skeletal muscle is the largest organ in humans. The viability and performance of this metabolically demanding organ are exquisitely dependent on the integrity of its microcirculation. The architectural and functional attributes of the skeletal muscle microvasculature are acquired during embryonic and early postnatal development. However, peripheral vascular disease in the adult can damage the distal microvasculature, together with damaging the skeletal myofibers. Importantly, adult skeletal muscle has the capacity to regenerate. Understanding the extent to which the microvascular network also reforms, and acquires structural and functional competence, will thus be critical to regenerative medicine efforts for those with peripheral artery disease (PAD). Herein, we discuss recent advances in studying the regenerating microvasculature in the mouse hindlimb following severe ischemic injury. We highlight new insights arising from real-time imaging of the microcirculation. This includes identifying otherwise hidden flaws in both network microarchitecture and function, deficiencies that could underlie the progressive nature of PAD and its refractoriness to therapy. Recognizing and overcoming these vulnerabilities in regenerative angiogenesis will be important for advancing treatment options for PAD.
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Affiliation(s)
- Hao Yin
- Robarts Research Institute, Western University, London, ON, Canada
| | | | - Jason J Lee
- Robarts Research Institute, Western University, London, ON, Canada.,Department of Medicine, Western University, London, ON, Canada
| | - J Geoffrey Pickering
- Robarts Research Institute, Western University, London, ON, Canada.,Department of Medicine, Western University, London, ON, Canada.,Department of Medical Biophysics, Western University, London, ON, Canada.,Department of Biochemistry, Western University, London, ON, Canada
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11
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A distributed lumped parameter model of blood flow with fluid-structure interaction. Biomech Model Mechanobiol 2021; 20:1659-1674. [PMID: 34076757 DOI: 10.1007/s10237-021-01468-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 05/17/2021] [Indexed: 12/22/2022]
Abstract
A distributed lumped parameter (DLP) model of blood flow was recently developed that can be simulated in minutes while still incorporating complex sources of energy dissipation in blood vessels. The aim of this work was to extend the previous DLP modeling framework to include fluid-structure interactions (DLP-FSI). This was done by using a simple compliance term to calculate pressure that does not increase the simulation complexity of the original DLP models. Verification and validation studies found DLP-FSI simulations had good agreement compared to analytical solutions of the wave equations, experimental measurements of pulsatile flow in elastic tubes, and in vivo MRI measurements of thoracic aortic flow. This new development of DLP-FSI allows for significantly improved computational efficiency of FSI simulations compared to FSI approaches that solve the full 3D conservation of mass and momentum equations while also including the complex sources of energy dissipation occurring in cardiovascular flows that other simplified models neglect.
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12
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DeMarco KR, Yang PC, Singh V, Furutani K, Dawson JRD, Jeng MT, Fettinger JC, Bekker S, Ngo VA, Noskov SY, Yarov-Yarovoy V, Sack JT, Wulff H, Clancy CE, Vorobyov I. Molecular determinants of pro-arrhythmia proclivity of d- and l-sotalol via a multi-scale modeling pipeline. J Mol Cell Cardiol 2021; 158:163-177. [PMID: 34062207 PMCID: PMC8906354 DOI: 10.1016/j.yjmcc.2021.05.015] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2020] [Revised: 05/03/2021] [Accepted: 05/24/2021] [Indexed: 11/20/2022]
Abstract
Drug isomers may differ in their proarrhythmia risk. An interesting example is the drug sotalol, an antiarrhythmic drug comprising d- and l- enantiomers that both block the hERG cardiac potassium channel and confer differing degrees of proarrhythmic risk. We developed a multi-scale in silico pipeline focusing on hERG channel – drug interactions and used it to probe and predict the mechanisms of pro-arrhythmia risks of the two enantiomers of sotalol. Molecular dynamics (MD) simulations predicted comparable hERG channel binding affinities for d- and l-sotalol, which were validated with electrophysiology experiments. MD derived thermodynamic and kinetic parameters were used to build multi-scale functional computational models of cardiac electrophysiology at the cell and tissue scales. Functional models were used to predict inactivated state binding affinities to recapitulate electrocardiogram (ECG) QT interval prolongation observed in clinical data. Our study demonstrates how modeling and simulation can be applied to predict drug effects from the atom to the rhythm for dl-sotalol and also increased proarrhythmia proclivity of d- vs. l-sotalol when accounting for stereospecific beta-adrenergic receptor blocking.
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Affiliation(s)
- Kevin R DeMarco
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA
| | - Pei-Chi Yang
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA
| | - Vikrant Singh
- Department of Pharmacology, University of California Davis, Davis, CA 95616, USA
| | - Kazuharu Furutani
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Pharmacology, Faculty of Pharmaceutical Sciences, Tokushima Bunri University, Tokushima, Tokushima 770-8514, Japan
| | - John R D Dawson
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Biophysics Graduate Group, University of California Davis, Davis, CA 95616, USA
| | - Mao-Tsuen Jeng
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA
| | - James C Fettinger
- Department of Chemistry, University of California Davis, Davis, CA 95616, USA
| | - Slava Bekker
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Science and Engineering, American River College, Sacramento, CA 95841, USA
| | - Van A Ngo
- Centre for Molecular Simulation and Biochemistry Research Cluster, Department of Biological Sciences, University of Calgary, Calgary, AB T2N1N4, Canada
| | - Sergei Y Noskov
- Centre for Molecular Simulation and Biochemistry Research Cluster, Department of Biological Sciences, University of Calgary, Calgary, AB T2N1N4, Canada
| | - Vladimir Yarov-Yarovoy
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Anesthesiology and Pain Medicine, University of California Davis, Davis, CA 95616, USA
| | - Jon T Sack
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Anesthesiology and Pain Medicine, University of California Davis, Davis, CA 95616, USA
| | - Heike Wulff
- Department of Pharmacology, University of California Davis, Davis, CA 95616, USA
| | - Colleen E Clancy
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Pharmacology, University of California Davis, Davis, CA 95616, USA
| | - Igor Vorobyov
- Department of Physiology and Membrane Biology, University of California Davis, Davis, CA 95616, USA; Department of Pharmacology, University of California Davis, Davis, CA 95616, USA.
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13
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Tretter F, Wolkenhauer O, Meyer-Hermann M, Dietrich JW, Green S, Marcum J, Weckwerth W. The Quest for System-Theoretical Medicine in the COVID-19 Era. Front Med (Lausanne) 2021; 8:640974. [PMID: 33855036 PMCID: PMC8039135 DOI: 10.3389/fmed.2021.640974] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2020] [Accepted: 02/17/2021] [Indexed: 12/15/2022] Open
Abstract
Precision medicine and molecular systems medicine (MSM) are highly utilized and successful approaches to improve understanding, diagnosis, and treatment of many diseases from bench-to-bedside. Especially in the COVID-19 pandemic, molecular techniques and biotechnological innovation have proven to be of utmost importance for rapid developments in disease diagnostics and treatment, including DNA and RNA sequencing technology, treatment with drugs and natural products and vaccine development. The COVID-19 crisis, however, has also demonstrated the need for systemic thinking and transdisciplinarity and the limits of MSM: the neglect of the bio-psycho-social systemic nature of humans and their context as the object of individual therapeutic and population-oriented interventions. COVID-19 illustrates how a medical problem requires a transdisciplinary approach in epidemiology, pathology, internal medicine, public health, environmental medicine, and socio-economic modeling. Regarding the need for conceptual integration of these different kinds of knowledge we suggest the application of general system theory (GST). This approach endorses an organism-centered view on health and disease, which according to Ludwig von Bertalanffy who was the founder of GST, we call Organismal Systems Medicine (OSM). We argue that systems science offers wider applications in the field of pathology and can contribute to an integrative systems medicine by (i) integration of evidence across functional and structural differentially scaled subsystems, (ii) conceptualization of complex multilevel systems, and (iii) suggesting mechanisms and non-linear relationships underlying the observed phenomena. We underline these points with a proposal on multi-level systems pathology including neurophysiology, endocrinology, immune system, genetics, and general metabolism. An integration of these areas is necessary to understand excess mortality rates and polypharmacological treatments. In the pandemic era this multi-level systems pathology is most important to assess potential vaccines, their effectiveness, short-, and long-time adverse effects. We further argue that these conceptual frameworks are not only valid in the COVID-19 era but also important to be integrated in a medicinal curriculum.
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Affiliation(s)
- Felix Tretter
- Bertalanffy Center for the Study of Systems Science, Vienna, Austria
| | - Olaf Wolkenhauer
- Department of Systems Biology & Bioinformatics, University of Rostock, Rostock, Germany
| | - Michael Meyer-Hermann
- Department of Systems Immunology and Braunschweig Integrated Centre of Systems Biology, Helmholtz Centre for Infection Research, Braunschweig, Germany
| | - Johannes W Dietrich
- Endocrine Research, Medical Hospital I, Bergmannsheil University Hospitals, Ruhr University of Bochum, Bochum, Germany.,Ruhr Center for Rare Diseases (CeSER), Ruhr University of Bochum, Witten/Herdecke University, Bochum, Germany
| | - Sara Green
- Section for History and Philosophy of Science, Department of Science Education, University of Copenhagen, Copenhagen, Denmark
| | - James Marcum
- Department of Philosophy, Baylor University, Waco, TX, United States
| | - Wolfram Weckwerth
- Molecular Systems Biology (MOSYS), University of Vienna, Vienna, Austria.,Vienna Metabolomics Center (VIME), University of Vienna, Vienna, Austria
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14
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Myocardial Perfusion Simulation for Coronary Artery Disease: A Coupled Patient-Specific Multiscale Model. Ann Biomed Eng 2020; 49:1432-1447. [PMID: 33263155 PMCID: PMC8057976 DOI: 10.1007/s10439-020-02681-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Accepted: 10/25/2020] [Indexed: 11/26/2022]
Abstract
Patient-specific models of blood flow are being used clinically to diagnose and plan treatment for coronary artery disease. A remaining challenge is bridging scales from flow in arteries to the micro-circulation supplying the myocardium. Previously proposed models are descriptive rather than predictive and have not been applied to human data. The goal here is to develop a multiscale patient-specific model enabling blood flow simulation from large coronary arteries to myocardial tissue. Patient vasculatures are segmented from coronary computed tomography angiography data and extended from the image-based model down to the arteriole level using a space-filling forest of synthetic trees. Blood flow is modeled by coupling a 1D model of the coronary arteries to a single-compartment Darcy myocardium model. Simulated results on five patients with non-obstructive coronary artery disease compare overall well to [\documentclass[12pt]{minimal}
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\begin{document}$$\text {H}_{{2}}$$\end{document}H2O PET exam data for both resting and hyperemic conditions. Results on a patient with severe obstructive disease link coronary artery narrowing with impaired myocardial blood flow, demonstrating the model’s ability to predict myocardial regions with perfusion deficit. This is the first report of a computational model for simulating blood flow from the epicardial coronary arteries to the left ventricle myocardium applied to and validated on human data.
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15
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Glass L. Using mathematics to diagnose, cure, and predict cardiac arrhythmia. CHAOS (WOODBURY, N.Y.) 2020; 30:113132. [PMID: 33261334 DOI: 10.1063/5.0021844] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2020] [Accepted: 10/14/2020] [Indexed: 06/12/2023]
Abstract
Mathematics can be used to analyze and model cardiac arrhythmia. I discuss three different problems. (1) Diagnosis of atrial fibrillation based on the time intervals between subsequent beats. The probability density histograms of the differences of the intervals between consecutive beats have characteristic shapes for atrial fibrillation. (2) Curing atrial fibrillation by ablation of the core of rotors. Recent clinical studies have proposed that ablating the core of rotors in atrial tissue can cure atrial fibrillation. However, the claims are controversial. One problem that arises relates to difficulties associated with developing algorithms to identify the core of rotors. In model tissue culture systems, heterogeneity in the structure makes it difficult to unambiguously locate the core of rotors. (3) Risk stratification for sudden cardiac death (SCD). Despite numerous clinical studies, there is still a need for improved criteria to assess the risk of SCD. I discuss the possibility of using the dynamics of premature ventricular complexes to help make predictions. The development of wearable devices to record and analyze cardiac rhythms offers new prospects for the diagnosis and treatment of cardiac arrhythmia.
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Affiliation(s)
- Leon Glass
- Department of Physiology, McGill University, 3655 Promenade Sir William Osler, Montreal, Quebec H3G 1Y6, Canada
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16
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Virot E, Spandan V, Niu L, van Rees WM, Mahadevan L. Elastohydrodynamic Scaling Law for Heart Rates. PHYSICAL REVIEW LETTERS 2020; 125:058102. [PMID: 32794888 DOI: 10.1103/physrevlett.125.058102] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Accepted: 06/04/2020] [Indexed: 06/11/2023]
Abstract
Animal hearts are soft shells that actively pump blood to oxygenate tissues. Here, we propose an allometric scaling law for the heart rate based on the idea of elastohydrodynamic resonance of a fluid-loaded soft active elastic shell that buckles and contracts axially when twisted periodically. We show that this picture is consistent with numerical simulations of soft cylindrical shells that twist-buckle while pumping a viscous fluid, yielding optimum ejection fractions of 35%-40% when driven resonantly. Our scaling law is consistent with experimental measurements of heart rates over 2 orders of magnitude, and provides a mechanistic basis for how metabolism scales with organism size. In addition to providing a physical rationale for the heart rate and metabolism of an organism, our results suggest a simple design principle for soft fluidic pumps.
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Affiliation(s)
- E Virot
- John A. Paulson School of Engineering and Applied Sciences, Harvard University
| | - V Spandan
- John A. Paulson School of Engineering and Applied Sciences, Harvard University
| | - L Niu
- Department of Physics, Harvard University, Cambridge, Massachusetts 02139, USA
| | - W M van Rees
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02138, USA
| | - L Mahadevan
- John A. Paulson School of Engineering and Applied Sciences, Harvard University
- Department of Physics, Harvard University, Cambridge, Massachusetts 02139, USA
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts 02138, USA
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17
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Lin X, Li X, Lin X. A Review on Applications of Computational Methods in Drug Screening and Design. Molecules 2020; 25:E1375. [PMID: 32197324 PMCID: PMC7144386 DOI: 10.3390/molecules25061375] [Citation(s) in RCA: 217] [Impact Index Per Article: 54.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 03/16/2020] [Accepted: 03/16/2020] [Indexed: 12/27/2022] Open
Abstract
Drug development is one of the most significant processes in the pharmaceutical industry. Various computational methods have dramatically reduced the time and cost of drug discovery. In this review, we firstly discussed roles of multiscale biomolecular simulations in identifying drug binding sites on the target macromolecule and elucidating drug action mechanisms. Then, virtual screening methods (e.g., molecular docking, pharmacophore modeling, and QSAR) as well as structure- and ligand-based classical/de novo drug design were introduced and discussed. Last, we explored the development of machine learning methods and their applications in aforementioned computational methods to speed up the drug discovery process. Also, several application examples of combining various methods was discussed. A combination of different methods to jointly solve the tough problem at different scales and dimensions will be an inevitable trend in drug screening and design.
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Affiliation(s)
- Xiaoqian Lin
- Institute of Single Cell Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing 100191, China;
- School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
| | - Xiu Li
- School of Chemistry and Material Science, Shanxi Normal University, Linfen 041004, China;
| | - Xubo Lin
- Institute of Single Cell Engineering, Beijing Advanced Innovation Center for Biomedical Engineering, Beihang University, Beijing 100191, China;
- School of Biological Science and Medical Engineering, Beihang University, Beijing 100191, China
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18
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Labarrere CA, Dabiri AE, Kassab GS. Thrombogenic and Inflammatory Reactions to Biomaterials in Medical Devices. Front Bioeng Biotechnol 2020; 8:123. [PMID: 32226783 PMCID: PMC7080654 DOI: 10.3389/fbioe.2020.00123] [Citation(s) in RCA: 45] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Accepted: 02/10/2020] [Indexed: 12/17/2022] Open
Abstract
Blood-contacting medical devices of different biomaterials are often used to treat various cardiovascular diseases. Thrombus formation is a common cause of failure of cardiovascular devices. Currently, there are no clinically available biomaterials that can totally inhibit thrombosis under the more challenging environments (e.g., low flow in the venous system). Although some biomaterials reduce protein adsorption or cell adhesion, the issue of biomaterial associated with thrombosis and inflammation still exists. To better understand how to develop more thrombosis-resistant medical devices, it is essential to understand the biology and mechano-transduction of thrombus nucleation and progression. In this review, we will compare the mechanisms of thrombus development and progression in the arterial and venous systems. We will address various aspects of thrombosis, starting with biology of thrombosis, mathematical modeling to integrate the mechanism of thrombosis, and thrombus formation on medical devices. Prevention of these problems requires a multifaceted approach that involves more effective and safer thrombolytic agents but more importantly the development of novel thrombosis-resistant biomaterials mimicking the biological characteristics of the endothelium and extracellular matrix tissues that also ameliorate the development and the progression of chronic inflammation as part of the processes associated with the detrimental generation of late thrombosis and neo-atherosclerosis. Until such developments occur, engineers and clinicians must work together to develop devices that require minimal anticoagulants and thrombolytics to mitigate thrombosis and inflammation without causing serious bleeding side effects.
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Affiliation(s)
| | - Ali E Dabiri
- California Medical Innovations Institute, San Diego, CA, United States
| | - Ghassan S Kassab
- California Medical Innovations Institute, San Diego, CA, United States
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19
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Pewowaruk RJ, Philip JL, Tewari SG, Chen CS, Nyaeme MS, Wang Z, Tabima DM, Baker AJ, Beard DA, Chesler NC. Multiscale Computational Analysis of Right Ventricular Mechanoenergetics. J Biomech Eng 2019; 140:2679646. [PMID: 30003251 DOI: 10.1115/1.4040044] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2017] [Indexed: 11/08/2022]
Abstract
Right ventricular (RV) failure, which occurs in the setting of pressure overload, is characterized by abnormalities in mechanical and energetic function. The effects of these cell- and tissue-level changes on organ-level RV function are unknown. The primary aim of this study was to investigate the effects of myofiber mechanics and mitochondrial energetics on organ-level RV function in the context of pressure overload using a multiscale model of the cardiovascular system. The model integrates the mitochondria-generated metabolite concentrations that drive intracellular actin-myosin cross-bridging and extracellular myocardial tissue mechanics in a biventricular heart model coupled with simple lumped parameter circulations. Three types of pressure overload were simulated and compared to experimental results. The computational model was able to capture a wide range of cardiovascular physiology and pathophysiology from mild RV dysfunction to RV failure. Our results confirm that, in response to pressure overload alone, the RV is able to maintain cardiac output (CO) and predict that alterations in either RV active myofiber mechanics or RV metabolite concentrations are necessary to decrease CO.
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Affiliation(s)
- Ryan J Pewowaruk
- Mem. ASME Biomedical Engineering, University of Wisconsin-Madison, 2145 Engineering Centers Building, 1550 Engineering Drive, Madison, WI 53706 e-mail:
| | - Jennifer L Philip
- Surgery, University of Wisconsin-Madison, , 1550 Engineering Drive, Madison, WI 53706 e-mail:
| | - Shivendra G Tewari
- Molecular & Integrative Physiology, University of Michigan-Ann Arbor, , North Campus Research Center, Ann Arbor, MI 48109-5622 e-mail:
| | - Claire S Chen
- Mechanical Engineering, University of Wisconsin-Madison, , 1550 Engineering Drive, Madison, WI 53706 e-mail:
| | - Mark S Nyaeme
- Biomedical Engineering, University of Wisconsin-Madison, , 1550 Engineering Drive, Madison, WI 53706 e-mail:
| | - Zhijie Wang
- Mechanical Engineering, Colorado State University, , Fort Collins, CO 80521 e-mail:
| | - Diana M Tabima
- Biomedical Engineering, University of Wisconsin-Madison, , 1550 Engineering Drive, Madison, WI 53706 e-mail:
| | - Anthony J Baker
- Medicine, University of California-San Francisco, , San Francisco, CA 94121; VA Medical Center, 4150 Clement St., San Francisco, CA 94121 e-mail:
| | - Daniel A Beard
- Molecular & Integrative Physiology, University of Michigan-Ann Arbor, , North Campus Research Center, Ann Arbor, MI 48109-5622 e-mail:
| | - Naomi C Chesler
- Fellow ASME Biomedical Engineering, University of Wisconsin-Madison Medicine, , 1550 Engineering Drive, Madison, WI 53706 e-mail:
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20
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RAMEZANPOUR MEHDI, MAEREFAT MEHDI, RAMEZANPOUR NAHID, MOKHTARI-DIZAJI MANIJHE, ROSHANALI FARIDEH, NEZAMI FARHADRIKHTEGAR. NUMERICAL INVESTIGATION OF THE EFFECTS OF BED SHAPE ON THE END-TO-SIDE CABG HEMODYNAMICS. J MECH MED BIOL 2019. [DOI: 10.1142/s0219519419500192] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Disrupted flow initiates and aggravates intimal thickening in the end-to-side (ETS) coronary artery bypass grafting (CABG), which may lead to failure. To enhance the post-intervention hemodynamics, the geometry is either optimized or totally reconfigured. Majority of configurations proposed by researchers have not suited CABG surgery, for they entailed rigorous manipulation on conventional grafts in situ, which was neither swift nor straightforward. The aim of the present study is, thus, to introduce a slight, yet effective, modification to a conventional ETS CABG configuration, and numerically investigate its effects on updated hemodynamic and structural environment, anticipating the longevity of proposed configuration and CABG success. This fairly simple modification may easily be made positioning a pre-designed anastomotic device between the bed of host artery in the conventional ETS CABG and its surrounding tissues. Conducting comprehensive numerical simulations, performance of the proposed configuration was assessed using idealized and patient-specific geometries of the conventional ETS CABG. Blood flow was simulated in a conventional and an updated CABG configuration considering 2-way fluid–structure interaction. Results revealed that, although the proposed configuration may induce higher structural stresses in vessels walls, it may improve important hemodynamic metrics such as wall shear stress gradient, oscillatory shear index, and relative residence time on host artery bed reducing disruption of flow. This study may also set the stage for design engineers and regulatory officials to evolve ETS CABG toward more hemodynamics-friendly approaches. Further in vitro, preclinical, and clinical experiments are, yet, entailed to accomplish ideal designs of procedural guidelines/grafts.
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Affiliation(s)
- MEHDI RAMEZANPOUR
- Department of Mechanical Engineering, Tarbiat Modares University, Tehran, P. O. Box 14115-143, Iran
| | - MEHDI MAEREFAT
- Department of Mechanical Engineering, Tarbiat Modares University, Tehran, P. O. Box 14115-143, Iran
| | - NAHID RAMEZANPOUR
- Medical Biotechnology Research Center, Faculty of Paramedicine, Guilan, University of Medical Sciences, Rasht, P. O. Box 41887-94755, Iran
| | | | - FARIDEH ROSHANALI
- Department of Cardiac Surgery, Day General Hospital, Valiasr Street, Tehran, Iran
| | - FARHAD RIKHTEGAR NEZAMI
- Institute for Medical Engineering and Science, Massachusetts Institute of Technology, 77 Mass. Ave., Cambridge, Massachusetts, US
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21
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Kudaibergenova M, Perissinotti LL, Noskov SY. Lipid roles in hERG function and interactions with drugs. Neurosci Lett 2019; 700:70-77. [DOI: 10.1016/j.neulet.2018.05.019] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 05/08/2018] [Accepted: 05/11/2018] [Indexed: 01/29/2023]
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22
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Zhou S, Xu L, Hao L, Xiao H, Yao Y, Qi L, Yao Y. A review on low-dimensional physics-based models of systemic arteries: application to estimation of central aortic pressure. Biomed Eng Online 2019; 18:41. [PMID: 30940144 PMCID: PMC6446386 DOI: 10.1186/s12938-019-0660-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2018] [Accepted: 03/26/2019] [Indexed: 12/16/2022] Open
Abstract
The physiological processes and mechanisms of an arterial system are complex and subtle. Physics-based models have been proven to be a very useful tool to simulate actual physiological behavior of the arteries. The current physics-based models include high-dimensional models (2D and 3D models) and low-dimensional models (0D, 1D and tube-load models). High-dimensional models can describe the local hemodynamic information of arteries in detail. With regard to an exact model of the whole arterial system, a high-dimensional model is computationally impracticable since the complex geometry, viscosity or elastic properties and complex vectorial output need to be provided. For low-dimensional models, the structure, centerline and viscosity or elastic properties only need to be provided. Therefore, low-dimensional modeling with lower computational costs might be a more applicable approach to represent hemodynamic properties of the entire arterial system and these three types of low-dimensional models have been extensively used in the study of cardiovascular dynamics. In recent decades, application of physics-based models to estimate central aortic pressure has attracted increasing interest. However, to our best knowledge, there has been few review paper about reconstruction of central aortic pressure using these physics-based models. In this paper, three types of low-dimensional physical models (0D, 1D and tube-load models) of systemic arteries are reviewed, the application of three types of models on estimation of central aortic pressure is taken as an example to discuss their advantages and disadvantages, and the proper choice of models for specific researches and applications are advised.
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Affiliation(s)
- Shuran Zhou
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110819 China
| | - Lisheng Xu
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110819 China
- Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang, 110167 China
| | - Liling Hao
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110819 China
| | - Hanguang Xiao
- Chongqing Key Laboratory of Modern Photoelectric Detection Technology and Instrument, School of Optoelectronic Information, Chongqing University of Technology, Chongqing, 400054 China
| | - Yang Yao
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110819 China
| | - Lin Qi
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110819 China
| | - Yudong Yao
- Sino-Dutch Biomedical and Information Engineering School, Northeastern University, Shenyang, 110819 China
- Neusoft Research of Intelligent Healthcare Technology, Co. Ltd., Shenyang, 110167 China
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23
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Savoji H, Mohammadi MH, Rafatian N, Toroghi MK, Wang EY, Zhao Y, Korolj A, Ahadian S, Radisic M. Cardiovascular disease models: A game changing paradigm in drug discovery and screening. Biomaterials 2019; 198:3-26. [PMID: 30343824 PMCID: PMC6397087 DOI: 10.1016/j.biomaterials.2018.09.036] [Citation(s) in RCA: 113] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 09/11/2018] [Accepted: 09/22/2018] [Indexed: 02/06/2023]
Abstract
Cardiovascular disease is the leading cause of death worldwide. Although investment in drug discovery and development has been sky-rocketing, the number of approved drugs has been declining. Cardiovascular toxicity due to therapeutic drug use claims the highest incidence and severity of adverse drug reactions in late-stage clinical development. Therefore, to address this issue, new, additional, replacement and combinatorial approaches are needed to fill the gap in effective drug discovery and screening. The motivation for developing accurate, predictive models is twofold: first, to study and discover new treatments for cardiac pathologies which are leading in worldwide morbidity and mortality rates; and second, to screen for adverse drug reactions on the heart, a primary risk in drug development. In addition to in vivo animal models, in vitro and in silico models have been recently proposed to mimic the physiological conditions of heart and vasculature. Here, we describe current in vitro, in vivo, and in silico platforms for modelling healthy and pathological cardiac tissues and their advantages and disadvantages for drug screening and discovery applications. We review the pathophysiology and the underlying pathways of different cardiac diseases, as well as the new tools being developed to facilitate their study. We finally suggest a roadmap for employing these non-animal platforms in assessing drug cardiotoxicity and safety.
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Affiliation(s)
- Houman Savoji
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, 170 College St, Toronto, Ontario, M5S 3G9, Canada; Toronto General Research Institute, University Health Network, University of Toronto, 200 Elizabeth St, Toronto, Ontario, M5G 2C4, Canada
| | - Mohammad Hossein Mohammadi
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, 170 College St, Toronto, Ontario, M5S 3G9, Canada; Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College St, Toronto, Ontario, M5S 3E5, Canada; Toronto General Research Institute, University Health Network, University of Toronto, 200 Elizabeth St, Toronto, Ontario, M5G 2C4, Canada
| | - Naimeh Rafatian
- Toronto General Research Institute, University Health Network, University of Toronto, 200 Elizabeth St, Toronto, Ontario, M5G 2C4, Canada
| | - Masood Khaksar Toroghi
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College St, Toronto, Ontario, M5S 3E5, Canada
| | - Erika Yan Wang
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, 170 College St, Toronto, Ontario, M5S 3G9, Canada
| | - Yimu Zhao
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, 170 College St, Toronto, Ontario, M5S 3G9, Canada; Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College St, Toronto, Ontario, M5S 3E5, Canada
| | - Anastasia Korolj
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, 170 College St, Toronto, Ontario, M5S 3G9, Canada; Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College St, Toronto, Ontario, M5S 3E5, Canada
| | - Samad Ahadian
- Toronto General Research Institute, University Health Network, University of Toronto, 200 Elizabeth St, Toronto, Ontario, M5G 2C4, Canada
| | - Milica Radisic
- Institute of Biomaterials and Biomedical Engineering, University of Toronto, 170 College St, Toronto, Ontario, M5S 3G9, Canada; Department of Chemical Engineering and Applied Chemistry, University of Toronto, 200 College St, Toronto, Ontario, M5S 3E5, Canada; Toronto General Research Institute, University Health Network, University of Toronto, 200 Elizabeth St, Toronto, Ontario, M5G 2C4, Canada.
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24
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Santiago A, Aguado-Sierra J, Zavala-Aké M, Doste-Beltran R, Gómez S, Arís R, Cajas JC, Casoni E, Vázquez M. Fully coupled fluid-electro-mechanical model of the human heart for supercomputers. INTERNATIONAL JOURNAL FOR NUMERICAL METHODS IN BIOMEDICAL ENGINEERING 2018; 34:e3140. [PMID: 30117302 DOI: 10.1002/cnm.3140] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/31/2017] [Revised: 04/28/2018] [Accepted: 07/22/2018] [Indexed: 05/12/2023]
Abstract
In this work, we present a fully coupled fluid-electro-mechanical model of a 50th percentile human heart. The model is implemented on Alya, the BSC multi-physics parallel code, capable of running efficiently in supercomputers. Blood in the cardiac cavities is modeled by the incompressible Navier-Stokes equations and an arbitrary Lagrangian-Eulerian (ALE) scheme. Electrophysiology is modeled with a monodomain scheme and the O'Hara-Rudy cell model. Solid mechanics is modeled with a total Lagrangian formulation for discrete strains using the Holzapfel-Ogden cardiac tissue material model. The three problems are simultaneously and bidirectionally coupled through an electromechanical feedback and a fluid-structure interaction scheme. In this paper, we present the scheme in detail and propose it as a computational cardiac workbench.
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Affiliation(s)
- Alfonso Santiago
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Jazmín Aguado-Sierra
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Miguel Zavala-Aké
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | | | - Samuel Gómez
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Ruth Arís
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Juan C Cajas
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Eva Casoni
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), Barcelona, Spain
| | - Mariano Vázquez
- Department of Computer Applications in Science and Engineering, Barcelona Supercomputing Center (BSC), Barcelona, Spain
- Instituto de Investigación en Inteligencia Artificial (IIIA), Consejo Superior de Investigaciones Científicas (CSIC), Barcelona, Spain
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25
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Garbey M, Casarin S, Berceli SA. A versatile hybrid agent-based, particle and partial differential equations method to analyze vascular adaptation. Biomech Model Mechanobiol 2018; 18:29-44. [PMID: 30094656 PMCID: PMC6373284 DOI: 10.1007/s10237-018-1065-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2018] [Accepted: 07/26/2018] [Indexed: 11/27/2022]
Abstract
Peripheral arterial occlusive disease is a chronic pathology affecting at least 8–12 million people in the USA, typically treated with a vein graft bypass or through the deployment of a stent in order to restore the physiological circulation. Failure of peripheral endovascular interventions occurs at the intersection of vascular biology, biomechanics, and clinical decision making. It is our hypothesis that the majority of endovascular treatment approaches share the same driving mechanisms and that a deep understanding of the adaptation process is pivotal in order to improve the current outcome of the procedure. The postsurgical adaptation of vein graft bypasses offers the perfect example of how the balance between intimal hyperplasia and wall remodeling determines the failure or the success of the intervention. Accordingly, this work presents a versatile computational model able to capture the feedback loop that describes the interaction between events at cellular/tissue level and mechano-environmental conditions. The work here presented is a generalization and an improvement of a previous work by our group of investigators, where an agent-based model uses a cellular automata principle on a fixed hexagonal grid to reproduce the leading events of the graft’s restenosis. The new hybrid model here presented allows a more realistic simulation both of the biological laws that drive the cellular behavior and of the active role of the membranes that separate the various layers of the vein. The novel feature is to use an immersed boundary implementation of a highly viscous flow to represent SMC motility and matrix reorganization in response to graft adaptation. Our implementation is modular, and this makes us able to choose the right compromise between closeness to the physiological reality and complexity of the model. The focus of this paper is to offer a new modular implementation that combines the best features of an agent-based model, continuum mechanics, and particle-tracking methods to cope with the multiscale nature of the adaptation phenomena. This hybrid method allows us to quickly test various hypotheses with a particular attention to cellular motility, a process that we demonstrated should be driven by mechanical homeostasis in order to maintain the right balance between cells and extracellular matrix in order to reproduce a distribution similar to histological experimental data from vein grafts.
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Affiliation(s)
- Marc Garbey
- Houston Methodist Research Institute, Houston, TX, USA. .,Department of Surgery, Houston Methodist Hospital, Houston, TX, USA. .,LaSIE, UMR CNRS 7356, University of la Rochelle, La Rochelle, France.
| | - Stefano Casarin
- Houston Methodist Research Institute, Houston, TX, USA.,LaSIE, UMR CNRS 7356, University of la Rochelle, La Rochelle, France
| | - Scott A Berceli
- Department of Surgery, University of Florida, Gainesville, FL, USA.,Malcom Randall VAMC, Gainesville, FL, USA
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26
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Philip JL, Pewowaruk RJ, Chen CS, Tabima DM, Beard DA, Baker AJ, Chesler NC. Impaired Myofilament Contraction Drives Right Ventricular Failure Secondary to Pressure Overload: Model Simulations, Experimental Validation, and Treatment Predictions. Front Physiol 2018; 9:731. [PMID: 29997518 PMCID: PMC6030352 DOI: 10.3389/fphys.2018.00731] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2018] [Accepted: 05/25/2018] [Indexed: 12/31/2022] Open
Abstract
Introduction: Pulmonary hypertension (PH) causes pressure overload leading to right ventricular failure (RVF). Myocardial structure and myocyte mechanics are altered in RVF but the direct impact of these cellular level factors on organ level function remain unclear. A computational model of the cardiovascular system that integrates cellular function into whole organ function has recently been developed. This model is a useful tool for investigating how changes in myocyte structure and mechanics contribute to organ function. We use this model to determine how measured changes in myocyte and myocardial mechanics contribute to RVF at the organ level and predict the impact of myocyte-targeted therapy. Methods: A multiscale computational framework was tuned to model PH due to bleomycin exposure in mice. Pressure overload was modeled by increasing the pulmonary vascular resistance (PVR) and decreasing pulmonary artery compliance (CPA). Myocardial fibrosis and the impairment of myocyte maximum force generation (Fmax) were simulated by increasing the collagen content (↑PVR + ↓CPA + fibrosis) and decreasing Fmax (↑PVR + ↓CPA + fibrosis + ↓Fmax). A61603 (A6), a selective α1A-subtype adrenergic receptor agonist, shown to improve Fmax was simulated to explore targeting myocyte generated Fmax in PH. Results: Increased afterload (RV systolic pressure and arterial elastance) in simulations matched experimental results for bleomycin exposure. Pressure overload alone (↑PVR + ↓CPA) caused decreased RV ejection fraction (EF) similar to experimental findings but preservation of cardiac output (CO). Myocardial fibrosis in the setting of pressure overload (↑PVR + ↓PAC + fibrosis) had minimal impact compared to pressure overload alone. Including impaired myocyte function (↑PVR + ↓PAC + fibrosis + ↓Fmax) reduced CO, similar to experiment, and impaired EF. Simulations predicted that A6 treatment preserves EF and CO despite maintained RV pressure overload. Conclusion: Multiscale computational modeling enabled prediction of the contribution of cellular level changes to whole organ function. Impaired Fmax is a key feature that directly contributes to RVF. Simulations further demonstrate the therapeutic benefit of targeting Fmax, which warrants additional study. Future work should incorporate growth and remodeling into the computational model to enable prediction of the multiscale drivers of the transition from dysfunction to failure.
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Affiliation(s)
- Jennifer L. Philip
- Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States
- Department of Surgery, University of Wisconsin–Madison, Madison, WI, United States
| | - Ryan J. Pewowaruk
- Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States
| | - Claire S. Chen
- Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, WI, United States
| | - Diana M. Tabima
- Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States
| | - Daniel A. Beard
- Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, United States
| | - Anthony J. Baker
- San Francisco Veterans Affairs Medical Center, San Francisco, CA, United States
- Department of Medicine, University of California, San Francisco, San Francisco, CA, United States
| | - Naomi C. Chesler
- Department of Biomedical Engineering, University of Wisconsin–Madison, Madison, WI, United States
- Department of Mechanical Engineering, University of Wisconsin–Madison, Madison, WI, United States
- Department of Medicine, University of Wisconsin–Madison, Madison, WI, United States
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27
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Owen B, Bojdo N, Jivkov A, Keavney B, Revell A. Structural modelling of the cardiovascular system. Biomech Model Mechanobiol 2018; 17:1217-1242. [PMID: 29911296 PMCID: PMC6154127 DOI: 10.1007/s10237-018-1024-9] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2017] [Accepted: 04/25/2018] [Indexed: 02/02/2023]
Abstract
Computational modelling of the cardiovascular system offers much promise, but represents a truly interdisciplinary challenge, requiring knowledge of physiology, mechanics of materials, fluid dynamics and biochemistry. This paper aims to provide a summary of the recent advances in cardiovascular structural modelling, including the numerical methods, main constitutive models and modelling procedures developed to represent cardiovascular structures and pathologies across a broad range of length and timescales; serving as an accessible point of reference to newcomers to the field. The class of so-called hyperelastic materials provides the theoretical foundation for the modelling of how these materials deform under load, and so an overview of these models is provided; comparing classical to application-specific phenomenological models. The physiology is split into components and pathologies of the cardiovascular system and linked back to constitutive modelling developments, identifying current state of the art in modelling procedures from both clinical and engineering sources. Models which have originally been derived for one application and scale are shown to be used for an increasing range and for similar applications. The trend for such approaches is discussed in the context of increasing availability of high performance computing resources, where in some cases computer hardware can impact the choice of modelling approach used.
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Affiliation(s)
- Benjamin Owen
- School of Mechanical, Aerospace and Civil Engineering, University of Manchester, George Begg Building, Manchester, M1 3BB, UK.
| | - Nicholas Bojdo
- School of Mechanical, Aerospace and Civil Engineering, University of Manchester, George Begg Building, Manchester, M1 3BB, UK
| | - Andrey Jivkov
- School of Mechanical, Aerospace and Civil Engineering, University of Manchester, George Begg Building, Manchester, M1 3BB, UK
| | - Bernard Keavney
- Division of Cardiovascular Sciences, University of Manchester, AV Hill Building, Manchester, M13 9PT, UK
| | - Alistair Revell
- School of Mechanical, Aerospace and Civil Engineering, University of Manchester, George Begg Building, Manchester, M1 3BB, UK
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Mattson JM, Zhang Y. Structural and Functional Differences Between Porcine Aorta and Vena Cava. J Biomech Eng 2018; 139:2612941. [PMID: 28303272 DOI: 10.1115/1.4036261] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Indexed: 12/14/2022]
Abstract
Elastin and collagen fibers are the major load-bearing extracellular matrix (ECM) constituents of the vascular wall. Arteries function differently than veins in the circulatory system; however as a result from several treatment options, veins are subjected to sudden elevated arterial pressure. It is thus important to recognize the fundamental structure and function differences between a vein and an artery. Our research compared the relationship between biaxial mechanical function and ECM structure of porcine thoracic aorta and inferior vena cava. Our study suggests that aorta contains slightly more elastin than collagen due to the cyclical extensibility, but vena cava contains almost four times more collagen than elastin to maintain integrity. Furthermore, multiphoton imaging of vena cava showed longitudinally oriented elastin and circumferentially oriented collagen that is recruited at supraphysiologic stress, but low levels of strain. However in aorta, elastin is distributed uniformly, and the primarily circumferentially oriented collagen is recruited at higher levels of strain than vena cava. These structural observations support the functional finding that vena cava is highly anisotropic with the longitude being more compliant and the circumference stiffening substantially at low levels of strain. Overall, our research demonstrates that fiber distributions and recruitment should be considered in addition to relative collagen and elastin contents. Also, the importance of accounting for the structural and functional differences between arteries and veins should be taken into account when considering disease treatment options.
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Affiliation(s)
- Jeffrey M Mattson
- Department of Mechanical Engineering, Boston University, Boston, MA 02215 e-mail:
| | - Yanhang Zhang
- Department of Mechanical Engineering, Department of Biomedical Engineering, Boston University, 110 Cummington Mall, Boston, MA 02215 e-mail:
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Krogh-Madsen T, Jacobson AF, Ortega FA, Christini DJ. Global Optimization of Ventricular Myocyte Model to Multi-Variable Objective Improves Predictions of Drug-Induced Torsades de Pointes. Front Physiol 2017; 8:1059. [PMID: 29311985 PMCID: PMC5742183 DOI: 10.3389/fphys.2017.01059] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2017] [Accepted: 12/04/2017] [Indexed: 01/22/2023] Open
Abstract
In silico cardiac myocyte models present powerful tools for drug safety testing and for predicting phenotypical consequences of ion channel mutations, but their accuracy is sometimes limited. For example, several models describing human ventricular electrophysiology perform poorly when simulating effects of long QT mutations. Model optimization represents one way of obtaining models with stronger predictive power. Using a recent human ventricular myocyte model, we demonstrate that model optimization to clinical long QT data, in conjunction with physiologically-based bounds on intracellular calcium and sodium concentrations, better constrains model parameters. To determine if the model optimized to congenital long QT data better predicts risk of drug-induced long QT arrhythmogenesis, in particular Torsades de Pointes risk, we tested the optimized model against a database of known arrhythmogenic and non-arrhythmogenic ion channel blockers. When doing so, the optimized model provided an improved risk assessment. In particular, we demonstrate an elimination of false-positive outcomes generated by the baseline model, in which simulations of non-torsadogenic drugs, in particular verapamil, predict action potential prolongation. Our results underscore the importance of currents beyond those directly impacted by a drug block in determining torsadogenic risk. Our study also highlights the need for rich data in cardiac myocyte model optimization and substantiates such optimization as a method to generate models with higher accuracy of predictions of drug-induced cardiotoxicity.
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Affiliation(s)
- Trine Krogh-Madsen
- Greenberg Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, United States.,Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, United States.,Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY, United States
| | - Anna F Jacobson
- Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY, United States
| | - Francis A Ortega
- Physiology, Biophysics and Systems Biology Graduate Program, Weill Cornell Graduate School, New York, NY, United States
| | - David J Christini
- Greenberg Division of Cardiology, Department of Medicine, Weill Cornell Medicine, New York, NY, United States.,Institute for Computational Biomedicine, Weill Cornell Medicine, New York, NY, United States.,Cardiovascular Research Institute, Weill Cornell Medicine, New York, NY, United States
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Abstract
The mechanical integrity of the soft tissue structures supporting the fetus may play a role in maintaining a healthy pregnancy and triggering the onset of labor. Currently, the level of mechanical loading on the uterus, cervix, and fetal membranes during pregnancy is unknown, and it is hypothesized that the over-stretch of these tissues contributes to the premature onset of contractility, tissue remodeling, and membrane rupture, leading to preterm birth. The purpose of this review article is to introduce and discuss engineering analysis tools to evaluate and predict the mechanical loads on the uterus, cervix, and fetal membranes. Here we will explore the potential of using computational biomechanics and finite element analysis to study the causes of preterm birth and to develop a diagnostic tool that can predict gestational outcome. We will define engineering terms and identify the potential engineering variables that could be used to signal an abnormal pregnancy. We will discuss the translational ability of computational models for the better management of clinical patients. We will also discuss the process of model validation and the limitations of these models. We will explore how we can borrow from parallel engineering fields to push the boundary of patient care so that we can work toward eliminating preterm birth.
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Affiliation(s)
- Andrea R Westervelt
- Department of Mechanical Engineering, School of Engineering and Applied Science, Columbia University, 500 W, 120th St, Mudd 220, New York, NY 10027
| | - Kristin M Myers
- Department of Mechanical Engineering, School of Engineering and Applied Science, Columbia University, 500 W, 120th St, Mudd 220, New York, NY 10027.
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Miranda WE, Ngo VA, Perissinotti LL, Noskov SY. Computational membrane biophysics: From ion channel interactions with drugs to cellular function. BIOCHIMICA ET BIOPHYSICA ACTA. PROTEINS AND PROTEOMICS 2017; 1865:1643-1653. [PMID: 28847523 PMCID: PMC5764198 DOI: 10.1016/j.bbapap.2017.08.008] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/07/2017] [Revised: 08/16/2017] [Accepted: 08/16/2017] [Indexed: 12/16/2022]
Abstract
The rapid development of experimental and computational techniques has changed fundamentally our understanding of cellular-membrane transport. The advent of powerful computers and refined force-fields for proteins, ions, and lipids has expanded the applicability of Molecular Dynamics (MD) simulations. A myriad of cellular responses is modulated through the binding of endogenous and exogenous ligands (e.g. neurotransmitters and drugs, respectively) to ion channels. Deciphering the thermodynamics and kinetics of the ligand binding processes to these membrane proteins is at the heart of modern drug development. The ever-increasing computational power has already provided insightful data on the thermodynamics and kinetics of drug-target interactions, free energies of solvation, and partitioning into lipid bilayers for drugs. This review aims to provide a brief summary about modeling approaches to map out crucial binding pathways with intermediate conformations and free-energy surfaces for drug-ion channel binding mechanisms that are responsible for multiple effects on cellular functions. We will discuss post-processing analysis of simulation-generated data, which are then transformed to kinetic models to better understand the molecular underpinning of the experimental observables under the influence of drugs or mutations in ion channels. This review highlights crucial mathematical frameworks and perspectives on bridging different well-established computational techniques to connect the dynamics and timescales from all-atom MD and free energy simulations of ion channels to the physiology of action potentials in cellular models. This article is part of a Special Issue entitled: Biophysics in Canada, edited by Lewis Kay, John Baenziger, Albert Berghuis and Peter Tieleman.
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Affiliation(s)
- Williams E Miranda
- Centre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Van A Ngo
- Centre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Laura L Perissinotti
- Centre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada
| | - Sergei Yu Noskov
- Centre for Molecular Simulations, Department of Biological Sciences, University of Calgary, Calgary, AB, Canada.
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Garbey M, Casarin S, Berceli SA. Vascular Adaptation: Pattern Formation and Cross Validation between an Agent Based Model and a Dynamical System. J Theor Biol 2017; 429:149-163. [PMID: 28645858 PMCID: PMC5572567 DOI: 10.1016/j.jtbi.2017.06.013] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2016] [Revised: 05/09/2017] [Accepted: 06/12/2017] [Indexed: 11/24/2022]
Abstract
Myocardial infarction is the global leading cause of mortality (Go et al., 2014). Coronary artery occlusion is its main etiology and it is commonly treated by Coronary Artery Bypass Graft (CABG) surgery (Wilson et al, 2007). The long-term outcome remains unsatisfactory (Benedetto, 2016) as the graft faces the phenomenon of restenosis during the post-surgery, which consists of re-occlusion of the lumen and usually requires secondary intervention even within one year after the initial surgery (Harskamp, 2013). In this work, we propose an extensive study of the restenosis phenomenon by implementing two mathematical models previously developed by our group: a heuristic Dynamical System (DS) (Garbey and Berceli, 2013), and a stochastic Agent Based Model (ABM) (Garbey et al., 2015). With an extensive use of the ABM, we retrieved the pattern formations of the cellular events that mainly lead the restenosis, especially focusing on mitosis in intima, caused by alteration in shear stress, and mitosis in media, fostered by alteration in wall tension. A deep understanding of the elements at the base of the restenosis is indeed crucial in order to improve the final outcome of vein graft bypass. We also turned the ABM closer to the physiological reality by abating its original assumption of circumferential symmetry. This allowed us to finely replicate the trigger event of the restenosis, i.e. the loss of the endothelium in the early stage of the post-surgical follow up (Roubos et al., 1995) and to simulate the encroachment of the lumen in a fashion aligned with histological evidences (Owens et al., 2015). Finally, we cross-validated the two models by creating an accurate matching procedure. In this way we added the degree of accuracy given by the ABM to a simplified model (DS) that can serve as powerful predictive tool for the clinic.
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Affiliation(s)
- Marc Garbey
- University of La Rochelle, LASIE UMR CNRS, La Rochelle, France ; Houston Methodist Hospital Research Institute, Houston, TX, USA.
| | - Stefano Casarin
- University of La Rochelle, LASIE UMR CNRS, La Rochelle, France ; Houston Methodist Hospital Research Institute, Houston, TX, USA
| | - Scott A Berceli
- Malcom Randall VAMC, Gainesville, FL, USA; Department of Surgery, University of Florida, Gainesville, FL, USA
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Touati J, Bologna M, Schwein A, Migliavacca F, Garbey M. A robust construction algorithm of the centerline skeleton for complex aortic vascular structure using computational fluid dynamics. Comput Biol Med 2017; 86:6-17. [PMID: 28494383 DOI: 10.1016/j.compbiomed.2017.04.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2016] [Revised: 04/06/2017] [Accepted: 04/26/2017] [Indexed: 10/19/2022]
Abstract
Centerlines of blood vessels are useful tools to make important anatomical measurements (length, diameter, area), which cannot be accurately obtained using 2D images. In this paper a brand new method for centerline extraction of vascular trees is presented. By using computational fluid dynamics (CFD) we are able to obtain a robust and purely functional centerline allowing us to support better measurements than classic purely geometrical-based centerlines. We show that the CFD-based centerline is within a few pixels from the geometrical centerline where the latter is defined (far away from inlet/outlets and from the branches). We show that the centerline computed with our method is not affected by traditional errors of other classical volume-based algorithms such as topological thinning, and could be a potential alternative to be considered for future studies.
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Affiliation(s)
- Julien Touati
- Center for Computational Surgery, Houston Methodist Hospital, 6670 Bertner Avenue, WP254, Houston, TX 77030, USA
| | - Marco Bologna
- Center for Computational Surgery, Houston Methodist Hospital, 6670 Bertner Avenue, WP254, Houston, TX 77030, USA; Biosignals, Bioimaging and Bioinformatics Laboratory, Department of Electronics, Information and Bioengineering, Politecnico di Milano, Via Golgi 39, 20133, Milan, Italy.
| | - Adeline Schwein
- Center for Computational Surgery, Houston Methodist Hospital, 6670 Bertner Avenue, WP254, Houston, TX 77030, USA; Department of Vascular Surgery and Kidney Transplantation, University Hospital of Strasbourg, 1 Place de L Hôpital, 67091, Strasbourg, France
| | - Francesco Migliavacca
- Laboratory of Biological Structure Mechanics, Chemistry, Materials and Chemical Engineering Department "G. Natta", Politecnico di Milano, Piazza Leonardo Da Vinci 32, 20133, Milan, Italy
| | - Marc Garbey
- Center for Computational Surgery, Houston Methodist Hospital, 6670 Bertner Avenue, WP254, Houston, TX 77030, USA; LaSIE UMR - 7356 CNRS - University of La Rochelle, Avenue Michel Crépeau, 17042, La Rochelle Cedex 1, France
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Durdagi S, Erol I, Salmas RE, Patterson M, Noskov SY. First universal pharmacophore model for hERG1 K + channel activators: acthER. J Mol Graph Model 2017; 74:153-170. [PMID: 28499268 DOI: 10.1016/j.jmgm.2017.03.020] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Revised: 03/28/2017] [Accepted: 03/29/2017] [Indexed: 01/31/2023]
Abstract
The intra-cavitary drug blockade of hERG1 channel has been extensively studied, both experimentally and theoretically. Structurally diverse ligands inadvertently block the hERG1 K+ channel currents lead to drug induced Long QT Syndrome (LQTS). Accordingly, designing either hERG1 channel openers or current activators, with the potential to target other binding pockets of the channel, has been introduced as a viable approach in modern anti-arrhythmia drug development. However, reports and investigations on the molecular mechanisms underlying activators binding to the hERG1 channel remain sparse and the overall molecular design principles are largely unknown. Most of the hERG1 activators were discovered during mandatory screening for hERG1 blockade. To fill this apparent deficit, the first universal pharmacophore model for hERG1 K+ channel activators was developed using PHASE. 3D structures of 18 hERG1 K+ channel activators and their corresponding measured binding affinity values were used in the development of pharmacophore models. These compounds spanned a range of structurally different chemotypes with moderate variation in binding affinity. A five sites AAHRR (A, hydrogen-bond accepting, H, hydrophobic, R, aromatic) pharmacophore model has shown reasonable high statistical results compared to the other developed more than 1000 hypotheses. This model was used to construct steric and electrostatic contour maps. The predictive power of the model was tested with 3 external test set compounds as true unknowns. Finally, the pharmacophore model was combined with the previously developed receptor-based model of hERG1 K+ channel to develop and screen novel activators. The results are quite striking and it suggests a greater future role for pharmacophore modeling and virtual drug screening simulations in deciphering complex patterns of molecular mechanisms of hERG1 channel openers at the target sites. The developed model is available upon request and it may serve as basis for the synthesis of novel therapeutic hERG1 activators.
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Affiliation(s)
- Serdar Durdagi
- Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey.
| | - Ismail Erol
- Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey; Department of Chemistry, Gebze Technical University, Kocaeli, Turkey
| | - Ramin Ekhteiari Salmas
- Computational Biology and Molecular Simulations Laboratory, Department of Biophysics, School of Medicine, Bahcesehir University, Istanbul, Turkey
| | - Matthew Patterson
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada
| | - Sergei Y Noskov
- Centre for Molecular Simulation, Department of Biological Sciences, University of Calgary, Calgary, Alberta, Canada.
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Dewan S, McCabe KJ, Regnier M, McCulloch AD. Insights and Challenges of Multi-Scale Modeling of Sarcomere Mechanics in cTn and Tm DCM Mutants-Genotype to Cellular Phenotype. Front Physiol 2017; 8:151. [PMID: 28352236 PMCID: PMC5348544 DOI: 10.3389/fphys.2017.00151] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 02/24/2017] [Indexed: 01/18/2023] Open
Abstract
Dilated Cardiomyopathy (DCM) is a leading cause of sudden cardiac death characterized by impaired pump function and dilatation of cardiac ventricles. In this review we discuss various in silico approaches to elucidating the mechanisms of genetic mutations leading to DCM. The approaches covered in this review focus on bridging the spatial and temporal gaps that exist between molecular and cellular processes. Mutations in sarcomeric regulatory thin filament proteins such as the troponin complex (cTn) and Tropomyosin (Tm) have been associated with DCM. Despite the experimentally-observed myofilament measures of contractility in the case of these mutations, the mechanisms by which the underlying molecular changes and protein interactions scale up to organ failure by these mutations remains elusive. The review highlights multi-scale modeling approaches and their applicability to study the effects of sarcomeric gene mutations in-silico. We discuss some of the insights that can be gained from computational models of cardiac biomechanics when scaling from molecular states to cellular level.
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Affiliation(s)
- Sukriti Dewan
- Departments of Bioengineering and Medicine, University of California San Diego, La Jolla, CA, USA
| | - Kimberly J McCabe
- Departments of Bioengineering and Medicine, University of California San Diego, La Jolla, CA, USA
| | - Michael Regnier
- Departments of Bioengineering and Medicine, University of Washington Seattle, WA, USA
| | - Andrew D McCulloch
- Departments of Bioengineering and Medicine, University of California San Diego, La Jolla, CA, USA
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Jain KK. Personalized Management of Cardiovascular Disorders. Med Princ Pract 2017; 26:399-414. [PMID: 28898880 PMCID: PMC5757599 DOI: 10.1159/000481403] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Accepted: 09/11/2017] [Indexed: 12/28/2022] Open
Abstract
Personalized management of cardiovascular disorders (CVD), also referred to as personalized or precision cardiology in accordance with general principles of personalized medicine, is selection of the best treatment for an individual patient. It involves the integration of various "omics" technologies such as genomics and proteomics as well as other new technologies such as nanobiotechnology. Molecular diagnostics and biomarkers are important for linking diagnosis with therapy and monitoring therapy. Because CVD involve perturbations of large complex biological networks, a systems biology approach to CVD risk stratification may be used for improving risk-estimating algorithms, and modeling of personalized benefit of treatment may be helpful for guiding the choice of intervention. Bioinformatics tools are helpful in analyzing and integrating large amounts of data from various sources. Personalized therapy is considered during drug development, including methods of targeted drug delivery and clinical trials. Individualized recommendations consider multiple factors - genetic as well as epigenetic - for patients' risk of heart disease. Examples of personalized treatment are those of chronic myocardial ischemia, heart failure, and hypertension. Similar approaches can be used for the management of atrial fibrillation and hypercholesterolemia, as well as the use of anticoagulants. Personalized management includes pharmacotherapy, surgery, lifestyle modifications, and combinations thereof. Further progress in understanding the pathomechanism of complex cardiovascular diseases and identification of causative factors at the individual patient level will provide opportunities for the development of personalized cardiology. Application of principles of personalized medicine will improve the care of the patients with CVD.
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Affiliation(s)
- Kewal K. Jain
- *Prof. K.K. Jain, MD, FRACS, FFPM, CEO, Jain PharmaBiotech, Bläsiring 7, CH-4057 Basel (Switzerland), E-Mail
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Myrmel T, Larsen M, Bartnes K. The International Registry of Acute Aortic Dissections (IRAD) – experiences from the first 20 years. SCAND CARDIOVASC J 2016; 50:329-333. [DOI: 10.1080/14017431.2016.1240829] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Affiliation(s)
- Truls Myrmel
- The Heart and Lung Clinic, University Hospital North Norway, Tromsø, Norway
- The University of Tromsø, The Arctic University of Norway, Tromsø, Norway
| | - Magnus Larsen
- Department of Urology and Endocrine Surgery, University Hospital North Norway, Tromsø, Norway
| | - Kristian Bartnes
- The Heart and Lung Clinic, University Hospital North Norway, Tromsø, Norway
- The University of Tromsø, The Arctic University of Norway, Tromsø, Norway
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