A mathematical model of the murine ventricular myocyte: a data-driven biophysically based approach applied to mice overexpressing the canine NCX isoform

Li, Liren; Niederer, Steven A.; Idigo, W; Zhang, Yinhua; Swietach, Pawel; Casadei, Barbara; Smith, Nicolas P.

doi:10.1152/ajpheart.00219.2010

Cited by 51 publications

(65 citation statements)

References 62 publications

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“…To provide a specific set of examples of particular relevance to this study, in models of cardiac myocyte electrophysiology and contraction, the majority of integrated data have been recorded from small mammals, namely mouse, rat, guinea pig and rabbit. The increase in both quality and quantity of this experimental data is now supporting a transition from more generic mammalian-based models (Luo & Rudy, 1994) to increasingly species-specific models parameterised mainly from data collected from a given species under consistent conditions (Smith et al 2007;Niederer et al 2009;Li et al 2010). However, in the majority of cases this transition remains incomplete due to reuse of model components because of lack of experimental data, slowing the transition to species-specific understandings.…”

Section: Introductionmentioning

confidence: 97%

Quantifying inter‐species differences in contractile function through biophysical modelling

Tøndel

Land

Niederer

et al. 2015

The Journal of Physiology

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Key pointsr To facilitate translation of data from animal models into clinical applications, it is important to analyse and quantify the differences and relevance of specific physiological mechanisms between species.r We propose a novel approach for the quantification of inter-species differences in terms of biophysical model parameters and apply this to elucidate the differences in cardiac contraction mechanisms between mouse, rat and human.r Our results indicate that the parameters related to the sensitivity and cooperativity of calcium binding to troponin C and the activation and relaxation rates of tropomyosin/crossbridge binding kinetics differ most significantly between mouse, rat and human.r Our results predict crossbridge binding to be slowest in human and fastest in mouse.Abstract Animal models and measurements are frequently used to guide and evaluate clinical interventions. In this context, knowledge of inter-species differences in physiology is crucial for understanding the limitations and relevance of animal experimental assays for informing clinical applications. Extensive effort has been put into studying the structure and function of cardiac contractile proteins and how differences in these translate into the functional properties of muscles. However, integrating this knowledge into a quantitative description, formalising and highlighting inter-species differences both in the kinetics and in the regulation of physiological mechanisms, remains challenging. In this study we propose and apply a novel approach for the quantification of inter-species differences between mouse, rat and human. Assuming conservation of the fundamental physiological mechanisms underpinning contraction, biophysically based computational models are fitted to simulate experimentally recorded phenotypes from multiple species. The phenotypic differences between species are then succinctly quantified as differences in the biophysical model parameter values. This provides the potential of quantitatively establishing the human relevance of both animal-based experimental and computational models for application in a clinical context. Our results indicate that the parameters related to the sensitivity and cooperativity of calcium binding to troponin C and the activation and relaxation rates of tropomyosin/crossbridge binding kinetics differ most significantly between mouse, rat and human, while for example the reference tension, as expected, shows only minor differences between the species. Hence, while confirming expected inter-species differences in calcium sensitivity due to large differences in the observed calcium transients, our results also indicate more unexpected differences in the cooperativity mechanism. Specifically, the decrease in the unbinding rate of calcium to troponin C with increasing active tension was much lower for mouse than for rat and human. Our results also predicted crossbridge binding to be slowest in human and fastest in mouse.

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Section: Introductionmentioning

confidence: 97%

Quantifying inter‐species differences in contractile function through biophysical modelling

Tøndel

Land

Niederer

et al. 2015

The Journal of Physiology

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“…[37][38][39][40][41][42][43][44][45][46][47][48] As illustrated in Figures 10.1 and 10.2, current single-cell cardiac electrophysiology models include detailed representation of the most important ionic transport mechanisms such as sodium and calcium and potassium ion channels, the sodium/calcium exchanger and the sodium/ potassium pump, and also the biophysical processes underlying calcium dynamics across intracellular compartments of the sarcoplasmic reticulum. In some cases signalling pathways such as those underlying beta-adrenoceptor stimulation and the CaMKII cascade are also incorporated.…”

Section: Single Cardiomyocyte Modelsmentioning

confidence: 99%

In Silico Organ Modelling in Predicting Efficacy and Safety of New Medicines

Rodríguez¹

2014

Human-Based Systems for Translational Research

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Over the last 50 years, a number of areas of physiology have experienced great progress in the development and integration of in silico models and simulation tools of different organs. Multiscale human organ computational models are available, for different organs including heart, 1,2 lungs 3-6 and cancer, 7,8 with ne-grained biophysical detail and a great level of integration from the genetic to the whole body level. Multiscale modelling and simulation have been crucial in improving our understanding of mechanisms of physiological and pathological phenomena, therapy and diagnosis. The advanced in silico technology is currently opening up promising and powerful avenues for the investigation and improvement of the efficiency of therapies and for the development of new medicines.Perhaps the most advanced area of computational physiology is computational cardiology, concerned with the investigation of the physiology and pathology of the heart using computational modelling and simulating.

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“…Perhaps the most complicated term in cardiac electrophysiology models is the nonlinear term representing the cellular dynamics accounting for transmembrane and subcellular currents [see, for example, the following studies (21,26,30,39,40,54,55,58,67,70,92)]. From the electrophysiological point of view, the cellular membrane acts as an electrical isolator, which hosts proteins of transmembrane ionic transport, functioning as ion channels, exchangers, and pumps.…”

Section: Multiscale Models and Simulations In Cardiac Electrophysiologymentioning

confidence: 99%

“…Whereas the mathematical framework described above is generic for cardiac tissue, the models are aimed at being specific, for example, of a particular animal species or spatial location within the heart (for example, dog vs. rabbit, atria vs. ventricles). Data obtained from wet-laboratory experiments are the means whereby the generic and abstract mathematical equations are related to specific and particular cardiac physiological features and processes (1,26,30,34,39,40,70,54,55,58,79). Parameter values in the models are obtained directly from experimental measurements (when possible) or indirectly by minimizing the difference between simulated and mean experimental behavior using similar conditions in both cases.…”

Section: Multiscale Models and Simulations In Cardiac Electrophysiologymentioning

confidence: 99%

“…Figure 4 illustrates examples of studies providing a comparison between simulations and experiments at the single cell level and at the whole ventricular level. The comparison can be performed in two ways (and often a combination of both): 1) quantitatively, by checking that the value for a specific electrophysiological property (such as action potential duration) in simulations is within the range reported in experiments [see, for example, the following studies (26,54,55,70,84,100,104)] or 2) qualitatively, by observing the outcome of a particular intervention (for example, a certain drug block leads to abnormalities in repolarization or reentry) (26,55,70,88,108). The perceived robustness of these two modes of validation is a very important issue that requires further reflection and that, however, goes beyond the scope of this article.…”

Section: Implications For Validationmentioning

confidence: 99%

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Bridging experiments, models and simulations: an integrative approach to validation in computational cardiac electrophysiology

Carusi

Burrage

Rodríguez

2012

American Journal of Physiology-Heart and Circulatory Physiology

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Carusi A, Burrage K, Rodríguez B. Bridging experiments, models and simulations: an integrative approach to validation in computational cardiac electrophysiology. Am J Physiol Heart Circ Physiol 303: H144 -H155, 2012. First published May 11, 2012; doi:10.1152/ajpheart.01151.2011.-Computational models in physiology often integrate functional and structural information from a large range of spatiotemporal scales from the ionic to the whole organ level. Their sophistication raises both expectations and skepticism concerning how computational methods can improve our understanding of living organisms and also how they can reduce, replace, and refine animal experiments. A fundamental requirement to fulfill these expectations and achieve the full potential of computational physiology is a clear understanding of what models represent and how they can be validated. The present study aims at informing strategies for validation by elucidating the complex interrelations among experiments, models, and simulations in cardiac electrophysiology. We describe the processes, data, and knowledge involved in the construction of whole ventricular multiscale models of cardiac electrophysiology. Our analysis reveals that models, simulations, and experiments are intertwined, in an assemblage that is a system itself, namely the model-simulation-experiment (MSE) system. We argue that validation is part of the whole MSE system and is contingent upon 1) understanding and coping with sources of biovariability; 2) testing and developing robust techniques and tools as a prerequisite to conducting physiological investigations; 3) defining and adopting standards to facilitate the interoperability of experiments, models, and simulations; 4) and understanding physiological validation as an iterative process that contributes to defining the specific aspects of cardiac electrophysiology the MSE system targets, rather than being only an external test, and that this is driven by advances in experimental and computational methods and the combination of both. computational physiology; systems biology; computer simulations; whole ventricular models; cardiac electrophysiology COMPUTATIONAL PHYSIOLOGY belongs to the broad family of research in the life sciences referred to as systems biology. As with other domains of systems biology, it considers biological processes as systems of interacting components, and draws upon mathematical and computational modeling to bring these into new configurations with experimentation. It shares the basic commitments of systems biology to nonreductionist or integrative principles, geared towards the exploration of emergence and nonlinear interactions among components and between levels (12,16,41,49,53,71,88). From a sociological point of view, it is also a mode of research that depends on a high degree of interdisciplinary collaboration, where the increased sophistication of computational modeling in the life sciences can elicit high expectations but also skepticism sometimes, thus making collaboration more difficult (19,20,...

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A mathematical model of the murine ventricular myocyte: a data-driven biophysically based approach applied to mice overexpressing the canine NCX isoform

Cited by 51 publications

References 62 publications

Quantifying inter‐species differences in contractile function through biophysical modelling

Quantifying inter‐species differences in contractile function through biophysical modelling

In Silico Organ Modelling in Predicting Efficacy and Safety of New Medicines

Bridging experiments, models and simulations: an integrative approach to validation in computational cardiac electrophysiology

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