Closed-loop investigation of the dynamical properties of cardiomyocyte electrophysiology by means of Dynamic clamp and Mathematical modelling

The research field of my PhD concerns mathematical modeling and numerical simulation, applied to the cardiac electrophysiology analysis at a single cell level. This is possible thanks to the development of mathematical descriptions of single cellular components, ionic channels, pumps, exchangers and subcellular compartments. Due to the difficulties of vivo experiments on human cells, most of the measurements are acquired in vitro using animal models (e.g. guinea pig, dog, rabbit). Moreover, to study the cardiac action potential and all its features, it is necessary to acquire more specific knowledge about single ionic currents that contribute to the cardiac activity. Electrophysiological models of the heart have become very accurate in recent years giving rise to extremely complicated systems of differential equations. Although describing the behavior of cardiac cells quite well, the models are computationally demanding for numerical simulations and are very difficult to analyze from a mathematical (dynamical-systems) viewpoint. Simplified mathematical models that capture the underlying dynamics to a certain extent are therefore frequently used. The results presented in this thesis have confirmed that a close integration of computational modeling and experimental recordings in real myocytes, as performed by dynamic clamp, is a useful tool in enhancing our understanding of various components of normal cardiac electrophysiology, but also arrhythmogenic mechanisms in a pathological condition, especially when fully integrated with experimental data.

Computational Modelling of Cardiac Electrophysiology: from Cell to Bedside

Heart diseases are the leading cause of death worldwide, both for men and women. However, the ionic mechanisms underlying many cardiac arrhythmias and genetic disorders are not completely understood, thus leading to a limited efficacy of the current available therapies and leaving many open questions for cardiac electrophysiologists. On the other hand, experimental data availability is still a great issue in this field: most of the experiments are performed in vitro and/or using animal models (e.g. rabbit, dog and mouse), even when the final aim is to better understand the electrical behaviour of in vivo human heart either in physiological or pathological conditions. Computational modelling constitutes a primary tool in cardiac electrophysiology: in silico simulations, based on the available experimental data, may help to understand the electrical properties of the heart and the ionic mechanisms underlying a specific phenomenon. Once validated, mathematical models can be used for making predictions and testing hypotheses, thus suggesting potential therapeutic targets. This PhD thesis aims to apply computational cardiac modelling of human single cell action potential (AP) to three clinical scenarios, in order to gain new insights into the ionic mechanisms involved in the electrophysiological changes observed in vitro and/or in vivo. The first context is blood electrolyte variations, which may occur in patients due to different pathologies and/or therapies. In particular, we focused on extracellular Ca2+ and its effect on the AP duration (APD). The second context is haemodialysis (HD) therapy: in addition to blood electrolyte variations, patients undergo a lot of other different changes during HD, e.g. heart rate, cell volume, pH, and sympatho-vagal balance. The third context is human hypertrophic cardiomyopathy (HCM), a genetic disorder characterised by an increased arrhythmic risk, and still lacking a specific pharmacological treatment.

Percezione della direzione del proprio movimento: dalla registrazione dell'attività corticale al modello computazionale.

The main aim of this thesis is strongly interdisciplinary: it involves and presumes a knowledge on Neurophysiology, to understand the mechanisms that undergo the studied phenomena, a knowledge and experience on Electronics, necessary during the hardware experimental set-up to acquire neuronal data, on Informatics and programming to write the code necessary to control the behaviours of the subjects during experiments and the visual presentation of stimuli. At last, neuronal and statistical models should be well known to help in interpreting data. The project started with an accurate bibliographic research: until now the mechanism of perception of heading (or direction of motion) are still poorly known. The main interest is to understand how the integration of visual information relative to our motion with eye position information happens. To investigate the cortical response to visual stimuli in motion and the integration with eye position, we decided to study an animal model, using Optic Flow expansion and contraction as visual stimuli. In the first chapter of the thesis, the basic aims of the research project are presented, together with the reasons why it’s interesting and important to study perception of motion. Moreover, this chapter describes the methods my research group thought to be more adequate to contribute to scientific community and underlines my personal contribute to the project. The second chapter presents an overview on useful knowledge to follow the main part of the thesis: it starts with a brief introduction on central nervous system, on cortical functions, then it presents more deeply associations areas, which are the main target of our study. Furthermore, it tries to explain why studies on animal models are necessary to understand mechanism at a cellular level, that could not be addressed on any other way. In the second part of the chapter, basics on electrophysiology and cellular communication are presented, together with traditional neuronal data analysis methods. The third chapter is intended to be a helpful resource for future works in the laboratory: it presents the hardware used for experimental sessions, how to control animal behaviour during the experiments by means of C routines and a software, and how to present visual stimuli on a screen. The forth chapter is the main core of the research project and the thesis. In the methods, experimental paradigms, visual stimuli and data analysis are presented. In the results, cellular response of area PEc to visual stimuli in motion combined with different eye positions are shown. In brief, this study led to the identification of different cellular behaviour in relation to focus of expansion (the direction of motion given by the optic flow pattern) and eye position. The originality and importance of the results are pointed out in the conclusions: this is the first study aimed to investigate perception of motion in this particular cortical area. In the last paragraph, a neuronal network model is presented: the aim is simulating cellular pre-saccadic and post-saccadic response of neuron in area PEc, during eye movement tasks. The same data presented in chapter four, are further analysed in chapter fifth. The analysis started from the observation of the neuronal responses during 1s time period in which the visual stimulation was the same. It was clear that cells activities showed oscillations in time, that had been neglected by the previous analysis based on mean firing frequency. Results distinguished two cellular behaviour by their response characteristics: some neurons showed oscillations that changed depending on eye and optic flow position, while others kept the same oscillations characteristics independent of the stimulus. The last chapter discusses the results of the research project, comments the originality and interdisciplinary of the study and proposes some future developments.

Computational modelling of human stem cell-derived cardiomyocytes - Texture descriptors for biological image processing

This thesis investigates two distinct research topics. The main topic (Part I) is the computational modelling of cardiomyocytes derived from human stem cells, both embryonic (hESC-CM) and induced-pluripotent (hiPSC-CM). The aim of this research line lies in developing models of the electrophysiology of hESC-CM and hiPSC-CM in order to integrate the available experimental data and getting in-silico models to be used for studying/making new hypotheses/planning experiments on aspects not fully understood yet, such as the maturation process, the functionality of the Ca2+ hangling or why the hESC-CM/hiPSC-CM action potentials (APs) show some differences with respect to APs from adult cardiomyocytes. Chapter I.1 introduces the main concepts about hESC-CMs/hiPSC-CMs, the cardiac AP, and computational modelling. Chapter I.2 presents the hESC-CM AP model, able to simulate the maturation process through two developmental stages, Early and Late, based on experimental and literature data. Chapter I.3 describes the hiPSC-CM AP model, able to simulate the ventricular-like and atrial-like phenotypes. This model was used to assess which currents are responsible for the differences between the ventricular-like AP and the adult ventricular AP. The secondary topic (Part II) consists in the study of texture descriptors for biological image processing. Chapter II.1 provides an overview on important texture descriptors such as Local Binary Pattern or Local Phase Quantization. Moreover the non-binary coding and the multi-threshold approach are here introduced. Chapter II.2 shows that the non-binary coding and the multi-threshold approach improve the classification performance of cellular/sub-cellular part images, taken from six datasets. Chapter II.3 describes the case study of the classification of indirect immunofluorescence images of HEp2 cells, used for the antinuclear antibody clinical test. Finally the general conclusions are reported.

Computational Modeling of Cardiac Excitation-Contraction Coupling in Physiological and Pathological Conditions

The cardiomyocyte is a complex biological system where many mechanisms interact non-linearly to regulate the coupling between electrical excitation and mechanical contraction. For this reason, the development of mathematical models is fundamental in the field of cardiac electrophysiology, where the use of computational tools has become complementary to the classical experimentation. My doctoral research has been focusing on the development of such models for investigating the regulation of ventricular excitation-contraction coupling at the single cell level. In particular, the following researches are presented in this thesis: 1) Study of the unexpected deleterious effect of a Na channel blocker on a long QT syndrome type 3 patient. Experimental results were used to tune a Na current model that recapitulates the effect of the mutation and the treatment, in order to investigate how these influence the human action potential. Our research suggested that the analysis of the clinical phenotype is not sufficient for recommending drugs to patients carrying mutations with undefined electrophysiological properties. 2) Development of a model of L-type Ca channel inactivation in rabbit myocytes to faithfully reproduce the relative roles of voltage- and Ca-dependent inactivation. The model was applied to the analysis of Ca current inactivation kinetics during normal and abnormal repolarization, and predicts arrhythmogenic activity when inhibiting Ca-dependent inactivation, which is the predominant mechanism in physiological conditions. 3) Analysis of the arrhythmogenic consequences of the crosstalk between β-adrenergic and Ca-calmodulin dependent protein kinase signaling pathways. The descriptions of the two regulatory mechanisms, both enhanced in heart failure, were integrated into a novel murine action potential model to investigate how they concur to the development of cardiac arrhythmias. These studies show how mathematical modeling is suitable to provide new insights into the mechanisms underlying cardiac excitation-contraction coupling and arrhythmogenesis.