Integrated Cardiac Electromechanics: Modeling and Personalization

Cardiac disease remains the leading cause of morbidity and mortality in the world. A variety of heart diagnosis techniques have been developed during the last century, and generally fall into two groups. The first group evaluates the electrical function of the heart using electrophysiological data such as electrocardiogram (ECG), while the second group aims to assess the mechanical function of the heart through medical imaging data. Nevertheless, the heart is an integrated electromechanical organ, where its cyclic pumping arises from the synergy of its electrical and mechanical function which requires first to be electrically excited in order to contract. At the same time, cardiac electrical function experiences feedback from mechanical contraction. This inter-dependent relationship determines that neither electrical function nor mechanical function alone can completely reflect the pathophysiological conditions of the heart. The aim of this thesis is working towards building an integrated framework for heart diagnosis through evaluation of electrical and mechanical functions simultaneously. The basic rational is to obtain quantitative interpretation of a subject-specific heart system by combining an electromechanical heart model and individual clinical measurements of the heart. To this end, we first develop a biologically-inspired mathematical model of the heart that provides a general, macroscopic description of cardiac electromechanics. The intrinsic electromechanical coupling arises from both excitation-induced contraction and deformation-induced mechano-electrical feedback. Then, as a first step towards a fully electromechanically integrated framework, we develop a model-based approach for investigating the effect of cardiac motion on noninvasive transmural imaging of cardiac electrophysiology. Specifically, we utilize the proposed heart model to obtain updated heart geometry through simulation, and further recover the electrical activities of the heart from body surface potential maps (BSPMs) by solving an optimization problem. Various simulations of the heart have been performed under healthy and abnormal conditions, which demonstrate the physiological plausibility of the proposed integrated electromechanical heart model. What\u27s more, this work presents the effect of cardiac motion to the solution of noninvasive estimation of cardiac electrophysiology and shows the importance of integrating cardiac electrical and mechanical functions for heart diagnosis. This thesis also paves the road for noninvasive evaluation of cardiac electromechanics

3D imaging and quantitative analysis of intact tissues and organs

Embryonic development and tumor growth are highly complex and dynamic processes that exist in both time and space. To fully understand the molecular mechanisms that control these processes, it is crucial to study RNA expression and protein translation with single-cell spatiotemporal resolution. This is feasible by microscopic imaging that enables multidimensional assessments of cells, tissues, and organs. Here, a time-lapse calcium imaging and three-dimensional imaging was used to study physiological development of the brain or pathological development of cancer, respectively. In Paper I, spatiotemporal calcium imaging revealed a new mechanism of neurogenesis during brain development. In Paper II, a new clearing method of clinically stored specimens, DIPCO (diagnosing immunolabeled paraffin-embedded cleared organs), was developed that allows better characterization and staging of intact human tumors. In Paper III, the DIPCO method was applied to determine tumor stage and characterize the microlymphatic system in bladder cancer. In Paper IV, a novel method for RNA labeling of volumetric specimens, DIIFCO (diagnosing in situ and immunofluorescence-labeled cleared onco-sample) was developed to study RNAs expression and localization in intact tumors. Overall, the aim of the thesis was to demonstrate that multidimensional imaging extends the understanding of both physiological and pathological biological developmental processes

A fully automated high-throughput workflow for 3D-based chemical screening in human midbrain organoids

Three-dimensional (3D) culture systems have fueled hopes to bring about the next generation of more physiologically relevant high-throughput screens (HTS). However, current protocols yield either complex but highly heterogeneous aggregates ('organoids') or 3D structures with less physiological relevance ('spheroids'). Here, we present a scalable, HTS-compatible workflow for the automated generation, maintenance, and optical analysis of human midbrain organoids in standard 96-well-plates. The resulting organoids possess a highly homogeneous morphology, size, global gene expression, cellular composition, and structure. They present significant features of the human midbrain and display spontaneous aggregate-wide synchronized neural activity. By automating the entire workflow from generation to analysis, we enhance the intra- and inter-batch reproducibility as demonstrated via RNA sequencing and quantitative whole mount high-content imaging. This allows assessing drug effects at the single-cell level within a complex 3D cell environment in a fully automated HTS workflow

Imaging as a tool to study leaf development in Arabidopsis thaliana

In contrast to humans and animals, the body plan of a plant is not completely defined within the embryonic stages. Organ formation continues throughout plant development and this iterative and modular process is continuously controlled by environmental cues such as light, gravity, temperature, humidity and chemicals. In most plant species, the above-ground plant body is dominated by leaves, the organs specialized in photosynthesis. This process converts carbon dioxide into organic components utilizing energy from sunlight; making leaves the energy production site and the growth engine of plants. In addition, in many cases the majority of a plant’s biomass consists of leaves, also making them important organs for the production of food, feed and bio-energy. The final leaf size is determined by the total number of cells and the average cell size that result from cell division and cell expansion, respectively. During leaf development of dicotyledonous species, a cell proliferation phase, characterized by actively dividing cells, is followed by a cell expansion phase, characterized by cell growth and differentiation. After expansion, cells mature and the final leaf size is reached. At the proliferation-to-expansion phase transition, cell division ceases along a longitudinal gradient from leaf tip to base. In this thesis, we set out to gain further insight in these developmental processes affecting leaf size, assisted by the use of imaging technology and automated image analysis. For these studies we used the model species Arabidopsis thaliana, focusing primarily on the epidermis of the developing leaves as divisions there are strictly anticlinal. Moreover this layer is thought to be the main tissue layer controlling leaf growth. As a first step, we developed different image analysis tools to allow for a better and more efficient analysis of the leaf developmental process. In the first place we developed an online framework, designated Leaf Image Analysis Interface (LIMANI), in which venation patterns are automatically segmented and measured on dark-field images. Image segmentation may be manually corrected through use of an interactive interface, allowing supervision and rectification steps in the automated image analysis pipeline and ensuring high-fidelity analysis. We subsequently used this framework to study vascular differentiation during leaf development and to analyze the venation pattern in transgenic lines with contrasting cellular and leaf size traits. A major conclusion from this work was that, as vascular differentiation occurs relatively late in development, the influence of a fully functional and differentiated venation pattern on final leaf size is rather limited. Furthermore, we describe a proof-of-concept to automate the kinematic analysis of leaf growth based on DIC pictures, by a sophisticated image processing chain and a data analysis pipeline. Next, we also developed imaging scripts to extract complete seedlings grown on soil and on Petri dishes and integrated those into three phenotyping platforms which monitor plant growth. Finally, we investigated the potential of emerging imaging technologies, particularly X-ray computed tomography, for future applications in plant growth analysis. The newly developed kinematic analysis tools allowed us to show that the transcription factors, SHORT-ROOT (SHR) and SCARECROW (SCR), next to their specific roles in cortex/endodermis differentiation and stem cell maintenance in the root, primarily function as general regulators of cell proliferation in leaves. The analysis of leaf growth revealed how these proteins affect the cellular growth dynamics and formed the basis to unravel the molecular mechanism controlling this. It turned out that they promote leaf growth mainly by the down-regulation of cell cycle inhibitors, known to restrain the activity of the transcription factor, E2Fa, stimulating S-phase progression. Although the dynamics of cell division and cell expansion processes can be analyzed rigorously by the leaf growth kinematics, knowledge of cell cycle duration, cell expansion, and their interaction at the individual cell level is still poorly understood, not only because of technical obstacles to study these phenomena, but also because the processes are intimately intertwined, shown by the fact that a reduced cell proliferation is often compensated by an increase in cell size and vice versa. A mathematical model fitted to detailed cellular measurements retrieved by automated image analysis of microscopic drawings of the leaf epidermis, revealed that average cell cycle duration remains constant throughout leaf development. Surprisingly, no evidence for a maximum cell size threshold for cell division of pavement cells was found in this analysis. We could estimate the division and expansion parameters of pavement and guard cell populations within the growing leaf separately and the model predicted that neighboring cells of different sizes within the epidermis expand at distinctly different relative rates. We could finally verify this by direct observations using live imaging. The mathematical model helped us to gain a better and more detailed insight into the processes that define leaf growth. But the transition from cell proliferation to cell expansion was a developmental time point that was still not characterized in detail. Differences in the timing of this transition strongly affects the number of cells formed and therefore potentially also serves as a control point determining mature leaf size. Several genes have been identified that alter leaf size by affecting the transition from primary to secondary morphogenesis. We characterized the progression of the transition on the morphological and molecular level using transcriptome analysis and imaging algorithms to visualize and quantify the size and shape of pavement cells along the proximal-distal axis of the leaf during transition. Both analyses showed that the transition from cell proliferation to expansion was established and abolished abruptly. Furthermore, the establishment of the cell cycle arrest front occurs simultaneously with the onset of photomorphogenesis. We provide evidence that retrograde signaling from chloroplasts can affect the onset of transition, revealing a previously unknown level of regulatory complexity during the transition from primary to secondary morphogenesis