Jonathan Wong

Multiscale Computational Models for Optogenetic Control of Cardiac Function

The ability to stimulate mammalian cells with light has significantly changed our understanding of electrically excitable tissues in health and disease, paving the way toward various novel therapeutic applications. Here, we demonstrate the potential of optogenetic control in cardiac cells using a hybrid experimental/computational technique. Experimentally, we introduced channelrhodopsin-2 into undifferentiated human embryonic stem cells via a lentiviral vector, and sorted and expanded the genetically engineered cells. Via directed differentiation, we created channelrhodopsin-expressing cardiomyocytes, which we subjected to optical stimulation. To quantify the impact of photostimulation, we assessed electrical, biochemical, and mechanical signals using patch-clamping, multielectrode array recordings, and video microscopy. Computationally, we introduced channelrhodopsin-2 into a classic autorhythmic cardiac cell model via an additional photocurrent governed by a light-sensitive gating variable. Upon optical stimulation, the channel opens and allows sodium ions to enter the cell, inducing a fast upstroke of the transmembrane potential. We calibrated the channelrhodopsin-expressing cell model using single action potential readings for different photostimulation amplitudes, pulse widths, and frequencies. To illustrate the potential of the proposed approach, we virtually injected channelrhodopsin-expressing cells into different locations of a human heart, and explored its activation sequences upon optical stimulation. Our experimentally calibrated computational toolbox allows us to virtually probe landscapes of process parameters, and identify optimal photostimulation sequences toward pacing hearts with light.

Generating fibre orientation maps in human heart models using Poisson interpolation

Smoothly varying muscle fibre orientations in the heart are critical to its electrical and mechanical function. From detailed histological studies and diffusion tensor imaging, we now know that fibre orientations in humans vary gradually from approximately − 70° in the outer wall to +80° in the inner wall. However, the creation of fibre orientation maps for computational analyses remains one of the most challenging problems in cardiac electrophysiology and cardiac mechanics. Here, we show that Poisson interpolation generates smoothly varying vector fields that satisfy a set of user-defined constraints in arbitrary domains. Specifically, we enforce the Poisson interpolation in the weak sense using a standard linear finite element algorithm for scalar-valued second-order boundary value problems and introduce the feature to be interpolated as a global unknown. User-defined constraints are then simply enforced in the strong sense as Dirichlet boundary conditions. We demonstrate that the proposed concept is capable of generating smoothly varying fibre orientations, quickly, efficiently and robustly, both in a generic bi-ventricular model and in a patient-specific human heart. Sensitivity analyses demonstrate that the underlying algorithm is conceptually able to handle both arbitrarily and uniformly distributed user-defined constraints; however, the quality of the interpolation is best for uniformly distributed constraints. We anticipate our algorithm to be immediately transformative to experimental and clinical settings, in which it will allow us to quickly and reliably create smooth interpolations of arbitrary fields from data-sets, which are sparse but uniformly distributed.

Computational modeling of chemo‐electro‐mechanical coupling: A novel implicit monolithic finite element approach

Computational modeling of the human heart allows us to predict how chemical, electrical, and mechanical fields interact throughout a cardiac cycle. Pharmacological treatment of cardiac disease has advanced significantly over the past decades, yet it remains unclear how the local biochemistry of an individual heart cell translates into global cardiac function. Here, we propose a novel, unified strategy to simulate excitable biological systems across three biological scales. To discretize the governing chemical, electrical, and mechanical equations in space, we propose a monolithic finite element scheme. We apply a highly efficient and inherently modular global-local split, in which the deformation and the transmembrane potential are introduced globally as nodal degrees of freedom, whereas the chemical state variables are treated locally as internal variables. To ensure unconditional algorithmic stability, we apply an implicit backward Euler finite difference scheme to discretize the resulting system in time. To increase algorithmic robustness and guarantee optimal quadratic convergence, we suggest an incremental iterative Newton-Raphson scheme. The proposed algorithm allows us to simulate the interaction of chemical, electrical, and mechanical fields during a representative cardiac cycle on a patient-specific geometry, robust and stable, with calculation times on the order of 4 days on a standard desktop computer.

Early CMV Viremia Is Associated with Impaired Viral Control following Nonmyeloablative Hematopoietic Cell Transplantation with a Total Lymphoid Irradiation and Antithymocyte Globulin Preparative Regimen

The reconstitution of immune function after hematopoietic cell transplant (HCT) plays an important role in the control of viral infections. Both donor and recipient cytomegalovirus (CMV) serostatus has been shown to contribute to effective immune function; however, the influence of a nonmyeloablative preparative (NMA) regimen using total lymphoid irradiation (TLI) and antithymocyte globulin (ATG) on antiviral immune reconstitution has not yet been described. In 117 recipients of NMA HCT patients following ATG and TLI, not unexpectedly, CMV viremia was seen in approximately 60% of the seropositive patients regardless of donor serostatus, and recipient seropositivity significantly increased the odds of CMV viremia after transplant in a multivariate analysis. The administration of ATG and TLI resulted in a strikingly earlier viremia in the posttransplant period when compared to the previously reported timing of viremia following myeloablative preparative regimens, especially for transplant recipients who were seropositive for CMV with seronegative donors. Furthermore, early viremia in the setting of a CMV naïve donor was associated with a delay in functional antiviral control. These observations demonstrate the dynamic nature of immunity in relation to CMV antigen exposure in the complex environment resulting from NMA conditions where both donor and residual recipient immune response affect viral control.

Characterisation of electrophysiological conduction in cardiomyocyte co-cultures using co-occurrence analysis.

Cardiac arrhythmias are disturbances of the electrical conduction pattern in the heart with severe clinical implications. The damage of existing cells or the transplantation of foreign cells may disturb functional conduction pathways and may increase the risk of arrhythmias. Although these conduction disturbances are easily accessible with the human eye, there is no algorithmic method to extract quantitative features that quickly portray the conduction pattern. Here, we show that co-occurrence analysis, a well-established method for feature recognition in texture analysis, provides insightful quantitative information about the uniformity and the homogeneity of an excitation wave. As a first proof-of-principle, we illustrate the potential of co-occurrence analysis by means of conduction patterns of cardiomyocyte–fibroblast co-cultures, generated both in vitro and in silico. To characterise signal propagation in vitro, we perform a conduction analysis of co-cultured murine HL-1 cardiomyocytes and murine 3T3 fibroblasts using microelectrode arrays. To characterise signal propagation in silico, we establish a conduction analysis of co-cultured electrically active, conductive cardiomyocytes and non-conductive fibroblasts using the finite element method. Our results demonstrate that co-occurrence analysis is a powerful tool to create purity–conduction relationships and to quickly quantify conduction patterns in terms of co-occurrence energy and contrast. We anticipate this first preliminary study to be a starting point for more sophisticated analyses of different co-culture systems. In particular, in view of stem cell therapies, we expect co-occurrence analysis to provide valuable quantitative insight into the integration of foreign cells into a functional host system.

Computational Modelling of Optogenetics in Cardiac Cells

Channelrhodopsin-2 (ChR2) is a light-activated ion channel that can allow scientists to electrically activate cells via optical stimulation. Using a combination of existing computational electrophysiological and mechanical cardiac cell models with a novel ChR2 ion channel model, we created a model for ChR2-transduced cardiac myocytes. We implemented this model into a commonly available finite element platform and simulated both the single cell and the tissue electromechanical response. Our simulations show that it is possible to stimulate cardiac tissue optically with ChR2-transduced cells.Copyright

Finite Element Modeling of Mechanically Driven Skin Growth due to Different Expander Geometries

Tissue expansion has become an important technique used in breast reconstruction after mastectomy and for repairing large damaged skin areas such as burns [1]. According to the National Cancer Institute, the estimated number of breast cancer cases in 2010 in the United States was 207,090 [2]. Many of these women underwent mastectomies, and tissue expanders were used for breast reconstruction as a common procedure afterwards. Even though several studies from clinical and experimental points of view have been presented, there is still a poor understanding of the mechanobiological procedures occurring during skin growth. In particular, it is of interest to determine the effect of expanders with different geometries in strain, stress, and area gained during expansion.Copyright

Computational Simulation of Biventricular Pacing in an Asymptomatic Human Heart

Cardiac resynchronization therapy (CRT) through biventricular stimulation was first used in the early 1990s as a treatment option for patients with systolic heart failure, intraventricular conduction delay, and other cardiac arrhythmias [1]. CRT, also known as biventricular pacing (BiVP), is an alternative to right ventricular stimulation, which induces dyssynchronous ventricular contraction. In BiVP, three pacing leads are usually placed on the myocardium of the right atrium, the right ventricle, and the left ventricle in the distal cardiac vein. Because there are no standardized loci for lead placement in BiVP, physicians rely on trial and error when inserting pacemaker leads and use electrocardiograms (ECG) to determine the effectiveness of the BiVP lead placement. The ECG measures the electrical conduction, contraction pacing, and projections of the anatomy of the myocardium. Abnormalities in the sinusoidal waves of the ECG reveal problems. Therefore, the ECG can depict a quantitative representation of the effectiveness of biventricular pacing lead placement.© 2011 ASME

Computational Simulation of Traveling Arrhythmic Waves in Myocardial Tissue

Cardiac arrhythmias are common cardiac disorders characterized by irregular electrical activity of the heart. Each year in the United States alone, about half a million deaths and 835,000 hospital discharges result from arrhythmias. In fact, atrial fibrillation is responsible for 15–20% of all ischemic strokes [1]. Due to the complexity of the electrical conduction pathways in myocardium, computational models are useful platforms for gaining insight into the origin of arrhythmias, as well as the development of corrective options. For these purposes, a quantitative finite element model based on the phenomenological Aliev and Panfilov model [2] was implemented to characterize the electrical behavior of cardiac tissue. Several examples of simulated re-entrant spiral waves demonstrate that our implementation can indeed capture the electrical aspects of cardiac tissue.Copyright