Virtual cardiac monolayers for electrical wave propagation

The complex structure of cardiac tissue is considered to be one of the main determinants of an arrhythmogenic substrate. This study is aimed at developing the first mathematical model to describe the formation of cardiac tissue, using a joint in silico-in vitro approach. First, we performed experiments under various conditions to carefully characterise the morphology of cardiac tissue in a culture of neonatal rat ventricular cells. We considered two cell types, namely, cardiomyocytes and fibroblasts. Next, we proposed a mathematical model, based on the Glazier-Graner-Hogeweg model, which is widely used in tissue growth studies. The resultant tissue morphology was coupled to the detailed electrophysiological Korhonen-Majumder model for neonatal rat ventricular cardiomyocytes, in order to study wave propagation. The simulated waves had the same anisotropy ratio and wavefront complexity as those in the experiment. Thus, we conclude that our approach allows us to reproduce the morphological and physiological properties of cardiac tissue

EHV-1 Pathogenesis: Current in vitro Models and Future Perspectives

Primary infection and pathogenesis of equine herpesvirus type 1 (EHV-1) require an intricate interaction of virus with the mucosal epithelium, mononuclear cells and the vascular endothelium. Studies on EHV-1 have been facilitated by the development of different in vitro models that recapitulate the in vivo tissue complexity. The available in vitro assays can be categorized into (i) models mimicking the epithelium-peripheral blood mononuclear cell (PBMC) interaction, which include ex vivo mucosal (nasal and vaginal) explants and equine respiratory epithelial cells (EREC) cultures; and (ii) PBMC-endothelium mimicking models, including flow chamber and contact assays. These in vitro models have proven their worth in attempts to recapitulate the in vivo architecture and complexity, produce data relevant to natural host infection, and reduce animal use due to in vivo experiments. Although horse models are still needed for certain experiments, e.g., EHV-1 myeloencephalopathy or vaccination studies, available in vitro models can be used to obtain highly valuable data on virus-host tissue interactions. Microfluidic based 3D culture system (e.g., horse-on-a-chip) could be a potential upgraded version of these in vitro models for future research

Development of a protocol for maintaining viability while shipping organoid-derived retinal tissue.

Retinal organoid technology enables generation of an inexhaustible supply of three-dimensional retinal tissue from human pluripotent stem cells (hPSCs) for regenerative medicine applications. The high similarity of organoid-derived retinal tissue and transplantable human fetal retina provides an opportunity for evaluating and modeling retinal tissue replacement strategies in relevant animal models in the effort to develop a functional retinal patch to restore vision in patients with profound blindness caused by retinal degeneration. Because of the complexity of this very promising approach requiring specialized stem cell and grafting techniques, the tasks of retinal tissue derivation and transplantation are frequently split between geographically distant teams. Delivery of delicate and perishable neural tissue such as retina to the surgical sites requires a reliable shipping protocol and also controlled temperature conditions with damage-reporting mechanisms in place to prevent transplantation of tissue damaged in transit into expensive animal models. We have developed a robust overnight tissue shipping protocol providing reliable temperature control, live monitoring of the shipment conditions and physical location of the package, and damage reporting at the time of delivery. This allows for shipping of viable (transplantation-competent) hPSC-derived retinal tissue over large distances, thus enabling stem cell and surgical teams from different parts of the country to work together and maximize successful engraftment of organoid-derived retinal tissue. Although this protocol was developed for preclinical in vivo studies in animal models, it is potentially translatable for clinical transplantation in the future and will contribute to developing clinical protocols for restoring vision in patients with retinal degeneration

Analysis of Passive Charge Balancing for Safe Current-Mode Neural Stimulation

Charge balancing has been often considered as one of the most critical requirement for neural stimulation circuits. Over the years several solutions have been proposed to precisely balance the charge transferred to the tissue during anodic and cathodic phases. Elaborate dynamic current sources/sinks with improved matching, and feedback loops have been proposed with a penalty on circuit complexity, area or power consumption. Here we review the dominant assumptions in safe stimulation protocols, and derive mathematical models to determine the effectiveness of passive charge balancing in a typical application scenario

Evolution and development of Brain Networks: From Caenorhabditis elegans to Homo sapiens

Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes involving a limited amount of tasks and modalities to complex functional and behavioral processing integrating different kinds of information from highly specialized tissue. However, studies in a range of species suggest that fundamental similarities, in spatial and topological features as well as in developmental mechanisms for network formation, are retained across evolution. 'Small-world' topology and highly connected regions (hubs) are prevalent across the evolutionary scale, ensuring efficient processing and resilience to internal (e.g. lesions) and external (e.g. environment) changes. Furthermore, in most species, even the establishment of hubs, long-range connections linking distant components, and a modular organization, relies on similar mechanisms. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints

Engineering vascularised tissues in vitro

Tissue engineering aims at replacing or regenerating tissues lost due to diseases or traumas (Langer and Vacanti, 1993). However, mimicking in vitro the physiological complexity of vascularized tissue is a major obstacle, which possibly contributes to impaired healing in vivo. In higher organisms, native features including the vascular network, the lymphatic networks and interstitial flow promote both mass transport and organ development. Attempts to mimic those features in engineered tissues will lead to more clinically relevant cell-based therapies. Aside from current strategies promoting angiogenesis from the host, an alternative concept termed prevascularization is emerging. It aims at creating a biological vasculature inside an engineered tissue prior to implantation. This vasculature can rapidly anastamose with the host and enhances tissue survival and differentiation. Interestingly, growing evidence supports a role of the vasculature in regulating pattern formation and tissue differentiation. Thus, prevascularized tissues also benefit from an intrinsic contribution of their vascular system to their development. From those early attempts are emerging a body of principles and strategies to grow and maintain, in vitro, those self-assembled biological vascular networks. This could lead to the generation of engineered tissues of more physiologically relevant complexity and improved regenerative potential

Hyperspectral colon tissue cell classification

A novel algorithm to discriminate between normal and malignant tissue cells of the human colon is presented. The microscopic level images of human colon tissue cells were acquired using hyperspectral imaging technology at contiguous wavelength intervals of visible light. While hyperspectral imagery data provides a wealth of information, its large size normally means high computational processing complexity. Several methods exist to avoid the so-called curse of dimensionality and hence reduce the computational complexity. In this study, we experimented with Principal Component Analysis (PCA) and two modifications of Independent Component Analysis (ICA). In the first stage of the algorithm, the extracted components are used to separate four constituent parts of the colon tissue: nuclei, cytoplasm, lamina propria, and lumen. The segmentation is performed in an unsupervised fashion using the nearest centroid clustering algorithm. The segmented image is further used, in the second stage of the classification algorithm, to exploit the spatial relationship between the labeled constituent parts. Experimental results using supervised Support Vector Machines (SVM) classification based on multiscale morphological features reveal the discrimination between normal and malignant tissue cells with a reasonable degree of accuracy