Genetic Epidemiology of Glaucoma

Glaucoma is a heterogeneous group of optic neuropathies that have in common an accelerated degeneration of retinal ganglion cells and their axons, a subsequent typical excavation of the optic disc and a concomitant pattern of irreversible visual field loss. Glaucoma affects approximately 2% of individuals of European descent and up to 10% of individuals of sub-Saharan African descent over 50 years of age. It is a progressive disease, which without adequate treatment can result in severe visual disability and eventually blindness. Primary open-angle glaucoma (POAG) is the predominant form of glaucoma in Western countries. The disease is distinct from other forms of glaucoma through its age-related, insidious onset and an unobstructed iridocorneal angle with a normal appearance. Traditionally, an elevated intraocular pressure (IOP) was part of the clinical definition. However, an estimated 20 - 50% of all patients with otherwise characteristic POAG have IOPs consistently within the normal range (a condition referred to as “normal tension glaucoma”), whereas most individuals with an elevated IOP do not have any signs of glaucomatous optic neuropathy or visual field loss (a condition called “ocular hypertension”). Nevertheless, an elevated IOP is considered an important causative factor and the major risk factor for POAG. The 10-year incidence of glaucomatous visual field loss has been reported to increase by 11% [6-15%] per millimeter of mercury increase in IOP. Moreover, IOP is currently the only modifiable risk factor. Lowering the IOP, either by medication or surgically, has been shown to reduce the risk of conversion from ocular hypertension to glaucoma and to slow down the progression of glaucoma

Signal processing in slit-scan flow cytometry of cell conjugates

The design and implementation of a real-time signal processing system for slit-scan flow cytometry is described. The system is used to measure the separate scatter and fluorescence peak heights of 2 adherent cells. Preliminary measurements of changes in the membrane potential induced by interactions between natural killer (NK) cells and their target cells are presented

Modeling Morphogenesis in silico and in vitro: Towards Quantitative, Predictive, Cell-based Modeling

Cell-based, mathematical models help make sense of morphogenesis—i.e. cells organizing into shape and pattern—by capturing cell behavior in simple, purely descriptive models. Cell-based models then predict the tissue-level patterns the cells produce collectively. The first step in a cell-based modeling approach is to isolate sub-processes, e.g. the patterning capabilities of one or a few cell types in cell cultures. Cell-based models can then identify the mechanisms responsible for patterning in vitro. This review discusses two cell culture models of morphogenesis that have been studied using this combined experimental-mathematical approach: chondrogenesis (cartilage patterning) and vasculogenesis (de novo blood vessel growth). In both these systems, radically dif- ferent models can equally plausibly explain the in vitro patterns. Quantitative descriptions of cell behavior would help choose between alternative models. We will briefly review the experimental methodology (microfluidics technology and traction force microscopy) used to measure responses of individual cells to their micro-environment, including chemical gradients, physical forces and neighboring cells. We conclude by discussing how to include quantitative cell descriptions into a cell-based model: the Cellular Potts model

Computational modeling of angiogenesis: towards a multi-scale understanding of cell-cell and cell-matrix interactions

Combined with in vitro and in vivo experiments, mathematical and com- putational modeling are key to unraveling how mechanical and chemical signaling by endothelial cells coordinates their organization into capillary-like tubes. While in vitro and in vivo experiments can unveil the effects of for example environmental changes or gene knockouts, computational models provide a way to formalize and understand the mechanisms underlying these observations. This chapter reviews re- cent computational approaches to model angiogenesis, and discusses the insights they provide in the mechanisms of angiogenesis. We introduce a new cell-based computational model of an in vitro assay of angio- genic sprouting from endothelial monolayers in fibrin matrices. Endothelial cells are modeled by the Cellular Potts Model, combined with continuum descriptions to model haptotaxis and proteolysis of the extracellular matrix. The computational model demonstrates how a variety of cellular structural properties and behaviors determine the dynamics of tube formation. We aim to extend this model to a multi-scale model in the sense that cells, extracellular matrix and cell-regulation are de- scribed at different levels of detail and feedback on each other. Finally we discuss how computational modeling, combined with in vitro and in vivo modeling steers experiments, and how it generates new experimental hypotheses and insights on the mechanics of angiogenesis