Nuclear Architecture: Image Processing and Analyses

Cancer is one of the most well-known groups of diseases that finds its cause in cells having chromosomal aberrations. How and why these aberrations can occur is one of the most important questions asked in modern molecular biology. In the last decades it has become clear that gene regulation in the nucleus, where the chromosomes reside, is strongly correlated with structural organization of nuclear components like the telomeres, centromeres and the chromosomes. With new microscopes, better cameras and new fluorescent labels, the demand for analyses of all the images that can be made is growing. The goal of this thesis is the development of image processing and analyses methods for three dimensional (3D) images acquired by fluorescence microscopy. Several microscopy techniques are described, together with two techniques to visualize the nuclear components (chapter 2). In chapter 3 several deconvolution methods are described. Chapter 4 gives two methods to segment the components in the images. Several analyses can be done after segmentation. In chapter 4 we show, after localization, that telomeres from mouse lymphocytes redistribute into a disk-like structure during G2. In chapter 5 we give a novel method to determine the relative length of telomeres by measuring the integrated intensity in the 3D images. Using this information we can define extremely high signals as telomere aggregates. In chapter 6 we use the segmentation and localization techniques to measure the radial redistributions of components in human mesenchymal stem cells.Applied Science

A network model for the biofilm growth in porous media and its effects on permeability and porosity

Successful microbial enhanced oil recovery depends on several factors like reservoir characteristics and microbial activity. In this work, a pore network is used to study the hydrodynamic evolution over time as a result of the development of a biofilm in the pores. A new microscopic model is proposed for biofilm growth which takes into account that nutrients might not fully penetrate the biofilm. An important novelty in this model is that acknowledges the continuous spreading of the biofilm over the network. The results from the current study can be used to obtain a new relation between the porosity and permeability which might be used as an alternative to the Kozeny Carman relation.</p

A network model for the biolm growth evolution in porous media and its eects on permeability and porosity

Numerical AnalysisMathematical Physic

A Network Model for the Kinetics of Bioclogged Flow Diversion for Enhanced Oil Recovery

After the primary extraction in oil reservoirs up to 60 % of the oil remains trapped in the reservoir (Sen, 2008). Therefore, different mechanisms have been developed to get the oil out to the reservoir. One of these techniques is Microbial Enhanced Oil Recovery (MEOR) which is a technique used to produce more oil in a secondary extraction by using microbes in the reservoir. The main effects caused by microbes in oil recovery is the reduction of the interfacial tension between oil and water, wettability change of the rock and bioclogging caused by the growth and development of biofilm. Among these mechanisms, interfacial tension reduction and biclogging is thought to have the greatest impact on recovery (Sen, 2008). In this work, we describe the growth of biofilm, the growth of the microbial population and the transport of nutrients using a pore network model. We follow the previous models of Thullner et al. (Thullner, 2008) and Ezeuko et al. (Ezeuko, 2011) in which the biofilm is considered as a permeable layer. We consider the biofilm and the bacteria separately. Additionally, we assume that once a tube is full with biofilm, this biofilm can spread to the neighboring tubes. Finally, we study the changes in the hydrodynamic properties of the medium caused by the plugging of the pores and we study the flow diversion of water caused by plugging of the high permeability zones.Numerical AnalysisMathematical Physic

A network model for the biofilm growth in porous media and its effects on permeability and porosity

Successful microbial enhanced oil recovery depends on several factors like reservoir characteristics and microbial activity. In this work, a pore network is used to study the hydrodynamic evolution over time as a result of the development of a biofilm in the pores. A new microscopic model is proposed for biofilm growth which takes into account that nutrients might not fully penetrate the biofilm. An important novelty in this model is that acknowledges the continuous spreading of the biofilm over the network. The results from the current study can be used to obtain a new relation between the porosity and permeability which might be used as an alternative to the Kozeny Carman relation.Numerical AnalysisMathematical Physic

Conditions for upscalability of bioclogging in pore network models

In this work, we model the biofilm growth at the microscale using a rectangular pore network model in 2D and a cubic network in 3D. For the 2D network, we study the effects of bioclogging on porosity and permeability when we change parameters like the number of nodes in the network, the network size, and the concentration of nutrients at the inlet. We use a 3D cubic network to study the influence of the number of nodes in the z direction on the biofilm growth and on upscalability. We show that the biofilm can grow uniformly or heterogeneously through the network. Using these results, we determine the conditions for upscalability of bioclogging for rectangular and cubic networks. If there is uniform biofilm growth, there is a unique relation between permeability and porosity, K ∼ ϕ2, this relation does not depend on the volume of the network, therefore the system is upscalable. However, if there is preferential biofilm growth, the porosity-permeability relation is not uniquely defined, hence upscalability is not possible. The Damköhler number is used to determine when upscalability is possible. If the Damköhler number is less than 101, the biofilm grows uniformly and therefore the system is upscalable. However, if the Damköhler number is greater than 103, the biofilm growth exhibits a deviation from uniform biofilm growth and heterogeneous growth is observed, therefore upscalability is not possible. There is a transition from uniform growth to preferential growth if the Damköhler number is between 101 and 103.Numerical AnalysisMathematical Physic