Investigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography.

Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.

Minimum error contrast enhancement

Contrast enhancement is an image processing technique where the objective is to preprocess the image so that relevant information can be either seen or further processed more reliably. These techniques are typically applied when the image itself or the device used for image reproduction provides poor visibility and distinguishability of different regions of interest inthe image. In most studies, the emphasis is on the visualization of image data,but this human observer biased goal often results to images which are not optimal for automated processing. The main contribution of this study is to express the contrast enhancement as a mapping from N-channel image data to 1-channel gray-level image, and to devise a projection method which results to an image with minimal error to the correct contrast image. The projection, the minimum-error contrast image, possess the optimal contrast between the regions of interest in the image. The method is based on estimation of the probability density distributions of the region values, and it employs Bayesian inference to establish the minimum error projection.

Lentiviral vectors efficiently transduce the EGFP gene into cardiomyocytes in vivo : immunohistology and Elisa quantification of the transgene

RESUME Les maladies cardio-vasculaires représentent la cause la plus importante de mortalité et de morbidité dans les pays occidentaux. La thérapie génique offre une nouvelle approche au traitement de ces maladies. L'expression de gènes protecteurs dans le myocarde par des technologies de transfert génique peut améliorer la fonction ventriculaire lors de l'insuffisance cardiaque ou stimuler la formation de nouveaux vaisseaux dans la maladie coronarienne. Etant donné qu'une majorité des maladies cardiaques sont des maladies chroniques, l'expression durable du gène thérapeutique introduit dans le coeur est souhaitable dans de nombreux cas. Malheureusement, l'utilité des vecteurs de transfert génique les plus utilisés en thérapie génique cardiovasculaire est limitée par une performance faible (ADN plasmidique) et une courte durée d'expression (adénovirus). Récemment, des vecteurs de transfert génique dérivés des lentivirus, une sous-famille des rétrovirus, ont retenu l'attention de la communauté scientifique en raison de leur capacité à exprimer des gènes à long terme. Contrairement aux vecteurs rétroviraux traditionnels, les vecteurs lentiviraux transduisent des gènes même dans des cellules qui ne se divisent pas, ce qui est le cas des cardiomyocytes adultes. Ces vecteurs présentent un profil de biosécurité comparable à celui des vecteurs rétroviraux traditionnels. Nous avons donc décidé de tester l'utilité des vecteurs lentiviraux pour le transfert génique dans des cardiomyocytes de rat adulte in vitro et in vivo. Plusieurs versions de vecteurs lentiviraux contenant différent promoteurs ont été construites. Ces vecteurs contenant le gène marqueur EGFP (enhanced green fluorescent protein) ont été testés dans des cardiomyocytes de rat in vitro, ainsi que dans des coeurs de rat in vivo. Le but de ces expériences était de déterminer la durée de l'expression du transgène après injection intramyocardique chez le rat. Pour ce faire, nous avons développé une technique ELISA pour détecter la protéine EGFP dans des extraits de tissu cardiaque. Les résultats ont montré que la protéine EGFP était encore présente à des niveaux significatifs jusqu'à dix semaines après l'injection de vecteurs lentiviraux, alors que l'expression transgénique obtenue avec un vecteur adénoviral traditionnel a été plus limitée dans le temps. Ces résultats démontrent la capacité des vecteurs lentiviraux à exprimer des gènes d'intérêt de manière performante et stable dans le cœur de rat adulte in vivo. SUMMARY Cardiovascular diseases are the first cause of morbidity and mortality in Western countries. Gene therapy offers a new approach to these diseases. Expression of therapeutic genes in the myocardium by gene transfer technologies can improve ventricular function in heart failure and stimulate neovascularization in coronary disease. Chronic heart diseases likely require sustained expression of the therapeutic gene within the heart itself. Unfortunately, the most commonly used vectors in cardiovascular gene therapy, i.e. plasmid DNA and recombinant adenovirus vectors, are limited by poor DNA uptake and transient transgene expression, respectively. Recently, lentivirus-derived vectors have attracted much interest because of their ability to achieve long-term transgene expression. In contrast to traditional retroviral vectors, lentiviral vectors are also able to transduce non- dividing cells, while presenting a comparable biosafety profile. Adult cardiomyocytes are terminally differentiated cells that do not divide under normal conditions. For these reasons, we have decided to evaluate the efficiency of lentiviral vectors for gene-transduction of adult cardiomyocytes both in vitro and in vivo. We constructed various types of lentiviral vectors containing various promoters. Vectors encoding EGFP as a reporter gene were tested in rat cardiomyocytes in vitro and in rat hearts in vivo. The aim of the experiments involved in this thesis work was to determine the duration of the expression of the transgene after rat intramyocardial injection using a quantitative assay. Therefore, an ELISA technique was set up to measure the EGFP protein in rat heart tissue extracts. Our results showed that the EGFP protein was still present at significant levels at ten weeks after lentiviral vector injection, whereas the duration of expression with adenoviral vectors was shorter. These results demonstrate that lentiviral vectors efficiently deliver genes and achieve sustained transgene expression in adult rat cardiomyocytes in vivo.

Development of a hepatocyte hollow fiber bioreactor for the study of contrast agents by magnetic resonance imaging

Thanks to the continuous progress made in recent years, medical imaging has become an important tool in the diagnosis of various pathologies. In particular, magnetic resonance imaging (MRI) permits to obtain images with a remarkably high resolution without the use of ionizing radiation and is consequently widely applied for a broad range of conditions in all parts of the body. Contrast agents are used in MRI to improve tissue discrimination. Different categories of contrast agents are clinically available, the most widely used being gadolinium chelates. One can distinguish between extracellular gadolinium chelates such as Gd-DTPA, and hepatobiliary gadolinium chelates such as Gd-BOPTA. The latter are able to enter hepatocytes from where they are partially excreted into the bile to an extent dependent on the contrast agent and animal species. Due to this property, hepatobiliary contrast agents are particularly interesting for the MRI of the liver. Actually, a change in signal intensity can result from a change in transport functions signaling the presence of impaired hepatocytes, e.g. in the case of focal (like cancer) or diffuse (like cirrhosis) liver diseases. Although the excretion mechanism into the bile is well known, the uptake mechanisms of hepatobiliary contrast agents into hepatocytes are still not completely understood and several hypotheses have been proposed. As a good knowledge of these transport mechanisms is required to allow an efficient diagnosis by MRI of the functional state of the liver, more fundamental research is needed and an efficient MRI compatible in vitro model would be an asset. So far, most data concerning these transport mechanisms have been obtained by MRI with in vivo models or by a method of detection other than MRI with cellular or sub-cellular models. Actually, no in vitro model is currently available for the study and quantification of contrast agents by MRI notably because high cellular densities are needed to allow detection, and no metallic devices can be used inside the magnet room, which is incompatible with most tissue or cell cultures that require controlled temperature and oxygenation. The aim of this thesis is thus to develop an MRI compatible in vitro cellular model to study the transport of hepatobiliary contrast agents, in particular Gd-BOPTA, into hepatocytes directly by MRI. A better understanding of this transport and especially of its modification in case of hepatic disorder could permit in a second step to extrapolate this knowledge to humans and to use the kinetics of hepatobiliary contrast agents as a tool for the diagnosis of hepatic diseases.

Identifying quantitative operation principles in metabolic pathways: a systematic method for searching feasible enzyme activity patterns leading to cellular adaptive responses

Background: Optimization methods allow designing changes in a system so that specific goals are attained. These techniques are fundamental for metabolic engineering. However, they are not directly applicable for investigating the evolution of metabolic adaptation to environmental changes. Although biological systems have evolved by natural selection and result in well-adapted systems, we can hardly expect that actual metabolic processes are at the theoretical optimum that could result from an optimization analysis. More likely, natural systems are to be found in a feasible region compatible with global physiological requirements. Results: We first present a new method for globally optimizing nonlinear models of metabolic pathways that are based on the Generalized Mass Action (GMA) representation. The optimization task is posed as a nonconvex nonlinear programming (NLP) problem that is solved by an outer- approximation algorithm. This method relies on solving iteratively reduced NLP slave subproblems and mixed-integer linear programming (MILP) master problems that provide valid upper and lower bounds, respectively, on the global solution to the original NLP. The capabilities of this method are illustrated through its application to the anaerobic fermentation pathway in Saccharomyces cerevisiae. We next introduce a method to identify the feasibility parametric regions that allow a system to meet a set of physiological constraints that can be represented in mathematical terms through algebraic equations. This technique is based on applying the outer-approximation based algorithm iteratively over a reduced search space in order to identify regions that contain feasible solutions to the problem and discard others in which no feasible solution exists. As an example, we characterize the feasible enzyme activity changes that are compatible with an appropriate adaptive response of yeast Saccharomyces cerevisiae to heat shock Conclusion: Our results show the utility of the suggested approach for investigating the evolution of adaptive responses to environmental changes. The proposed method can be used in other important applications such as the evaluation of parameter changes that are compatible with health and disease states.

Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock

Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. Results: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. Conclusion: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.

Quantitative developmental response to the length of exposure to long photoperiod in wheat and barley

The present study was designed to analyse the effect of the length of exposure to a long photoperiod imposed c. 3 weeks after sowing in spring wheat (cv. UQ189) and barley (cv. Arapiles) to (i) establish whether the response to the number of cycles of exposure is quantitative or qualitative, (ii) determine the existence of a commitment to particular stages well before the stage has been observable, and (iii) study the interrelationships between the effects on final leaf number and phyllochron when the stimulus is provided several days after seedling emergence. Both wheat and barley seemed to respond quantitatively to the number of long-day cycles they were exposed to. However, wheat showed a requirement of approximately 4 long-day cycles to be able to produce a significant response in time to heading. The barley cultivar used in the study was responsive to the minimum length of exposure. The response to extended photoperiod cycles during the stem elongation phase was due to the ‘ memory’ photoperiod effects being related, in the case of wheat, to the fact that the pre-terminal spikelet appearance phase saturated its photoperiod response well before that stage was reached. Therefore, the commitment to the terminal spikelet appearance in wheat may be reached well before this stage could be recognized. As the response in duration to heading exceeded that of the final leaf number, and the stem elongation phase responded to memory effects of photoperiod, the phyllochron of both cereals was responsive to the treatments accelerating the average phyllochron when exposed to longer periods of long days. The response in average phyllochron was due to a switch from bi-linear to linear models of leaf number v. time when the conditions were increasingly inductive, with the phyllochron of the initial (6–8) leaves being similar for all treatments (within each species), and from then on increased.

Selection of internal control genes for real-time quantitative PCR in ovary and uterus of sows across pregnancy

Reproductive traits play a key role in pig production in order to reduce costs and increase economic returns. Among others, gene expression analyses represent a useful approach to study genetic mechanisms underlying reproductive traits in pigs. The application of reverse-transcription quantitative PCR requires the selection of appropriate reference genes, whose expression levels should not be affected by the experimental conditions, especially when comparing gene expression across different physiological stages.