A fully adaptive numerical approximation for a two-dimensional epidemic model with nonlinear cross-diffusion

An epidemic model is formulated by a reactionâeuro"diffusion system where the spatial pattern formation is driven by cross-diffusion. The reaction terms describe the local dynamics of susceptible and infected species, whereas the diffusion terms account for the spatial distribution dynamics. For both self-diffusion and cross-diffusion, nonlinear constitutive assumptions are suggested. To simulate the pattern formation two finite volume formulations are proposed, which employ a conservative and a non-conservative discretization, respectively. An efficient simulation is obtained by a fully adaptive multiresolution strategy. Numerical examples illustrate the impact of the cross-diffusion on the pattern formation.

Simulation of stromatolite growth using diffusion-limited aggregation and a discrete model of biogeochemical exchanges in microbial mat

Resume : Mieux comprendre les stromatolithes et les tapis microbiens est un sujet important en biogéosciences puisque cela aide à l'étude des premières formes de vie sur Terre, a mieux cerner l'écologie des communautés microbiennes et la contribution des microorganismes a la biominéralisation, et même à poser certains fondements dans les recherches en exobiologie. D'autre part, la modélisation est un outil puissant utilisé dans les sciences naturelles pour appréhender différents phénomènes de façon théorique. Les modèles sont généralement construits sur un système d'équations différentielles et les résultats sont obtenus en résolvant ce système. Les logiciels disponibles pour implémenter les modèles incluent les logiciels mathématiques et les logiciels généraux de simulation. L'objectif principal de cette thèse est de développer des modèles et des logiciels pour aider a comprendre, via la simulation, le fonctionnement des stromatolithes et des tapis microbiens. Ces logiciels ont été développés en C++ en ne partant d'aucun pré-requis de façon a privilégier performance et flexibilité maximales. Cette démarche permet de construire des modèles bien plus spécifiques et plus appropriés aux phénomènes a modéliser. Premièrement, nous avons étudié la croissance et la morphologie des stromatolithes. Nous avons construit un modèle tridimensionnel fondé sur l'agrégation par diffusion limitée. Le modèle a été implémenté en deux applications C++: un moteur de simulation capable d'exécuter un batch de simulations et de produire des fichiers de résultats, et un outil de visualisation qui permet d'analyser les résultats en trois dimensions. Après avoir vérifié que ce modèle peut en effet reproduire la croissance et la morphologie de plusieurs types de stromatolithes, nous avons introduit un processus de sédimentation comme facteur externe. Ceci nous a mené a des résultats intéressants, et permis de soutenir l'hypothèse que la morphologie des stromatolithes pourrait être le résultat de facteurs externes autant que de facteurs internes. Ceci est important car la classification des stromatolithes est généralement fondée sur leur morphologie, imposant que la forme d'un stromatolithe est dépendante de facteurs internes uniquement (c'est-à-dire les tapis microbiens). Les résultats avancés dans ce mémoire contredisent donc ces assertions communément admises. Ensuite, nous avons décidé de mener des recherches plus en profondeur sur les aspects fonctionnels des tapis microbiens. Nous avons construit un modèle bidimensionnel de réaction-diffusion fondé sur la simulation discrète. Ce modèle a été implémenté dans une application C++ qui permet de paramétrer et exécuter des simulations. Nous avons ensuite pu comparer les résultats de simulation avec des données du monde réel et vérifier que le modèle peut en effet imiter le comportement de certains tapis microbiens. Ainsi, nous avons pu émettre et vérifier des hypothèses sur le fonctionnement de certains tapis microbiens pour nous aider à mieux en comprendre certains aspects, comme la dynamique des éléments, en particulier le soufre et l'oxygène. En conclusion, ce travail a abouti à l'écriture de logiciels dédiés à la simulation de tapis microbiens d'un point de vue tant morphologique que fonctionnel, suivant deux approches différentes, l'une holistique, l'autre plus analytique. Ces logiciels sont gratuits et diffusés sous licence GPL (General Public License). Abstract : Better understanding of stromatolites and microbial mats is an important topic in biogeosciences as it helps studying the early forms of life on Earth, provides clues re- garding the ecology of microbial ecosystems and their contribution to biomineralization, and gives basis to a new science, exobiology. On the other hand, modelling is a powerful tool used in natural sciences for the theoretical approach of various phenomena. Models are usually built on a system of differential equations and results are obtained by solving that system. Available software to implement models includes mathematical solvers and general simulation software. The main objective of this thesis is to develop models and software able to help to understand the functioning of stromatolites and microbial mats. Software was developed in C++ from scratch for maximum performance and flexibility. This allows to build models much more specific to a phenomenon rather than general software. First, we studied stromatolite growth and morphology. We built a three-dimensional model based on diffusion-limited aggregation. The model was implemented in two C++ applications: a simulator engine, which can run a batch of simulations and produce result files, and a Visualization tool, which allows results to be analysed in three dimensions. After verifying that our model can indeed reproduce the growth and morphology of several types of stromatolites, we introduced a sedimentation process as an external factor. This lead to interesting results, and allowed to emit the hypothesis that stromatolite morphology may be the result of external factors as much as internal factors. This is important as stromatolite classification is usually based on their morphology, imposing that a stromatolite shape is dependant on internal factors only (i.e. the microbial mat). This statement is contradicted by our findings, Second, we decided to investigate deeper the functioning of microbial mats, We built a two-dimensional reaction-diffusion model based on discrete simulation, The model was implemented in a C++ application that allows setting and running simulations. We could then compare simulation results with real world data and verify that our model can indeed mimic the behaviour of some microbial mats. Thus, we have proposed and verified hypotheses regarding microbial mats functioning in order to help to better understand them, e.g. the cycle of some elements such as oxygen or sulfur. ln conclusion, this PhD provides a simulation software, dealing with two different approaches. This software is free and available under a GPL licence.

A methodology for the adaptation of a PMP at the determination of a PMF

This paper presents a new type of very fine grid hydrological model based on the spatiotemporal repartition of a PMP (Probable Maximum Precipitation) and on the topography. The goal is to estimate the influence of this rain on a PMF (Probable Maximum Flood) on a catchment area in Switzerland. The spatiotemporal distribution of the PMP was realized using six clouds modeled by the advection-diffusion equation. The equation shows the movement of the clouds over the terrain and also gives the evolution of the rain intensity in time. This hydrological modeling is followed by a hydraulic modeling of the surface and subterranean flow, done considering the factors that contribute to the hydrological cycle, such as the infiltration, the resurgence and the snowmelt. These added factors make the developed model closer to reality and also offer flexibility in the initial condition that is added to the factors concerning the PMP, such as the duration of the rain, the speed and direction of the wind. All these initial conditions taken together offer a complete image of the PMF.

The estimation of PMP and PMF on alpine basins in Switzerland

This paper presents a very fine grid hydrological model based on the spatiotemporal repartition of precipitation and on the topography. The goal is to estimate the flood on a catchment area, using a Probable Maximum Precipitation (PMP) leading to a Probable Maximum Flood (PMF). The spatiotemporal distribution of the precipitation was realized using six clouds modeled by the advection-diffusion equation. The equation shows the movement of the clouds over the terrain and also gives the evolution of the rain intensity in time. This hydrological modeling is followed by a hydraulic modeling of the surface and subterranean flows, done considering the factors that contribute to the hydrological cycle, such as the infiltration, the exfiltration and the snowmelt. This model was applied to several Swiss basins using measured rain, with results showing a good correlation between the simulated and observed flows. This good correlation proves that the model is valid and gives us the confidence that the results can be extrapolated to phenomena of extreme rainfall of PMP type. In this article we present some results obtained using a PMP rainfall and the developed model.

An active strain electromechanical model for cardiac tissue

We propose a finite element approximation of a system of partial differential equations describing the coupling between the propagation of electrical potential and large deformations of the cardiac tissue. The underlying mathematical model is based on the active strain assumption, in which it is assumed that a multiplicative decomposition of the deformation tensor into a passive and active part holds, the latter carrying the information of the electrical potential propagation and anisotropy of the cardiac tissue into the equations of either incompressible or compressible nonlinear elasticity, governing the mechanical response of the biological material. In addition, by changing from an Eulerian to a Lagrangian configuration, the bidomain or monodomain equations modeling the evolution of the electrical propagation exhibit a nonlinear diffusion term. Piecewise quadratic finite elements are employed to approximate the displacements field, whereas for pressure, electrical potentials and ionic variables are approximated by piecewise linear elements. Various numerical tests performed with a parallel finite element code illustrate that the proposed model can capture some important features of the electromechanical coupling, and show that our numerical scheme is efficient and accurate.

Diverse set of Turing nanopatterns coat corneae across insect lineages.

Nipple-like nanostructures covering the corneal surfaces of moths, butterflies, and Drosophila have been studied by electron and atomic force microscopy, and their antireflective properties have been described. In contrast, corneal nanostructures of the majority of other insect orders have either been unexamined or examined by methods that did not allow precise morphological characterization. Here we provide a comprehensive analysis of corneal surfaces in 23 insect orders, revealing a rich diversity of insect corneal nanocoatings. These nanocoatings are categorized into four major morphological patterns and various transitions between them, many, to our knowledge, never described before. Remarkably, this unexpectedly diverse range of the corneal nanostructures replicates the complete set of Turing patterns, thus likely being a result of processes similar to those modeled by Alan Turing in his famous reaction-diffusion system. These findings reveal a beautiful diversity of insect corneal nanostructures and shed light on their molecular origin and evolutionary diversification. They may also be the first-ever biological example of Turing nanopatterns.

Targeting anticancer therapy : clinical and preclinical approaches

AbstractCancer treatment has shifted from cytotoxic and nonspecific chemotherapy to chronic treatment with targeted molecular therapies. These new classes of drugs directed against cancer-specific molecules and signaling pathways, act at a particular level of the tumor cell development. However, in both types of therapeutic approaches (standard cytotoxic chemotherapy and targeted signal transduction inhibitions), toxicity and side effects can occur. The aim of this thesis was to investigate various approaches to improve the activity and tolerability of cancer treatment, in a clinical setting, a) by molecular targeting through the use of tyrosine kinase inhibitors (TKIs), whose dosage can be adapted to each patient according to plasma levels, and, b) in a preclinical model, by tissue targeting with locoregional administration of cytotoxic chemotherapy to increase drug exposure in the target tissue while reducing systemic toxicity of the treatment.A comprehensive program for the Therapeutic Drug Monitoring (TDM) of the new class of targeted anticancer drugs of TKIs in patient's blood has been therefore initiated comprising the setting up, validation and clinical application of a multiplex assay by liquid chromatography coupled to tandem mass spectrometry of TKIs in plasma from cancer patients. Information on drugs exposure may be clinically useful for an optimal follow-up of patients' anticancer treatment, especially in case of less than optimal clinical response, occurrence of adverse drug reaction effects and the numerous risks of drug-drug interactions. In this context, better knowledge of the potential drug interactions between TKIs and widely prescribed co- medications is of critical importance for clinicians, to improve their daily care of cancer patients. For one of the first TKI imatinib, TDM interpretation is nowadays based on total plasma concentrations but, only the unbound (free) form is likely to enter cell to exert its pharmacological action. Pharmacokinetic analysis of the total and free plasma level of imatinib measured simultaneously in patients have allowed to refine and validate a population pharmacokinetic model integrating factors influencing in patients the exposure of pharmacological active species. The equation developed from this model may be used for extrapolating free imatinib plasma concentration based on the total plasma levels that are currently measured in TDM from patients. Finally, the specific influence of Pglycoprotein on the intracellular disposition of TKIs has been studies in cell systems using the siRNA silencing approach.Another approach to enhance the selectivity of anticancer treatment may be achieved by the loco-regional administration of a cytostatic agent to the target organ while sparing non- affected tissues. Isolated lung perfusion (ILP) was designed for the treatment of loco-regional malignancies of the lung but clinical results have been so far disappointing. It has been shown in a preclinical model in rats that ILP with the cytotoxic agent doxorubicin alone allows a high drug uptake in lung tissue, and a low systemic toxicity, but was characterized by a high spatial tissular heterogeneity in drug exposure and doxorubicin uptake in tumor was comparatively smaller than in normal lung tissue. Photodynamic therapy (PDT) is a new approach for the treatment of superficial tumors, and implies the application of a sensitizer activated by a laser light at a specific wavelength, that disrupts endothelial barrier of tumor vessels to increase locally the distribution of cytostatics into the tumor tissue. PDT pre-treatment before intravenous administration of liposomal doxorubicin was indeed shown to selectively increase drug uptake in tumors in a rat model of sarcoma tumors to the lung.RésuméLe traitement de certains cancers s'est progressivement transformé et est passé de la chimiothérapie, cytotoxique et non spécifique, au traitement chronique des patients avec des thérapies moléculaires ciblées. Ces médicaments ont une action ciblée en interférant à un niveau spécifique du développement de la cellule tumorale. Dans les deux types d'approches thérapeutiques (chimiothérapie cytotoxique et traitements ciblés), on est confronté à la présence de toxicité et aux effets secondaires du traitement anticancéreux. Le but de cette thèse a donc été d'étudier diverses approches visant à améliorer l'efficacité et la tolérabilité du traitement anticancéreux, a) dans le cadre d'une recherche clinique, par le ciblage moléculaire grâce aux inhibiteurs de tyrosines kinases (TKIs) dont la posologie est adaptée à chaque patient, et b) dans un modèle préclinique, par le ciblage tissulaire grâce à l'administration locorégionale de chimiothérapie cytotoxique, afin d'augmenter l'exposition dans le tissu cible et de réduire la toxicité systémique du traitement.Un programme de recherche sur le suivi thérapeutique (Therapeutic Drug Monitoring, TDM) des inhibiteurs de tyrosine kinases a été ainsi mis en place et a impliqué le développement, la validation et l'application clinique d'une méthode multiplex par chromatographie liquide couplée à la spectrométrie de masse en tandem des TKIs chez les patients souffrant de cancer. L'information fournie par le TDM sur l'exposition des patients aux traitements ciblés est cliniquement utile et est susceptible d'optimiser la dose administrée, notamment dans les cas où la réponse clinique au traitement des patients est sous-optimale, en présence d'effets secondaires du traitement ciblé, ou lorsque des risques d'interactions médicamenteuses sont suspectés. Dans ce contexte, l'étude des interactions entre les TKIs et les co-médications couramment associées est utile pour les cliniciens en charge d'améliorer au jour le jour la prise en charge du traitement anticancéreux. Pour le premier TKI imatinib, l'interprétation TDM est actuellement basée sur la mesure des concentrations plasmatiques totales alors que seule la fraction libre (médicament non lié aux protéines plasmatiques circulantes) est susceptible de pénétrer dans la cellule pour exercer son action pharmacologique. L'analyse pharmacocinétique des taux plasmatiques totaux et libres d'imatinib mesurés simultanément chez les patients a permis d'affiner et de valider un modèle de pharmacocinétique de population qui intègre les facteurs influençant l'exposition à la fraction de médicament pharmacologiquement active. L'équation développée à partir de ce modèle permet d'extrapoler les concentrations libres d'imatinib à partir des concentrations plasmatiques totales qui sont actuellement mesurées lors du TDM des patients. Finalement, l'influence de la P-glycoprotéine sur la disposition cellulaire des TKIs a été étudiée dans un modèle cellulaire utilisant l'approche par la technologie du siRNA permettant de bloquer sélectivement l'expression du gène de cette protéine d'efflux des médicaments.Une autre approche pour augmenter la sélectivité du traitement anticancéreux consiste en une administration loco-régionale d'un agent cytostatique directement au sein de l'organe cible tout en préservant les tissus sains. La perfusion isolée du poumon (ILP) a été conçue pour le traitement loco-régional des cancers affectant les tissus pulmonaires mais les résultats cliniques ont été jusqu'à ce jour décevants. Dans des modèles précliniques chez le rat, il a pu être démontré que l'ILP avec la doxorubicine, un agent cytotoxique, administré seul, permet une exposition élevée au niveau du tissu pulmonaire, et une faible toxicité systémique. Toutefois, cette technique est caractérisée par une importante variabilité de la distribution dans les tissus pulmonaires et une pénétration du médicament au sein de la tumeur comparativement plus faible que dans les tissus sains.La thérapie photodynamique (PDT) est une nouvelle approche pour le traitement des tumeurs superficielles, qui consiste en l'application d'un agent sensibilisateur activé par une lumière laser de longueur d'onde spécifique, qui perturbe l'intégrité physiologique de la barrière endothéliale des vaisseaux alimentant la tumeur et permet d'augmenter localement la pénétration des agents cytostatiques.Nos études ont montré qu'un pré-traitement par PDT permet d'augmenter sélectivement l'absorption de doxorubicine dans les tumeurs lors d'administration i.v. de doxorubicine liposomale dans un modèle de sarcome de poumons de rongeurs.Résumé large publicDepuis une dizaine d'année, le traitement de certains cancers s'est progressivement transformé et les patients qui devaient jusqu'alors subir des chimiothérapies, toxiques et non spécifiques, peuvent maintenant bénéficier de traitements chroniques avec des thérapies ciblées. Avec les deux types d'approches thérapeutiques, on reste cependant confronté à la toxicité et aux effets secondaires du traitement.Le but de cette thèse a été d'étudier chez les patients et dans des modèles précliniques les diverses approches visant à améliorer l'activité et la tolérance des traitements à travers un meilleur ciblage de la thérapie anticancéreuse. Cet effort de recherche nous a conduits à nous intéresser à l'optimisation du traitement par les inhibiteurs de tyrosines kinases (TKIs), une nouvelle génération d'agents anticancéreux ciblés agissant sélectivement sur les cellules tumorales, en particulier chez les patients souffrant de leucémie myéloïde chronique et de tumeurs stromales gastro-intestinales. L'activité clinique ainsi que la toxicité de ces TKIs paraissent dépendre non pas de la dose de médicament administrée, mais de la quantité de médicaments circulant dans le sang auxquelles les tumeurs cancéreuses sont exposées et qui varient beaucoup d'un patient à l'autre. A cet effet, nous avons développé une méthode par chromatographie couplée à la spectrométrie de masse pour mesurer chez les patients les taux de médicaments de la classe des TKIs dans la perspective de piloter le traitement par une approche de suivi thérapeutique (Therapeutic Drug Monitoring, TDM). Le TDM repose sur la mesure de la quantité de médicament dans le sang d'un patient dans le but d'adapter individuellement la posologie la plus appropriée: des quantités insuffisantes de médicament dans le sang peuvent conduire à un échec thérapeutique alors qu'un taux sanguin excessif peut entraîner des manifestations toxiques.Dans une seconde partie préclinique, nous nous sommes concentrés sur l'optimisation de la chimiothérapie loco-régionale dans un modèle de sarcome du poumon chez le rat, afin d'augmenter l'exposition dans la tumeur tout en réduisant la toxicité dans les tissus non affectés.La perfusion isolée du poumon (ILP) permet d'administrer un médicament anticancéreux cytotoxique comme la doxorubicine, sélectivement au niveau le tissu pulmonaire où sont généralement localisées les métastases de sarcome. L'administration par ILP de doxorubicine, toxique pour le coeur, a permis une forte accumulation des médicaments dans le poumon, tout en épargnant le coeur. Il a été malheureusement constaté que la doxorubicine ne pénètre que faiblement dans la tumeur sarcomateuse, témoignant des réponses cliniques décevantes observées avec cette approche en clinique. Nous avons ainsi étudié l'impact sur la pénétration tumorale de l'association d'une chimiothérapie cytotoxique avec la thérapie photodynamique (PDT) qui consiste en l'irradiation spécifique du tissu-cible cancéreux, après l'administration d'un agent photosensibilisateur. Dans ce modèle animal, nous avons observé qu'un traitement par PDT permet effectivement d'augmenter de façon sélective l'accumulation de doxorubicine dans les tumeurs lors d'administration intraveineuse de médicament.

Devolatilization-induced pressure build-up: Implications for reaction front movement and breccia pipe formation

Generation of fluids during metamorphism can significantly influence the fluid overpressure, and thus the fluid flow in metamorphic terrains. There is currently a large focus on developing numerical reactive transport models, and with it follows the need for analytical solutions to ensure correct numerical implementation. In this study, we derive both analytical and numerical solutions to reaction-induced fluid overpressure, coupled to temperature and fluid flow out of the reacting front. All equations are derived from basic principles of conservation of mass, energy and momentum. We focus on contact metamorphism, where devolatilization reactions are particularly important owing to high thermal fluxes allowing large volumes of fluids to be rapidly generated. The analytical solutions reveal three key factors involved in the pressure build-up: (i) The efficiency of the devolatilizing reaction front (pressure build-up) relative to fluid flow (pressure relaxation), (ii) the reaction temperature relative to the available heat in the system and (iii) the feedback of overpressure on the reaction temperature as a function of the Clapeyron slope. Finally, we apply the model to two geological case scenarios. In the first case, we investigate the influence of fluid overpressure on the movement of the reaction front and show that it can slow down significantly and may even be terminated owing to increased effective reaction temperature. In the second case, the model is applied to constrain the conditions for fracturing and inferred breccia pipe formation in organic-rich shales owing to methane generation in the contact aureole.

Negative control of keratinocyte differentiation by Rho/CRIK signaling coupled with up-regulation of KyoT1/2 (FHL1) expression.

Rho GTPases integrate control of cell structure and adhesion with downstream signaling events. In keratinocytes, RhoA is activated at early times of differentiation and plays an essential function in establishment of cell-cell adhesion. We report here that, surprisingly, Rho signaling suppresses downstream gene expression events associated with differentiation. Similar inhibitory effects are exerted by a specific Rho effector, CRIK (Citron kinase), which is selectively down-modulated with differentiation, thereby allowing the normal process to occur. The suppressing function of Rho/CRIK on differentiation is associated with induction of KyoT1/2, a LIM domain protein gene implicated in integrin-mediated processes and/or Notch signaling. Like activated Rho and CRIK, elevated KyoT1/2 expression suppresses differentiation. Thus, Rho signaling exerts an unexpectedly complex role in keratinocyte differentiation, which is coupled with induction of KyoT1/2, a LIM domain protein gene with a potentially important role in control of cell self renewal.

A rapid assay for the coupled cell free generation of oxylipins

We developed a rapid and simple assay for the coupled in vitro synthesis of oxylipins using free unsaturated fatty acids as substrates. Reactions were catalysed with extracts expressed from living plant tissues. Preliminary experiments involving the cell free transformation of fatty acid hydroperoxides revealed that storage or pretreatment of the plant extract rapidly altered its capacity to catalyse the generation of oxidised fatty acid derivatives. This could reflect changes in oxylipin generation that might take place in situ in damaged plant cells during herbivory. All subsequent experiments were performed without dilution, titration or any other modification of the plant extract prior to its addition to the assay system. The assays were used to study, for the first time, tissue-specific differences in fatty acid transformation to divinyl ethers. Root tissues from tomato efficiently catalysed the formation of corneleic and colnelenic acids from linoleic acid and linolenic acids, respectively, whereas leaf, hypocotyl and cotyledon extracts did not promote the formation of these compounds. We observed the efficient generation of 9-oxo-nonanoic acid from the substrate linolenic acid and speculate that this aldehyde could arise either from the action of hydroperoxide lyase on 9-hydroperoxylinolenic acid or by a novel route involving cleavage of colnelenic acid which was also present among the products of the reaction. A potential role of divinyl ethers as substrates for the generation of toxic aldehydes is discussed

Wipe sampling procedure coupled to LC-MS/MS analysis for the simultaneous determination of 10 cytotoxic drugs on different surfaces.

A simple wipe sampling procedure was developed for the surface contamination determination of ten cytotoxic drugs: cytarabine, gemcitabine, methotrexate, etoposide phosphate, cyclophosphamide, ifosfamide, irinotecan, doxorubicin, epirubicin and vincristine. Wiping was performed using Whatman filter paper on different surfaces such as stainless steel, polypropylene, polystyrol, glass, latex gloves, computer mouse and coated paperboard. Wiping and desorption procedures were investigated: The same solution containing 20% acetonitrile and 0.1% formic acid in water gave the best results. After ultrasonic desorption and then centrifugation, samples were analysed by a validated liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) in selected reaction monitoring mode. The whole analytical strategy from wipe sampling to LC-MS/MS analysis was evaluated to determine quantitative performance. The lowest limit of quantification of 10 ng per wiping sample (i.e. 0.1 ng cm(-2)) was determined for the ten investigated cytotoxic drugs. Relative standard deviation for intermediate precision was always inferior to 20%. As recovery was dependent on the tested surface for each drug, a correction factor was determined and applied for real samples. The method was then successfully applied at the cytotoxic production unit of the Geneva University Hospitals pharmacy.

Estimation of jump-diffusion processes via empirical characteristic functions

Preface The starting point for this work and eventually the subject of the whole thesis was the question: how to estimate parameters of the affine stochastic volatility jump-diffusion models. These models are very important for contingent claim pricing. Their major advantage, availability T of analytical solutions for characteristic functions, made them the models of choice for many theoretical constructions and practical applications. At the same time, estimation of parameters of stochastic volatility jump-diffusion models is not a straightforward task. The problem is coming from the variance process, which is non-observable. There are several estimation methodologies that deal with estimation problems of latent variables. One appeared to be particularly interesting. It proposes the estimator that in contrast to the other methods requires neither discretization nor simulation of the process: the Continuous Empirical Characteristic function estimator (EGF) based on the unconditional characteristic function. However, the procedure was derived only for the stochastic volatility models without jumps. Thus, it has become the subject of my research. This thesis consists of three parts. Each one is written as independent and self contained article. At the same time, questions that are answered by the second and third parts of this Work arise naturally from the issues investigated and results obtained in the first one. The first chapter is the theoretical foundation of the thesis. It proposes an estimation procedure for the stochastic volatility models with jumps both in the asset price and variance processes. The estimation procedure is based on the joint unconditional characteristic function for the stochastic process. The major analytical result of this part as well as of the whole thesis is the closed form expression for the joint unconditional characteristic function for the stochastic volatility jump-diffusion models. The empirical part of the chapter suggests that besides a stochastic volatility, jumps both in the mean and the volatility equation are relevant for modelling returns of the S&P500 index, which has been chosen as a general representative of the stock asset class. Hence, the next question is: what jump process to use to model returns of the S&P500. The decision about the jump process in the framework of the affine jump- diffusion models boils down to defining the intensity of the compound Poisson process, a constant or some function of state variables, and to choosing the distribution of the jump size. While the jump in the variance process is usually assumed to be exponential, there are at least three distributions of the jump size which are currently used for the asset log-prices: normal, exponential and double exponential. The second part of this thesis shows that normal jumps in the asset log-returns should be used if we are to model S&P500 index by a stochastic volatility jump-diffusion model. This is a surprising result. Exponential distribution has fatter tails and for this reason either exponential or double exponential jump size was expected to provide the best it of the stochastic volatility jump-diffusion models to the data. The idea of testing the efficiency of the Continuous ECF estimator on the simulated data has already appeared when the first estimation results of the first chapter were obtained. In the absence of a benchmark or any ground for comparison it is unreasonable to be sure that our parameter estimates and the true parameters of the models coincide. The conclusion of the second chapter provides one more reason to do that kind of test. Thus, the third part of this thesis concentrates on the estimation of parameters of stochastic volatility jump- diffusion models on the basis of the asset price time-series simulated from various "true" parameter sets. The goal is to show that the Continuous ECF estimator based on the joint unconditional characteristic function is capable of finding the true parameters. And, the third chapter proves that our estimator indeed has the ability to do so. Once it is clear that the Continuous ECF estimator based on the unconditional characteristic function is working, the next question does not wait to appear. The question is whether the computation effort can be reduced without affecting the efficiency of the estimator, or whether the efficiency of the estimator can be improved without dramatically increasing the computational burden. The efficiency of the Continuous ECF estimator depends on the number of dimensions of the joint unconditional characteristic function which is used for its construction. Theoretically, the more dimensions there are, the more efficient is the estimation procedure. In practice, however, this relationship is not so straightforward due to the increasing computational difficulties. The second chapter, for example, in addition to the choice of the jump process, discusses the possibility of using the marginal, i.e. one-dimensional, unconditional characteristic function in the estimation instead of the joint, bi-dimensional, unconditional characteristic function. As result, the preference for one or the other depends on the model to be estimated. Thus, the computational effort can be reduced in some cases without affecting the efficiency of the estimator. The improvement of the estimator s efficiency by increasing its dimensionality faces more difficulties. The third chapter of this thesis, in addition to what was discussed above, compares the performance of the estimators with bi- and three-dimensional unconditional characteristic functions on the simulated data. It shows that the theoretical efficiency of the Continuous ECF estimator based on the three-dimensional unconditional characteristic function is not attainable in practice, at least for the moment, due to the limitations on the computer power and optimization toolboxes available to the general public. Thus, the Continuous ECF estimator based on the joint, bi-dimensional, unconditional characteristic function has all the reasons to exist and to be used for the estimation of parameters of the stochastic volatility jump-diffusion models.

Estimation of a maximum Lu diffusion rate in a natural eclogite garnet

Lutetium zoning in garnet within eclogites from the Zermatt-Saas Fee zone, Western Alps, reveal sharp, exponentially decreasing central peaks. They can be used to constrain maximum Lu volume diffusion in garnets. A prograde garnet growth temperature interval of 450-600 A degrees C has been estimated based on pseudosection calculations and garnet-clinopyroxene thermometry. The maximum pre-exponential diffusion coefficient which fits the measured central peak is in the order of D-0= 5.7*10(-6) m(2)/s, taking an estimated activation energy of 270 kJ/mol based on diffusion experiments for other rare earth elements in garnet. This corresponds to a maximum diffusion rate of D (600 A degrees C) = 4.0*10(-22) m(2)/s. The diffusion estimate of Lu can be used to estimate the minimum closure temperature, T-c, for Sm-Nd and Lu-Hf age data that have been obtained in eclogites of the Western Alps, postulating, based on a literature review, that D (Hf) < D (Nd) < D (Sm) a parts per thousand currency sign D (Lu). T-c calculations, using the Dodson equation, yielded minimum closure temperatures of about 630 A degrees C, assuming a rapid initial exhumation rate of 50A degrees/m.y., and an average crystal size of garnets (r = 1 mm). This suggests that Sm/Nd and Lu/Hf isochron age differences in eclogites from the Western Alps, where peak temperatures did rarely exceed 600 A degrees C must be interpreted in terms of prograde metamorphism.

Interplay of oxidative, nitrosative/nitrative stress, inflammation, cell death and autophagy in diabetic cardiomyopathy.

Diabetes is a recognized risk factor for cardiovascular diseases and heart failure. Diabetic cardiovascular dysfunction also underscores the development of diabetic retinopathy, nephropathy and neuropathy. Despite the broad availability of antidiabetic therapy, glycemic control still remains a major challenge in the management of diabetic patients. Hyperglycemia triggers formation of advanced glycosylation end products (AGEs), activates protein kinase C, enhances polyol pathway, glucose autoxidation, which coupled with elevated levels of free fatty acids, and leptin have been implicated in increased generation of superoxide anion by mitochondria, NADPH oxidases and xanthine oxidoreductase in diabetic vasculature and myocardium. Superoxide anion interacts with nitric oxide forming the potent toxin peroxynitrite via diffusion limited reaction, which in concert with other oxidants triggers activation of stress kinases, endoplasmic reticulum stress, mitochondrial and poly(ADP-ribose) polymerase 1-dependent cell death, dysregulates autophagy/mitophagy, inactivates key proteins involved in myocardial calcium handling/contractility and antioxidant defense, activates matrix metalloproteinases and redox-dependent pro-inflammatory transcription factors (e.g. nuclear factor kappaB) promoting inflammation, AGEs formation, eventually culminating in myocardial dysfunction, remodeling and heart failure. Understanding the complex interplay of oxidative/nitrosative stress with pro-inflammatory, metabolic and cell death pathways is critical to devise novel targeted therapies for diabetic cardiomyopathy, which will be overviewed in this brief synopsis. This article is part of a Special Issue entitled: Autophagy and protein quality control in cardiometabolic diseases.

Use of the dried blood spot sampling process coupled with fast gas chromatography and negative-ion chemical ionization tandem mass spectrometry: application to fluoxetine, norfluoxetine, reboxetine, and paroxetine analysis.

The objective of this work was to combine the advantages of the dried blood spot (DBS) sampling process with the highly sensitive and selective negative-ion chemical ionization tandem mass spectrometry (NICI-MS-MS) to analyze for recent antidepressants including fluoxetine, norfluoxetine, reboxetine, and paroxetine from micro whole blood samples (i.e., 10 microL). Before analysis, DBS samples were punched out, and antidepressants were simultaneously extracted and derivatized in a single step by use of pentafluoropropionic acid anhydride and 0.02% triethylamine in butyl chloride for 30 min at 60 degrees C under ultrasonication. Derivatives were then separated on a gas chromatograph coupled with a triple-quadrupole mass spectrometer operating in negative selected reaction monitoring mode for a total run time of 5 min. To establish the validity of the method, trueness, precision, and selectivity were determined on the basis of the guidelines of the "Société Française des Sciences et des Techniques Pharmaceutiques" (SFSTP). The assay was found to be linear in the concentration ranges 1 to 500 ng mL(-1) for fluoxetine and norfluoxetine and 20 to 500 ng mL(-1) for reboxetine and paroxetine. Despite the small sampling volume, the limit of detection was estimated at 20 pg mL(-1) for all the analytes. The stability of DBS was also evaluated at -20 degrees C, 4 degrees C, 25 degrees C, and 40 degrees C for up to 30 days. Furthermore, the method was successfully applied to a pharmacokinetic investigation performed on a healthy volunteer after oral administration of a single 40-mg dose of fluoxetine. Thus, this validated DBS method combines an extractive-derivative single step with a fast and sensitive GC-NICI-MS-MS technique. Using microliter blood samples, this procedure offers a patient-friendly tool in many biomedical fields such as checking treatment adherence, therapeutic drug monitoring, toxicological analyses, or pharmacokinetic studies.