Activation of Transient Receptor Potential Canonical 3 (TRPC3)-mediated Ca2+ Entry by A1 Adenosine Receptor in Cardiomyocytes Disturbs Atrioventricular Conduction.

Although the activation of the A(1)-subtype of the adenosine receptors (A(1)AR) is arrhythmogenic in the developing heart, little is known about the underlying downstream mechanisms. The aim of this study was to determine to what extent the transient receptor potential canonical (TRPC) channel 3, functioning as receptor-operated channel (ROC), contributes to the A(1)AR-induced conduction disturbances. Using embryonic atrial and ventricular myocytes obtained from 4-day-old chick embryos, we found that the specific activation of A(1)AR by CCPA induced sarcolemmal Ca(2+) entry. However, A(1)AR stimulation did not induce Ca(2+) release from the sarcoplasmic reticulum. Specific blockade of TRPC3 activity by Pyr3, by a dominant negative of TRPC3 construct, or inhibition of phospholipase Cs and PKCs strongly inhibited the A(1)AR-enhanced Ca(2+) entry. Ca(2+) entry through TRPC3 was activated by the 1,2-diacylglycerol (DAG) analog OAG via PKC-independent and -dependent mechanisms in atrial and ventricular myocytes, respectively. In parallel, inhibition of the atypical PKCζ by myristoylated PKCζ pseudosubstrate inhibitor significantly decreased the A(1)AR-enhanced Ca(2+) entry in both types of myocytes. Additionally, electrocardiography showed that inhibition of TRPC3 channel suppressed transient A(1)AR-induced conduction disturbances in the embryonic heart. Our data showing that A(1)AR activation subtly mediates a proarrhythmic Ca(2+) entry through TRPC3-encoded ROC by stimulating the phospholipase C/DAG/PKC cascade provide evidence for a novel pathway whereby Ca(2+) entry and cardiac function are altered. Thus, the A(1)AR-TRPC3 axis may represent a potential therapeutic target.

Détermination des vents extrêmes à l'aide d'analyses statistiques et de modélisations numériques dans une topographie accidentée en Suisse.

Les constructions en Suisse et en Europe doivent être dimensionnées pour subir sans dommages des vents extrêmes (rafales) avec une période de retour d'au moins 50 ans. Des analyses de Gumbel ont donc été effectuées sur des séries de mesures d'une vingtaine d'années à 67 endroits de la Suisse, afin de déterminer les vitesses extrêmes des vents pour différents courants régionaux. Elles ont abouti à de bons résultats pour la majorité des endroits. Mais ces vitesses extrêmes ne peuvent être extrapolées linéairement aux autres régions dans une topographie aussi accidentée que la Suisse. Un modèle numérique tridimensionnel des écoulements non hydrostatique a été expérimenté pour calculer les champs de vent extrêmes en Suisse avec une résolution horizontale de 2 km et une période de retour de 50 ans. Ces modélisations ont permis de reproduire de manière satisfaisante ces vents extrêmes pour l'ensemble du pays. Toutefois, elles sous-estiment leurs intensités sur les reliefs jurassiens et alpins, comparativement aux vallées alpines et au Plateau Suisse.

Electromagnetic radiation initiated by hadronic jets from microquasars in the ISM

Microquasars are potential candidates to produce a non-negligible fraction of the observed galactic cosmic rays. The protons accelerated at the jet termination shock interact with the interstellar medium and may produce detectable fluxes of extended emission at different energy bands: high-energy and very high-energy gamma-rays produced by neutral pion-decay, synchrotron and bremsstrahlung emission in a wide energy range generated by the secondary electrons produced by charged pion-decay. We discuss the association between this scenario and some of the unidentified EGRET sources in the galactic plane.

Time-lapse and probabilistic inversion strategies for plane-wave electromagnetic data.

L'utilisation efficace des systèmes géothermaux, la séquestration du CO2 pour limiter le changement climatique et la prévention de l'intrusion d'eau salée dans les aquifères costaux ne sont que quelques exemples qui démontrent notre besoin en technologies nouvelles pour suivre l'évolution des processus souterrains à partir de la surface. Un défi majeur est d'assurer la caractérisation et l'optimisation des performances de ces technologies à différentes échelles spatiales et temporelles. Les méthodes électromagnétiques (EM) d'ondes planes sont sensibles à la conductivité électrique du sous-sol et, par conséquent, à la conductivité électrique des fluides saturant la roche, à la présence de fractures connectées, à la température et aux matériaux géologiques. Ces méthodes sont régies par des équations valides sur de larges gammes de fréquences, permettant détudier de manières analogues des processus allant de quelques mètres sous la surface jusqu'à plusieurs kilomètres de profondeur. Néanmoins, ces méthodes sont soumises à une perte de résolution avec la profondeur à cause des propriétés diffusives du champ électromagnétique. Pour cette raison, l'estimation des modèles du sous-sol par ces méthodes doit prendre en compte des informations a priori afin de contraindre les modèles autant que possible et de permettre la quantification des incertitudes de ces modèles de façon appropriée. Dans la présente thèse, je développe des approches permettant la caractérisation statique et dynamique du sous-sol à l'aide d'ondes EM planes. Dans une première partie, je présente une approche déterministe permettant de réaliser des inversions répétées dans le temps (time-lapse) de données d'ondes EM planes en deux dimensions. Cette stratégie est basée sur l'incorporation dans l'algorithme d'informations a priori en fonction des changements du modèle de conductivité électrique attendus. Ceci est réalisé en intégrant une régularisation stochastique et des contraintes flexibles par rapport à la gamme des changements attendus en utilisant les multiplicateurs de Lagrange. J'utilise des normes différentes de la norme l2 pour contraindre la structure du modèle et obtenir des transitions abruptes entre les régions du model qui subissent des changements dans le temps et celles qui n'en subissent pas. Aussi, j'incorpore une stratégie afin d'éliminer les erreurs systématiques de données time-lapse. Ce travail a mis en évidence l'amélioration de la caractérisation des changements temporels par rapport aux approches classiques qui réalisent des inversions indépendantes à chaque pas de temps et comparent les modèles. Dans la seconde partie de cette thèse, j'adopte un formalisme bayésien et je teste la possibilité de quantifier les incertitudes sur les paramètres du modèle dans l'inversion d'ondes EM planes. Pour ce faire, je présente une stratégie d'inversion probabiliste basée sur des pixels à deux dimensions pour des inversions de données d'ondes EM planes et de tomographies de résistivité électrique (ERT) séparées et jointes. Je compare les incertitudes des paramètres du modèle en considérant différents types d'information a priori sur la structure du modèle et différentes fonctions de vraisemblance pour décrire les erreurs sur les données. Les résultats indiquent que la régularisation du modèle est nécessaire lorsqu'on a à faire à un large nombre de paramètres car cela permet d'accélérer la convergence des chaînes et d'obtenir des modèles plus réalistes. Cependent, ces contraintes mènent à des incertitudes d'estimations plus faibles, ce qui implique des distributions a posteriori qui ne contiennent pas le vrai modèledans les régions ou` la méthode présente une sensibilité limitée. Cette situation peut être améliorée en combinant des méthodes d'ondes EM planes avec d'autres méthodes complémentaires telles que l'ERT. De plus, je montre que le poids de régularisation des paramètres et l'écart-type des erreurs sur les données peuvent être retrouvés par une inversion probabiliste. Finalement, j'évalue la possibilité de caractériser une distribution tridimensionnelle d'un panache de traceur salin injecté dans le sous-sol en réalisant une inversion probabiliste time-lapse tridimensionnelle d'ondes EM planes. Etant donné que les inversions probabilistes sont très coûteuses en temps de calcul lorsque l'espace des paramètres présente une grande dimension, je propose une stratégie de réduction du modèle ou` les coefficients de décomposition des moments de Legendre du panache de traceur injecté ainsi que sa position sont estimés. Pour ce faire, un modèle de résistivité de base est nécessaire. Il peut être obtenu avant l'expérience time-lapse. Un test synthétique montre que la méthodologie marche bien quand le modèle de résistivité de base est caractérisé correctement. Cette méthodologie est aussi appliquée à un test de trac¸age par injection d'une solution saline et d'acides réalisé dans un système géothermal en Australie, puis comparée à une inversion time-lapse tridimensionnelle réalisée selon une approche déterministe. L'inversion probabiliste permet de mieux contraindre le panache du traceur salin gr^ace à la grande quantité d'informations a priori incluse dans l'algorithme. Néanmoins, les changements de conductivités nécessaires pour expliquer les changements observés dans les données sont plus grands que ce qu'expliquent notre connaissance actuelle des phénomenès physiques. Ce problème peut être lié à la qualité limitée du modèle de résistivité de base utilisé, indiquant ainsi que des efforts plus grands devront être fournis dans le futur pour obtenir des modèles de base de bonne qualité avant de réaliser des expériences dynamiques. Les études décrites dans cette thèse montrent que les méthodes d'ondes EM planes sont très utiles pour caractériser et suivre les variations temporelles du sous-sol sur de larges échelles. Les présentes approches améliorent l'évaluation des modèles obtenus, autant en termes d'incorporation d'informations a priori, qu'en termes de quantification d'incertitudes a posteriori. De plus, les stratégies développées peuvent être appliquées à d'autres méthodes géophysiques, et offrent une grande flexibilité pour l'incorporation d'informations additionnelles lorsqu'elles sont disponibles. -- The efficient use of geothermal systems, the sequestration of CO2 to mitigate climate change, and the prevention of seawater intrusion in coastal aquifers are only some examples that demonstrate the need for novel technologies to monitor subsurface processes from the surface. A main challenge is to assure optimal performance of such technologies at different temporal and spatial scales. Plane-wave electromagnetic (EM) methods are sensitive to subsurface electrical conductivity and consequently to fluid conductivity, fracture connectivity, temperature, and rock mineralogy. These methods have governing equations that are the same over a large range of frequencies, thus allowing to study in an analogous manner processes on scales ranging from few meters close to the surface down to several hundreds of kilometers depth. Unfortunately, they suffer from a significant resolution loss with depth due to the diffusive nature of the electromagnetic fields. Therefore, estimations of subsurface models that use these methods should incorporate a priori information to better constrain the models, and provide appropriate measures of model uncertainty. During my thesis, I have developed approaches to improve the static and dynamic characterization of the subsurface with plane-wave EM methods. In the first part of this thesis, I present a two-dimensional deterministic approach to perform time-lapse inversion of plane-wave EM data. The strategy is based on the incorporation of prior information into the inversion algorithm regarding the expected temporal changes in electrical conductivity. This is done by incorporating a flexible stochastic regularization and constraints regarding the expected ranges of the changes by using Lagrange multipliers. I use non-l2 norms to penalize the model update in order to obtain sharp transitions between regions that experience temporal changes and regions that do not. I also incorporate a time-lapse differencing strategy to remove systematic errors in the time-lapse inversion. This work presents improvements in the characterization of temporal changes with respect to the classical approach of performing separate inversions and computing differences between the models. In the second part of this thesis, I adopt a Bayesian framework and use Markov chain Monte Carlo (MCMC) simulations to quantify model parameter uncertainty in plane-wave EM inversion. For this purpose, I present a two-dimensional pixel-based probabilistic inversion strategy for separate and joint inversions of plane-wave EM and electrical resistivity tomography (ERT) data. I compare the uncertainties of the model parameters when considering different types of prior information on the model structure and different likelihood functions to describe the data errors. The results indicate that model regularization is necessary when dealing with a large number of model parameters because it helps to accelerate the convergence of the chains and leads to more realistic models. These constraints also lead to smaller uncertainty estimates, which imply posterior distributions that do not include the true underlying model in regions where the method has limited sensitivity. This situation can be improved by combining planewave EM methods with complimentary geophysical methods such as ERT. In addition, I show that an appropriate regularization weight and the standard deviation of the data errors can be retrieved by the MCMC inversion. Finally, I evaluate the possibility of characterizing the three-dimensional distribution of an injected water plume by performing three-dimensional time-lapse MCMC inversion of planewave EM data. Since MCMC inversion involves a significant computational burden in high parameter dimensions, I propose a model reduction strategy where the coefficients of a Legendre moment decomposition of the injected water plume and its location are estimated. For this purpose, a base resistivity model is needed which is obtained prior to the time-lapse experiment. A synthetic test shows that the methodology works well when the base resistivity model is correctly characterized. The methodology is also applied to an injection experiment performed in a geothermal system in Australia, and compared to a three-dimensional time-lapse inversion performed within a deterministic framework. The MCMC inversion better constrains the water plumes due to the larger amount of prior information that is included in the algorithm. The conductivity changes needed to explain the time-lapse data are much larger than what is physically possible based on present day understandings. This issue may be related to the base resistivity model used, therefore indicating that more efforts should be given to obtain high-quality base models prior to dynamic experiments. The studies described herein give clear evidence that plane-wave EM methods are useful to characterize and monitor the subsurface at a wide range of scales. The presented approaches contribute to an improved appraisal of the obtained models, both in terms of the incorporation of prior information in the algorithms and the posterior uncertainty quantification. In addition, the developed strategies can be applied to other geophysical methods, and offer great flexibility to incorporate additional information when available.

Precursor uptake assays and metabolic analyses in isolated tomato fruit chromoplasts

Background Carotenoids are the most widespread group of pigments found in nature. In addition to their role in the physiology of the plant, carotenoids also have nutritional relevance as their incorporation in the human diet provides health benefits. In non-photosynthetic tissues, carotenoids are synthesized and stored in specialized plastids called chromoplasts. At present very little is known about the origin of the metabolic precursors and cofactors required to sustain the high rate of carotenoid biosynthesis in these plastids. Recent proteomic data have revealed a number of biochemical and metabolic processes potentially operating in fruit chromoplasts. However, considering that chloroplast to chromoplast differentiation is a very rapid process during fruit ripening, there is the possibility that some of the proteins identified in the proteomic analysis could represent remnants no longer having a functional role in chromoplasts. Therefore, experimental validation is necessary to prove whether these predicted processes are actually operative in chromoplasts. Results A method has been established for high-yield purification of tomato fruit chromoplasts suitable for metabolic studies. Radiolabeled precursors were efficiently incorporated and further metabolized in isolated chromoplast. Analysis of labeled lipophilic compounds has revealed that lipid biosynthesis is a very efficient process in chromoplasts, while the relatively low incorporation levels found in carotenoids suggest that lipid production may represent a competing pathway for carotenoid biosynthesis. Malate and pyruvate are efficiently converted into acetyl-CoA, in agreement with the active operation of the malic enzyme and the pyruvate dehydrogenase complex in the chromoplast. Our results have also shown that isolated chromoplasts can actively sustain anabolic processes without the exogenous supply of ATP, thus suggesting that these organelles may generate this energetic cofactor in an autonomous way. Conclusions We have set up a method for high yield purification of intact tomato fruit chromoplasts suitable for precursor uptake assays and metabolic analyses. Using targeted radiolabeled precursors we have been able to unravel novel biochemical and metabolic aspects related with carotenoid and lipid biosynthesis in tomato fruit chromoplasts. The reported chromoplast system could represent a valuable platform to address the validation and characterization of functional processes predicted from recent transcriptomic and proteomic data.

Glibenclamide enhances neurogenesis and improves long-term functional recovery after transient focal cerebral ischemia

Glibenclamide is neuroprotective against cerebral ischemia in rats. We studied whether glibenclamide enhances long-term brain repair and improves behavioral recovery after stroke. Adult male Wistar rats were subjected to transient middle cerebral artery occlusion (MCAO) for 90 minutes. A low dose of glibenclamide (total 0.6mg) was administered intravenously 6, 12, and 24 hours after reperfusion. We assessed behavioral outcome during a 30-day follow-up and animals were perfused for histological evaluation. In vitro specific binding of glibenclamide to microglia increased after pro-inflammatory stimuli. In vivo glibenclamide was associated with increased migration of doublecortin-positive cells in the striatum toward the ischemic lesion 72 hours after MCAO, and reactive microglia expressed sulfonylurea receptor 1 (SUR1) and Kir6.2 in the medial striatum. One month after MCAO, glibenclamide was also associated with increased number of NeuN-positive and 5-bromo-2-deoxyuridine-positive neurons in the cortex and hippocampus, and enhanced angiogenesis in the hippocampus. Consequently, glibenclamide-treated MCAO rats showed improved performance in the limb-placing test on postoperative days 22 to 29, and in the cylinder and water-maze test on postoperative day 29. Therefore, acute blockade of SUR1 by glibenclamide enhanced long-term brain repair in MCAO rats, which was associated with improved behavioral outcome.

Ultrastructural and morphometrical analyses of the brown adipocyte nucleus in a hibernating dormouse.

The fine morphology, size, and perichromatin granule frequency were analysed in brown adipocyte nuclei from hibernating, arousing, and euthermic dormice, Muscardinus avellanarius. Unusual nuclear structural constituents such as nuclear amorphous bodies, coiled body-like constituents and bundles of nucleoplasmic filaments were described as typical of hibernating nuclei. Morphometrical findings showed significant difference in total nuclear and nucleolar size in the three physiological conditions investigated as well as decreasing frequency of perichromatin granules in nuclei of hibernating to arousing to euthermic animals. A possible involvement of these granules in the intranuclear transport or storage of pre-mRNA is discussed in the context of other experimental evidence.

Systematic review of population pharmacokinetic analyses of imatinib and relationships with treatment outcomes

Several population pharmacokinetic (PPK) analyses of the anticancer drug imatinib have been performed to investigate different patient populations and covariate effects. The present analysis offers a systematic qualitative and quantitative summary and comparison of those. Its primary objective was to provide useful information for evaluating the expectedness of imatinib plasma concentration measurements in the frame of therapeutic drug monitoring. The secondary objective was to review clinically important concentration-effect relationships to provide help in evaluating the potential suitability of plasma concentration values. Nine PPK models describing total imatinib plasma concentration were identified. Parameter estimates were standardized to common covariate values whenever possible. Predicted median exposure (Cmin) was derived by simulations and ranged between models from 555 to 1388 ng/mL (grand median: 870 ng/mL and interquartile "reference" range: 520-1390 ng/mL). Covariates of potential clinical importance (up to 30% change in pharmacokinetic predicted by at least 1 model) included body weight, albumin, α1 acid glycoprotein, and white blood cell count. Various other covariates were included but were statistically not significant or seemed clinically less important or physiologically controversial. Concentration-response relationships had more importance below the average reference range and concentration-toxicity relationships above. Therapeutic drug monitoring-guided dosage adjustment seems justified for imatinib, but a formal predictive therapeutic range remains difficult to propose in the absence of prospective target concentration intervention trials. To evaluate the expectedness of a drug concentration measurement in practice, this review allows comparison of the measurement either to the average reference range or to a specific range accounting for individual patient characteristics. For future research, external PPK model validation or meta-model development should be considered.

Suboptimal filtering and nonlinear time scale transformation for the analysis of multiexponential decays

Multiexponential decays may contain time-constants differing in several orders of magnitudes. In such cases, uniform sampling results in very long records featuring a high degree of oversampling at the final part of the transient. Here, we analyze a nonlinear time scale transformation to reduce the total number of samples with minimum signal distortion, achieving an important reduction of the computational cost of subsequent analyses. We propose a time-varying filter whose length is optimized for minimum mean square error

Improved multiexponential transient spectroscopy by iterative deconvolution

The analysis of multiexponential decays is challenging because of their complex nature. When analyzing these signals, not only the parameters, but also the orders of the models, have to be estimated. We present an improved spectroscopic technique specially suited for this purpose. The proposed algorithm combines an iterative linear filter with an iterative deconvolution method. A thorough analysis of the noise effect is presented. The performance is tested with synthetic and experimental data.

Expression analyses of three members of the AtPHO1 family reveal differential interactions between signaling pathways involved in phosphate deficiency and the responses to auxin, cytokinin, and abscisic acid.

The PHO1 protein is involved in loading inorganic phosphate (Pi) to the root xylem. Ten genes homologous to AtPHO1 are present in the Arabidopsis thaliana (L.) Heyn genome. From this gene family, transcript levels of only AtPHO1, AtPHO1;H1 and AtPHO1;H10 were increased by Pi-deficiency. While the up-regulation of AtPHO1;H1 and AtPHO1;H10 by Pi deficiency followed the same rapid kinetics and was dependent on the PHR1 transcription factor, phosphite only strongly suppressed the expression of AtPHO1;H1 and had a minor effect on AtPHO1;H10. Addition of sucrose was found to increase transcript levels of both AtPHO1 and AtPHO1;H1 in Pi-sufficient or Pi-deficient plants, but to suppress AtPHO1:H10 under the same conditions. Treatments of plants with auxin or cytokinin had contrasting effect depending on the gene and on the Pi status of the plants. Thus, while both hormones down-regulated expression of AtPHO1 independently of the plant Pi status, auxin and cytokinin up-regulated AtPHO1;H1 and AtPHO1;H10 expression in Pi-sufficient plants and down-regulated expression in Pi-deficient plants. Treatments with abscisic acid inhibited AtPHO1 and AtPHO1;H1 expression in both Pi-sufficient and Pi-deficient plants, but increased AtPHO1;H10 expression under the same conditions. The inhibition of expression by abscisic acid of AtPHO1 and AtPHO1;H1, and of the Pi-starvation responsive genes AtPHT1;1 and AtIPS1, was dependant on the ABI1 type 2C protein phosphatase. These results reveal that various levels of cross talk between the signal transduction pathways to Pi, sucrose and phytohormones are involved in the regulation of expression of the three AtPHO1 homologues.