The Human Mesenchymal Stromal Cell-Derived Osteocyte Capacity to Modulate Dendritic Cell Functions Is Strictly Dependent on the Culture System.

In vitro differentiation of mesenchymal stromal cells (MSC) into osteocytes (human differentiated osteogenic cells, hDOC) before implantation has been proposed to optimize bone regeneration. However, a deep characterization of the immunological properties of DOC, including their effect on dendritic cell (DC) function, is not available. DOC can be used either as cellular suspension (detached, Det-DOC) or as adherent cells implanted on scaffolds (adherent, Adh-DOC). By mimicking in vitro these two different routes of administration, we show that both Det-DOC and Adh-DOC can modulate DC functions. Specifically, the weak downregulation of CD80 and CD86 caused by Det-DOC on DC surface results in a weak modulation of DC functions, which indeed retain a high capacity to induce T-cell proliferation and to generate CD4(+)CD25(+)Foxp3(+) T cells. Moreover, Det-DOC enhance the DC capacity to differentiate CD4(+)CD161(+)CD196(+) Th17-cells by upregulating IL-6 secretion. Conversely, Adh-DOC strongly suppress DC functions by a profound downregulation of CD80 and CD86 on DC as well as by the inhibition of TGF-β production. In conclusion, we demonstrate that different types of DOC cell preparation may have a different impact on the modulation of the host immune system. This finding may have relevant implications for the design of cell-based tissue-engineering strategies.

A Gradient based algorithm for blind inversion of Wiener System using multi-variate score functions

A Wiener system is a linear time-invariant filter, followed by an invertible nonlinear distortion. Assuming that the input signal is an independent and identically distributed (iid) sequence, we propose an algorithm for estimating the input signal only by observing the output of the Wiener system. The algorithm is based on minimizing the mutual information of the output samples, by means of a steepest descent gradient approach.

Estimating 750 years of temperature variations and uncertainties in the Pyrenees by tree-ring reconstructions and climate simulations.

Past temperature variations are usually inferred from proxy data or estimated using general circulation models. Comparisons between climate estimations derived from proxy records and from model simulations help to better understand mechanisms driving climate variations, and also offer the possibility to identify deficiencies in both approaches. This paper presents regional temperature reconstructions based on tree-ring maximum density series in the Pyrenees, and compares them with the output of global simulations for this region and with regional climate model simulations conducted for the target region. An ensemble of 24 reconstructions of May-to-September regional mean temperature was derived from 22 maximum density tree-ring site chronologies distributed over the larger Pyrenees area. Four different tree-ring series standardization procedures were applied, combining two detrending methods: 300-yr spline and the regional curve standardization (RCS). Additionally, different methodological variants for the regional chronology were generated by using three different aggregation methods. Calibration verification trials were performed in split periods and using two methods: regression and a simple variance matching. The resulting set of temperature reconstructions was compared with climate simulations performed with global (ECHO-G) and regional (MM5) climate models. The 24 variants of May-to-September temperature reconstructions reveal a generally coherent pattern of inter-annual to multi-centennial temperature variations in the Pyrenees region for the last 750 yr. However, some reconstructions display a marked positive trend for the entire length of the reconstruction, pointing out that the application of the RCS method to a suboptimal set of samples may lead to unreliable results. Climate model simulations agree with the tree-ring based reconstructions at multi-decadal time scales, suggesting solar variability and volcanism as the main factors controlling preindustrial mean temperature variations in the Pyrenees. Nevertheless, the comparison also highlights differences with the reconstructions, mainly in the amplitude of past temperature variations and in the 20th century trends. Neither proxy-based reconstructions nor model simulations are able to perfectly track the temperature variations of the instrumental record, suggesting that both approximations still need further improvements.

A Population-Based Model to Consider the Effect of Seasonal Variation on Serum 25(OH)D and Vitamin D Status.

Background. We elaborated a model that predicts the centiles of the 25(OH)D distribution taking into account seasonal variation. Methods. Data from two Swiss population-based studies were used to generate (CoLaus) and validate (Bus Santé) the model. Serum 25(OH)D was measured by ultra high pressure LC-MS/MS and immunoassay. Linear regression models on square-root transformed 25(OH)D values were used to predict centiles of the 25(OH)D distribution. Distribution functions of the observations from the replication set predicted with the model were inspected to assess replication. Results. Overall, 4,912 and 2,537 Caucasians were included in original and replication sets, respectively. Mean (SD) 25(OH)D, age, BMI, and % of men were 47.5 (22.1) nmol/L, 49.8 (8.5) years, 25.6 (4.1) kg/m(2), and 49.3% in the original study. The best model included gender, BMI, and sin-cos functions of measurement day. Sex- and BMI-specific 25(OH)D centile curves as a function of measurement date were generated. The model estimates any centile of the 25(OH)D distribution for given values of sex, BMI, and date and the quantile corresponding to a 25(OH)D measurement. Conclusions. We generated and validated centile curves of 25(OH)D in the general adult Caucasian population. These curves can help rank vitamin D centile independently of when 25(OH)D is measured.

Phylogeography and population genetics of north European Atlantic salmon (Salmo salar L.)

Although abundant in the number of individuals, the Atlantic salmon may be considered as a threatened species in many areas of its native distribution range. Human activities such as building of power plant dams, offshore overfishing, pollution, clearing of riverbeds for timber floating and badly designed stocking regimes have diminished the distribution of Atlantic salmon. As a result of this, many of the historical populations both in Europe and northern America have gone extinct or are severely depressed. In fact, only 1% of Atlantic salmon existing today are of natural origin, the rest being farmed salmon. All of this has lead to a vast amount of research and many restoration programmes aiming to bring Atlantic salmon back to rivers from where it has vanished. However, many of the restoration programmes conducted thus far have been unsuccessful due to inadequate scientific research or lack of its implementation, highlighting the fact that more research is needed to fully understand the biology of this complex species. The White and Barents Seas in northwest Russia are among the last regions in Europe where Atlantic salmon populations are still stable, thus forming an important source of biodiversity for the entire European region. Salmon stocks from this area are also of immense economic and social importance for the local people in the form of fishing tourism. The main aim of this thesis was to elucidate the post-glacial history and population genetic structure of north European and particularly northwest Russian Atlantic salmon, both of which are aspects of great importance for the management and conservation of the species. Throughout the whole thesis, these populations were studied by utilizing microsatellites as the main molecular tool. One of the most important discoveries of the thesis was the division of Atlantic salmon from the White and Barents Seas into four separate clusters, which has not been observed in previous studies employing nuclear markers although is supported by mtDNA studies. Populations from the western Barents Sea clustered together with the northeast Atlantic populations into a clearly distinguishable group while populations from the White Sea and eastern Barents Sea were separated into three additional groups. This has important conservation implications as this thesis clearly indicates that conservation of populations from all of the observed clusters is warranted in order to conserve as much of the genetic diversity as possible in this area. The thesis also demonstrates how differences in population life histories within a species, migratory behaviour in this case, and in their phylogeographic origin affect the genetic characteristics of populations, namely diversity and divergence levels. The anadromous populations from the Atlantic Ocean, White Sea and Barents Sea possessed higher levels of genetic diversity than the anadromous populations form the Baltic Sea basin. Among the non-anadromous populations the result was the opposite: the Baltic freshwater populations were more variable. This emphasises the importance of taking the life history of a population into consideration when developing conservation strategies: due to the limited possibilities for new genetic diversity to be generated via gene flow, it is expected that freshwater Atlantic salmon populations would be more vulnerable to extinction following a population crash and thus deserve a high conservation status. In the last chapter of this thesis immune relevant marker loci were developed and screened for signatures of natural selection along with loci linked to genes with other functions or no function at all. Also, a novel landscape genomics method, which combines environmental information with molecular data, was employed to investigate whether immune relevant markers displayed significant correlations to various environmental variables more frequently than other loci. Indications of stronger selection pressure among immune-relevant loci compared to non-immune relevant EST-linked loci was found but further studies are needed to evaluate whether it is a common phenomenon in Atlantic salmon.

Ligand binding to heparan sulfate proteoglycans induces their aggregation and distribution along actin cytoskeleton

Cell surface heparan sulfate proteoglycans (HSPGs) participate in molecular events that regulate cell adhesion, migration, and proliferation. The present study demonstrates that soluble heparin-binding proteins or cross-linking antibodies induce the aggregation of cell surface HSPGs and their distribution along underlying actin filaments. Immunofluorescence and confocal microscopy and immunogold and electron microscopy indicate that, in the absence of ligands, HSPGs are irregularly distributed on the fibroblast cell surface, without any apparent codistribution with the actin cytoskeleton. In the presence of ligand (lipoprotein lipase) or antibodies against heparan sulfate, HSPGs aggregate and colocalize with the actin cytoskeleton. Triton X-100 extraction and immunoelectron microscopy have demonstrated that in this condition HSPGs were clustered and associated with the actin filaments. Crosslinking experiments that use biotinylated lipoprotein lipase have revealed three major proteoglycans as binding sites at the fibroblast cell surface. These cross-linked proteoglycans appeared in the Triton X-100 insoluble fraction. Platinum/carbon replicas of the fibroblast surface incubated either with lipoprotein lipase or antiheparan sulfate showed large aggregates of HSPGs regularly distributed along cytoplasmic fibers. Quantification of the spacing between HSPGs by confocal microscopy confirmed that the nonrandom distribution of HSPG aggregates along the actin cytoskeleton was induced by ligand binding. When cells were incubated either with lipoprotein lipase or antibodies against heparan sulfate, the distance between immunofluorescence spots was uniform. In contrast, the spacing between HSPGs on fixed cells not incubated with ligand was more variable. This highly organized spatial relationship between actin and proteoglycans suggests that cortical actin filaments could organize the molecular machinery involved in signal transduction and molecular movements on the cell surface that are triggered by heparin-binding proteins.

Error models in hydrogeology applications

Notre consommation en eau souterraine, en particulier comme eau potable ou pour l'irrigation, a considérablement augmenté au cours des années. De nombreux problèmes font alors leur apparition, allant de la prospection de nouvelles ressources à la remédiation des aquifères pollués. Indépendamment du problème hydrogéologique considéré, le principal défi reste la caractérisation des propriétés du sous-sol. Une approche stochastique est alors nécessaire afin de représenter cette incertitude en considérant de multiples scénarios géologiques et en générant un grand nombre de réalisations géostatistiques. Nous rencontrons alors la principale limitation de ces approches qui est le coût de calcul dû à la simulation des processus d'écoulements complexes pour chacune de ces réalisations. Dans la première partie de la thèse, ce problème est investigué dans le contexte de propagation de l'incertitude, oú un ensemble de réalisations est identifié comme représentant les propriétés du sous-sol. Afin de propager cette incertitude à la quantité d'intérêt tout en limitant le coût de calcul, les méthodes actuelles font appel à des modèles d'écoulement approximés. Cela permet l'identification d'un sous-ensemble de réalisations représentant la variabilité de l'ensemble initial. Le modèle complexe d'écoulement est alors évalué uniquement pour ce sousensemble, et, sur la base de ces réponses complexes, l'inférence est faite. Notre objectif est d'améliorer la performance de cette approche en utilisant toute l'information à disposition. Pour cela, le sous-ensemble de réponses approximées et exactes est utilisé afin de construire un modèle d'erreur, qui sert ensuite à corriger le reste des réponses approximées et prédire la réponse du modèle complexe. Cette méthode permet de maximiser l'utilisation de l'information à disposition sans augmentation perceptible du temps de calcul. La propagation de l'incertitude est alors plus précise et plus robuste. La stratégie explorée dans le premier chapitre consiste à apprendre d'un sous-ensemble de réalisations la relation entre les modèles d'écoulement approximé et complexe. Dans la seconde partie de la thèse, cette méthodologie est formalisée mathématiquement en introduisant un modèle de régression entre les réponses fonctionnelles. Comme ce problème est mal posé, il est nécessaire d'en réduire la dimensionnalité. Dans cette optique, l'innovation du travail présenté provient de l'utilisation de l'analyse en composantes principales fonctionnelles (ACPF), qui non seulement effectue la réduction de dimensionnalités tout en maximisant l'information retenue, mais permet aussi de diagnostiquer la qualité du modèle d'erreur dans cet espace fonctionnel. La méthodologie proposée est appliquée à un problème de pollution par une phase liquide nonaqueuse et les résultats obtenus montrent que le modèle d'erreur permet une forte réduction du temps de calcul tout en estimant correctement l'incertitude. De plus, pour chaque réponse approximée, une prédiction de la réponse complexe est fournie par le modèle d'erreur. Le concept de modèle d'erreur fonctionnel est donc pertinent pour la propagation de l'incertitude, mais aussi pour les problèmes d'inférence bayésienne. Les méthodes de Monte Carlo par chaîne de Markov (MCMC) sont les algorithmes les plus communément utilisés afin de générer des réalisations géostatistiques en accord avec les observations. Cependant, ces méthodes souffrent d'un taux d'acceptation très bas pour les problèmes de grande dimensionnalité, résultant en un grand nombre de simulations d'écoulement gaspillées. Une approche en deux temps, le "MCMC en deux étapes", a été introduite afin d'éviter les simulations du modèle complexe inutiles par une évaluation préliminaire de la réalisation. Dans la troisième partie de la thèse, le modèle d'écoulement approximé couplé à un modèle d'erreur sert d'évaluation préliminaire pour le "MCMC en deux étapes". Nous démontrons une augmentation du taux d'acceptation par un facteur de 1.5 à 3 en comparaison avec une implémentation classique de MCMC. Une question reste sans réponse : comment choisir la taille de l'ensemble d'entrainement et comment identifier les réalisations permettant d'optimiser la construction du modèle d'erreur. Cela requiert une stratégie itérative afin que, à chaque nouvelle simulation d'écoulement, le modèle d'erreur soit amélioré en incorporant les nouvelles informations. Ceci est développé dans la quatrième partie de la thèse, oú cette méthodologie est appliquée à un problème d'intrusion saline dans un aquifère côtier. -- Our consumption of groundwater, in particular as drinking water and for irrigation, has considerably increased over the years and groundwater is becoming an increasingly scarce and endangered resource. Nofadays, we are facing many problems ranging from water prospection to sustainable management and remediation of polluted aquifers. Independently of the hydrogeological problem, the main challenge remains dealing with the incomplete knofledge of the underground properties. Stochastic approaches have been developed to represent this uncertainty by considering multiple geological scenarios and generating a large number of realizations. The main limitation of this approach is the computational cost associated with performing complex of simulations in each realization. In the first part of the thesis, we explore this issue in the context of uncertainty propagation, where an ensemble of geostatistical realizations is identified as representative of the subsurface uncertainty. To propagate this lack of knofledge to the quantity of interest (e.g., the concentration of pollutant in extracted water), it is necessary to evaluate the of response of each realization. Due to computational constraints, state-of-the-art methods make use of approximate of simulation, to identify a subset of realizations that represents the variability of the ensemble. The complex and computationally heavy of model is then run for this subset based on which inference is made. Our objective is to increase the performance of this approach by using all of the available information and not solely the subset of exact responses. Two error models are proposed to correct the approximate responses follofing a machine learning approach. For the subset identified by a classical approach (here the distance kernel method) both the approximate and the exact responses are knofn. This information is used to construct an error model and correct the ensemble of approximate responses to predict the "expected" responses of the exact model. The proposed methodology makes use of all the available information without perceptible additional computational costs and leads to an increase in accuracy and robustness of the uncertainty propagation. The strategy explored in the first chapter consists in learning from a subset of realizations the relationship between proxy and exact curves. In the second part of this thesis, the strategy is formalized in a rigorous mathematical framework by defining a regression model between functions. As this problem is ill-posed, it is necessary to reduce its dimensionality. The novelty of the work comes from the use of functional principal component analysis (FPCA), which not only performs the dimensionality reduction while maximizing the retained information, but also allofs a diagnostic of the quality of the error model in the functional space. The proposed methodology is applied to a pollution problem by a non-aqueous phase-liquid. The error model allofs a strong reduction of the computational cost while providing a good estimate of the uncertainty. The individual correction of the proxy response by the error model leads to an excellent prediction of the exact response, opening the door to many applications. The concept of functional error model is useful not only in the context of uncertainty propagation, but also, and maybe even more so, to perform Bayesian inference. Monte Carlo Markov Chain (MCMC) algorithms are the most common choice to ensure that the generated realizations are sampled in accordance with the observations. Hofever, this approach suffers from lof acceptance rate in high dimensional problems, resulting in a large number of wasted of simulations. This led to the introduction of two-stage MCMC, where the computational cost is decreased by avoiding unnecessary simulation of the exact of thanks to a preliminary evaluation of the proposal. In the third part of the thesis, a proxy is coupled to an error model to provide an approximate response for the two-stage MCMC set-up. We demonstrate an increase in acceptance rate by a factor three with respect to one-stage MCMC results. An open question remains: hof do we choose the size of the learning set and identify the realizations to optimize the construction of the error model. This requires devising an iterative strategy to construct the error model, such that, as new of simulations are performed, the error model is iteratively improved by incorporating the new information. This is discussed in the fourth part of the thesis, in which we apply this methodology to a problem of saline intrusion in a coastal aquifer.

The specificity of the familial aggregation of early-onset bipolar disorder: A controlled 10-year follow-up study of offspring of parents with mood disorders.

BACKGROUND: Two major sources of heterogeneity of mood disorders that have been demonstrated in clinical, family and genetic studies are the mood disorder subtype (i.e. bipolar (BPD) and major depressive disorder (MDD)) and age of onset of mood episodes. Using a prospective high-risk study design, our aims were to test the specificity of the parent-child transmission of BPD and MDD and to establish the risk of psychopathology in offspring in function of the age of onset of the parental disorder. METHODS: Clinical information was collected on 208 probands (n=81 with BPD, n=64 with MDD, n=63 medical controls) as well as their 202 spouses and 372 children aged 6-17 years at study entry. Parents and children were directly interviewed every 3 years (mean duration of follow-up=10.6 years). Parental age of onset was dichotomized at age 21. RESULTS: Offspring of parents with early onset BPD entailed a higher risk of BPD HR=7.9(1.8-34.6) and substance use disorders HR=5.0(1.1-21.9) than those with later onset and controls. Depressive disorders were not significantly increased in offspring regardless of parental mood disorder subtype or age of onset. LIMITATIONS: Limited sample size, age of onset in probands was obtained retrospectively, age of onset in co-parents was not adequately documented, and a quarter of the children had no direct interview. CONCLUSIONS: Our results provide support for the independence of familial aggregation of BPD from MDD and the heterogeneity of BPD based on patterns of onset. Future studies should further investigate correlates of early versus later onset BPD.

Post-transcriptional regulation of circadian gene expression by miRNAs

La grande majorité des organismes vivants ont développé un système d'horloges biologiques internes, appelées aussi horloges circadiennes, contrôlant l'expression de gênes impliqués dans de nombreux processus moléculaires et comportementaux. Au cours de la dernière décennie, des analyses « microarray » et séquençages à haut débit sur divers tissus de mammifères, indiquent que jusqu'à 20% du transcriptome serait sous contrôle circadien. Il était jusqu'à présent admis que la majorité des ARNm ayant une accumulation rythmique était générée par une transcription qui était elle-même rythmique. Toutefois, de récentes études ont suggéré qu'une proportion considérable des ARNm cycliques serait en fait générée par des mécanismes post-transcriptionnelles, incluant une régulation par micro-ARN (miARN). Lorsque j'ai débuté mon travail de thèse, l'influence des miARN sur l'expression des gènes circadiens, au niveau pangénomique, était encore méconnue. Par l'utilisation d'un modèle murin, dont la biogenèse des miARN a été spécifiquement désactivée au niveau des cellules hépatiques (knockout conditionnel pour Dicer), je me suis donc intéressée au rôle que jouaient ces molécules régulatrices sur la rythmicité de l'expression génique dans le foie. Des séquençages sur l'ensemble du transcriptome révèlent que l'horloge interne du foie est étonnement résistante à la perte totale des miARN. Nous avons cependant trouvé que les miARN agissent de façon importante sur la régulation de l'expression des gènes contrôlés par l'horloge moléculaire. La corégulation par les miARN, affectant jusqu'à 30% des gènes transcrits de façon rythmiques, conduit ainsi à une modulation de phase et d'amplitude du rythme de l'abondance des ARNm. En revanche, seuls peu de transcrits dépendent uniquement des miARN pour la rythmicité de leur accumulation. Enfin, mon travail met en évidence plusieurs miARN spécifiques, qui semblent préférentiellement moduler l'expression des gènes cycliques et permet l'identification de voies hépatiques particulièrement sujettes à une double régulation par les miARN et l'horloge biologique interne. La première masse d'analyses a essentiellement porté sur le rôle que jouent les miARN au niveau de l'expression des gènes contrôlés par l'horloge interne. Dans deux études de suivi, je me suis penchée sur deux aspects supplémentaires et complémentaires de la manière dont les miARN et l'oscillation de l'expression des gènes interagissent. Dans les hépatocytes murins, spécifiquement privés de Dicer, je me suis demandée si un phénotype horloge avait pu être masqué, dû à un entraînement stable de l'horloge du foie par l'horloge maîtresse du cerveau. J'ai donc commencé une série d'expériences ambitieuses (impliquant la mesure de la rythmicité du foie in vivo, chez l'animal vivant) afin de déséquilibrer l'entrainement de l'horloge hépatique via l'utilisation d'un protocole nutritionnel spécifique. Les premiers résultats suggèrent que dans des conditions où l'animal subit une restriction alimentaire pendant la journée, les miARN sont importants dans la cinétique d'adaptation des organes périphériques à un nouvel horaire de sustentation. Dans une deuxième ligne de recherche, j'ai plus profondément étudié quels seraient les miARN responsables des rythmes post-transcriptionnels des ARNm, en utilisant le séquençage de « small » ARN sur 24h. L'analyse est en cours et se poursuivra après l'obtention de mon diplôme. De façon générale, mon travail révèle d'importants et nouveaux rôles des miARN dans la modulation de l'expression circadienne des gènes hépatiques. De plus, le set de données générées dans l'étude déjà publiée, peut dorénavant servir de ressource valable pour de prochaines investigations sur le rôle physiologique que les miARN jouent au niveau du foie. -- Most living organisms have developed internal timing systems, called circadian clocks, to drive the rhythmic expression of genes involved in many molecular and behavioral processes. Over the last decade, microarray analyses and high- throughput sequencing from various mammalian tissues have indicated that up to 20% of the transcriptome are under circadian control. It was generally assumed that the majority of rhythmic mRNA accumulation is generated by rhythmic transcription. However, recent studies have suggested that a considerable proportion of mRNA cycling may actually be generated by post-transcriptional mechanisms, including by microRNAs. When I started my thesis work, it was still unknown how miRNAs influence circadian gene expression in a genome-wide fashion. Using a mouse model in which miRNA biogenesis can be inactivated in hepatocytes (conditional Dicer knockout mouse), I have thus addressed the role that these regulatory molecules play in rhythmic gene expression in the liver. Whole transcriptome sequencing revealed that the hepatic core clock was surprisingly resilient to total miRNA loss. However, we found that miRNAs acted as important regulators of clock-controlled gene expression. Co- regulation by miRNAs, which affected up to 30% of rhythmically transcribed genes, thus led to the modulation of phases and amplitudes of mRNA abundance rhythms. By contrast, only very few transcripts were strictly dependent on miRNAs for their rhythmic accumulation. Finally, my work highlights several specific miRNAs that appear to preferentially modulate cyclic gene expression, and identifies pathways in the liver that are particularly prone to dual regulation through miRNAs and the clock. The first bulk of analyses mainly dealt with the role that miRNAs play at the level of rhythmic clock output gene expression. In two follow-up studies I further delved into two additional, complementary aspects of how miRNAs and gene expression oscillations interact. First, I addressed whether a core clock phenotype in the hepatocyte-specific Dicer knockout could have been masked due to the stable entrainment of the liver clock by the animals' master clock in the brain. I thus started a series of ambitious experiments (involving the in vivo recording of liver rhythms in live animals) to bring the stable entrainment of the liver clock out of equilibrium using specific feeding protocols. My first results suggest that under conditions when animals are challenged by food restriction to daytime, miRNAs are important for the kinetics of adapting to unusual mealtime in peripheral tissue. In a second line of research, I have more carefully investigated which miRNAs are responsible for post- transcriptional mRNA rhythms using small RNA sequencing around-the-clock. The analyses are ongoing and will be continued after my graduation. Overall, my work uncovered important and novel roles of miRNA activity in shaping hepatic circadian gene expression; moreover, the datasets collect in the published studies can serve as a valuable resource for further investigations into the physiological roles that miRNAs play in liver. -- L'alternance du jour et de la nuit dirige depuis longtemps la vie quotidienne des êtres humains et de la plupart des organismes sur terre. Ce cycle de 24 heures façonne beaucoup de changements comportementaux et physiologiques tels que la vigilance, la température corporelle et le sommeil. Les rythmes journaliers, appelés rythmes circadiens, sont dirigés par des horloges biologiques tournant dans presque chaque cellule du corps. Une structure dans le cerveau agit en tant qu'horloge maitresse pour synchroniser les horloges internes entre elles et en fonction des signaux de jour/nuit extérieurs. Dans les cellules "les gènes de l'horloge" sont activés et désactivés une fois par jour ce qui déclenche des cycles dans lesquels des protéines sont produites de manière circadienne. Ces rythmes protéiques sont spécialisés pour chaque tissu ou organe et peuvent les aider à réaliser leurs tâches quotidiennes. Les rythmes circadiens peuvent être générés d'autres manières n'impliquant pas directement les composants des gènes de l'horloge. Les ARN messagers (ARNm) sont des molécules intermédiaires dans la production de protéines à partir d'ADN. Dans le foie des souris jusqu'à 20% des molécules d'ARNm sont produites suivant des rythmes circadiens. Le foie réalise des tâches essentielles dans le contrôle du métabolisme incluant celui des hydrates de carbone, des graisses et du cholestérol. Un timing précis est important afin de traiter les substances nutritives correctement lors des repas il en résulte une variation des quantités de certains ARNm et protéines coïncidant avec les repas. Les microARNs constituent une autre classe de molécules ARN de très petite taille qui régulent l'efficacité de traduction des ARNm en protéines et la stabilité des ARNm. Lors de mon travail de thèse, j'ai exploré de manière approfondie l'influence de ces petits régulateurs sur les rythmes circadiens du foie de souris. Ces expériences qui impliquaient le "Knock-out" d'un gène essentiel à la production de microARNs montrent qu'au lieu de générer les rythmes des ARNm, les microARNs les ajustent pour répondre aux besoins spécifiques du foie comme assurer leur pic au bon moment de la journée. Le ciblage de microARNs spécifiques peut révéler de nouvelles stratégies pour rectifier ces rythmes lorsque par exemple les fonctions métaboliques ne fonctionnent plus normalement. -- The rising and setting of the sun have long driven the daily schedules of humans and most organisms on the earth. This 24-hr cycle shapes many behavioural and physiological changes, such as alertness, body temperature, and sleep. These daily rhythms, which are called circadian rhythms, are dictated by biological clocks that are ticking in almost every single cell of the body. A region in the brain acts as a master clock to synchronize the internal clocks with each other and with the outside light/dark cycles. In cells, "core clock genes" are turned on and off once per day, which triggers cycles that cause some proteins to be produced in a circadian manner. The protein rhythms are specialized to a particular tissue or organ, and may help them to carry out their designated daily tasks. However, circadian rhythms might also be produced by other ways that do not involve these core clock components. Messenger RNAs (mRNAs) are intermediate molecules in the production of proteins from DNA. In the mouse liver, up to 20% of mRNA molecules are produced in circadian cycles. The liver performs essential tasks that control metabolism-including that of carbohydrates, fats, and cholesterol. Precisely timing when certain mRNAs and proteins reach peaks and troughs in their activities to coincide with mealtimes is important for nutrients to be properly processed. Other RNA molecules called microRNAs, i.e. RNAs of very small size, regulate at which rate mRNA molecules are translated into proteins. In my thesis work, I have explored at the influence of these small regulators on circadian rhythms in the mouse liver in greater detail. These experiments, which involved "knocking out" a gene that is essential for the production of microRNAs, show that rather than generating the mRNA rhythms, the microRNAs appear to adjust them to meet the specific needs of the liver, such as ensuring that they peak at the right time-of-day. Targeting specific microRNA molecules may reveal new strategies to tweak these rhythms, which could help to improve conditions when metabolic functions go wrong.

Dynamically generated resonances from the vector octet-baryon octet interaction

We study the interaction of vector mesons with the octet of stable baryons in the framework of the local hidden gauge formalism using a coupled channels unitary approach. We examine the scattering amplitudes and their poles, which can be associated to known J P = 1/2- , 3/2- baryon resonances, in some cases, or give predictions in other ones. The formalism employed produces doublets of degenerate J P = 1/2- , 3/2- states, a pattern which is observed experimentally in several cases. The findings of this work should also be useful to guide present experimental programs searching for new resonances, in particular in the strange sector where the current information is very poor.

Sidelobe elimination for generalized synthetic discriminant functions by a two-filter correlation and subsequent postprocessing of the intensity distributions

One of the most important problems in optical pattern recognition by correlation is the appearance of sidelobes in the correlation plane, which causes false alarms. We present a method that eliminate sidelobes of up to a given height if certain conditions are satisfied. The method can be applied to any generalized synthetic discriminant function filter and is capable of rejecting lateral peaks that are even higher than the central correlation. Satisfactory results were obtained in both computer simulations and optical implementation.

Comprehensive Genomic Characterization of Long Non-coding RNAs across Human Cancers.

The discovery of long non-coding RNA (lncRNA) has dramatically altered our understanding of cancer. Here, we describe a comprehensive analysis of lncRNA alterations at transcriptional, genomic, and epigenetic levels in 5,037 human tumor specimens across 13 cancer types from The Cancer Genome Atlas. Our results suggest that the expression and dysregulation of lncRNAs are highly cancer type specific compared with protein-coding genes. Using the integrative data generated by this analysis, we present a clinically guided small interfering RNA screening strategy and a co-expression analysis approach to identify cancer driver lncRNAs and predict their functions. This provides a resource for investigating lncRNAs in cancer and lays the groundwork for the development of new diagnostics and treatments.

Role of Connexins and Pannexins in the Pancreas.

The pancreas produces enzymes with a digestive function and hormones with a metabolic function, which are produced by distinct cell types of acini and islets, respectively. Within these units, secretory cells coordinate their functioning by exchanging information via signals that flow in the intercellular spaces and are generated either at distance (several neural and hormonal inputs) or nearby the pancreatic cells themselves (inputs mediated by membrane ionic-specific channels and by ionic- and metabolite-permeant pannexin channels and connexin "hemichannels"). Pancreatic secretory cells further interact via the extracellular matrix of the pancreas (inputs mediated by integrins) and directly with neighboring cells, by mechanisms that do not require extracellular mediators (inputs mediated by gap and tight junction channels). Here, we review the expression and function of the connexins and pannexins that are expressed by the main secretory cells of the exocrine and endocrine pancreatic cells. Available data show that the patterns of expression of these proteins differ in acini and islets, supporting distinct functions in the physiological secretion of pancreatic enzymes and hormones. Circumstantial evidence further suggests that alterations in the signaling provided by these proteins are involved in pancreatic diseases.