Glycogen content in the cerebral cortex increases with sleep loss in C57BL/6J mice.

We hypothesized that a function of sleep is to replenish brain glycogen stores that become depleted while awake. We have previously tested this hypothesis in three inbred strains of mice by measuring brain glycogen after a 6h sleep deprivation (SD). Unexpectedly, glycogen content in the cerebral cortex did not decrease with SD in two of the strains and was even found to increase in mice of the C57BL/6J (B6) strain. Manipulations that initially induce glycogenolysis can also induce subsequent glycogen synthesis thereby elevating glycogen content beyond baseline. It is thus possible that in B6 mice, cortical glycogen content decreased early during SD and became elevated later in SD. In the present study, we therefore measured changes in brain glycogen over the course of a 6 h SD and during recovery sleep in B6 mice. We found no evidence of a decrease at any time during the SD, instead, cortical glycogen content monotonically increased with time-spent-awake and, when sleep was allowed, started to revert to control levels. Such a time-course is opposite to the one predicted by our initial hypothesis. These results demonstrate that glycogen synthesis can be achieved during prolonged wakefulness to the extent that it outweighs glycogenolysis. Maintaining this energy store seems thus not to be functionally related to sleep in this strain.

Identification of psychological dysfunctions and eating disorders in obese women seeking weight loss: cross-sectional study.

Objective. The aim of this study is to analyse associations between eating behaviour and psychological dysfunctions in treatment-seeking obese patients and identify parameters for the development of diagnostic tools with regard to eating and psychological disorders. Design and Methods. Cross-sectional data were analysed from 138 obese women. Bulimic Investigatory Test of Edinburgh and Eating Disorder Inventory-2 assessed eating behaviours. Beck Depression Inventory II, Spielberger State-Trait Anxiety Inventory, form Y, Rathus Assertiveness Schedule, and Marks and Mathews Fear Questionnaire assessed psychological profile. Results. 61% of patients showed moderate or major depressive symptoms and 77% showed symptoms of anxiety. Half of the participants presented with a low degree of assertiveness. No correlation was found between psychological profile and age or anthropometric measurements. The prevalence and severity of depression, anxiety, and assertiveness increased with the degree of eating disorders. The feeling of ineffectiveness explained a large degree of score variance. It explained 30 to 50% of the variability of assertiveness, phobias, anxiety, and depression. Conclusion. Psychological dysfunctions had a high prevalence and their severity is correlated with degree of eating disorders. The feeling of ineffectiveness constitutes the major predictor of the psychological profile and could open new ways to develop screening tools.

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.

Gene loss and evolutionary rates following whole-genome duplication in teleost fishes.

Teleost fishes provide the first unambiguous support for ancient whole-genome duplication in an animal lineage. Studies in yeast or plants have shown that the effects of such duplications can be mediated by a complex pattern of gene retention and changes in evolutionary pressure. To explore such patterns in fishes, we have determined by phylogenetic analysis the evolutionary origin of 675 Tetraodon duplicated genes assigned to chromosomes, using additional data from other species of actinopterygian fishes. The subset of genes, which was retained in double after the genome duplication, is enriched in development, signaling, behavior, and regulation functional categories. The evolutionary rate of duplicate fish genes appears to be determined by 3 forces: 1) fish proteins evolve faster than mammalian orthologs; 2) the genes kept in double after genome duplication represent the subset under strongest purifying selection; and 3) following duplication, there is an asymmetric acceleration of evolutionary rate in one of the paralogs. These results show that similar mechanisms are at work in fishes as in yeast or plants and provide a framework for future investigation of the consequences of duplication in fishes and other animals.

Large calcite and bulk-rock volume loss in metacarbonate xenoliths from the Qu,rigut massif (French Pyrenees)

Chemical mass transfer was quantified in a metacarbonate xenolith enclosed within the granodiorite of the Qu,rigut massif (Pyrenees, France). Mass balance calculations suggest a strong decrease of CaO, SrO and CO(2) contents (up to -90%), correlated with a decrease of modal calcite content as the contact is approached. Most other chemical elements behave immobile during metasomatism. They are therefore passively enriched. Only a small increase of SiO(2), Al(2)O(3) and Fe(2)O(3) contents occurs in the immediate vicinity of the contact. Hence, in this study, skarn formation is characterized by the lack of large chemical element influx from the granitoid protolith. A large decrease of the initial carbonate volume (up to -86%) resulted from a combination of decarbonation reactions and loss of CaO and CO(2). The resulting volume change has potentially important consequences for the interpretation of stable isotope profiles: the isotope alteration could have occured over greater distances than those observed today.

Loss of Memo, a novel FGFR regulator, results in reduced lifespan.

Memo is a widely expressed 33-kDa protein required for heregulin (HRG)-, epidermal growth factor (EGF)-, and fibroblast growth factor (FGF)-induced cell motility. Studies in mouse embryonic fibroblasts, wild-type or knockout for Memo, were performed to further investigate the role of Memo downstream of FGFR. We demonstrated that Memo associates with the FGFR signalosome and is necessary for optimal activation of signaling. To uncover Memo's physiological role, Memo conditional-knockout mice were generated. These animals showed a reduced life span, increased insulin sensitivity, small stature, graying hair, alopecia, kyphosis, loss of subcutaneous fat, and loss of spermatozoa in the epididymis. Memo-knockout mice also have elevated serum levels of active vitamin D, 1,25-dihydroxyvitamin D3 (1,25(OH)2D), and calcium compared to control littermates expressing Memo. In summary, the results from in vivo and in vitro models support the hypothesis that Memo is a novel regulator of FGFR signaling with a role in controlling 1,25(OH)2D production and normal calcium homeostasis.

Transformation kernel density estimation of actuarial loss functions

[cat] Es presenta un estimador nucli transformat que és adequat per a distribucions de cua pesada. Utilitzant una transformació basada en la distribució de probabilitat Beta l’elecció del paràmetre de finestra és molt directa. Es presenta una aplicació a dades d’assegurances i es mostra com calcular el Valor en Risc.

Low-loss rib waveguides containing Si nanocrystals embedded in SiO2

We report on the study and modeling of the structural and optical properties of rib-loaded waveguides working in the 600-900-nm spectral range. A Si nanocrystal (Si-nc) rich SiO2 layer with nominal Si excess ranging from 10% to 20% was produced by quadrupole ion implantation of Si into thermal SiO2 formed on a silicon substrate. Si-ncs were precipitated by annealing at 1100°C, forming a 0.4-um-thick core layer in the waveguide. The Si content, the Si-nc density and size, the Si-nc emission, and the active layer effective refractive index were determined by dedicated experiments using x-ray photoelectron spectroscopy, Raman spectroscopy, energy-filtered transmission electron microscopy, photoluminescence and m-lines spectroscopy. Rib-loaded waveguides were fabricated by photolithographic and reactive ion etching processes, with patterned rib widths ranging from 1¿to¿8¿¿m. Light propagation in the waveguide was observed and losses of 11dB/cm at 633 and 780 nm were measured, modeled and interpreted.

Sweet taste loss in myasthenia gravis: more than a coincidence?

Sweet dysgeusia, a rare taste disorder, may be encountered in severe anti-acetylcholine receptor antibody (AChRAb)-myasthenia gravis (MG). A 42 year-old man reported progressive loss of sweet taste evolving for almost 10 weeks, revealing an AChRAb-positive MG with thymoma. Improvement of sweet perception paralleled reduction of the MG composite score during the 15 months follow up period, with immunosuppressive and surgical treatments. We suggest that sweet dysgeusia is a non-motor manifestation of MG that may result from a thymoma-dependent autoimmune mechanism targeting gustducin-positive G-protein-coupled taste receptor cells, in line with recent data from MRL/MpJ-Fas lpr/ (MRL/lpr) transgenic mice with autoimmune disease.

Loss-of-function mutations of an inhibitory upstream ORF in the human hairless transcript cause Marie Unna hereditary hypotrichosis.

Marie Unna hereditary hypotrichosis (MUHH) is an autosomal dominant form of genetic hair loss. In a large Chinese family carrying MUHH, we identified a pathogenic initiation codon mutation in U2HR, an inhibitory upstream ORF in the 5' UTR of the gene encoding the human hairless homolog (HR). U2HR is predicted to encode a 34-amino acid peptide that is highly conserved among mammals. In 18 more families from different ancestral groups, we identified a range of defects in U2HR, including loss of initiation, delayed termination codon and nonsense and missense mutations. Functional analysis showed that these classes of mutations all resulted in increased translation of the main HR physiological ORF. Our results establish the link between MUHH and U2HR, show that fine-tuning of HR protein levels is important in control of hair growth, and identify a potential mechanism for preventing hair loss or promoting hair removal.

Transformation kernel density estimation of actuarial loss functions

[cat] Es presenta un estimador nucli transformat que és adequat per a distribucions de cua pesada. Utilitzant una transformació basada en la distribució de probabilitat Beta l’elecció del paràmetre de finestra és molt directa. Es presenta una aplicació a dades d’assegurances i es mostra com calcular el Valor en Risc.