Schizophrenia: glutathione deficit as a new vulnerability factor for disconnectivity syndrome

(from the journal abstract) Schizophrenia, a major psychiatric disease, affects individuals in the centre of their personality. Its aetiology is not clearly established. In this review, we will present evidence that patients suffering of schizophrenia present a brain deficit in glutathione, a major endogenous redox regulator and antioxidant. We will also show that, in experimental models, a decrease in glutathione, particularly during development, induces morphological, electrophysiological and behavioural anomalies consistent with those observed in the disease. In the cerebrospinal fluid of drug-naive schizophrenics, glutathione level was decreased by 27% and its direct metabolite of glutathione by 16%. Glutathione level in prefrontal cortex of patients, measured by magnetic resonance spectroscopy, was 52% lower than in controls. Patients' fibroblasts reveal a decrease in mRNA levels of the two glutathione synthesising enzymes, glutamatecysteine ligase modulatory subunit (GCLM) and glutathione synthetase. GCLM expression level in fibroblasts correlates negatively with symptoms severity. Glutathione is an important endogenous redox regulator and neuroactive substance. It is protecting cells from damage by reactive oxygen species generated, among others, by dopamine metabolism. A glutathione deficit-induced oxidative stress would lead to lipid peroxidation and micro-lesions at the level of dendritic spines, a synaptic damage responsible for abnormal nervous connections or structural disconnectivity. On the other hand, a glutathione deficit could also lead to a functional disconnectivity by depressing NMDA neurotransmission, in analogy to phencyclidine effects. Present experimental data are consistent with the proposed hypothesis: decreasing pharmacologically glutathione level in experimental models, with or without blocking dopamine (DA) uptake (GBR12909), induces morphological, electrophysiological and behavioural changes similar to those observed in patients. In summary, a deficit of glutathione and/or glutathione-related enzymes during early development would lead to both a functional and a structural disconnectivity, which could be at the basis of some perceptive, cognitive and behavioural troubles of the disease. It could constitute a major vulnerability factor for schizophrenia. Attempts to restore physiological glutathione functions could open new therapeutic avenues. This translational research, made possible by a close interaction between clinicians and neuroscientists, should also pave the way to the identification of biological markers for schizophrenia. In turn, they should allow early diagnostic and hopefully preventive intervention to this devastating disease. (PsycINFO Database Record (c) 2005 APA, all rights reserved)

Basal cell carcinoma - molecular biology and potential new therapies.

Basal cell carcinoma (BCC) of the skin, the most common malignancy in individuals of mixed European descent, is increasing in incidence due to an aging population and sun exposure habits. The realization that aberrant activation of Hedgehog signaling is a pathognomonic feature of BCC development has opened the way for exciting progress toward understanding BCC biology and translation of this knowledge to the clinic. Genetic mouse models closely mimicking human BCCs have provided answers about the tumor cell of origin, and inhibition of Hedgehog signaling is emerging as a potentially useful targeted therapy for patients with advanced or multiple BCCs that have hitherto lacked effective treatment.

European Integration Without EU Membership : Models, Experiences, Perspectives

At the beginning of the 1990s, the concept of "European integration" could still be said to be fairly unambiguous. Nowadays, it has become plural and complex almost to the point of unintelligibility. This is due, of course, to the internal differentiation of EU membership, with several Member States pulling out of key integrative projects such as establishing an area without frontiers, the "Schengen" area, and a common currency. But this is also due to the differentiated extension of key integrative projects to European non-EU countries - Schengen is again a case in point. Such processes of "integration without membership", the focus of the present publication, are acquiring an ever-growing topicality both in the political arena and in academia. International relations between the EU and its neighbouring countries are crucial for both, and their development through new agreements features prominently on the continent's political agenda. Over and above this aspect, the dissemination of EU values and standards beyond the Union's borders raises a whole host of theoretical and methodological questions, unsettling in some cases traditional conceptions of the autonomy and separation of national legal orders. This publication brings together the papers presented at the Integration without EU Membership workshop held in May 2008 at the EUI (Max Weber Programme and Department of Law). It aims to compare different models and experiences of integration between the EU, on the one hand, and those European countries that do not currently have an accession perspective on the other hand. In delimiting the geographical scope of the inquiry, so as to scale it down to manageable proportions, the guiding principles have been to include both the "Eastern" and "Western" neighbours of the EU, and to examine both structured frameworks of cooperation, such as the European Neighbourhood Policy and the European Economic Area, and bilateral relations developing on a more ad hoc basis. These principles are reflected in the arrangement of the papers, which consider in turn the positions of Ukraine, Russia, Norway, and Switzerland in European integration - current standing, perspectives for evolution, consequences in terms of the EU-ization of their respective legal orders1. These subjects are examined from several perspectives. We had the privilege of receiving contributions from leading practitioners and scholars from the countries concerned, from EU highranking officials, from prominent specialists in EU external relations law, and from young and talented researchers. We wish to thank them all here for their invaluable insights. We are moreover deeply indebted to Marise Cremona (EUI, Law Department, EUI) for her inspiring advice and encouragement, as well as to Ramon Marimon, Karin Tilmans, Lotte Holm, Alyson Price and Susan Garvin (Max Weber Programme, EUI) for their unflinching support throughout this project. A word is perhaps needed on the propriety and usefulness of the research concept embodied in this publication. Does it make sense to compare the integration models and experiences of countries as different as Norway, Russia, Switzerland, and Ukraine? Needless to say, this list of four evokes a staggering diversity of political, social, cultural, and economic conditions, and at least as great a diversity of approaches to European integration. Still, we would argue that such diversity only makes comparisons more meaningful. Indeed, while the particularities and idiosyncratic elements of each "model" of integration are fully displayed in the present volume, common themes and preoccupations run through the pages of every contribution: the difficulty in conceptualizing the finalité and essence of integration, which is evident in the EU today but which is greatly amplified for non-EU countries; the asymmetries and tradeoffs between integration and autonomy that are inherent in any attempt to participate in European integration from outside; the alteration of deeply seated legal concepts, and concepts about the law, that are already observable in the most integrated of the non-EU countries concerned. These issues are not transient or coincidental: they are inextricably bound up with the integration of non-EU countries in the EU project. By publishing this collection, we make no claim to have dealt with them in an exhaustive, still less in a definitive manner. Our ambition is more modest: to highlight the relevance of these themes, to place them more firmly on the scientific agenda, and to provide a stimulating basis for future research and reflection.

The Caribbean-North America-Cocos Triple Junction and the dynamics of the Polochic-Motagua fault systems: Pull-up and zipper models

The Polochic-Motagua fault systems (PMFS) are part of the sinistral transform boundary between the North American and Caribbean plates. To the west, these systems interact with the subduction zone of the Cocos plate, forming a subduction-subduction-transform triple junction. The North American plate moves westward relative to the Caribbean plate. This movement does not affect the geometry of the subducted Cocos plate, which implies that deformation is accommodated entirely in the two overriding plates. Structural data, fault kinematic analysis, and geomorphic observations provide new elements that help to understand the late Cenozoic evolution of this triple junction. In the Miocene, extension and shortening occurred south and north of the Motagua fault, respectively. This strain regime migrated northward to the Polochic fault after the late Miocene. This shift is interpreted as a ``pull-up'' of North American blocks into the Caribbean realm. To the west, the PMFS interact with a trench-parallel fault zone that links the Tonala fault to the Jalpatagua fault. These faults bound a fore-arc sliver that is shared by the two overriding plates. We propose that the dextral Jalpatagua fault merges with the sinistral PMFS, leaving behind a suturing structure, the Tonala fault. This tectonic ``zipper'' allows the migration of the triple junction. As a result, the fore-arc sliver comes into contact with the North American plate and helps to maintain a linear subduction zone along the trailing edge of the Caribbean plate. All these processes currently make the triple junction increasingly diffuse as it propagates eastward and inland within both overriding plates.

A new low-latitude Late Paleocene-Early Eocene radiolarian biozonation based on Unitary Associations: Applications for accreted terranes.

The late Paleocene - early Eocene sequences of DSDP Leg 10 Sites 86, 94, 95, and 96, Leg 43 Site 384 and ODP Leg 171B Hole 1051A have been re-sampled and re-examined for radiolarians. A new late Paleocene to early Eocene low-latitude radiolarian zonation suited for the correlation of accreted terranes is established by using the Unitary Association (UA) method. This method has the property of attributing equal weight to each species occurrence, which has the advantage of not being dependant on a limited set of key datums. Twenty-two UAs have been erected and correlated to the existing age models (given by nannofossils, planktonic foraminifera and radiolarians) for each site. The 22 UAs have been united into seven Unitary Associations Zones (UA Zones) (JP10-JE4) to increase lateral traceability. Herein we present the resulting composite range chart and correlation between the studied cores. The position of the UA Zones in the Paleogene timescale of.Berggren et al. (1995) have been estimated using a general consensus correlation with calcareous microfossil groups and the existing radiolarian zonation. Reproducible radiolarian events identified in the present work are bound to directly tied and compiled absolute ages given by Nigrini et al. (2006) and Sanfilippo and Nigrini (1998a). The RP zones (Sanfilippo and Nigrini 1998a) and the UA Zones are consistent. Unitary Associations permit to distinguish supplementary zonal subdivisions within RP7 and RP6. Topotypes from DSDP Leg 10 have been illustrated using mainly SEM imaging to facilitate the identification of re-crystallized forms.

Decompression scenarios in a new underground transportation system

BACKGROUND: The risks of a public exposure to a sudden decompression, until now, have been related to civil aviation and, at a lesser extent, to diving activities. However, engineers are currently planning the use of low pressure environments for underground transportation. This method has been proposed for the future Swissmetro, a high-speed underground train designed for inter-urban linking in Switzerland. HYPOTHESIS: The use of a low pressure environment in an underground public transportation system must be considered carefully regarding the decompression risks. Indeed, due to the enclosed environment, both decompression kinetics and safety measures may differ from aviation decompression cases. METHOD: A theoretical study of decompression risks has been conducted at an early stage of the Swissmetro project. A three-compartment theoretical model, based on the physics of fluids, has been implemented with flow processing software (Ithink 5.0). Simulations have been conducted in order to analyze "decompression scenarios" for a wide range of parameters, relevant in the context of the Swissmetro main study. RESULTS: Simulation results cover a wide range from slow to explosive decompression, depending on the simulation parameters. Not surprisingly, the leaking orifice area has a tremendous impact on barotraumatic effects, while the tunnel pressure may significantly affect both hypoxic and barotraumatic effects. Calculations have also shown that reducing the free space around the vehicle may mitigate significantly an accidental decompression. CONCLUSION: Numeric simulations are relevant to assess decompression risks in the future Swissmetro system. The decompression model has proven to be useful in assisting both design choices and safety management.

A New Look at Emotional Intelligence: A Dual-Process Framework

In this article, the author provides a framework to guide¦research in emotional intelligence. Studies conducted up¦to the present bear on a conception of emotional intelligence¦as pertaining to the domain of consciousness and¦investigate the construct with a correlational approach.¦As an alternative, the author explores processes underlying¦emotional intelligence, introducing the distinction¦between conscious and automatic processing as a potential¦source of variability in emotionally intelligent¦behavior. Empirical literature is reviewed to support the¦central hypothesis that individual differences in emotional¦intelligence may be best understood by considering¦the way individuals automatically process emotional¦stimuli. Providing directions for research, the author¦encourages the integration of experimental investigation¦of processes underlying emotional intelligence with¦correlational analysis of individual differences and¦fosters the exploration of the automaticity component¦of emotional intelligence.

Establishment and characterization of models of chemotherapy resistance in colorectal cancer: Towards a predictive signature of chemoresistance.

Current standard treatments for metastatic colorectal cancer (CRC) are based on combination regimens with one of the two chemotherapeutic drugs, irinotecan or oxaliplatin. However, drug resistance frequently limits the clinical efficacy of these therapies. In order to gain new insights into mechanisms associated with chemoresistance, and departing from three distinct CRC cell models, we generated a panel of human colorectal cancer cell lines with acquired resistance to either oxaliplatin or irinotecan. We characterized the resistant cell line variants with regards to their drug resistance profile and transcriptome, and matched our results with datasets generated from relevant clinical material to derive putative resistance biomarkers. We found that the chemoresistant cell line variants had distinctive irinotecan- or oxaliplatin-specific resistance profiles, with non-reciprocal cross-resistance. Furthermore, we could identify several new, as well as some previously described, drug resistance-associated genes for each resistant cell line variant. Each chemoresistant cell line variant acquired a unique set of changes that may represent distinct functional subtypes of chemotherapy resistance. In addition, and given the potential implications for selection of subsequent treatment, we also performed an exploratory analysis, in relevant patient cohorts, of the predictive value of each of the specific genes identified in our cellular models.

Evolutionary Games in Networked Populations: Models and Experiments

Cooperation and coordination are desirable behaviors that are fundamental for the harmonious development of society. People need to rely on cooperation with other individuals in many aspects of everyday life, such as teamwork and economic exchange in anonymous markets. However, cooperation may easily fall prey to exploitation by selfish individuals who only care about short- term gain. For cooperation to evolve, specific conditions and mechanisms are required, such as kinship, direct and indirect reciprocity through repeated interactions, or external interventions such as punishment. In this dissertation we investigate the effect of the network structure of the population on the evolution of cooperation and coordination. We consider several kinds of static and dynamical network topologies, such as Baraba´si-Albert, social network models and spatial networks. We perform numerical simulations and laboratory experiments using the Prisoner's Dilemma and co- ordination games in order to contrast human behavior with theoretical results. We show by numerical simulations that even a moderate amount of random noise on the Baraba´si-Albert scale-free network links causes a significant loss of cooperation, to the point that cooperation almost vanishes altogether in the Prisoner's Dilemma when the noise rate is high enough. Moreover, when we consider fixed social-like networks we find that current models of social networks may allow cooperation to emerge and to be robust at least as much as in scale-free networks. In the framework of spatial networks, we investigate whether cooperation can evolve and be stable when agents move randomly or performing Le´vy flights in a continuous space. We also consider discrete space adopting purposeful mobility and binary birth-death process to dis- cover emergent cooperative patterns. The fundamental result is that cooperation may be enhanced when this migration is opportunistic or even when agents follow very simple heuristics. In the experimental laboratory, we investigate the issue of social coordination between indi- viduals located on networks of contacts. In contrast to simulations, we find that human players dynamics do not converge to the efficient outcome more often in a social-like network than in a random network. In another experiment, we study the behavior of people who play a pure co- ordination game in a spatial environment in which they can move around and when changing convention is costly. We find that each convention forms homogeneous clusters and is adopted by approximately half of the individuals. When we provide them with global information, i.e., the number of subjects currently adopting one of the conventions, global consensus is reached in most, but not all, cases. Our results allow us to extract the heuristics used by the participants and to build a numerical simulation model that agrees very well with the experiments. Our findings have important implications for policymakers intending to promote specific, desired behaviors in a mobile population. Furthermore, we carry out an experiment with human subjects playing the Prisoner's Dilemma game in a diluted grid where people are able to move around. In contrast to previous results on purposeful rewiring in relational networks, we find no noticeable effect of mobility in space on the level of cooperation. Clusters of cooperators form momentarily but in a few rounds they dissolve as cooperators at the boundaries stop tolerating being cheated upon. Our results highlight the difficulties that mobile agents have to establish a cooperative environment in a spatial setting without a device such as reputation or the possibility of retaliation. i.e. punishment. Finally, we test experimentally the evolution of cooperation in social networks taking into ac- count a setting where we allow people to make or break links at their will. In this work we give particular attention to whether information on an individual's actions is freely available to poten- tial partners or not. Studying the role of information is relevant as information on other people's actions is often not available for free: a recruiting firm may need to call a job candidate's refer- ences, a bank may need to find out about the credit history of a new client, etc. We find that people cooperate almost fully when information on their actions is freely available to their potential part- ners. Cooperation is less likely, however, if people have to pay about half of what they gain from cooperating with a cooperator. Cooperation declines even further if people have to pay a cost that is almost equivalent to the gain from cooperating with a cooperator. Thus, costly information on potential neighbors' actions can undermine the incentive to cooperate in dynamical networks.

Central serous chorioretinopathy: Recent findings and new physiopathology hypothesis.

Central serous chorioretinopathy (CSCR) is a major cause of vision threat among middle-aged male individuals. Multimodal imaging led to the description of a wide range of CSCR manifestations, and highlighted the contribution of the choroid and pigment epithelium in CSCR pathogenesis. However, the exact molecular mechanisms of CSCR have remained uncertain. The aim of this review is to recapitulate the clinical understanding of CSCR, with an emphasis on the most recent findings on epidemiology, risk factors, clinical and imaging diagnosis, and treatments options. It also gives an overview of the novel mineralocorticoid pathway hypothesis, from animal data to clinical evidences of the biological efficacy of oral mineralocorticoid antagonists in acute and chronic CSCR patients. In rodents, activation of the mineralocorticoid pathway in ocular cells either by intravitreous injection of its specific ligand, aldosterone, or by over-expression of the receptor specifically in the vascular endothelium, induced ocular phenotypes carrying many features of acute CSCR. Molecular mechanisms include expression of the calcium-dependent potassium channel (KCa2.3) in the endothelium of choroidal vessels, inducing subsequent vasodilation. Inappropriate or over-activation of the mineralocorticoid receptor in ocular cells and other tissues (such as brain, vessels) could link CSCR with the known co-morbidities observed in CSCR patients, including hypertension, coronary disease and psychological stress.

Dendritic Cells Cause Bone Lesions in a New Mouse Model of Histiocytosis.

Langerhans cell histiocytosis (LCH) is a rare disease caused by the clonal accumulation of dendritic Langerhans cells, which is often accompanied by osteolytic lesions. It has been reported that osteoclast-like cells play a major role in the pathogenic bone destruction seen in patients with LCH and these cells are postulated to originate from the fusion of DCs. However, due to the lack of reliable animal models the pathogenesis of LCH is still poorly understood. In this study, we have established a mouse model of histiocytosis- recapitulating human disease for osteolytic lesions seen in LCH patients. At 12 weeks after birth, severe bone lesions were observed in our multisystem histiocytosis (Mushi) model, when CD8α conventional dendritic cells (DCs) are transformed (MuTuDC) and accumulate. Most importantly, our study demonstrates that bone loss in LCH can be accounted for the transdifferentiation of MuTuDCs into functional osteoclasts both in vivo and in vitro. Moreover, we have shown that injected MuTuDCs reverse the osteopetrotic phenotype of oc/oc mice in vivo. In conclusion, our results support a crucial role of DCs in bone lesions in histiocytosis patients. Furthermore, our new model of LCH based on adoptive transfer of MuTuDC lines, leading to bone lesions within 1-2 weeks, will be an important tool for investigating the pathophysiology of this disease and ultimately for evaluating the potential of anti-resorptive drugs for the treatment of bone lesions.

Cell Cycle Proteins and Retinal Degeneration: Evidences of New Potential Therapeutic Targets.

During different forms of neurodegenerative diseases, including the retinal degeneration, several cell cycle proteins are expressed in the dying neurons from Drosophila to human revealing that these proteins are a hallmark of neuronal degeneration. This is true for animal models of Alzheimer's, and Parkinson's diseases, Amyotrophic Lateral Sclerosis and for Retinitis Pigmentosa as well as for acute injuries such as stroke and light damage. Longitudinal investigation and loss-of-function studies attest that cell cycle proteins participate to the process of cell death although with different impacts, depending on the disease. In the retina, inhibition of cell cycle protein action can result to massive protection. Nonetheless, the dissection of the molecular mechanisms of neuronal cell death is necessary to develop adapted therapeutic tools to efficiently protect photoreceptors as well as other neuron types.

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.

Overcoming limitations of modelling rare species by using ensembles of small models

1. Species distribution models (SDMs) have become a standard tool in ecology and applied conservation biology. Modelling rare and threatened species is particularly important for conservation purposes. However, modelling rare species is difficult because the combination of few occurrences and many predictor variables easily leads to model overfitting. A new strategy using ensembles of small models was recently developed in an attempt to overcome this limitation of rare species modelling and has been tested successfully for only a single species so far. Here, we aim to test the approach more comprehensively on a large number of species including a transferability assessment. 2. For each species numerous small (here bivariate) models were calibrated, evaluated and averaged to an ensemble weighted by AUC scores. These 'ensembles of small models' (ESMs) were compared to standard Species Distribution Models (SDMs) using three commonly used modelling techniques (GLM, GBM, Maxent) and their ensemble prediction. We tested 107 rare and under-sampled plant species of conservation concern in Switzerland. 3. We show that ESMs performed significantly better than standard SDMs. The rarer the species, the more pronounced the effects were. ESMs were also superior to standard SDMs and their ensemble when they were independently evaluated using a transferability assessment. 4. By averaging simple small models to an ensemble, ESMs avoid overfitting without losing explanatory power through reducing the number of predictor variables. They further improve the reliability of species distribution models, especially for rare species, and thus help to overcome limitations of modelling rare species.

Creatine deficiency syndomes : a new model of partial GAMT deficiency affecting brain cell development

Les syndromes de déficiences cérébrales en créatine (CCDS) sont dus à des mutations dans les gènes GATM et G AMT (codant pour les enzymes AGAT et G AMT de la voie de synthèse de créatine) ainsi que SLC6A8 (transporteur de créatine), et génèrent une absence ou une très forte baisse de créatine (Cr) dans le cerveau, mesurée par spectroscopic de résonance magnétique. Les patients CCDS développent des handicaps neurologiques sévères. Les patients AGAT et GAMT peuvent être traités avec des doses importantes de Cr, mais gardent dans la plupart des cas des séquelles neurologiques irréversibles. Aucun traitement efficace n'existe à ce jour pour la déficience en SLC6A8. Bien que de nombreux modèles aient été développés pour comprendre la Cr cérébrale en conditions physiologiques, les pathomécanismes des CCDS ne sont pas encore compris. Des souris transgéniques pour les gènes Gatm, Gamt et Slc6a8 ont été générées, mais elles ne miment que partiellement la pathologie humaine. Parmi les CCDS, la déficience en GAMT est la plus sévère, en raison de l'accumulation cérébrale de l'intermédiaire guanidinoacétate (GAA). Alors que la toxicité cérébrale du GAA a été étudiée par exposition directe au GAA d'animaux adultes sains, les mécanismes de la toxicité du GAA en condition de déficience en GAMT dans le cerveau en développement sont encore inconnus. Le but de ce projet était donc de développer un modèle de déficience en GAMT dans des cultures 3D primaires de cellules nerveuses de rat en agrégats par knock-down du gène GAMT, en utilisant un virus adéno-associé (AAV) induisant le mécanisme d'interférence à l'ARN (RNAi). Le virus scAAV2, à la multiplicité d'infection de 1000, s'est révélé le plus efficace pour transduire tous les types de cellules nerveuses des cultures (neurones, astrocytes, oligodendrocytes), et générer un knock-down maximal de la protéine GAMT de 85% (jour in vitro 18). Cette déficience partielle en GAMT s'est révélée insuffisante pour générer une déficience en Cr, mais a causé l'accumulation attendue de GAA, à des doses comparables aux niveaux observés dans le LCR des patients GAMT. Le GAA a induit une croissance axonale anarchique accompagnée d'une baisse de l'apoptose naturelle, suivis par une induction tardive de mort cellulaire non-apoptotique. Le co-traitement par la Cr a prévenu tous les effets toxiques du GAA. Ce travail montre que l'accumulation de GAA en absence de déficience en Cr est suffisante pour affecter le développement du tissu nerveux, et suggère que des formes de déficiences en GAMT supplémentaires, ne présentant pas de déficiences en Cr, pourraient être découvertes par mesure du GAA, en particulier à travers les programmes récemment proposés de dépistage néonatal de la déficience en GAMT. -- Cerebral creatine deficiency syndromes (CCDS) are caused by mutations in the genes GATM and GAMT (respectively coding for the two enzymes of the creatine synthetic pathway, AGAT and GAMT) as well as SLC6A8 (creatine transporter), and lead to the absence or very strong decrease of creatine (Cr) in the brain when measured by magnetic resonance spectroscopy. Affected patients show severe neurological impairments. While AGAT and GAMT deficient patients can be treated with high dosages of Cr, most remain with irreversible brain sequelae. No treatment has been successful so far for SLC6A8 deficiency. While many models have helped understanding the cerebral Cr pathways in physiological conditions, the pathomechanisms underlying CCDS are yet to be elucidated. Transgenic mice carrying mutations in the Gatm, Gamt and Slc6a8 genes have been developed, but only partially mimic the human pathology. Among CCDS, GAMT deficiency is the most severe, due to the CNS accumulation of the guanidinoacetate (GAA) intermediate. While brain toxicity of GAA has been explored through direct GAA exposure of adult healthy animals, the mechanisms underlying GAA toxicity in GAMT deficiency conditions on the developing CNS are yet unknown. The aim of this project was thus to develop and characterize a GAMT deficiency model in developing brain cells by gene knockdown, by adeno-associated virus (AAV)-driven RNA interference (RNAi) in rat 3D organotypic primary brain cell cultures in aggregates. scAAV2 with a multiplicity of infection of 1000 was shown as the most efficient serotype, was able to transduce all brain cell types (neurons, astrocytes, oligodendrocytes) and to induce a maximal GAMT protein knockdown of 85% (day in vitro 18). Metabolite analysis showed that partial GAMT knockdown was insufficient to induce Cr deficiency but generated the awaited GAA accumulation at concentrations comparable to the levels observed in cerebrospinal fluid of GAMT-deficient patients. Accumulated GAA induced axonal hypersprouting paralleled with inhibition of natural apoptosis, followed by a later induction in non-apoptotic cell death. Cr supplementation led to the prevention of all GAA-induced toxic effects. This work shows that GAA accumulation without Cr deficiency is sufficient to affect CNS development, and suggests that additional partial GAMT deficiencies, which may not show the classical brain Cr deficiency, may be discovered through GAA measurement including by recently proposed neonatal screening programs for GAMT deficiency.