In vitro neuroendocrine effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in the AhR-expressing hypothalamic rat GnV-3 cell line.

The aryl hydrocarbon receptor (AhR) is involved in a wide variety of biological and toxicological responses, including neuroendocrine signaling. Due to the complexity of neuroendocrine pathways in e.g. the hypothalamus and pituitary, there are limited in vitro models available despite the strong demand for such systems to study and predict neuroendocrine effects of chemicals. In this study, the applicability of the AhR-expressing rat hypothalamic GnV-3 cell line was investigated as a novel model to screen for neuroendocrine effects of AhR ligands using 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) as reference compound. The qRT-PCR analyses demonstrated the presence of several sets of neurotransmitter receptors in the GnV-3 cells. TCDD (10nM) altered neurotransmitter signaling by up-regulation of glutamate (Grik2), gamma-amino butyric acid (Gabra2) and serotonin (Ht2C) receptor mRNA levels. However, no significant changes in basal and serotonin-evoked intracellular Ca(2+) concentration ([Ca(2+)]i) or serotonin release were observed. On the other hand, TCDD de-regulated period circadian protein homolog 1 (Per1) and gonadotropin releasing hormone (Gnrh) mRNA levels within a 24-h time period. Both Per1 and Gnrh genes displayed a similar mRNA expression pattern in GnV-3 cells. Moreover, the involvement of AhR in TCDD-induced alteration of Neuropeptide Y (Npy) gene expression was found and confirmed by using siRNA targeted against Ahr in GnV-3 cells. Overall, the combined results demonstrate that GnV-3 cells may be a suitable model to predict some mechanisms of action and effects of AhR ligands in the hypothalamus.

Systems biology of plants : from intraspecific genome variation to computational morphodynamics

Recently, the introduction of second generation sequencing and further advance-ments in confocal microscopy have enabled system-level studies for the functional characterization of genes. The degree of complexity intrinsic to these approaches needs the development of bioinformatics methodologies and computational models for extracting meaningful biological knowledge from the enormous amount of experi¬mental data which is continuously generated. This PhD thesis presents several novel bioinformatics methods and computational models to address specific biological questions in Plant Biology by using the plant Arabidopsis thaliana as a model system. First, a spatio-temporal qualitative analysis of quantitative transcript and protein profiles is applied to show the role of the BREVIS RADIX (BRX) protein in the auxin- cytokinin crosstalk for root meristem growth. Core of this PhD work is the functional characterization of the interplay between the BRX protein and the plant hormone auxin in the root meristem by using a computational model based on experimental evidence. Hyphotesis generated by the modelled to the discovery of a differential endocytosis pattern in the root meristem that splits the auxin transcriptional response via the plasma membrane to nucleus partitioning of BRX. This positional information system creates an auxin transcriptional pattern that deviates from the canonical auxin response and is necessary to sustain the expression of a subset of BRX-dependent auxin-responsive genes to drive root meristem growth. In the second part of this PhD thesis, we characterized the genome-wide impact of large scale deletions on four divergent Arabidopsis natural strains, through the integration of Ultra-High Throughput Sequencing data with data from genomic hybridizations on tiling arrays. Analysis of the identified deletions revealed a considerable portion of protein coding genes affected and supported a history of genomic rearrangements shaped by evolution. In the last part of the thesis, we showed that VIP3 gene in Arabidopsis has an evo-lutionary conserved role in the 3' to 5' mRNA degradation machinery, by applying a novel approach for the analysis of mRNA-Seq data from random-primed mRNA. Altogether, this PhD research contains major advancements in the study of natural genomic variation in plants and in the application of computational morphodynamics models for the functional characterization of biological pathways essential for the plant. - Récemment, l'introduction du séquençage de seconde génération et les avancées dans la microscopie confocale ont permis des études à l'échelle des différents systèmes cellulaires pour la caractérisation fonctionnelle de gènes. Le degrés de complexité intrinsèque à ces approches ont requis le développement de méthodologies bioinformatiques et de modèles mathématiques afin d'extraire de la masse de données expérimentale générée, des information biologiques significatives. Ce doctorat présente à la fois des méthodes bioinformatiques originales et des modèles mathématiques pour répondre à certaines questions spécifiques de Biologie Végétale en utilisant la plante Arabidopsis thaliana comme modèle. Premièrement, une analyse qualitative spatio-temporelle de profiles quantitatifs de transcripts et de protéines est utilisée pour montrer le rôle de la protéine BREVIS RADIX (BRX) dans le dialogue entre l'auxine et les cytokinines, des phytohormones, dans la croissance du méristème racinaire. Le noyau de ce travail de thèse est la caractérisation fonctionnelle de l'interaction entre la protéine BRX et la phytohormone auxine dans le méristème de la racine en utilisant des modèles informatiques basés sur des preuves expérimentales. Les hypothèses produites par le modèle ont mené à la découverte d'un schéma différentiel d'endocytose dans le méristème racinaire qui divise la réponse transcriptionnelle à l'auxine par le partitionnement de BRX de la membrane plasmique au noyau de la cellule. Cette information positionnelle crée une réponse transcriptionnelle à l'auxine qui dévie de la réponse canonique à l'auxine et est nécessaire pour soutenir l'expression d'un sous ensemble de gènes répondant à l'auxine et dépendant de BRX pour conduire la croissance du méristème. Dans la seconde partie de cette thèse de doctorat, nous avons caractérisé l'impact sur l'ensemble du génome des délétions à grande échelle sur quatre souches divergentes naturelles d'Arabidopsis, à travers l'intégration du séquençage à ultra-haut-débit avec l'hybridation génomique sur puces ADN. L'analyse des délétions identifiées a révélé qu'une proportion considérable de gènes codant était affectée, supportant l'idée d'un historique de réarrangement génomique modelé durant l'évolution. Dans la dernière partie de cette thèse, nous avons montré que le gène VÏP3 dans Arabidopsis a conservé un rôle évolutif dans la machinerie de dégradation des ARNm dans le sens 3' à 5', en appliquant une nouvelle approche pour l'analyse des données de séquençage d'ARNm issue de transcripts amplifiés aléatoirement. Dans son ensemble, cette recherche de doctorat contient des avancées majeures dans l'étude des variations génomiques naturelles des plantes et dans l'application de modèles morphodynamiques informatiques pour la caractérisation de réseaux biologiques essentiels à la plante. - Le développement des plantes est écrit dans leurs codes génétiques. Pour comprendre comment les plantes sont capables de s'adapter aux changements environnementaux, il est essentiel d'étudier comment leurs gènes gouvernent leur formation. Plus nous essayons de comprendre le fonctionnement d'une plante, plus nous réalisons la complexité des mécanismes biologiques, à tel point que l'utilisation d'outils et de modèles mathématiques devient indispensable. Dans ce travail, avec l'utilisation de la plante modèle Arabidopsis thalicinci nous avons résolu des problèmes biologiques spécifiques à travers le développement et l'application de méthodes informatiques concrètes. Dans un premier temps, nous avons investigué comment le gène BREVIS RADIX (BRX) régule le développement de la racine en contrôlant la réponse à deux hormones : l'auxine et la cytokinine. Nous avons employé une analyse statistique sur des mesures quantitatives de transcripts et de produits de gènes afin de démontrer que BRX joue un rôle antagonisant dans le dialogue entre ces deux hormones. Lorsque ce-dialogue moléculaire est perturbé, la racine primaire voit sa longueur dramatiquement réduite. Pour comprendre comment BRX répond à l'auxine, nous avons développé un modèle informatique basé sur des résultats expérimentaux. Les simulations successives ont mené à la découverte d'un signal positionnel qui contrôle la réponse de la racine à l'auxine par la régulation du mouvement intracellulaire de BRX. Dans la seconde partie de cette thèse, nous avons analysé le génome entier de quatre souches naturelles d'Arabidopsis et nous avons trouvé qu'une grande partie de leurs gènes étaient manquant par rapport à la souche de référence. Ce résultat indique que l'historique des modifications génomiques conduites par l'évolution détermine une disponibilité différentielle des gènes fonctionnels dans ces plantes. Dans la dernière partie de ce travail, nous avons analysé les données du transcriptome de la plante où le gène VIP3 était non fonctionnel. Ceci nous a permis de découvrir le rôle double de VIP3 dans la régulation de l'initiation de la transcription et dans la dégradation des transcripts. Ce rôle double n'avait jusqu'alors été démontrée que chez l'homme. Ce travail de doctorat supporte le développement et l'application de méthodologies informatiques comme outils inestimables pour résoudre la complexité des problèmes biologiques dans la recherche végétale. L'intégration de la biologie végétale et l'informatique est devenue de plus en plus importante pour l'avancée de nos connaissances sur le fonctionnement et le développement des plantes.

Method to assess and optimise dependability of complex macro-systems: application to a railway signalling system

Achieving a high degree of dependability in complex macro-systems is challenging. Because of the large number of components and numerous independent teams involved, an overview of the global system performance is usually lacking to support both design and operation adequately. A functional failure mode, effects and criticality analysis (FMECA) approach is proposed to address the dependability optimisation of large and complex systems. The basic inductive model FMECA has been enriched to include considerations such as operational procedures, alarm systems. environmental and human factors, as well as operation in degraded mode. Its implementation on a commercial software tool allows an active linking between the functional layers of the system and facilitates data processing and retrieval, which enables to contribute actively to the system optimisation. The proposed methodology has been applied to optimise dependability in a railway signalling system. Signalling systems are typical example of large complex systems made of multiple hierarchical layers. The proposed approach appears appropriate to assess the global risk- and availability-level of the system as well as to identify its vulnerabilities. This enriched-FMECA approach enables to overcome some of the limitations and pitfalls previously reported with classical FMECA approaches.

Dynamic Modelling of Material Flows and Sustainable Resource Use: Case Studies in Regional Metabolism and Space Life Support Systems

Sustainable resource use is one of the most important environmental issues of our times. It is closely related to discussions on the 'peaking' of various natural resources serving as energy sources, agricultural nutrients, or metals indispensable in high-technology applications. Although the peaking theory remains controversial, it is commonly recognized that a more sustainable use of resources would alleviate negative environmental impacts related to resource use. In this thesis, sustainable resource use is analysed from a practical standpoint, through several different case studies. Four of these case studies relate to resource metabolism in the Canton of Geneva in Switzerland: the aim was to model the evolution of chosen resource stocks and flows in the coming decades. The studied resources were copper (a bulk metal), phosphorus (a vital agricultural nutrient), and wood (a renewable resource). In addition, the case of lithium (a critical metal) was analysed briefly in a qualitative manner and in an electric mobility perspective. In addition to the Geneva case studies, this thesis includes a case study on the sustainability of space life support systems. Space life support systems are systems whose aim is to provide the crew of a spacecraft with the necessary metabolic consumables over the course of a mission. Sustainability was again analysed from a resource use perspective. In this case study, the functioning of two different types of life support systems, ARES and BIORAT, were evaluated and compared; these systems represent, respectively, physico-chemical and biological life support systems. Space life support systems could in fact be used as a kind of 'laboratory of sustainability' given that they represent closed and relatively simple systems compared to complex and open terrestrial systems such as the Canton of Geneva. The chosen analysis method used in the Geneva case studies was dynamic material flow analysis: dynamic material flow models were constructed for the resources copper, phosphorus, and wood. Besides a baseline scenario, various alternative scenarios (notably involving increased recycling) were also examined. In the case of space life support systems, the methodology of material flow analysis was also employed, but as the data available on the dynamic behaviour of the systems was insufficient, only static simulations could be performed. The results of the case studies in the Canton of Geneva show the following: were resource use to follow population growth, resource consumption would be multiplied by nearly 1.2 by 2030 and by 1.5 by 2080. A complete transition to electric mobility would be expected to only slightly (+5%) increase the copper consumption per capita while the lithium demand in cars would increase 350 fold. For example, phosphorus imports could be decreased by recycling sewage sludge or human urine; however, the health and environmental impacts of these options have yet to be studied. Increasing the wood production in the Canton would not significantly decrease the dependence on wood imports as the Canton's production represents only 5% of total consumption. In the comparison of space life support systems ARES and BIORAT, BIORAT outperforms ARES in resource use but not in energy use. However, as the systems are dimensioned very differently, it remains questionable whether they can be compared outright. In conclusion, the use of dynamic material flow analysis can provide useful information for policy makers and strategic decision-making; however, uncertainty in reference data greatly influences the precision of the results. Space life support systems constitute an extreme case of resource-using systems; nevertheless, it is not clear how their example could be of immediate use to terrestrial systems.

Modeling and mitigation of supply-demand mismatches

In this thesis, I develop analytical models to price the value of supply chain investments under demand uncer¬tainty. This thesis includes three self-contained papers. In the first paper, we investigate the value of lead-time reduction under the risk of sudden and abnormal changes in demand forecasts. We first consider the risk of a complete and permanent loss of demand. We then provide a more general jump-diffusion model, where we add a compound Poisson process to a constant-volatility demand process to explore the impact of sudden changes in demand forecasts on the value of lead-time reduction. We use an Edgeworth series expansion to divide the lead-time cost into that arising from constant instantaneous volatility, and that arising from the risk of jumps. We show that the value of lead-time reduction increases substantially in the intensity and/or the magnitude of jumps. In the second paper, we analyze the value of quantity flexibility in the presence of supply-chain dis- intermediation problems. We use the multiplicative martingale model and the "contracts as reference points" theory to capture both positive and negative effects of quantity flexibility for the downstream level in a supply chain. We show that lead-time reduction reduces both supply-chain disintermediation problems and supply- demand mismatches. We furthermore analyze the impact of the supplier's cost structure on the profitability of quantity-flexibility contracts. When the supplier's initial investment cost is relatively low, supply-chain disin¬termediation risk becomes less important, and hence the contract becomes more profitable for the retailer. We also find that the supply-chain efficiency increases substantially with the supplier's ability to disintermediate the chain when the initial investment cost is relatively high. In the third paper, we investigate the value of dual sourcing for the products with heavy-tailed demand distributions. We apply extreme-value theory and analyze the effects of tail heaviness of demand distribution on the optimal dual-sourcing strategy. We find that the effects of tail heaviness depend on the characteristics of demand and profit parameters. When both the profit margin of the product and the cost differential between the suppliers are relatively high, it is optimal to buffer the mismatch risk by increasing both the inventory level and the responsive capacity as demand uncertainty increases. In that case, however, both the optimal inventory level and the optimal responsive capacity decrease as the tail of demand becomes heavier. When the profit margin of the product is relatively high, and the cost differential between the suppliers is relatively low, it is optimal to buffer the mismatch risk by increasing the responsive capacity and reducing the inventory level as the demand uncertainty increases. In that case, how¬ever, it is optimal to buffer with more inventory and less capacity as the tail of demand becomes heavier. We also show that the optimal responsive capacity is higher for the products with heavier tails when the fill rate is extremely high.