Characterization of polycystin-1 in ADPKD pathogenetic mechanism : biogenesis and functional implications by genetic approaches in mouse

La polykystose rénale autosomique dominante (ADPKD) est une des maladies génétiques les plus communes. ADPKD se manifeste le plus souvent au stade adulte par la présence de kystes rénaux, et bien souvent de kystes hépatiques, avec une progression très variable. ADPKD mène à une insuffisance rénale: les seuls recours sont la dialyse puis la transplantation rénale. Les mutations dispersées sur les gènes PKD1 (majoritairement; la protéine polycystine-1, PC1) et PKD2 (la protéine polycystine-2, PC2) sont responsables de l’ADPKD. Le mécanisme pathogénétique de perte de fonction (LOF) et donc d’un effet récessif cellulaire est évoqué comme causatif de l’ADPKD. LOF est en effet supporté par les modèles murins d’inactivation de gènes PKD1/PKD2, qui développent de kystes, quoique in utéro et avec une rapidité impressionnante dans les reins mais pas dans le foie. Malgré de nombreuses études in vitro, le rôle de PC1/PC2 membranaire/ciliaire reste plutôt hypothétique et contexte-dépendant. Ces études ont associé PC1/PC2 à une panoplie de voies de signalisation et ont souligné une complexité structurelle et fonctionnelle exceptionnelle, dont l’implication a été testée notamment chez les modèles de LOF. Toutefois, les observations patho-cellulaires chez l’humain dont une expression soutenue, voire augmentée, de PKD1/PC1 et l’absence de phénotypes extrarénaux particuliers remet en question l’exclusivité du mécanisme de LOF. Il était donc primordial 1) d’éclaircir le mécanisme pathogénétique, 2) de générer des outils in vivo authentiques d’ADPKD en terme d’initiation et de progression de la maladie et 3) de mieux connaitre les fonctions des PC1/PC2 indispensables pour une translation clinique adéquate. Cette thèse aborde tous ces points. Tout d’abord, nous avons démontré qu’une augmentation de PKD1 endogène sauvage, tout comme chez l’humain, est pathogénétique en générant et caractérisant en détail un modèle murin transgénique de Pkd1 (Pkd1TAG). Ce modèle reproduit non seulement les caractéristiques humaines rénales, associées aux défauts du cil primaire, mais aussi extrarénales comme les kystes hépatiques. La sévérité du phénotype corrèle avec le niveau d’expression de Pkd1 ce qui supporte fortement un modèle de dosage. Dans un deuxième temps, nous avons démontré par les études de complémentations génétiques que ces deux organes reposent sur une balance du clivage GPS de Pc1, une modification post-traductionelle typique des aGPCR, et dont l’activité et l’abondance semblent strictement contrôlées. De plus, nous avons caractérisé extensivement la biogénèse de Pc1 et de ses dérivés in vivo générés suite au clivage GPS. Nous avons identifié une toute nouvelle forme et prédominante à la membrane, la forme Pc1deN, en plus de confirmer deux fragments N- et C-terminal de Pc1 (NTF et CTF, respectivement) qui eux s’associent de manière non-covalente. Nous avons démontré de façon importante que le trafic de Pc1deN i.e., une forme NTF détachée du CTF, est toutefois dépendant de l’intégrité du fragment CTF in vivo. Par la suite, nous avons généré un premier modèle humanisant une mutation PKD1 non-sens tronquée au niveau du domaine NTF(E3043X) en la reproduisant chez une souris transgénique (Pkd1extra). Structurellement, cette mutation, qui mimique la forme Pc1deN, s’est également avérée causative de PKD. Le modèle Pkd1extra a permis entre autre de postuler l’existence d’une cross-interaction entre différentes formes de Pc1. De plus, nos deux modèles murins sont tous les deux associés à des niveaux altérés de c-Myc et Pc2, et soutiennent une implication réelle de ces derniers dans l’ADPKD tou comme une interaction fonctionnelle entre les polycystines. Finalement, nous avons démontré un chevauchement significatif entre l’ADPKD et le dommage rénal aigüe (ischémie/AKI) dont une expression augmentée de Pc1 et Pc2 mais aussi une stimulation de plusieurs facteurs cystogéniques tel que la tubérine, la β-caténine et l’oncogène c-Myc. Nos études ont donc apporté des évidences cruciales sur la contribution du gène dosage dans l’ADPKD. Nous avons développé deux modèles murins qui serviront d’outil pour l’analyse de la pathologie humaine ainsi que pour la validation préclinique ADPKD. L’identification d’une nouvelle forme de Pc1 ajoute un niveau de complexité supplémentaire expliquant en partie une capacité de régulation de plusieurs voies de signalisation par Pc1. Nos résultats nous amènent à proposer de nouvelles approches thérapeutiques: d’une part, le ciblage de CTF i.e., de style chaperonne, et d’autre part le ciblage de modulateurs intracellulaires (c-Myc, Pc2, Hif1α). Ensemble, nos travaux sont d’une importance primordiale du point de vue informatif et pratique pour un avancement vers une thérapie contre l’ADPKD. Le partage de voies communes entre AKI et ADPKD ouvre la voie aux approches thérapeutiques parallèles pour un traitement assurément beaucoup plus rapide.

Reinforcement Learning Approaches to Power System Scheduling

One major component of power system operation is generation scheduling. The objective of the work is to develop efficient control strategies to the power scheduling problems through Reinforcement Learning approaches. The three important active power scheduling problems are Unit Commitment, Economic Dispatch and Automatic Generation Control. Numerical solution methods proposed for solution of power scheduling are insufficient in handling large and complex systems. Soft Computing methods like Simulated Annealing, Evolutionary Programming etc., are efficient in handling complex cost functions, but find limitation in handling stochastic data existing in a practical system. Also the learning steps are to be repeated for each load demand which increases the computation time.Reinforcement Learning (RL) is a method of learning through interactions with environment. The main advantage of this approach is it does not require a precise mathematical formulation. It can learn either by interacting with the environment or interacting with a simulation model. Several optimization and control problems have been solved through Reinforcement Learning approach. The application of Reinforcement Learning in the field of Power system has been a few. The objective is to introduce and extend Reinforcement Learning approaches for the active power scheduling problems in an implementable manner. The main objectives can be enumerated as:(i) Evolve Reinforcement Learning based solutions to the Unit Commitment Problem.(ii) Find suitable solution strategies through Reinforcement Learning approach for Economic Dispatch. (iii) Extend the Reinforcement Learning solution to Automatic Generation Control with a different perspective. (iv) Check the suitability of the scheduling solutions to one of the existing power systems.First part of the thesis is concerned with the Reinforcement Learning approach to Unit Commitment problem. Unit Commitment Problem is formulated as a multi stage decision process. Q learning solution is developed to obtain the optimwn commitment schedule. Method of state aggregation is used to formulate an efficient solution considering the minimwn up time I down time constraints. The performance of the algorithms are evaluated for different systems and compared with other stochastic methods like Genetic Algorithm.Second stage of the work is concerned with solving Economic Dispatch problem. A simple and straight forward decision making strategy is first proposed in the Learning Automata algorithm. Then to solve the scheduling task of systems with large number of generating units, the problem is formulated as a multi stage decision making task. The solution obtained is extended in order to incorporate the transmission losses in the system. To make the Reinforcement Learning solution more efficient and to handle continuous state space, a fimction approximation strategy is proposed. The performance of the developed algorithms are tested for several standard test cases. Proposed method is compared with other recent methods like Partition Approach Algorithm, Simulated Annealing etc.As the final step of implementing the active power control loops in power system, Automatic Generation Control is also taken into consideration.Reinforcement Learning has already been applied to solve Automatic Generation Control loop. The RL solution is extended to take up the approach of common frequency for all the interconnected areas, more similar to practical systems. Performance of the RL controller is also compared with that of the conventional integral controller.In order to prove the suitability of the proposed methods to practical systems, second plant ofNeyveli Thennal Power Station (NTPS IT) is taken for case study. The perfonnance of the Reinforcement Learning solution is found to be better than the other existing methods, which provide the promising step towards RL based control schemes for practical power industry.Reinforcement Learning is applied to solve the scheduling problems in the power industry and found to give satisfactory perfonnance. Proposed solution provides a scope for getting more profit as the economic schedule is obtained instantaneously. Since Reinforcement Learning method can take the stochastic cost data obtained time to time from a plant, it gives an implementable method. As a further step, with suitable methods to interface with on line data, economic scheduling can be achieved instantaneously in a generation control center. Also power scheduling of systems with different sources such as hydro, thermal etc. can be looked into and Reinforcement Learning solutions can be achieved.

Novel Approaches to Biodegradable Polymers: Synthesis and Biodegradation Studies

Biodegradable polymers have opened an emerging area of great interest because they are the ultimate solution for the disposal problems of synthetic polymers used for short time applications in the environmental and biomedical field. The biodegradable polymers available until recently have a number of limitations in terms of strength and dimensional stability. Most of them have processing problems and are also very expensive. Recent developments in biodegradable polymers show that monomers and polymers obtained from renewable resources are important owing to their inherent biodegradability, biocompatibility and easy availability. The present study is, therefore, mostly concemed with the utilization of renewable resources by effecting chemical modification/copolymerization on existing synthetic polymers/natural polymers for introducing better biodegradability and material properties.The thesis describes multiple approaches in the design of new biodegradable polymers: (1) Chemical modification of an existing nonbiodegradable polymer, polyethylene, by anchoring monosaccharides after functionalization to introduce biodegradability. (2) Copolymerization of an existing biodegradable polymer, polylactide, with suitable monomers and/or polymers to tailor their properties to suit the emerging requirements such as (2a) graft copolymerization of lactide onto chitosan to get controlled solvation and biodegradability and (2b) copolymerization of polylactide with cycloaliphatic amide segments to improve upon the thermal properties and processability.

“Development of lymphoid cell culture system from Penaeus monodon and molecular approaches for its transformation

Unveiling the molecular and regulatory mechanisms that prevent in vitro transformation in shrimp remains elusive in the development of continuous cell lines, with an arduous history of over 25 years (Jayesh et al., 2012). Despite presenting challenges to researchers in developing a cell line, the billion dollar aquaculture industry is under viral threat. In addition, the regulatory mechanisms that prevent in vitro transformation and carcinoma in shrimps might provide new leads for the development of anti-ageing and anti-cancer interventions in human (Vogt, 2011) and in higher vertebrates. This highlights the importance of developing shrimp cell lines, to bring out effective prophylactics against shrimp viruses and for understanding the mechanism that induce cancer and ageing in human.. Advances in molecular biology and various gene transfer technologies for immortalization of cells have resulted in the development of hundreds of cell lines from insects and mammals, but yet not a single cell line has been developed from shrimp and other marine invertebrates. With this backdrop, the research described in this thesis attempted to develop molecular tools for induced in vitro transformation in lymphoid cells from Penaeus monodon and for the development of continuous cell lines using conventional and novel technologies to address the problems at cellular and molecular level.

Molecular Approaches For Characterization And Determination Of Pathogenicity Of Vibrios With Special Reference To Vibrio Harveyi From Penaeus Monodon Larval Production Systems

The present study focuses on vibrios especially Vibrio harveyi isolated from shrimp (P. monodon) larval production systems from both east and west coasts during times of mortality. A comprehensive approach has been made to work out their systematics through numerical taxonomy and group them based on RAPD profiling and to segregate the virulent from non- virulent isolates based on the presence of virulent genes as well as their phenotypic expression. The information gathered has helped to develop a simple scheme of identification based on phenotypic characters and segregate the virulent from non virulent strains of V. harveyi.

Reinforcement Learning approaches to Economic Dispatch problem

This paper presents Reinforcement Learning (RL) approaches to Economic Dispatch problem. In this paper, formulation of Economic Dispatch as a multi stage decision making problem is carried out, then two variants of RL algorithms are presented. A third algorithm which takes into consideration the transmission losses is also explained. Efficiency and flexibility of the proposed algorithms are demonstrated through different representative systems: a three generator system with given generation cost table, IEEE 30 bus system with quadratic cost functions, 10 generator system having piecewise quadratic cost functions and a 20 generator system considering transmission losses. A comparison of the computation times of different algorithms is also carried out.

Characterization and applications of two protease enzymes obtained by culture dependent and independent approaches from mangrove sediments

Soil community genomics or metagenomics is employed in this study to analyze the evolutionary related - ness of mangrove microbial community. The metagenomic DNA was isolated from mangrove sediment and 16SrDNA was amplified using universal primers. The amplicons were ligated into pTZ57R/T cloning vector and transformed onto E. coli JM109 host cells. The recombinant plasmids were isolated from positive clones and the insert was confirmed by its reamplification. The amplicons were subjected to Amplified Ribosomal DNA Restriction Analysis (ARDRA) using three different tetra cutter restriction enzymes namely Sau3A1, Hha1 and HpaII. The 16SrDNA insert were sequenced and their identity was determined. The sequences were submitted to NCBI database and accession numbers obtained. The phylo - genetic tree was constructed based on Neighbor-Joining technique. Clones belonged to two major phyla of the bacterial domain, namely Firmicutes and Proteobacteria, with members of Firmicutes predominating. The microbial diversity of the mangrove sediment was explored in this manner.

Management approaches in organic potato and tomato production

The presented thesis considered three different system approach topics to ensure yield and plant health in organically grown potatoes and tomatoes. The first topic describes interactions between late blight (Phytophthora infestans) incidence and soil nitrogen supply on yield in organic potato farming focussing in detail on the yield loss relationship of late blight based on results of several field trials. The interactive effects of soil N-supply, climatic conditions and late blight on the yield were studied in the presence and absence of copper fungicides from 2002-2004 for the potato cultivar Nicola. Under conditions of central Germany the use of copper significantly reduced late blight in almost all cases (15-30 %). However, the reductions in disease through copper application did not result in statistically significant yield increases (+0 – +10 %). Subsequently, only 30 % of the variation in yield could be attributed to disease reductions. A multiple regression model (R²Max), however, including disease reduction, growth duration and temperature sum from planting until 60 % disease severity was reached and soil mineral N contents 10 days after emergence could explain 75 % of the observed variations in yield. The second topic describes the effect of some selected organic fertilisers and biostimulant products on nitrogen-mineralization and efficiency, yield and diseases in organic potato and tomato trials. The organic fertilisers Biofeed Basis (BFB, plant derived, AgroBioProducts, Wageningen, Netherlands) and BioIlsa 12,5 Export (physically hydrolysed leather shavings, hair and skin of animals; ILSA, Arizignano, Italy) and two biostimulant products BioFeed Quality (BFQ, multi-compound seaweed extract, AgroBioProducts) and AUSMA (aqueous pine and spruce needle extract, A/S BIOLAT, Latvia), were tested. Both fertilisers supplied considerable amounts of nitrogen during the main uptake phases of the crops and reached yields as high or higher as compared to the control with horn meal fertilisation. The N-efficiency of the tested fertilisers in potatoes ranged from 90 to 159 kg yield*kg-1 N – input. Most effective with tomatoes were the combined treatments of fertiliser BFB and the biostimulants AUSMA and BFQ. Both biostimulants significantly increased the share of healthy fruit and/or the number of fruits. BFQ significantly increased potato yields (+6 %) in one out of two years and reduced R. solani-infestation in the potatoes. This suggests that the biostimulants had effects on plant metabolism and resistance properties. However, no effects of biostimulants on potato late blight could be observed in the fields. The third topic focused on the effect of suppressive composts and seed tuber health on the saprophytic pathogen Rhizoctonia solani in organic potato systems. In the present study 5t ha-1 DM of a yard and bio-waste (60/40) compost produced in a 5 month composting process and a 15 month old 100 % yard waste compost were used to assess the effects on potato infection with R. solani when applying composts within the limits allowed. Across the differences in initial seed tuber infestation and 12 cultivars 5t DM ha-1 of high quality composts, applied in the seed tuber area, reduced the infestation of harvested potatoes with black scurf, tuber malformations and dry core tubers by 20 to 84 %, 20 to 49 % and 38 to 54 %, respectively, while marketable yields were increased by 5 to 25 % due to lower rates of wastes after sorting (marketable yield is gross yield minus malformed tubers, tubers with dry core, tubers with black scurf > 15% infested skin). The rate of initial black scurf infection of the seed tubers also affected tuber number, health and quality significantly. Compared to healthy seed tubers initial black scurf sclerotia infestation of 2-5 and >10 % of tuber surface led in untreated plots to a decrease in marketable yields by 14-19 and 44-66 %, a increase of black scurf severity by 8-40 and 34-86 % and also increased the amount of malformed and dry core tubers by 32-57 and 109-214 %.

Finding Spaces for Urban Food Production – Matching Spatial and Stakeholder Analysis with Urban Agriculture Approaches in the Urban Renewal Area of Dortmund-Hörde, Germany

Using the case of an economically declined neighbourhood in the post-industrial German Ruhr Area (sometimes characterized as Germany’s “Rust Belt”), we analyse, describe and conclude how urban agriculture can be used as a catalyst to stimulate and support urban renewal and regeneration, especially from a socio-cultural perspective. Using the methodological framework of participatory action research, and linking bottom-up and top-down planning approaches, a project path was developed to include the population affected and foster individual responsibility for their district, as well as to strengthen inhabitants and stakeholder groups in a permanent collective stewardship for the individual forms of urban agriculture developed and implemented. On a more abstract level, the research carried out can be characterized as a form of action research with an intended transgression of the boundaries between research, planning, design, and implementation. We conclude that by synchronously combining those four domains with intense feedback loops, synergies for the academic knowledge on the potential performance of urban agriculture in terms of sustainable development, as well as the benefits for the case-study area and the interests of individual urban gardeners can be achieved.

A compositional data analysis package for R providing multiple approaches

”compositions” is a new R-package for the analysis of compositional and positive data. It contains four classes corresponding to the four different types of compositional and positive geometry (including the Aitchison geometry). It provides means for computation, plotting and high-level multivariate statistical analysis in all four geometries. These geometries are treated in an fully analogous way, based on the principle of working in coordinates, and the object-oriented programming paradigm of R. In this way, called functions automatically select the most appropriate type of analysis as a function of the geometry. The graphical capabilities include ternary diagrams and tetrahedrons, various compositional plots (boxplots, barplots, piecharts) and extensive graphical tools for principal components. Afterwards, ortion and proportion lines, straight lines and ellipses in all geometries can be added to plots. The package is accompanied by a hands-on-introduction, documentation for every function, demos of the graphical capabilities and plenty of usage examples. It allows direct and parallel computation in all four vector spaces and provides the beginner with a copy-and-paste style of data analysis, while letting advanced users keep the functionality and customizability they demand of R, as well as all necessary tools to add own analysis routines. A complete example is included in the appendix

Approaches to Learning

Looks at some of the models of learning and discusses how they apply to university students

Análisis cruzado de las respuestas del neoinstitucionalismo liberal y del constructivismo social aplicadas al estudio de la OTAN y sus Estados miembros

Esta monografía ayuda a responder la pregunta del porque los Estados actuan a través de organizaciones internacionales a partir de los postulados del neoliberalismo institucional de Robert Keohane y del constructivismo Social de Alexander Wendt.

Interdisciplinary approaches: Readings 1

Biglan (1975a,1975b) Ortega Gasset (1930) , Chynoweth (2009) All references can be found in your mendeley collection WEBS6203 https://www.mendeley.com/groups/4904781/webs6203/ WEBS2002 https://www.mendeley.com/groups/4931801/webs2002/

Interdisciplinary Approaches: Readings 2

Tiropanis et al 2015 can be used as a model for a comparison of disciplinary approaches Trowler 2013 discusses conceptualising the idea of 'discipline' Hughes 2013 reviews some of the key previous papers All references can be found in the module mendeley collection WEBS 6203 https://www.mendeley.com/groups/4904781/webs6203/ WEBS2002 https://www.mendeley.com/groups/4931801/webs2002/