Intestinal microbiology in Crohn's disease: a study of Escherichia coli as a potential etiologic agent

La malaltia de Crohn és una malaltia inflamatòria intestinal crònica d'etiologia encara desconeguda. Actualment es pensa que hi participen factors genètics i immunològics que confereixen una susceptibilitat a l'hoste, i factors externs o ambientals, com serien els microorganismes i/o l'estil de vida. L'objectiu principal d'aquest treball ha estat descriure les poblacions bacterianes associades especialment als malalts de Crohn, amb la intenció d'identificar possibles agents etiològics. Els resultats d'aquest treball coincideixen amb investigacions prèvies que descriuen l'alteració bacteriana present en els malalts de Crohn (disbiosi) i recolzen la hipòtesi que implica el recentment descrit patovar "Adherent- Invasive Escherichia coli" (AIEC) en l'etiologia d'aquesta malaltia inflamatòria intestinal. A més, contribuïm a la descripció de les poblacions d'E. coli associades a la mucosa intestinal aportant dades sobre aspectes ecològics i patogènics. Finalment, descrivim nous aspectes fenotípics d'AIEC que podrien estar relacionats amb la seva patogènia, com seria la capacitat de formar biofilms.

Development of molecular monitoring methods and assessment of the environmental fate of the biological control agent of fire blight Pseudomonas fluorescens EPS62e

Pseudomonas fluorescens EPS62e es va seleccionar com a agent de biocontrol del foc bacterià per la seva eficàcia en el control de Erwinia amylovora. En aquest treball es van desenvolupar mètodes de traçabilitat que van permetre la seva detecció específica i quantificació. Mitjançant les tècniques RAPD i U-PCR es van obtenir fragments d'amplificació diferencial per EPS62e que es van seqüenciar i caracteritzar com marcadors SCAR per dissenyar una PCR en temps real. La PCR a temps real es va utilitzar simultàniament amb mètodes microbiològics per estudiar l'adaptabilitat epifítica de EPS62e en pomera i perera. L'ús combinat de mètodes microbiològics i moleculars va permetre la identificació de tres estats fisiològics de EPS62e: la colonització activa, l'entrada en un estat de viable però no cultivable, i la mort cel·lular. Aquest treball mostra que EPS62e està ben adaptada a la colonització de flors a camp, encoratjant la seva utilització dins d'una estratègia de control biològic contra el foc bacterià.

Studies of dynamics of physical agent ecosystems

This thesis addresses the problem of learning in physical heterogeneous multi-agent systems (MAS) and the analysis of the benefits of using heterogeneous MAS with respect to homogeneous ones. An algorithm is developed for this task; building on a previous work on stability in distributed systems by Tad Hogg and Bernardo Huberman, and combining two phenomena observed in natural systems, task partition and hierarchical dominance. This algorithm is devised for allowing agents to learn which are the best tasks to perform on the basis of each agent's skills and the contribution to the team global performance. Agents learn by interacting with the environment and other teammates, and get rewards from the result of the actions they perform. This algorithm is specially designed for problems where all robots have to co-operate and work simultaneously towards the same goal. One example of such a problem is role distribution in a team of heterogeneous robots that form a soccer team, where all members take decisions and co-operate simultaneously. Soccer offers the possibility of conducting research in MAS, where co-operation plays a very important role in a dynamical and changing environment. For these reasons and the experience of the University of Girona in this domain, soccer has been selected as the test-bed for this research. In the case of soccer, tasks are grouped by means of roles. One of the most interesting features of this algorithm is that it endows MAS with a high adaptability to changes in the environment. It allows the team to perform their tasks, while adapting to the environment. This is studied in several cases, for changes in the environment and in the robot's body. Other features are also analysed, especially a parameter that defines the fitness (biological concept) of each agent in the system, which contributes to performance and team adaptability. The algorithm is applied later to allow agents to learn in teams of homogeneous and heterogeneous robots which roles they have to select, in order to maximise team performance. The teams are compared and the performance is evaluated in the games against three hand-coded teams and against the different homogeneous and heterogeneous teams built in this thesis. This section focuses on the analysis of performance and task partition, in order to study the benefits of heterogeneity in physical MAS. In order to study heterogeneity from a rigorous point of view, a diversity measure is developed building on the hierarchic social entropy defined by Tucker Balch. This is adapted to quantify physical diversity in robot teams. This tool presents very interesting features, as it can be used in the future to design heterogeneous teams on the basis of the knowledge on other teams.