Cuticular defects lead to full immunity to a major plant pathogen.

In addition to its role as a barrier, the cuticle is also a source of signals perceived by invading fungi. Cuticular breakdown products have been shown previously to be potent inducers of cutinase or developmental processes in fungal pathogens. Here the question was addressed as to whether plants themselves can perceive modifications of the cuticle. This was studied using Arabidopsis thaliana plants with altered cuticular structure. The expression of a cell wall-targeted fungal cutinase in A. thaliana was found to provide total immunity to Botrytis cinerea. The response observed in such cutinase-expressing plants is independent of signal transduction pathways involving salicylic acid, ethylene or jasmonic acid. It is accompanied by the release of a fungitoxic activity and increased expression of members of the lipid transfer protein, peroxidase and protein inhibitor gene families that provide resistance when overexpressed in wild-type plants. The same experiments were made in the bodyguard (bdg) mutant of A. thaliana. This mutant exhibits cuticular defects and remained free of symptoms after inoculation with B. cinerea. The expression of resistance was accompanied by the release of a fungitoxic activity and increased expression of the same genes as observed in cutinase-expressing plants. Structural defects of the cuticle can thus be converted into an effective multi-factorial defence, and reveal a hitherto hidden aspect of the innate immune response of plants.

Glucose metabolism, gray matter structure, and memory decline in subjective memory impairment.

OBJECTIVE: To identify biological evidence for Alzheimer disease (AD) in individuals with subjective memory impairment (SMI) and unimpaired cognitive performance and to investigate the longitudinal cognitive course in these subjects. METHOD: [¹⁸F]fluoro-2-deoxyglucose PET (FDG-PET) and structural MRI were acquired in 31 subjects with SMI and 56 controls. Cognitive follow-up testing was performed (average follow-up time: 35 months). Differences in baseline brain imaging data and in memory decline were assessed between both groups. Associations of memory decline with brain imaging data were tested. RESULTS: The SMI group showed hypometabolism in the right precuneus and hypermetabolism in the right medial temporal lobe. Gray matter volume was reduced in the right hippocampus in the SMI group. At follow-up, subjects with SMI showed a poorer performance than controls on measures of episodic memory. Longitudinal memory decline in the SMI group was associated with reduced glucose metabolism in the right precuneus at baseline. CONCLUSION: The cross-sectional difference in 2 independent neuroimaging modalities indicates early AD pathology in SMI. The poorer memory performance at follow-up and the association of reduced longitudinal memory performance with hypometabolism in the precuneus at baseline support the concept of SMI as the earliest manifestation of AD.

Artificial evolution on network structures : how time and space influence dynamics

Abstract The main objective of this work is to show how the choice of the temporal dimension and of the spatial structure of the population influences an artificial evolutionary process. In the field of Artificial Evolution we can observe a common trend in synchronously evolv¬ing panmictic populations, i.e., populations in which any individual can be recombined with any other individual. Already in the '90s, the works of Spiessens and Manderick, Sarma and De Jong, and Gorges-Schleuter have pointed out that, if a population is struc¬tured according to a mono- or bi-dimensional regular lattice, the evolutionary process shows a different dynamic with respect to the panmictic case. In particular, Sarma and De Jong have studied the selection pressure (i.e., the diffusion of a best individual when the only selection operator is active) induced by a regular bi-dimensional structure of the population, proposing a logistic modeling of the selection pressure curves. This model supposes that the diffusion of a best individual in a population follows an exponential law. We show that such a model is inadequate to describe the process, since the growth speed must be quadratic or sub-quadratic in the case of a bi-dimensional regular lattice. New linear and sub-quadratic models are proposed for modeling the selection pressure curves in, respectively, mono- and bi-dimensional regu¬lar structures. These models are extended to describe the process when asynchronous evolutions are employed. Different dynamics of the populations imply different search strategies of the resulting algorithm, when the evolutionary process is used to solve optimisation problems. A benchmark of both discrete and continuous test problems is used to study the search characteristics of the different topologies and updates of the populations. In the last decade, the pioneering studies of Watts and Strogatz have shown that most real networks, both in the biological and sociological worlds as well as in man-made structures, have mathematical properties that set them apart from regular and random structures. In particular, they introduced the concepts of small-world graphs, and they showed that this new family of structures has interesting computing capabilities. Populations structured according to these new topologies are proposed, and their evolutionary dynamics are studied and modeled. We also propose asynchronous evolutions for these structures, and the resulting evolutionary behaviors are investigated. Many man-made networks have grown, and are still growing incrementally, and explanations have been proposed for their actual shape, such as Albert and Barabasi's preferential attachment growth rule. However, many actual networks seem to have undergone some kind of Darwinian variation and selection. Thus, how these networks might have come to be selected is an interesting yet unanswered question. In the last part of this work, we show how a simple evolutionary algorithm can enable the emrgence o these kinds of structures for two prototypical problems of the automata networks world, the majority classification and the synchronisation problems. Synopsis L'objectif principal de ce travail est de montrer l'influence du choix de la dimension temporelle et de la structure spatiale d'une population sur un processus évolutionnaire artificiel. Dans le domaine de l'Evolution Artificielle on peut observer une tendence à évoluer d'une façon synchrone des populations panmictiques, où chaque individu peut être récombiné avec tout autre individu dans la population. Déjà dans les année '90, Spiessens et Manderick, Sarma et De Jong, et Gorges-Schleuter ont observé que, si une population possède une structure régulière mono- ou bi-dimensionnelle, le processus évolutionnaire montre une dynamique différente de celle d'une population panmictique. En particulier, Sarma et De Jong ont étudié la pression de sélection (c-à-d la diffusion d'un individu optimal quand seul l'opérateur de sélection est actif) induite par une structure régulière bi-dimensionnelle de la population, proposant une modélisation logistique des courbes de pression de sélection. Ce modèle suppose que la diffusion d'un individu optimal suit une loi exponentielle. On montre que ce modèle est inadéquat pour décrire ce phénomène, étant donné que la vitesse de croissance doit obéir à une loi quadratique ou sous-quadratique dans le cas d'une structure régulière bi-dimensionnelle. De nouveaux modèles linéaires et sous-quadratique sont proposés pour des structures mono- et bi-dimensionnelles. Ces modèles sont étendus pour décrire des processus évolutionnaires asynchrones. Différentes dynamiques de la population impliquent strategies différentes de recherche de l'algorithme résultant lorsque le processus évolutionnaire est utilisé pour résoudre des problèmes d'optimisation. Un ensemble de problèmes discrets et continus est utilisé pour étudier les charactéristiques de recherche des différentes topologies et mises à jour des populations. Ces dernières années, les études de Watts et Strogatz ont montré que beaucoup de réseaux, aussi bien dans les mondes biologiques et sociologiques que dans les structures produites par l'homme, ont des propriétés mathématiques qui les séparent à la fois des structures régulières et des structures aléatoires. En particulier, ils ont introduit la notion de graphe sm,all-world et ont montré que cette nouvelle famille de structures possède des intéressantes propriétés dynamiques. Des populations ayant ces nouvelles topologies sont proposés, et leurs dynamiques évolutionnaires sont étudiées et modélisées. Pour des populations ayant ces structures, des méthodes d'évolution asynchrone sont proposées, et la dynamique résultante est étudiée. Beaucoup de réseaux produits par l'homme se sont formés d'une façon incrémentale, et des explications pour leur forme actuelle ont été proposées, comme le preferential attachment de Albert et Barabàsi. Toutefois, beaucoup de réseaux existants doivent être le produit d'un processus de variation et sélection darwiniennes. Ainsi, la façon dont ces structures ont pu être sélectionnées est une question intéressante restée sans réponse. Dans la dernière partie de ce travail, on montre comment un simple processus évolutif artificiel permet à ce type de topologies d'émerger dans le cas de deux problèmes prototypiques des réseaux d'automates, les tâches de densité et de synchronisation.

Does evolution lead to maximizing behavior?

A long-standing question in biology and economics is whether individual organisms evolve to behave as if they were striving to maximize some goal function. We here formalize this "as if" question in a patch-structured population in which individuals obtain material payoffs from (perhaps very complex multimove) social interactions. These material payoffs determine personal fitness and, ultimately, invasion fitness. We ask whether individuals in uninvadable population states will appear to be maximizing conventional goal functions (with population-structure coefficients exogenous to the individual's behavior), when what is really being maximized is invasion fitness at the genetic level. We reach two broad conclusions. First, no simple and general individual-centered goal function emerges from the analysis. This stems from the fact that invasion fitness is a gene-centered multigenerational measure of evolutionary success. Second, when selection is weak, all multigenerational effects of selection can be summarized in a neutral type-distribution quantifying identity-by-descent between individuals within patches. Individuals then behave as if they were striving to maximize a weighted sum of material payoffs (own and others). At an uninvadable state it is as if individuals would freely choose their actions and play a Nash equilibrium of a game with a goal function that combines self-interest (own material payoff), group interest (group material payoff if everyone does the same), and local rivalry (material payoff differences).

Improving the molecular diagnosis of Chlamydia psittaci and Chlamydia abortus infection with a species-specific duplex real-time PCR.

Chlamydia psittaci and Chlamydia abortus are closely related intracellular bacteria exhibiting different tissue tropism that may cause severe but distinct infection in humans. C. psittaci causes psittacosis, a respiratory zoonotic infection transmitted by birds. C. abortus is an abortigenic agent in small ruminants, which can also colonize the human placenta and lead to foetal death and miscarriage. Infections caused by C. psittaci and C. abortus are underestimated mainly due to diagnosis difficulties resulting from their strict intracellular growth. We developed a duplex real-time PCR to detect and distinguish these two bacteria in clinical samples. The first PCR (PCR1) targeted a sequence of the 16S-23S rRNA operon allowing the detection of both C. psittaci and C. abortus. The second PCR (PCR2) targeted the coding DNA sequence CPSIT_0607 unique to C. psittaci. The two PCRs showed 100 % detection for ≥ 10 DNA copies per reaction (1000 copies ml- 1). Using a set of 120 samples, including bacterial reference strains, clinical specimens and infected cell culture material, we monitored 100 % sensitivity and 100 % specificity for the detection of C. psittaci and C. abortus for PCR1. When PCR1 was positive, PCR2 could discriminate C. psittaci from C. abortus with a positive predictive value of 100 % and a negative predictive value of 88 %. In conclusion, this new duplex PCR represents a low-cost and time-saving method with high-throughput potential, expected to improve the routine diagnosis of psittacosis and pregnancy complication in large-scale screening programs and also during outbreaks.

Analysis of space-time environmental data in complex regions

This thesis develops a comprehensive and a flexible statistical framework for the analysis and detection of space, time and space-time clusters of environmental point data. The developed clustering methods were applied in both simulated datasets and real-world environmental phenomena; however, only the cases of forest fires in Canton of Ticino (Switzerland) and in Portugal are expounded in this document. Normally, environmental phenomena can be modelled as stochastic point processes where each event, e.g. the forest fire ignition point, is characterised by its spatial location and occurrence in time. Additionally, information such as burned area, ignition causes, landuse, topographic, climatic and meteorological features, etc., can also be used to characterise the studied phenomenon. Thereby, the space-time pattern characterisa- tion represents a powerful tool to understand the distribution and behaviour of the events and their correlation with underlying processes, for instance, socio-economic, environmental and meteorological factors. Consequently, we propose a methodology based on the adaptation and application of statistical and fractal point process measures for both global (e.g. the Morisita Index, the Box-counting fractal method, the multifractal formalism and the Ripley's K-function) and local (e.g. Scan Statistics) analysis. Many measures describing the space-time distribution of environmental phenomena have been proposed in a wide variety of disciplines; nevertheless, most of these measures are of global character and do not consider complex spatial constraints, high variability and multivariate nature of the events. Therefore, we proposed an statistical framework that takes into account the complexities of the geographical space, where phenomena take place, by introducing the Validity Domain concept and carrying out clustering analyses in data with different constrained geographical spaces, hence, assessing the relative degree of clustering of the real distribution. Moreover, exclusively to the forest fire case, this research proposes two new methodologies to defining and mapping both the Wildland-Urban Interface (WUI) described as the interaction zone between burnable vegetation and anthropogenic infrastructures, and the prediction of fire ignition susceptibility. In this regard, the main objective of this Thesis was to carry out a basic statistical/- geospatial research with a strong application part to analyse and to describe complex phenomena as well as to overcome unsolved methodological problems in the characterisation of space-time patterns, in particular, the forest fire occurrences. Thus, this Thesis provides a response to the increasing demand for both environmental monitoring and management tools for the assessment of natural and anthropogenic hazards and risks, sustainable development, retrospective success analysis, etc. The major contributions of this work were presented at national and international conferences and published in 5 scientific journals. National and international collaborations were also established and successfully accomplished. -- Cette thèse développe une méthodologie statistique complète et flexible pour l'analyse et la détection des structures spatiales, temporelles et spatio-temporelles de données environnementales représentées comme de semis de points. Les méthodes ici développées ont été appliquées aux jeux de données simulées autant qu'A des phénomènes environnementaux réels; nonobstant, seulement le cas des feux forestiers dans le Canton du Tessin (la Suisse) et celui de Portugal sont expliqués dans ce document. Normalement, les phénomènes environnementaux peuvent être modélisés comme des processus ponctuels stochastiques ou chaque événement, par ex. les point d'ignition des feux forestiers, est déterminé par son emplacement spatial et son occurrence dans le temps. De plus, des informations tels que la surface bru^lée, les causes d'ignition, l'utilisation du sol, les caractéristiques topographiques, climatiques et météorologiques, etc., peuvent aussi être utilisées pour caractériser le phénomène étudié. Par conséquent, la définition de la structure spatio-temporelle représente un outil puissant pour compren- dre la distribution du phénomène et sa corrélation avec des processus sous-jacents tels que les facteurs socio-économiques, environnementaux et météorologiques. De ce fait, nous proposons une méthodologie basée sur l'adaptation et l'application de mesures statistiques et fractales des processus ponctuels d'analyse global (par ex. l'indice de Morisita, la dimension fractale par comptage de boîtes, le formalisme multifractal et la fonction K de Ripley) et local (par ex. la statistique de scan). Des nombreuses mesures décrivant les structures spatio-temporelles de phénomènes environnementaux peuvent être trouvées dans la littérature. Néanmoins, la plupart de ces mesures sont de caractère global et ne considèrent pas de contraintes spatiales com- plexes, ainsi que la haute variabilité et la nature multivariée des événements. A cet effet, la méthodologie ici proposée prend en compte les complexités de l'espace géographique ou le phénomène a lieu, à travers de l'introduction du concept de Domaine de Validité et l'application des mesures d'analyse spatiale dans des données en présentant différentes contraintes géographiques. Cela permet l'évaluation du degré relatif d'agrégation spatiale/temporelle des structures du phénomène observé. En plus, exclusif au cas de feux forestiers, cette recherche propose aussi deux nouvelles méthodologies pour la définition et la cartographie des zones périurbaines, décrites comme des espaces anthropogéniques à proximité de la végétation sauvage ou de la forêt, et de la prédiction de la susceptibilité à l'ignition de feu. A cet égard, l'objectif principal de cette Thèse a été d'effectuer une recherche statistique/géospatiale avec une forte application dans des cas réels, pour analyser et décrire des phénomènes environnementaux complexes aussi bien que surmonter des problèmes méthodologiques non résolus relatifs à la caractérisation des structures spatio-temporelles, particulièrement, celles des occurrences de feux forestières. Ainsi, cette Thèse fournit une réponse à la demande croissante de la gestion et du monitoring environnemental pour le déploiement d'outils d'évaluation des risques et des dangers naturels et anthro- pogéniques. Les majeures contributions de ce travail ont été présentées aux conférences nationales et internationales, et ont été aussi publiées dans 5 revues internationales avec comité de lecture. Des collaborations nationales et internationales ont été aussi établies et accomplies avec succès.

Chemical profiling: a tool to decipher the structure and organisation of illicit drugs markets: an 8-year study in Western Switzerland

Illicit drug analyses usually focus on the identification and quantitation of questioned material to support the judicial process. In parallel, more and more laboratories develop physical and chemical profiling methods in a forensic intelligence perspective. The analysis of large databases resulting from this approach enables not only to draw tactical and operational intelligence, but may also contribute to the strategic overview of drugs markets. In Western Switzerland, the chemical analysis of illicit drug seizures is centralised in a laboratory hosted by the University of Lausanne. For over 8 years, this laboratory has analysed 5875 cocaine and 2728 heroin specimens, coming from respectively 1138 and 614 seizures operated by police and border guards or customs. Chemical (major and minor alkaloids, purity, cutting agents, chemical class), physical (packaging and appearance) as well as circumstantial (criminal case number, mass of drug seized, date and place of seizure) information are collated in a dedicated database for each specimen. The study capitalises on this extended database and defines several indicators to characterise the structure of drugs markets, to follow-up on their evolution and to compare cocaine and heroin markets. Relational, spatial, temporal and quantitative analyses of data reveal the emergence and importance of distribution networks. They enable to evaluate the cross-jurisdictional character of drug trafficking and the observation time of drug batches, as well as the quantity of drugs entering the market every year. Results highlight the stable nature of drugs markets over the years despite the very dynamic flows of distribution and consumption. This research work illustrates how the systematic analysis of forensic data may elicit knowledge on criminal activities at a strategic level. In combination with information from other sources, such knowledge can help to devise intelligence-based preventive and repressive measures and to discuss the impact of countermeasures.