Environmental factors in multiple sclerosis [Environmental factors in multiple sclerosis]

Although multiple sclerosis (MS) is recognized as a disorder involving the immune system, the interplay of environmental factors and individual genetic susceptibility seems to influence MS onset and clinical expression, as well as therapeutic responsiveness. Multiple human epidemiological and animal model studies have evaluated the effect of different environmental factors, such as viral infections, vitamin intake, sun exposure, or still dietary and life habits on MS prevalence. Previous Epstein-Barr virus infection, especially if this infection occurs in late childhood, and lack of vitamin D (VitD) currently appear to be the most robust environmental factors for the risk of MS, at least from an epidemiological standpoint. Ultraviolet radiation (UVR) activates VitD production but there are also some elements supporting the fact that insufficient UVR exposure during childhood may represent a VitD-independent risk factor of MS development, as well as negative effect on the clinical and radiological course of MS. Recently, there has been a growing interest in the gut-brain axis, a bidirectional neuro-hormonal communication system between the intestinal microbiota and the central nervous system (CNS). Indeed, components of the intestinal microbiota may be pro-inflammatory, promote the migration of immune cells into the CNS, and thus be a key parameter for the development of autoimmune disorders such as MS. Interestingly most environmental factors seem to play a role during childhood. Thus, if childhood is the most fragile period to develop MS later in life, preventive measures should be applied early in life. For example, adopting a diet enriched in VitD, playing outdoor and avoiding passive smoking would be extremely simple measures of primary prevention for public health strategies. However, these hypotheses need to be confirmed by prospective evaluations, which are obviously difficult to conduct. In addition, it remains to be determined whether and how VitD supplementation in adult life would be useful in alleviating the course of MS, once this disease has already started. A better knowledge of the influence of various environmental stimuli on MS risk and course would certainly allow the development of add-on therapies or measures in parallel to the immunotherapies currently used in MS.

Environmental influence on the phenotype of ant workers revealed by common garden experiment

Many organism traits vary along environmental gradients. Common garden experiments provide powerful means to disentangle the role of intrinsic factors, such as genetic or maternal effects, from extrinsic environmental factors in shaping phenotypic variation. Here, we investigate body size and lipid content variation in workers of the socially polymorphic ant Formica selysi along several independent elevation gradients in Switzerland. We compare field-collected workers and workers sampled as eggs from the same colonies but reared in common laboratory conditions. Overall, field-collected workers from high elevation are larger than those from low elevation, but the trend varies substantially among valleys. The same pattern is recovered when the eggs are reared in a common garden, which indicates that body size variation along elevation gradients and valleys is partly explained by genetic or maternal effects. However, both body size and lipid content exhibit significantly greater variation in field-collected workers than in laboratory-reared workers. Hence, much of the phenotypic variation results from a plastic response to the environment, rather than from genetic differences. Eggs from different elevations also show no significant difference in development time in the common garden. Overall, selection on individual worker phenotypes is unlikely to drive the altitudinal distribution of single- and multiple-queen colonies in this system, as phenotypic variation tends to be plastic and can be decoupled from social structure. This study provides insights into the interplay between individual phenotypic variation and social organization and how the two jointly respond to differing environmental conditions.

The environmental effects of changing speed limits: a quantile regression approach

Two speed management policies were implemented in the metropolitan area of Barcelona aimed at reducing air pollution concentration levels. In 2008, the maximum speed limit was reduced to 80 km/h and, in 2009, a variable speed system was introduced on some metropolitan motorways. This paper evaluates whether such policies have been successful in promoting cleaner air, not only in terms of mean pollutant levels but also during high and low pollution episodes. We use a quantile regression approach for fixed effect panel data. We find that the variable speed system improves air quality with regard to the two pollutants considered here, being most effective when nitrogen oxide levels are not too low and when particulate matter concentrations are below extremely high levels. However, reducing the maximum speed limit from 120/100 km/h to 80 km/h has no effect – or even a slightly increasing effect –on the two pollutants, depending on the pollution scenario. Length: 32 pages

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.

Change points detection in crime-related time series: an on-line fuzzy approach based on a shape space representation

The extension of traditional data mining methods to time series has been effectively applied to a wide range of domains such as finance, econometrics, biology, security, and medicine. Many existing mining methods deal with the task of change points detection, but very few provide a flexible approach. Querying specific change points with linguistic variables is particularly useful in crime analysis, where intuitive, understandable, and appropriate detection of changes can significantly improve the allocation of resources for timely and concise operations. In this paper, we propose an on-line method for detecting and querying change points in crime-related time series with the use of a meaningful representation and a fuzzy inference system. Change points detection is based on a shape space representation, and linguistic terms describing geometric properties of the change points are used to express queries, offering the advantage of intuitiveness and flexibility. An empirical evaluation is first conducted on a crime data set to confirm the validity of the proposed method and then on a financial data set to test its general applicability. A comparison to a similar change-point detection algorithm and a sensitivity analysis are also conducted. Results show that the method is able to accurately detect change points at very low computational costs. More broadly, the detection of specific change points within time series of virtually any domain is made more intuitive and more understandable, even for experts not related to data mining.

Bio-inspired Mechanisms for Artificial Self-organised Systems

Self-organization is a growing interdisciplinary field of research about a phenomenon that can be observed in the Universe, in Nature and in social contexts. Research on self-organization tries to describe and explain forms, complex patterns and behaviours that arise from a collection of entities without an external organizer. As researchers in artificial systems, our aim is not to mimic self-organizing phenomena arising in Nature, but to understand and to control underlying mechanisms allowing desired emergence of forms, complex patterns and behaviours. Rather than attempting to eliminate such self-organization in artificial systems, we think that this might be deliberately harnessed in order to reach desirable global properties. In this paper we analyze three forms of self-organization: stigmergy, reinforcement mechanisms and cooperation. The amplification phenomena founded in stigmergic process or in reinforcement process are different forms of positive feedbacks that play a major role in building group activity or social organization. Cooperation is a functional form for self-organization because of its ability to guide local behaviours in order to obtain a relevant collective one. For each forms of self-organisation, we present a case study to show how we transposed it to some artificial systems and then analyse the strengths and weaknesses of such an approach

Assessment of Environmental Impacts of Power Generation

Through indisputable evidence of climate change and its link to the greenhouse gas emissions comes the necessity for change in energy production infrastructure during the coming decades. Through political conventions and restrictions energy industry is pushed toward using bigger share of renewable energy sources as energy supply. In addition to climate change, sustainable energy supply is another major issue for future development plans, but neither of these should come with unbearable price. All the power production types have environmental effects as well as strengths and weaknesses. Although each change comes with a price, right track in minimising the environmental impacts and energy supply security can be found by combining all possible low-carbon technologies and by improving energy efficiency in all sectors, for creating a new power production infrastructure of tolerable energy price and of minor environmental effects. GEMIS-Global Emission Model for Integrated Systems is a life-cycle analysis program which was used in this thesis to make indicative energy models for Finland’s future energy supply. Results indicate that the energy supply must comprise both high capacity nuclear power as well as large variation of renewable energy sources for minimization of all environmental effects and keeping energy price reasonable.

Developing the environmental marketing of an industrial company

The objective of this study was to examine how the customers of Larox Flowsys value environmental issues and how environmental issues affect their purchasing behaviour. A comparison between Larox peristaltic pumps and competing pump brands and types was also made in order to find out whether LPP pumps possess some more environmentally beneficial features that other pumps do not have. Finally, if the answers to the first two research questions show that a need for a new marketing message does exist, then the final stage is to select the most appropriate environmental arguments for Larox Flowsys. The empirical data in the study was collected from several different sources, but the main sources were the customer interviews and the outsourced market research. The data was analysed mainly by using content analysis, but theme formation and quantification were also utilized. The results showed that the customers do not consider environmental issues as a main purchasing criterion, but they may well be the criterion that differentiates the product from competing ones. The comparison proved that LPP pumps do possess some significant environmental benefits over competing pumps and therefore, the prerequisite for the use of environmental arguments exists. The final stage in the study was to select the proper environmental arguments for Larox Flowsys.

Capillary thermal desorption unit for near real-time analysis of VOCs at sub-trace levels. Application to the analysis of environmental air contamination and breath samples

A capillary microtrap thermal desorption module is developed for near real-time analysis of volatile organic compounds (VOCs) at sub-ppbv levels in air samples. The device allows the direct injection of the thermally desorbed VOCs into a chromatographic column. It does not use a second cryotrap to focalize the adsorbed compounds before entering the separation column so reducing the formation of artifacts. The connection of the microtrap to a GC–MS allows the quantitative determination of VOCs in less than 40 min with detection limits of between 5 and 10 pptv (25 °C and 760 mmHg), which correspond to 19–43 ng m−3, using sampling volumes of 775 cm3. The microtrap is applied to the analysis of environmental air contamination in different laboratories of our faculty. The results obtained indicate that most volatile compounds are easily diffused through the air and that they also may contaminate the surrounding areas when the habitual safety precautions (e.g., working under fume hoods) are used during the manipulation of solvents. The application of the microtrap to the analysis of VOCs in breath samples suggest that 2,5-dimethylfuran may be a strong indicator of a person's smoking status

The influence of genetic and environmental factors among MDMA users in cognitive performance

This study is aimed to clarify the association between MDMA cumulative use and cognitive dysfunction, and the potential role of candidate genetic polymorphisms in explaining individual differences in the cognitive effects of MDMA. Gene polymorphisms related to reduced serotonin function, poor competency of executive control and memory consolidation systems, and high enzymatic activity linked to bioactivation of MDMA to neurotoxic metabolites may contribute to explain variations in the cognitive impact of MDMA across regular users of this drug. Sixty ecstasy polydrug users, 110 cannabis users and 93 non-drug users were assessed using cognitive measures of Verbal Memory (California Verbal Learning Test, CVLT), Visual Memory (Rey-Osterrieth Complex Figure Test, ROCFT), Semantic Fluency, and Perceptual Attention (Symbol Digit Modalities Test, SDMT). Participants were also genotyped for polymorphisms within the 5HTT, 5HTR2A, COMT, CYP2D6, BDNF, and GRIN2B genes using polymerase chain reaction and TaqMan polymerase assays. Lifetime cumulative MDMA use was significantly associated with poorer performance on visuospatial memory and perceptual attention. Heavy MDMA users (>100 tablets lifetime use) interacted with candidate gene polymorphisms in explaining individual differences in cognitive performance between MDMA users and controls. MDMA users carrying COMT val/val and SERT s/s had poorer performance than paired controls on visuospatial attention and memory, and MDMA users with CYP2D6 ultra-rapid metabolizers performed worse than controls on semantic fluency. Both MDMA lifetime use and gene-related individual differences influence cognitive dysfunction in ecstasy users.

Riesgo de contaminar y tributos autómicos

El propósito del presente trabajo es el de ofrecer una puesta al día de la normativa vigente en lo relativo a aquellos impuestos autonómicos propios que inciden sobre las emisiones atmosféricas, las instalaciones que se califican como contaminantes y determinadas actividades consideradas de riesgo.