Towards high-quality simultaneous EEG-fMRI at 7T: Detection and reduction of EEG artifacts due to head motion.

The enhanced functional sensitivity offered by ultra-high field imaging may significantly benefit simultaneous EEG-fMRI studies, but the concurrent increases in artifact contamination can strongly compromise EEG data quality. In the present study, we focus on EEG artifacts created by head motion in the static B0 field. A novel approach for motion artifact detection is proposed, based on a simple modification of a commercial EEG cap, in which four electrodes are non-permanently adapted to record only magnetic induction effects. Simultaneous EEG-fMRI data were acquired with this setup, at 7T, from healthy volunteers undergoing a reversing-checkerboard visual stimulation paradigm. Data analysis assisted by the motion sensors revealed that, after gradient artifact correction, EEG signal variance was largely dominated by pulse artifacts (81-93%), but contributions from spontaneous motion (4-13%) were still comparable to or even larger than those of actual neuronal activity (3-9%). Multiple approaches were tested to determine the most effective procedure for denoising EEG data incorporating motion sensor information. Optimal results were obtained by applying an initial pulse artifact correction step (AAS-based), followed by motion artifact correction (based on the motion sensors) and ICA denoising. On average, motion artifact correction (after AAS) yielded a 61% reduction in signal power and a 62% increase in VEP trial-by-trial consistency. Combined with ICA, these improvements rose to a 74% power reduction and an 86% increase in trial consistency. Overall, the improvements achieved were well appreciable at single-subject and single-trial levels, and set an encouraging quality mark for simultaneous EEG-fMRI at ultra-high field.

Obese, smoker, and obese smoker : is there a general lifestyle gradient?

Aim: Obesity and smoking are major CVD risk factors and may be associated with other unfavourable lifestyle behaviours. Our aim was to investigate the significance of obesity, heavy smoking, and both combined in terms of prevalence trends and their relationship with other lifestyle factors. Methods: We used data from the population-based cross-sectional Swiss Health Survey (5 waves, 1992-2012) comprising 85,575 individuals aged 18 years. Height, weight, and smoking status were self-reported. We used multinomial logistic regression to analyse differences in lifestyle for the combinations of BMI category and smoking status, focusing on obese and heavy smokers. We defined normal-weight never smokers as reference.

Assessing the use of very high resolution data to predict species distribution in a mountain environment

Nowadays, Species Distribution Models (SDMs) are a widely used tool. Using different statistical approaches these models reconstruct the realized niche of a species using presence data and a set of variables, often topoclimatic. There utilization range is quite large from understanding single species requirements, to the creation of nature reserve based on species hotspots, or modeling of climate change impact, etc... Most of the time these models are using variables at a resolution of 50km x 50km or 1 km x 1 km. However in some cases these models are used with resolutions below the kilometer scale and thus called high resolution models (100 m x 100 m or 25 m x 25 m). Quite recently a new kind of data has emerged enabling precision up to lm x lm and thus allowing very high resolution modeling. However these new variables are very costly and need an important amount of time to be processed. This is especially the case when these variables are used in complex calculation like models projections over large areas. Moreover the importance of very high resolution data in SDMs has not been assessed yet and is not well understood. Some basic knowledge on what drive species presence-absences is still missing. Indeed, it is not clear whether in mountain areas like the Alps coarse topoclimatic gradients are driving species distributions or if fine scale temperature or topography are more important or if their importance can be neglected when balance to competition or stochasticity. In this thesis I investigated the importance of very high resolution data (2-5m) in species distribution models using either very high resolution topographic, climatic or edaphic variables over a 2000m elevation gradient in the Western Swiss Alps. I also investigated more local responses of these variables for a subset of species living in this area at two precise elvation belts. During this thesis I showed that high resolution data necessitates very good datasets (species and variables for the models) to produce satisfactory results. Indeed, in mountain areas, temperature is the most important factor driving species distribution and needs to be modeled at very fine resolution instead of being interpolated over large surface to produce satisfactory results. Despite the instinctive idea that topographic should be very important at high resolution, results are mitigated. However looking at the importance of variables over a large gradient buffers the importance of the variables. Indeed topographic factors have been shown to be highly important at the subalpine level but their importance decrease at lower elevations. Wether at the mountane level edaphic and land use factors are more important high resolution topographic data is more imporatant at the subalpine level. Finally the biggest improvement in the models happens when edaphic variables are added. Indeed, adding soil variables is of high importance and variables like pH are overpassing the usual topographic variables in SDMs in term of importance in the models. To conclude high resolution is very important in modeling but necessitate very good datasets. Only increasing the resolution of the usual topoclimatic predictors is not sufficient and the use of edaphic predictors has been highlighted as fundamental to produce significantly better models. This is of primary importance, especially if these models are used to reconstruct communities or as basis for biodiversity assessments. -- Ces dernières années, l'utilisation des modèles de distribution d'espèces (SDMs) a continuellement augmenté. Ces modèles utilisent différents outils statistiques afin de reconstruire la niche réalisée d'une espèce à l'aide de variables, notamment climatiques ou topographiques, et de données de présence récoltées sur le terrain. Leur utilisation couvre de nombreux domaines allant de l'étude de l'écologie d'une espèce à la reconstruction de communautés ou à l'impact du réchauffement climatique. La plupart du temps, ces modèles utilisent des occur-rences issues des bases de données mondiales à une résolution plutôt large (1 km ou même 50 km). Certaines bases de données permettent cependant de travailler à haute résolution, par conséquent de descendre en dessous de l'échelle du kilomètre et de travailler avec des résolutions de 100 m x 100 m ou de 25 m x 25 m. Récemment, une nouvelle génération de données à très haute résolution est apparue et permet de travailler à l'échelle du mètre. Les variables qui peuvent être générées sur la base de ces nouvelles données sont cependant très coûteuses et nécessitent un temps conséquent quant à leur traitement. En effet, tout calcul statistique complexe, comme des projections de distribution d'espèces sur de larges surfaces, demande des calculateurs puissants et beaucoup de temps. De plus, les facteurs régissant la distribution des espèces à fine échelle sont encore mal connus et l'importance de variables à haute résolution comme la microtopographie ou la température dans les modèles n'est pas certaine. D'autres facteurs comme la compétition ou la stochasticité naturelle pourraient avoir une influence toute aussi forte. C'est dans ce contexte que se situe mon travail de thèse. J'ai cherché à comprendre l'importance de la haute résolution dans les modèles de distribution d'espèces, que ce soit pour la température, la microtopographie ou les variables édaphiques le long d'un important gradient d'altitude dans les Préalpes vaudoises. J'ai également cherché à comprendre l'impact local de certaines variables potentiellement négligées en raison d'effets confondants le long du gradient altitudinal. Durant cette thèse, j'ai pu monter que les variables à haute résolution, qu'elles soient liées à la température ou à la microtopographie, ne permettent qu'une amélioration substantielle des modèles. Afin de distinguer une amélioration conséquente, il est nécessaire de travailler avec des jeux de données plus importants, tant au niveau des espèces que des variables utilisées. Par exemple, les couches climatiques habituellement interpolées doivent être remplacées par des couches de température modélisées à haute résolution sur la base de données de terrain. Le fait de travailler le long d'un gradient de température de 2000m rend naturellement la température très importante au niveau des modèles. L'importance de la microtopographie est négligeable par rapport à la topographie à une résolution de 25m. Cependant, lorsque l'on regarde à une échelle plus locale, la haute résolution est une variable extrêmement importante dans le milieu subalpin. À l'étage montagnard par contre, les variables liées aux sols et à l'utilisation du sol sont très importantes. Finalement, les modèles de distribution d'espèces ont été particulièrement améliorés par l'addition de variables édaphiques, principalement le pH, dont l'importance supplante ou égale les variables topographique lors de leur ajout aux modèles de distribution d'espèces habituels.

Impact of T cell receptor affinity on the molecular mechanisms modulating CD8 T cell signalling and function against NY-ESO-1 tumour antigen

It is well established that cytotoxic T lymphocytes play a pivotal role in the protection against intracellular pathogens and tumour cells. Such protective immune responses rely on the specific T cell receptor (TCR)-mediated recognition by CD8 T cells of small antigenic peptides presented in the context of class-I Major Histocompatibility Complex molecules (pMHCs) on the surface of infected or malignant cells. The strength (affinity/avidity) of this interaction is a major correlate of protection. Although tumour-reactive CD8 T cells can be observed in cancer patients, anti-tumour immune responses are often ineffective in controlling or eradicating the disease due to the relative low TCR affinity of these cells. To overcome this limitation, tumour-specific CD8 T cells can be genetically modified to express TCRs of improved binding strength against a defined tumour antigen before adoptive cell transfer into cancer patients. We previously generated a panel of TCRs specific for the cancer-testis antigen NY-ESO-l,57.165 with progressively increased affinities for the pMHC complex, thus providing us with a unique tool to investigate the causal link between the surface expression of such TCRs and T cell activation and function. We recently demonstrated that anti-tumour CD8 T cell reactivity could only be improved within physiological affinity limits, beyond which drastic functional declines were observed, suggesting the presence of multiple regulatory mechanisms limiting T cell activation and function in a TCR affinity-dependent manner. The overarching goal of this thesis was (i) to assess the precise impact of TCR affinity on T cell activation and signalling at the molecular level and (ii) to gain further insights on the mechanisms that regulate and delimitate maximal/optimized CD8 T cell activation and signalling. Specifically, by combining several technical approaches we characterized the activation status of proximal (i.e. CD3Ç, Lek, and ZAP-70) and distal (i.e. ERK1/2) signalling molecules along the TCR affinity gradient. Moreover, we assessed the extent of TCR downmodulation, a critical step for initial T cell activation. CD8 T cells engineered with the optimal TCR affinity variants showed increased activation levels of both proximal and distal signalling molecules when compared to the wild-type T cells. Our analyses also highlighted the "paradoxical" status of tumour-reactive CD8 T cells bearing very high TCR affinities, which retained strong proximal signalling capacity and TCR downmodulation, but were unable to propagate signalling distally (i.e. pERKl/2), resulting in impaired cell-mediated functions. Importantly, these very high affinity T cells displayed maximal levels of SHP-1 and SHP-2 phosphatases, two negative regulatory molecules, and this correlated with a partial pERKl/2 signalling recovery upon pharmacological SHP-l/SHP-2 inhibition. These findings revealed the putative presence of inhibitory regulators of the TCR signalling cascade acting very rapidly following tumour-specific stimulation. Moreover, the very high affinity T cells were only able to transiently express enhanced proximal signalling molecules, suggesting the presence of an additional level of regulation that operates through the activation of negative feedback loops over time, limiting the duration of the TCR-mediated signalling. Overall, the determination of TCR-pMHC binding parameters eliciting optimal CD8 T cell activation, signalling, and effector function while guaranteeing high antigen specificity, together with the identification of critical regulatory mechanisms acting proximally in the TCR signalling cascade, will directly contribute to optimize and support the development of future TCR-based adoptive T cell strategies for the treatment of malignant diseases. -- Les lymphocytes T CD8 cytotoxiques jouent un rôle prédominant dans la protection contre les pathogènes intracellulaires et les cellules tumorales. Ces réponses immunitaires dépendent de la spécificité avec laquelle les récepteurs T (TCR) des lymphocytes CD8 reconnaissent les peptides antigéniques présentés par les molécules du complexe Majeur de Histocompatibilité de classe I (pCMH) à la surface des cellules infectées ou malignes. La force (ou affinité/avidité) de l'interaction du TCR-pCMH est un corrélat majeur de protection. Les réponses immunitaires sont cependant souvent inefficaces et ne permettent pas de contrôler ou d'éliminer les cellules tumorales chez les patients atteint du cancer, et ce à cause de la relative faible reconnaissance des TCRs exprimés par les lymphocytes T CD8 envers les antigènes tumoraux. Afin de surmonter cette limitation, les cellules T anti-tumorales peuvent être génétiquement modifiées en les dotant de TCRs préalablement optimisés afin d'augmenter leur reconnaissance ou affinité contre les antigènes tumoraux, avant leur ré¬infusion dans le patient. Nous avons récemment généré des cellules T CD8 exprimant un panel de TCRs spécifiques pour l'antigène tumoral NY-ESO-l157.16J avec des affinités croissantes, permettant ainsi d'investiguer la causalité directe entre l'affinité du TCR-pCMH et la fonction des cellules T CD8. Nous avons démontré que la réactivité anti-tumorale pouvait être améliorée en augmentant l'affinité du TCR dans une intervalle physiologique, mais au delà duquel nous observons un important déclin fonctionnel. Ces résultats suggèrent la présence de mécanismes de régulation limitant l'activation des cellules T de manière dépendante de l'affinité du TCR. Le but de cette thèse a été (i) de définir l'impact précis de l'affinité du TCR sur l'activation et la signalisation des cellules T CD8 au niveau moléculaire et (ii) d'acquérir de nouvelles connaissances sur les mécanismes qui régulent et délimitent l'activation et la signalisation maximale des cellules T CD8 optimisées. Spécifiquement, en combinant plusieurs approches technologiques, nous avons caractérisé l'état d'activation de différentes protéines de la voie de signalisation proximale (CD3Ç, Lek et ZAP-70) et distale (ERK1/2) le long du gradient d'affinité du TCR, ainsi que l'internalisation du TCR, une étape clef dans l'activation initiale des cellules T. Les lymphocytes T CD8 exprimant des TCRs d'affinité optimale ont montré des niveaux d'activation augmentés des molécules proximales et distales par rapport aux cellules de type sauvage (wild-type). Nos analyses ont également mis en évidence un paradoxe chez les cellules T CD8 équipées avec des TCRs de très haute affinité. En effet, ces cellules anti-tumorales sont capables d'activer leurs circuits biochimiques au niveau proximal et d'internaliser efficacement leur TCR, mais ne parviennent pas à propager les signaux biochimiques dépendants du TCR jusqu'au niveau distal (via phospho-ERKl/2), avec pour conséquence une limitation de leur capacité fonctionnelle. Finalement, nous avons démontré que SHP-1 et SHP-2, deux phosphatases avec des propriétés régulatrices négatives, étaient majoritairement exprimées dans les cellules T CD8 de très hautes affinités. Une récupération partielle des niveaux d'activation de ERK1/2 a pu être observée après l'inhibition pharmacologique de ces phosphatases. Ces découvertes révèlent la présence de régulateurs moléculaires qui inhibent le complexe de signalisation du TCR très rapidement après la stimulation anti-tumorale. De plus, les cellules T de très hautes affinités ne sont capables d'activer les molécules de la cascade de signalisation proximale que de manière transitoire, suggérant ainsi un second niveau de régulation via l'activation de mécanismes de rétroaction prenant place progressivement au cours du temps et limitant la durée de la signalisation dépendante du TCR. En résumé, la détermination des paramètres impliqués dans l'interaction du TCR-pCMH permettant l'activation de voies de signalisation et des fonctions effectrices optimales ainsi que l'identification des mécanismes de régulation au niveau proximal de la cascade de signalisation du TCR contribuent directement à l'optimisation et au développement de stratégies anti-tumorales basées sur l'ingénierie des TCRs pour le traitement des maladies malignes.

Novel Approaches for Fungal Transcriptomics from Host Samples.

Candida albicans adaptation to the host requires a profound reprogramming of the fungal transcriptome as compared to in vitro laboratory conditions. A detailed knowledge of the C. albicans transcriptome during the infection process is necessary in order to understand which of the fungal genes are important for host adaptation. Such genes could be thought of as potential targets for antifungal therapy. The acquisition of the C. albicans transcriptome is, however, technically challenging due to the low proportion of fungal RNA in host tissues. Two emerging technologies were used recently to circumvent this problem. One consists of the detection of low abundance fungal RNA using capture and reporter gene probes which is followed by emission and quantification of resulting fluorescent signals (nanoString). The other is based first on the capture of fungal RNA by short biotinylated oligonucleotide baits covering the C. albicans ORFome permitting fungal RNA purification. Next, the enriched fungal RNA is amplified and subjected to RNA sequencing (RNA-seq). Here we detail these two transcriptome approaches and discuss their advantages and limitations and future perspectives in microbial transcriptomics from host material.

Personalized approaches to active immunotherapy in cancer

Immunotherapy is emerging as a promising anti-cancer curative modality. However, in contrast to recent advances obtained employing checkpoint blockade agents and T cell therapies, clinical efficacy of therapeutic cancer vaccines is still limited. Most vaccination attempts in the clinic represent "off-the shelf" approaches since they target common "self" tumor antigens, shared among different patients. In contrast, personalized approaches of vaccination are tailor-made for each patient and in spite being laborious, hold great potential. Recent technical advancement enabled the first steps in the clinic of personalized vaccines that target patient-specific mutated neo-antigens. Such vaccines could induce enhanced tumor-specific immune response since neo-antigens are mutation-derived antigens that can be recognized by high affinity T cells, not limited by central tolerance. Alternatively, the use of personalized vaccines based on whole autologous tumor cells, overcome the need for the identification of specific tumor antigens. Whole autologous tumor cells could be administered alone, pulsed on dendritic cells as lysate, DNA, RNA or delivered to dendritic cells in-vivo through encapsulation in nanoparticle vehicles. Such vaccines may provide a source for the full repertoire of the patient-specific tumor antigens, including its private neo-antigens. Furthermore, combining next-generation personalized vaccination with other immunotherapy modalities might be the key for achieving significant therapeutic outcome.

From Regional Landslide Detection to Site-Specific Slope Deformation Monitoring and Modelling Based on Active Remote Sensors

Landslide processes can have direct and indirect consequences affecting human lives and activities. In order to improve landslide risk management procedures, this PhD thesis aims to investigate capabilities of active LiDAR and RaDAR sensors for landslides detection and characterization at regional scales, spatial risk assessment over large areas and slope instabilities monitoring and modelling at site-specific scales. At regional scales, we first demonstrated recent boat-based mobile LiDAR capabilities to model topography of the Normand coastal cliffs. By comparing annual acquisitions, we validated as well our approach to detect surface changes and thus map rock collapses, landslides and toe erosions affecting the shoreline at a county scale. Then, we applied a spaceborne InSAR approach to detect large slope instabilities in Argentina. Based on both phase and amplitude RaDAR signals, we extracted decisive information to detect, characterize and monitor two unknown extremely slow landslides, and to quantify water level variations of an involved close dam reservoir. Finally, advanced investigations on fragmental rockfall risk assessment were conducted along roads of the Val de Bagnes, by improving approaches of the Slope Angle Distribution and the FlowR software. Therefore, both rock-mass-failure susceptibilities and relative frequencies of block propagations were assessed and rockfall hazard and risk maps could be established at the valley scale. At slope-specific scales, in the Swiss Alps, we first integrated ground-based InSAR and terrestrial LiDAR acquisitions to map, monitor and model the Perraire rock slope deformation. By interpreting both methods individually and originally integrated as well, we therefore delimited the rockslide borders, computed volumes and highlighted non-uniform translational displacements along a wedge failure surface. Finally, we studied specific requirements and practical issues experimented on early warning systems of some of the most studied landslides worldwide. As a result, we highlighted valuable key recommendations to design new reliable systems; in addition, we also underlined conceptual issues that must be solved to improve current procedures. To sum up, the diversity of experimented situations brought an extensive experience that revealed the potential and limitations of both methods and highlighted as well the necessity of their complementary and integrated uses.

Estimating extreme value cumulative distribution functions using bias-corrected kernel approaches

We propose a new kernel estimation of the cumulative distribution function based on transformation and on bias reducing techniques. We derive the optimal bandwidth that minimises the asymptotic integrated mean squared error. The simulation results show that our proposed kernel estimation improves alternative approaches when the variable has an extreme value distribution with heavy tail and the sample size is small.

Convergent Approaches for the Synthesis of the Anti-tumoral Peptide, Kahalalide F. Study of Orthogonal Protecting Groups

Kahalalide compounds are peptides that are isolated from a Hawaiian herbivorous marine species of mollusc, Elysia rufescens, and its diet, the green alga Bryopsis sp. Kahalalide F and its synthetic analogues are the most promising compounds of the Kahalalide family because they show anti-tumoral activity. Linear solid-phase syntheses of Kahalalide F have been reported. Here we describe several new improved synthetic routes based on convergent approaches with distinct orthogonal protection schemes for the preparation of Kahaladide analogues. These strategies allow a better control and characterization of the intermediates because more reactions are performed in solution. Five derivatives of Kahalalide F were synthesized using several convergent approaches.

Role of human hydroxysteroid (17beta) dehydrogenase type 1 (HSD17B1) in steroid-dependent diseases in females –novel indications for HSD17B1 inhibitors. Phenotypic analysis of transgenic mice overexpressing human HSD17B1.

Hormone-dependent diseases, e.g. cancers, rank high in mortality in the modern world, and thus, there is an urgent need for new drugs to treat these diseases. Although the diseases are clearly hormone-dependent, changes in circulating hormone concentrations do not explain all the pathological processes observed in the diseased tissues. A more inclusive explanation is provided by intracrinology – a regulation of hormone concentrations at the target tissue level. This is mediated by the expression of a pattern of steroid-activating and -inactivating enzymes in steroid target tissues, thus enabling a concentration gradient between the blood circulation and the tissue. Hydroxysteroid (17beta) dehydrogenases (HSD17Bs) form a family of enzymes that catalyze the conversion between low active 17-ketosteroids and highly active 17beta-hydroxysteroids. HSD17B1 converts low active estrogen (E1) to highly active estradiol (E2) with high catalytic efficiency, and altered HSD17B1 expression has been associated with several hormone-dependent diseases, including breast cancer, endometriosis, endometrial hyperplasia and cancer, and ovarian epithelial cancer. Because of its putative role in E2 biosynthesis in ovaries and peripheral target tissues, HSD17B1 is considered to be a promising drug target for estrogen-dependent diseases. A few studies have indicated that the enzyme also has androgenic activity, but they have been ignored. In the present study, transgenic mice overexpressing human HSD17B1 (HSD17B1TG mice) were used to study the effects of the enzyme in vivo. Firstly, the substrate specificity of human HSD17B1 was determined in vivo. The results indicated that human HSD17B1 has significant androgenic activity in female mice in vivo, which resulted in increased fetal testosterone concentration and female disorder of sexual development appearing as masculinized phenotype (increased anogenital distance, lack of nipples, lack of vaginal opening, combination of vagina with urethra, enlarged Wolffian duct remnants in the mesovarium and enlarged female prostate). Fetal androgen exposure has been linked to polycystic ovary syndrome (PCOS) and metabolic syndrome during adulthood in experimental animals and humans, but the genes involved in PCOS are largely unknown. A putative mechanism to accumulate androgens during fetal life by HSD17B1 overexpression was shown in the present study. Furthermore, as a result of prenatal androgen exposure locally in the ovaries, HSD17B1TG females developed ovarian benign serous cystadenomas in adulthood. These benign lesions are precursors of low-grade ovarian serous tumors. Ovarian cancer ranks fifth in mortality of all female cancers in Finland, and most of the ovarian cancers arise from the surface epithelium. The formation of the lesions was prevented by prenatal antiandrogen treatment and by transplanting wild type (WT) ovaries prepubertally into HSD17B1TG females. The results obtained in our non-clinical TG mouse model, together with a literature analysis, suggest that HSD17B1 has a role in ovarian epithelial carcinogenesis, and especially in the development of serous tumors. The role of androgens in ovarian carcinogenesis is considered controversial, but the present study provides further evidence for the androgen hypothesis. Moreover, it directly links HSD17B1-induced prenatal androgen exposure to ovarian epithelial carcinogenesis in mice. As expected, significant estrogenic activity was also detected for human HSD17B1. HSD17B1TG mice had enhanced peripheral conversion of E1 to E2 in a variety of target tissues, including the uterus. Furthermore, this activity was significantly decreased by treatments with specific HSD17B1 inhibitors. As a result, several estrogen-dependent disorders were found in HSD17B1TG females. Here we report that HSD17B1TG mice invariably developed endometrial hyperplasia and failed to ovulate in adulthood. As in humans, endometrial hyperplasia in HSD17B1TG females was reversible upon ovulation induction, triggering a rise in circulating progesterone levels, and in response to exogenous progestins. Remarkably, treatment with a HSD17B1 inhibitor failed to restore ovulation, yet completely reversed the hyperplastic morphology of epithelial cells in the glandular compartment. We also demonstrate that HSD17B1 is expressed in normal human endometrium, hyperplasia, and cancer. Collectively, our non-clinical data and literature analysis suggest that HSD17B1 inhibition could be one of several possible approaches to decrease endometrial estrogen production in endometrial hyperplasia and cancer. HSD17B1 expression has been found in bones of humans and rats. The non-clinical data in the present study suggest that human HSD17B1 is likely to have an important role in the regulation of bone formation, strength and length during reproductive years in female mice. Bone density in HSD17B1TG females was highly increased in femurs, but in lesser amounts also in tibias. Especially the tibia growth plate, but not other regions of bone, was susceptible to respond to HSD17B1 inhibition by increasing bone length, whereas the inhibitors did not affect bone density. Therefore, HSD17B1 inhibitors could be safer than aromatase inhibitors in regard to bone in the treatment of breast cancer and endometriosis. Furthermore, diseases related to improper growth, are a promising new indication for HSD17B1 inhibitors.

Design of an Event Based Messaging System

B2B document handling is moving from paper to electronic networks and electronic domain very rapidly. Moving, handling and transforming large electronic business documents requires a lot from the systems handling them. This paper explores new technologies such as SOA, event-driven systems and ESB and a scalable, event-driven enterprise service bus is created to demonstrate these new approaches to message handling. As an end result, we have a small but fully functional messaging system with several different components. This is the first larger Java-project done in-house, so on the side we developed our own set of best practices of Java development, setting up configurations, tools, code repositories and class naming and much more.

Lo que no es nuevo puede ser actual: hacia distintos puntos de mira de la didáctica del arte What is not new can be current - towards different approaches of the didactics of art

With this article we want to present a state of affairs of the didactics of art in our context, and at the same time we want todiscuss on its pluri- and interdisciplinary construction. We check the different disciplines that configure it and we analysethe paradigm of artistic education as a discipline (DBAE) and its passage to post-modernity. This example focuses thediscussion about the opportunity of adapting holistic educative models and the transition of the current educativeinnovation towards skill models

Developing a Comprehensive Model for Marketing Planning — Combining the Major Approaches

Mix marketing and relationships marketing are two major approaches that often form a basis for organizational marketing planning. The superiority of these approaches has been debated for long without any rational conclusion. Lately there have been studies indicating that both of the major approaches are many times used side by side in marketing planning. There have been also studies suggesting that even combining the mix marketing and relationship marketing approaches might be possible. The aim of this thesis is to provide knowledge about the usage of mix marketing and relationship marketing approaches in organizations and possibilities in combining the approaches. Also a settlement of strengths, weaknesses and risks of combining is intended to provide. The objectives were met through the literature and a case study research. In the case study, interviews were conducted in order to gain a deeper knowledge about marketing planning in various organizations. Based on this study, the combining of the major marketing approaches will be possible and even recommended when keeping in mind few aspects which might cause some troubles in the combining process.

Lipase-catalyzed Approaches towards Secondary Alcohols: Intermediates for Enantiopure Drugs

The use of enantiopure intermediates for drug synthesis is a trend in pharmaceutical industry. Different physiological effects are associated with the enantiomers of chiral molecules. Thus, the safety profile of a drug based on an enantiopure active pharmaceutical ingredient is more reliable. Biocatalysis is an important tool to access enantiopure molecules. In biocatalysis, the advantage of selectivity (chemo-, regio- and stereoselectivity) is combined with the benefits of a green synthesis strategy. Chemoenzymatic syntheses of drug molecules, obtained by combining biocatalysis with modern chemical synthesis steps usually consists of fewer reaction steps, reduced waste production and improved overall synthetic efficiency both in yields and enantio- and/or diastereoselectivities compared with classical chemical synthesis. The experimental work together with the literature review clearly indicates that lipase catalysis is highly applicable in the synthesis of enantiopure intermediates of drug molecules as the basis to infer the correct stereochemistry. By lipase catalysis, enantiopure secondary alcohols used as intermediates in the synthesis of Dorzolamide, an antiglaucoma drug, were obtained. Enantiopure _-hydroxy nitriles as potential intermediates for the synthesis of antidepressant drugs with 1-aryl-3- methylaminopropan-1-ol structure were also obtained with lipases. Kinetic resolution of racemates was the main biocatalytic approach applied. Candida Antarctica lipase B, Burkholderia cepacia lipase and Thermomyces lanuginosus lipase were applied for the acylation of alcohols and the alcoholysis of their esters in organic solvents, such as in diisopropyl ether and tert-butyl methyl ether. Candida Antarctica lipase B was used under solvent free conditions for the acylation of ethyl 3-hydroxybutanoate.

Teaching mathematics and programming : new approaches with empirical evaluation

Programming and mathematics are core areas of computer science (CS) and consequently also important parts of CS education. Introductory instruction in these two topics is, however, not without problems. Studies show that CS students find programming difficult to learn and that teaching mathematical topics to CS novices is challenging. One reason for the latter is the disconnection between mathematics and programming found in many CS curricula, which results in students not seeing the relevance of the subject for their studies. In addition, reports indicate that students' mathematical capability and maturity levels are dropping. The challenges faced when teaching mathematics and programming at CS departments can also be traced back to gaps in students' prior education. In Finland the high school curriculum does not include CS as a subject; instead, focus is on learning to use the computer and its applications as tools. Similarly, many of the mathematics courses emphasize application of formulas, while logic, formalisms and proofs, which are important in CS, are avoided. Consequently, high school graduates are not well prepared for studies in CS. Motivated by these challenges, the goal of the present work is to describe new approaches to teaching mathematics and programming aimed at addressing these issues: Structured derivations is a logic-based approach to teaching mathematics, where formalisms and justifications are made explicit. The aim is to help students become better at communicating their reasoning using mathematical language and logical notation at the same time as they become more confident with formalisms. The Python programming language was originally designed with education in mind, and has a simple syntax compared to many other popular languages. The aim of using it in instruction is to address algorithms and their implementation in a way that allows focus to be put on learning algorithmic thinking and programming instead of on learning a complex syntax. Invariant based programming is a diagrammatic approach to developing programs that are correct by construction. The approach is based on elementary propositional and predicate logic, and makes explicit the underlying mathematical foundations of programming. The aim is also to show how mathematics in general, and logic in particular, can be used to create better programs.