143 resultados para Applications for positions.


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Glioblastoma multiforme is the most common and most malignant primary brain tumour with a dismal prognosis. The advent of new chemotherapies with alkylating agents crossing the blood-brain barrier, like temozolomide, have permitted to notably ameliorate the survival of a subgroup of patients. Improved outcome was associated with epigenetic silencing of the MGMT (O6-methylguanin methyltransferase) gene by promotor methylation, thereby blocking its repair capability, thus rendering the alkylating agents more effective. This particularity can be tested by methylation specific PCR on resected tumour tissue, best on fresh frozen biopsies, and allows identification of patients more susceptible to respond favourably to the treatment.

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Over the past decade, CMRA has emerged as a unique clinical imaging tool with applications in selected populations. Patients with suspected coronary artery anomalies and patients with Kawasaki disease and coronary aneurysms are among those for whom CMRA has demonstrated clinical usefulness. For assessment of patients with atherosclerotic CAD, CMRA is useful for detection of patency of bypass grafts. At centers with appropriate expertise and resources, CMRA also appears to be of value for exclusion of severe proximal multivessel CAD in selected patients. Data from multicenter trials will continue to define the clinical role of CMRA, particularly as it relates to assessment of CAD. Future developments and enhancements of CMRA promise better lumen and coronary artery wall imaging. This may become the new target in noninvasive evaluation of CAD.

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Osteoporosis is a serious worldwide epidemic. Increased risk of fractures is the hallmark of the disease and is associated with increased morbidity, mortality and economic burden. FRAX® is a web-based tool developed by the Sheffield WHO Collaborating Center team, that integrates clinical risk factors, femoral neck BMD, country specific mortality and fracture data and calculates the 10 year fracture probability in order to help health care professionals identify patients who need treatment. However, only 31 countries have a FRAX® calculator at the time paper was accepted for publication. In the absence of a FRAX® model for a particular country, it has been suggested to use a surrogate country for which the epidemiology of osteoporosis most closely approximates the index country. More specific recommendations for clinicians in these countries are not available. In North America, concerns have also been raised regarding the assumptions used to construct the US ethnic specific FRAX® calculators with respect to the correction factors applied to derive fracture probabilities in Blacks, Asians and Hispanics in comparison to Whites. In addition, questions were raised about calculating fracture risk in other ethnic groups e.g., Native Americans and First Canadians. In order to provide additional guidance to clinicians, a FRAX® International Task Force was formed to address specific questions raised by physicians in countries without FRAX® calculators and seeking to integrate FRAX® into their clinical practice. The main questions that the task force tried to answer were the following: The Task Force members conducted appropriate literature reviews and developed preliminary statements that were discussed and graded by a panel of experts at the ISCD-IOF joint conference. The statements approved by the panel of experts are discussed in the current paper.

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Stimulated echoes are widely used for imaging functional tissue parameters such as diffusion coefficient, perfusion, and flow rates. They are potentially interesting for the assessment of various cardiac functions. However, severe limitations of the stimulated echo acquisition mode occur, which are related to the special dynamic properties of the beating heart and flowing blood. To the well-known signal decay due to longitudinal relaxation and through-plane motion between the preparation and the read-out period of the stimulated echoes, additional signal loss is often observed. As the prepared magnetization is fixed with respect to the tissue, this signal loss is caused by the tissue deformation during the cardiac cycle, which leads to a modification of the modulation frequency of the magnetization. These effects are theoretically derived and corroborated by phantom and in vivo experiments.

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Analysis of variance is commonly used in morphometry in order to ascertain differences in parameters between several populations. Failure to detect significant differences between populations (type II error) may be due to suboptimal sampling and lead to erroneous conclusions; the concept of statistical power allows one to avoid such failures by means of an adequate sampling. Several examples are given in the morphometry of the nervous system, showing the use of the power of a hierarchical analysis of variance test for the choice of appropriate sample and subsample sizes. In the first case chosen, neuronal densities in the human visual cortex, we find the number of observations to be of little effect. For dendritic spine densities in the visual cortex of mice and humans, the effect is somewhat larger. A substantial effect is shown in our last example, dendritic segmental lengths in monkey lateral geniculate nucleus. It is in the nature of the hierarchical model that sample size is always more important than subsample size. The relative weight to be attributed to subsample size thus depends on the relative magnitude of the between observations variance compared to the between individuals variance.

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Abstract This PhD thesis addresses the issue of alleviating the burden of developing ad hoc applications. Such applications have the particularity of running on mobile devices, communicating in a peer-to-peer manner and implement some proximity-based semantics. A typical example of such application can be a radar application where users see their avatar as well as the avatars of their friends on a map on their mobile phone. Such application become increasingly popular with the advent of the latest generation of mobile smart phones with their impressive computational power, their peer-to-peer communication capabilities and their location detection technology. Unfortunately, the existing programming support for such applications is limited, hence the need to address this issue in order to alleviate their development burden. This thesis specifically tackles this problem by providing several tools for application development support. First, it provides the location-based publish/subscribe service (LPSS), a communication abstraction, which elegantly captures recurrent communication issues and thus allows to dramatically reduce the code complexity. LPSS is implemented in a modular manner in order to be able to target two different network architectures. One pragmatic implementation is aimed at mainstream infrastructure-based mobile networks, where mobile devices can communicate through fixed antennas. The other fully decentralized implementation targets emerging mobile ad hoc networks (MANETs), where no fixed infrastructure is available and communication can only occur in a peer-to-peer fashion. For each of these architectures, various implementation strategies tailored for different application scenarios that can be parametrized at deployment time. Second, this thesis provides two location-based message diffusion protocols, namely 6Shot broadcast and 6Shot multicast, specifically aimed at MANETs and fine tuned to be used as building blocks for LPSS. Finally this thesis proposes Phomo, a phone motion testing tool that allows to test proximity semantics of ad hoc applications without having to move around with mobile devices. These different developing support tools have been packaged in a coherent middleware framework called Pervaho.

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Summary The specific CD8+ T cell immune response against tumors relies on the recognition by the T cell receptor (TCR) on cytotoxic T lymphocytes (CTL) of antigenic peptides bound to the class I major histocompatibility complex (MHC) molecule. Such tumor associated antigenic peptides are the focus of tumor immunotherapy with peptide vaccines. The strategy for obtaining an improved immune response often involves the design of modified tumor associated antigenic peptides. Such modifications aim at creating higher affinity and/or degradation resistant peptides and require precise structures of the peptide-MHC class I complex. In addition, the modified peptide must be cross-recognized by CTLs specific for the parental peptide, i.e. preserve the structure of the epitope. Detailed structural information on the modified peptide in complex with MHC is necessary for such predictions. In this thesis, the main focus is the development of theoretical in silico methods for prediction of both structure and cross-reactivity of peptide-MHC class I complexes. Applications of these methods in the context of immunotherapy are also presented. First, a theoretical method for structure prediction of peptide-MHC class I complexes is developed and validated. The approach is based on a molecular dynamics protocol to sample the conformational space of the peptide in its MHC environment. The sampled conformers are evaluated using conformational free energy calculations. The method, which is evaluated for its ability to reproduce 41 X-ray crystallographic structures of different peptide-MHC class I complexes, shows an overall prediction success of 83%. Importantly, in the clinically highly relevant subset of peptide-HLAA*0201 complexes, the prediction success is 100%. Based on these structure predictions, a theoretical approach for prediction of cross-reactivity is developed and validated. This method involves the generation of quantitative structure-activity relationships using three-dimensional molecular descriptors and a genetic neural network. The generated relationships are highly predictive as proved by high cross-validated correlation coefficients (0.78-0.79). Together, the here developed theoretical methods open the door for efficient rational design of improved peptides to be used in immunotherapy. Résumé La réponse immunitaire spécifique contre des tumeurs dépend de la reconnaissance par les récepteurs des cellules T CD8+ de peptides antigéniques présentés par les complexes majeurs d'histocompatibilité (CMH) de classe I. Ces peptides sont utilisés comme cible dans l'immunothérapie par vaccins peptidiques. Afin d'augmenter la réponse immunitaire, les peptides sont modifiés de façon à améliorer l'affinité et/ou la résistance à la dégradation. Ceci nécessite de connaître la structure tridimensionnelle des complexes peptide-CMH. De plus, les peptides modifiés doivent être reconnus par des cellules T spécifiques du peptide natif. La structure de l'épitope doit donc être préservée et des structures détaillées des complexes peptide-CMH sont nécessaires. Dans cette thèse, le thème central est le développement des méthodes computationnelles de prédiction des structures des complexes peptide-CMH classe I et de la reconnaissance croisée. Des applications de ces méthodes de prédiction à l'immunothérapie sont également présentées. Premièrement, une méthode théorique de prédiction des structures des complexes peptide-CMH classe I est développée et validée. Cette méthode est basée sur un échantillonnage de l'espace conformationnel du peptide dans le contexte du récepteur CMH classe I par dynamique moléculaire. Les conformations sont évaluées par leurs énergies libres conformationnelles. La méthode est validée par sa capacité à reproduire 41 structures des complexes peptide-CMH classe I obtenues par cristallographie aux rayons X. Le succès prédictif général est de 83%. Pour le sous-groupe HLA-A*0201 de complexes de grande importance pour l'immunothérapie, ce succès est de 100%. Deuxièmement, à partir de ces structures prédites in silico, une méthode théorique de prédiction de la reconnaissance croisée est développée et validée. Celle-ci consiste à générer des relations structure-activité quantitatives en utilisant des descripteurs moléculaires tridimensionnels et un réseau de neurones couplé à un algorithme génétique. Les relations générées montrent une capacité de prédiction remarquable avec des valeurs de coefficients de corrélation de validation croisée élevées (0.78-0.79). Les méthodes théoriques développées dans le cadre de cette thèse ouvrent la voie du design de vaccins peptidiques améliorés.

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Voting Advice Applications (VAAs) have become a central component of election campaigns worldwide. Through matching political preferences of voters to parties and candidates, the web application grants voters a look into their political mirror and reveals the most suitable political choices to them in terms of policy congruence. Both the dense and concise information on the electoral offer and the comparative nature of the application make VAAs an unprecedented information source for electoral decision making. In times where electoral choices are found to be highly individualized and driven by political issue positions, an ever increasing number of voters turn to VAAs before casting their ballots. With VAAs in high demand, the question of their effects on voters has become a pressing research topic. In various countries, survey research has been used to proclaim an impact of VAAs on electoral behavior, yet practically all studies fail to provide the scientific evidence that would allow for making such claims. In this thesis, I set out to systematically establish the causal link between VAA use and electoral behavior, using various data sources and appropriate statistical techniques in doing so. The focus lies on the Swiss VAA smartvote, introduced in the forefront of the 2003 Swiss federal elections and meanwhile an integral part of the national election campaign, smartvote has produced over a million voting recommendations in the last Swiss federal elections to an active electorate of two million, potentially guiding a vast amount of voters in their choices on the ballot. In order to determine the effect of the VAA on electoral behavior, I analyze both voting preferences and choice among Swiss voters during two consecutive election periods. First, I introduce statistical techniques to adequately examine VAA effects in observational studies and use them to demonstrate that voters who used smartvote prior to the 2007 Swiss federal elections were significantly more likely to swing vote in the elections than non- users. Second, I analyze preference voting during the same election and show that the smartvote voting recommendation inclines politically knowledgeable voters to modify their ballots and cast candidate specific preference votes. Third, to further tackle the indication that smartvote use affects the preference structure of voters, I employ an experimental research design to demonstrate that voters who use the application tend to strengthen their vote propensities for their most preferred party and adapt their overall party preferences in a way that they consider more than one party as eligible vote options after engaging with the application. Finally, vote choice is examined for the 2011 Swiss federal election, showing once more that the VAA initiated a change of party choice among voters. In sum, this thesis presents empirical evidence for the transformative effect of the Swiss VAA smartvote on the electoral behavior.