Antigen Processing and Presentation in Multiple Sclerosis

CD4(+) T cells play a central role in the pathogenesis of multiple sclerosis (MS). Generation, activation and effector function of these cells crucially depends on their interaction with MHC II-peptide complexes displayed by antigen presenting cells (APC). Processing and presentation of self antigens by different APC therefore influences the disease course at all stages. Selection by thymic APC leads to the generation of autoreactive T cells, which can be activated by peripheral APC. Reactivation by central nervous system APC leads to the initiation of the inflammatory response resulting in demyelination. In this review we will focus on how MHC class II antigenic epitopes are created by different APC from the thymus, the periphery and from the brain, and will discuss the relevance of the balance between creation and destruction of such epitopes in the context of MS. A solid understanding of these processes offers the possibility for designing future therapeutic strategies.

Autophagy in cancer and chemotherapy

Cancer cells often exhibit mutations in critical molecules of the apoptotic machinery, resulting in resistance to common anticancer therapies. In the absence of apoptosis, autophagic cell death can be an alternative form of cell death by excessive self-digestion. Therefore, autophagic cell death can be considered as a backup cell death mechanism when apoptotic cell death mechanisms fail. However, many tumors also exhibit deficiencies in autophagy that may result in both genomic instability and further anticancer drug resistance. This chapter summarizes our current understanding regarding the regulation of autophagy in tumors and discusses potential new anticancer drug treatment strategies.

Depressive symptoms from kindergarten to early school age: longitudinal associations with social skills deficits and peer victimization

BACKGROUND: Depressive symptoms in children are associated with social skills deficits and problems with peers. We propose a model which suggests different mechanisms for the impact of deficits in self-oriented social skills (assertiveness and social participation) and other-oriented social skills (pro-social, cooperative and non-aggressive behaviors) on children's depressive symptoms. We hypothesized that deficits in self-oriented social skills have a direct impact on children's depressive symptoms because these children have non-rewarding interactions with peers, whereas the impact of deficits in other-oriented social skills on depressive symptoms is mediated through negative reactions from peers such as peer victimization. METHOD: 378 kindergarten children (163 girls) participated at two assessments (Age at T1: M = 5.8, T2: M = 7.4). Teachers completed questionnaires on children's social skills at T1. Teacher reports on peer victimization and depressive symptoms were assessed at both assessment points. RESULTS: Our study partially confirmed the suggested conceptual model. Deficits in self-oriented social skills significantly predicted depressive symptoms, whereas deficits in other-oriented social skills were more strongly associated with peer victimization. Longitudinal associations between other-oriented social skills and depressive symptoms were mediated through peer victimization. CONCLUSION: The study emphasizes the role of deficits in self-oriented social skills and peer victimization for the development of internalizing disorders.

A communication and information technology infrastructure for real time monitoring and management of type 1 diabetes patients

This paper is focused on the integration of state-of-the-art technologies in the fields of telecommunications, simulation algorithms, and data mining in order to develop a Type 1 diabetes patient's semi to fully-automated monitoring and management system. The main components of the system are a glucose measurement device, an insulin delivery system (insulin injection or insulin pumps), a mobile phone for the GPRS network, and a PDA or laptop for the Internet. In the medical environment, appropriate infrastructure for storage, analysis and visualizing of patients' data has been implemented to facilitate treatment design by health care experts.

Software Engineering and eLearning: The MuSofT Project

eLearning supports the education in certain disciplines. Here, we report about novel eLearning concepts, techniques, and tools to support education in Software Engineering, a subdiscipline of computer science. We call this "Software Engineering eLearning". On the other side, software support is a substantial prerequisite for eLearning in any discipline. Thus, Software Engineering techniques have to be applied to develop and maintain those software systems. We call this "eLearning Software Engineering". Both aspects have been investigated in a large joint, BMBF-funded research project, termed MuSofT (Multimedia in Software Engineering). The main results are summarized in this paper.

Why Freeter and NEET are Misunderstood: Recognizing the New Precarious Conditions of Japanese Youth

In developed countries, the transition from school to work has radically changed over the past two decades. It has become prolonged, complicated and individualized (Bynner et al., 1997; Walther et al., 2004). Young people used to transition directly from school to stable employment, or with a very short unemployed period. In many European countries, this situation has been changing since the eighties: overall youth unemployment has increased, and many young people experience long periods of unemployment, government training schemes and part-time or temporary jobs. In Japan, this change has taken a decade later to appear, becoming prevalent by the late nineties (Inui, 2003). The transiting process has become not only precarious for young people, but also difficult for society to precisely understand the risks and problems. Traditionally, we have been able to recognize young people's situation by a simple category: in education, employed, in training or unemployed. However, these categories no longer accurately represent young people's state. In Japan, most young people used to move from school directly to full-time employment through the new graduate recruitment system (Inui, 1993). Therefore, in official statistics such as the School Basic Survey, 'employed' includes only those who are in regular employment, while those who are in part-time or temporary work are covered by the categories 'jobless' and 'others'. However, with the increase in non-full-time jobs in the nineties, these categories have become less useful for describing the actual employment conditions of young people. Indeed, this is why, in the late of nineties, the Japanese Ministry of Education changed the category name from 'jobless' to 'others'.

What Price Social and Health Care? Commodities, Competition and Consumers

In this paper we explore some important disputes and problems surrounding the legal status and social purpose of Health

Entwicklung einer Methodik zur Generierung einer Datenbasis für Optimierungssysteme in der maritimen Leercontainerlogistik

Dieser Beitrag stellt ein Vorgehen zur Entwicklung einer Methodik zur Generierung einer praxisnahen Datenbasis für numerische Untersuchungen im Rahmen der maritimen Leercontainerlogistik vor. Das Vorgehen wird an einem exemplarischen Anwendungsfall verdeutlicht. Die Resultate sollen Testläufe für Szenarien der Leercontainerlogistik unterstützen und somit eine Basis für die Entwicklung und Bewertung organisatorischer Verbesserungsansätze, mathematischer Optimierungsmodelle, entsprechender Lösungsalgorithmen und praxisnaher Simulationsumgebungen bilden.

Flow-R, a model for susceptibility mapping of debris flows and other gravitational hazards at a regional scale

The development of susceptibility maps for debris flows is of primary importance due to population pressure in hazardous zones. However, hazard assessment by process-based modelling at a regional scale is difficult due to the complex nature of the phenomenon, the variability of local controlling factors, and the uncertainty in modelling parameters. A regional assessment must consider a simplified approach that is not highly parameter dependant and that can provide zonation with minimum data requirements. A distributed empirical model has thus been developed for regional susceptibility assessments using essentially a digital elevation model (DEM). The model is called Flow-R for Flow path assessment of gravitational hazards at a Regional scale (available free of charge under http://www.flow-r.org) and has been successfully applied to different case studies in various countries with variable data quality. It provides a substantial basis for a preliminary susceptibility assessment at a regional scale. The model was also found relevant to assess other natural hazards such as rockfall, snow avalanches and floods. The model allows for automatic source area delineation, given user criteria, and for the assessment of the propagation extent based on various spreading algorithms and simple frictional laws. We developed a new spreading algorithm, an improved version of Holmgren's direction algorithm, that is less sensitive to small variations of the DEM and that is avoiding over-channelization, and so produces more realistic extents. The choices of the datasets and the algorithms are open to the user, which makes it compliant for various applications and dataset availability. Amongst the possible datasets, the DEM is the only one that is really needed for both the source area delineation and the propagation assessment; its quality is of major importance for the results accuracy. We consider a 10 m DEM resolution as a good compromise between processing time and quality of results. However, valuable results have still been obtained on the basis of lower quality DEMs with 25 m resolution.

Aggression, impulsivity and serotonin in drug dependence

Aggression, impulsivity, and central serotonergic function were evaluated in two groups of human volunteers; one group having a history of substance dependence (DRUG+) and another group with no drug use history (DRUG$-$). The hypothesis was that DRUG+ subjects would be more aggressive, more impulsive, and have attenuated serotonergic function. Results showed that DRUG+ subjects behaved more aggressively in a computer paradigm of aggression and also reported more aggression on questionnaires than DRUG$-$ subjects. In a computer paradigm of impulsivity, the DRUG+ group showed a lesser ability to delay gratification than the DRUG$-$ group in the last session of testing. The DRUG+ subjects also reported more venturesomeness and problems associated with low impulse control on questionnaires. Serotonergic function was measured through the neuroendocrine and hypothermic response to an orally administered serotonin (5-HT) agonist specific to the 5-HT$\rm\sb{1A}$ receptor subtype (ipsapirone). The neuroendocrine responses did not differ between DRUG$\pm$ groups, indicating no difference in the sensitivity of the presynaptic or postsynaptic 5-HT$\rm\sb{1A}$ receptors. An unexpected result was that the indicator hormone, cortisol, was at a lower baseline level in the DRUG+ group than the DRUG$-$ group. Lowered cortisol levels have been previously noted in children at high risk foul antisociality and future drug use. A principal components analysis including impulsivity, aggression, and serotonergic function measures produced three unique factors. The factors, Antisocial Tendency and Self-Control and Serotonergic Function combined to produce a significant regression equation explaining 36% of variability in the DRUG$\pm$ groups. These factors included measures of aggression, impulsivity, mood, and educational attainment. These results suggest that the current measures of aggression and impulsivity were predictive of a drug dependence disorder but that neuroendocrine function is not yet a useful indicator of drug dependence status. ^

There is more than "more is up": Hand and foot responses reverse the vertical association of number magnitudes

Recent research in cognitive sciences shows a growing interest in spatial-numerical associations. The horizontal SNARC (spatial-numerical association of response codes) effect is defined by faster left-sided responses to small numbers and faster right-sided responses to large numbers in a parity judgment task. In this study we investigated whether there is also a SNARC effect for upper and lower responses. The grounded cognition approach suggests that the universal experience of "more is up" serves as a robust frame of reference for vertical number representation. In line with this view, lower hand responses to small numbers were faster than to large numbers (Experiment 1). Interestingly, the vertical SNARC effect reversed when the lower responses were given by foot instead of the hand (Experiments 2, 3, and 4). We found faster upper (hand) responses to small numbers and faster lower (foot) responses to large numbers. Additional experiments showed that spatial factors cannot account for the reversal of the vertical SNARC effect (Experiments 4 and 5). Our results question the view of "more is up" as a robust frame of reference for spatial-numerical associations. We discuss our results within a hierarchical framework of numerical cognition and point to a possible link between effectors and number representation.

Does the (structural) context matter? Analysing individual and structural factors of members’ commitment to sports clubs

Introduction: Over the last decades, Swiss sports clubs have lost their "monopoly" in the market for sports-related services and increasingly are in competition with other sports providers. For many sport clubs long-term membership cannot be seen as a matter of course. Current research on sports clubs in Switzerland – as well as for other European countries – confirms the increasing difficulties in achieving long-term member commitment. Looking at recent findings of the Swiss sport clubs report (Lamprecht, Fischer & Stamm, 2012), it can be noted, that a decrease in memberships does not equally affect all clubs. There are sports clubs – because of their specific situational and structural conditions – that have few problems with member fluctuation, while other clubs show considerable declines in membership. Therefore, a clear understanding of individual and structural factors that trigger and sustain member commitment would help sports clubs to tackle this problem more effectively. This situation poses the question: What are the individual and structural determinants that influence the tendency to continue or to quit the membership? Methods: Existing research has extensively investigated the drivers of members’ commitment at an individual level. As commitment of members usually occurs within an organizational context, the characteristics of the organisation should be also considered. However, this context has been largely neglected in current research. This presentation addresses both the individual characteristics of members and the corresponding structural conditions of sports clubs resulting in a multi-level framework for the investigation of the factors of members’ commitment in sports clubs. The multilevel analysis grant a adequate handling of hierarchically structured data (e.g., Hox, 2002). The influences of both the individual and context level on the stability of memberships are estimated in multi-level models based on a sample of n = 1,434 sport club members from 36 sports clubs. Results: Results of these multi-level analyses indicate that commitment of members is not just an outcome of individual characteristics, such as strong identification with the club, positively perceived communication and cooperation, satisfaction with sports clubs’ offers, or voluntary engagement. It is also influenced by club-specific structural conditions: stable memberships are more probable in rural sports clubs, and in clubs that explicitly support sociability, whereas sporting-success oriented goals in clubs have a destabilizing effect. Discussion/Conclusion: The proposed multi-level framework and the multi-level analysis can open new perspectives for research concerning commitment of members to sports clubs and other topics and problems of sport organisation research, especially in assisting to understand individual behavior within organizational contexts. References: Hox, J. J. (2002). Multilevel analysis: Techniques and applications. Mahwah: Lawrence Erlbaum. Lamprecht, M., Fischer, A., & Stamm, H.-P. (2012). Die Schweizer Sportvereine – Strukturen, Leistungen, Herausforderungen. Zurich: Seismo.

The block numerical range of analytic operator functions

We introduce the block numerical range Wn(L) of an operator function L with respect to a decomposition H = H1⊕. . .⊕Hn of the underlying Hilbert space. Our main results include the spectral inclusion property and estimates of the norm of the resolvent for analytic L . They generalise, and improve, the corresponding results for the numerical range (which is the case n = 1) since the block numerical range is contained in, and may be much smaller than, the usual numerical range. We show that refinements of the decomposition entail inclusions between the corresponding block numerical ranges and that the block numerical range of the operator matrix function L contains those of its principal subminors. For the special case of operator polynomials, we investigate the boundedness of Wn(L) and we prove a Perron-Frobenius type result for the block numerical radius of monic operator polynomials with coefficients that are positive in Hilbert lattice sense.

Lung Nodule Detection by Microdose CT Versus Chest Radiography (Standard and Dual-Energy Subtracted).

OBJECTIVE The purpose of this study was to investigate the feasibility of microdose CT using a comparable dose as for conventional chest radiographs in two planes including dual-energy subtraction for lung nodule assessment. MATERIALS AND METHODS We investigated 65 chest phantoms with 141 lung nodules, using an anthropomorphic chest phantom with artificial lung nodules. Microdose CT parameters were 80 kV and 6 mAs, with pitch of 2.2. Iterative reconstruction algorithms and an integrated circuit detector system (Stellar, Siemens Healthcare) were applied for maximum dose reduction. Maximum intensity projections (MIPs) were reconstructed. Chest radiographs were acquired in two projections with bone suppression. Four blinded radiologists interpreted the images in random order. RESULTS A soft-tissue CT kernel (I30f) delivered better sensitivities in a pilot study than a hard kernel (I70f), with respective mean (SD) sensitivities of 91.1% ± 2.2% versus 85.6% ± 5.6% (p = 0.041). Nodule size was measured accurately for all kernels. Mean clustered nodule sensitivity with chest radiography was 45.7% ± 8.1% (with bone suppression, 46.1% ± 8%; p = 0.94); for microdose CT, nodule sensitivity was 83.6% ± 9% without MIP (with additional MIP, 92.5% ± 6%; p < 10(-3)). Individual sensitivities of microdose CT for readers 1, 2, 3, and 4 were 84.3%, 90.7%, 68.6%, and 45.0%, respectively. Sensitivities with chest radiography for readers 1, 2, 3, and 4 were 42.9%, 58.6%, 36.4%, and 90.7%, respectively. In the per-phantom analysis, respective sensitivities of microdose CT versus chest radiography were 96.2% and 75% (p < 10(-6)). The effective dose for chest radiography including dual-energy subtraction was 0.242 mSv; for microdose CT, the applied dose was 0.1323 mSv. CONCLUSION Microdose CT is better than the combination of chest radiography and dual-energy subtraction for the detection of solid nodules between 5 and 12 mm at a lower dose level of 0.13 mSv. Soft-tissue kernels allow better sensitivities. These preliminary results indicate that microdose CT has the potential to replace conventional chest radiography for lung nodule detection.

Evaluation of Three State-of-the-Art Classifiers for Recognition of Activities of Daily Living from Smart Home Ambient Data

Smart homes for the aging population have recently started attracting the attention of the research community. The "health state" of smart homes is comprised of many different levels; starting with the physical health of citizens, it also includes longer-term health norms and outcomes, as well as the arena of positive behavior changes. One of the problems of interest is to monitor the activities of daily living (ADL) of the elderly, aiming at their protection and well-being. For this purpose, we installed passive infrared (PIR) sensors to detect motion in a specific area inside a smart apartment and used them to collect a set of ADL. In a novel approach, we describe a technology that allows the ground truth collected in one smart home to train activity recognition systems for other smart homes. We asked the users to label all instances of all ADL only once and subsequently applied data mining techniques to cluster in-home sensor firings. Each cluster would therefore represent the instances of the same activity. Once the clusters were associated to their corresponding activities, our system was able to recognize future activities. To improve the activity recognition accuracy, our system preprocessed raw sensor data by identifying overlapping activities. To evaluate the recognition performance from a 200-day dataset, we implemented three different active learning classification algorithms and compared their performance: naive Bayesian (NB), support vector machine (SVM) and random forest (RF). Based on our results, the RF classifier recognized activities with an average specificity of 96.53%, a sensitivity of 68.49%, a precision of 74.41% and an F-measure of 71.33%, outperforming both the NB and SVM classifiers. Further clustering markedly improved the results of the RF classifier. An activity recognition system based on PIR sensors in conjunction with a clustering classification approach was able to detect ADL from datasets collected from different homes. Thus, our PIR-based smart home technology could improve care and provide valuable information to better understand the functioning of our societies, as well as to inform both individual and collective action in a smart city scenario.