Socio-economic differences in self-esteem of adolescents influenced by personality, mental health and social support

Background: Previous studies indicate that self-esteem is lower among adolescents of low socio-economic status and is associated with a number of intrapersonal, interpersonal and socio-cultural factors. Evidence on the mechanisms by which these factors contribute to the connection between socio-economic status and developing self-esteem is incomplete, however. The purpose of this cross-sectional study is to assess whether personality, mental health and social support contribute to the relationship between socio-economic status and self-esteem. Methods: A sample of 3694 elementary-school students from Slovakia (mean age = 14.3 years, 49% boys) filled out the Rosenberg Self-esteem Scale, the Family Affluence Scale, the Ten-Item Personality Inventory, the 12-item General Health Questionnaire and the Perceived Social Support Scale. Results: Hierarchical linear regression showed family affluence, personality dimensions of extroversion, emotional stability and openness to experience, as well as mental health subscales and social support from family and significant others to be associated with self-esteem. Results indicate that personality dimensions and mental health subscales contribute to the association between family affluence and self-esteem. Conclusion: The contribution of personality and mental problems in the relation between socio-economic status and self-esteem may have important implications for the design of promotional programs aimed at enhancing self-esteem

Smart Environments for Collaborative Design, Implementation, and Interpretation of Scientific Experiments

Ambient intelligence promises to enable humans to smoothly interact with their environment, mediated by computer technology. In the literature on ambient intelligence, empirical scientists are not often mentioned. Yet they form an interesting target group for this technology. In this position paper, we describe a project aimed at realising an ambient intelligence environment for face-to-face meetings of researchers with different academic backgrounds involved in molecular biology “omics” experiments. In particular, microarray experiments are a focus of attention because these experiments require multidisciplinary collaboration for their design, analysis, and interpretation. Such an environment is characterised by a high degree of complexity that has to be mitigated by ambient intelligence technology. By experimenting in a real-life setting, we will learn more about life scientists as a user group

Introduction to Protein Structure

While many good textbooks are available on Protein Structure, Molecular Simulations, Thermodynamics and Bioinformatics methods in general, there is no good introductory level book for the field of Structural Bioinformatics. This book aims to give an introduction into Structural Bioinformatics, which is where the previous topics meet to explore three dimensional protein structures through computational analysis. We provide an overview of existing computational techniques, to validate, simulate, predict and analyse protein structures. More importantly, it will aim to provide practical knowledge about how and when to use such techniques. We will consider proteins from three major vantage points: Protein structure quantification, Protein structure prediction, and Protein simulation & dynamics. Within the living cell, protein molecules perform specific functions, typically by interacting with other proteins, DNA, RNA or small molecules. They take on a specific three dimensional structure, encoded by its amino acid sequence, which allows them to function within the cell. Hence, the understanding of a protein's function is tightly coupled to its sequence and its three dimensional structure. Before going into protein structure analysis and prediction, and protein folding and dynamics, here, we give a short and concise introduction into the basics of protein structures