Suizidprävention: Vorgehensweisen und Wirksamkeit

According to official statistics every year 11,000 persons in Germany die from suicide. 20 years ago nearly 19,000 suicides were registered. What are the causes for this decrease? Do suicide preventive measures contribute to the reduction of suicide rates? Different universal prevention strategies ( e. g. restriction of access to means) and selective approaches ( programs for special high-risk groups; e. g. patients after attempted suicide) are presented and discussed regarding their preventive value. In most cases it is hardly possible to scientifically prove the efficacy of suicide prevention strategies. Neither the role of psychosocial interventions nor the impact of psychotropic agents can be sufficiently quantified. Due to various methodological reasons ( e. g. small sample sizes and the lack of randomization), interpretation of the data is difficult. In terms of a comprehensive approach of suicide prevention a combination of different activities should be most adequate in the long run

Boolean Dynamics with Random Couplings

This paper reviews a class of generic dissipative dynamical systems called N-K models. In these models, the dynamics of N elements, defined as Boolean variables, develop step by step, clocked by a discrete time variable. Each of the N Boolean elements at a given time is given a value which depends upon K elements in the previous time step. We review the work of many authors on the behavior of the models, looking particularly at the structure and lengths of their cycles, the sizes of their basins of attraction, and the flow of information through the systems. In the limit of infinite N, there is a phase transition between a chaotic and an ordered phase, with a critical phase in between. We argue that the behavior of this system depends significantly on the topology of the network connections. If the elements are placed upon a lattice with dimension d, the system shows correlations related to the standard percolation or directed percolation phase transition on such a lattice. On the other hand, a very different behavior is seen in the Kauffman net in which all spins are equally likely to be coupled to a given spin. In this situation, coupling loops are mostly suppressed, and the behavior of the system is much more like that of a mean field theory. We also describe possible applications of the models to, for example, genetic networks, cell differentiation, evolution, democracy in social systems and neural networks.Comment: 69 pages, 16 figures, Submitted to Springer Applied Mathematical Sciences Serie

Overview of homocysteine and folate metabolism. With special references to cardiovascular disease and neural tube defects

This overview addresses homocysteine and folate metabolism. Its functions and complexity are described, leading to explanations why disturbed homocysteine and folate metabolism is implicated in many different diseases, including congenital birth defects like congenital heart disease, cleft lip and palate, late pregnancy complications, different kinds of neurodegenerative and psychiatric diseases, osteoporosis and cancer. In addition, the inborn errors leading to hyperhomocysteinemia and homocystinuria are described. These extreme human hyperhomocysteinemia models provide knowledge about which part of the homocysteine and folate pathways are linked to which disease. For example, the very high risk for arterial and venous occlusive disease in patients with severe hyperhomocysteinemia irrespective of the location of the defect in remethylation or transsulphuration indicates that homocysteine itself or one of its “direct” derivatives is considered toxic for the cardiovascular system. Finally, common diseases associated with elevated homocysteine are discussed with the focus on cardiovascular disease and neural tube defects

Probing intermediates in the activation cycle of [NiFe] hydrogenase by infrared spectroscopy: the Ni-SIr state and its light sensitivity

The [NiFe] hydrogenase from the sulphate-reducing bacterium Desulfovibrio vulgaris Miyazaki F is reversibly inhibited in the presence of molecular oxygen. A key intermediate in the reactivation process, Ni-SIr, provides the link between fully oxidized (Ni-A, Ni-B) and active (Ni-SIa, Ni-C and Ni-R) forms of hydrogenase. In this work Ni-SIr was found to be light-sensitive (T ≤ 110 K), similar to the active Ni-C and the CO-inhibited states. Transition to the final photoproduct state (Ni-SL) was shown to involve an additional transient light-induced state (Ni-SI1961). Rapid scan kinetic infrared measurements provided activation energies for the transition from Ni-SL to Ni-SIr in protonated as well as in deuterated samples. The inhibitor CO was found not to react with the active site of the Ni-SL state. The wavelength dependence of the Ni-SIr photoconversion was examined in the range between 410 and 680 nm. Light-induced effects were associated with a nickel-centred electronic transition, possibly involving a change in the spin state of nickel (Ni2+). In addition, at T ≤ 40 K the CN− stretching vibrations of Ni-SL were found to be dependent on the colour of the monochromatic light used to irradiate the species, suggesting a change in the interaction of the hydrogen-bonding network of the surrounding amino acids. A possible mechanism for the photochemical process, involving displacement of the oxygen-based ligand, is discussed

Hyperdimensional Analysis of Amino Acid Pair Distributions in Proteins

Our manuscript presents a novel approach to protein structure analyses. We have organized an 8-dimensional data cube with protein 3D-structural information from 8706 high-resolution non-redundant protein-chains with the aim of identifying packing rules at the amino acid pair level. The cube contains information about amino acid type, solvent accessibility, spatial and sequence distance, secondary structure and sequence length. We are able to pose structural queries to the data cube using program ProPack. The response is a 1, 2 or 3D graph. Whereas the response is of a statistical nature, the user can obtain an instant list of all PDB-structures where such pair is found. The user may select a particular structure, which is displayed highlighting the pair in question. The user may pose millions of different queries and for each one he will receive the answer in a few seconds. In order to demonstrate the capabilities of the data cube as well as the programs, we have selected well known structural features, disulphide bridges and salt bridges, where we illustrate how the queries are posed, and how answers are given. Motifs involving cysteines such as disulphide bridges, zinc-fingers and iron-sulfur clusters are clearly identified and differentiated. ProPack also reveals that whereas pairs of Lys residues virtually never appear in close spatial proximity, pairs of Arg are abundant and appear at close spatial distance, contrasting the belief that electrostatic repulsion would prevent this juxtaposition and that Arg-Lys is perceived as a conservative mutation. The presented programs can find and visualize novel packing preferences in proteins structures allowing the user to unravel correlations between pairs of amino acids. The new tools allow the user to view statistical information and visualize instantly the structures that underpin the statistical information, which is far from trivial with most other SW tools for protein structure analysis

Prognostic factors for perceived recovery or functional improvement in non-specific low back pain: secondary analyses of three randomized clinical trials

The objective of this study was to report on secondary analyses of a merged trial dataset aimed at exploring the potential importance of patient factors associated with clinically relevant improvements in non-acute, non-specific low back pain (LBP). From 273 predominantly male army workers (mean age 39 ± 10.5 years, range 20–56 years, 4 women) with LBP who were recruited in three randomized clinical trials, baseline individual patient factors, pain-related factors, work-related psychosocial factors, and psychological factors were evaluated as potential prognostic variables in a short-term (post-treatment) and a long-term logistic regression model (6 months after treatment). We found one dominant prognostic factor for improvement directly after treatment as well as 6 months later: baseline functional disability, expressed in Roland–Morris Disability Questionnaire scores. Baseline fear of movement, expressed in Tampa Scale for Kinesiophobia scores, had also significant prognostic value for long-term improvement. Less strongly associated with the outcome, but also included in our final models, were supervisor social support and duration of complaints (short-term model), and co-worker social support and pain radiation (long-term model). Information about initial levels of functional disability and fear-avoidance behaviour can be of value in the treatment of patient populations with characteristics comparable to the current army study population (e.g., predominantly male, physically active, working, moderate but chronic back problems). Individuals at risk for poor long-term LBP recovery, i.e., individuals with high initial level of disability and prominent fear-avoidance behaviour, can be distinguished that may need additional cognitive-behavioural treatment

Developing risk prediction models for type 2 diabetes: a systematic review of methodology and reporting

<p>Abstract</p> <p>Background</p> <p>The World Health Organisation estimates that by 2030 there will be approximately 350 million people with type 2 diabetes. Associated with renal complications, heart disease, stroke and peripheral vascular disease, early identification of patients with undiagnosed type 2 diabetes or those at an increased risk of developing type 2 diabetes is an important challenge. We sought to systematically review and critically assess the conduct and reporting of methods used to develop risk prediction models for predicting the risk of having undiagnosed (prevalent) or future risk of developing (incident) type 2 diabetes in adults.</p> <p>Methods</p> <p>We conducted a systematic search of PubMed and EMBASE databases to identify studies published before May 2011 that describe the development of models combining two or more variables to predict the risk of prevalent or incident type 2 diabetes. We extracted key information that describes aspects of developing a prediction model including study design, sample size and number of events, outcome definition, risk predictor selection and coding, missing data, model-building strategies and aspects of performance.</p> <p>Results</p> <p>Thirty-nine studies comprising 43 risk prediction models were included. Seventeen studies (44%) reported the development of models to predict incident type 2 diabetes, whilst 15 studies (38%) described the derivation of models to predict prevalent type 2 diabetes. In nine studies (23%), the number of events per variable was less than ten, whilst in fourteen studies there was insufficient information reported for this measure to be calculated. The number of candidate risk predictors ranged from four to sixty-four, and in seven studies it was unclear how many risk predictors were considered. A method, not recommended to select risk predictors for inclusion in the multivariate model, using statistical significance from univariate screening was carried out in eight studies (21%), whilst the selection procedure was unclear in ten studies (26%). Twenty-one risk prediction models (49%) were developed by categorising all continuous risk predictors. The treatment and handling of missing data were not reported in 16 studies (41%).</p> <p>Conclusions</p> <p>We found widespread use of poor methods that could jeopardise model development, including univariate pre-screening of variables, categorisation of continuous risk predictors and poor handling of missing data. The use of poor methods affects the reliability of the prediction model and ultimately compromises the accuracy of the probability estimates of having undiagnosed type 2 diabetes or the predicted risk of developing type 2 diabetes. In addition, many studies were characterised by a generally poor level of reporting, with many key details to objectively judge the usefulness of the models often omitted.</p

A cluster-randomized controlled trial to reduce sedentary behavior and promote physical activity and health of 8-9 year olds: The Transform-Us! Study

Background: Physical activity (PA) is associated with positive cardio-metabolic health and emerging evidence suggests sedentary behavior (SB) may be detrimental to children&rsquo;s health independent of PA. The primary aim of the Transform-Us! study is to determine whether an 18-month, behavioral and environmental intervention in the school and family settings results in higher levels of PA and lower rates of SB among 8-9 year old children compared with usual practice (post-intervention and 12-months follow-up). The secondary aims are to determine the independent and combined effects of PA and SB on children&rsquo;s cardio-metabolic health risk factors; identify the factors that mediate the success of the intervention; and determine whether the intervention is cost-effective.Methods/design: A four-arm cluster-randomized controlled trial (RCT) with a 2 &times; 2 factorial design, with schools as the unit of randomization. Twenty schools will be allocated to one of four intervention groups, sedentary behavior (SB-I), physical activity (PA-I), combined SB and PA (SB+PA-I) or current practice control (C), which will be evaluated among approximately 600 children aged 8-9 years in school year 3 living in Melbourne, Australia. All children in year 3 at intervention schools in 2010 (8-9 years) will receive the intervention over an 18-month period with a maintenance &lsquo;booster&rsquo; delivered in 2012 and children at all schools will be invited to participate in the evaluation assessments. To maximize the sample and to capture new students arriving at intervention and control schools, recruitment will be on-going up to the post-intervention time point. Primary outcomes are time spent sitting and in PA assessed via accelerometers and inclinometers and survey.Discussion: To our knowledge, Transform-Us! is the first RCT to examine the effectiveness of intervention strategies for reducing children&rsquo;s overall sedentary time, promoting PA and optimizing health outcomes. The integration of consistent strategies and messages to children from teachers and parents in both school and family settings is a critical component of this study, and if shown to be effective, may have a significant impact on educational policies as well as on pedagogical and parenting practices.<br /