A feasibility trial to examine the social norms approach for the prevention and reduction of licit and illicit drug use in European University and college students.

Background: Incorrect perceptions of high rates of peer alcohol and tobacco use are predictive of increased personal use in student populations. Correcting misperceptions by providing feedback has been shown to be an effective intervention for reducing licit drug use. It is currently unknown if social norms interventions are effective in preventing and reducing illicit drug use in European students. The purpose of this paper is to describe the design of a multi-site cluster controlled trial of a web-based social norms intervention aimed at reducing licit and preventing illicit drug use in European university students. Methods/Design: An online questionnaire to assess rates of drug use will be developed and translated based on existing social norms surveys. Students from sixteen universities in seven participating European countries will be invited to complete the questionnaire. Both intervention and control sites will be chosen by convenience. In each country, the intervention site will be the university that the local principal investigator is affiliated with. We aim to recruit 1000 students per site (baseline assessment). All participants will complete the online questionnaire at baseline. Baseline data will be used to develop social norms messages that will be included in a web-based intervention. The intervention group will receive individualized social norms feedback. The website will remain online during the following 5 months. After five months, a second survey will be conducted and effects of the intervention on social norms and drug use will be measured in comparison to the control site. Discussion: This project is the first cross-national European collaboration to investigate the feasibility of a social norms intervention to reduce licit and prevent illicit drug use among European university students. Final trial registration number DRKS00004375 on the ‘German Clinical Trials Register’.This study is funded by the European Commission, Directorate General Justice, Freedom and Security (JLS/2009-2010/DPIP/AG

Polarized secretion of Leukemia Inhibitory Factor

<p>Abstract</p> <p>Background</p> <p>The direction of cytokine secretion from polarized cells determines the cytokine's cellular targets. Leukemia inhibitory factor (LIF) belongs to the interleukin-6 (IL-6) family of cytokines and signals through LIFR/gp130. Three factors which may regulate the direction of LIF secretion were studied: the site of stimulation, signal peptides, and expression levels. Stimulation with IL-1β is known to promote IL-6 secretion from the stimulated membrane (apical or basolateral) in the human intestinal epithelial cell line Caco-2. Since LIF is related to IL-6, LIF secretion was also tested in Caco-2 following IL-1β stimulation. Signal peptides may influence the trafficking of LIF. Two isoforms of murine LIF, LIF-M and LIF-D, encode different signal peptides which have been associated with different locations of the mature protein in fibroblasts. To determine the effect of the signal peptides on LIF secretion, secretion levels were compared in Madin-Darby canine kidney (MDCK) clones which expressed murine LIF-M or LIF-D or human LIF under the control of an inducible promoter. Low and high levels of LIF expression were also compared since saturation of the apical or basolateral route would reveal specific transporters for LIF.</p> <p>Results</p> <p>When Caco-2 was grown on permeable supports, LIF was secreted constitutively with around 40% secreted into the apical chamber. Stimulation with IL-1β increased LIF production. After treating the apical surface with IL-1β, the percentage secreted apically remained similar to the untreated, whereas, when the cells were stimulated at the basolateral surface only 20% was secreted apically. In MDCK cells, an endogenous LIF-like protein was detected entirely in the apical compartment. The two mLIF isoforms showed no difference in their secretion patterns in MDCK. Interestingly, about 70% of murine and human LIF was secreted apically from MDCK over a 400-fold range of expression levels within clones and a 200,000-fold range across clones.</p> <p>Conclusion</p> <p>The site of stimulation affected the polarity of LIF secretion, while, signal peptides and expression levels did not. Exogenous LIF is transported in MDCK without readily saturated steps.</p

Community peer-led falls prevention presentations: What do the experts suggest?

Falls among older adults are a major problem. Despite considerable progress in falls prevention research, older adults often show low motivation to engage in recommended preventive strategies. Peer-led falls prevention education for older adults may have potential for bridging the research evidence-practice gap, thereby promoting the uptake of falls prevention strategies. We evaluated peer educators’ presentations of falls prevention education to community-dwelling older adults in regard to established criteria that were consistent with adult learning principles, the framework of health behaviour change, falls prevention guidelines, and recommendations for providing falls prevention information. We conducted a within-stage mixed model study using purposive and snowball sampling techniques to recruit 10 experts to evaluate video recordings of the delivery of three peer-led falls prevention presentations. Each expert viewed three videos and rated them using a questionnaire containing both open-ended and closed items. There was a good level of expert agreement across the questionnaire domains. Though the experts rated some aspects of the presentations highly, they thought that the presentations were mainly didactic in delivery, not consistently personally relevant to the older adult audience, and did not encourage older adults to engage in the preventive strategies that were presented. Based on the experts’ findings, we developed five key themes and recommendations for the effective delivery of peer led falls prevention presentations. These included recommending that peer educators share falls prevention messages in a more interactive and experiential manner and that uptake of strategies should be facilitated by encouraging the older adults to develop a personalised action plan. Findings suggest that if peer-led falls prevention presentations capitalise on older adults’ capability, opportunity, and motivation, the older adults may be more receptive to take up falls prevention messages

Using genetic variation and environmental risk factor data to identify individuals at high risk for age-related macular degeneration

A major goal of personalized medicine is to pre-symptomatically identify individuals at high risk for disease using knowledge of each individual's particular genetic profile and constellation of environmental risk factors. With the identification of several well-replicated risk factors for age-related macular degeneration (AMD), the leading cause of legal blindness in older adults, this previously unreachable goal is beginning to seem less elusive. However, recently developed algorithms have either been much less accurate than expected, given the strong effects of the identified risk factors, or have not been applied to independent datasets, leaving unknown how well they would perform in the population at large. We sought to increase accuracy by using novel modeling strategies, including multifactor dimensionality reduction (MDR) and grammatical evolution of neural networks (GENN), in addition to the traditional logistic regression approach. Furthermore, we rigorously designed and tested our models in three distinct datasets: a Vanderbilt-Miami (VM) clinic-based case-control dataset, a VM family dataset, and the population-based Age-related Maculopathy Ancillary (ARMA) Study cohort. Using a consensus approach to combine the results from logistic regression and GENN models, our algorithm was successful in differentiating between high- and low-risk groups (sensitivity 77.0%, specificity 74.1%). In the ARMA cohort, the positive and negative predictive values were 63.3% and 70.7%, respectively. We expect that future efforts to refine this algorithm by increasing the sample size available for model building, including novel susceptibility factors as they are discovered, and by calibrating the model for diverse populations will improve accuracy

Moving toward a system genetics view of disease

Testing hundreds of thousands of DNA markers in human, mouse, and other species for association to complex traits like disease is now a reality. However, information on how variations in DNA impact complex physiologic processes flows through transcriptional and other molecular networks. In other words, DNA variations impact complex diseases through the perturbations they cause to transcriptional and other biological networks, and these molecular phenotypes are intermediate to clinically defined disease. Because it is also now possible to monitor transcript levels in a comprehensive fashion, integrating DNA variation, transcription, and phenotypic data has the potential to enhance identification of the associations between DNA variation and diseases like obesity and diabetes, as well as characterize those parts of the molecular networks that drive these diseases. Toward that end, we review methods for integrating expression quantitative trait loci (eQTLs), gene expression, and clinical data to infer causal relationships among gene expression traits and between expression and clinical traits. We further describe methods to integrate these data in a more comprehensive manner by constructing coexpression gene networks that leverage pairwise gene interaction data to represent more general relationships. To infer gene networks that capture causal information, we describe a Bayesian algorithm that further integrates eQTLs, expression, and clinical phenotype data to reconstruct whole-gene networks capable of representing causal relationships among genes and traits in the network. These emerging network approaches, aimed at processing high-dimensional biological data by integrating data from multiple sources, represent some of the first steps in statistical genetics to identify multiple genetic perturbations that alter the states of molecular networks and that in turn push systems into disease states. Evolving statistical procedures that operate on networks will be critical to extracting information related to complex phenotypes like disease, as research goes beyond a single-gene focus. The early successes achieved with the methods described herein suggest that these more integrative genomics approaches to dissecting disease traits will significantly enhance the identification of key drivers of disease beyond what could be achieved by genetic association studies alone

Search for CP violation in D+→ϕπ+ and D+s→K0Sπ+ decays

A search for CP violation in D + → ϕπ + decays is performed using data collected in 2011 by the LHCb experiment corresponding to an integrated luminosity of 1.0 fb−1 at a centre of mass energy of 7 TeV. The CP -violating asymmetry is measured to be (−0.04 ± 0.14 ± 0.14)% for candidates with K − K + mass within 20 MeV/c 2 of the ϕ meson mass. A search for a CP -violating asymmetry that varies across the ϕ mass region of the D + → K − K + π + Dalitz plot is also performed, and no evidence for CP violation is found. In addition, the CP asymmetry in the D+s→K0Sπ+ decay is measured to be (0.61 ± 0.83 ± 0.14)%

Feasibility of pseudocontinuous arterial spin labeling at 7 T with whole-brain coverage

Neuro Imaging Researc

Cirrhotic livers reveal genetic changes in the MDM2-P14ARF system of cell cycle regulators

The genesis of hepatocellular carcinoma is promoted by changes in the regulatory MDM2-P14ARF system. The incidence of such changes has to date not been analysed in non-tumourous livers showing regenerative proliferation. In the present study, 24 cirrhotic livers of alcohol-, autoimmue disorder- or HCV-caused genesis were screened for MDM2-P14ARF alterations at the level of protein, DNA and mRNA. Using confocal laser scanning microscopy, the absence of MDM2 and P14ARF expression was detected in all samples except three HCV-infected livers (four livers) which contained hepatocytes overexpressing MDM2 (P14ARF) protein. In two of the samples lacking P14ARF expression, laser microdissection and PCR demonstrated deletion of the P14ARF gene. The P14ARF gene amplified from other specimens did not carry mutations. MDM2 splicing variants were present in tissues from alcohol- and autoimmune disorder-induced cirrhoses. Sequencing of full-size mRNA revealed a MDM2 mis-sense mutation in an alcohol-induced cirrhosis. One sample contained regenerative nodules with genetic instability occurring at MDM2 locus D12S83 according to the data of automatic PCR fragment analysis. In summary, this study gives first evidence for different types of MDM2 and P14ARF alterations in cirrhotic livers. We suggest that the changes impair the regulatory MDM2-P14ARF system, thus possibly favouring regenerative proliferation and transformation

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

How Friendship Network Characteristics Influence Subjective Well-Being

This article explores how friendship network characteristics influence subjective well-being (SWB). Using data from the 2003 General Social Survey of Canada, three components of the friendship network are differentiated: number of friends, frequency of contact, and heterogeneity of friends. We argue that these characteristics shape SWB through the benefits they bring. Benefits considered are more social trust, less stress, better health, and more social support. Results confirm that higher frequency of contacts and higher number of friends, as well as lower heterogeneity of the friendship network are related to more social trust, less stress, and a better health. Frequency of contact and number of friends, as well as more heterogeneity of the friendship network increase the chance of receiving help from friends. With the exception of receiving help from friends, these benefits are in turn related to higher levels of SWB. Only the frequency of meeting friends face-to-face has a remaining positive direct influence on SWB