Psychoactive substance use and problematic Internet use as predictors of bullying and cyberbullying victimization

Research exploring the relationship between addictions and experiences of bullying suggests that problem behaviors may generally be associated with an increased risk of victimization. The aim of the present study was to examine the role of psychoactive substance use, excessive Internet use, and social support in both traditional offline bullying and online Bcyberbullying^ victimization in a nationally representative sample of adolescents (N = 6237; 51% male; Mage = 16.62 years, SD = 0.95). Results demonstrated that traditional bullying victimization was associated with cyberbullying victimization. Furthermore, psychoactive substance use and problematic Internet use predicted both traditional bullying and cyberbullying victimization. Finally, perceived social support was found to be an important protective factor against both traditional and cyberbullying victimization. However, psychoactive substance use and problematic Internet use accounted for only a small proportion of variance in victimization

Automated Model Merge by Design Space Exploration

Industrial applications of model-driven engineering to develop large and complex systems resulted in an increasing demand for collaboration features. However, use cases such as model differencing and merging have turned out to be a difficult challenge, due to (i) the graph-like nature of models, and (ii) the complexity of certain operations (e.g. hierarchy refactoring) that are common today. In the paper, we present a novel search-based automated model merge approach where rule-based design space exploration is used to search the space of solution candidates that represent conflict-free merged models. Our method also allows engineers to easily incorporate domain-specific knowledge into the merge process to provide better solutions. The merge process automatically calculates multiple merge candidates to be presented to domain experts for final selection. Furthermore, we propose to adopt a generic synthetic benchmark to carry out an initial scalability assessment for model merge with large models and large change sets

Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine

In the field of predictive, preventive and personalised medicine, researchers are keen to identify novel and reliable ways to predict and diagnose disease, as well as to monitor patient response to therapeutic agents. In the last decade alone, the sensitivity of profiling technologies has undergone huge improvements in detection sensitivity, thus allowing quantification of minute samples, for example body fluids that were previously difficult to assay. As a consequence, there has been a huge increase in tear fluid investigation, predominantly in the field of ocular surface disease. As tears are a more accessible and less complex body fluid (than serum or plasma) and sampling is much less invasive, research is starting to focus on how disease processes affect the proteomic, lipidomic and metabolomic composition of the tear film. By determining compositional changes to tear profiles, crucial pathways in disease progression may be identified, allowing for more predictive and personalised therapy of the individual. This article will provide an overview of the various putative tear fluid biomarkers that have been identified to date, ranging from ocular surface disease and retinopathies to cancer and multiple sclerosis. Putative tear fluid biomarkers of ocular disorders, as well as the more recent field of systemic disease biomarkers, will be shown

Bocepreviralapú hármas kezelés hatékonyságának és biztonságosságának retrospektív elemzése előrehaladott fibrosisstádiumú, hepatitis C-vírus 1-es genotípussal fertőzött, korábban sikertelenül kezelt magyar betegeknél

INTRODUCTION: During 2011 and 2013, 155 Hungarian hepatitis C genotype 1 infected patients, mostly with advanced liver fibrosis, who did not respond to prior peginterferon + ribavirin dual therapy, started boceprevir based triple therapy in an early access program. AIM AND METHOD: Efficacy and safety of the therapy was retrospectively assessed based on sustained virologic responses, as well as on frequency and type of serious adverse events and of those leading to therapy discontinuation. RESULTS: In an intent-to-treat analysis 39.4% patients (61/155) reached sustained virologic response. Amongst pervious relapsers, partial responders and null-responders 59.5%, 41.4 % and 22.9% (p<0.05 compared to the other two categories) reached sustained virologic response, respectively, while amongst non-cirrhotics and cirrhotics 52.5% and 31.3% (p<0.05 compared to the non-cirrhotics) achieved sutained virologic response, respectively. Six out of the 33 most difficult to cure patients (previous null responder and cirrhotic) have reached sustained virologic response (18.2%). Frequency of early discontinuations due to insufficient virologic response was 31.1%, while due to adverse event 10.3%. Reported frequency of serious adverse event was 9.8%. These events represented anemia, diarrhoea, depression, agranulocytosis, elevated aminotransferases, generalized dermatitis and severe gingivitis with loss of teeth, prolonged QT interval on ECG, generalized oedema and severe dyspnoea, uroinfection, exacerbation of Crohn's disease, Campylobacter pylori infection and unacceptable weakness and fatigue. Eight patients received transfusion, 4 patients erythropoietin and 1 granulocyte colony stimulating factor during therapy. No death has been reported. CONCLUSIONS: With boceprevir based triple therapy, one of the bests available in 2011-2013 in Hungary, a relevant proportion of hepatitis C infected patients with advanced liver fibrosis achieved sustained viral response. In this cohort, side-effects resembled those reported in registration studies, and resulted in therapy discontinuation with consequent treatment failure in a relevant number of patients. Efficacy and tolerability of boceprevir-based triple therapy are suboptimal, particularly in the most difficult to cure patient population. Orv. Hetil., 2016, 157(34), 1366-1374

Model-driven engineering of an openCypher engine: using graph queries to compile graph queries

Graph database systems are increasingly adapted for storing and processing heterogeneous network-like datasets. Many challenging applications with near real-time requirements - such as financial fraud detection, on-the-fly model validation and root cause analysis - can be formalised as graph problems and tackled with graph databases efficiently. However, as no standard graph query language has yet emerged, users are subjected to the possibility of vendor lock-in. The openCypher group aims to define an open specification for a declarative graph query language. However, creating an openCypher-compatible query engine requires significant research and engineering efforts. Meanwhile, model-driven language workbenches support the creation of domain-specific languages by providing high-level tools to create parsers, editors and compilers. In this paper, we present an approach to build a compiler and optimizer for openCypher using model-driven technologies, which allows developers to define declarative optimization rules

Glial cell type-specific changes in spinal dipeptidyl peptidase 4 expression and effects of its inhibitors in inflammatory and neuropatic pain

Altered pain sensations such as hyperalgesia and allodynia are characteristic features of various pain states, and remain difficult to treat. We have shown previously that spinal application of dipeptidyl peptidase 4 (DPP4) inhibitors induces strong antihyperalgesic effect during inflammatory pain. In this study we observed low level of DPP4 mRNA in the rat spinal dorsal horn in physiological conditions, which did not change significantly either in carrageenan-induced inflammatory or partial nerve ligation-generated neuropathic states. In naive animals, microglia and astrocytes expressed DPP4 protein with one and two orders of magnitude higher than neurons, respectively. DPP4 significantly increased in astrocytes during inflammation and in microglia in neuropathy. Intrathecal application of two DPP4 inhibitors tripeptide isoleucin-prolin-isoleucin (IPI) and the antidiabetic drug vildagliptin resulted in robust opioid-dependent antihyperalgesic effect during inflammation, and milder but significant opioid-independent antihyperalgesic action in the neuropathic model. The opioid-mediated antihyperalgesic effect of IPI was exclusively related to mu-opioid receptors, while vildagliptin affected mainly delta-receptor activity, although mu- and kappa-receptors were also involved. None of the inhibitors influenced allodynia. Our results suggest pathology and glia-type specific changes of DPP4 activity in the spinal cord, which contribute to the development and maintenance of hyperalgesia and interact with endogenous opioid systems