A novel approach to simulate gene-environment interactions in complex diseases

Background: Complex diseases are multifactorial traits caused by both genetic and environmental factors. They represent the major part of human diseases and include those with largest prevalence and mortality (cancer, heart disease, obesity, etc.). Despite a large amount of information that has been collected about both genetic and environmental risk factors, there are few examples of studies on their interactions in epidemiological literature. One reason can be the incomplete knowledge of the power of statistical methods designed to search for risk factors and their interactions in these data sets. An improvement in this direction would lead to a better understanding and description of gene-environment interactions. To this aim, a possible strategy is to challenge the different statistical methods against data sets where the underlying phenomenon is completely known and fully controllable, for example simulated ones. Results: We present a mathematical approach that models gene-environment interactions. By this method it is possible to generate simulated populations having gene-environment interactions of any form, involving any number of genetic and environmental factors and also allowing non-linear interactions as epistasis. In particular, we implemented a simple version of this model in a Gene-Environment iNteraction Simulator (GENS), a tool designed to simulate case-control data sets where a one gene-one environment interaction influences the disease risk. The main aim has been to allow the input of population characteristics by using standard epidemiological measures and to implement constraints to make the simulator behaviour biologically meaningful. Conclusions: By the multi-logistic model implemented in GENS it is possible to simulate case-control samples of complex disease where gene-environment interactions influence the disease risk. The user has full control of the main characteristics of the simulated population and a Monte Carlo process allows random variability. A knowledge-based approach reduces the complexity of the mathematical model by using reasonable biological constraints and makes the simulation more understandable in biological terms. Simulated data sets can be used for the assessment of novel statistical methods or for the evaluation of the statistical power when designing a study

The determinants of vulnerability to currency crises: country-specific factors versus regional factors

We investigate the determinants of exchange market pressures (EMP) for some new EU member states at both the national and regional levels, where macroeconomic and financial variables are considered as potential sources. The regional common factors are extracted from these variables by using dynamic factor analysis. The linear empirical analysis, in general, highlights the importance of country-specific factors to defend themselves against vulnerability in their external sectors. Yet, given a significant impact of the common component in credit on EMP, a contagion effect is apparent through the conduit of credit market integration across these countries under investigation

MHD models of Pulsar Wind Nebulae

Pulsar Wind Nebulae (PWNe) are bubbles or relativistic plasma that form when the pulsar wind is confined by the SNR or the ISM. Recent observations have shown a richness of emission features that has driven a renewed interest in the theoretical modeling of these objects. In recent years a MHD paradigm has been developed, capable of reproducing almost all of the observed properties of PWNe, shedding new light on many old issues. Given that PWNe are perhaps the nearest systems where processes related to relativistic dynamics can be investigated with high accuracy, a reliable model of their behavior is paramount for a correct understanding of high energy astrophysics in general. I will review the present status of MHD models: what are the key ingredients, their successes, and open questions that still need further investigation.Comment: 18 pages, 5 figures, Invited Review, Proceedings of the "ICREA Workshop on The High-Energy Emission from Pulsars and their Systems", Sant Cugat, Spain, April 12-16, 201

Breakdown of Fermi-liquid theory in a cuprate superconductor

The behaviour of electrons in solids is remarkably well described by Landau's Fermi-liquid theory, which says that even though electrons in a metal interact they can still be treated as well-defined fermions, called ``quasiparticles''. At low temperature, the ability of quasiparticles to transport heat is strictly given by their ability to transport charge, via a universal relation known as the Wiedemann-Franz law, which no material in nature has been known to violate. High-temperature superconductors have long been thought to fall outside the realm of Fermi-liquid theory, as suggested by several anomalous properties, but this has yet to be shown conclusively. Here we report on the first experimental test of the Wiedemann-Franz law in a cuprate superconductor, (Pr,Ce)$_2$CuO$_4$. Our study reveals a clear departure from the universal law and provides compelling evidence for the breakdown of Fermi-liquid theory in high-temperature superconductors.Comment: 7 pages, 3 figure

Influence of Interferon beta treatment on quality of life in multiple sclerosis patients

BACKGROUND: Interferon-beta (IFN-β) shows beneficial effect on the course of multiple sclerosis (MS), nevertheless its route and frequency of administration and side effects might impact negatively the quality of life (QoL) of MS patients. The objective of this study was to evaluate the influence of IFN-β on QoL in MS patients. METHODS: Seventy-seven disease modifying treatment (DMT) free and 41 IFN-β treated MS patients were evaluated. QoL, assessed by MSQoL-54, was related to IFN-β treatment and to clinical and demographic parameters at baseline and after two years. Multivariate hierarchical linear model for repeated measurements was used. RESULTS: Treated patients showed a younger age, a lower disease duration and a higher relapse rate in the two years preceding study entry. At inclusion time treated and untreated patients did not differ in relapse rate, expanded disability status scale (EDSS), fatigue, depression, physical and mental QoL. IFN-β did not influence QoL at inclusion time, but when QoL was evaluated after two years, treatment negatively affected mental QoL. Depression and fatigue negatively influenced physical and mental QoL both at baseline and after two years. EDSS correlated with a poor physical QoL only at baseline. CONCLUSION: IFN-β had a negative impact on QoL over the time in MS patients, influencing mainly mental QoL. The impairment of QoL in MS was strongly associated with increasing fatigue and depression, whereas clinical disability had a minor unfavourable role

Socio-demographic and behavioural characteristics of illegal motorcycle street racers in Malaysia

<p>Abstract</p> <p>Background</p> <p>This study sought to understand the factors associated with street racing among the illegal motorcycle racers in Malaysia or known as the <it>"Mat Rempit"</it>.</p> <p>Methods</p> <p>Street outreach interviewer-administered surveys were conducted from June 2008 to January 2009 in this multi-state study.</p> <p>Results</p> <p>A total of 2022 participants were surveyed, the mean ± <it>SD </it>age of the participants was 20.5 ± 3.4 years (age range: 12 to 35 years). Mean duration of street racing was 2.65(<it>SD </it>± 1.77) years (range: 2 months to 12 years), with 50.1% and 35.8% reporting stunt riding and alcohol drinking while racing, respectively. With regard to risk behaviours, cigarette smoking was highly prevalent among the study participants (78.3%), followed by alcohol drinking (27.8%) and recreational drug use (18.8%). Participants scored high on the masculinity scale (15.7 ± 4.0 out of 21.0). The results of the logistic regression analysis showed that socio-demographic variables, risk behaviour and masculinity scores were associated with racing frequency.</p> <p>Conclusion</p> <p>Given these associations, tailoring family-centered interventions to the needs of the lower socio-economic groups and interventions recognizing the negative consequences of health risk behaviours related to street racing as an expression of traditional masculinity should be emphasized.</p

The potential impact of climate change on Australia's soil organic carbon resources

BACKGROUND: Soil organic carbon (SOC) represents a significant pool of carbon within the biosphere. Climatic shifts in temperature and precipitation have a major influence on the decomposition and amount of SOC stored within an ecosystem and that released into the atmosphere. We have linked net primary production (NPP) algorithms, which include the impact of enhanced atmospheric CO(2 )on plant growth, to the SOCRATES terrestrial carbon model to estimate changes in SOC for the Australia continent between the years 1990 and 2100 in response to climate changes generated by the CSIRO Mark 2 Global Circulation Model (GCM). RESULTS: We estimate organic carbon storage in the topsoil (0–10 cm) of the Australian continent in 1990 to be 8.1 Gt. This equates to 19 and 34 Gt in the top 30 and 100 cm of soil, respectively. By the year 2100, under a low emissions scenario, topsoil organic carbon stores of the continent will have increased by 0.6% (49 Mt C). Under a high emissions scenario, the Australian continent becomes a source of CO(2 )with a net reduction of 6.4% (518 Mt) in topsoil carbon, when compared to no climate change. This is partially offset by the predicted increase in NPP of 20.3% CONCLUSION: Climate change impacts must be studied holistically, requiring integration of climate, plant, ecosystem and soil sciences. The SOCRATES terrestrial carbon cycling model provides realistic estimates of changes in SOC storage in response to climate change over the next century, and confirms the need for greater consideration of soils in assessing the full impact of climate change and the development of quantifiable mitigation strategies