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

Spatial effects should be allowed for in primary care and other community-based cluster RCTS

<p>Abstract</p> <p>Background</p> <p>Typical advice on the design and analysis of cluster randomized trials (C-RCTs) focuses on allowance for the clustering at the level of the unit of allocation. However often C-RCTs are also organised spatially as may occur in the fields of Public Health and Primary Care where populations may even overlap.</p> <p>Methods</p> <p>We allowed for spatial effects on the error variance by a multiple membership model. These are a form of hierarchical model in which each lower level unit is a member of more than one higher level unit. Membership may be determined through adjacency or through Euclidean distance of centroids or in other ways such as the proportion of overlapping population. Such models may be estimated for Normal, binary and Poisson responses in Stata (v10 or above) as well as in WinBUGS or MLWin. We used this to analyse a dummy trial and two real, previously published cluster-allocated studies (one allocating general practices within one City and the other allocating general practices within one County) to investigate the extent to which ignoring spatial effects affected the estimate of treatment effect, using different methods for defining membership with Akaike's Information Criterion to determine the "best" model.</p> <p>Results</p> <p>The best fitting model included both a fixed North-South gradient and a random cluster effect for the dummy RCT. For one of the real RCTs the best fitting model included both a random practice effect plus a multiple membership spatial term, while for the other RCT the best fitting model ignored the clustering but included a fixed North-South gradient. Alternative models which fitted only slightly less well all included spatial effects in one form or another, with some variation in parameter estimates (greater when less well fitting models were included).</p> <p>Conclusions</p> <p>These particular results are only illustrative. However, we believe when designing C-RCTs in a primary care setting the possibility of spatial effects should be considered in relation to the intervention and response, as well as any explanatory effect of fixed covariates, together with any implications for sample size and methods for planned analyses.</p

The Passive Yet Successful Way of Planktonic Life: Genomic and Experimental Analysis of the Ecology of a Free-Living Polynucleobacter Population

Background: The bacterial taxon Polynucleobacter necessarius subspecies asymbioticus represents a group of planktonic freshwater bacteria with cosmopolitan and ubiquitous distribution in standing freshwater habitats. These bacteria comprise,1 % to 70 % (on average about 20%) of total bacterioplankton cells in various freshwater habitats. The ubiquity of this taxon was recently explained by intra-taxon ecological diversification, i.e. specialization of lineages to specific environmental conditions; however, details on specific adaptations are not known. Here we investigated by means of genomic and experimental analyses the ecological adaptation of a persistent population dwelling in a small acidic pond. Findings: The investigated population (F10 lineage) contributed on average 11 % to total bacterioplankton in the pond during the vegetation periods (ice-free period, usually May to November). Only a low degree of genetic diversification of the population could be revealed. These bacteria are characterized by a small genome size (2.1 Mb), a relatively small number of genes involved in transduction of environmental signals, and the lack of motility and quorum sensing. Experiments indicated that these bacteria live as chemoorganotrophs by mainly utilizing low-molecular-weight substrates derived from photooxidation of humic substances. Conclusions: Evolutionary genome streamlining resulted in a highly passive lifestyle so far only known among free-living bacteria from pelagic marine taxa dwelling in environmentally stable nutrient-poor off-shore systems. Surprisingly, such a lifestyle is also successful in a highly dynamic and nutrient-richer environment such as the water column of the investigate

Examining leptogenesis with lepton flavor violation and the dark matter abundance

Within a supersymmetric (SUSY) type-I seesaw framework with flavor-blind universal boundary conditions, we study the consequences of requiring that the observed baryon asymmetry of the Universe be explained by either thermal or non-thermal leptogenesis. In the former case, we find that the parameter space is very constrained. In the bulk and stop-coannihilation regions of mSUGRA parameter space (that are consistent with the measured dark matter abundance), lepton flavor-violating (LFV) processes are accessible at MEG and future experiments. However, the very high reheat temperature of the Universe needed after inflation (of about 10^{12} GeV) leads to a severe gravitino problem, which disfavors either thermal leptogenesis or neutralino dark matter. Non-thermal leptogenesis in the preheating phase from SUSY flat directions relaxes the gravitino problem by lowering the required reheat temperature. The baryon asymmetry can then be explained while preserving neutralino dark matter, and for the bulk or stop-coannihilation regions LFV processes should be observed in current or future experiments.Comment: 20 pages, 5 figures, 1 tabl

Direct determination of the solar neutrino fluxes from solar neutrino data

We determine the solar neutrino fluxes from a global analysis of the solar and terrestrial neutrino data in the framework of three-neutrino mixing. Using a Bayesian approach we reconstruct the posterior probability distribution function for the eight normalization parameters of the solar neutrino fluxes plus the relevant masses and mixing, with and without imposing the luminosity constraint. This is done by means of a Markov Chain Monte Carlo employing the Metropolis-Hastings algorithm. We also describe how these results can be applied to test the predictions of the Standard Solar Models. Our results show that, at present, both models with low and high metallicity can describe the data with good statistical agreement.Comment: 24 pages, 1 table, 7 figures. Acknowledgments correcte

Thermally nucleated magnetic reversal in CoFeB/MgO nanodots

Power consumption is the main limitation in the development of new high performance random access memory for portable electronic devices. Magnetic RAM (MRAM) with CoFeB/MgO based magnetic tunnel junctions (MTJs) is a promising candidate for reducing the power consumption given its non-volatile nature while achieving high performance. The dynamic properties and switching mechanisms of MTJs are critical to understanding device operation and to enable scaling of devices below 30 nm in diameter. Here we show that the magnetic reversal mechanism is incoherent and that the switching is thermally nucleated at device operating temperatures. Moreover, we find an intrinsic thermal switching field distribution arising on the sub-nanosecond time-scale even in the absence of size and anisotropy distributions or material defects. These features represent the characteristic signature of the dynamic properties in MTJs and give an intrinsic limit to reversal reliability in small magnetic nanodevices

Cosmogenic neutron production at the Sudbury Neutrino Observatory

Neutrons produced in nuclear interactions initiated by cosmic-ray muons present an irreducible background to many rare-event searches, even in detectors located deep underground. Models for the production of these neutrons have been tested against previous experimental data, but the extrapolation to deeper sites is not well understood. Here we report results from an analysis of cosmogenically produced neutrons at the Sudbury Neutrino Observatory. A specific set of observables are presented, which can be used to benchmark the validity of geant4 physics models. In addition, the cosmogenic neutron yield, in units of 10-4 cm2/(g·μ), is measured to be 7.28±0.09(stat)-1.12+1.59(syst) in pure heavy water and 7.30±0.07(stat)-1.02+1.40(syst) in NaCl-loaded heavy water. These results provide unique insights into this potential background source for experiments at SNOLAB

In Situ Identification of Plant-Invasive Bacteria with MALDI-TOF Mass Spectrometry

Rhizobia form a disparate collection of soil bacteria capable of reducing atmospheric nitrogen in symbiosis with legumes. The study of rhizobial populations in nature involves the collection of large numbers of nodules found on roots or stems of legumes, and the subsequent typing of nodule bacteria. To avoid the time-consuming steps of isolating and cultivating nodule bacteria prior to genotyping, a protocol of strain identification based on the comparison of MALDI-TOF MS spectra was established. In this procedure, plant nodules were considered as natural bioreactors that amplify clonal populations of nitrogen-fixing bacteroids. Following a simple isolation procedure, bacteroids were fingerprinted by analysing biomarker cellular proteins of 3 to 13 kDa using Matrix Assisted Laser Desorption/Ionization Time of Flight (MALDI-TOF) mass spectrometry. In total, bacteroids of more than 1,200 nodules collected from roots of three legumes of the Phaseoleae tribe (cowpea, soybean or siratro) were examined. Plants were inoculated with pure cultures of a slow-growing Bradyrhizobium japonicum strain G49, or either of two closely related and fast-growing Sinorhizobium fredii strains NGR234 and USDA257, or with mixed inoculants. In the fully automatic mode, correct identification of bacteroids was obtained for >97% of the nodules, and reached 100% with a minimal manual input in processing of spectra. These results showed that MALDI-TOF MS is a powerful tool for the identification of intracellular bacteria taken directly from plant tissues

Constraints on Nucleon Decay via "Invisible" Modes from the Sudbury Neutrino Observatory

Data from the Sudbury Neutrino Observatory have been used to constrain the lifetime for nucleon decay to ``invisible'' modes, such as n -> 3 nu. The analysis was based on a search for gamma-rays from the de-excitation of the residual nucleus that would result from the disappearance of either a proton or neutron from O16. A limit of tau_inv > 2 x 10^{29} years is obtained at 90% confidence for either neutron or proton decay modes. This is about an order of magnitude more stringent than previous constraints on invisible proton decay modes and 400 times more stringent than similar neutron modes.Comment: Update includes missing efficiency factor (limits change by factor of 2) Submitted to Physical Review Letter