146 research outputs found

    Spreading Patterns of the Influenza A (H1N1) Pandemic

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    We investigate the dynamics of the 2009 influenza A (H1N1/S-OIV) pandemic by analyzing data obtained from World Health Organization containing the total number of laboratory-confirmed cases of infections - by country - in a period of 69 days, from 26 April to 3 July, 2009. Specifically, we find evidence of exponential growth in the total number of confirmed cases and linear growth in the number of countries with confirmed cases. We also find that, i) at early stages, the cumulative distribution of cases among countries exhibits linear behavior on log-log scale, being well approximated by a power law decay; ii) for larger times, the cumulative distribution presents a systematic curvature on log-log scale, indicating a gradual change to lognormal behavior. Finally, we compare these empirical findings with the predictions of a simple stochastic model. Our results could help to select more realistic models of the dynamics of influenza-type pandemics

    Genetic variation in the pleiotropic association between physical activity and body weight in mice

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    <p>Abstract</p> <p>Background</p> <p>A sedentary lifestyle is often assumed to lead to increases in body weight and potentially obesity and related diseases but in fact little is known about the genetic association between physical activity and body weight. We tested for such an association between body weight and the distance, duration, and speed voluntarily run by 310 mice from the F<sub>2 </sub>generation produced from an intercross of two inbred lines that differed dramatically in their physical activity levels.</p> <p>Methods</p> <p>We used a conventional interval mapping approach with SNP markers to search for QTLs that affected both body weight and activity traits. We also conducted a genome scan to search for relationship QTLs (<it>rel</it>QTLs), or chromosomal regions that affected an activity trait variably depending on the phenotypic value of body weight.</p> <p>Results</p> <p>We uncovered seven quantitative trait loci (QTLs) affecting body weight, but only one co-localized with another QTL previously found for activity traits. We discovered 19 <it>rel</it>QTLs that provided evidence for a genetic (pleiotropic) association of physical activity and body weight. The three genotypes at each of these loci typically exhibited a combination of negative, zero, and positive regressions of the activity traits on body weight, the net effect of which was to produce overall independence of body weight from physical activity. We also demonstrated that the <it>rel</it>QTLs produced these varying associations through differential epistatic interactions with a number of other epistatic QTLs throughout the genome.</p> <p>Conclusion</p> <p>It was concluded that individuals with specific combinations of genotypes at the <it>rel</it>QTLs and <it>epi</it>QTLs might account for some of the variation typically seen in plots of the association of physical activity with body weight.</p

    Synthetic human cell fate regulation by protein-driven RNA switches

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    Understanding how to control cell fate is crucial in biology, medical science and engineering. In this study, we introduce a method that uses an intracellular protein as a trigger for regulating human cell fate. The ON/OFF translational switches, composed of an intracellular protein L7Ae and its binding RNA motif, regulate the expression of a desired target protein and control two distinct apoptosis pathways in target human cells. Combined use of the switches demonstrates that a specific protein can simultaneously repress and activate the translation of two different mRNAs: one protein achieves both up- and downregulation of two different proteins/pathways. A genome-encoded protein fused to L7Ae controlled apoptosis in both directions (death or survival) depending on its cellular expression. The method has potential for curing cellular defects or improving the intracellular production of useful molecules by bypassing or rewiring intrinsic signal networks

    Are Happiness and Life Satisfaction Different Across Religious groups? Exploring Determinants of Happiness and Life Satisfaction

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    This study explores whether different religions experience different levels of happiness and life satisfaction and in case this is affected by country economic and cultural environment. Using World Value Survey (from 1981 to 2014), this study found that individual religiosity and country level of development play a significant role in shaping people’s subjective well-being (SWB). Protestants, Buddhists and Roman Catholic were happier and most satisfied with their lives compared to other religious groups. Orthodox has the lowest SWB. Health status, household’s financial satisfaction and freedom of choice are means by which religious groups and governments across the globe can improve the SWB of their citizens. Keywords: happiness; life satisfaction; religion; religious differences; cultur

    Viral epidemics in a cell culture: novel high resolution data and their interpretation by a percolation theory based model

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    Because of its relevance to everyday life, the spreading of viral infections has been of central interest in a variety of scientific communities involved in fighting, preventing and theoretically interpreting epidemic processes. Recent large scale observations have resulted in major discoveries concerning the overall features of the spreading process in systems with highly mobile susceptible units, but virtually no data are available about observations of infection spreading for a very large number of immobile units. Here we present the first detailed quantitative documentation of percolation-type viral epidemics in a highly reproducible in vitro system consisting of tens of thousands of virtually motionless cells. We use a confluent astroglial monolayer in a Petri dish and induce productive infection in a limited number of cells with a genetically modified herpesvirus strain. This approach allows extreme high resolution tracking of the spatio-temporal development of the epidemic. We show that a simple model is capable of reproducing the basic features of our observations, i.e., the observed behaviour is likely to be applicable to many different kinds of systems. Statistical physics inspired approaches to our data, such as fractal dimension of the infected clusters as well as their size distribution, seem to fit into a percolation theory based interpretation. We suggest that our observations may be used to model epidemics in more complex systems, which are difficult to study in isolation.Comment: To appear in PLoS ONE. Supporting material can be downloaded from http://amur.elte.hu/BDGVirus

    Efficient Network Reconstruction from Dynamical Cascades Identifies Small-World Topology of Neuronal Avalanches

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    Cascading activity is commonly found in complex systems with directed interactions such as metabolic networks, neuronal networks, or disease spreading in social networks. Substantial insight into a system's organization can be obtained by reconstructing the underlying functional network architecture from the observed activity cascades. Here we focus on Bayesian approaches and reduce their computational demands by introducing the Iterative Bayesian (IB) and Posterior Weighted Averaging (PWA) methods. We introduce a special case of PWA, cast in nonparametric form, which we call the normalized count (NC) algorithm. NC efficiently reconstructs random and small-world functional network topologies and architectures from subcritical, critical, and supercritical cascading dynamics and yields significant improvements over commonly used correlation methods. With experimental data, NC identified a functional and structural small-world topology and its corresponding traffic in cortical networks with neuronal avalanche dynamics

    Reduced Food Intake and Body Weight in Mice Deficient for the G Protein-Coupled Receptor GPR82

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    G protein-coupled receptors (GPCR) are involved in the regulation of numerous physiological functions. Therefore, GPCR variants may have conferred important selective advantages during periods of human evolution. Indeed, several genomic loci with signatures of recent selection in humans contain GPCR genes among them the X-chromosomally located gene for GPR82. This gene encodes a so-called orphan GPCR with unknown function. To address the functional relevance of GPR82 gene-deficient mice were characterized. GPR82-deficient mice were viable, reproduced normally, and showed no gross anatomical abnormalities. However, GPR82-deficient mice have a reduced body weight and body fat content associated with a lower food intake. Moreover, GPR82-deficient mice showed decreased serum triacylglyceride levels, increased insulin sensitivity and glucose tolerance, most pronounced under Western diet. Because there were no differences in respiratory and metabolic rates between wild-type and GPR82-deficient mice our data suggest that GPR82 function influences food intake and, therefore, energy and body weight balance. GPR82 may represent a thrifty gene most probably representing an advantage during human expansion into new environments

    Effects of Extreme Precipitation to the Distribution of Infectious Diseases in Taiwan, 1994–2008

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    The incidence of extreme precipitation has increased with the exacerbation of worldwide climate disruption. We hypothesize an association between precipitation and the distribution patterns that would affect the endemic burden of 8 infectious diseases in Taiwan, including water- and vector-borne infectious diseases. A database integrating daily precipitation and temperature, along with the infectious disease case registry for all 352 townships in the main island of Taiwan was analysed for the period from 1994 to 2008. Four precipitation levels, <130 mm, 130–200 mm, 200–350 mm and >350 mm, were categorized to represent quantitative differences, and their associations with each specific disease was investigated using the Generalized Additive Mixed Model and afterwards mapped on to the Geographical Information System. Daily precipitation levels were significantly correlated with all 8 mandatory-notified infectious diseases in Taiwan. For water-borne infections, extreme torrential precipitation (>350 mm/day) was found to result in the highest relative risk for bacillary dysentery and enterovirus infections when compared to ordinary rain (<130 mm/day). Yet, for vector-borne diseases, the relative risk of dengue fever and Japanese encephalitis increased with greater precipitation only up to 350 mm. Differential lag effects following precipitation were statistically associated with increased risk for contracting individual infectious diseases. This study’s findings can help health resource sector management better allocate medical resources and be better prepared to deal with infectious disease outbreaks following future extreme precipitation events

    How Landscape Heterogeneity Frames Optimal Diffusivity in Searching Processes

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    Theoretical and empirical investigations of search strategies typically have failed to distinguish the distinct roles played by density versus patchiness of resources. It is well known that motility and diffusivity of organisms often increase in environments with low density of resources, but thus far there has been little progress in understanding the specific role of landscape heterogeneity and disorder on random, non-oriented motility. Here we address the general question of how the landscape heterogeneity affects the efficiency of encounter interactions under global constant density of scarce resources. We unveil the key mechanism coupling the landscape structure with optimal search diffusivity. In particular, our main result leads to an empirically testable prediction: enhanced diffusivity (including superdiffusive searches), with shift in the diffusion exponent, favors the success of target encounters in heterogeneous landscapes

    Dissociable Modulation of Overt Visual Attention in Valence and Arousal Revealed by Topology of Scan Path

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    Emotional stimuli have evolutionary significance for the survival of organisms; therefore, they are attention-grabbing and are processed preferentially. The neural underpinnings of two principle emotional dimensions in affective space, valence (degree of pleasantness) and arousal (intensity of evoked emotion), have been shown to be dissociable in the olfactory, gustatory and memory systems. However, the separable roles of valence and arousal in scene perception are poorly understood. In this study, we asked how these two emotional dimensions modulate overt visual attention. Twenty-two healthy volunteers freely viewed images from the International Affective Picture System (IAPS) that were graded for affective levels of valence and arousal (high, medium, and low). Subjects' heads were immobilized and eye movements were recorded by camera to track overt shifts of visual attention. Algebraic graph-based approaches were introduced to model scan paths as weighted undirected path graphs, generating global topology metrics that characterize the algebraic connectivity of scan paths. Our data suggest that human subjects show different scanning patterns to stimuli with different affective ratings. Valence salient stimuli (with neutral arousal) elicited faster and larger shifts of attention, while arousal salient stimuli (with neutral valence) elicited local scanning, dense attention allocation and deep processing. Furthermore, our model revealed that the modulatory effect of valence was linearly related to the valence level, whereas the relation between the modulatory effect and the level of arousal was nonlinear. Hence, visual attention seems to be modulated by mechanisms that are separate for valence and arousal
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